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] 549.0 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: 29,220,797 # Trainable Weights: 44,637,501 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ============================ 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, 125) [#0187] class-predict/bias:0 => (125,) [#0188] box-predict/kernel:0 => (1024, 500) [#0189] box-predict/bias:0 => (500,) [#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, 125) [#0201] mask_fcn_logits/bias:0 => (125,) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # ============================================= # 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: 1655008557.9714499 iteration: 5 throughput: 2.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.00064 FastRCNN class loss: 0.97977 FastRCNN total loss: 0.98041 L1 loss: 0.0000e+00 L2 loss: 2.24396 Learning rate: 0.00018 Mask loss: 0.7865 RPN box loss: 0.16552 RPN score loss: 0.67609 RPN total loss: 0.84162 Total loss: 4.85248 timestamp: 1655008561.2577176 iteration: 10 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.00098 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.06688 L1 loss: 0.0000e+00 L2 loss: 2.24396 Learning rate: 0.00028 Mask loss: 0.7793 RPN box loss: 0.0734 RPN score loss: 0.57977 RPN total loss: 0.65317 Total loss: 3.74331 timestamp: 1655008564.418919 iteration: 15 throughput: 25.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33928 FastRCNN class loss: 0.10173 FastRCNN total loss: 0.44101 L1 loss: 0.0000e+00 L2 loss: 2.24396 Learning rate: 0.00038 Mask loss: 0.6587 RPN box loss: 0.02072 RPN score loss: 0.38972 RPN total loss: 0.41044 Total loss: 3.75411 timestamp: 1655008567.6381588 iteration: 20 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4708 FastRCNN class loss: 0.30287 FastRCNN total loss: 0.77368 L1 loss: 0.0000e+00 L2 loss: 2.24396 Learning rate: 0.00048 Mask loss: 0.72303 RPN box loss: 0.09854 RPN score loss: 0.18622 RPN total loss: 0.28476 Total loss: 4.02543 timestamp: 1655008570.823227 iteration: 25 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5282 FastRCNN class loss: 0.19691 FastRCNN total loss: 0.72511 L1 loss: 0.0000e+00 L2 loss: 2.24395 Learning rate: 0.00058 Mask loss: 0.62793 RPN box loss: 0.15658 RPN score loss: 0.12369 RPN total loss: 0.28027 Total loss: 3.87726 timestamp: 1655008573.9034204 iteration: 30 throughput: 25.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58273 FastRCNN class loss: 0.27572 FastRCNN total loss: 0.85845 L1 loss: 0.0000e+00 L2 loss: 2.24394 Learning rate: 0.00068 Mask loss: 0.61203 RPN box loss: 0.02622 RPN score loss: 0.08215 RPN total loss: 0.10837 Total loss: 3.82279 timestamp: 1655008577.093717 iteration: 35 throughput: 25.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50704 FastRCNN class loss: 0.20854 FastRCNN total loss: 0.71559 L1 loss: 0.0000e+00 L2 loss: 2.24392 Learning rate: 0.00078 Mask loss: 0.65341 RPN box loss: 0.02967 RPN score loss: 0.06953 RPN total loss: 0.09919 Total loss: 3.71211 timestamp: 1655008580.2689703 iteration: 40 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4747 FastRCNN class loss: 0.20086 FastRCNN total loss: 0.67556 L1 loss: 0.0000e+00 L2 loss: 2.24391 Learning rate: 0.00088 Mask loss: 0.59975 RPN box loss: 0.03759 RPN score loss: 0.04564 RPN total loss: 0.08323 Total loss: 3.60244 timestamp: 1655008583.3898387 iteration: 45 throughput: 26.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51788 FastRCNN class loss: 0.2649 FastRCNN total loss: 0.78278 L1 loss: 0.0000e+00 L2 loss: 2.24389 Learning rate: 0.00098 Mask loss: 0.54333 RPN box loss: 0.06647 RPN score loss: 0.04995 RPN total loss: 0.11642 Total loss: 3.68643 timestamp: 1655008586.4255972 iteration: 50 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48868 FastRCNN class loss: 0.2153 FastRCNN total loss: 0.70398 L1 loss: 0.0000e+00 L2 loss: 2.24386 Learning rate: 0.00108 Mask loss: 0.59392 RPN box loss: 0.04712 RPN score loss: 0.04355 RPN total loss: 0.09067 Total loss: 3.63243 timestamp: 1655008589.578771 iteration: 55 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47269 FastRCNN class loss: 0.19517 FastRCNN total loss: 0.66786 L1 loss: 0.0000e+00 L2 loss: 2.24384 Learning rate: 0.00117 Mask loss: 0.50732 RPN box loss: 0.16708 RPN score loss: 0.0473 RPN total loss: 0.21439 Total loss: 3.6334 timestamp: 1655008592.7392642 iteration: 60 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55645 FastRCNN class loss: 0.41344 FastRCNN total loss: 0.96989 L1 loss: 0.0000e+00 L2 loss: 2.24381 Learning rate: 0.00127 Mask loss: 0.58927 RPN box loss: 0.05989 RPN score loss: 0.04901 RPN total loss: 0.10891 Total loss: 3.91188 timestamp: 1655008595.8849063 iteration: 65 throughput: 26.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46126 FastRCNN class loss: 0.18744 FastRCNN total loss: 0.6487 L1 loss: 0.0000e+00 L2 loss: 2.24378 Learning rate: 0.00137 Mask loss: 0.49147 RPN box loss: 0.09049 RPN score loss: 0.03922 RPN total loss: 0.12971 Total loss: 3.51365 timestamp: 1655008599.0636106 iteration: 70 throughput: 23.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43815 FastRCNN class loss: 0.25157 FastRCNN total loss: 0.68972 L1 loss: 0.0000e+00 L2 loss: 2.24375 Learning rate: 0.00147 Mask loss: 0.48404 RPN box loss: 0.10107 RPN score loss: 0.03873 RPN total loss: 0.1398 Total loss: 3.55732 timestamp: 1655008602.2779555 iteration: 75 throughput: 26.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54419 FastRCNN class loss: 0.22436 FastRCNN total loss: 0.76855 L1 loss: 0.0000e+00 L2 loss: 2.24372 Learning rate: 0.00157 Mask loss: 0.53308 RPN box loss: 0.0772 RPN score loss: 0.04789 RPN total loss: 0.12509 Total loss: 3.67044 timestamp: 1655008605.3959968 iteration: 80 throughput: 26.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47081 FastRCNN class loss: 0.08652 FastRCNN total loss: 0.55733 L1 loss: 0.0000e+00 L2 loss: 2.24369 Learning rate: 0.00167 Mask loss: 0.47095 RPN box loss: 0.08559 RPN score loss: 0.03144 RPN total loss: 0.11703 Total loss: 3.389 timestamp: 1655008608.572422 iteration: 85 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53275 FastRCNN class loss: 0.26077 FastRCNN total loss: 0.79352 L1 loss: 0.0000e+00 L2 loss: 2.24365 Learning rate: 0.00177 Mask loss: 0.55817 RPN box loss: 0.06412 RPN score loss: 0.04875 RPN total loss: 0.11286 Total loss: 3.7082 timestamp: 1655008611.7428873 iteration: 90 throughput: 25.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.59804 FastRCNN class loss: 0.17611 FastRCNN total loss: 0.77415 L1 loss: 0.0000e+00 L2 loss: 2.24362 Learning rate: 0.00187 Mask loss: 0.65031 RPN box loss: 0.06663 RPN score loss: 0.03022 RPN total loss: 0.09685 Total loss: 3.76493 timestamp: 1655008614.9401443 iteration: 95 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51617 FastRCNN class loss: 0.11912 FastRCNN total loss: 0.63528 L1 loss: 0.0000e+00 L2 loss: 2.24358 Learning rate: 0.00197 Mask loss: 0.41377 RPN box loss: 0.02721 RPN score loss: 0.02319 RPN total loss: 0.0504 Total loss: 3.34303 timestamp: 1655008618.107441 iteration: 100 throughput: 25.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51809 FastRCNN class loss: 0.11247 FastRCNN total loss: 0.63056 L1 loss: 0.0000e+00 L2 loss: 2.24354 Learning rate: 0.00207 Mask loss: 0.59971 RPN box loss: 0.06779 RPN score loss: 0.03359 RPN total loss: 0.10139 Total loss: 3.5752 timestamp: 1655008621.372357 iteration: 105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48572 FastRCNN class loss: 0.18007 FastRCNN total loss: 0.66578 L1 loss: 0.0000e+00 L2 loss: 2.2435 Learning rate: 0.00217 Mask loss: 0.46711 RPN box loss: 0.06248 RPN score loss: 0.04221 RPN total loss: 0.10469 Total loss: 3.48108 timestamp: 1655008624.5295677 iteration: 110 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53954 FastRCNN class loss: 0.10574 FastRCNN total loss: 0.64528 L1 loss: 0.0000e+00 L2 loss: 2.24346 Learning rate: 0.00227 Mask loss: 0.53166 RPN box loss: 0.03534 RPN score loss: 0.03315 RPN total loss: 0.06849 Total loss: 3.48889 timestamp: 1655008627.7493498 iteration: 115 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48945 FastRCNN class loss: 0.16654 FastRCNN total loss: 0.65599 L1 loss: 0.0000e+00 L2 loss: 2.24342 Learning rate: 0.00237 Mask loss: 0.53839 RPN box loss: 0.054 RPN score loss: 0.02926 RPN total loss: 0.08326 Total loss: 3.52106 timestamp: 1655008630.9486024 iteration: 120 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43964 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.52732 L1 loss: 0.0000e+00 L2 loss: 2.24337 Learning rate: 0.00247 Mask loss: 0.37315 RPN box loss: 0.01885 RPN score loss: 0.01908 RPN total loss: 0.03793 Total loss: 3.18177 timestamp: 1655008634.1267416 iteration: 125 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51367 FastRCNN class loss: 0.14682 FastRCNN total loss: 0.66048 L1 loss: 0.0000e+00 L2 loss: 2.24332 Learning rate: 0.00257 Mask loss: 0.47589 RPN box loss: 0.06833 RPN score loss: 0.03122 RPN total loss: 0.09955 Total loss: 3.47925 timestamp: 1655008637.3170724 iteration: 130 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45373 FastRCNN class loss: 0.16523 FastRCNN total loss: 0.61896 L1 loss: 0.0000e+00 L2 loss: 2.24327 Learning rate: 0.00267 Mask loss: 0.46074 RPN box loss: 0.19329 RPN score loss: 0.03565 RPN total loss: 0.22895 Total loss: 3.55192 timestamp: 1655008640.619474 iteration: 135 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34272 FastRCNN class loss: 0.11257 FastRCNN total loss: 0.45529 L1 loss: 0.0000e+00 L2 loss: 2.24322 Learning rate: 0.00277 Mask loss: 0.35842 RPN box loss: 0.06561 RPN score loss: 0.02881 RPN total loss: 0.09441 Total loss: 3.15134 timestamp: 1655008643.8296847 iteration: 140 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42991 FastRCNN class loss: 0.17874 FastRCNN total loss: 0.60865 L1 loss: 0.0000e+00 L2 loss: 2.24316 Learning rate: 0.00287 Mask loss: 0.39523 RPN box loss: 0.05813 RPN score loss: 0.0263 RPN total loss: 0.08444 Total loss: 3.33148 timestamp: 1655008647.040941 iteration: 145 throughput: 25.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46277 FastRCNN class loss: 0.17703 FastRCNN total loss: 0.63981 L1 loss: 0.0000e+00 L2 loss: 2.24311 Learning rate: 0.00297 Mask loss: 0.35318 RPN box loss: 0.03463 RPN score loss: 0.02297 RPN total loss: 0.05759 Total loss: 3.29368 timestamp: 1655008650.268807 iteration: 150 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4976 FastRCNN class loss: 0.1698 FastRCNN total loss: 0.6674 L1 loss: 0.0000e+00 L2 loss: 2.24304 Learning rate: 0.00307 Mask loss: 0.42132 RPN box loss: 0.07234 RPN score loss: 0.02554 RPN total loss: 0.09788 Total loss: 3.42965 timestamp: 1655008653.6385825 iteration: 155 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39238 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.48219 L1 loss: 0.0000e+00 L2 loss: 2.24299 Learning rate: 0.00316 Mask loss: 0.37675 RPN box loss: 0.02498 RPN score loss: 0.02023 RPN total loss: 0.04521 Total loss: 3.14714 timestamp: 1655008656.9722366 iteration: 160 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52711 FastRCNN class loss: 0.19714 FastRCNN total loss: 0.72424 L1 loss: 0.0000e+00 L2 loss: 2.24293 Learning rate: 0.00326 Mask loss: 0.41341 RPN box loss: 0.03158 RPN score loss: 0.02272 RPN total loss: 0.05431 Total loss: 3.4349 timestamp: 1655008660.2177162 iteration: 165 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56408 FastRCNN class loss: 0.12723 FastRCNN total loss: 0.69132 L1 loss: 0.0000e+00 L2 loss: 2.24288 Learning rate: 0.00336 Mask loss: 0.50779 RPN box loss: 0.08128 RPN score loss: 0.02897 RPN total loss: 0.11025 Total loss: 3.55224 timestamp: 1655008663.452524 iteration: 170 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42166 FastRCNN class loss: 0.11828 FastRCNN total loss: 0.53995 L1 loss: 0.0000e+00 L2 loss: 2.24283 Learning rate: 0.00346 Mask loss: 0.48828 RPN box loss: 0.12448 RPN score loss: 0.04177 RPN total loss: 0.16625 Total loss: 3.4373 timestamp: 1655008666.7110229 iteration: 175 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40318 FastRCNN class loss: 0.13017 FastRCNN total loss: 0.53336 L1 loss: 0.0000e+00 L2 loss: 2.24279 Learning rate: 0.00356 Mask loss: 0.39821 RPN box loss: 0.02054 RPN score loss: 0.02724 RPN total loss: 0.04778 Total loss: 3.22213 timestamp: 1655008669.96351 iteration: 180 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56545 FastRCNN class loss: 0.28318 FastRCNN total loss: 0.84863 L1 loss: 0.0000e+00 L2 loss: 2.24274 Learning rate: 0.00366 Mask loss: 0.60886 RPN box loss: 0.08081 RPN score loss: 0.03801 RPN total loss: 0.11882 Total loss: 3.81905 timestamp: 1655008673.1620011 iteration: 185 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52699 FastRCNN class loss: 0.33371 FastRCNN total loss: 0.86069 L1 loss: 0.0000e+00 L2 loss: 2.24269 Learning rate: 0.00376 Mask loss: 0.66372 RPN box loss: 0.1205 RPN score loss: 0.0874 RPN total loss: 0.2079 Total loss: 3.975 timestamp: 1655008676.3965757 iteration: 190 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51467 FastRCNN class loss: 0.19184 FastRCNN total loss: 0.70651 L1 loss: 0.0000e+00 L2 loss: 2.24266 Learning rate: 0.00386 Mask loss: 0.64833 RPN box loss: 0.11192 RPN score loss: 0.04675 RPN total loss: 0.15867 Total loss: 3.75616 timestamp: 1655008679.6052644 iteration: 195 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56011 FastRCNN class loss: 0.17162 FastRCNN total loss: 0.73173 L1 loss: 0.0000e+00 L2 loss: 2.24261 Learning rate: 0.00396 Mask loss: 0.66613 RPN box loss: 0.13933 RPN score loss: 0.03442 RPN total loss: 0.17375 Total loss: 3.81423 timestamp: 1655008682.8440015 iteration: 200 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.60312 FastRCNN class loss: 0.16717 FastRCNN total loss: 0.77029 L1 loss: 0.0000e+00 L2 loss: 2.24255 Learning rate: 0.00406 Mask loss: 0.56817 RPN box loss: 0.18292 RPN score loss: 0.03716 RPN total loss: 0.22008 Total loss: 3.80108 timestamp: 1655008686.0854526 iteration: 205 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51728 FastRCNN class loss: 0.19849 FastRCNN total loss: 0.71577 L1 loss: 0.0000e+00 L2 loss: 2.24247 Learning rate: 0.00416 Mask loss: 0.60724 RPN box loss: 0.07947 RPN score loss: 0.03347 RPN total loss: 0.11294 Total loss: 3.67842 timestamp: 1655008689.2926931 iteration: 210 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58748 FastRCNN class loss: 0.20056 FastRCNN total loss: 0.78804 L1 loss: 0.0000e+00 L2 loss: 2.24239 Learning rate: 0.00426 Mask loss: 0.66212 RPN box loss: 0.05178 RPN score loss: 0.03413 RPN total loss: 0.0859 Total loss: 3.77845 timestamp: 1655008692.488457 iteration: 215 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56117 FastRCNN class loss: 0.20198 FastRCNN total loss: 0.76315 L1 loss: 0.0000e+00 L2 loss: 2.2423 Learning rate: 0.00436 Mask loss: 0.55869 RPN box loss: 0.06678 RPN score loss: 0.03028 RPN total loss: 0.09706 Total loss: 3.6612 timestamp: 1655008695.7251952 iteration: 220 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48931 FastRCNN class loss: 0.1894 FastRCNN total loss: 0.67871 L1 loss: 0.0000e+00 L2 loss: 2.24221 Learning rate: 0.00446 Mask loss: 0.54162 RPN box loss: 0.06121 RPN score loss: 0.02694 RPN total loss: 0.08814 Total loss: 3.55069 timestamp: 1655008698.951321 iteration: 225 throughput: 24.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55489 FastRCNN class loss: 0.16027 FastRCNN total loss: 0.71516 L1 loss: 0.0000e+00 L2 loss: 2.24212 Learning rate: 0.00456 Mask loss: 0.58998 RPN box loss: 0.06052 RPN score loss: 0.02322 RPN total loss: 0.08374 Total loss: 3.631 timestamp: 1655008702.2720177 iteration: 230 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.66857 FastRCNN class loss: 0.24013 FastRCNN total loss: 0.9087 L1 loss: 0.0000e+00 L2 loss: 2.24202 Learning rate: 0.00466 Mask loss: 0.61931 RPN box loss: 0.06768 RPN score loss: 0.0295 RPN total loss: 0.09718 Total loss: 3.86721 timestamp: 1655008705.4993584 iteration: 235 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43685 FastRCNN class loss: 0.12778 FastRCNN total loss: 0.56463 L1 loss: 0.0000e+00 L2 loss: 2.24192 Learning rate: 0.00476 Mask loss: 0.536 RPN box loss: 0.01356 RPN score loss: 0.02278 RPN total loss: 0.03634 Total loss: 3.37889 timestamp: 1655008708.742649 iteration: 240 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54638 FastRCNN class loss: 0.13907 FastRCNN total loss: 0.68544 L1 loss: 0.0000e+00 L2 loss: 2.24182 Learning rate: 0.00486 Mask loss: 0.57786 RPN box loss: 0.05926 RPN score loss: 0.01876 RPN total loss: 0.07802 Total loss: 3.58314 timestamp: 1655008712.0552716 iteration: 245 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.62058 FastRCNN class loss: 0.13763 FastRCNN total loss: 0.75821 L1 loss: 0.0000e+00 L2 loss: 2.24171 Learning rate: 0.00496 Mask loss: 0.6256 RPN box loss: 0.07754 RPN score loss: 0.03305 RPN total loss: 0.11058 Total loss: 3.73611 timestamp: 1655008715.4313192 iteration: 250 throughput: 24.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45529 FastRCNN class loss: 0.12771 FastRCNN total loss: 0.583 L1 loss: 0.0000e+00 L2 loss: 2.2416 Learning rate: 0.00506 Mask loss: 0.56263 RPN box loss: 0.02637 RPN score loss: 0.01642 RPN total loss: 0.04278 Total loss: 3.43003 timestamp: 1655008718.7859397 iteration: 255 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55985 FastRCNN class loss: 0.13743 FastRCNN total loss: 0.69729 L1 loss: 0.0000e+00 L2 loss: 2.24149 Learning rate: 0.00515 Mask loss: 0.5241 RPN box loss: 0.02698 RPN score loss: 0.02313 RPN total loss: 0.05011 Total loss: 3.51299 timestamp: 1655008722.0776675 iteration: 260 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55481 FastRCNN class loss: 0.14221 FastRCNN total loss: 0.69703 L1 loss: 0.0000e+00 L2 loss: 2.24137 Learning rate: 0.00525 Mask loss: 0.53798 RPN box loss: 0.03281 RPN score loss: 0.02827 RPN total loss: 0.06109 Total loss: 3.53747 timestamp: 1655008725.242086 iteration: 265 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5421 FastRCNN class loss: 0.15568 FastRCNN total loss: 0.69778 L1 loss: 0.0000e+00 L2 loss: 2.24125 Learning rate: 0.00535 Mask loss: 0.5397 RPN box loss: 0.10916 RPN score loss: 0.04166 RPN total loss: 0.15082 Total loss: 3.62955 timestamp: 1655008728.619741 iteration: 270 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58272 FastRCNN class loss: 0.18352 FastRCNN total loss: 0.76624 L1 loss: 0.0000e+00 L2 loss: 2.24113 Learning rate: 0.00545 Mask loss: 0.54934 RPN box loss: 0.03132 RPN score loss: 0.02225 RPN total loss: 0.05357 Total loss: 3.61028 timestamp: 1655008731.877741 iteration: 275 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51453 FastRCNN class loss: 0.19786 FastRCNN total loss: 0.71238 L1 loss: 0.0000e+00 L2 loss: 2.24102 Learning rate: 0.00555 Mask loss: 0.62219 RPN box loss: 0.04938 RPN score loss: 0.02153 RPN total loss: 0.07091 Total loss: 3.6465 timestamp: 1655008735.2087061 iteration: 280 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.64948 FastRCNN class loss: 0.23795 FastRCNN total loss: 0.88742 L1 loss: 0.0000e+00 L2 loss: 2.24089 Learning rate: 0.00565 Mask loss: 0.67095 RPN box loss: 0.02916 RPN score loss: 0.02447 RPN total loss: 0.05363 Total loss: 3.8529 timestamp: 1655008738.6861174 iteration: 285 throughput: 24.7 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57028 FastRCNN class loss: 0.16874 FastRCNN total loss: 0.73902 L1 loss: 0.0000e+00 L2 loss: 2.24077 Learning rate: 0.00575 Mask loss: 0.50936 RPN box loss: 0.07821 RPN score loss: 0.02506 RPN total loss: 0.10327 Total loss: 3.59242 timestamp: 1655008742.1443584 iteration: 290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55648 FastRCNN class loss: 0.15992 FastRCNN total loss: 0.7164 L1 loss: 0.0000e+00 L2 loss: 2.24064 Learning rate: 0.00585 Mask loss: 0.58858 RPN box loss: 0.085 RPN score loss: 0.02514 RPN total loss: 0.11015 Total loss: 3.65577 timestamp: 1655008745.4360638 iteration: 295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38684 FastRCNN class loss: 0.11488 FastRCNN total loss: 0.50172 L1 loss: 0.0000e+00 L2 loss: 2.2405 Learning rate: 0.00595 Mask loss: 0.56398 RPN box loss: 0.16416 RPN score loss: 0.03222 RPN total loss: 0.19638 Total loss: 3.50259 timestamp: 1655008748.7052996 iteration: 300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51151 FastRCNN class loss: 0.17078 FastRCNN total loss: 0.68229 L1 loss: 0.0000e+00 L2 loss: 2.24037 Learning rate: 0.00605 Mask loss: 0.58025 RPN box loss: 0.09229 RPN score loss: 0.04327 RPN total loss: 0.13556 Total loss: 3.63847 timestamp: 1655008752.0252693 iteration: 305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51717 FastRCNN class loss: 0.15745 FastRCNN total loss: 0.67462 L1 loss: 0.0000e+00 L2 loss: 2.24024 Learning rate: 0.00615 Mask loss: 0.68154 RPN box loss: 0.04771 RPN score loss: 0.02757 RPN total loss: 0.07529 Total loss: 3.67168 timestamp: 1655008755.3509483 iteration: 310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43699 FastRCNN class loss: 0.14991 FastRCNN total loss: 0.5869 L1 loss: 0.0000e+00 L2 loss: 2.2401 Learning rate: 0.00625 Mask loss: 0.5366 RPN box loss: 0.05977 RPN score loss: 0.02291 RPN total loss: 0.08268 Total loss: 3.44628 timestamp: 1655008758.631234 iteration: 315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53065 FastRCNN class loss: 0.15304 FastRCNN total loss: 0.68369 L1 loss: 0.0000e+00 L2 loss: 2.23996 Learning rate: 0.00635 Mask loss: 0.53564 RPN box loss: 0.07609 RPN score loss: 0.02027 RPN total loss: 0.09636 Total loss: 3.55565 timestamp: 1655008761.9903631 iteration: 320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52324 FastRCNN class loss: 0.18648 FastRCNN total loss: 0.70972 L1 loss: 0.0000e+00 L2 loss: 2.23982 Learning rate: 0.00645 Mask loss: 0.61849 RPN box loss: 0.03573 RPN score loss: 0.01668 RPN total loss: 0.05241 Total loss: 3.62044 timestamp: 1655008765.2613654 iteration: 325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46369 FastRCNN class loss: 0.10458 FastRCNN total loss: 0.56826 L1 loss: 0.0000e+00 L2 loss: 2.23968 Learning rate: 0.00655 Mask loss: 0.5011 RPN box loss: 0.07439 RPN score loss: 0.0147 RPN total loss: 0.08909 Total loss: 3.39813 timestamp: 1655008768.6817951 iteration: 330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42705 FastRCNN class loss: 0.11543 FastRCNN total loss: 0.54248 L1 loss: 0.0000e+00 L2 loss: 2.23953 Learning rate: 0.00665 Mask loss: 0.59731 RPN box loss: 0.08489 RPN score loss: 0.03158 RPN total loss: 0.11647 Total loss: 3.4958 timestamp: 1655008772.0374193 iteration: 335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4758 FastRCNN class loss: 0.13695 FastRCNN total loss: 0.61274 L1 loss: 0.0000e+00 L2 loss: 2.23938 Learning rate: 0.00675 Mask loss: 0.51346 RPN box loss: 0.08378 RPN score loss: 0.04317 RPN total loss: 0.12695 Total loss: 3.49254 timestamp: 1655008775.3577793 iteration: 340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49422 FastRCNN class loss: 0.16497 FastRCNN total loss: 0.65918 L1 loss: 0.0000e+00 L2 loss: 2.23923 Learning rate: 0.00685 Mask loss: 0.66313 RPN box loss: 0.06632 RPN score loss: 0.01662 RPN total loss: 0.08294 Total loss: 3.64449 timestamp: 1655008778.7016494 iteration: 345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52184 FastRCNN class loss: 0.15885 FastRCNN total loss: 0.68069 L1 loss: 0.0000e+00 L2 loss: 2.23908 Learning rate: 0.00695 Mask loss: 0.53521 RPN box loss: 0.0403 RPN score loss: 0.03094 RPN total loss: 0.07124 Total loss: 3.52622 timestamp: 1655008782.009353 iteration: 350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41437 FastRCNN class loss: 0.14295 FastRCNN total loss: 0.55732 L1 loss: 0.0000e+00 L2 loss: 2.23893 Learning rate: 0.00705 Mask loss: 0.61097 RPN box loss: 0.13602 RPN score loss: 0.06514 RPN total loss: 0.20116 Total loss: 3.60838 timestamp: 1655008785.332921 iteration: 355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34951 FastRCNN class loss: 0.1009 FastRCNN total loss: 0.45041 L1 loss: 0.0000e+00 L2 loss: 2.23877 Learning rate: 0.00714 Mask loss: 0.50928 RPN box loss: 0.06728 RPN score loss: 0.01508 RPN total loss: 0.08235 Total loss: 3.28082 timestamp: 1655008788.659243 iteration: 360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54572 FastRCNN class loss: 0.2351 FastRCNN total loss: 0.78081 L1 loss: 0.0000e+00 L2 loss: 2.23861 Learning rate: 0.00724 Mask loss: 0.62061 RPN box loss: 0.09082 RPN score loss: 0.03168 RPN total loss: 0.1225 Total loss: 3.76254 timestamp: 1655008791.9878418 iteration: 365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45008 FastRCNN class loss: 0.12166 FastRCNN total loss: 0.57174 L1 loss: 0.0000e+00 L2 loss: 2.23845 Learning rate: 0.00734 Mask loss: 0.66423 RPN box loss: 0.05385 RPN score loss: 0.022 RPN total loss: 0.07585 Total loss: 3.55027 timestamp: 1655008795.340201 iteration: 370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47779 FastRCNN class loss: 0.1403 FastRCNN total loss: 0.61809 L1 loss: 0.0000e+00 L2 loss: 2.23829 Learning rate: 0.00744 Mask loss: 0.6155 RPN box loss: 0.07957 RPN score loss: 0.02444 RPN total loss: 0.10401 Total loss: 3.57588 timestamp: 1655008798.7710607 iteration: 375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52303 FastRCNN class loss: 0.18152 FastRCNN total loss: 0.70455 L1 loss: 0.0000e+00 L2 loss: 2.23812 Learning rate: 0.00754 Mask loss: 0.59391 RPN box loss: 0.08569 RPN score loss: 0.02518 RPN total loss: 0.11087 Total loss: 3.64745 timestamp: 1655008802.1844945 iteration: 380 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45003 FastRCNN class loss: 0.24209 FastRCNN total loss: 0.69212 L1 loss: 0.0000e+00 L2 loss: 2.23795 Learning rate: 0.00764 Mask loss: 0.58036 RPN box loss: 0.06225 RPN score loss: 0.02516 RPN total loss: 0.0874 Total loss: 3.59784 timestamp: 1655008805.5509584 iteration: 385 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53491 FastRCNN class loss: 0.29737 FastRCNN total loss: 0.83228 L1 loss: 0.0000e+00 L2 loss: 2.23779 Learning rate: 0.00774 Mask loss: 0.60233 RPN box loss: 0.15068 RPN score loss: 0.08281 RPN total loss: 0.23349 Total loss: 3.90588 timestamp: 1655008808.8161538 iteration: 390 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46638 FastRCNN class loss: 0.11779 FastRCNN total loss: 0.58417 L1 loss: 0.0000e+00 L2 loss: 2.23761 Learning rate: 0.00784 Mask loss: 0.5845 RPN box loss: 0.02577 RPN score loss: 0.0178 RPN total loss: 0.04358 Total loss: 3.44986 timestamp: 1655008812.1273947 iteration: 395 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44687 FastRCNN class loss: 0.14152 FastRCNN total loss: 0.58839 L1 loss: 0.0000e+00 L2 loss: 2.23744 Learning rate: 0.00794 Mask loss: 0.59814 RPN box loss: 0.14012 RPN score loss: 0.01668 RPN total loss: 0.15679 Total loss: 3.58075 timestamp: 1655008815.486214 iteration: 400 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27591 FastRCNN class loss: 0.07894 FastRCNN total loss: 0.35485 L1 loss: 0.0000e+00 L2 loss: 2.23726 Learning rate: 0.00804 Mask loss: 0.63057 RPN box loss: 0.08657 RPN score loss: 0.01052 RPN total loss: 0.09709 Total loss: 3.31977 timestamp: 1655008818.8276796 iteration: 405 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44038 FastRCNN class loss: 0.14259 FastRCNN total loss: 0.58298 L1 loss: 0.0000e+00 L2 loss: 2.23708 Learning rate: 0.00814 Mask loss: 0.55581 RPN box loss: 0.0243 RPN score loss: 0.02023 RPN total loss: 0.04452 Total loss: 3.42039 timestamp: 1655008822.2794116 iteration: 410 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4643 FastRCNN class loss: 0.17923 FastRCNN total loss: 0.64354 L1 loss: 0.0000e+00 L2 loss: 2.23689 Learning rate: 0.00824 Mask loss: 0.66481 RPN box loss: 0.05477 RPN score loss: 0.04917 RPN total loss: 0.10394 Total loss: 3.64918 timestamp: 1655008825.5356574 iteration: 415 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58176 FastRCNN class loss: 0.16802 FastRCNN total loss: 0.74979 L1 loss: 0.0000e+00 L2 loss: 2.23671 Learning rate: 0.00834 Mask loss: 0.57598 RPN box loss: 0.05853 RPN score loss: 0.02088 RPN total loss: 0.07941 Total loss: 3.64189 timestamp: 1655008828.8146763 iteration: 420 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45973 FastRCNN class loss: 0.09968 FastRCNN total loss: 0.5594 L1 loss: 0.0000e+00 L2 loss: 2.23653 Learning rate: 0.00844 Mask loss: 0.5606 RPN box loss: 0.02374 RPN score loss: 0.01488 RPN total loss: 0.03862 Total loss: 3.39515 timestamp: 1655008832.1876357 iteration: 425 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53169 FastRCNN class loss: 0.2086 FastRCNN total loss: 0.7403 L1 loss: 0.0000e+00 L2 loss: 2.23634 Learning rate: 0.00854 Mask loss: 0.66141 RPN box loss: 0.15486 RPN score loss: 0.03179 RPN total loss: 0.18665 Total loss: 3.82469 timestamp: 1655008835.573997 iteration: 430 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50727 FastRCNN class loss: 0.1974 FastRCNN total loss: 0.70466 L1 loss: 0.0000e+00 L2 loss: 2.23615 Learning rate: 0.00864 Mask loss: 0.55112 RPN box loss: 0.05655 RPN score loss: 0.02195 RPN total loss: 0.07849 Total loss: 3.57043 timestamp: 1655008839.0050998 iteration: 435 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45215 FastRCNN class loss: 0.13577 FastRCNN total loss: 0.58792 L1 loss: 0.0000e+00 L2 loss: 2.23595 Learning rate: 0.00874 Mask loss: 0.55866 RPN box loss: 0.11707 RPN score loss: 0.03704 RPN total loss: 0.1541 Total loss: 3.53663 timestamp: 1655008842.4687142 iteration: 440 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46238 FastRCNN class loss: 0.10742 FastRCNN total loss: 0.56981 L1 loss: 0.0000e+00 L2 loss: 2.23576 Learning rate: 0.00884 Mask loss: 0.58372 RPN box loss: 0.09075 RPN score loss: 0.0177 RPN total loss: 0.10845 Total loss: 3.49773 timestamp: 1655008845.8729362 iteration: 445 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36261 FastRCNN class loss: 0.11136 FastRCNN total loss: 0.47397 L1 loss: 0.0000e+00 L2 loss: 2.23556 Learning rate: 0.00894 Mask loss: 0.4682 RPN box loss: 0.06001 RPN score loss: 0.0248 RPN total loss: 0.08481 Total loss: 3.26254 timestamp: 1655008849.243755 iteration: 450 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.433 FastRCNN class loss: 0.09515 FastRCNN total loss: 0.52815 L1 loss: 0.0000e+00 L2 loss: 2.23537 Learning rate: 0.00904 Mask loss: 0.58364 RPN box loss: 0.07436 RPN score loss: 0.03118 RPN total loss: 0.10554 Total loss: 3.4527 timestamp: 1655008852.6748154 iteration: 455 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49215 FastRCNN class loss: 0.23885 FastRCNN total loss: 0.731 L1 loss: 0.0000e+00 L2 loss: 2.23517 Learning rate: 0.00913 Mask loss: 0.58783 RPN box loss: 0.14661 RPN score loss: 0.04924 RPN total loss: 0.19585 Total loss: 3.74984 timestamp: 1655008856.1255152 iteration: 460 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41243 FastRCNN class loss: 0.12752 FastRCNN total loss: 0.53994 L1 loss: 0.0000e+00 L2 loss: 2.23496 Learning rate: 0.00923 Mask loss: 0.52551 RPN box loss: 0.12911 RPN score loss: 0.03528 RPN total loss: 0.1644 Total loss: 3.46481 timestamp: 1655008859.5226712 iteration: 465 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4371 FastRCNN class loss: 0.14368 FastRCNN total loss: 0.58078 L1 loss: 0.0000e+00 L2 loss: 2.23474 Learning rate: 0.00933 Mask loss: 0.55955 RPN box loss: 0.00905 RPN score loss: 0.01622 RPN total loss: 0.02526 Total loss: 3.40033 timestamp: 1655008862.8565936 iteration: 470 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58065 FastRCNN class loss: 0.28009 FastRCNN total loss: 0.86074 L1 loss: 0.0000e+00 L2 loss: 2.23452 Learning rate: 0.00943 Mask loss: 0.61476 RPN box loss: 0.07276 RPN score loss: 0.04721 RPN total loss: 0.11997 Total loss: 3.82999 timestamp: 1655008866.2272487 iteration: 475 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32264 FastRCNN class loss: 0.1125 FastRCNN total loss: 0.43514 L1 loss: 0.0000e+00 L2 loss: 2.23431 Learning rate: 0.00953 Mask loss: 0.58865 RPN box loss: 0.05895 RPN score loss: 0.01711 RPN total loss: 0.07606 Total loss: 3.33416 timestamp: 1655008869.6695113 iteration: 480 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39583 FastRCNN class loss: 0.15889 FastRCNN total loss: 0.55472 L1 loss: 0.0000e+00 L2 loss: 2.23409 Learning rate: 0.00963 Mask loss: 0.52065 RPN box loss: 0.05815 RPN score loss: 0.03083 RPN total loss: 0.08898 Total loss: 3.39844 timestamp: 1655008873.0636902 iteration: 485 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31817 FastRCNN class loss: 0.09998 FastRCNN total loss: 0.41815 L1 loss: 0.0000e+00 L2 loss: 2.23387 Learning rate: 0.00973 Mask loss: 0.53636 RPN box loss: 0.06035 RPN score loss: 0.02686 RPN total loss: 0.08721 Total loss: 3.27559 timestamp: 1655008876.4873123 iteration: 490 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3561 FastRCNN class loss: 0.10262 FastRCNN total loss: 0.45872 L1 loss: 0.0000e+00 L2 loss: 2.23365 Learning rate: 0.00983 Mask loss: 0.49798 RPN box loss: 0.07355 RPN score loss: 0.04415 RPN total loss: 0.1177 Total loss: 3.30805 timestamp: 1655008879.8843203 iteration: 495 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50022 FastRCNN class loss: 0.17599 FastRCNN total loss: 0.67621 L1 loss: 0.0000e+00 L2 loss: 2.23343 Learning rate: 0.00993 Mask loss: 0.56722 RPN box loss: 0.0694 RPN score loss: 0.02801 RPN total loss: 0.09741 Total loss: 3.57428 timestamp: 1655008883.2255027 iteration: 500 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54105 FastRCNN class loss: 0.23066 FastRCNN total loss: 0.77171 L1 loss: 0.0000e+00 L2 loss: 2.23321 Learning rate: 0.01003 Mask loss: 0.48682 RPN box loss: 0.03051 RPN score loss: 0.01822 RPN total loss: 0.04873 Total loss: 3.54047 timestamp: 1655008886.5124426 iteration: 505 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56538 FastRCNN class loss: 0.15551 FastRCNN total loss: 0.72088 L1 loss: 0.0000e+00 L2 loss: 2.23298 Learning rate: 0.01013 Mask loss: 0.62716 RPN box loss: 0.01634 RPN score loss: 0.01247 RPN total loss: 0.02881 Total loss: 3.60984 timestamp: 1655008889.7088108 iteration: 510 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3772 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.44858 L1 loss: 0.0000e+00 L2 loss: 2.23276 Learning rate: 0.01023 Mask loss: 0.56941 RPN box loss: 0.05413 RPN score loss: 0.0174 RPN total loss: 0.07153 Total loss: 3.32227 timestamp: 1655008893.0729928 iteration: 515 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39149 FastRCNN class loss: 0.11406 FastRCNN total loss: 0.50555 L1 loss: 0.0000e+00 L2 loss: 2.23253 Learning rate: 0.01033 Mask loss: 0.4985 RPN box loss: 0.06966 RPN score loss: 0.04024 RPN total loss: 0.1099 Total loss: 3.34648 timestamp: 1655008896.408322 iteration: 520 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48942 FastRCNN class loss: 0.12301 FastRCNN total loss: 0.61243 L1 loss: 0.0000e+00 L2 loss: 2.23231 Learning rate: 0.01043 Mask loss: 0.63212 RPN box loss: 0.04008 RPN score loss: 0.01306 RPN total loss: 0.05314 Total loss: 3.53001 timestamp: 1655008899.7903383 iteration: 525 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4363 FastRCNN class loss: 0.12619 FastRCNN total loss: 0.56249 L1 loss: 0.0000e+00 L2 loss: 2.23208 Learning rate: 0.01053 Mask loss: 0.50646 RPN box loss: 0.12773 RPN score loss: 0.02498 RPN total loss: 0.15272 Total loss: 3.45375 timestamp: 1655008903.1511724 iteration: 530 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49137 FastRCNN class loss: 0.16122 FastRCNN total loss: 0.6526 L1 loss: 0.0000e+00 L2 loss: 2.23185 Learning rate: 0.01063 Mask loss: 0.60484 RPN box loss: 0.10024 RPN score loss: 0.02797 RPN total loss: 0.1282 Total loss: 3.61749 timestamp: 1655008906.4174469 iteration: 535 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43553 FastRCNN class loss: 0.15263 FastRCNN total loss: 0.58815 L1 loss: 0.0000e+00 L2 loss: 2.23162 Learning rate: 0.01073 Mask loss: 0.60488 RPN box loss: 0.04917 RPN score loss: 0.02477 RPN total loss: 0.07394 Total loss: 3.49859 timestamp: 1655008909.7480671 iteration: 540 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36035 FastRCNN class loss: 0.13421 FastRCNN total loss: 0.49456 L1 loss: 0.0000e+00 L2 loss: 2.23138 Learning rate: 0.01083 Mask loss: 0.47369 RPN box loss: 0.01934 RPN score loss: 0.01249 RPN total loss: 0.03183 Total loss: 3.23146 timestamp: 1655008913.2225564 iteration: 545 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52371 FastRCNN class loss: 0.13948 FastRCNN total loss: 0.66319 L1 loss: 0.0000e+00 L2 loss: 2.23114 Learning rate: 0.01093 Mask loss: 0.5429 RPN box loss: 0.09352 RPN score loss: 0.05927 RPN total loss: 0.15279 Total loss: 3.59002 timestamp: 1655008916.6841571 iteration: 550 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48368 FastRCNN class loss: 0.1859 FastRCNN total loss: 0.66958 L1 loss: 0.0000e+00 L2 loss: 2.23091 Learning rate: 0.01103 Mask loss: 0.70789 RPN box loss: 0.031 RPN score loss: 0.03872 RPN total loss: 0.06972 Total loss: 3.6781 timestamp: 1655008920.0226524 iteration: 555 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43865 FastRCNN class loss: 0.12543 FastRCNN total loss: 0.56408 L1 loss: 0.0000e+00 L2 loss: 2.23066 Learning rate: 0.01112 Mask loss: 0.63065 RPN box loss: 0.0963 RPN score loss: 0.02858 RPN total loss: 0.12487 Total loss: 3.55026 timestamp: 1655008923.233859 iteration: 560 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49235 FastRCNN class loss: 0.21892 FastRCNN total loss: 0.71127 L1 loss: 0.0000e+00 L2 loss: 2.23042 Learning rate: 0.01122 Mask loss: 0.60546 RPN box loss: 0.08168 RPN score loss: 0.0411 RPN total loss: 0.12278 Total loss: 3.66992 timestamp: 1655008926.6681693 iteration: 565 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37802 FastRCNN class loss: 0.11395 FastRCNN total loss: 0.49197 L1 loss: 0.0000e+00 L2 loss: 2.23017 Learning rate: 0.01132 Mask loss: 0.55614 RPN box loss: 0.12949 RPN score loss: 0.02832 RPN total loss: 0.15781 Total loss: 3.43609 timestamp: 1655008929.9723175 iteration: 570 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50898 FastRCNN class loss: 0.14828 FastRCNN total loss: 0.65727 L1 loss: 0.0000e+00 L2 loss: 2.22992 Learning rate: 0.01142 Mask loss: 0.59251 RPN box loss: 0.08821 RPN score loss: 0.02822 RPN total loss: 0.11644 Total loss: 3.59613 timestamp: 1655008933.3184612 iteration: 575 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37927 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.45822 L1 loss: 0.0000e+00 L2 loss: 2.22966 Learning rate: 0.01152 Mask loss: 0.58897 RPN box loss: 0.03545 RPN score loss: 0.02096 RPN total loss: 0.0564 Total loss: 3.33325 timestamp: 1655008936.802586 iteration: 580 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53028 FastRCNN class loss: 0.23912 FastRCNN total loss: 0.7694 L1 loss: 0.0000e+00 L2 loss: 2.22941 Learning rate: 0.01162 Mask loss: 0.59711 RPN box loss: 0.05562 RPN score loss: 0.02938 RPN total loss: 0.085 Total loss: 3.68091 timestamp: 1655008940.1527183 iteration: 585 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5538 FastRCNN class loss: 0.2116 FastRCNN total loss: 0.76539 L1 loss: 0.0000e+00 L2 loss: 2.22915 Learning rate: 0.01172 Mask loss: 0.56214 RPN box loss: 0.03736 RPN score loss: 0.05143 RPN total loss: 0.08879 Total loss: 3.64547 timestamp: 1655008943.432323 iteration: 590 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38414 FastRCNN class loss: 0.13634 FastRCNN total loss: 0.52049 L1 loss: 0.0000e+00 L2 loss: 2.22889 Learning rate: 0.01182 Mask loss: 0.54388 RPN box loss: 0.06157 RPN score loss: 0.0191 RPN total loss: 0.08066 Total loss: 3.37393 timestamp: 1655008946.7520525 iteration: 595 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37981 FastRCNN class loss: 0.12941 FastRCNN total loss: 0.50922 L1 loss: 0.0000e+00 L2 loss: 2.22864 Learning rate: 0.01192 Mask loss: 0.5013 RPN box loss: 0.07143 RPN score loss: 0.02367 RPN total loss: 0.09509 Total loss: 3.33425 timestamp: 1655008950.1156583 iteration: 600 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.59993 FastRCNN class loss: 0.20323 FastRCNN total loss: 0.80316 L1 loss: 0.0000e+00 L2 loss: 2.2284 Learning rate: 0.01202 Mask loss: 0.60569 RPN box loss: 0.13531 RPN score loss: 0.0226 RPN total loss: 0.15791 Total loss: 3.79516 timestamp: 1655008953.4260952 iteration: 605 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49613 FastRCNN class loss: 0.20784 FastRCNN total loss: 0.70397 L1 loss: 0.0000e+00 L2 loss: 2.2281 Learning rate: 0.01212 Mask loss: 0.56668 RPN box loss: 0.11116 RPN score loss: 0.03295 RPN total loss: 0.1441 Total loss: 3.64285 timestamp: 1655008956.7595618 iteration: 610 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43912 FastRCNN class loss: 0.12237 FastRCNN total loss: 0.56149 L1 loss: 0.0000e+00 L2 loss: 2.22781 Learning rate: 0.01222 Mask loss: 0.58212 RPN box loss: 0.0801 RPN score loss: 0.03707 RPN total loss: 0.11718 Total loss: 3.4886 timestamp: 1655008960.073714 iteration: 615 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.6682 FastRCNN class loss: 0.14063 FastRCNN total loss: 0.80883 L1 loss: 0.0000e+00 L2 loss: 2.22754 Learning rate: 0.01232 Mask loss: 0.5866 RPN box loss: 0.09581 RPN score loss: 0.03026 RPN total loss: 0.12607 Total loss: 3.74904 timestamp: 1655008963.3881946 iteration: 620 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55963 FastRCNN class loss: 0.20838 FastRCNN total loss: 0.76801 L1 loss: 0.0000e+00 L2 loss: 2.22725 Learning rate: 0.01242 Mask loss: 0.5566 RPN box loss: 0.05823 RPN score loss: 0.01334 RPN total loss: 0.07157 Total loss: 3.62343 timestamp: 1655008966.7851796 iteration: 625 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43262 FastRCNN class loss: 0.16048 FastRCNN total loss: 0.59309 L1 loss: 0.0000e+00 L2 loss: 2.22696 Learning rate: 0.01252 Mask loss: 0.57499 RPN box loss: 0.05222 RPN score loss: 0.01492 RPN total loss: 0.06714 Total loss: 3.46219 timestamp: 1655008970.0995843 iteration: 630 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34458 FastRCNN class loss: 0.13266 FastRCNN total loss: 0.47724 L1 loss: 0.0000e+00 L2 loss: 2.22669 Learning rate: 0.01262 Mask loss: 0.491 RPN box loss: 0.08118 RPN score loss: 0.01998 RPN total loss: 0.10116 Total loss: 3.29609 timestamp: 1655008973.2853284 iteration: 635 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50464 FastRCNN class loss: 0.11597 FastRCNN total loss: 0.6206 L1 loss: 0.0000e+00 L2 loss: 2.22641 Learning rate: 0.01272 Mask loss: 0.66055 RPN box loss: 0.02283 RPN score loss: 0.01252 RPN total loss: 0.03535 Total loss: 3.54291 timestamp: 1655008976.544266 iteration: 640 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56068 FastRCNN class loss: 0.23852 FastRCNN total loss: 0.7992 L1 loss: 0.0000e+00 L2 loss: 2.22613 Learning rate: 0.01282 Mask loss: 0.61364 RPN box loss: 0.10362 RPN score loss: 0.03177 RPN total loss: 0.13539 Total loss: 3.77437 timestamp: 1655008979.87448 iteration: 645 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52498 FastRCNN class loss: 0.25318 FastRCNN total loss: 0.77816 L1 loss: 0.0000e+00 L2 loss: 2.22584 Learning rate: 0.01292 Mask loss: 0.62593 RPN box loss: 0.05053 RPN score loss: 0.01813 RPN total loss: 0.06866 Total loss: 3.6986 timestamp: 1655008983.1218188 iteration: 650 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46245 FastRCNN class loss: 0.11125 FastRCNN total loss: 0.5737 L1 loss: 0.0000e+00 L2 loss: 2.22556 Learning rate: 0.01302 Mask loss: 0.57764 RPN box loss: 0.05474 RPN score loss: 0.02304 RPN total loss: 0.07778 Total loss: 3.45469 timestamp: 1655008986.4099407 iteration: 655 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45367 FastRCNN class loss: 0.1549 FastRCNN total loss: 0.60857 L1 loss: 0.0000e+00 L2 loss: 2.22526 Learning rate: 0.01311 Mask loss: 0.52723 RPN box loss: 0.03143 RPN score loss: 0.01523 RPN total loss: 0.04666 Total loss: 3.40773 timestamp: 1655008989.8763556 iteration: 660 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49045 FastRCNN class loss: 0.21103 FastRCNN total loss: 0.70147 L1 loss: 0.0000e+00 L2 loss: 2.22497 Learning rate: 0.01321 Mask loss: 0.6486 RPN box loss: 0.17563 RPN score loss: 0.03163 RPN total loss: 0.20726 Total loss: 3.7823 timestamp: 1655008993.2878392 iteration: 665 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57464 FastRCNN class loss: 0.18239 FastRCNN total loss: 0.75703 L1 loss: 0.0000e+00 L2 loss: 2.22467 Learning rate: 0.01331 Mask loss: 0.70584 RPN box loss: 0.03145 RPN score loss: 0.02063 RPN total loss: 0.05208 Total loss: 3.73962 timestamp: 1655008996.6961029 iteration: 670 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4173 FastRCNN class loss: 0.14298 FastRCNN total loss: 0.56029 L1 loss: 0.0000e+00 L2 loss: 2.22438 Learning rate: 0.01341 Mask loss: 0.53602 RPN box loss: 0.04436 RPN score loss: 0.01139 RPN total loss: 0.05575 Total loss: 3.37644 timestamp: 1655009000.1048505 iteration: 675 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47408 FastRCNN class loss: 0.12349 FastRCNN total loss: 0.59757 L1 loss: 0.0000e+00 L2 loss: 2.22409 Learning rate: 0.01351 Mask loss: 0.54534 RPN box loss: 0.01722 RPN score loss: 0.01451 RPN total loss: 0.03173 Total loss: 3.39873 timestamp: 1655009003.5261574 iteration: 680 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5548 FastRCNN class loss: 0.12681 FastRCNN total loss: 0.68162 L1 loss: 0.0000e+00 L2 loss: 2.22379 Learning rate: 0.01361 Mask loss: 0.57969 RPN box loss: 0.06776 RPN score loss: 0.02382 RPN total loss: 0.09159 Total loss: 3.57669 timestamp: 1655009007.0509524 iteration: 685 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3789 FastRCNN class loss: 0.15238 FastRCNN total loss: 0.53128 L1 loss: 0.0000e+00 L2 loss: 2.22349 Learning rate: 0.01371 Mask loss: 0.54108 RPN box loss: 0.0697 RPN score loss: 0.02554 RPN total loss: 0.09524 Total loss: 3.3911 timestamp: 1655009010.4583833 iteration: 690 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54276 FastRCNN class loss: 0.22142 FastRCNN total loss: 0.76418 L1 loss: 0.0000e+00 L2 loss: 2.22321 Learning rate: 0.01381 Mask loss: 0.73075 RPN box loss: 0.08972 RPN score loss: 0.01964 RPN total loss: 0.10936 Total loss: 3.82749 timestamp: 1655009013.7792249 iteration: 695 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48702 FastRCNN class loss: 0.16447 FastRCNN total loss: 0.65148 L1 loss: 0.0000e+00 L2 loss: 2.2229 Learning rate: 0.01391 Mask loss: 0.59542 RPN box loss: 0.07186 RPN score loss: 0.02274 RPN total loss: 0.09461 Total loss: 3.56441 timestamp: 1655009017.0795407 iteration: 700 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39526 FastRCNN class loss: 0.15713 FastRCNN total loss: 0.5524 L1 loss: 0.0000e+00 L2 loss: 2.2226 Learning rate: 0.01401 Mask loss: 0.56843 RPN box loss: 0.05149 RPN score loss: 0.0362 RPN total loss: 0.08769 Total loss: 3.43112 timestamp: 1655009020.483055 iteration: 705 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.60934 FastRCNN class loss: 0.17639 FastRCNN total loss: 0.78573 L1 loss: 0.0000e+00 L2 loss: 2.22229 Learning rate: 0.01411 Mask loss: 0.56927 RPN box loss: 0.01115 RPN score loss: 0.01542 RPN total loss: 0.02657 Total loss: 3.60386 timestamp: 1655009023.9116573 iteration: 710 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38761 FastRCNN class loss: 0.08295 FastRCNN total loss: 0.47056 L1 loss: 0.0000e+00 L2 loss: 2.222 Learning rate: 0.01421 Mask loss: 0.50764 RPN box loss: 0.04696 RPN score loss: 0.02333 RPN total loss: 0.07029 Total loss: 3.2705 timestamp: 1655009027.2537746 iteration: 715 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50753 FastRCNN class loss: 0.12646 FastRCNN total loss: 0.63399 L1 loss: 0.0000e+00 L2 loss: 2.22168 Learning rate: 0.01431 Mask loss: 0.56406 RPN box loss: 0.06974 RPN score loss: 0.01929 RPN total loss: 0.08904 Total loss: 3.50877 timestamp: 1655009030.5416303 iteration: 720 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47967 FastRCNN class loss: 0.14302 FastRCNN total loss: 0.62269 L1 loss: 0.0000e+00 L2 loss: 2.22139 Learning rate: 0.01441 Mask loss: 0.60019 RPN box loss: 0.08238 RPN score loss: 0.02079 RPN total loss: 0.10317 Total loss: 3.54744 timestamp: 1655009033.7684064 iteration: 725 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55608 FastRCNN class loss: 0.12701 FastRCNN total loss: 0.68309 L1 loss: 0.0000e+00 L2 loss: 2.22108 Learning rate: 0.01451 Mask loss: 0.55513 RPN box loss: 0.02421 RPN score loss: 0.01282 RPN total loss: 0.03703 Total loss: 3.49633 timestamp: 1655009037.106598 iteration: 730 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41234 FastRCNN class loss: 0.12256 FastRCNN total loss: 0.53491 L1 loss: 0.0000e+00 L2 loss: 2.22079 Learning rate: 0.01461 Mask loss: 0.50116 RPN box loss: 0.09182 RPN score loss: 0.01727 RPN total loss: 0.10908 Total loss: 3.36593 timestamp: 1655009040.310029 iteration: 735 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40865 FastRCNN class loss: 0.179 FastRCNN total loss: 0.58764 L1 loss: 0.0000e+00 L2 loss: 2.22047 Learning rate: 0.01471 Mask loss: 0.5616 RPN box loss: 0.05801 RPN score loss: 0.02305 RPN total loss: 0.08107 Total loss: 3.45078 timestamp: 1655009043.582618 iteration: 740 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51908 FastRCNN class loss: 0.11593 FastRCNN total loss: 0.63501 L1 loss: 0.0000e+00 L2 loss: 2.22014 Learning rate: 0.01481 Mask loss: 0.57078 RPN box loss: 0.05424 RPN score loss: 0.04053 RPN total loss: 0.09478 Total loss: 3.52071 timestamp: 1655009046.8441029 iteration: 745 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41976 FastRCNN class loss: 0.15798 FastRCNN total loss: 0.57774 L1 loss: 0.0000e+00 L2 loss: 2.21982 Learning rate: 0.01491 Mask loss: 0.63907 RPN box loss: 0.04762 RPN score loss: 0.02122 RPN total loss: 0.06884 Total loss: 3.50547 timestamp: 1655009050.0697064 iteration: 750 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56739 FastRCNN class loss: 0.13564 FastRCNN total loss: 0.70303 L1 loss: 0.0000e+00 L2 loss: 2.21948 Learning rate: 0.01501 Mask loss: 0.60962 RPN box loss: 0.1036 RPN score loss: 0.04992 RPN total loss: 0.15352 Total loss: 3.68566 timestamp: 1655009053.398041 iteration: 755 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37045 FastRCNN class loss: 0.14289 FastRCNN total loss: 0.51334 L1 loss: 0.0000e+00 L2 loss: 2.21913 Learning rate: 0.0151 Mask loss: 0.53218 RPN box loss: 0.13824 RPN score loss: 0.03761 RPN total loss: 0.17586 Total loss: 3.4405 timestamp: 1655009056.757991 iteration: 760 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48821 FastRCNN class loss: 0.12296 FastRCNN total loss: 0.61118 L1 loss: 0.0000e+00 L2 loss: 2.21879 Learning rate: 0.0152 Mask loss: 0.46268 RPN box loss: 0.08108 RPN score loss: 0.02406 RPN total loss: 0.10514 Total loss: 3.39779 timestamp: 1655009060.1284473 iteration: 765 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45202 FastRCNN class loss: 0.16239 FastRCNN total loss: 0.6144 L1 loss: 0.0000e+00 L2 loss: 2.21843 Learning rate: 0.0153 Mask loss: 0.61042 RPN box loss: 0.0715 RPN score loss: 0.02002 RPN total loss: 0.09151 Total loss: 3.53477 timestamp: 1655009063.511778 iteration: 770 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42073 FastRCNN class loss: 0.16914 FastRCNN total loss: 0.58987 L1 loss: 0.0000e+00 L2 loss: 2.21809 Learning rate: 0.0154 Mask loss: 0.57482 RPN box loss: 0.07468 RPN score loss: 0.01805 RPN total loss: 0.09273 Total loss: 3.47551 timestamp: 1655009066.9005034 iteration: 775 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49511 FastRCNN class loss: 0.18938 FastRCNN total loss: 0.68449 L1 loss: 0.0000e+00 L2 loss: 2.21774 Learning rate: 0.0155 Mask loss: 0.55136 RPN box loss: 0.04405 RPN score loss: 0.0219 RPN total loss: 0.06594 Total loss: 3.51954 timestamp: 1655009070.2527034 iteration: 780 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39359 FastRCNN class loss: 0.14223 FastRCNN total loss: 0.53582 L1 loss: 0.0000e+00 L2 loss: 2.2174 Learning rate: 0.0156 Mask loss: 0.56813 RPN box loss: 0.04671 RPN score loss: 0.00997 RPN total loss: 0.05668 Total loss: 3.37804 timestamp: 1655009073.6796536 iteration: 785 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44286 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.56797 L1 loss: 0.0000e+00 L2 loss: 2.21705 Learning rate: 0.0157 Mask loss: 0.5347 RPN box loss: 0.06954 RPN score loss: 0.02424 RPN total loss: 0.09378 Total loss: 3.4135 timestamp: 1655009077.0275214 iteration: 790 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40225 FastRCNN class loss: 0.18217 FastRCNN total loss: 0.58442 L1 loss: 0.0000e+00 L2 loss: 2.2167 Learning rate: 0.0158 Mask loss: 0.47789 RPN box loss: 0.04725 RPN score loss: 0.02869 RPN total loss: 0.07594 Total loss: 3.35495 timestamp: 1655009080.3307753 iteration: 795 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46186 FastRCNN class loss: 0.15417 FastRCNN total loss: 0.61603 L1 loss: 0.0000e+00 L2 loss: 2.21635 Learning rate: 0.0159 Mask loss: 0.54255 RPN box loss: 0.07518 RPN score loss: 0.03108 RPN total loss: 0.10627 Total loss: 3.48119 timestamp: 1655009083.6878302 iteration: 800 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45228 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.5556 L1 loss: 0.0000e+00 L2 loss: 2.21598 Learning rate: 0.016 Mask loss: 0.5916 RPN box loss: 0.03333 RPN score loss: 0.01117 RPN total loss: 0.04451 Total loss: 3.4077 timestamp: 1655009087.0191417 iteration: 805 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4238 FastRCNN class loss: 0.17105 FastRCNN total loss: 0.59484 L1 loss: 0.0000e+00 L2 loss: 2.21562 Learning rate: 0.0161 Mask loss: 0.56766 RPN box loss: 0.17441 RPN score loss: 0.02765 RPN total loss: 0.20207 Total loss: 3.58019 timestamp: 1655009090.3725214 iteration: 810 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38373 FastRCNN class loss: 0.09021 FastRCNN total loss: 0.47394 L1 loss: 0.0000e+00 L2 loss: 2.21526 Learning rate: 0.0162 Mask loss: 0.54439 RPN box loss: 0.01293 RPN score loss: 0.01892 RPN total loss: 0.03185 Total loss: 3.26544 timestamp: 1655009093.6555617 iteration: 815 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37514 FastRCNN class loss: 0.11721 FastRCNN total loss: 0.49235 L1 loss: 0.0000e+00 L2 loss: 2.21491 Learning rate: 0.0163 Mask loss: 0.55233 RPN box loss: 0.19028 RPN score loss: 0.01944 RPN total loss: 0.20973 Total loss: 3.46932 timestamp: 1655009096.9313107 iteration: 820 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4207 FastRCNN class loss: 0.18758 FastRCNN total loss: 0.60828 L1 loss: 0.0000e+00 L2 loss: 2.21454 Learning rate: 0.0164 Mask loss: 0.54232 RPN box loss: 0.0314 RPN score loss: 0.02103 RPN total loss: 0.05242 Total loss: 3.41757 timestamp: 1655009100.3843973 iteration: 825 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.68193 FastRCNN class loss: 0.16944 FastRCNN total loss: 0.85137 L1 loss: 0.0000e+00 L2 loss: 2.21418 Learning rate: 0.0165 Mask loss: 0.60631 RPN box loss: 0.08222 RPN score loss: 0.02512 RPN total loss: 0.10735 Total loss: 3.77921 timestamp: 1655009103.7829235 iteration: 830 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40727 FastRCNN class loss: 0.148 FastRCNN total loss: 0.55527 L1 loss: 0.0000e+00 L2 loss: 2.21381 Learning rate: 0.0166 Mask loss: 0.50457 RPN box loss: 0.03797 RPN score loss: 0.03802 RPN total loss: 0.076 Total loss: 3.34965 timestamp: 1655009107.036318 iteration: 835 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4595 FastRCNN class loss: 0.17702 FastRCNN total loss: 0.63653 L1 loss: 0.0000e+00 L2 loss: 2.21344 Learning rate: 0.0167 Mask loss: 0.50519 RPN box loss: 0.07304 RPN score loss: 0.02704 RPN total loss: 0.10008 Total loss: 3.45525 timestamp: 1655009110.4043527 iteration: 840 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43053 FastRCNN class loss: 0.11757 FastRCNN total loss: 0.5481 L1 loss: 0.0000e+00 L2 loss: 2.21307 Learning rate: 0.0168 Mask loss: 0.48769 RPN box loss: 0.03524 RPN score loss: 0.01662 RPN total loss: 0.05186 Total loss: 3.30072 timestamp: 1655009113.744247 iteration: 845 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45432 FastRCNN class loss: 0.21486 FastRCNN total loss: 0.66918 L1 loss: 0.0000e+00 L2 loss: 2.2127 Learning rate: 0.0169 Mask loss: 0.55293 RPN box loss: 0.02867 RPN score loss: 0.01709 RPN total loss: 0.04577 Total loss: 3.48058 timestamp: 1655009117.028291 iteration: 850 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40602 FastRCNN class loss: 0.12148 FastRCNN total loss: 0.5275 L1 loss: 0.0000e+00 L2 loss: 2.21233 Learning rate: 0.017 Mask loss: 0.59039 RPN box loss: 0.08206 RPN score loss: 0.02183 RPN total loss: 0.10389 Total loss: 3.43411 timestamp: 1655009120.360529 iteration: 855 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47413 FastRCNN class loss: 0.15813 FastRCNN total loss: 0.63227 L1 loss: 0.0000e+00 L2 loss: 2.21194 Learning rate: 0.01709 Mask loss: 0.56419 RPN box loss: 0.06458 RPN score loss: 0.02557 RPN total loss: 0.09015 Total loss: 3.49854 timestamp: 1655009123.9426289 iteration: 860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53197 FastRCNN class loss: 0.1877 FastRCNN total loss: 0.71967 L1 loss: 0.0000e+00 L2 loss: 2.21156 Learning rate: 0.01719 Mask loss: 0.56041 RPN box loss: 0.10538 RPN score loss: 0.04163 RPN total loss: 0.147 Total loss: 3.63865 timestamp: 1655009127.3865948 iteration: 865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33686 FastRCNN class loss: 0.12884 FastRCNN total loss: 0.46569 L1 loss: 0.0000e+00 L2 loss: 2.21118 Learning rate: 0.01729 Mask loss: 0.57362 RPN box loss: 0.05048 RPN score loss: 0.01508 RPN total loss: 0.06555 Total loss: 3.31604 timestamp: 1655009130.8571703 iteration: 870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51501 FastRCNN class loss: 0.11479 FastRCNN total loss: 0.6298 L1 loss: 0.0000e+00 L2 loss: 2.21079 Learning rate: 0.01739 Mask loss: 0.58283 RPN box loss: 0.19592 RPN score loss: 0.03436 RPN total loss: 0.23028 Total loss: 3.6537 timestamp: 1655009134.2010572 iteration: 875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35664 FastRCNN class loss: 0.18231 FastRCNN total loss: 0.53895 L1 loss: 0.0000e+00 L2 loss: 2.21041 Learning rate: 0.01749 Mask loss: 0.48345 RPN box loss: 0.06716 RPN score loss: 0.02227 RPN total loss: 0.08943 Total loss: 3.32224 timestamp: 1655009137.6723232 iteration: 880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37385 FastRCNN class loss: 0.13901 FastRCNN total loss: 0.51286 L1 loss: 0.0000e+00 L2 loss: 2.21002 Learning rate: 0.01759 Mask loss: 0.57406 RPN box loss: 0.10726 RPN score loss: 0.05825 RPN total loss: 0.16551 Total loss: 3.46246 timestamp: 1655009141.1217747 iteration: 885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38096 FastRCNN class loss: 0.15941 FastRCNN total loss: 0.54037 L1 loss: 0.0000e+00 L2 loss: 2.20964 Learning rate: 0.01769 Mask loss: 0.47445 RPN box loss: 0.06269 RPN score loss: 0.02404 RPN total loss: 0.08674 Total loss: 3.3112 timestamp: 1655009144.4337957 iteration: 890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47493 FastRCNN class loss: 0.15566 FastRCNN total loss: 0.63059 L1 loss: 0.0000e+00 L2 loss: 2.20925 Learning rate: 0.01779 Mask loss: 0.59605 RPN box loss: 0.08207 RPN score loss: 0.03583 RPN total loss: 0.1179 Total loss: 3.55378 timestamp: 1655009147.7431448 iteration: 895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38459 FastRCNN class loss: 0.14655 FastRCNN total loss: 0.53113 L1 loss: 0.0000e+00 L2 loss: 2.20886 Learning rate: 0.01789 Mask loss: 0.52143 RPN box loss: 0.04751 RPN score loss: 0.0175 RPN total loss: 0.06501 Total loss: 3.32644 timestamp: 1655009151.0205128 iteration: 900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38116 FastRCNN class loss: 0.1406 FastRCNN total loss: 0.52176 L1 loss: 0.0000e+00 L2 loss: 2.20846 Learning rate: 0.01799 Mask loss: 0.53249 RPN box loss: 0.04069 RPN score loss: 0.04368 RPN total loss: 0.08437 Total loss: 3.34709 timestamp: 1655009154.5393226 iteration: 905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36842 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.4682 L1 loss: 0.0000e+00 L2 loss: 2.20807 Learning rate: 0.01809 Mask loss: 0.4857 RPN box loss: 0.02556 RPN score loss: 0.01395 RPN total loss: 0.03951 Total loss: 3.20147 timestamp: 1655009158.0302658 iteration: 910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50852 FastRCNN class loss: 0.17306 FastRCNN total loss: 0.68158 L1 loss: 0.0000e+00 L2 loss: 2.20767 Learning rate: 0.01819 Mask loss: 0.60967 RPN box loss: 0.09363 RPN score loss: 0.06267 RPN total loss: 0.15629 Total loss: 3.65521 timestamp: 1655009161.5449758 iteration: 915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46818 FastRCNN class loss: 0.15709 FastRCNN total loss: 0.62527 L1 loss: 0.0000e+00 L2 loss: 2.20727 Learning rate: 0.01829 Mask loss: 0.45592 RPN box loss: 0.09665 RPN score loss: 0.03715 RPN total loss: 0.13379 Total loss: 3.42224 timestamp: 1655009164.8667295 iteration: 920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47992 FastRCNN class loss: 0.17636 FastRCNN total loss: 0.65627 L1 loss: 0.0000e+00 L2 loss: 2.20687 Learning rate: 0.01839 Mask loss: 0.58934 RPN box loss: 0.05446 RPN score loss: 0.02151 RPN total loss: 0.07597 Total loss: 3.52845 timestamp: 1655009168.2314513 iteration: 925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46232 FastRCNN class loss: 0.11155 FastRCNN total loss: 0.57387 L1 loss: 0.0000e+00 L2 loss: 2.20647 Learning rate: 0.01849 Mask loss: 0.55553 RPN box loss: 0.0295 RPN score loss: 0.01615 RPN total loss: 0.04565 Total loss: 3.38152 timestamp: 1655009171.6583247 iteration: 930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46022 FastRCNN class loss: 0.11841 FastRCNN total loss: 0.57863 L1 loss: 0.0000e+00 L2 loss: 2.20606 Learning rate: 0.01859 Mask loss: 0.50575 RPN box loss: 0.07146 RPN score loss: 0.03372 RPN total loss: 0.10518 Total loss: 3.39562 timestamp: 1655009175.004143 iteration: 935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44651 FastRCNN class loss: 0.15067 FastRCNN total loss: 0.59717 L1 loss: 0.0000e+00 L2 loss: 2.20565 Learning rate: 0.01869 Mask loss: 0.54508 RPN box loss: 0.04002 RPN score loss: 0.01902 RPN total loss: 0.05904 Total loss: 3.40694 timestamp: 1655009178.3151662 iteration: 940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52911 FastRCNN class loss: 0.17489 FastRCNN total loss: 0.70401 L1 loss: 0.0000e+00 L2 loss: 2.20523 Learning rate: 0.01879 Mask loss: 0.55118 RPN box loss: 0.03531 RPN score loss: 0.01872 RPN total loss: 0.05403 Total loss: 3.51445 timestamp: 1655009181.7083092 iteration: 945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49641 FastRCNN class loss: 0.09877 FastRCNN total loss: 0.59518 L1 loss: 0.0000e+00 L2 loss: 2.20482 Learning rate: 0.01889 Mask loss: 0.6357 RPN box loss: 0.02561 RPN score loss: 0.01994 RPN total loss: 0.04554 Total loss: 3.48124 timestamp: 1655009185.1421776 iteration: 950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41144 FastRCNN class loss: 0.20342 FastRCNN total loss: 0.61486 L1 loss: 0.0000e+00 L2 loss: 2.20441 Learning rate: 0.01899 Mask loss: 0.56822 RPN box loss: 0.07209 RPN score loss: 0.0551 RPN total loss: 0.1272 Total loss: 3.51469 timestamp: 1655009188.5762453 iteration: 955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45205 FastRCNN class loss: 0.12463 FastRCNN total loss: 0.57667 L1 loss: 0.0000e+00 L2 loss: 2.20398 Learning rate: 0.01908 Mask loss: 0.51884 RPN box loss: 0.05285 RPN score loss: 0.02617 RPN total loss: 0.07902 Total loss: 3.37851 timestamp: 1655009191.8982399 iteration: 960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44126 FastRCNN class loss: 0.1701 FastRCNN total loss: 0.61136 L1 loss: 0.0000e+00 L2 loss: 2.20356 Learning rate: 0.01918 Mask loss: 0.58186 RPN box loss: 0.04345 RPN score loss: 0.01596 RPN total loss: 0.0594 Total loss: 3.45618 timestamp: 1655009195.2677302 iteration: 965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57203 FastRCNN class loss: 0.16002 FastRCNN total loss: 0.73205 L1 loss: 0.0000e+00 L2 loss: 2.20314 Learning rate: 0.01928 Mask loss: 0.5788 RPN box loss: 0.11148 RPN score loss: 0.02162 RPN total loss: 0.1331 Total loss: 3.64709 timestamp: 1655009198.6267838 iteration: 970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44476 FastRCNN class loss: 0.1697 FastRCNN total loss: 0.61447 L1 loss: 0.0000e+00 L2 loss: 2.20271 Learning rate: 0.01938 Mask loss: 0.54551 RPN box loss: 0.08566 RPN score loss: 0.0326 RPN total loss: 0.11826 Total loss: 3.48094 timestamp: 1655009201.9325259 iteration: 975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44658 FastRCNN class loss: 0.14085 FastRCNN total loss: 0.58744 L1 loss: 0.0000e+00 L2 loss: 2.20227 Learning rate: 0.01948 Mask loss: 0.56222 RPN box loss: 0.07191 RPN score loss: 0.01533 RPN total loss: 0.08724 Total loss: 3.43917 timestamp: 1655009205.2385037 iteration: 980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48718 FastRCNN class loss: 0.14827 FastRCNN total loss: 0.63545 L1 loss: 0.0000e+00 L2 loss: 2.20185 Learning rate: 0.01958 Mask loss: 0.51676 RPN box loss: 0.09722 RPN score loss: 0.02341 RPN total loss: 0.12064 Total loss: 3.47469 timestamp: 1655009208.4830098 iteration: 985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44764 FastRCNN class loss: 0.12094 FastRCNN total loss: 0.56858 L1 loss: 0.0000e+00 L2 loss: 2.20143 Learning rate: 0.01968 Mask loss: 0.60726 RPN box loss: 0.01132 RPN score loss: 0.01245 RPN total loss: 0.02378 Total loss: 3.40104 timestamp: 1655009211.7618742 iteration: 990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39173 FastRCNN class loss: 0.13425 FastRCNN total loss: 0.52599 L1 loss: 0.0000e+00 L2 loss: 2.20101 Learning rate: 0.01978 Mask loss: 0.52013 RPN box loss: 0.12687 RPN score loss: 0.01916 RPN total loss: 0.14602 Total loss: 3.39314 timestamp: 1655009215.0880013 iteration: 995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36429 FastRCNN class loss: 0.15875 FastRCNN total loss: 0.52303 L1 loss: 0.0000e+00 L2 loss: 2.20058 Learning rate: 0.01988 Mask loss: 0.54429 RPN box loss: 0.07617 RPN score loss: 0.03303 RPN total loss: 0.1092 Total loss: 3.3771 timestamp: 1655009218.4109366 iteration: 1000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29383 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.38528 L1 loss: 0.0000e+00 L2 loss: 2.20014 Learning rate: 0.01998 Mask loss: 0.5667 RPN box loss: 0.06073 RPN score loss: 0.01938 RPN total loss: 0.08011 Total loss: 3.23223 timestamp: 1655009221.7388237 iteration: 1005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35904 FastRCNN class loss: 0.09069 FastRCNN total loss: 0.44974 L1 loss: 0.0000e+00 L2 loss: 2.1997 Learning rate: 0.02 Mask loss: 0.53805 RPN box loss: 0.11799 RPN score loss: 0.02197 RPN total loss: 0.13996 Total loss: 3.32745 timestamp: 1655009225.1802692 iteration: 1010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49416 FastRCNN class loss: 0.11656 FastRCNN total loss: 0.61072 L1 loss: 0.0000e+00 L2 loss: 2.19927 Learning rate: 0.02 Mask loss: 0.59047 RPN box loss: 0.09084 RPN score loss: 0.02169 RPN total loss: 0.11253 Total loss: 3.51299 timestamp: 1655009228.5769925 iteration: 1015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31804 FastRCNN class loss: 0.09058 FastRCNN total loss: 0.40863 L1 loss: 0.0000e+00 L2 loss: 2.19881 Learning rate: 0.02 Mask loss: 0.54698 RPN box loss: 0.0254 RPN score loss: 0.01318 RPN total loss: 0.03858 Total loss: 3.193 timestamp: 1655009231.9638867 iteration: 1020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44636 FastRCNN class loss: 0.19835 FastRCNN total loss: 0.64471 L1 loss: 0.0000e+00 L2 loss: 2.19838 Learning rate: 0.02 Mask loss: 0.57876 RPN box loss: 0.06893 RPN score loss: 0.06262 RPN total loss: 0.13155 Total loss: 3.5534 timestamp: 1655009235.3391376 iteration: 1025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40352 FastRCNN class loss: 0.17355 FastRCNN total loss: 0.57707 L1 loss: 0.0000e+00 L2 loss: 2.19793 Learning rate: 0.02 Mask loss: 0.47026 RPN box loss: 0.05872 RPN score loss: 0.01567 RPN total loss: 0.07439 Total loss: 3.31965 timestamp: 1655009238.648604 iteration: 1030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41274 FastRCNN class loss: 0.17885 FastRCNN total loss: 0.59159 L1 loss: 0.0000e+00 L2 loss: 2.19749 Learning rate: 0.02 Mask loss: 0.59405 RPN box loss: 0.22353 RPN score loss: 0.04235 RPN total loss: 0.26589 Total loss: 3.64902 timestamp: 1655009241.9308019 iteration: 1035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39844 FastRCNN class loss: 0.12792 FastRCNN total loss: 0.52636 L1 loss: 0.0000e+00 L2 loss: 2.19704 Learning rate: 0.02 Mask loss: 0.54874 RPN box loss: 0.06902 RPN score loss: 0.04919 RPN total loss: 0.11821 Total loss: 3.39035 timestamp: 1655009245.2925477 iteration: 1040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4074 FastRCNN class loss: 0.1385 FastRCNN total loss: 0.5459 L1 loss: 0.0000e+00 L2 loss: 2.19661 Learning rate: 0.02 Mask loss: 0.69097 RPN box loss: 0.06906 RPN score loss: 0.0244 RPN total loss: 0.09345 Total loss: 3.52694 timestamp: 1655009248.686108 iteration: 1045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33701 FastRCNN class loss: 0.10787 FastRCNN total loss: 0.44488 L1 loss: 0.0000e+00 L2 loss: 2.19617 Learning rate: 0.02 Mask loss: 0.54073 RPN box loss: 0.05306 RPN score loss: 0.02889 RPN total loss: 0.08195 Total loss: 3.26373 timestamp: 1655009251.9639204 iteration: 1050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41385 FastRCNN class loss: 0.12865 FastRCNN total loss: 0.54251 L1 loss: 0.0000e+00 L2 loss: 2.19574 Learning rate: 0.02 Mask loss: 0.56173 RPN box loss: 0.12212 RPN score loss: 0.02705 RPN total loss: 0.14917 Total loss: 3.44915 timestamp: 1655009255.2538455 iteration: 1055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45713 FastRCNN class loss: 0.11653 FastRCNN total loss: 0.57366 L1 loss: 0.0000e+00 L2 loss: 2.1953 Learning rate: 0.02 Mask loss: 0.56432 RPN box loss: 0.02642 RPN score loss: 0.02264 RPN total loss: 0.04907 Total loss: 3.38235 timestamp: 1655009258.6497552 iteration: 1060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42909 FastRCNN class loss: 0.14223 FastRCNN total loss: 0.57132 L1 loss: 0.0000e+00 L2 loss: 2.19487 Learning rate: 0.02 Mask loss: 0.47818 RPN box loss: 0.07228 RPN score loss: 0.01808 RPN total loss: 0.09036 Total loss: 3.33473 timestamp: 1655009261.95019 iteration: 1065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43509 FastRCNN class loss: 0.14017 FastRCNN total loss: 0.57526 L1 loss: 0.0000e+00 L2 loss: 2.19443 Learning rate: 0.02 Mask loss: 0.53654 RPN box loss: 0.09734 RPN score loss: 0.01844 RPN total loss: 0.11578 Total loss: 3.42201 timestamp: 1655009265.2568743 iteration: 1070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39168 FastRCNN class loss: 0.13659 FastRCNN total loss: 0.52827 L1 loss: 0.0000e+00 L2 loss: 2.19399 Learning rate: 0.02 Mask loss: 0.58885 RPN box loss: 0.07312 RPN score loss: 0.03278 RPN total loss: 0.10589 Total loss: 3.41701 timestamp: 1655009268.5964916 iteration: 1075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42975 FastRCNN class loss: 0.11465 FastRCNN total loss: 0.5444 L1 loss: 0.0000e+00 L2 loss: 2.19354 Learning rate: 0.02 Mask loss: 0.56057 RPN box loss: 0.04289 RPN score loss: 0.01793 RPN total loss: 0.06082 Total loss: 3.35933 timestamp: 1655009272.0616107 iteration: 1080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35586 FastRCNN class loss: 0.10427 FastRCNN total loss: 0.46013 L1 loss: 0.0000e+00 L2 loss: 2.1931 Learning rate: 0.02 Mask loss: 0.47365 RPN box loss: 0.04516 RPN score loss: 0.01698 RPN total loss: 0.06214 Total loss: 3.18902 timestamp: 1655009275.4826138 iteration: 1085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57343 FastRCNN class loss: 0.23418 FastRCNN total loss: 0.8076 L1 loss: 0.0000e+00 L2 loss: 2.19268 Learning rate: 0.02 Mask loss: 0.61258 RPN box loss: 0.01933 RPN score loss: 0.01375 RPN total loss: 0.03308 Total loss: 3.64595 timestamp: 1655009278.892664 iteration: 1090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38157 FastRCNN class loss: 0.10939 FastRCNN total loss: 0.49096 L1 loss: 0.0000e+00 L2 loss: 2.19223 Learning rate: 0.02 Mask loss: 0.57804 RPN box loss: 0.0719 RPN score loss: 0.01503 RPN total loss: 0.08693 Total loss: 3.34816 timestamp: 1655009282.3390265 iteration: 1095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38688 FastRCNN class loss: 0.1176 FastRCNN total loss: 0.50449 L1 loss: 0.0000e+00 L2 loss: 2.1918 Learning rate: 0.02 Mask loss: 0.62118 RPN box loss: 0.13646 RPN score loss: 0.04568 RPN total loss: 0.18214 Total loss: 3.49961 timestamp: 1655009285.6968296 iteration: 1100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27507 FastRCNN class loss: 0.11258 FastRCNN total loss: 0.38766 L1 loss: 0.0000e+00 L2 loss: 2.19135 Learning rate: 0.02 Mask loss: 0.61241 RPN box loss: 0.22551 RPN score loss: 0.01707 RPN total loss: 0.24259 Total loss: 3.434 timestamp: 1655009289.0862193 iteration: 1105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42538 FastRCNN class loss: 0.10743 FastRCNN total loss: 0.53281 L1 loss: 0.0000e+00 L2 loss: 2.19093 Learning rate: 0.02 Mask loss: 0.62735 RPN box loss: 0.07196 RPN score loss: 0.02096 RPN total loss: 0.09292 Total loss: 3.44401 timestamp: 1655009292.5378604 iteration: 1110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35609 FastRCNN class loss: 0.11358 FastRCNN total loss: 0.46967 L1 loss: 0.0000e+00 L2 loss: 2.1905 Learning rate: 0.02 Mask loss: 0.4666 RPN box loss: 0.05456 RPN score loss: 0.04257 RPN total loss: 0.09712 Total loss: 3.2239 timestamp: 1655009295.9658732 iteration: 1115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46496 FastRCNN class loss: 0.1778 FastRCNN total loss: 0.64276 L1 loss: 0.0000e+00 L2 loss: 2.19006 Learning rate: 0.02 Mask loss: 0.63678 RPN box loss: 0.08757 RPN score loss: 0.02404 RPN total loss: 0.1116 Total loss: 3.5812 timestamp: 1655009299.3265123 iteration: 1120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34756 FastRCNN class loss: 0.15805 FastRCNN total loss: 0.50561 L1 loss: 0.0000e+00 L2 loss: 2.18962 Learning rate: 0.02 Mask loss: 0.51406 RPN box loss: 0.10341 RPN score loss: 0.01604 RPN total loss: 0.11945 Total loss: 3.32874 timestamp: 1655009302.5840695 iteration: 1125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31528 FastRCNN class loss: 0.07852 FastRCNN total loss: 0.3938 L1 loss: 0.0000e+00 L2 loss: 2.1892 Learning rate: 0.02 Mask loss: 0.51308 RPN box loss: 0.13337 RPN score loss: 0.02943 RPN total loss: 0.16279 Total loss: 3.25887 timestamp: 1655009305.902145 iteration: 1130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44482 FastRCNN class loss: 0.1304 FastRCNN total loss: 0.57522 L1 loss: 0.0000e+00 L2 loss: 2.18876 Learning rate: 0.02 Mask loss: 0.57401 RPN box loss: 0.02366 RPN score loss: 0.01432 RPN total loss: 0.03798 Total loss: 3.37596 timestamp: 1655009309.2305202 iteration: 1135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49098 FastRCNN class loss: 0.14128 FastRCNN total loss: 0.63226 L1 loss: 0.0000e+00 L2 loss: 2.18832 Learning rate: 0.02 Mask loss: 0.58968 RPN box loss: 0.0159 RPN score loss: 0.01675 RPN total loss: 0.03265 Total loss: 3.44291 timestamp: 1655009312.6486778 iteration: 1140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49026 FastRCNN class loss: 0.12671 FastRCNN total loss: 0.61697 L1 loss: 0.0000e+00 L2 loss: 2.18787 Learning rate: 0.02 Mask loss: 0.56707 RPN box loss: 0.01296 RPN score loss: 0.01493 RPN total loss: 0.02789 Total loss: 3.3998 timestamp: 1655009316.0576894 iteration: 1145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38626 FastRCNN class loss: 0.1627 FastRCNN total loss: 0.54897 L1 loss: 0.0000e+00 L2 loss: 2.18744 Learning rate: 0.02 Mask loss: 0.47355 RPN box loss: 0.09128 RPN score loss: 0.02845 RPN total loss: 0.11973 Total loss: 3.32968 timestamp: 1655009319.4005015 iteration: 1150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49307 FastRCNN class loss: 0.15349 FastRCNN total loss: 0.64656 L1 loss: 0.0000e+00 L2 loss: 2.18701 Learning rate: 0.02 Mask loss: 0.50918 RPN box loss: 0.0881 RPN score loss: 0.02438 RPN total loss: 0.11248 Total loss: 3.45524 timestamp: 1655009322.9023073 iteration: 1155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47432 FastRCNN class loss: 0.12356 FastRCNN total loss: 0.59788 L1 loss: 0.0000e+00 L2 loss: 2.18659 Learning rate: 0.02 Mask loss: 0.50247 RPN box loss: 0.05901 RPN score loss: 0.01614 RPN total loss: 0.07514 Total loss: 3.36207 timestamp: 1655009326.370997 iteration: 1160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42759 FastRCNN class loss: 0.1401 FastRCNN total loss: 0.56769 L1 loss: 0.0000e+00 L2 loss: 2.18615 Learning rate: 0.02 Mask loss: 0.49899 RPN box loss: 0.0394 RPN score loss: 0.0112 RPN total loss: 0.05061 Total loss: 3.30344 timestamp: 1655009329.9163706 iteration: 1165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56798 FastRCNN class loss: 0.19218 FastRCNN total loss: 0.76016 L1 loss: 0.0000e+00 L2 loss: 2.18572 Learning rate: 0.02 Mask loss: 0.64717 RPN box loss: 0.03423 RPN score loss: 0.01895 RPN total loss: 0.05318 Total loss: 3.64623 timestamp: 1655009333.318976 iteration: 1170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4895 FastRCNN class loss: 0.14135 FastRCNN total loss: 0.63085 L1 loss: 0.0000e+00 L2 loss: 2.18529 Learning rate: 0.02 Mask loss: 0.55436 RPN box loss: 0.05469 RPN score loss: 0.01784 RPN total loss: 0.07253 Total loss: 3.44303 timestamp: 1655009336.7349892 iteration: 1175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40659 FastRCNN class loss: 0.11826 FastRCNN total loss: 0.52486 L1 loss: 0.0000e+00 L2 loss: 2.18484 Learning rate: 0.02 Mask loss: 0.5047 RPN box loss: 0.06227 RPN score loss: 0.04083 RPN total loss: 0.10311 Total loss: 3.3175 timestamp: 1655009340.138463 iteration: 1180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31178 FastRCNN class loss: 0.09567 FastRCNN total loss: 0.40745 L1 loss: 0.0000e+00 L2 loss: 2.1844 Learning rate: 0.02 Mask loss: 0.55207 RPN box loss: 0.14261 RPN score loss: 0.02396 RPN total loss: 0.16656 Total loss: 3.31048 timestamp: 1655009343.528102 iteration: 1185 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33689 FastRCNN class loss: 0.13129 FastRCNN total loss: 0.46818 L1 loss: 0.0000e+00 L2 loss: 2.18398 Learning rate: 0.02 Mask loss: 0.54935 RPN box loss: 0.04338 RPN score loss: 0.01484 RPN total loss: 0.05822 Total loss: 3.25973 timestamp: 1655009346.8743987 iteration: 1190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52939 FastRCNN class loss: 0.17628 FastRCNN total loss: 0.70567 L1 loss: 0.0000e+00 L2 loss: 2.18354 Learning rate: 0.02 Mask loss: 0.65534 RPN box loss: 0.07714 RPN score loss: 0.02682 RPN total loss: 0.10396 Total loss: 3.64851 timestamp: 1655009350.1744251 iteration: 1195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36437 FastRCNN class loss: 0.0985 FastRCNN total loss: 0.46287 L1 loss: 0.0000e+00 L2 loss: 2.18311 Learning rate: 0.02 Mask loss: 0.56491 RPN box loss: 0.18043 RPN score loss: 0.0201 RPN total loss: 0.20054 Total loss: 3.41142 timestamp: 1655009353.520112 iteration: 1200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40782 FastRCNN class loss: 0.12949 FastRCNN total loss: 0.53731 L1 loss: 0.0000e+00 L2 loss: 2.18268 Learning rate: 0.02 Mask loss: 0.5384 RPN box loss: 0.01889 RPN score loss: 0.01313 RPN total loss: 0.03202 Total loss: 3.2904 timestamp: 1655009356.8535533 iteration: 1205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48234 FastRCNN class loss: 0.25935 FastRCNN total loss: 0.74169 L1 loss: 0.0000e+00 L2 loss: 2.18224 Learning rate: 0.02 Mask loss: 0.60399 RPN box loss: 0.16367 RPN score loss: 0.02471 RPN total loss: 0.18838 Total loss: 3.7163 timestamp: 1655009360.1435795 iteration: 1210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38085 FastRCNN class loss: 0.08738 FastRCNN total loss: 0.46823 L1 loss: 0.0000e+00 L2 loss: 2.18181 Learning rate: 0.02 Mask loss: 0.58728 RPN box loss: 0.10783 RPN score loss: 0.0138 RPN total loss: 0.12163 Total loss: 3.35895 timestamp: 1655009363.4931884 iteration: 1215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37935 FastRCNN class loss: 0.14493 FastRCNN total loss: 0.52428 L1 loss: 0.0000e+00 L2 loss: 2.18137 Learning rate: 0.02 Mask loss: 0.55143 RPN box loss: 0.1246 RPN score loss: 0.02 RPN total loss: 0.1446 Total loss: 3.40168 timestamp: 1655009366.8576496 iteration: 1220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38228 FastRCNN class loss: 0.10331 FastRCNN total loss: 0.48559 L1 loss: 0.0000e+00 L2 loss: 2.18094 Learning rate: 0.02 Mask loss: 0.49876 RPN box loss: 0.06367 RPN score loss: 0.03406 RPN total loss: 0.09773 Total loss: 3.26302 timestamp: 1655009370.3024628 iteration: 1225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31766 FastRCNN class loss: 0.08741 FastRCNN total loss: 0.40507 L1 loss: 0.0000e+00 L2 loss: 2.18051 Learning rate: 0.02 Mask loss: 0.50525 RPN box loss: 0.04855 RPN score loss: 0.01703 RPN total loss: 0.06558 Total loss: 3.15641 timestamp: 1655009373.788902 iteration: 1230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44107 FastRCNN class loss: 0.1347 FastRCNN total loss: 0.57577 L1 loss: 0.0000e+00 L2 loss: 2.18009 Learning rate: 0.02 Mask loss: 0.58367 RPN box loss: 0.05779 RPN score loss: 0.06053 RPN total loss: 0.11831 Total loss: 3.45784 timestamp: 1655009377.1972501 iteration: 1235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5025 FastRCNN class loss: 0.16053 FastRCNN total loss: 0.66303 L1 loss: 0.0000e+00 L2 loss: 2.17964 Learning rate: 0.02 Mask loss: 0.59004 RPN box loss: 0.07195 RPN score loss: 0.02561 RPN total loss: 0.09755 Total loss: 3.53026 timestamp: 1655009380.5509572 iteration: 1240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52263 FastRCNN class loss: 0.25736 FastRCNN total loss: 0.77998 L1 loss: 0.0000e+00 L2 loss: 2.17922 Learning rate: 0.02 Mask loss: 0.64112 RPN box loss: 0.07802 RPN score loss: 0.04354 RPN total loss: 0.12156 Total loss: 3.72188 timestamp: 1655009383.9818163 iteration: 1245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35906 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.4507 L1 loss: 0.0000e+00 L2 loss: 2.17878 Learning rate: 0.02 Mask loss: 0.60405 RPN box loss: 0.10704 RPN score loss: 0.02776 RPN total loss: 0.1348 Total loss: 3.36832 timestamp: 1655009387.3144379 iteration: 1250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31062 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.37703 L1 loss: 0.0000e+00 L2 loss: 2.17835 Learning rate: 0.02 Mask loss: 0.55225 RPN box loss: 0.10015 RPN score loss: 0.01122 RPN total loss: 0.11136 Total loss: 3.21899 timestamp: 1655009390.6263049 iteration: 1255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37914 FastRCNN class loss: 0.10074 FastRCNN total loss: 0.47988 L1 loss: 0.0000e+00 L2 loss: 2.17791 Learning rate: 0.02 Mask loss: 0.56071 RPN box loss: 0.08206 RPN score loss: 0.03094 RPN total loss: 0.113 Total loss: 3.33149 timestamp: 1655009394.0033114 iteration: 1260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52986 FastRCNN class loss: 0.17093 FastRCNN total loss: 0.70079 L1 loss: 0.0000e+00 L2 loss: 2.17748 Learning rate: 0.02 Mask loss: 0.64812 RPN box loss: 0.04832 RPN score loss: 0.01795 RPN total loss: 0.06627 Total loss: 3.59265 timestamp: 1655009397.419988 iteration: 1265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37718 FastRCNN class loss: 0.16568 FastRCNN total loss: 0.54287 L1 loss: 0.0000e+00 L2 loss: 2.17704 Learning rate: 0.02 Mask loss: 0.53685 RPN box loss: 0.10568 RPN score loss: 0.03303 RPN total loss: 0.13871 Total loss: 3.39546 timestamp: 1655009400.8040879 iteration: 1270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42816 FastRCNN class loss: 0.11932 FastRCNN total loss: 0.54749 L1 loss: 0.0000e+00 L2 loss: 2.17662 Learning rate: 0.02 Mask loss: 0.59269 RPN box loss: 0.0302 RPN score loss: 0.0096 RPN total loss: 0.03981 Total loss: 3.35661 timestamp: 1655009404.1705961 iteration: 1275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34395 FastRCNN class loss: 0.11399 FastRCNN total loss: 0.45794 L1 loss: 0.0000e+00 L2 loss: 2.17619 Learning rate: 0.02 Mask loss: 0.50928 RPN box loss: 0.071 RPN score loss: 0.02171 RPN total loss: 0.09271 Total loss: 3.23612 timestamp: 1655009407.653443 iteration: 1280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43999 FastRCNN class loss: 0.1625 FastRCNN total loss: 0.60249 L1 loss: 0.0000e+00 L2 loss: 2.17576 Learning rate: 0.02 Mask loss: 0.5137 RPN box loss: 0.07737 RPN score loss: 0.01191 RPN total loss: 0.08928 Total loss: 3.38123 timestamp: 1655009411.1493652 iteration: 1285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52733 FastRCNN class loss: 0.14089 FastRCNN total loss: 0.66822 L1 loss: 0.0000e+00 L2 loss: 2.17534 Learning rate: 0.02 Mask loss: 0.51058 RPN box loss: 0.0247 RPN score loss: 0.01452 RPN total loss: 0.03921 Total loss: 3.39336 timestamp: 1655009414.5637105 iteration: 1290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48959 FastRCNN class loss: 0.10267 FastRCNN total loss: 0.59226 L1 loss: 0.0000e+00 L2 loss: 2.17492 Learning rate: 0.02 Mask loss: 0.58096 RPN box loss: 0.02687 RPN score loss: 0.01725 RPN total loss: 0.04412 Total loss: 3.39226 timestamp: 1655009417.955658 iteration: 1295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.58925 FastRCNN class loss: 0.14323 FastRCNN total loss: 0.73248 L1 loss: 0.0000e+00 L2 loss: 2.1745 Learning rate: 0.02 Mask loss: 0.67913 RPN box loss: 0.06019 RPN score loss: 0.02609 RPN total loss: 0.08628 Total loss: 3.67239 timestamp: 1655009421.3420942 iteration: 1300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4208 FastRCNN class loss: 0.14724 FastRCNN total loss: 0.56803 L1 loss: 0.0000e+00 L2 loss: 2.17406 Learning rate: 0.02 Mask loss: 0.56003 RPN box loss: 0.03449 RPN score loss: 0.0193 RPN total loss: 0.05379 Total loss: 3.35591 timestamp: 1655009424.7032683 iteration: 1305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38583 FastRCNN class loss: 0.08828 FastRCNN total loss: 0.47411 L1 loss: 0.0000e+00 L2 loss: 2.17362 Learning rate: 0.02 Mask loss: 0.54613 RPN box loss: 0.05489 RPN score loss: 0.0168 RPN total loss: 0.07169 Total loss: 3.26555 timestamp: 1655009428.0779307 iteration: 1310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40774 FastRCNN class loss: 0.12409 FastRCNN total loss: 0.53184 L1 loss: 0.0000e+00 L2 loss: 2.17318 Learning rate: 0.02 Mask loss: 0.51534 RPN box loss: 0.05976 RPN score loss: 0.02114 RPN total loss: 0.0809 Total loss: 3.30126 timestamp: 1655009431.4258435 iteration: 1315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4283 FastRCNN class loss: 0.09974 FastRCNN total loss: 0.52804 L1 loss: 0.0000e+00 L2 loss: 2.17277 Learning rate: 0.02 Mask loss: 0.57277 RPN box loss: 0.09353 RPN score loss: 0.03221 RPN total loss: 0.12574 Total loss: 3.39933 timestamp: 1655009434.749926 iteration: 1320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42637 FastRCNN class loss: 0.13459 FastRCNN total loss: 0.56096 L1 loss: 0.0000e+00 L2 loss: 2.17236 Learning rate: 0.02 Mask loss: 0.5469 RPN box loss: 0.0335 RPN score loss: 0.00752 RPN total loss: 0.04102 Total loss: 3.32123 timestamp: 1655009438.100609 iteration: 1325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42692 FastRCNN class loss: 0.11107 FastRCNN total loss: 0.53799 L1 loss: 0.0000e+00 L2 loss: 2.17194 Learning rate: 0.02 Mask loss: 0.60265 RPN box loss: 0.11325 RPN score loss: 0.02852 RPN total loss: 0.14176 Total loss: 3.45435 timestamp: 1655009441.6200783 iteration: 1330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49257 FastRCNN class loss: 0.19874 FastRCNN total loss: 0.69131 L1 loss: 0.0000e+00 L2 loss: 2.1715 Learning rate: 0.02 Mask loss: 0.48426 RPN box loss: 0.04982 RPN score loss: 0.03039 RPN total loss: 0.08021 Total loss: 3.42728 timestamp: 1655009445.0356486 iteration: 1335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40002 FastRCNN class loss: 0.12491 FastRCNN total loss: 0.52493 L1 loss: 0.0000e+00 L2 loss: 2.17106 Learning rate: 0.02 Mask loss: 0.5529 RPN box loss: 0.03609 RPN score loss: 0.00908 RPN total loss: 0.04517 Total loss: 3.29406 timestamp: 1655009448.3896234 iteration: 1340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40829 FastRCNN class loss: 0.14981 FastRCNN total loss: 0.5581 L1 loss: 0.0000e+00 L2 loss: 2.17063 Learning rate: 0.02 Mask loss: 0.52331 RPN box loss: 0.04744 RPN score loss: 0.01917 RPN total loss: 0.06661 Total loss: 3.31866 timestamp: 1655009451.6817408 iteration: 1345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36985 FastRCNN class loss: 0.12269 FastRCNN total loss: 0.49254 L1 loss: 0.0000e+00 L2 loss: 2.1702 Learning rate: 0.02 Mask loss: 0.56892 RPN box loss: 0.09433 RPN score loss: 0.03578 RPN total loss: 0.1301 Total loss: 3.36177 timestamp: 1655009455.015339 iteration: 1350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39865 FastRCNN class loss: 0.11878 FastRCNN total loss: 0.51743 L1 loss: 0.0000e+00 L2 loss: 2.16977 Learning rate: 0.02 Mask loss: 0.54992 RPN box loss: 0.0845 RPN score loss: 0.027 RPN total loss: 0.1115 Total loss: 3.34862 timestamp: 1655009458.3472328 iteration: 1355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27967 FastRCNN class loss: 0.09489 FastRCNN total loss: 0.37456 L1 loss: 0.0000e+00 L2 loss: 2.16934 Learning rate: 0.02 Mask loss: 0.47396 RPN box loss: 0.05374 RPN score loss: 0.0248 RPN total loss: 0.07855 Total loss: 3.0964 timestamp: 1655009461.686717 iteration: 1360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4253 FastRCNN class loss: 0.13092 FastRCNN total loss: 0.55622 L1 loss: 0.0000e+00 L2 loss: 2.16889 Learning rate: 0.02 Mask loss: 0.56107 RPN box loss: 0.04687 RPN score loss: 0.01943 RPN total loss: 0.0663 Total loss: 3.35249 timestamp: 1655009465.0062215 iteration: 1365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33381 FastRCNN class loss: 0.07846 FastRCNN total loss: 0.41227 L1 loss: 0.0000e+00 L2 loss: 2.16846 Learning rate: 0.02 Mask loss: 0.49369 RPN box loss: 0.01838 RPN score loss: 0.00929 RPN total loss: 0.02766 Total loss: 3.10207 timestamp: 1655009468.4292648 iteration: 1370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48504 FastRCNN class loss: 0.16608 FastRCNN total loss: 0.65112 L1 loss: 0.0000e+00 L2 loss: 2.16803 Learning rate: 0.02 Mask loss: 0.54903 RPN box loss: 0.06367 RPN score loss: 0.0201 RPN total loss: 0.08377 Total loss: 3.45194 timestamp: 1655009471.83365 iteration: 1375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46398 FastRCNN class loss: 0.12312 FastRCNN total loss: 0.5871 L1 loss: 0.0000e+00 L2 loss: 2.16759 Learning rate: 0.02 Mask loss: 0.57055 RPN box loss: 0.0678 RPN score loss: 0.01765 RPN total loss: 0.08544 Total loss: 3.41069 timestamp: 1655009475.2271638 iteration: 1380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35845 FastRCNN class loss: 0.131 FastRCNN total loss: 0.48945 L1 loss: 0.0000e+00 L2 loss: 2.16716 Learning rate: 0.02 Mask loss: 0.54145 RPN box loss: 0.07557 RPN score loss: 0.03292 RPN total loss: 0.10849 Total loss: 3.30654 timestamp: 1655009478.7107286 iteration: 1385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37249 FastRCNN class loss: 0.11374 FastRCNN total loss: 0.48623 L1 loss: 0.0000e+00 L2 loss: 2.16672 Learning rate: 0.02 Mask loss: 0.48921 RPN box loss: 0.04287 RPN score loss: 0.01552 RPN total loss: 0.05839 Total loss: 3.20055 timestamp: 1655009482.0801458 iteration: 1390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43095 FastRCNN class loss: 0.12659 FastRCNN total loss: 0.55754 L1 loss: 0.0000e+00 L2 loss: 2.16629 Learning rate: 0.02 Mask loss: 0.51971 RPN box loss: 0.08333 RPN score loss: 0.01929 RPN total loss: 0.10262 Total loss: 3.34616 timestamp: 1655009485.3380787 iteration: 1395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49285 FastRCNN class loss: 0.19589 FastRCNN total loss: 0.68874 L1 loss: 0.0000e+00 L2 loss: 2.16586 Learning rate: 0.02 Mask loss: 0.52964 RPN box loss: 0.02056 RPN score loss: 0.01214 RPN total loss: 0.0327 Total loss: 3.41693 timestamp: 1655009488.7015564 iteration: 1400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38459 FastRCNN class loss: 0.11647 FastRCNN total loss: 0.50106 L1 loss: 0.0000e+00 L2 loss: 2.16542 Learning rate: 0.02 Mask loss: 0.52431 RPN box loss: 0.14846 RPN score loss: 0.02136 RPN total loss: 0.16982 Total loss: 3.36062 timestamp: 1655009492.0091195 iteration: 1405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36396 FastRCNN class loss: 0.13906 FastRCNN total loss: 0.50301 L1 loss: 0.0000e+00 L2 loss: 2.16499 Learning rate: 0.02 Mask loss: 0.57608 RPN box loss: 0.07952 RPN score loss: 0.04568 RPN total loss: 0.1252 Total loss: 3.36929 timestamp: 1655009495.3613443 iteration: 1410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56225 FastRCNN class loss: 0.18808 FastRCNN total loss: 0.75033 L1 loss: 0.0000e+00 L2 loss: 2.16457 Learning rate: 0.02 Mask loss: 0.54 RPN box loss: 0.02498 RPN score loss: 0.01463 RPN total loss: 0.03961 Total loss: 3.4945 timestamp: 1655009498.7707345 iteration: 1415 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40495 FastRCNN class loss: 0.20953 FastRCNN total loss: 0.61448 L1 loss: 0.0000e+00 L2 loss: 2.16414 Learning rate: 0.02 Mask loss: 0.51975 RPN box loss: 0.11951 RPN score loss: 0.02258 RPN total loss: 0.14208 Total loss: 3.44045 timestamp: 1655009502.1909964 iteration: 1420 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43347 FastRCNN class loss: 0.12216 FastRCNN total loss: 0.55564 L1 loss: 0.0000e+00 L2 loss: 2.16371 Learning rate: 0.02 Mask loss: 0.5612 RPN box loss: 0.0586 RPN score loss: 0.01735 RPN total loss: 0.07595 Total loss: 3.3565 timestamp: 1655009505.552807 iteration: 1425 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33973 FastRCNN class loss: 0.10935 FastRCNN total loss: 0.44908 L1 loss: 0.0000e+00 L2 loss: 2.16327 Learning rate: 0.02 Mask loss: 0.55466 RPN box loss: 0.1025 RPN score loss: 0.05295 RPN total loss: 0.15545 Total loss: 3.32245 timestamp: 1655009508.9379277 iteration: 1430 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52214 FastRCNN class loss: 0.18966 FastRCNN total loss: 0.7118 L1 loss: 0.0000e+00 L2 loss: 2.16284 Learning rate: 0.02 Mask loss: 0.57346 RPN box loss: 0.04173 RPN score loss: 0.02462 RPN total loss: 0.06636 Total loss: 3.51446 timestamp: 1655009512.276128 iteration: 1435 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38198 FastRCNN class loss: 0.14453 FastRCNN total loss: 0.52651 L1 loss: 0.0000e+00 L2 loss: 2.1624 Learning rate: 0.02 Mask loss: 0.50279 RPN box loss: 0.08629 RPN score loss: 0.01479 RPN total loss: 0.10107 Total loss: 3.29277 timestamp: 1655009515.6226554 iteration: 1440 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39898 FastRCNN class loss: 0.1701 FastRCNN total loss: 0.56908 L1 loss: 0.0000e+00 L2 loss: 2.16198 Learning rate: 0.02 Mask loss: 0.61458 RPN box loss: 0.06113 RPN score loss: 0.0259 RPN total loss: 0.08703 Total loss: 3.43267 timestamp: 1655009519.0188756 iteration: 1445 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52956 FastRCNN class loss: 0.20199 FastRCNN total loss: 0.73154 L1 loss: 0.0000e+00 L2 loss: 2.16154 Learning rate: 0.02 Mask loss: 0.56263 RPN box loss: 0.06437 RPN score loss: 0.02408 RPN total loss: 0.08845 Total loss: 3.54416 timestamp: 1655009522.462607 iteration: 1450 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42323 FastRCNN class loss: 0.11314 FastRCNN total loss: 0.53637 L1 loss: 0.0000e+00 L2 loss: 2.16111 Learning rate: 0.02 Mask loss: 0.58361 RPN box loss: 0.08316 RPN score loss: 0.02611 RPN total loss: 0.10927 Total loss: 3.39036 timestamp: 1655009525.9157827 iteration: 1455 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48724 FastRCNN class loss: 0.19869 FastRCNN total loss: 0.68593 L1 loss: 0.0000e+00 L2 loss: 2.16069 Learning rate: 0.02 Mask loss: 0.56635 RPN box loss: 0.05489 RPN score loss: 0.02982 RPN total loss: 0.08471 Total loss: 3.49768 timestamp: 1655009529.3078554 iteration: 1460 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45793 FastRCNN class loss: 0.12163 FastRCNN total loss: 0.57956 L1 loss: 0.0000e+00 L2 loss: 2.16026 Learning rate: 0.02 Mask loss: 0.545 RPN box loss: 0.08555 RPN score loss: 0.02534 RPN total loss: 0.11088 Total loss: 3.3957 timestamp: 1655009532.7287 iteration: 1465 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32356 FastRCNN class loss: 0.14113 FastRCNN total loss: 0.46469 L1 loss: 0.0000e+00 L2 loss: 2.15983 Learning rate: 0.02 Mask loss: 0.48975 RPN box loss: 0.07576 RPN score loss: 0.02581 RPN total loss: 0.10156 Total loss: 3.21583 timestamp: 1655009536.1323354 iteration: 1470 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48391 FastRCNN class loss: 0.22969 FastRCNN total loss: 0.7136 L1 loss: 0.0000e+00 L2 loss: 2.15941 Learning rate: 0.02 Mask loss: 0.52812 RPN box loss: 0.07129 RPN score loss: 0.04133 RPN total loss: 0.11262 Total loss: 3.51374 timestamp: 1655009539.5525088 iteration: 1475 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39657 FastRCNN class loss: 0.13975 FastRCNN total loss: 0.53632 L1 loss: 0.0000e+00 L2 loss: 2.15897 Learning rate: 0.02 Mask loss: 0.58518 RPN box loss: 0.05224 RPN score loss: 0.01397 RPN total loss: 0.06621 Total loss: 3.34668 timestamp: 1655009542.9730327 iteration: 1480 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32455 FastRCNN class loss: 0.13041 FastRCNN total loss: 0.45496 L1 loss: 0.0000e+00 L2 loss: 2.15854 Learning rate: 0.02 Mask loss: 0.49054 RPN box loss: 0.06052 RPN score loss: 0.02407 RPN total loss: 0.0846 Total loss: 3.18864 timestamp: 1655009546.4203885 iteration: 1485 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34465 FastRCNN class loss: 0.13746 FastRCNN total loss: 0.48211 L1 loss: 0.0000e+00 L2 loss: 2.15811 Learning rate: 0.02 Mask loss: 0.51561 RPN box loss: 0.08735 RPN score loss: 0.02512 RPN total loss: 0.11247 Total loss: 3.26831 timestamp: 1655009549.7304773 iteration: 1490 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39118 FastRCNN class loss: 0.13989 FastRCNN total loss: 0.53107 L1 loss: 0.0000e+00 L2 loss: 2.15768 Learning rate: 0.02 Mask loss: 0.56973 RPN box loss: 0.05072 RPN score loss: 0.01581 RPN total loss: 0.06653 Total loss: 3.325 timestamp: 1655009553.2050977 iteration: 1495 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45916 FastRCNN class loss: 0.13005 FastRCNN total loss: 0.58921 L1 loss: 0.0000e+00 L2 loss: 2.15724 Learning rate: 0.02 Mask loss: 0.5608 RPN box loss: 0.07195 RPN score loss: 0.04532 RPN total loss: 0.11727 Total loss: 3.42453 timestamp: 1655009556.6990628 iteration: 1500 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38436 FastRCNN class loss: 0.13227 FastRCNN total loss: 0.51663 L1 loss: 0.0000e+00 L2 loss: 2.1568 Learning rate: 0.02 Mask loss: 0.5096 RPN box loss: 0.09749 RPN score loss: 0.0489 RPN total loss: 0.14639 Total loss: 3.32943 timestamp: 1655009560.106498 iteration: 1505 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4766 FastRCNN class loss: 0.10628 FastRCNN total loss: 0.58288 L1 loss: 0.0000e+00 L2 loss: 2.15638 Learning rate: 0.02 Mask loss: 0.56456 RPN box loss: 0.03109 RPN score loss: 0.01321 RPN total loss: 0.0443 Total loss: 3.34811 timestamp: 1655009563.4335606 iteration: 1510 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36247 FastRCNN class loss: 0.11128 FastRCNN total loss: 0.47374 L1 loss: 0.0000e+00 L2 loss: 2.15596 Learning rate: 0.02 Mask loss: 0.69617 RPN box loss: 0.07984 RPN score loss: 0.03645 RPN total loss: 0.11629 Total loss: 3.44215 timestamp: 1655009566.773108 iteration: 1515 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36274 FastRCNN class loss: 0.1505 FastRCNN total loss: 0.51324 L1 loss: 0.0000e+00 L2 loss: 2.15553 Learning rate: 0.02 Mask loss: 0.51894 RPN box loss: 0.04333 RPN score loss: 0.01521 RPN total loss: 0.05854 Total loss: 3.24626 timestamp: 1655009570.075377 iteration: 1520 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39263 FastRCNN class loss: 0.12664 FastRCNN total loss: 0.51927 L1 loss: 0.0000e+00 L2 loss: 2.15511 Learning rate: 0.02 Mask loss: 0.54392 RPN box loss: 0.06191 RPN score loss: 0.01846 RPN total loss: 0.08037 Total loss: 3.29867 timestamp: 1655009573.4306304 iteration: 1525 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30115 FastRCNN class loss: 0.06079 FastRCNN total loss: 0.36194 L1 loss: 0.0000e+00 L2 loss: 2.15468 Learning rate: 0.02 Mask loss: 0.50771 RPN box loss: 0.04799 RPN score loss: 0.02886 RPN total loss: 0.07685 Total loss: 3.10118 timestamp: 1655009576.83297 iteration: 1530 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33306 FastRCNN class loss: 0.12399 FastRCNN total loss: 0.45705 L1 loss: 0.0000e+00 L2 loss: 2.15427 Learning rate: 0.02 Mask loss: 0.5389 RPN box loss: 0.14155 RPN score loss: 0.02138 RPN total loss: 0.16293 Total loss: 3.31315 timestamp: 1655009580.2080088 iteration: 1535 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46475 FastRCNN class loss: 0.12522 FastRCNN total loss: 0.58997 L1 loss: 0.0000e+00 L2 loss: 2.15385 Learning rate: 0.02 Mask loss: 0.53543 RPN box loss: 0.08122 RPN score loss: 0.02357 RPN total loss: 0.10479 Total loss: 3.38404 timestamp: 1655009583.5481575 iteration: 1540 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45688 FastRCNN class loss: 0.11557 FastRCNN total loss: 0.57246 L1 loss: 0.0000e+00 L2 loss: 2.15342 Learning rate: 0.02 Mask loss: 0.62693 RPN box loss: 0.01777 RPN score loss: 0.01155 RPN total loss: 0.02932 Total loss: 3.38213 timestamp: 1655009586.8052304 iteration: 1545 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51561 FastRCNN class loss: 0.11233 FastRCNN total loss: 0.62794 L1 loss: 0.0000e+00 L2 loss: 2.15299 Learning rate: 0.02 Mask loss: 0.53748 RPN box loss: 0.02853 RPN score loss: 0.01493 RPN total loss: 0.04346 Total loss: 3.36188 timestamp: 1655009590.1136103 iteration: 1550 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25694 FastRCNN class loss: 0.05903 FastRCNN total loss: 0.31597 L1 loss: 0.0000e+00 L2 loss: 2.15258 Learning rate: 0.02 Mask loss: 0.49269 RPN box loss: 0.10687 RPN score loss: 0.01287 RPN total loss: 0.11974 Total loss: 3.08098 timestamp: 1655009593.3795316 iteration: 1555 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3745 FastRCNN class loss: 0.10174 FastRCNN total loss: 0.47624 L1 loss: 0.0000e+00 L2 loss: 2.15216 Learning rate: 0.02 Mask loss: 0.48142 RPN box loss: 0.04344 RPN score loss: 0.01272 RPN total loss: 0.05616 Total loss: 3.16599 timestamp: 1655009596.7013054 iteration: 1560 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35915 FastRCNN class loss: 0.10612 FastRCNN total loss: 0.46527 L1 loss: 0.0000e+00 L2 loss: 2.15174 Learning rate: 0.02 Mask loss: 0.50913 RPN box loss: 0.03904 RPN score loss: 0.01687 RPN total loss: 0.0559 Total loss: 3.18205 timestamp: 1655009599.9868717 iteration: 1565 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41837 FastRCNN class loss: 0.1152 FastRCNN total loss: 0.53356 L1 loss: 0.0000e+00 L2 loss: 2.15133 Learning rate: 0.02 Mask loss: 0.49668 RPN box loss: 0.11851 RPN score loss: 0.02702 RPN total loss: 0.14553 Total loss: 3.3271 timestamp: 1655009603.360179 iteration: 1570 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.53674 FastRCNN class loss: 0.1709 FastRCNN total loss: 0.70764 L1 loss: 0.0000e+00 L2 loss: 2.15089 Learning rate: 0.02 Mask loss: 0.56812 RPN box loss: 0.0884 RPN score loss: 0.03792 RPN total loss: 0.12632 Total loss: 3.55296 timestamp: 1655009606.7678332 iteration: 1575 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3436 FastRCNN class loss: 0.15088 FastRCNN total loss: 0.49449 L1 loss: 0.0000e+00 L2 loss: 2.15047 Learning rate: 0.02 Mask loss: 0.57406 RPN box loss: 0.07487 RPN score loss: 0.05864 RPN total loss: 0.1335 Total loss: 3.35252 timestamp: 1655009610.2186592 iteration: 1580 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48503 FastRCNN class loss: 0.13848 FastRCNN total loss: 0.62351 L1 loss: 0.0000e+00 L2 loss: 2.15006 Learning rate: 0.02 Mask loss: 0.48364 RPN box loss: 0.08839 RPN score loss: 0.0267 RPN total loss: 0.11509 Total loss: 3.3723 timestamp: 1655009613.6375568 iteration: 1585 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40589 FastRCNN class loss: 0.14203 FastRCNN total loss: 0.54792 L1 loss: 0.0000e+00 L2 loss: 2.14965 Learning rate: 0.02 Mask loss: 0.5064 RPN box loss: 0.12181 RPN score loss: 0.01614 RPN total loss: 0.13795 Total loss: 3.34192 timestamp: 1655009617.0541537 iteration: 1590 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41297 FastRCNN class loss: 0.09575 FastRCNN total loss: 0.50872 L1 loss: 0.0000e+00 L2 loss: 2.14927 Learning rate: 0.02 Mask loss: 0.5686 RPN box loss: 0.13377 RPN score loss: 0.09164 RPN total loss: 0.22541 Total loss: 3.452 timestamp: 1655009620.2450466 iteration: 1595 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42452 FastRCNN class loss: 0.19072 FastRCNN total loss: 0.61523 L1 loss: 0.0000e+00 L2 loss: 2.14888 Learning rate: 0.02 Mask loss: 0.62611 RPN box loss: 0.05708 RPN score loss: 0.00865 RPN total loss: 0.06572 Total loss: 3.45595 timestamp: 1655009623.5795531 iteration: 1600 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5207 FastRCNN class loss: 0.202 FastRCNN total loss: 0.72269 L1 loss: 0.0000e+00 L2 loss: 2.14847 Learning rate: 0.02 Mask loss: 0.65014 RPN box loss: 0.07595 RPN score loss: 0.0229 RPN total loss: 0.09885 Total loss: 3.62016 timestamp: 1655009626.853824 iteration: 1605 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48354 FastRCNN class loss: 0.20678 FastRCNN total loss: 0.69031 L1 loss: 0.0000e+00 L2 loss: 2.14805 Learning rate: 0.02 Mask loss: 0.57873 RPN box loss: 0.06524 RPN score loss: 0.02881 RPN total loss: 0.09405 Total loss: 3.51115 timestamp: 1655009630.1510751 iteration: 1610 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48985 FastRCNN class loss: 0.16725 FastRCNN total loss: 0.6571 L1 loss: 0.0000e+00 L2 loss: 2.14763 Learning rate: 0.02 Mask loss: 0.57992 RPN box loss: 0.06295 RPN score loss: 0.03896 RPN total loss: 0.10191 Total loss: 3.48656 timestamp: 1655009633.5850997 iteration: 1615 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3839 FastRCNN class loss: 0.11801 FastRCNN total loss: 0.50191 L1 loss: 0.0000e+00 L2 loss: 2.1472 Learning rate: 0.02 Mask loss: 0.5495 RPN box loss: 0.03949 RPN score loss: 0.04978 RPN total loss: 0.08927 Total loss: 3.28788 timestamp: 1655009636.9357913 iteration: 1620 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45074 FastRCNN class loss: 0.18849 FastRCNN total loss: 0.63923 L1 loss: 0.0000e+00 L2 loss: 2.14676 Learning rate: 0.02 Mask loss: 0.55919 RPN box loss: 0.13182 RPN score loss: 0.03932 RPN total loss: 0.17114 Total loss: 3.51633 timestamp: 1655009640.3398502 iteration: 1625 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4609 FastRCNN class loss: 0.11683 FastRCNN total loss: 0.57774 L1 loss: 0.0000e+00 L2 loss: 2.14632 Learning rate: 0.02 Mask loss: 0.57884 RPN box loss: 0.25523 RPN score loss: 0.02877 RPN total loss: 0.284 Total loss: 3.5869 timestamp: 1655009643.587299 iteration: 1630 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44486 FastRCNN class loss: 0.11014 FastRCNN total loss: 0.55501 L1 loss: 0.0000e+00 L2 loss: 2.14588 Learning rate: 0.02 Mask loss: 0.50113 RPN box loss: 0.17695 RPN score loss: 0.02745 RPN total loss: 0.2044 Total loss: 3.40642 timestamp: 1655009647.0269024 iteration: 1635 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23306 FastRCNN class loss: 0.12304 FastRCNN total loss: 0.3561 L1 loss: 0.0000e+00 L2 loss: 2.14545 Learning rate: 0.02 Mask loss: 0.53331 RPN box loss: 0.09115 RPN score loss: 0.17063 RPN total loss: 0.26177 Total loss: 3.29663 timestamp: 1655009650.3854518 iteration: 1640 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47835 FastRCNN class loss: 0.22183 FastRCNN total loss: 0.70018 L1 loss: 0.0000e+00 L2 loss: 2.14501 Learning rate: 0.02 Mask loss: 0.61058 RPN box loss: 0.06416 RPN score loss: 0.03226 RPN total loss: 0.09642 Total loss: 3.5522 timestamp: 1655009653.7577968 iteration: 1645 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45087 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.54562 L1 loss: 0.0000e+00 L2 loss: 2.14459 Learning rate: 0.02 Mask loss: 0.60379 RPN box loss: 0.09182 RPN score loss: 0.02109 RPN total loss: 0.11291 Total loss: 3.40691 timestamp: 1655009657.2746313 iteration: 1650 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45503 FastRCNN class loss: 0.13866 FastRCNN total loss: 0.59368 L1 loss: 0.0000e+00 L2 loss: 2.14415 Learning rate: 0.02 Mask loss: 0.53371 RPN box loss: 0.07995 RPN score loss: 0.04021 RPN total loss: 0.12016 Total loss: 3.3917 timestamp: 1655009660.547025 iteration: 1655 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40275 FastRCNN class loss: 0.1453 FastRCNN total loss: 0.54805 L1 loss: 0.0000e+00 L2 loss: 2.14372 Learning rate: 0.02 Mask loss: 0.53889 RPN box loss: 0.04375 RPN score loss: 0.02343 RPN total loss: 0.06718 Total loss: 3.29784 timestamp: 1655009664.005664 iteration: 1660 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33245 FastRCNN class loss: 0.15615 FastRCNN total loss: 0.48861 L1 loss: 0.0000e+00 L2 loss: 2.14329 Learning rate: 0.02 Mask loss: 0.60333 RPN box loss: 0.04241 RPN score loss: 0.02987 RPN total loss: 0.07228 Total loss: 3.30751 timestamp: 1655009667.5442245 iteration: 1665 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46503 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.55659 L1 loss: 0.0000e+00 L2 loss: 2.14286 Learning rate: 0.02 Mask loss: 0.52319 RPN box loss: 0.0616 RPN score loss: 0.01476 RPN total loss: 0.07636 Total loss: 3.29901 timestamp: 1655009671.0424068 iteration: 1670 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38941 FastRCNN class loss: 0.09928 FastRCNN total loss: 0.48869 L1 loss: 0.0000e+00 L2 loss: 2.14242 Learning rate: 0.02 Mask loss: 0.55403 RPN box loss: 0.06496 RPN score loss: 0.03015 RPN total loss: 0.09511 Total loss: 3.28025 timestamp: 1655009674.4855018 iteration: 1675 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37155 FastRCNN class loss: 0.11849 FastRCNN total loss: 0.49004 L1 loss: 0.0000e+00 L2 loss: 2.142 Learning rate: 0.02 Mask loss: 0.47668 RPN box loss: 0.14121 RPN score loss: 0.0132 RPN total loss: 0.15441 Total loss: 3.26313 timestamp: 1655009677.868969 iteration: 1680 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50482 FastRCNN class loss: 0.14675 FastRCNN total loss: 0.65156 L1 loss: 0.0000e+00 L2 loss: 2.14156 Learning rate: 0.02 Mask loss: 0.55164 RPN box loss: 0.04326 RPN score loss: 0.01708 RPN total loss: 0.06034 Total loss: 3.4051 timestamp: 1655009681.2106283 iteration: 1685 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48339 FastRCNN class loss: 0.20878 FastRCNN total loss: 0.69217 L1 loss: 0.0000e+00 L2 loss: 2.14113 Learning rate: 0.02 Mask loss: 0.55675 RPN box loss: 0.05129 RPN score loss: 0.01709 RPN total loss: 0.06838 Total loss: 3.45843 timestamp: 1655009684.5573106 iteration: 1690 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48022 FastRCNN class loss: 0.15893 FastRCNN total loss: 0.63915 L1 loss: 0.0000e+00 L2 loss: 2.14072 Learning rate: 0.02 Mask loss: 0.51499 RPN box loss: 0.09012 RPN score loss: 0.02936 RPN total loss: 0.11948 Total loss: 3.41434 timestamp: 1655009687.8648384 iteration: 1695 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49428 FastRCNN class loss: 0.1608 FastRCNN total loss: 0.65507 L1 loss: 0.0000e+00 L2 loss: 2.14029 Learning rate: 0.02 Mask loss: 0.47888 RPN box loss: 0.02805 RPN score loss: 0.01926 RPN total loss: 0.04731 Total loss: 3.32155 timestamp: 1655009691.2357624 iteration: 1700 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37233 FastRCNN class loss: 0.11247 FastRCNN total loss: 0.48481 L1 loss: 0.0000e+00 L2 loss: 2.13985 Learning rate: 0.02 Mask loss: 0.50613 RPN box loss: 0.02551 RPN score loss: 0.01655 RPN total loss: 0.04206 Total loss: 3.17285 timestamp: 1655009694.5321183 iteration: 1705 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48918 FastRCNN class loss: 0.21572 FastRCNN total loss: 0.70491 L1 loss: 0.0000e+00 L2 loss: 2.13943 Learning rate: 0.02 Mask loss: 0.53601 RPN box loss: 0.05927 RPN score loss: 0.03743 RPN total loss: 0.0967 Total loss: 3.47705 timestamp: 1655009697.8089411 iteration: 1710 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41392 FastRCNN class loss: 0.18375 FastRCNN total loss: 0.59767 L1 loss: 0.0000e+00 L2 loss: 2.13901 Learning rate: 0.02 Mask loss: 0.55144 RPN box loss: 0.08755 RPN score loss: 0.02848 RPN total loss: 0.11603 Total loss: 3.40416 timestamp: 1655009701.1387255 iteration: 1715 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.57283 FastRCNN class loss: 0.12877 FastRCNN total loss: 0.7016 L1 loss: 0.0000e+00 L2 loss: 2.13858 Learning rate: 0.02 Mask loss: 0.54399 RPN box loss: 0.07597 RPN score loss: 0.01524 RPN total loss: 0.09122 Total loss: 3.47539 timestamp: 1655009704.5058436 iteration: 1720 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43331 FastRCNN class loss: 0.10112 FastRCNN total loss: 0.53443 L1 loss: 0.0000e+00 L2 loss: 2.13815 Learning rate: 0.02 Mask loss: 0.52157 RPN box loss: 0.07859 RPN score loss: 0.02428 RPN total loss: 0.10287 Total loss: 3.29703 timestamp: 1655009707.923821 iteration: 1725 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31088 FastRCNN class loss: 0.15964 FastRCNN total loss: 0.47052 L1 loss: 0.0000e+00 L2 loss: 2.13771 Learning rate: 0.02 Mask loss: 0.53031 RPN box loss: 0.11232 RPN score loss: 0.04801 RPN total loss: 0.16032 Total loss: 3.29886 timestamp: 1655009711.2285042 iteration: 1730 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43244 FastRCNN class loss: 0.12356 FastRCNN total loss: 0.556 L1 loss: 0.0000e+00 L2 loss: 2.13729 Learning rate: 0.02 Mask loss: 0.60771 RPN box loss: 0.03718 RPN score loss: 0.02113 RPN total loss: 0.05831 Total loss: 3.35931 timestamp: 1655009714.4985821 iteration: 1735 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.387 FastRCNN class loss: 0.15783 FastRCNN total loss: 0.54482 L1 loss: 0.0000e+00 L2 loss: 2.13686 Learning rate: 0.02 Mask loss: 0.51478 RPN box loss: 0.08288 RPN score loss: 0.07049 RPN total loss: 0.15337 Total loss: 3.34983 timestamp: 1655009717.8595598 iteration: 1740 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49775 FastRCNN class loss: 0.11438 FastRCNN total loss: 0.61213 L1 loss: 0.0000e+00 L2 loss: 2.13642 Learning rate: 0.02 Mask loss: 0.48518 RPN box loss: 0.03654 RPN score loss: 0.0127 RPN total loss: 0.04924 Total loss: 3.28297 timestamp: 1655009721.2442276 iteration: 1745 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31704 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.41666 L1 loss: 0.0000e+00 L2 loss: 2.13601 Learning rate: 0.02 Mask loss: 0.64451 RPN box loss: 0.04034 RPN score loss: 0.01376 RPN total loss: 0.0541 Total loss: 3.25128 timestamp: 1655009724.5912435 iteration: 1750 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44418 FastRCNN class loss: 0.11872 FastRCNN total loss: 0.56291 L1 loss: 0.0000e+00 L2 loss: 2.13558 Learning rate: 0.02 Mask loss: 0.50731 RPN box loss: 0.06116 RPN score loss: 0.01363 RPN total loss: 0.07479 Total loss: 3.28058 timestamp: 1655009727.8235297 iteration: 1755 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36312 FastRCNN class loss: 0.08546 FastRCNN total loss: 0.44858 L1 loss: 0.0000e+00 L2 loss: 2.13515 Learning rate: 0.02 Mask loss: 0.45674 RPN box loss: 0.08104 RPN score loss: 0.01079 RPN total loss: 0.09183 Total loss: 3.13231 timestamp: 1655009731.0962095 iteration: 1760 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42713 FastRCNN class loss: 0.21499 FastRCNN total loss: 0.64212 L1 loss: 0.0000e+00 L2 loss: 2.13475 Learning rate: 0.02 Mask loss: 0.51486 RPN box loss: 0.06746 RPN score loss: 0.03851 RPN total loss: 0.10597 Total loss: 3.3977 timestamp: 1655009734.4942315 iteration: 1765 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34467 FastRCNN class loss: 0.1189 FastRCNN total loss: 0.46356 L1 loss: 0.0000e+00 L2 loss: 2.13431 Learning rate: 0.02 Mask loss: 0.56125 RPN box loss: 0.20137 RPN score loss: 0.03376 RPN total loss: 0.23514 Total loss: 3.39426 timestamp: 1655009737.874728 iteration: 1770 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5071 FastRCNN class loss: 0.16401 FastRCNN total loss: 0.67112 L1 loss: 0.0000e+00 L2 loss: 2.13388 Learning rate: 0.02 Mask loss: 0.68705 RPN box loss: 0.10681 RPN score loss: 0.0198 RPN total loss: 0.12661 Total loss: 3.61865 timestamp: 1655009741.4117491 iteration: 1775 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56294 FastRCNN class loss: 0.13493 FastRCNN total loss: 0.69787 L1 loss: 0.0000e+00 L2 loss: 2.13346 Learning rate: 0.02 Mask loss: 0.60524 RPN box loss: 0.07066 RPN score loss: 0.02023 RPN total loss: 0.09088 Total loss: 3.52745 timestamp: 1655009744.7379627 iteration: 1780 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32794 FastRCNN class loss: 0.12386 FastRCNN total loss: 0.4518 L1 loss: 0.0000e+00 L2 loss: 2.13303 Learning rate: 0.02 Mask loss: 0.57718 RPN box loss: 0.10964 RPN score loss: 0.02756 RPN total loss: 0.1372 Total loss: 3.29921 timestamp: 1655009748.1004827 iteration: 1785 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4186 FastRCNN class loss: 0.15103 FastRCNN total loss: 0.56963 L1 loss: 0.0000e+00 L2 loss: 2.13261 Learning rate: 0.02 Mask loss: 0.56807 RPN box loss: 0.01981 RPN score loss: 0.01553 RPN total loss: 0.03534 Total loss: 3.30565 timestamp: 1655009751.5381024 iteration: 1790 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39901 FastRCNN class loss: 0.14885 FastRCNN total loss: 0.54786 L1 loss: 0.0000e+00 L2 loss: 2.13218 Learning rate: 0.02 Mask loss: 0.51191 RPN box loss: 0.09297 RPN score loss: 0.05677 RPN total loss: 0.14974 Total loss: 3.34168 timestamp: 1655009754.8997233 iteration: 1795 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38205 FastRCNN class loss: 0.09615 FastRCNN total loss: 0.4782 L1 loss: 0.0000e+00 L2 loss: 2.13176 Learning rate: 0.02 Mask loss: 0.56713 RPN box loss: 0.05087 RPN score loss: 0.02151 RPN total loss: 0.07238 Total loss: 3.24947 timestamp: 1655009758.2762742 iteration: 1800 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40581 FastRCNN class loss: 0.14663 FastRCNN total loss: 0.55244 L1 loss: 0.0000e+00 L2 loss: 2.13133 Learning rate: 0.02 Mask loss: 0.62689 RPN box loss: 0.16332 RPN score loss: 0.03448 RPN total loss: 0.1978 Total loss: 3.50846 timestamp: 1655009761.605783 iteration: 1805 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32949 FastRCNN class loss: 0.07907 FastRCNN total loss: 0.40857 L1 loss: 0.0000e+00 L2 loss: 2.1309 Learning rate: 0.02 Mask loss: 0.55628 RPN box loss: 0.03048 RPN score loss: 0.03114 RPN total loss: 0.06162 Total loss: 3.15737 timestamp: 1655009764.982708 iteration: 1810 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50745 FastRCNN class loss: 0.12976 FastRCNN total loss: 0.63721 L1 loss: 0.0000e+00 L2 loss: 2.13048 Learning rate: 0.02 Mask loss: 0.53774 RPN box loss: 0.02743 RPN score loss: 0.01031 RPN total loss: 0.03774 Total loss: 3.34317 timestamp: 1655009768.2781723 iteration: 1815 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29758 FastRCNN class loss: 0.09878 FastRCNN total loss: 0.39637 L1 loss: 0.0000e+00 L2 loss: 2.13005 Learning rate: 0.02 Mask loss: 0.55414 RPN box loss: 0.10847 RPN score loss: 0.01756 RPN total loss: 0.12603 Total loss: 3.20658 timestamp: 1655009771.6360924 iteration: 1820 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48796 FastRCNN class loss: 0.13557 FastRCNN total loss: 0.62353 L1 loss: 0.0000e+00 L2 loss: 2.12963 Learning rate: 0.02 Mask loss: 0.53569 RPN box loss: 0.03949 RPN score loss: 0.01671 RPN total loss: 0.0562 Total loss: 3.34505 timestamp: 1655009775.040802 iteration: 1825 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34421 FastRCNN class loss: 0.17236 FastRCNN total loss: 0.51658 L1 loss: 0.0000e+00 L2 loss: 2.12922 Learning rate: 0.02 Mask loss: 0.49818 RPN box loss: 0.0702 RPN score loss: 0.03406 RPN total loss: 0.10426 Total loss: 3.24824 timestamp: 1655009778.39055 iteration: 1830 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37669 FastRCNN class loss: 0.08539 FastRCNN total loss: 0.46208 L1 loss: 0.0000e+00 L2 loss: 2.12879 Learning rate: 0.02 Mask loss: 0.49279 RPN box loss: 0.09295 RPN score loss: 0.01789 RPN total loss: 0.11084 Total loss: 3.1945 timestamp: 1655009781.8124068 iteration: 1835 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41381 FastRCNN class loss: 0.14293 FastRCNN total loss: 0.55674 L1 loss: 0.0000e+00 L2 loss: 2.12838 Learning rate: 0.02 Mask loss: 0.51935 RPN box loss: 0.05923 RPN score loss: 0.01837 RPN total loss: 0.0776 Total loss: 3.28206 timestamp: 1655009785.0917814 iteration: 1840 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46165 FastRCNN class loss: 0.11282 FastRCNN total loss: 0.57447 L1 loss: 0.0000e+00 L2 loss: 2.12796 Learning rate: 0.02 Mask loss: 0.55008 RPN box loss: 0.05424 RPN score loss: 0.01415 RPN total loss: 0.06839 Total loss: 3.3209 timestamp: 1655009788.5538368 iteration: 1845 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38321 FastRCNN class loss: 0.16031 FastRCNN total loss: 0.54353 L1 loss: 0.0000e+00 L2 loss: 2.12753 Learning rate: 0.02 Mask loss: 0.49675 RPN box loss: 0.03915 RPN score loss: 0.0239 RPN total loss: 0.06305 Total loss: 3.23085 timestamp: 1655009791.9445353 iteration: 1850 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37049 FastRCNN class loss: 0.0927 FastRCNN total loss: 0.4632 L1 loss: 0.0000e+00 L2 loss: 2.12711 Learning rate: 0.02 Mask loss: 0.50912 RPN box loss: 0.15599 RPN score loss: 0.0258 RPN total loss: 0.18179 Total loss: 3.28121 timestamp: 1655009795.393611 iteration: 1855 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48262 FastRCNN class loss: 0.1875 FastRCNN total loss: 0.67011 L1 loss: 0.0000e+00 L2 loss: 2.12669 Learning rate: 0.02 Mask loss: 0.51885 RPN box loss: 0.04967 RPN score loss: 0.021 RPN total loss: 0.07067 Total loss: 3.38632 timestamp: 1655009798.8255844 iteration: 1860 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.55036 FastRCNN class loss: 0.19316 FastRCNN total loss: 0.74352 L1 loss: 0.0000e+00 L2 loss: 2.12626 Learning rate: 0.02 Mask loss: 0.57196 RPN box loss: 0.08364 RPN score loss: 0.02053 RPN total loss: 0.10417 Total loss: 3.54591 timestamp: 1655009802.2645075 iteration: 1865 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49588 FastRCNN class loss: 0.21884 FastRCNN total loss: 0.71471 L1 loss: 0.0000e+00 L2 loss: 2.12584 Learning rate: 0.02 Mask loss: 0.5756 RPN box loss: 0.10262 RPN score loss: 0.04716 RPN total loss: 0.14978 Total loss: 3.56594 timestamp: 1655009805.6068618 iteration: 1870 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42651 FastRCNN class loss: 0.12748 FastRCNN total loss: 0.55399 L1 loss: 0.0000e+00 L2 loss: 2.12542 Learning rate: 0.02 Mask loss: 0.5804 RPN box loss: 0.05067 RPN score loss: 0.01941 RPN total loss: 0.07008 Total loss: 3.32988 timestamp: 1655009808.8991034 iteration: 1875 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45861 FastRCNN class loss: 0.11417 FastRCNN total loss: 0.57278 L1 loss: 0.0000e+00 L2 loss: 2.125 Learning rate: 0.02 Mask loss: 0.58145 RPN box loss: 0.01262 RPN score loss: 0.01132 RPN total loss: 0.02394 Total loss: 3.30316 timestamp: 1655009812.2553973 iteration: 1880 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34606 FastRCNN class loss: 0.09524 FastRCNN total loss: 0.44131 L1 loss: 0.0000e+00 L2 loss: 2.12456 Learning rate: 0.02 Mask loss: 0.49076 RPN box loss: 0.08832 RPN score loss: 0.02199 RPN total loss: 0.11032 Total loss: 3.16694 timestamp: 1655009815.5959978 iteration: 1885 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34968 FastRCNN class loss: 0.13655 FastRCNN total loss: 0.48624 L1 loss: 0.0000e+00 L2 loss: 2.12414 Learning rate: 0.02 Mask loss: 0.56351 RPN box loss: 0.07738 RPN score loss: 0.02211 RPN total loss: 0.09949 Total loss: 3.27338 timestamp: 1655009819.0002022 iteration: 1890 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39549 FastRCNN class loss: 0.14357 FastRCNN total loss: 0.53906 L1 loss: 0.0000e+00 L2 loss: 2.12371 Learning rate: 0.02 Mask loss: 0.52395 RPN box loss: 0.06678 RPN score loss: 0.02178 RPN total loss: 0.08857 Total loss: 3.27529 timestamp: 1655009822.2841501 iteration: 1895 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35728 FastRCNN class loss: 0.12881 FastRCNN total loss: 0.48609 L1 loss: 0.0000e+00 L2 loss: 2.1233 Learning rate: 0.02 Mask loss: 0.51756 RPN box loss: 0.11264 RPN score loss: 0.04476 RPN total loss: 0.1574 Total loss: 3.28434 timestamp: 1655009825.6150527 iteration: 1900 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40312 FastRCNN class loss: 0.11038 FastRCNN total loss: 0.5135 L1 loss: 0.0000e+00 L2 loss: 2.12288 Learning rate: 0.02 Mask loss: 0.53361 RPN box loss: 0.08703 RPN score loss: 0.0267 RPN total loss: 0.11374 Total loss: 3.28373 timestamp: 1655009829.0169353 iteration: 1905 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.483 FastRCNN class loss: 0.13916 FastRCNN total loss: 0.62216 L1 loss: 0.0000e+00 L2 loss: 2.12245 Learning rate: 0.02 Mask loss: 0.5325 RPN box loss: 0.10141 RPN score loss: 0.0139 RPN total loss: 0.11531 Total loss: 3.39242 timestamp: 1655009832.4424438 iteration: 1910 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46603 FastRCNN class loss: 0.19553 FastRCNN total loss: 0.66156 L1 loss: 0.0000e+00 L2 loss: 2.12203 Learning rate: 0.02 Mask loss: 0.58368 RPN box loss: 0.14443 RPN score loss: 0.03754 RPN total loss: 0.18198 Total loss: 3.54925 timestamp: 1655009835.798814 iteration: 1915 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39199 FastRCNN class loss: 0.10683 FastRCNN total loss: 0.49881 L1 loss: 0.0000e+00 L2 loss: 2.12161 Learning rate: 0.02 Mask loss: 0.51398 RPN box loss: 0.16615 RPN score loss: 0.01532 RPN total loss: 0.18147 Total loss: 3.31588 timestamp: 1655009839.1528249 iteration: 1920 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42811 FastRCNN class loss: 0.12578 FastRCNN total loss: 0.5539 L1 loss: 0.0000e+00 L2 loss: 2.1212 Learning rate: 0.02 Mask loss: 0.69629 RPN box loss: 0.01981 RPN score loss: 0.01048 RPN total loss: 0.03029 Total loss: 3.40168 timestamp: 1655009842.4998639 iteration: 1925 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45781 FastRCNN class loss: 0.11823 FastRCNN total loss: 0.57604 L1 loss: 0.0000e+00 L2 loss: 2.12078 Learning rate: 0.02 Mask loss: 0.61086 RPN box loss: 0.05659 RPN score loss: 0.01624 RPN total loss: 0.07283 Total loss: 3.3805 timestamp: 1655009845.7946124 iteration: 1930 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40817 FastRCNN class loss: 0.18795 FastRCNN total loss: 0.59612 L1 loss: 0.0000e+00 L2 loss: 2.12035 Learning rate: 0.02 Mask loss: 0.52315 RPN box loss: 0.02887 RPN score loss: 0.01746 RPN total loss: 0.04632 Total loss: 3.28594 timestamp: 1655009849.0916038 iteration: 1935 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33352 FastRCNN class loss: 0.13701 FastRCNN total loss: 0.47053 L1 loss: 0.0000e+00 L2 loss: 2.11994 Learning rate: 0.02 Mask loss: 0.58747 RPN box loss: 0.1434 RPN score loss: 0.04676 RPN total loss: 0.19016 Total loss: 3.3681 timestamp: 1655009852.4842286 iteration: 1940 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.5676 FastRCNN class loss: 0.23052 FastRCNN total loss: 0.79812 L1 loss: 0.0000e+00 L2 loss: 2.11952 Learning rate: 0.02 Mask loss: 0.59047 RPN box loss: 0.04967 RPN score loss: 0.02262 RPN total loss: 0.0723 Total loss: 3.5804 timestamp: 1655009855.9057286 iteration: 1945 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42762 FastRCNN class loss: 0.18175 FastRCNN total loss: 0.60937 L1 loss: 0.0000e+00 L2 loss: 2.11911 Learning rate: 0.02 Mask loss: 0.56624 RPN box loss: 0.02769 RPN score loss: 0.01622 RPN total loss: 0.04391 Total loss: 3.33863 timestamp: 1655009859.370893 iteration: 1950 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33929 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.42342 L1 loss: 0.0000e+00 L2 loss: 2.11869 Learning rate: 0.02 Mask loss: 0.52711 RPN box loss: 0.07953 RPN score loss: 0.02426 RPN total loss: 0.10379 Total loss: 3.173 timestamp: 1655009862.7433295 iteration: 1955 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28309 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.36559 L1 loss: 0.0000e+00 L2 loss: 2.11829 Learning rate: 0.02 Mask loss: 0.5235 RPN box loss: 0.08536 RPN score loss: 0.01742 RPN total loss: 0.10278 Total loss: 3.11016 timestamp: 1655009866.2287474 iteration: 1960 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30947 FastRCNN class loss: 0.13186 FastRCNN total loss: 0.44133 L1 loss: 0.0000e+00 L2 loss: 2.11789 Learning rate: 0.02 Mask loss: 0.49789 RPN box loss: 0.03882 RPN score loss: 0.01195 RPN total loss: 0.05077 Total loss: 3.10788 timestamp: 1655009869.600225 iteration: 1965 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42826 FastRCNN class loss: 0.19641 FastRCNN total loss: 0.62467 L1 loss: 0.0000e+00 L2 loss: 2.11748 Learning rate: 0.02 Mask loss: 0.58279 RPN box loss: 0.09962 RPN score loss: 0.03107 RPN total loss: 0.13069 Total loss: 3.45562 timestamp: 1655009873.0474975 iteration: 1970 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29909 FastRCNN class loss: 0.1133 FastRCNN total loss: 0.41239 L1 loss: 0.0000e+00 L2 loss: 2.11706 Learning rate: 0.02 Mask loss: 0.56511 RPN box loss: 0.07779 RPN score loss: 0.02999 RPN total loss: 0.10778 Total loss: 3.20234 timestamp: 1655009876.439556 iteration: 1975 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47171 FastRCNN class loss: 0.22193 FastRCNN total loss: 0.69364 L1 loss: 0.0000e+00 L2 loss: 2.11665 Learning rate: 0.02 Mask loss: 0.57367 RPN box loss: 0.08226 RPN score loss: 0.05999 RPN total loss: 0.14225 Total loss: 3.5262 timestamp: 1655009879.8416014 iteration: 1980 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29996 FastRCNN class loss: 0.11423 FastRCNN total loss: 0.41419 L1 loss: 0.0000e+00 L2 loss: 2.11622 Learning rate: 0.02 Mask loss: 0.49929 RPN box loss: 0.0394 RPN score loss: 0.02968 RPN total loss: 0.06908 Total loss: 3.09878 timestamp: 1655009883.213883 iteration: 1985 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35164 FastRCNN class loss: 0.14268 FastRCNN total loss: 0.49432 L1 loss: 0.0000e+00 L2 loss: 2.1158 Learning rate: 0.02 Mask loss: 0.59048 RPN box loss: 0.0927 RPN score loss: 0.04142 RPN total loss: 0.13411 Total loss: 3.33472 timestamp: 1655009886.6476564 iteration: 1990 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41541 FastRCNN class loss: 0.10906 FastRCNN total loss: 0.52447 L1 loss: 0.0000e+00 L2 loss: 2.11537 Learning rate: 0.02 Mask loss: 0.52611 RPN box loss: 0.06547 RPN score loss: 0.02736 RPN total loss: 0.09283 Total loss: 3.25878 timestamp: 1655009890.012888 iteration: 1995 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36851 FastRCNN class loss: 0.09704 FastRCNN total loss: 0.46555 L1 loss: 0.0000e+00 L2 loss: 2.11496 Learning rate: 0.02 Mask loss: 0.5494 RPN box loss: 0.09131 RPN score loss: 0.02098 RPN total loss: 0.11228 Total loss: 3.2422 timestamp: 1655009893.4628463 iteration: 2000 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39371 FastRCNN class loss: 0.16507 FastRCNN total loss: 0.55878 L1 loss: 0.0000e+00 L2 loss: 2.11455 Learning rate: 0.02 Mask loss: 0.49803 RPN box loss: 0.04947 RPN score loss: 0.02279 RPN total loss: 0.07226 Total loss: 3.24362 timestamp: 1655009897.05533 iteration: 2005 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40199 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.4928 L1 loss: 0.0000e+00 L2 loss: 2.11415 Learning rate: 0.02 Mask loss: 0.51863 RPN box loss: 0.01064 RPN score loss: 0.01106 RPN total loss: 0.0217 Total loss: 3.14728 timestamp: 1655009900.4614122 iteration: 2010 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47814 FastRCNN class loss: 0.14093 FastRCNN total loss: 0.61907 L1 loss: 0.0000e+00 L2 loss: 2.11374 Learning rate: 0.02 Mask loss: 0.63021 RPN box loss: 0.05918 RPN score loss: 0.01602 RPN total loss: 0.0752 Total loss: 3.43822 timestamp: 1655009903.867389 iteration: 2015 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3448 FastRCNN class loss: 0.1151 FastRCNN total loss: 0.4599 L1 loss: 0.0000e+00 L2 loss: 2.11334 Learning rate: 0.02 Mask loss: 0.59837 RPN box loss: 0.08431 RPN score loss: 0.01825 RPN total loss: 0.10256 Total loss: 3.27417 timestamp: 1655009907.2759356 iteration: 2020 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37284 FastRCNN class loss: 0.15212 FastRCNN total loss: 0.52496 L1 loss: 0.0000e+00 L2 loss: 2.11294 Learning rate: 0.02 Mask loss: 0.58908 RPN box loss: 0.09162 RPN score loss: 0.03317 RPN total loss: 0.12478 Total loss: 3.35177 timestamp: 1655009910.6177673 iteration: 2025 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36074 FastRCNN class loss: 0.12164 FastRCNN total loss: 0.48238 L1 loss: 0.0000e+00 L2 loss: 2.11252 Learning rate: 0.02 Mask loss: 0.51597 RPN box loss: 0.14866 RPN score loss: 0.02816 RPN total loss: 0.17683 Total loss: 3.2877 timestamp: 1655009914.0988302 iteration: 2030 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43242 FastRCNN class loss: 0.15911 FastRCNN total loss: 0.59152 L1 loss: 0.0000e+00 L2 loss: 2.11211 Learning rate: 0.02 Mask loss: 0.55892 RPN box loss: 0.06917 RPN score loss: 0.05795 RPN total loss: 0.12712 Total loss: 3.38967 timestamp: 1655009917.4395018 iteration: 2035 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43583 FastRCNN class loss: 0.11307 FastRCNN total loss: 0.5489 L1 loss: 0.0000e+00 L2 loss: 2.11169 Learning rate: 0.02 Mask loss: 0.59165 RPN box loss: 0.07156 RPN score loss: 0.01557 RPN total loss: 0.08713 Total loss: 3.33937 timestamp: 1655009920.8125324 iteration: 2040 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38518 FastRCNN class loss: 0.10777 FastRCNN total loss: 0.49295 L1 loss: 0.0000e+00 L2 loss: 2.11126 Learning rate: 0.02 Mask loss: 0.55935 RPN box loss: 0.05328 RPN score loss: 0.01464 RPN total loss: 0.06792 Total loss: 3.23148 timestamp: 1655009924.1943061 iteration: 2045 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3777 FastRCNN class loss: 0.11465 FastRCNN total loss: 0.49235 L1 loss: 0.0000e+00 L2 loss: 2.11083 Learning rate: 0.02 Mask loss: 0.58375 RPN box loss: 0.09075 RPN score loss: 0.03058 RPN total loss: 0.12133 Total loss: 3.30826 timestamp: 1655009927.5847867 iteration: 2050 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45585 FastRCNN class loss: 0.09646 FastRCNN total loss: 0.55231 L1 loss: 0.0000e+00 L2 loss: 2.11042 Learning rate: 0.02 Mask loss: 0.58525 RPN box loss: 0.0592 RPN score loss: 0.01257 RPN total loss: 0.07177 Total loss: 3.31974 timestamp: 1655009930.987056 iteration: 2055 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42678 FastRCNN class loss: 0.12824 FastRCNN total loss: 0.55501 L1 loss: 0.0000e+00 L2 loss: 2.10999 Learning rate: 0.02 Mask loss: 0.50506 RPN box loss: 0.0992 RPN score loss: 0.03667 RPN total loss: 0.13587 Total loss: 3.30594 timestamp: 1655009934.3786685 iteration: 2060 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50779 FastRCNN class loss: 0.13456 FastRCNN total loss: 0.64235 L1 loss: 0.0000e+00 L2 loss: 2.10956 Learning rate: 0.02 Mask loss: 0.60866 RPN box loss: 0.03569 RPN score loss: 0.02153 RPN total loss: 0.05722 Total loss: 3.41778 timestamp: 1655009937.771172 iteration: 2065 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45045 FastRCNN class loss: 0.14757 FastRCNN total loss: 0.59803 L1 loss: 0.0000e+00 L2 loss: 2.10914 Learning rate: 0.02 Mask loss: 0.60411 RPN box loss: 0.10575 RPN score loss: 0.02725 RPN total loss: 0.13301 Total loss: 3.44428 timestamp: 1655009941.0258586 iteration: 2070 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30438 FastRCNN class loss: 0.08283 FastRCNN total loss: 0.38721 L1 loss: 0.0000e+00 L2 loss: 2.10872 Learning rate: 0.02 Mask loss: 0.56783 RPN box loss: 0.02424 RPN score loss: 0.01453 RPN total loss: 0.03877 Total loss: 3.10254 timestamp: 1655009944.3730476 iteration: 2075 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25756 FastRCNN class loss: 0.08524 FastRCNN total loss: 0.3428 L1 loss: 0.0000e+00 L2 loss: 2.1083 Learning rate: 0.02 Mask loss: 0.50217 RPN box loss: 0.05064 RPN score loss: 0.03749 RPN total loss: 0.08812 Total loss: 3.0414 timestamp: 1655009947.674591 iteration: 2080 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36421 FastRCNN class loss: 0.09942 FastRCNN total loss: 0.46363 L1 loss: 0.0000e+00 L2 loss: 2.10787 Learning rate: 0.02 Mask loss: 0.5035 RPN box loss: 0.1105 RPN score loss: 0.01156 RPN total loss: 0.12206 Total loss: 3.19705 timestamp: 1655009950.9553995 iteration: 2085 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46886 FastRCNN class loss: 0.10527 FastRCNN total loss: 0.57413 L1 loss: 0.0000e+00 L2 loss: 2.10746 Learning rate: 0.02 Mask loss: 0.56033 RPN box loss: 0.0257 RPN score loss: 0.01074 RPN total loss: 0.03644 Total loss: 3.27836 timestamp: 1655009954.2294686 iteration: 2090 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33495 FastRCNN class loss: 0.10287 FastRCNN total loss: 0.43782 L1 loss: 0.0000e+00 L2 loss: 2.10704 Learning rate: 0.02 Mask loss: 0.58505 RPN box loss: 0.0742 RPN score loss: 0.02621 RPN total loss: 0.10041 Total loss: 3.23032 timestamp: 1655009957.602006 iteration: 2095 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.50319 FastRCNN class loss: 0.16318 FastRCNN total loss: 0.66638 L1 loss: 0.0000e+00 L2 loss: 2.10661 Learning rate: 0.02 Mask loss: 0.53274 RPN box loss: 0.04587 RPN score loss: 0.02011 RPN total loss: 0.06597 Total loss: 3.3717 timestamp: 1655009961.052996 iteration: 2100 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44512 FastRCNN class loss: 0.14397 FastRCNN total loss: 0.58909 L1 loss: 0.0000e+00 L2 loss: 2.10619 Learning rate: 0.02 Mask loss: 0.52566 RPN box loss: 0.06919 RPN score loss: 0.03269 RPN total loss: 0.10188 Total loss: 3.32282 timestamp: 1655009964.4084485 iteration: 2105 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36069 FastRCNN class loss: 0.13755 FastRCNN total loss: 0.49824 L1 loss: 0.0000e+00 L2 loss: 2.10578 Learning rate: 0.02 Mask loss: 0.49087 RPN box loss: 0.07762 RPN score loss: 0.02548 RPN total loss: 0.1031 Total loss: 3.19799 timestamp: 1655009967.7374253 iteration: 2110 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46763 FastRCNN class loss: 0.11414 FastRCNN total loss: 0.58177 L1 loss: 0.0000e+00 L2 loss: 2.10536 Learning rate: 0.02 Mask loss: 0.51896 RPN box loss: 0.06993 RPN score loss: 0.01958 RPN total loss: 0.08951 Total loss: 3.29561 timestamp: 1655009971.0890982 iteration: 2115 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48377 FastRCNN class loss: 0.13817 FastRCNN total loss: 0.62194 L1 loss: 0.0000e+00 L2 loss: 2.10495 Learning rate: 0.02 Mask loss: 0.50876 RPN box loss: 0.06251 RPN score loss: 0.02333 RPN total loss: 0.08584 Total loss: 3.3215 timestamp: 1655009974.5094564 iteration: 2120 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46462 FastRCNN class loss: 0.14147 FastRCNN total loss: 0.60609 L1 loss: 0.0000e+00 L2 loss: 2.10454 Learning rate: 0.02 Mask loss: 0.51028 RPN box loss: 0.07644 RPN score loss: 0.02629 RPN total loss: 0.10273 Total loss: 3.32364 timestamp: 1655009977.8933215 iteration: 2125 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3816 FastRCNN class loss: 0.14831 FastRCNN total loss: 0.52991 L1 loss: 0.0000e+00 L2 loss: 2.10412 Learning rate: 0.02 Mask loss: 0.49337 RPN box loss: 0.10006 RPN score loss: 0.02482 RPN total loss: 0.12488 Total loss: 3.25228 timestamp: 1655009981.246102 iteration: 2130 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38426 FastRCNN class loss: 0.10219 FastRCNN total loss: 0.48645 L1 loss: 0.0000e+00 L2 loss: 2.10372 Learning rate: 0.02 Mask loss: 0.51771 RPN box loss: 0.03814 RPN score loss: 0.01144 RPN total loss: 0.04958 Total loss: 3.15746 timestamp: 1655009984.56874 iteration: 2135 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4862 FastRCNN class loss: 0.13384 FastRCNN total loss: 0.62004 L1 loss: 0.0000e+00 L2 loss: 2.10333 Learning rate: 0.02 Mask loss: 0.4711 RPN box loss: 0.03558 RPN score loss: 0.01658 RPN total loss: 0.05216 Total loss: 3.24663 timestamp: 1655009987.939147 iteration: 2140 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38507 FastRCNN class loss: 0.11139 FastRCNN total loss: 0.49645 L1 loss: 0.0000e+00 L2 loss: 2.10291 Learning rate: 0.02 Mask loss: 0.52533 RPN box loss: 0.06668 RPN score loss: 0.01835 RPN total loss: 0.08503 Total loss: 3.20972 timestamp: 1655009991.2406662 iteration: 2145 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43259 FastRCNN class loss: 0.1439 FastRCNN total loss: 0.57649 L1 loss: 0.0000e+00 L2 loss: 2.1025 Learning rate: 0.02 Mask loss: 0.47612 RPN box loss: 0.10617 RPN score loss: 0.06173 RPN total loss: 0.1679 Total loss: 3.32301 timestamp: 1655009994.455657 iteration: 2150 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4945 FastRCNN class loss: 0.13449 FastRCNN total loss: 0.629 L1 loss: 0.0000e+00 L2 loss: 2.10212 Learning rate: 0.02 Mask loss: 0.54145 RPN box loss: 0.10284 RPN score loss: 0.05337 RPN total loss: 0.15621 Total loss: 3.42878 timestamp: 1655009997.7300637 iteration: 2155 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36467 FastRCNN class loss: 0.11809 FastRCNN total loss: 0.48276 L1 loss: 0.0000e+00 L2 loss: 2.10173 Learning rate: 0.02 Mask loss: 0.64278 RPN box loss: 0.07658 RPN score loss: 0.01982 RPN total loss: 0.09641 Total loss: 3.32367 timestamp: 1655010001.1074188 iteration: 2160 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36408 FastRCNN class loss: 0.13395 FastRCNN total loss: 0.49803 L1 loss: 0.0000e+00 L2 loss: 2.10131 Learning rate: 0.02 Mask loss: 0.55646 RPN box loss: 0.04282 RPN score loss: 0.03238 RPN total loss: 0.07521 Total loss: 3.23101 timestamp: 1655010004.4570735 iteration: 2165 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36998 FastRCNN class loss: 0.12203 FastRCNN total loss: 0.49202 L1 loss: 0.0000e+00 L2 loss: 2.10092 Learning rate: 0.02 Mask loss: 0.46725 RPN box loss: 0.03255 RPN score loss: 0.02495 RPN total loss: 0.0575 Total loss: 3.11768 timestamp: 1655010007.6763015 iteration: 2170 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47981 FastRCNN class loss: 0.13891 FastRCNN total loss: 0.61872 L1 loss: 0.0000e+00 L2 loss: 2.10051 Learning rate: 0.02 Mask loss: 0.48992 RPN box loss: 0.09283 RPN score loss: 0.01456 RPN total loss: 0.10738 Total loss: 3.31654 timestamp: 1655010011.0576031 iteration: 2175 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43268 FastRCNN class loss: 0.12928 FastRCNN total loss: 0.56196 L1 loss: 0.0000e+00 L2 loss: 2.10012 Learning rate: 0.02 Mask loss: 0.57627 RPN box loss: 0.10351 RPN score loss: 0.02645 RPN total loss: 0.12996 Total loss: 3.36832 timestamp: 1655010014.509342 iteration: 2180 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44825 FastRCNN class loss: 0.18696 FastRCNN total loss: 0.63521 L1 loss: 0.0000e+00 L2 loss: 2.09974 Learning rate: 0.02 Mask loss: 0.51547 RPN box loss: 0.08058 RPN score loss: 0.03137 RPN total loss: 0.11195 Total loss: 3.36237 timestamp: 1655010017.8605704 iteration: 2185 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47367 FastRCNN class loss: 0.14908 FastRCNN total loss: 0.62275 L1 loss: 0.0000e+00 L2 loss: 2.09933 Learning rate: 0.02 Mask loss: 0.58479 RPN box loss: 0.04028 RPN score loss: 0.01916 RPN total loss: 0.05944 Total loss: 3.36631 timestamp: 1655010021.2590842 iteration: 2190 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44056 FastRCNN class loss: 0.15645 FastRCNN total loss: 0.59701 L1 loss: 0.0000e+00 L2 loss: 2.09893 Learning rate: 0.02 Mask loss: 0.57705 RPN box loss: 0.08646 RPN score loss: 0.02932 RPN total loss: 0.11579 Total loss: 3.38877 timestamp: 1655010024.6370502 iteration: 2195 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38241 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.47009 L1 loss: 0.0000e+00 L2 loss: 2.09852 Learning rate: 0.02 Mask loss: 0.60157 RPN box loss: 0.05357 RPN score loss: 0.02175 RPN total loss: 0.07532 Total loss: 3.2455 timestamp: 1655010028.0289567 iteration: 2200 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47777 FastRCNN class loss: 0.20831 FastRCNN total loss: 0.68608 L1 loss: 0.0000e+00 L2 loss: 2.09812 Learning rate: 0.02 Mask loss: 0.53543 RPN box loss: 0.07651 RPN score loss: 0.01807 RPN total loss: 0.09458 Total loss: 3.41421 timestamp: 1655010031.404946 iteration: 2205 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.54564 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.62663 L1 loss: 0.0000e+00 L2 loss: 2.09771 Learning rate: 0.02 Mask loss: 0.49482 RPN box loss: 0.0336 RPN score loss: 0.01334 RPN total loss: 0.04693 Total loss: 3.2661 timestamp: 1655010034.8365068 iteration: 2210 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.47601 FastRCNN class loss: 0.16006 FastRCNN total loss: 0.63607 L1 loss: 0.0000e+00 L2 loss: 2.09729 Learning rate: 0.02 Mask loss: 0.55602 RPN box loss: 0.06702 RPN score loss: 0.08504 RPN total loss: 0.15206 Total loss: 3.44144 timestamp: 1655010038.1092145 iteration: 2215 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48816 FastRCNN class loss: 0.2177 FastRCNN total loss: 0.70586 L1 loss: 0.0000e+00 L2 loss: 2.09689 Learning rate: 0.02 Mask loss: 0.55622 RPN box loss: 0.07079 RPN score loss: 0.0274 RPN total loss: 0.09819 Total loss: 3.45716 timestamp: 1655010041.4176376 iteration: 2220 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35199 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.45217 L1 loss: 0.0000e+00 L2 loss: 2.09647 Learning rate: 0.02 Mask loss: 0.49864 RPN box loss: 0.02503 RPN score loss: 0.00865 RPN total loss: 0.03368 Total loss: 3.08097 timestamp: 1655010044.703371 iteration: 2225 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44849 FastRCNN class loss: 0.11691 FastRCNN total loss: 0.5654 L1 loss: 0.0000e+00 L2 loss: 2.09606 Learning rate: 0.02 Mask loss: 0.57414 RPN box loss: 0.09474 RPN score loss: 0.0263 RPN total loss: 0.12104 Total loss: 3.35664 timestamp: 1655010047.9747956 iteration: 2230 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42493 FastRCNN class loss: 0.15134 FastRCNN total loss: 0.57627 L1 loss: 0.0000e+00 L2 loss: 2.09566 Learning rate: 0.02 Mask loss: 0.52203 RPN box loss: 0.05879 RPN score loss: 0.02052 RPN total loss: 0.07931 Total loss: 3.27327 timestamp: 1655010051.3730452 iteration: 2235 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23669 FastRCNN class loss: 0.13043 FastRCNN total loss: 0.36711 L1 loss: 0.0000e+00 L2 loss: 2.09526 Learning rate: 0.02 Mask loss: 0.43716 RPN box loss: 0.08495 RPN score loss: 0.03129 RPN total loss: 0.11624 Total loss: 3.01578 timestamp: 1655010054.694071 iteration: 2240 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37461 FastRCNN class loss: 0.13332 FastRCNN total loss: 0.50793 L1 loss: 0.0000e+00 L2 loss: 2.09487 Learning rate: 0.02 Mask loss: 0.6986 RPN box loss: 0.06545 RPN score loss: 0.02461 RPN total loss: 0.09006 Total loss: 3.39146 timestamp: 1655010058.1209593 iteration: 2245 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41744 FastRCNN class loss: 0.13751 FastRCNN total loss: 0.55494 L1 loss: 0.0000e+00 L2 loss: 2.09438 Learning rate: 0.02 Mask loss: 0.62376 RPN box loss: 0.04565 RPN score loss: 0.0196 RPN total loss: 0.06525 Total loss: 3.33833 timestamp: 1655010061.5013113 iteration: 2250 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46512 FastRCNN class loss: 0.1579 FastRCNN total loss: 0.62301 L1 loss: 0.0000e+00 L2 loss: 2.09394 Learning rate: 0.02 Mask loss: 0.55732 RPN box loss: 0.15413 RPN score loss: 0.01813 RPN total loss: 0.17227 Total loss: 3.44655 timestamp: 1655010064.7666419 iteration: 2255 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32929 FastRCNN class loss: 0.1015 FastRCNN total loss: 0.43079 L1 loss: 0.0000e+00 L2 loss: 2.09351 Learning rate: 0.02 Mask loss: 0.62197 RPN box loss: 0.05345 RPN score loss: 0.01272 RPN total loss: 0.06617 Total loss: 3.21244 timestamp: 1655010068.1792545 iteration: 2260 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34481 FastRCNN class loss: 0.16573 FastRCNN total loss: 0.51054 L1 loss: 0.0000e+00 L2 loss: 2.0931 Learning rate: 0.02 Mask loss: 0.56384 RPN box loss: 0.0752 RPN score loss: 0.03677 RPN total loss: 0.11197 Total loss: 3.27945 timestamp: 1655010071.5331838 iteration: 2265 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.48182 FastRCNN class loss: 0.16053 FastRCNN total loss: 0.64235 L1 loss: 0.0000e+00 L2 loss: 2.09268 Learning rate: 0.02 Mask loss: 0.5939 RPN box loss: 0.10771 RPN score loss: 0.02663 RPN total loss: 0.13434 Total loss: 3.46326 timestamp: 1655010074.8893542 iteration: 2270 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29402 FastRCNN class loss: 0.11489 FastRCNN total loss: 0.40891 L1 loss: 0.0000e+00 L2 loss: 2.09226 Learning rate: 0.02 Mask loss: 0.4925 RPN box loss: 0.11181 RPN score loss: 0.0252 RPN total loss: 0.137 Total loss: 3.13067 timestamp: 1655010078.2621057 iteration: 2275 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37517 FastRCNN class loss: 0.13086 FastRCNN total loss: 0.50603 L1 loss: 0.0000e+00 L2 loss: 2.09185 Learning rate: 0.02 Mask loss: 0.43621 RPN box loss: 0.08862 RPN score loss: 0.02605 RPN total loss: 0.11468 Total loss: 3.14877 timestamp: 1655010081.777936 iteration: 2280 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36424 FastRCNN class loss: 0.11983 FastRCNN total loss: 0.48407 L1 loss: 0.0000e+00 L2 loss: 2.09143 Learning rate: 0.02 Mask loss: 0.42543 RPN box loss: 0.02566 RPN score loss: 0.01644 RPN total loss: 0.0421 Total loss: 3.04303 timestamp: 1655010085.2215908 iteration: 2285 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34485 FastRCNN class loss: 0.19717 FastRCNN total loss: 0.54202 L1 loss: 0.0000e+00 L2 loss: 2.09101 Learning rate: 0.02 Mask loss: 0.48315 RPN box loss: 0.03793 RPN score loss: 0.01583 RPN total loss: 0.05376 Total loss: 3.16993 timestamp: 1655010088.5378783 iteration: 2290 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46103 FastRCNN class loss: 0.12725 FastRCNN total loss: 0.58828 L1 loss: 0.0000e+00 L2 loss: 2.09061 Learning rate: 0.02 Mask loss: 0.48578 RPN box loss: 0.02773 RPN score loss: 0.01217 RPN total loss: 0.0399 Total loss: 3.20457 timestamp: 1655010091.8717694 iteration: 2295 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51506 FastRCNN class loss: 0.16279 FastRCNN total loss: 0.67785 L1 loss: 0.0000e+00 L2 loss: 2.09019 Learning rate: 0.02 Mask loss: 0.56118 RPN box loss: 0.0563 RPN score loss: 0.01794 RPN total loss: 0.07423 Total loss: 3.40345 timestamp: 1655010095.2769835 iteration: 2300 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43533 FastRCNN class loss: 0.14743 FastRCNN total loss: 0.58277 L1 loss: 0.0000e+00 L2 loss: 2.08978 Learning rate: 0.02 Mask loss: 0.69759 RPN box loss: 0.03783 RPN score loss: 0.01385 RPN total loss: 0.05169 Total loss: 3.42182 timestamp: 1655010098.5773504 iteration: 2305 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40557 FastRCNN class loss: 0.12561 FastRCNN total loss: 0.53118 L1 loss: 0.0000e+00 L2 loss: 2.08937 Learning rate: 0.02 Mask loss: 0.63383 RPN box loss: 0.13245 RPN score loss: 0.0286 RPN total loss: 0.16105 Total loss: 3.41543 timestamp: 1655010101.9337287 iteration: 2310 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39165 FastRCNN class loss: 0.20116 FastRCNN total loss: 0.59281 L1 loss: 0.0000e+00 L2 loss: 2.08896 Learning rate: 0.02 Mask loss: 0.55368 RPN box loss: 0.06337 RPN score loss: 0.01393 RPN total loss: 0.07729 Total loss: 3.31274 timestamp: 1655010105.2383616 iteration: 2315 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39306 FastRCNN class loss: 0.14728 FastRCNN total loss: 0.54034 L1 loss: 0.0000e+00 L2 loss: 2.08853 Learning rate: 0.02 Mask loss: 0.52787 RPN box loss: 0.05585 RPN score loss: 0.0244 RPN total loss: 0.08024 Total loss: 3.23699 timestamp: 1655010108.4910524 iteration: 2320 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43187 FastRCNN class loss: 0.10812 FastRCNN total loss: 0.53999 L1 loss: 0.0000e+00 L2 loss: 2.08814 Learning rate: 0.02 Mask loss: 0.55485 RPN box loss: 0.07977 RPN score loss: 0.04816 RPN total loss: 0.12793 Total loss: 3.3109 timestamp: 1655010111.789045 iteration: 2325 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.49156 FastRCNN class loss: 0.1484 FastRCNN total loss: 0.63996 L1 loss: 0.0000e+00 L2 loss: 2.08772 Learning rate: 0.02 Mask loss: 0.57531 RPN box loss: 0.03933 RPN score loss: 0.01809 RPN total loss: 0.05742 Total loss: 3.36041 timestamp: 1655010115.0937235 iteration: 2330 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.56381 FastRCNN class loss: 0.17221 FastRCNN total loss: 0.73602 L1 loss: 0.0000e+00 L2 loss: 2.08731 Learning rate: 0.02 Mask loss: 0.56269 RPN box loss: 0.08459 RPN score loss: 0.02876 RPN total loss: 0.11335 Total loss: 3.49937 timestamp: 1655010118.539756 iteration: 2335 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36542 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.45885 L1 loss: 0.0000e+00 L2 loss: 2.08688 Learning rate: 0.02 Mask loss: 0.57228 RPN box loss: 0.0783 RPN score loss: 0.02046 RPN total loss: 0.09876 Total loss: 3.21677 timestamp: 1655010121.9588468 iteration: 2340 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42467 FastRCNN class loss: 0.15319 FastRCNN total loss: 0.57786 L1 loss: 0.0000e+00 L2 loss: 2.08646 Learning rate: 0.02 Mask loss: 0.58062 RPN box loss: 0.03169 RPN score loss: 0.01265 RPN total loss: 0.04433 Total loss: 3.28927 timestamp: 1655010125.423455 iteration: 2345 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41427 FastRCNN class loss: 0.1216 FastRCNN total loss: 0.53587 L1 loss: 0.0000e+00 L2 loss: 2.08605 Learning rate: 0.02 Mask loss: 0.51429 RPN box loss: 0.10813 RPN score loss: 0.02533 RPN total loss: 0.13345 Total loss: 3.26967 timestamp: 1655010128.7350926 iteration: 2350 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.52226 FastRCNN class loss: 0.15266 FastRCNN total loss: 0.67492 L1 loss: 0.0000e+00 L2 loss: 2.08566 Learning rate: 0.02 Mask loss: 0.50385 RPN box loss: 0.05965 RPN score loss: 0.02116 RPN total loss: 0.08081 Total loss: 3.34523 timestamp: 1655010132.0814402 iteration: 2355 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39834 FastRCNN class loss: 0.15547 FastRCNN total loss: 0.55381 L1 loss: 0.0000e+00 L2 loss: 2.08525 Learning rate: 0.02 Mask loss: 0.53047 RPN box loss: 0.08607 RPN score loss: 0.0214 RPN total loss: 0.10747 Total loss: 3.277 timestamp: 1655010135.5013177 iteration: 2360 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31007 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.37716 L1 loss: 0.0000e+00 L2 loss: 2.08486 Learning rate: 0.02 Mask loss: 0.53825 RPN box loss: 0.03052 RPN score loss: 0.01659 RPN total loss: 0.04711 Total loss: 3.04737 timestamp: 1655010138.8244371 iteration: 2365 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46753 FastRCNN class loss: 0.1679 FastRCNN total loss: 0.63542 L1 loss: 0.0000e+00 L2 loss: 2.08446 Learning rate: 0.02 Mask loss: 0.47568 RPN box loss: 0.08191 RPN score loss: 0.01284 RPN total loss: 0.09475 Total loss: 3.29031 timestamp: 1655010142.104611 iteration: 2370 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34584 FastRCNN class loss: 0.13141 FastRCNN total loss: 0.47725 L1 loss: 0.0000e+00 L2 loss: 2.08405 Learning rate: 0.02 Mask loss: 0.52339 RPN box loss: 0.09316 RPN score loss: 0.02195 RPN total loss: 0.11511 Total loss: 3.1998 timestamp: 1655010145.280232 iteration: 2375 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3502 FastRCNN class loss: 0.11092 FastRCNN total loss: 0.46112 L1 loss: 0.0000e+00 L2 loss: 2.08364 Learning rate: 0.02 Mask loss: 0.49982 RPN box loss: 0.0915 RPN score loss: 0.0248 RPN total loss: 0.1163 Total loss: 3.16087 timestamp: 1655010148.5789955 iteration: 2380 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42182 FastRCNN class loss: 0.13549 FastRCNN total loss: 0.55732 L1 loss: 0.0000e+00 L2 loss: 2.08325 Learning rate: 0.02 Mask loss: 0.45884 RPN box loss: 0.01232 RPN score loss: 0.01039 RPN total loss: 0.02271 Total loss: 3.12212 timestamp: 1655010151.9043708 iteration: 2385 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42978 FastRCNN class loss: 0.1223 FastRCNN total loss: 0.55208 L1 loss: 0.0000e+00 L2 loss: 2.08287 Learning rate: 0.02 Mask loss: 0.52146 RPN box loss: 0.10598 RPN score loss: 0.03645 RPN total loss: 0.14243 Total loss: 3.29884 timestamp: 1655010155.179511 iteration: 2390 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34027 FastRCNN class loss: 0.10556 FastRCNN total loss: 0.44583 L1 loss: 0.0000e+00 L2 loss: 2.08248 Learning rate: 0.02 Mask loss: 0.58073 RPN box loss: 0.07877 RPN score loss: 0.0136 RPN total loss: 0.09237 Total loss: 3.20141 timestamp: 1655010158.4551685 iteration: 2395 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33185 FastRCNN class loss: 0.13294 FastRCNN total loss: 0.46479 L1 loss: 0.0000e+00 L2 loss: 2.08207 Learning rate: 0.02 Mask loss: 0.47359 RPN box loss: 0.12162 RPN score loss: 0.0124 RPN total loss: 0.13401 Total loss: 3.15447 timestamp: 1655010161.754688 iteration: 2400 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43505 FastRCNN class loss: 0.13457 FastRCNN total loss: 0.56962 L1 loss: 0.0000e+00 L2 loss: 2.08166 Learning rate: 0.02 Mask loss: 0.48169 RPN box loss: 0.08278 RPN score loss: 0.02345 RPN total loss: 0.10623 Total loss: 3.2392 timestamp: 1655010165.12107 iteration: 2405 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.4952 FastRCNN class loss: 0.18703 FastRCNN total loss: 0.68223 L1 loss: 0.0000e+00 L2 loss: 2.08127 Learning rate: 0.02 Mask loss: 0.63568 RPN box loss: 0.05514 RPN score loss: 0.0218 RPN total loss: 0.07694 Total loss: 3.47612 timestamp: 1655010168.5003216 iteration: 2410 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31781 FastRCNN class loss: 0.11032 FastRCNN total loss: 0.42813 L1 loss: 0.0000e+00 L2 loss: 2.08084 Learning rate: 0.02 Mask loss: 0.50528 RPN box loss: 0.12283 RPN score loss: 0.02555 RPN total loss: 0.14838 Total loss: 3.16263 timestamp: 1655010171.9032369 iteration: 2415 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36084 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.43846 L1 loss: 0.0000e+00 L2 loss: 2.08044 Learning rate: 0.02 Mask loss: 0.47896 RPN box loss: 0.09899 RPN score loss: 0.02203 RPN total loss: 0.12101 Total loss: 3.11887 timestamp: 1655010175.3305945 iteration: 2420 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46357 FastRCNN class loss: 0.1202 FastRCNN total loss: 0.58377 L1 loss: 0.0000e+00 L2 loss: 2.08006 Learning rate: 0.02 Mask loss: 0.48269 RPN box loss: 0.0507 RPN score loss: 0.05781 RPN total loss: 0.10851 Total loss: 3.25504 timestamp: 1655010178.6464717 iteration: 2425 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41299 FastRCNN class loss: 0.1459 FastRCNN total loss: 0.55889 L1 loss: 0.0000e+00 L2 loss: 2.07969 Learning rate: 0.02 Mask loss: 0.50628 RPN box loss: 0.12075 RPN score loss: 0.02479 RPN total loss: 0.14554 Total loss: 3.2904 timestamp: 1655010181.936939 iteration: 2430 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40711 FastRCNN class loss: 0.12033 FastRCNN total loss: 0.52744 L1 loss: 0.0000e+00 L2 loss: 2.07931 Learning rate: 0.02 Mask loss: 0.53866 RPN box loss: 0.05257 RPN score loss: 0.01709 RPN total loss: 0.06965 Total loss: 3.21506 timestamp: 1655010185.3337433 iteration: 2435 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31341 FastRCNN class loss: 0.12695 FastRCNN total loss: 0.44035 L1 loss: 0.0000e+00 L2 loss: 2.07891 Learning rate: 0.02 Mask loss: 0.38325 RPN box loss: 0.02593 RPN score loss: 0.01557 RPN total loss: 0.0415 Total loss: 2.94402 timestamp: 1655010188.6912708 iteration: 2440 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.51397 FastRCNN class loss: 0.15564 FastRCNN total loss: 0.66961 L1 loss: 0.0000e+00 L2 loss: 2.07852 Learning rate: 0.02 Mask loss: 0.61966 RPN box loss: 0.13072 RPN score loss: 0.02144 RPN total loss: 0.15216 Total loss: 3.51996 timestamp: 1655010192.0652912 iteration: 2445 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46553 FastRCNN class loss: 0.19529 FastRCNN total loss: 0.66082 L1 loss: 0.0000e+00 L2 loss: 2.07814 Learning rate: 0.02 Mask loss: 0.65308 RPN box loss: 0.08158 RPN score loss: 0.02102 RPN total loss: 0.10261 Total loss: 3.49465 timestamp: 1655010195.4142 iteration: 2450 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42531 FastRCNN class loss: 0.16561 FastRCNN total loss: 0.59092 L1 loss: 0.0000e+00 L2 loss: 2.07776 Learning rate: 0.02 Mask loss: 0.43388 RPN box loss: 0.05822 RPN score loss: 0.03768 RPN total loss: 0.0959 Total loss: 3.19847 timestamp: 1655010198.7809415 iteration: 2455 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38279 FastRCNN class loss: 0.12337 FastRCNN total loss: 0.50616 L1 loss: 0.0000e+00 L2 loss: 2.07738 Learning rate: 0.02 Mask loss: 0.43646 RPN box loss: 0.0574 RPN score loss: 0.02583 RPN total loss: 0.08323 Total loss: 3.10324 timestamp: 1655010202.1619341 iteration: 2460 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33587 FastRCNN class loss: 0.10618 FastRCNN total loss: 0.44205 L1 loss: 0.0000e+00 L2 loss: 2.07698 Learning rate: 0.02 Mask loss: 0.52446 RPN box loss: 0.04447 RPN score loss: 0.02868 RPN total loss: 0.07314 Total loss: 3.11664 timestamp: 1655010205.5283535 iteration: 2465 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42415 FastRCNN class loss: 0.13027 FastRCNN total loss: 0.55442 L1 loss: 0.0000e+00 L2 loss: 2.07659 Learning rate: 0.02 Mask loss: 0.50453 RPN box loss: 0.07603 RPN score loss: 0.0215 RPN total loss: 0.09752 Total loss: 3.23306 timestamp: 1655010208.8126228 iteration: 2470 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37006 FastRCNN class loss: 0.13309 FastRCNN total loss: 0.50315 L1 loss: 0.0000e+00 L2 loss: 2.0762 Learning rate: 0.02 Mask loss: 0.44423 RPN box loss: 0.04605 RPN score loss: 0.02302 RPN total loss: 0.06907 Total loss: 3.09265 timestamp: 1655010212.1291409 iteration: 2475 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3509 FastRCNN class loss: 0.12267 FastRCNN total loss: 0.47357 L1 loss: 0.0000e+00 L2 loss: 2.07578 Learning rate: 0.02 Mask loss: 0.36224 RPN box loss: 0.06592 RPN score loss: 0.01996 RPN total loss: 0.08588 Total loss: 2.99748 timestamp: 1655010215.4761562 iteration: 2480 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36847 FastRCNN class loss: 0.17005 FastRCNN total loss: 0.53851 L1 loss: 0.0000e+00 L2 loss: 2.07539 Learning rate: 0.02 Mask loss: 0.39506 RPN box loss: 0.08102 RPN score loss: 0.02157 RPN total loss: 0.10259 Total loss: 3.11156 timestamp: 1655010218.8458786 iteration: 2485 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3573 FastRCNN class loss: 0.14472 FastRCNN total loss: 0.50202 L1 loss: 0.0000e+00 L2 loss: 2.07498 Learning rate: 0.02 Mask loss: 0.43771 RPN box loss: 0.15628 RPN score loss: 0.0201 RPN total loss: 0.17638 Total loss: 3.19109 timestamp: 1655010222.3053763 iteration: 2490 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42223 FastRCNN class loss: 0.14519 FastRCNN total loss: 0.56742 L1 loss: 0.0000e+00 L2 loss: 2.07457 Learning rate: 0.02 Mask loss: 0.39159 RPN box loss: 0.03451 RPN score loss: 0.00786 RPN total loss: 0.04238 Total loss: 3.07595 timestamp: 1655010225.6966927 iteration: 2495 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38588 FastRCNN class loss: 0.11729 FastRCNN total loss: 0.50318 L1 loss: 0.0000e+00 L2 loss: 2.07417 Learning rate: 0.02 Mask loss: 0.35949 RPN box loss: 0.03808 RPN score loss: 0.01687 RPN total loss: 0.05495 Total loss: 2.99179 timestamp: 1655010229.1391385 iteration: 2500 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.43189 FastRCNN class loss: 0.1797 FastRCNN total loss: 0.61159 L1 loss: 0.0000e+00 L2 loss: 2.07377 Learning rate: 0.02 Mask loss: 0.42976 RPN box loss: 0.11004 RPN score loss: 0.03582 RPN total loss: 0.14586 Total loss: 3.26097 timestamp: 1655010232.5708363 iteration: 2505 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38437 FastRCNN class loss: 0.12064 FastRCNN total loss: 0.50501 L1 loss: 0.0000e+00 L2 loss: 2.07338 Learning rate: 0.02 Mask loss: 0.50514 RPN box loss: 0.05393 RPN score loss: 0.0227 RPN total loss: 0.07663 Total loss: 3.16016 timestamp: 1655010235.9222393 iteration: 2510 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41713 FastRCNN class loss: 0.16311 FastRCNN total loss: 0.58024 L1 loss: 0.0000e+00 L2 loss: 2.07298 Learning rate: 0.02 Mask loss: 0.48037 RPN box loss: 0.09046 RPN score loss: 0.0401 RPN total loss: 0.13056 Total loss: 3.26415 timestamp: 1655010239.2921472 iteration: 2515 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33252 FastRCNN class loss: 0.13632 FastRCNN total loss: 0.46884 L1 loss: 0.0000e+00 L2 loss: 2.07258 Learning rate: 0.02 Mask loss: 0.51252 RPN box loss: 0.1772 RPN score loss: 0.04164 RPN total loss: 0.21884 Total loss: 3.27278 timestamp: 1655010242.6128335 iteration: 2520 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42814 FastRCNN class loss: 0.17211 FastRCNN total loss: 0.60026 L1 loss: 0.0000e+00 L2 loss: 2.0722 Learning rate: 0.02 Mask loss: 0.43822 RPN box loss: 0.08171 RPN score loss: 0.02075 RPN total loss: 0.10246 Total loss: 3.21313 timestamp: 1655010246.014836 iteration: 2525 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36684 FastRCNN class loss: 0.10684 FastRCNN total loss: 0.47367 L1 loss: 0.0000e+00 L2 loss: 2.0718 Learning rate: 0.02 Mask loss: 0.45286 RPN box loss: 0.12633 RPN score loss: 0.03907 RPN total loss: 0.1654 Total loss: 3.16374 timestamp: 1655010249.3677902 iteration: 2530 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40857 FastRCNN class loss: 0.16133 FastRCNN total loss: 0.5699 L1 loss: 0.0000e+00 L2 loss: 2.07141 Learning rate: 0.02 Mask loss: 0.48949 RPN box loss: 0.04477 RPN score loss: 0.01498 RPN total loss: 0.05975 Total loss: 3.19055 timestamp: 1655010252.6915035 iteration: 2535 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40305 FastRCNN class loss: 0.12762 FastRCNN total loss: 0.53068 L1 loss: 0.0000e+00 L2 loss: 2.07102 Learning rate: 0.02 Mask loss: 0.4126 RPN box loss: 0.04871 RPN score loss: 0.02117 RPN total loss: 0.06987 Total loss: 3.08417 timestamp: 1655010256.0979962 iteration: 2540 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31843 FastRCNN class loss: 0.12455 FastRCNN total loss: 0.44298 L1 loss: 0.0000e+00 L2 loss: 2.07063 Learning rate: 0.02 Mask loss: 0.45354 RPN box loss: 0.0965 RPN score loss: 0.02555 RPN total loss: 0.12205 Total loss: 3.0892 timestamp: 1655010259.4920814 iteration: 2545 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33299 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.42671 L1 loss: 0.0000e+00 L2 loss: 2.07024 Learning rate: 0.02 Mask loss: 0.37966 RPN box loss: 0.12684 RPN score loss: 0.01897 RPN total loss: 0.14581 Total loss: 3.02241 timestamp: 1655010262.7642207 iteration: 2550 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45595 FastRCNN class loss: 0.16884 FastRCNN total loss: 0.62479 L1 loss: 0.0000e+00 L2 loss: 2.06985 Learning rate: 0.02 Mask loss: 0.46758 RPN box loss: 0.04362 RPN score loss: 0.00693 RPN total loss: 0.05054 Total loss: 3.21276 timestamp: 1655010266.0804632 iteration: 2555 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35709 FastRCNN class loss: 0.13296 FastRCNN total loss: 0.49005 L1 loss: 0.0000e+00 L2 loss: 2.06946 Learning rate: 0.02 Mask loss: 0.43628 RPN box loss: 0.11888 RPN score loss: 0.01633 RPN total loss: 0.1352 Total loss: 3.131 timestamp: 1655010269.3956175 iteration: 2560 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37682 FastRCNN class loss: 0.13857 FastRCNN total loss: 0.51539 L1 loss: 0.0000e+00 L2 loss: 2.06908 Learning rate: 0.02 Mask loss: 0.38366 RPN box loss: 0.08952 RPN score loss: 0.03894 RPN total loss: 0.12846 Total loss: 3.09659 timestamp: 1655010272.762295 iteration: 2565 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38383 FastRCNN class loss: 0.15072 FastRCNN total loss: 0.53455 L1 loss: 0.0000e+00 L2 loss: 2.0687 Learning rate: 0.02 Mask loss: 0.39496 RPN box loss: 0.11666 RPN score loss: 0.02754 RPN total loss: 0.14421 Total loss: 3.14242 timestamp: 1655010276.191777 iteration: 2570 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3778 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.46397 L1 loss: 0.0000e+00 L2 loss: 2.0683 Learning rate: 0.02 Mask loss: 0.3751 RPN box loss: 0.01992 RPN score loss: 0.0116 RPN total loss: 0.03152 Total loss: 2.93889 timestamp: 1655010279.515225 iteration: 2575 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.348 FastRCNN class loss: 0.14414 FastRCNN total loss: 0.49214 L1 loss: 0.0000e+00 L2 loss: 2.06793 Learning rate: 0.02 Mask loss: 0.35423 RPN box loss: 0.04256 RPN score loss: 0.01449 RPN total loss: 0.05706 Total loss: 2.97135 timestamp: 1655010282.910468 iteration: 2580 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28892 FastRCNN class loss: 0.11718 FastRCNN total loss: 0.4061 L1 loss: 0.0000e+00 L2 loss: 2.06757 Learning rate: 0.02 Mask loss: 0.30903 RPN box loss: 0.13005 RPN score loss: 0.05722 RPN total loss: 0.18726 Total loss: 2.96995 timestamp: 1655010286.279824 iteration: 2585 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28896 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.34626 L1 loss: 0.0000e+00 L2 loss: 2.06718 Learning rate: 0.02 Mask loss: 0.3939 RPN box loss: 0.05331 RPN score loss: 0.01145 RPN total loss: 0.06476 Total loss: 2.8721 timestamp: 1655010289.5560915 iteration: 2590 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28266 FastRCNN class loss: 0.09716 FastRCNN total loss: 0.37982 L1 loss: 0.0000e+00 L2 loss: 2.06681 Learning rate: 0.02 Mask loss: 0.30839 RPN box loss: 0.02597 RPN score loss: 0.00795 RPN total loss: 0.03392 Total loss: 2.78894 timestamp: 1655010292.9609613 iteration: 2595 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.44153 FastRCNN class loss: 0.17183 FastRCNN total loss: 0.61336 L1 loss: 0.0000e+00 L2 loss: 2.06642 Learning rate: 0.02 Mask loss: 0.49284 RPN box loss: 0.17888 RPN score loss: 0.02413 RPN total loss: 0.203 Total loss: 3.37562 timestamp: 1655010296.3959816 iteration: 2600 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32885 FastRCNN class loss: 0.12642 FastRCNN total loss: 0.45527 L1 loss: 0.0000e+00 L2 loss: 2.06603 Learning rate: 0.02 Mask loss: 0.38539 RPN box loss: 0.05437 RPN score loss: 0.0178 RPN total loss: 0.07217 Total loss: 2.97886 timestamp: 1655010299.828147 iteration: 2605 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31197 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.41132 L1 loss: 0.0000e+00 L2 loss: 2.06565 Learning rate: 0.02 Mask loss: 0.30904 RPN box loss: 0.02195 RPN score loss: 0.00863 RPN total loss: 0.03058 Total loss: 2.81658 timestamp: 1655010303.1938972 iteration: 2610 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31141 FastRCNN class loss: 0.15287 FastRCNN total loss: 0.46429 L1 loss: 0.0000e+00 L2 loss: 2.06526 Learning rate: 0.02 Mask loss: 0.36734 RPN box loss: 0.04857 RPN score loss: 0.01587 RPN total loss: 0.06444 Total loss: 2.96133 timestamp: 1655010306.5088158 iteration: 2615 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3186 FastRCNN class loss: 0.11903 FastRCNN total loss: 0.43763 L1 loss: 0.0000e+00 L2 loss: 2.06488 Learning rate: 0.02 Mask loss: 0.44301 RPN box loss: 0.0656 RPN score loss: 0.03222 RPN total loss: 0.09782 Total loss: 3.04334 timestamp: 1655010309.903681 iteration: 2620 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30215 FastRCNN class loss: 0.11673 FastRCNN total loss: 0.41887 L1 loss: 0.0000e+00 L2 loss: 2.0645 Learning rate: 0.02 Mask loss: 0.44801 RPN box loss: 0.03993 RPN score loss: 0.01825 RPN total loss: 0.05818 Total loss: 2.98956 timestamp: 1655010313.2526746 iteration: 2625 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33519 FastRCNN class loss: 0.11514 FastRCNN total loss: 0.45032 L1 loss: 0.0000e+00 L2 loss: 2.06412 Learning rate: 0.02 Mask loss: 0.32423 RPN box loss: 0.04527 RPN score loss: 0.01426 RPN total loss: 0.05953 Total loss: 2.8982 timestamp: 1655010316.5825067 iteration: 2630 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29505 FastRCNN class loss: 0.11764 FastRCNN total loss: 0.41269 L1 loss: 0.0000e+00 L2 loss: 2.06374 Learning rate: 0.02 Mask loss: 0.35382 RPN box loss: 0.09551 RPN score loss: 0.01819 RPN total loss: 0.1137 Total loss: 2.94395 timestamp: 1655010319.9110951 iteration: 2635 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34532 FastRCNN class loss: 0.12748 FastRCNN total loss: 0.4728 L1 loss: 0.0000e+00 L2 loss: 2.06335 Learning rate: 0.02 Mask loss: 0.3356 RPN box loss: 0.03304 RPN score loss: 0.00812 RPN total loss: 0.04116 Total loss: 2.91291 timestamp: 1655010323.2585387 iteration: 2640 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38814 FastRCNN class loss: 0.12847 FastRCNN total loss: 0.51661 L1 loss: 0.0000e+00 L2 loss: 2.06296 Learning rate: 0.02 Mask loss: 0.31908 RPN box loss: 0.05378 RPN score loss: 0.01376 RPN total loss: 0.06754 Total loss: 2.96618 timestamp: 1655010326.5775273 iteration: 2645 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19919 FastRCNN class loss: 0.0942 FastRCNN total loss: 0.29338 L1 loss: 0.0000e+00 L2 loss: 2.06258 Learning rate: 0.02 Mask loss: 0.2649 RPN box loss: 0.12582 RPN score loss: 0.01775 RPN total loss: 0.14356 Total loss: 2.76442 timestamp: 1655010329.8595052 iteration: 2650 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26304 FastRCNN class loss: 0.10178 FastRCNN total loss: 0.36482 L1 loss: 0.0000e+00 L2 loss: 2.06219 Learning rate: 0.02 Mask loss: 0.2881 RPN box loss: 0.02935 RPN score loss: 0.02775 RPN total loss: 0.0571 Total loss: 2.77221 timestamp: 1655010333.1995165 iteration: 2655 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2647 FastRCNN class loss: 0.08986 FastRCNN total loss: 0.35456 L1 loss: 0.0000e+00 L2 loss: 2.0618 Learning rate: 0.02 Mask loss: 0.38299 RPN box loss: 0.05018 RPN score loss: 0.03234 RPN total loss: 0.08252 Total loss: 2.88187 timestamp: 1655010336.601069 iteration: 2660 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34236 FastRCNN class loss: 0.10863 FastRCNN total loss: 0.45099 L1 loss: 0.0000e+00 L2 loss: 2.06141 Learning rate: 0.02 Mask loss: 0.39223 RPN box loss: 0.05095 RPN score loss: 0.01135 RPN total loss: 0.0623 Total loss: 2.96692 timestamp: 1655010339.9738202 iteration: 2665 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34285 FastRCNN class loss: 0.1718 FastRCNN total loss: 0.51465 L1 loss: 0.0000e+00 L2 loss: 2.06103 Learning rate: 0.02 Mask loss: 0.34953 RPN box loss: 0.06298 RPN score loss: 0.02069 RPN total loss: 0.08367 Total loss: 3.00887 timestamp: 1655010343.3084106 iteration: 2670 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34247 FastRCNN class loss: 0.10677 FastRCNN total loss: 0.44924 L1 loss: 0.0000e+00 L2 loss: 2.06063 Learning rate: 0.02 Mask loss: 0.33822 RPN box loss: 0.065 RPN score loss: 0.01705 RPN total loss: 0.08204 Total loss: 2.93014 timestamp: 1655010346.607439 iteration: 2675 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35197 FastRCNN class loss: 0.12474 FastRCNN total loss: 0.47671 L1 loss: 0.0000e+00 L2 loss: 2.06025 Learning rate: 0.02 Mask loss: 0.37485 RPN box loss: 0.02924 RPN score loss: 0.0179 RPN total loss: 0.04714 Total loss: 2.95895 timestamp: 1655010350.0757856 iteration: 2680 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3524 FastRCNN class loss: 0.16431 FastRCNN total loss: 0.51671 L1 loss: 0.0000e+00 L2 loss: 2.05988 Learning rate: 0.02 Mask loss: 0.41921 RPN box loss: 0.07284 RPN score loss: 0.01747 RPN total loss: 0.09031 Total loss: 3.0861 timestamp: 1655010353.4887888 iteration: 2685 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31647 FastRCNN class loss: 0.13973 FastRCNN total loss: 0.4562 L1 loss: 0.0000e+00 L2 loss: 2.05949 Learning rate: 0.02 Mask loss: 0.36102 RPN box loss: 0.13704 RPN score loss: 0.02392 RPN total loss: 0.16096 Total loss: 3.03767 timestamp: 1655010356.840506 iteration: 2690 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39193 FastRCNN class loss: 0.27435 FastRCNN total loss: 0.66627 L1 loss: 0.0000e+00 L2 loss: 2.05911 Learning rate: 0.02 Mask loss: 0.38761 RPN box loss: 0.15022 RPN score loss: 0.03465 RPN total loss: 0.18487 Total loss: 3.29787 timestamp: 1655010360.2752934 iteration: 2695 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28493 FastRCNN class loss: 0.08763 FastRCNN total loss: 0.37255 L1 loss: 0.0000e+00 L2 loss: 2.05873 Learning rate: 0.02 Mask loss: 0.31893 RPN box loss: 0.06268 RPN score loss: 0.01099 RPN total loss: 0.07367 Total loss: 2.82388 timestamp: 1655010363.6262007 iteration: 2700 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3041 FastRCNN class loss: 0.10828 FastRCNN total loss: 0.41238 L1 loss: 0.0000e+00 L2 loss: 2.05834 Learning rate: 0.02 Mask loss: 0.33467 RPN box loss: 0.08287 RPN score loss: 0.01438 RPN total loss: 0.09726 Total loss: 2.90264 timestamp: 1655010366.999834 iteration: 2705 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33939 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.44453 L1 loss: 0.0000e+00 L2 loss: 2.05797 Learning rate: 0.02 Mask loss: 0.35682 RPN box loss: 0.10001 RPN score loss: 0.04052 RPN total loss: 0.14053 Total loss: 2.99984 timestamp: 1655010370.3044014 iteration: 2710 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23916 FastRCNN class loss: 0.09894 FastRCNN total loss: 0.3381 L1 loss: 0.0000e+00 L2 loss: 2.05758 Learning rate: 0.02 Mask loss: 0.27704 RPN box loss: 0.02083 RPN score loss: 0.00937 RPN total loss: 0.03019 Total loss: 2.70291 timestamp: 1655010373.6768675 iteration: 2715 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20382 FastRCNN class loss: 0.11984 FastRCNN total loss: 0.32365 L1 loss: 0.0000e+00 L2 loss: 2.05721 Learning rate: 0.02 Mask loss: 0.28917 RPN box loss: 0.07672 RPN score loss: 0.02606 RPN total loss: 0.10278 Total loss: 2.77281 timestamp: 1655010377.081123 iteration: 2720 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3004 FastRCNN class loss: 0.12038 FastRCNN total loss: 0.42077 L1 loss: 0.0000e+00 L2 loss: 2.05681 Learning rate: 0.02 Mask loss: 0.39083 RPN box loss: 0.05148 RPN score loss: 0.03643 RPN total loss: 0.08791 Total loss: 2.95632 timestamp: 1655010380.484431 iteration: 2725 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35427 FastRCNN class loss: 0.15632 FastRCNN total loss: 0.51059 L1 loss: 0.0000e+00 L2 loss: 2.05643 Learning rate: 0.02 Mask loss: 0.40482 RPN box loss: 0.06151 RPN score loss: 0.0218 RPN total loss: 0.08331 Total loss: 3.05516 timestamp: 1655010383.9044666 iteration: 2730 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21512 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.30777 L1 loss: 0.0000e+00 L2 loss: 2.05604 Learning rate: 0.02 Mask loss: 0.22923 RPN box loss: 0.08954 RPN score loss: 0.01625 RPN total loss: 0.1058 Total loss: 2.69883 timestamp: 1655010387.3612206 iteration: 2735 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22903 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.33016 L1 loss: 0.0000e+00 L2 loss: 2.05567 Learning rate: 0.02 Mask loss: 0.27554 RPN box loss: 0.04681 RPN score loss: 0.01897 RPN total loss: 0.06578 Total loss: 2.72716 timestamp: 1655010390.819337 iteration: 2740 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37791 FastRCNN class loss: 0.12515 FastRCNN total loss: 0.50307 L1 loss: 0.0000e+00 L2 loss: 2.05529 Learning rate: 0.02 Mask loss: 0.35239 RPN box loss: 0.12398 RPN score loss: 0.01382 RPN total loss: 0.1378 Total loss: 3.04854 timestamp: 1655010394.2054467 iteration: 2745 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2793 FastRCNN class loss: 0.11571 FastRCNN total loss: 0.39501 L1 loss: 0.0000e+00 L2 loss: 2.0549 Learning rate: 0.02 Mask loss: 0.25729 RPN box loss: 0.08544 RPN score loss: 0.0363 RPN total loss: 0.12174 Total loss: 2.82894 timestamp: 1655010397.5239117 iteration: 2750 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.46396 FastRCNN class loss: 0.13971 FastRCNN total loss: 0.60367 L1 loss: 0.0000e+00 L2 loss: 2.0545 Learning rate: 0.02 Mask loss: 0.39846 RPN box loss: 0.07121 RPN score loss: 0.01267 RPN total loss: 0.08389 Total loss: 3.14052 timestamp: 1655010400.9041615 iteration: 2755 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.41919 FastRCNN class loss: 0.17207 FastRCNN total loss: 0.59126 L1 loss: 0.0000e+00 L2 loss: 2.05413 Learning rate: 0.02 Mask loss: 0.47862 RPN box loss: 0.04623 RPN score loss: 0.01891 RPN total loss: 0.06515 Total loss: 3.18916 timestamp: 1655010404.3086214 iteration: 2760 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35093 FastRCNN class loss: 0.24795 FastRCNN total loss: 0.59888 L1 loss: 0.0000e+00 L2 loss: 2.05378 Learning rate: 0.02 Mask loss: 0.35211 RPN box loss: 0.04722 RPN score loss: 0.02276 RPN total loss: 0.06998 Total loss: 3.07474 timestamp: 1655010407.713919 iteration: 2765 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33242 FastRCNN class loss: 0.14114 FastRCNN total loss: 0.47356 L1 loss: 0.0000e+00 L2 loss: 2.05342 Learning rate: 0.02 Mask loss: 0.37723 RPN box loss: 0.04354 RPN score loss: 0.0267 RPN total loss: 0.07024 Total loss: 2.97445 timestamp: 1655010411.0897653 iteration: 2770 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31488 FastRCNN class loss: 0.14678 FastRCNN total loss: 0.46167 L1 loss: 0.0000e+00 L2 loss: 2.05302 Learning rate: 0.02 Mask loss: 0.35673 RPN box loss: 0.09018 RPN score loss: 0.01703 RPN total loss: 0.10722 Total loss: 2.97863 timestamp: 1655010414.5451422 iteration: 2775 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27534 FastRCNN class loss: 0.09999 FastRCNN total loss: 0.37533 L1 loss: 0.0000e+00 L2 loss: 2.05264 Learning rate: 0.02 Mask loss: 0.26138 RPN box loss: 0.05566 RPN score loss: 0.03929 RPN total loss: 0.09495 Total loss: 2.78431 timestamp: 1655010417.9534311 iteration: 2780 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27844 FastRCNN class loss: 0.10958 FastRCNN total loss: 0.38802 L1 loss: 0.0000e+00 L2 loss: 2.05227 Learning rate: 0.02 Mask loss: 0.29591 RPN box loss: 0.02415 RPN score loss: 0.00686 RPN total loss: 0.03101 Total loss: 2.76721 timestamp: 1655010421.4102714 iteration: 2785 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25914 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.33492 L1 loss: 0.0000e+00 L2 loss: 2.0519 Learning rate: 0.02 Mask loss: 0.31321 RPN box loss: 0.11347 RPN score loss: 0.01762 RPN total loss: 0.13109 Total loss: 2.83112 timestamp: 1655010424.8325317 iteration: 2790 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2487 FastRCNN class loss: 0.11503 FastRCNN total loss: 0.36373 L1 loss: 0.0000e+00 L2 loss: 2.05149 Learning rate: 0.02 Mask loss: 0.32716 RPN box loss: 0.02924 RPN score loss: 0.01249 RPN total loss: 0.04173 Total loss: 2.78411 timestamp: 1655010428.236777 iteration: 2795 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26356 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.35068 L1 loss: 0.0000e+00 L2 loss: 2.05113 Learning rate: 0.02 Mask loss: 0.26282 RPN box loss: 0.02306 RPN score loss: 0.00888 RPN total loss: 0.03194 Total loss: 2.69656 timestamp: 1655010431.539615 iteration: 2800 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.45448 FastRCNN class loss: 0.13005 FastRCNN total loss: 0.58453 L1 loss: 0.0000e+00 L2 loss: 2.05075 Learning rate: 0.02 Mask loss: 0.40363 RPN box loss: 0.08502 RPN score loss: 0.02995 RPN total loss: 0.11497 Total loss: 3.15388 timestamp: 1655010434.928582 iteration: 2805 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20769 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.27519 L1 loss: 0.0000e+00 L2 loss: 2.05033 Learning rate: 0.02 Mask loss: 0.27539 RPN box loss: 0.07894 RPN score loss: 0.01325 RPN total loss: 0.09219 Total loss: 2.69311 timestamp: 1655010438.2640696 iteration: 2810 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31333 FastRCNN class loss: 0.17149 FastRCNN total loss: 0.48482 L1 loss: 0.0000e+00 L2 loss: 2.04995 Learning rate: 0.02 Mask loss: 0.48299 RPN box loss: 0.07775 RPN score loss: 0.01764 RPN total loss: 0.09538 Total loss: 3.11314 timestamp: 1655010441.618607 iteration: 2815 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29823 FastRCNN class loss: 0.12206 FastRCNN total loss: 0.42029 L1 loss: 0.0000e+00 L2 loss: 2.04957 Learning rate: 0.02 Mask loss: 0.30595 RPN box loss: 0.02523 RPN score loss: 0.00833 RPN total loss: 0.03356 Total loss: 2.80936 timestamp: 1655010444.9369535 iteration: 2820 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34629 FastRCNN class loss: 0.11783 FastRCNN total loss: 0.46412 L1 loss: 0.0000e+00 L2 loss: 2.04917 Learning rate: 0.02 Mask loss: 0.30288 RPN box loss: 0.05582 RPN score loss: 0.0167 RPN total loss: 0.07253 Total loss: 2.88871 timestamp: 1655010448.3429718 iteration: 2825 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33779 FastRCNN class loss: 0.11459 FastRCNN total loss: 0.45238 L1 loss: 0.0000e+00 L2 loss: 2.04878 Learning rate: 0.02 Mask loss: 0.3853 RPN box loss: 0.09111 RPN score loss: 0.01388 RPN total loss: 0.105 Total loss: 2.99145 timestamp: 1655010451.6982827 iteration: 2830 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2069 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.30574 L1 loss: 0.0000e+00 L2 loss: 2.0484 Learning rate: 0.02 Mask loss: 0.30211 RPN box loss: 0.07243 RPN score loss: 0.02051 RPN total loss: 0.09294 Total loss: 2.7492 timestamp: 1655010455.0397222 iteration: 2835 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22879 FastRCNN class loss: 0.0999 FastRCNN total loss: 0.32869 L1 loss: 0.0000e+00 L2 loss: 2.04801 Learning rate: 0.02 Mask loss: 0.26221 RPN box loss: 0.07146 RPN score loss: 0.03584 RPN total loss: 0.1073 Total loss: 2.74621 timestamp: 1655010458.3344414 iteration: 2840 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27791 FastRCNN class loss: 0.11993 FastRCNN total loss: 0.39783 L1 loss: 0.0000e+00 L2 loss: 2.04763 Learning rate: 0.02 Mask loss: 0.43997 RPN box loss: 0.11055 RPN score loss: 0.03571 RPN total loss: 0.14626 Total loss: 3.0317 timestamp: 1655010461.6054978 iteration: 2845 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26173 FastRCNN class loss: 0.1023 FastRCNN total loss: 0.36403 L1 loss: 0.0000e+00 L2 loss: 2.04723 Learning rate: 0.02 Mask loss: 0.29882 RPN box loss: 0.0492 RPN score loss: 0.01695 RPN total loss: 0.06615 Total loss: 2.77622 timestamp: 1655010464.9712484 iteration: 2850 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20595 FastRCNN class loss: 0.09603 FastRCNN total loss: 0.30199 L1 loss: 0.0000e+00 L2 loss: 2.04682 Learning rate: 0.02 Mask loss: 0.26806 RPN box loss: 0.04279 RPN score loss: 0.02456 RPN total loss: 0.06735 Total loss: 2.68421 timestamp: 1655010468.2542038 iteration: 2855 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26543 FastRCNN class loss: 0.11497 FastRCNN total loss: 0.3804 L1 loss: 0.0000e+00 L2 loss: 2.04645 Learning rate: 0.02 Mask loss: 0.29159 RPN box loss: 0.07509 RPN score loss: 0.02678 RPN total loss: 0.10187 Total loss: 2.82032 timestamp: 1655010471.6009672 iteration: 2860 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24488 FastRCNN class loss: 0.11899 FastRCNN total loss: 0.36387 L1 loss: 0.0000e+00 L2 loss: 2.04606 Learning rate: 0.02 Mask loss: 0.29145 RPN box loss: 0.05928 RPN score loss: 0.00778 RPN total loss: 0.06706 Total loss: 2.76845 timestamp: 1655010474.9734657 iteration: 2865 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22991 FastRCNN class loss: 0.09427 FastRCNN total loss: 0.32418 L1 loss: 0.0000e+00 L2 loss: 2.04568 Learning rate: 0.02 Mask loss: 0.34765 RPN box loss: 0.04654 RPN score loss: 0.0089 RPN total loss: 0.05543 Total loss: 2.77293 timestamp: 1655010478.35107 iteration: 2870 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3096 FastRCNN class loss: 0.11704 FastRCNN total loss: 0.42664 L1 loss: 0.0000e+00 L2 loss: 2.04529 Learning rate: 0.02 Mask loss: 0.34971 RPN box loss: 0.09451 RPN score loss: 0.02342 RPN total loss: 0.11793 Total loss: 2.93956 timestamp: 1655010481.7154758 iteration: 2875 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3 FastRCNN class loss: 0.12962 FastRCNN total loss: 0.42962 L1 loss: 0.0000e+00 L2 loss: 2.0449 Learning rate: 0.02 Mask loss: 0.34302 RPN box loss: 0.04003 RPN score loss: 0.01286 RPN total loss: 0.05289 Total loss: 2.87043 timestamp: 1655010484.9627028 iteration: 2880 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28539 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.37504 L1 loss: 0.0000e+00 L2 loss: 2.04451 Learning rate: 0.02 Mask loss: 0.30869 RPN box loss: 0.01896 RPN score loss: 0.00723 RPN total loss: 0.0262 Total loss: 2.75444 timestamp: 1655010488.3188884 iteration: 2885 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25186 FastRCNN class loss: 0.12102 FastRCNN total loss: 0.37289 L1 loss: 0.0000e+00 L2 loss: 2.04414 Learning rate: 0.02 Mask loss: 0.33102 RPN box loss: 0.03316 RPN score loss: 0.00716 RPN total loss: 0.04032 Total loss: 2.78836 timestamp: 1655010491.716072 iteration: 2890 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38913 FastRCNN class loss: 0.13452 FastRCNN total loss: 0.52365 L1 loss: 0.0000e+00 L2 loss: 2.04374 Learning rate: 0.02 Mask loss: 0.45924 RPN box loss: 0.06812 RPN score loss: 0.03818 RPN total loss: 0.10631 Total loss: 3.13294 timestamp: 1655010495.0915458 iteration: 2895 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25298 FastRCNN class loss: 0.12212 FastRCNN total loss: 0.3751 L1 loss: 0.0000e+00 L2 loss: 2.04335 Learning rate: 0.02 Mask loss: 0.30494 RPN box loss: 0.14188 RPN score loss: 0.01627 RPN total loss: 0.15815 Total loss: 2.88154 timestamp: 1655010498.5095134 iteration: 2900 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25183 FastRCNN class loss: 0.14691 FastRCNN total loss: 0.39875 L1 loss: 0.0000e+00 L2 loss: 2.04296 Learning rate: 0.02 Mask loss: 0.27963 RPN box loss: 0.12911 RPN score loss: 0.02865 RPN total loss: 0.15776 Total loss: 2.8791 timestamp: 1655010501.8464804 iteration: 2905 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30916 FastRCNN class loss: 0.12343 FastRCNN total loss: 0.43259 L1 loss: 0.0000e+00 L2 loss: 2.04259 Learning rate: 0.02 Mask loss: 0.273 RPN box loss: 0.13119 RPN score loss: 0.01912 RPN total loss: 0.15031 Total loss: 2.8985 timestamp: 1655010505.194261 iteration: 2910 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3812 FastRCNN class loss: 0.15915 FastRCNN total loss: 0.54035 L1 loss: 0.0000e+00 L2 loss: 2.0422 Learning rate: 0.02 Mask loss: 0.35293 RPN box loss: 0.07964 RPN score loss: 0.02462 RPN total loss: 0.10426 Total loss: 3.03974 timestamp: 1655010508.6275115 iteration: 2915 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21897 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.28677 L1 loss: 0.0000e+00 L2 loss: 2.04181 Learning rate: 0.02 Mask loss: 0.22028 RPN box loss: 0.00581 RPN score loss: 0.00915 RPN total loss: 0.01496 Total loss: 2.56382 timestamp: 1655010512.1290433 iteration: 2920 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30305 FastRCNN class loss: 0.14065 FastRCNN total loss: 0.44371 L1 loss: 0.0000e+00 L2 loss: 2.04142 Learning rate: 0.02 Mask loss: 0.3456 RPN box loss: 0.05945 RPN score loss: 0.03292 RPN total loss: 0.09237 Total loss: 2.9231 timestamp: 1655010515.4321096 iteration: 2925 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40128 FastRCNN class loss: 0.16427 FastRCNN total loss: 0.56555 L1 loss: 0.0000e+00 L2 loss: 2.04105 Learning rate: 0.02 Mask loss: 0.68086 RPN box loss: 0.07514 RPN score loss: 0.00776 RPN total loss: 0.0829 Total loss: 3.37036 timestamp: 1655010518.7840273 iteration: 2930 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29607 FastRCNN class loss: 0.14132 FastRCNN total loss: 0.43739 L1 loss: 0.0000e+00 L2 loss: 2.04064 Learning rate: 0.02 Mask loss: 0.31944 RPN box loss: 0.10231 RPN score loss: 0.01495 RPN total loss: 0.11726 Total loss: 2.91472 timestamp: 1655010522.1688716 iteration: 2935 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30182 FastRCNN class loss: 0.1475 FastRCNN total loss: 0.44932 L1 loss: 0.0000e+00 L2 loss: 2.04025 Learning rate: 0.02 Mask loss: 0.35564 RPN box loss: 0.09198 RPN score loss: 0.01696 RPN total loss: 0.10894 Total loss: 2.95416 timestamp: 1655010525.5460086 iteration: 2940 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18651 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.26971 L1 loss: 0.0000e+00 L2 loss: 2.03988 Learning rate: 0.02 Mask loss: 0.43194 RPN box loss: 0.04749 RPN score loss: 0.01256 RPN total loss: 0.06004 Total loss: 2.80157 timestamp: 1655010528.9230173 iteration: 2945 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24675 FastRCNN class loss: 0.10293 FastRCNN total loss: 0.34968 L1 loss: 0.0000e+00 L2 loss: 2.03948 Learning rate: 0.02 Mask loss: 0.25982 RPN box loss: 0.06786 RPN score loss: 0.0615 RPN total loss: 0.12936 Total loss: 2.77835 timestamp: 1655010532.3896224 iteration: 2950 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32199 FastRCNN class loss: 0.12351 FastRCNN total loss: 0.4455 L1 loss: 0.0000e+00 L2 loss: 2.03909 Learning rate: 0.02 Mask loss: 0.26921 RPN box loss: 0.09842 RPN score loss: 0.01181 RPN total loss: 0.11022 Total loss: 2.86402 timestamp: 1655010535.7898583 iteration: 2955 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33431 FastRCNN class loss: 0.12034 FastRCNN total loss: 0.45465 L1 loss: 0.0000e+00 L2 loss: 2.03869 Learning rate: 0.02 Mask loss: 0.3089 RPN box loss: 0.01903 RPN score loss: 0.01507 RPN total loss: 0.0341 Total loss: 2.83634 timestamp: 1655010539.1976845 iteration: 2960 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25236 FastRCNN class loss: 0.14101 FastRCNN total loss: 0.39337 L1 loss: 0.0000e+00 L2 loss: 2.03829 Learning rate: 0.02 Mask loss: 0.39081 RPN box loss: 0.04275 RPN score loss: 0.0073 RPN total loss: 0.05005 Total loss: 2.87253 timestamp: 1655010542.5239344 iteration: 2965 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3434 FastRCNN class loss: 0.12636 FastRCNN total loss: 0.46976 L1 loss: 0.0000e+00 L2 loss: 2.03792 Learning rate: 0.02 Mask loss: 0.28827 RPN box loss: 0.05312 RPN score loss: 0.02687 RPN total loss: 0.07999 Total loss: 2.87594 timestamp: 1655010545.86318 iteration: 2970 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33277 FastRCNN class loss: 0.14008 FastRCNN total loss: 0.47285 L1 loss: 0.0000e+00 L2 loss: 2.03754 Learning rate: 0.02 Mask loss: 0.34758 RPN box loss: 0.06437 RPN score loss: 0.0428 RPN total loss: 0.10717 Total loss: 2.96514 timestamp: 1655010549.1376324 iteration: 2975 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19148 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.25611 L1 loss: 0.0000e+00 L2 loss: 2.03715 Learning rate: 0.02 Mask loss: 0.247 RPN box loss: 0.02188 RPN score loss: 0.00734 RPN total loss: 0.02922 Total loss: 2.56948 timestamp: 1655010552.435778 iteration: 2980 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3238 FastRCNN class loss: 0.11017 FastRCNN total loss: 0.43398 L1 loss: 0.0000e+00 L2 loss: 2.03677 Learning rate: 0.02 Mask loss: 0.35513 RPN box loss: 0.03138 RPN score loss: 0.00698 RPN total loss: 0.03836 Total loss: 2.86424 timestamp: 1655010555.7286556 iteration: 2985 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25817 FastRCNN class loss: 0.09467 FastRCNN total loss: 0.35283 L1 loss: 0.0000e+00 L2 loss: 2.03638 Learning rate: 0.02 Mask loss: 0.29201 RPN box loss: 0.04152 RPN score loss: 0.01544 RPN total loss: 0.05696 Total loss: 2.73818 timestamp: 1655010559.1087725 iteration: 2990 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26391 FastRCNN class loss: 0.09272 FastRCNN total loss: 0.35663 L1 loss: 0.0000e+00 L2 loss: 2.03598 Learning rate: 0.02 Mask loss: 0.29148 RPN box loss: 0.05201 RPN score loss: 0.02031 RPN total loss: 0.07232 Total loss: 2.75641 timestamp: 1655010562.4277353 iteration: 2995 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17947 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.27091 L1 loss: 0.0000e+00 L2 loss: 2.03561 Learning rate: 0.02 Mask loss: 0.23989 RPN box loss: 0.08758 RPN score loss: 0.02201 RPN total loss: 0.10959 Total loss: 2.656 timestamp: 1655010565.6958153 iteration: 3000 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18854 FastRCNN class loss: 0.10057 FastRCNN total loss: 0.28911 L1 loss: 0.0000e+00 L2 loss: 2.03521 Learning rate: 0.02 Mask loss: 0.23854 RPN box loss: 0.06113 RPN score loss: 0.01704 RPN total loss: 0.07817 Total loss: 2.64103 timestamp: 1655010569.0818367 iteration: 3005 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.38408 FastRCNN class loss: 0.15753 FastRCNN total loss: 0.54161 L1 loss: 0.0000e+00 L2 loss: 2.03483 Learning rate: 0.02 Mask loss: 0.39178 RPN box loss: 0.01756 RPN score loss: 0.03007 RPN total loss: 0.04763 Total loss: 3.01584 timestamp: 1655010572.5496588 iteration: 3010 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22022 FastRCNN class loss: 0.15332 FastRCNN total loss: 0.37354 L1 loss: 0.0000e+00 L2 loss: 2.03443 Learning rate: 0.02 Mask loss: 0.37155 RPN box loss: 0.05209 RPN score loss: 0.03115 RPN total loss: 0.08324 Total loss: 2.86276 timestamp: 1655010575.9213123 iteration: 3015 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2723 FastRCNN class loss: 0.14703 FastRCNN total loss: 0.41933 L1 loss: 0.0000e+00 L2 loss: 2.03403 Learning rate: 0.02 Mask loss: 0.26658 RPN box loss: 0.07507 RPN score loss: 0.01735 RPN total loss: 0.09242 Total loss: 2.81236 timestamp: 1655010579.272465 iteration: 3020 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20496 FastRCNN class loss: 0.07085 FastRCNN total loss: 0.27581 L1 loss: 0.0000e+00 L2 loss: 2.03365 Learning rate: 0.02 Mask loss: 0.26462 RPN box loss: 0.02794 RPN score loss: 0.00636 RPN total loss: 0.0343 Total loss: 2.60838 timestamp: 1655010582.626633 iteration: 3025 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29631 FastRCNN class loss: 0.11236 FastRCNN total loss: 0.40867 L1 loss: 0.0000e+00 L2 loss: 2.03327 Learning rate: 0.02 Mask loss: 0.28336 RPN box loss: 0.05725 RPN score loss: 0.01756 RPN total loss: 0.07482 Total loss: 2.80012 timestamp: 1655010585.9584055 iteration: 3030 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2108 FastRCNN class loss: 0.10299 FastRCNN total loss: 0.31379 L1 loss: 0.0000e+00 L2 loss: 2.03286 Learning rate: 0.02 Mask loss: 0.44041 RPN box loss: 0.06491 RPN score loss: 0.02246 RPN total loss: 0.08737 Total loss: 2.87444 timestamp: 1655010589.353527 iteration: 3035 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23546 FastRCNN class loss: 0.10365 FastRCNN total loss: 0.33911 L1 loss: 0.0000e+00 L2 loss: 2.03248 Learning rate: 0.02 Mask loss: 0.26276 RPN box loss: 0.01329 RPN score loss: 0.00659 RPN total loss: 0.01988 Total loss: 2.65423 timestamp: 1655010592.749333 iteration: 3040 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30373 FastRCNN class loss: 0.08879 FastRCNN total loss: 0.39252 L1 loss: 0.0000e+00 L2 loss: 2.03209 Learning rate: 0.02 Mask loss: 0.31533 RPN box loss: 0.10356 RPN score loss: 0.03279 RPN total loss: 0.13635 Total loss: 2.8763 timestamp: 1655010596.183947 iteration: 3045 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36146 FastRCNN class loss: 0.11072 FastRCNN total loss: 0.47218 L1 loss: 0.0000e+00 L2 loss: 2.03169 Learning rate: 0.02 Mask loss: 0.30518 RPN box loss: 0.1159 RPN score loss: 0.01512 RPN total loss: 0.13102 Total loss: 2.94007 timestamp: 1655010599.5620544 iteration: 3050 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22353 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.31488 L1 loss: 0.0000e+00 L2 loss: 2.03131 Learning rate: 0.02 Mask loss: 0.33787 RPN box loss: 0.06594 RPN score loss: 0.02114 RPN total loss: 0.08708 Total loss: 2.77113 timestamp: 1655010602.895773 iteration: 3055 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19065 FastRCNN class loss: 0.08348 FastRCNN total loss: 0.27413 L1 loss: 0.0000e+00 L2 loss: 2.03091 Learning rate: 0.02 Mask loss: 0.2686 RPN box loss: 0.07485 RPN score loss: 0.05136 RPN total loss: 0.1262 Total loss: 2.69984 timestamp: 1655010606.2212455 iteration: 3060 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27443 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.37003 L1 loss: 0.0000e+00 L2 loss: 2.03052 Learning rate: 0.02 Mask loss: 0.23207 RPN box loss: 0.04688 RPN score loss: 0.02413 RPN total loss: 0.07101 Total loss: 2.70363 timestamp: 1655010609.591062 iteration: 3065 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27686 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.34792 L1 loss: 0.0000e+00 L2 loss: 2.03014 Learning rate: 0.02 Mask loss: 0.22186 RPN box loss: 0.04409 RPN score loss: 0.02008 RPN total loss: 0.06417 Total loss: 2.6641 timestamp: 1655010612.975722 iteration: 3070 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25397 FastRCNN class loss: 0.10775 FastRCNN total loss: 0.36171 L1 loss: 0.0000e+00 L2 loss: 2.02976 Learning rate: 0.02 Mask loss: 0.32327 RPN box loss: 0.10323 RPN score loss: 0.0189 RPN total loss: 0.12213 Total loss: 2.83687 timestamp: 1655010616.4012933 iteration: 3075 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25444 FastRCNN class loss: 0.09227 FastRCNN total loss: 0.34672 L1 loss: 0.0000e+00 L2 loss: 2.02938 Learning rate: 0.02 Mask loss: 0.24553 RPN box loss: 0.1188 RPN score loss: 0.02085 RPN total loss: 0.13966 Total loss: 2.76129 timestamp: 1655010619.798642 iteration: 3080 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18616 FastRCNN class loss: 0.0628 FastRCNN total loss: 0.24896 L1 loss: 0.0000e+00 L2 loss: 2.029 Learning rate: 0.02 Mask loss: 0.27468 RPN box loss: 0.11605 RPN score loss: 0.00839 RPN total loss: 0.12444 Total loss: 2.67708 timestamp: 1655010623.151136 iteration: 3085 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18688 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.27536 L1 loss: 0.0000e+00 L2 loss: 2.0286 Learning rate: 0.02 Mask loss: 0.3538 RPN box loss: 0.10684 RPN score loss: 0.01829 RPN total loss: 0.12513 Total loss: 2.78288 timestamp: 1655010626.536833 iteration: 3090 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22955 FastRCNN class loss: 0.08916 FastRCNN total loss: 0.3187 L1 loss: 0.0000e+00 L2 loss: 2.02824 Learning rate: 0.02 Mask loss: 0.29421 RPN box loss: 0.06757 RPN score loss: 0.01605 RPN total loss: 0.08363 Total loss: 2.72478 timestamp: 1655010629.9155924 iteration: 3095 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30597 FastRCNN class loss: 0.18397 FastRCNN total loss: 0.48994 L1 loss: 0.0000e+00 L2 loss: 2.02785 Learning rate: 0.02 Mask loss: 0.43498 RPN box loss: 0.05351 RPN score loss: 0.03027 RPN total loss: 0.08377 Total loss: 3.03654 timestamp: 1655010633.3215055 iteration: 3100 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18548 FastRCNN class loss: 0.11121 FastRCNN total loss: 0.29669 L1 loss: 0.0000e+00 L2 loss: 2.02745 Learning rate: 0.02 Mask loss: 0.3355 RPN box loss: 0.10005 RPN score loss: 0.04265 RPN total loss: 0.1427 Total loss: 2.80234 timestamp: 1655010636.7001882 iteration: 3105 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24067 FastRCNN class loss: 0.12661 FastRCNN total loss: 0.36728 L1 loss: 0.0000e+00 L2 loss: 2.02706 Learning rate: 0.02 Mask loss: 0.28686 RPN box loss: 0.12396 RPN score loss: 0.02965 RPN total loss: 0.15362 Total loss: 2.8348 timestamp: 1655010640.0611026 iteration: 3110 throughput: 23.8 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33389 FastRCNN class loss: 0.1842 FastRCNN total loss: 0.51809 L1 loss: 0.0000e+00 L2 loss: 2.02667 Learning rate: 0.02 Mask loss: 0.38097 RPN box loss: 0.07147 RPN score loss: 0.01527 RPN total loss: 0.08674 Total loss: 3.01248 timestamp: 1655010643.35558 iteration: 3115 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16994 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.25048 L1 loss: 0.0000e+00 L2 loss: 2.02629 Learning rate: 0.02 Mask loss: 0.25615 RPN box loss: 0.08159 RPN score loss: 0.01739 RPN total loss: 0.09898 Total loss: 2.6319 timestamp: 1655010646.5934713 iteration: 3120 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32087 FastRCNN class loss: 0.15656 FastRCNN total loss: 0.47743 L1 loss: 0.0000e+00 L2 loss: 2.02588 Learning rate: 0.02 Mask loss: 0.34765 RPN box loss: 0.07979 RPN score loss: 0.01684 RPN total loss: 0.09663 Total loss: 2.94759 timestamp: 1655010649.8273566 iteration: 3125 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24606 FastRCNN class loss: 0.12524 FastRCNN total loss: 0.3713 L1 loss: 0.0000e+00 L2 loss: 2.02549 Learning rate: 0.02 Mask loss: 0.21983 RPN box loss: 0.06873 RPN score loss: 0.01546 RPN total loss: 0.08419 Total loss: 2.70081 timestamp: 1655010653.1937058 iteration: 3130 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23434 FastRCNN class loss: 0.07998 FastRCNN total loss: 0.31432 L1 loss: 0.0000e+00 L2 loss: 2.02509 Learning rate: 0.02 Mask loss: 0.27327 RPN box loss: 0.03713 RPN score loss: 0.00528 RPN total loss: 0.04241 Total loss: 2.65509 timestamp: 1655010656.6174293 iteration: 3135 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32253 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.39752 L1 loss: 0.0000e+00 L2 loss: 2.02472 Learning rate: 0.02 Mask loss: 0.31846 RPN box loss: 0.10758 RPN score loss: 0.02535 RPN total loss: 0.13293 Total loss: 2.87362 timestamp: 1655010660.0338018 iteration: 3140 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17701 FastRCNN class loss: 0.10881 FastRCNN total loss: 0.28583 L1 loss: 0.0000e+00 L2 loss: 2.02434 Learning rate: 0.02 Mask loss: 0.31345 RPN box loss: 0.11867 RPN score loss: 0.03567 RPN total loss: 0.15434 Total loss: 2.77796 timestamp: 1655010663.373809 iteration: 3145 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32345 FastRCNN class loss: 0.12418 FastRCNN total loss: 0.44762 L1 loss: 0.0000e+00 L2 loss: 2.02396 Learning rate: 0.02 Mask loss: 0.34532 RPN box loss: 0.11763 RPN score loss: 0.02055 RPN total loss: 0.13818 Total loss: 2.95508 timestamp: 1655010666.6839018 iteration: 3150 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28111 FastRCNN class loss: 0.14736 FastRCNN total loss: 0.42847 L1 loss: 0.0000e+00 L2 loss: 2.02356 Learning rate: 0.02 Mask loss: 0.33814 RPN box loss: 0.10269 RPN score loss: 0.0139 RPN total loss: 0.11659 Total loss: 2.90677 timestamp: 1655010670.0236537 iteration: 3155 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34713 FastRCNN class loss: 0.12743 FastRCNN total loss: 0.47456 L1 loss: 0.0000e+00 L2 loss: 2.02317 Learning rate: 0.02 Mask loss: 0.3055 RPN box loss: 0.08202 RPN score loss: 0.0215 RPN total loss: 0.10352 Total loss: 2.90675 timestamp: 1655010673.33886 iteration: 3160 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22965 FastRCNN class loss: 0.13791 FastRCNN total loss: 0.36757 L1 loss: 0.0000e+00 L2 loss: 2.02279 Learning rate: 0.02 Mask loss: 0.30026 RPN box loss: 0.09431 RPN score loss: 0.05631 RPN total loss: 0.15062 Total loss: 2.84124 timestamp: 1655010676.6968548 iteration: 3165 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27017 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.36635 L1 loss: 0.0000e+00 L2 loss: 2.02239 Learning rate: 0.02 Mask loss: 0.25439 RPN box loss: 0.06735 RPN score loss: 0.02241 RPN total loss: 0.08976 Total loss: 2.73289 timestamp: 1655010680.0864675 iteration: 3170 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2718 FastRCNN class loss: 0.13749 FastRCNN total loss: 0.40929 L1 loss: 0.0000e+00 L2 loss: 2.02201 Learning rate: 0.02 Mask loss: 0.27025 RPN box loss: 0.11976 RPN score loss: 0.03464 RPN total loss: 0.15439 Total loss: 2.85594 timestamp: 1655010683.4829454 iteration: 3175 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22523 FastRCNN class loss: 0.11765 FastRCNN total loss: 0.34288 L1 loss: 0.0000e+00 L2 loss: 2.02161 Learning rate: 0.02 Mask loss: 0.27678 RPN box loss: 0.09456 RPN score loss: 0.03692 RPN total loss: 0.13148 Total loss: 2.77275 timestamp: 1655010686.7937005 iteration: 3180 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31015 FastRCNN class loss: 0.2284 FastRCNN total loss: 0.53855 L1 loss: 0.0000e+00 L2 loss: 2.02124 Learning rate: 0.02 Mask loss: 0.35106 RPN box loss: 0.06825 RPN score loss: 0.05607 RPN total loss: 0.12432 Total loss: 3.03517 timestamp: 1655010690.2177258 iteration: 3185 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24253 FastRCNN class loss: 0.18088 FastRCNN total loss: 0.42341 L1 loss: 0.0000e+00 L2 loss: 2.02087 Learning rate: 0.02 Mask loss: 0.26615 RPN box loss: 0.08184 RPN score loss: 0.02682 RPN total loss: 0.10866 Total loss: 2.81908 timestamp: 1655010693.484216 iteration: 3190 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29974 FastRCNN class loss: 0.17982 FastRCNN total loss: 0.47956 L1 loss: 0.0000e+00 L2 loss: 2.02049 Learning rate: 0.02 Mask loss: 0.35326 RPN box loss: 0.14361 RPN score loss: 0.05454 RPN total loss: 0.19815 Total loss: 3.05146 timestamp: 1655010696.8245811 iteration: 3195 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32565 FastRCNN class loss: 0.14494 FastRCNN total loss: 0.47059 L1 loss: 0.0000e+00 L2 loss: 2.02009 Learning rate: 0.02 Mask loss: 0.30917 RPN box loss: 0.01736 RPN score loss: 0.01251 RPN total loss: 0.02987 Total loss: 2.82973 timestamp: 1655010700.1733274 iteration: 3200 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20874 FastRCNN class loss: 0.08002 FastRCNN total loss: 0.28876 L1 loss: 0.0000e+00 L2 loss: 2.01971 Learning rate: 0.02 Mask loss: 0.2712 RPN box loss: 0.12704 RPN score loss: 0.02052 RPN total loss: 0.14756 Total loss: 2.72722 timestamp: 1655010703.5052674 iteration: 3205 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28698 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.37499 L1 loss: 0.0000e+00 L2 loss: 2.01933 Learning rate: 0.02 Mask loss: 0.32663 RPN box loss: 0.03112 RPN score loss: 0.01522 RPN total loss: 0.04633 Total loss: 2.76729 timestamp: 1655010706.9052503 iteration: 3210 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17181 FastRCNN class loss: 0.06594 FastRCNN total loss: 0.23776 L1 loss: 0.0000e+00 L2 loss: 2.01895 Learning rate: 0.02 Mask loss: 0.23497 RPN box loss: 0.02462 RPN score loss: 0.01143 RPN total loss: 0.03605 Total loss: 2.52773 timestamp: 1655010710.243497 iteration: 3215 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26701 FastRCNN class loss: 0.17983 FastRCNN total loss: 0.44684 L1 loss: 0.0000e+00 L2 loss: 2.01856 Learning rate: 0.02 Mask loss: 0.34244 RPN box loss: 0.03856 RPN score loss: 0.01294 RPN total loss: 0.0515 Total loss: 2.85935 timestamp: 1655010713.6011953 iteration: 3220 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.21244 L1 loss: 0.0000e+00 L2 loss: 2.01816 Learning rate: 0.02 Mask loss: 0.31053 RPN box loss: 0.10961 RPN score loss: 0.03557 RPN total loss: 0.14517 Total loss: 2.6863 timestamp: 1655010716.9850862 iteration: 3225 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1678 FastRCNN class loss: 0.05664 FastRCNN total loss: 0.22443 L1 loss: 0.0000e+00 L2 loss: 2.0178 Learning rate: 0.02 Mask loss: 0.22329 RPN box loss: 0.06686 RPN score loss: 0.01382 RPN total loss: 0.08068 Total loss: 2.5462 timestamp: 1655010720.2524643 iteration: 3230 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28296 FastRCNN class loss: 0.11985 FastRCNN total loss: 0.40281 L1 loss: 0.0000e+00 L2 loss: 2.01743 Learning rate: 0.02 Mask loss: 0.26109 RPN box loss: 0.08266 RPN score loss: 0.00981 RPN total loss: 0.09247 Total loss: 2.7738 timestamp: 1655010723.5291007 iteration: 3235 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25058 FastRCNN class loss: 0.11459 FastRCNN total loss: 0.36518 L1 loss: 0.0000e+00 L2 loss: 2.01704 Learning rate: 0.02 Mask loss: 0.36555 RPN box loss: 0.07569 RPN score loss: 0.0239 RPN total loss: 0.09958 Total loss: 2.84735 timestamp: 1655010726.7838628 iteration: 3240 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27544 FastRCNN class loss: 0.14058 FastRCNN total loss: 0.41601 L1 loss: 0.0000e+00 L2 loss: 2.01665 Learning rate: 0.02 Mask loss: 0.38391 RPN box loss: 0.09738 RPN score loss: 0.02395 RPN total loss: 0.12133 Total loss: 2.93791 timestamp: 1655010730.131416 iteration: 3245 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28178 FastRCNN class loss: 0.13213 FastRCNN total loss: 0.41391 L1 loss: 0.0000e+00 L2 loss: 2.01625 Learning rate: 0.02 Mask loss: 0.37296 RPN box loss: 0.04149 RPN score loss: 0.03007 RPN total loss: 0.07156 Total loss: 2.87469 timestamp: 1655010733.3777544 iteration: 3250 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25865 FastRCNN class loss: 0.13573 FastRCNN total loss: 0.39438 L1 loss: 0.0000e+00 L2 loss: 2.01587 Learning rate: 0.02 Mask loss: 0.31025 RPN box loss: 0.0407 RPN score loss: 0.01224 RPN total loss: 0.05294 Total loss: 2.77344 timestamp: 1655010736.6955822 iteration: 3255 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27197 FastRCNN class loss: 0.10883 FastRCNN total loss: 0.3808 L1 loss: 0.0000e+00 L2 loss: 2.01548 Learning rate: 0.02 Mask loss: 0.37069 RPN box loss: 0.03822 RPN score loss: 0.01527 RPN total loss: 0.05349 Total loss: 2.82045 timestamp: 1655010740.0517032 iteration: 3260 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24873 FastRCNN class loss: 0.1211 FastRCNN total loss: 0.36983 L1 loss: 0.0000e+00 L2 loss: 2.0151 Learning rate: 0.02 Mask loss: 0.24568 RPN box loss: 0.04174 RPN score loss: 0.01758 RPN total loss: 0.05932 Total loss: 2.68992 timestamp: 1655010743.3820345 iteration: 3265 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20914 FastRCNN class loss: 0.112 FastRCNN total loss: 0.32115 L1 loss: 0.0000e+00 L2 loss: 2.01472 Learning rate: 0.02 Mask loss: 0.24752 RPN box loss: 0.04539 RPN score loss: 0.01606 RPN total loss: 0.06144 Total loss: 2.64483 timestamp: 1655010746.736855 iteration: 3270 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15519 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.24794 L1 loss: 0.0000e+00 L2 loss: 2.01433 Learning rate: 0.02 Mask loss: 0.24616 RPN box loss: 0.03642 RPN score loss: 0.03583 RPN total loss: 0.07225 Total loss: 2.58068 timestamp: 1655010750.0739431 iteration: 3275 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33598 FastRCNN class loss: 0.16636 FastRCNN total loss: 0.50234 L1 loss: 0.0000e+00 L2 loss: 2.01396 Learning rate: 0.02 Mask loss: 0.40693 RPN box loss: 0.05502 RPN score loss: 0.03775 RPN total loss: 0.09277 Total loss: 3.016 timestamp: 1655010753.3712354 iteration: 3280 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21726 FastRCNN class loss: 0.12714 FastRCNN total loss: 0.3444 L1 loss: 0.0000e+00 L2 loss: 2.01358 Learning rate: 0.02 Mask loss: 0.23495 RPN box loss: 0.04429 RPN score loss: 0.01386 RPN total loss: 0.05815 Total loss: 2.65108 timestamp: 1655010756.7202265 iteration: 3285 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23226 FastRCNN class loss: 0.11165 FastRCNN total loss: 0.3439 L1 loss: 0.0000e+00 L2 loss: 2.01319 Learning rate: 0.02 Mask loss: 0.2636 RPN box loss: 0.08827 RPN score loss: 0.03331 RPN total loss: 0.12158 Total loss: 2.74228 timestamp: 1655010760.070123 iteration: 3290 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19773 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.28434 L1 loss: 0.0000e+00 L2 loss: 2.01281 Learning rate: 0.02 Mask loss: 0.25051 RPN box loss: 0.06306 RPN score loss: 0.02062 RPN total loss: 0.08368 Total loss: 2.63133 timestamp: 1655010763.4319332 iteration: 3295 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24839 FastRCNN class loss: 0.11861 FastRCNN total loss: 0.367 L1 loss: 0.0000e+00 L2 loss: 2.01242 Learning rate: 0.02 Mask loss: 0.218 RPN box loss: 0.06242 RPN score loss: 0.01417 RPN total loss: 0.07659 Total loss: 2.67401 timestamp: 1655010766.8734508 iteration: 3300 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29253 FastRCNN class loss: 0.15768 FastRCNN total loss: 0.45021 L1 loss: 0.0000e+00 L2 loss: 2.01204 Learning rate: 0.02 Mask loss: 0.30446 RPN box loss: 0.05144 RPN score loss: 0.01935 RPN total loss: 0.07078 Total loss: 2.83749 timestamp: 1655010770.250478 iteration: 3305 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20888 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.305 L1 loss: 0.0000e+00 L2 loss: 2.01164 Learning rate: 0.02 Mask loss: 0.26341 RPN box loss: 0.08297 RPN score loss: 0.02244 RPN total loss: 0.10541 Total loss: 2.68546 timestamp: 1655010773.5605032 iteration: 3310 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28111 FastRCNN class loss: 0.13898 FastRCNN total loss: 0.4201 L1 loss: 0.0000e+00 L2 loss: 2.01127 Learning rate: 0.02 Mask loss: 0.43862 RPN box loss: 0.08312 RPN score loss: 0.02788 RPN total loss: 0.111 Total loss: 2.98099 timestamp: 1655010776.8526685 iteration: 3315 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29444 FastRCNN class loss: 0.13681 FastRCNN total loss: 0.43124 L1 loss: 0.0000e+00 L2 loss: 2.01088 Learning rate: 0.02 Mask loss: 0.27721 RPN box loss: 0.03651 RPN score loss: 0.01337 RPN total loss: 0.04989 Total loss: 2.76922 timestamp: 1655010780.1222613 iteration: 3320 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28882 FastRCNN class loss: 0.11432 FastRCNN total loss: 0.40314 L1 loss: 0.0000e+00 L2 loss: 2.0105 Learning rate: 0.02 Mask loss: 0.27723 RPN box loss: 0.00669 RPN score loss: 0.01162 RPN total loss: 0.01831 Total loss: 2.70918 timestamp: 1655010783.4018533 iteration: 3325 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27111 FastRCNN class loss: 0.13326 FastRCNN total loss: 0.40438 L1 loss: 0.0000e+00 L2 loss: 2.01012 Learning rate: 0.02 Mask loss: 0.37291 RPN box loss: 0.0168 RPN score loss: 0.01301 RPN total loss: 0.0298 Total loss: 2.81721 timestamp: 1655010786.5816116 iteration: 3330 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30814 FastRCNN class loss: 0.15247 FastRCNN total loss: 0.4606 L1 loss: 0.0000e+00 L2 loss: 2.00974 Learning rate: 0.02 Mask loss: 0.29125 RPN box loss: 0.05685 RPN score loss: 0.01135 RPN total loss: 0.0682 Total loss: 2.8298 timestamp: 1655010789.92815 iteration: 3335 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21254 FastRCNN class loss: 0.10399 FastRCNN total loss: 0.31652 L1 loss: 0.0000e+00 L2 loss: 2.00936 Learning rate: 0.02 Mask loss: 0.21034 RPN box loss: 0.04525 RPN score loss: 0.02735 RPN total loss: 0.0726 Total loss: 2.60882 timestamp: 1655010793.2479124 iteration: 3340 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16869 FastRCNN class loss: 0.067 FastRCNN total loss: 0.23569 L1 loss: 0.0000e+00 L2 loss: 2.00898 Learning rate: 0.02 Mask loss: 0.21391 RPN box loss: 0.0255 RPN score loss: 0.01566 RPN total loss: 0.04117 Total loss: 2.49975 timestamp: 1655010796.5929692 iteration: 3345 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26334 FastRCNN class loss: 0.11522 FastRCNN total loss: 0.37856 L1 loss: 0.0000e+00 L2 loss: 2.00862 Learning rate: 0.02 Mask loss: 0.32582 RPN box loss: 0.03443 RPN score loss: 0.01439 RPN total loss: 0.04882 Total loss: 2.76181 timestamp: 1655010799.8783245 iteration: 3350 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35586 FastRCNN class loss: 0.16419 FastRCNN total loss: 0.52005 L1 loss: 0.0000e+00 L2 loss: 2.00822 Learning rate: 0.02 Mask loss: 0.3808 RPN box loss: 0.07021 RPN score loss: 0.04459 RPN total loss: 0.1148 Total loss: 3.02388 timestamp: 1655010803.1452098 iteration: 3355 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29016 FastRCNN class loss: 0.12261 FastRCNN total loss: 0.41277 L1 loss: 0.0000e+00 L2 loss: 2.00784 Learning rate: 0.02 Mask loss: 0.35076 RPN box loss: 0.09692 RPN score loss: 0.02005 RPN total loss: 0.11696 Total loss: 2.88833 timestamp: 1655010806.449408 iteration: 3360 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37166 FastRCNN class loss: 0.12653 FastRCNN total loss: 0.49819 L1 loss: 0.0000e+00 L2 loss: 2.00745 Learning rate: 0.02 Mask loss: 0.22475 RPN box loss: 0.14002 RPN score loss: 0.02167 RPN total loss: 0.16169 Total loss: 2.89207 timestamp: 1655010809.868011 iteration: 3365 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25296 FastRCNN class loss: 0.12587 FastRCNN total loss: 0.37883 L1 loss: 0.0000e+00 L2 loss: 2.00705 Learning rate: 0.02 Mask loss: 0.31558 RPN box loss: 0.05032 RPN score loss: 0.01764 RPN total loss: 0.06796 Total loss: 2.76942 timestamp: 1655010813.1889765 iteration: 3370 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29746 FastRCNN class loss: 0.15744 FastRCNN total loss: 0.45491 L1 loss: 0.0000e+00 L2 loss: 2.0067 Learning rate: 0.02 Mask loss: 0.29747 RPN box loss: 0.08976 RPN score loss: 0.02203 RPN total loss: 0.11179 Total loss: 2.87087 timestamp: 1655010816.4653425 iteration: 3375 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19727 FastRCNN class loss: 0.09704 FastRCNN total loss: 0.29431 L1 loss: 0.0000e+00 L2 loss: 2.00633 Learning rate: 0.02 Mask loss: 0.23669 RPN box loss: 0.02935 RPN score loss: 0.01064 RPN total loss: 0.03998 Total loss: 2.57731 timestamp: 1655010819.7738864 iteration: 3380 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18063 FastRCNN class loss: 0.09024 FastRCNN total loss: 0.27088 L1 loss: 0.0000e+00 L2 loss: 2.00592 Learning rate: 0.02 Mask loss: 0.29964 RPN box loss: 0.01679 RPN score loss: 0.00868 RPN total loss: 0.02546 Total loss: 2.60191 timestamp: 1655010823.0900888 iteration: 3385 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21541 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.31247 L1 loss: 0.0000e+00 L2 loss: 2.00553 Learning rate: 0.02 Mask loss: 0.22687 RPN box loss: 0.08262 RPN score loss: 0.01256 RPN total loss: 0.09519 Total loss: 2.64006 timestamp: 1655010826.4537525 iteration: 3390 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28248 FastRCNN class loss: 0.1216 FastRCNN total loss: 0.40408 L1 loss: 0.0000e+00 L2 loss: 2.00513 Learning rate: 0.02 Mask loss: 0.34283 RPN box loss: 0.08427 RPN score loss: 0.01164 RPN total loss: 0.0959 Total loss: 2.84795 timestamp: 1655010829.8023593 iteration: 3395 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27272 FastRCNN class loss: 0.14368 FastRCNN total loss: 0.41639 L1 loss: 0.0000e+00 L2 loss: 2.00478 Learning rate: 0.02 Mask loss: 0.37385 RPN box loss: 0.06798 RPN score loss: 0.01656 RPN total loss: 0.08454 Total loss: 2.87957 timestamp: 1655010833.1443644 iteration: 3400 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23712 FastRCNN class loss: 0.14483 FastRCNN total loss: 0.38195 L1 loss: 0.0000e+00 L2 loss: 2.0044 Learning rate: 0.02 Mask loss: 0.2595 RPN box loss: 0.03215 RPN score loss: 0.00762 RPN total loss: 0.03978 Total loss: 2.68563 timestamp: 1655010836.5558062 iteration: 3405 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17549 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.27459 L1 loss: 0.0000e+00 L2 loss: 2.004 Learning rate: 0.02 Mask loss: 0.29445 RPN box loss: 0.12185 RPN score loss: 0.02313 RPN total loss: 0.14498 Total loss: 2.71803 timestamp: 1655010839.8936064 iteration: 3410 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19583 FastRCNN class loss: 0.08605 FastRCNN total loss: 0.28189 L1 loss: 0.0000e+00 L2 loss: 2.00364 Learning rate: 0.02 Mask loss: 0.30639 RPN box loss: 0.08858 RPN score loss: 0.01452 RPN total loss: 0.10311 Total loss: 2.69502 timestamp: 1655010843.1827953 iteration: 3415 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19781 FastRCNN class loss: 0.09092 FastRCNN total loss: 0.28873 L1 loss: 0.0000e+00 L2 loss: 2.00325 Learning rate: 0.02 Mask loss: 0.27842 RPN box loss: 0.04079 RPN score loss: 0.04673 RPN total loss: 0.08753 Total loss: 2.65792 timestamp: 1655010846.5141597 iteration: 3420 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1821 FastRCNN class loss: 0.09833 FastRCNN total loss: 0.28043 L1 loss: 0.0000e+00 L2 loss: 2.00287 Learning rate: 0.02 Mask loss: 0.33865 RPN box loss: 0.06991 RPN score loss: 0.01232 RPN total loss: 0.08223 Total loss: 2.70418 timestamp: 1655010849.826925 iteration: 3425 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42576 FastRCNN class loss: 0.17862 FastRCNN total loss: 0.60438 L1 loss: 0.0000e+00 L2 loss: 2.00248 Learning rate: 0.02 Mask loss: 0.37478 RPN box loss: 0.06508 RPN score loss: 0.02182 RPN total loss: 0.0869 Total loss: 3.06854 timestamp: 1655010853.082683 iteration: 3430 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19899 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.27246 L1 loss: 0.0000e+00 L2 loss: 2.0021 Learning rate: 0.02 Mask loss: 0.20639 RPN box loss: 0.07737 RPN score loss: 0.011 RPN total loss: 0.08837 Total loss: 2.56931 timestamp: 1655010856.435143 iteration: 3435 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18657 FastRCNN class loss: 0.12479 FastRCNN total loss: 0.31136 L1 loss: 0.0000e+00 L2 loss: 2.00172 Learning rate: 0.02 Mask loss: 0.31989 RPN box loss: 0.10518 RPN score loss: 0.02422 RPN total loss: 0.1294 Total loss: 2.76237 timestamp: 1655010859.8273523 iteration: 3440 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2921 FastRCNN class loss: 0.12327 FastRCNN total loss: 0.41537 L1 loss: 0.0000e+00 L2 loss: 2.00134 Learning rate: 0.02 Mask loss: 0.27866 RPN box loss: 0.05249 RPN score loss: 0.01377 RPN total loss: 0.06625 Total loss: 2.76163 timestamp: 1655010863.2335336 iteration: 3445 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19872 FastRCNN class loss: 0.09236 FastRCNN total loss: 0.29108 L1 loss: 0.0000e+00 L2 loss: 2.00096 Learning rate: 0.02 Mask loss: 0.29388 RPN box loss: 0.01797 RPN score loss: 0.01409 RPN total loss: 0.03206 Total loss: 2.61798 timestamp: 1655010866.591961 iteration: 3450 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29314 FastRCNN class loss: 0.10615 FastRCNN total loss: 0.39929 L1 loss: 0.0000e+00 L2 loss: 2.00058 Learning rate: 0.02 Mask loss: 0.28819 RPN box loss: 0.0597 RPN score loss: 0.01096 RPN total loss: 0.07066 Total loss: 2.75871 timestamp: 1655010869.8819027 iteration: 3455 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25568 FastRCNN class loss: 0.112 FastRCNN total loss: 0.36768 L1 loss: 0.0000e+00 L2 loss: 2.0002 Learning rate: 0.02 Mask loss: 0.19439 RPN box loss: 0.04208 RPN score loss: 0.00809 RPN total loss: 0.05017 Total loss: 2.61244 timestamp: 1655010873.2070673 iteration: 3460 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21766 FastRCNN class loss: 0.09509 FastRCNN total loss: 0.31275 L1 loss: 0.0000e+00 L2 loss: 1.99981 Learning rate: 0.02 Mask loss: 0.29744 RPN box loss: 0.09485 RPN score loss: 0.01328 RPN total loss: 0.10813 Total loss: 2.71813 timestamp: 1655010876.4751074 iteration: 3465 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3364 FastRCNN class loss: 0.12377 FastRCNN total loss: 0.46017 L1 loss: 0.0000e+00 L2 loss: 1.99943 Learning rate: 0.02 Mask loss: 0.33645 RPN box loss: 0.06232 RPN score loss: 0.02261 RPN total loss: 0.08493 Total loss: 2.88097 timestamp: 1655010879.847903 iteration: 3470 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24046 FastRCNN class loss: 0.09351 FastRCNN total loss: 0.33396 L1 loss: 0.0000e+00 L2 loss: 1.99905 Learning rate: 0.02 Mask loss: 0.2939 RPN box loss: 0.04499 RPN score loss: 0.01252 RPN total loss: 0.05751 Total loss: 2.68442 timestamp: 1655010883.1984324 iteration: 3475 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3186 FastRCNN class loss: 0.09991 FastRCNN total loss: 0.4185 L1 loss: 0.0000e+00 L2 loss: 1.99866 Learning rate: 0.02 Mask loss: 0.37406 RPN box loss: 0.1284 RPN score loss: 0.02268 RPN total loss: 0.15108 Total loss: 2.94231 timestamp: 1655010886.467334 iteration: 3480 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25824 FastRCNN class loss: 0.10798 FastRCNN total loss: 0.36622 L1 loss: 0.0000e+00 L2 loss: 1.99828 Learning rate: 0.02 Mask loss: 0.22579 RPN box loss: 0.13969 RPN score loss: 0.02325 RPN total loss: 0.16294 Total loss: 2.75324 timestamp: 1655010889.789288 iteration: 3485 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2905 FastRCNN class loss: 0.12756 FastRCNN total loss: 0.41806 L1 loss: 0.0000e+00 L2 loss: 1.99791 Learning rate: 0.02 Mask loss: 0.31243 RPN box loss: 0.02372 RPN score loss: 0.02088 RPN total loss: 0.0446 Total loss: 2.773 timestamp: 1655010893.2825243 iteration: 3490 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30753 FastRCNN class loss: 0.11788 FastRCNN total loss: 0.42541 L1 loss: 0.0000e+00 L2 loss: 1.99748 Learning rate: 0.02 Mask loss: 0.30349 RPN box loss: 0.01682 RPN score loss: 0.01874 RPN total loss: 0.03556 Total loss: 2.76194 timestamp: 1655010896.6121733 iteration: 3495 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28888 FastRCNN class loss: 0.10851 FastRCNN total loss: 0.39739 L1 loss: 0.0000e+00 L2 loss: 1.99712 Learning rate: 0.02 Mask loss: 0.29585 RPN box loss: 0.04505 RPN score loss: 0.01526 RPN total loss: 0.0603 Total loss: 2.75066 timestamp: 1655010899.889957 iteration: 3500 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27914 FastRCNN class loss: 0.10627 FastRCNN total loss: 0.38542 L1 loss: 0.0000e+00 L2 loss: 1.99674 Learning rate: 0.02 Mask loss: 0.30184 RPN box loss: 0.05241 RPN score loss: 0.02847 RPN total loss: 0.08088 Total loss: 2.76488 timestamp: 1655010903.1723175 iteration: 3505 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.256 FastRCNN class loss: 0.10087 FastRCNN total loss: 0.35687 L1 loss: 0.0000e+00 L2 loss: 1.99636 Learning rate: 0.02 Mask loss: 0.23149 RPN box loss: 0.05812 RPN score loss: 0.00955 RPN total loss: 0.06767 Total loss: 2.65239 timestamp: 1655010906.4654877 iteration: 3510 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22556 FastRCNN class loss: 0.1387 FastRCNN total loss: 0.36426 L1 loss: 0.0000e+00 L2 loss: 1.99598 Learning rate: 0.02 Mask loss: 0.2555 RPN box loss: 0.08702 RPN score loss: 0.02782 RPN total loss: 0.11484 Total loss: 2.73058 timestamp: 1655010909.7595985 iteration: 3515 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29207 FastRCNN class loss: 0.14671 FastRCNN total loss: 0.43878 L1 loss: 0.0000e+00 L2 loss: 1.99562 Learning rate: 0.02 Mask loss: 0.38566 RPN box loss: 0.05263 RPN score loss: 0.01497 RPN total loss: 0.0676 Total loss: 2.88765 timestamp: 1655010913.0545454 iteration: 3520 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24481 FastRCNN class loss: 0.10923 FastRCNN total loss: 0.35404 L1 loss: 0.0000e+00 L2 loss: 1.99521 Learning rate: 0.02 Mask loss: 0.29308 RPN box loss: 0.03322 RPN score loss: 0.00542 RPN total loss: 0.03863 Total loss: 2.68096 timestamp: 1655010916.3268178 iteration: 3525 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17183 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.24549 L1 loss: 0.0000e+00 L2 loss: 1.99484 Learning rate: 0.02 Mask loss: 0.24353 RPN box loss: 0.05225 RPN score loss: 0.01034 RPN total loss: 0.06259 Total loss: 2.54645 timestamp: 1655010919.6412048 iteration: 3530 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28327 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.37172 L1 loss: 0.0000e+00 L2 loss: 1.99447 Learning rate: 0.02 Mask loss: 0.24131 RPN box loss: 0.07726 RPN score loss: 0.01576 RPN total loss: 0.09302 Total loss: 2.70052 timestamp: 1655010923.0088527 iteration: 3535 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16609 FastRCNN class loss: 0.1396 FastRCNN total loss: 0.30569 L1 loss: 0.0000e+00 L2 loss: 1.99409 Learning rate: 0.02 Mask loss: 0.22214 RPN box loss: 0.05407 RPN score loss: 0.04925 RPN total loss: 0.10332 Total loss: 2.62524 timestamp: 1655010926.3105202 iteration: 3540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28964 FastRCNN class loss: 0.14979 FastRCNN total loss: 0.43944 L1 loss: 0.0000e+00 L2 loss: 1.99371 Learning rate: 0.02 Mask loss: 0.33374 RPN box loss: 0.04018 RPN score loss: 0.01154 RPN total loss: 0.05172 Total loss: 2.81861 timestamp: 1655010929.5894556 iteration: 3545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20859 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.2937 L1 loss: 0.0000e+00 L2 loss: 1.99332 Learning rate: 0.02 Mask loss: 0.27823 RPN box loss: 0.02979 RPN score loss: 0.01379 RPN total loss: 0.04358 Total loss: 2.60884 timestamp: 1655010932.9429379 iteration: 3550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24155 FastRCNN class loss: 0.11355 FastRCNN total loss: 0.3551 L1 loss: 0.0000e+00 L2 loss: 1.99295 Learning rate: 0.02 Mask loss: 0.3103 RPN box loss: 0.03892 RPN score loss: 0.01207 RPN total loss: 0.051 Total loss: 2.70935 timestamp: 1655010936.3088515 iteration: 3555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20114 FastRCNN class loss: 0.09157 FastRCNN total loss: 0.29271 L1 loss: 0.0000e+00 L2 loss: 1.99256 Learning rate: 0.02 Mask loss: 0.27741 RPN box loss: 0.06503 RPN score loss: 0.01358 RPN total loss: 0.07861 Total loss: 2.64129 timestamp: 1655010939.6106946 iteration: 3560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25798 FastRCNN class loss: 0.12495 FastRCNN total loss: 0.38293 L1 loss: 0.0000e+00 L2 loss: 1.99218 Learning rate: 0.02 Mask loss: 0.29787 RPN box loss: 0.04055 RPN score loss: 0.01181 RPN total loss: 0.05236 Total loss: 2.72534 timestamp: 1655010942.9297771 iteration: 3565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25941 FastRCNN class loss: 0.14387 FastRCNN total loss: 0.40328 L1 loss: 0.0000e+00 L2 loss: 1.9918 Learning rate: 0.02 Mask loss: 0.22789 RPN box loss: 0.04795 RPN score loss: 0.01647 RPN total loss: 0.06442 Total loss: 2.6874 timestamp: 1655010946.2959466 iteration: 3570 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2261 FastRCNN class loss: 0.10138 FastRCNN total loss: 0.32748 L1 loss: 0.0000e+00 L2 loss: 1.99143 Learning rate: 0.02 Mask loss: 0.19584 RPN box loss: 0.10626 RPN score loss: 0.02196 RPN total loss: 0.12822 Total loss: 2.64297 timestamp: 1655010949.5971832 iteration: 3575 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15339 FastRCNN class loss: 0.07719 FastRCNN total loss: 0.23058 L1 loss: 0.0000e+00 L2 loss: 1.99105 Learning rate: 0.02 Mask loss: 0.20655 RPN box loss: 0.04113 RPN score loss: 0.00633 RPN total loss: 0.04747 Total loss: 2.47564 timestamp: 1655010952.9136975 iteration: 3580 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20071 FastRCNN class loss: 0.11005 FastRCNN total loss: 0.31076 L1 loss: 0.0000e+00 L2 loss: 1.99068 Learning rate: 0.02 Mask loss: 0.2159 RPN box loss: 0.04208 RPN score loss: 0.01211 RPN total loss: 0.0542 Total loss: 2.57154 timestamp: 1655010956.1824136 iteration: 3585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27588 FastRCNN class loss: 0.0955 FastRCNN total loss: 0.37138 L1 loss: 0.0000e+00 L2 loss: 1.99031 Learning rate: 0.02 Mask loss: 0.18772 RPN box loss: 0.05446 RPN score loss: 0.01102 RPN total loss: 0.06548 Total loss: 2.61489 timestamp: 1655010959.4660692 iteration: 3590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16304 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.24401 L1 loss: 0.0000e+00 L2 loss: 1.98994 Learning rate: 0.02 Mask loss: 0.30073 RPN box loss: 0.03739 RPN score loss: 0.01298 RPN total loss: 0.05036 Total loss: 2.58503 timestamp: 1655010962.7353022 iteration: 3595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32255 FastRCNN class loss: 0.2399 FastRCNN total loss: 0.56246 L1 loss: 0.0000e+00 L2 loss: 1.98954 Learning rate: 0.02 Mask loss: 0.44072 RPN box loss: 0.12258 RPN score loss: 0.03497 RPN total loss: 0.15755 Total loss: 3.15027 timestamp: 1655010966.00583 iteration: 3600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17778 FastRCNN class loss: 0.07395 FastRCNN total loss: 0.25173 L1 loss: 0.0000e+00 L2 loss: 1.98916 Learning rate: 0.02 Mask loss: 0.24183 RPN box loss: 0.05831 RPN score loss: 0.0291 RPN total loss: 0.08741 Total loss: 2.57012 timestamp: 1655010969.3155553 iteration: 3605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18275 FastRCNN class loss: 0.08524 FastRCNN total loss: 0.26799 L1 loss: 0.0000e+00 L2 loss: 1.98877 Learning rate: 0.02 Mask loss: 0.15049 RPN box loss: 0.0227 RPN score loss: 0.00663 RPN total loss: 0.02933 Total loss: 2.43658 timestamp: 1655010972.5809686 iteration: 3610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21689 FastRCNN class loss: 0.08004 FastRCNN total loss: 0.29693 L1 loss: 0.0000e+00 L2 loss: 1.9884 Learning rate: 0.02 Mask loss: 0.24054 RPN box loss: 0.03888 RPN score loss: 0.01311 RPN total loss: 0.05199 Total loss: 2.57787 timestamp: 1655010975.9380686 iteration: 3615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2372 FastRCNN class loss: 0.20672 FastRCNN total loss: 0.44393 L1 loss: 0.0000e+00 L2 loss: 1.98802 Learning rate: 0.02 Mask loss: 0.25888 RPN box loss: 0.06435 RPN score loss: 0.01441 RPN total loss: 0.07876 Total loss: 2.76959 timestamp: 1655010979.2938986 iteration: 3620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.39066 FastRCNN class loss: 0.11431 FastRCNN total loss: 0.50498 L1 loss: 0.0000e+00 L2 loss: 1.98765 Learning rate: 0.02 Mask loss: 0.31311 RPN box loss: 0.07332 RPN score loss: 0.01923 RPN total loss: 0.09254 Total loss: 2.89827 timestamp: 1655010982.603648 iteration: 3625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22875 FastRCNN class loss: 0.08148 FastRCNN total loss: 0.31024 L1 loss: 0.0000e+00 L2 loss: 1.98727 Learning rate: 0.02 Mask loss: 0.24055 RPN box loss: 0.07136 RPN score loss: 0.01576 RPN total loss: 0.08712 Total loss: 2.62518 timestamp: 1655010985.9459062 iteration: 3630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21709 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.32542 L1 loss: 0.0000e+00 L2 loss: 1.98691 Learning rate: 0.02 Mask loss: 0.28887 RPN box loss: 0.03015 RPN score loss: 0.01419 RPN total loss: 0.04434 Total loss: 2.64554 timestamp: 1655010989.2685332 iteration: 3635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25074 FastRCNN class loss: 0.12783 FastRCNN total loss: 0.37858 L1 loss: 0.0000e+00 L2 loss: 1.98652 Learning rate: 0.02 Mask loss: 0.34713 RPN box loss: 0.18023 RPN score loss: 0.02373 RPN total loss: 0.20396 Total loss: 2.91618 timestamp: 1655010992.6283684 iteration: 3640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25446 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.33549 L1 loss: 0.0000e+00 L2 loss: 1.98613 Learning rate: 0.02 Mask loss: 0.21495 RPN box loss: 0.05794 RPN score loss: 0.00788 RPN total loss: 0.06582 Total loss: 2.60239 timestamp: 1655010995.91267 iteration: 3645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23305 FastRCNN class loss: 0.11452 FastRCNN total loss: 0.34757 L1 loss: 0.0000e+00 L2 loss: 1.98576 Learning rate: 0.02 Mask loss: 0.2773 RPN box loss: 0.0722 RPN score loss: 0.0336 RPN total loss: 0.10581 Total loss: 2.71645 timestamp: 1655010999.1885817 iteration: 3650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1835 FastRCNN class loss: 0.06662 FastRCNN total loss: 0.25011 L1 loss: 0.0000e+00 L2 loss: 1.98538 Learning rate: 0.02 Mask loss: 0.30087 RPN box loss: 0.0497 RPN score loss: 0.01355 RPN total loss: 0.06325 Total loss: 2.59961 timestamp: 1655011002.5766668 iteration: 3655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26165 FastRCNN class loss: 0.18403 FastRCNN total loss: 0.44568 L1 loss: 0.0000e+00 L2 loss: 1.98501 Learning rate: 0.02 Mask loss: 0.35052 RPN box loss: 0.04555 RPN score loss: 0.03194 RPN total loss: 0.0775 Total loss: 2.85871 timestamp: 1655011005.8823943 iteration: 3660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18874 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.2751 L1 loss: 0.0000e+00 L2 loss: 1.98463 Learning rate: 0.02 Mask loss: 0.18344 RPN box loss: 0.10407 RPN score loss: 0.03196 RPN total loss: 0.13604 Total loss: 2.57922 timestamp: 1655011009.288401 iteration: 3665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21574 FastRCNN class loss: 0.21983 FastRCNN total loss: 0.43557 L1 loss: 0.0000e+00 L2 loss: 1.98425 Learning rate: 0.02 Mask loss: 0.27875 RPN box loss: 0.06293 RPN score loss: 0.01494 RPN total loss: 0.07787 Total loss: 2.77644 timestamp: 1655011012.6660392 iteration: 3670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27827 FastRCNN class loss: 0.06372 FastRCNN total loss: 0.342 L1 loss: 0.0000e+00 L2 loss: 1.98389 Learning rate: 0.02 Mask loss: 0.26754 RPN box loss: 0.02303 RPN score loss: 0.00592 RPN total loss: 0.02895 Total loss: 2.62238 timestamp: 1655011016.0477624 iteration: 3675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24557 FastRCNN class loss: 0.16561 FastRCNN total loss: 0.41118 L1 loss: 0.0000e+00 L2 loss: 1.98352 Learning rate: 0.02 Mask loss: 0.23377 RPN box loss: 0.05425 RPN score loss: 0.02632 RPN total loss: 0.08057 Total loss: 2.70905 timestamp: 1655011019.3580315 iteration: 3680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18764 FastRCNN class loss: 0.09951 FastRCNN total loss: 0.28715 L1 loss: 0.0000e+00 L2 loss: 1.98315 Learning rate: 0.02 Mask loss: 0.29032 RPN box loss: 0.01691 RPN score loss: 0.01119 RPN total loss: 0.0281 Total loss: 2.58871 timestamp: 1655011022.6270382 iteration: 3685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17976 FastRCNN class loss: 0.09271 FastRCNN total loss: 0.27247 L1 loss: 0.0000e+00 L2 loss: 1.98277 Learning rate: 0.02 Mask loss: 0.25597 RPN box loss: 0.05333 RPN score loss: 0.03587 RPN total loss: 0.0892 Total loss: 2.60041 timestamp: 1655011025.9592874 iteration: 3690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24249 FastRCNN class loss: 0.14181 FastRCNN total loss: 0.3843 L1 loss: 0.0000e+00 L2 loss: 1.98238 Learning rate: 0.02 Mask loss: 0.27853 RPN box loss: 0.01958 RPN score loss: 0.00785 RPN total loss: 0.02743 Total loss: 2.67263 timestamp: 1655011029.2848144 iteration: 3695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26654 FastRCNN class loss: 0.10192 FastRCNN total loss: 0.36846 L1 loss: 0.0000e+00 L2 loss: 1.982 Learning rate: 0.02 Mask loss: 0.24739 RPN box loss: 0.04215 RPN score loss: 0.01697 RPN total loss: 0.05912 Total loss: 2.65698 timestamp: 1655011032.6421192 iteration: 3700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19025 FastRCNN class loss: 0.12571 FastRCNN total loss: 0.31596 L1 loss: 0.0000e+00 L2 loss: 1.98162 Learning rate: 0.02 Mask loss: 0.34083 RPN box loss: 0.0789 RPN score loss: 0.03999 RPN total loss: 0.11889 Total loss: 2.75729 timestamp: 1655011035.9643106 iteration: 3705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29601 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.38468 L1 loss: 0.0000e+00 L2 loss: 1.98121 Learning rate: 0.02 Mask loss: 0.20504 RPN box loss: 0.02749 RPN score loss: 0.01344 RPN total loss: 0.04093 Total loss: 2.61187 timestamp: 1655011039.2702737 iteration: 3710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28499 FastRCNN class loss: 0.08865 FastRCNN total loss: 0.37364 L1 loss: 0.0000e+00 L2 loss: 1.98087 Learning rate: 0.02 Mask loss: 0.27787 RPN box loss: 0.03273 RPN score loss: 0.01004 RPN total loss: 0.04277 Total loss: 2.67515 timestamp: 1655011042.5617008 iteration: 3715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23802 FastRCNN class loss: 0.10198 FastRCNN total loss: 0.34001 L1 loss: 0.0000e+00 L2 loss: 1.98049 Learning rate: 0.02 Mask loss: 0.24583 RPN box loss: 0.04849 RPN score loss: 0.01517 RPN total loss: 0.06366 Total loss: 2.62999 timestamp: 1655011045.839403 iteration: 3720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18392 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.28139 L1 loss: 0.0000e+00 L2 loss: 1.98013 Learning rate: 0.02 Mask loss: 0.16879 RPN box loss: 0.08318 RPN score loss: 0.0136 RPN total loss: 0.09678 Total loss: 2.52709 timestamp: 1655011049.2279422 iteration: 3725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16367 FastRCNN class loss: 0.09908 FastRCNN total loss: 0.26275 L1 loss: 0.0000e+00 L2 loss: 1.97975 Learning rate: 0.02 Mask loss: 0.31103 RPN box loss: 0.03951 RPN score loss: 0.043 RPN total loss: 0.08252 Total loss: 2.63606 timestamp: 1655011052.5768611 iteration: 3730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26074 FastRCNN class loss: 0.08884 FastRCNN total loss: 0.34958 L1 loss: 0.0000e+00 L2 loss: 1.97936 Learning rate: 0.02 Mask loss: 0.3479 RPN box loss: 0.02828 RPN score loss: 0.01973 RPN total loss: 0.048 Total loss: 2.72484 timestamp: 1655011055.8484423 iteration: 3735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14429 FastRCNN class loss: 0.11415 FastRCNN total loss: 0.25844 L1 loss: 0.0000e+00 L2 loss: 1.979 Learning rate: 0.02 Mask loss: 0.21886 RPN box loss: 0.05174 RPN score loss: 0.01466 RPN total loss: 0.06641 Total loss: 2.5227 timestamp: 1655011059.2012177 iteration: 3740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30814 FastRCNN class loss: 0.10009 FastRCNN total loss: 0.40823 L1 loss: 0.0000e+00 L2 loss: 1.97862 Learning rate: 0.02 Mask loss: 0.23456 RPN box loss: 0.0158 RPN score loss: 0.00811 RPN total loss: 0.02391 Total loss: 2.64532 timestamp: 1655011062.5039666 iteration: 3745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22604 FastRCNN class loss: 0.08851 FastRCNN total loss: 0.31455 L1 loss: 0.0000e+00 L2 loss: 1.97826 Learning rate: 0.02 Mask loss: 0.31108 RPN box loss: 0.03405 RPN score loss: 0.00883 RPN total loss: 0.04288 Total loss: 2.64677 timestamp: 1655011065.7756264 iteration: 3750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27779 FastRCNN class loss: 0.10142 FastRCNN total loss: 0.37921 L1 loss: 0.0000e+00 L2 loss: 1.97788 Learning rate: 0.02 Mask loss: 0.25179 RPN box loss: 0.06909 RPN score loss: 0.02058 RPN total loss: 0.08968 Total loss: 2.69855 timestamp: 1655011069.0341346 iteration: 3755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26742 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.33291 L1 loss: 0.0000e+00 L2 loss: 1.97748 Learning rate: 0.02 Mask loss: 0.22778 RPN box loss: 0.02854 RPN score loss: 0.00892 RPN total loss: 0.03746 Total loss: 2.57563 timestamp: 1655011072.4010177 iteration: 3760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1496 FastRCNN class loss: 0.07516 FastRCNN total loss: 0.22476 L1 loss: 0.0000e+00 L2 loss: 1.9771 Learning rate: 0.02 Mask loss: 0.22669 RPN box loss: 0.07661 RPN score loss: 0.01213 RPN total loss: 0.08874 Total loss: 2.51729 timestamp: 1655011075.6791427 iteration: 3765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17086 FastRCNN class loss: 0.13405 FastRCNN total loss: 0.30491 L1 loss: 0.0000e+00 L2 loss: 1.97674 Learning rate: 0.02 Mask loss: 0.28992 RPN box loss: 0.03219 RPN score loss: 0.01631 RPN total loss: 0.0485 Total loss: 2.62007 timestamp: 1655011079.0270796 iteration: 3770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25853 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.35423 L1 loss: 0.0000e+00 L2 loss: 1.97637 Learning rate: 0.02 Mask loss: 0.31618 RPN box loss: 0.05337 RPN score loss: 0.01136 RPN total loss: 0.06474 Total loss: 2.71152 timestamp: 1655011082.2706985 iteration: 3775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1902 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.26732 L1 loss: 0.0000e+00 L2 loss: 1.97599 Learning rate: 0.02 Mask loss: 0.24673 RPN box loss: 0.0928 RPN score loss: 0.01523 RPN total loss: 0.10803 Total loss: 2.59807 timestamp: 1655011085.684073 iteration: 3780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19073 FastRCNN class loss: 0.09108 FastRCNN total loss: 0.28181 L1 loss: 0.0000e+00 L2 loss: 1.97561 Learning rate: 0.02 Mask loss: 0.20822 RPN box loss: 0.05038 RPN score loss: 0.01866 RPN total loss: 0.06904 Total loss: 2.53469 timestamp: 1655011089.0154736 iteration: 3785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25676 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.33592 L1 loss: 0.0000e+00 L2 loss: 1.97523 Learning rate: 0.02 Mask loss: 0.31271 RPN box loss: 0.04922 RPN score loss: 0.02342 RPN total loss: 0.07264 Total loss: 2.6965 timestamp: 1655011092.318318 iteration: 3790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17856 FastRCNN class loss: 0.11165 FastRCNN total loss: 0.29022 L1 loss: 0.0000e+00 L2 loss: 1.97485 Learning rate: 0.02 Mask loss: 0.27301 RPN box loss: 0.06335 RPN score loss: 0.03434 RPN total loss: 0.09769 Total loss: 2.63576 timestamp: 1655011095.6625106 iteration: 3795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23153 FastRCNN class loss: 0.0993 FastRCNN total loss: 0.33083 L1 loss: 0.0000e+00 L2 loss: 1.97446 Learning rate: 0.02 Mask loss: 0.20278 RPN box loss: 0.03536 RPN score loss: 0.02557 RPN total loss: 0.06093 Total loss: 2.56899 timestamp: 1655011098.9190397 iteration: 3800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28457 FastRCNN class loss: 0.13301 FastRCNN total loss: 0.41757 L1 loss: 0.0000e+00 L2 loss: 1.97409 Learning rate: 0.02 Mask loss: 0.223 RPN box loss: 0.03255 RPN score loss: 0.00713 RPN total loss: 0.03968 Total loss: 2.65435 timestamp: 1655011102.266072 iteration: 3805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19951 FastRCNN class loss: 0.13631 FastRCNN total loss: 0.33582 L1 loss: 0.0000e+00 L2 loss: 1.97371 Learning rate: 0.02 Mask loss: 0.33738 RPN box loss: 0.08542 RPN score loss: 0.02659 RPN total loss: 0.11201 Total loss: 2.75892 timestamp: 1655011105.6641018 iteration: 3810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32281 FastRCNN class loss: 0.2317 FastRCNN total loss: 0.55451 L1 loss: 0.0000e+00 L2 loss: 1.97333 Learning rate: 0.02 Mask loss: 0.26578 RPN box loss: 0.11407 RPN score loss: 0.02785 RPN total loss: 0.14192 Total loss: 2.93555 timestamp: 1655011109.0150564 iteration: 3815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27489 FastRCNN class loss: 0.094 FastRCNN total loss: 0.36889 L1 loss: 0.0000e+00 L2 loss: 1.97296 Learning rate: 0.02 Mask loss: 0.25271 RPN box loss: 0.04727 RPN score loss: 0.00963 RPN total loss: 0.0569 Total loss: 2.65146 timestamp: 1655011112.371026 iteration: 3820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18006 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.27187 L1 loss: 0.0000e+00 L2 loss: 1.9726 Learning rate: 0.02 Mask loss: 0.27441 RPN box loss: 0.08389 RPN score loss: 0.01715 RPN total loss: 0.10104 Total loss: 2.61993 timestamp: 1655011115.703743 iteration: 3825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20286 FastRCNN class loss: 0.12139 FastRCNN total loss: 0.32426 L1 loss: 0.0000e+00 L2 loss: 1.97221 Learning rate: 0.02 Mask loss: 0.25333 RPN box loss: 0.10518 RPN score loss: 0.0291 RPN total loss: 0.13428 Total loss: 2.68408 timestamp: 1655011118.9903913 iteration: 3830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19514 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.29047 L1 loss: 0.0000e+00 L2 loss: 1.97184 Learning rate: 0.02 Mask loss: 0.25966 RPN box loss: 0.0442 RPN score loss: 0.01361 RPN total loss: 0.05781 Total loss: 2.57979 timestamp: 1655011122.2266235 iteration: 3835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32399 FastRCNN class loss: 0.13418 FastRCNN total loss: 0.45817 L1 loss: 0.0000e+00 L2 loss: 1.97145 Learning rate: 0.02 Mask loss: 0.23284 RPN box loss: 0.0183 RPN score loss: 0.00929 RPN total loss: 0.02759 Total loss: 2.69005 timestamp: 1655011125.5595486 iteration: 3840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18017 FastRCNN class loss: 0.06482 FastRCNN total loss: 0.24499 L1 loss: 0.0000e+00 L2 loss: 1.97108 Learning rate: 0.02 Mask loss: 0.20739 RPN box loss: 0.03413 RPN score loss: 0.01298 RPN total loss: 0.04711 Total loss: 2.47057 timestamp: 1655011128.8892765 iteration: 3845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26838 FastRCNN class loss: 0.12253 FastRCNN total loss: 0.39091 L1 loss: 0.0000e+00 L2 loss: 1.97071 Learning rate: 0.02 Mask loss: 0.25689 RPN box loss: 0.02985 RPN score loss: 0.01482 RPN total loss: 0.04468 Total loss: 2.6632 timestamp: 1655011132.2473104 iteration: 3850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17486 FastRCNN class loss: 0.06085 FastRCNN total loss: 0.23571 L1 loss: 0.0000e+00 L2 loss: 1.97034 Learning rate: 0.02 Mask loss: 0.16306 RPN box loss: 0.04936 RPN score loss: 0.0081 RPN total loss: 0.05746 Total loss: 2.42657 timestamp: 1655011135.5663714 iteration: 3855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23831 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.34046 L1 loss: 0.0000e+00 L2 loss: 1.96995 Learning rate: 0.02 Mask loss: 0.28797 RPN box loss: 0.00773 RPN score loss: 0.00674 RPN total loss: 0.01446 Total loss: 2.61285 timestamp: 1655011138.8249497 iteration: 3860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1921 FastRCNN class loss: 0.16638 FastRCNN total loss: 0.35848 L1 loss: 0.0000e+00 L2 loss: 1.96958 Learning rate: 0.02 Mask loss: 0.33425 RPN box loss: 0.02665 RPN score loss: 0.0139 RPN total loss: 0.04054 Total loss: 2.70286 timestamp: 1655011142.2284863 iteration: 3865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23491 FastRCNN class loss: 0.09593 FastRCNN total loss: 0.33084 L1 loss: 0.0000e+00 L2 loss: 1.9692 Learning rate: 0.02 Mask loss: 0.25403 RPN box loss: 0.04147 RPN score loss: 0.00525 RPN total loss: 0.04673 Total loss: 2.6008 timestamp: 1655011145.5705743 iteration: 3870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21075 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.29437 L1 loss: 0.0000e+00 L2 loss: 1.96882 Learning rate: 0.02 Mask loss: 0.30822 RPN box loss: 0.03425 RPN score loss: 0.01144 RPN total loss: 0.04569 Total loss: 2.6171 timestamp: 1655011148.9804854 iteration: 3875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25679 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.35165 L1 loss: 0.0000e+00 L2 loss: 1.96844 Learning rate: 0.02 Mask loss: 0.21875 RPN box loss: 0.08763 RPN score loss: 0.03161 RPN total loss: 0.11924 Total loss: 2.65808 timestamp: 1655011152.2896948 iteration: 3880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18014 FastRCNN class loss: 0.09471 FastRCNN total loss: 0.27485 L1 loss: 0.0000e+00 L2 loss: 1.96807 Learning rate: 0.02 Mask loss: 0.27636 RPN box loss: 0.07086 RPN score loss: 0.01941 RPN total loss: 0.09027 Total loss: 2.60954 timestamp: 1655011155.5825253 iteration: 3885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18738 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.26154 L1 loss: 0.0000e+00 L2 loss: 1.9677 Learning rate: 0.02 Mask loss: 0.19706 RPN box loss: 0.0369 RPN score loss: 0.01296 RPN total loss: 0.04986 Total loss: 2.47616 timestamp: 1655011158.9336956 iteration: 3890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20267 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.28884 L1 loss: 0.0000e+00 L2 loss: 1.96733 Learning rate: 0.02 Mask loss: 0.35592 RPN box loss: 0.05009 RPN score loss: 0.02667 RPN total loss: 0.07676 Total loss: 2.68885 timestamp: 1655011162.211172 iteration: 3895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2283 FastRCNN class loss: 0.09333 FastRCNN total loss: 0.32163 L1 loss: 0.0000e+00 L2 loss: 1.96694 Learning rate: 0.02 Mask loss: 0.25656 RPN box loss: 0.05573 RPN score loss: 0.0109 RPN total loss: 0.06662 Total loss: 2.61176 timestamp: 1655011165.4654167 iteration: 3900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21679 FastRCNN class loss: 0.10277 FastRCNN total loss: 0.31956 L1 loss: 0.0000e+00 L2 loss: 1.96656 Learning rate: 0.02 Mask loss: 0.32138 RPN box loss: 0.11933 RPN score loss: 0.01941 RPN total loss: 0.13874 Total loss: 2.74624 timestamp: 1655011168.7667408 iteration: 3905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24053 FastRCNN class loss: 0.13144 FastRCNN total loss: 0.37197 L1 loss: 0.0000e+00 L2 loss: 1.96621 Learning rate: 0.02 Mask loss: 0.28731 RPN box loss: 0.04345 RPN score loss: 0.00929 RPN total loss: 0.05274 Total loss: 2.67823 timestamp: 1655011172.069777 iteration: 3910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25716 FastRCNN class loss: 0.12494 FastRCNN total loss: 0.38211 L1 loss: 0.0000e+00 L2 loss: 1.96585 Learning rate: 0.02 Mask loss: 0.23917 RPN box loss: 0.0738 RPN score loss: 0.01673 RPN total loss: 0.09053 Total loss: 2.67766 timestamp: 1655011175.4195392 iteration: 3915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22242 FastRCNN class loss: 0.10098 FastRCNN total loss: 0.32339 L1 loss: 0.0000e+00 L2 loss: 1.96547 Learning rate: 0.02 Mask loss: 0.20055 RPN box loss: 0.04323 RPN score loss: 0.02265 RPN total loss: 0.06588 Total loss: 2.55529 timestamp: 1655011178.6739478 iteration: 3920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17198 FastRCNN class loss: 0.07014 FastRCNN total loss: 0.24213 L1 loss: 0.0000e+00 L2 loss: 1.96508 Learning rate: 0.02 Mask loss: 0.33289 RPN box loss: 0.02426 RPN score loss: 0.01566 RPN total loss: 0.03992 Total loss: 2.58002 timestamp: 1655011182.0255063 iteration: 3925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25346 FastRCNN class loss: 0.10134 FastRCNN total loss: 0.3548 L1 loss: 0.0000e+00 L2 loss: 1.96471 Learning rate: 0.02 Mask loss: 0.19473 RPN box loss: 0.0317 RPN score loss: 0.01994 RPN total loss: 0.05164 Total loss: 2.56588 timestamp: 1655011185.3084116 iteration: 3930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23481 FastRCNN class loss: 0.09008 FastRCNN total loss: 0.3249 L1 loss: 0.0000e+00 L2 loss: 1.96432 Learning rate: 0.02 Mask loss: 0.1803 RPN box loss: 0.04918 RPN score loss: 0.00536 RPN total loss: 0.05453 Total loss: 2.52405 timestamp: 1655011188.6280582 iteration: 3935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19356 FastRCNN class loss: 0.10098 FastRCNN total loss: 0.29454 L1 loss: 0.0000e+00 L2 loss: 1.96394 Learning rate: 0.02 Mask loss: 0.27402 RPN box loss: 0.01657 RPN score loss: 0.01491 RPN total loss: 0.03148 Total loss: 2.56399 timestamp: 1655011191.8739493 iteration: 3940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22906 FastRCNN class loss: 0.09303 FastRCNN total loss: 0.32209 L1 loss: 0.0000e+00 L2 loss: 1.96358 Learning rate: 0.02 Mask loss: 0.18932 RPN box loss: 0.08012 RPN score loss: 0.01387 RPN total loss: 0.09399 Total loss: 2.56898 timestamp: 1655011195.1267297 iteration: 3945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16866 FastRCNN class loss: 0.11096 FastRCNN total loss: 0.27962 L1 loss: 0.0000e+00 L2 loss: 1.96322 Learning rate: 0.02 Mask loss: 0.25539 RPN box loss: 0.04516 RPN score loss: 0.0188 RPN total loss: 0.06396 Total loss: 2.5622 timestamp: 1655011198.3893518 iteration: 3950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25959 FastRCNN class loss: 0.15354 FastRCNN total loss: 0.41312 L1 loss: 0.0000e+00 L2 loss: 1.96285 Learning rate: 0.02 Mask loss: 0.33875 RPN box loss: 0.05371 RPN score loss: 0.0285 RPN total loss: 0.08221 Total loss: 2.79694 timestamp: 1655011201.7455902 iteration: 3955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37 FastRCNN class loss: 0.11979 FastRCNN total loss: 0.48978 L1 loss: 0.0000e+00 L2 loss: 1.96245 Learning rate: 0.02 Mask loss: 0.31743 RPN box loss: 0.01923 RPN score loss: 0.015 RPN total loss: 0.03423 Total loss: 2.80389 timestamp: 1655011205.0634882 iteration: 3960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28961 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.37323 L1 loss: 0.0000e+00 L2 loss: 1.96208 Learning rate: 0.02 Mask loss: 0.19652 RPN box loss: 0.05656 RPN score loss: 0.01884 RPN total loss: 0.0754 Total loss: 2.60723 timestamp: 1655011208.3387709 iteration: 3965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29501 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.41503 L1 loss: 0.0000e+00 L2 loss: 1.96173 Learning rate: 0.02 Mask loss: 0.27369 RPN box loss: 0.05711 RPN score loss: 0.02682 RPN total loss: 0.08393 Total loss: 2.73437 timestamp: 1655011211.629449 iteration: 3970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25987 FastRCNN class loss: 0.10581 FastRCNN total loss: 0.36568 L1 loss: 0.0000e+00 L2 loss: 1.96137 Learning rate: 0.02 Mask loss: 0.39638 RPN box loss: 0.04856 RPN score loss: 0.01406 RPN total loss: 0.06262 Total loss: 2.78604 timestamp: 1655011214.9363327 iteration: 3975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24112 FastRCNN class loss: 0.1122 FastRCNN total loss: 0.35332 L1 loss: 0.0000e+00 L2 loss: 1.961 Learning rate: 0.02 Mask loss: 0.24089 RPN box loss: 0.07241 RPN score loss: 0.02931 RPN total loss: 0.10172 Total loss: 2.65693 timestamp: 1655011218.1769595 iteration: 3980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26235 FastRCNN class loss: 0.10243 FastRCNN total loss: 0.36479 L1 loss: 0.0000e+00 L2 loss: 1.96063 Learning rate: 0.02 Mask loss: 0.43001 RPN box loss: 0.0583 RPN score loss: 0.02773 RPN total loss: 0.08603 Total loss: 2.84146 timestamp: 1655011221.5774257 iteration: 3985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27464 FastRCNN class loss: 0.08066 FastRCNN total loss: 0.3553 L1 loss: 0.0000e+00 L2 loss: 1.96024 Learning rate: 0.02 Mask loss: 0.22803 RPN box loss: 0.00873 RPN score loss: 0.01042 RPN total loss: 0.01915 Total loss: 2.56271 timestamp: 1655011224.8770297 iteration: 3990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32289 FastRCNN class loss: 0.15279 FastRCNN total loss: 0.47568 L1 loss: 0.0000e+00 L2 loss: 1.95985 Learning rate: 0.02 Mask loss: 0.31482 RPN box loss: 0.0194 RPN score loss: 0.01096 RPN total loss: 0.03037 Total loss: 2.78072 timestamp: 1655011228.169183 iteration: 3995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15943 FastRCNN class loss: 0.09302 FastRCNN total loss: 0.25245 L1 loss: 0.0000e+00 L2 loss: 1.95948 Learning rate: 0.02 Mask loss: 0.22438 RPN box loss: 0.06056 RPN score loss: 0.01846 RPN total loss: 0.07902 Total loss: 2.51533 timestamp: 1655011231.4671755 iteration: 4000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.42232 FastRCNN class loss: 0.14675 FastRCNN total loss: 0.56907 L1 loss: 0.0000e+00 L2 loss: 1.9591 Learning rate: 0.02 Mask loss: 0.34556 RPN box loss: 0.03953 RPN score loss: 0.01419 RPN total loss: 0.05372 Total loss: 2.92745 timestamp: 1655011234.7318501 iteration: 4005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19363 FastRCNN class loss: 0.16074 FastRCNN total loss: 0.35437 L1 loss: 0.0000e+00 L2 loss: 1.95873 Learning rate: 0.02 Mask loss: 0.27586 RPN box loss: 0.02987 RPN score loss: 0.0122 RPN total loss: 0.04207 Total loss: 2.63103 timestamp: 1655011238.0722222 iteration: 4010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20146 FastRCNN class loss: 0.09504 FastRCNN total loss: 0.29651 L1 loss: 0.0000e+00 L2 loss: 1.95835 Learning rate: 0.02 Mask loss: 0.19916 RPN box loss: 0.06913 RPN score loss: 0.01761 RPN total loss: 0.08674 Total loss: 2.54075 timestamp: 1655011241.3703198 iteration: 4015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29848 FastRCNN class loss: 0.12583 FastRCNN total loss: 0.42431 L1 loss: 0.0000e+00 L2 loss: 1.95798 Learning rate: 0.02 Mask loss: 0.3032 RPN box loss: 0.02156 RPN score loss: 0.01337 RPN total loss: 0.03494 Total loss: 2.72042 timestamp: 1655011244.7358007 iteration: 4020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23421 FastRCNN class loss: 0.14898 FastRCNN total loss: 0.38319 L1 loss: 0.0000e+00 L2 loss: 1.9576 Learning rate: 0.02 Mask loss: 0.28151 RPN box loss: 0.10511 RPN score loss: 0.01138 RPN total loss: 0.11649 Total loss: 2.7388 timestamp: 1655011248.0131178 iteration: 4025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17266 FastRCNN class loss: 0.08262 FastRCNN total loss: 0.25528 L1 loss: 0.0000e+00 L2 loss: 1.95726 Learning rate: 0.02 Mask loss: 0.32521 RPN box loss: 0.03123 RPN score loss: 0.00719 RPN total loss: 0.03842 Total loss: 2.57617 timestamp: 1655011251.3186646 iteration: 4030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25573 FastRCNN class loss: 0.10643 FastRCNN total loss: 0.36216 L1 loss: 0.0000e+00 L2 loss: 1.9569 Learning rate: 0.02 Mask loss: 0.22592 RPN box loss: 0.02513 RPN score loss: 0.00559 RPN total loss: 0.03072 Total loss: 2.57569 timestamp: 1655011254.584769 iteration: 4035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29152 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.37284 L1 loss: 0.0000e+00 L2 loss: 1.95652 Learning rate: 0.02 Mask loss: 0.27345 RPN box loss: 0.06835 RPN score loss: 0.0187 RPN total loss: 0.08705 Total loss: 2.68986 timestamp: 1655011257.8522248 iteration: 4040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2716 FastRCNN class loss: 0.16908 FastRCNN total loss: 0.44068 L1 loss: 0.0000e+00 L2 loss: 1.95614 Learning rate: 0.02 Mask loss: 0.39214 RPN box loss: 0.12861 RPN score loss: 0.02714 RPN total loss: 0.15575 Total loss: 2.94472 timestamp: 1655011261.1579914 iteration: 4045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11687 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.17904 L1 loss: 0.0000e+00 L2 loss: 1.95576 Learning rate: 0.02 Mask loss: 0.39434 RPN box loss: 0.07075 RPN score loss: 0.01458 RPN total loss: 0.08533 Total loss: 2.61446 timestamp: 1655011264.4407651 iteration: 4050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20461 FastRCNN class loss: 0.06521 FastRCNN total loss: 0.26982 L1 loss: 0.0000e+00 L2 loss: 1.95541 Learning rate: 0.02 Mask loss: 0.17923 RPN box loss: 0.03945 RPN score loss: 0.00971 RPN total loss: 0.04916 Total loss: 2.45361 timestamp: 1655011267.837279 iteration: 4055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20955 FastRCNN class loss: 0.08509 FastRCNN total loss: 0.29464 L1 loss: 0.0000e+00 L2 loss: 1.95503 Learning rate: 0.02 Mask loss: 0.20485 RPN box loss: 0.07132 RPN score loss: 0.01914 RPN total loss: 0.09046 Total loss: 2.54498 timestamp: 1655011271.1274276 iteration: 4060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22061 FastRCNN class loss: 0.08974 FastRCNN total loss: 0.31035 L1 loss: 0.0000e+00 L2 loss: 1.95464 Learning rate: 0.02 Mask loss: 0.20606 RPN box loss: 0.07364 RPN score loss: 0.00775 RPN total loss: 0.08138 Total loss: 2.55244 timestamp: 1655011274.440174 iteration: 4065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16526 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.22905 L1 loss: 0.0000e+00 L2 loss: 1.95428 Learning rate: 0.02 Mask loss: 0.20075 RPN box loss: 0.04001 RPN score loss: 0.01213 RPN total loss: 0.05214 Total loss: 2.43622 timestamp: 1655011277.7200978 iteration: 4070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24168 FastRCNN class loss: 0.10286 FastRCNN total loss: 0.34454 L1 loss: 0.0000e+00 L2 loss: 1.95391 Learning rate: 0.02 Mask loss: 0.25267 RPN box loss: 0.03071 RPN score loss: 0.00651 RPN total loss: 0.03722 Total loss: 2.58834 timestamp: 1655011280.965179 iteration: 4075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17643 FastRCNN class loss: 0.08684 FastRCNN total loss: 0.26327 L1 loss: 0.0000e+00 L2 loss: 1.95356 Learning rate: 0.02 Mask loss: 0.2463 RPN box loss: 0.02895 RPN score loss: 0.02244 RPN total loss: 0.0514 Total loss: 2.51452 timestamp: 1655011284.2690158 iteration: 4080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2552 FastRCNN class loss: 0.11379 FastRCNN total loss: 0.36899 L1 loss: 0.0000e+00 L2 loss: 1.95319 Learning rate: 0.02 Mask loss: 0.297 RPN box loss: 0.06019 RPN score loss: 0.01993 RPN total loss: 0.08011 Total loss: 2.69929 timestamp: 1655011287.6050088 iteration: 4085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27233 FastRCNN class loss: 0.14589 FastRCNN total loss: 0.41822 L1 loss: 0.0000e+00 L2 loss: 1.9528 Learning rate: 0.02 Mask loss: 0.3172 RPN box loss: 0.14638 RPN score loss: 0.0276 RPN total loss: 0.17398 Total loss: 2.8622 timestamp: 1655011290.8741124 iteration: 4090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28338 FastRCNN class loss: 0.13922 FastRCNN total loss: 0.42259 L1 loss: 0.0000e+00 L2 loss: 1.95242 Learning rate: 0.02 Mask loss: 0.29185 RPN box loss: 0.08165 RPN score loss: 0.02082 RPN total loss: 0.10246 Total loss: 2.76932 timestamp: 1655011294.2099404 iteration: 4095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24792 FastRCNN class loss: 0.11296 FastRCNN total loss: 0.36087 L1 loss: 0.0000e+00 L2 loss: 1.95206 Learning rate: 0.02 Mask loss: 0.17231 RPN box loss: 0.027 RPN score loss: 0.01349 RPN total loss: 0.04049 Total loss: 2.52573 timestamp: 1655011297.4234746 iteration: 4100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15905 FastRCNN class loss: 0.0629 FastRCNN total loss: 0.22195 L1 loss: 0.0000e+00 L2 loss: 1.95168 Learning rate: 0.02 Mask loss: 0.23004 RPN box loss: 0.09368 RPN score loss: 0.01799 RPN total loss: 0.11168 Total loss: 2.51534 timestamp: 1655011300.732312 iteration: 4105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22658 FastRCNN class loss: 0.12769 FastRCNN total loss: 0.35427 L1 loss: 0.0000e+00 L2 loss: 1.95132 Learning rate: 0.02 Mask loss: 0.25601 RPN box loss: 0.03505 RPN score loss: 0.00733 RPN total loss: 0.04239 Total loss: 2.60399 timestamp: 1655011304.0409532 iteration: 4110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29024 FastRCNN class loss: 0.10855 FastRCNN total loss: 0.39879 L1 loss: 0.0000e+00 L2 loss: 1.95094 Learning rate: 0.02 Mask loss: 0.25629 RPN box loss: 0.04684 RPN score loss: 0.01319 RPN total loss: 0.06002 Total loss: 2.66604 timestamp: 1655011307.3812077 iteration: 4115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22279 FastRCNN class loss: 0.14795 FastRCNN total loss: 0.37073 L1 loss: 0.0000e+00 L2 loss: 1.95058 Learning rate: 0.02 Mask loss: 0.24291 RPN box loss: 0.04692 RPN score loss: 0.0235 RPN total loss: 0.07043 Total loss: 2.63465 timestamp: 1655011310.6909573 iteration: 4120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17128 FastRCNN class loss: 0.08882 FastRCNN total loss: 0.2601 L1 loss: 0.0000e+00 L2 loss: 1.9502 Learning rate: 0.02 Mask loss: 0.24472 RPN box loss: 0.10623 RPN score loss: 0.02606 RPN total loss: 0.13229 Total loss: 2.58731 timestamp: 1655011313.9907858 iteration: 4125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30706 FastRCNN class loss: 0.1143 FastRCNN total loss: 0.42136 L1 loss: 0.0000e+00 L2 loss: 1.94983 Learning rate: 0.02 Mask loss: 0.27596 RPN box loss: 0.06181 RPN score loss: 0.01688 RPN total loss: 0.07869 Total loss: 2.72584 timestamp: 1655011317.2762353 iteration: 4130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1938 FastRCNN class loss: 0.1991 FastRCNN total loss: 0.3929 L1 loss: 0.0000e+00 L2 loss: 1.94944 Learning rate: 0.02 Mask loss: 0.37412 RPN box loss: 0.06224 RPN score loss: 0.14622 RPN total loss: 0.20846 Total loss: 2.92493 timestamp: 1655011320.5717783 iteration: 4135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.17278 L1 loss: 0.0000e+00 L2 loss: 1.94906 Learning rate: 0.02 Mask loss: 0.19589 RPN box loss: 0.13268 RPN score loss: 0.00991 RPN total loss: 0.14259 Total loss: 2.46032 timestamp: 1655011323.8898976 iteration: 4140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22914 FastRCNN class loss: 0.13259 FastRCNN total loss: 0.36172 L1 loss: 0.0000e+00 L2 loss: 1.94867 Learning rate: 0.02 Mask loss: 0.19858 RPN box loss: 0.08268 RPN score loss: 0.0091 RPN total loss: 0.09178 Total loss: 2.60075 timestamp: 1655011327.1531124 iteration: 4145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19267 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.2822 L1 loss: 0.0000e+00 L2 loss: 1.9483 Learning rate: 0.02 Mask loss: 0.22348 RPN box loss: 0.08181 RPN score loss: 0.01425 RPN total loss: 0.09606 Total loss: 2.55005 timestamp: 1655011330.4680855 iteration: 4150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24953 FastRCNN class loss: 0.1109 FastRCNN total loss: 0.36043 L1 loss: 0.0000e+00 L2 loss: 1.94795 Learning rate: 0.02 Mask loss: 0.29021 RPN box loss: 0.04384 RPN score loss: 0.01599 RPN total loss: 0.05984 Total loss: 2.65843 timestamp: 1655011333.8172088 iteration: 4155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19209 FastRCNN class loss: 0.09963 FastRCNN total loss: 0.29172 L1 loss: 0.0000e+00 L2 loss: 1.94759 Learning rate: 0.02 Mask loss: 0.22241 RPN box loss: 0.07587 RPN score loss: 0.01046 RPN total loss: 0.08633 Total loss: 2.54805 timestamp: 1655011337.2113001 iteration: 4160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1342 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.19653 L1 loss: 0.0000e+00 L2 loss: 1.94723 Learning rate: 0.02 Mask loss: 0.23888 RPN box loss: 0.04739 RPN score loss: 0.00522 RPN total loss: 0.05261 Total loss: 2.43525 timestamp: 1655011340.5043826 iteration: 4165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.05571 FastRCNN total loss: 0.19845 L1 loss: 0.0000e+00 L2 loss: 1.94685 Learning rate: 0.02 Mask loss: 0.26413 RPN box loss: 0.09582 RPN score loss: 0.02001 RPN total loss: 0.11583 Total loss: 2.52526 timestamp: 1655011343.8767347 iteration: 4170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20244 FastRCNN class loss: 0.14216 FastRCNN total loss: 0.3446 L1 loss: 0.0000e+00 L2 loss: 1.94647 Learning rate: 0.02 Mask loss: 0.34593 RPN box loss: 0.05198 RPN score loss: 0.01648 RPN total loss: 0.06846 Total loss: 2.70546 timestamp: 1655011347.2162025 iteration: 4175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19756 FastRCNN class loss: 0.09024 FastRCNN total loss: 0.2878 L1 loss: 0.0000e+00 L2 loss: 1.94609 Learning rate: 0.02 Mask loss: 0.21766 RPN box loss: 0.08567 RPN score loss: 0.01644 RPN total loss: 0.1021 Total loss: 2.55366 timestamp: 1655011350.6450663 iteration: 4180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21039 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.27818 L1 loss: 0.0000e+00 L2 loss: 1.94572 Learning rate: 0.02 Mask loss: 0.23329 RPN box loss: 0.08826 RPN score loss: 0.01146 RPN total loss: 0.09972 Total loss: 2.55691 timestamp: 1655011354.0807097 iteration: 4185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15694 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.2123 L1 loss: 0.0000e+00 L2 loss: 1.94535 Learning rate: 0.02 Mask loss: 0.31501 RPN box loss: 0.00582 RPN score loss: 0.00411 RPN total loss: 0.00994 Total loss: 2.4826 timestamp: 1655011357.3849447 iteration: 4190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21302 FastRCNN class loss: 0.111 FastRCNN total loss: 0.32401 L1 loss: 0.0000e+00 L2 loss: 1.94497 Learning rate: 0.02 Mask loss: 0.24404 RPN box loss: 0.04397 RPN score loss: 0.02305 RPN total loss: 0.06702 Total loss: 2.58004 timestamp: 1655011360.622303 iteration: 4195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26051 FastRCNN class loss: 0.1498 FastRCNN total loss: 0.41031 L1 loss: 0.0000e+00 L2 loss: 1.94461 Learning rate: 0.02 Mask loss: 0.2953 RPN box loss: 0.08117 RPN score loss: 0.02716 RPN total loss: 0.10833 Total loss: 2.75854 timestamp: 1655011363.92209 iteration: 4200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27442 FastRCNN class loss: 0.12811 FastRCNN total loss: 0.40252 L1 loss: 0.0000e+00 L2 loss: 1.94423 Learning rate: 0.02 Mask loss: 0.22497 RPN box loss: 0.02816 RPN score loss: 0.01881 RPN total loss: 0.04697 Total loss: 2.61869 timestamp: 1655011367.2436044 iteration: 4205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28992 FastRCNN class loss: 0.13033 FastRCNN total loss: 0.42024 L1 loss: 0.0000e+00 L2 loss: 1.94384 Learning rate: 0.02 Mask loss: 0.34321 RPN box loss: 0.01652 RPN score loss: 0.01103 RPN total loss: 0.02755 Total loss: 2.73483 timestamp: 1655011370.502115 iteration: 4210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19999 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.28087 L1 loss: 0.0000e+00 L2 loss: 1.94346 Learning rate: 0.02 Mask loss: 0.20852 RPN box loss: 0.06005 RPN score loss: 0.00826 RPN total loss: 0.0683 Total loss: 2.50115 timestamp: 1655011373.792786 iteration: 4215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16666 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.23385 L1 loss: 0.0000e+00 L2 loss: 1.9431 Learning rate: 0.02 Mask loss: 0.30198 RPN box loss: 0.0278 RPN score loss: 0.00583 RPN total loss: 0.03364 Total loss: 2.51257 timestamp: 1655011377.1121495 iteration: 4220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20231 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.2702 L1 loss: 0.0000e+00 L2 loss: 1.94273 Learning rate: 0.02 Mask loss: 0.2415 RPN box loss: 0.10262 RPN score loss: 0.01084 RPN total loss: 0.11346 Total loss: 2.56788 timestamp: 1655011380.449623 iteration: 4225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2084 FastRCNN class loss: 0.09301 FastRCNN total loss: 0.30142 L1 loss: 0.0000e+00 L2 loss: 1.94235 Learning rate: 0.02 Mask loss: 0.21376 RPN box loss: 0.07154 RPN score loss: 0.011 RPN total loss: 0.08254 Total loss: 2.54007 timestamp: 1655011383.7739766 iteration: 4230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20522 FastRCNN class loss: 0.12595 FastRCNN total loss: 0.33117 L1 loss: 0.0000e+00 L2 loss: 1.94199 Learning rate: 0.02 Mask loss: 0.21268 RPN box loss: 0.04973 RPN score loss: 0.01056 RPN total loss: 0.06029 Total loss: 2.54613 timestamp: 1655011387.0714846 iteration: 4235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27566 FastRCNN class loss: 0.11339 FastRCNN total loss: 0.38905 L1 loss: 0.0000e+00 L2 loss: 1.94164 Learning rate: 0.02 Mask loss: 0.23855 RPN box loss: 0.04637 RPN score loss: 0.01509 RPN total loss: 0.06145 Total loss: 2.63069 timestamp: 1655011390.4280512 iteration: 4240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1998 FastRCNN class loss: 0.12647 FastRCNN total loss: 0.32627 L1 loss: 0.0000e+00 L2 loss: 1.94127 Learning rate: 0.02 Mask loss: 0.26761 RPN box loss: 0.0318 RPN score loss: 0.00886 RPN total loss: 0.04066 Total loss: 2.57581 timestamp: 1655011393.720497 iteration: 4245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15888 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.23752 L1 loss: 0.0000e+00 L2 loss: 1.9409 Learning rate: 0.02 Mask loss: 0.23093 RPN box loss: 0.04345 RPN score loss: 0.00801 RPN total loss: 0.05147 Total loss: 2.46082 timestamp: 1655011397.128622 iteration: 4250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13694 FastRCNN class loss: 0.11313 FastRCNN total loss: 0.25007 L1 loss: 0.0000e+00 L2 loss: 1.94055 Learning rate: 0.02 Mask loss: 0.21164 RPN box loss: 0.03017 RPN score loss: 0.01249 RPN total loss: 0.04265 Total loss: 2.44491 timestamp: 1655011400.463656 iteration: 4255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26132 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.34868 L1 loss: 0.0000e+00 L2 loss: 1.9402 Learning rate: 0.02 Mask loss: 0.23297 RPN box loss: 0.08298 RPN score loss: 0.01337 RPN total loss: 0.09634 Total loss: 2.6182 timestamp: 1655011403.7780797 iteration: 4260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26566 FastRCNN class loss: 0.21542 FastRCNN total loss: 0.48108 L1 loss: 0.0000e+00 L2 loss: 1.93983 Learning rate: 0.02 Mask loss: 0.35101 RPN box loss: 0.02445 RPN score loss: 0.01452 RPN total loss: 0.03897 Total loss: 2.81089 timestamp: 1655011407.0200803 iteration: 4265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17185 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.28348 L1 loss: 0.0000e+00 L2 loss: 1.93946 Learning rate: 0.02 Mask loss: 0.22435 RPN box loss: 0.05602 RPN score loss: 0.0557 RPN total loss: 0.11173 Total loss: 2.55902 timestamp: 1655011410.4114208 iteration: 4270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2338 FastRCNN class loss: 0.12713 FastRCNN total loss: 0.36093 L1 loss: 0.0000e+00 L2 loss: 1.93909 Learning rate: 0.02 Mask loss: 0.27127 RPN box loss: 0.03468 RPN score loss: 0.02191 RPN total loss: 0.05659 Total loss: 2.62789 timestamp: 1655011413.721734 iteration: 4275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23049 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.31856 L1 loss: 0.0000e+00 L2 loss: 1.93874 Learning rate: 0.02 Mask loss: 0.2042 RPN box loss: 0.0256 RPN score loss: 0.01321 RPN total loss: 0.03881 Total loss: 2.50031 timestamp: 1655011416.999452 iteration: 4280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21483 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.29054 L1 loss: 0.0000e+00 L2 loss: 1.93835 Learning rate: 0.02 Mask loss: 0.23248 RPN box loss: 0.03275 RPN score loss: 0.01097 RPN total loss: 0.04372 Total loss: 2.50508 timestamp: 1655011420.3442073 iteration: 4285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22795 FastRCNN class loss: 0.12846 FastRCNN total loss: 0.35641 L1 loss: 0.0000e+00 L2 loss: 1.93799 Learning rate: 0.02 Mask loss: 0.2786 RPN box loss: 0.06347 RPN score loss: 0.01141 RPN total loss: 0.07488 Total loss: 2.64789 timestamp: 1655011423.6121602 iteration: 4290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27191 FastRCNN class loss: 0.10466 FastRCNN total loss: 0.37657 L1 loss: 0.0000e+00 L2 loss: 1.93762 Learning rate: 0.02 Mask loss: 0.34437 RPN box loss: 0.06979 RPN score loss: 0.02124 RPN total loss: 0.09103 Total loss: 2.74959 timestamp: 1655011426.987947 iteration: 4295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21271 FastRCNN class loss: 0.09371 FastRCNN total loss: 0.30643 L1 loss: 0.0000e+00 L2 loss: 1.93727 Learning rate: 0.02 Mask loss: 0.20325 RPN box loss: 0.07362 RPN score loss: 0.00895 RPN total loss: 0.08257 Total loss: 2.52952 timestamp: 1655011430.2987309 iteration: 4300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2216 FastRCNN class loss: 0.10208 FastRCNN total loss: 0.32368 L1 loss: 0.0000e+00 L2 loss: 1.93689 Learning rate: 0.02 Mask loss: 0.26015 RPN box loss: 0.06663 RPN score loss: 0.01869 RPN total loss: 0.08532 Total loss: 2.60604 timestamp: 1655011433.6736305 iteration: 4305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13816 FastRCNN class loss: 0.10995 FastRCNN total loss: 0.24811 L1 loss: 0.0000e+00 L2 loss: 1.93651 Learning rate: 0.02 Mask loss: 0.21479 RPN box loss: 0.05182 RPN score loss: 0.01065 RPN total loss: 0.06246 Total loss: 2.46188 timestamp: 1655011436.9561 iteration: 4310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18687 FastRCNN class loss: 0.09922 FastRCNN total loss: 0.28609 L1 loss: 0.0000e+00 L2 loss: 1.93613 Learning rate: 0.02 Mask loss: 0.24407 RPN box loss: 0.12196 RPN score loss: 0.01361 RPN total loss: 0.13557 Total loss: 2.60186 timestamp: 1655011440.2363713 iteration: 4315 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19888 FastRCNN class loss: 0.16508 FastRCNN total loss: 0.36397 L1 loss: 0.0000e+00 L2 loss: 1.93577 Learning rate: 0.02 Mask loss: 0.24277 RPN box loss: 0.0896 RPN score loss: 0.01668 RPN total loss: 0.10628 Total loss: 2.64878 timestamp: 1655011443.545048 iteration: 4320 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21968 FastRCNN class loss: 0.12206 FastRCNN total loss: 0.34174 L1 loss: 0.0000e+00 L2 loss: 1.93542 Learning rate: 0.02 Mask loss: 0.19307 RPN box loss: 0.09664 RPN score loss: 0.04299 RPN total loss: 0.13963 Total loss: 2.60986 timestamp: 1655011446.8022375 iteration: 4325 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26283 FastRCNN class loss: 0.1066 FastRCNN total loss: 0.36942 L1 loss: 0.0000e+00 L2 loss: 1.93505 Learning rate: 0.02 Mask loss: 0.22321 RPN box loss: 0.07529 RPN score loss: 0.0472 RPN total loss: 0.12249 Total loss: 2.65017 timestamp: 1655011450.1323504 iteration: 4330 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23962 FastRCNN class loss: 0.11951 FastRCNN total loss: 0.35914 L1 loss: 0.0000e+00 L2 loss: 1.93468 Learning rate: 0.02 Mask loss: 0.27864 RPN box loss: 0.05234 RPN score loss: 0.00959 RPN total loss: 0.06193 Total loss: 2.63439 timestamp: 1655011453.3750412 iteration: 4335 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22507 FastRCNN class loss: 0.08254 FastRCNN total loss: 0.30762 L1 loss: 0.0000e+00 L2 loss: 1.93431 Learning rate: 0.02 Mask loss: 0.21544 RPN box loss: 0.05279 RPN score loss: 0.0092 RPN total loss: 0.06199 Total loss: 2.51936 timestamp: 1655011456.700396 iteration: 4340 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27685 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.36296 L1 loss: 0.0000e+00 L2 loss: 1.93394 Learning rate: 0.02 Mask loss: 0.34255 RPN box loss: 0.0319 RPN score loss: 0.00551 RPN total loss: 0.03741 Total loss: 2.67687 timestamp: 1655011459.9929652 iteration: 4345 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21552 FastRCNN class loss: 0.09929 FastRCNN total loss: 0.31481 L1 loss: 0.0000e+00 L2 loss: 1.93356 Learning rate: 0.02 Mask loss: 0.19673 RPN box loss: 0.01945 RPN score loss: 0.00954 RPN total loss: 0.02899 Total loss: 2.47409 timestamp: 1655011463.3466341 iteration: 4350 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29904 FastRCNN class loss: 0.1805 FastRCNN total loss: 0.47954 L1 loss: 0.0000e+00 L2 loss: 1.93318 Learning rate: 0.02 Mask loss: 0.33953 RPN box loss: 0.05196 RPN score loss: 0.03808 RPN total loss: 0.09004 Total loss: 2.8423 timestamp: 1655011466.7142308 iteration: 4355 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2692 FastRCNN class loss: 0.12672 FastRCNN total loss: 0.39592 L1 loss: 0.0000e+00 L2 loss: 1.93283 Learning rate: 0.02 Mask loss: 0.2826 RPN box loss: 0.04124 RPN score loss: 0.00675 RPN total loss: 0.04798 Total loss: 2.65933 timestamp: 1655011470.0512493 iteration: 4360 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15874 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.249 L1 loss: 0.0000e+00 L2 loss: 1.93247 Learning rate: 0.02 Mask loss: 0.17181 RPN box loss: 0.02729 RPN score loss: 0.01243 RPN total loss: 0.03972 Total loss: 2.393 timestamp: 1655011473.3574858 iteration: 4365 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20339 FastRCNN class loss: 0.08681 FastRCNN total loss: 0.2902 L1 loss: 0.0000e+00 L2 loss: 1.9321 Learning rate: 0.02 Mask loss: 0.2115 RPN box loss: 0.0311 RPN score loss: 0.0056 RPN total loss: 0.0367 Total loss: 2.47049 timestamp: 1655011476.7684164 iteration: 4370 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22232 FastRCNN class loss: 0.18541 FastRCNN total loss: 0.40774 L1 loss: 0.0000e+00 L2 loss: 1.93171 Learning rate: 0.02 Mask loss: 0.31787 RPN box loss: 0.03988 RPN score loss: 0.0074 RPN total loss: 0.04729 Total loss: 2.7046 timestamp: 1655011480.1396956 iteration: 4375 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25274 FastRCNN class loss: 0.12549 FastRCNN total loss: 0.37823 L1 loss: 0.0000e+00 L2 loss: 1.93135 Learning rate: 0.02 Mask loss: 0.28429 RPN box loss: 0.06249 RPN score loss: 0.02412 RPN total loss: 0.08661 Total loss: 2.68047 timestamp: 1655011483.508571 iteration: 4380 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18052 FastRCNN class loss: 0.10487 FastRCNN total loss: 0.28539 L1 loss: 0.0000e+00 L2 loss: 1.93101 Learning rate: 0.02 Mask loss: 0.22683 RPN box loss: 0.07965 RPN score loss: 0.02688 RPN total loss: 0.10653 Total loss: 2.54975 timestamp: 1655011486.8368187 iteration: 4385 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2369 FastRCNN class loss: 0.10433 FastRCNN total loss: 0.34123 L1 loss: 0.0000e+00 L2 loss: 1.93064 Learning rate: 0.02 Mask loss: 0.24448 RPN box loss: 0.02582 RPN score loss: 0.01099 RPN total loss: 0.03681 Total loss: 2.55316 timestamp: 1655011490.1610982 iteration: 4390 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21219 FastRCNN class loss: 0.11238 FastRCNN total loss: 0.32456 L1 loss: 0.0000e+00 L2 loss: 1.93027 Learning rate: 0.02 Mask loss: 0.17055 RPN box loss: 0.03746 RPN score loss: 0.00932 RPN total loss: 0.04678 Total loss: 2.47216 timestamp: 1655011493.4292889 iteration: 4395 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31942 FastRCNN class loss: 0.16531 FastRCNN total loss: 0.48473 L1 loss: 0.0000e+00 L2 loss: 1.92991 Learning rate: 0.02 Mask loss: 0.4311 RPN box loss: 0.06091 RPN score loss: 0.02377 RPN total loss: 0.08467 Total loss: 2.93041 timestamp: 1655011496.668399 iteration: 4400 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15701 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.22723 L1 loss: 0.0000e+00 L2 loss: 1.92954 Learning rate: 0.02 Mask loss: 0.16054 RPN box loss: 0.06205 RPN score loss: 0.03344 RPN total loss: 0.0955 Total loss: 2.41281 timestamp: 1655011500.0273626 iteration: 4405 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15667 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.23618 L1 loss: 0.0000e+00 L2 loss: 1.92917 Learning rate: 0.02 Mask loss: 0.37227 RPN box loss: 0.02984 RPN score loss: 0.00702 RPN total loss: 0.03686 Total loss: 2.57448 timestamp: 1655011503.4434576 iteration: 4410 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20921 FastRCNN class loss: 0.11357 FastRCNN total loss: 0.32278 L1 loss: 0.0000e+00 L2 loss: 1.92879 Learning rate: 0.02 Mask loss: 0.23562 RPN box loss: 0.06181 RPN score loss: 0.02121 RPN total loss: 0.08302 Total loss: 2.57021 timestamp: 1655011506.7464032 iteration: 4415 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.302 FastRCNN class loss: 0.16851 FastRCNN total loss: 0.4705 L1 loss: 0.0000e+00 L2 loss: 1.92844 Learning rate: 0.02 Mask loss: 0.39264 RPN box loss: 0.06887 RPN score loss: 0.02277 RPN total loss: 0.09165 Total loss: 2.88323 timestamp: 1655011510.014197 iteration: 4420 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23408 FastRCNN class loss: 0.09004 FastRCNN total loss: 0.32412 L1 loss: 0.0000e+00 L2 loss: 1.92809 Learning rate: 0.02 Mask loss: 0.21503 RPN box loss: 0.01308 RPN score loss: 0.00355 RPN total loss: 0.01663 Total loss: 2.48387 timestamp: 1655011513.275047 iteration: 4425 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24278 FastRCNN class loss: 0.13309 FastRCNN total loss: 0.37586 L1 loss: 0.0000e+00 L2 loss: 1.92772 Learning rate: 0.02 Mask loss: 0.20714 RPN box loss: 0.02889 RPN score loss: 0.02633 RPN total loss: 0.05522 Total loss: 2.56594 timestamp: 1655011516.648169 iteration: 4430 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23733 FastRCNN class loss: 0.09688 FastRCNN total loss: 0.33421 L1 loss: 0.0000e+00 L2 loss: 1.92736 Learning rate: 0.02 Mask loss: 0.19883 RPN box loss: 0.03137 RPN score loss: 0.01184 RPN total loss: 0.04322 Total loss: 2.50361 timestamp: 1655011519.9971871 iteration: 4435 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20062 FastRCNN class loss: 0.0932 FastRCNN total loss: 0.29383 L1 loss: 0.0000e+00 L2 loss: 1.92698 Learning rate: 0.02 Mask loss: 0.22006 RPN box loss: 0.06454 RPN score loss: 0.03019 RPN total loss: 0.09473 Total loss: 2.5356 timestamp: 1655011523.3396137 iteration: 4440 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20211 FastRCNN class loss: 0.10024 FastRCNN total loss: 0.30235 L1 loss: 0.0000e+00 L2 loss: 1.92661 Learning rate: 0.02 Mask loss: 0.31169 RPN box loss: 0.06694 RPN score loss: 0.02378 RPN total loss: 0.09072 Total loss: 2.63136 timestamp: 1655011526.7007287 iteration: 4445 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27683 FastRCNN class loss: 0.175 FastRCNN total loss: 0.45182 L1 loss: 0.0000e+00 L2 loss: 1.92623 Learning rate: 0.02 Mask loss: 0.29146 RPN box loss: 0.09312 RPN score loss: 0.01411 RPN total loss: 0.10723 Total loss: 2.77673 timestamp: 1655011529.9907038 iteration: 4450 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22391 FastRCNN class loss: 0.1962 FastRCNN total loss: 0.42011 L1 loss: 0.0000e+00 L2 loss: 1.92587 Learning rate: 0.02 Mask loss: 0.2632 RPN box loss: 0.06052 RPN score loss: 0.01905 RPN total loss: 0.07958 Total loss: 2.68875 timestamp: 1655011533.2858436 iteration: 4455 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19406 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.26097 L1 loss: 0.0000e+00 L2 loss: 1.92551 Learning rate: 0.02 Mask loss: 0.29806 RPN box loss: 0.06997 RPN score loss: 0.01911 RPN total loss: 0.08908 Total loss: 2.57363 timestamp: 1655011536.5597034 iteration: 4460 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23018 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.33551 L1 loss: 0.0000e+00 L2 loss: 1.92515 Learning rate: 0.02 Mask loss: 0.2226 RPN box loss: 0.03081 RPN score loss: 0.00763 RPN total loss: 0.03843 Total loss: 2.52169 timestamp: 1655011539.766244 iteration: 4465 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14338 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.19993 L1 loss: 0.0000e+00 L2 loss: 1.92478 Learning rate: 0.02 Mask loss: 0.16181 RPN box loss: 0.07919 RPN score loss: 0.0137 RPN total loss: 0.09289 Total loss: 2.3794 timestamp: 1655011543.1318996 iteration: 4470 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27208 FastRCNN class loss: 0.16755 FastRCNN total loss: 0.43963 L1 loss: 0.0000e+00 L2 loss: 1.9244 Learning rate: 0.02 Mask loss: 0.29283 RPN box loss: 0.0496 RPN score loss: 0.01642 RPN total loss: 0.06602 Total loss: 2.72288 timestamp: 1655011546.35937 iteration: 4475 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27054 FastRCNN class loss: 0.14695 FastRCNN total loss: 0.41749 L1 loss: 0.0000e+00 L2 loss: 1.92402 Learning rate: 0.02 Mask loss: 0.25939 RPN box loss: 0.02188 RPN score loss: 0.01173 RPN total loss: 0.03361 Total loss: 2.63452 timestamp: 1655011549.6518786 iteration: 4480 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32257 FastRCNN class loss: 0.12945 FastRCNN total loss: 0.45201 L1 loss: 0.0000e+00 L2 loss: 1.92367 Learning rate: 0.02 Mask loss: 0.29621 RPN box loss: 0.0425 RPN score loss: 0.0273 RPN total loss: 0.06979 Total loss: 2.74169 timestamp: 1655011552.9577672 iteration: 4485 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18738 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.26202 L1 loss: 0.0000e+00 L2 loss: 1.92332 Learning rate: 0.02 Mask loss: 0.15125 RPN box loss: 0.01879 RPN score loss: 0.00711 RPN total loss: 0.0259 Total loss: 2.3625 timestamp: 1655011556.2447631 iteration: 4490 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14373 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.20496 L1 loss: 0.0000e+00 L2 loss: 1.92298 Learning rate: 0.02 Mask loss: 0.12441 RPN box loss: 0.07782 RPN score loss: 0.00935 RPN total loss: 0.08717 Total loss: 2.33951 timestamp: 1655011559.5649204 iteration: 4495 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13534 FastRCNN class loss: 0.06272 FastRCNN total loss: 0.19806 L1 loss: 0.0000e+00 L2 loss: 1.92261 Learning rate: 0.02 Mask loss: 0.20146 RPN box loss: 0.08994 RPN score loss: 0.00893 RPN total loss: 0.09887 Total loss: 2.421 timestamp: 1655011562.8072205 iteration: 4500 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17996 FastRCNN class loss: 0.11393 FastRCNN total loss: 0.29389 L1 loss: 0.0000e+00 L2 loss: 1.92224 Learning rate: 0.02 Mask loss: 0.1799 RPN box loss: 0.04342 RPN score loss: 0.00518 RPN total loss: 0.04859 Total loss: 2.44462 timestamp: 1655011566.1706908 iteration: 4505 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2031 FastRCNN class loss: 0.12765 FastRCNN total loss: 0.33076 L1 loss: 0.0000e+00 L2 loss: 1.92187 Learning rate: 0.02 Mask loss: 0.33371 RPN box loss: 0.0297 RPN score loss: 0.01076 RPN total loss: 0.04045 Total loss: 2.6268 timestamp: 1655011569.5242474 iteration: 4510 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26851 FastRCNN class loss: 0.11084 FastRCNN total loss: 0.37935 L1 loss: 0.0000e+00 L2 loss: 1.92151 Learning rate: 0.02 Mask loss: 0.34875 RPN box loss: 0.03104 RPN score loss: 0.00513 RPN total loss: 0.03617 Total loss: 2.68577 timestamp: 1655011572.8391602 iteration: 4515 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20592 FastRCNN class loss: 0.13343 FastRCNN total loss: 0.33934 L1 loss: 0.0000e+00 L2 loss: 1.92113 Learning rate: 0.02 Mask loss: 0.27582 RPN box loss: 0.08065 RPN score loss: 0.01756 RPN total loss: 0.09821 Total loss: 2.6345 timestamp: 1655011576.102128 iteration: 4520 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22864 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.31351 L1 loss: 0.0000e+00 L2 loss: 1.92077 Learning rate: 0.02 Mask loss: 0.22803 RPN box loss: 0.09519 RPN score loss: 0.01771 RPN total loss: 0.11289 Total loss: 2.5752 timestamp: 1655011579.4234927 iteration: 4525 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20108 FastRCNN class loss: 0.1018 FastRCNN total loss: 0.30289 L1 loss: 0.0000e+00 L2 loss: 1.9204 Learning rate: 0.02 Mask loss: 0.22494 RPN box loss: 0.03244 RPN score loss: 0.01452 RPN total loss: 0.04696 Total loss: 2.49518 timestamp: 1655011582.728157 iteration: 4530 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23065 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.29532 L1 loss: 0.0000e+00 L2 loss: 1.92004 Learning rate: 0.02 Mask loss: 0.14302 RPN box loss: 0.00975 RPN score loss: 0.00535 RPN total loss: 0.0151 Total loss: 2.37347 timestamp: 1655011585.995729 iteration: 4535 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22432 FastRCNN class loss: 0.12883 FastRCNN total loss: 0.35315 L1 loss: 0.0000e+00 L2 loss: 1.91965 Learning rate: 0.02 Mask loss: 0.20474 RPN box loss: 0.05006 RPN score loss: 0.00806 RPN total loss: 0.05812 Total loss: 2.53567 timestamp: 1655011589.31403 iteration: 4540 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17654 FastRCNN class loss: 0.12499 FastRCNN total loss: 0.30152 L1 loss: 0.0000e+00 L2 loss: 1.9193 Learning rate: 0.02 Mask loss: 0.27108 RPN box loss: 0.08923 RPN score loss: 0.06637 RPN total loss: 0.1556 Total loss: 2.6475 timestamp: 1655011592.5937974 iteration: 4545 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23981 FastRCNN class loss: 0.11372 FastRCNN total loss: 0.35353 L1 loss: 0.0000e+00 L2 loss: 1.91892 Learning rate: 0.02 Mask loss: 0.22945 RPN box loss: 0.05024 RPN score loss: 0.02549 RPN total loss: 0.07574 Total loss: 2.57763 timestamp: 1655011595.8951285 iteration: 4550 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17053 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.2355 L1 loss: 0.0000e+00 L2 loss: 1.91853 Learning rate: 0.02 Mask loss: 0.24995 RPN box loss: 0.01933 RPN score loss: 0.00772 RPN total loss: 0.02704 Total loss: 2.43103 timestamp: 1655011599.2107494 iteration: 4555 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21732 FastRCNN class loss: 0.12904 FastRCNN total loss: 0.34637 L1 loss: 0.0000e+00 L2 loss: 1.91819 Learning rate: 0.02 Mask loss: 0.2287 RPN box loss: 0.04133 RPN score loss: 0.02002 RPN total loss: 0.06134 Total loss: 2.55459 timestamp: 1655011602.4383812 iteration: 4560 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30719 FastRCNN class loss: 0.19053 FastRCNN total loss: 0.49772 L1 loss: 0.0000e+00 L2 loss: 1.91781 Learning rate: 0.02 Mask loss: 0.29336 RPN box loss: 0.13492 RPN score loss: 0.0282 RPN total loss: 0.16311 Total loss: 2.872 timestamp: 1655011605.7869449 iteration: 4565 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19679 FastRCNN class loss: 0.14566 FastRCNN total loss: 0.34245 L1 loss: 0.0000e+00 L2 loss: 1.91747 Learning rate: 0.02 Mask loss: 0.24837 RPN box loss: 0.0596 RPN score loss: 0.02006 RPN total loss: 0.07966 Total loss: 2.58795 timestamp: 1655011609.0567107 iteration: 4570 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22006 FastRCNN class loss: 0.09045 FastRCNN total loss: 0.31051 L1 loss: 0.0000e+00 L2 loss: 1.91709 Learning rate: 0.02 Mask loss: 0.17795 RPN box loss: 0.07709 RPN score loss: 0.01123 RPN total loss: 0.08832 Total loss: 2.49387 timestamp: 1655011612.4475014 iteration: 4575 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16367 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.25601 L1 loss: 0.0000e+00 L2 loss: 1.91674 Learning rate: 0.02 Mask loss: 0.21459 RPN box loss: 0.03104 RPN score loss: 0.01327 RPN total loss: 0.04431 Total loss: 2.43164 timestamp: 1655011615.825622 iteration: 4580 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19389 FastRCNN class loss: 0.09922 FastRCNN total loss: 0.29311 L1 loss: 0.0000e+00 L2 loss: 1.91639 Learning rate: 0.02 Mask loss: 0.21985 RPN box loss: 0.0486 RPN score loss: 0.01839 RPN total loss: 0.06699 Total loss: 2.49633 timestamp: 1655011619.1584926 iteration: 4585 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.19482 L1 loss: 0.0000e+00 L2 loss: 1.91602 Learning rate: 0.02 Mask loss: 0.1652 RPN box loss: 0.00511 RPN score loss: 0.00615 RPN total loss: 0.01126 Total loss: 2.28729 timestamp: 1655011622.4645736 iteration: 4590 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13489 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.20258 L1 loss: 0.0000e+00 L2 loss: 1.91564 Learning rate: 0.02 Mask loss: 0.19734 RPN box loss: 0.01356 RPN score loss: 0.00415 RPN total loss: 0.01771 Total loss: 2.33327 timestamp: 1655011625.7074113 iteration: 4595 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21548 FastRCNN class loss: 0.10488 FastRCNN total loss: 0.32036 L1 loss: 0.0000e+00 L2 loss: 1.91528 Learning rate: 0.02 Mask loss: 0.29488 RPN box loss: 0.01536 RPN score loss: 0.02527 RPN total loss: 0.04064 Total loss: 2.57116 timestamp: 1655011628.9599738 iteration: 4600 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14842 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.23827 L1 loss: 0.0000e+00 L2 loss: 1.91492 Learning rate: 0.02 Mask loss: 0.22302 RPN box loss: 0.05244 RPN score loss: 0.00819 RPN total loss: 0.06063 Total loss: 2.43683 timestamp: 1655011632.2185795 iteration: 4605 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26265 FastRCNN class loss: 0.11001 FastRCNN total loss: 0.37265 L1 loss: 0.0000e+00 L2 loss: 1.91457 Learning rate: 0.02 Mask loss: 0.27502 RPN box loss: 0.09583 RPN score loss: 0.02504 RPN total loss: 0.12087 Total loss: 2.68311 timestamp: 1655011635.4748807 iteration: 4610 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16612 FastRCNN class loss: 0.08654 FastRCNN total loss: 0.25267 L1 loss: 0.0000e+00 L2 loss: 1.91421 Learning rate: 0.02 Mask loss: 0.18866 RPN box loss: 0.0265 RPN score loss: 0.0259 RPN total loss: 0.05239 Total loss: 2.40794 timestamp: 1655011638.7769024 iteration: 4615 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16415 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.24629 L1 loss: 0.0000e+00 L2 loss: 1.91384 Learning rate: 0.02 Mask loss: 0.24078 RPN box loss: 0.09089 RPN score loss: 0.01793 RPN total loss: 0.10882 Total loss: 2.50973 timestamp: 1655011642.0446198 iteration: 4620 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22304 FastRCNN class loss: 0.16014 FastRCNN total loss: 0.38318 L1 loss: 0.0000e+00 L2 loss: 1.91347 Learning rate: 0.02 Mask loss: 0.28954 RPN box loss: 0.04513 RPN score loss: 0.00788 RPN total loss: 0.053 Total loss: 2.6392 timestamp: 1655011645.3612058 iteration: 4625 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24209 FastRCNN class loss: 0.15703 FastRCNN total loss: 0.39912 L1 loss: 0.0000e+00 L2 loss: 1.91311 Learning rate: 0.02 Mask loss: 0.23002 RPN box loss: 0.08595 RPN score loss: 0.00864 RPN total loss: 0.09459 Total loss: 2.63684 timestamp: 1655011648.7158337 iteration: 4630 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30266 FastRCNN class loss: 0.13803 FastRCNN total loss: 0.44069 L1 loss: 0.0000e+00 L2 loss: 1.91274 Learning rate: 0.02 Mask loss: 0.38468 RPN box loss: 0.08705 RPN score loss: 0.017 RPN total loss: 0.10405 Total loss: 2.84216 timestamp: 1655011652.0904186 iteration: 4635 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18972 FastRCNN class loss: 0.10032 FastRCNN total loss: 0.29004 L1 loss: 0.0000e+00 L2 loss: 1.91236 Learning rate: 0.02 Mask loss: 0.26794 RPN box loss: 0.07222 RPN score loss: 0.01496 RPN total loss: 0.08717 Total loss: 2.55751 timestamp: 1655011655.4178317 iteration: 4640 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24362 FastRCNN class loss: 0.11301 FastRCNN total loss: 0.35663 L1 loss: 0.0000e+00 L2 loss: 1.91202 Learning rate: 0.02 Mask loss: 0.2296 RPN box loss: 0.04609 RPN score loss: 0.01343 RPN total loss: 0.05952 Total loss: 2.55777 timestamp: 1655011658.8503706 iteration: 4645 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21305 FastRCNN class loss: 0.12636 FastRCNN total loss: 0.33941 L1 loss: 0.0000e+00 L2 loss: 1.91167 Learning rate: 0.02 Mask loss: 0.253 RPN box loss: 0.04157 RPN score loss: 0.00996 RPN total loss: 0.05153 Total loss: 2.55561 timestamp: 1655011662.1574972 iteration: 4650 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2463 FastRCNN class loss: 0.10903 FastRCNN total loss: 0.35533 L1 loss: 0.0000e+00 L2 loss: 1.91129 Learning rate: 0.02 Mask loss: 0.19085 RPN box loss: 0.07394 RPN score loss: 0.00664 RPN total loss: 0.08057 Total loss: 2.53804 timestamp: 1655011665.4738762 iteration: 4655 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22464 FastRCNN class loss: 0.08156 FastRCNN total loss: 0.3062 L1 loss: 0.0000e+00 L2 loss: 1.91091 Learning rate: 0.02 Mask loss: 0.22673 RPN box loss: 0.01849 RPN score loss: 0.00751 RPN total loss: 0.026 Total loss: 2.46983 timestamp: 1655011668.809128 iteration: 4660 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20771 FastRCNN class loss: 0.17899 FastRCNN total loss: 0.38671 L1 loss: 0.0000e+00 L2 loss: 1.91057 Learning rate: 0.02 Mask loss: 0.19115 RPN box loss: 0.06036 RPN score loss: 0.01238 RPN total loss: 0.07274 Total loss: 2.56117 timestamp: 1655011672.1640203 iteration: 4665 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22078 FastRCNN class loss: 0.15842 FastRCNN total loss: 0.37919 L1 loss: 0.0000e+00 L2 loss: 1.91023 Learning rate: 0.02 Mask loss: 0.22733 RPN box loss: 0.04248 RPN score loss: 0.02862 RPN total loss: 0.0711 Total loss: 2.58785 timestamp: 1655011675.4174068 iteration: 4670 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0816 FastRCNN class loss: 0.04574 FastRCNN total loss: 0.12733 L1 loss: 0.0000e+00 L2 loss: 1.90987 Learning rate: 0.02 Mask loss: 0.18462 RPN box loss: 0.04706 RPN score loss: 0.00435 RPN total loss: 0.05142 Total loss: 2.27324 timestamp: 1655011678.7625816 iteration: 4675 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24458 FastRCNN class loss: 0.15275 FastRCNN total loss: 0.39733 L1 loss: 0.0000e+00 L2 loss: 1.90949 Learning rate: 0.02 Mask loss: 0.26614 RPN box loss: 0.09456 RPN score loss: 0.01337 RPN total loss: 0.10793 Total loss: 2.68089 timestamp: 1655011682.0385232 iteration: 4680 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28129 FastRCNN class loss: 0.14747 FastRCNN total loss: 0.42876 L1 loss: 0.0000e+00 L2 loss: 1.90914 Learning rate: 0.02 Mask loss: 0.27207 RPN box loss: 0.14876 RPN score loss: 0.01441 RPN total loss: 0.16317 Total loss: 2.77314 timestamp: 1655011685.4044886 iteration: 4685 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19604 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.30759 L1 loss: 0.0000e+00 L2 loss: 1.90878 Learning rate: 0.02 Mask loss: 0.26122 RPN box loss: 0.04361 RPN score loss: 0.01968 RPN total loss: 0.06329 Total loss: 2.54088 timestamp: 1655011688.6619387 iteration: 4690 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20439 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.28435 L1 loss: 0.0000e+00 L2 loss: 1.9084 Learning rate: 0.02 Mask loss: 0.22499 RPN box loss: 0.0491 RPN score loss: 0.01035 RPN total loss: 0.05945 Total loss: 2.47719 timestamp: 1655011692.033422 iteration: 4695 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21244 FastRCNN class loss: 0.15032 FastRCNN total loss: 0.36276 L1 loss: 0.0000e+00 L2 loss: 1.90805 Learning rate: 0.02 Mask loss: 0.21663 RPN box loss: 0.03614 RPN score loss: 0.00691 RPN total loss: 0.04305 Total loss: 2.53049 timestamp: 1655011695.4258988 iteration: 4700 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.37 FastRCNN class loss: 0.14945 FastRCNN total loss: 0.51945 L1 loss: 0.0000e+00 L2 loss: 1.90768 Learning rate: 0.02 Mask loss: 0.27623 RPN box loss: 0.05305 RPN score loss: 0.03022 RPN total loss: 0.08328 Total loss: 2.78664 timestamp: 1655011698.6873372 iteration: 4705 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15193 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.22137 L1 loss: 0.0000e+00 L2 loss: 1.90731 Learning rate: 0.02 Mask loss: 0.2133 RPN box loss: 0.03087 RPN score loss: 0.0089 RPN total loss: 0.03977 Total loss: 2.38175 timestamp: 1655011701.968699 iteration: 4710 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17653 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.2656 L1 loss: 0.0000e+00 L2 loss: 1.90694 Learning rate: 0.02 Mask loss: 0.22593 RPN box loss: 0.10397 RPN score loss: 0.03809 RPN total loss: 0.14205 Total loss: 2.54052 timestamp: 1655011705.3452988 iteration: 4715 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13734 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.22402 L1 loss: 0.0000e+00 L2 loss: 1.90658 Learning rate: 0.02 Mask loss: 0.21604 RPN box loss: 0.02949 RPN score loss: 0.01051 RPN total loss: 0.04001 Total loss: 2.38664 timestamp: 1655011708.7706506 iteration: 4720 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2213 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.29703 L1 loss: 0.0000e+00 L2 loss: 1.90623 Learning rate: 0.02 Mask loss: 0.19966 RPN box loss: 0.04127 RPN score loss: 0.01516 RPN total loss: 0.05642 Total loss: 2.45935 timestamp: 1655011712.092176 iteration: 4725 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22456 FastRCNN class loss: 0.10208 FastRCNN total loss: 0.32665 L1 loss: 0.0000e+00 L2 loss: 1.90587 Learning rate: 0.02 Mask loss: 0.22339 RPN box loss: 0.04497 RPN score loss: 0.01278 RPN total loss: 0.05775 Total loss: 2.51366 timestamp: 1655011715.4038348 iteration: 4730 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29212 FastRCNN class loss: 0.17357 FastRCNN total loss: 0.46569 L1 loss: 0.0000e+00 L2 loss: 1.90552 Learning rate: 0.02 Mask loss: 0.30141 RPN box loss: 0.10362 RPN score loss: 0.02464 RPN total loss: 0.12827 Total loss: 2.80089 timestamp: 1655011718.7402122 iteration: 4735 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13364 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.19294 L1 loss: 0.0000e+00 L2 loss: 1.90516 Learning rate: 0.02 Mask loss: 0.16746 RPN box loss: 0.0198 RPN score loss: 0.00511 RPN total loss: 0.02491 Total loss: 2.29047 timestamp: 1655011721.97927 iteration: 4740 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23806 FastRCNN class loss: 0.13565 FastRCNN total loss: 0.37371 L1 loss: 0.0000e+00 L2 loss: 1.90478 Learning rate: 0.02 Mask loss: 0.21546 RPN box loss: 0.05825 RPN score loss: 0.01199 RPN total loss: 0.07025 Total loss: 2.5642 timestamp: 1655011725.2037106 iteration: 4745 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16543 FastRCNN class loss: 0.11623 FastRCNN total loss: 0.28167 L1 loss: 0.0000e+00 L2 loss: 1.90444 Learning rate: 0.02 Mask loss: 0.27315 RPN box loss: 0.03054 RPN score loss: 0.00795 RPN total loss: 0.03848 Total loss: 2.49773 timestamp: 1655011728.4929452 iteration: 4750 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1715 FastRCNN class loss: 0.10428 FastRCNN total loss: 0.27577 L1 loss: 0.0000e+00 L2 loss: 1.90407 Learning rate: 0.02 Mask loss: 0.21935 RPN box loss: 0.0427 RPN score loss: 0.00892 RPN total loss: 0.05162 Total loss: 2.45081 timestamp: 1655011731.8163724 iteration: 4755 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07266 FastRCNN class loss: 0.09499 FastRCNN total loss: 0.16765 L1 loss: 0.0000e+00 L2 loss: 1.90372 Learning rate: 0.02 Mask loss: 0.2658 RPN box loss: 0.05371 RPN score loss: 0.03532 RPN total loss: 0.08903 Total loss: 2.42619 timestamp: 1655011735.0811515 iteration: 4760 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22893 FastRCNN class loss: 0.13473 FastRCNN total loss: 0.36366 L1 loss: 0.0000e+00 L2 loss: 1.90336 Learning rate: 0.02 Mask loss: 0.32145 RPN box loss: 0.04259 RPN score loss: 0.01401 RPN total loss: 0.0566 Total loss: 2.64507 timestamp: 1655011738.448845 iteration: 4765 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18786 FastRCNN class loss: 0.10197 FastRCNN total loss: 0.28983 L1 loss: 0.0000e+00 L2 loss: 1.90301 Learning rate: 0.02 Mask loss: 0.19554 RPN box loss: 0.02974 RPN score loss: 0.01303 RPN total loss: 0.04278 Total loss: 2.43115 timestamp: 1655011741.7312312 iteration: 4770 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21739 FastRCNN class loss: 0.16795 FastRCNN total loss: 0.38534 L1 loss: 0.0000e+00 L2 loss: 1.90265 Learning rate: 0.02 Mask loss: 0.35484 RPN box loss: 0.08956 RPN score loss: 0.0174 RPN total loss: 0.10696 Total loss: 2.74979 timestamp: 1655011745.0831409 iteration: 4775 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2562 FastRCNN class loss: 0.11239 FastRCNN total loss: 0.36859 L1 loss: 0.0000e+00 L2 loss: 1.90228 Learning rate: 0.02 Mask loss: 0.38334 RPN box loss: 0.08754 RPN score loss: 0.01013 RPN total loss: 0.09768 Total loss: 2.75189 timestamp: 1655011748.2882686 iteration: 4780 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19565 FastRCNN class loss: 0.10362 FastRCNN total loss: 0.29927 L1 loss: 0.0000e+00 L2 loss: 1.90191 Learning rate: 0.02 Mask loss: 0.25597 RPN box loss: 0.03041 RPN score loss: 0.02897 RPN total loss: 0.05938 Total loss: 2.51653 timestamp: 1655011751.5343325 iteration: 4785 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21382 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.29268 L1 loss: 0.0000e+00 L2 loss: 1.90154 Learning rate: 0.02 Mask loss: 0.26717 RPN box loss: 0.10148 RPN score loss: 0.01444 RPN total loss: 0.11592 Total loss: 2.5773 timestamp: 1655011754.9011927 iteration: 4790 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18813 FastRCNN class loss: 0.07051 FastRCNN total loss: 0.25863 L1 loss: 0.0000e+00 L2 loss: 1.90119 Learning rate: 0.02 Mask loss: 0.24527 RPN box loss: 0.04596 RPN score loss: 0.01019 RPN total loss: 0.05615 Total loss: 2.46124 timestamp: 1655011758.1713235 iteration: 4795 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29773 FastRCNN class loss: 0.14218 FastRCNN total loss: 0.43992 L1 loss: 0.0000e+00 L2 loss: 1.90083 Learning rate: 0.02 Mask loss: 0.24422 RPN box loss: 0.04471 RPN score loss: 0.01803 RPN total loss: 0.06275 Total loss: 2.64771 timestamp: 1655011761.5483925 iteration: 4800 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18207 FastRCNN class loss: 0.10204 FastRCNN total loss: 0.28411 L1 loss: 0.0000e+00 L2 loss: 1.90045 Learning rate: 0.02 Mask loss: 0.2478 RPN box loss: 0.07663 RPN score loss: 0.02458 RPN total loss: 0.10121 Total loss: 2.53357 timestamp: 1655011764.8220735 iteration: 4805 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22376 FastRCNN class loss: 0.15452 FastRCNN total loss: 0.37828 L1 loss: 0.0000e+00 L2 loss: 1.90009 Learning rate: 0.02 Mask loss: 0.26589 RPN box loss: 0.08835 RPN score loss: 0.01529 RPN total loss: 0.10365 Total loss: 2.64791 timestamp: 1655011768.2009366 iteration: 4810 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2299 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.31424 L1 loss: 0.0000e+00 L2 loss: 1.89972 Learning rate: 0.02 Mask loss: 0.20678 RPN box loss: 0.05417 RPN score loss: 0.00892 RPN total loss: 0.06309 Total loss: 2.48383 timestamp: 1655011771.4175432 iteration: 4815 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14434 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.21936 L1 loss: 0.0000e+00 L2 loss: 1.89937 Learning rate: 0.02 Mask loss: 0.19783 RPN box loss: 0.02371 RPN score loss: 0.01739 RPN total loss: 0.0411 Total loss: 2.35767 timestamp: 1655011774.6643603 iteration: 4820 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13108 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.1808 L1 loss: 0.0000e+00 L2 loss: 1.89902 Learning rate: 0.02 Mask loss: 0.17081 RPN box loss: 0.03233 RPN score loss: 0.00834 RPN total loss: 0.04067 Total loss: 2.2913 timestamp: 1655011777.9482043 iteration: 4825 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30266 FastRCNN class loss: 0.22364 FastRCNN total loss: 0.52629 L1 loss: 0.0000e+00 L2 loss: 1.89865 Learning rate: 0.02 Mask loss: 0.3437 RPN box loss: 0.13548 RPN score loss: 0.02388 RPN total loss: 0.15935 Total loss: 2.928 timestamp: 1655011781.288332 iteration: 4830 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22619 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.31929 L1 loss: 0.0000e+00 L2 loss: 1.89831 Learning rate: 0.02 Mask loss: 0.18458 RPN box loss: 0.01357 RPN score loss: 0.0039 RPN total loss: 0.01747 Total loss: 2.41966 timestamp: 1655011784.621865 iteration: 4835 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23059 FastRCNN class loss: 0.15147 FastRCNN total loss: 0.38206 L1 loss: 0.0000e+00 L2 loss: 1.89797 Learning rate: 0.02 Mask loss: 0.2178 RPN box loss: 0.05727 RPN score loss: 0.01964 RPN total loss: 0.07691 Total loss: 2.57473 timestamp: 1655011787.9004323 iteration: 4840 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20086 FastRCNN class loss: 0.10281 FastRCNN total loss: 0.30367 L1 loss: 0.0000e+00 L2 loss: 1.89763 Learning rate: 0.02 Mask loss: 0.18629 RPN box loss: 0.04265 RPN score loss: 0.0059 RPN total loss: 0.04856 Total loss: 2.43614 timestamp: 1655011791.2263882 iteration: 4845 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13279 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.19225 L1 loss: 0.0000e+00 L2 loss: 1.89726 Learning rate: 0.02 Mask loss: 0.16986 RPN box loss: 0.01566 RPN score loss: 0.00971 RPN total loss: 0.02536 Total loss: 2.28474 timestamp: 1655011794.509079 iteration: 4850 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17158 FastRCNN class loss: 0.11354 FastRCNN total loss: 0.28512 L1 loss: 0.0000e+00 L2 loss: 1.89689 Learning rate: 0.02 Mask loss: 0.17942 RPN box loss: 0.02013 RPN score loss: 0.01618 RPN total loss: 0.0363 Total loss: 2.39772 timestamp: 1655011797.8703616 iteration: 4855 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1723 FastRCNN class loss: 0.08454 FastRCNN total loss: 0.25684 L1 loss: 0.0000e+00 L2 loss: 1.89652 Learning rate: 0.02 Mask loss: 0.2589 RPN box loss: 0.07243 RPN score loss: 0.00892 RPN total loss: 0.08135 Total loss: 2.49361 timestamp: 1655011801.1664066 iteration: 4860 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16821 FastRCNN class loss: 0.10271 FastRCNN total loss: 0.27091 L1 loss: 0.0000e+00 L2 loss: 1.89615 Learning rate: 0.02 Mask loss: 0.22147 RPN box loss: 0.05017 RPN score loss: 0.01659 RPN total loss: 0.06676 Total loss: 2.45529 timestamp: 1655011804.4485152 iteration: 4865 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26646 FastRCNN class loss: 0.13417 FastRCNN total loss: 0.40062 L1 loss: 0.0000e+00 L2 loss: 1.8958 Learning rate: 0.02 Mask loss: 0.28058 RPN box loss: 0.03771 RPN score loss: 0.04639 RPN total loss: 0.0841 Total loss: 2.66111 timestamp: 1655011807.697301 iteration: 4870 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1682 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.243 L1 loss: 0.0000e+00 L2 loss: 1.89545 Learning rate: 0.02 Mask loss: 0.17126 RPN box loss: 0.0467 RPN score loss: 0.02349 RPN total loss: 0.0702 Total loss: 2.37991 timestamp: 1655011810.9953816 iteration: 4875 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28507 FastRCNN class loss: 0.12731 FastRCNN total loss: 0.41238 L1 loss: 0.0000e+00 L2 loss: 1.89508 Learning rate: 0.02 Mask loss: 0.32141 RPN box loss: 0.04038 RPN score loss: 0.02208 RPN total loss: 0.06246 Total loss: 2.69133 timestamp: 1655011814.3689651 iteration: 4880 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24962 FastRCNN class loss: 0.14646 FastRCNN total loss: 0.39608 L1 loss: 0.0000e+00 L2 loss: 1.89472 Learning rate: 0.02 Mask loss: 0.40225 RPN box loss: 0.05112 RPN score loss: 0.012 RPN total loss: 0.06312 Total loss: 2.75618 timestamp: 1655011817.6279502 iteration: 4885 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27539 FastRCNN class loss: 0.16309 FastRCNN total loss: 0.43847 L1 loss: 0.0000e+00 L2 loss: 1.89435 Learning rate: 0.02 Mask loss: 0.27746 RPN box loss: 0.07777 RPN score loss: 0.01352 RPN total loss: 0.09129 Total loss: 2.70157 timestamp: 1655011820.9467773 iteration: 4890 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18744 FastRCNN class loss: 0.08381 FastRCNN total loss: 0.27124 L1 loss: 0.0000e+00 L2 loss: 1.894 Learning rate: 0.02 Mask loss: 0.18651 RPN box loss: 0.01297 RPN score loss: 0.00754 RPN total loss: 0.02051 Total loss: 2.37227 timestamp: 1655011824.2567148 iteration: 4895 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1792 FastRCNN class loss: 0.09124 FastRCNN total loss: 0.27044 L1 loss: 0.0000e+00 L2 loss: 1.89365 Learning rate: 0.02 Mask loss: 0.19989 RPN box loss: 0.03925 RPN score loss: 0.01102 RPN total loss: 0.05027 Total loss: 2.41425 timestamp: 1655011827.5882611 iteration: 4900 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18625 FastRCNN class loss: 0.08729 FastRCNN total loss: 0.27354 L1 loss: 0.0000e+00 L2 loss: 1.89332 Learning rate: 0.02 Mask loss: 0.27788 RPN box loss: 0.03429 RPN score loss: 0.01718 RPN total loss: 0.05147 Total loss: 2.49622 timestamp: 1655011830.9244137 iteration: 4905 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20757 FastRCNN class loss: 0.12206 FastRCNN total loss: 0.32963 L1 loss: 0.0000e+00 L2 loss: 1.89295 Learning rate: 0.02 Mask loss: 0.20482 RPN box loss: 0.08609 RPN score loss: 0.00801 RPN total loss: 0.0941 Total loss: 2.5215 timestamp: 1655011834.3019238 iteration: 4910 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21207 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.28099 L1 loss: 0.0000e+00 L2 loss: 1.8926 Learning rate: 0.02 Mask loss: 0.20506 RPN box loss: 0.02242 RPN score loss: 0.00514 RPN total loss: 0.02756 Total loss: 2.40621 timestamp: 1655011837.6562893 iteration: 4915 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17729 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.247 L1 loss: 0.0000e+00 L2 loss: 1.89224 Learning rate: 0.02 Mask loss: 0.19279 RPN box loss: 0.06467 RPN score loss: 0.01829 RPN total loss: 0.08295 Total loss: 2.41499 timestamp: 1655011840.9023693 iteration: 4920 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.16076 L1 loss: 0.0000e+00 L2 loss: 1.8919 Learning rate: 0.02 Mask loss: 0.19036 RPN box loss: 0.01647 RPN score loss: 0.00549 RPN total loss: 0.02195 Total loss: 2.26498 timestamp: 1655011844.196554 iteration: 4925 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24029 FastRCNN class loss: 0.07077 FastRCNN total loss: 0.31106 L1 loss: 0.0000e+00 L2 loss: 1.89155 Learning rate: 0.02 Mask loss: 0.17016 RPN box loss: 0.02493 RPN score loss: 0.00923 RPN total loss: 0.03417 Total loss: 2.40693 timestamp: 1655011847.5109599 iteration: 4930 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27132 FastRCNN class loss: 0.15857 FastRCNN total loss: 0.42989 L1 loss: 0.0000e+00 L2 loss: 1.89119 Learning rate: 0.02 Mask loss: 0.23837 RPN box loss: 0.03532 RPN score loss: 0.01809 RPN total loss: 0.05341 Total loss: 2.61286 timestamp: 1655011850.7944124 iteration: 4935 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11683 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.18313 L1 loss: 0.0000e+00 L2 loss: 1.89082 Learning rate: 0.02 Mask loss: 0.21337 RPN box loss: 0.11056 RPN score loss: 0.01103 RPN total loss: 0.12159 Total loss: 2.40892 timestamp: 1655011854.0694 iteration: 4940 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19654 FastRCNN class loss: 0.06344 FastRCNN total loss: 0.25998 L1 loss: 0.0000e+00 L2 loss: 1.89046 Learning rate: 0.02 Mask loss: 0.19665 RPN box loss: 0.09899 RPN score loss: 0.00868 RPN total loss: 0.10766 Total loss: 2.45476 timestamp: 1655011857.3516073 iteration: 4945 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21955 FastRCNN class loss: 0.13223 FastRCNN total loss: 0.35178 L1 loss: 0.0000e+00 L2 loss: 1.89011 Learning rate: 0.02 Mask loss: 0.21289 RPN box loss: 0.10792 RPN score loss: 0.03157 RPN total loss: 0.13949 Total loss: 2.59427 timestamp: 1655011860.6472452 iteration: 4950 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26185 FastRCNN class loss: 0.203 FastRCNN total loss: 0.46485 L1 loss: 0.0000e+00 L2 loss: 1.88975 Learning rate: 0.02 Mask loss: 0.28446 RPN box loss: 0.11819 RPN score loss: 0.02582 RPN total loss: 0.14401 Total loss: 2.78307 timestamp: 1655011863.9848285 iteration: 4955 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25878 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.34431 L1 loss: 0.0000e+00 L2 loss: 1.8894 Learning rate: 0.02 Mask loss: 0.22334 RPN box loss: 0.02121 RPN score loss: 0.00331 RPN total loss: 0.02452 Total loss: 2.48157 timestamp: 1655011867.3398201 iteration: 4960 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19818 FastRCNN class loss: 0.10154 FastRCNN total loss: 0.29972 L1 loss: 0.0000e+00 L2 loss: 1.88902 Learning rate: 0.02 Mask loss: 0.26356 RPN box loss: 0.05883 RPN score loss: 0.00824 RPN total loss: 0.06706 Total loss: 2.51936 timestamp: 1655011870.6408834 iteration: 4965 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24348 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.32344 L1 loss: 0.0000e+00 L2 loss: 1.88866 Learning rate: 0.02 Mask loss: 0.3113 RPN box loss: 0.02 RPN score loss: 0.00398 RPN total loss: 0.02399 Total loss: 2.54739 timestamp: 1655011873.9516447 iteration: 4970 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.236 FastRCNN class loss: 0.13219 FastRCNN total loss: 0.36819 L1 loss: 0.0000e+00 L2 loss: 1.8883 Learning rate: 0.02 Mask loss: 0.20741 RPN box loss: 0.02609 RPN score loss: 0.01431 RPN total loss: 0.0404 Total loss: 2.5043 timestamp: 1655011877.331446 iteration: 4975 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28854 FastRCNN class loss: 0.11433 FastRCNN total loss: 0.40287 L1 loss: 0.0000e+00 L2 loss: 1.88795 Learning rate: 0.02 Mask loss: 0.29868 RPN box loss: 0.08636 RPN score loss: 0.01703 RPN total loss: 0.10339 Total loss: 2.69289 timestamp: 1655011880.6518748 iteration: 4980 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28276 FastRCNN class loss: 0.14058 FastRCNN total loss: 0.42334 L1 loss: 0.0000e+00 L2 loss: 1.8876 Learning rate: 0.02 Mask loss: 0.25305 RPN box loss: 0.07108 RPN score loss: 0.02632 RPN total loss: 0.09739 Total loss: 2.66139 timestamp: 1655011883.995567 iteration: 4985 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15275 FastRCNN class loss: 0.09854 FastRCNN total loss: 0.25129 L1 loss: 0.0000e+00 L2 loss: 1.88722 Learning rate: 0.02 Mask loss: 0.18853 RPN box loss: 0.06846 RPN score loss: 0.02254 RPN total loss: 0.091 Total loss: 2.41804 timestamp: 1655011887.3856702 iteration: 4990 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27118 FastRCNN class loss: 0.18985 FastRCNN total loss: 0.46102 L1 loss: 0.0000e+00 L2 loss: 1.88686 Learning rate: 0.02 Mask loss: 0.25447 RPN box loss: 0.06751 RPN score loss: 0.0112 RPN total loss: 0.07871 Total loss: 2.68106 timestamp: 1655011890.7157257 iteration: 4995 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29197 FastRCNN class loss: 0.16118 FastRCNN total loss: 0.45314 L1 loss: 0.0000e+00 L2 loss: 1.88652 Learning rate: 0.02 Mask loss: 0.33681 RPN box loss: 0.02668 RPN score loss: 0.01076 RPN total loss: 0.03744 Total loss: 2.71391 timestamp: 1655011894.011906 iteration: 5000 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.0839 FastRCNN total loss: 0.21163 L1 loss: 0.0000e+00 L2 loss: 1.88617 Learning rate: 0.02 Mask loss: 0.21851 RPN box loss: 0.04126 RPN score loss: 0.01527 RPN total loss: 0.05653 Total loss: 2.37284 timestamp: 1655011897.286502 iteration: 5005 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23407 FastRCNN class loss: 0.17055 FastRCNN total loss: 0.40461 L1 loss: 0.0000e+00 L2 loss: 1.88584 Learning rate: 0.02 Mask loss: 0.24218 RPN box loss: 0.06611 RPN score loss: 0.07274 RPN total loss: 0.13884 Total loss: 2.67147 timestamp: 1655011900.607909 iteration: 5010 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22515 FastRCNN class loss: 0.11294 FastRCNN total loss: 0.33808 L1 loss: 0.0000e+00 L2 loss: 1.88547 Learning rate: 0.02 Mask loss: 0.30772 RPN box loss: 0.05823 RPN score loss: 0.01409 RPN total loss: 0.07231 Total loss: 2.60359 timestamp: 1655011903.9698572 iteration: 5015 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16511 FastRCNN class loss: 0.11014 FastRCNN total loss: 0.27525 L1 loss: 0.0000e+00 L2 loss: 1.88511 Learning rate: 0.02 Mask loss: 0.30354 RPN box loss: 0.10973 RPN score loss: 0.02085 RPN total loss: 0.13058 Total loss: 2.59448 timestamp: 1655011907.3544333 iteration: 5020 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16438 FastRCNN class loss: 0.07829 FastRCNN total loss: 0.24267 L1 loss: 0.0000e+00 L2 loss: 1.88477 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.00641 RPN score loss: 0.00686 RPN total loss: 0.01327 Total loss: 2.28784 timestamp: 1655011910.7615275 iteration: 5025 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2172 FastRCNN class loss: 0.11888 FastRCNN total loss: 0.33607 L1 loss: 0.0000e+00 L2 loss: 1.8844 Learning rate: 0.02 Mask loss: 0.2712 RPN box loss: 0.03994 RPN score loss: 0.02945 RPN total loss: 0.06939 Total loss: 2.56106 timestamp: 1655011914.1380563 iteration: 5030 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18638 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.24174 L1 loss: 0.0000e+00 L2 loss: 1.88403 Learning rate: 0.02 Mask loss: 0.22315 RPN box loss: 0.01721 RPN score loss: 0.01046 RPN total loss: 0.02766 Total loss: 2.37659 timestamp: 1655011917.5219648 iteration: 5035 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20073 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.26907 L1 loss: 0.0000e+00 L2 loss: 1.88366 Learning rate: 0.02 Mask loss: 0.28275 RPN box loss: 0.03729 RPN score loss: 0.00972 RPN total loss: 0.04701 Total loss: 2.48249 timestamp: 1655011920.890394 iteration: 5040 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25945 FastRCNN class loss: 0.14475 FastRCNN total loss: 0.40419 L1 loss: 0.0000e+00 L2 loss: 1.88332 Learning rate: 0.02 Mask loss: 0.27026 RPN box loss: 0.07583 RPN score loss: 0.04595 RPN total loss: 0.12178 Total loss: 2.67955 timestamp: 1655011924.1870992 iteration: 5045 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18052 FastRCNN class loss: 0.10146 FastRCNN total loss: 0.28198 L1 loss: 0.0000e+00 L2 loss: 1.88297 Learning rate: 0.02 Mask loss: 0.17244 RPN box loss: 0.0334 RPN score loss: 0.00847 RPN total loss: 0.04186 Total loss: 2.37925 timestamp: 1655011927.588703 iteration: 5050 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13543 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.21346 L1 loss: 0.0000e+00 L2 loss: 1.88262 Learning rate: 0.02 Mask loss: 0.18445 RPN box loss: 0.01556 RPN score loss: 0.0091 RPN total loss: 0.02465 Total loss: 2.30518 timestamp: 1655011930.9810703 iteration: 5055 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21417 FastRCNN class loss: 0.1116 FastRCNN total loss: 0.32577 L1 loss: 0.0000e+00 L2 loss: 1.88227 Learning rate: 0.02 Mask loss: 0.23138 RPN box loss: 0.02861 RPN score loss: 0.00544 RPN total loss: 0.03405 Total loss: 2.47347 timestamp: 1655011934.3900332 iteration: 5060 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21493 FastRCNN class loss: 0.12697 FastRCNN total loss: 0.34191 L1 loss: 0.0000e+00 L2 loss: 1.8819 Learning rate: 0.02 Mask loss: 0.25038 RPN box loss: 0.10172 RPN score loss: 0.01283 RPN total loss: 0.11455 Total loss: 2.58874 timestamp: 1655011937.8044915 iteration: 5065 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22488 FastRCNN class loss: 0.11099 FastRCNN total loss: 0.33586 L1 loss: 0.0000e+00 L2 loss: 1.88155 Learning rate: 0.02 Mask loss: 0.23621 RPN box loss: 0.03023 RPN score loss: 0.0322 RPN total loss: 0.06243 Total loss: 2.51606 timestamp: 1655011941.115521 iteration: 5070 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24548 FastRCNN class loss: 0.13106 FastRCNN total loss: 0.37654 L1 loss: 0.0000e+00 L2 loss: 1.88119 Learning rate: 0.02 Mask loss: 0.24486 RPN box loss: 0.06884 RPN score loss: 0.01225 RPN total loss: 0.08109 Total loss: 2.58368 timestamp: 1655011944.4386137 iteration: 5075 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25537 FastRCNN class loss: 0.12836 FastRCNN total loss: 0.38373 L1 loss: 0.0000e+00 L2 loss: 1.88085 Learning rate: 0.02 Mask loss: 0.43903 RPN box loss: 0.02791 RPN score loss: 0.00733 RPN total loss: 0.03524 Total loss: 2.73884 timestamp: 1655011947.8010032 iteration: 5080 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20596 FastRCNN class loss: 0.10593 FastRCNN total loss: 0.31189 L1 loss: 0.0000e+00 L2 loss: 1.88049 Learning rate: 0.02 Mask loss: 0.15468 RPN box loss: 0.04173 RPN score loss: 0.00911 RPN total loss: 0.05084 Total loss: 2.3979 timestamp: 1655011951.1224453 iteration: 5085 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19266 FastRCNN class loss: 0.10504 FastRCNN total loss: 0.29771 L1 loss: 0.0000e+00 L2 loss: 1.88013 Learning rate: 0.02 Mask loss: 0.25314 RPN box loss: 0.04801 RPN score loss: 0.02082 RPN total loss: 0.06883 Total loss: 2.49981 timestamp: 1655011954.44157 iteration: 5090 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16796 FastRCNN class loss: 0.07795 FastRCNN total loss: 0.24591 L1 loss: 0.0000e+00 L2 loss: 1.87978 Learning rate: 0.02 Mask loss: 0.26627 RPN box loss: 0.02239 RPN score loss: 0.00697 RPN total loss: 0.02936 Total loss: 2.42132 timestamp: 1655011957.7944438 iteration: 5095 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13677 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.23283 L1 loss: 0.0000e+00 L2 loss: 1.87943 Learning rate: 0.02 Mask loss: 0.18504 RPN box loss: 0.10324 RPN score loss: 0.02074 RPN total loss: 0.12398 Total loss: 2.42128 timestamp: 1655011961.1246498 iteration: 5100 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25048 FastRCNN class loss: 0.11863 FastRCNN total loss: 0.36911 L1 loss: 0.0000e+00 L2 loss: 1.87907 Learning rate: 0.02 Mask loss: 0.19432 RPN box loss: 0.03939 RPN score loss: 0.01438 RPN total loss: 0.05377 Total loss: 2.49626 timestamp: 1655011964.4557407 iteration: 5105 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25005 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.31519 L1 loss: 0.0000e+00 L2 loss: 1.87872 Learning rate: 0.02 Mask loss: 0.2058 RPN box loss: 0.01761 RPN score loss: 0.00566 RPN total loss: 0.02328 Total loss: 2.42299 timestamp: 1655011967.7835274 iteration: 5110 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18007 FastRCNN class loss: 0.07845 FastRCNN total loss: 0.25852 L1 loss: 0.0000e+00 L2 loss: 1.87835 Learning rate: 0.02 Mask loss: 0.26483 RPN box loss: 0.04965 RPN score loss: 0.04097 RPN total loss: 0.09062 Total loss: 2.49232 timestamp: 1655011971.09518 iteration: 5115 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21329 FastRCNN class loss: 0.10711 FastRCNN total loss: 0.3204 L1 loss: 0.0000e+00 L2 loss: 1.87801 Learning rate: 0.02 Mask loss: 0.23889 RPN box loss: 0.06263 RPN score loss: 0.00895 RPN total loss: 0.07158 Total loss: 2.50888 timestamp: 1655011974.3640547 iteration: 5120 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24076 FastRCNN class loss: 0.09437 FastRCNN total loss: 0.33513 L1 loss: 0.0000e+00 L2 loss: 1.87766 Learning rate: 0.02 Mask loss: 0.24441 RPN box loss: 0.05278 RPN score loss: 0.01207 RPN total loss: 0.06485 Total loss: 2.52204 timestamp: 1655011977.7063713 iteration: 5125 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15048 FastRCNN class loss: 0.09615 FastRCNN total loss: 0.24663 L1 loss: 0.0000e+00 L2 loss: 1.87731 Learning rate: 0.02 Mask loss: 0.22498 RPN box loss: 0.0126 RPN score loss: 0.00724 RPN total loss: 0.01984 Total loss: 2.36876 timestamp: 1655011980.9888089 iteration: 5130 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23487 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.33236 L1 loss: 0.0000e+00 L2 loss: 1.87692 Learning rate: 0.02 Mask loss: 0.18007 RPN box loss: 0.06421 RPN score loss: 0.02159 RPN total loss: 0.08579 Total loss: 2.47514 timestamp: 1655011984.4149778 iteration: 5135 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19017 FastRCNN class loss: 0.15045 FastRCNN total loss: 0.34062 L1 loss: 0.0000e+00 L2 loss: 1.87656 Learning rate: 0.02 Mask loss: 0.25558 RPN box loss: 0.04885 RPN score loss: 0.01041 RPN total loss: 0.05926 Total loss: 2.53202 timestamp: 1655011987.778464 iteration: 5140 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34619 FastRCNN class loss: 0.11523 FastRCNN total loss: 0.46141 L1 loss: 0.0000e+00 L2 loss: 1.87622 Learning rate: 0.02 Mask loss: 0.21244 RPN box loss: 0.01198 RPN score loss: 0.00774 RPN total loss: 0.01972 Total loss: 2.56979 timestamp: 1655011991.0517561 iteration: 5145 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17413 FastRCNN class loss: 0.12153 FastRCNN total loss: 0.29566 L1 loss: 0.0000e+00 L2 loss: 1.87587 Learning rate: 0.02 Mask loss: 0.2224 RPN box loss: 0.04275 RPN score loss: 0.01157 RPN total loss: 0.05433 Total loss: 2.44826 timestamp: 1655011994.3830261 iteration: 5150 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17561 FastRCNN class loss: 0.15357 FastRCNN total loss: 0.32918 L1 loss: 0.0000e+00 L2 loss: 1.8755 Learning rate: 0.02 Mask loss: 0.26816 RPN box loss: 0.02945 RPN score loss: 0.01038 RPN total loss: 0.03984 Total loss: 2.51267 timestamp: 1655011997.7428017 iteration: 5155 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18079 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.2688 L1 loss: 0.0000e+00 L2 loss: 1.87515 Learning rate: 0.02 Mask loss: 0.15079 RPN box loss: 0.02974 RPN score loss: 0.01421 RPN total loss: 0.04395 Total loss: 2.33869 timestamp: 1655012001.0700157 iteration: 5160 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20742 FastRCNN class loss: 0.13901 FastRCNN total loss: 0.34643 L1 loss: 0.0000e+00 L2 loss: 1.87479 Learning rate: 0.02 Mask loss: 0.19026 RPN box loss: 0.0531 RPN score loss: 0.00965 RPN total loss: 0.06275 Total loss: 2.47422 timestamp: 1655012004.3233175 iteration: 5165 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17488 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.25314 L1 loss: 0.0000e+00 L2 loss: 1.87443 Learning rate: 0.02 Mask loss: 0.17717 RPN box loss: 0.02994 RPN score loss: 0.00764 RPN total loss: 0.03758 Total loss: 2.34233 timestamp: 1655012007.6318328 iteration: 5170 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32149 FastRCNN class loss: 0.19283 FastRCNN total loss: 0.51432 L1 loss: 0.0000e+00 L2 loss: 1.87407 Learning rate: 0.02 Mask loss: 0.34124 RPN box loss: 0.02903 RPN score loss: 0.02312 RPN total loss: 0.05216 Total loss: 2.78179 timestamp: 1655012010.9533806 iteration: 5175 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25316 FastRCNN class loss: 0.11063 FastRCNN total loss: 0.36379 L1 loss: 0.0000e+00 L2 loss: 1.87371 Learning rate: 0.02 Mask loss: 0.19759 RPN box loss: 0.06825 RPN score loss: 0.01028 RPN total loss: 0.07853 Total loss: 2.51363 timestamp: 1655012014.24235 iteration: 5180 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27834 FastRCNN class loss: 0.12223 FastRCNN total loss: 0.40056 L1 loss: 0.0000e+00 L2 loss: 1.87336 Learning rate: 0.02 Mask loss: 0.26457 RPN box loss: 0.06142 RPN score loss: 0.01358 RPN total loss: 0.07499 Total loss: 2.61348 timestamp: 1655012017.432665 iteration: 5185 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16199 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.22895 L1 loss: 0.0000e+00 L2 loss: 1.873 Learning rate: 0.02 Mask loss: 0.16697 RPN box loss: 0.05677 RPN score loss: 0.01096 RPN total loss: 0.06772 Total loss: 2.33664 timestamp: 1655012020.6803455 iteration: 5190 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27467 FastRCNN class loss: 0.13587 FastRCNN total loss: 0.41054 L1 loss: 0.0000e+00 L2 loss: 1.87264 Learning rate: 0.02 Mask loss: 0.32782 RPN box loss: 0.01352 RPN score loss: 0.00876 RPN total loss: 0.02228 Total loss: 2.63328 timestamp: 1655012023.9904714 iteration: 5195 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2266 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.32231 L1 loss: 0.0000e+00 L2 loss: 1.87229 Learning rate: 0.02 Mask loss: 0.19634 RPN box loss: 0.11633 RPN score loss: 0.01032 RPN total loss: 0.12666 Total loss: 2.5176 timestamp: 1655012027.2843683 iteration: 5200 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21803 FastRCNN class loss: 0.09175 FastRCNN total loss: 0.30979 L1 loss: 0.0000e+00 L2 loss: 1.87193 Learning rate: 0.02 Mask loss: 0.19308 RPN box loss: 0.02846 RPN score loss: 0.00532 RPN total loss: 0.03378 Total loss: 2.40858 timestamp: 1655012030.6205754 iteration: 5205 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20888 FastRCNN class loss: 0.15484 FastRCNN total loss: 0.36372 L1 loss: 0.0000e+00 L2 loss: 1.87157 Learning rate: 0.02 Mask loss: 0.26224 RPN box loss: 0.02436 RPN score loss: 0.01098 RPN total loss: 0.03534 Total loss: 2.53286 timestamp: 1655012033.9821167 iteration: 5210 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28985 FastRCNN class loss: 0.10408 FastRCNN total loss: 0.39393 L1 loss: 0.0000e+00 L2 loss: 1.8712 Learning rate: 0.02 Mask loss: 0.24695 RPN box loss: 0.09704 RPN score loss: 0.01863 RPN total loss: 0.11566 Total loss: 2.62774 timestamp: 1655012037.2948582 iteration: 5215 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29362 FastRCNN class loss: 0.117 FastRCNN total loss: 0.41062 L1 loss: 0.0000e+00 L2 loss: 1.87085 Learning rate: 0.02 Mask loss: 0.31752 RPN box loss: 0.07757 RPN score loss: 0.03213 RPN total loss: 0.1097 Total loss: 2.70869 timestamp: 1655012040.6244476 iteration: 5220 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24721 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.33018 L1 loss: 0.0000e+00 L2 loss: 1.87052 Learning rate: 0.02 Mask loss: 0.18455 RPN box loss: 0.04269 RPN score loss: 0.02857 RPN total loss: 0.07126 Total loss: 2.45651 timestamp: 1655012043.9474592 iteration: 5225 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31183 FastRCNN class loss: 0.13856 FastRCNN total loss: 0.4504 L1 loss: 0.0000e+00 L2 loss: 1.87017 Learning rate: 0.02 Mask loss: 0.28087 RPN box loss: 0.08166 RPN score loss: 0.02619 RPN total loss: 0.10785 Total loss: 2.70929 timestamp: 1655012047.215036 iteration: 5230 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17836 FastRCNN class loss: 0.10653 FastRCNN total loss: 0.2849 L1 loss: 0.0000e+00 L2 loss: 1.86982 Learning rate: 0.02 Mask loss: 0.33083 RPN box loss: 0.05026 RPN score loss: 0.02781 RPN total loss: 0.07807 Total loss: 2.56363 timestamp: 1655012050.626759 iteration: 5235 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20245 FastRCNN class loss: 0.11427 FastRCNN total loss: 0.31672 L1 loss: 0.0000e+00 L2 loss: 1.86946 Learning rate: 0.02 Mask loss: 0.15645 RPN box loss: 0.04228 RPN score loss: 0.01742 RPN total loss: 0.05969 Total loss: 2.40233 timestamp: 1655012053.873683 iteration: 5240 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.09635 FastRCNN total loss: 0.20257 L1 loss: 0.0000e+00 L2 loss: 1.8691 Learning rate: 0.02 Mask loss: 0.1983 RPN box loss: 0.08316 RPN score loss: 0.01822 RPN total loss: 0.10138 Total loss: 2.37135 timestamp: 1655012057.2765741 iteration: 5245 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17127 FastRCNN class loss: 0.0717 FastRCNN total loss: 0.24297 L1 loss: 0.0000e+00 L2 loss: 1.86875 Learning rate: 0.02 Mask loss: 0.1859 RPN box loss: 0.09886 RPN score loss: 0.01547 RPN total loss: 0.11433 Total loss: 2.41195 timestamp: 1655012060.5006864 iteration: 5250 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21224 FastRCNN class loss: 0.09426 FastRCNN total loss: 0.3065 L1 loss: 0.0000e+00 L2 loss: 1.86839 Learning rate: 0.02 Mask loss: 0.2489 RPN box loss: 0.1034 RPN score loss: 0.0103 RPN total loss: 0.11369 Total loss: 2.53749 timestamp: 1655012063.7994037 iteration: 5255 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.35313 FastRCNN class loss: 0.09284 FastRCNN total loss: 0.44598 L1 loss: 0.0000e+00 L2 loss: 1.86803 Learning rate: 0.02 Mask loss: 0.21198 RPN box loss: 0.01358 RPN score loss: 0.009 RPN total loss: 0.02258 Total loss: 2.54857 timestamp: 1655012067.0590148 iteration: 5260 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20876 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.32219 L1 loss: 0.0000e+00 L2 loss: 1.86771 Learning rate: 0.02 Mask loss: 0.23661 RPN box loss: 0.02813 RPN score loss: 0.01461 RPN total loss: 0.04274 Total loss: 2.46924 timestamp: 1655012070.389447 iteration: 5265 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16241 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.23379 L1 loss: 0.0000e+00 L2 loss: 1.86735 Learning rate: 0.02 Mask loss: 0.1841 RPN box loss: 0.02807 RPN score loss: 0.01029 RPN total loss: 0.03837 Total loss: 2.3236 timestamp: 1655012073.6976779 iteration: 5270 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17542 FastRCNN class loss: 0.11041 FastRCNN total loss: 0.28583 L1 loss: 0.0000e+00 L2 loss: 1.867 Learning rate: 0.02 Mask loss: 0.32074 RPN box loss: 0.04155 RPN score loss: 0.01556 RPN total loss: 0.05711 Total loss: 2.53067 timestamp: 1655012077.0949903 iteration: 5275 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21663 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.29613 L1 loss: 0.0000e+00 L2 loss: 1.86665 Learning rate: 0.02 Mask loss: 0.2355 RPN box loss: 0.06041 RPN score loss: 0.01066 RPN total loss: 0.07107 Total loss: 2.46935 timestamp: 1655012080.4486005 iteration: 5280 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23001 FastRCNN class loss: 0.16046 FastRCNN total loss: 0.39047 L1 loss: 0.0000e+00 L2 loss: 1.86631 Learning rate: 0.02 Mask loss: 0.18045 RPN box loss: 0.04976 RPN score loss: 0.01943 RPN total loss: 0.06919 Total loss: 2.50642 timestamp: 1655012083.7433505 iteration: 5285 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28596 FastRCNN class loss: 0.10032 FastRCNN total loss: 0.38629 L1 loss: 0.0000e+00 L2 loss: 1.86595 Learning rate: 0.02 Mask loss: 0.21153 RPN box loss: 0.02416 RPN score loss: 0.00507 RPN total loss: 0.02923 Total loss: 2.49299 timestamp: 1655012087.0659769 iteration: 5290 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24037 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.30817 L1 loss: 0.0000e+00 L2 loss: 1.86561 Learning rate: 0.02 Mask loss: 0.16276 RPN box loss: 0.01422 RPN score loss: 0.00668 RPN total loss: 0.0209 Total loss: 2.35744 timestamp: 1655012090.3890958 iteration: 5295 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21918 FastRCNN class loss: 0.11518 FastRCNN total loss: 0.33436 L1 loss: 0.0000e+00 L2 loss: 1.86527 Learning rate: 0.02 Mask loss: 0.27242 RPN box loss: 0.09106 RPN score loss: 0.0172 RPN total loss: 0.10826 Total loss: 2.58031 timestamp: 1655012093.7140355 iteration: 5300 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17015 FastRCNN class loss: 0.09027 FastRCNN total loss: 0.26042 L1 loss: 0.0000e+00 L2 loss: 1.86489 Learning rate: 0.02 Mask loss: 0.21527 RPN box loss: 0.06005 RPN score loss: 0.01036 RPN total loss: 0.07041 Total loss: 2.41098 timestamp: 1655012096.9626682 iteration: 5305 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20229 FastRCNN class loss: 0.15278 FastRCNN total loss: 0.35507 L1 loss: 0.0000e+00 L2 loss: 1.86452 Learning rate: 0.02 Mask loss: 0.30624 RPN box loss: 0.04217 RPN score loss: 0.02088 RPN total loss: 0.06305 Total loss: 2.58888 timestamp: 1655012100.3150845 iteration: 5310 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12963 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.20941 L1 loss: 0.0000e+00 L2 loss: 1.86415 Learning rate: 0.02 Mask loss: 0.2212 RPN box loss: 0.01034 RPN score loss: 0.01142 RPN total loss: 0.02175 Total loss: 2.31651 timestamp: 1655012103.6229968 iteration: 5315 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19582 FastRCNN class loss: 0.11344 FastRCNN total loss: 0.30925 L1 loss: 0.0000e+00 L2 loss: 1.86383 Learning rate: 0.02 Mask loss: 0.27924 RPN box loss: 0.03856 RPN score loss: 0.00515 RPN total loss: 0.04371 Total loss: 2.49603 timestamp: 1655012106.9417515 iteration: 5320 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1979 FastRCNN class loss: 0.1194 FastRCNN total loss: 0.3173 L1 loss: 0.0000e+00 L2 loss: 1.86349 Learning rate: 0.02 Mask loss: 0.28608 RPN box loss: 0.05416 RPN score loss: 0.00663 RPN total loss: 0.0608 Total loss: 2.52767 timestamp: 1655012110.2827938 iteration: 5325 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.09175 FastRCNN total loss: 0.25502 L1 loss: 0.0000e+00 L2 loss: 1.86313 Learning rate: 0.02 Mask loss: 0.2378 RPN box loss: 0.08247 RPN score loss: 0.00844 RPN total loss: 0.09091 Total loss: 2.44687 timestamp: 1655012113.5698965 iteration: 5330 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24685 FastRCNN class loss: 0.12864 FastRCNN total loss: 0.37549 L1 loss: 0.0000e+00 L2 loss: 1.8628 Learning rate: 0.02 Mask loss: 0.27038 RPN box loss: 0.019 RPN score loss: 0.02069 RPN total loss: 0.03969 Total loss: 2.54836 timestamp: 1655012116.8331933 iteration: 5335 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20358 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.27996 L1 loss: 0.0000e+00 L2 loss: 1.86245 Learning rate: 0.02 Mask loss: 0.22799 RPN box loss: 0.10304 RPN score loss: 0.01192 RPN total loss: 0.11496 Total loss: 2.48536 timestamp: 1655012120.1478558 iteration: 5340 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12818 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.19499 L1 loss: 0.0000e+00 L2 loss: 1.8621 Learning rate: 0.02 Mask loss: 0.18286 RPN box loss: 0.09209 RPN score loss: 0.01187 RPN total loss: 0.10396 Total loss: 2.3439 timestamp: 1655012123.3957474 iteration: 5345 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15862 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.24837 L1 loss: 0.0000e+00 L2 loss: 1.86173 Learning rate: 0.02 Mask loss: 0.24677 RPN box loss: 0.07846 RPN score loss: 0.01637 RPN total loss: 0.09484 Total loss: 2.4517 timestamp: 1655012126.698955 iteration: 5350 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16413 FastRCNN class loss: 0.08013 FastRCNN total loss: 0.24426 L1 loss: 0.0000e+00 L2 loss: 1.86137 Learning rate: 0.02 Mask loss: 0.18309 RPN box loss: 0.06172 RPN score loss: 0.01158 RPN total loss: 0.0733 Total loss: 2.36203 timestamp: 1655012129.9876468 iteration: 5355 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24177 FastRCNN class loss: 0.102 FastRCNN total loss: 0.34377 L1 loss: 0.0000e+00 L2 loss: 1.86103 Learning rate: 0.02 Mask loss: 0.20473 RPN box loss: 0.04579 RPN score loss: 0.04453 RPN total loss: 0.09032 Total loss: 2.49985 timestamp: 1655012133.3400998 iteration: 5360 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24892 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.33309 L1 loss: 0.0000e+00 L2 loss: 1.86069 Learning rate: 0.02 Mask loss: 0.20069 RPN box loss: 0.03066 RPN score loss: 0.00752 RPN total loss: 0.03818 Total loss: 2.43264 timestamp: 1655012136.6305096 iteration: 5365 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12704 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.18943 L1 loss: 0.0000e+00 L2 loss: 1.86034 Learning rate: 0.02 Mask loss: 0.24666 RPN box loss: 0.0247 RPN score loss: 0.01398 RPN total loss: 0.03869 Total loss: 2.33512 timestamp: 1655012139.8344977 iteration: 5370 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25628 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.36014 L1 loss: 0.0000e+00 L2 loss: 1.85998 Learning rate: 0.02 Mask loss: 0.18714 RPN box loss: 0.04469 RPN score loss: 0.02131 RPN total loss: 0.066 Total loss: 2.47326 timestamp: 1655012143.1092231 iteration: 5375 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25349 FastRCNN class loss: 0.13071 FastRCNN total loss: 0.38421 L1 loss: 0.0000e+00 L2 loss: 1.85962 Learning rate: 0.02 Mask loss: 0.26093 RPN box loss: 0.10925 RPN score loss: 0.01971 RPN total loss: 0.12896 Total loss: 2.63372 timestamp: 1655012146.4368763 iteration: 5380 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30926 FastRCNN class loss: 0.1071 FastRCNN total loss: 0.41635 L1 loss: 0.0000e+00 L2 loss: 1.85928 Learning rate: 0.02 Mask loss: 0.24179 RPN box loss: 0.05598 RPN score loss: 0.01188 RPN total loss: 0.06787 Total loss: 2.58528 timestamp: 1655012149.7812335 iteration: 5385 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1744 FastRCNN class loss: 0.08461 FastRCNN total loss: 0.25901 L1 loss: 0.0000e+00 L2 loss: 1.85893 Learning rate: 0.02 Mask loss: 0.16336 RPN box loss: 0.07696 RPN score loss: 0.00666 RPN total loss: 0.08362 Total loss: 2.36493 timestamp: 1655012153.0892618 iteration: 5390 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20071 FastRCNN class loss: 0.13316 FastRCNN total loss: 0.33387 L1 loss: 0.0000e+00 L2 loss: 1.85858 Learning rate: 0.02 Mask loss: 0.23158 RPN box loss: 0.08752 RPN score loss: 0.02277 RPN total loss: 0.11029 Total loss: 2.53434 timestamp: 1655012156.409748 iteration: 5395 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13438 FastRCNN class loss: 0.06637 FastRCNN total loss: 0.20075 L1 loss: 0.0000e+00 L2 loss: 1.85825 Learning rate: 0.02 Mask loss: 0.16713 RPN box loss: 0.08121 RPN score loss: 0.00789 RPN total loss: 0.0891 Total loss: 2.31522 timestamp: 1655012159.7643945 iteration: 5400 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2098 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.27858 L1 loss: 0.0000e+00 L2 loss: 1.8579 Learning rate: 0.02 Mask loss: 0.35026 RPN box loss: 0.03153 RPN score loss: 0.00639 RPN total loss: 0.03792 Total loss: 2.52466 timestamp: 1655012163.112042 iteration: 5405 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18847 FastRCNN class loss: 0.14069 FastRCNN total loss: 0.32916 L1 loss: 0.0000e+00 L2 loss: 1.85755 Learning rate: 0.02 Mask loss: 0.17862 RPN box loss: 0.03738 RPN score loss: 0.01163 RPN total loss: 0.04901 Total loss: 2.41434 timestamp: 1655012166.4885058 iteration: 5410 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18055 FastRCNN class loss: 0.08238 FastRCNN total loss: 0.26294 L1 loss: 0.0000e+00 L2 loss: 1.8572 Learning rate: 0.02 Mask loss: 0.23463 RPN box loss: 0.02229 RPN score loss: 0.00781 RPN total loss: 0.0301 Total loss: 2.38486 timestamp: 1655012169.7755435 iteration: 5415 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17658 FastRCNN class loss: 0.09933 FastRCNN total loss: 0.27591 L1 loss: 0.0000e+00 L2 loss: 1.85686 Learning rate: 0.02 Mask loss: 0.22355 RPN box loss: 0.11753 RPN score loss: 0.00551 RPN total loss: 0.12304 Total loss: 2.47935 timestamp: 1655012173.123755 iteration: 5420 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16678 FastRCNN class loss: 0.047 FastRCNN total loss: 0.21378 L1 loss: 0.0000e+00 L2 loss: 1.85651 Learning rate: 0.02 Mask loss: 0.19282 RPN box loss: 0.03515 RPN score loss: 0.01178 RPN total loss: 0.04693 Total loss: 2.31003 timestamp: 1655012176.5713081 iteration: 5425 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22042 FastRCNN class loss: 0.08691 FastRCNN total loss: 0.30732 L1 loss: 0.0000e+00 L2 loss: 1.85614 Learning rate: 0.02 Mask loss: 0.24453 RPN box loss: 0.07942 RPN score loss: 0.03679 RPN total loss: 0.11621 Total loss: 2.5242 timestamp: 1655012179.9253302 iteration: 5430 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12509 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.17487 L1 loss: 0.0000e+00 L2 loss: 1.85581 Learning rate: 0.02 Mask loss: 0.22323 RPN box loss: 0.03016 RPN score loss: 0.01062 RPN total loss: 0.04078 Total loss: 2.2947 timestamp: 1655012183.2167048 iteration: 5435 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17583 FastRCNN class loss: 0.0852 FastRCNN total loss: 0.26102 L1 loss: 0.0000e+00 L2 loss: 1.85545 Learning rate: 0.02 Mask loss: 0.20322 RPN box loss: 0.05894 RPN score loss: 0.01035 RPN total loss: 0.06928 Total loss: 2.38898 timestamp: 1655012186.5144408 iteration: 5440 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24289 FastRCNN class loss: 0.11896 FastRCNN total loss: 0.36185 L1 loss: 0.0000e+00 L2 loss: 1.85509 Learning rate: 0.02 Mask loss: 0.24507 RPN box loss: 0.05828 RPN score loss: 0.02665 RPN total loss: 0.08494 Total loss: 2.54695 timestamp: 1655012189.7815967 iteration: 5445 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21209 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.28407 L1 loss: 0.0000e+00 L2 loss: 1.85474 Learning rate: 0.02 Mask loss: 0.19977 RPN box loss: 0.06765 RPN score loss: 0.01478 RPN total loss: 0.08242 Total loss: 2.42101 timestamp: 1655012193.0460458 iteration: 5450 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18702 FastRCNN class loss: 0.06 FastRCNN total loss: 0.24702 L1 loss: 0.0000e+00 L2 loss: 1.8544 Learning rate: 0.02 Mask loss: 0.15513 RPN box loss: 0.02065 RPN score loss: 0.00526 RPN total loss: 0.02591 Total loss: 2.28246 timestamp: 1655012196.4278302 iteration: 5455 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18287 FastRCNN class loss: 0.09313 FastRCNN total loss: 0.276 L1 loss: 0.0000e+00 L2 loss: 1.85405 Learning rate: 0.02 Mask loss: 0.19978 RPN box loss: 0.0812 RPN score loss: 0.01915 RPN total loss: 0.10035 Total loss: 2.43018 timestamp: 1655012199.7779205 iteration: 5460 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26684 FastRCNN class loss: 0.0921 FastRCNN total loss: 0.35893 L1 loss: 0.0000e+00 L2 loss: 1.85371 Learning rate: 0.02 Mask loss: 0.1796 RPN box loss: 0.03538 RPN score loss: 0.01043 RPN total loss: 0.04581 Total loss: 2.43805 timestamp: 1655012203.1422088 iteration: 5465 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20137 FastRCNN class loss: 0.15671 FastRCNN total loss: 0.35808 L1 loss: 0.0000e+00 L2 loss: 1.85336 Learning rate: 0.02 Mask loss: 0.2816 RPN box loss: 0.05591 RPN score loss: 0.00921 RPN total loss: 0.06512 Total loss: 2.55816 timestamp: 1655012206.381843 iteration: 5470 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27979 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.38163 L1 loss: 0.0000e+00 L2 loss: 1.85299 Learning rate: 0.02 Mask loss: 0.32658 RPN box loss: 0.07631 RPN score loss: 0.01252 RPN total loss: 0.08883 Total loss: 2.65003 timestamp: 1655012209.6117816 iteration: 5475 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1741 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.25057 L1 loss: 0.0000e+00 L2 loss: 1.85262 Learning rate: 0.02 Mask loss: 0.20757 RPN box loss: 0.04411 RPN score loss: 0.01041 RPN total loss: 0.05452 Total loss: 2.36527 timestamp: 1655012212.9709888 iteration: 5480 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.05363 FastRCNN total loss: 0.20489 L1 loss: 0.0000e+00 L2 loss: 1.85227 Learning rate: 0.02 Mask loss: 0.16094 RPN box loss: 0.04909 RPN score loss: 0.00698 RPN total loss: 0.05606 Total loss: 2.27417 timestamp: 1655012216.2780674 iteration: 5485 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1963 FastRCNN class loss: 0.11917 FastRCNN total loss: 0.31548 L1 loss: 0.0000e+00 L2 loss: 1.85194 Learning rate: 0.02 Mask loss: 0.36401 RPN box loss: 0.01783 RPN score loss: 0.00969 RPN total loss: 0.02751 Total loss: 2.55893 timestamp: 1655012219.5646536 iteration: 5490 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.34525 FastRCNN class loss: 0.17884 FastRCNN total loss: 0.52409 L1 loss: 0.0000e+00 L2 loss: 1.8516 Learning rate: 0.02 Mask loss: 0.28537 RPN box loss: 0.05561 RPN score loss: 0.01481 RPN total loss: 0.07042 Total loss: 2.73148 timestamp: 1655012222.848037 iteration: 5495 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23802 FastRCNN class loss: 0.11612 FastRCNN total loss: 0.35414 L1 loss: 0.0000e+00 L2 loss: 1.85124 Learning rate: 0.02 Mask loss: 0.20507 RPN box loss: 0.09165 RPN score loss: 0.0204 RPN total loss: 0.11205 Total loss: 2.52251 timestamp: 1655012226.2043917 iteration: 5500 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16174 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.21373 L1 loss: 0.0000e+00 L2 loss: 1.8509 Learning rate: 0.02 Mask loss: 0.15873 RPN box loss: 0.02688 RPN score loss: 0.00734 RPN total loss: 0.03422 Total loss: 2.25758 timestamp: 1655012229.4921777 iteration: 5505 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12416 FastRCNN class loss: 0.06 FastRCNN total loss: 0.18416 L1 loss: 0.0000e+00 L2 loss: 1.85055 Learning rate: 0.02 Mask loss: 0.18863 RPN box loss: 0.02535 RPN score loss: 0.00501 RPN total loss: 0.03036 Total loss: 2.25369 timestamp: 1655012232.7870717 iteration: 5510 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24248 FastRCNN class loss: 0.14409 FastRCNN total loss: 0.38656 L1 loss: 0.0000e+00 L2 loss: 1.85018 Learning rate: 0.02 Mask loss: 0.26502 RPN box loss: 0.03474 RPN score loss: 0.01177 RPN total loss: 0.04651 Total loss: 2.54828 timestamp: 1655012236.0658803 iteration: 5515 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26176 FastRCNN class loss: 0.1373 FastRCNN total loss: 0.39906 L1 loss: 0.0000e+00 L2 loss: 1.84984 Learning rate: 0.02 Mask loss: 0.33129 RPN box loss: 0.06249 RPN score loss: 0.02043 RPN total loss: 0.08292 Total loss: 2.66311 timestamp: 1655012239.3393376 iteration: 5520 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24245 FastRCNN class loss: 0.12799 FastRCNN total loss: 0.37044 L1 loss: 0.0000e+00 L2 loss: 1.84948 Learning rate: 0.02 Mask loss: 0.25327 RPN box loss: 0.07716 RPN score loss: 0.0181 RPN total loss: 0.09526 Total loss: 2.56846 timestamp: 1655012242.6171722 iteration: 5525 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25443 FastRCNN class loss: 0.11066 FastRCNN total loss: 0.36509 L1 loss: 0.0000e+00 L2 loss: 1.84913 Learning rate: 0.02 Mask loss: 0.2064 RPN box loss: 0.02248 RPN score loss: 0.00877 RPN total loss: 0.03125 Total loss: 2.45187 timestamp: 1655012245.948154 iteration: 5530 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2547 FastRCNN class loss: 0.10555 FastRCNN total loss: 0.36025 L1 loss: 0.0000e+00 L2 loss: 1.84878 Learning rate: 0.02 Mask loss: 0.28834 RPN box loss: 0.04086 RPN score loss: 0.00814 RPN total loss: 0.049 Total loss: 2.54637 timestamp: 1655012249.3404112 iteration: 5535 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14313 FastRCNN class loss: 0.11674 FastRCNN total loss: 0.25987 L1 loss: 0.0000e+00 L2 loss: 1.84843 Learning rate: 0.02 Mask loss: 0.23195 RPN box loss: 0.08289 RPN score loss: 0.03165 RPN total loss: 0.11455 Total loss: 2.4548 timestamp: 1655012252.6627321 iteration: 5540 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26477 FastRCNN class loss: 0.12459 FastRCNN total loss: 0.38936 L1 loss: 0.0000e+00 L2 loss: 1.84811 Learning rate: 0.02 Mask loss: 0.24798 RPN box loss: 0.10496 RPN score loss: 0.0176 RPN total loss: 0.12256 Total loss: 2.608 timestamp: 1655012255.922966 iteration: 5545 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.40208 FastRCNN class loss: 0.18292 FastRCNN total loss: 0.585 L1 loss: 0.0000e+00 L2 loss: 1.84774 Learning rate: 0.02 Mask loss: 0.34637 RPN box loss: 0.05625 RPN score loss: 0.01301 RPN total loss: 0.06926 Total loss: 2.84838 timestamp: 1655012259.2378309 iteration: 5550 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16007 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.235 L1 loss: 0.0000e+00 L2 loss: 1.8474 Learning rate: 0.02 Mask loss: 0.15086 RPN box loss: 0.08552 RPN score loss: 0.00678 RPN total loss: 0.09231 Total loss: 2.32556 timestamp: 1655012262.56336 iteration: 5555 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28123 FastRCNN class loss: 0.16257 FastRCNN total loss: 0.4438 L1 loss: 0.0000e+00 L2 loss: 1.84707 Learning rate: 0.02 Mask loss: 0.3237 RPN box loss: 0.10705 RPN score loss: 0.02718 RPN total loss: 0.13423 Total loss: 2.74881 timestamp: 1655012265.8411143 iteration: 5560 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1227 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 1.84671 Learning rate: 0.02 Mask loss: 0.1635 RPN box loss: 0.04444 RPN score loss: 0.01861 RPN total loss: 0.06304 Total loss: 2.2507 timestamp: 1655012269.1099348 iteration: 5565 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2668 FastRCNN class loss: 0.11446 FastRCNN total loss: 0.38126 L1 loss: 0.0000e+00 L2 loss: 1.84634 Learning rate: 0.02 Mask loss: 0.18896 RPN box loss: 0.03995 RPN score loss: 0.01671 RPN total loss: 0.05666 Total loss: 2.47322 timestamp: 1655012272.393381 iteration: 5570 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.08568 FastRCNN total loss: 0.18743 L1 loss: 0.0000e+00 L2 loss: 1.846 Learning rate: 0.02 Mask loss: 0.2121 RPN box loss: 0.04757 RPN score loss: 0.01977 RPN total loss: 0.06734 Total loss: 2.31288 timestamp: 1655012275.781722 iteration: 5575 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26654 FastRCNN class loss: 0.16702 FastRCNN total loss: 0.43356 L1 loss: 0.0000e+00 L2 loss: 1.84566 Learning rate: 0.02 Mask loss: 0.15863 RPN box loss: 0.04384 RPN score loss: 0.01398 RPN total loss: 0.05781 Total loss: 2.49566 timestamp: 1655012279.1594813 iteration: 5580 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12833 FastRCNN class loss: 0.10359 FastRCNN total loss: 0.23192 L1 loss: 0.0000e+00 L2 loss: 1.84532 Learning rate: 0.02 Mask loss: 0.16839 RPN box loss: 0.08357 RPN score loss: 0.0173 RPN total loss: 0.10087 Total loss: 2.3465 timestamp: 1655012282.4661763 iteration: 5585 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18667 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.26933 L1 loss: 0.0000e+00 L2 loss: 1.84498 Learning rate: 0.02 Mask loss: 0.21004 RPN box loss: 0.01954 RPN score loss: 0.01323 RPN total loss: 0.03277 Total loss: 2.35712 timestamp: 1655012285.7836297 iteration: 5590 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20361 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.30055 L1 loss: 0.0000e+00 L2 loss: 1.84465 Learning rate: 0.02 Mask loss: 0.24477 RPN box loss: 0.11382 RPN score loss: 0.01249 RPN total loss: 0.12631 Total loss: 2.51627 timestamp: 1655012289.0976462 iteration: 5595 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17779 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.27118 L1 loss: 0.0000e+00 L2 loss: 1.84428 Learning rate: 0.02 Mask loss: 0.20853 RPN box loss: 0.07722 RPN score loss: 0.01729 RPN total loss: 0.09451 Total loss: 2.41849 timestamp: 1655012292.3944302 iteration: 5600 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20775 FastRCNN class loss: 0.14029 FastRCNN total loss: 0.34803 L1 loss: 0.0000e+00 L2 loss: 1.84392 Learning rate: 0.02 Mask loss: 0.23423 RPN box loss: 0.11028 RPN score loss: 0.01312 RPN total loss: 0.1234 Total loss: 2.54958 timestamp: 1655012295.619591 iteration: 5605 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13266 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.19772 L1 loss: 0.0000e+00 L2 loss: 1.84359 Learning rate: 0.02 Mask loss: 0.22062 RPN box loss: 0.00566 RPN score loss: 0.00786 RPN total loss: 0.01352 Total loss: 2.27545 timestamp: 1655012298.9194577 iteration: 5610 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24885 FastRCNN class loss: 0.14646 FastRCNN total loss: 0.39531 L1 loss: 0.0000e+00 L2 loss: 1.84325 Learning rate: 0.02 Mask loss: 0.25496 RPN box loss: 0.04786 RPN score loss: 0.00809 RPN total loss: 0.05595 Total loss: 2.54948 timestamp: 1655012302.1446357 iteration: 5615 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27829 FastRCNN class loss: 0.11849 FastRCNN total loss: 0.39678 L1 loss: 0.0000e+00 L2 loss: 1.84291 Learning rate: 0.02 Mask loss: 0.30834 RPN box loss: 0.03045 RPN score loss: 0.01091 RPN total loss: 0.04136 Total loss: 2.5894 timestamp: 1655012305.473298 iteration: 5620 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20986 FastRCNN class loss: 0.10277 FastRCNN total loss: 0.31264 L1 loss: 0.0000e+00 L2 loss: 1.84258 Learning rate: 0.02 Mask loss: 0.23923 RPN box loss: 0.05929 RPN score loss: 0.01246 RPN total loss: 0.07175 Total loss: 2.46619 timestamp: 1655012308.7495785 iteration: 5625 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18317 FastRCNN class loss: 0.10874 FastRCNN total loss: 0.29191 L1 loss: 0.0000e+00 L2 loss: 1.84223 Learning rate: 0.02 Mask loss: 0.18142 RPN box loss: 0.0684 RPN score loss: 0.00525 RPN total loss: 0.07365 Total loss: 2.38921 timestamp: 1655012311.8864214 iteration: 5630 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21977 FastRCNN class loss: 0.11009 FastRCNN total loss: 0.32986 L1 loss: 0.0000e+00 L2 loss: 1.84189 Learning rate: 0.02 Mask loss: 0.24769 RPN box loss: 0.03903 RPN score loss: 0.01 RPN total loss: 0.04903 Total loss: 2.46847 timestamp: 1655012315.1654105 iteration: 5635 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33141 FastRCNN class loss: 0.10274 FastRCNN total loss: 0.43414 L1 loss: 0.0000e+00 L2 loss: 1.84154 Learning rate: 0.02 Mask loss: 0.24748 RPN box loss: 0.02025 RPN score loss: 0.00392 RPN total loss: 0.02417 Total loss: 2.54733 timestamp: 1655012318.4761298 iteration: 5640 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16346 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.2723 L1 loss: 0.0000e+00 L2 loss: 1.84118 Learning rate: 0.02 Mask loss: 0.23339 RPN box loss: 0.01376 RPN score loss: 0.0025 RPN total loss: 0.01626 Total loss: 2.36313 timestamp: 1655012321.7776315 iteration: 5645 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18511 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.23864 L1 loss: 0.0000e+00 L2 loss: 1.84084 Learning rate: 0.02 Mask loss: 0.21711 RPN box loss: 0.02519 RPN score loss: 0.0036 RPN total loss: 0.02879 Total loss: 2.32538 timestamp: 1655012325.0603657 iteration: 5650 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13012 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.20293 L1 loss: 0.0000e+00 L2 loss: 1.84048 Learning rate: 0.02 Mask loss: 0.20676 RPN box loss: 0.08246 RPN score loss: 0.01031 RPN total loss: 0.09277 Total loss: 2.34294 timestamp: 1655012328.370192 iteration: 5655 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2954 FastRCNN class loss: 0.14319 FastRCNN total loss: 0.43859 L1 loss: 0.0000e+00 L2 loss: 1.84012 Learning rate: 0.02 Mask loss: 0.28705 RPN box loss: 0.04124 RPN score loss: 0.04475 RPN total loss: 0.08598 Total loss: 2.65175 timestamp: 1655012331.7371335 iteration: 5660 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19556 FastRCNN class loss: 0.13833 FastRCNN total loss: 0.33389 L1 loss: 0.0000e+00 L2 loss: 1.83978 Learning rate: 0.02 Mask loss: 0.22942 RPN box loss: 0.08725 RPN score loss: 0.01385 RPN total loss: 0.10109 Total loss: 2.50419 timestamp: 1655012335.0321748 iteration: 5665 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24144 FastRCNN class loss: 0.11081 FastRCNN total loss: 0.35225 L1 loss: 0.0000e+00 L2 loss: 1.83943 Learning rate: 0.02 Mask loss: 0.21277 RPN box loss: 0.10033 RPN score loss: 0.02315 RPN total loss: 0.12348 Total loss: 2.52793 timestamp: 1655012338.3276787 iteration: 5670 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19792 FastRCNN class loss: 0.08454 FastRCNN total loss: 0.28246 L1 loss: 0.0000e+00 L2 loss: 1.8391 Learning rate: 0.02 Mask loss: 0.14403 RPN box loss: 0.0342 RPN score loss: 0.00792 RPN total loss: 0.04213 Total loss: 2.30772 timestamp: 1655012341.5837553 iteration: 5675 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13359 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.21433 L1 loss: 0.0000e+00 L2 loss: 1.83876 Learning rate: 0.02 Mask loss: 0.33811 RPN box loss: 0.01218 RPN score loss: 0.00423 RPN total loss: 0.01641 Total loss: 2.40762 timestamp: 1655012344.9214094 iteration: 5680 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24865 FastRCNN class loss: 0.15784 FastRCNN total loss: 0.40649 L1 loss: 0.0000e+00 L2 loss: 1.83841 Learning rate: 0.02 Mask loss: 0.33058 RPN box loss: 0.04399 RPN score loss: 0.02949 RPN total loss: 0.07347 Total loss: 2.64896 timestamp: 1655012348.1938825 iteration: 5685 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28022 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.36842 L1 loss: 0.0000e+00 L2 loss: 1.83805 Learning rate: 0.02 Mask loss: 0.22631 RPN box loss: 0.05186 RPN score loss: 0.01459 RPN total loss: 0.06645 Total loss: 2.49923 timestamp: 1655012351.5222826 iteration: 5690 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19534 FastRCNN class loss: 0.13934 FastRCNN total loss: 0.33469 L1 loss: 0.0000e+00 L2 loss: 1.8377 Learning rate: 0.02 Mask loss: 0.24337 RPN box loss: 0.08767 RPN score loss: 0.01034 RPN total loss: 0.09801 Total loss: 2.51377 timestamp: 1655012354.7487807 iteration: 5695 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16239 FastRCNN class loss: 0.09274 FastRCNN total loss: 0.25514 L1 loss: 0.0000e+00 L2 loss: 1.83734 Learning rate: 0.02 Mask loss: 0.17769 RPN box loss: 0.06544 RPN score loss: 0.00914 RPN total loss: 0.07458 Total loss: 2.34474 timestamp: 1655012358.0383713 iteration: 5700 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19897 FastRCNN class loss: 0.10529 FastRCNN total loss: 0.30425 L1 loss: 0.0000e+00 L2 loss: 1.837 Learning rate: 0.02 Mask loss: 0.21934 RPN box loss: 0.02409 RPN score loss: 0.01388 RPN total loss: 0.03797 Total loss: 2.39857 timestamp: 1655012361.3366313 iteration: 5705 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1839 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.25509 L1 loss: 0.0000e+00 L2 loss: 1.83667 Learning rate: 0.02 Mask loss: 0.33235 RPN box loss: 0.01395 RPN score loss: 0.00635 RPN total loss: 0.0203 Total loss: 2.44442 timestamp: 1655012364.6246786 iteration: 5710 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19647 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.29271 L1 loss: 0.0000e+00 L2 loss: 1.83632 Learning rate: 0.02 Mask loss: 0.24765 RPN box loss: 0.05555 RPN score loss: 0.01241 RPN total loss: 0.06796 Total loss: 2.44464 timestamp: 1655012368.0287855 iteration: 5715 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22158 FastRCNN class loss: 0.10259 FastRCNN total loss: 0.32417 L1 loss: 0.0000e+00 L2 loss: 1.83597 Learning rate: 0.02 Mask loss: 0.24138 RPN box loss: 0.05448 RPN score loss: 0.01041 RPN total loss: 0.06489 Total loss: 2.46641 timestamp: 1655012371.4366026 iteration: 5720 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21076 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.27147 L1 loss: 0.0000e+00 L2 loss: 1.83564 Learning rate: 0.02 Mask loss: 0.16044 RPN box loss: 0.02127 RPN score loss: 0.00474 RPN total loss: 0.02602 Total loss: 2.29357 timestamp: 1655012374.6915154 iteration: 5725 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21438 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.2854 L1 loss: 0.0000e+00 L2 loss: 1.83529 Learning rate: 0.02 Mask loss: 0.22544 RPN box loss: 0.02658 RPN score loss: 0.00485 RPN total loss: 0.03143 Total loss: 2.37757 timestamp: 1655012377.958698 iteration: 5730 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26381 FastRCNN class loss: 0.14455 FastRCNN total loss: 0.40836 L1 loss: 0.0000e+00 L2 loss: 1.83496 Learning rate: 0.02 Mask loss: 0.22954 RPN box loss: 0.04648 RPN score loss: 0.00856 RPN total loss: 0.05503 Total loss: 2.5279 timestamp: 1655012381.248473 iteration: 5735 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15182 FastRCNN class loss: 0.08033 FastRCNN total loss: 0.23215 L1 loss: 0.0000e+00 L2 loss: 1.83462 Learning rate: 0.02 Mask loss: 0.18115 RPN box loss: 0.03787 RPN score loss: 0.00364 RPN total loss: 0.04151 Total loss: 2.28943 timestamp: 1655012384.5369854 iteration: 5740 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20495 FastRCNN class loss: 0.11707 FastRCNN total loss: 0.32203 L1 loss: 0.0000e+00 L2 loss: 1.83428 Learning rate: 0.02 Mask loss: 0.20582 RPN box loss: 0.06463 RPN score loss: 0.0373 RPN total loss: 0.10194 Total loss: 2.46406 timestamp: 1655012387.8581836 iteration: 5745 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27933 FastRCNN class loss: 0.10248 FastRCNN total loss: 0.3818 L1 loss: 0.0000e+00 L2 loss: 1.83391 Learning rate: 0.02 Mask loss: 0.26308 RPN box loss: 0.04773 RPN score loss: 0.01208 RPN total loss: 0.05982 Total loss: 2.53861 timestamp: 1655012391.1320176 iteration: 5750 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24302 FastRCNN class loss: 0.12528 FastRCNN total loss: 0.3683 L1 loss: 0.0000e+00 L2 loss: 1.83356 Learning rate: 0.02 Mask loss: 0.21165 RPN box loss: 0.09286 RPN score loss: 0.01513 RPN total loss: 0.10799 Total loss: 2.5215 timestamp: 1655012394.406493 iteration: 5755 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18046 FastRCNN class loss: 0.13563 FastRCNN total loss: 0.31609 L1 loss: 0.0000e+00 L2 loss: 1.83322 Learning rate: 0.02 Mask loss: 0.21761 RPN box loss: 0.02823 RPN score loss: 0.00844 RPN total loss: 0.03667 Total loss: 2.40359 timestamp: 1655012397.735729 iteration: 5760 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18869 FastRCNN class loss: 0.07539 FastRCNN total loss: 0.26408 L1 loss: 0.0000e+00 L2 loss: 1.8329 Learning rate: 0.02 Mask loss: 0.21374 RPN box loss: 0.05684 RPN score loss: 0.01355 RPN total loss: 0.07039 Total loss: 2.38111 timestamp: 1655012401.0272253 iteration: 5765 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24459 FastRCNN class loss: 0.11528 FastRCNN total loss: 0.35987 L1 loss: 0.0000e+00 L2 loss: 1.83256 Learning rate: 0.02 Mask loss: 0.28478 RPN box loss: 0.04411 RPN score loss: 0.01278 RPN total loss: 0.05689 Total loss: 2.5341 timestamp: 1655012404.3567693 iteration: 5770 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27781 FastRCNN class loss: 0.17668 FastRCNN total loss: 0.45449 L1 loss: 0.0000e+00 L2 loss: 1.8322 Learning rate: 0.02 Mask loss: 0.26442 RPN box loss: 0.08632 RPN score loss: 0.01417 RPN total loss: 0.10049 Total loss: 2.6516 timestamp: 1655012407.600906 iteration: 5775 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21226 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.30429 L1 loss: 0.0000e+00 L2 loss: 1.83184 Learning rate: 0.02 Mask loss: 0.29891 RPN box loss: 0.08554 RPN score loss: 0.01371 RPN total loss: 0.09924 Total loss: 2.53429 timestamp: 1655012410.8332503 iteration: 5780 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21213 FastRCNN class loss: 0.11064 FastRCNN total loss: 0.32277 L1 loss: 0.0000e+00 L2 loss: 1.83152 Learning rate: 0.02 Mask loss: 0.20213 RPN box loss: 0.08209 RPN score loss: 0.01345 RPN total loss: 0.09554 Total loss: 2.45196 timestamp: 1655012414.1455593 iteration: 5785 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19839 FastRCNN class loss: 0.09639 FastRCNN total loss: 0.29479 L1 loss: 0.0000e+00 L2 loss: 1.83118 Learning rate: 0.02 Mask loss: 0.24495 RPN box loss: 0.06169 RPN score loss: 0.01616 RPN total loss: 0.07786 Total loss: 2.44877 timestamp: 1655012417.4501824 iteration: 5790 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17523 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.25333 L1 loss: 0.0000e+00 L2 loss: 1.83085 Learning rate: 0.02 Mask loss: 0.18389 RPN box loss: 0.03732 RPN score loss: 0.01051 RPN total loss: 0.04783 Total loss: 2.3159 timestamp: 1655012420.7831318 iteration: 5795 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.19345 L1 loss: 0.0000e+00 L2 loss: 1.83051 Learning rate: 0.02 Mask loss: 0.1991 RPN box loss: 0.05864 RPN score loss: 0.02081 RPN total loss: 0.07945 Total loss: 2.30251 timestamp: 1655012424.0938814 iteration: 5800 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32864 FastRCNN class loss: 0.1723 FastRCNN total loss: 0.50093 L1 loss: 0.0000e+00 L2 loss: 1.83016 Learning rate: 0.02 Mask loss: 0.31051 RPN box loss: 0.04098 RPN score loss: 0.01926 RPN total loss: 0.06024 Total loss: 2.70184 timestamp: 1655012427.4047115 iteration: 5805 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24121 FastRCNN class loss: 0.12545 FastRCNN total loss: 0.36666 L1 loss: 0.0000e+00 L2 loss: 1.82982 Learning rate: 0.02 Mask loss: 0.29101 RPN box loss: 0.06463 RPN score loss: 0.00981 RPN total loss: 0.07444 Total loss: 2.56193 timestamp: 1655012430.7374027 iteration: 5810 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19712 FastRCNN class loss: 0.15432 FastRCNN total loss: 0.35144 L1 loss: 0.0000e+00 L2 loss: 1.82947 Learning rate: 0.02 Mask loss: 0.22118 RPN box loss: 0.10122 RPN score loss: 0.02459 RPN total loss: 0.12582 Total loss: 2.52792 timestamp: 1655012434.0296736 iteration: 5815 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19917 FastRCNN class loss: 0.10379 FastRCNN total loss: 0.30296 L1 loss: 0.0000e+00 L2 loss: 1.82912 Learning rate: 0.02 Mask loss: 0.29118 RPN box loss: 0.03267 RPN score loss: 0.02135 RPN total loss: 0.05402 Total loss: 2.47727 timestamp: 1655012437.3759747 iteration: 5820 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2763 FastRCNN class loss: 0.13053 FastRCNN total loss: 0.40683 L1 loss: 0.0000e+00 L2 loss: 1.82878 Learning rate: 0.02 Mask loss: 0.25348 RPN box loss: 0.01346 RPN score loss: 0.00816 RPN total loss: 0.02162 Total loss: 2.51071 timestamp: 1655012440.6488154 iteration: 5825 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14377 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.23652 L1 loss: 0.0000e+00 L2 loss: 1.82843 Learning rate: 0.02 Mask loss: 0.17163 RPN box loss: 0.0211 RPN score loss: 0.00832 RPN total loss: 0.02942 Total loss: 2.266 timestamp: 1655012443.9334176 iteration: 5830 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15176 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.22344 L1 loss: 0.0000e+00 L2 loss: 1.8281 Learning rate: 0.02 Mask loss: 0.20641 RPN box loss: 0.06333 RPN score loss: 0.01568 RPN total loss: 0.07901 Total loss: 2.33696 timestamp: 1655012447.1801548 iteration: 5835 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23209 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.30958 L1 loss: 0.0000e+00 L2 loss: 1.82776 Learning rate: 0.02 Mask loss: 0.20031 RPN box loss: 0.04339 RPN score loss: 0.00707 RPN total loss: 0.05046 Total loss: 2.38812 timestamp: 1655012450.6271365 iteration: 5840 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17198 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.2509 L1 loss: 0.0000e+00 L2 loss: 1.82741 Learning rate: 0.02 Mask loss: 0.32742 RPN box loss: 0.06667 RPN score loss: 0.01792 RPN total loss: 0.08459 Total loss: 2.49031 timestamp: 1655012453.9083548 iteration: 5845 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21722 FastRCNN class loss: 0.08882 FastRCNN total loss: 0.30604 L1 loss: 0.0000e+00 L2 loss: 1.82706 Learning rate: 0.02 Mask loss: 0.19701 RPN box loss: 0.06413 RPN score loss: 0.00822 RPN total loss: 0.07235 Total loss: 2.40245 timestamp: 1655012457.2135963 iteration: 5850 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26102 FastRCNN class loss: 0.21584 FastRCNN total loss: 0.47686 L1 loss: 0.0000e+00 L2 loss: 1.82673 Learning rate: 0.02 Mask loss: 0.25461 RPN box loss: 0.13787 RPN score loss: 0.01141 RPN total loss: 0.14929 Total loss: 2.70749 timestamp: 1655012460.4903834 iteration: 5855 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27935 FastRCNN class loss: 0.13304 FastRCNN total loss: 0.41239 L1 loss: 0.0000e+00 L2 loss: 1.82639 Learning rate: 0.02 Mask loss: 0.36345 RPN box loss: 0.04758 RPN score loss: 0.01768 RPN total loss: 0.06526 Total loss: 2.66749 timestamp: 1655012463.7180219 iteration: 5860 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14607 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.2084 L1 loss: 0.0000e+00 L2 loss: 1.82605 Learning rate: 0.02 Mask loss: 0.3005 RPN box loss: 0.01672 RPN score loss: 0.00447 RPN total loss: 0.02119 Total loss: 2.35614 timestamp: 1655012467.0443175 iteration: 5865 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11867 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.18682 L1 loss: 0.0000e+00 L2 loss: 1.8257 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.02782 RPN score loss: 0.00812 RPN total loss: 0.03594 Total loss: 2.2027 timestamp: 1655012470.3797944 iteration: 5870 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16572 FastRCNN class loss: 0.13239 FastRCNN total loss: 0.2981 L1 loss: 0.0000e+00 L2 loss: 1.82538 Learning rate: 0.02 Mask loss: 0.15776 RPN box loss: 0.07623 RPN score loss: 0.00751 RPN total loss: 0.08374 Total loss: 2.36498 timestamp: 1655012473.6587136 iteration: 5875 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10429 FastRCNN class loss: 0.05556 FastRCNN total loss: 0.15985 L1 loss: 0.0000e+00 L2 loss: 1.82503 Learning rate: 0.02 Mask loss: 0.24397 RPN box loss: 0.06861 RPN score loss: 0.01214 RPN total loss: 0.08076 Total loss: 2.3096 timestamp: 1655012476.928381 iteration: 5880 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21994 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 1.8247 Learning rate: 0.02 Mask loss: 0.19838 RPN box loss: 0.04529 RPN score loss: 0.00934 RPN total loss: 0.05463 Total loss: 2.37331 timestamp: 1655012480.2018821 iteration: 5885 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25167 FastRCNN class loss: 0.14657 FastRCNN total loss: 0.39824 L1 loss: 0.0000e+00 L2 loss: 1.82434 Learning rate: 0.02 Mask loss: 0.30556 RPN box loss: 0.03043 RPN score loss: 0.02927 RPN total loss: 0.0597 Total loss: 2.58784 timestamp: 1655012483.5645127 iteration: 5890 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23928 FastRCNN class loss: 0.13239 FastRCNN total loss: 0.37166 L1 loss: 0.0000e+00 L2 loss: 1.824 Learning rate: 0.02 Mask loss: 0.18486 RPN box loss: 0.08394 RPN score loss: 0.01688 RPN total loss: 0.10083 Total loss: 2.48135 timestamp: 1655012486.8761694 iteration: 5895 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36833 FastRCNN class loss: 0.11227 FastRCNN total loss: 0.48061 L1 loss: 0.0000e+00 L2 loss: 1.82367 Learning rate: 0.02 Mask loss: 0.19396 RPN box loss: 0.02702 RPN score loss: 0.00722 RPN total loss: 0.03424 Total loss: 2.53247 timestamp: 1655012490.1699047 iteration: 5900 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28126 FastRCNN class loss: 0.13498 FastRCNN total loss: 0.41624 L1 loss: 0.0000e+00 L2 loss: 1.82332 Learning rate: 0.02 Mask loss: 0.23742 RPN box loss: 0.02863 RPN score loss: 0.00346 RPN total loss: 0.03209 Total loss: 2.50907 timestamp: 1655012493.411069 iteration: 5905 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1706 FastRCNN class loss: 0.09669 FastRCNN total loss: 0.2673 L1 loss: 0.0000e+00 L2 loss: 1.82299 Learning rate: 0.02 Mask loss: 0.29792 RPN box loss: 0.11656 RPN score loss: 0.01948 RPN total loss: 0.13604 Total loss: 2.52425 timestamp: 1655012496.7132838 iteration: 5910 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2231 FastRCNN class loss: 0.13084 FastRCNN total loss: 0.35394 L1 loss: 0.0000e+00 L2 loss: 1.82264 Learning rate: 0.02 Mask loss: 0.21325 RPN box loss: 0.05048 RPN score loss: 0.01335 RPN total loss: 0.06383 Total loss: 2.45366 timestamp: 1655012500.0541596 iteration: 5915 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20804 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.29648 L1 loss: 0.0000e+00 L2 loss: 1.82229 Learning rate: 0.02 Mask loss: 0.32764 RPN box loss: 0.0421 RPN score loss: 0.0096 RPN total loss: 0.0517 Total loss: 2.49811 timestamp: 1655012503.357674 iteration: 5920 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1999 FastRCNN class loss: 0.08916 FastRCNN total loss: 0.28905 L1 loss: 0.0000e+00 L2 loss: 1.82197 Learning rate: 0.02 Mask loss: 0.17715 RPN box loss: 0.0907 RPN score loss: 0.02427 RPN total loss: 0.11497 Total loss: 2.40315 timestamp: 1655012506.6772218 iteration: 5925 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21007 FastRCNN class loss: 0.1326 FastRCNN total loss: 0.34267 L1 loss: 0.0000e+00 L2 loss: 1.82163 Learning rate: 0.02 Mask loss: 0.20392 RPN box loss: 0.07138 RPN score loss: 0.01196 RPN total loss: 0.08334 Total loss: 2.45156 timestamp: 1655012510.0196662 iteration: 5930 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16198 FastRCNN class loss: 0.0878 FastRCNN total loss: 0.24978 L1 loss: 0.0000e+00 L2 loss: 1.8213 Learning rate: 0.02 Mask loss: 0.25066 RPN box loss: 0.09208 RPN score loss: 0.01268 RPN total loss: 0.10476 Total loss: 2.4265 timestamp: 1655012513.304075 iteration: 5935 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21078 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.29168 L1 loss: 0.0000e+00 L2 loss: 1.82094 Learning rate: 0.02 Mask loss: 0.23155 RPN box loss: 0.02614 RPN score loss: 0.00669 RPN total loss: 0.03284 Total loss: 2.377 timestamp: 1655012516.6289003 iteration: 5940 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17105 FastRCNN class loss: 0.09932 FastRCNN total loss: 0.27038 L1 loss: 0.0000e+00 L2 loss: 1.82059 Learning rate: 0.02 Mask loss: 0.26518 RPN box loss: 0.06028 RPN score loss: 0.01955 RPN total loss: 0.07983 Total loss: 2.43598 timestamp: 1655012519.9537566 iteration: 5945 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22693 FastRCNN class loss: 0.12875 FastRCNN total loss: 0.35568 L1 loss: 0.0000e+00 L2 loss: 1.82025 Learning rate: 0.02 Mask loss: 0.28028 RPN box loss: 0.0839 RPN score loss: 0.03844 RPN total loss: 0.12234 Total loss: 2.57855 timestamp: 1655012523.2475479 iteration: 5950 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21541 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.28026 L1 loss: 0.0000e+00 L2 loss: 1.8199 Learning rate: 0.02 Mask loss: 0.21377 RPN box loss: 0.03774 RPN score loss: 0.01478 RPN total loss: 0.05253 Total loss: 2.36646 timestamp: 1655012526.56496 iteration: 5955 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21207 FastRCNN class loss: 0.09696 FastRCNN total loss: 0.30903 L1 loss: 0.0000e+00 L2 loss: 1.81957 Learning rate: 0.02 Mask loss: 0.1849 RPN box loss: 0.04715 RPN score loss: 0.01195 RPN total loss: 0.0591 Total loss: 2.37259 timestamp: 1655012529.8357775 iteration: 5960 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29193 FastRCNN class loss: 0.08546 FastRCNN total loss: 0.37739 L1 loss: 0.0000e+00 L2 loss: 1.81922 Learning rate: 0.02 Mask loss: 0.27105 RPN box loss: 0.03623 RPN score loss: 0.0053 RPN total loss: 0.04153 Total loss: 2.50919 timestamp: 1655012533.1281168 iteration: 5965 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28396 FastRCNN class loss: 0.11903 FastRCNN total loss: 0.40299 L1 loss: 0.0000e+00 L2 loss: 1.81889 Learning rate: 0.02 Mask loss: 0.30068 RPN box loss: 0.04784 RPN score loss: 0.02503 RPN total loss: 0.07287 Total loss: 2.59543 timestamp: 1655012536.4320195 iteration: 5970 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1507 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.2171 L1 loss: 0.0000e+00 L2 loss: 1.81856 Learning rate: 0.02 Mask loss: 0.18917 RPN box loss: 0.01261 RPN score loss: 0.01355 RPN total loss: 0.02615 Total loss: 2.25098 timestamp: 1655012539.6925569 iteration: 5975 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21897 FastRCNN class loss: 0.15831 FastRCNN total loss: 0.37727 L1 loss: 0.0000e+00 L2 loss: 1.8182 Learning rate: 0.02 Mask loss: 0.29945 RPN box loss: 0.13253 RPN score loss: 0.01365 RPN total loss: 0.14618 Total loss: 2.6411 timestamp: 1655012542.9617531 iteration: 5980 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14506 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.21939 L1 loss: 0.0000e+00 L2 loss: 1.81786 Learning rate: 0.02 Mask loss: 0.2026 RPN box loss: 0.07344 RPN score loss: 0.00608 RPN total loss: 0.07953 Total loss: 2.31938 timestamp: 1655012546.3069534 iteration: 5985 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20338 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.29493 L1 loss: 0.0000e+00 L2 loss: 1.81752 Learning rate: 0.02 Mask loss: 0.28854 RPN box loss: 0.02389 RPN score loss: 0.0061 RPN total loss: 0.02999 Total loss: 2.43098 timestamp: 1655012549.6858506 iteration: 5990 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28097 FastRCNN class loss: 0.12863 FastRCNN total loss: 0.40959 L1 loss: 0.0000e+00 L2 loss: 1.81719 Learning rate: 0.02 Mask loss: 0.22059 RPN box loss: 0.04743 RPN score loss: 0.00923 RPN total loss: 0.05666 Total loss: 2.50403 timestamp: 1655012552.9658515 iteration: 5995 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08972 FastRCNN class loss: 0.0307 FastRCNN total loss: 0.12043 L1 loss: 0.0000e+00 L2 loss: 1.81685 Learning rate: 0.02 Mask loss: 0.15124 RPN box loss: 0.00186 RPN score loss: 0.00469 RPN total loss: 0.00655 Total loss: 2.09506 timestamp: 1655012556.2905183 iteration: 6000 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14337 FastRCNN class loss: 0.06897 FastRCNN total loss: 0.21234 L1 loss: 0.0000e+00 L2 loss: 1.81653 Learning rate: 0.02 Mask loss: 0.19223 RPN box loss: 0.06442 RPN score loss: 0.00582 RPN total loss: 0.07024 Total loss: 2.29134 timestamp: 1655012559.5903492 iteration: 6005 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18181 FastRCNN class loss: 0.09419 FastRCNN total loss: 0.276 L1 loss: 0.0000e+00 L2 loss: 1.81618 Learning rate: 0.02 Mask loss: 0.17761 RPN box loss: 0.02213 RPN score loss: 0.00668 RPN total loss: 0.02881 Total loss: 2.29861 timestamp: 1655012562.9005277 iteration: 6010 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19485 FastRCNN class loss: 0.19344 FastRCNN total loss: 0.38829 L1 loss: 0.0000e+00 L2 loss: 1.81583 Learning rate: 0.02 Mask loss: 0.26662 RPN box loss: 0.04768 RPN score loss: 0.00755 RPN total loss: 0.05523 Total loss: 2.52597 timestamp: 1655012566.2735548 iteration: 6015 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23592 FastRCNN class loss: 0.10039 FastRCNN total loss: 0.33631 L1 loss: 0.0000e+00 L2 loss: 1.81551 Learning rate: 0.02 Mask loss: 0.23266 RPN box loss: 0.03715 RPN score loss: 0.01523 RPN total loss: 0.05237 Total loss: 2.43685 timestamp: 1655012569.5696752 iteration: 6020 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24274 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.3466 L1 loss: 0.0000e+00 L2 loss: 1.81517 Learning rate: 0.02 Mask loss: 0.24118 RPN box loss: 0.04197 RPN score loss: 0.01119 RPN total loss: 0.05317 Total loss: 2.45612 timestamp: 1655012572.9655764 iteration: 6025 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1884 FastRCNN class loss: 0.06038 FastRCNN total loss: 0.24878 L1 loss: 0.0000e+00 L2 loss: 1.81485 Learning rate: 0.02 Mask loss: 0.1937 RPN box loss: 0.0408 RPN score loss: 0.00656 RPN total loss: 0.04735 Total loss: 2.30468 timestamp: 1655012576.275746 iteration: 6030 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17316 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.24137 L1 loss: 0.0000e+00 L2 loss: 1.8145 Learning rate: 0.02 Mask loss: 0.31595 RPN box loss: 0.07696 RPN score loss: 0.00903 RPN total loss: 0.08599 Total loss: 2.4578 timestamp: 1655012579.5910797 iteration: 6035 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19768 FastRCNN class loss: 0.12778 FastRCNN total loss: 0.32546 L1 loss: 0.0000e+00 L2 loss: 1.81415 Learning rate: 0.02 Mask loss: 0.20245 RPN box loss: 0.05823 RPN score loss: 0.02508 RPN total loss: 0.08331 Total loss: 2.42538 timestamp: 1655012582.8333535 iteration: 6040 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20897 FastRCNN class loss: 0.12567 FastRCNN total loss: 0.33464 L1 loss: 0.0000e+00 L2 loss: 1.8138 Learning rate: 0.02 Mask loss: 0.25302 RPN box loss: 0.01065 RPN score loss: 0.00765 RPN total loss: 0.0183 Total loss: 2.41975 timestamp: 1655012586.076912 iteration: 6045 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28055 FastRCNN class loss: 0.11544 FastRCNN total loss: 0.39599 L1 loss: 0.0000e+00 L2 loss: 1.81345 Learning rate: 0.02 Mask loss: 0.39304 RPN box loss: 0.07733 RPN score loss: 0.0195 RPN total loss: 0.09682 Total loss: 2.69931 timestamp: 1655012589.3369014 iteration: 6050 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12469 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.18864 L1 loss: 0.0000e+00 L2 loss: 1.81311 Learning rate: 0.02 Mask loss: 0.17475 RPN box loss: 0.06531 RPN score loss: 0.00755 RPN total loss: 0.07286 Total loss: 2.24936 timestamp: 1655012592.6700382 iteration: 6055 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18855 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.26895 L1 loss: 0.0000e+00 L2 loss: 1.81275 Learning rate: 0.02 Mask loss: 0.22146 RPN box loss: 0.06626 RPN score loss: 0.00374 RPN total loss: 0.07 Total loss: 2.37316 timestamp: 1655012595.978608 iteration: 6060 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09739 FastRCNN class loss: 0.10429 FastRCNN total loss: 0.20168 L1 loss: 0.0000e+00 L2 loss: 1.8124 Learning rate: 0.02 Mask loss: 0.21081 RPN box loss: 0.08686 RPN score loss: 0.02598 RPN total loss: 0.11284 Total loss: 2.33773 timestamp: 1655012599.2767534 iteration: 6065 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22054 FastRCNN class loss: 0.10268 FastRCNN total loss: 0.32321 L1 loss: 0.0000e+00 L2 loss: 1.81207 Learning rate: 0.02 Mask loss: 0.2344 RPN box loss: 0.04332 RPN score loss: 0.00841 RPN total loss: 0.05173 Total loss: 2.42141 timestamp: 1655012602.4945865 iteration: 6070 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23167 FastRCNN class loss: 0.18302 FastRCNN total loss: 0.41469 L1 loss: 0.0000e+00 L2 loss: 1.81175 Learning rate: 0.02 Mask loss: 0.2246 RPN box loss: 0.05727 RPN score loss: 0.00415 RPN total loss: 0.06141 Total loss: 2.51245 timestamp: 1655012605.6868823 iteration: 6075 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.206 FastRCNN class loss: 0.08405 FastRCNN total loss: 0.29005 L1 loss: 0.0000e+00 L2 loss: 1.81141 Learning rate: 0.02 Mask loss: 0.23476 RPN box loss: 0.02794 RPN score loss: 0.01679 RPN total loss: 0.04473 Total loss: 2.38095 timestamp: 1655012609.036833 iteration: 6080 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15468 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.2294 L1 loss: 0.0000e+00 L2 loss: 1.81108 Learning rate: 0.02 Mask loss: 0.22512 RPN box loss: 0.02507 RPN score loss: 0.00224 RPN total loss: 0.02731 Total loss: 2.29291 timestamp: 1655012612.357655 iteration: 6085 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1431 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.21571 L1 loss: 0.0000e+00 L2 loss: 1.81073 Learning rate: 0.02 Mask loss: 0.23363 RPN box loss: 0.02995 RPN score loss: 0.00976 RPN total loss: 0.03971 Total loss: 2.29979 timestamp: 1655012615.65877 iteration: 6090 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20766 FastRCNN class loss: 0.09452 FastRCNN total loss: 0.30218 L1 loss: 0.0000e+00 L2 loss: 1.8104 Learning rate: 0.02 Mask loss: 0.2332 RPN box loss: 0.05333 RPN score loss: 0.00762 RPN total loss: 0.06095 Total loss: 2.40672 timestamp: 1655012618.961507 iteration: 6095 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19936 FastRCNN class loss: 0.09412 FastRCNN total loss: 0.29348 L1 loss: 0.0000e+00 L2 loss: 1.81006 Learning rate: 0.02 Mask loss: 0.32715 RPN box loss: 0.06097 RPN score loss: 0.01319 RPN total loss: 0.07416 Total loss: 2.50485 timestamp: 1655012622.340328 iteration: 6100 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17682 FastRCNN class loss: 0.096 FastRCNN total loss: 0.27282 L1 loss: 0.0000e+00 L2 loss: 1.8097 Learning rate: 0.02 Mask loss: 0.19035 RPN box loss: 0.06333 RPN score loss: 0.01543 RPN total loss: 0.07875 Total loss: 2.35162 timestamp: 1655012625.6684437 iteration: 6105 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24128 FastRCNN class loss: 0.12679 FastRCNN total loss: 0.36807 L1 loss: 0.0000e+00 L2 loss: 1.80935 Learning rate: 0.02 Mask loss: 0.22287 RPN box loss: 0.06214 RPN score loss: 0.01504 RPN total loss: 0.07718 Total loss: 2.47746 timestamp: 1655012629.0608518 iteration: 6110 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15124 FastRCNN class loss: 0.05453 FastRCNN total loss: 0.20577 L1 loss: 0.0000e+00 L2 loss: 1.80901 Learning rate: 0.02 Mask loss: 0.14265 RPN box loss: 0.01686 RPN score loss: 0.00596 RPN total loss: 0.02282 Total loss: 2.18026 timestamp: 1655012632.3826964 iteration: 6115 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13219 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.19756 L1 loss: 0.0000e+00 L2 loss: 1.80867 Learning rate: 0.02 Mask loss: 0.1976 RPN box loss: 0.04027 RPN score loss: 0.01916 RPN total loss: 0.05943 Total loss: 2.26326 timestamp: 1655012635.6241784 iteration: 6120 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15065 FastRCNN class loss: 0.08324 FastRCNN total loss: 0.23388 L1 loss: 0.0000e+00 L2 loss: 1.80831 Learning rate: 0.02 Mask loss: 0.15147 RPN box loss: 0.05473 RPN score loss: 0.00904 RPN total loss: 0.06377 Total loss: 2.25744 timestamp: 1655012638.9721143 iteration: 6125 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18028 FastRCNN class loss: 0.11913 FastRCNN total loss: 0.29941 L1 loss: 0.0000e+00 L2 loss: 1.80799 Learning rate: 0.02 Mask loss: 0.19722 RPN box loss: 0.05596 RPN score loss: 0.01308 RPN total loss: 0.06904 Total loss: 2.37366 timestamp: 1655012642.3415983 iteration: 6130 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3778 FastRCNN class loss: 0.10288 FastRCNN total loss: 0.48068 L1 loss: 0.0000e+00 L2 loss: 1.80766 Learning rate: 0.02 Mask loss: 0.33113 RPN box loss: 0.05882 RPN score loss: 0.0098 RPN total loss: 0.06863 Total loss: 2.6881 timestamp: 1655012645.631209 iteration: 6135 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20665 FastRCNN class loss: 0.12339 FastRCNN total loss: 0.33004 L1 loss: 0.0000e+00 L2 loss: 1.80732 Learning rate: 0.02 Mask loss: 0.19838 RPN box loss: 0.04266 RPN score loss: 0.00997 RPN total loss: 0.05263 Total loss: 2.38837 timestamp: 1655012648.996529 iteration: 6140 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17487 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.27373 L1 loss: 0.0000e+00 L2 loss: 1.80697 Learning rate: 0.02 Mask loss: 0.15531 RPN box loss: 0.01499 RPN score loss: 0.00447 RPN total loss: 0.01946 Total loss: 2.25547 timestamp: 1655012652.4418366 iteration: 6145 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21377 FastRCNN class loss: 0.10996 FastRCNN total loss: 0.32373 L1 loss: 0.0000e+00 L2 loss: 1.80663 Learning rate: 0.02 Mask loss: 0.20759 RPN box loss: 0.04197 RPN score loss: 0.00798 RPN total loss: 0.04995 Total loss: 2.3879 timestamp: 1655012655.8168423 iteration: 6150 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17689 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.26629 L1 loss: 0.0000e+00 L2 loss: 1.80629 Learning rate: 0.02 Mask loss: 0.25139 RPN box loss: 0.02343 RPN score loss: 0.0051 RPN total loss: 0.02853 Total loss: 2.35251 timestamp: 1655012659.1729631 iteration: 6155 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1866 FastRCNN class loss: 0.11191 FastRCNN total loss: 0.29851 L1 loss: 0.0000e+00 L2 loss: 1.80594 Learning rate: 0.02 Mask loss: 0.20097 RPN box loss: 0.02838 RPN score loss: 0.00682 RPN total loss: 0.0352 Total loss: 2.34062 timestamp: 1655012662.4606884 iteration: 6160 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25602 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.33559 L1 loss: 0.0000e+00 L2 loss: 1.80559 Learning rate: 0.02 Mask loss: 0.15721 RPN box loss: 0.00666 RPN score loss: 0.0057 RPN total loss: 0.01237 Total loss: 2.31075 timestamp: 1655012665.7460678 iteration: 6165 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11749 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.18298 L1 loss: 0.0000e+00 L2 loss: 1.80526 Learning rate: 0.02 Mask loss: 0.21492 RPN box loss: 0.09143 RPN score loss: 0.01732 RPN total loss: 0.10875 Total loss: 2.31191 timestamp: 1655012669.0545924 iteration: 6170 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27557 FastRCNN class loss: 0.21897 FastRCNN total loss: 0.49453 L1 loss: 0.0000e+00 L2 loss: 1.80494 Learning rate: 0.02 Mask loss: 0.18868 RPN box loss: 0.07987 RPN score loss: 0.01638 RPN total loss: 0.09625 Total loss: 2.58441 timestamp: 1655012672.3386376 iteration: 6175 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23517 FastRCNN class loss: 0.10588 FastRCNN total loss: 0.34105 L1 loss: 0.0000e+00 L2 loss: 1.80462 Learning rate: 0.02 Mask loss: 0.31414 RPN box loss: 0.04793 RPN score loss: 0.01029 RPN total loss: 0.05821 Total loss: 2.51802 timestamp: 1655012675.5966256 iteration: 6180 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17993 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.25921 L1 loss: 0.0000e+00 L2 loss: 1.80427 Learning rate: 0.02 Mask loss: 0.19046 RPN box loss: 0.01759 RPN score loss: 0.01574 RPN total loss: 0.03334 Total loss: 2.28727 timestamp: 1655012678.9189966 iteration: 6185 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2768 FastRCNN class loss: 0.22229 FastRCNN total loss: 0.49908 L1 loss: 0.0000e+00 L2 loss: 1.80393 Learning rate: 0.02 Mask loss: 0.29922 RPN box loss: 0.06743 RPN score loss: 0.01783 RPN total loss: 0.08526 Total loss: 2.68749 timestamp: 1655012682.2116914 iteration: 6190 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21749 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.30857 L1 loss: 0.0000e+00 L2 loss: 1.80359 Learning rate: 0.02 Mask loss: 0.24123 RPN box loss: 0.05365 RPN score loss: 0.00745 RPN total loss: 0.06109 Total loss: 2.41449 timestamp: 1655012685.4926581 iteration: 6195 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14644 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.205 L1 loss: 0.0000e+00 L2 loss: 1.80326 Learning rate: 0.02 Mask loss: 0.22781 RPN box loss: 0.02215 RPN score loss: 0.00693 RPN total loss: 0.02909 Total loss: 2.26516 timestamp: 1655012688.8527524 iteration: 6200 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.09162 FastRCNN total loss: 0.23471 L1 loss: 0.0000e+00 L2 loss: 1.80291 Learning rate: 0.02 Mask loss: 0.15222 RPN box loss: 0.01363 RPN score loss: 0.0039 RPN total loss: 0.01753 Total loss: 2.20737 timestamp: 1655012692.1776867 iteration: 6205 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16737 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.25684 L1 loss: 0.0000e+00 L2 loss: 1.80256 Learning rate: 0.02 Mask loss: 0.17943 RPN box loss: 0.04011 RPN score loss: 0.01062 RPN total loss: 0.05073 Total loss: 2.28957 timestamp: 1655012695.4066627 iteration: 6210 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15865 FastRCNN class loss: 0.09729 FastRCNN total loss: 0.25595 L1 loss: 0.0000e+00 L2 loss: 1.80222 Learning rate: 0.02 Mask loss: 0.23629 RPN box loss: 0.05718 RPN score loss: 0.01591 RPN total loss: 0.07309 Total loss: 2.36754 timestamp: 1655012698.7904315 iteration: 6215 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12898 FastRCNN class loss: 0.0733 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 1.8019 Learning rate: 0.02 Mask loss: 0.2084 RPN box loss: 0.07085 RPN score loss: 0.01498 RPN total loss: 0.08583 Total loss: 2.29841 timestamp: 1655012702.084832 iteration: 6220 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26018 FastRCNN class loss: 0.09517 FastRCNN total loss: 0.35535 L1 loss: 0.0000e+00 L2 loss: 1.80156 Learning rate: 0.02 Mask loss: 0.24269 RPN box loss: 0.03169 RPN score loss: 0.01566 RPN total loss: 0.04734 Total loss: 2.44694 timestamp: 1655012705.3051295 iteration: 6225 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15068 FastRCNN class loss: 0.0669 FastRCNN total loss: 0.21758 L1 loss: 0.0000e+00 L2 loss: 1.80121 Learning rate: 0.02 Mask loss: 0.21301 RPN box loss: 0.03284 RPN score loss: 0.01618 RPN total loss: 0.04902 Total loss: 2.28081 timestamp: 1655012708.6342232 iteration: 6230 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31887 FastRCNN class loss: 0.13808 FastRCNN total loss: 0.45695 L1 loss: 0.0000e+00 L2 loss: 1.80088 Learning rate: 0.02 Mask loss: 0.29102 RPN box loss: 0.08806 RPN score loss: 0.00874 RPN total loss: 0.0968 Total loss: 2.64565 timestamp: 1655012711.8171449 iteration: 6235 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14881 FastRCNN class loss: 0.10358 FastRCNN total loss: 0.25239 L1 loss: 0.0000e+00 L2 loss: 1.80054 Learning rate: 0.02 Mask loss: 0.22882 RPN box loss: 0.04132 RPN score loss: 0.0118 RPN total loss: 0.05313 Total loss: 2.33486 timestamp: 1655012715.0660324 iteration: 6240 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20421 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.30611 L1 loss: 0.0000e+00 L2 loss: 1.8002 Learning rate: 0.02 Mask loss: 0.22214 RPN box loss: 0.02488 RPN score loss: 0.04008 RPN total loss: 0.06495 Total loss: 2.3934 timestamp: 1655012718.3351011 iteration: 6245 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17577 FastRCNN class loss: 0.06758 FastRCNN total loss: 0.24335 L1 loss: 0.0000e+00 L2 loss: 1.79985 Learning rate: 0.02 Mask loss: 0.14728 RPN box loss: 0.00586 RPN score loss: 0.00445 RPN total loss: 0.01031 Total loss: 2.20078 timestamp: 1655012721.6139805 iteration: 6250 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22817 FastRCNN class loss: 0.09221 FastRCNN total loss: 0.32038 L1 loss: 0.0000e+00 L2 loss: 1.79952 Learning rate: 0.02 Mask loss: 0.21491 RPN box loss: 0.03086 RPN score loss: 0.0044 RPN total loss: 0.03526 Total loss: 2.37007 timestamp: 1655012724.9530668 iteration: 6255 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21025 FastRCNN class loss: 0.06322 FastRCNN total loss: 0.27347 L1 loss: 0.0000e+00 L2 loss: 1.79919 Learning rate: 0.02 Mask loss: 0.16872 RPN box loss: 0.02054 RPN score loss: 0.00769 RPN total loss: 0.02822 Total loss: 2.2696 timestamp: 1655012728.244763 iteration: 6260 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22097 FastRCNN class loss: 0.17268 FastRCNN total loss: 0.39366 L1 loss: 0.0000e+00 L2 loss: 1.79884 Learning rate: 0.02 Mask loss: 0.2288 RPN box loss: 0.04246 RPN score loss: 0.01484 RPN total loss: 0.05731 Total loss: 2.47861 timestamp: 1655012731.5854764 iteration: 6265 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26395 FastRCNN class loss: 0.11924 FastRCNN total loss: 0.38319 L1 loss: 0.0000e+00 L2 loss: 1.79851 Learning rate: 0.02 Mask loss: 0.25759 RPN box loss: 0.04416 RPN score loss: 0.01209 RPN total loss: 0.05625 Total loss: 2.49554 timestamp: 1655012734.849446 iteration: 6270 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20746 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.30682 L1 loss: 0.0000e+00 L2 loss: 1.79817 Learning rate: 0.02 Mask loss: 0.18158 RPN box loss: 0.05956 RPN score loss: 0.0121 RPN total loss: 0.07165 Total loss: 2.35822 timestamp: 1655012738.1465347 iteration: 6275 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1941 FastRCNN class loss: 0.09365 FastRCNN total loss: 0.28775 L1 loss: 0.0000e+00 L2 loss: 1.79782 Learning rate: 0.02 Mask loss: 0.24015 RPN box loss: 0.01472 RPN score loss: 0.00525 RPN total loss: 0.01997 Total loss: 2.34569 timestamp: 1655012741.4514253 iteration: 6280 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21719 FastRCNN class loss: 0.10716 FastRCNN total loss: 0.32435 L1 loss: 0.0000e+00 L2 loss: 1.79748 Learning rate: 0.02 Mask loss: 0.25829 RPN box loss: 0.01267 RPN score loss: 0.00802 RPN total loss: 0.0207 Total loss: 2.40082 timestamp: 1655012744.7216578 iteration: 6285 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21962 FastRCNN class loss: 0.118 FastRCNN total loss: 0.33762 L1 loss: 0.0000e+00 L2 loss: 1.79715 Learning rate: 0.02 Mask loss: 0.23288 RPN box loss: 0.0267 RPN score loss: 0.01171 RPN total loss: 0.03841 Total loss: 2.40606 timestamp: 1655012747.9898095 iteration: 6290 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21428 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.28784 L1 loss: 0.0000e+00 L2 loss: 1.79681 Learning rate: 0.02 Mask loss: 0.23784 RPN box loss: 0.0938 RPN score loss: 0.01491 RPN total loss: 0.10871 Total loss: 2.4312 timestamp: 1655012751.3020635 iteration: 6295 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25076 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.33034 L1 loss: 0.0000e+00 L2 loss: 1.79647 Learning rate: 0.02 Mask loss: 0.2192 RPN box loss: 0.12849 RPN score loss: 0.01435 RPN total loss: 0.14284 Total loss: 2.48885 timestamp: 1655012754.6387892 iteration: 6300 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26155 FastRCNN class loss: 0.09954 FastRCNN total loss: 0.36109 L1 loss: 0.0000e+00 L2 loss: 1.79613 Learning rate: 0.02 Mask loss: 0.25288 RPN box loss: 0.04632 RPN score loss: 0.0087 RPN total loss: 0.05502 Total loss: 2.46513 timestamp: 1655012757.8543108 iteration: 6305 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21812 FastRCNN class loss: 0.19395 FastRCNN total loss: 0.41206 L1 loss: 0.0000e+00 L2 loss: 1.79581 Learning rate: 0.02 Mask loss: 0.28455 RPN box loss: 0.10729 RPN score loss: 0.0115 RPN total loss: 0.11879 Total loss: 2.61121 timestamp: 1655012761.2120242 iteration: 6310 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23648 FastRCNN class loss: 0.10832 FastRCNN total loss: 0.34481 L1 loss: 0.0000e+00 L2 loss: 1.79548 Learning rate: 0.02 Mask loss: 0.2645 RPN box loss: 0.08094 RPN score loss: 0.01806 RPN total loss: 0.099 Total loss: 2.50379 timestamp: 1655012764.4478385 iteration: 6315 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23198 FastRCNN class loss: 0.11953 FastRCNN total loss: 0.35151 L1 loss: 0.0000e+00 L2 loss: 1.79515 Learning rate: 0.02 Mask loss: 0.29746 RPN box loss: 0.02322 RPN score loss: 0.00995 RPN total loss: 0.03317 Total loss: 2.47729 timestamp: 1655012767.8572598 iteration: 6320 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18012 FastRCNN class loss: 0.13638 FastRCNN total loss: 0.3165 L1 loss: 0.0000e+00 L2 loss: 1.7948 Learning rate: 0.02 Mask loss: 0.23518 RPN box loss: 0.07867 RPN score loss: 0.01324 RPN total loss: 0.09191 Total loss: 2.43838 timestamp: 1655012771.2676122 iteration: 6325 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2483 FastRCNN class loss: 0.07716 FastRCNN total loss: 0.32546 L1 loss: 0.0000e+00 L2 loss: 1.79446 Learning rate: 0.02 Mask loss: 0.45765 RPN box loss: 0.03693 RPN score loss: 0.01191 RPN total loss: 0.04884 Total loss: 2.6264 timestamp: 1655012774.5932186 iteration: 6330 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25317 FastRCNN class loss: 0.09556 FastRCNN total loss: 0.34873 L1 loss: 0.0000e+00 L2 loss: 1.79411 Learning rate: 0.02 Mask loss: 0.3049 RPN box loss: 0.04845 RPN score loss: 0.00995 RPN total loss: 0.0584 Total loss: 2.50615 timestamp: 1655012777.853985 iteration: 6335 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17216 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.25859 L1 loss: 0.0000e+00 L2 loss: 1.79378 Learning rate: 0.02 Mask loss: 0.16996 RPN box loss: 0.07069 RPN score loss: 0.02182 RPN total loss: 0.09251 Total loss: 2.31484 timestamp: 1655012781.0935373 iteration: 6340 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11751 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.20724 L1 loss: 0.0000e+00 L2 loss: 1.79344 Learning rate: 0.02 Mask loss: 0.21409 RPN box loss: 0.01056 RPN score loss: 0.00637 RPN total loss: 0.01693 Total loss: 2.2317 timestamp: 1655012784.4154243 iteration: 6345 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23659 FastRCNN class loss: 0.12829 FastRCNN total loss: 0.36488 L1 loss: 0.0000e+00 L2 loss: 1.79311 Learning rate: 0.02 Mask loss: 0.23111 RPN box loss: 0.05228 RPN score loss: 0.00941 RPN total loss: 0.0617 Total loss: 2.4508 timestamp: 1655012787.703654 iteration: 6350 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19131 FastRCNN class loss: 0.11562 FastRCNN total loss: 0.30693 L1 loss: 0.0000e+00 L2 loss: 1.79278 Learning rate: 0.02 Mask loss: 0.23977 RPN box loss: 0.05676 RPN score loss: 0.01553 RPN total loss: 0.07229 Total loss: 2.41178 timestamp: 1655012790.9850926 iteration: 6355 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24533 FastRCNN class loss: 0.16216 FastRCNN total loss: 0.40749 L1 loss: 0.0000e+00 L2 loss: 1.79243 Learning rate: 0.02 Mask loss: 0.21859 RPN box loss: 0.08129 RPN score loss: 0.02336 RPN total loss: 0.10465 Total loss: 2.52315 timestamp: 1655012794.3618762 iteration: 6360 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29232 FastRCNN class loss: 0.08684 FastRCNN total loss: 0.37916 L1 loss: 0.0000e+00 L2 loss: 1.79209 Learning rate: 0.02 Mask loss: 0.24163 RPN box loss: 0.04691 RPN score loss: 0.01214 RPN total loss: 0.05905 Total loss: 2.47193 timestamp: 1655012797.651027 iteration: 6365 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1731 FastRCNN class loss: 0.06344 FastRCNN total loss: 0.23654 L1 loss: 0.0000e+00 L2 loss: 1.79176 Learning rate: 0.02 Mask loss: 0.21125 RPN box loss: 0.12371 RPN score loss: 0.0122 RPN total loss: 0.13591 Total loss: 2.37546 timestamp: 1655012800.9809709 iteration: 6370 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23659 FastRCNN class loss: 0.16218 FastRCNN total loss: 0.39877 L1 loss: 0.0000e+00 L2 loss: 1.7914 Learning rate: 0.02 Mask loss: 0.24259 RPN box loss: 0.01484 RPN score loss: 0.00724 RPN total loss: 0.02208 Total loss: 2.45485 timestamp: 1655012804.262669 iteration: 6375 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25209 FastRCNN class loss: 0.06832 FastRCNN total loss: 0.32041 L1 loss: 0.0000e+00 L2 loss: 1.79106 Learning rate: 0.02 Mask loss: 0.16678 RPN box loss: 0.00729 RPN score loss: 0.00621 RPN total loss: 0.0135 Total loss: 2.29176 timestamp: 1655012807.570524 iteration: 6380 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1918 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.27339 L1 loss: 0.0000e+00 L2 loss: 1.79074 Learning rate: 0.02 Mask loss: 0.2009 RPN box loss: 0.04502 RPN score loss: 0.01159 RPN total loss: 0.0566 Total loss: 2.32163 timestamp: 1655012810.8595238 iteration: 6385 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12618 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.20753 L1 loss: 0.0000e+00 L2 loss: 1.79042 Learning rate: 0.02 Mask loss: 0.29867 RPN box loss: 0.00941 RPN score loss: 0.0086 RPN total loss: 0.01801 Total loss: 2.31463 timestamp: 1655012814.2419164 iteration: 6390 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11469 FastRCNN class loss: 0.0587 FastRCNN total loss: 0.17339 L1 loss: 0.0000e+00 L2 loss: 1.79008 Learning rate: 0.02 Mask loss: 0.21259 RPN box loss: 0.02496 RPN score loss: 0.00782 RPN total loss: 0.03277 Total loss: 2.20883 timestamp: 1655012817.5909002 iteration: 6395 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.16326 L1 loss: 0.0000e+00 L2 loss: 1.78974 Learning rate: 0.02 Mask loss: 0.20579 RPN box loss: 0.02445 RPN score loss: 0.03228 RPN total loss: 0.05673 Total loss: 2.21552 timestamp: 1655012820.923838 iteration: 6400 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22287 FastRCNN class loss: 0.08942 FastRCNN total loss: 0.31229 L1 loss: 0.0000e+00 L2 loss: 1.7894 Learning rate: 0.02 Mask loss: 0.2059 RPN box loss: 0.0707 RPN score loss: 0.01247 RPN total loss: 0.08318 Total loss: 2.39078 timestamp: 1655012824.2258096 iteration: 6405 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22399 FastRCNN class loss: 0.15657 FastRCNN total loss: 0.38056 L1 loss: 0.0000e+00 L2 loss: 1.78907 Learning rate: 0.02 Mask loss: 0.23284 RPN box loss: 0.05456 RPN score loss: 0.02337 RPN total loss: 0.07792 Total loss: 2.4804 timestamp: 1655012827.5265467 iteration: 6410 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18075 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.25412 L1 loss: 0.0000e+00 L2 loss: 1.78875 Learning rate: 0.02 Mask loss: 0.17517 RPN box loss: 0.07329 RPN score loss: 0.01381 RPN total loss: 0.08709 Total loss: 2.30514 timestamp: 1655012830.832807 iteration: 6415 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18335 FastRCNN class loss: 0.09474 FastRCNN total loss: 0.27809 L1 loss: 0.0000e+00 L2 loss: 1.7884 Learning rate: 0.02 Mask loss: 0.26484 RPN box loss: 0.05214 RPN score loss: 0.01524 RPN total loss: 0.06738 Total loss: 2.3987 timestamp: 1655012834.1842499 iteration: 6420 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11182 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.17867 L1 loss: 0.0000e+00 L2 loss: 1.78806 Learning rate: 0.02 Mask loss: 0.12802 RPN box loss: 0.03978 RPN score loss: 0.00848 RPN total loss: 0.04826 Total loss: 2.14301 timestamp: 1655012837.511519 iteration: 6425 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26787 FastRCNN class loss: 0.16903 FastRCNN total loss: 0.43691 L1 loss: 0.0000e+00 L2 loss: 1.78772 Learning rate: 0.02 Mask loss: 0.31537 RPN box loss: 0.03067 RPN score loss: 0.00586 RPN total loss: 0.03653 Total loss: 2.57653 timestamp: 1655012840.8913047 iteration: 6430 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18241 FastRCNN class loss: 0.10521 FastRCNN total loss: 0.28761 L1 loss: 0.0000e+00 L2 loss: 1.78737 Learning rate: 0.02 Mask loss: 0.18092 RPN box loss: 0.04113 RPN score loss: 0.00784 RPN total loss: 0.04898 Total loss: 2.30489 timestamp: 1655012844.2653446 iteration: 6435 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20667 FastRCNN class loss: 0.14054 FastRCNN total loss: 0.34721 L1 loss: 0.0000e+00 L2 loss: 1.78704 Learning rate: 0.02 Mask loss: 0.26461 RPN box loss: 0.02678 RPN score loss: 0.01534 RPN total loss: 0.04212 Total loss: 2.44098 timestamp: 1655012847.5924664 iteration: 6440 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13637 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.21209 L1 loss: 0.0000e+00 L2 loss: 1.7867 Learning rate: 0.02 Mask loss: 0.21235 RPN box loss: 0.08012 RPN score loss: 0.01146 RPN total loss: 0.09158 Total loss: 2.30272 timestamp: 1655012850.9770706 iteration: 6445 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29894 FastRCNN class loss: 0.12847 FastRCNN total loss: 0.42741 L1 loss: 0.0000e+00 L2 loss: 1.78635 Learning rate: 0.02 Mask loss: 0.27515 RPN box loss: 0.03148 RPN score loss: 0.01007 RPN total loss: 0.04155 Total loss: 2.53046 timestamp: 1655012854.2486527 iteration: 6450 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22838 FastRCNN class loss: 0.15603 FastRCNN total loss: 0.3844 L1 loss: 0.0000e+00 L2 loss: 1.78604 Learning rate: 0.02 Mask loss: 0.32985 RPN box loss: 0.0394 RPN score loss: 0.02219 RPN total loss: 0.06159 Total loss: 2.56189 timestamp: 1655012857.592628 iteration: 6455 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15556 FastRCNN class loss: 0.09642 FastRCNN total loss: 0.25198 L1 loss: 0.0000e+00 L2 loss: 1.78571 Learning rate: 0.02 Mask loss: 0.21628 RPN box loss: 0.04867 RPN score loss: 0.01164 RPN total loss: 0.06031 Total loss: 2.31429 timestamp: 1655012860.848239 iteration: 6460 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24501 FastRCNN class loss: 0.11564 FastRCNN total loss: 0.36065 L1 loss: 0.0000e+00 L2 loss: 1.78538 Learning rate: 0.02 Mask loss: 0.19881 RPN box loss: 0.06033 RPN score loss: 0.01437 RPN total loss: 0.07471 Total loss: 2.41955 timestamp: 1655012864.1393592 iteration: 6465 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26908 FastRCNN class loss: 0.12055 FastRCNN total loss: 0.38963 L1 loss: 0.0000e+00 L2 loss: 1.78504 Learning rate: 0.02 Mask loss: 0.26184 RPN box loss: 0.03588 RPN score loss: 0.00954 RPN total loss: 0.04542 Total loss: 2.48194 timestamp: 1655012867.4631612 iteration: 6470 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18556 FastRCNN class loss: 0.11156 FastRCNN total loss: 0.29712 L1 loss: 0.0000e+00 L2 loss: 1.78471 Learning rate: 0.02 Mask loss: 0.22302 RPN box loss: 0.01996 RPN score loss: 0.00715 RPN total loss: 0.0271 Total loss: 2.33196 timestamp: 1655012870.7753415 iteration: 6475 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15913 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.24363 L1 loss: 0.0000e+00 L2 loss: 1.78436 Learning rate: 0.02 Mask loss: 0.15943 RPN box loss: 0.10328 RPN score loss: 0.01039 RPN total loss: 0.11368 Total loss: 2.3011 timestamp: 1655012874.083699 iteration: 6480 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22203 FastRCNN class loss: 0.08859 FastRCNN total loss: 0.31062 L1 loss: 0.0000e+00 L2 loss: 1.78403 Learning rate: 0.02 Mask loss: 0.19625 RPN box loss: 0.02196 RPN score loss: 0.00721 RPN total loss: 0.02918 Total loss: 2.32008 timestamp: 1655012877.382751 iteration: 6485 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17494 FastRCNN class loss: 0.10943 FastRCNN total loss: 0.28437 L1 loss: 0.0000e+00 L2 loss: 1.78367 Learning rate: 0.02 Mask loss: 0.18166 RPN box loss: 0.03786 RPN score loss: 0.0131 RPN total loss: 0.05095 Total loss: 2.30065 timestamp: 1655012880.7469819 iteration: 6490 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18069 FastRCNN class loss: 0.10686 FastRCNN total loss: 0.28755 L1 loss: 0.0000e+00 L2 loss: 1.78334 Learning rate: 0.02 Mask loss: 0.22925 RPN box loss: 0.08336 RPN score loss: 0.03361 RPN total loss: 0.11697 Total loss: 2.41711 timestamp: 1655012884.0570285 iteration: 6495 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24264 FastRCNN class loss: 0.10907 FastRCNN total loss: 0.35171 L1 loss: 0.0000e+00 L2 loss: 1.78302 Learning rate: 0.02 Mask loss: 0.20292 RPN box loss: 0.02587 RPN score loss: 0.01149 RPN total loss: 0.03735 Total loss: 2.375 timestamp: 1655012887.390308 iteration: 6500 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19571 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.25411 L1 loss: 0.0000e+00 L2 loss: 1.7827 Learning rate: 0.02 Mask loss: 0.1817 RPN box loss: 0.03332 RPN score loss: 0.01252 RPN total loss: 0.04584 Total loss: 2.26435 timestamp: 1655012890.6904824 iteration: 6505 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19314 FastRCNN class loss: 0.11594 FastRCNN total loss: 0.30908 L1 loss: 0.0000e+00 L2 loss: 1.78234 Learning rate: 0.02 Mask loss: 0.24554 RPN box loss: 0.05849 RPN score loss: 0.01645 RPN total loss: 0.07495 Total loss: 2.4119 timestamp: 1655012894.039875 iteration: 6510 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.243 FastRCNN class loss: 0.11393 FastRCNN total loss: 0.35693 L1 loss: 0.0000e+00 L2 loss: 1.78199 Learning rate: 0.02 Mask loss: 0.20924 RPN box loss: 0.05003 RPN score loss: 0.00964 RPN total loss: 0.05967 Total loss: 2.40783 timestamp: 1655012897.3252344 iteration: 6515 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19122 FastRCNN class loss: 0.0797 FastRCNN total loss: 0.27092 L1 loss: 0.0000e+00 L2 loss: 1.78167 Learning rate: 0.02 Mask loss: 0.18006 RPN box loss: 0.02317 RPN score loss: 0.0095 RPN total loss: 0.03267 Total loss: 2.26532 timestamp: 1655012900.586886 iteration: 6520 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28131 FastRCNN class loss: 0.12753 FastRCNN total loss: 0.40884 L1 loss: 0.0000e+00 L2 loss: 1.78134 Learning rate: 0.02 Mask loss: 0.26774 RPN box loss: 0.01918 RPN score loss: 0.00702 RPN total loss: 0.02619 Total loss: 2.48412 timestamp: 1655012903.966064 iteration: 6525 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21937 FastRCNN class loss: 0.13571 FastRCNN total loss: 0.35508 L1 loss: 0.0000e+00 L2 loss: 1.781 Learning rate: 0.02 Mask loss: 0.24107 RPN box loss: 0.02973 RPN score loss: 0.00907 RPN total loss: 0.0388 Total loss: 2.41595 timestamp: 1655012907.2601302 iteration: 6530 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27286 FastRCNN class loss: 0.09623 FastRCNN total loss: 0.36909 L1 loss: 0.0000e+00 L2 loss: 1.78066 Learning rate: 0.02 Mask loss: 0.29868 RPN box loss: 0.03133 RPN score loss: 0.01414 RPN total loss: 0.04547 Total loss: 2.49389 timestamp: 1655012910.5680475 iteration: 6535 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22055 FastRCNN class loss: 0.10631 FastRCNN total loss: 0.32687 L1 loss: 0.0000e+00 L2 loss: 1.78033 Learning rate: 0.02 Mask loss: 0.25156 RPN box loss: 0.03602 RPN score loss: 0.01418 RPN total loss: 0.05019 Total loss: 2.40895 timestamp: 1655012913.9280355 iteration: 6540 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24999 FastRCNN class loss: 0.10367 FastRCNN total loss: 0.35366 L1 loss: 0.0000e+00 L2 loss: 1.78002 Learning rate: 0.02 Mask loss: 0.24568 RPN box loss: 0.06207 RPN score loss: 0.02062 RPN total loss: 0.08269 Total loss: 2.46204 timestamp: 1655012917.244311 iteration: 6545 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24814 FastRCNN class loss: 0.18621 FastRCNN total loss: 0.43435 L1 loss: 0.0000e+00 L2 loss: 1.77966 Learning rate: 0.02 Mask loss: 0.258 RPN box loss: 0.08594 RPN score loss: 0.05089 RPN total loss: 0.13684 Total loss: 2.60886 timestamp: 1655012920.630832 iteration: 6550 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.04365 FastRCNN total loss: 0.13852 L1 loss: 0.0000e+00 L2 loss: 1.77933 Learning rate: 0.02 Mask loss: 0.20403 RPN box loss: 0.06788 RPN score loss: 0.00741 RPN total loss: 0.07529 Total loss: 2.19717 timestamp: 1655012923.9808958 iteration: 6555 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14719 FastRCNN class loss: 0.09144 FastRCNN total loss: 0.23864 L1 loss: 0.0000e+00 L2 loss: 1.77898 Learning rate: 0.02 Mask loss: 0.2031 RPN box loss: 0.02933 RPN score loss: 0.00302 RPN total loss: 0.03234 Total loss: 2.25307 timestamp: 1655012927.2592554 iteration: 6560 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19267 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.27221 L1 loss: 0.0000e+00 L2 loss: 1.77866 Learning rate: 0.02 Mask loss: 0.23479 RPN box loss: 0.05009 RPN score loss: 0.00906 RPN total loss: 0.05915 Total loss: 2.34482 timestamp: 1655012930.6329656 iteration: 6565 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13684 FastRCNN class loss: 0.07396 FastRCNN total loss: 0.21079 L1 loss: 0.0000e+00 L2 loss: 1.77834 Learning rate: 0.02 Mask loss: 0.21377 RPN box loss: 0.05224 RPN score loss: 0.00594 RPN total loss: 0.05818 Total loss: 2.26108 timestamp: 1655012933.911899 iteration: 6570 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14812 FastRCNN class loss: 0.09038 FastRCNN total loss: 0.2385 L1 loss: 0.0000e+00 L2 loss: 1.77801 Learning rate: 0.02 Mask loss: 0.15309 RPN box loss: 0.01559 RPN score loss: 0.00958 RPN total loss: 0.02517 Total loss: 2.19477 timestamp: 1655012937.188052 iteration: 6575 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.1672 L1 loss: 0.0000e+00 L2 loss: 1.77767 Learning rate: 0.02 Mask loss: 0.1537 RPN box loss: 0.02425 RPN score loss: 0.00681 RPN total loss: 0.03106 Total loss: 2.12963 timestamp: 1655012940.4567554 iteration: 6580 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.06155 FastRCNN total loss: 0.19137 L1 loss: 0.0000e+00 L2 loss: 1.77732 Learning rate: 0.02 Mask loss: 0.16538 RPN box loss: 0.00585 RPN score loss: 0.00329 RPN total loss: 0.00914 Total loss: 2.14321 timestamp: 1655012943.701968 iteration: 6585 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15411 FastRCNN class loss: 0.12683 FastRCNN total loss: 0.28094 L1 loss: 0.0000e+00 L2 loss: 1.777 Learning rate: 0.02 Mask loss: 0.18366 RPN box loss: 0.05405 RPN score loss: 0.01049 RPN total loss: 0.06454 Total loss: 2.30614 timestamp: 1655012946.9049838 iteration: 6590 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22178 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.30768 L1 loss: 0.0000e+00 L2 loss: 1.77669 Learning rate: 0.02 Mask loss: 0.22932 RPN box loss: 0.05419 RPN score loss: 0.00878 RPN total loss: 0.06297 Total loss: 2.37667 timestamp: 1655012950.214596 iteration: 6595 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17882 FastRCNN class loss: 0.09245 FastRCNN total loss: 0.27127 L1 loss: 0.0000e+00 L2 loss: 1.77636 Learning rate: 0.02 Mask loss: 0.16647 RPN box loss: 0.06078 RPN score loss: 0.02292 RPN total loss: 0.08371 Total loss: 2.29781 timestamp: 1655012953.4735112 iteration: 6600 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21173 FastRCNN class loss: 0.11402 FastRCNN total loss: 0.32575 L1 loss: 0.0000e+00 L2 loss: 1.77602 Learning rate: 0.02 Mask loss: 0.18476 RPN box loss: 0.07727 RPN score loss: 0.03147 RPN total loss: 0.10874 Total loss: 2.39528 timestamp: 1655012956.713265 iteration: 6605 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16599 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.23561 L1 loss: 0.0000e+00 L2 loss: 1.77568 Learning rate: 0.02 Mask loss: 0.17664 RPN box loss: 0.03172 RPN score loss: 0.00598 RPN total loss: 0.03771 Total loss: 2.22564 timestamp: 1655012960.033972 iteration: 6610 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24119 FastRCNN class loss: 0.1533 FastRCNN total loss: 0.39449 L1 loss: 0.0000e+00 L2 loss: 1.77535 Learning rate: 0.02 Mask loss: 0.22074 RPN box loss: 0.04973 RPN score loss: 0.00928 RPN total loss: 0.05901 Total loss: 2.4496 timestamp: 1655012963.3479793 iteration: 6615 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18472 FastRCNN class loss: 0.1606 FastRCNN total loss: 0.34532 L1 loss: 0.0000e+00 L2 loss: 1.77501 Learning rate: 0.02 Mask loss: 0.21866 RPN box loss: 0.07412 RPN score loss: 0.03401 RPN total loss: 0.10812 Total loss: 2.44711 timestamp: 1655012966.6358156 iteration: 6620 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20237 FastRCNN class loss: 0.09171 FastRCNN total loss: 0.29408 L1 loss: 0.0000e+00 L2 loss: 1.77468 Learning rate: 0.02 Mask loss: 0.16869 RPN box loss: 0.08263 RPN score loss: 0.00368 RPN total loss: 0.08631 Total loss: 2.32376 timestamp: 1655012970.0240524 iteration: 6625 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2121 FastRCNN class loss: 0.085 FastRCNN total loss: 0.2971 L1 loss: 0.0000e+00 L2 loss: 1.77434 Learning rate: 0.02 Mask loss: 0.26559 RPN box loss: 0.12985 RPN score loss: 0.01192 RPN total loss: 0.14177 Total loss: 2.4788 timestamp: 1655012973.3422825 iteration: 6630 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20795 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.29327 L1 loss: 0.0000e+00 L2 loss: 1.774 Learning rate: 0.02 Mask loss: 0.24352 RPN box loss: 0.0414 RPN score loss: 0.00603 RPN total loss: 0.04743 Total loss: 2.35822 timestamp: 1655012976.629968 iteration: 6635 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.16955 L1 loss: 0.0000e+00 L2 loss: 1.77368 Learning rate: 0.02 Mask loss: 0.11896 RPN box loss: 0.07647 RPN score loss: 0.00986 RPN total loss: 0.08633 Total loss: 2.14852 timestamp: 1655012979.920585 iteration: 6640 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15305 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.25065 L1 loss: 0.0000e+00 L2 loss: 1.77337 Learning rate: 0.02 Mask loss: 0.19218 RPN box loss: 0.1134 RPN score loss: 0.02437 RPN total loss: 0.13778 Total loss: 2.35398 timestamp: 1655012983.18224 iteration: 6645 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2005 FastRCNN class loss: 0.12307 FastRCNN total loss: 0.32357 L1 loss: 0.0000e+00 L2 loss: 1.77303 Learning rate: 0.02 Mask loss: 0.23181 RPN box loss: 0.06887 RPN score loss: 0.01382 RPN total loss: 0.08268 Total loss: 2.41109 timestamp: 1655012986.3871546 iteration: 6650 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.33932 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.42522 L1 loss: 0.0000e+00 L2 loss: 1.77268 Learning rate: 0.02 Mask loss: 0.17516 RPN box loss: 0.06511 RPN score loss: 0.01328 RPN total loss: 0.07839 Total loss: 2.45144 timestamp: 1655012989.676703 iteration: 6655 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22968 FastRCNN class loss: 0.13352 FastRCNN total loss: 0.3632 L1 loss: 0.0000e+00 L2 loss: 1.77235 Learning rate: 0.02 Mask loss: 0.24116 RPN box loss: 0.04902 RPN score loss: 0.01217 RPN total loss: 0.06119 Total loss: 2.43789 timestamp: 1655012992.9731393 iteration: 6660 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16213 FastRCNN class loss: 0.05778 FastRCNN total loss: 0.21991 L1 loss: 0.0000e+00 L2 loss: 1.77201 Learning rate: 0.02 Mask loss: 0.20356 RPN box loss: 0.04949 RPN score loss: 0.00494 RPN total loss: 0.05443 Total loss: 2.24992 timestamp: 1655012996.2065327 iteration: 6665 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.12823 FastRCNN total loss: 0.28468 L1 loss: 0.0000e+00 L2 loss: 1.77168 Learning rate: 0.02 Mask loss: 0.25794 RPN box loss: 0.01242 RPN score loss: 0.00652 RPN total loss: 0.01894 Total loss: 2.33323 timestamp: 1655012999.5588288 iteration: 6670 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.238 FastRCNN class loss: 0.14002 FastRCNN total loss: 0.37802 L1 loss: 0.0000e+00 L2 loss: 1.77134 Learning rate: 0.02 Mask loss: 0.4114 RPN box loss: 0.02165 RPN score loss: 0.00523 RPN total loss: 0.02688 Total loss: 2.58763 timestamp: 1655013002.8707292 iteration: 6675 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32825 FastRCNN class loss: 0.16756 FastRCNN total loss: 0.49581 L1 loss: 0.0000e+00 L2 loss: 1.77099 Learning rate: 0.02 Mask loss: 0.24863 RPN box loss: 0.03931 RPN score loss: 0.00639 RPN total loss: 0.0457 Total loss: 2.56112 timestamp: 1655013006.1991377 iteration: 6680 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14995 FastRCNN class loss: 0.06806 FastRCNN total loss: 0.21801 L1 loss: 0.0000e+00 L2 loss: 1.77068 Learning rate: 0.02 Mask loss: 0.21726 RPN box loss: 0.07508 RPN score loss: 0.01442 RPN total loss: 0.08949 Total loss: 2.29544 timestamp: 1655013009.513735 iteration: 6685 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19692 FastRCNN class loss: 0.09635 FastRCNN total loss: 0.29327 L1 loss: 0.0000e+00 L2 loss: 1.77038 Learning rate: 0.02 Mask loss: 0.24862 RPN box loss: 0.04288 RPN score loss: 0.02504 RPN total loss: 0.06792 Total loss: 2.38017 timestamp: 1655013012.8372939 iteration: 6690 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19509 FastRCNN class loss: 0.07285 FastRCNN total loss: 0.26794 L1 loss: 0.0000e+00 L2 loss: 1.77004 Learning rate: 0.02 Mask loss: 0.15265 RPN box loss: 0.05723 RPN score loss: 0.01267 RPN total loss: 0.06991 Total loss: 2.26054 timestamp: 1655013016.1223211 iteration: 6695 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25242 FastRCNN class loss: 0.13737 FastRCNN total loss: 0.38979 L1 loss: 0.0000e+00 L2 loss: 1.76971 Learning rate: 0.02 Mask loss: 0.31647 RPN box loss: 0.03976 RPN score loss: 0.00966 RPN total loss: 0.04942 Total loss: 2.52539 timestamp: 1655013019.4418006 iteration: 6700 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13823 FastRCNN class loss: 0.08836 FastRCNN total loss: 0.22659 L1 loss: 0.0000e+00 L2 loss: 1.76936 Learning rate: 0.02 Mask loss: 0.1909 RPN box loss: 0.05875 RPN score loss: 0.0062 RPN total loss: 0.06495 Total loss: 2.25181 timestamp: 1655013022.854117 iteration: 6705 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14332 FastRCNN class loss: 0.08029 FastRCNN total loss: 0.22361 L1 loss: 0.0000e+00 L2 loss: 1.76903 Learning rate: 0.02 Mask loss: 0.15433 RPN box loss: 0.03765 RPN score loss: 0.00525 RPN total loss: 0.0429 Total loss: 2.18987 timestamp: 1655013026.1210234 iteration: 6710 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14093 FastRCNN class loss: 0.07998 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 1.7687 Learning rate: 0.02 Mask loss: 0.22467 RPN box loss: 0.27499 RPN score loss: 0.01702 RPN total loss: 0.29201 Total loss: 2.5063 timestamp: 1655013029.4413762 iteration: 6715 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14098 FastRCNN class loss: 0.09037 FastRCNN total loss: 0.23135 L1 loss: 0.0000e+00 L2 loss: 1.76838 Learning rate: 0.02 Mask loss: 0.22799 RPN box loss: 0.06188 RPN score loss: 0.00885 RPN total loss: 0.07073 Total loss: 2.29845 timestamp: 1655013032.7805078 iteration: 6720 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18552 FastRCNN class loss: 0.11953 FastRCNN total loss: 0.30505 L1 loss: 0.0000e+00 L2 loss: 1.76804 Learning rate: 0.02 Mask loss: 0.18012 RPN box loss: 0.11476 RPN score loss: 0.00572 RPN total loss: 0.12048 Total loss: 2.3737 timestamp: 1655013036.1177292 iteration: 6725 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20518 FastRCNN class loss: 0.13305 FastRCNN total loss: 0.33824 L1 loss: 0.0000e+00 L2 loss: 1.7677 Learning rate: 0.02 Mask loss: 0.2608 RPN box loss: 0.04622 RPN score loss: 0.01017 RPN total loss: 0.05639 Total loss: 2.42314 timestamp: 1655013039.474443 iteration: 6730 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22215 FastRCNN class loss: 0.1542 FastRCNN total loss: 0.37635 L1 loss: 0.0000e+00 L2 loss: 1.76738 Learning rate: 0.02 Mask loss: 0.36489 RPN box loss: 0.05188 RPN score loss: 0.04631 RPN total loss: 0.09819 Total loss: 2.60681 timestamp: 1655013042.7381337 iteration: 6735 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18677 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.27003 L1 loss: 0.0000e+00 L2 loss: 1.76703 Learning rate: 0.02 Mask loss: 0.1504 RPN box loss: 0.05226 RPN score loss: 0.01299 RPN total loss: 0.06525 Total loss: 2.25271 timestamp: 1655013046.0652661 iteration: 6740 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16496 FastRCNN class loss: 0.09926 FastRCNN total loss: 0.26422 L1 loss: 0.0000e+00 L2 loss: 1.76671 Learning rate: 0.02 Mask loss: 0.27764 RPN box loss: 0.04136 RPN score loss: 0.02022 RPN total loss: 0.06158 Total loss: 2.37016 timestamp: 1655013049.4676304 iteration: 6745 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20202 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.26776 L1 loss: 0.0000e+00 L2 loss: 1.76639 Learning rate: 0.02 Mask loss: 0.14041 RPN box loss: 0.03721 RPN score loss: 0.00455 RPN total loss: 0.04176 Total loss: 2.21633 timestamp: 1655013052.7558007 iteration: 6750 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18581 FastRCNN class loss: 0.16564 FastRCNN total loss: 0.35144 L1 loss: 0.0000e+00 L2 loss: 1.76605 Learning rate: 0.02 Mask loss: 0.1789 RPN box loss: 0.02732 RPN score loss: 0.00632 RPN total loss: 0.03364 Total loss: 2.33003 timestamp: 1655013056.1767228 iteration: 6755 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19952 FastRCNN class loss: 0.12226 FastRCNN total loss: 0.32178 L1 loss: 0.0000e+00 L2 loss: 1.76571 Learning rate: 0.02 Mask loss: 0.19876 RPN box loss: 0.02752 RPN score loss: 0.02068 RPN total loss: 0.0482 Total loss: 2.33446 timestamp: 1655013059.5520802 iteration: 6760 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11859 FastRCNN class loss: 0.04224 FastRCNN total loss: 0.16082 L1 loss: 0.0000e+00 L2 loss: 1.76539 Learning rate: 0.02 Mask loss: 0.17505 RPN box loss: 0.04545 RPN score loss: 0.00184 RPN total loss: 0.04729 Total loss: 2.14855 timestamp: 1655013062.8145516 iteration: 6765 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15448 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.22286 L1 loss: 0.0000e+00 L2 loss: 1.76507 Learning rate: 0.02 Mask loss: 0.15661 RPN box loss: 0.0453 RPN score loss: 0.00901 RPN total loss: 0.05431 Total loss: 2.19885 timestamp: 1655013066.137579 iteration: 6770 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22063 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.30752 L1 loss: 0.0000e+00 L2 loss: 1.76474 Learning rate: 0.02 Mask loss: 0.18115 RPN box loss: 0.05113 RPN score loss: 0.00832 RPN total loss: 0.05946 Total loss: 2.31287 timestamp: 1655013069.3927815 iteration: 6775 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15081 FastRCNN class loss: 0.09931 FastRCNN total loss: 0.25012 L1 loss: 0.0000e+00 L2 loss: 1.76442 Learning rate: 0.02 Mask loss: 0.25217 RPN box loss: 0.0194 RPN score loss: 0.00664 RPN total loss: 0.02604 Total loss: 2.29274 timestamp: 1655013072.7535152 iteration: 6780 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07498 FastRCNN class loss: 0.05565 FastRCNN total loss: 0.13062 L1 loss: 0.0000e+00 L2 loss: 1.76409 Learning rate: 0.02 Mask loss: 0.24985 RPN box loss: 0.02784 RPN score loss: 0.01115 RPN total loss: 0.039 Total loss: 2.18356 timestamp: 1655013076.0395408 iteration: 6785 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10554 FastRCNN class loss: 0.10576 FastRCNN total loss: 0.2113 L1 loss: 0.0000e+00 L2 loss: 1.76375 Learning rate: 0.02 Mask loss: 0.12663 RPN box loss: 0.0176 RPN score loss: 0.00445 RPN total loss: 0.02205 Total loss: 2.12374 timestamp: 1655013079.2893412 iteration: 6790 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13957 FastRCNN class loss: 0.07431 FastRCNN total loss: 0.21388 L1 loss: 0.0000e+00 L2 loss: 1.76344 Learning rate: 0.02 Mask loss: 0.13906 RPN box loss: 0.01066 RPN score loss: 0.00792 RPN total loss: 0.01858 Total loss: 2.13496 timestamp: 1655013082.4884427 iteration: 6795 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19955 FastRCNN class loss: 0.11455 FastRCNN total loss: 0.3141 L1 loss: 0.0000e+00 L2 loss: 1.76311 Learning rate: 0.02 Mask loss: 0.18982 RPN box loss: 0.07949 RPN score loss: 0.01399 RPN total loss: 0.09349 Total loss: 2.36051 timestamp: 1655013085.7873137 iteration: 6800 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16753 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.24185 L1 loss: 0.0000e+00 L2 loss: 1.76277 Learning rate: 0.02 Mask loss: 0.21947 RPN box loss: 0.045 RPN score loss: 0.00502 RPN total loss: 0.05001 Total loss: 2.27411 timestamp: 1655013089.1406724 iteration: 6805 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.07022 FastRCNN total loss: 0.20298 L1 loss: 0.0000e+00 L2 loss: 1.76242 Learning rate: 0.02 Mask loss: 0.17681 RPN box loss: 0.05617 RPN score loss: 0.00704 RPN total loss: 0.06321 Total loss: 2.20542 timestamp: 1655013092.4531446 iteration: 6810 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11661 FastRCNN class loss: 0.05094 FastRCNN total loss: 0.16755 L1 loss: 0.0000e+00 L2 loss: 1.76208 Learning rate: 0.02 Mask loss: 0.19497 RPN box loss: 0.04271 RPN score loss: 0.00243 RPN total loss: 0.04514 Total loss: 2.16973 timestamp: 1655013095.7450407 iteration: 6815 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16986 FastRCNN class loss: 0.13626 FastRCNN total loss: 0.30612 L1 loss: 0.0000e+00 L2 loss: 1.76174 Learning rate: 0.02 Mask loss: 0.26475 RPN box loss: 0.02837 RPN score loss: 0.02113 RPN total loss: 0.04949 Total loss: 2.3821 timestamp: 1655013099.1021965 iteration: 6820 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22148 FastRCNN class loss: 0.11719 FastRCNN total loss: 0.33867 L1 loss: 0.0000e+00 L2 loss: 1.76144 Learning rate: 0.02 Mask loss: 0.16319 RPN box loss: 0.0141 RPN score loss: 0.00449 RPN total loss: 0.01859 Total loss: 2.2819 timestamp: 1655013102.4365454 iteration: 6825 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26036 FastRCNN class loss: 0.11187 FastRCNN total loss: 0.37223 L1 loss: 0.0000e+00 L2 loss: 1.76111 Learning rate: 0.02 Mask loss: 0.28858 RPN box loss: 0.041 RPN score loss: 0.00488 RPN total loss: 0.04588 Total loss: 2.4678 timestamp: 1655013105.7670965 iteration: 6830 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17783 FastRCNN class loss: 0.13993 FastRCNN total loss: 0.31776 L1 loss: 0.0000e+00 L2 loss: 1.76078 Learning rate: 0.02 Mask loss: 0.19005 RPN box loss: 0.03147 RPN score loss: 0.01368 RPN total loss: 0.04514 Total loss: 2.31373 timestamp: 1655013109.072672 iteration: 6835 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14077 FastRCNN class loss: 0.09866 FastRCNN total loss: 0.23944 L1 loss: 0.0000e+00 L2 loss: 1.76046 Learning rate: 0.02 Mask loss: 0.16632 RPN box loss: 0.06164 RPN score loss: 0.01372 RPN total loss: 0.07536 Total loss: 2.24158 timestamp: 1655013112.3835406 iteration: 6840 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14081 FastRCNN class loss: 0.08895 FastRCNN total loss: 0.22976 L1 loss: 0.0000e+00 L2 loss: 1.76013 Learning rate: 0.02 Mask loss: 0.31331 RPN box loss: 0.03945 RPN score loss: 0.01183 RPN total loss: 0.05129 Total loss: 2.35448 timestamp: 1655013115.6430926 iteration: 6845 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17146 FastRCNN class loss: 0.10103 FastRCNN total loss: 0.2725 L1 loss: 0.0000e+00 L2 loss: 1.75979 Learning rate: 0.02 Mask loss: 0.1902 RPN box loss: 0.02373 RPN score loss: 0.00517 RPN total loss: 0.0289 Total loss: 2.25139 timestamp: 1655013119.0086198 iteration: 6850 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14161 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.20009 L1 loss: 0.0000e+00 L2 loss: 1.75945 Learning rate: 0.02 Mask loss: 0.21155 RPN box loss: 0.00958 RPN score loss: 0.00773 RPN total loss: 0.01731 Total loss: 2.1884 timestamp: 1655013122.2473087 iteration: 6855 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11456 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.18101 L1 loss: 0.0000e+00 L2 loss: 1.75911 Learning rate: 0.02 Mask loss: 0.28642 RPN box loss: 0.02021 RPN score loss: 0.00747 RPN total loss: 0.02768 Total loss: 2.25422 timestamp: 1655013125.568818 iteration: 6860 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16778 FastRCNN class loss: 0.08945 FastRCNN total loss: 0.25723 L1 loss: 0.0000e+00 L2 loss: 1.75877 Learning rate: 0.02 Mask loss: 0.17614 RPN box loss: 0.03435 RPN score loss: 0.00421 RPN total loss: 0.03856 Total loss: 2.2307 timestamp: 1655013128.826219 iteration: 6865 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24821 FastRCNN class loss: 0.13145 FastRCNN total loss: 0.37967 L1 loss: 0.0000e+00 L2 loss: 1.75846 Learning rate: 0.02 Mask loss: 0.27508 RPN box loss: 0.01967 RPN score loss: 0.03804 RPN total loss: 0.05772 Total loss: 2.47092 timestamp: 1655013132.1741352 iteration: 6870 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18871 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.26252 L1 loss: 0.0000e+00 L2 loss: 1.75815 Learning rate: 0.02 Mask loss: 0.25601 RPN box loss: 0.03385 RPN score loss: 0.00951 RPN total loss: 0.04336 Total loss: 2.32004 timestamp: 1655013135.4726574 iteration: 6875 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15563 FastRCNN class loss: 0.07725 FastRCNN total loss: 0.23288 L1 loss: 0.0000e+00 L2 loss: 1.75783 Learning rate: 0.02 Mask loss: 0.19042 RPN box loss: 0.07191 RPN score loss: 0.00226 RPN total loss: 0.07416 Total loss: 2.25529 timestamp: 1655013138.7888527 iteration: 6880 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19776 FastRCNN class loss: 0.12832 FastRCNN total loss: 0.32608 L1 loss: 0.0000e+00 L2 loss: 1.7575 Learning rate: 0.02 Mask loss: 0.21236 RPN box loss: 0.03848 RPN score loss: 0.01541 RPN total loss: 0.05389 Total loss: 2.34982 timestamp: 1655013142.0793037 iteration: 6885 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16483 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.24001 L1 loss: 0.0000e+00 L2 loss: 1.75718 Learning rate: 0.02 Mask loss: 0.17702 RPN box loss: 0.04186 RPN score loss: 0.00907 RPN total loss: 0.05093 Total loss: 2.22513 timestamp: 1655013145.399618 iteration: 6890 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19286 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.28857 L1 loss: 0.0000e+00 L2 loss: 1.75685 Learning rate: 0.02 Mask loss: 0.26452 RPN box loss: 0.06546 RPN score loss: 0.01396 RPN total loss: 0.07942 Total loss: 2.38935 timestamp: 1655013148.7625594 iteration: 6895 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20118 FastRCNN class loss: 0.09846 FastRCNN total loss: 0.29964 L1 loss: 0.0000e+00 L2 loss: 1.75651 Learning rate: 0.02 Mask loss: 0.29977 RPN box loss: 0.15301 RPN score loss: 0.0135 RPN total loss: 0.16652 Total loss: 2.52244 timestamp: 1655013152.0356114 iteration: 6900 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17092 FastRCNN class loss: 0.07693 FastRCNN total loss: 0.24786 L1 loss: 0.0000e+00 L2 loss: 1.75619 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.06749 RPN score loss: 0.02403 RPN total loss: 0.09152 Total loss: 2.29542 timestamp: 1655013155.3959002 iteration: 6905 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17907 FastRCNN class loss: 0.12253 FastRCNN total loss: 0.30159 L1 loss: 0.0000e+00 L2 loss: 1.75585 Learning rate: 0.02 Mask loss: 0.23088 RPN box loss: 0.02075 RPN score loss: 0.00503 RPN total loss: 0.02578 Total loss: 2.3141 timestamp: 1655013158.6301525 iteration: 6910 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25169 FastRCNN class loss: 0.14673 FastRCNN total loss: 0.39842 L1 loss: 0.0000e+00 L2 loss: 1.75552 Learning rate: 0.02 Mask loss: 0.22542 RPN box loss: 0.01292 RPN score loss: 0.00406 RPN total loss: 0.01699 Total loss: 2.39635 timestamp: 1655013162.0264704 iteration: 6915 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27334 FastRCNN class loss: 0.14649 FastRCNN total loss: 0.41983 L1 loss: 0.0000e+00 L2 loss: 1.75518 Learning rate: 0.02 Mask loss: 0.29218 RPN box loss: 0.04897 RPN score loss: 0.01533 RPN total loss: 0.0643 Total loss: 2.53149 timestamp: 1655013165.3467507 iteration: 6920 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22279 FastRCNN class loss: 0.08669 FastRCNN total loss: 0.30948 L1 loss: 0.0000e+00 L2 loss: 1.75485 Learning rate: 0.02 Mask loss: 0.21224 RPN box loss: 0.0228 RPN score loss: 0.0089 RPN total loss: 0.0317 Total loss: 2.30828 timestamp: 1655013168.7034318 iteration: 6925 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25546 FastRCNN class loss: 0.081 FastRCNN total loss: 0.33647 L1 loss: 0.0000e+00 L2 loss: 1.75454 Learning rate: 0.02 Mask loss: 0.25766 RPN box loss: 0.01911 RPN score loss: 0.00821 RPN total loss: 0.02732 Total loss: 2.37598 timestamp: 1655013172.0376923 iteration: 6930 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32585 FastRCNN class loss: 0.16048 FastRCNN total loss: 0.48632 L1 loss: 0.0000e+00 L2 loss: 1.75421 Learning rate: 0.02 Mask loss: 0.27367 RPN box loss: 0.03484 RPN score loss: 0.00682 RPN total loss: 0.04166 Total loss: 2.55587 timestamp: 1655013175.3783555 iteration: 6935 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14804 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.20721 L1 loss: 0.0000e+00 L2 loss: 1.75389 Learning rate: 0.02 Mask loss: 0.16197 RPN box loss: 0.01732 RPN score loss: 0.00526 RPN total loss: 0.02258 Total loss: 2.14565 timestamp: 1655013178.7032926 iteration: 6940 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18845 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.27085 L1 loss: 0.0000e+00 L2 loss: 1.75357 Learning rate: 0.02 Mask loss: 0.20086 RPN box loss: 0.06038 RPN score loss: 0.01627 RPN total loss: 0.07666 Total loss: 2.30194 timestamp: 1655013182.0728707 iteration: 6945 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20005 FastRCNN class loss: 0.10183 FastRCNN total loss: 0.30188 L1 loss: 0.0000e+00 L2 loss: 1.75323 Learning rate: 0.02 Mask loss: 0.30683 RPN box loss: 0.06115 RPN score loss: 0.01688 RPN total loss: 0.07803 Total loss: 2.43997 timestamp: 1655013185.3695238 iteration: 6950 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23664 FastRCNN class loss: 0.13404 FastRCNN total loss: 0.37068 L1 loss: 0.0000e+00 L2 loss: 1.75291 Learning rate: 0.02 Mask loss: 0.26243 RPN box loss: 0.0313 RPN score loss: 0.00692 RPN total loss: 0.03822 Total loss: 2.42424 timestamp: 1655013188.6713138 iteration: 6955 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12923 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 1.7526 Learning rate: 0.02 Mask loss: 0.22487 RPN box loss: 0.02289 RPN score loss: 0.01284 RPN total loss: 0.03573 Total loss: 2.22029 timestamp: 1655013191.9689548 iteration: 6960 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28824 FastRCNN class loss: 0.09872 FastRCNN total loss: 0.38696 L1 loss: 0.0000e+00 L2 loss: 1.75226 Learning rate: 0.02 Mask loss: 0.17114 RPN box loss: 0.02538 RPN score loss: 0.00959 RPN total loss: 0.03497 Total loss: 2.34533 timestamp: 1655013195.2286134 iteration: 6965 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26328 FastRCNN class loss: 0.1046 FastRCNN total loss: 0.36788 L1 loss: 0.0000e+00 L2 loss: 1.75194 Learning rate: 0.02 Mask loss: 0.18121 RPN box loss: 0.11384 RPN score loss: 0.01345 RPN total loss: 0.12729 Total loss: 2.42833 timestamp: 1655013198.55734 iteration: 6970 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2373 FastRCNN class loss: 0.15131 FastRCNN total loss: 0.38861 L1 loss: 0.0000e+00 L2 loss: 1.75161 Learning rate: 0.02 Mask loss: 0.24291 RPN box loss: 0.03006 RPN score loss: 0.00774 RPN total loss: 0.0378 Total loss: 2.42093 timestamp: 1655013201.9514034 iteration: 6975 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18908 FastRCNN class loss: 0.11209 FastRCNN total loss: 0.30117 L1 loss: 0.0000e+00 L2 loss: 1.75129 Learning rate: 0.02 Mask loss: 0.30376 RPN box loss: 0.09246 RPN score loss: 0.00834 RPN total loss: 0.1008 Total loss: 2.45702 timestamp: 1655013205.2710643 iteration: 6980 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22118 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.30287 L1 loss: 0.0000e+00 L2 loss: 1.75098 Learning rate: 0.02 Mask loss: 0.18143 RPN box loss: 0.05261 RPN score loss: 0.0116 RPN total loss: 0.06421 Total loss: 2.29948 timestamp: 1655013208.4977958 iteration: 6985 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19755 FastRCNN class loss: 0.09353 FastRCNN total loss: 0.29108 L1 loss: 0.0000e+00 L2 loss: 1.75063 Learning rate: 0.02 Mask loss: 0.22991 RPN box loss: 0.03538 RPN score loss: 0.00994 RPN total loss: 0.04532 Total loss: 2.31695 timestamp: 1655013211.8327582 iteration: 6990 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12441 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.18935 L1 loss: 0.0000e+00 L2 loss: 1.7503 Learning rate: 0.02 Mask loss: 0.18604 RPN box loss: 0.04463 RPN score loss: 0.00694 RPN total loss: 0.05157 Total loss: 2.17726 timestamp: 1655013215.0687256 iteration: 6995 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24674 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.32075 L1 loss: 0.0000e+00 L2 loss: 1.75 Learning rate: 0.02 Mask loss: 0.17637 RPN box loss: 0.04994 RPN score loss: 0.00996 RPN total loss: 0.0599 Total loss: 2.30702 timestamp: 1655013218.3737493 iteration: 7000 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21777 FastRCNN class loss: 0.14265 FastRCNN total loss: 0.36042 L1 loss: 0.0000e+00 L2 loss: 1.74969 Learning rate: 0.02 Mask loss: 0.24916 RPN box loss: 0.04208 RPN score loss: 0.01294 RPN total loss: 0.05502 Total loss: 2.41429 timestamp: 1655013221.695488 iteration: 7005 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18444 FastRCNN class loss: 0.08638 FastRCNN total loss: 0.27082 L1 loss: 0.0000e+00 L2 loss: 1.74937 Learning rate: 0.02 Mask loss: 0.19258 RPN box loss: 0.04001 RPN score loss: 0.00957 RPN total loss: 0.04958 Total loss: 2.26234 timestamp: 1655013225.0411913 iteration: 7010 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16706 FastRCNN class loss: 0.1102 FastRCNN total loss: 0.27726 L1 loss: 0.0000e+00 L2 loss: 1.74904 Learning rate: 0.02 Mask loss: 0.17248 RPN box loss: 0.05837 RPN score loss: 0.00577 RPN total loss: 0.06413 Total loss: 2.26292 timestamp: 1655013228.288792 iteration: 7015 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20791 FastRCNN class loss: 0.0818 FastRCNN total loss: 0.28971 L1 loss: 0.0000e+00 L2 loss: 1.74871 Learning rate: 0.02 Mask loss: 0.15862 RPN box loss: 0.03371 RPN score loss: 0.01046 RPN total loss: 0.04417 Total loss: 2.24121 timestamp: 1655013231.6309273 iteration: 7020 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13443 FastRCNN class loss: 0.08619 FastRCNN total loss: 0.22063 L1 loss: 0.0000e+00 L2 loss: 1.74839 Learning rate: 0.02 Mask loss: 0.19034 RPN box loss: 0.08321 RPN score loss: 0.00775 RPN total loss: 0.09096 Total loss: 2.25031 timestamp: 1655013235.0080643 iteration: 7025 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14136 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.21555 L1 loss: 0.0000e+00 L2 loss: 1.74807 Learning rate: 0.02 Mask loss: 0.12968 RPN box loss: 0.02259 RPN score loss: 0.00347 RPN total loss: 0.02606 Total loss: 2.11936 timestamp: 1655013238.3620946 iteration: 7030 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.32915 L1 loss: 0.0000e+00 L2 loss: 1.74771 Learning rate: 0.02 Mask loss: 0.20925 RPN box loss: 0.04313 RPN score loss: 0.00701 RPN total loss: 0.05015 Total loss: 2.33626 timestamp: 1655013241.7643096 iteration: 7035 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25537 FastRCNN class loss: 0.17557 FastRCNN total loss: 0.43094 L1 loss: 0.0000e+00 L2 loss: 1.7474 Learning rate: 0.02 Mask loss: 0.27544 RPN box loss: 0.05694 RPN score loss: 0.00985 RPN total loss: 0.06678 Total loss: 2.52057 timestamp: 1655013245.0052435 iteration: 7040 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25536 FastRCNN class loss: 0.07409 FastRCNN total loss: 0.32945 L1 loss: 0.0000e+00 L2 loss: 1.74708 Learning rate: 0.02 Mask loss: 0.18829 RPN box loss: 0.06398 RPN score loss: 0.01978 RPN total loss: 0.08376 Total loss: 2.34857 timestamp: 1655013248.3094938 iteration: 7045 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24611 FastRCNN class loss: 0.13549 FastRCNN total loss: 0.38161 L1 loss: 0.0000e+00 L2 loss: 1.74675 Learning rate: 0.02 Mask loss: 0.36863 RPN box loss: 0.01427 RPN score loss: 0.03057 RPN total loss: 0.04484 Total loss: 2.54182 timestamp: 1655013251.566252 iteration: 7050 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2458 FastRCNN class loss: 0.09777 FastRCNN total loss: 0.34357 L1 loss: 0.0000e+00 L2 loss: 1.74641 Learning rate: 0.02 Mask loss: 0.26089 RPN box loss: 0.03408 RPN score loss: 0.01278 RPN total loss: 0.04685 Total loss: 2.39771 timestamp: 1655013254.87326 iteration: 7055 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14438 FastRCNN class loss: 0.07051 FastRCNN total loss: 0.21489 L1 loss: 0.0000e+00 L2 loss: 1.74608 Learning rate: 0.02 Mask loss: 0.14264 RPN box loss: 0.06935 RPN score loss: 0.01428 RPN total loss: 0.08363 Total loss: 2.18724 timestamp: 1655013258.243587 iteration: 7060 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16099 FastRCNN class loss: 0.11493 FastRCNN total loss: 0.27592 L1 loss: 0.0000e+00 L2 loss: 1.74576 Learning rate: 0.02 Mask loss: 0.23459 RPN box loss: 0.05336 RPN score loss: 0.01742 RPN total loss: 0.07078 Total loss: 2.32705 timestamp: 1655013261.5692515 iteration: 7065 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14967 FastRCNN class loss: 0.10283 FastRCNN total loss: 0.2525 L1 loss: 0.0000e+00 L2 loss: 1.74543 Learning rate: 0.02 Mask loss: 0.20452 RPN box loss: 0.03206 RPN score loss: 0.01026 RPN total loss: 0.04233 Total loss: 2.24477 timestamp: 1655013264.822398 iteration: 7070 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1912 FastRCNN class loss: 0.11915 FastRCNN total loss: 0.31035 L1 loss: 0.0000e+00 L2 loss: 1.74511 Learning rate: 0.02 Mask loss: 0.25751 RPN box loss: 0.03255 RPN score loss: 0.00514 RPN total loss: 0.03769 Total loss: 2.35066 timestamp: 1655013268.0599825 iteration: 7075 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.22323 L1 loss: 0.0000e+00 L2 loss: 1.74476 Learning rate: 0.02 Mask loss: 0.24089 RPN box loss: 0.04755 RPN score loss: 0.00541 RPN total loss: 0.05297 Total loss: 2.26184 timestamp: 1655013271.3909051 iteration: 7080 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22996 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.32661 L1 loss: 0.0000e+00 L2 loss: 1.74444 Learning rate: 0.02 Mask loss: 0.25658 RPN box loss: 0.01177 RPN score loss: 0.00538 RPN total loss: 0.01716 Total loss: 2.34478 timestamp: 1655013274.6838026 iteration: 7085 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25524 FastRCNN class loss: 0.18409 FastRCNN total loss: 0.43933 L1 loss: 0.0000e+00 L2 loss: 1.74413 Learning rate: 0.02 Mask loss: 0.24051 RPN box loss: 0.05017 RPN score loss: 0.01293 RPN total loss: 0.0631 Total loss: 2.48707 timestamp: 1655013278.0062048 iteration: 7090 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22145 FastRCNN class loss: 0.1052 FastRCNN total loss: 0.32665 L1 loss: 0.0000e+00 L2 loss: 1.74379 Learning rate: 0.02 Mask loss: 0.18497 RPN box loss: 0.05644 RPN score loss: 0.01 RPN total loss: 0.06644 Total loss: 2.32185 timestamp: 1655013281.2264588 iteration: 7095 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15297 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.24235 L1 loss: 0.0000e+00 L2 loss: 1.74348 Learning rate: 0.02 Mask loss: 0.18055 RPN box loss: 0.05425 RPN score loss: 0.0127 RPN total loss: 0.06695 Total loss: 2.23334 timestamp: 1655013284.5088987 iteration: 7100 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18298 FastRCNN class loss: 0.10329 FastRCNN total loss: 0.28627 L1 loss: 0.0000e+00 L2 loss: 1.74315 Learning rate: 0.02 Mask loss: 0.26689 RPN box loss: 0.06381 RPN score loss: 0.0227 RPN total loss: 0.08652 Total loss: 2.38283 timestamp: 1655013287.7908592 iteration: 7105 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10848 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.16627 L1 loss: 0.0000e+00 L2 loss: 1.74282 Learning rate: 0.02 Mask loss: 0.19138 RPN box loss: 0.02831 RPN score loss: 0.00538 RPN total loss: 0.03369 Total loss: 2.13417 timestamp: 1655013291.068092 iteration: 7110 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11452 FastRCNN class loss: 0.03943 FastRCNN total loss: 0.15395 L1 loss: 0.0000e+00 L2 loss: 1.7425 Learning rate: 0.02 Mask loss: 0.17233 RPN box loss: 0.0045 RPN score loss: 0.00836 RPN total loss: 0.01285 Total loss: 2.08163 timestamp: 1655013294.3398452 iteration: 7115 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25617 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.3269 L1 loss: 0.0000e+00 L2 loss: 1.74217 Learning rate: 0.02 Mask loss: 0.16328 RPN box loss: 0.04636 RPN score loss: 0.00578 RPN total loss: 0.05213 Total loss: 2.28449 timestamp: 1655013297.6133378 iteration: 7120 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17696 FastRCNN class loss: 0.11089 FastRCNN total loss: 0.28786 L1 loss: 0.0000e+00 L2 loss: 1.74185 Learning rate: 0.02 Mask loss: 0.17619 RPN box loss: 0.0563 RPN score loss: 0.01338 RPN total loss: 0.06967 Total loss: 2.27558 timestamp: 1655013300.888048 iteration: 7125 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19912 FastRCNN class loss: 0.09832 FastRCNN total loss: 0.29744 L1 loss: 0.0000e+00 L2 loss: 1.74151 Learning rate: 0.02 Mask loss: 0.2046 RPN box loss: 0.03074 RPN score loss: 0.00762 RPN total loss: 0.03835 Total loss: 2.28189 timestamp: 1655013304.1811337 iteration: 7130 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18626 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.26733 L1 loss: 0.0000e+00 L2 loss: 1.74118 Learning rate: 0.02 Mask loss: 0.20584 RPN box loss: 0.02523 RPN score loss: 0.00944 RPN total loss: 0.03466 Total loss: 2.24901 timestamp: 1655013307.5553408 iteration: 7135 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18202 FastRCNN class loss: 0.13754 FastRCNN total loss: 0.31956 L1 loss: 0.0000e+00 L2 loss: 1.74086 Learning rate: 0.02 Mask loss: 0.17962 RPN box loss: 0.12105 RPN score loss: 0.0168 RPN total loss: 0.13785 Total loss: 2.37788 timestamp: 1655013310.8441396 iteration: 7140 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19716 FastRCNN class loss: 0.08831 FastRCNN total loss: 0.28547 L1 loss: 0.0000e+00 L2 loss: 1.74054 Learning rate: 0.02 Mask loss: 0.18436 RPN box loss: 0.04599 RPN score loss: 0.00784 RPN total loss: 0.05383 Total loss: 2.2642 timestamp: 1655013314.1919444 iteration: 7145 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22762 FastRCNN class loss: 0.12388 FastRCNN total loss: 0.3515 L1 loss: 0.0000e+00 L2 loss: 1.74022 Learning rate: 0.02 Mask loss: 0.23897 RPN box loss: 0.06978 RPN score loss: 0.01195 RPN total loss: 0.08173 Total loss: 2.41242 timestamp: 1655013317.4549468 iteration: 7150 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16708 FastRCNN class loss: 0.09982 FastRCNN total loss: 0.26691 L1 loss: 0.0000e+00 L2 loss: 1.73991 Learning rate: 0.02 Mask loss: 0.21825 RPN box loss: 0.03814 RPN score loss: 0.00629 RPN total loss: 0.04444 Total loss: 2.2695 timestamp: 1655013320.7657874 iteration: 7155 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18407 FastRCNN class loss: 0.10958 FastRCNN total loss: 0.29364 L1 loss: 0.0000e+00 L2 loss: 1.73959 Learning rate: 0.02 Mask loss: 0.22661 RPN box loss: 0.02022 RPN score loss: 0.00716 RPN total loss: 0.02739 Total loss: 2.28724 timestamp: 1655013324.0558188 iteration: 7160 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22659 FastRCNN class loss: 0.17398 FastRCNN total loss: 0.40057 L1 loss: 0.0000e+00 L2 loss: 1.73928 Learning rate: 0.02 Mask loss: 0.26483 RPN box loss: 0.03695 RPN score loss: 0.03163 RPN total loss: 0.06858 Total loss: 2.47326 timestamp: 1655013327.38016 iteration: 7165 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22287 FastRCNN class loss: 0.0963 FastRCNN total loss: 0.31917 L1 loss: 0.0000e+00 L2 loss: 1.73895 Learning rate: 0.02 Mask loss: 0.21265 RPN box loss: 0.03779 RPN score loss: 0.01226 RPN total loss: 0.05006 Total loss: 2.32082 timestamp: 1655013330.7335181 iteration: 7170 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31683 FastRCNN class loss: 0.14855 FastRCNN total loss: 0.46538 L1 loss: 0.0000e+00 L2 loss: 1.73861 Learning rate: 0.02 Mask loss: 0.2686 RPN box loss: 0.02087 RPN score loss: 0.00511 RPN total loss: 0.02597 Total loss: 2.49856 timestamp: 1655013333.9924903 iteration: 7175 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22639 FastRCNN class loss: 0.1251 FastRCNN total loss: 0.35149 L1 loss: 0.0000e+00 L2 loss: 1.73828 Learning rate: 0.02 Mask loss: 0.20601 RPN box loss: 0.0468 RPN score loss: 0.01124 RPN total loss: 0.05804 Total loss: 2.35382 timestamp: 1655013337.2672594 iteration: 7180 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.187 FastRCNN class loss: 0.15406 FastRCNN total loss: 0.34106 L1 loss: 0.0000e+00 L2 loss: 1.73796 Learning rate: 0.02 Mask loss: 0.1776 RPN box loss: 0.0455 RPN score loss: 0.00592 RPN total loss: 0.05143 Total loss: 2.30805 timestamp: 1655013340.5450227 iteration: 7185 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21401 FastRCNN class loss: 0.14616 FastRCNN total loss: 0.36017 L1 loss: 0.0000e+00 L2 loss: 1.73762 Learning rate: 0.02 Mask loss: 0.23384 RPN box loss: 0.02739 RPN score loss: 0.00777 RPN total loss: 0.03517 Total loss: 2.3668 timestamp: 1655013343.753363 iteration: 7190 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1556 FastRCNN class loss: 0.13017 FastRCNN total loss: 0.28577 L1 loss: 0.0000e+00 L2 loss: 1.7373 Learning rate: 0.02 Mask loss: 0.21993 RPN box loss: 0.01142 RPN score loss: 0.0037 RPN total loss: 0.01511 Total loss: 2.25811 timestamp: 1655013347.021296 iteration: 7195 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18264 FastRCNN class loss: 0.1031 FastRCNN total loss: 0.28573 L1 loss: 0.0000e+00 L2 loss: 1.73698 Learning rate: 0.02 Mask loss: 0.29274 RPN box loss: 0.02744 RPN score loss: 0.00835 RPN total loss: 0.0358 Total loss: 2.35124 timestamp: 1655013350.358783 iteration: 7200 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15689 FastRCNN class loss: 0.13196 FastRCNN total loss: 0.28885 L1 loss: 0.0000e+00 L2 loss: 1.73666 Learning rate: 0.02 Mask loss: 0.30889 RPN box loss: 0.06278 RPN score loss: 0.00731 RPN total loss: 0.07009 Total loss: 2.40449 timestamp: 1655013353.6644497 iteration: 7205 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20437 FastRCNN class loss: 0.16726 FastRCNN total loss: 0.37163 L1 loss: 0.0000e+00 L2 loss: 1.73636 Learning rate: 0.02 Mask loss: 0.15808 RPN box loss: 0.02103 RPN score loss: 0.00328 RPN total loss: 0.02432 Total loss: 2.29039 timestamp: 1655013356.9052641 iteration: 7210 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2405 FastRCNN class loss: 0.17661 FastRCNN total loss: 0.4171 L1 loss: 0.0000e+00 L2 loss: 1.73604 Learning rate: 0.02 Mask loss: 0.39287 RPN box loss: 0.04532 RPN score loss: 0.00345 RPN total loss: 0.04877 Total loss: 2.59478 timestamp: 1655013360.1438894 iteration: 7215 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21479 FastRCNN class loss: 0.12619 FastRCNN total loss: 0.34099 L1 loss: 0.0000e+00 L2 loss: 1.73571 Learning rate: 0.02 Mask loss: 0.23774 RPN box loss: 0.08965 RPN score loss: 0.02482 RPN total loss: 0.11448 Total loss: 2.42891 timestamp: 1655013363.4533308 iteration: 7220 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14355 FastRCNN class loss: 0.09982 FastRCNN total loss: 0.24336 L1 loss: 0.0000e+00 L2 loss: 1.73537 Learning rate: 0.02 Mask loss: 0.46996 RPN box loss: 0.03484 RPN score loss: 0.00786 RPN total loss: 0.04269 Total loss: 2.49139 timestamp: 1655013366.6888602 iteration: 7225 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22725 FastRCNN class loss: 0.10742 FastRCNN total loss: 0.33466 L1 loss: 0.0000e+00 L2 loss: 1.73502 Learning rate: 0.02 Mask loss: 0.18398 RPN box loss: 0.02274 RPN score loss: 0.00473 RPN total loss: 0.02747 Total loss: 2.28113 timestamp: 1655013370.0852866 iteration: 7230 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20467 FastRCNN class loss: 0.13237 FastRCNN total loss: 0.33704 L1 loss: 0.0000e+00 L2 loss: 1.73471 Learning rate: 0.02 Mask loss: 0.35251 RPN box loss: 0.03578 RPN score loss: 0.00705 RPN total loss: 0.04283 Total loss: 2.46709 timestamp: 1655013373.3803546 iteration: 7235 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19077 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.27436 L1 loss: 0.0000e+00 L2 loss: 1.73439 Learning rate: 0.02 Mask loss: 0.18977 RPN box loss: 0.03397 RPN score loss: 0.00794 RPN total loss: 0.04191 Total loss: 2.24044 timestamp: 1655013376.649712 iteration: 7240 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22954 FastRCNN class loss: 0.22442 FastRCNN total loss: 0.45396 L1 loss: 0.0000e+00 L2 loss: 1.73407 Learning rate: 0.02 Mask loss: 0.2877 RPN box loss: 0.04039 RPN score loss: 0.01746 RPN total loss: 0.05785 Total loss: 2.53357 timestamp: 1655013379.9072232 iteration: 7245 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19026 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.28911 L1 loss: 0.0000e+00 L2 loss: 1.73375 Learning rate: 0.02 Mask loss: 0.18598 RPN box loss: 0.03732 RPN score loss: 0.01368 RPN total loss: 0.051 Total loss: 2.25984 timestamp: 1655013383.2718275 iteration: 7250 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2094 FastRCNN class loss: 0.0939 FastRCNN total loss: 0.3033 L1 loss: 0.0000e+00 L2 loss: 1.73342 Learning rate: 0.02 Mask loss: 0.20569 RPN box loss: 0.03901 RPN score loss: 0.00608 RPN total loss: 0.04509 Total loss: 2.2875 timestamp: 1655013386.5323477 iteration: 7255 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16332 FastRCNN class loss: 0.14867 FastRCNN total loss: 0.312 L1 loss: 0.0000e+00 L2 loss: 1.7331 Learning rate: 0.02 Mask loss: 0.20999 RPN box loss: 0.03044 RPN score loss: 0.009 RPN total loss: 0.03944 Total loss: 2.29453 timestamp: 1655013389.8047564 iteration: 7260 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22669 FastRCNN class loss: 0.13529 FastRCNN total loss: 0.36198 L1 loss: 0.0000e+00 L2 loss: 1.73278 Learning rate: 0.02 Mask loss: 0.2488 RPN box loss: 0.08222 RPN score loss: 0.01077 RPN total loss: 0.09299 Total loss: 2.43655 timestamp: 1655013393.0214093 iteration: 7265 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18466 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.252 L1 loss: 0.0000e+00 L2 loss: 1.73246 Learning rate: 0.02 Mask loss: 0.12939 RPN box loss: 0.03051 RPN score loss: 0.00472 RPN total loss: 0.03523 Total loss: 2.14909 timestamp: 1655013396.2835128 iteration: 7270 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16094 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.25688 L1 loss: 0.0000e+00 L2 loss: 1.73215 Learning rate: 0.02 Mask loss: 0.22422 RPN box loss: 0.02433 RPN score loss: 0.00682 RPN total loss: 0.03116 Total loss: 2.24442 timestamp: 1655013399.6102955 iteration: 7275 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12784 FastRCNN class loss: 0.12666 FastRCNN total loss: 0.2545 L1 loss: 0.0000e+00 L2 loss: 1.73182 Learning rate: 0.02 Mask loss: 0.23865 RPN box loss: 0.02307 RPN score loss: 0.00452 RPN total loss: 0.02758 Total loss: 2.25255 timestamp: 1655013402.9809382 iteration: 7280 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16906 FastRCNN class loss: 0.11104 FastRCNN total loss: 0.28009 L1 loss: 0.0000e+00 L2 loss: 1.73149 Learning rate: 0.02 Mask loss: 0.19732 RPN box loss: 0.08457 RPN score loss: 0.01757 RPN total loss: 0.10214 Total loss: 2.31105 timestamp: 1655013406.2000327 iteration: 7285 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.08514 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 1.73117 Learning rate: 0.02 Mask loss: 0.1679 RPN box loss: 0.01886 RPN score loss: 0.00296 RPN total loss: 0.02182 Total loss: 2.17964 timestamp: 1655013409.4833615 iteration: 7290 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19103 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.26624 L1 loss: 0.0000e+00 L2 loss: 1.73086 Learning rate: 0.02 Mask loss: 0.16422 RPN box loss: 0.05442 RPN score loss: 0.00551 RPN total loss: 0.05993 Total loss: 2.22124 timestamp: 1655013412.765628 iteration: 7295 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18014 FastRCNN class loss: 0.0926 FastRCNN total loss: 0.27274 L1 loss: 0.0000e+00 L2 loss: 1.73053 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.04913 RPN score loss: 0.01492 RPN total loss: 0.06405 Total loss: 2.23398 timestamp: 1655013416.0097682 iteration: 7300 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36716 FastRCNN class loss: 0.10842 FastRCNN total loss: 0.47558 L1 loss: 0.0000e+00 L2 loss: 1.7302 Learning rate: 0.02 Mask loss: 0.21711 RPN box loss: 0.08176 RPN score loss: 0.01499 RPN total loss: 0.09675 Total loss: 2.51963 timestamp: 1655013419.2788215 iteration: 7305 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19765 FastRCNN class loss: 0.08993 FastRCNN total loss: 0.28758 L1 loss: 0.0000e+00 L2 loss: 1.72985 Learning rate: 0.02 Mask loss: 0.18522 RPN box loss: 0.05375 RPN score loss: 0.00618 RPN total loss: 0.05993 Total loss: 2.26257 timestamp: 1655013422.6631415 iteration: 7310 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21658 FastRCNN class loss: 0.08092 FastRCNN total loss: 0.2975 L1 loss: 0.0000e+00 L2 loss: 1.72953 Learning rate: 0.02 Mask loss: 0.17073 RPN box loss: 0.04048 RPN score loss: 0.00563 RPN total loss: 0.04611 Total loss: 2.24386 timestamp: 1655013425.999273 iteration: 7315 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2664 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.34846 L1 loss: 0.0000e+00 L2 loss: 1.72923 Learning rate: 0.02 Mask loss: 0.1936 RPN box loss: 0.02029 RPN score loss: 0.00722 RPN total loss: 0.02751 Total loss: 2.2988 timestamp: 1655013429.3620825 iteration: 7320 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23281 FastRCNN class loss: 0.13174 FastRCNN total loss: 0.36455 L1 loss: 0.0000e+00 L2 loss: 1.7289 Learning rate: 0.02 Mask loss: 0.26087 RPN box loss: 0.0453 RPN score loss: 0.01607 RPN total loss: 0.06136 Total loss: 2.41569 timestamp: 1655013432.653291 iteration: 7325 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17799 FastRCNN class loss: 0.09562 FastRCNN total loss: 0.27361 L1 loss: 0.0000e+00 L2 loss: 1.72858 Learning rate: 0.02 Mask loss: 0.19253 RPN box loss: 0.04063 RPN score loss: 0.01307 RPN total loss: 0.0537 Total loss: 2.24842 timestamp: 1655013435.9229274 iteration: 7330 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24262 FastRCNN class loss: 0.16932 FastRCNN total loss: 0.41194 L1 loss: 0.0000e+00 L2 loss: 1.72826 Learning rate: 0.02 Mask loss: 0.23747 RPN box loss: 0.05881 RPN score loss: 0.02643 RPN total loss: 0.08524 Total loss: 2.46291 timestamp: 1655013439.3760247 iteration: 7335 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16422 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.25067 L1 loss: 0.0000e+00 L2 loss: 1.72794 Learning rate: 0.02 Mask loss: 0.23272 RPN box loss: 0.01188 RPN score loss: 0.0126 RPN total loss: 0.02449 Total loss: 2.23582 timestamp: 1655013442.610206 iteration: 7340 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19467 FastRCNN class loss: 0.07511 FastRCNN total loss: 0.26978 L1 loss: 0.0000e+00 L2 loss: 1.72761 Learning rate: 0.02 Mask loss: 0.19973 RPN box loss: 0.054 RPN score loss: 0.00935 RPN total loss: 0.06335 Total loss: 2.26048 timestamp: 1655013445.8380384 iteration: 7345 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17001 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.24196 L1 loss: 0.0000e+00 L2 loss: 1.72729 Learning rate: 0.02 Mask loss: 0.21186 RPN box loss: 0.04769 RPN score loss: 0.00975 RPN total loss: 0.05744 Total loss: 2.23856 timestamp: 1655013449.1042151 iteration: 7350 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23438 FastRCNN class loss: 0.11095 FastRCNN total loss: 0.34533 L1 loss: 0.0000e+00 L2 loss: 1.72697 Learning rate: 0.02 Mask loss: 0.2397 RPN box loss: 0.04996 RPN score loss: 0.01232 RPN total loss: 0.06228 Total loss: 2.37428 timestamp: 1655013452.371037 iteration: 7355 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27449 FastRCNN class loss: 0.11262 FastRCNN total loss: 0.38711 L1 loss: 0.0000e+00 L2 loss: 1.72666 Learning rate: 0.02 Mask loss: 0.27379 RPN box loss: 0.02779 RPN score loss: 0.01017 RPN total loss: 0.03796 Total loss: 2.42552 timestamp: 1655013455.6058226 iteration: 7360 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2576 FastRCNN class loss: 0.15578 FastRCNN total loss: 0.41338 L1 loss: 0.0000e+00 L2 loss: 1.72636 Learning rate: 0.02 Mask loss: 0.26417 RPN box loss: 0.05569 RPN score loss: 0.00916 RPN total loss: 0.06485 Total loss: 2.46876 timestamp: 1655013458.9212022 iteration: 7365 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1309 FastRCNN class loss: 0.05997 FastRCNN total loss: 0.19087 L1 loss: 0.0000e+00 L2 loss: 1.72603 Learning rate: 0.02 Mask loss: 0.17996 RPN box loss: 0.01385 RPN score loss: 0.00554 RPN total loss: 0.01938 Total loss: 2.11625 timestamp: 1655013462.2447443 iteration: 7370 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26417 FastRCNN class loss: 0.13627 FastRCNN total loss: 0.40044 L1 loss: 0.0000e+00 L2 loss: 1.72569 Learning rate: 0.02 Mask loss: 0.21723 RPN box loss: 0.07425 RPN score loss: 0.01697 RPN total loss: 0.09122 Total loss: 2.43458 timestamp: 1655013465.4783275 iteration: 7375 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13961 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.18942 L1 loss: 0.0000e+00 L2 loss: 1.72535 Learning rate: 0.02 Mask loss: 0.22308 RPN box loss: 0.07645 RPN score loss: 0.0228 RPN total loss: 0.09925 Total loss: 2.2371 timestamp: 1655013468.9496658 iteration: 7380 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18353 FastRCNN class loss: 0.10231 FastRCNN total loss: 0.28583 L1 loss: 0.0000e+00 L2 loss: 1.725 Learning rate: 0.02 Mask loss: 0.29802 RPN box loss: 0.06737 RPN score loss: 0.0343 RPN total loss: 0.10168 Total loss: 2.41052 timestamp: 1655013472.1412194 iteration: 7385 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12172 FastRCNN class loss: 0.10414 FastRCNN total loss: 0.22586 L1 loss: 0.0000e+00 L2 loss: 1.72469 Learning rate: 0.02 Mask loss: 0.26085 RPN box loss: 0.08557 RPN score loss: 0.01563 RPN total loss: 0.10121 Total loss: 2.31261 timestamp: 1655013475.5698674 iteration: 7390 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11174 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.18299 L1 loss: 0.0000e+00 L2 loss: 1.72438 Learning rate: 0.02 Mask loss: 0.26198 RPN box loss: 0.0453 RPN score loss: 0.01169 RPN total loss: 0.05699 Total loss: 2.22635 timestamp: 1655013478.843694 iteration: 7395 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14294 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.21226 L1 loss: 0.0000e+00 L2 loss: 1.72408 Learning rate: 0.02 Mask loss: 0.2762 RPN box loss: 0.01191 RPN score loss: 0.00543 RPN total loss: 0.01734 Total loss: 2.22988 timestamp: 1655013482.3250475 iteration: 7400 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1934 FastRCNN class loss: 0.08932 FastRCNN total loss: 0.28272 L1 loss: 0.0000e+00 L2 loss: 1.72376 Learning rate: 0.02 Mask loss: 0.20169 RPN box loss: 0.03431 RPN score loss: 0.01547 RPN total loss: 0.04977 Total loss: 2.25795 timestamp: 1655013485.6225383 iteration: 7405 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15695 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.24582 L1 loss: 0.0000e+00 L2 loss: 1.72344 Learning rate: 0.02 Mask loss: 0.18238 RPN box loss: 0.10119 RPN score loss: 0.01755 RPN total loss: 0.11875 Total loss: 2.27038 timestamp: 1655013488.972899 iteration: 7410 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20088 FastRCNN class loss: 0.08448 FastRCNN total loss: 0.28537 L1 loss: 0.0000e+00 L2 loss: 1.72311 Learning rate: 0.02 Mask loss: 0.17709 RPN box loss: 0.05217 RPN score loss: 0.02889 RPN total loss: 0.08106 Total loss: 2.26663 timestamp: 1655013492.3820252 iteration: 7415 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09346 FastRCNN class loss: 0.04942 FastRCNN total loss: 0.14288 L1 loss: 0.0000e+00 L2 loss: 1.7228 Learning rate: 0.02 Mask loss: 0.15767 RPN box loss: 0.00553 RPN score loss: 0.00453 RPN total loss: 0.01007 Total loss: 2.03341 timestamp: 1655013495.658739 iteration: 7420 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.25137 L1 loss: 0.0000e+00 L2 loss: 1.72247 Learning rate: 0.02 Mask loss: 0.21774 RPN box loss: 0.02669 RPN score loss: 0.00794 RPN total loss: 0.03463 Total loss: 2.22622 timestamp: 1655013499.0137975 iteration: 7425 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.04227 FastRCNN total loss: 0.12624 L1 loss: 0.0000e+00 L2 loss: 1.72215 Learning rate: 0.02 Mask loss: 0.13841 RPN box loss: 0.07256 RPN score loss: 0.00817 RPN total loss: 0.08073 Total loss: 2.06753 timestamp: 1655013502.2120547 iteration: 7430 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14587 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.20828 L1 loss: 0.0000e+00 L2 loss: 1.72183 Learning rate: 0.02 Mask loss: 0.1609 RPN box loss: 0.02911 RPN score loss: 0.00835 RPN total loss: 0.03746 Total loss: 2.12847 timestamp: 1655013505.5711088 iteration: 7435 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21683 FastRCNN class loss: 0.15393 FastRCNN total loss: 0.37076 L1 loss: 0.0000e+00 L2 loss: 1.7215 Learning rate: 0.02 Mask loss: 0.22626 RPN box loss: 0.05735 RPN score loss: 0.01059 RPN total loss: 0.06793 Total loss: 2.38646 timestamp: 1655013508.8804185 iteration: 7440 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11753 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.18507 L1 loss: 0.0000e+00 L2 loss: 1.72117 Learning rate: 0.02 Mask loss: 0.12613 RPN box loss: 0.05303 RPN score loss: 0.00837 RPN total loss: 0.06141 Total loss: 2.09378 timestamp: 1655013512.2717838 iteration: 7445 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1728 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.24893 L1 loss: 0.0000e+00 L2 loss: 1.72084 Learning rate: 0.02 Mask loss: 0.15681 RPN box loss: 0.03018 RPN score loss: 0.00823 RPN total loss: 0.03841 Total loss: 2.16499 timestamp: 1655013515.7722971 iteration: 7450 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18938 FastRCNN class loss: 0.12397 FastRCNN total loss: 0.31335 L1 loss: 0.0000e+00 L2 loss: 1.7205 Learning rate: 0.02 Mask loss: 0.24527 RPN box loss: 0.06257 RPN score loss: 0.00837 RPN total loss: 0.07095 Total loss: 2.35006 timestamp: 1655013519.070437 iteration: 7455 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19752 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.27325 L1 loss: 0.0000e+00 L2 loss: 1.72017 Learning rate: 0.02 Mask loss: 0.16744 RPN box loss: 0.01756 RPN score loss: 0.00456 RPN total loss: 0.02213 Total loss: 2.18298 timestamp: 1655013522.466023 iteration: 7460 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1701 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.24841 L1 loss: 0.0000e+00 L2 loss: 1.71986 Learning rate: 0.02 Mask loss: 0.14887 RPN box loss: 0.02451 RPN score loss: 0.00779 RPN total loss: 0.0323 Total loss: 2.14944 timestamp: 1655013525.888534 iteration: 7465 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23196 FastRCNN class loss: 0.11008 FastRCNN total loss: 0.34204 L1 loss: 0.0000e+00 L2 loss: 1.71955 Learning rate: 0.02 Mask loss: 0.22225 RPN box loss: 0.01892 RPN score loss: 0.00635 RPN total loss: 0.02527 Total loss: 2.30911 timestamp: 1655013529.3588126 iteration: 7470 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17038 FastRCNN class loss: 0.17187 FastRCNN total loss: 0.34225 L1 loss: 0.0000e+00 L2 loss: 1.71925 Learning rate: 0.02 Mask loss: 0.23176 RPN box loss: 0.07251 RPN score loss: 0.02113 RPN total loss: 0.09364 Total loss: 2.3869 timestamp: 1655013532.6214507 iteration: 7475 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19349 FastRCNN class loss: 0.16085 FastRCNN total loss: 0.35434 L1 loss: 0.0000e+00 L2 loss: 1.71894 Learning rate: 0.02 Mask loss: 0.21833 RPN box loss: 0.05482 RPN score loss: 0.01768 RPN total loss: 0.0725 Total loss: 2.36411 timestamp: 1655013536.029519 iteration: 7480 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17781 FastRCNN class loss: 0.11183 FastRCNN total loss: 0.28964 L1 loss: 0.0000e+00 L2 loss: 1.71861 Learning rate: 0.02 Mask loss: 0.2188 RPN box loss: 0.0668 RPN score loss: 0.01961 RPN total loss: 0.08641 Total loss: 2.31346 timestamp: 1655013539.4290857 iteration: 7485 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23782 FastRCNN class loss: 0.11096 FastRCNN total loss: 0.34878 L1 loss: 0.0000e+00 L2 loss: 1.71828 Learning rate: 0.02 Mask loss: 0.20153 RPN box loss: 0.02613 RPN score loss: 0.00745 RPN total loss: 0.03357 Total loss: 2.30216 timestamp: 1655013542.759549 iteration: 7490 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23158 FastRCNN class loss: 0.13927 FastRCNN total loss: 0.37085 L1 loss: 0.0000e+00 L2 loss: 1.71795 Learning rate: 0.02 Mask loss: 0.2353 RPN box loss: 0.05783 RPN score loss: 0.01476 RPN total loss: 0.07259 Total loss: 2.39669 timestamp: 1655013546.0429306 iteration: 7495 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22263 FastRCNN class loss: 0.0945 FastRCNN total loss: 0.31714 L1 loss: 0.0000e+00 L2 loss: 1.71761 Learning rate: 0.02 Mask loss: 0.17516 RPN box loss: 0.03606 RPN score loss: 0.01043 RPN total loss: 0.04648 Total loss: 2.25639 timestamp: 1655013549.295938 iteration: 7500 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17163 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.23774 L1 loss: 0.0000e+00 L2 loss: 1.71729 Learning rate: 0.02 Mask loss: 0.15055 RPN box loss: 0.04097 RPN score loss: 0.01561 RPN total loss: 0.05658 Total loss: 2.16216 timestamp: 1655013552.7273366 iteration: 7505 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25828 FastRCNN class loss: 0.12472 FastRCNN total loss: 0.383 L1 loss: 0.0000e+00 L2 loss: 1.71696 Learning rate: 0.02 Mask loss: 0.20531 RPN box loss: 0.04115 RPN score loss: 0.01619 RPN total loss: 0.05734 Total loss: 2.36261 timestamp: 1655013556.128711 iteration: 7510 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17799 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.25046 L1 loss: 0.0000e+00 L2 loss: 1.71666 Learning rate: 0.02 Mask loss: 0.14985 RPN box loss: 0.03729 RPN score loss: 0.00761 RPN total loss: 0.04489 Total loss: 2.16187 timestamp: 1655013559.5005624 iteration: 7515 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21521 FastRCNN class loss: 0.10971 FastRCNN total loss: 0.32492 L1 loss: 0.0000e+00 L2 loss: 1.71633 Learning rate: 0.02 Mask loss: 0.18472 RPN box loss: 0.05254 RPN score loss: 0.01881 RPN total loss: 0.07135 Total loss: 2.29732 timestamp: 1655013562.928321 iteration: 7520 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19493 FastRCNN class loss: 0.11842 FastRCNN total loss: 0.31335 L1 loss: 0.0000e+00 L2 loss: 1.71601 Learning rate: 0.02 Mask loss: 0.16358 RPN box loss: 0.05378 RPN score loss: 0.00966 RPN total loss: 0.06344 Total loss: 2.25637 timestamp: 1655013566.2220883 iteration: 7525 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27254 FastRCNN class loss: 0.09171 FastRCNN total loss: 0.36425 L1 loss: 0.0000e+00 L2 loss: 1.71566 Learning rate: 0.02 Mask loss: 0.23984 RPN box loss: 0.0752 RPN score loss: 0.00867 RPN total loss: 0.08387 Total loss: 2.40363 timestamp: 1655013569.6118982 iteration: 7530 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26615 FastRCNN class loss: 0.16385 FastRCNN total loss: 0.43 L1 loss: 0.0000e+00 L2 loss: 1.71535 Learning rate: 0.02 Mask loss: 0.25545 RPN box loss: 0.1058 RPN score loss: 0.02533 RPN total loss: 0.13113 Total loss: 2.53193 timestamp: 1655013572.8466334 iteration: 7535 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17656 FastRCNN class loss: 0.15859 FastRCNN total loss: 0.33514 L1 loss: 0.0000e+00 L2 loss: 1.71506 Learning rate: 0.02 Mask loss: 0.31079 RPN box loss: 0.04485 RPN score loss: 0.02204 RPN total loss: 0.06689 Total loss: 2.42789 timestamp: 1655013576.290435 iteration: 7540 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14865 FastRCNN class loss: 0.12521 FastRCNN total loss: 0.27386 L1 loss: 0.0000e+00 L2 loss: 1.71474 Learning rate: 0.02 Mask loss: 0.17081 RPN box loss: 0.04259 RPN score loss: 0.00564 RPN total loss: 0.04822 Total loss: 2.20763 timestamp: 1655013579.5951517 iteration: 7545 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13537 FastRCNN class loss: 0.09123 FastRCNN total loss: 0.2266 L1 loss: 0.0000e+00 L2 loss: 1.71442 Learning rate: 0.02 Mask loss: 0.1914 RPN box loss: 0.08249 RPN score loss: 0.00636 RPN total loss: 0.08886 Total loss: 2.22128 timestamp: 1655013582.8969467 iteration: 7550 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14698 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.23558 L1 loss: 0.0000e+00 L2 loss: 1.71406 Learning rate: 0.02 Mask loss: 0.15301 RPN box loss: 0.056 RPN score loss: 0.00957 RPN total loss: 0.06557 Total loss: 2.16822 timestamp: 1655013586.124978 iteration: 7555 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16576 FastRCNN class loss: 0.10089 FastRCNN total loss: 0.26665 L1 loss: 0.0000e+00 L2 loss: 1.71375 Learning rate: 0.02 Mask loss: 0.22479 RPN box loss: 0.06361 RPN score loss: 0.01578 RPN total loss: 0.07938 Total loss: 2.28457 timestamp: 1655013589.474574 iteration: 7560 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14742 FastRCNN class loss: 0.09894 FastRCNN total loss: 0.24635 L1 loss: 0.0000e+00 L2 loss: 1.71345 Learning rate: 0.02 Mask loss: 0.22463 RPN box loss: 0.08928 RPN score loss: 0.04272 RPN total loss: 0.13201 Total loss: 2.31644 timestamp: 1655013592.8577433 iteration: 7565 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10105 FastRCNN class loss: 0.05781 FastRCNN total loss: 0.15886 L1 loss: 0.0000e+00 L2 loss: 1.71312 Learning rate: 0.02 Mask loss: 0.16149 RPN box loss: 0.04563 RPN score loss: 0.02238 RPN total loss: 0.068 Total loss: 2.10147 timestamp: 1655013596.1881647 iteration: 7570 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.22953 L1 loss: 0.0000e+00 L2 loss: 1.71279 Learning rate: 0.02 Mask loss: 0.15763 RPN box loss: 0.05376 RPN score loss: 0.01211 RPN total loss: 0.06587 Total loss: 2.16581 timestamp: 1655013599.4625273 iteration: 7575 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19202 FastRCNN class loss: 0.09397 FastRCNN total loss: 0.286 L1 loss: 0.0000e+00 L2 loss: 1.71248 Learning rate: 0.02 Mask loss: 0.18626 RPN box loss: 0.06394 RPN score loss: 0.01088 RPN total loss: 0.07482 Total loss: 2.25955 timestamp: 1655013602.6626139 iteration: 7580 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26079 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.34122 L1 loss: 0.0000e+00 L2 loss: 1.71216 Learning rate: 0.02 Mask loss: 0.28932 RPN box loss: 0.08784 RPN score loss: 0.01044 RPN total loss: 0.09828 Total loss: 2.44098 timestamp: 1655013605.9368684 iteration: 7585 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14241 FastRCNN class loss: 0.14106 FastRCNN total loss: 0.28347 L1 loss: 0.0000e+00 L2 loss: 1.71185 Learning rate: 0.02 Mask loss: 0.21988 RPN box loss: 0.04549 RPN score loss: 0.01431 RPN total loss: 0.0598 Total loss: 2.27499 timestamp: 1655013609.2699444 iteration: 7590 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22067 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.29009 L1 loss: 0.0000e+00 L2 loss: 1.71153 Learning rate: 0.02 Mask loss: 0.18868 RPN box loss: 0.04305 RPN score loss: 0.01516 RPN total loss: 0.05821 Total loss: 2.2485 timestamp: 1655013612.692332 iteration: 7595 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23917 FastRCNN class loss: 0.15214 FastRCNN total loss: 0.3913 L1 loss: 0.0000e+00 L2 loss: 1.71122 Learning rate: 0.02 Mask loss: 0.23288 RPN box loss: 0.03385 RPN score loss: 0.03756 RPN total loss: 0.07141 Total loss: 2.40681 timestamp: 1655013615.906563 iteration: 7600 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21528 FastRCNN class loss: 0.06692 FastRCNN total loss: 0.2822 L1 loss: 0.0000e+00 L2 loss: 1.71089 Learning rate: 0.02 Mask loss: 0.19496 RPN box loss: 0.01366 RPN score loss: 0.0064 RPN total loss: 0.02005 Total loss: 2.20809 timestamp: 1655013619.3801565 iteration: 7605 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14405 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.22142 L1 loss: 0.0000e+00 L2 loss: 1.71057 Learning rate: 0.02 Mask loss: 0.11803 RPN box loss: 0.01901 RPN score loss: 0.00587 RPN total loss: 0.02488 Total loss: 2.07491 timestamp: 1655013622.7594943 iteration: 7610 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13881 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.22079 L1 loss: 0.0000e+00 L2 loss: 1.71028 Learning rate: 0.02 Mask loss: 0.12048 RPN box loss: 0.02593 RPN score loss: 0.00301 RPN total loss: 0.02894 Total loss: 2.08049 timestamp: 1655013625.9861877 iteration: 7615 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21463 FastRCNN class loss: 0.15007 FastRCNN total loss: 0.3647 L1 loss: 0.0000e+00 L2 loss: 1.70996 Learning rate: 0.02 Mask loss: 0.21276 RPN box loss: 0.09551 RPN score loss: 0.01478 RPN total loss: 0.11029 Total loss: 2.39771 timestamp: 1655013629.4000404 iteration: 7620 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.04725 FastRCNN total loss: 0.1404 L1 loss: 0.0000e+00 L2 loss: 1.70965 Learning rate: 0.02 Mask loss: 0.15021 RPN box loss: 0.07902 RPN score loss: 0.00814 RPN total loss: 0.08715 Total loss: 2.08741 timestamp: 1655013632.6812565 iteration: 7625 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22569 FastRCNN class loss: 0.10892 FastRCNN total loss: 0.33461 L1 loss: 0.0000e+00 L2 loss: 1.70933 Learning rate: 0.02 Mask loss: 0.29093 RPN box loss: 0.06586 RPN score loss: 0.00975 RPN total loss: 0.07562 Total loss: 2.41048 timestamp: 1655013636.1884634 iteration: 7630 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24349 FastRCNN class loss: 0.17333 FastRCNN total loss: 0.41682 L1 loss: 0.0000e+00 L2 loss: 1.709 Learning rate: 0.02 Mask loss: 0.24555 RPN box loss: 0.04691 RPN score loss: 0.0197 RPN total loss: 0.0666 Total loss: 2.43797 timestamp: 1655013639.4171193 iteration: 7635 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29905 FastRCNN class loss: 0.10753 FastRCNN total loss: 0.40658 L1 loss: 0.0000e+00 L2 loss: 1.70869 Learning rate: 0.02 Mask loss: 0.25635 RPN box loss: 0.03056 RPN score loss: 0.01893 RPN total loss: 0.0495 Total loss: 2.42112 timestamp: 1655013642.7872245 iteration: 7640 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19302 FastRCNN class loss: 0.11899 FastRCNN total loss: 0.31201 L1 loss: 0.0000e+00 L2 loss: 1.70838 Learning rate: 0.02 Mask loss: 0.20285 RPN box loss: 0.03974 RPN score loss: 0.01179 RPN total loss: 0.05154 Total loss: 2.27478 timestamp: 1655013646.1149094 iteration: 7645 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07186 FastRCNN class loss: 0.05739 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 1.70807 Learning rate: 0.02 Mask loss: 0.24078 RPN box loss: 0.06115 RPN score loss: 0.0099 RPN total loss: 0.07105 Total loss: 2.14915 timestamp: 1655013649.4391286 iteration: 7650 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.03264 FastRCNN total loss: 0.12776 L1 loss: 0.0000e+00 L2 loss: 1.70775 Learning rate: 0.02 Mask loss: 0.14003 RPN box loss: 0.00335 RPN score loss: 0.00268 RPN total loss: 0.00603 Total loss: 1.98157 timestamp: 1655013652.8757553 iteration: 7655 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21524 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.30077 L1 loss: 0.0000e+00 L2 loss: 1.7074 Learning rate: 0.02 Mask loss: 0.16256 RPN box loss: 0.0442 RPN score loss: 0.00731 RPN total loss: 0.05151 Total loss: 2.22225 timestamp: 1655013656.086508 iteration: 7660 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20852 FastRCNN class loss: 0.12244 FastRCNN total loss: 0.33096 L1 loss: 0.0000e+00 L2 loss: 1.70707 Learning rate: 0.02 Mask loss: 0.2027 RPN box loss: 0.03345 RPN score loss: 0.00615 RPN total loss: 0.0396 Total loss: 2.28034 timestamp: 1655013659.5840647 iteration: 7665 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15823 FastRCNN class loss: 0.06864 FastRCNN total loss: 0.22688 L1 loss: 0.0000e+00 L2 loss: 1.70677 Learning rate: 0.02 Mask loss: 0.1456 RPN box loss: 0.04932 RPN score loss: 0.00602 RPN total loss: 0.05534 Total loss: 2.13458 timestamp: 1655013662.8777397 iteration: 7670 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21617 FastRCNN class loss: 0.12365 FastRCNN total loss: 0.33982 L1 loss: 0.0000e+00 L2 loss: 1.70645 Learning rate: 0.02 Mask loss: 0.26901 RPN box loss: 0.05747 RPN score loss: 0.00931 RPN total loss: 0.06678 Total loss: 2.38206 timestamp: 1655013666.312374 iteration: 7675 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25887 FastRCNN class loss: 0.15116 FastRCNN total loss: 0.41004 L1 loss: 0.0000e+00 L2 loss: 1.70613 Learning rate: 0.02 Mask loss: 0.27796 RPN box loss: 0.01572 RPN score loss: 0.00646 RPN total loss: 0.02217 Total loss: 2.41631 timestamp: 1655013669.5707943 iteration: 7680 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16933 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.22616 L1 loss: 0.0000e+00 L2 loss: 1.70582 Learning rate: 0.02 Mask loss: 0.20198 RPN box loss: 0.06658 RPN score loss: 0.01509 RPN total loss: 0.08167 Total loss: 2.21564 timestamp: 1655013673.0124073 iteration: 7685 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10985 FastRCNN class loss: 0.05686 FastRCNN total loss: 0.16671 L1 loss: 0.0000e+00 L2 loss: 1.7055 Learning rate: 0.02 Mask loss: 0.15781 RPN box loss: 0.07134 RPN score loss: 0.01687 RPN total loss: 0.08821 Total loss: 2.11823 timestamp: 1655013676.3428118 iteration: 7690 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22549 FastRCNN class loss: 0.16726 FastRCNN total loss: 0.39276 L1 loss: 0.0000e+00 L2 loss: 1.70517 Learning rate: 0.02 Mask loss: 0.29943 RPN box loss: 0.03806 RPN score loss: 0.01166 RPN total loss: 0.04972 Total loss: 2.44708 timestamp: 1655013679.6729467 iteration: 7695 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17075 FastRCNN class loss: 0.10021 FastRCNN total loss: 0.27097 L1 loss: 0.0000e+00 L2 loss: 1.70486 Learning rate: 0.02 Mask loss: 0.24862 RPN box loss: 0.04379 RPN score loss: 0.01049 RPN total loss: 0.05428 Total loss: 2.27873 timestamp: 1655013683.051439 iteration: 7700 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24068 FastRCNN class loss: 0.10549 FastRCNN total loss: 0.34617 L1 loss: 0.0000e+00 L2 loss: 1.70455 Learning rate: 0.02 Mask loss: 0.17291 RPN box loss: 0.03133 RPN score loss: 0.00778 RPN total loss: 0.03911 Total loss: 2.26274 timestamp: 1655013686.3293068 iteration: 7705 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25564 FastRCNN class loss: 0.12962 FastRCNN total loss: 0.38527 L1 loss: 0.0000e+00 L2 loss: 1.70423 Learning rate: 0.02 Mask loss: 0.2307 RPN box loss: 0.03009 RPN score loss: 0.01413 RPN total loss: 0.04422 Total loss: 2.36441 timestamp: 1655013689.7553294 iteration: 7710 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16119 FastRCNN class loss: 0.11408 FastRCNN total loss: 0.27527 L1 loss: 0.0000e+00 L2 loss: 1.7039 Learning rate: 0.02 Mask loss: 0.41518 RPN box loss: 0.09706 RPN score loss: 0.04452 RPN total loss: 0.14158 Total loss: 2.53593 timestamp: 1655013693.0170474 iteration: 7715 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25225 FastRCNN class loss: 0.1166 FastRCNN total loss: 0.36885 L1 loss: 0.0000e+00 L2 loss: 1.70357 Learning rate: 0.02 Mask loss: 0.32147 RPN box loss: 0.02678 RPN score loss: 0.00753 RPN total loss: 0.03431 Total loss: 2.42821 timestamp: 1655013696.4867935 iteration: 7720 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28065 FastRCNN class loss: 0.14187 FastRCNN total loss: 0.42252 L1 loss: 0.0000e+00 L2 loss: 1.70326 Learning rate: 0.02 Mask loss: 0.26842 RPN box loss: 0.0675 RPN score loss: 0.01344 RPN total loss: 0.08094 Total loss: 2.47514 timestamp: 1655013699.7402513 iteration: 7725 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11361 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.17492 L1 loss: 0.0000e+00 L2 loss: 1.70294 Learning rate: 0.02 Mask loss: 0.17684 RPN box loss: 0.08173 RPN score loss: 0.00943 RPN total loss: 0.09116 Total loss: 2.14586 timestamp: 1655013703.1089458 iteration: 7730 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16253 FastRCNN class loss: 0.10852 FastRCNN total loss: 0.27105 L1 loss: 0.0000e+00 L2 loss: 1.70262 Learning rate: 0.02 Mask loss: 0.24621 RPN box loss: 0.04795 RPN score loss: 0.0425 RPN total loss: 0.09045 Total loss: 2.31033 timestamp: 1655013706.3907285 iteration: 7735 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15567 FastRCNN class loss: 0.0767 FastRCNN total loss: 0.23237 L1 loss: 0.0000e+00 L2 loss: 1.70228 Learning rate: 0.02 Mask loss: 0.15201 RPN box loss: 0.03285 RPN score loss: 0.00604 RPN total loss: 0.03889 Total loss: 2.12555 timestamp: 1655013709.8397207 iteration: 7740 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24367 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.33344 L1 loss: 0.0000e+00 L2 loss: 1.70196 Learning rate: 0.02 Mask loss: 0.14517 RPN box loss: 0.02504 RPN score loss: 0.00674 RPN total loss: 0.03178 Total loss: 2.21235 timestamp: 1655013713.184855 iteration: 7745 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21936 FastRCNN class loss: 0.06971 FastRCNN total loss: 0.28907 L1 loss: 0.0000e+00 L2 loss: 1.70164 Learning rate: 0.02 Mask loss: 0.19407 RPN box loss: 0.04413 RPN score loss: 0.00603 RPN total loss: 0.05017 Total loss: 2.23495 timestamp: 1655013716.5107768 iteration: 7750 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14803 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.21446 L1 loss: 0.0000e+00 L2 loss: 1.70134 Learning rate: 0.02 Mask loss: 0.30116 RPN box loss: 0.04147 RPN score loss: 0.00954 RPN total loss: 0.05101 Total loss: 2.26797 timestamp: 1655013719.9616628 iteration: 7755 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18676 FastRCNN class loss: 0.111 FastRCNN total loss: 0.29776 L1 loss: 0.0000e+00 L2 loss: 1.70102 Learning rate: 0.02 Mask loss: 0.18379 RPN box loss: 0.05429 RPN score loss: 0.00683 RPN total loss: 0.06112 Total loss: 2.24369 timestamp: 1655013723.2409415 iteration: 7760 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19667 FastRCNN class loss: 0.12429 FastRCNN total loss: 0.32097 L1 loss: 0.0000e+00 L2 loss: 1.7007 Learning rate: 0.02 Mask loss: 0.19592 RPN box loss: 0.08707 RPN score loss: 0.01634 RPN total loss: 0.10341 Total loss: 2.32099 timestamp: 1655013726.6091838 iteration: 7765 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20612 FastRCNN class loss: 0.08419 FastRCNN total loss: 0.29031 L1 loss: 0.0000e+00 L2 loss: 1.70039 Learning rate: 0.02 Mask loss: 0.15651 RPN box loss: 0.01884 RPN score loss: 0.00355 RPN total loss: 0.0224 Total loss: 2.16962 timestamp: 1655013729.8926175 iteration: 7770 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17196 FastRCNN class loss: 0.10117 FastRCNN total loss: 0.27313 L1 loss: 0.0000e+00 L2 loss: 1.70009 Learning rate: 0.02 Mask loss: 0.12966 RPN box loss: 0.06139 RPN score loss: 0.00765 RPN total loss: 0.06904 Total loss: 2.17192 timestamp: 1655013733.2844205 iteration: 7775 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19216 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.2765 L1 loss: 0.0000e+00 L2 loss: 1.69978 Learning rate: 0.02 Mask loss: 0.19314 RPN box loss: 0.02652 RPN score loss: 0.00873 RPN total loss: 0.03525 Total loss: 2.20467 timestamp: 1655013736.6742275 iteration: 7780 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30857 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.40951 L1 loss: 0.0000e+00 L2 loss: 1.69945 Learning rate: 0.02 Mask loss: 0.22835 RPN box loss: 0.02459 RPN score loss: 0.00601 RPN total loss: 0.0306 Total loss: 2.36791 timestamp: 1655013739.9226303 iteration: 7785 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20671 FastRCNN class loss: 0.15038 FastRCNN total loss: 0.35709 L1 loss: 0.0000e+00 L2 loss: 1.69913 Learning rate: 0.02 Mask loss: 0.21365 RPN box loss: 0.03651 RPN score loss: 0.01507 RPN total loss: 0.05158 Total loss: 2.32145 timestamp: 1655013743.2685459 iteration: 7790 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19051 FastRCNN class loss: 0.06827 FastRCNN total loss: 0.25878 L1 loss: 0.0000e+00 L2 loss: 1.69881 Learning rate: 0.02 Mask loss: 0.27307 RPN box loss: 0.02347 RPN score loss: 0.0104 RPN total loss: 0.03387 Total loss: 2.26454 timestamp: 1655013746.6083353 iteration: 7795 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20816 FastRCNN class loss: 0.11637 FastRCNN total loss: 0.32453 L1 loss: 0.0000e+00 L2 loss: 1.69851 Learning rate: 0.02 Mask loss: 0.17322 RPN box loss: 0.01923 RPN score loss: 0.00807 RPN total loss: 0.0273 Total loss: 2.22355 timestamp: 1655013750.0534525 iteration: 7800 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12212 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.20087 L1 loss: 0.0000e+00 L2 loss: 1.69821 Learning rate: 0.02 Mask loss: 0.1388 RPN box loss: 0.04815 RPN score loss: 0.00856 RPN total loss: 0.05671 Total loss: 2.09457 timestamp: 1655013753.3757997 iteration: 7805 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31534 FastRCNN class loss: 0.08776 FastRCNN total loss: 0.4031 L1 loss: 0.0000e+00 L2 loss: 1.69789 Learning rate: 0.02 Mask loss: 0.19686 RPN box loss: 0.05404 RPN score loss: 0.00836 RPN total loss: 0.0624 Total loss: 2.36024 timestamp: 1655013756.923974 iteration: 7810 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1464 FastRCNN class loss: 0.055 FastRCNN total loss: 0.2014 L1 loss: 0.0000e+00 L2 loss: 1.69756 Learning rate: 0.02 Mask loss: 0.17011 RPN box loss: 0.03817 RPN score loss: 0.00865 RPN total loss: 0.04681 Total loss: 2.11588 timestamp: 1655013760.1491067 iteration: 7815 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16819 FastRCNN class loss: 0.08376 FastRCNN total loss: 0.25195 L1 loss: 0.0000e+00 L2 loss: 1.69725 Learning rate: 0.02 Mask loss: 0.16628 RPN box loss: 0.04103 RPN score loss: 0.00935 RPN total loss: 0.05039 Total loss: 2.16587 timestamp: 1655013763.631655 iteration: 7820 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19302 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.25995 L1 loss: 0.0000e+00 L2 loss: 1.69694 Learning rate: 0.02 Mask loss: 0.17692 RPN box loss: 0.02079 RPN score loss: 0.00385 RPN total loss: 0.02464 Total loss: 2.15844 timestamp: 1655013767.0016992 iteration: 7825 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18319 FastRCNN class loss: 0.10322 FastRCNN total loss: 0.28641 L1 loss: 0.0000e+00 L2 loss: 1.69661 Learning rate: 0.02 Mask loss: 0.29887 RPN box loss: 0.04225 RPN score loss: 0.00805 RPN total loss: 0.0503 Total loss: 2.33218 timestamp: 1655013770.2682915 iteration: 7830 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19191 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.26148 L1 loss: 0.0000e+00 L2 loss: 1.6963 Learning rate: 0.02 Mask loss: 0.21209 RPN box loss: 0.01293 RPN score loss: 0.00614 RPN total loss: 0.01907 Total loss: 2.18895 timestamp: 1655013773.7453732 iteration: 7835 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17331 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.27845 L1 loss: 0.0000e+00 L2 loss: 1.696 Learning rate: 0.02 Mask loss: 0.17415 RPN box loss: 0.04164 RPN score loss: 0.00855 RPN total loss: 0.05019 Total loss: 2.1988 timestamp: 1655013777.0722919 iteration: 7840 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20679 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.30029 L1 loss: 0.0000e+00 L2 loss: 1.69569 Learning rate: 0.02 Mask loss: 0.20967 RPN box loss: 0.03695 RPN score loss: 0.00622 RPN total loss: 0.04317 Total loss: 2.24882 timestamp: 1655013780.5051775 iteration: 7845 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21865 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.3192 L1 loss: 0.0000e+00 L2 loss: 1.69538 Learning rate: 0.02 Mask loss: 0.17658 RPN box loss: 0.02908 RPN score loss: 0.00456 RPN total loss: 0.03364 Total loss: 2.22481 timestamp: 1655013783.8022976 iteration: 7850 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19204 FastRCNN class loss: 0.12295 FastRCNN total loss: 0.31499 L1 loss: 0.0000e+00 L2 loss: 1.69505 Learning rate: 0.02 Mask loss: 0.19315 RPN box loss: 0.0648 RPN score loss: 0.01874 RPN total loss: 0.08354 Total loss: 2.28674 timestamp: 1655013787.2473047 iteration: 7855 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1824 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.24355 L1 loss: 0.0000e+00 L2 loss: 1.69473 Learning rate: 0.02 Mask loss: 0.17085 RPN box loss: 0.02689 RPN score loss: 0.00516 RPN total loss: 0.03205 Total loss: 2.14119 timestamp: 1655013790.6200025 iteration: 7860 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16025 FastRCNN class loss: 0.08459 FastRCNN total loss: 0.24484 L1 loss: 0.0000e+00 L2 loss: 1.69441 Learning rate: 0.02 Mask loss: 0.16639 RPN box loss: 0.01544 RPN score loss: 0.00387 RPN total loss: 0.01931 Total loss: 2.12495 timestamp: 1655013793.9625628 iteration: 7865 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18357 FastRCNN class loss: 0.10045 FastRCNN total loss: 0.28402 L1 loss: 0.0000e+00 L2 loss: 1.6941 Learning rate: 0.02 Mask loss: 0.15813 RPN box loss: 0.06975 RPN score loss: 0.01392 RPN total loss: 0.08366 Total loss: 2.21991 timestamp: 1655013797.2675226 iteration: 7870 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17475 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.25181 L1 loss: 0.0000e+00 L2 loss: 1.6938 Learning rate: 0.02 Mask loss: 0.28046 RPN box loss: 0.04004 RPN score loss: 0.00443 RPN total loss: 0.04446 Total loss: 2.27053 timestamp: 1655013800.521659 iteration: 7875 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23133 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.30988 L1 loss: 0.0000e+00 L2 loss: 1.69348 Learning rate: 0.02 Mask loss: 0.21641 RPN box loss: 0.04271 RPN score loss: 0.00954 RPN total loss: 0.05225 Total loss: 2.27202 timestamp: 1655013803.911514 iteration: 7880 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15468 FastRCNN class loss: 0.08931 FastRCNN total loss: 0.24399 L1 loss: 0.0000e+00 L2 loss: 1.69315 Learning rate: 0.02 Mask loss: 0.22437 RPN box loss: 0.02223 RPN score loss: 0.00837 RPN total loss: 0.0306 Total loss: 2.19211 timestamp: 1655013807.2443838 iteration: 7885 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15688 FastRCNN class loss: 0.10663 FastRCNN total loss: 0.26351 L1 loss: 0.0000e+00 L2 loss: 1.69284 Learning rate: 0.02 Mask loss: 0.31313 RPN box loss: 0.06461 RPN score loss: 0.00933 RPN total loss: 0.07395 Total loss: 2.34342 timestamp: 1655013810.6411307 iteration: 7890 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18408 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.26876 L1 loss: 0.0000e+00 L2 loss: 1.69253 Learning rate: 0.02 Mask loss: 0.26507 RPN box loss: 0.02896 RPN score loss: 0.00424 RPN total loss: 0.03321 Total loss: 2.25958 timestamp: 1655013813.9771357 iteration: 7895 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24419 FastRCNN class loss: 0.06399 FastRCNN total loss: 0.30818 L1 loss: 0.0000e+00 L2 loss: 1.6922 Learning rate: 0.02 Mask loss: 0.21482 RPN box loss: 0.06698 RPN score loss: 0.01357 RPN total loss: 0.08055 Total loss: 2.29576 timestamp: 1655013817.3876057 iteration: 7900 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1347 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.23134 L1 loss: 0.0000e+00 L2 loss: 1.6919 Learning rate: 0.02 Mask loss: 0.2612 RPN box loss: 0.00677 RPN score loss: 0.00723 RPN total loss: 0.014 Total loss: 2.19845 timestamp: 1655013820.733219 iteration: 7905 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18867 FastRCNN class loss: 0.16641 FastRCNN total loss: 0.35508 L1 loss: 0.0000e+00 L2 loss: 1.69158 Learning rate: 0.02 Mask loss: 0.18172 RPN box loss: 0.05593 RPN score loss: 0.02097 RPN total loss: 0.0769 Total loss: 2.30528 timestamp: 1655013824.0667503 iteration: 7910 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12396 FastRCNN class loss: 0.05628 FastRCNN total loss: 0.18023 L1 loss: 0.0000e+00 L2 loss: 1.69127 Learning rate: 0.02 Mask loss: 0.15125 RPN box loss: 0.02981 RPN score loss: 0.00484 RPN total loss: 0.03465 Total loss: 2.0574 timestamp: 1655013827.4521742 iteration: 7915 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28683 FastRCNN class loss: 0.07972 FastRCNN total loss: 0.36655 L1 loss: 0.0000e+00 L2 loss: 1.69096 Learning rate: 0.02 Mask loss: 0.18863 RPN box loss: 0.01865 RPN score loss: 0.00687 RPN total loss: 0.02552 Total loss: 2.27166 timestamp: 1655013830.684572 iteration: 7920 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25088 FastRCNN class loss: 0.06437 FastRCNN total loss: 0.31524 L1 loss: 0.0000e+00 L2 loss: 1.69066 Learning rate: 0.02 Mask loss: 0.17235 RPN box loss: 0.02113 RPN score loss: 0.00659 RPN total loss: 0.02772 Total loss: 2.20597 timestamp: 1655013833.9711123 iteration: 7925 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21671 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.29451 L1 loss: 0.0000e+00 L2 loss: 1.69035 Learning rate: 0.02 Mask loss: 0.25205 RPN box loss: 0.01431 RPN score loss: 0.00402 RPN total loss: 0.01833 Total loss: 2.25523 timestamp: 1655013837.2299736 iteration: 7930 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23249 FastRCNN class loss: 0.08837 FastRCNN total loss: 0.32087 L1 loss: 0.0000e+00 L2 loss: 1.69002 Learning rate: 0.02 Mask loss: 0.24028 RPN box loss: 0.04126 RPN score loss: 0.00523 RPN total loss: 0.0465 Total loss: 2.29766 timestamp: 1655013840.644747 iteration: 7935 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19792 FastRCNN class loss: 0.11177 FastRCNN total loss: 0.30969 L1 loss: 0.0000e+00 L2 loss: 1.6897 Learning rate: 0.02 Mask loss: 0.20238 RPN box loss: 0.02942 RPN score loss: 0.00569 RPN total loss: 0.0351 Total loss: 2.23687 timestamp: 1655013843.8841243 iteration: 7940 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19165 FastRCNN class loss: 0.11199 FastRCNN total loss: 0.30364 L1 loss: 0.0000e+00 L2 loss: 1.68941 Learning rate: 0.02 Mask loss: 0.24988 RPN box loss: 0.00848 RPN score loss: 0.00597 RPN total loss: 0.01445 Total loss: 2.25738 timestamp: 1655013847.2648535 iteration: 7945 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15243 FastRCNN class loss: 0.08127 FastRCNN total loss: 0.2337 L1 loss: 0.0000e+00 L2 loss: 1.68909 Learning rate: 0.02 Mask loss: 0.16036 RPN box loss: 0.03827 RPN score loss: 0.00755 RPN total loss: 0.04582 Total loss: 2.12897 timestamp: 1655013850.7170777 iteration: 7950 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14508 FastRCNN class loss: 0.05098 FastRCNN total loss: 0.19606 L1 loss: 0.0000e+00 L2 loss: 1.68879 Learning rate: 0.02 Mask loss: 0.1619 RPN box loss: 0.03544 RPN score loss: 0.00448 RPN total loss: 0.03992 Total loss: 2.08667 timestamp: 1655013854.0141058 iteration: 7955 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14374 FastRCNN class loss: 0.09958 FastRCNN total loss: 0.24332 L1 loss: 0.0000e+00 L2 loss: 1.6885 Learning rate: 0.02 Mask loss: 0.19302 RPN box loss: 0.03815 RPN score loss: 0.01436 RPN total loss: 0.05251 Total loss: 2.17735 timestamp: 1655013857.458451 iteration: 7960 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18852 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.26756 L1 loss: 0.0000e+00 L2 loss: 1.68819 Learning rate: 0.02 Mask loss: 0.19577 RPN box loss: 0.16079 RPN score loss: 0.00886 RPN total loss: 0.16965 Total loss: 2.32117 timestamp: 1655013860.8117208 iteration: 7965 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13791 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.19737 L1 loss: 0.0000e+00 L2 loss: 1.68788 Learning rate: 0.02 Mask loss: 0.11673 RPN box loss: 0.04327 RPN score loss: 0.00738 RPN total loss: 0.05066 Total loss: 2.05264 timestamp: 1655013864.1879504 iteration: 7970 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18646 FastRCNN class loss: 0.0898 FastRCNN total loss: 0.27627 L1 loss: 0.0000e+00 L2 loss: 1.68757 Learning rate: 0.02 Mask loss: 0.22745 RPN box loss: 0.06264 RPN score loss: 0.00388 RPN total loss: 0.06652 Total loss: 2.2578 timestamp: 1655013867.3983011 iteration: 7975 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25091 FastRCNN class loss: 0.12487 FastRCNN total loss: 0.37578 L1 loss: 0.0000e+00 L2 loss: 1.68726 Learning rate: 0.02 Mask loss: 0.18431 RPN box loss: 0.07711 RPN score loss: 0.03539 RPN total loss: 0.1125 Total loss: 2.35985 timestamp: 1655013870.7873695 iteration: 7980 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15875 FastRCNN class loss: 0.09295 FastRCNN total loss: 0.2517 L1 loss: 0.0000e+00 L2 loss: 1.68696 Learning rate: 0.02 Mask loss: 0.19078 RPN box loss: 0.01754 RPN score loss: 0.00618 RPN total loss: 0.02372 Total loss: 2.15317 timestamp: 1655013874.2200139 iteration: 7985 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22115 FastRCNN class loss: 0.09733 FastRCNN total loss: 0.31848 L1 loss: 0.0000e+00 L2 loss: 1.68665 Learning rate: 0.02 Mask loss: 0.20475 RPN box loss: 0.04375 RPN score loss: 0.01073 RPN total loss: 0.05447 Total loss: 2.26436 timestamp: 1655013877.5065212 iteration: 7990 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17235 FastRCNN class loss: 0.1082 FastRCNN total loss: 0.28055 L1 loss: 0.0000e+00 L2 loss: 1.68631 Learning rate: 0.02 Mask loss: 0.16953 RPN box loss: 0.04388 RPN score loss: 0.009 RPN total loss: 0.05288 Total loss: 2.18928 timestamp: 1655013880.9832928 iteration: 7995 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16984 FastRCNN class loss: 0.10767 FastRCNN total loss: 0.2775 L1 loss: 0.0000e+00 L2 loss: 1.68601 Learning rate: 0.02 Mask loss: 0.22909 RPN box loss: 0.06169 RPN score loss: 0.01171 RPN total loss: 0.07339 Total loss: 2.266 timestamp: 1655013884.244752 iteration: 8000 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15996 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.22578 L1 loss: 0.0000e+00 L2 loss: 1.68571 Learning rate: 0.02 Mask loss: 0.23756 RPN box loss: 0.03185 RPN score loss: 0.01127 RPN total loss: 0.04312 Total loss: 2.19217 timestamp: 1655013887.608052 iteration: 8005 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19885 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.28773 L1 loss: 0.0000e+00 L2 loss: 1.6854 Learning rate: 0.02 Mask loss: 0.15491 RPN box loss: 0.02836 RPN score loss: 0.00816 RPN total loss: 0.03651 Total loss: 2.16455 timestamp: 1655013890.8476124 iteration: 8010 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22077 FastRCNN class loss: 0.10047 FastRCNN total loss: 0.32124 L1 loss: 0.0000e+00 L2 loss: 1.68509 Learning rate: 0.02 Mask loss: 0.21171 RPN box loss: 0.08477 RPN score loss: 0.00946 RPN total loss: 0.09423 Total loss: 2.31228 timestamp: 1655013894.2162557 iteration: 8015 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22358 FastRCNN class loss: 0.12247 FastRCNN total loss: 0.34605 L1 loss: 0.0000e+00 L2 loss: 1.68476 Learning rate: 0.02 Mask loss: 0.18709 RPN box loss: 0.05363 RPN score loss: 0.01035 RPN total loss: 0.06399 Total loss: 2.28188 timestamp: 1655013897.4930964 iteration: 8020 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11139 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.18902 L1 loss: 0.0000e+00 L2 loss: 1.68445 Learning rate: 0.02 Mask loss: 0.21104 RPN box loss: 0.0643 RPN score loss: 0.00681 RPN total loss: 0.0711 Total loss: 2.15561 timestamp: 1655013900.7828937 iteration: 8025 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21959 FastRCNN class loss: 0.10468 FastRCNN total loss: 0.32427 L1 loss: 0.0000e+00 L2 loss: 1.68413 Learning rate: 0.02 Mask loss: 0.21459 RPN box loss: 0.0615 RPN score loss: 0.01056 RPN total loss: 0.07205 Total loss: 2.29505 timestamp: 1655013904.1970382 iteration: 8030 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.3222 FastRCNN class loss: 0.15872 FastRCNN total loss: 0.48093 L1 loss: 0.0000e+00 L2 loss: 1.68381 Learning rate: 0.02 Mask loss: 0.18185 RPN box loss: 0.02217 RPN score loss: 0.01596 RPN total loss: 0.03813 Total loss: 2.38472 timestamp: 1655013907.4395177 iteration: 8035 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14254 FastRCNN class loss: 0.1228 FastRCNN total loss: 0.26535 L1 loss: 0.0000e+00 L2 loss: 1.68352 Learning rate: 0.02 Mask loss: 0.20205 RPN box loss: 0.07244 RPN score loss: 0.01816 RPN total loss: 0.0906 Total loss: 2.24152 timestamp: 1655013910.9308407 iteration: 8040 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.21645 L1 loss: 0.0000e+00 L2 loss: 1.68321 Learning rate: 0.02 Mask loss: 0.15126 RPN box loss: 0.01108 RPN score loss: 0.01253 RPN total loss: 0.0236 Total loss: 2.07453 timestamp: 1655013914.251602 iteration: 8045 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29591 FastRCNN class loss: 0.14511 FastRCNN total loss: 0.44102 L1 loss: 0.0000e+00 L2 loss: 1.6829 Learning rate: 0.02 Mask loss: 0.26058 RPN box loss: 0.03265 RPN score loss: 0.0057 RPN total loss: 0.03835 Total loss: 2.42285 timestamp: 1655013917.6132433 iteration: 8050 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16005 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.2317 L1 loss: 0.0000e+00 L2 loss: 1.68258 Learning rate: 0.02 Mask loss: 0.18965 RPN box loss: 0.00889 RPN score loss: 0.00227 RPN total loss: 0.01116 Total loss: 2.1151 timestamp: 1655013920.9230628 iteration: 8055 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20436 FastRCNN class loss: 0.08194 FastRCNN total loss: 0.2863 L1 loss: 0.0000e+00 L2 loss: 1.68228 Learning rate: 0.02 Mask loss: 0.22392 RPN box loss: 0.04179 RPN score loss: 0.00402 RPN total loss: 0.0458 Total loss: 2.2383 timestamp: 1655013924.3582602 iteration: 8060 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14634 FastRCNN class loss: 0.094 FastRCNN total loss: 0.24034 L1 loss: 0.0000e+00 L2 loss: 1.68197 Learning rate: 0.02 Mask loss: 0.13595 RPN box loss: 0.01362 RPN score loss: 0.00442 RPN total loss: 0.01803 Total loss: 2.07629 timestamp: 1655013927.7257702 iteration: 8065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18479 FastRCNN class loss: 0.12428 FastRCNN total loss: 0.30907 L1 loss: 0.0000e+00 L2 loss: 1.68165 Learning rate: 0.02 Mask loss: 0.19378 RPN box loss: 0.10318 RPN score loss: 0.01732 RPN total loss: 0.12049 Total loss: 2.30499 timestamp: 1655013931.0243962 iteration: 8070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18151 FastRCNN class loss: 0.12606 FastRCNN total loss: 0.30757 L1 loss: 0.0000e+00 L2 loss: 1.68135 Learning rate: 0.02 Mask loss: 0.2616 RPN box loss: 0.04593 RPN score loss: 0.01037 RPN total loss: 0.0563 Total loss: 2.30681 timestamp: 1655013934.417126 iteration: 8075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22511 FastRCNN class loss: 0.14019 FastRCNN total loss: 0.36531 L1 loss: 0.0000e+00 L2 loss: 1.68104 Learning rate: 0.02 Mask loss: 0.23209 RPN box loss: 0.02795 RPN score loss: 0.00669 RPN total loss: 0.03464 Total loss: 2.31308 timestamp: 1655013937.7076292 iteration: 8080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19391 FastRCNN class loss: 0.11086 FastRCNN total loss: 0.30477 L1 loss: 0.0000e+00 L2 loss: 1.68074 Learning rate: 0.02 Mask loss: 0.23484 RPN box loss: 0.03952 RPN score loss: 0.01074 RPN total loss: 0.05026 Total loss: 2.27061 timestamp: 1655013941.0514903 iteration: 8085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17937 FastRCNN class loss: 0.08308 FastRCNN total loss: 0.26245 L1 loss: 0.0000e+00 L2 loss: 1.68043 Learning rate: 0.02 Mask loss: 0.3183 RPN box loss: 0.02045 RPN score loss: 0.00461 RPN total loss: 0.02506 Total loss: 2.28624 timestamp: 1655013944.2828891 iteration: 8090 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20106 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.2749 L1 loss: 0.0000e+00 L2 loss: 1.68011 Learning rate: 0.02 Mask loss: 0.17297 RPN box loss: 0.02251 RPN score loss: 0.00873 RPN total loss: 0.03124 Total loss: 2.15922 timestamp: 1655013947.592553 iteration: 8095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12771 FastRCNN class loss: 0.09373 FastRCNN total loss: 0.22143 L1 loss: 0.0000e+00 L2 loss: 1.67979 Learning rate: 0.02 Mask loss: 0.18354 RPN box loss: 0.06553 RPN score loss: 0.01705 RPN total loss: 0.08258 Total loss: 2.16733 timestamp: 1655013950.9270272 iteration: 8100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16441 FastRCNN class loss: 0.05832 FastRCNN total loss: 0.22273 L1 loss: 0.0000e+00 L2 loss: 1.67946 Learning rate: 0.02 Mask loss: 0.16966 RPN box loss: 0.03079 RPN score loss: 0.005 RPN total loss: 0.0358 Total loss: 2.10764 timestamp: 1655013954.2968354 iteration: 8105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12461 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.2053 L1 loss: 0.0000e+00 L2 loss: 1.67914 Learning rate: 0.02 Mask loss: 0.33215 RPN box loss: 0.09676 RPN score loss: 0.05425 RPN total loss: 0.15101 Total loss: 2.3676 timestamp: 1655013957.5563233 iteration: 8110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17289 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.24736 L1 loss: 0.0000e+00 L2 loss: 1.67881 Learning rate: 0.02 Mask loss: 0.21719 RPN box loss: 0.05793 RPN score loss: 0.01469 RPN total loss: 0.07261 Total loss: 2.21598 timestamp: 1655013960.9756396 iteration: 8115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21753 FastRCNN class loss: 0.09492 FastRCNN total loss: 0.31245 L1 loss: 0.0000e+00 L2 loss: 1.67852 Learning rate: 0.02 Mask loss: 0.17779 RPN box loss: 0.0505 RPN score loss: 0.01239 RPN total loss: 0.06289 Total loss: 2.23165 timestamp: 1655013964.3083797 iteration: 8120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19333 FastRCNN class loss: 0.09052 FastRCNN total loss: 0.28385 L1 loss: 0.0000e+00 L2 loss: 1.67822 Learning rate: 0.02 Mask loss: 0.18799 RPN box loss: 0.06664 RPN score loss: 0.00638 RPN total loss: 0.07302 Total loss: 2.22308 timestamp: 1655013967.626182 iteration: 8125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2666 FastRCNN class loss: 0.19712 FastRCNN total loss: 0.46371 L1 loss: 0.0000e+00 L2 loss: 1.67792 Learning rate: 0.02 Mask loss: 0.28892 RPN box loss: 0.07436 RPN score loss: 0.04893 RPN total loss: 0.12329 Total loss: 2.55385 timestamp: 1655013970.9040964 iteration: 8130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21606 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.27463 L1 loss: 0.0000e+00 L2 loss: 1.67759 Learning rate: 0.02 Mask loss: 0.13432 RPN box loss: 0.02205 RPN score loss: 0.00849 RPN total loss: 0.03053 Total loss: 2.11709 timestamp: 1655013974.2458224 iteration: 8135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21893 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.29046 L1 loss: 0.0000e+00 L2 loss: 1.67727 Learning rate: 0.02 Mask loss: 0.21194 RPN box loss: 0.03607 RPN score loss: 0.00524 RPN total loss: 0.04131 Total loss: 2.22098 timestamp: 1655013977.7054594 iteration: 8140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09533 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.1573 L1 loss: 0.0000e+00 L2 loss: 1.67699 Learning rate: 0.02 Mask loss: 0.12766 RPN box loss: 0.06412 RPN score loss: 0.01413 RPN total loss: 0.07824 Total loss: 2.0402 timestamp: 1655013980.9984992 iteration: 8145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17256 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.25295 L1 loss: 0.0000e+00 L2 loss: 1.67668 Learning rate: 0.02 Mask loss: 0.36015 RPN box loss: 0.06916 RPN score loss: 0.01279 RPN total loss: 0.08194 Total loss: 2.37173 timestamp: 1655013984.4057226 iteration: 8150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22344 FastRCNN class loss: 0.18379 FastRCNN total loss: 0.40724 L1 loss: 0.0000e+00 L2 loss: 1.67636 Learning rate: 0.02 Mask loss: 0.19016 RPN box loss: 0.09142 RPN score loss: 0.03027 RPN total loss: 0.12169 Total loss: 2.39545 timestamp: 1655013987.7460613 iteration: 8155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14649 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.19858 L1 loss: 0.0000e+00 L2 loss: 1.67605 Learning rate: 0.02 Mask loss: 0.19328 RPN box loss: 0.02712 RPN score loss: 0.01481 RPN total loss: 0.04193 Total loss: 2.10984 timestamp: 1655013991.242409 iteration: 8160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30344 FastRCNN class loss: 0.10639 FastRCNN total loss: 0.40982 L1 loss: 0.0000e+00 L2 loss: 1.67574 Learning rate: 0.02 Mask loss: 0.16258 RPN box loss: 0.04699 RPN score loss: 0.01666 RPN total loss: 0.06365 Total loss: 2.3118 timestamp: 1655013994.635817 iteration: 8165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22067 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.30166 L1 loss: 0.0000e+00 L2 loss: 1.67542 Learning rate: 0.02 Mask loss: 0.23848 RPN box loss: 0.03606 RPN score loss: 0.01548 RPN total loss: 0.05154 Total loss: 2.2671 timestamp: 1655013997.920199 iteration: 8170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20184 FastRCNN class loss: 0.09318 FastRCNN total loss: 0.29502 L1 loss: 0.0000e+00 L2 loss: 1.67509 Learning rate: 0.02 Mask loss: 0.20069 RPN box loss: 0.05654 RPN score loss: 0.02416 RPN total loss: 0.0807 Total loss: 2.25151 timestamp: 1655014001.2168803 iteration: 8175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17619 FastRCNN class loss: 0.10259 FastRCNN total loss: 0.27877 L1 loss: 0.0000e+00 L2 loss: 1.6748 Learning rate: 0.02 Mask loss: 0.16947 RPN box loss: 0.02704 RPN score loss: 0.0059 RPN total loss: 0.03293 Total loss: 2.15597 timestamp: 1655014004.4604402 iteration: 8180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.12467 FastRCNN total loss: 0.28404 L1 loss: 0.0000e+00 L2 loss: 1.67449 Learning rate: 0.02 Mask loss: 0.24838 RPN box loss: 0.04683 RPN score loss: 0.0141 RPN total loss: 0.06094 Total loss: 2.26784 timestamp: 1655014007.8211608 iteration: 8185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23072 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.3358 L1 loss: 0.0000e+00 L2 loss: 1.67417 Learning rate: 0.02 Mask loss: 0.1898 RPN box loss: 0.01111 RPN score loss: 0.00312 RPN total loss: 0.01423 Total loss: 2.21399 timestamp: 1655014011.0711443 iteration: 8190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21969 FastRCNN class loss: 0.13355 FastRCNN total loss: 0.35325 L1 loss: 0.0000e+00 L2 loss: 1.67385 Learning rate: 0.02 Mask loss: 0.20179 RPN box loss: 0.04237 RPN score loss: 0.00835 RPN total loss: 0.05072 Total loss: 2.27961 timestamp: 1655014014.4373229 iteration: 8195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14775 FastRCNN class loss: 0.05141 FastRCNN total loss: 0.19916 L1 loss: 0.0000e+00 L2 loss: 1.67354 Learning rate: 0.02 Mask loss: 0.14463 RPN box loss: 0.02486 RPN score loss: 0.00777 RPN total loss: 0.03262 Total loss: 2.04996 timestamp: 1655014017.6928966 iteration: 8200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1139 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.1907 L1 loss: 0.0000e+00 L2 loss: 1.67323 Learning rate: 0.02 Mask loss: 0.14524 RPN box loss: 0.04935 RPN score loss: 0.01491 RPN total loss: 0.06426 Total loss: 2.07343 timestamp: 1655014021.208587 iteration: 8205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14869 FastRCNN class loss: 0.09133 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 1.67291 Learning rate: 0.02 Mask loss: 0.2382 RPN box loss: 0.17182 RPN score loss: 0.0106 RPN total loss: 0.18242 Total loss: 2.33354 timestamp: 1655014024.6147492 iteration: 8210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20447 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.27784 L1 loss: 0.0000e+00 L2 loss: 1.67258 Learning rate: 0.02 Mask loss: 0.16791 RPN box loss: 0.07807 RPN score loss: 0.01061 RPN total loss: 0.08868 Total loss: 2.20701 timestamp: 1655014027.832046 iteration: 8215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16981 FastRCNN class loss: 0.05394 FastRCNN total loss: 0.22375 L1 loss: 0.0000e+00 L2 loss: 1.67226 Learning rate: 0.02 Mask loss: 0.13278 RPN box loss: 0.04013 RPN score loss: 0.00794 RPN total loss: 0.04807 Total loss: 2.07687 timestamp: 1655014031.2546685 iteration: 8220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20396 FastRCNN class loss: 0.10784 FastRCNN total loss: 0.3118 L1 loss: 0.0000e+00 L2 loss: 1.67198 Learning rate: 0.02 Mask loss: 0.2073 RPN box loss: 0.02031 RPN score loss: 0.00525 RPN total loss: 0.02557 Total loss: 2.21664 timestamp: 1655014034.579292 iteration: 8225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13376 FastRCNN class loss: 0.09859 FastRCNN total loss: 0.23235 L1 loss: 0.0000e+00 L2 loss: 1.67168 Learning rate: 0.02 Mask loss: 0.20112 RPN box loss: 0.0327 RPN score loss: 0.00834 RPN total loss: 0.04104 Total loss: 2.14619 timestamp: 1655014037.92183 iteration: 8230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21061 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.309 L1 loss: 0.0000e+00 L2 loss: 1.67137 Learning rate: 0.02 Mask loss: 0.21536 RPN box loss: 0.05021 RPN score loss: 0.00632 RPN total loss: 0.05653 Total loss: 2.25225 timestamp: 1655014041.2261918 iteration: 8235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17091 FastRCNN class loss: 0.11417 FastRCNN total loss: 0.28508 L1 loss: 0.0000e+00 L2 loss: 1.67106 Learning rate: 0.02 Mask loss: 0.20499 RPN box loss: 0.04252 RPN score loss: 0.00543 RPN total loss: 0.04795 Total loss: 2.20908 timestamp: 1655014044.6380885 iteration: 8240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28574 FastRCNN class loss: 0.12962 FastRCNN total loss: 0.41537 L1 loss: 0.0000e+00 L2 loss: 1.67074 Learning rate: 0.02 Mask loss: 0.36992 RPN box loss: 0.03527 RPN score loss: 0.00884 RPN total loss: 0.04411 Total loss: 2.50014 timestamp: 1655014047.9168189 iteration: 8245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15514 FastRCNN class loss: 0.09316 FastRCNN total loss: 0.24829 L1 loss: 0.0000e+00 L2 loss: 1.67042 Learning rate: 0.02 Mask loss: 0.21315 RPN box loss: 0.01814 RPN score loss: 0.00608 RPN total loss: 0.02422 Total loss: 2.15609 timestamp: 1655014051.215765 iteration: 8250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23603 FastRCNN class loss: 0.14599 FastRCNN total loss: 0.38202 L1 loss: 0.0000e+00 L2 loss: 1.67011 Learning rate: 0.02 Mask loss: 0.25631 RPN box loss: 0.03067 RPN score loss: 0.0215 RPN total loss: 0.05217 Total loss: 2.36061 timestamp: 1655014054.5918393 iteration: 8255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15932 FastRCNN class loss: 0.04625 FastRCNN total loss: 0.20556 L1 loss: 0.0000e+00 L2 loss: 1.6698 Learning rate: 0.02 Mask loss: 0.205 RPN box loss: 0.07937 RPN score loss: 0.00779 RPN total loss: 0.08716 Total loss: 2.16751 timestamp: 1655014057.9413764 iteration: 8260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17107 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.2645 L1 loss: 0.0000e+00 L2 loss: 1.66948 Learning rate: 0.02 Mask loss: 0.17457 RPN box loss: 0.03642 RPN score loss: 0.008 RPN total loss: 0.04442 Total loss: 2.15297 timestamp: 1655014061.4114187 iteration: 8265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22485 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.30905 L1 loss: 0.0000e+00 L2 loss: 1.66918 Learning rate: 0.02 Mask loss: 0.23503 RPN box loss: 0.02747 RPN score loss: 0.01184 RPN total loss: 0.03931 Total loss: 2.25257 timestamp: 1655014064.6798735 iteration: 8270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27849 FastRCNN class loss: 0.12013 FastRCNN total loss: 0.39861 L1 loss: 0.0000e+00 L2 loss: 1.66887 Learning rate: 0.02 Mask loss: 0.35514 RPN box loss: 0.05826 RPN score loss: 0.01339 RPN total loss: 0.07165 Total loss: 2.49428 timestamp: 1655014068.1332037 iteration: 8275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20898 FastRCNN class loss: 0.09645 FastRCNN total loss: 0.30543 L1 loss: 0.0000e+00 L2 loss: 1.66855 Learning rate: 0.02 Mask loss: 0.23787 RPN box loss: 0.06186 RPN score loss: 0.00832 RPN total loss: 0.07018 Total loss: 2.28203 timestamp: 1655014071.3631015 iteration: 8280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24778 FastRCNN class loss: 0.10478 FastRCNN total loss: 0.35256 L1 loss: 0.0000e+00 L2 loss: 1.66823 Learning rate: 0.02 Mask loss: 0.38281 RPN box loss: 0.02575 RPN score loss: 0.00837 RPN total loss: 0.03411 Total loss: 2.43771 timestamp: 1655014074.7516887 iteration: 8285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22403 FastRCNN class loss: 0.0955 FastRCNN total loss: 0.31953 L1 loss: 0.0000e+00 L2 loss: 1.66791 Learning rate: 0.02 Mask loss: 0.22147 RPN box loss: 0.03696 RPN score loss: 0.0056 RPN total loss: 0.04256 Total loss: 2.25147 timestamp: 1655014078.0910523 iteration: 8290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20144 FastRCNN class loss: 0.10912 FastRCNN total loss: 0.31056 L1 loss: 0.0000e+00 L2 loss: 1.6676 Learning rate: 0.02 Mask loss: 0.24223 RPN box loss: 0.02646 RPN score loss: 0.00685 RPN total loss: 0.03331 Total loss: 2.2537 timestamp: 1655014081.5232592 iteration: 8295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15872 FastRCNN class loss: 0.1317 FastRCNN total loss: 0.29042 L1 loss: 0.0000e+00 L2 loss: 1.66729 Learning rate: 0.02 Mask loss: 0.24316 RPN box loss: 0.05827 RPN score loss: 0.0154 RPN total loss: 0.07367 Total loss: 2.27453 timestamp: 1655014084.9421399 iteration: 8300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22982 FastRCNN class loss: 0.21351 FastRCNN total loss: 0.44333 L1 loss: 0.0000e+00 L2 loss: 1.66699 Learning rate: 0.02 Mask loss: 0.30056 RPN box loss: 0.05309 RPN score loss: 0.02099 RPN total loss: 0.07408 Total loss: 2.48496 timestamp: 1655014088.1903756 iteration: 8305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26412 FastRCNN class loss: 0.08856 FastRCNN total loss: 0.35269 L1 loss: 0.0000e+00 L2 loss: 1.66668 Learning rate: 0.02 Mask loss: 0.15725 RPN box loss: 0.06821 RPN score loss: 0.00643 RPN total loss: 0.07464 Total loss: 2.25126 timestamp: 1655014091.550742 iteration: 8310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28407 FastRCNN class loss: 0.19641 FastRCNN total loss: 0.48048 L1 loss: 0.0000e+00 L2 loss: 1.66636 Learning rate: 0.02 Mask loss: 0.27829 RPN box loss: 0.07227 RPN score loss: 0.03104 RPN total loss: 0.10331 Total loss: 2.52843 timestamp: 1655014094.8036232 iteration: 8315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24873 FastRCNN class loss: 0.21832 FastRCNN total loss: 0.46706 L1 loss: 0.0000e+00 L2 loss: 1.66605 Learning rate: 0.02 Mask loss: 0.22765 RPN box loss: 0.06724 RPN score loss: 0.01484 RPN total loss: 0.08208 Total loss: 2.44284 timestamp: 1655014098.1231325 iteration: 8320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19916 FastRCNN class loss: 0.11799 FastRCNN total loss: 0.31715 L1 loss: 0.0000e+00 L2 loss: 1.66573 Learning rate: 0.02 Mask loss: 0.20231 RPN box loss: 0.03127 RPN score loss: 0.01518 RPN total loss: 0.04645 Total loss: 2.23163 timestamp: 1655014101.4226732 iteration: 8325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19078 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.28019 L1 loss: 0.0000e+00 L2 loss: 1.66544 Learning rate: 0.02 Mask loss: 0.17186 RPN box loss: 0.02294 RPN score loss: 0.00826 RPN total loss: 0.0312 Total loss: 2.14869 timestamp: 1655014104.8447838 iteration: 8330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12718 FastRCNN class loss: 0.10243 FastRCNN total loss: 0.22961 L1 loss: 0.0000e+00 L2 loss: 1.66512 Learning rate: 0.02 Mask loss: 0.19249 RPN box loss: 0.01048 RPN score loss: 0.00334 RPN total loss: 0.01382 Total loss: 2.10103 timestamp: 1655014108.265319 iteration: 8335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14423 FastRCNN class loss: 0.0941 FastRCNN total loss: 0.23832 L1 loss: 0.0000e+00 L2 loss: 1.66481 Learning rate: 0.02 Mask loss: 0.1817 RPN box loss: 0.07074 RPN score loss: 0.00918 RPN total loss: 0.07992 Total loss: 2.16475 timestamp: 1655014111.521506 iteration: 8340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18306 FastRCNN class loss: 0.12882 FastRCNN total loss: 0.31188 L1 loss: 0.0000e+00 L2 loss: 1.66451 Learning rate: 0.02 Mask loss: 0.25799 RPN box loss: 0.03181 RPN score loss: 0.01021 RPN total loss: 0.04203 Total loss: 2.2764 timestamp: 1655014114.952119 iteration: 8345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19549 FastRCNN class loss: 0.09939 FastRCNN total loss: 0.29488 L1 loss: 0.0000e+00 L2 loss: 1.66422 Learning rate: 0.02 Mask loss: 0.19404 RPN box loss: 0.0786 RPN score loss: 0.00916 RPN total loss: 0.08776 Total loss: 2.24091 timestamp: 1655014118.271597 iteration: 8350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23351 FastRCNN class loss: 0.12093 FastRCNN total loss: 0.35444 L1 loss: 0.0000e+00 L2 loss: 1.66393 Learning rate: 0.02 Mask loss: 0.24805 RPN box loss: 0.04804 RPN score loss: 0.01051 RPN total loss: 0.05855 Total loss: 2.32497 timestamp: 1655014121.6350276 iteration: 8355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22479 FastRCNN class loss: 0.09491 FastRCNN total loss: 0.31969 L1 loss: 0.0000e+00 L2 loss: 1.66361 Learning rate: 0.02 Mask loss: 0.19206 RPN box loss: 0.04678 RPN score loss: 0.00994 RPN total loss: 0.05672 Total loss: 2.23208 timestamp: 1655014124.9426231 iteration: 8360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16947 FastRCNN class loss: 0.1336 FastRCNN total loss: 0.30308 L1 loss: 0.0000e+00 L2 loss: 1.6633 Learning rate: 0.02 Mask loss: 0.2089 RPN box loss: 0.02394 RPN score loss: 0.01136 RPN total loss: 0.03531 Total loss: 2.21058 timestamp: 1655014128.2923756 iteration: 8365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12524 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.1954 L1 loss: 0.0000e+00 L2 loss: 1.66299 Learning rate: 0.02 Mask loss: 0.17131 RPN box loss: 0.02607 RPN score loss: 0.00816 RPN total loss: 0.03424 Total loss: 2.06393 timestamp: 1655014131.6333919 iteration: 8370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21748 FastRCNN class loss: 0.15408 FastRCNN total loss: 0.37156 L1 loss: 0.0000e+00 L2 loss: 1.66268 Learning rate: 0.02 Mask loss: 0.1901 RPN box loss: 0.03083 RPN score loss: 0.00828 RPN total loss: 0.03912 Total loss: 2.26346 timestamp: 1655014134.9489913 iteration: 8375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15412 FastRCNN class loss: 0.06078 FastRCNN total loss: 0.2149 L1 loss: 0.0000e+00 L2 loss: 1.66236 Learning rate: 0.02 Mask loss: 0.17511 RPN box loss: 0.01526 RPN score loss: 0.00551 RPN total loss: 0.02077 Total loss: 2.07315 timestamp: 1655014138.3369102 iteration: 8380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18719 FastRCNN class loss: 0.11945 FastRCNN total loss: 0.30663 L1 loss: 0.0000e+00 L2 loss: 1.66205 Learning rate: 0.02 Mask loss: 0.19938 RPN box loss: 0.04235 RPN score loss: 0.01763 RPN total loss: 0.05998 Total loss: 2.22804 timestamp: 1655014141.5601687 iteration: 8385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25541 FastRCNN class loss: 0.10524 FastRCNN total loss: 0.36065 L1 loss: 0.0000e+00 L2 loss: 1.66174 Learning rate: 0.02 Mask loss: 0.21585 RPN box loss: 0.01759 RPN score loss: 0.00908 RPN total loss: 0.02667 Total loss: 2.2649 timestamp: 1655014144.956252 iteration: 8390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19521 FastRCNN class loss: 0.10721 FastRCNN total loss: 0.30241 L1 loss: 0.0000e+00 L2 loss: 1.66146 Learning rate: 0.02 Mask loss: 0.20332 RPN box loss: 0.0478 RPN score loss: 0.00887 RPN total loss: 0.05667 Total loss: 2.22386 timestamp: 1655014148.218223 iteration: 8395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1165 FastRCNN class loss: 0.04601 FastRCNN total loss: 0.16251 L1 loss: 0.0000e+00 L2 loss: 1.66115 Learning rate: 0.02 Mask loss: 0.1083 RPN box loss: 0.10331 RPN score loss: 0.00845 RPN total loss: 0.11176 Total loss: 2.04372 timestamp: 1655014151.540929 iteration: 8400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24453 FastRCNN class loss: 0.08094 FastRCNN total loss: 0.32547 L1 loss: 0.0000e+00 L2 loss: 1.66083 Learning rate: 0.02 Mask loss: 0.20315 RPN box loss: 0.1022 RPN score loss: 0.01756 RPN total loss: 0.11977 Total loss: 2.30921 timestamp: 1655014154.8831685 iteration: 8405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21421 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.28453 L1 loss: 0.0000e+00 L2 loss: 1.66053 Learning rate: 0.02 Mask loss: 0.19658 RPN box loss: 0.01056 RPN score loss: 0.00334 RPN total loss: 0.0139 Total loss: 2.15554 timestamp: 1655014158.2252083 iteration: 8410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24106 FastRCNN class loss: 0.16738 FastRCNN total loss: 0.40844 L1 loss: 0.0000e+00 L2 loss: 1.66022 Learning rate: 0.02 Mask loss: 0.24854 RPN box loss: 0.02455 RPN score loss: 0.03069 RPN total loss: 0.05524 Total loss: 2.37244 timestamp: 1655014161.5644877 iteration: 8415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22042 FastRCNN class loss: 0.15912 FastRCNN total loss: 0.37954 L1 loss: 0.0000e+00 L2 loss: 1.65989 Learning rate: 0.02 Mask loss: 0.25152 RPN box loss: 0.08378 RPN score loss: 0.01398 RPN total loss: 0.09776 Total loss: 2.3887 timestamp: 1655014165.0354111 iteration: 8420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13691 FastRCNN class loss: 0.091 FastRCNN total loss: 0.22791 L1 loss: 0.0000e+00 L2 loss: 1.65957 Learning rate: 0.02 Mask loss: 0.16698 RPN box loss: 0.09776 RPN score loss: 0.03108 RPN total loss: 0.12884 Total loss: 2.1833 timestamp: 1655014168.484917 iteration: 8425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10309 FastRCNN class loss: 0.09765 FastRCNN total loss: 0.20074 L1 loss: 0.0000e+00 L2 loss: 1.65927 Learning rate: 0.02 Mask loss: 0.11805 RPN box loss: 0.06336 RPN score loss: 0.00811 RPN total loss: 0.07147 Total loss: 2.04953 timestamp: 1655014171.8188083 iteration: 8430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19327 FastRCNN class loss: 0.09311 FastRCNN total loss: 0.28638 L1 loss: 0.0000e+00 L2 loss: 1.65895 Learning rate: 0.02 Mask loss: 0.28696 RPN box loss: 0.06022 RPN score loss: 0.01208 RPN total loss: 0.0723 Total loss: 2.30459 timestamp: 1655014175.216433 iteration: 8435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26633 FastRCNN class loss: 0.10268 FastRCNN total loss: 0.36901 L1 loss: 0.0000e+00 L2 loss: 1.65866 Learning rate: 0.02 Mask loss: 0.24222 RPN box loss: 0.05234 RPN score loss: 0.01664 RPN total loss: 0.06897 Total loss: 2.33887 timestamp: 1655014178.5237534 iteration: 8440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11394 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.16431 L1 loss: 0.0000e+00 L2 loss: 1.65839 Learning rate: 0.02 Mask loss: 0.16417 RPN box loss: 0.02602 RPN score loss: 0.0052 RPN total loss: 0.03121 Total loss: 2.01808 timestamp: 1655014181.8758144 iteration: 8445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20338 FastRCNN class loss: 0.09267 FastRCNN total loss: 0.29605 L1 loss: 0.0000e+00 L2 loss: 1.65808 Learning rate: 0.02 Mask loss: 0.15215 RPN box loss: 0.02408 RPN score loss: 0.00779 RPN total loss: 0.03187 Total loss: 2.13816 timestamp: 1655014185.1940758 iteration: 8450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30739 FastRCNN class loss: 0.11367 FastRCNN total loss: 0.42105 L1 loss: 0.0000e+00 L2 loss: 1.65776 Learning rate: 0.02 Mask loss: 0.2373 RPN box loss: 0.04541 RPN score loss: 0.00794 RPN total loss: 0.05335 Total loss: 2.36947 timestamp: 1655014188.6070385 iteration: 8455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1629 FastRCNN class loss: 0.09519 FastRCNN total loss: 0.25809 L1 loss: 0.0000e+00 L2 loss: 1.65743 Learning rate: 0.02 Mask loss: 0.18548 RPN box loss: 0.09709 RPN score loss: 0.01652 RPN total loss: 0.11361 Total loss: 2.21461 timestamp: 1655014191.8700254 iteration: 8460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15331 FastRCNN class loss: 0.10841 FastRCNN total loss: 0.26172 L1 loss: 0.0000e+00 L2 loss: 1.65714 Learning rate: 0.02 Mask loss: 0.3211 RPN box loss: 0.04101 RPN score loss: 0.0133 RPN total loss: 0.0543 Total loss: 2.29426 timestamp: 1655014195.2212887 iteration: 8465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14022 FastRCNN class loss: 0.06828 FastRCNN total loss: 0.20849 L1 loss: 0.0000e+00 L2 loss: 1.65683 Learning rate: 0.02 Mask loss: 0.15738 RPN box loss: 0.01969 RPN score loss: 0.0062 RPN total loss: 0.02588 Total loss: 2.04859 timestamp: 1655014198.5650911 iteration: 8470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17817 FastRCNN class loss: 0.10007 FastRCNN total loss: 0.27825 L1 loss: 0.0000e+00 L2 loss: 1.65652 Learning rate: 0.02 Mask loss: 0.26177 RPN box loss: 0.02836 RPN score loss: 0.00974 RPN total loss: 0.0381 Total loss: 2.23464 timestamp: 1655014201.863245 iteration: 8475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14069 FastRCNN class loss: 0.10039 FastRCNN total loss: 0.24107 L1 loss: 0.0000e+00 L2 loss: 1.6562 Learning rate: 0.02 Mask loss: 0.16556 RPN box loss: 0.0408 RPN score loss: 0.00939 RPN total loss: 0.05019 Total loss: 2.11303 timestamp: 1655014205.2262647 iteration: 8480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23309 FastRCNN class loss: 0.11504 FastRCNN total loss: 0.34813 L1 loss: 0.0000e+00 L2 loss: 1.65588 Learning rate: 0.02 Mask loss: 0.27569 RPN box loss: 0.02516 RPN score loss: 0.02494 RPN total loss: 0.0501 Total loss: 2.32979 timestamp: 1655014208.5416145 iteration: 8485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13409 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.20032 L1 loss: 0.0000e+00 L2 loss: 1.65555 Learning rate: 0.02 Mask loss: 0.19388 RPN box loss: 0.0478 RPN score loss: 0.01119 RPN total loss: 0.05899 Total loss: 2.10873 timestamp: 1655014211.9663124 iteration: 8490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16632 FastRCNN class loss: 0.12552 FastRCNN total loss: 0.29184 L1 loss: 0.0000e+00 L2 loss: 1.65526 Learning rate: 0.02 Mask loss: 0.19066 RPN box loss: 0.0386 RPN score loss: 0.00523 RPN total loss: 0.04383 Total loss: 2.18158 timestamp: 1655014215.248205 iteration: 8495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17482 FastRCNN class loss: 0.11792 FastRCNN total loss: 0.29273 L1 loss: 0.0000e+00 L2 loss: 1.65495 Learning rate: 0.02 Mask loss: 0.11394 RPN box loss: 0.0406 RPN score loss: 0.00467 RPN total loss: 0.04528 Total loss: 2.1069 timestamp: 1655014218.7585049 iteration: 8500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19087 FastRCNN class loss: 0.12655 FastRCNN total loss: 0.31741 L1 loss: 0.0000e+00 L2 loss: 1.65464 Learning rate: 0.02 Mask loss: 0.28956 RPN box loss: 0.05218 RPN score loss: 0.00765 RPN total loss: 0.05983 Total loss: 2.32144 timestamp: 1655014222.1519861 iteration: 8505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14014 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.21691 L1 loss: 0.0000e+00 L2 loss: 1.65432 Learning rate: 0.02 Mask loss: 0.18939 RPN box loss: 0.04044 RPN score loss: 0.01296 RPN total loss: 0.05341 Total loss: 2.11402 timestamp: 1655014225.4376578 iteration: 8510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24563 FastRCNN class loss: 0.13041 FastRCNN total loss: 0.37604 L1 loss: 0.0000e+00 L2 loss: 1.65402 Learning rate: 0.02 Mask loss: 0.2545 RPN box loss: 0.01732 RPN score loss: 0.00713 RPN total loss: 0.02444 Total loss: 2.30901 timestamp: 1655014228.7803679 iteration: 8515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14782 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.21853 L1 loss: 0.0000e+00 L2 loss: 1.65372 Learning rate: 0.02 Mask loss: 0.13227 RPN box loss: 0.08141 RPN score loss: 0.00871 RPN total loss: 0.09012 Total loss: 2.09463 timestamp: 1655014232.1116905 iteration: 8520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17238 FastRCNN class loss: 0.06195 FastRCNN total loss: 0.23433 L1 loss: 0.0000e+00 L2 loss: 1.65343 Learning rate: 0.02 Mask loss: 0.19389 RPN box loss: 0.01262 RPN score loss: 0.00557 RPN total loss: 0.0182 Total loss: 2.09985 timestamp: 1655014235.5602877 iteration: 8525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22092 FastRCNN class loss: 0.08817 FastRCNN total loss: 0.30909 L1 loss: 0.0000e+00 L2 loss: 1.65314 Learning rate: 0.02 Mask loss: 0.15646 RPN box loss: 0.01597 RPN score loss: 0.00966 RPN total loss: 0.02563 Total loss: 2.14432 timestamp: 1655014238.861157 iteration: 8530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24034 FastRCNN class loss: 0.10544 FastRCNN total loss: 0.34578 L1 loss: 0.0000e+00 L2 loss: 1.65283 Learning rate: 0.02 Mask loss: 0.17581 RPN box loss: 0.03396 RPN score loss: 0.00895 RPN total loss: 0.04291 Total loss: 2.21733 timestamp: 1655014242.2719095 iteration: 8535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15888 FastRCNN class loss: 0.11942 FastRCNN total loss: 0.2783 L1 loss: 0.0000e+00 L2 loss: 1.65252 Learning rate: 0.02 Mask loss: 0.26422 RPN box loss: 0.02498 RPN score loss: 0.00499 RPN total loss: 0.02997 Total loss: 2.22501 timestamp: 1655014245.581934 iteration: 8540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27742 FastRCNN class loss: 0.11943 FastRCNN total loss: 0.39684 L1 loss: 0.0000e+00 L2 loss: 1.65221 Learning rate: 0.02 Mask loss: 0.17728 RPN box loss: 0.03101 RPN score loss: 0.0064 RPN total loss: 0.03741 Total loss: 2.26375 timestamp: 1655014248.9824698 iteration: 8545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18215 FastRCNN class loss: 0.09517 FastRCNN total loss: 0.27733 L1 loss: 0.0000e+00 L2 loss: 1.6519 Learning rate: 0.02 Mask loss: 0.18514 RPN box loss: 0.01499 RPN score loss: 0.01145 RPN total loss: 0.02644 Total loss: 2.14081 timestamp: 1655014252.3784785 iteration: 8550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15957 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.2541 L1 loss: 0.0000e+00 L2 loss: 1.65162 Learning rate: 0.02 Mask loss: 0.2204 RPN box loss: 0.03826 RPN score loss: 0.01304 RPN total loss: 0.05131 Total loss: 2.17743 timestamp: 1655014255.637918 iteration: 8555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1883 FastRCNN class loss: 0.12135 FastRCNN total loss: 0.30966 L1 loss: 0.0000e+00 L2 loss: 1.65132 Learning rate: 0.02 Mask loss: 0.23041 RPN box loss: 0.13486 RPN score loss: 0.02203 RPN total loss: 0.15689 Total loss: 2.34828 timestamp: 1655014259.0781343 iteration: 8560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25553 FastRCNN class loss: 0.12388 FastRCNN total loss: 0.3794 L1 loss: 0.0000e+00 L2 loss: 1.65101 Learning rate: 0.02 Mask loss: 0.3096 RPN box loss: 0.04367 RPN score loss: 0.02553 RPN total loss: 0.0692 Total loss: 2.40922 timestamp: 1655014262.3445005 iteration: 8565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13368 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.21576 L1 loss: 0.0000e+00 L2 loss: 1.65071 Learning rate: 0.02 Mask loss: 0.17025 RPN box loss: 0.0241 RPN score loss: 0.00292 RPN total loss: 0.02703 Total loss: 2.06375 timestamp: 1655014265.76021 iteration: 8570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.17875 L1 loss: 0.0000e+00 L2 loss: 1.6504 Learning rate: 0.02 Mask loss: 0.15583 RPN box loss: 0.1358 RPN score loss: 0.00712 RPN total loss: 0.14293 Total loss: 2.1279 timestamp: 1655014269.0484962 iteration: 8575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18579 FastRCNN class loss: 0.11611 FastRCNN total loss: 0.3019 L1 loss: 0.0000e+00 L2 loss: 1.65009 Learning rate: 0.02 Mask loss: 0.17799 RPN box loss: 0.06438 RPN score loss: 0.0137 RPN total loss: 0.07808 Total loss: 2.20806 timestamp: 1655014272.4521728 iteration: 8580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20457 FastRCNN class loss: 0.14126 FastRCNN total loss: 0.34582 L1 loss: 0.0000e+00 L2 loss: 1.64979 Learning rate: 0.02 Mask loss: 0.19698 RPN box loss: 0.02764 RPN score loss: 0.01531 RPN total loss: 0.04296 Total loss: 2.23555 timestamp: 1655014275.6853585 iteration: 8585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18882 FastRCNN class loss: 0.13118 FastRCNN total loss: 0.32001 L1 loss: 0.0000e+00 L2 loss: 1.64949 Learning rate: 0.02 Mask loss: 0.32418 RPN box loss: 0.12459 RPN score loss: 0.01655 RPN total loss: 0.14115 Total loss: 2.43482 timestamp: 1655014279.1567843 iteration: 8590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26656 FastRCNN class loss: 0.15518 FastRCNN total loss: 0.42173 L1 loss: 0.0000e+00 L2 loss: 1.64917 Learning rate: 0.02 Mask loss: 0.31087 RPN box loss: 0.04734 RPN score loss: 0.01256 RPN total loss: 0.05989 Total loss: 2.44167 timestamp: 1655014282.5757854 iteration: 8595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17329 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.26488 L1 loss: 0.0000e+00 L2 loss: 1.64887 Learning rate: 0.02 Mask loss: 0.24228 RPN box loss: 0.02827 RPN score loss: 0.00555 RPN total loss: 0.03382 Total loss: 2.18985 timestamp: 1655014285.8288357 iteration: 8600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20083 FastRCNN class loss: 0.16183 FastRCNN total loss: 0.36266 L1 loss: 0.0000e+00 L2 loss: 1.64856 Learning rate: 0.02 Mask loss: 0.29145 RPN box loss: 0.0749 RPN score loss: 0.03013 RPN total loss: 0.10503 Total loss: 2.4077 timestamp: 1655014289.1516657 iteration: 8605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12735 FastRCNN class loss: 0.13896 FastRCNN total loss: 0.26631 L1 loss: 0.0000e+00 L2 loss: 1.64825 Learning rate: 0.02 Mask loss: 0.18757 RPN box loss: 0.02531 RPN score loss: 0.01858 RPN total loss: 0.04388 Total loss: 2.14601 timestamp: 1655014292.4429567 iteration: 8610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.20751 L1 loss: 0.0000e+00 L2 loss: 1.64796 Learning rate: 0.02 Mask loss: 0.26759 RPN box loss: 0.08536 RPN score loss: 0.01003 RPN total loss: 0.0954 Total loss: 2.21846 timestamp: 1655014295.8372808 iteration: 8615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21029 FastRCNN class loss: 0.08606 FastRCNN total loss: 0.29635 L1 loss: 0.0000e+00 L2 loss: 1.64767 Learning rate: 0.02 Mask loss: 0.17339 RPN box loss: 0.06477 RPN score loss: 0.02272 RPN total loss: 0.08749 Total loss: 2.2049 timestamp: 1655014299.153674 iteration: 8620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16155 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.25417 L1 loss: 0.0000e+00 L2 loss: 1.64736 Learning rate: 0.02 Mask loss: 0.12316 RPN box loss: 0.09883 RPN score loss: 0.00911 RPN total loss: 0.10794 Total loss: 2.13263 timestamp: 1655014302.564651 iteration: 8625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1408 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.22328 L1 loss: 0.0000e+00 L2 loss: 1.64705 Learning rate: 0.02 Mask loss: 0.22788 RPN box loss: 0.01983 RPN score loss: 0.00591 RPN total loss: 0.02574 Total loss: 2.12395 timestamp: 1655014305.8124933 iteration: 8630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12325 FastRCNN class loss: 0.0961 FastRCNN total loss: 0.21934 L1 loss: 0.0000e+00 L2 loss: 1.64672 Learning rate: 0.02 Mask loss: 0.20633 RPN box loss: 0.01524 RPN score loss: 0.00396 RPN total loss: 0.0192 Total loss: 2.09159 timestamp: 1655014309.2504313 iteration: 8635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24587 FastRCNN class loss: 0.14472 FastRCNN total loss: 0.39059 L1 loss: 0.0000e+00 L2 loss: 1.64642 Learning rate: 0.02 Mask loss: 0.22788 RPN box loss: 0.07744 RPN score loss: 0.02886 RPN total loss: 0.1063 Total loss: 2.37118 timestamp: 1655014312.5165346 iteration: 8640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20229 FastRCNN class loss: 0.10301 FastRCNN total loss: 0.3053 L1 loss: 0.0000e+00 L2 loss: 1.64612 Learning rate: 0.02 Mask loss: 0.18192 RPN box loss: 0.01995 RPN score loss: 0.01005 RPN total loss: 0.03 Total loss: 2.16334 timestamp: 1655014315.7387946 iteration: 8645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1796 FastRCNN class loss: 0.05824 FastRCNN total loss: 0.23784 L1 loss: 0.0000e+00 L2 loss: 1.64582 Learning rate: 0.02 Mask loss: 0.17429 RPN box loss: 0.08104 RPN score loss: 0.01305 RPN total loss: 0.09409 Total loss: 2.15204 timestamp: 1655014319.1398602 iteration: 8650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20362 FastRCNN class loss: 0.12622 FastRCNN total loss: 0.32983 L1 loss: 0.0000e+00 L2 loss: 1.64553 Learning rate: 0.02 Mask loss: 0.21197 RPN box loss: 0.0165 RPN score loss: 0.00594 RPN total loss: 0.02244 Total loss: 2.20977 timestamp: 1655014322.445507 iteration: 8655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19114 FastRCNN class loss: 0.15253 FastRCNN total loss: 0.34367 L1 loss: 0.0000e+00 L2 loss: 1.64521 Learning rate: 0.02 Mask loss: 0.25943 RPN box loss: 0.06746 RPN score loss: 0.01717 RPN total loss: 0.08464 Total loss: 2.33295 timestamp: 1655014325.7901704 iteration: 8660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26915 FastRCNN class loss: 0.16361 FastRCNN total loss: 0.43277 L1 loss: 0.0000e+00 L2 loss: 1.64491 Learning rate: 0.02 Mask loss: 0.26183 RPN box loss: 0.05793 RPN score loss: 0.01497 RPN total loss: 0.0729 Total loss: 2.41241 timestamp: 1655014329.0910738 iteration: 8665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11726 FastRCNN class loss: 0.0528 FastRCNN total loss: 0.17006 L1 loss: 0.0000e+00 L2 loss: 1.6446 Learning rate: 0.02 Mask loss: 0.1642 RPN box loss: 0.02436 RPN score loss: 0.0058 RPN total loss: 0.03015 Total loss: 2.00901 timestamp: 1655014332.4107935 iteration: 8670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20345 FastRCNN class loss: 0.14295 FastRCNN total loss: 0.34641 L1 loss: 0.0000e+00 L2 loss: 1.64428 Learning rate: 0.02 Mask loss: 0.24442 RPN box loss: 0.06325 RPN score loss: 0.00886 RPN total loss: 0.07211 Total loss: 2.30722 timestamp: 1655014335.724711 iteration: 8675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15683 FastRCNN class loss: 0.06584 FastRCNN total loss: 0.22266 L1 loss: 0.0000e+00 L2 loss: 1.64396 Learning rate: 0.02 Mask loss: 0.17158 RPN box loss: 0.09805 RPN score loss: 0.01111 RPN total loss: 0.10916 Total loss: 2.14737 timestamp: 1655014339.0904844 iteration: 8680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13387 FastRCNN class loss: 0.04619 FastRCNN total loss: 0.18006 L1 loss: 0.0000e+00 L2 loss: 1.64366 Learning rate: 0.02 Mask loss: 0.12171 RPN box loss: 0.02358 RPN score loss: 0.00308 RPN total loss: 0.02666 Total loss: 1.97209 timestamp: 1655014342.4784315 iteration: 8685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27758 FastRCNN class loss: 0.16489 FastRCNN total loss: 0.44247 L1 loss: 0.0000e+00 L2 loss: 1.64336 Learning rate: 0.02 Mask loss: 0.24728 RPN box loss: 0.03484 RPN score loss: 0.01365 RPN total loss: 0.04848 Total loss: 2.38159 timestamp: 1655014345.7871504 iteration: 8690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1574 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.26894 L1 loss: 0.0000e+00 L2 loss: 1.64307 Learning rate: 0.02 Mask loss: 0.21224 RPN box loss: 0.01204 RPN score loss: 0.00429 RPN total loss: 0.01633 Total loss: 2.14059 timestamp: 1655014349.1623733 iteration: 8695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22012 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.31215 L1 loss: 0.0000e+00 L2 loss: 1.64277 Learning rate: 0.02 Mask loss: 0.22601 RPN box loss: 0.02076 RPN score loss: 0.00234 RPN total loss: 0.0231 Total loss: 2.20403 timestamp: 1655014352.5132256 iteration: 8700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21348 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.30582 L1 loss: 0.0000e+00 L2 loss: 1.64247 Learning rate: 0.02 Mask loss: 0.22527 RPN box loss: 0.01207 RPN score loss: 0.01059 RPN total loss: 0.02266 Total loss: 2.19622 timestamp: 1655014356.0660706 iteration: 8705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18736 FastRCNN class loss: 0.08588 FastRCNN total loss: 0.27324 L1 loss: 0.0000e+00 L2 loss: 1.64217 Learning rate: 0.02 Mask loss: 0.21535 RPN box loss: 0.02574 RPN score loss: 0.00348 RPN total loss: 0.02923 Total loss: 2.15999 timestamp: 1655014359.3265047 iteration: 8710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16706 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.22238 L1 loss: 0.0000e+00 L2 loss: 1.64187 Learning rate: 0.02 Mask loss: 0.15624 RPN box loss: 0.00498 RPN score loss: 0.00633 RPN total loss: 0.01132 Total loss: 2.03181 timestamp: 1655014362.7386923 iteration: 8715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24404 FastRCNN class loss: 0.12907 FastRCNN total loss: 0.3731 L1 loss: 0.0000e+00 L2 loss: 1.64157 Learning rate: 0.02 Mask loss: 0.23785 RPN box loss: 0.04942 RPN score loss: 0.01848 RPN total loss: 0.06791 Total loss: 2.32044 timestamp: 1655014366.0638843 iteration: 8720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23643 FastRCNN class loss: 0.11909 FastRCNN total loss: 0.35552 L1 loss: 0.0000e+00 L2 loss: 1.64127 Learning rate: 0.02 Mask loss: 0.20359 RPN box loss: 0.04062 RPN score loss: 0.01729 RPN total loss: 0.05792 Total loss: 2.2583 timestamp: 1655014369.375531 iteration: 8725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09059 FastRCNN class loss: 0.10201 FastRCNN total loss: 0.1926 L1 loss: 0.0000e+00 L2 loss: 1.64098 Learning rate: 0.02 Mask loss: 0.11165 RPN box loss: 0.01171 RPN score loss: 0.00524 RPN total loss: 0.01695 Total loss: 1.96218 timestamp: 1655014372.8173182 iteration: 8730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30516 FastRCNN class loss: 0.16743 FastRCNN total loss: 0.47259 L1 loss: 0.0000e+00 L2 loss: 1.64068 Learning rate: 0.02 Mask loss: 0.16874 RPN box loss: 0.05148 RPN score loss: 0.01789 RPN total loss: 0.06937 Total loss: 2.35137 timestamp: 1655014376.121993 iteration: 8735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20204 FastRCNN class loss: 0.13522 FastRCNN total loss: 0.33727 L1 loss: 0.0000e+00 L2 loss: 1.64036 Learning rate: 0.02 Mask loss: 0.22379 RPN box loss: 0.05822 RPN score loss: 0.01997 RPN total loss: 0.07819 Total loss: 2.27961 timestamp: 1655014379.5025444 iteration: 8740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20521 FastRCNN class loss: 0.11972 FastRCNN total loss: 0.32493 L1 loss: 0.0000e+00 L2 loss: 1.64006 Learning rate: 0.02 Mask loss: 0.23701 RPN box loss: 0.08599 RPN score loss: 0.0134 RPN total loss: 0.09939 Total loss: 2.30139 timestamp: 1655014382.763924 iteration: 8745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12374 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.18553 L1 loss: 0.0000e+00 L2 loss: 1.63976 Learning rate: 0.02 Mask loss: 0.16446 RPN box loss: 0.01011 RPN score loss: 0.00598 RPN total loss: 0.0161 Total loss: 2.00585 timestamp: 1655014386.0974762 iteration: 8750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15113 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.25703 L1 loss: 0.0000e+00 L2 loss: 1.63945 Learning rate: 0.02 Mask loss: 0.24047 RPN box loss: 0.09366 RPN score loss: 0.01273 RPN total loss: 0.1064 Total loss: 2.24334 timestamp: 1655014389.373962 iteration: 8755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15963 FastRCNN class loss: 0.09403 FastRCNN total loss: 0.25366 L1 loss: 0.0000e+00 L2 loss: 1.63913 Learning rate: 0.02 Mask loss: 0.19762 RPN box loss: 0.01585 RPN score loss: 0.00351 RPN total loss: 0.01936 Total loss: 2.10977 timestamp: 1655014392.758779 iteration: 8760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18285 FastRCNN class loss: 0.06195 FastRCNN total loss: 0.2448 L1 loss: 0.0000e+00 L2 loss: 1.63882 Learning rate: 0.02 Mask loss: 0.13614 RPN box loss: 0.01706 RPN score loss: 0.00281 RPN total loss: 0.01987 Total loss: 2.03963 timestamp: 1655014396.045302 iteration: 8765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22948 FastRCNN class loss: 0.16592 FastRCNN total loss: 0.39539 L1 loss: 0.0000e+00 L2 loss: 1.63851 Learning rate: 0.02 Mask loss: 0.22655 RPN box loss: 0.03863 RPN score loss: 0.01799 RPN total loss: 0.05662 Total loss: 2.31708 timestamp: 1655014399.401345 iteration: 8770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.16761 L1 loss: 0.0000e+00 L2 loss: 1.63822 Learning rate: 0.02 Mask loss: 0.17879 RPN box loss: 0.04962 RPN score loss: 0.01069 RPN total loss: 0.06031 Total loss: 2.04493 timestamp: 1655014402.7724192 iteration: 8775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15271 FastRCNN class loss: 0.16312 FastRCNN total loss: 0.31583 L1 loss: 0.0000e+00 L2 loss: 1.63791 Learning rate: 0.02 Mask loss: 0.20494 RPN box loss: 0.05142 RPN score loss: 0.01882 RPN total loss: 0.07023 Total loss: 2.22891 timestamp: 1655014406.0296128 iteration: 8780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16637 FastRCNN class loss: 0.09473 FastRCNN total loss: 0.2611 L1 loss: 0.0000e+00 L2 loss: 1.63762 Learning rate: 0.02 Mask loss: 0.15288 RPN box loss: 0.02667 RPN score loss: 0.00824 RPN total loss: 0.0349 Total loss: 2.0865 timestamp: 1655014409.422398 iteration: 8785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12739 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.20396 L1 loss: 0.0000e+00 L2 loss: 1.63731 Learning rate: 0.02 Mask loss: 0.13199 RPN box loss: 0.05553 RPN score loss: 0.00653 RPN total loss: 0.06206 Total loss: 2.03532 timestamp: 1655014412.7637727 iteration: 8790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15072 FastRCNN class loss: 0.11491 FastRCNN total loss: 0.26562 L1 loss: 0.0000e+00 L2 loss: 1.637 Learning rate: 0.02 Mask loss: 0.20606 RPN box loss: 0.06019 RPN score loss: 0.01871 RPN total loss: 0.0789 Total loss: 2.18759 timestamp: 1655014416.1799164 iteration: 8795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17256 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.26437 L1 loss: 0.0000e+00 L2 loss: 1.63669 Learning rate: 0.02 Mask loss: 0.19807 RPN box loss: 0.15036 RPN score loss: 0.01461 RPN total loss: 0.16497 Total loss: 2.26411 timestamp: 1655014419.4525468 iteration: 8800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25474 FastRCNN class loss: 0.07164 FastRCNN total loss: 0.32638 L1 loss: 0.0000e+00 L2 loss: 1.63638 Learning rate: 0.02 Mask loss: 0.15785 RPN box loss: 0.02806 RPN score loss: 0.00753 RPN total loss: 0.03559 Total loss: 2.1562 timestamp: 1655014422.840669 iteration: 8805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20797 FastRCNN class loss: 0.09192 FastRCNN total loss: 0.2999 L1 loss: 0.0000e+00 L2 loss: 1.63608 Learning rate: 0.02 Mask loss: 0.21947 RPN box loss: 0.0662 RPN score loss: 0.00989 RPN total loss: 0.0761 Total loss: 2.23154 timestamp: 1655014426.1313078 iteration: 8810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13661 FastRCNN class loss: 0.07194 FastRCNN total loss: 0.20855 L1 loss: 0.0000e+00 L2 loss: 1.63575 Learning rate: 0.02 Mask loss: 0.24907 RPN box loss: 0.01616 RPN score loss: 0.0039 RPN total loss: 0.02005 Total loss: 2.11342 timestamp: 1655014429.5524292 iteration: 8815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18292 FastRCNN class loss: 0.12533 FastRCNN total loss: 0.30825 L1 loss: 0.0000e+00 L2 loss: 1.63545 Learning rate: 0.02 Mask loss: 0.23765 RPN box loss: 0.05055 RPN score loss: 0.02596 RPN total loss: 0.07651 Total loss: 2.25786 timestamp: 1655014432.9424934 iteration: 8820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22124 FastRCNN class loss: 0.13003 FastRCNN total loss: 0.35127 L1 loss: 0.0000e+00 L2 loss: 1.63516 Learning rate: 0.02 Mask loss: 0.31618 RPN box loss: 0.04091 RPN score loss: 0.04688 RPN total loss: 0.08779 Total loss: 2.39039 timestamp: 1655014436.2385995 iteration: 8825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17901 FastRCNN class loss: 0.09529 FastRCNN total loss: 0.2743 L1 loss: 0.0000e+00 L2 loss: 1.63485 Learning rate: 0.02 Mask loss: 0.30846 RPN box loss: 0.00462 RPN score loss: 0.00344 RPN total loss: 0.00806 Total loss: 2.22566 timestamp: 1655014439.6537218 iteration: 8830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13033 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.18806 L1 loss: 0.0000e+00 L2 loss: 1.63456 Learning rate: 0.02 Mask loss: 0.21402 RPN box loss: 0.01833 RPN score loss: 0.00689 RPN total loss: 0.02522 Total loss: 2.06185 timestamp: 1655014442.884712 iteration: 8835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16633 FastRCNN class loss: 0.10306 FastRCNN total loss: 0.26939 L1 loss: 0.0000e+00 L2 loss: 1.63426 Learning rate: 0.02 Mask loss: 0.20718 RPN box loss: 0.0353 RPN score loss: 0.00938 RPN total loss: 0.04468 Total loss: 2.1555 timestamp: 1655014446.3788111 iteration: 8840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24566 FastRCNN class loss: 0.08892 FastRCNN total loss: 0.33458 L1 loss: 0.0000e+00 L2 loss: 1.63394 Learning rate: 0.02 Mask loss: 0.22044 RPN box loss: 0.04519 RPN score loss: 0.0108 RPN total loss: 0.05599 Total loss: 2.24495 timestamp: 1655014449.6593072 iteration: 8845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18504 FastRCNN class loss: 0.08445 FastRCNN total loss: 0.26949 L1 loss: 0.0000e+00 L2 loss: 1.63366 Learning rate: 0.02 Mask loss: 0.22225 RPN box loss: 0.1106 RPN score loss: 0.00932 RPN total loss: 0.11992 Total loss: 2.24531 timestamp: 1655014453.1301527 iteration: 8850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19006 FastRCNN class loss: 0.0741 FastRCNN total loss: 0.26416 L1 loss: 0.0000e+00 L2 loss: 1.63335 Learning rate: 0.02 Mask loss: 0.15817 RPN box loss: 0.04337 RPN score loss: 0.01111 RPN total loss: 0.05448 Total loss: 2.11016 timestamp: 1655014456.4002492 iteration: 8855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31065 FastRCNN class loss: 0.11048 FastRCNN total loss: 0.42114 L1 loss: 0.0000e+00 L2 loss: 1.63305 Learning rate: 0.02 Mask loss: 0.22668 RPN box loss: 0.08412 RPN score loss: 0.0113 RPN total loss: 0.09542 Total loss: 2.37628 timestamp: 1655014459.8343344 iteration: 8860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12257 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 1.63272 Learning rate: 0.02 Mask loss: 0.2191 RPN box loss: 0.05865 RPN score loss: 0.00833 RPN total loss: 0.06698 Total loss: 2.11608 timestamp: 1655014463.2814093 iteration: 8865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13185 FastRCNN class loss: 0.05122 FastRCNN total loss: 0.18307 L1 loss: 0.0000e+00 L2 loss: 1.63242 Learning rate: 0.02 Mask loss: 0.15479 RPN box loss: 0.04629 RPN score loss: 0.00829 RPN total loss: 0.05458 Total loss: 2.02485 timestamp: 1655014466.5764425 iteration: 8870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25047 FastRCNN class loss: 0.14908 FastRCNN total loss: 0.39955 L1 loss: 0.0000e+00 L2 loss: 1.63214 Learning rate: 0.02 Mask loss: 0.22157 RPN box loss: 0.07148 RPN score loss: 0.03432 RPN total loss: 0.10581 Total loss: 2.35907 timestamp: 1655014469.8288097 iteration: 8875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15855 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.2145 L1 loss: 0.0000e+00 L2 loss: 1.63184 Learning rate: 0.02 Mask loss: 0.12319 RPN box loss: 0.04022 RPN score loss: 0.00567 RPN total loss: 0.04589 Total loss: 2.01543 timestamp: 1655014473.053801 iteration: 8880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17083 FastRCNN class loss: 0.13953 FastRCNN total loss: 0.31035 L1 loss: 0.0000e+00 L2 loss: 1.63153 Learning rate: 0.02 Mask loss: 0.2388 RPN box loss: 0.06378 RPN score loss: 0.02303 RPN total loss: 0.08681 Total loss: 2.26749 timestamp: 1655014476.42207 iteration: 8885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1687 FastRCNN class loss: 0.06254 FastRCNN total loss: 0.23123 L1 loss: 0.0000e+00 L2 loss: 1.63122 Learning rate: 0.02 Mask loss: 0.13115 RPN box loss: 0.07262 RPN score loss: 0.01033 RPN total loss: 0.08295 Total loss: 2.07656 timestamp: 1655014479.7402718 iteration: 8890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16832 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.24761 L1 loss: 0.0000e+00 L2 loss: 1.63092 Learning rate: 0.02 Mask loss: 0.29872 RPN box loss: 0.03422 RPN score loss: 0.01112 RPN total loss: 0.04534 Total loss: 2.22258 timestamp: 1655014483.0204446 iteration: 8895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21648 FastRCNN class loss: 0.09576 FastRCNN total loss: 0.31223 L1 loss: 0.0000e+00 L2 loss: 1.6306 Learning rate: 0.02 Mask loss: 0.22714 RPN box loss: 0.09549 RPN score loss: 0.0125 RPN total loss: 0.108 Total loss: 2.27797 timestamp: 1655014486.388941 iteration: 8900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13101 FastRCNN class loss: 0.0983 FastRCNN total loss: 0.22932 L1 loss: 0.0000e+00 L2 loss: 1.63028 Learning rate: 0.02 Mask loss: 0.21548 RPN box loss: 0.00735 RPN score loss: 0.00662 RPN total loss: 0.01397 Total loss: 2.08905 timestamp: 1655014489.6563993 iteration: 8905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20803 FastRCNN class loss: 0.12931 FastRCNN total loss: 0.33733 L1 loss: 0.0000e+00 L2 loss: 1.62999 Learning rate: 0.02 Mask loss: 0.18642 RPN box loss: 0.05921 RPN score loss: 0.01292 RPN total loss: 0.07212 Total loss: 2.22586 timestamp: 1655014493.059527 iteration: 8910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1444 FastRCNN class loss: 0.12373 FastRCNN total loss: 0.26813 L1 loss: 0.0000e+00 L2 loss: 1.6297 Learning rate: 0.02 Mask loss: 0.21764 RPN box loss: 0.08055 RPN score loss: 0.03191 RPN total loss: 0.11247 Total loss: 2.22794 timestamp: 1655014496.3193293 iteration: 8915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21468 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.29697 L1 loss: 0.0000e+00 L2 loss: 1.62939 Learning rate: 0.02 Mask loss: 0.18568 RPN box loss: 0.03967 RPN score loss: 0.0085 RPN total loss: 0.04816 Total loss: 2.1602 timestamp: 1655014499.7312884 iteration: 8920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18464 FastRCNN class loss: 0.14505 FastRCNN total loss: 0.32969 L1 loss: 0.0000e+00 L2 loss: 1.62909 Learning rate: 0.02 Mask loss: 0.20558 RPN box loss: 0.03929 RPN score loss: 0.0087 RPN total loss: 0.04798 Total loss: 2.21234 timestamp: 1655014503.0462854 iteration: 8925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07887 FastRCNN class loss: 0.05711 FastRCNN total loss: 0.13598 L1 loss: 0.0000e+00 L2 loss: 1.62878 Learning rate: 0.02 Mask loss: 0.12948 RPN box loss: 0.0139 RPN score loss: 0.0047 RPN total loss: 0.0186 Total loss: 1.91283 timestamp: 1655014506.4641562 iteration: 8930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13391 FastRCNN class loss: 0.09468 FastRCNN total loss: 0.22858 L1 loss: 0.0000e+00 L2 loss: 1.62848 Learning rate: 0.02 Mask loss: 0.16249 RPN box loss: 0.06636 RPN score loss: 0.00418 RPN total loss: 0.07054 Total loss: 2.0901 timestamp: 1655014509.7430894 iteration: 8935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24145 FastRCNN class loss: 0.12348 FastRCNN total loss: 0.36493 L1 loss: 0.0000e+00 L2 loss: 1.62819 Learning rate: 0.02 Mask loss: 0.40628 RPN box loss: 0.07458 RPN score loss: 0.02392 RPN total loss: 0.0985 Total loss: 2.49791 timestamp: 1655014513.1099823 iteration: 8940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19988 FastRCNN class loss: 0.14354 FastRCNN total loss: 0.34342 L1 loss: 0.0000e+00 L2 loss: 1.62789 Learning rate: 0.02 Mask loss: 0.26349 RPN box loss: 0.04879 RPN score loss: 0.00659 RPN total loss: 0.05538 Total loss: 2.29019 timestamp: 1655014516.688733 iteration: 8945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24291 FastRCNN class loss: 0.11937 FastRCNN total loss: 0.36229 L1 loss: 0.0000e+00 L2 loss: 1.62758 Learning rate: 0.02 Mask loss: 0.40067 RPN box loss: 0.03001 RPN score loss: 0.01117 RPN total loss: 0.04118 Total loss: 2.43172 timestamp: 1655014519.9302921 iteration: 8950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12685 FastRCNN class loss: 0.08935 FastRCNN total loss: 0.2162 L1 loss: 0.0000e+00 L2 loss: 1.62731 Learning rate: 0.02 Mask loss: 0.18227 RPN box loss: 0.02916 RPN score loss: 0.01438 RPN total loss: 0.04354 Total loss: 2.06932 timestamp: 1655014523.3805487 iteration: 8955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22045 FastRCNN class loss: 0.1166 FastRCNN total loss: 0.33705 L1 loss: 0.0000e+00 L2 loss: 1.62701 Learning rate: 0.02 Mask loss: 0.22527 RPN box loss: 0.03793 RPN score loss: 0.01322 RPN total loss: 0.05115 Total loss: 2.24047 timestamp: 1655014526.6879961 iteration: 8960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27364 FastRCNN class loss: 0.1044 FastRCNN total loss: 0.37804 L1 loss: 0.0000e+00 L2 loss: 1.62672 Learning rate: 0.02 Mask loss: 0.22084 RPN box loss: 0.06216 RPN score loss: 0.00648 RPN total loss: 0.06864 Total loss: 2.29424 timestamp: 1655014530.0178053 iteration: 8965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23247 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.29542 L1 loss: 0.0000e+00 L2 loss: 1.62643 Learning rate: 0.02 Mask loss: 0.19031 RPN box loss: 0.04855 RPN score loss: 0.01123 RPN total loss: 0.05979 Total loss: 2.17195 timestamp: 1655014533.2937546 iteration: 8970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16597 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.25478 L1 loss: 0.0000e+00 L2 loss: 1.62613 Learning rate: 0.02 Mask loss: 0.19041 RPN box loss: 0.02754 RPN score loss: 0.00397 RPN total loss: 0.0315 Total loss: 2.10283 timestamp: 1655014536.6708279 iteration: 8975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23502 FastRCNN class loss: 0.17058 FastRCNN total loss: 0.4056 L1 loss: 0.0000e+00 L2 loss: 1.62583 Learning rate: 0.02 Mask loss: 0.20786 RPN box loss: 0.01587 RPN score loss: 0.00564 RPN total loss: 0.02151 Total loss: 2.26079 timestamp: 1655014539.950501 iteration: 8980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16246 FastRCNN class loss: 0.07241 FastRCNN total loss: 0.23487 L1 loss: 0.0000e+00 L2 loss: 1.62551 Learning rate: 0.02 Mask loss: 0.15687 RPN box loss: 0.01164 RPN score loss: 0.00593 RPN total loss: 0.01757 Total loss: 2.03483 timestamp: 1655014543.3783455 iteration: 8985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18346 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.27267 L1 loss: 0.0000e+00 L2 loss: 1.62523 Learning rate: 0.02 Mask loss: 0.13513 RPN box loss: 0.04385 RPN score loss: 0.00442 RPN total loss: 0.04827 Total loss: 2.0813 timestamp: 1655014546.9126756 iteration: 8990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14515 FastRCNN class loss: 0.10708 FastRCNN total loss: 0.25222 L1 loss: 0.0000e+00 L2 loss: 1.62492 Learning rate: 0.02 Mask loss: 0.16312 RPN box loss: 0.05105 RPN score loss: 0.0153 RPN total loss: 0.06635 Total loss: 2.10661 timestamp: 1655014550.2306159 iteration: 8995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13205 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.2279 L1 loss: 0.0000e+00 L2 loss: 1.62461 Learning rate: 0.02 Mask loss: 0.15872 RPN box loss: 0.0718 RPN score loss: 0.01509 RPN total loss: 0.08688 Total loss: 2.09811 timestamp: 1655014553.6357918 iteration: 9000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15214 FastRCNN class loss: 0.05253 FastRCNN total loss: 0.20466 L1 loss: 0.0000e+00 L2 loss: 1.6243 Learning rate: 0.02 Mask loss: 0.16043 RPN box loss: 0.01743 RPN score loss: 0.00729 RPN total loss: 0.02472 Total loss: 2.01411 timestamp: 1655014556.9584692 iteration: 9005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29095 FastRCNN class loss: 0.13071 FastRCNN total loss: 0.42166 L1 loss: 0.0000e+00 L2 loss: 1.62401 Learning rate: 0.02 Mask loss: 0.2607 RPN box loss: 0.03122 RPN score loss: 0.00646 RPN total loss: 0.03767 Total loss: 2.34404 timestamp: 1655014560.38077 iteration: 9010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19333 FastRCNN class loss: 0.11665 FastRCNN total loss: 0.30998 L1 loss: 0.0000e+00 L2 loss: 1.62373 Learning rate: 0.02 Mask loss: 0.17585 RPN box loss: 0.03971 RPN score loss: 0.00734 RPN total loss: 0.04705 Total loss: 2.15661 timestamp: 1655014563.6465523 iteration: 9015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15501 FastRCNN class loss: 0.11411 FastRCNN total loss: 0.26912 L1 loss: 0.0000e+00 L2 loss: 1.62343 Learning rate: 0.02 Mask loss: 0.39522 RPN box loss: 0.0358 RPN score loss: 0.00904 RPN total loss: 0.04485 Total loss: 2.33262 timestamp: 1655014566.9675138 iteration: 9020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11151 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.18318 L1 loss: 0.0000e+00 L2 loss: 1.62313 Learning rate: 0.02 Mask loss: 0.20193 RPN box loss: 0.09981 RPN score loss: 0.00708 RPN total loss: 0.10689 Total loss: 2.11513 timestamp: 1655014570.376626 iteration: 9025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2245 FastRCNN class loss: 0.14347 FastRCNN total loss: 0.36796 L1 loss: 0.0000e+00 L2 loss: 1.62282 Learning rate: 0.02 Mask loss: 0.24922 RPN box loss: 0.02252 RPN score loss: 0.01825 RPN total loss: 0.04077 Total loss: 2.28078 timestamp: 1655014573.6519043 iteration: 9030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05926 FastRCNN class loss: 0.04317 FastRCNN total loss: 0.10243 L1 loss: 0.0000e+00 L2 loss: 1.62253 Learning rate: 0.02 Mask loss: 0.15739 RPN box loss: 0.07537 RPN score loss: 0.00436 RPN total loss: 0.07973 Total loss: 1.96208 timestamp: 1655014577.1215332 iteration: 9035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23185 FastRCNN class loss: 0.15221 FastRCNN total loss: 0.38406 L1 loss: 0.0000e+00 L2 loss: 1.62222 Learning rate: 0.02 Mask loss: 0.26311 RPN box loss: 0.05791 RPN score loss: 0.0198 RPN total loss: 0.07771 Total loss: 2.34711 timestamp: 1655014580.4208539 iteration: 9040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26733 FastRCNN class loss: 0.21377 FastRCNN total loss: 0.48111 L1 loss: 0.0000e+00 L2 loss: 1.62192 Learning rate: 0.02 Mask loss: 0.24059 RPN box loss: 0.03386 RPN score loss: 0.01717 RPN total loss: 0.05103 Total loss: 2.39466 timestamp: 1655014583.795103 iteration: 9045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21455 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.30596 L1 loss: 0.0000e+00 L2 loss: 1.62164 Learning rate: 0.02 Mask loss: 0.19952 RPN box loss: 0.05482 RPN score loss: 0.01405 RPN total loss: 0.06887 Total loss: 2.19599 timestamp: 1655014587.0374658 iteration: 9050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19023 FastRCNN class loss: 0.13124 FastRCNN total loss: 0.32147 L1 loss: 0.0000e+00 L2 loss: 1.62134 Learning rate: 0.02 Mask loss: 0.2402 RPN box loss: 0.07185 RPN score loss: 0.01129 RPN total loss: 0.08314 Total loss: 2.26616 timestamp: 1655014590.494303 iteration: 9055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22854 FastRCNN class loss: 0.1325 FastRCNN total loss: 0.36103 L1 loss: 0.0000e+00 L2 loss: 1.62104 Learning rate: 0.02 Mask loss: 0.29984 RPN box loss: 0.01832 RPN score loss: 0.01018 RPN total loss: 0.02849 Total loss: 2.31041 timestamp: 1655014593.7080493 iteration: 9060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23657 FastRCNN class loss: 0.12616 FastRCNN total loss: 0.36274 L1 loss: 0.0000e+00 L2 loss: 1.62071 Learning rate: 0.02 Mask loss: 0.17951 RPN box loss: 0.04188 RPN score loss: 0.01205 RPN total loss: 0.05393 Total loss: 2.21689 timestamp: 1655014597.1148434 iteration: 9065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16955 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.24498 L1 loss: 0.0000e+00 L2 loss: 1.62041 Learning rate: 0.02 Mask loss: 0.14874 RPN box loss: 0.05494 RPN score loss: 0.0071 RPN total loss: 0.06205 Total loss: 2.07617 timestamp: 1655014600.5819385 iteration: 9070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13662 FastRCNN class loss: 0.09952 FastRCNN total loss: 0.23614 L1 loss: 0.0000e+00 L2 loss: 1.62011 Learning rate: 0.02 Mask loss: 0.23362 RPN box loss: 0.01719 RPN score loss: 0.00436 RPN total loss: 0.02155 Total loss: 2.11142 timestamp: 1655014603.85961 iteration: 9075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21387 FastRCNN class loss: 0.10789 FastRCNN total loss: 0.32177 L1 loss: 0.0000e+00 L2 loss: 1.61982 Learning rate: 0.02 Mask loss: 0.16969 RPN box loss: 0.06213 RPN score loss: 0.00434 RPN total loss: 0.06648 Total loss: 2.17776 timestamp: 1655014607.3236516 iteration: 9080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19339 FastRCNN class loss: 0.12194 FastRCNN total loss: 0.31533 L1 loss: 0.0000e+00 L2 loss: 1.61954 Learning rate: 0.02 Mask loss: 0.19418 RPN box loss: 0.01189 RPN score loss: 0.02219 RPN total loss: 0.03408 Total loss: 2.16313 timestamp: 1655014610.6690722 iteration: 9085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19652 FastRCNN class loss: 0.07852 FastRCNN total loss: 0.27504 L1 loss: 0.0000e+00 L2 loss: 1.61925 Learning rate: 0.02 Mask loss: 0.20441 RPN box loss: 0.08924 RPN score loss: 0.00737 RPN total loss: 0.09661 Total loss: 2.19531 timestamp: 1655014613.9652083 iteration: 9090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15553 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.21792 L1 loss: 0.0000e+00 L2 loss: 1.61895 Learning rate: 0.02 Mask loss: 0.21818 RPN box loss: 0.04344 RPN score loss: 0.00344 RPN total loss: 0.04688 Total loss: 2.10194 timestamp: 1655014617.2213945 iteration: 9095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19281 FastRCNN class loss: 0.10069 FastRCNN total loss: 0.2935 L1 loss: 0.0000e+00 L2 loss: 1.61865 Learning rate: 0.02 Mask loss: 0.11779 RPN box loss: 0.02623 RPN score loss: 0.00609 RPN total loss: 0.03232 Total loss: 2.06226 timestamp: 1655014620.6307406 iteration: 9100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12916 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.20742 L1 loss: 0.0000e+00 L2 loss: 1.61836 Learning rate: 0.02 Mask loss: 0.12661 RPN box loss: 0.01849 RPN score loss: 0.0035 RPN total loss: 0.02199 Total loss: 1.97439 timestamp: 1655014623.9012628 iteration: 9105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23758 FastRCNN class loss: 0.12509 FastRCNN total loss: 0.36266 L1 loss: 0.0000e+00 L2 loss: 1.61804 Learning rate: 0.02 Mask loss: 0.2419 RPN box loss: 0.09012 RPN score loss: 0.01571 RPN total loss: 0.10583 Total loss: 2.32843 timestamp: 1655014627.2920742 iteration: 9110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1816 FastRCNN class loss: 0.16802 FastRCNN total loss: 0.34962 L1 loss: 0.0000e+00 L2 loss: 1.61775 Learning rate: 0.02 Mask loss: 0.18974 RPN box loss: 0.11726 RPN score loss: 0.01583 RPN total loss: 0.13309 Total loss: 2.2902 timestamp: 1655014630.7541783 iteration: 9115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20609 FastRCNN class loss: 0.10891 FastRCNN total loss: 0.315 L1 loss: 0.0000e+00 L2 loss: 1.61746 Learning rate: 0.02 Mask loss: 0.15824 RPN box loss: 0.03656 RPN score loss: 0.01137 RPN total loss: 0.04793 Total loss: 2.13863 timestamp: 1655014633.9802043 iteration: 9120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16278 FastRCNN class loss: 0.09518 FastRCNN total loss: 0.25795 L1 loss: 0.0000e+00 L2 loss: 1.61716 Learning rate: 0.02 Mask loss: 0.16481 RPN box loss: 0.03879 RPN score loss: 0.00363 RPN total loss: 0.04242 Total loss: 2.08234 timestamp: 1655014637.3139298 iteration: 9125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20881 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.2925 L1 loss: 0.0000e+00 L2 loss: 1.61687 Learning rate: 0.02 Mask loss: 0.20591 RPN box loss: 0.04895 RPN score loss: 0.01121 RPN total loss: 0.06016 Total loss: 2.17544 timestamp: 1655014640.6899247 iteration: 9130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1571 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.23911 L1 loss: 0.0000e+00 L2 loss: 1.61657 Learning rate: 0.02 Mask loss: 0.27152 RPN box loss: 0.04467 RPN score loss: 0.01736 RPN total loss: 0.06202 Total loss: 2.18923 timestamp: 1655014644.1385033 iteration: 9135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18286 FastRCNN class loss: 0.09934 FastRCNN total loss: 0.2822 L1 loss: 0.0000e+00 L2 loss: 1.61627 Learning rate: 0.02 Mask loss: 0.25552 RPN box loss: 0.08773 RPN score loss: 0.01086 RPN total loss: 0.09859 Total loss: 2.25259 timestamp: 1655014647.4954386 iteration: 9140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25865 FastRCNN class loss: 0.11211 FastRCNN total loss: 0.37075 L1 loss: 0.0000e+00 L2 loss: 1.61597 Learning rate: 0.02 Mask loss: 0.18703 RPN box loss: 0.05676 RPN score loss: 0.00483 RPN total loss: 0.06159 Total loss: 2.23534 timestamp: 1655014651.0111585 iteration: 9145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16063 FastRCNN class loss: 0.09643 FastRCNN total loss: 0.25706 L1 loss: 0.0000e+00 L2 loss: 1.61568 Learning rate: 0.02 Mask loss: 0.21577 RPN box loss: 0.0638 RPN score loss: 0.00896 RPN total loss: 0.07276 Total loss: 2.16127 timestamp: 1655014654.2669315 iteration: 9150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17919 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.26286 L1 loss: 0.0000e+00 L2 loss: 1.61539 Learning rate: 0.02 Mask loss: 0.3129 RPN box loss: 0.03924 RPN score loss: 0.03041 RPN total loss: 0.06965 Total loss: 2.26079 timestamp: 1655014657.6268919 iteration: 9155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24864 FastRCNN class loss: 0.11445 FastRCNN total loss: 0.36309 L1 loss: 0.0000e+00 L2 loss: 1.61508 Learning rate: 0.02 Mask loss: 0.20595 RPN box loss: 0.01348 RPN score loss: 0.00277 RPN total loss: 0.01625 Total loss: 2.20037 timestamp: 1655014661.0417 iteration: 9160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13616 FastRCNN class loss: 0.09468 FastRCNN total loss: 0.23084 L1 loss: 0.0000e+00 L2 loss: 1.61479 Learning rate: 0.02 Mask loss: 0.21592 RPN box loss: 0.04692 RPN score loss: 0.00355 RPN total loss: 0.05047 Total loss: 2.11202 timestamp: 1655014664.2539978 iteration: 9165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.07944 FastRCNN total loss: 0.19897 L1 loss: 0.0000e+00 L2 loss: 1.61451 Learning rate: 0.02 Mask loss: 0.16697 RPN box loss: 0.07175 RPN score loss: 0.02762 RPN total loss: 0.09937 Total loss: 2.07982 timestamp: 1655014667.604452 iteration: 9170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12326 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.18407 L1 loss: 0.0000e+00 L2 loss: 1.6142 Learning rate: 0.02 Mask loss: 0.12497 RPN box loss: 0.01235 RPN score loss: 0.00603 RPN total loss: 0.01837 Total loss: 1.94162 timestamp: 1655014670.9245293 iteration: 9175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15946 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.24299 L1 loss: 0.0000e+00 L2 loss: 1.61391 Learning rate: 0.02 Mask loss: 0.12398 RPN box loss: 0.03545 RPN score loss: 0.01376 RPN total loss: 0.0492 Total loss: 2.03008 timestamp: 1655014674.3573482 iteration: 9180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1568 FastRCNN class loss: 0.11395 FastRCNN total loss: 0.27075 L1 loss: 0.0000e+00 L2 loss: 1.61362 Learning rate: 0.02 Mask loss: 0.16538 RPN box loss: 0.04473 RPN score loss: 0.01035 RPN total loss: 0.05509 Total loss: 2.10484 timestamp: 1655014677.6266983 iteration: 9185 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14647 FastRCNN class loss: 0.08376 FastRCNN total loss: 0.23023 L1 loss: 0.0000e+00 L2 loss: 1.61331 Learning rate: 0.02 Mask loss: 0.19658 RPN box loss: 0.10555 RPN score loss: 0.02352 RPN total loss: 0.12906 Total loss: 2.16919 timestamp: 1655014681.0329473 iteration: 9190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15856 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.25552 L1 loss: 0.0000e+00 L2 loss: 1.613 Learning rate: 0.02 Mask loss: 0.18787 RPN box loss: 0.03973 RPN score loss: 0.0139 RPN total loss: 0.05363 Total loss: 2.11002 timestamp: 1655014684.4141097 iteration: 9195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18024 FastRCNN class loss: 0.10026 FastRCNN total loss: 0.2805 L1 loss: 0.0000e+00 L2 loss: 1.6127 Learning rate: 0.02 Mask loss: 0.19634 RPN box loss: 0.04498 RPN score loss: 0.00993 RPN total loss: 0.05491 Total loss: 2.14444 timestamp: 1655014687.7384434 iteration: 9200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22005 FastRCNN class loss: 0.23124 FastRCNN total loss: 0.45128 L1 loss: 0.0000e+00 L2 loss: 1.6124 Learning rate: 0.02 Mask loss: 0.15628 RPN box loss: 0.05959 RPN score loss: 0.00792 RPN total loss: 0.06751 Total loss: 2.28747 timestamp: 1655014691.1086519 iteration: 9205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15502 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.22725 L1 loss: 0.0000e+00 L2 loss: 1.6121 Learning rate: 0.02 Mask loss: 0.16237 RPN box loss: 0.09652 RPN score loss: 0.00972 RPN total loss: 0.10623 Total loss: 2.10795 timestamp: 1655014694.3343403 iteration: 9210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13879 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.1979 L1 loss: 0.0000e+00 L2 loss: 1.6118 Learning rate: 0.02 Mask loss: 0.10251 RPN box loss: 0.01636 RPN score loss: 0.01294 RPN total loss: 0.0293 Total loss: 1.9415 timestamp: 1655014697.7364564 iteration: 9215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1312 FastRCNN class loss: 0.08837 FastRCNN total loss: 0.21957 L1 loss: 0.0000e+00 L2 loss: 1.6115 Learning rate: 0.02 Mask loss: 0.13635 RPN box loss: 0.01365 RPN score loss: 0.00523 RPN total loss: 0.01888 Total loss: 1.9863 timestamp: 1655014701.0599 iteration: 9220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29087 FastRCNN class loss: 0.09293 FastRCNN total loss: 0.38379 L1 loss: 0.0000e+00 L2 loss: 1.61124 Learning rate: 0.02 Mask loss: 0.20745 RPN box loss: 0.03049 RPN score loss: 0.00545 RPN total loss: 0.03594 Total loss: 2.23843 timestamp: 1655014704.5178277 iteration: 9225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17933 FastRCNN class loss: 0.08724 FastRCNN total loss: 0.26657 L1 loss: 0.0000e+00 L2 loss: 1.61095 Learning rate: 0.02 Mask loss: 0.24386 RPN box loss: 0.01434 RPN score loss: 0.0043 RPN total loss: 0.01863 Total loss: 2.14002 timestamp: 1655014707.8042269 iteration: 9230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16971 FastRCNN class loss: 0.09695 FastRCNN total loss: 0.26666 L1 loss: 0.0000e+00 L2 loss: 1.61064 Learning rate: 0.02 Mask loss: 0.15216 RPN box loss: 0.10569 RPN score loss: 0.0107 RPN total loss: 0.11639 Total loss: 2.14584 timestamp: 1655014711.118066 iteration: 9235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13771 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 1.61035 Learning rate: 0.02 Mask loss: 0.19494 RPN box loss: 0.01416 RPN score loss: 0.00373 RPN total loss: 0.01789 Total loss: 2.02372 timestamp: 1655014714.5563796 iteration: 9240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20147 FastRCNN class loss: 0.15791 FastRCNN total loss: 0.35937 L1 loss: 0.0000e+00 L2 loss: 1.61005 Learning rate: 0.02 Mask loss: 0.32248 RPN box loss: 0.05173 RPN score loss: 0.05737 RPN total loss: 0.1091 Total loss: 2.40101 timestamp: 1655014717.8025827 iteration: 9245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1505 FastRCNN class loss: 0.08934 FastRCNN total loss: 0.23984 L1 loss: 0.0000e+00 L2 loss: 1.60974 Learning rate: 0.02 Mask loss: 0.20762 RPN box loss: 0.06696 RPN score loss: 0.01379 RPN total loss: 0.08076 Total loss: 2.13796 timestamp: 1655014721.3654804 iteration: 9250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2266 FastRCNN class loss: 0.15309 FastRCNN total loss: 0.3797 L1 loss: 0.0000e+00 L2 loss: 1.60945 Learning rate: 0.02 Mask loss: 0.23369 RPN box loss: 0.05912 RPN score loss: 0.01329 RPN total loss: 0.07241 Total loss: 2.29525 timestamp: 1655014724.6433275 iteration: 9255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15171 FastRCNN class loss: 0.08926 FastRCNN total loss: 0.24097 L1 loss: 0.0000e+00 L2 loss: 1.60914 Learning rate: 0.02 Mask loss: 0.22766 RPN box loss: 0.03768 RPN score loss: 0.01545 RPN total loss: 0.05313 Total loss: 2.13089 timestamp: 1655014727.8907857 iteration: 9260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18704 FastRCNN class loss: 0.14283 FastRCNN total loss: 0.32988 L1 loss: 0.0000e+00 L2 loss: 1.60884 Learning rate: 0.02 Mask loss: 0.27516 RPN box loss: 0.03697 RPN score loss: 0.01477 RPN total loss: 0.05174 Total loss: 2.26561 timestamp: 1655014731.130813 iteration: 9265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12806 FastRCNN class loss: 0.08708 FastRCNN total loss: 0.21514 L1 loss: 0.0000e+00 L2 loss: 1.60855 Learning rate: 0.02 Mask loss: 0.19285 RPN box loss: 0.04537 RPN score loss: 0.01651 RPN total loss: 0.06188 Total loss: 2.07843 timestamp: 1655014734.5639544 iteration: 9270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17527 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.2953 L1 loss: 0.0000e+00 L2 loss: 1.60825 Learning rate: 0.02 Mask loss: 0.21747 RPN box loss: 0.02709 RPN score loss: 0.00379 RPN total loss: 0.03088 Total loss: 2.1519 timestamp: 1655014737.9148595 iteration: 9275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2385 FastRCNN class loss: 0.11701 FastRCNN total loss: 0.35551 L1 loss: 0.0000e+00 L2 loss: 1.60794 Learning rate: 0.02 Mask loss: 0.15478 RPN box loss: 0.0428 RPN score loss: 0.00498 RPN total loss: 0.04777 Total loss: 2.16602 timestamp: 1655014741.3342896 iteration: 9280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17376 FastRCNN class loss: 0.07982 FastRCNN total loss: 0.25358 L1 loss: 0.0000e+00 L2 loss: 1.60764 Learning rate: 0.02 Mask loss: 0.14767 RPN box loss: 0.02299 RPN score loss: 0.00486 RPN total loss: 0.02784 Total loss: 2.03674 timestamp: 1655014744.7660582 iteration: 9285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29047 FastRCNN class loss: 0.11181 FastRCNN total loss: 0.40228 L1 loss: 0.0000e+00 L2 loss: 1.60735 Learning rate: 0.02 Mask loss: 0.17408 RPN box loss: 0.06225 RPN score loss: 0.0096 RPN total loss: 0.07185 Total loss: 2.25555 timestamp: 1655014748.0819714 iteration: 9290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1903 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.26231 L1 loss: 0.0000e+00 L2 loss: 1.60707 Learning rate: 0.02 Mask loss: 0.15497 RPN box loss: 0.00821 RPN score loss: 0.00837 RPN total loss: 0.01658 Total loss: 2.04093 timestamp: 1655014751.5285974 iteration: 9295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14985 FastRCNN class loss: 0.07344 FastRCNN total loss: 0.2233 L1 loss: 0.0000e+00 L2 loss: 1.60678 Learning rate: 0.02 Mask loss: 0.14309 RPN box loss: 0.05886 RPN score loss: 0.01266 RPN total loss: 0.07152 Total loss: 2.04468 timestamp: 1655014754.8682923 iteration: 9300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11075 FastRCNN class loss: 0.11602 FastRCNN total loss: 0.22677 L1 loss: 0.0000e+00 L2 loss: 1.60647 Learning rate: 0.02 Mask loss: 0.23042 RPN box loss: 0.08974 RPN score loss: 0.0105 RPN total loss: 0.10024 Total loss: 2.1639 timestamp: 1655014758.2936413 iteration: 9305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14515 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.2164 L1 loss: 0.0000e+00 L2 loss: 1.60617 Learning rate: 0.02 Mask loss: 0.19774 RPN box loss: 0.05644 RPN score loss: 0.00469 RPN total loss: 0.06114 Total loss: 2.08145 timestamp: 1655014761.5444355 iteration: 9310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16236 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.22106 L1 loss: 0.0000e+00 L2 loss: 1.60589 Learning rate: 0.02 Mask loss: 0.14309 RPN box loss: 0.09386 RPN score loss: 0.00744 RPN total loss: 0.1013 Total loss: 2.07134 timestamp: 1655014765.013359 iteration: 9315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24032 FastRCNN class loss: 0.12328 FastRCNN total loss: 0.3636 L1 loss: 0.0000e+00 L2 loss: 1.6056 Learning rate: 0.02 Mask loss: 0.20524 RPN box loss: 0.09915 RPN score loss: 0.02413 RPN total loss: 0.12328 Total loss: 2.29772 timestamp: 1655014768.3986018 iteration: 9320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11917 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 1.60531 Learning rate: 0.02 Mask loss: 0.1734 RPN box loss: 0.01907 RPN score loss: 0.00619 RPN total loss: 0.02526 Total loss: 1.98644 timestamp: 1655014771.7168686 iteration: 9325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23577 FastRCNN class loss: 0.08557 FastRCNN total loss: 0.32134 L1 loss: 0.0000e+00 L2 loss: 1.60502 Learning rate: 0.02 Mask loss: 0.25181 RPN box loss: 0.04028 RPN score loss: 0.00719 RPN total loss: 0.04747 Total loss: 2.22563 timestamp: 1655014775.1057603 iteration: 9330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12907 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.21549 L1 loss: 0.0000e+00 L2 loss: 1.60473 Learning rate: 0.02 Mask loss: 0.16651 RPN box loss: 0.04548 RPN score loss: 0.00819 RPN total loss: 0.05367 Total loss: 2.04041 timestamp: 1655014778.4309206 iteration: 9335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18533 FastRCNN class loss: 0.09924 FastRCNN total loss: 0.28457 L1 loss: 0.0000e+00 L2 loss: 1.60445 Learning rate: 0.02 Mask loss: 0.12295 RPN box loss: 0.04337 RPN score loss: 0.00483 RPN total loss: 0.0482 Total loss: 2.06017 timestamp: 1655014781.8471441 iteration: 9340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16734 FastRCNN class loss: 0.08129 FastRCNN total loss: 0.24863 L1 loss: 0.0000e+00 L2 loss: 1.60413 Learning rate: 0.02 Mask loss: 0.21652 RPN box loss: 0.12421 RPN score loss: 0.00843 RPN total loss: 0.13264 Total loss: 2.20192 timestamp: 1655014785.133228 iteration: 9345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23503 FastRCNN class loss: 0.12182 FastRCNN total loss: 0.35685 L1 loss: 0.0000e+00 L2 loss: 1.60382 Learning rate: 0.02 Mask loss: 0.26547 RPN box loss: 0.02274 RPN score loss: 0.01952 RPN total loss: 0.04226 Total loss: 2.2684 timestamp: 1655014788.5244737 iteration: 9350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21408 FastRCNN class loss: 0.07367 FastRCNN total loss: 0.28774 L1 loss: 0.0000e+00 L2 loss: 1.60352 Learning rate: 0.02 Mask loss: 0.18567 RPN box loss: 0.03889 RPN score loss: 0.00436 RPN total loss: 0.04325 Total loss: 2.12018 timestamp: 1655014791.7753966 iteration: 9355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20667 FastRCNN class loss: 0.15254 FastRCNN total loss: 0.35921 L1 loss: 0.0000e+00 L2 loss: 1.60322 Learning rate: 0.02 Mask loss: 0.22503 RPN box loss: 0.05645 RPN score loss: 0.02207 RPN total loss: 0.07852 Total loss: 2.26598 timestamp: 1655014795.104521 iteration: 9360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17225 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 1.60293 Learning rate: 0.02 Mask loss: 0.15418 RPN box loss: 0.05036 RPN score loss: 0.01003 RPN total loss: 0.06039 Total loss: 2.04429 timestamp: 1655014798.5792346 iteration: 9365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21907 FastRCNN class loss: 0.12811 FastRCNN total loss: 0.34718 L1 loss: 0.0000e+00 L2 loss: 1.60264 Learning rate: 0.02 Mask loss: 0.21823 RPN box loss: 0.01612 RPN score loss: 0.00931 RPN total loss: 0.02543 Total loss: 2.19349 timestamp: 1655014801.8839326 iteration: 9370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17997 FastRCNN class loss: 0.09923 FastRCNN total loss: 0.2792 L1 loss: 0.0000e+00 L2 loss: 1.60235 Learning rate: 0.02 Mask loss: 0.31159 RPN box loss: 0.06343 RPN score loss: 0.01779 RPN total loss: 0.08123 Total loss: 2.27437 timestamp: 1655014805.2201526 iteration: 9375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21091 FastRCNN class loss: 0.17308 FastRCNN total loss: 0.38399 L1 loss: 0.0000e+00 L2 loss: 1.60207 Learning rate: 0.02 Mask loss: 0.26464 RPN box loss: 0.07159 RPN score loss: 0.01766 RPN total loss: 0.08925 Total loss: 2.33996 timestamp: 1655014808.48518 iteration: 9380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29939 FastRCNN class loss: 0.13236 FastRCNN total loss: 0.43175 L1 loss: 0.0000e+00 L2 loss: 1.60178 Learning rate: 0.02 Mask loss: 0.1788 RPN box loss: 0.02908 RPN score loss: 0.02648 RPN total loss: 0.05556 Total loss: 2.26788 timestamp: 1655014811.8525333 iteration: 9385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19697 FastRCNN class loss: 0.18247 FastRCNN total loss: 0.37944 L1 loss: 0.0000e+00 L2 loss: 1.60149 Learning rate: 0.02 Mask loss: 0.28601 RPN box loss: 0.0691 RPN score loss: 0.01284 RPN total loss: 0.08194 Total loss: 2.34888 timestamp: 1655014815.1373882 iteration: 9390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20943 FastRCNN class loss: 0.0721 FastRCNN total loss: 0.28153 L1 loss: 0.0000e+00 L2 loss: 1.60118 Learning rate: 0.02 Mask loss: 0.16918 RPN box loss: 0.04155 RPN score loss: 0.01116 RPN total loss: 0.05271 Total loss: 2.1046 timestamp: 1655014818.6309295 iteration: 9395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23837 FastRCNN class loss: 0.11231 FastRCNN total loss: 0.35069 L1 loss: 0.0000e+00 L2 loss: 1.60088 Learning rate: 0.02 Mask loss: 0.1777 RPN box loss: 0.07034 RPN score loss: 0.0431 RPN total loss: 0.11344 Total loss: 2.24269 timestamp: 1655014821.9332037 iteration: 9400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15187 FastRCNN class loss: 0.07724 FastRCNN total loss: 0.22912 L1 loss: 0.0000e+00 L2 loss: 1.60056 Learning rate: 0.02 Mask loss: 0.27028 RPN box loss: 0.0542 RPN score loss: 0.00615 RPN total loss: 0.06035 Total loss: 2.1603 timestamp: 1655014825.366757 iteration: 9405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13795 FastRCNN class loss: 0.0973 FastRCNN total loss: 0.23526 L1 loss: 0.0000e+00 L2 loss: 1.60027 Learning rate: 0.02 Mask loss: 0.27143 RPN box loss: 0.05672 RPN score loss: 0.00637 RPN total loss: 0.0631 Total loss: 2.17006 timestamp: 1655014828.75493 iteration: 9410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17729 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.27664 L1 loss: 0.0000e+00 L2 loss: 1.59997 Learning rate: 0.02 Mask loss: 0.17913 RPN box loss: 0.02342 RPN score loss: 0.00506 RPN total loss: 0.02849 Total loss: 2.08423 timestamp: 1655014832.0404367 iteration: 9415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14117 FastRCNN class loss: 0.07254 FastRCNN total loss: 0.21372 L1 loss: 0.0000e+00 L2 loss: 1.5997 Learning rate: 0.02 Mask loss: 0.16129 RPN box loss: 0.0107 RPN score loss: 0.00457 RPN total loss: 0.01527 Total loss: 1.98997 timestamp: 1655014835.4408953 iteration: 9420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14303 FastRCNN class loss: 0.11712 FastRCNN total loss: 0.26015 L1 loss: 0.0000e+00 L2 loss: 1.59941 Learning rate: 0.02 Mask loss: 0.22354 RPN box loss: 0.05601 RPN score loss: 0.02092 RPN total loss: 0.07693 Total loss: 2.16003 timestamp: 1655014838.7365253 iteration: 9425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18112 FastRCNN class loss: 0.10777 FastRCNN total loss: 0.28888 L1 loss: 0.0000e+00 L2 loss: 1.59913 Learning rate: 0.02 Mask loss: 0.27045 RPN box loss: 0.09013 RPN score loss: 0.01168 RPN total loss: 0.10181 Total loss: 2.26027 timestamp: 1655014842.172989 iteration: 9430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1665 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.23371 L1 loss: 0.0000e+00 L2 loss: 1.59884 Learning rate: 0.02 Mask loss: 0.22081 RPN box loss: 0.11199 RPN score loss: 0.01364 RPN total loss: 0.12563 Total loss: 2.17898 timestamp: 1655014845.4587812 iteration: 9435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19109 FastRCNN class loss: 0.15089 FastRCNN total loss: 0.34198 L1 loss: 0.0000e+00 L2 loss: 1.59854 Learning rate: 0.02 Mask loss: 0.25073 RPN box loss: 0.05346 RPN score loss: 0.01487 RPN total loss: 0.06833 Total loss: 2.25958 timestamp: 1655014848.86943 iteration: 9440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18083 FastRCNN class loss: 0.11374 FastRCNN total loss: 0.29457 L1 loss: 0.0000e+00 L2 loss: 1.59822 Learning rate: 0.02 Mask loss: 0.15251 RPN box loss: 0.04953 RPN score loss: 0.00777 RPN total loss: 0.0573 Total loss: 2.10261 timestamp: 1655014852.0961125 iteration: 9445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15128 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.22672 L1 loss: 0.0000e+00 L2 loss: 1.59789 Learning rate: 0.02 Mask loss: 0.22634 RPN box loss: 0.09189 RPN score loss: 0.01044 RPN total loss: 0.10233 Total loss: 2.15329 timestamp: 1655014855.4657214 iteration: 9450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.18703 L1 loss: 0.0000e+00 L2 loss: 1.59761 Learning rate: 0.02 Mask loss: 0.13279 RPN box loss: 0.01861 RPN score loss: 0.00669 RPN total loss: 0.02531 Total loss: 1.94273 timestamp: 1655014858.8118348 iteration: 9455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20163 FastRCNN class loss: 0.10103 FastRCNN total loss: 0.30265 L1 loss: 0.0000e+00 L2 loss: 1.59734 Learning rate: 0.02 Mask loss: 0.24924 RPN box loss: 0.04478 RPN score loss: 0.02149 RPN total loss: 0.06627 Total loss: 2.2155 timestamp: 1655014862.05474 iteration: 9460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.10805 FastRCNN total loss: 0.28166 L1 loss: 0.0000e+00 L2 loss: 1.59707 Learning rate: 0.02 Mask loss: 0.19103 RPN box loss: 0.05171 RPN score loss: 0.01142 RPN total loss: 0.06313 Total loss: 2.13289 timestamp: 1655014865.4616537 iteration: 9465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12628 FastRCNN class loss: 0.04725 FastRCNN total loss: 0.17353 L1 loss: 0.0000e+00 L2 loss: 1.59678 Learning rate: 0.02 Mask loss: 0.12141 RPN box loss: 0.08758 RPN score loss: 0.02899 RPN total loss: 0.11657 Total loss: 2.00829 timestamp: 1655014868.7148707 iteration: 9470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15869 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.22826 L1 loss: 0.0000e+00 L2 loss: 1.59648 Learning rate: 0.02 Mask loss: 0.12527 RPN box loss: 0.02656 RPN score loss: 0.00704 RPN total loss: 0.0336 Total loss: 1.98361 timestamp: 1655014872.1397555 iteration: 9475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14612 FastRCNN class loss: 0.17685 FastRCNN total loss: 0.32297 L1 loss: 0.0000e+00 L2 loss: 1.59618 Learning rate: 0.02 Mask loss: 0.30422 RPN box loss: 0.0699 RPN score loss: 0.13087 RPN total loss: 0.20077 Total loss: 2.42414 timestamp: 1655014875.3556707 iteration: 9480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14703 FastRCNN class loss: 0.07238 FastRCNN total loss: 0.21941 L1 loss: 0.0000e+00 L2 loss: 1.5959 Learning rate: 0.02 Mask loss: 0.19507 RPN box loss: 0.04672 RPN score loss: 0.01622 RPN total loss: 0.06294 Total loss: 2.07331 timestamp: 1655014878.7010517 iteration: 9485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22975 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.30727 L1 loss: 0.0000e+00 L2 loss: 1.59561 Learning rate: 0.02 Mask loss: 0.26783 RPN box loss: 0.02832 RPN score loss: 0.01209 RPN total loss: 0.04042 Total loss: 2.21113 timestamp: 1655014881.989739 iteration: 9490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22722 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.2999 L1 loss: 0.0000e+00 L2 loss: 1.59534 Learning rate: 0.02 Mask loss: 0.23928 RPN box loss: 0.04776 RPN score loss: 0.00847 RPN total loss: 0.05623 Total loss: 2.19074 timestamp: 1655014885.3255992 iteration: 9495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32868 FastRCNN class loss: 0.13231 FastRCNN total loss: 0.46099 L1 loss: 0.0000e+00 L2 loss: 1.59503 Learning rate: 0.02 Mask loss: 0.2212 RPN box loss: 0.0483 RPN score loss: 0.01612 RPN total loss: 0.06442 Total loss: 2.34163 timestamp: 1655014888.728116 iteration: 9500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26227 FastRCNN class loss: 0.12641 FastRCNN total loss: 0.38868 L1 loss: 0.0000e+00 L2 loss: 1.59473 Learning rate: 0.02 Mask loss: 0.26405 RPN box loss: 0.04838 RPN score loss: 0.01084 RPN total loss: 0.05922 Total loss: 2.30668 timestamp: 1655014891.9768689 iteration: 9505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.185 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.2722 L1 loss: 0.0000e+00 L2 loss: 1.59445 Learning rate: 0.02 Mask loss: 0.14447 RPN box loss: 0.04277 RPN score loss: 0.01314 RPN total loss: 0.05591 Total loss: 2.06703 timestamp: 1655014895.440363 iteration: 9510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23515 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.29377 L1 loss: 0.0000e+00 L2 loss: 1.59417 Learning rate: 0.02 Mask loss: 0.1809 RPN box loss: 0.02776 RPN score loss: 0.00238 RPN total loss: 0.03015 Total loss: 2.09899 timestamp: 1655014898.7419314 iteration: 9515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21321 FastRCNN class loss: 0.12095 FastRCNN total loss: 0.33416 L1 loss: 0.0000e+00 L2 loss: 1.59387 Learning rate: 0.02 Mask loss: 0.2315 RPN box loss: 0.05644 RPN score loss: 0.00742 RPN total loss: 0.06387 Total loss: 2.2234 timestamp: 1655014902.137853 iteration: 9520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11817 FastRCNN class loss: 0.09097 FastRCNN total loss: 0.20915 L1 loss: 0.0000e+00 L2 loss: 1.59358 Learning rate: 0.02 Mask loss: 0.20739 RPN box loss: 0.0286 RPN score loss: 0.00606 RPN total loss: 0.03466 Total loss: 2.04477 timestamp: 1655014905.371411 iteration: 9525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.08484 FastRCNN total loss: 0.19215 L1 loss: 0.0000e+00 L2 loss: 1.59329 Learning rate: 0.02 Mask loss: 0.15975 RPN box loss: 0.07149 RPN score loss: 0.00535 RPN total loss: 0.07685 Total loss: 2.02203 timestamp: 1655014908.8915284 iteration: 9530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19888 FastRCNN class loss: 0.08125 FastRCNN total loss: 0.28012 L1 loss: 0.0000e+00 L2 loss: 1.59299 Learning rate: 0.02 Mask loss: 0.20262 RPN box loss: 0.07349 RPN score loss: 0.00783 RPN total loss: 0.08132 Total loss: 2.15705 timestamp: 1655014912.1678905 iteration: 9535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15569 FastRCNN class loss: 0.10917 FastRCNN total loss: 0.26486 L1 loss: 0.0000e+00 L2 loss: 1.59271 Learning rate: 0.02 Mask loss: 0.19233 RPN box loss: 0.02836 RPN score loss: 0.02646 RPN total loss: 0.05482 Total loss: 2.10472 timestamp: 1655014915.5716765 iteration: 9540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15528 FastRCNN class loss: 0.10377 FastRCNN total loss: 0.25904 L1 loss: 0.0000e+00 L2 loss: 1.5924 Learning rate: 0.02 Mask loss: 0.18095 RPN box loss: 0.03038 RPN score loss: 0.00668 RPN total loss: 0.03706 Total loss: 2.06945 timestamp: 1655014919.0751145 iteration: 9545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19198 FastRCNN class loss: 0.11869 FastRCNN total loss: 0.31067 L1 loss: 0.0000e+00 L2 loss: 1.59208 Learning rate: 0.02 Mask loss: 0.27432 RPN box loss: 0.069 RPN score loss: 0.01511 RPN total loss: 0.08411 Total loss: 2.26118 timestamp: 1655014922.3824017 iteration: 9550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17784 FastRCNN class loss: 0.122 FastRCNN total loss: 0.29984 L1 loss: 0.0000e+00 L2 loss: 1.59179 Learning rate: 0.02 Mask loss: 0.20777 RPN box loss: 0.02222 RPN score loss: 0.01169 RPN total loss: 0.03391 Total loss: 2.13331 timestamp: 1655014925.761415 iteration: 9555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21118 FastRCNN class loss: 0.1111 FastRCNN total loss: 0.32228 L1 loss: 0.0000e+00 L2 loss: 1.5915 Learning rate: 0.02 Mask loss: 0.21532 RPN box loss: 0.08479 RPN score loss: 0.01332 RPN total loss: 0.09811 Total loss: 2.22721 timestamp: 1655014929.0686395 iteration: 9560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15189 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.23531 L1 loss: 0.0000e+00 L2 loss: 1.5912 Learning rate: 0.02 Mask loss: 0.17508 RPN box loss: 0.0327 RPN score loss: 0.00547 RPN total loss: 0.03818 Total loss: 2.03977 timestamp: 1655014932.4066644 iteration: 9565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17637 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.2341 L1 loss: 0.0000e+00 L2 loss: 1.59091 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.02819 RPN score loss: 0.00821 RPN total loss: 0.03641 Total loss: 2.00798 timestamp: 1655014935.6762817 iteration: 9570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18132 FastRCNN class loss: 0.13205 FastRCNN total loss: 0.31337 L1 loss: 0.0000e+00 L2 loss: 1.59062 Learning rate: 0.02 Mask loss: 0.18985 RPN box loss: 0.05171 RPN score loss: 0.01736 RPN total loss: 0.06907 Total loss: 2.16291 timestamp: 1655014939.089483 iteration: 9575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16857 FastRCNN class loss: 0.10671 FastRCNN total loss: 0.27528 L1 loss: 0.0000e+00 L2 loss: 1.59032 Learning rate: 0.02 Mask loss: 0.13987 RPN box loss: 0.06758 RPN score loss: 0.00849 RPN total loss: 0.07607 Total loss: 2.08154 timestamp: 1655014942.4031403 iteration: 9580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19946 FastRCNN class loss: 0.08086 FastRCNN total loss: 0.28032 L1 loss: 0.0000e+00 L2 loss: 1.59 Learning rate: 0.02 Mask loss: 0.1937 RPN box loss: 0.058 RPN score loss: 0.01031 RPN total loss: 0.06831 Total loss: 2.13233 timestamp: 1655014945.7733924 iteration: 9585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23495 FastRCNN class loss: 0.111 FastRCNN total loss: 0.34595 L1 loss: 0.0000e+00 L2 loss: 1.5897 Learning rate: 0.02 Mask loss: 0.25678 RPN box loss: 0.03614 RPN score loss: 0.02023 RPN total loss: 0.05637 Total loss: 2.24881 timestamp: 1655014949.2480686 iteration: 9590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17195 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.24277 L1 loss: 0.0000e+00 L2 loss: 1.58942 Learning rate: 0.02 Mask loss: 0.14868 RPN box loss: 0.01565 RPN score loss: 0.00673 RPN total loss: 0.02237 Total loss: 2.00325 timestamp: 1655014952.6589952 iteration: 9595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30502 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.40897 L1 loss: 0.0000e+00 L2 loss: 1.58912 Learning rate: 0.02 Mask loss: 0.22824 RPN box loss: 0.05168 RPN score loss: 0.00761 RPN total loss: 0.05929 Total loss: 2.28561 timestamp: 1655014956.0607712 iteration: 9600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15948 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.25565 L1 loss: 0.0000e+00 L2 loss: 1.58884 Learning rate: 0.02 Mask loss: 0.17643 RPN box loss: 0.04228 RPN score loss: 0.00838 RPN total loss: 0.05066 Total loss: 2.07158 timestamp: 1655014959.395374 iteration: 9605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17597 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.26643 L1 loss: 0.0000e+00 L2 loss: 1.58856 Learning rate: 0.02 Mask loss: 0.19768 RPN box loss: 0.0755 RPN score loss: 0.00708 RPN total loss: 0.08257 Total loss: 2.13524 timestamp: 1655014962.8751059 iteration: 9610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20907 FastRCNN class loss: 0.18274 FastRCNN total loss: 0.39181 L1 loss: 0.0000e+00 L2 loss: 1.5883 Learning rate: 0.02 Mask loss: 0.2 RPN box loss: 0.06861 RPN score loss: 0.02331 RPN total loss: 0.09191 Total loss: 2.27202 timestamp: 1655014966.158319 iteration: 9615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13901 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.2102 L1 loss: 0.0000e+00 L2 loss: 1.588 Learning rate: 0.02 Mask loss: 0.11828 RPN box loss: 0.0266 RPN score loss: 0.00403 RPN total loss: 0.03063 Total loss: 1.94711 timestamp: 1655014969.6155074 iteration: 9620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1158 FastRCNN class loss: 0.04684 FastRCNN total loss: 0.16264 L1 loss: 0.0000e+00 L2 loss: 1.5877 Learning rate: 0.02 Mask loss: 0.1208 RPN box loss: 0.0214 RPN score loss: 0.00443 RPN total loss: 0.02583 Total loss: 1.89697 timestamp: 1655014972.9882138 iteration: 9625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16191 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.22761 L1 loss: 0.0000e+00 L2 loss: 1.5874 Learning rate: 0.02 Mask loss: 0.17802 RPN box loss: 0.04773 RPN score loss: 0.00534 RPN total loss: 0.05306 Total loss: 2.04609 timestamp: 1655014976.3224 iteration: 9630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24528 FastRCNN class loss: 0.12825 FastRCNN total loss: 0.37353 L1 loss: 0.0000e+00 L2 loss: 1.58711 Learning rate: 0.02 Mask loss: 0.22165 RPN box loss: 0.04571 RPN score loss: 0.01013 RPN total loss: 0.05584 Total loss: 2.23812 timestamp: 1655014979.684953 iteration: 9635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18575 FastRCNN class loss: 0.11357 FastRCNN total loss: 0.29932 L1 loss: 0.0000e+00 L2 loss: 1.58682 Learning rate: 0.02 Mask loss: 0.20665 RPN box loss: 0.00887 RPN score loss: 0.00621 RPN total loss: 0.01508 Total loss: 2.10788 timestamp: 1655014982.9786258 iteration: 9640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16704 FastRCNN class loss: 0.05336 FastRCNN total loss: 0.2204 L1 loss: 0.0000e+00 L2 loss: 1.58654 Learning rate: 0.02 Mask loss: 0.18205 RPN box loss: 0.0705 RPN score loss: 0.0088 RPN total loss: 0.0793 Total loss: 2.06829 timestamp: 1655014986.3539598 iteration: 9645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15817 FastRCNN class loss: 0.10437 FastRCNN total loss: 0.26254 L1 loss: 0.0000e+00 L2 loss: 1.58623 Learning rate: 0.02 Mask loss: 0.16061 RPN box loss: 0.02249 RPN score loss: 0.00785 RPN total loss: 0.03034 Total loss: 2.03973 timestamp: 1655014989.6548767 iteration: 9650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.0938 FastRCNN total loss: 0.20821 L1 loss: 0.0000e+00 L2 loss: 1.58593 Learning rate: 0.02 Mask loss: 0.19407 RPN box loss: 0.04545 RPN score loss: 0.01046 RPN total loss: 0.05591 Total loss: 2.04411 timestamp: 1655014993.0144632 iteration: 9655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20116 FastRCNN class loss: 0.10855 FastRCNN total loss: 0.30971 L1 loss: 0.0000e+00 L2 loss: 1.58563 Learning rate: 0.02 Mask loss: 0.25411 RPN box loss: 0.04636 RPN score loss: 0.00422 RPN total loss: 0.05058 Total loss: 2.20002 timestamp: 1655014996.3487759 iteration: 9660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22109 FastRCNN class loss: 0.16484 FastRCNN total loss: 0.38593 L1 loss: 0.0000e+00 L2 loss: 1.58535 Learning rate: 0.02 Mask loss: 0.1932 RPN box loss: 0.04825 RPN score loss: 0.01042 RPN total loss: 0.05867 Total loss: 2.22315 timestamp: 1655014999.6441035 iteration: 9665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21073 FastRCNN class loss: 0.13244 FastRCNN total loss: 0.34317 L1 loss: 0.0000e+00 L2 loss: 1.58506 Learning rate: 0.02 Mask loss: 0.23739 RPN box loss: 0.05446 RPN score loss: 0.00963 RPN total loss: 0.06409 Total loss: 2.2297 timestamp: 1655015003.0075338 iteration: 9670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19517 FastRCNN class loss: 0.09377 FastRCNN total loss: 0.28894 L1 loss: 0.0000e+00 L2 loss: 1.58478 Learning rate: 0.02 Mask loss: 0.17905 RPN box loss: 0.02862 RPN score loss: 0.00632 RPN total loss: 0.03494 Total loss: 2.0877 timestamp: 1655015006.3297515 iteration: 9675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16469 FastRCNN class loss: 0.07429 FastRCNN total loss: 0.23898 L1 loss: 0.0000e+00 L2 loss: 1.58449 Learning rate: 0.02 Mask loss: 0.18819 RPN box loss: 0.02883 RPN score loss: 0.00536 RPN total loss: 0.03419 Total loss: 2.04585 timestamp: 1655015009.7313883 iteration: 9680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24206 FastRCNN class loss: 0.06399 FastRCNN total loss: 0.30605 L1 loss: 0.0000e+00 L2 loss: 1.58419 Learning rate: 0.02 Mask loss: 0.24917 RPN box loss: 0.02175 RPN score loss: 0.00788 RPN total loss: 0.02963 Total loss: 2.16903 timestamp: 1655015012.9851706 iteration: 9685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15649 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.22561 L1 loss: 0.0000e+00 L2 loss: 1.58388 Learning rate: 0.02 Mask loss: 0.17463 RPN box loss: 0.05903 RPN score loss: 0.00601 RPN total loss: 0.06504 Total loss: 2.04917 timestamp: 1655015016.3137617 iteration: 9690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11254 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.20675 L1 loss: 0.0000e+00 L2 loss: 1.58362 Learning rate: 0.02 Mask loss: 0.19771 RPN box loss: 0.01588 RPN score loss: 0.00477 RPN total loss: 0.02065 Total loss: 2.00873 timestamp: 1655015019.5614614 iteration: 9695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17006 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.23078 L1 loss: 0.0000e+00 L2 loss: 1.58333 Learning rate: 0.02 Mask loss: 0.18271 RPN box loss: 0.00526 RPN score loss: 0.00568 RPN total loss: 0.01093 Total loss: 2.00776 timestamp: 1655015022.887366 iteration: 9700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20054 FastRCNN class loss: 0.10423 FastRCNN total loss: 0.30477 L1 loss: 0.0000e+00 L2 loss: 1.58304 Learning rate: 0.02 Mask loss: 0.10989 RPN box loss: 0.01614 RPN score loss: 0.00455 RPN total loss: 0.02069 Total loss: 2.01838 timestamp: 1655015026.1740072 iteration: 9705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13088 FastRCNN class loss: 0.09534 FastRCNN total loss: 0.22622 L1 loss: 0.0000e+00 L2 loss: 1.58273 Learning rate: 0.02 Mask loss: 0.16563 RPN box loss: 0.04493 RPN score loss: 0.00632 RPN total loss: 0.05125 Total loss: 2.02584 timestamp: 1655015029.6273699 iteration: 9710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19684 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.2772 L1 loss: 0.0000e+00 L2 loss: 1.58245 Learning rate: 0.02 Mask loss: 0.13306 RPN box loss: 0.05748 RPN score loss: 0.00515 RPN total loss: 0.06263 Total loss: 2.05535 timestamp: 1655015033.1333008 iteration: 9715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17421 FastRCNN class loss: 0.10938 FastRCNN total loss: 0.28359 L1 loss: 0.0000e+00 L2 loss: 1.58215 Learning rate: 0.02 Mask loss: 0.22696 RPN box loss: 0.09461 RPN score loss: 0.02108 RPN total loss: 0.11569 Total loss: 2.2084 timestamp: 1655015036.4739428 iteration: 9720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20529 FastRCNN class loss: 0.12362 FastRCNN total loss: 0.32891 L1 loss: 0.0000e+00 L2 loss: 1.58184 Learning rate: 0.02 Mask loss: 0.24483 RPN box loss: 0.03742 RPN score loss: 0.01406 RPN total loss: 0.05148 Total loss: 2.20706 timestamp: 1655015039.9060395 iteration: 9725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17298 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.25304 L1 loss: 0.0000e+00 L2 loss: 1.58153 Learning rate: 0.02 Mask loss: 0.19237 RPN box loss: 0.03455 RPN score loss: 0.0083 RPN total loss: 0.04285 Total loss: 2.06979 timestamp: 1655015043.2051778 iteration: 9730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07348 FastRCNN class loss: 0.04379 FastRCNN total loss: 0.11727 L1 loss: 0.0000e+00 L2 loss: 1.58122 Learning rate: 0.02 Mask loss: 0.14857 RPN box loss: 0.00397 RPN score loss: 0.00329 RPN total loss: 0.00726 Total loss: 1.85432 timestamp: 1655015046.705758 iteration: 9735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09368 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.16185 L1 loss: 0.0000e+00 L2 loss: 1.58093 Learning rate: 0.02 Mask loss: 0.19776 RPN box loss: 0.02301 RPN score loss: 0.00741 RPN total loss: 0.03042 Total loss: 1.97096 timestamp: 1655015049.9693568 iteration: 9740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09046 FastRCNN class loss: 0.11991 FastRCNN total loss: 0.21037 L1 loss: 0.0000e+00 L2 loss: 1.58066 Learning rate: 0.02 Mask loss: 0.20065 RPN box loss: 0.11317 RPN score loss: 0.0666 RPN total loss: 0.17977 Total loss: 2.17144 timestamp: 1655015053.4454656 iteration: 9745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17571 FastRCNN class loss: 0.08771 FastRCNN total loss: 0.26343 L1 loss: 0.0000e+00 L2 loss: 1.58037 Learning rate: 0.02 Mask loss: 0.25924 RPN box loss: 0.05821 RPN score loss: 0.01051 RPN total loss: 0.06872 Total loss: 2.17176 timestamp: 1655015056.8413956 iteration: 9750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18964 FastRCNN class loss: 0.11642 FastRCNN total loss: 0.30606 L1 loss: 0.0000e+00 L2 loss: 1.5801 Learning rate: 0.02 Mask loss: 0.22787 RPN box loss: 0.05168 RPN score loss: 0.01998 RPN total loss: 0.07166 Total loss: 2.18569 timestamp: 1655015060.095368 iteration: 9755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.11481 FastRCNN total loss: 0.23841 L1 loss: 0.0000e+00 L2 loss: 1.57982 Learning rate: 0.02 Mask loss: 0.1929 RPN box loss: 0.05573 RPN score loss: 0.00818 RPN total loss: 0.06391 Total loss: 2.07504 timestamp: 1655015063.4622586 iteration: 9760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1209 FastRCNN class loss: 0.09123 FastRCNN total loss: 0.21213 L1 loss: 0.0000e+00 L2 loss: 1.57952 Learning rate: 0.02 Mask loss: 0.1731 RPN box loss: 0.0804 RPN score loss: 0.01297 RPN total loss: 0.09337 Total loss: 2.05812 timestamp: 1655015066.8261087 iteration: 9765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16615 FastRCNN class loss: 0.11755 FastRCNN total loss: 0.28371 L1 loss: 0.0000e+00 L2 loss: 1.57924 Learning rate: 0.02 Mask loss: 0.37926 RPN box loss: 0.05744 RPN score loss: 0.01914 RPN total loss: 0.07658 Total loss: 2.31877 timestamp: 1655015070.1939082 iteration: 9770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25463 FastRCNN class loss: 0.09799 FastRCNN total loss: 0.35262 L1 loss: 0.0000e+00 L2 loss: 1.57895 Learning rate: 0.02 Mask loss: 0.24821 RPN box loss: 0.02483 RPN score loss: 0.00455 RPN total loss: 0.02938 Total loss: 2.20916 timestamp: 1655015073.4587164 iteration: 9775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20448 FastRCNN class loss: 0.08747 FastRCNN total loss: 0.29195 L1 loss: 0.0000e+00 L2 loss: 1.57866 Learning rate: 0.02 Mask loss: 0.19474 RPN box loss: 0.07138 RPN score loss: 0.01279 RPN total loss: 0.08417 Total loss: 2.14953 timestamp: 1655015076.8767376 iteration: 9780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12043 FastRCNN class loss: 0.15298 FastRCNN total loss: 0.2734 L1 loss: 0.0000e+00 L2 loss: 1.57838 Learning rate: 0.02 Mask loss: 0.17108 RPN box loss: 0.06363 RPN score loss: 0.00826 RPN total loss: 0.0719 Total loss: 2.09476 timestamp: 1655015080.1352293 iteration: 9785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21338 FastRCNN class loss: 0.12816 FastRCNN total loss: 0.34154 L1 loss: 0.0000e+00 L2 loss: 1.57809 Learning rate: 0.02 Mask loss: 0.32794 RPN box loss: 0.06661 RPN score loss: 0.01249 RPN total loss: 0.0791 Total loss: 2.32667 timestamp: 1655015083.4743514 iteration: 9790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15935 FastRCNN class loss: 0.08031 FastRCNN total loss: 0.23966 L1 loss: 0.0000e+00 L2 loss: 1.57778 Learning rate: 0.02 Mask loss: 0.21087 RPN box loss: 0.01017 RPN score loss: 0.00358 RPN total loss: 0.01374 Total loss: 2.04205 timestamp: 1655015086.8214233 iteration: 9795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27702 FastRCNN class loss: 0.21337 FastRCNN total loss: 0.49039 L1 loss: 0.0000e+00 L2 loss: 1.57749 Learning rate: 0.02 Mask loss: 0.29236 RPN box loss: 0.12007 RPN score loss: 0.01264 RPN total loss: 0.13271 Total loss: 2.49294 timestamp: 1655015090.1473856 iteration: 9800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12454 FastRCNN class loss: 0.07828 FastRCNN total loss: 0.20283 L1 loss: 0.0000e+00 L2 loss: 1.5772 Learning rate: 0.02 Mask loss: 0.15687 RPN box loss: 0.03388 RPN score loss: 0.0103 RPN total loss: 0.04419 Total loss: 1.98108 timestamp: 1655015093.4864526 iteration: 9805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17505 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.24427 L1 loss: 0.0000e+00 L2 loss: 1.57692 Learning rate: 0.02 Mask loss: 0.14509 RPN box loss: 0.00798 RPN score loss: 0.00416 RPN total loss: 0.01214 Total loss: 1.97842 timestamp: 1655015096.7691777 iteration: 9810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1555 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.24519 L1 loss: 0.0000e+00 L2 loss: 1.57663 Learning rate: 0.02 Mask loss: 0.13946 RPN box loss: 0.07781 RPN score loss: 0.00495 RPN total loss: 0.08276 Total loss: 2.04404 timestamp: 1655015100.2367184 iteration: 9815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15511 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.25406 L1 loss: 0.0000e+00 L2 loss: 1.57636 Learning rate: 0.02 Mask loss: 0.13817 RPN box loss: 0.07001 RPN score loss: 0.01968 RPN total loss: 0.08969 Total loss: 2.05828 timestamp: 1655015103.6415913 iteration: 9820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20717 FastRCNN class loss: 0.08608 FastRCNN total loss: 0.29325 L1 loss: 0.0000e+00 L2 loss: 1.57607 Learning rate: 0.02 Mask loss: 0.25573 RPN box loss: 0.05811 RPN score loss: 0.01267 RPN total loss: 0.07077 Total loss: 2.19582 timestamp: 1655015107.0397942 iteration: 9825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20016 FastRCNN class loss: 0.10839 FastRCNN total loss: 0.30855 L1 loss: 0.0000e+00 L2 loss: 1.57577 Learning rate: 0.02 Mask loss: 0.20998 RPN box loss: 0.03257 RPN score loss: 0.0086 RPN total loss: 0.04117 Total loss: 2.13547 timestamp: 1655015110.3445346 iteration: 9830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09339 FastRCNN class loss: 0.04375 FastRCNN total loss: 0.13714 L1 loss: 0.0000e+00 L2 loss: 1.57547 Learning rate: 0.02 Mask loss: 0.11959 RPN box loss: 0.01945 RPN score loss: 0.01151 RPN total loss: 0.03096 Total loss: 1.86315 timestamp: 1655015113.7164242 iteration: 9835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26165 FastRCNN class loss: 0.14035 FastRCNN total loss: 0.40199 L1 loss: 0.0000e+00 L2 loss: 1.57518 Learning rate: 0.02 Mask loss: 0.30962 RPN box loss: 0.01882 RPN score loss: 0.00473 RPN total loss: 0.02355 Total loss: 2.31033 timestamp: 1655015117.103085 iteration: 9840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13803 FastRCNN class loss: 0.09542 FastRCNN total loss: 0.23345 L1 loss: 0.0000e+00 L2 loss: 1.5749 Learning rate: 0.02 Mask loss: 0.22064 RPN box loss: 0.02442 RPN score loss: 0.00788 RPN total loss: 0.0323 Total loss: 2.06129 timestamp: 1655015120.381731 iteration: 9845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20746 FastRCNN class loss: 0.10532 FastRCNN total loss: 0.31278 L1 loss: 0.0000e+00 L2 loss: 1.57462 Learning rate: 0.02 Mask loss: 0.14811 RPN box loss: 0.02696 RPN score loss: 0.0279 RPN total loss: 0.05486 Total loss: 2.09037 timestamp: 1655015123.6940274 iteration: 9850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.09476 FastRCNN total loss: 0.25337 L1 loss: 0.0000e+00 L2 loss: 1.57431 Learning rate: 0.02 Mask loss: 0.1506 RPN box loss: 0.16652 RPN score loss: 0.00918 RPN total loss: 0.1757 Total loss: 2.15397 timestamp: 1655015126.9311519 iteration: 9855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17116 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.27502 L1 loss: 0.0000e+00 L2 loss: 1.57402 Learning rate: 0.02 Mask loss: 0.17564 RPN box loss: 0.02102 RPN score loss: 0.01296 RPN total loss: 0.03398 Total loss: 2.05865 timestamp: 1655015130.2858264 iteration: 9860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15623 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.21844 L1 loss: 0.0000e+00 L2 loss: 1.57372 Learning rate: 0.02 Mask loss: 0.17233 RPN box loss: 0.06277 RPN score loss: 0.00897 RPN total loss: 0.07173 Total loss: 2.03622 timestamp: 1655015133.5654376 iteration: 9865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24282 FastRCNN class loss: 0.11565 FastRCNN total loss: 0.35847 L1 loss: 0.0000e+00 L2 loss: 1.57344 Learning rate: 0.02 Mask loss: 0.25147 RPN box loss: 0.02302 RPN score loss: 0.01355 RPN total loss: 0.03657 Total loss: 2.21996 timestamp: 1655015136.9279099 iteration: 9870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18269 FastRCNN class loss: 0.10817 FastRCNN total loss: 0.29085 L1 loss: 0.0000e+00 L2 loss: 1.57315 Learning rate: 0.02 Mask loss: 0.16845 RPN box loss: 0.03816 RPN score loss: 0.01289 RPN total loss: 0.05105 Total loss: 2.08351 timestamp: 1655015140.2347543 iteration: 9875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20997 FastRCNN class loss: 0.10207 FastRCNN total loss: 0.31204 L1 loss: 0.0000e+00 L2 loss: 1.57286 Learning rate: 0.02 Mask loss: 0.18688 RPN box loss: 0.08136 RPN score loss: 0.02029 RPN total loss: 0.10165 Total loss: 2.17344 timestamp: 1655015143.5728333 iteration: 9880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14608 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.23295 L1 loss: 0.0000e+00 L2 loss: 1.57255 Learning rate: 0.02 Mask loss: 0.22528 RPN box loss: 0.03295 RPN score loss: 0.01154 RPN total loss: 0.0445 Total loss: 2.07528 timestamp: 1655015146.9448924 iteration: 9885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22064 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.29845 L1 loss: 0.0000e+00 L2 loss: 1.57229 Learning rate: 0.02 Mask loss: 0.19526 RPN box loss: 0.05583 RPN score loss: 0.00886 RPN total loss: 0.06469 Total loss: 2.13069 timestamp: 1655015150.1866899 iteration: 9890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.216 FastRCNN class loss: 0.1773 FastRCNN total loss: 0.3933 L1 loss: 0.0000e+00 L2 loss: 1.572 Learning rate: 0.02 Mask loss: 0.21133 RPN box loss: 0.0454 RPN score loss: 0.01553 RPN total loss: 0.06092 Total loss: 2.23755 timestamp: 1655015153.569942 iteration: 9895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2049 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.26813 L1 loss: 0.0000e+00 L2 loss: 1.5717 Learning rate: 0.02 Mask loss: 0.25315 RPN box loss: 0.04504 RPN score loss: 0.00527 RPN total loss: 0.05031 Total loss: 2.14329 timestamp: 1655015156.939064 iteration: 9900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15028 FastRCNN class loss: 0.13494 FastRCNN total loss: 0.28522 L1 loss: 0.0000e+00 L2 loss: 1.57141 Learning rate: 0.02 Mask loss: 0.1774 RPN box loss: 0.02541 RPN score loss: 0.00827 RPN total loss: 0.03368 Total loss: 2.06772 timestamp: 1655015160.3534324 iteration: 9905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31038 FastRCNN class loss: 0.19407 FastRCNN total loss: 0.50445 L1 loss: 0.0000e+00 L2 loss: 1.57112 Learning rate: 0.02 Mask loss: 0.52205 RPN box loss: 0.04719 RPN score loss: 0.0183 RPN total loss: 0.06549 Total loss: 2.66311 timestamp: 1655015163.6479723 iteration: 9910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20725 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.31149 L1 loss: 0.0000e+00 L2 loss: 1.57083 Learning rate: 0.02 Mask loss: 0.22509 RPN box loss: 0.03318 RPN score loss: 0.00908 RPN total loss: 0.04226 Total loss: 2.14966 timestamp: 1655015167.1235495 iteration: 9915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13984 FastRCNN class loss: 0.07383 FastRCNN total loss: 0.21367 L1 loss: 0.0000e+00 L2 loss: 1.57055 Learning rate: 0.02 Mask loss: 0.18065 RPN box loss: 0.04361 RPN score loss: 0.01843 RPN total loss: 0.06203 Total loss: 2.0269 timestamp: 1655015170.3872945 iteration: 9920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1769 FastRCNN class loss: 0.06297 FastRCNN total loss: 0.23987 L1 loss: 0.0000e+00 L2 loss: 1.57027 Learning rate: 0.02 Mask loss: 0.12362 RPN box loss: 0.03858 RPN score loss: 0.00857 RPN total loss: 0.04715 Total loss: 1.98091 timestamp: 1655015173.7086728 iteration: 9925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20329 FastRCNN class loss: 0.13123 FastRCNN total loss: 0.33452 L1 loss: 0.0000e+00 L2 loss: 1.56998 Learning rate: 0.02 Mask loss: 0.24795 RPN box loss: 0.07255 RPN score loss: 0.01065 RPN total loss: 0.08319 Total loss: 2.23564 timestamp: 1655015177.1159306 iteration: 9930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20243 FastRCNN class loss: 0.11292 FastRCNN total loss: 0.31536 L1 loss: 0.0000e+00 L2 loss: 1.5697 Learning rate: 0.02 Mask loss: 0.22771 RPN box loss: 0.06811 RPN score loss: 0.01238 RPN total loss: 0.0805 Total loss: 2.19327 timestamp: 1655015180.3816338 iteration: 9935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19984 FastRCNN class loss: 0.05808 FastRCNN total loss: 0.25792 L1 loss: 0.0000e+00 L2 loss: 1.5694 Learning rate: 0.02 Mask loss: 0.1826 RPN box loss: 0.09395 RPN score loss: 0.00365 RPN total loss: 0.0976 Total loss: 2.10751 timestamp: 1655015183.7467408 iteration: 9940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28758 FastRCNN class loss: 0.17515 FastRCNN total loss: 0.46272 L1 loss: 0.0000e+00 L2 loss: 1.5691 Learning rate: 0.02 Mask loss: 0.27423 RPN box loss: 0.02196 RPN score loss: 0.01522 RPN total loss: 0.03718 Total loss: 2.34323 timestamp: 1655015187.0065763 iteration: 9945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15955 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.24492 L1 loss: 0.0000e+00 L2 loss: 1.56881 Learning rate: 0.02 Mask loss: 0.16977 RPN box loss: 0.03015 RPN score loss: 0.00732 RPN total loss: 0.03747 Total loss: 2.02097 timestamp: 1655015190.3892047 iteration: 9950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22786 FastRCNN class loss: 0.11737 FastRCNN total loss: 0.34523 L1 loss: 0.0000e+00 L2 loss: 1.56853 Learning rate: 0.02 Mask loss: 0.19387 RPN box loss: 0.03947 RPN score loss: 0.0048 RPN total loss: 0.04427 Total loss: 2.1519 timestamp: 1655015193.684201 iteration: 9955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17407 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.25622 L1 loss: 0.0000e+00 L2 loss: 1.56824 Learning rate: 0.02 Mask loss: 0.20005 RPN box loss: 0.01129 RPN score loss: 0.01148 RPN total loss: 0.02278 Total loss: 2.04729 timestamp: 1655015197.0669274 iteration: 9960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1763 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.2384 L1 loss: 0.0000e+00 L2 loss: 1.56795 Learning rate: 0.02 Mask loss: 0.16074 RPN box loss: 0.06275 RPN score loss: 0.00997 RPN total loss: 0.07271 Total loss: 2.03981 timestamp: 1655015200.365325 iteration: 9965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13321 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.22583 L1 loss: 0.0000e+00 L2 loss: 1.56765 Learning rate: 0.02 Mask loss: 0.13433 RPN box loss: 0.03106 RPN score loss: 0.00566 RPN total loss: 0.03673 Total loss: 1.96454 timestamp: 1655015203.7724524 iteration: 9970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17886 FastRCNN class loss: 0.07618 FastRCNN total loss: 0.25504 L1 loss: 0.0000e+00 L2 loss: 1.56736 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.08082 RPN score loss: 0.00759 RPN total loss: 0.08841 Total loss: 2.09404 timestamp: 1655015207.084029 iteration: 9975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08089 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.14416 L1 loss: 0.0000e+00 L2 loss: 1.56706 Learning rate: 0.02 Mask loss: 0.12379 RPN box loss: 0.02795 RPN score loss: 0.00324 RPN total loss: 0.03119 Total loss: 1.86621 timestamp: 1655015210.3126268 iteration: 9980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16979 FastRCNN class loss: 0.10015 FastRCNN total loss: 0.26993 L1 loss: 0.0000e+00 L2 loss: 1.56679 Learning rate: 0.02 Mask loss: 0.15037 RPN box loss: 0.07301 RPN score loss: 0.00518 RPN total loss: 0.07819 Total loss: 2.06528 timestamp: 1655015213.7493472 iteration: 9985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18459 FastRCNN class loss: 0.11532 FastRCNN total loss: 0.29991 L1 loss: 0.0000e+00 L2 loss: 1.56649 Learning rate: 0.02 Mask loss: 0.25811 RPN box loss: 0.05592 RPN score loss: 0.00942 RPN total loss: 0.06534 Total loss: 2.18985 timestamp: 1655015217.09421 iteration: 9990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20469 FastRCNN class loss: 0.09973 FastRCNN total loss: 0.30441 L1 loss: 0.0000e+00 L2 loss: 1.56622 Learning rate: 0.02 Mask loss: 0.12683 RPN box loss: 0.01435 RPN score loss: 0.00359 RPN total loss: 0.01794 Total loss: 2.01541 timestamp: 1655015220.559056 iteration: 9995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23805 FastRCNN class loss: 0.14005 FastRCNN total loss: 0.37811 L1 loss: 0.0000e+00 L2 loss: 1.56594 Learning rate: 0.02 Mask loss: 0.33034 RPN box loss: 0.08084 RPN score loss: 0.01164 RPN total loss: 0.09248 Total loss: 2.36686 timestamp: 1655015223.8239448 iteration: 10000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18592 FastRCNN class loss: 0.13008 FastRCNN total loss: 0.316 L1 loss: 0.0000e+00 L2 loss: 1.56563 Learning rate: 0.02 Mask loss: 0.32362 RPN box loss: 0.04209 RPN score loss: 0.00629 RPN total loss: 0.04838 Total loss: 2.25363 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 7.6025s - Throughput: 0.5 imgs/s Running inference on batch 002/125... - Step Time: 0.8325s - Throughput: 4.8 imgs/s Running inference on batch 003/125... - Step Time: 0.7994s - Throughput: 5.0 imgs/s Running inference on batch 004/125... - Step Time: 0.8256s - Throughput: 4.8 imgs/s Running inference on batch 005/125... - Step Time: 0.8662s - Throughput: 4.6 imgs/s Running inference on batch 006/125... - Step Time: 0.8327s - Throughput: 4.8 imgs/s Running inference on batch 007/125... - Step Time: 0.7920s - Throughput: 5.1 imgs/s Running inference on batch 008/125... - Step Time: 0.8491s - Throughput: 4.7 imgs/s Running inference on batch 009/125... - Step Time: 0.8509s - Throughput: 4.7 imgs/s Running inference on batch 010/125... - Step Time: 0.7815s - Throughput: 5.1 imgs/s Running inference on batch 011/125... - Step Time: 0.8351s - Throughput: 4.8 imgs/s Running inference on batch 012/125... - Step Time: 0.8198s - Throughput: 4.9 imgs/s Running inference on batch 013/125... - Step Time: 0.8456s - Throughput: 4.7 imgs/s Running inference on batch 014/125... - Step Time: 0.8153s - Throughput: 4.9 imgs/s Running inference on batch 015/125... - Step Time: 0.8012s - Throughput: 5.0 imgs/s Running inference on batch 016/125... - Step Time: 0.8195s - Throughput: 4.9 imgs/s Running inference on batch 017/125... - Step Time: 0.7981s - Throughput: 5.0 imgs/s Running inference on batch 018/125... - Step Time: 0.8191s - Throughput: 4.9 imgs/s Running inference on batch 019/125... - Step Time: 0.8356s - Throughput: 4.8 imgs/s Running inference on batch 020/125... - Step Time: 0.8213s - Throughput: 4.9 imgs/s Running inference on batch 021/125... - Step Time: 0.7994s - Throughput: 5.0 imgs/s Running inference on batch 022/125... - Step Time: 0.8751s - Throughput: 4.6 imgs/s Running inference on batch 023/125... - Step Time: 0.7917s - Throughput: 5.1 imgs/s Running inference on batch 024/125... - 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Step Time: 0.8111s - Throughput: 4.9 imgs/s Running inference on batch 085/125... - Step Time: 0.7921s - Throughput: 5.0 imgs/s Running inference on batch 086/125... - Step Time: 0.7826s - Throughput: 5.1 imgs/s Running inference on batch 087/125... - Step Time: 0.8275s - Throughput: 4.8 imgs/s Running inference on batch 088/125... - Step Time: 0.8375s - Throughput: 4.8 imgs/s Running inference on batch 089/125... - Step Time: 0.6308s - Throughput: 6.3 imgs/s Running inference on batch 090/125... - Step Time: 0.5694s - Throughput: 7.0 imgs/s Running inference on batch 091/125... - Step Time: 0.7853s - Throughput: 5.1 imgs/s Running inference on batch 092/125... - Step Time: 0.8526s - Throughput: 4.7 imgs/s Running inference on batch 093/125... - Step Time: 0.8406s - Throughput: 4.8 imgs/s Running inference on batch 094/125... - Step Time: 0.8333s - Throughput: 4.8 imgs/s Running inference on batch 095/125... - Step Time: 0.8594s - Throughput: 4.7 imgs/s Running inference on batch 096/125... - Step Time: 0.8280s - Throughput: 4.8 imgs/s Running inference on batch 097/125... - Step Time: 0.8479s - Throughput: 4.7 imgs/s Running inference on batch 098/125... - Step Time: 0.8280s - Throughput: 4.8 imgs/s Running inference on batch 099/125... - Step Time: 0.8290s - Throughput: 4.8 imgs/s Running inference on batch 100/125... - Step Time: 0.8057s - Throughput: 5.0 imgs/s Running inference on batch 101/125... - Step Time: 0.7991s - Throughput: 5.0 imgs/s Running inference on batch 102/125... - Step Time: 0.8132s - Throughput: 4.9 imgs/s Running inference on batch 103/125... - Step Time: 0.7989s - Throughput: 5.0 imgs/s Running inference on batch 104/125... - Step Time: 0.8291s - Throughput: 4.8 imgs/s Running inference on batch 105/125... - Step Time: 0.7690s - Throughput: 5.2 imgs/s Running inference on batch 106/125... - Step Time: 0.8574s - Throughput: 4.7 imgs/s Running inference on batch 107/125... - Step Time: 0.8420s - Throughput: 4.8 imgs/s Running inference on batch 108/125... - Step Time: 0.8304s - Throughput: 4.8 imgs/s Running inference on batch 109/125... - Step Time: 0.8486s - Throughput: 4.7 imgs/s Running inference on batch 110/125... - Step Time: 0.8511s - Throughput: 4.7 imgs/s Running inference on batch 111/125... - Step Time: 0.8236s - Throughput: 4.9 imgs/s Running inference on batch 112/125... - Step Time: 0.8312s - Throughput: 4.8 imgs/s Running inference on batch 113/125... - Step Time: 0.8072s - Throughput: 5.0 imgs/s Running inference on batch 114/125... - Step Time: 0.7809s - Throughput: 5.1 imgs/s Running inference on batch 115/125... - Step Time: 0.8439s - Throughput: 4.7 imgs/s Running inference on batch 116/125... - Step Time: 0.8155s - Throughput: 4.9 imgs/s Running inference on batch 117/125... - Step Time: 0.8142s - Throughput: 4.9 imgs/s Running inference on batch 118/125... - Step Time: 0.8554s - Throughput: 4.7 imgs/s Running inference on batch 119/125... - Step Time: 0.8411s - Throughput: 4.8 imgs/s Running inference on batch 120/125... - Step Time: 0.8460s - Throughput: 4.7 imgs/s Running inference on batch 121/125... - Step Time: 0.7968s - Throughput: 5.0 imgs/s Running inference on batch 122/125... - Step Time: 0.7855s - Throughput: 5.1 imgs/s Running inference on batch 123/125... - Step Time: 0.8599s - Throughput: 4.7 imgs/s Running inference on batch 124/125... - Step Time: 0.8699s - Throughput: 4.6 imgs/s Running inference on batch 125/125... - Step Time: 0.8001s - Throughput: 5.0 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: 4.9 samples/sec Total processed steps: 125 Total processing time: 0.0h 10m 12s ==================== Metrics ==================== AP: 0.130846322 AP50: 0.211062625 AP75: 0.130689710 APl: 0.149077654 APm: 0.030454604 APs: 0.011551155 ARl: 0.375218093 ARm: 0.055879917 ARmax1: 0.237178430 ARmax10: 0.316862017 ARmax100: 0.321332246 ARs: 0.011111111 mask_AP: 0.103156842 mask_AP50: 0.168024048 mask_AP75: 0.104458734 mask_APl: 0.117250413 mask_APm: 0.006485220 mask_APs: 0.000000000 mask_ARl: 0.224884510 mask_ARm: 0.024648033 mask_ARmax1: 0.153925180 mask_ARmax10: 0.187095568 mask_ARmax100: 0.190151230 mask_ARs: 0.000000000 ================================= 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] 549.0 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: 1655016572.569876 iteration: 10005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15086 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.21064 L1 loss: 0.0000e+00 L2 loss: 1.56534 Learning rate: 0.02 Mask loss: 0.1323 RPN box loss: 0.02987 RPN score loss: 0.00398 RPN total loss: 0.03385 Total loss: 1.94212 timestamp: 1655016575.8285158 iteration: 10010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10887 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.18669 L1 loss: 0.0000e+00 L2 loss: 1.56506 Learning rate: 0.02 Mask loss: 0.17704 RPN box loss: 0.02896 RPN score loss: 0.0064 RPN total loss: 0.03536 Total loss: 1.96415 timestamp: 1655016579.2712657 iteration: 10015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14538 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.21453 L1 loss: 0.0000e+00 L2 loss: 1.5648 Learning rate: 0.02 Mask loss: 0.22475 RPN box loss: 0.01061 RPN score loss: 0.00609 RPN total loss: 0.0167 Total loss: 2.02078 timestamp: 1655016582.570606 iteration: 10020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27555 FastRCNN class loss: 0.09931 FastRCNN total loss: 0.37486 L1 loss: 0.0000e+00 L2 loss: 1.56452 Learning rate: 0.02 Mask loss: 0.34611 RPN box loss: 0.0457 RPN score loss: 0.00499 RPN total loss: 0.05069 Total loss: 2.33618 timestamp: 1655016585.9218495 iteration: 10025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10354 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.16863 L1 loss: 0.0000e+00 L2 loss: 1.56421 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.08285 RPN score loss: 0.00514 RPN total loss: 0.08799 Total loss: 1.9875 timestamp: 1655016589.3817222 iteration: 10030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15809 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.24964 L1 loss: 0.0000e+00 L2 loss: 1.56392 Learning rate: 0.02 Mask loss: 0.13765 RPN box loss: 0.01881 RPN score loss: 0.00701 RPN total loss: 0.02582 Total loss: 1.97703 timestamp: 1655016592.6313872 iteration: 10035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11298 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.18712 L1 loss: 0.0000e+00 L2 loss: 1.56364 Learning rate: 0.02 Mask loss: 0.21575 RPN box loss: 0.01706 RPN score loss: 0.0035 RPN total loss: 0.02057 Total loss: 1.98707 timestamp: 1655016596.141674 iteration: 10040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18009 FastRCNN class loss: 0.09525 FastRCNN total loss: 0.27534 L1 loss: 0.0000e+00 L2 loss: 1.56336 Learning rate: 0.02 Mask loss: 0.24077 RPN box loss: 0.021 RPN score loss: 0.00299 RPN total loss: 0.024 Total loss: 2.10346 timestamp: 1655016599.4685915 iteration: 10045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2436 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.32948 L1 loss: 0.0000e+00 L2 loss: 1.56305 Learning rate: 0.02 Mask loss: 0.14643 RPN box loss: 0.01851 RPN score loss: 0.01312 RPN total loss: 0.03162 Total loss: 2.07059 timestamp: 1655016603.0208943 iteration: 10050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2485 FastRCNN class loss: 0.12203 FastRCNN total loss: 0.37053 L1 loss: 0.0000e+00 L2 loss: 1.56277 Learning rate: 0.02 Mask loss: 0.23763 RPN box loss: 0.01897 RPN score loss: 0.00447 RPN total loss: 0.02344 Total loss: 2.19437 timestamp: 1655016606.3819194 iteration: 10055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18938 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.26722 L1 loss: 0.0000e+00 L2 loss: 1.5625 Learning rate: 0.02 Mask loss: 0.15431 RPN box loss: 0.04153 RPN score loss: 0.00727 RPN total loss: 0.0488 Total loss: 2.03282 timestamp: 1655016609.7781425 iteration: 10060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23158 FastRCNN class loss: 0.20368 FastRCNN total loss: 0.43527 L1 loss: 0.0000e+00 L2 loss: 1.56221 Learning rate: 0.02 Mask loss: 0.32697 RPN box loss: 0.05531 RPN score loss: 0.01053 RPN total loss: 0.06583 Total loss: 2.39028 timestamp: 1655016613.3562026 iteration: 10065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14472 FastRCNN class loss: 0.08667 FastRCNN total loss: 0.23139 L1 loss: 0.0000e+00 L2 loss: 1.56193 Learning rate: 0.02 Mask loss: 0.19938 RPN box loss: 0.05961 RPN score loss: 0.00549 RPN total loss: 0.0651 Total loss: 2.0578 timestamp: 1655016616.616523 iteration: 10070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16636 FastRCNN class loss: 0.14091 FastRCNN total loss: 0.30727 L1 loss: 0.0000e+00 L2 loss: 1.56164 Learning rate: 0.02 Mask loss: 0.15306 RPN box loss: 0.06288 RPN score loss: 0.0066 RPN total loss: 0.06947 Total loss: 2.09144 timestamp: 1655016619.9955878 iteration: 10075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22862 FastRCNN class loss: 0.1197 FastRCNN total loss: 0.34832 L1 loss: 0.0000e+00 L2 loss: 1.56132 Learning rate: 0.02 Mask loss: 0.19669 RPN box loss: 0.03668 RPN score loss: 0.01504 RPN total loss: 0.05172 Total loss: 2.15805 timestamp: 1655016623.294247 iteration: 10080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11304 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.16307 L1 loss: 0.0000e+00 L2 loss: 1.56104 Learning rate: 0.02 Mask loss: 0.16924 RPN box loss: 0.02693 RPN score loss: 0.0068 RPN total loss: 0.03374 Total loss: 1.92708 timestamp: 1655016626.7155936 iteration: 10085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1981 FastRCNN class loss: 0.11108 FastRCNN total loss: 0.30919 L1 loss: 0.0000e+00 L2 loss: 1.56078 Learning rate: 0.02 Mask loss: 0.25338 RPN box loss: 0.04247 RPN score loss: 0.01012 RPN total loss: 0.05259 Total loss: 2.17594 timestamp: 1655016630.1023564 iteration: 10090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28003 FastRCNN class loss: 0.11128 FastRCNN total loss: 0.39131 L1 loss: 0.0000e+00 L2 loss: 1.56049 Learning rate: 0.02 Mask loss: 0.21388 RPN box loss: 0.05953 RPN score loss: 0.00745 RPN total loss: 0.06697 Total loss: 2.23266 timestamp: 1655016633.5062926 iteration: 10095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.134 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.18897 L1 loss: 0.0000e+00 L2 loss: 1.5602 Learning rate: 0.02 Mask loss: 0.10223 RPN box loss: 0.03354 RPN score loss: 0.00943 RPN total loss: 0.04297 Total loss: 1.89437 timestamp: 1655016637.0129414 iteration: 10100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14347 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.20699 L1 loss: 0.0000e+00 L2 loss: 1.5599 Learning rate: 0.02 Mask loss: 0.12124 RPN box loss: 0.03275 RPN score loss: 0.00956 RPN total loss: 0.04232 Total loss: 1.93044 timestamp: 1655016640.3528066 iteration: 10105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22416 FastRCNN class loss: 0.10396 FastRCNN total loss: 0.32812 L1 loss: 0.0000e+00 L2 loss: 1.55961 Learning rate: 0.02 Mask loss: 0.17756 RPN box loss: 0.05765 RPN score loss: 0.01042 RPN total loss: 0.06807 Total loss: 2.13337 timestamp: 1655016643.8483932 iteration: 10110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14147 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.20575 L1 loss: 0.0000e+00 L2 loss: 1.55931 Learning rate: 0.02 Mask loss: 0.16562 RPN box loss: 0.01388 RPN score loss: 0.0075 RPN total loss: 0.02138 Total loss: 1.95206 timestamp: 1655016647.102488 iteration: 10115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20781 FastRCNN class loss: 0.08117 FastRCNN total loss: 0.28898 L1 loss: 0.0000e+00 L2 loss: 1.55904 Learning rate: 0.02 Mask loss: 0.26693 RPN box loss: 0.05272 RPN score loss: 0.00873 RPN total loss: 0.06146 Total loss: 2.1764 timestamp: 1655016650.4839451 iteration: 10120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11216 FastRCNN class loss: 0.04646 FastRCNN total loss: 0.15862 L1 loss: 0.0000e+00 L2 loss: 1.55876 Learning rate: 0.02 Mask loss: 0.1638 RPN box loss: 0.00381 RPN score loss: 0.00382 RPN total loss: 0.00763 Total loss: 1.8888 timestamp: 1655016653.7934334 iteration: 10125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16948 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.2474 L1 loss: 0.0000e+00 L2 loss: 1.55847 Learning rate: 0.02 Mask loss: 0.16427 RPN box loss: 0.03466 RPN score loss: 0.01167 RPN total loss: 0.04633 Total loss: 2.01647 timestamp: 1655016657.1272092 iteration: 10130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16163 FastRCNN class loss: 0.08315 FastRCNN total loss: 0.24478 L1 loss: 0.0000e+00 L2 loss: 1.55817 Learning rate: 0.02 Mask loss: 0.20305 RPN box loss: 0.11361 RPN score loss: 0.01051 RPN total loss: 0.12412 Total loss: 2.13011 timestamp: 1655016660.5382318 iteration: 10135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19695 FastRCNN class loss: 0.10206 FastRCNN total loss: 0.29901 L1 loss: 0.0000e+00 L2 loss: 1.55789 Learning rate: 0.02 Mask loss: 0.1798 RPN box loss: 0.04933 RPN score loss: 0.01081 RPN total loss: 0.06013 Total loss: 2.09683 timestamp: 1655016663.9255064 iteration: 10140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21902 FastRCNN class loss: 0.13094 FastRCNN total loss: 0.34996 L1 loss: 0.0000e+00 L2 loss: 1.55762 Learning rate: 0.02 Mask loss: 0.17132 RPN box loss: 0.03151 RPN score loss: 0.00839 RPN total loss: 0.0399 Total loss: 2.1188 timestamp: 1655016667.3550768 iteration: 10145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13778 FastRCNN class loss: 0.08258 FastRCNN total loss: 0.22036 L1 loss: 0.0000e+00 L2 loss: 1.55734 Learning rate: 0.02 Mask loss: 0.15302 RPN box loss: 0.01072 RPN score loss: 0.0053 RPN total loss: 0.01602 Total loss: 1.94674 timestamp: 1655016670.6926327 iteration: 10150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16108 FastRCNN class loss: 0.11534 FastRCNN total loss: 0.27642 L1 loss: 0.0000e+00 L2 loss: 1.55705 Learning rate: 0.02 Mask loss: 0.16889 RPN box loss: 0.02748 RPN score loss: 0.00577 RPN total loss: 0.03324 Total loss: 2.03561 timestamp: 1655016674.1943393 iteration: 10155 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12247 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.19025 L1 loss: 0.0000e+00 L2 loss: 1.55679 Learning rate: 0.02 Mask loss: 0.14607 RPN box loss: 0.01453 RPN score loss: 0.00258 RPN total loss: 0.01711 Total loss: 1.91022 timestamp: 1655016677.4789412 iteration: 10160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16402 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.24553 L1 loss: 0.0000e+00 L2 loss: 1.55652 Learning rate: 0.02 Mask loss: 0.22633 RPN box loss: 0.0129 RPN score loss: 0.00463 RPN total loss: 0.01753 Total loss: 2.0459 timestamp: 1655016680.8903635 iteration: 10165 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09926 FastRCNN class loss: 0.06439 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 1.55625 Learning rate: 0.02 Mask loss: 0.15204 RPN box loss: 0.05527 RPN score loss: 0.00988 RPN total loss: 0.06515 Total loss: 1.93708 timestamp: 1655016684.1960537 iteration: 10170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.08771 FastRCNN total loss: 0.20657 L1 loss: 0.0000e+00 L2 loss: 1.55596 Learning rate: 0.02 Mask loss: 0.27346 RPN box loss: 0.04918 RPN score loss: 0.01699 RPN total loss: 0.06617 Total loss: 2.10217 timestamp: 1655016687.6510952 iteration: 10175 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17182 FastRCNN class loss: 0.08341 FastRCNN total loss: 0.25522 L1 loss: 0.0000e+00 L2 loss: 1.55568 Learning rate: 0.02 Mask loss: 0.18214 RPN box loss: 0.01272 RPN score loss: 0.00819 RPN total loss: 0.02092 Total loss: 2.01395 timestamp: 1655016691.0538437 iteration: 10180 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17695 FastRCNN class loss: 0.09866 FastRCNN total loss: 0.27561 L1 loss: 0.0000e+00 L2 loss: 1.55539 Learning rate: 0.02 Mask loss: 0.21058 RPN box loss: 0.03681 RPN score loss: 0.00904 RPN total loss: 0.04586 Total loss: 2.08744 timestamp: 1655016694.4049747 iteration: 10185 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19467 FastRCNN class loss: 0.15976 FastRCNN total loss: 0.35443 L1 loss: 0.0000e+00 L2 loss: 1.55508 Learning rate: 0.02 Mask loss: 0.25169 RPN box loss: 0.06906 RPN score loss: 0.02809 RPN total loss: 0.09714 Total loss: 2.25834 timestamp: 1655016697.7635906 iteration: 10190 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21838 FastRCNN class loss: 0.11577 FastRCNN total loss: 0.33415 L1 loss: 0.0000e+00 L2 loss: 1.55479 Learning rate: 0.02 Mask loss: 0.20357 RPN box loss: 0.05662 RPN score loss: 0.01092 RPN total loss: 0.06754 Total loss: 2.16005 timestamp: 1655016701.0060651 iteration: 10195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.164 FastRCNN class loss: 0.11419 FastRCNN total loss: 0.27819 L1 loss: 0.0000e+00 L2 loss: 1.5545 Learning rate: 0.02 Mask loss: 0.27323 RPN box loss: 0.03949 RPN score loss: 0.00927 RPN total loss: 0.04876 Total loss: 2.15468 timestamp: 1655016704.442833 iteration: 10200 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23148 FastRCNN class loss: 0.11921 FastRCNN total loss: 0.3507 L1 loss: 0.0000e+00 L2 loss: 1.55422 Learning rate: 0.02 Mask loss: 0.19553 RPN box loss: 0.10595 RPN score loss: 0.01401 RPN total loss: 0.11996 Total loss: 2.22041 timestamp: 1655016707.8281724 iteration: 10205 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.12213 FastRCNN total loss: 0.27029 L1 loss: 0.0000e+00 L2 loss: 1.55396 Learning rate: 0.02 Mask loss: 0.18787 RPN box loss: 0.09759 RPN score loss: 0.01148 RPN total loss: 0.10908 Total loss: 2.1212 timestamp: 1655016711.2219539 iteration: 10210 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19877 FastRCNN class loss: 0.11491 FastRCNN total loss: 0.31369 L1 loss: 0.0000e+00 L2 loss: 1.55368 Learning rate: 0.02 Mask loss: 0.31349 RPN box loss: 0.02814 RPN score loss: 0.00856 RPN total loss: 0.03671 Total loss: 2.21756 timestamp: 1655016714.6898124 iteration: 10215 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16097 FastRCNN class loss: 0.0981 FastRCNN total loss: 0.25907 L1 loss: 0.0000e+00 L2 loss: 1.55337 Learning rate: 0.02 Mask loss: 0.21925 RPN box loss: 0.02931 RPN score loss: 0.00863 RPN total loss: 0.03794 Total loss: 2.06963 timestamp: 1655016718.0274367 iteration: 10220 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09071 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.15295 L1 loss: 0.0000e+00 L2 loss: 1.55308 Learning rate: 0.02 Mask loss: 0.12418 RPN box loss: 0.03607 RPN score loss: 0.00914 RPN total loss: 0.04521 Total loss: 1.87542 timestamp: 1655016721.5581245 iteration: 10225 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.05453 FastRCNN total loss: 0.1671 L1 loss: 0.0000e+00 L2 loss: 1.55283 Learning rate: 0.02 Mask loss: 0.13582 RPN box loss: 0.03399 RPN score loss: 0.00718 RPN total loss: 0.04117 Total loss: 1.89692 timestamp: 1655016724.7651906 iteration: 10230 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21005 FastRCNN class loss: 0.13304 FastRCNN total loss: 0.34309 L1 loss: 0.0000e+00 L2 loss: 1.55255 Learning rate: 0.02 Mask loss: 0.36938 RPN box loss: 0.02811 RPN score loss: 0.00853 RPN total loss: 0.03664 Total loss: 2.30166 timestamp: 1655016728.1609962 iteration: 10235 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14115 FastRCNN class loss: 0.07085 FastRCNN total loss: 0.212 L1 loss: 0.0000e+00 L2 loss: 1.55228 Learning rate: 0.02 Mask loss: 0.20912 RPN box loss: 0.01303 RPN score loss: 0.00565 RPN total loss: 0.01869 Total loss: 1.99209 timestamp: 1655016731.448555 iteration: 10240 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19004 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.26157 L1 loss: 0.0000e+00 L2 loss: 1.55201 Learning rate: 0.02 Mask loss: 0.16364 RPN box loss: 0.0307 RPN score loss: 0.01036 RPN total loss: 0.04106 Total loss: 2.01828 timestamp: 1655016734.9002385 iteration: 10245 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15404 FastRCNN class loss: 0.09899 FastRCNN total loss: 0.25304 L1 loss: 0.0000e+00 L2 loss: 1.55174 Learning rate: 0.02 Mask loss: 0.19661 RPN box loss: 0.05195 RPN score loss: 0.01142 RPN total loss: 0.06337 Total loss: 2.06476 timestamp: 1655016738.3301463 iteration: 10250 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17268 FastRCNN class loss: 0.06316 FastRCNN total loss: 0.23584 L1 loss: 0.0000e+00 L2 loss: 1.55147 Learning rate: 0.02 Mask loss: 0.14614 RPN box loss: 0.01449 RPN score loss: 0.00362 RPN total loss: 0.01812 Total loss: 1.95157 timestamp: 1655016741.6377332 iteration: 10255 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18957 FastRCNN class loss: 0.08348 FastRCNN total loss: 0.27304 L1 loss: 0.0000e+00 L2 loss: 1.55118 Learning rate: 0.02 Mask loss: 0.1292 RPN box loss: 0.01249 RPN score loss: 0.00502 RPN total loss: 0.01751 Total loss: 1.97094 timestamp: 1655016744.891037 iteration: 10260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.22147 L1 loss: 0.0000e+00 L2 loss: 1.5509 Learning rate: 0.02 Mask loss: 0.18823 RPN box loss: 0.00917 RPN score loss: 0.00994 RPN total loss: 0.01911 Total loss: 1.9797 timestamp: 1655016748.2052295 iteration: 10265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17283 FastRCNN class loss: 0.09905 FastRCNN total loss: 0.27187 L1 loss: 0.0000e+00 L2 loss: 1.5506 Learning rate: 0.02 Mask loss: 0.17227 RPN box loss: 0.06815 RPN score loss: 0.01304 RPN total loss: 0.0812 Total loss: 2.07594 timestamp: 1655016751.6201384 iteration: 10270 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20149 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.29377 L1 loss: 0.0000e+00 L2 loss: 1.55033 Learning rate: 0.02 Mask loss: 0.22124 RPN box loss: 0.02824 RPN score loss: 0.0152 RPN total loss: 0.04344 Total loss: 2.10878 timestamp: 1655016754.8860466 iteration: 10275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21142 FastRCNN class loss: 0.11576 FastRCNN total loss: 0.32718 L1 loss: 0.0000e+00 L2 loss: 1.55003 Learning rate: 0.02 Mask loss: 0.21539 RPN box loss: 0.04501 RPN score loss: 0.00456 RPN total loss: 0.04957 Total loss: 2.14217 timestamp: 1655016758.259565 iteration: 10280 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20693 FastRCNN class loss: 0.10447 FastRCNN total loss: 0.3114 L1 loss: 0.0000e+00 L2 loss: 1.54974 Learning rate: 0.02 Mask loss: 0.24474 RPN box loss: 0.01072 RPN score loss: 0.00337 RPN total loss: 0.01409 Total loss: 2.11997 timestamp: 1655016761.5982876 iteration: 10285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17985 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.24093 L1 loss: 0.0000e+00 L2 loss: 1.54946 Learning rate: 0.02 Mask loss: 0.13412 RPN box loss: 0.03994 RPN score loss: 0.01033 RPN total loss: 0.05026 Total loss: 1.97477 timestamp: 1655016765.0597765 iteration: 10290 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16949 FastRCNN class loss: 0.0953 FastRCNN total loss: 0.26479 L1 loss: 0.0000e+00 L2 loss: 1.54919 Learning rate: 0.02 Mask loss: 0.16951 RPN box loss: 0.04101 RPN score loss: 0.00562 RPN total loss: 0.04663 Total loss: 2.03011 timestamp: 1655016768.4049044 iteration: 10295 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12305 FastRCNN class loss: 0.07684 FastRCNN total loss: 0.19989 L1 loss: 0.0000e+00 L2 loss: 1.5489 Learning rate: 0.02 Mask loss: 0.17994 RPN box loss: 0.1128 RPN score loss: 0.0161 RPN total loss: 0.1289 Total loss: 2.05763 timestamp: 1655016771.7407784 iteration: 10300 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20111 FastRCNN class loss: 0.136 FastRCNN total loss: 0.33712 L1 loss: 0.0000e+00 L2 loss: 1.54863 Learning rate: 0.02 Mask loss: 0.21782 RPN box loss: 0.06329 RPN score loss: 0.01194 RPN total loss: 0.07523 Total loss: 2.1788 timestamp: 1655016775.1413803 iteration: 10305 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18786 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.27689 L1 loss: 0.0000e+00 L2 loss: 1.54835 Learning rate: 0.02 Mask loss: 0.19162 RPN box loss: 0.03047 RPN score loss: 0.00534 RPN total loss: 0.03582 Total loss: 2.05267 timestamp: 1655016778.4425476 iteration: 10310 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20216 FastRCNN class loss: 0.11045 FastRCNN total loss: 0.3126 L1 loss: 0.0000e+00 L2 loss: 1.54807 Learning rate: 0.02 Mask loss: 0.19534 RPN box loss: 0.02822 RPN score loss: 0.00629 RPN total loss: 0.03451 Total loss: 2.09052 timestamp: 1655016781.8376803 iteration: 10315 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13018 FastRCNN class loss: 0.07133 FastRCNN total loss: 0.20152 L1 loss: 0.0000e+00 L2 loss: 1.54779 Learning rate: 0.02 Mask loss: 0.20629 RPN box loss: 0.04956 RPN score loss: 0.00539 RPN total loss: 0.05496 Total loss: 2.01055 timestamp: 1655016785.1705935 iteration: 10320 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21922 FastRCNN class loss: 0.10063 FastRCNN total loss: 0.31985 L1 loss: 0.0000e+00 L2 loss: 1.54751 Learning rate: 0.02 Mask loss: 0.26217 RPN box loss: 0.0226 RPN score loss: 0.00425 RPN total loss: 0.02684 Total loss: 2.15637 timestamp: 1655016788.6811173 iteration: 10325 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09882 FastRCNN class loss: 0.06756 FastRCNN total loss: 0.16638 L1 loss: 0.0000e+00 L2 loss: 1.54723 Learning rate: 0.02 Mask loss: 0.17546 RPN box loss: 0.03413 RPN score loss: 0.00138 RPN total loss: 0.03551 Total loss: 1.92459 timestamp: 1655016792.0712597 iteration: 10330 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17741 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.25256 L1 loss: 0.0000e+00 L2 loss: 1.54696 Learning rate: 0.02 Mask loss: 0.19876 RPN box loss: 0.05648 RPN score loss: 0.01012 RPN total loss: 0.06659 Total loss: 2.06488 timestamp: 1655016795.3562417 iteration: 10335 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18074 FastRCNN class loss: 0.09785 FastRCNN total loss: 0.27859 L1 loss: 0.0000e+00 L2 loss: 1.54668 Learning rate: 0.02 Mask loss: 0.16127 RPN box loss: 0.06414 RPN score loss: 0.02596 RPN total loss: 0.0901 Total loss: 2.07663 timestamp: 1655016798.7787802 iteration: 10340 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15985 FastRCNN class loss: 0.08245 FastRCNN total loss: 0.2423 L1 loss: 0.0000e+00 L2 loss: 1.54638 Learning rate: 0.02 Mask loss: 0.25026 RPN box loss: 0.0285 RPN score loss: 0.00502 RPN total loss: 0.03351 Total loss: 2.07245 timestamp: 1655016802.028453 iteration: 10345 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17606 FastRCNN class loss: 0.09298 FastRCNN total loss: 0.26903 L1 loss: 0.0000e+00 L2 loss: 1.54608 Learning rate: 0.02 Mask loss: 0.2096 RPN box loss: 0.02922 RPN score loss: 0.02097 RPN total loss: 0.0502 Total loss: 2.07491 timestamp: 1655016805.482171 iteration: 10350 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23316 FastRCNN class loss: 0.15152 FastRCNN total loss: 0.38468 L1 loss: 0.0000e+00 L2 loss: 1.5458 Learning rate: 0.02 Mask loss: 0.27434 RPN box loss: 0.05208 RPN score loss: 0.03834 RPN total loss: 0.09042 Total loss: 2.29525 timestamp: 1655016808.7590594 iteration: 10355 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15816 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 1.54549 Learning rate: 0.02 Mask loss: 0.13518 RPN box loss: 0.01787 RPN score loss: 0.00781 RPN total loss: 0.02568 Total loss: 1.94353 timestamp: 1655016812.1341667 iteration: 10360 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21857 FastRCNN class loss: 0.14978 FastRCNN total loss: 0.36835 L1 loss: 0.0000e+00 L2 loss: 1.5452 Learning rate: 0.02 Mask loss: 0.27558 RPN box loss: 0.0607 RPN score loss: 0.01379 RPN total loss: 0.07449 Total loss: 2.26362 timestamp: 1655016815.4289007 iteration: 10365 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15774 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.2446 L1 loss: 0.0000e+00 L2 loss: 1.54491 Learning rate: 0.02 Mask loss: 0.15959 RPN box loss: 0.0384 RPN score loss: 0.00881 RPN total loss: 0.04721 Total loss: 1.9963 timestamp: 1655016818.799861 iteration: 10370 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19443 FastRCNN class loss: 0.1146 FastRCNN total loss: 0.30903 L1 loss: 0.0000e+00 L2 loss: 1.54461 Learning rate: 0.02 Mask loss: 0.16457 RPN box loss: 0.02898 RPN score loss: 0.00316 RPN total loss: 0.03214 Total loss: 2.05035 timestamp: 1655016822.2120147 iteration: 10375 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18743 FastRCNN class loss: 0.107 FastRCNN total loss: 0.29443 L1 loss: 0.0000e+00 L2 loss: 1.54434 Learning rate: 0.02 Mask loss: 0.26449 RPN box loss: 0.03169 RPN score loss: 0.00789 RPN total loss: 0.03958 Total loss: 2.14284 timestamp: 1655016825.5179565 iteration: 10380 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15024 FastRCNN class loss: 0.10142 FastRCNN total loss: 0.25166 L1 loss: 0.0000e+00 L2 loss: 1.54407 Learning rate: 0.02 Mask loss: 0.25545 RPN box loss: 0.0474 RPN score loss: 0.01102 RPN total loss: 0.05843 Total loss: 2.10961 timestamp: 1655016828.9934938 iteration: 10385 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32025 FastRCNN class loss: 0.15807 FastRCNN total loss: 0.47832 L1 loss: 0.0000e+00 L2 loss: 1.54379 Learning rate: 0.02 Mask loss: 0.27759 RPN box loss: 0.07082 RPN score loss: 0.0637 RPN total loss: 0.13452 Total loss: 2.43422 timestamp: 1655016832.343607 iteration: 10390 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16385 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.23483 L1 loss: 0.0000e+00 L2 loss: 1.54351 Learning rate: 0.02 Mask loss: 0.27812 RPN box loss: 0.03438 RPN score loss: 0.00825 RPN total loss: 0.04263 Total loss: 2.09909 timestamp: 1655016835.8075578 iteration: 10395 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18247 FastRCNN class loss: 0.12477 FastRCNN total loss: 0.30724 L1 loss: 0.0000e+00 L2 loss: 1.54323 Learning rate: 0.02 Mask loss: 0.19963 RPN box loss: 0.0322 RPN score loss: 0.0106 RPN total loss: 0.0428 Total loss: 2.0929 timestamp: 1655016839.1328557 iteration: 10400 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13502 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.20533 L1 loss: 0.0000e+00 L2 loss: 1.54295 Learning rate: 0.02 Mask loss: 0.14736 RPN box loss: 0.01895 RPN score loss: 0.01024 RPN total loss: 0.02919 Total loss: 1.92483 timestamp: 1655016842.5243084 iteration: 10405 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15517 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.2395 L1 loss: 0.0000e+00 L2 loss: 1.54269 Learning rate: 0.02 Mask loss: 0.16976 RPN box loss: 0.00953 RPN score loss: 0.00323 RPN total loss: 0.01276 Total loss: 1.96471 timestamp: 1655016845.868755 iteration: 10410 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25709 FastRCNN class loss: 0.15697 FastRCNN total loss: 0.41406 L1 loss: 0.0000e+00 L2 loss: 1.54239 Learning rate: 0.02 Mask loss: 0.17228 RPN box loss: 0.04073 RPN score loss: 0.01397 RPN total loss: 0.05469 Total loss: 2.18343 timestamp: 1655016849.2359202 iteration: 10415 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18682 FastRCNN class loss: 0.0999 FastRCNN total loss: 0.28672 L1 loss: 0.0000e+00 L2 loss: 1.54209 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.01505 RPN score loss: 0.00898 RPN total loss: 0.02403 Total loss: 1.99996 timestamp: 1655016852.6891277 iteration: 10420 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13556 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.19301 L1 loss: 0.0000e+00 L2 loss: 1.54181 Learning rate: 0.02 Mask loss: 0.1887 RPN box loss: 0.05837 RPN score loss: 0.00807 RPN total loss: 0.06644 Total loss: 1.98995 timestamp: 1655016855.9991045 iteration: 10425 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1877 FastRCNN class loss: 0.10044 FastRCNN total loss: 0.28814 L1 loss: 0.0000e+00 L2 loss: 1.54153 Learning rate: 0.02 Mask loss: 0.25296 RPN box loss: 0.07298 RPN score loss: 0.0135 RPN total loss: 0.08648 Total loss: 2.16911 timestamp: 1655016859.4908142 iteration: 10430 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26951 FastRCNN class loss: 0.11277 FastRCNN total loss: 0.38228 L1 loss: 0.0000e+00 L2 loss: 1.54124 Learning rate: 0.02 Mask loss: 0.24357 RPN box loss: 0.04454 RPN score loss: 0.00666 RPN total loss: 0.0512 Total loss: 2.21829 timestamp: 1655016862.7900789 iteration: 10435 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14969 FastRCNN class loss: 0.1163 FastRCNN total loss: 0.26598 L1 loss: 0.0000e+00 L2 loss: 1.54093 Learning rate: 0.02 Mask loss: 0.23895 RPN box loss: 0.06516 RPN score loss: 0.01415 RPN total loss: 0.07931 Total loss: 2.12518 timestamp: 1655016866.2360897 iteration: 10440 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21614 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.31027 L1 loss: 0.0000e+00 L2 loss: 1.54066 Learning rate: 0.02 Mask loss: 0.20145 RPN box loss: 0.04005 RPN score loss: 0.00401 RPN total loss: 0.04406 Total loss: 2.09644 timestamp: 1655016869.6437657 iteration: 10445 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15413 FastRCNN class loss: 0.07757 FastRCNN total loss: 0.2317 L1 loss: 0.0000e+00 L2 loss: 1.54039 Learning rate: 0.02 Mask loss: 0.18622 RPN box loss: 0.0571 RPN score loss: 0.00644 RPN total loss: 0.06354 Total loss: 2.02185 timestamp: 1655016872.972138 iteration: 10450 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17487 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.25716 L1 loss: 0.0000e+00 L2 loss: 1.5401 Learning rate: 0.02 Mask loss: 0.17034 RPN box loss: 0.01403 RPN score loss: 0.01904 RPN total loss: 0.03307 Total loss: 2.00066 timestamp: 1655016876.4349422 iteration: 10455 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2053 FastRCNN class loss: 0.1604 FastRCNN total loss: 0.3657 L1 loss: 0.0000e+00 L2 loss: 1.53981 Learning rate: 0.02 Mask loss: 0.24657 RPN box loss: 0.08778 RPN score loss: 0.01976 RPN total loss: 0.10754 Total loss: 2.25961 timestamp: 1655016879.6928017 iteration: 10460 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14608 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.22272 L1 loss: 0.0000e+00 L2 loss: 1.53952 Learning rate: 0.02 Mask loss: 0.20092 RPN box loss: 0.08315 RPN score loss: 0.00913 RPN total loss: 0.09228 Total loss: 2.05544 timestamp: 1655016883.0720189 iteration: 10465 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17884 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.23341 L1 loss: 0.0000e+00 L2 loss: 1.53926 Learning rate: 0.02 Mask loss: 0.19443 RPN box loss: 0.00382 RPN score loss: 0.00415 RPN total loss: 0.00797 Total loss: 1.97508 timestamp: 1655016886.4522836 iteration: 10470 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16322 FastRCNN class loss: 0.1445 FastRCNN total loss: 0.30772 L1 loss: 0.0000e+00 L2 loss: 1.53898 Learning rate: 0.02 Mask loss: 0.19899 RPN box loss: 0.07675 RPN score loss: 0.01869 RPN total loss: 0.09545 Total loss: 2.14114 timestamp: 1655016889.8464828 iteration: 10475 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2447 FastRCNN class loss: 0.09161 FastRCNN total loss: 0.33631 L1 loss: 0.0000e+00 L2 loss: 1.53868 Learning rate: 0.02 Mask loss: 0.22399 RPN box loss: 0.02602 RPN score loss: 0.00383 RPN total loss: 0.02986 Total loss: 2.12883 timestamp: 1655016893.1849372 iteration: 10480 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18092 FastRCNN class loss: 0.14581 FastRCNN total loss: 0.32674 L1 loss: 0.0000e+00 L2 loss: 1.53839 Learning rate: 0.02 Mask loss: 0.19349 RPN box loss: 0.05494 RPN score loss: 0.00807 RPN total loss: 0.06301 Total loss: 2.12162 timestamp: 1655016896.5760682 iteration: 10485 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1158 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.18799 L1 loss: 0.0000e+00 L2 loss: 1.53812 Learning rate: 0.02 Mask loss: 0.15 RPN box loss: 0.05802 RPN score loss: 0.01426 RPN total loss: 0.07228 Total loss: 1.94839 timestamp: 1655016899.8998234 iteration: 10490 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08194 FastRCNN class loss: 0.04805 FastRCNN total loss: 0.12999 L1 loss: 0.0000e+00 L2 loss: 1.53785 Learning rate: 0.02 Mask loss: 0.14194 RPN box loss: 0.05994 RPN score loss: 0.01512 RPN total loss: 0.07506 Total loss: 1.88485 timestamp: 1655016903.1852927 iteration: 10495 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19187 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.28201 L1 loss: 0.0000e+00 L2 loss: 1.53759 Learning rate: 0.02 Mask loss: 0.25581 RPN box loss: 0.03245 RPN score loss: 0.00606 RPN total loss: 0.03851 Total loss: 2.11392 timestamp: 1655016906.5595706 iteration: 10500 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23939 FastRCNN class loss: 0.09297 FastRCNN total loss: 0.33236 L1 loss: 0.0000e+00 L2 loss: 1.53734 Learning rate: 0.02 Mask loss: 0.16784 RPN box loss: 0.01683 RPN score loss: 0.00575 RPN total loss: 0.02258 Total loss: 2.06011 timestamp: 1655016909.8303568 iteration: 10505 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.149 FastRCNN class loss: 0.06102 FastRCNN total loss: 0.21002 L1 loss: 0.0000e+00 L2 loss: 1.53706 Learning rate: 0.02 Mask loss: 0.20644 RPN box loss: 0.00526 RPN score loss: 0.01229 RPN total loss: 0.01755 Total loss: 1.97106 timestamp: 1655016913.176466 iteration: 10510 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16142 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.22272 L1 loss: 0.0000e+00 L2 loss: 1.53676 Learning rate: 0.02 Mask loss: 0.16639 RPN box loss: 0.05686 RPN score loss: 0.0067 RPN total loss: 0.06356 Total loss: 1.98944 timestamp: 1655016916.4611988 iteration: 10515 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13881 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.21723 L1 loss: 0.0000e+00 L2 loss: 1.53647 Learning rate: 0.02 Mask loss: 0.17436 RPN box loss: 0.04319 RPN score loss: 0.0116 RPN total loss: 0.05479 Total loss: 1.98285 timestamp: 1655016919.8310225 iteration: 10520 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11538 FastRCNN class loss: 0.0569 FastRCNN total loss: 0.17227 L1 loss: 0.0000e+00 L2 loss: 1.53619 Learning rate: 0.02 Mask loss: 0.13739 RPN box loss: 0.01658 RPN score loss: 0.00606 RPN total loss: 0.02264 Total loss: 1.86849 timestamp: 1655016923.1514266 iteration: 10525 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16722 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.23906 L1 loss: 0.0000e+00 L2 loss: 1.53591 Learning rate: 0.02 Mask loss: 0.15232 RPN box loss: 0.06703 RPN score loss: 0.00551 RPN total loss: 0.07254 Total loss: 1.99983 timestamp: 1655016926.4419608 iteration: 10530 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14817 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.24021 L1 loss: 0.0000e+00 L2 loss: 1.53564 Learning rate: 0.02 Mask loss: 0.20904 RPN box loss: 0.06436 RPN score loss: 0.00757 RPN total loss: 0.07193 Total loss: 2.05683 timestamp: 1655016929.875628 iteration: 10535 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15946 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.24183 L1 loss: 0.0000e+00 L2 loss: 1.53537 Learning rate: 0.02 Mask loss: 0.17129 RPN box loss: 0.02544 RPN score loss: 0.00624 RPN total loss: 0.03168 Total loss: 1.98017 timestamp: 1655016933.1237097 iteration: 10540 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13458 FastRCNN class loss: 0.059 FastRCNN total loss: 0.19359 L1 loss: 0.0000e+00 L2 loss: 1.53509 Learning rate: 0.02 Mask loss: 0.09159 RPN box loss: 0.00987 RPN score loss: 0.00196 RPN total loss: 0.01184 Total loss: 1.8321 timestamp: 1655016936.5547526 iteration: 10545 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25041 FastRCNN class loss: 0.12401 FastRCNN total loss: 0.37441 L1 loss: 0.0000e+00 L2 loss: 1.53478 Learning rate: 0.02 Mask loss: 0.241 RPN box loss: 0.09245 RPN score loss: 0.03073 RPN total loss: 0.12318 Total loss: 2.27338 timestamp: 1655016939.8402796 iteration: 10550 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17644 FastRCNN class loss: 0.09676 FastRCNN total loss: 0.2732 L1 loss: 0.0000e+00 L2 loss: 1.5345 Learning rate: 0.02 Mask loss: 0.2174 RPN box loss: 0.02585 RPN score loss: 0.02151 RPN total loss: 0.04736 Total loss: 2.07246 timestamp: 1655016943.311481 iteration: 10555 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.23295 L1 loss: 0.0000e+00 L2 loss: 1.53424 Learning rate: 0.02 Mask loss: 0.23465 RPN box loss: 0.03995 RPN score loss: 0.01203 RPN total loss: 0.05198 Total loss: 2.05382 timestamp: 1655016946.5694146 iteration: 10560 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30504 FastRCNN class loss: 0.15559 FastRCNN total loss: 0.46064 L1 loss: 0.0000e+00 L2 loss: 1.53394 Learning rate: 0.02 Mask loss: 0.28825 RPN box loss: 0.0412 RPN score loss: 0.01599 RPN total loss: 0.05719 Total loss: 2.34002 timestamp: 1655016949.9206846 iteration: 10565 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1193 FastRCNN class loss: 0.06994 FastRCNN total loss: 0.18924 L1 loss: 0.0000e+00 L2 loss: 1.53366 Learning rate: 0.02 Mask loss: 0.1994 RPN box loss: 0.0351 RPN score loss: 0.00873 RPN total loss: 0.04382 Total loss: 1.96613 timestamp: 1655016953.163265 iteration: 10570 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20618 FastRCNN class loss: 0.08781 FastRCNN total loss: 0.29399 L1 loss: 0.0000e+00 L2 loss: 1.53338 Learning rate: 0.02 Mask loss: 0.32717 RPN box loss: 0.04335 RPN score loss: 0.01318 RPN total loss: 0.05653 Total loss: 2.21107 timestamp: 1655016956.592568 iteration: 10575 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1096 FastRCNN class loss: 0.04847 FastRCNN total loss: 0.15807 L1 loss: 0.0000e+00 L2 loss: 1.53309 Learning rate: 0.02 Mask loss: 0.17579 RPN box loss: 0.03618 RPN score loss: 0.0074 RPN total loss: 0.04358 Total loss: 1.91053 timestamp: 1655016959.958037 iteration: 10580 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19126 FastRCNN class loss: 0.17553 FastRCNN total loss: 0.36678 L1 loss: 0.0000e+00 L2 loss: 1.53282 Learning rate: 0.02 Mask loss: 0.17987 RPN box loss: 0.02138 RPN score loss: 0.00863 RPN total loss: 0.03002 Total loss: 2.10949 timestamp: 1655016963.3025255 iteration: 10585 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2642 FastRCNN class loss: 0.14804 FastRCNN total loss: 0.41225 L1 loss: 0.0000e+00 L2 loss: 1.53253 Learning rate: 0.02 Mask loss: 0.37362 RPN box loss: 0.01481 RPN score loss: 0.01736 RPN total loss: 0.03217 Total loss: 2.35057 timestamp: 1655016966.7288709 iteration: 10590 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20074 FastRCNN class loss: 0.1027 FastRCNN total loss: 0.30344 L1 loss: 0.0000e+00 L2 loss: 1.53224 Learning rate: 0.02 Mask loss: 0.19961 RPN box loss: 0.02646 RPN score loss: 0.00553 RPN total loss: 0.03199 Total loss: 2.06728 timestamp: 1655016969.9904642 iteration: 10595 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23902 FastRCNN class loss: 0.10497 FastRCNN total loss: 0.34399 L1 loss: 0.0000e+00 L2 loss: 1.53198 Learning rate: 0.02 Mask loss: 0.17482 RPN box loss: 0.02711 RPN score loss: 0.01318 RPN total loss: 0.04029 Total loss: 2.09108 timestamp: 1655016973.3895006 iteration: 10600 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22501 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.31354 L1 loss: 0.0000e+00 L2 loss: 1.53172 Learning rate: 0.02 Mask loss: 0.14244 RPN box loss: 0.06748 RPN score loss: 0.00922 RPN total loss: 0.0767 Total loss: 2.06441 timestamp: 1655016976.6187558 iteration: 10605 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17961 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.26063 L1 loss: 0.0000e+00 L2 loss: 1.53145 Learning rate: 0.02 Mask loss: 0.15831 RPN box loss: 0.03706 RPN score loss: 0.01444 RPN total loss: 0.05151 Total loss: 2.00189 timestamp: 1655016979.961701 iteration: 10610 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20113 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.28006 L1 loss: 0.0000e+00 L2 loss: 1.53115 Learning rate: 0.02 Mask loss: 0.18354 RPN box loss: 0.07567 RPN score loss: 0.00821 RPN total loss: 0.08388 Total loss: 2.07864 timestamp: 1655016983.2967649 iteration: 10615 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23353 FastRCNN class loss: 0.10476 FastRCNN total loss: 0.33829 L1 loss: 0.0000e+00 L2 loss: 1.53087 Learning rate: 0.02 Mask loss: 0.24415 RPN box loss: 0.04323 RPN score loss: 0.00992 RPN total loss: 0.05315 Total loss: 2.16646 timestamp: 1655016986.6186047 iteration: 10620 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20749 FastRCNN class loss: 0.1275 FastRCNN total loss: 0.33499 L1 loss: 0.0000e+00 L2 loss: 1.53058 Learning rate: 0.02 Mask loss: 0.25399 RPN box loss: 0.01364 RPN score loss: 0.00626 RPN total loss: 0.0199 Total loss: 2.13946 timestamp: 1655016990.0675716 iteration: 10625 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18541 FastRCNN class loss: 0.09426 FastRCNN total loss: 0.27967 L1 loss: 0.0000e+00 L2 loss: 1.53029 Learning rate: 0.02 Mask loss: 0.17798 RPN box loss: 0.02249 RPN score loss: 0.01018 RPN total loss: 0.03267 Total loss: 2.02061 timestamp: 1655016993.3147893 iteration: 10630 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10528 FastRCNN class loss: 0.04711 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 1.53 Learning rate: 0.02 Mask loss: 0.13912 RPN box loss: 0.09358 RPN score loss: 0.01273 RPN total loss: 0.10632 Total loss: 1.92782 timestamp: 1655016996.6662166 iteration: 10635 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1654 FastRCNN class loss: 0.09851 FastRCNN total loss: 0.26391 L1 loss: 0.0000e+00 L2 loss: 1.52974 Learning rate: 0.02 Mask loss: 0.16479 RPN box loss: 0.0153 RPN score loss: 0.00472 RPN total loss: 0.02002 Total loss: 1.97846 timestamp: 1655016999.9157438 iteration: 10640 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25514 FastRCNN class loss: 0.13492 FastRCNN total loss: 0.39006 L1 loss: 0.0000e+00 L2 loss: 1.52949 Learning rate: 0.02 Mask loss: 0.22811 RPN box loss: 0.05014 RPN score loss: 0.01109 RPN total loss: 0.06123 Total loss: 2.20889 timestamp: 1655017003.2477353 iteration: 10645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22927 FastRCNN class loss: 0.12296 FastRCNN total loss: 0.35223 L1 loss: 0.0000e+00 L2 loss: 1.52923 Learning rate: 0.02 Mask loss: 0.1938 RPN box loss: 0.02311 RPN score loss: 0.00753 RPN total loss: 0.03064 Total loss: 2.10591 timestamp: 1655017006.4815834 iteration: 10650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09914 FastRCNN class loss: 0.07395 FastRCNN total loss: 0.17309 L1 loss: 0.0000e+00 L2 loss: 1.52894 Learning rate: 0.02 Mask loss: 0.17804 RPN box loss: 0.06941 RPN score loss: 0.01209 RPN total loss: 0.0815 Total loss: 1.96158 timestamp: 1655017009.8458464 iteration: 10655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14286 FastRCNN class loss: 0.09553 FastRCNN total loss: 0.23838 L1 loss: 0.0000e+00 L2 loss: 1.52864 Learning rate: 0.02 Mask loss: 0.18261 RPN box loss: 0.02007 RPN score loss: 0.00827 RPN total loss: 0.02833 Total loss: 1.97797 timestamp: 1655017013.1197534 iteration: 10660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19147 FastRCNN class loss: 0.10851 FastRCNN total loss: 0.29998 L1 loss: 0.0000e+00 L2 loss: 1.52839 Learning rate: 0.02 Mask loss: 0.31575 RPN box loss: 0.08913 RPN score loss: 0.00935 RPN total loss: 0.09849 Total loss: 2.24261 timestamp: 1655017016.4704254 iteration: 10665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13747 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.20199 L1 loss: 0.0000e+00 L2 loss: 1.5281 Learning rate: 0.02 Mask loss: 0.20947 RPN box loss: 0.04932 RPN score loss: 0.00538 RPN total loss: 0.0547 Total loss: 1.99425 timestamp: 1655017019.9395053 iteration: 10670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20591 FastRCNN class loss: 0.10961 FastRCNN total loss: 0.31552 L1 loss: 0.0000e+00 L2 loss: 1.52779 Learning rate: 0.02 Mask loss: 0.2055 RPN box loss: 0.04557 RPN score loss: 0.00527 RPN total loss: 0.05084 Total loss: 2.09965 timestamp: 1655017023.2008905 iteration: 10675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16683 FastRCNN class loss: 0.05816 FastRCNN total loss: 0.22498 L1 loss: 0.0000e+00 L2 loss: 1.52754 Learning rate: 0.02 Mask loss: 0.17319 RPN box loss: 0.00428 RPN score loss: 0.00373 RPN total loss: 0.00802 Total loss: 1.93374 timestamp: 1655017026.6028485 iteration: 10680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18604 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.26074 L1 loss: 0.0000e+00 L2 loss: 1.52728 Learning rate: 0.02 Mask loss: 0.11019 RPN box loss: 0.06707 RPN score loss: 0.0117 RPN total loss: 0.07877 Total loss: 1.97698 timestamp: 1655017029.835598 iteration: 10685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16526 FastRCNN class loss: 0.10022 FastRCNN total loss: 0.26548 L1 loss: 0.0000e+00 L2 loss: 1.52699 Learning rate: 0.02 Mask loss: 0.25641 RPN box loss: 0.06867 RPN score loss: 0.01186 RPN total loss: 0.08054 Total loss: 2.12941 timestamp: 1655017033.1888666 iteration: 10690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23281 FastRCNN class loss: 0.14329 FastRCNN total loss: 0.3761 L1 loss: 0.0000e+00 L2 loss: 1.5267 Learning rate: 0.02 Mask loss: 0.22862 RPN box loss: 0.03962 RPN score loss: 0.00812 RPN total loss: 0.04774 Total loss: 2.17916 timestamp: 1655017036.4949973 iteration: 10695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20817 FastRCNN class loss: 0.12024 FastRCNN total loss: 0.32841 L1 loss: 0.0000e+00 L2 loss: 1.52643 Learning rate: 0.02 Mask loss: 0.37168 RPN box loss: 0.06848 RPN score loss: 0.0102 RPN total loss: 0.07869 Total loss: 2.30521 timestamp: 1655017039.890219 iteration: 10700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23082 FastRCNN class loss: 0.11951 FastRCNN total loss: 0.35033 L1 loss: 0.0000e+00 L2 loss: 1.52614 Learning rate: 0.02 Mask loss: 0.27982 RPN box loss: 0.02602 RPN score loss: 0.0139 RPN total loss: 0.03992 Total loss: 2.1962 timestamp: 1655017043.177887 iteration: 10705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.145 FastRCNN class loss: 0.08494 FastRCNN total loss: 0.22995 L1 loss: 0.0000e+00 L2 loss: 1.52587 Learning rate: 0.02 Mask loss: 0.14305 RPN box loss: 0.00554 RPN score loss: 0.00381 RPN total loss: 0.00935 Total loss: 1.90822 timestamp: 1655017046.532193 iteration: 10710 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14637 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.21424 L1 loss: 0.0000e+00 L2 loss: 1.52557 Learning rate: 0.02 Mask loss: 0.17874 RPN box loss: 0.01722 RPN score loss: 0.00346 RPN total loss: 0.02068 Total loss: 1.93924 timestamp: 1655017049.8843565 iteration: 10715 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12356 FastRCNN class loss: 0.06605 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 1.5253 Learning rate: 0.02 Mask loss: 0.15141 RPN box loss: 0.03881 RPN score loss: 0.00548 RPN total loss: 0.0443 Total loss: 1.91062 timestamp: 1655017053.2359538 iteration: 10720 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.36747 FastRCNN class loss: 0.09219 FastRCNN total loss: 0.45965 L1 loss: 0.0000e+00 L2 loss: 1.52503 Learning rate: 0.02 Mask loss: 0.16504 RPN box loss: 0.07443 RPN score loss: 0.01558 RPN total loss: 0.09001 Total loss: 2.23974 timestamp: 1655017056.621979 iteration: 10725 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1 FastRCNN class loss: 0.05634 FastRCNN total loss: 0.15634 L1 loss: 0.0000e+00 L2 loss: 1.52475 Learning rate: 0.02 Mask loss: 0.22791 RPN box loss: 0.02063 RPN score loss: 0.00665 RPN total loss: 0.02728 Total loss: 1.93628 timestamp: 1655017059.8809624 iteration: 10730 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11639 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.18212 L1 loss: 0.0000e+00 L2 loss: 1.52446 Learning rate: 0.02 Mask loss: 0.18225 RPN box loss: 0.05601 RPN score loss: 0.01009 RPN total loss: 0.0661 Total loss: 1.95493 timestamp: 1655017063.2157254 iteration: 10735 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14915 FastRCNN class loss: 0.09941 FastRCNN total loss: 0.24856 L1 loss: 0.0000e+00 L2 loss: 1.52417 Learning rate: 0.02 Mask loss: 0.12397 RPN box loss: 0.04402 RPN score loss: 0.00667 RPN total loss: 0.0507 Total loss: 1.94739 timestamp: 1655017066.4739385 iteration: 10740 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09581 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.14987 L1 loss: 0.0000e+00 L2 loss: 1.52389 Learning rate: 0.02 Mask loss: 0.12898 RPN box loss: 0.03428 RPN score loss: 0.00768 RPN total loss: 0.04196 Total loss: 1.84471 timestamp: 1655017069.7891824 iteration: 10745 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15866 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.23874 L1 loss: 0.0000e+00 L2 loss: 1.5236 Learning rate: 0.02 Mask loss: 0.22452 RPN box loss: 0.02239 RPN score loss: 0.00516 RPN total loss: 0.02755 Total loss: 2.01441 timestamp: 1655017073.0440712 iteration: 10750 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.262 FastRCNN class loss: 0.12357 FastRCNN total loss: 0.38557 L1 loss: 0.0000e+00 L2 loss: 1.52333 Learning rate: 0.02 Mask loss: 0.19748 RPN box loss: 0.03777 RPN score loss: 0.0315 RPN total loss: 0.06927 Total loss: 2.17565 timestamp: 1655017076.3676488 iteration: 10755 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14857 FastRCNN class loss: 0.13547 FastRCNN total loss: 0.28405 L1 loss: 0.0000e+00 L2 loss: 1.52304 Learning rate: 0.02 Mask loss: 0.20798 RPN box loss: 0.04632 RPN score loss: 0.01718 RPN total loss: 0.0635 Total loss: 2.07856 timestamp: 1655017079.6973753 iteration: 10760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18696 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.26523 L1 loss: 0.0000e+00 L2 loss: 1.52274 Learning rate: 0.02 Mask loss: 0.15452 RPN box loss: 0.03296 RPN score loss: 0.0059 RPN total loss: 0.03886 Total loss: 1.98135 timestamp: 1655017082.9720368 iteration: 10765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27085 FastRCNN class loss: 0.10091 FastRCNN total loss: 0.37176 L1 loss: 0.0000e+00 L2 loss: 1.52245 Learning rate: 0.02 Mask loss: 0.20797 RPN box loss: 0.02449 RPN score loss: 0.00701 RPN total loss: 0.0315 Total loss: 2.13368 timestamp: 1655017086.4468248 iteration: 10770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30632 FastRCNN class loss: 0.11385 FastRCNN total loss: 0.42017 L1 loss: 0.0000e+00 L2 loss: 1.52217 Learning rate: 0.02 Mask loss: 0.21648 RPN box loss: 0.0468 RPN score loss: 0.00493 RPN total loss: 0.05173 Total loss: 2.21054 timestamp: 1655017089.7359433 iteration: 10775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13841 FastRCNN class loss: 0.07239 FastRCNN total loss: 0.21081 L1 loss: 0.0000e+00 L2 loss: 1.52192 Learning rate: 0.02 Mask loss: 0.15455 RPN box loss: 0.04798 RPN score loss: 0.00774 RPN total loss: 0.05573 Total loss: 1.943 timestamp: 1655017093.1335065 iteration: 10780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10082 FastRCNN class loss: 0.057 FastRCNN total loss: 0.15782 L1 loss: 0.0000e+00 L2 loss: 1.52165 Learning rate: 0.02 Mask loss: 0.23652 RPN box loss: 0.01809 RPN score loss: 0.00563 RPN total loss: 0.02372 Total loss: 1.9397 timestamp: 1655017096.452588 iteration: 10785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1696 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.26123 L1 loss: 0.0000e+00 L2 loss: 1.52134 Learning rate: 0.02 Mask loss: 0.20891 RPN box loss: 0.05261 RPN score loss: 0.01162 RPN total loss: 0.06423 Total loss: 2.05572 timestamp: 1655017099.8217332 iteration: 10790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13934 FastRCNN class loss: 0.11914 FastRCNN total loss: 0.25848 L1 loss: 0.0000e+00 L2 loss: 1.52104 Learning rate: 0.02 Mask loss: 0.15405 RPN box loss: 0.0256 RPN score loss: 0.00758 RPN total loss: 0.03318 Total loss: 1.96674 timestamp: 1655017103.075581 iteration: 10795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.09716 FastRCNN total loss: 0.22122 L1 loss: 0.0000e+00 L2 loss: 1.52077 Learning rate: 0.02 Mask loss: 0.17952 RPN box loss: 0.0311 RPN score loss: 0.00557 RPN total loss: 0.03667 Total loss: 1.95818 timestamp: 1655017106.433869 iteration: 10800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24164 FastRCNN class loss: 0.07815 FastRCNN total loss: 0.31979 L1 loss: 0.0000e+00 L2 loss: 1.52051 Learning rate: 0.02 Mask loss: 0.2013 RPN box loss: 0.03399 RPN score loss: 0.00432 RPN total loss: 0.03831 Total loss: 2.07991 timestamp: 1655017109.8400779 iteration: 10805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22927 FastRCNN class loss: 0.11982 FastRCNN total loss: 0.34908 L1 loss: 0.0000e+00 L2 loss: 1.52026 Learning rate: 0.02 Mask loss: 0.24931 RPN box loss: 0.05437 RPN score loss: 0.00841 RPN total loss: 0.06278 Total loss: 2.18143 timestamp: 1655017113.0803611 iteration: 10810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13828 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.19254 L1 loss: 0.0000e+00 L2 loss: 1.52 Learning rate: 0.02 Mask loss: 0.2188 RPN box loss: 0.00544 RPN score loss: 0.00643 RPN total loss: 0.01187 Total loss: 1.94321 timestamp: 1655017116.3883345 iteration: 10815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16186 FastRCNN class loss: 0.08461 FastRCNN total loss: 0.24647 L1 loss: 0.0000e+00 L2 loss: 1.5197 Learning rate: 0.02 Mask loss: 0.19854 RPN box loss: 0.0757 RPN score loss: 0.0096 RPN total loss: 0.0853 Total loss: 2.05002 timestamp: 1655017119.633655 iteration: 10820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23128 FastRCNN class loss: 0.12689 FastRCNN total loss: 0.35817 L1 loss: 0.0000e+00 L2 loss: 1.51943 Learning rate: 0.02 Mask loss: 0.23963 RPN box loss: 0.01749 RPN score loss: 0.00498 RPN total loss: 0.02247 Total loss: 2.1397 timestamp: 1655017122.995486 iteration: 10825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17526 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.26212 L1 loss: 0.0000e+00 L2 loss: 1.51915 Learning rate: 0.02 Mask loss: 0.22931 RPN box loss: 0.06025 RPN score loss: 0.01794 RPN total loss: 0.0782 Total loss: 2.08877 timestamp: 1655017126.2494023 iteration: 10830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18494 FastRCNN class loss: 0.1173 FastRCNN total loss: 0.30225 L1 loss: 0.0000e+00 L2 loss: 1.51886 Learning rate: 0.02 Mask loss: 0.19615 RPN box loss: 0.02806 RPN score loss: 0.00773 RPN total loss: 0.03579 Total loss: 2.05305 timestamp: 1655017129.7773952 iteration: 10835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13141 FastRCNN class loss: 0.10488 FastRCNN total loss: 0.23629 L1 loss: 0.0000e+00 L2 loss: 1.51858 Learning rate: 0.02 Mask loss: 0.14486 RPN box loss: 0.0395 RPN score loss: 0.00806 RPN total loss: 0.04756 Total loss: 1.94729 timestamp: 1655017133.123039 iteration: 10840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21937 FastRCNN class loss: 0.08193 FastRCNN total loss: 0.3013 L1 loss: 0.0000e+00 L2 loss: 1.51829 Learning rate: 0.02 Mask loss: 0.19006 RPN box loss: 0.03065 RPN score loss: 0.00604 RPN total loss: 0.03669 Total loss: 2.04634 timestamp: 1655017136.468003 iteration: 10845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15161 FastRCNN class loss: 0.08576 FastRCNN total loss: 0.23737 L1 loss: 0.0000e+00 L2 loss: 1.51803 Learning rate: 0.02 Mask loss: 0.16421 RPN box loss: 0.01874 RPN score loss: 0.00429 RPN total loss: 0.02303 Total loss: 1.94264 timestamp: 1655017139.8445477 iteration: 10850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12499 FastRCNN class loss: 0.08389 FastRCNN total loss: 0.20887 L1 loss: 0.0000e+00 L2 loss: 1.51775 Learning rate: 0.02 Mask loss: 0.13742 RPN box loss: 0.04869 RPN score loss: 0.00707 RPN total loss: 0.05575 Total loss: 1.9198 timestamp: 1655017143.1384826 iteration: 10855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16531 FastRCNN class loss: 0.10447 FastRCNN total loss: 0.26978 L1 loss: 0.0000e+00 L2 loss: 1.51748 Learning rate: 0.02 Mask loss: 0.1505 RPN box loss: 0.02781 RPN score loss: 0.00505 RPN total loss: 0.03286 Total loss: 1.97061 timestamp: 1655017146.4325037 iteration: 10860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1469 FastRCNN class loss: 0.1186 FastRCNN total loss: 0.2655 L1 loss: 0.0000e+00 L2 loss: 1.5172 Learning rate: 0.02 Mask loss: 0.18206 RPN box loss: 0.05231 RPN score loss: 0.01475 RPN total loss: 0.06706 Total loss: 2.03182 timestamp: 1655017149.676565 iteration: 10865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16547 FastRCNN class loss: 0.08454 FastRCNN total loss: 0.25 L1 loss: 0.0000e+00 L2 loss: 1.51691 Learning rate: 0.02 Mask loss: 0.1967 RPN box loss: 0.03457 RPN score loss: 0.00346 RPN total loss: 0.03803 Total loss: 2.00164 timestamp: 1655017153.091978 iteration: 10870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18172 FastRCNN class loss: 0.11967 FastRCNN total loss: 0.30138 L1 loss: 0.0000e+00 L2 loss: 1.51663 Learning rate: 0.02 Mask loss: 0.19445 RPN box loss: 0.08735 RPN score loss: 0.01226 RPN total loss: 0.09961 Total loss: 2.11207 timestamp: 1655017156.3659708 iteration: 10875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1902 FastRCNN class loss: 0.13473 FastRCNN total loss: 0.32493 L1 loss: 0.0000e+00 L2 loss: 1.51636 Learning rate: 0.02 Mask loss: 0.24075 RPN box loss: 0.04353 RPN score loss: 0.0159 RPN total loss: 0.05943 Total loss: 2.14147 timestamp: 1655017159.7076244 iteration: 10880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21675 FastRCNN class loss: 0.17048 FastRCNN total loss: 0.38722 L1 loss: 0.0000e+00 L2 loss: 1.51606 Learning rate: 0.02 Mask loss: 0.29432 RPN box loss: 0.06693 RPN score loss: 0.02125 RPN total loss: 0.08818 Total loss: 2.28578 timestamp: 1655017162.9983227 iteration: 10885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12741 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.22264 L1 loss: 0.0000e+00 L2 loss: 1.51578 Learning rate: 0.02 Mask loss: 0.16839 RPN box loss: 0.03312 RPN score loss: 0.01253 RPN total loss: 0.04565 Total loss: 1.95247 timestamp: 1655017166.3568165 iteration: 10890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15755 FastRCNN class loss: 0.07575 FastRCNN total loss: 0.2333 L1 loss: 0.0000e+00 L2 loss: 1.51552 Learning rate: 0.02 Mask loss: 0.21615 RPN box loss: 0.08434 RPN score loss: 0.01462 RPN total loss: 0.09896 Total loss: 2.06393 timestamp: 1655017169.738147 iteration: 10895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16821 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.25238 L1 loss: 0.0000e+00 L2 loss: 1.51526 Learning rate: 0.02 Mask loss: 0.12369 RPN box loss: 0.03839 RPN score loss: 0.00699 RPN total loss: 0.04538 Total loss: 1.9367 timestamp: 1655017173.0193264 iteration: 10900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09542 FastRCNN class loss: 0.07847 FastRCNN total loss: 0.17389 L1 loss: 0.0000e+00 L2 loss: 1.51501 Learning rate: 0.02 Mask loss: 0.22389 RPN box loss: 0.04149 RPN score loss: 0.03146 RPN total loss: 0.07295 Total loss: 1.98574 timestamp: 1655017176.5265417 iteration: 10905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.1794 L1 loss: 0.0000e+00 L2 loss: 1.51472 Learning rate: 0.02 Mask loss: 0.12148 RPN box loss: 0.03449 RPN score loss: 0.00762 RPN total loss: 0.04211 Total loss: 1.8577 timestamp: 1655017179.7892609 iteration: 10910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16378 FastRCNN class loss: 0.09777 FastRCNN total loss: 0.26156 L1 loss: 0.0000e+00 L2 loss: 1.51443 Learning rate: 0.02 Mask loss: 0.20871 RPN box loss: 0.05773 RPN score loss: 0.02562 RPN total loss: 0.08335 Total loss: 2.06804 timestamp: 1655017183.1895187 iteration: 10915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15172 FastRCNN class loss: 0.0923 FastRCNN total loss: 0.24402 L1 loss: 0.0000e+00 L2 loss: 1.51415 Learning rate: 0.02 Mask loss: 0.12951 RPN box loss: 0.07843 RPN score loss: 0.01641 RPN total loss: 0.09484 Total loss: 1.98252 timestamp: 1655017186.4688005 iteration: 10920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13586 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.20657 L1 loss: 0.0000e+00 L2 loss: 1.51388 Learning rate: 0.02 Mask loss: 0.19117 RPN box loss: 0.03621 RPN score loss: 0.00933 RPN total loss: 0.04554 Total loss: 1.95716 timestamp: 1655017189.8397555 iteration: 10925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12368 FastRCNN class loss: 0.06793 FastRCNN total loss: 0.19161 L1 loss: 0.0000e+00 L2 loss: 1.51361 Learning rate: 0.02 Mask loss: 0.16566 RPN box loss: 0.01694 RPN score loss: 0.00247 RPN total loss: 0.01941 Total loss: 1.89028 timestamp: 1655017193.2371206 iteration: 10930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13724 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.19933 L1 loss: 0.0000e+00 L2 loss: 1.51336 Learning rate: 0.02 Mask loss: 0.17144 RPN box loss: 0.01753 RPN score loss: 0.00988 RPN total loss: 0.02742 Total loss: 1.91155 timestamp: 1655017196.622047 iteration: 10935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28901 FastRCNN class loss: 0.12055 FastRCNN total loss: 0.40956 L1 loss: 0.0000e+00 L2 loss: 1.51307 Learning rate: 0.02 Mask loss: 0.26845 RPN box loss: 0.0295 RPN score loss: 0.01371 RPN total loss: 0.04321 Total loss: 2.2343 timestamp: 1655017200.0658524 iteration: 10940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19875 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.29407 L1 loss: 0.0000e+00 L2 loss: 1.5128 Learning rate: 0.02 Mask loss: 0.16854 RPN box loss: 0.01928 RPN score loss: 0.00765 RPN total loss: 0.02693 Total loss: 2.00234 timestamp: 1655017203.3295238 iteration: 10945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12402 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.20209 L1 loss: 0.0000e+00 L2 loss: 1.51251 Learning rate: 0.02 Mask loss: 0.21811 RPN box loss: 0.03326 RPN score loss: 0.01136 RPN total loss: 0.04462 Total loss: 1.97733 timestamp: 1655017206.7480516 iteration: 10950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17088 FastRCNN class loss: 0.12914 FastRCNN total loss: 0.30002 L1 loss: 0.0000e+00 L2 loss: 1.51224 Learning rate: 0.02 Mask loss: 0.21206 RPN box loss: 0.04355 RPN score loss: 0.02482 RPN total loss: 0.06838 Total loss: 2.09269 timestamp: 1655017210.041517 iteration: 10955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18701 FastRCNN class loss: 0.08697 FastRCNN total loss: 0.27398 L1 loss: 0.0000e+00 L2 loss: 1.51196 Learning rate: 0.02 Mask loss: 0.16896 RPN box loss: 0.05966 RPN score loss: 0.01143 RPN total loss: 0.07109 Total loss: 2.02599 timestamp: 1655017213.422022 iteration: 10960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21105 FastRCNN class loss: 0.12447 FastRCNN total loss: 0.33553 L1 loss: 0.0000e+00 L2 loss: 1.51168 Learning rate: 0.02 Mask loss: 0.18503 RPN box loss: 0.04625 RPN score loss: 0.00843 RPN total loss: 0.05468 Total loss: 2.08691 timestamp: 1655017216.6801972 iteration: 10965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16571 FastRCNN class loss: 0.09894 FastRCNN total loss: 0.26465 L1 loss: 0.0000e+00 L2 loss: 1.5114 Learning rate: 0.02 Mask loss: 0.24522 RPN box loss: 0.05087 RPN score loss: 0.00645 RPN total loss: 0.05732 Total loss: 2.0786 timestamp: 1655017220.1097107 iteration: 10970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25672 FastRCNN class loss: 0.12065 FastRCNN total loss: 0.37738 L1 loss: 0.0000e+00 L2 loss: 1.51113 Learning rate: 0.02 Mask loss: 0.22127 RPN box loss: 0.06471 RPN score loss: 0.01149 RPN total loss: 0.0762 Total loss: 2.18598 timestamp: 1655017223.4606094 iteration: 10975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1937 FastRCNN class loss: 0.09388 FastRCNN total loss: 0.28758 L1 loss: 0.0000e+00 L2 loss: 1.51084 Learning rate: 0.02 Mask loss: 0.15371 RPN box loss: 0.06995 RPN score loss: 0.00638 RPN total loss: 0.07633 Total loss: 2.02846 timestamp: 1655017226.7373555 iteration: 10980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1795 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.26965 L1 loss: 0.0000e+00 L2 loss: 1.51055 Learning rate: 0.02 Mask loss: 0.16826 RPN box loss: 0.08824 RPN score loss: 0.00884 RPN total loss: 0.09708 Total loss: 2.04554 timestamp: 1655017230.0029385 iteration: 10985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08582 FastRCNN class loss: 0.09111 FastRCNN total loss: 0.17693 L1 loss: 0.0000e+00 L2 loss: 1.51027 Learning rate: 0.02 Mask loss: 0.26297 RPN box loss: 0.00685 RPN score loss: 0.00926 RPN total loss: 0.01611 Total loss: 1.96627 timestamp: 1655017233.2726433 iteration: 10990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14183 FastRCNN class loss: 0.09722 FastRCNN total loss: 0.23905 L1 loss: 0.0000e+00 L2 loss: 1.51001 Learning rate: 0.02 Mask loss: 0.17384 RPN box loss: 0.04784 RPN score loss: 0.00478 RPN total loss: 0.05262 Total loss: 1.97552 timestamp: 1655017236.6744237 iteration: 10995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14099 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.22396 L1 loss: 0.0000e+00 L2 loss: 1.50973 Learning rate: 0.02 Mask loss: 0.16426 RPN box loss: 0.09938 RPN score loss: 0.02683 RPN total loss: 0.12622 Total loss: 2.02417 timestamp: 1655017239.9282007 iteration: 11000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16514 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.22663 L1 loss: 0.0000e+00 L2 loss: 1.50946 Learning rate: 0.02 Mask loss: 0.16182 RPN box loss: 0.06098 RPN score loss: 0.00688 RPN total loss: 0.06786 Total loss: 1.96577 timestamp: 1655017243.3015676 iteration: 11005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11019 FastRCNN class loss: 0.05145 FastRCNN total loss: 0.16164 L1 loss: 0.0000e+00 L2 loss: 1.50919 Learning rate: 0.02 Mask loss: 0.14178 RPN box loss: 0.0729 RPN score loss: 0.00785 RPN total loss: 0.08075 Total loss: 1.89336 timestamp: 1655017246.5950694 iteration: 11010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27915 FastRCNN class loss: 0.10225 FastRCNN total loss: 0.38139 L1 loss: 0.0000e+00 L2 loss: 1.50892 Learning rate: 0.02 Mask loss: 0.19042 RPN box loss: 0.05834 RPN score loss: 0.00909 RPN total loss: 0.06743 Total loss: 2.14816 timestamp: 1655017250.0613728 iteration: 11015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.05099 FastRCNN total loss: 0.15251 L1 loss: 0.0000e+00 L2 loss: 1.50864 Learning rate: 0.02 Mask loss: 0.19225 RPN box loss: 0.01748 RPN score loss: 0.0084 RPN total loss: 0.02588 Total loss: 1.87927 timestamp: 1655017253.4363885 iteration: 11020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26119 FastRCNN class loss: 0.11644 FastRCNN total loss: 0.37763 L1 loss: 0.0000e+00 L2 loss: 1.50836 Learning rate: 0.02 Mask loss: 0.28897 RPN box loss: 0.04868 RPN score loss: 0.03037 RPN total loss: 0.07905 Total loss: 2.25401 timestamp: 1655017256.7796917 iteration: 11025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1795 FastRCNN class loss: 0.11297 FastRCNN total loss: 0.29248 L1 loss: 0.0000e+00 L2 loss: 1.50808 Learning rate: 0.02 Mask loss: 0.16569 RPN box loss: 0.02927 RPN score loss: 0.00556 RPN total loss: 0.03482 Total loss: 2.00106 timestamp: 1655017260.1840174 iteration: 11030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.19048 L1 loss: 0.0000e+00 L2 loss: 1.5078 Learning rate: 0.02 Mask loss: 0.19318 RPN box loss: 0.15148 RPN score loss: 0.01468 RPN total loss: 0.16616 Total loss: 2.05761 timestamp: 1655017263.5250173 iteration: 11035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14567 FastRCNN class loss: 0.11982 FastRCNN total loss: 0.26548 L1 loss: 0.0000e+00 L2 loss: 1.5075 Learning rate: 0.02 Mask loss: 0.18392 RPN box loss: 0.04131 RPN score loss: 0.01671 RPN total loss: 0.05802 Total loss: 2.01492 timestamp: 1655017266.8431375 iteration: 11040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26825 FastRCNN class loss: 0.11264 FastRCNN total loss: 0.38089 L1 loss: 0.0000e+00 L2 loss: 1.50722 Learning rate: 0.02 Mask loss: 0.26428 RPN box loss: 0.02374 RPN score loss: 0.01214 RPN total loss: 0.03588 Total loss: 2.18827 timestamp: 1655017270.2004519 iteration: 11045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24116 FastRCNN class loss: 0.06725 FastRCNN total loss: 0.30841 L1 loss: 0.0000e+00 L2 loss: 1.50693 Learning rate: 0.02 Mask loss: 0.22213 RPN box loss: 0.05145 RPN score loss: 0.0101 RPN total loss: 0.06155 Total loss: 2.09903 timestamp: 1655017273.5211694 iteration: 11050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13986 FastRCNN class loss: 0.09981 FastRCNN total loss: 0.23967 L1 loss: 0.0000e+00 L2 loss: 1.50665 Learning rate: 0.02 Mask loss: 0.18017 RPN box loss: 0.08011 RPN score loss: 0.01095 RPN total loss: 0.09106 Total loss: 2.01756 timestamp: 1655017276.7848518 iteration: 11055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13363 FastRCNN class loss: 0.05552 FastRCNN total loss: 0.18915 L1 loss: 0.0000e+00 L2 loss: 1.50641 Learning rate: 0.02 Mask loss: 0.12627 RPN box loss: 0.02555 RPN score loss: 0.01178 RPN total loss: 0.03733 Total loss: 1.85916 timestamp: 1655017280.2230158 iteration: 11060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17783 FastRCNN class loss: 0.09299 FastRCNN total loss: 0.27082 L1 loss: 0.0000e+00 L2 loss: 1.50613 Learning rate: 0.02 Mask loss: 0.13804 RPN box loss: 0.03074 RPN score loss: 0.00618 RPN total loss: 0.03692 Total loss: 1.95191 timestamp: 1655017283.5815034 iteration: 11065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1828 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.27389 L1 loss: 0.0000e+00 L2 loss: 1.50585 Learning rate: 0.02 Mask loss: 0.20993 RPN box loss: 0.07255 RPN score loss: 0.00701 RPN total loss: 0.07956 Total loss: 2.06923 timestamp: 1655017286.9581144 iteration: 11070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16883 FastRCNN class loss: 0.12587 FastRCNN total loss: 0.2947 L1 loss: 0.0000e+00 L2 loss: 1.50557 Learning rate: 0.02 Mask loss: 0.18919 RPN box loss: 0.06211 RPN score loss: 0.00952 RPN total loss: 0.07162 Total loss: 2.06108 timestamp: 1655017290.3921096 iteration: 11075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19459 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.26802 L1 loss: 0.0000e+00 L2 loss: 1.5053 Learning rate: 0.02 Mask loss: 0.19643 RPN box loss: 0.04369 RPN score loss: 0.00577 RPN total loss: 0.04947 Total loss: 2.01922 timestamp: 1655017293.6831782 iteration: 11080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16459 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.23353 L1 loss: 0.0000e+00 L2 loss: 1.50505 Learning rate: 0.02 Mask loss: 0.16295 RPN box loss: 0.01449 RPN score loss: 0.01079 RPN total loss: 0.02527 Total loss: 1.92679 timestamp: 1655017297.0271206 iteration: 11085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20761 FastRCNN class loss: 0.11109 FastRCNN total loss: 0.3187 L1 loss: 0.0000e+00 L2 loss: 1.50477 Learning rate: 0.02 Mask loss: 0.22057 RPN box loss: 0.04806 RPN score loss: 0.00787 RPN total loss: 0.05593 Total loss: 2.09998 timestamp: 1655017300.367295 iteration: 11090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20659 FastRCNN class loss: 0.09888 FastRCNN total loss: 0.30547 L1 loss: 0.0000e+00 L2 loss: 1.50449 Learning rate: 0.02 Mask loss: 0.16973 RPN box loss: 0.01471 RPN score loss: 0.00441 RPN total loss: 0.01912 Total loss: 1.99881 timestamp: 1655017303.7937787 iteration: 11095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16376 FastRCNN class loss: 0.09326 FastRCNN total loss: 0.25702 L1 loss: 0.0000e+00 L2 loss: 1.50422 Learning rate: 0.02 Mask loss: 0.2025 RPN box loss: 0.08127 RPN score loss: 0.00892 RPN total loss: 0.09019 Total loss: 2.05393 timestamp: 1655017307.1189957 iteration: 11100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18442 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.25202 L1 loss: 0.0000e+00 L2 loss: 1.50394 Learning rate: 0.02 Mask loss: 0.22496 RPN box loss: 0.21674 RPN score loss: 0.00934 RPN total loss: 0.22608 Total loss: 2.20699 timestamp: 1655017310.5002224 iteration: 11105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14248 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.20757 L1 loss: 0.0000e+00 L2 loss: 1.50367 Learning rate: 0.02 Mask loss: 0.2054 RPN box loss: 0.04962 RPN score loss: 0.00769 RPN total loss: 0.05731 Total loss: 1.97395 timestamp: 1655017313.9652526 iteration: 11110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20134 FastRCNN class loss: 0.11989 FastRCNN total loss: 0.32123 L1 loss: 0.0000e+00 L2 loss: 1.50339 Learning rate: 0.02 Mask loss: 0.19591 RPN box loss: 0.0249 RPN score loss: 0.0181 RPN total loss: 0.04299 Total loss: 2.06352 timestamp: 1655017317.1935928 iteration: 11115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22472 FastRCNN class loss: 0.11762 FastRCNN total loss: 0.34233 L1 loss: 0.0000e+00 L2 loss: 1.5031 Learning rate: 0.02 Mask loss: 0.23434 RPN box loss: 0.1031 RPN score loss: 0.0098 RPN total loss: 0.1129 Total loss: 2.19267 timestamp: 1655017320.812842 iteration: 11120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12129 FastRCNN class loss: 0.09045 FastRCNN total loss: 0.21174 L1 loss: 0.0000e+00 L2 loss: 1.50284 Learning rate: 0.02 Mask loss: 0.15976 RPN box loss: 0.0525 RPN score loss: 0.00652 RPN total loss: 0.05902 Total loss: 1.93336 timestamp: 1655017324.194621 iteration: 11125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15109 FastRCNN class loss: 0.06832 FastRCNN total loss: 0.21941 L1 loss: 0.0000e+00 L2 loss: 1.50257 Learning rate: 0.02 Mask loss: 0.19376 RPN box loss: 0.10584 RPN score loss: 0.01297 RPN total loss: 0.1188 Total loss: 2.03455 timestamp: 1655017327.6794167 iteration: 11130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20574 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.2617 L1 loss: 0.0000e+00 L2 loss: 1.50229 Learning rate: 0.02 Mask loss: 0.17807 RPN box loss: 0.00894 RPN score loss: 0.00613 RPN total loss: 0.01507 Total loss: 1.95713 timestamp: 1655017330.9910314 iteration: 11135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20002 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.27063 L1 loss: 0.0000e+00 L2 loss: 1.50202 Learning rate: 0.02 Mask loss: 0.21472 RPN box loss: 0.02297 RPN score loss: 0.00653 RPN total loss: 0.02951 Total loss: 2.01688 timestamp: 1655017334.4319124 iteration: 11140 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09885 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.15714 L1 loss: 0.0000e+00 L2 loss: 1.50175 Learning rate: 0.02 Mask loss: 0.11584 RPN box loss: 0.00631 RPN score loss: 0.00326 RPN total loss: 0.00957 Total loss: 1.78429 timestamp: 1655017338.041013 iteration: 11145 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18604 FastRCNN class loss: 0.11219 FastRCNN total loss: 0.29823 L1 loss: 0.0000e+00 L2 loss: 1.50149 Learning rate: 0.02 Mask loss: 0.12915 RPN box loss: 0.03302 RPN score loss: 0.00475 RPN total loss: 0.03778 Total loss: 1.96664 timestamp: 1655017341.3419504 iteration: 11150 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19416 FastRCNN class loss: 0.11745 FastRCNN total loss: 0.31161 L1 loss: 0.0000e+00 L2 loss: 1.50121 Learning rate: 0.02 Mask loss: 0.23747 RPN box loss: 0.04787 RPN score loss: 0.01113 RPN total loss: 0.059 Total loss: 2.10929 timestamp: 1655017344.71942 iteration: 11155 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21179 FastRCNN class loss: 0.063 FastRCNN total loss: 0.27478 L1 loss: 0.0000e+00 L2 loss: 1.50093 Learning rate: 0.02 Mask loss: 0.16392 RPN box loss: 0.02819 RPN score loss: 0.00827 RPN total loss: 0.03646 Total loss: 1.9761 timestamp: 1655017348.0358872 iteration: 11160 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18354 FastRCNN class loss: 0.06344 FastRCNN total loss: 0.24698 L1 loss: 0.0000e+00 L2 loss: 1.50067 Learning rate: 0.02 Mask loss: 0.12934 RPN box loss: 0.01529 RPN score loss: 0.00486 RPN total loss: 0.02015 Total loss: 1.89715 timestamp: 1655017351.4191494 iteration: 11165 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19406 FastRCNN class loss: 0.09406 FastRCNN total loss: 0.28812 L1 loss: 0.0000e+00 L2 loss: 1.50039 Learning rate: 0.02 Mask loss: 0.22631 RPN box loss: 0.02297 RPN score loss: 0.00755 RPN total loss: 0.03052 Total loss: 2.04534 timestamp: 1655017354.899439 iteration: 11170 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14809 FastRCNN class loss: 0.0926 FastRCNN total loss: 0.24069 L1 loss: 0.0000e+00 L2 loss: 1.50013 Learning rate: 0.02 Mask loss: 0.19041 RPN box loss: 0.04569 RPN score loss: 0.00887 RPN total loss: 0.05456 Total loss: 1.98579 timestamp: 1655017358.282922 iteration: 11175 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19064 FastRCNN class loss: 0.11583 FastRCNN total loss: 0.30647 L1 loss: 0.0000e+00 L2 loss: 1.49985 Learning rate: 0.02 Mask loss: 0.18065 RPN box loss: 0.02715 RPN score loss: 0.01737 RPN total loss: 0.04452 Total loss: 2.03149 timestamp: 1655017361.6430428 iteration: 11180 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2386 FastRCNN class loss: 0.11641 FastRCNN total loss: 0.35501 L1 loss: 0.0000e+00 L2 loss: 1.49956 Learning rate: 0.02 Mask loss: 0.23627 RPN box loss: 0.09404 RPN score loss: 0.01343 RPN total loss: 0.10747 Total loss: 2.19832 timestamp: 1655017364.9627492 iteration: 11185 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17137 FastRCNN class loss: 0.11899 FastRCNN total loss: 0.29036 L1 loss: 0.0000e+00 L2 loss: 1.49929 Learning rate: 0.02 Mask loss: 0.22314 RPN box loss: 0.03449 RPN score loss: 0.00647 RPN total loss: 0.04096 Total loss: 2.05376 timestamp: 1655017368.3451574 iteration: 11190 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22598 FastRCNN class loss: 0.12135 FastRCNN total loss: 0.34733 L1 loss: 0.0000e+00 L2 loss: 1.49902 Learning rate: 0.02 Mask loss: 0.16172 RPN box loss: 0.02778 RPN score loss: 0.01387 RPN total loss: 0.04164 Total loss: 2.04972 timestamp: 1655017371.6691418 iteration: 11195 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12347 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.19074 L1 loss: 0.0000e+00 L2 loss: 1.49876 Learning rate: 0.02 Mask loss: 0.16241 RPN box loss: 0.09115 RPN score loss: 0.00949 RPN total loss: 0.10065 Total loss: 1.95257 timestamp: 1655017375.0898137 iteration: 11200 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14769 FastRCNN class loss: 0.08897 FastRCNN total loss: 0.23666 L1 loss: 0.0000e+00 L2 loss: 1.4985 Learning rate: 0.02 Mask loss: 0.18589 RPN box loss: 0.01385 RPN score loss: 0.00315 RPN total loss: 0.017 Total loss: 1.93805 timestamp: 1655017378.3761935 iteration: 11205 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15909 FastRCNN class loss: 0.17994 FastRCNN total loss: 0.33903 L1 loss: 0.0000e+00 L2 loss: 1.49823 Learning rate: 0.02 Mask loss: 0.23349 RPN box loss: 0.11907 RPN score loss: 0.01405 RPN total loss: 0.13312 Total loss: 2.20387 timestamp: 1655017381.6790001 iteration: 11210 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.14439 L1 loss: 0.0000e+00 L2 loss: 1.49795 Learning rate: 0.02 Mask loss: 0.17222 RPN box loss: 0.03738 RPN score loss: 0.0108 RPN total loss: 0.04818 Total loss: 1.86275 timestamp: 1655017384.9753056 iteration: 11215 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13243 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.23458 L1 loss: 0.0000e+00 L2 loss: 1.49766 Learning rate: 0.02 Mask loss: 0.20149 RPN box loss: 0.05768 RPN score loss: 0.00659 RPN total loss: 0.06427 Total loss: 1.998 timestamp: 1655017388.1644552 iteration: 11220 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1619 FastRCNN class loss: 0.09471 FastRCNN total loss: 0.25661 L1 loss: 0.0000e+00 L2 loss: 1.49739 Learning rate: 0.02 Mask loss: 0.19689 RPN box loss: 0.05199 RPN score loss: 0.01123 RPN total loss: 0.06323 Total loss: 2.01412 timestamp: 1655017391.5334427 iteration: 11225 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17207 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.2424 L1 loss: 0.0000e+00 L2 loss: 1.4971 Learning rate: 0.02 Mask loss: 0.15082 RPN box loss: 0.01692 RPN score loss: 0.0054 RPN total loss: 0.02233 Total loss: 1.91266 timestamp: 1655017394.8237936 iteration: 11230 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1592 FastRCNN class loss: 0.10119 FastRCNN total loss: 0.26039 L1 loss: 0.0000e+00 L2 loss: 1.49686 Learning rate: 0.02 Mask loss: 0.1689 RPN box loss: 0.03686 RPN score loss: 0.01046 RPN total loss: 0.04733 Total loss: 1.97347 timestamp: 1655017398.2238028 iteration: 11235 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19611 FastRCNN class loss: 0.11088 FastRCNN total loss: 0.30698 L1 loss: 0.0000e+00 L2 loss: 1.49659 Learning rate: 0.02 Mask loss: 0.23171 RPN box loss: 0.03082 RPN score loss: 0.01326 RPN total loss: 0.04409 Total loss: 2.07938 timestamp: 1655017401.5027125 iteration: 11240 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25324 FastRCNN class loss: 0.16388 FastRCNN total loss: 0.41712 L1 loss: 0.0000e+00 L2 loss: 1.49632 Learning rate: 0.02 Mask loss: 0.29972 RPN box loss: 0.02734 RPN score loss: 0.01798 RPN total loss: 0.04532 Total loss: 2.25848 timestamp: 1655017404.9453719 iteration: 11245 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1624 FastRCNN class loss: 0.07968 FastRCNN total loss: 0.24207 L1 loss: 0.0000e+00 L2 loss: 1.49604 Learning rate: 0.02 Mask loss: 0.1607 RPN box loss: 0.06089 RPN score loss: 0.01558 RPN total loss: 0.07646 Total loss: 1.97527 timestamp: 1655017408.2124782 iteration: 11250 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1425 FastRCNN class loss: 0.07025 FastRCNN total loss: 0.21275 L1 loss: 0.0000e+00 L2 loss: 1.49575 Learning rate: 0.02 Mask loss: 0.18194 RPN box loss: 0.04626 RPN score loss: 0.00408 RPN total loss: 0.05034 Total loss: 1.94077 timestamp: 1655017411.6793087 iteration: 11255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19736 FastRCNN class loss: 0.08056 FastRCNN total loss: 0.27793 L1 loss: 0.0000e+00 L2 loss: 1.49547 Learning rate: 0.02 Mask loss: 0.16552 RPN box loss: 0.06299 RPN score loss: 0.00824 RPN total loss: 0.07122 Total loss: 2.01014 timestamp: 1655017415.00218 iteration: 11260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18001 FastRCNN class loss: 0.1016 FastRCNN total loss: 0.28161 L1 loss: 0.0000e+00 L2 loss: 1.49521 Learning rate: 0.02 Mask loss: 0.20123 RPN box loss: 0.01293 RPN score loss: 0.00879 RPN total loss: 0.02172 Total loss: 1.99977 timestamp: 1655017418.250868 iteration: 11265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20817 FastRCNN class loss: 0.15121 FastRCNN total loss: 0.35938 L1 loss: 0.0000e+00 L2 loss: 1.49495 Learning rate: 0.02 Mask loss: 0.20488 RPN box loss: 0.04433 RPN score loss: 0.00814 RPN total loss: 0.05247 Total loss: 2.11167 timestamp: 1655017421.6275752 iteration: 11270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14059 FastRCNN class loss: 0.07177 FastRCNN total loss: 0.21236 L1 loss: 0.0000e+00 L2 loss: 1.4947 Learning rate: 0.02 Mask loss: 0.12012 RPN box loss: 0.00584 RPN score loss: 0.00718 RPN total loss: 0.01302 Total loss: 1.84019 timestamp: 1655017424.9926963 iteration: 11275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19864 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.29188 L1 loss: 0.0000e+00 L2 loss: 1.49441 Learning rate: 0.02 Mask loss: 0.1402 RPN box loss: 0.04236 RPN score loss: 0.0129 RPN total loss: 0.05526 Total loss: 1.98176 timestamp: 1655017428.4675596 iteration: 11280 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20243 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.2898 L1 loss: 0.0000e+00 L2 loss: 1.49415 Learning rate: 0.02 Mask loss: 0.22363 RPN box loss: 0.05224 RPN score loss: 0.00946 RPN total loss: 0.06169 Total loss: 2.06927 timestamp: 1655017431.8096342 iteration: 11285 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23275 FastRCNN class loss: 0.09731 FastRCNN total loss: 0.33006 L1 loss: 0.0000e+00 L2 loss: 1.49389 Learning rate: 0.02 Mask loss: 0.29438 RPN box loss: 0.01096 RPN score loss: 0.00568 RPN total loss: 0.01664 Total loss: 2.13497 timestamp: 1655017435.240039 iteration: 11290 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15983 FastRCNN class loss: 0.07511 FastRCNN total loss: 0.23494 L1 loss: 0.0000e+00 L2 loss: 1.4936 Learning rate: 0.02 Mask loss: 0.17288 RPN box loss: 0.02056 RPN score loss: 0.00553 RPN total loss: 0.02609 Total loss: 1.92751 timestamp: 1655017438.5012574 iteration: 11295 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19421 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.29037 L1 loss: 0.0000e+00 L2 loss: 1.49331 Learning rate: 0.02 Mask loss: 0.15981 RPN box loss: 0.03147 RPN score loss: 0.01003 RPN total loss: 0.0415 Total loss: 1.98499 timestamp: 1655017441.9180236 iteration: 11300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22957 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.31912 L1 loss: 0.0000e+00 L2 loss: 1.49304 Learning rate: 0.02 Mask loss: 0.14216 RPN box loss: 0.04044 RPN score loss: 0.01249 RPN total loss: 0.05293 Total loss: 2.00725 timestamp: 1655017445.3050628 iteration: 11305 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11642 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.1768 L1 loss: 0.0000e+00 L2 loss: 1.49276 Learning rate: 0.02 Mask loss: 0.13258 RPN box loss: 0.03422 RPN score loss: 0.00787 RPN total loss: 0.04208 Total loss: 1.84422 timestamp: 1655017448.5757835 iteration: 11310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15815 FastRCNN class loss: 0.09337 FastRCNN total loss: 0.25152 L1 loss: 0.0000e+00 L2 loss: 1.4925 Learning rate: 0.02 Mask loss: 0.17467 RPN box loss: 0.02877 RPN score loss: 0.00937 RPN total loss: 0.03814 Total loss: 1.95683 timestamp: 1655017451.9932923 iteration: 11315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21607 FastRCNN class loss: 0.09256 FastRCNN total loss: 0.30863 L1 loss: 0.0000e+00 L2 loss: 1.49223 Learning rate: 0.02 Mask loss: 0.19677 RPN box loss: 0.09019 RPN score loss: 0.01552 RPN total loss: 0.10572 Total loss: 2.10335 timestamp: 1655017455.272929 iteration: 11320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10849 FastRCNN class loss: 0.0672 FastRCNN total loss: 0.17569 L1 loss: 0.0000e+00 L2 loss: 1.49196 Learning rate: 0.02 Mask loss: 0.10562 RPN box loss: 0.01901 RPN score loss: 0.00546 RPN total loss: 0.02447 Total loss: 1.79773 timestamp: 1655017458.7487683 iteration: 11325 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2211 FastRCNN class loss: 0.09727 FastRCNN total loss: 0.31837 L1 loss: 0.0000e+00 L2 loss: 1.49169 Learning rate: 0.02 Mask loss: 0.25931 RPN box loss: 0.08953 RPN score loss: 0.01033 RPN total loss: 0.09986 Total loss: 2.16923 timestamp: 1655017462.028459 iteration: 11330 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20655 FastRCNN class loss: 0.21474 FastRCNN total loss: 0.4213 L1 loss: 0.0000e+00 L2 loss: 1.4914 Learning rate: 0.02 Mask loss: 0.23534 RPN box loss: 0.01832 RPN score loss: 0.00797 RPN total loss: 0.02629 Total loss: 2.17433 timestamp: 1655017465.346158 iteration: 11335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16006 FastRCNN class loss: 0.06114 FastRCNN total loss: 0.2212 L1 loss: 0.0000e+00 L2 loss: 1.49113 Learning rate: 0.02 Mask loss: 0.15491 RPN box loss: 0.01038 RPN score loss: 0.00385 RPN total loss: 0.01424 Total loss: 1.88148 timestamp: 1655017468.7377353 iteration: 11340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16217 FastRCNN class loss: 0.09521 FastRCNN total loss: 0.25738 L1 loss: 0.0000e+00 L2 loss: 1.49087 Learning rate: 0.02 Mask loss: 0.1415 RPN box loss: 0.03609 RPN score loss: 0.00449 RPN total loss: 0.04058 Total loss: 1.93032 timestamp: 1655017472.0438204 iteration: 11345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18877 FastRCNN class loss: 0.13173 FastRCNN total loss: 0.3205 L1 loss: 0.0000e+00 L2 loss: 1.49061 Learning rate: 0.02 Mask loss: 0.28205 RPN box loss: 0.02917 RPN score loss: 0.01194 RPN total loss: 0.04111 Total loss: 2.13427 timestamp: 1655017475.4986987 iteration: 11350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11001 FastRCNN class loss: 0.06468 FastRCNN total loss: 0.17469 L1 loss: 0.0000e+00 L2 loss: 1.49033 Learning rate: 0.02 Mask loss: 0.14561 RPN box loss: 0.05179 RPN score loss: 0.00797 RPN total loss: 0.05975 Total loss: 1.87038 timestamp: 1655017478.7668438 iteration: 11355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20681 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.28755 L1 loss: 0.0000e+00 L2 loss: 1.49006 Learning rate: 0.02 Mask loss: 0.14825 RPN box loss: 0.05304 RPN score loss: 0.00608 RPN total loss: 0.05913 Total loss: 1.98499 timestamp: 1655017482.1393113 iteration: 11360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19516 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.29265 L1 loss: 0.0000e+00 L2 loss: 1.48981 Learning rate: 0.02 Mask loss: 0.16887 RPN box loss: 0.02282 RPN score loss: 0.00264 RPN total loss: 0.02546 Total loss: 1.97678 timestamp: 1655017485.4291036 iteration: 11365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11113 FastRCNN class loss: 0.03331 FastRCNN total loss: 0.14444 L1 loss: 0.0000e+00 L2 loss: 1.48953 Learning rate: 0.02 Mask loss: 0.10348 RPN box loss: 0.03456 RPN score loss: 0.00324 RPN total loss: 0.0378 Total loss: 1.77526 timestamp: 1655017488.8286197 iteration: 11370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16685 FastRCNN class loss: 0.09509 FastRCNN total loss: 0.26194 L1 loss: 0.0000e+00 L2 loss: 1.48927 Learning rate: 0.02 Mask loss: 0.16991 RPN box loss: 0.01255 RPN score loss: 0.0065 RPN total loss: 0.01905 Total loss: 1.94017 timestamp: 1655017492.07385 iteration: 11375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17733 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.26043 L1 loss: 0.0000e+00 L2 loss: 1.48901 Learning rate: 0.02 Mask loss: 0.23979 RPN box loss: 0.04294 RPN score loss: 0.01092 RPN total loss: 0.05386 Total loss: 2.04308 timestamp: 1655017495.3917708 iteration: 11380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21254 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.29534 L1 loss: 0.0000e+00 L2 loss: 1.48871 Learning rate: 0.02 Mask loss: 0.16988 RPN box loss: 0.02603 RPN score loss: 0.0133 RPN total loss: 0.03933 Total loss: 1.99326 timestamp: 1655017498.8178625 iteration: 11385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16047 FastRCNN class loss: 0.06924 FastRCNN total loss: 0.22971 L1 loss: 0.0000e+00 L2 loss: 1.48842 Learning rate: 0.02 Mask loss: 0.13292 RPN box loss: 0.01006 RPN score loss: 0.00309 RPN total loss: 0.01314 Total loss: 1.86419 timestamp: 1655017502.1258836 iteration: 11390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15048 FastRCNN class loss: 0.07723 FastRCNN total loss: 0.22771 L1 loss: 0.0000e+00 L2 loss: 1.48815 Learning rate: 0.02 Mask loss: 0.16615 RPN box loss: 0.03794 RPN score loss: 0.00321 RPN total loss: 0.04115 Total loss: 1.92316 timestamp: 1655017505.498948 iteration: 11395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11511 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.20501 L1 loss: 0.0000e+00 L2 loss: 1.48789 Learning rate: 0.02 Mask loss: 0.18653 RPN box loss: 0.01471 RPN score loss: 0.00278 RPN total loss: 0.01749 Total loss: 1.89692 timestamp: 1655017508.7180817 iteration: 11400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15545 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.22616 L1 loss: 0.0000e+00 L2 loss: 1.48763 Learning rate: 0.02 Mask loss: 0.15959 RPN box loss: 0.11804 RPN score loss: 0.00849 RPN total loss: 0.12653 Total loss: 1.99992 timestamp: 1655017512.2254348 iteration: 11405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16915 FastRCNN class loss: 0.12014 FastRCNN total loss: 0.28929 L1 loss: 0.0000e+00 L2 loss: 1.48735 Learning rate: 0.02 Mask loss: 0.21991 RPN box loss: 0.07993 RPN score loss: 0.01997 RPN total loss: 0.0999 Total loss: 2.09645 timestamp: 1655017515.5657253 iteration: 11410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20135 FastRCNN class loss: 0.11014 FastRCNN total loss: 0.31149 L1 loss: 0.0000e+00 L2 loss: 1.48709 Learning rate: 0.02 Mask loss: 0.18523 RPN box loss: 0.01221 RPN score loss: 0.0059 RPN total loss: 0.0181 Total loss: 2.00191 timestamp: 1655017519.0372539 iteration: 11415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22522 FastRCNN class loss: 0.15734 FastRCNN total loss: 0.38256 L1 loss: 0.0000e+00 L2 loss: 1.48681 Learning rate: 0.02 Mask loss: 0.21664 RPN box loss: 0.09234 RPN score loss: 0.00988 RPN total loss: 0.10222 Total loss: 2.18824 timestamp: 1655017522.3132756 iteration: 11420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11122 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.18078 L1 loss: 0.0000e+00 L2 loss: 1.48657 Learning rate: 0.02 Mask loss: 0.17271 RPN box loss: 0.03937 RPN score loss: 0.00252 RPN total loss: 0.04189 Total loss: 1.88195 timestamp: 1655017525.7015965 iteration: 11425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20302 FastRCNN class loss: 0.10239 FastRCNN total loss: 0.30541 L1 loss: 0.0000e+00 L2 loss: 1.48631 Learning rate: 0.02 Mask loss: 0.18986 RPN box loss: 0.07322 RPN score loss: 0.02451 RPN total loss: 0.09773 Total loss: 2.0793 timestamp: 1655017529.0515597 iteration: 11430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22012 FastRCNN class loss: 0.1217 FastRCNN total loss: 0.34183 L1 loss: 0.0000e+00 L2 loss: 1.48602 Learning rate: 0.02 Mask loss: 0.2553 RPN box loss: 0.02373 RPN score loss: 0.00859 RPN total loss: 0.03232 Total loss: 2.11547 timestamp: 1655017532.3663132 iteration: 11435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14394 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 1.48575 Learning rate: 0.02 Mask loss: 0.21925 RPN box loss: 0.06359 RPN score loss: 0.00661 RPN total loss: 0.0702 Total loss: 1.98812 timestamp: 1655017535.7544136 iteration: 11440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17092 FastRCNN class loss: 0.09452 FastRCNN total loss: 0.26544 L1 loss: 0.0000e+00 L2 loss: 1.48547 Learning rate: 0.02 Mask loss: 0.17583 RPN box loss: 0.01935 RPN score loss: 0.00708 RPN total loss: 0.02643 Total loss: 1.95317 timestamp: 1655017539.131259 iteration: 11445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16509 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.2565 L1 loss: 0.0000e+00 L2 loss: 1.48522 Learning rate: 0.02 Mask loss: 0.18882 RPN box loss: 0.06183 RPN score loss: 0.00874 RPN total loss: 0.07057 Total loss: 2.00111 timestamp: 1655017542.4105623 iteration: 11450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14976 FastRCNN class loss: 0.10284 FastRCNN total loss: 0.2526 L1 loss: 0.0000e+00 L2 loss: 1.48497 Learning rate: 0.02 Mask loss: 0.21572 RPN box loss: 0.01735 RPN score loss: 0.00981 RPN total loss: 0.02717 Total loss: 1.98046 timestamp: 1655017545.7233505 iteration: 11455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20092 FastRCNN class loss: 0.12434 FastRCNN total loss: 0.32526 L1 loss: 0.0000e+00 L2 loss: 1.48469 Learning rate: 0.02 Mask loss: 0.23613 RPN box loss: 0.03443 RPN score loss: 0.01423 RPN total loss: 0.04866 Total loss: 2.09474 timestamp: 1655017549.0527594 iteration: 11460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18145 FastRCNN class loss: 0.10202 FastRCNN total loss: 0.28347 L1 loss: 0.0000e+00 L2 loss: 1.48442 Learning rate: 0.02 Mask loss: 0.17561 RPN box loss: 0.06459 RPN score loss: 0.01024 RPN total loss: 0.07482 Total loss: 2.01832 timestamp: 1655017552.317353 iteration: 11465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18718 FastRCNN class loss: 0.12308 FastRCNN total loss: 0.31025 L1 loss: 0.0000e+00 L2 loss: 1.48415 Learning rate: 0.02 Mask loss: 0.20095 RPN box loss: 0.06083 RPN score loss: 0.01067 RPN total loss: 0.0715 Total loss: 2.06685 timestamp: 1655017555.685986 iteration: 11470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16084 FastRCNN class loss: 0.14102 FastRCNN total loss: 0.30186 L1 loss: 0.0000e+00 L2 loss: 1.48389 Learning rate: 0.02 Mask loss: 0.24719 RPN box loss: 0.04273 RPN score loss: 0.01803 RPN total loss: 0.06076 Total loss: 2.0937 timestamp: 1655017559.069079 iteration: 11475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24177 FastRCNN class loss: 0.1089 FastRCNN total loss: 0.35067 L1 loss: 0.0000e+00 L2 loss: 1.48363 Learning rate: 0.02 Mask loss: 0.22159 RPN box loss: 0.03747 RPN score loss: 0.00422 RPN total loss: 0.04169 Total loss: 2.09759 timestamp: 1655017562.3059425 iteration: 11480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16807 FastRCNN class loss: 0.10579 FastRCNN total loss: 0.27385 L1 loss: 0.0000e+00 L2 loss: 1.48336 Learning rate: 0.02 Mask loss: 0.13884 RPN box loss: 0.06125 RPN score loss: 0.00952 RPN total loss: 0.07077 Total loss: 1.96682 timestamp: 1655017565.6464663 iteration: 11485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1536 FastRCNN class loss: 0.09152 FastRCNN total loss: 0.24512 L1 loss: 0.0000e+00 L2 loss: 1.4831 Learning rate: 0.02 Mask loss: 0.18818 RPN box loss: 0.06079 RPN score loss: 0.01675 RPN total loss: 0.07754 Total loss: 1.99394 timestamp: 1655017568.966068 iteration: 11490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11401 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.18913 L1 loss: 0.0000e+00 L2 loss: 1.48285 Learning rate: 0.02 Mask loss: 0.11755 RPN box loss: 0.03924 RPN score loss: 0.00271 RPN total loss: 0.04195 Total loss: 1.83147 timestamp: 1655017572.3844216 iteration: 11495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20035 FastRCNN class loss: 0.11839 FastRCNN total loss: 0.31874 L1 loss: 0.0000e+00 L2 loss: 1.48256 Learning rate: 0.02 Mask loss: 0.20826 RPN box loss: 0.04717 RPN score loss: 0.01175 RPN total loss: 0.05892 Total loss: 2.06849 timestamp: 1655017575.6556811 iteration: 11500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23215 FastRCNN class loss: 0.15133 FastRCNN total loss: 0.38348 L1 loss: 0.0000e+00 L2 loss: 1.4823 Learning rate: 0.02 Mask loss: 0.26213 RPN box loss: 0.0356 RPN score loss: 0.0159 RPN total loss: 0.0515 Total loss: 2.17941 timestamp: 1655017579.1078792 iteration: 11505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.05102 FastRCNN total loss: 0.15726 L1 loss: 0.0000e+00 L2 loss: 1.48204 Learning rate: 0.02 Mask loss: 0.15322 RPN box loss: 0.02648 RPN score loss: 0.00554 RPN total loss: 0.03201 Total loss: 1.82453 timestamp: 1655017582.4783792 iteration: 11510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14472 FastRCNN class loss: 0.08581 FastRCNN total loss: 0.23054 L1 loss: 0.0000e+00 L2 loss: 1.48177 Learning rate: 0.02 Mask loss: 0.22448 RPN box loss: 0.08219 RPN score loss: 0.01764 RPN total loss: 0.09983 Total loss: 2.03662 timestamp: 1655017585.9014416 iteration: 11515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20182 FastRCNN class loss: 0.1048 FastRCNN total loss: 0.30662 L1 loss: 0.0000e+00 L2 loss: 1.48149 Learning rate: 0.02 Mask loss: 0.15147 RPN box loss: 0.01365 RPN score loss: 0.00559 RPN total loss: 0.01924 Total loss: 1.95882 timestamp: 1655017589.3164833 iteration: 11520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17047 FastRCNN class loss: 0.10933 FastRCNN total loss: 0.2798 L1 loss: 0.0000e+00 L2 loss: 1.48122 Learning rate: 0.02 Mask loss: 0.18517 RPN box loss: 0.08684 RPN score loss: 0.01274 RPN total loss: 0.09958 Total loss: 2.04577 timestamp: 1655017592.5578604 iteration: 11525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10719 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.15777 L1 loss: 0.0000e+00 L2 loss: 1.48097 Learning rate: 0.02 Mask loss: 0.1731 RPN box loss: 0.02995 RPN score loss: 0.00566 RPN total loss: 0.03561 Total loss: 1.84744 timestamp: 1655017595.973186 iteration: 11530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14989 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.22583 L1 loss: 0.0000e+00 L2 loss: 1.48069 Learning rate: 0.02 Mask loss: 0.16588 RPN box loss: 0.12392 RPN score loss: 0.01664 RPN total loss: 0.14056 Total loss: 2.01296 timestamp: 1655017599.1931658 iteration: 11535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16911 FastRCNN class loss: 0.12086 FastRCNN total loss: 0.28997 L1 loss: 0.0000e+00 L2 loss: 1.4804 Learning rate: 0.02 Mask loss: 0.25872 RPN box loss: 0.03979 RPN score loss: 0.0082 RPN total loss: 0.04799 Total loss: 2.07709 timestamp: 1655017602.6053102 iteration: 11540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14126 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.19964 L1 loss: 0.0000e+00 L2 loss: 1.4801 Learning rate: 0.02 Mask loss: 0.24699 RPN box loss: 0.03238 RPN score loss: 0.00645 RPN total loss: 0.03883 Total loss: 1.96557 timestamp: 1655017605.8427546 iteration: 11545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19935 FastRCNN class loss: 0.06663 FastRCNN total loss: 0.26599 L1 loss: 0.0000e+00 L2 loss: 1.47984 Learning rate: 0.02 Mask loss: 0.20618 RPN box loss: 0.0106 RPN score loss: 0.0066 RPN total loss: 0.0172 Total loss: 1.96921 timestamp: 1655017609.2744446 iteration: 11550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06958 FastRCNN class loss: 0.03744 FastRCNN total loss: 0.10702 L1 loss: 0.0000e+00 L2 loss: 1.47959 Learning rate: 0.02 Mask loss: 0.13028 RPN box loss: 0.09311 RPN score loss: 0.00407 RPN total loss: 0.09718 Total loss: 1.81407 timestamp: 1655017612.6102536 iteration: 11555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23888 FastRCNN class loss: 0.09591 FastRCNN total loss: 0.33479 L1 loss: 0.0000e+00 L2 loss: 1.47934 Learning rate: 0.02 Mask loss: 0.16775 RPN box loss: 0.00869 RPN score loss: 0.00459 RPN total loss: 0.01328 Total loss: 1.99517 timestamp: 1655017615.8636055 iteration: 11560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13107 FastRCNN class loss: 0.06007 FastRCNN total loss: 0.19113 L1 loss: 0.0000e+00 L2 loss: 1.47907 Learning rate: 0.02 Mask loss: 0.14374 RPN box loss: 0.03575 RPN score loss: 0.00769 RPN total loss: 0.04344 Total loss: 1.85738 timestamp: 1655017619.2127662 iteration: 11565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1267 FastRCNN class loss: 0.0916 FastRCNN total loss: 0.2183 L1 loss: 0.0000e+00 L2 loss: 1.47878 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.04918 RPN score loss: 0.00975 RPN total loss: 0.05893 Total loss: 1.91026 timestamp: 1655017622.5320158 iteration: 11570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16126 FastRCNN class loss: 0.10265 FastRCNN total loss: 0.26391 L1 loss: 0.0000e+00 L2 loss: 1.47851 Learning rate: 0.02 Mask loss: 0.22598 RPN box loss: 0.05058 RPN score loss: 0.01119 RPN total loss: 0.06177 Total loss: 2.03016 timestamp: 1655017625.901581 iteration: 11575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21393 FastRCNN class loss: 0.14838 FastRCNN total loss: 0.36232 L1 loss: 0.0000e+00 L2 loss: 1.47823 Learning rate: 0.02 Mask loss: 0.19774 RPN box loss: 0.03274 RPN score loss: 0.01468 RPN total loss: 0.04742 Total loss: 2.08572 timestamp: 1655017629.2173078 iteration: 11580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21101 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.28999 L1 loss: 0.0000e+00 L2 loss: 1.47797 Learning rate: 0.02 Mask loss: 0.17797 RPN box loss: 0.01696 RPN score loss: 0.01164 RPN total loss: 0.0286 Total loss: 1.97453 timestamp: 1655017632.6804876 iteration: 11585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19707 FastRCNN class loss: 0.08158 FastRCNN total loss: 0.27866 L1 loss: 0.0000e+00 L2 loss: 1.47772 Learning rate: 0.02 Mask loss: 0.14533 RPN box loss: 0.08971 RPN score loss: 0.00841 RPN total loss: 0.09812 Total loss: 1.99983 timestamp: 1655017635.9386308 iteration: 11590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2216 FastRCNN class loss: 0.11873 FastRCNN total loss: 0.34033 L1 loss: 0.0000e+00 L2 loss: 1.47745 Learning rate: 0.02 Mask loss: 0.23919 RPN box loss: 0.05266 RPN score loss: 0.01449 RPN total loss: 0.06715 Total loss: 2.12413 timestamp: 1655017639.3350575 iteration: 11595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12082 FastRCNN class loss: 0.10671 FastRCNN total loss: 0.22753 L1 loss: 0.0000e+00 L2 loss: 1.47718 Learning rate: 0.02 Mask loss: 0.30195 RPN box loss: 0.02739 RPN score loss: 0.0055 RPN total loss: 0.03289 Total loss: 2.03956 timestamp: 1655017642.7488098 iteration: 11600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19004 FastRCNN class loss: 0.11472 FastRCNN total loss: 0.30477 L1 loss: 0.0000e+00 L2 loss: 1.47692 Learning rate: 0.02 Mask loss: 0.23122 RPN box loss: 0.04355 RPN score loss: 0.00474 RPN total loss: 0.04829 Total loss: 2.06119 timestamp: 1655017646.0045576 iteration: 11605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29157 FastRCNN class loss: 0.1753 FastRCNN total loss: 0.46687 L1 loss: 0.0000e+00 L2 loss: 1.47663 Learning rate: 0.02 Mask loss: 0.27279 RPN box loss: 0.06487 RPN score loss: 0.01551 RPN total loss: 0.08038 Total loss: 2.29667 timestamp: 1655017649.316842 iteration: 11610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25954 FastRCNN class loss: 0.11673 FastRCNN total loss: 0.37627 L1 loss: 0.0000e+00 L2 loss: 1.47636 Learning rate: 0.02 Mask loss: 0.20007 RPN box loss: 0.04708 RPN score loss: 0.01548 RPN total loss: 0.06257 Total loss: 2.11528 timestamp: 1655017652.551866 iteration: 11615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1722 FastRCNN class loss: 0.08929 FastRCNN total loss: 0.26149 L1 loss: 0.0000e+00 L2 loss: 1.47611 Learning rate: 0.02 Mask loss: 0.20577 RPN box loss: 0.02703 RPN score loss: 0.00756 RPN total loss: 0.03459 Total loss: 1.97796 timestamp: 1655017655.8164647 iteration: 11620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16794 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.24048 L1 loss: 0.0000e+00 L2 loss: 1.47587 Learning rate: 0.02 Mask loss: 0.15287 RPN box loss: 0.06237 RPN score loss: 0.0088 RPN total loss: 0.07117 Total loss: 1.94039 timestamp: 1655017659.141653 iteration: 11625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18969 FastRCNN class loss: 0.114 FastRCNN total loss: 0.30369 L1 loss: 0.0000e+00 L2 loss: 1.47561 Learning rate: 0.02 Mask loss: 0.19192 RPN box loss: 0.23093 RPN score loss: 0.01194 RPN total loss: 0.24287 Total loss: 2.21409 timestamp: 1655017662.5347567 iteration: 11630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1233 FastRCNN class loss: 0.06304 FastRCNN total loss: 0.18635 L1 loss: 0.0000e+00 L2 loss: 1.47535 Learning rate: 0.02 Mask loss: 0.14912 RPN box loss: 0.1132 RPN score loss: 0.01051 RPN total loss: 0.12371 Total loss: 1.93453 timestamp: 1655017665.7757318 iteration: 11635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.16837 FastRCNN total loss: 0.27202 L1 loss: 0.0000e+00 L2 loss: 1.47508 Learning rate: 0.02 Mask loss: 0.24843 RPN box loss: 0.06173 RPN score loss: 0.10684 RPN total loss: 0.16857 Total loss: 2.1641 timestamp: 1655017669.0980897 iteration: 11640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15808 FastRCNN class loss: 0.13133 FastRCNN total loss: 0.2894 L1 loss: 0.0000e+00 L2 loss: 1.47478 Learning rate: 0.02 Mask loss: 0.20346 RPN box loss: 0.04551 RPN score loss: 0.01048 RPN total loss: 0.05598 Total loss: 2.02363 timestamp: 1655017672.6075435 iteration: 11645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21616 FastRCNN class loss: 0.08223 FastRCNN total loss: 0.29839 L1 loss: 0.0000e+00 L2 loss: 1.47452 Learning rate: 0.02 Mask loss: 0.23072 RPN box loss: 0.046 RPN score loss: 0.00873 RPN total loss: 0.05473 Total loss: 2.05836 timestamp: 1655017676.0355756 iteration: 11650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16392 FastRCNN class loss: 0.09035 FastRCNN total loss: 0.25427 L1 loss: 0.0000e+00 L2 loss: 1.47426 Learning rate: 0.02 Mask loss: 0.15252 RPN box loss: 0.05218 RPN score loss: 0.01092 RPN total loss: 0.06309 Total loss: 1.94414 timestamp: 1655017679.408835 iteration: 11655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23226 FastRCNN class loss: 0.11448 FastRCNN total loss: 0.34673 L1 loss: 0.0000e+00 L2 loss: 1.47398 Learning rate: 0.02 Mask loss: 0.17225 RPN box loss: 0.02219 RPN score loss: 0.00697 RPN total loss: 0.02916 Total loss: 2.02211 timestamp: 1655017682.711313 iteration: 11660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2358 FastRCNN class loss: 0.11998 FastRCNN total loss: 0.35578 L1 loss: 0.0000e+00 L2 loss: 1.47371 Learning rate: 0.02 Mask loss: 0.22119 RPN box loss: 0.02905 RPN score loss: 0.01557 RPN total loss: 0.04462 Total loss: 2.0953 timestamp: 1655017686.0019228 iteration: 11665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1319 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.1943 L1 loss: 0.0000e+00 L2 loss: 1.47345 Learning rate: 0.02 Mask loss: 0.15824 RPN box loss: 0.03429 RPN score loss: 0.00371 RPN total loss: 0.038 Total loss: 1.864 timestamp: 1655017689.365261 iteration: 11670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.18823 L1 loss: 0.0000e+00 L2 loss: 1.47317 Learning rate: 0.02 Mask loss: 0.16131 RPN box loss: 0.02721 RPN score loss: 0.0067 RPN total loss: 0.03391 Total loss: 1.85662 timestamp: 1655017692.8268332 iteration: 11675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18942 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.26444 L1 loss: 0.0000e+00 L2 loss: 1.47291 Learning rate: 0.02 Mask loss: 0.14003 RPN box loss: 0.12033 RPN score loss: 0.00411 RPN total loss: 0.12444 Total loss: 2.00182 timestamp: 1655017696.266586 iteration: 11680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17104 FastRCNN class loss: 0.08322 FastRCNN total loss: 0.25426 L1 loss: 0.0000e+00 L2 loss: 1.47265 Learning rate: 0.02 Mask loss: 0.13151 RPN box loss: 0.02756 RPN score loss: 0.00443 RPN total loss: 0.03199 Total loss: 1.8904 timestamp: 1655017699.6200025 iteration: 11685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17612 FastRCNN class loss: 0.13337 FastRCNN total loss: 0.30949 L1 loss: 0.0000e+00 L2 loss: 1.4724 Learning rate: 0.02 Mask loss: 0.19484 RPN box loss: 0.03435 RPN score loss: 0.00517 RPN total loss: 0.03952 Total loss: 2.01625 timestamp: 1655017702.9960735 iteration: 11690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17367 FastRCNN class loss: 0.09952 FastRCNN total loss: 0.27319 L1 loss: 0.0000e+00 L2 loss: 1.47212 Learning rate: 0.02 Mask loss: 0.17813 RPN box loss: 0.05936 RPN score loss: 0.01735 RPN total loss: 0.07671 Total loss: 2.00015 timestamp: 1655017706.2749822 iteration: 11695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14303 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.2311 L1 loss: 0.0000e+00 L2 loss: 1.47184 Learning rate: 0.02 Mask loss: 0.15567 RPN box loss: 0.01067 RPN score loss: 0.00276 RPN total loss: 0.01343 Total loss: 1.87205 timestamp: 1655017709.7282972 iteration: 11700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19939 FastRCNN class loss: 0.10636 FastRCNN total loss: 0.30575 L1 loss: 0.0000e+00 L2 loss: 1.4716 Learning rate: 0.02 Mask loss: 0.20868 RPN box loss: 0.0198 RPN score loss: 0.00275 RPN total loss: 0.02255 Total loss: 2.00857 timestamp: 1655017713.0727007 iteration: 11705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21957 FastRCNN class loss: 0.15083 FastRCNN total loss: 0.3704 L1 loss: 0.0000e+00 L2 loss: 1.47135 Learning rate: 0.02 Mask loss: 0.2211 RPN box loss: 0.0829 RPN score loss: 0.01885 RPN total loss: 0.10175 Total loss: 2.1646 timestamp: 1655017716.4955745 iteration: 11710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15464 FastRCNN class loss: 0.11904 FastRCNN total loss: 0.27368 L1 loss: 0.0000e+00 L2 loss: 1.47107 Learning rate: 0.02 Mask loss: 0.16682 RPN box loss: 0.08009 RPN score loss: 0.01716 RPN total loss: 0.09725 Total loss: 2.00882 timestamp: 1655017719.8320816 iteration: 11715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19628 FastRCNN class loss: 0.09738 FastRCNN total loss: 0.29365 L1 loss: 0.0000e+00 L2 loss: 1.4708 Learning rate: 0.02 Mask loss: 0.20856 RPN box loss: 0.04777 RPN score loss: 0.0039 RPN total loss: 0.05166 Total loss: 2.02467 timestamp: 1655017723.343964 iteration: 11720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16575 FastRCNN class loss: 0.07024 FastRCNN total loss: 0.23599 L1 loss: 0.0000e+00 L2 loss: 1.47053 Learning rate: 0.02 Mask loss: 0.16096 RPN box loss: 0.08224 RPN score loss: 0.01044 RPN total loss: 0.09268 Total loss: 1.96016 timestamp: 1655017726.7331955 iteration: 11725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.32976 FastRCNN class loss: 0.1634 FastRCNN total loss: 0.49316 L1 loss: 0.0000e+00 L2 loss: 1.47026 Learning rate: 0.02 Mask loss: 0.3024 RPN box loss: 0.05636 RPN score loss: 0.02048 RPN total loss: 0.07684 Total loss: 2.34266 timestamp: 1655017730.043911 iteration: 11730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19206 FastRCNN class loss: 0.1118 FastRCNN total loss: 0.30386 L1 loss: 0.0000e+00 L2 loss: 1.47 Learning rate: 0.02 Mask loss: 0.27813 RPN box loss: 0.02046 RPN score loss: 0.00554 RPN total loss: 0.026 Total loss: 2.07799 timestamp: 1655017733.4552798 iteration: 11735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20449 FastRCNN class loss: 0.11959 FastRCNN total loss: 0.32408 L1 loss: 0.0000e+00 L2 loss: 1.46975 Learning rate: 0.02 Mask loss: 0.1725 RPN box loss: 0.0583 RPN score loss: 0.016 RPN total loss: 0.0743 Total loss: 2.04063 timestamp: 1655017736.8200288 iteration: 11740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1943 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.26004 L1 loss: 0.0000e+00 L2 loss: 1.46948 Learning rate: 0.02 Mask loss: 0.15191 RPN box loss: 0.01891 RPN score loss: 0.00473 RPN total loss: 0.02364 Total loss: 1.90506 timestamp: 1655017740.1240304 iteration: 11745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19317 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.26854 L1 loss: 0.0000e+00 L2 loss: 1.46918 Learning rate: 0.02 Mask loss: 0.13261 RPN box loss: 0.01202 RPN score loss: 0.00582 RPN total loss: 0.01783 Total loss: 1.88817 timestamp: 1655017743.3550818 iteration: 11750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13075 FastRCNN class loss: 0.06011 FastRCNN total loss: 0.19086 L1 loss: 0.0000e+00 L2 loss: 1.4689 Learning rate: 0.02 Mask loss: 0.19901 RPN box loss: 0.03452 RPN score loss: 0.00446 RPN total loss: 0.03898 Total loss: 1.89774 timestamp: 1655017746.6907663 iteration: 11755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15314 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.2129 L1 loss: 0.0000e+00 L2 loss: 1.46864 Learning rate: 0.02 Mask loss: 0.16934 RPN box loss: 0.02059 RPN score loss: 0.00463 RPN total loss: 0.02523 Total loss: 1.87611 timestamp: 1655017750.2006323 iteration: 11760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25329 FastRCNN class loss: 0.17322 FastRCNN total loss: 0.4265 L1 loss: 0.0000e+00 L2 loss: 1.4684 Learning rate: 0.02 Mask loss: 0.1542 RPN box loss: 0.03623 RPN score loss: 0.0158 RPN total loss: 0.05203 Total loss: 2.10114 timestamp: 1655017753.4949386 iteration: 11765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21633 FastRCNN class loss: 0.10997 FastRCNN total loss: 0.3263 L1 loss: 0.0000e+00 L2 loss: 1.46814 Learning rate: 0.02 Mask loss: 0.28404 RPN box loss: 0.06644 RPN score loss: 0.01224 RPN total loss: 0.07868 Total loss: 2.15717 timestamp: 1655017757.016876 iteration: 11770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18698 FastRCNN class loss: 0.09602 FastRCNN total loss: 0.28301 L1 loss: 0.0000e+00 L2 loss: 1.46788 Learning rate: 0.02 Mask loss: 0.20063 RPN box loss: 0.04046 RPN score loss: 0.01432 RPN total loss: 0.05478 Total loss: 2.00629 timestamp: 1655017760.3182137 iteration: 11775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20737 FastRCNN class loss: 0.09559 FastRCNN total loss: 0.30296 L1 loss: 0.0000e+00 L2 loss: 1.46757 Learning rate: 0.02 Mask loss: 0.17964 RPN box loss: 0.05225 RPN score loss: 0.00557 RPN total loss: 0.05782 Total loss: 2.00799 timestamp: 1655017763.8090804 iteration: 11780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22519 FastRCNN class loss: 0.09146 FastRCNN total loss: 0.31666 L1 loss: 0.0000e+00 L2 loss: 1.4673 Learning rate: 0.02 Mask loss: 0.22147 RPN box loss: 0.06521 RPN score loss: 0.00962 RPN total loss: 0.07482 Total loss: 2.08026 timestamp: 1655017767.06179 iteration: 11785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12933 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.19515 L1 loss: 0.0000e+00 L2 loss: 1.46705 Learning rate: 0.02 Mask loss: 0.14676 RPN box loss: 0.012 RPN score loss: 0.00417 RPN total loss: 0.01617 Total loss: 1.82513 timestamp: 1655017770.521724 iteration: 11790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28491 FastRCNN class loss: 0.10216 FastRCNN total loss: 0.38707 L1 loss: 0.0000e+00 L2 loss: 1.4668 Learning rate: 0.02 Mask loss: 0.1978 RPN box loss: 0.0789 RPN score loss: 0.0229 RPN total loss: 0.1018 Total loss: 2.15346 timestamp: 1655017773.951305 iteration: 11795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 1.46653 Learning rate: 0.02 Mask loss: 0.16983 RPN box loss: 0.02722 RPN score loss: 0.00546 RPN total loss: 0.03268 Total loss: 1.8162 timestamp: 1655017777.2779536 iteration: 11800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24786 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.3521 L1 loss: 0.0000e+00 L2 loss: 1.46625 Learning rate: 0.02 Mask loss: 0.31157 RPN box loss: 0.08769 RPN score loss: 0.01701 RPN total loss: 0.10471 Total loss: 2.23463 timestamp: 1655017780.6437535 iteration: 11805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1671 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.23655 L1 loss: 0.0000e+00 L2 loss: 1.46598 Learning rate: 0.02 Mask loss: 0.17094 RPN box loss: 0.014 RPN score loss: 0.00513 RPN total loss: 0.01913 Total loss: 1.8926 timestamp: 1655017783.9460788 iteration: 11810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19612 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.27569 L1 loss: 0.0000e+00 L2 loss: 1.46571 Learning rate: 0.02 Mask loss: 0.14871 RPN box loss: 0.03346 RPN score loss: 0.00433 RPN total loss: 0.03779 Total loss: 1.92791 timestamp: 1655017787.3049402 iteration: 11815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19238 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.26746 L1 loss: 0.0000e+00 L2 loss: 1.46543 Learning rate: 0.02 Mask loss: 0.19239 RPN box loss: 0.08342 RPN score loss: 0.01108 RPN total loss: 0.09451 Total loss: 2.01978 timestamp: 1655017790.4914184 iteration: 11820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14806 FastRCNN class loss: 0.093 FastRCNN total loss: 0.24106 L1 loss: 0.0000e+00 L2 loss: 1.46516 Learning rate: 0.02 Mask loss: 0.15065 RPN box loss: 0.02997 RPN score loss: 0.00531 RPN total loss: 0.03528 Total loss: 1.89215 timestamp: 1655017793.9510183 iteration: 11825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23597 FastRCNN class loss: 0.13396 FastRCNN total loss: 0.36994 L1 loss: 0.0000e+00 L2 loss: 1.46492 Learning rate: 0.02 Mask loss: 0.25836 RPN box loss: 0.03907 RPN score loss: 0.01648 RPN total loss: 0.05556 Total loss: 2.14877 timestamp: 1655017797.248043 iteration: 11830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10476 FastRCNN class loss: 0.0444 FastRCNN total loss: 0.14916 L1 loss: 0.0000e+00 L2 loss: 1.46467 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.06935 RPN score loss: 0.00544 RPN total loss: 0.07478 Total loss: 1.8207 timestamp: 1655017800.582156 iteration: 11835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27899 FastRCNN class loss: 0.10363 FastRCNN total loss: 0.38262 L1 loss: 0.0000e+00 L2 loss: 1.46442 Learning rate: 0.02 Mask loss: 0.18636 RPN box loss: 0.02467 RPN score loss: 0.00534 RPN total loss: 0.03001 Total loss: 2.0634 timestamp: 1655017803.980285 iteration: 11840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12667 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.19114 L1 loss: 0.0000e+00 L2 loss: 1.46414 Learning rate: 0.02 Mask loss: 0.11923 RPN box loss: 0.02042 RPN score loss: 0.00509 RPN total loss: 0.02551 Total loss: 1.80001 timestamp: 1655017807.1683667 iteration: 11845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12953 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.22328 L1 loss: 0.0000e+00 L2 loss: 1.46385 Learning rate: 0.02 Mask loss: 0.1329 RPN box loss: 0.02613 RPN score loss: 0.00598 RPN total loss: 0.03211 Total loss: 1.85214 timestamp: 1655017810.633803 iteration: 11850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13143 FastRCNN class loss: 0.0638 FastRCNN total loss: 0.19523 L1 loss: 0.0000e+00 L2 loss: 1.46358 Learning rate: 0.02 Mask loss: 0.14187 RPN box loss: 0.08202 RPN score loss: 0.01022 RPN total loss: 0.09224 Total loss: 1.89292 timestamp: 1655017813.922141 iteration: 11855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16953 FastRCNN class loss: 0.08283 FastRCNN total loss: 0.25235 L1 loss: 0.0000e+00 L2 loss: 1.46332 Learning rate: 0.02 Mask loss: 0.1476 RPN box loss: 0.083 RPN score loss: 0.00834 RPN total loss: 0.09134 Total loss: 1.95462 timestamp: 1655017817.32363 iteration: 11860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16187 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.25384 L1 loss: 0.0000e+00 L2 loss: 1.46306 Learning rate: 0.02 Mask loss: 0.18478 RPN box loss: 0.03602 RPN score loss: 0.01132 RPN total loss: 0.04734 Total loss: 1.94903 timestamp: 1655017820.5423012 iteration: 11865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19605 FastRCNN class loss: 0.13963 FastRCNN total loss: 0.33568 L1 loss: 0.0000e+00 L2 loss: 1.46279 Learning rate: 0.02 Mask loss: 0.22195 RPN box loss: 0.05996 RPN score loss: 0.0386 RPN total loss: 0.09856 Total loss: 2.11899 timestamp: 1655017823.9606543 iteration: 11870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20487 FastRCNN class loss: 0.09681 FastRCNN total loss: 0.30168 L1 loss: 0.0000e+00 L2 loss: 1.46252 Learning rate: 0.02 Mask loss: 0.21375 RPN box loss: 0.07537 RPN score loss: 0.01654 RPN total loss: 0.09192 Total loss: 2.06987 timestamp: 1655017827.247925 iteration: 11875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16664 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.24559 L1 loss: 0.0000e+00 L2 loss: 1.46227 Learning rate: 0.02 Mask loss: 0.19998 RPN box loss: 0.02936 RPN score loss: 0.01192 RPN total loss: 0.04127 Total loss: 1.94911 timestamp: 1655017830.566798 iteration: 11880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12757 FastRCNN class loss: 0.07271 FastRCNN total loss: 0.20028 L1 loss: 0.0000e+00 L2 loss: 1.462 Learning rate: 0.02 Mask loss: 0.21617 RPN box loss: 0.03219 RPN score loss: 0.00793 RPN total loss: 0.04012 Total loss: 1.91856 timestamp: 1655017833.9833803 iteration: 11885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18122 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.28518 L1 loss: 0.0000e+00 L2 loss: 1.46173 Learning rate: 0.02 Mask loss: 0.29166 RPN box loss: 0.04317 RPN score loss: 0.00928 RPN total loss: 0.05245 Total loss: 2.09101 timestamp: 1655017837.308651 iteration: 11890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11074 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.19069 L1 loss: 0.0000e+00 L2 loss: 1.46145 Learning rate: 0.02 Mask loss: 0.16675 RPN box loss: 0.03409 RPN score loss: 0.00624 RPN total loss: 0.04033 Total loss: 1.85921 timestamp: 1655017840.723325 iteration: 11895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18599 FastRCNN class loss: 0.11243 FastRCNN total loss: 0.29841 L1 loss: 0.0000e+00 L2 loss: 1.46119 Learning rate: 0.02 Mask loss: 0.21457 RPN box loss: 0.09203 RPN score loss: 0.01163 RPN total loss: 0.10366 Total loss: 2.07784 timestamp: 1655017843.9693482 iteration: 11900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15362 FastRCNN class loss: 0.07948 FastRCNN total loss: 0.2331 L1 loss: 0.0000e+00 L2 loss: 1.46093 Learning rate: 0.02 Mask loss: 0.20517 RPN box loss: 0.03541 RPN score loss: 0.0178 RPN total loss: 0.0532 Total loss: 1.9524 timestamp: 1655017847.429292 iteration: 11905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13123 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.21076 L1 loss: 0.0000e+00 L2 loss: 1.46068 Learning rate: 0.02 Mask loss: 0.1926 RPN box loss: 0.10035 RPN score loss: 0.00737 RPN total loss: 0.10773 Total loss: 1.97177 timestamp: 1655017850.7235365 iteration: 11910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25278 FastRCNN class loss: 0.22033 FastRCNN total loss: 0.47311 L1 loss: 0.0000e+00 L2 loss: 1.46042 Learning rate: 0.02 Mask loss: 0.30949 RPN box loss: 0.06576 RPN score loss: 0.01846 RPN total loss: 0.08421 Total loss: 2.32723 timestamp: 1655017854.0956166 iteration: 11915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13086 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.18631 L1 loss: 0.0000e+00 L2 loss: 1.46017 Learning rate: 0.02 Mask loss: 0.13958 RPN box loss: 0.15992 RPN score loss: 0.00549 RPN total loss: 0.16541 Total loss: 1.95147 timestamp: 1655017857.3393855 iteration: 11920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19418 FastRCNN class loss: 0.07662 FastRCNN total loss: 0.27079 L1 loss: 0.0000e+00 L2 loss: 1.45993 Learning rate: 0.02 Mask loss: 0.18613 RPN box loss: 0.00892 RPN score loss: 0.00628 RPN total loss: 0.0152 Total loss: 1.93205 timestamp: 1655017860.642013 iteration: 11925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16353 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.24144 L1 loss: 0.0000e+00 L2 loss: 1.45966 Learning rate: 0.02 Mask loss: 0.2512 RPN box loss: 0.04004 RPN score loss: 0.0064 RPN total loss: 0.04644 Total loss: 1.99874 timestamp: 1655017863.9499586 iteration: 11930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18066 FastRCNN class loss: 0.09457 FastRCNN total loss: 0.27523 L1 loss: 0.0000e+00 L2 loss: 1.45936 Learning rate: 0.02 Mask loss: 0.20908 RPN box loss: 0.01288 RPN score loss: 0.00414 RPN total loss: 0.01702 Total loss: 1.9607 timestamp: 1655017867.2601569 iteration: 11935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25042 FastRCNN class loss: 0.1191 FastRCNN total loss: 0.36952 L1 loss: 0.0000e+00 L2 loss: 1.4591 Learning rate: 0.02 Mask loss: 0.24203 RPN box loss: 0.08464 RPN score loss: 0.0227 RPN total loss: 0.10735 Total loss: 2.178 timestamp: 1655017870.6931458 iteration: 11940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18362 FastRCNN class loss: 0.10097 FastRCNN total loss: 0.28458 L1 loss: 0.0000e+00 L2 loss: 1.45883 Learning rate: 0.02 Mask loss: 0.20034 RPN box loss: 0.0252 RPN score loss: 0.00656 RPN total loss: 0.03177 Total loss: 1.97552 timestamp: 1655017873.9636436 iteration: 11945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12646 FastRCNN class loss: 0.09112 FastRCNN total loss: 0.21757 L1 loss: 0.0000e+00 L2 loss: 1.45856 Learning rate: 0.02 Mask loss: 0.15215 RPN box loss: 0.01526 RPN score loss: 0.0023 RPN total loss: 0.01756 Total loss: 1.84585 timestamp: 1655017877.5144205 iteration: 11950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17796 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.24994 L1 loss: 0.0000e+00 L2 loss: 1.4583 Learning rate: 0.02 Mask loss: 0.17375 RPN box loss: 0.06185 RPN score loss: 0.00876 RPN total loss: 0.07061 Total loss: 1.95259 timestamp: 1655017880.8509262 iteration: 11955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20088 FastRCNN class loss: 0.08574 FastRCNN total loss: 0.28662 L1 loss: 0.0000e+00 L2 loss: 1.45804 Learning rate: 0.02 Mask loss: 0.14995 RPN box loss: 0.05499 RPN score loss: 0.01079 RPN total loss: 0.06578 Total loss: 1.96038 timestamp: 1655017884.2370307 iteration: 11960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14426 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.22425 L1 loss: 0.0000e+00 L2 loss: 1.45779 Learning rate: 0.02 Mask loss: 0.14257 RPN box loss: 0.03256 RPN score loss: 0.0061 RPN total loss: 0.03866 Total loss: 1.86327 timestamp: 1655017887.549363 iteration: 11965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17317 FastRCNN class loss: 0.14465 FastRCNN total loss: 0.31782 L1 loss: 0.0000e+00 L2 loss: 1.45753 Learning rate: 0.02 Mask loss: 0.19164 RPN box loss: 0.04013 RPN score loss: 0.00823 RPN total loss: 0.04836 Total loss: 2.01534 timestamp: 1655017890.9899652 iteration: 11970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15409 FastRCNN class loss: 0.08664 FastRCNN total loss: 0.24073 L1 loss: 0.0000e+00 L2 loss: 1.45726 Learning rate: 0.02 Mask loss: 0.20806 RPN box loss: 0.01441 RPN score loss: 0.01545 RPN total loss: 0.02986 Total loss: 1.93591 timestamp: 1655017894.401796 iteration: 11975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22921 FastRCNN class loss: 0.16338 FastRCNN total loss: 0.3926 L1 loss: 0.0000e+00 L2 loss: 1.45701 Learning rate: 0.02 Mask loss: 0.29031 RPN box loss: 0.03547 RPN score loss: 0.02659 RPN total loss: 0.06206 Total loss: 2.20198 timestamp: 1655017897.706021 iteration: 11980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13453 FastRCNN class loss: 0.06602 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 1.45677 Learning rate: 0.02 Mask loss: 0.14456 RPN box loss: 0.0286 RPN score loss: 0.01799 RPN total loss: 0.0466 Total loss: 1.84847 timestamp: 1655017901.064308 iteration: 11985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22079 FastRCNN class loss: 0.10922 FastRCNN total loss: 0.33001 L1 loss: 0.0000e+00 L2 loss: 1.45649 Learning rate: 0.02 Mask loss: 0.19471 RPN box loss: 0.06708 RPN score loss: 0.01426 RPN total loss: 0.08134 Total loss: 2.06255 timestamp: 1655017904.3235736 iteration: 11990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18469 FastRCNN class loss: 0.11733 FastRCNN total loss: 0.30202 L1 loss: 0.0000e+00 L2 loss: 1.4562 Learning rate: 0.02 Mask loss: 0.28424 RPN box loss: 0.03687 RPN score loss: 0.00603 RPN total loss: 0.0429 Total loss: 2.08535 timestamp: 1655017907.7310965 iteration: 11995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.16999 L1 loss: 0.0000e+00 L2 loss: 1.45592 Learning rate: 0.02 Mask loss: 0.16992 RPN box loss: 0.04765 RPN score loss: 0.00718 RPN total loss: 0.05483 Total loss: 1.85067 timestamp: 1655017911.017704 iteration: 12000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15042 FastRCNN class loss: 0.12902 FastRCNN total loss: 0.27944 L1 loss: 0.0000e+00 L2 loss: 1.45567 Learning rate: 0.02 Mask loss: 0.15155 RPN box loss: 0.03666 RPN score loss: 0.00798 RPN total loss: 0.04464 Total loss: 1.93131 timestamp: 1655017914.413137 iteration: 12005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11777 FastRCNN class loss: 0.06143 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 1.45542 Learning rate: 0.02 Mask loss: 0.21423 RPN box loss: 0.0042 RPN score loss: 0.00612 RPN total loss: 0.01033 Total loss: 1.85918 timestamp: 1655017917.8385427 iteration: 12010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19888 FastRCNN class loss: 0.09829 FastRCNN total loss: 0.29717 L1 loss: 0.0000e+00 L2 loss: 1.45515 Learning rate: 0.02 Mask loss: 0.288 RPN box loss: 0.02383 RPN score loss: 0.006 RPN total loss: 0.02982 Total loss: 2.07014 timestamp: 1655017921.2171226 iteration: 12015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20605 FastRCNN class loss: 0.09117 FastRCNN total loss: 0.29722 L1 loss: 0.0000e+00 L2 loss: 1.45489 Learning rate: 0.02 Mask loss: 0.17314 RPN box loss: 0.06171 RPN score loss: 0.0101 RPN total loss: 0.07181 Total loss: 1.99705 timestamp: 1655017924.7286544 iteration: 12020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20183 FastRCNN class loss: 0.13335 FastRCNN total loss: 0.33518 L1 loss: 0.0000e+00 L2 loss: 1.45464 Learning rate: 0.02 Mask loss: 0.19207 RPN box loss: 0.08721 RPN score loss: 0.01637 RPN total loss: 0.10358 Total loss: 2.08547 timestamp: 1655017927.9976594 iteration: 12025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20485 FastRCNN class loss: 0.11809 FastRCNN total loss: 0.32294 L1 loss: 0.0000e+00 L2 loss: 1.45435 Learning rate: 0.02 Mask loss: 0.17212 RPN box loss: 0.13241 RPN score loss: 0.01139 RPN total loss: 0.1438 Total loss: 2.09321 timestamp: 1655017931.2974012 iteration: 12030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21013 FastRCNN class loss: 0.12884 FastRCNN total loss: 0.33897 L1 loss: 0.0000e+00 L2 loss: 1.45408 Learning rate: 0.02 Mask loss: 0.21997 RPN box loss: 0.03443 RPN score loss: 0.01373 RPN total loss: 0.04815 Total loss: 2.06117 timestamp: 1655017934.6627765 iteration: 12035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11656 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 1.45381 Learning rate: 0.02 Mask loss: 0.18124 RPN box loss: 0.01999 RPN score loss: 0.0127 RPN total loss: 0.03269 Total loss: 1.85311 timestamp: 1655017938.0859694 iteration: 12040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17548 FastRCNN class loss: 0.07424 FastRCNN total loss: 0.24972 L1 loss: 0.0000e+00 L2 loss: 1.45356 Learning rate: 0.02 Mask loss: 0.13441 RPN box loss: 0.03395 RPN score loss: 0.01074 RPN total loss: 0.0447 Total loss: 1.88239 timestamp: 1655017941.403783 iteration: 12045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22198 FastRCNN class loss: 0.12583 FastRCNN total loss: 0.34781 L1 loss: 0.0000e+00 L2 loss: 1.45329 Learning rate: 0.02 Mask loss: 0.22349 RPN box loss: 0.07222 RPN score loss: 0.00876 RPN total loss: 0.08098 Total loss: 2.10557 timestamp: 1655017944.8400507 iteration: 12050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14319 FastRCNN class loss: 0.04049 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 1.45302 Learning rate: 0.02 Mask loss: 0.26392 RPN box loss: 0.04267 RPN score loss: 0.00689 RPN total loss: 0.04957 Total loss: 1.95019 timestamp: 1655017948.2708838 iteration: 12055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21514 FastRCNN class loss: 0.1188 FastRCNN total loss: 0.33394 L1 loss: 0.0000e+00 L2 loss: 1.45277 Learning rate: 0.02 Mask loss: 0.16721 RPN box loss: 0.0558 RPN score loss: 0.01743 RPN total loss: 0.07323 Total loss: 2.02714 timestamp: 1655017951.521873 iteration: 12060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17619 FastRCNN class loss: 0.09061 FastRCNN total loss: 0.2668 L1 loss: 0.0000e+00 L2 loss: 1.4525 Learning rate: 0.02 Mask loss: 0.15653 RPN box loss: 0.02664 RPN score loss: 0.00947 RPN total loss: 0.0361 Total loss: 1.91194 timestamp: 1655017954.9374535 iteration: 12065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17267 FastRCNN class loss: 0.09531 FastRCNN total loss: 0.26798 L1 loss: 0.0000e+00 L2 loss: 1.45223 Learning rate: 0.02 Mask loss: 0.21909 RPN box loss: 0.0789 RPN score loss: 0.0066 RPN total loss: 0.0855 Total loss: 2.02479 timestamp: 1655017958.3254526 iteration: 12070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21264 FastRCNN class loss: 0.06534 FastRCNN total loss: 0.27799 L1 loss: 0.0000e+00 L2 loss: 1.45197 Learning rate: 0.02 Mask loss: 0.15956 RPN box loss: 0.01907 RPN score loss: 0.00493 RPN total loss: 0.02401 Total loss: 1.91353 timestamp: 1655017961.8105114 iteration: 12075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16805 FastRCNN class loss: 0.07005 FastRCNN total loss: 0.2381 L1 loss: 0.0000e+00 L2 loss: 1.4517 Learning rate: 0.02 Mask loss: 0.18338 RPN box loss: 0.02715 RPN score loss: 0.01322 RPN total loss: 0.04037 Total loss: 1.91355 timestamp: 1655017965.1778603 iteration: 12080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09995 FastRCNN class loss: 0.04338 FastRCNN total loss: 0.14333 L1 loss: 0.0000e+00 L2 loss: 1.45145 Learning rate: 0.02 Mask loss: 0.10999 RPN box loss: 0.03776 RPN score loss: 0.00567 RPN total loss: 0.04343 Total loss: 1.74821 timestamp: 1655017968.658522 iteration: 12085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1542 FastRCNN class loss: 0.09247 FastRCNN total loss: 0.24667 L1 loss: 0.0000e+00 L2 loss: 1.45119 Learning rate: 0.02 Mask loss: 0.19481 RPN box loss: 0.01609 RPN score loss: 0.00342 RPN total loss: 0.01951 Total loss: 1.91218 timestamp: 1655017972.0704558 iteration: 12090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17273 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.26704 L1 loss: 0.0000e+00 L2 loss: 1.45087 Learning rate: 0.02 Mask loss: 0.17817 RPN box loss: 0.07162 RPN score loss: 0.01472 RPN total loss: 0.08634 Total loss: 1.98243 timestamp: 1655017975.3729343 iteration: 12095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16209 FastRCNN class loss: 0.10816 FastRCNN total loss: 0.27025 L1 loss: 0.0000e+00 L2 loss: 1.45062 Learning rate: 0.02 Mask loss: 0.22769 RPN box loss: 0.01872 RPN score loss: 0.01049 RPN total loss: 0.02921 Total loss: 1.97776 timestamp: 1655017978.7581534 iteration: 12100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25108 FastRCNN class loss: 0.0982 FastRCNN total loss: 0.34927 L1 loss: 0.0000e+00 L2 loss: 1.45037 Learning rate: 0.02 Mask loss: 0.20669 RPN box loss: 0.0757 RPN score loss: 0.00982 RPN total loss: 0.08552 Total loss: 2.09186 timestamp: 1655017982.0565677 iteration: 12105 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1598 FastRCNN class loss: 0.11467 FastRCNN total loss: 0.27447 L1 loss: 0.0000e+00 L2 loss: 1.45012 Learning rate: 0.02 Mask loss: 0.19209 RPN box loss: 0.05869 RPN score loss: 0.00793 RPN total loss: 0.06663 Total loss: 1.98331 timestamp: 1655017985.5329463 iteration: 12110 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1781 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.25963 L1 loss: 0.0000e+00 L2 loss: 1.44986 Learning rate: 0.02 Mask loss: 0.12408 RPN box loss: 0.05699 RPN score loss: 0.00885 RPN total loss: 0.06585 Total loss: 1.89942 timestamp: 1655017988.8256729 iteration: 12115 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24066 FastRCNN class loss: 0.13224 FastRCNN total loss: 0.37291 L1 loss: 0.0000e+00 L2 loss: 1.44959 Learning rate: 0.02 Mask loss: 0.1809 RPN box loss: 0.02701 RPN score loss: 0.00956 RPN total loss: 0.03657 Total loss: 2.03996 timestamp: 1655017992.2301202 iteration: 12120 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22961 FastRCNN class loss: 0.09774 FastRCNN total loss: 0.32735 L1 loss: 0.0000e+00 L2 loss: 1.44934 Learning rate: 0.02 Mask loss: 0.20676 RPN box loss: 0.06089 RPN score loss: 0.01412 RPN total loss: 0.07501 Total loss: 2.05845 timestamp: 1655017995.5085907 iteration: 12125 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11869 FastRCNN class loss: 0.09381 FastRCNN total loss: 0.2125 L1 loss: 0.0000e+00 L2 loss: 1.4491 Learning rate: 0.02 Mask loss: 0.15992 RPN box loss: 0.04445 RPN score loss: 0.01016 RPN total loss: 0.05461 Total loss: 1.87613 timestamp: 1655017998.8670568 iteration: 12130 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12062 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.17285 L1 loss: 0.0000e+00 L2 loss: 1.44884 Learning rate: 0.02 Mask loss: 0.11362 RPN box loss: 0.03398 RPN score loss: 0.00587 RPN total loss: 0.03985 Total loss: 1.77516 timestamp: 1655018002.2077806 iteration: 12135 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16851 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.23808 L1 loss: 0.0000e+00 L2 loss: 1.44857 Learning rate: 0.02 Mask loss: 0.15994 RPN box loss: 0.01861 RPN score loss: 0.01121 RPN total loss: 0.02982 Total loss: 1.87641 timestamp: 1655018005.6119921 iteration: 12140 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.143 FastRCNN class loss: 0.08609 FastRCNN total loss: 0.22909 L1 loss: 0.0000e+00 L2 loss: 1.44831 Learning rate: 0.02 Mask loss: 0.14889 RPN box loss: 0.03293 RPN score loss: 0.00763 RPN total loss: 0.04056 Total loss: 1.86684 timestamp: 1655018008.9605281 iteration: 12145 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1892 FastRCNN class loss: 0.12588 FastRCNN total loss: 0.31508 L1 loss: 0.0000e+00 L2 loss: 1.44805 Learning rate: 0.02 Mask loss: 0.27953 RPN box loss: 0.07223 RPN score loss: 0.01699 RPN total loss: 0.08922 Total loss: 2.13188 timestamp: 1655018012.213251 iteration: 12150 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20402 FastRCNN class loss: 0.10778 FastRCNN total loss: 0.3118 L1 loss: 0.0000e+00 L2 loss: 1.4478 Learning rate: 0.02 Mask loss: 0.26498 RPN box loss: 0.06828 RPN score loss: 0.01864 RPN total loss: 0.08693 Total loss: 2.11151 timestamp: 1655018015.658835 iteration: 12155 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14548 FastRCNN class loss: 0.06182 FastRCNN total loss: 0.2073 L1 loss: 0.0000e+00 L2 loss: 1.44753 Learning rate: 0.02 Mask loss: 0.22105 RPN box loss: 0.06393 RPN score loss: 0.01768 RPN total loss: 0.08162 Total loss: 1.9575 timestamp: 1655018018.8539803 iteration: 12160 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12574 FastRCNN class loss: 0.08444 FastRCNN total loss: 0.21019 L1 loss: 0.0000e+00 L2 loss: 1.44729 Learning rate: 0.02 Mask loss: 0.12604 RPN box loss: 0.05236 RPN score loss: 0.01568 RPN total loss: 0.06804 Total loss: 1.85157 timestamp: 1655018022.2808387 iteration: 12165 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16252 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.2286 L1 loss: 0.0000e+00 L2 loss: 1.44705 Learning rate: 0.02 Mask loss: 0.19673 RPN box loss: 0.00708 RPN score loss: 0.01211 RPN total loss: 0.01919 Total loss: 1.89156 timestamp: 1655018025.5300367 iteration: 12170 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17273 FastRCNN class loss: 0.09482 FastRCNN total loss: 0.26755 L1 loss: 0.0000e+00 L2 loss: 1.44677 Learning rate: 0.02 Mask loss: 0.17278 RPN box loss: 0.07219 RPN score loss: 0.00707 RPN total loss: 0.07926 Total loss: 1.96635 timestamp: 1655018028.919399 iteration: 12175 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14243 FastRCNN class loss: 0.09912 FastRCNN total loss: 0.24156 L1 loss: 0.0000e+00 L2 loss: 1.44649 Learning rate: 0.02 Mask loss: 0.15295 RPN box loss: 0.02459 RPN score loss: 0.02491 RPN total loss: 0.0495 Total loss: 1.8905 timestamp: 1655018032.2876394 iteration: 12180 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28201 FastRCNN class loss: 0.18044 FastRCNN total loss: 0.46245 L1 loss: 0.0000e+00 L2 loss: 1.44622 Learning rate: 0.02 Mask loss: 0.19388 RPN box loss: 0.01946 RPN score loss: 0.015 RPN total loss: 0.03446 Total loss: 2.13701 timestamp: 1655018035.6295493 iteration: 12185 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09704 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 1.44598 Learning rate: 0.02 Mask loss: 0.14455 RPN box loss: 0.0232 RPN score loss: 0.00689 RPN total loss: 0.03008 Total loss: 1.77299 timestamp: 1655018038.9733672 iteration: 12190 throughput: 23.9 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17599 FastRCNN class loss: 0.10137 FastRCNN total loss: 0.27736 L1 loss: 0.0000e+00 L2 loss: 1.44572 Learning rate: 0.02 Mask loss: 0.21578 RPN box loss: 0.0354 RPN score loss: 0.01421 RPN total loss: 0.04961 Total loss: 1.98847 timestamp: 1655018042.1938546 iteration: 12195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19639 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.2682 L1 loss: 0.0000e+00 L2 loss: 1.44545 Learning rate: 0.02 Mask loss: 0.31153 RPN box loss: 0.02709 RPN score loss: 0.00616 RPN total loss: 0.03324 Total loss: 2.05842 timestamp: 1655018045.5754778 iteration: 12200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1038 FastRCNN class loss: 0.09848 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 1.44519 Learning rate: 0.02 Mask loss: 0.15902 RPN box loss: 0.02725 RPN score loss: 0.00562 RPN total loss: 0.03287 Total loss: 1.83936 timestamp: 1655018048.860017 iteration: 12205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12801 FastRCNN class loss: 0.04097 FastRCNN total loss: 0.16897 L1 loss: 0.0000e+00 L2 loss: 1.44493 Learning rate: 0.02 Mask loss: 0.15508 RPN box loss: 0.02937 RPN score loss: 0.00808 RPN total loss: 0.03746 Total loss: 1.80645 timestamp: 1655018052.2352571 iteration: 12210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24937 FastRCNN class loss: 0.14153 FastRCNN total loss: 0.3909 L1 loss: 0.0000e+00 L2 loss: 1.44468 Learning rate: 0.02 Mask loss: 0.25231 RPN box loss: 0.05668 RPN score loss: 0.02835 RPN total loss: 0.08503 Total loss: 2.17292 timestamp: 1655018055.4269214 iteration: 12215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21254 FastRCNN class loss: 0.12656 FastRCNN total loss: 0.3391 L1 loss: 0.0000e+00 L2 loss: 1.44442 Learning rate: 0.02 Mask loss: 0.25011 RPN box loss: 0.05122 RPN score loss: 0.01062 RPN total loss: 0.06184 Total loss: 2.09547 timestamp: 1655018058.9220066 iteration: 12220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15686 FastRCNN class loss: 0.06617 FastRCNN total loss: 0.22304 L1 loss: 0.0000e+00 L2 loss: 1.44417 Learning rate: 0.02 Mask loss: 0.15515 RPN box loss: 0.01287 RPN score loss: 0.00721 RPN total loss: 0.02008 Total loss: 1.84244 timestamp: 1655018062.265739 iteration: 12225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21864 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.29637 L1 loss: 0.0000e+00 L2 loss: 1.4439 Learning rate: 0.02 Mask loss: 0.18519 RPN box loss: 0.13275 RPN score loss: 0.01523 RPN total loss: 0.14799 Total loss: 2.07345 timestamp: 1655018065.5576801 iteration: 12230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19426 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.27466 L1 loss: 0.0000e+00 L2 loss: 1.44364 Learning rate: 0.02 Mask loss: 0.19657 RPN box loss: 0.0586 RPN score loss: 0.00602 RPN total loss: 0.06462 Total loss: 1.97949 timestamp: 1655018068.9277275 iteration: 12235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1722 FastRCNN class loss: 0.10955 FastRCNN total loss: 0.28175 L1 loss: 0.0000e+00 L2 loss: 1.44335 Learning rate: 0.02 Mask loss: 0.1358 RPN box loss: 0.04308 RPN score loss: 0.01444 RPN total loss: 0.05751 Total loss: 1.91842 timestamp: 1655018072.152089 iteration: 12240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16494 FastRCNN class loss: 0.11037 FastRCNN total loss: 0.27532 L1 loss: 0.0000e+00 L2 loss: 1.4431 Learning rate: 0.02 Mask loss: 0.25123 RPN box loss: 0.02759 RPN score loss: 0.00985 RPN total loss: 0.03744 Total loss: 2.00709 timestamp: 1655018075.550264 iteration: 12245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13893 FastRCNN class loss: 0.0833 FastRCNN total loss: 0.22222 L1 loss: 0.0000e+00 L2 loss: 1.44285 Learning rate: 0.02 Mask loss: 0.21104 RPN box loss: 0.02012 RPN score loss: 0.00677 RPN total loss: 0.02688 Total loss: 1.903 timestamp: 1655018078.8012872 iteration: 12250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22669 FastRCNN class loss: 0.10847 FastRCNN total loss: 0.33516 L1 loss: 0.0000e+00 L2 loss: 1.44259 Learning rate: 0.02 Mask loss: 0.14606 RPN box loss: 0.0908 RPN score loss: 0.01017 RPN total loss: 0.10097 Total loss: 2.02478 timestamp: 1655018082.1719084 iteration: 12255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13685 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.18365 L1 loss: 0.0000e+00 L2 loss: 1.44231 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.02109 RPN score loss: 0.01174 RPN total loss: 0.03283 Total loss: 1.81302 timestamp: 1655018085.4566243 iteration: 12260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20476 FastRCNN class loss: 0.14808 FastRCNN total loss: 0.35284 L1 loss: 0.0000e+00 L2 loss: 1.44203 Learning rate: 0.02 Mask loss: 0.24206 RPN box loss: 0.04239 RPN score loss: 0.00931 RPN total loss: 0.05171 Total loss: 2.08865 timestamp: 1655018088.8598776 iteration: 12265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19236 FastRCNN class loss: 0.11003 FastRCNN total loss: 0.30239 L1 loss: 0.0000e+00 L2 loss: 1.44177 Learning rate: 0.02 Mask loss: 0.13836 RPN box loss: 0.10277 RPN score loss: 0.01034 RPN total loss: 0.11312 Total loss: 1.99563 timestamp: 1655018092.253441 iteration: 12270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13336 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.19703 L1 loss: 0.0000e+00 L2 loss: 1.44152 Learning rate: 0.02 Mask loss: 0.16347 RPN box loss: 0.0698 RPN score loss: 0.01075 RPN total loss: 0.08055 Total loss: 1.88257 timestamp: 1655018095.559083 iteration: 12275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1179 FastRCNN class loss: 0.09161 FastRCNN total loss: 0.20951 L1 loss: 0.0000e+00 L2 loss: 1.44126 Learning rate: 0.02 Mask loss: 0.15678 RPN box loss: 0.04305 RPN score loss: 0.01149 RPN total loss: 0.05454 Total loss: 1.86209 timestamp: 1655018098.900088 iteration: 12280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1506 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.22668 L1 loss: 0.0000e+00 L2 loss: 1.44102 Learning rate: 0.02 Mask loss: 0.1452 RPN box loss: 0.02835 RPN score loss: 0.00722 RPN total loss: 0.03557 Total loss: 1.84848 timestamp: 1655018102.1916327 iteration: 12285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1446 FastRCNN class loss: 0.1323 FastRCNN total loss: 0.2769 L1 loss: 0.0000e+00 L2 loss: 1.44077 Learning rate: 0.02 Mask loss: 0.18064 RPN box loss: 0.02034 RPN score loss: 0.01072 RPN total loss: 0.03105 Total loss: 1.92936 timestamp: 1655018105.568652 iteration: 12290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19471 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.26848 L1 loss: 0.0000e+00 L2 loss: 1.44049 Learning rate: 0.02 Mask loss: 0.14028 RPN box loss: 0.01161 RPN score loss: 0.00578 RPN total loss: 0.01739 Total loss: 1.86664 timestamp: 1655018108.9227972 iteration: 12295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2446 FastRCNN class loss: 0.10789 FastRCNN total loss: 0.35249 L1 loss: 0.0000e+00 L2 loss: 1.44023 Learning rate: 0.02 Mask loss: 0.23037 RPN box loss: 0.024 RPN score loss: 0.00521 RPN total loss: 0.02921 Total loss: 2.0523 timestamp: 1655018112.3579268 iteration: 12300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15075 FastRCNN class loss: 0.12597 FastRCNN total loss: 0.27672 L1 loss: 0.0000e+00 L2 loss: 1.43996 Learning rate: 0.02 Mask loss: 0.17772 RPN box loss: 0.0086 RPN score loss: 0.00823 RPN total loss: 0.01684 Total loss: 1.91124 timestamp: 1655018115.6991308 iteration: 12305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10676 FastRCNN class loss: 0.09685 FastRCNN total loss: 0.20361 L1 loss: 0.0000e+00 L2 loss: 1.43971 Learning rate: 0.02 Mask loss: 0.22122 RPN box loss: 0.07677 RPN score loss: 0.00784 RPN total loss: 0.08461 Total loss: 1.94915 timestamp: 1655018119.0804777 iteration: 12310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06422 FastRCNN class loss: 0.08956 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 1.43945 Learning rate: 0.02 Mask loss: 0.14351 RPN box loss: 0.06011 RPN score loss: 0.00456 RPN total loss: 0.06467 Total loss: 1.8014 timestamp: 1655018122.5112329 iteration: 12315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19067 FastRCNN class loss: 0.105 FastRCNN total loss: 0.29567 L1 loss: 0.0000e+00 L2 loss: 1.4392 Learning rate: 0.02 Mask loss: 0.15929 RPN box loss: 0.04508 RPN score loss: 0.00889 RPN total loss: 0.05397 Total loss: 1.94813 timestamp: 1655018125.8757174 iteration: 12320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24505 FastRCNN class loss: 0.10967 FastRCNN total loss: 0.35472 L1 loss: 0.0000e+00 L2 loss: 1.43895 Learning rate: 0.02 Mask loss: 0.17726 RPN box loss: 0.03684 RPN score loss: 0.03141 RPN total loss: 0.06825 Total loss: 2.03918 timestamp: 1655018129.3406022 iteration: 12325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15762 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.23966 L1 loss: 0.0000e+00 L2 loss: 1.4387 Learning rate: 0.02 Mask loss: 0.18071 RPN box loss: 0.02098 RPN score loss: 0.00949 RPN total loss: 0.03046 Total loss: 1.88953 timestamp: 1655018132.667434 iteration: 12330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17338 FastRCNN class loss: 0.08893 FastRCNN total loss: 0.26231 L1 loss: 0.0000e+00 L2 loss: 1.43843 Learning rate: 0.02 Mask loss: 0.17255 RPN box loss: 0.07354 RPN score loss: 0.01042 RPN total loss: 0.08396 Total loss: 1.95726 timestamp: 1655018136.1027014 iteration: 12335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13612 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.19094 L1 loss: 0.0000e+00 L2 loss: 1.43817 Learning rate: 0.02 Mask loss: 0.13996 RPN box loss: 0.03283 RPN score loss: 0.00916 RPN total loss: 0.042 Total loss: 1.81107 timestamp: 1655018139.392623 iteration: 12340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12958 FastRCNN class loss: 0.0936 FastRCNN total loss: 0.22317 L1 loss: 0.0000e+00 L2 loss: 1.43793 Learning rate: 0.02 Mask loss: 0.16549 RPN box loss: 0.01793 RPN score loss: 0.00294 RPN total loss: 0.02087 Total loss: 1.84747 timestamp: 1655018142.8085299 iteration: 12345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19043 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.26714 L1 loss: 0.0000e+00 L2 loss: 1.43768 Learning rate: 0.02 Mask loss: 0.22797 RPN box loss: 0.05326 RPN score loss: 0.00916 RPN total loss: 0.06242 Total loss: 1.99521 timestamp: 1655018146.281609 iteration: 12350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16597 FastRCNN class loss: 0.09312 FastRCNN total loss: 0.25909 L1 loss: 0.0000e+00 L2 loss: 1.43743 Learning rate: 0.02 Mask loss: 0.1673 RPN box loss: 0.04285 RPN score loss: 0.0113 RPN total loss: 0.05415 Total loss: 1.91797 timestamp: 1655018149.5944302 iteration: 12355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25357 FastRCNN class loss: 0.097 FastRCNN total loss: 0.35057 L1 loss: 0.0000e+00 L2 loss: 1.43718 Learning rate: 0.02 Mask loss: 0.18156 RPN box loss: 0.04593 RPN score loss: 0.01532 RPN total loss: 0.06124 Total loss: 2.03055 timestamp: 1655018152.8555615 iteration: 12360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07707 FastRCNN class loss: 0.04409 FastRCNN total loss: 0.12116 L1 loss: 0.0000e+00 L2 loss: 1.43693 Learning rate: 0.02 Mask loss: 0.32343 RPN box loss: 0.04892 RPN score loss: 0.00779 RPN total loss: 0.05671 Total loss: 1.93822 timestamp: 1655018156.174448 iteration: 12365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10602 FastRCNN class loss: 0.10959 FastRCNN total loss: 0.2156 L1 loss: 0.0000e+00 L2 loss: 1.43666 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.03971 RPN score loss: 0.00364 RPN total loss: 0.04335 Total loss: 1.82772 timestamp: 1655018159.552608 iteration: 12370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12829 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.21093 L1 loss: 0.0000e+00 L2 loss: 1.4364 Learning rate: 0.02 Mask loss: 0.16501 RPN box loss: 0.03159 RPN score loss: 0.01146 RPN total loss: 0.04305 Total loss: 1.85539 timestamp: 1655018162.8721292 iteration: 12375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14458 FastRCNN class loss: 0.08545 FastRCNN total loss: 0.23003 L1 loss: 0.0000e+00 L2 loss: 1.43612 Learning rate: 0.02 Mask loss: 0.16237 RPN box loss: 0.05699 RPN score loss: 0.00695 RPN total loss: 0.06395 Total loss: 1.89246 timestamp: 1655018166.2686784 iteration: 12380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17571 FastRCNN class loss: 0.10982 FastRCNN total loss: 0.28553 L1 loss: 0.0000e+00 L2 loss: 1.43583 Learning rate: 0.02 Mask loss: 0.14731 RPN box loss: 0.01398 RPN score loss: 0.00282 RPN total loss: 0.0168 Total loss: 1.88547 timestamp: 1655018169.5156264 iteration: 12385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15759 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.23542 L1 loss: 0.0000e+00 L2 loss: 1.43558 Learning rate: 0.02 Mask loss: 0.13803 RPN box loss: 0.05542 RPN score loss: 0.0093 RPN total loss: 0.06472 Total loss: 1.87375 timestamp: 1655018172.8719277 iteration: 12390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15823 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.22888 L1 loss: 0.0000e+00 L2 loss: 1.43532 Learning rate: 0.02 Mask loss: 0.17443 RPN box loss: 0.01714 RPN score loss: 0.00705 RPN total loss: 0.02419 Total loss: 1.86281 timestamp: 1655018176.3124444 iteration: 12395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13965 FastRCNN class loss: 0.06047 FastRCNN total loss: 0.20012 L1 loss: 0.0000e+00 L2 loss: 1.43506 Learning rate: 0.02 Mask loss: 0.12452 RPN box loss: 0.09255 RPN score loss: 0.00473 RPN total loss: 0.09728 Total loss: 1.85698 timestamp: 1655018179.634469 iteration: 12400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18607 FastRCNN class loss: 0.09082 FastRCNN total loss: 0.27689 L1 loss: 0.0000e+00 L2 loss: 1.43481 Learning rate: 0.02 Mask loss: 0.1413 RPN box loss: 0.0619 RPN score loss: 0.01132 RPN total loss: 0.07321 Total loss: 1.92621 timestamp: 1655018183.088998 iteration: 12405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19507 FastRCNN class loss: 0.12848 FastRCNN total loss: 0.32356 L1 loss: 0.0000e+00 L2 loss: 1.43456 Learning rate: 0.02 Mask loss: 0.22262 RPN box loss: 0.01861 RPN score loss: 0.00952 RPN total loss: 0.02813 Total loss: 2.00887 timestamp: 1655018186.3563368 iteration: 12410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20463 FastRCNN class loss: 0.112 FastRCNN total loss: 0.31663 L1 loss: 0.0000e+00 L2 loss: 1.43431 Learning rate: 0.02 Mask loss: 0.22721 RPN box loss: 0.08101 RPN score loss: 0.0074 RPN total loss: 0.08841 Total loss: 2.06656 timestamp: 1655018189.6904664 iteration: 12415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14824 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.20678 L1 loss: 0.0000e+00 L2 loss: 1.43404 Learning rate: 0.02 Mask loss: 0.14082 RPN box loss: 0.04929 RPN score loss: 0.01183 RPN total loss: 0.06112 Total loss: 1.84277 timestamp: 1655018193.0063732 iteration: 12420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18964 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.27818 L1 loss: 0.0000e+00 L2 loss: 1.43379 Learning rate: 0.02 Mask loss: 0.20399 RPN box loss: 0.03925 RPN score loss: 0.02741 RPN total loss: 0.06666 Total loss: 1.98262 timestamp: 1655018196.3582582 iteration: 12425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15907 FastRCNN class loss: 0.12634 FastRCNN total loss: 0.28542 L1 loss: 0.0000e+00 L2 loss: 1.43353 Learning rate: 0.02 Mask loss: 0.23752 RPN box loss: 0.09319 RPN score loss: 0.01774 RPN total loss: 0.11094 Total loss: 2.0674 timestamp: 1655018199.623059 iteration: 12430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.08361 FastRCNN total loss: 0.25721 L1 loss: 0.0000e+00 L2 loss: 1.43327 Learning rate: 0.02 Mask loss: 0.16038 RPN box loss: 0.05547 RPN score loss: 0.00665 RPN total loss: 0.06212 Total loss: 1.91298 timestamp: 1655018202.8969052 iteration: 12435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15675 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.21884 L1 loss: 0.0000e+00 L2 loss: 1.43301 Learning rate: 0.02 Mask loss: 0.12023 RPN box loss: 0.01052 RPN score loss: 0.00369 RPN total loss: 0.01421 Total loss: 1.7863 timestamp: 1655018206.2617178 iteration: 12440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18311 FastRCNN class loss: 0.10347 FastRCNN total loss: 0.28658 L1 loss: 0.0000e+00 L2 loss: 1.43275 Learning rate: 0.02 Mask loss: 0.29316 RPN box loss: 0.12085 RPN score loss: 0.00839 RPN total loss: 0.12924 Total loss: 2.14172 timestamp: 1655018209.449335 iteration: 12445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26481 FastRCNN class loss: 0.10245 FastRCNN total loss: 0.36725 L1 loss: 0.0000e+00 L2 loss: 1.43249 Learning rate: 0.02 Mask loss: 0.25414 RPN box loss: 0.07684 RPN score loss: 0.00714 RPN total loss: 0.08399 Total loss: 2.13786 timestamp: 1655018212.9203033 iteration: 12450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14736 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.23348 L1 loss: 0.0000e+00 L2 loss: 1.43224 Learning rate: 0.02 Mask loss: 0.19183 RPN box loss: 0.06131 RPN score loss: 0.03008 RPN total loss: 0.0914 Total loss: 1.94895 timestamp: 1655018216.1687355 iteration: 12455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14369 FastRCNN class loss: 0.079 FastRCNN total loss: 0.22268 L1 loss: 0.0000e+00 L2 loss: 1.43197 Learning rate: 0.02 Mask loss: 0.23621 RPN box loss: 0.01482 RPN score loss: 0.00923 RPN total loss: 0.02405 Total loss: 1.91492 timestamp: 1655018219.6025262 iteration: 12460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18993 FastRCNN class loss: 0.12398 FastRCNN total loss: 0.31391 L1 loss: 0.0000e+00 L2 loss: 1.43171 Learning rate: 0.02 Mask loss: 0.22764 RPN box loss: 0.02992 RPN score loss: 0.00794 RPN total loss: 0.03786 Total loss: 2.01112 timestamp: 1655018222.9003744 iteration: 12465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18654 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.26106 L1 loss: 0.0000e+00 L2 loss: 1.43145 Learning rate: 0.02 Mask loss: 0.15478 RPN box loss: 0.03745 RPN score loss: 0.00721 RPN total loss: 0.04467 Total loss: 1.89196 timestamp: 1655018226.2781992 iteration: 12470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12721 FastRCNN class loss: 0.09717 FastRCNN total loss: 0.22438 L1 loss: 0.0000e+00 L2 loss: 1.43121 Learning rate: 0.02 Mask loss: 0.15959 RPN box loss: 0.02862 RPN score loss: 0.00966 RPN total loss: 0.03828 Total loss: 1.85346 timestamp: 1655018229.496092 iteration: 12475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17438 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.24743 L1 loss: 0.0000e+00 L2 loss: 1.43096 Learning rate: 0.02 Mask loss: 0.19206 RPN box loss: 0.03604 RPN score loss: 0.00513 RPN total loss: 0.04117 Total loss: 1.91161 timestamp: 1655018232.7581315 iteration: 12480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18429 FastRCNN class loss: 0.14188 FastRCNN total loss: 0.32616 L1 loss: 0.0000e+00 L2 loss: 1.43068 Learning rate: 0.02 Mask loss: 0.20351 RPN box loss: 0.04936 RPN score loss: 0.01027 RPN total loss: 0.05963 Total loss: 2.01998 timestamp: 1655018236.1606016 iteration: 12485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10705 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 1.43044 Learning rate: 0.02 Mask loss: 0.13357 RPN box loss: 0.06753 RPN score loss: 0.00514 RPN total loss: 0.07266 Total loss: 1.82435 timestamp: 1655018239.4200354 iteration: 12490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17068 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.25948 L1 loss: 0.0000e+00 L2 loss: 1.43017 Learning rate: 0.02 Mask loss: 0.11814 RPN box loss: 0.0217 RPN score loss: 0.00819 RPN total loss: 0.02989 Total loss: 1.83768 timestamp: 1655018242.8512247 iteration: 12495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12904 FastRCNN class loss: 0.07287 FastRCNN total loss: 0.20191 L1 loss: 0.0000e+00 L2 loss: 1.42992 Learning rate: 0.02 Mask loss: 0.12664 RPN box loss: 0.01656 RPN score loss: 0.00594 RPN total loss: 0.02251 Total loss: 1.78098 timestamp: 1655018246.1573546 iteration: 12500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13994 FastRCNN class loss: 0.11811 FastRCNN total loss: 0.25805 L1 loss: 0.0000e+00 L2 loss: 1.42966 Learning rate: 0.02 Mask loss: 0.12708 RPN box loss: 0.05895 RPN score loss: 0.00774 RPN total loss: 0.06669 Total loss: 1.88149 timestamp: 1655018249.5253153 iteration: 12505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18842 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.25896 L1 loss: 0.0000e+00 L2 loss: 1.42941 Learning rate: 0.02 Mask loss: 0.15461 RPN box loss: 0.04335 RPN score loss: 0.00649 RPN total loss: 0.04984 Total loss: 1.89282 timestamp: 1655018252.8215225 iteration: 12510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.2356 L1 loss: 0.0000e+00 L2 loss: 1.42914 Learning rate: 0.02 Mask loss: 0.17941 RPN box loss: 0.05071 RPN score loss: 0.00474 RPN total loss: 0.05545 Total loss: 1.89961 timestamp: 1655018256.133321 iteration: 12515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19286 FastRCNN class loss: 0.11693 FastRCNN total loss: 0.30978 L1 loss: 0.0000e+00 L2 loss: 1.42889 Learning rate: 0.02 Mask loss: 0.24518 RPN box loss: 0.06636 RPN score loss: 0.02084 RPN total loss: 0.0872 Total loss: 2.07104 timestamp: 1655018259.5219238 iteration: 12520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12936 FastRCNN class loss: 0.08774 FastRCNN total loss: 0.2171 L1 loss: 0.0000e+00 L2 loss: 1.42862 Learning rate: 0.02 Mask loss: 0.20921 RPN box loss: 0.06515 RPN score loss: 0.01569 RPN total loss: 0.08084 Total loss: 1.93576 timestamp: 1655018262.8935184 iteration: 12525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13369 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.2036 L1 loss: 0.0000e+00 L2 loss: 1.42837 Learning rate: 0.02 Mask loss: 0.2061 RPN box loss: 0.07596 RPN score loss: 0.01869 RPN total loss: 0.09465 Total loss: 1.93272 timestamp: 1655018266.2961295 iteration: 12530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1387 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.21556 L1 loss: 0.0000e+00 L2 loss: 1.42812 Learning rate: 0.02 Mask loss: 0.2347 RPN box loss: 0.02017 RPN score loss: 0.00577 RPN total loss: 0.02594 Total loss: 1.90431 timestamp: 1655018269.6345196 iteration: 12535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21663 FastRCNN class loss: 0.07857 FastRCNN total loss: 0.2952 L1 loss: 0.0000e+00 L2 loss: 1.42786 Learning rate: 0.02 Mask loss: 0.17489 RPN box loss: 0.02786 RPN score loss: 0.01531 RPN total loss: 0.04317 Total loss: 1.94112 timestamp: 1655018273.079996 iteration: 12540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14288 FastRCNN class loss: 0.11875 FastRCNN total loss: 0.26164 L1 loss: 0.0000e+00 L2 loss: 1.42761 Learning rate: 0.02 Mask loss: 0.276 RPN box loss: 0.05325 RPN score loss: 0.00895 RPN total loss: 0.0622 Total loss: 2.02745 timestamp: 1655018276.3558629 iteration: 12545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12833 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.17547 L1 loss: 0.0000e+00 L2 loss: 1.42733 Learning rate: 0.02 Mask loss: 0.18336 RPN box loss: 0.08931 RPN score loss: 0.00749 RPN total loss: 0.09681 Total loss: 1.88297 timestamp: 1655018279.7160368 iteration: 12550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18475 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.26839 L1 loss: 0.0000e+00 L2 loss: 1.42707 Learning rate: 0.02 Mask loss: 0.22478 RPN box loss: 0.0178 RPN score loss: 0.00453 RPN total loss: 0.02233 Total loss: 1.94257 timestamp: 1655018283.0303025 iteration: 12555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19304 FastRCNN class loss: 0.08432 FastRCNN total loss: 0.27736 L1 loss: 0.0000e+00 L2 loss: 1.42679 Learning rate: 0.02 Mask loss: 0.26957 RPN box loss: 0.14176 RPN score loss: 0.00728 RPN total loss: 0.14904 Total loss: 2.12276 timestamp: 1655018286.3711238 iteration: 12560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15929 FastRCNN class loss: 0.16408 FastRCNN total loss: 0.32337 L1 loss: 0.0000e+00 L2 loss: 1.42652 Learning rate: 0.02 Mask loss: 0.20429 RPN box loss: 0.05841 RPN score loss: 0.01882 RPN total loss: 0.07723 Total loss: 2.03141 timestamp: 1655018289.693825 iteration: 12565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16509 FastRCNN class loss: 0.10811 FastRCNN total loss: 0.2732 L1 loss: 0.0000e+00 L2 loss: 1.42628 Learning rate: 0.02 Mask loss: 0.1718 RPN box loss: 0.08452 RPN score loss: 0.00951 RPN total loss: 0.09404 Total loss: 1.96531 timestamp: 1655018293.0832443 iteration: 12570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15949 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.22978 L1 loss: 0.0000e+00 L2 loss: 1.42601 Learning rate: 0.02 Mask loss: 0.13645 RPN box loss: 0.02163 RPN score loss: 0.00157 RPN total loss: 0.0232 Total loss: 1.81544 timestamp: 1655018296.4706202 iteration: 12575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15466 FastRCNN class loss: 0.12776 FastRCNN total loss: 0.28242 L1 loss: 0.0000e+00 L2 loss: 1.42576 Learning rate: 0.02 Mask loss: 0.2714 RPN box loss: 0.02658 RPN score loss: 0.00877 RPN total loss: 0.03535 Total loss: 2.01492 timestamp: 1655018299.7592087 iteration: 12580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21682 FastRCNN class loss: 0.14225 FastRCNN total loss: 0.35906 L1 loss: 0.0000e+00 L2 loss: 1.4255 Learning rate: 0.02 Mask loss: 0.22004 RPN box loss: 0.09051 RPN score loss: 0.01992 RPN total loss: 0.11042 Total loss: 2.11503 timestamp: 1655018303.1752489 iteration: 12585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13035 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.19276 L1 loss: 0.0000e+00 L2 loss: 1.42524 Learning rate: 0.02 Mask loss: 0.20945 RPN box loss: 0.03419 RPN score loss: 0.00481 RPN total loss: 0.039 Total loss: 1.86644 timestamp: 1655018306.449828 iteration: 12590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17425 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.24784 L1 loss: 0.0000e+00 L2 loss: 1.42498 Learning rate: 0.02 Mask loss: 0.12269 RPN box loss: 0.02276 RPN score loss: 0.00433 RPN total loss: 0.0271 Total loss: 1.82261 timestamp: 1655018309.8840818 iteration: 12595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23109 FastRCNN class loss: 0.12669 FastRCNN total loss: 0.35778 L1 loss: 0.0000e+00 L2 loss: 1.42474 Learning rate: 0.02 Mask loss: 0.2111 RPN box loss: 0.10257 RPN score loss: 0.01727 RPN total loss: 0.11984 Total loss: 2.11345 timestamp: 1655018313.1893368 iteration: 12600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14546 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.22526 L1 loss: 0.0000e+00 L2 loss: 1.42448 Learning rate: 0.02 Mask loss: 0.18063 RPN box loss: 0.05063 RPN score loss: 0.00795 RPN total loss: 0.05858 Total loss: 1.88894 timestamp: 1655018316.4882152 iteration: 12605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12826 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.18977 L1 loss: 0.0000e+00 L2 loss: 1.42424 Learning rate: 0.02 Mask loss: 0.19509 RPN box loss: 0.00739 RPN score loss: 0.00564 RPN total loss: 0.01303 Total loss: 1.82213 timestamp: 1655018319.7921736 iteration: 12610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12524 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.20406 L1 loss: 0.0000e+00 L2 loss: 1.42399 Learning rate: 0.02 Mask loss: 0.12663 RPN box loss: 0.02724 RPN score loss: 0.00359 RPN total loss: 0.03083 Total loss: 1.78551 timestamp: 1655018323.2687309 iteration: 12615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16623 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.25689 L1 loss: 0.0000e+00 L2 loss: 1.42371 Learning rate: 0.02 Mask loss: 0.2383 RPN box loss: 0.03336 RPN score loss: 0.01745 RPN total loss: 0.05081 Total loss: 1.9697 timestamp: 1655018326.6628203 iteration: 12620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18727 FastRCNN class loss: 0.10318 FastRCNN total loss: 0.29045 L1 loss: 0.0000e+00 L2 loss: 1.42345 Learning rate: 0.02 Mask loss: 0.33633 RPN box loss: 0.01596 RPN score loss: 0.00304 RPN total loss: 0.01899 Total loss: 2.06922 timestamp: 1655018329.9665258 iteration: 12625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13008 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.19235 L1 loss: 0.0000e+00 L2 loss: 1.4232 Learning rate: 0.02 Mask loss: 0.14906 RPN box loss: 0.04787 RPN score loss: 0.00683 RPN total loss: 0.0547 Total loss: 1.81931 timestamp: 1655018333.3256285 iteration: 12630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14332 FastRCNN class loss: 0.10821 FastRCNN total loss: 0.25153 L1 loss: 0.0000e+00 L2 loss: 1.42296 Learning rate: 0.02 Mask loss: 0.17805 RPN box loss: 0.05868 RPN score loss: 0.00707 RPN total loss: 0.06575 Total loss: 1.91829 timestamp: 1655018336.6275465 iteration: 12635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10318 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.17171 L1 loss: 0.0000e+00 L2 loss: 1.42271 Learning rate: 0.02 Mask loss: 0.12175 RPN box loss: 0.01112 RPN score loss: 0.0047 RPN total loss: 0.01583 Total loss: 1.73199 timestamp: 1655018339.9895701 iteration: 12640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23586 FastRCNN class loss: 0.08754 FastRCNN total loss: 0.3234 L1 loss: 0.0000e+00 L2 loss: 1.42245 Learning rate: 0.02 Mask loss: 0.20743 RPN box loss: 0.03397 RPN score loss: 0.00841 RPN total loss: 0.04238 Total loss: 1.99566 timestamp: 1655018343.3428023 iteration: 12645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11071 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.1609 L1 loss: 0.0000e+00 L2 loss: 1.4222 Learning rate: 0.02 Mask loss: 0.10938 RPN box loss: 0.04625 RPN score loss: 0.00994 RPN total loss: 0.05619 Total loss: 1.74866 timestamp: 1655018346.6577828 iteration: 12650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17042 FastRCNN class loss: 0.07367 FastRCNN total loss: 0.24409 L1 loss: 0.0000e+00 L2 loss: 1.42195 Learning rate: 0.02 Mask loss: 0.14614 RPN box loss: 0.0116 RPN score loss: 0.00771 RPN total loss: 0.01931 Total loss: 1.83149 timestamp: 1655018349.9822078 iteration: 12655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15535 FastRCNN class loss: 0.09279 FastRCNN total loss: 0.24814 L1 loss: 0.0000e+00 L2 loss: 1.4217 Learning rate: 0.02 Mask loss: 0.19563 RPN box loss: 0.01575 RPN score loss: 0.00793 RPN total loss: 0.02368 Total loss: 1.88916 timestamp: 1655018353.3363872 iteration: 12660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24385 FastRCNN class loss: 0.10427 FastRCNN total loss: 0.34812 L1 loss: 0.0000e+00 L2 loss: 1.42144 Learning rate: 0.02 Mask loss: 0.22543 RPN box loss: 0.01691 RPN score loss: 0.00496 RPN total loss: 0.02187 Total loss: 2.01686 timestamp: 1655018356.8382492 iteration: 12665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17532 FastRCNN class loss: 0.11742 FastRCNN total loss: 0.29275 L1 loss: 0.0000e+00 L2 loss: 1.42118 Learning rate: 0.02 Mask loss: 0.20456 RPN box loss: 0.05171 RPN score loss: 0.01302 RPN total loss: 0.06473 Total loss: 1.98322 timestamp: 1655018360.055878 iteration: 12670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15353 FastRCNN class loss: 0.0752 FastRCNN total loss: 0.22873 L1 loss: 0.0000e+00 L2 loss: 1.42091 Learning rate: 0.02 Mask loss: 0.17465 RPN box loss: 0.07136 RPN score loss: 0.00837 RPN total loss: 0.07973 Total loss: 1.90403 timestamp: 1655018363.3896408 iteration: 12675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16226 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.23676 L1 loss: 0.0000e+00 L2 loss: 1.42065 Learning rate: 0.02 Mask loss: 0.18897 RPN box loss: 0.01706 RPN score loss: 0.00528 RPN total loss: 0.02234 Total loss: 1.86872 timestamp: 1655018366.769509 iteration: 12680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16711 FastRCNN class loss: 0.0967 FastRCNN total loss: 0.2638 L1 loss: 0.0000e+00 L2 loss: 1.42039 Learning rate: 0.02 Mask loss: 0.22886 RPN box loss: 0.05308 RPN score loss: 0.00883 RPN total loss: 0.06191 Total loss: 1.97497 timestamp: 1655018370.1508527 iteration: 12685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09669 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.18713 L1 loss: 0.0000e+00 L2 loss: 1.42015 Learning rate: 0.02 Mask loss: 0.2048 RPN box loss: 0.05773 RPN score loss: 0.00809 RPN total loss: 0.06582 Total loss: 1.8779 timestamp: 1655018373.4266295 iteration: 12690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17161 FastRCNN class loss: 0.17075 FastRCNN total loss: 0.34236 L1 loss: 0.0000e+00 L2 loss: 1.4199 Learning rate: 0.02 Mask loss: 0.21786 RPN box loss: 0.07688 RPN score loss: 0.01588 RPN total loss: 0.09276 Total loss: 2.07288 timestamp: 1655018376.780013 iteration: 12695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07863 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.13724 L1 loss: 0.0000e+00 L2 loss: 1.41964 Learning rate: 0.02 Mask loss: 0.17701 RPN box loss: 0.0401 RPN score loss: 0.00762 RPN total loss: 0.04772 Total loss: 1.7816 timestamp: 1655018380.1684566 iteration: 12700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15702 FastRCNN class loss: 0.07888 FastRCNN total loss: 0.2359 L1 loss: 0.0000e+00 L2 loss: 1.41935 Learning rate: 0.02 Mask loss: 0.19513 RPN box loss: 0.08242 RPN score loss: 0.00496 RPN total loss: 0.08737 Total loss: 1.93775 timestamp: 1655018383.5837612 iteration: 12705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18023 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.26684 L1 loss: 0.0000e+00 L2 loss: 1.4191 Learning rate: 0.02 Mask loss: 0.2151 RPN box loss: 0.07799 RPN score loss: 0.02003 RPN total loss: 0.09803 Total loss: 1.99907 timestamp: 1655018386.9069855 iteration: 12710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11888 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.18236 L1 loss: 0.0000e+00 L2 loss: 1.41885 Learning rate: 0.02 Mask loss: 0.16354 RPN box loss: 0.02524 RPN score loss: 0.00568 RPN total loss: 0.03092 Total loss: 1.79566 timestamp: 1655018390.108911 iteration: 12715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16269 FastRCNN class loss: 0.1252 FastRCNN total loss: 0.28789 L1 loss: 0.0000e+00 L2 loss: 1.41859 Learning rate: 0.02 Mask loss: 0.12966 RPN box loss: 0.0442 RPN score loss: 0.0102 RPN total loss: 0.0544 Total loss: 1.89054 timestamp: 1655018393.4612947 iteration: 12720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15918 FastRCNN class loss: 0.11821 FastRCNN total loss: 0.27739 L1 loss: 0.0000e+00 L2 loss: 1.41834 Learning rate: 0.02 Mask loss: 0.2041 RPN box loss: 0.05668 RPN score loss: 0.02312 RPN total loss: 0.0798 Total loss: 1.97963 timestamp: 1655018396.7684429 iteration: 12725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.23682 L1 loss: 0.0000e+00 L2 loss: 1.4181 Learning rate: 0.02 Mask loss: 0.19009 RPN box loss: 0.03742 RPN score loss: 0.00934 RPN total loss: 0.04676 Total loss: 1.89177 timestamp: 1655018400.177699 iteration: 12730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18412 FastRCNN class loss: 0.06284 FastRCNN total loss: 0.24696 L1 loss: 0.0000e+00 L2 loss: 1.41785 Learning rate: 0.02 Mask loss: 0.11949 RPN box loss: 0.05029 RPN score loss: 0.01022 RPN total loss: 0.06051 Total loss: 1.84481 timestamp: 1655018403.5421932 iteration: 12735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15186 FastRCNN class loss: 0.09863 FastRCNN total loss: 0.2505 L1 loss: 0.0000e+00 L2 loss: 1.4176 Learning rate: 0.02 Mask loss: 0.19494 RPN box loss: 0.02377 RPN score loss: 0.00634 RPN total loss: 0.03011 Total loss: 1.89315 timestamp: 1655018407.0423002 iteration: 12740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23008 FastRCNN class loss: 0.10734 FastRCNN total loss: 0.33742 L1 loss: 0.0000e+00 L2 loss: 1.41735 Learning rate: 0.02 Mask loss: 0.19369 RPN box loss: 0.0801 RPN score loss: 0.00384 RPN total loss: 0.08394 Total loss: 2.03239 timestamp: 1655018410.4015884 iteration: 12745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24835 FastRCNN class loss: 0.15136 FastRCNN total loss: 0.39971 L1 loss: 0.0000e+00 L2 loss: 1.41708 Learning rate: 0.02 Mask loss: 0.20669 RPN box loss: 0.12472 RPN score loss: 0.00885 RPN total loss: 0.13357 Total loss: 2.15705 timestamp: 1655018413.8006136 iteration: 12750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21118 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.30263 L1 loss: 0.0000e+00 L2 loss: 1.41682 Learning rate: 0.02 Mask loss: 0.15845 RPN box loss: 0.08004 RPN score loss: 0.00403 RPN total loss: 0.08407 Total loss: 1.96196 timestamp: 1655018417.089843 iteration: 12755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22404 FastRCNN class loss: 0.0836 FastRCNN total loss: 0.30764 L1 loss: 0.0000e+00 L2 loss: 1.41658 Learning rate: 0.02 Mask loss: 0.23823 RPN box loss: 0.04681 RPN score loss: 0.018 RPN total loss: 0.06481 Total loss: 2.02725 timestamp: 1655018420.473992 iteration: 12760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1787 FastRCNN class loss: 0.13039 FastRCNN total loss: 0.30909 L1 loss: 0.0000e+00 L2 loss: 1.41633 Learning rate: 0.02 Mask loss: 0.16873 RPN box loss: 0.02732 RPN score loss: 0.01201 RPN total loss: 0.03932 Total loss: 1.93348 timestamp: 1655018423.9057524 iteration: 12765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19486 FastRCNN class loss: 0.08987 FastRCNN total loss: 0.28473 L1 loss: 0.0000e+00 L2 loss: 1.41608 Learning rate: 0.02 Mask loss: 0.22952 RPN box loss: 0.06133 RPN score loss: 0.0053 RPN total loss: 0.06663 Total loss: 1.99696 timestamp: 1655018427.1985915 iteration: 12770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09775 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.17328 L1 loss: 0.0000e+00 L2 loss: 1.41581 Learning rate: 0.02 Mask loss: 0.15031 RPN box loss: 0.05607 RPN score loss: 0.00524 RPN total loss: 0.0613 Total loss: 1.80069 timestamp: 1655018430.658425 iteration: 12775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18357 FastRCNN class loss: 0.15458 FastRCNN total loss: 0.33815 L1 loss: 0.0000e+00 L2 loss: 1.41556 Learning rate: 0.02 Mask loss: 0.21253 RPN box loss: 0.02759 RPN score loss: 0.01805 RPN total loss: 0.04565 Total loss: 2.01188 timestamp: 1655018433.995051 iteration: 12780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13758 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.20965 L1 loss: 0.0000e+00 L2 loss: 1.4153 Learning rate: 0.02 Mask loss: 0.13463 RPN box loss: 0.01484 RPN score loss: 0.00314 RPN total loss: 0.01798 Total loss: 1.77755 timestamp: 1655018437.3922746 iteration: 12785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14561 FastRCNN class loss: 0.07267 FastRCNN total loss: 0.21828 L1 loss: 0.0000e+00 L2 loss: 1.41503 Learning rate: 0.02 Mask loss: 0.19559 RPN box loss: 0.04539 RPN score loss: 0.00909 RPN total loss: 0.05449 Total loss: 1.88338 timestamp: 1655018440.8150847 iteration: 12790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13885 FastRCNN class loss: 0.07901 FastRCNN total loss: 0.21786 L1 loss: 0.0000e+00 L2 loss: 1.41478 Learning rate: 0.02 Mask loss: 0.19094 RPN box loss: 0.02349 RPN score loss: 0.00345 RPN total loss: 0.02694 Total loss: 1.85052 timestamp: 1655018444.1339734 iteration: 12795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14772 FastRCNN class loss: 0.04433 FastRCNN total loss: 0.19205 L1 loss: 0.0000e+00 L2 loss: 1.41451 Learning rate: 0.02 Mask loss: 0.16674 RPN box loss: 0.01474 RPN score loss: 0.00555 RPN total loss: 0.02029 Total loss: 1.79358 timestamp: 1655018447.5592177 iteration: 12800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18315 FastRCNN class loss: 0.12246 FastRCNN total loss: 0.30561 L1 loss: 0.0000e+00 L2 loss: 1.41427 Learning rate: 0.02 Mask loss: 0.22951 RPN box loss: 0.04161 RPN score loss: 0.00716 RPN total loss: 0.04877 Total loss: 1.99817 timestamp: 1655018450.8967197 iteration: 12805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12715 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.20875 L1 loss: 0.0000e+00 L2 loss: 1.41402 Learning rate: 0.02 Mask loss: 0.11518 RPN box loss: 0.01762 RPN score loss: 0.00224 RPN total loss: 0.01986 Total loss: 1.75781 timestamp: 1655018454.2988136 iteration: 12810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19197 FastRCNN class loss: 0.09305 FastRCNN total loss: 0.28502 L1 loss: 0.0000e+00 L2 loss: 1.41378 Learning rate: 0.02 Mask loss: 0.26733 RPN box loss: 0.07272 RPN score loss: 0.0069 RPN total loss: 0.07962 Total loss: 2.04574 timestamp: 1655018457.6124434 iteration: 12815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18986 FastRCNN class loss: 0.08944 FastRCNN total loss: 0.27929 L1 loss: 0.0000e+00 L2 loss: 1.41354 Learning rate: 0.02 Mask loss: 0.1732 RPN box loss: 0.01334 RPN score loss: 0.0032 RPN total loss: 0.01654 Total loss: 1.88257 timestamp: 1655018461.0481348 iteration: 12820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1533 FastRCNN class loss: 0.09258 FastRCNN total loss: 0.24588 L1 loss: 0.0000e+00 L2 loss: 1.41328 Learning rate: 0.02 Mask loss: 0.13574 RPN box loss: 0.03183 RPN score loss: 0.00594 RPN total loss: 0.03777 Total loss: 1.83268 timestamp: 1655018464.4092996 iteration: 12825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09295 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.17606 L1 loss: 0.0000e+00 L2 loss: 1.413 Learning rate: 0.02 Mask loss: 0.17805 RPN box loss: 0.04582 RPN score loss: 0.00752 RPN total loss: 0.05334 Total loss: 1.82045 timestamp: 1655018467.7425795 iteration: 12830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13709 FastRCNN class loss: 0.08954 FastRCNN total loss: 0.22663 L1 loss: 0.0000e+00 L2 loss: 1.41277 Learning rate: 0.02 Mask loss: 0.18687 RPN box loss: 0.04867 RPN score loss: 0.00789 RPN total loss: 0.05657 Total loss: 1.88283 timestamp: 1655018471.1343117 iteration: 12835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.09395 FastRCNN total loss: 0.25256 L1 loss: 0.0000e+00 L2 loss: 1.4125 Learning rate: 0.02 Mask loss: 0.12394 RPN box loss: 0.02995 RPN score loss: 0.00597 RPN total loss: 0.03592 Total loss: 1.82492 timestamp: 1655018474.4397328 iteration: 12840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27886 FastRCNN class loss: 0.16457 FastRCNN total loss: 0.44342 L1 loss: 0.0000e+00 L2 loss: 1.41225 Learning rate: 0.02 Mask loss: 0.24075 RPN box loss: 0.03877 RPN score loss: 0.04473 RPN total loss: 0.0835 Total loss: 2.17992 timestamp: 1655018477.8024747 iteration: 12845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.1915 L1 loss: 0.0000e+00 L2 loss: 1.41199 Learning rate: 0.02 Mask loss: 0.13244 RPN box loss: 0.05306 RPN score loss: 0.01006 RPN total loss: 0.06312 Total loss: 1.79906 timestamp: 1655018481.0757194 iteration: 12850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16861 FastRCNN class loss: 0.06199 FastRCNN total loss: 0.2306 L1 loss: 0.0000e+00 L2 loss: 1.41172 Learning rate: 0.02 Mask loss: 0.16024 RPN box loss: 0.01614 RPN score loss: 0.01068 RPN total loss: 0.02682 Total loss: 1.82939 timestamp: 1655018484.4742491 iteration: 12855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19298 FastRCNN class loss: 0.11109 FastRCNN total loss: 0.30408 L1 loss: 0.0000e+00 L2 loss: 1.41148 Learning rate: 0.02 Mask loss: 0.20431 RPN box loss: 0.05908 RPN score loss: 0.01912 RPN total loss: 0.0782 Total loss: 1.99808 timestamp: 1655018487.7365298 iteration: 12860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12319 FastRCNN class loss: 0.09272 FastRCNN total loss: 0.21591 L1 loss: 0.0000e+00 L2 loss: 1.41123 Learning rate: 0.02 Mask loss: 0.12612 RPN box loss: 0.03894 RPN score loss: 0.00449 RPN total loss: 0.04344 Total loss: 1.7967 timestamp: 1655018491.0099318 iteration: 12865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.18755 L1 loss: 0.0000e+00 L2 loss: 1.41098 Learning rate: 0.02 Mask loss: 0.20847 RPN box loss: 0.05177 RPN score loss: 0.00598 RPN total loss: 0.05774 Total loss: 1.86474 timestamp: 1655018494.3260155 iteration: 12870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21548 FastRCNN class loss: 0.07851 FastRCNN total loss: 0.294 L1 loss: 0.0000e+00 L2 loss: 1.41073 Learning rate: 0.02 Mask loss: 0.19236 RPN box loss: 0.04981 RPN score loss: 0.01592 RPN total loss: 0.06573 Total loss: 1.96282 timestamp: 1655018497.5750456 iteration: 12875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15822 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.23332 L1 loss: 0.0000e+00 L2 loss: 1.41045 Learning rate: 0.02 Mask loss: 0.13293 RPN box loss: 0.04014 RPN score loss: 0.0061 RPN total loss: 0.04624 Total loss: 1.82295 timestamp: 1655018500.887544 iteration: 12880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11714 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.17873 L1 loss: 0.0000e+00 L2 loss: 1.4102 Learning rate: 0.02 Mask loss: 0.16046 RPN box loss: 0.0112 RPN score loss: 0.00332 RPN total loss: 0.01452 Total loss: 1.7639 timestamp: 1655018504.1258993 iteration: 12885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1724 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.24641 L1 loss: 0.0000e+00 L2 loss: 1.40996 Learning rate: 0.02 Mask loss: 0.20216 RPN box loss: 0.02415 RPN score loss: 0.00784 RPN total loss: 0.03199 Total loss: 1.89052 timestamp: 1655018507.4779556 iteration: 12890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17751 FastRCNN class loss: 0.10869 FastRCNN total loss: 0.2862 L1 loss: 0.0000e+00 L2 loss: 1.40971 Learning rate: 0.02 Mask loss: 0.26876 RPN box loss: 0.02801 RPN score loss: 0.00828 RPN total loss: 0.03628 Total loss: 2.00095 timestamp: 1655018510.783839 iteration: 12895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11827 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.20488 L1 loss: 0.0000e+00 L2 loss: 1.40945 Learning rate: 0.02 Mask loss: 0.14476 RPN box loss: 0.11098 RPN score loss: 0.01289 RPN total loss: 0.12387 Total loss: 1.88296 timestamp: 1655018514.1708822 iteration: 12900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1597 FastRCNN class loss: 0.10058 FastRCNN total loss: 0.26028 L1 loss: 0.0000e+00 L2 loss: 1.40919 Learning rate: 0.02 Mask loss: 0.17898 RPN box loss: 0.07114 RPN score loss: 0.02255 RPN total loss: 0.09369 Total loss: 1.94214 timestamp: 1655018517.5068822 iteration: 12905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23835 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.32929 L1 loss: 0.0000e+00 L2 loss: 1.40893 Learning rate: 0.02 Mask loss: 0.1816 RPN box loss: 0.12597 RPN score loss: 0.00832 RPN total loss: 0.1343 Total loss: 2.05411 timestamp: 1655018520.8834856 iteration: 12910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22572 FastRCNN class loss: 0.11999 FastRCNN total loss: 0.34572 L1 loss: 0.0000e+00 L2 loss: 1.40869 Learning rate: 0.02 Mask loss: 0.23246 RPN box loss: 0.04793 RPN score loss: 0.01196 RPN total loss: 0.05989 Total loss: 2.04676 timestamp: 1655018524.2300596 iteration: 12915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10262 FastRCNN class loss: 0.0404 FastRCNN total loss: 0.14303 L1 loss: 0.0000e+00 L2 loss: 1.40845 Learning rate: 0.02 Mask loss: 0.11226 RPN box loss: 0.00947 RPN score loss: 0.00304 RPN total loss: 0.01251 Total loss: 1.67625 timestamp: 1655018527.5611205 iteration: 12920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17698 FastRCNN class loss: 0.10185 FastRCNN total loss: 0.27883 L1 loss: 0.0000e+00 L2 loss: 1.40818 Learning rate: 0.02 Mask loss: 0.21195 RPN box loss: 0.05888 RPN score loss: 0.0193 RPN total loss: 0.07818 Total loss: 1.97715 timestamp: 1655018530.9431198 iteration: 12925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27146 FastRCNN class loss: 0.10066 FastRCNN total loss: 0.37212 L1 loss: 0.0000e+00 L2 loss: 1.40792 Learning rate: 0.02 Mask loss: 0.33926 RPN box loss: 0.06857 RPN score loss: 0.00656 RPN total loss: 0.07513 Total loss: 2.19443 timestamp: 1655018534.1840007 iteration: 12930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16388 FastRCNN class loss: 0.10562 FastRCNN total loss: 0.26951 L1 loss: 0.0000e+00 L2 loss: 1.40769 Learning rate: 0.02 Mask loss: 0.23574 RPN box loss: 0.06277 RPN score loss: 0.0056 RPN total loss: 0.06838 Total loss: 1.98131 timestamp: 1655018537.6470718 iteration: 12935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18242 FastRCNN class loss: 0.13747 FastRCNN total loss: 0.31989 L1 loss: 0.0000e+00 L2 loss: 1.40742 Learning rate: 0.02 Mask loss: 0.15785 RPN box loss: 0.05671 RPN score loss: 0.00729 RPN total loss: 0.064 Total loss: 1.94916 timestamp: 1655018540.957072 iteration: 12940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10825 FastRCNN class loss: 0.05389 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 1.40715 Learning rate: 0.02 Mask loss: 0.29097 RPN box loss: 0.03251 RPN score loss: 0.00659 RPN total loss: 0.0391 Total loss: 1.89935 timestamp: 1655018544.3530629 iteration: 12945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17481 FastRCNN class loss: 0.10078 FastRCNN total loss: 0.27558 L1 loss: 0.0000e+00 L2 loss: 1.40688 Learning rate: 0.02 Mask loss: 0.19221 RPN box loss: 0.04023 RPN score loss: 0.02285 RPN total loss: 0.06308 Total loss: 1.93775 timestamp: 1655018547.6221483 iteration: 12950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15544 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.22963 L1 loss: 0.0000e+00 L2 loss: 1.40664 Learning rate: 0.02 Mask loss: 0.14705 RPN box loss: 0.03088 RPN score loss: 0.00699 RPN total loss: 0.03787 Total loss: 1.82119 timestamp: 1655018551.059154 iteration: 12955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14939 FastRCNN class loss: 0.11093 FastRCNN total loss: 0.26033 L1 loss: 0.0000e+00 L2 loss: 1.4064 Learning rate: 0.02 Mask loss: 0.18651 RPN box loss: 0.00932 RPN score loss: 0.0055 RPN total loss: 0.01482 Total loss: 1.86805 timestamp: 1655018554.4071016 iteration: 12960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12833 FastRCNN class loss: 0.09104 FastRCNN total loss: 0.21937 L1 loss: 0.0000e+00 L2 loss: 1.40615 Learning rate: 0.02 Mask loss: 0.15154 RPN box loss: 0.01771 RPN score loss: 0.00297 RPN total loss: 0.02068 Total loss: 1.79774 timestamp: 1655018557.7206142 iteration: 12965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21928 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.32208 L1 loss: 0.0000e+00 L2 loss: 1.40592 Learning rate: 0.02 Mask loss: 0.16619 RPN box loss: 0.05366 RPN score loss: 0.00904 RPN total loss: 0.0627 Total loss: 1.95689 timestamp: 1655018561.0711503 iteration: 12970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20905 FastRCNN class loss: 0.11953 FastRCNN total loss: 0.32858 L1 loss: 0.0000e+00 L2 loss: 1.40566 Learning rate: 0.02 Mask loss: 0.1953 RPN box loss: 0.03473 RPN score loss: 0.01349 RPN total loss: 0.04822 Total loss: 1.97775 timestamp: 1655018564.4309804 iteration: 12975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13492 FastRCNN class loss: 0.0457 FastRCNN total loss: 0.18062 L1 loss: 0.0000e+00 L2 loss: 1.40543 Learning rate: 0.02 Mask loss: 0.13596 RPN box loss: 0.01648 RPN score loss: 0.00402 RPN total loss: 0.0205 Total loss: 1.74252 timestamp: 1655018567.9216778 iteration: 12980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29956 FastRCNN class loss: 0.08795 FastRCNN total loss: 0.38751 L1 loss: 0.0000e+00 L2 loss: 1.40518 Learning rate: 0.02 Mask loss: 0.23196 RPN box loss: 0.01689 RPN score loss: 0.00488 RPN total loss: 0.02178 Total loss: 2.04643 timestamp: 1655018571.316908 iteration: 12985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1231 FastRCNN class loss: 0.09094 FastRCNN total loss: 0.21404 L1 loss: 0.0000e+00 L2 loss: 1.40493 Learning rate: 0.02 Mask loss: 0.19119 RPN box loss: 0.02591 RPN score loss: 0.00753 RPN total loss: 0.03344 Total loss: 1.8436 timestamp: 1655018574.7064502 iteration: 12990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22333 FastRCNN class loss: 0.08312 FastRCNN total loss: 0.30645 L1 loss: 0.0000e+00 L2 loss: 1.40467 Learning rate: 0.02 Mask loss: 0.16388 RPN box loss: 0.02027 RPN score loss: 0.00599 RPN total loss: 0.02625 Total loss: 1.90126 timestamp: 1655018577.9890196 iteration: 12995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.18827 L1 loss: 0.0000e+00 L2 loss: 1.40441 Learning rate: 0.02 Mask loss: 0.13254 RPN box loss: 0.086 RPN score loss: 0.00853 RPN total loss: 0.09453 Total loss: 1.81976 timestamp: 1655018581.3095217 iteration: 13000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16085 FastRCNN class loss: 0.11206 FastRCNN total loss: 0.27292 L1 loss: 0.0000e+00 L2 loss: 1.40419 Learning rate: 0.02 Mask loss: 0.1802 RPN box loss: 0.02892 RPN score loss: 0.01449 RPN total loss: 0.04342 Total loss: 1.90072 timestamp: 1655018584.6783524 iteration: 13005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.08896 FastRCNN total loss: 0.24106 L1 loss: 0.0000e+00 L2 loss: 1.40393 Learning rate: 0.02 Mask loss: 0.20825 RPN box loss: 0.01339 RPN score loss: 0.01145 RPN total loss: 0.02484 Total loss: 1.87809 timestamp: 1655018587.947973 iteration: 13010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18287 FastRCNN class loss: 0.17484 FastRCNN total loss: 0.35771 L1 loss: 0.0000e+00 L2 loss: 1.40368 Learning rate: 0.02 Mask loss: 0.30574 RPN box loss: 0.04091 RPN score loss: 0.01796 RPN total loss: 0.05887 Total loss: 2.126 timestamp: 1655018591.2614448 iteration: 13015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19919 FastRCNN class loss: 0.13026 FastRCNN total loss: 0.32945 L1 loss: 0.0000e+00 L2 loss: 1.40343 Learning rate: 0.02 Mask loss: 0.16383 RPN box loss: 0.05385 RPN score loss: 0.00962 RPN total loss: 0.06347 Total loss: 1.96018 timestamp: 1655018594.578836 iteration: 13020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0726 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.13082 L1 loss: 0.0000e+00 L2 loss: 1.40318 Learning rate: 0.02 Mask loss: 0.16252 RPN box loss: 0.01863 RPN score loss: 0.00973 RPN total loss: 0.02836 Total loss: 1.72489 timestamp: 1655018597.931236 iteration: 13025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22297 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.32372 L1 loss: 0.0000e+00 L2 loss: 1.40292 Learning rate: 0.02 Mask loss: 0.17734 RPN box loss: 0.02201 RPN score loss: 0.0042 RPN total loss: 0.02621 Total loss: 1.93019 timestamp: 1655018601.145609 iteration: 13030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12143 FastRCNN class loss: 0.08505 FastRCNN total loss: 0.20648 L1 loss: 0.0000e+00 L2 loss: 1.40268 Learning rate: 0.02 Mask loss: 0.20111 RPN box loss: 0.04706 RPN score loss: 0.01318 RPN total loss: 0.06025 Total loss: 1.87051 timestamp: 1655018604.851602 iteration: 13035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11554 FastRCNN class loss: 0.07735 FastRCNN total loss: 0.19289 L1 loss: 0.0000e+00 L2 loss: 1.40245 Learning rate: 0.02 Mask loss: 0.14916 RPN box loss: 0.00971 RPN score loss: 0.00322 RPN total loss: 0.01293 Total loss: 1.75744 timestamp: 1655018608.3435404 iteration: 13040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21362 FastRCNN class loss: 0.07899 FastRCNN total loss: 0.2926 L1 loss: 0.0000e+00 L2 loss: 1.40222 Learning rate: 0.02 Mask loss: 0.15949 RPN box loss: 0.06204 RPN score loss: 0.01021 RPN total loss: 0.07225 Total loss: 1.92656 timestamp: 1655018611.634149 iteration: 13045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30147 FastRCNN class loss: 0.08222 FastRCNN total loss: 0.38369 L1 loss: 0.0000e+00 L2 loss: 1.40194 Learning rate: 0.02 Mask loss: 0.19575 RPN box loss: 0.05431 RPN score loss: 0.01164 RPN total loss: 0.06595 Total loss: 2.04733 timestamp: 1655018615.1318667 iteration: 13050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18322 FastRCNN class loss: 0.11045 FastRCNN total loss: 0.29368 L1 loss: 0.0000e+00 L2 loss: 1.40168 Learning rate: 0.02 Mask loss: 0.20424 RPN box loss: 0.03538 RPN score loss: 0.01166 RPN total loss: 0.04704 Total loss: 1.94664 timestamp: 1655018618.3992531 iteration: 13055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14705 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.20553 L1 loss: 0.0000e+00 L2 loss: 1.40141 Learning rate: 0.02 Mask loss: 0.15816 RPN box loss: 0.04895 RPN score loss: 0.02534 RPN total loss: 0.07429 Total loss: 1.8394 timestamp: 1655018621.7521417 iteration: 13060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25235 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.33922 L1 loss: 0.0000e+00 L2 loss: 1.40114 Learning rate: 0.02 Mask loss: 0.16332 RPN box loss: 0.03062 RPN score loss: 0.01248 RPN total loss: 0.04309 Total loss: 1.94676 timestamp: 1655018625.0406265 iteration: 13065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14764 FastRCNN class loss: 0.09918 FastRCNN total loss: 0.24682 L1 loss: 0.0000e+00 L2 loss: 1.40089 Learning rate: 0.02 Mask loss: 0.17294 RPN box loss: 0.0353 RPN score loss: 0.00643 RPN total loss: 0.04173 Total loss: 1.86238 timestamp: 1655018628.4028661 iteration: 13070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21675 FastRCNN class loss: 0.09622 FastRCNN total loss: 0.31297 L1 loss: 0.0000e+00 L2 loss: 1.40063 Learning rate: 0.02 Mask loss: 0.1728 RPN box loss: 0.10708 RPN score loss: 0.01293 RPN total loss: 0.12001 Total loss: 2.00641 timestamp: 1655018631.6819243 iteration: 13075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12122 FastRCNN class loss: 0.0805 FastRCNN total loss: 0.20172 L1 loss: 0.0000e+00 L2 loss: 1.40041 Learning rate: 0.02 Mask loss: 0.18157 RPN box loss: 0.06094 RPN score loss: 0.00412 RPN total loss: 0.06506 Total loss: 1.84876 timestamp: 1655018635.1017606 iteration: 13080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15145 FastRCNN class loss: 0.05697 FastRCNN total loss: 0.20842 L1 loss: 0.0000e+00 L2 loss: 1.40019 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.05015 RPN score loss: 0.00479 RPN total loss: 0.05494 Total loss: 1.8209 timestamp: 1655018638.6804345 iteration: 13085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18582 FastRCNN class loss: 0.10769 FastRCNN total loss: 0.29352 L1 loss: 0.0000e+00 L2 loss: 1.39995 Learning rate: 0.02 Mask loss: 0.21434 RPN box loss: 0.04227 RPN score loss: 0.0066 RPN total loss: 0.04887 Total loss: 1.95667 timestamp: 1655018641.9786315 iteration: 13090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.15066 L1 loss: 0.0000e+00 L2 loss: 1.39968 Learning rate: 0.02 Mask loss: 0.15628 RPN box loss: 0.05556 RPN score loss: 0.0108 RPN total loss: 0.06636 Total loss: 1.77298 timestamp: 1655018645.468195 iteration: 13095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20946 FastRCNN class loss: 0.12902 FastRCNN total loss: 0.33848 L1 loss: 0.0000e+00 L2 loss: 1.39943 Learning rate: 0.02 Mask loss: 0.34195 RPN box loss: 0.02765 RPN score loss: 0.00891 RPN total loss: 0.03656 Total loss: 2.11642 timestamp: 1655018648.7579467 iteration: 13100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.10529 FastRCNN total loss: 0.22155 L1 loss: 0.0000e+00 L2 loss: 1.39917 Learning rate: 0.02 Mask loss: 0.19957 RPN box loss: 0.08243 RPN score loss: 0.02428 RPN total loss: 0.1067 Total loss: 1.92699 timestamp: 1655018652.0750954 iteration: 13105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16626 FastRCNN class loss: 0.11031 FastRCNN total loss: 0.27658 L1 loss: 0.0000e+00 L2 loss: 1.39891 Learning rate: 0.02 Mask loss: 0.19027 RPN box loss: 0.09316 RPN score loss: 0.01964 RPN total loss: 0.11281 Total loss: 1.97856 timestamp: 1655018655.316474 iteration: 13110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22434 FastRCNN class loss: 0.14092 FastRCNN total loss: 0.36526 L1 loss: 0.0000e+00 L2 loss: 1.39865 Learning rate: 0.02 Mask loss: 0.19041 RPN box loss: 0.05331 RPN score loss: 0.01062 RPN total loss: 0.06393 Total loss: 2.01825 timestamp: 1655018658.6510108 iteration: 13115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14217 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.21329 L1 loss: 0.0000e+00 L2 loss: 1.3984 Learning rate: 0.02 Mask loss: 0.15799 RPN box loss: 0.06282 RPN score loss: 0.00981 RPN total loss: 0.07263 Total loss: 1.84231 timestamp: 1655018661.9728296 iteration: 13120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21947 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.31107 L1 loss: 0.0000e+00 L2 loss: 1.39816 Learning rate: 0.02 Mask loss: 0.18186 RPN box loss: 0.02446 RPN score loss: 0.01091 RPN total loss: 0.03536 Total loss: 1.92645 timestamp: 1655018665.2818434 iteration: 13125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14017 FastRCNN class loss: 0.10205 FastRCNN total loss: 0.24222 L1 loss: 0.0000e+00 L2 loss: 1.3979 Learning rate: 0.02 Mask loss: 0.14738 RPN box loss: 0.03927 RPN score loss: 0.0077 RPN total loss: 0.04697 Total loss: 1.83448 timestamp: 1655018668.6209662 iteration: 13130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08034 FastRCNN class loss: 0.04473 FastRCNN total loss: 0.12507 L1 loss: 0.0000e+00 L2 loss: 1.39765 Learning rate: 0.02 Mask loss: 0.10967 RPN box loss: 0.03418 RPN score loss: 0.0045 RPN total loss: 0.03868 Total loss: 1.67108 timestamp: 1655018671.937334 iteration: 13135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13796 FastRCNN class loss: 0.06354 FastRCNN total loss: 0.20149 L1 loss: 0.0000e+00 L2 loss: 1.3974 Learning rate: 0.02 Mask loss: 0.23542 RPN box loss: 0.03672 RPN score loss: 0.01486 RPN total loss: 0.05158 Total loss: 1.88589 timestamp: 1655018675.3721502 iteration: 13140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14658 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.22817 L1 loss: 0.0000e+00 L2 loss: 1.39715 Learning rate: 0.02 Mask loss: 0.23095 RPN box loss: 0.06836 RPN score loss: 0.01832 RPN total loss: 0.08668 Total loss: 1.94296 timestamp: 1655018678.6090088 iteration: 13145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25286 FastRCNN class loss: 0.15796 FastRCNN total loss: 0.41082 L1 loss: 0.0000e+00 L2 loss: 1.3969 Learning rate: 0.02 Mask loss: 0.2743 RPN box loss: 0.04495 RPN score loss: 0.0119 RPN total loss: 0.05684 Total loss: 2.13887 timestamp: 1655018682.0500107 iteration: 13150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20884 FastRCNN class loss: 0.1311 FastRCNN total loss: 0.33993 L1 loss: 0.0000e+00 L2 loss: 1.39666 Learning rate: 0.02 Mask loss: 0.23047 RPN box loss: 0.05449 RPN score loss: 0.01298 RPN total loss: 0.06747 Total loss: 2.03453 timestamp: 1655018685.2991195 iteration: 13155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22645 FastRCNN class loss: 0.13959 FastRCNN total loss: 0.36604 L1 loss: 0.0000e+00 L2 loss: 1.39642 Learning rate: 0.02 Mask loss: 0.18466 RPN box loss: 0.06665 RPN score loss: 0.01071 RPN total loss: 0.07736 Total loss: 2.02447 timestamp: 1655018688.7180464 iteration: 13160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12179 FastRCNN class loss: 0.12651 FastRCNN total loss: 0.2483 L1 loss: 0.0000e+00 L2 loss: 1.39616 Learning rate: 0.02 Mask loss: 0.20054 RPN box loss: 0.06184 RPN score loss: 0.02468 RPN total loss: 0.08652 Total loss: 1.93152 timestamp: 1655018692.04673 iteration: 13165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17663 FastRCNN class loss: 0.08715 FastRCNN total loss: 0.26378 L1 loss: 0.0000e+00 L2 loss: 1.39591 Learning rate: 0.02 Mask loss: 0.18364 RPN box loss: 0.0564 RPN score loss: 0.0085 RPN total loss: 0.0649 Total loss: 1.90824 timestamp: 1655018695.330663 iteration: 13170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16834 FastRCNN class loss: 0.09118 FastRCNN total loss: 0.25952 L1 loss: 0.0000e+00 L2 loss: 1.39565 Learning rate: 0.02 Mask loss: 0.16226 RPN box loss: 0.10602 RPN score loss: 0.01201 RPN total loss: 0.11803 Total loss: 1.93546 timestamp: 1655018698.7400553 iteration: 13175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16557 FastRCNN class loss: 0.10811 FastRCNN total loss: 0.27368 L1 loss: 0.0000e+00 L2 loss: 1.3954 Learning rate: 0.02 Mask loss: 0.17863 RPN box loss: 0.05639 RPN score loss: 0.00978 RPN total loss: 0.06617 Total loss: 1.91388 timestamp: 1655018702.0275955 iteration: 13180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21446 FastRCNN class loss: 0.16246 FastRCNN total loss: 0.37692 L1 loss: 0.0000e+00 L2 loss: 1.39516 Learning rate: 0.02 Mask loss: 0.25674 RPN box loss: 0.0425 RPN score loss: 0.02126 RPN total loss: 0.06376 Total loss: 2.09257 timestamp: 1655018705.4542286 iteration: 13185 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12216 FastRCNN class loss: 0.13513 FastRCNN total loss: 0.25728 L1 loss: 0.0000e+00 L2 loss: 1.39491 Learning rate: 0.02 Mask loss: 0.18831 RPN box loss: 0.05919 RPN score loss: 0.01512 RPN total loss: 0.07431 Total loss: 1.91481 timestamp: 1655018708.6654363 iteration: 13190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19585 FastRCNN class loss: 0.15706 FastRCNN total loss: 0.35291 L1 loss: 0.0000e+00 L2 loss: 1.39466 Learning rate: 0.02 Mask loss: 0.23152 RPN box loss: 0.05632 RPN score loss: 0.04124 RPN total loss: 0.09756 Total loss: 2.07665 timestamp: 1655018712.0316842 iteration: 13195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16394 FastRCNN class loss: 0.11983 FastRCNN total loss: 0.28377 L1 loss: 0.0000e+00 L2 loss: 1.39441 Learning rate: 0.02 Mask loss: 0.18079 RPN box loss: 0.01127 RPN score loss: 0.00544 RPN total loss: 0.01671 Total loss: 1.87567 timestamp: 1655018715.3606575 iteration: 13200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18326 FastRCNN class loss: 0.09457 FastRCNN total loss: 0.27783 L1 loss: 0.0000e+00 L2 loss: 1.39417 Learning rate: 0.02 Mask loss: 0.21682 RPN box loss: 0.07092 RPN score loss: 0.01154 RPN total loss: 0.08246 Total loss: 1.97128 timestamp: 1655018718.7386024 iteration: 13205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21467 FastRCNN class loss: 0.09643 FastRCNN total loss: 0.31111 L1 loss: 0.0000e+00 L2 loss: 1.39393 Learning rate: 0.02 Mask loss: 0.23718 RPN box loss: 0.01928 RPN score loss: 0.00367 RPN total loss: 0.02295 Total loss: 1.96517 timestamp: 1655018722.0615172 iteration: 13210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14105 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.21806 L1 loss: 0.0000e+00 L2 loss: 1.39368 Learning rate: 0.02 Mask loss: 0.12566 RPN box loss: 0.01479 RPN score loss: 0.00234 RPN total loss: 0.01713 Total loss: 1.75454 timestamp: 1655018725.3724182 iteration: 13215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23186 FastRCNN class loss: 0.12482 FastRCNN total loss: 0.35669 L1 loss: 0.0000e+00 L2 loss: 1.39343 Learning rate: 0.02 Mask loss: 0.19122 RPN box loss: 0.0195 RPN score loss: 0.00728 RPN total loss: 0.02678 Total loss: 1.96812 timestamp: 1655018728.820631 iteration: 13220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22727 FastRCNN class loss: 0.13796 FastRCNN total loss: 0.36523 L1 loss: 0.0000e+00 L2 loss: 1.39318 Learning rate: 0.02 Mask loss: 0.27047 RPN box loss: 0.07239 RPN score loss: 0.01261 RPN total loss: 0.085 Total loss: 2.11388 timestamp: 1655018732.1339543 iteration: 13225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14886 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.2136 L1 loss: 0.0000e+00 L2 loss: 1.39293 Learning rate: 0.02 Mask loss: 0.17087 RPN box loss: 0.03165 RPN score loss: 0.0065 RPN total loss: 0.03815 Total loss: 1.81555 timestamp: 1655018735.5257185 iteration: 13230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16134 FastRCNN class loss: 0.084 FastRCNN total loss: 0.24534 L1 loss: 0.0000e+00 L2 loss: 1.3927 Learning rate: 0.02 Mask loss: 0.12441 RPN box loss: 0.02033 RPN score loss: 0.00536 RPN total loss: 0.02569 Total loss: 1.78814 timestamp: 1655018738.7904263 iteration: 13235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19724 FastRCNN class loss: 0.11703 FastRCNN total loss: 0.31427 L1 loss: 0.0000e+00 L2 loss: 1.39245 Learning rate: 0.02 Mask loss: 0.40376 RPN box loss: 0.05459 RPN score loss: 0.0106 RPN total loss: 0.06519 Total loss: 2.17567 timestamp: 1655018742.2317035 iteration: 13240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20877 FastRCNN class loss: 0.10989 FastRCNN total loss: 0.31866 L1 loss: 0.0000e+00 L2 loss: 1.39218 Learning rate: 0.02 Mask loss: 0.26773 RPN box loss: 0.0486 RPN score loss: 0.01455 RPN total loss: 0.06315 Total loss: 2.04173 timestamp: 1655018745.4680464 iteration: 13245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21045 FastRCNN class loss: 0.10595 FastRCNN total loss: 0.3164 L1 loss: 0.0000e+00 L2 loss: 1.39193 Learning rate: 0.02 Mask loss: 0.20643 RPN box loss: 0.03963 RPN score loss: 0.01651 RPN total loss: 0.05614 Total loss: 1.9709 timestamp: 1655018748.8965569 iteration: 13250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20549 FastRCNN class loss: 0.11769 FastRCNN total loss: 0.32318 L1 loss: 0.0000e+00 L2 loss: 1.39167 Learning rate: 0.02 Mask loss: 0.1833 RPN box loss: 0.03978 RPN score loss: 0.01293 RPN total loss: 0.05272 Total loss: 1.95086 timestamp: 1655018752.2188373 iteration: 13255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20186 FastRCNN class loss: 0.09254 FastRCNN total loss: 0.2944 L1 loss: 0.0000e+00 L2 loss: 1.3914 Learning rate: 0.02 Mask loss: 0.22795 RPN box loss: 0.04544 RPN score loss: 0.00784 RPN total loss: 0.05328 Total loss: 1.96703 timestamp: 1655018755.5209198 iteration: 13260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1431 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.24003 L1 loss: 0.0000e+00 L2 loss: 1.39116 Learning rate: 0.02 Mask loss: 0.12996 RPN box loss: 0.02539 RPN score loss: 0.00621 RPN total loss: 0.0316 Total loss: 1.79274 timestamp: 1655018758.9136868 iteration: 13265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.20135 L1 loss: 0.0000e+00 L2 loss: 1.39091 Learning rate: 0.02 Mask loss: 0.14043 RPN box loss: 0.04057 RPN score loss: 0.00945 RPN total loss: 0.05001 Total loss: 1.78271 timestamp: 1655018762.1366472 iteration: 13270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14778 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.25173 L1 loss: 0.0000e+00 L2 loss: 1.39066 Learning rate: 0.02 Mask loss: 0.21011 RPN box loss: 0.02455 RPN score loss: 0.01392 RPN total loss: 0.03847 Total loss: 1.89097 timestamp: 1655018765.540155 iteration: 13275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24325 FastRCNN class loss: 0.11893 FastRCNN total loss: 0.36218 L1 loss: 0.0000e+00 L2 loss: 1.39041 Learning rate: 0.02 Mask loss: 0.31471 RPN box loss: 0.04731 RPN score loss: 0.01453 RPN total loss: 0.06184 Total loss: 2.12915 timestamp: 1655018768.825389 iteration: 13280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13553 FastRCNN class loss: 0.07908 FastRCNN total loss: 0.21461 L1 loss: 0.0000e+00 L2 loss: 1.39015 Learning rate: 0.02 Mask loss: 0.11872 RPN box loss: 0.04674 RPN score loss: 0.00571 RPN total loss: 0.05245 Total loss: 1.77593 timestamp: 1655018772.2753024 iteration: 13285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09364 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 1.3899 Learning rate: 0.02 Mask loss: 0.1696 RPN box loss: 0.07696 RPN score loss: 0.01093 RPN total loss: 0.08788 Total loss: 1.82664 timestamp: 1655018775.6397035 iteration: 13290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12095 FastRCNN class loss: 0.08 FastRCNN total loss: 0.20095 L1 loss: 0.0000e+00 L2 loss: 1.38963 Learning rate: 0.02 Mask loss: 0.14292 RPN box loss: 0.05934 RPN score loss: 0.01481 RPN total loss: 0.07415 Total loss: 1.80765 timestamp: 1655018778.9602618 iteration: 13295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1864 FastRCNN class loss: 0.09481 FastRCNN total loss: 0.28121 L1 loss: 0.0000e+00 L2 loss: 1.38937 Learning rate: 0.02 Mask loss: 0.15989 RPN box loss: 0.03784 RPN score loss: 0.00747 RPN total loss: 0.04531 Total loss: 1.87578 timestamp: 1655018782.3427253 iteration: 13300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16847 FastRCNN class loss: 0.11294 FastRCNN total loss: 0.28142 L1 loss: 0.0000e+00 L2 loss: 1.38912 Learning rate: 0.02 Mask loss: 0.16411 RPN box loss: 0.04459 RPN score loss: 0.00805 RPN total loss: 0.05263 Total loss: 1.88729 timestamp: 1655018785.574846 iteration: 13305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21124 FastRCNN class loss: 0.13263 FastRCNN total loss: 0.34387 L1 loss: 0.0000e+00 L2 loss: 1.38889 Learning rate: 0.02 Mask loss: 0.19176 RPN box loss: 0.04232 RPN score loss: 0.01085 RPN total loss: 0.05317 Total loss: 1.97768 timestamp: 1655018789.0005484 iteration: 13310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17251 FastRCNN class loss: 0.1065 FastRCNN total loss: 0.27901 L1 loss: 0.0000e+00 L2 loss: 1.38866 Learning rate: 0.02 Mask loss: 0.30519 RPN box loss: 0.04878 RPN score loss: 0.01584 RPN total loss: 0.06461 Total loss: 2.03748 timestamp: 1655018792.294343 iteration: 13315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17944 FastRCNN class loss: 0.10692 FastRCNN total loss: 0.28636 L1 loss: 0.0000e+00 L2 loss: 1.3884 Learning rate: 0.02 Mask loss: 0.21189 RPN box loss: 0.02756 RPN score loss: 0.00505 RPN total loss: 0.03261 Total loss: 1.91927 timestamp: 1655018795.7431543 iteration: 13320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20443 FastRCNN class loss: 0.1227 FastRCNN total loss: 0.32713 L1 loss: 0.0000e+00 L2 loss: 1.38816 Learning rate: 0.02 Mask loss: 0.19221 RPN box loss: 0.00558 RPN score loss: 0.00822 RPN total loss: 0.0138 Total loss: 1.9213 timestamp: 1655018798.9803545 iteration: 13325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24865 FastRCNN class loss: 0.11459 FastRCNN total loss: 0.36324 L1 loss: 0.0000e+00 L2 loss: 1.38794 Learning rate: 0.02 Mask loss: 0.21233 RPN box loss: 0.00905 RPN score loss: 0.00312 RPN total loss: 0.01216 Total loss: 1.97567 timestamp: 1655018802.3104029 iteration: 13330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19588 FastRCNN class loss: 0.12594 FastRCNN total loss: 0.32182 L1 loss: 0.0000e+00 L2 loss: 1.38769 Learning rate: 0.02 Mask loss: 0.1789 RPN box loss: 0.04837 RPN score loss: 0.00705 RPN total loss: 0.05543 Total loss: 1.94383 timestamp: 1655018805.6109443 iteration: 13335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17353 FastRCNN class loss: 0.09084 FastRCNN total loss: 0.26437 L1 loss: 0.0000e+00 L2 loss: 1.38744 Learning rate: 0.02 Mask loss: 0.17082 RPN box loss: 0.02651 RPN score loss: 0.01151 RPN total loss: 0.03802 Total loss: 1.86066 timestamp: 1655018809.091606 iteration: 13340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13504 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.20423 L1 loss: 0.0000e+00 L2 loss: 1.38719 Learning rate: 0.02 Mask loss: 0.11838 RPN box loss: 0.02844 RPN score loss: 0.0117 RPN total loss: 0.04014 Total loss: 1.74995 timestamp: 1655018812.5001605 iteration: 13345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18056 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.2622 L1 loss: 0.0000e+00 L2 loss: 1.38696 Learning rate: 0.02 Mask loss: 0.1688 RPN box loss: 0.00786 RPN score loss: 0.00819 RPN total loss: 0.01605 Total loss: 1.83401 timestamp: 1655018815.8364453 iteration: 13350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26416 FastRCNN class loss: 0.12411 FastRCNN total loss: 0.38827 L1 loss: 0.0000e+00 L2 loss: 1.3867 Learning rate: 0.02 Mask loss: 0.2126 RPN box loss: 0.04191 RPN score loss: 0.01001 RPN total loss: 0.05192 Total loss: 2.03949 timestamp: 1655018819.28547 iteration: 13355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18297 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.26239 L1 loss: 0.0000e+00 L2 loss: 1.38645 Learning rate: 0.02 Mask loss: 0.25464 RPN box loss: 0.06538 RPN score loss: 0.01128 RPN total loss: 0.07666 Total loss: 1.98014 timestamp: 1655018822.6110978 iteration: 13360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16539 FastRCNN class loss: 0.09876 FastRCNN total loss: 0.26415 L1 loss: 0.0000e+00 L2 loss: 1.38621 Learning rate: 0.02 Mask loss: 0.15183 RPN box loss: 0.12122 RPN score loss: 0.01545 RPN total loss: 0.13667 Total loss: 1.93886 timestamp: 1655018826.0410018 iteration: 13365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14457 FastRCNN class loss: 0.12877 FastRCNN total loss: 0.27334 L1 loss: 0.0000e+00 L2 loss: 1.38595 Learning rate: 0.02 Mask loss: 0.22737 RPN box loss: 0.03581 RPN score loss: 0.0106 RPN total loss: 0.04641 Total loss: 1.93307 timestamp: 1655018829.29627 iteration: 13370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21451 FastRCNN class loss: 0.15089 FastRCNN total loss: 0.3654 L1 loss: 0.0000e+00 L2 loss: 1.38569 Learning rate: 0.02 Mask loss: 0.22557 RPN box loss: 0.05563 RPN score loss: 0.01028 RPN total loss: 0.06591 Total loss: 2.04256 timestamp: 1655018832.7170978 iteration: 13375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15811 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.2349 L1 loss: 0.0000e+00 L2 loss: 1.38546 Learning rate: 0.02 Mask loss: 0.12763 RPN box loss: 0.02797 RPN score loss: 0.00443 RPN total loss: 0.0324 Total loss: 1.78039 timestamp: 1655018836.1056447 iteration: 13380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1378 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.19638 L1 loss: 0.0000e+00 L2 loss: 1.38521 Learning rate: 0.02 Mask loss: 0.25565 RPN box loss: 0.0123 RPN score loss: 0.0051 RPN total loss: 0.0174 Total loss: 1.85464 timestamp: 1655018839.455321 iteration: 13385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.18573 L1 loss: 0.0000e+00 L2 loss: 1.38496 Learning rate: 0.02 Mask loss: 0.14333 RPN box loss: 0.02774 RPN score loss: 0.00828 RPN total loss: 0.03602 Total loss: 1.75004 timestamp: 1655018842.891499 iteration: 13390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19362 FastRCNN class loss: 0.11683 FastRCNN total loss: 0.31044 L1 loss: 0.0000e+00 L2 loss: 1.38472 Learning rate: 0.02 Mask loss: 0.16704 RPN box loss: 0.02739 RPN score loss: 0.0107 RPN total loss: 0.03809 Total loss: 1.9003 timestamp: 1655018846.1776245 iteration: 13395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24471 FastRCNN class loss: 0.12596 FastRCNN total loss: 0.37067 L1 loss: 0.0000e+00 L2 loss: 1.38448 Learning rate: 0.02 Mask loss: 0.29958 RPN box loss: 0.04349 RPN score loss: 0.00275 RPN total loss: 0.04624 Total loss: 2.10098 timestamp: 1655018849.5880632 iteration: 13400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.23285 L1 loss: 0.0000e+00 L2 loss: 1.38424 Learning rate: 0.02 Mask loss: 0.19437 RPN box loss: 0.01495 RPN score loss: 0.00408 RPN total loss: 0.01902 Total loss: 1.83049 timestamp: 1655018852.8600028 iteration: 13405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12492 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.20729 L1 loss: 0.0000e+00 L2 loss: 1.384 Learning rate: 0.02 Mask loss: 0.17045 RPN box loss: 0.06299 RPN score loss: 0.01028 RPN total loss: 0.07326 Total loss: 1.83501 timestamp: 1655018856.1917758 iteration: 13410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07627 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.13166 L1 loss: 0.0000e+00 L2 loss: 1.38375 Learning rate: 0.02 Mask loss: 0.20812 RPN box loss: 0.05681 RPN score loss: 0.00617 RPN total loss: 0.06298 Total loss: 1.78651 timestamp: 1655018859.453615 iteration: 13415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1733 FastRCNN class loss: 0.10967 FastRCNN total loss: 0.28297 L1 loss: 0.0000e+00 L2 loss: 1.38348 Learning rate: 0.02 Mask loss: 0.23762 RPN box loss: 0.02829 RPN score loss: 0.027 RPN total loss: 0.05529 Total loss: 1.95937 timestamp: 1655018862.8620474 iteration: 13420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19643 FastRCNN class loss: 0.11012 FastRCNN total loss: 0.30655 L1 loss: 0.0000e+00 L2 loss: 1.38323 Learning rate: 0.02 Mask loss: 0.26859 RPN box loss: 0.0291 RPN score loss: 0.00762 RPN total loss: 0.03672 Total loss: 1.99509 timestamp: 1655018866.2363584 iteration: 13425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22144 FastRCNN class loss: 0.13582 FastRCNN total loss: 0.35726 L1 loss: 0.0000e+00 L2 loss: 1.38297 Learning rate: 0.02 Mask loss: 0.22742 RPN box loss: 0.0367 RPN score loss: 0.01788 RPN total loss: 0.05458 Total loss: 2.02223 timestamp: 1655018869.5937555 iteration: 13430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12131 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.17596 L1 loss: 0.0000e+00 L2 loss: 1.38272 Learning rate: 0.02 Mask loss: 0.11987 RPN box loss: 0.05173 RPN score loss: 0.00673 RPN total loss: 0.05846 Total loss: 1.73702 timestamp: 1655018872.9230478 iteration: 13435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13793 FastRCNN class loss: 0.09573 FastRCNN total loss: 0.23365 L1 loss: 0.0000e+00 L2 loss: 1.38248 Learning rate: 0.02 Mask loss: 0.21354 RPN box loss: 0.07849 RPN score loss: 0.02199 RPN total loss: 0.10048 Total loss: 1.93015 timestamp: 1655018876.2513826 iteration: 13440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16017 FastRCNN class loss: 0.11299 FastRCNN total loss: 0.27316 L1 loss: 0.0000e+00 L2 loss: 1.38223 Learning rate: 0.02 Mask loss: 0.23932 RPN box loss: 0.03882 RPN score loss: 0.00496 RPN total loss: 0.04377 Total loss: 1.93849 timestamp: 1655018879.624891 iteration: 13445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1872 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.27097 L1 loss: 0.0000e+00 L2 loss: 1.38198 Learning rate: 0.02 Mask loss: 0.22584 RPN box loss: 0.01704 RPN score loss: 0.0059 RPN total loss: 0.02295 Total loss: 1.90175 timestamp: 1655018882.9689863 iteration: 13450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12629 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.18375 L1 loss: 0.0000e+00 L2 loss: 1.38174 Learning rate: 0.02 Mask loss: 0.1894 RPN box loss: 0.04993 RPN score loss: 0.00388 RPN total loss: 0.05381 Total loss: 1.8087 timestamp: 1655018886.3802352 iteration: 13455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14842 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.23744 L1 loss: 0.0000e+00 L2 loss: 1.3815 Learning rate: 0.02 Mask loss: 0.10661 RPN box loss: 0.02682 RPN score loss: 0.00423 RPN total loss: 0.03104 Total loss: 1.75658 timestamp: 1655018889.7003155 iteration: 13460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.24817 L1 loss: 0.0000e+00 L2 loss: 1.38126 Learning rate: 0.02 Mask loss: 0.17847 RPN box loss: 0.07857 RPN score loss: 0.01156 RPN total loss: 0.09013 Total loss: 1.89803 timestamp: 1655018893.0546684 iteration: 13465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19538 FastRCNN class loss: 0.10911 FastRCNN total loss: 0.30449 L1 loss: 0.0000e+00 L2 loss: 1.38102 Learning rate: 0.02 Mask loss: 0.25558 RPN box loss: 0.0594 RPN score loss: 0.01665 RPN total loss: 0.07605 Total loss: 2.01713 timestamp: 1655018896.5082774 iteration: 13470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18776 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.25913 L1 loss: 0.0000e+00 L2 loss: 1.38077 Learning rate: 0.02 Mask loss: 0.17921 RPN box loss: 0.02198 RPN score loss: 0.01072 RPN total loss: 0.03271 Total loss: 1.85182 timestamp: 1655018899.734715 iteration: 13475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18745 FastRCNN class loss: 0.13826 FastRCNN total loss: 0.3257 L1 loss: 0.0000e+00 L2 loss: 1.38052 Learning rate: 0.02 Mask loss: 0.24152 RPN box loss: 0.08452 RPN score loss: 0.00896 RPN total loss: 0.09348 Total loss: 2.04122 timestamp: 1655018903.2355003 iteration: 13480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24791 FastRCNN class loss: 0.12778 FastRCNN total loss: 0.37569 L1 loss: 0.0000e+00 L2 loss: 1.38027 Learning rate: 0.02 Mask loss: 0.15693 RPN box loss: 0.09277 RPN score loss: 0.01417 RPN total loss: 0.10693 Total loss: 2.01983 timestamp: 1655018906.4800293 iteration: 13485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17551 FastRCNN class loss: 0.11521 FastRCNN total loss: 0.29071 L1 loss: 0.0000e+00 L2 loss: 1.38003 Learning rate: 0.02 Mask loss: 0.1831 RPN box loss: 0.03249 RPN score loss: 0.02026 RPN total loss: 0.05275 Total loss: 1.90659 timestamp: 1655018909.8362422 iteration: 13490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17398 FastRCNN class loss: 0.10484 FastRCNN total loss: 0.27882 L1 loss: 0.0000e+00 L2 loss: 1.37978 Learning rate: 0.02 Mask loss: 0.18777 RPN box loss: 0.01006 RPN score loss: 0.00889 RPN total loss: 0.01895 Total loss: 1.86532 timestamp: 1655018913.1239953 iteration: 13495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16836 FastRCNN class loss: 0.08892 FastRCNN total loss: 0.25728 L1 loss: 0.0000e+00 L2 loss: 1.37954 Learning rate: 0.02 Mask loss: 0.17999 RPN box loss: 0.02377 RPN score loss: 0.00571 RPN total loss: 0.02948 Total loss: 1.84629 timestamp: 1655018916.5152876 iteration: 13500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17228 FastRCNN class loss: 0.09601 FastRCNN total loss: 0.2683 L1 loss: 0.0000e+00 L2 loss: 1.37928 Learning rate: 0.02 Mask loss: 0.19851 RPN box loss: 0.02966 RPN score loss: 0.01059 RPN total loss: 0.04026 Total loss: 1.88634 timestamp: 1655018919.943879 iteration: 13505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16099 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.22309 L1 loss: 0.0000e+00 L2 loss: 1.37903 Learning rate: 0.02 Mask loss: 0.13527 RPN box loss: 0.02677 RPN score loss: 0.0077 RPN total loss: 0.03447 Total loss: 1.77186 timestamp: 1655018923.1823554 iteration: 13510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23488 FastRCNN class loss: 0.11475 FastRCNN total loss: 0.34963 L1 loss: 0.0000e+00 L2 loss: 1.37877 Learning rate: 0.02 Mask loss: 0.19538 RPN box loss: 0.06707 RPN score loss: 0.01859 RPN total loss: 0.08566 Total loss: 2.00944 timestamp: 1655018926.6219244 iteration: 13515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20136 FastRCNN class loss: 0.13584 FastRCNN total loss: 0.33721 L1 loss: 0.0000e+00 L2 loss: 1.37851 Learning rate: 0.02 Mask loss: 0.24332 RPN box loss: 0.01719 RPN score loss: 0.00672 RPN total loss: 0.02391 Total loss: 1.98295 timestamp: 1655018929.8378553 iteration: 13520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12742 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.19192 L1 loss: 0.0000e+00 L2 loss: 1.37828 Learning rate: 0.02 Mask loss: 0.22174 RPN box loss: 0.01927 RPN score loss: 0.00399 RPN total loss: 0.02327 Total loss: 1.81521 timestamp: 1655018933.2257123 iteration: 13525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12918 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.1882 L1 loss: 0.0000e+00 L2 loss: 1.37806 Learning rate: 0.02 Mask loss: 0.13174 RPN box loss: 0.03138 RPN score loss: 0.00373 RPN total loss: 0.03511 Total loss: 1.73311 timestamp: 1655018936.515052 iteration: 13530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19386 FastRCNN class loss: 0.0965 FastRCNN total loss: 0.29036 L1 loss: 0.0000e+00 L2 loss: 1.37782 Learning rate: 0.02 Mask loss: 0.203 RPN box loss: 0.03828 RPN score loss: 0.00971 RPN total loss: 0.048 Total loss: 1.91917 timestamp: 1655018939.9192388 iteration: 13535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15433 FastRCNN class loss: 0.16033 FastRCNN total loss: 0.31466 L1 loss: 0.0000e+00 L2 loss: 1.37756 Learning rate: 0.02 Mask loss: 0.158 RPN box loss: 0.05529 RPN score loss: 0.01489 RPN total loss: 0.07018 Total loss: 1.9204 timestamp: 1655018943.194744 iteration: 13540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20162 FastRCNN class loss: 0.11077 FastRCNN total loss: 0.31239 L1 loss: 0.0000e+00 L2 loss: 1.37732 Learning rate: 0.02 Mask loss: 0.2419 RPN box loss: 0.03999 RPN score loss: 0.00764 RPN total loss: 0.04762 Total loss: 1.97924 timestamp: 1655018946.558893 iteration: 13545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1324 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.20328 L1 loss: 0.0000e+00 L2 loss: 1.37707 Learning rate: 0.02 Mask loss: 0.17535 RPN box loss: 0.04258 RPN score loss: 0.00414 RPN total loss: 0.04671 Total loss: 1.80241 timestamp: 1655018950.050804 iteration: 13550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1786 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.26261 L1 loss: 0.0000e+00 L2 loss: 1.37681 Learning rate: 0.02 Mask loss: 0.1594 RPN box loss: 0.0159 RPN score loss: 0.00611 RPN total loss: 0.02202 Total loss: 1.82084 timestamp: 1655018953.299051 iteration: 13555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12 FastRCNN class loss: 0.07051 FastRCNN total loss: 0.19052 L1 loss: 0.0000e+00 L2 loss: 1.37658 Learning rate: 0.02 Mask loss: 0.26743 RPN box loss: 0.035 RPN score loss: 0.00646 RPN total loss: 0.04145 Total loss: 1.87599 timestamp: 1655018956.668508 iteration: 13560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.17428 L1 loss: 0.0000e+00 L2 loss: 1.37636 Learning rate: 0.02 Mask loss: 0.13418 RPN box loss: 0.02631 RPN score loss: 0.01157 RPN total loss: 0.03788 Total loss: 1.72269 timestamp: 1655018959.9308696 iteration: 13565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19276 FastRCNN class loss: 0.10655 FastRCNN total loss: 0.29931 L1 loss: 0.0000e+00 L2 loss: 1.37611 Learning rate: 0.02 Mask loss: 0.16063 RPN box loss: 0.04274 RPN score loss: 0.01212 RPN total loss: 0.05486 Total loss: 1.89091 timestamp: 1655018963.25782 iteration: 13570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.22162 L1 loss: 0.0000e+00 L2 loss: 1.37585 Learning rate: 0.02 Mask loss: 0.15726 RPN box loss: 0.07218 RPN score loss: 0.0065 RPN total loss: 0.07868 Total loss: 1.83341 timestamp: 1655018966.5500572 iteration: 13575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15062 FastRCNN class loss: 0.07328 FastRCNN total loss: 0.2239 L1 loss: 0.0000e+00 L2 loss: 1.3756 Learning rate: 0.02 Mask loss: 0.13945 RPN box loss: 0.02193 RPN score loss: 0.00523 RPN total loss: 0.02717 Total loss: 1.76611 timestamp: 1655018969.9569075 iteration: 13580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14903 FastRCNN class loss: 0.09965 FastRCNN total loss: 0.24868 L1 loss: 0.0000e+00 L2 loss: 1.37537 Learning rate: 0.02 Mask loss: 0.15811 RPN box loss: 0.03125 RPN score loss: 0.00502 RPN total loss: 0.03627 Total loss: 1.81843 timestamp: 1655018973.145932 iteration: 13585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15554 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.2331 L1 loss: 0.0000e+00 L2 loss: 1.37512 Learning rate: 0.02 Mask loss: 0.11713 RPN box loss: 0.054 RPN score loss: 0.00487 RPN total loss: 0.05887 Total loss: 1.78422 timestamp: 1655018976.577601 iteration: 13590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13361 FastRCNN class loss: 0.07721 FastRCNN total loss: 0.21083 L1 loss: 0.0000e+00 L2 loss: 1.37488 Learning rate: 0.02 Mask loss: 0.2334 RPN box loss: 0.01405 RPN score loss: 0.00579 RPN total loss: 0.01984 Total loss: 1.83895 timestamp: 1655018979.9293292 iteration: 13595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17767 FastRCNN class loss: 0.19747 FastRCNN total loss: 0.37514 L1 loss: 0.0000e+00 L2 loss: 1.37463 Learning rate: 0.02 Mask loss: 0.31599 RPN box loss: 0.06115 RPN score loss: 0.02151 RPN total loss: 0.08266 Total loss: 2.14842 timestamp: 1655018983.211031 iteration: 13600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10764 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.17427 L1 loss: 0.0000e+00 L2 loss: 1.37439 Learning rate: 0.02 Mask loss: 0.17766 RPN box loss: 0.0278 RPN score loss: 0.02412 RPN total loss: 0.05192 Total loss: 1.77823 timestamp: 1655018986.5505383 iteration: 13605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09794 FastRCNN class loss: 0.06375 FastRCNN total loss: 0.16169 L1 loss: 0.0000e+00 L2 loss: 1.37414 Learning rate: 0.02 Mask loss: 0.07938 RPN box loss: 0.01407 RPN score loss: 0.00274 RPN total loss: 0.01681 Total loss: 1.63203 timestamp: 1655018989.8717544 iteration: 13610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12506 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.1975 L1 loss: 0.0000e+00 L2 loss: 1.37389 Learning rate: 0.02 Mask loss: 0.18839 RPN box loss: 0.02179 RPN score loss: 0.00378 RPN total loss: 0.02557 Total loss: 1.78535 timestamp: 1655018993.2509723 iteration: 13615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17756 FastRCNN class loss: 0.15592 FastRCNN total loss: 0.33348 L1 loss: 0.0000e+00 L2 loss: 1.37365 Learning rate: 0.02 Mask loss: 0.19338 RPN box loss: 0.03104 RPN score loss: 0.00551 RPN total loss: 0.03656 Total loss: 1.93706 timestamp: 1655018996.5766487 iteration: 13620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24482 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.32703 L1 loss: 0.0000e+00 L2 loss: 1.37339 Learning rate: 0.02 Mask loss: 0.17016 RPN box loss: 0.06919 RPN score loss: 0.01196 RPN total loss: 0.08114 Total loss: 1.95172 timestamp: 1655018999.8625355 iteration: 13625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16915 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.25349 L1 loss: 0.0000e+00 L2 loss: 1.37314 Learning rate: 0.02 Mask loss: 0.18844 RPN box loss: 0.0509 RPN score loss: 0.00567 RPN total loss: 0.05657 Total loss: 1.87164 timestamp: 1655019003.136767 iteration: 13630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11164 FastRCNN class loss: 0.08209 FastRCNN total loss: 0.19373 L1 loss: 0.0000e+00 L2 loss: 1.37292 Learning rate: 0.02 Mask loss: 0.16142 RPN box loss: 0.0188 RPN score loss: 0.00626 RPN total loss: 0.02506 Total loss: 1.75312 timestamp: 1655019006.5227947 iteration: 13635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19228 FastRCNN class loss: 0.13704 FastRCNN total loss: 0.32933 L1 loss: 0.0000e+00 L2 loss: 1.37266 Learning rate: 0.02 Mask loss: 0.22182 RPN box loss: 0.1776 RPN score loss: 0.0186 RPN total loss: 0.1962 Total loss: 2.12001 timestamp: 1655019009.9056156 iteration: 13640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1052 FastRCNN class loss: 0.06081 FastRCNN total loss: 0.166 L1 loss: 0.0000e+00 L2 loss: 1.3724 Learning rate: 0.02 Mask loss: 0.15333 RPN box loss: 0.05692 RPN score loss: 0.00354 RPN total loss: 0.06046 Total loss: 1.75219 timestamp: 1655019013.1298304 iteration: 13645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.12135 FastRCNN total loss: 0.28463 L1 loss: 0.0000e+00 L2 loss: 1.37217 Learning rate: 0.02 Mask loss: 0.18987 RPN box loss: 0.05248 RPN score loss: 0.02173 RPN total loss: 0.07421 Total loss: 1.92089 timestamp: 1655019016.572637 iteration: 13650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13794 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.20674 L1 loss: 0.0000e+00 L2 loss: 1.37192 Learning rate: 0.02 Mask loss: 0.18612 RPN box loss: 0.02684 RPN score loss: 0.00934 RPN total loss: 0.03617 Total loss: 1.80096 timestamp: 1655019019.8494756 iteration: 13655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19413 FastRCNN class loss: 0.19004 FastRCNN total loss: 0.38417 L1 loss: 0.0000e+00 L2 loss: 1.37167 Learning rate: 0.02 Mask loss: 0.26628 RPN box loss: 0.03212 RPN score loss: 0.00871 RPN total loss: 0.04083 Total loss: 2.06296 timestamp: 1655019023.272519 iteration: 13660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12273 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.21399 L1 loss: 0.0000e+00 L2 loss: 1.3714 Learning rate: 0.02 Mask loss: 0.14067 RPN box loss: 0.06765 RPN score loss: 0.02651 RPN total loss: 0.09416 Total loss: 1.82022 timestamp: 1655019026.5985014 iteration: 13665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20444 FastRCNN class loss: 0.16041 FastRCNN total loss: 0.36486 L1 loss: 0.0000e+00 L2 loss: 1.37115 Learning rate: 0.02 Mask loss: 0.16594 RPN box loss: 0.03253 RPN score loss: 0.00825 RPN total loss: 0.04078 Total loss: 1.94272 timestamp: 1655019030.0847805 iteration: 13670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20773 FastRCNN class loss: 0.063 FastRCNN total loss: 0.27073 L1 loss: 0.0000e+00 L2 loss: 1.37092 Learning rate: 0.02 Mask loss: 0.12807 RPN box loss: 0.01839 RPN score loss: 0.00272 RPN total loss: 0.02111 Total loss: 1.79082 timestamp: 1655019033.370897 iteration: 13675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18663 FastRCNN class loss: 0.13613 FastRCNN total loss: 0.32276 L1 loss: 0.0000e+00 L2 loss: 1.37067 Learning rate: 0.02 Mask loss: 0.16415 RPN box loss: 0.03827 RPN score loss: 0.01958 RPN total loss: 0.05785 Total loss: 1.91543 timestamp: 1655019036.6644998 iteration: 13680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11424 FastRCNN class loss: 0.06733 FastRCNN total loss: 0.18157 L1 loss: 0.0000e+00 L2 loss: 1.37045 Learning rate: 0.02 Mask loss: 0.20721 RPN box loss: 0.02091 RPN score loss: 0.00422 RPN total loss: 0.02513 Total loss: 1.78437 timestamp: 1655019040.0066302 iteration: 13685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08121 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.14363 L1 loss: 0.0000e+00 L2 loss: 1.37022 Learning rate: 0.02 Mask loss: 0.14619 RPN box loss: 0.02106 RPN score loss: 0.02717 RPN total loss: 0.04823 Total loss: 1.70828 timestamp: 1655019043.284454 iteration: 13690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19962 FastRCNN class loss: 0.12475 FastRCNN total loss: 0.32438 L1 loss: 0.0000e+00 L2 loss: 1.36996 Learning rate: 0.02 Mask loss: 0.222 RPN box loss: 0.01839 RPN score loss: 0.00449 RPN total loss: 0.02288 Total loss: 1.93922 timestamp: 1655019046.6846614 iteration: 13695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16114 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.22272 L1 loss: 0.0000e+00 L2 loss: 1.36969 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.01224 RPN score loss: 0.00983 RPN total loss: 0.02208 Total loss: 1.7528 timestamp: 1655019050.0190556 iteration: 13700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16797 FastRCNN class loss: 0.12524 FastRCNN total loss: 0.29321 L1 loss: 0.0000e+00 L2 loss: 1.36946 Learning rate: 0.02 Mask loss: 0.25886 RPN box loss: 0.08092 RPN score loss: 0.01658 RPN total loss: 0.09751 Total loss: 2.01903 timestamp: 1655019053.3058283 iteration: 13705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13453 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.22196 L1 loss: 0.0000e+00 L2 loss: 1.36921 Learning rate: 0.02 Mask loss: 0.10468 RPN box loss: 0.02711 RPN score loss: 0.0039 RPN total loss: 0.03101 Total loss: 1.72686 timestamp: 1655019056.527634 iteration: 13710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24051 FastRCNN class loss: 0.1016 FastRCNN total loss: 0.34211 L1 loss: 0.0000e+00 L2 loss: 1.36897 Learning rate: 0.02 Mask loss: 0.31359 RPN box loss: 0.02262 RPN score loss: 0.01091 RPN total loss: 0.03352 Total loss: 2.05819 timestamp: 1655019059.8957517 iteration: 13715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13238 FastRCNN class loss: 0.09244 FastRCNN total loss: 0.22482 L1 loss: 0.0000e+00 L2 loss: 1.36873 Learning rate: 0.02 Mask loss: 0.15598 RPN box loss: 0.01585 RPN score loss: 0.00808 RPN total loss: 0.02393 Total loss: 1.77347 timestamp: 1655019063.0928967 iteration: 13720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13588 FastRCNN class loss: 0.08305 FastRCNN total loss: 0.21893 L1 loss: 0.0000e+00 L2 loss: 1.36849 Learning rate: 0.02 Mask loss: 0.14896 RPN box loss: 0.10418 RPN score loss: 0.00909 RPN total loss: 0.11327 Total loss: 1.84964 timestamp: 1655019066.629711 iteration: 13725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19825 FastRCNN class loss: 0.1133 FastRCNN total loss: 0.31155 L1 loss: 0.0000e+00 L2 loss: 1.36824 Learning rate: 0.02 Mask loss: 0.23449 RPN box loss: 0.03841 RPN score loss: 0.02121 RPN total loss: 0.05962 Total loss: 1.97391 timestamp: 1655019070.0626667 iteration: 13730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22597 FastRCNN class loss: 0.09934 FastRCNN total loss: 0.3253 L1 loss: 0.0000e+00 L2 loss: 1.368 Learning rate: 0.02 Mask loss: 0.26559 RPN box loss: 0.05308 RPN score loss: 0.00749 RPN total loss: 0.06057 Total loss: 2.01946 timestamp: 1655019073.3538003 iteration: 13735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.0911 FastRCNN total loss: 0.2033 L1 loss: 0.0000e+00 L2 loss: 1.36776 Learning rate: 0.02 Mask loss: 0.1617 RPN box loss: 0.03659 RPN score loss: 0.00829 RPN total loss: 0.04488 Total loss: 1.77764 timestamp: 1655019076.7420313 iteration: 13740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16682 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.25946 L1 loss: 0.0000e+00 L2 loss: 1.36753 Learning rate: 0.02 Mask loss: 0.14807 RPN box loss: 0.00728 RPN score loss: 0.00502 RPN total loss: 0.0123 Total loss: 1.78736 timestamp: 1655019080.0230317 iteration: 13745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14576 FastRCNN class loss: 0.08068 FastRCNN total loss: 0.22644 L1 loss: 0.0000e+00 L2 loss: 1.36728 Learning rate: 0.02 Mask loss: 0.21626 RPN box loss: 0.02586 RPN score loss: 0.00916 RPN total loss: 0.03503 Total loss: 1.845 timestamp: 1655019083.4386964 iteration: 13750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2206 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.29861 L1 loss: 0.0000e+00 L2 loss: 1.36702 Learning rate: 0.02 Mask loss: 0.18214 RPN box loss: 0.02942 RPN score loss: 0.01275 RPN total loss: 0.04216 Total loss: 1.88993 timestamp: 1655019086.7875848 iteration: 13755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16129 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.22533 L1 loss: 0.0000e+00 L2 loss: 1.36677 Learning rate: 0.02 Mask loss: 0.17567 RPN box loss: 0.02035 RPN score loss: 0.00291 RPN total loss: 0.02327 Total loss: 1.79103 timestamp: 1655019090.2471788 iteration: 13760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.06526 FastRCNN total loss: 0.20379 L1 loss: 0.0000e+00 L2 loss: 1.36654 Learning rate: 0.02 Mask loss: 0.18691 RPN box loss: 0.05563 RPN score loss: 0.00931 RPN total loss: 0.06494 Total loss: 1.82218 timestamp: 1655019093.6884267 iteration: 13765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13626 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.22125 L1 loss: 0.0000e+00 L2 loss: 1.36631 Learning rate: 0.02 Mask loss: 0.19633 RPN box loss: 0.03542 RPN score loss: 0.00867 RPN total loss: 0.0441 Total loss: 1.82798 timestamp: 1655019097.071536 iteration: 13770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1842 FastRCNN class loss: 0.08449 FastRCNN total loss: 0.26869 L1 loss: 0.0000e+00 L2 loss: 1.36607 Learning rate: 0.02 Mask loss: 0.19444 RPN box loss: 0.051 RPN score loss: 0.00609 RPN total loss: 0.05709 Total loss: 1.8863 timestamp: 1655019100.5491624 iteration: 13775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21567 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.28789 L1 loss: 0.0000e+00 L2 loss: 1.36584 Learning rate: 0.02 Mask loss: 0.17168 RPN box loss: 0.07223 RPN score loss: 0.00934 RPN total loss: 0.08157 Total loss: 1.90698 timestamp: 1655019103.9093144 iteration: 13780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10733 FastRCNN class loss: 0.09801 FastRCNN total loss: 0.20534 L1 loss: 0.0000e+00 L2 loss: 1.36558 Learning rate: 0.02 Mask loss: 0.09258 RPN box loss: 0.02368 RPN score loss: 0.00994 RPN total loss: 0.03362 Total loss: 1.69712 timestamp: 1655019107.3527422 iteration: 13785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16696 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.26012 L1 loss: 0.0000e+00 L2 loss: 1.36532 Learning rate: 0.02 Mask loss: 0.24901 RPN box loss: 0.0452 RPN score loss: 0.01353 RPN total loss: 0.05873 Total loss: 1.93318 timestamp: 1655019110.675811 iteration: 13790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17195 FastRCNN class loss: 0.10048 FastRCNN total loss: 0.27243 L1 loss: 0.0000e+00 L2 loss: 1.36506 Learning rate: 0.02 Mask loss: 0.23807 RPN box loss: 0.04701 RPN score loss: 0.01294 RPN total loss: 0.05996 Total loss: 1.93552 timestamp: 1655019114.0823002 iteration: 13795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24354 FastRCNN class loss: 0.07555 FastRCNN total loss: 0.31909 L1 loss: 0.0000e+00 L2 loss: 1.3648 Learning rate: 0.02 Mask loss: 0.14677 RPN box loss: 0.03476 RPN score loss: 0.01927 RPN total loss: 0.05404 Total loss: 1.88469 timestamp: 1655019117.39545 iteration: 13800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2124 FastRCNN class loss: 0.1016 FastRCNN total loss: 0.314 L1 loss: 0.0000e+00 L2 loss: 1.36456 Learning rate: 0.02 Mask loss: 0.18576 RPN box loss: 0.03038 RPN score loss: 0.00256 RPN total loss: 0.03294 Total loss: 1.89726 timestamp: 1655019120.8132722 iteration: 13805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17317 FastRCNN class loss: 0.15475 FastRCNN total loss: 0.32792 L1 loss: 0.0000e+00 L2 loss: 1.36431 Learning rate: 0.02 Mask loss: 0.33758 RPN box loss: 0.10071 RPN score loss: 0.01555 RPN total loss: 0.11626 Total loss: 2.14608 timestamp: 1655019124.2801716 iteration: 13810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20938 FastRCNN class loss: 0.17086 FastRCNN total loss: 0.38024 L1 loss: 0.0000e+00 L2 loss: 1.36407 Learning rate: 0.02 Mask loss: 0.18051 RPN box loss: 0.06464 RPN score loss: 0.01655 RPN total loss: 0.08119 Total loss: 2.006 timestamp: 1655019127.5864768 iteration: 13815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20294 FastRCNN class loss: 0.08978 FastRCNN total loss: 0.29272 L1 loss: 0.0000e+00 L2 loss: 1.36384 Learning rate: 0.02 Mask loss: 0.16759 RPN box loss: 0.03952 RPN score loss: 0.00543 RPN total loss: 0.04495 Total loss: 1.8691 timestamp: 1655019130.960189 iteration: 13820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16267 FastRCNN class loss: 0.09517 FastRCNN total loss: 0.25784 L1 loss: 0.0000e+00 L2 loss: 1.3636 Learning rate: 0.02 Mask loss: 0.19756 RPN box loss: 0.0497 RPN score loss: 0.00914 RPN total loss: 0.05884 Total loss: 1.87784 timestamp: 1655019134.228347 iteration: 13825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1848 FastRCNN class loss: 0.13836 FastRCNN total loss: 0.32315 L1 loss: 0.0000e+00 L2 loss: 1.36334 Learning rate: 0.02 Mask loss: 0.1795 RPN box loss: 0.1229 RPN score loss: 0.02024 RPN total loss: 0.14314 Total loss: 2.00913 timestamp: 1655019137.6214359 iteration: 13830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1478 FastRCNN class loss: 0.09003 FastRCNN total loss: 0.23783 L1 loss: 0.0000e+00 L2 loss: 1.36309 Learning rate: 0.02 Mask loss: 0.12346 RPN box loss: 0.02513 RPN score loss: 0.00749 RPN total loss: 0.03262 Total loss: 1.757 timestamp: 1655019140.950272 iteration: 13835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18916 FastRCNN class loss: 0.1209 FastRCNN total loss: 0.31006 L1 loss: 0.0000e+00 L2 loss: 1.36283 Learning rate: 0.02 Mask loss: 0.14759 RPN box loss: 0.01357 RPN score loss: 0.00436 RPN total loss: 0.01793 Total loss: 1.83841 timestamp: 1655019144.242378 iteration: 13840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13062 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.17265 L1 loss: 0.0000e+00 L2 loss: 1.3626 Learning rate: 0.02 Mask loss: 0.1224 RPN box loss: 0.01378 RPN score loss: 0.00874 RPN total loss: 0.02252 Total loss: 1.68017 timestamp: 1655019147.6322632 iteration: 13845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17178 FastRCNN class loss: 0.10415 FastRCNN total loss: 0.27593 L1 loss: 0.0000e+00 L2 loss: 1.36236 Learning rate: 0.02 Mask loss: 0.22381 RPN box loss: 0.03449 RPN score loss: 0.01055 RPN total loss: 0.04504 Total loss: 1.90714 timestamp: 1655019150.82549 iteration: 13850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16819 FastRCNN class loss: 0.05643 FastRCNN total loss: 0.22462 L1 loss: 0.0000e+00 L2 loss: 1.36213 Learning rate: 0.02 Mask loss: 0.09738 RPN box loss: 0.02934 RPN score loss: 0.00311 RPN total loss: 0.03244 Total loss: 1.71657 timestamp: 1655019154.2087 iteration: 13855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19506 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.28255 L1 loss: 0.0000e+00 L2 loss: 1.36187 Learning rate: 0.02 Mask loss: 0.21822 RPN box loss: 0.00614 RPN score loss: 0.00251 RPN total loss: 0.00865 Total loss: 1.87129 timestamp: 1655019157.4612086 iteration: 13860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.10671 FastRCNN total loss: 0.21902 L1 loss: 0.0000e+00 L2 loss: 1.36162 Learning rate: 0.02 Mask loss: 0.21183 RPN box loss: 0.01999 RPN score loss: 0.00434 RPN total loss: 0.02433 Total loss: 1.8168 timestamp: 1655019160.9007032 iteration: 13865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1178 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.18981 L1 loss: 0.0000e+00 L2 loss: 1.36139 Learning rate: 0.02 Mask loss: 0.16451 RPN box loss: 0.02547 RPN score loss: 0.01187 RPN total loss: 0.03734 Total loss: 1.75305 timestamp: 1655019164.1897528 iteration: 13870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16682 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.24857 L1 loss: 0.0000e+00 L2 loss: 1.36115 Learning rate: 0.02 Mask loss: 0.22019 RPN box loss: 0.01491 RPN score loss: 0.00755 RPN total loss: 0.02247 Total loss: 1.85237 timestamp: 1655019167.6079228 iteration: 13875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19737 FastRCNN class loss: 0.11381 FastRCNN total loss: 0.31118 L1 loss: 0.0000e+00 L2 loss: 1.36088 Learning rate: 0.02 Mask loss: 0.2172 RPN box loss: 0.06192 RPN score loss: 0.01536 RPN total loss: 0.07728 Total loss: 1.96653 timestamp: 1655019170.9314222 iteration: 13880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13395 FastRCNN class loss: 0.09332 FastRCNN total loss: 0.22728 L1 loss: 0.0000e+00 L2 loss: 1.36063 Learning rate: 0.02 Mask loss: 0.25676 RPN box loss: 0.02569 RPN score loss: 0.01446 RPN total loss: 0.04015 Total loss: 1.88482 timestamp: 1655019174.2361479 iteration: 13885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13611 FastRCNN class loss: 0.08323 FastRCNN total loss: 0.21933 L1 loss: 0.0000e+00 L2 loss: 1.3604 Learning rate: 0.02 Mask loss: 0.21045 RPN box loss: 0.0282 RPN score loss: 0.00538 RPN total loss: 0.03359 Total loss: 1.82377 timestamp: 1655019177.5737193 iteration: 13890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13942 FastRCNN class loss: 0.09855 FastRCNN total loss: 0.23797 L1 loss: 0.0000e+00 L2 loss: 1.36016 Learning rate: 0.02 Mask loss: 0.26627 RPN box loss: 0.02584 RPN score loss: 0.01008 RPN total loss: 0.03592 Total loss: 1.90033 timestamp: 1655019180.7933846 iteration: 13895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16239 FastRCNN class loss: 0.09499 FastRCNN total loss: 0.25739 L1 loss: 0.0000e+00 L2 loss: 1.35991 Learning rate: 0.02 Mask loss: 0.19351 RPN box loss: 0.06393 RPN score loss: 0.00535 RPN total loss: 0.06928 Total loss: 1.88008 timestamp: 1655019184.1268692 iteration: 13900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18698 FastRCNN class loss: 0.09664 FastRCNN total loss: 0.28362 L1 loss: 0.0000e+00 L2 loss: 1.35966 Learning rate: 0.02 Mask loss: 0.16507 RPN box loss: 0.09112 RPN score loss: 0.01414 RPN total loss: 0.10527 Total loss: 1.91362 timestamp: 1655019187.3519757 iteration: 13905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17161 FastRCNN class loss: 0.1071 FastRCNN total loss: 0.27871 L1 loss: 0.0000e+00 L2 loss: 1.35942 Learning rate: 0.02 Mask loss: 0.13951 RPN box loss: 0.02979 RPN score loss: 0.00684 RPN total loss: 0.03663 Total loss: 1.81427 timestamp: 1655019190.6555305 iteration: 13910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17568 FastRCNN class loss: 0.10252 FastRCNN total loss: 0.2782 L1 loss: 0.0000e+00 L2 loss: 1.35919 Learning rate: 0.02 Mask loss: 0.19302 RPN box loss: 0.0877 RPN score loss: 0.01298 RPN total loss: 0.10068 Total loss: 1.93108 timestamp: 1655019194.0399106 iteration: 13915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18906 FastRCNN class loss: 0.10042 FastRCNN total loss: 0.28948 L1 loss: 0.0000e+00 L2 loss: 1.35895 Learning rate: 0.02 Mask loss: 0.1395 RPN box loss: 0.01974 RPN score loss: 0.01006 RPN total loss: 0.02979 Total loss: 1.81773 timestamp: 1655019197.43708 iteration: 13920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2354 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.31132 L1 loss: 0.0000e+00 L2 loss: 1.35871 Learning rate: 0.02 Mask loss: 0.25267 RPN box loss: 0.02309 RPN score loss: 0.00876 RPN total loss: 0.03185 Total loss: 1.95454 timestamp: 1655019200.7459111 iteration: 13925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16623 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.24629 L1 loss: 0.0000e+00 L2 loss: 1.35848 Learning rate: 0.02 Mask loss: 0.15083 RPN box loss: 0.02278 RPN score loss: 0.00761 RPN total loss: 0.0304 Total loss: 1.786 timestamp: 1655019204.0417702 iteration: 13930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15748 FastRCNN class loss: 0.089 FastRCNN total loss: 0.24648 L1 loss: 0.0000e+00 L2 loss: 1.35822 Learning rate: 0.02 Mask loss: 0.1334 RPN box loss: 0.02029 RPN score loss: 0.00277 RPN total loss: 0.02306 Total loss: 1.76116 timestamp: 1655019207.4174469 iteration: 13935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23714 FastRCNN class loss: 0.11524 FastRCNN total loss: 0.35238 L1 loss: 0.0000e+00 L2 loss: 1.35796 Learning rate: 0.02 Mask loss: 0.26461 RPN box loss: 0.01367 RPN score loss: 0.00753 RPN total loss: 0.02119 Total loss: 1.99614 timestamp: 1655019210.7298176 iteration: 13940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.24542 L1 loss: 0.0000e+00 L2 loss: 1.3577 Learning rate: 0.02 Mask loss: 0.16742 RPN box loss: 0.04259 RPN score loss: 0.01157 RPN total loss: 0.05417 Total loss: 1.82471 timestamp: 1655019214.092754 iteration: 13945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14175 FastRCNN class loss: 0.11238 FastRCNN total loss: 0.25412 L1 loss: 0.0000e+00 L2 loss: 1.35744 Learning rate: 0.02 Mask loss: 0.22353 RPN box loss: 0.03955 RPN score loss: 0.00822 RPN total loss: 0.04777 Total loss: 1.88286 timestamp: 1655019217.3680263 iteration: 13950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18811 FastRCNN class loss: 0.17672 FastRCNN total loss: 0.36483 L1 loss: 0.0000e+00 L2 loss: 1.35721 Learning rate: 0.02 Mask loss: 0.25732 RPN box loss: 0.02834 RPN score loss: 0.01704 RPN total loss: 0.04538 Total loss: 2.02473 timestamp: 1655019220.846504 iteration: 13955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17915 FastRCNN class loss: 0.11489 FastRCNN total loss: 0.29404 L1 loss: 0.0000e+00 L2 loss: 1.35697 Learning rate: 0.02 Mask loss: 0.25851 RPN box loss: 0.011 RPN score loss: 0.01135 RPN total loss: 0.02235 Total loss: 1.93187 timestamp: 1655019224.1325493 iteration: 13960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18663 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.2667 L1 loss: 0.0000e+00 L2 loss: 1.35673 Learning rate: 0.02 Mask loss: 0.13629 RPN box loss: 0.03665 RPN score loss: 0.00743 RPN total loss: 0.04408 Total loss: 1.8038 timestamp: 1655019227.517732 iteration: 13965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20806 FastRCNN class loss: 0.12577 FastRCNN total loss: 0.33382 L1 loss: 0.0000e+00 L2 loss: 1.3565 Learning rate: 0.02 Mask loss: 0.25264 RPN box loss: 0.06186 RPN score loss: 0.02241 RPN total loss: 0.08427 Total loss: 2.02724 timestamp: 1655019230.819106 iteration: 13970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17272 FastRCNN class loss: 0.09919 FastRCNN total loss: 0.27191 L1 loss: 0.0000e+00 L2 loss: 1.35626 Learning rate: 0.02 Mask loss: 0.22163 RPN box loss: 0.02102 RPN score loss: 0.00896 RPN total loss: 0.02998 Total loss: 1.87977 timestamp: 1655019234.2136135 iteration: 13975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18916 FastRCNN class loss: 0.13391 FastRCNN total loss: 0.32307 L1 loss: 0.0000e+00 L2 loss: 1.35602 Learning rate: 0.02 Mask loss: 0.20486 RPN box loss: 0.05499 RPN score loss: 0.01757 RPN total loss: 0.07255 Total loss: 1.9565 timestamp: 1655019237.5278847 iteration: 13980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19641 FastRCNN class loss: 0.10062 FastRCNN total loss: 0.29703 L1 loss: 0.0000e+00 L2 loss: 1.35579 Learning rate: 0.02 Mask loss: 0.29772 RPN box loss: 0.05986 RPN score loss: 0.01155 RPN total loss: 0.07142 Total loss: 2.02195 timestamp: 1655019240.818267 iteration: 13985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19367 FastRCNN class loss: 0.06245 FastRCNN total loss: 0.25612 L1 loss: 0.0000e+00 L2 loss: 1.35554 Learning rate: 0.02 Mask loss: 0.13707 RPN box loss: 0.01579 RPN score loss: 0.00577 RPN total loss: 0.02156 Total loss: 1.77029 timestamp: 1655019244.2540884 iteration: 13990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23326 FastRCNN class loss: 0.1224 FastRCNN total loss: 0.35566 L1 loss: 0.0000e+00 L2 loss: 1.35529 Learning rate: 0.02 Mask loss: 0.2472 RPN box loss: 0.01504 RPN score loss: 0.00483 RPN total loss: 0.01987 Total loss: 1.97801 timestamp: 1655019247.4815695 iteration: 13995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11701 FastRCNN class loss: 0.07674 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 1.35507 Learning rate: 0.02 Mask loss: 0.14306 RPN box loss: 0.05932 RPN score loss: 0.0093 RPN total loss: 0.06863 Total loss: 1.76051 timestamp: 1655019250.905277 iteration: 14000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25986 FastRCNN class loss: 0.1057 FastRCNN total loss: 0.36556 L1 loss: 0.0000e+00 L2 loss: 1.35482 Learning rate: 0.02 Mask loss: 0.20977 RPN box loss: 0.03044 RPN score loss: 0.00575 RPN total loss: 0.03619 Total loss: 1.96634 timestamp: 1655019254.1999602 iteration: 14005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19464 FastRCNN class loss: 0.11571 FastRCNN total loss: 0.31035 L1 loss: 0.0000e+00 L2 loss: 1.35457 Learning rate: 0.02 Mask loss: 0.16335 RPN box loss: 0.02718 RPN score loss: 0.00554 RPN total loss: 0.03273 Total loss: 1.861 timestamp: 1655019257.8342552 iteration: 14010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16507 FastRCNN class loss: 0.10536 FastRCNN total loss: 0.27043 L1 loss: 0.0000e+00 L2 loss: 1.35433 Learning rate: 0.02 Mask loss: 0.13206 RPN box loss: 0.05567 RPN score loss: 0.01171 RPN total loss: 0.06738 Total loss: 1.8242 timestamp: 1655019261.255359 iteration: 14015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16753 FastRCNN class loss: 0.0597 FastRCNN total loss: 0.22723 L1 loss: 0.0000e+00 L2 loss: 1.35407 Learning rate: 0.02 Mask loss: 0.14861 RPN box loss: 0.02564 RPN score loss: 0.00968 RPN total loss: 0.03532 Total loss: 1.76524 timestamp: 1655019264.5840523 iteration: 14020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17337 FastRCNN class loss: 0.11683 FastRCNN total loss: 0.2902 L1 loss: 0.0000e+00 L2 loss: 1.35384 Learning rate: 0.02 Mask loss: 0.19277 RPN box loss: 0.08112 RPN score loss: 0.00908 RPN total loss: 0.0902 Total loss: 1.92702 timestamp: 1655019268.0132947 iteration: 14025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19704 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.26861 L1 loss: 0.0000e+00 L2 loss: 1.35361 Learning rate: 0.02 Mask loss: 0.25828 RPN box loss: 0.02841 RPN score loss: 0.00615 RPN total loss: 0.03456 Total loss: 1.91505 timestamp: 1655019271.3142443 iteration: 14030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19602 FastRCNN class loss: 0.0926 FastRCNN total loss: 0.28862 L1 loss: 0.0000e+00 L2 loss: 1.35337 Learning rate: 0.02 Mask loss: 0.20803 RPN box loss: 0.01934 RPN score loss: 0.00487 RPN total loss: 0.02421 Total loss: 1.87423 timestamp: 1655019274.6620967 iteration: 14035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20737 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.28509 L1 loss: 0.0000e+00 L2 loss: 1.35314 Learning rate: 0.02 Mask loss: 0.17053 RPN box loss: 0.05862 RPN score loss: 0.01241 RPN total loss: 0.07103 Total loss: 1.87979 timestamp: 1655019277.878485 iteration: 14040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19187 FastRCNN class loss: 0.15433 FastRCNN total loss: 0.34619 L1 loss: 0.0000e+00 L2 loss: 1.3529 Learning rate: 0.02 Mask loss: 0.26445 RPN box loss: 0.04966 RPN score loss: 0.01331 RPN total loss: 0.06297 Total loss: 2.02651 timestamp: 1655019281.2530227 iteration: 14045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12385 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.19429 L1 loss: 0.0000e+00 L2 loss: 1.35265 Learning rate: 0.02 Mask loss: 0.28546 RPN box loss: 0.04356 RPN score loss: 0.00993 RPN total loss: 0.05349 Total loss: 1.88589 timestamp: 1655019284.5039296 iteration: 14050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13497 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.19433 L1 loss: 0.0000e+00 L2 loss: 1.35241 Learning rate: 0.02 Mask loss: 0.13059 RPN box loss: 0.02787 RPN score loss: 0.00374 RPN total loss: 0.03161 Total loss: 1.70895 timestamp: 1655019287.8275044 iteration: 14055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16606 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.24899 L1 loss: 0.0000e+00 L2 loss: 1.35216 Learning rate: 0.02 Mask loss: 0.17287 RPN box loss: 0.05457 RPN score loss: 0.01132 RPN total loss: 0.06589 Total loss: 1.83991 timestamp: 1655019291.3188598 iteration: 14060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22145 FastRCNN class loss: 0.10314 FastRCNN total loss: 0.32459 L1 loss: 0.0000e+00 L2 loss: 1.35193 Learning rate: 0.02 Mask loss: 0.19424 RPN box loss: 0.06162 RPN score loss: 0.00587 RPN total loss: 0.06749 Total loss: 1.93826 timestamp: 1655019294.5815191 iteration: 14065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1628 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.23483 L1 loss: 0.0000e+00 L2 loss: 1.35167 Learning rate: 0.02 Mask loss: 0.17874 RPN box loss: 0.02022 RPN score loss: 0.00635 RPN total loss: 0.02657 Total loss: 1.79182 timestamp: 1655019297.958622 iteration: 14070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17639 FastRCNN class loss: 0.07967 FastRCNN total loss: 0.25606 L1 loss: 0.0000e+00 L2 loss: 1.35144 Learning rate: 0.02 Mask loss: 0.17748 RPN box loss: 0.02091 RPN score loss: 0.00416 RPN total loss: 0.02508 Total loss: 1.81005 timestamp: 1655019301.3305914 iteration: 14075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12612 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.21308 L1 loss: 0.0000e+00 L2 loss: 1.35123 Learning rate: 0.02 Mask loss: 0.17774 RPN box loss: 0.01948 RPN score loss: 0.01091 RPN total loss: 0.0304 Total loss: 1.77245 timestamp: 1655019304.7094529 iteration: 14080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17805 FastRCNN class loss: 0.10896 FastRCNN total loss: 0.28701 L1 loss: 0.0000e+00 L2 loss: 1.351 Learning rate: 0.02 Mask loss: 0.25899 RPN box loss: 0.04209 RPN score loss: 0.0084 RPN total loss: 0.05049 Total loss: 1.94749 timestamp: 1655019308.005947 iteration: 14085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27004 FastRCNN class loss: 0.15271 FastRCNN total loss: 0.42275 L1 loss: 0.0000e+00 L2 loss: 1.35074 Learning rate: 0.02 Mask loss: 0.28716 RPN box loss: 0.0749 RPN score loss: 0.01183 RPN total loss: 0.08673 Total loss: 2.14737 timestamp: 1655019311.351643 iteration: 14090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2153 FastRCNN class loss: 0.13613 FastRCNN total loss: 0.35143 L1 loss: 0.0000e+00 L2 loss: 1.35048 Learning rate: 0.02 Mask loss: 0.19621 RPN box loss: 0.02344 RPN score loss: 0.00853 RPN total loss: 0.03197 Total loss: 1.93009 timestamp: 1655019314.6077554 iteration: 14095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14307 FastRCNN class loss: 0.07852 FastRCNN total loss: 0.22159 L1 loss: 0.0000e+00 L2 loss: 1.35025 Learning rate: 0.02 Mask loss: 0.13425 RPN box loss: 0.01634 RPN score loss: 0.00797 RPN total loss: 0.02431 Total loss: 1.7304 timestamp: 1655019317.9920027 iteration: 14100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22946 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.30075 L1 loss: 0.0000e+00 L2 loss: 1.35002 Learning rate: 0.02 Mask loss: 0.16809 RPN box loss: 0.05336 RPN score loss: 0.00955 RPN total loss: 0.06291 Total loss: 1.88177 timestamp: 1655019321.4210608 iteration: 14105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16335 FastRCNN class loss: 0.10829 FastRCNN total loss: 0.27164 L1 loss: 0.0000e+00 L2 loss: 1.34979 Learning rate: 0.02 Mask loss: 0.18942 RPN box loss: 0.01445 RPN score loss: 0.0032 RPN total loss: 0.01764 Total loss: 1.82849 timestamp: 1655019324.653949 iteration: 14110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20401 FastRCNN class loss: 0.0937 FastRCNN total loss: 0.29771 L1 loss: 0.0000e+00 L2 loss: 1.34955 Learning rate: 0.02 Mask loss: 0.15216 RPN box loss: 0.03351 RPN score loss: 0.00727 RPN total loss: 0.04078 Total loss: 1.8402 timestamp: 1655019327.9909592 iteration: 14115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16631 FastRCNN class loss: 0.12504 FastRCNN total loss: 0.29135 L1 loss: 0.0000e+00 L2 loss: 1.34932 Learning rate: 0.02 Mask loss: 0.15076 RPN box loss: 0.04895 RPN score loss: 0.01962 RPN total loss: 0.06857 Total loss: 1.86 timestamp: 1655019331.2813084 iteration: 14120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.177 FastRCNN class loss: 0.09648 FastRCNN total loss: 0.27348 L1 loss: 0.0000e+00 L2 loss: 1.34907 Learning rate: 0.02 Mask loss: 0.22702 RPN box loss: 0.04528 RPN score loss: 0.01848 RPN total loss: 0.06376 Total loss: 1.91333 timestamp: 1655019334.749079 iteration: 14125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23209 FastRCNN class loss: 0.08766 FastRCNN total loss: 0.31975 L1 loss: 0.0000e+00 L2 loss: 1.34882 Learning rate: 0.02 Mask loss: 0.18276 RPN box loss: 0.04339 RPN score loss: 0.01239 RPN total loss: 0.05578 Total loss: 1.9071 timestamp: 1655019338.070873 iteration: 14130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16877 FastRCNN class loss: 0.18836 FastRCNN total loss: 0.35713 L1 loss: 0.0000e+00 L2 loss: 1.34857 Learning rate: 0.02 Mask loss: 0.28233 RPN box loss: 0.03487 RPN score loss: 0.12282 RPN total loss: 0.15769 Total loss: 2.14571 timestamp: 1655019341.3649707 iteration: 14135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.05113 FastRCNN total loss: 0.14034 L1 loss: 0.0000e+00 L2 loss: 1.34833 Learning rate: 0.02 Mask loss: 0.1504 RPN box loss: 0.07127 RPN score loss: 0.005 RPN total loss: 0.07628 Total loss: 1.71536 timestamp: 1655019344.670218 iteration: 14140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22011 FastRCNN class loss: 0.10031 FastRCNN total loss: 0.32042 L1 loss: 0.0000e+00 L2 loss: 1.34811 Learning rate: 0.02 Mask loss: 0.16444 RPN box loss: 0.04276 RPN score loss: 0.00896 RPN total loss: 0.05171 Total loss: 1.88469 timestamp: 1655019348.0249302 iteration: 14145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16512 FastRCNN class loss: 0.09123 FastRCNN total loss: 0.25634 L1 loss: 0.0000e+00 L2 loss: 1.34786 Learning rate: 0.02 Mask loss: 0.16732 RPN box loss: 0.05891 RPN score loss: 0.0129 RPN total loss: 0.07181 Total loss: 1.84334 timestamp: 1655019351.4545915 iteration: 14150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16335 FastRCNN class loss: 0.09384 FastRCNN total loss: 0.25719 L1 loss: 0.0000e+00 L2 loss: 1.34759 Learning rate: 0.02 Mask loss: 0.19591 RPN box loss: 0.03084 RPN score loss: 0.00838 RPN total loss: 0.03922 Total loss: 1.83991 timestamp: 1655019354.693456 iteration: 14155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14657 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.23683 L1 loss: 0.0000e+00 L2 loss: 1.34736 Learning rate: 0.02 Mask loss: 0.24779 RPN box loss: 0.05833 RPN score loss: 0.00387 RPN total loss: 0.0622 Total loss: 1.89418 timestamp: 1655019358.148069 iteration: 14160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10516 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.16326 L1 loss: 0.0000e+00 L2 loss: 1.34712 Learning rate: 0.02 Mask loss: 0.13945 RPN box loss: 0.02432 RPN score loss: 0.0031 RPN total loss: 0.02742 Total loss: 1.67725 timestamp: 1655019361.494009 iteration: 14165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10417 FastRCNN class loss: 0.03908 FastRCNN total loss: 0.14324 L1 loss: 0.0000e+00 L2 loss: 1.34688 Learning rate: 0.02 Mask loss: 0.21529 RPN box loss: 0.05916 RPN score loss: 0.0166 RPN total loss: 0.07576 Total loss: 1.78117 timestamp: 1655019364.8583953 iteration: 14170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1584 FastRCNN class loss: 0.13104 FastRCNN total loss: 0.28945 L1 loss: 0.0000e+00 L2 loss: 1.34663 Learning rate: 0.02 Mask loss: 0.2105 RPN box loss: 0.03376 RPN score loss: 0.00944 RPN total loss: 0.04319 Total loss: 1.88976 timestamp: 1655019368.14082 iteration: 14175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13129 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.2166 L1 loss: 0.0000e+00 L2 loss: 1.34638 Learning rate: 0.02 Mask loss: 0.12973 RPN box loss: 0.05421 RPN score loss: 0.00616 RPN total loss: 0.06037 Total loss: 1.75309 timestamp: 1655019371.5914497 iteration: 14180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17839 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.23999 L1 loss: 0.0000e+00 L2 loss: 1.34615 Learning rate: 0.02 Mask loss: 0.18217 RPN box loss: 0.10092 RPN score loss: 0.01086 RPN total loss: 0.11179 Total loss: 1.8801 timestamp: 1655019374.8935025 iteration: 14185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07739 FastRCNN class loss: 0.04356 FastRCNN total loss: 0.12094 L1 loss: 0.0000e+00 L2 loss: 1.34592 Learning rate: 0.02 Mask loss: 0.22037 RPN box loss: 0.00517 RPN score loss: 0.00302 RPN total loss: 0.00819 Total loss: 1.69542 timestamp: 1655019378.3044107 iteration: 14190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18995 FastRCNN class loss: 0.14961 FastRCNN total loss: 0.33956 L1 loss: 0.0000e+00 L2 loss: 1.34566 Learning rate: 0.02 Mask loss: 0.21554 RPN box loss: 0.03231 RPN score loss: 0.01756 RPN total loss: 0.04987 Total loss: 1.95063 timestamp: 1655019381.6486375 iteration: 14195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19977 FastRCNN class loss: 0.15724 FastRCNN total loss: 0.357 L1 loss: 0.0000e+00 L2 loss: 1.34544 Learning rate: 0.02 Mask loss: 0.35367 RPN box loss: 0.05055 RPN score loss: 0.01418 RPN total loss: 0.06473 Total loss: 2.12085 timestamp: 1655019384.9267151 iteration: 14200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20798 FastRCNN class loss: 0.10927 FastRCNN total loss: 0.31726 L1 loss: 0.0000e+00 L2 loss: 1.34519 Learning rate: 0.02 Mask loss: 0.15587 RPN box loss: 0.03641 RPN score loss: 0.02738 RPN total loss: 0.06379 Total loss: 1.88211 timestamp: 1655019388.3148327 iteration: 14205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22491 FastRCNN class loss: 0.10632 FastRCNN total loss: 0.33123 L1 loss: 0.0000e+00 L2 loss: 1.34492 Learning rate: 0.02 Mask loss: 0.2459 RPN box loss: 0.01419 RPN score loss: 0.00731 RPN total loss: 0.02149 Total loss: 1.94353 timestamp: 1655019391.5288699 iteration: 14210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12907 FastRCNN class loss: 0.06007 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 1.34468 Learning rate: 0.02 Mask loss: 0.15506 RPN box loss: 0.03008 RPN score loss: 0.00626 RPN total loss: 0.03634 Total loss: 1.72522 timestamp: 1655019394.9740686 iteration: 14215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.05695 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 1.34445 Learning rate: 0.02 Mask loss: 0.25802 RPN box loss: 0.01444 RPN score loss: 0.00249 RPN total loss: 0.01693 Total loss: 1.78256 timestamp: 1655019398.2594578 iteration: 14220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.07015 FastRCNN total loss: 0.21064 L1 loss: 0.0000e+00 L2 loss: 1.34421 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.05141 RPN score loss: 0.00722 RPN total loss: 0.05863 Total loss: 1.76256 timestamp: 1655019401.6639862 iteration: 14225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.159 FastRCNN class loss: 0.06833 FastRCNN total loss: 0.22733 L1 loss: 0.0000e+00 L2 loss: 1.34397 Learning rate: 0.02 Mask loss: 0.15306 RPN box loss: 0.06214 RPN score loss: 0.01107 RPN total loss: 0.07322 Total loss: 1.79758 timestamp: 1655019404.9000177 iteration: 14230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18581 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.26771 L1 loss: 0.0000e+00 L2 loss: 1.34373 Learning rate: 0.02 Mask loss: 0.15368 RPN box loss: 0.01652 RPN score loss: 0.01001 RPN total loss: 0.02653 Total loss: 1.79164 timestamp: 1655019408.2428997 iteration: 14235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22528 FastRCNN class loss: 0.09284 FastRCNN total loss: 0.31813 L1 loss: 0.0000e+00 L2 loss: 1.34348 Learning rate: 0.02 Mask loss: 0.19629 RPN box loss: 0.04002 RPN score loss: 0.00815 RPN total loss: 0.04817 Total loss: 1.90607 timestamp: 1655019411.5306566 iteration: 14240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17816 FastRCNN class loss: 0.09867 FastRCNN total loss: 0.27683 L1 loss: 0.0000e+00 L2 loss: 1.34325 Learning rate: 0.02 Mask loss: 0.21694 RPN box loss: 0.04577 RPN score loss: 0.00556 RPN total loss: 0.05133 Total loss: 1.88836 timestamp: 1655019414.801143 iteration: 14245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12268 FastRCNN class loss: 0.04931 FastRCNN total loss: 0.17198 L1 loss: 0.0000e+00 L2 loss: 1.343 Learning rate: 0.02 Mask loss: 0.20967 RPN box loss: 0.03698 RPN score loss: 0.00385 RPN total loss: 0.04083 Total loss: 1.76549 timestamp: 1655019418.1753476 iteration: 14250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08683 FastRCNN class loss: 0.09152 FastRCNN total loss: 0.17834 L1 loss: 0.0000e+00 L2 loss: 1.34276 Learning rate: 0.02 Mask loss: 0.15184 RPN box loss: 0.02774 RPN score loss: 0.00826 RPN total loss: 0.036 Total loss: 1.70894 timestamp: 1655019421.4571614 iteration: 14255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20878 FastRCNN class loss: 0.07009 FastRCNN total loss: 0.27887 L1 loss: 0.0000e+00 L2 loss: 1.34255 Learning rate: 0.02 Mask loss: 0.10152 RPN box loss: 0.04268 RPN score loss: 0.00933 RPN total loss: 0.05201 Total loss: 1.77494 timestamp: 1655019424.8423965 iteration: 14260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17667 FastRCNN class loss: 0.17256 FastRCNN total loss: 0.34923 L1 loss: 0.0000e+00 L2 loss: 1.34231 Learning rate: 0.02 Mask loss: 0.24416 RPN box loss: 0.01661 RPN score loss: 0.00414 RPN total loss: 0.02075 Total loss: 1.95645 timestamp: 1655019428.0980036 iteration: 14265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09591 FastRCNN class loss: 0.09655 FastRCNN total loss: 0.19247 L1 loss: 0.0000e+00 L2 loss: 1.34207 Learning rate: 0.02 Mask loss: 0.1346 RPN box loss: 0.04706 RPN score loss: 0.03086 RPN total loss: 0.07793 Total loss: 1.74706 timestamp: 1655019431.4846647 iteration: 14270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13992 FastRCNN class loss: 0.10583 FastRCNN total loss: 0.24575 L1 loss: 0.0000e+00 L2 loss: 1.34183 Learning rate: 0.02 Mask loss: 0.1936 RPN box loss: 0.03267 RPN score loss: 0.0119 RPN total loss: 0.04457 Total loss: 1.82575 timestamp: 1655019434.813626 iteration: 14275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.21221 L1 loss: 0.0000e+00 L2 loss: 1.34159 Learning rate: 0.02 Mask loss: 0.14166 RPN box loss: 0.02402 RPN score loss: 0.00527 RPN total loss: 0.02928 Total loss: 1.72474 timestamp: 1655019438.2837002 iteration: 14280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14785 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.20417 L1 loss: 0.0000e+00 L2 loss: 1.34134 Learning rate: 0.02 Mask loss: 0.15085 RPN box loss: 0.03112 RPN score loss: 0.00867 RPN total loss: 0.03979 Total loss: 1.73616 timestamp: 1655019441.7084622 iteration: 14285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15942 FastRCNN class loss: 0.10485 FastRCNN total loss: 0.26427 L1 loss: 0.0000e+00 L2 loss: 1.3411 Learning rate: 0.02 Mask loss: 0.21271 RPN box loss: 0.03391 RPN score loss: 0.01094 RPN total loss: 0.04486 Total loss: 1.86294 timestamp: 1655019444.994268 iteration: 14290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16606 FastRCNN class loss: 0.10079 FastRCNN total loss: 0.26684 L1 loss: 0.0000e+00 L2 loss: 1.34086 Learning rate: 0.02 Mask loss: 0.19874 RPN box loss: 0.03486 RPN score loss: 0.01816 RPN total loss: 0.05303 Total loss: 1.85947 timestamp: 1655019448.476974 iteration: 14295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20838 FastRCNN class loss: 0.08665 FastRCNN total loss: 0.29503 L1 loss: 0.0000e+00 L2 loss: 1.34063 Learning rate: 0.02 Mask loss: 0.19991 RPN box loss: 0.07285 RPN score loss: 0.00631 RPN total loss: 0.07916 Total loss: 1.91473 timestamp: 1655019451.775755 iteration: 14300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10541 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.18106 L1 loss: 0.0000e+00 L2 loss: 1.34041 Learning rate: 0.02 Mask loss: 0.17672 RPN box loss: 0.06167 RPN score loss: 0.01283 RPN total loss: 0.0745 Total loss: 1.77268 timestamp: 1655019455.1479366 iteration: 14305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13535 FastRCNN class loss: 0.08592 FastRCNN total loss: 0.22127 L1 loss: 0.0000e+00 L2 loss: 1.34016 Learning rate: 0.02 Mask loss: 0.13718 RPN box loss: 0.01569 RPN score loss: 0.00415 RPN total loss: 0.01984 Total loss: 1.71845 timestamp: 1655019458.4292274 iteration: 14310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14377 FastRCNN class loss: 0.10258 FastRCNN total loss: 0.24636 L1 loss: 0.0000e+00 L2 loss: 1.33991 Learning rate: 0.02 Mask loss: 0.17893 RPN box loss: 0.10397 RPN score loss: 0.00883 RPN total loss: 0.1128 Total loss: 1.87799 timestamp: 1655019461.8397212 iteration: 14315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16739 FastRCNN class loss: 0.13457 FastRCNN total loss: 0.30196 L1 loss: 0.0000e+00 L2 loss: 1.33965 Learning rate: 0.02 Mask loss: 0.19331 RPN box loss: 0.07817 RPN score loss: 0.01041 RPN total loss: 0.08858 Total loss: 1.9235 timestamp: 1655019465.0659385 iteration: 14320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2204 FastRCNN class loss: 0.10922 FastRCNN total loss: 0.32962 L1 loss: 0.0000e+00 L2 loss: 1.33942 Learning rate: 0.02 Mask loss: 0.17447 RPN box loss: 0.06059 RPN score loss: 0.02663 RPN total loss: 0.08723 Total loss: 1.93074 timestamp: 1655019468.4610262 iteration: 14325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18465 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.24766 L1 loss: 0.0000e+00 L2 loss: 1.33919 Learning rate: 0.02 Mask loss: 0.12857 RPN box loss: 0.0505 RPN score loss: 0.03482 RPN total loss: 0.08532 Total loss: 1.80073 timestamp: 1655019471.9866824 iteration: 14330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16675 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.25522 L1 loss: 0.0000e+00 L2 loss: 1.33893 Learning rate: 0.02 Mask loss: 0.17386 RPN box loss: 0.04721 RPN score loss: 0.0044 RPN total loss: 0.05161 Total loss: 1.81963 timestamp: 1655019475.291231 iteration: 14335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17259 FastRCNN class loss: 0.07554 FastRCNN total loss: 0.24813 L1 loss: 0.0000e+00 L2 loss: 1.33867 Learning rate: 0.02 Mask loss: 0.16701 RPN box loss: 0.05995 RPN score loss: 0.00798 RPN total loss: 0.06794 Total loss: 1.82175 timestamp: 1655019478.5983412 iteration: 14340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18924 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.25869 L1 loss: 0.0000e+00 L2 loss: 1.33843 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.01657 RPN score loss: 0.00445 RPN total loss: 0.02102 Total loss: 1.77057 timestamp: 1655019481.9223466 iteration: 14345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1115 FastRCNN class loss: 0.08517 FastRCNN total loss: 0.19667 L1 loss: 0.0000e+00 L2 loss: 1.33819 Learning rate: 0.02 Mask loss: 0.12584 RPN box loss: 0.03543 RPN score loss: 0.0036 RPN total loss: 0.03903 Total loss: 1.69973 timestamp: 1655019485.2996387 iteration: 14350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30764 FastRCNN class loss: 0.17851 FastRCNN total loss: 0.48615 L1 loss: 0.0000e+00 L2 loss: 1.33795 Learning rate: 0.02 Mask loss: 0.27563 RPN box loss: 0.04064 RPN score loss: 0.01596 RPN total loss: 0.0566 Total loss: 2.15633 timestamp: 1655019488.6270401 iteration: 14355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14558 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.21776 L1 loss: 0.0000e+00 L2 loss: 1.33773 Learning rate: 0.02 Mask loss: 0.20502 RPN box loss: 0.03285 RPN score loss: 0.00359 RPN total loss: 0.03643 Total loss: 1.79695 timestamp: 1655019491.9755924 iteration: 14360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11356 FastRCNN class loss: 0.06133 FastRCNN total loss: 0.1749 L1 loss: 0.0000e+00 L2 loss: 1.33752 Learning rate: 0.02 Mask loss: 0.12358 RPN box loss: 0.03516 RPN score loss: 0.00438 RPN total loss: 0.03954 Total loss: 1.67554 timestamp: 1655019495.3970706 iteration: 14365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16388 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.21922 L1 loss: 0.0000e+00 L2 loss: 1.33727 Learning rate: 0.02 Mask loss: 0.14903 RPN box loss: 0.03133 RPN score loss: 0.00471 RPN total loss: 0.03604 Total loss: 1.74155 timestamp: 1655019498.6013756 iteration: 14370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16409 FastRCNN class loss: 0.13506 FastRCNN total loss: 0.29915 L1 loss: 0.0000e+00 L2 loss: 1.337 Learning rate: 0.02 Mask loss: 0.21296 RPN box loss: 0.02718 RPN score loss: 0.00367 RPN total loss: 0.03085 Total loss: 1.87997 timestamp: 1655019501.8612552 iteration: 14375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29734 FastRCNN class loss: 0.1131 FastRCNN total loss: 0.41044 L1 loss: 0.0000e+00 L2 loss: 1.33675 Learning rate: 0.02 Mask loss: 0.21184 RPN box loss: 0.04469 RPN score loss: 0.00873 RPN total loss: 0.05343 Total loss: 2.01246 timestamp: 1655019505.2141888 iteration: 14380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17578 FastRCNN class loss: 0.09946 FastRCNN total loss: 0.27524 L1 loss: 0.0000e+00 L2 loss: 1.33653 Learning rate: 0.02 Mask loss: 0.16243 RPN box loss: 0.08125 RPN score loss: 0.00928 RPN total loss: 0.09053 Total loss: 1.86473 timestamp: 1655019508.592602 iteration: 14385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1876 FastRCNN class loss: 0.0867 FastRCNN total loss: 0.2743 L1 loss: 0.0000e+00 L2 loss: 1.33628 Learning rate: 0.02 Mask loss: 0.17049 RPN box loss: 0.03642 RPN score loss: 0.0063 RPN total loss: 0.04272 Total loss: 1.82379 timestamp: 1655019511.9401896 iteration: 14390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13848 FastRCNN class loss: 0.08384 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 1.33603 Learning rate: 0.02 Mask loss: 0.14053 RPN box loss: 0.04066 RPN score loss: 0.0062 RPN total loss: 0.04687 Total loss: 1.74574 timestamp: 1655019515.4105117 iteration: 14395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19799 FastRCNN class loss: 0.1304 FastRCNN total loss: 0.32838 L1 loss: 0.0000e+00 L2 loss: 1.33583 Learning rate: 0.02 Mask loss: 0.2656 RPN box loss: 0.04687 RPN score loss: 0.01288 RPN total loss: 0.05975 Total loss: 1.98956 timestamp: 1655019518.7380304 iteration: 14400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12578 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.21533 L1 loss: 0.0000e+00 L2 loss: 1.33559 Learning rate: 0.02 Mask loss: 0.13742 RPN box loss: 0.03757 RPN score loss: 0.01582 RPN total loss: 0.05339 Total loss: 1.74173 timestamp: 1655019522.0236096 iteration: 14405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14166 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.22902 L1 loss: 0.0000e+00 L2 loss: 1.33536 Learning rate: 0.02 Mask loss: 0.31952 RPN box loss: 0.01581 RPN score loss: 0.0049 RPN total loss: 0.02071 Total loss: 1.90461 timestamp: 1655019525.3895872 iteration: 14410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19248 FastRCNN class loss: 0.13624 FastRCNN total loss: 0.32872 L1 loss: 0.0000e+00 L2 loss: 1.33513 Learning rate: 0.02 Mask loss: 0.1992 RPN box loss: 0.04265 RPN score loss: 0.00999 RPN total loss: 0.05264 Total loss: 1.91569 timestamp: 1655019528.6229753 iteration: 14415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17069 FastRCNN class loss: 0.13001 FastRCNN total loss: 0.3007 L1 loss: 0.0000e+00 L2 loss: 1.33488 Learning rate: 0.02 Mask loss: 0.25323 RPN box loss: 0.05729 RPN score loss: 0.0163 RPN total loss: 0.07359 Total loss: 1.9624 timestamp: 1655019531.998857 iteration: 14420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14168 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.21278 L1 loss: 0.0000e+00 L2 loss: 1.33466 Learning rate: 0.02 Mask loss: 0.16631 RPN box loss: 0.02843 RPN score loss: 0.00214 RPN total loss: 0.03056 Total loss: 1.74432 timestamp: 1655019535.2788668 iteration: 14425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.187 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.2828 L1 loss: 0.0000e+00 L2 loss: 1.33442 Learning rate: 0.02 Mask loss: 0.16017 RPN box loss: 0.0277 RPN score loss: 0.01351 RPN total loss: 0.04122 Total loss: 1.81861 timestamp: 1655019538.6490529 iteration: 14430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23097 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.30538 L1 loss: 0.0000e+00 L2 loss: 1.33418 Learning rate: 0.02 Mask loss: 0.14332 RPN box loss: 0.03204 RPN score loss: 0.01049 RPN total loss: 0.04252 Total loss: 1.82541 timestamp: 1655019541.974504 iteration: 14435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20962 FastRCNN class loss: 0.11694 FastRCNN total loss: 0.32657 L1 loss: 0.0000e+00 L2 loss: 1.33395 Learning rate: 0.02 Mask loss: 0.20859 RPN box loss: 0.0576 RPN score loss: 0.01701 RPN total loss: 0.07461 Total loss: 1.94371 timestamp: 1655019545.3092647 iteration: 14440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1459 FastRCNN class loss: 0.10631 FastRCNN total loss: 0.2522 L1 loss: 0.0000e+00 L2 loss: 1.3337 Learning rate: 0.02 Mask loss: 0.2091 RPN box loss: 0.05 RPN score loss: 0.01569 RPN total loss: 0.06568 Total loss: 1.86068 timestamp: 1655019548.5964022 iteration: 14445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1678 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.26392 L1 loss: 0.0000e+00 L2 loss: 1.33347 Learning rate: 0.02 Mask loss: 0.21971 RPN box loss: 0.04528 RPN score loss: 0.01052 RPN total loss: 0.05579 Total loss: 1.8729 timestamp: 1655019551.9489639 iteration: 14450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16368 FastRCNN class loss: 0.14416 FastRCNN total loss: 0.30784 L1 loss: 0.0000e+00 L2 loss: 1.33326 Learning rate: 0.02 Mask loss: 0.19224 RPN box loss: 0.04468 RPN score loss: 0.01629 RPN total loss: 0.06097 Total loss: 1.8943 timestamp: 1655019555.3520525 iteration: 14455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17098 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.22855 L1 loss: 0.0000e+00 L2 loss: 1.33301 Learning rate: 0.02 Mask loss: 0.21886 RPN box loss: 0.05907 RPN score loss: 0.02024 RPN total loss: 0.07931 Total loss: 1.85972 timestamp: 1655019558.640749 iteration: 14460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18029 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.26068 L1 loss: 0.0000e+00 L2 loss: 1.33278 Learning rate: 0.02 Mask loss: 0.18319 RPN box loss: 0.03337 RPN score loss: 0.00286 RPN total loss: 0.03623 Total loss: 1.81287 timestamp: 1655019562.000697 iteration: 14465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14526 FastRCNN class loss: 0.07299 FastRCNN total loss: 0.21825 L1 loss: 0.0000e+00 L2 loss: 1.33254 Learning rate: 0.02 Mask loss: 0.17171 RPN box loss: 0.10775 RPN score loss: 0.00369 RPN total loss: 0.11144 Total loss: 1.83394 timestamp: 1655019565.3411307 iteration: 14470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24162 FastRCNN class loss: 0.16634 FastRCNN total loss: 0.40796 L1 loss: 0.0000e+00 L2 loss: 1.33229 Learning rate: 0.02 Mask loss: 0.27509 RPN box loss: 0.02257 RPN score loss: 0.00933 RPN total loss: 0.0319 Total loss: 2.04724 timestamp: 1655019568.7570581 iteration: 14475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21811 FastRCNN class loss: 0.12952 FastRCNN total loss: 0.34763 L1 loss: 0.0000e+00 L2 loss: 1.33204 Learning rate: 0.02 Mask loss: 0.19452 RPN box loss: 0.02248 RPN score loss: 0.01297 RPN total loss: 0.03545 Total loss: 1.90964 timestamp: 1655019571.9687886 iteration: 14480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22172 FastRCNN class loss: 0.10925 FastRCNN total loss: 0.33097 L1 loss: 0.0000e+00 L2 loss: 1.33181 Learning rate: 0.02 Mask loss: 0.23155 RPN box loss: 0.02639 RPN score loss: 0.01386 RPN total loss: 0.04025 Total loss: 1.93458 timestamp: 1655019575.2679315 iteration: 14485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1217 FastRCNN class loss: 0.0532 FastRCNN total loss: 0.1749 L1 loss: 0.0000e+00 L2 loss: 1.33156 Learning rate: 0.02 Mask loss: 0.1008 RPN box loss: 0.01319 RPN score loss: 0.00425 RPN total loss: 0.01744 Total loss: 1.62469 timestamp: 1655019578.5578136 iteration: 14490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09279 FastRCNN class loss: 0.05361 FastRCNN total loss: 0.1464 L1 loss: 0.0000e+00 L2 loss: 1.33134 Learning rate: 0.02 Mask loss: 0.10183 RPN box loss: 0.10834 RPN score loss: 0.00582 RPN total loss: 0.11416 Total loss: 1.69374 timestamp: 1655019581.9660969 iteration: 14495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12263 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.17009 L1 loss: 0.0000e+00 L2 loss: 1.33112 Learning rate: 0.02 Mask loss: 0.14231 RPN box loss: 0.087 RPN score loss: 0.00588 RPN total loss: 0.09288 Total loss: 1.73639 timestamp: 1655019585.4328468 iteration: 14500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16017 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.23867 L1 loss: 0.0000e+00 L2 loss: 1.33089 Learning rate: 0.02 Mask loss: 0.14582 RPN box loss: 0.04616 RPN score loss: 0.00376 RPN total loss: 0.04992 Total loss: 1.7653 timestamp: 1655019588.6726267 iteration: 14505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18362 FastRCNN class loss: 0.15118 FastRCNN total loss: 0.3348 L1 loss: 0.0000e+00 L2 loss: 1.33065 Learning rate: 0.02 Mask loss: 0.27859 RPN box loss: 0.01633 RPN score loss: 0.00498 RPN total loss: 0.02131 Total loss: 1.96535 timestamp: 1655019592.0629184 iteration: 14510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22471 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.30714 L1 loss: 0.0000e+00 L2 loss: 1.33041 Learning rate: 0.02 Mask loss: 0.3015 RPN box loss: 0.02367 RPN score loss: 0.00243 RPN total loss: 0.0261 Total loss: 1.96515 timestamp: 1655019595.386139 iteration: 14515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16902 FastRCNN class loss: 0.10542 FastRCNN total loss: 0.27445 L1 loss: 0.0000e+00 L2 loss: 1.33017 Learning rate: 0.02 Mask loss: 0.23697 RPN box loss: 0.04862 RPN score loss: 0.00545 RPN total loss: 0.05407 Total loss: 1.89566 timestamp: 1655019598.8456645 iteration: 14520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20734 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.28447 L1 loss: 0.0000e+00 L2 loss: 1.32992 Learning rate: 0.02 Mask loss: 0.17302 RPN box loss: 0.04828 RPN score loss: 0.01117 RPN total loss: 0.05945 Total loss: 1.84687 timestamp: 1655019602.1837134 iteration: 14525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13784 FastRCNN class loss: 0.09872 FastRCNN total loss: 0.23656 L1 loss: 0.0000e+00 L2 loss: 1.3297 Learning rate: 0.02 Mask loss: 0.19814 RPN box loss: 0.02113 RPN score loss: 0.01022 RPN total loss: 0.03135 Total loss: 1.79575 timestamp: 1655019605.5071623 iteration: 14530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15337 FastRCNN class loss: 0.04951 FastRCNN total loss: 0.20289 L1 loss: 0.0000e+00 L2 loss: 1.32949 Learning rate: 0.02 Mask loss: 0.0914 RPN box loss: 0.01006 RPN score loss: 0.00264 RPN total loss: 0.0127 Total loss: 1.63647 timestamp: 1655019608.808546 iteration: 14535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15882 FastRCNN class loss: 0.09172 FastRCNN total loss: 0.25054 L1 loss: 0.0000e+00 L2 loss: 1.32923 Learning rate: 0.02 Mask loss: 0.1613 RPN box loss: 0.02188 RPN score loss: 0.00577 RPN total loss: 0.02765 Total loss: 1.76873 timestamp: 1655019612.147138 iteration: 14540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16803 FastRCNN class loss: 0.13359 FastRCNN total loss: 0.30163 L1 loss: 0.0000e+00 L2 loss: 1.329 Learning rate: 0.02 Mask loss: 0.24696 RPN box loss: 0.05893 RPN score loss: 0.03596 RPN total loss: 0.0949 Total loss: 1.97249 timestamp: 1655019615.4765751 iteration: 14545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18413 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.2776 L1 loss: 0.0000e+00 L2 loss: 1.32877 Learning rate: 0.02 Mask loss: 0.1491 RPN box loss: 0.01944 RPN score loss: 0.00817 RPN total loss: 0.0276 Total loss: 1.78307 timestamp: 1655019618.768003 iteration: 14550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19394 FastRCNN class loss: 0.06674 FastRCNN total loss: 0.26069 L1 loss: 0.0000e+00 L2 loss: 1.32852 Learning rate: 0.02 Mask loss: 0.16783 RPN box loss: 0.01972 RPN score loss: 0.00574 RPN total loss: 0.02546 Total loss: 1.7825 timestamp: 1655019622.2113616 iteration: 14555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16034 FastRCNN class loss: 0.12211 FastRCNN total loss: 0.28245 L1 loss: 0.0000e+00 L2 loss: 1.32831 Learning rate: 0.02 Mask loss: 0.15518 RPN box loss: 0.02957 RPN score loss: 0.00406 RPN total loss: 0.03362 Total loss: 1.79957 timestamp: 1655019625.4815614 iteration: 14560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28208 FastRCNN class loss: 0.16353 FastRCNN total loss: 0.44561 L1 loss: 0.0000e+00 L2 loss: 1.3281 Learning rate: 0.02 Mask loss: 0.24661 RPN box loss: 0.09036 RPN score loss: 0.01758 RPN total loss: 0.10793 Total loss: 2.12825 timestamp: 1655019628.893247 iteration: 14565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12036 FastRCNN class loss: 0.12359 FastRCNN total loss: 0.24395 L1 loss: 0.0000e+00 L2 loss: 1.32785 Learning rate: 0.02 Mask loss: 0.22028 RPN box loss: 0.04587 RPN score loss: 0.02086 RPN total loss: 0.06673 Total loss: 1.85881 timestamp: 1655019632.2140625 iteration: 14570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15042 FastRCNN class loss: 0.07918 FastRCNN total loss: 0.2296 L1 loss: 0.0000e+00 L2 loss: 1.32761 Learning rate: 0.02 Mask loss: 0.12386 RPN box loss: 0.06953 RPN score loss: 0.01217 RPN total loss: 0.08169 Total loss: 1.76277 timestamp: 1655019635.531421 iteration: 14575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11894 FastRCNN class loss: 0.08002 FastRCNN total loss: 0.19896 L1 loss: 0.0000e+00 L2 loss: 1.32738 Learning rate: 0.02 Mask loss: 0.18846 RPN box loss: 0.02425 RPN score loss: 0.00833 RPN total loss: 0.03258 Total loss: 1.74738 timestamp: 1655019638.8277225 iteration: 14580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16463 FastRCNN class loss: 0.09531 FastRCNN total loss: 0.25994 L1 loss: 0.0000e+00 L2 loss: 1.32715 Learning rate: 0.02 Mask loss: 0.17693 RPN box loss: 0.04159 RPN score loss: 0.00599 RPN total loss: 0.04758 Total loss: 1.8116 timestamp: 1655019642.1732874 iteration: 14585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08692 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.1478 L1 loss: 0.0000e+00 L2 loss: 1.32694 Learning rate: 0.02 Mask loss: 0.12123 RPN box loss: 0.00255 RPN score loss: 0.003 RPN total loss: 0.00555 Total loss: 1.60151 timestamp: 1655019645.5749345 iteration: 14590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09882 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.14907 L1 loss: 0.0000e+00 L2 loss: 1.3267 Learning rate: 0.02 Mask loss: 0.13299 RPN box loss: 0.01265 RPN score loss: 0.00691 RPN total loss: 0.01956 Total loss: 1.62832 timestamp: 1655019648.812181 iteration: 14595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14922 FastRCNN class loss: 0.10556 FastRCNN total loss: 0.25477 L1 loss: 0.0000e+00 L2 loss: 1.32645 Learning rate: 0.02 Mask loss: 0.19192 RPN box loss: 0.02485 RPN score loss: 0.00335 RPN total loss: 0.0282 Total loss: 1.80135 timestamp: 1655019652.2414765 iteration: 14600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11406 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.19463 L1 loss: 0.0000e+00 L2 loss: 1.32621 Learning rate: 0.02 Mask loss: 0.15036 RPN box loss: 0.03133 RPN score loss: 0.00839 RPN total loss: 0.03973 Total loss: 1.71093 timestamp: 1655019655.492997 iteration: 14605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1569 FastRCNN class loss: 0.10598 FastRCNN total loss: 0.26288 L1 loss: 0.0000e+00 L2 loss: 1.326 Learning rate: 0.02 Mask loss: 0.19245 RPN box loss: 0.07295 RPN score loss: 0.01385 RPN total loss: 0.08681 Total loss: 1.86813 timestamp: 1655019658.9226336 iteration: 14610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14344 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.22577 L1 loss: 0.0000e+00 L2 loss: 1.32577 Learning rate: 0.02 Mask loss: 0.1564 RPN box loss: 0.01469 RPN score loss: 0.02196 RPN total loss: 0.03665 Total loss: 1.7446 timestamp: 1655019662.2284887 iteration: 14615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17463 FastRCNN class loss: 0.10493 FastRCNN total loss: 0.27956 L1 loss: 0.0000e+00 L2 loss: 1.32553 Learning rate: 0.02 Mask loss: 0.23722 RPN box loss: 0.04015 RPN score loss: 0.01048 RPN total loss: 0.05063 Total loss: 1.89294 timestamp: 1655019665.5533116 iteration: 14620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1902 FastRCNN class loss: 0.12876 FastRCNN total loss: 0.31896 L1 loss: 0.0000e+00 L2 loss: 1.32527 Learning rate: 0.02 Mask loss: 0.21166 RPN box loss: 0.03232 RPN score loss: 0.00566 RPN total loss: 0.03798 Total loss: 1.89386 timestamp: 1655019668.8443344 iteration: 14625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19503 FastRCNN class loss: 0.1389 FastRCNN total loss: 0.33393 L1 loss: 0.0000e+00 L2 loss: 1.32504 Learning rate: 0.02 Mask loss: 0.17558 RPN box loss: 0.04822 RPN score loss: 0.00509 RPN total loss: 0.05331 Total loss: 1.88786 timestamp: 1655019672.2418983 iteration: 14630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16504 FastRCNN class loss: 0.08677 FastRCNN total loss: 0.25181 L1 loss: 0.0000e+00 L2 loss: 1.32481 Learning rate: 0.02 Mask loss: 0.21418 RPN box loss: 0.03957 RPN score loss: 0.01367 RPN total loss: 0.05324 Total loss: 1.84405 timestamp: 1655019675.6729984 iteration: 14635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16765 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.25129 L1 loss: 0.0000e+00 L2 loss: 1.32457 Learning rate: 0.02 Mask loss: 0.20161 RPN box loss: 0.05627 RPN score loss: 0.00832 RPN total loss: 0.06459 Total loss: 1.84206 timestamp: 1655019678.8849046 iteration: 14640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14733 FastRCNN class loss: 0.10662 FastRCNN total loss: 0.25395 L1 loss: 0.0000e+00 L2 loss: 1.32434 Learning rate: 0.02 Mask loss: 0.14748 RPN box loss: 0.03047 RPN score loss: 0.00716 RPN total loss: 0.03762 Total loss: 1.7634 timestamp: 1655019682.2739627 iteration: 14645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14372 FastRCNN class loss: 0.12322 FastRCNN total loss: 0.26694 L1 loss: 0.0000e+00 L2 loss: 1.32412 Learning rate: 0.02 Mask loss: 0.16404 RPN box loss: 0.04047 RPN score loss: 0.00359 RPN total loss: 0.04406 Total loss: 1.79915 timestamp: 1655019685.625051 iteration: 14650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17586 FastRCNN class loss: 0.09125 FastRCNN total loss: 0.26711 L1 loss: 0.0000e+00 L2 loss: 1.32387 Learning rate: 0.02 Mask loss: 0.14064 RPN box loss: 0.05026 RPN score loss: 0.00764 RPN total loss: 0.0579 Total loss: 1.78952 timestamp: 1655019688.9797692 iteration: 14655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13109 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.20428 L1 loss: 0.0000e+00 L2 loss: 1.32364 Learning rate: 0.02 Mask loss: 0.17938 RPN box loss: 0.00974 RPN score loss: 0.00385 RPN total loss: 0.01359 Total loss: 1.72089 timestamp: 1655019692.280985 iteration: 14660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18998 FastRCNN class loss: 0.16252 FastRCNN total loss: 0.3525 L1 loss: 0.0000e+00 L2 loss: 1.32341 Learning rate: 0.02 Mask loss: 0.14129 RPN box loss: 0.05141 RPN score loss: 0.01067 RPN total loss: 0.06208 Total loss: 1.87928 timestamp: 1655019695.6604583 iteration: 14665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15651 FastRCNN class loss: 0.15161 FastRCNN total loss: 0.30812 L1 loss: 0.0000e+00 L2 loss: 1.32318 Learning rate: 0.02 Mask loss: 0.18108 RPN box loss: 0.04359 RPN score loss: 0.01015 RPN total loss: 0.05374 Total loss: 1.86612 timestamp: 1655019698.8803911 iteration: 14670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06557 FastRCNN class loss: 0.03426 FastRCNN total loss: 0.09983 L1 loss: 0.0000e+00 L2 loss: 1.32294 Learning rate: 0.02 Mask loss: 0.12711 RPN box loss: 0.03149 RPN score loss: 0.00214 RPN total loss: 0.03362 Total loss: 1.58351 timestamp: 1655019702.396543 iteration: 14675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18556 FastRCNN class loss: 0.13997 FastRCNN total loss: 0.32553 L1 loss: 0.0000e+00 L2 loss: 1.32269 Learning rate: 0.02 Mask loss: 0.19248 RPN box loss: 0.05357 RPN score loss: 0.00923 RPN total loss: 0.0628 Total loss: 1.90351 timestamp: 1655019705.8014264 iteration: 14680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23412 FastRCNN class loss: 0.1161 FastRCNN total loss: 0.35023 L1 loss: 0.0000e+00 L2 loss: 1.32246 Learning rate: 0.02 Mask loss: 0.18979 RPN box loss: 0.1167 RPN score loss: 0.01116 RPN total loss: 0.12786 Total loss: 1.99035 timestamp: 1655019709.081568 iteration: 14685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1607 FastRCNN class loss: 0.13314 FastRCNN total loss: 0.29384 L1 loss: 0.0000e+00 L2 loss: 1.32224 Learning rate: 0.02 Mask loss: 0.25176 RPN box loss: 0.04493 RPN score loss: 0.01423 RPN total loss: 0.05916 Total loss: 1.927 timestamp: 1655019712.5170312 iteration: 14690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08824 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.1517 L1 loss: 0.0000e+00 L2 loss: 1.322 Learning rate: 0.02 Mask loss: 0.14873 RPN box loss: 0.04463 RPN score loss: 0.00989 RPN total loss: 0.05453 Total loss: 1.67696 timestamp: 1655019715.8046646 iteration: 14695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15438 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.24923 L1 loss: 0.0000e+00 L2 loss: 1.32178 Learning rate: 0.02 Mask loss: 0.17383 RPN box loss: 0.04555 RPN score loss: 0.0072 RPN total loss: 0.05276 Total loss: 1.7976 timestamp: 1655019719.212686 iteration: 14700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30038 FastRCNN class loss: 0.1922 FastRCNN total loss: 0.49259 L1 loss: 0.0000e+00 L2 loss: 1.32155 Learning rate: 0.02 Mask loss: 0.23076 RPN box loss: 0.06386 RPN score loss: 0.02739 RPN total loss: 0.09125 Total loss: 2.13614 timestamp: 1655019722.4949067 iteration: 14705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12647 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.18565 L1 loss: 0.0000e+00 L2 loss: 1.32131 Learning rate: 0.02 Mask loss: 0.16126 RPN box loss: 0.02333 RPN score loss: 0.00508 RPN total loss: 0.02841 Total loss: 1.69664 timestamp: 1655019725.8273559 iteration: 14710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14621 FastRCNN class loss: 0.11596 FastRCNN total loss: 0.26217 L1 loss: 0.0000e+00 L2 loss: 1.32106 Learning rate: 0.02 Mask loss: 0.16649 RPN box loss: 0.07072 RPN score loss: 0.02983 RPN total loss: 0.10055 Total loss: 1.85026 timestamp: 1655019729.1415074 iteration: 14715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.06925 FastRCNN total loss: 0.18051 L1 loss: 0.0000e+00 L2 loss: 1.32081 Learning rate: 0.02 Mask loss: 0.19768 RPN box loss: 0.03042 RPN score loss: 0.00786 RPN total loss: 0.03828 Total loss: 1.73728 timestamp: 1655019732.6222699 iteration: 14720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12831 FastRCNN class loss: 0.06913 FastRCNN total loss: 0.19744 L1 loss: 0.0000e+00 L2 loss: 1.32058 Learning rate: 0.02 Mask loss: 0.1696 RPN box loss: 0.05021 RPN score loss: 0.01612 RPN total loss: 0.06633 Total loss: 1.75394 timestamp: 1655019736.0258837 iteration: 14725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19709 FastRCNN class loss: 0.08987 FastRCNN total loss: 0.28695 L1 loss: 0.0000e+00 L2 loss: 1.32035 Learning rate: 0.02 Mask loss: 0.16849 RPN box loss: 0.03069 RPN score loss: 0.0088 RPN total loss: 0.0395 Total loss: 1.81529 timestamp: 1655019739.3761983 iteration: 14730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16391 FastRCNN class loss: 0.15345 FastRCNN total loss: 0.31737 L1 loss: 0.0000e+00 L2 loss: 1.32011 Learning rate: 0.02 Mask loss: 0.22454 RPN box loss: 0.04963 RPN score loss: 0.01817 RPN total loss: 0.06779 Total loss: 1.92981 timestamp: 1655019742.8043473 iteration: 14735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.14185 L1 loss: 0.0000e+00 L2 loss: 1.31985 Learning rate: 0.02 Mask loss: 0.16164 RPN box loss: 0.01493 RPN score loss: 0.00518 RPN total loss: 0.02011 Total loss: 1.64344 timestamp: 1655019746.0115628 iteration: 14740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18386 FastRCNN class loss: 0.09557 FastRCNN total loss: 0.27944 L1 loss: 0.0000e+00 L2 loss: 1.3196 Learning rate: 0.02 Mask loss: 0.1626 RPN box loss: 0.05815 RPN score loss: 0.00835 RPN total loss: 0.06649 Total loss: 1.82813 timestamp: 1655019749.36305 iteration: 14745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13203 FastRCNN class loss: 0.08827 FastRCNN total loss: 0.22031 L1 loss: 0.0000e+00 L2 loss: 1.31937 Learning rate: 0.02 Mask loss: 0.18429 RPN box loss: 0.04326 RPN score loss: 0.00612 RPN total loss: 0.04938 Total loss: 1.77335 timestamp: 1655019752.6280687 iteration: 14750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16879 FastRCNN class loss: 0.1009 FastRCNN total loss: 0.2697 L1 loss: 0.0000e+00 L2 loss: 1.31914 Learning rate: 0.02 Mask loss: 0.1431 RPN box loss: 0.03842 RPN score loss: 0.00405 RPN total loss: 0.04246 Total loss: 1.7744 timestamp: 1655019756.0536005 iteration: 14755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.10207 FastRCNN total loss: 0.22104 L1 loss: 0.0000e+00 L2 loss: 1.31892 Learning rate: 0.02 Mask loss: 0.241 RPN box loss: 0.0324 RPN score loss: 0.02007 RPN total loss: 0.05247 Total loss: 1.83342 timestamp: 1655019759.320197 iteration: 14760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16681 FastRCNN class loss: 0.10319 FastRCNN total loss: 0.26999 L1 loss: 0.0000e+00 L2 loss: 1.31871 Learning rate: 0.02 Mask loss: 0.26071 RPN box loss: 0.03219 RPN score loss: 0.00652 RPN total loss: 0.03871 Total loss: 1.88813 timestamp: 1655019762.7541506 iteration: 14765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1224 FastRCNN class loss: 0.0736 FastRCNN total loss: 0.196 L1 loss: 0.0000e+00 L2 loss: 1.31848 Learning rate: 0.02 Mask loss: 0.11562 RPN box loss: 0.01976 RPN score loss: 0.00788 RPN total loss: 0.02764 Total loss: 1.65773 timestamp: 1655019766.0552933 iteration: 14770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16503 FastRCNN class loss: 0.15907 FastRCNN total loss: 0.3241 L1 loss: 0.0000e+00 L2 loss: 1.31824 Learning rate: 0.02 Mask loss: 0.24397 RPN box loss: 0.05384 RPN score loss: 0.01067 RPN total loss: 0.06451 Total loss: 1.95082 timestamp: 1655019769.2853956 iteration: 14775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24465 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.34212 L1 loss: 0.0000e+00 L2 loss: 1.31801 Learning rate: 0.02 Mask loss: 0.32485 RPN box loss: 0.06359 RPN score loss: 0.00878 RPN total loss: 0.07236 Total loss: 2.05734 timestamp: 1655019772.7537062 iteration: 14780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14863 FastRCNN class loss: 0.09726 FastRCNN total loss: 0.2459 L1 loss: 0.0000e+00 L2 loss: 1.31773 Learning rate: 0.02 Mask loss: 0.15893 RPN box loss: 0.01689 RPN score loss: 0.01927 RPN total loss: 0.03616 Total loss: 1.75872 timestamp: 1655019776.0021765 iteration: 14785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.168 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.23935 L1 loss: 0.0000e+00 L2 loss: 1.31751 Learning rate: 0.02 Mask loss: 0.1863 RPN box loss: 0.11384 RPN score loss: 0.00854 RPN total loss: 0.12239 Total loss: 1.86554 timestamp: 1655019779.4790812 iteration: 14790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12752 FastRCNN class loss: 0.07122 FastRCNN total loss: 0.19874 L1 loss: 0.0000e+00 L2 loss: 1.3173 Learning rate: 0.02 Mask loss: 0.18983 RPN box loss: 0.03483 RPN score loss: 0.0058 RPN total loss: 0.04063 Total loss: 1.74649 timestamp: 1655019782.8005548 iteration: 14795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14929 FastRCNN class loss: 0.10326 FastRCNN total loss: 0.25255 L1 loss: 0.0000e+00 L2 loss: 1.31709 Learning rate: 0.02 Mask loss: 0.21318 RPN box loss: 0.01979 RPN score loss: 0.00523 RPN total loss: 0.02502 Total loss: 1.80784 timestamp: 1655019786.203831 iteration: 14800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19845 FastRCNN class loss: 0.10587 FastRCNN total loss: 0.30432 L1 loss: 0.0000e+00 L2 loss: 1.31683 Learning rate: 0.02 Mask loss: 0.20048 RPN box loss: 0.05332 RPN score loss: 0.01248 RPN total loss: 0.0658 Total loss: 1.88743 timestamp: 1655019789.483997 iteration: 14805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17223 FastRCNN class loss: 0.10644 FastRCNN total loss: 0.27867 L1 loss: 0.0000e+00 L2 loss: 1.3166 Learning rate: 0.02 Mask loss: 0.19619 RPN box loss: 0.07702 RPN score loss: 0.00871 RPN total loss: 0.08573 Total loss: 1.87719 timestamp: 1655019792.9308217 iteration: 14810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19157 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.28151 L1 loss: 0.0000e+00 L2 loss: 1.31635 Learning rate: 0.02 Mask loss: 0.14538 RPN box loss: 0.01929 RPN score loss: 0.01193 RPN total loss: 0.03122 Total loss: 1.77446 timestamp: 1655019796.2826924 iteration: 14815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12826 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.19064 L1 loss: 0.0000e+00 L2 loss: 1.31613 Learning rate: 0.02 Mask loss: 0.14132 RPN box loss: 0.045 RPN score loss: 0.01402 RPN total loss: 0.05902 Total loss: 1.70711 timestamp: 1655019799.673778 iteration: 14820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07853 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 1.31592 Learning rate: 0.02 Mask loss: 0.12111 RPN box loss: 0.02262 RPN score loss: 0.00593 RPN total loss: 0.02854 Total loss: 1.60022 timestamp: 1655019803.114232 iteration: 14825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22009 FastRCNN class loss: 0.15169 FastRCNN total loss: 0.37178 L1 loss: 0.0000e+00 L2 loss: 1.31569 Learning rate: 0.02 Mask loss: 0.28464 RPN box loss: 0.12862 RPN score loss: 0.01445 RPN total loss: 0.14307 Total loss: 2.11518 timestamp: 1655019806.4295897 iteration: 14830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17912 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.24487 L1 loss: 0.0000e+00 L2 loss: 1.31547 Learning rate: 0.02 Mask loss: 0.15184 RPN box loss: 0.01232 RPN score loss: 0.00385 RPN total loss: 0.01618 Total loss: 1.72835 timestamp: 1655019809.8793948 iteration: 14835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15685 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.25419 L1 loss: 0.0000e+00 L2 loss: 1.31523 Learning rate: 0.02 Mask loss: 0.15014 RPN box loss: 0.04956 RPN score loss: 0.01193 RPN total loss: 0.06149 Total loss: 1.78106 timestamp: 1655019813.1219501 iteration: 14840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12704 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.18662 L1 loss: 0.0000e+00 L2 loss: 1.315 Learning rate: 0.02 Mask loss: 0.13589 RPN box loss: 0.0372 RPN score loss: 0.00514 RPN total loss: 0.04234 Total loss: 1.67985 timestamp: 1655019816.4753475 iteration: 14845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08016 FastRCNN class loss: 0.03987 FastRCNN total loss: 0.12003 L1 loss: 0.0000e+00 L2 loss: 1.31477 Learning rate: 0.02 Mask loss: 0.15517 RPN box loss: 0.01584 RPN score loss: 0.00672 RPN total loss: 0.02256 Total loss: 1.61253 timestamp: 1655019819.9154067 iteration: 14850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08538 FastRCNN class loss: 0.09795 FastRCNN total loss: 0.18333 L1 loss: 0.0000e+00 L2 loss: 1.31452 Learning rate: 0.02 Mask loss: 0.11903 RPN box loss: 0.01132 RPN score loss: 0.01321 RPN total loss: 0.02453 Total loss: 1.64142 timestamp: 1655019823.2103536 iteration: 14855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11414 FastRCNN class loss: 0.06366 FastRCNN total loss: 0.1778 L1 loss: 0.0000e+00 L2 loss: 1.31429 Learning rate: 0.02 Mask loss: 0.22498 RPN box loss: 0.04206 RPN score loss: 0.00634 RPN total loss: 0.0484 Total loss: 1.76547 timestamp: 1655019826.596532 iteration: 14860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18253 FastRCNN class loss: 0.09119 FastRCNN total loss: 0.27371 L1 loss: 0.0000e+00 L2 loss: 1.31405 Learning rate: 0.02 Mask loss: 0.16113 RPN box loss: 0.03051 RPN score loss: 0.01147 RPN total loss: 0.04197 Total loss: 1.79087 timestamp: 1655019829.9355948 iteration: 14865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20368 FastRCNN class loss: 0.11571 FastRCNN total loss: 0.3194 L1 loss: 0.0000e+00 L2 loss: 1.3138 Learning rate: 0.02 Mask loss: 0.23084 RPN box loss: 0.029 RPN score loss: 0.03258 RPN total loss: 0.06158 Total loss: 1.92561 timestamp: 1655019833.2628443 iteration: 14870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1532 FastRCNN class loss: 0.09957 FastRCNN total loss: 0.25277 L1 loss: 0.0000e+00 L2 loss: 1.31358 Learning rate: 0.02 Mask loss: 0.14653 RPN box loss: 0.04012 RPN score loss: 0.00864 RPN total loss: 0.04877 Total loss: 1.76165 timestamp: 1655019836.5396776 iteration: 14875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13808 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.24314 L1 loss: 0.0000e+00 L2 loss: 1.31335 Learning rate: 0.02 Mask loss: 0.27035 RPN box loss: 0.03233 RPN score loss: 0.01099 RPN total loss: 0.04333 Total loss: 1.87017 timestamp: 1655019839.985116 iteration: 14880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20704 FastRCNN class loss: 0.1337 FastRCNN total loss: 0.34074 L1 loss: 0.0000e+00 L2 loss: 1.31313 Learning rate: 0.02 Mask loss: 0.30368 RPN box loss: 0.02656 RPN score loss: 0.01386 RPN total loss: 0.04042 Total loss: 1.99797 timestamp: 1655019843.1887538 iteration: 14885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23889 FastRCNN class loss: 0.13147 FastRCNN total loss: 0.37036 L1 loss: 0.0000e+00 L2 loss: 1.31292 Learning rate: 0.02 Mask loss: 0.18036 RPN box loss: 0.05878 RPN score loss: 0.00666 RPN total loss: 0.06544 Total loss: 1.92907 timestamp: 1655019846.5492554 iteration: 14890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15053 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.2224 L1 loss: 0.0000e+00 L2 loss: 1.31266 Learning rate: 0.02 Mask loss: 0.09479 RPN box loss: 0.00896 RPN score loss: 0.00468 RPN total loss: 0.01364 Total loss: 1.64349 timestamp: 1655019849.998352 iteration: 14895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1586 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.22789 L1 loss: 0.0000e+00 L2 loss: 1.31243 Learning rate: 0.02 Mask loss: 0.16581 RPN box loss: 0.03829 RPN score loss: 0.00963 RPN total loss: 0.04792 Total loss: 1.75405 timestamp: 1655019853.2934914 iteration: 14900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18118 FastRCNN class loss: 0.08538 FastRCNN total loss: 0.26656 L1 loss: 0.0000e+00 L2 loss: 1.31221 Learning rate: 0.02 Mask loss: 0.16357 RPN box loss: 0.0224 RPN score loss: 0.01156 RPN total loss: 0.03396 Total loss: 1.77629 timestamp: 1655019856.6841276 iteration: 14905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12638 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.21872 L1 loss: 0.0000e+00 L2 loss: 1.31195 Learning rate: 0.02 Mask loss: 0.16664 RPN box loss: 0.07256 RPN score loss: 0.00629 RPN total loss: 0.07886 Total loss: 1.77616 timestamp: 1655019860.0463736 iteration: 14910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16386 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.21462 L1 loss: 0.0000e+00 L2 loss: 1.31172 Learning rate: 0.02 Mask loss: 0.17433 RPN box loss: 0.02629 RPN score loss: 0.00497 RPN total loss: 0.03126 Total loss: 1.73194 timestamp: 1655019863.5534782 iteration: 14915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18143 FastRCNN class loss: 0.0959 FastRCNN total loss: 0.27732 L1 loss: 0.0000e+00 L2 loss: 1.31151 Learning rate: 0.02 Mask loss: 0.24287 RPN box loss: 0.06388 RPN score loss: 0.01322 RPN total loss: 0.0771 Total loss: 1.9088 timestamp: 1655019866.815958 iteration: 14920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0824 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.13032 L1 loss: 0.0000e+00 L2 loss: 1.31129 Learning rate: 0.02 Mask loss: 0.13877 RPN box loss: 0.00739 RPN score loss: 0.00346 RPN total loss: 0.01085 Total loss: 1.59123 timestamp: 1655019870.1661067 iteration: 14925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18209 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.24103 L1 loss: 0.0000e+00 L2 loss: 1.31104 Learning rate: 0.02 Mask loss: 0.12668 RPN box loss: 0.01286 RPN score loss: 0.00844 RPN total loss: 0.0213 Total loss: 1.70005 timestamp: 1655019873.4641573 iteration: 14930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14019 FastRCNN class loss: 0.10088 FastRCNN total loss: 0.24107 L1 loss: 0.0000e+00 L2 loss: 1.31081 Learning rate: 0.02 Mask loss: 0.17103 RPN box loss: 0.05311 RPN score loss: 0.01084 RPN total loss: 0.06395 Total loss: 1.78687 timestamp: 1655019876.8061051 iteration: 14935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07942 FastRCNN class loss: 0.06618 FastRCNN total loss: 0.1456 L1 loss: 0.0000e+00 L2 loss: 1.31059 Learning rate: 0.02 Mask loss: 0.15285 RPN box loss: 0.08926 RPN score loss: 0.00801 RPN total loss: 0.09727 Total loss: 1.7063 timestamp: 1655019880.1946838 iteration: 14940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22653 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.28189 L1 loss: 0.0000e+00 L2 loss: 1.31037 Learning rate: 0.02 Mask loss: 0.17067 RPN box loss: 0.06846 RPN score loss: 0.00404 RPN total loss: 0.0725 Total loss: 1.83543 timestamp: 1655019883.4432838 iteration: 14945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17646 FastRCNN class loss: 0.13382 FastRCNN total loss: 0.31028 L1 loss: 0.0000e+00 L2 loss: 1.31017 Learning rate: 0.02 Mask loss: 0.19989 RPN box loss: 0.08757 RPN score loss: 0.01561 RPN total loss: 0.10318 Total loss: 1.92352 timestamp: 1655019886.7890499 iteration: 14950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21414 FastRCNN class loss: 0.20448 FastRCNN total loss: 0.41862 L1 loss: 0.0000e+00 L2 loss: 1.30994 Learning rate: 0.02 Mask loss: 0.23469 RPN box loss: 0.09719 RPN score loss: 0.02525 RPN total loss: 0.12244 Total loss: 2.08568 timestamp: 1655019890.1232998 iteration: 14955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18089 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.26255 L1 loss: 0.0000e+00 L2 loss: 1.30969 Learning rate: 0.02 Mask loss: 0.17028 RPN box loss: 0.00595 RPN score loss: 0.00331 RPN total loss: 0.00926 Total loss: 1.75178 timestamp: 1655019893.4441395 iteration: 14960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11871 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.20264 L1 loss: 0.0000e+00 L2 loss: 1.30945 Learning rate: 0.02 Mask loss: 0.17129 RPN box loss: 0.02791 RPN score loss: 0.00568 RPN total loss: 0.03358 Total loss: 1.71696 timestamp: 1655019896.7462862 iteration: 14965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15568 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.23769 L1 loss: 0.0000e+00 L2 loss: 1.30921 Learning rate: 0.02 Mask loss: 0.23447 RPN box loss: 0.01048 RPN score loss: 0.00376 RPN total loss: 0.01425 Total loss: 1.79562 timestamp: 1655019900.1091855 iteration: 14970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1681 FastRCNN class loss: 0.12193 FastRCNN total loss: 0.29003 L1 loss: 0.0000e+00 L2 loss: 1.30897 Learning rate: 0.02 Mask loss: 0.18244 RPN box loss: 0.03779 RPN score loss: 0.00795 RPN total loss: 0.04574 Total loss: 1.82717 timestamp: 1655019903.3994043 iteration: 14975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18978 FastRCNN class loss: 0.10101 FastRCNN total loss: 0.29079 L1 loss: 0.0000e+00 L2 loss: 1.30874 Learning rate: 0.02 Mask loss: 0.23947 RPN box loss: 0.04714 RPN score loss: 0.0129 RPN total loss: 0.06003 Total loss: 1.89903 timestamp: 1655019906.7309933 iteration: 14980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1894 FastRCNN class loss: 0.13384 FastRCNN total loss: 0.32324 L1 loss: 0.0000e+00 L2 loss: 1.30853 Learning rate: 0.02 Mask loss: 0.21014 RPN box loss: 0.03465 RPN score loss: 0.01343 RPN total loss: 0.04808 Total loss: 1.88999 timestamp: 1655019910.1147335 iteration: 14985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15648 FastRCNN class loss: 0.10368 FastRCNN total loss: 0.26017 L1 loss: 0.0000e+00 L2 loss: 1.30828 Learning rate: 0.02 Mask loss: 0.16271 RPN box loss: 0.06171 RPN score loss: 0.01302 RPN total loss: 0.07473 Total loss: 1.80589 timestamp: 1655019913.4229217 iteration: 14990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21237 FastRCNN class loss: 0.12393 FastRCNN total loss: 0.3363 L1 loss: 0.0000e+00 L2 loss: 1.30804 Learning rate: 0.02 Mask loss: 0.16499 RPN box loss: 0.06023 RPN score loss: 0.01088 RPN total loss: 0.07111 Total loss: 1.88044 timestamp: 1655019916.8239427 iteration: 14995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18286 FastRCNN class loss: 0.12126 FastRCNN total loss: 0.30412 L1 loss: 0.0000e+00 L2 loss: 1.30782 Learning rate: 0.02 Mask loss: 0.24882 RPN box loss: 0.01947 RPN score loss: 0.005 RPN total loss: 0.02447 Total loss: 1.88523 timestamp: 1655019920.1693356 iteration: 15000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12842 FastRCNN class loss: 0.09067 FastRCNN total loss: 0.21909 L1 loss: 0.0000e+00 L2 loss: 1.30759 Learning rate: 0.02 Mask loss: 0.20111 RPN box loss: 0.02834 RPN score loss: 0.00818 RPN total loss: 0.03651 Total loss: 1.76431 timestamp: 1655019923.5690334 iteration: 15005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21689 FastRCNN class loss: 0.14239 FastRCNN total loss: 0.35928 L1 loss: 0.0000e+00 L2 loss: 1.30738 Learning rate: 0.02 Mask loss: 0.19509 RPN box loss: 0.04596 RPN score loss: 0.0548 RPN total loss: 0.10076 Total loss: 1.96252 timestamp: 1655019926.875143 iteration: 15010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15611 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.22828 L1 loss: 0.0000e+00 L2 loss: 1.30714 Learning rate: 0.02 Mask loss: 0.18871 RPN box loss: 0.02442 RPN score loss: 0.00693 RPN total loss: 0.03135 Total loss: 1.75548 timestamp: 1655019930.2807589 iteration: 15015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14695 FastRCNN class loss: 0.09887 FastRCNN total loss: 0.24582 L1 loss: 0.0000e+00 L2 loss: 1.3069 Learning rate: 0.02 Mask loss: 0.25744 RPN box loss: 0.09318 RPN score loss: 0.01527 RPN total loss: 0.10845 Total loss: 1.91861 timestamp: 1655019933.6041546 iteration: 15020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12809 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.19052 L1 loss: 0.0000e+00 L2 loss: 1.30666 Learning rate: 0.02 Mask loss: 0.09597 RPN box loss: 0.0058 RPN score loss: 0.00727 RPN total loss: 0.01306 Total loss: 1.60622 timestamp: 1655019936.962652 iteration: 15025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18068 FastRCNN class loss: 0.12756 FastRCNN total loss: 0.30823 L1 loss: 0.0000e+00 L2 loss: 1.30641 Learning rate: 0.02 Mask loss: 0.24525 RPN box loss: 0.04896 RPN score loss: 0.02394 RPN total loss: 0.07291 Total loss: 1.9328 timestamp: 1655019940.32303 iteration: 15030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13073 FastRCNN class loss: 0.05679 FastRCNN total loss: 0.18752 L1 loss: 0.0000e+00 L2 loss: 1.30617 Learning rate: 0.02 Mask loss: 0.14378 RPN box loss: 0.01594 RPN score loss: 0.00281 RPN total loss: 0.01875 Total loss: 1.65621 timestamp: 1655019943.6097558 iteration: 15035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16871 FastRCNN class loss: 0.05949 FastRCNN total loss: 0.2282 L1 loss: 0.0000e+00 L2 loss: 1.30594 Learning rate: 0.02 Mask loss: 0.19065 RPN box loss: 0.04523 RPN score loss: 0.00931 RPN total loss: 0.05454 Total loss: 1.77933 timestamp: 1655019946.9251053 iteration: 15040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21213 FastRCNN class loss: 0.1283 FastRCNN total loss: 0.34042 L1 loss: 0.0000e+00 L2 loss: 1.30573 Learning rate: 0.02 Mask loss: 0.2184 RPN box loss: 0.06307 RPN score loss: 0.03525 RPN total loss: 0.09832 Total loss: 1.96288 timestamp: 1655019950.2224035 iteration: 15045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13208 FastRCNN class loss: 0.0719 FastRCNN total loss: 0.20398 L1 loss: 0.0000e+00 L2 loss: 1.30551 Learning rate: 0.02 Mask loss: 0.09337 RPN box loss: 0.0363 RPN score loss: 0.00997 RPN total loss: 0.04626 Total loss: 1.64913 timestamp: 1655019953.668185 iteration: 15050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.18128 L1 loss: 0.0000e+00 L2 loss: 1.30527 Learning rate: 0.02 Mask loss: 0.17211 RPN box loss: 0.01985 RPN score loss: 0.0048 RPN total loss: 0.02465 Total loss: 1.6833 timestamp: 1655019956.9779768 iteration: 15055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.26977 L1 loss: 0.0000e+00 L2 loss: 1.30505 Learning rate: 0.02 Mask loss: 0.16331 RPN box loss: 0.01599 RPN score loss: 0.00418 RPN total loss: 0.02017 Total loss: 1.7583 timestamp: 1655019960.3511748 iteration: 15060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17102 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.27563 L1 loss: 0.0000e+00 L2 loss: 1.30484 Learning rate: 0.02 Mask loss: 0.15805 RPN box loss: 0.05572 RPN score loss: 0.01329 RPN total loss: 0.06901 Total loss: 1.80753 timestamp: 1655019963.7012117 iteration: 15065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19253 FastRCNN class loss: 0.08086 FastRCNN total loss: 0.27339 L1 loss: 0.0000e+00 L2 loss: 1.30462 Learning rate: 0.02 Mask loss: 0.14401 RPN box loss: 0.04255 RPN score loss: 0.01715 RPN total loss: 0.0597 Total loss: 1.78172 timestamp: 1655019966.9682877 iteration: 15070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19081 FastRCNN class loss: 0.1044 FastRCNN total loss: 0.2952 L1 loss: 0.0000e+00 L2 loss: 1.30437 Learning rate: 0.02 Mask loss: 0.16743 RPN box loss: 0.07151 RPN score loss: 0.00791 RPN total loss: 0.07942 Total loss: 1.84643 timestamp: 1655019970.3888962 iteration: 15075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17564 FastRCNN class loss: 0.12312 FastRCNN total loss: 0.29876 L1 loss: 0.0000e+00 L2 loss: 1.30413 Learning rate: 0.02 Mask loss: 0.27256 RPN box loss: 0.02179 RPN score loss: 0.00297 RPN total loss: 0.02476 Total loss: 1.90021 timestamp: 1655019973.6435683 iteration: 15080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13236 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.21165 L1 loss: 0.0000e+00 L2 loss: 1.30389 Learning rate: 0.02 Mask loss: 0.13909 RPN box loss: 0.0278 RPN score loss: 0.01101 RPN total loss: 0.03881 Total loss: 1.69344 timestamp: 1655019977.0529008 iteration: 15085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13577 FastRCNN class loss: 0.1141 FastRCNN total loss: 0.24987 L1 loss: 0.0000e+00 L2 loss: 1.30364 Learning rate: 0.02 Mask loss: 0.18559 RPN box loss: 0.02506 RPN score loss: 0.01469 RPN total loss: 0.03975 Total loss: 1.77884 timestamp: 1655019980.3750398 iteration: 15090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1287 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.20865 L1 loss: 0.0000e+00 L2 loss: 1.30342 Learning rate: 0.02 Mask loss: 0.21356 RPN box loss: 0.02315 RPN score loss: 0.00342 RPN total loss: 0.02657 Total loss: 1.7522 timestamp: 1655019983.7398982 iteration: 15095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19056 FastRCNN class loss: 0.11003 FastRCNN total loss: 0.30059 L1 loss: 0.0000e+00 L2 loss: 1.3032 Learning rate: 0.02 Mask loss: 0.18021 RPN box loss: 0.0492 RPN score loss: 0.02015 RPN total loss: 0.06935 Total loss: 1.85335 timestamp: 1655019986.9923832 iteration: 15100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17914 FastRCNN class loss: 0.08476 FastRCNN total loss: 0.2639 L1 loss: 0.0000e+00 L2 loss: 1.30297 Learning rate: 0.02 Mask loss: 0.12167 RPN box loss: 0.03565 RPN score loss: 0.0123 RPN total loss: 0.04796 Total loss: 1.73649 timestamp: 1655019990.355859 iteration: 15105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12386 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.17953 L1 loss: 0.0000e+00 L2 loss: 1.30277 Learning rate: 0.02 Mask loss: 0.12914 RPN box loss: 0.01539 RPN score loss: 0.00558 RPN total loss: 0.02098 Total loss: 1.63242 timestamp: 1655019993.7213588 iteration: 15110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16965 FastRCNN class loss: 0.09632 FastRCNN total loss: 0.26597 L1 loss: 0.0000e+00 L2 loss: 1.30254 Learning rate: 0.02 Mask loss: 0.18774 RPN box loss: 0.04218 RPN score loss: 0.01513 RPN total loss: 0.05731 Total loss: 1.81356 timestamp: 1655019996.983604 iteration: 15115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19293 FastRCNN class loss: 0.10729 FastRCNN total loss: 0.30022 L1 loss: 0.0000e+00 L2 loss: 1.3023 Learning rate: 0.02 Mask loss: 0.17479 RPN box loss: 0.04413 RPN score loss: 0.00621 RPN total loss: 0.05034 Total loss: 1.82766 timestamp: 1655020000.4182208 iteration: 15120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16822 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.23849 L1 loss: 0.0000e+00 L2 loss: 1.30208 Learning rate: 0.02 Mask loss: 0.19699 RPN box loss: 0.03548 RPN score loss: 0.00657 RPN total loss: 0.04205 Total loss: 1.77961 timestamp: 1655020003.7483215 iteration: 15125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12066 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.19663 L1 loss: 0.0000e+00 L2 loss: 1.30187 Learning rate: 0.02 Mask loss: 0.15315 RPN box loss: 0.00914 RPN score loss: 0.00658 RPN total loss: 0.01572 Total loss: 1.66737 timestamp: 1655020007.0422635 iteration: 15130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12184 FastRCNN class loss: 0.06623 FastRCNN total loss: 0.18807 L1 loss: 0.0000e+00 L2 loss: 1.30161 Learning rate: 0.02 Mask loss: 0.14358 RPN box loss: 0.06085 RPN score loss: 0.01347 RPN total loss: 0.07432 Total loss: 1.70759 timestamp: 1655020010.283652 iteration: 15135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.10596 FastRCNN total loss: 0.22079 L1 loss: 0.0000e+00 L2 loss: 1.30138 Learning rate: 0.02 Mask loss: 0.1737 RPN box loss: 0.03902 RPN score loss: 0.01092 RPN total loss: 0.04994 Total loss: 1.74581 timestamp: 1655020013.680651 iteration: 15140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22612 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.31307 L1 loss: 0.0000e+00 L2 loss: 1.30117 Learning rate: 0.02 Mask loss: 0.17027 RPN box loss: 0.01366 RPN score loss: 0.00556 RPN total loss: 0.01922 Total loss: 1.80373 timestamp: 1655020016.8719108 iteration: 15145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13746 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.23076 L1 loss: 0.0000e+00 L2 loss: 1.30093 Learning rate: 0.02 Mask loss: 0.18901 RPN box loss: 0.03495 RPN score loss: 0.00723 RPN total loss: 0.04218 Total loss: 1.76288 timestamp: 1655020020.2473514 iteration: 15150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20863 FastRCNN class loss: 0.14304 FastRCNN total loss: 0.35166 L1 loss: 0.0000e+00 L2 loss: 1.3007 Learning rate: 0.02 Mask loss: 0.24665 RPN box loss: 0.02121 RPN score loss: 0.00621 RPN total loss: 0.02741 Total loss: 1.92643 timestamp: 1655020023.7183514 iteration: 15155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16295 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.23242 L1 loss: 0.0000e+00 L2 loss: 1.30046 Learning rate: 0.02 Mask loss: 0.11309 RPN box loss: 0.02809 RPN score loss: 0.00798 RPN total loss: 0.03607 Total loss: 1.68202 timestamp: 1655020027.0044494 iteration: 15160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15802 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.24508 L1 loss: 0.0000e+00 L2 loss: 1.30023 Learning rate: 0.02 Mask loss: 0.13324 RPN box loss: 0.06174 RPN score loss: 0.00542 RPN total loss: 0.06716 Total loss: 1.74571 timestamp: 1655020030.386657 iteration: 15165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13994 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.21782 L1 loss: 0.0000e+00 L2 loss: 1.30001 Learning rate: 0.02 Mask loss: 0.12525 RPN box loss: 0.02734 RPN score loss: 0.00544 RPN total loss: 0.03278 Total loss: 1.67586 timestamp: 1655020033.7337327 iteration: 15170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20668 FastRCNN class loss: 0.19723 FastRCNN total loss: 0.40391 L1 loss: 0.0000e+00 L2 loss: 1.29978 Learning rate: 0.02 Mask loss: 0.2568 RPN box loss: 0.02111 RPN score loss: 0.01259 RPN total loss: 0.03371 Total loss: 1.99418 timestamp: 1655020037.147802 iteration: 15175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18373 FastRCNN class loss: 0.0977 FastRCNN total loss: 0.28144 L1 loss: 0.0000e+00 L2 loss: 1.29954 Learning rate: 0.02 Mask loss: 0.12857 RPN box loss: 0.05305 RPN score loss: 0.00595 RPN total loss: 0.059 Total loss: 1.76854 timestamp: 1655020040.458105 iteration: 15180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21071 FastRCNN class loss: 0.12895 FastRCNN total loss: 0.33965 L1 loss: 0.0000e+00 L2 loss: 1.29933 Learning rate: 0.02 Mask loss: 0.23915 RPN box loss: 0.03694 RPN score loss: 0.00731 RPN total loss: 0.04425 Total loss: 1.92238 timestamp: 1655020043.8063004 iteration: 15185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10743 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.16583 L1 loss: 0.0000e+00 L2 loss: 1.2991 Learning rate: 0.02 Mask loss: 0.14918 RPN box loss: 0.03193 RPN score loss: 0.01096 RPN total loss: 0.04289 Total loss: 1.657 timestamp: 1655020047.0906732 iteration: 15190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20304 FastRCNN class loss: 0.11783 FastRCNN total loss: 0.32086 L1 loss: 0.0000e+00 L2 loss: 1.29886 Learning rate: 0.02 Mask loss: 0.26496 RPN box loss: 0.01599 RPN score loss: 0.0045 RPN total loss: 0.02049 Total loss: 1.90518 timestamp: 1655020050.4416773 iteration: 15195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14211 FastRCNN class loss: 0.10168 FastRCNN total loss: 0.24379 L1 loss: 0.0000e+00 L2 loss: 1.29864 Learning rate: 0.02 Mask loss: 0.15706 RPN box loss: 0.08405 RPN score loss: 0.00604 RPN total loss: 0.09009 Total loss: 1.78958 timestamp: 1655020053.7966027 iteration: 15200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23093 FastRCNN class loss: 0.09741 FastRCNN total loss: 0.32835 L1 loss: 0.0000e+00 L2 loss: 1.29839 Learning rate: 0.02 Mask loss: 0.20688 RPN box loss: 0.02421 RPN score loss: 0.00605 RPN total loss: 0.03026 Total loss: 1.86388 timestamp: 1655020057.0757508 iteration: 15205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09869 FastRCNN class loss: 0.11952 FastRCNN total loss: 0.21821 L1 loss: 0.0000e+00 L2 loss: 1.29814 Learning rate: 0.02 Mask loss: 0.20773 RPN box loss: 0.00832 RPN score loss: 0.00313 RPN total loss: 0.01145 Total loss: 1.73553 timestamp: 1655020060.421124 iteration: 15210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18421 FastRCNN class loss: 0.09657 FastRCNN total loss: 0.28078 L1 loss: 0.0000e+00 L2 loss: 1.29792 Learning rate: 0.02 Mask loss: 0.14403 RPN box loss: 0.05545 RPN score loss: 0.00936 RPN total loss: 0.06481 Total loss: 1.78754 timestamp: 1655020063.682674 iteration: 15215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25226 FastRCNN class loss: 0.10965 FastRCNN total loss: 0.36192 L1 loss: 0.0000e+00 L2 loss: 1.29771 Learning rate: 0.02 Mask loss: 0.24523 RPN box loss: 0.05132 RPN score loss: 0.02215 RPN total loss: 0.07347 Total loss: 1.97832 timestamp: 1655020067.1008036 iteration: 15220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24916 FastRCNN class loss: 0.10488 FastRCNN total loss: 0.35405 L1 loss: 0.0000e+00 L2 loss: 1.29751 Learning rate: 0.02 Mask loss: 0.14217 RPN box loss: 0.05463 RPN score loss: 0.01856 RPN total loss: 0.0732 Total loss: 1.86693 timestamp: 1655020070.4239998 iteration: 15225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21429 FastRCNN class loss: 0.14265 FastRCNN total loss: 0.35694 L1 loss: 0.0000e+00 L2 loss: 1.29727 Learning rate: 0.02 Mask loss: 0.26795 RPN box loss: 0.04513 RPN score loss: 0.01993 RPN total loss: 0.06506 Total loss: 1.98721 timestamp: 1655020073.7810009 iteration: 15230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1604 FastRCNN class loss: 0.10419 FastRCNN total loss: 0.26459 L1 loss: 0.0000e+00 L2 loss: 1.29702 Learning rate: 0.02 Mask loss: 0.25706 RPN box loss: 0.03272 RPN score loss: 0.01275 RPN total loss: 0.04547 Total loss: 1.86414 timestamp: 1655020077.0859506 iteration: 15235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.10647 FastRCNN total loss: 0.23419 L1 loss: 0.0000e+00 L2 loss: 1.2968 Learning rate: 0.02 Mask loss: 0.12576 RPN box loss: 0.02219 RPN score loss: 0.01037 RPN total loss: 0.03256 Total loss: 1.6893 timestamp: 1655020080.5385654 iteration: 15240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09611 FastRCNN class loss: 0.09119 FastRCNN total loss: 0.1873 L1 loss: 0.0000e+00 L2 loss: 1.29655 Learning rate: 0.02 Mask loss: 0.13237 RPN box loss: 0.03785 RPN score loss: 0.01026 RPN total loss: 0.04811 Total loss: 1.66433 timestamp: 1655020083.909208 iteration: 15245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10562 FastRCNN class loss: 0.09485 FastRCNN total loss: 0.20046 L1 loss: 0.0000e+00 L2 loss: 1.29631 Learning rate: 0.02 Mask loss: 0.15426 RPN box loss: 0.05473 RPN score loss: 0.00903 RPN total loss: 0.06377 Total loss: 1.7148 timestamp: 1655020087.2917151 iteration: 15250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.2376 L1 loss: 0.0000e+00 L2 loss: 1.29609 Learning rate: 0.02 Mask loss: 0.18847 RPN box loss: 0.06036 RPN score loss: 0.00844 RPN total loss: 0.0688 Total loss: 1.79096 timestamp: 1655020090.7746983 iteration: 15255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23335 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.3231 L1 loss: 0.0000e+00 L2 loss: 1.29588 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.00859 RPN score loss: 0.00516 RPN total loss: 0.01374 Total loss: 1.78696 timestamp: 1655020094.0622098 iteration: 15260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15235 FastRCNN class loss: 0.08658 FastRCNN total loss: 0.23894 L1 loss: 0.0000e+00 L2 loss: 1.29566 Learning rate: 0.02 Mask loss: 0.18842 RPN box loss: 0.02793 RPN score loss: 0.00983 RPN total loss: 0.03776 Total loss: 1.76078 timestamp: 1655020097.4075809 iteration: 15265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11889 FastRCNN class loss: 0.05253 FastRCNN total loss: 0.17142 L1 loss: 0.0000e+00 L2 loss: 1.29543 Learning rate: 0.02 Mask loss: 0.10316 RPN box loss: 0.02418 RPN score loss: 0.00338 RPN total loss: 0.02756 Total loss: 1.59758 timestamp: 1655020100.7117262 iteration: 15270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10019 FastRCNN class loss: 0.0807 FastRCNN total loss: 0.18089 L1 loss: 0.0000e+00 L2 loss: 1.29519 Learning rate: 0.02 Mask loss: 0.20822 RPN box loss: 0.02446 RPN score loss: 0.00297 RPN total loss: 0.02744 Total loss: 1.71173 timestamp: 1655020104.0760562 iteration: 15275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23607 FastRCNN class loss: 0.09511 FastRCNN total loss: 0.33119 L1 loss: 0.0000e+00 L2 loss: 1.29496 Learning rate: 0.02 Mask loss: 0.17275 RPN box loss: 0.04738 RPN score loss: 0.0087 RPN total loss: 0.05609 Total loss: 1.85499 timestamp: 1655020107.3748763 iteration: 15280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20856 FastRCNN class loss: 0.14843 FastRCNN total loss: 0.35699 L1 loss: 0.0000e+00 L2 loss: 1.29475 Learning rate: 0.02 Mask loss: 0.13962 RPN box loss: 0.04337 RPN score loss: 0.01657 RPN total loss: 0.05993 Total loss: 1.85129 timestamp: 1655020110.6772625 iteration: 15285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19135 FastRCNN class loss: 0.07986 FastRCNN total loss: 0.27121 L1 loss: 0.0000e+00 L2 loss: 1.2945 Learning rate: 0.02 Mask loss: 0.15586 RPN box loss: 0.03086 RPN score loss: 0.00731 RPN total loss: 0.03818 Total loss: 1.75975 timestamp: 1655020114.1023893 iteration: 15290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20417 FastRCNN class loss: 0.06967 FastRCNN total loss: 0.27383 L1 loss: 0.0000e+00 L2 loss: 1.29426 Learning rate: 0.02 Mask loss: 0.11814 RPN box loss: 0.01774 RPN score loss: 0.0056 RPN total loss: 0.02334 Total loss: 1.70956 timestamp: 1655020117.4806926 iteration: 15295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18094 FastRCNN class loss: 0.09414 FastRCNN total loss: 0.27508 L1 loss: 0.0000e+00 L2 loss: 1.29405 Learning rate: 0.02 Mask loss: 0.19435 RPN box loss: 0.10758 RPN score loss: 0.00694 RPN total loss: 0.11452 Total loss: 1.878 timestamp: 1655020120.8673053 iteration: 15300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15932 FastRCNN class loss: 0.06923 FastRCNN total loss: 0.22855 L1 loss: 0.0000e+00 L2 loss: 1.29381 Learning rate: 0.02 Mask loss: 0.19594 RPN box loss: 0.02035 RPN score loss: 0.0095 RPN total loss: 0.02985 Total loss: 1.74815 timestamp: 1655020124.140641 iteration: 15305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12391 FastRCNN class loss: 0.12626 FastRCNN total loss: 0.25017 L1 loss: 0.0000e+00 L2 loss: 1.29357 Learning rate: 0.02 Mask loss: 0.24415 RPN box loss: 0.02603 RPN score loss: 0.01544 RPN total loss: 0.04147 Total loss: 1.82936 timestamp: 1655020127.472578 iteration: 15310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.17891 L1 loss: 0.0000e+00 L2 loss: 1.29334 Learning rate: 0.02 Mask loss: 0.14261 RPN box loss: 0.00627 RPN score loss: 0.0014 RPN total loss: 0.00767 Total loss: 1.62253 timestamp: 1655020130.778503 iteration: 15315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11611 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.18487 L1 loss: 0.0000e+00 L2 loss: 1.29312 Learning rate: 0.02 Mask loss: 0.21431 RPN box loss: 0.06588 RPN score loss: 0.0031 RPN total loss: 0.06897 Total loss: 1.76126 timestamp: 1655020134.140591 iteration: 15320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15019 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.23885 L1 loss: 0.0000e+00 L2 loss: 1.29287 Learning rate: 0.02 Mask loss: 0.21682 RPN box loss: 0.02657 RPN score loss: 0.00526 RPN total loss: 0.03182 Total loss: 1.78037 timestamp: 1655020137.5896733 iteration: 15325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14852 FastRCNN class loss: 0.09599 FastRCNN total loss: 0.24451 L1 loss: 0.0000e+00 L2 loss: 1.29265 Learning rate: 0.02 Mask loss: 0.18531 RPN box loss: 0.05182 RPN score loss: 0.00538 RPN total loss: 0.0572 Total loss: 1.77967 timestamp: 1655020140.872634 iteration: 15330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21148 FastRCNN class loss: 0.1316 FastRCNN total loss: 0.34308 L1 loss: 0.0000e+00 L2 loss: 1.29243 Learning rate: 0.02 Mask loss: 0.23434 RPN box loss: 0.01326 RPN score loss: 0.01264 RPN total loss: 0.0259 Total loss: 1.89575 timestamp: 1655020144.2558284 iteration: 15335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15685 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.23534 L1 loss: 0.0000e+00 L2 loss: 1.29221 Learning rate: 0.02 Mask loss: 0.20247 RPN box loss: 0.03526 RPN score loss: 0.00547 RPN total loss: 0.04073 Total loss: 1.77076 timestamp: 1655020147.565175 iteration: 15340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15372 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.23147 L1 loss: 0.0000e+00 L2 loss: 1.29201 Learning rate: 0.02 Mask loss: 0.15629 RPN box loss: 0.07529 RPN score loss: 0.01251 RPN total loss: 0.08781 Total loss: 1.76759 timestamp: 1655020150.9097648 iteration: 15345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12453 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.18422 L1 loss: 0.0000e+00 L2 loss: 1.29177 Learning rate: 0.02 Mask loss: 0.23466 RPN box loss: 0.06631 RPN score loss: 0.01134 RPN total loss: 0.07765 Total loss: 1.78829 timestamp: 1655020154.2486572 iteration: 15350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11894 FastRCNN class loss: 0.06768 FastRCNN total loss: 0.18662 L1 loss: 0.0000e+00 L2 loss: 1.29151 Learning rate: 0.02 Mask loss: 0.1694 RPN box loss: 0.03505 RPN score loss: 0.01113 RPN total loss: 0.04618 Total loss: 1.69371 timestamp: 1655020157.6084442 iteration: 15355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23133 FastRCNN class loss: 0.09211 FastRCNN total loss: 0.32344 L1 loss: 0.0000e+00 L2 loss: 1.29128 Learning rate: 0.02 Mask loss: 0.17007 RPN box loss: 0.04518 RPN score loss: 0.02956 RPN total loss: 0.07474 Total loss: 1.85952 timestamp: 1655020160.9387047 iteration: 15360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2068 FastRCNN class loss: 0.09599 FastRCNN total loss: 0.30279 L1 loss: 0.0000e+00 L2 loss: 1.29105 Learning rate: 0.02 Mask loss: 0.15865 RPN box loss: 0.04426 RPN score loss: 0.00332 RPN total loss: 0.04758 Total loss: 1.80007 timestamp: 1655020164.3444088 iteration: 15365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06484 FastRCNN class loss: 0.03896 FastRCNN total loss: 0.10379 L1 loss: 0.0000e+00 L2 loss: 1.29084 Learning rate: 0.02 Mask loss: 0.15806 RPN box loss: 0.01784 RPN score loss: 0.01177 RPN total loss: 0.02962 Total loss: 1.58231 timestamp: 1655020167.8166578 iteration: 15370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19632 FastRCNN class loss: 0.08846 FastRCNN total loss: 0.28478 L1 loss: 0.0000e+00 L2 loss: 1.29061 Learning rate: 0.02 Mask loss: 0.18553 RPN box loss: 0.03781 RPN score loss: 0.00947 RPN total loss: 0.04728 Total loss: 1.8082 timestamp: 1655020171.0571306 iteration: 15375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21386 FastRCNN class loss: 0.12342 FastRCNN total loss: 0.33728 L1 loss: 0.0000e+00 L2 loss: 1.29038 Learning rate: 0.02 Mask loss: 0.23385 RPN box loss: 0.06456 RPN score loss: 0.01645 RPN total loss: 0.08101 Total loss: 1.94251 timestamp: 1655020174.3545625 iteration: 15380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23671 FastRCNN class loss: 0.09219 FastRCNN total loss: 0.32891 L1 loss: 0.0000e+00 L2 loss: 1.29016 Learning rate: 0.02 Mask loss: 0.22372 RPN box loss: 0.0409 RPN score loss: 0.00486 RPN total loss: 0.04576 Total loss: 1.88854 timestamp: 1655020177.6576986 iteration: 15385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11616 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.17677 L1 loss: 0.0000e+00 L2 loss: 1.28992 Learning rate: 0.02 Mask loss: 0.12668 RPN box loss: 0.0719 RPN score loss: 0.00505 RPN total loss: 0.07695 Total loss: 1.67032 timestamp: 1655020181.0640988 iteration: 15390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12311 FastRCNN class loss: 0.10266 FastRCNN total loss: 0.22577 L1 loss: 0.0000e+00 L2 loss: 1.28968 Learning rate: 0.02 Mask loss: 0.16395 RPN box loss: 0.06375 RPN score loss: 0.01457 RPN total loss: 0.07832 Total loss: 1.75771 timestamp: 1655020184.308799 iteration: 15395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09399 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.14696 L1 loss: 0.0000e+00 L2 loss: 1.28946 Learning rate: 0.02 Mask loss: 0.14351 RPN box loss: 0.10582 RPN score loss: 0.00677 RPN total loss: 0.1126 Total loss: 1.69253 timestamp: 1655020187.7123919 iteration: 15400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20587 FastRCNN class loss: 0.06801 FastRCNN total loss: 0.27388 L1 loss: 0.0000e+00 L2 loss: 1.28926 Learning rate: 0.02 Mask loss: 0.23408 RPN box loss: 0.0208 RPN score loss: 0.0037 RPN total loss: 0.0245 Total loss: 1.82172 timestamp: 1655020191.081103 iteration: 15405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12575 FastRCNN class loss: 0.11956 FastRCNN total loss: 0.24531 L1 loss: 0.0000e+00 L2 loss: 1.28905 Learning rate: 0.02 Mask loss: 0.14645 RPN box loss: 0.02827 RPN score loss: 0.00511 RPN total loss: 0.03338 Total loss: 1.71419 timestamp: 1655020194.4385674 iteration: 15410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12735 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.18489 L1 loss: 0.0000e+00 L2 loss: 1.28882 Learning rate: 0.02 Mask loss: 0.14462 RPN box loss: 0.0186 RPN score loss: 0.00279 RPN total loss: 0.02139 Total loss: 1.63972 timestamp: 1655020197.7758794 iteration: 15415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16457 FastRCNN class loss: 0.07061 FastRCNN total loss: 0.23518 L1 loss: 0.0000e+00 L2 loss: 1.28859 Learning rate: 0.02 Mask loss: 0.21337 RPN box loss: 0.07936 RPN score loss: 0.00604 RPN total loss: 0.08541 Total loss: 1.82255 timestamp: 1655020201.0239182 iteration: 15420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.04063 FastRCNN total loss: 0.13147 L1 loss: 0.0000e+00 L2 loss: 1.28836 Learning rate: 0.02 Mask loss: 0.11248 RPN box loss: 0.0337 RPN score loss: 0.00771 RPN total loss: 0.04142 Total loss: 1.57373 timestamp: 1655020204.5435452 iteration: 15425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11135 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.19377 L1 loss: 0.0000e+00 L2 loss: 1.28811 Learning rate: 0.02 Mask loss: 0.19777 RPN box loss: 0.05072 RPN score loss: 0.05131 RPN total loss: 0.10203 Total loss: 1.78167 timestamp: 1655020207.7727623 iteration: 15430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07712 FastRCNN class loss: 0.04619 FastRCNN total loss: 0.12331 L1 loss: 0.0000e+00 L2 loss: 1.2879 Learning rate: 0.02 Mask loss: 0.1531 RPN box loss: 0.02165 RPN score loss: 0.00424 RPN total loss: 0.02589 Total loss: 1.5902 timestamp: 1655020211.1915557 iteration: 15435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.06456 FastRCNN total loss: 0.17642 L1 loss: 0.0000e+00 L2 loss: 1.28768 Learning rate: 0.02 Mask loss: 0.13205 RPN box loss: 0.05187 RPN score loss: 0.00713 RPN total loss: 0.059 Total loss: 1.65516 timestamp: 1655020214.5578432 iteration: 15440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21403 FastRCNN class loss: 0.10142 FastRCNN total loss: 0.31544 L1 loss: 0.0000e+00 L2 loss: 1.28745 Learning rate: 0.02 Mask loss: 0.24847 RPN box loss: 0.06089 RPN score loss: 0.01373 RPN total loss: 0.07462 Total loss: 1.92598 timestamp: 1655020217.8938038 iteration: 15445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10077 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.16355 L1 loss: 0.0000e+00 L2 loss: 1.28724 Learning rate: 0.02 Mask loss: 0.18275 RPN box loss: 0.02715 RPN score loss: 0.00468 RPN total loss: 0.03183 Total loss: 1.66536 timestamp: 1655020221.1892686 iteration: 15450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11063 FastRCNN class loss: 0.052 FastRCNN total loss: 0.16263 L1 loss: 0.0000e+00 L2 loss: 1.28702 Learning rate: 0.02 Mask loss: 0.11261 RPN box loss: 0.0279 RPN score loss: 0.00292 RPN total loss: 0.03082 Total loss: 1.59308 timestamp: 1655020224.6267753 iteration: 15455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20373 FastRCNN class loss: 0.09126 FastRCNN total loss: 0.29499 L1 loss: 0.0000e+00 L2 loss: 1.2868 Learning rate: 0.02 Mask loss: 0.1642 RPN box loss: 0.04583 RPN score loss: 0.01871 RPN total loss: 0.06453 Total loss: 1.81053 timestamp: 1655020227.9756732 iteration: 15460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18909 FastRCNN class loss: 0.09505 FastRCNN total loss: 0.28414 L1 loss: 0.0000e+00 L2 loss: 1.28657 Learning rate: 0.02 Mask loss: 0.13952 RPN box loss: 0.02249 RPN score loss: 0.00628 RPN total loss: 0.02877 Total loss: 1.739 timestamp: 1655020231.301851 iteration: 15465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13121 FastRCNN class loss: 0.10974 FastRCNN total loss: 0.24095 L1 loss: 0.0000e+00 L2 loss: 1.28634 Learning rate: 0.02 Mask loss: 0.21933 RPN box loss: 0.06898 RPN score loss: 0.00503 RPN total loss: 0.07401 Total loss: 1.82064 timestamp: 1655020234.7019167 iteration: 15470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21598 FastRCNN class loss: 0.09726 FastRCNN total loss: 0.31324 L1 loss: 0.0000e+00 L2 loss: 1.28609 Learning rate: 0.02 Mask loss: 0.2122 RPN box loss: 0.03833 RPN score loss: 0.01757 RPN total loss: 0.0559 Total loss: 1.86743 timestamp: 1655020238.0039372 iteration: 15475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15612 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.2168 L1 loss: 0.0000e+00 L2 loss: 1.28585 Learning rate: 0.02 Mask loss: 0.16458 RPN box loss: 0.05352 RPN score loss: 0.00998 RPN total loss: 0.0635 Total loss: 1.73074 timestamp: 1655020241.368251 iteration: 15480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10014 FastRCNN class loss: 0.05895 FastRCNN total loss: 0.1591 L1 loss: 0.0000e+00 L2 loss: 1.28563 Learning rate: 0.02 Mask loss: 0.13007 RPN box loss: 0.04495 RPN score loss: 0.00992 RPN total loss: 0.05487 Total loss: 1.62966 timestamp: 1655020244.6618686 iteration: 15485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14282 FastRCNN class loss: 0.10886 FastRCNN total loss: 0.25168 L1 loss: 0.0000e+00 L2 loss: 1.28542 Learning rate: 0.02 Mask loss: 0.30096 RPN box loss: 0.01645 RPN score loss: 0.00839 RPN total loss: 0.02484 Total loss: 1.86291 timestamp: 1655020248.091948 iteration: 15490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23758 FastRCNN class loss: 0.17894 FastRCNN total loss: 0.41652 L1 loss: 0.0000e+00 L2 loss: 1.28523 Learning rate: 0.02 Mask loss: 0.19396 RPN box loss: 0.03926 RPN score loss: 0.00903 RPN total loss: 0.04828 Total loss: 1.94399 timestamp: 1655020251.3802807 iteration: 15495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21727 FastRCNN class loss: 0.14064 FastRCNN total loss: 0.35791 L1 loss: 0.0000e+00 L2 loss: 1.28499 Learning rate: 0.02 Mask loss: 0.21465 RPN box loss: 0.08592 RPN score loss: 0.0176 RPN total loss: 0.10352 Total loss: 1.96108 timestamp: 1655020254.7419372 iteration: 15500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.04565 FastRCNN total loss: 0.17777 L1 loss: 0.0000e+00 L2 loss: 1.28477 Learning rate: 0.02 Mask loss: 0.11637 RPN box loss: 0.02401 RPN score loss: 0.00511 RPN total loss: 0.02911 Total loss: 1.60803 timestamp: 1655020258.0928226 iteration: 15505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10587 FastRCNN class loss: 0.05349 FastRCNN total loss: 0.15936 L1 loss: 0.0000e+00 L2 loss: 1.28452 Learning rate: 0.02 Mask loss: 0.16651 RPN box loss: 0.0351 RPN score loss: 0.00271 RPN total loss: 0.03781 Total loss: 1.6482 timestamp: 1655020261.4829948 iteration: 15510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17577 FastRCNN class loss: 0.13849 FastRCNN total loss: 0.31426 L1 loss: 0.0000e+00 L2 loss: 1.28426 Learning rate: 0.02 Mask loss: 0.22589 RPN box loss: 0.0501 RPN score loss: 0.00858 RPN total loss: 0.05868 Total loss: 1.8831 timestamp: 1655020264.8284125 iteration: 15515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18687 FastRCNN class loss: 0.14434 FastRCNN total loss: 0.33122 L1 loss: 0.0000e+00 L2 loss: 1.28404 Learning rate: 0.02 Mask loss: 0.2402 RPN box loss: 0.03261 RPN score loss: 0.01276 RPN total loss: 0.04537 Total loss: 1.90083 timestamp: 1655020268.121248 iteration: 15520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17817 FastRCNN class loss: 0.10274 FastRCNN total loss: 0.2809 L1 loss: 0.0000e+00 L2 loss: 1.28382 Learning rate: 0.02 Mask loss: 0.23095 RPN box loss: 0.03989 RPN score loss: 0.01657 RPN total loss: 0.05646 Total loss: 1.85214 timestamp: 1655020271.4490447 iteration: 15525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19025 FastRCNN class loss: 0.09837 FastRCNN total loss: 0.28862 L1 loss: 0.0000e+00 L2 loss: 1.28359 Learning rate: 0.02 Mask loss: 0.13686 RPN box loss: 0.02229 RPN score loss: 0.0043 RPN total loss: 0.02658 Total loss: 1.73564 timestamp: 1655020274.7274745 iteration: 15530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17796 FastRCNN class loss: 0.09221 FastRCNN total loss: 0.27016 L1 loss: 0.0000e+00 L2 loss: 1.28337 Learning rate: 0.02 Mask loss: 0.2729 RPN box loss: 0.02359 RPN score loss: 0.00731 RPN total loss: 0.0309 Total loss: 1.85734 timestamp: 1655020278.1281834 iteration: 15535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15161 FastRCNN class loss: 0.11856 FastRCNN total loss: 0.27017 L1 loss: 0.0000e+00 L2 loss: 1.28314 Learning rate: 0.02 Mask loss: 0.21477 RPN box loss: 0.06711 RPN score loss: 0.02681 RPN total loss: 0.09391 Total loss: 1.862 timestamp: 1655020281.4405882 iteration: 15540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17294 FastRCNN class loss: 0.11193 FastRCNN total loss: 0.28487 L1 loss: 0.0000e+00 L2 loss: 1.28293 Learning rate: 0.02 Mask loss: 0.17376 RPN box loss: 0.05801 RPN score loss: 0.02294 RPN total loss: 0.08095 Total loss: 1.82251 timestamp: 1655020284.8092878 iteration: 15545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26072 FastRCNN class loss: 0.15221 FastRCNN total loss: 0.41293 L1 loss: 0.0000e+00 L2 loss: 1.2827 Learning rate: 0.02 Mask loss: 0.28313 RPN box loss: 0.03518 RPN score loss: 0.00581 RPN total loss: 0.04099 Total loss: 2.01975 timestamp: 1655020288.2133162 iteration: 15550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14888 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.22001 L1 loss: 0.0000e+00 L2 loss: 1.28245 Learning rate: 0.02 Mask loss: 0.12191 RPN box loss: 0.04687 RPN score loss: 0.0059 RPN total loss: 0.05277 Total loss: 1.67714 timestamp: 1655020291.5135655 iteration: 15555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2475 FastRCNN class loss: 0.12869 FastRCNN total loss: 0.37618 L1 loss: 0.0000e+00 L2 loss: 1.28223 Learning rate: 0.02 Mask loss: 0.27647 RPN box loss: 0.07628 RPN score loss: 0.02718 RPN total loss: 0.10346 Total loss: 2.03834 timestamp: 1655020294.8803067 iteration: 15560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0892 FastRCNN class loss: 0.04132 FastRCNN total loss: 0.13052 L1 loss: 0.0000e+00 L2 loss: 1.28202 Learning rate: 0.02 Mask loss: 0.12437 RPN box loss: 0.0422 RPN score loss: 0.00944 RPN total loss: 0.05164 Total loss: 1.58856 timestamp: 1655020298.1481547 iteration: 15565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20345 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.304 L1 loss: 0.0000e+00 L2 loss: 1.2818 Learning rate: 0.02 Mask loss: 0.1714 RPN box loss: 0.03255 RPN score loss: 0.01109 RPN total loss: 0.04364 Total loss: 1.80083 timestamp: 1655020301.5366654 iteration: 15570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11461 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.20747 L1 loss: 0.0000e+00 L2 loss: 1.28157 Learning rate: 0.02 Mask loss: 0.25431 RPN box loss: 0.04136 RPN score loss: 0.01437 RPN total loss: 0.05573 Total loss: 1.79908 timestamp: 1655020304.8425052 iteration: 15575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24819 FastRCNN class loss: 0.15831 FastRCNN total loss: 0.4065 L1 loss: 0.0000e+00 L2 loss: 1.28136 Learning rate: 0.02 Mask loss: 0.14271 RPN box loss: 0.02658 RPN score loss: 0.00896 RPN total loss: 0.03554 Total loss: 1.86611 timestamp: 1655020308.2768035 iteration: 15580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.10143 FastRCNN total loss: 0.19828 L1 loss: 0.0000e+00 L2 loss: 1.28112 Learning rate: 0.02 Mask loss: 0.1464 RPN box loss: 0.05123 RPN score loss: 0.0131 RPN total loss: 0.06433 Total loss: 1.69013 timestamp: 1655020311.5481539 iteration: 15585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15289 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.23433 L1 loss: 0.0000e+00 L2 loss: 1.28088 Learning rate: 0.02 Mask loss: 0.14416 RPN box loss: 0.03765 RPN score loss: 0.00272 RPN total loss: 0.04038 Total loss: 1.69974 timestamp: 1655020314.911543 iteration: 15590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1614 FastRCNN class loss: 0.08096 FastRCNN total loss: 0.24236 L1 loss: 0.0000e+00 L2 loss: 1.28066 Learning rate: 0.02 Mask loss: 0.1759 RPN box loss: 0.09159 RPN score loss: 0.00672 RPN total loss: 0.09831 Total loss: 1.79724 timestamp: 1655020318.3927271 iteration: 15595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12205 FastRCNN class loss: 0.0777 FastRCNN total loss: 0.19974 L1 loss: 0.0000e+00 L2 loss: 1.28041 Learning rate: 0.02 Mask loss: 0.17821 RPN box loss: 0.05322 RPN score loss: 0.01635 RPN total loss: 0.06958 Total loss: 1.72794 timestamp: 1655020321.680494 iteration: 15600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16581 FastRCNN class loss: 0.12221 FastRCNN total loss: 0.28802 L1 loss: 0.0000e+00 L2 loss: 1.28018 Learning rate: 0.02 Mask loss: 0.1804 RPN box loss: 0.08715 RPN score loss: 0.00995 RPN total loss: 0.0971 Total loss: 1.8457 timestamp: 1655020325.0614355 iteration: 15605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10099 FastRCNN class loss: 0.03567 FastRCNN total loss: 0.13666 L1 loss: 0.0000e+00 L2 loss: 1.27998 Learning rate: 0.02 Mask loss: 0.13593 RPN box loss: 0.00586 RPN score loss: 0.00529 RPN total loss: 0.01115 Total loss: 1.56371 timestamp: 1655020328.3593113 iteration: 15610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15452 FastRCNN class loss: 0.09012 FastRCNN total loss: 0.24465 L1 loss: 0.0000e+00 L2 loss: 1.27976 Learning rate: 0.02 Mask loss: 0.19227 RPN box loss: 0.06521 RPN score loss: 0.00751 RPN total loss: 0.07272 Total loss: 1.7894 timestamp: 1655020331.7253919 iteration: 15615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21128 FastRCNN class loss: 0.10317 FastRCNN total loss: 0.31445 L1 loss: 0.0000e+00 L2 loss: 1.27952 Learning rate: 0.02 Mask loss: 0.2519 RPN box loss: 0.03388 RPN score loss: 0.00733 RPN total loss: 0.0412 Total loss: 1.88708 timestamp: 1655020334.9482777 iteration: 15620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20112 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.26589 L1 loss: 0.0000e+00 L2 loss: 1.27932 Learning rate: 0.02 Mask loss: 0.17481 RPN box loss: 0.05217 RPN score loss: 0.00812 RPN total loss: 0.06029 Total loss: 1.78032 timestamp: 1655020338.3313706 iteration: 15625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19161 FastRCNN class loss: 0.09698 FastRCNN total loss: 0.28859 L1 loss: 0.0000e+00 L2 loss: 1.27908 Learning rate: 0.02 Mask loss: 0.15919 RPN box loss: 0.05474 RPN score loss: 0.00415 RPN total loss: 0.0589 Total loss: 1.78576 timestamp: 1655020341.664212 iteration: 15630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18309 FastRCNN class loss: 0.12224 FastRCNN total loss: 0.30533 L1 loss: 0.0000e+00 L2 loss: 1.27884 Learning rate: 0.02 Mask loss: 0.18331 RPN box loss: 0.02806 RPN score loss: 0.00787 RPN total loss: 0.03593 Total loss: 1.80342 timestamp: 1655020344.980338 iteration: 15635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2342 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.31772 L1 loss: 0.0000e+00 L2 loss: 1.27862 Learning rate: 0.02 Mask loss: 0.22326 RPN box loss: 0.02638 RPN score loss: 0.00351 RPN total loss: 0.0299 Total loss: 1.8495 timestamp: 1655020348.3509092 iteration: 15640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12013 FastRCNN class loss: 0.10295 FastRCNN total loss: 0.22308 L1 loss: 0.0000e+00 L2 loss: 1.27838 Learning rate: 0.02 Mask loss: 0.1585 RPN box loss: 0.01053 RPN score loss: 0.0029 RPN total loss: 0.01343 Total loss: 1.6734 timestamp: 1655020351.6135623 iteration: 15645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.04023 FastRCNN total loss: 0.14604 L1 loss: 0.0000e+00 L2 loss: 1.27816 Learning rate: 0.02 Mask loss: 0.14481 RPN box loss: 0.01566 RPN score loss: 0.00267 RPN total loss: 0.01833 Total loss: 1.58734 timestamp: 1655020354.9749281 iteration: 15650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1109 FastRCNN class loss: 0.04899 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 1.27797 Learning rate: 0.02 Mask loss: 0.16864 RPN box loss: 0.05054 RPN score loss: 0.00694 RPN total loss: 0.05748 Total loss: 1.66398 timestamp: 1655020358.2505944 iteration: 15655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19799 FastRCNN class loss: 0.12435 FastRCNN total loss: 0.32234 L1 loss: 0.0000e+00 L2 loss: 1.27773 Learning rate: 0.02 Mask loss: 0.24605 RPN box loss: 0.03149 RPN score loss: 0.02056 RPN total loss: 0.05205 Total loss: 1.89817 timestamp: 1655020361.67288 iteration: 15660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17076 FastRCNN class loss: 0.11267 FastRCNN total loss: 0.28344 L1 loss: 0.0000e+00 L2 loss: 1.27752 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.0292 RPN score loss: 0.01491 RPN total loss: 0.04412 Total loss: 1.75415 timestamp: 1655020364.9402654 iteration: 15665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15256 FastRCNN class loss: 0.09359 FastRCNN total loss: 0.24615 L1 loss: 0.0000e+00 L2 loss: 1.27728 Learning rate: 0.02 Mask loss: 0.14057 RPN box loss: 0.05868 RPN score loss: 0.0229 RPN total loss: 0.08157 Total loss: 1.74558 timestamp: 1655020368.2666469 iteration: 15670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14149 FastRCNN class loss: 0.05444 FastRCNN total loss: 0.19593 L1 loss: 0.0000e+00 L2 loss: 1.27707 Learning rate: 0.02 Mask loss: 0.11449 RPN box loss: 0.06775 RPN score loss: 0.00315 RPN total loss: 0.0709 Total loss: 1.65839 timestamp: 1655020371.6876256 iteration: 15675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10689 FastRCNN class loss: 0.08563 FastRCNN total loss: 0.19252 L1 loss: 0.0000e+00 L2 loss: 1.27683 Learning rate: 0.02 Mask loss: 0.23598 RPN box loss: 0.01007 RPN score loss: 0.00415 RPN total loss: 0.01422 Total loss: 1.71955 timestamp: 1655020374.9348955 iteration: 15680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22788 FastRCNN class loss: 0.14398 FastRCNN total loss: 0.37185 L1 loss: 0.0000e+00 L2 loss: 1.27659 Learning rate: 0.02 Mask loss: 0.22762 RPN box loss: 0.04563 RPN score loss: 0.01476 RPN total loss: 0.06038 Total loss: 1.93644 timestamp: 1655020378.322625 iteration: 15685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22136 FastRCNN class loss: 0.09569 FastRCNN total loss: 0.31705 L1 loss: 0.0000e+00 L2 loss: 1.27636 Learning rate: 0.02 Mask loss: 0.16347 RPN box loss: 0.03802 RPN score loss: 0.00867 RPN total loss: 0.04669 Total loss: 1.80357 timestamp: 1655020381.58654 iteration: 15690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13519 FastRCNN class loss: 0.15498 FastRCNN total loss: 0.29017 L1 loss: 0.0000e+00 L2 loss: 1.27614 Learning rate: 0.02 Mask loss: 0.15098 RPN box loss: 0.06416 RPN score loss: 0.01 RPN total loss: 0.07416 Total loss: 1.79145 timestamp: 1655020385.0250802 iteration: 15695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10314 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.18689 L1 loss: 0.0000e+00 L2 loss: 1.27591 Learning rate: 0.02 Mask loss: 0.13078 RPN box loss: 0.03645 RPN score loss: 0.00926 RPN total loss: 0.04571 Total loss: 1.63929 timestamp: 1655020388.355732 iteration: 15700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18976 FastRCNN class loss: 0.07867 FastRCNN total loss: 0.26842 L1 loss: 0.0000e+00 L2 loss: 1.27569 Learning rate: 0.02 Mask loss: 0.17149 RPN box loss: 0.02254 RPN score loss: 0.01382 RPN total loss: 0.03636 Total loss: 1.75196 timestamp: 1655020391.7701974 iteration: 15705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.16476 L1 loss: 0.0000e+00 L2 loss: 1.27548 Learning rate: 0.02 Mask loss: 0.23126 RPN box loss: 0.01056 RPN score loss: 0.00675 RPN total loss: 0.01731 Total loss: 1.68881 timestamp: 1655020395.0333707 iteration: 15710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.06204 FastRCNN total loss: 0.17449 L1 loss: 0.0000e+00 L2 loss: 1.27527 Learning rate: 0.02 Mask loss: 0.18751 RPN box loss: 0.09473 RPN score loss: 0.00998 RPN total loss: 0.10471 Total loss: 1.74197 timestamp: 1655020398.370272 iteration: 15715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18231 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.25568 L1 loss: 0.0000e+00 L2 loss: 1.27503 Learning rate: 0.02 Mask loss: 0.17735 RPN box loss: 0.05653 RPN score loss: 0.00721 RPN total loss: 0.06375 Total loss: 1.77181 timestamp: 1655020401.7195675 iteration: 15720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.0525 FastRCNN total loss: 0.16771 L1 loss: 0.0000e+00 L2 loss: 1.27483 Learning rate: 0.02 Mask loss: 0.12305 RPN box loss: 0.02924 RPN score loss: 0.00292 RPN total loss: 0.03216 Total loss: 1.59775 timestamp: 1655020404.9126759 iteration: 15725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12869 FastRCNN class loss: 0.04885 FastRCNN total loss: 0.17754 L1 loss: 0.0000e+00 L2 loss: 1.27463 Learning rate: 0.02 Mask loss: 0.14187 RPN box loss: 0.02544 RPN score loss: 0.00554 RPN total loss: 0.03098 Total loss: 1.62501 timestamp: 1655020408.289473 iteration: 15730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17884 FastRCNN class loss: 0.12351 FastRCNN total loss: 0.30235 L1 loss: 0.0000e+00 L2 loss: 1.27441 Learning rate: 0.02 Mask loss: 0.19986 RPN box loss: 0.0234 RPN score loss: 0.00382 RPN total loss: 0.02722 Total loss: 1.80384 timestamp: 1655020411.6798081 iteration: 15735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12344 FastRCNN class loss: 0.05903 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 1.27418 Learning rate: 0.02 Mask loss: 0.16301 RPN box loss: 0.04297 RPN score loss: 0.00624 RPN total loss: 0.04921 Total loss: 1.66887 timestamp: 1655020415.0339186 iteration: 15740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1415 FastRCNN class loss: 0.0906 FastRCNN total loss: 0.2321 L1 loss: 0.0000e+00 L2 loss: 1.27398 Learning rate: 0.02 Mask loss: 0.20282 RPN box loss: 0.07834 RPN score loss: 0.0313 RPN total loss: 0.10963 Total loss: 1.81854 timestamp: 1655020418.3437295 iteration: 15745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21349 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.28376 L1 loss: 0.0000e+00 L2 loss: 1.27373 Learning rate: 0.02 Mask loss: 0.27654 RPN box loss: 0.03607 RPN score loss: 0.00939 RPN total loss: 0.04547 Total loss: 1.8795 timestamp: 1655020421.6683133 iteration: 15750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14229 FastRCNN class loss: 0.10637 FastRCNN total loss: 0.24866 L1 loss: 0.0000e+00 L2 loss: 1.27348 Learning rate: 0.02 Mask loss: 0.1861 RPN box loss: 0.03932 RPN score loss: 0.00885 RPN total loss: 0.04817 Total loss: 1.75641 timestamp: 1655020424.9879909 iteration: 15755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12487 FastRCNN class loss: 0.11402 FastRCNN total loss: 0.23889 L1 loss: 0.0000e+00 L2 loss: 1.27329 Learning rate: 0.02 Mask loss: 0.14211 RPN box loss: 0.03592 RPN score loss: 0.00413 RPN total loss: 0.04005 Total loss: 1.69434 timestamp: 1655020428.3767405 iteration: 15760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12555 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.20127 L1 loss: 0.0000e+00 L2 loss: 1.27309 Learning rate: 0.02 Mask loss: 0.19124 RPN box loss: 0.02185 RPN score loss: 0.00762 RPN total loss: 0.02947 Total loss: 1.69507 timestamp: 1655020431.6825361 iteration: 15765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20119 FastRCNN class loss: 0.10955 FastRCNN total loss: 0.31074 L1 loss: 0.0000e+00 L2 loss: 1.27286 Learning rate: 0.02 Mask loss: 0.2287 RPN box loss: 0.02465 RPN score loss: 0.00906 RPN total loss: 0.0337 Total loss: 1.84601 timestamp: 1655020434.9423003 iteration: 15770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20185 FastRCNN class loss: 0.15259 FastRCNN total loss: 0.35445 L1 loss: 0.0000e+00 L2 loss: 1.27264 Learning rate: 0.02 Mask loss: 0.21086 RPN box loss: 0.09323 RPN score loss: 0.01036 RPN total loss: 0.10359 Total loss: 1.94153 timestamp: 1655020438.3121188 iteration: 15775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15675 FastRCNN class loss: 0.08914 FastRCNN total loss: 0.24588 L1 loss: 0.0000e+00 L2 loss: 1.27241 Learning rate: 0.02 Mask loss: 0.23004 RPN box loss: 0.06928 RPN score loss: 0.00833 RPN total loss: 0.0776 Total loss: 1.82594 timestamp: 1655020441.5796702 iteration: 15780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13757 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.21676 L1 loss: 0.0000e+00 L2 loss: 1.2722 Learning rate: 0.02 Mask loss: 0.12404 RPN box loss: 0.04805 RPN score loss: 0.00951 RPN total loss: 0.05756 Total loss: 1.67055 timestamp: 1655020444.9481943 iteration: 15785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14964 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.22853 L1 loss: 0.0000e+00 L2 loss: 1.27197 Learning rate: 0.02 Mask loss: 0.1988 RPN box loss: 0.02471 RPN score loss: 0.01137 RPN total loss: 0.03608 Total loss: 1.73537 timestamp: 1655020448.2326877 iteration: 15790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16073 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.23324 L1 loss: 0.0000e+00 L2 loss: 1.27172 Learning rate: 0.02 Mask loss: 0.17446 RPN box loss: 0.03326 RPN score loss: 0.01123 RPN total loss: 0.0445 Total loss: 1.72391 timestamp: 1655020451.6949303 iteration: 15795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10241 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.168 L1 loss: 0.0000e+00 L2 loss: 1.27149 Learning rate: 0.02 Mask loss: 0.16116 RPN box loss: 0.0542 RPN score loss: 0.00388 RPN total loss: 0.05808 Total loss: 1.65873 timestamp: 1655020454.9804788 iteration: 15800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23431 FastRCNN class loss: 0.13986 FastRCNN total loss: 0.37417 L1 loss: 0.0000e+00 L2 loss: 1.27126 Learning rate: 0.02 Mask loss: 0.25206 RPN box loss: 0.0447 RPN score loss: 0.01186 RPN total loss: 0.05657 Total loss: 1.95407 timestamp: 1655020458.3424127 iteration: 15805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15176 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.24783 L1 loss: 0.0000e+00 L2 loss: 1.27104 Learning rate: 0.02 Mask loss: 0.17746 RPN box loss: 0.05711 RPN score loss: 0.00872 RPN total loss: 0.06584 Total loss: 1.76217 timestamp: 1655020461.6722522 iteration: 15810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16997 FastRCNN class loss: 0.12175 FastRCNN total loss: 0.29173 L1 loss: 0.0000e+00 L2 loss: 1.27083 Learning rate: 0.02 Mask loss: 0.20164 RPN box loss: 0.0766 RPN score loss: 0.019 RPN total loss: 0.09561 Total loss: 1.8598 timestamp: 1655020464.9855216 iteration: 15815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14088 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.21868 L1 loss: 0.0000e+00 L2 loss: 1.27062 Learning rate: 0.02 Mask loss: 0.23637 RPN box loss: 0.03312 RPN score loss: 0.01774 RPN total loss: 0.05086 Total loss: 1.77652 timestamp: 1655020468.3047268 iteration: 15820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22327 FastRCNN class loss: 0.10518 FastRCNN total loss: 0.32845 L1 loss: 0.0000e+00 L2 loss: 1.27041 Learning rate: 0.02 Mask loss: 0.18895 RPN box loss: 0.01319 RPN score loss: 0.00265 RPN total loss: 0.01584 Total loss: 1.80364 timestamp: 1655020471.5890281 iteration: 15825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08682 FastRCNN class loss: 0.07158 FastRCNN total loss: 0.1584 L1 loss: 0.0000e+00 L2 loss: 1.27019 Learning rate: 0.02 Mask loss: 0.17279 RPN box loss: 0.01617 RPN score loss: 0.00678 RPN total loss: 0.02295 Total loss: 1.62433 timestamp: 1655020474.9129436 iteration: 15830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11182 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.17629 L1 loss: 0.0000e+00 L2 loss: 1.26998 Learning rate: 0.02 Mask loss: 0.19645 RPN box loss: 0.06815 RPN score loss: 0.00709 RPN total loss: 0.07524 Total loss: 1.71796 timestamp: 1655020478.1993804 iteration: 15835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13031 FastRCNN class loss: 0.06743 FastRCNN total loss: 0.19774 L1 loss: 0.0000e+00 L2 loss: 1.26976 Learning rate: 0.02 Mask loss: 0.16979 RPN box loss: 0.02247 RPN score loss: 0.00705 RPN total loss: 0.02952 Total loss: 1.66682 timestamp: 1655020481.5751643 iteration: 15840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13112 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.20505 L1 loss: 0.0000e+00 L2 loss: 1.26952 Learning rate: 0.02 Mask loss: 0.32866 RPN box loss: 0.07833 RPN score loss: 0.01909 RPN total loss: 0.09741 Total loss: 1.90064 timestamp: 1655020484.8349872 iteration: 15845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15055 FastRCNN class loss: 0.08391 FastRCNN total loss: 0.23446 L1 loss: 0.0000e+00 L2 loss: 1.26928 Learning rate: 0.02 Mask loss: 0.161 RPN box loss: 0.0388 RPN score loss: 0.00615 RPN total loss: 0.04494 Total loss: 1.70969 timestamp: 1655020488.23296 iteration: 15850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17235 FastRCNN class loss: 0.15495 FastRCNN total loss: 0.3273 L1 loss: 0.0000e+00 L2 loss: 1.26909 Learning rate: 0.02 Mask loss: 0.19693 RPN box loss: 0.07786 RPN score loss: 0.01383 RPN total loss: 0.09169 Total loss: 1.88501 timestamp: 1655020491.6075385 iteration: 15855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14494 FastRCNN class loss: 0.10509 FastRCNN total loss: 0.25003 L1 loss: 0.0000e+00 L2 loss: 1.26886 Learning rate: 0.02 Mask loss: 0.25737 RPN box loss: 0.06062 RPN score loss: 0.01481 RPN total loss: 0.07543 Total loss: 1.85169 timestamp: 1655020494.9504588 iteration: 15860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14122 FastRCNN class loss: 0.05 FastRCNN total loss: 0.19122 L1 loss: 0.0000e+00 L2 loss: 1.26863 Learning rate: 0.02 Mask loss: 0.1544 RPN box loss: 0.01048 RPN score loss: 0.00603 RPN total loss: 0.01651 Total loss: 1.63076 timestamp: 1655020498.3140626 iteration: 15865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09202 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.15252 L1 loss: 0.0000e+00 L2 loss: 1.26844 Learning rate: 0.02 Mask loss: 0.11623 RPN box loss: 0.03028 RPN score loss: 0.00536 RPN total loss: 0.03564 Total loss: 1.57283 timestamp: 1655020501.6492925 iteration: 15870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12993 FastRCNN class loss: 0.13421 FastRCNN total loss: 0.26414 L1 loss: 0.0000e+00 L2 loss: 1.26823 Learning rate: 0.02 Mask loss: 0.11539 RPN box loss: 0.03812 RPN score loss: 0.0048 RPN total loss: 0.04291 Total loss: 1.69067 timestamp: 1655020504.9520485 iteration: 15875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.04624 FastRCNN total loss: 0.15686 L1 loss: 0.0000e+00 L2 loss: 1.26799 Learning rate: 0.02 Mask loss: 0.18976 RPN box loss: 0.05255 RPN score loss: 0.00783 RPN total loss: 0.06038 Total loss: 1.67499 timestamp: 1655020508.243996 iteration: 15880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15446 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.22821 L1 loss: 0.0000e+00 L2 loss: 1.26778 Learning rate: 0.02 Mask loss: 0.15303 RPN box loss: 0.03069 RPN score loss: 0.00482 RPN total loss: 0.03552 Total loss: 1.68453 timestamp: 1655020511.6025662 iteration: 15885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20832 FastRCNN class loss: 0.11775 FastRCNN total loss: 0.32607 L1 loss: 0.0000e+00 L2 loss: 1.26755 Learning rate: 0.02 Mask loss: 0.26769 RPN box loss: 0.01764 RPN score loss: 0.01396 RPN total loss: 0.0316 Total loss: 1.89291 timestamp: 1655020514.952229 iteration: 15890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1863 FastRCNN class loss: 0.13018 FastRCNN total loss: 0.31648 L1 loss: 0.0000e+00 L2 loss: 1.26731 Learning rate: 0.02 Mask loss: 0.15453 RPN box loss: 0.08921 RPN score loss: 0.0118 RPN total loss: 0.10101 Total loss: 1.83933 timestamp: 1655020518.2834616 iteration: 15895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22352 FastRCNN class loss: 0.09185 FastRCNN total loss: 0.31538 L1 loss: 0.0000e+00 L2 loss: 1.26711 Learning rate: 0.02 Mask loss: 0.13539 RPN box loss: 0.03305 RPN score loss: 0.00606 RPN total loss: 0.03912 Total loss: 1.75699 timestamp: 1655020521.73863 iteration: 15900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2036 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.29343 L1 loss: 0.0000e+00 L2 loss: 1.26691 Learning rate: 0.02 Mask loss: 0.16014 RPN box loss: 0.02074 RPN score loss: 0.0038 RPN total loss: 0.02454 Total loss: 1.74503 timestamp: 1655020525.0836332 iteration: 15905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0973 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.17274 L1 loss: 0.0000e+00 L2 loss: 1.26671 Learning rate: 0.02 Mask loss: 0.20706 RPN box loss: 0.09248 RPN score loss: 0.01745 RPN total loss: 0.10993 Total loss: 1.75644 timestamp: 1655020528.523371 iteration: 15910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21507 FastRCNN class loss: 0.12082 FastRCNN total loss: 0.33589 L1 loss: 0.0000e+00 L2 loss: 1.26647 Learning rate: 0.02 Mask loss: 0.16204 RPN box loss: 0.03022 RPN score loss: 0.00784 RPN total loss: 0.03806 Total loss: 1.80246 timestamp: 1655020531.8023503 iteration: 15915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10949 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.18274 L1 loss: 0.0000e+00 L2 loss: 1.26623 Learning rate: 0.02 Mask loss: 0.188 RPN box loss: 0.02215 RPN score loss: 0.00959 RPN total loss: 0.03174 Total loss: 1.66871 timestamp: 1655020535.127732 iteration: 15920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16591 FastRCNN class loss: 0.11257 FastRCNN total loss: 0.27848 L1 loss: 0.0000e+00 L2 loss: 1.26601 Learning rate: 0.02 Mask loss: 0.17642 RPN box loss: 0.0638 RPN score loss: 0.01017 RPN total loss: 0.07397 Total loss: 1.79488 timestamp: 1655020538.4647505 iteration: 15925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14284 FastRCNN class loss: 0.10948 FastRCNN total loss: 0.25232 L1 loss: 0.0000e+00 L2 loss: 1.2658 Learning rate: 0.02 Mask loss: 0.15027 RPN box loss: 0.02635 RPN score loss: 0.00918 RPN total loss: 0.03553 Total loss: 1.70392 timestamp: 1655020541.853552 iteration: 15930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21005 FastRCNN class loss: 0.10717 FastRCNN total loss: 0.31722 L1 loss: 0.0000e+00 L2 loss: 1.26558 Learning rate: 0.02 Mask loss: 0.20739 RPN box loss: 0.04861 RPN score loss: 0.00753 RPN total loss: 0.05615 Total loss: 1.84633 timestamp: 1655020545.112231 iteration: 15935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19838 FastRCNN class loss: 0.06916 FastRCNN total loss: 0.26754 L1 loss: 0.0000e+00 L2 loss: 1.26533 Learning rate: 0.02 Mask loss: 0.16677 RPN box loss: 0.02682 RPN score loss: 0.00454 RPN total loss: 0.03136 Total loss: 1.73101 timestamp: 1655020548.4844322 iteration: 15940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10976 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.18183 L1 loss: 0.0000e+00 L2 loss: 1.26511 Learning rate: 0.02 Mask loss: 0.21225 RPN box loss: 0.0513 RPN score loss: 0.01853 RPN total loss: 0.06984 Total loss: 1.72902 timestamp: 1655020551.809576 iteration: 15945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23891 FastRCNN class loss: 0.16409 FastRCNN total loss: 0.403 L1 loss: 0.0000e+00 L2 loss: 1.2649 Learning rate: 0.02 Mask loss: 0.23688 RPN box loss: 0.04878 RPN score loss: 0.02723 RPN total loss: 0.07601 Total loss: 1.98079 timestamp: 1655020555.07311 iteration: 15950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24893 FastRCNN class loss: 0.09284 FastRCNN total loss: 0.34177 L1 loss: 0.0000e+00 L2 loss: 1.26469 Learning rate: 0.02 Mask loss: 0.16624 RPN box loss: 0.04162 RPN score loss: 0.0038 RPN total loss: 0.04542 Total loss: 1.81812 timestamp: 1655020558.4826922 iteration: 15955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16812 FastRCNN class loss: 0.07923 FastRCNN total loss: 0.24736 L1 loss: 0.0000e+00 L2 loss: 1.26449 Learning rate: 0.02 Mask loss: 0.15991 RPN box loss: 0.03073 RPN score loss: 0.00623 RPN total loss: 0.03696 Total loss: 1.70872 timestamp: 1655020561.832914 iteration: 15960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29685 FastRCNN class loss: 0.09161 FastRCNN total loss: 0.38846 L1 loss: 0.0000e+00 L2 loss: 1.26425 Learning rate: 0.02 Mask loss: 0.14638 RPN box loss: 0.0122 RPN score loss: 0.00789 RPN total loss: 0.02009 Total loss: 1.81919 timestamp: 1655020565.1533382 iteration: 15965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20434 FastRCNN class loss: 0.1035 FastRCNN total loss: 0.30783 L1 loss: 0.0000e+00 L2 loss: 1.26401 Learning rate: 0.02 Mask loss: 0.22432 RPN box loss: 0.03458 RPN score loss: 0.02412 RPN total loss: 0.0587 Total loss: 1.85487 timestamp: 1655020568.437796 iteration: 15970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15377 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.20491 L1 loss: 0.0000e+00 L2 loss: 1.26379 Learning rate: 0.02 Mask loss: 0.17889 RPN box loss: 0.00755 RPN score loss: 0.00155 RPN total loss: 0.0091 Total loss: 1.6567 timestamp: 1655020571.813261 iteration: 15975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18144 FastRCNN class loss: 0.13984 FastRCNN total loss: 0.32128 L1 loss: 0.0000e+00 L2 loss: 1.26356 Learning rate: 0.02 Mask loss: 0.26567 RPN box loss: 0.11416 RPN score loss: 0.00969 RPN total loss: 0.12385 Total loss: 1.97436 timestamp: 1655020575.1878028 iteration: 15980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12181 FastRCNN class loss: 0.07955 FastRCNN total loss: 0.20136 L1 loss: 0.0000e+00 L2 loss: 1.26334 Learning rate: 0.02 Mask loss: 0.20183 RPN box loss: 0.03181 RPN score loss: 0.00622 RPN total loss: 0.03802 Total loss: 1.70456 timestamp: 1655020578.4291742 iteration: 15985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17308 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.25806 L1 loss: 0.0000e+00 L2 loss: 1.26312 Learning rate: 0.02 Mask loss: 0.23608 RPN box loss: 0.01134 RPN score loss: 0.00615 RPN total loss: 0.01749 Total loss: 1.77474 timestamp: 1655020581.7841995 iteration: 15990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2198 FastRCNN class loss: 0.09898 FastRCNN total loss: 0.31878 L1 loss: 0.0000e+00 L2 loss: 1.2629 Learning rate: 0.02 Mask loss: 0.15625 RPN box loss: 0.06746 RPN score loss: 0.01163 RPN total loss: 0.07909 Total loss: 1.81702 timestamp: 1655020585.0955381 iteration: 15995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.03987 FastRCNN total loss: 0.13019 L1 loss: 0.0000e+00 L2 loss: 1.26269 Learning rate: 0.02 Mask loss: 0.14963 RPN box loss: 0.0014 RPN score loss: 0.00327 RPN total loss: 0.00467 Total loss: 1.54719 timestamp: 1655020588.5531962 iteration: 16000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11743 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.17276 L1 loss: 0.0000e+00 L2 loss: 1.26248 Learning rate: 0.02 Mask loss: 0.2125 RPN box loss: 0.05657 RPN score loss: 0.00394 RPN total loss: 0.06051 Total loss: 1.70825 timestamp: 1655020591.7626042 iteration: 16005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15631 FastRCNN class loss: 0.07707 FastRCNN total loss: 0.23338 L1 loss: 0.0000e+00 L2 loss: 1.26226 Learning rate: 0.02 Mask loss: 0.13194 RPN box loss: 0.02585 RPN score loss: 0.00156 RPN total loss: 0.02741 Total loss: 1.655 timestamp: 1655020595.1311164 iteration: 16010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15193 FastRCNN class loss: 0.17171 FastRCNN total loss: 0.32364 L1 loss: 0.0000e+00 L2 loss: 1.26203 Learning rate: 0.02 Mask loss: 0.20319 RPN box loss: 0.0384 RPN score loss: 0.00699 RPN total loss: 0.04538 Total loss: 1.83424 timestamp: 1655020598.3706622 iteration: 16015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14285 FastRCNN class loss: 0.10585 FastRCNN total loss: 0.2487 L1 loss: 0.0000e+00 L2 loss: 1.26183 Learning rate: 0.02 Mask loss: 0.17527 RPN box loss: 0.03602 RPN score loss: 0.01097 RPN total loss: 0.04699 Total loss: 1.73278 timestamp: 1655020601.77328 iteration: 16020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21837 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.30786 L1 loss: 0.0000e+00 L2 loss: 1.26161 Learning rate: 0.02 Mask loss: 0.18778 RPN box loss: 0.02752 RPN score loss: 0.00902 RPN total loss: 0.03654 Total loss: 1.7938 timestamp: 1655020605.1607192 iteration: 16025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20679 FastRCNN class loss: 0.07166 FastRCNN total loss: 0.27845 L1 loss: 0.0000e+00 L2 loss: 1.26138 Learning rate: 0.02 Mask loss: 0.14197 RPN box loss: 0.02211 RPN score loss: 0.00333 RPN total loss: 0.02544 Total loss: 1.70724 timestamp: 1655020608.4268968 iteration: 16030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.22431 L1 loss: 0.0000e+00 L2 loss: 1.26115 Learning rate: 0.02 Mask loss: 0.32054 RPN box loss: 0.06491 RPN score loss: 0.00462 RPN total loss: 0.06953 Total loss: 1.87554 timestamp: 1655020611.783916 iteration: 16035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11577 FastRCNN class loss: 0.10781 FastRCNN total loss: 0.22357 L1 loss: 0.0000e+00 L2 loss: 1.26094 Learning rate: 0.02 Mask loss: 0.17138 RPN box loss: 0.02496 RPN score loss: 0.0168 RPN total loss: 0.04176 Total loss: 1.69765 timestamp: 1655020615.112767 iteration: 16040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19304 FastRCNN class loss: 0.10032 FastRCNN total loss: 0.29336 L1 loss: 0.0000e+00 L2 loss: 1.2607 Learning rate: 0.02 Mask loss: 0.19756 RPN box loss: 0.01488 RPN score loss: 0.00687 RPN total loss: 0.02175 Total loss: 1.77337 timestamp: 1655020618.4519367 iteration: 16045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2173 FastRCNN class loss: 0.11461 FastRCNN total loss: 0.3319 L1 loss: 0.0000e+00 L2 loss: 1.26048 Learning rate: 0.02 Mask loss: 0.28016 RPN box loss: 0.04218 RPN score loss: 0.00807 RPN total loss: 0.05026 Total loss: 1.92281 timestamp: 1655020621.7515922 iteration: 16050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11527 FastRCNN class loss: 0.05628 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 1.26027 Learning rate: 0.02 Mask loss: 0.17186 RPN box loss: 0.08689 RPN score loss: 0.00945 RPN total loss: 0.09634 Total loss: 1.70003 timestamp: 1655020625.1554418 iteration: 16055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15232 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.21687 L1 loss: 0.0000e+00 L2 loss: 1.26005 Learning rate: 0.02 Mask loss: 0.13771 RPN box loss: 0.0566 RPN score loss: 0.0063 RPN total loss: 0.0629 Total loss: 1.67752 timestamp: 1655020628.4227853 iteration: 16060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12544 FastRCNN class loss: 0.08508 FastRCNN total loss: 0.21052 L1 loss: 0.0000e+00 L2 loss: 1.25983 Learning rate: 0.02 Mask loss: 0.16245 RPN box loss: 0.06726 RPN score loss: 0.02186 RPN total loss: 0.08912 Total loss: 1.72192 timestamp: 1655020631.8634577 iteration: 16065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17327 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.26774 L1 loss: 0.0000e+00 L2 loss: 1.25961 Learning rate: 0.02 Mask loss: 0.16444 RPN box loss: 0.02817 RPN score loss: 0.00489 RPN total loss: 0.03305 Total loss: 1.72485 timestamp: 1655020635.304309 iteration: 16070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20108 FastRCNN class loss: 0.1529 FastRCNN total loss: 0.35398 L1 loss: 0.0000e+00 L2 loss: 1.25939 Learning rate: 0.02 Mask loss: 0.18327 RPN box loss: 0.04862 RPN score loss: 0.00468 RPN total loss: 0.0533 Total loss: 1.84994 timestamp: 1655020638.494848 iteration: 16075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17898 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.25518 L1 loss: 0.0000e+00 L2 loss: 1.25915 Learning rate: 0.02 Mask loss: 0.21429 RPN box loss: 0.02078 RPN score loss: 0.01065 RPN total loss: 0.03142 Total loss: 1.76005 timestamp: 1655020641.9071085 iteration: 16080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1262 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.19525 L1 loss: 0.0000e+00 L2 loss: 1.25894 Learning rate: 0.02 Mask loss: 0.14358 RPN box loss: 0.0128 RPN score loss: 0.0052 RPN total loss: 0.01799 Total loss: 1.61576 timestamp: 1655020645.1721525 iteration: 16085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10618 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.15919 L1 loss: 0.0000e+00 L2 loss: 1.25871 Learning rate: 0.02 Mask loss: 0.16196 RPN box loss: 0.02004 RPN score loss: 0.00748 RPN total loss: 0.02752 Total loss: 1.60738 timestamp: 1655020648.4339101 iteration: 16090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16222 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.23218 L1 loss: 0.0000e+00 L2 loss: 1.2585 Learning rate: 0.02 Mask loss: 0.23364 RPN box loss: 0.02563 RPN score loss: 0.00402 RPN total loss: 0.02965 Total loss: 1.75397 timestamp: 1655020651.6736798 iteration: 16095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22479 FastRCNN class loss: 0.10888 FastRCNN total loss: 0.33367 L1 loss: 0.0000e+00 L2 loss: 1.25828 Learning rate: 0.02 Mask loss: 0.31811 RPN box loss: 0.03212 RPN score loss: 0.00678 RPN total loss: 0.0389 Total loss: 1.94897 timestamp: 1655020655.1072512 iteration: 16100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13683 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.21788 L1 loss: 0.0000e+00 L2 loss: 1.25806 Learning rate: 0.02 Mask loss: 0.15572 RPN box loss: 0.02851 RPN score loss: 0.01097 RPN total loss: 0.03948 Total loss: 1.67114 timestamp: 1655020658.3169782 iteration: 16105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19552 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.27671 L1 loss: 0.0000e+00 L2 loss: 1.25786 Learning rate: 0.02 Mask loss: 0.20422 RPN box loss: 0.03158 RPN score loss: 0.00791 RPN total loss: 0.03949 Total loss: 1.77829 timestamp: 1655020661.8000524 iteration: 16110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18204 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.24453 L1 loss: 0.0000e+00 L2 loss: 1.25766 Learning rate: 0.02 Mask loss: 0.14366 RPN box loss: 0.01239 RPN score loss: 0.00681 RPN total loss: 0.0192 Total loss: 1.66505 timestamp: 1655020665.213931 iteration: 16115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.19766 L1 loss: 0.0000e+00 L2 loss: 1.2574 Learning rate: 0.02 Mask loss: 0.1644 RPN box loss: 0.03743 RPN score loss: 0.01331 RPN total loss: 0.05074 Total loss: 1.6702 timestamp: 1655020668.4794662 iteration: 16120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14788 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.24226 L1 loss: 0.0000e+00 L2 loss: 1.25716 Learning rate: 0.02 Mask loss: 0.14463 RPN box loss: 0.03182 RPN score loss: 0.00629 RPN total loss: 0.03811 Total loss: 1.68216 timestamp: 1655020671.8884995 iteration: 16125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16074 FastRCNN class loss: 0.10418 FastRCNN total loss: 0.26492 L1 loss: 0.0000e+00 L2 loss: 1.25692 Learning rate: 0.02 Mask loss: 0.16575 RPN box loss: 0.03118 RPN score loss: 0.00545 RPN total loss: 0.03663 Total loss: 1.72423 timestamp: 1655020675.2083879 iteration: 16130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26419 FastRCNN class loss: 0.09788 FastRCNN total loss: 0.36208 L1 loss: 0.0000e+00 L2 loss: 1.2567 Learning rate: 0.02 Mask loss: 0.24059 RPN box loss: 0.07294 RPN score loss: 0.0085 RPN total loss: 0.08144 Total loss: 1.9408 timestamp: 1655020678.6657786 iteration: 16135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13407 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.23443 L1 loss: 0.0000e+00 L2 loss: 1.2565 Learning rate: 0.02 Mask loss: 0.15169 RPN box loss: 0.0229 RPN score loss: 0.00426 RPN total loss: 0.02716 Total loss: 1.66977 timestamp: 1655020681.9836767 iteration: 16140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14925 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.22966 L1 loss: 0.0000e+00 L2 loss: 1.25626 Learning rate: 0.02 Mask loss: 0.11958 RPN box loss: 0.01362 RPN score loss: 0.00555 RPN total loss: 0.01917 Total loss: 1.62467 timestamp: 1655020685.4189346 iteration: 16145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.194 FastRCNN class loss: 0.11645 FastRCNN total loss: 0.31045 L1 loss: 0.0000e+00 L2 loss: 1.25604 Learning rate: 0.02 Mask loss: 0.16521 RPN box loss: 0.02571 RPN score loss: 0.00738 RPN total loss: 0.03308 Total loss: 1.76478 timestamp: 1655020688.9132955 iteration: 16150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15152 FastRCNN class loss: 0.08609 FastRCNN total loss: 0.23761 L1 loss: 0.0000e+00 L2 loss: 1.25581 Learning rate: 0.02 Mask loss: 0.18096 RPN box loss: 0.01664 RPN score loss: 0.00514 RPN total loss: 0.02178 Total loss: 1.69617 timestamp: 1655020692.2550576 iteration: 16155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14527 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.22953 L1 loss: 0.0000e+00 L2 loss: 1.25558 Learning rate: 0.02 Mask loss: 0.1678 RPN box loss: 0.0349 RPN score loss: 0.0061 RPN total loss: 0.041 Total loss: 1.6939 timestamp: 1655020695.5723133 iteration: 16160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17981 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.25993 L1 loss: 0.0000e+00 L2 loss: 1.25538 Learning rate: 0.02 Mask loss: 0.12357 RPN box loss: 0.00693 RPN score loss: 0.00513 RPN total loss: 0.01206 Total loss: 1.65093 timestamp: 1655020698.8785787 iteration: 16165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10028 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.17521 L1 loss: 0.0000e+00 L2 loss: 1.25517 Learning rate: 0.02 Mask loss: 0.22343 RPN box loss: 0.08037 RPN score loss: 0.01743 RPN total loss: 0.0978 Total loss: 1.75161 timestamp: 1655020702.2859569 iteration: 16170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20766 FastRCNN class loss: 0.18068 FastRCNN total loss: 0.38835 L1 loss: 0.0000e+00 L2 loss: 1.25495 Learning rate: 0.02 Mask loss: 0.17308 RPN box loss: 0.05999 RPN score loss: 0.01109 RPN total loss: 0.07108 Total loss: 1.88745 timestamp: 1655020705.588356 iteration: 16175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24021 FastRCNN class loss: 0.11643 FastRCNN total loss: 0.35664 L1 loss: 0.0000e+00 L2 loss: 1.25474 Learning rate: 0.02 Mask loss: 0.27499 RPN box loss: 0.05652 RPN score loss: 0.01031 RPN total loss: 0.06683 Total loss: 1.9532 timestamp: 1655020708.9413226 iteration: 16180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10944 FastRCNN class loss: 0.06801 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 1.2545 Learning rate: 0.02 Mask loss: 0.12575 RPN box loss: 0.01452 RPN score loss: 0.01547 RPN total loss: 0.02999 Total loss: 1.58769 timestamp: 1655020712.1887295 iteration: 16185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21537 FastRCNN class loss: 0.19145 FastRCNN total loss: 0.40682 L1 loss: 0.0000e+00 L2 loss: 1.25427 Learning rate: 0.02 Mask loss: 0.29464 RPN box loss: 0.05132 RPN score loss: 0.00877 RPN total loss: 0.06009 Total loss: 2.01582 timestamp: 1655020715.5213652 iteration: 16190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13567 FastRCNN class loss: 0.07724 FastRCNN total loss: 0.2129 L1 loss: 0.0000e+00 L2 loss: 1.25405 Learning rate: 0.02 Mask loss: 0.22955 RPN box loss: 0.03619 RPN score loss: 0.00942 RPN total loss: 0.04561 Total loss: 1.74212 timestamp: 1655020718.8421578 iteration: 16195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13311 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.19213 L1 loss: 0.0000e+00 L2 loss: 1.25384 Learning rate: 0.02 Mask loss: 0.15732 RPN box loss: 0.02001 RPN score loss: 0.00514 RPN total loss: 0.02515 Total loss: 1.62844 timestamp: 1655020722.1264784 iteration: 16200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10617 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.18064 L1 loss: 0.0000e+00 L2 loss: 1.25363 Learning rate: 0.02 Mask loss: 0.12235 RPN box loss: 0.01194 RPN score loss: 0.00478 RPN total loss: 0.01672 Total loss: 1.57335 timestamp: 1655020725.5167055 iteration: 16205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08538 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.15515 L1 loss: 0.0000e+00 L2 loss: 1.2534 Learning rate: 0.02 Mask loss: 0.13635 RPN box loss: 0.02559 RPN score loss: 0.00534 RPN total loss: 0.03092 Total loss: 1.57582 timestamp: 1655020728.8065062 iteration: 16210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13948 FastRCNN class loss: 0.08726 FastRCNN total loss: 0.22674 L1 loss: 0.0000e+00 L2 loss: 1.2532 Learning rate: 0.02 Mask loss: 0.18466 RPN box loss: 0.04447 RPN score loss: 0.00727 RPN total loss: 0.05174 Total loss: 1.71634 timestamp: 1655020732.2022228 iteration: 16215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10603 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.18043 L1 loss: 0.0000e+00 L2 loss: 1.25301 Learning rate: 0.02 Mask loss: 0.1526 RPN box loss: 0.0547 RPN score loss: 0.01152 RPN total loss: 0.06622 Total loss: 1.65226 timestamp: 1655020735.4241462 iteration: 16220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13755 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.22328 L1 loss: 0.0000e+00 L2 loss: 1.25277 Learning rate: 0.02 Mask loss: 0.20661 RPN box loss: 0.02425 RPN score loss: 0.00936 RPN total loss: 0.03361 Total loss: 1.71627 timestamp: 1655020738.7384408 iteration: 16225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13041 FastRCNN class loss: 0.06782 FastRCNN total loss: 0.19823 L1 loss: 0.0000e+00 L2 loss: 1.25254 Learning rate: 0.02 Mask loss: 0.16998 RPN box loss: 0.02628 RPN score loss: 0.01027 RPN total loss: 0.03655 Total loss: 1.65731 timestamp: 1655020741.9989648 iteration: 16230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20514 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.29747 L1 loss: 0.0000e+00 L2 loss: 1.25233 Learning rate: 0.02 Mask loss: 0.19279 RPN box loss: 0.06374 RPN score loss: 0.01238 RPN total loss: 0.07612 Total loss: 1.81872 timestamp: 1655020745.3822222 iteration: 16235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17702 FastRCNN class loss: 0.10289 FastRCNN total loss: 0.27991 L1 loss: 0.0000e+00 L2 loss: 1.25212 Learning rate: 0.02 Mask loss: 0.18627 RPN box loss: 0.03446 RPN score loss: 0.01005 RPN total loss: 0.04451 Total loss: 1.76281 timestamp: 1655020748.7255747 iteration: 16240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19348 FastRCNN class loss: 0.10854 FastRCNN total loss: 0.30202 L1 loss: 0.0000e+00 L2 loss: 1.25191 Learning rate: 0.02 Mask loss: 0.19603 RPN box loss: 0.02471 RPN score loss: 0.01845 RPN total loss: 0.04316 Total loss: 1.79312 timestamp: 1655020752.035243 iteration: 16245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19439 FastRCNN class loss: 0.0571 FastRCNN total loss: 0.25149 L1 loss: 0.0000e+00 L2 loss: 1.25167 Learning rate: 0.02 Mask loss: 0.13436 RPN box loss: 0.01321 RPN score loss: 0.00192 RPN total loss: 0.01513 Total loss: 1.65265 timestamp: 1655020755.3774028 iteration: 16250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1224 FastRCNN class loss: 0.05227 FastRCNN total loss: 0.17468 L1 loss: 0.0000e+00 L2 loss: 1.25149 Learning rate: 0.02 Mask loss: 0.17896 RPN box loss: 0.02526 RPN score loss: 0.00304 RPN total loss: 0.02831 Total loss: 1.63343 timestamp: 1655020758.6398284 iteration: 16255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16215 FastRCNN class loss: 0.05079 FastRCNN total loss: 0.21294 L1 loss: 0.0000e+00 L2 loss: 1.25128 Learning rate: 0.02 Mask loss: 0.12109 RPN box loss: 0.03137 RPN score loss: 0.00578 RPN total loss: 0.03716 Total loss: 1.62248 timestamp: 1655020761.995243 iteration: 16260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17928 FastRCNN class loss: 0.16699 FastRCNN total loss: 0.34627 L1 loss: 0.0000e+00 L2 loss: 1.25105 Learning rate: 0.02 Mask loss: 0.20224 RPN box loss: 0.02743 RPN score loss: 0.00668 RPN total loss: 0.03411 Total loss: 1.83367 timestamp: 1655020765.2602851 iteration: 16265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20652 FastRCNN class loss: 0.09249 FastRCNN total loss: 0.29901 L1 loss: 0.0000e+00 L2 loss: 1.25081 Learning rate: 0.02 Mask loss: 0.2051 RPN box loss: 0.02801 RPN score loss: 0.00825 RPN total loss: 0.03625 Total loss: 1.79117 timestamp: 1655020768.6843822 iteration: 16270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15959 FastRCNN class loss: 0.07607 FastRCNN total loss: 0.23566 L1 loss: 0.0000e+00 L2 loss: 1.25058 Learning rate: 0.02 Mask loss: 0.15193 RPN box loss: 0.04497 RPN score loss: 0.00567 RPN total loss: 0.05064 Total loss: 1.68882 timestamp: 1655020771.9281502 iteration: 16275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19927 FastRCNN class loss: 0.08701 FastRCNN total loss: 0.28628 L1 loss: 0.0000e+00 L2 loss: 1.25036 Learning rate: 0.02 Mask loss: 0.13957 RPN box loss: 0.03573 RPN score loss: 0.0042 RPN total loss: 0.03993 Total loss: 1.71614 timestamp: 1655020775.4083576 iteration: 16280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15311 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.2214 L1 loss: 0.0000e+00 L2 loss: 1.25012 Learning rate: 0.02 Mask loss: 0.15519 RPN box loss: 0.00497 RPN score loss: 0.00567 RPN total loss: 0.01064 Total loss: 1.63735 timestamp: 1655020778.8021057 iteration: 16285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1914 FastRCNN class loss: 0.09889 FastRCNN total loss: 0.29029 L1 loss: 0.0000e+00 L2 loss: 1.24992 Learning rate: 0.02 Mask loss: 0.16732 RPN box loss: 0.03033 RPN score loss: 0.01128 RPN total loss: 0.04161 Total loss: 1.74915 timestamp: 1655020782.0728858 iteration: 16290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10949 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 1.24972 Learning rate: 0.02 Mask loss: 0.25712 RPN box loss: 0.06201 RPN score loss: 0.0109 RPN total loss: 0.07291 Total loss: 1.75261 timestamp: 1655020785.4662693 iteration: 16295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19041 FastRCNN class loss: 0.09883 FastRCNN total loss: 0.28923 L1 loss: 0.0000e+00 L2 loss: 1.2495 Learning rate: 0.02 Mask loss: 0.16975 RPN box loss: 0.07907 RPN score loss: 0.00681 RPN total loss: 0.08588 Total loss: 1.79436 timestamp: 1655020788.8004556 iteration: 16300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18993 FastRCNN class loss: 0.11929 FastRCNN total loss: 0.30922 L1 loss: 0.0000e+00 L2 loss: 1.24928 Learning rate: 0.02 Mask loss: 0.2191 RPN box loss: 0.0352 RPN score loss: 0.00573 RPN total loss: 0.04092 Total loss: 1.81853 timestamp: 1655020792.1299365 iteration: 16305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15298 FastRCNN class loss: 0.15107 FastRCNN total loss: 0.30405 L1 loss: 0.0000e+00 L2 loss: 1.24906 Learning rate: 0.02 Mask loss: 0.21839 RPN box loss: 0.06501 RPN score loss: 0.0116 RPN total loss: 0.07661 Total loss: 1.84811 timestamp: 1655020795.4827657 iteration: 16310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19314 FastRCNN class loss: 0.12218 FastRCNN total loss: 0.31532 L1 loss: 0.0000e+00 L2 loss: 1.24884 Learning rate: 0.02 Mask loss: 0.27084 RPN box loss: 0.04657 RPN score loss: 0.00831 RPN total loss: 0.05488 Total loss: 1.88987 timestamp: 1655020798.825224 iteration: 16315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16938 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.25053 L1 loss: 0.0000e+00 L2 loss: 1.24863 Learning rate: 0.02 Mask loss: 0.22857 RPN box loss: 0.02935 RPN score loss: 0.00919 RPN total loss: 0.03853 Total loss: 1.76626 timestamp: 1655020802.1355855 iteration: 16320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17112 FastRCNN class loss: 0.133 FastRCNN total loss: 0.30412 L1 loss: 0.0000e+00 L2 loss: 1.2484 Learning rate: 0.02 Mask loss: 0.18006 RPN box loss: 0.05437 RPN score loss: 0.01009 RPN total loss: 0.06446 Total loss: 1.79705 timestamp: 1655020805.4885361 iteration: 16325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18996 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.25942 L1 loss: 0.0000e+00 L2 loss: 1.24817 Learning rate: 0.02 Mask loss: 0.3769 RPN box loss: 0.03491 RPN score loss: 0.00919 RPN total loss: 0.04409 Total loss: 1.92859 timestamp: 1655020808.8390427 iteration: 16330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18375 FastRCNN class loss: 0.10344 FastRCNN total loss: 0.28719 L1 loss: 0.0000e+00 L2 loss: 1.24797 Learning rate: 0.02 Mask loss: 0.22662 RPN box loss: 0.04294 RPN score loss: 0.01066 RPN total loss: 0.0536 Total loss: 1.81537 timestamp: 1655020812.1391106 iteration: 16335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12949 FastRCNN class loss: 0.08795 FastRCNN total loss: 0.21743 L1 loss: 0.0000e+00 L2 loss: 1.24776 Learning rate: 0.02 Mask loss: 0.16055 RPN box loss: 0.04742 RPN score loss: 0.00878 RPN total loss: 0.0562 Total loss: 1.68195 timestamp: 1655020815.5375972 iteration: 16340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08921 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 1.24754 Learning rate: 0.02 Mask loss: 0.16853 RPN box loss: 0.01167 RPN score loss: 0.00426 RPN total loss: 0.01594 Total loss: 1.59439 timestamp: 1655020818.798097 iteration: 16345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17863 FastRCNN class loss: 0.11312 FastRCNN total loss: 0.29174 L1 loss: 0.0000e+00 L2 loss: 1.24733 Learning rate: 0.02 Mask loss: 0.1951 RPN box loss: 0.04306 RPN score loss: 0.00496 RPN total loss: 0.04802 Total loss: 1.78219 timestamp: 1655020822.1523561 iteration: 16350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16257 FastRCNN class loss: 0.10662 FastRCNN total loss: 0.26919 L1 loss: 0.0000e+00 L2 loss: 1.2471 Learning rate: 0.02 Mask loss: 0.18914 RPN box loss: 0.0772 RPN score loss: 0.01072 RPN total loss: 0.08791 Total loss: 1.79334 timestamp: 1655020825.4563425 iteration: 16355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20296 FastRCNN class loss: 0.17791 FastRCNN total loss: 0.38087 L1 loss: 0.0000e+00 L2 loss: 1.24685 Learning rate: 0.02 Mask loss: 0.17492 RPN box loss: 0.06334 RPN score loss: 0.0201 RPN total loss: 0.08344 Total loss: 1.88608 timestamp: 1655020828.9161167 iteration: 16360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19873 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.26012 L1 loss: 0.0000e+00 L2 loss: 1.24664 Learning rate: 0.02 Mask loss: 0.15832 RPN box loss: 0.0329 RPN score loss: 0.00994 RPN total loss: 0.04284 Total loss: 1.70792 timestamp: 1655020832.2292721 iteration: 16365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16709 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.2202 L1 loss: 0.0000e+00 L2 loss: 1.24644 Learning rate: 0.02 Mask loss: 0.17071 RPN box loss: 0.10173 RPN score loss: 0.00836 RPN total loss: 0.11008 Total loss: 1.74743 timestamp: 1655020835.6424718 iteration: 16370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1719 FastRCNN class loss: 0.11077 FastRCNN total loss: 0.28267 L1 loss: 0.0000e+00 L2 loss: 1.24621 Learning rate: 0.02 Mask loss: 0.20808 RPN box loss: 0.00879 RPN score loss: 0.00561 RPN total loss: 0.0144 Total loss: 1.75136 timestamp: 1655020838.956595 iteration: 16375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18942 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.25832 L1 loss: 0.0000e+00 L2 loss: 1.246 Learning rate: 0.02 Mask loss: 0.12646 RPN box loss: 0.02831 RPN score loss: 0.00363 RPN total loss: 0.03194 Total loss: 1.66273 timestamp: 1655020842.250446 iteration: 16380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1342 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.21197 L1 loss: 0.0000e+00 L2 loss: 1.24578 Learning rate: 0.02 Mask loss: 0.15517 RPN box loss: 0.04092 RPN score loss: 0.00674 RPN total loss: 0.04766 Total loss: 1.66058 timestamp: 1655020845.6504083 iteration: 16385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12303 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.18932 L1 loss: 0.0000e+00 L2 loss: 1.24558 Learning rate: 0.02 Mask loss: 0.20576 RPN box loss: 0.0121 RPN score loss: 0.00791 RPN total loss: 0.02001 Total loss: 1.66066 timestamp: 1655020848.9038105 iteration: 16390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06532 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.11741 L1 loss: 0.0000e+00 L2 loss: 1.24535 Learning rate: 0.02 Mask loss: 0.20564 RPN box loss: 0.02942 RPN score loss: 0.01062 RPN total loss: 0.04004 Total loss: 1.60844 timestamp: 1655020852.3093424 iteration: 16395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07167 FastRCNN class loss: 0.0843 FastRCNN total loss: 0.15597 L1 loss: 0.0000e+00 L2 loss: 1.24515 Learning rate: 0.02 Mask loss: 0.18578 RPN box loss: 0.02399 RPN score loss: 0.01893 RPN total loss: 0.04292 Total loss: 1.62981 timestamp: 1655020855.6424232 iteration: 16400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1638 FastRCNN class loss: 0.08276 FastRCNN total loss: 0.24656 L1 loss: 0.0000e+00 L2 loss: 1.24492 Learning rate: 0.02 Mask loss: 0.188 RPN box loss: 0.04043 RPN score loss: 0.01485 RPN total loss: 0.05528 Total loss: 1.73477 timestamp: 1655020859.0493543 iteration: 16405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1315 FastRCNN class loss: 0.11364 FastRCNN total loss: 0.24514 L1 loss: 0.0000e+00 L2 loss: 1.24468 Learning rate: 0.02 Mask loss: 0.18208 RPN box loss: 0.06466 RPN score loss: 0.01736 RPN total loss: 0.08203 Total loss: 1.75393 timestamp: 1655020862.2865648 iteration: 16410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14315 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.21423 L1 loss: 0.0000e+00 L2 loss: 1.24448 Learning rate: 0.02 Mask loss: 0.17657 RPN box loss: 0.08583 RPN score loss: 0.0042 RPN total loss: 0.09003 Total loss: 1.72531 timestamp: 1655020865.6063716 iteration: 16415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13015 FastRCNN class loss: 0.10155 FastRCNN total loss: 0.23171 L1 loss: 0.0000e+00 L2 loss: 1.24427 Learning rate: 0.02 Mask loss: 0.20555 RPN box loss: 0.04202 RPN score loss: 0.01233 RPN total loss: 0.05435 Total loss: 1.73588 timestamp: 1655020868.9937682 iteration: 16420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.121 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 1.24404 Learning rate: 0.02 Mask loss: 0.12337 RPN box loss: 0.05738 RPN score loss: 0.00885 RPN total loss: 0.06623 Total loss: 1.63269 timestamp: 1655020872.3016474 iteration: 16425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22003 FastRCNN class loss: 0.12913 FastRCNN total loss: 0.34916 L1 loss: 0.0000e+00 L2 loss: 1.24382 Learning rate: 0.02 Mask loss: 0.30565 RPN box loss: 0.01899 RPN score loss: 0.00252 RPN total loss: 0.02152 Total loss: 1.92015 timestamp: 1655020875.7014234 iteration: 16430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1648 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.23487 L1 loss: 0.0000e+00 L2 loss: 1.24362 Learning rate: 0.02 Mask loss: 0.13258 RPN box loss: 0.02019 RPN score loss: 0.01246 RPN total loss: 0.03265 Total loss: 1.64372 timestamp: 1655020878.9193394 iteration: 16435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16546 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.27079 L1 loss: 0.0000e+00 L2 loss: 1.24339 Learning rate: 0.02 Mask loss: 0.219 RPN box loss: 0.01857 RPN score loss: 0.00685 RPN total loss: 0.02541 Total loss: 1.7586 timestamp: 1655020882.268489 iteration: 16440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15631 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.23312 L1 loss: 0.0000e+00 L2 loss: 1.24321 Learning rate: 0.02 Mask loss: 0.19112 RPN box loss: 0.06477 RPN score loss: 0.00959 RPN total loss: 0.07436 Total loss: 1.74181 timestamp: 1655020885.5238304 iteration: 16445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23385 FastRCNN class loss: 0.09948 FastRCNN total loss: 0.33333 L1 loss: 0.0000e+00 L2 loss: 1.24298 Learning rate: 0.02 Mask loss: 0.19409 RPN box loss: 0.0292 RPN score loss: 0.00601 RPN total loss: 0.03521 Total loss: 1.80562 timestamp: 1655020888.963836 iteration: 16450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23128 FastRCNN class loss: 0.12129 FastRCNN total loss: 0.35257 L1 loss: 0.0000e+00 L2 loss: 1.24278 Learning rate: 0.02 Mask loss: 0.26104 RPN box loss: 0.02527 RPN score loss: 0.01411 RPN total loss: 0.03937 Total loss: 1.89576 timestamp: 1655020892.2176955 iteration: 16455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14105 FastRCNN class loss: 0.09772 FastRCNN total loss: 0.23877 L1 loss: 0.0000e+00 L2 loss: 1.24256 Learning rate: 0.02 Mask loss: 0.18743 RPN box loss: 0.02747 RPN score loss: 0.00654 RPN total loss: 0.03401 Total loss: 1.70277 timestamp: 1655020895.5856814 iteration: 16460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21061 FastRCNN class loss: 0.10727 FastRCNN total loss: 0.31788 L1 loss: 0.0000e+00 L2 loss: 1.2423 Learning rate: 0.02 Mask loss: 0.16314 RPN box loss: 0.04008 RPN score loss: 0.01375 RPN total loss: 0.05383 Total loss: 1.77716 timestamp: 1655020898.9450915 iteration: 16465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22554 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.32029 L1 loss: 0.0000e+00 L2 loss: 1.24208 Learning rate: 0.02 Mask loss: 0.20524 RPN box loss: 0.01527 RPN score loss: 0.0035 RPN total loss: 0.01877 Total loss: 1.78638 timestamp: 1655020902.2151418 iteration: 16470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15359 FastRCNN class loss: 0.08963 FastRCNN total loss: 0.24323 L1 loss: 0.0000e+00 L2 loss: 1.24187 Learning rate: 0.02 Mask loss: 0.23926 RPN box loss: 0.013 RPN score loss: 0.00681 RPN total loss: 0.01981 Total loss: 1.74416 timestamp: 1655020905.6028085 iteration: 16475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.093 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 1.24164 Learning rate: 0.02 Mask loss: 0.11804 RPN box loss: 0.0781 RPN score loss: 0.00735 RPN total loss: 0.08545 Total loss: 1.60582 timestamp: 1655020908.9359362 iteration: 16480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16484 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.24258 L1 loss: 0.0000e+00 L2 loss: 1.24143 Learning rate: 0.02 Mask loss: 0.15537 RPN box loss: 0.02225 RPN score loss: 0.00284 RPN total loss: 0.02509 Total loss: 1.66447 timestamp: 1655020912.2585716 iteration: 16485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13346 FastRCNN class loss: 0.08218 FastRCNN total loss: 0.21564 L1 loss: 0.0000e+00 L2 loss: 1.2412 Learning rate: 0.02 Mask loss: 0.14418 RPN box loss: 0.04424 RPN score loss: 0.00824 RPN total loss: 0.05248 Total loss: 1.6535 timestamp: 1655020915.5503044 iteration: 16490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22077 FastRCNN class loss: 0.10979 FastRCNN total loss: 0.33056 L1 loss: 0.0000e+00 L2 loss: 1.24099 Learning rate: 0.02 Mask loss: 0.18512 RPN box loss: 0.03865 RPN score loss: 0.02136 RPN total loss: 0.06001 Total loss: 1.81668 timestamp: 1655020918.872032 iteration: 16495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21549 FastRCNN class loss: 0.09364 FastRCNN total loss: 0.30913 L1 loss: 0.0000e+00 L2 loss: 1.24079 Learning rate: 0.02 Mask loss: 0.16844 RPN box loss: 0.02902 RPN score loss: 0.00709 RPN total loss: 0.0361 Total loss: 1.75447 timestamp: 1655020922.1933908 iteration: 16500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13193 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.18783 L1 loss: 0.0000e+00 L2 loss: 1.24059 Learning rate: 0.02 Mask loss: 0.15233 RPN box loss: 0.02903 RPN score loss: 0.00839 RPN total loss: 0.03743 Total loss: 1.61817 timestamp: 1655020925.6240654 iteration: 16505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1246 FastRCNN class loss: 0.0801 FastRCNN total loss: 0.2047 L1 loss: 0.0000e+00 L2 loss: 1.24036 Learning rate: 0.02 Mask loss: 0.21418 RPN box loss: 0.04476 RPN score loss: 0.00751 RPN total loss: 0.05227 Total loss: 1.7115 timestamp: 1655020929.126042 iteration: 16510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22776 FastRCNN class loss: 0.08605 FastRCNN total loss: 0.31382 L1 loss: 0.0000e+00 L2 loss: 1.24013 Learning rate: 0.02 Mask loss: 0.16315 RPN box loss: 0.04617 RPN score loss: 0.00815 RPN total loss: 0.05433 Total loss: 1.77143 timestamp: 1655020932.4562664 iteration: 16515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20647 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.28882 L1 loss: 0.0000e+00 L2 loss: 1.23991 Learning rate: 0.02 Mask loss: 0.17569 RPN box loss: 0.0183 RPN score loss: 0.0045 RPN total loss: 0.0228 Total loss: 1.72722 timestamp: 1655020935.8808334 iteration: 16520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18863 FastRCNN class loss: 0.1138 FastRCNN total loss: 0.30243 L1 loss: 0.0000e+00 L2 loss: 1.2397 Learning rate: 0.02 Mask loss: 0.15213 RPN box loss: 0.01309 RPN score loss: 0.00188 RPN total loss: 0.01498 Total loss: 1.70924 timestamp: 1655020939.1427252 iteration: 16525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17645 FastRCNN class loss: 0.10087 FastRCNN total loss: 0.27732 L1 loss: 0.0000e+00 L2 loss: 1.23946 Learning rate: 0.02 Mask loss: 0.20516 RPN box loss: 0.01883 RPN score loss: 0.00354 RPN total loss: 0.02238 Total loss: 1.74431 timestamp: 1655020942.442071 iteration: 16530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18572 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.27392 L1 loss: 0.0000e+00 L2 loss: 1.23923 Learning rate: 0.02 Mask loss: 0.22259 RPN box loss: 0.01721 RPN score loss: 0.01227 RPN total loss: 0.02948 Total loss: 1.76523 timestamp: 1655020945.6958613 iteration: 16535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19964 FastRCNN class loss: 0.0941 FastRCNN total loss: 0.29375 L1 loss: 0.0000e+00 L2 loss: 1.23903 Learning rate: 0.02 Mask loss: 0.20503 RPN box loss: 0.04667 RPN score loss: 0.01006 RPN total loss: 0.05673 Total loss: 1.79454 timestamp: 1655020949.1650836 iteration: 16540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18141 FastRCNN class loss: 0.09786 FastRCNN total loss: 0.27926 L1 loss: 0.0000e+00 L2 loss: 1.23882 Learning rate: 0.02 Mask loss: 0.21371 RPN box loss: 0.04139 RPN score loss: 0.02115 RPN total loss: 0.06254 Total loss: 1.79433 timestamp: 1655020952.6377158 iteration: 16545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20571 FastRCNN class loss: 0.16459 FastRCNN total loss: 0.3703 L1 loss: 0.0000e+00 L2 loss: 1.2386 Learning rate: 0.02 Mask loss: 0.23265 RPN box loss: 0.08526 RPN score loss: 0.04191 RPN total loss: 0.12717 Total loss: 1.96871 timestamp: 1655020955.95052 iteration: 16550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08331 FastRCNN class loss: 0.04412 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 1.23838 Learning rate: 0.02 Mask loss: 0.13626 RPN box loss: 0.08175 RPN score loss: 0.00745 RPN total loss: 0.08919 Total loss: 1.59127 timestamp: 1655020959.366773 iteration: 16555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.14233 L1 loss: 0.0000e+00 L2 loss: 1.23816 Learning rate: 0.02 Mask loss: 0.13079 RPN box loss: 0.01948 RPN score loss: 0.00227 RPN total loss: 0.02175 Total loss: 1.53303 timestamp: 1655020962.5971205 iteration: 16560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09476 FastRCNN class loss: 0.05967 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 1.23796 Learning rate: 0.02 Mask loss: 0.16524 RPN box loss: 0.0529 RPN score loss: 0.00981 RPN total loss: 0.06271 Total loss: 1.62033 timestamp: 1655020966.007506 iteration: 16565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12529 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.20102 L1 loss: 0.0000e+00 L2 loss: 1.23776 Learning rate: 0.02 Mask loss: 0.16699 RPN box loss: 0.05557 RPN score loss: 0.00569 RPN total loss: 0.06125 Total loss: 1.66702 timestamp: 1655020969.3161514 iteration: 16570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07202 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.1259 L1 loss: 0.0000e+00 L2 loss: 1.23753 Learning rate: 0.02 Mask loss: 0.14996 RPN box loss: 0.01521 RPN score loss: 0.00346 RPN total loss: 0.01866 Total loss: 1.53206 timestamp: 1655020972.6854143 iteration: 16575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.14744 L1 loss: 0.0000e+00 L2 loss: 1.2373 Learning rate: 0.02 Mask loss: 0.13473 RPN box loss: 0.02399 RPN score loss: 0.00197 RPN total loss: 0.02596 Total loss: 1.54542 timestamp: 1655020975.9739978 iteration: 16580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07491 FastRCNN class loss: 0.04189 FastRCNN total loss: 0.1168 L1 loss: 0.0000e+00 L2 loss: 1.23708 Learning rate: 0.02 Mask loss: 0.13308 RPN box loss: 0.00614 RPN score loss: 0.00131 RPN total loss: 0.00745 Total loss: 1.49441 timestamp: 1655020979.3617914 iteration: 16585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15772 FastRCNN class loss: 0.12063 FastRCNN total loss: 0.27835 L1 loss: 0.0000e+00 L2 loss: 1.23686 Learning rate: 0.02 Mask loss: 0.16987 RPN box loss: 0.03977 RPN score loss: 0.0068 RPN total loss: 0.04657 Total loss: 1.73165 timestamp: 1655020982.7141087 iteration: 16590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17006 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.23867 L1 loss: 0.0000e+00 L2 loss: 1.23664 Learning rate: 0.02 Mask loss: 0.20078 RPN box loss: 0.03808 RPN score loss: 0.00512 RPN total loss: 0.0432 Total loss: 1.71928 timestamp: 1655020986.0216446 iteration: 16595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15427 FastRCNN class loss: 0.09398 FastRCNN total loss: 0.24824 L1 loss: 0.0000e+00 L2 loss: 1.23644 Learning rate: 0.02 Mask loss: 0.15155 RPN box loss: 0.04616 RPN score loss: 0.00594 RPN total loss: 0.05209 Total loss: 1.68833 timestamp: 1655020989.3868933 iteration: 16600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18389 FastRCNN class loss: 0.114 FastRCNN total loss: 0.29789 L1 loss: 0.0000e+00 L2 loss: 1.23622 Learning rate: 0.02 Mask loss: 0.17695 RPN box loss: 0.06747 RPN score loss: 0.02388 RPN total loss: 0.09135 Total loss: 1.80241 timestamp: 1655020992.6345568 iteration: 16605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13183 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.19811 L1 loss: 0.0000e+00 L2 loss: 1.236 Learning rate: 0.02 Mask loss: 0.12797 RPN box loss: 0.02302 RPN score loss: 0.00452 RPN total loss: 0.02755 Total loss: 1.58963 timestamp: 1655020995.9579918 iteration: 16610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2395 FastRCNN class loss: 0.11221 FastRCNN total loss: 0.35171 L1 loss: 0.0000e+00 L2 loss: 1.23578 Learning rate: 0.02 Mask loss: 0.17048 RPN box loss: 0.0489 RPN score loss: 0.00557 RPN total loss: 0.05447 Total loss: 1.81244 timestamp: 1655020999.297738 iteration: 16615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15374 FastRCNN class loss: 0.14404 FastRCNN total loss: 0.29778 L1 loss: 0.0000e+00 L2 loss: 1.23554 Learning rate: 0.02 Mask loss: 0.17665 RPN box loss: 0.03589 RPN score loss: 0.02154 RPN total loss: 0.05743 Total loss: 1.76741 timestamp: 1655021002.6208882 iteration: 16620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1605 FastRCNN class loss: 0.07859 FastRCNN total loss: 0.23909 L1 loss: 0.0000e+00 L2 loss: 1.23534 Learning rate: 0.02 Mask loss: 0.14148 RPN box loss: 0.05883 RPN score loss: 0.00739 RPN total loss: 0.06621 Total loss: 1.68212 timestamp: 1655021005.9362836 iteration: 16625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13726 FastRCNN class loss: 0.08752 FastRCNN total loss: 0.22479 L1 loss: 0.0000e+00 L2 loss: 1.23512 Learning rate: 0.02 Mask loss: 0.2146 RPN box loss: 0.13521 RPN score loss: 0.01407 RPN total loss: 0.14928 Total loss: 1.82378 timestamp: 1655021009.2621603 iteration: 16630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15511 FastRCNN class loss: 0.07677 FastRCNN total loss: 0.23188 L1 loss: 0.0000e+00 L2 loss: 1.23491 Learning rate: 0.02 Mask loss: 0.27148 RPN box loss: 0.03058 RPN score loss: 0.00737 RPN total loss: 0.03795 Total loss: 1.77621 timestamp: 1655021012.6528254 iteration: 16635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06421 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.10824 L1 loss: 0.0000e+00 L2 loss: 1.23471 Learning rate: 0.02 Mask loss: 0.09317 RPN box loss: 0.06551 RPN score loss: 0.00941 RPN total loss: 0.07492 Total loss: 1.51104 timestamp: 1655021015.889352 iteration: 16640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17951 FastRCNN class loss: 0.11829 FastRCNN total loss: 0.2978 L1 loss: 0.0000e+00 L2 loss: 1.2345 Learning rate: 0.02 Mask loss: 0.22948 RPN box loss: 0.07575 RPN score loss: 0.02168 RPN total loss: 0.09743 Total loss: 1.85921 timestamp: 1655021019.287035 iteration: 16645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22233 FastRCNN class loss: 0.13783 FastRCNN total loss: 0.36016 L1 loss: 0.0000e+00 L2 loss: 1.23428 Learning rate: 0.02 Mask loss: 0.17713 RPN box loss: 0.08422 RPN score loss: 0.01217 RPN total loss: 0.09639 Total loss: 1.86796 timestamp: 1655021022.5437202 iteration: 16650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27526 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.34069 L1 loss: 0.0000e+00 L2 loss: 1.23405 Learning rate: 0.02 Mask loss: 0.14097 RPN box loss: 0.06859 RPN score loss: 0.01751 RPN total loss: 0.0861 Total loss: 1.80181 timestamp: 1655021025.9258726 iteration: 16655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14984 FastRCNN class loss: 0.11057 FastRCNN total loss: 0.2604 L1 loss: 0.0000e+00 L2 loss: 1.23382 Learning rate: 0.02 Mask loss: 0.18773 RPN box loss: 0.05204 RPN score loss: 0.00977 RPN total loss: 0.06181 Total loss: 1.74376 timestamp: 1655021029.1942303 iteration: 16660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12407 FastRCNN class loss: 0.05737 FastRCNN total loss: 0.18144 L1 loss: 0.0000e+00 L2 loss: 1.23362 Learning rate: 0.02 Mask loss: 0.16554 RPN box loss: 0.04649 RPN score loss: 0.00298 RPN total loss: 0.04947 Total loss: 1.63006 timestamp: 1655021032.5663242 iteration: 16665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10673 FastRCNN class loss: 0.09727 FastRCNN total loss: 0.204 L1 loss: 0.0000e+00 L2 loss: 1.2334 Learning rate: 0.02 Mask loss: 0.20955 RPN box loss: 0.00888 RPN score loss: 0.00314 RPN total loss: 0.01202 Total loss: 1.65897 timestamp: 1655021035.7858095 iteration: 16670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2413 FastRCNN class loss: 0.13849 FastRCNN total loss: 0.37979 L1 loss: 0.0000e+00 L2 loss: 1.23318 Learning rate: 0.02 Mask loss: 0.36978 RPN box loss: 0.02064 RPN score loss: 0.00475 RPN total loss: 0.0254 Total loss: 2.00815 timestamp: 1655021039.1302133 iteration: 16675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27372 FastRCNN class loss: 0.13279 FastRCNN total loss: 0.4065 L1 loss: 0.0000e+00 L2 loss: 1.23298 Learning rate: 0.02 Mask loss: 0.1954 RPN box loss: 0.02607 RPN score loss: 0.0054 RPN total loss: 0.03147 Total loss: 1.86634 timestamp: 1655021042.5736775 iteration: 16680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13365 FastRCNN class loss: 0.0508 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 1.23277 Learning rate: 0.02 Mask loss: 0.14835 RPN box loss: 0.03657 RPN score loss: 0.01183 RPN total loss: 0.0484 Total loss: 1.61396 timestamp: 1655021045.8948026 iteration: 16685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15746 FastRCNN class loss: 0.10253 FastRCNN total loss: 0.25999 L1 loss: 0.0000e+00 L2 loss: 1.23257 Learning rate: 0.02 Mask loss: 0.22405 RPN box loss: 0.03184 RPN score loss: 0.0148 RPN total loss: 0.04664 Total loss: 1.76324 timestamp: 1655021049.2397296 iteration: 16690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21264 FastRCNN class loss: 0.07949 FastRCNN total loss: 0.29213 L1 loss: 0.0000e+00 L2 loss: 1.23236 Learning rate: 0.02 Mask loss: 0.12547 RPN box loss: 0.03125 RPN score loss: 0.00949 RPN total loss: 0.04074 Total loss: 1.69069 timestamp: 1655021052.488147 iteration: 16695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18539 FastRCNN class loss: 0.10349 FastRCNN total loss: 0.28888 L1 loss: 0.0000e+00 L2 loss: 1.23214 Learning rate: 0.02 Mask loss: 0.31061 RPN box loss: 0.03176 RPN score loss: 0.00732 RPN total loss: 0.03908 Total loss: 1.87071 timestamp: 1655021055.9209826 iteration: 16700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08867 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.1649 L1 loss: 0.0000e+00 L2 loss: 1.2319 Learning rate: 0.02 Mask loss: 0.18784 RPN box loss: 0.02928 RPN score loss: 0.00339 RPN total loss: 0.03267 Total loss: 1.61731 timestamp: 1655021059.1688907 iteration: 16705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1394 FastRCNN class loss: 0.08865 FastRCNN total loss: 0.22804 L1 loss: 0.0000e+00 L2 loss: 1.23164 Learning rate: 0.02 Mask loss: 0.12442 RPN box loss: 0.024 RPN score loss: 0.00902 RPN total loss: 0.03301 Total loss: 1.61712 timestamp: 1655021062.4280832 iteration: 16710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08761 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.1538 L1 loss: 0.0000e+00 L2 loss: 1.23143 Learning rate: 0.02 Mask loss: 0.18473 RPN box loss: 0.23372 RPN score loss: 0.00905 RPN total loss: 0.24278 Total loss: 1.81273 timestamp: 1655021065.705604 iteration: 16715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.08181 FastRCNN total loss: 0.19627 L1 loss: 0.0000e+00 L2 loss: 1.23123 Learning rate: 0.02 Mask loss: 0.16626 RPN box loss: 0.05422 RPN score loss: 0.00792 RPN total loss: 0.06214 Total loss: 1.65591 timestamp: 1655021069.1061358 iteration: 16720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10841 FastRCNN class loss: 0.1017 FastRCNN total loss: 0.21011 L1 loss: 0.0000e+00 L2 loss: 1.23101 Learning rate: 0.02 Mask loss: 0.15316 RPN box loss: 0.06204 RPN score loss: 0.00492 RPN total loss: 0.06696 Total loss: 1.66125 timestamp: 1655021072.5352259 iteration: 16725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18506 FastRCNN class loss: 0.12703 FastRCNN total loss: 0.31209 L1 loss: 0.0000e+00 L2 loss: 1.23079 Learning rate: 0.02 Mask loss: 0.20185 RPN box loss: 0.03571 RPN score loss: 0.00785 RPN total loss: 0.04356 Total loss: 1.78829 timestamp: 1655021075.8139627 iteration: 16730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2545 FastRCNN class loss: 0.1604 FastRCNN total loss: 0.41489 L1 loss: 0.0000e+00 L2 loss: 1.23059 Learning rate: 0.02 Mask loss: 0.30492 RPN box loss: 0.06581 RPN score loss: 0.02988 RPN total loss: 0.09568 Total loss: 2.04608 timestamp: 1655021079.111108 iteration: 16735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14786 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.22165 L1 loss: 0.0000e+00 L2 loss: 1.23038 Learning rate: 0.02 Mask loss: 0.1021 RPN box loss: 0.04135 RPN score loss: 0.00669 RPN total loss: 0.04804 Total loss: 1.60217 timestamp: 1655021082.4264362 iteration: 16740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12823 FastRCNN class loss: 0.09488 FastRCNN total loss: 0.2231 L1 loss: 0.0000e+00 L2 loss: 1.23017 Learning rate: 0.02 Mask loss: 0.25522 RPN box loss: 0.04093 RPN score loss: 0.00879 RPN total loss: 0.04972 Total loss: 1.75821 timestamp: 1655021085.8985715 iteration: 16745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14994 FastRCNN class loss: 0.063 FastRCNN total loss: 0.21294 L1 loss: 0.0000e+00 L2 loss: 1.22997 Learning rate: 0.02 Mask loss: 0.11859 RPN box loss: 0.03908 RPN score loss: 0.00269 RPN total loss: 0.04177 Total loss: 1.60327 timestamp: 1655021089.2621439 iteration: 16750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20037 FastRCNN class loss: 0.14919 FastRCNN total loss: 0.34957 L1 loss: 0.0000e+00 L2 loss: 1.22974 Learning rate: 0.02 Mask loss: 0.16725 RPN box loss: 0.01969 RPN score loss: 0.00455 RPN total loss: 0.02423 Total loss: 1.77079 timestamp: 1655021092.688268 iteration: 16755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13126 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.22559 L1 loss: 0.0000e+00 L2 loss: 1.22953 Learning rate: 0.02 Mask loss: 0.16856 RPN box loss: 0.02245 RPN score loss: 0.02452 RPN total loss: 0.04697 Total loss: 1.67066 timestamp: 1655021096.2045841 iteration: 16760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12075 FastRCNN class loss: 0.05375 FastRCNN total loss: 0.1745 L1 loss: 0.0000e+00 L2 loss: 1.22932 Learning rate: 0.02 Mask loss: 0.13735 RPN box loss: 0.04007 RPN score loss: 0.00229 RPN total loss: 0.04236 Total loss: 1.58353 timestamp: 1655021099.510867 iteration: 16765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10913 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.17081 L1 loss: 0.0000e+00 L2 loss: 1.2291 Learning rate: 0.02 Mask loss: 0.13786 RPN box loss: 0.02421 RPN score loss: 0.01402 RPN total loss: 0.03824 Total loss: 1.57601 timestamp: 1655021102.8833628 iteration: 16770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15448 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.22196 L1 loss: 0.0000e+00 L2 loss: 1.22888 Learning rate: 0.02 Mask loss: 0.16208 RPN box loss: 0.05009 RPN score loss: 0.00685 RPN total loss: 0.05694 Total loss: 1.66985 timestamp: 1655021106.234233 iteration: 16775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11393 FastRCNN class loss: 0.08902 FastRCNN total loss: 0.20295 L1 loss: 0.0000e+00 L2 loss: 1.22866 Learning rate: 0.02 Mask loss: 0.21129 RPN box loss: 0.0228 RPN score loss: 0.00691 RPN total loss: 0.02971 Total loss: 1.67261 timestamp: 1655021109.746142 iteration: 16780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05274 FastRCNN class loss: 0.04085 FastRCNN total loss: 0.09359 L1 loss: 0.0000e+00 L2 loss: 1.22846 Learning rate: 0.02 Mask loss: 0.26918 RPN box loss: 0.02017 RPN score loss: 0.00793 RPN total loss: 0.0281 Total loss: 1.61932 timestamp: 1655021113.005811 iteration: 16785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08053 FastRCNN class loss: 0.10375 FastRCNN total loss: 0.18428 L1 loss: 0.0000e+00 L2 loss: 1.22826 Learning rate: 0.02 Mask loss: 0.10887 RPN box loss: 0.01 RPN score loss: 0.00378 RPN total loss: 0.01378 Total loss: 1.5352 timestamp: 1655021116.3927195 iteration: 16790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13138 FastRCNN class loss: 0.06856 FastRCNN total loss: 0.19994 L1 loss: 0.0000e+00 L2 loss: 1.22808 Learning rate: 0.02 Mask loss: 0.12933 RPN box loss: 0.01598 RPN score loss: 0.00594 RPN total loss: 0.02191 Total loss: 1.57926 timestamp: 1655021119.712359 iteration: 16795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21721 FastRCNN class loss: 0.12 FastRCNN total loss: 0.33721 L1 loss: 0.0000e+00 L2 loss: 1.22786 Learning rate: 0.02 Mask loss: 0.13996 RPN box loss: 0.05208 RPN score loss: 0.01331 RPN total loss: 0.06539 Total loss: 1.77041 timestamp: 1655021123.1257558 iteration: 16800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13592 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.19661 L1 loss: 0.0000e+00 L2 loss: 1.22764 Learning rate: 0.02 Mask loss: 0.19179 RPN box loss: 0.03373 RPN score loss: 0.00318 RPN total loss: 0.03691 Total loss: 1.65294 timestamp: 1655021126.5512707 iteration: 16805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1193 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.19164 L1 loss: 0.0000e+00 L2 loss: 1.2274 Learning rate: 0.02 Mask loss: 0.17054 RPN box loss: 0.01681 RPN score loss: 0.00601 RPN total loss: 0.02282 Total loss: 1.61241 timestamp: 1655021129.7996614 iteration: 16810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.04501 FastRCNN total loss: 0.14146 L1 loss: 0.0000e+00 L2 loss: 1.22718 Learning rate: 0.02 Mask loss: 0.15429 RPN box loss: 0.04995 RPN score loss: 0.00242 RPN total loss: 0.05236 Total loss: 1.57529 timestamp: 1655021133.1322854 iteration: 16815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19037 FastRCNN class loss: 0.13563 FastRCNN total loss: 0.326 L1 loss: 0.0000e+00 L2 loss: 1.22696 Learning rate: 0.02 Mask loss: 0.22486 RPN box loss: 0.02743 RPN score loss: 0.01084 RPN total loss: 0.03827 Total loss: 1.81609 timestamp: 1655021136.3402138 iteration: 16820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17641 FastRCNN class loss: 0.08927 FastRCNN total loss: 0.26568 L1 loss: 0.0000e+00 L2 loss: 1.22677 Learning rate: 0.02 Mask loss: 0.14022 RPN box loss: 0.01551 RPN score loss: 0.00347 RPN total loss: 0.01898 Total loss: 1.65165 timestamp: 1655021139.7471263 iteration: 16825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20725 FastRCNN class loss: 0.09379 FastRCNN total loss: 0.30104 L1 loss: 0.0000e+00 L2 loss: 1.22656 Learning rate: 0.02 Mask loss: 0.18518 RPN box loss: 0.03892 RPN score loss: 0.007 RPN total loss: 0.04592 Total loss: 1.7587 timestamp: 1655021143.006596 iteration: 16830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14842 FastRCNN class loss: 0.11135 FastRCNN total loss: 0.25976 L1 loss: 0.0000e+00 L2 loss: 1.22634 Learning rate: 0.02 Mask loss: 0.13762 RPN box loss: 0.02396 RPN score loss: 0.01251 RPN total loss: 0.03647 Total loss: 1.66019 timestamp: 1655021146.3063636 iteration: 16835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12188 FastRCNN class loss: 0.09011 FastRCNN total loss: 0.212 L1 loss: 0.0000e+00 L2 loss: 1.22613 Learning rate: 0.02 Mask loss: 0.14196 RPN box loss: 0.06871 RPN score loss: 0.01243 RPN total loss: 0.08114 Total loss: 1.66123 timestamp: 1655021149.5216548 iteration: 16840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1043 FastRCNN class loss: 0.0923 FastRCNN total loss: 0.1966 L1 loss: 0.0000e+00 L2 loss: 1.22591 Learning rate: 0.02 Mask loss: 0.25585 RPN box loss: 0.03291 RPN score loss: 0.00921 RPN total loss: 0.04211 Total loss: 1.72048 timestamp: 1655021152.8690972 iteration: 16845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16532 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.24638 L1 loss: 0.0000e+00 L2 loss: 1.22568 Learning rate: 0.02 Mask loss: 0.12793 RPN box loss: 0.0388 RPN score loss: 0.00631 RPN total loss: 0.04511 Total loss: 1.6451 timestamp: 1655021156.2543254 iteration: 16850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14824 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.2152 L1 loss: 0.0000e+00 L2 loss: 1.22546 Learning rate: 0.02 Mask loss: 0.16368 RPN box loss: 0.01143 RPN score loss: 0.00386 RPN total loss: 0.01529 Total loss: 1.61963 timestamp: 1655021159.5923085 iteration: 16855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08296 FastRCNN class loss: 0.05145 FastRCNN total loss: 0.13441 L1 loss: 0.0000e+00 L2 loss: 1.22525 Learning rate: 0.02 Mask loss: 0.21096 RPN box loss: 0.03137 RPN score loss: 0.00607 RPN total loss: 0.03744 Total loss: 1.60805 timestamp: 1655021162.9102638 iteration: 16860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.21103 L1 loss: 0.0000e+00 L2 loss: 1.22501 Learning rate: 0.02 Mask loss: 0.13292 RPN box loss: 0.02678 RPN score loss: 0.00519 RPN total loss: 0.03197 Total loss: 1.60093 timestamp: 1655021166.1311405 iteration: 16865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24783 FastRCNN class loss: 0.12807 FastRCNN total loss: 0.3759 L1 loss: 0.0000e+00 L2 loss: 1.22479 Learning rate: 0.02 Mask loss: 0.27415 RPN box loss: 0.02442 RPN score loss: 0.0348 RPN total loss: 0.05922 Total loss: 1.93406 timestamp: 1655021169.523076 iteration: 16870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15873 FastRCNN class loss: 0.07888 FastRCNN total loss: 0.23761 L1 loss: 0.0000e+00 L2 loss: 1.2246 Learning rate: 0.02 Mask loss: 0.22941 RPN box loss: 0.01254 RPN score loss: 0.00733 RPN total loss: 0.01988 Total loss: 1.7115 timestamp: 1655021172.8648863 iteration: 16875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1603 FastRCNN class loss: 0.07353 FastRCNN total loss: 0.23382 L1 loss: 0.0000e+00 L2 loss: 1.22439 Learning rate: 0.02 Mask loss: 0.16448 RPN box loss: 0.03258 RPN score loss: 0.00424 RPN total loss: 0.03681 Total loss: 1.65951 timestamp: 1655021176.2247324 iteration: 16880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1445 FastRCNN class loss: 0.09718 FastRCNN total loss: 0.24168 L1 loss: 0.0000e+00 L2 loss: 1.22419 Learning rate: 0.02 Mask loss: 0.17026 RPN box loss: 0.04042 RPN score loss: 0.0124 RPN total loss: 0.05283 Total loss: 1.68896 timestamp: 1655021179.4672601 iteration: 16885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04601 FastRCNN class loss: 0.0405 FastRCNN total loss: 0.08651 L1 loss: 0.0000e+00 L2 loss: 1.22397 Learning rate: 0.02 Mask loss: 0.12318 RPN box loss: 0.02611 RPN score loss: 0.00501 RPN total loss: 0.03112 Total loss: 1.46479 timestamp: 1655021182.875376 iteration: 16890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15376 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.23266 L1 loss: 0.0000e+00 L2 loss: 1.22376 Learning rate: 0.02 Mask loss: 0.21016 RPN box loss: 0.10849 RPN score loss: 0.01607 RPN total loss: 0.12456 Total loss: 1.79113 timestamp: 1655021186.2189057 iteration: 16895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15057 FastRCNN class loss: 0.10537 FastRCNN total loss: 0.25594 L1 loss: 0.0000e+00 L2 loss: 1.22353 Learning rate: 0.02 Mask loss: 0.24787 RPN box loss: 0.09658 RPN score loss: 0.00901 RPN total loss: 0.1056 Total loss: 1.83294 timestamp: 1655021189.4902308 iteration: 16900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15784 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.23802 L1 loss: 0.0000e+00 L2 loss: 1.22332 Learning rate: 0.02 Mask loss: 0.18578 RPN box loss: 0.06706 RPN score loss: 0.02267 RPN total loss: 0.08973 Total loss: 1.73685 timestamp: 1655021192.881165 iteration: 16905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12668 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.20113 L1 loss: 0.0000e+00 L2 loss: 1.22311 Learning rate: 0.02 Mask loss: 0.1363 RPN box loss: 0.0254 RPN score loss: 0.00335 RPN total loss: 0.02875 Total loss: 1.58929 timestamp: 1655021196.1617002 iteration: 16910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15186 FastRCNN class loss: 0.10516 FastRCNN total loss: 0.25702 L1 loss: 0.0000e+00 L2 loss: 1.22288 Learning rate: 0.02 Mask loss: 0.16254 RPN box loss: 0.01834 RPN score loss: 0.00358 RPN total loss: 0.02192 Total loss: 1.66436 timestamp: 1655021199.5413089 iteration: 16915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27097 FastRCNN class loss: 0.1541 FastRCNN total loss: 0.42507 L1 loss: 0.0000e+00 L2 loss: 1.22269 Learning rate: 0.02 Mask loss: 0.25284 RPN box loss: 0.04528 RPN score loss: 0.01269 RPN total loss: 0.05797 Total loss: 1.95857 timestamp: 1655021202.8519156 iteration: 16920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11711 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.18116 L1 loss: 0.0000e+00 L2 loss: 1.22249 Learning rate: 0.02 Mask loss: 0.14181 RPN box loss: 0.03205 RPN score loss: 0.00819 RPN total loss: 0.04024 Total loss: 1.5857 timestamp: 1655021206.180937 iteration: 16925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11391 FastRCNN class loss: 0.06499 FastRCNN total loss: 0.1789 L1 loss: 0.0000e+00 L2 loss: 1.22229 Learning rate: 0.02 Mask loss: 0.20841 RPN box loss: 0.01824 RPN score loss: 0.00658 RPN total loss: 0.02481 Total loss: 1.63442 timestamp: 1655021209.39716 iteration: 16930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2308 FastRCNN class loss: 0.16409 FastRCNN total loss: 0.39489 L1 loss: 0.0000e+00 L2 loss: 1.22209 Learning rate: 0.02 Mask loss: 0.23439 RPN box loss: 0.03303 RPN score loss: 0.00722 RPN total loss: 0.04025 Total loss: 1.89162 timestamp: 1655021212.8272288 iteration: 16935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12283 FastRCNN class loss: 0.0578 FastRCNN total loss: 0.18063 L1 loss: 0.0000e+00 L2 loss: 1.22187 Learning rate: 0.02 Mask loss: 0.13401 RPN box loss: 0.01873 RPN score loss: 0.00274 RPN total loss: 0.02148 Total loss: 1.558 timestamp: 1655021216.309412 iteration: 16940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16706 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.26301 L1 loss: 0.0000e+00 L2 loss: 1.22166 Learning rate: 0.02 Mask loss: 0.20357 RPN box loss: 0.05712 RPN score loss: 0.00633 RPN total loss: 0.06345 Total loss: 1.75168 timestamp: 1655021219.5554876 iteration: 16945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16671 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.26295 L1 loss: 0.0000e+00 L2 loss: 1.22144 Learning rate: 0.02 Mask loss: 0.22705 RPN box loss: 0.05208 RPN score loss: 0.01145 RPN total loss: 0.06353 Total loss: 1.77496 timestamp: 1655021222.852081 iteration: 16950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17971 FastRCNN class loss: 0.11845 FastRCNN total loss: 0.29816 L1 loss: 0.0000e+00 L2 loss: 1.22125 Learning rate: 0.02 Mask loss: 0.21704 RPN box loss: 0.03062 RPN score loss: 0.00382 RPN total loss: 0.03444 Total loss: 1.77089 timestamp: 1655021226.0372667 iteration: 16955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09294 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.17089 L1 loss: 0.0000e+00 L2 loss: 1.22105 Learning rate: 0.02 Mask loss: 0.21643 RPN box loss: 0.01625 RPN score loss: 0.01356 RPN total loss: 0.02981 Total loss: 1.63818 timestamp: 1655021229.4542804 iteration: 16960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20192 FastRCNN class loss: 0.07829 FastRCNN total loss: 0.28021 L1 loss: 0.0000e+00 L2 loss: 1.22082 Learning rate: 0.02 Mask loss: 0.13815 RPN box loss: 0.03979 RPN score loss: 0.00787 RPN total loss: 0.04766 Total loss: 1.68683 timestamp: 1655021232.7096505 iteration: 16965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23859 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.34319 L1 loss: 0.0000e+00 L2 loss: 1.22061 Learning rate: 0.02 Mask loss: 0.18825 RPN box loss: 0.06449 RPN score loss: 0.01253 RPN total loss: 0.07703 Total loss: 1.82908 timestamp: 1655021236.0234811 iteration: 16970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20555 FastRCNN class loss: 0.14475 FastRCNN total loss: 0.3503 L1 loss: 0.0000e+00 L2 loss: 1.2204 Learning rate: 0.02 Mask loss: 0.21758 RPN box loss: 0.0341 RPN score loss: 0.005 RPN total loss: 0.03909 Total loss: 1.82738 timestamp: 1655021239.3178399 iteration: 16975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1235 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.20985 L1 loss: 0.0000e+00 L2 loss: 1.2202 Learning rate: 0.02 Mask loss: 0.21079 RPN box loss: 0.04532 RPN score loss: 0.00576 RPN total loss: 0.05108 Total loss: 1.69192 timestamp: 1655021242.7954643 iteration: 16980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16175 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.2254 L1 loss: 0.0000e+00 L2 loss: 1.21999 Learning rate: 0.02 Mask loss: 0.16036 RPN box loss: 0.02705 RPN score loss: 0.01052 RPN total loss: 0.03757 Total loss: 1.64333 timestamp: 1655021246.0827935 iteration: 16985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15541 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.23203 L1 loss: 0.0000e+00 L2 loss: 1.21978 Learning rate: 0.02 Mask loss: 0.16937 RPN box loss: 0.01664 RPN score loss: 0.005 RPN total loss: 0.02164 Total loss: 1.64283 timestamp: 1655021249.3593435 iteration: 16990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09612 FastRCNN class loss: 0.04644 FastRCNN total loss: 0.14255 L1 loss: 0.0000e+00 L2 loss: 1.21956 Learning rate: 0.02 Mask loss: 0.15883 RPN box loss: 0.03653 RPN score loss: 0.0054 RPN total loss: 0.04193 Total loss: 1.56288 timestamp: 1655021252.7608259 iteration: 16995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16965 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.23526 L1 loss: 0.0000e+00 L2 loss: 1.21935 Learning rate: 0.02 Mask loss: 0.14989 RPN box loss: 0.04709 RPN score loss: 0.00358 RPN total loss: 0.05066 Total loss: 1.65517 timestamp: 1655021256.0407903 iteration: 17000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16072 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.28583 L1 loss: 0.0000e+00 L2 loss: 1.21915 Learning rate: 0.02 Mask loss: 0.16779 RPN box loss: 0.02984 RPN score loss: 0.00886 RPN total loss: 0.0387 Total loss: 1.71148 timestamp: 1655021259.4485142 iteration: 17005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12139 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 1.21897 Learning rate: 0.02 Mask loss: 0.14289 RPN box loss: 0.03788 RPN score loss: 0.00637 RPN total loss: 0.04425 Total loss: 1.60986 timestamp: 1655021262.8001072 iteration: 17010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14032 FastRCNN class loss: 0.08195 FastRCNN total loss: 0.22228 L1 loss: 0.0000e+00 L2 loss: 1.21876 Learning rate: 0.02 Mask loss: 0.15236 RPN box loss: 0.06395 RPN score loss: 0.00395 RPN total loss: 0.06789 Total loss: 1.66129 timestamp: 1655021266.121542 iteration: 17015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21476 FastRCNN class loss: 0.0908 FastRCNN total loss: 0.30556 L1 loss: 0.0000e+00 L2 loss: 1.21854 Learning rate: 0.02 Mask loss: 0.11157 RPN box loss: 0.03072 RPN score loss: 0.01022 RPN total loss: 0.04095 Total loss: 1.67662 timestamp: 1655021269.3850965 iteration: 17020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.05123 FastRCNN total loss: 0.11989 L1 loss: 0.0000e+00 L2 loss: 1.21832 Learning rate: 0.02 Mask loss: 0.13407 RPN box loss: 0.04827 RPN score loss: 0.00408 RPN total loss: 0.05236 Total loss: 1.52464 timestamp: 1655021272.8219645 iteration: 17025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14667 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.205 L1 loss: 0.0000e+00 L2 loss: 1.2181 Learning rate: 0.02 Mask loss: 0.09223 RPN box loss: 0.01866 RPN score loss: 0.00202 RPN total loss: 0.02068 Total loss: 1.53602 timestamp: 1655021276.2536235 iteration: 17030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18957 FastRCNN class loss: 0.08327 FastRCNN total loss: 0.27284 L1 loss: 0.0000e+00 L2 loss: 1.21787 Learning rate: 0.02 Mask loss: 0.1582 RPN box loss: 0.03344 RPN score loss: 0.00716 RPN total loss: 0.04059 Total loss: 1.68951 timestamp: 1655021279.5707772 iteration: 17035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22569 FastRCNN class loss: 0.15277 FastRCNN total loss: 0.37846 L1 loss: 0.0000e+00 L2 loss: 1.21768 Learning rate: 0.02 Mask loss: 0.25854 RPN box loss: 0.03731 RPN score loss: 0.0126 RPN total loss: 0.0499 Total loss: 1.90458 timestamp: 1655021282.9437273 iteration: 17040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18779 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.27597 L1 loss: 0.0000e+00 L2 loss: 1.21746 Learning rate: 0.02 Mask loss: 0.18418 RPN box loss: 0.04138 RPN score loss: 0.01689 RPN total loss: 0.05827 Total loss: 1.73587 timestamp: 1655021286.2334466 iteration: 17045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23987 FastRCNN class loss: 0.16475 FastRCNN total loss: 0.40463 L1 loss: 0.0000e+00 L2 loss: 1.21725 Learning rate: 0.02 Mask loss: 0.28397 RPN box loss: 0.00989 RPN score loss: 0.02392 RPN total loss: 0.03381 Total loss: 1.93966 timestamp: 1655021289.5789287 iteration: 17050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17467 FastRCNN class loss: 0.10709 FastRCNN total loss: 0.28175 L1 loss: 0.0000e+00 L2 loss: 1.21704 Learning rate: 0.02 Mask loss: 0.20831 RPN box loss: 0.04574 RPN score loss: 0.00428 RPN total loss: 0.05002 Total loss: 1.75713 timestamp: 1655021292.8298016 iteration: 17055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14886 FastRCNN class loss: 0.10482 FastRCNN total loss: 0.25368 L1 loss: 0.0000e+00 L2 loss: 1.21682 Learning rate: 0.02 Mask loss: 0.15442 RPN box loss: 0.10239 RPN score loss: 0.00524 RPN total loss: 0.10762 Total loss: 1.73255 timestamp: 1655021296.2595825 iteration: 17060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12663 FastRCNN class loss: 0.09504 FastRCNN total loss: 0.22166 L1 loss: 0.0000e+00 L2 loss: 1.21662 Learning rate: 0.02 Mask loss: 0.19244 RPN box loss: 0.04244 RPN score loss: 0.00753 RPN total loss: 0.04997 Total loss: 1.68069 timestamp: 1655021299.5091782 iteration: 17065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10231 FastRCNN class loss: 0.07131 FastRCNN total loss: 0.17362 L1 loss: 0.0000e+00 L2 loss: 1.21642 Learning rate: 0.02 Mask loss: 0.20025 RPN box loss: 0.0208 RPN score loss: 0.00952 RPN total loss: 0.03032 Total loss: 1.6206 timestamp: 1655021302.840805 iteration: 17070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13672 FastRCNN class loss: 0.08245 FastRCNN total loss: 0.21917 L1 loss: 0.0000e+00 L2 loss: 1.21622 Learning rate: 0.02 Mask loss: 0.21876 RPN box loss: 0.0242 RPN score loss: 0.0049 RPN total loss: 0.02911 Total loss: 1.68325 timestamp: 1655021306.1928096 iteration: 17075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15491 FastRCNN class loss: 0.06281 FastRCNN total loss: 0.21772 L1 loss: 0.0000e+00 L2 loss: 1.216 Learning rate: 0.02 Mask loss: 0.21591 RPN box loss: 0.02335 RPN score loss: 0.00569 RPN total loss: 0.02904 Total loss: 1.67867 timestamp: 1655021309.4665906 iteration: 17080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10614 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 1.21578 Learning rate: 0.02 Mask loss: 0.20024 RPN box loss: 0.00816 RPN score loss: 0.00373 RPN total loss: 0.0119 Total loss: 1.59458 timestamp: 1655021312.9957175 iteration: 17085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24585 FastRCNN class loss: 0.19032 FastRCNN total loss: 0.43617 L1 loss: 0.0000e+00 L2 loss: 1.21558 Learning rate: 0.02 Mask loss: 0.24266 RPN box loss: 0.03051 RPN score loss: 0.01031 RPN total loss: 0.04082 Total loss: 1.93524 timestamp: 1655021316.2642374 iteration: 17090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16532 FastRCNN class loss: 0.09436 FastRCNN total loss: 0.25968 L1 loss: 0.0000e+00 L2 loss: 1.21535 Learning rate: 0.02 Mask loss: 0.16444 RPN box loss: 0.03661 RPN score loss: 0.00423 RPN total loss: 0.04084 Total loss: 1.68031 timestamp: 1655021319.8077574 iteration: 17095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11659 FastRCNN class loss: 0.08569 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 1.21514 Learning rate: 0.02 Mask loss: 0.14287 RPN box loss: 0.05309 RPN score loss: 0.01017 RPN total loss: 0.06326 Total loss: 1.62355 timestamp: 1655021323.1491055 iteration: 17100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.182 FastRCNN class loss: 0.11949 FastRCNN total loss: 0.30149 L1 loss: 0.0000e+00 L2 loss: 1.21494 Learning rate: 0.02 Mask loss: 0.2323 RPN box loss: 0.07284 RPN score loss: 0.02147 RPN total loss: 0.09431 Total loss: 1.84304 timestamp: 1655021326.508058 iteration: 17105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09364 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.15479 L1 loss: 0.0000e+00 L2 loss: 1.21471 Learning rate: 0.02 Mask loss: 0.16246 RPN box loss: 0.02283 RPN score loss: 0.00518 RPN total loss: 0.02801 Total loss: 1.55998 timestamp: 1655021329.8293273 iteration: 17110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08162 FastRCNN class loss: 0.03799 FastRCNN total loss: 0.11962 L1 loss: 0.0000e+00 L2 loss: 1.21448 Learning rate: 0.02 Mask loss: 0.11888 RPN box loss: 0.00308 RPN score loss: 0.00223 RPN total loss: 0.00531 Total loss: 1.45828 timestamp: 1655021333.0905619 iteration: 17115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20346 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.27976 L1 loss: 0.0000e+00 L2 loss: 1.21427 Learning rate: 0.02 Mask loss: 0.15479 RPN box loss: 0.02486 RPN score loss: 0.00527 RPN total loss: 0.03012 Total loss: 1.67896 timestamp: 1655021336.493889 iteration: 17120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1382 FastRCNN class loss: 0.09006 FastRCNN total loss: 0.22826 L1 loss: 0.0000e+00 L2 loss: 1.21407 Learning rate: 0.02 Mask loss: 0.15268 RPN box loss: 0.05116 RPN score loss: 0.01256 RPN total loss: 0.06372 Total loss: 1.65874 timestamp: 1655021339.801443 iteration: 17125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16909 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.25991 L1 loss: 0.0000e+00 L2 loss: 1.21386 Learning rate: 0.02 Mask loss: 0.22889 RPN box loss: 0.05481 RPN score loss: 0.00371 RPN total loss: 0.05851 Total loss: 1.76117 timestamp: 1655021343.2705052 iteration: 17130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14327 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 1.21367 Learning rate: 0.02 Mask loss: 0.14621 RPN box loss: 0.01166 RPN score loss: 0.00294 RPN total loss: 0.0146 Total loss: 1.59679 timestamp: 1655021346.5221188 iteration: 17135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17228 FastRCNN class loss: 0.11707 FastRCNN total loss: 0.28935 L1 loss: 0.0000e+00 L2 loss: 1.21346 Learning rate: 0.02 Mask loss: 0.14632 RPN box loss: 0.10411 RPN score loss: 0.01372 RPN total loss: 0.11783 Total loss: 1.76696 timestamp: 1655021350.0022838 iteration: 17140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1561 FastRCNN class loss: 0.09652 FastRCNN total loss: 0.25261 L1 loss: 0.0000e+00 L2 loss: 1.21324 Learning rate: 0.02 Mask loss: 0.17134 RPN box loss: 0.02958 RPN score loss: 0.00548 RPN total loss: 0.03506 Total loss: 1.67225 timestamp: 1655021353.2302508 iteration: 17145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19859 FastRCNN class loss: 0.13651 FastRCNN total loss: 0.3351 L1 loss: 0.0000e+00 L2 loss: 1.21303 Learning rate: 0.02 Mask loss: 0.23282 RPN box loss: 0.03505 RPN score loss: 0.00755 RPN total loss: 0.0426 Total loss: 1.82355 timestamp: 1655021356.5990043 iteration: 17150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12789 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.21737 L1 loss: 0.0000e+00 L2 loss: 1.21283 Learning rate: 0.02 Mask loss: 0.19655 RPN box loss: 0.02444 RPN score loss: 0.0022 RPN total loss: 0.02664 Total loss: 1.65339 timestamp: 1655021359.9712095 iteration: 17155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.158 FastRCNN class loss: 0.11072 FastRCNN total loss: 0.26872 L1 loss: 0.0000e+00 L2 loss: 1.21264 Learning rate: 0.02 Mask loss: 0.1507 RPN box loss: 0.01269 RPN score loss: 0.00369 RPN total loss: 0.01638 Total loss: 1.64844 timestamp: 1655021363.2199948 iteration: 17160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21537 FastRCNN class loss: 0.18987 FastRCNN total loss: 0.40524 L1 loss: 0.0000e+00 L2 loss: 1.21242 Learning rate: 0.02 Mask loss: 0.22205 RPN box loss: 0.03035 RPN score loss: 0.01187 RPN total loss: 0.04222 Total loss: 1.88194 timestamp: 1655021366.5522249 iteration: 17165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21425 FastRCNN class loss: 0.08629 FastRCNN total loss: 0.30054 L1 loss: 0.0000e+00 L2 loss: 1.21219 Learning rate: 0.02 Mask loss: 0.18157 RPN box loss: 0.04533 RPN score loss: 0.01365 RPN total loss: 0.05898 Total loss: 1.75329 timestamp: 1655021369.7956924 iteration: 17170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19092 FastRCNN class loss: 0.11069 FastRCNN total loss: 0.30161 L1 loss: 0.0000e+00 L2 loss: 1.21197 Learning rate: 0.02 Mask loss: 0.19801 RPN box loss: 0.02046 RPN score loss: 0.00714 RPN total loss: 0.0276 Total loss: 1.7392 timestamp: 1655021373.0428278 iteration: 17175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16288 FastRCNN class loss: 0.10531 FastRCNN total loss: 0.26819 L1 loss: 0.0000e+00 L2 loss: 1.21177 Learning rate: 0.02 Mask loss: 0.18082 RPN box loss: 0.03373 RPN score loss: 0.00939 RPN total loss: 0.04312 Total loss: 1.70391 timestamp: 1655021376.3142226 iteration: 17180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1731 FastRCNN class loss: 0.12193 FastRCNN total loss: 0.29504 L1 loss: 0.0000e+00 L2 loss: 1.21156 Learning rate: 0.02 Mask loss: 0.15048 RPN box loss: 0.03418 RPN score loss: 0.00334 RPN total loss: 0.03752 Total loss: 1.69459 timestamp: 1655021379.7082038 iteration: 17185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19437 FastRCNN class loss: 0.13659 FastRCNN total loss: 0.33096 L1 loss: 0.0000e+00 L2 loss: 1.21135 Learning rate: 0.02 Mask loss: 0.20065 RPN box loss: 0.02231 RPN score loss: 0.00594 RPN total loss: 0.02825 Total loss: 1.77121 timestamp: 1655021382.9280102 iteration: 17190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.09131 FastRCNN total loss: 0.19604 L1 loss: 0.0000e+00 L2 loss: 1.21115 Learning rate: 0.02 Mask loss: 0.13693 RPN box loss: 0.00887 RPN score loss: 0.00337 RPN total loss: 0.01223 Total loss: 1.55635 timestamp: 1655021386.2149463 iteration: 17195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22847 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.31998 L1 loss: 0.0000e+00 L2 loss: 1.21093 Learning rate: 0.02 Mask loss: 0.25787 RPN box loss: 0.01434 RPN score loss: 0.00882 RPN total loss: 0.02316 Total loss: 1.81194 timestamp: 1655021389.6231284 iteration: 17200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16281 FastRCNN class loss: 0.12128 FastRCNN total loss: 0.28409 L1 loss: 0.0000e+00 L2 loss: 1.2107 Learning rate: 0.02 Mask loss: 0.28646 RPN box loss: 0.03765 RPN score loss: 0.00415 RPN total loss: 0.04179 Total loss: 1.82305 timestamp: 1655021392.9031255 iteration: 17205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15373 FastRCNN class loss: 0.14995 FastRCNN total loss: 0.30368 L1 loss: 0.0000e+00 L2 loss: 1.21048 Learning rate: 0.02 Mask loss: 0.13416 RPN box loss: 0.0151 RPN score loss: 0.0031 RPN total loss: 0.0182 Total loss: 1.66653 timestamp: 1655021396.1825323 iteration: 17210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16258 FastRCNN class loss: 0.11259 FastRCNN total loss: 0.27517 L1 loss: 0.0000e+00 L2 loss: 1.21029 Learning rate: 0.02 Mask loss: 0.19722 RPN box loss: 0.03015 RPN score loss: 0.00216 RPN total loss: 0.03231 Total loss: 1.71498 timestamp: 1655021399.4374661 iteration: 17215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1673 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.26758 L1 loss: 0.0000e+00 L2 loss: 1.21007 Learning rate: 0.02 Mask loss: 0.2145 RPN box loss: 0.05754 RPN score loss: 0.03105 RPN total loss: 0.0886 Total loss: 1.78074 timestamp: 1655021402.8708272 iteration: 17220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14036 FastRCNN class loss: 0.09341 FastRCNN total loss: 0.23376 L1 loss: 0.0000e+00 L2 loss: 1.20985 Learning rate: 0.02 Mask loss: 0.44475 RPN box loss: 0.01211 RPN score loss: 0.00501 RPN total loss: 0.01711 Total loss: 1.90548 timestamp: 1655021406.1101897 iteration: 17225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19684 FastRCNN class loss: 0.1012 FastRCNN total loss: 0.29804 L1 loss: 0.0000e+00 L2 loss: 1.20962 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.01633 RPN score loss: 0.00387 RPN total loss: 0.0202 Total loss: 1.67443 timestamp: 1655021409.4596574 iteration: 17230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23796 FastRCNN class loss: 0.13418 FastRCNN total loss: 0.37214 L1 loss: 0.0000e+00 L2 loss: 1.20941 Learning rate: 0.02 Mask loss: 0.28623 RPN box loss: 0.02457 RPN score loss: 0.00339 RPN total loss: 0.02796 Total loss: 1.89573 timestamp: 1655021412.7268536 iteration: 17235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18946 FastRCNN class loss: 0.07736 FastRCNN total loss: 0.26682 L1 loss: 0.0000e+00 L2 loss: 1.20921 Learning rate: 0.02 Mask loss: 0.13103 RPN box loss: 0.02655 RPN score loss: 0.00296 RPN total loss: 0.02951 Total loss: 1.63656 timestamp: 1655021416.1526673 iteration: 17240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19603 FastRCNN class loss: 0.19301 FastRCNN total loss: 0.38904 L1 loss: 0.0000e+00 L2 loss: 1.20904 Learning rate: 0.02 Mask loss: 0.26355 RPN box loss: 0.03184 RPN score loss: 0.01344 RPN total loss: 0.04528 Total loss: 1.9069 timestamp: 1655021419.515421 iteration: 17245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13418 FastRCNN class loss: 0.08568 FastRCNN total loss: 0.21986 L1 loss: 0.0000e+00 L2 loss: 1.20883 Learning rate: 0.02 Mask loss: 0.13694 RPN box loss: 0.03067 RPN score loss: 0.00725 RPN total loss: 0.03792 Total loss: 1.60355 timestamp: 1655021422.7705302 iteration: 17250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20831 FastRCNN class loss: 0.08812 FastRCNN total loss: 0.29643 L1 loss: 0.0000e+00 L2 loss: 1.20862 Learning rate: 0.02 Mask loss: 0.19751 RPN box loss: 0.05063 RPN score loss: 0.00378 RPN total loss: 0.05441 Total loss: 1.75697 timestamp: 1655021426.126337 iteration: 17255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.12264 FastRCNN total loss: 0.26319 L1 loss: 0.0000e+00 L2 loss: 1.2084 Learning rate: 0.02 Mask loss: 0.18624 RPN box loss: 0.01941 RPN score loss: 0.00656 RPN total loss: 0.02597 Total loss: 1.6838 timestamp: 1655021429.418278 iteration: 17260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17513 FastRCNN class loss: 0.11622 FastRCNN total loss: 0.29135 L1 loss: 0.0000e+00 L2 loss: 1.20818 Learning rate: 0.02 Mask loss: 0.21846 RPN box loss: 0.06375 RPN score loss: 0.00622 RPN total loss: 0.06998 Total loss: 1.78798 timestamp: 1655021432.7291822 iteration: 17265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12159 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.18096 L1 loss: 0.0000e+00 L2 loss: 1.20799 Learning rate: 0.02 Mask loss: 0.11107 RPN box loss: 0.02563 RPN score loss: 0.00499 RPN total loss: 0.03062 Total loss: 1.53063 timestamp: 1655021436.0439308 iteration: 17270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13971 FastRCNN class loss: 0.07352 FastRCNN total loss: 0.21323 L1 loss: 0.0000e+00 L2 loss: 1.20779 Learning rate: 0.02 Mask loss: 0.19505 RPN box loss: 0.01705 RPN score loss: 0.00654 RPN total loss: 0.02359 Total loss: 1.63966 timestamp: 1655021439.401537 iteration: 17275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10672 FastRCNN class loss: 0.10726 FastRCNN total loss: 0.21398 L1 loss: 0.0000e+00 L2 loss: 1.20756 Learning rate: 0.02 Mask loss: 0.17509 RPN box loss: 0.01141 RPN score loss: 0.00389 RPN total loss: 0.0153 Total loss: 1.61193 timestamp: 1655021442.8235807 iteration: 17280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16457 FastRCNN class loss: 0.10225 FastRCNN total loss: 0.26683 L1 loss: 0.0000e+00 L2 loss: 1.20735 Learning rate: 0.02 Mask loss: 0.16519 RPN box loss: 0.06207 RPN score loss: 0.01898 RPN total loss: 0.08105 Total loss: 1.72042 timestamp: 1655021446.170937 iteration: 17285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16571 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.23594 L1 loss: 0.0000e+00 L2 loss: 1.20714 Learning rate: 0.02 Mask loss: 0.11107 RPN box loss: 0.01503 RPN score loss: 0.00297 RPN total loss: 0.018 Total loss: 1.57214 timestamp: 1655021449.579258 iteration: 17290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18611 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.26231 L1 loss: 0.0000e+00 L2 loss: 1.20693 Learning rate: 0.02 Mask loss: 0.15305 RPN box loss: 0.01925 RPN score loss: 0.00618 RPN total loss: 0.02543 Total loss: 1.64772 timestamp: 1655021452.832588 iteration: 17295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15756 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.2332 L1 loss: 0.0000e+00 L2 loss: 1.20671 Learning rate: 0.02 Mask loss: 0.11809 RPN box loss: 0.05198 RPN score loss: 0.00897 RPN total loss: 0.06095 Total loss: 1.61895 timestamp: 1655021456.2716966 iteration: 17300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25163 FastRCNN class loss: 0.1043 FastRCNN total loss: 0.35594 L1 loss: 0.0000e+00 L2 loss: 1.20649 Learning rate: 0.02 Mask loss: 0.19343 RPN box loss: 0.0549 RPN score loss: 0.00854 RPN total loss: 0.06345 Total loss: 1.81931 timestamp: 1655021459.5019073 iteration: 17305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17616 FastRCNN class loss: 0.08258 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 1.20629 Learning rate: 0.02 Mask loss: 0.13902 RPN box loss: 0.03584 RPN score loss: 0.00502 RPN total loss: 0.04086 Total loss: 1.64491 timestamp: 1655021462.861058 iteration: 17310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15169 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.20959 L1 loss: 0.0000e+00 L2 loss: 1.2061 Learning rate: 0.02 Mask loss: 0.16821 RPN box loss: 0.03858 RPN score loss: 0.00486 RPN total loss: 0.04345 Total loss: 1.62734 timestamp: 1655021466.1149106 iteration: 17315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12158 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.19215 L1 loss: 0.0000e+00 L2 loss: 1.2059 Learning rate: 0.02 Mask loss: 0.16544 RPN box loss: 0.01464 RPN score loss: 0.00573 RPN total loss: 0.02036 Total loss: 1.58385 timestamp: 1655021469.5037134 iteration: 17320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21084 FastRCNN class loss: 0.11014 FastRCNN total loss: 0.32098 L1 loss: 0.0000e+00 L2 loss: 1.20568 Learning rate: 0.02 Mask loss: 0.19777 RPN box loss: 0.04536 RPN score loss: 0.01369 RPN total loss: 0.05905 Total loss: 1.78348 timestamp: 1655021472.7273378 iteration: 17325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14925 FastRCNN class loss: 0.09405 FastRCNN total loss: 0.2433 L1 loss: 0.0000e+00 L2 loss: 1.20547 Learning rate: 0.02 Mask loss: 0.15528 RPN box loss: 0.03266 RPN score loss: 0.0091 RPN total loss: 0.04175 Total loss: 1.64581 timestamp: 1655021476.1209538 iteration: 17330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24732 FastRCNN class loss: 0.13864 FastRCNN total loss: 0.38596 L1 loss: 0.0000e+00 L2 loss: 1.20526 Learning rate: 0.02 Mask loss: 0.20656 RPN box loss: 0.05518 RPN score loss: 0.02032 RPN total loss: 0.07549 Total loss: 1.87327 timestamp: 1655021479.485953 iteration: 17335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13537 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.22487 L1 loss: 0.0000e+00 L2 loss: 1.20504 Learning rate: 0.02 Mask loss: 0.21089 RPN box loss: 0.01432 RPN score loss: 0.00695 RPN total loss: 0.02127 Total loss: 1.66207 timestamp: 1655021482.7456722 iteration: 17340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16231 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.23837 L1 loss: 0.0000e+00 L2 loss: 1.20482 Learning rate: 0.02 Mask loss: 0.14936 RPN box loss: 0.04381 RPN score loss: 0.00529 RPN total loss: 0.0491 Total loss: 1.64165 timestamp: 1655021486.139812 iteration: 17345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13477 FastRCNN class loss: 0.09329 FastRCNN total loss: 0.22806 L1 loss: 0.0000e+00 L2 loss: 1.20462 Learning rate: 0.02 Mask loss: 0.22027 RPN box loss: 0.02588 RPN score loss: 0.00394 RPN total loss: 0.02982 Total loss: 1.68277 timestamp: 1655021489.357406 iteration: 17350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19888 FastRCNN class loss: 0.1193 FastRCNN total loss: 0.31818 L1 loss: 0.0000e+00 L2 loss: 1.20442 Learning rate: 0.02 Mask loss: 0.21878 RPN box loss: 0.04145 RPN score loss: 0.00628 RPN total loss: 0.04773 Total loss: 1.78911 timestamp: 1655021492.6858401 iteration: 17355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21097 FastRCNN class loss: 0.10272 FastRCNN total loss: 0.31369 L1 loss: 0.0000e+00 L2 loss: 1.2042 Learning rate: 0.02 Mask loss: 0.2213 RPN box loss: 0.03285 RPN score loss: 0.00857 RPN total loss: 0.04142 Total loss: 1.78062 timestamp: 1655021496.0204616 iteration: 17360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13268 FastRCNN class loss: 0.11835 FastRCNN total loss: 0.25103 L1 loss: 0.0000e+00 L2 loss: 1.204 Learning rate: 0.02 Mask loss: 0.20335 RPN box loss: 0.03753 RPN score loss: 0.00349 RPN total loss: 0.04103 Total loss: 1.69941 timestamp: 1655021499.394014 iteration: 17365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08444 FastRCNN class loss: 0.04308 FastRCNN total loss: 0.12752 L1 loss: 0.0000e+00 L2 loss: 1.20379 Learning rate: 0.02 Mask loss: 0.14013 RPN box loss: 0.01998 RPN score loss: 0.00394 RPN total loss: 0.02392 Total loss: 1.49536 timestamp: 1655021502.6656222 iteration: 17370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18012 FastRCNN class loss: 0.11382 FastRCNN total loss: 0.29394 L1 loss: 0.0000e+00 L2 loss: 1.20356 Learning rate: 0.02 Mask loss: 0.14376 RPN box loss: 0.06306 RPN score loss: 0.00976 RPN total loss: 0.07282 Total loss: 1.71409 timestamp: 1655021506.0171897 iteration: 17375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10867 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.16782 L1 loss: 0.0000e+00 L2 loss: 1.20335 Learning rate: 0.02 Mask loss: 0.17239 RPN box loss: 0.04753 RPN score loss: 0.00952 RPN total loss: 0.05705 Total loss: 1.60061 timestamp: 1655021509.2481718 iteration: 17380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14817 FastRCNN class loss: 0.12654 FastRCNN total loss: 0.27471 L1 loss: 0.0000e+00 L2 loss: 1.20314 Learning rate: 0.02 Mask loss: 0.23316 RPN box loss: 0.0577 RPN score loss: 0.02512 RPN total loss: 0.08281 Total loss: 1.79382 timestamp: 1655021512.5333905 iteration: 17385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11225 FastRCNN class loss: 0.08516 FastRCNN total loss: 0.19742 L1 loss: 0.0000e+00 L2 loss: 1.20294 Learning rate: 0.02 Mask loss: 0.1597 RPN box loss: 0.08306 RPN score loss: 0.01541 RPN total loss: 0.09847 Total loss: 1.65852 timestamp: 1655021515.9005876 iteration: 17390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13504 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.20728 L1 loss: 0.0000e+00 L2 loss: 1.20275 Learning rate: 0.02 Mask loss: 0.20444 RPN box loss: 0.03804 RPN score loss: 0.00672 RPN total loss: 0.04476 Total loss: 1.65923 timestamp: 1655021519.1738498 iteration: 17395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12622 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 1.20254 Learning rate: 0.02 Mask loss: 0.23178 RPN box loss: 0.00883 RPN score loss: 0.00552 RPN total loss: 0.01435 Total loss: 1.64079 timestamp: 1655021522.5452895 iteration: 17400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16683 FastRCNN class loss: 0.07843 FastRCNN total loss: 0.24526 L1 loss: 0.0000e+00 L2 loss: 1.20234 Learning rate: 0.02 Mask loss: 0.16245 RPN box loss: 0.04408 RPN score loss: 0.00789 RPN total loss: 0.05197 Total loss: 1.66202 timestamp: 1655021525.820507 iteration: 17405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11008 FastRCNN class loss: 0.0972 FastRCNN total loss: 0.20728 L1 loss: 0.0000e+00 L2 loss: 1.20212 Learning rate: 0.02 Mask loss: 0.15966 RPN box loss: 0.10551 RPN score loss: 0.0124 RPN total loss: 0.11791 Total loss: 1.68698 timestamp: 1655021529.1385968 iteration: 17410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13863 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.22567 L1 loss: 0.0000e+00 L2 loss: 1.20191 Learning rate: 0.02 Mask loss: 0.15364 RPN box loss: 0.02881 RPN score loss: 0.03559 RPN total loss: 0.0644 Total loss: 1.64561 timestamp: 1655021532.3606656 iteration: 17415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06674 FastRCNN class loss: 0.04048 FastRCNN total loss: 0.10722 L1 loss: 0.0000e+00 L2 loss: 1.2017 Learning rate: 0.02 Mask loss: 0.12276 RPN box loss: 0.01198 RPN score loss: 0.00434 RPN total loss: 0.01632 Total loss: 1.448 timestamp: 1655021535.862701 iteration: 17420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18537 FastRCNN class loss: 0.07373 FastRCNN total loss: 0.2591 L1 loss: 0.0000e+00 L2 loss: 1.20149 Learning rate: 0.02 Mask loss: 0.18823 RPN box loss: 0.02745 RPN score loss: 0.00813 RPN total loss: 0.03558 Total loss: 1.6844 timestamp: 1655021539.299998 iteration: 17425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06049 FastRCNN class loss: 0.04917 FastRCNN total loss: 0.10966 L1 loss: 0.0000e+00 L2 loss: 1.2013 Learning rate: 0.02 Mask loss: 0.11804 RPN box loss: 0.06694 RPN score loss: 0.01209 RPN total loss: 0.07903 Total loss: 1.50804 timestamp: 1655021542.5384898 iteration: 17430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14758 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.21024 L1 loss: 0.0000e+00 L2 loss: 1.20109 Learning rate: 0.02 Mask loss: 0.12634 RPN box loss: 0.02524 RPN score loss: 0.01693 RPN total loss: 0.04217 Total loss: 1.57983 timestamp: 1655021546.0101848 iteration: 17435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17782 FastRCNN class loss: 0.12594 FastRCNN total loss: 0.30376 L1 loss: 0.0000e+00 L2 loss: 1.20088 Learning rate: 0.02 Mask loss: 0.20427 RPN box loss: 0.04644 RPN score loss: 0.01333 RPN total loss: 0.05978 Total loss: 1.76869 timestamp: 1655021549.2523797 iteration: 17440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0936 FastRCNN class loss: 0.09264 FastRCNN total loss: 0.18624 L1 loss: 0.0000e+00 L2 loss: 1.20069 Learning rate: 0.02 Mask loss: 0.10134 RPN box loss: 0.03477 RPN score loss: 0.01066 RPN total loss: 0.04543 Total loss: 1.5337 timestamp: 1655021552.661582 iteration: 17445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.21289 L1 loss: 0.0000e+00 L2 loss: 1.20046 Learning rate: 0.02 Mask loss: 0.12105 RPN box loss: 0.02846 RPN score loss: 0.00541 RPN total loss: 0.03387 Total loss: 1.56827 timestamp: 1655021555.9517484 iteration: 17450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17784 FastRCNN class loss: 0.11693 FastRCNN total loss: 0.29477 L1 loss: 0.0000e+00 L2 loss: 1.20023 Learning rate: 0.02 Mask loss: 0.25259 RPN box loss: 0.06077 RPN score loss: 0.00695 RPN total loss: 0.06772 Total loss: 1.8153 timestamp: 1655021559.316271 iteration: 17455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14428 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.20922 L1 loss: 0.0000e+00 L2 loss: 1.19999 Learning rate: 0.02 Mask loss: 0.13248 RPN box loss: 0.0125 RPN score loss: 0.00205 RPN total loss: 0.01454 Total loss: 1.55624 timestamp: 1655021562.6332161 iteration: 17460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13399 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.21496 L1 loss: 0.0000e+00 L2 loss: 1.19979 Learning rate: 0.02 Mask loss: 0.10774 RPN box loss: 0.01995 RPN score loss: 0.0062 RPN total loss: 0.02616 Total loss: 1.54865 timestamp: 1655021566.0243037 iteration: 17465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19785 FastRCNN class loss: 0.09604 FastRCNN total loss: 0.29389 L1 loss: 0.0000e+00 L2 loss: 1.19958 Learning rate: 0.02 Mask loss: 0.17313 RPN box loss: 0.01528 RPN score loss: 0.00479 RPN total loss: 0.02006 Total loss: 1.68666 timestamp: 1655021569.4983623 iteration: 17470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15366 FastRCNN class loss: 0.14546 FastRCNN total loss: 0.29912 L1 loss: 0.0000e+00 L2 loss: 1.19939 Learning rate: 0.02 Mask loss: 0.19684 RPN box loss: 0.0681 RPN score loss: 0.01695 RPN total loss: 0.08504 Total loss: 1.78039 timestamp: 1655021572.7974608 iteration: 17475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1547 FastRCNN class loss: 0.1115 FastRCNN total loss: 0.2662 L1 loss: 0.0000e+00 L2 loss: 1.19921 Learning rate: 0.02 Mask loss: 0.16071 RPN box loss: 0.03786 RPN score loss: 0.01416 RPN total loss: 0.05203 Total loss: 1.67814 timestamp: 1655021576.1955788 iteration: 17480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14685 FastRCNN class loss: 0.11987 FastRCNN total loss: 0.26672 L1 loss: 0.0000e+00 L2 loss: 1.19899 Learning rate: 0.02 Mask loss: 0.20989 RPN box loss: 0.06376 RPN score loss: 0.01474 RPN total loss: 0.0785 Total loss: 1.7541 timestamp: 1655021579.5468774 iteration: 17485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20703 FastRCNN class loss: 0.10873 FastRCNN total loss: 0.31576 L1 loss: 0.0000e+00 L2 loss: 1.19877 Learning rate: 0.02 Mask loss: 0.1578 RPN box loss: 0.01548 RPN score loss: 0.00485 RPN total loss: 0.02033 Total loss: 1.69267 timestamp: 1655021582.9826958 iteration: 17490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2302 FastRCNN class loss: 0.13994 FastRCNN total loss: 0.37015 L1 loss: 0.0000e+00 L2 loss: 1.19858 Learning rate: 0.02 Mask loss: 0.21259 RPN box loss: 0.05444 RPN score loss: 0.00797 RPN total loss: 0.06241 Total loss: 1.84372 timestamp: 1655021586.2679977 iteration: 17495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17107 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.26341 L1 loss: 0.0000e+00 L2 loss: 1.19836 Learning rate: 0.02 Mask loss: 0.16472 RPN box loss: 0.02614 RPN score loss: 0.01314 RPN total loss: 0.03927 Total loss: 1.66577 timestamp: 1655021589.6842806 iteration: 17500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16457 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.23682 L1 loss: 0.0000e+00 L2 loss: 1.19815 Learning rate: 0.02 Mask loss: 0.12983 RPN box loss: 0.032 RPN score loss: 0.00853 RPN total loss: 0.04052 Total loss: 1.60532 timestamp: 1655021593.0461266 iteration: 17505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17025 FastRCNN class loss: 0.09386 FastRCNN total loss: 0.2641 L1 loss: 0.0000e+00 L2 loss: 1.19794 Learning rate: 0.02 Mask loss: 0.17689 RPN box loss: 0.04841 RPN score loss: 0.00995 RPN total loss: 0.05836 Total loss: 1.69728 timestamp: 1655021596.2622817 iteration: 17510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09962 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.16248 L1 loss: 0.0000e+00 L2 loss: 1.19774 Learning rate: 0.02 Mask loss: 0.13271 RPN box loss: 0.04778 RPN score loss: 0.00438 RPN total loss: 0.05215 Total loss: 1.54509 timestamp: 1655021599.5890038 iteration: 17515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16302 FastRCNN class loss: 0.10647 FastRCNN total loss: 0.26949 L1 loss: 0.0000e+00 L2 loss: 1.19753 Learning rate: 0.02 Mask loss: 0.18431 RPN box loss: 0.02907 RPN score loss: 0.01287 RPN total loss: 0.04194 Total loss: 1.69327 timestamp: 1655021602.8388622 iteration: 17520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17381 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.26115 L1 loss: 0.0000e+00 L2 loss: 1.19732 Learning rate: 0.02 Mask loss: 0.14076 RPN box loss: 0.05652 RPN score loss: 0.01145 RPN total loss: 0.06796 Total loss: 1.6672 timestamp: 1655021606.2575214 iteration: 17525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16037 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 1.1971 Learning rate: 0.02 Mask loss: 0.22387 RPN box loss: 0.03387 RPN score loss: 0.00596 RPN total loss: 0.03983 Total loss: 1.68755 timestamp: 1655021609.5660114 iteration: 17530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26856 FastRCNN class loss: 0.16487 FastRCNN total loss: 0.43344 L1 loss: 0.0000e+00 L2 loss: 1.1969 Learning rate: 0.02 Mask loss: 0.22103 RPN box loss: 0.08534 RPN score loss: 0.02451 RPN total loss: 0.10984 Total loss: 1.9612 timestamp: 1655021612.9187984 iteration: 17535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20477 FastRCNN class loss: 0.14632 FastRCNN total loss: 0.35109 L1 loss: 0.0000e+00 L2 loss: 1.19671 Learning rate: 0.02 Mask loss: 0.28688 RPN box loss: 0.0369 RPN score loss: 0.01236 RPN total loss: 0.04926 Total loss: 1.88394 timestamp: 1655021616.188007 iteration: 17540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11137 FastRCNN class loss: 0.09323 FastRCNN total loss: 0.2046 L1 loss: 0.0000e+00 L2 loss: 1.19651 Learning rate: 0.02 Mask loss: 0.17324 RPN box loss: 0.0305 RPN score loss: 0.00428 RPN total loss: 0.03478 Total loss: 1.60914 timestamp: 1655021619.489427 iteration: 17545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07933 FastRCNN class loss: 0.07975 FastRCNN total loss: 0.15907 L1 loss: 0.0000e+00 L2 loss: 1.19631 Learning rate: 0.02 Mask loss: 0.20151 RPN box loss: 0.06964 RPN score loss: 0.00388 RPN total loss: 0.07352 Total loss: 1.63042 timestamp: 1655021622.8217232 iteration: 17550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.22195 L1 loss: 0.0000e+00 L2 loss: 1.19609 Learning rate: 0.02 Mask loss: 0.1212 RPN box loss: 0.05078 RPN score loss: 0.00969 RPN total loss: 0.06046 Total loss: 1.5997 timestamp: 1655021626.0731258 iteration: 17555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12236 FastRCNN class loss: 0.08464 FastRCNN total loss: 0.207 L1 loss: 0.0000e+00 L2 loss: 1.19587 Learning rate: 0.02 Mask loss: 0.19341 RPN box loss: 0.03203 RPN score loss: 0.00947 RPN total loss: 0.0415 Total loss: 1.63778 timestamp: 1655021629.4729986 iteration: 17560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12688 FastRCNN class loss: 0.08196 FastRCNN total loss: 0.20884 L1 loss: 0.0000e+00 L2 loss: 1.19567 Learning rate: 0.02 Mask loss: 0.19163 RPN box loss: 0.06668 RPN score loss: 0.02973 RPN total loss: 0.09641 Total loss: 1.69256 timestamp: 1655021632.7464843 iteration: 17565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07525 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.14443 L1 loss: 0.0000e+00 L2 loss: 1.19545 Learning rate: 0.02 Mask loss: 0.13813 RPN box loss: 0.0393 RPN score loss: 0.00846 RPN total loss: 0.04776 Total loss: 1.52578 timestamp: 1655021636.1783 iteration: 17570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15074 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.24029 L1 loss: 0.0000e+00 L2 loss: 1.19524 Learning rate: 0.02 Mask loss: 0.1311 RPN box loss: 0.05191 RPN score loss: 0.00631 RPN total loss: 0.05822 Total loss: 1.62484 timestamp: 1655021639.431767 iteration: 17575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18992 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.27698 L1 loss: 0.0000e+00 L2 loss: 1.19504 Learning rate: 0.02 Mask loss: 0.17782 RPN box loss: 0.07193 RPN score loss: 0.01413 RPN total loss: 0.08605 Total loss: 1.73589 timestamp: 1655021642.8516169 iteration: 17580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23393 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.30814 L1 loss: 0.0000e+00 L2 loss: 1.19484 Learning rate: 0.02 Mask loss: 0.33693 RPN box loss: 0.05343 RPN score loss: 0.00729 RPN total loss: 0.06073 Total loss: 1.90063 timestamp: 1655021646.1621559 iteration: 17585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1437 FastRCNN class loss: 0.12614 FastRCNN total loss: 0.26984 L1 loss: 0.0000e+00 L2 loss: 1.19463 Learning rate: 0.02 Mask loss: 0.20164 RPN box loss: 0.04318 RPN score loss: 0.00991 RPN total loss: 0.05309 Total loss: 1.7192 timestamp: 1655021649.5589166 iteration: 17590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15301 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.22441 L1 loss: 0.0000e+00 L2 loss: 1.19442 Learning rate: 0.02 Mask loss: 0.1544 RPN box loss: 0.03058 RPN score loss: 0.01094 RPN total loss: 0.04152 Total loss: 1.61475 timestamp: 1655021652.894794 iteration: 17595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21972 FastRCNN class loss: 0.13943 FastRCNN total loss: 0.35915 L1 loss: 0.0000e+00 L2 loss: 1.19421 Learning rate: 0.02 Mask loss: 0.19509 RPN box loss: 0.01951 RPN score loss: 0.03309 RPN total loss: 0.0526 Total loss: 1.80105 timestamp: 1655021656.152991 iteration: 17600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.0477 FastRCNN total loss: 0.14184 L1 loss: 0.0000e+00 L2 loss: 1.19399 Learning rate: 0.02 Mask loss: 0.14321 RPN box loss: 0.01542 RPN score loss: 0.00586 RPN total loss: 0.02128 Total loss: 1.50032 timestamp: 1655021659.571698 iteration: 17605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.18554 L1 loss: 0.0000e+00 L2 loss: 1.19379 Learning rate: 0.02 Mask loss: 0.08856 RPN box loss: 0.01799 RPN score loss: 0.00384 RPN total loss: 0.02183 Total loss: 1.48972 timestamp: 1655021662.802681 iteration: 17610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1782 FastRCNN class loss: 0.07744 FastRCNN total loss: 0.25564 L1 loss: 0.0000e+00 L2 loss: 1.19359 Learning rate: 0.02 Mask loss: 0.08762 RPN box loss: 0.02186 RPN score loss: 0.00099 RPN total loss: 0.02285 Total loss: 1.55971 timestamp: 1655021666.185853 iteration: 17615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18386 FastRCNN class loss: 0.13644 FastRCNN total loss: 0.3203 L1 loss: 0.0000e+00 L2 loss: 1.19339 Learning rate: 0.02 Mask loss: 0.18102 RPN box loss: 0.04504 RPN score loss: 0.01013 RPN total loss: 0.05516 Total loss: 1.74988 timestamp: 1655021669.484496 iteration: 17620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06032 FastRCNN class loss: 0.03945 FastRCNN total loss: 0.09977 L1 loss: 0.0000e+00 L2 loss: 1.1932 Learning rate: 0.02 Mask loss: 0.12518 RPN box loss: 0.05886 RPN score loss: 0.00779 RPN total loss: 0.06665 Total loss: 1.4848 timestamp: 1655021672.8956897 iteration: 17625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14971 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.22035 L1 loss: 0.0000e+00 L2 loss: 1.193 Learning rate: 0.02 Mask loss: 0.24323 RPN box loss: 0.02564 RPN score loss: 0.01116 RPN total loss: 0.0368 Total loss: 1.69339 timestamp: 1655021676.1626334 iteration: 17630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22517 FastRCNN class loss: 0.14494 FastRCNN total loss: 0.37011 L1 loss: 0.0000e+00 L2 loss: 1.19279 Learning rate: 0.02 Mask loss: 0.2088 RPN box loss: 0.03106 RPN score loss: 0.01227 RPN total loss: 0.04333 Total loss: 1.81503 timestamp: 1655021679.5810225 iteration: 17635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23585 FastRCNN class loss: 0.1116 FastRCNN total loss: 0.34745 L1 loss: 0.0000e+00 L2 loss: 1.1926 Learning rate: 0.02 Mask loss: 0.21162 RPN box loss: 0.02352 RPN score loss: 0.01399 RPN total loss: 0.03751 Total loss: 1.78918 timestamp: 1655021682.9940255 iteration: 17640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17024 FastRCNN class loss: 0.10572 FastRCNN total loss: 0.27596 L1 loss: 0.0000e+00 L2 loss: 1.19237 Learning rate: 0.02 Mask loss: 0.17848 RPN box loss: 0.03603 RPN score loss: 0.01064 RPN total loss: 0.04667 Total loss: 1.69349 timestamp: 1655021686.1969633 iteration: 17645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06219 FastRCNN class loss: 0.05361 FastRCNN total loss: 0.11579 L1 loss: 0.0000e+00 L2 loss: 1.19218 Learning rate: 0.02 Mask loss: 0.17742 RPN box loss: 0.03111 RPN score loss: 0.00631 RPN total loss: 0.03742 Total loss: 1.52281 timestamp: 1655021689.539795 iteration: 17650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08356 FastRCNN class loss: 0.04006 FastRCNN total loss: 0.12362 L1 loss: 0.0000e+00 L2 loss: 1.19199 Learning rate: 0.02 Mask loss: 0.15363 RPN box loss: 0.00456 RPN score loss: 0.00199 RPN total loss: 0.00655 Total loss: 1.47579 timestamp: 1655021692.8023787 iteration: 17655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17614 FastRCNN class loss: 0.08194 FastRCNN total loss: 0.25808 L1 loss: 0.0000e+00 L2 loss: 1.19173 Learning rate: 0.02 Mask loss: 0.1391 RPN box loss: 0.02005 RPN score loss: 0.00532 RPN total loss: 0.02536 Total loss: 1.61428 timestamp: 1655021696.1050618 iteration: 17660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17868 FastRCNN class loss: 0.09365 FastRCNN total loss: 0.27233 L1 loss: 0.0000e+00 L2 loss: 1.19153 Learning rate: 0.02 Mask loss: 0.18515 RPN box loss: 0.04343 RPN score loss: 0.00362 RPN total loss: 0.04705 Total loss: 1.69606 timestamp: 1655021699.3431807 iteration: 17665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13719 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.19794 L1 loss: 0.0000e+00 L2 loss: 1.19133 Learning rate: 0.02 Mask loss: 0.16262 RPN box loss: 0.03864 RPN score loss: 0.00691 RPN total loss: 0.04555 Total loss: 1.59744 timestamp: 1655021702.738203 iteration: 17670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12409 FastRCNN class loss: 0.0987 FastRCNN total loss: 0.2228 L1 loss: 0.0000e+00 L2 loss: 1.1911 Learning rate: 0.02 Mask loss: 0.22088 RPN box loss: 0.04028 RPN score loss: 0.01173 RPN total loss: 0.05201 Total loss: 1.68679 timestamp: 1655021706.0019295 iteration: 17675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21238 FastRCNN class loss: 0.11424 FastRCNN total loss: 0.32662 L1 loss: 0.0000e+00 L2 loss: 1.19091 Learning rate: 0.02 Mask loss: 0.22115 RPN box loss: 0.01469 RPN score loss: 0.00531 RPN total loss: 0.02 Total loss: 1.75868 timestamp: 1655021709.3494723 iteration: 17680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11226 FastRCNN class loss: 0.04733 FastRCNN total loss: 0.15959 L1 loss: 0.0000e+00 L2 loss: 1.19074 Learning rate: 0.02 Mask loss: 0.17431 RPN box loss: 0.09821 RPN score loss: 0.01086 RPN total loss: 0.10907 Total loss: 1.6337 timestamp: 1655021712.763856 iteration: 17685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11492 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.18316 L1 loss: 0.0000e+00 L2 loss: 1.19053 Learning rate: 0.02 Mask loss: 0.14162 RPN box loss: 0.05076 RPN score loss: 0.01211 RPN total loss: 0.06287 Total loss: 1.57819 timestamp: 1655021716.0808804 iteration: 17690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18627 FastRCNN class loss: 0.11945 FastRCNN total loss: 0.30572 L1 loss: 0.0000e+00 L2 loss: 1.19029 Learning rate: 0.02 Mask loss: 0.27187 RPN box loss: 0.02506 RPN score loss: 0.01388 RPN total loss: 0.03893 Total loss: 1.80682 timestamp: 1655021719.4773235 iteration: 17695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15147 FastRCNN class loss: 0.08161 FastRCNN total loss: 0.23308 L1 loss: 0.0000e+00 L2 loss: 1.19009 Learning rate: 0.02 Mask loss: 0.16467 RPN box loss: 0.03352 RPN score loss: 0.00971 RPN total loss: 0.04324 Total loss: 1.63108 timestamp: 1655021722.7923112 iteration: 17700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17066 FastRCNN class loss: 0.09125 FastRCNN total loss: 0.26191 L1 loss: 0.0000e+00 L2 loss: 1.18989 Learning rate: 0.02 Mask loss: 0.14898 RPN box loss: 0.03243 RPN score loss: 0.0085 RPN total loss: 0.04092 Total loss: 1.6417 timestamp: 1655021726.1240804 iteration: 17705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20672 FastRCNN class loss: 0.12785 FastRCNN total loss: 0.33458 L1 loss: 0.0000e+00 L2 loss: 1.18969 Learning rate: 0.02 Mask loss: 0.18858 RPN box loss: 0.02573 RPN score loss: 0.01201 RPN total loss: 0.03774 Total loss: 1.75059 timestamp: 1655021729.3839355 iteration: 17710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13839 FastRCNN class loss: 0.11319 FastRCNN total loss: 0.25158 L1 loss: 0.0000e+00 L2 loss: 1.18948 Learning rate: 0.02 Mask loss: 0.29259 RPN box loss: 0.12676 RPN score loss: 0.01919 RPN total loss: 0.14594 Total loss: 1.87959 timestamp: 1655021732.789492 iteration: 17715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19338 FastRCNN class loss: 0.08649 FastRCNN total loss: 0.27987 L1 loss: 0.0000e+00 L2 loss: 1.18928 Learning rate: 0.02 Mask loss: 0.29147 RPN box loss: 0.01696 RPN score loss: 0.00678 RPN total loss: 0.02374 Total loss: 1.78436 timestamp: 1655021736.0220068 iteration: 17720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23358 FastRCNN class loss: 0.13067 FastRCNN total loss: 0.36425 L1 loss: 0.0000e+00 L2 loss: 1.18907 Learning rate: 0.02 Mask loss: 0.19398 RPN box loss: 0.04205 RPN score loss: 0.01247 RPN total loss: 0.05452 Total loss: 1.80182 timestamp: 1655021739.351012 iteration: 17725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10165 FastRCNN class loss: 0.06601 FastRCNN total loss: 0.16766 L1 loss: 0.0000e+00 L2 loss: 1.18887 Learning rate: 0.02 Mask loss: 0.12378 RPN box loss: 0.05847 RPN score loss: 0.00975 RPN total loss: 0.06822 Total loss: 1.54853 timestamp: 1655021742.7434537 iteration: 17730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15567 FastRCNN class loss: 0.09502 FastRCNN total loss: 0.25069 L1 loss: 0.0000e+00 L2 loss: 1.18868 Learning rate: 0.02 Mask loss: 0.20486 RPN box loss: 0.03655 RPN score loss: 0.03088 RPN total loss: 0.06743 Total loss: 1.71165 timestamp: 1655021746.0304973 iteration: 17735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15657 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.21855 L1 loss: 0.0000e+00 L2 loss: 1.18845 Learning rate: 0.02 Mask loss: 0.12416 RPN box loss: 0.03035 RPN score loss: 0.00612 RPN total loss: 0.03647 Total loss: 1.56764 timestamp: 1655021749.4403458 iteration: 17740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20643 FastRCNN class loss: 0.10031 FastRCNN total loss: 0.30674 L1 loss: 0.0000e+00 L2 loss: 1.18823 Learning rate: 0.02 Mask loss: 0.1138 RPN box loss: 0.01533 RPN score loss: 0.00465 RPN total loss: 0.01998 Total loss: 1.62875 timestamp: 1655021752.7129905 iteration: 17745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17444 FastRCNN class loss: 0.08171 FastRCNN total loss: 0.25615 L1 loss: 0.0000e+00 L2 loss: 1.18803 Learning rate: 0.02 Mask loss: 0.16277 RPN box loss: 0.02357 RPN score loss: 0.00835 RPN total loss: 0.03191 Total loss: 1.63887 timestamp: 1655021756.117551 iteration: 17750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.05823 FastRCNN total loss: 0.19557 L1 loss: 0.0000e+00 L2 loss: 1.18784 Learning rate: 0.02 Mask loss: 0.15438 RPN box loss: 0.03795 RPN score loss: 0.00718 RPN total loss: 0.04512 Total loss: 1.58292 timestamp: 1655021759.4678926 iteration: 17755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15539 FastRCNN class loss: 0.09775 FastRCNN total loss: 0.25314 L1 loss: 0.0000e+00 L2 loss: 1.18763 Learning rate: 0.02 Mask loss: 0.17661 RPN box loss: 0.04678 RPN score loss: 0.01031 RPN total loss: 0.0571 Total loss: 1.67448 timestamp: 1655021762.841522 iteration: 17760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.195 FastRCNN class loss: 0.12495 FastRCNN total loss: 0.31995 L1 loss: 0.0000e+00 L2 loss: 1.18742 Learning rate: 0.02 Mask loss: 0.20377 RPN box loss: 0.07271 RPN score loss: 0.01751 RPN total loss: 0.09022 Total loss: 1.80136 timestamp: 1655021766.084692 iteration: 17765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20257 FastRCNN class loss: 0.1024 FastRCNN total loss: 0.30497 L1 loss: 0.0000e+00 L2 loss: 1.18722 Learning rate: 0.02 Mask loss: 0.15827 RPN box loss: 0.01249 RPN score loss: 0.00469 RPN total loss: 0.01717 Total loss: 1.66762 timestamp: 1655021769.5239239 iteration: 17770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1385 FastRCNN class loss: 0.0915 FastRCNN total loss: 0.22999 L1 loss: 0.0000e+00 L2 loss: 1.18702 Learning rate: 0.02 Mask loss: 0.10452 RPN box loss: 0.02969 RPN score loss: 0.00672 RPN total loss: 0.03641 Total loss: 1.55794 timestamp: 1655021772.9219272 iteration: 17775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13966 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.19923 L1 loss: 0.0000e+00 L2 loss: 1.18682 Learning rate: 0.02 Mask loss: 0.14952 RPN box loss: 0.02764 RPN score loss: 0.01184 RPN total loss: 0.03948 Total loss: 1.57505 timestamp: 1655021776.0892973 iteration: 17780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26005 FastRCNN class loss: 0.08567 FastRCNN total loss: 0.34572 L1 loss: 0.0000e+00 L2 loss: 1.18662 Learning rate: 0.02 Mask loss: 0.19177 RPN box loss: 0.01778 RPN score loss: 0.00427 RPN total loss: 0.02205 Total loss: 1.74616 timestamp: 1655021779.4398696 iteration: 17785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14636 FastRCNN class loss: 0.14033 FastRCNN total loss: 0.2867 L1 loss: 0.0000e+00 L2 loss: 1.18638 Learning rate: 0.02 Mask loss: 0.18108 RPN box loss: 0.0357 RPN score loss: 0.01094 RPN total loss: 0.04664 Total loss: 1.7008 timestamp: 1655021782.7586741 iteration: 17790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12523 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 1.18617 Learning rate: 0.02 Mask loss: 0.2002 RPN box loss: 0.02089 RPN score loss: 0.0086 RPN total loss: 0.02949 Total loss: 1.60746 timestamp: 1655021786.163293 iteration: 17795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18755 FastRCNN class loss: 0.1047 FastRCNN total loss: 0.29225 L1 loss: 0.0000e+00 L2 loss: 1.18598 Learning rate: 0.02 Mask loss: 0.15518 RPN box loss: 0.01361 RPN score loss: 0.00431 RPN total loss: 0.01792 Total loss: 1.65134 timestamp: 1655021789.47229 iteration: 17800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10439 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.16006 L1 loss: 0.0000e+00 L2 loss: 1.18578 Learning rate: 0.02 Mask loss: 0.12806 RPN box loss: 0.05106 RPN score loss: 0.01037 RPN total loss: 0.06144 Total loss: 1.53533 timestamp: 1655021792.8324764 iteration: 17805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23187 FastRCNN class loss: 0.08096 FastRCNN total loss: 0.31283 L1 loss: 0.0000e+00 L2 loss: 1.18558 Learning rate: 0.02 Mask loss: 0.15475 RPN box loss: 0.0466 RPN score loss: 0.00333 RPN total loss: 0.04992 Total loss: 1.70308 timestamp: 1655021796.0912743 iteration: 17810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08782 FastRCNN class loss: 0.05206 FastRCNN total loss: 0.13988 L1 loss: 0.0000e+00 L2 loss: 1.18536 Learning rate: 0.02 Mask loss: 0.13405 RPN box loss: 0.04581 RPN score loss: 0.0101 RPN total loss: 0.05591 Total loss: 1.51521 timestamp: 1655021799.4611394 iteration: 17815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14408 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.21918 L1 loss: 0.0000e+00 L2 loss: 1.18515 Learning rate: 0.02 Mask loss: 0.15095 RPN box loss: 0.02405 RPN score loss: 0.00641 RPN total loss: 0.03046 Total loss: 1.58574 timestamp: 1655021802.903151 iteration: 17820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.05971 FastRCNN total loss: 0.18744 L1 loss: 0.0000e+00 L2 loss: 1.18494 Learning rate: 0.02 Mask loss: 0.14348 RPN box loss: 0.01715 RPN score loss: 0.00789 RPN total loss: 0.02503 Total loss: 1.5409 timestamp: 1655021806.1317878 iteration: 17825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17473 FastRCNN class loss: 0.11232 FastRCNN total loss: 0.28705 L1 loss: 0.0000e+00 L2 loss: 1.1847 Learning rate: 0.02 Mask loss: 0.26884 RPN box loss: 0.03415 RPN score loss: 0.00688 RPN total loss: 0.04103 Total loss: 1.78163 timestamp: 1655021809.5407448 iteration: 17830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16184 FastRCNN class loss: 0.06673 FastRCNN total loss: 0.22858 L1 loss: 0.0000e+00 L2 loss: 1.18451 Learning rate: 0.02 Mask loss: 0.16435 RPN box loss: 0.03197 RPN score loss: 0.0062 RPN total loss: 0.03817 Total loss: 1.61561 timestamp: 1655021812.8865216 iteration: 17835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13091 FastRCNN class loss: 0.10173 FastRCNN total loss: 0.23265 L1 loss: 0.0000e+00 L2 loss: 1.18434 Learning rate: 0.02 Mask loss: 0.14845 RPN box loss: 0.02743 RPN score loss: 0.00619 RPN total loss: 0.03362 Total loss: 1.59905 timestamp: 1655021816.2885377 iteration: 17840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15477 FastRCNN class loss: 0.07591 FastRCNN total loss: 0.23068 L1 loss: 0.0000e+00 L2 loss: 1.18415 Learning rate: 0.02 Mask loss: 0.1636 RPN box loss: 0.04144 RPN score loss: 0.00593 RPN total loss: 0.04737 Total loss: 1.62581 timestamp: 1655021819.543644 iteration: 17845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17197 FastRCNN class loss: 0.09984 FastRCNN total loss: 0.27181 L1 loss: 0.0000e+00 L2 loss: 1.18395 Learning rate: 0.02 Mask loss: 0.12916 RPN box loss: 0.01846 RPN score loss: 0.0031 RPN total loss: 0.02156 Total loss: 1.60648 timestamp: 1655021822.935586 iteration: 17850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17742 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.27011 L1 loss: 0.0000e+00 L2 loss: 1.18374 Learning rate: 0.02 Mask loss: 0.162 RPN box loss: 0.07276 RPN score loss: 0.0138 RPN total loss: 0.08656 Total loss: 1.7024 timestamp: 1655021826.2023656 iteration: 17855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22443 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.28986 L1 loss: 0.0000e+00 L2 loss: 1.1835 Learning rate: 0.02 Mask loss: 0.14739 RPN box loss: 0.02014 RPN score loss: 0.00742 RPN total loss: 0.02756 Total loss: 1.64831 timestamp: 1655021829.5868876 iteration: 17860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13225 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.20267 L1 loss: 0.0000e+00 L2 loss: 1.18331 Learning rate: 0.02 Mask loss: 0.15004 RPN box loss: 0.01261 RPN score loss: 0.00782 RPN total loss: 0.02043 Total loss: 1.55645 timestamp: 1655021833.0135872 iteration: 17865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.11657 FastRCNN total loss: 0.27301 L1 loss: 0.0000e+00 L2 loss: 1.18314 Learning rate: 0.02 Mask loss: 0.16126 RPN box loss: 0.05522 RPN score loss: 0.01287 RPN total loss: 0.06808 Total loss: 1.68549 timestamp: 1655021836.3533816 iteration: 17870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10753 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.18411 L1 loss: 0.0000e+00 L2 loss: 1.18294 Learning rate: 0.02 Mask loss: 0.19625 RPN box loss: 0.02667 RPN score loss: 0.00421 RPN total loss: 0.03089 Total loss: 1.59418 timestamp: 1655021839.6750221 iteration: 17875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17637 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.25063 L1 loss: 0.0000e+00 L2 loss: 1.18274 Learning rate: 0.02 Mask loss: 0.15914 RPN box loss: 0.03788 RPN score loss: 0.00407 RPN total loss: 0.04195 Total loss: 1.63447 timestamp: 1655021843.0225894 iteration: 17880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11394 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.17135 L1 loss: 0.0000e+00 L2 loss: 1.18254 Learning rate: 0.02 Mask loss: 0.18413 RPN box loss: 0.02357 RPN score loss: 0.00595 RPN total loss: 0.02952 Total loss: 1.56753 timestamp: 1655021846.374086 iteration: 17885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13923 FastRCNN class loss: 0.08942 FastRCNN total loss: 0.22865 L1 loss: 0.0000e+00 L2 loss: 1.18233 Learning rate: 0.02 Mask loss: 0.24973 RPN box loss: 0.02939 RPN score loss: 0.00576 RPN total loss: 0.03514 Total loss: 1.69585 timestamp: 1655021849.6142788 iteration: 17890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14425 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.22188 L1 loss: 0.0000e+00 L2 loss: 1.18214 Learning rate: 0.02 Mask loss: 0.19929 RPN box loss: 0.03018 RPN score loss: 0.00616 RPN total loss: 0.03634 Total loss: 1.63965 timestamp: 1655021852.9730217 iteration: 17895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.07981 FastRCNN total loss: 0.208 L1 loss: 0.0000e+00 L2 loss: 1.18194 Learning rate: 0.02 Mask loss: 0.14013 RPN box loss: 0.07469 RPN score loss: 0.00779 RPN total loss: 0.08248 Total loss: 1.61254 timestamp: 1655021856.2152765 iteration: 17900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08439 FastRCNN class loss: 0.09909 FastRCNN total loss: 0.18348 L1 loss: 0.0000e+00 L2 loss: 1.18174 Learning rate: 0.02 Mask loss: 0.23395 RPN box loss: 0.00676 RPN score loss: 0.00214 RPN total loss: 0.00891 Total loss: 1.60808 timestamp: 1655021859.6195097 iteration: 17905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16901 FastRCNN class loss: 0.14051 FastRCNN total loss: 0.30952 L1 loss: 0.0000e+00 L2 loss: 1.18152 Learning rate: 0.02 Mask loss: 0.15481 RPN box loss: 0.04655 RPN score loss: 0.01082 RPN total loss: 0.05738 Total loss: 1.70322 timestamp: 1655021862.9244096 iteration: 17910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11828 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.17098 L1 loss: 0.0000e+00 L2 loss: 1.18133 Learning rate: 0.02 Mask loss: 0.11905 RPN box loss: 0.0255 RPN score loss: 0.00185 RPN total loss: 0.02735 Total loss: 1.49871 timestamp: 1655021866.1401477 iteration: 17915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20095 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.28014 L1 loss: 0.0000e+00 L2 loss: 1.18113 Learning rate: 0.02 Mask loss: 0.15488 RPN box loss: 0.03455 RPN score loss: 0.00377 RPN total loss: 0.03832 Total loss: 1.65447 timestamp: 1655021869.5284784 iteration: 17920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18511 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.25038 L1 loss: 0.0000e+00 L2 loss: 1.18093 Learning rate: 0.02 Mask loss: 0.13981 RPN box loss: 0.0181 RPN score loss: 0.00504 RPN total loss: 0.02314 Total loss: 1.59427 timestamp: 1655021872.76806 iteration: 17925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13332 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.2075 L1 loss: 0.0000e+00 L2 loss: 1.18073 Learning rate: 0.02 Mask loss: 0.16439 RPN box loss: 0.02005 RPN score loss: 0.00364 RPN total loss: 0.02369 Total loss: 1.5763 timestamp: 1655021876.1917582 iteration: 17930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17844 FastRCNN class loss: 0.08571 FastRCNN total loss: 0.26415 L1 loss: 0.0000e+00 L2 loss: 1.18051 Learning rate: 0.02 Mask loss: 0.22913 RPN box loss: 0.02993 RPN score loss: 0.00239 RPN total loss: 0.03232 Total loss: 1.70611 timestamp: 1655021879.422402 iteration: 17935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13291 FastRCNN class loss: 0.09356 FastRCNN total loss: 0.22647 L1 loss: 0.0000e+00 L2 loss: 1.18028 Learning rate: 0.02 Mask loss: 0.17287 RPN box loss: 0.02019 RPN score loss: 0.00501 RPN total loss: 0.0252 Total loss: 1.60482 timestamp: 1655021882.8540206 iteration: 17940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16249 FastRCNN class loss: 0.08793 FastRCNN total loss: 0.25042 L1 loss: 0.0000e+00 L2 loss: 1.1801 Learning rate: 0.02 Mask loss: 0.18588 RPN box loss: 0.00836 RPN score loss: 0.00411 RPN total loss: 0.01247 Total loss: 1.62886 timestamp: 1655021886.1934302 iteration: 17945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1607 FastRCNN class loss: 0.07649 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 1.17989 Learning rate: 0.02 Mask loss: 0.13627 RPN box loss: 0.0238 RPN score loss: 0.00496 RPN total loss: 0.02876 Total loss: 1.58209 timestamp: 1655021889.6119068 iteration: 17950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10012 FastRCNN class loss: 0.04971 FastRCNN total loss: 0.14984 L1 loss: 0.0000e+00 L2 loss: 1.17969 Learning rate: 0.02 Mask loss: 0.13214 RPN box loss: 0.0236 RPN score loss: 0.00446 RPN total loss: 0.02807 Total loss: 1.48974 timestamp: 1655021892.8803701 iteration: 17955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.182 FastRCNN class loss: 0.10433 FastRCNN total loss: 0.28633 L1 loss: 0.0000e+00 L2 loss: 1.17952 Learning rate: 0.02 Mask loss: 0.17217 RPN box loss: 0.04212 RPN score loss: 0.0112 RPN total loss: 0.05332 Total loss: 1.69134 timestamp: 1655021896.1648834 iteration: 17960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19694 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.25881 L1 loss: 0.0000e+00 L2 loss: 1.17932 Learning rate: 0.02 Mask loss: 0.17109 RPN box loss: 0.18097 RPN score loss: 0.00917 RPN total loss: 0.19014 Total loss: 1.79936 timestamp: 1655021899.4832504 iteration: 17965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.18546 L1 loss: 0.0000e+00 L2 loss: 1.17913 Learning rate: 0.02 Mask loss: 0.10603 RPN box loss: 0.02769 RPN score loss: 0.00466 RPN total loss: 0.03236 Total loss: 1.50297 timestamp: 1655021902.709726 iteration: 17970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13552 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.19725 L1 loss: 0.0000e+00 L2 loss: 1.17892 Learning rate: 0.02 Mask loss: 0.16591 RPN box loss: 0.04865 RPN score loss: 0.00253 RPN total loss: 0.05118 Total loss: 1.59326 timestamp: 1655021906.1472545 iteration: 17975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18447 FastRCNN class loss: 0.09712 FastRCNN total loss: 0.28159 L1 loss: 0.0000e+00 L2 loss: 1.17872 Learning rate: 0.02 Mask loss: 0.18286 RPN box loss: 0.05605 RPN score loss: 0.01613 RPN total loss: 0.07218 Total loss: 1.71534 timestamp: 1655021909.447613 iteration: 17980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12086 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.1926 L1 loss: 0.0000e+00 L2 loss: 1.1785 Learning rate: 0.02 Mask loss: 0.14869 RPN box loss: 0.01692 RPN score loss: 0.00682 RPN total loss: 0.02374 Total loss: 1.54354 timestamp: 1655021912.8442354 iteration: 17985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18811 FastRCNN class loss: 0.08999 FastRCNN total loss: 0.27811 L1 loss: 0.0000e+00 L2 loss: 1.17828 Learning rate: 0.02 Mask loss: 0.17455 RPN box loss: 0.01208 RPN score loss: 0.009 RPN total loss: 0.02108 Total loss: 1.65202 timestamp: 1655021916.129142 iteration: 17990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14898 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.22028 L1 loss: 0.0000e+00 L2 loss: 1.17807 Learning rate: 0.02 Mask loss: 0.12359 RPN box loss: 0.04716 RPN score loss: 0.01158 RPN total loss: 0.05873 Total loss: 1.58066 timestamp: 1655021919.4955556 iteration: 17995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12751 FastRCNN class loss: 0.07719 FastRCNN total loss: 0.2047 L1 loss: 0.0000e+00 L2 loss: 1.17789 Learning rate: 0.02 Mask loss: 0.16885 RPN box loss: 0.04233 RPN score loss: 0.01283 RPN total loss: 0.05516 Total loss: 1.6066 timestamp: 1655021922.901658 iteration: 18000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10053 FastRCNN class loss: 0.0512 FastRCNN total loss: 0.15173 L1 loss: 0.0000e+00 L2 loss: 1.17769 Learning rate: 0.02 Mask loss: 0.16072 RPN box loss: 0.03232 RPN score loss: 0.00726 RPN total loss: 0.03958 Total loss: 1.52972 timestamp: 1655021926.132144 iteration: 18005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16631 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.24128 L1 loss: 0.0000e+00 L2 loss: 1.1775 Learning rate: 0.02 Mask loss: 0.11822 RPN box loss: 0.02504 RPN score loss: 0.00401 RPN total loss: 0.02905 Total loss: 1.56605 timestamp: 1655021929.4735038 iteration: 18010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13712 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.21614 L1 loss: 0.0000e+00 L2 loss: 1.1773 Learning rate: 0.02 Mask loss: 0.17095 RPN box loss: 0.11028 RPN score loss: 0.00503 RPN total loss: 0.11531 Total loss: 1.67971 timestamp: 1655021932.6981602 iteration: 18015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13495 FastRCNN class loss: 0.10948 FastRCNN total loss: 0.24443 L1 loss: 0.0000e+00 L2 loss: 1.17709 Learning rate: 0.02 Mask loss: 0.15435 RPN box loss: 0.04689 RPN score loss: 0.00508 RPN total loss: 0.05198 Total loss: 1.62785 timestamp: 1655021936.0144022 iteration: 18020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12551 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 1.1769 Learning rate: 0.02 Mask loss: 0.19047 RPN box loss: 0.07121 RPN score loss: 0.00363 RPN total loss: 0.07484 Total loss: 1.63342 timestamp: 1655021939.2995222 iteration: 18025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21138 FastRCNN class loss: 0.09266 FastRCNN total loss: 0.30404 L1 loss: 0.0000e+00 L2 loss: 1.17668 Learning rate: 0.02 Mask loss: 0.28917 RPN box loss: 0.07945 RPN score loss: 0.01137 RPN total loss: 0.09082 Total loss: 1.86071 timestamp: 1655021942.6433225 iteration: 18030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25904 FastRCNN class loss: 0.10695 FastRCNN total loss: 0.366 L1 loss: 0.0000e+00 L2 loss: 1.17649 Learning rate: 0.02 Mask loss: 0.14681 RPN box loss: 0.01865 RPN score loss: 0.01658 RPN total loss: 0.03523 Total loss: 1.72453 timestamp: 1655021945.9303162 iteration: 18035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11754 FastRCNN class loss: 0.11286 FastRCNN total loss: 0.2304 L1 loss: 0.0000e+00 L2 loss: 1.17631 Learning rate: 0.02 Mask loss: 0.1986 RPN box loss: 0.05245 RPN score loss: 0.01843 RPN total loss: 0.07089 Total loss: 1.6762 timestamp: 1655021949.3813694 iteration: 18040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12639 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.19976 L1 loss: 0.0000e+00 L2 loss: 1.17611 Learning rate: 0.02 Mask loss: 0.10967 RPN box loss: 0.00711 RPN score loss: 0.00537 RPN total loss: 0.01248 Total loss: 1.49802 timestamp: 1655021952.7708592 iteration: 18045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22659 FastRCNN class loss: 0.12171 FastRCNN total loss: 0.3483 L1 loss: 0.0000e+00 L2 loss: 1.17588 Learning rate: 0.02 Mask loss: 0.19806 RPN box loss: 0.02016 RPN score loss: 0.01199 RPN total loss: 0.03215 Total loss: 1.75438 timestamp: 1655021956.0027628 iteration: 18050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09175 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.15303 L1 loss: 0.0000e+00 L2 loss: 1.17568 Learning rate: 0.02 Mask loss: 0.14863 RPN box loss: 0.0121 RPN score loss: 0.00274 RPN total loss: 0.01483 Total loss: 1.49217 timestamp: 1655021959.360335 iteration: 18055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1684 FastRCNN class loss: 0.08256 FastRCNN total loss: 0.25096 L1 loss: 0.0000e+00 L2 loss: 1.17549 Learning rate: 0.02 Mask loss: 0.21143 RPN box loss: 0.03094 RPN score loss: 0.00323 RPN total loss: 0.03417 Total loss: 1.67205 timestamp: 1655021962.6789877 iteration: 18060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.0943 FastRCNN total loss: 0.18613 L1 loss: 0.0000e+00 L2 loss: 1.17529 Learning rate: 0.02 Mask loss: 0.10541 RPN box loss: 0.01029 RPN score loss: 0.00218 RPN total loss: 0.01248 Total loss: 1.47931 timestamp: 1655021966.1210184 iteration: 18065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25172 FastRCNN class loss: 0.14222 FastRCNN total loss: 0.39394 L1 loss: 0.0000e+00 L2 loss: 1.17506 Learning rate: 0.02 Mask loss: 0.18331 RPN box loss: 0.07119 RPN score loss: 0.01323 RPN total loss: 0.08442 Total loss: 1.83673 timestamp: 1655021969.4317558 iteration: 18070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.09593 FastRCNN total loss: 0.21823 L1 loss: 0.0000e+00 L2 loss: 1.17485 Learning rate: 0.02 Mask loss: 0.22145 RPN box loss: 0.04216 RPN score loss: 0.00664 RPN total loss: 0.0488 Total loss: 1.66334 timestamp: 1655021972.8136618 iteration: 18075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15759 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.26183 L1 loss: 0.0000e+00 L2 loss: 1.17464 Learning rate: 0.02 Mask loss: 0.19915 RPN box loss: 0.02373 RPN score loss: 0.00555 RPN total loss: 0.02928 Total loss: 1.6649 timestamp: 1655021976.2427974 iteration: 18080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22137 FastRCNN class loss: 0.10687 FastRCNN total loss: 0.32824 L1 loss: 0.0000e+00 L2 loss: 1.17445 Learning rate: 0.02 Mask loss: 0.21872 RPN box loss: 0.03426 RPN score loss: 0.01006 RPN total loss: 0.04432 Total loss: 1.76573 timestamp: 1655021979.5492744 iteration: 18085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11573 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.18338 L1 loss: 0.0000e+00 L2 loss: 1.17427 Learning rate: 0.02 Mask loss: 0.38691 RPN box loss: 0.02382 RPN score loss: 0.00314 RPN total loss: 0.02695 Total loss: 1.77151 timestamp: 1655021982.7844324 iteration: 18090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13139 FastRCNN class loss: 0.0594 FastRCNN total loss: 0.19079 L1 loss: 0.0000e+00 L2 loss: 1.17408 Learning rate: 0.02 Mask loss: 0.12788 RPN box loss: 0.02585 RPN score loss: 0.00407 RPN total loss: 0.02993 Total loss: 1.52268 timestamp: 1655021986.0970464 iteration: 18095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12149 FastRCNN class loss: 0.099 FastRCNN total loss: 0.22049 L1 loss: 0.0000e+00 L2 loss: 1.17386 Learning rate: 0.02 Mask loss: 0.1298 RPN box loss: 0.05047 RPN score loss: 0.01056 RPN total loss: 0.06103 Total loss: 1.58518 timestamp: 1655021989.4450617 iteration: 18100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12657 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.17848 L1 loss: 0.0000e+00 L2 loss: 1.17366 Learning rate: 0.02 Mask loss: 0.16198 RPN box loss: 0.04745 RPN score loss: 0.0052 RPN total loss: 0.05265 Total loss: 1.56676 timestamp: 1655021992.6619103 iteration: 18105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13721 FastRCNN class loss: 0.11213 FastRCNN total loss: 0.24935 L1 loss: 0.0000e+00 L2 loss: 1.17345 Learning rate: 0.02 Mask loss: 0.24652 RPN box loss: 0.08835 RPN score loss: 0.02723 RPN total loss: 0.11557 Total loss: 1.78488 timestamp: 1655021996.0065563 iteration: 18110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.2002 L1 loss: 0.0000e+00 L2 loss: 1.17324 Learning rate: 0.02 Mask loss: 0.16447 RPN box loss: 0.03025 RPN score loss: 0.00655 RPN total loss: 0.03679 Total loss: 1.57471 timestamp: 1655021999.2868984 iteration: 18115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13077 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.20324 L1 loss: 0.0000e+00 L2 loss: 1.17305 Learning rate: 0.02 Mask loss: 0.15322 RPN box loss: 0.03633 RPN score loss: 0.00662 RPN total loss: 0.04295 Total loss: 1.57246 timestamp: 1655022002.6081514 iteration: 18120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1602 FastRCNN class loss: 0.08745 FastRCNN total loss: 0.24765 L1 loss: 0.0000e+00 L2 loss: 1.17285 Learning rate: 0.02 Mask loss: 0.17325 RPN box loss: 0.03887 RPN score loss: 0.00558 RPN total loss: 0.04446 Total loss: 1.63821 timestamp: 1655022006.0009265 iteration: 18125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19601 FastRCNN class loss: 0.17555 FastRCNN total loss: 0.37156 L1 loss: 0.0000e+00 L2 loss: 1.17267 Learning rate: 0.02 Mask loss: 0.21613 RPN box loss: 0.05326 RPN score loss: 0.04372 RPN total loss: 0.09697 Total loss: 1.85734 timestamp: 1655022009.2701924 iteration: 18130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16807 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.22722 L1 loss: 0.0000e+00 L2 loss: 1.17246 Learning rate: 0.02 Mask loss: 0.10484 RPN box loss: 0.0302 RPN score loss: 0.00463 RPN total loss: 0.03484 Total loss: 1.53935 timestamp: 1655022012.6826687 iteration: 18135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14312 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.20369 L1 loss: 0.0000e+00 L2 loss: 1.17223 Learning rate: 0.02 Mask loss: 0.18424 RPN box loss: 0.03247 RPN score loss: 0.00513 RPN total loss: 0.03761 Total loss: 1.59777 timestamp: 1655022015.9978306 iteration: 18140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08169 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.14138 L1 loss: 0.0000e+00 L2 loss: 1.17203 Learning rate: 0.02 Mask loss: 0.09667 RPN box loss: 0.04717 RPN score loss: 0.01118 RPN total loss: 0.05834 Total loss: 1.46842 timestamp: 1655022019.293014 iteration: 18145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14173 FastRCNN class loss: 0.08444 FastRCNN total loss: 0.22617 L1 loss: 0.0000e+00 L2 loss: 1.17183 Learning rate: 0.02 Mask loss: 0.33567 RPN box loss: 0.0461 RPN score loss: 0.01052 RPN total loss: 0.05662 Total loss: 1.79029 timestamp: 1655022022.6497633 iteration: 18150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19767 FastRCNN class loss: 0.19126 FastRCNN total loss: 0.38894 L1 loss: 0.0000e+00 L2 loss: 1.17164 Learning rate: 0.02 Mask loss: 0.18886 RPN box loss: 0.03443 RPN score loss: 0.02389 RPN total loss: 0.05832 Total loss: 1.80775 timestamp: 1655022025.9617019 iteration: 18155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12308 FastRCNN class loss: 0.04559 FastRCNN total loss: 0.16866 L1 loss: 0.0000e+00 L2 loss: 1.17146 Learning rate: 0.02 Mask loss: 0.15677 RPN box loss: 0.06368 RPN score loss: 0.00758 RPN total loss: 0.07126 Total loss: 1.56815 timestamp: 1655022029.2023988 iteration: 18160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21839 FastRCNN class loss: 0.13254 FastRCNN total loss: 0.35093 L1 loss: 0.0000e+00 L2 loss: 1.17126 Learning rate: 0.02 Mask loss: 0.16035 RPN box loss: 0.03332 RPN score loss: 0.01457 RPN total loss: 0.04789 Total loss: 1.73043 timestamp: 1655022032.591262 iteration: 18165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13657 FastRCNN class loss: 0.06632 FastRCNN total loss: 0.20289 L1 loss: 0.0000e+00 L2 loss: 1.17105 Learning rate: 0.02 Mask loss: 0.20175 RPN box loss: 0.03449 RPN score loss: 0.00695 RPN total loss: 0.04145 Total loss: 1.61713 timestamp: 1655022035.9821053 iteration: 18170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21398 FastRCNN class loss: 0.10264 FastRCNN total loss: 0.31661 L1 loss: 0.0000e+00 L2 loss: 1.17083 Learning rate: 0.02 Mask loss: 0.21484 RPN box loss: 0.03745 RPN score loss: 0.02102 RPN total loss: 0.05847 Total loss: 1.76075 timestamp: 1655022039.2773588 iteration: 18175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17546 FastRCNN class loss: 0.11553 FastRCNN total loss: 0.29099 L1 loss: 0.0000e+00 L2 loss: 1.17063 Learning rate: 0.02 Mask loss: 0.185 RPN box loss: 0.01349 RPN score loss: 0.004 RPN total loss: 0.01749 Total loss: 1.66411 timestamp: 1655022042.6386814 iteration: 18180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16813 FastRCNN class loss: 0.15448 FastRCNN total loss: 0.32261 L1 loss: 0.0000e+00 L2 loss: 1.17045 Learning rate: 0.02 Mask loss: 0.20153 RPN box loss: 0.02077 RPN score loss: 0.01731 RPN total loss: 0.03808 Total loss: 1.73266 timestamp: 1655022045.9307632 iteration: 18185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1765 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.25197 L1 loss: 0.0000e+00 L2 loss: 1.17023 Learning rate: 0.02 Mask loss: 0.16528 RPN box loss: 0.01432 RPN score loss: 0.00567 RPN total loss: 0.02 Total loss: 1.60747 timestamp: 1655022049.2911675 iteration: 18190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15768 FastRCNN class loss: 0.13126 FastRCNN total loss: 0.28894 L1 loss: 0.0000e+00 L2 loss: 1.17002 Learning rate: 0.02 Mask loss: 0.16292 RPN box loss: 0.02583 RPN score loss: 0.00242 RPN total loss: 0.02825 Total loss: 1.65013 timestamp: 1655022052.4910855 iteration: 18195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08945 FastRCNN class loss: 0.04099 FastRCNN total loss: 0.13044 L1 loss: 0.0000e+00 L2 loss: 1.16983 Learning rate: 0.02 Mask loss: 0.13097 RPN box loss: 0.026 RPN score loss: 0.00743 RPN total loss: 0.03343 Total loss: 1.46466 timestamp: 1655022055.8138447 iteration: 18200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11234 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.19272 L1 loss: 0.0000e+00 L2 loss: 1.16962 Learning rate: 0.02 Mask loss: 0.14129 RPN box loss: 0.03263 RPN score loss: 0.01637 RPN total loss: 0.049 Total loss: 1.55263 timestamp: 1655022059.0527277 iteration: 18205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13721 FastRCNN class loss: 0.09828 FastRCNN total loss: 0.23549 L1 loss: 0.0000e+00 L2 loss: 1.16942 Learning rate: 0.02 Mask loss: 0.16079 RPN box loss: 0.09198 RPN score loss: 0.01013 RPN total loss: 0.10212 Total loss: 1.66782 timestamp: 1655022062.4630303 iteration: 18210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22562 FastRCNN class loss: 0.07824 FastRCNN total loss: 0.30386 L1 loss: 0.0000e+00 L2 loss: 1.16922 Learning rate: 0.02 Mask loss: 0.16489 RPN box loss: 0.05651 RPN score loss: 0.0085 RPN total loss: 0.06501 Total loss: 1.70297 timestamp: 1655022065.773466 iteration: 18215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10488 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.1512 L1 loss: 0.0000e+00 L2 loss: 1.16901 Learning rate: 0.02 Mask loss: 0.09254 RPN box loss: 0.0494 RPN score loss: 0.00829 RPN total loss: 0.05769 Total loss: 1.47044 timestamp: 1655022069.0086968 iteration: 18220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17382 FastRCNN class loss: 0.08355 FastRCNN total loss: 0.25737 L1 loss: 0.0000e+00 L2 loss: 1.16884 Learning rate: 0.02 Mask loss: 0.19825 RPN box loss: 0.02397 RPN score loss: 0.00422 RPN total loss: 0.02819 Total loss: 1.65264 timestamp: 1655022072.356236 iteration: 18225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10337 FastRCNN class loss: 0.07103 FastRCNN total loss: 0.1744 L1 loss: 0.0000e+00 L2 loss: 1.16864 Learning rate: 0.02 Mask loss: 0.15363 RPN box loss: 0.03252 RPN score loss: 0.00381 RPN total loss: 0.03632 Total loss: 1.53299 timestamp: 1655022075.6777625 iteration: 18230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12674 FastRCNN class loss: 0.08995 FastRCNN total loss: 0.2167 L1 loss: 0.0000e+00 L2 loss: 1.16843 Learning rate: 0.02 Mask loss: 0.1868 RPN box loss: 0.02792 RPN score loss: 0.00618 RPN total loss: 0.0341 Total loss: 1.60602 timestamp: 1655022079.015737 iteration: 18235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13151 FastRCNN class loss: 0.07396 FastRCNN total loss: 0.20547 L1 loss: 0.0000e+00 L2 loss: 1.16824 Learning rate: 0.02 Mask loss: 0.17368 RPN box loss: 0.03345 RPN score loss: 0.00246 RPN total loss: 0.03591 Total loss: 1.5833 timestamp: 1655022082.34825 iteration: 18240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21706 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.30105 L1 loss: 0.0000e+00 L2 loss: 1.16803 Learning rate: 0.02 Mask loss: 0.23027 RPN box loss: 0.03141 RPN score loss: 0.00721 RPN total loss: 0.03862 Total loss: 1.73796 timestamp: 1655022085.704875 iteration: 18245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08689 FastRCNN class loss: 0.0741 FastRCNN total loss: 0.16099 L1 loss: 0.0000e+00 L2 loss: 1.1678 Learning rate: 0.02 Mask loss: 0.16423 RPN box loss: 0.00977 RPN score loss: 0.00763 RPN total loss: 0.0174 Total loss: 1.51042 timestamp: 1655022088.920529 iteration: 18250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23432 FastRCNN class loss: 0.14826 FastRCNN total loss: 0.38258 L1 loss: 0.0000e+00 L2 loss: 1.1676 Learning rate: 0.02 Mask loss: 0.22798 RPN box loss: 0.04022 RPN score loss: 0.01904 RPN total loss: 0.05926 Total loss: 1.83742 timestamp: 1655022092.331174 iteration: 18255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15793 FastRCNN class loss: 0.05259 FastRCNN total loss: 0.21051 L1 loss: 0.0000e+00 L2 loss: 1.1674 Learning rate: 0.02 Mask loss: 0.18569 RPN box loss: 0.02835 RPN score loss: 0.01099 RPN total loss: 0.03934 Total loss: 1.60294 timestamp: 1655022095.720278 iteration: 18260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17806 FastRCNN class loss: 0.10214 FastRCNN total loss: 0.2802 L1 loss: 0.0000e+00 L2 loss: 1.16717 Learning rate: 0.02 Mask loss: 0.14899 RPN box loss: 0.02652 RPN score loss: 0.00502 RPN total loss: 0.03154 Total loss: 1.62789 timestamp: 1655022099.0696604 iteration: 18265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17058 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.24371 L1 loss: 0.0000e+00 L2 loss: 1.16698 Learning rate: 0.02 Mask loss: 0.20664 RPN box loss: 0.01908 RPN score loss: 0.00813 RPN total loss: 0.02721 Total loss: 1.64453 timestamp: 1655022102.3903084 iteration: 18270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23483 FastRCNN class loss: 0.13118 FastRCNN total loss: 0.36602 L1 loss: 0.0000e+00 L2 loss: 1.16677 Learning rate: 0.02 Mask loss: 0.29567 RPN box loss: 0.0252 RPN score loss: 0.00847 RPN total loss: 0.03367 Total loss: 1.86213 timestamp: 1655022105.6845372 iteration: 18275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18308 FastRCNN class loss: 0.13282 FastRCNN total loss: 0.3159 L1 loss: 0.0000e+00 L2 loss: 1.16657 Learning rate: 0.02 Mask loss: 0.21051 RPN box loss: 0.05486 RPN score loss: 0.00433 RPN total loss: 0.05918 Total loss: 1.75216 timestamp: 1655022109.0577939 iteration: 18280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20212 FastRCNN class loss: 0.10408 FastRCNN total loss: 0.3062 L1 loss: 0.0000e+00 L2 loss: 1.16636 Learning rate: 0.02 Mask loss: 0.34686 RPN box loss: 0.01647 RPN score loss: 0.00579 RPN total loss: 0.02226 Total loss: 1.84169 timestamp: 1655022112.3623042 iteration: 18285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18829 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.26102 L1 loss: 0.0000e+00 L2 loss: 1.16615 Learning rate: 0.02 Mask loss: 0.17332 RPN box loss: 0.01743 RPN score loss: 0.0047 RPN total loss: 0.02213 Total loss: 1.62262 timestamp: 1655022115.6684396 iteration: 18290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18665 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.28036 L1 loss: 0.0000e+00 L2 loss: 1.16596 Learning rate: 0.02 Mask loss: 0.21279 RPN box loss: 0.03011 RPN score loss: 0.00783 RPN total loss: 0.03794 Total loss: 1.69705 timestamp: 1655022118.9448218 iteration: 18295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16647 FastRCNN class loss: 0.15889 FastRCNN total loss: 0.32535 L1 loss: 0.0000e+00 L2 loss: 1.16576 Learning rate: 0.02 Mask loss: 0.21812 RPN box loss: 0.04787 RPN score loss: 0.00953 RPN total loss: 0.0574 Total loss: 1.76664 timestamp: 1655022122.2917385 iteration: 18300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15951 FastRCNN class loss: 0.19399 FastRCNN total loss: 0.3535 L1 loss: 0.0000e+00 L2 loss: 1.16555 Learning rate: 0.02 Mask loss: 0.23232 RPN box loss: 0.06203 RPN score loss: 0.01632 RPN total loss: 0.07836 Total loss: 1.82973 timestamp: 1655022125.6246955 iteration: 18305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20229 FastRCNN class loss: 0.07797 FastRCNN total loss: 0.28026 L1 loss: 0.0000e+00 L2 loss: 1.16537 Learning rate: 0.02 Mask loss: 0.13145 RPN box loss: 0.05733 RPN score loss: 0.00508 RPN total loss: 0.0624 Total loss: 1.63948 timestamp: 1655022128.9852452 iteration: 18310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23578 FastRCNN class loss: 0.16559 FastRCNN total loss: 0.40137 L1 loss: 0.0000e+00 L2 loss: 1.16518 Learning rate: 0.02 Mask loss: 0.25216 RPN box loss: 0.06278 RPN score loss: 0.02819 RPN total loss: 0.09097 Total loss: 1.90968 timestamp: 1655022132.2912724 iteration: 18315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21403 FastRCNN class loss: 0.19399 FastRCNN total loss: 0.40802 L1 loss: 0.0000e+00 L2 loss: 1.16499 Learning rate: 0.02 Mask loss: 0.19597 RPN box loss: 0.04838 RPN score loss: 0.01683 RPN total loss: 0.06521 Total loss: 1.83419 timestamp: 1655022135.5008838 iteration: 18320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14778 FastRCNN class loss: 0.12213 FastRCNN total loss: 0.26991 L1 loss: 0.0000e+00 L2 loss: 1.16477 Learning rate: 0.02 Mask loss: 0.15891 RPN box loss: 0.02742 RPN score loss: 0.00609 RPN total loss: 0.03351 Total loss: 1.62709 timestamp: 1655022138.9626524 iteration: 18325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.2486 L1 loss: 0.0000e+00 L2 loss: 1.16457 Learning rate: 0.02 Mask loss: 0.12483 RPN box loss: 0.01104 RPN score loss: 0.00365 RPN total loss: 0.01468 Total loss: 1.55269 timestamp: 1655022142.2457986 iteration: 18330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12218 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.20443 L1 loss: 0.0000e+00 L2 loss: 1.1644 Learning rate: 0.02 Mask loss: 0.15502 RPN box loss: 0.00879 RPN score loss: 0.00326 RPN total loss: 0.01205 Total loss: 1.5359 timestamp: 1655022145.6993985 iteration: 18335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12121 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.20236 L1 loss: 0.0000e+00 L2 loss: 1.16418 Learning rate: 0.02 Mask loss: 0.1654 RPN box loss: 0.05754 RPN score loss: 0.00993 RPN total loss: 0.06746 Total loss: 1.5994 timestamp: 1655022149.0367475 iteration: 18340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14574 FastRCNN class loss: 0.1167 FastRCNN total loss: 0.26244 L1 loss: 0.0000e+00 L2 loss: 1.16397 Learning rate: 0.02 Mask loss: 0.1811 RPN box loss: 0.03038 RPN score loss: 0.00607 RPN total loss: 0.03646 Total loss: 1.64397 timestamp: 1655022152.4326265 iteration: 18345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13378 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.219 L1 loss: 0.0000e+00 L2 loss: 1.16379 Learning rate: 0.02 Mask loss: 0.18308 RPN box loss: 0.05159 RPN score loss: 0.00668 RPN total loss: 0.05827 Total loss: 1.62415 timestamp: 1655022155.8995786 iteration: 18350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17617 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.26015 L1 loss: 0.0000e+00 L2 loss: 1.16361 Learning rate: 0.02 Mask loss: 0.22276 RPN box loss: 0.04426 RPN score loss: 0.00711 RPN total loss: 0.05137 Total loss: 1.6979 timestamp: 1655022159.164335 iteration: 18355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22893 FastRCNN class loss: 0.09336 FastRCNN total loss: 0.32229 L1 loss: 0.0000e+00 L2 loss: 1.16341 Learning rate: 0.02 Mask loss: 0.17399 RPN box loss: 0.04448 RPN score loss: 0.00715 RPN total loss: 0.05162 Total loss: 1.71132 timestamp: 1655022162.589186 iteration: 18360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15572 FastRCNN class loss: 0.11158 FastRCNN total loss: 0.2673 L1 loss: 0.0000e+00 L2 loss: 1.1632 Learning rate: 0.02 Mask loss: 0.154 RPN box loss: 0.01423 RPN score loss: 0.00307 RPN total loss: 0.0173 Total loss: 1.6018 timestamp: 1655022165.8607695 iteration: 18365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10749 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.16898 L1 loss: 0.0000e+00 L2 loss: 1.16299 Learning rate: 0.02 Mask loss: 0.15783 RPN box loss: 0.01822 RPN score loss: 0.00336 RPN total loss: 0.02159 Total loss: 1.51139 timestamp: 1655022169.2717347 iteration: 18370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1857 FastRCNN class loss: 0.13788 FastRCNN total loss: 0.32359 L1 loss: 0.0000e+00 L2 loss: 1.16278 Learning rate: 0.02 Mask loss: 0.14658 RPN box loss: 0.01715 RPN score loss: 0.00354 RPN total loss: 0.02068 Total loss: 1.65363 timestamp: 1655022172.5641987 iteration: 18375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14374 FastRCNN class loss: 0.05435 FastRCNN total loss: 0.19809 L1 loss: 0.0000e+00 L2 loss: 1.16259 Learning rate: 0.02 Mask loss: 0.17245 RPN box loss: 0.00709 RPN score loss: 0.00362 RPN total loss: 0.01071 Total loss: 1.54383 timestamp: 1655022175.8903718 iteration: 18380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15891 FastRCNN class loss: 0.10801 FastRCNN total loss: 0.26692 L1 loss: 0.0000e+00 L2 loss: 1.16241 Learning rate: 0.02 Mask loss: 0.19288 RPN box loss: 0.04599 RPN score loss: 0.01277 RPN total loss: 0.05877 Total loss: 1.68098 timestamp: 1655022179.1670196 iteration: 18385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24755 FastRCNN class loss: 0.10125 FastRCNN total loss: 0.3488 L1 loss: 0.0000e+00 L2 loss: 1.16222 Learning rate: 0.02 Mask loss: 0.20254 RPN box loss: 0.01835 RPN score loss: 0.00967 RPN total loss: 0.02802 Total loss: 1.74159 timestamp: 1655022182.6255722 iteration: 18390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13179 FastRCNN class loss: 0.11904 FastRCNN total loss: 0.25083 L1 loss: 0.0000e+00 L2 loss: 1.16203 Learning rate: 0.02 Mask loss: 0.18553 RPN box loss: 0.03448 RPN score loss: 0.01095 RPN total loss: 0.04543 Total loss: 1.64384 timestamp: 1655022186.00667 iteration: 18395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08901 FastRCNN class loss: 0.04845 FastRCNN total loss: 0.13747 L1 loss: 0.0000e+00 L2 loss: 1.16183 Learning rate: 0.02 Mask loss: 0.08844 RPN box loss: 0.11543 RPN score loss: 0.00523 RPN total loss: 0.12066 Total loss: 1.50839 timestamp: 1655022189.3468213 iteration: 18400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24373 FastRCNN class loss: 0.10273 FastRCNN total loss: 0.34646 L1 loss: 0.0000e+00 L2 loss: 1.16161 Learning rate: 0.02 Mask loss: 0.19807 RPN box loss: 0.0701 RPN score loss: 0.01613 RPN total loss: 0.08622 Total loss: 1.79236 timestamp: 1655022192.6494234 iteration: 18405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15531 FastRCNN class loss: 0.0839 FastRCNN total loss: 0.23921 L1 loss: 0.0000e+00 L2 loss: 1.16142 Learning rate: 0.02 Mask loss: 0.14194 RPN box loss: 0.00622 RPN score loss: 0.00646 RPN total loss: 0.01268 Total loss: 1.55525 timestamp: 1655022195.924198 iteration: 18410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25631 FastRCNN class loss: 0.18415 FastRCNN total loss: 0.44047 L1 loss: 0.0000e+00 L2 loss: 1.16122 Learning rate: 0.02 Mask loss: 0.18919 RPN box loss: 0.02185 RPN score loss: 0.01828 RPN total loss: 0.04013 Total loss: 1.831 timestamp: 1655022199.2677817 iteration: 18415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20841 FastRCNN class loss: 0.16962 FastRCNN total loss: 0.37804 L1 loss: 0.0000e+00 L2 loss: 1.16101 Learning rate: 0.02 Mask loss: 0.22562 RPN box loss: 0.07141 RPN score loss: 0.00897 RPN total loss: 0.08038 Total loss: 1.84504 timestamp: 1655022202.5500007 iteration: 18420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.07879 FastRCNN total loss: 0.18458 L1 loss: 0.0000e+00 L2 loss: 1.1608 Learning rate: 0.02 Mask loss: 0.1821 RPN box loss: 0.07087 RPN score loss: 0.0157 RPN total loss: 0.08657 Total loss: 1.61405 timestamp: 1655022205.9218109 iteration: 18425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12113 FastRCNN class loss: 0.07607 FastRCNN total loss: 0.1972 L1 loss: 0.0000e+00 L2 loss: 1.16061 Learning rate: 0.02 Mask loss: 0.09094 RPN box loss: 0.05602 RPN score loss: 0.00204 RPN total loss: 0.05806 Total loss: 1.50681 timestamp: 1655022209.1596634 iteration: 18430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19244 FastRCNN class loss: 0.09843 FastRCNN total loss: 0.29087 L1 loss: 0.0000e+00 L2 loss: 1.16042 Learning rate: 0.02 Mask loss: 0.26192 RPN box loss: 0.04087 RPN score loss: 0.00738 RPN total loss: 0.04825 Total loss: 1.76146 timestamp: 1655022212.5845156 iteration: 18435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25983 FastRCNN class loss: 0.12152 FastRCNN total loss: 0.38134 L1 loss: 0.0000e+00 L2 loss: 1.16024 Learning rate: 0.02 Mask loss: 0.22027 RPN box loss: 0.06377 RPN score loss: 0.01595 RPN total loss: 0.07972 Total loss: 1.84157 timestamp: 1655022216.041049 iteration: 18440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10086 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.16785 L1 loss: 0.0000e+00 L2 loss: 1.16005 Learning rate: 0.02 Mask loss: 0.14195 RPN box loss: 0.01639 RPN score loss: 0.00424 RPN total loss: 0.02063 Total loss: 1.49049 timestamp: 1655022219.315547 iteration: 18445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15452 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.23202 L1 loss: 0.0000e+00 L2 loss: 1.15983 Learning rate: 0.02 Mask loss: 0.11488 RPN box loss: 0.01754 RPN score loss: 0.00746 RPN total loss: 0.025 Total loss: 1.53173 timestamp: 1655022222.8340926 iteration: 18450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20488 FastRCNN class loss: 0.09341 FastRCNN total loss: 0.29829 L1 loss: 0.0000e+00 L2 loss: 1.15963 Learning rate: 0.02 Mask loss: 0.22754 RPN box loss: 0.0332 RPN score loss: 0.00739 RPN total loss: 0.04059 Total loss: 1.72604 timestamp: 1655022226.0867236 iteration: 18455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13937 FastRCNN class loss: 0.09 FastRCNN total loss: 0.22938 L1 loss: 0.0000e+00 L2 loss: 1.15941 Learning rate: 0.02 Mask loss: 0.15563 RPN box loss: 0.08554 RPN score loss: 0.0158 RPN total loss: 0.10134 Total loss: 1.64575 timestamp: 1655022229.4720511 iteration: 18460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17105 FastRCNN class loss: 0.08786 FastRCNN total loss: 0.25891 L1 loss: 0.0000e+00 L2 loss: 1.15923 Learning rate: 0.02 Mask loss: 0.27788 RPN box loss: 0.04035 RPN score loss: 0.00637 RPN total loss: 0.04672 Total loss: 1.74273 timestamp: 1655022232.7699847 iteration: 18465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.05844 FastRCNN total loss: 0.15536 L1 loss: 0.0000e+00 L2 loss: 1.15903 Learning rate: 0.02 Mask loss: 0.12911 RPN box loss: 0.02398 RPN score loss: 0.00713 RPN total loss: 0.0311 Total loss: 1.4746 timestamp: 1655022236.1331508 iteration: 18470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15132 FastRCNN class loss: 0.08671 FastRCNN total loss: 0.23803 L1 loss: 0.0000e+00 L2 loss: 1.15882 Learning rate: 0.02 Mask loss: 0.25333 RPN box loss: 0.02647 RPN score loss: 0.00963 RPN total loss: 0.0361 Total loss: 1.68627 timestamp: 1655022239.3995497 iteration: 18475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09636 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.17499 L1 loss: 0.0000e+00 L2 loss: 1.1586 Learning rate: 0.02 Mask loss: 0.15419 RPN box loss: 0.02719 RPN score loss: 0.00413 RPN total loss: 0.03132 Total loss: 1.5191 timestamp: 1655022242.7039924 iteration: 18480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21543 FastRCNN class loss: 0.10316 FastRCNN total loss: 0.31859 L1 loss: 0.0000e+00 L2 loss: 1.1584 Learning rate: 0.02 Mask loss: 0.20572 RPN box loss: 0.02843 RPN score loss: 0.02704 RPN total loss: 0.05548 Total loss: 1.73818 timestamp: 1655022246.0746832 iteration: 18485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17462 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.25167 L1 loss: 0.0000e+00 L2 loss: 1.1582 Learning rate: 0.02 Mask loss: 0.16206 RPN box loss: 0.04492 RPN score loss: 0.00812 RPN total loss: 0.05304 Total loss: 1.62496 timestamp: 1655022249.4303727 iteration: 18490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10787 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.18985 L1 loss: 0.0000e+00 L2 loss: 1.15801 Learning rate: 0.02 Mask loss: 0.13485 RPN box loss: 0.06506 RPN score loss: 0.00557 RPN total loss: 0.07062 Total loss: 1.55334 timestamp: 1655022252.8816125 iteration: 18495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12302 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.19427 L1 loss: 0.0000e+00 L2 loss: 1.1578 Learning rate: 0.02 Mask loss: 0.09713 RPN box loss: 0.03691 RPN score loss: 0.00307 RPN total loss: 0.03998 Total loss: 1.48918 timestamp: 1655022256.190406 iteration: 18500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16137 FastRCNN class loss: 0.0957 FastRCNN total loss: 0.25707 L1 loss: 0.0000e+00 L2 loss: 1.15758 Learning rate: 0.02 Mask loss: 0.25397 RPN box loss: 0.04205 RPN score loss: 0.00409 RPN total loss: 0.04615 Total loss: 1.71476 timestamp: 1655022259.6623135 iteration: 18505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11213 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.18159 L1 loss: 0.0000e+00 L2 loss: 1.15739 Learning rate: 0.02 Mask loss: 0.17032 RPN box loss: 0.02808 RPN score loss: 0.0062 RPN total loss: 0.03428 Total loss: 1.54359 timestamp: 1655022262.9304469 iteration: 18510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25126 FastRCNN class loss: 0.11903 FastRCNN total loss: 0.37029 L1 loss: 0.0000e+00 L2 loss: 1.15723 Learning rate: 0.02 Mask loss: 0.24993 RPN box loss: 0.00843 RPN score loss: 0.0056 RPN total loss: 0.01403 Total loss: 1.79149 timestamp: 1655022266.288959 iteration: 18515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14358 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.20954 L1 loss: 0.0000e+00 L2 loss: 1.15705 Learning rate: 0.02 Mask loss: 0.11112 RPN box loss: 0.07584 RPN score loss: 0.00458 RPN total loss: 0.08042 Total loss: 1.55813 timestamp: 1655022269.5832164 iteration: 18520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14697 FastRCNN class loss: 0.04779 FastRCNN total loss: 0.19477 L1 loss: 0.0000e+00 L2 loss: 1.15685 Learning rate: 0.02 Mask loss: 0.19751 RPN box loss: 0.00886 RPN score loss: 0.00802 RPN total loss: 0.01688 Total loss: 1.56601 timestamp: 1655022272.8491054 iteration: 18525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15756 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.22543 L1 loss: 0.0000e+00 L2 loss: 1.15665 Learning rate: 0.02 Mask loss: 0.11695 RPN box loss: 0.01348 RPN score loss: 0.00277 RPN total loss: 0.01625 Total loss: 1.51528 timestamp: 1655022276.355428 iteration: 18530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20543 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.28171 L1 loss: 0.0000e+00 L2 loss: 1.15643 Learning rate: 0.02 Mask loss: 0.14943 RPN box loss: 0.02686 RPN score loss: 0.00738 RPN total loss: 0.03424 Total loss: 1.62181 timestamp: 1655022279.6252081 iteration: 18535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13771 FastRCNN class loss: 0.12416 FastRCNN total loss: 0.26187 L1 loss: 0.0000e+00 L2 loss: 1.1562 Learning rate: 0.02 Mask loss: 0.26924 RPN box loss: 0.02805 RPN score loss: 0.00167 RPN total loss: 0.02972 Total loss: 1.71704 timestamp: 1655022282.9415503 iteration: 18540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2718 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.36443 L1 loss: 0.0000e+00 L2 loss: 1.156 Learning rate: 0.02 Mask loss: 0.12916 RPN box loss: 0.03265 RPN score loss: 0.00693 RPN total loss: 0.03958 Total loss: 1.68916 timestamp: 1655022286.1664214 iteration: 18545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14117 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.21999 L1 loss: 0.0000e+00 L2 loss: 1.15582 Learning rate: 0.02 Mask loss: 0.1713 RPN box loss: 0.0218 RPN score loss: 0.00635 RPN total loss: 0.02814 Total loss: 1.57525 timestamp: 1655022289.538721 iteration: 18550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14065 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.22289 L1 loss: 0.0000e+00 L2 loss: 1.15563 Learning rate: 0.02 Mask loss: 0.20689 RPN box loss: 0.02383 RPN score loss: 0.01318 RPN total loss: 0.03702 Total loss: 1.62243 timestamp: 1655022292.8476062 iteration: 18555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19443 FastRCNN class loss: 0.14789 FastRCNN total loss: 0.34231 L1 loss: 0.0000e+00 L2 loss: 1.15545 Learning rate: 0.02 Mask loss: 0.22297 RPN box loss: 0.13173 RPN score loss: 0.01621 RPN total loss: 0.14793 Total loss: 1.86867 timestamp: 1655022296.2616217 iteration: 18560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21584 FastRCNN class loss: 0.11261 FastRCNN total loss: 0.32845 L1 loss: 0.0000e+00 L2 loss: 1.15526 Learning rate: 0.02 Mask loss: 0.31318 RPN box loss: 0.05072 RPN score loss: 0.01729 RPN total loss: 0.06801 Total loss: 1.86489 timestamp: 1655022299.6053724 iteration: 18565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09534 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.17889 L1 loss: 0.0000e+00 L2 loss: 1.15507 Learning rate: 0.02 Mask loss: 0.14233 RPN box loss: 0.01729 RPN score loss: 0.0047 RPN total loss: 0.02199 Total loss: 1.49827 timestamp: 1655022302.909416 iteration: 18570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11339 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.19148 L1 loss: 0.0000e+00 L2 loss: 1.15488 Learning rate: 0.02 Mask loss: 0.13189 RPN box loss: 0.06972 RPN score loss: 0.01001 RPN total loss: 0.07973 Total loss: 1.55798 timestamp: 1655022306.2666042 iteration: 18575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15039 FastRCNN class loss: 0.09488 FastRCNN total loss: 0.24528 L1 loss: 0.0000e+00 L2 loss: 1.15468 Learning rate: 0.02 Mask loss: 0.14185 RPN box loss: 0.02981 RPN score loss: 0.01105 RPN total loss: 0.04086 Total loss: 1.58267 timestamp: 1655022309.513116 iteration: 18580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16149 FastRCNN class loss: 0.13165 FastRCNN total loss: 0.29313 L1 loss: 0.0000e+00 L2 loss: 1.15448 Learning rate: 0.02 Mask loss: 0.18199 RPN box loss: 0.02928 RPN score loss: 0.00806 RPN total loss: 0.03734 Total loss: 1.66695 timestamp: 1655022312.8138347 iteration: 18585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17944 FastRCNN class loss: 0.1155 FastRCNN total loss: 0.29494 L1 loss: 0.0000e+00 L2 loss: 1.15429 Learning rate: 0.02 Mask loss: 0.19875 RPN box loss: 0.07504 RPN score loss: 0.01534 RPN total loss: 0.09038 Total loss: 1.73836 timestamp: 1655022316.0774846 iteration: 18590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17852 FastRCNN class loss: 0.13143 FastRCNN total loss: 0.30995 L1 loss: 0.0000e+00 L2 loss: 1.15408 Learning rate: 0.02 Mask loss: 0.24863 RPN box loss: 0.04351 RPN score loss: 0.00891 RPN total loss: 0.05243 Total loss: 1.76508 timestamp: 1655022319.4834635 iteration: 18595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.18475 L1 loss: 0.0000e+00 L2 loss: 1.15387 Learning rate: 0.02 Mask loss: 0.1972 RPN box loss: 0.03374 RPN score loss: 0.00559 RPN total loss: 0.03933 Total loss: 1.57515 timestamp: 1655022322.7326694 iteration: 18600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23639 FastRCNN class loss: 0.15172 FastRCNN total loss: 0.38811 L1 loss: 0.0000e+00 L2 loss: 1.15369 Learning rate: 0.02 Mask loss: 0.286 RPN box loss: 0.05125 RPN score loss: 0.01677 RPN total loss: 0.06802 Total loss: 1.89581 timestamp: 1655022326.045987 iteration: 18605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10453 FastRCNN class loss: 0.12655 FastRCNN total loss: 0.23108 L1 loss: 0.0000e+00 L2 loss: 1.15349 Learning rate: 0.02 Mask loss: 0.15761 RPN box loss: 0.01716 RPN score loss: 0.01453 RPN total loss: 0.03168 Total loss: 1.57386 timestamp: 1655022329.404778 iteration: 18610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09858 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.15771 L1 loss: 0.0000e+00 L2 loss: 1.1533 Learning rate: 0.02 Mask loss: 0.18592 RPN box loss: 0.10408 RPN score loss: 0.00812 RPN total loss: 0.1122 Total loss: 1.60913 timestamp: 1655022332.632364 iteration: 18615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17321 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.25569 L1 loss: 0.0000e+00 L2 loss: 1.15312 Learning rate: 0.02 Mask loss: 0.1595 RPN box loss: 0.04855 RPN score loss: 0.01645 RPN total loss: 0.06501 Total loss: 1.63332 timestamp: 1655022336.0689497 iteration: 18620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14077 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.21781 L1 loss: 0.0000e+00 L2 loss: 1.15292 Learning rate: 0.02 Mask loss: 0.12346 RPN box loss: 0.05132 RPN score loss: 0.00913 RPN total loss: 0.06045 Total loss: 1.55465 timestamp: 1655022339.3232706 iteration: 18625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14797 FastRCNN class loss: 0.07847 FastRCNN total loss: 0.22644 L1 loss: 0.0000e+00 L2 loss: 1.15272 Learning rate: 0.02 Mask loss: 0.20153 RPN box loss: 0.04178 RPN score loss: 0.00767 RPN total loss: 0.04945 Total loss: 1.63014 timestamp: 1655022342.6969738 iteration: 18630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11127 FastRCNN class loss: 0.06653 FastRCNN total loss: 0.1778 L1 loss: 0.0000e+00 L2 loss: 1.15249 Learning rate: 0.02 Mask loss: 0.15235 RPN box loss: 0.014 RPN score loss: 0.00294 RPN total loss: 0.01694 Total loss: 1.49958 timestamp: 1655022345.9140477 iteration: 18635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22266 FastRCNN class loss: 0.12208 FastRCNN total loss: 0.34474 L1 loss: 0.0000e+00 L2 loss: 1.1523 Learning rate: 0.02 Mask loss: 0.19789 RPN box loss: 0.06421 RPN score loss: 0.02403 RPN total loss: 0.08823 Total loss: 1.78316 timestamp: 1655022349.3699932 iteration: 18640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17699 FastRCNN class loss: 0.0977 FastRCNN total loss: 0.27469 L1 loss: 0.0000e+00 L2 loss: 1.15211 Learning rate: 0.02 Mask loss: 0.15936 RPN box loss: 0.0157 RPN score loss: 0.00761 RPN total loss: 0.02331 Total loss: 1.60947 timestamp: 1655022352.619117 iteration: 18645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.22047 L1 loss: 0.0000e+00 L2 loss: 1.15194 Learning rate: 0.02 Mask loss: 0.15501 RPN box loss: 0.05732 RPN score loss: 0.01309 RPN total loss: 0.07041 Total loss: 1.59782 timestamp: 1655022355.9848173 iteration: 18650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1444 FastRCNN class loss: 0.10557 FastRCNN total loss: 0.24997 L1 loss: 0.0000e+00 L2 loss: 1.15177 Learning rate: 0.02 Mask loss: 0.17447 RPN box loss: 0.01889 RPN score loss: 0.00493 RPN total loss: 0.02381 Total loss: 1.60002 timestamp: 1655022359.3028793 iteration: 18655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16688 FastRCNN class loss: 0.14105 FastRCNN total loss: 0.30794 L1 loss: 0.0000e+00 L2 loss: 1.15155 Learning rate: 0.02 Mask loss: 0.23822 RPN box loss: 0.03835 RPN score loss: 0.02195 RPN total loss: 0.0603 Total loss: 1.758 timestamp: 1655022362.6149735 iteration: 18660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24447 FastRCNN class loss: 0.2091 FastRCNN total loss: 0.45356 L1 loss: 0.0000e+00 L2 loss: 1.15135 Learning rate: 0.02 Mask loss: 0.2602 RPN box loss: 0.02941 RPN score loss: 0.01567 RPN total loss: 0.04508 Total loss: 1.91019 timestamp: 1655022366.035437 iteration: 18665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08505 FastRCNN class loss: 0.04959 FastRCNN total loss: 0.13465 L1 loss: 0.0000e+00 L2 loss: 1.15115 Learning rate: 0.02 Mask loss: 0.13727 RPN box loss: 0.03717 RPN score loss: 0.00358 RPN total loss: 0.04075 Total loss: 1.46381 timestamp: 1655022369.3628373 iteration: 18670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26452 FastRCNN class loss: 0.12051 FastRCNN total loss: 0.38503 L1 loss: 0.0000e+00 L2 loss: 1.15093 Learning rate: 0.02 Mask loss: 0.24245 RPN box loss: 0.03319 RPN score loss: 0.00928 RPN total loss: 0.04247 Total loss: 1.82087 timestamp: 1655022372.7466033 iteration: 18675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1145 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.18243 L1 loss: 0.0000e+00 L2 loss: 1.15071 Learning rate: 0.02 Mask loss: 0.14797 RPN box loss: 0.06822 RPN score loss: 0.00967 RPN total loss: 0.07789 Total loss: 1.55899 timestamp: 1655022376.0533073 iteration: 18680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12719 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.18194 L1 loss: 0.0000e+00 L2 loss: 1.15052 Learning rate: 0.02 Mask loss: 0.09701 RPN box loss: 0.01924 RPN score loss: 0.00231 RPN total loss: 0.02155 Total loss: 1.45103 timestamp: 1655022379.44745 iteration: 18685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20826 FastRCNN class loss: 0.14693 FastRCNN total loss: 0.35519 L1 loss: 0.0000e+00 L2 loss: 1.15035 Learning rate: 0.02 Mask loss: 0.18108 RPN box loss: 0.03009 RPN score loss: 0.01449 RPN total loss: 0.04459 Total loss: 1.7312 timestamp: 1655022382.7149339 iteration: 18690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13701 FastRCNN class loss: 0.09382 FastRCNN total loss: 0.23083 L1 loss: 0.0000e+00 L2 loss: 1.15015 Learning rate: 0.02 Mask loss: 0.15256 RPN box loss: 0.01442 RPN score loss: 0.0048 RPN total loss: 0.01922 Total loss: 1.55276 timestamp: 1655022386.0743868 iteration: 18695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12259 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 1.14994 Learning rate: 0.02 Mask loss: 0.16431 RPN box loss: 0.02125 RPN score loss: 0.00284 RPN total loss: 0.02408 Total loss: 1.53356 timestamp: 1655022389.3918805 iteration: 18700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18266 FastRCNN class loss: 0.08915 FastRCNN total loss: 0.27181 L1 loss: 0.0000e+00 L2 loss: 1.14974 Learning rate: 0.02 Mask loss: 0.205 RPN box loss: 0.01205 RPN score loss: 0.00409 RPN total loss: 0.01614 Total loss: 1.64269 timestamp: 1655022392.710258 iteration: 18705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14638 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.22335 L1 loss: 0.0000e+00 L2 loss: 1.14955 Learning rate: 0.02 Mask loss: 0.1773 RPN box loss: 0.034 RPN score loss: 0.00492 RPN total loss: 0.03892 Total loss: 1.58911 timestamp: 1655022396.0312517 iteration: 18710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16604 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.2237 L1 loss: 0.0000e+00 L2 loss: 1.14936 Learning rate: 0.02 Mask loss: 0.1604 RPN box loss: 0.00364 RPN score loss: 0.0044 RPN total loss: 0.00803 Total loss: 1.5415 timestamp: 1655022399.2753584 iteration: 18715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1794 FastRCNN class loss: 0.11646 FastRCNN total loss: 0.29586 L1 loss: 0.0000e+00 L2 loss: 1.14918 Learning rate: 0.02 Mask loss: 0.19126 RPN box loss: 0.04607 RPN score loss: 0.01696 RPN total loss: 0.06303 Total loss: 1.69932 timestamp: 1655022402.6560578 iteration: 18720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22372 FastRCNN class loss: 0.12015 FastRCNN total loss: 0.34386 L1 loss: 0.0000e+00 L2 loss: 1.14897 Learning rate: 0.02 Mask loss: 0.18098 RPN box loss: 0.02945 RPN score loss: 0.01247 RPN total loss: 0.04191 Total loss: 1.71573 timestamp: 1655022405.969902 iteration: 18725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09754 FastRCNN class loss: 0.07722 FastRCNN total loss: 0.17477 L1 loss: 0.0000e+00 L2 loss: 1.14877 Learning rate: 0.02 Mask loss: 0.09956 RPN box loss: 0.01541 RPN score loss: 0.00405 RPN total loss: 0.01946 Total loss: 1.44255 timestamp: 1655022409.3160803 iteration: 18730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26009 FastRCNN class loss: 0.16217 FastRCNN total loss: 0.42226 L1 loss: 0.0000e+00 L2 loss: 1.14859 Learning rate: 0.02 Mask loss: 0.18211 RPN box loss: 0.04109 RPN score loss: 0.009 RPN total loss: 0.05009 Total loss: 1.80306 timestamp: 1655022412.5822039 iteration: 18735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14997 FastRCNN class loss: 0.114 FastRCNN total loss: 0.26397 L1 loss: 0.0000e+00 L2 loss: 1.14838 Learning rate: 0.02 Mask loss: 0.19359 RPN box loss: 0.04713 RPN score loss: 0.01732 RPN total loss: 0.06445 Total loss: 1.6704 timestamp: 1655022416.00972 iteration: 18740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2116 FastRCNN class loss: 0.11924 FastRCNN total loss: 0.33084 L1 loss: 0.0000e+00 L2 loss: 1.14819 Learning rate: 0.02 Mask loss: 0.23926 RPN box loss: 0.07704 RPN score loss: 0.01209 RPN total loss: 0.08914 Total loss: 1.80743 timestamp: 1655022419.3716247 iteration: 18745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11737 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.16984 L1 loss: 0.0000e+00 L2 loss: 1.14799 Learning rate: 0.02 Mask loss: 0.13976 RPN box loss: 0.01371 RPN score loss: 0.00629 RPN total loss: 0.02 Total loss: 1.4776 timestamp: 1655022422.598432 iteration: 18750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10258 FastRCNN class loss: 0.07894 FastRCNN total loss: 0.18151 L1 loss: 0.0000e+00 L2 loss: 1.14778 Learning rate: 0.02 Mask loss: 0.21822 RPN box loss: 0.0481 RPN score loss: 0.0138 RPN total loss: 0.06189 Total loss: 1.60941 timestamp: 1655022426.0275586 iteration: 18755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14563 FastRCNN class loss: 0.09866 FastRCNN total loss: 0.24429 L1 loss: 0.0000e+00 L2 loss: 1.14758 Learning rate: 0.02 Mask loss: 0.1703 RPN box loss: 0.0138 RPN score loss: 0.00199 RPN total loss: 0.01579 Total loss: 1.57795 timestamp: 1655022429.3027136 iteration: 18760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12278 FastRCNN class loss: 0.05827 FastRCNN total loss: 0.18105 L1 loss: 0.0000e+00 L2 loss: 1.14738 Learning rate: 0.02 Mask loss: 0.15227 RPN box loss: 0.00997 RPN score loss: 0.00318 RPN total loss: 0.01315 Total loss: 1.49385 timestamp: 1655022432.7038474 iteration: 18765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21235 FastRCNN class loss: 0.15982 FastRCNN total loss: 0.37217 L1 loss: 0.0000e+00 L2 loss: 1.14718 Learning rate: 0.02 Mask loss: 0.18164 RPN box loss: 0.04026 RPN score loss: 0.01222 RPN total loss: 0.05248 Total loss: 1.75347 timestamp: 1655022435.9511511 iteration: 18770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.099 FastRCNN class loss: 0.05781 FastRCNN total loss: 0.1568 L1 loss: 0.0000e+00 L2 loss: 1.147 Learning rate: 0.02 Mask loss: 0.14388 RPN box loss: 0.04625 RPN score loss: 0.00885 RPN total loss: 0.0551 Total loss: 1.50278 timestamp: 1655022439.2503266 iteration: 18775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14327 FastRCNN class loss: 0.1285 FastRCNN total loss: 0.27177 L1 loss: 0.0000e+00 L2 loss: 1.14679 Learning rate: 0.02 Mask loss: 0.18296 RPN box loss: 0.0674 RPN score loss: 0.01755 RPN total loss: 0.08496 Total loss: 1.68648 timestamp: 1655022442.6129262 iteration: 18780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18617 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.27676 L1 loss: 0.0000e+00 L2 loss: 1.1466 Learning rate: 0.02 Mask loss: 0.1232 RPN box loss: 0.02704 RPN score loss: 0.00518 RPN total loss: 0.03222 Total loss: 1.57878 timestamp: 1655022445.8862355 iteration: 18785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13994 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.2153 L1 loss: 0.0000e+00 L2 loss: 1.14639 Learning rate: 0.02 Mask loss: 0.10565 RPN box loss: 0.04654 RPN score loss: 0.00645 RPN total loss: 0.05299 Total loss: 1.52033 timestamp: 1655022449.2685559 iteration: 18790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15015 FastRCNN class loss: 0.09848 FastRCNN total loss: 0.24863 L1 loss: 0.0000e+00 L2 loss: 1.1462 Learning rate: 0.02 Mask loss: 0.19258 RPN box loss: 0.03606 RPN score loss: 0.01684 RPN total loss: 0.0529 Total loss: 1.64032 timestamp: 1655022452.561109 iteration: 18795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17255 FastRCNN class loss: 0.08937 FastRCNN total loss: 0.26192 L1 loss: 0.0000e+00 L2 loss: 1.14601 Learning rate: 0.02 Mask loss: 0.18059 RPN box loss: 0.1246 RPN score loss: 0.01141 RPN total loss: 0.13601 Total loss: 1.72454 timestamp: 1655022455.934898 iteration: 18800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21312 FastRCNN class loss: 0.07408 FastRCNN total loss: 0.2872 L1 loss: 0.0000e+00 L2 loss: 1.14583 Learning rate: 0.02 Mask loss: 0.13256 RPN box loss: 0.02328 RPN score loss: 0.00595 RPN total loss: 0.02923 Total loss: 1.59483 timestamp: 1655022459.2278605 iteration: 18805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25436 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.33794 L1 loss: 0.0000e+00 L2 loss: 1.14564 Learning rate: 0.02 Mask loss: 0.16221 RPN box loss: 0.05257 RPN score loss: 0.00387 RPN total loss: 0.05644 Total loss: 1.70223 timestamp: 1655022462.5594614 iteration: 18810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.14576 L1 loss: 0.0000e+00 L2 loss: 1.14542 Learning rate: 0.02 Mask loss: 0.22729 RPN box loss: 0.01206 RPN score loss: 0.00307 RPN total loss: 0.01513 Total loss: 1.53361 timestamp: 1655022465.8680518 iteration: 18815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15757 FastRCNN class loss: 0.09766 FastRCNN total loss: 0.25524 L1 loss: 0.0000e+00 L2 loss: 1.14523 Learning rate: 0.02 Mask loss: 0.23651 RPN box loss: 0.03904 RPN score loss: 0.02485 RPN total loss: 0.0639 Total loss: 1.70088 timestamp: 1655022469.2377758 iteration: 18820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16117 FastRCNN class loss: 0.12915 FastRCNN total loss: 0.29032 L1 loss: 0.0000e+00 L2 loss: 1.14502 Learning rate: 0.02 Mask loss: 0.24765 RPN box loss: 0.02543 RPN score loss: 0.03115 RPN total loss: 0.05658 Total loss: 1.73957 timestamp: 1655022472.484393 iteration: 18825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.08321 FastRCNN total loss: 0.22308 L1 loss: 0.0000e+00 L2 loss: 1.1448 Learning rate: 0.02 Mask loss: 0.20416 RPN box loss: 0.00754 RPN score loss: 0.00224 RPN total loss: 0.00978 Total loss: 1.58182 timestamp: 1655022475.7858577 iteration: 18830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12431 FastRCNN class loss: 0.05292 FastRCNN total loss: 0.17723 L1 loss: 0.0000e+00 L2 loss: 1.14461 Learning rate: 0.02 Mask loss: 0.17939 RPN box loss: 0.01335 RPN score loss: 0.00361 RPN total loss: 0.01696 Total loss: 1.51819 timestamp: 1655022479.0759203 iteration: 18835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13596 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.22409 L1 loss: 0.0000e+00 L2 loss: 1.14442 Learning rate: 0.02 Mask loss: 0.18881 RPN box loss: 0.07644 RPN score loss: 0.00981 RPN total loss: 0.08625 Total loss: 1.64358 timestamp: 1655022482.3552737 iteration: 18840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19375 FastRCNN class loss: 0.09193 FastRCNN total loss: 0.28568 L1 loss: 0.0000e+00 L2 loss: 1.14423 Learning rate: 0.02 Mask loss: 0.16942 RPN box loss: 0.03178 RPN score loss: 0.00738 RPN total loss: 0.03916 Total loss: 1.63848 timestamp: 1655022485.6890996 iteration: 18845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1096 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.18177 L1 loss: 0.0000e+00 L2 loss: 1.14405 Learning rate: 0.02 Mask loss: 0.17179 RPN box loss: 0.09128 RPN score loss: 0.00392 RPN total loss: 0.0952 Total loss: 1.59281 timestamp: 1655022488.9765737 iteration: 18850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17786 FastRCNN class loss: 0.06231 FastRCNN total loss: 0.24017 L1 loss: 0.0000e+00 L2 loss: 1.14384 Learning rate: 0.02 Mask loss: 0.12331 RPN box loss: 0.02578 RPN score loss: 0.00747 RPN total loss: 0.03325 Total loss: 1.54058 timestamp: 1655022492.3580573 iteration: 18855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28056 FastRCNN class loss: 0.10433 FastRCNN total loss: 0.38488 L1 loss: 0.0000e+00 L2 loss: 1.14366 Learning rate: 0.02 Mask loss: 0.1638 RPN box loss: 0.08842 RPN score loss: 0.01235 RPN total loss: 0.10077 Total loss: 1.79312 timestamp: 1655022495.6442988 iteration: 18860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12602 FastRCNN class loss: 0.07193 FastRCNN total loss: 0.19795 L1 loss: 0.0000e+00 L2 loss: 1.14346 Learning rate: 0.02 Mask loss: 0.17457 RPN box loss: 0.02995 RPN score loss: 0.00723 RPN total loss: 0.03718 Total loss: 1.55316 timestamp: 1655022498.923645 iteration: 18865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15027 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.21135 L1 loss: 0.0000e+00 L2 loss: 1.14326 Learning rate: 0.02 Mask loss: 0.15359 RPN box loss: 0.03538 RPN score loss: 0.01006 RPN total loss: 0.04544 Total loss: 1.55363 timestamp: 1655022502.2354224 iteration: 18870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18443 FastRCNN class loss: 0.14208 FastRCNN total loss: 0.32651 L1 loss: 0.0000e+00 L2 loss: 1.14308 Learning rate: 0.02 Mask loss: 0.22653 RPN box loss: 0.07329 RPN score loss: 0.0183 RPN total loss: 0.09159 Total loss: 1.78772 timestamp: 1655022505.6130807 iteration: 18875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13638 FastRCNN class loss: 0.05489 FastRCNN total loss: 0.19126 L1 loss: 0.0000e+00 L2 loss: 1.14289 Learning rate: 0.02 Mask loss: 0.12015 RPN box loss: 0.02625 RPN score loss: 0.00664 RPN total loss: 0.03288 Total loss: 1.48719 timestamp: 1655022508.8956277 iteration: 18880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15838 FastRCNN class loss: 0.1368 FastRCNN total loss: 0.29518 L1 loss: 0.0000e+00 L2 loss: 1.14269 Learning rate: 0.02 Mask loss: 0.21039 RPN box loss: 0.05797 RPN score loss: 0.0278 RPN total loss: 0.08577 Total loss: 1.73403 timestamp: 1655022512.1837182 iteration: 18885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17648 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.2351 L1 loss: 0.0000e+00 L2 loss: 1.14251 Learning rate: 0.02 Mask loss: 0.09883 RPN box loss: 0.06394 RPN score loss: 0.01061 RPN total loss: 0.07455 Total loss: 1.55098 timestamp: 1655022515.6630313 iteration: 18890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15537 FastRCNN class loss: 0.07836 FastRCNN total loss: 0.23373 L1 loss: 0.0000e+00 L2 loss: 1.14232 Learning rate: 0.02 Mask loss: 0.18564 RPN box loss: 0.03653 RPN score loss: 0.00618 RPN total loss: 0.04271 Total loss: 1.6044 timestamp: 1655022518.952773 iteration: 18895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18121 FastRCNN class loss: 0.08877 FastRCNN total loss: 0.26998 L1 loss: 0.0000e+00 L2 loss: 1.1421 Learning rate: 0.02 Mask loss: 0.1902 RPN box loss: 0.05263 RPN score loss: 0.01093 RPN total loss: 0.06356 Total loss: 1.66584 timestamp: 1655022522.3311775 iteration: 18900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09622 FastRCNN class loss: 0.10502 FastRCNN total loss: 0.20125 L1 loss: 0.0000e+00 L2 loss: 1.1419 Learning rate: 0.02 Mask loss: 0.14759 RPN box loss: 0.00808 RPN score loss: 0.00375 RPN total loss: 0.01183 Total loss: 1.50256 timestamp: 1655022525.5962486 iteration: 18905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18633 FastRCNN class loss: 0.14248 FastRCNN total loss: 0.32881 L1 loss: 0.0000e+00 L2 loss: 1.14173 Learning rate: 0.02 Mask loss: 0.17452 RPN box loss: 0.03739 RPN score loss: 0.00904 RPN total loss: 0.04643 Total loss: 1.69149 timestamp: 1655022528.8967428 iteration: 18910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13904 FastRCNN class loss: 0.10906 FastRCNN total loss: 0.24811 L1 loss: 0.0000e+00 L2 loss: 1.14154 Learning rate: 0.02 Mask loss: 0.18281 RPN box loss: 0.05987 RPN score loss: 0.02428 RPN total loss: 0.08416 Total loss: 1.65662 timestamp: 1655022532.2349129 iteration: 18915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18928 FastRCNN class loss: 0.07832 FastRCNN total loss: 0.2676 L1 loss: 0.0000e+00 L2 loss: 1.14133 Learning rate: 0.02 Mask loss: 0.17834 RPN box loss: 0.04372 RPN score loss: 0.00941 RPN total loss: 0.05313 Total loss: 1.64039 timestamp: 1655022535.7098732 iteration: 18920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14718 FastRCNN class loss: 0.1158 FastRCNN total loss: 0.26297 L1 loss: 0.0000e+00 L2 loss: 1.14112 Learning rate: 0.02 Mask loss: 0.17654 RPN box loss: 0.02408 RPN score loss: 0.00755 RPN total loss: 0.03163 Total loss: 1.61226 timestamp: 1655022539.0808043 iteration: 18925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07148 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.1263 L1 loss: 0.0000e+00 L2 loss: 1.14092 Learning rate: 0.02 Mask loss: 0.11043 RPN box loss: 0.01274 RPN score loss: 0.00908 RPN total loss: 0.02182 Total loss: 1.39947 timestamp: 1655022542.3257651 iteration: 18930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.09768 FastRCNN total loss: 0.2039 L1 loss: 0.0000e+00 L2 loss: 1.14074 Learning rate: 0.02 Mask loss: 0.14044 RPN box loss: 0.04846 RPN score loss: 0.00328 RPN total loss: 0.05174 Total loss: 1.53681 timestamp: 1655022545.6425784 iteration: 18935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2148 FastRCNN class loss: 0.12409 FastRCNN total loss: 0.33889 L1 loss: 0.0000e+00 L2 loss: 1.14055 Learning rate: 0.02 Mask loss: 0.31804 RPN box loss: 0.05319 RPN score loss: 0.02139 RPN total loss: 0.07458 Total loss: 1.87207 timestamp: 1655022548.981468 iteration: 18940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19262 FastRCNN class loss: 0.13555 FastRCNN total loss: 0.32817 L1 loss: 0.0000e+00 L2 loss: 1.14035 Learning rate: 0.02 Mask loss: 0.23299 RPN box loss: 0.03617 RPN score loss: 0.00546 RPN total loss: 0.04163 Total loss: 1.74315 timestamp: 1655022552.4129407 iteration: 18945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19795 FastRCNN class loss: 0.11295 FastRCNN total loss: 0.31091 L1 loss: 0.0000e+00 L2 loss: 1.14015 Learning rate: 0.02 Mask loss: 0.30001 RPN box loss: 0.01854 RPN score loss: 0.011 RPN total loss: 0.02954 Total loss: 1.7806 timestamp: 1655022555.657715 iteration: 18950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1144 FastRCNN class loss: 0.0975 FastRCNN total loss: 0.21191 L1 loss: 0.0000e+00 L2 loss: 1.13998 Learning rate: 0.02 Mask loss: 0.13196 RPN box loss: 0.0301 RPN score loss: 0.01261 RPN total loss: 0.04271 Total loss: 1.52655 timestamp: 1655022558.988328 iteration: 18955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.22765 L1 loss: 0.0000e+00 L2 loss: 1.13978 Learning rate: 0.02 Mask loss: 0.16631 RPN box loss: 0.02544 RPN score loss: 0.01075 RPN total loss: 0.03619 Total loss: 1.56994 timestamp: 1655022562.2947845 iteration: 18960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20754 FastRCNN class loss: 0.09618 FastRCNN total loss: 0.30373 L1 loss: 0.0000e+00 L2 loss: 1.1396 Learning rate: 0.02 Mask loss: 0.19817 RPN box loss: 0.03277 RPN score loss: 0.0044 RPN total loss: 0.03717 Total loss: 1.67867 timestamp: 1655022565.6115754 iteration: 18965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15787 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.23164 L1 loss: 0.0000e+00 L2 loss: 1.13941 Learning rate: 0.02 Mask loss: 0.17501 RPN box loss: 0.0702 RPN score loss: 0.00151 RPN total loss: 0.07171 Total loss: 1.61777 timestamp: 1655022569.0001802 iteration: 18970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15978 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.25113 L1 loss: 0.0000e+00 L2 loss: 1.13922 Learning rate: 0.02 Mask loss: 0.17807 RPN box loss: 0.02643 RPN score loss: 0.00453 RPN total loss: 0.03096 Total loss: 1.59938 timestamp: 1655022572.2309456 iteration: 18975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20581 FastRCNN class loss: 0.15446 FastRCNN total loss: 0.36027 L1 loss: 0.0000e+00 L2 loss: 1.13902 Learning rate: 0.02 Mask loss: 0.17801 RPN box loss: 0.02232 RPN score loss: 0.00342 RPN total loss: 0.02574 Total loss: 1.70305 timestamp: 1655022575.6040375 iteration: 18980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.154 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 1.13882 Learning rate: 0.02 Mask loss: 0.13172 RPN box loss: 0.0055 RPN score loss: 0.00432 RPN total loss: 0.00982 Total loss: 1.49338 timestamp: 1655022578.843923 iteration: 18985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14252 FastRCNN class loss: 0.08509 FastRCNN total loss: 0.22762 L1 loss: 0.0000e+00 L2 loss: 1.13864 Learning rate: 0.02 Mask loss: 0.12198 RPN box loss: 0.02675 RPN score loss: 0.00713 RPN total loss: 0.03388 Total loss: 1.52212 timestamp: 1655022582.14652 iteration: 18990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14303 FastRCNN class loss: 0.10383 FastRCNN total loss: 0.24686 L1 loss: 0.0000e+00 L2 loss: 1.13844 Learning rate: 0.02 Mask loss: 0.14976 RPN box loss: 0.0482 RPN score loss: 0.01094 RPN total loss: 0.05914 Total loss: 1.5942 timestamp: 1655022585.4284196 iteration: 18995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09966 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.17966 L1 loss: 0.0000e+00 L2 loss: 1.13823 Learning rate: 0.02 Mask loss: 0.13093 RPN box loss: 0.06283 RPN score loss: 0.01125 RPN total loss: 0.07407 Total loss: 1.5229 timestamp: 1655022588.7223022 iteration: 19000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12508 FastRCNN class loss: 0.03666 FastRCNN total loss: 0.16174 L1 loss: 0.0000e+00 L2 loss: 1.13803 Learning rate: 0.02 Mask loss: 0.13416 RPN box loss: 0.0559 RPN score loss: 0.00353 RPN total loss: 0.05944 Total loss: 1.49337 timestamp: 1655022592.0492306 iteration: 19005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24827 FastRCNN class loss: 0.11076 FastRCNN total loss: 0.35903 L1 loss: 0.0000e+00 L2 loss: 1.13787 Learning rate: 0.02 Mask loss: 0.20782 RPN box loss: 0.02518 RPN score loss: 0.00483 RPN total loss: 0.03001 Total loss: 1.73473 timestamp: 1655022595.367495 iteration: 19010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20128 FastRCNN class loss: 0.09575 FastRCNN total loss: 0.29703 L1 loss: 0.0000e+00 L2 loss: 1.13768 Learning rate: 0.02 Mask loss: 0.13951 RPN box loss: 0.01881 RPN score loss: 0.00527 RPN total loss: 0.02408 Total loss: 1.5983 timestamp: 1655022598.6482062 iteration: 19015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10886 FastRCNN class loss: 0.11395 FastRCNN total loss: 0.22282 L1 loss: 0.0000e+00 L2 loss: 1.13747 Learning rate: 0.02 Mask loss: 0.34627 RPN box loss: 0.03015 RPN score loss: 0.00523 RPN total loss: 0.03538 Total loss: 1.74194 timestamp: 1655022601.9152606 iteration: 19020 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07493 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.13727 L1 loss: 0.0000e+00 L2 loss: 1.1373 Learning rate: 0.02 Mask loss: 0.20289 RPN box loss: 0.06689 RPN score loss: 0.00762 RPN total loss: 0.07451 Total loss: 1.55197 timestamp: 1655022605.3064387 iteration: 19025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16917 FastRCNN class loss: 0.11299 FastRCNN total loss: 0.28216 L1 loss: 0.0000e+00 L2 loss: 1.13709 Learning rate: 0.02 Mask loss: 0.22753 RPN box loss: 0.02308 RPN score loss: 0.01166 RPN total loss: 0.03473 Total loss: 1.68151 timestamp: 1655022608.6072915 iteration: 19030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07428 FastRCNN class loss: 0.04533 FastRCNN total loss: 0.11961 L1 loss: 0.0000e+00 L2 loss: 1.13692 Learning rate: 0.02 Mask loss: 0.13034 RPN box loss: 0.046 RPN score loss: 0.0047 RPN total loss: 0.05069 Total loss: 1.43756 timestamp: 1655022611.9146614 iteration: 19035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20942 FastRCNN class loss: 0.18481 FastRCNN total loss: 0.39422 L1 loss: 0.0000e+00 L2 loss: 1.13675 Learning rate: 0.02 Mask loss: 0.28502 RPN box loss: 0.04951 RPN score loss: 0.01224 RPN total loss: 0.06174 Total loss: 1.87773 timestamp: 1655022615.164084 iteration: 19040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22384 FastRCNN class loss: 0.16659 FastRCNN total loss: 0.39042 L1 loss: 0.0000e+00 L2 loss: 1.13655 Learning rate: 0.02 Mask loss: 0.19872 RPN box loss: 0.04421 RPN score loss: 0.01082 RPN total loss: 0.05503 Total loss: 1.78071 timestamp: 1655022618.5171156 iteration: 19045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20149 FastRCNN class loss: 0.08176 FastRCNN total loss: 0.28325 L1 loss: 0.0000e+00 L2 loss: 1.13637 Learning rate: 0.02 Mask loss: 0.18519 RPN box loss: 0.04893 RPN score loss: 0.00853 RPN total loss: 0.05746 Total loss: 1.66226 timestamp: 1655022621.7120724 iteration: 19050 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14033 FastRCNN class loss: 0.11067 FastRCNN total loss: 0.251 L1 loss: 0.0000e+00 L2 loss: 1.13616 Learning rate: 0.02 Mask loss: 0.23242 RPN box loss: 0.074 RPN score loss: 0.00987 RPN total loss: 0.08386 Total loss: 1.70344 timestamp: 1655022625.0929043 iteration: 19055 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19108 FastRCNN class loss: 0.14146 FastRCNN total loss: 0.33254 L1 loss: 0.0000e+00 L2 loss: 1.13596 Learning rate: 0.02 Mask loss: 0.2278 RPN box loss: 0.02169 RPN score loss: 0.0072 RPN total loss: 0.02889 Total loss: 1.72518 timestamp: 1655022628.5114744 iteration: 19060 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17965 FastRCNN class loss: 0.13144 FastRCNN total loss: 0.31109 L1 loss: 0.0000e+00 L2 loss: 1.13576 Learning rate: 0.02 Mask loss: 0.14812 RPN box loss: 0.02877 RPN score loss: 0.01212 RPN total loss: 0.04089 Total loss: 1.63586 timestamp: 1655022631.7977111 iteration: 19065 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16745 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.24807 L1 loss: 0.0000e+00 L2 loss: 1.13558 Learning rate: 0.02 Mask loss: 0.13402 RPN box loss: 0.04071 RPN score loss: 0.00616 RPN total loss: 0.04687 Total loss: 1.56453 timestamp: 1655022635.1589177 iteration: 19070 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14251 FastRCNN class loss: 0.09152 FastRCNN total loss: 0.23403 L1 loss: 0.0000e+00 L2 loss: 1.13539 Learning rate: 0.02 Mask loss: 0.18796 RPN box loss: 0.02642 RPN score loss: 0.00221 RPN total loss: 0.02863 Total loss: 1.586 timestamp: 1655022638.4302206 iteration: 19075 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17524 FastRCNN class loss: 0.09998 FastRCNN total loss: 0.27521 L1 loss: 0.0000e+00 L2 loss: 1.13517 Learning rate: 0.02 Mask loss: 0.16161 RPN box loss: 0.04078 RPN score loss: 0.00595 RPN total loss: 0.04674 Total loss: 1.61874 timestamp: 1655022641.733147 iteration: 19080 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10597 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.18115 L1 loss: 0.0000e+00 L2 loss: 1.13499 Learning rate: 0.02 Mask loss: 0.13925 RPN box loss: 0.00945 RPN score loss: 0.02765 RPN total loss: 0.03711 Total loss: 1.49249 timestamp: 1655022645.0520244 iteration: 19085 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17408 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.24616 L1 loss: 0.0000e+00 L2 loss: 1.13482 Learning rate: 0.02 Mask loss: 0.18829 RPN box loss: 0.06866 RPN score loss: 0.00647 RPN total loss: 0.07513 Total loss: 1.6444 timestamp: 1655022648.41011 iteration: 19090 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11157 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.16686 L1 loss: 0.0000e+00 L2 loss: 1.13462 Learning rate: 0.02 Mask loss: 0.20034 RPN box loss: 0.0396 RPN score loss: 0.00336 RPN total loss: 0.04296 Total loss: 1.54479 timestamp: 1655022651.6941288 iteration: 19095 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.22611 L1 loss: 0.0000e+00 L2 loss: 1.13443 Learning rate: 0.02 Mask loss: 0.09708 RPN box loss: 0.03594 RPN score loss: 0.00467 RPN total loss: 0.04061 Total loss: 1.49823 timestamp: 1655022655.0932448 iteration: 19100 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0767 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.13313 L1 loss: 0.0000e+00 L2 loss: 1.13426 Learning rate: 0.02 Mask loss: 0.10766 RPN box loss: 0.0139 RPN score loss: 0.0032 RPN total loss: 0.0171 Total loss: 1.39215 timestamp: 1655022658.481188 iteration: 19105 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20536 FastRCNN class loss: 0.10847 FastRCNN total loss: 0.31383 L1 loss: 0.0000e+00 L2 loss: 1.13404 Learning rate: 0.02 Mask loss: 0.20247 RPN box loss: 0.09409 RPN score loss: 0.0084 RPN total loss: 0.10249 Total loss: 1.75283 timestamp: 1655022661.7363617 iteration: 19110 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.12233 FastRCNN total loss: 0.24914 L1 loss: 0.0000e+00 L2 loss: 1.13385 Learning rate: 0.02 Mask loss: 0.16001 RPN box loss: 0.07909 RPN score loss: 0.00826 RPN total loss: 0.08736 Total loss: 1.63036 timestamp: 1655022665.0758216 iteration: 19115 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1736 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.26315 L1 loss: 0.0000e+00 L2 loss: 1.13367 Learning rate: 0.02 Mask loss: 0.14359 RPN box loss: 0.02987 RPN score loss: 0.00581 RPN total loss: 0.03568 Total loss: 1.57608 timestamp: 1655022668.2825327 iteration: 19120 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.21023 L1 loss: 0.0000e+00 L2 loss: 1.13348 Learning rate: 0.02 Mask loss: 0.1518 RPN box loss: 0.01255 RPN score loss: 0.00347 RPN total loss: 0.01602 Total loss: 1.51153 timestamp: 1655022671.5644372 iteration: 19125 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17847 FastRCNN class loss: 0.06943 FastRCNN total loss: 0.24789 L1 loss: 0.0000e+00 L2 loss: 1.13328 Learning rate: 0.02 Mask loss: 0.17377 RPN box loss: 0.01761 RPN score loss: 0.00995 RPN total loss: 0.02757 Total loss: 1.58251 timestamp: 1655022674.8688328 iteration: 19130 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17894 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.27327 L1 loss: 0.0000e+00 L2 loss: 1.13309 Learning rate: 0.02 Mask loss: 0.26085 RPN box loss: 0.03167 RPN score loss: 0.01576 RPN total loss: 0.04743 Total loss: 1.71464 timestamp: 1655022678.335789 iteration: 19135 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14101 FastRCNN class loss: 0.08732 FastRCNN total loss: 0.22833 L1 loss: 0.0000e+00 L2 loss: 1.1329 Learning rate: 0.02 Mask loss: 0.22084 RPN box loss: 0.06849 RPN score loss: 0.00698 RPN total loss: 0.07546 Total loss: 1.65753 timestamp: 1655022681.6009007 iteration: 19140 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22309 FastRCNN class loss: 0.09806 FastRCNN total loss: 0.32115 L1 loss: 0.0000e+00 L2 loss: 1.1327 Learning rate: 0.02 Mask loss: 0.14167 RPN box loss: 0.03614 RPN score loss: 0.00494 RPN total loss: 0.04108 Total loss: 1.6366 timestamp: 1655022685.5221841 iteration: 19145 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13309 FastRCNN class loss: 0.10922 FastRCNN total loss: 0.24231 L1 loss: 0.0000e+00 L2 loss: 1.1325 Learning rate: 0.02 Mask loss: 0.20454 RPN box loss: 0.1109 RPN score loss: 0.00802 RPN total loss: 0.11892 Total loss: 1.69827 timestamp: 1655022688.9107974 iteration: 19150 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16008 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 1.13231 Learning rate: 0.02 Mask loss: 0.25696 RPN box loss: 0.0307 RPN score loss: 0.03115 RPN total loss: 0.06185 Total loss: 1.6883 timestamp: 1655022692.1305425 iteration: 19155 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19782 FastRCNN class loss: 0.09316 FastRCNN total loss: 0.29098 L1 loss: 0.0000e+00 L2 loss: 1.13213 Learning rate: 0.02 Mask loss: 0.1757 RPN box loss: 0.00837 RPN score loss: 0.00366 RPN total loss: 0.01203 Total loss: 1.61084 timestamp: 1655022695.5669224 iteration: 19160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.19341 L1 loss: 0.0000e+00 L2 loss: 1.13195 Learning rate: 0.02 Mask loss: 0.17727 RPN box loss: 0.0418 RPN score loss: 0.00611 RPN total loss: 0.04791 Total loss: 1.55053 timestamp: 1655022698.769745 iteration: 19165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10463 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.16053 L1 loss: 0.0000e+00 L2 loss: 1.13177 Learning rate: 0.02 Mask loss: 0.14238 RPN box loss: 0.10109 RPN score loss: 0.0228 RPN total loss: 0.12389 Total loss: 1.55856 timestamp: 1655022702.0826492 iteration: 19170 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08272 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.13288 L1 loss: 0.0000e+00 L2 loss: 1.13158 Learning rate: 0.02 Mask loss: 0.09691 RPN box loss: 0.01015 RPN score loss: 0.00418 RPN total loss: 0.01432 Total loss: 1.37569 timestamp: 1655022705.2967396 iteration: 19175 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13885 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.21921 L1 loss: 0.0000e+00 L2 loss: 1.13138 Learning rate: 0.02 Mask loss: 0.10139 RPN box loss: 0.01489 RPN score loss: 0.0098 RPN total loss: 0.02469 Total loss: 1.47668 timestamp: 1655022708.7027545 iteration: 19180 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09141 FastRCNN class loss: 0.0979 FastRCNN total loss: 0.1893 L1 loss: 0.0000e+00 L2 loss: 1.13118 Learning rate: 0.02 Mask loss: 0.12268 RPN box loss: 0.04279 RPN score loss: 0.00386 RPN total loss: 0.04665 Total loss: 1.48981 timestamp: 1655022712.086658 iteration: 19185 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1559 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.23345 L1 loss: 0.0000e+00 L2 loss: 1.13096 Learning rate: 0.02 Mask loss: 0.19854 RPN box loss: 0.10674 RPN score loss: 0.01912 RPN total loss: 0.12585 Total loss: 1.6888 timestamp: 1655022715.4236054 iteration: 19190 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15422 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.23588 L1 loss: 0.0000e+00 L2 loss: 1.13074 Learning rate: 0.02 Mask loss: 0.22877 RPN box loss: 0.02772 RPN score loss: 0.00446 RPN total loss: 0.03218 Total loss: 1.62757 timestamp: 1655022718.771281 iteration: 19195 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14126 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 1.13056 Learning rate: 0.02 Mask loss: 0.16565 RPN box loss: 0.03568 RPN score loss: 0.01119 RPN total loss: 0.04687 Total loss: 1.54998 timestamp: 1655022722.0204225 iteration: 19200 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18788 FastRCNN class loss: 0.18966 FastRCNN total loss: 0.37755 L1 loss: 0.0000e+00 L2 loss: 1.13038 Learning rate: 0.02 Mask loss: 0.139 RPN box loss: 0.06924 RPN score loss: 0.00998 RPN total loss: 0.07922 Total loss: 1.72615 timestamp: 1655022725.424885 iteration: 19205 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14447 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.20838 L1 loss: 0.0000e+00 L2 loss: 1.13018 Learning rate: 0.02 Mask loss: 0.15325 RPN box loss: 0.07604 RPN score loss: 0.00625 RPN total loss: 0.08229 Total loss: 1.5741 timestamp: 1655022728.6717348 iteration: 19210 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09043 FastRCNN class loss: 0.04991 FastRCNN total loss: 0.14035 L1 loss: 0.0000e+00 L2 loss: 1.12997 Learning rate: 0.02 Mask loss: 0.09008 RPN box loss: 0.01601 RPN score loss: 0.00765 RPN total loss: 0.02366 Total loss: 1.38406 timestamp: 1655022731.9951642 iteration: 19215 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12823 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.19998 L1 loss: 0.0000e+00 L2 loss: 1.12975 Learning rate: 0.02 Mask loss: 0.12829 RPN box loss: 0.00863 RPN score loss: 0.00463 RPN total loss: 0.01326 Total loss: 1.47128 timestamp: 1655022735.2913272 iteration: 19220 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21068 FastRCNN class loss: 0.06845 FastRCNN total loss: 0.27913 L1 loss: 0.0000e+00 L2 loss: 1.1296 Learning rate: 0.02 Mask loss: 0.17885 RPN box loss: 0.02689 RPN score loss: 0.00502 RPN total loss: 0.0319 Total loss: 1.61949 timestamp: 1655022738.6358008 iteration: 19225 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12502 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.20444 L1 loss: 0.0000e+00 L2 loss: 1.12941 Learning rate: 0.02 Mask loss: 0.20812 RPN box loss: 0.0153 RPN score loss: 0.00456 RPN total loss: 0.01986 Total loss: 1.56183 timestamp: 1655022742.0324724 iteration: 19230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13708 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.22325 L1 loss: 0.0000e+00 L2 loss: 1.12922 Learning rate: 0.02 Mask loss: 0.13032 RPN box loss: 0.09387 RPN score loss: 0.01036 RPN total loss: 0.10423 Total loss: 1.58702 timestamp: 1655022745.2498708 iteration: 19235 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.05032 FastRCNN total loss: 0.17179 L1 loss: 0.0000e+00 L2 loss: 1.12903 Learning rate: 0.02 Mask loss: 0.15151 RPN box loss: 0.00728 RPN score loss: 0.00307 RPN total loss: 0.01035 Total loss: 1.46267 timestamp: 1655022748.616463 iteration: 19240 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.162 FastRCNN class loss: 0.15473 FastRCNN total loss: 0.31673 L1 loss: 0.0000e+00 L2 loss: 1.12883 Learning rate: 0.02 Mask loss: 0.28709 RPN box loss: 0.0386 RPN score loss: 0.05365 RPN total loss: 0.09225 Total loss: 1.82491 timestamp: 1655022751.8657517 iteration: 19245 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14864 FastRCNN class loss: 0.08872 FastRCNN total loss: 0.23736 L1 loss: 0.0000e+00 L2 loss: 1.12864 Learning rate: 0.02 Mask loss: 0.2246 RPN box loss: 0.04811 RPN score loss: 0.01012 RPN total loss: 0.05823 Total loss: 1.64883 timestamp: 1655022755.2403913 iteration: 19250 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22296 FastRCNN class loss: 0.14238 FastRCNN total loss: 0.36534 L1 loss: 0.0000e+00 L2 loss: 1.12846 Learning rate: 0.02 Mask loss: 0.21638 RPN box loss: 0.09482 RPN score loss: 0.0105 RPN total loss: 0.10532 Total loss: 1.8155 timestamp: 1655022758.5476382 iteration: 19255 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12289 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.19707 L1 loss: 0.0000e+00 L2 loss: 1.12826 Learning rate: 0.02 Mask loss: 0.18643 RPN box loss: 0.03086 RPN score loss: 0.00899 RPN total loss: 0.03985 Total loss: 1.55161 timestamp: 1655022762.0265954 iteration: 19260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15401 FastRCNN class loss: 0.12187 FastRCNN total loss: 0.27588 L1 loss: 0.0000e+00 L2 loss: 1.12806 Learning rate: 0.02 Mask loss: 0.25311 RPN box loss: 0.02727 RPN score loss: 0.01404 RPN total loss: 0.04131 Total loss: 1.69836 timestamp: 1655022765.2448924 iteration: 19265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09824 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.16434 L1 loss: 0.0000e+00 L2 loss: 1.1279 Learning rate: 0.02 Mask loss: 0.17151 RPN box loss: 0.04387 RPN score loss: 0.01303 RPN total loss: 0.05689 Total loss: 1.52064 timestamp: 1655022768.6050322 iteration: 19270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15562 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.25475 L1 loss: 0.0000e+00 L2 loss: 1.12771 Learning rate: 0.02 Mask loss: 0.19871 RPN box loss: 0.01952 RPN score loss: 0.00515 RPN total loss: 0.02467 Total loss: 1.60584 timestamp: 1655022772.0356195 iteration: 19275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14781 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.22099 L1 loss: 0.0000e+00 L2 loss: 1.1275 Learning rate: 0.02 Mask loss: 0.1202 RPN box loss: 0.03028 RPN score loss: 0.00476 RPN total loss: 0.03504 Total loss: 1.50372 timestamp: 1655022775.2418854 iteration: 19280 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11651 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.17868 L1 loss: 0.0000e+00 L2 loss: 1.1273 Learning rate: 0.02 Mask loss: 0.12414 RPN box loss: 0.03975 RPN score loss: 0.00473 RPN total loss: 0.04447 Total loss: 1.47458 timestamp: 1655022778.6796336 iteration: 19285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25854 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.3397 L1 loss: 0.0000e+00 L2 loss: 1.12711 Learning rate: 0.02 Mask loss: 0.13912 RPN box loss: 0.05195 RPN score loss: 0.00863 RPN total loss: 0.06058 Total loss: 1.66651 timestamp: 1655022781.9413772 iteration: 19290 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20428 FastRCNN class loss: 0.07901 FastRCNN total loss: 0.2833 L1 loss: 0.0000e+00 L2 loss: 1.12693 Learning rate: 0.02 Mask loss: 0.1324 RPN box loss: 0.00626 RPN score loss: 0.00623 RPN total loss: 0.0125 Total loss: 1.55512 timestamp: 1655022785.4225593 iteration: 19295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.18374 L1 loss: 0.0000e+00 L2 loss: 1.12675 Learning rate: 0.02 Mask loss: 0.13854 RPN box loss: 0.04406 RPN score loss: 0.00951 RPN total loss: 0.05358 Total loss: 1.50262 timestamp: 1655022788.777829 iteration: 19300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16508 FastRCNN class loss: 0.15804 FastRCNN total loss: 0.32312 L1 loss: 0.0000e+00 L2 loss: 1.12654 Learning rate: 0.02 Mask loss: 0.18866 RPN box loss: 0.07143 RPN score loss: 0.00922 RPN total loss: 0.08065 Total loss: 1.71897 timestamp: 1655022792.1690166 iteration: 19305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15733 FastRCNN class loss: 0.08766 FastRCNN total loss: 0.24499 L1 loss: 0.0000e+00 L2 loss: 1.12634 Learning rate: 0.02 Mask loss: 0.17144 RPN box loss: 0.02127 RPN score loss: 0.00343 RPN total loss: 0.0247 Total loss: 1.56747 timestamp: 1655022795.4407735 iteration: 19310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11125 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.16128 L1 loss: 0.0000e+00 L2 loss: 1.12615 Learning rate: 0.02 Mask loss: 0.11965 RPN box loss: 0.09903 RPN score loss: 0.00555 RPN total loss: 0.10458 Total loss: 1.51166 timestamp: 1655022798.7772079 iteration: 19315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20036 FastRCNN class loss: 0.12349 FastRCNN total loss: 0.32385 L1 loss: 0.0000e+00 L2 loss: 1.12596 Learning rate: 0.02 Mask loss: 0.18239 RPN box loss: 0.05819 RPN score loss: 0.0183 RPN total loss: 0.07649 Total loss: 1.70869 timestamp: 1655022802.2047982 iteration: 19320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14222 FastRCNN class loss: 0.07271 FastRCNN total loss: 0.21493 L1 loss: 0.0000e+00 L2 loss: 1.12577 Learning rate: 0.02 Mask loss: 0.16417 RPN box loss: 0.01862 RPN score loss: 0.00528 RPN total loss: 0.0239 Total loss: 1.52877 timestamp: 1655022805.4840858 iteration: 19325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12884 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.20996 L1 loss: 0.0000e+00 L2 loss: 1.12559 Learning rate: 0.02 Mask loss: 0.24707 RPN box loss: 0.02664 RPN score loss: 0.00659 RPN total loss: 0.03323 Total loss: 1.61585 timestamp: 1655022808.87348 iteration: 19330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.18295 L1 loss: 0.0000e+00 L2 loss: 1.12542 Learning rate: 0.02 Mask loss: 0.14628 RPN box loss: 0.04525 RPN score loss: 0.01037 RPN total loss: 0.05562 Total loss: 1.51027 timestamp: 1655022812.122224 iteration: 19335 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16701 FastRCNN class loss: 0.09183 FastRCNN total loss: 0.25884 L1 loss: 0.0000e+00 L2 loss: 1.12525 Learning rate: 0.02 Mask loss: 0.12551 RPN box loss: 0.0329 RPN score loss: 0.00312 RPN total loss: 0.03602 Total loss: 1.54562 timestamp: 1655022815.4390783 iteration: 19340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14419 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.22633 L1 loss: 0.0000e+00 L2 loss: 1.12503 Learning rate: 0.02 Mask loss: 0.1861 RPN box loss: 0.09936 RPN score loss: 0.01021 RPN total loss: 0.10957 Total loss: 1.64703 timestamp: 1655022818.7557693 iteration: 19345 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23348 FastRCNN class loss: 0.12817 FastRCNN total loss: 0.36164 L1 loss: 0.0000e+00 L2 loss: 1.12484 Learning rate: 0.02 Mask loss: 0.25856 RPN box loss: 0.03187 RPN score loss: 0.01169 RPN total loss: 0.04356 Total loss: 1.78861 timestamp: 1655022822.2063444 iteration: 19350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18112 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.26568 L1 loss: 0.0000e+00 L2 loss: 1.12463 Learning rate: 0.02 Mask loss: 0.15385 RPN box loss: 0.02831 RPN score loss: 0.00421 RPN total loss: 0.03252 Total loss: 1.57668 timestamp: 1655022825.5197074 iteration: 19355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20001 FastRCNN class loss: 0.14375 FastRCNN total loss: 0.34376 L1 loss: 0.0000e+00 L2 loss: 1.12444 Learning rate: 0.02 Mask loss: 0.25649 RPN box loss: 0.05532 RPN score loss: 0.01358 RPN total loss: 0.0689 Total loss: 1.7936 timestamp: 1655022828.7892492 iteration: 19360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13933 FastRCNN class loss: 0.06599 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 1.12425 Learning rate: 0.02 Mask loss: 0.11621 RPN box loss: 0.0415 RPN score loss: 0.00722 RPN total loss: 0.04872 Total loss: 1.49451 timestamp: 1655022832.12268 iteration: 19365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14467 FastRCNN class loss: 0.10838 FastRCNN total loss: 0.25305 L1 loss: 0.0000e+00 L2 loss: 1.12409 Learning rate: 0.02 Mask loss: 0.19718 RPN box loss: 0.02181 RPN score loss: 0.00358 RPN total loss: 0.02538 Total loss: 1.59971 timestamp: 1655022835.3936872 iteration: 19370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15126 FastRCNN class loss: 0.09686 FastRCNN total loss: 0.24812 L1 loss: 0.0000e+00 L2 loss: 1.12392 Learning rate: 0.02 Mask loss: 0.27601 RPN box loss: 0.06984 RPN score loss: 0.01473 RPN total loss: 0.08457 Total loss: 1.73262 timestamp: 1655022838.8134394 iteration: 19375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21227 FastRCNN class loss: 0.15884 FastRCNN total loss: 0.37111 L1 loss: 0.0000e+00 L2 loss: 1.12374 Learning rate: 0.02 Mask loss: 0.22038 RPN box loss: 0.04253 RPN score loss: 0.0148 RPN total loss: 0.05733 Total loss: 1.77256 timestamp: 1655022842.1515737 iteration: 19380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23916 FastRCNN class loss: 0.10346 FastRCNN total loss: 0.34262 L1 loss: 0.0000e+00 L2 loss: 1.12354 Learning rate: 0.02 Mask loss: 0.18148 RPN box loss: 0.02055 RPN score loss: 0.01535 RPN total loss: 0.0359 Total loss: 1.68354 timestamp: 1655022845.4930756 iteration: 19385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15701 FastRCNN class loss: 0.13699 FastRCNN total loss: 0.294 L1 loss: 0.0000e+00 L2 loss: 1.12333 Learning rate: 0.02 Mask loss: 0.20085 RPN box loss: 0.05039 RPN score loss: 0.00949 RPN total loss: 0.05988 Total loss: 1.67806 timestamp: 1655022848.7665794 iteration: 19390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13775 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.21116 L1 loss: 0.0000e+00 L2 loss: 1.12313 Learning rate: 0.02 Mask loss: 0.16109 RPN box loss: 0.03192 RPN score loss: 0.00591 RPN total loss: 0.03783 Total loss: 1.5332 timestamp: 1655022852.144634 iteration: 19395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15798 FastRCNN class loss: 0.09408 FastRCNN total loss: 0.25206 L1 loss: 0.0000e+00 L2 loss: 1.12293 Learning rate: 0.02 Mask loss: 0.17142 RPN box loss: 0.0579 RPN score loss: 0.04514 RPN total loss: 0.10304 Total loss: 1.64944 timestamp: 1655022855.3605053 iteration: 19400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14164 FastRCNN class loss: 0.07131 FastRCNN total loss: 0.21295 L1 loss: 0.0000e+00 L2 loss: 1.1227 Learning rate: 0.02 Mask loss: 0.29665 RPN box loss: 0.03762 RPN score loss: 0.00432 RPN total loss: 0.04194 Total loss: 1.67423 timestamp: 1655022858.739744 iteration: 19405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11153 FastRCNN class loss: 0.09439 FastRCNN total loss: 0.20593 L1 loss: 0.0000e+00 L2 loss: 1.12252 Learning rate: 0.02 Mask loss: 0.19963 RPN box loss: 0.02725 RPN score loss: 0.00915 RPN total loss: 0.0364 Total loss: 1.56447 timestamp: 1655022862.005209 iteration: 19410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15483 FastRCNN class loss: 0.08341 FastRCNN total loss: 0.23825 L1 loss: 0.0000e+00 L2 loss: 1.12235 Learning rate: 0.02 Mask loss: 0.14494 RPN box loss: 0.03056 RPN score loss: 0.00419 RPN total loss: 0.03475 Total loss: 1.54029 timestamp: 1655022865.300556 iteration: 19415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12416 FastRCNN class loss: 0.06964 FastRCNN total loss: 0.19381 L1 loss: 0.0000e+00 L2 loss: 1.12218 Learning rate: 0.02 Mask loss: 0.13437 RPN box loss: 0.00805 RPN score loss: 0.00789 RPN total loss: 0.01594 Total loss: 1.46629 timestamp: 1655022868.712179 iteration: 19420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15186 FastRCNN class loss: 0.09241 FastRCNN total loss: 0.24426 L1 loss: 0.0000e+00 L2 loss: 1.12199 Learning rate: 0.02 Mask loss: 0.18126 RPN box loss: 0.0648 RPN score loss: 0.0176 RPN total loss: 0.0824 Total loss: 1.6299 timestamp: 1655022872.013824 iteration: 19425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12084 FastRCNN class loss: 0.08535 FastRCNN total loss: 0.20619 L1 loss: 0.0000e+00 L2 loss: 1.12178 Learning rate: 0.02 Mask loss: 0.22337 RPN box loss: 0.04793 RPN score loss: 0.01325 RPN total loss: 0.06118 Total loss: 1.61251 timestamp: 1655022875.4232697 iteration: 19430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2103 FastRCNN class loss: 0.10628 FastRCNN total loss: 0.31658 L1 loss: 0.0000e+00 L2 loss: 1.12159 Learning rate: 0.02 Mask loss: 0.19153 RPN box loss: 0.08569 RPN score loss: 0.01102 RPN total loss: 0.09671 Total loss: 1.7264 timestamp: 1655022878.7488027 iteration: 19435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17965 FastRCNN class loss: 0.11209 FastRCNN total loss: 0.29174 L1 loss: 0.0000e+00 L2 loss: 1.12141 Learning rate: 0.02 Mask loss: 0.1788 RPN box loss: 0.05681 RPN score loss: 0.018 RPN total loss: 0.07482 Total loss: 1.66676 timestamp: 1655022882.1305788 iteration: 19440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15391 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.25088 L1 loss: 0.0000e+00 L2 loss: 1.12118 Learning rate: 0.02 Mask loss: 0.19286 RPN box loss: 0.03801 RPN score loss: 0.00483 RPN total loss: 0.04284 Total loss: 1.60776 timestamp: 1655022885.419698 iteration: 19445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15835 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.23101 L1 loss: 0.0000e+00 L2 loss: 1.12098 Learning rate: 0.02 Mask loss: 0.20887 RPN box loss: 0.03888 RPN score loss: 0.01371 RPN total loss: 0.05259 Total loss: 1.61345 timestamp: 1655022888.7433474 iteration: 19450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04895 FastRCNN class loss: 0.05328 FastRCNN total loss: 0.10224 L1 loss: 0.0000e+00 L2 loss: 1.1208 Learning rate: 0.02 Mask loss: 0.09497 RPN box loss: 0.0283 RPN score loss: 0.00283 RPN total loss: 0.03113 Total loss: 1.34914 timestamp: 1655022892.184064 iteration: 19455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1724 FastRCNN class loss: 0.09334 FastRCNN total loss: 0.26574 L1 loss: 0.0000e+00 L2 loss: 1.12062 Learning rate: 0.02 Mask loss: 0.26313 RPN box loss: 0.04459 RPN score loss: 0.02132 RPN total loss: 0.06591 Total loss: 1.71541 timestamp: 1655022895.43294 iteration: 19460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16742 FastRCNN class loss: 0.11916 FastRCNN total loss: 0.28658 L1 loss: 0.0000e+00 L2 loss: 1.12045 Learning rate: 0.02 Mask loss: 0.16372 RPN box loss: 0.04155 RPN score loss: 0.00965 RPN total loss: 0.0512 Total loss: 1.62195 timestamp: 1655022898.7669234 iteration: 19465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11295 FastRCNN class loss: 0.05847 FastRCNN total loss: 0.17142 L1 loss: 0.0000e+00 L2 loss: 1.12026 Learning rate: 0.02 Mask loss: 0.11914 RPN box loss: 0.05956 RPN score loss: 0.02192 RPN total loss: 0.08148 Total loss: 1.49231 timestamp: 1655022901.957672 iteration: 19470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10354 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.15723 L1 loss: 0.0000e+00 L2 loss: 1.12006 Learning rate: 0.02 Mask loss: 0.09969 RPN box loss: 0.02249 RPN score loss: 0.01156 RPN total loss: 0.03406 Total loss: 1.41104 timestamp: 1655022905.2317636 iteration: 19475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15932 FastRCNN class loss: 0.2061 FastRCNN total loss: 0.36542 L1 loss: 0.0000e+00 L2 loss: 1.11985 Learning rate: 0.02 Mask loss: 0.29525 RPN box loss: 0.05583 RPN score loss: 0.12028 RPN total loss: 0.17611 Total loss: 1.95663 timestamp: 1655022908.4747062 iteration: 19480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11986 FastRCNN class loss: 0.05763 FastRCNN total loss: 0.17749 L1 loss: 0.0000e+00 L2 loss: 1.11965 Learning rate: 0.02 Mask loss: 0.21209 RPN box loss: 0.03296 RPN score loss: 0.01463 RPN total loss: 0.0476 Total loss: 1.55683 timestamp: 1655022911.9551623 iteration: 19485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1603 FastRCNN class loss: 0.09484 FastRCNN total loss: 0.25514 L1 loss: 0.0000e+00 L2 loss: 1.11948 Learning rate: 0.02 Mask loss: 0.25326 RPN box loss: 0.03915 RPN score loss: 0.00643 RPN total loss: 0.04557 Total loss: 1.67346 timestamp: 1655022915.216309 iteration: 19490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17561 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.2435 L1 loss: 0.0000e+00 L2 loss: 1.11929 Learning rate: 0.02 Mask loss: 0.21413 RPN box loss: 0.03538 RPN score loss: 0.00436 RPN total loss: 0.03973 Total loss: 1.61665 timestamp: 1655022918.4447906 iteration: 19495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24629 FastRCNN class loss: 0.13002 FastRCNN total loss: 0.37631 L1 loss: 0.0000e+00 L2 loss: 1.11909 Learning rate: 0.02 Mask loss: 0.20306 RPN box loss: 0.03976 RPN score loss: 0.01058 RPN total loss: 0.05034 Total loss: 1.7488 timestamp: 1655022921.7662923 iteration: 19500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20944 FastRCNN class loss: 0.11475 FastRCNN total loss: 0.32419 L1 loss: 0.0000e+00 L2 loss: 1.1189 Learning rate: 0.02 Mask loss: 0.251 RPN box loss: 0.03553 RPN score loss: 0.01064 RPN total loss: 0.04618 Total loss: 1.74026 timestamp: 1655022925.0331779 iteration: 19505 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16995 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.25387 L1 loss: 0.0000e+00 L2 loss: 1.11873 Learning rate: 0.02 Mask loss: 0.1298 RPN box loss: 0.05299 RPN score loss: 0.00712 RPN total loss: 0.06011 Total loss: 1.56251 timestamp: 1655022928.3619354 iteration: 19510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21692 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.2871 L1 loss: 0.0000e+00 L2 loss: 1.11855 Learning rate: 0.02 Mask loss: 0.15144 RPN box loss: 0.0218 RPN score loss: 0.00319 RPN total loss: 0.02499 Total loss: 1.58209 timestamp: 1655022931.6118586 iteration: 19515 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18079 FastRCNN class loss: 0.10013 FastRCNN total loss: 0.28092 L1 loss: 0.0000e+00 L2 loss: 1.11837 Learning rate: 0.02 Mask loss: 0.20205 RPN box loss: 0.03968 RPN score loss: 0.00681 RPN total loss: 0.04648 Total loss: 1.64782 timestamp: 1655022935.1235833 iteration: 19520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10527 FastRCNN class loss: 0.07887 FastRCNN total loss: 0.18413 L1 loss: 0.0000e+00 L2 loss: 1.11818 Learning rate: 0.02 Mask loss: 0.19833 RPN box loss: 0.0282 RPN score loss: 0.0046 RPN total loss: 0.03281 Total loss: 1.53345 timestamp: 1655022938.3495119 iteration: 19525 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0877 FastRCNN class loss: 0.07862 FastRCNN total loss: 0.16632 L1 loss: 0.0000e+00 L2 loss: 1.118 Learning rate: 0.02 Mask loss: 0.14086 RPN box loss: 0.06511 RPN score loss: 0.00601 RPN total loss: 0.07112 Total loss: 1.4963 timestamp: 1655022941.815163 iteration: 19530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18048 FastRCNN class loss: 0.06252 FastRCNN total loss: 0.243 L1 loss: 0.0000e+00 L2 loss: 1.11781 Learning rate: 0.02 Mask loss: 0.15555 RPN box loss: 0.06927 RPN score loss: 0.00531 RPN total loss: 0.07458 Total loss: 1.59094 timestamp: 1655022945.0445204 iteration: 19535 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15618 FastRCNN class loss: 0.11175 FastRCNN total loss: 0.26794 L1 loss: 0.0000e+00 L2 loss: 1.11762 Learning rate: 0.02 Mask loss: 0.19353 RPN box loss: 0.03835 RPN score loss: 0.01068 RPN total loss: 0.04903 Total loss: 1.62813 timestamp: 1655022948.3888867 iteration: 19540 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14621 FastRCNN class loss: 0.1233 FastRCNN total loss: 0.26951 L1 loss: 0.0000e+00 L2 loss: 1.11743 Learning rate: 0.02 Mask loss: 0.18526 RPN box loss: 0.01804 RPN score loss: 0.00632 RPN total loss: 0.02436 Total loss: 1.59656 timestamp: 1655022951.6836011 iteration: 19545 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1902 FastRCNN class loss: 0.13339 FastRCNN total loss: 0.32359 L1 loss: 0.0000e+00 L2 loss: 1.11723 Learning rate: 0.02 Mask loss: 0.24317 RPN box loss: 0.04572 RPN score loss: 0.0131 RPN total loss: 0.05882 Total loss: 1.74281 timestamp: 1655022954.9213364 iteration: 19550 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15571 FastRCNN class loss: 0.10119 FastRCNN total loss: 0.2569 L1 loss: 0.0000e+00 L2 loss: 1.11703 Learning rate: 0.02 Mask loss: 0.16915 RPN box loss: 0.02325 RPN score loss: 0.01064 RPN total loss: 0.03389 Total loss: 1.57698 timestamp: 1655022958.380851 iteration: 19555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20966 FastRCNN class loss: 0.11296 FastRCNN total loss: 0.32262 L1 loss: 0.0000e+00 L2 loss: 1.11686 Learning rate: 0.02 Mask loss: 0.17696 RPN box loss: 0.0854 RPN score loss: 0.01018 RPN total loss: 0.09558 Total loss: 1.71202 timestamp: 1655022961.743115 iteration: 19560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13591 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.2194 L1 loss: 0.0000e+00 L2 loss: 1.11667 Learning rate: 0.02 Mask loss: 0.14602 RPN box loss: 0.02725 RPN score loss: 0.00586 RPN total loss: 0.03311 Total loss: 1.5152 timestamp: 1655022965.0462682 iteration: 19565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1319 FastRCNN class loss: 0.05817 FastRCNN total loss: 0.19007 L1 loss: 0.0000e+00 L2 loss: 1.11649 Learning rate: 0.02 Mask loss: 0.10735 RPN box loss: 0.02524 RPN score loss: 0.00192 RPN total loss: 0.02716 Total loss: 1.44106 timestamp: 1655022968.347106 iteration: 19570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16712 FastRCNN class loss: 0.1319 FastRCNN total loss: 0.29902 L1 loss: 0.0000e+00 L2 loss: 1.1163 Learning rate: 0.02 Mask loss: 0.1804 RPN box loss: 0.03806 RPN score loss: 0.00843 RPN total loss: 0.04648 Total loss: 1.6422 timestamp: 1655022971.6932368 iteration: 19575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.07653 FastRCNN total loss: 0.18604 L1 loss: 0.0000e+00 L2 loss: 1.11611 Learning rate: 0.02 Mask loss: 0.13531 RPN box loss: 0.05761 RPN score loss: 0.00715 RPN total loss: 0.06477 Total loss: 1.50222 timestamp: 1655022974.9749866 iteration: 19580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2011 FastRCNN class loss: 0.08782 FastRCNN total loss: 0.28892 L1 loss: 0.0000e+00 L2 loss: 1.11589 Learning rate: 0.02 Mask loss: 0.1597 RPN box loss: 0.03966 RPN score loss: 0.01054 RPN total loss: 0.05019 Total loss: 1.6147 timestamp: 1655022978.3947604 iteration: 19585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24781 FastRCNN class loss: 0.10419 FastRCNN total loss: 0.35201 L1 loss: 0.0000e+00 L2 loss: 1.1157 Learning rate: 0.02 Mask loss: 0.19775 RPN box loss: 0.02263 RPN score loss: 0.0125 RPN total loss: 0.03513 Total loss: 1.70058 timestamp: 1655022981.7161055 iteration: 19590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12106 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.19424 L1 loss: 0.0000e+00 L2 loss: 1.11552 Learning rate: 0.02 Mask loss: 0.13627 RPN box loss: 0.01378 RPN score loss: 0.00743 RPN total loss: 0.02121 Total loss: 1.46725 timestamp: 1655022985.015317 iteration: 19595 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30746 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.3976 L1 loss: 0.0000e+00 L2 loss: 1.11532 Learning rate: 0.02 Mask loss: 0.16903 RPN box loss: 0.03847 RPN score loss: 0.00982 RPN total loss: 0.04829 Total loss: 1.73025 timestamp: 1655022988.4738922 iteration: 19600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12602 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.21306 L1 loss: 0.0000e+00 L2 loss: 1.11514 Learning rate: 0.02 Mask loss: 0.16786 RPN box loss: 0.02985 RPN score loss: 0.00483 RPN total loss: 0.03468 Total loss: 1.53073 timestamp: 1655022991.74658 iteration: 19605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2034 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.28005 L1 loss: 0.0000e+00 L2 loss: 1.11496 Learning rate: 0.02 Mask loss: 0.1809 RPN box loss: 0.06769 RPN score loss: 0.00735 RPN total loss: 0.07504 Total loss: 1.65096 timestamp: 1655022995.058908 iteration: 19610 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16881 FastRCNN class loss: 0.14335 FastRCNN total loss: 0.31216 L1 loss: 0.0000e+00 L2 loss: 1.11478 Learning rate: 0.02 Mask loss: 0.17271 RPN box loss: 0.05338 RPN score loss: 0.02061 RPN total loss: 0.074 Total loss: 1.67365 timestamp: 1655022998.326625 iteration: 19615 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13093 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.19445 L1 loss: 0.0000e+00 L2 loss: 1.11458 Learning rate: 0.02 Mask loss: 0.09746 RPN box loss: 0.0273 RPN score loss: 0.00495 RPN total loss: 0.03225 Total loss: 1.43873 timestamp: 1655023001.6975462 iteration: 19620 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.03624 FastRCNN total loss: 0.12342 L1 loss: 0.0000e+00 L2 loss: 1.11439 Learning rate: 0.02 Mask loss: 0.09366 RPN box loss: 0.0197 RPN score loss: 0.00188 RPN total loss: 0.02158 Total loss: 1.35305 timestamp: 1655023005.028225 iteration: 19625 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17116 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.23192 L1 loss: 0.0000e+00 L2 loss: 1.11418 Learning rate: 0.02 Mask loss: 0.14898 RPN box loss: 0.01248 RPN score loss: 0.00663 RPN total loss: 0.01911 Total loss: 1.5142 timestamp: 1655023008.4823792 iteration: 19630 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23981 FastRCNN class loss: 0.10854 FastRCNN total loss: 0.34835 L1 loss: 0.0000e+00 L2 loss: 1.11398 Learning rate: 0.02 Mask loss: 0.20422 RPN box loss: 0.03978 RPN score loss: 0.01032 RPN total loss: 0.05009 Total loss: 1.71665 timestamp: 1655023011.8941994 iteration: 19635 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14516 FastRCNN class loss: 0.09922 FastRCNN total loss: 0.24438 L1 loss: 0.0000e+00 L2 loss: 1.11381 Learning rate: 0.02 Mask loss: 0.16855 RPN box loss: 0.01639 RPN score loss: 0.00758 RPN total loss: 0.02397 Total loss: 1.55072 timestamp: 1655023015.2123075 iteration: 19640 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1451 FastRCNN class loss: 0.0535 FastRCNN total loss: 0.1986 L1 loss: 0.0000e+00 L2 loss: 1.11364 Learning rate: 0.02 Mask loss: 0.16294 RPN box loss: 0.03761 RPN score loss: 0.00775 RPN total loss: 0.04536 Total loss: 1.52054 timestamp: 1655023018.550234 iteration: 19645 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15898 FastRCNN class loss: 0.10074 FastRCNN total loss: 0.25973 L1 loss: 0.0000e+00 L2 loss: 1.11344 Learning rate: 0.02 Mask loss: 0.14455 RPN box loss: 0.03104 RPN score loss: 0.00891 RPN total loss: 0.03995 Total loss: 1.55766 timestamp: 1655023021.922324 iteration: 19650 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.08854 FastRCNN total loss: 0.18335 L1 loss: 0.0000e+00 L2 loss: 1.11325 Learning rate: 0.02 Mask loss: 0.18002 RPN box loss: 0.03243 RPN score loss: 0.01058 RPN total loss: 0.04301 Total loss: 1.51963 timestamp: 1655023025.2506964 iteration: 19655 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16083 FastRCNN class loss: 0.09435 FastRCNN total loss: 0.25517 L1 loss: 0.0000e+00 L2 loss: 1.11305 Learning rate: 0.02 Mask loss: 0.22169 RPN box loss: 0.04215 RPN score loss: 0.00478 RPN total loss: 0.04694 Total loss: 1.63685 timestamp: 1655023028.5435586 iteration: 19660 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14572 FastRCNN class loss: 0.16774 FastRCNN total loss: 0.31346 L1 loss: 0.0000e+00 L2 loss: 1.11286 Learning rate: 0.02 Mask loss: 0.17185 RPN box loss: 0.05629 RPN score loss: 0.00474 RPN total loss: 0.06103 Total loss: 1.6592 timestamp: 1655023031.9180624 iteration: 19665 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15969 FastRCNN class loss: 0.10451 FastRCNN total loss: 0.2642 L1 loss: 0.0000e+00 L2 loss: 1.11268 Learning rate: 0.02 Mask loss: 0.22049 RPN box loss: 0.05866 RPN score loss: 0.00901 RPN total loss: 0.06767 Total loss: 1.66504 timestamp: 1655023035.1825116 iteration: 19670 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18545 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.25069 L1 loss: 0.0000e+00 L2 loss: 1.11249 Learning rate: 0.02 Mask loss: 0.16174 RPN box loss: 0.03068 RPN score loss: 0.00438 RPN total loss: 0.03506 Total loss: 1.55999 timestamp: 1655023038.53292 iteration: 19675 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11244 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.18612 L1 loss: 0.0000e+00 L2 loss: 1.1123 Learning rate: 0.02 Mask loss: 0.19645 RPN box loss: 0.0223 RPN score loss: 0.00319 RPN total loss: 0.02549 Total loss: 1.52037 timestamp: 1655023041.9686868 iteration: 19680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22149 FastRCNN class loss: 0.068 FastRCNN total loss: 0.28949 L1 loss: 0.0000e+00 L2 loss: 1.11212 Learning rate: 0.02 Mask loss: 0.18039 RPN box loss: 0.01026 RPN score loss: 0.00542 RPN total loss: 0.01568 Total loss: 1.59767 timestamp: 1655023045.3208344 iteration: 19685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10521 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.16106 L1 loss: 0.0000e+00 L2 loss: 1.11191 Learning rate: 0.02 Mask loss: 0.15188 RPN box loss: 0.02716 RPN score loss: 0.00289 RPN total loss: 0.03004 Total loss: 1.45489 timestamp: 1655023048.630859 iteration: 19690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10632 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.17946 L1 loss: 0.0000e+00 L2 loss: 1.11172 Learning rate: 0.02 Mask loss: 0.15769 RPN box loss: 0.0386 RPN score loss: 0.00304 RPN total loss: 0.04164 Total loss: 1.49051 timestamp: 1655023051.8764062 iteration: 19695 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14916 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.20876 L1 loss: 0.0000e+00 L2 loss: 1.11154 Learning rate: 0.02 Mask loss: 0.16771 RPN box loss: 0.00561 RPN score loss: 0.00246 RPN total loss: 0.00807 Total loss: 1.49607 timestamp: 1655023055.2585335 iteration: 19700 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18788 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.2743 L1 loss: 0.0000e+00 L2 loss: 1.11137 Learning rate: 0.02 Mask loss: 0.0822 RPN box loss: 0.01177 RPN score loss: 0.00459 RPN total loss: 0.01636 Total loss: 1.48422 timestamp: 1655023058.5455513 iteration: 19705 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08268 FastRCNN class loss: 0.07805 FastRCNN total loss: 0.16073 L1 loss: 0.0000e+00 L2 loss: 1.11117 Learning rate: 0.02 Mask loss: 0.15058 RPN box loss: 0.02599 RPN score loss: 0.00507 RPN total loss: 0.03106 Total loss: 1.45354 timestamp: 1655023061.8900163 iteration: 19710 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16832 FastRCNN class loss: 0.07866 FastRCNN total loss: 0.24697 L1 loss: 0.0000e+00 L2 loss: 1.11097 Learning rate: 0.02 Mask loss: 0.12861 RPN box loss: 0.03405 RPN score loss: 0.00518 RPN total loss: 0.03923 Total loss: 1.52577 timestamp: 1655023065.1896262 iteration: 19715 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.166 FastRCNN class loss: 0.11767 FastRCNN total loss: 0.28367 L1 loss: 0.0000e+00 L2 loss: 1.11078 Learning rate: 0.02 Mask loss: 0.20902 RPN box loss: 0.0319 RPN score loss: 0.01625 RPN total loss: 0.04815 Total loss: 1.65161 timestamp: 1655023068.5134797 iteration: 19720 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24206 FastRCNN class loss: 0.11895 FastRCNN total loss: 0.361 L1 loss: 0.0000e+00 L2 loss: 1.11057 Learning rate: 0.02 Mask loss: 0.22542 RPN box loss: 0.03705 RPN score loss: 0.01395 RPN total loss: 0.05101 Total loss: 1.748 timestamp: 1655023071.9033277 iteration: 19725 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1705 FastRCNN class loss: 0.08394 FastRCNN total loss: 0.25444 L1 loss: 0.0000e+00 L2 loss: 1.11036 Learning rate: 0.02 Mask loss: 0.18635 RPN box loss: 0.06523 RPN score loss: 0.00443 RPN total loss: 0.06967 Total loss: 1.62082 timestamp: 1655023075.184168 iteration: 19730 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05912 FastRCNN class loss: 0.03856 FastRCNN total loss: 0.09768 L1 loss: 0.0000e+00 L2 loss: 1.11017 Learning rate: 0.02 Mask loss: 0.11938 RPN box loss: 0.00398 RPN score loss: 0.00154 RPN total loss: 0.00552 Total loss: 1.33275 timestamp: 1655023078.4198818 iteration: 19735 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06509 FastRCNN class loss: 0.05265 FastRCNN total loss: 0.11774 L1 loss: 0.0000e+00 L2 loss: 1.10999 Learning rate: 0.02 Mask loss: 0.16957 RPN box loss: 0.02051 RPN score loss: 0.00532 RPN total loss: 0.02582 Total loss: 1.42311 timestamp: 1655023081.7022066 iteration: 19740 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.12689 FastRCNN total loss: 0.2318 L1 loss: 0.0000e+00 L2 loss: 1.10982 Learning rate: 0.02 Mask loss: 0.18683 RPN box loss: 0.07229 RPN score loss: 0.05298 RPN total loss: 0.12527 Total loss: 1.65372 timestamp: 1655023085.0310304 iteration: 19745 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.16163 L1 loss: 0.0000e+00 L2 loss: 1.10963 Learning rate: 0.02 Mask loss: 0.20838 RPN box loss: 0.0388 RPN score loss: 0.0099 RPN total loss: 0.0487 Total loss: 1.52834 timestamp: 1655023088.3191319 iteration: 19750 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13841 FastRCNN class loss: 0.11808 FastRCNN total loss: 0.2565 L1 loss: 0.0000e+00 L2 loss: 1.10944 Learning rate: 0.02 Mask loss: 0.2377 RPN box loss: 0.03646 RPN score loss: 0.01418 RPN total loss: 0.05065 Total loss: 1.65429 timestamp: 1655023091.6599603 iteration: 19755 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08999 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.17188 L1 loss: 0.0000e+00 L2 loss: 1.10926 Learning rate: 0.02 Mask loss: 0.14236 RPN box loss: 0.05383 RPN score loss: 0.00507 RPN total loss: 0.05891 Total loss: 1.48241 timestamp: 1655023095.0123956 iteration: 19760 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08673 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 1.10907 Learning rate: 0.02 Mask loss: 0.14666 RPN box loss: 0.0775 RPN score loss: 0.01167 RPN total loss: 0.08917 Total loss: 1.51616 timestamp: 1655023098.3626645 iteration: 19765 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.13177 FastRCNN total loss: 0.28055 L1 loss: 0.0000e+00 L2 loss: 1.10889 Learning rate: 0.02 Mask loss: 0.26993 RPN box loss: 0.05468 RPN score loss: 0.01562 RPN total loss: 0.0703 Total loss: 1.72967 timestamp: 1655023101.7083905 iteration: 19770 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21678 FastRCNN class loss: 0.09449 FastRCNN total loss: 0.31127 L1 loss: 0.0000e+00 L2 loss: 1.10871 Learning rate: 0.02 Mask loss: 0.16692 RPN box loss: 0.01975 RPN score loss: 0.00485 RPN total loss: 0.0246 Total loss: 1.6115 timestamp: 1655023105.0630994 iteration: 19775 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22312 FastRCNN class loss: 0.09882 FastRCNN total loss: 0.32194 L1 loss: 0.0000e+00 L2 loss: 1.10854 Learning rate: 0.02 Mask loss: 0.20565 RPN box loss: 0.06166 RPN score loss: 0.00631 RPN total loss: 0.06797 Total loss: 1.7041 timestamp: 1655023108.5535984 iteration: 19780 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10965 FastRCNN class loss: 0.1103 FastRCNN total loss: 0.21995 L1 loss: 0.0000e+00 L2 loss: 1.10832 Learning rate: 0.02 Mask loss: 0.13422 RPN box loss: 0.08037 RPN score loss: 0.00717 RPN total loss: 0.08755 Total loss: 1.55004 timestamp: 1655023111.8400667 iteration: 19785 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17313 FastRCNN class loss: 0.11647 FastRCNN total loss: 0.28959 L1 loss: 0.0000e+00 L2 loss: 1.10812 Learning rate: 0.02 Mask loss: 0.29307 RPN box loss: 0.05842 RPN score loss: 0.00979 RPN total loss: 0.06821 Total loss: 1.759 timestamp: 1655023115.1969602 iteration: 19790 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16279 FastRCNN class loss: 0.0732 FastRCNN total loss: 0.23599 L1 loss: 0.0000e+00 L2 loss: 1.10792 Learning rate: 0.02 Mask loss: 0.19349 RPN box loss: 0.0091 RPN score loss: 0.00677 RPN total loss: 0.01587 Total loss: 1.55326 timestamp: 1655023118.4211605 iteration: 19795 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25454 FastRCNN class loss: 0.20666 FastRCNN total loss: 0.46119 L1 loss: 0.0000e+00 L2 loss: 1.10774 Learning rate: 0.02 Mask loss: 0.2692 RPN box loss: 0.10582 RPN score loss: 0.01857 RPN total loss: 0.12439 Total loss: 1.96252 timestamp: 1655023121.857467 iteration: 19800 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12012 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.19183 L1 loss: 0.0000e+00 L2 loss: 1.10756 Learning rate: 0.02 Mask loss: 0.14358 RPN box loss: 0.04528 RPN score loss: 0.00556 RPN total loss: 0.05084 Total loss: 1.49381 timestamp: 1655023125.2292864 iteration: 19805 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18765 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.23546 L1 loss: 0.0000e+00 L2 loss: 1.10739 Learning rate: 0.02 Mask loss: 0.1193 RPN box loss: 0.00522 RPN score loss: 0.00283 RPN total loss: 0.00805 Total loss: 1.4702 timestamp: 1655023128.4743938 iteration: 19810 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11713 FastRCNN class loss: 0.07696 FastRCNN total loss: 0.1941 L1 loss: 0.0000e+00 L2 loss: 1.1072 Learning rate: 0.02 Mask loss: 0.12381 RPN box loss: 0.05296 RPN score loss: 0.00625 RPN total loss: 0.05921 Total loss: 1.48432 timestamp: 1655023131.9595027 iteration: 19815 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11975 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.20655 L1 loss: 0.0000e+00 L2 loss: 1.10702 Learning rate: 0.02 Mask loss: 0.12575 RPN box loss: 0.04442 RPN score loss: 0.01674 RPN total loss: 0.06116 Total loss: 1.50047 timestamp: 1655023135.2868102 iteration: 19820 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18663 FastRCNN class loss: 0.097 FastRCNN total loss: 0.28362 L1 loss: 0.0000e+00 L2 loss: 1.10685 Learning rate: 0.02 Mask loss: 0.2289 RPN box loss: 0.0404 RPN score loss: 0.00967 RPN total loss: 0.05007 Total loss: 1.66944 timestamp: 1655023138.7916806 iteration: 19825 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24844 FastRCNN class loss: 0.10377 FastRCNN total loss: 0.35221 L1 loss: 0.0000e+00 L2 loss: 1.10666 Learning rate: 0.02 Mask loss: 0.20555 RPN box loss: 0.02249 RPN score loss: 0.00898 RPN total loss: 0.03148 Total loss: 1.69589 timestamp: 1655023142.139355 iteration: 19830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05746 FastRCNN class loss: 0.04229 FastRCNN total loss: 0.09975 L1 loss: 0.0000e+00 L2 loss: 1.10648 Learning rate: 0.02 Mask loss: 0.11651 RPN box loss: 0.0175 RPN score loss: 0.0139 RPN total loss: 0.0314 Total loss: 1.35413 timestamp: 1655023145.5400763 iteration: 19835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1954 FastRCNN class loss: 0.10457 FastRCNN total loss: 0.29997 L1 loss: 0.0000e+00 L2 loss: 1.1063 Learning rate: 0.02 Mask loss: 0.27607 RPN box loss: 0.01639 RPN score loss: 0.00451 RPN total loss: 0.0209 Total loss: 1.70324 timestamp: 1655023148.8459973 iteration: 19840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10615 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.18777 L1 loss: 0.0000e+00 L2 loss: 1.10614 Learning rate: 0.02 Mask loss: 0.20199 RPN box loss: 0.02681 RPN score loss: 0.00634 RPN total loss: 0.03315 Total loss: 1.52905 timestamp: 1655023152.1224325 iteration: 19845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1743 FastRCNN class loss: 0.09323 FastRCNN total loss: 0.26752 L1 loss: 0.0000e+00 L2 loss: 1.10596 Learning rate: 0.02 Mask loss: 0.12502 RPN box loss: 0.02197 RPN score loss: 0.02233 RPN total loss: 0.04429 Total loss: 1.5428 timestamp: 1655023155.4961329 iteration: 19850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13472 FastRCNN class loss: 0.077 FastRCNN total loss: 0.21171 L1 loss: 0.0000e+00 L2 loss: 1.10572 Learning rate: 0.02 Mask loss: 0.14451 RPN box loss: 0.13439 RPN score loss: 0.00637 RPN total loss: 0.14076 Total loss: 1.60271 timestamp: 1655023158.7625904 iteration: 19855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17488 FastRCNN class loss: 0.10813 FastRCNN total loss: 0.28302 L1 loss: 0.0000e+00 L2 loss: 1.10554 Learning rate: 0.02 Mask loss: 0.15395 RPN box loss: 0.02876 RPN score loss: 0.00908 RPN total loss: 0.03785 Total loss: 1.58036 timestamp: 1655023162.0791533 iteration: 19860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12627 FastRCNN class loss: 0.05123 FastRCNN total loss: 0.1775 L1 loss: 0.0000e+00 L2 loss: 1.10534 Learning rate: 0.02 Mask loss: 0.14969 RPN box loss: 0.03634 RPN score loss: 0.00475 RPN total loss: 0.04108 Total loss: 1.47362 timestamp: 1655023165.3958032 iteration: 19865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19706 FastRCNN class loss: 0.10848 FastRCNN total loss: 0.30555 L1 loss: 0.0000e+00 L2 loss: 1.10516 Learning rate: 0.02 Mask loss: 0.21122 RPN box loss: 0.02569 RPN score loss: 0.00396 RPN total loss: 0.02965 Total loss: 1.65158 timestamp: 1655023168.742179 iteration: 19870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15333 FastRCNN class loss: 0.09638 FastRCNN total loss: 0.24971 L1 loss: 0.0000e+00 L2 loss: 1.10499 Learning rate: 0.02 Mask loss: 0.1639 RPN box loss: 0.03911 RPN score loss: 0.01056 RPN total loss: 0.04968 Total loss: 1.56827 timestamp: 1655023171.9533007 iteration: 19875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19782 FastRCNN class loss: 0.09165 FastRCNN total loss: 0.28947 L1 loss: 0.0000e+00 L2 loss: 1.10479 Learning rate: 0.02 Mask loss: 0.16995 RPN box loss: 0.05904 RPN score loss: 0.02072 RPN total loss: 0.07976 Total loss: 1.64397 timestamp: 1655023175.387596 iteration: 19880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15719 FastRCNN class loss: 0.08741 FastRCNN total loss: 0.2446 L1 loss: 0.0000e+00 L2 loss: 1.10461 Learning rate: 0.02 Mask loss: 0.21354 RPN box loss: 0.02127 RPN score loss: 0.00764 RPN total loss: 0.02891 Total loss: 1.59166 timestamp: 1655023178.7003384 iteration: 19885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18592 FastRCNN class loss: 0.0887 FastRCNN total loss: 0.27462 L1 loss: 0.0000e+00 L2 loss: 1.10443 Learning rate: 0.02 Mask loss: 0.18314 RPN box loss: 0.04096 RPN score loss: 0.00731 RPN total loss: 0.04827 Total loss: 1.61046 timestamp: 1655023182.0489652 iteration: 19890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16861 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.29807 L1 loss: 0.0000e+00 L2 loss: 1.10425 Learning rate: 0.02 Mask loss: 0.15971 RPN box loss: 0.06118 RPN score loss: 0.0113 RPN total loss: 0.07248 Total loss: 1.63452 timestamp: 1655023185.3989844 iteration: 19895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2103 FastRCNN class loss: 0.05142 FastRCNN total loss: 0.26172 L1 loss: 0.0000e+00 L2 loss: 1.10406 Learning rate: 0.02 Mask loss: 0.17897 RPN box loss: 0.03263 RPN score loss: 0.00193 RPN total loss: 0.03457 Total loss: 1.57931 timestamp: 1655023188.675325 iteration: 19900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12334 FastRCNN class loss: 0.10387 FastRCNN total loss: 0.22721 L1 loss: 0.0000e+00 L2 loss: 1.10386 Learning rate: 0.02 Mask loss: 0.17477 RPN box loss: 0.02064 RPN score loss: 0.00619 RPN total loss: 0.02683 Total loss: 1.53267 timestamp: 1655023192.0832436 iteration: 19905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26557 FastRCNN class loss: 0.1671 FastRCNN total loss: 0.43267 L1 loss: 0.0000e+00 L2 loss: 1.10368 Learning rate: 0.02 Mask loss: 0.38512 RPN box loss: 0.03784 RPN score loss: 0.01975 RPN total loss: 0.05759 Total loss: 1.97906 timestamp: 1655023195.40768 iteration: 19910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16142 FastRCNN class loss: 0.09376 FastRCNN total loss: 0.25518 L1 loss: 0.0000e+00 L2 loss: 1.10349 Learning rate: 0.02 Mask loss: 0.18723 RPN box loss: 0.03265 RPN score loss: 0.00552 RPN total loss: 0.03817 Total loss: 1.58408 timestamp: 1655023198.737732 iteration: 19915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14229 FastRCNN class loss: 0.07609 FastRCNN total loss: 0.21838 L1 loss: 0.0000e+00 L2 loss: 1.1033 Learning rate: 0.02 Mask loss: 0.1865 RPN box loss: 0.08871 RPN score loss: 0.01506 RPN total loss: 0.10376 Total loss: 1.61195 timestamp: 1655023202.023662 iteration: 19920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.15683 L1 loss: 0.0000e+00 L2 loss: 1.10311 Learning rate: 0.02 Mask loss: 0.11581 RPN box loss: 0.02897 RPN score loss: 0.00945 RPN total loss: 0.03841 Total loss: 1.41417 timestamp: 1655023205.387647 iteration: 19925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21942 FastRCNN class loss: 0.109 FastRCNN total loss: 0.32842 L1 loss: 0.0000e+00 L2 loss: 1.10295 Learning rate: 0.02 Mask loss: 0.2603 RPN box loss: 0.0571 RPN score loss: 0.01113 RPN total loss: 0.06822 Total loss: 1.75989 timestamp: 1655023208.8061554 iteration: 19930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21807 FastRCNN class loss: 0.11179 FastRCNN total loss: 0.32986 L1 loss: 0.0000e+00 L2 loss: 1.10277 Learning rate: 0.02 Mask loss: 0.20775 RPN box loss: 0.02922 RPN score loss: 0.00991 RPN total loss: 0.03912 Total loss: 1.67951 timestamp: 1655023212.06165 iteration: 19935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21491 FastRCNN class loss: 0.08535 FastRCNN total loss: 0.30025 L1 loss: 0.0000e+00 L2 loss: 1.10257 Learning rate: 0.02 Mask loss: 0.17025 RPN box loss: 0.03851 RPN score loss: 0.00661 RPN total loss: 0.04512 Total loss: 1.61819 timestamp: 1655023215.413357 iteration: 19940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19582 FastRCNN class loss: 0.14659 FastRCNN total loss: 0.34241 L1 loss: 0.0000e+00 L2 loss: 1.10239 Learning rate: 0.02 Mask loss: 0.23487 RPN box loss: 0.0238 RPN score loss: 0.01363 RPN total loss: 0.03744 Total loss: 1.7171 timestamp: 1655023218.6260564 iteration: 19945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13252 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.20933 L1 loss: 0.0000e+00 L2 loss: 1.10221 Learning rate: 0.02 Mask loss: 0.13958 RPN box loss: 0.026 RPN score loss: 0.00375 RPN total loss: 0.02976 Total loss: 1.48087 timestamp: 1655023221.9631758 iteration: 19950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21267 FastRCNN class loss: 0.11363 FastRCNN total loss: 0.3263 L1 loss: 0.0000e+00 L2 loss: 1.10201 Learning rate: 0.02 Mask loss: 0.1851 RPN box loss: 0.03523 RPN score loss: 0.00284 RPN total loss: 0.03808 Total loss: 1.65148 timestamp: 1655023225.1985955 iteration: 19955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12455 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.20306 L1 loss: 0.0000e+00 L2 loss: 1.10181 Learning rate: 0.02 Mask loss: 0.17781 RPN box loss: 0.00501 RPN score loss: 0.00646 RPN total loss: 0.01146 Total loss: 1.49414 timestamp: 1655023228.60248 iteration: 19960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18026 FastRCNN class loss: 0.06114 FastRCNN total loss: 0.2414 L1 loss: 0.0000e+00 L2 loss: 1.10164 Learning rate: 0.02 Mask loss: 0.13395 RPN box loss: 0.06866 RPN score loss: 0.00727 RPN total loss: 0.07593 Total loss: 1.55291 timestamp: 1655023231.841698 iteration: 19965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10199 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 1.10145 Learning rate: 0.02 Mask loss: 0.11501 RPN box loss: 0.02968 RPN score loss: 0.00268 RPN total loss: 0.03236 Total loss: 1.41525 timestamp: 1655023235.2271225 iteration: 19970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17306 FastRCNN class loss: 0.13153 FastRCNN total loss: 0.30459 L1 loss: 0.0000e+00 L2 loss: 1.10126 Learning rate: 0.02 Mask loss: 0.18689 RPN box loss: 0.0724 RPN score loss: 0.00934 RPN total loss: 0.08174 Total loss: 1.67448 timestamp: 1655023238.6727011 iteration: 19975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09137 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.16194 L1 loss: 0.0000e+00 L2 loss: 1.10106 Learning rate: 0.02 Mask loss: 0.12201 RPN box loss: 0.00884 RPN score loss: 0.00266 RPN total loss: 0.0115 Total loss: 1.3965 timestamp: 1655023241.9783423 iteration: 19980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16608 FastRCNN class loss: 0.11351 FastRCNN total loss: 0.27959 L1 loss: 0.0000e+00 L2 loss: 1.10088 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.07801 RPN score loss: 0.00635 RPN total loss: 0.08436 Total loss: 1.61195 timestamp: 1655023245.447164 iteration: 19985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16371 FastRCNN class loss: 0.0925 FastRCNN total loss: 0.25621 L1 loss: 0.0000e+00 L2 loss: 1.10067 Learning rate: 0.02 Mask loss: 0.26242 RPN box loss: 0.04574 RPN score loss: 0.01003 RPN total loss: 0.05577 Total loss: 1.67507 timestamp: 1655023248.7617352 iteration: 19990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17762 FastRCNN class loss: 0.10134 FastRCNN total loss: 0.27897 L1 loss: 0.0000e+00 L2 loss: 1.10049 Learning rate: 0.02 Mask loss: 0.12872 RPN box loss: 0.00882 RPN score loss: 0.00144 RPN total loss: 0.01026 Total loss: 1.51843 timestamp: 1655023252.019212 iteration: 19995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20047 FastRCNN class loss: 0.12198 FastRCNN total loss: 0.32244 L1 loss: 0.0000e+00 L2 loss: 1.10033 Learning rate: 0.02 Mask loss: 0.28637 RPN box loss: 0.06782 RPN score loss: 0.01228 RPN total loss: 0.0801 Total loss: 1.78924 timestamp: 1655023255.3181965 iteration: 20000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17463 FastRCNN class loss: 0.10256 FastRCNN total loss: 0.27719 L1 loss: 0.0000e+00 L2 loss: 1.10013 Learning rate: 0.02 Mask loss: 0.22637 RPN box loss: 0.03233 RPN score loss: 0.00595 RPN total loss: 0.03828 Total loss: 1.64197 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.8510s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.8128s - Throughput: 4.9 imgs/s Running inference on batch 003/125... - Step Time: 0.8300s - Throughput: 4.8 imgs/s Running inference on batch 004/125... - Step Time: 0.8354s - Throughput: 4.8 imgs/s Running inference on batch 005/125... - Step Time: 0.7949s - Throughput: 5.0 imgs/s Running inference on batch 006/125... - Step Time: 0.8414s - Throughput: 4.8 imgs/s Running inference on batch 007/125... - Step Time: 0.8215s - Throughput: 4.9 imgs/s Running inference on batch 008/125... - Step Time: 0.8751s - Throughput: 4.6 imgs/s Running inference on batch 009/125... - Step Time: 0.9020s - Throughput: 4.4 imgs/s Running inference on batch 010/125... - Step Time: 0.8006s - Throughput: 5.0 imgs/s Running inference on batch 011/125... - Step Time: 0.8506s - Throughput: 4.7 imgs/s Running inference on batch 012/125... - Step Time: 0.8250s - Throughput: 4.8 imgs/s Running inference on batch 013/125... - Step Time: 0.8301s - Throughput: 4.8 imgs/s Running inference on batch 014/125... - Step Time: 0.7974s - Throughput: 5.0 imgs/s Running inference on batch 015/125... - Step Time: 0.8036s - Throughput: 5.0 imgs/s Running inference on batch 016/125... - Step Time: 0.7996s - Throughput: 5.0 imgs/s Running inference on batch 017/125... - Step Time: 0.8102s - Throughput: 4.9 imgs/s Running inference on batch 018/125... - Step Time: 0.7900s - Throughput: 5.1 imgs/s Running inference on batch 019/125... - Step Time: 0.8439s - Throughput: 4.7 imgs/s Running inference on batch 020/125... - Step Time: 0.8096s - Throughput: 4.9 imgs/s Running inference on batch 021/125... - Step Time: 0.8072s - Throughput: 5.0 imgs/s Running inference on batch 022/125... - Step Time: 0.8749s - Throughput: 4.6 imgs/s Running inference on batch 023/125... - Step Time: 0.8454s - Throughput: 4.7 imgs/s Running inference on batch 024/125... - Step Time: 0.7741s - Throughput: 5.2 imgs/s Running inference on batch 025/125... - Step Time: 0.8290s - Throughput: 4.8 imgs/s Running inference on batch 026/125... - Step Time: 0.8236s - Throughput: 4.9 imgs/s Running inference on batch 027/125... - Step Time: 0.7905s - Throughput: 5.1 imgs/s Running inference on batch 028/125... - Step Time: 0.8136s - Throughput: 4.9 imgs/s Running inference on batch 029/125... - Step Time: 0.8119s - Throughput: 4.9 imgs/s Running inference on batch 030/125... - Step Time: 0.8501s - Throughput: 4.7 imgs/s Running inference on batch 031/125... - Step Time: 0.8334s - Throughput: 4.8 imgs/s Running inference on batch 032/125... - Step Time: 0.8896s - Throughput: 4.5 imgs/s Running inference on batch 033/125... - Step Time: 0.8472s - Throughput: 4.7 imgs/s Running inference on batch 034/125... - Step Time: 0.8628s - Throughput: 4.6 imgs/s Running inference on batch 035/125... - Step Time: 0.7888s - Throughput: 5.1 imgs/s Running inference on batch 036/125... - Step Time: 0.8277s - Throughput: 4.8 imgs/s Running inference on batch 037/125... - Step Time: 0.8422s - Throughput: 4.7 imgs/s Running inference on batch 038/125... - Step Time: 0.7989s - Throughput: 5.0 imgs/s Running inference on batch 039/125... - Step Time: 0.8452s - Throughput: 4.7 imgs/s Running inference on batch 040/125... - Step Time: 0.6336s - Throughput: 6.3 imgs/s Running inference on batch 041/125... - Step Time: 0.8677s - Throughput: 4.6 imgs/s Running inference on batch 042/125... - Step Time: 0.8345s - Throughput: 4.8 imgs/s Running inference on batch 043/125... - Step Time: 0.7909s - Throughput: 5.1 imgs/s Running inference on batch 044/125... - Step Time: 0.8416s - Throughput: 4.8 imgs/s Running inference on batch 045/125... - Step Time: 0.8459s - Throughput: 4.7 imgs/s Running inference on batch 046/125... - Step Time: 0.8368s - Throughput: 4.8 imgs/s Running inference on batch 047/125... - Step Time: 0.8346s - Throughput: 4.8 imgs/s Running inference on batch 048/125... - Step Time: 0.8840s - Throughput: 4.5 imgs/s Running inference on batch 049/125... - Step Time: 0.8474s - Throughput: 4.7 imgs/s Running inference on batch 050/125... - Step Time: 0.8411s - Throughput: 4.8 imgs/s Running inference on batch 051/125... - Step Time: 0.8498s - Throughput: 4.7 imgs/s Running inference on batch 052/125... - Step Time: 0.7781s - Throughput: 5.1 imgs/s Running inference on batch 053/125... - Step Time: 0.8736s - Throughput: 4.6 imgs/s Running inference on batch 054/125... - Step Time: 0.8121s - Throughput: 4.9 imgs/s Running inference on batch 055/125... - Step Time: 0.8043s - Throughput: 5.0 imgs/s Running inference on batch 056/125... - Step Time: 0.8102s - Throughput: 4.9 imgs/s Running inference on batch 057/125... - Step Time: 0.8009s - Throughput: 5.0 imgs/s Running inference on batch 058/125... - Step Time: 0.8143s - Throughput: 4.9 imgs/s Running inference on batch 059/125... - Step Time: 0.8236s - Throughput: 4.9 imgs/s Running inference on batch 060/125... - Step Time: 0.8253s - Throughput: 4.8 imgs/s Running inference on batch 061/125... - Step Time: 0.8137s - Throughput: 4.9 imgs/s Running inference on batch 062/125... - Step Time: 0.8706s - Throughput: 4.6 imgs/s Running inference on batch 063/125... - Step Time: 0.8236s - Throughput: 4.9 imgs/s Running inference on batch 064/125... - Step Time: 0.8508s - Throughput: 4.7 imgs/s Running inference on batch 065/125... - Step Time: 0.8378s - Throughput: 4.8 imgs/s Running inference on batch 066/125... - Step Time: 0.8240s - Throughput: 4.9 imgs/s Running inference on batch 067/125... - Step Time: 0.7832s - Throughput: 5.1 imgs/s Running inference on batch 068/125... - Step Time: 0.8269s - Throughput: 4.8 imgs/s Running inference on batch 069/125... - Step Time: 0.8343s - Throughput: 4.8 imgs/s Running inference on batch 070/125... - Step Time: 0.8445s - Throughput: 4.7 imgs/s Running inference on batch 071/125... - Step Time: 0.7988s - Throughput: 5.0 imgs/s Running inference on batch 072/125... - Step Time: 0.8453s - Throughput: 4.7 imgs/s Running inference on batch 073/125... - Step Time: 0.8130s - Throughput: 4.9 imgs/s Running inference on batch 074/125... - Step Time: 0.8081s - Throughput: 5.0 imgs/s Running inference on batch 075/125... - Step Time: 0.8535s - Throughput: 4.7 imgs/s Running inference on batch 076/125... - Step Time: 0.8366s - Throughput: 4.8 imgs/s Running inference on batch 077/125... - Step Time: 0.8272s - Throughput: 4.8 imgs/s Running inference on batch 078/125... - Step Time: 0.8265s - Throughput: 4.8 imgs/s Running inference on batch 079/125... - Step Time: 0.8349s - Throughput: 4.8 imgs/s Running inference on batch 080/125... - Step Time: 0.8993s - Throughput: 4.4 imgs/s Running inference on batch 081/125... - Step Time: 0.7983s - Throughput: 5.0 imgs/s Running inference on batch 082/125... - Step Time: 0.8000s - Throughput: 5.0 imgs/s Running inference on batch 083/125... - Step Time: 0.8187s - Throughput: 4.9 imgs/s Running inference on batch 084/125... - Step Time: 0.8058s - Throughput: 5.0 imgs/s Running inference on batch 085/125... - Step Time: 0.8116s - Throughput: 4.9 imgs/s Running inference on batch 086/125... - Step Time: 0.7906s - Throughput: 5.1 imgs/s Running inference on batch 087/125... - Step Time: 0.8505s - Throughput: 4.7 imgs/s Running inference on batch 088/125... - Step Time: 0.8454s - Throughput: 4.7 imgs/s Running inference on batch 089/125... - Step Time: 0.8828s - Throughput: 4.5 imgs/s Running inference on batch 090/125... - Step Time: 0.7485s - Throughput: 5.3 imgs/s Running inference on batch 091/125... - Step Time: 0.8557s - Throughput: 4.7 imgs/s Running inference on batch 092/125... - Step Time: 0.8393s - Throughput: 4.8 imgs/s Running inference on batch 093/125... - Step Time: 0.8149s - Throughput: 4.9 imgs/s Running inference on batch 094/125... - Step Time: 0.8680s - Throughput: 4.6 imgs/s Running inference on batch 095/125... - Step Time: 0.8394s - Throughput: 4.8 imgs/s Running inference on batch 096/125... - Step Time: 0.8416s - Throughput: 4.8 imgs/s Running inference on batch 097/125... - Step Time: 0.8476s - Throughput: 4.7 imgs/s Running inference on batch 098/125... - Step Time: 0.8385s - Throughput: 4.8 imgs/s Running inference on batch 099/125... - Step Time: 0.8401s - Throughput: 4.8 imgs/s Running inference on batch 100/125... - Step Time: 0.7885s - Throughput: 5.1 imgs/s Running inference on batch 101/125... - Step Time: 0.8201s - Throughput: 4.9 imgs/s Running inference on batch 102/125... - Step Time: 0.8253s - Throughput: 4.8 imgs/s Running inference on batch 103/125... - Step Time: 0.8264s - Throughput: 4.8 imgs/s Running inference on batch 104/125... - Step Time: 0.8297s - Throughput: 4.8 imgs/s Running inference on batch 105/125... - Step Time: 0.7707s - Throughput: 5.2 imgs/s Running inference on batch 106/125... - Step Time: 0.8482s - Throughput: 4.7 imgs/s Running inference on batch 107/125... - Step Time: 0.8544s - Throughput: 4.7 imgs/s Running inference on batch 108/125... - Step Time: 0.8489s - Throughput: 4.7 imgs/s Running inference on batch 109/125... - Step Time: 0.8372s - Throughput: 4.8 imgs/s Running inference on batch 110/125... - Step Time: 0.8760s - Throughput: 4.6 imgs/s Running inference on batch 111/125... - Step Time: 0.8385s - Throughput: 4.8 imgs/s Running inference on batch 112/125... - Step Time: 0.8334s - Throughput: 4.8 imgs/s Running inference on batch 113/125... - Step Time: 0.8450s - Throughput: 4.7 imgs/s Running inference on batch 114/125... - Step Time: 0.8125s - Throughput: 4.9 imgs/s Running inference on batch 115/125... - Step Time: 0.8185s - Throughput: 4.9 imgs/s Running inference on batch 116/125... - Step Time: 0.8365s - Throughput: 4.8 imgs/s Running inference on batch 117/125... - Step Time: 0.8259s - Throughput: 4.8 imgs/s Running inference on batch 118/125... - Step Time: 0.8685s - Throughput: 4.6 imgs/s Running inference on batch 119/125... - Step Time: 0.8532s - Throughput: 4.7 imgs/s Running inference on batch 120/125... - Step Time: 0.8444s - Throughput: 4.7 imgs/s Running inference on batch 121/125... - Step Time: 0.8127s - Throughput: 4.9 imgs/s Running inference on batch 122/125... - Step Time: 0.7951s - Throughput: 5.0 imgs/s Running inference on batch 123/125... - Step Time: 0.8354s - Throughput: 4.8 imgs/s Running inference on batch 124/125... - Step Time: 0.8749s - Throughput: 4.6 imgs/s Running inference on batch 125/125... - Step Time: 0.6135s - Throughput: 6.5 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: 4.8 samples/sec Total processed steps: 125 Total processing time: 0.0h 10m 02s ==================== Metrics ==================== AP: 0.156986177 AP50: 0.240531310 AP75: 0.156212777 APl: 0.182949886 APm: 0.042182051 APs: 0.006653030 ARl: 0.398809224 ARm: 0.076754257 ARmax1: 0.240874916 ARmax10: 0.340371102 ARmax100: 0.344642699 ARs: 0.007798482 mask_AP: 0.128189906 mask_AP50: 0.205159470 mask_AP75: 0.135007083 mask_APl: 0.151302442 mask_APm: 0.013083026 mask_APs: 0.000022919 mask_ARl: 0.275996000 mask_ARm: 0.038180176 mask_ARmax1: 0.182545274 mask_ARmax10: 0.228658289 mask_ARmax100: 0.232366398 mask_ARs: 0.000966184 ================================= 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] 549.0 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: 1655024520.205986 iteration: 20005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15624 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.21734 L1 loss: 0.0000e+00 L2 loss: 1.09995 Learning rate: 0.02 Mask loss: 0.12566 RPN box loss: 0.02387 RPN score loss: 0.00194 RPN total loss: 0.02581 Total loss: 1.46876 timestamp: 1655024523.6849582 iteration: 20010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0984 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.17447 L1 loss: 0.0000e+00 L2 loss: 1.09979 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.02713 RPN score loss: 0.00764 RPN total loss: 0.03477 Total loss: 1.46146 timestamp: 1655024527.020228 iteration: 20015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11829 FastRCNN class loss: 0.06293 FastRCNN total loss: 0.18122 L1 loss: 0.0000e+00 L2 loss: 1.09961 Learning rate: 0.02 Mask loss: 0.20596 RPN box loss: 0.00976 RPN score loss: 0.00876 RPN total loss: 0.01852 Total loss: 1.50531 timestamp: 1655024530.318748 iteration: 20020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23961 FastRCNN class loss: 0.08705 FastRCNN total loss: 0.32667 L1 loss: 0.0000e+00 L2 loss: 1.09941 Learning rate: 0.02 Mask loss: 0.22911 RPN box loss: 0.05678 RPN score loss: 0.00958 RPN total loss: 0.06636 Total loss: 1.72155 timestamp: 1655024533.6896634 iteration: 20025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1124 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.16923 L1 loss: 0.0000e+00 L2 loss: 1.0992 Learning rate: 0.02 Mask loss: 0.14844 RPN box loss: 0.08424 RPN score loss: 0.00573 RPN total loss: 0.08997 Total loss: 1.50684 timestamp: 1655024536.963655 iteration: 20030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12367 FastRCNN class loss: 0.08917 FastRCNN total loss: 0.21284 L1 loss: 0.0000e+00 L2 loss: 1.09901 Learning rate: 0.02 Mask loss: 0.11539 RPN box loss: 0.01235 RPN score loss: 0.00364 RPN total loss: 0.01599 Total loss: 1.44323 timestamp: 1655024540.4350297 iteration: 20035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11977 FastRCNN class loss: 0.0864 FastRCNN total loss: 0.20617 L1 loss: 0.0000e+00 L2 loss: 1.09884 Learning rate: 0.02 Mask loss: 0.18745 RPN box loss: 0.01402 RPN score loss: 0.00294 RPN total loss: 0.01696 Total loss: 1.50941 timestamp: 1655024543.7105517 iteration: 20040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1465 FastRCNN class loss: 0.07562 FastRCNN total loss: 0.22213 L1 loss: 0.0000e+00 L2 loss: 1.09866 Learning rate: 0.02 Mask loss: 0.21177 RPN box loss: 0.00798 RPN score loss: 0.00504 RPN total loss: 0.01302 Total loss: 1.54558 timestamp: 1655024547.1282752 iteration: 20045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2384 FastRCNN class loss: 0.11106 FastRCNN total loss: 0.34945 L1 loss: 0.0000e+00 L2 loss: 1.09848 Learning rate: 0.02 Mask loss: 0.13627 RPN box loss: 0.03098 RPN score loss: 0.00568 RPN total loss: 0.03666 Total loss: 1.62087 timestamp: 1655024550.526961 iteration: 20050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14214 FastRCNN class loss: 0.10875 FastRCNN total loss: 0.25089 L1 loss: 0.0000e+00 L2 loss: 1.0983 Learning rate: 0.02 Mask loss: 0.15591 RPN box loss: 0.01785 RPN score loss: 0.00493 RPN total loss: 0.02277 Total loss: 1.52787 timestamp: 1655024553.7738407 iteration: 20055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16448 FastRCNN class loss: 0.0605 FastRCNN total loss: 0.22498 L1 loss: 0.0000e+00 L2 loss: 1.09812 Learning rate: 0.02 Mask loss: 0.11817 RPN box loss: 0.04534 RPN score loss: 0.0061 RPN total loss: 0.05144 Total loss: 1.49271 timestamp: 1655024557.2245011 iteration: 20060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1599 FastRCNN class loss: 0.16301 FastRCNN total loss: 0.32291 L1 loss: 0.0000e+00 L2 loss: 1.09794 Learning rate: 0.02 Mask loss: 0.25129 RPN box loss: 0.0565 RPN score loss: 0.01204 RPN total loss: 0.06854 Total loss: 1.74067 timestamp: 1655024560.4481878 iteration: 20065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12901 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.18936 L1 loss: 0.0000e+00 L2 loss: 1.09776 Learning rate: 0.02 Mask loss: 0.1574 RPN box loss: 0.06828 RPN score loss: 0.00422 RPN total loss: 0.0725 Total loss: 1.51703 timestamp: 1655024564.0000863 iteration: 20070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13958 FastRCNN class loss: 0.11649 FastRCNN total loss: 0.25607 L1 loss: 0.0000e+00 L2 loss: 1.09759 Learning rate: 0.02 Mask loss: 0.12922 RPN box loss: 0.04474 RPN score loss: 0.00497 RPN total loss: 0.04971 Total loss: 1.53258 timestamp: 1655024567.3277345 iteration: 20075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19725 FastRCNN class loss: 0.12736 FastRCNN total loss: 0.32461 L1 loss: 0.0000e+00 L2 loss: 1.09738 Learning rate: 0.02 Mask loss: 0.18627 RPN box loss: 0.03036 RPN score loss: 0.01081 RPN total loss: 0.04117 Total loss: 1.64943 timestamp: 1655024570.6714025 iteration: 20080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07639 FastRCNN class loss: 0.04279 FastRCNN total loss: 0.11918 L1 loss: 0.0000e+00 L2 loss: 1.09721 Learning rate: 0.02 Mask loss: 0.12462 RPN box loss: 0.01796 RPN score loss: 0.00599 RPN total loss: 0.02395 Total loss: 1.36496 timestamp: 1655024573.9602108 iteration: 20085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14617 FastRCNN class loss: 0.10628 FastRCNN total loss: 0.25245 L1 loss: 0.0000e+00 L2 loss: 1.09703 Learning rate: 0.02 Mask loss: 0.20241 RPN box loss: 0.04754 RPN score loss: 0.00935 RPN total loss: 0.05689 Total loss: 1.60878 timestamp: 1655024577.4170182 iteration: 20090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21513 FastRCNN class loss: 0.09646 FastRCNN total loss: 0.31159 L1 loss: 0.0000e+00 L2 loss: 1.09684 Learning rate: 0.02 Mask loss: 0.17661 RPN box loss: 0.03278 RPN score loss: 0.00693 RPN total loss: 0.03971 Total loss: 1.62474 timestamp: 1655024580.8026142 iteration: 20095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10565 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.1611 L1 loss: 0.0000e+00 L2 loss: 1.09665 Learning rate: 0.02 Mask loss: 0.09459 RPN box loss: 0.02301 RPN score loss: 0.00535 RPN total loss: 0.02836 Total loss: 1.3807 timestamp: 1655024584.0238438 iteration: 20100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14372 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.20589 L1 loss: 0.0000e+00 L2 loss: 1.09645 Learning rate: 0.02 Mask loss: 0.11913 RPN box loss: 0.04063 RPN score loss: 0.00648 RPN total loss: 0.04711 Total loss: 1.46858 timestamp: 1655024587.38764 iteration: 20105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20245 FastRCNN class loss: 0.10663 FastRCNN total loss: 0.30907 L1 loss: 0.0000e+00 L2 loss: 1.09626 Learning rate: 0.02 Mask loss: 0.14818 RPN box loss: 0.04997 RPN score loss: 0.00647 RPN total loss: 0.05644 Total loss: 1.60995 timestamp: 1655024590.6501205 iteration: 20110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17585 FastRCNN class loss: 0.06599 FastRCNN total loss: 0.24184 L1 loss: 0.0000e+00 L2 loss: 1.09608 Learning rate: 0.02 Mask loss: 0.14742 RPN box loss: 0.01716 RPN score loss: 0.00891 RPN total loss: 0.02607 Total loss: 1.51141 timestamp: 1655024594.11071 iteration: 20115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15912 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.23477 L1 loss: 0.0000e+00 L2 loss: 1.09591 Learning rate: 0.02 Mask loss: 0.21105 RPN box loss: 0.0354 RPN score loss: 0.0074 RPN total loss: 0.0428 Total loss: 1.58453 timestamp: 1655024597.4263966 iteration: 20120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06952 FastRCNN class loss: 0.03731 FastRCNN total loss: 0.10683 L1 loss: 0.0000e+00 L2 loss: 1.09572 Learning rate: 0.02 Mask loss: 0.11989 RPN box loss: 0.00299 RPN score loss: 0.00278 RPN total loss: 0.00577 Total loss: 1.32822 timestamp: 1655024600.796498 iteration: 20125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1346 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.21242 L1 loss: 0.0000e+00 L2 loss: 1.09553 Learning rate: 0.02 Mask loss: 0.15015 RPN box loss: 0.03377 RPN score loss: 0.00744 RPN total loss: 0.04122 Total loss: 1.49931 timestamp: 1655024604.2594647 iteration: 20130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18986 FastRCNN class loss: 0.10924 FastRCNN total loss: 0.2991 L1 loss: 0.0000e+00 L2 loss: 1.09536 Learning rate: 0.02 Mask loss: 0.20433 RPN box loss: 0.08725 RPN score loss: 0.00758 RPN total loss: 0.09483 Total loss: 1.69362 timestamp: 1655024607.6078033 iteration: 20135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.08742 FastRCNN total loss: 0.21558 L1 loss: 0.0000e+00 L2 loss: 1.09516 Learning rate: 0.02 Mask loss: 0.16493 RPN box loss: 0.03664 RPN score loss: 0.0126 RPN total loss: 0.04924 Total loss: 1.52491 timestamp: 1655024610.840221 iteration: 20140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17603 FastRCNN class loss: 0.13335 FastRCNN total loss: 0.30938 L1 loss: 0.0000e+00 L2 loss: 1.09496 Learning rate: 0.02 Mask loss: 0.16161 RPN box loss: 0.02301 RPN score loss: 0.00626 RPN total loss: 0.02928 Total loss: 1.59523 timestamp: 1655024614.160138 iteration: 20145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14175 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.20193 L1 loss: 0.0000e+00 L2 loss: 1.09478 Learning rate: 0.02 Mask loss: 0.12824 RPN box loss: 0.00516 RPN score loss: 0.00433 RPN total loss: 0.00949 Total loss: 1.43445 timestamp: 1655024617.4585445 iteration: 20150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14093 FastRCNN class loss: 0.10354 FastRCNN total loss: 0.24448 L1 loss: 0.0000e+00 L2 loss: 1.09459 Learning rate: 0.02 Mask loss: 0.15864 RPN box loss: 0.04438 RPN score loss: 0.00682 RPN total loss: 0.0512 Total loss: 1.54891 timestamp: 1655024620.7687833 iteration: 20155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13244 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.18814 L1 loss: 0.0000e+00 L2 loss: 1.09443 Learning rate: 0.02 Mask loss: 0.12324 RPN box loss: 0.0129 RPN score loss: 0.00457 RPN total loss: 0.01747 Total loss: 1.42327 timestamp: 1655024624.2042193 iteration: 20160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15367 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.22882 L1 loss: 0.0000e+00 L2 loss: 1.09424 Learning rate: 0.02 Mask loss: 0.18534 RPN box loss: 0.01797 RPN score loss: 0.0049 RPN total loss: 0.02287 Total loss: 1.53127 timestamp: 1655024627.493913 iteration: 20165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.06809 FastRCNN total loss: 0.18152 L1 loss: 0.0000e+00 L2 loss: 1.09407 Learning rate: 0.02 Mask loss: 0.14217 RPN box loss: 0.01061 RPN score loss: 0.0058 RPN total loss: 0.01641 Total loss: 1.43416 timestamp: 1655024630.9222076 iteration: 20170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.0899 FastRCNN total loss: 0.21476 L1 loss: 0.0000e+00 L2 loss: 1.09388 Learning rate: 0.02 Mask loss: 0.26628 RPN box loss: 0.07509 RPN score loss: 0.00991 RPN total loss: 0.085 Total loss: 1.65992 timestamp: 1655024634.3140473 iteration: 20175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1191 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.1786 L1 loss: 0.0000e+00 L2 loss: 1.09368 Learning rate: 0.02 Mask loss: 0.13567 RPN box loss: 0.00857 RPN score loss: 0.00625 RPN total loss: 0.01482 Total loss: 1.42276 timestamp: 1655024637.6395543 iteration: 20180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18585 FastRCNN class loss: 0.10919 FastRCNN total loss: 0.29504 L1 loss: 0.0000e+00 L2 loss: 1.09349 Learning rate: 0.02 Mask loss: 0.1726 RPN box loss: 0.03135 RPN score loss: 0.00599 RPN total loss: 0.03733 Total loss: 1.59846 timestamp: 1655024640.9347093 iteration: 20185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17499 FastRCNN class loss: 0.14968 FastRCNN total loss: 0.32467 L1 loss: 0.0000e+00 L2 loss: 1.09332 Learning rate: 0.02 Mask loss: 0.2016 RPN box loss: 0.04895 RPN score loss: 0.01779 RPN total loss: 0.06674 Total loss: 1.68633 timestamp: 1655024644.1844513 iteration: 20190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15601 FastRCNN class loss: 0.12785 FastRCNN total loss: 0.28386 L1 loss: 0.0000e+00 L2 loss: 1.09313 Learning rate: 0.02 Mask loss: 0.18268 RPN box loss: 0.03159 RPN score loss: 0.00732 RPN total loss: 0.0389 Total loss: 1.59858 timestamp: 1655024647.4800694 iteration: 20195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16313 FastRCNN class loss: 0.10133 FastRCNN total loss: 0.26447 L1 loss: 0.0000e+00 L2 loss: 1.09295 Learning rate: 0.02 Mask loss: 0.24309 RPN box loss: 0.0543 RPN score loss: 0.00926 RPN total loss: 0.06357 Total loss: 1.66407 timestamp: 1655024650.7583568 iteration: 20200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23166 FastRCNN class loss: 0.11884 FastRCNN total loss: 0.3505 L1 loss: 0.0000e+00 L2 loss: 1.09278 Learning rate: 0.02 Mask loss: 0.17164 RPN box loss: 0.06608 RPN score loss: 0.01494 RPN total loss: 0.08102 Total loss: 1.69595 timestamp: 1655024654.0950692 iteration: 20205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12218 FastRCNN class loss: 0.10552 FastRCNN total loss: 0.2277 L1 loss: 0.0000e+00 L2 loss: 1.09262 Learning rate: 0.02 Mask loss: 0.14236 RPN box loss: 0.05206 RPN score loss: 0.00688 RPN total loss: 0.05894 Total loss: 1.52162 timestamp: 1655024657.4055998 iteration: 20210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14751 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.23457 L1 loss: 0.0000e+00 L2 loss: 1.09244 Learning rate: 0.02 Mask loss: 0.28666 RPN box loss: 0.03271 RPN score loss: 0.01023 RPN total loss: 0.04294 Total loss: 1.6566 timestamp: 1655024660.830248 iteration: 20215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13912 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.20395 L1 loss: 0.0000e+00 L2 loss: 1.09224 Learning rate: 0.02 Mask loss: 0.19582 RPN box loss: 0.02464 RPN score loss: 0.01013 RPN total loss: 0.03477 Total loss: 1.52678 timestamp: 1655024664.1758392 iteration: 20220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08802 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.15059 L1 loss: 0.0000e+00 L2 loss: 1.09205 Learning rate: 0.02 Mask loss: 0.10829 RPN box loss: 0.01225 RPN score loss: 0.00881 RPN total loss: 0.02106 Total loss: 1.37199 timestamp: 1655024667.475069 iteration: 20225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13756 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.20929 L1 loss: 0.0000e+00 L2 loss: 1.09187 Learning rate: 0.02 Mask loss: 0.14245 RPN box loss: 0.02327 RPN score loss: 0.00632 RPN total loss: 0.02958 Total loss: 1.4732 timestamp: 1655024670.9314747 iteration: 20230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18221 FastRCNN class loss: 0.10289 FastRCNN total loss: 0.2851 L1 loss: 0.0000e+00 L2 loss: 1.09169 Learning rate: 0.02 Mask loss: 0.31044 RPN box loss: 0.02049 RPN score loss: 0.00956 RPN total loss: 0.03005 Total loss: 1.71728 timestamp: 1655024674.2527068 iteration: 20235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.19263 L1 loss: 0.0000e+00 L2 loss: 1.09152 Learning rate: 0.02 Mask loss: 0.14634 RPN box loss: 0.01475 RPN score loss: 0.00285 RPN total loss: 0.0176 Total loss: 1.44809 timestamp: 1655024677.6200664 iteration: 20240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15849 FastRCNN class loss: 0.05877 FastRCNN total loss: 0.21726 L1 loss: 0.0000e+00 L2 loss: 1.09133 Learning rate: 0.02 Mask loss: 0.13068 RPN box loss: 0.01173 RPN score loss: 0.00524 RPN total loss: 0.01698 Total loss: 1.45625 timestamp: 1655024680.9757545 iteration: 20245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13786 FastRCNN class loss: 0.07794 FastRCNN total loss: 0.2158 L1 loss: 0.0000e+00 L2 loss: 1.09115 Learning rate: 0.02 Mask loss: 0.1725 RPN box loss: 0.03675 RPN score loss: 0.00874 RPN total loss: 0.04549 Total loss: 1.52495 timestamp: 1655024684.3492317 iteration: 20250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12889 FastRCNN class loss: 0.05664 FastRCNN total loss: 0.18553 L1 loss: 0.0000e+00 L2 loss: 1.09098 Learning rate: 0.02 Mask loss: 0.12248 RPN box loss: 0.03917 RPN score loss: 0.0048 RPN total loss: 0.04397 Total loss: 1.44296 timestamp: 1655024687.6961846 iteration: 20255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18662 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.25539 L1 loss: 0.0000e+00 L2 loss: 1.09079 Learning rate: 0.02 Mask loss: 0.10546 RPN box loss: 0.01807 RPN score loss: 0.00658 RPN total loss: 0.02465 Total loss: 1.47629 timestamp: 1655024691.2064424 iteration: 20260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11352 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.1877 L1 loss: 0.0000e+00 L2 loss: 1.0906 Learning rate: 0.02 Mask loss: 0.15232 RPN box loss: 0.01341 RPN score loss: 0.00488 RPN total loss: 0.01829 Total loss: 1.44891 timestamp: 1655024694.4893732 iteration: 20265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17685 FastRCNN class loss: 0.09824 FastRCNN total loss: 0.2751 L1 loss: 0.0000e+00 L2 loss: 1.0904 Learning rate: 0.02 Mask loss: 0.15462 RPN box loss: 0.0561 RPN score loss: 0.01181 RPN total loss: 0.06791 Total loss: 1.58803 timestamp: 1655024697.794121 iteration: 20270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15293 FastRCNN class loss: 0.08786 FastRCNN total loss: 0.24078 L1 loss: 0.0000e+00 L2 loss: 1.09021 Learning rate: 0.02 Mask loss: 0.19276 RPN box loss: 0.01918 RPN score loss: 0.01106 RPN total loss: 0.03024 Total loss: 1.554 timestamp: 1655024701.2749543 iteration: 20275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14846 FastRCNN class loss: 0.10732 FastRCNN total loss: 0.25578 L1 loss: 0.0000e+00 L2 loss: 1.09003 Learning rate: 0.02 Mask loss: 0.17949 RPN box loss: 0.04055 RPN score loss: 0.00353 RPN total loss: 0.04408 Total loss: 1.56939 timestamp: 1655024704.586012 iteration: 20280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21027 FastRCNN class loss: 0.09341 FastRCNN total loss: 0.30368 L1 loss: 0.0000e+00 L2 loss: 1.08985 Learning rate: 0.02 Mask loss: 0.19252 RPN box loss: 0.00797 RPN score loss: 0.00252 RPN total loss: 0.0105 Total loss: 1.59656 timestamp: 1655024707.9897966 iteration: 20285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15819 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.22868 L1 loss: 0.0000e+00 L2 loss: 1.08968 Learning rate: 0.02 Mask loss: 0.12528 RPN box loss: 0.01623 RPN score loss: 0.00539 RPN total loss: 0.02163 Total loss: 1.46526 timestamp: 1655024711.2876158 iteration: 20290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10648 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.17996 L1 loss: 0.0000e+00 L2 loss: 1.08952 Learning rate: 0.02 Mask loss: 0.12343 RPN box loss: 0.03181 RPN score loss: 0.00523 RPN total loss: 0.03704 Total loss: 1.42995 timestamp: 1655024714.6020515 iteration: 20295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10223 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.16676 L1 loss: 0.0000e+00 L2 loss: 1.08933 Learning rate: 0.02 Mask loss: 0.15979 RPN box loss: 0.07607 RPN score loss: 0.01091 RPN total loss: 0.08698 Total loss: 1.50285 timestamp: 1655024717.8519373 iteration: 20300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16104 FastRCNN class loss: 0.1231 FastRCNN total loss: 0.28414 L1 loss: 0.0000e+00 L2 loss: 1.08914 Learning rate: 0.02 Mask loss: 0.18871 RPN box loss: 0.04212 RPN score loss: 0.01144 RPN total loss: 0.05355 Total loss: 1.61554 timestamp: 1655024721.1876655 iteration: 20305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15455 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.23393 L1 loss: 0.0000e+00 L2 loss: 1.08896 Learning rate: 0.02 Mask loss: 0.16837 RPN box loss: 0.03184 RPN score loss: 0.01012 RPN total loss: 0.04197 Total loss: 1.53323 timestamp: 1655024724.6667752 iteration: 20310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16917 FastRCNN class loss: 0.10531 FastRCNN total loss: 0.27448 L1 loss: 0.0000e+00 L2 loss: 1.08876 Learning rate: 0.02 Mask loss: 0.16876 RPN box loss: 0.02642 RPN score loss: 0.00732 RPN total loss: 0.03374 Total loss: 1.56574 timestamp: 1655024727.9253778 iteration: 20315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11805 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.17903 L1 loss: 0.0000e+00 L2 loss: 1.08858 Learning rate: 0.02 Mask loss: 0.16321 RPN box loss: 0.02995 RPN score loss: 0.00413 RPN total loss: 0.03408 Total loss: 1.4649 timestamp: 1655024731.4190578 iteration: 20320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17813 FastRCNN class loss: 0.09048 FastRCNN total loss: 0.26861 L1 loss: 0.0000e+00 L2 loss: 1.08843 Learning rate: 0.02 Mask loss: 0.21995 RPN box loss: 0.01969 RPN score loss: 0.00134 RPN total loss: 0.02103 Total loss: 1.59802 timestamp: 1655024734.6792758 iteration: 20325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.05615 FastRCNN total loss: 0.1502 L1 loss: 0.0000e+00 L2 loss: 1.08825 Learning rate: 0.02 Mask loss: 0.16608 RPN box loss: 0.02753 RPN score loss: 0.00183 RPN total loss: 0.02936 Total loss: 1.43389 timestamp: 1655024738.029248 iteration: 20330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17931 FastRCNN class loss: 0.0787 FastRCNN total loss: 0.258 L1 loss: 0.0000e+00 L2 loss: 1.08805 Learning rate: 0.02 Mask loss: 0.17989 RPN box loss: 0.03535 RPN score loss: 0.00484 RPN total loss: 0.04019 Total loss: 1.56613 timestamp: 1655024741.2635949 iteration: 20335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13061 FastRCNN class loss: 0.10633 FastRCNN total loss: 0.23694 L1 loss: 0.0000e+00 L2 loss: 1.08788 Learning rate: 0.02 Mask loss: 0.15439 RPN box loss: 0.04706 RPN score loss: 0.01445 RPN total loss: 0.06151 Total loss: 1.54072 timestamp: 1655024744.6897736 iteration: 20340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16058 FastRCNN class loss: 0.08211 FastRCNN total loss: 0.24269 L1 loss: 0.0000e+00 L2 loss: 1.08769 Learning rate: 0.02 Mask loss: 0.24001 RPN box loss: 0.03437 RPN score loss: 0.00224 RPN total loss: 0.03661 Total loss: 1.607 timestamp: 1655024748.1260624 iteration: 20345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14936 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.22523 L1 loss: 0.0000e+00 L2 loss: 1.08751 Learning rate: 0.02 Mask loss: 0.16545 RPN box loss: 0.01647 RPN score loss: 0.01636 RPN total loss: 0.03283 Total loss: 1.51102 timestamp: 1655024751.4023252 iteration: 20350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2413 FastRCNN class loss: 0.13143 FastRCNN total loss: 0.37273 L1 loss: 0.0000e+00 L2 loss: 1.08734 Learning rate: 0.02 Mask loss: 0.2509 RPN box loss: 0.06077 RPN score loss: 0.01933 RPN total loss: 0.0801 Total loss: 1.79106 timestamp: 1655024754.7803998 iteration: 20355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16565 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.22885 L1 loss: 0.0000e+00 L2 loss: 1.08714 Learning rate: 0.02 Mask loss: 0.12332 RPN box loss: 0.01982 RPN score loss: 0.01131 RPN total loss: 0.03113 Total loss: 1.47044 timestamp: 1655024758.0063066 iteration: 20360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18051 FastRCNN class loss: 0.15428 FastRCNN total loss: 0.3348 L1 loss: 0.0000e+00 L2 loss: 1.08697 Learning rate: 0.02 Mask loss: 0.24855 RPN box loss: 0.0468 RPN score loss: 0.01113 RPN total loss: 0.05793 Total loss: 1.72824 timestamp: 1655024761.4867008 iteration: 20365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12429 FastRCNN class loss: 0.08819 FastRCNN total loss: 0.21248 L1 loss: 0.0000e+00 L2 loss: 1.08678 Learning rate: 0.02 Mask loss: 0.14545 RPN box loss: 0.02884 RPN score loss: 0.0058 RPN total loss: 0.03464 Total loss: 1.47935 timestamp: 1655024764.7902663 iteration: 20370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14013 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.22205 L1 loss: 0.0000e+00 L2 loss: 1.08658 Learning rate: 0.02 Mask loss: 0.12784 RPN box loss: 0.03088 RPN score loss: 0.00394 RPN total loss: 0.03482 Total loss: 1.47128 timestamp: 1655024768.1244774 iteration: 20375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15083 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.23092 L1 loss: 0.0000e+00 L2 loss: 1.08641 Learning rate: 0.02 Mask loss: 0.23745 RPN box loss: 0.0433 RPN score loss: 0.00604 RPN total loss: 0.04934 Total loss: 1.60413 timestamp: 1655024771.4231775 iteration: 20380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13198 FastRCNN class loss: 0.1359 FastRCNN total loss: 0.26788 L1 loss: 0.0000e+00 L2 loss: 1.08624 Learning rate: 0.02 Mask loss: 0.22912 RPN box loss: 0.04498 RPN score loss: 0.00906 RPN total loss: 0.05404 Total loss: 1.63728 timestamp: 1655024774.7960973 iteration: 20385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.31115 FastRCNN class loss: 0.16058 FastRCNN total loss: 0.47173 L1 loss: 0.0000e+00 L2 loss: 1.08607 Learning rate: 0.02 Mask loss: 0.22755 RPN box loss: 0.06573 RPN score loss: 0.07592 RPN total loss: 0.14165 Total loss: 1.927 timestamp: 1655024778.177641 iteration: 20390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11725 FastRCNN class loss: 0.05367 FastRCNN total loss: 0.17093 L1 loss: 0.0000e+00 L2 loss: 1.0859 Learning rate: 0.02 Mask loss: 0.29211 RPN box loss: 0.0307 RPN score loss: 0.00342 RPN total loss: 0.03411 Total loss: 1.58305 timestamp: 1655024781.5426128 iteration: 20395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.11915 FastRCNN total loss: 0.23787 L1 loss: 0.0000e+00 L2 loss: 1.08573 Learning rate: 0.02 Mask loss: 0.15161 RPN box loss: 0.05232 RPN score loss: 0.01453 RPN total loss: 0.06685 Total loss: 1.54207 timestamp: 1655024784.9787652 iteration: 20400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1231 FastRCNN class loss: 0.06204 FastRCNN total loss: 0.18515 L1 loss: 0.0000e+00 L2 loss: 1.08556 Learning rate: 0.02 Mask loss: 0.12861 RPN box loss: 0.01078 RPN score loss: 0.00317 RPN total loss: 0.01396 Total loss: 1.41327 timestamp: 1655024788.275821 iteration: 20405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13222 FastRCNN class loss: 0.07729 FastRCNN total loss: 0.20951 L1 loss: 0.0000e+00 L2 loss: 1.0854 Learning rate: 0.02 Mask loss: 0.17142 RPN box loss: 0.01146 RPN score loss: 0.00379 RPN total loss: 0.01525 Total loss: 1.48157 timestamp: 1655024791.6485918 iteration: 20410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16534 FastRCNN class loss: 0.12013 FastRCNN total loss: 0.28547 L1 loss: 0.0000e+00 L2 loss: 1.08521 Learning rate: 0.02 Mask loss: 0.15251 RPN box loss: 0.03465 RPN score loss: 0.01003 RPN total loss: 0.04467 Total loss: 1.56787 timestamp: 1655024794.9894156 iteration: 20415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13619 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.21657 L1 loss: 0.0000e+00 L2 loss: 1.085 Learning rate: 0.02 Mask loss: 0.12961 RPN box loss: 0.02457 RPN score loss: 0.01107 RPN total loss: 0.03564 Total loss: 1.46682 timestamp: 1655024798.3923168 iteration: 20420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14927 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.2015 L1 loss: 0.0000e+00 L2 loss: 1.08481 Learning rate: 0.02 Mask loss: 0.17346 RPN box loss: 0.01189 RPN score loss: 0.00196 RPN total loss: 0.01385 Total loss: 1.47362 timestamp: 1655024801.6724114 iteration: 20425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12683 FastRCNN class loss: 0.08961 FastRCNN total loss: 0.21644 L1 loss: 0.0000e+00 L2 loss: 1.08464 Learning rate: 0.02 Mask loss: 0.19587 RPN box loss: 0.07258 RPN score loss: 0.01103 RPN total loss: 0.08361 Total loss: 1.58056 timestamp: 1655024805.1153338 iteration: 20430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20387 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.29726 L1 loss: 0.0000e+00 L2 loss: 1.08445 Learning rate: 0.02 Mask loss: 0.21171 RPN box loss: 0.02061 RPN score loss: 0.01037 RPN total loss: 0.03098 Total loss: 1.62441 timestamp: 1655024808.4742572 iteration: 20435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17053 FastRCNN class loss: 0.10324 FastRCNN total loss: 0.27378 L1 loss: 0.0000e+00 L2 loss: 1.08425 Learning rate: 0.02 Mask loss: 0.22943 RPN box loss: 0.04386 RPN score loss: 0.0135 RPN total loss: 0.05736 Total loss: 1.64481 timestamp: 1655024811.781512 iteration: 20440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20576 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.29167 L1 loss: 0.0000e+00 L2 loss: 1.08408 Learning rate: 0.02 Mask loss: 0.2036 RPN box loss: 0.03112 RPN score loss: 0.00341 RPN total loss: 0.03453 Total loss: 1.61388 timestamp: 1655024815.2126215 iteration: 20445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.1834 L1 loss: 0.0000e+00 L2 loss: 1.08391 Learning rate: 0.02 Mask loss: 0.17111 RPN box loss: 0.04307 RPN score loss: 0.00804 RPN total loss: 0.05111 Total loss: 1.48952 timestamp: 1655024818.5407414 iteration: 20450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13257 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.20673 L1 loss: 0.0000e+00 L2 loss: 1.08372 Learning rate: 0.02 Mask loss: 0.15533 RPN box loss: 0.02153 RPN score loss: 0.00997 RPN total loss: 0.0315 Total loss: 1.47728 timestamp: 1655024821.9359148 iteration: 20455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19863 FastRCNN class loss: 0.21392 FastRCNN total loss: 0.41254 L1 loss: 0.0000e+00 L2 loss: 1.08354 Learning rate: 0.02 Mask loss: 0.21454 RPN box loss: 0.05657 RPN score loss: 0.01581 RPN total loss: 0.07238 Total loss: 1.78301 timestamp: 1655024825.2405367 iteration: 20460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10981 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 1.08335 Learning rate: 0.02 Mask loss: 0.14967 RPN box loss: 0.05364 RPN score loss: 0.0084 RPN total loss: 0.06205 Total loss: 1.47239 timestamp: 1655024828.6479673 iteration: 20465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1494 FastRCNN class loss: 0.04797 FastRCNN total loss: 0.19737 L1 loss: 0.0000e+00 L2 loss: 1.08316 Learning rate: 0.02 Mask loss: 0.16507 RPN box loss: 0.00459 RPN score loss: 0.00225 RPN total loss: 0.00684 Total loss: 1.45244 timestamp: 1655024832.0321581 iteration: 20470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.1104 FastRCNN total loss: 0.23058 L1 loss: 0.0000e+00 L2 loss: 1.08299 Learning rate: 0.02 Mask loss: 0.16485 RPN box loss: 0.03685 RPN score loss: 0.02609 RPN total loss: 0.06294 Total loss: 1.54136 timestamp: 1655024835.2637568 iteration: 20475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18042 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.26439 L1 loss: 0.0000e+00 L2 loss: 1.08278 Learning rate: 0.02 Mask loss: 0.1736 RPN box loss: 0.02365 RPN score loss: 0.00216 RPN total loss: 0.02581 Total loss: 1.54657 timestamp: 1655024838.6774325 iteration: 20480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17714 FastRCNN class loss: 0.11471 FastRCNN total loss: 0.29185 L1 loss: 0.0000e+00 L2 loss: 1.08261 Learning rate: 0.02 Mask loss: 0.16836 RPN box loss: 0.0398 RPN score loss: 0.00935 RPN total loss: 0.04915 Total loss: 1.59196 timestamp: 1655024841.9651003 iteration: 20485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.20337 L1 loss: 0.0000e+00 L2 loss: 1.08244 Learning rate: 0.02 Mask loss: 0.14188 RPN box loss: 0.04019 RPN score loss: 0.01148 RPN total loss: 0.05167 Total loss: 1.47935 timestamp: 1655024845.3938365 iteration: 20490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08094 FastRCNN class loss: 0.04035 FastRCNN total loss: 0.12129 L1 loss: 0.0000e+00 L2 loss: 1.08225 Learning rate: 0.02 Mask loss: 0.14224 RPN box loss: 0.06654 RPN score loss: 0.0089 RPN total loss: 0.07544 Total loss: 1.42122 timestamp: 1655024848.6686707 iteration: 20495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17121 FastRCNN class loss: 0.07561 FastRCNN total loss: 0.24682 L1 loss: 0.0000e+00 L2 loss: 1.08211 Learning rate: 0.02 Mask loss: 0.21899 RPN box loss: 0.03989 RPN score loss: 0.011 RPN total loss: 0.05088 Total loss: 1.5988 timestamp: 1655024852.0031707 iteration: 20500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20852 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.2966 L1 loss: 0.0000e+00 L2 loss: 1.08195 Learning rate: 0.02 Mask loss: 0.1651 RPN box loss: 0.01164 RPN score loss: 0.00282 RPN total loss: 0.01446 Total loss: 1.5581 timestamp: 1655024855.2477298 iteration: 20505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12005 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.17227 L1 loss: 0.0000e+00 L2 loss: 1.08176 Learning rate: 0.02 Mask loss: 0.14177 RPN box loss: 0.00817 RPN score loss: 0.00378 RPN total loss: 0.01196 Total loss: 1.40776 timestamp: 1655024858.6045322 iteration: 20510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.17607 L1 loss: 0.0000e+00 L2 loss: 1.08159 Learning rate: 0.02 Mask loss: 0.15369 RPN box loss: 0.03573 RPN score loss: 0.00447 RPN total loss: 0.04019 Total loss: 1.45154 timestamp: 1655024862.0075955 iteration: 20515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.08262 FastRCNN total loss: 0.19935 L1 loss: 0.0000e+00 L2 loss: 1.08139 Learning rate: 0.02 Mask loss: 0.14466 RPN box loss: 0.04064 RPN score loss: 0.01147 RPN total loss: 0.05211 Total loss: 1.47751 timestamp: 1655024865.2722745 iteration: 20520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08242 FastRCNN class loss: 0.04431 FastRCNN total loss: 0.12674 L1 loss: 0.0000e+00 L2 loss: 1.08121 Learning rate: 0.02 Mask loss: 0.13966 RPN box loss: 0.02148 RPN score loss: 0.00539 RPN total loss: 0.02687 Total loss: 1.37448 timestamp: 1655024868.6721766 iteration: 20525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15741 FastRCNN class loss: 0.08672 FastRCNN total loss: 0.24413 L1 loss: 0.0000e+00 L2 loss: 1.08102 Learning rate: 0.02 Mask loss: 0.14016 RPN box loss: 0.05027 RPN score loss: 0.00529 RPN total loss: 0.05557 Total loss: 1.52088 timestamp: 1655024871.938969 iteration: 20530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11964 FastRCNN class loss: 0.07987 FastRCNN total loss: 0.1995 L1 loss: 0.0000e+00 L2 loss: 1.08084 Learning rate: 0.02 Mask loss: 0.20829 RPN box loss: 0.0426 RPN score loss: 0.00531 RPN total loss: 0.04791 Total loss: 1.53654 timestamp: 1655024875.2648377 iteration: 20535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14203 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.20736 L1 loss: 0.0000e+00 L2 loss: 1.08065 Learning rate: 0.02 Mask loss: 0.168 RPN box loss: 0.0176 RPN score loss: 0.00376 RPN total loss: 0.02136 Total loss: 1.47737 timestamp: 1655024878.5026202 iteration: 20540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08318 FastRCNN class loss: 0.05104 FastRCNN total loss: 0.13422 L1 loss: 0.0000e+00 L2 loss: 1.08048 Learning rate: 0.02 Mask loss: 0.07912 RPN box loss: 0.00866 RPN score loss: 0.00164 RPN total loss: 0.0103 Total loss: 1.30412 timestamp: 1655024881.839119 iteration: 20545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18955 FastRCNN class loss: 0.11308 FastRCNN total loss: 0.30263 L1 loss: 0.0000e+00 L2 loss: 1.08028 Learning rate: 0.02 Mask loss: 0.20864 RPN box loss: 0.06277 RPN score loss: 0.02426 RPN total loss: 0.08703 Total loss: 1.67858 timestamp: 1655024885.1914368 iteration: 20550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16473 FastRCNN class loss: 0.11586 FastRCNN total loss: 0.28059 L1 loss: 0.0000e+00 L2 loss: 1.0801 Learning rate: 0.02 Mask loss: 0.16268 RPN box loss: 0.0228 RPN score loss: 0.00863 RPN total loss: 0.03143 Total loss: 1.5548 timestamp: 1655024888.7036183 iteration: 20555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10044 FastRCNN class loss: 0.07492 FastRCNN total loss: 0.17536 L1 loss: 0.0000e+00 L2 loss: 1.07994 Learning rate: 0.02 Mask loss: 0.18864 RPN box loss: 0.05071 RPN score loss: 0.00662 RPN total loss: 0.05732 Total loss: 1.50127 timestamp: 1655024892.0489526 iteration: 20560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2405 FastRCNN class loss: 0.13748 FastRCNN total loss: 0.37798 L1 loss: 0.0000e+00 L2 loss: 1.07974 Learning rate: 0.02 Mask loss: 0.24838 RPN box loss: 0.02091 RPN score loss: 0.01738 RPN total loss: 0.03829 Total loss: 1.74439 timestamp: 1655024895.3812997 iteration: 20565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.06556 FastRCNN total loss: 0.14586 L1 loss: 0.0000e+00 L2 loss: 1.07956 Learning rate: 0.02 Mask loss: 0.18951 RPN box loss: 0.03518 RPN score loss: 0.01103 RPN total loss: 0.04622 Total loss: 1.46114 timestamp: 1655024898.8570576 iteration: 20570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14933 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.21787 L1 loss: 0.0000e+00 L2 loss: 1.07938 Learning rate: 0.02 Mask loss: 0.30935 RPN box loss: 0.03124 RPN score loss: 0.00997 RPN total loss: 0.04121 Total loss: 1.64781 timestamp: 1655024902.1179438 iteration: 20575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16151 FastRCNN class loss: 0.06175 FastRCNN total loss: 0.22326 L1 loss: 0.0000e+00 L2 loss: 1.07921 Learning rate: 0.02 Mask loss: 0.15728 RPN box loss: 0.04891 RPN score loss: 0.00543 RPN total loss: 0.05433 Total loss: 1.51408 timestamp: 1655024905.4639285 iteration: 20580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16087 FastRCNN class loss: 0.11705 FastRCNN total loss: 0.27792 L1 loss: 0.0000e+00 L2 loss: 1.07901 Learning rate: 0.02 Mask loss: 0.15426 RPN box loss: 0.01591 RPN score loss: 0.00584 RPN total loss: 0.02175 Total loss: 1.53295 timestamp: 1655024908.6620445 iteration: 20585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19701 FastRCNN class loss: 0.11433 FastRCNN total loss: 0.31134 L1 loss: 0.0000e+00 L2 loss: 1.07881 Learning rate: 0.02 Mask loss: 0.32096 RPN box loss: 0.0117 RPN score loss: 0.00987 RPN total loss: 0.02157 Total loss: 1.73268 timestamp: 1655024912.0067828 iteration: 20590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16969 FastRCNN class loss: 0.08293 FastRCNN total loss: 0.25262 L1 loss: 0.0000e+00 L2 loss: 1.07862 Learning rate: 0.02 Mask loss: 0.19594 RPN box loss: 0.02168 RPN score loss: 0.00494 RPN total loss: 0.02661 Total loss: 1.55379 timestamp: 1655024915.2614052 iteration: 20595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21747 FastRCNN class loss: 0.10035 FastRCNN total loss: 0.31783 L1 loss: 0.0000e+00 L2 loss: 1.07845 Learning rate: 0.02 Mask loss: 0.14435 RPN box loss: 0.02792 RPN score loss: 0.01055 RPN total loss: 0.03846 Total loss: 1.57909 timestamp: 1655024918.5433455 iteration: 20600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23641 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.3164 L1 loss: 0.0000e+00 L2 loss: 1.07827 Learning rate: 0.02 Mask loss: 0.13465 RPN box loss: 0.0623 RPN score loss: 0.01232 RPN total loss: 0.07462 Total loss: 1.60394 timestamp: 1655024921.9595459 iteration: 20605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17046 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.25526 L1 loss: 0.0000e+00 L2 loss: 1.07811 Learning rate: 0.02 Mask loss: 0.11861 RPN box loss: 0.06022 RPN score loss: 0.01447 RPN total loss: 0.07469 Total loss: 1.52667 timestamp: 1655024925.2759142 iteration: 20610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1675 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.251 L1 loss: 0.0000e+00 L2 loss: 1.07792 Learning rate: 0.02 Mask loss: 0.15213 RPN box loss: 0.05624 RPN score loss: 0.00684 RPN total loss: 0.06308 Total loss: 1.54413 timestamp: 1655024928.6370955 iteration: 20615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17786 FastRCNN class loss: 0.09867 FastRCNN total loss: 0.27653 L1 loss: 0.0000e+00 L2 loss: 1.07774 Learning rate: 0.02 Mask loss: 0.22748 RPN box loss: 0.04524 RPN score loss: 0.00664 RPN total loss: 0.05188 Total loss: 1.63363 timestamp: 1655024931.9240608 iteration: 20620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18905 FastRCNN class loss: 0.10009 FastRCNN total loss: 0.28915 L1 loss: 0.0000e+00 L2 loss: 1.07754 Learning rate: 0.02 Mask loss: 0.19494 RPN box loss: 0.02035 RPN score loss: 0.00661 RPN total loss: 0.02696 Total loss: 1.58859 timestamp: 1655024935.274434 iteration: 20625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1648 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.24553 L1 loss: 0.0000e+00 L2 loss: 1.07734 Learning rate: 0.02 Mask loss: 0.14343 RPN box loss: 0.02298 RPN score loss: 0.00589 RPN total loss: 0.02888 Total loss: 1.49517 timestamp: 1655024938.5557637 iteration: 20630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09579 FastRCNN class loss: 0.06539 FastRCNN total loss: 0.16117 L1 loss: 0.0000e+00 L2 loss: 1.07714 Learning rate: 0.02 Mask loss: 0.1264 RPN box loss: 0.07027 RPN score loss: 0.00808 RPN total loss: 0.07835 Total loss: 1.44306 timestamp: 1655024941.886384 iteration: 20635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1519 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 1.07696 Learning rate: 0.02 Mask loss: 0.17982 RPN box loss: 0.01504 RPN score loss: 0.00344 RPN total loss: 0.01848 Total loss: 1.50232 timestamp: 1655024945.115727 iteration: 20640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19667 FastRCNN class loss: 0.12275 FastRCNN total loss: 0.31942 L1 loss: 0.0000e+00 L2 loss: 1.07681 Learning rate: 0.02 Mask loss: 0.19819 RPN box loss: 0.04013 RPN score loss: 0.00516 RPN total loss: 0.0453 Total loss: 1.63971 timestamp: 1655024948.439255 iteration: 20645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1795 FastRCNN class loss: 0.10712 FastRCNN total loss: 0.28661 L1 loss: 0.0000e+00 L2 loss: 1.07663 Learning rate: 0.02 Mask loss: 0.19092 RPN box loss: 0.03042 RPN score loss: 0.00626 RPN total loss: 0.03667 Total loss: 1.59084 timestamp: 1655024951.762285 iteration: 20650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11341 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.19527 L1 loss: 0.0000e+00 L2 loss: 1.07644 Learning rate: 0.02 Mask loss: 0.17345 RPN box loss: 0.03245 RPN score loss: 0.01141 RPN total loss: 0.04385 Total loss: 1.48902 timestamp: 1655024954.9882305 iteration: 20655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09556 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.15626 L1 loss: 0.0000e+00 L2 loss: 1.07625 Learning rate: 0.02 Mask loss: 0.14777 RPN box loss: 0.02064 RPN score loss: 0.00355 RPN total loss: 0.02419 Total loss: 1.40447 timestamp: 1655024958.4168003 iteration: 20660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15874 FastRCNN class loss: 0.09229 FastRCNN total loss: 0.25103 L1 loss: 0.0000e+00 L2 loss: 1.0761 Learning rate: 0.02 Mask loss: 0.26664 RPN box loss: 0.07599 RPN score loss: 0.00782 RPN total loss: 0.08381 Total loss: 1.67757 timestamp: 1655024961.747267 iteration: 20665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15517 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.22465 L1 loss: 0.0000e+00 L2 loss: 1.07593 Learning rate: 0.02 Mask loss: 0.19374 RPN box loss: 0.01405 RPN score loss: 0.00389 RPN total loss: 0.01794 Total loss: 1.51226 timestamp: 1655024965.1757329 iteration: 20670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17362 FastRCNN class loss: 0.11214 FastRCNN total loss: 0.28576 L1 loss: 0.0000e+00 L2 loss: 1.07572 Learning rate: 0.02 Mask loss: 0.16492 RPN box loss: 0.04455 RPN score loss: 0.00477 RPN total loss: 0.04933 Total loss: 1.57572 timestamp: 1655024968.480807 iteration: 20675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12943 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.18297 L1 loss: 0.0000e+00 L2 loss: 1.07556 Learning rate: 0.02 Mask loss: 0.16311 RPN box loss: 0.00319 RPN score loss: 0.00163 RPN total loss: 0.00482 Total loss: 1.42646 timestamp: 1655024971.932251 iteration: 20680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19459 FastRCNN class loss: 0.08072 FastRCNN total loss: 0.2753 L1 loss: 0.0000e+00 L2 loss: 1.07538 Learning rate: 0.02 Mask loss: 0.11355 RPN box loss: 0.0576 RPN score loss: 0.00445 RPN total loss: 0.06205 Total loss: 1.52628 timestamp: 1655024975.1973162 iteration: 20685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16704 FastRCNN class loss: 0.08459 FastRCNN total loss: 0.25163 L1 loss: 0.0000e+00 L2 loss: 1.07519 Learning rate: 0.02 Mask loss: 0.22737 RPN box loss: 0.02036 RPN score loss: 0.00644 RPN total loss: 0.0268 Total loss: 1.581 timestamp: 1655024978.4974008 iteration: 20690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2081 FastRCNN class loss: 0.11933 FastRCNN total loss: 0.32743 L1 loss: 0.0000e+00 L2 loss: 1.075 Learning rate: 0.02 Mask loss: 0.19928 RPN box loss: 0.0321 RPN score loss: 0.01164 RPN total loss: 0.04375 Total loss: 1.64545 timestamp: 1655024981.8892543 iteration: 20695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18672 FastRCNN class loss: 0.11949 FastRCNN total loss: 0.30621 L1 loss: 0.0000e+00 L2 loss: 1.07483 Learning rate: 0.02 Mask loss: 0.27029 RPN box loss: 0.0484 RPN score loss: 0.00979 RPN total loss: 0.05819 Total loss: 1.70952 timestamp: 1655024985.1682944 iteration: 20700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19411 FastRCNN class loss: 0.08982 FastRCNN total loss: 0.28393 L1 loss: 0.0000e+00 L2 loss: 1.07465 Learning rate: 0.02 Mask loss: 0.20153 RPN box loss: 0.03979 RPN score loss: 0.0101 RPN total loss: 0.04989 Total loss: 1.61 timestamp: 1655024988.6225474 iteration: 20705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13785 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.21788 L1 loss: 0.0000e+00 L2 loss: 1.07448 Learning rate: 0.02 Mask loss: 0.11836 RPN box loss: 0.00577 RPN score loss: 0.00384 RPN total loss: 0.00961 Total loss: 1.42033 timestamp: 1655024991.9011688 iteration: 20710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12189 FastRCNN class loss: 0.05956 FastRCNN total loss: 0.18145 L1 loss: 0.0000e+00 L2 loss: 1.07428 Learning rate: 0.02 Mask loss: 0.16225 RPN box loss: 0.02337 RPN score loss: 0.00382 RPN total loss: 0.02719 Total loss: 1.44517 timestamp: 1655024995.1840522 iteration: 20715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10316 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.16516 L1 loss: 0.0000e+00 L2 loss: 1.07411 Learning rate: 0.02 Mask loss: 0.14458 RPN box loss: 0.041 RPN score loss: 0.00599 RPN total loss: 0.04699 Total loss: 1.43084 timestamp: 1655024998.5400376 iteration: 20720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28682 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.36685 L1 loss: 0.0000e+00 L2 loss: 1.07395 Learning rate: 0.02 Mask loss: 0.13397 RPN box loss: 0.05756 RPN score loss: 0.0121 RPN total loss: 0.06965 Total loss: 1.64443 timestamp: 1655025002.092718 iteration: 20725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11459 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 1.07376 Learning rate: 0.02 Mask loss: 0.17756 RPN box loss: 0.02463 RPN score loss: 0.00548 RPN total loss: 0.0301 Total loss: 1.44838 timestamp: 1655025005.3825257 iteration: 20730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.05734 FastRCNN total loss: 0.19689 L1 loss: 0.0000e+00 L2 loss: 1.07355 Learning rate: 0.02 Mask loss: 0.15172 RPN box loss: 0.03992 RPN score loss: 0.00593 RPN total loss: 0.04586 Total loss: 1.46801 timestamp: 1655025008.7543554 iteration: 20735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15515 FastRCNN class loss: 0.09953 FastRCNN total loss: 0.25468 L1 loss: 0.0000e+00 L2 loss: 1.07335 Learning rate: 0.02 Mask loss: 0.11467 RPN box loss: 0.03151 RPN score loss: 0.00494 RPN total loss: 0.03645 Total loss: 1.47915 timestamp: 1655025012.0943122 iteration: 20740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08966 FastRCNN class loss: 0.0524 FastRCNN total loss: 0.14206 L1 loss: 0.0000e+00 L2 loss: 1.07318 Learning rate: 0.02 Mask loss: 0.1141 RPN box loss: 0.03586 RPN score loss: 0.00648 RPN total loss: 0.04234 Total loss: 1.37167 timestamp: 1655025015.3655593 iteration: 20745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12953 FastRCNN class loss: 0.09076 FastRCNN total loss: 0.22028 L1 loss: 0.0000e+00 L2 loss: 1.073 Learning rate: 0.02 Mask loss: 0.17828 RPN box loss: 0.02448 RPN score loss: 0.00216 RPN total loss: 0.02664 Total loss: 1.4982 timestamp: 1655025018.7992911 iteration: 20750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22435 FastRCNN class loss: 0.12841 FastRCNN total loss: 0.35276 L1 loss: 0.0000e+00 L2 loss: 1.07283 Learning rate: 0.02 Mask loss: 0.19129 RPN box loss: 0.04653 RPN score loss: 0.02125 RPN total loss: 0.06779 Total loss: 1.68466 timestamp: 1655025022.0532534 iteration: 20755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.12329 FastRCNN total loss: 0.22005 L1 loss: 0.0000e+00 L2 loss: 1.07263 Learning rate: 0.02 Mask loss: 0.18045 RPN box loss: 0.03217 RPN score loss: 0.00646 RPN total loss: 0.03862 Total loss: 1.51175 timestamp: 1655025025.447902 iteration: 20760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.07472 FastRCNN total loss: 0.23715 L1 loss: 0.0000e+00 L2 loss: 1.07243 Learning rate: 0.02 Mask loss: 0.15275 RPN box loss: 0.0214 RPN score loss: 0.0046 RPN total loss: 0.026 Total loss: 1.48834 timestamp: 1655025028.7501476 iteration: 20765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23423 FastRCNN class loss: 0.10303 FastRCNN total loss: 0.33726 L1 loss: 0.0000e+00 L2 loss: 1.07225 Learning rate: 0.02 Mask loss: 0.2067 RPN box loss: 0.02375 RPN score loss: 0.00443 RPN total loss: 0.02818 Total loss: 1.64439 timestamp: 1655025032.1486604 iteration: 20770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22882 FastRCNN class loss: 0.09556 FastRCNN total loss: 0.32438 L1 loss: 0.0000e+00 L2 loss: 1.07205 Learning rate: 0.02 Mask loss: 0.1629 RPN box loss: 0.03585 RPN score loss: 0.00505 RPN total loss: 0.0409 Total loss: 1.60023 timestamp: 1655025035.4582813 iteration: 20775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09739 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.16891 L1 loss: 0.0000e+00 L2 loss: 1.0719 Learning rate: 0.02 Mask loss: 0.13822 RPN box loss: 0.03341 RPN score loss: 0.00847 RPN total loss: 0.04189 Total loss: 1.42091 timestamp: 1655025038.704114 iteration: 20780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06057 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.12836 L1 loss: 0.0000e+00 L2 loss: 1.07173 Learning rate: 0.02 Mask loss: 0.23801 RPN box loss: 0.01519 RPN score loss: 0.00161 RPN total loss: 0.0168 Total loss: 1.4549 timestamp: 1655025042.0722427 iteration: 20785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15058 FastRCNN class loss: 0.08203 FastRCNN total loss: 0.23262 L1 loss: 0.0000e+00 L2 loss: 1.07151 Learning rate: 0.02 Mask loss: 0.20721 RPN box loss: 0.07041 RPN score loss: 0.0172 RPN total loss: 0.08761 Total loss: 1.59895 timestamp: 1655025045.414156 iteration: 20790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12915 FastRCNN class loss: 0.09282 FastRCNN total loss: 0.22197 L1 loss: 0.0000e+00 L2 loss: 1.07135 Learning rate: 0.02 Mask loss: 0.14097 RPN box loss: 0.02818 RPN score loss: 0.01123 RPN total loss: 0.0394 Total loss: 1.47369 timestamp: 1655025048.8610446 iteration: 20795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09212 FastRCNN class loss: 0.08445 FastRCNN total loss: 0.17656 L1 loss: 0.0000e+00 L2 loss: 1.07117 Learning rate: 0.02 Mask loss: 0.17149 RPN box loss: 0.02926 RPN score loss: 0.00424 RPN total loss: 0.03351 Total loss: 1.45273 timestamp: 1655025052.134478 iteration: 20800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20382 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.27478 L1 loss: 0.0000e+00 L2 loss: 1.071 Learning rate: 0.02 Mask loss: 0.16861 RPN box loss: 0.03303 RPN score loss: 0.00377 RPN total loss: 0.03681 Total loss: 1.55119 timestamp: 1655025055.474787 iteration: 20805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15773 FastRCNN class loss: 0.10172 FastRCNN total loss: 0.25945 L1 loss: 0.0000e+00 L2 loss: 1.07083 Learning rate: 0.02 Mask loss: 0.20006 RPN box loss: 0.01695 RPN score loss: 0.00864 RPN total loss: 0.02559 Total loss: 1.55593 timestamp: 1655025058.760792 iteration: 20810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.04554 FastRCNN total loss: 0.1506 L1 loss: 0.0000e+00 L2 loss: 1.07067 Learning rate: 0.02 Mask loss: 0.19296 RPN box loss: 0.00468 RPN score loss: 0.00253 RPN total loss: 0.00722 Total loss: 1.42144 timestamp: 1655025062.1453352 iteration: 20815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.07489 FastRCNN total loss: 0.17761 L1 loss: 0.0000e+00 L2 loss: 1.07049 Learning rate: 0.02 Mask loss: 0.16877 RPN box loss: 0.07084 RPN score loss: 0.00928 RPN total loss: 0.08012 Total loss: 1.49699 timestamp: 1655025065.4375248 iteration: 20820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18928 FastRCNN class loss: 0.10972 FastRCNN total loss: 0.299 L1 loss: 0.0000e+00 L2 loss: 1.07032 Learning rate: 0.02 Mask loss: 0.20749 RPN box loss: 0.01329 RPN score loss: 0.00488 RPN total loss: 0.01817 Total loss: 1.59499 timestamp: 1655025068.6518872 iteration: 20825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17787 FastRCNN class loss: 0.08383 FastRCNN total loss: 0.2617 L1 loss: 0.0000e+00 L2 loss: 1.07013 Learning rate: 0.02 Mask loss: 0.2066 RPN box loss: 0.0418 RPN score loss: 0.01298 RPN total loss: 0.05478 Total loss: 1.5932 timestamp: 1655025072.0776663 iteration: 20830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10302 FastRCNN class loss: 0.10272 FastRCNN total loss: 0.20573 L1 loss: 0.0000e+00 L2 loss: 1.06994 Learning rate: 0.02 Mask loss: 0.16335 RPN box loss: 0.02485 RPN score loss: 0.01191 RPN total loss: 0.03676 Total loss: 1.47578 timestamp: 1655025075.3636377 iteration: 20835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10443 FastRCNN class loss: 0.12668 FastRCNN total loss: 0.23112 L1 loss: 0.0000e+00 L2 loss: 1.06976 Learning rate: 0.02 Mask loss: 0.13482 RPN box loss: 0.04126 RPN score loss: 0.00875 RPN total loss: 0.05001 Total loss: 1.48571 timestamp: 1655025078.7187197 iteration: 20840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19191 FastRCNN class loss: 0.08536 FastRCNN total loss: 0.27727 L1 loss: 0.0000e+00 L2 loss: 1.06956 Learning rate: 0.02 Mask loss: 0.15435 RPN box loss: 0.02412 RPN score loss: 0.0059 RPN total loss: 0.03003 Total loss: 1.53121 timestamp: 1655025082.033493 iteration: 20845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13838 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.22922 L1 loss: 0.0000e+00 L2 loss: 1.0694 Learning rate: 0.02 Mask loss: 0.13828 RPN box loss: 0.01373 RPN score loss: 0.00312 RPN total loss: 0.01684 Total loss: 1.45373 timestamp: 1655025085.383373 iteration: 20850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0957 FastRCNN class loss: 0.09068 FastRCNN total loss: 0.18637 L1 loss: 0.0000e+00 L2 loss: 1.06922 Learning rate: 0.02 Mask loss: 0.12034 RPN box loss: 0.05023 RPN score loss: 0.00487 RPN total loss: 0.0551 Total loss: 1.43104 timestamp: 1655025088.6761754 iteration: 20855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15399 FastRCNN class loss: 0.11056 FastRCNN total loss: 0.26456 L1 loss: 0.0000e+00 L2 loss: 1.06903 Learning rate: 0.02 Mask loss: 0.1294 RPN box loss: 0.02461 RPN score loss: 0.01117 RPN total loss: 0.03579 Total loss: 1.49877 timestamp: 1655025091.9641955 iteration: 20860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.10691 FastRCNN total loss: 0.22709 L1 loss: 0.0000e+00 L2 loss: 1.06884 Learning rate: 0.02 Mask loss: 0.15882 RPN box loss: 0.04709 RPN score loss: 0.00991 RPN total loss: 0.05701 Total loss: 1.51176 timestamp: 1655025095.3914788 iteration: 20865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1379 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.21841 L1 loss: 0.0000e+00 L2 loss: 1.06867 Learning rate: 0.02 Mask loss: 0.17049 RPN box loss: 0.02816 RPN score loss: 0.00355 RPN total loss: 0.03171 Total loss: 1.48927 timestamp: 1655025098.6648536 iteration: 20870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22063 FastRCNN class loss: 0.11928 FastRCNN total loss: 0.33991 L1 loss: 0.0000e+00 L2 loss: 1.0685 Learning rate: 0.02 Mask loss: 0.16642 RPN box loss: 0.09817 RPN score loss: 0.01232 RPN total loss: 0.11048 Total loss: 1.68531 timestamp: 1655025101.9761662 iteration: 20875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18792 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.29228 L1 loss: 0.0000e+00 L2 loss: 1.06832 Learning rate: 0.02 Mask loss: 0.18865 RPN box loss: 0.04045 RPN score loss: 0.01308 RPN total loss: 0.05354 Total loss: 1.60279 timestamp: 1655025105.201744 iteration: 20880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21028 FastRCNN class loss: 0.11158 FastRCNN total loss: 0.32185 L1 loss: 0.0000e+00 L2 loss: 1.06812 Learning rate: 0.02 Mask loss: 0.28123 RPN box loss: 0.04884 RPN score loss: 0.01586 RPN total loss: 0.06471 Total loss: 1.73592 timestamp: 1655025108.6562855 iteration: 20885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12512 FastRCNN class loss: 0.10131 FastRCNN total loss: 0.22643 L1 loss: 0.0000e+00 L2 loss: 1.06794 Learning rate: 0.02 Mask loss: 0.1321 RPN box loss: 0.0338 RPN score loss: 0.01088 RPN total loss: 0.04469 Total loss: 1.47116 timestamp: 1655025111.9747388 iteration: 20890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14835 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.21656 L1 loss: 0.0000e+00 L2 loss: 1.06775 Learning rate: 0.02 Mask loss: 0.20198 RPN box loss: 0.06186 RPN score loss: 0.01306 RPN total loss: 0.07492 Total loss: 1.56121 timestamp: 1655025115.3340743 iteration: 20895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12999 FastRCNN class loss: 0.07321 FastRCNN total loss: 0.2032 L1 loss: 0.0000e+00 L2 loss: 1.06758 Learning rate: 0.02 Mask loss: 0.10336 RPN box loss: 0.02581 RPN score loss: 0.00895 RPN total loss: 0.03476 Total loss: 1.40891 timestamp: 1655025118.5911493 iteration: 20900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07582 FastRCNN class loss: 0.07752 FastRCNN total loss: 0.15334 L1 loss: 0.0000e+00 L2 loss: 1.06742 Learning rate: 0.02 Mask loss: 0.22382 RPN box loss: 0.04223 RPN score loss: 0.02457 RPN total loss: 0.0668 Total loss: 1.51138 timestamp: 1655025121.9500656 iteration: 20905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.15604 L1 loss: 0.0000e+00 L2 loss: 1.06722 Learning rate: 0.02 Mask loss: 0.10216 RPN box loss: 0.01402 RPN score loss: 0.00762 RPN total loss: 0.02163 Total loss: 1.34705 timestamp: 1655025125.2721097 iteration: 20910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12869 FastRCNN class loss: 0.09782 FastRCNN total loss: 0.22651 L1 loss: 0.0000e+00 L2 loss: 1.06703 Learning rate: 0.02 Mask loss: 0.20443 RPN box loss: 0.0539 RPN score loss: 0.02196 RPN total loss: 0.07586 Total loss: 1.57383 timestamp: 1655025128.5983043 iteration: 20915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11304 FastRCNN class loss: 0.0916 FastRCNN total loss: 0.20464 L1 loss: 0.0000e+00 L2 loss: 1.06683 Learning rate: 0.02 Mask loss: 0.1136 RPN box loss: 0.04509 RPN score loss: 0.02172 RPN total loss: 0.06681 Total loss: 1.45189 timestamp: 1655025132.0967262 iteration: 20920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.18688 L1 loss: 0.0000e+00 L2 loss: 1.06667 Learning rate: 0.02 Mask loss: 0.16729 RPN box loss: 0.01001 RPN score loss: 0.0057 RPN total loss: 0.01572 Total loss: 1.43656 timestamp: 1655025135.4349961 iteration: 20925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07774 FastRCNN class loss: 0.05812 FastRCNN total loss: 0.13586 L1 loss: 0.0000e+00 L2 loss: 1.06651 Learning rate: 0.02 Mask loss: 0.16453 RPN box loss: 0.01266 RPN score loss: 0.00158 RPN total loss: 0.01424 Total loss: 1.38114 timestamp: 1655025138.88237 iteration: 20930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14882 FastRCNN class loss: 0.07332 FastRCNN total loss: 0.22214 L1 loss: 0.0000e+00 L2 loss: 1.06634 Learning rate: 0.02 Mask loss: 0.14777 RPN box loss: 0.01788 RPN score loss: 0.00429 RPN total loss: 0.02216 Total loss: 1.45842 timestamp: 1655025142.196328 iteration: 20935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21491 FastRCNN class loss: 0.1313 FastRCNN total loss: 0.34621 L1 loss: 0.0000e+00 L2 loss: 1.06614 Learning rate: 0.02 Mask loss: 0.23345 RPN box loss: 0.01441 RPN score loss: 0.01107 RPN total loss: 0.02548 Total loss: 1.67128 timestamp: 1655025145.5464609 iteration: 20940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19665 FastRCNN class loss: 0.10196 FastRCNN total loss: 0.29861 L1 loss: 0.0000e+00 L2 loss: 1.06598 Learning rate: 0.02 Mask loss: 0.17003 RPN box loss: 0.03175 RPN score loss: 0.0065 RPN total loss: 0.03825 Total loss: 1.57286 timestamp: 1655025148.9350355 iteration: 20945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13577 FastRCNN class loss: 0.06731 FastRCNN total loss: 0.20309 L1 loss: 0.0000e+00 L2 loss: 1.0658 Learning rate: 0.02 Mask loss: 0.1895 RPN box loss: 0.00565 RPN score loss: 0.00758 RPN total loss: 0.01323 Total loss: 1.47161 timestamp: 1655025152.2333848 iteration: 20950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16937 FastRCNN class loss: 0.12107 FastRCNN total loss: 0.29045 L1 loss: 0.0000e+00 L2 loss: 1.06561 Learning rate: 0.02 Mask loss: 0.19967 RPN box loss: 0.04512 RPN score loss: 0.0155 RPN total loss: 0.06062 Total loss: 1.61636 timestamp: 1655025155.5292287 iteration: 20955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18333 FastRCNN class loss: 0.08834 FastRCNN total loss: 0.27167 L1 loss: 0.0000e+00 L2 loss: 1.06545 Learning rate: 0.02 Mask loss: 0.11864 RPN box loss: 0.06239 RPN score loss: 0.01422 RPN total loss: 0.07662 Total loss: 1.53238 timestamp: 1655025158.724036 iteration: 20960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22328 FastRCNN class loss: 0.12858 FastRCNN total loss: 0.35186 L1 loss: 0.0000e+00 L2 loss: 1.06526 Learning rate: 0.02 Mask loss: 0.16467 RPN box loss: 0.03147 RPN score loss: 0.01054 RPN total loss: 0.042 Total loss: 1.6238 timestamp: 1655025162.0767252 iteration: 20965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16882 FastRCNN class loss: 0.09191 FastRCNN total loss: 0.26073 L1 loss: 0.0000e+00 L2 loss: 1.06508 Learning rate: 0.02 Mask loss: 0.22008 RPN box loss: 0.03526 RPN score loss: 0.00779 RPN total loss: 0.04305 Total loss: 1.58893 timestamp: 1655025165.3965814 iteration: 20970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20572 FastRCNN class loss: 0.10353 FastRCNN total loss: 0.30925 L1 loss: 0.0000e+00 L2 loss: 1.06491 Learning rate: 0.02 Mask loss: 0.18122 RPN box loss: 0.04598 RPN score loss: 0.00723 RPN total loss: 0.05321 Total loss: 1.60859 timestamp: 1655025168.684574 iteration: 20975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16269 FastRCNN class loss: 0.08372 FastRCNN total loss: 0.24641 L1 loss: 0.0000e+00 L2 loss: 1.06472 Learning rate: 0.02 Mask loss: 0.13864 RPN box loss: 0.04762 RPN score loss: 0.0062 RPN total loss: 0.05382 Total loss: 1.50359 timestamp: 1655025171.9622526 iteration: 20980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17737 FastRCNN class loss: 0.0917 FastRCNN total loss: 0.26907 L1 loss: 0.0000e+00 L2 loss: 1.06452 Learning rate: 0.02 Mask loss: 0.1412 RPN box loss: 0.05372 RPN score loss: 0.0061 RPN total loss: 0.05982 Total loss: 1.53462 timestamp: 1655025175.276433 iteration: 20985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06212 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.12362 L1 loss: 0.0000e+00 L2 loss: 1.06433 Learning rate: 0.02 Mask loss: 0.27455 RPN box loss: 0.00661 RPN score loss: 0.00754 RPN total loss: 0.01414 Total loss: 1.47666 timestamp: 1655025178.6039443 iteration: 20990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13686 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.23184 L1 loss: 0.0000e+00 L2 loss: 1.06418 Learning rate: 0.02 Mask loss: 0.15054 RPN box loss: 0.03886 RPN score loss: 0.00798 RPN total loss: 0.04684 Total loss: 1.49339 timestamp: 1655025181.9866586 iteration: 20995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16204 FastRCNN class loss: 0.08918 FastRCNN total loss: 0.25122 L1 loss: 0.0000e+00 L2 loss: 1.06399 Learning rate: 0.02 Mask loss: 0.15771 RPN box loss: 0.04539 RPN score loss: 0.02779 RPN total loss: 0.07317 Total loss: 1.5461 timestamp: 1655025185.3533025 iteration: 21000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1432 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.19903 L1 loss: 0.0000e+00 L2 loss: 1.06382 Learning rate: 0.02 Mask loss: 0.13327 RPN box loss: 0.04996 RPN score loss: 0.00738 RPN total loss: 0.05735 Total loss: 1.45346 timestamp: 1655025188.7042325 iteration: 21005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11842 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.16823 L1 loss: 0.0000e+00 L2 loss: 1.06367 Learning rate: 0.02 Mask loss: 0.15302 RPN box loss: 0.07255 RPN score loss: 0.0119 RPN total loss: 0.08445 Total loss: 1.46937 timestamp: 1655025192.1041903 iteration: 21010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19254 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.26925 L1 loss: 0.0000e+00 L2 loss: 1.06349 Learning rate: 0.02 Mask loss: 0.18748 RPN box loss: 0.04785 RPN score loss: 0.00665 RPN total loss: 0.05451 Total loss: 1.57472 timestamp: 1655025195.4287076 iteration: 21015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08634 FastRCNN class loss: 0.04295 FastRCNN total loss: 0.12929 L1 loss: 0.0000e+00 L2 loss: 1.06332 Learning rate: 0.02 Mask loss: 0.16448 RPN box loss: 0.00854 RPN score loss: 0.00562 RPN total loss: 0.01416 Total loss: 1.37125 timestamp: 1655025198.7887282 iteration: 21020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2443 FastRCNN class loss: 0.13138 FastRCNN total loss: 0.37567 L1 loss: 0.0000e+00 L2 loss: 1.06313 Learning rate: 0.02 Mask loss: 0.30865 RPN box loss: 0.03455 RPN score loss: 0.01842 RPN total loss: 0.05297 Total loss: 1.80042 timestamp: 1655025202.0570514 iteration: 21025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1458 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.2414 L1 loss: 0.0000e+00 L2 loss: 1.06294 Learning rate: 0.02 Mask loss: 0.1379 RPN box loss: 0.02198 RPN score loss: 0.00641 RPN total loss: 0.0284 Total loss: 1.47065 timestamp: 1655025205.4120576 iteration: 21030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.08384 FastRCNN total loss: 0.16412 L1 loss: 0.0000e+00 L2 loss: 1.06275 Learning rate: 0.02 Mask loss: 0.17364 RPN box loss: 0.12939 RPN score loss: 0.01508 RPN total loss: 0.14447 Total loss: 1.54499 timestamp: 1655025208.7812243 iteration: 21035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12654 FastRCNN class loss: 0.11383 FastRCNN total loss: 0.24037 L1 loss: 0.0000e+00 L2 loss: 1.06255 Learning rate: 0.02 Mask loss: 0.16643 RPN box loss: 0.03227 RPN score loss: 0.01123 RPN total loss: 0.0435 Total loss: 1.51285 timestamp: 1655025212.063758 iteration: 21040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25275 FastRCNN class loss: 0.10543 FastRCNN total loss: 0.35818 L1 loss: 0.0000e+00 L2 loss: 1.06239 Learning rate: 0.02 Mask loss: 0.23532 RPN box loss: 0.0432 RPN score loss: 0.00863 RPN total loss: 0.05183 Total loss: 1.70774 timestamp: 1655025215.4008172 iteration: 21045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17087 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.23055 L1 loss: 0.0000e+00 L2 loss: 1.06221 Learning rate: 0.02 Mask loss: 0.17291 RPN box loss: 0.0187 RPN score loss: 0.00928 RPN total loss: 0.02798 Total loss: 1.49366 timestamp: 1655025218.6382284 iteration: 21050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11746 FastRCNN class loss: 0.07975 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 1.06203 Learning rate: 0.02 Mask loss: 0.1787 RPN box loss: 0.04373 RPN score loss: 0.00627 RPN total loss: 0.04999 Total loss: 1.48793 timestamp: 1655025222.0414553 iteration: 21055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.05274 FastRCNN total loss: 0.14732 L1 loss: 0.0000e+00 L2 loss: 1.06187 Learning rate: 0.02 Mask loss: 0.11477 RPN box loss: 0.02485 RPN score loss: 0.00433 RPN total loss: 0.02918 Total loss: 1.35314 timestamp: 1655025225.3960757 iteration: 21060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17269 FastRCNN class loss: 0.09104 FastRCNN total loss: 0.26373 L1 loss: 0.0000e+00 L2 loss: 1.06168 Learning rate: 0.02 Mask loss: 0.13365 RPN box loss: 0.02601 RPN score loss: 0.00513 RPN total loss: 0.03114 Total loss: 1.49021 timestamp: 1655025228.887387 iteration: 21065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10701 FastRCNN class loss: 0.07972 FastRCNN total loss: 0.18673 L1 loss: 0.0000e+00 L2 loss: 1.06148 Learning rate: 0.02 Mask loss: 0.18062 RPN box loss: 0.06606 RPN score loss: 0.00639 RPN total loss: 0.07245 Total loss: 1.50127 timestamp: 1655025232.1417887 iteration: 21070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15835 FastRCNN class loss: 0.11148 FastRCNN total loss: 0.26983 L1 loss: 0.0000e+00 L2 loss: 1.0613 Learning rate: 0.02 Mask loss: 0.16542 RPN box loss: 0.06589 RPN score loss: 0.00813 RPN total loss: 0.07402 Total loss: 1.57057 timestamp: 1655025235.458445 iteration: 21075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.0662 FastRCNN total loss: 0.1798 L1 loss: 0.0000e+00 L2 loss: 1.06113 Learning rate: 0.02 Mask loss: 0.18085 RPN box loss: 0.01749 RPN score loss: 0.00509 RPN total loss: 0.02257 Total loss: 1.44435 timestamp: 1655025238.855649 iteration: 21080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15288 FastRCNN class loss: 0.05633 FastRCNN total loss: 0.2092 L1 loss: 0.0000e+00 L2 loss: 1.06096 Learning rate: 0.02 Mask loss: 0.14363 RPN box loss: 0.02042 RPN score loss: 0.00778 RPN total loss: 0.0282 Total loss: 1.44199 timestamp: 1655025242.1088548 iteration: 21085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17169 FastRCNN class loss: 0.11407 FastRCNN total loss: 0.28575 L1 loss: 0.0000e+00 L2 loss: 1.06077 Learning rate: 0.02 Mask loss: 0.23503 RPN box loss: 0.01697 RPN score loss: 0.00404 RPN total loss: 0.021 Total loss: 1.60256 timestamp: 1655025245.495602 iteration: 21090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1897 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.26329 L1 loss: 0.0000e+00 L2 loss: 1.06061 Learning rate: 0.02 Mask loss: 0.17573 RPN box loss: 0.02212 RPN score loss: 0.00776 RPN total loss: 0.02988 Total loss: 1.5295 timestamp: 1655025248.8443487 iteration: 21095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15704 FastRCNN class loss: 0.10196 FastRCNN total loss: 0.259 L1 loss: 0.0000e+00 L2 loss: 1.06045 Learning rate: 0.02 Mask loss: 0.19921 RPN box loss: 0.06232 RPN score loss: 0.00751 RPN total loss: 0.06983 Total loss: 1.58848 timestamp: 1655025252.1410465 iteration: 21100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20081 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.26994 L1 loss: 0.0000e+00 L2 loss: 1.06026 Learning rate: 0.02 Mask loss: 0.21441 RPN box loss: 0.06497 RPN score loss: 0.0118 RPN total loss: 0.07677 Total loss: 1.62137 timestamp: 1655025255.398345 iteration: 21105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09022 FastRCNN class loss: 0.0612 FastRCNN total loss: 0.15143 L1 loss: 0.0000e+00 L2 loss: 1.06009 Learning rate: 0.02 Mask loss: 0.16988 RPN box loss: 0.03665 RPN score loss: 0.00568 RPN total loss: 0.04233 Total loss: 1.42373 timestamp: 1655025258.7402928 iteration: 21110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17374 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.25646 L1 loss: 0.0000e+00 L2 loss: 1.05991 Learning rate: 0.02 Mask loss: 0.19742 RPN box loss: 0.03336 RPN score loss: 0.01068 RPN total loss: 0.04404 Total loss: 1.55783 timestamp: 1655025262.0316782 iteration: 21115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2147 FastRCNN class loss: 0.09189 FastRCNN total loss: 0.30658 L1 loss: 0.0000e+00 L2 loss: 1.05971 Learning rate: 0.02 Mask loss: 0.20094 RPN box loss: 0.06711 RPN score loss: 0.00581 RPN total loss: 0.07292 Total loss: 1.64015 timestamp: 1655025265.4813414 iteration: 21120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10897 FastRCNN class loss: 0.08304 FastRCNN total loss: 0.19202 L1 loss: 0.0000e+00 L2 loss: 1.05956 Learning rate: 0.02 Mask loss: 0.14379 RPN box loss: 0.0465 RPN score loss: 0.00398 RPN total loss: 0.05049 Total loss: 1.44586 timestamp: 1655025268.8018382 iteration: 21125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1568 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.2273 L1 loss: 0.0000e+00 L2 loss: 1.0594 Learning rate: 0.02 Mask loss: 0.21036 RPN box loss: 0.06177 RPN score loss: 0.01043 RPN total loss: 0.07221 Total loss: 1.56927 timestamp: 1655025272.0738716 iteration: 21130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1833 FastRCNN class loss: 0.03685 FastRCNN total loss: 0.22015 L1 loss: 0.0000e+00 L2 loss: 1.05922 Learning rate: 0.02 Mask loss: 0.12956 RPN box loss: 0.00631 RPN score loss: 0.00898 RPN total loss: 0.01529 Total loss: 1.42422 timestamp: 1655025275.467872 iteration: 21135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12036 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.1942 L1 loss: 0.0000e+00 L2 loss: 1.05906 Learning rate: 0.02 Mask loss: 0.18043 RPN box loss: 0.01381 RPN score loss: 0.00269 RPN total loss: 0.0165 Total loss: 1.45018 timestamp: 1655025278.7787313 iteration: 21140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07687 FastRCNN class loss: 0.05188 FastRCNN total loss: 0.12875 L1 loss: 0.0000e+00 L2 loss: 1.05886 Learning rate: 0.02 Mask loss: 0.0931 RPN box loss: 0.00847 RPN score loss: 0.00425 RPN total loss: 0.01271 Total loss: 1.29343 timestamp: 1655025282.1342454 iteration: 21145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20878 FastRCNN class loss: 0.10887 FastRCNN total loss: 0.31765 L1 loss: 0.0000e+00 L2 loss: 1.0587 Learning rate: 0.02 Mask loss: 0.11097 RPN box loss: 0.03078 RPN score loss: 0.00642 RPN total loss: 0.0372 Total loss: 1.52453 timestamp: 1655025285.3825467 iteration: 21150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17128 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.28471 L1 loss: 0.0000e+00 L2 loss: 1.05853 Learning rate: 0.02 Mask loss: 0.19178 RPN box loss: 0.04535 RPN score loss: 0.00946 RPN total loss: 0.05481 Total loss: 1.58982 timestamp: 1655025288.8134382 iteration: 21155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15802 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.23013 L1 loss: 0.0000e+00 L2 loss: 1.05833 Learning rate: 0.02 Mask loss: 0.13737 RPN box loss: 0.02145 RPN score loss: 0.00271 RPN total loss: 0.02416 Total loss: 1.44999 timestamp: 1655025292.0215213 iteration: 21160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1832 FastRCNN class loss: 0.05435 FastRCNN total loss: 0.23755 L1 loss: 0.0000e+00 L2 loss: 1.05817 Learning rate: 0.02 Mask loss: 0.11907 RPN box loss: 0.01922 RPN score loss: 0.00462 RPN total loss: 0.02384 Total loss: 1.43863 timestamp: 1655025295.3929079 iteration: 21165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17184 FastRCNN class loss: 0.08954 FastRCNN total loss: 0.26138 L1 loss: 0.0000e+00 L2 loss: 1.058 Learning rate: 0.02 Mask loss: 0.19383 RPN box loss: 0.01986 RPN score loss: 0.00379 RPN total loss: 0.02365 Total loss: 1.53686 timestamp: 1655025298.7004423 iteration: 21170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11738 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.19854 L1 loss: 0.0000e+00 L2 loss: 1.05782 Learning rate: 0.02 Mask loss: 0.15259 RPN box loss: 0.02669 RPN score loss: 0.00502 RPN total loss: 0.03171 Total loss: 1.44066 timestamp: 1655025301.9830425 iteration: 21175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18531 FastRCNN class loss: 0.11937 FastRCNN total loss: 0.30468 L1 loss: 0.0000e+00 L2 loss: 1.05764 Learning rate: 0.02 Mask loss: 0.2024 RPN box loss: 0.01539 RPN score loss: 0.00556 RPN total loss: 0.02095 Total loss: 1.58568 timestamp: 1655025305.3487222 iteration: 21180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20358 FastRCNN class loss: 0.09847 FastRCNN total loss: 0.30205 L1 loss: 0.0000e+00 L2 loss: 1.05745 Learning rate: 0.02 Mask loss: 0.18593 RPN box loss: 0.08674 RPN score loss: 0.01437 RPN total loss: 0.1011 Total loss: 1.64653 timestamp: 1655025308.5603318 iteration: 21185 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16935 FastRCNN class loss: 0.10569 FastRCNN total loss: 0.27504 L1 loss: 0.0000e+00 L2 loss: 1.05727 Learning rate: 0.02 Mask loss: 0.2013 RPN box loss: 0.03777 RPN score loss: 0.00358 RPN total loss: 0.04135 Total loss: 1.57496 timestamp: 1655025312.0662236 iteration: 21190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.10382 FastRCNN total loss: 0.24727 L1 loss: 0.0000e+00 L2 loss: 1.05711 Learning rate: 0.02 Mask loss: 0.124 RPN box loss: 0.02967 RPN score loss: 0.00872 RPN total loss: 0.03838 Total loss: 1.46676 timestamp: 1655025315.3942804 iteration: 21195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16477 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.22672 L1 loss: 0.0000e+00 L2 loss: 1.05694 Learning rate: 0.02 Mask loss: 0.16833 RPN box loss: 0.06696 RPN score loss: 0.00906 RPN total loss: 0.07602 Total loss: 1.528 timestamp: 1655025318.8311496 iteration: 21200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16107 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.21992 L1 loss: 0.0000e+00 L2 loss: 1.05677 Learning rate: 0.02 Mask loss: 0.15432 RPN box loss: 0.01127 RPN score loss: 0.00484 RPN total loss: 0.01612 Total loss: 1.44713 timestamp: 1655025322.1154888 iteration: 21205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11825 FastRCNN class loss: 0.13567 FastRCNN total loss: 0.25392 L1 loss: 0.0000e+00 L2 loss: 1.0566 Learning rate: 0.02 Mask loss: 0.25758 RPN box loss: 0.19642 RPN score loss: 0.00858 RPN total loss: 0.205 Total loss: 1.7731 timestamp: 1655025325.4866612 iteration: 21210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.13826 L1 loss: 0.0000e+00 L2 loss: 1.05642 Learning rate: 0.02 Mask loss: 0.14415 RPN box loss: 0.05081 RPN score loss: 0.00807 RPN total loss: 0.05888 Total loss: 1.39771 timestamp: 1655025328.7921417 iteration: 21215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.09748 FastRCNN total loss: 0.1969 L1 loss: 0.0000e+00 L2 loss: 1.0562 Learning rate: 0.02 Mask loss: 0.19631 RPN box loss: 0.02181 RPN score loss: 0.00471 RPN total loss: 0.02652 Total loss: 1.47594 timestamp: 1655025332.0826752 iteration: 21220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17309 FastRCNN class loss: 0.0855 FastRCNN total loss: 0.25859 L1 loss: 0.0000e+00 L2 loss: 1.05604 Learning rate: 0.02 Mask loss: 0.20788 RPN box loss: 0.03978 RPN score loss: 0.00814 RPN total loss: 0.04793 Total loss: 1.57043 timestamp: 1655025335.4387639 iteration: 21225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13012 FastRCNN class loss: 0.05002 FastRCNN total loss: 0.18013 L1 loss: 0.0000e+00 L2 loss: 1.05585 Learning rate: 0.02 Mask loss: 0.13401 RPN box loss: 0.02956 RPN score loss: 0.00724 RPN total loss: 0.03681 Total loss: 1.40679 timestamp: 1655025338.800227 iteration: 21230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.2043 L1 loss: 0.0000e+00 L2 loss: 1.05569 Learning rate: 0.02 Mask loss: 0.15337 RPN box loss: 0.02832 RPN score loss: 0.01571 RPN total loss: 0.04402 Total loss: 1.45739 timestamp: 1655025342.1828303 iteration: 21235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19455 FastRCNN class loss: 0.13871 FastRCNN total loss: 0.33326 L1 loss: 0.0000e+00 L2 loss: 1.05554 Learning rate: 0.02 Mask loss: 0.22779 RPN box loss: 0.02304 RPN score loss: 0.01425 RPN total loss: 0.03729 Total loss: 1.65388 timestamp: 1655025345.4537477 iteration: 21240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2327 FastRCNN class loss: 0.14746 FastRCNN total loss: 0.38015 L1 loss: 0.0000e+00 L2 loss: 1.05537 Learning rate: 0.02 Mask loss: 0.28618 RPN box loss: 0.02774 RPN score loss: 0.01168 RPN total loss: 0.03941 Total loss: 1.76112 timestamp: 1655025348.7810857 iteration: 21245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15654 FastRCNN class loss: 0.07887 FastRCNN total loss: 0.23541 L1 loss: 0.0000e+00 L2 loss: 1.05519 Learning rate: 0.02 Mask loss: 0.1362 RPN box loss: 0.05091 RPN score loss: 0.00716 RPN total loss: 0.05807 Total loss: 1.48487 timestamp: 1655025352.0223808 iteration: 21250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12691 FastRCNN class loss: 0.08019 FastRCNN total loss: 0.2071 L1 loss: 0.0000e+00 L2 loss: 1.055 Learning rate: 0.02 Mask loss: 0.15154 RPN box loss: 0.02793 RPN score loss: 0.00237 RPN total loss: 0.0303 Total loss: 1.44394 timestamp: 1655025355.4770703 iteration: 21255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19784 FastRCNN class loss: 0.07579 FastRCNN total loss: 0.27363 L1 loss: 0.0000e+00 L2 loss: 1.05482 Learning rate: 0.02 Mask loss: 0.14101 RPN box loss: 0.06362 RPN score loss: 0.01215 RPN total loss: 0.07576 Total loss: 1.54523 timestamp: 1655025358.8589199 iteration: 21260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15569 FastRCNN class loss: 0.09129 FastRCNN total loss: 0.24699 L1 loss: 0.0000e+00 L2 loss: 1.05465 Learning rate: 0.02 Mask loss: 0.17537 RPN box loss: 0.01908 RPN score loss: 0.00778 RPN total loss: 0.02686 Total loss: 1.50387 timestamp: 1655025362.1633096 iteration: 21265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16569 FastRCNN class loss: 0.12218 FastRCNN total loss: 0.28787 L1 loss: 0.0000e+00 L2 loss: 1.05447 Learning rate: 0.02 Mask loss: 0.16963 RPN box loss: 0.05218 RPN score loss: 0.00657 RPN total loss: 0.05875 Total loss: 1.57073 timestamp: 1655025365.5490386 iteration: 21270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10746 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.1646 L1 loss: 0.0000e+00 L2 loss: 1.05433 Learning rate: 0.02 Mask loss: 0.10836 RPN box loss: 0.00565 RPN score loss: 0.00449 RPN total loss: 0.01013 Total loss: 1.33742 timestamp: 1655025368.8443131 iteration: 21275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18385 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.2673 L1 loss: 0.0000e+00 L2 loss: 1.05416 Learning rate: 0.02 Mask loss: 0.11245 RPN box loss: 0.02206 RPN score loss: 0.00344 RPN total loss: 0.0255 Total loss: 1.4594 timestamp: 1655025372.1923227 iteration: 21280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15014 FastRCNN class loss: 0.08448 FastRCNN total loss: 0.23463 L1 loss: 0.0000e+00 L2 loss: 1.05397 Learning rate: 0.02 Mask loss: 0.20169 RPN box loss: 0.0305 RPN score loss: 0.00447 RPN total loss: 0.03497 Total loss: 1.52526 timestamp: 1655025375.5128453 iteration: 21285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16454 FastRCNN class loss: 0.07633 FastRCNN total loss: 0.24087 L1 loss: 0.0000e+00 L2 loss: 1.0538 Learning rate: 0.02 Mask loss: 0.20211 RPN box loss: 0.01114 RPN score loss: 0.0042 RPN total loss: 0.01534 Total loss: 1.51211 timestamp: 1655025378.8624032 iteration: 21290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14766 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 1.0536 Learning rate: 0.02 Mask loss: 0.13344 RPN box loss: 0.03338 RPN score loss: 0.00417 RPN total loss: 0.03755 Total loss: 1.43268 timestamp: 1655025382.1794882 iteration: 21295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17326 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.2597 L1 loss: 0.0000e+00 L2 loss: 1.05341 Learning rate: 0.02 Mask loss: 0.15429 RPN box loss: 0.01666 RPN score loss: 0.00872 RPN total loss: 0.02537 Total loss: 1.49277 timestamp: 1655025385.6461515 iteration: 21300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23702 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.32398 L1 loss: 0.0000e+00 L2 loss: 1.05326 Learning rate: 0.02 Mask loss: 0.12445 RPN box loss: 0.03297 RPN score loss: 0.00664 RPN total loss: 0.03961 Total loss: 1.5413 timestamp: 1655025389.0159092 iteration: 21305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14562 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.19566 L1 loss: 0.0000e+00 L2 loss: 1.05307 Learning rate: 0.02 Mask loss: 0.11522 RPN box loss: 0.02355 RPN score loss: 0.00525 RPN total loss: 0.0288 Total loss: 1.39275 timestamp: 1655025392.2890959 iteration: 21310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15401 FastRCNN class loss: 0.08337 FastRCNN total loss: 0.23737 L1 loss: 0.0000e+00 L2 loss: 1.0529 Learning rate: 0.02 Mask loss: 0.16337 RPN box loss: 0.03405 RPN score loss: 0.00661 RPN total loss: 0.04066 Total loss: 1.49431 timestamp: 1655025395.6714993 iteration: 21315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20801 FastRCNN class loss: 0.09362 FastRCNN total loss: 0.30163 L1 loss: 0.0000e+00 L2 loss: 1.05272 Learning rate: 0.02 Mask loss: 0.17436 RPN box loss: 0.06832 RPN score loss: 0.01175 RPN total loss: 0.08007 Total loss: 1.60878 timestamp: 1655025398.9439363 iteration: 21320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12295 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.19868 L1 loss: 0.0000e+00 L2 loss: 1.05255 Learning rate: 0.02 Mask loss: 0.10057 RPN box loss: 0.01739 RPN score loss: 0.00444 RPN total loss: 0.02183 Total loss: 1.37363 timestamp: 1655025402.3576732 iteration: 21325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21256 FastRCNN class loss: 0.1136 FastRCNN total loss: 0.32616 L1 loss: 0.0000e+00 L2 loss: 1.05237 Learning rate: 0.02 Mask loss: 0.25592 RPN box loss: 0.05551 RPN score loss: 0.00861 RPN total loss: 0.06412 Total loss: 1.69857 timestamp: 1655025405.6519542 iteration: 21330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1645 FastRCNN class loss: 0.14997 FastRCNN total loss: 0.31448 L1 loss: 0.0000e+00 L2 loss: 1.05217 Learning rate: 0.02 Mask loss: 0.20641 RPN box loss: 0.02448 RPN score loss: 0.00364 RPN total loss: 0.02811 Total loss: 1.60118 timestamp: 1655025408.996837 iteration: 21335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12141 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.18263 L1 loss: 0.0000e+00 L2 loss: 1.05199 Learning rate: 0.02 Mask loss: 0.12721 RPN box loss: 0.00861 RPN score loss: 0.00462 RPN total loss: 0.01322 Total loss: 1.37505 timestamp: 1655025412.2633932 iteration: 21340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10508 FastRCNN class loss: 0.08265 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 1.05181 Learning rate: 0.02 Mask loss: 0.11532 RPN box loss: 0.03568 RPN score loss: 0.00313 RPN total loss: 0.03881 Total loss: 1.39367 timestamp: 1655025415.6110203 iteration: 21345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21097 FastRCNN class loss: 0.13 FastRCNN total loss: 0.34097 L1 loss: 0.0000e+00 L2 loss: 1.05165 Learning rate: 0.02 Mask loss: 0.31469 RPN box loss: 0.04092 RPN score loss: 0.01054 RPN total loss: 0.05147 Total loss: 1.75879 timestamp: 1655025418.9959867 iteration: 21350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1302 FastRCNN class loss: 0.06707 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 1.0515 Learning rate: 0.02 Mask loss: 0.13421 RPN box loss: 0.03709 RPN score loss: 0.00516 RPN total loss: 0.04225 Total loss: 1.42523 timestamp: 1655025422.2438803 iteration: 21355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1883 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.26573 L1 loss: 0.0000e+00 L2 loss: 1.05132 Learning rate: 0.02 Mask loss: 0.15098 RPN box loss: 0.02531 RPN score loss: 0.00713 RPN total loss: 0.03244 Total loss: 1.50047 timestamp: 1655025425.6319935 iteration: 21360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14603 FastRCNN class loss: 0.09253 FastRCNN total loss: 0.23856 L1 loss: 0.0000e+00 L2 loss: 1.05114 Learning rate: 0.02 Mask loss: 0.13811 RPN box loss: 0.01462 RPN score loss: 0.00399 RPN total loss: 0.01861 Total loss: 1.44643 timestamp: 1655025428.8905904 iteration: 21365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06644 FastRCNN class loss: 0.03612 FastRCNN total loss: 0.10257 L1 loss: 0.0000e+00 L2 loss: 1.05097 Learning rate: 0.02 Mask loss: 0.11016 RPN box loss: 0.02783 RPN score loss: 0.00202 RPN total loss: 0.02985 Total loss: 1.29355 timestamp: 1655025432.230329 iteration: 21370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13613 FastRCNN class loss: 0.07674 FastRCNN total loss: 0.21287 L1 loss: 0.0000e+00 L2 loss: 1.0508 Learning rate: 0.02 Mask loss: 0.13732 RPN box loss: 0.02401 RPN score loss: 0.00503 RPN total loss: 0.02904 Total loss: 1.43003 timestamp: 1655025435.49434 iteration: 21375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1452 FastRCNN class loss: 0.07532 FastRCNN total loss: 0.22051 L1 loss: 0.0000e+00 L2 loss: 1.05063 Learning rate: 0.02 Mask loss: 0.20954 RPN box loss: 0.02882 RPN score loss: 0.0121 RPN total loss: 0.04092 Total loss: 1.5216 timestamp: 1655025438.8127143 iteration: 21380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17502 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.25384 L1 loss: 0.0000e+00 L2 loss: 1.05044 Learning rate: 0.02 Mask loss: 0.1652 RPN box loss: 0.02371 RPN score loss: 0.01075 RPN total loss: 0.03446 Total loss: 1.50394 timestamp: 1655025442.0550444 iteration: 21385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.19557 L1 loss: 0.0000e+00 L2 loss: 1.05023 Learning rate: 0.02 Mask loss: 0.11366 RPN box loss: 0.01698 RPN score loss: 0.0055 RPN total loss: 0.02248 Total loss: 1.38194 timestamp: 1655025445.4739523 iteration: 21390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 1.05006 Learning rate: 0.02 Mask loss: 0.16071 RPN box loss: 0.0324 RPN score loss: 0.00538 RPN total loss: 0.03778 Total loss: 1.41774 timestamp: 1655025448.868498 iteration: 21395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1233 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.2128 L1 loss: 0.0000e+00 L2 loss: 1.0499 Learning rate: 0.02 Mask loss: 0.16925 RPN box loss: 0.01073 RPN score loss: 0.00194 RPN total loss: 0.01267 Total loss: 1.44463 timestamp: 1655025452.1245134 iteration: 21400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14303 FastRCNN class loss: 0.05053 FastRCNN total loss: 0.19356 L1 loss: 0.0000e+00 L2 loss: 1.04974 Learning rate: 0.02 Mask loss: 0.13523 RPN box loss: 0.1227 RPN score loss: 0.00718 RPN total loss: 0.12987 Total loss: 1.5084 timestamp: 1655025455.4902253 iteration: 21405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16704 FastRCNN class loss: 0.10425 FastRCNN total loss: 0.27129 L1 loss: 0.0000e+00 L2 loss: 1.04955 Learning rate: 0.02 Mask loss: 0.23305 RPN box loss: 0.07181 RPN score loss: 0.01154 RPN total loss: 0.08336 Total loss: 1.63724 timestamp: 1655025458.695696 iteration: 21410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2014 FastRCNN class loss: 0.09568 FastRCNN total loss: 0.29708 L1 loss: 0.0000e+00 L2 loss: 1.0494 Learning rate: 0.02 Mask loss: 0.15093 RPN box loss: 0.01012 RPN score loss: 0.0115 RPN total loss: 0.02162 Total loss: 1.51903 timestamp: 1655025462.0442598 iteration: 21415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16576 FastRCNN class loss: 0.13076 FastRCNN total loss: 0.29651 L1 loss: 0.0000e+00 L2 loss: 1.04923 Learning rate: 0.02 Mask loss: 0.17541 RPN box loss: 0.06601 RPN score loss: 0.00698 RPN total loss: 0.07299 Total loss: 1.59415 timestamp: 1655025465.404498 iteration: 21420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15684 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.23043 L1 loss: 0.0000e+00 L2 loss: 1.04906 Learning rate: 0.02 Mask loss: 0.12767 RPN box loss: 0.01562 RPN score loss: 0.00302 RPN total loss: 0.01864 Total loss: 1.4258 timestamp: 1655025468.7681572 iteration: 21425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1548 FastRCNN class loss: 0.09746 FastRCNN total loss: 0.25226 L1 loss: 0.0000e+00 L2 loss: 1.04887 Learning rate: 0.02 Mask loss: 0.17046 RPN box loss: 0.05747 RPN score loss: 0.01387 RPN total loss: 0.07134 Total loss: 1.54293 timestamp: 1655025472.066515 iteration: 21430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18263 FastRCNN class loss: 0.09629 FastRCNN total loss: 0.27892 L1 loss: 0.0000e+00 L2 loss: 1.04866 Learning rate: 0.02 Mask loss: 0.23125 RPN box loss: 0.02728 RPN score loss: 0.0096 RPN total loss: 0.03688 Total loss: 1.59571 timestamp: 1655025475.4927733 iteration: 21435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1936 FastRCNN class loss: 0.08885 FastRCNN total loss: 0.28245 L1 loss: 0.0000e+00 L2 loss: 1.04847 Learning rate: 0.02 Mask loss: 0.15055 RPN box loss: 0.03521 RPN score loss: 0.00791 RPN total loss: 0.04312 Total loss: 1.52459 timestamp: 1655025478.7764535 iteration: 21440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12394 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.2158 L1 loss: 0.0000e+00 L2 loss: 1.0483 Learning rate: 0.02 Mask loss: 0.1536 RPN box loss: 0.02034 RPN score loss: 0.00637 RPN total loss: 0.02671 Total loss: 1.44441 timestamp: 1655025482.0777664 iteration: 21445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16054 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.23753 L1 loss: 0.0000e+00 L2 loss: 1.04815 Learning rate: 0.02 Mask loss: 0.1838 RPN box loss: 0.02738 RPN score loss: 0.00769 RPN total loss: 0.03506 Total loss: 1.50455 timestamp: 1655025485.5862608 iteration: 21450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13649 FastRCNN class loss: 0.08554 FastRCNN total loss: 0.22203 L1 loss: 0.0000e+00 L2 loss: 1.04798 Learning rate: 0.02 Mask loss: 0.19391 RPN box loss: 0.03379 RPN score loss: 0.0058 RPN total loss: 0.03959 Total loss: 1.50351 timestamp: 1655025488.892024 iteration: 21455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17088 FastRCNN class loss: 0.12782 FastRCNN total loss: 0.2987 L1 loss: 0.0000e+00 L2 loss: 1.0478 Learning rate: 0.02 Mask loss: 0.19221 RPN box loss: 0.03805 RPN score loss: 0.01178 RPN total loss: 0.04983 Total loss: 1.58854 timestamp: 1655025492.158364 iteration: 21460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17255 FastRCNN class loss: 0.09702 FastRCNN total loss: 0.26958 L1 loss: 0.0000e+00 L2 loss: 1.04762 Learning rate: 0.02 Mask loss: 0.1514 RPN box loss: 0.0389 RPN score loss: 0.00598 RPN total loss: 0.04489 Total loss: 1.51348 timestamp: 1655025495.5022218 iteration: 21465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15531 FastRCNN class loss: 0.1128 FastRCNN total loss: 0.26811 L1 loss: 0.0000e+00 L2 loss: 1.04744 Learning rate: 0.02 Mask loss: 0.18917 RPN box loss: 0.05962 RPN score loss: 0.0071 RPN total loss: 0.06672 Total loss: 1.57143 timestamp: 1655025498.8383398 iteration: 21470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17743 FastRCNN class loss: 0.16393 FastRCNN total loss: 0.34136 L1 loss: 0.0000e+00 L2 loss: 1.04728 Learning rate: 0.02 Mask loss: 0.23992 RPN box loss: 0.02765 RPN score loss: 0.01091 RPN total loss: 0.03856 Total loss: 1.66713 timestamp: 1655025502.1397738 iteration: 21475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23441 FastRCNN class loss: 0.09797 FastRCNN total loss: 0.33239 L1 loss: 0.0000e+00 L2 loss: 1.04711 Learning rate: 0.02 Mask loss: 0.22783 RPN box loss: 0.01624 RPN score loss: 0.00294 RPN total loss: 0.01918 Total loss: 1.62651 timestamp: 1655025505.5980906 iteration: 21480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14092 FastRCNN class loss: 0.08502 FastRCNN total loss: 0.22593 L1 loss: 0.0000e+00 L2 loss: 1.04693 Learning rate: 0.02 Mask loss: 0.11024 RPN box loss: 0.03193 RPN score loss: 0.0085 RPN total loss: 0.04043 Total loss: 1.42353 timestamp: 1655025509.0170972 iteration: 21485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15669 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.24683 L1 loss: 0.0000e+00 L2 loss: 1.04677 Learning rate: 0.02 Mask loss: 0.18347 RPN box loss: 0.0541 RPN score loss: 0.01159 RPN total loss: 0.06569 Total loss: 1.54275 timestamp: 1655025512.2432036 iteration: 21490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11265 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.18692 L1 loss: 0.0000e+00 L2 loss: 1.0466 Learning rate: 0.02 Mask loss: 0.09813 RPN box loss: 0.03944 RPN score loss: 0.00328 RPN total loss: 0.04273 Total loss: 1.37439 timestamp: 1655025515.6258314 iteration: 21495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15629 FastRCNN class loss: 0.10441 FastRCNN total loss: 0.2607 L1 loss: 0.0000e+00 L2 loss: 1.04642 Learning rate: 0.02 Mask loss: 0.1692 RPN box loss: 0.01522 RPN score loss: 0.01023 RPN total loss: 0.02545 Total loss: 1.50177 timestamp: 1655025518.9688332 iteration: 21500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16237 FastRCNN class loss: 0.13673 FastRCNN total loss: 0.2991 L1 loss: 0.0000e+00 L2 loss: 1.04628 Learning rate: 0.02 Mask loss: 0.25893 RPN box loss: 0.05003 RPN score loss: 0.01592 RPN total loss: 0.06595 Total loss: 1.67026 timestamp: 1655025522.3171492 iteration: 21505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12021 FastRCNN class loss: 0.04867 FastRCNN total loss: 0.16888 L1 loss: 0.0000e+00 L2 loss: 1.04612 Learning rate: 0.02 Mask loss: 0.14427 RPN box loss: 0.02201 RPN score loss: 0.00216 RPN total loss: 0.02417 Total loss: 1.38344 timestamp: 1655025525.616184 iteration: 21510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1014 FastRCNN class loss: 0.0769 FastRCNN total loss: 0.1783 L1 loss: 0.0000e+00 L2 loss: 1.04594 Learning rate: 0.02 Mask loss: 0.18701 RPN box loss: 0.04883 RPN score loss: 0.01274 RPN total loss: 0.06157 Total loss: 1.47283 timestamp: 1655025529.067473 iteration: 21515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16758 FastRCNN class loss: 0.10636 FastRCNN total loss: 0.27394 L1 loss: 0.0000e+00 L2 loss: 1.04575 Learning rate: 0.02 Mask loss: 0.13081 RPN box loss: 0.0142 RPN score loss: 0.00251 RPN total loss: 0.01671 Total loss: 1.46722 timestamp: 1655025532.338482 iteration: 21520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17608 FastRCNN class loss: 0.11373 FastRCNN total loss: 0.28981 L1 loss: 0.0000e+00 L2 loss: 1.04559 Learning rate: 0.02 Mask loss: 0.17195 RPN box loss: 0.04076 RPN score loss: 0.01211 RPN total loss: 0.05286 Total loss: 1.5602 timestamp: 1655025535.667572 iteration: 21525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0968 FastRCNN class loss: 0.039 FastRCNN total loss: 0.13579 L1 loss: 0.0000e+00 L2 loss: 1.04543 Learning rate: 0.02 Mask loss: 0.1574 RPN box loss: 0.01694 RPN score loss: 0.00961 RPN total loss: 0.02656 Total loss: 1.36518 timestamp: 1655025539.0740895 iteration: 21530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.08715 FastRCNN total loss: 0.2496 L1 loss: 0.0000e+00 L2 loss: 1.04525 Learning rate: 0.02 Mask loss: 0.1722 RPN box loss: 0.09188 RPN score loss: 0.00836 RPN total loss: 0.10024 Total loss: 1.56729 timestamp: 1655025542.3628476 iteration: 21535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12668 FastRCNN class loss: 0.10943 FastRCNN total loss: 0.23611 L1 loss: 0.0000e+00 L2 loss: 1.04506 Learning rate: 0.02 Mask loss: 0.24677 RPN box loss: 0.04122 RPN score loss: 0.00517 RPN total loss: 0.04639 Total loss: 1.57433 timestamp: 1655025545.7129319 iteration: 21540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11335 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.16974 L1 loss: 0.0000e+00 L2 loss: 1.04487 Learning rate: 0.02 Mask loss: 0.23078 RPN box loss: 0.01026 RPN score loss: 0.00519 RPN total loss: 0.01546 Total loss: 1.46084 timestamp: 1655025549.0525832 iteration: 21545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12706 FastRCNN class loss: 0.04688 FastRCNN total loss: 0.17394 L1 loss: 0.0000e+00 L2 loss: 1.0447 Learning rate: 0.02 Mask loss: 0.18506 RPN box loss: 0.02068 RPN score loss: 0.00326 RPN total loss: 0.02395 Total loss: 1.42765 timestamp: 1655025552.4310956 iteration: 21550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05872 FastRCNN class loss: 0.03396 FastRCNN total loss: 0.09267 L1 loss: 0.0000e+00 L2 loss: 1.04454 Learning rate: 0.02 Mask loss: 0.12707 RPN box loss: 0.0365 RPN score loss: 0.00688 RPN total loss: 0.04338 Total loss: 1.30766 timestamp: 1655025555.794676 iteration: 21555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17937 FastRCNN class loss: 0.06896 FastRCNN total loss: 0.24833 L1 loss: 0.0000e+00 L2 loss: 1.04437 Learning rate: 0.02 Mask loss: 0.13603 RPN box loss: 0.01022 RPN score loss: 0.00348 RPN total loss: 0.0137 Total loss: 1.44243 timestamp: 1655025559.1299455 iteration: 21560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09224 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.14031 L1 loss: 0.0000e+00 L2 loss: 1.0442 Learning rate: 0.02 Mask loss: 0.12571 RPN box loss: 0.03174 RPN score loss: 0.00485 RPN total loss: 0.03659 Total loss: 1.34681 timestamp: 1655025562.3573968 iteration: 21565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14101 FastRCNN class loss: 0.10636 FastRCNN total loss: 0.24737 L1 loss: 0.0000e+00 L2 loss: 1.04402 Learning rate: 0.02 Mask loss: 0.16173 RPN box loss: 0.05272 RPN score loss: 0.00664 RPN total loss: 0.05936 Total loss: 1.51247 timestamp: 1655025565.7296588 iteration: 21570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15197 FastRCNN class loss: 0.08568 FastRCNN total loss: 0.23765 L1 loss: 0.0000e+00 L2 loss: 1.04385 Learning rate: 0.02 Mask loss: 0.22124 RPN box loss: 0.03478 RPN score loss: 0.0077 RPN total loss: 0.04248 Total loss: 1.54523 timestamp: 1655025569.1447308 iteration: 21575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20445 FastRCNN class loss: 0.17001 FastRCNN total loss: 0.37446 L1 loss: 0.0000e+00 L2 loss: 1.04366 Learning rate: 0.02 Mask loss: 0.20213 RPN box loss: 0.03728 RPN score loss: 0.01161 RPN total loss: 0.04889 Total loss: 1.66913 timestamp: 1655025572.4209151 iteration: 21580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14583 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.21881 L1 loss: 0.0000e+00 L2 loss: 1.04347 Learning rate: 0.02 Mask loss: 0.14736 RPN box loss: 0.04018 RPN score loss: 0.00771 RPN total loss: 0.04789 Total loss: 1.45754 timestamp: 1655025575.9269466 iteration: 21585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15263 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.22759 L1 loss: 0.0000e+00 L2 loss: 1.04333 Learning rate: 0.02 Mask loss: 0.11749 RPN box loss: 0.04951 RPN score loss: 0.00848 RPN total loss: 0.058 Total loss: 1.44641 timestamp: 1655025579.2009706 iteration: 21590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20598 FastRCNN class loss: 0.09067 FastRCNN total loss: 0.29664 L1 loss: 0.0000e+00 L2 loss: 1.04316 Learning rate: 0.02 Mask loss: 0.19699 RPN box loss: 0.03838 RPN score loss: 0.0147 RPN total loss: 0.05308 Total loss: 1.58986 timestamp: 1655025582.4675756 iteration: 21595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09815 FastRCNN class loss: 0.07374 FastRCNN total loss: 0.17188 L1 loss: 0.0000e+00 L2 loss: 1.04298 Learning rate: 0.02 Mask loss: 0.24539 RPN box loss: 0.02896 RPN score loss: 0.0025 RPN total loss: 0.03146 Total loss: 1.49171 timestamp: 1655025585.8292584 iteration: 21600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15464 FastRCNN class loss: 0.11906 FastRCNN total loss: 0.2737 L1 loss: 0.0000e+00 L2 loss: 1.04282 Learning rate: 0.02 Mask loss: 0.19904 RPN box loss: 0.03123 RPN score loss: 0.0044 RPN total loss: 0.03563 Total loss: 1.55118 timestamp: 1655025589.1367395 iteration: 21605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27932 FastRCNN class loss: 0.1591 FastRCNN total loss: 0.43842 L1 loss: 0.0000e+00 L2 loss: 1.04265 Learning rate: 0.02 Mask loss: 0.24762 RPN box loss: 0.06064 RPN score loss: 0.01863 RPN total loss: 0.07927 Total loss: 1.80796 timestamp: 1655025592.6018612 iteration: 21610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21347 FastRCNN class loss: 0.11607 FastRCNN total loss: 0.32955 L1 loss: 0.0000e+00 L2 loss: 1.04247 Learning rate: 0.02 Mask loss: 0.17917 RPN box loss: 0.03472 RPN score loss: 0.01079 RPN total loss: 0.04551 Total loss: 1.5967 timestamp: 1655025595.8303385 iteration: 21615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14375 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.22117 L1 loss: 0.0000e+00 L2 loss: 1.04229 Learning rate: 0.02 Mask loss: 0.19258 RPN box loss: 0.03401 RPN score loss: 0.00353 RPN total loss: 0.03753 Total loss: 1.49358 timestamp: 1655025599.1836476 iteration: 21620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18967 FastRCNN class loss: 0.106 FastRCNN total loss: 0.29566 L1 loss: 0.0000e+00 L2 loss: 1.04215 Learning rate: 0.02 Mask loss: 0.14959 RPN box loss: 0.03766 RPN score loss: 0.00648 RPN total loss: 0.04414 Total loss: 1.53154 timestamp: 1655025606.132496 iteration: 21625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17746 FastRCNN class loss: 0.10511 FastRCNN total loss: 0.28257 L1 loss: 0.0000e+00 L2 loss: 1.04197 Learning rate: 0.02 Mask loss: 0.17856 RPN box loss: 0.18753 RPN score loss: 0.0092 RPN total loss: 0.19673 Total loss: 1.69983 timestamp: 1655025609.403629 iteration: 21630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07274 FastRCNN class loss: 0.04321 FastRCNN total loss: 0.11596 L1 loss: 0.0000e+00 L2 loss: 1.04183 Learning rate: 0.02 Mask loss: 0.1342 RPN box loss: 0.07208 RPN score loss: 0.01126 RPN total loss: 0.08333 Total loss: 1.37532 timestamp: 1655025612.7893288 iteration: 21635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.14365 FastRCNN total loss: 0.24007 L1 loss: 0.0000e+00 L2 loss: 1.04166 Learning rate: 0.02 Mask loss: 0.23868 RPN box loss: 0.06897 RPN score loss: 0.09328 RPN total loss: 0.16224 Total loss: 1.68266 timestamp: 1655025616.2210696 iteration: 21640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.147 FastRCNN class loss: 0.13278 FastRCNN total loss: 0.27979 L1 loss: 0.0000e+00 L2 loss: 1.04145 Learning rate: 0.02 Mask loss: 0.20418 RPN box loss: 0.03444 RPN score loss: 0.00754 RPN total loss: 0.04199 Total loss: 1.56741 timestamp: 1655025619.4569085 iteration: 21645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21367 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.30116 L1 loss: 0.0000e+00 L2 loss: 1.04129 Learning rate: 0.02 Mask loss: 0.1982 RPN box loss: 0.03968 RPN score loss: 0.01234 RPN total loss: 0.05202 Total loss: 1.59267 timestamp: 1655025622.9365876 iteration: 21650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14708 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.23181 L1 loss: 0.0000e+00 L2 loss: 1.04111 Learning rate: 0.02 Mask loss: 0.17493 RPN box loss: 0.04848 RPN score loss: 0.00996 RPN total loss: 0.05844 Total loss: 1.50629 timestamp: 1655025626.1605127 iteration: 21655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18911 FastRCNN class loss: 0.09127 FastRCNN total loss: 0.28038 L1 loss: 0.0000e+00 L2 loss: 1.04092 Learning rate: 0.02 Mask loss: 0.15356 RPN box loss: 0.01911 RPN score loss: 0.00577 RPN total loss: 0.02488 Total loss: 1.49974 timestamp: 1655025629.6683438 iteration: 21660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19982 FastRCNN class loss: 0.10637 FastRCNN total loss: 0.30619 L1 loss: 0.0000e+00 L2 loss: 1.04075 Learning rate: 0.02 Mask loss: 0.2144 RPN box loss: 0.02874 RPN score loss: 0.0122 RPN total loss: 0.04094 Total loss: 1.60229 timestamp: 1655025632.9453723 iteration: 21665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12633 FastRCNN class loss: 0.0549 FastRCNN total loss: 0.18124 L1 loss: 0.0000e+00 L2 loss: 1.0406 Learning rate: 0.02 Mask loss: 0.15789 RPN box loss: 0.01845 RPN score loss: 0.006 RPN total loss: 0.02445 Total loss: 1.40417 timestamp: 1655025636.3423908 iteration: 21670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10229 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.1676 L1 loss: 0.0000e+00 L2 loss: 1.04042 Learning rate: 0.02 Mask loss: 0.13657 RPN box loss: 0.03317 RPN score loss: 0.00528 RPN total loss: 0.03846 Total loss: 1.38305 timestamp: 1655025639.6557848 iteration: 21675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17528 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.2569 L1 loss: 0.0000e+00 L2 loss: 1.04024 Learning rate: 0.02 Mask loss: 0.14083 RPN box loss: 0.08231 RPN score loss: 0.0062 RPN total loss: 0.08851 Total loss: 1.52648 timestamp: 1655025643.0503445 iteration: 21680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13878 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.20104 L1 loss: 0.0000e+00 L2 loss: 1.04007 Learning rate: 0.02 Mask loss: 0.11618 RPN box loss: 0.02276 RPN score loss: 0.00251 RPN total loss: 0.02527 Total loss: 1.38256 timestamp: 1655025646.4775631 iteration: 21685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16668 FastRCNN class loss: 0.14601 FastRCNN total loss: 0.31269 L1 loss: 0.0000e+00 L2 loss: 1.03993 Learning rate: 0.02 Mask loss: 0.19425 RPN box loss: 0.02372 RPN score loss: 0.00452 RPN total loss: 0.02824 Total loss: 1.57512 timestamp: 1655025649.7777264 iteration: 21690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1594 FastRCNN class loss: 0.08569 FastRCNN total loss: 0.24509 L1 loss: 0.0000e+00 L2 loss: 1.03974 Learning rate: 0.02 Mask loss: 0.16175 RPN box loss: 0.04438 RPN score loss: 0.01123 RPN total loss: 0.05561 Total loss: 1.50219 timestamp: 1655025653.1667817 iteration: 21695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17828 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.27803 L1 loss: 0.0000e+00 L2 loss: 1.03956 Learning rate: 0.02 Mask loss: 0.14298 RPN box loss: 0.00709 RPN score loss: 0.00449 RPN total loss: 0.01157 Total loss: 1.47215 timestamp: 1655025656.41785 iteration: 21700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17428 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.25427 L1 loss: 0.0000e+00 L2 loss: 1.03943 Learning rate: 0.02 Mask loss: 0.15175 RPN box loss: 0.02064 RPN score loss: 0.00529 RPN total loss: 0.02593 Total loss: 1.47138 timestamp: 1655025659.7440314 iteration: 21705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22234 FastRCNN class loss: 0.14257 FastRCNN total loss: 0.36491 L1 loss: 0.0000e+00 L2 loss: 1.03926 Learning rate: 0.02 Mask loss: 0.2112 RPN box loss: 0.05558 RPN score loss: 0.01745 RPN total loss: 0.07303 Total loss: 1.6884 timestamp: 1655025663.0018547 iteration: 21710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1459 FastRCNN class loss: 0.10179 FastRCNN total loss: 0.2477 L1 loss: 0.0000e+00 L2 loss: 1.03906 Learning rate: 0.02 Mask loss: 0.13866 RPN box loss: 0.07102 RPN score loss: 0.01694 RPN total loss: 0.08796 Total loss: 1.51339 timestamp: 1655025666.412205 iteration: 21715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12485 FastRCNN class loss: 0.09563 FastRCNN total loss: 0.22048 L1 loss: 0.0000e+00 L2 loss: 1.03888 Learning rate: 0.02 Mask loss: 0.19499 RPN box loss: 0.03041 RPN score loss: 0.00464 RPN total loss: 0.03505 Total loss: 1.4894 timestamp: 1655025669.6744583 iteration: 21720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17072 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.22697 L1 loss: 0.0000e+00 L2 loss: 1.03873 Learning rate: 0.02 Mask loss: 0.12521 RPN box loss: 0.04336 RPN score loss: 0.00696 RPN total loss: 0.05032 Total loss: 1.44122 timestamp: 1655025673.0164576 iteration: 21725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25377 FastRCNN class loss: 0.14189 FastRCNN total loss: 0.39566 L1 loss: 0.0000e+00 L2 loss: 1.03855 Learning rate: 0.02 Mask loss: 0.28593 RPN box loss: 0.05843 RPN score loss: 0.02305 RPN total loss: 0.08149 Total loss: 1.80163 timestamp: 1655025676.3744013 iteration: 21730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15621 FastRCNN class loss: 0.07693 FastRCNN total loss: 0.23313 L1 loss: 0.0000e+00 L2 loss: 1.03839 Learning rate: 0.02 Mask loss: 0.23267 RPN box loss: 0.03762 RPN score loss: 0.00451 RPN total loss: 0.04214 Total loss: 1.54634 timestamp: 1655025679.6766114 iteration: 21735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1852 FastRCNN class loss: 0.12193 FastRCNN total loss: 0.30713 L1 loss: 0.0000e+00 L2 loss: 1.03822 Learning rate: 0.02 Mask loss: 0.14466 RPN box loss: 0.05846 RPN score loss: 0.01467 RPN total loss: 0.07314 Total loss: 1.56315 timestamp: 1655025683.0552833 iteration: 21740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18007 FastRCNN class loss: 0.06831 FastRCNN total loss: 0.24838 L1 loss: 0.0000e+00 L2 loss: 1.03806 Learning rate: 0.02 Mask loss: 0.15702 RPN box loss: 0.01787 RPN score loss: 0.00467 RPN total loss: 0.02254 Total loss: 1.466 timestamp: 1655025686.3212779 iteration: 21745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15725 FastRCNN class loss: 0.08104 FastRCNN total loss: 0.23829 L1 loss: 0.0000e+00 L2 loss: 1.03787 Learning rate: 0.02 Mask loss: 0.11655 RPN box loss: 0.01536 RPN score loss: 0.00832 RPN total loss: 0.02368 Total loss: 1.41639 timestamp: 1655025689.7325156 iteration: 21750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13029 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.19055 L1 loss: 0.0000e+00 L2 loss: 1.03768 Learning rate: 0.02 Mask loss: 0.16206 RPN box loss: 0.01425 RPN score loss: 0.00254 RPN total loss: 0.01679 Total loss: 1.40708 timestamp: 1655025693.0088584 iteration: 21755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07725 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.12923 L1 loss: 0.0000e+00 L2 loss: 1.03751 Learning rate: 0.02 Mask loss: 0.14971 RPN box loss: 0.02717 RPN score loss: 0.00217 RPN total loss: 0.02934 Total loss: 1.34579 timestamp: 1655025696.302538 iteration: 21760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21087 FastRCNN class loss: 0.17358 FastRCNN total loss: 0.38445 L1 loss: 0.0000e+00 L2 loss: 1.03737 Learning rate: 0.02 Mask loss: 0.14611 RPN box loss: 0.04058 RPN score loss: 0.0119 RPN total loss: 0.05248 Total loss: 1.62041 timestamp: 1655025699.5807989 iteration: 21765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18296 FastRCNN class loss: 0.11612 FastRCNN total loss: 0.29908 L1 loss: 0.0000e+00 L2 loss: 1.0372 Learning rate: 0.02 Mask loss: 0.24665 RPN box loss: 0.07602 RPN score loss: 0.01712 RPN total loss: 0.09313 Total loss: 1.67606 timestamp: 1655025702.9648588 iteration: 21770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21017 FastRCNN class loss: 0.10425 FastRCNN total loss: 0.31442 L1 loss: 0.0000e+00 L2 loss: 1.03702 Learning rate: 0.02 Mask loss: 0.2086 RPN box loss: 0.04426 RPN score loss: 0.01481 RPN total loss: 0.05907 Total loss: 1.61911 timestamp: 1655025706.451287 iteration: 21775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18237 FastRCNN class loss: 0.08013 FastRCNN total loss: 0.2625 L1 loss: 0.0000e+00 L2 loss: 1.03682 Learning rate: 0.02 Mask loss: 0.17735 RPN box loss: 0.02184 RPN score loss: 0.00814 RPN total loss: 0.02998 Total loss: 1.50665 timestamp: 1655025709.7144349 iteration: 21780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20426 FastRCNN class loss: 0.08714 FastRCNN total loss: 0.2914 L1 loss: 0.0000e+00 L2 loss: 1.03663 Learning rate: 0.02 Mask loss: 0.18527 RPN box loss: 0.03622 RPN score loss: 0.00653 RPN total loss: 0.04275 Total loss: 1.55605 timestamp: 1655025713.0942187 iteration: 21785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11577 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.1735 L1 loss: 0.0000e+00 L2 loss: 1.03646 Learning rate: 0.02 Mask loss: 0.13573 RPN box loss: 0.00693 RPN score loss: 0.00377 RPN total loss: 0.0107 Total loss: 1.35638 timestamp: 1655025716.3829837 iteration: 21790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26436 FastRCNN class loss: 0.10807 FastRCNN total loss: 0.37242 L1 loss: 0.0000e+00 L2 loss: 1.03631 Learning rate: 0.02 Mask loss: 0.20146 RPN box loss: 0.09442 RPN score loss: 0.01369 RPN total loss: 0.10812 Total loss: 1.71831 timestamp: 1655025719.7772279 iteration: 21795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08892 FastRCNN class loss: 0.05909 FastRCNN total loss: 0.14801 L1 loss: 0.0000e+00 L2 loss: 1.03613 Learning rate: 0.02 Mask loss: 0.18588 RPN box loss: 0.02104 RPN score loss: 0.00749 RPN total loss: 0.02853 Total loss: 1.39855 timestamp: 1655025723.089239 iteration: 21800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21028 FastRCNN class loss: 0.09929 FastRCNN total loss: 0.30956 L1 loss: 0.0000e+00 L2 loss: 1.03593 Learning rate: 0.02 Mask loss: 0.29432 RPN box loss: 0.06271 RPN score loss: 0.01727 RPN total loss: 0.07998 Total loss: 1.71979 timestamp: 1655025726.4076736 iteration: 21805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14393 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.21929 L1 loss: 0.0000e+00 L2 loss: 1.03576 Learning rate: 0.02 Mask loss: 0.16316 RPN box loss: 0.01122 RPN score loss: 0.00366 RPN total loss: 0.01489 Total loss: 1.4331 timestamp: 1655025729.7636495 iteration: 21810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18285 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.2578 L1 loss: 0.0000e+00 L2 loss: 1.03561 Learning rate: 0.02 Mask loss: 0.12884 RPN box loss: 0.02193 RPN score loss: 0.00628 RPN total loss: 0.0282 Total loss: 1.45045 timestamp: 1655025733.216206 iteration: 21815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1848 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.24844 L1 loss: 0.0000e+00 L2 loss: 1.03541 Learning rate: 0.02 Mask loss: 0.18916 RPN box loss: 0.06977 RPN score loss: 0.00947 RPN total loss: 0.07925 Total loss: 1.55226 timestamp: 1655025736.4552126 iteration: 21820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19977 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.28282 L1 loss: 0.0000e+00 L2 loss: 1.03525 Learning rate: 0.02 Mask loss: 0.13405 RPN box loss: 0.02725 RPN score loss: 0.00739 RPN total loss: 0.03464 Total loss: 1.48676 timestamp: 1655025739.7029157 iteration: 21825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19958 FastRCNN class loss: 0.12711 FastRCNN total loss: 0.3267 L1 loss: 0.0000e+00 L2 loss: 1.03509 Learning rate: 0.02 Mask loss: 0.2432 RPN box loss: 0.05073 RPN score loss: 0.00799 RPN total loss: 0.05873 Total loss: 1.66371 timestamp: 1655025743.0136955 iteration: 21830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11948 FastRCNN class loss: 0.04173 FastRCNN total loss: 0.16121 L1 loss: 0.0000e+00 L2 loss: 1.03494 Learning rate: 0.02 Mask loss: 0.12351 RPN box loss: 0.07191 RPN score loss: 0.00705 RPN total loss: 0.07897 Total loss: 1.39862 timestamp: 1655025746.288316 iteration: 21835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21664 FastRCNN class loss: 0.09379 FastRCNN total loss: 0.31043 L1 loss: 0.0000e+00 L2 loss: 1.03478 Learning rate: 0.02 Mask loss: 0.17664 RPN box loss: 0.03161 RPN score loss: 0.00621 RPN total loss: 0.03782 Total loss: 1.55967 timestamp: 1655025749.7018864 iteration: 21840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09955 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.16056 L1 loss: 0.0000e+00 L2 loss: 1.03458 Learning rate: 0.02 Mask loss: 0.10221 RPN box loss: 0.02335 RPN score loss: 0.00476 RPN total loss: 0.0281 Total loss: 1.32546 timestamp: 1655025752.9208698 iteration: 21845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12965 FastRCNN class loss: 0.0838 FastRCNN total loss: 0.21345 L1 loss: 0.0000e+00 L2 loss: 1.0344 Learning rate: 0.02 Mask loss: 0.12535 RPN box loss: 0.0149 RPN score loss: 0.00386 RPN total loss: 0.01876 Total loss: 1.39197 timestamp: 1655025756.367474 iteration: 21850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.22168 L1 loss: 0.0000e+00 L2 loss: 1.03421 Learning rate: 0.02 Mask loss: 0.13966 RPN box loss: 0.13211 RPN score loss: 0.01371 RPN total loss: 0.14582 Total loss: 1.54137 timestamp: 1655025759.6154168 iteration: 21855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1379 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.22816 L1 loss: 0.0000e+00 L2 loss: 1.03402 Learning rate: 0.02 Mask loss: 0.15551 RPN box loss: 0.06946 RPN score loss: 0.00339 RPN total loss: 0.07285 Total loss: 1.49055 timestamp: 1655025763.0280924 iteration: 21860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1504 FastRCNN class loss: 0.08425 FastRCNN total loss: 0.23465 L1 loss: 0.0000e+00 L2 loss: 1.03386 Learning rate: 0.02 Mask loss: 0.1788 RPN box loss: 0.05321 RPN score loss: 0.00942 RPN total loss: 0.06264 Total loss: 1.50994 timestamp: 1655025766.4975922 iteration: 21865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18013 FastRCNN class loss: 0.13247 FastRCNN total loss: 0.3126 L1 loss: 0.0000e+00 L2 loss: 1.03369 Learning rate: 0.02 Mask loss: 0.18374 RPN box loss: 0.05731 RPN score loss: 0.02849 RPN total loss: 0.0858 Total loss: 1.61584 timestamp: 1655025769.848946 iteration: 21870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15166 FastRCNN class loss: 0.09568 FastRCNN total loss: 0.24734 L1 loss: 0.0000e+00 L2 loss: 1.0335 Learning rate: 0.02 Mask loss: 0.18547 RPN box loss: 0.04831 RPN score loss: 0.01196 RPN total loss: 0.06026 Total loss: 1.52657 timestamp: 1655025773.2602265 iteration: 21875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11783 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.17774 L1 loss: 0.0000e+00 L2 loss: 1.03336 Learning rate: 0.02 Mask loss: 0.1803 RPN box loss: 0.02615 RPN score loss: 0.00313 RPN total loss: 0.02928 Total loss: 1.42069 timestamp: 1655025776.539954 iteration: 21880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11121 FastRCNN class loss: 0.0567 FastRCNN total loss: 0.1679 L1 loss: 0.0000e+00 L2 loss: 1.03319 Learning rate: 0.02 Mask loss: 0.18303 RPN box loss: 0.03047 RPN score loss: 0.00902 RPN total loss: 0.03949 Total loss: 1.42361 timestamp: 1655025780.0496 iteration: 21885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1168 FastRCNN class loss: 0.08348 FastRCNN total loss: 0.20028 L1 loss: 0.0000e+00 L2 loss: 1.033 Learning rate: 0.02 Mask loss: 0.25561 RPN box loss: 0.01499 RPN score loss: 0.00395 RPN total loss: 0.01894 Total loss: 1.50783 timestamp: 1655025783.3282673 iteration: 21890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09425 FastRCNN class loss: 0.06846 FastRCNN total loss: 0.16271 L1 loss: 0.0000e+00 L2 loss: 1.03282 Learning rate: 0.02 Mask loss: 0.16218 RPN box loss: 0.02349 RPN score loss: 0.00422 RPN total loss: 0.0277 Total loss: 1.38541 timestamp: 1655025786.7296166 iteration: 21895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12946 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.2217 L1 loss: 0.0000e+00 L2 loss: 1.03267 Learning rate: 0.02 Mask loss: 0.19673 RPN box loss: 0.07723 RPN score loss: 0.00725 RPN total loss: 0.08449 Total loss: 1.5356 timestamp: 1655025789.9969912 iteration: 21900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1471 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.23189 L1 loss: 0.0000e+00 L2 loss: 1.03251 Learning rate: 0.02 Mask loss: 0.19694 RPN box loss: 0.04112 RPN score loss: 0.01318 RPN total loss: 0.05431 Total loss: 1.51564 timestamp: 1655025793.3211527 iteration: 21905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12332 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.19593 L1 loss: 0.0000e+00 L2 loss: 1.03233 Learning rate: 0.02 Mask loss: 0.15741 RPN box loss: 0.06011 RPN score loss: 0.01045 RPN total loss: 0.07056 Total loss: 1.45623 timestamp: 1655025796.814256 iteration: 21910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21308 FastRCNN class loss: 0.13531 FastRCNN total loss: 0.34839 L1 loss: 0.0000e+00 L2 loss: 1.03214 Learning rate: 0.02 Mask loss: 0.30083 RPN box loss: 0.06003 RPN score loss: 0.01181 RPN total loss: 0.07184 Total loss: 1.7532 timestamp: 1655025800.070126 iteration: 21915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11733 FastRCNN class loss: 0.0478 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 1.03197 Learning rate: 0.02 Mask loss: 0.11351 RPN box loss: 0.16439 RPN score loss: 0.00585 RPN total loss: 0.17024 Total loss: 1.48086 timestamp: 1655025803.4927726 iteration: 21920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20659 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.28104 L1 loss: 0.0000e+00 L2 loss: 1.03184 Learning rate: 0.02 Mask loss: 0.19569 RPN box loss: 0.00895 RPN score loss: 0.00377 RPN total loss: 0.01271 Total loss: 1.52128 timestamp: 1655025806.8173757 iteration: 21925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15727 FastRCNN class loss: 0.07193 FastRCNN total loss: 0.2292 L1 loss: 0.0000e+00 L2 loss: 1.03167 Learning rate: 0.02 Mask loss: 0.22863 RPN box loss: 0.03617 RPN score loss: 0.00263 RPN total loss: 0.03881 Total loss: 1.52831 timestamp: 1655025810.285471 iteration: 21930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2006 FastRCNN class loss: 0.09717 FastRCNN total loss: 0.29777 L1 loss: 0.0000e+00 L2 loss: 1.0315 Learning rate: 0.02 Mask loss: 0.18505 RPN box loss: 0.01044 RPN score loss: 0.00911 RPN total loss: 0.01955 Total loss: 1.53387 timestamp: 1655025813.553178 iteration: 21935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23192 FastRCNN class loss: 0.12409 FastRCNN total loss: 0.35601 L1 loss: 0.0000e+00 L2 loss: 1.03134 Learning rate: 0.02 Mask loss: 0.24243 RPN box loss: 0.06148 RPN score loss: 0.02385 RPN total loss: 0.08534 Total loss: 1.71512 timestamp: 1655025816.8712492 iteration: 21940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13928 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.23362 L1 loss: 0.0000e+00 L2 loss: 1.03116 Learning rate: 0.02 Mask loss: 0.16654 RPN box loss: 0.01835 RPN score loss: 0.005 RPN total loss: 0.02335 Total loss: 1.45466 timestamp: 1655025820.1837504 iteration: 21945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11181 FastRCNN class loss: 0.0757 FastRCNN total loss: 0.18751 L1 loss: 0.0000e+00 L2 loss: 1.03098 Learning rate: 0.02 Mask loss: 0.13898 RPN box loss: 0.0136 RPN score loss: 0.00312 RPN total loss: 0.01671 Total loss: 1.37419 timestamp: 1655025823.5288374 iteration: 21950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12968 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.18788 L1 loss: 0.0000e+00 L2 loss: 1.03081 Learning rate: 0.02 Mask loss: 0.15718 RPN box loss: 0.05429 RPN score loss: 0.00851 RPN total loss: 0.06279 Total loss: 1.43866 timestamp: 1655025826.8217306 iteration: 21955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17461 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.24473 L1 loss: 0.0000e+00 L2 loss: 1.03064 Learning rate: 0.02 Mask loss: 0.14911 RPN box loss: 0.04469 RPN score loss: 0.01022 RPN total loss: 0.0549 Total loss: 1.47938 timestamp: 1655025830.1954656 iteration: 21960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10902 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.18522 L1 loss: 0.0000e+00 L2 loss: 1.03049 Learning rate: 0.02 Mask loss: 0.12565 RPN box loss: 0.03658 RPN score loss: 0.00653 RPN total loss: 0.04311 Total loss: 1.38447 timestamp: 1655025833.5124714 iteration: 21965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1492 FastRCNN class loss: 0.11501 FastRCNN total loss: 0.26421 L1 loss: 0.0000e+00 L2 loss: 1.03032 Learning rate: 0.02 Mask loss: 0.15253 RPN box loss: 0.04756 RPN score loss: 0.01026 RPN total loss: 0.05782 Total loss: 1.50488 timestamp: 1655025836.8546789 iteration: 21970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14492 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.23535 L1 loss: 0.0000e+00 L2 loss: 1.03014 Learning rate: 0.02 Mask loss: 0.16538 RPN box loss: 0.02378 RPN score loss: 0.0029 RPN total loss: 0.02668 Total loss: 1.45756 timestamp: 1655025840.2503605 iteration: 21975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16978 FastRCNN class loss: 0.1506 FastRCNN total loss: 0.32038 L1 loss: 0.0000e+00 L2 loss: 1.02999 Learning rate: 0.02 Mask loss: 0.25841 RPN box loss: 0.02513 RPN score loss: 0.02637 RPN total loss: 0.0515 Total loss: 1.66028 timestamp: 1655025843.55575 iteration: 21980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09195 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.15151 L1 loss: 0.0000e+00 L2 loss: 1.02984 Learning rate: 0.02 Mask loss: 0.1342 RPN box loss: 0.02732 RPN score loss: 0.01968 RPN total loss: 0.047 Total loss: 1.36255 timestamp: 1655025846.9536855 iteration: 21985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23874 FastRCNN class loss: 0.12022 FastRCNN total loss: 0.35897 L1 loss: 0.0000e+00 L2 loss: 1.02965 Learning rate: 0.02 Mask loss: 0.19153 RPN box loss: 0.03719 RPN score loss: 0.01339 RPN total loss: 0.05058 Total loss: 1.63072 timestamp: 1655025850.3187203 iteration: 21990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14435 FastRCNN class loss: 0.10193 FastRCNN total loss: 0.24627 L1 loss: 0.0000e+00 L2 loss: 1.02947 Learning rate: 0.02 Mask loss: 0.26708 RPN box loss: 0.0308 RPN score loss: 0.00534 RPN total loss: 0.03614 Total loss: 1.57896 timestamp: 1655025853.5439847 iteration: 21995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10029 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.16744 L1 loss: 0.0000e+00 L2 loss: 1.0293 Learning rate: 0.02 Mask loss: 0.14011 RPN box loss: 0.04655 RPN score loss: 0.00425 RPN total loss: 0.0508 Total loss: 1.38764 timestamp: 1655025856.984451 iteration: 22000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11011 FastRCNN class loss: 0.1206 FastRCNN total loss: 0.23071 L1 loss: 0.0000e+00 L2 loss: 1.02915 Learning rate: 0.02 Mask loss: 0.13742 RPN box loss: 0.02046 RPN score loss: 0.00644 RPN total loss: 0.0269 Total loss: 1.42417 timestamp: 1655025860.3504 iteration: 22005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13797 FastRCNN class loss: 0.06491 FastRCNN total loss: 0.20287 L1 loss: 0.0000e+00 L2 loss: 1.029 Learning rate: 0.02 Mask loss: 0.20774 RPN box loss: 0.00423 RPN score loss: 0.00887 RPN total loss: 0.0131 Total loss: 1.45271 timestamp: 1655025863.7351475 iteration: 22010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18087 FastRCNN class loss: 0.10389 FastRCNN total loss: 0.28476 L1 loss: 0.0000e+00 L2 loss: 1.02881 Learning rate: 0.02 Mask loss: 0.23804 RPN box loss: 0.02398 RPN score loss: 0.00794 RPN total loss: 0.03192 Total loss: 1.58352 timestamp: 1655025867.09064 iteration: 22015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16159 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.23215 L1 loss: 0.0000e+00 L2 loss: 1.02864 Learning rate: 0.02 Mask loss: 0.15898 RPN box loss: 0.04285 RPN score loss: 0.01102 RPN total loss: 0.05387 Total loss: 1.47365 timestamp: 1655025870.5132866 iteration: 22020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2086 FastRCNN class loss: 0.14996 FastRCNN total loss: 0.35856 L1 loss: 0.0000e+00 L2 loss: 1.02849 Learning rate: 0.02 Mask loss: 0.18595 RPN box loss: 0.06513 RPN score loss: 0.00972 RPN total loss: 0.07485 Total loss: 1.64785 timestamp: 1655025873.7756069 iteration: 22025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16091 FastRCNN class loss: 0.11441 FastRCNN total loss: 0.27532 L1 loss: 0.0000e+00 L2 loss: 1.02832 Learning rate: 0.02 Mask loss: 0.1528 RPN box loss: 0.09567 RPN score loss: 0.01115 RPN total loss: 0.10682 Total loss: 1.56326 timestamp: 1655025877.202526 iteration: 22030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20996 FastRCNN class loss: 0.11684 FastRCNN total loss: 0.3268 L1 loss: 0.0000e+00 L2 loss: 1.02814 Learning rate: 0.02 Mask loss: 0.21635 RPN box loss: 0.03206 RPN score loss: 0.00987 RPN total loss: 0.04193 Total loss: 1.61323 timestamp: 1655025880.6641598 iteration: 22035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11586 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.17352 L1 loss: 0.0000e+00 L2 loss: 1.02796 Learning rate: 0.02 Mask loss: 0.17314 RPN box loss: 0.02788 RPN score loss: 0.01019 RPN total loss: 0.03807 Total loss: 1.41269 timestamp: 1655025883.9486794 iteration: 22040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14939 FastRCNN class loss: 0.07209 FastRCNN total loss: 0.22149 L1 loss: 0.0000e+00 L2 loss: 1.02781 Learning rate: 0.02 Mask loss: 0.11237 RPN box loss: 0.04135 RPN score loss: 0.00608 RPN total loss: 0.04744 Total loss: 1.40911 timestamp: 1655025887.4026968 iteration: 22045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19033 FastRCNN class loss: 0.09685 FastRCNN total loss: 0.28718 L1 loss: 0.0000e+00 L2 loss: 1.02765 Learning rate: 0.02 Mask loss: 0.17039 RPN box loss: 0.06209 RPN score loss: 0.00754 RPN total loss: 0.06963 Total loss: 1.55485 timestamp: 1655025890.6395335 iteration: 22050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08874 FastRCNN class loss: 0.04213 FastRCNN total loss: 0.13087 L1 loss: 0.0000e+00 L2 loss: 1.02748 Learning rate: 0.02 Mask loss: 0.20293 RPN box loss: 0.05864 RPN score loss: 0.00644 RPN total loss: 0.06507 Total loss: 1.42635 timestamp: 1655025894.0205169 iteration: 22055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17201 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.28085 L1 loss: 0.0000e+00 L2 loss: 1.02731 Learning rate: 0.02 Mask loss: 0.15524 RPN box loss: 0.05637 RPN score loss: 0.00817 RPN total loss: 0.06454 Total loss: 1.52794 timestamp: 1655025897.2951148 iteration: 22060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21199 FastRCNN class loss: 0.11458 FastRCNN total loss: 0.32657 L1 loss: 0.0000e+00 L2 loss: 1.02714 Learning rate: 0.02 Mask loss: 0.16461 RPN box loss: 0.01789 RPN score loss: 0.00576 RPN total loss: 0.02365 Total loss: 1.54198 timestamp: 1655025900.6497598 iteration: 22065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14933 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.22929 L1 loss: 0.0000e+00 L2 loss: 1.02697 Learning rate: 0.02 Mask loss: 0.18705 RPN box loss: 0.09941 RPN score loss: 0.01261 RPN total loss: 0.11202 Total loss: 1.55533 timestamp: 1655025903.994648 iteration: 22070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23824 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.30136 L1 loss: 0.0000e+00 L2 loss: 1.02681 Learning rate: 0.02 Mask loss: 0.14259 RPN box loss: 0.01678 RPN score loss: 0.00741 RPN total loss: 0.02418 Total loss: 1.49494 timestamp: 1655025907.3810892 iteration: 22075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13452 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.19763 L1 loss: 0.0000e+00 L2 loss: 1.02663 Learning rate: 0.02 Mask loss: 0.16968 RPN box loss: 0.03001 RPN score loss: 0.0148 RPN total loss: 0.04481 Total loss: 1.43875 timestamp: 1655025910.7382174 iteration: 22080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11565 FastRCNN class loss: 0.03907 FastRCNN total loss: 0.15472 L1 loss: 0.0000e+00 L2 loss: 1.02647 Learning rate: 0.02 Mask loss: 0.09765 RPN box loss: 0.04686 RPN score loss: 0.00385 RPN total loss: 0.05072 Total loss: 1.32956 timestamp: 1655025914.0501194 iteration: 22085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12743 FastRCNN class loss: 0.08091 FastRCNN total loss: 0.20834 L1 loss: 0.0000e+00 L2 loss: 1.0263 Learning rate: 0.02 Mask loss: 0.17998 RPN box loss: 0.01297 RPN score loss: 0.00302 RPN total loss: 0.01599 Total loss: 1.43061 timestamp: 1655025917.4465704 iteration: 22090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1494 FastRCNN class loss: 0.09928 FastRCNN total loss: 0.24868 L1 loss: 0.0000e+00 L2 loss: 1.02611 Learning rate: 0.02 Mask loss: 0.13978 RPN box loss: 0.05728 RPN score loss: 0.01696 RPN total loss: 0.07424 Total loss: 1.48881 timestamp: 1655025920.6566334 iteration: 22095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09989 FastRCNN class loss: 0.09959 FastRCNN total loss: 0.19948 L1 loss: 0.0000e+00 L2 loss: 1.02592 Learning rate: 0.02 Mask loss: 0.21715 RPN box loss: 0.01947 RPN score loss: 0.00226 RPN total loss: 0.02173 Total loss: 1.46428 timestamp: 1655025924.0331252 iteration: 22100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14674 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.21845 L1 loss: 0.0000e+00 L2 loss: 1.02574 Learning rate: 0.02 Mask loss: 0.12338 RPN box loss: 0.08157 RPN score loss: 0.01307 RPN total loss: 0.09463 Total loss: 1.46221 timestamp: 1655025927.3010175 iteration: 22105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12222 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.19885 L1 loss: 0.0000e+00 L2 loss: 1.02559 Learning rate: 0.02 Mask loss: 0.19099 RPN box loss: 0.04273 RPN score loss: 0.00653 RPN total loss: 0.04927 Total loss: 1.4647 timestamp: 1655025930.7152152 iteration: 22110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13416 FastRCNN class loss: 0.06133 FastRCNN total loss: 0.19549 L1 loss: 0.0000e+00 L2 loss: 1.02541 Learning rate: 0.02 Mask loss: 0.10682 RPN box loss: 0.04234 RPN score loss: 0.00836 RPN total loss: 0.0507 Total loss: 1.37843 timestamp: 1655025934.1179695 iteration: 22115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22158 FastRCNN class loss: 0.1364 FastRCNN total loss: 0.35798 L1 loss: 0.0000e+00 L2 loss: 1.02522 Learning rate: 0.02 Mask loss: 0.18248 RPN box loss: 0.03678 RPN score loss: 0.00701 RPN total loss: 0.0438 Total loss: 1.60948 timestamp: 1655025937.3874214 iteration: 22120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17757 FastRCNN class loss: 0.08794 FastRCNN total loss: 0.26552 L1 loss: 0.0000e+00 L2 loss: 1.02506 Learning rate: 0.02 Mask loss: 0.19414 RPN box loss: 0.05353 RPN score loss: 0.01454 RPN total loss: 0.06808 Total loss: 1.55279 timestamp: 1655025940.7427168 iteration: 22125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09113 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.1671 L1 loss: 0.0000e+00 L2 loss: 1.02493 Learning rate: 0.02 Mask loss: 0.13961 RPN box loss: 0.05985 RPN score loss: 0.01128 RPN total loss: 0.07113 Total loss: 1.40277 timestamp: 1655025944.0610437 iteration: 22130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12738 FastRCNN class loss: 0.06 FastRCNN total loss: 0.18739 L1 loss: 0.0000e+00 L2 loss: 1.02476 Learning rate: 0.02 Mask loss: 0.09759 RPN box loss: 0.02325 RPN score loss: 0.00252 RPN total loss: 0.02577 Total loss: 1.33551 timestamp: 1655025947.4564574 iteration: 22135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2052 FastRCNN class loss: 0.07582 FastRCNN total loss: 0.28102 L1 loss: 0.0000e+00 L2 loss: 1.02458 Learning rate: 0.02 Mask loss: 0.15938 RPN box loss: 0.01263 RPN score loss: 0.00392 RPN total loss: 0.01655 Total loss: 1.48153 timestamp: 1655025950.7956007 iteration: 22140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14339 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.23208 L1 loss: 0.0000e+00 L2 loss: 1.0244 Learning rate: 0.02 Mask loss: 0.15062 RPN box loss: 0.02843 RPN score loss: 0.00564 RPN total loss: 0.03407 Total loss: 1.44117 timestamp: 1655025954.011894 iteration: 22145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20213 FastRCNN class loss: 0.11607 FastRCNN total loss: 0.3182 L1 loss: 0.0000e+00 L2 loss: 1.02423 Learning rate: 0.02 Mask loss: 0.26537 RPN box loss: 0.04995 RPN score loss: 0.01855 RPN total loss: 0.0685 Total loss: 1.6763 timestamp: 1655025957.224052 iteration: 22150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21747 FastRCNN class loss: 0.09381 FastRCNN total loss: 0.31128 L1 loss: 0.0000e+00 L2 loss: 1.02406 Learning rate: 0.02 Mask loss: 0.18784 RPN box loss: 0.05251 RPN score loss: 0.01297 RPN total loss: 0.06548 Total loss: 1.58867 timestamp: 1655025960.6276705 iteration: 22155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18847 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.26031 L1 loss: 0.0000e+00 L2 loss: 1.02388 Learning rate: 0.02 Mask loss: 0.17012 RPN box loss: 0.0584 RPN score loss: 0.0117 RPN total loss: 0.0701 Total loss: 1.52441 timestamp: 1655025963.9819624 iteration: 22160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10206 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.17715 L1 loss: 0.0000e+00 L2 loss: 1.02373 Learning rate: 0.02 Mask loss: 0.11252 RPN box loss: 0.04254 RPN score loss: 0.0087 RPN total loss: 0.05124 Total loss: 1.36464 timestamp: 1655025967.3300145 iteration: 22165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16579 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.23876 L1 loss: 0.0000e+00 L2 loss: 1.02356 Learning rate: 0.02 Mask loss: 0.18024 RPN box loss: 0.00771 RPN score loss: 0.00812 RPN total loss: 0.01583 Total loss: 1.45839 timestamp: 1655025970.6705534 iteration: 22170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19868 FastRCNN class loss: 0.09121 FastRCNN total loss: 0.28989 L1 loss: 0.0000e+00 L2 loss: 1.02339 Learning rate: 0.02 Mask loss: 0.15534 RPN box loss: 0.05968 RPN score loss: 0.00982 RPN total loss: 0.0695 Total loss: 1.53812 timestamp: 1655025973.9162216 iteration: 22175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11448 FastRCNN class loss: 0.06955 FastRCNN total loss: 0.18404 L1 loss: 0.0000e+00 L2 loss: 1.02322 Learning rate: 0.02 Mask loss: 0.14454 RPN box loss: 0.04064 RPN score loss: 0.01573 RPN total loss: 0.05637 Total loss: 1.40817 timestamp: 1655025977.3297818 iteration: 22180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25612 FastRCNN class loss: 0.20555 FastRCNN total loss: 0.46167 L1 loss: 0.0000e+00 L2 loss: 1.02304 Learning rate: 0.02 Mask loss: 0.15719 RPN box loss: 0.02445 RPN score loss: 0.01056 RPN total loss: 0.03501 Total loss: 1.67691 timestamp: 1655025980.611746 iteration: 22185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.056 FastRCNN total loss: 0.14735 L1 loss: 0.0000e+00 L2 loss: 1.02287 Learning rate: 0.02 Mask loss: 0.15255 RPN box loss: 0.02541 RPN score loss: 0.0089 RPN total loss: 0.03431 Total loss: 1.35709 timestamp: 1655025983.9570124 iteration: 22190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18527 FastRCNN class loss: 0.09216 FastRCNN total loss: 0.27743 L1 loss: 0.0000e+00 L2 loss: 1.0227 Learning rate: 0.02 Mask loss: 0.18208 RPN box loss: 0.03245 RPN score loss: 0.01434 RPN total loss: 0.04678 Total loss: 1.52899 timestamp: 1655025987.1922104 iteration: 22195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19705 FastRCNN class loss: 0.08649 FastRCNN total loss: 0.28355 L1 loss: 0.0000e+00 L2 loss: 1.02252 Learning rate: 0.02 Mask loss: 0.27625 RPN box loss: 0.0283 RPN score loss: 0.00457 RPN total loss: 0.03287 Total loss: 1.61518 timestamp: 1655025990.64044 iteration: 22200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08826 FastRCNN class loss: 0.09968 FastRCNN total loss: 0.18794 L1 loss: 0.0000e+00 L2 loss: 1.02236 Learning rate: 0.02 Mask loss: 0.128 RPN box loss: 0.02659 RPN score loss: 0.00386 RPN total loss: 0.03045 Total loss: 1.36875 timestamp: 1655025994.1072874 iteration: 22205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15254 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.20211 L1 loss: 0.0000e+00 L2 loss: 1.02219 Learning rate: 0.02 Mask loss: 0.13614 RPN box loss: 0.02922 RPN score loss: 0.00291 RPN total loss: 0.03213 Total loss: 1.39256 timestamp: 1655025997.357772 iteration: 22210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20105 FastRCNN class loss: 0.12587 FastRCNN total loss: 0.32692 L1 loss: 0.0000e+00 L2 loss: 1.02201 Learning rate: 0.02 Mask loss: 0.25093 RPN box loss: 0.03706 RPN score loss: 0.03086 RPN total loss: 0.06792 Total loss: 1.66779 timestamp: 1655026000.7369938 iteration: 22215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11991 FastRCNN class loss: 0.1009 FastRCNN total loss: 0.22081 L1 loss: 0.0000e+00 L2 loss: 1.02185 Learning rate: 0.02 Mask loss: 0.19277 RPN box loss: 0.02706 RPN score loss: 0.00878 RPN total loss: 0.03584 Total loss: 1.47127 timestamp: 1655026003.9694002 iteration: 22220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15025 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.23234 L1 loss: 0.0000e+00 L2 loss: 1.02166 Learning rate: 0.02 Mask loss: 0.12856 RPN box loss: 0.01634 RPN score loss: 0.0042 RPN total loss: 0.02054 Total loss: 1.40311 timestamp: 1655026007.3985982 iteration: 22225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19578 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.27275 L1 loss: 0.0000e+00 L2 loss: 1.02149 Learning rate: 0.02 Mask loss: 0.18048 RPN box loss: 0.08926 RPN score loss: 0.01471 RPN total loss: 0.10396 Total loss: 1.57869 timestamp: 1655026010.6851869 iteration: 22230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15802 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 1.02132 Learning rate: 0.02 Mask loss: 0.17309 RPN box loss: 0.04419 RPN score loss: 0.00572 RPN total loss: 0.04991 Total loss: 1.47111 timestamp: 1655026014.1020465 iteration: 22235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10791 FastRCNN class loss: 0.09163 FastRCNN total loss: 0.19954 L1 loss: 0.0000e+00 L2 loss: 1.02113 Learning rate: 0.02 Mask loss: 0.12061 RPN box loss: 0.03247 RPN score loss: 0.01281 RPN total loss: 0.04528 Total loss: 1.38656 timestamp: 1655026017.339877 iteration: 22240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16024 FastRCNN class loss: 0.12134 FastRCNN total loss: 0.28159 L1 loss: 0.0000e+00 L2 loss: 1.02098 Learning rate: 0.02 Mask loss: 0.2176 RPN box loss: 0.04233 RPN score loss: 0.00733 RPN total loss: 0.04965 Total loss: 1.56982 timestamp: 1655026020.7546773 iteration: 22245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.07157 FastRCNN total loss: 0.18255 L1 loss: 0.0000e+00 L2 loss: 1.02081 Learning rate: 0.02 Mask loss: 0.18298 RPN box loss: 0.02874 RPN score loss: 0.00845 RPN total loss: 0.03719 Total loss: 1.42353 timestamp: 1655026024.0395315 iteration: 22250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22734 FastRCNN class loss: 0.09667 FastRCNN total loss: 0.324 L1 loss: 0.0000e+00 L2 loss: 1.02064 Learning rate: 0.02 Mask loss: 0.13529 RPN box loss: 0.08901 RPN score loss: 0.00899 RPN total loss: 0.098 Total loss: 1.57793 timestamp: 1655026027.3674915 iteration: 22255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12546 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.17815 L1 loss: 0.0000e+00 L2 loss: 1.02046 Learning rate: 0.02 Mask loss: 0.1425 RPN box loss: 0.01674 RPN score loss: 0.00834 RPN total loss: 0.02508 Total loss: 1.36619 timestamp: 1655026030.806706 iteration: 22260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12784 FastRCNN class loss: 0.13636 FastRCNN total loss: 0.2642 L1 loss: 0.0000e+00 L2 loss: 1.02027 Learning rate: 0.02 Mask loss: 0.22124 RPN box loss: 0.03508 RPN score loss: 0.00948 RPN total loss: 0.04456 Total loss: 1.55028 timestamp: 1655026034.062117 iteration: 22265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14969 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.25364 L1 loss: 0.0000e+00 L2 loss: 1.02011 Learning rate: 0.02 Mask loss: 0.13108 RPN box loss: 0.04803 RPN score loss: 0.01475 RPN total loss: 0.06278 Total loss: 1.46761 timestamp: 1655026037.6272707 iteration: 22270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13506 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.2109 L1 loss: 0.0000e+00 L2 loss: 1.01996 Learning rate: 0.02 Mask loss: 0.1455 RPN box loss: 0.05823 RPN score loss: 0.00912 RPN total loss: 0.06736 Total loss: 1.44371 timestamp: 1655026040.9682295 iteration: 22275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.112 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.19341 L1 loss: 0.0000e+00 L2 loss: 1.01979 Learning rate: 0.02 Mask loss: 0.12804 RPN box loss: 0.03308 RPN score loss: 0.01103 RPN total loss: 0.04411 Total loss: 1.38535 timestamp: 1655026044.3767674 iteration: 22280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.18641 L1 loss: 0.0000e+00 L2 loss: 1.01964 Learning rate: 0.02 Mask loss: 0.13259 RPN box loss: 0.02119 RPN score loss: 0.01036 RPN total loss: 0.03155 Total loss: 1.3702 timestamp: 1655026047.7198608 iteration: 22285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1328 FastRCNN class loss: 0.10854 FastRCNN total loss: 0.24134 L1 loss: 0.0000e+00 L2 loss: 1.01949 Learning rate: 0.02 Mask loss: 0.15025 RPN box loss: 0.02205 RPN score loss: 0.00973 RPN total loss: 0.03178 Total loss: 1.44285 timestamp: 1655026050.9797268 iteration: 22290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16423 FastRCNN class loss: 0.06703 FastRCNN total loss: 0.23126 L1 loss: 0.0000e+00 L2 loss: 1.0193 Learning rate: 0.02 Mask loss: 0.13019 RPN box loss: 0.01047 RPN score loss: 0.0035 RPN total loss: 0.01397 Total loss: 1.39472 timestamp: 1655026054.3693912 iteration: 22295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24018 FastRCNN class loss: 0.08927 FastRCNN total loss: 0.32944 L1 loss: 0.0000e+00 L2 loss: 1.01913 Learning rate: 0.02 Mask loss: 0.27093 RPN box loss: 0.01718 RPN score loss: 0.00892 RPN total loss: 0.0261 Total loss: 1.64559 timestamp: 1655026057.7258098 iteration: 22300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14357 FastRCNN class loss: 0.08934 FastRCNN total loss: 0.23291 L1 loss: 0.0000e+00 L2 loss: 1.01894 Learning rate: 0.02 Mask loss: 0.14401 RPN box loss: 0.00692 RPN score loss: 0.0044 RPN total loss: 0.01132 Total loss: 1.40718 timestamp: 1655026061.1085432 iteration: 22305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15102 FastRCNN class loss: 0.09967 FastRCNN total loss: 0.25069 L1 loss: 0.0000e+00 L2 loss: 1.01879 Learning rate: 0.02 Mask loss: 0.18504 RPN box loss: 0.04438 RPN score loss: 0.0112 RPN total loss: 0.05558 Total loss: 1.51009 timestamp: 1655026064.3647912 iteration: 22310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06576 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.13753 L1 loss: 0.0000e+00 L2 loss: 1.01862 Learning rate: 0.02 Mask loss: 0.12045 RPN box loss: 0.04648 RPN score loss: 0.00585 RPN total loss: 0.05233 Total loss: 1.32893 timestamp: 1655026067.7260203 iteration: 22315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15721 FastRCNN class loss: 0.09477 FastRCNN total loss: 0.25198 L1 loss: 0.0000e+00 L2 loss: 1.01846 Learning rate: 0.02 Mask loss: 0.1368 RPN box loss: 0.04938 RPN score loss: 0.00877 RPN total loss: 0.05815 Total loss: 1.46539 timestamp: 1655026070.9656935 iteration: 22320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20804 FastRCNN class loss: 0.09504 FastRCNN total loss: 0.30309 L1 loss: 0.0000e+00 L2 loss: 1.01829 Learning rate: 0.02 Mask loss: 0.1864 RPN box loss: 0.03972 RPN score loss: 0.02394 RPN total loss: 0.06366 Total loss: 1.57143 timestamp: 1655026074.3944583 iteration: 22325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20049 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.28094 L1 loss: 0.0000e+00 L2 loss: 1.01812 Learning rate: 0.02 Mask loss: 0.1687 RPN box loss: 0.01718 RPN score loss: 0.00551 RPN total loss: 0.02269 Total loss: 1.49045 timestamp: 1655026077.7396572 iteration: 22330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15929 FastRCNN class loss: 0.11286 FastRCNN total loss: 0.27215 L1 loss: 0.0000e+00 L2 loss: 1.01794 Learning rate: 0.02 Mask loss: 0.16796 RPN box loss: 0.05762 RPN score loss: 0.01334 RPN total loss: 0.07096 Total loss: 1.529 timestamp: 1655026081.012341 iteration: 22335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09255 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.14309 L1 loss: 0.0000e+00 L2 loss: 1.01777 Learning rate: 0.02 Mask loss: 0.13259 RPN box loss: 0.02991 RPN score loss: 0.00722 RPN total loss: 0.03713 Total loss: 1.33059 timestamp: 1655026084.3644257 iteration: 22340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13822 FastRCNN class loss: 0.08895 FastRCNN total loss: 0.22718 L1 loss: 0.0000e+00 L2 loss: 1.01763 Learning rate: 0.02 Mask loss: 0.13567 RPN box loss: 0.0144 RPN score loss: 0.00743 RPN total loss: 0.02183 Total loss: 1.40231 timestamp: 1655026087.67616 iteration: 22345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12691 FastRCNN class loss: 0.05812 FastRCNN total loss: 0.18503 L1 loss: 0.0000e+00 L2 loss: 1.01745 Learning rate: 0.02 Mask loss: 0.18878 RPN box loss: 0.0476 RPN score loss: 0.00637 RPN total loss: 0.05397 Total loss: 1.44523 timestamp: 1655026091.1393938 iteration: 22350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1289 FastRCNN class loss: 0.08407 FastRCNN total loss: 0.21297 L1 loss: 0.0000e+00 L2 loss: 1.01728 Learning rate: 0.02 Mask loss: 0.17004 RPN box loss: 0.02261 RPN score loss: 0.00855 RPN total loss: 0.03116 Total loss: 1.43145 timestamp: 1655026094.4023829 iteration: 22355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.28416 FastRCNN class loss: 0.11989 FastRCNN total loss: 0.40406 L1 loss: 0.0000e+00 L2 loss: 1.01714 Learning rate: 0.02 Mask loss: 0.17456 RPN box loss: 0.03065 RPN score loss: 0.01769 RPN total loss: 0.04834 Total loss: 1.64409 timestamp: 1655026097.768209 iteration: 22360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.05397 FastRCNN total loss: 0.16478 L1 loss: 0.0000e+00 L2 loss: 1.01698 Learning rate: 0.02 Mask loss: 0.31401 RPN box loss: 0.0159 RPN score loss: 0.00413 RPN total loss: 0.02004 Total loss: 1.51581 timestamp: 1655026101.0934064 iteration: 22365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1056 FastRCNN class loss: 0.09778 FastRCNN total loss: 0.20337 L1 loss: 0.0000e+00 L2 loss: 1.01684 Learning rate: 0.02 Mask loss: 0.13138 RPN box loss: 0.05563 RPN score loss: 0.00396 RPN total loss: 0.05959 Total loss: 1.41117 timestamp: 1655026104.4523768 iteration: 22370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10657 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.19154 L1 loss: 0.0000e+00 L2 loss: 1.01668 Learning rate: 0.02 Mask loss: 0.14659 RPN box loss: 0.02222 RPN score loss: 0.00935 RPN total loss: 0.03156 Total loss: 1.38637 timestamp: 1655026107.86017 iteration: 22375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14596 FastRCNN class loss: 0.07822 FastRCNN total loss: 0.22417 L1 loss: 0.0000e+00 L2 loss: 1.01648 Learning rate: 0.02 Mask loss: 0.18215 RPN box loss: 0.04543 RPN score loss: 0.0047 RPN total loss: 0.05013 Total loss: 1.47293 timestamp: 1655026111.1367593 iteration: 22380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12556 FastRCNN class loss: 0.07623 FastRCNN total loss: 0.2018 L1 loss: 0.0000e+00 L2 loss: 1.01628 Learning rate: 0.02 Mask loss: 0.12183 RPN box loss: 0.03102 RPN score loss: 0.00589 RPN total loss: 0.03691 Total loss: 1.37682 timestamp: 1655026114.6288488 iteration: 22385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13563 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.2187 L1 loss: 0.0000e+00 L2 loss: 1.01609 Learning rate: 0.02 Mask loss: 0.13978 RPN box loss: 0.05439 RPN score loss: 0.01248 RPN total loss: 0.06687 Total loss: 1.44144 timestamp: 1655026117.9211373 iteration: 22390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08792 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.14598 L1 loss: 0.0000e+00 L2 loss: 1.01593 Learning rate: 0.02 Mask loss: 0.17157 RPN box loss: 0.01009 RPN score loss: 0.00742 RPN total loss: 0.01751 Total loss: 1.35098 timestamp: 1655026121.3855484 iteration: 22395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12768 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.19033 L1 loss: 0.0000e+00 L2 loss: 1.01578 Learning rate: 0.02 Mask loss: 0.13209 RPN box loss: 0.10043 RPN score loss: 0.00564 RPN total loss: 0.10606 Total loss: 1.44426 timestamp: 1655026124.5987449 iteration: 22400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13815 FastRCNN class loss: 0.08259 FastRCNN total loss: 0.22074 L1 loss: 0.0000e+00 L2 loss: 1.01561 Learning rate: 0.02 Mask loss: 0.12659 RPN box loss: 0.0674 RPN score loss: 0.00605 RPN total loss: 0.07345 Total loss: 1.43639 timestamp: 1655026127.971593 iteration: 22405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20296 FastRCNN class loss: 0.12019 FastRCNN total loss: 0.32315 L1 loss: 0.0000e+00 L2 loss: 1.01543 Learning rate: 0.02 Mask loss: 0.22397 RPN box loss: 0.02183 RPN score loss: 0.00336 RPN total loss: 0.0252 Total loss: 1.58775 timestamp: 1655026131.326921 iteration: 22410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14354 FastRCNN class loss: 0.10673 FastRCNN total loss: 0.25027 L1 loss: 0.0000e+00 L2 loss: 1.01529 Learning rate: 0.02 Mask loss: 0.20178 RPN box loss: 0.06788 RPN score loss: 0.00675 RPN total loss: 0.07463 Total loss: 1.54197 timestamp: 1655026134.7679698 iteration: 22415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16516 FastRCNN class loss: 0.06361 FastRCNN total loss: 0.22877 L1 loss: 0.0000e+00 L2 loss: 1.0151 Learning rate: 0.02 Mask loss: 0.13877 RPN box loss: 0.05031 RPN score loss: 0.00764 RPN total loss: 0.05795 Total loss: 1.44059 timestamp: 1655026138.1212645 iteration: 22420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1512 FastRCNN class loss: 0.09223 FastRCNN total loss: 0.24343 L1 loss: 0.0000e+00 L2 loss: 1.01494 Learning rate: 0.02 Mask loss: 0.19034 RPN box loss: 0.02687 RPN score loss: 0.02454 RPN total loss: 0.05141 Total loss: 1.50012 timestamp: 1655026141.4827285 iteration: 22425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13065 FastRCNN class loss: 0.12242 FastRCNN total loss: 0.25307 L1 loss: 0.0000e+00 L2 loss: 1.01477 Learning rate: 0.02 Mask loss: 0.21336 RPN box loss: 0.08225 RPN score loss: 0.01668 RPN total loss: 0.09894 Total loss: 1.58014 timestamp: 1655026144.7656415 iteration: 22430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16196 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.24561 L1 loss: 0.0000e+00 L2 loss: 1.01459 Learning rate: 0.02 Mask loss: 0.13195 RPN box loss: 0.03106 RPN score loss: 0.00323 RPN total loss: 0.03429 Total loss: 1.42644 timestamp: 1655026148.0601957 iteration: 22435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10522 FastRCNN class loss: 0.0462 FastRCNN total loss: 0.15142 L1 loss: 0.0000e+00 L2 loss: 1.01444 Learning rate: 0.02 Mask loss: 0.11096 RPN box loss: 0.01373 RPN score loss: 0.00412 RPN total loss: 0.01785 Total loss: 1.29467 timestamp: 1655026151.5592384 iteration: 22440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1696 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.25295 L1 loss: 0.0000e+00 L2 loss: 1.01426 Learning rate: 0.02 Mask loss: 0.26632 RPN box loss: 0.10616 RPN score loss: 0.00644 RPN total loss: 0.1126 Total loss: 1.64613 timestamp: 1655026154.805006 iteration: 22445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23841 FastRCNN class loss: 0.09887 FastRCNN total loss: 0.33728 L1 loss: 0.0000e+00 L2 loss: 1.01409 Learning rate: 0.02 Mask loss: 0.24369 RPN box loss: 0.05723 RPN score loss: 0.00699 RPN total loss: 0.06423 Total loss: 1.65928 timestamp: 1655026158.2125447 iteration: 22450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1197 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.20223 L1 loss: 0.0000e+00 L2 loss: 1.01395 Learning rate: 0.02 Mask loss: 0.1609 RPN box loss: 0.03476 RPN score loss: 0.02734 RPN total loss: 0.0621 Total loss: 1.43917 timestamp: 1655026161.599085 iteration: 22455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14827 FastRCNN class loss: 0.09418 FastRCNN total loss: 0.24245 L1 loss: 0.0000e+00 L2 loss: 1.01378 Learning rate: 0.02 Mask loss: 0.21924 RPN box loss: 0.02563 RPN score loss: 0.00635 RPN total loss: 0.03197 Total loss: 1.50745 timestamp: 1655026164.8291888 iteration: 22460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19495 FastRCNN class loss: 0.09193 FastRCNN total loss: 0.28688 L1 loss: 0.0000e+00 L2 loss: 1.01361 Learning rate: 0.02 Mask loss: 0.22307 RPN box loss: 0.03136 RPN score loss: 0.00559 RPN total loss: 0.03694 Total loss: 1.56049 timestamp: 1655026168.1777928 iteration: 22465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17548 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.26351 L1 loss: 0.0000e+00 L2 loss: 1.01344 Learning rate: 0.02 Mask loss: 0.15029 RPN box loss: 0.01362 RPN score loss: 0.0091 RPN total loss: 0.02272 Total loss: 1.44996 timestamp: 1655026171.408109 iteration: 22470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12867 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.21135 L1 loss: 0.0000e+00 L2 loss: 1.01329 Learning rate: 0.02 Mask loss: 0.14895 RPN box loss: 0.018 RPN score loss: 0.00579 RPN total loss: 0.02379 Total loss: 1.39738 timestamp: 1655026174.7937431 iteration: 22475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19663 FastRCNN class loss: 0.10198 FastRCNN total loss: 0.29861 L1 loss: 0.0000e+00 L2 loss: 1.01311 Learning rate: 0.02 Mask loss: 0.18632 RPN box loss: 0.04854 RPN score loss: 0.00948 RPN total loss: 0.05802 Total loss: 1.55606 timestamp: 1655026178.1001825 iteration: 22480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13226 FastRCNN class loss: 0.11005 FastRCNN total loss: 0.24231 L1 loss: 0.0000e+00 L2 loss: 1.01292 Learning rate: 0.02 Mask loss: 0.18202 RPN box loss: 0.04038 RPN score loss: 0.00914 RPN total loss: 0.04952 Total loss: 1.48677 timestamp: 1655026181.4811413 iteration: 22485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10472 FastRCNN class loss: 0.09267 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 1.01277 Learning rate: 0.02 Mask loss: 0.1148 RPN box loss: 0.04173 RPN score loss: 0.00314 RPN total loss: 0.04487 Total loss: 1.36983 timestamp: 1655026184.7167833 iteration: 22490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11628 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.18797 L1 loss: 0.0000e+00 L2 loss: 1.0126 Learning rate: 0.02 Mask loss: 0.10623 RPN box loss: 0.0123 RPN score loss: 0.00278 RPN total loss: 0.01509 Total loss: 1.32189 timestamp: 1655026188.015098 iteration: 22495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07899 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.14567 L1 loss: 0.0000e+00 L2 loss: 1.01244 Learning rate: 0.02 Mask loss: 0.10829 RPN box loss: 0.00843 RPN score loss: 0.00356 RPN total loss: 0.01199 Total loss: 1.27838 timestamp: 1655026191.348923 iteration: 22500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17728 FastRCNN class loss: 0.11752 FastRCNN total loss: 0.2948 L1 loss: 0.0000e+00 L2 loss: 1.01226 Learning rate: 0.02 Mask loss: 0.10539 RPN box loss: 0.06091 RPN score loss: 0.00656 RPN total loss: 0.06747 Total loss: 1.47991 timestamp: 1655026194.670881 iteration: 22505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12216 FastRCNN class loss: 0.07956 FastRCNN total loss: 0.20173 L1 loss: 0.0000e+00 L2 loss: 1.0121 Learning rate: 0.02 Mask loss: 0.15245 RPN box loss: 0.03711 RPN score loss: 0.00616 RPN total loss: 0.04327 Total loss: 1.40954 timestamp: 1655026198.0209777 iteration: 22510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11173 FastRCNN class loss: 0.09514 FastRCNN total loss: 0.20688 L1 loss: 0.0000e+00 L2 loss: 1.01193 Learning rate: 0.02 Mask loss: 0.16583 RPN box loss: 0.04595 RPN score loss: 0.00513 RPN total loss: 0.05108 Total loss: 1.43571 timestamp: 1655026201.3736198 iteration: 22515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19729 FastRCNN class loss: 0.127 FastRCNN total loss: 0.32429 L1 loss: 0.0000e+00 L2 loss: 1.01176 Learning rate: 0.02 Mask loss: 0.21545 RPN box loss: 0.05661 RPN score loss: 0.0126 RPN total loss: 0.06922 Total loss: 1.62071 timestamp: 1655026204.9058964 iteration: 22520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14891 FastRCNN class loss: 0.08111 FastRCNN total loss: 0.23002 L1 loss: 0.0000e+00 L2 loss: 1.01159 Learning rate: 0.02 Mask loss: 0.19431 RPN box loss: 0.04903 RPN score loss: 0.01524 RPN total loss: 0.06426 Total loss: 1.50018 timestamp: 1655026208.2447958 iteration: 22525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13198 FastRCNN class loss: 0.09544 FastRCNN total loss: 0.22741 L1 loss: 0.0000e+00 L2 loss: 1.01143 Learning rate: 0.02 Mask loss: 0.18793 RPN box loss: 0.06532 RPN score loss: 0.00647 RPN total loss: 0.07179 Total loss: 1.49856 timestamp: 1655026211.6268897 iteration: 22530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12552 FastRCNN class loss: 0.06909 FastRCNN total loss: 0.19461 L1 loss: 0.0000e+00 L2 loss: 1.01127 Learning rate: 0.02 Mask loss: 0.13573 RPN box loss: 0.01613 RPN score loss: 0.0052 RPN total loss: 0.02132 Total loss: 1.36293 timestamp: 1655026215.1022356 iteration: 22535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12442 FastRCNN class loss: 0.07303 FastRCNN total loss: 0.19746 L1 loss: 0.0000e+00 L2 loss: 1.01111 Learning rate: 0.02 Mask loss: 0.15851 RPN box loss: 0.02403 RPN score loss: 0.00832 RPN total loss: 0.03235 Total loss: 1.39942 timestamp: 1655026218.4119413 iteration: 22540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16046 FastRCNN class loss: 0.11777 FastRCNN total loss: 0.27823 L1 loss: 0.0000e+00 L2 loss: 1.01094 Learning rate: 0.02 Mask loss: 0.26357 RPN box loss: 0.0376 RPN score loss: 0.0056 RPN total loss: 0.04321 Total loss: 1.59595 timestamp: 1655026221.8202918 iteration: 22545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15236 FastRCNN class loss: 0.05144 FastRCNN total loss: 0.20381 L1 loss: 0.0000e+00 L2 loss: 1.01075 Learning rate: 0.02 Mask loss: 0.19028 RPN box loss: 0.05546 RPN score loss: 0.00751 RPN total loss: 0.06297 Total loss: 1.4678 timestamp: 1655026225.1006172 iteration: 22550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15614 FastRCNN class loss: 0.07654 FastRCNN total loss: 0.23269 L1 loss: 0.0000e+00 L2 loss: 1.01056 Learning rate: 0.02 Mask loss: 0.19924 RPN box loss: 0.01882 RPN score loss: 0.00563 RPN total loss: 0.02445 Total loss: 1.46694 timestamp: 1655026228.375965 iteration: 22555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17862 FastRCNN class loss: 0.08289 FastRCNN total loss: 0.26151 L1 loss: 0.0000e+00 L2 loss: 1.01036 Learning rate: 0.02 Mask loss: 0.27882 RPN box loss: 0.06281 RPN score loss: 0.00893 RPN total loss: 0.07174 Total loss: 1.62243 timestamp: 1655026231.6741002 iteration: 22560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14417 FastRCNN class loss: 0.16709 FastRCNN total loss: 0.31126 L1 loss: 0.0000e+00 L2 loss: 1.0102 Learning rate: 0.02 Mask loss: 0.23451 RPN box loss: 0.05423 RPN score loss: 0.00912 RPN total loss: 0.06335 Total loss: 1.61931 timestamp: 1655026234.8922417 iteration: 22565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20839 FastRCNN class loss: 0.13635 FastRCNN total loss: 0.34474 L1 loss: 0.0000e+00 L2 loss: 1.01005 Learning rate: 0.02 Mask loss: 0.19446 RPN box loss: 0.08632 RPN score loss: 0.01075 RPN total loss: 0.09708 Total loss: 1.64633 timestamp: 1655026238.1849334 iteration: 22570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14946 FastRCNN class loss: 0.0614 FastRCNN total loss: 0.21086 L1 loss: 0.0000e+00 L2 loss: 1.00989 Learning rate: 0.02 Mask loss: 0.12161 RPN box loss: 0.01202 RPN score loss: 0.00376 RPN total loss: 0.01578 Total loss: 1.35814 timestamp: 1655026241.4702613 iteration: 22575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13513 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.23541 L1 loss: 0.0000e+00 L2 loss: 1.00973 Learning rate: 0.02 Mask loss: 0.16032 RPN box loss: 0.02379 RPN score loss: 0.00659 RPN total loss: 0.03038 Total loss: 1.43584 timestamp: 1655026244.9045172 iteration: 22580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1591 FastRCNN class loss: 0.12838 FastRCNN total loss: 0.28747 L1 loss: 0.0000e+00 L2 loss: 1.00956 Learning rate: 0.02 Mask loss: 0.241 RPN box loss: 0.07705 RPN score loss: 0.01982 RPN total loss: 0.09688 Total loss: 1.63491 timestamp: 1655026248.2219026 iteration: 22585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.17422 L1 loss: 0.0000e+00 L2 loss: 1.00938 Learning rate: 0.02 Mask loss: 0.21589 RPN box loss: 0.03079 RPN score loss: 0.00446 RPN total loss: 0.03525 Total loss: 1.43474 timestamp: 1655026251.6542947 iteration: 22590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1734 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.23748 L1 loss: 0.0000e+00 L2 loss: 1.00921 Learning rate: 0.02 Mask loss: 0.11026 RPN box loss: 0.02034 RPN score loss: 0.00443 RPN total loss: 0.02478 Total loss: 1.38172 timestamp: 1655026254.9678895 iteration: 22595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20914 FastRCNN class loss: 0.1265 FastRCNN total loss: 0.33564 L1 loss: 0.0000e+00 L2 loss: 1.00905 Learning rate: 0.02 Mask loss: 0.17425 RPN box loss: 0.09672 RPN score loss: 0.01688 RPN total loss: 0.11359 Total loss: 1.63253 timestamp: 1655026258.4191504 iteration: 22600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1469 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 1.0089 Learning rate: 0.02 Mask loss: 0.20987 RPN box loss: 0.04203 RPN score loss: 0.00933 RPN total loss: 0.05136 Total loss: 1.49104 timestamp: 1655026261.7604418 iteration: 22605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14007 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.20915 L1 loss: 0.0000e+00 L2 loss: 1.00877 Learning rate: 0.02 Mask loss: 0.20042 RPN box loss: 0.01532 RPN score loss: 0.00551 RPN total loss: 0.02082 Total loss: 1.43916 timestamp: 1655026265.1804984 iteration: 22610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.17983 L1 loss: 0.0000e+00 L2 loss: 1.00859 Learning rate: 0.02 Mask loss: 0.12624 RPN box loss: 0.0198 RPN score loss: 0.0016 RPN total loss: 0.0214 Total loss: 1.33606 timestamp: 1655026268.4201186 iteration: 22615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10899 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.19059 L1 loss: 0.0000e+00 L2 loss: 1.0084 Learning rate: 0.02 Mask loss: 0.20546 RPN box loss: 0.029 RPN score loss: 0.02163 RPN total loss: 0.05063 Total loss: 1.45509 timestamp: 1655026271.8887324 iteration: 22620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17472 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.24252 L1 loss: 0.0000e+00 L2 loss: 1.00824 Learning rate: 0.02 Mask loss: 0.31225 RPN box loss: 0.02063 RPN score loss: 0.003 RPN total loss: 0.02363 Total loss: 1.58664 timestamp: 1655026275.2821288 iteration: 22625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14773 FastRCNN class loss: 0.0685 FastRCNN total loss: 0.21623 L1 loss: 0.0000e+00 L2 loss: 1.00809 Learning rate: 0.02 Mask loss: 0.12838 RPN box loss: 0.02961 RPN score loss: 0.00773 RPN total loss: 0.03734 Total loss: 1.39005 timestamp: 1655026278.553942 iteration: 22630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.14196 L1 loss: 0.0000e+00 L2 loss: 1.00793 Learning rate: 0.02 Mask loss: 0.12867 RPN box loss: 0.08644 RPN score loss: 0.00512 RPN total loss: 0.09156 Total loss: 1.37012 timestamp: 1655026281.908306 iteration: 22635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10985 FastRCNN class loss: 0.06385 FastRCNN total loss: 0.1737 L1 loss: 0.0000e+00 L2 loss: 1.00776 Learning rate: 0.02 Mask loss: 0.1126 RPN box loss: 0.01069 RPN score loss: 0.00369 RPN total loss: 0.01438 Total loss: 1.30844 timestamp: 1655026285.2182434 iteration: 22640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22754 FastRCNN class loss: 0.07793 FastRCNN total loss: 0.30546 L1 loss: 0.0000e+00 L2 loss: 1.0076 Learning rate: 0.02 Mask loss: 0.21306 RPN box loss: 0.04037 RPN score loss: 0.00384 RPN total loss: 0.04421 Total loss: 1.57033 timestamp: 1655026288.6643987 iteration: 22645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11383 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.16055 L1 loss: 0.0000e+00 L2 loss: 1.00744 Learning rate: 0.02 Mask loss: 0.10572 RPN box loss: 0.09109 RPN score loss: 0.0097 RPN total loss: 0.10078 Total loss: 1.3745 timestamp: 1655026291.9787755 iteration: 22650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15568 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.22066 L1 loss: 0.0000e+00 L2 loss: 1.00728 Learning rate: 0.02 Mask loss: 0.1317 RPN box loss: 0.01922 RPN score loss: 0.00224 RPN total loss: 0.02146 Total loss: 1.38109 timestamp: 1655026295.3850276 iteration: 22655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1445 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.21696 L1 loss: 0.0000e+00 L2 loss: 1.00711 Learning rate: 0.02 Mask loss: 0.18016 RPN box loss: 0.02268 RPN score loss: 0.00292 RPN total loss: 0.02561 Total loss: 1.42984 timestamp: 1655026298.683281 iteration: 22660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18228 FastRCNN class loss: 0.10752 FastRCNN total loss: 0.2898 L1 loss: 0.0000e+00 L2 loss: 1.00693 Learning rate: 0.02 Mask loss: 0.17832 RPN box loss: 0.01763 RPN score loss: 0.00414 RPN total loss: 0.02177 Total loss: 1.49682 timestamp: 1655026301.9682214 iteration: 22665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19374 FastRCNN class loss: 0.14703 FastRCNN total loss: 0.34077 L1 loss: 0.0000e+00 L2 loss: 1.00675 Learning rate: 0.02 Mask loss: 0.19702 RPN box loss: 0.04297 RPN score loss: 0.01102 RPN total loss: 0.05399 Total loss: 1.59854 timestamp: 1655026305.2975955 iteration: 22670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1787 FastRCNN class loss: 0.06113 FastRCNN total loss: 0.23983 L1 loss: 0.0000e+00 L2 loss: 1.00657 Learning rate: 0.02 Mask loss: 0.16773 RPN box loss: 0.05799 RPN score loss: 0.00715 RPN total loss: 0.06514 Total loss: 1.47927 timestamp: 1655026308.5333116 iteration: 22675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14046 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.2096 L1 loss: 0.0000e+00 L2 loss: 1.0064 Learning rate: 0.02 Mask loss: 0.17156 RPN box loss: 0.01463 RPN score loss: 0.00538 RPN total loss: 0.02001 Total loss: 1.40757 timestamp: 1655026311.9960496 iteration: 22680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10016 FastRCNN class loss: 0.08797 FastRCNN total loss: 0.18813 L1 loss: 0.0000e+00 L2 loss: 1.00624 Learning rate: 0.02 Mask loss: 0.25233 RPN box loss: 0.0455 RPN score loss: 0.00678 RPN total loss: 0.05228 Total loss: 1.49898 timestamp: 1655026315.2241673 iteration: 22685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08001 FastRCNN class loss: 0.09897 FastRCNN total loss: 0.17898 L1 loss: 0.0000e+00 L2 loss: 1.00608 Learning rate: 0.02 Mask loss: 0.18038 RPN box loss: 0.09762 RPN score loss: 0.00862 RPN total loss: 0.10624 Total loss: 1.47168 timestamp: 1655026318.525434 iteration: 22690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13949 FastRCNN class loss: 0.14658 FastRCNN total loss: 0.28607 L1 loss: 0.0000e+00 L2 loss: 1.00592 Learning rate: 0.02 Mask loss: 0.19567 RPN box loss: 0.07157 RPN score loss: 0.0163 RPN total loss: 0.08787 Total loss: 1.57553 timestamp: 1655026321.8869736 iteration: 22695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05925 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.11069 L1 loss: 0.0000e+00 L2 loss: 1.00575 Learning rate: 0.02 Mask loss: 0.19233 RPN box loss: 0.03602 RPN score loss: 0.00592 RPN total loss: 0.04194 Total loss: 1.35071 timestamp: 1655026325.1810613 iteration: 22700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12934 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.20164 L1 loss: 0.0000e+00 L2 loss: 1.00557 Learning rate: 0.02 Mask loss: 0.14373 RPN box loss: 0.05807 RPN score loss: 0.00762 RPN total loss: 0.0657 Total loss: 1.41664 timestamp: 1655026328.453952 iteration: 22705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17295 FastRCNN class loss: 0.09535 FastRCNN total loss: 0.2683 L1 loss: 0.0000e+00 L2 loss: 1.00538 Learning rate: 0.02 Mask loss: 0.19577 RPN box loss: 0.05954 RPN score loss: 0.01247 RPN total loss: 0.07202 Total loss: 1.54146 timestamp: 1655026331.7800317 iteration: 22710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.14526 L1 loss: 0.0000e+00 L2 loss: 1.00522 Learning rate: 0.02 Mask loss: 0.14197 RPN box loss: 0.02269 RPN score loss: 0.00515 RPN total loss: 0.02784 Total loss: 1.32029 timestamp: 1655026335.1947773 iteration: 22715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14892 FastRCNN class loss: 0.13623 FastRCNN total loss: 0.28514 L1 loss: 0.0000e+00 L2 loss: 1.00505 Learning rate: 0.02 Mask loss: 0.11416 RPN box loss: 0.0425 RPN score loss: 0.01231 RPN total loss: 0.05481 Total loss: 1.45917 timestamp: 1655026338.502646 iteration: 22720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13709 FastRCNN class loss: 0.09757 FastRCNN total loss: 0.23466 L1 loss: 0.0000e+00 L2 loss: 1.00489 Learning rate: 0.02 Mask loss: 0.17411 RPN box loss: 0.04179 RPN score loss: 0.01717 RPN total loss: 0.05895 Total loss: 1.47261 timestamp: 1655026341.8018906 iteration: 22725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1114 FastRCNN class loss: 0.09018 FastRCNN total loss: 0.20158 L1 loss: 0.0000e+00 L2 loss: 1.00474 Learning rate: 0.02 Mask loss: 0.18465 RPN box loss: 0.03318 RPN score loss: 0.01045 RPN total loss: 0.04363 Total loss: 1.43459 timestamp: 1655026345.0252926 iteration: 22730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14414 FastRCNN class loss: 0.06137 FastRCNN total loss: 0.20551 L1 loss: 0.0000e+00 L2 loss: 1.00458 Learning rate: 0.02 Mask loss: 0.10659 RPN box loss: 0.04524 RPN score loss: 0.00774 RPN total loss: 0.05299 Total loss: 1.36967 timestamp: 1655026348.4515307 iteration: 22735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1171 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.18857 L1 loss: 0.0000e+00 L2 loss: 1.00441 Learning rate: 0.02 Mask loss: 0.16845 RPN box loss: 0.02146 RPN score loss: 0.00477 RPN total loss: 0.02623 Total loss: 1.38766 timestamp: 1655026351.7847736 iteration: 22740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21188 FastRCNN class loss: 0.10074 FastRCNN total loss: 0.31262 L1 loss: 0.0000e+00 L2 loss: 1.00425 Learning rate: 0.02 Mask loss: 0.18153 RPN box loss: 0.07559 RPN score loss: 0.00668 RPN total loss: 0.08227 Total loss: 1.58068 timestamp: 1655026355.1723452 iteration: 22745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17881 FastRCNN class loss: 0.10509 FastRCNN total loss: 0.2839 L1 loss: 0.0000e+00 L2 loss: 1.00407 Learning rate: 0.02 Mask loss: 0.1653 RPN box loss: 0.12019 RPN score loss: 0.00796 RPN total loss: 0.12815 Total loss: 1.58142 timestamp: 1655026358.4550338 iteration: 22750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14745 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.21934 L1 loss: 0.0000e+00 L2 loss: 1.0039 Learning rate: 0.02 Mask loss: 0.15562 RPN box loss: 0.06038 RPN score loss: 0.0055 RPN total loss: 0.06589 Total loss: 1.44474 timestamp: 1655026361.6987925 iteration: 22755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23546 FastRCNN class loss: 0.08174 FastRCNN total loss: 0.3172 L1 loss: 0.0000e+00 L2 loss: 1.00374 Learning rate: 0.02 Mask loss: 0.21537 RPN box loss: 0.02094 RPN score loss: 0.01128 RPN total loss: 0.03222 Total loss: 1.56852 timestamp: 1655026364.975123 iteration: 22760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15838 FastRCNN class loss: 0.12026 FastRCNN total loss: 0.27864 L1 loss: 0.0000e+00 L2 loss: 1.00358 Learning rate: 0.02 Mask loss: 0.15453 RPN box loss: 0.02438 RPN score loss: 0.00996 RPN total loss: 0.03435 Total loss: 1.47109 timestamp: 1655026368.2260623 iteration: 22765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1648 FastRCNN class loss: 0.06924 FastRCNN total loss: 0.23404 L1 loss: 0.0000e+00 L2 loss: 1.00343 Learning rate: 0.02 Mask loss: 0.18477 RPN box loss: 0.04366 RPN score loss: 0.00461 RPN total loss: 0.04828 Total loss: 1.47052 timestamp: 1655026371.4777691 iteration: 22770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12068 FastRCNN class loss: 0.08203 FastRCNN total loss: 0.20271 L1 loss: 0.0000e+00 L2 loss: 1.00327 Learning rate: 0.02 Mask loss: 0.14972 RPN box loss: 0.04915 RPN score loss: 0.0033 RPN total loss: 0.05245 Total loss: 1.40815 timestamp: 1655026374.781475 iteration: 22775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17312 FastRCNN class loss: 0.15563 FastRCNN total loss: 0.32875 L1 loss: 0.0000e+00 L2 loss: 1.0031 Learning rate: 0.02 Mask loss: 0.18307 RPN box loss: 0.0201 RPN score loss: 0.00774 RPN total loss: 0.02784 Total loss: 1.54277 timestamp: 1655026378.258427 iteration: 22780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12262 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.18883 L1 loss: 0.0000e+00 L2 loss: 1.00294 Learning rate: 0.02 Mask loss: 0.13055 RPN box loss: 0.02795 RPN score loss: 0.00243 RPN total loss: 0.03038 Total loss: 1.3527 timestamp: 1655026381.5090759 iteration: 22785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12521 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.20708 L1 loss: 0.0000e+00 L2 loss: 1.00275 Learning rate: 0.02 Mask loss: 0.15083 RPN box loss: 0.05948 RPN score loss: 0.0081 RPN total loss: 0.06758 Total loss: 1.42824 timestamp: 1655026384.9329846 iteration: 22790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11215 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.1833 L1 loss: 0.0000e+00 L2 loss: 1.0026 Learning rate: 0.02 Mask loss: 0.15042 RPN box loss: 0.01478 RPN score loss: 0.00413 RPN total loss: 0.01892 Total loss: 1.35523 timestamp: 1655026388.376198 iteration: 22795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1196 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 1.00243 Learning rate: 0.02 Mask loss: 0.14595 RPN box loss: 0.00894 RPN score loss: 0.00521 RPN total loss: 0.01415 Total loss: 1.3284 timestamp: 1655026391.6456518 iteration: 22800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18517 FastRCNN class loss: 0.12466 FastRCNN total loss: 0.30983 L1 loss: 0.0000e+00 L2 loss: 1.00227 Learning rate: 0.02 Mask loss: 0.22963 RPN box loss: 0.02617 RPN score loss: 0.00778 RPN total loss: 0.03395 Total loss: 1.57568 timestamp: 1655026395.0750232 iteration: 22805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12152 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.19026 L1 loss: 0.0000e+00 L2 loss: 1.00212 Learning rate: 0.02 Mask loss: 0.10851 RPN box loss: 0.01593 RPN score loss: 0.00257 RPN total loss: 0.01851 Total loss: 1.3194 timestamp: 1655026398.4547927 iteration: 22810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16568 FastRCNN class loss: 0.09574 FastRCNN total loss: 0.26142 L1 loss: 0.0000e+00 L2 loss: 1.00194 Learning rate: 0.02 Mask loss: 0.20982 RPN box loss: 0.06942 RPN score loss: 0.0087 RPN total loss: 0.07811 Total loss: 1.5513 timestamp: 1655026401.7257807 iteration: 22815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17966 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.26389 L1 loss: 0.0000e+00 L2 loss: 1.00177 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.01135 RPN score loss: 0.00217 RPN total loss: 0.01352 Total loss: 1.46241 timestamp: 1655026405.0314167 iteration: 22820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20492 FastRCNN class loss: 0.098 FastRCNN total loss: 0.30292 L1 loss: 0.0000e+00 L2 loss: 1.00163 Learning rate: 0.02 Mask loss: 0.13036 RPN box loss: 0.01525 RPN score loss: 0.00409 RPN total loss: 0.01934 Total loss: 1.45425 timestamp: 1655026408.361735 iteration: 22825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11455 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.18697 L1 loss: 0.0000e+00 L2 loss: 1.00146 Learning rate: 0.02 Mask loss: 0.17946 RPN box loss: 0.04205 RPN score loss: 0.00739 RPN total loss: 0.04944 Total loss: 1.41733 timestamp: 1655026411.5981505 iteration: 22830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10279 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.1832 L1 loss: 0.0000e+00 L2 loss: 1.0013 Learning rate: 0.02 Mask loss: 0.1743 RPN box loss: 0.05639 RPN score loss: 0.00802 RPN total loss: 0.0644 Total loss: 1.4232 timestamp: 1655026414.982757 iteration: 22835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14838 FastRCNN class loss: 0.11626 FastRCNN total loss: 0.26464 L1 loss: 0.0000e+00 L2 loss: 1.00112 Learning rate: 0.02 Mask loss: 0.14004 RPN box loss: 0.02625 RPN score loss: 0.00337 RPN total loss: 0.02962 Total loss: 1.43543 timestamp: 1655026418.3256397 iteration: 22840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2642 FastRCNN class loss: 0.19156 FastRCNN total loss: 0.45575 L1 loss: 0.0000e+00 L2 loss: 1.00096 Learning rate: 0.02 Mask loss: 0.24408 RPN box loss: 0.03779 RPN score loss: 0.01831 RPN total loss: 0.05611 Total loss: 1.7569 timestamp: 1655026421.614073 iteration: 22845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10739 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.17477 L1 loss: 0.0000e+00 L2 loss: 1.00078 Learning rate: 0.02 Mask loss: 0.12901 RPN box loss: 0.05786 RPN score loss: 0.00851 RPN total loss: 0.06637 Total loss: 1.37093 timestamp: 1655026425.0056944 iteration: 22850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13684 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.19692 L1 loss: 0.0000e+00 L2 loss: 1.00059 Learning rate: 0.02 Mask loss: 0.14484 RPN box loss: 0.03976 RPN score loss: 0.01055 RPN total loss: 0.05031 Total loss: 1.39267 timestamp: 1655026428.283324 iteration: 22855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16743 FastRCNN class loss: 0.10454 FastRCNN total loss: 0.27197 L1 loss: 0.0000e+00 L2 loss: 1.00043 Learning rate: 0.02 Mask loss: 0.18418 RPN box loss: 0.04658 RPN score loss: 0.014 RPN total loss: 0.06059 Total loss: 1.51716 timestamp: 1655026431.7060056 iteration: 22860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13251 FastRCNN class loss: 0.08835 FastRCNN total loss: 0.22086 L1 loss: 0.0000e+00 L2 loss: 1.00026 Learning rate: 0.02 Mask loss: 0.10936 RPN box loss: 0.02459 RPN score loss: 0.00438 RPN total loss: 0.02897 Total loss: 1.35945 timestamp: 1655026434.9745355 iteration: 22865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09237 FastRCNN class loss: 0.07147 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 1.0001 Learning rate: 0.02 Mask loss: 0.18892 RPN box loss: 0.03493 RPN score loss: 0.00278 RPN total loss: 0.03771 Total loss: 1.39056 timestamp: 1655026438.4169586 iteration: 22870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17664 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.2522 L1 loss: 0.0000e+00 L2 loss: 0.99996 Learning rate: 0.02 Mask loss: 0.18676 RPN box loss: 0.04304 RPN score loss: 0.0112 RPN total loss: 0.05424 Total loss: 1.49316 timestamp: 1655026441.6358244 iteration: 22875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16971 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.24597 L1 loss: 0.0000e+00 L2 loss: 0.99979 Learning rate: 0.02 Mask loss: 0.11478 RPN box loss: 0.03864 RPN score loss: 0.00486 RPN total loss: 0.0435 Total loss: 1.40404 timestamp: 1655026444.9860432 iteration: 22880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14496 FastRCNN class loss: 0.05236 FastRCNN total loss: 0.19733 L1 loss: 0.0000e+00 L2 loss: 0.99964 Learning rate: 0.02 Mask loss: 0.12807 RPN box loss: 0.0088 RPN score loss: 0.00421 RPN total loss: 0.01301 Total loss: 1.33805 timestamp: 1655026448.3690135 iteration: 22885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12717 FastRCNN class loss: 0.05106 FastRCNN total loss: 0.17823 L1 loss: 0.0000e+00 L2 loss: 0.99947 Learning rate: 0.02 Mask loss: 0.16163 RPN box loss: 0.01912 RPN score loss: 0.00593 RPN total loss: 0.02506 Total loss: 1.36439 timestamp: 1655026451.6158118 iteration: 22890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22958 FastRCNN class loss: 0.11894 FastRCNN total loss: 0.34852 L1 loss: 0.0000e+00 L2 loss: 0.9993 Learning rate: 0.02 Mask loss: 0.25795 RPN box loss: 0.03157 RPN score loss: 0.00574 RPN total loss: 0.03732 Total loss: 1.64309 timestamp: 1655026455.2185705 iteration: 22895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12961 FastRCNN class loss: 0.08387 FastRCNN total loss: 0.21348 L1 loss: 0.0000e+00 L2 loss: 0.99915 Learning rate: 0.02 Mask loss: 0.14028 RPN box loss: 0.10599 RPN score loss: 0.01125 RPN total loss: 0.11725 Total loss: 1.47016 timestamp: 1655026458.5243394 iteration: 22900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15474 FastRCNN class loss: 0.0927 FastRCNN total loss: 0.24744 L1 loss: 0.0000e+00 L2 loss: 0.99899 Learning rate: 0.02 Mask loss: 0.18019 RPN box loss: 0.07977 RPN score loss: 0.01502 RPN total loss: 0.09479 Total loss: 1.52141 timestamp: 1655026461.895259 iteration: 22905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.08458 FastRCNN total loss: 0.25598 L1 loss: 0.0000e+00 L2 loss: 0.99881 Learning rate: 0.02 Mask loss: 0.15411 RPN box loss: 0.106 RPN score loss: 0.00745 RPN total loss: 0.11345 Total loss: 1.52236 timestamp: 1655026465.2246904 iteration: 22910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15965 FastRCNN class loss: 0.12527 FastRCNN total loss: 0.28492 L1 loss: 0.0000e+00 L2 loss: 0.99865 Learning rate: 0.02 Mask loss: 0.21744 RPN box loss: 0.03974 RPN score loss: 0.00936 RPN total loss: 0.0491 Total loss: 1.5501 timestamp: 1655026468.5398457 iteration: 22915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08253 FastRCNN class loss: 0.03741 FastRCNN total loss: 0.11994 L1 loss: 0.0000e+00 L2 loss: 0.9985 Learning rate: 0.02 Mask loss: 0.10912 RPN box loss: 0.00787 RPN score loss: 0.00368 RPN total loss: 0.01155 Total loss: 1.23911 timestamp: 1655026471.7574637 iteration: 22920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16471 FastRCNN class loss: 0.07489 FastRCNN total loss: 0.23961 L1 loss: 0.0000e+00 L2 loss: 0.99833 Learning rate: 0.02 Mask loss: 0.1875 RPN box loss: 0.04885 RPN score loss: 0.02316 RPN total loss: 0.07201 Total loss: 1.49744 timestamp: 1655026475.1905959 iteration: 22925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22609 FastRCNN class loss: 0.10485 FastRCNN total loss: 0.33094 L1 loss: 0.0000e+00 L2 loss: 0.99816 Learning rate: 0.02 Mask loss: 0.31514 RPN box loss: 0.05728 RPN score loss: 0.00617 RPN total loss: 0.06345 Total loss: 1.70769 timestamp: 1655026478.684562 iteration: 22930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14707 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.2358 L1 loss: 0.0000e+00 L2 loss: 0.99802 Learning rate: 0.02 Mask loss: 0.24654 RPN box loss: 0.05487 RPN score loss: 0.00689 RPN total loss: 0.06175 Total loss: 1.54212 timestamp: 1655026481.9040747 iteration: 22935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12267 FastRCNN class loss: 0.1309 FastRCNN total loss: 0.25357 L1 loss: 0.0000e+00 L2 loss: 0.99787 Learning rate: 0.02 Mask loss: 0.15126 RPN box loss: 0.0255 RPN score loss: 0.00458 RPN total loss: 0.03007 Total loss: 1.43276 timestamp: 1655026485.4220066 iteration: 22940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.05029 FastRCNN total loss: 0.14425 L1 loss: 0.0000e+00 L2 loss: 0.99768 Learning rate: 0.02 Mask loss: 0.29691 RPN box loss: 0.00447 RPN score loss: 0.00888 RPN total loss: 0.01334 Total loss: 1.45219 timestamp: 1655026488.6444552 iteration: 22945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15593 FastRCNN class loss: 0.10754 FastRCNN total loss: 0.26347 L1 loss: 0.0000e+00 L2 loss: 0.9975 Learning rate: 0.02 Mask loss: 0.2099 RPN box loss: 0.04035 RPN score loss: 0.01401 RPN total loss: 0.05436 Total loss: 1.52523 timestamp: 1655026492.0531623 iteration: 22950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12849 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.18996 L1 loss: 0.0000e+00 L2 loss: 0.99735 Learning rate: 0.02 Mask loss: 0.13471 RPN box loss: 0.03365 RPN score loss: 0.00517 RPN total loss: 0.03882 Total loss: 1.36084 timestamp: 1655026495.3397856 iteration: 22955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12707 FastRCNN class loss: 0.10003 FastRCNN total loss: 0.22711 L1 loss: 0.0000e+00 L2 loss: 0.99719 Learning rate: 0.02 Mask loss: 0.15447 RPN box loss: 0.00993 RPN score loss: 0.0083 RPN total loss: 0.01823 Total loss: 1.397 timestamp: 1655026498.759078 iteration: 22960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09471 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.17891 L1 loss: 0.0000e+00 L2 loss: 0.99702 Learning rate: 0.02 Mask loss: 0.13663 RPN box loss: 0.01291 RPN score loss: 0.00546 RPN total loss: 0.01837 Total loss: 1.33093 timestamp: 1655026502.1321433 iteration: 22965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16086 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.25241 L1 loss: 0.0000e+00 L2 loss: 0.99684 Learning rate: 0.02 Mask loss: 0.22775 RPN box loss: 0.04912 RPN score loss: 0.00606 RPN total loss: 0.05518 Total loss: 1.53217 timestamp: 1655026505.4597664 iteration: 22970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15829 FastRCNN class loss: 0.10481 FastRCNN total loss: 0.2631 L1 loss: 0.0000e+00 L2 loss: 0.99667 Learning rate: 0.02 Mask loss: 0.17153 RPN box loss: 0.02999 RPN score loss: 0.01156 RPN total loss: 0.04154 Total loss: 1.47284 timestamp: 1655026508.7709422 iteration: 22975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08935 FastRCNN class loss: 0.04242 FastRCNN total loss: 0.13177 L1 loss: 0.0000e+00 L2 loss: 0.99653 Learning rate: 0.02 Mask loss: 0.15392 RPN box loss: 0.00828 RPN score loss: 0.00307 RPN total loss: 0.01136 Total loss: 1.29358 timestamp: 1655026512.0585687 iteration: 22980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23684 FastRCNN class loss: 0.09235 FastRCNN total loss: 0.3292 L1 loss: 0.0000e+00 L2 loss: 0.99639 Learning rate: 0.02 Mask loss: 0.22201 RPN box loss: 0.01581 RPN score loss: 0.00445 RPN total loss: 0.02026 Total loss: 1.56786 timestamp: 1655026515.4846394 iteration: 22985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10859 FastRCNN class loss: 0.08613 FastRCNN total loss: 0.19472 L1 loss: 0.0000e+00 L2 loss: 0.99622 Learning rate: 0.02 Mask loss: 0.18418 RPN box loss: 0.02203 RPN score loss: 0.0041 RPN total loss: 0.02613 Total loss: 1.40125 timestamp: 1655026518.7849739 iteration: 22990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18678 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.25375 L1 loss: 0.0000e+00 L2 loss: 0.99605 Learning rate: 0.02 Mask loss: 0.15704 RPN box loss: 0.0343 RPN score loss: 0.00556 RPN total loss: 0.03986 Total loss: 1.4467 timestamp: 1655026522.1531732 iteration: 22995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08828 FastRCNN class loss: 0.07855 FastRCNN total loss: 0.16682 L1 loss: 0.0000e+00 L2 loss: 0.9959 Learning rate: 0.02 Mask loss: 0.1294 RPN box loss: 0.0746 RPN score loss: 0.01 RPN total loss: 0.08461 Total loss: 1.37673 timestamp: 1655026525.4230983 iteration: 23000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.10186 FastRCNN total loss: 0.24241 L1 loss: 0.0000e+00 L2 loss: 0.99574 Learning rate: 0.02 Mask loss: 0.14988 RPN box loss: 0.04878 RPN score loss: 0.00973 RPN total loss: 0.05851 Total loss: 1.44654 timestamp: 1655026528.87754 iteration: 23005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16432 FastRCNN class loss: 0.08633 FastRCNN total loss: 0.25066 L1 loss: 0.0000e+00 L2 loss: 0.9956 Learning rate: 0.02 Mask loss: 0.19746 RPN box loss: 0.01192 RPN score loss: 0.01844 RPN total loss: 0.03037 Total loss: 1.47408 timestamp: 1655026532.3071764 iteration: 23010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18157 FastRCNN class loss: 0.17964 FastRCNN total loss: 0.36122 L1 loss: 0.0000e+00 L2 loss: 0.99544 Learning rate: 0.02 Mask loss: 0.2872 RPN box loss: 0.03386 RPN score loss: 0.01293 RPN total loss: 0.04678 Total loss: 1.69064 timestamp: 1655026535.6297657 iteration: 23015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17948 FastRCNN class loss: 0.10012 FastRCNN total loss: 0.2796 L1 loss: 0.0000e+00 L2 loss: 0.99527 Learning rate: 0.02 Mask loss: 0.14424 RPN box loss: 0.02744 RPN score loss: 0.01119 RPN total loss: 0.03863 Total loss: 1.45774 timestamp: 1655026539.152106 iteration: 23020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08065 FastRCNN class loss: 0.06824 FastRCNN total loss: 0.14888 L1 loss: 0.0000e+00 L2 loss: 0.9951 Learning rate: 0.02 Mask loss: 0.15916 RPN box loss: 0.01191 RPN score loss: 0.00127 RPN total loss: 0.01318 Total loss: 1.31632 timestamp: 1655026542.3811266 iteration: 23025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20886 FastRCNN class loss: 0.11846 FastRCNN total loss: 0.32731 L1 loss: 0.0000e+00 L2 loss: 0.99491 Learning rate: 0.02 Mask loss: 0.169 RPN box loss: 0.03307 RPN score loss: 0.00419 RPN total loss: 0.03726 Total loss: 1.52849 timestamp: 1655026545.735095 iteration: 23030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.16959 L1 loss: 0.0000e+00 L2 loss: 0.99475 Learning rate: 0.02 Mask loss: 0.25634 RPN box loss: 0.02378 RPN score loss: 0.01039 RPN total loss: 0.03418 Total loss: 1.45486 timestamp: 1655026549.0107646 iteration: 23035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12302 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.18372 L1 loss: 0.0000e+00 L2 loss: 0.99463 Learning rate: 0.02 Mask loss: 0.14076 RPN box loss: 0.01373 RPN score loss: 0.00575 RPN total loss: 0.01949 Total loss: 1.3386 timestamp: 1655026552.340364 iteration: 23040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1881 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.27683 L1 loss: 0.0000e+00 L2 loss: 0.99449 Learning rate: 0.02 Mask loss: 0.16069 RPN box loss: 0.05446 RPN score loss: 0.00773 RPN total loss: 0.0622 Total loss: 1.49421 timestamp: 1655026556.060461 iteration: 23045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24263 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.32078 L1 loss: 0.0000e+00 L2 loss: 0.99427 Learning rate: 0.02 Mask loss: 0.16478 RPN box loss: 0.10641 RPN score loss: 0.00818 RPN total loss: 0.11458 Total loss: 1.59441 timestamp: 1655026559.2771034 iteration: 23050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17703 FastRCNN class loss: 0.10393 FastRCNN total loss: 0.28097 L1 loss: 0.0000e+00 L2 loss: 0.9941 Learning rate: 0.02 Mask loss: 0.20242 RPN box loss: 0.03268 RPN score loss: 0.00716 RPN total loss: 0.03984 Total loss: 1.51733 timestamp: 1655026562.6395743 iteration: 23055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13946 FastRCNN class loss: 0.082 FastRCNN total loss: 0.22147 L1 loss: 0.0000e+00 L2 loss: 0.99394 Learning rate: 0.02 Mask loss: 0.15682 RPN box loss: 0.03485 RPN score loss: 0.01834 RPN total loss: 0.05319 Total loss: 1.42542 timestamp: 1655026565.9196508 iteration: 23060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21494 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.29483 L1 loss: 0.0000e+00 L2 loss: 0.99376 Learning rate: 0.02 Mask loss: 0.12522 RPN box loss: 0.02406 RPN score loss: 0.01095 RPN total loss: 0.03502 Total loss: 1.44883 timestamp: 1655026569.3415794 iteration: 23065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17858 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.2736 L1 loss: 0.0000e+00 L2 loss: 0.99361 Learning rate: 0.02 Mask loss: 0.15649 RPN box loss: 0.04162 RPN score loss: 0.00476 RPN total loss: 0.04638 Total loss: 1.47008 timestamp: 1655026572.6191351 iteration: 23070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15853 FastRCNN class loss: 0.10862 FastRCNN total loss: 0.26715 L1 loss: 0.0000e+00 L2 loss: 0.99345 Learning rate: 0.02 Mask loss: 0.17278 RPN box loss: 0.04428 RPN score loss: 0.01045 RPN total loss: 0.05473 Total loss: 1.48812 timestamp: 1655026576.0303874 iteration: 23075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12762 FastRCNN class loss: 0.08421 FastRCNN total loss: 0.21183 L1 loss: 0.0000e+00 L2 loss: 0.99333 Learning rate: 0.02 Mask loss: 0.16726 RPN box loss: 0.03781 RPN score loss: 0.00548 RPN total loss: 0.04328 Total loss: 1.4157 timestamp: 1655026579.2337122 iteration: 23080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13887 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.20969 L1 loss: 0.0000e+00 L2 loss: 0.99319 Learning rate: 0.02 Mask loss: 0.15794 RPN box loss: 0.03225 RPN score loss: 0.00296 RPN total loss: 0.03521 Total loss: 1.39604 timestamp: 1655026582.5839522 iteration: 23085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16623 FastRCNN class loss: 0.0905 FastRCNN total loss: 0.25673 L1 loss: 0.0000e+00 L2 loss: 0.99302 Learning rate: 0.02 Mask loss: 0.1863 RPN box loss: 0.04063 RPN score loss: 0.00555 RPN total loss: 0.04618 Total loss: 1.48221 timestamp: 1655026585.934168 iteration: 23090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.13053 L1 loss: 0.0000e+00 L2 loss: 0.99284 Learning rate: 0.02 Mask loss: 0.14916 RPN box loss: 0.03892 RPN score loss: 0.0055 RPN total loss: 0.04442 Total loss: 1.31694 timestamp: 1655026589.2896848 iteration: 23095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18524 FastRCNN class loss: 0.12113 FastRCNN total loss: 0.30637 L1 loss: 0.0000e+00 L2 loss: 0.99266 Learning rate: 0.02 Mask loss: 0.32115 RPN box loss: 0.01572 RPN score loss: 0.0048 RPN total loss: 0.02052 Total loss: 1.6407 timestamp: 1655026592.7860618 iteration: 23100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05417 FastRCNN class loss: 0.08334 FastRCNN total loss: 0.13751 L1 loss: 0.0000e+00 L2 loss: 0.9925 Learning rate: 0.02 Mask loss: 0.17546 RPN box loss: 0.06077 RPN score loss: 0.02572 RPN total loss: 0.08649 Total loss: 1.39196 timestamp: 1655026595.998336 iteration: 23105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.1343 FastRCNN total loss: 0.29758 L1 loss: 0.0000e+00 L2 loss: 0.99233 Learning rate: 0.02 Mask loss: 0.18949 RPN box loss: 0.06378 RPN score loss: 0.01424 RPN total loss: 0.07803 Total loss: 1.55742 timestamp: 1655026599.3797843 iteration: 23110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20276 FastRCNN class loss: 0.12349 FastRCNN total loss: 0.32625 L1 loss: 0.0000e+00 L2 loss: 0.99215 Learning rate: 0.02 Mask loss: 0.17184 RPN box loss: 0.06198 RPN score loss: 0.00861 RPN total loss: 0.07059 Total loss: 1.56084 timestamp: 1655026602.6480663 iteration: 23115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13435 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.19695 L1 loss: 0.0000e+00 L2 loss: 0.99201 Learning rate: 0.02 Mask loss: 0.13444 RPN box loss: 0.07019 RPN score loss: 0.00836 RPN total loss: 0.07855 Total loss: 1.40195 timestamp: 1655026606.050738 iteration: 23120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17978 FastRCNN class loss: 0.10635 FastRCNN total loss: 0.28613 L1 loss: 0.0000e+00 L2 loss: 0.99185 Learning rate: 0.02 Mask loss: 0.14668 RPN box loss: 0.01841 RPN score loss: 0.00685 RPN total loss: 0.02526 Total loss: 1.44992 timestamp: 1655026609.284093 iteration: 23125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.19592 L1 loss: 0.0000e+00 L2 loss: 0.99169 Learning rate: 0.02 Mask loss: 0.11803 RPN box loss: 0.03432 RPN score loss: 0.00526 RPN total loss: 0.03959 Total loss: 1.34523 timestamp: 1655026612.5883682 iteration: 23130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05178 FastRCNN class loss: 0.03217 FastRCNN total loss: 0.08395 L1 loss: 0.0000e+00 L2 loss: 0.99153 Learning rate: 0.02 Mask loss: 0.10787 RPN box loss: 0.02753 RPN score loss: 0.00188 RPN total loss: 0.02941 Total loss: 1.21275 timestamp: 1655026615.943846 iteration: 23135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14818 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.20341 L1 loss: 0.0000e+00 L2 loss: 0.99137 Learning rate: 0.02 Mask loss: 0.19412 RPN box loss: 0.02513 RPN score loss: 0.01296 RPN total loss: 0.03809 Total loss: 1.42699 timestamp: 1655026619.2804375 iteration: 23140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1582 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.25755 L1 loss: 0.0000e+00 L2 loss: 0.99123 Learning rate: 0.02 Mask loss: 0.21866 RPN box loss: 0.04787 RPN score loss: 0.01445 RPN total loss: 0.06232 Total loss: 1.52976 timestamp: 1655026622.752377 iteration: 23145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23175 FastRCNN class loss: 0.13056 FastRCNN total loss: 0.36231 L1 loss: 0.0000e+00 L2 loss: 0.99106 Learning rate: 0.02 Mask loss: 0.26523 RPN box loss: 0.05785 RPN score loss: 0.01381 RPN total loss: 0.07166 Total loss: 1.69026 timestamp: 1655026626.0689578 iteration: 23150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17117 FastRCNN class loss: 0.12085 FastRCNN total loss: 0.29202 L1 loss: 0.0000e+00 L2 loss: 0.9909 Learning rate: 0.02 Mask loss: 0.23565 RPN box loss: 0.09545 RPN score loss: 0.01204 RPN total loss: 0.10748 Total loss: 1.62605 timestamp: 1655026629.4103847 iteration: 23155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19201 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.32148 L1 loss: 0.0000e+00 L2 loss: 0.99076 Learning rate: 0.02 Mask loss: 0.17899 RPN box loss: 0.0512 RPN score loss: 0.01257 RPN total loss: 0.06377 Total loss: 1.555 timestamp: 1655026632.7240818 iteration: 23160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1281 FastRCNN class loss: 0.11504 FastRCNN total loss: 0.24314 L1 loss: 0.0000e+00 L2 loss: 0.99059 Learning rate: 0.02 Mask loss: 0.18271 RPN box loss: 0.05492 RPN score loss: 0.02349 RPN total loss: 0.07841 Total loss: 1.49485 timestamp: 1655026636.146543 iteration: 23165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19168 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.26604 L1 loss: 0.0000e+00 L2 loss: 0.99042 Learning rate: 0.02 Mask loss: 0.1713 RPN box loss: 0.05598 RPN score loss: 0.00603 RPN total loss: 0.06201 Total loss: 1.48977 timestamp: 1655026639.3360512 iteration: 23170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16378 FastRCNN class loss: 0.1017 FastRCNN total loss: 0.26548 L1 loss: 0.0000e+00 L2 loss: 0.99025 Learning rate: 0.02 Mask loss: 0.16334 RPN box loss: 0.09067 RPN score loss: 0.01741 RPN total loss: 0.10808 Total loss: 1.52714 timestamp: 1655026642.9687116 iteration: 23175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15024 FastRCNN class loss: 0.11853 FastRCNN total loss: 0.26878 L1 loss: 0.0000e+00 L2 loss: 0.99008 Learning rate: 0.02 Mask loss: 0.16828 RPN box loss: 0.03944 RPN score loss: 0.00881 RPN total loss: 0.04824 Total loss: 1.47538 timestamp: 1655026646.472022 iteration: 23180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18225 FastRCNN class loss: 0.14213 FastRCNN total loss: 0.32438 L1 loss: 0.0000e+00 L2 loss: 0.98994 Learning rate: 0.02 Mask loss: 0.25119 RPN box loss: 0.02947 RPN score loss: 0.01605 RPN total loss: 0.04552 Total loss: 1.61103 timestamp: 1655026649.7396138 iteration: 23185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14722 FastRCNN class loss: 0.11568 FastRCNN total loss: 0.26291 L1 loss: 0.0000e+00 L2 loss: 0.98979 Learning rate: 0.02 Mask loss: 0.16817 RPN box loss: 0.06993 RPN score loss: 0.0151 RPN total loss: 0.08504 Total loss: 1.5059 timestamp: 1655026653.2401543 iteration: 23190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22197 FastRCNN class loss: 0.15903 FastRCNN total loss: 0.381 L1 loss: 0.0000e+00 L2 loss: 0.98963 Learning rate: 0.02 Mask loss: 0.19679 RPN box loss: 0.04474 RPN score loss: 0.03511 RPN total loss: 0.07985 Total loss: 1.64727 timestamp: 1655026656.5108557 iteration: 23195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12125 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.23672 L1 loss: 0.0000e+00 L2 loss: 0.98945 Learning rate: 0.02 Mask loss: 0.17373 RPN box loss: 0.00798 RPN score loss: 0.00295 RPN total loss: 0.01093 Total loss: 1.41082 timestamp: 1655026660.090685 iteration: 23200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15243 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.24425 L1 loss: 0.0000e+00 L2 loss: 0.98929 Learning rate: 0.02 Mask loss: 0.19855 RPN box loss: 0.06576 RPN score loss: 0.00997 RPN total loss: 0.07573 Total loss: 1.50782 timestamp: 1655026663.3671749 iteration: 23205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17759 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.26113 L1 loss: 0.0000e+00 L2 loss: 0.98915 Learning rate: 0.02 Mask loss: 0.19858 RPN box loss: 0.03021 RPN score loss: 0.0045 RPN total loss: 0.03471 Total loss: 1.48356 timestamp: 1655026666.7739427 iteration: 23210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08267 FastRCNN class loss: 0.0577 FastRCNN total loss: 0.14037 L1 loss: 0.0000e+00 L2 loss: 0.98899 Learning rate: 0.02 Mask loss: 0.1076 RPN box loss: 0.05742 RPN score loss: 0.00566 RPN total loss: 0.06308 Total loss: 1.30004 timestamp: 1655026670.2831457 iteration: 23215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17498 FastRCNN class loss: 0.13165 FastRCNN total loss: 0.30663 L1 loss: 0.0000e+00 L2 loss: 0.98882 Learning rate: 0.02 Mask loss: 0.15649 RPN box loss: 0.02904 RPN score loss: 0.00833 RPN total loss: 0.03737 Total loss: 1.4893 timestamp: 1655026673.5850072 iteration: 23220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20494 FastRCNN class loss: 0.13059 FastRCNN total loss: 0.33553 L1 loss: 0.0000e+00 L2 loss: 0.98866 Learning rate: 0.02 Mask loss: 0.25206 RPN box loss: 0.06673 RPN score loss: 0.00986 RPN total loss: 0.07659 Total loss: 1.65284 timestamp: 1655026677.0010703 iteration: 23225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07387 FastRCNN class loss: 0.05002 FastRCNN total loss: 0.12389 L1 loss: 0.0000e+00 L2 loss: 0.98847 Learning rate: 0.02 Mask loss: 0.16187 RPN box loss: 0.04193 RPN score loss: 0.00336 RPN total loss: 0.04529 Total loss: 1.31952 timestamp: 1655026680.3019307 iteration: 23230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16211 FastRCNN class loss: 0.09553 FastRCNN total loss: 0.25764 L1 loss: 0.0000e+00 L2 loss: 0.98832 Learning rate: 0.02 Mask loss: 0.0953 RPN box loss: 0.01994 RPN score loss: 0.00375 RPN total loss: 0.02369 Total loss: 1.36494 timestamp: 1655026683.8147914 iteration: 23235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1346 FastRCNN class loss: 0.09241 FastRCNN total loss: 0.22701 L1 loss: 0.0000e+00 L2 loss: 0.98816 Learning rate: 0.02 Mask loss: 0.28229 RPN box loss: 0.06174 RPN score loss: 0.00976 RPN total loss: 0.0715 Total loss: 1.56896 timestamp: 1655026687.1380718 iteration: 23240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19802 FastRCNN class loss: 0.11176 FastRCNN total loss: 0.30978 L1 loss: 0.0000e+00 L2 loss: 0.98798 Learning rate: 0.02 Mask loss: 0.24168 RPN box loss: 0.03809 RPN score loss: 0.01195 RPN total loss: 0.05004 Total loss: 1.58949 timestamp: 1655026690.5917563 iteration: 23245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17946 FastRCNN class loss: 0.11063 FastRCNN total loss: 0.29009 L1 loss: 0.0000e+00 L2 loss: 0.98782 Learning rate: 0.02 Mask loss: 0.15464 RPN box loss: 0.06116 RPN score loss: 0.01602 RPN total loss: 0.07718 Total loss: 1.50973 timestamp: 1655026693.8697584 iteration: 23250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18079 FastRCNN class loss: 0.10623 FastRCNN total loss: 0.28703 L1 loss: 0.0000e+00 L2 loss: 0.98766 Learning rate: 0.02 Mask loss: 0.16221 RPN box loss: 0.03904 RPN score loss: 0.0088 RPN total loss: 0.04785 Total loss: 1.48475 timestamp: 1655026697.075649 iteration: 23255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18343 FastRCNN class loss: 0.08578 FastRCNN total loss: 0.26921 L1 loss: 0.0000e+00 L2 loss: 0.9875 Learning rate: 0.02 Mask loss: 0.19323 RPN box loss: 0.03262 RPN score loss: 0.00686 RPN total loss: 0.03949 Total loss: 1.48943 timestamp: 1655026700.5247 iteration: 23260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12317 FastRCNN class loss: 0.08152 FastRCNN total loss: 0.20469 L1 loss: 0.0000e+00 L2 loss: 0.98735 Learning rate: 0.02 Mask loss: 0.10841 RPN box loss: 0.02295 RPN score loss: 0.00606 RPN total loss: 0.02901 Total loss: 1.32946 timestamp: 1655026703.8138552 iteration: 23265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10629 FastRCNN class loss: 0.06349 FastRCNN total loss: 0.16978 L1 loss: 0.0000e+00 L2 loss: 0.98719 Learning rate: 0.02 Mask loss: 0.12328 RPN box loss: 0.02032 RPN score loss: 0.00346 RPN total loss: 0.02378 Total loss: 1.30403 timestamp: 1655026707.195967 iteration: 23270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.225 L1 loss: 0.0000e+00 L2 loss: 0.98703 Learning rate: 0.02 Mask loss: 0.19407 RPN box loss: 0.03207 RPN score loss: 0.0144 RPN total loss: 0.04647 Total loss: 1.45258 timestamp: 1655026710.4560285 iteration: 23275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16902 FastRCNN class loss: 0.10607 FastRCNN total loss: 0.27509 L1 loss: 0.0000e+00 L2 loss: 0.98688 Learning rate: 0.02 Mask loss: 0.27098 RPN box loss: 0.03676 RPN score loss: 0.01492 RPN total loss: 0.05167 Total loss: 1.58462 timestamp: 1655026713.821342 iteration: 23280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.18495 L1 loss: 0.0000e+00 L2 loss: 0.98671 Learning rate: 0.02 Mask loss: 0.10851 RPN box loss: 0.03869 RPN score loss: 0.00361 RPN total loss: 0.04231 Total loss: 1.32247 timestamp: 1655026717.1086419 iteration: 23285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11875 FastRCNN class loss: 0.10032 FastRCNN total loss: 0.21907 L1 loss: 0.0000e+00 L2 loss: 0.98652 Learning rate: 0.02 Mask loss: 0.17166 RPN box loss: 0.05615 RPN score loss: 0.01014 RPN total loss: 0.06629 Total loss: 1.44355 timestamp: 1655026720.5030487 iteration: 23290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10835 FastRCNN class loss: 0.08428 FastRCNN total loss: 0.19263 L1 loss: 0.0000e+00 L2 loss: 0.98635 Learning rate: 0.02 Mask loss: 0.15816 RPN box loss: 0.03951 RPN score loss: 0.01105 RPN total loss: 0.05055 Total loss: 1.38769 timestamp: 1655026723.8622484 iteration: 23295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18848 FastRCNN class loss: 0.10734 FastRCNN total loss: 0.29583 L1 loss: 0.0000e+00 L2 loss: 0.98616 Learning rate: 0.02 Mask loss: 0.15276 RPN box loss: 0.02904 RPN score loss: 0.00551 RPN total loss: 0.03455 Total loss: 1.4693 timestamp: 1655026727.154923 iteration: 23300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15938 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.25853 L1 loss: 0.0000e+00 L2 loss: 0.98602 Learning rate: 0.02 Mask loss: 0.12942 RPN box loss: 0.02844 RPN score loss: 0.0079 RPN total loss: 0.03634 Total loss: 1.41031 timestamp: 1655026730.565113 iteration: 23305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13212 FastRCNN class loss: 0.12066 FastRCNN total loss: 0.25279 L1 loss: 0.0000e+00 L2 loss: 0.9859 Learning rate: 0.02 Mask loss: 0.14055 RPN box loss: 0.02522 RPN score loss: 0.01249 RPN total loss: 0.03771 Total loss: 1.41694 timestamp: 1655026733.8641744 iteration: 23310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18249 FastRCNN class loss: 0.12195 FastRCNN total loss: 0.30444 L1 loss: 0.0000e+00 L2 loss: 0.98575 Learning rate: 0.02 Mask loss: 0.28341 RPN box loss: 0.04592 RPN score loss: 0.00885 RPN total loss: 0.05477 Total loss: 1.62838 timestamp: 1655026737.2850275 iteration: 23315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17199 FastRCNN class loss: 0.11597 FastRCNN total loss: 0.28796 L1 loss: 0.0000e+00 L2 loss: 0.98559 Learning rate: 0.02 Mask loss: 0.21902 RPN box loss: 0.02445 RPN score loss: 0.00458 RPN total loss: 0.02904 Total loss: 1.5216 timestamp: 1655026740.564684 iteration: 23320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15553 FastRCNN class loss: 0.10747 FastRCNN total loss: 0.263 L1 loss: 0.0000e+00 L2 loss: 0.98543 Learning rate: 0.02 Mask loss: 0.16647 RPN box loss: 0.00525 RPN score loss: 0.0081 RPN total loss: 0.01336 Total loss: 1.42826 timestamp: 1655026743.9885256 iteration: 23325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1735 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.2726 L1 loss: 0.0000e+00 L2 loss: 0.98528 Learning rate: 0.02 Mask loss: 0.19024 RPN box loss: 0.0078 RPN score loss: 0.00291 RPN total loss: 0.01071 Total loss: 1.45883 timestamp: 1655026747.2771568 iteration: 23330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16653 FastRCNN class loss: 0.08924 FastRCNN total loss: 0.25577 L1 loss: 0.0000e+00 L2 loss: 0.98513 Learning rate: 0.02 Mask loss: 0.15328 RPN box loss: 0.02509 RPN score loss: 0.00906 RPN total loss: 0.03415 Total loss: 1.42833 timestamp: 1655026750.6483262 iteration: 23335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15266 FastRCNN class loss: 0.10468 FastRCNN total loss: 0.25733 L1 loss: 0.0000e+00 L2 loss: 0.98496 Learning rate: 0.02 Mask loss: 0.16515 RPN box loss: 0.02418 RPN score loss: 0.00795 RPN total loss: 0.03213 Total loss: 1.43957 timestamp: 1655026754.029611 iteration: 23340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11175 FastRCNN class loss: 0.05091 FastRCNN total loss: 0.16266 L1 loss: 0.0000e+00 L2 loss: 0.9848 Learning rate: 0.02 Mask loss: 0.13258 RPN box loss: 0.00947 RPN score loss: 0.00682 RPN total loss: 0.0163 Total loss: 1.29633 timestamp: 1655026757.326296 iteration: 23345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17147 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.24545 L1 loss: 0.0000e+00 L2 loss: 0.98466 Learning rate: 0.02 Mask loss: 0.16346 RPN box loss: 0.04864 RPN score loss: 0.00715 RPN total loss: 0.05579 Total loss: 1.44935 timestamp: 1655026760.7276654 iteration: 23350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18027 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.30029 L1 loss: 0.0000e+00 L2 loss: 0.98448 Learning rate: 0.02 Mask loss: 0.18341 RPN box loss: 0.02907 RPN score loss: 0.01176 RPN total loss: 0.04083 Total loss: 1.50901 timestamp: 1655026763.9775221 iteration: 23355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15212 FastRCNN class loss: 0.06671 FastRCNN total loss: 0.21883 L1 loss: 0.0000e+00 L2 loss: 0.98432 Learning rate: 0.02 Mask loss: 0.23952 RPN box loss: 0.054 RPN score loss: 0.01495 RPN total loss: 0.06895 Total loss: 1.51162 timestamp: 1655026767.429296 iteration: 23360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11518 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.19892 L1 loss: 0.0000e+00 L2 loss: 0.98417 Learning rate: 0.02 Mask loss: 0.13731 RPN box loss: 0.08402 RPN score loss: 0.01451 RPN total loss: 0.09853 Total loss: 1.41894 timestamp: 1655026770.753746 iteration: 23365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14777 FastRCNN class loss: 0.12037 FastRCNN total loss: 0.26814 L1 loss: 0.0000e+00 L2 loss: 0.98401 Learning rate: 0.02 Mask loss: 0.21776 RPN box loss: 0.03853 RPN score loss: 0.01107 RPN total loss: 0.0496 Total loss: 1.51952 timestamp: 1655026774.1041486 iteration: 23370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19086 FastRCNN class loss: 0.13323 FastRCNN total loss: 0.32409 L1 loss: 0.0000e+00 L2 loss: 0.98382 Learning rate: 0.02 Mask loss: 0.21696 RPN box loss: 0.0691 RPN score loss: 0.00833 RPN total loss: 0.07743 Total loss: 1.60231 timestamp: 1655026777.408965 iteration: 23375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10446 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.16585 L1 loss: 0.0000e+00 L2 loss: 0.98367 Learning rate: 0.02 Mask loss: 0.12032 RPN box loss: 0.02756 RPN score loss: 0.00378 RPN total loss: 0.03134 Total loss: 1.30118 timestamp: 1655026780.8288674 iteration: 23380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13259 FastRCNN class loss: 0.04284 FastRCNN total loss: 0.17544 L1 loss: 0.0000e+00 L2 loss: 0.98353 Learning rate: 0.02 Mask loss: 0.2106 RPN box loss: 0.01276 RPN score loss: 0.00326 RPN total loss: 0.01602 Total loss: 1.38558 timestamp: 1655026784.2658412 iteration: 23385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08909 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.16522 L1 loss: 0.0000e+00 L2 loss: 0.98338 Learning rate: 0.02 Mask loss: 0.13357 RPN box loss: 0.01688 RPN score loss: 0.00917 RPN total loss: 0.02605 Total loss: 1.30822 timestamp: 1655026787.6285007 iteration: 23390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16014 FastRCNN class loss: 0.09 FastRCNN total loss: 0.25013 L1 loss: 0.0000e+00 L2 loss: 0.98325 Learning rate: 0.02 Mask loss: 0.16036 RPN box loss: 0.05393 RPN score loss: 0.00789 RPN total loss: 0.06183 Total loss: 1.45557 timestamp: 1655026791.082801 iteration: 23395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2157 FastRCNN class loss: 0.1196 FastRCNN total loss: 0.3353 L1 loss: 0.0000e+00 L2 loss: 0.98309 Learning rate: 0.02 Mask loss: 0.26061 RPN box loss: 0.04243 RPN score loss: 0.00401 RPN total loss: 0.04644 Total loss: 1.62544 timestamp: 1655026794.2691092 iteration: 23400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15529 FastRCNN class loss: 0.08205 FastRCNN total loss: 0.23734 L1 loss: 0.0000e+00 L2 loss: 0.98292 Learning rate: 0.02 Mask loss: 0.18463 RPN box loss: 0.01941 RPN score loss: 0.0041 RPN total loss: 0.02351 Total loss: 1.4284 timestamp: 1655026797.622041 iteration: 23405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1063 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.18333 L1 loss: 0.0000e+00 L2 loss: 0.98276 Learning rate: 0.02 Mask loss: 0.14556 RPN box loss: 0.04917 RPN score loss: 0.00708 RPN total loss: 0.05625 Total loss: 1.3679 timestamp: 1655026800.832591 iteration: 23410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10643 FastRCNN class loss: 0.06641 FastRCNN total loss: 0.17283 L1 loss: 0.0000e+00 L2 loss: 0.9826 Learning rate: 0.02 Mask loss: 0.17585 RPN box loss: 0.03179 RPN score loss: 0.00606 RPN total loss: 0.03785 Total loss: 1.36914 timestamp: 1655026804.1764743 iteration: 23415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15614 FastRCNN class loss: 0.11711 FastRCNN total loss: 0.27324 L1 loss: 0.0000e+00 L2 loss: 0.98246 Learning rate: 0.02 Mask loss: 0.18953 RPN box loss: 0.02636 RPN score loss: 0.01871 RPN total loss: 0.04508 Total loss: 1.4903 timestamp: 1655026807.5997937 iteration: 23420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.19478 L1 loss: 0.0000e+00 L2 loss: 0.98229 Learning rate: 0.02 Mask loss: 0.21709 RPN box loss: 0.00825 RPN score loss: 0.00437 RPN total loss: 0.01263 Total loss: 1.40679 timestamp: 1655026810.8901005 iteration: 23425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20126 FastRCNN class loss: 0.12132 FastRCNN total loss: 0.32259 L1 loss: 0.0000e+00 L2 loss: 0.98212 Learning rate: 0.02 Mask loss: 0.19592 RPN box loss: 0.02626 RPN score loss: 0.01016 RPN total loss: 0.03642 Total loss: 1.53705 timestamp: 1655026814.3883011 iteration: 23430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.04976 FastRCNN total loss: 0.14432 L1 loss: 0.0000e+00 L2 loss: 0.98195 Learning rate: 0.02 Mask loss: 0.10137 RPN box loss: 0.04864 RPN score loss: 0.0073 RPN total loss: 0.05593 Total loss: 1.28357 timestamp: 1655026817.660499 iteration: 23435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12489 FastRCNN class loss: 0.09131 FastRCNN total loss: 0.21621 L1 loss: 0.0000e+00 L2 loss: 0.98178 Learning rate: 0.02 Mask loss: 0.1598 RPN box loss: 0.04736 RPN score loss: 0.013 RPN total loss: 0.06036 Total loss: 1.41815 timestamp: 1655026821.0561073 iteration: 23440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12553 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.20999 L1 loss: 0.0000e+00 L2 loss: 0.98162 Learning rate: 0.02 Mask loss: 0.20198 RPN box loss: 0.02777 RPN score loss: 0.00471 RPN total loss: 0.03248 Total loss: 1.42606 timestamp: 1655026824.267754 iteration: 23445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11307 FastRCNN class loss: 0.09088 FastRCNN total loss: 0.20395 L1 loss: 0.0000e+00 L2 loss: 0.98148 Learning rate: 0.02 Mask loss: 0.16974 RPN box loss: 0.0109 RPN score loss: 0.00768 RPN total loss: 0.01858 Total loss: 1.37375 timestamp: 1655026827.678818 iteration: 23450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10384 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.98134 Learning rate: 0.02 Mask loss: 0.15041 RPN box loss: 0.03232 RPN score loss: 0.00724 RPN total loss: 0.03956 Total loss: 1.33672 timestamp: 1655026830.947583 iteration: 23455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10129 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.18167 L1 loss: 0.0000e+00 L2 loss: 0.98117 Learning rate: 0.02 Mask loss: 0.10292 RPN box loss: 0.01351 RPN score loss: 0.00226 RPN total loss: 0.01577 Total loss: 1.28153 timestamp: 1655026834.3143888 iteration: 23460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15276 FastRCNN class loss: 0.08139 FastRCNN total loss: 0.23415 L1 loss: 0.0000e+00 L2 loss: 0.98101 Learning rate: 0.02 Mask loss: 0.16504 RPN box loss: 0.03585 RPN score loss: 0.00487 RPN total loss: 0.04072 Total loss: 1.42091 timestamp: 1655026837.7700458 iteration: 23465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17398 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.27539 L1 loss: 0.0000e+00 L2 loss: 0.98084 Learning rate: 0.02 Mask loss: 0.19762 RPN box loss: 0.02715 RPN score loss: 0.01143 RPN total loss: 0.03859 Total loss: 1.49244 timestamp: 1655026841.0535178 iteration: 23470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13747 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.20513 L1 loss: 0.0000e+00 L2 loss: 0.98069 Learning rate: 0.02 Mask loss: 0.17494 RPN box loss: 0.01928 RPN score loss: 0.00781 RPN total loss: 0.0271 Total loss: 1.38785 timestamp: 1655026844.470744 iteration: 23475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19567 FastRCNN class loss: 0.12503 FastRCNN total loss: 0.3207 L1 loss: 0.0000e+00 L2 loss: 0.98053 Learning rate: 0.02 Mask loss: 0.20787 RPN box loss: 0.04128 RPN score loss: 0.01425 RPN total loss: 0.05553 Total loss: 1.56463 timestamp: 1655026847.793192 iteration: 23480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19314 FastRCNN class loss: 0.14066 FastRCNN total loss: 0.3338 L1 loss: 0.0000e+00 L2 loss: 0.98037 Learning rate: 0.02 Mask loss: 0.14072 RPN box loss: 0.06153 RPN score loss: 0.01218 RPN total loss: 0.07371 Total loss: 1.5286 timestamp: 1655026851.199408 iteration: 23485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17164 FastRCNN class loss: 0.14393 FastRCNN total loss: 0.31556 L1 loss: 0.0000e+00 L2 loss: 0.98023 Learning rate: 0.02 Mask loss: 0.16596 RPN box loss: 0.02606 RPN score loss: 0.00524 RPN total loss: 0.0313 Total loss: 1.49305 timestamp: 1655026854.515951 iteration: 23490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15592 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.24561 L1 loss: 0.0000e+00 L2 loss: 0.98007 Learning rate: 0.02 Mask loss: 0.16862 RPN box loss: 0.00868 RPN score loss: 0.00502 RPN total loss: 0.0137 Total loss: 1.40799 timestamp: 1655026857.913968 iteration: 23495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12842 FastRCNN class loss: 0.07847 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 0.9799 Learning rate: 0.02 Mask loss: 0.12871 RPN box loss: 0.01897 RPN score loss: 0.0069 RPN total loss: 0.02586 Total loss: 1.34136 timestamp: 1655026861.2192895 iteration: 23500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14725 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.22627 L1 loss: 0.0000e+00 L2 loss: 0.97975 Learning rate: 0.02 Mask loss: 0.17276 RPN box loss: 0.02643 RPN score loss: 0.01546 RPN total loss: 0.04188 Total loss: 1.42067 timestamp: 1655026864.7841902 iteration: 23505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1362 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.20793 L1 loss: 0.0000e+00 L2 loss: 0.97959 Learning rate: 0.02 Mask loss: 0.13229 RPN box loss: 0.02452 RPN score loss: 0.00627 RPN total loss: 0.03079 Total loss: 1.35061 timestamp: 1655026868.1196957 iteration: 23510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20714 FastRCNN class loss: 0.14354 FastRCNN total loss: 0.35068 L1 loss: 0.0000e+00 L2 loss: 0.97941 Learning rate: 0.02 Mask loss: 0.18754 RPN box loss: 0.07758 RPN score loss: 0.01483 RPN total loss: 0.09241 Total loss: 1.61004 timestamp: 1655026871.4119847 iteration: 23515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17683 FastRCNN class loss: 0.11809 FastRCNN total loss: 0.29491 L1 loss: 0.0000e+00 L2 loss: 0.97923 Learning rate: 0.02 Mask loss: 0.23128 RPN box loss: 0.01575 RPN score loss: 0.00492 RPN total loss: 0.02067 Total loss: 1.52609 timestamp: 1655026874.8535752 iteration: 23520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16813 FastRCNN class loss: 0.07677 FastRCNN total loss: 0.24491 L1 loss: 0.0000e+00 L2 loss: 0.97908 Learning rate: 0.02 Mask loss: 0.21945 RPN box loss: 0.0165 RPN score loss: 0.00388 RPN total loss: 0.02038 Total loss: 1.46382 timestamp: 1655026878.1274462 iteration: 23525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11573 FastRCNN class loss: 0.05407 FastRCNN total loss: 0.1698 L1 loss: 0.0000e+00 L2 loss: 0.97895 Learning rate: 0.02 Mask loss: 0.11367 RPN box loss: 0.03776 RPN score loss: 0.00204 RPN total loss: 0.03981 Total loss: 1.30223 timestamp: 1655026881.5394976 iteration: 23530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17766 FastRCNN class loss: 0.09803 FastRCNN total loss: 0.27569 L1 loss: 0.0000e+00 L2 loss: 0.97881 Learning rate: 0.02 Mask loss: 0.19839 RPN box loss: 0.02654 RPN score loss: 0.00607 RPN total loss: 0.03261 Total loss: 1.48551 timestamp: 1655026884.8680575 iteration: 23535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13179 FastRCNN class loss: 0.13153 FastRCNN total loss: 0.26332 L1 loss: 0.0000e+00 L2 loss: 0.97864 Learning rate: 0.02 Mask loss: 0.15799 RPN box loss: 0.0421 RPN score loss: 0.01268 RPN total loss: 0.05478 Total loss: 1.45474 timestamp: 1655026888.2885246 iteration: 23540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16333 FastRCNN class loss: 0.10263 FastRCNN total loss: 0.26597 L1 loss: 0.0000e+00 L2 loss: 0.97849 Learning rate: 0.02 Mask loss: 0.2341 RPN box loss: 0.03205 RPN score loss: 0.00317 RPN total loss: 0.03522 Total loss: 1.51378 timestamp: 1655026891.6129897 iteration: 23545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07028 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.13011 L1 loss: 0.0000e+00 L2 loss: 0.97831 Learning rate: 0.02 Mask loss: 0.13001 RPN box loss: 0.03353 RPN score loss: 0.00889 RPN total loss: 0.04242 Total loss: 1.28085 timestamp: 1655026894.8785276 iteration: 23550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16565 FastRCNN class loss: 0.09787 FastRCNN total loss: 0.26352 L1 loss: 0.0000e+00 L2 loss: 0.97814 Learning rate: 0.02 Mask loss: 0.15779 RPN box loss: 0.01172 RPN score loss: 0.00449 RPN total loss: 0.01622 Total loss: 1.41566 timestamp: 1655026898.2331429 iteration: 23555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12046 FastRCNN class loss: 0.06863 FastRCNN total loss: 0.18909 L1 loss: 0.0000e+00 L2 loss: 0.97798 Learning rate: 0.02 Mask loss: 0.1989 RPN box loss: 0.02238 RPN score loss: 0.00306 RPN total loss: 0.02543 Total loss: 1.3914 timestamp: 1655026901.5274768 iteration: 23560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12855 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.20559 L1 loss: 0.0000e+00 L2 loss: 0.97785 Learning rate: 0.02 Mask loss: 0.11151 RPN box loss: 0.01541 RPN score loss: 0.00803 RPN total loss: 0.02344 Total loss: 1.31838 timestamp: 1655026904.9430044 iteration: 23565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16519 FastRCNN class loss: 0.09374 FastRCNN total loss: 0.25893 L1 loss: 0.0000e+00 L2 loss: 0.97768 Learning rate: 0.02 Mask loss: 0.14082 RPN box loss: 0.03306 RPN score loss: 0.01168 RPN total loss: 0.04473 Total loss: 1.42216 timestamp: 1655026908.2169526 iteration: 23570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10536 FastRCNN class loss: 0.09451 FastRCNN total loss: 0.19986 L1 loss: 0.0000e+00 L2 loss: 0.97752 Learning rate: 0.02 Mask loss: 0.12784 RPN box loss: 0.06836 RPN score loss: 0.00469 RPN total loss: 0.07305 Total loss: 1.37828 timestamp: 1655026911.653564 iteration: 23575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.06514 FastRCNN total loss: 0.18231 L1 loss: 0.0000e+00 L2 loss: 0.97736 Learning rate: 0.02 Mask loss: 0.13367 RPN box loss: 0.02984 RPN score loss: 0.00712 RPN total loss: 0.03697 Total loss: 1.33031 timestamp: 1655026914.9730744 iteration: 23580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18351 FastRCNN class loss: 0.07651 FastRCNN total loss: 0.26002 L1 loss: 0.0000e+00 L2 loss: 0.97721 Learning rate: 0.02 Mask loss: 0.14187 RPN box loss: 0.01474 RPN score loss: 0.00519 RPN total loss: 0.01993 Total loss: 1.39904 timestamp: 1655026918.3210847 iteration: 23585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.057 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.97705 Learning rate: 0.02 Mask loss: 0.09864 RPN box loss: 0.04606 RPN score loss: 0.00936 RPN total loss: 0.05541 Total loss: 1.32358 timestamp: 1655026921.7110195 iteration: 23590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12136 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.1811 L1 loss: 0.0000e+00 L2 loss: 0.97691 Learning rate: 0.02 Mask loss: 0.21126 RPN box loss: 0.01486 RPN score loss: 0.00475 RPN total loss: 0.01961 Total loss: 1.38887 timestamp: 1655026924.9677446 iteration: 23595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20183 FastRCNN class loss: 0.18159 FastRCNN total loss: 0.38342 L1 loss: 0.0000e+00 L2 loss: 0.97674 Learning rate: 0.02 Mask loss: 0.272 RPN box loss: 0.05291 RPN score loss: 0.01419 RPN total loss: 0.06711 Total loss: 1.69927 timestamp: 1655026928.43438 iteration: 23600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14929 FastRCNN class loss: 0.0761 FastRCNN total loss: 0.22539 L1 loss: 0.0000e+00 L2 loss: 0.97658 Learning rate: 0.02 Mask loss: 0.18968 RPN box loss: 0.02436 RPN score loss: 0.01407 RPN total loss: 0.03843 Total loss: 1.43009 timestamp: 1655026931.6792927 iteration: 23605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.086 FastRCNN class loss: 0.04732 FastRCNN total loss: 0.13333 L1 loss: 0.0000e+00 L2 loss: 0.97642 Learning rate: 0.02 Mask loss: 0.07653 RPN box loss: 0.00405 RPN score loss: 0.00359 RPN total loss: 0.00764 Total loss: 1.19392 timestamp: 1655026935.0810027 iteration: 23610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08866 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.15625 L1 loss: 0.0000e+00 L2 loss: 0.97627 Learning rate: 0.02 Mask loss: 0.1654 RPN box loss: 0.01915 RPN score loss: 0.00246 RPN total loss: 0.0216 Total loss: 1.31952 timestamp: 1655026938.4172366 iteration: 23615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14111 FastRCNN class loss: 0.12867 FastRCNN total loss: 0.26978 L1 loss: 0.0000e+00 L2 loss: 0.9761 Learning rate: 0.02 Mask loss: 0.1873 RPN box loss: 0.02768 RPN score loss: 0.00538 RPN total loss: 0.03307 Total loss: 1.46626 timestamp: 1655026941.8270893 iteration: 23620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24858 FastRCNN class loss: 0.0806 FastRCNN total loss: 0.32918 L1 loss: 0.0000e+00 L2 loss: 0.97593 Learning rate: 0.02 Mask loss: 0.178 RPN box loss: 0.04242 RPN score loss: 0.01112 RPN total loss: 0.05354 Total loss: 1.53666 timestamp: 1655026945.1015165 iteration: 23625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16228 FastRCNN class loss: 0.07742 FastRCNN total loss: 0.2397 L1 loss: 0.0000e+00 L2 loss: 0.97578 Learning rate: 0.02 Mask loss: 0.15643 RPN box loss: 0.04161 RPN score loss: 0.00319 RPN total loss: 0.0448 Total loss: 1.41671 timestamp: 1655026948.451665 iteration: 23630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11593 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.19073 L1 loss: 0.0000e+00 L2 loss: 0.97562 Learning rate: 0.02 Mask loss: 0.15683 RPN box loss: 0.02686 RPN score loss: 0.00554 RPN total loss: 0.0324 Total loss: 1.35558 timestamp: 1655026951.8772135 iteration: 23635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16566 FastRCNN class loss: 0.12929 FastRCNN total loss: 0.29495 L1 loss: 0.0000e+00 L2 loss: 0.97547 Learning rate: 0.02 Mask loss: 0.21287 RPN box loss: 0.14155 RPN score loss: 0.01759 RPN total loss: 0.15914 Total loss: 1.64243 timestamp: 1655026955.1899793 iteration: 23640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10523 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.17597 L1 loss: 0.0000e+00 L2 loss: 0.97529 Learning rate: 0.02 Mask loss: 0.12679 RPN box loss: 0.03447 RPN score loss: 0.00224 RPN total loss: 0.0367 Total loss: 1.31475 timestamp: 1655026958.6894338 iteration: 23645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.12227 FastRCNN total loss: 0.27076 L1 loss: 0.0000e+00 L2 loss: 0.97513 Learning rate: 0.02 Mask loss: 0.15241 RPN box loss: 0.03872 RPN score loss: 0.02302 RPN total loss: 0.06173 Total loss: 1.46003 timestamp: 1655026961.9587986 iteration: 23650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10426 FastRCNN class loss: 0.05818 FastRCNN total loss: 0.16245 L1 loss: 0.0000e+00 L2 loss: 0.97496 Learning rate: 0.02 Mask loss: 0.18186 RPN box loss: 0.01558 RPN score loss: 0.00756 RPN total loss: 0.02314 Total loss: 1.34241 timestamp: 1655026965.341209 iteration: 23655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14401 FastRCNN class loss: 0.14224 FastRCNN total loss: 0.28625 L1 loss: 0.0000e+00 L2 loss: 0.97479 Learning rate: 0.02 Mask loss: 0.22493 RPN box loss: 0.02337 RPN score loss: 0.00514 RPN total loss: 0.02851 Total loss: 1.51449 timestamp: 1655026968.647889 iteration: 23660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20247 FastRCNN class loss: 0.08615 FastRCNN total loss: 0.28862 L1 loss: 0.0000e+00 L2 loss: 0.97462 Learning rate: 0.02 Mask loss: 0.13023 RPN box loss: 0.04414 RPN score loss: 0.02766 RPN total loss: 0.07179 Total loss: 1.46527 timestamp: 1655026972.018643 iteration: 23665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14496 FastRCNN class loss: 0.14865 FastRCNN total loss: 0.2936 L1 loss: 0.0000e+00 L2 loss: 0.97447 Learning rate: 0.02 Mask loss: 0.15446 RPN box loss: 0.0242 RPN score loss: 0.00697 RPN total loss: 0.03117 Total loss: 1.4537 timestamp: 1655026975.346454 iteration: 23670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16943 FastRCNN class loss: 0.05921 FastRCNN total loss: 0.22864 L1 loss: 0.0000e+00 L2 loss: 0.97432 Learning rate: 0.02 Mask loss: 0.12241 RPN box loss: 0.01727 RPN score loss: 0.00104 RPN total loss: 0.01831 Total loss: 1.34368 timestamp: 1655026978.6831799 iteration: 23675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14955 FastRCNN class loss: 0.12783 FastRCNN total loss: 0.27738 L1 loss: 0.0000e+00 L2 loss: 0.97418 Learning rate: 0.02 Mask loss: 0.1405 RPN box loss: 0.03562 RPN score loss: 0.01374 RPN total loss: 0.04937 Total loss: 1.44143 timestamp: 1655026982.0671504 iteration: 23680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08071 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.14054 L1 loss: 0.0000e+00 L2 loss: 0.97404 Learning rate: 0.02 Mask loss: 0.19785 RPN box loss: 0.01937 RPN score loss: 0.00169 RPN total loss: 0.02106 Total loss: 1.3335 timestamp: 1655026985.285133 iteration: 23685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07152 FastRCNN class loss: 0.06673 FastRCNN total loss: 0.13825 L1 loss: 0.0000e+00 L2 loss: 0.97389 Learning rate: 0.02 Mask loss: 0.1456 RPN box loss: 0.02182 RPN score loss: 0.02362 RPN total loss: 0.04544 Total loss: 1.30317 timestamp: 1655026988.6386173 iteration: 23690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25872 FastRCNN class loss: 0.13747 FastRCNN total loss: 0.39619 L1 loss: 0.0000e+00 L2 loss: 0.9737 Learning rate: 0.02 Mask loss: 0.20496 RPN box loss: 0.02285 RPN score loss: 0.0031 RPN total loss: 0.02595 Total loss: 1.60079 timestamp: 1655026992.0168324 iteration: 23695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1422 FastRCNN class loss: 0.05391 FastRCNN total loss: 0.19612 L1 loss: 0.0000e+00 L2 loss: 0.97353 Learning rate: 0.02 Mask loss: 0.12345 RPN box loss: 0.01205 RPN score loss: 0.00417 RPN total loss: 0.01623 Total loss: 1.30932 timestamp: 1655026995.3795288 iteration: 23700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17698 FastRCNN class loss: 0.14058 FastRCNN total loss: 0.31756 L1 loss: 0.0000e+00 L2 loss: 0.97337 Learning rate: 0.02 Mask loss: 0.24035 RPN box loss: 0.03367 RPN score loss: 0.01785 RPN total loss: 0.05152 Total loss: 1.58281 timestamp: 1655026998.67809 iteration: 23705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10066 FastRCNN class loss: 0.06542 FastRCNN total loss: 0.16607 L1 loss: 0.0000e+00 L2 loss: 0.9732 Learning rate: 0.02 Mask loss: 0.09741 RPN box loss: 0.01598 RPN score loss: 0.00621 RPN total loss: 0.02219 Total loss: 1.25888 timestamp: 1655027002.112816 iteration: 23710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24213 FastRCNN class loss: 0.09595 FastRCNN total loss: 0.33808 L1 loss: 0.0000e+00 L2 loss: 0.97306 Learning rate: 0.02 Mask loss: 0.26542 RPN box loss: 0.02102 RPN score loss: 0.00731 RPN total loss: 0.02833 Total loss: 1.60489 timestamp: 1655027005.429269 iteration: 23715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.08701 FastRCNN total loss: 0.22435 L1 loss: 0.0000e+00 L2 loss: 0.97293 Learning rate: 0.02 Mask loss: 0.14993 RPN box loss: 0.01608 RPN score loss: 0.00795 RPN total loss: 0.02404 Total loss: 1.37125 timestamp: 1655027008.827081 iteration: 23720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11147 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.18913 L1 loss: 0.0000e+00 L2 loss: 0.97278 Learning rate: 0.02 Mask loss: 0.12996 RPN box loss: 0.05124 RPN score loss: 0.00471 RPN total loss: 0.05595 Total loss: 1.34782 timestamp: 1655027012.1659338 iteration: 23725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12793 FastRCNN class loss: 0.09012 FastRCNN total loss: 0.21805 L1 loss: 0.0000e+00 L2 loss: 0.97264 Learning rate: 0.02 Mask loss: 0.21087 RPN box loss: 0.03729 RPN score loss: 0.02179 RPN total loss: 0.05908 Total loss: 1.46065 timestamp: 1655027015.4616246 iteration: 23730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20352 FastRCNN class loss: 0.09403 FastRCNN total loss: 0.29754 L1 loss: 0.0000e+00 L2 loss: 0.97247 Learning rate: 0.02 Mask loss: 0.25289 RPN box loss: 0.05212 RPN score loss: 0.00587 RPN total loss: 0.05799 Total loss: 1.58089 timestamp: 1655027018.9028106 iteration: 23735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.0838 FastRCNN total loss: 0.18659 L1 loss: 0.0000e+00 L2 loss: 0.97233 Learning rate: 0.02 Mask loss: 0.1481 RPN box loss: 0.04093 RPN score loss: 0.00543 RPN total loss: 0.04636 Total loss: 1.35338 timestamp: 1655027022.15893 iteration: 23740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14464 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.20891 L1 loss: 0.0000e+00 L2 loss: 0.97219 Learning rate: 0.02 Mask loss: 0.13675 RPN box loss: 0.01267 RPN score loss: 0.00324 RPN total loss: 0.01591 Total loss: 1.33377 timestamp: 1655027025.5937915 iteration: 23745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15845 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.22864 L1 loss: 0.0000e+00 L2 loss: 0.97204 Learning rate: 0.02 Mask loss: 0.19267 RPN box loss: 0.02141 RPN score loss: 0.00509 RPN total loss: 0.0265 Total loss: 1.41985 timestamp: 1655027028.884521 iteration: 23750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14745 FastRCNN class loss: 0.08808 FastRCNN total loss: 0.23553 L1 loss: 0.0000e+00 L2 loss: 0.97185 Learning rate: 0.02 Mask loss: 0.18055 RPN box loss: 0.03694 RPN score loss: 0.01146 RPN total loss: 0.04841 Total loss: 1.43633 timestamp: 1655027032.3432357 iteration: 23755 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12209 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.17678 L1 loss: 0.0000e+00 L2 loss: 0.97168 Learning rate: 0.02 Mask loss: 0.17533 RPN box loss: 0.01516 RPN score loss: 0.00438 RPN total loss: 0.01954 Total loss: 1.34334 timestamp: 1655027035.6965477 iteration: 23760 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07604 FastRCNN class loss: 0.04439 FastRCNN total loss: 0.12042 L1 loss: 0.0000e+00 L2 loss: 0.97153 Learning rate: 0.02 Mask loss: 0.16213 RPN box loss: 0.05607 RPN score loss: 0.00618 RPN total loss: 0.06225 Total loss: 1.31634 timestamp: 1655027038.9327092 iteration: 23765 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.20819 L1 loss: 0.0000e+00 L2 loss: 0.97138 Learning rate: 0.02 Mask loss: 0.19515 RPN box loss: 0.05365 RPN score loss: 0.0067 RPN total loss: 0.06035 Total loss: 1.43507 timestamp: 1655027042.2994509 iteration: 23770 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19486 FastRCNN class loss: 0.08241 FastRCNN total loss: 0.27727 L1 loss: 0.0000e+00 L2 loss: 0.97123 Learning rate: 0.02 Mask loss: 0.15961 RPN box loss: 0.04684 RPN score loss: 0.00832 RPN total loss: 0.05516 Total loss: 1.46327 timestamp: 1655027045.612281 iteration: 23775 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15342 FastRCNN class loss: 0.07829 FastRCNN total loss: 0.23171 L1 loss: 0.0000e+00 L2 loss: 0.97105 Learning rate: 0.02 Mask loss: 0.17377 RPN box loss: 0.06302 RPN score loss: 0.00787 RPN total loss: 0.07089 Total loss: 1.44742 timestamp: 1655027049.0005713 iteration: 23780 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11524 FastRCNN class loss: 0.1012 FastRCNN total loss: 0.21645 L1 loss: 0.0000e+00 L2 loss: 0.97089 Learning rate: 0.02 Mask loss: 0.09398 RPN box loss: 0.03018 RPN score loss: 0.00492 RPN total loss: 0.03511 Total loss: 1.31642 timestamp: 1655027052.2759063 iteration: 23785 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24671 FastRCNN class loss: 0.10015 FastRCNN total loss: 0.34686 L1 loss: 0.0000e+00 L2 loss: 0.97072 Learning rate: 0.02 Mask loss: 0.22838 RPN box loss: 0.03321 RPN score loss: 0.00759 RPN total loss: 0.0408 Total loss: 1.58676 timestamp: 1655027055.6052709 iteration: 23790 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15914 FastRCNN class loss: 0.10294 FastRCNN total loss: 0.26208 L1 loss: 0.0000e+00 L2 loss: 0.97056 Learning rate: 0.02 Mask loss: 0.23458 RPN box loss: 0.03611 RPN score loss: 0.00999 RPN total loss: 0.0461 Total loss: 1.51332 timestamp: 1655027058.9286358 iteration: 23795 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13528 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.20183 L1 loss: 0.0000e+00 L2 loss: 0.97041 Learning rate: 0.02 Mask loss: 0.16297 RPN box loss: 0.0261 RPN score loss: 0.01731 RPN total loss: 0.04341 Total loss: 1.37861 timestamp: 1655027062.2409596 iteration: 23800 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15325 FastRCNN class loss: 0.09069 FastRCNN total loss: 0.24394 L1 loss: 0.0000e+00 L2 loss: 0.97024 Learning rate: 0.02 Mask loss: 0.17896 RPN box loss: 0.01994 RPN score loss: 0.00283 RPN total loss: 0.02277 Total loss: 1.41592 timestamp: 1655027065.6741056 iteration: 23805 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16353 FastRCNN class loss: 0.13073 FastRCNN total loss: 0.29427 L1 loss: 0.0000e+00 L2 loss: 0.97009 Learning rate: 0.02 Mask loss: 0.30084 RPN box loss: 0.07153 RPN score loss: 0.00968 RPN total loss: 0.08121 Total loss: 1.64641 timestamp: 1655027068.9851286 iteration: 23810 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17709 FastRCNN class loss: 0.15744 FastRCNN total loss: 0.33453 L1 loss: 0.0000e+00 L2 loss: 0.96993 Learning rate: 0.02 Mask loss: 0.16328 RPN box loss: 0.06507 RPN score loss: 0.01816 RPN total loss: 0.08323 Total loss: 1.55097 timestamp: 1655027072.436315 iteration: 23815 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15073 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.22143 L1 loss: 0.0000e+00 L2 loss: 0.96981 Learning rate: 0.02 Mask loss: 0.13281 RPN box loss: 0.03677 RPN score loss: 0.00334 RPN total loss: 0.04011 Total loss: 1.36416 timestamp: 1655027075.6788688 iteration: 23820 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13807 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.23992 L1 loss: 0.0000e+00 L2 loss: 0.96965 Learning rate: 0.02 Mask loss: 0.19604 RPN box loss: 0.03591 RPN score loss: 0.00438 RPN total loss: 0.04029 Total loss: 1.4459 timestamp: 1655027079.1668591 iteration: 23825 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20949 FastRCNN class loss: 0.11126 FastRCNN total loss: 0.32076 L1 loss: 0.0000e+00 L2 loss: 0.96946 Learning rate: 0.02 Mask loss: 0.16005 RPN box loss: 0.10579 RPN score loss: 0.01723 RPN total loss: 0.12302 Total loss: 1.57329 timestamp: 1655027082.4410942 iteration: 23830 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11516 FastRCNN class loss: 0.07937 FastRCNN total loss: 0.19452 L1 loss: 0.0000e+00 L2 loss: 0.96933 Learning rate: 0.02 Mask loss: 0.13859 RPN box loss: 0.0226 RPN score loss: 0.0108 RPN total loss: 0.0334 Total loss: 1.33584 timestamp: 1655027085.7919986 iteration: 23835 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18826 FastRCNN class loss: 0.10677 FastRCNN total loss: 0.29503 L1 loss: 0.0000e+00 L2 loss: 0.96916 Learning rate: 0.02 Mask loss: 0.12452 RPN box loss: 0.01151 RPN score loss: 0.00857 RPN total loss: 0.02008 Total loss: 1.40879 timestamp: 1655027089.0636091 iteration: 23840 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08558 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.13881 L1 loss: 0.0000e+00 L2 loss: 0.969 Learning rate: 0.02 Mask loss: 0.11001 RPN box loss: 0.02202 RPN score loss: 0.00291 RPN total loss: 0.02493 Total loss: 1.24276 timestamp: 1655027092.5495033 iteration: 23845 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12537 FastRCNN class loss: 0.09339 FastRCNN total loss: 0.21876 L1 loss: 0.0000e+00 L2 loss: 0.96887 Learning rate: 0.02 Mask loss: 0.18466 RPN box loss: 0.02442 RPN score loss: 0.00552 RPN total loss: 0.02994 Total loss: 1.40222 timestamp: 1655027095.9174924 iteration: 23850 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15958 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.21237 L1 loss: 0.0000e+00 L2 loss: 0.96871 Learning rate: 0.02 Mask loss: 0.08982 RPN box loss: 0.0271 RPN score loss: 0.00261 RPN total loss: 0.02971 Total loss: 1.30062 timestamp: 1655027099.2598326 iteration: 23855 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17824 FastRCNN class loss: 0.08743 FastRCNN total loss: 0.26567 L1 loss: 0.0000e+00 L2 loss: 0.96853 Learning rate: 0.02 Mask loss: 0.20707 RPN box loss: 0.00576 RPN score loss: 0.00227 RPN total loss: 0.00803 Total loss: 1.4493 timestamp: 1655027102.6843216 iteration: 23860 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10495 FastRCNN class loss: 0.09042 FastRCNN total loss: 0.19537 L1 loss: 0.0000e+00 L2 loss: 0.96837 Learning rate: 0.02 Mask loss: 0.22044 RPN box loss: 0.01705 RPN score loss: 0.00804 RPN total loss: 0.0251 Total loss: 1.40928 timestamp: 1655027106.0148823 iteration: 23865 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1142 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.96824 Learning rate: 0.02 Mask loss: 0.14207 RPN box loss: 0.02684 RPN score loss: 0.00328 RPN total loss: 0.03012 Total loss: 1.33731 timestamp: 1655027109.3182254 iteration: 23870 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14956 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.22845 L1 loss: 0.0000e+00 L2 loss: 0.96809 Learning rate: 0.02 Mask loss: 0.18022 RPN box loss: 0.01559 RPN score loss: 0.0084 RPN total loss: 0.02399 Total loss: 1.40076 timestamp: 1655027112.615587 iteration: 23875 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17372 FastRCNN class loss: 0.0991 FastRCNN total loss: 0.27282 L1 loss: 0.0000e+00 L2 loss: 0.9679 Learning rate: 0.02 Mask loss: 0.21995 RPN box loss: 0.06094 RPN score loss: 0.01057 RPN total loss: 0.0715 Total loss: 1.53217 timestamp: 1655027116.0563757 iteration: 23880 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1222 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.20821 L1 loss: 0.0000e+00 L2 loss: 0.96775 Learning rate: 0.02 Mask loss: 0.22765 RPN box loss: 0.04704 RPN score loss: 0.01019 RPN total loss: 0.05723 Total loss: 1.46085 timestamp: 1655027119.4143088 iteration: 23885 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13706 FastRCNN class loss: 0.06748 FastRCNN total loss: 0.20453 L1 loss: 0.0000e+00 L2 loss: 0.96761 Learning rate: 0.02 Mask loss: 0.19652 RPN box loss: 0.01431 RPN score loss: 0.0034 RPN total loss: 0.01771 Total loss: 1.38637 timestamp: 1655027122.6072397 iteration: 23890 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12436 FastRCNN class loss: 0.10048 FastRCNN total loss: 0.22484 L1 loss: 0.0000e+00 L2 loss: 0.96745 Learning rate: 0.02 Mask loss: 0.21404 RPN box loss: 0.01714 RPN score loss: 0.01229 RPN total loss: 0.02943 Total loss: 1.43576 timestamp: 1655027125.9621632 iteration: 23895 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.19581 L1 loss: 0.0000e+00 L2 loss: 0.96729 Learning rate: 0.02 Mask loss: 0.18331 RPN box loss: 0.06257 RPN score loss: 0.00488 RPN total loss: 0.06745 Total loss: 1.41386 timestamp: 1655027129.2318673 iteration: 23900 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13911 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.2211 L1 loss: 0.0000e+00 L2 loss: 0.96714 Learning rate: 0.02 Mask loss: 0.15507 RPN box loss: 0.07512 RPN score loss: 0.00924 RPN total loss: 0.08436 Total loss: 1.42767 timestamp: 1655027132.6026063 iteration: 23905 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14878 FastRCNN class loss: 0.09999 FastRCNN total loss: 0.24877 L1 loss: 0.0000e+00 L2 loss: 0.96699 Learning rate: 0.02 Mask loss: 0.14188 RPN box loss: 0.01647 RPN score loss: 0.00592 RPN total loss: 0.02239 Total loss: 1.38002 timestamp: 1655027135.8892024 iteration: 23910 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15049 FastRCNN class loss: 0.09892 FastRCNN total loss: 0.24941 L1 loss: 0.0000e+00 L2 loss: 0.96685 Learning rate: 0.02 Mask loss: 0.17384 RPN box loss: 0.06694 RPN score loss: 0.01068 RPN total loss: 0.07762 Total loss: 1.46773 timestamp: 1655027139.2517548 iteration: 23915 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17398 FastRCNN class loss: 0.08763 FastRCNN total loss: 0.26161 L1 loss: 0.0000e+00 L2 loss: 0.96671 Learning rate: 0.02 Mask loss: 0.11771 RPN box loss: 0.0187 RPN score loss: 0.01065 RPN total loss: 0.02934 Total loss: 1.37537 timestamp: 1655027142.572659 iteration: 23920 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18338 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.25799 L1 loss: 0.0000e+00 L2 loss: 0.96655 Learning rate: 0.02 Mask loss: 0.20951 RPN box loss: 0.02118 RPN score loss: 0.00694 RPN total loss: 0.02812 Total loss: 1.46217 timestamp: 1655027145.9930422 iteration: 23925 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17238 FastRCNN class loss: 0.07446 FastRCNN total loss: 0.24684 L1 loss: 0.0000e+00 L2 loss: 0.96641 Learning rate: 0.02 Mask loss: 0.13046 RPN box loss: 0.01825 RPN score loss: 0.00393 RPN total loss: 0.02218 Total loss: 1.36588 timestamp: 1655027149.4314535 iteration: 23930 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11157 FastRCNN class loss: 0.05994 FastRCNN total loss: 0.17151 L1 loss: 0.0000e+00 L2 loss: 0.96624 Learning rate: 0.02 Mask loss: 0.12113 RPN box loss: 0.02721 RPN score loss: 0.00283 RPN total loss: 0.03005 Total loss: 1.28893 timestamp: 1655027152.6917822 iteration: 23935 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18954 FastRCNN class loss: 0.09553 FastRCNN total loss: 0.28508 L1 loss: 0.0000e+00 L2 loss: 0.96606 Learning rate: 0.02 Mask loss: 0.22796 RPN box loss: 0.01476 RPN score loss: 0.0076 RPN total loss: 0.02236 Total loss: 1.50146 timestamp: 1655027156.0315344 iteration: 23940 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.19169 L1 loss: 0.0000e+00 L2 loss: 0.9659 Learning rate: 0.02 Mask loss: 0.17027 RPN box loss: 0.06292 RPN score loss: 0.00908 RPN total loss: 0.07199 Total loss: 1.39985 timestamp: 1655027159.245141 iteration: 23945 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13302 FastRCNN class loss: 0.09853 FastRCNN total loss: 0.23155 L1 loss: 0.0000e+00 L2 loss: 0.96573 Learning rate: 0.02 Mask loss: 0.1897 RPN box loss: 0.03889 RPN score loss: 0.00534 RPN total loss: 0.04423 Total loss: 1.43121 timestamp: 1655027162.693239 iteration: 23950 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18992 FastRCNN class loss: 0.17741 FastRCNN total loss: 0.36734 L1 loss: 0.0000e+00 L2 loss: 0.96558 Learning rate: 0.02 Mask loss: 0.21395 RPN box loss: 0.02929 RPN score loss: 0.01563 RPN total loss: 0.04492 Total loss: 1.59179 timestamp: 1655027165.9481177 iteration: 23955 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17282 FastRCNN class loss: 0.11553 FastRCNN total loss: 0.28835 L1 loss: 0.0000e+00 L2 loss: 0.96541 Learning rate: 0.02 Mask loss: 0.24814 RPN box loss: 0.01299 RPN score loss: 0.00953 RPN total loss: 0.02252 Total loss: 1.52443 timestamp: 1655027169.329033 iteration: 23960 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16386 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.2399 L1 loss: 0.0000e+00 L2 loss: 0.96525 Learning rate: 0.02 Mask loss: 0.14694 RPN box loss: 0.0641 RPN score loss: 0.00683 RPN total loss: 0.07093 Total loss: 1.42302 timestamp: 1655027172.6751733 iteration: 23965 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20243 FastRCNN class loss: 0.12072 FastRCNN total loss: 0.32315 L1 loss: 0.0000e+00 L2 loss: 0.96512 Learning rate: 0.02 Mask loss: 0.26092 RPN box loss: 0.03941 RPN score loss: 0.01889 RPN total loss: 0.0583 Total loss: 1.60748 timestamp: 1655027175.9737298 iteration: 23970 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16302 FastRCNN class loss: 0.09427 FastRCNN total loss: 0.25729 L1 loss: 0.0000e+00 L2 loss: 0.96496 Learning rate: 0.02 Mask loss: 0.19957 RPN box loss: 0.02207 RPN score loss: 0.00713 RPN total loss: 0.0292 Total loss: 1.45102 timestamp: 1655027179.2641187 iteration: 23975 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18714 FastRCNN class loss: 0.13045 FastRCNN total loss: 0.31759 L1 loss: 0.0000e+00 L2 loss: 0.96479 Learning rate: 0.02 Mask loss: 0.18608 RPN box loss: 0.04888 RPN score loss: 0.01924 RPN total loss: 0.06813 Total loss: 1.53659 timestamp: 1655027182.5262284 iteration: 23980 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.09084 FastRCNN total loss: 0.23299 L1 loss: 0.0000e+00 L2 loss: 0.96463 Learning rate: 0.02 Mask loss: 0.23628 RPN box loss: 0.05598 RPN score loss: 0.00901 RPN total loss: 0.06499 Total loss: 1.49889 timestamp: 1655027185.8940618 iteration: 23985 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17309 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.22933 L1 loss: 0.0000e+00 L2 loss: 0.96446 Learning rate: 0.02 Mask loss: 0.12288 RPN box loss: 0.00957 RPN score loss: 0.00334 RPN total loss: 0.01292 Total loss: 1.32959 timestamp: 1655027189.18537 iteration: 23990 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22128 FastRCNN class loss: 0.11049 FastRCNN total loss: 0.33177 L1 loss: 0.0000e+00 L2 loss: 0.9643 Learning rate: 0.02 Mask loss: 0.22648 RPN box loss: 0.0121 RPN score loss: 0.00408 RPN total loss: 0.01618 Total loss: 1.53873 timestamp: 1655027192.5374181 iteration: 23995 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11282 FastRCNN class loss: 0.08013 FastRCNN total loss: 0.19294 L1 loss: 0.0000e+00 L2 loss: 0.96416 Learning rate: 0.02 Mask loss: 0.16122 RPN box loss: 0.02276 RPN score loss: 0.01348 RPN total loss: 0.03624 Total loss: 1.35457 timestamp: 1655027195.8234267 iteration: 24000 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20853 FastRCNN class loss: 0.091 FastRCNN total loss: 0.29953 L1 loss: 0.0000e+00 L2 loss: 0.96401 Learning rate: 0.02 Mask loss: 0.16283 RPN box loss: 0.03158 RPN score loss: 0.00637 RPN total loss: 0.03795 Total loss: 1.46433 timestamp: 1655027199.02672 iteration: 24005 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14095 FastRCNN class loss: 0.11097 FastRCNN total loss: 0.25192 L1 loss: 0.0000e+00 L2 loss: 0.96386 Learning rate: 0.02 Mask loss: 0.1445 RPN box loss: 0.02161 RPN score loss: 0.00616 RPN total loss: 0.02778 Total loss: 1.38805 timestamp: 1655027202.2620869 iteration: 24010 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19265 FastRCNN class loss: 0.09045 FastRCNN total loss: 0.2831 L1 loss: 0.0000e+00 L2 loss: 0.96371 Learning rate: 0.02 Mask loss: 0.15832 RPN box loss: 0.03264 RPN score loss: 0.01647 RPN total loss: 0.0491 Total loss: 1.45423 timestamp: 1655027205.670141 iteration: 24015 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15332 FastRCNN class loss: 0.07857 FastRCNN total loss: 0.23189 L1 loss: 0.0000e+00 L2 loss: 0.96353 Learning rate: 0.02 Mask loss: 0.13315 RPN box loss: 0.02977 RPN score loss: 0.00864 RPN total loss: 0.03842 Total loss: 1.36699 timestamp: 1655027209.0938337 iteration: 24020 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1588 FastRCNN class loss: 0.10832 FastRCNN total loss: 0.26712 L1 loss: 0.0000e+00 L2 loss: 0.96337 Learning rate: 0.02 Mask loss: 0.18911 RPN box loss: 0.07077 RPN score loss: 0.00454 RPN total loss: 0.07531 Total loss: 1.49491 timestamp: 1655027212.4192836 iteration: 24025 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18604 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.25816 L1 loss: 0.0000e+00 L2 loss: 0.96324 Learning rate: 0.02 Mask loss: 0.25136 RPN box loss: 0.02291 RPN score loss: 0.005 RPN total loss: 0.02791 Total loss: 1.50067 timestamp: 1655027215.7316408 iteration: 24030 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13278 FastRCNN class loss: 0.08974 FastRCNN total loss: 0.22252 L1 loss: 0.0000e+00 L2 loss: 0.96309 Learning rate: 0.02 Mask loss: 0.17505 RPN box loss: 0.01607 RPN score loss: 0.00422 RPN total loss: 0.02029 Total loss: 1.38094 timestamp: 1655027219.018774 iteration: 24035 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19592 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.27432 L1 loss: 0.0000e+00 L2 loss: 0.96294 Learning rate: 0.02 Mask loss: 0.14853 RPN box loss: 0.06486 RPN score loss: 0.00621 RPN total loss: 0.07107 Total loss: 1.45687 timestamp: 1655027222.3441658 iteration: 24040 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20811 FastRCNN class loss: 0.16486 FastRCNN total loss: 0.37297 L1 loss: 0.0000e+00 L2 loss: 0.96277 Learning rate: 0.02 Mask loss: 0.26428 RPN box loss: 0.03641 RPN score loss: 0.01323 RPN total loss: 0.04964 Total loss: 1.64967 timestamp: 1655027225.60693 iteration: 24045 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08615 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.14042 L1 loss: 0.0000e+00 L2 loss: 0.96259 Learning rate: 0.02 Mask loss: 0.21898 RPN box loss: 0.04243 RPN score loss: 0.00579 RPN total loss: 0.04823 Total loss: 1.37022 timestamp: 1655027228.9840238 iteration: 24050 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10659 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.16564 L1 loss: 0.0000e+00 L2 loss: 0.96243 Learning rate: 0.02 Mask loss: 0.11397 RPN box loss: 0.0236 RPN score loss: 0.00221 RPN total loss: 0.0258 Total loss: 1.26784 timestamp: 1655027232.228058 iteration: 24055 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14598 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.21784 L1 loss: 0.0000e+00 L2 loss: 0.96227 Learning rate: 0.02 Mask loss: 0.14383 RPN box loss: 0.04393 RPN score loss: 0.01421 RPN total loss: 0.05814 Total loss: 1.38208 timestamp: 1655027235.6097062 iteration: 24060 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1753 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.24714 L1 loss: 0.0000e+00 L2 loss: 0.96214 Learning rate: 0.02 Mask loss: 0.14947 RPN box loss: 0.05907 RPN score loss: 0.0056 RPN total loss: 0.06467 Total loss: 1.42342 timestamp: 1655027239.0423763 iteration: 24065 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16776 FastRCNN class loss: 0.06222 FastRCNN total loss: 0.22998 L1 loss: 0.0000e+00 L2 loss: 0.96199 Learning rate: 0.02 Mask loss: 0.15021 RPN box loss: 0.01841 RPN score loss: 0.00687 RPN total loss: 0.02528 Total loss: 1.36745 timestamp: 1655027242.3435228 iteration: 24070 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15511 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.23816 L1 loss: 0.0000e+00 L2 loss: 0.96184 Learning rate: 0.02 Mask loss: 0.17482 RPN box loss: 0.0138 RPN score loss: 0.00731 RPN total loss: 0.02111 Total loss: 1.39593 timestamp: 1655027245.70687 iteration: 24075 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10734 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.17874 L1 loss: 0.0000e+00 L2 loss: 0.96171 Learning rate: 0.02 Mask loss: 0.16485 RPN box loss: 0.01853 RPN score loss: 0.00866 RPN total loss: 0.02718 Total loss: 1.33248 timestamp: 1655027248.9688206 iteration: 24080 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19872 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.30057 L1 loss: 0.0000e+00 L2 loss: 0.96157 Learning rate: 0.02 Mask loss: 0.21238 RPN box loss: 0.05514 RPN score loss: 0.01041 RPN total loss: 0.06556 Total loss: 1.54007 timestamp: 1655027252.3166168 iteration: 24085 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23695 FastRCNN class loss: 0.14666 FastRCNN total loss: 0.38361 L1 loss: 0.0000e+00 L2 loss: 0.96137 Learning rate: 0.02 Mask loss: 0.27175 RPN box loss: 0.04776 RPN score loss: 0.01359 RPN total loss: 0.06135 Total loss: 1.67808 timestamp: 1655027255.5728197 iteration: 24090 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17808 FastRCNN class loss: 0.11017 FastRCNN total loss: 0.28825 L1 loss: 0.0000e+00 L2 loss: 0.96119 Learning rate: 0.02 Mask loss: 0.16369 RPN box loss: 0.01444 RPN score loss: 0.01357 RPN total loss: 0.02801 Total loss: 1.44114 timestamp: 1655027259.0167353 iteration: 24095 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0941 FastRCNN class loss: 0.07968 FastRCNN total loss: 0.17378 L1 loss: 0.0000e+00 L2 loss: 0.96103 Learning rate: 0.02 Mask loss: 0.11802 RPN box loss: 0.0298 RPN score loss: 0.00548 RPN total loss: 0.03528 Total loss: 1.2881 timestamp: 1655027262.296233 iteration: 24100 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17537 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.24798 L1 loss: 0.0000e+00 L2 loss: 0.96088 Learning rate: 0.02 Mask loss: 0.1609 RPN box loss: 0.05309 RPN score loss: 0.00995 RPN total loss: 0.06304 Total loss: 1.4328 timestamp: 1655027265.7974741 iteration: 24105 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22995 FastRCNN class loss: 0.12076 FastRCNN total loss: 0.35071 L1 loss: 0.0000e+00 L2 loss: 0.96074 Learning rate: 0.02 Mask loss: 0.17765 RPN box loss: 0.0133 RPN score loss: 0.00488 RPN total loss: 0.01818 Total loss: 1.50727 timestamp: 1655027269.1972308 iteration: 24110 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20603 FastRCNN class loss: 0.10894 FastRCNN total loss: 0.31497 L1 loss: 0.0000e+00 L2 loss: 0.9606 Learning rate: 0.02 Mask loss: 0.16303 RPN box loss: 0.02107 RPN score loss: 0.00873 RPN total loss: 0.0298 Total loss: 1.4684 timestamp: 1655027272.4720662 iteration: 24115 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12008 FastRCNN class loss: 0.10504 FastRCNN total loss: 0.22512 L1 loss: 0.0000e+00 L2 loss: 0.96045 Learning rate: 0.02 Mask loss: 0.1248 RPN box loss: 0.04365 RPN score loss: 0.01526 RPN total loss: 0.05892 Total loss: 1.36928 timestamp: 1655027275.8305678 iteration: 24120 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16991 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.25607 L1 loss: 0.0000e+00 L2 loss: 0.96029 Learning rate: 0.02 Mask loss: 0.20347 RPN box loss: 0.05097 RPN score loss: 0.01553 RPN total loss: 0.0665 Total loss: 1.48633 timestamp: 1655027279.1560688 iteration: 24125 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24368 FastRCNN class loss: 0.09899 FastRCNN total loss: 0.34268 L1 loss: 0.0000e+00 L2 loss: 0.96012 Learning rate: 0.02 Mask loss: 0.17047 RPN box loss: 0.03382 RPN score loss: 0.0087 RPN total loss: 0.04252 Total loss: 1.51578 timestamp: 1655027282.478736 iteration: 24130 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17462 FastRCNN class loss: 0.20861 FastRCNN total loss: 0.38323 L1 loss: 0.0000e+00 L2 loss: 0.95997 Learning rate: 0.02 Mask loss: 0.2711 RPN box loss: 0.05961 RPN score loss: 0.08655 RPN total loss: 0.14616 Total loss: 1.76046 timestamp: 1655027285.702501 iteration: 24135 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08551 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.13575 L1 loss: 0.0000e+00 L2 loss: 0.95981 Learning rate: 0.02 Mask loss: 0.1335 RPN box loss: 0.0613 RPN score loss: 0.00704 RPN total loss: 0.06835 Total loss: 1.29741 timestamp: 1655027289.1409009 iteration: 24140 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19229 FastRCNN class loss: 0.08234 FastRCNN total loss: 0.27464 L1 loss: 0.0000e+00 L2 loss: 0.95967 Learning rate: 0.02 Mask loss: 0.15397 RPN box loss: 0.03814 RPN score loss: 0.00726 RPN total loss: 0.04541 Total loss: 1.43369 timestamp: 1655027292.357877 iteration: 24145 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12652 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.19102 L1 loss: 0.0000e+00 L2 loss: 0.95951 Learning rate: 0.02 Mask loss: 0.14155 RPN box loss: 0.07597 RPN score loss: 0.00745 RPN total loss: 0.08342 Total loss: 1.3755 timestamp: 1655027295.7286155 iteration: 24150 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18132 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.26961 L1 loss: 0.0000e+00 L2 loss: 0.95934 Learning rate: 0.02 Mask loss: 0.19361 RPN box loss: 0.04066 RPN score loss: 0.0046 RPN total loss: 0.04526 Total loss: 1.46783 timestamp: 1655027299.1273174 iteration: 24155 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12657 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.21374 L1 loss: 0.0000e+00 L2 loss: 0.95918 Learning rate: 0.02 Mask loss: 0.18606 RPN box loss: 0.08063 RPN score loss: 0.00495 RPN total loss: 0.08559 Total loss: 1.44457 timestamp: 1655027302.3650281 iteration: 24160 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.16011 L1 loss: 0.0000e+00 L2 loss: 0.95901 Learning rate: 0.02 Mask loss: 0.10401 RPN box loss: 0.02676 RPN score loss: 0.00278 RPN total loss: 0.02955 Total loss: 1.25268 timestamp: 1655027305.8551466 iteration: 24165 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09498 FastRCNN class loss: 0.0483 FastRCNN total loss: 0.14327 L1 loss: 0.0000e+00 L2 loss: 0.95886 Learning rate: 0.02 Mask loss: 0.20568 RPN box loss: 0.04533 RPN score loss: 0.01774 RPN total loss: 0.06307 Total loss: 1.37089 timestamp: 1655027309.1721678 iteration: 24170 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14297 FastRCNN class loss: 0.10406 FastRCNN total loss: 0.24702 L1 loss: 0.0000e+00 L2 loss: 0.95869 Learning rate: 0.02 Mask loss: 0.19272 RPN box loss: 0.02367 RPN score loss: 0.01219 RPN total loss: 0.03586 Total loss: 1.43429 timestamp: 1655027312.6219428 iteration: 24175 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08684 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.14901 L1 loss: 0.0000e+00 L2 loss: 0.95852 Learning rate: 0.02 Mask loss: 0.11665 RPN box loss: 0.01761 RPN score loss: 0.00826 RPN total loss: 0.02587 Total loss: 1.25004 timestamp: 1655027315.940915 iteration: 24180 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17664 FastRCNN class loss: 0.06491 FastRCNN total loss: 0.24155 L1 loss: 0.0000e+00 L2 loss: 0.95836 Learning rate: 0.02 Mask loss: 0.15721 RPN box loss: 0.09323 RPN score loss: 0.00568 RPN total loss: 0.09891 Total loss: 1.45603 timestamp: 1655027319.3037639 iteration: 24185 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06996 FastRCNN class loss: 0.03938 FastRCNN total loss: 0.10934 L1 loss: 0.0000e+00 L2 loss: 0.95823 Learning rate: 0.02 Mask loss: 0.18258 RPN box loss: 0.00618 RPN score loss: 0.00321 RPN total loss: 0.00939 Total loss: 1.25954 timestamp: 1655027322.6239474 iteration: 24190 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14428 FastRCNN class loss: 0.1139 FastRCNN total loss: 0.25818 L1 loss: 0.0000e+00 L2 loss: 0.95809 Learning rate: 0.02 Mask loss: 0.2154 RPN box loss: 0.05255 RPN score loss: 0.01729 RPN total loss: 0.06984 Total loss: 1.50151 timestamp: 1655027325.9690711 iteration: 24195 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18653 FastRCNN class loss: 0.14464 FastRCNN total loss: 0.33117 L1 loss: 0.0000e+00 L2 loss: 0.95795 Learning rate: 0.02 Mask loss: 0.25437 RPN box loss: 0.06067 RPN score loss: 0.01158 RPN total loss: 0.07225 Total loss: 1.61574 timestamp: 1655027329.4023757 iteration: 24200 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16075 FastRCNN class loss: 0.09991 FastRCNN total loss: 0.26065 L1 loss: 0.0000e+00 L2 loss: 0.95777 Learning rate: 0.02 Mask loss: 0.14395 RPN box loss: 0.02958 RPN score loss: 0.02494 RPN total loss: 0.05451 Total loss: 1.41688 timestamp: 1655027332.6377048 iteration: 24205 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16293 FastRCNN class loss: 0.10255 FastRCNN total loss: 0.26548 L1 loss: 0.0000e+00 L2 loss: 0.95758 Learning rate: 0.02 Mask loss: 0.22303 RPN box loss: 0.01668 RPN score loss: 0.00349 RPN total loss: 0.02017 Total loss: 1.46625 timestamp: 1655027336.0119128 iteration: 24210 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15735 FastRCNN class loss: 0.05338 FastRCNN total loss: 0.21073 L1 loss: 0.0000e+00 L2 loss: 0.95744 Learning rate: 0.02 Mask loss: 0.1429 RPN box loss: 0.05705 RPN score loss: 0.00685 RPN total loss: 0.06391 Total loss: 1.37498 timestamp: 1655027339.2782626 iteration: 24215 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09919 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.16425 L1 loss: 0.0000e+00 L2 loss: 0.95732 Learning rate: 0.02 Mask loss: 0.22288 RPN box loss: 0.00584 RPN score loss: 0.0032 RPN total loss: 0.00905 Total loss: 1.35349 timestamp: 1655027342.7641697 iteration: 24220 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12847 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.19534 L1 loss: 0.0000e+00 L2 loss: 0.95717 Learning rate: 0.02 Mask loss: 0.13395 RPN box loss: 0.03344 RPN score loss: 0.00689 RPN total loss: 0.04033 Total loss: 1.32677 timestamp: 1655027346.1148376 iteration: 24225 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16053 FastRCNN class loss: 0.06617 FastRCNN total loss: 0.2267 L1 loss: 0.0000e+00 L2 loss: 0.95701 Learning rate: 0.02 Mask loss: 0.12956 RPN box loss: 0.0493 RPN score loss: 0.00759 RPN total loss: 0.05689 Total loss: 1.37016 timestamp: 1655027349.5039818 iteration: 24230 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15852 FastRCNN class loss: 0.06907 FastRCNN total loss: 0.22759 L1 loss: 0.0000e+00 L2 loss: 0.95685 Learning rate: 0.02 Mask loss: 0.1303 RPN box loss: 0.02228 RPN score loss: 0.00352 RPN total loss: 0.0258 Total loss: 1.34055 timestamp: 1655027352.7784317 iteration: 24235 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21559 FastRCNN class loss: 0.09119 FastRCNN total loss: 0.30678 L1 loss: 0.0000e+00 L2 loss: 0.95669 Learning rate: 0.02 Mask loss: 0.16682 RPN box loss: 0.03669 RPN score loss: 0.00516 RPN total loss: 0.04185 Total loss: 1.47214 timestamp: 1655027356.1051497 iteration: 24240 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11171 FastRCNN class loss: 0.08684 FastRCNN total loss: 0.19855 L1 loss: 0.0000e+00 L2 loss: 0.95653 Learning rate: 0.02 Mask loss: 0.19424 RPN box loss: 0.01483 RPN score loss: 0.006 RPN total loss: 0.02083 Total loss: 1.37015 timestamp: 1655027359.372882 iteration: 24245 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10203 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.16051 L1 loss: 0.0000e+00 L2 loss: 0.95636 Learning rate: 0.02 Mask loss: 0.17191 RPN box loss: 0.02443 RPN score loss: 0.00487 RPN total loss: 0.02929 Total loss: 1.31807 timestamp: 1655027362.6571555 iteration: 24250 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07965 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.15878 L1 loss: 0.0000e+00 L2 loss: 0.9562 Learning rate: 0.02 Mask loss: 0.13172 RPN box loss: 0.02114 RPN score loss: 0.01227 RPN total loss: 0.03341 Total loss: 1.28011 timestamp: 1655027366.0303042 iteration: 24255 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19836 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.25743 L1 loss: 0.0000e+00 L2 loss: 0.95606 Learning rate: 0.02 Mask loss: 0.1064 RPN box loss: 0.04702 RPN score loss: 0.00943 RPN total loss: 0.05645 Total loss: 1.37634 timestamp: 1655027369.2996097 iteration: 24260 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11428 FastRCNN class loss: 0.11567 FastRCNN total loss: 0.22995 L1 loss: 0.0000e+00 L2 loss: 0.95592 Learning rate: 0.02 Mask loss: 0.25499 RPN box loss: 0.02215 RPN score loss: 0.00448 RPN total loss: 0.02663 Total loss: 1.46749 timestamp: 1655027372.757769 iteration: 24265 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09549 FastRCNN class loss: 0.13096 FastRCNN total loss: 0.22645 L1 loss: 0.0000e+00 L2 loss: 0.95577 Learning rate: 0.02 Mask loss: 0.12084 RPN box loss: 0.03692 RPN score loss: 0.02233 RPN total loss: 0.05924 Total loss: 1.36231 timestamp: 1655027376.039516 iteration: 24270 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16328 FastRCNN class loss: 0.10712 FastRCNN total loss: 0.27039 L1 loss: 0.0000e+00 L2 loss: 0.95561 Learning rate: 0.02 Mask loss: 0.18622 RPN box loss: 0.02622 RPN score loss: 0.01171 RPN total loss: 0.03792 Total loss: 1.45014 timestamp: 1655027379.4387593 iteration: 24275 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19742 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.26746 L1 loss: 0.0000e+00 L2 loss: 0.95545 Learning rate: 0.02 Mask loss: 0.15813 RPN box loss: 0.02408 RPN score loss: 0.00525 RPN total loss: 0.02933 Total loss: 1.41037 timestamp: 1655027382.9177477 iteration: 24280 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14826 FastRCNN class loss: 0.05629 FastRCNN total loss: 0.20455 L1 loss: 0.0000e+00 L2 loss: 0.95528 Learning rate: 0.02 Mask loss: 0.15875 RPN box loss: 0.02133 RPN score loss: 0.00514 RPN total loss: 0.02647 Total loss: 1.34505 timestamp: 1655027386.27996 iteration: 24285 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14818 FastRCNN class loss: 0.09479 FastRCNN total loss: 0.24297 L1 loss: 0.0000e+00 L2 loss: 0.95513 Learning rate: 0.02 Mask loss: 0.19185 RPN box loss: 0.02205 RPN score loss: 0.00476 RPN total loss: 0.0268 Total loss: 1.41676 timestamp: 1655027389.7024093 iteration: 24290 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18399 FastRCNN class loss: 0.09064 FastRCNN total loss: 0.27463 L1 loss: 0.0000e+00 L2 loss: 0.95498 Learning rate: 0.02 Mask loss: 0.19631 RPN box loss: 0.03373 RPN score loss: 0.0145 RPN total loss: 0.04823 Total loss: 1.47416 timestamp: 1655027393.0966249 iteration: 24295 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15755 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.23697 L1 loss: 0.0000e+00 L2 loss: 0.95483 Learning rate: 0.02 Mask loss: 0.18015 RPN box loss: 0.07015 RPN score loss: 0.00261 RPN total loss: 0.07276 Total loss: 1.44472 timestamp: 1655027396.502651 iteration: 24300 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12447 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.19934 L1 loss: 0.0000e+00 L2 loss: 0.95468 Learning rate: 0.02 Mask loss: 0.16919 RPN box loss: 0.02408 RPN score loss: 0.00807 RPN total loss: 0.03215 Total loss: 1.35537 timestamp: 1655027399.8327932 iteration: 24305 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08657 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.16532 L1 loss: 0.0000e+00 L2 loss: 0.95451 Learning rate: 0.02 Mask loss: 0.12415 RPN box loss: 0.02049 RPN score loss: 0.00379 RPN total loss: 0.02428 Total loss: 1.26826 timestamp: 1655027403.2297518 iteration: 24310 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20074 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.30264 L1 loss: 0.0000e+00 L2 loss: 0.95435 Learning rate: 0.02 Mask loss: 0.16505 RPN box loss: 0.0806 RPN score loss: 0.00815 RPN total loss: 0.08875 Total loss: 1.51079 timestamp: 1655027406.5184145 iteration: 24315 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15238 FastRCNN class loss: 0.13408 FastRCNN total loss: 0.28646 L1 loss: 0.0000e+00 L2 loss: 0.95417 Learning rate: 0.02 Mask loss: 0.18248 RPN box loss: 0.08231 RPN score loss: 0.00459 RPN total loss: 0.0869 Total loss: 1.51002 timestamp: 1655027409.960681 iteration: 24320 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17033 FastRCNN class loss: 0.11655 FastRCNN total loss: 0.28688 L1 loss: 0.0000e+00 L2 loss: 0.95402 Learning rate: 0.02 Mask loss: 0.16895 RPN box loss: 0.04899 RPN score loss: 0.0227 RPN total loss: 0.07168 Total loss: 1.48153 timestamp: 1655027413.3540194 iteration: 24325 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17759 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.2407 L1 loss: 0.0000e+00 L2 loss: 0.95389 Learning rate: 0.02 Mask loss: 0.11743 RPN box loss: 0.04546 RPN score loss: 0.04351 RPN total loss: 0.08897 Total loss: 1.401 timestamp: 1655027416.64591 iteration: 24330 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16392 FastRCNN class loss: 0.08749 FastRCNN total loss: 0.25141 L1 loss: 0.0000e+00 L2 loss: 0.95374 Learning rate: 0.02 Mask loss: 0.18738 RPN box loss: 0.03868 RPN score loss: 0.00229 RPN total loss: 0.04097 Total loss: 1.43349 timestamp: 1655027419.9613338 iteration: 24335 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13672 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.21566 L1 loss: 0.0000e+00 L2 loss: 0.95356 Learning rate: 0.02 Mask loss: 0.1473 RPN box loss: 0.04134 RPN score loss: 0.00711 RPN total loss: 0.04845 Total loss: 1.36496 timestamp: 1655027423.2240505 iteration: 24340 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17671 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.24124 L1 loss: 0.0000e+00 L2 loss: 0.95342 Learning rate: 0.02 Mask loss: 0.12765 RPN box loss: 0.01414 RPN score loss: 0.00468 RPN total loss: 0.01882 Total loss: 1.34113 timestamp: 1655027426.683135 iteration: 24345 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12707 FastRCNN class loss: 0.09262 FastRCNN total loss: 0.21969 L1 loss: 0.0000e+00 L2 loss: 0.95328 Learning rate: 0.02 Mask loss: 0.10464 RPN box loss: 0.03181 RPN score loss: 0.00239 RPN total loss: 0.0342 Total loss: 1.3118 timestamp: 1655027429.9156585 iteration: 24350 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23601 FastRCNN class loss: 0.14967 FastRCNN total loss: 0.38568 L1 loss: 0.0000e+00 L2 loss: 0.95314 Learning rate: 0.02 Mask loss: 0.25131 RPN box loss: 0.04003 RPN score loss: 0.01397 RPN total loss: 0.054 Total loss: 1.64413 timestamp: 1655027433.3513155 iteration: 24355 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10817 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.18622 L1 loss: 0.0000e+00 L2 loss: 0.953 Learning rate: 0.02 Mask loss: 0.17688 RPN box loss: 0.03359 RPN score loss: 0.00272 RPN total loss: 0.03631 Total loss: 1.35241 timestamp: 1655027436.6138914 iteration: 24360 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11881 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.19666 L1 loss: 0.0000e+00 L2 loss: 0.95286 Learning rate: 0.02 Mask loss: 0.1168 RPN box loss: 0.02738 RPN score loss: 0.00345 RPN total loss: 0.03083 Total loss: 1.29715 timestamp: 1655027439.9604099 iteration: 24365 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15234 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.21613 L1 loss: 0.0000e+00 L2 loss: 0.9527 Learning rate: 0.02 Mask loss: 0.13643 RPN box loss: 0.03056 RPN score loss: 0.00549 RPN total loss: 0.03605 Total loss: 1.34132 timestamp: 1655027443.484468 iteration: 24370 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13401 FastRCNN class loss: 0.13848 FastRCNN total loss: 0.2725 L1 loss: 0.0000e+00 L2 loss: 0.95254 Learning rate: 0.02 Mask loss: 0.21318 RPN box loss: 0.01427 RPN score loss: 0.00292 RPN total loss: 0.01719 Total loss: 1.45541 timestamp: 1655027446.808797 iteration: 24375 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18624 FastRCNN class loss: 0.0986 FastRCNN total loss: 0.28483 L1 loss: 0.0000e+00 L2 loss: 0.95237 Learning rate: 0.02 Mask loss: 0.20369 RPN box loss: 0.04107 RPN score loss: 0.01018 RPN total loss: 0.05125 Total loss: 1.49214 timestamp: 1655027450.3217397 iteration: 24380 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16382 FastRCNN class loss: 0.08496 FastRCNN total loss: 0.24878 L1 loss: 0.0000e+00 L2 loss: 0.95223 Learning rate: 0.02 Mask loss: 0.15505 RPN box loss: 0.06249 RPN score loss: 0.01072 RPN total loss: 0.07321 Total loss: 1.42927 timestamp: 1655027453.6803956 iteration: 24385 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1656 FastRCNN class loss: 0.08493 FastRCNN total loss: 0.25053 L1 loss: 0.0000e+00 L2 loss: 0.95207 Learning rate: 0.02 Mask loss: 0.17782 RPN box loss: 0.03165 RPN score loss: 0.00527 RPN total loss: 0.03692 Total loss: 1.41734 timestamp: 1655027457.1356168 iteration: 24390 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12081 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.19196 L1 loss: 0.0000e+00 L2 loss: 0.9519 Learning rate: 0.02 Mask loss: 0.12707 RPN box loss: 0.02893 RPN score loss: 0.00505 RPN total loss: 0.03398 Total loss: 1.30491 timestamp: 1655027460.421864 iteration: 24395 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16757 FastRCNN class loss: 0.13373 FastRCNN total loss: 0.3013 L1 loss: 0.0000e+00 L2 loss: 0.95178 Learning rate: 0.02 Mask loss: 0.22168 RPN box loss: 0.03096 RPN score loss: 0.01204 RPN total loss: 0.043 Total loss: 1.51775 timestamp: 1655027463.8796704 iteration: 24400 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1277 FastRCNN class loss: 0.12498 FastRCNN total loss: 0.25268 L1 loss: 0.0000e+00 L2 loss: 0.95164 Learning rate: 0.02 Mask loss: 0.14191 RPN box loss: 0.04635 RPN score loss: 0.01256 RPN total loss: 0.05891 Total loss: 1.40513 timestamp: 1655027467.291526 iteration: 24405 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12622 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.19372 L1 loss: 0.0000e+00 L2 loss: 0.95151 Learning rate: 0.02 Mask loss: 0.3536 RPN box loss: 0.03654 RPN score loss: 0.00408 RPN total loss: 0.04063 Total loss: 1.53947 timestamp: 1655027470.6013324 iteration: 24410 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19274 FastRCNN class loss: 0.12416 FastRCNN total loss: 0.3169 L1 loss: 0.0000e+00 L2 loss: 0.95136 Learning rate: 0.02 Mask loss: 0.19995 RPN box loss: 0.04633 RPN score loss: 0.00993 RPN total loss: 0.05627 Total loss: 1.52447 timestamp: 1655027473.9379816 iteration: 24415 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16253 FastRCNN class loss: 0.10757 FastRCNN total loss: 0.2701 L1 loss: 0.0000e+00 L2 loss: 0.95118 Learning rate: 0.02 Mask loss: 0.19918 RPN box loss: 0.05179 RPN score loss: 0.01715 RPN total loss: 0.06893 Total loss: 1.4894 timestamp: 1655027477.2431014 iteration: 24420 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10055 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.17525 L1 loss: 0.0000e+00 L2 loss: 0.95105 Learning rate: 0.02 Mask loss: 0.14261 RPN box loss: 0.01795 RPN score loss: 0.0014 RPN total loss: 0.01935 Total loss: 1.28826 timestamp: 1655027480.6688216 iteration: 24425 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.09224 FastRCNN total loss: 0.2275 L1 loss: 0.0000e+00 L2 loss: 0.95089 Learning rate: 0.02 Mask loss: 0.15495 RPN box loss: 0.02701 RPN score loss: 0.01798 RPN total loss: 0.04499 Total loss: 1.37833 timestamp: 1655027483.9661682 iteration: 24430 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24272 FastRCNN class loss: 0.07702 FastRCNN total loss: 0.31975 L1 loss: 0.0000e+00 L2 loss: 0.95074 Learning rate: 0.02 Mask loss: 0.13303 RPN box loss: 0.02149 RPN score loss: 0.01 RPN total loss: 0.03148 Total loss: 1.435 timestamp: 1655027487.4893904 iteration: 24435 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20544 FastRCNN class loss: 0.09373 FastRCNN total loss: 0.29917 L1 loss: 0.0000e+00 L2 loss: 0.95059 Learning rate: 0.02 Mask loss: 0.17637 RPN box loss: 0.04673 RPN score loss: 0.01785 RPN total loss: 0.06457 Total loss: 1.4907 timestamp: 1655027490.9566598 iteration: 24440 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13939 FastRCNN class loss: 0.10196 FastRCNN total loss: 0.24135 L1 loss: 0.0000e+00 L2 loss: 0.95042 Learning rate: 0.02 Mask loss: 0.18783 RPN box loss: 0.05077 RPN score loss: 0.00532 RPN total loss: 0.05609 Total loss: 1.43569 timestamp: 1655027494.2104988 iteration: 24445 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14602 FastRCNN class loss: 0.10174 FastRCNN total loss: 0.24775 L1 loss: 0.0000e+00 L2 loss: 0.95026 Learning rate: 0.02 Mask loss: 0.18435 RPN box loss: 0.04753 RPN score loss: 0.01199 RPN total loss: 0.05952 Total loss: 1.44189 timestamp: 1655027497.6561363 iteration: 24450 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13405 FastRCNN class loss: 0.15697 FastRCNN total loss: 0.29102 L1 loss: 0.0000e+00 L2 loss: 0.95011 Learning rate: 0.02 Mask loss: 0.18271 RPN box loss: 0.04821 RPN score loss: 0.0183 RPN total loss: 0.06652 Total loss: 1.49036 timestamp: 1655027500.9606361 iteration: 24455 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13582 FastRCNN class loss: 0.06003 FastRCNN total loss: 0.19585 L1 loss: 0.0000e+00 L2 loss: 0.94995 Learning rate: 0.02 Mask loss: 0.21033 RPN box loss: 0.04919 RPN score loss: 0.01329 RPN total loss: 0.06248 Total loss: 1.41861 timestamp: 1655027504.2860413 iteration: 24460 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20213 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.29202 L1 loss: 0.0000e+00 L2 loss: 0.94981 Learning rate: 0.02 Mask loss: 0.17052 RPN box loss: 0.01957 RPN score loss: 0.00466 RPN total loss: 0.02423 Total loss: 1.43658 timestamp: 1655027507.5321093 iteration: 24465 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1226 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.18713 L1 loss: 0.0000e+00 L2 loss: 0.94966 Learning rate: 0.02 Mask loss: 0.13556 RPN box loss: 0.0775 RPN score loss: 0.00471 RPN total loss: 0.0822 Total loss: 1.35456 timestamp: 1655027510.8997943 iteration: 24470 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19097 FastRCNN class loss: 0.15989 FastRCNN total loss: 0.35086 L1 loss: 0.0000e+00 L2 loss: 0.9495 Learning rate: 0.02 Mask loss: 0.23184 RPN box loss: 0.01656 RPN score loss: 0.00807 RPN total loss: 0.02464 Total loss: 1.55684 timestamp: 1655027514.2145143 iteration: 24475 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16813 FastRCNN class loss: 0.13343 FastRCNN total loss: 0.30156 L1 loss: 0.0000e+00 L2 loss: 0.94934 Learning rate: 0.02 Mask loss: 0.18026 RPN box loss: 0.03306 RPN score loss: 0.01216 RPN total loss: 0.04522 Total loss: 1.47638 timestamp: 1655027517.5139935 iteration: 24480 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19003 FastRCNN class loss: 0.11775 FastRCNN total loss: 0.30778 L1 loss: 0.0000e+00 L2 loss: 0.94918 Learning rate: 0.02 Mask loss: 0.19617 RPN box loss: 0.0349 RPN score loss: 0.01174 RPN total loss: 0.04664 Total loss: 1.49978 timestamp: 1655027520.9309468 iteration: 24485 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06338 FastRCNN class loss: 0.04528 FastRCNN total loss: 0.10866 L1 loss: 0.0000e+00 L2 loss: 0.94903 Learning rate: 0.02 Mask loss: 0.08849 RPN box loss: 0.02461 RPN score loss: 0.00382 RPN total loss: 0.02843 Total loss: 1.1746 timestamp: 1655027524.1648793 iteration: 24490 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06666 FastRCNN class loss: 0.06066 FastRCNN total loss: 0.12732 L1 loss: 0.0000e+00 L2 loss: 0.94889 Learning rate: 0.02 Mask loss: 0.08761 RPN box loss: 0.0768 RPN score loss: 0.00377 RPN total loss: 0.08057 Total loss: 1.24439 timestamp: 1655027527.4687192 iteration: 24495 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12416 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.17209 L1 loss: 0.0000e+00 L2 loss: 0.94874 Learning rate: 0.02 Mask loss: 0.13259 RPN box loss: 0.06178 RPN score loss: 0.00708 RPN total loss: 0.06886 Total loss: 1.32227 timestamp: 1655027530.7918496 iteration: 24500 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11318 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.18402 L1 loss: 0.0000e+00 L2 loss: 0.94858 Learning rate: 0.02 Mask loss: 0.12953 RPN box loss: 0.04683 RPN score loss: 0.00642 RPN total loss: 0.05325 Total loss: 1.31538 timestamp: 1655027534.1417367 iteration: 24505 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18753 FastRCNN class loss: 0.14125 FastRCNN total loss: 0.32877 L1 loss: 0.0000e+00 L2 loss: 0.94842 Learning rate: 0.02 Mask loss: 0.21446 RPN box loss: 0.01818 RPN score loss: 0.00291 RPN total loss: 0.0211 Total loss: 1.51275 timestamp: 1655027537.4646835 iteration: 24510 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19841 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.27374 L1 loss: 0.0000e+00 L2 loss: 0.94826 Learning rate: 0.02 Mask loss: 0.2576 RPN box loss: 0.01816 RPN score loss: 0.00194 RPN total loss: 0.0201 Total loss: 1.4997 timestamp: 1655027540.9022086 iteration: 24515 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18022 FastRCNN class loss: 0.1238 FastRCNN total loss: 0.30401 L1 loss: 0.0000e+00 L2 loss: 0.9481 Learning rate: 0.02 Mask loss: 0.23125 RPN box loss: 0.04958 RPN score loss: 0.01172 RPN total loss: 0.06129 Total loss: 1.54465 timestamp: 1655027544.2433605 iteration: 24520 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19752 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.27217 L1 loss: 0.0000e+00 L2 loss: 0.94794 Learning rate: 0.02 Mask loss: 0.15296 RPN box loss: 0.04931 RPN score loss: 0.0136 RPN total loss: 0.06291 Total loss: 1.43598 timestamp: 1655027547.6524553 iteration: 24525 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15011 FastRCNN class loss: 0.11897 FastRCNN total loss: 0.26907 L1 loss: 0.0000e+00 L2 loss: 0.94779 Learning rate: 0.02 Mask loss: 0.19214 RPN box loss: 0.02998 RPN score loss: 0.00277 RPN total loss: 0.03275 Total loss: 1.44175 timestamp: 1655027551.0011947 iteration: 24530 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15726 FastRCNN class loss: 0.04967 FastRCNN total loss: 0.20693 L1 loss: 0.0000e+00 L2 loss: 0.94765 Learning rate: 0.02 Mask loss: 0.08523 RPN box loss: 0.01012 RPN score loss: 0.00297 RPN total loss: 0.01309 Total loss: 1.2529 timestamp: 1655027554.2669432 iteration: 24535 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1874 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.27799 L1 loss: 0.0000e+00 L2 loss: 0.94749 Learning rate: 0.02 Mask loss: 0.16669 RPN box loss: 0.03502 RPN score loss: 0.00295 RPN total loss: 0.03798 Total loss: 1.43014 timestamp: 1655027557.6404135 iteration: 24540 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17459 FastRCNN class loss: 0.13519 FastRCNN total loss: 0.30978 L1 loss: 0.0000e+00 L2 loss: 0.94734 Learning rate: 0.02 Mask loss: 0.23324 RPN box loss: 0.05235 RPN score loss: 0.0338 RPN total loss: 0.08615 Total loss: 1.57651 timestamp: 1655027560.9116232 iteration: 24545 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14518 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.24041 L1 loss: 0.0000e+00 L2 loss: 0.94719 Learning rate: 0.02 Mask loss: 0.14329 RPN box loss: 0.02694 RPN score loss: 0.00982 RPN total loss: 0.03677 Total loss: 1.36766 timestamp: 1655027564.2937512 iteration: 24550 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15214 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.2099 L1 loss: 0.0000e+00 L2 loss: 0.94703 Learning rate: 0.02 Mask loss: 0.15381 RPN box loss: 0.00496 RPN score loss: 0.0058 RPN total loss: 0.01076 Total loss: 1.3215 timestamp: 1655027567.499373 iteration: 24555 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.11213 FastRCNN total loss: 0.22294 L1 loss: 0.0000e+00 L2 loss: 0.94689 Learning rate: 0.02 Mask loss: 0.14035 RPN box loss: 0.05129 RPN score loss: 0.00661 RPN total loss: 0.0579 Total loss: 1.36809 timestamp: 1655027570.7829912 iteration: 24560 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22383 FastRCNN class loss: 0.13692 FastRCNN total loss: 0.36075 L1 loss: 0.0000e+00 L2 loss: 0.94676 Learning rate: 0.02 Mask loss: 0.22943 RPN box loss: 0.08256 RPN score loss: 0.01047 RPN total loss: 0.09302 Total loss: 1.62996 timestamp: 1655027574.054407 iteration: 24565 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.13206 FastRCNN total loss: 0.23871 L1 loss: 0.0000e+00 L2 loss: 0.94661 Learning rate: 0.02 Mask loss: 0.20901 RPN box loss: 0.0278 RPN score loss: 0.01611 RPN total loss: 0.04392 Total loss: 1.43824 timestamp: 1655027577.4526057 iteration: 24570 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13565 FastRCNN class loss: 0.05725 FastRCNN total loss: 0.1929 L1 loss: 0.0000e+00 L2 loss: 0.94645 Learning rate: 0.02 Mask loss: 0.10319 RPN box loss: 0.08359 RPN score loss: 0.00985 RPN total loss: 0.09343 Total loss: 1.33598 timestamp: 1655027580.7858012 iteration: 24575 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13409 FastRCNN class loss: 0.07811 FastRCNN total loss: 0.21221 L1 loss: 0.0000e+00 L2 loss: 0.9463 Learning rate: 0.02 Mask loss: 0.16655 RPN box loss: 0.03545 RPN score loss: 0.00916 RPN total loss: 0.04461 Total loss: 1.36966 timestamp: 1655027584.1234164 iteration: 24580 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11832 FastRCNN class loss: 0.07874 FastRCNN total loss: 0.19707 L1 loss: 0.0000e+00 L2 loss: 0.94615 Learning rate: 0.02 Mask loss: 0.14027 RPN box loss: 0.03534 RPN score loss: 0.00348 RPN total loss: 0.03881 Total loss: 1.3223 timestamp: 1655027587.5197246 iteration: 24585 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07221 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.12508 L1 loss: 0.0000e+00 L2 loss: 0.94599 Learning rate: 0.02 Mask loss: 0.10545 RPN box loss: 0.00255 RPN score loss: 0.00285 RPN total loss: 0.00541 Total loss: 1.18193 timestamp: 1655027590.7727416 iteration: 24590 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0747 FastRCNN class loss: 0.04395 FastRCNN total loss: 0.11866 L1 loss: 0.0000e+00 L2 loss: 0.94585 Learning rate: 0.02 Mask loss: 0.10059 RPN box loss: 0.00377 RPN score loss: 0.00125 RPN total loss: 0.00502 Total loss: 1.17011 timestamp: 1655027594.1785553 iteration: 24595 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15035 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.24732 L1 loss: 0.0000e+00 L2 loss: 0.94569 Learning rate: 0.02 Mask loss: 0.16687 RPN box loss: 0.01147 RPN score loss: 0.00318 RPN total loss: 0.01466 Total loss: 1.37454 timestamp: 1655027597.4535573 iteration: 24600 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13221 FastRCNN class loss: 0.07548 FastRCNN total loss: 0.20769 L1 loss: 0.0000e+00 L2 loss: 0.94552 Learning rate: 0.02 Mask loss: 0.14101 RPN box loss: 0.00868 RPN score loss: 0.00752 RPN total loss: 0.0162 Total loss: 1.31042 timestamp: 1655027600.864318 iteration: 24605 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15014 FastRCNN class loss: 0.10303 FastRCNN total loss: 0.25318 L1 loss: 0.0000e+00 L2 loss: 0.94539 Learning rate: 0.02 Mask loss: 0.17552 RPN box loss: 0.04367 RPN score loss: 0.01072 RPN total loss: 0.05439 Total loss: 1.42848 timestamp: 1655027604.0789027 iteration: 24610 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15128 FastRCNN class loss: 0.1001 FastRCNN total loss: 0.25138 L1 loss: 0.0000e+00 L2 loss: 0.94526 Learning rate: 0.02 Mask loss: 0.1478 RPN box loss: 0.01163 RPN score loss: 0.01654 RPN total loss: 0.02817 Total loss: 1.37261 timestamp: 1655027607.4411523 iteration: 24615 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12634 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.20735 L1 loss: 0.0000e+00 L2 loss: 0.94509 Learning rate: 0.02 Mask loss: 0.17445 RPN box loss: 0.06087 RPN score loss: 0.01196 RPN total loss: 0.07283 Total loss: 1.39973 timestamp: 1655027610.8917801 iteration: 24620 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14399 FastRCNN class loss: 0.10367 FastRCNN total loss: 0.24767 L1 loss: 0.0000e+00 L2 loss: 0.9449 Learning rate: 0.02 Mask loss: 0.19242 RPN box loss: 0.03715 RPN score loss: 0.00657 RPN total loss: 0.04372 Total loss: 1.42871 timestamp: 1655027614.1839328 iteration: 24625 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2045 FastRCNN class loss: 0.13442 FastRCNN total loss: 0.33892 L1 loss: 0.0000e+00 L2 loss: 0.94477 Learning rate: 0.02 Mask loss: 0.16744 RPN box loss: 0.048 RPN score loss: 0.00487 RPN total loss: 0.05287 Total loss: 1.504 timestamp: 1655027617.5547225 iteration: 24630 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18029 FastRCNN class loss: 0.10211 FastRCNN total loss: 0.2824 L1 loss: 0.0000e+00 L2 loss: 0.94463 Learning rate: 0.02 Mask loss: 0.20292 RPN box loss: 0.04031 RPN score loss: 0.00782 RPN total loss: 0.04813 Total loss: 1.47809 timestamp: 1655027620.8241148 iteration: 24635 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.168 L1 loss: 0.0000e+00 L2 loss: 0.94449 Learning rate: 0.02 Mask loss: 0.1983 RPN box loss: 0.03172 RPN score loss: 0.00833 RPN total loss: 0.04004 Total loss: 1.35082 timestamp: 1655027624.2087185 iteration: 24640 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15671 FastRCNN class loss: 0.08878 FastRCNN total loss: 0.24549 L1 loss: 0.0000e+00 L2 loss: 0.94436 Learning rate: 0.02 Mask loss: 0.15911 RPN box loss: 0.03563 RPN score loss: 0.00878 RPN total loss: 0.04441 Total loss: 1.39336 timestamp: 1655027627.5125885 iteration: 24645 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10641 FastRCNN class loss: 0.11953 FastRCNN total loss: 0.22594 L1 loss: 0.0000e+00 L2 loss: 0.94419 Learning rate: 0.02 Mask loss: 0.13467 RPN box loss: 0.02301 RPN score loss: 0.00454 RPN total loss: 0.02754 Total loss: 1.33235 timestamp: 1655027630.8246691 iteration: 24650 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14265 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.22302 L1 loss: 0.0000e+00 L2 loss: 0.94403 Learning rate: 0.02 Mask loss: 0.15334 RPN box loss: 0.04692 RPN score loss: 0.00461 RPN total loss: 0.05153 Total loss: 1.37192 timestamp: 1655027634.0948365 iteration: 24655 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13103 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.20081 L1 loss: 0.0000e+00 L2 loss: 0.94389 Learning rate: 0.02 Mask loss: 0.15495 RPN box loss: 0.01091 RPN score loss: 0.00219 RPN total loss: 0.0131 Total loss: 1.31275 timestamp: 1655027637.4887495 iteration: 24660 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15321 FastRCNN class loss: 0.13213 FastRCNN total loss: 0.28534 L1 loss: 0.0000e+00 L2 loss: 0.94375 Learning rate: 0.02 Mask loss: 0.11775 RPN box loss: 0.05342 RPN score loss: 0.00927 RPN total loss: 0.06269 Total loss: 1.40953 timestamp: 1655027640.8385375 iteration: 24665 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.162 FastRCNN class loss: 0.14558 FastRCNN total loss: 0.30758 L1 loss: 0.0000e+00 L2 loss: 0.94362 Learning rate: 0.02 Mask loss: 0.199 RPN box loss: 0.06312 RPN score loss: 0.01082 RPN total loss: 0.07393 Total loss: 1.52412 timestamp: 1655027644.0875907 iteration: 24670 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06877 FastRCNN class loss: 0.03278 FastRCNN total loss: 0.10155 L1 loss: 0.0000e+00 L2 loss: 0.94347 Learning rate: 0.02 Mask loss: 0.11281 RPN box loss: 0.02833 RPN score loss: 0.00207 RPN total loss: 0.03039 Total loss: 1.18822 timestamp: 1655027647.4200094 iteration: 24675 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.165 FastRCNN class loss: 0.13658 FastRCNN total loss: 0.30158 L1 loss: 0.0000e+00 L2 loss: 0.94332 Learning rate: 0.02 Mask loss: 0.16362 RPN box loss: 0.0612 RPN score loss: 0.00556 RPN total loss: 0.06676 Total loss: 1.47527 timestamp: 1655027650.649829 iteration: 24680 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23898 FastRCNN class loss: 0.11329 FastRCNN total loss: 0.35227 L1 loss: 0.0000e+00 L2 loss: 0.94316 Learning rate: 0.02 Mask loss: 0.18159 RPN box loss: 0.04635 RPN score loss: 0.01161 RPN total loss: 0.05796 Total loss: 1.53498 timestamp: 1655027654.0830953 iteration: 24685 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13226 FastRCNN class loss: 0.11053 FastRCNN total loss: 0.24279 L1 loss: 0.0000e+00 L2 loss: 0.943 Learning rate: 0.02 Mask loss: 0.23086 RPN box loss: 0.02332 RPN score loss: 0.01407 RPN total loss: 0.03738 Total loss: 1.45404 timestamp: 1655027657.4298797 iteration: 24690 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09359 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.1559 L1 loss: 0.0000e+00 L2 loss: 0.94285 Learning rate: 0.02 Mask loss: 0.13459 RPN box loss: 0.02538 RPN score loss: 0.00545 RPN total loss: 0.03083 Total loss: 1.26416 timestamp: 1655027660.8048234 iteration: 24695 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11997 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.21184 L1 loss: 0.0000e+00 L2 loss: 0.9427 Learning rate: 0.02 Mask loss: 0.1443 RPN box loss: 0.0255 RPN score loss: 0.00704 RPN total loss: 0.03254 Total loss: 1.33139 timestamp: 1655027664.0628188 iteration: 24700 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22547 FastRCNN class loss: 0.16336 FastRCNN total loss: 0.38883 L1 loss: 0.0000e+00 L2 loss: 0.94256 Learning rate: 0.02 Mask loss: 0.2314 RPN box loss: 0.04461 RPN score loss: 0.02165 RPN total loss: 0.06626 Total loss: 1.62905 timestamp: 1655027667.4886432 iteration: 24705 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0999 FastRCNN class loss: 0.05364 FastRCNN total loss: 0.15354 L1 loss: 0.0000e+00 L2 loss: 0.94241 Learning rate: 0.02 Mask loss: 0.153 RPN box loss: 0.01901 RPN score loss: 0.0025 RPN total loss: 0.02152 Total loss: 1.27046 timestamp: 1655027670.8641596 iteration: 24710 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14896 FastRCNN class loss: 0.0942 FastRCNN total loss: 0.24316 L1 loss: 0.0000e+00 L2 loss: 0.94223 Learning rate: 0.02 Mask loss: 0.15452 RPN box loss: 0.06417 RPN score loss: 0.02764 RPN total loss: 0.09181 Total loss: 1.43173 timestamp: 1655027674.1212447 iteration: 24715 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09673 FastRCNN class loss: 0.05336 FastRCNN total loss: 0.15009 L1 loss: 0.0000e+00 L2 loss: 0.94208 Learning rate: 0.02 Mask loss: 0.16477 RPN box loss: 0.03166 RPN score loss: 0.00387 RPN total loss: 0.03554 Total loss: 1.29248 timestamp: 1655027677.4909282 iteration: 24720 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15514 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.22087 L1 loss: 0.0000e+00 L2 loss: 0.94193 Learning rate: 0.02 Mask loss: 0.1592 RPN box loss: 0.04741 RPN score loss: 0.01519 RPN total loss: 0.0626 Total loss: 1.3846 timestamp: 1655027680.771269 iteration: 24725 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19797 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.28009 L1 loss: 0.0000e+00 L2 loss: 0.94178 Learning rate: 0.02 Mask loss: 0.1428 RPN box loss: 0.03201 RPN score loss: 0.00574 RPN total loss: 0.03775 Total loss: 1.40242 timestamp: 1655027684.2102418 iteration: 24730 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1779 FastRCNN class loss: 0.14442 FastRCNN total loss: 0.32232 L1 loss: 0.0000e+00 L2 loss: 0.94163 Learning rate: 0.02 Mask loss: 0.20671 RPN box loss: 0.02514 RPN score loss: 0.02188 RPN total loss: 0.04701 Total loss: 1.51768 timestamp: 1655027687.511367 iteration: 24735 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0838 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.14181 L1 loss: 0.0000e+00 L2 loss: 0.94145 Learning rate: 0.02 Mask loss: 0.16487 RPN box loss: 0.01369 RPN score loss: 0.00174 RPN total loss: 0.01543 Total loss: 1.26356 timestamp: 1655027690.9014487 iteration: 24740 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18512 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.2736 L1 loss: 0.0000e+00 L2 loss: 0.94129 Learning rate: 0.02 Mask loss: 0.13963 RPN box loss: 0.03747 RPN score loss: 0.0066 RPN total loss: 0.04407 Total loss: 1.39858 timestamp: 1655027694.1875873 iteration: 24745 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13748 FastRCNN class loss: 0.09007 FastRCNN total loss: 0.22755 L1 loss: 0.0000e+00 L2 loss: 0.94114 Learning rate: 0.02 Mask loss: 0.17082 RPN box loss: 0.02192 RPN score loss: 0.00395 RPN total loss: 0.02588 Total loss: 1.36538 timestamp: 1655027697.5597289 iteration: 24750 throughput: 24.0 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15727 FastRCNN class loss: 0.09114 FastRCNN total loss: 0.24841 L1 loss: 0.0000e+00 L2 loss: 0.941 Learning rate: 0.02 Mask loss: 0.12449 RPN box loss: 0.03798 RPN score loss: 0.00356 RPN total loss: 0.04154 Total loss: 1.35543 timestamp: 1655027700.9841342 iteration: 24755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11927 FastRCNN class loss: 0.10699 FastRCNN total loss: 0.22627 L1 loss: 0.0000e+00 L2 loss: 0.94083 Learning rate: 0.02 Mask loss: 0.27978 RPN box loss: 0.02775 RPN score loss: 0.01715 RPN total loss: 0.04489 Total loss: 1.49177 timestamp: 1655027704.2829058 iteration: 24760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.156 FastRCNN class loss: 0.10344 FastRCNN total loss: 0.25944 L1 loss: 0.0000e+00 L2 loss: 0.94071 Learning rate: 0.02 Mask loss: 0.22817 RPN box loss: 0.02727 RPN score loss: 0.00736 RPN total loss: 0.03463 Total loss: 1.46295 timestamp: 1655027707.7047946 iteration: 24765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09493 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.16604 L1 loss: 0.0000e+00 L2 loss: 0.94057 Learning rate: 0.02 Mask loss: 0.11499 RPN box loss: 0.00683 RPN score loss: 0.01069 RPN total loss: 0.01752 Total loss: 1.23911 timestamp: 1655027711.002204 iteration: 24770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17766 FastRCNN class loss: 0.15998 FastRCNN total loss: 0.33764 L1 loss: 0.0000e+00 L2 loss: 0.94041 Learning rate: 0.02 Mask loss: 0.2262 RPN box loss: 0.04815 RPN score loss: 0.01263 RPN total loss: 0.06077 Total loss: 1.56502 timestamp: 1655027714.2361255 iteration: 24775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15845 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.22726 L1 loss: 0.0000e+00 L2 loss: 0.94024 Learning rate: 0.02 Mask loss: 0.26483 RPN box loss: 0.06547 RPN score loss: 0.00764 RPN total loss: 0.07311 Total loss: 1.50545 timestamp: 1655027717.5949924 iteration: 24780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13505 FastRCNN class loss: 0.10522 FastRCNN total loss: 0.24026 L1 loss: 0.0000e+00 L2 loss: 0.94006 Learning rate: 0.02 Mask loss: 0.15234 RPN box loss: 0.02016 RPN score loss: 0.0099 RPN total loss: 0.03006 Total loss: 1.36272 timestamp: 1655027720.930715 iteration: 24785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14561 FastRCNN class loss: 0.07915 FastRCNN total loss: 0.22476 L1 loss: 0.0000e+00 L2 loss: 0.93993 Learning rate: 0.02 Mask loss: 0.15554 RPN box loss: 0.08537 RPN score loss: 0.00578 RPN total loss: 0.09115 Total loss: 1.41138 timestamp: 1655027724.2362275 iteration: 24790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12815 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.18603 L1 loss: 0.0000e+00 L2 loss: 0.93978 Learning rate: 0.02 Mask loss: 0.18018 RPN box loss: 0.02216 RPN score loss: 0.00491 RPN total loss: 0.02707 Total loss: 1.33306 timestamp: 1655027727.5941405 iteration: 24795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15129 FastRCNN class loss: 0.08203 FastRCNN total loss: 0.23332 L1 loss: 0.0000e+00 L2 loss: 0.93963 Learning rate: 0.02 Mask loss: 0.22765 RPN box loss: 0.02804 RPN score loss: 0.00475 RPN total loss: 0.03279 Total loss: 1.4334 timestamp: 1655027730.996403 iteration: 24800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18613 FastRCNN class loss: 0.1194 FastRCNN total loss: 0.30553 L1 loss: 0.0000e+00 L2 loss: 0.93949 Learning rate: 0.02 Mask loss: 0.18638 RPN box loss: 0.03095 RPN score loss: 0.01214 RPN total loss: 0.04309 Total loss: 1.47449 timestamp: 1655027734.3370264 iteration: 24805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16736 FastRCNN class loss: 0.11289 FastRCNN total loss: 0.28025 L1 loss: 0.0000e+00 L2 loss: 0.93934 Learning rate: 0.02 Mask loss: 0.16956 RPN box loss: 0.04762 RPN score loss: 0.00524 RPN total loss: 0.05286 Total loss: 1.44201 timestamp: 1655027737.8110726 iteration: 24810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18761 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.27634 L1 loss: 0.0000e+00 L2 loss: 0.93917 Learning rate: 0.02 Mask loss: 0.13003 RPN box loss: 0.0267 RPN score loss: 0.00584 RPN total loss: 0.03254 Total loss: 1.37808 timestamp: 1655027741.091239 iteration: 24815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08367 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.14988 L1 loss: 0.0000e+00 L2 loss: 0.93904 Learning rate: 0.02 Mask loss: 0.13578 RPN box loss: 0.05021 RPN score loss: 0.01098 RPN total loss: 0.06119 Total loss: 1.28589 timestamp: 1655027744.3759668 iteration: 24820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05295 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.0961 L1 loss: 0.0000e+00 L2 loss: 0.93892 Learning rate: 0.02 Mask loss: 0.10131 RPN box loss: 0.02146 RPN score loss: 0.00526 RPN total loss: 0.02672 Total loss: 1.16305 timestamp: 1655027747.6467645 iteration: 24825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18321 FastRCNN class loss: 0.10964 FastRCNN total loss: 0.29285 L1 loss: 0.0000e+00 L2 loss: 0.93876 Learning rate: 0.02 Mask loss: 0.25492 RPN box loss: 0.08906 RPN score loss: 0.01849 RPN total loss: 0.10755 Total loss: 1.5941 timestamp: 1655027750.9679685 iteration: 24830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20667 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.26191 L1 loss: 0.0000e+00 L2 loss: 0.93861 Learning rate: 0.02 Mask loss: 0.13329 RPN box loss: 0.00961 RPN score loss: 0.00673 RPN total loss: 0.01634 Total loss: 1.35015 timestamp: 1655027754.2670434 iteration: 24835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13988 FastRCNN class loss: 0.08959 FastRCNN total loss: 0.22948 L1 loss: 0.0000e+00 L2 loss: 0.93846 Learning rate: 0.02 Mask loss: 0.15397 RPN box loss: 0.04791 RPN score loss: 0.00978 RPN total loss: 0.05769 Total loss: 1.3796 timestamp: 1655027757.655603 iteration: 24840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.04334 FastRCNN total loss: 0.13097 L1 loss: 0.0000e+00 L2 loss: 0.9383 Learning rate: 0.02 Mask loss: 0.13026 RPN box loss: 0.02778 RPN score loss: 0.00251 RPN total loss: 0.03029 Total loss: 1.22982 timestamp: 1655027761.0254893 iteration: 24845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09665 FastRCNN class loss: 0.03804 FastRCNN total loss: 0.13469 L1 loss: 0.0000e+00 L2 loss: 0.93814 Learning rate: 0.02 Mask loss: 0.13466 RPN box loss: 0.009 RPN score loss: 0.0043 RPN total loss: 0.0133 Total loss: 1.22079 timestamp: 1655027764.3385048 iteration: 24850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12535 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.21713 L1 loss: 0.0000e+00 L2 loss: 0.93796 Learning rate: 0.02 Mask loss: 0.12554 RPN box loss: 0.04718 RPN score loss: 0.01488 RPN total loss: 0.06206 Total loss: 1.34269 timestamp: 1655027767.6892195 iteration: 24855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.16194 L1 loss: 0.0000e+00 L2 loss: 0.93781 Learning rate: 0.02 Mask loss: 0.2285 RPN box loss: 0.02533 RPN score loss: 0.00409 RPN total loss: 0.02942 Total loss: 1.35768 timestamp: 1655027770.9922373 iteration: 24860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14515 FastRCNN class loss: 0.10173 FastRCNN total loss: 0.24688 L1 loss: 0.0000e+00 L2 loss: 0.93765 Learning rate: 0.02 Mask loss: 0.15013 RPN box loss: 0.0177 RPN score loss: 0.01335 RPN total loss: 0.03105 Total loss: 1.36572 timestamp: 1655027774.4178474 iteration: 24865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16841 FastRCNN class loss: 0.10709 FastRCNN total loss: 0.27549 L1 loss: 0.0000e+00 L2 loss: 0.93748 Learning rate: 0.02 Mask loss: 0.1902 RPN box loss: 0.02382 RPN score loss: 0.02186 RPN total loss: 0.04567 Total loss: 1.44884 timestamp: 1655027777.6815517 iteration: 24870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11384 FastRCNN class loss: 0.08575 FastRCNN total loss: 0.19959 L1 loss: 0.0000e+00 L2 loss: 0.93735 Learning rate: 0.02 Mask loss: 0.13342 RPN box loss: 0.0194 RPN score loss: 0.00575 RPN total loss: 0.02515 Total loss: 1.29551 timestamp: 1655027781.0185027 iteration: 24875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16994 FastRCNN class loss: 0.10401 FastRCNN total loss: 0.27395 L1 loss: 0.0000e+00 L2 loss: 0.93718 Learning rate: 0.02 Mask loss: 0.23353 RPN box loss: 0.03722 RPN score loss: 0.01562 RPN total loss: 0.05284 Total loss: 1.4975 timestamp: 1655027784.272417 iteration: 24880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17152 FastRCNN class loss: 0.11435 FastRCNN total loss: 0.28586 L1 loss: 0.0000e+00 L2 loss: 0.93704 Learning rate: 0.02 Mask loss: 0.27075 RPN box loss: 0.03072 RPN score loss: 0.00917 RPN total loss: 0.03989 Total loss: 1.53354 timestamp: 1655027787.65115 iteration: 24885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18456 FastRCNN class loss: 0.10037 FastRCNN total loss: 0.28493 L1 loss: 0.0000e+00 L2 loss: 0.93691 Learning rate: 0.02 Mask loss: 0.14911 RPN box loss: 0.04407 RPN score loss: 0.00369 RPN total loss: 0.04776 Total loss: 1.4187 timestamp: 1655027791.000997 iteration: 24890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14003 FastRCNN class loss: 0.06706 FastRCNN total loss: 0.2071 L1 loss: 0.0000e+00 L2 loss: 0.93672 Learning rate: 0.02 Mask loss: 0.08537 RPN box loss: 0.01328 RPN score loss: 0.00249 RPN total loss: 0.01577 Total loss: 1.24495 timestamp: 1655027794.3288124 iteration: 24895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1358 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.20495 L1 loss: 0.0000e+00 L2 loss: 0.93658 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.03045 RPN score loss: 0.00585 RPN total loss: 0.0363 Total loss: 1.3445 timestamp: 1655027797.7266347 iteration: 24900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17383 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.25509 L1 loss: 0.0000e+00 L2 loss: 0.93644 Learning rate: 0.02 Mask loss: 0.1521 RPN box loss: 0.01063 RPN score loss: 0.00771 RPN total loss: 0.01834 Total loss: 1.36196 timestamp: 1655027800.95456 iteration: 24905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13197 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.20798 L1 loss: 0.0000e+00 L2 loss: 0.93628 Learning rate: 0.02 Mask loss: 0.17031 RPN box loss: 0.0763 RPN score loss: 0.00555 RPN total loss: 0.08185 Total loss: 1.39642 timestamp: 1655027804.312747 iteration: 24910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13878 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.19016 L1 loss: 0.0000e+00 L2 loss: 0.93615 Learning rate: 0.02 Mask loss: 0.16302 RPN box loss: 0.02098 RPN score loss: 0.00229 RPN total loss: 0.02328 Total loss: 1.31261 timestamp: 1655027807.5742106 iteration: 24915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13668 FastRCNN class loss: 0.08812 FastRCNN total loss: 0.2248 L1 loss: 0.0000e+00 L2 loss: 0.93601 Learning rate: 0.02 Mask loss: 0.21176 RPN box loss: 0.04612 RPN score loss: 0.01508 RPN total loss: 0.0612 Total loss: 1.43377 timestamp: 1655027810.9135346 iteration: 24920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09808 FastRCNN class loss: 0.04624 FastRCNN total loss: 0.14433 L1 loss: 0.0000e+00 L2 loss: 0.93587 Learning rate: 0.02 Mask loss: 0.11982 RPN box loss: 0.00574 RPN score loss: 0.00145 RPN total loss: 0.00719 Total loss: 1.2072 timestamp: 1655027814.2379148 iteration: 24925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1593 FastRCNN class loss: 0.05061 FastRCNN total loss: 0.20992 L1 loss: 0.0000e+00 L2 loss: 0.93571 Learning rate: 0.02 Mask loss: 0.10253 RPN box loss: 0.01142 RPN score loss: 0.00484 RPN total loss: 0.01627 Total loss: 1.26443 timestamp: 1655027817.6152692 iteration: 24930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15395 FastRCNN class loss: 0.09725 FastRCNN total loss: 0.2512 L1 loss: 0.0000e+00 L2 loss: 0.93556 Learning rate: 0.02 Mask loss: 0.15965 RPN box loss: 0.04495 RPN score loss: 0.01313 RPN total loss: 0.05807 Total loss: 1.40448 timestamp: 1655027821.0046656 iteration: 24935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08466 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.15355 L1 loss: 0.0000e+00 L2 loss: 0.93542 Learning rate: 0.02 Mask loss: 0.14681 RPN box loss: 0.04496 RPN score loss: 0.00664 RPN total loss: 0.0516 Total loss: 1.28737 timestamp: 1655027824.265204 iteration: 24940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17104 FastRCNN class loss: 0.04905 FastRCNN total loss: 0.22009 L1 loss: 0.0000e+00 L2 loss: 0.93526 Learning rate: 0.02 Mask loss: 0.18327 RPN box loss: 0.04851 RPN score loss: 0.00233 RPN total loss: 0.05085 Total loss: 1.38947 timestamp: 1655027827.663427 iteration: 24945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11797 FastRCNN class loss: 0.1154 FastRCNN total loss: 0.23337 L1 loss: 0.0000e+00 L2 loss: 0.93514 Learning rate: 0.02 Mask loss: 0.1986 RPN box loss: 0.06556 RPN score loss: 0.01954 RPN total loss: 0.0851 Total loss: 1.4522 timestamp: 1655027830.929659 iteration: 24950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1654 FastRCNN class loss: 0.17899 FastRCNN total loss: 0.34439 L1 loss: 0.0000e+00 L2 loss: 0.93498 Learning rate: 0.02 Mask loss: 0.2522 RPN box loss: 0.08586 RPN score loss: 0.02079 RPN total loss: 0.10665 Total loss: 1.63823 timestamp: 1655027834.201303 iteration: 24955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18667 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.26896 L1 loss: 0.0000e+00 L2 loss: 0.93483 Learning rate: 0.02 Mask loss: 0.16877 RPN box loss: 0.01731 RPN score loss: 0.00323 RPN total loss: 0.02055 Total loss: 1.39311 timestamp: 1655027837.5111659 iteration: 24960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.16384 L1 loss: 0.0000e+00 L2 loss: 0.93467 Learning rate: 0.02 Mask loss: 0.17139 RPN box loss: 0.02194 RPN score loss: 0.0086 RPN total loss: 0.03054 Total loss: 1.30043 timestamp: 1655027840.8022192 iteration: 24965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14707 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.21095 L1 loss: 0.0000e+00 L2 loss: 0.9345 Learning rate: 0.02 Mask loss: 0.2338 RPN box loss: 0.0082 RPN score loss: 0.00245 RPN total loss: 0.01065 Total loss: 1.3899 timestamp: 1655027844.0969677 iteration: 24970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14735 FastRCNN class loss: 0.12044 FastRCNN total loss: 0.26779 L1 loss: 0.0000e+00 L2 loss: 0.93435 Learning rate: 0.02 Mask loss: 0.15612 RPN box loss: 0.02714 RPN score loss: 0.00559 RPN total loss: 0.03273 Total loss: 1.39099 timestamp: 1655027847.5024538 iteration: 24975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18396 FastRCNN class loss: 0.0893 FastRCNN total loss: 0.27326 L1 loss: 0.0000e+00 L2 loss: 0.93419 Learning rate: 0.02 Mask loss: 0.23548 RPN box loss: 0.07114 RPN score loss: 0.01683 RPN total loss: 0.08798 Total loss: 1.5309 timestamp: 1655027850.8479831 iteration: 24980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16695 FastRCNN class loss: 0.13475 FastRCNN total loss: 0.30169 L1 loss: 0.0000e+00 L2 loss: 0.93405 Learning rate: 0.02 Mask loss: 0.21073 RPN box loss: 0.05453 RPN score loss: 0.01131 RPN total loss: 0.06585 Total loss: 1.51232 timestamp: 1655027854.1448603 iteration: 24985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16544 FastRCNN class loss: 0.09782 FastRCNN total loss: 0.26326 L1 loss: 0.0000e+00 L2 loss: 0.93389 Learning rate: 0.02 Mask loss: 0.17002 RPN box loss: 0.05432 RPN score loss: 0.0112 RPN total loss: 0.06552 Total loss: 1.43269 timestamp: 1655027857.5618157 iteration: 24990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19765 FastRCNN class loss: 0.12252 FastRCNN total loss: 0.32017 L1 loss: 0.0000e+00 L2 loss: 0.93373 Learning rate: 0.02 Mask loss: 0.16134 RPN box loss: 0.03709 RPN score loss: 0.00652 RPN total loss: 0.04361 Total loss: 1.45886 timestamp: 1655027860.8929179 iteration: 24995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15253 FastRCNN class loss: 0.11888 FastRCNN total loss: 0.2714 L1 loss: 0.0000e+00 L2 loss: 0.93359 Learning rate: 0.02 Mask loss: 0.23081 RPN box loss: 0.02202 RPN score loss: 0.00201 RPN total loss: 0.02403 Total loss: 1.45983 timestamp: 1655027864.282084 iteration: 25000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15579 FastRCNN class loss: 0.09645 FastRCNN total loss: 0.25223 L1 loss: 0.0000e+00 L2 loss: 0.93345 Learning rate: 0.02 Mask loss: 0.20299 RPN box loss: 0.02005 RPN score loss: 0.00419 RPN total loss: 0.02423 Total loss: 1.4129 timestamp: 1655027867.526953 iteration: 25005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21107 FastRCNN class loss: 0.15138 FastRCNN total loss: 0.36245 L1 loss: 0.0000e+00 L2 loss: 0.93331 Learning rate: 0.02 Mask loss: 0.20629 RPN box loss: 0.04708 RPN score loss: 0.05223 RPN total loss: 0.09932 Total loss: 1.60137 timestamp: 1655027870.8681378 iteration: 25010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18388 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.26395 L1 loss: 0.0000e+00 L2 loss: 0.93316 Learning rate: 0.02 Mask loss: 0.17295 RPN box loss: 0.03494 RPN score loss: 0.0048 RPN total loss: 0.03975 Total loss: 1.4098 timestamp: 1655027874.215607 iteration: 25015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.11165 FastRCNN total loss: 0.26113 L1 loss: 0.0000e+00 L2 loss: 0.93301 Learning rate: 0.02 Mask loss: 0.2137 RPN box loss: 0.11622 RPN score loss: 0.01681 RPN total loss: 0.13304 Total loss: 1.54086 timestamp: 1655027877.630852 iteration: 25020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10802 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.17724 L1 loss: 0.0000e+00 L2 loss: 0.93286 Learning rate: 0.02 Mask loss: 0.10302 RPN box loss: 0.00536 RPN score loss: 0.00551 RPN total loss: 0.01087 Total loss: 1.22399 timestamp: 1655027880.9920368 iteration: 25025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16379 FastRCNN class loss: 0.10588 FastRCNN total loss: 0.26967 L1 loss: 0.0000e+00 L2 loss: 0.9327 Learning rate: 0.02 Mask loss: 0.24322 RPN box loss: 0.03517 RPN score loss: 0.01722 RPN total loss: 0.05239 Total loss: 1.49799 timestamp: 1655027884.26998 iteration: 25030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14826 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.22072 L1 loss: 0.0000e+00 L2 loss: 0.93253 Learning rate: 0.02 Mask loss: 0.13155 RPN box loss: 0.00765 RPN score loss: 0.00307 RPN total loss: 0.01072 Total loss: 1.29551 timestamp: 1655027887.622163 iteration: 25035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16006 FastRCNN class loss: 0.0588 FastRCNN total loss: 0.21886 L1 loss: 0.0000e+00 L2 loss: 0.93235 Learning rate: 0.02 Mask loss: 0.16547 RPN box loss: 0.05604 RPN score loss: 0.00654 RPN total loss: 0.06258 Total loss: 1.37926 timestamp: 1655027890.891153 iteration: 25040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18754 FastRCNN class loss: 0.13057 FastRCNN total loss: 0.31811 L1 loss: 0.0000e+00 L2 loss: 0.93223 Learning rate: 0.02 Mask loss: 0.21511 RPN box loss: 0.04261 RPN score loss: 0.04 RPN total loss: 0.08261 Total loss: 1.54806 timestamp: 1655027894.2107234 iteration: 25045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.17648 L1 loss: 0.0000e+00 L2 loss: 0.93209 Learning rate: 0.02 Mask loss: 0.09732 RPN box loss: 0.03088 RPN score loss: 0.01015 RPN total loss: 0.04103 Total loss: 1.24691 timestamp: 1655027897.4382427 iteration: 25050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.06121 FastRCNN total loss: 0.1691 L1 loss: 0.0000e+00 L2 loss: 0.93191 Learning rate: 0.02 Mask loss: 0.15558 RPN box loss: 0.01942 RPN score loss: 0.00333 RPN total loss: 0.02275 Total loss: 1.27934 timestamp: 1655027900.7942622 iteration: 25055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17776 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.25765 L1 loss: 0.0000e+00 L2 loss: 0.93177 Learning rate: 0.02 Mask loss: 0.13747 RPN box loss: 0.02009 RPN score loss: 0.00736 RPN total loss: 0.02745 Total loss: 1.35434 timestamp: 1655027904.0658355 iteration: 25060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17448 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.25414 L1 loss: 0.0000e+00 L2 loss: 0.93163 Learning rate: 0.02 Mask loss: 0.16535 RPN box loss: 0.06079 RPN score loss: 0.00851 RPN total loss: 0.0693 Total loss: 1.42041 timestamp: 1655027907.2740498 iteration: 25065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15125 FastRCNN class loss: 0.08081 FastRCNN total loss: 0.23206 L1 loss: 0.0000e+00 L2 loss: 0.93149 Learning rate: 0.02 Mask loss: 0.14786 RPN box loss: 0.03193 RPN score loss: 0.01812 RPN total loss: 0.05005 Total loss: 1.36146 timestamp: 1655027910.6697981 iteration: 25070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18338 FastRCNN class loss: 0.08988 FastRCNN total loss: 0.27327 L1 loss: 0.0000e+00 L2 loss: 0.93134 Learning rate: 0.02 Mask loss: 0.14575 RPN box loss: 0.05731 RPN score loss: 0.00659 RPN total loss: 0.0639 Total loss: 1.41425 timestamp: 1655027913.9654577 iteration: 25075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15668 FastRCNN class loss: 0.10574 FastRCNN total loss: 0.26242 L1 loss: 0.0000e+00 L2 loss: 0.93119 Learning rate: 0.02 Mask loss: 0.1458 RPN box loss: 0.01998 RPN score loss: 0.00395 RPN total loss: 0.02393 Total loss: 1.36335 timestamp: 1655027917.3376431 iteration: 25080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14049 FastRCNN class loss: 0.07281 FastRCNN total loss: 0.2133 L1 loss: 0.0000e+00 L2 loss: 0.93103 Learning rate: 0.02 Mask loss: 0.1163 RPN box loss: 0.02882 RPN score loss: 0.00932 RPN total loss: 0.03814 Total loss: 1.29877 timestamp: 1655027920.597012 iteration: 25085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11506 FastRCNN class loss: 0.11391 FastRCNN total loss: 0.22897 L1 loss: 0.0000e+00 L2 loss: 0.93087 Learning rate: 0.02 Mask loss: 0.16376 RPN box loss: 0.02299 RPN score loss: 0.00756 RPN total loss: 0.03055 Total loss: 1.35415 timestamp: 1655027923.8497999 iteration: 25090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.16695 L1 loss: 0.0000e+00 L2 loss: 0.93072 Learning rate: 0.02 Mask loss: 0.18092 RPN box loss: 0.0222 RPN score loss: 0.00366 RPN total loss: 0.02587 Total loss: 1.30445 timestamp: 1655027927.1715522 iteration: 25095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17925 FastRCNN class loss: 0.09051 FastRCNN total loss: 0.26976 L1 loss: 0.0000e+00 L2 loss: 0.9306 Learning rate: 0.02 Mask loss: 0.1713 RPN box loss: 0.05307 RPN score loss: 0.01844 RPN total loss: 0.07151 Total loss: 1.44317 timestamp: 1655027930.507864 iteration: 25100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13205 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.19886 L1 loss: 0.0000e+00 L2 loss: 0.93045 Learning rate: 0.02 Mask loss: 0.10065 RPN box loss: 0.06685 RPN score loss: 0.01528 RPN total loss: 0.08214 Total loss: 1.3121 timestamp: 1655027933.7798326 iteration: 25105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08212 FastRCNN class loss: 0.03928 FastRCNN total loss: 0.12139 L1 loss: 0.0000e+00 L2 loss: 0.93031 Learning rate: 0.02 Mask loss: 0.11845 RPN box loss: 0.01119 RPN score loss: 0.00462 RPN total loss: 0.01581 Total loss: 1.18596 timestamp: 1655027937.1796606 iteration: 25110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15112 FastRCNN class loss: 0.10325 FastRCNN total loss: 0.25437 L1 loss: 0.0000e+00 L2 loss: 0.93018 Learning rate: 0.02 Mask loss: 0.19197 RPN box loss: 0.03957 RPN score loss: 0.00912 RPN total loss: 0.04869 Total loss: 1.42521 timestamp: 1655027940.615542 iteration: 25115 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1221 FastRCNN class loss: 0.09888 FastRCNN total loss: 0.22098 L1 loss: 0.0000e+00 L2 loss: 0.93003 Learning rate: 0.02 Mask loss: 0.16423 RPN box loss: 0.03581 RPN score loss: 0.00457 RPN total loss: 0.04038 Total loss: 1.35561 timestamp: 1655027943.8606575 iteration: 25120 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20886 FastRCNN class loss: 0.08333 FastRCNN total loss: 0.29219 L1 loss: 0.0000e+00 L2 loss: 0.92989 Learning rate: 0.02 Mask loss: 0.20522 RPN box loss: 0.0152 RPN score loss: 0.00376 RPN total loss: 0.01896 Total loss: 1.44626 timestamp: 1655027947.2446856 iteration: 25125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07957 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.14092 L1 loss: 0.0000e+00 L2 loss: 0.92974 Learning rate: 0.02 Mask loss: 0.1361 RPN box loss: 0.00919 RPN score loss: 0.00255 RPN total loss: 0.01174 Total loss: 1.2185 timestamp: 1655027950.4956954 iteration: 25130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12697 FastRCNN class loss: 0.07647 FastRCNN total loss: 0.20344 L1 loss: 0.0000e+00 L2 loss: 0.92957 Learning rate: 0.02 Mask loss: 0.13366 RPN box loss: 0.04103 RPN score loss: 0.00673 RPN total loss: 0.04776 Total loss: 1.31443 timestamp: 1655027953.8005176 iteration: 25135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10882 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.18644 L1 loss: 0.0000e+00 L2 loss: 0.92944 Learning rate: 0.02 Mask loss: 0.17823 RPN box loss: 0.05467 RPN score loss: 0.00906 RPN total loss: 0.06374 Total loss: 1.35786 timestamp: 1655027957.0765018 iteration: 25140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1364 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.19708 L1 loss: 0.0000e+00 L2 loss: 0.92931 Learning rate: 0.02 Mask loss: 0.12154 RPN box loss: 0.00556 RPN score loss: 0.00458 RPN total loss: 0.01014 Total loss: 1.25806 timestamp: 1655027960.4574156 iteration: 25145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13369 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.2151 L1 loss: 0.0000e+00 L2 loss: 0.92915 Learning rate: 0.02 Mask loss: 0.15454 RPN box loss: 0.03533 RPN score loss: 0.0055 RPN total loss: 0.04084 Total loss: 1.33962 timestamp: 1655027963.6871536 iteration: 25150 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15222 FastRCNN class loss: 0.10212 FastRCNN total loss: 0.25433 L1 loss: 0.0000e+00 L2 loss: 0.929 Learning rate: 0.02 Mask loss: 0.19849 RPN box loss: 0.02702 RPN score loss: 0.00322 RPN total loss: 0.03024 Total loss: 1.41207 timestamp: 1655027967.188739 iteration: 25155 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13009 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.20765 L1 loss: 0.0000e+00 L2 loss: 0.92882 Learning rate: 0.02 Mask loss: 0.10718 RPN box loss: 0.02985 RPN score loss: 0.00489 RPN total loss: 0.03474 Total loss: 1.27839 timestamp: 1655027970.5250208 iteration: 25160 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1477 FastRCNN class loss: 0.11179 FastRCNN total loss: 0.25949 L1 loss: 0.0000e+00 L2 loss: 0.92868 Learning rate: 0.02 Mask loss: 0.11603 RPN box loss: 0.02593 RPN score loss: 0.00643 RPN total loss: 0.03236 Total loss: 1.33657 timestamp: 1655027973.8037724 iteration: 25165 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12006 FastRCNN class loss: 0.07045 FastRCNN total loss: 0.1905 L1 loss: 0.0000e+00 L2 loss: 0.92854 Learning rate: 0.02 Mask loss: 0.12523 RPN box loss: 0.01701 RPN score loss: 0.0046 RPN total loss: 0.02161 Total loss: 1.26589 timestamp: 1655027977.1774077 iteration: 25170 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19433 FastRCNN class loss: 0.14873 FastRCNN total loss: 0.34306 L1 loss: 0.0000e+00 L2 loss: 0.92841 Learning rate: 0.02 Mask loss: 0.23695 RPN box loss: 0.0197 RPN score loss: 0.01054 RPN total loss: 0.03024 Total loss: 1.53865 timestamp: 1655027980.5012507 iteration: 25175 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21199 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.30156 L1 loss: 0.0000e+00 L2 loss: 0.92825 Learning rate: 0.02 Mask loss: 0.14253 RPN box loss: 0.02403 RPN score loss: 0.01045 RPN total loss: 0.03449 Total loss: 1.40683 timestamp: 1655027983.9283097 iteration: 25180 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18581 FastRCNN class loss: 0.12478 FastRCNN total loss: 0.31059 L1 loss: 0.0000e+00 L2 loss: 0.92812 Learning rate: 0.02 Mask loss: 0.24518 RPN box loss: 0.0335 RPN score loss: 0.00962 RPN total loss: 0.04312 Total loss: 1.52701 timestamp: 1655027987.1133344 iteration: 25185 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16432 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.23926 L1 loss: 0.0000e+00 L2 loss: 0.92797 Learning rate: 0.02 Mask loss: 0.15753 RPN box loss: 0.03401 RPN score loss: 0.00693 RPN total loss: 0.04094 Total loss: 1.36569 timestamp: 1655027990.498511 iteration: 25190 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15311 FastRCNN class loss: 0.09714 FastRCNN total loss: 0.25025 L1 loss: 0.0000e+00 L2 loss: 0.92781 Learning rate: 0.02 Mask loss: 0.2337 RPN box loss: 0.02165 RPN score loss: 0.00476 RPN total loss: 0.02641 Total loss: 1.43817 timestamp: 1655027993.8027694 iteration: 25195 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17275 FastRCNN class loss: 0.09391 FastRCNN total loss: 0.26665 L1 loss: 0.0000e+00 L2 loss: 0.92767 Learning rate: 0.02 Mask loss: 0.16605 RPN box loss: 0.07823 RPN score loss: 0.00776 RPN total loss: 0.08599 Total loss: 1.44637 timestamp: 1655027997.1646457 iteration: 25200 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21601 FastRCNN class loss: 0.08997 FastRCNN total loss: 0.30598 L1 loss: 0.0000e+00 L2 loss: 0.92749 Learning rate: 0.02 Mask loss: 0.19139 RPN box loss: 0.02759 RPN score loss: 0.0079 RPN total loss: 0.03549 Total loss: 1.46036 timestamp: 1655028000.5695674 iteration: 25205 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08409 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.16805 L1 loss: 0.0000e+00 L2 loss: 0.92732 Learning rate: 0.02 Mask loss: 0.17622 RPN box loss: 0.00725 RPN score loss: 0.00234 RPN total loss: 0.00959 Total loss: 1.28119 timestamp: 1655028003.839093 iteration: 25210 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17781 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.27111 L1 loss: 0.0000e+00 L2 loss: 0.92719 Learning rate: 0.02 Mask loss: 0.1576 RPN box loss: 0.04549 RPN score loss: 0.00831 RPN total loss: 0.0538 Total loss: 1.4097 timestamp: 1655028007.3254898 iteration: 25215 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25376 FastRCNN class loss: 0.13116 FastRCNN total loss: 0.38493 L1 loss: 0.0000e+00 L2 loss: 0.92706 Learning rate: 0.02 Mask loss: 0.22257 RPN box loss: 0.05372 RPN score loss: 0.01693 RPN total loss: 0.07065 Total loss: 1.60521 timestamp: 1655028010.5654666 iteration: 25220 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23299 FastRCNN class loss: 0.10788 FastRCNN total loss: 0.34087 L1 loss: 0.0000e+00 L2 loss: 0.92694 Learning rate: 0.02 Mask loss: 0.12403 RPN box loss: 0.03196 RPN score loss: 0.01935 RPN total loss: 0.05131 Total loss: 1.44315 timestamp: 1655028013.9435856 iteration: 25225 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16913 FastRCNN class loss: 0.11741 FastRCNN total loss: 0.28654 L1 loss: 0.0000e+00 L2 loss: 0.9268 Learning rate: 0.02 Mask loss: 0.22814 RPN box loss: 0.05229 RPN score loss: 0.02578 RPN total loss: 0.07807 Total loss: 1.51955 timestamp: 1655028017.210528 iteration: 25230 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15734 FastRCNN class loss: 0.09386 FastRCNN total loss: 0.2512 L1 loss: 0.0000e+00 L2 loss: 0.92664 Learning rate: 0.02 Mask loss: 0.25825 RPN box loss: 0.02769 RPN score loss: 0.01286 RPN total loss: 0.04055 Total loss: 1.47664 timestamp: 1655028020.6307087 iteration: 25235 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14473 FastRCNN class loss: 0.10652 FastRCNN total loss: 0.25125 L1 loss: 0.0000e+00 L2 loss: 0.92648 Learning rate: 0.02 Mask loss: 0.1322 RPN box loss: 0.02872 RPN score loss: 0.00988 RPN total loss: 0.0386 Total loss: 1.34852 timestamp: 1655028023.933263 iteration: 25240 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09822 FastRCNN class loss: 0.09411 FastRCNN total loss: 0.19233 L1 loss: 0.0000e+00 L2 loss: 0.92632 Learning rate: 0.02 Mask loss: 0.12171 RPN box loss: 0.06059 RPN score loss: 0.01105 RPN total loss: 0.07164 Total loss: 1.31201 timestamp: 1655028027.3881197 iteration: 25245 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0843 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.14878 L1 loss: 0.0000e+00 L2 loss: 0.92619 Learning rate: 0.02 Mask loss: 0.13852 RPN box loss: 0.05777 RPN score loss: 0.00475 RPN total loss: 0.06252 Total loss: 1.27602 timestamp: 1655028030.8349845 iteration: 25250 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13128 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.2049 L1 loss: 0.0000e+00 L2 loss: 0.92605 Learning rate: 0.02 Mask loss: 0.17456 RPN box loss: 0.04664 RPN score loss: 0.00768 RPN total loss: 0.05432 Total loss: 1.35983 timestamp: 1655028034.1306667 iteration: 25255 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21987 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.29007 L1 loss: 0.0000e+00 L2 loss: 0.92591 Learning rate: 0.02 Mask loss: 0.13937 RPN box loss: 0.02488 RPN score loss: 0.00567 RPN total loss: 0.03055 Total loss: 1.38589 timestamp: 1655028037.5014296 iteration: 25260 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15271 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.22811 L1 loss: 0.0000e+00 L2 loss: 0.92577 Learning rate: 0.02 Mask loss: 0.20004 RPN box loss: 0.02997 RPN score loss: 0.00794 RPN total loss: 0.03791 Total loss: 1.39183 timestamp: 1655028040.7787929 iteration: 25265 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.17364 L1 loss: 0.0000e+00 L2 loss: 0.9256 Learning rate: 0.02 Mask loss: 0.10408 RPN box loss: 0.01341 RPN score loss: 0.00205 RPN total loss: 0.01546 Total loss: 1.21877 timestamp: 1655028044.2457285 iteration: 25270 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10316 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.17452 L1 loss: 0.0000e+00 L2 loss: 0.92544 Learning rate: 0.02 Mask loss: 0.20895 RPN box loss: 0.03327 RPN score loss: 0.00272 RPN total loss: 0.03599 Total loss: 1.3449 timestamp: 1655028047.4754684 iteration: 25275 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1558 FastRCNN class loss: 0.0865 FastRCNN total loss: 0.2423 L1 loss: 0.0000e+00 L2 loss: 0.9253 Learning rate: 0.02 Mask loss: 0.14683 RPN box loss: 0.05254 RPN score loss: 0.00592 RPN total loss: 0.05847 Total loss: 1.3729 timestamp: 1655028050.7998395 iteration: 25280 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16092 FastRCNN class loss: 0.11036 FastRCNN total loss: 0.27127 L1 loss: 0.0000e+00 L2 loss: 0.92516 Learning rate: 0.02 Mask loss: 0.12084 RPN box loss: 0.04577 RPN score loss: 0.01405 RPN total loss: 0.05982 Total loss: 1.37709 timestamp: 1655028054.2038238 iteration: 25285 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20793 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.27761 L1 loss: 0.0000e+00 L2 loss: 0.92501 Learning rate: 0.02 Mask loss: 0.13863 RPN box loss: 0.01355 RPN score loss: 0.00323 RPN total loss: 0.01678 Total loss: 1.35803 timestamp: 1655028057.4691398 iteration: 25290 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1922 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.25339 L1 loss: 0.0000e+00 L2 loss: 0.92485 Learning rate: 0.02 Mask loss: 0.10894 RPN box loss: 0.0201 RPN score loss: 0.00582 RPN total loss: 0.02592 Total loss: 1.3131 timestamp: 1655028060.9190874 iteration: 25295 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14016 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.22637 L1 loss: 0.0000e+00 L2 loss: 0.92472 Learning rate: 0.02 Mask loss: 0.18809 RPN box loss: 0.06733 RPN score loss: 0.00905 RPN total loss: 0.07638 Total loss: 1.41556 timestamp: 1655028064.103371 iteration: 25300 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10751 FastRCNN class loss: 0.05463 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.92456 Learning rate: 0.02 Mask loss: 0.18052 RPN box loss: 0.02066 RPN score loss: 0.00835 RPN total loss: 0.02901 Total loss: 1.29624 timestamp: 1655028067.471915 iteration: 25305 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14955 FastRCNN class loss: 0.10379 FastRCNN total loss: 0.25334 L1 loss: 0.0000e+00 L2 loss: 0.92442 Learning rate: 0.02 Mask loss: 0.23896 RPN box loss: 0.02125 RPN score loss: 0.01313 RPN total loss: 0.03438 Total loss: 1.4511 timestamp: 1655028070.7214282 iteration: 25310 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04332 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.09027 L1 loss: 0.0000e+00 L2 loss: 0.92425 Learning rate: 0.02 Mask loss: 0.11936 RPN box loss: 0.00394 RPN score loss: 0.00287 RPN total loss: 0.00681 Total loss: 1.14069 timestamp: 1655028074.0852375 iteration: 25315 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12005 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.19237 L1 loss: 0.0000e+00 L2 loss: 0.9241 Learning rate: 0.02 Mask loss: 0.21122 RPN box loss: 0.037 RPN score loss: 0.00445 RPN total loss: 0.04145 Total loss: 1.36914 timestamp: 1655028077.3266182 iteration: 25320 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10551 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.18285 L1 loss: 0.0000e+00 L2 loss: 0.92394 Learning rate: 0.02 Mask loss: 0.19357 RPN box loss: 0.03973 RPN score loss: 0.00449 RPN total loss: 0.04422 Total loss: 1.34458 timestamp: 1655028080.7091491 iteration: 25325 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11901 FastRCNN class loss: 0.08193 FastRCNN total loss: 0.20093 L1 loss: 0.0000e+00 L2 loss: 0.92381 Learning rate: 0.02 Mask loss: 0.18011 RPN box loss: 0.04371 RPN score loss: 0.00473 RPN total loss: 0.04843 Total loss: 1.35328 timestamp: 1655028084.089363 iteration: 25330 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17495 FastRCNN class loss: 0.10917 FastRCNN total loss: 0.28412 L1 loss: 0.0000e+00 L2 loss: 0.92367 Learning rate: 0.02 Mask loss: 0.22911 RPN box loss: 0.01123 RPN score loss: 0.01048 RPN total loss: 0.02171 Total loss: 1.45862 timestamp: 1655028087.366774 iteration: 25335 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12867 FastRCNN class loss: 0.08077 FastRCNN total loss: 0.20945 L1 loss: 0.0000e+00 L2 loss: 0.92353 Learning rate: 0.02 Mask loss: 0.18047 RPN box loss: 0.01549 RPN score loss: 0.00528 RPN total loss: 0.02077 Total loss: 1.33421 timestamp: 1655028090.6761608 iteration: 25340 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.18075 L1 loss: 0.0000e+00 L2 loss: 0.92338 Learning rate: 0.02 Mask loss: 0.13465 RPN box loss: 0.08991 RPN score loss: 0.00737 RPN total loss: 0.09728 Total loss: 1.33607 timestamp: 1655028093.9378567 iteration: 25345 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.0586 FastRCNN total loss: 0.17109 L1 loss: 0.0000e+00 L2 loss: 0.9232 Learning rate: 0.02 Mask loss: 0.19425 RPN box loss: 0.07173 RPN score loss: 0.00371 RPN total loss: 0.07544 Total loss: 1.36398 timestamp: 1655028097.2606132 iteration: 25350 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12153 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.18804 L1 loss: 0.0000e+00 L2 loss: 0.92304 Learning rate: 0.02 Mask loss: 0.15118 RPN box loss: 0.07195 RPN score loss: 0.01172 RPN total loss: 0.08367 Total loss: 1.34592 timestamp: 1655028100.4894278 iteration: 25355 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21941 FastRCNN class loss: 0.11824 FastRCNN total loss: 0.33766 L1 loss: 0.0000e+00 L2 loss: 0.92288 Learning rate: 0.02 Mask loss: 0.17355 RPN box loss: 0.03697 RPN score loss: 0.03339 RPN total loss: 0.07036 Total loss: 1.50444 timestamp: 1655028103.842669 iteration: 25360 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18766 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.28784 L1 loss: 0.0000e+00 L2 loss: 0.92274 Learning rate: 0.02 Mask loss: 0.21423 RPN box loss: 0.02938 RPN score loss: 0.00286 RPN total loss: 0.03223 Total loss: 1.45704 timestamp: 1655028107.173675 iteration: 25365 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11178 FastRCNN class loss: 0.04423 FastRCNN total loss: 0.15602 L1 loss: 0.0000e+00 L2 loss: 0.9226 Learning rate: 0.02 Mask loss: 0.17417 RPN box loss: 0.00534 RPN score loss: 0.00867 RPN total loss: 0.01401 Total loss: 1.2668 timestamp: 1655028110.4416602 iteration: 25370 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14384 FastRCNN class loss: 0.08731 FastRCNN total loss: 0.23115 L1 loss: 0.0000e+00 L2 loss: 0.92245 Learning rate: 0.02 Mask loss: 0.17459 RPN box loss: 0.02235 RPN score loss: 0.00484 RPN total loss: 0.02718 Total loss: 1.35536 timestamp: 1655028113.8519483 iteration: 25375 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22837 FastRCNN class loss: 0.10004 FastRCNN total loss: 0.3284 L1 loss: 0.0000e+00 L2 loss: 0.9223 Learning rate: 0.02 Mask loss: 0.28296 RPN box loss: 0.07632 RPN score loss: 0.01482 RPN total loss: 0.09114 Total loss: 1.62481 timestamp: 1655028117.1578672 iteration: 25380 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25894 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.34793 L1 loss: 0.0000e+00 L2 loss: 0.92215 Learning rate: 0.02 Mask loss: 0.17832 RPN box loss: 0.05673 RPN score loss: 0.00532 RPN total loss: 0.06205 Total loss: 1.51045 timestamp: 1655028120.5318587 iteration: 25385 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11492 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.17749 L1 loss: 0.0000e+00 L2 loss: 0.92202 Learning rate: 0.02 Mask loss: 0.13212 RPN box loss: 0.04776 RPN score loss: 0.01061 RPN total loss: 0.05837 Total loss: 1.29 timestamp: 1655028123.7878585 iteration: 25390 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11013 FastRCNN class loss: 0.09361 FastRCNN total loss: 0.20374 L1 loss: 0.0000e+00 L2 loss: 0.92186 Learning rate: 0.02 Mask loss: 0.14338 RPN box loss: 0.03299 RPN score loss: 0.01339 RPN total loss: 0.04638 Total loss: 1.31537 timestamp: 1655028127.0881133 iteration: 25395 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09175 FastRCNN class loss: 0.05427 FastRCNN total loss: 0.14601 L1 loss: 0.0000e+00 L2 loss: 0.92173 Learning rate: 0.02 Mask loss: 0.12879 RPN box loss: 0.06036 RPN score loss: 0.00787 RPN total loss: 0.06822 Total loss: 1.26476 timestamp: 1655028130.3755674 iteration: 25400 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20727 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.28474 L1 loss: 0.0000e+00 L2 loss: 0.9216 Learning rate: 0.02 Mask loss: 0.22936 RPN box loss: 0.01905 RPN score loss: 0.00313 RPN total loss: 0.02218 Total loss: 1.45787 timestamp: 1655028133.696476 iteration: 25405 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10234 FastRCNN class loss: 0.10512 FastRCNN total loss: 0.20746 L1 loss: 0.0000e+00 L2 loss: 0.92146 Learning rate: 0.02 Mask loss: 0.12981 RPN box loss: 0.02986 RPN score loss: 0.0027 RPN total loss: 0.03256 Total loss: 1.29128 timestamp: 1655028136.9431207 iteration: 25410 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.05526 FastRCNN total loss: 0.15871 L1 loss: 0.0000e+00 L2 loss: 0.92129 Learning rate: 0.02 Mask loss: 0.13728 RPN box loss: 0.02133 RPN score loss: 0.00176 RPN total loss: 0.02309 Total loss: 1.24037 timestamp: 1655028140.3552701 iteration: 25415 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16696 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.2491 L1 loss: 0.0000e+00 L2 loss: 0.92113 Learning rate: 0.02 Mask loss: 0.20788 RPN box loss: 0.06694 RPN score loss: 0.00653 RPN total loss: 0.07347 Total loss: 1.45157 timestamp: 1655028143.8258164 iteration: 25420 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.03424 FastRCNN total loss: 0.11927 L1 loss: 0.0000e+00 L2 loss: 0.92099 Learning rate: 0.02 Mask loss: 0.10752 RPN box loss: 0.02446 RPN score loss: 0.00775 RPN total loss: 0.03221 Total loss: 1.17999 timestamp: 1655028147.1196568 iteration: 25425 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11144 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.18889 L1 loss: 0.0000e+00 L2 loss: 0.92082 Learning rate: 0.02 Mask loss: 0.17263 RPN box loss: 0.06083 RPN score loss: 0.04211 RPN total loss: 0.10294 Total loss: 1.38528 timestamp: 1655028150.530338 iteration: 25430 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08222 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.1278 L1 loss: 0.0000e+00 L2 loss: 0.9207 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.02713 RPN score loss: 0.00582 RPN total loss: 0.03295 Total loss: 1.21977 timestamp: 1655028153.8092377 iteration: 25435 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.17304 L1 loss: 0.0000e+00 L2 loss: 0.92056 Learning rate: 0.02 Mask loss: 0.12713 RPN box loss: 0.02738 RPN score loss: 0.00705 RPN total loss: 0.03443 Total loss: 1.25517 timestamp: 1655028157.1627545 iteration: 25440 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13972 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.22562 L1 loss: 0.0000e+00 L2 loss: 0.9204 Learning rate: 0.02 Mask loss: 0.22724 RPN box loss: 0.05596 RPN score loss: 0.01814 RPN total loss: 0.0741 Total loss: 1.44737 timestamp: 1655028160.4533386 iteration: 25445 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09092 FastRCNN class loss: 0.04949 FastRCNN total loss: 0.14041 L1 loss: 0.0000e+00 L2 loss: 0.92027 Learning rate: 0.02 Mask loss: 0.14692 RPN box loss: 0.02279 RPN score loss: 0.00266 RPN total loss: 0.02545 Total loss: 1.23305 timestamp: 1655028163.8136728 iteration: 25450 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14352 FastRCNN class loss: 0.05925 FastRCNN total loss: 0.20277 L1 loss: 0.0000e+00 L2 loss: 0.92013 Learning rate: 0.02 Mask loss: 0.11884 RPN box loss: 0.00791 RPN score loss: 0.00362 RPN total loss: 0.01153 Total loss: 1.25327 timestamp: 1655028167.1935945 iteration: 25455 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20395 FastRCNN class loss: 0.09369 FastRCNN total loss: 0.29764 L1 loss: 0.0000e+00 L2 loss: 0.91996 Learning rate: 0.02 Mask loss: 0.15316 RPN box loss: 0.0342 RPN score loss: 0.01299 RPN total loss: 0.04719 Total loss: 1.41795 timestamp: 1655028170.612402 iteration: 25460 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23006 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.31461 L1 loss: 0.0000e+00 L2 loss: 0.9198 Learning rate: 0.02 Mask loss: 0.1195 RPN box loss: 0.03087 RPN score loss: 0.00673 RPN total loss: 0.03759 Total loss: 1.39151 timestamp: 1655028174.0586927 iteration: 25465 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.20566 L1 loss: 0.0000e+00 L2 loss: 0.91966 Learning rate: 0.02 Mask loss: 0.20273 RPN box loss: 0.04142 RPN score loss: 0.00362 RPN total loss: 0.04504 Total loss: 1.37309 timestamp: 1655028177.3375552 iteration: 25470 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11941 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.19425 L1 loss: 0.0000e+00 L2 loss: 0.91952 Learning rate: 0.02 Mask loss: 0.16276 RPN box loss: 0.0339 RPN score loss: 0.0065 RPN total loss: 0.0404 Total loss: 1.31693 timestamp: 1655028180.7454057 iteration: 25475 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.16441 L1 loss: 0.0000e+00 L2 loss: 0.91936 Learning rate: 0.02 Mask loss: 0.13798 RPN box loss: 0.04281 RPN score loss: 0.01205 RPN total loss: 0.05486 Total loss: 1.27661 timestamp: 1655028184.0638635 iteration: 25480 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08261 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.13685 L1 loss: 0.0000e+00 L2 loss: 0.91921 Learning rate: 0.02 Mask loss: 0.11085 RPN box loss: 0.02951 RPN score loss: 0.0025 RPN total loss: 0.03201 Total loss: 1.19892 timestamp: 1655028187.427178 iteration: 25485 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15048 FastRCNN class loss: 0.0997 FastRCNN total loss: 0.25017 L1 loss: 0.0000e+00 L2 loss: 0.91909 Learning rate: 0.02 Mask loss: 0.30065 RPN box loss: 0.01093 RPN score loss: 0.00253 RPN total loss: 0.01346 Total loss: 1.48337 timestamp: 1655028190.709237 iteration: 25490 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22749 FastRCNN class loss: 0.15324 FastRCNN total loss: 0.38074 L1 loss: 0.0000e+00 L2 loss: 0.91897 Learning rate: 0.02 Mask loss: 0.18748 RPN box loss: 0.02472 RPN score loss: 0.01014 RPN total loss: 0.03486 Total loss: 1.52205 timestamp: 1655028194.1217191 iteration: 25495 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18695 FastRCNN class loss: 0.1119 FastRCNN total loss: 0.29884 L1 loss: 0.0000e+00 L2 loss: 0.91882 Learning rate: 0.02 Mask loss: 0.17794 RPN box loss: 0.08641 RPN score loss: 0.01206 RPN total loss: 0.09847 Total loss: 1.49407 timestamp: 1655028197.5779908 iteration: 25500 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.04799 FastRCNN total loss: 0.13866 L1 loss: 0.0000e+00 L2 loss: 0.91867 Learning rate: 0.02 Mask loss: 0.1105 RPN box loss: 0.00797 RPN score loss: 0.0068 RPN total loss: 0.01477 Total loss: 1.18261 timestamp: 1655028200.8620193 iteration: 25505 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06797 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.12628 L1 loss: 0.0000e+00 L2 loss: 0.9185 Learning rate: 0.02 Mask loss: 0.16594 RPN box loss: 0.02742 RPN score loss: 0.00322 RPN total loss: 0.03064 Total loss: 1.24135 timestamp: 1655028204.2525837 iteration: 25510 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.175 FastRCNN class loss: 0.13167 FastRCNN total loss: 0.30666 L1 loss: 0.0000e+00 L2 loss: 0.91833 Learning rate: 0.02 Mask loss: 0.21855 RPN box loss: 0.043 RPN score loss: 0.0116 RPN total loss: 0.0546 Total loss: 1.49815 timestamp: 1655028207.6075602 iteration: 25515 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14138 FastRCNN class loss: 0.13247 FastRCNN total loss: 0.27385 L1 loss: 0.0000e+00 L2 loss: 0.91819 Learning rate: 0.02 Mask loss: 0.20291 RPN box loss: 0.03782 RPN score loss: 0.01127 RPN total loss: 0.04909 Total loss: 1.44404 timestamp: 1655028211.0889888 iteration: 25520 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15892 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.24217 L1 loss: 0.0000e+00 L2 loss: 0.91806 Learning rate: 0.02 Mask loss: 0.18323 RPN box loss: 0.03732 RPN score loss: 0.01725 RPN total loss: 0.05457 Total loss: 1.39804 timestamp: 1655028214.4220335 iteration: 25525 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15935 FastRCNN class loss: 0.088 FastRCNN total loss: 0.24734 L1 loss: 0.0000e+00 L2 loss: 0.91791 Learning rate: 0.02 Mask loss: 0.12704 RPN box loss: 0.02075 RPN score loss: 0.00453 RPN total loss: 0.02528 Total loss: 1.31757 timestamp: 1655028217.7611184 iteration: 25530 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18478 FastRCNN class loss: 0.09196 FastRCNN total loss: 0.27674 L1 loss: 0.0000e+00 L2 loss: 0.91775 Learning rate: 0.02 Mask loss: 0.22382 RPN box loss: 0.03176 RPN score loss: 0.00313 RPN total loss: 0.03489 Total loss: 1.4532 timestamp: 1655028220.9879873 iteration: 25535 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16308 FastRCNN class loss: 0.12717 FastRCNN total loss: 0.29025 L1 loss: 0.0000e+00 L2 loss: 0.91762 Learning rate: 0.02 Mask loss: 0.21164 RPN box loss: 0.06705 RPN score loss: 0.01872 RPN total loss: 0.08577 Total loss: 1.50527 timestamp: 1655028224.2821522 iteration: 25540 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21427 FastRCNN class loss: 0.10362 FastRCNN total loss: 0.31789 L1 loss: 0.0000e+00 L2 loss: 0.9175 Learning rate: 0.02 Mask loss: 0.15815 RPN box loss: 0.03771 RPN score loss: 0.01573 RPN total loss: 0.05344 Total loss: 1.44698 timestamp: 1655028227.6736283 iteration: 25545 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25994 FastRCNN class loss: 0.11124 FastRCNN total loss: 0.37118 L1 loss: 0.0000e+00 L2 loss: 0.91734 Learning rate: 0.02 Mask loss: 0.25481 RPN box loss: 0.06539 RPN score loss: 0.01079 RPN total loss: 0.07618 Total loss: 1.6195 timestamp: 1655028230.9808307 iteration: 25550 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08559 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.14747 L1 loss: 0.0000e+00 L2 loss: 0.9172 Learning rate: 0.02 Mask loss: 0.11523 RPN box loss: 0.0281 RPN score loss: 0.00301 RPN total loss: 0.03111 Total loss: 1.21101 timestamp: 1655028234.4936137 iteration: 25555 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17859 FastRCNN class loss: 0.11295 FastRCNN total loss: 0.29153 L1 loss: 0.0000e+00 L2 loss: 0.91705 Learning rate: 0.02 Mask loss: 0.2835 RPN box loss: 0.05802 RPN score loss: 0.02701 RPN total loss: 0.08503 Total loss: 1.57712 timestamp: 1655028237.8287053 iteration: 25560 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12129 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.16415 L1 loss: 0.0000e+00 L2 loss: 0.91693 Learning rate: 0.02 Mask loss: 0.14353 RPN box loss: 0.03399 RPN score loss: 0.00954 RPN total loss: 0.04353 Total loss: 1.26813 timestamp: 1655028241.1272166 iteration: 25565 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21615 FastRCNN class loss: 0.08692 FastRCNN total loss: 0.30307 L1 loss: 0.0000e+00 L2 loss: 0.91678 Learning rate: 0.02 Mask loss: 0.20241 RPN box loss: 0.02597 RPN score loss: 0.00904 RPN total loss: 0.03501 Total loss: 1.45728 timestamp: 1655028244.3306663 iteration: 25570 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11307 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.1986 L1 loss: 0.0000e+00 L2 loss: 0.91662 Learning rate: 0.02 Mask loss: 0.19902 RPN box loss: 0.03067 RPN score loss: 0.01423 RPN total loss: 0.0449 Total loss: 1.35915 timestamp: 1655028247.7945218 iteration: 25575 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18132 FastRCNN class loss: 0.15193 FastRCNN total loss: 0.33325 L1 loss: 0.0000e+00 L2 loss: 0.91648 Learning rate: 0.02 Mask loss: 0.14388 RPN box loss: 0.02958 RPN score loss: 0.0045 RPN total loss: 0.03408 Total loss: 1.4277 timestamp: 1655028251.1621375 iteration: 25580 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1099 FastRCNN class loss: 0.11927 FastRCNN total loss: 0.22917 L1 loss: 0.0000e+00 L2 loss: 0.91633 Learning rate: 0.02 Mask loss: 0.14726 RPN box loss: 0.03669 RPN score loss: 0.01185 RPN total loss: 0.04855 Total loss: 1.34131 timestamp: 1655028254.4895356 iteration: 25585 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12872 FastRCNN class loss: 0.07868 FastRCNN total loss: 0.2074 L1 loss: 0.0000e+00 L2 loss: 0.91616 Learning rate: 0.02 Mask loss: 0.12899 RPN box loss: 0.0185 RPN score loss: 0.0032 RPN total loss: 0.0217 Total loss: 1.27425 timestamp: 1655028257.912038 iteration: 25590 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1705 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.24506 L1 loss: 0.0000e+00 L2 loss: 0.91603 Learning rate: 0.02 Mask loss: 0.16137 RPN box loss: 0.05842 RPN score loss: 0.00778 RPN total loss: 0.0662 Total loss: 1.38867 timestamp: 1655028261.1455922 iteration: 25595 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.22204 L1 loss: 0.0000e+00 L2 loss: 0.9159 Learning rate: 0.02 Mask loss: 0.15621 RPN box loss: 0.04685 RPN score loss: 0.01532 RPN total loss: 0.06217 Total loss: 1.35632 timestamp: 1655028264.5753484 iteration: 25600 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15136 FastRCNN class loss: 0.12338 FastRCNN total loss: 0.27474 L1 loss: 0.0000e+00 L2 loss: 0.91574 Learning rate: 0.02 Mask loss: 0.17362 RPN box loss: 0.0213 RPN score loss: 0.00947 RPN total loss: 0.03076 Total loss: 1.39486 timestamp: 1655028267.8871818 iteration: 25605 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06874 FastRCNN class loss: 0.03662 FastRCNN total loss: 0.10536 L1 loss: 0.0000e+00 L2 loss: 0.91561 Learning rate: 0.02 Mask loss: 0.1251 RPN box loss: 0.0045 RPN score loss: 0.00454 RPN total loss: 0.00904 Total loss: 1.15512 timestamp: 1655028271.3117964 iteration: 25610 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11712 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.19735 L1 loss: 0.0000e+00 L2 loss: 0.91547 Learning rate: 0.02 Mask loss: 0.18143 RPN box loss: 0.05063 RPN score loss: 0.0047 RPN total loss: 0.05533 Total loss: 1.34958 timestamp: 1655028274.605733 iteration: 25615 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21497 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.31244 L1 loss: 0.0000e+00 L2 loss: 0.9153 Learning rate: 0.02 Mask loss: 0.2295 RPN box loss: 0.03504 RPN score loss: 0.00747 RPN total loss: 0.0425 Total loss: 1.49975 timestamp: 1655028277.9860713 iteration: 25620 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14576 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.2118 L1 loss: 0.0000e+00 L2 loss: 0.91519 Learning rate: 0.02 Mask loss: 0.19591 RPN box loss: 0.06354 RPN score loss: 0.00695 RPN total loss: 0.07049 Total loss: 1.39339 timestamp: 1655028281.2614558 iteration: 25625 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18916 FastRCNN class loss: 0.10494 FastRCNN total loss: 0.2941 L1 loss: 0.0000e+00 L2 loss: 0.91502 Learning rate: 0.02 Mask loss: 0.15787 RPN box loss: 0.02679 RPN score loss: 0.00354 RPN total loss: 0.03034 Total loss: 1.39733 timestamp: 1655028284.5597928 iteration: 25630 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18252 FastRCNN class loss: 0.11666 FastRCNN total loss: 0.29917 L1 loss: 0.0000e+00 L2 loss: 0.91487 Learning rate: 0.02 Mask loss: 0.19445 RPN box loss: 0.02408 RPN score loss: 0.01277 RPN total loss: 0.03685 Total loss: 1.44534 timestamp: 1655028287.995722 iteration: 25635 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22624 FastRCNN class loss: 0.08477 FastRCNN total loss: 0.31101 L1 loss: 0.0000e+00 L2 loss: 0.91473 Learning rate: 0.02 Mask loss: 0.24508 RPN box loss: 0.02316 RPN score loss: 0.00395 RPN total loss: 0.02711 Total loss: 1.49793 timestamp: 1655028291.275132 iteration: 25640 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13342 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.21987 L1 loss: 0.0000e+00 L2 loss: 0.91458 Learning rate: 0.02 Mask loss: 0.15581 RPN box loss: 0.01211 RPN score loss: 0.00342 RPN total loss: 0.01552 Total loss: 1.30578 timestamp: 1655028294.7363858 iteration: 25645 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10167 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.15141 L1 loss: 0.0000e+00 L2 loss: 0.91443 Learning rate: 0.02 Mask loss: 0.13039 RPN box loss: 0.01185 RPN score loss: 0.00575 RPN total loss: 0.0176 Total loss: 1.21382 timestamp: 1655028298.0485244 iteration: 25650 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08623 FastRCNN class loss: 0.0541 FastRCNN total loss: 0.14033 L1 loss: 0.0000e+00 L2 loss: 0.9143 Learning rate: 0.02 Mask loss: 0.16602 RPN box loss: 0.0328 RPN score loss: 0.00733 RPN total loss: 0.04013 Total loss: 1.26078 timestamp: 1655028301.3928103 iteration: 25655 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18115 FastRCNN class loss: 0.13376 FastRCNN total loss: 0.31491 L1 loss: 0.0000e+00 L2 loss: 0.91415 Learning rate: 0.02 Mask loss: 0.21147 RPN box loss: 0.02392 RPN score loss: 0.01371 RPN total loss: 0.03764 Total loss: 1.47816 timestamp: 1655028304.7510738 iteration: 25660 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13479 FastRCNN class loss: 0.07984 FastRCNN total loss: 0.21463 L1 loss: 0.0000e+00 L2 loss: 0.91404 Learning rate: 0.02 Mask loss: 0.12782 RPN box loss: 0.0449 RPN score loss: 0.00974 RPN total loss: 0.05464 Total loss: 1.31112 timestamp: 1655028308.0497272 iteration: 25665 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1729 FastRCNN class loss: 0.08222 FastRCNN total loss: 0.25512 L1 loss: 0.0000e+00 L2 loss: 0.91388 Learning rate: 0.02 Mask loss: 0.1501 RPN box loss: 0.06184 RPN score loss: 0.02011 RPN total loss: 0.08195 Total loss: 1.40106 timestamp: 1655028311.3706293 iteration: 25670 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14565 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.20195 L1 loss: 0.0000e+00 L2 loss: 0.91374 Learning rate: 0.02 Mask loss: 0.10723 RPN box loss: 0.06527 RPN score loss: 0.00315 RPN total loss: 0.06842 Total loss: 1.29134 timestamp: 1655028314.6940076 iteration: 25675 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08132 FastRCNN class loss: 0.07892 FastRCNN total loss: 0.16024 L1 loss: 0.0000e+00 L2 loss: 0.91361 Learning rate: 0.02 Mask loss: 0.20457 RPN box loss: 0.00559 RPN score loss: 0.00168 RPN total loss: 0.00727 Total loss: 1.2857 timestamp: 1655028318.1557994 iteration: 25680 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22252 FastRCNN class loss: 0.16039 FastRCNN total loss: 0.38292 L1 loss: 0.0000e+00 L2 loss: 0.91344 Learning rate: 0.02 Mask loss: 0.22318 RPN box loss: 0.03435 RPN score loss: 0.01246 RPN total loss: 0.0468 Total loss: 1.56634 timestamp: 1655028321.4425106 iteration: 25685 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18632 FastRCNN class loss: 0.10245 FastRCNN total loss: 0.28878 L1 loss: 0.0000e+00 L2 loss: 0.91326 Learning rate: 0.02 Mask loss: 0.16108 RPN box loss: 0.0449 RPN score loss: 0.00689 RPN total loss: 0.05179 Total loss: 1.41491 timestamp: 1655028324.7331417 iteration: 25690 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11999 FastRCNN class loss: 0.11852 FastRCNN total loss: 0.23851 L1 loss: 0.0000e+00 L2 loss: 0.91313 Learning rate: 0.02 Mask loss: 0.14877 RPN box loss: 0.04728 RPN score loss: 0.00923 RPN total loss: 0.05651 Total loss: 1.35692 timestamp: 1655028327.9691656 iteration: 25695 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14593 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.21363 L1 loss: 0.0000e+00 L2 loss: 0.913 Learning rate: 0.02 Mask loss: 0.13369 RPN box loss: 0.02402 RPN score loss: 0.00976 RPN total loss: 0.03379 Total loss: 1.2941 timestamp: 1655028331.3600597 iteration: 25700 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1999 FastRCNN class loss: 0.08184 FastRCNN total loss: 0.28174 L1 loss: 0.0000e+00 L2 loss: 0.91285 Learning rate: 0.02 Mask loss: 0.15772 RPN box loss: 0.01854 RPN score loss: 0.00793 RPN total loss: 0.02647 Total loss: 1.37878 timestamp: 1655028334.6216412 iteration: 25705 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06872 FastRCNN class loss: 0.05788 FastRCNN total loss: 0.1266 L1 loss: 0.0000e+00 L2 loss: 0.9127 Learning rate: 0.02 Mask loss: 0.2093 RPN box loss: 0.00781 RPN score loss: 0.00394 RPN total loss: 0.01175 Total loss: 1.26035 timestamp: 1655028338.0474033 iteration: 25710 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12473 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.19255 L1 loss: 0.0000e+00 L2 loss: 0.91256 Learning rate: 0.02 Mask loss: 0.22742 RPN box loss: 0.06612 RPN score loss: 0.00845 RPN total loss: 0.07457 Total loss: 1.4071 timestamp: 1655028341.430534 iteration: 25715 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15595 FastRCNN class loss: 0.09158 FastRCNN total loss: 0.24753 L1 loss: 0.0000e+00 L2 loss: 0.91242 Learning rate: 0.02 Mask loss: 0.18047 RPN box loss: 0.04053 RPN score loss: 0.0058 RPN total loss: 0.04633 Total loss: 1.38675 timestamp: 1655028344.687304 iteration: 25720 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.04151 FastRCNN total loss: 0.15312 L1 loss: 0.0000e+00 L2 loss: 0.91232 Learning rate: 0.02 Mask loss: 0.11602 RPN box loss: 0.01615 RPN score loss: 0.00504 RPN total loss: 0.02118 Total loss: 1.20265 timestamp: 1655028348.0360935 iteration: 25725 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11702 FastRCNN class loss: 0.04369 FastRCNN total loss: 0.16071 L1 loss: 0.0000e+00 L2 loss: 0.9122 Learning rate: 0.02 Mask loss: 0.12229 RPN box loss: 0.03443 RPN score loss: 0.00424 RPN total loss: 0.03868 Total loss: 1.23388 timestamp: 1655028351.3315718 iteration: 25730 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11481 FastRCNN class loss: 0.11867 FastRCNN total loss: 0.23348 L1 loss: 0.0000e+00 L2 loss: 0.91205 Learning rate: 0.02 Mask loss: 0.13352 RPN box loss: 0.03818 RPN score loss: 0.00688 RPN total loss: 0.04506 Total loss: 1.32411 timestamp: 1655028354.6355479 iteration: 25735 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10743 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.16952 L1 loss: 0.0000e+00 L2 loss: 0.91189 Learning rate: 0.02 Mask loss: 0.13921 RPN box loss: 0.04768 RPN score loss: 0.0019 RPN total loss: 0.04959 Total loss: 1.27021 timestamp: 1655028357.8893614 iteration: 25740 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12989 FastRCNN class loss: 0.09881 FastRCNN total loss: 0.22869 L1 loss: 0.0000e+00 L2 loss: 0.91175 Learning rate: 0.02 Mask loss: 0.16059 RPN box loss: 0.07671 RPN score loss: 0.02565 RPN total loss: 0.10236 Total loss: 1.40339 timestamp: 1655028361.3582578 iteration: 25745 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21492 FastRCNN class loss: 0.06054 FastRCNN total loss: 0.27546 L1 loss: 0.0000e+00 L2 loss: 0.91155 Learning rate: 0.02 Mask loss: 0.22142 RPN box loss: 0.02631 RPN score loss: 0.00834 RPN total loss: 0.03465 Total loss: 1.44308 timestamp: 1655028364.674849 iteration: 25750 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.08554 FastRCNN total loss: 0.20572 L1 loss: 0.0000e+00 L2 loss: 0.9114 Learning rate: 0.02 Mask loss: 0.1666 RPN box loss: 0.02823 RPN score loss: 0.00815 RPN total loss: 0.03637 Total loss: 1.32009 timestamp: 1655028367.9956338 iteration: 25755 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07586 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.15443 L1 loss: 0.0000e+00 L2 loss: 0.91128 Learning rate: 0.02 Mask loss: 0.12681 RPN box loss: 0.04245 RPN score loss: 0.00404 RPN total loss: 0.04649 Total loss: 1.23901 timestamp: 1655028371.4154558 iteration: 25760 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12012 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.18318 L1 loss: 0.0000e+00 L2 loss: 0.91116 Learning rate: 0.02 Mask loss: 0.18021 RPN box loss: 0.02891 RPN score loss: 0.01206 RPN total loss: 0.04098 Total loss: 1.31552 timestamp: 1655028374.690526 iteration: 25765 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12888 FastRCNN class loss: 0.07837 FastRCNN total loss: 0.20724 L1 loss: 0.0000e+00 L2 loss: 0.911 Learning rate: 0.02 Mask loss: 0.17242 RPN box loss: 0.02208 RPN score loss: 0.00654 RPN total loss: 0.02863 Total loss: 1.31929 timestamp: 1655028378.0759242 iteration: 25770 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1417 FastRCNN class loss: 0.12023 FastRCNN total loss: 0.26193 L1 loss: 0.0000e+00 L2 loss: 0.91087 Learning rate: 0.02 Mask loss: 0.19793 RPN box loss: 0.08758 RPN score loss: 0.00893 RPN total loss: 0.0965 Total loss: 1.46723 timestamp: 1655028381.3302917 iteration: 25775 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.91074 Learning rate: 0.02 Mask loss: 0.18967 RPN box loss: 0.04197 RPN score loss: 0.01005 RPN total loss: 0.05201 Total loss: 1.35142 timestamp: 1655028384.6430762 iteration: 25780 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12769 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.20584 L1 loss: 0.0000e+00 L2 loss: 0.91059 Learning rate: 0.02 Mask loss: 0.15494 RPN box loss: 0.04147 RPN score loss: 0.00998 RPN total loss: 0.05145 Total loss: 1.32281 timestamp: 1655028387.9089653 iteration: 25785 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13587 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.20179 L1 loss: 0.0000e+00 L2 loss: 0.91044 Learning rate: 0.02 Mask loss: 0.17875 RPN box loss: 0.01766 RPN score loss: 0.00663 RPN total loss: 0.02429 Total loss: 1.31526 timestamp: 1655028391.2996595 iteration: 25790 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21307 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.28994 L1 loss: 0.0000e+00 L2 loss: 0.91028 Learning rate: 0.02 Mask loss: 0.1586 RPN box loss: 0.03778 RPN score loss: 0.01069 RPN total loss: 0.04847 Total loss: 1.4073 timestamp: 1655028394.6595325 iteration: 25795 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08422 FastRCNN class loss: 0.05067 FastRCNN total loss: 0.13489 L1 loss: 0.0000e+00 L2 loss: 0.91015 Learning rate: 0.02 Mask loss: 0.16798 RPN box loss: 0.02991 RPN score loss: 0.00512 RPN total loss: 0.03504 Total loss: 1.24805 timestamp: 1655028398.0668693 iteration: 25800 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20022 FastRCNN class loss: 0.10905 FastRCNN total loss: 0.30927 L1 loss: 0.0000e+00 L2 loss: 0.90999 Learning rate: 0.02 Mask loss: 0.22466 RPN box loss: 0.04526 RPN score loss: 0.01198 RPN total loss: 0.05724 Total loss: 1.50117 timestamp: 1655028401.4801123 iteration: 25805 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13393 FastRCNN class loss: 0.12229 FastRCNN total loss: 0.25621 L1 loss: 0.0000e+00 L2 loss: 0.90984 Learning rate: 0.02 Mask loss: 0.15529 RPN box loss: 0.09079 RPN score loss: 0.00486 RPN total loss: 0.09565 Total loss: 1.41699 timestamp: 1655028404.6522243 iteration: 25810 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1929 FastRCNN class loss: 0.12044 FastRCNN total loss: 0.31335 L1 loss: 0.0000e+00 L2 loss: 0.90971 Learning rate: 0.02 Mask loss: 0.20172 RPN box loss: 0.09654 RPN score loss: 0.01395 RPN total loss: 0.1105 Total loss: 1.53527 timestamp: 1655028408.005299 iteration: 25815 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13382 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.2089 L1 loss: 0.0000e+00 L2 loss: 0.90958 Learning rate: 0.02 Mask loss: 0.22466 RPN box loss: 0.03154 RPN score loss: 0.01343 RPN total loss: 0.04498 Total loss: 1.38812 timestamp: 1655028411.2662256 iteration: 25820 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17224 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.25162 L1 loss: 0.0000e+00 L2 loss: 0.90945 Learning rate: 0.02 Mask loss: 0.17029 RPN box loss: 0.0198 RPN score loss: 0.00505 RPN total loss: 0.02485 Total loss: 1.35622 timestamp: 1655028414.6615775 iteration: 25825 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07599 FastRCNN class loss: 0.0591 FastRCNN total loss: 0.13509 L1 loss: 0.0000e+00 L2 loss: 0.90931 Learning rate: 0.02 Mask loss: 0.17309 RPN box loss: 0.0179 RPN score loss: 0.00348 RPN total loss: 0.02138 Total loss: 1.23887 timestamp: 1655028417.8846462 iteration: 25830 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17344 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.2576 L1 loss: 0.0000e+00 L2 loss: 0.90916 Learning rate: 0.02 Mask loss: 0.20545 RPN box loss: 0.042 RPN score loss: 0.00541 RPN total loss: 0.04741 Total loss: 1.41962 timestamp: 1655028421.334997 iteration: 25835 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11755 FastRCNN class loss: 0.06029 FastRCNN total loss: 0.17785 L1 loss: 0.0000e+00 L2 loss: 0.90901 Learning rate: 0.02 Mask loss: 0.15747 RPN box loss: 0.04009 RPN score loss: 0.0025 RPN total loss: 0.04259 Total loss: 1.28692 timestamp: 1655028424.5521662 iteration: 25840 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16112 FastRCNN class loss: 0.07865 FastRCNN total loss: 0.23977 L1 loss: 0.0000e+00 L2 loss: 0.90886 Learning rate: 0.02 Mask loss: 0.30513 RPN box loss: 0.06668 RPN score loss: 0.01491 RPN total loss: 0.08159 Total loss: 1.53535 timestamp: 1655028427.9578454 iteration: 25845 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11574 FastRCNN class loss: 0.08481 FastRCNN total loss: 0.20055 L1 loss: 0.0000e+00 L2 loss: 0.90872 Learning rate: 0.02 Mask loss: 0.14864 RPN box loss: 0.0222 RPN score loss: 0.00483 RPN total loss: 0.02703 Total loss: 1.28494 timestamp: 1655028431.3878403 iteration: 25850 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13997 FastRCNN class loss: 0.15551 FastRCNN total loss: 0.29547 L1 loss: 0.0000e+00 L2 loss: 0.9086 Learning rate: 0.02 Mask loss: 0.20308 RPN box loss: 0.09177 RPN score loss: 0.01356 RPN total loss: 0.10533 Total loss: 1.51247 timestamp: 1655028434.7172766 iteration: 25855 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13994 FastRCNN class loss: 0.08747 FastRCNN total loss: 0.22741 L1 loss: 0.0000e+00 L2 loss: 0.90844 Learning rate: 0.02 Mask loss: 0.22309 RPN box loss: 0.02823 RPN score loss: 0.01415 RPN total loss: 0.04238 Total loss: 1.40132 timestamp: 1655028438.1832335 iteration: 25860 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11734 FastRCNN class loss: 0.05484 FastRCNN total loss: 0.17218 L1 loss: 0.0000e+00 L2 loss: 0.90828 Learning rate: 0.02 Mask loss: 0.1309 RPN box loss: 0.01088 RPN score loss: 0.00199 RPN total loss: 0.01286 Total loss: 1.22423 timestamp: 1655028441.509563 iteration: 25865 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10553 FastRCNN class loss: 0.04948 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.90816 Learning rate: 0.02 Mask loss: 0.10488 RPN box loss: 0.04444 RPN score loss: 0.00543 RPN total loss: 0.04987 Total loss: 1.21792 timestamp: 1655028444.865015 iteration: 25870 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11031 FastRCNN class loss: 0.10841 FastRCNN total loss: 0.21872 L1 loss: 0.0000e+00 L2 loss: 0.908 Learning rate: 0.02 Mask loss: 0.10246 RPN box loss: 0.03396 RPN score loss: 0.00485 RPN total loss: 0.03881 Total loss: 1.26799 timestamp: 1655028448.0889666 iteration: 25875 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10383 FastRCNN class loss: 0.04748 FastRCNN total loss: 0.15131 L1 loss: 0.0000e+00 L2 loss: 0.90785 Learning rate: 0.02 Mask loss: 0.149 RPN box loss: 0.0736 RPN score loss: 0.011 RPN total loss: 0.0846 Total loss: 1.29276 timestamp: 1655028451.4902563 iteration: 25880 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14839 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.21404 L1 loss: 0.0000e+00 L2 loss: 0.90769 Learning rate: 0.02 Mask loss: 0.15318 RPN box loss: 0.0254 RPN score loss: 0.00689 RPN total loss: 0.03228 Total loss: 1.3072 timestamp: 1655028454.746305 iteration: 25885 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1734 FastRCNN class loss: 0.10683 FastRCNN total loss: 0.28022 L1 loss: 0.0000e+00 L2 loss: 0.90756 Learning rate: 0.02 Mask loss: 0.22935 RPN box loss: 0.01983 RPN score loss: 0.02139 RPN total loss: 0.04122 Total loss: 1.45835 timestamp: 1655028458.076649 iteration: 25890 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17391 FastRCNN class loss: 0.14284 FastRCNN total loss: 0.31675 L1 loss: 0.0000e+00 L2 loss: 0.90741 Learning rate: 0.02 Mask loss: 0.15954 RPN box loss: 0.05346 RPN score loss: 0.00782 RPN total loss: 0.06128 Total loss: 1.44498 timestamp: 1655028461.3489857 iteration: 25895 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27346 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.37051 L1 loss: 0.0000e+00 L2 loss: 0.90729 Learning rate: 0.02 Mask loss: 0.12695 RPN box loss: 0.02505 RPN score loss: 0.00428 RPN total loss: 0.02934 Total loss: 1.43408 timestamp: 1655028464.6335113 iteration: 25900 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17102 FastRCNN class loss: 0.10149 FastRCNN total loss: 0.2725 L1 loss: 0.0000e+00 L2 loss: 0.90715 Learning rate: 0.02 Mask loss: 0.14589 RPN box loss: 0.02655 RPN score loss: 0.00388 RPN total loss: 0.03044 Total loss: 1.35597 timestamp: 1655028468.0006692 iteration: 25905 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12693 FastRCNN class loss: 0.08725 FastRCNN total loss: 0.21418 L1 loss: 0.0000e+00 L2 loss: 0.90702 Learning rate: 0.02 Mask loss: 0.20259 RPN box loss: 0.08085 RPN score loss: 0.01706 RPN total loss: 0.09791 Total loss: 1.4217 timestamp: 1655028471.2409596 iteration: 25910 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1852 FastRCNN class loss: 0.12273 FastRCNN total loss: 0.30793 L1 loss: 0.0000e+00 L2 loss: 0.90687 Learning rate: 0.02 Mask loss: 0.15406 RPN box loss: 0.053 RPN score loss: 0.00695 RPN total loss: 0.05995 Total loss: 1.42881 timestamp: 1655028474.5952337 iteration: 25915 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12848 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.1947 L1 loss: 0.0000e+00 L2 loss: 0.90672 Learning rate: 0.02 Mask loss: 0.17654 RPN box loss: 0.0233 RPN score loss: 0.00807 RPN total loss: 0.03137 Total loss: 1.30932 timestamp: 1655028477.933037 iteration: 25920 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15082 FastRCNN class loss: 0.09825 FastRCNN total loss: 0.24906 L1 loss: 0.0000e+00 L2 loss: 0.90659 Learning rate: 0.02 Mask loss: 0.1452 RPN box loss: 0.05382 RPN score loss: 0.01075 RPN total loss: 0.06457 Total loss: 1.36542 timestamp: 1655028481.2748954 iteration: 25925 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1048 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.19381 L1 loss: 0.0000e+00 L2 loss: 0.90645 Learning rate: 0.02 Mask loss: 0.12843 RPN box loss: 0.02992 RPN score loss: 0.01025 RPN total loss: 0.04018 Total loss: 1.26887 timestamp: 1655028484.5434675 iteration: 25930 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19866 FastRCNN class loss: 0.10952 FastRCNN total loss: 0.30818 L1 loss: 0.0000e+00 L2 loss: 0.9063 Learning rate: 0.02 Mask loss: 0.19099 RPN box loss: 0.04976 RPN score loss: 0.00607 RPN total loss: 0.05583 Total loss: 1.4613 timestamp: 1655028487.917161 iteration: 25935 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17142 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.24945 L1 loss: 0.0000e+00 L2 loss: 0.90613 Learning rate: 0.02 Mask loss: 0.16434 RPN box loss: 0.03082 RPN score loss: 0.00686 RPN total loss: 0.03768 Total loss: 1.35761 timestamp: 1655028491.357206 iteration: 25940 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08058 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.15864 L1 loss: 0.0000e+00 L2 loss: 0.906 Learning rate: 0.02 Mask loss: 0.18749 RPN box loss: 0.04244 RPN score loss: 0.01477 RPN total loss: 0.05721 Total loss: 1.30933 timestamp: 1655028494.6577578 iteration: 25945 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17933 FastRCNN class loss: 0.14439 FastRCNN total loss: 0.32372 L1 loss: 0.0000e+00 L2 loss: 0.90586 Learning rate: 0.02 Mask loss: 0.21168 RPN box loss: 0.02981 RPN score loss: 0.02595 RPN total loss: 0.05576 Total loss: 1.49703 timestamp: 1655028498.0235925 iteration: 25950 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14455 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.21433 L1 loss: 0.0000e+00 L2 loss: 0.90572 Learning rate: 0.02 Mask loss: 0.15867 RPN box loss: 0.03477 RPN score loss: 0.00816 RPN total loss: 0.04293 Total loss: 1.32165 timestamp: 1655028501.2598321 iteration: 25955 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19125 FastRCNN class loss: 0.09391 FastRCNN total loss: 0.28516 L1 loss: 0.0000e+00 L2 loss: 0.90559 Learning rate: 0.02 Mask loss: 0.15157 RPN box loss: 0.03483 RPN score loss: 0.0072 RPN total loss: 0.04203 Total loss: 1.38435 timestamp: 1655028504.7443626 iteration: 25960 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21816 FastRCNN class loss: 0.09762 FastRCNN total loss: 0.31578 L1 loss: 0.0000e+00 L2 loss: 0.90544 Learning rate: 0.02 Mask loss: 0.14285 RPN box loss: 0.01504 RPN score loss: 0.00807 RPN total loss: 0.02311 Total loss: 1.38719 timestamp: 1655028508.0401042 iteration: 25965 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21352 FastRCNN class loss: 0.12384 FastRCNN total loss: 0.33736 L1 loss: 0.0000e+00 L2 loss: 0.90529 Learning rate: 0.02 Mask loss: 0.21148 RPN box loss: 0.02562 RPN score loss: 0.02162 RPN total loss: 0.04725 Total loss: 1.50137 timestamp: 1655028511.4584966 iteration: 25970 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11247 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.162 L1 loss: 0.0000e+00 L2 loss: 0.90515 Learning rate: 0.02 Mask loss: 0.12761 RPN box loss: 0.01231 RPN score loss: 0.00111 RPN total loss: 0.01342 Total loss: 1.20818 timestamp: 1655028514.7637656 iteration: 25975 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14081 FastRCNN class loss: 0.10294 FastRCNN total loss: 0.24375 L1 loss: 0.0000e+00 L2 loss: 0.90501 Learning rate: 0.02 Mask loss: 0.27503 RPN box loss: 0.07263 RPN score loss: 0.00939 RPN total loss: 0.08202 Total loss: 1.50582 timestamp: 1655028518.1124582 iteration: 25980 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.1827 L1 loss: 0.0000e+00 L2 loss: 0.90488 Learning rate: 0.02 Mask loss: 0.17918 RPN box loss: 0.04283 RPN score loss: 0.00457 RPN total loss: 0.0474 Total loss: 1.31416 timestamp: 1655028521.5357306 iteration: 25985 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.20343 L1 loss: 0.0000e+00 L2 loss: 0.90474 Learning rate: 0.02 Mask loss: 0.18584 RPN box loss: 0.02417 RPN score loss: 0.00503 RPN total loss: 0.0292 Total loss: 1.32321 timestamp: 1655028524.8246655 iteration: 25990 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20728 FastRCNN class loss: 0.11393 FastRCNN total loss: 0.32121 L1 loss: 0.0000e+00 L2 loss: 0.90458 Learning rate: 0.02 Mask loss: 0.15459 RPN box loss: 0.05985 RPN score loss: 0.00371 RPN total loss: 0.06357 Total loss: 1.44394 timestamp: 1655028528.1999452 iteration: 25995 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06029 FastRCNN class loss: 0.02924 FastRCNN total loss: 0.08953 L1 loss: 0.0000e+00 L2 loss: 0.90445 Learning rate: 0.02 Mask loss: 0.15042 RPN box loss: 0.00102 RPN score loss: 0.00182 RPN total loss: 0.00284 Total loss: 1.14724 timestamp: 1655028531.4971004 iteration: 26000 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.13839 L1 loss: 0.0000e+00 L2 loss: 0.9043 Learning rate: 0.02 Mask loss: 0.20242 RPN box loss: 0.02327 RPN score loss: 0.00235 RPN total loss: 0.02561 Total loss: 1.27073 timestamp: 1655028534.8973637 iteration: 26005 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1255 FastRCNN class loss: 0.07528 FastRCNN total loss: 0.20078 L1 loss: 0.0000e+00 L2 loss: 0.90416 Learning rate: 0.02 Mask loss: 0.11004 RPN box loss: 0.02224 RPN score loss: 0.0035 RPN total loss: 0.02574 Total loss: 1.24072 timestamp: 1655028538.1896114 iteration: 26010 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16832 FastRCNN class loss: 0.15955 FastRCNN total loss: 0.32787 L1 loss: 0.0000e+00 L2 loss: 0.90401 Learning rate: 0.02 Mask loss: 0.21304 RPN box loss: 0.03758 RPN score loss: 0.0067 RPN total loss: 0.04428 Total loss: 1.4892 timestamp: 1655028541.5820625 iteration: 26015 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13332 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.22326 L1 loss: 0.0000e+00 L2 loss: 0.90386 Learning rate: 0.02 Mask loss: 0.16806 RPN box loss: 0.03916 RPN score loss: 0.0099 RPN total loss: 0.04906 Total loss: 1.34424 timestamp: 1655028544.9789104 iteration: 26020 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14592 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.23151 L1 loss: 0.0000e+00 L2 loss: 0.90372 Learning rate: 0.02 Mask loss: 0.17012 RPN box loss: 0.02241 RPN score loss: 0.00863 RPN total loss: 0.03105 Total loss: 1.33639 timestamp: 1655028548.2612784 iteration: 26025 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24592 FastRCNN class loss: 0.05413 FastRCNN total loss: 0.30005 L1 loss: 0.0000e+00 L2 loss: 0.90358 Learning rate: 0.02 Mask loss: 0.13201 RPN box loss: 0.04252 RPN score loss: 0.01085 RPN total loss: 0.05336 Total loss: 1.389 timestamp: 1655028551.528357 iteration: 26030 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13787 FastRCNN class loss: 0.079 FastRCNN total loss: 0.21688 L1 loss: 0.0000e+00 L2 loss: 0.90344 Learning rate: 0.02 Mask loss: 0.30427 RPN box loss: 0.04979 RPN score loss: 0.00311 RPN total loss: 0.0529 Total loss: 1.47749 timestamp: 1655028554.8527026 iteration: 26035 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14631 FastRCNN class loss: 0.11789 FastRCNN total loss: 0.2642 L1 loss: 0.0000e+00 L2 loss: 0.90331 Learning rate: 0.02 Mask loss: 0.17219 RPN box loss: 0.03617 RPN score loss: 0.01803 RPN total loss: 0.05421 Total loss: 1.3939 timestamp: 1655028558.1565282 iteration: 26040 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13489 FastRCNN class loss: 0.07584 FastRCNN total loss: 0.21073 L1 loss: 0.0000e+00 L2 loss: 0.90315 Learning rate: 0.02 Mask loss: 0.15539 RPN box loss: 0.01679 RPN score loss: 0.00586 RPN total loss: 0.02265 Total loss: 1.29191 timestamp: 1655028561.4036086 iteration: 26045 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18694 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.29386 L1 loss: 0.0000e+00 L2 loss: 0.90299 Learning rate: 0.02 Mask loss: 0.25209 RPN box loss: 0.05176 RPN score loss: 0.00907 RPN total loss: 0.06083 Total loss: 1.50977 timestamp: 1655028564.558564 iteration: 26050 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.1768 L1 loss: 0.0000e+00 L2 loss: 0.90284 Learning rate: 0.02 Mask loss: 0.16794 RPN box loss: 0.06718 RPN score loss: 0.00853 RPN total loss: 0.07571 Total loss: 1.32328 timestamp: 1655028567.7208686 iteration: 26055 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.05314 FastRCNN total loss: 0.15586 L1 loss: 0.0000e+00 L2 loss: 0.90269 Learning rate: 0.02 Mask loss: 0.1233 RPN box loss: 0.07015 RPN score loss: 0.00274 RPN total loss: 0.07289 Total loss: 1.25473 timestamp: 1655028570.9902582 iteration: 26060 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14864 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.23426 L1 loss: 0.0000e+00 L2 loss: 0.90256 Learning rate: 0.02 Mask loss: 0.14749 RPN box loss: 0.0577 RPN score loss: 0.01791 RPN total loss: 0.07561 Total loss: 1.35992 timestamp: 1655028574.2383149 iteration: 26065 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.09321 FastRCNN total loss: 0.22461 L1 loss: 0.0000e+00 L2 loss: 0.90243 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.02177 RPN score loss: 0.00496 RPN total loss: 0.02673 Total loss: 1.29672 timestamp: 1655028577.4970744 iteration: 26070 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20126 FastRCNN class loss: 0.13666 FastRCNN total loss: 0.33791 L1 loss: 0.0000e+00 L2 loss: 0.90228 Learning rate: 0.02 Mask loss: 0.16362 RPN box loss: 0.04912 RPN score loss: 0.00319 RPN total loss: 0.05232 Total loss: 1.45613 timestamp: 1655028580.7946086 iteration: 26075 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14755 FastRCNN class loss: 0.06504 FastRCNN total loss: 0.2126 L1 loss: 0.0000e+00 L2 loss: 0.90211 Learning rate: 0.02 Mask loss: 0.17125 RPN box loss: 0.01756 RPN score loss: 0.01137 RPN total loss: 0.02893 Total loss: 1.31489 timestamp: 1655028584.0314946 iteration: 26080 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11789 FastRCNN class loss: 0.05813 FastRCNN total loss: 0.17602 L1 loss: 0.0000e+00 L2 loss: 0.90198 Learning rate: 0.02 Mask loss: 0.12434 RPN box loss: 0.01223 RPN score loss: 0.00303 RPN total loss: 0.01526 Total loss: 1.21759 timestamp: 1655028587.3289118 iteration: 26085 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07621 FastRCNN class loss: 0.04889 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.90182 Learning rate: 0.02 Mask loss: 0.1623 RPN box loss: 0.03503 RPN score loss: 0.00881 RPN total loss: 0.04385 Total loss: 1.23306 timestamp: 1655028590.6116843 iteration: 26090 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15746 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.22099 L1 loss: 0.0000e+00 L2 loss: 0.90169 Learning rate: 0.02 Mask loss: 0.1892 RPN box loss: 0.02878 RPN score loss: 0.00591 RPN total loss: 0.03469 Total loss: 1.34657 timestamp: 1655028593.8403604 iteration: 26095 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13073 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.20772 L1 loss: 0.0000e+00 L2 loss: 0.90156 Learning rate: 0.02 Mask loss: 0.27975 RPN box loss: 0.0497 RPN score loss: 0.00579 RPN total loss: 0.05549 Total loss: 1.44452 timestamp: 1655028597.0979846 iteration: 26100 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13738 FastRCNN class loss: 0.08184 FastRCNN total loss: 0.21923 L1 loss: 0.0000e+00 L2 loss: 0.90142 Learning rate: 0.02 Mask loss: 0.16122 RPN box loss: 0.02753 RPN score loss: 0.0104 RPN total loss: 0.03793 Total loss: 1.3198 timestamp: 1655028600.382345 iteration: 26105 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20661 FastRCNN class loss: 0.09024 FastRCNN total loss: 0.29685 L1 loss: 0.0000e+00 L2 loss: 0.9013 Learning rate: 0.02 Mask loss: 0.19368 RPN box loss: 0.03216 RPN score loss: 0.00902 RPN total loss: 0.04118 Total loss: 1.43301 timestamp: 1655028603.7082145 iteration: 26110 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11516 FastRCNN class loss: 0.06301 FastRCNN total loss: 0.17817 L1 loss: 0.0000e+00 L2 loss: 0.90116 Learning rate: 0.02 Mask loss: 0.09732 RPN box loss: 0.00738 RPN score loss: 0.00176 RPN total loss: 0.00914 Total loss: 1.18579 timestamp: 1655028606.9862 iteration: 26115 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10476 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.15907 L1 loss: 0.0000e+00 L2 loss: 0.90101 Learning rate: 0.02 Mask loss: 0.17319 RPN box loss: 0.05038 RPN score loss: 0.01593 RPN total loss: 0.06631 Total loss: 1.29958 timestamp: 1655028610.2962303 iteration: 26120 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19724 FastRCNN class loss: 0.10142 FastRCNN total loss: 0.29866 L1 loss: 0.0000e+00 L2 loss: 0.90086 Learning rate: 0.02 Mask loss: 0.13619 RPN box loss: 0.02451 RPN score loss: 0.00964 RPN total loss: 0.03415 Total loss: 1.36986 timestamp: 1655028613.6759255 iteration: 26125 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1446 FastRCNN class loss: 0.09518 FastRCNN total loss: 0.23978 L1 loss: 0.0000e+00 L2 loss: 0.9007 Learning rate: 0.02 Mask loss: 0.15303 RPN box loss: 0.02244 RPN score loss: 0.00524 RPN total loss: 0.02767 Total loss: 1.32118 timestamp: 1655028617.004769 iteration: 26130 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25414 FastRCNN class loss: 0.10304 FastRCNN total loss: 0.35717 L1 loss: 0.0000e+00 L2 loss: 0.90056 Learning rate: 0.02 Mask loss: 0.22962 RPN box loss: 0.05984 RPN score loss: 0.01053 RPN total loss: 0.07037 Total loss: 1.55772 timestamp: 1655028620.3340118 iteration: 26135 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10487 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.18661 L1 loss: 0.0000e+00 L2 loss: 0.90044 Learning rate: 0.02 Mask loss: 0.13939 RPN box loss: 0.03059 RPN score loss: 0.00351 RPN total loss: 0.0341 Total loss: 1.26054 timestamp: 1655028623.652114 iteration: 26140 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.08494 FastRCNN total loss: 0.2155 L1 loss: 0.0000e+00 L2 loss: 0.90029 Learning rate: 0.02 Mask loss: 0.09615 RPN box loss: 0.01674 RPN score loss: 0.00297 RPN total loss: 0.01971 Total loss: 1.23165 timestamp: 1655028626.939948 iteration: 26145 throughput: 24.1 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18431 FastRCNN class loss: 0.1209 FastRCNN total loss: 0.30521 L1 loss: 0.0000e+00 L2 loss: 0.90015 Learning rate: 0.02 Mask loss: 0.17903 RPN box loss: 0.01979 RPN score loss: 0.00353 RPN total loss: 0.02332 Total loss: 1.40771 timestamp: 1655028630.2633939 iteration: 26150 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10273 FastRCNN class loss: 0.07569 FastRCNN total loss: 0.17842 L1 loss: 0.0000e+00 L2 loss: 0.90001 Learning rate: 0.02 Mask loss: 0.15688 RPN box loss: 0.01694 RPN score loss: 0.00122 RPN total loss: 0.01816 Total loss: 1.25347 timestamp: 1655028633.5424676 iteration: 26155 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15525 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.25005 L1 loss: 0.0000e+00 L2 loss: 0.89986 Learning rate: 0.02 Mask loss: 0.16667 RPN box loss: 0.02572 RPN score loss: 0.00554 RPN total loss: 0.03126 Total loss: 1.34783 timestamp: 1655028636.8098247 iteration: 26160 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15201 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.22285 L1 loss: 0.0000e+00 L2 loss: 0.89974 Learning rate: 0.02 Mask loss: 0.1208 RPN box loss: 0.0073 RPN score loss: 0.00247 RPN total loss: 0.00976 Total loss: 1.25316 timestamp: 1655028640.0713527 iteration: 26165 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.06374 FastRCNN total loss: 0.15204 L1 loss: 0.0000e+00 L2 loss: 0.89962 Learning rate: 0.02 Mask loss: 0.17685 RPN box loss: 0.05365 RPN score loss: 0.01304 RPN total loss: 0.06668 Total loss: 1.29519 timestamp: 1655028643.3066578 iteration: 26170 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20468 FastRCNN class loss: 0.14732 FastRCNN total loss: 0.352 L1 loss: 0.0000e+00 L2 loss: 0.89948 Learning rate: 0.02 Mask loss: 0.16894 RPN box loss: 0.04192 RPN score loss: 0.01321 RPN total loss: 0.05513 Total loss: 1.47555 timestamp: 1655028646.700587 iteration: 26175 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21475 FastRCNN class loss: 0.10939 FastRCNN total loss: 0.32415 L1 loss: 0.0000e+00 L2 loss: 0.89936 Learning rate: 0.02 Mask loss: 0.24191 RPN box loss: 0.03791 RPN score loss: 0.00421 RPN total loss: 0.04212 Total loss: 1.50754 timestamp: 1655028649.989067 iteration: 26180 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12225 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 0.89921 Learning rate: 0.02 Mask loss: 0.14006 RPN box loss: 0.01967 RPN score loss: 0.00698 RPN total loss: 0.02665 Total loss: 1.26313 timestamp: 1655028653.3446953 iteration: 26185 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16692 FastRCNN class loss: 0.15323 FastRCNN total loss: 0.32016 L1 loss: 0.0000e+00 L2 loss: 0.89905 Learning rate: 0.02 Mask loss: 0.24008 RPN box loss: 0.04838 RPN score loss: 0.01139 RPN total loss: 0.05977 Total loss: 1.51905 timestamp: 1655028656.610828 iteration: 26190 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11114 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.18337 L1 loss: 0.0000e+00 L2 loss: 0.89891 Learning rate: 0.02 Mask loss: 0.21678 RPN box loss: 0.0299 RPN score loss: 0.00419 RPN total loss: 0.03409 Total loss: 1.33315 timestamp: 1655028659.8675928 iteration: 26195 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.05557 FastRCNN total loss: 0.17183 L1 loss: 0.0000e+00 L2 loss: 0.89879 Learning rate: 0.02 Mask loss: 0.15166 RPN box loss: 0.0191 RPN score loss: 0.0022 RPN total loss: 0.0213 Total loss: 1.24358 timestamp: 1655028663.1207988 iteration: 26200 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10433 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.17151 L1 loss: 0.0000e+00 L2 loss: 0.89864 Learning rate: 0.02 Mask loss: 0.12647 RPN box loss: 0.00865 RPN score loss: 0.0019 RPN total loss: 0.01055 Total loss: 1.20718 timestamp: 1655028666.3606868 iteration: 26205 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10458 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.18065 L1 loss: 0.0000e+00 L2 loss: 0.89849 Learning rate: 0.02 Mask loss: 0.12311 RPN box loss: 0.03736 RPN score loss: 0.01149 RPN total loss: 0.04885 Total loss: 1.2511 timestamp: 1655028669.633904 iteration: 26210 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12799 FastRCNN class loss: 0.09882 FastRCNN total loss: 0.22682 L1 loss: 0.0000e+00 L2 loss: 0.89837 Learning rate: 0.02 Mask loss: 0.1768 RPN box loss: 0.02163 RPN score loss: 0.00745 RPN total loss: 0.02908 Total loss: 1.33107 timestamp: 1655028672.953897 iteration: 26215 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10754 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.17938 L1 loss: 0.0000e+00 L2 loss: 0.89825 Learning rate: 0.02 Mask loss: 0.15878 RPN box loss: 0.04997 RPN score loss: 0.00723 RPN total loss: 0.0572 Total loss: 1.29361 timestamp: 1655028676.1830776 iteration: 26220 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13689 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.22543 L1 loss: 0.0000e+00 L2 loss: 0.89808 Learning rate: 0.02 Mask loss: 0.19029 RPN box loss: 0.0717 RPN score loss: 0.01173 RPN total loss: 0.08343 Total loss: 1.39723 timestamp: 1655028679.4910433 iteration: 26225 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14463 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.21094 L1 loss: 0.0000e+00 L2 loss: 0.89795 Learning rate: 0.02 Mask loss: 0.1798 RPN box loss: 0.03261 RPN score loss: 0.00977 RPN total loss: 0.04238 Total loss: 1.33107 timestamp: 1655028682.8345938 iteration: 26230 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18115 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.2778 L1 loss: 0.0000e+00 L2 loss: 0.89782 Learning rate: 0.02 Mask loss: 0.17819 RPN box loss: 0.06069 RPN score loss: 0.00691 RPN total loss: 0.0676 Total loss: 1.42141 timestamp: 1655028686.055261 iteration: 26235 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14547 FastRCNN class loss: 0.09886 FastRCNN total loss: 0.24433 L1 loss: 0.0000e+00 L2 loss: 0.89767 Learning rate: 0.02 Mask loss: 0.15012 RPN box loss: 0.02182 RPN score loss: 0.01406 RPN total loss: 0.03589 Total loss: 1.32801 timestamp: 1655028689.3305757 iteration: 26240 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18339 FastRCNN class loss: 0.12326 FastRCNN total loss: 0.30666 L1 loss: 0.0000e+00 L2 loss: 0.89752 Learning rate: 0.02 Mask loss: 0.18419 RPN box loss: 0.02153 RPN score loss: 0.0151 RPN total loss: 0.03663 Total loss: 1.425 timestamp: 1655028692.6059892 iteration: 26245 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17014 FastRCNN class loss: 0.05014 FastRCNN total loss: 0.22028 L1 loss: 0.0000e+00 L2 loss: 0.89736 Learning rate: 0.02 Mask loss: 0.12163 RPN box loss: 0.01089 RPN score loss: 0.00248 RPN total loss: 0.01336 Total loss: 1.25263 timestamp: 1655028695.9549215 iteration: 26250 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10334 FastRCNN class loss: 0.04599 FastRCNN total loss: 0.14933 L1 loss: 0.0000e+00 L2 loss: 0.89724 Learning rate: 0.02 Mask loss: 0.1531 RPN box loss: 0.02399 RPN score loss: 0.00242 RPN total loss: 0.02641 Total loss: 1.22608 timestamp: 1655028699.2396219 iteration: 26255 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12939 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.1772 L1 loss: 0.0000e+00 L2 loss: 0.89711 Learning rate: 0.02 Mask loss: 0.12864 RPN box loss: 0.01639 RPN score loss: 0.00452 RPN total loss: 0.02091 Total loss: 1.22385 timestamp: 1655028702.5559065 iteration: 26260 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15116 FastRCNN class loss: 0.1959 FastRCNN total loss: 0.34707 L1 loss: 0.0000e+00 L2 loss: 0.89694 Learning rate: 0.02 Mask loss: 0.19658 RPN box loss: 0.04482 RPN score loss: 0.00544 RPN total loss: 0.05026 Total loss: 1.49085 timestamp: 1655028705.818734 iteration: 26265 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17717 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.2724 L1 loss: 0.0000e+00 L2 loss: 0.89678 Learning rate: 0.02 Mask loss: 0.17897 RPN box loss: 0.02817 RPN score loss: 0.00861 RPN total loss: 0.03679 Total loss: 1.38495 timestamp: 1655028709.0749168 iteration: 26270 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14066 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.20832 L1 loss: 0.0000e+00 L2 loss: 0.89664 Learning rate: 0.02 Mask loss: 0.1304 RPN box loss: 0.02924 RPN score loss: 0.006 RPN total loss: 0.03524 Total loss: 1.27059 timestamp: 1655028712.3923893 iteration: 26275 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13541 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.21203 L1 loss: 0.0000e+00 L2 loss: 0.89649 Learning rate: 0.02 Mask loss: 0.13703 RPN box loss: 0.027 RPN score loss: 0.00452 RPN total loss: 0.03151 Total loss: 1.27706 timestamp: 1655028715.6841424 iteration: 26280 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14266 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.20506 L1 loss: 0.0000e+00 L2 loss: 0.89633 Learning rate: 0.02 Mask loss: 0.14155 RPN box loss: 0.00936 RPN score loss: 0.0041 RPN total loss: 0.01346 Total loss: 1.2564 timestamp: 1655028718.9865618 iteration: 26285 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14414 FastRCNN class loss: 0.0985 FastRCNN total loss: 0.24263 L1 loss: 0.0000e+00 L2 loss: 0.89621 Learning rate: 0.02 Mask loss: 0.14462 RPN box loss: 0.01714 RPN score loss: 0.00982 RPN total loss: 0.02696 Total loss: 1.31042 timestamp: 1655028722.2321546 iteration: 26290 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0997 FastRCNN class loss: 0.04992 FastRCNN total loss: 0.14963 L1 loss: 0.0000e+00 L2 loss: 0.89608 Learning rate: 0.02 Mask loss: 0.25308 RPN box loss: 0.05526 RPN score loss: 0.0076 RPN total loss: 0.06286 Total loss: 1.36165 timestamp: 1655028725.5241017 iteration: 26295 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24172 FastRCNN class loss: 0.092 FastRCNN total loss: 0.33372 L1 loss: 0.0000e+00 L2 loss: 0.89593 Learning rate: 0.02 Mask loss: 0.20094 RPN box loss: 0.04347 RPN score loss: 0.0083 RPN total loss: 0.05177 Total loss: 1.48235 timestamp: 1655028728.8219929 iteration: 26300 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21497 FastRCNN class loss: 0.1214 FastRCNN total loss: 0.33638 L1 loss: 0.0000e+00 L2 loss: 0.89578 Learning rate: 0.02 Mask loss: 0.19465 RPN box loss: 0.02833 RPN score loss: 0.00241 RPN total loss: 0.03074 Total loss: 1.45755 timestamp: 1655028732.1357422 iteration: 26305 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1494 FastRCNN class loss: 0.15935 FastRCNN total loss: 0.30875 L1 loss: 0.0000e+00 L2 loss: 0.89563 Learning rate: 0.02 Mask loss: 0.19745 RPN box loss: 0.04872 RPN score loss: 0.0122 RPN total loss: 0.06092 Total loss: 1.46276 timestamp: 1655028735.434612 iteration: 26310 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18068 FastRCNN class loss: 0.13076 FastRCNN total loss: 0.31145 L1 loss: 0.0000e+00 L2 loss: 0.89551 Learning rate: 0.02 Mask loss: 0.2866 RPN box loss: 0.03255 RPN score loss: 0.01058 RPN total loss: 0.04313 Total loss: 1.53668 timestamp: 1655028738.755448 iteration: 26315 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12731 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 0.89537 Learning rate: 0.02 Mask loss: 0.25007 RPN box loss: 0.01181 RPN score loss: 0.0071 RPN total loss: 0.01891 Total loss: 1.37124 timestamp: 1655028742.0450692 iteration: 26320 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17461 FastRCNN class loss: 0.15696 FastRCNN total loss: 0.33157 L1 loss: 0.0000e+00 L2 loss: 0.89522 Learning rate: 0.02 Mask loss: 0.19129 RPN box loss: 0.048 RPN score loss: 0.00451 RPN total loss: 0.05251 Total loss: 1.47059 timestamp: 1655028745.3865016 iteration: 26325 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14135 FastRCNN class loss: 0.06321 FastRCNN total loss: 0.20456 L1 loss: 0.0000e+00 L2 loss: 0.89507 Learning rate: 0.02 Mask loss: 0.25373 RPN box loss: 0.02259 RPN score loss: 0.0075 RPN total loss: 0.03009 Total loss: 1.38345 timestamp: 1655028748.6551394 iteration: 26330 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18098 FastRCNN class loss: 0.08991 FastRCNN total loss: 0.27089 L1 loss: 0.0000e+00 L2 loss: 0.89494 Learning rate: 0.02 Mask loss: 0.23109 RPN box loss: 0.05037 RPN score loss: 0.00889 RPN total loss: 0.05926 Total loss: 1.45618 timestamp: 1655028751.9023252 iteration: 26335 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13736 FastRCNN class loss: 0.10322 FastRCNN total loss: 0.24058 L1 loss: 0.0000e+00 L2 loss: 0.8948 Learning rate: 0.02 Mask loss: 0.15544 RPN box loss: 0.06352 RPN score loss: 0.00947 RPN total loss: 0.07299 Total loss: 1.36381 timestamp: 1655028755.1354423 iteration: 26340 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07636 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.13204 L1 loss: 0.0000e+00 L2 loss: 0.89465 Learning rate: 0.02 Mask loss: 0.15442 RPN box loss: 0.01043 RPN score loss: 0.00235 RPN total loss: 0.01278 Total loss: 1.19389 timestamp: 1655028758.3870213 iteration: 26345 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15931 FastRCNN class loss: 0.10865 FastRCNN total loss: 0.26796 L1 loss: 0.0000e+00 L2 loss: 0.89452 Learning rate: 0.02 Mask loss: 0.18713 RPN box loss: 0.03978 RPN score loss: 0.00414 RPN total loss: 0.04392 Total loss: 1.39353 timestamp: 1655028761.6223762 iteration: 26350 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12767 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.21932 L1 loss: 0.0000e+00 L2 loss: 0.89435 Learning rate: 0.02 Mask loss: 0.15176 RPN box loss: 0.08825 RPN score loss: 0.01028 RPN total loss: 0.09853 Total loss: 1.36397 timestamp: 1655028764.8663335 iteration: 26355 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18862 FastRCNN class loss: 0.14532 FastRCNN total loss: 0.33394 L1 loss: 0.0000e+00 L2 loss: 0.89418 Learning rate: 0.02 Mask loss: 0.16557 RPN box loss: 0.05346 RPN score loss: 0.01275 RPN total loss: 0.06622 Total loss: 1.4599 timestamp: 1655028768.1778283 iteration: 26360 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19018 FastRCNN class loss: 0.0631 FastRCNN total loss: 0.25328 L1 loss: 0.0000e+00 L2 loss: 0.89403 Learning rate: 0.02 Mask loss: 0.13778 RPN box loss: 0.03034 RPN score loss: 0.00986 RPN total loss: 0.0402 Total loss: 1.32529 timestamp: 1655028771.4687831 iteration: 26365 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13959 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.20117 L1 loss: 0.0000e+00 L2 loss: 0.89392 Learning rate: 0.02 Mask loss: 0.17535 RPN box loss: 0.0992 RPN score loss: 0.0134 RPN total loss: 0.1126 Total loss: 1.38305 timestamp: 1655028774.7511442 iteration: 26370 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18076 FastRCNN class loss: 0.1277 FastRCNN total loss: 0.30846 L1 loss: 0.0000e+00 L2 loss: 0.89377 Learning rate: 0.02 Mask loss: 0.20228 RPN box loss: 0.01118 RPN score loss: 0.00424 RPN total loss: 0.01542 Total loss: 1.41993 timestamp: 1655028777.9523075 iteration: 26375 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14796 FastRCNN class loss: 0.05573 FastRCNN total loss: 0.2037 L1 loss: 0.0000e+00 L2 loss: 0.89362 Learning rate: 0.02 Mask loss: 0.10682 RPN box loss: 0.00901 RPN score loss: 0.00507 RPN total loss: 0.01409 Total loss: 1.21823 timestamp: 1655028781.2017822 iteration: 26380 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13239 FastRCNN class loss: 0.07695 FastRCNN total loss: 0.20934 L1 loss: 0.0000e+00 L2 loss: 0.89348 Learning rate: 0.02 Mask loss: 0.13401 RPN box loss: 0.03131 RPN score loss: 0.0057 RPN total loss: 0.03701 Total loss: 1.27384 timestamp: 1655028784.5115705 iteration: 26385 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11681 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.17442 L1 loss: 0.0000e+00 L2 loss: 0.89335 Learning rate: 0.02 Mask loss: 0.20477 RPN box loss: 0.01408 RPN score loss: 0.00735 RPN total loss: 0.02142 Total loss: 1.29397 timestamp: 1655028787.7296593 iteration: 26390 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.15284 L1 loss: 0.0000e+00 L2 loss: 0.8932 Learning rate: 0.02 Mask loss: 0.18563 RPN box loss: 0.01848 RPN score loss: 0.0041 RPN total loss: 0.02257 Total loss: 1.25425 timestamp: 1655028791.0404336 iteration: 26395 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09492 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.17891 L1 loss: 0.0000e+00 L2 loss: 0.89306 Learning rate: 0.02 Mask loss: 0.1632 RPN box loss: 0.02448 RPN score loss: 0.02234 RPN total loss: 0.04682 Total loss: 1.28199 timestamp: 1655028794.3256333 iteration: 26400 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15492 FastRCNN class loss: 0.06993 FastRCNN total loss: 0.22486 L1 loss: 0.0000e+00 L2 loss: 0.89291 Learning rate: 0.02 Mask loss: 0.19475 RPN box loss: 0.02872 RPN score loss: 0.011 RPN total loss: 0.03971 Total loss: 1.35224 timestamp: 1655028797.5433815 iteration: 26405 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15748 FastRCNN class loss: 0.1095 FastRCNN total loss: 0.26698 L1 loss: 0.0000e+00 L2 loss: 0.89275 Learning rate: 0.02 Mask loss: 0.15189 RPN box loss: 0.03864 RPN score loss: 0.02366 RPN total loss: 0.0623 Total loss: 1.37391 timestamp: 1655028800.8329034 iteration: 26410 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12383 FastRCNN class loss: 0.08641 FastRCNN total loss: 0.21024 L1 loss: 0.0000e+00 L2 loss: 0.89264 Learning rate: 0.02 Mask loss: 0.16849 RPN box loss: 0.05666 RPN score loss: 0.00578 RPN total loss: 0.06244 Total loss: 1.33381 timestamp: 1655028804.0944276 iteration: 26415 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.08734 FastRCNN total loss: 0.20323 L1 loss: 0.0000e+00 L2 loss: 0.89251 Learning rate: 0.02 Mask loss: 0.20253 RPN box loss: 0.0398 RPN score loss: 0.0124 RPN total loss: 0.0522 Total loss: 1.35046 timestamp: 1655028807.429799 iteration: 26420 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10698 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.16976 L1 loss: 0.0000e+00 L2 loss: 0.89236 Learning rate: 0.02 Mask loss: 0.12359 RPN box loss: 0.04975 RPN score loss: 0.00441 RPN total loss: 0.05416 Total loss: 1.23987 timestamp: 1655028810.6781056 iteration: 26425 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20536 FastRCNN class loss: 0.13276 FastRCNN total loss: 0.33812 L1 loss: 0.0000e+00 L2 loss: 0.8922 Learning rate: 0.02 Mask loss: 0.22509 RPN box loss: 0.01729 RPN score loss: 0.00704 RPN total loss: 0.02434 Total loss: 1.47974 timestamp: 1655028813.9638886 iteration: 26430 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1506 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.2375 L1 loss: 0.0000e+00 L2 loss: 0.89207 Learning rate: 0.02 Mask loss: 0.13552 RPN box loss: 0.02388 RPN score loss: 0.00457 RPN total loss: 0.02845 Total loss: 1.29354 timestamp: 1655028817.208184 iteration: 26435 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15614 FastRCNN class loss: 0.11062 FastRCNN total loss: 0.26675 L1 loss: 0.0000e+00 L2 loss: 0.89193 Learning rate: 0.02 Mask loss: 0.23204 RPN box loss: 0.01876 RPN score loss: 0.00904 RPN total loss: 0.0278 Total loss: 1.41853 timestamp: 1655028820.4945316 iteration: 26440 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.07264 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 0.8918 Learning rate: 0.02 Mask loss: 0.17448 RPN box loss: 0.05006 RPN score loss: 0.00622 RPN total loss: 0.05629 Total loss: 1.31418 timestamp: 1655028823.7117624 iteration: 26445 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18836 FastRCNN class loss: 0.09061 FastRCNN total loss: 0.27897 L1 loss: 0.0000e+00 L2 loss: 0.89165 Learning rate: 0.02 Mask loss: 0.19234 RPN box loss: 0.0171 RPN score loss: 0.01258 RPN total loss: 0.02967 Total loss: 1.39263 timestamp: 1655028826.9082963 iteration: 26450 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17737 FastRCNN class loss: 0.11899 FastRCNN total loss: 0.29636 L1 loss: 0.0000e+00 L2 loss: 0.89152 Learning rate: 0.02 Mask loss: 0.26118 RPN box loss: 0.01872 RPN score loss: 0.01568 RPN total loss: 0.03439 Total loss: 1.48345 timestamp: 1655028830.1302018 iteration: 26455 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12314 FastRCNN class loss: 0.1038 FastRCNN total loss: 0.22695 L1 loss: 0.0000e+00 L2 loss: 0.89139 Learning rate: 0.02 Mask loss: 0.19922 RPN box loss: 0.02724 RPN score loss: 0.0037 RPN total loss: 0.03095 Total loss: 1.3485 timestamp: 1655028833.3934646 iteration: 26460 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19518 FastRCNN class loss: 0.09918 FastRCNN total loss: 0.29435 L1 loss: 0.0000e+00 L2 loss: 0.89122 Learning rate: 0.02 Mask loss: 0.16474 RPN box loss: 0.03451 RPN score loss: 0.00935 RPN total loss: 0.04386 Total loss: 1.39418 timestamp: 1655028836.7469914 iteration: 26465 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23686 FastRCNN class loss: 0.10091 FastRCNN total loss: 0.33778 L1 loss: 0.0000e+00 L2 loss: 0.89106 Learning rate: 0.02 Mask loss: 0.20044 RPN box loss: 0.01148 RPN score loss: 0.00473 RPN total loss: 0.01621 Total loss: 1.44548 timestamp: 1655028840.030612 iteration: 26470 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1167 FastRCNN class loss: 0.08551 FastRCNN total loss: 0.20221 L1 loss: 0.0000e+00 L2 loss: 0.89091 Learning rate: 0.02 Mask loss: 0.21189 RPN box loss: 0.01267 RPN score loss: 0.00666 RPN total loss: 0.01933 Total loss: 1.32434 timestamp: 1655028843.3218725 iteration: 26475 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11702 FastRCNN class loss: 0.0937 FastRCNN total loss: 0.21072 L1 loss: 0.0000e+00 L2 loss: 0.89075 Learning rate: 0.02 Mask loss: 0.1357 RPN box loss: 0.05955 RPN score loss: 0.0067 RPN total loss: 0.06625 Total loss: 1.30342 timestamp: 1655028846.544229 iteration: 26480 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1385 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.22207 L1 loss: 0.0000e+00 L2 loss: 0.89062 Learning rate: 0.02 Mask loss: 0.13754 RPN box loss: 0.01163 RPN score loss: 0.00428 RPN total loss: 0.01591 Total loss: 1.26614 timestamp: 1655028849.8562038 iteration: 26485 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12711 FastRCNN class loss: 0.07662 FastRCNN total loss: 0.20373 L1 loss: 0.0000e+00 L2 loss: 0.89048 Learning rate: 0.02 Mask loss: 0.15323 RPN box loss: 0.02603 RPN score loss: 0.00554 RPN total loss: 0.03157 Total loss: 1.27902 timestamp: 1655028853.1398785 iteration: 26490 throughput: 24.2 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17283 FastRCNN class loss: 0.11007 FastRCNN total loss: 0.28291 L1 loss: 0.0000e+00 L2 loss: 0.89035 Learning rate: 0.02 Mask loss: 0.17372 RPN box loss: 0.05722 RPN score loss: 0.01535 RPN total loss: 0.07257 Total loss: 1.41956 timestamp: 1655028856.3814836 iteration: 26495 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23461 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.31247 L1 loss: 0.0000e+00 L2 loss: 0.89022 Learning rate: 0.02 Mask loss: 0.15888 RPN box loss: 0.02326 RPN score loss: 0.00611 RPN total loss: 0.02937 Total loss: 1.39093 timestamp: 1655028859.6716506 iteration: 26500 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13696 FastRCNN class loss: 0.05425 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.89009 Learning rate: 0.02 Mask loss: 0.15415 RPN box loss: 0.02527 RPN score loss: 0.00734 RPN total loss: 0.03262 Total loss: 1.26807 timestamp: 1655028862.942525 iteration: 26505 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.16917 L1 loss: 0.0000e+00 L2 loss: 0.88994 Learning rate: 0.02 Mask loss: 0.2127 RPN box loss: 0.03927 RPN score loss: 0.00979 RPN total loss: 0.04906 Total loss: 1.32086 timestamp: 1655028866.1633449 iteration: 26510 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16229 FastRCNN class loss: 0.08179 FastRCNN total loss: 0.24408 L1 loss: 0.0000e+00 L2 loss: 0.8898 Learning rate: 0.02 Mask loss: 0.15114 RPN box loss: 0.04424 RPN score loss: 0.00927 RPN total loss: 0.05351 Total loss: 1.33853 timestamp: 1655028869.46738 iteration: 26515 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15283 FastRCNN class loss: 0.08168 FastRCNN total loss: 0.23451 L1 loss: 0.0000e+00 L2 loss: 0.88967 Learning rate: 0.02 Mask loss: 0.15849 RPN box loss: 0.01706 RPN score loss: 0.00755 RPN total loss: 0.02461 Total loss: 1.30727 timestamp: 1655028872.6630917 iteration: 26520 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13919 FastRCNN class loss: 0.08659 FastRCNN total loss: 0.22579 L1 loss: 0.0000e+00 L2 loss: 0.88955 Learning rate: 0.02 Mask loss: 0.14505 RPN box loss: 0.01674 RPN score loss: 0.00225 RPN total loss: 0.01899 Total loss: 1.27938 timestamp: 1655028875.9174032 iteration: 26525 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15317 FastRCNN class loss: 0.08308 FastRCNN total loss: 0.23624 L1 loss: 0.0000e+00 L2 loss: 0.88938 Learning rate: 0.02 Mask loss: 0.18188 RPN box loss: 0.01744 RPN score loss: 0.00706 RPN total loss: 0.0245 Total loss: 1.33201 timestamp: 1655028879.167169 iteration: 26530 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15589 FastRCNN class loss: 0.08607 FastRCNN total loss: 0.24196 L1 loss: 0.0000e+00 L2 loss: 0.88925 Learning rate: 0.02 Mask loss: 0.18586 RPN box loss: 0.0173 RPN score loss: 0.0071 RPN total loss: 0.0244 Total loss: 1.34148 timestamp: 1655028882.4233465 iteration: 26535 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15834 FastRCNN class loss: 0.11337 FastRCNN total loss: 0.27171 L1 loss: 0.0000e+00 L2 loss: 0.88913 Learning rate: 0.02 Mask loss: 0.2164 RPN box loss: 0.03683 RPN score loss: 0.00978 RPN total loss: 0.04661 Total loss: 1.42384 timestamp: 1655028885.6685355 iteration: 26540 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18036 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.27346 L1 loss: 0.0000e+00 L2 loss: 0.889 Learning rate: 0.02 Mask loss: 0.18195 RPN box loss: 0.03387 RPN score loss: 0.01638 RPN total loss: 0.05026 Total loss: 1.39466 timestamp: 1655028888.9627182 iteration: 26545 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17415 FastRCNN class loss: 0.12928 FastRCNN total loss: 0.30343 L1 loss: 0.0000e+00 L2 loss: 0.88884 Learning rate: 0.02 Mask loss: 0.22962 RPN box loss: 0.07795 RPN score loss: 0.04372 RPN total loss: 0.12166 Total loss: 1.54355 timestamp: 1655028892.222621 iteration: 26550 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08668 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.88869 Learning rate: 0.02 Mask loss: 0.14565 RPN box loss: 0.04392 RPN score loss: 0.0065 RPN total loss: 0.05042 Total loss: 1.23259 timestamp: 1655028895.5447686 iteration: 26555 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09059 FastRCNN class loss: 0.06153 FastRCNN total loss: 0.15213 L1 loss: 0.0000e+00 L2 loss: 0.88854 Learning rate: 0.02 Mask loss: 0.11989 RPN box loss: 0.02342 RPN score loss: 0.00424 RPN total loss: 0.02766 Total loss: 1.18822 timestamp: 1655028898.8498402 iteration: 26560 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12036 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.1829 L1 loss: 0.0000e+00 L2 loss: 0.88841 Learning rate: 0.02 Mask loss: 0.15485 RPN box loss: 0.03583 RPN score loss: 0.00423 RPN total loss: 0.04006 Total loss: 1.26622 timestamp: 1655028902.209228 iteration: 26565 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11355 FastRCNN class loss: 0.07641 FastRCNN total loss: 0.18996 L1 loss: 0.0000e+00 L2 loss: 0.88827 Learning rate: 0.02 Mask loss: 0.16442 RPN box loss: 0.04441 RPN score loss: 0.00479 RPN total loss: 0.04919 Total loss: 1.29185 timestamp: 1655028905.4900067 iteration: 26570 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11447 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.19373 L1 loss: 0.0000e+00 L2 loss: 0.88812 Learning rate: 0.02 Mask loss: 0.15292 RPN box loss: 0.04239 RPN score loss: 0.00528 RPN total loss: 0.04767 Total loss: 1.28244 timestamp: 1655028908.7759602 iteration: 26575 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10143 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.1563 L1 loss: 0.0000e+00 L2 loss: 0.88799 Learning rate: 0.02 Mask loss: 0.14384 RPN box loss: 0.02436 RPN score loss: 0.00286 RPN total loss: 0.02722 Total loss: 1.21535 timestamp: 1655028912.0193753 iteration: 26580 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07256 FastRCNN class loss: 0.04136 FastRCNN total loss: 0.11392 L1 loss: 0.0000e+00 L2 loss: 0.88785 Learning rate: 0.02 Mask loss: 0.13416 RPN box loss: 0.00574 RPN score loss: 0.00356 RPN total loss: 0.00931 Total loss: 1.14524 timestamp: 1655028915.297068 iteration: 26585 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.19292 L1 loss: 0.0000e+00 L2 loss: 0.8877 Learning rate: 0.02 Mask loss: 0.135 RPN box loss: 0.02585 RPN score loss: 0.01028 RPN total loss: 0.03613 Total loss: 1.25176 timestamp: 1655028918.5410256 iteration: 26590 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.22027 L1 loss: 0.0000e+00 L2 loss: 0.88757 Learning rate: 0.02 Mask loss: 0.19663 RPN box loss: 0.02573 RPN score loss: 0.00417 RPN total loss: 0.0299 Total loss: 1.33437 timestamp: 1655028921.764943 iteration: 26595 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17225 FastRCNN class loss: 0.1032 FastRCNN total loss: 0.27545 L1 loss: 0.0000e+00 L2 loss: 0.88744 Learning rate: 0.02 Mask loss: 0.13361 RPN box loss: 0.0511 RPN score loss: 0.01183 RPN total loss: 0.06293 Total loss: 1.35943 timestamp: 1655028925.0885775 iteration: 26600 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15061 FastRCNN class loss: 0.10347 FastRCNN total loss: 0.25408 L1 loss: 0.0000e+00 L2 loss: 0.88729 Learning rate: 0.02 Mask loss: 0.16938 RPN box loss: 0.06423 RPN score loss: 0.02609 RPN total loss: 0.09033 Total loss: 1.40107 timestamp: 1655028928.352749 iteration: 26605 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11962 FastRCNN class loss: 0.05383 FastRCNN total loss: 0.17345 L1 loss: 0.0000e+00 L2 loss: 0.88715 Learning rate: 0.02 Mask loss: 0.12804 RPN box loss: 0.02541 RPN score loss: 0.00403 RPN total loss: 0.02944 Total loss: 1.21808 timestamp: 1655028931.5884855 iteration: 26610 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19495 FastRCNN class loss: 0.10596 FastRCNN total loss: 0.30091 L1 loss: 0.0000e+00 L2 loss: 0.887 Learning rate: 0.02 Mask loss: 0.1632 RPN box loss: 0.04823 RPN score loss: 0.00523 RPN total loss: 0.05346 Total loss: 1.40457 timestamp: 1655028934.7614725 iteration: 26615 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13061 FastRCNN class loss: 0.12377 FastRCNN total loss: 0.25438 L1 loss: 0.0000e+00 L2 loss: 0.88686 Learning rate: 0.02 Mask loss: 0.15356 RPN box loss: 0.04352 RPN score loss: 0.01976 RPN total loss: 0.06328 Total loss: 1.35808 timestamp: 1655028938.0243971 iteration: 26620 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13909 FastRCNN class loss: 0.07456 FastRCNN total loss: 0.21365 L1 loss: 0.0000e+00 L2 loss: 0.88674 Learning rate: 0.02 Mask loss: 0.13258 RPN box loss: 0.08434 RPN score loss: 0.00468 RPN total loss: 0.08902 Total loss: 1.32199 timestamp: 1655028941.3269522 iteration: 26625 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10828 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.18929 L1 loss: 0.0000e+00 L2 loss: 0.88659 Learning rate: 0.02 Mask loss: 0.19045 RPN box loss: 0.0937 RPN score loss: 0.01317 RPN total loss: 0.10687 Total loss: 1.37321 timestamp: 1655028944.6055994 iteration: 26630 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13482 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.21609 L1 loss: 0.0000e+00 L2 loss: 0.88645 Learning rate: 0.02 Mask loss: 0.26178 RPN box loss: 0.02923 RPN score loss: 0.00512 RPN total loss: 0.03435 Total loss: 1.39867 timestamp: 1655028947.8600066 iteration: 26635 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.04904 FastRCNN total loss: 0.15174 L1 loss: 0.0000e+00 L2 loss: 0.88633 Learning rate: 0.02 Mask loss: 0.10801 RPN box loss: 0.04428 RPN score loss: 0.00835 RPN total loss: 0.05263 Total loss: 1.19871 timestamp: 1655028951.1983182 iteration: 26640 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1604 FastRCNN class loss: 0.09811 FastRCNN total loss: 0.25851 L1 loss: 0.0000e+00 L2 loss: 0.88618 Learning rate: 0.02 Mask loss: 0.20292 RPN box loss: 0.07966 RPN score loss: 0.01234 RPN total loss: 0.092 Total loss: 1.43962 timestamp: 1655028954.4776196 iteration: 26645 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17901 FastRCNN class loss: 0.13013 FastRCNN total loss: 0.30914 L1 loss: 0.0000e+00 L2 loss: 0.88603 Learning rate: 0.02 Mask loss: 0.16225 RPN box loss: 0.04013 RPN score loss: 0.01363 RPN total loss: 0.05376 Total loss: 1.41118 timestamp: 1655028957.6898813 iteration: 26650 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23811 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.31023 L1 loss: 0.0000e+00 L2 loss: 0.88587 Learning rate: 0.02 Mask loss: 0.13348 RPN box loss: 0.05101 RPN score loss: 0.01706 RPN total loss: 0.06807 Total loss: 1.39765 timestamp: 1655028960.892608 iteration: 26655 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12962 FastRCNN class loss: 0.10004 FastRCNN total loss: 0.22965 L1 loss: 0.0000e+00 L2 loss: 0.88572 Learning rate: 0.02 Mask loss: 0.18605 RPN box loss: 0.03231 RPN score loss: 0.01187 RPN total loss: 0.04418 Total loss: 1.3456 timestamp: 1655028964.2181234 iteration: 26660 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12964 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.19467 L1 loss: 0.0000e+00 L2 loss: 0.88561 Learning rate: 0.02 Mask loss: 0.13989 RPN box loss: 0.04569 RPN score loss: 0.00422 RPN total loss: 0.04991 Total loss: 1.27009 timestamp: 1655028967.419688 iteration: 26665 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11069 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.19281 L1 loss: 0.0000e+00 L2 loss: 0.88547 Learning rate: 0.02 Mask loss: 0.1859 RPN box loss: 0.01083 RPN score loss: 0.00155 RPN total loss: 0.01238 Total loss: 1.27657 timestamp: 1655028970.627081 iteration: 26670 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14159 FastRCNN class loss: 0.09635 FastRCNN total loss: 0.23794 L1 loss: 0.0000e+00 L2 loss: 0.88534 Learning rate: 0.02 Mask loss: 0.2018 RPN box loss: 0.02372 RPN score loss: 0.00313 RPN total loss: 0.02684 Total loss: 1.35192 timestamp: 1655028973.8794065 iteration: 26675 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21871 FastRCNN class loss: 0.12776 FastRCNN total loss: 0.34647 L1 loss: 0.0000e+00 L2 loss: 0.8852 Learning rate: 0.02 Mask loss: 0.19015 RPN box loss: 0.02324 RPN score loss: 0.00333 RPN total loss: 0.02657 Total loss: 1.44838 timestamp: 1655028977.1098342 iteration: 26680 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08673 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.14274 L1 loss: 0.0000e+00 L2 loss: 0.88507 Learning rate: 0.02 Mask loss: 0.15504 RPN box loss: 0.05065 RPN score loss: 0.01321 RPN total loss: 0.06386 Total loss: 1.24671 timestamp: 1655028980.4674137 iteration: 26685 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16836 FastRCNN class loss: 0.12715 FastRCNN total loss: 0.29551 L1 loss: 0.0000e+00 L2 loss: 0.88495 Learning rate: 0.02 Mask loss: 0.20473 RPN box loss: 0.03067 RPN score loss: 0.0104 RPN total loss: 0.04107 Total loss: 1.42626 timestamp: 1655028983.7331002 iteration: 26690 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19992 FastRCNN class loss: 0.08447 FastRCNN total loss: 0.28439 L1 loss: 0.0000e+00 L2 loss: 0.8848 Learning rate: 0.02 Mask loss: 0.12527 RPN box loss: 0.025 RPN score loss: 0.00804 RPN total loss: 0.03305 Total loss: 1.32752 timestamp: 1655028987.0654368 iteration: 26695 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17592 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.26942 L1 loss: 0.0000e+00 L2 loss: 0.88465 Learning rate: 0.02 Mask loss: 0.29707 RPN box loss: 0.03251 RPN score loss: 0.01103 RPN total loss: 0.04354 Total loss: 1.49468 timestamp: 1655028990.322398 iteration: 26700 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10854 FastRCNN class loss: 0.08177 FastRCNN total loss: 0.19031 L1 loss: 0.0000e+00 L2 loss: 0.88448 Learning rate: 0.02 Mask loss: 0.16627 RPN box loss: 0.02053 RPN score loss: 0.00286 RPN total loss: 0.02339 Total loss: 1.26445 timestamp: 1655028993.6605449 iteration: 26705 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1125 FastRCNN class loss: 0.08558 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.88432 Learning rate: 0.02 Mask loss: 0.12077 RPN box loss: 0.0137 RPN score loss: 0.00561 RPN total loss: 0.01931 Total loss: 1.22248 timestamp: 1655028996.9221961 iteration: 26710 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08456 FastRCNN class loss: 0.07237 FastRCNN total loss: 0.15693 L1 loss: 0.0000e+00 L2 loss: 0.88419 Learning rate: 0.02 Mask loss: 0.17695 RPN box loss: 0.1838 RPN score loss: 0.01486 RPN total loss: 0.19865 Total loss: 1.41672 timestamp: 1655029000.2070787 iteration: 26715 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12247 FastRCNN class loss: 0.08753 FastRCNN total loss: 0.21001 L1 loss: 0.0000e+00 L2 loss: 0.88406 Learning rate: 0.02 Mask loss: 0.19132 RPN box loss: 0.03483 RPN score loss: 0.0071 RPN total loss: 0.04193 Total loss: 1.32732 timestamp: 1655029003.4935741 iteration: 26720 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11032 FastRCNN class loss: 0.08828 FastRCNN total loss: 0.1986 L1 loss: 0.0000e+00 L2 loss: 0.88392 Learning rate: 0.02 Mask loss: 0.14404 RPN box loss: 0.10469 RPN score loss: 0.00229 RPN total loss: 0.10698 Total loss: 1.33354 timestamp: 1655029006.7780912 iteration: 26725 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14361 FastRCNN class loss: 0.10452 FastRCNN total loss: 0.24812 L1 loss: 0.0000e+00 L2 loss: 0.88378 Learning rate: 0.02 Mask loss: 0.17746 RPN box loss: 0.02319 RPN score loss: 0.00888 RPN total loss: 0.03207 Total loss: 1.34143 timestamp: 1655029010.0169618 iteration: 26730 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20188 FastRCNN class loss: 0.11898 FastRCNN total loss: 0.32086 L1 loss: 0.0000e+00 L2 loss: 0.88363 Learning rate: 0.02 Mask loss: 0.2564 RPN box loss: 0.08183 RPN score loss: 0.02745 RPN total loss: 0.10929 Total loss: 1.57018 timestamp: 1655029013.2813833 iteration: 26735 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13857 FastRCNN class loss: 0.07435 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 0.88352 Learning rate: 0.02 Mask loss: 0.08551 RPN box loss: 0.03536 RPN score loss: 0.00754 RPN total loss: 0.0429 Total loss: 1.22485 timestamp: 1655029016.5856879 iteration: 26740 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14228 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.22388 L1 loss: 0.0000e+00 L2 loss: 0.8834 Learning rate: 0.02 Mask loss: 0.26884 RPN box loss: 0.03317 RPN score loss: 0.01165 RPN total loss: 0.04482 Total loss: 1.42094 timestamp: 1655029019.9474587 iteration: 26745 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14352 FastRCNN class loss: 0.05262 FastRCNN total loss: 0.19614 L1 loss: 0.0000e+00 L2 loss: 0.88324 Learning rate: 0.02 Mask loss: 0.09892 RPN box loss: 0.06051 RPN score loss: 0.00293 RPN total loss: 0.06344 Total loss: 1.24175 timestamp: 1655029023.231673 iteration: 26750 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18214 FastRCNN class loss: 0.13645 FastRCNN total loss: 0.31859 L1 loss: 0.0000e+00 L2 loss: 0.88308 Learning rate: 0.02 Mask loss: 0.15277 RPN box loss: 0.01882 RPN score loss: 0.00375 RPN total loss: 0.02257 Total loss: 1.37701 timestamp: 1655029026.539303 iteration: 26755 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11618 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.20096 L1 loss: 0.0000e+00 L2 loss: 0.88295 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.03546 RPN score loss: 0.02088 RPN total loss: 0.05635 Total loss: 1.29761 timestamp: 1655029029.7845418 iteration: 26760 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10077 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.15024 L1 loss: 0.0000e+00 L2 loss: 0.8828 Learning rate: 0.02 Mask loss: 0.1146 RPN box loss: 0.04266 RPN score loss: 0.00204 RPN total loss: 0.0447 Total loss: 1.19235 timestamp: 1655029033.1456747 iteration: 26765 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10249 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.16782 L1 loss: 0.0000e+00 L2 loss: 0.88265 Learning rate: 0.02 Mask loss: 0.13976 RPN box loss: 0.02514 RPN score loss: 0.01083 RPN total loss: 0.03596 Total loss: 1.2262 timestamp: 1655029036.5027206 iteration: 26770 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15123 FastRCNN class loss: 0.07907 FastRCNN total loss: 0.2303 L1 loss: 0.0000e+00 L2 loss: 0.88251 Learning rate: 0.02 Mask loss: 0.15708 RPN box loss: 0.03706 RPN score loss: 0.01222 RPN total loss: 0.04928 Total loss: 1.31917 timestamp: 1655029039.852996 iteration: 26775 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08034 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.16433 L1 loss: 0.0000e+00 L2 loss: 0.88235 Learning rate: 0.02 Mask loss: 0.16722 RPN box loss: 0.01663 RPN score loss: 0.00352 RPN total loss: 0.02015 Total loss: 1.23405 timestamp: 1655029043.182001 iteration: 26780 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06505 FastRCNN class loss: 0.04456 FastRCNN total loss: 0.10961 L1 loss: 0.0000e+00 L2 loss: 0.88221 Learning rate: 0.02 Mask loss: 0.25161 RPN box loss: 0.02565 RPN score loss: 0.00354 RPN total loss: 0.02919 Total loss: 1.27262 timestamp: 1655029046.4572346 iteration: 26785 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07955 FastRCNN class loss: 0.0992 FastRCNN total loss: 0.17875 L1 loss: 0.0000e+00 L2 loss: 0.8821 Learning rate: 0.02 Mask loss: 0.09656 RPN box loss: 0.01197 RPN score loss: 0.00458 RPN total loss: 0.01655 Total loss: 1.17396 timestamp: 1655029049.7229645 iteration: 26790 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13456 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.20226 L1 loss: 0.0000e+00 L2 loss: 0.88199 Learning rate: 0.02 Mask loss: 0.12848 RPN box loss: 0.02138 RPN score loss: 0.005 RPN total loss: 0.02638 Total loss: 1.23911 timestamp: 1655029053.0398412 iteration: 26795 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16209 FastRCNN class loss: 0.09418 FastRCNN total loss: 0.25627 L1 loss: 0.0000e+00 L2 loss: 0.88183 Learning rate: 0.02 Mask loss: 0.12841 RPN box loss: 0.06061 RPN score loss: 0.00774 RPN total loss: 0.06835 Total loss: 1.33487 timestamp: 1655029056.4070807 iteration: 26800 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10469 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.16485 L1 loss: 0.0000e+00 L2 loss: 0.88169 Learning rate: 0.02 Mask loss: 0.18821 RPN box loss: 0.03216 RPN score loss: 0.00319 RPN total loss: 0.03534 Total loss: 1.27009 timestamp: 1655029059.7068958 iteration: 26805 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15509 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.22566 L1 loss: 0.0000e+00 L2 loss: 0.88155 Learning rate: 0.02 Mask loss: 0.18691 RPN box loss: 0.01874 RPN score loss: 0.0019 RPN total loss: 0.02064 Total loss: 1.31476 timestamp: 1655029063.006648 iteration: 26810 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0897 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.13913 L1 loss: 0.0000e+00 L2 loss: 0.88142 Learning rate: 0.02 Mask loss: 0.1346 RPN box loss: 0.02287 RPN score loss: 0.00183 RPN total loss: 0.0247 Total loss: 1.17984 timestamp: 1655029066.269525 iteration: 26815 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11178 FastRCNN class loss: 0.11743 FastRCNN total loss: 0.22921 L1 loss: 0.0000e+00 L2 loss: 0.88127 Learning rate: 0.02 Mask loss: 0.21243 RPN box loss: 0.02377 RPN score loss: 0.00912 RPN total loss: 0.03289 Total loss: 1.3558 timestamp: 1655029069.5493548 iteration: 26820 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13725 FastRCNN class loss: 0.06633 FastRCNN total loss: 0.20359 L1 loss: 0.0000e+00 L2 loss: 0.88115 Learning rate: 0.02 Mask loss: 0.12198 RPN box loss: 0.01321 RPN score loss: 0.00297 RPN total loss: 0.01618 Total loss: 1.22289 timestamp: 1655029072.7492864 iteration: 26825 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16387 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.22872 L1 loss: 0.0000e+00 L2 loss: 0.88103 Learning rate: 0.02 Mask loss: 0.15228 RPN box loss: 0.03817 RPN score loss: 0.00373 RPN total loss: 0.04189 Total loss: 1.30393 timestamp: 1655029076.0353634 iteration: 26830 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12085 FastRCNN class loss: 0.12121 FastRCNN total loss: 0.24206 L1 loss: 0.0000e+00 L2 loss: 0.88088 Learning rate: 0.02 Mask loss: 0.12136 RPN box loss: 0.02382 RPN score loss: 0.01166 RPN total loss: 0.03548 Total loss: 1.27978 timestamp: 1655029079.2573767 iteration: 26835 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12123 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.20796 L1 loss: 0.0000e+00 L2 loss: 0.88074 Learning rate: 0.02 Mask loss: 0.13555 RPN box loss: 0.04601 RPN score loss: 0.0099 RPN total loss: 0.05591 Total loss: 1.28016 timestamp: 1655029082.6164892 iteration: 26840 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0897 FastRCNN class loss: 0.07172 FastRCNN total loss: 0.16143 L1 loss: 0.0000e+00 L2 loss: 0.88059 Learning rate: 0.02 Mask loss: 0.21817 RPN box loss: 0.04572 RPN score loss: 0.00637 RPN total loss: 0.05209 Total loss: 1.31228 timestamp: 1655029085.9143617 iteration: 26845 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.23229 L1 loss: 0.0000e+00 L2 loss: 0.88042 Learning rate: 0.02 Mask loss: 0.15304 RPN box loss: 0.01256 RPN score loss: 0.00323 RPN total loss: 0.01578 Total loss: 1.28154 timestamp: 1655029089.2309036 iteration: 26850 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09428 FastRCNN class loss: 0.05148 FastRCNN total loss: 0.14576 L1 loss: 0.0000e+00 L2 loss: 0.88029 Learning rate: 0.02 Mask loss: 0.14786 RPN box loss: 0.00708 RPN score loss: 0.00474 RPN total loss: 0.01182 Total loss: 1.18573 timestamp: 1655029092.5434616 iteration: 26855 throughput: 24.3 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08909 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.13928 L1 loss: 0.0000e+00 L2 loss: 0.88014 Learning rate: 0.02 Mask loss: 0.26044 RPN box loss: 0.03104 RPN score loss: 0.00342 RPN total loss: 0.03445 Total loss: 1.31432 timestamp: 1655029095.8432045 iteration: 26860 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.114 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.19149 L1 loss: 0.0000e+00 L2 loss: 0.87998 Learning rate: 0.02 Mask loss: 0.14063 RPN box loss: 0.01495 RPN score loss: 0.00558 RPN total loss: 0.02053 Total loss: 1.23263 timestamp: 1655029099.129472 iteration: 26865 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20681 FastRCNN class loss: 0.09684 FastRCNN total loss: 0.30365 L1 loss: 0.0000e+00 L2 loss: 0.87984 Learning rate: 0.02 Mask loss: 0.21555 RPN box loss: 0.01918 RPN score loss: 0.01105 RPN total loss: 0.03022 Total loss: 1.42927 timestamp: 1655029102.3897808 iteration: 26870 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12672 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.17883 L1 loss: 0.0000e+00 L2 loss: 0.87973 Learning rate: 0.02 Mask loss: 0.20446 RPN box loss: 0.02934 RPN score loss: 0.00649 RPN total loss: 0.03583 Total loss: 1.29885 timestamp: 1655029105.750898 iteration: 26875 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15334 FastRCNN class loss: 0.05377 FastRCNN total loss: 0.20711 L1 loss: 0.0000e+00 L2 loss: 0.87962 Learning rate: 0.02 Mask loss: 0.13759 RPN box loss: 0.03146 RPN score loss: 0.00372 RPN total loss: 0.03518 Total loss: 1.2595 timestamp: 1655029109.0799935 iteration: 26880 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14706 FastRCNN class loss: 0.08555 FastRCNN total loss: 0.23261 L1 loss: 0.0000e+00 L2 loss: 0.87948 Learning rate: 0.02 Mask loss: 0.15207 RPN box loss: 0.02281 RPN score loss: 0.01254 RPN total loss: 0.03534 Total loss: 1.29951 timestamp: 1655029112.3394322 iteration: 26885 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10046 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.15658 L1 loss: 0.0000e+00 L2 loss: 0.87934 Learning rate: 0.02 Mask loss: 0.1487 RPN box loss: 0.02229 RPN score loss: 0.00628 RPN total loss: 0.02857 Total loss: 1.21319 timestamp: 1655029115.5611703 iteration: 26890 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16482 FastRCNN class loss: 0.08535 FastRCNN total loss: 0.25017 L1 loss: 0.0000e+00 L2 loss: 0.8792 Learning rate: 0.02 Mask loss: 0.18733 RPN box loss: 0.02698 RPN score loss: 0.01111 RPN total loss: 0.03809 Total loss: 1.35479 timestamp: 1655029118.8277538 iteration: 26895 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11613 FastRCNN class loss: 0.09424 FastRCNN total loss: 0.21036 L1 loss: 0.0000e+00 L2 loss: 0.87907 Learning rate: 0.02 Mask loss: 0.21792 RPN box loss: 0.10928 RPN score loss: 0.00911 RPN total loss: 0.11839 Total loss: 1.42574 timestamp: 1655029122.154582 iteration: 26900 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16975 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.26095 L1 loss: 0.0000e+00 L2 loss: 0.87893 Learning rate: 0.02 Mask loss: 0.17914 RPN box loss: 0.06523 RPN score loss: 0.02381 RPN total loss: 0.08904 Total loss: 1.40806 timestamp: 1655029125.4282186 iteration: 26905 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10924 FastRCNN class loss: 0.06703 FastRCNN total loss: 0.17627 L1 loss: 0.0000e+00 L2 loss: 0.87878 Learning rate: 0.02 Mask loss: 0.13568 RPN box loss: 0.02802 RPN score loss: 0.0028 RPN total loss: 0.03082 Total loss: 1.22154 timestamp: 1655029128.7416089 iteration: 26910 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13242 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.21468 L1 loss: 0.0000e+00 L2 loss: 0.87863 Learning rate: 0.02 Mask loss: 0.13839 RPN box loss: 0.01965 RPN score loss: 0.00381 RPN total loss: 0.02346 Total loss: 1.25515 timestamp: 1655029132.0417118 iteration: 26915 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19667 FastRCNN class loss: 0.10177 FastRCNN total loss: 0.29844 L1 loss: 0.0000e+00 L2 loss: 0.8785 Learning rate: 0.02 Mask loss: 0.20172 RPN box loss: 0.04691 RPN score loss: 0.0089 RPN total loss: 0.05581 Total loss: 1.43447 timestamp: 1655029135.3313882 iteration: 26920 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09237 FastRCNN class loss: 0.05672 FastRCNN total loss: 0.14908 L1 loss: 0.0000e+00 L2 loss: 0.87837 Learning rate: 0.02 Mask loss: 0.13036 RPN box loss: 0.02642 RPN score loss: 0.01332 RPN total loss: 0.03974 Total loss: 1.19756 timestamp: 1655029138.5382988 iteration: 26925 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13285 FastRCNN class loss: 0.06011 FastRCNN total loss: 0.19296 L1 loss: 0.0000e+00 L2 loss: 0.87823 Learning rate: 0.02 Mask loss: 0.19188 RPN box loss: 0.0225 RPN score loss: 0.00387 RPN total loss: 0.02636 Total loss: 1.28944 timestamp: 1655029141.7882705 iteration: 26930 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19923 FastRCNN class loss: 0.15637 FastRCNN total loss: 0.35561 L1 loss: 0.0000e+00 L2 loss: 0.87811 Learning rate: 0.02 Mask loss: 0.21786 RPN box loss: 0.03194 RPN score loss: 0.00868 RPN total loss: 0.04062 Total loss: 1.49219 timestamp: 1655029145.0691845 iteration: 26935 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.0518 FastRCNN total loss: 0.17941 L1 loss: 0.0000e+00 L2 loss: 0.87798 Learning rate: 0.02 Mask loss: 0.1197 RPN box loss: 0.0169 RPN score loss: 0.00521 RPN total loss: 0.02211 Total loss: 1.1992 timestamp: 1655029148.331373 iteration: 26940 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16849 FastRCNN class loss: 0.0885 FastRCNN total loss: 0.257 L1 loss: 0.0000e+00 L2 loss: 0.87784 Learning rate: 0.02 Mask loss: 0.18961 RPN box loss: 0.06993 RPN score loss: 0.00815 RPN total loss: 0.07808 Total loss: 1.40254 timestamp: 1655029151.5351415 iteration: 26945 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11809 FastRCNN class loss: 0.0978 FastRCNN total loss: 0.21588 L1 loss: 0.0000e+00 L2 loss: 0.87769 Learning rate: 0.02 Mask loss: 0.19324 RPN box loss: 0.0629 RPN score loss: 0.00923 RPN total loss: 0.07213 Total loss: 1.35894 timestamp: 1655029154.8157036 iteration: 26950 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1617 FastRCNN class loss: 0.11897 FastRCNN total loss: 0.28067 L1 loss: 0.0000e+00 L2 loss: 0.87758 Learning rate: 0.02 Mask loss: 0.22245 RPN box loss: 0.02635 RPN score loss: 0.00386 RPN total loss: 0.03021 Total loss: 1.4109 timestamp: 1655029158.1423106 iteration: 26955 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10521 FastRCNN class loss: 0.08247 FastRCNN total loss: 0.18768 L1 loss: 0.0000e+00 L2 loss: 0.87745 Learning rate: 0.02 Mask loss: 0.17347 RPN box loss: 0.02176 RPN score loss: 0.01042 RPN total loss: 0.03218 Total loss: 1.27078 timestamp: 1655029161.4423614 iteration: 26960 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20898 FastRCNN class loss: 0.07142 FastRCNN total loss: 0.2804 L1 loss: 0.0000e+00 L2 loss: 0.87729 Learning rate: 0.02 Mask loss: 0.12819 RPN box loss: 0.0663 RPN score loss: 0.00709 RPN total loss: 0.07339 Total loss: 1.35927 timestamp: 1655029164.7471716 iteration: 26965 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2014 FastRCNN class loss: 0.10505 FastRCNN total loss: 0.30645 L1 loss: 0.0000e+00 L2 loss: 0.87716 Learning rate: 0.02 Mask loss: 0.17752 RPN box loss: 0.05401 RPN score loss: 0.01215 RPN total loss: 0.06617 Total loss: 1.42731 timestamp: 1655029167.9709563 iteration: 26970 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21394 FastRCNN class loss: 0.12897 FastRCNN total loss: 0.3429 L1 loss: 0.0000e+00 L2 loss: 0.87704 Learning rate: 0.02 Mask loss: 0.20059 RPN box loss: 0.0336 RPN score loss: 0.00489 RPN total loss: 0.0385 Total loss: 1.45902 timestamp: 1655029171.228553 iteration: 26975 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.20013 L1 loss: 0.0000e+00 L2 loss: 0.8769 Learning rate: 0.02 Mask loss: 0.17764 RPN box loss: 0.01387 RPN score loss: 0.00525 RPN total loss: 0.01912 Total loss: 1.27379 timestamp: 1655029174.5188928 iteration: 26980 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16773 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.23748 L1 loss: 0.0000e+00 L2 loss: 0.87677 Learning rate: 0.02 Mask loss: 0.14893 RPN box loss: 0.03248 RPN score loss: 0.00815 RPN total loss: 0.04063 Total loss: 1.30381 timestamp: 1655029177.7497513 iteration: 26985 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12278 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.20032 L1 loss: 0.0000e+00 L2 loss: 0.87663 Learning rate: 0.02 Mask loss: 0.15881 RPN box loss: 0.02142 RPN score loss: 0.00296 RPN total loss: 0.02438 Total loss: 1.26013 timestamp: 1655029181.0805814 iteration: 26990 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15818 FastRCNN class loss: 0.0768 FastRCNN total loss: 0.23498 L1 loss: 0.0000e+00 L2 loss: 0.87648 Learning rate: 0.02 Mask loss: 0.15854 RPN box loss: 0.02446 RPN score loss: 0.00442 RPN total loss: 0.02888 Total loss: 1.29887 timestamp: 1655029184.3286495 iteration: 26995 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17934 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.24207 L1 loss: 0.0000e+00 L2 loss: 0.87635 Learning rate: 0.02 Mask loss: 0.14353 RPN box loss: 0.03633 RPN score loss: 0.00689 RPN total loss: 0.04322 Total loss: 1.30517 timestamp: 1655029187.5557277 iteration: 27000 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13958 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.24088 L1 loss: 0.0000e+00 L2 loss: 0.87622 Learning rate: 0.02 Mask loss: 0.15204 RPN box loss: 0.02798 RPN score loss: 0.01184 RPN total loss: 0.03983 Total loss: 1.30896 timestamp: 1655029190.8419986 iteration: 27005 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07417 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.14293 L1 loss: 0.0000e+00 L2 loss: 0.87608 Learning rate: 0.02 Mask loss: 0.13224 RPN box loss: 0.03003 RPN score loss: 0.00325 RPN total loss: 0.03328 Total loss: 1.18454 timestamp: 1655029194.169372 iteration: 27010 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12284 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 0.87595 Learning rate: 0.02 Mask loss: 0.16174 RPN box loss: 0.04614 RPN score loss: 0.00616 RPN total loss: 0.0523 Total loss: 1.28815 timestamp: 1655029197.41505 iteration: 27015 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15839 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.23801 L1 loss: 0.0000e+00 L2 loss: 0.87584 Learning rate: 0.02 Mask loss: 0.10542 RPN box loss: 0.03231 RPN score loss: 0.00494 RPN total loss: 0.03725 Total loss: 1.25652 timestamp: 1655029200.6849196 iteration: 27020 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09997 FastRCNN class loss: 0.04814 FastRCNN total loss: 0.14811 L1 loss: 0.0000e+00 L2 loss: 0.87571 Learning rate: 0.02 Mask loss: 0.12505 RPN box loss: 0.06288 RPN score loss: 0.00353 RPN total loss: 0.06641 Total loss: 1.21527 timestamp: 1655029203.9486916 iteration: 27025 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16095 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.22175 L1 loss: 0.0000e+00 L2 loss: 0.87555 Learning rate: 0.02 Mask loss: 0.09071 RPN box loss: 0.00818 RPN score loss: 0.00251 RPN total loss: 0.01069 Total loss: 1.1987 timestamp: 1655029207.2684193 iteration: 27030 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18787 FastRCNN class loss: 0.09529 FastRCNN total loss: 0.28316 L1 loss: 0.0000e+00 L2 loss: 0.8754 Learning rate: 0.02 Mask loss: 0.15314 RPN box loss: 0.0243 RPN score loss: 0.00427 RPN total loss: 0.02857 Total loss: 1.34026 timestamp: 1655029210.5908678 iteration: 27035 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20841 FastRCNN class loss: 0.14575 FastRCNN total loss: 0.35416 L1 loss: 0.0000e+00 L2 loss: 0.87529 Learning rate: 0.02 Mask loss: 0.26945 RPN box loss: 0.0257 RPN score loss: 0.00557 RPN total loss: 0.03127 Total loss: 1.53017 timestamp: 1655029213.805969 iteration: 27040 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18856 FastRCNN class loss: 0.09671 FastRCNN total loss: 0.28526 L1 loss: 0.0000e+00 L2 loss: 0.87515 Learning rate: 0.02 Mask loss: 0.15979 RPN box loss: 0.02168 RPN score loss: 0.01257 RPN total loss: 0.03426 Total loss: 1.35445 timestamp: 1655029217.0414064 iteration: 27045 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19149 FastRCNN class loss: 0.10804 FastRCNN total loss: 0.29953 L1 loss: 0.0000e+00 L2 loss: 0.875 Learning rate: 0.02 Mask loss: 0.28216 RPN box loss: 0.01042 RPN score loss: 0.01829 RPN total loss: 0.02871 Total loss: 1.48539 timestamp: 1655029220.3505836 iteration: 27050 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14019 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.21374 L1 loss: 0.0000e+00 L2 loss: 0.87485 Learning rate: 0.02 Mask loss: 0.16382 RPN box loss: 0.05744 RPN score loss: 0.0054 RPN total loss: 0.06283 Total loss: 1.31524 timestamp: 1655029223.6456256 iteration: 27055 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12065 FastRCNN class loss: 0.09108 FastRCNN total loss: 0.21173 L1 loss: 0.0000e+00 L2 loss: 0.87471 Learning rate: 0.02 Mask loss: 0.13766 RPN box loss: 0.04419 RPN score loss: 0.00398 RPN total loss: 0.04817 Total loss: 1.27227 timestamp: 1655029226.9578562 iteration: 27060 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14619 FastRCNN class loss: 0.08707 FastRCNN total loss: 0.23326 L1 loss: 0.0000e+00 L2 loss: 0.87459 Learning rate: 0.02 Mask loss: 0.17592 RPN box loss: 0.01639 RPN score loss: 0.00615 RPN total loss: 0.02254 Total loss: 1.30631 timestamp: 1655029230.1897075 iteration: 27065 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06642 FastRCNN class loss: 0.0714 FastRCNN total loss: 0.13781 L1 loss: 0.0000e+00 L2 loss: 0.87447 Learning rate: 0.02 Mask loss: 0.16712 RPN box loss: 0.01481 RPN score loss: 0.01054 RPN total loss: 0.02535 Total loss: 1.20475 timestamp: 1655029233.4474537 iteration: 27070 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15415 FastRCNN class loss: 0.07968 FastRCNN total loss: 0.23383 L1 loss: 0.0000e+00 L2 loss: 0.87432 Learning rate: 0.02 Mask loss: 0.20963 RPN box loss: 0.02426 RPN score loss: 0.00948 RPN total loss: 0.03373 Total loss: 1.35151 timestamp: 1655029236.7279825 iteration: 27075 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09347 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.15046 L1 loss: 0.0000e+00 L2 loss: 0.87416 Learning rate: 0.02 Mask loss: 0.26407 RPN box loss: 0.03584 RPN score loss: 0.00753 RPN total loss: 0.04337 Total loss: 1.33206 timestamp: 1655029240.023916 iteration: 27080 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11537 FastRCNN class loss: 0.06152 FastRCNN total loss: 0.17689 L1 loss: 0.0000e+00 L2 loss: 0.87401 Learning rate: 0.02 Mask loss: 0.19177 RPN box loss: 0.01104 RPN score loss: 0.0034 RPN total loss: 0.01444 Total loss: 1.25712 timestamp: 1655029243.2172263 iteration: 27085 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18959 FastRCNN class loss: 0.14063 FastRCNN total loss: 0.33023 L1 loss: 0.0000e+00 L2 loss: 0.87389 Learning rate: 0.02 Mask loss: 0.21662 RPN box loss: 0.02947 RPN score loss: 0.00834 RPN total loss: 0.03781 Total loss: 1.45854 timestamp: 1655029246.4785433 iteration: 27090 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15059 FastRCNN class loss: 0.07301 FastRCNN total loss: 0.2236 L1 loss: 0.0000e+00 L2 loss: 0.87374 Learning rate: 0.02 Mask loss: 0.14383 RPN box loss: 0.04935 RPN score loss: 0.00617 RPN total loss: 0.05552 Total loss: 1.29669 timestamp: 1655029249.7328634 iteration: 27095 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08594 FastRCNN class loss: 0.06904 FastRCNN total loss: 0.15498 L1 loss: 0.0000e+00 L2 loss: 0.87361 Learning rate: 0.02 Mask loss: 0.1523 RPN box loss: 0.08647 RPN score loss: 0.00998 RPN total loss: 0.09646 Total loss: 1.27735 timestamp: 1655029252.9800918 iteration: 27100 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10282 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.18232 L1 loss: 0.0000e+00 L2 loss: 0.87348 Learning rate: 0.02 Mask loss: 0.216 RPN box loss: 0.07366 RPN score loss: 0.01664 RPN total loss: 0.0903 Total loss: 1.3621 timestamp: 1655029256.2569714 iteration: 27105 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.16617 L1 loss: 0.0000e+00 L2 loss: 0.87334 Learning rate: 0.02 Mask loss: 0.15128 RPN box loss: 0.00684 RPN score loss: 0.00436 RPN total loss: 0.01121 Total loss: 1.202 timestamp: 1655029259.5062451 iteration: 27110 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07284 FastRCNN class loss: 0.04218 FastRCNN total loss: 0.11501 L1 loss: 0.0000e+00 L2 loss: 0.87317 Learning rate: 0.02 Mask loss: 0.11121 RPN box loss: 0.00379 RPN score loss: 0.00286 RPN total loss: 0.00665 Total loss: 1.10605 timestamp: 1655029262.738001 iteration: 27115 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15634 FastRCNN class loss: 0.07924 FastRCNN total loss: 0.23558 L1 loss: 0.0000e+00 L2 loss: 0.87303 Learning rate: 0.02 Mask loss: 0.14197 RPN box loss: 0.01847 RPN score loss: 0.00397 RPN total loss: 0.02244 Total loss: 1.27302 timestamp: 1655029266.0653117 iteration: 27120 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15891 FastRCNN class loss: 0.11088 FastRCNN total loss: 0.2698 L1 loss: 0.0000e+00 L2 loss: 0.8729 Learning rate: 0.02 Mask loss: 0.15409 RPN box loss: 0.04055 RPN score loss: 0.01364 RPN total loss: 0.05419 Total loss: 1.35097 timestamp: 1655029269.3177247 iteration: 27125 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21427 FastRCNN class loss: 0.0888 FastRCNN total loss: 0.30307 L1 loss: 0.0000e+00 L2 loss: 0.87276 Learning rate: 0.02 Mask loss: 0.20799 RPN box loss: 0.03189 RPN score loss: 0.00287 RPN total loss: 0.03476 Total loss: 1.41858 timestamp: 1655029272.5892565 iteration: 27130 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14111 FastRCNN class loss: 0.07048 FastRCNN total loss: 0.21159 L1 loss: 0.0000e+00 L2 loss: 0.87264 Learning rate: 0.02 Mask loss: 0.14568 RPN box loss: 0.0121 RPN score loss: 0.00272 RPN total loss: 0.01482 Total loss: 1.24472 timestamp: 1655029275.8433478 iteration: 27135 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16669 FastRCNN class loss: 0.09996 FastRCNN total loss: 0.26665 L1 loss: 0.0000e+00 L2 loss: 0.87251 Learning rate: 0.02 Mask loss: 0.13184 RPN box loss: 0.09241 RPN score loss: 0.01404 RPN total loss: 0.10644 Total loss: 1.37744 timestamp: 1655029279.1516714 iteration: 27140 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11133 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.20692 L1 loss: 0.0000e+00 L2 loss: 0.87236 Learning rate: 0.02 Mask loss: 0.15801 RPN box loss: 0.01949 RPN score loss: 0.00532 RPN total loss: 0.02481 Total loss: 1.2621 timestamp: 1655029282.3873844 iteration: 27145 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16353 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.25334 L1 loss: 0.0000e+00 L2 loss: 0.87224 Learning rate: 0.02 Mask loss: 0.21079 RPN box loss: 0.03279 RPN score loss: 0.0093 RPN total loss: 0.0421 Total loss: 1.37848 timestamp: 1655029285.6401627 iteration: 27150 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1281 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.20383 L1 loss: 0.0000e+00 L2 loss: 0.87212 Learning rate: 0.02 Mask loss: 0.16022 RPN box loss: 0.05223 RPN score loss: 0.00201 RPN total loss: 0.05424 Total loss: 1.2904 timestamp: 1655029288.9378917 iteration: 27155 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16297 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.25002 L1 loss: 0.0000e+00 L2 loss: 0.87199 Learning rate: 0.02 Mask loss: 0.13017 RPN box loss: 0.01154 RPN score loss: 0.00529 RPN total loss: 0.01683 Total loss: 1.26902 timestamp: 1655029292.178249 iteration: 27160 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17241 FastRCNN class loss: 0.1623 FastRCNN total loss: 0.33471 L1 loss: 0.0000e+00 L2 loss: 0.87184 Learning rate: 0.02 Mask loss: 0.20308 RPN box loss: 0.02889 RPN score loss: 0.0093 RPN total loss: 0.03819 Total loss: 1.44782 timestamp: 1655029295.4355862 iteration: 27165 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16565 FastRCNN class loss: 0.09416 FastRCNN total loss: 0.25981 L1 loss: 0.0000e+00 L2 loss: 0.87169 Learning rate: 0.02 Mask loss: 0.17232 RPN box loss: 0.03376 RPN score loss: 0.00784 RPN total loss: 0.04159 Total loss: 1.34541 timestamp: 1655029298.6750166 iteration: 27170 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17246 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.2648 L1 loss: 0.0000e+00 L2 loss: 0.87154 Learning rate: 0.02 Mask loss: 0.18778 RPN box loss: 0.01444 RPN score loss: 0.00454 RPN total loss: 0.01899 Total loss: 1.34311 timestamp: 1655029302.005563 iteration: 27175 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19037 FastRCNN class loss: 0.12858 FastRCNN total loss: 0.31895 L1 loss: 0.0000e+00 L2 loss: 0.8714 Learning rate: 0.02 Mask loss: 0.1904 RPN box loss: 0.04724 RPN score loss: 0.00859 RPN total loss: 0.05583 Total loss: 1.43657 timestamp: 1655029305.227562 iteration: 27180 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15005 FastRCNN class loss: 0.13285 FastRCNN total loss: 0.2829 L1 loss: 0.0000e+00 L2 loss: 0.87127 Learning rate: 0.02 Mask loss: 0.14278 RPN box loss: 0.03789 RPN score loss: 0.00619 RPN total loss: 0.04408 Total loss: 1.34102 timestamp: 1655029308.4412098 iteration: 27185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17827 FastRCNN class loss: 0.11627 FastRCNN total loss: 0.29454 L1 loss: 0.0000e+00 L2 loss: 0.87113 Learning rate: 0.02 Mask loss: 0.1915 RPN box loss: 0.02691 RPN score loss: 0.00609 RPN total loss: 0.03301 Total loss: 1.39018 timestamp: 1655029311.6711402 iteration: 27190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10371 FastRCNN class loss: 0.08386 FastRCNN total loss: 0.18756 L1 loss: 0.0000e+00 L2 loss: 0.87099 Learning rate: 0.02 Mask loss: 0.13473 RPN box loss: 0.00889 RPN score loss: 0.00452 RPN total loss: 0.01342 Total loss: 1.20671 timestamp: 1655029314.9743404 iteration: 27195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18359 FastRCNN class loss: 0.07579 FastRCNN total loss: 0.25939 L1 loss: 0.0000e+00 L2 loss: 0.87084 Learning rate: 0.02 Mask loss: 0.19856 RPN box loss: 0.02078 RPN score loss: 0.00926 RPN total loss: 0.03004 Total loss: 1.35883 timestamp: 1655029318.252109 iteration: 27200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1388 FastRCNN class loss: 0.11366 FastRCNN total loss: 0.25246 L1 loss: 0.0000e+00 L2 loss: 0.87071 Learning rate: 0.02 Mask loss: 0.22774 RPN box loss: 0.02754 RPN score loss: 0.0091 RPN total loss: 0.03664 Total loss: 1.38755 timestamp: 1655029321.561177 iteration: 27205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.13751 FastRCNN total loss: 0.2336 L1 loss: 0.0000e+00 L2 loss: 0.8706 Learning rate: 0.02 Mask loss: 0.12266 RPN box loss: 0.02189 RPN score loss: 0.00374 RPN total loss: 0.02564 Total loss: 1.25249 timestamp: 1655029324.814241 iteration: 27210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15313 FastRCNN class loss: 0.12459 FastRCNN total loss: 0.27772 L1 loss: 0.0000e+00 L2 loss: 0.87049 Learning rate: 0.02 Mask loss: 0.18978 RPN box loss: 0.03544 RPN score loss: 0.00194 RPN total loss: 0.03738 Total loss: 1.37536 timestamp: 1655029328.0372775 iteration: 27215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1549 FastRCNN class loss: 0.09995 FastRCNN total loss: 0.25485 L1 loss: 0.0000e+00 L2 loss: 0.87034 Learning rate: 0.02 Mask loss: 0.19426 RPN box loss: 0.06936 RPN score loss: 0.02033 RPN total loss: 0.08969 Total loss: 1.40914 timestamp: 1655029331.4024706 iteration: 27220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10985 FastRCNN class loss: 0.08536 FastRCNN total loss: 0.19521 L1 loss: 0.0000e+00 L2 loss: 0.87018 Learning rate: 0.02 Mask loss: 0.41174 RPN box loss: 0.02097 RPN score loss: 0.00394 RPN total loss: 0.02491 Total loss: 1.50204 timestamp: 1655029334.638044 iteration: 27225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.24153 L1 loss: 0.0000e+00 L2 loss: 0.87001 Learning rate: 0.02 Mask loss: 0.13616 RPN box loss: 0.01337 RPN score loss: 0.00971 RPN total loss: 0.02308 Total loss: 1.27078 timestamp: 1655029337.9200315 iteration: 27230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19452 FastRCNN class loss: 0.10602 FastRCNN total loss: 0.30054 L1 loss: 0.0000e+00 L2 loss: 0.86989 Learning rate: 0.02 Mask loss: 0.21164 RPN box loss: 0.02993 RPN score loss: 0.00486 RPN total loss: 0.0348 Total loss: 1.41687 timestamp: 1655029341.1570523 iteration: 27235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16096 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.23235 L1 loss: 0.0000e+00 L2 loss: 0.86978 Learning rate: 0.02 Mask loss: 0.14423 RPN box loss: 0.01249 RPN score loss: 0.0023 RPN total loss: 0.01479 Total loss: 1.26114 timestamp: 1655029344.3541498 iteration: 27240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17849 FastRCNN class loss: 0.18407 FastRCNN total loss: 0.36256 L1 loss: 0.0000e+00 L2 loss: 0.86968 Learning rate: 0.02 Mask loss: 0.26206 RPN box loss: 0.03285 RPN score loss: 0.00957 RPN total loss: 0.04243 Total loss: 1.53672 timestamp: 1655029347.6216173 iteration: 27245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17111 FastRCNN class loss: 0.09188 FastRCNN total loss: 0.26298 L1 loss: 0.0000e+00 L2 loss: 0.86955 Learning rate: 0.02 Mask loss: 0.1313 RPN box loss: 0.04629 RPN score loss: 0.00936 RPN total loss: 0.05565 Total loss: 1.31948 timestamp: 1655029350.9062939 iteration: 27250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19372 FastRCNN class loss: 0.0955 FastRCNN total loss: 0.28922 L1 loss: 0.0000e+00 L2 loss: 0.86941 Learning rate: 0.02 Mask loss: 0.18922 RPN box loss: 0.04919 RPN score loss: 0.00544 RPN total loss: 0.05463 Total loss: 1.40247 timestamp: 1655029354.1734362 iteration: 27255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14648 FastRCNN class loss: 0.13762 FastRCNN total loss: 0.28409 L1 loss: 0.0000e+00 L2 loss: 0.86926 Learning rate: 0.02 Mask loss: 0.18442 RPN box loss: 0.01228 RPN score loss: 0.00679 RPN total loss: 0.01907 Total loss: 1.35685 timestamp: 1655029357.4108722 iteration: 27260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18483 FastRCNN class loss: 0.1236 FastRCNN total loss: 0.30843 L1 loss: 0.0000e+00 L2 loss: 0.86913 Learning rate: 0.02 Mask loss: 0.26238 RPN box loss: 0.06205 RPN score loss: 0.01241 RPN total loss: 0.07446 Total loss: 1.51441 timestamp: 1655029360.6884193 iteration: 27265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13185 FastRCNN class loss: 0.05739 FastRCNN total loss: 0.18924 L1 loss: 0.0000e+00 L2 loss: 0.869 Learning rate: 0.02 Mask loss: 0.11114 RPN box loss: 0.01884 RPN score loss: 0.00288 RPN total loss: 0.02172 Total loss: 1.1911 timestamp: 1655029363.9846907 iteration: 27270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11502 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 0.86888 Learning rate: 0.02 Mask loss: 0.18214 RPN box loss: 0.01182 RPN score loss: 0.00603 RPN total loss: 0.01784 Total loss: 1.26792 timestamp: 1655029367.3106368 iteration: 27275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11255 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.20584 L1 loss: 0.0000e+00 L2 loss: 0.86873 Learning rate: 0.02 Mask loss: 0.15918 RPN box loss: 0.0089 RPN score loss: 0.00121 RPN total loss: 0.0101 Total loss: 1.24386 timestamp: 1655029370.5716147 iteration: 27280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16602 FastRCNN class loss: 0.08387 FastRCNN total loss: 0.24989 L1 loss: 0.0000e+00 L2 loss: 0.8686 Learning rate: 0.02 Mask loss: 0.14566 RPN box loss: 0.06196 RPN score loss: 0.01262 RPN total loss: 0.07458 Total loss: 1.33873 timestamp: 1655029373.8327873 iteration: 27285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11932 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.18675 L1 loss: 0.0000e+00 L2 loss: 0.86847 Learning rate: 0.02 Mask loss: 0.10425 RPN box loss: 0.01528 RPN score loss: 0.00271 RPN total loss: 0.01799 Total loss: 1.17746 timestamp: 1655029377.0218906 iteration: 27290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15963 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 0.86833 Learning rate: 0.02 Mask loss: 0.15011 RPN box loss: 0.03111 RPN score loss: 0.00945 RPN total loss: 0.04056 Total loss: 1.27991 timestamp: 1655029380.2755406 iteration: 27295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.09651 FastRCNN total loss: 0.20361 L1 loss: 0.0000e+00 L2 loss: 0.86819 Learning rate: 0.02 Mask loss: 0.113 RPN box loss: 0.01441 RPN score loss: 0.00475 RPN total loss: 0.01916 Total loss: 1.20396 timestamp: 1655029383.5398786 iteration: 27300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2308 FastRCNN class loss: 0.07932 FastRCNN total loss: 0.31012 L1 loss: 0.0000e+00 L2 loss: 0.86804 Learning rate: 0.02 Mask loss: 0.20345 RPN box loss: 0.04334 RPN score loss: 0.00942 RPN total loss: 0.05275 Total loss: 1.43437 timestamp: 1655029386.771545 iteration: 27305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1617 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.24412 L1 loss: 0.0000e+00 L2 loss: 0.86791 Learning rate: 0.02 Mask loss: 0.14783 RPN box loss: 0.03074 RPN score loss: 0.00477 RPN total loss: 0.03551 Total loss: 1.29537 timestamp: 1655029390.0446944 iteration: 27310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20461 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 0.86778 Learning rate: 0.02 Mask loss: 0.18174 RPN box loss: 0.02645 RPN score loss: 0.00377 RPN total loss: 0.03021 Total loss: 1.37534 timestamp: 1655029393.344877 iteration: 27315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09211 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.15929 L1 loss: 0.0000e+00 L2 loss: 0.86766 Learning rate: 0.02 Mask loss: 0.18454 RPN box loss: 0.02461 RPN score loss: 0.00569 RPN total loss: 0.03029 Total loss: 1.24178 timestamp: 1655029396.6838048 iteration: 27320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22734 FastRCNN class loss: 0.09831 FastRCNN total loss: 0.32564 L1 loss: 0.0000e+00 L2 loss: 0.86752 Learning rate: 0.02 Mask loss: 0.21258 RPN box loss: 0.0423 RPN score loss: 0.01293 RPN total loss: 0.05523 Total loss: 1.46097 timestamp: 1655029399.9539974 iteration: 27325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.21509 L1 loss: 0.0000e+00 L2 loss: 0.86737 Learning rate: 0.02 Mask loss: 0.14195 RPN box loss: 0.03448 RPN score loss: 0.01458 RPN total loss: 0.04906 Total loss: 1.27347 timestamp: 1655029403.2662842 iteration: 27330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19527 FastRCNN class loss: 0.13026 FastRCNN total loss: 0.32553 L1 loss: 0.0000e+00 L2 loss: 0.86722 Learning rate: 0.02 Mask loss: 0.18951 RPN box loss: 0.04763 RPN score loss: 0.01684 RPN total loss: 0.06447 Total loss: 1.44673 timestamp: 1655029406.5125074 iteration: 27335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10268 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.16804 L1 loss: 0.0000e+00 L2 loss: 0.8671 Learning rate: 0.02 Mask loss: 0.21791 RPN box loss: 0.0152 RPN score loss: 0.00373 RPN total loss: 0.01892 Total loss: 1.27197 timestamp: 1655029409.8365467 iteration: 27340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.08982 FastRCNN total loss: 0.24919 L1 loss: 0.0000e+00 L2 loss: 0.86693 Learning rate: 0.02 Mask loss: 0.17644 RPN box loss: 0.02869 RPN score loss: 0.00626 RPN total loss: 0.03495 Total loss: 1.32752 timestamp: 1655029413.100657 iteration: 27345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13193 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.20231 L1 loss: 0.0000e+00 L2 loss: 0.86678 Learning rate: 0.02 Mask loss: 0.23719 RPN box loss: 0.01372 RPN score loss: 0.00383 RPN total loss: 0.01755 Total loss: 1.32384 timestamp: 1655029416.3420644 iteration: 27350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15145 FastRCNN class loss: 0.10655 FastRCNN total loss: 0.25799 L1 loss: 0.0000e+00 L2 loss: 0.86666 Learning rate: 0.02 Mask loss: 0.1777 RPN box loss: 0.06812 RPN score loss: 0.00719 RPN total loss: 0.07531 Total loss: 1.37766 timestamp: 1655029419.633539 iteration: 27355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21346 FastRCNN class loss: 0.09925 FastRCNN total loss: 0.31271 L1 loss: 0.0000e+00 L2 loss: 0.86653 Learning rate: 0.02 Mask loss: 0.20502 RPN box loss: 0.06511 RPN score loss: 0.00537 RPN total loss: 0.07048 Total loss: 1.45475 timestamp: 1655029422.8872774 iteration: 27360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16928 FastRCNN class loss: 0.12992 FastRCNN total loss: 0.29921 L1 loss: 0.0000e+00 L2 loss: 0.86639 Learning rate: 0.02 Mask loss: 0.19571 RPN box loss: 0.02863 RPN score loss: 0.00291 RPN total loss: 0.03153 Total loss: 1.39283 timestamp: 1655029426.179165 iteration: 27365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.05718 FastRCNN total loss: 0.17222 L1 loss: 0.0000e+00 L2 loss: 0.86626 Learning rate: 0.02 Mask loss: 0.16192 RPN box loss: 0.01388 RPN score loss: 0.00597 RPN total loss: 0.01985 Total loss: 1.22024 timestamp: 1655029429.5069034 iteration: 27370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19196 FastRCNN class loss: 0.11242 FastRCNN total loss: 0.30438 L1 loss: 0.0000e+00 L2 loss: 0.86611 Learning rate: 0.02 Mask loss: 0.14293 RPN box loss: 0.06225 RPN score loss: 0.01094 RPN total loss: 0.07319 Total loss: 1.3866 timestamp: 1655029432.8209767 iteration: 27375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.04085 FastRCNN total loss: 0.14512 L1 loss: 0.0000e+00 L2 loss: 0.86597 Learning rate: 0.02 Mask loss: 0.17271 RPN box loss: 0.0435 RPN score loss: 0.01307 RPN total loss: 0.05657 Total loss: 1.24036 timestamp: 1655029436.1255496 iteration: 27380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1395 FastRCNN class loss: 0.11087 FastRCNN total loss: 0.25037 L1 loss: 0.0000e+00 L2 loss: 0.86583 Learning rate: 0.02 Mask loss: 0.22031 RPN box loss: 0.06723 RPN score loss: 0.02575 RPN total loss: 0.09298 Total loss: 1.4295 timestamp: 1655029439.3994672 iteration: 27385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.07474 FastRCNN total loss: 0.15253 L1 loss: 0.0000e+00 L2 loss: 0.86573 Learning rate: 0.02 Mask loss: 0.13352 RPN box loss: 0.0617 RPN score loss: 0.01324 RPN total loss: 0.07494 Total loss: 1.22672 timestamp: 1655029442.6204743 iteration: 27390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09078 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.14965 L1 loss: 0.0000e+00 L2 loss: 0.86559 Learning rate: 0.02 Mask loss: 0.18268 RPN box loss: 0.02699 RPN score loss: 0.00988 RPN total loss: 0.03688 Total loss: 1.23481 timestamp: 1655029445.8841329 iteration: 27395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.06469 FastRCNN total loss: 0.14454 L1 loss: 0.0000e+00 L2 loss: 0.86545 Learning rate: 0.02 Mask loss: 0.17715 RPN box loss: 0.0078 RPN score loss: 0.0025 RPN total loss: 0.0103 Total loss: 1.19744 timestamp: 1655029449.1549854 iteration: 27400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20692 FastRCNN class loss: 0.07237 FastRCNN total loss: 0.27928 L1 loss: 0.0000e+00 L2 loss: 0.86533 Learning rate: 0.02 Mask loss: 0.17296 RPN box loss: 0.03662 RPN score loss: 0.00727 RPN total loss: 0.04389 Total loss: 1.36147 timestamp: 1655029452.46651 iteration: 27405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12304 FastRCNN class loss: 0.08059 FastRCNN total loss: 0.20363 L1 loss: 0.0000e+00 L2 loss: 0.86519 Learning rate: 0.02 Mask loss: 0.14941 RPN box loss: 0.0877 RPN score loss: 0.01235 RPN total loss: 0.10005 Total loss: 1.31828 timestamp: 1655029455.7717 iteration: 27410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15899 FastRCNN class loss: 0.10044 FastRCNN total loss: 0.25943 L1 loss: 0.0000e+00 L2 loss: 0.86503 Learning rate: 0.02 Mask loss: 0.15571 RPN box loss: 0.02905 RPN score loss: 0.01847 RPN total loss: 0.04752 Total loss: 1.32769 timestamp: 1655029459.00535 iteration: 27415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06533 FastRCNN class loss: 0.04722 FastRCNN total loss: 0.11255 L1 loss: 0.0000e+00 L2 loss: 0.86491 Learning rate: 0.02 Mask loss: 0.1099 RPN box loss: 0.00441 RPN score loss: 0.00478 RPN total loss: 0.00919 Total loss: 1.09656 timestamp: 1655029462.2604055 iteration: 27420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17094 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.24243 L1 loss: 0.0000e+00 L2 loss: 0.86479 Learning rate: 0.02 Mask loss: 0.16665 RPN box loss: 0.02492 RPN score loss: 0.00998 RPN total loss: 0.0349 Total loss: 1.30876 timestamp: 1655029465.5255668 iteration: 27425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06486 FastRCNN class loss: 0.04281 FastRCNN total loss: 0.10767 L1 loss: 0.0000e+00 L2 loss: 0.86468 Learning rate: 0.02 Mask loss: 0.10787 RPN box loss: 0.04104 RPN score loss: 0.00798 RPN total loss: 0.04902 Total loss: 1.12925 timestamp: 1655029468.741832 iteration: 27430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10686 FastRCNN class loss: 0.05526 FastRCNN total loss: 0.16212 L1 loss: 0.0000e+00 L2 loss: 0.86454 Learning rate: 0.02 Mask loss: 0.12553 RPN box loss: 0.01554 RPN score loss: 0.00794 RPN total loss: 0.02348 Total loss: 1.17567 timestamp: 1655029472.0184696 iteration: 27435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18381 FastRCNN class loss: 0.13509 FastRCNN total loss: 0.3189 L1 loss: 0.0000e+00 L2 loss: 0.8644 Learning rate: 0.02 Mask loss: 0.21304 RPN box loss: 0.06151 RPN score loss: 0.01403 RPN total loss: 0.07554 Total loss: 1.47188 timestamp: 1655029475.335163 iteration: 27440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08887 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.15562 L1 loss: 0.0000e+00 L2 loss: 0.86426 Learning rate: 0.02 Mask loss: 0.11025 RPN box loss: 0.04103 RPN score loss: 0.0099 RPN total loss: 0.05093 Total loss: 1.18106 timestamp: 1655029478.6233912 iteration: 27445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11987 FastRCNN class loss: 0.05379 FastRCNN total loss: 0.17366 L1 loss: 0.0000e+00 L2 loss: 0.8641 Learning rate: 0.02 Mask loss: 0.11237 RPN box loss: 0.02708 RPN score loss: 0.00554 RPN total loss: 0.03262 Total loss: 1.18275 timestamp: 1655029481.963594 iteration: 27450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13595 FastRCNN class loss: 0.1078 FastRCNN total loss: 0.24375 L1 loss: 0.0000e+00 L2 loss: 0.86399 Learning rate: 0.02 Mask loss: 0.24088 RPN box loss: 0.03668 RPN score loss: 0.00565 RPN total loss: 0.04233 Total loss: 1.39096 timestamp: 1655029485.2002132 iteration: 27455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16712 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.24494 L1 loss: 0.0000e+00 L2 loss: 0.86383 Learning rate: 0.02 Mask loss: 0.12071 RPN box loss: 0.01462 RPN score loss: 0.00208 RPN total loss: 0.0167 Total loss: 1.24618 timestamp: 1655029488.4245043 iteration: 27460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11382 FastRCNN class loss: 0.06986 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 0.86369 Learning rate: 0.02 Mask loss: 0.11084 RPN box loss: 0.03576 RPN score loss: 0.00434 RPN total loss: 0.0401 Total loss: 1.19831 timestamp: 1655029491.708349 iteration: 27465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2065 FastRCNN class loss: 0.10364 FastRCNN total loss: 0.31014 L1 loss: 0.0000e+00 L2 loss: 0.86356 Learning rate: 0.02 Mask loss: 0.16111 RPN box loss: 0.01704 RPN score loss: 0.00339 RPN total loss: 0.02043 Total loss: 1.35524 timestamp: 1655029494.9636695 iteration: 27470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14883 FastRCNN class loss: 0.13361 FastRCNN total loss: 0.28245 L1 loss: 0.0000e+00 L2 loss: 0.86344 Learning rate: 0.02 Mask loss: 0.18676 RPN box loss: 0.0541 RPN score loss: 0.0117 RPN total loss: 0.0658 Total loss: 1.39844 timestamp: 1655029498.2931323 iteration: 27475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12299 FastRCNN class loss: 0.10465 FastRCNN total loss: 0.22764 L1 loss: 0.0000e+00 L2 loss: 0.8633 Learning rate: 0.02 Mask loss: 0.15203 RPN box loss: 0.0405 RPN score loss: 0.01003 RPN total loss: 0.05053 Total loss: 1.2935 timestamp: 1655029501.5371902 iteration: 27480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13954 FastRCNN class loss: 0.10884 FastRCNN total loss: 0.24838 L1 loss: 0.0000e+00 L2 loss: 0.86316 Learning rate: 0.02 Mask loss: 0.16215 RPN box loss: 0.05224 RPN score loss: 0.01916 RPN total loss: 0.0714 Total loss: 1.34508 timestamp: 1655029504.7382448 iteration: 27485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14912 FastRCNN class loss: 0.09418 FastRCNN total loss: 0.24329 L1 loss: 0.0000e+00 L2 loss: 0.86302 Learning rate: 0.02 Mask loss: 0.15675 RPN box loss: 0.00989 RPN score loss: 0.00315 RPN total loss: 0.01305 Total loss: 1.27612 timestamp: 1655029508.0083551 iteration: 27490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23697 FastRCNN class loss: 0.10017 FastRCNN total loss: 0.33714 L1 loss: 0.0000e+00 L2 loss: 0.86288 Learning rate: 0.02 Mask loss: 0.21379 RPN box loss: 0.05129 RPN score loss: 0.00859 RPN total loss: 0.05988 Total loss: 1.4737 timestamp: 1655029511.236275 iteration: 27495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14857 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.23391 L1 loss: 0.0000e+00 L2 loss: 0.86276 Learning rate: 0.02 Mask loss: 0.15233 RPN box loss: 0.03414 RPN score loss: 0.00529 RPN total loss: 0.03942 Total loss: 1.28842 timestamp: 1655029514.5218916 iteration: 27500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17413 FastRCNN class loss: 0.0914 FastRCNN total loss: 0.26553 L1 loss: 0.0000e+00 L2 loss: 0.86262 Learning rate: 0.02 Mask loss: 0.12918 RPN box loss: 0.01807 RPN score loss: 0.00604 RPN total loss: 0.02411 Total loss: 1.28145 timestamp: 1655029517.7326503 iteration: 27505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21794 FastRCNN class loss: 0.08403 FastRCNN total loss: 0.30197 L1 loss: 0.0000e+00 L2 loss: 0.86249 Learning rate: 0.02 Mask loss: 0.16873 RPN box loss: 0.03257 RPN score loss: 0.00627 RPN total loss: 0.03883 Total loss: 1.37202 timestamp: 1655029521.0151212 iteration: 27510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12423 FastRCNN class loss: 0.0583 FastRCNN total loss: 0.18253 L1 loss: 0.0000e+00 L2 loss: 0.86238 Learning rate: 0.02 Mask loss: 0.13804 RPN box loss: 0.0423 RPN score loss: 0.00549 RPN total loss: 0.04778 Total loss: 1.23074 timestamp: 1655029524.3226454 iteration: 27515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15484 FastRCNN class loss: 0.1012 FastRCNN total loss: 0.25604 L1 loss: 0.0000e+00 L2 loss: 0.86225 Learning rate: 0.02 Mask loss: 0.15317 RPN box loss: 0.04653 RPN score loss: 0.0158 RPN total loss: 0.06233 Total loss: 1.3338 timestamp: 1655029527.627063 iteration: 27520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14962 FastRCNN class loss: 0.08715 FastRCNN total loss: 0.23677 L1 loss: 0.0000e+00 L2 loss: 0.86212 Learning rate: 0.02 Mask loss: 0.11913 RPN box loss: 0.02457 RPN score loss: 0.00737 RPN total loss: 0.03194 Total loss: 1.24995 timestamp: 1655029530.9547193 iteration: 27525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16149 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.22083 L1 loss: 0.0000e+00 L2 loss: 0.86197 Learning rate: 0.02 Mask loss: 0.19301 RPN box loss: 0.02061 RPN score loss: 0.00937 RPN total loss: 0.02998 Total loss: 1.30579 timestamp: 1655029534.206839 iteration: 27530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22614 FastRCNN class loss: 0.17252 FastRCNN total loss: 0.39866 L1 loss: 0.0000e+00 L2 loss: 0.86183 Learning rate: 0.02 Mask loss: 0.22077 RPN box loss: 0.04411 RPN score loss: 0.01968 RPN total loss: 0.06378 Total loss: 1.54505 timestamp: 1655029537.4798853 iteration: 27535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16092 FastRCNN class loss: 0.13158 FastRCNN total loss: 0.29251 L1 loss: 0.0000e+00 L2 loss: 0.86171 Learning rate: 0.02 Mask loss: 0.25958 RPN box loss: 0.04214 RPN score loss: 0.01261 RPN total loss: 0.05475 Total loss: 1.46854 timestamp: 1655029540.7249625 iteration: 27540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14045 FastRCNN class loss: 0.09051 FastRCNN total loss: 0.23096 L1 loss: 0.0000e+00 L2 loss: 0.86159 Learning rate: 0.02 Mask loss: 0.16175 RPN box loss: 0.03423 RPN score loss: 0.00348 RPN total loss: 0.0377 Total loss: 1.292 timestamp: 1655029543.9726036 iteration: 27545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07147 FastRCNN class loss: 0.07845 FastRCNN total loss: 0.14991 L1 loss: 0.0000e+00 L2 loss: 0.86143 Learning rate: 0.02 Mask loss: 0.23072 RPN box loss: 0.0719 RPN score loss: 0.00675 RPN total loss: 0.07865 Total loss: 1.32072 timestamp: 1655029547.2523754 iteration: 27550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09074 FastRCNN class loss: 0.07864 FastRCNN total loss: 0.16939 L1 loss: 0.0000e+00 L2 loss: 0.86129 Learning rate: 0.02 Mask loss: 0.10062 RPN box loss: 0.03856 RPN score loss: 0.00582 RPN total loss: 0.04438 Total loss: 1.17568 timestamp: 1655029550.5180614 iteration: 27555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11059 FastRCNN class loss: 0.10905 FastRCNN total loss: 0.21964 L1 loss: 0.0000e+00 L2 loss: 0.86117 Learning rate: 0.02 Mask loss: 0.20646 RPN box loss: 0.03 RPN score loss: 0.00577 RPN total loss: 0.03576 Total loss: 1.32304 timestamp: 1655029553.8138843 iteration: 27560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15604 FastRCNN class loss: 0.10202 FastRCNN total loss: 0.25806 L1 loss: 0.0000e+00 L2 loss: 0.86103 Learning rate: 0.02 Mask loss: 0.25797 RPN box loss: 0.07206 RPN score loss: 0.02512 RPN total loss: 0.09717 Total loss: 1.47423 timestamp: 1655029557.0841823 iteration: 27565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08494 FastRCNN class loss: 0.05823 FastRCNN total loss: 0.14318 L1 loss: 0.0000e+00 L2 loss: 0.86089 Learning rate: 0.02 Mask loss: 0.13353 RPN box loss: 0.0299 RPN score loss: 0.00721 RPN total loss: 0.03711 Total loss: 1.17471 timestamp: 1655029560.406475 iteration: 27570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15047 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.22872 L1 loss: 0.0000e+00 L2 loss: 0.86075 Learning rate: 0.02 Mask loss: 0.12522 RPN box loss: 0.02238 RPN score loss: 0.0057 RPN total loss: 0.02809 Total loss: 1.24278 timestamp: 1655029563.6396976 iteration: 27575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13364 FastRCNN class loss: 0.08528 FastRCNN total loss: 0.21891 L1 loss: 0.0000e+00 L2 loss: 0.86061 Learning rate: 0.02 Mask loss: 0.16019 RPN box loss: 0.07477 RPN score loss: 0.00963 RPN total loss: 0.0844 Total loss: 1.32411 timestamp: 1655029566.8586338 iteration: 27580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20245 FastRCNN class loss: 0.08478 FastRCNN total loss: 0.28723 L1 loss: 0.0000e+00 L2 loss: 0.86047 Learning rate: 0.02 Mask loss: 0.34657 RPN box loss: 0.0661 RPN score loss: 0.0065 RPN total loss: 0.0726 Total loss: 1.56686 timestamp: 1655029570.128065 iteration: 27585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10303 FastRCNN class loss: 0.1135 FastRCNN total loss: 0.21653 L1 loss: 0.0000e+00 L2 loss: 0.86032 Learning rate: 0.02 Mask loss: 0.1914 RPN box loss: 0.02898 RPN score loss: 0.0082 RPN total loss: 0.03718 Total loss: 1.30542 timestamp: 1655029573.4416952 iteration: 27590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13427 FastRCNN class loss: 0.08028 FastRCNN total loss: 0.21455 L1 loss: 0.0000e+00 L2 loss: 0.86018 Learning rate: 0.02 Mask loss: 0.17111 RPN box loss: 0.0285 RPN score loss: 0.01266 RPN total loss: 0.04117 Total loss: 1.28702 timestamp: 1655029576.66857 iteration: 27595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14002 FastRCNN class loss: 0.11343 FastRCNN total loss: 0.25345 L1 loss: 0.0000e+00 L2 loss: 0.86007 Learning rate: 0.02 Mask loss: 0.17261 RPN box loss: 0.02777 RPN score loss: 0.03229 RPN total loss: 0.06006 Total loss: 1.34619 timestamp: 1655029579.9236903 iteration: 27600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18012 FastRCNN class loss: 0.04966 FastRCNN total loss: 0.22978 L1 loss: 0.0000e+00 L2 loss: 0.8599 Learning rate: 0.02 Mask loss: 0.14333 RPN box loss: 0.01488 RPN score loss: 0.00896 RPN total loss: 0.02385 Total loss: 1.25685 timestamp: 1655029583.210308 iteration: 27605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10933 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 0.85975 Learning rate: 0.02 Mask loss: 0.08975 RPN box loss: 0.01122 RPN score loss: 0.00331 RPN total loss: 0.01453 Total loss: 1.13211 timestamp: 1655029586.5031757 iteration: 27610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1238 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.18831 L1 loss: 0.0000e+00 L2 loss: 0.85965 Learning rate: 0.02 Mask loss: 0.07957 RPN box loss: 0.01795 RPN score loss: 0.00072 RPN total loss: 0.01867 Total loss: 1.1462 timestamp: 1655029589.820869 iteration: 27615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18804 FastRCNN class loss: 0.12667 FastRCNN total loss: 0.31471 L1 loss: 0.0000e+00 L2 loss: 0.85952 Learning rate: 0.02 Mask loss: 0.18029 RPN box loss: 0.06585 RPN score loss: 0.00862 RPN total loss: 0.07447 Total loss: 1.42899 timestamp: 1655029593.17905 iteration: 27620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05534 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.10203 L1 loss: 0.0000e+00 L2 loss: 0.85941 Learning rate: 0.02 Mask loss: 0.13487 RPN box loss: 0.08087 RPN score loss: 0.00956 RPN total loss: 0.09043 Total loss: 1.18674 timestamp: 1655029596.4616914 iteration: 27625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13473 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.21516 L1 loss: 0.0000e+00 L2 loss: 0.85929 Learning rate: 0.02 Mask loss: 0.2196 RPN box loss: 0.04738 RPN score loss: 0.00632 RPN total loss: 0.0537 Total loss: 1.34775 timestamp: 1655029599.7206259 iteration: 27630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18992 FastRCNN class loss: 0.117 FastRCNN total loss: 0.30692 L1 loss: 0.0000e+00 L2 loss: 0.85915 Learning rate: 0.02 Mask loss: 0.17638 RPN box loss: 0.02603 RPN score loss: 0.00995 RPN total loss: 0.03598 Total loss: 1.37843 timestamp: 1655029603.0475998 iteration: 27635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21209 FastRCNN class loss: 0.10484 FastRCNN total loss: 0.31693 L1 loss: 0.0000e+00 L2 loss: 0.85904 Learning rate: 0.02 Mask loss: 0.21613 RPN box loss: 0.02361 RPN score loss: 0.00721 RPN total loss: 0.03082 Total loss: 1.42292 timestamp: 1655029606.341001 iteration: 27640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18381 FastRCNN class loss: 0.08558 FastRCNN total loss: 0.2694 L1 loss: 0.0000e+00 L2 loss: 0.85892 Learning rate: 0.02 Mask loss: 0.1578 RPN box loss: 0.03201 RPN score loss: 0.01073 RPN total loss: 0.04274 Total loss: 1.32885 timestamp: 1655029609.6793878 iteration: 27645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0574 FastRCNN class loss: 0.04893 FastRCNN total loss: 0.10633 L1 loss: 0.0000e+00 L2 loss: 0.8588 Learning rate: 0.02 Mask loss: 0.20065 RPN box loss: 0.02261 RPN score loss: 0.00748 RPN total loss: 0.03008 Total loss: 1.19587 timestamp: 1655029612.9474416 iteration: 27650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.03654 FastRCNN total loss: 0.11014 L1 loss: 0.0000e+00 L2 loss: 0.8587 Learning rate: 0.02 Mask loss: 0.12647 RPN box loss: 0.0062 RPN score loss: 0.00176 RPN total loss: 0.00796 Total loss: 1.10326 timestamp: 1655029616.2262743 iteration: 27655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17349 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.24043 L1 loss: 0.0000e+00 L2 loss: 0.85852 Learning rate: 0.02 Mask loss: 0.12399 RPN box loss: 0.03518 RPN score loss: 0.00378 RPN total loss: 0.03896 Total loss: 1.26191 timestamp: 1655029619.5034928 iteration: 27660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14263 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.21321 L1 loss: 0.0000e+00 L2 loss: 0.85839 Learning rate: 0.02 Mask loss: 0.14813 RPN box loss: 0.03242 RPN score loss: 0.00537 RPN total loss: 0.03779 Total loss: 1.25752 timestamp: 1655029622.79273 iteration: 27665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.05248 FastRCNN total loss: 0.17878 L1 loss: 0.0000e+00 L2 loss: 0.85825 Learning rate: 0.02 Mask loss: 0.14692 RPN box loss: 0.05201 RPN score loss: 0.00488 RPN total loss: 0.05689 Total loss: 1.24084 timestamp: 1655029626.062008 iteration: 27670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.09437 FastRCNN total loss: 0.19896 L1 loss: 0.0000e+00 L2 loss: 0.8581 Learning rate: 0.02 Mask loss: 0.19884 RPN box loss: 0.04327 RPN score loss: 0.01199 RPN total loss: 0.05526 Total loss: 1.31117 timestamp: 1655029629.355624 iteration: 27675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25321 FastRCNN class loss: 0.12875 FastRCNN total loss: 0.38196 L1 loss: 0.0000e+00 L2 loss: 0.85795 Learning rate: 0.02 Mask loss: 0.21943 RPN box loss: 0.01841 RPN score loss: 0.00457 RPN total loss: 0.02298 Total loss: 1.48232 timestamp: 1655029632.7253575 iteration: 27680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11033 FastRCNN class loss: 0.04692 FastRCNN total loss: 0.15724 L1 loss: 0.0000e+00 L2 loss: 0.85782 Learning rate: 0.02 Mask loss: 0.16487 RPN box loss: 0.08869 RPN score loss: 0.00878 RPN total loss: 0.09748 Total loss: 1.27742 timestamp: 1655029636.0268846 iteration: 27685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08896 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.1465 L1 loss: 0.0000e+00 L2 loss: 0.85768 Learning rate: 0.02 Mask loss: 0.16133 RPN box loss: 0.04906 RPN score loss: 0.01406 RPN total loss: 0.06312 Total loss: 1.22863 timestamp: 1655029639.3503852 iteration: 27690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19126 FastRCNN class loss: 0.13378 FastRCNN total loss: 0.32503 L1 loss: 0.0000e+00 L2 loss: 0.85754 Learning rate: 0.02 Mask loss: 0.2284 RPN box loss: 0.02858 RPN score loss: 0.0054 RPN total loss: 0.03398 Total loss: 1.44495 timestamp: 1655029642.65377 iteration: 27695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14658 FastRCNN class loss: 0.08855 FastRCNN total loss: 0.23513 L1 loss: 0.0000e+00 L2 loss: 0.85743 Learning rate: 0.02 Mask loss: 0.15223 RPN box loss: 0.0385 RPN score loss: 0.00789 RPN total loss: 0.04638 Total loss: 1.29116 timestamp: 1655029645.9511573 iteration: 27700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15776 FastRCNN class loss: 0.10892 FastRCNN total loss: 0.26669 L1 loss: 0.0000e+00 L2 loss: 0.85729 Learning rate: 0.02 Mask loss: 0.14747 RPN box loss: 0.02388 RPN score loss: 0.00329 RPN total loss: 0.02718 Total loss: 1.29863 timestamp: 1655029649.2237957 iteration: 27705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14851 FastRCNN class loss: 0.11095 FastRCNN total loss: 0.25946 L1 loss: 0.0000e+00 L2 loss: 0.85715 Learning rate: 0.02 Mask loss: 0.20518 RPN box loss: 0.02522 RPN score loss: 0.01057 RPN total loss: 0.03579 Total loss: 1.35758 timestamp: 1655029652.4320881 iteration: 27710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12498 FastRCNN class loss: 0.10273 FastRCNN total loss: 0.22771 L1 loss: 0.0000e+00 L2 loss: 0.857 Learning rate: 0.02 Mask loss: 0.26529 RPN box loss: 0.1285 RPN score loss: 0.0173 RPN total loss: 0.1458 Total loss: 1.4958 timestamp: 1655029655.6825664 iteration: 27715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22052 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.32127 L1 loss: 0.0000e+00 L2 loss: 0.85688 Learning rate: 0.02 Mask loss: 0.29629 RPN box loss: 0.00928 RPN score loss: 0.00841 RPN total loss: 0.01769 Total loss: 1.49212 timestamp: 1655029659.0182855 iteration: 27720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2129 FastRCNN class loss: 0.11341 FastRCNN total loss: 0.32631 L1 loss: 0.0000e+00 L2 loss: 0.85673 Learning rate: 0.02 Mask loss: 0.1968 RPN box loss: 0.04429 RPN score loss: 0.01258 RPN total loss: 0.05687 Total loss: 1.43672 timestamp: 1655029662.28847 iteration: 27725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10452 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.17833 L1 loss: 0.0000e+00 L2 loss: 0.8566 Learning rate: 0.02 Mask loss: 0.12517 RPN box loss: 0.06995 RPN score loss: 0.00851 RPN total loss: 0.07846 Total loss: 1.23857 timestamp: 1655029665.5399842 iteration: 27730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17852 FastRCNN class loss: 0.10803 FastRCNN total loss: 0.28655 L1 loss: 0.0000e+00 L2 loss: 0.85648 Learning rate: 0.02 Mask loss: 0.21968 RPN box loss: 0.03762 RPN score loss: 0.02302 RPN total loss: 0.06064 Total loss: 1.42336 timestamp: 1655029668.7855413 iteration: 27735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17595 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.23714 L1 loss: 0.0000e+00 L2 loss: 0.85633 Learning rate: 0.02 Mask loss: 0.11086 RPN box loss: 0.03521 RPN score loss: 0.00585 RPN total loss: 0.04106 Total loss: 1.24539 timestamp: 1655029672.0580032 iteration: 27740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22848 FastRCNN class loss: 0.10125 FastRCNN total loss: 0.32974 L1 loss: 0.0000e+00 L2 loss: 0.85618 Learning rate: 0.02 Mask loss: 0.10645 RPN box loss: 0.02234 RPN score loss: 0.00566 RPN total loss: 0.02801 Total loss: 1.32038 timestamp: 1655029675.3544095 iteration: 27745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16156 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.22134 L1 loss: 0.0000e+00 L2 loss: 0.85604 Learning rate: 0.02 Mask loss: 0.15894 RPN box loss: 0.03408 RPN score loss: 0.00715 RPN total loss: 0.04123 Total loss: 1.27754 timestamp: 1655029678.6951098 iteration: 27750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14571 FastRCNN class loss: 0.0609 FastRCNN total loss: 0.2066 L1 loss: 0.0000e+00 L2 loss: 0.85594 Learning rate: 0.02 Mask loss: 0.13126 RPN box loss: 0.02477 RPN score loss: 0.00555 RPN total loss: 0.03031 Total loss: 1.22411 timestamp: 1655029682.0110526 iteration: 27755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11779 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.20344 L1 loss: 0.0000e+00 L2 loss: 0.85582 Learning rate: 0.02 Mask loss: 0.16616 RPN box loss: 0.03192 RPN score loss: 0.00919 RPN total loss: 0.04111 Total loss: 1.26652 timestamp: 1655029685.284627 iteration: 27760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16928 FastRCNN class loss: 0.13238 FastRCNN total loss: 0.30166 L1 loss: 0.0000e+00 L2 loss: 0.85569 Learning rate: 0.02 Mask loss: 0.21774 RPN box loss: 0.06636 RPN score loss: 0.01147 RPN total loss: 0.07783 Total loss: 1.45291 timestamp: 1655029688.509154 iteration: 27765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19347 FastRCNN class loss: 0.10166 FastRCNN total loss: 0.29513 L1 loss: 0.0000e+00 L2 loss: 0.85557 Learning rate: 0.02 Mask loss: 0.14215 RPN box loss: 0.01431 RPN score loss: 0.00353 RPN total loss: 0.01784 Total loss: 1.3107 timestamp: 1655029691.7567208 iteration: 27770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09698 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.17337 L1 loss: 0.0000e+00 L2 loss: 0.85544 Learning rate: 0.02 Mask loss: 0.09861 RPN box loss: 0.05485 RPN score loss: 0.00535 RPN total loss: 0.0602 Total loss: 1.18763 timestamp: 1655029695.0611184 iteration: 27775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14167 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.1931 L1 loss: 0.0000e+00 L2 loss: 0.85531 Learning rate: 0.02 Mask loss: 0.14354 RPN box loss: 0.05117 RPN score loss: 0.00843 RPN total loss: 0.0596 Total loss: 1.25155 timestamp: 1655029698.3342519 iteration: 27780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22617 FastRCNN class loss: 0.07844 FastRCNN total loss: 0.30461 L1 loss: 0.0000e+00 L2 loss: 0.85518 Learning rate: 0.02 Mask loss: 0.15985 RPN box loss: 0.01391 RPN score loss: 0.00658 RPN total loss: 0.02049 Total loss: 1.34013 timestamp: 1655029701.6220233 iteration: 27785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16255 FastRCNN class loss: 0.12326 FastRCNN total loss: 0.28581 L1 loss: 0.0000e+00 L2 loss: 0.85502 Learning rate: 0.02 Mask loss: 0.15308 RPN box loss: 0.03471 RPN score loss: 0.01009 RPN total loss: 0.0448 Total loss: 1.33871 timestamp: 1655029704.9429762 iteration: 27790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14281 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.21299 L1 loss: 0.0000e+00 L2 loss: 0.85491 Learning rate: 0.02 Mask loss: 0.19179 RPN box loss: 0.01824 RPN score loss: 0.00571 RPN total loss: 0.02395 Total loss: 1.28363 timestamp: 1655029708.2661357 iteration: 27795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18072 FastRCNN class loss: 0.11222 FastRCNN total loss: 0.29294 L1 loss: 0.0000e+00 L2 loss: 0.85479 Learning rate: 0.02 Mask loss: 0.16432 RPN box loss: 0.02497 RPN score loss: 0.00585 RPN total loss: 0.03082 Total loss: 1.34287 timestamp: 1655029711.5277495 iteration: 27800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09274 FastRCNN class loss: 0.06848 FastRCNN total loss: 0.16122 L1 loss: 0.0000e+00 L2 loss: 0.85465 Learning rate: 0.02 Mask loss: 0.12073 RPN box loss: 0.04654 RPN score loss: 0.00963 RPN total loss: 0.05617 Total loss: 1.19278 timestamp: 1655029714.8045604 iteration: 27805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20787 FastRCNN class loss: 0.07919 FastRCNN total loss: 0.28706 L1 loss: 0.0000e+00 L2 loss: 0.85451 Learning rate: 0.02 Mask loss: 0.13641 RPN box loss: 0.04002 RPN score loss: 0.00508 RPN total loss: 0.0451 Total loss: 1.32308 timestamp: 1655029718.0617845 iteration: 27810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09627 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.1479 L1 loss: 0.0000e+00 L2 loss: 0.85436 Learning rate: 0.02 Mask loss: 0.12224 RPN box loss: 0.05244 RPN score loss: 0.00868 RPN total loss: 0.06112 Total loss: 1.18562 timestamp: 1655029721.298804 iteration: 27815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13502 FastRCNN class loss: 0.06556 FastRCNN total loss: 0.20059 L1 loss: 0.0000e+00 L2 loss: 0.85423 Learning rate: 0.02 Mask loss: 0.13166 RPN box loss: 0.02378 RPN score loss: 0.00493 RPN total loss: 0.0287 Total loss: 1.21518 timestamp: 1655029724.6637027 iteration: 27820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14827 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.20289 L1 loss: 0.0000e+00 L2 loss: 0.8541 Learning rate: 0.02 Mask loss: 0.14427 RPN box loss: 0.01947 RPN score loss: 0.00522 RPN total loss: 0.02469 Total loss: 1.22595 timestamp: 1655029727.9361782 iteration: 27825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12261 FastRCNN class loss: 0.09685 FastRCNN total loss: 0.21946 L1 loss: 0.0000e+00 L2 loss: 0.85393 Learning rate: 0.02 Mask loss: 0.25208 RPN box loss: 0.03279 RPN score loss: 0.00673 RPN total loss: 0.03952 Total loss: 1.36499 timestamp: 1655029731.2456064 iteration: 27830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14296 FastRCNN class loss: 0.0681 FastRCNN total loss: 0.21106 L1 loss: 0.0000e+00 L2 loss: 0.85381 Learning rate: 0.02 Mask loss: 0.15967 RPN box loss: 0.01787 RPN score loss: 0.00264 RPN total loss: 0.0205 Total loss: 1.24504 timestamp: 1655029734.513596 iteration: 27835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13766 FastRCNN class loss: 0.10161 FastRCNN total loss: 0.23926 L1 loss: 0.0000e+00 L2 loss: 0.8537 Learning rate: 0.02 Mask loss: 0.13644 RPN box loss: 0.02053 RPN score loss: 0.00759 RPN total loss: 0.02812 Total loss: 1.25752 timestamp: 1655029737.7494645 iteration: 27840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14372 FastRCNN class loss: 0.0701 FastRCNN total loss: 0.21382 L1 loss: 0.0000e+00 L2 loss: 0.8536 Learning rate: 0.02 Mask loss: 0.15456 RPN box loss: 0.03826 RPN score loss: 0.00476 RPN total loss: 0.04301 Total loss: 1.26498 timestamp: 1655029740.9665225 iteration: 27845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1841 FastRCNN class loss: 0.08593 FastRCNN total loss: 0.27002 L1 loss: 0.0000e+00 L2 loss: 0.85347 Learning rate: 0.02 Mask loss: 0.11339 RPN box loss: 0.02253 RPN score loss: 0.00323 RPN total loss: 0.02576 Total loss: 1.26265 timestamp: 1655029744.2209494 iteration: 27850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19134 FastRCNN class loss: 0.1019 FastRCNN total loss: 0.29324 L1 loss: 0.0000e+00 L2 loss: 0.85334 Learning rate: 0.02 Mask loss: 0.15073 RPN box loss: 0.05849 RPN score loss: 0.00994 RPN total loss: 0.06843 Total loss: 1.36573 timestamp: 1655029747.6253343 iteration: 27855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12741 FastRCNN class loss: 0.05074 FastRCNN total loss: 0.17816 L1 loss: 0.0000e+00 L2 loss: 0.85319 Learning rate: 0.02 Mask loss: 0.12382 RPN box loss: 0.01412 RPN score loss: 0.00377 RPN total loss: 0.01789 Total loss: 1.17305 timestamp: 1655029750.873144 iteration: 27860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10829 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.17137 L1 loss: 0.0000e+00 L2 loss: 0.85307 Learning rate: 0.02 Mask loss: 0.15107 RPN box loss: 0.01493 RPN score loss: 0.00392 RPN total loss: 0.01885 Total loss: 1.19437 timestamp: 1655029754.1927829 iteration: 27865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19175 FastRCNN class loss: 0.12766 FastRCNN total loss: 0.31942 L1 loss: 0.0000e+00 L2 loss: 0.85294 Learning rate: 0.02 Mask loss: 0.17417 RPN box loss: 0.05113 RPN score loss: 0.01262 RPN total loss: 0.06375 Total loss: 1.41028 timestamp: 1655029757.5074809 iteration: 27870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12625 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.21117 L1 loss: 0.0000e+00 L2 loss: 0.85281 Learning rate: 0.02 Mask loss: 0.18802 RPN box loss: 0.02344 RPN score loss: 0.00413 RPN total loss: 0.02758 Total loss: 1.27958 timestamp: 1655029760.747352 iteration: 27875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12079 FastRCNN class loss: 0.05877 FastRCNN total loss: 0.17956 L1 loss: 0.0000e+00 L2 loss: 0.85267 Learning rate: 0.02 Mask loss: 0.15784 RPN box loss: 0.02513 RPN score loss: 0.00427 RPN total loss: 0.0294 Total loss: 1.21946 timestamp: 1655029764.0541556 iteration: 27880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07714 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.12909 L1 loss: 0.0000e+00 L2 loss: 0.85252 Learning rate: 0.02 Mask loss: 0.1763 RPN box loss: 0.03583 RPN score loss: 0.00787 RPN total loss: 0.0437 Total loss: 1.20161 timestamp: 1655029767.2695556 iteration: 27885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1571 FastRCNN class loss: 0.08744 FastRCNN total loss: 0.24454 L1 loss: 0.0000e+00 L2 loss: 0.85239 Learning rate: 0.02 Mask loss: 0.26304 RPN box loss: 0.02999 RPN score loss: 0.00626 RPN total loss: 0.03625 Total loss: 1.39622 timestamp: 1655029770.4898436 iteration: 27890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12805 FastRCNN class loss: 0.06682 FastRCNN total loss: 0.19486 L1 loss: 0.0000e+00 L2 loss: 0.85227 Learning rate: 0.02 Mask loss: 0.15941 RPN box loss: 0.02306 RPN score loss: 0.00388 RPN total loss: 0.02695 Total loss: 1.23349 timestamp: 1655029773.8380535 iteration: 27895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13558 FastRCNN class loss: 0.05718 FastRCNN total loss: 0.19275 L1 loss: 0.0000e+00 L2 loss: 0.85215 Learning rate: 0.02 Mask loss: 0.13512 RPN box loss: 0.04918 RPN score loss: 0.009 RPN total loss: 0.05818 Total loss: 1.23821 timestamp: 1655029777.0942216 iteration: 27900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07498 FastRCNN class loss: 0.0882 FastRCNN total loss: 0.16318 L1 loss: 0.0000e+00 L2 loss: 0.85203 Learning rate: 0.02 Mask loss: 0.17482 RPN box loss: 0.00767 RPN score loss: 0.00559 RPN total loss: 0.01326 Total loss: 1.20328 timestamp: 1655029780.365766 iteration: 27905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14194 FastRCNN class loss: 0.13754 FastRCNN total loss: 0.27948 L1 loss: 0.0000e+00 L2 loss: 0.85186 Learning rate: 0.02 Mask loss: 0.13845 RPN box loss: 0.02907 RPN score loss: 0.01386 RPN total loss: 0.04293 Total loss: 1.31272 timestamp: 1655029783.6094577 iteration: 27910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08217 FastRCNN class loss: 0.04242 FastRCNN total loss: 0.12459 L1 loss: 0.0000e+00 L2 loss: 0.85173 Learning rate: 0.02 Mask loss: 0.10747 RPN box loss: 0.02087 RPN score loss: 0.00227 RPN total loss: 0.02314 Total loss: 1.10692 timestamp: 1655029786.9284432 iteration: 27915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16993 FastRCNN class loss: 0.0769 FastRCNN total loss: 0.24683 L1 loss: 0.0000e+00 L2 loss: 0.8516 Learning rate: 0.02 Mask loss: 0.16246 RPN box loss: 0.02714 RPN score loss: 0.00212 RPN total loss: 0.02926 Total loss: 1.29015 timestamp: 1655029790.1956196 iteration: 27920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16138 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.23493 L1 loss: 0.0000e+00 L2 loss: 0.85148 Learning rate: 0.02 Mask loss: 0.14485 RPN box loss: 0.01169 RPN score loss: 0.00697 RPN total loss: 0.01865 Total loss: 1.24992 timestamp: 1655029793.4225986 iteration: 27925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14678 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.20808 L1 loss: 0.0000e+00 L2 loss: 0.85136 Learning rate: 0.02 Mask loss: 0.20899 RPN box loss: 0.02583 RPN score loss: 0.00555 RPN total loss: 0.03138 Total loss: 1.29982 timestamp: 1655029796.739345 iteration: 27930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17394 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.25333 L1 loss: 0.0000e+00 L2 loss: 0.85122 Learning rate: 0.02 Mask loss: 0.16868 RPN box loss: 0.01704 RPN score loss: 0.00396 RPN total loss: 0.021 Total loss: 1.29423 timestamp: 1655029800.0099943 iteration: 27935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14897 FastRCNN class loss: 0.09033 FastRCNN total loss: 0.2393 L1 loss: 0.0000e+00 L2 loss: 0.85107 Learning rate: 0.02 Mask loss: 0.18042 RPN box loss: 0.01612 RPN score loss: 0.00714 RPN total loss: 0.02326 Total loss: 1.29405 timestamp: 1655029803.2151482 iteration: 27940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16092 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.24952 L1 loss: 0.0000e+00 L2 loss: 0.85098 Learning rate: 0.02 Mask loss: 0.17137 RPN box loss: 0.00448 RPN score loss: 0.00346 RPN total loss: 0.00794 Total loss: 1.27982 timestamp: 1655029806.5370188 iteration: 27945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13137 FastRCNN class loss: 0.07127 FastRCNN total loss: 0.20263 L1 loss: 0.0000e+00 L2 loss: 0.85084 Learning rate: 0.02 Mask loss: 0.11954 RPN box loss: 0.02443 RPN score loss: 0.00253 RPN total loss: 0.02695 Total loss: 1.19997 timestamp: 1655029809.8381383 iteration: 27950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09733 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.15188 L1 loss: 0.0000e+00 L2 loss: 0.85071 Learning rate: 0.02 Mask loss: 0.12664 RPN box loss: 0.01985 RPN score loss: 0.00527 RPN total loss: 0.02512 Total loss: 1.15435 timestamp: 1655029813.0795908 iteration: 27955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12257 FastRCNN class loss: 0.10501 FastRCNN total loss: 0.22758 L1 loss: 0.0000e+00 L2 loss: 0.85061 Learning rate: 0.02 Mask loss: 0.15163 RPN box loss: 0.02838 RPN score loss: 0.00897 RPN total loss: 0.03735 Total loss: 1.26717 timestamp: 1655029816.3001072 iteration: 27960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13993 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.19978 L1 loss: 0.0000e+00 L2 loss: 0.85048 Learning rate: 0.02 Mask loss: 0.14884 RPN box loss: 0.1512 RPN score loss: 0.0083 RPN total loss: 0.1595 Total loss: 1.35859 timestamp: 1655029819.5673423 iteration: 27965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12699 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.18022 L1 loss: 0.0000e+00 L2 loss: 0.85036 Learning rate: 0.02 Mask loss: 0.09407 RPN box loss: 0.01348 RPN score loss: 0.00558 RPN total loss: 0.01907 Total loss: 1.14372 timestamp: 1655029822.7872334 iteration: 27970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21737 FastRCNN class loss: 0.07028 FastRCNN total loss: 0.28765 L1 loss: 0.0000e+00 L2 loss: 0.85023 Learning rate: 0.02 Mask loss: 0.17212 RPN box loss: 0.04711 RPN score loss: 0.00583 RPN total loss: 0.05294 Total loss: 1.36294 timestamp: 1655029826.1574183 iteration: 27975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12607 FastRCNN class loss: 0.08426 FastRCNN total loss: 0.21032 L1 loss: 0.0000e+00 L2 loss: 0.85009 Learning rate: 0.02 Mask loss: 0.15862 RPN box loss: 0.06008 RPN score loss: 0.01246 RPN total loss: 0.07254 Total loss: 1.29158 timestamp: 1655029829.4546409 iteration: 27980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11146 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.84996 Learning rate: 0.02 Mask loss: 0.15158 RPN box loss: 0.03061 RPN score loss: 0.0058 RPN total loss: 0.03642 Total loss: 1.21104 timestamp: 1655029832.741354 iteration: 27985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17063 FastRCNN class loss: 0.07752 FastRCNN total loss: 0.24815 L1 loss: 0.0000e+00 L2 loss: 0.84982 Learning rate: 0.02 Mask loss: 0.16517 RPN box loss: 0.02866 RPN score loss: 0.00803 RPN total loss: 0.03669 Total loss: 1.29983 timestamp: 1655029836.0060148 iteration: 27990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.10169 FastRCNN total loss: 0.27309 L1 loss: 0.0000e+00 L2 loss: 0.84968 Learning rate: 0.02 Mask loss: 0.14657 RPN box loss: 0.03303 RPN score loss: 0.01083 RPN total loss: 0.04387 Total loss: 1.3132 timestamp: 1655029839.3540063 iteration: 27995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14629 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.21768 L1 loss: 0.0000e+00 L2 loss: 0.84957 Learning rate: 0.02 Mask loss: 0.1524 RPN box loss: 0.03131 RPN score loss: 0.01254 RPN total loss: 0.04385 Total loss: 1.26349 timestamp: 1655029842.5645926 iteration: 28000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10665 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.16234 L1 loss: 0.0000e+00 L2 loss: 0.84944 Learning rate: 0.02 Mask loss: 0.16866 RPN box loss: 0.01527 RPN score loss: 0.01008 RPN total loss: 0.02535 Total loss: 1.20579 timestamp: 1655029845.7894661 iteration: 28005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13909 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.20296 L1 loss: 0.0000e+00 L2 loss: 0.8493 Learning rate: 0.02 Mask loss: 0.1151 RPN box loss: 0.01487 RPN score loss: 0.00331 RPN total loss: 0.01817 Total loss: 1.18554 timestamp: 1655029849.1019022 iteration: 28010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12453 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.20222 L1 loss: 0.0000e+00 L2 loss: 0.84917 Learning rate: 0.02 Mask loss: 0.15691 RPN box loss: 0.07383 RPN score loss: 0.00636 RPN total loss: 0.08019 Total loss: 1.28849 timestamp: 1655029852.3708193 iteration: 28015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12282 FastRCNN class loss: 0.10577 FastRCNN total loss: 0.22859 L1 loss: 0.0000e+00 L2 loss: 0.84903 Learning rate: 0.02 Mask loss: 0.13519 RPN box loss: 0.04519 RPN score loss: 0.01223 RPN total loss: 0.05742 Total loss: 1.27023 timestamp: 1655029855.6421182 iteration: 28020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10404 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.17435 L1 loss: 0.0000e+00 L2 loss: 0.84889 Learning rate: 0.02 Mask loss: 0.15329 RPN box loss: 0.04628 RPN score loss: 0.00869 RPN total loss: 0.05498 Total loss: 1.2315 timestamp: 1655029858.9514084 iteration: 28025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1893 FastRCNN class loss: 0.10103 FastRCNN total loss: 0.29033 L1 loss: 0.0000e+00 L2 loss: 0.84875 Learning rate: 0.02 Mask loss: 0.23476 RPN box loss: 0.03881 RPN score loss: 0.00944 RPN total loss: 0.04825 Total loss: 1.42209 timestamp: 1655029862.251416 iteration: 28030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21952 FastRCNN class loss: 0.09785 FastRCNN total loss: 0.31737 L1 loss: 0.0000e+00 L2 loss: 0.84862 Learning rate: 0.02 Mask loss: 0.1431 RPN box loss: 0.02066 RPN score loss: 0.0149 RPN total loss: 0.03557 Total loss: 1.34467 timestamp: 1655029865.4765947 iteration: 28035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1267 FastRCNN class loss: 0.12638 FastRCNN total loss: 0.25307 L1 loss: 0.0000e+00 L2 loss: 0.8485 Learning rate: 0.02 Mask loss: 0.20417 RPN box loss: 0.0515 RPN score loss: 0.0152 RPN total loss: 0.06671 Total loss: 1.37246 timestamp: 1655029868.7534683 iteration: 28040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11699 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.19589 L1 loss: 0.0000e+00 L2 loss: 0.84839 Learning rate: 0.02 Mask loss: 0.10038 RPN box loss: 0.0164 RPN score loss: 0.0034 RPN total loss: 0.0198 Total loss: 1.16447 timestamp: 1655029872.0241747 iteration: 28045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22132 FastRCNN class loss: 0.1336 FastRCNN total loss: 0.35493 L1 loss: 0.0000e+00 L2 loss: 0.84824 Learning rate: 0.02 Mask loss: 0.21363 RPN box loss: 0.02188 RPN score loss: 0.00608 RPN total loss: 0.02797 Total loss: 1.44476 timestamp: 1655029875.269221 iteration: 28050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10687 FastRCNN class loss: 0.05485 FastRCNN total loss: 0.16172 L1 loss: 0.0000e+00 L2 loss: 0.84811 Learning rate: 0.02 Mask loss: 0.15316 RPN box loss: 0.00881 RPN score loss: 0.00732 RPN total loss: 0.01613 Total loss: 1.17912 timestamp: 1655029878.6152432 iteration: 28055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10924 FastRCNN class loss: 0.07048 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.84798 Learning rate: 0.02 Mask loss: 0.17895 RPN box loss: 0.03328 RPN score loss: 0.00209 RPN total loss: 0.03537 Total loss: 1.24202 timestamp: 1655029881.8784337 iteration: 28060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08827 FastRCNN class loss: 0.08607 FastRCNN total loss: 0.17434 L1 loss: 0.0000e+00 L2 loss: 0.84786 Learning rate: 0.02 Mask loss: 0.09551 RPN box loss: 0.01487 RPN score loss: 0.00291 RPN total loss: 0.01778 Total loss: 1.13549 timestamp: 1655029885.1336389 iteration: 28065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1908 FastRCNN class loss: 0.1286 FastRCNN total loss: 0.3194 L1 loss: 0.0000e+00 L2 loss: 0.8477 Learning rate: 0.02 Mask loss: 0.17689 RPN box loss: 0.07043 RPN score loss: 0.01144 RPN total loss: 0.08187 Total loss: 1.42586 timestamp: 1655029888.3902228 iteration: 28070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09124 FastRCNN class loss: 0.10717 FastRCNN total loss: 0.1984 L1 loss: 0.0000e+00 L2 loss: 0.84757 Learning rate: 0.02 Mask loss: 0.20282 RPN box loss: 0.02671 RPN score loss: 0.00581 RPN total loss: 0.03252 Total loss: 1.28131 timestamp: 1655029891.702133 iteration: 28075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14316 FastRCNN class loss: 0.11465 FastRCNN total loss: 0.25781 L1 loss: 0.0000e+00 L2 loss: 0.84743 Learning rate: 0.02 Mask loss: 0.20027 RPN box loss: 0.02127 RPN score loss: 0.00516 RPN total loss: 0.02643 Total loss: 1.33194 timestamp: 1655029894.927119 iteration: 28080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1834 FastRCNN class loss: 0.10028 FastRCNN total loss: 0.28368 L1 loss: 0.0000e+00 L2 loss: 0.84731 Learning rate: 0.02 Mask loss: 0.20517 RPN box loss: 0.0412 RPN score loss: 0.00576 RPN total loss: 0.04696 Total loss: 1.38313 timestamp: 1655029898.203332 iteration: 28085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11318 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.17861 L1 loss: 0.0000e+00 L2 loss: 0.8472 Learning rate: 0.02 Mask loss: 0.39284 RPN box loss: 0.00751 RPN score loss: 0.00416 RPN total loss: 0.01167 Total loss: 1.43033 timestamp: 1655029901.474505 iteration: 28090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12183 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.17293 L1 loss: 0.0000e+00 L2 loss: 0.84708 Learning rate: 0.02 Mask loss: 0.12949 RPN box loss: 0.02025 RPN score loss: 0.00893 RPN total loss: 0.02919 Total loss: 1.17868 timestamp: 1655029904.747153 iteration: 28095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10625 FastRCNN class loss: 0.08724 FastRCNN total loss: 0.19349 L1 loss: 0.0000e+00 L2 loss: 0.84694 Learning rate: 0.02 Mask loss: 0.11977 RPN box loss: 0.04422 RPN score loss: 0.00492 RPN total loss: 0.04913 Total loss: 1.20934 timestamp: 1655029908.0500731 iteration: 28100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1255 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.17724 L1 loss: 0.0000e+00 L2 loss: 0.84679 Learning rate: 0.02 Mask loss: 0.14992 RPN box loss: 0.04731 RPN score loss: 0.00163 RPN total loss: 0.04894 Total loss: 1.22289 timestamp: 1655029911.3171782 iteration: 28105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13333 FastRCNN class loss: 0.09658 FastRCNN total loss: 0.22991 L1 loss: 0.0000e+00 L2 loss: 0.84665 Learning rate: 0.02 Mask loss: 0.28476 RPN box loss: 0.07076 RPN score loss: 0.03573 RPN total loss: 0.10649 Total loss: 1.46781 timestamp: 1655029914.5494685 iteration: 28110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1092 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.17551 L1 loss: 0.0000e+00 L2 loss: 0.84653 Learning rate: 0.02 Mask loss: 0.16389 RPN box loss: 0.03379 RPN score loss: 0.00512 RPN total loss: 0.03891 Total loss: 1.22484 timestamp: 1655029917.7981296 iteration: 28115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11004 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.19442 L1 loss: 0.0000e+00 L2 loss: 0.84644 Learning rate: 0.02 Mask loss: 0.11961 RPN box loss: 0.03171 RPN score loss: 0.00418 RPN total loss: 0.03589 Total loss: 1.19636 timestamp: 1655029921.0004485 iteration: 28120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15455 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.22121 L1 loss: 0.0000e+00 L2 loss: 0.84632 Learning rate: 0.02 Mask loss: 0.16588 RPN box loss: 0.02862 RPN score loss: 0.00253 RPN total loss: 0.03116 Total loss: 1.26456 timestamp: 1655029924.308049 iteration: 28125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27878 FastRCNN class loss: 0.21727 FastRCNN total loss: 0.49605 L1 loss: 0.0000e+00 L2 loss: 0.8462 Learning rate: 0.02 Mask loss: 0.22282 RPN box loss: 0.05247 RPN score loss: 0.01997 RPN total loss: 0.07244 Total loss: 1.6375 timestamp: 1655029927.5853193 iteration: 28130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15175 FastRCNN class loss: 0.072 FastRCNN total loss: 0.22375 L1 loss: 0.0000e+00 L2 loss: 0.84604 Learning rate: 0.02 Mask loss: 0.10474 RPN box loss: 0.02955 RPN score loss: 0.00689 RPN total loss: 0.03644 Total loss: 1.21097 timestamp: 1655029930.9003026 iteration: 28135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08759 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.13895 L1 loss: 0.0000e+00 L2 loss: 0.84587 Learning rate: 0.02 Mask loss: 0.169 RPN box loss: 0.03557 RPN score loss: 0.00614 RPN total loss: 0.04171 Total loss: 1.19554 timestamp: 1655029934.2025955 iteration: 28140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08851 FastRCNN class loss: 0.06093 FastRCNN total loss: 0.14945 L1 loss: 0.0000e+00 L2 loss: 0.84575 Learning rate: 0.02 Mask loss: 0.10655 RPN box loss: 0.06054 RPN score loss: 0.00987 RPN total loss: 0.0704 Total loss: 1.17215 timestamp: 1655029937.476059 iteration: 28145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1154 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.18958 L1 loss: 0.0000e+00 L2 loss: 0.84561 Learning rate: 0.02 Mask loss: 0.34878 RPN box loss: 0.04004 RPN score loss: 0.00538 RPN total loss: 0.04542 Total loss: 1.42939 timestamp: 1655029940.7605453 iteration: 28150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21445 FastRCNN class loss: 0.23055 FastRCNN total loss: 0.445 L1 loss: 0.0000e+00 L2 loss: 0.84549 Learning rate: 0.02 Mask loss: 0.2104 RPN box loss: 0.04262 RPN score loss: 0.01308 RPN total loss: 0.0557 Total loss: 1.55658 timestamp: 1655029944.0617688 iteration: 28155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10454 FastRCNN class loss: 0.04122 FastRCNN total loss: 0.14576 L1 loss: 0.0000e+00 L2 loss: 0.84538 Learning rate: 0.02 Mask loss: 0.14899 RPN box loss: 0.02624 RPN score loss: 0.00882 RPN total loss: 0.03506 Total loss: 1.17519 timestamp: 1655029947.36341 iteration: 28160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21523 FastRCNN class loss: 0.11631 FastRCNN total loss: 0.33153 L1 loss: 0.0000e+00 L2 loss: 0.84524 Learning rate: 0.02 Mask loss: 0.1469 RPN box loss: 0.04415 RPN score loss: 0.01084 RPN total loss: 0.05498 Total loss: 1.37867 timestamp: 1655029950.6130383 iteration: 28165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11265 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.17223 L1 loss: 0.0000e+00 L2 loss: 0.84511 Learning rate: 0.02 Mask loss: 0.16355 RPN box loss: 0.03386 RPN score loss: 0.00617 RPN total loss: 0.04003 Total loss: 1.22092 timestamp: 1655029953.8615851 iteration: 28170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14163 FastRCNN class loss: 0.08352 FastRCNN total loss: 0.22515 L1 loss: 0.0000e+00 L2 loss: 0.84498 Learning rate: 0.02 Mask loss: 0.1971 RPN box loss: 0.02855 RPN score loss: 0.0177 RPN total loss: 0.04625 Total loss: 1.31348 timestamp: 1655029957.210325 iteration: 28175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12822 FastRCNN class loss: 0.10033 FastRCNN total loss: 0.22856 L1 loss: 0.0000e+00 L2 loss: 0.84485 Learning rate: 0.02 Mask loss: 0.17034 RPN box loss: 0.01309 RPN score loss: 0.00264 RPN total loss: 0.01574 Total loss: 1.25948 timestamp: 1655029960.4927213 iteration: 28180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16383 FastRCNN class loss: 0.14081 FastRCNN total loss: 0.30464 L1 loss: 0.0000e+00 L2 loss: 0.84473 Learning rate: 0.02 Mask loss: 0.17801 RPN box loss: 0.02632 RPN score loss: 0.00793 RPN total loss: 0.03426 Total loss: 1.36163 timestamp: 1655029963.7229626 iteration: 28185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1511 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.22283 L1 loss: 0.0000e+00 L2 loss: 0.84462 Learning rate: 0.02 Mask loss: 0.15194 RPN box loss: 0.01205 RPN score loss: 0.00451 RPN total loss: 0.01655 Total loss: 1.23593 timestamp: 1655029967.0898318 iteration: 28190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.11369 FastRCNN total loss: 0.24049 L1 loss: 0.0000e+00 L2 loss: 0.84448 Learning rate: 0.02 Mask loss: 0.16286 RPN box loss: 0.02525 RPN score loss: 0.00416 RPN total loss: 0.02942 Total loss: 1.27725 timestamp: 1655029970.352107 iteration: 28195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10773 FastRCNN class loss: 0.03737 FastRCNN total loss: 0.14509 L1 loss: 0.0000e+00 L2 loss: 0.84437 Learning rate: 0.02 Mask loss: 0.12134 RPN box loss: 0.03423 RPN score loss: 0.00521 RPN total loss: 0.03944 Total loss: 1.15024 timestamp: 1655029973.627992 iteration: 28200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10911 FastRCNN class loss: 0.07572 FastRCNN total loss: 0.18483 L1 loss: 0.0000e+00 L2 loss: 0.84423 Learning rate: 0.02 Mask loss: 0.13374 RPN box loss: 0.02185 RPN score loss: 0.0162 RPN total loss: 0.03806 Total loss: 1.20086 timestamp: 1655029976.8479874 iteration: 28205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1686 FastRCNN class loss: 0.09237 FastRCNN total loss: 0.26097 L1 loss: 0.0000e+00 L2 loss: 0.8441 Learning rate: 0.02 Mask loss: 0.14393 RPN box loss: 0.06399 RPN score loss: 0.00858 RPN total loss: 0.07257 Total loss: 1.32156 timestamp: 1655029980.126698 iteration: 28210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19166 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.2612 L1 loss: 0.0000e+00 L2 loss: 0.84396 Learning rate: 0.02 Mask loss: 0.1623 RPN box loss: 0.03696 RPN score loss: 0.0116 RPN total loss: 0.04856 Total loss: 1.31602 timestamp: 1655029983.4410925 iteration: 28215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0963 FastRCNN class loss: 0.0436 FastRCNN total loss: 0.1399 L1 loss: 0.0000e+00 L2 loss: 0.84381 Learning rate: 0.02 Mask loss: 0.08458 RPN box loss: 0.06486 RPN score loss: 0.00369 RPN total loss: 0.06855 Total loss: 1.13684 timestamp: 1655029986.7024367 iteration: 28220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17683 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.25248 L1 loss: 0.0000e+00 L2 loss: 0.84371 Learning rate: 0.02 Mask loss: 0.19185 RPN box loss: 0.0236 RPN score loss: 0.00427 RPN total loss: 0.02787 Total loss: 1.31591 timestamp: 1655029989.9343903 iteration: 28225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12152 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 0.84357 Learning rate: 0.02 Mask loss: 0.15691 RPN box loss: 0.03176 RPN score loss: 0.00676 RPN total loss: 0.03851 Total loss: 1.22814 timestamp: 1655029993.203595 iteration: 28230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.22265 L1 loss: 0.0000e+00 L2 loss: 0.84344 Learning rate: 0.02 Mask loss: 0.18246 RPN box loss: 0.01414 RPN score loss: 0.00509 RPN total loss: 0.01924 Total loss: 1.26779 timestamp: 1655029996.4558759 iteration: 28235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1099 FastRCNN class loss: 0.0677 FastRCNN total loss: 0.1776 L1 loss: 0.0000e+00 L2 loss: 0.84332 Learning rate: 0.02 Mask loss: 0.1599 RPN box loss: 0.02322 RPN score loss: 0.00476 RPN total loss: 0.02798 Total loss: 1.2088 timestamp: 1655029999.7493808 iteration: 28240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17849 FastRCNN class loss: 0.09478 FastRCNN total loss: 0.27327 L1 loss: 0.0000e+00 L2 loss: 0.84319 Learning rate: 0.02 Mask loss: 0.22299 RPN box loss: 0.02469 RPN score loss: 0.01113 RPN total loss: 0.03582 Total loss: 1.37527 timestamp: 1655030003.045504 iteration: 28245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09248 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.16309 L1 loss: 0.0000e+00 L2 loss: 0.84303 Learning rate: 0.02 Mask loss: 0.14883 RPN box loss: 0.01122 RPN score loss: 0.00238 RPN total loss: 0.01359 Total loss: 1.16855 timestamp: 1655030006.316554 iteration: 28250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22436 FastRCNN class loss: 0.14628 FastRCNN total loss: 0.37064 L1 loss: 0.0000e+00 L2 loss: 0.84289 Learning rate: 0.02 Mask loss: 0.20948 RPN box loss: 0.04594 RPN score loss: 0.02075 RPN total loss: 0.06668 Total loss: 1.4897 timestamp: 1655030009.5853865 iteration: 28255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10574 FastRCNN class loss: 0.04912 FastRCNN total loss: 0.15486 L1 loss: 0.0000e+00 L2 loss: 0.84275 Learning rate: 0.02 Mask loss: 0.17043 RPN box loss: 0.04421 RPN score loss: 0.00538 RPN total loss: 0.04958 Total loss: 1.21763 timestamp: 1655030012.8297832 iteration: 28260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.22438 L1 loss: 0.0000e+00 L2 loss: 0.8426 Learning rate: 0.02 Mask loss: 0.14861 RPN box loss: 0.03462 RPN score loss: 0.00585 RPN total loss: 0.04047 Total loss: 1.25606 timestamp: 1655030016.1091805 iteration: 28265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15677 FastRCNN class loss: 0.0646 FastRCNN total loss: 0.22137 L1 loss: 0.0000e+00 L2 loss: 0.84249 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.01392 RPN score loss: 0.00503 RPN total loss: 0.01895 Total loss: 1.2567 timestamp: 1655030019.4797976 iteration: 28270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17447 FastRCNN class loss: 0.12596 FastRCNN total loss: 0.30043 L1 loss: 0.0000e+00 L2 loss: 0.84237 Learning rate: 0.02 Mask loss: 0.30591 RPN box loss: 0.04451 RPN score loss: 0.00751 RPN total loss: 0.05202 Total loss: 1.50073 timestamp: 1655030022.7959857 iteration: 28275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14789 FastRCNN class loss: 0.11004 FastRCNN total loss: 0.25793 L1 loss: 0.0000e+00 L2 loss: 0.84223 Learning rate: 0.02 Mask loss: 0.18486 RPN box loss: 0.04119 RPN score loss: 0.00414 RPN total loss: 0.04533 Total loss: 1.33035 timestamp: 1655030026.0412452 iteration: 28280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21858 FastRCNN class loss: 0.12033 FastRCNN total loss: 0.33891 L1 loss: 0.0000e+00 L2 loss: 0.84211 Learning rate: 0.02 Mask loss: 0.30073 RPN box loss: 0.01686 RPN score loss: 0.00411 RPN total loss: 0.02096 Total loss: 1.50271 timestamp: 1655030029.3224926 iteration: 28285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15318 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.23009 L1 loss: 0.0000e+00 L2 loss: 0.84197 Learning rate: 0.02 Mask loss: 0.15377 RPN box loss: 0.01301 RPN score loss: 0.00364 RPN total loss: 0.01665 Total loss: 1.24248 timestamp: 1655030032.6929924 iteration: 28290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19604 FastRCNN class loss: 0.12462 FastRCNN total loss: 0.32066 L1 loss: 0.0000e+00 L2 loss: 0.84184 Learning rate: 0.02 Mask loss: 0.24687 RPN box loss: 0.0297 RPN score loss: 0.00461 RPN total loss: 0.03431 Total loss: 1.44368 timestamp: 1655030035.942563 iteration: 28295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14709 FastRCNN class loss: 0.13506 FastRCNN total loss: 0.28215 L1 loss: 0.0000e+00 L2 loss: 0.84169 Learning rate: 0.02 Mask loss: 0.1904 RPN box loss: 0.05644 RPN score loss: 0.01046 RPN total loss: 0.0669 Total loss: 1.38114 timestamp: 1655030039.27362 iteration: 28300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13856 FastRCNN class loss: 0.18487 FastRCNN total loss: 0.32343 L1 loss: 0.0000e+00 L2 loss: 0.84155 Learning rate: 0.02 Mask loss: 0.21272 RPN box loss: 0.05054 RPN score loss: 0.01531 RPN total loss: 0.06584 Total loss: 1.44354 timestamp: 1655030042.550548 iteration: 28305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20143 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.2838 L1 loss: 0.0000e+00 L2 loss: 0.84145 Learning rate: 0.02 Mask loss: 0.12683 RPN box loss: 0.05902 RPN score loss: 0.00357 RPN total loss: 0.06259 Total loss: 1.31466 timestamp: 1655030045.8456454 iteration: 28310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21112 FastRCNN class loss: 0.16515 FastRCNN total loss: 0.37627 L1 loss: 0.0000e+00 L2 loss: 0.84134 Learning rate: 0.02 Mask loss: 0.24574 RPN box loss: 0.05106 RPN score loss: 0.02313 RPN total loss: 0.07419 Total loss: 1.53753 timestamp: 1655030049.111759 iteration: 28315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16633 FastRCNN class loss: 0.16157 FastRCNN total loss: 0.3279 L1 loss: 0.0000e+00 L2 loss: 0.84121 Learning rate: 0.02 Mask loss: 0.20133 RPN box loss: 0.05787 RPN score loss: 0.01175 RPN total loss: 0.06962 Total loss: 1.44007 timestamp: 1655030052.485323 iteration: 28320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13183 FastRCNN class loss: 0.1027 FastRCNN total loss: 0.23453 L1 loss: 0.0000e+00 L2 loss: 0.84105 Learning rate: 0.02 Mask loss: 0.15537 RPN box loss: 0.02084 RPN score loss: 0.00688 RPN total loss: 0.02772 Total loss: 1.25867 timestamp: 1655030055.7828374 iteration: 28325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12091 FastRCNN class loss: 0.07317 FastRCNN total loss: 0.19408 L1 loss: 0.0000e+00 L2 loss: 0.84093 Learning rate: 0.02 Mask loss: 0.11322 RPN box loss: 0.02664 RPN score loss: 0.00619 RPN total loss: 0.03283 Total loss: 1.18106 timestamp: 1655030059.1154258 iteration: 28330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.08884 FastRCNN total loss: 0.2214 L1 loss: 0.0000e+00 L2 loss: 0.84081 Learning rate: 0.02 Mask loss: 0.1573 RPN box loss: 0.01021 RPN score loss: 0.0048 RPN total loss: 0.01501 Total loss: 1.23452 timestamp: 1655030062.4278634 iteration: 28335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12138 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.20727 L1 loss: 0.0000e+00 L2 loss: 0.84067 Learning rate: 0.02 Mask loss: 0.15747 RPN box loss: 0.05828 RPN score loss: 0.00716 RPN total loss: 0.06544 Total loss: 1.27085 timestamp: 1655030065.7388506 iteration: 28340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1323 FastRCNN class loss: 0.09819 FastRCNN total loss: 0.23048 L1 loss: 0.0000e+00 L2 loss: 0.84053 Learning rate: 0.02 Mask loss: 0.21452 RPN box loss: 0.02748 RPN score loss: 0.00197 RPN total loss: 0.02945 Total loss: 1.31499 timestamp: 1655030069.0341327 iteration: 28345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15621 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.24013 L1 loss: 0.0000e+00 L2 loss: 0.84042 Learning rate: 0.02 Mask loss: 0.17621 RPN box loss: 0.02239 RPN score loss: 0.00636 RPN total loss: 0.02875 Total loss: 1.28551 timestamp: 1655030072.2632034 iteration: 28350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21151 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.29999 L1 loss: 0.0000e+00 L2 loss: 0.84031 Learning rate: 0.02 Mask loss: 0.23595 RPN box loss: 0.03906 RPN score loss: 0.00385 RPN total loss: 0.04291 Total loss: 1.41916 timestamp: 1655030075.4843543 iteration: 28355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19731 FastRCNN class loss: 0.08877 FastRCNN total loss: 0.28608 L1 loss: 0.0000e+00 L2 loss: 0.84018 Learning rate: 0.02 Mask loss: 0.16189 RPN box loss: 0.03194 RPN score loss: 0.00842 RPN total loss: 0.04036 Total loss: 1.32851 timestamp: 1655030078.7936954 iteration: 28360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15282 FastRCNN class loss: 0.10353 FastRCNN total loss: 0.25635 L1 loss: 0.0000e+00 L2 loss: 0.84003 Learning rate: 0.02 Mask loss: 0.14545 RPN box loss: 0.01661 RPN score loss: 0.00347 RPN total loss: 0.02008 Total loss: 1.26191 timestamp: 1655030081.9944475 iteration: 28365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09751 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.14564 L1 loss: 0.0000e+00 L2 loss: 0.8399 Learning rate: 0.02 Mask loss: 0.14501 RPN box loss: 0.01585 RPN score loss: 0.00268 RPN total loss: 0.01853 Total loss: 1.14908 timestamp: 1655030085.268367 iteration: 28370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15176 FastRCNN class loss: 0.11096 FastRCNN total loss: 0.26272 L1 loss: 0.0000e+00 L2 loss: 0.83976 Learning rate: 0.02 Mask loss: 0.1698 RPN box loss: 0.01578 RPN score loss: 0.00438 RPN total loss: 0.02016 Total loss: 1.29245 timestamp: 1655030088.5674577 iteration: 28375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13285 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.19271 L1 loss: 0.0000e+00 L2 loss: 0.83963 Learning rate: 0.02 Mask loss: 0.15744 RPN box loss: 0.01126 RPN score loss: 0.00167 RPN total loss: 0.01293 Total loss: 1.20271 timestamp: 1655030091.783246 iteration: 28380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.10997 FastRCNN total loss: 0.26167 L1 loss: 0.0000e+00 L2 loss: 0.83951 Learning rate: 0.02 Mask loss: 0.16369 RPN box loss: 0.04932 RPN score loss: 0.01082 RPN total loss: 0.06014 Total loss: 1.325 timestamp: 1655030095.0757616 iteration: 28385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23164 FastRCNN class loss: 0.09279 FastRCNN total loss: 0.32443 L1 loss: 0.0000e+00 L2 loss: 0.83936 Learning rate: 0.02 Mask loss: 0.1973 RPN box loss: 0.01713 RPN score loss: 0.00406 RPN total loss: 0.02118 Total loss: 1.38227 timestamp: 1655030098.3069592 iteration: 28390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13396 FastRCNN class loss: 0.08646 FastRCNN total loss: 0.22042 L1 loss: 0.0000e+00 L2 loss: 0.83925 Learning rate: 0.02 Mask loss: 0.15197 RPN box loss: 0.03437 RPN score loss: 0.00895 RPN total loss: 0.04331 Total loss: 1.25496 timestamp: 1655030101.5929732 iteration: 28395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13008 FastRCNN class loss: 0.04865 FastRCNN total loss: 0.17873 L1 loss: 0.0000e+00 L2 loss: 0.83912 Learning rate: 0.02 Mask loss: 0.10137 RPN box loss: 0.02899 RPN score loss: 0.00577 RPN total loss: 0.03476 Total loss: 1.15398 timestamp: 1655030104.8572433 iteration: 28400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20322 FastRCNN class loss: 0.11185 FastRCNN total loss: 0.31506 L1 loss: 0.0000e+00 L2 loss: 0.83897 Learning rate: 0.02 Mask loss: 0.1851 RPN box loss: 0.09296 RPN score loss: 0.02016 RPN total loss: 0.11312 Total loss: 1.45226 timestamp: 1655030108.0862377 iteration: 28405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13976 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.21456 L1 loss: 0.0000e+00 L2 loss: 0.83886 Learning rate: 0.02 Mask loss: 0.10574 RPN box loss: 0.0073 RPN score loss: 0.00598 RPN total loss: 0.01328 Total loss: 1.17245 timestamp: 1655030111.3718462 iteration: 28410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20191 FastRCNN class loss: 0.17228 FastRCNN total loss: 0.3742 L1 loss: 0.0000e+00 L2 loss: 0.83873 Learning rate: 0.02 Mask loss: 0.17514 RPN box loss: 0.01803 RPN score loss: 0.02262 RPN total loss: 0.04065 Total loss: 1.42872 timestamp: 1655030114.6303318 iteration: 28415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15921 FastRCNN class loss: 0.13766 FastRCNN total loss: 0.29687 L1 loss: 0.0000e+00 L2 loss: 0.8386 Learning rate: 0.02 Mask loss: 0.21891 RPN box loss: 0.05371 RPN score loss: 0.00957 RPN total loss: 0.06328 Total loss: 1.41766 timestamp: 1655030117.910262 iteration: 28420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09763 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.1786 L1 loss: 0.0000e+00 L2 loss: 0.83847 Learning rate: 0.02 Mask loss: 0.17118 RPN box loss: 0.06515 RPN score loss: 0.01474 RPN total loss: 0.07989 Total loss: 1.26813 timestamp: 1655030121.164685 iteration: 28425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.1643 L1 loss: 0.0000e+00 L2 loss: 0.83834 Learning rate: 0.02 Mask loss: 0.07501 RPN box loss: 0.06016 RPN score loss: 0.00124 RPN total loss: 0.06141 Total loss: 1.13906 timestamp: 1655030124.4365423 iteration: 28430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14958 FastRCNN class loss: 0.08754 FastRCNN total loss: 0.23712 L1 loss: 0.0000e+00 L2 loss: 0.83821 Learning rate: 0.02 Mask loss: 0.22408 RPN box loss: 0.02937 RPN score loss: 0.01067 RPN total loss: 0.04004 Total loss: 1.33946 timestamp: 1655030127.7200434 iteration: 28435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2103 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.30517 L1 loss: 0.0000e+00 L2 loss: 0.83809 Learning rate: 0.02 Mask loss: 0.20734 RPN box loss: 0.0408 RPN score loss: 0.0158 RPN total loss: 0.0566 Total loss: 1.40719 timestamp: 1655030130.9298427 iteration: 28440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12262 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.19803 L1 loss: 0.0000e+00 L2 loss: 0.83798 Learning rate: 0.02 Mask loss: 0.147 RPN box loss: 0.01405 RPN score loss: 0.00493 RPN total loss: 0.01898 Total loss: 1.20199 timestamp: 1655030134.13591 iteration: 28445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12269 FastRCNN class loss: 0.05813 FastRCNN total loss: 0.18083 L1 loss: 0.0000e+00 L2 loss: 0.83785 Learning rate: 0.02 Mask loss: 0.11138 RPN box loss: 0.03217 RPN score loss: 0.00443 RPN total loss: 0.03659 Total loss: 1.16665 timestamp: 1655030137.4500659 iteration: 28450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22388 FastRCNN class loss: 0.09834 FastRCNN total loss: 0.32222 L1 loss: 0.0000e+00 L2 loss: 0.83771 Learning rate: 0.02 Mask loss: 0.22038 RPN box loss: 0.04698 RPN score loss: 0.00648 RPN total loss: 0.05347 Total loss: 1.43378 timestamp: 1655030140.6523762 iteration: 28455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11147 FastRCNN class loss: 0.07562 FastRCNN total loss: 0.18709 L1 loss: 0.0000e+00 L2 loss: 0.83756 Learning rate: 0.02 Mask loss: 0.1464 RPN box loss: 0.06437 RPN score loss: 0.01854 RPN total loss: 0.08291 Total loss: 1.25396 timestamp: 1655030143.8881605 iteration: 28460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16183 FastRCNN class loss: 0.12526 FastRCNN total loss: 0.28709 L1 loss: 0.0000e+00 L2 loss: 0.83745 Learning rate: 0.02 Mask loss: 0.3407 RPN box loss: 0.03915 RPN score loss: 0.00551 RPN total loss: 0.04467 Total loss: 1.50992 timestamp: 1655030147.11437 iteration: 28465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09752 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.15284 L1 loss: 0.0000e+00 L2 loss: 0.8373 Learning rate: 0.02 Mask loss: 0.12049 RPN box loss: 0.01615 RPN score loss: 0.00237 RPN total loss: 0.01853 Total loss: 1.12915 timestamp: 1655030150.3534684 iteration: 28470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.07422 FastRCNN total loss: 0.19986 L1 loss: 0.0000e+00 L2 loss: 0.83714 Learning rate: 0.02 Mask loss: 0.24175 RPN box loss: 0.03441 RPN score loss: 0.00739 RPN total loss: 0.04181 Total loss: 1.32055 timestamp: 1655030153.6007614 iteration: 28475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.08958 FastRCNN total loss: 0.19097 L1 loss: 0.0000e+00 L2 loss: 0.837 Learning rate: 0.02 Mask loss: 0.14084 RPN box loss: 0.02364 RPN score loss: 0.01001 RPN total loss: 0.03365 Total loss: 1.20246 timestamp: 1655030156.886347 iteration: 28480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16914 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.24273 L1 loss: 0.0000e+00 L2 loss: 0.83688 Learning rate: 0.02 Mask loss: 0.19989 RPN box loss: 0.02199 RPN score loss: 0.02531 RPN total loss: 0.0473 Total loss: 1.3268 timestamp: 1655030160.1104755 iteration: 28485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.19565 L1 loss: 0.0000e+00 L2 loss: 0.83675 Learning rate: 0.02 Mask loss: 0.15905 RPN box loss: 0.06269 RPN score loss: 0.00557 RPN total loss: 0.06826 Total loss: 1.25972 timestamp: 1655030163.3853147 iteration: 28490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10368 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.17062 L1 loss: 0.0000e+00 L2 loss: 0.83665 Learning rate: 0.02 Mask loss: 0.14052 RPN box loss: 0.06084 RPN score loss: 0.00783 RPN total loss: 0.06867 Total loss: 1.21645 timestamp: 1655030166.6963737 iteration: 28495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11193 FastRCNN class loss: 0.06568 FastRCNN total loss: 0.17762 L1 loss: 0.0000e+00 L2 loss: 0.8365 Learning rate: 0.02 Mask loss: 0.08187 RPN box loss: 0.02495 RPN score loss: 0.00642 RPN total loss: 0.03137 Total loss: 1.12736 timestamp: 1655030169.95731 iteration: 28500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10725 FastRCNN class loss: 0.09633 FastRCNN total loss: 0.20359 L1 loss: 0.0000e+00 L2 loss: 0.83637 Learning rate: 0.02 Mask loss: 0.2338 RPN box loss: 0.07086 RPN score loss: 0.00688 RPN total loss: 0.07774 Total loss: 1.3515 timestamp: 1655030173.24516 iteration: 28505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10038 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.1698 L1 loss: 0.0000e+00 L2 loss: 0.83626 Learning rate: 0.02 Mask loss: 0.16569 RPN box loss: 0.02401 RPN score loss: 0.00791 RPN total loss: 0.03191 Total loss: 1.20366 timestamp: 1655030176.5261059 iteration: 28510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20612 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.30796 L1 loss: 0.0000e+00 L2 loss: 0.83616 Learning rate: 0.02 Mask loss: 0.23956 RPN box loss: 0.01 RPN score loss: 0.01461 RPN total loss: 0.02461 Total loss: 1.40829 timestamp: 1655030179.8466551 iteration: 28515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11415 FastRCNN class loss: 0.05494 FastRCNN total loss: 0.16908 L1 loss: 0.0000e+00 L2 loss: 0.83604 Learning rate: 0.02 Mask loss: 0.10794 RPN box loss: 0.04132 RPN score loss: 0.00895 RPN total loss: 0.05026 Total loss: 1.16333 timestamp: 1655030183.1049492 iteration: 28520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12879 FastRCNN class loss: 0.05819 FastRCNN total loss: 0.18697 L1 loss: 0.0000e+00 L2 loss: 0.83591 Learning rate: 0.02 Mask loss: 0.15058 RPN box loss: 0.00969 RPN score loss: 0.00388 RPN total loss: 0.01357 Total loss: 1.18703 timestamp: 1655030186.3950994 iteration: 28525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14308 FastRCNN class loss: 0.07375 FastRCNN total loss: 0.21683 L1 loss: 0.0000e+00 L2 loss: 0.83579 Learning rate: 0.02 Mask loss: 0.10988 RPN box loss: 0.01933 RPN score loss: 0.0028 RPN total loss: 0.02212 Total loss: 1.18462 timestamp: 1655030189.6347113 iteration: 28530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16714 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.25177 L1 loss: 0.0000e+00 L2 loss: 0.83566 Learning rate: 0.02 Mask loss: 0.15313 RPN box loss: 0.03221 RPN score loss: 0.00684 RPN total loss: 0.03905 Total loss: 1.27961 timestamp: 1655030192.8756151 iteration: 28535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10713 FastRCNN class loss: 0.11553 FastRCNN total loss: 0.22265 L1 loss: 0.0000e+00 L2 loss: 0.83551 Learning rate: 0.02 Mask loss: 0.24751 RPN box loss: 0.01538 RPN score loss: 0.00338 RPN total loss: 0.01876 Total loss: 1.32443 timestamp: 1655030196.1496954 iteration: 28540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25007 FastRCNN class loss: 0.1098 FastRCNN total loss: 0.35986 L1 loss: 0.0000e+00 L2 loss: 0.83537 Learning rate: 0.02 Mask loss: 0.17914 RPN box loss: 0.01738 RPN score loss: 0.00772 RPN total loss: 0.0251 Total loss: 1.39947 timestamp: 1655030199.3787985 iteration: 28545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16263 FastRCNN class loss: 0.10046 FastRCNN total loss: 0.26309 L1 loss: 0.0000e+00 L2 loss: 0.83523 Learning rate: 0.02 Mask loss: 0.20712 RPN box loss: 0.01924 RPN score loss: 0.00743 RPN total loss: 0.02667 Total loss: 1.33211 timestamp: 1655030202.65975 iteration: 28550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.08728 FastRCNN total loss: 0.19949 L1 loss: 0.0000e+00 L2 loss: 0.83509 Learning rate: 0.02 Mask loss: 0.2018 RPN box loss: 0.02553 RPN score loss: 0.01475 RPN total loss: 0.04028 Total loss: 1.27665 timestamp: 1655030206.0219069 iteration: 28555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1527 FastRCNN class loss: 0.13148 FastRCNN total loss: 0.28418 L1 loss: 0.0000e+00 L2 loss: 0.83497 Learning rate: 0.02 Mask loss: 0.19083 RPN box loss: 0.09152 RPN score loss: 0.01612 RPN total loss: 0.10764 Total loss: 1.41762 timestamp: 1655030209.2705417 iteration: 28560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16944 FastRCNN class loss: 0.12136 FastRCNN total loss: 0.29081 L1 loss: 0.0000e+00 L2 loss: 0.83486 Learning rate: 0.02 Mask loss: 0.2403 RPN box loss: 0.04576 RPN score loss: 0.01884 RPN total loss: 0.0646 Total loss: 1.43056 timestamp: 1655030212.5265179 iteration: 28565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13741 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.22724 L1 loss: 0.0000e+00 L2 loss: 0.83474 Learning rate: 0.02 Mask loss: 0.13348 RPN box loss: 0.02274 RPN score loss: 0.00476 RPN total loss: 0.0275 Total loss: 1.22296 timestamp: 1655030215.9218085 iteration: 28570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12704 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.21296 L1 loss: 0.0000e+00 L2 loss: 0.83461 Learning rate: 0.02 Mask loss: 0.1225 RPN box loss: 0.05488 RPN score loss: 0.00725 RPN total loss: 0.06213 Total loss: 1.2322 timestamp: 1655030219.1870935 iteration: 28575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13321 FastRCNN class loss: 0.08516 FastRCNN total loss: 0.21837 L1 loss: 0.0000e+00 L2 loss: 0.83448 Learning rate: 0.02 Mask loss: 0.12851 RPN box loss: 0.0438 RPN score loss: 0.01175 RPN total loss: 0.05555 Total loss: 1.23691 timestamp: 1655030222.4469066 iteration: 28580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13347 FastRCNN class loss: 0.09812 FastRCNN total loss: 0.23159 L1 loss: 0.0000e+00 L2 loss: 0.83434 Learning rate: 0.02 Mask loss: 0.15807 RPN box loss: 0.01907 RPN score loss: 0.00766 RPN total loss: 0.02674 Total loss: 1.25074 timestamp: 1655030225.66419 iteration: 28585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14726 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.24762 L1 loss: 0.0000e+00 L2 loss: 0.8342 Learning rate: 0.02 Mask loss: 0.16839 RPN box loss: 0.0614 RPN score loss: 0.01305 RPN total loss: 0.07445 Total loss: 1.32466 timestamp: 1655030228.9314816 iteration: 28590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13617 FastRCNN class loss: 0.11926 FastRCNN total loss: 0.25543 L1 loss: 0.0000e+00 L2 loss: 0.83406 Learning rate: 0.02 Mask loss: 0.22384 RPN box loss: 0.04698 RPN score loss: 0.00534 RPN total loss: 0.05232 Total loss: 1.36565 timestamp: 1655030232.2370188 iteration: 28595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.09091 FastRCNN total loss: 0.24265 L1 loss: 0.0000e+00 L2 loss: 0.83393 Learning rate: 0.02 Mask loss: 0.19401 RPN box loss: 0.01318 RPN score loss: 0.00536 RPN total loss: 0.01854 Total loss: 1.28913 timestamp: 1655030235.557866 iteration: 28600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19313 FastRCNN class loss: 0.17159 FastRCNN total loss: 0.36471 L1 loss: 0.0000e+00 L2 loss: 0.83381 Learning rate: 0.02 Mask loss: 0.22702 RPN box loss: 0.0619 RPN score loss: 0.01489 RPN total loss: 0.07679 Total loss: 1.50233 timestamp: 1655030238.8394392 iteration: 28605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08702 FastRCNN class loss: 0.11875 FastRCNN total loss: 0.20577 L1 loss: 0.0000e+00 L2 loss: 0.83366 Learning rate: 0.02 Mask loss: 0.15894 RPN box loss: 0.01976 RPN score loss: 0.01298 RPN total loss: 0.03274 Total loss: 1.2311 timestamp: 1655030242.1175113 iteration: 28610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12389 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.1822 L1 loss: 0.0000e+00 L2 loss: 0.83355 Learning rate: 0.02 Mask loss: 0.19858 RPN box loss: 0.05814 RPN score loss: 0.00663 RPN total loss: 0.06477 Total loss: 1.2791 timestamp: 1655030245.419533 iteration: 28615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14868 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.23729 L1 loss: 0.0000e+00 L2 loss: 0.83343 Learning rate: 0.02 Mask loss: 0.15332 RPN box loss: 0.0462 RPN score loss: 0.01303 RPN total loss: 0.05924 Total loss: 1.28327 timestamp: 1655030248.6920078 iteration: 28620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12447 FastRCNN class loss: 0.07052 FastRCNN total loss: 0.19498 L1 loss: 0.0000e+00 L2 loss: 0.8333 Learning rate: 0.02 Mask loss: 0.1085 RPN box loss: 0.04092 RPN score loss: 0.01277 RPN total loss: 0.05369 Total loss: 1.19048 timestamp: 1655030251.9747727 iteration: 28625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13578 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.20807 L1 loss: 0.0000e+00 L2 loss: 0.83316 Learning rate: 0.02 Mask loss: 0.18184 RPN box loss: 0.02613 RPN score loss: 0.00971 RPN total loss: 0.03584 Total loss: 1.25891 timestamp: 1655030255.1677206 iteration: 28630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08398 FastRCNN class loss: 0.05711 FastRCNN total loss: 0.1411 L1 loss: 0.0000e+00 L2 loss: 0.83301 Learning rate: 0.02 Mask loss: 0.15402 RPN box loss: 0.01182 RPN score loss: 0.00114 RPN total loss: 0.01296 Total loss: 1.14109 timestamp: 1655030258.4319308 iteration: 28635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22057 FastRCNN class loss: 0.12158 FastRCNN total loss: 0.34215 L1 loss: 0.0000e+00 L2 loss: 0.83291 Learning rate: 0.02 Mask loss: 0.19358 RPN box loss: 0.0807 RPN score loss: 0.02138 RPN total loss: 0.10208 Total loss: 1.47072 timestamp: 1655030261.637936 iteration: 28640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17409 FastRCNN class loss: 0.09379 FastRCNN total loss: 0.26788 L1 loss: 0.0000e+00 L2 loss: 0.83279 Learning rate: 0.02 Mask loss: 0.16393 RPN box loss: 0.0156 RPN score loss: 0.00747 RPN total loss: 0.02307 Total loss: 1.28768 timestamp: 1655030264.7942314 iteration: 28645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10213 FastRCNN class loss: 0.05863 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.83268 Learning rate: 0.02 Mask loss: 0.1235 RPN box loss: 0.04328 RPN score loss: 0.01093 RPN total loss: 0.0542 Total loss: 1.17115 timestamp: 1655030268.1197646 iteration: 28650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13547 FastRCNN class loss: 0.12191 FastRCNN total loss: 0.25739 L1 loss: 0.0000e+00 L2 loss: 0.83256 Learning rate: 0.02 Mask loss: 0.15856 RPN box loss: 0.02079 RPN score loss: 0.00369 RPN total loss: 0.02448 Total loss: 1.27299 timestamp: 1655030271.4394295 iteration: 28655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14594 FastRCNN class loss: 0.1353 FastRCNN total loss: 0.28124 L1 loss: 0.0000e+00 L2 loss: 0.83241 Learning rate: 0.02 Mask loss: 0.23136 RPN box loss: 0.02816 RPN score loss: 0.01047 RPN total loss: 0.03863 Total loss: 1.38363 timestamp: 1655030274.7367268 iteration: 28660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19479 FastRCNN class loss: 0.15269 FastRCNN total loss: 0.34748 L1 loss: 0.0000e+00 L2 loss: 0.83227 Learning rate: 0.02 Mask loss: 0.22636 RPN box loss: 0.03584 RPN score loss: 0.01003 RPN total loss: 0.04587 Total loss: 1.45198 timestamp: 1655030278.0753622 iteration: 28665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.129 FastRCNN class loss: 0.05636 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 0.83214 Learning rate: 0.02 Mask loss: 0.14327 RPN box loss: 0.0265 RPN score loss: 0.00485 RPN total loss: 0.03134 Total loss: 1.19212 timestamp: 1655030281.342505 iteration: 28670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22579 FastRCNN class loss: 0.13052 FastRCNN total loss: 0.3563 L1 loss: 0.0000e+00 L2 loss: 0.832 Learning rate: 0.02 Mask loss: 0.22421 RPN box loss: 0.0294 RPN score loss: 0.00606 RPN total loss: 0.03545 Total loss: 1.44797 timestamp: 1655030284.6428595 iteration: 28675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14934 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.21101 L1 loss: 0.0000e+00 L2 loss: 0.83184 Learning rate: 0.02 Mask loss: 0.13474 RPN box loss: 0.0397 RPN score loss: 0.00965 RPN total loss: 0.04935 Total loss: 1.22694 timestamp: 1655030287.9150858 iteration: 28680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15607 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.21082 L1 loss: 0.0000e+00 L2 loss: 0.83173 Learning rate: 0.02 Mask loss: 0.09385 RPN box loss: 0.01624 RPN score loss: 0.00483 RPN total loss: 0.02108 Total loss: 1.15748 timestamp: 1655030291.2127275 iteration: 28685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1992 FastRCNN class loss: 0.15007 FastRCNN total loss: 0.34927 L1 loss: 0.0000e+00 L2 loss: 0.83163 Learning rate: 0.02 Mask loss: 0.17178 RPN box loss: 0.04756 RPN score loss: 0.0087 RPN total loss: 0.05626 Total loss: 1.40894 timestamp: 1655030294.5382879 iteration: 28690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.08963 FastRCNN total loss: 0.21458 L1 loss: 0.0000e+00 L2 loss: 0.83151 Learning rate: 0.02 Mask loss: 0.15526 RPN box loss: 0.01082 RPN score loss: 0.0013 RPN total loss: 0.01212 Total loss: 1.21348 timestamp: 1655030297.8433683 iteration: 28695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1525 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.22988 L1 loss: 0.0000e+00 L2 loss: 0.83136 Learning rate: 0.02 Mask loss: 0.16233 RPN box loss: 0.0154 RPN score loss: 0.00577 RPN total loss: 0.02117 Total loss: 1.24474 timestamp: 1655030301.1246226 iteration: 28700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1643 FastRCNN class loss: 0.08216 FastRCNN total loss: 0.24646 L1 loss: 0.0000e+00 L2 loss: 0.83122 Learning rate: 0.02 Mask loss: 0.19564 RPN box loss: 0.01587 RPN score loss: 0.0117 RPN total loss: 0.02757 Total loss: 1.30089 timestamp: 1655030304.435583 iteration: 28705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13585 FastRCNN class loss: 0.09295 FastRCNN total loss: 0.2288 L1 loss: 0.0000e+00 L2 loss: 0.8311 Learning rate: 0.02 Mask loss: 0.16224 RPN box loss: 0.02776 RPN score loss: 0.00244 RPN total loss: 0.03019 Total loss: 1.25234 timestamp: 1655030307.7590032 iteration: 28710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13385 FastRCNN class loss: 0.05194 FastRCNN total loss: 0.18579 L1 loss: 0.0000e+00 L2 loss: 0.83099 Learning rate: 0.02 Mask loss: 0.14246 RPN box loss: 0.0036 RPN score loss: 0.00531 RPN total loss: 0.00891 Total loss: 1.16816 timestamp: 1655030310.9909208 iteration: 28715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16758 FastRCNN class loss: 0.10127 FastRCNN total loss: 0.26884 L1 loss: 0.0000e+00 L2 loss: 0.83088 Learning rate: 0.02 Mask loss: 0.18393 RPN box loss: 0.05497 RPN score loss: 0.01489 RPN total loss: 0.06986 Total loss: 1.35352 timestamp: 1655030314.2341447 iteration: 28720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20744 FastRCNN class loss: 0.09664 FastRCNN total loss: 0.30408 L1 loss: 0.0000e+00 L2 loss: 0.83075 Learning rate: 0.02 Mask loss: 0.18313 RPN box loss: 0.03913 RPN score loss: 0.00823 RPN total loss: 0.04736 Total loss: 1.36532 timestamp: 1655030317.5449486 iteration: 28725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07677 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.14782 L1 loss: 0.0000e+00 L2 loss: 0.83063 Learning rate: 0.02 Mask loss: 0.10194 RPN box loss: 0.00829 RPN score loss: 0.00305 RPN total loss: 0.01134 Total loss: 1.09173 timestamp: 1655030320.7994926 iteration: 28730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24673 FastRCNN class loss: 0.15705 FastRCNN total loss: 0.40378 L1 loss: 0.0000e+00 L2 loss: 0.8305 Learning rate: 0.02 Mask loss: 0.15624 RPN box loss: 0.0334 RPN score loss: 0.00921 RPN total loss: 0.04261 Total loss: 1.43313 timestamp: 1655030324.1435392 iteration: 28735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15219 FastRCNN class loss: 0.12825 FastRCNN total loss: 0.28044 L1 loss: 0.0000e+00 L2 loss: 0.83035 Learning rate: 0.02 Mask loss: 0.18428 RPN box loss: 0.04333 RPN score loss: 0.0123 RPN total loss: 0.05562 Total loss: 1.3507 timestamp: 1655030327.4150772 iteration: 28740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22771 FastRCNN class loss: 0.1224 FastRCNN total loss: 0.35011 L1 loss: 0.0000e+00 L2 loss: 0.83022 Learning rate: 0.02 Mask loss: 0.2395 RPN box loss: 0.06893 RPN score loss: 0.00821 RPN total loss: 0.07714 Total loss: 1.49697 timestamp: 1655030330.6861844 iteration: 28745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11171 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.17232 L1 loss: 0.0000e+00 L2 loss: 0.8301 Learning rate: 0.02 Mask loss: 0.13565 RPN box loss: 0.0085 RPN score loss: 0.00518 RPN total loss: 0.01368 Total loss: 1.15176 timestamp: 1655030333.952316 iteration: 28750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.09513 FastRCNN total loss: 0.19941 L1 loss: 0.0000e+00 L2 loss: 0.82995 Learning rate: 0.02 Mask loss: 0.19934 RPN box loss: 0.05687 RPN score loss: 0.00958 RPN total loss: 0.06645 Total loss: 1.29515 timestamp: 1655030337.291262 iteration: 28755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16402 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.24737 L1 loss: 0.0000e+00 L2 loss: 0.82983 Learning rate: 0.02 Mask loss: 0.15168 RPN box loss: 0.01397 RPN score loss: 0.00213 RPN total loss: 0.0161 Total loss: 1.24499 timestamp: 1655030340.6230247 iteration: 28760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13925 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.19821 L1 loss: 0.0000e+00 L2 loss: 0.82971 Learning rate: 0.02 Mask loss: 0.14491 RPN box loss: 0.00772 RPN score loss: 0.00501 RPN total loss: 0.01273 Total loss: 1.18556 timestamp: 1655030343.8476756 iteration: 28765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20801 FastRCNN class loss: 0.14882 FastRCNN total loss: 0.35683 L1 loss: 0.0000e+00 L2 loss: 0.82958 Learning rate: 0.02 Mask loss: 0.20749 RPN box loss: 0.03899 RPN score loss: 0.0107 RPN total loss: 0.04969 Total loss: 1.44359 timestamp: 1655030347.0666502 iteration: 28770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10096 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.16273 L1 loss: 0.0000e+00 L2 loss: 0.82946 Learning rate: 0.02 Mask loss: 0.14091 RPN box loss: 0.04043 RPN score loss: 0.00649 RPN total loss: 0.04692 Total loss: 1.18002 timestamp: 1655030350.396181 iteration: 28775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18748 FastRCNN class loss: 0.13607 FastRCNN total loss: 0.32355 L1 loss: 0.0000e+00 L2 loss: 0.82931 Learning rate: 0.02 Mask loss: 0.2096 RPN box loss: 0.07507 RPN score loss: 0.01823 RPN total loss: 0.0933 Total loss: 1.45576 timestamp: 1655030353.673793 iteration: 28780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13015 FastRCNN class loss: 0.07672 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.8292 Learning rate: 0.02 Mask loss: 0.11695 RPN box loss: 0.01351 RPN score loss: 0.00533 RPN total loss: 0.01884 Total loss: 1.17186 timestamp: 1655030356.988376 iteration: 28785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15919 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.22508 L1 loss: 0.0000e+00 L2 loss: 0.82907 Learning rate: 0.02 Mask loss: 0.10149 RPN box loss: 0.04203 RPN score loss: 0.00615 RPN total loss: 0.04818 Total loss: 1.20382 timestamp: 1655030360.2197173 iteration: 28790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15564 FastRCNN class loss: 0.10793 FastRCNN total loss: 0.26357 L1 loss: 0.0000e+00 L2 loss: 0.82894 Learning rate: 0.02 Mask loss: 0.19892 RPN box loss: 0.03264 RPN score loss: 0.01246 RPN total loss: 0.04509 Total loss: 1.33652 timestamp: 1655030363.5505426 iteration: 28795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13326 FastRCNN class loss: 0.08205 FastRCNN total loss: 0.21532 L1 loss: 0.0000e+00 L2 loss: 0.82881 Learning rate: 0.02 Mask loss: 0.18021 RPN box loss: 0.11222 RPN score loss: 0.01057 RPN total loss: 0.12279 Total loss: 1.34712 timestamp: 1655030366.8399787 iteration: 28800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18146 FastRCNN class loss: 0.08524 FastRCNN total loss: 0.2667 L1 loss: 0.0000e+00 L2 loss: 0.8287 Learning rate: 0.02 Mask loss: 0.14336 RPN box loss: 0.02482 RPN score loss: 0.00544 RPN total loss: 0.03026 Total loss: 1.26902 timestamp: 1655030370.0789356 iteration: 28805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18271 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.26537 L1 loss: 0.0000e+00 L2 loss: 0.82858 Learning rate: 0.02 Mask loss: 0.16476 RPN box loss: 0.04245 RPN score loss: 0.00494 RPN total loss: 0.04739 Total loss: 1.30611 timestamp: 1655030373.3520317 iteration: 28810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.05082 FastRCNN total loss: 0.15622 L1 loss: 0.0000e+00 L2 loss: 0.82845 Learning rate: 0.02 Mask loss: 0.22234 RPN box loss: 0.01022 RPN score loss: 0.00433 RPN total loss: 0.01455 Total loss: 1.22156 timestamp: 1655030376.6617508 iteration: 28815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17932 FastRCNN class loss: 0.11198 FastRCNN total loss: 0.2913 L1 loss: 0.0000e+00 L2 loss: 0.82832 Learning rate: 0.02 Mask loss: 0.20531 RPN box loss: 0.02489 RPN score loss: 0.01967 RPN total loss: 0.04456 Total loss: 1.36949 timestamp: 1655030379.9052818 iteration: 28820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1665 FastRCNN class loss: 0.12284 FastRCNN total loss: 0.28934 L1 loss: 0.0000e+00 L2 loss: 0.82818 Learning rate: 0.02 Mask loss: 0.25306 RPN box loss: 0.02582 RPN score loss: 0.04467 RPN total loss: 0.0705 Total loss: 1.44108 timestamp: 1655030383.2622707 iteration: 28825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15827 FastRCNN class loss: 0.08702 FastRCNN total loss: 0.24529 L1 loss: 0.0000e+00 L2 loss: 0.82803 Learning rate: 0.02 Mask loss: 0.20659 RPN box loss: 0.00486 RPN score loss: 0.00104 RPN total loss: 0.0059 Total loss: 1.28582 timestamp: 1655030386.5184047 iteration: 28830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.16562 L1 loss: 0.0000e+00 L2 loss: 0.82793 Learning rate: 0.02 Mask loss: 0.16751 RPN box loss: 0.01594 RPN score loss: 0.00311 RPN total loss: 0.01905 Total loss: 1.18011 timestamp: 1655030389.8244605 iteration: 28835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12892 FastRCNN class loss: 0.08854 FastRCNN total loss: 0.21746 L1 loss: 0.0000e+00 L2 loss: 0.82782 Learning rate: 0.02 Mask loss: 0.20095 RPN box loss: 0.03115 RPN score loss: 0.00788 RPN total loss: 0.03902 Total loss: 1.28526 timestamp: 1655030393.1507568 iteration: 28840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16586 FastRCNN class loss: 0.085 FastRCNN total loss: 0.25086 L1 loss: 0.0000e+00 L2 loss: 0.82771 Learning rate: 0.02 Mask loss: 0.15955 RPN box loss: 0.03949 RPN score loss: 0.00464 RPN total loss: 0.04413 Total loss: 1.28225 timestamp: 1655030396.4055362 iteration: 28845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07968 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.15278 L1 loss: 0.0000e+00 L2 loss: 0.82757 Learning rate: 0.02 Mask loss: 0.17258 RPN box loss: 0.08279 RPN score loss: 0.00615 RPN total loss: 0.08894 Total loss: 1.24188 timestamp: 1655030399.758019 iteration: 28850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16233 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.23283 L1 loss: 0.0000e+00 L2 loss: 0.82744 Learning rate: 0.02 Mask loss: 0.10511 RPN box loss: 0.06479 RPN score loss: 0.00816 RPN total loss: 0.07296 Total loss: 1.23834 timestamp: 1655030403.0360935 iteration: 28855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24839 FastRCNN class loss: 0.09534 FastRCNN total loss: 0.34373 L1 loss: 0.0000e+00 L2 loss: 0.82734 Learning rate: 0.02 Mask loss: 0.16484 RPN box loss: 0.05773 RPN score loss: 0.00883 RPN total loss: 0.06657 Total loss: 1.40248 timestamp: 1655030406.3401232 iteration: 28860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12607 FastRCNN class loss: 0.06846 FastRCNN total loss: 0.19453 L1 loss: 0.0000e+00 L2 loss: 0.82721 Learning rate: 0.02 Mask loss: 0.16931 RPN box loss: 0.03336 RPN score loss: 0.00526 RPN total loss: 0.03862 Total loss: 1.22967 timestamp: 1655030409.5892277 iteration: 28865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14039 FastRCNN class loss: 0.04918 FastRCNN total loss: 0.18957 L1 loss: 0.0000e+00 L2 loss: 0.82706 Learning rate: 0.02 Mask loss: 0.14715 RPN box loss: 0.0411 RPN score loss: 0.00777 RPN total loss: 0.04886 Total loss: 1.21264 timestamp: 1655030412.806702 iteration: 28870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14224 FastRCNN class loss: 0.13795 FastRCNN total loss: 0.28019 L1 loss: 0.0000e+00 L2 loss: 0.82694 Learning rate: 0.02 Mask loss: 0.20635 RPN box loss: 0.06362 RPN score loss: 0.01187 RPN total loss: 0.07549 Total loss: 1.38898 timestamp: 1655030416.1117494 iteration: 28875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12859 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.19866 L1 loss: 0.0000e+00 L2 loss: 0.82681 Learning rate: 0.02 Mask loss: 0.11475 RPN box loss: 0.02545 RPN score loss: 0.00336 RPN total loss: 0.0288 Total loss: 1.16903 timestamp: 1655030419.3836234 iteration: 28880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12234 FastRCNN class loss: 0.14466 FastRCNN total loss: 0.26699 L1 loss: 0.0000e+00 L2 loss: 0.82665 Learning rate: 0.02 Mask loss: 0.18769 RPN box loss: 0.0389 RPN score loss: 0.01995 RPN total loss: 0.05885 Total loss: 1.34019 timestamp: 1655030422.6339397 iteration: 28885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16169 FastRCNN class loss: 0.06024 FastRCNN total loss: 0.22193 L1 loss: 0.0000e+00 L2 loss: 0.82655 Learning rate: 0.02 Mask loss: 0.11577 RPN box loss: 0.04619 RPN score loss: 0.00669 RPN total loss: 0.05288 Total loss: 1.21714 timestamp: 1655030425.9657497 iteration: 28890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14332 FastRCNN class loss: 0.0806 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 0.82646 Learning rate: 0.02 Mask loss: 0.17074 RPN box loss: 0.02136 RPN score loss: 0.0054 RPN total loss: 0.02676 Total loss: 1.24788 timestamp: 1655030429.198273 iteration: 28895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.82634 Learning rate: 0.02 Mask loss: 0.13751 RPN box loss: 0.08111 RPN score loss: 0.00837 RPN total loss: 0.08948 Total loss: 1.25233 timestamp: 1655030432.425403 iteration: 28900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08206 FastRCNN class loss: 0.08858 FastRCNN total loss: 0.17064 L1 loss: 0.0000e+00 L2 loss: 0.82619 Learning rate: 0.02 Mask loss: 0.12165 RPN box loss: 0.00825 RPN score loss: 0.00314 RPN total loss: 0.01139 Total loss: 1.12987 timestamp: 1655030435.7224562 iteration: 28905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15849 FastRCNN class loss: 0.12038 FastRCNN total loss: 0.27887 L1 loss: 0.0000e+00 L2 loss: 0.82607 Learning rate: 0.02 Mask loss: 0.16385 RPN box loss: 0.03459 RPN score loss: 0.00683 RPN total loss: 0.04142 Total loss: 1.31021 timestamp: 1655030438.950846 iteration: 28910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15685 FastRCNN class loss: 0.13789 FastRCNN total loss: 0.29474 L1 loss: 0.0000e+00 L2 loss: 0.82594 Learning rate: 0.02 Mask loss: 0.17847 RPN box loss: 0.07177 RPN score loss: 0.0217 RPN total loss: 0.09346 Total loss: 1.39262 timestamp: 1655030442.2265441 iteration: 28915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20756 FastRCNN class loss: 0.06924 FastRCNN total loss: 0.2768 L1 loss: 0.0000e+00 L2 loss: 0.82579 Learning rate: 0.02 Mask loss: 0.15737 RPN box loss: 0.02044 RPN score loss: 0.00748 RPN total loss: 0.02792 Total loss: 1.28789 timestamp: 1655030445.4610636 iteration: 28920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17476 FastRCNN class loss: 0.13269 FastRCNN total loss: 0.30745 L1 loss: 0.0000e+00 L2 loss: 0.82567 Learning rate: 0.02 Mask loss: 0.17098 RPN box loss: 0.02562 RPN score loss: 0.0052 RPN total loss: 0.03083 Total loss: 1.33492 timestamp: 1655030448.7088408 iteration: 28925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10452 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.16404 L1 loss: 0.0000e+00 L2 loss: 0.82554 Learning rate: 0.02 Mask loss: 0.12708 RPN box loss: 0.00888 RPN score loss: 0.00249 RPN total loss: 0.01136 Total loss: 1.12803 timestamp: 1655030451.985522 iteration: 28930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08955 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.16358 L1 loss: 0.0000e+00 L2 loss: 0.82541 Learning rate: 0.02 Mask loss: 0.13632 RPN box loss: 0.03076 RPN score loss: 0.00231 RPN total loss: 0.03307 Total loss: 1.15839 timestamp: 1655030455.2096622 iteration: 28935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17349 FastRCNN class loss: 0.1183 FastRCNN total loss: 0.29179 L1 loss: 0.0000e+00 L2 loss: 0.8253 Learning rate: 0.02 Mask loss: 0.29297 RPN box loss: 0.04888 RPN score loss: 0.02086 RPN total loss: 0.06974 Total loss: 1.4798 timestamp: 1655030458.5101645 iteration: 28940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1233 FastRCNN class loss: 0.13028 FastRCNN total loss: 0.25359 L1 loss: 0.0000e+00 L2 loss: 0.82517 Learning rate: 0.02 Mask loss: 0.19416 RPN box loss: 0.03072 RPN score loss: 0.00432 RPN total loss: 0.03504 Total loss: 1.30796 timestamp: 1655030461.8152764 iteration: 28945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17066 FastRCNN class loss: 0.09214 FastRCNN total loss: 0.2628 L1 loss: 0.0000e+00 L2 loss: 0.82505 Learning rate: 0.02 Mask loss: 0.32234 RPN box loss: 0.01984 RPN score loss: 0.00716 RPN total loss: 0.027 Total loss: 1.43719 timestamp: 1655030465.0472713 iteration: 28950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18024 FastRCNN class loss: 0.10899 FastRCNN total loss: 0.28923 L1 loss: 0.0000e+00 L2 loss: 0.82497 Learning rate: 0.02 Mask loss: 0.13539 RPN box loss: 0.02094 RPN score loss: 0.01121 RPN total loss: 0.03215 Total loss: 1.28174 timestamp: 1655030468.298528 iteration: 28955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16283 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.23005 L1 loss: 0.0000e+00 L2 loss: 0.82483 Learning rate: 0.02 Mask loss: 0.15405 RPN box loss: 0.02128 RPN score loss: 0.01047 RPN total loss: 0.03175 Total loss: 1.24068 timestamp: 1655030471.5435498 iteration: 28960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19003 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.27033 L1 loss: 0.0000e+00 L2 loss: 0.82472 Learning rate: 0.02 Mask loss: 0.19864 RPN box loss: 0.03955 RPN score loss: 0.00335 RPN total loss: 0.0429 Total loss: 1.33659 timestamp: 1655030474.8276567 iteration: 28965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14434 FastRCNN class loss: 0.06662 FastRCNN total loss: 0.21096 L1 loss: 0.0000e+00 L2 loss: 0.8246 Learning rate: 0.02 Mask loss: 0.18638 RPN box loss: 0.04412 RPN score loss: 0.00387 RPN total loss: 0.04799 Total loss: 1.26993 timestamp: 1655030478.13474 iteration: 28970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18451 FastRCNN class loss: 0.07276 FastRCNN total loss: 0.25727 L1 loss: 0.0000e+00 L2 loss: 0.82447 Learning rate: 0.02 Mask loss: 0.15782 RPN box loss: 0.03486 RPN score loss: 0.00354 RPN total loss: 0.03841 Total loss: 1.27797 timestamp: 1655030481.3542225 iteration: 28975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18289 FastRCNN class loss: 0.15271 FastRCNN total loss: 0.33561 L1 loss: 0.0000e+00 L2 loss: 0.82435 Learning rate: 0.02 Mask loss: 0.19948 RPN box loss: 0.02387 RPN score loss: 0.00729 RPN total loss: 0.03117 Total loss: 1.3906 timestamp: 1655030484.6312146 iteration: 28980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12473 FastRCNN class loss: 0.05255 FastRCNN total loss: 0.17727 L1 loss: 0.0000e+00 L2 loss: 0.82422 Learning rate: 0.02 Mask loss: 0.11684 RPN box loss: 0.00955 RPN score loss: 0.0079 RPN total loss: 0.01745 Total loss: 1.13579 timestamp: 1655030487.9242706 iteration: 28985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1484 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.2226 L1 loss: 0.0000e+00 L2 loss: 0.82411 Learning rate: 0.02 Mask loss: 0.12055 RPN box loss: 0.02814 RPN score loss: 0.00292 RPN total loss: 0.03106 Total loss: 1.19832 timestamp: 1655030491.1629474 iteration: 28990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13959 FastRCNN class loss: 0.09616 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 0.82399 Learning rate: 0.02 Mask loss: 0.15123 RPN box loss: 0.04173 RPN score loss: 0.01314 RPN total loss: 0.05488 Total loss: 1.26585 timestamp: 1655030494.5004158 iteration: 28995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09701 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.17774 L1 loss: 0.0000e+00 L2 loss: 0.82385 Learning rate: 0.02 Mask loss: 0.12377 RPN box loss: 0.05889 RPN score loss: 0.0117 RPN total loss: 0.07059 Total loss: 1.19595 timestamp: 1655030497.8307583 iteration: 29000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13363 FastRCNN class loss: 0.03418 FastRCNN total loss: 0.16781 L1 loss: 0.0000e+00 L2 loss: 0.82372 Learning rate: 0.02 Mask loss: 0.11728 RPN box loss: 0.05334 RPN score loss: 0.00236 RPN total loss: 0.0557 Total loss: 1.16452 timestamp: 1655030501.1299803 iteration: 29005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22125 FastRCNN class loss: 0.09931 FastRCNN total loss: 0.32056 L1 loss: 0.0000e+00 L2 loss: 0.8236 Learning rate: 0.02 Mask loss: 0.1897 RPN box loss: 0.02578 RPN score loss: 0.00387 RPN total loss: 0.02966 Total loss: 1.36352 timestamp: 1655030504.412821 iteration: 29010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13802 FastRCNN class loss: 0.09459 FastRCNN total loss: 0.23262 L1 loss: 0.0000e+00 L2 loss: 0.82349 Learning rate: 0.02 Mask loss: 0.12886 RPN box loss: 0.0222 RPN score loss: 0.00449 RPN total loss: 0.02669 Total loss: 1.21166 timestamp: 1655030507.663107 iteration: 29015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.09759 FastRCNN total loss: 0.18606 L1 loss: 0.0000e+00 L2 loss: 0.82338 Learning rate: 0.02 Mask loss: 0.3207 RPN box loss: 0.02465 RPN score loss: 0.00426 RPN total loss: 0.02891 Total loss: 1.35905 timestamp: 1655030510.9439042 iteration: 29020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10469 FastRCNN class loss: 0.06022 FastRCNN total loss: 0.16491 L1 loss: 0.0000e+00 L2 loss: 0.82325 Learning rate: 0.02 Mask loss: 0.18465 RPN box loss: 0.05763 RPN score loss: 0.00327 RPN total loss: 0.0609 Total loss: 1.23372 timestamp: 1655030514.3526976 iteration: 29025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14023 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.24138 L1 loss: 0.0000e+00 L2 loss: 0.8231 Learning rate: 0.02 Mask loss: 0.18807 RPN box loss: 0.01906 RPN score loss: 0.00871 RPN total loss: 0.02777 Total loss: 1.28031 timestamp: 1655030517.6159258 iteration: 29030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.82299 Learning rate: 0.02 Mask loss: 0.12571 RPN box loss: 0.02042 RPN score loss: 0.00471 RPN total loss: 0.02513 Total loss: 1.0999 timestamp: 1655030520.8055227 iteration: 29035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22536 FastRCNN class loss: 0.15785 FastRCNN total loss: 0.38321 L1 loss: 0.0000e+00 L2 loss: 0.82289 Learning rate: 0.02 Mask loss: 0.27621 RPN box loss: 0.05372 RPN score loss: 0.009 RPN total loss: 0.06272 Total loss: 1.54502 timestamp: 1655030524.0624938 iteration: 29040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20825 FastRCNN class loss: 0.1714 FastRCNN total loss: 0.37965 L1 loss: 0.0000e+00 L2 loss: 0.82276 Learning rate: 0.02 Mask loss: 0.17819 RPN box loss: 0.02978 RPN score loss: 0.00522 RPN total loss: 0.035 Total loss: 1.4156 timestamp: 1655030527.3217044 iteration: 29045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15159 FastRCNN class loss: 0.08365 FastRCNN total loss: 0.23525 L1 loss: 0.0000e+00 L2 loss: 0.82265 Learning rate: 0.02 Mask loss: 0.16854 RPN box loss: 0.03523 RPN score loss: 0.00911 RPN total loss: 0.04434 Total loss: 1.27078 timestamp: 1655030530.6256738 iteration: 29050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.10772 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 0.8225 Learning rate: 0.02 Mask loss: 0.24611 RPN box loss: 0.04999 RPN score loss: 0.00799 RPN total loss: 0.05799 Total loss: 1.36661 timestamp: 1655030533.8838394 iteration: 29055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14472 FastRCNN class loss: 0.12589 FastRCNN total loss: 0.2706 L1 loss: 0.0000e+00 L2 loss: 0.82236 Learning rate: 0.02 Mask loss: 0.18658 RPN box loss: 0.01159 RPN score loss: 0.00632 RPN total loss: 0.01791 Total loss: 1.29746 timestamp: 1655030537.107704 iteration: 29060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19718 FastRCNN class loss: 0.14211 FastRCNN total loss: 0.33929 L1 loss: 0.0000e+00 L2 loss: 0.82223 Learning rate: 0.02 Mask loss: 0.14183 RPN box loss: 0.02796 RPN score loss: 0.00873 RPN total loss: 0.03668 Total loss: 1.34004 timestamp: 1655030540.328563 iteration: 29065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13843 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.2133 L1 loss: 0.0000e+00 L2 loss: 0.82212 Learning rate: 0.02 Mask loss: 0.11971 RPN box loss: 0.03697 RPN score loss: 0.00517 RPN total loss: 0.04213 Total loss: 1.19726 timestamp: 1655030543.6391306 iteration: 29070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12186 FastRCNN class loss: 0.08105 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.822 Learning rate: 0.02 Mask loss: 0.15095 RPN box loss: 0.02758 RPN score loss: 0.00251 RPN total loss: 0.03009 Total loss: 1.20594 timestamp: 1655030546.9405398 iteration: 29075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1463 FastRCNN class loss: 0.08916 FastRCNN total loss: 0.23546 L1 loss: 0.0000e+00 L2 loss: 0.82185 Learning rate: 0.02 Mask loss: 0.15805 RPN box loss: 0.0222 RPN score loss: 0.00638 RPN total loss: 0.02858 Total loss: 1.24394 timestamp: 1655030550.161339 iteration: 29080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10304 FastRCNN class loss: 0.08775 FastRCNN total loss: 0.19079 L1 loss: 0.0000e+00 L2 loss: 0.82173 Learning rate: 0.02 Mask loss: 0.13093 RPN box loss: 0.01204 RPN score loss: 0.01901 RPN total loss: 0.03104 Total loss: 1.1745 timestamp: 1655030553.387529 iteration: 29085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15582 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.21473 L1 loss: 0.0000e+00 L2 loss: 0.82162 Learning rate: 0.02 Mask loss: 0.17099 RPN box loss: 0.1286 RPN score loss: 0.00768 RPN total loss: 0.13628 Total loss: 1.34363 timestamp: 1655030556.629819 iteration: 29090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11923 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.16637 L1 loss: 0.0000e+00 L2 loss: 0.82149 Learning rate: 0.02 Mask loss: 0.1844 RPN box loss: 0.04753 RPN score loss: 0.00393 RPN total loss: 0.05146 Total loss: 1.22373 timestamp: 1655030559.8493404 iteration: 29095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14428 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.23493 L1 loss: 0.0000e+00 L2 loss: 0.82137 Learning rate: 0.02 Mask loss: 0.10726 RPN box loss: 0.01782 RPN score loss: 0.00432 RPN total loss: 0.02214 Total loss: 1.18571 timestamp: 1655030563.1132467 iteration: 29100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0879 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.13705 L1 loss: 0.0000e+00 L2 loss: 0.82126 Learning rate: 0.02 Mask loss: 0.1018 RPN box loss: 0.00755 RPN score loss: 0.00332 RPN total loss: 0.01087 Total loss: 1.07097 timestamp: 1655030566.4131486 iteration: 29105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18413 FastRCNN class loss: 0.08552 FastRCNN total loss: 0.26965 L1 loss: 0.0000e+00 L2 loss: 0.82112 Learning rate: 0.02 Mask loss: 0.17254 RPN box loss: 0.07845 RPN score loss: 0.01008 RPN total loss: 0.08853 Total loss: 1.35185 timestamp: 1655030569.63711 iteration: 29110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.12401 FastRCNN total loss: 0.2389 L1 loss: 0.0000e+00 L2 loss: 0.82098 Learning rate: 0.02 Mask loss: 0.15892 RPN box loss: 0.07573 RPN score loss: 0.01386 RPN total loss: 0.08959 Total loss: 1.3084 timestamp: 1655030572.9444404 iteration: 29115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17919 FastRCNN class loss: 0.09318 FastRCNN total loss: 0.27237 L1 loss: 0.0000e+00 L2 loss: 0.82086 Learning rate: 0.02 Mask loss: 0.11794 RPN box loss: 0.02905 RPN score loss: 0.00641 RPN total loss: 0.03547 Total loss: 1.24664 timestamp: 1655030576.2371073 iteration: 29120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1119 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.18196 L1 loss: 0.0000e+00 L2 loss: 0.82074 Learning rate: 0.02 Mask loss: 0.15223 RPN box loss: 0.01468 RPN score loss: 0.00428 RPN total loss: 0.01896 Total loss: 1.17389 timestamp: 1655030579.4605672 iteration: 29125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16459 FastRCNN class loss: 0.07924 FastRCNN total loss: 0.24383 L1 loss: 0.0000e+00 L2 loss: 0.82061 Learning rate: 0.02 Mask loss: 0.17793 RPN box loss: 0.01587 RPN score loss: 0.01023 RPN total loss: 0.0261 Total loss: 1.26847 timestamp: 1655030582.7551377 iteration: 29130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18516 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.28206 L1 loss: 0.0000e+00 L2 loss: 0.82049 Learning rate: 0.02 Mask loss: 0.22701 RPN box loss: 0.02915 RPN score loss: 0.01052 RPN total loss: 0.03967 Total loss: 1.36923 timestamp: 1655030586.015711 iteration: 29135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17638 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 0.82037 Learning rate: 0.02 Mask loss: 0.19415 RPN box loss: 0.04053 RPN score loss: 0.00677 RPN total loss: 0.0473 Total loss: 1.33294 timestamp: 1655030589.2890887 iteration: 29140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1841 FastRCNN class loss: 0.10577 FastRCNN total loss: 0.28987 L1 loss: 0.0000e+00 L2 loss: 0.82024 Learning rate: 0.02 Mask loss: 0.12767 RPN box loss: 0.02638 RPN score loss: 0.00348 RPN total loss: 0.02986 Total loss: 1.26765 timestamp: 1655030592.5915277 iteration: 29145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17474 FastRCNN class loss: 0.08006 FastRCNN total loss: 0.2548 L1 loss: 0.0000e+00 L2 loss: 0.82011 Learning rate: 0.02 Mask loss: 0.21105 RPN box loss: 0.07702 RPN score loss: 0.00512 RPN total loss: 0.08214 Total loss: 1.3681 timestamp: 1655030595.8374574 iteration: 29150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14856 FastRCNN class loss: 0.07655 FastRCNN total loss: 0.2251 L1 loss: 0.0000e+00 L2 loss: 0.81998 Learning rate: 0.02 Mask loss: 0.2395 RPN box loss: 0.0334 RPN score loss: 0.01951 RPN total loss: 0.05291 Total loss: 1.3375 timestamp: 1655030599.0949373 iteration: 29155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.168 FastRCNN class loss: 0.09691 FastRCNN total loss: 0.26491 L1 loss: 0.0000e+00 L2 loss: 0.81985 Learning rate: 0.02 Mask loss: 0.16893 RPN box loss: 0.00818 RPN score loss: 0.0027 RPN total loss: 0.01088 Total loss: 1.26458 timestamp: 1655030602.3538074 iteration: 29160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09433 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.16789 L1 loss: 0.0000e+00 L2 loss: 0.81972 Learning rate: 0.02 Mask loss: 0.16738 RPN box loss: 0.01496 RPN score loss: 0.00397 RPN total loss: 0.01893 Total loss: 1.17391 timestamp: 1655030605.593072 iteration: 29165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07694 FastRCNN class loss: 0.04551 FastRCNN total loss: 0.12246 L1 loss: 0.0000e+00 L2 loss: 0.81961 Learning rate: 0.02 Mask loss: 0.13112 RPN box loss: 0.08906 RPN score loss: 0.02611 RPN total loss: 0.11517 Total loss: 1.18835 timestamp: 1655030608.8353744 iteration: 29170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11237 FastRCNN class loss: 0.05299 FastRCNN total loss: 0.16537 L1 loss: 0.0000e+00 L2 loss: 0.81948 Learning rate: 0.02 Mask loss: 0.09309 RPN box loss: 0.01079 RPN score loss: 0.00246 RPN total loss: 0.01325 Total loss: 1.09119 timestamp: 1655030612.1346457 iteration: 29175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.06203 FastRCNN total loss: 0.16276 L1 loss: 0.0000e+00 L2 loss: 0.81935 Learning rate: 0.02 Mask loss: 0.08532 RPN box loss: 0.01963 RPN score loss: 0.00971 RPN total loss: 0.02935 Total loss: 1.09678 timestamp: 1655030615.4229386 iteration: 29180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09247 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.17982 L1 loss: 0.0000e+00 L2 loss: 0.81923 Learning rate: 0.02 Mask loss: 0.11016 RPN box loss: 0.03703 RPN score loss: 0.00299 RPN total loss: 0.04002 Total loss: 1.14923 timestamp: 1655030618.6707993 iteration: 29185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12081 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.19114 L1 loss: 0.0000e+00 L2 loss: 0.81908 Learning rate: 0.02 Mask loss: 0.17022 RPN box loss: 0.07297 RPN score loss: 0.01284 RPN total loss: 0.08582 Total loss: 1.26626 timestamp: 1655030621.9663231 iteration: 29190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1116 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.1961 L1 loss: 0.0000e+00 L2 loss: 0.81895 Learning rate: 0.02 Mask loss: 0.18037 RPN box loss: 0.0328 RPN score loss: 0.00337 RPN total loss: 0.03616 Total loss: 1.23159 timestamp: 1655030625.2240455 iteration: 29195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11938 FastRCNN class loss: 0.06534 FastRCNN total loss: 0.18472 L1 loss: 0.0000e+00 L2 loss: 0.81884 Learning rate: 0.02 Mask loss: 0.17551 RPN box loss: 0.02035 RPN score loss: 0.00702 RPN total loss: 0.02738 Total loss: 1.20645 timestamp: 1655030628.4930387 iteration: 29200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21543 FastRCNN class loss: 0.19177 FastRCNN total loss: 0.40721 L1 loss: 0.0000e+00 L2 loss: 0.81871 Learning rate: 0.02 Mask loss: 0.12943 RPN box loss: 0.04735 RPN score loss: 0.00564 RPN total loss: 0.05299 Total loss: 1.40834 timestamp: 1655030631.7453556 iteration: 29205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13647 FastRCNN class loss: 0.07149 FastRCNN total loss: 0.20795 L1 loss: 0.0000e+00 L2 loss: 0.81857 Learning rate: 0.02 Mask loss: 0.14278 RPN box loss: 0.04978 RPN score loss: 0.0038 RPN total loss: 0.05358 Total loss: 1.22289 timestamp: 1655030634.982104 iteration: 29210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14696 FastRCNN class loss: 0.04648 FastRCNN total loss: 0.19344 L1 loss: 0.0000e+00 L2 loss: 0.81842 Learning rate: 0.02 Mask loss: 0.08114 RPN box loss: 0.02849 RPN score loss: 0.00517 RPN total loss: 0.03366 Total loss: 1.12666 timestamp: 1655030638.2654655 iteration: 29215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13765 FastRCNN class loss: 0.08408 FastRCNN total loss: 0.22173 L1 loss: 0.0000e+00 L2 loss: 0.81829 Learning rate: 0.02 Mask loss: 0.13094 RPN box loss: 0.01843 RPN score loss: 0.00267 RPN total loss: 0.0211 Total loss: 1.19206 timestamp: 1655030641.5066364 iteration: 29220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17541 FastRCNN class loss: 0.07104 FastRCNN total loss: 0.24644 L1 loss: 0.0000e+00 L2 loss: 0.81821 Learning rate: 0.02 Mask loss: 0.158 RPN box loss: 0.01689 RPN score loss: 0.00237 RPN total loss: 0.01926 Total loss: 1.24191 timestamp: 1655030644.7633502 iteration: 29225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.06937 FastRCNN total loss: 0.17903 L1 loss: 0.0000e+00 L2 loss: 0.8181 Learning rate: 0.02 Mask loss: 0.20116 RPN box loss: 0.01367 RPN score loss: 0.00196 RPN total loss: 0.01563 Total loss: 1.21392 timestamp: 1655030648.076295 iteration: 29230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15075 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.23274 L1 loss: 0.0000e+00 L2 loss: 0.81797 Learning rate: 0.02 Mask loss: 0.11311 RPN box loss: 0.06116 RPN score loss: 0.00984 RPN total loss: 0.071 Total loss: 1.23481 timestamp: 1655030651.2785714 iteration: 29235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.16387 L1 loss: 0.0000e+00 L2 loss: 0.81783 Learning rate: 0.02 Mask loss: 0.14362 RPN box loss: 0.00871 RPN score loss: 0.00208 RPN total loss: 0.01079 Total loss: 1.1361 timestamp: 1655030654.5470855 iteration: 29240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14775 FastRCNN class loss: 0.15432 FastRCNN total loss: 0.30207 L1 loss: 0.0000e+00 L2 loss: 0.8177 Learning rate: 0.02 Mask loss: 0.25672 RPN box loss: 0.04319 RPN score loss: 0.03738 RPN total loss: 0.08057 Total loss: 1.45706 timestamp: 1655030657.8573682 iteration: 29245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15227 FastRCNN class loss: 0.09912 FastRCNN total loss: 0.25139 L1 loss: 0.0000e+00 L2 loss: 0.81757 Learning rate: 0.02 Mask loss: 0.19112 RPN box loss: 0.06057 RPN score loss: 0.01076 RPN total loss: 0.07133 Total loss: 1.33142 timestamp: 1655030661.1307466 iteration: 29250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19592 FastRCNN class loss: 0.11872 FastRCNN total loss: 0.31464 L1 loss: 0.0000e+00 L2 loss: 0.81743 Learning rate: 0.02 Mask loss: 0.1609 RPN box loss: 0.04097 RPN score loss: 0.01524 RPN total loss: 0.05621 Total loss: 1.34918 timestamp: 1655030664.4794765 iteration: 29255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12096 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.19308 L1 loss: 0.0000e+00 L2 loss: 0.81731 Learning rate: 0.02 Mask loss: 0.17576 RPN box loss: 0.05378 RPN score loss: 0.00729 RPN total loss: 0.06106 Total loss: 1.24721 timestamp: 1655030667.690719 iteration: 29260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14586 FastRCNN class loss: 0.12927 FastRCNN total loss: 0.27513 L1 loss: 0.0000e+00 L2 loss: 0.81718 Learning rate: 0.02 Mask loss: 0.20382 RPN box loss: 0.03517 RPN score loss: 0.01193 RPN total loss: 0.0471 Total loss: 1.34324 timestamp: 1655030670.9442494 iteration: 29265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10524 FastRCNN class loss: 0.07729 FastRCNN total loss: 0.18253 L1 loss: 0.0000e+00 L2 loss: 0.81708 Learning rate: 0.02 Mask loss: 0.17003 RPN box loss: 0.04126 RPN score loss: 0.01257 RPN total loss: 0.05383 Total loss: 1.22347 timestamp: 1655030674.2057416 iteration: 29270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12331 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.21115 L1 loss: 0.0000e+00 L2 loss: 0.81695 Learning rate: 0.02 Mask loss: 0.17412 RPN box loss: 0.02476 RPN score loss: 0.00437 RPN total loss: 0.02913 Total loss: 1.23134 timestamp: 1655030677.4953578 iteration: 29275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13976 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.21783 L1 loss: 0.0000e+00 L2 loss: 0.81683 Learning rate: 0.02 Mask loss: 0.11479 RPN box loss: 0.01241 RPN score loss: 0.0043 RPN total loss: 0.01671 Total loss: 1.16617 timestamp: 1655030680.7977977 iteration: 29280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13689 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.21139 L1 loss: 0.0000e+00 L2 loss: 0.81671 Learning rate: 0.02 Mask loss: 0.135 RPN box loss: 0.02051 RPN score loss: 0.00319 RPN total loss: 0.0237 Total loss: 1.18681 timestamp: 1655030684.1023574 iteration: 29285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21231 FastRCNN class loss: 0.09269 FastRCNN total loss: 0.305 L1 loss: 0.0000e+00 L2 loss: 0.8166 Learning rate: 0.02 Mask loss: 0.14428 RPN box loss: 0.04614 RPN score loss: 0.00489 RPN total loss: 0.05102 Total loss: 1.31689 timestamp: 1655030687.3554494 iteration: 29290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17014 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.25735 L1 loss: 0.0000e+00 L2 loss: 0.81648 Learning rate: 0.02 Mask loss: 0.11632 RPN box loss: 0.00618 RPN score loss: 0.00526 RPN total loss: 0.01144 Total loss: 1.20159 timestamp: 1655030690.6110673 iteration: 29295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11019 FastRCNN class loss: 0.05571 FastRCNN total loss: 0.16591 L1 loss: 0.0000e+00 L2 loss: 0.81634 Learning rate: 0.02 Mask loss: 0.1192 RPN box loss: 0.04063 RPN score loss: 0.00551 RPN total loss: 0.04613 Total loss: 1.14758 timestamp: 1655030693.9028797 iteration: 29300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08274 FastRCNN class loss: 0.10958 FastRCNN total loss: 0.19232 L1 loss: 0.0000e+00 L2 loss: 0.81619 Learning rate: 0.02 Mask loss: 0.17816 RPN box loss: 0.05035 RPN score loss: 0.00805 RPN total loss: 0.0584 Total loss: 1.24507 timestamp: 1655030697.2463725 iteration: 29305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12735 FastRCNN class loss: 0.10668 FastRCNN total loss: 0.23403 L1 loss: 0.0000e+00 L2 loss: 0.81607 Learning rate: 0.02 Mask loss: 0.16661 RPN box loss: 0.018 RPN score loss: 0.00357 RPN total loss: 0.02157 Total loss: 1.23829 timestamp: 1655030700.4274983 iteration: 29310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0961 FastRCNN class loss: 0.05205 FastRCNN total loss: 0.14815 L1 loss: 0.0000e+00 L2 loss: 0.81595 Learning rate: 0.02 Mask loss: 0.12025 RPN box loss: 0.06293 RPN score loss: 0.00654 RPN total loss: 0.06947 Total loss: 1.15382 timestamp: 1655030703.667615 iteration: 29315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17209 FastRCNN class loss: 0.12585 FastRCNN total loss: 0.29794 L1 loss: 0.0000e+00 L2 loss: 0.81583 Learning rate: 0.02 Mask loss: 0.18849 RPN box loss: 0.06576 RPN score loss: 0.01314 RPN total loss: 0.0789 Total loss: 1.38116 timestamp: 1655030706.9374893 iteration: 29320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1255 FastRCNN class loss: 0.0679 FastRCNN total loss: 0.19339 L1 loss: 0.0000e+00 L2 loss: 0.81571 Learning rate: 0.02 Mask loss: 0.17108 RPN box loss: 0.01474 RPN score loss: 0.00396 RPN total loss: 0.0187 Total loss: 1.19888 timestamp: 1655030710.1868198 iteration: 29325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12176 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.19982 L1 loss: 0.0000e+00 L2 loss: 0.81559 Learning rate: 0.02 Mask loss: 0.22073 RPN box loss: 0.0277 RPN score loss: 0.00706 RPN total loss: 0.03476 Total loss: 1.2709 timestamp: 1655030713.4738495 iteration: 29330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.07457 FastRCNN total loss: 0.20217 L1 loss: 0.0000e+00 L2 loss: 0.81545 Learning rate: 0.02 Mask loss: 0.1634 RPN box loss: 0.03495 RPN score loss: 0.00691 RPN total loss: 0.04186 Total loss: 1.22288 timestamp: 1655030716.761573 iteration: 29335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14413 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.23983 L1 loss: 0.0000e+00 L2 loss: 0.81535 Learning rate: 0.02 Mask loss: 0.10438 RPN box loss: 0.02242 RPN score loss: 0.00282 RPN total loss: 0.02524 Total loss: 1.1848 timestamp: 1655030720.031152 iteration: 29340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09791 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.17221 L1 loss: 0.0000e+00 L2 loss: 0.81521 Learning rate: 0.02 Mask loss: 0.16283 RPN box loss: 0.05353 RPN score loss: 0.01232 RPN total loss: 0.06585 Total loss: 1.2161 timestamp: 1655030723.3152199 iteration: 29345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20611 FastRCNN class loss: 0.11259 FastRCNN total loss: 0.3187 L1 loss: 0.0000e+00 L2 loss: 0.81509 Learning rate: 0.02 Mask loss: 0.28495 RPN box loss: 0.02733 RPN score loss: 0.00782 RPN total loss: 0.03515 Total loss: 1.45389 timestamp: 1655030726.5828722 iteration: 29350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19261 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.26462 L1 loss: 0.0000e+00 L2 loss: 0.81497 Learning rate: 0.02 Mask loss: 0.16539 RPN box loss: 0.02437 RPN score loss: 0.00723 RPN total loss: 0.0316 Total loss: 1.27658 timestamp: 1655030729.8351607 iteration: 29355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16633 FastRCNN class loss: 0.14072 FastRCNN total loss: 0.30705 L1 loss: 0.0000e+00 L2 loss: 0.81484 Learning rate: 0.02 Mask loss: 0.22813 RPN box loss: 0.03746 RPN score loss: 0.01253 RPN total loss: 0.04999 Total loss: 1.40001 timestamp: 1655030733.1821392 iteration: 29360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13982 FastRCNN class loss: 0.05468 FastRCNN total loss: 0.1945 L1 loss: 0.0000e+00 L2 loss: 0.81471 Learning rate: 0.02 Mask loss: 0.08859 RPN box loss: 0.01881 RPN score loss: 0.00939 RPN total loss: 0.0282 Total loss: 1.126 timestamp: 1655030736.453605 iteration: 29365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15771 FastRCNN class loss: 0.13422 FastRCNN total loss: 0.29193 L1 loss: 0.0000e+00 L2 loss: 0.81462 Learning rate: 0.02 Mask loss: 0.18146 RPN box loss: 0.01815 RPN score loss: 0.00498 RPN total loss: 0.02313 Total loss: 1.31114 timestamp: 1655030739.7068362 iteration: 29370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13092 FastRCNN class loss: 0.09853 FastRCNN total loss: 0.22945 L1 loss: 0.0000e+00 L2 loss: 0.81451 Learning rate: 0.02 Mask loss: 0.2228 RPN box loss: 0.06054 RPN score loss: 0.01367 RPN total loss: 0.07421 Total loss: 1.34096 timestamp: 1655030742.9553862 iteration: 29375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16664 FastRCNN class loss: 0.12288 FastRCNN total loss: 0.28952 L1 loss: 0.0000e+00 L2 loss: 0.81438 Learning rate: 0.02 Mask loss: 0.19145 RPN box loss: 0.04682 RPN score loss: 0.02459 RPN total loss: 0.07141 Total loss: 1.36676 timestamp: 1655030746.2333164 iteration: 29380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1941 FastRCNN class loss: 0.10148 FastRCNN total loss: 0.29558 L1 loss: 0.0000e+00 L2 loss: 0.81425 Learning rate: 0.02 Mask loss: 0.18738 RPN box loss: 0.02514 RPN score loss: 0.02134 RPN total loss: 0.04648 Total loss: 1.34369 timestamp: 1655030749.5732388 iteration: 29385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13906 FastRCNN class loss: 0.13157 FastRCNN total loss: 0.27062 L1 loss: 0.0000e+00 L2 loss: 0.81413 Learning rate: 0.02 Mask loss: 0.19703 RPN box loss: 0.04321 RPN score loss: 0.00696 RPN total loss: 0.05017 Total loss: 1.33196 timestamp: 1655030752.8586714 iteration: 29390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12371 FastRCNN class loss: 0.05916 FastRCNN total loss: 0.18287 L1 loss: 0.0000e+00 L2 loss: 0.81401 Learning rate: 0.02 Mask loss: 0.15158 RPN box loss: 0.02846 RPN score loss: 0.00883 RPN total loss: 0.03729 Total loss: 1.18574 timestamp: 1655030756.0728827 iteration: 29395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1502 FastRCNN class loss: 0.10418 FastRCNN total loss: 0.25438 L1 loss: 0.0000e+00 L2 loss: 0.81389 Learning rate: 0.02 Mask loss: 0.14274 RPN box loss: 0.04392 RPN score loss: 0.03747 RPN total loss: 0.08139 Total loss: 1.29241 timestamp: 1655030759.2754722 iteration: 29400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14667 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.22452 L1 loss: 0.0000e+00 L2 loss: 0.81374 Learning rate: 0.02 Mask loss: 0.26325 RPN box loss: 0.03138 RPN score loss: 0.00485 RPN total loss: 0.03623 Total loss: 1.33775 timestamp: 1655030762.524654 iteration: 29405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.17375 L1 loss: 0.0000e+00 L2 loss: 0.81362 Learning rate: 0.02 Mask loss: 0.17934 RPN box loss: 0.04443 RPN score loss: 0.00621 RPN total loss: 0.05064 Total loss: 1.21735 timestamp: 1655030765.7012327 iteration: 29410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12161 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.2066 L1 loss: 0.0000e+00 L2 loss: 0.81351 Learning rate: 0.02 Mask loss: 0.12416 RPN box loss: 0.02285 RPN score loss: 0.00432 RPN total loss: 0.02718 Total loss: 1.17144 timestamp: 1655030768.9602637 iteration: 29415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.05654 FastRCNN total loss: 0.17944 L1 loss: 0.0000e+00 L2 loss: 0.8134 Learning rate: 0.02 Mask loss: 0.13052 RPN box loss: 0.01183 RPN score loss: 0.0028 RPN total loss: 0.01463 Total loss: 1.13799 timestamp: 1655030772.213557 iteration: 29420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15437 FastRCNN class loss: 0.09662 FastRCNN total loss: 0.25099 L1 loss: 0.0000e+00 L2 loss: 0.81327 Learning rate: 0.02 Mask loss: 0.20709 RPN box loss: 0.04744 RPN score loss: 0.01047 RPN total loss: 0.05791 Total loss: 1.32926 timestamp: 1655030775.5761127 iteration: 29425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10911 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.18124 L1 loss: 0.0000e+00 L2 loss: 0.81312 Learning rate: 0.02 Mask loss: 0.17924 RPN box loss: 0.09857 RPN score loss: 0.01588 RPN total loss: 0.11445 Total loss: 1.28804 timestamp: 1655030778.849248 iteration: 29430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17034 FastRCNN class loss: 0.08472 FastRCNN total loss: 0.25506 L1 loss: 0.0000e+00 L2 loss: 0.81301 Learning rate: 0.02 Mask loss: 0.18881 RPN box loss: 0.068 RPN score loss: 0.00828 RPN total loss: 0.07629 Total loss: 1.33317 timestamp: 1655030782.100087 iteration: 29435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20423 FastRCNN class loss: 0.12867 FastRCNN total loss: 0.3329 L1 loss: 0.0000e+00 L2 loss: 0.81291 Learning rate: 0.02 Mask loss: 0.18076 RPN box loss: 0.0397 RPN score loss: 0.01199 RPN total loss: 0.05169 Total loss: 1.37826 timestamp: 1655030785.3520267 iteration: 29440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11277 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.17457 L1 loss: 0.0000e+00 L2 loss: 0.81277 Learning rate: 0.02 Mask loss: 0.16771 RPN box loss: 0.0318 RPN score loss: 0.00543 RPN total loss: 0.03723 Total loss: 1.19228 timestamp: 1655030788.665538 iteration: 29445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13869 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.2098 L1 loss: 0.0000e+00 L2 loss: 0.81265 Learning rate: 0.02 Mask loss: 0.21171 RPN box loss: 0.09218 RPN score loss: 0.00569 RPN total loss: 0.09787 Total loss: 1.33203 timestamp: 1655030791.9793942 iteration: 29450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05943 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.12106 L1 loss: 0.0000e+00 L2 loss: 0.81254 Learning rate: 0.02 Mask loss: 0.09378 RPN box loss: 0.02531 RPN score loss: 0.00164 RPN total loss: 0.02695 Total loss: 1.05434 timestamp: 1655030795.2632403 iteration: 29455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14513 FastRCNN class loss: 0.08124 FastRCNN total loss: 0.22637 L1 loss: 0.0000e+00 L2 loss: 0.81243 Learning rate: 0.02 Mask loss: 0.24508 RPN box loss: 0.035 RPN score loss: 0.01957 RPN total loss: 0.05457 Total loss: 1.33844 timestamp: 1655030798.5047812 iteration: 29460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13327 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.21677 L1 loss: 0.0000e+00 L2 loss: 0.8123 Learning rate: 0.02 Mask loss: 0.15712 RPN box loss: 0.03669 RPN score loss: 0.01024 RPN total loss: 0.04693 Total loss: 1.23312 timestamp: 1655030801.8426728 iteration: 29465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08211 FastRCNN class loss: 0.04235 FastRCNN total loss: 0.12446 L1 loss: 0.0000e+00 L2 loss: 0.81218 Learning rate: 0.02 Mask loss: 0.10505 RPN box loss: 0.03473 RPN score loss: 0.02581 RPN total loss: 0.06054 Total loss: 1.10223 timestamp: 1655030805.1121726 iteration: 29470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12542 FastRCNN class loss: 0.06768 FastRCNN total loss: 0.1931 L1 loss: 0.0000e+00 L2 loss: 0.81205 Learning rate: 0.02 Mask loss: 0.09894 RPN box loss: 0.02179 RPN score loss: 0.00381 RPN total loss: 0.0256 Total loss: 1.12968 timestamp: 1655030808.38409 iteration: 29475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14535 FastRCNN class loss: 0.16673 FastRCNN total loss: 0.31208 L1 loss: 0.0000e+00 L2 loss: 0.8119 Learning rate: 0.02 Mask loss: 0.29473 RPN box loss: 0.05768 RPN score loss: 0.11041 RPN total loss: 0.16809 Total loss: 1.5868 timestamp: 1655030811.6961584 iteration: 29480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11595 FastRCNN class loss: 0.05089 FastRCNN total loss: 0.16685 L1 loss: 0.0000e+00 L2 loss: 0.81179 Learning rate: 0.02 Mask loss: 0.17974 RPN box loss: 0.03865 RPN score loss: 0.00783 RPN total loss: 0.04648 Total loss: 1.20486 timestamp: 1655030814.9302216 iteration: 29485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1416 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.22278 L1 loss: 0.0000e+00 L2 loss: 0.81169 Learning rate: 0.02 Mask loss: 0.2381 RPN box loss: 0.03157 RPN score loss: 0.00579 RPN total loss: 0.03737 Total loss: 1.30994 timestamp: 1655030818.137255 iteration: 29490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15729 FastRCNN class loss: 0.06802 FastRCNN total loss: 0.22531 L1 loss: 0.0000e+00 L2 loss: 0.81156 Learning rate: 0.02 Mask loss: 0.21122 RPN box loss: 0.04278 RPN score loss: 0.00539 RPN total loss: 0.04817 Total loss: 1.29626 timestamp: 1655030821.389823 iteration: 29495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23796 FastRCNN class loss: 0.12274 FastRCNN total loss: 0.3607 L1 loss: 0.0000e+00 L2 loss: 0.81141 Learning rate: 0.02 Mask loss: 0.19306 RPN box loss: 0.03868 RPN score loss: 0.00863 RPN total loss: 0.04731 Total loss: 1.41248 timestamp: 1655030824.7586021 iteration: 29500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20867 FastRCNN class loss: 0.10657 FastRCNN total loss: 0.31524 L1 loss: 0.0000e+00 L2 loss: 0.81129 Learning rate: 0.02 Mask loss: 0.24659 RPN box loss: 0.04101 RPN score loss: 0.0059 RPN total loss: 0.04691 Total loss: 1.42003 timestamp: 1655030828.0432925 iteration: 29505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16136 FastRCNN class loss: 0.08077 FastRCNN total loss: 0.24213 L1 loss: 0.0000e+00 L2 loss: 0.81119 Learning rate: 0.02 Mask loss: 0.10745 RPN box loss: 0.05073 RPN score loss: 0.00374 RPN total loss: 0.05447 Total loss: 1.21524 timestamp: 1655030831.2854397 iteration: 29510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17788 FastRCNN class loss: 0.06281 FastRCNN total loss: 0.24069 L1 loss: 0.0000e+00 L2 loss: 0.81108 Learning rate: 0.02 Mask loss: 0.14121 RPN box loss: 0.01954 RPN score loss: 0.00387 RPN total loss: 0.0234 Total loss: 1.21638 timestamp: 1655030834.5520327 iteration: 29515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18667 FastRCNN class loss: 0.10107 FastRCNN total loss: 0.28773 L1 loss: 0.0000e+00 L2 loss: 0.81096 Learning rate: 0.02 Mask loss: 0.19444 RPN box loss: 0.03942 RPN score loss: 0.00694 RPN total loss: 0.04637 Total loss: 1.3395 timestamp: 1655030837.7920098 iteration: 29520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11931 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.18932 L1 loss: 0.0000e+00 L2 loss: 0.81082 Learning rate: 0.02 Mask loss: 0.19802 RPN box loss: 0.01185 RPN score loss: 0.00609 RPN total loss: 0.01794 Total loss: 1.2161 timestamp: 1655030841.0460825 iteration: 29525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05838 FastRCNN class loss: 0.06734 FastRCNN total loss: 0.12572 L1 loss: 0.0000e+00 L2 loss: 0.8107 Learning rate: 0.02 Mask loss: 0.14734 RPN box loss: 0.04474 RPN score loss: 0.00801 RPN total loss: 0.05275 Total loss: 1.13651 timestamp: 1655030844.33202 iteration: 29530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13394 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.20082 L1 loss: 0.0000e+00 L2 loss: 0.8106 Learning rate: 0.02 Mask loss: 0.15175 RPN box loss: 0.0539 RPN score loss: 0.0058 RPN total loss: 0.0597 Total loss: 1.22286 timestamp: 1655030847.5872452 iteration: 29535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13666 FastRCNN class loss: 0.11459 FastRCNN total loss: 0.25125 L1 loss: 0.0000e+00 L2 loss: 0.81047 Learning rate: 0.02 Mask loss: 0.16777 RPN box loss: 0.03145 RPN score loss: 0.00776 RPN total loss: 0.03921 Total loss: 1.2687 timestamp: 1655030850.7971606 iteration: 29540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1274 FastRCNN class loss: 0.09965 FastRCNN total loss: 0.22705 L1 loss: 0.0000e+00 L2 loss: 0.81034 Learning rate: 0.02 Mask loss: 0.18559 RPN box loss: 0.01944 RPN score loss: 0.00318 RPN total loss: 0.02262 Total loss: 1.24559 timestamp: 1655030853.9832616 iteration: 29545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20647 FastRCNN class loss: 0.10853 FastRCNN total loss: 0.315 L1 loss: 0.0000e+00 L2 loss: 0.81019 Learning rate: 0.02 Mask loss: 0.20992 RPN box loss: 0.05445 RPN score loss: 0.00773 RPN total loss: 0.06218 Total loss: 1.39729 timestamp: 1655030857.2461169 iteration: 29550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15306 FastRCNN class loss: 0.094 FastRCNN total loss: 0.24706 L1 loss: 0.0000e+00 L2 loss: 0.81006 Learning rate: 0.02 Mask loss: 0.15033 RPN box loss: 0.02201 RPN score loss: 0.01164 RPN total loss: 0.03366 Total loss: 1.2411 timestamp: 1655030860.52468 iteration: 29555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19115 FastRCNN class loss: 0.10869 FastRCNN total loss: 0.29984 L1 loss: 0.0000e+00 L2 loss: 0.80995 Learning rate: 0.02 Mask loss: 0.16052 RPN box loss: 0.08034 RPN score loss: 0.00856 RPN total loss: 0.0889 Total loss: 1.35921 timestamp: 1655030863.7833426 iteration: 29560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12076 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.19414 L1 loss: 0.0000e+00 L2 loss: 0.80982 Learning rate: 0.02 Mask loss: 0.13969 RPN box loss: 0.03005 RPN score loss: 0.00622 RPN total loss: 0.03626 Total loss: 1.17992 timestamp: 1655030867.086605 iteration: 29565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12614 FastRCNN class loss: 0.04937 FastRCNN total loss: 0.17551 L1 loss: 0.0000e+00 L2 loss: 0.80971 Learning rate: 0.02 Mask loss: 0.10685 RPN box loss: 0.02204 RPN score loss: 0.00372 RPN total loss: 0.02576 Total loss: 1.11783 timestamp: 1655030870.376174 iteration: 29570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1489 FastRCNN class loss: 0.1345 FastRCNN total loss: 0.2834 L1 loss: 0.0000e+00 L2 loss: 0.80958 Learning rate: 0.02 Mask loss: 0.17262 RPN box loss: 0.03183 RPN score loss: 0.00722 RPN total loss: 0.03905 Total loss: 1.30465 timestamp: 1655030873.6726313 iteration: 29575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09533 FastRCNN class loss: 0.08821 FastRCNN total loss: 0.18354 L1 loss: 0.0000e+00 L2 loss: 0.80946 Learning rate: 0.02 Mask loss: 0.13316 RPN box loss: 0.03405 RPN score loss: 0.00816 RPN total loss: 0.0422 Total loss: 1.16836 timestamp: 1655030876.9297502 iteration: 29580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13081 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.21683 L1 loss: 0.0000e+00 L2 loss: 0.80931 Learning rate: 0.02 Mask loss: 0.12343 RPN box loss: 0.03865 RPN score loss: 0.0112 RPN total loss: 0.04985 Total loss: 1.19943 timestamp: 1655030880.229429 iteration: 29585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2435 FastRCNN class loss: 0.09873 FastRCNN total loss: 0.34224 L1 loss: 0.0000e+00 L2 loss: 0.80919 Learning rate: 0.02 Mask loss: 0.17423 RPN box loss: 0.02126 RPN score loss: 0.01244 RPN total loss: 0.0337 Total loss: 1.35935 timestamp: 1655030883.5214727 iteration: 29590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.18256 L1 loss: 0.0000e+00 L2 loss: 0.80908 Learning rate: 0.02 Mask loss: 0.13106 RPN box loss: 0.01907 RPN score loss: 0.00668 RPN total loss: 0.02575 Total loss: 1.14845 timestamp: 1655030886.7975101 iteration: 29595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19204 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.27277 L1 loss: 0.0000e+00 L2 loss: 0.80895 Learning rate: 0.02 Mask loss: 0.14927 RPN box loss: 0.04628 RPN score loss: 0.0099 RPN total loss: 0.05618 Total loss: 1.28717 timestamp: 1655030890.0632093 iteration: 29600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12836 FastRCNN class loss: 0.07451 FastRCNN total loss: 0.20287 L1 loss: 0.0000e+00 L2 loss: 0.80883 Learning rate: 0.02 Mask loss: 0.16459 RPN box loss: 0.02033 RPN score loss: 0.00819 RPN total loss: 0.02852 Total loss: 1.20481 timestamp: 1655030893.4313698 iteration: 29605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17184 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.24316 L1 loss: 0.0000e+00 L2 loss: 0.80872 Learning rate: 0.02 Mask loss: 0.16157 RPN box loss: 0.04847 RPN score loss: 0.00579 RPN total loss: 0.05426 Total loss: 1.26771 timestamp: 1655030896.7656987 iteration: 29610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13928 FastRCNN class loss: 0.13615 FastRCNN total loss: 0.27543 L1 loss: 0.0000e+00 L2 loss: 0.8086 Learning rate: 0.02 Mask loss: 0.17051 RPN box loss: 0.0607 RPN score loss: 0.01827 RPN total loss: 0.07897 Total loss: 1.33351 timestamp: 1655030900.040369 iteration: 29615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12219 FastRCNN class loss: 0.058 FastRCNN total loss: 0.18018 L1 loss: 0.0000e+00 L2 loss: 0.80846 Learning rate: 0.02 Mask loss: 0.10638 RPN box loss: 0.02707 RPN score loss: 0.00257 RPN total loss: 0.02964 Total loss: 1.12467 timestamp: 1655030903.3401494 iteration: 29620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06052 FastRCNN class loss: 0.03674 FastRCNN total loss: 0.09726 L1 loss: 0.0000e+00 L2 loss: 0.80834 Learning rate: 0.02 Mask loss: 0.09323 RPN box loss: 0.02496 RPN score loss: 0.0013 RPN total loss: 0.02627 Total loss: 1.0251 timestamp: 1655030906.6614199 iteration: 29625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13152 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.20267 L1 loss: 0.0000e+00 L2 loss: 0.80819 Learning rate: 0.02 Mask loss: 0.14558 RPN box loss: 0.0119 RPN score loss: 0.0032 RPN total loss: 0.01511 Total loss: 1.17155 timestamp: 1655030909.957272 iteration: 29630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20049 FastRCNN class loss: 0.10565 FastRCNN total loss: 0.30613 L1 loss: 0.0000e+00 L2 loss: 0.80807 Learning rate: 0.02 Mask loss: 0.20489 RPN box loss: 0.03554 RPN score loss: 0.00896 RPN total loss: 0.0445 Total loss: 1.3636 timestamp: 1655030913.3331797 iteration: 29635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14297 FastRCNN class loss: 0.07896 FastRCNN total loss: 0.22193 L1 loss: 0.0000e+00 L2 loss: 0.80797 Learning rate: 0.02 Mask loss: 0.17757 RPN box loss: 0.00645 RPN score loss: 0.00556 RPN total loss: 0.01201 Total loss: 1.21948 timestamp: 1655030916.598694 iteration: 29640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14098 FastRCNN class loss: 0.05259 FastRCNN total loss: 0.19357 L1 loss: 0.0000e+00 L2 loss: 0.80784 Learning rate: 0.02 Mask loss: 0.17008 RPN box loss: 0.02911 RPN score loss: 0.00966 RPN total loss: 0.03877 Total loss: 1.21026 timestamp: 1655030919.8462732 iteration: 29645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14838 FastRCNN class loss: 0.11036 FastRCNN total loss: 0.25874 L1 loss: 0.0000e+00 L2 loss: 0.8077 Learning rate: 0.02 Mask loss: 0.15044 RPN box loss: 0.0213 RPN score loss: 0.00517 RPN total loss: 0.02648 Total loss: 1.24335 timestamp: 1655030923.141168 iteration: 29650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08117 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.15347 L1 loss: 0.0000e+00 L2 loss: 0.80755 Learning rate: 0.02 Mask loss: 0.14351 RPN box loss: 0.03367 RPN score loss: 0.01038 RPN total loss: 0.04405 Total loss: 1.14859 timestamp: 1655030926.4882214 iteration: 29655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10049 FastRCNN class loss: 0.07799 FastRCNN total loss: 0.17849 L1 loss: 0.0000e+00 L2 loss: 0.80743 Learning rate: 0.02 Mask loss: 0.17366 RPN box loss: 0.0334 RPN score loss: 0.00594 RPN total loss: 0.03934 Total loss: 1.19892 timestamp: 1655030929.7705941 iteration: 29660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13997 FastRCNN class loss: 0.14062 FastRCNN total loss: 0.28058 L1 loss: 0.0000e+00 L2 loss: 0.80734 Learning rate: 0.02 Mask loss: 0.14965 RPN box loss: 0.03533 RPN score loss: 0.00524 RPN total loss: 0.04057 Total loss: 1.27815 timestamp: 1655030933.0512338 iteration: 29665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14952 FastRCNN class loss: 0.09481 FastRCNN total loss: 0.24432 L1 loss: 0.0000e+00 L2 loss: 0.80724 Learning rate: 0.02 Mask loss: 0.20972 RPN box loss: 0.06268 RPN score loss: 0.00679 RPN total loss: 0.06946 Total loss: 1.33074 timestamp: 1655030936.3860164 iteration: 29670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15935 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.23122 L1 loss: 0.0000e+00 L2 loss: 0.80712 Learning rate: 0.02 Mask loss: 0.13885 RPN box loss: 0.01656 RPN score loss: 0.00508 RPN total loss: 0.02163 Total loss: 1.19883 timestamp: 1655030939.6410906 iteration: 29675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09473 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.15152 L1 loss: 0.0000e+00 L2 loss: 0.80699 Learning rate: 0.02 Mask loss: 0.16309 RPN box loss: 0.02313 RPN score loss: 0.00389 RPN total loss: 0.02702 Total loss: 1.14862 timestamp: 1655030942.8634083 iteration: 29680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18955 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.24644 L1 loss: 0.0000e+00 L2 loss: 0.80684 Learning rate: 0.02 Mask loss: 0.16514 RPN box loss: 0.01272 RPN score loss: 0.00475 RPN total loss: 0.01748 Total loss: 1.2359 timestamp: 1655030946.2076108 iteration: 29685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09484 FastRCNN class loss: 0.05286 FastRCNN total loss: 0.1477 L1 loss: 0.0000e+00 L2 loss: 0.8067 Learning rate: 0.02 Mask loss: 0.1381 RPN box loss: 0.03774 RPN score loss: 0.00145 RPN total loss: 0.0392 Total loss: 1.13171 timestamp: 1655030949.5195243 iteration: 29690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.16084 L1 loss: 0.0000e+00 L2 loss: 0.80659 Learning rate: 0.02 Mask loss: 0.13803 RPN box loss: 0.04748 RPN score loss: 0.00215 RPN total loss: 0.04963 Total loss: 1.15509 timestamp: 1655030952.7418854 iteration: 29695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13978 FastRCNN class loss: 0.05751 FastRCNN total loss: 0.19729 L1 loss: 0.0000e+00 L2 loss: 0.80647 Learning rate: 0.02 Mask loss: 0.13961 RPN box loss: 0.00613 RPN score loss: 0.00252 RPN total loss: 0.00865 Total loss: 1.15202 timestamp: 1655030956.0073533 iteration: 29700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1676 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.24515 L1 loss: 0.0000e+00 L2 loss: 0.80638 Learning rate: 0.02 Mask loss: 0.09515 RPN box loss: 0.01192 RPN score loss: 0.00253 RPN total loss: 0.01445 Total loss: 1.16112 timestamp: 1655030959.2744231 iteration: 29705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09789 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.17315 L1 loss: 0.0000e+00 L2 loss: 0.80624 Learning rate: 0.02 Mask loss: 0.12931 RPN box loss: 0.03833 RPN score loss: 0.00312 RPN total loss: 0.04144 Total loss: 1.15014 timestamp: 1655030962.5891387 iteration: 29710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17313 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.23735 L1 loss: 0.0000e+00 L2 loss: 0.80611 Learning rate: 0.02 Mask loss: 0.12925 RPN box loss: 0.04897 RPN score loss: 0.00609 RPN total loss: 0.05506 Total loss: 1.22778 timestamp: 1655030965.8691206 iteration: 29715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18368 FastRCNN class loss: 0.11931 FastRCNN total loss: 0.30299 L1 loss: 0.0000e+00 L2 loss: 0.80598 Learning rate: 0.02 Mask loss: 0.19921 RPN box loss: 0.03001 RPN score loss: 0.01766 RPN total loss: 0.04767 Total loss: 1.35585 timestamp: 1655030969.0980232 iteration: 29720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21139 FastRCNN class loss: 0.11784 FastRCNN total loss: 0.32923 L1 loss: 0.0000e+00 L2 loss: 0.80585 Learning rate: 0.02 Mask loss: 0.21765 RPN box loss: 0.04437 RPN score loss: 0.01065 RPN total loss: 0.05502 Total loss: 1.40776 timestamp: 1655030972.4584966 iteration: 29725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1862 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.2689 L1 loss: 0.0000e+00 L2 loss: 0.80573 Learning rate: 0.02 Mask loss: 0.1989 RPN box loss: 0.05153 RPN score loss: 0.00658 RPN total loss: 0.05811 Total loss: 1.33164 timestamp: 1655030975.739523 iteration: 29730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0672 FastRCNN class loss: 0.04142 FastRCNN total loss: 0.10863 L1 loss: 0.0000e+00 L2 loss: 0.8056 Learning rate: 0.02 Mask loss: 0.11549 RPN box loss: 0.00391 RPN score loss: 0.00151 RPN total loss: 0.00543 Total loss: 1.03514 timestamp: 1655030979.0722492 iteration: 29735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0555 FastRCNN class loss: 0.04191 FastRCNN total loss: 0.0974 L1 loss: 0.0000e+00 L2 loss: 0.80549 Learning rate: 0.02 Mask loss: 0.16576 RPN box loss: 0.03167 RPN score loss: 0.0046 RPN total loss: 0.03628 Total loss: 1.10493 timestamp: 1655030982.3348281 iteration: 29740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0862 FastRCNN class loss: 0.11293 FastRCNN total loss: 0.19913 L1 loss: 0.0000e+00 L2 loss: 0.80541 Learning rate: 0.02 Mask loss: 0.17536 RPN box loss: 0.06541 RPN score loss: 0.03553 RPN total loss: 0.10094 Total loss: 1.28084 timestamp: 1655030985.5797963 iteration: 29745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10824 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.18162 L1 loss: 0.0000e+00 L2 loss: 0.80528 Learning rate: 0.02 Mask loss: 0.20639 RPN box loss: 0.02821 RPN score loss: 0.00811 RPN total loss: 0.03632 Total loss: 1.22961 timestamp: 1655030988.8974955 iteration: 29750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.11372 FastRCNN total loss: 0.23769 L1 loss: 0.0000e+00 L2 loss: 0.80514 Learning rate: 0.02 Mask loss: 0.22005 RPN box loss: 0.03483 RPN score loss: 0.01156 RPN total loss: 0.04639 Total loss: 1.30927 timestamp: 1655030992.144791 iteration: 29755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09802 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.16424 L1 loss: 0.0000e+00 L2 loss: 0.80504 Learning rate: 0.02 Mask loss: 0.12338 RPN box loss: 0.03547 RPN score loss: 0.0019 RPN total loss: 0.03737 Total loss: 1.13003 timestamp: 1655030995.4283605 iteration: 29760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08486 FastRCNN class loss: 0.08755 FastRCNN total loss: 0.17241 L1 loss: 0.0000e+00 L2 loss: 0.80492 Learning rate: 0.02 Mask loss: 0.13647 RPN box loss: 0.05028 RPN score loss: 0.01494 RPN total loss: 0.06521 Total loss: 1.17901 timestamp: 1655030998.6206942 iteration: 29765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15072 FastRCNN class loss: 0.12251 FastRCNN total loss: 0.27323 L1 loss: 0.0000e+00 L2 loss: 0.80479 Learning rate: 0.02 Mask loss: 0.23464 RPN box loss: 0.03303 RPN score loss: 0.01411 RPN total loss: 0.04714 Total loss: 1.3598 timestamp: 1655031001.8976066 iteration: 29770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16237 FastRCNN class loss: 0.09568 FastRCNN total loss: 0.25805 L1 loss: 0.0000e+00 L2 loss: 0.80468 Learning rate: 0.02 Mask loss: 0.16363 RPN box loss: 0.01788 RPN score loss: 0.00673 RPN total loss: 0.02461 Total loss: 1.25098 timestamp: 1655031005.1948051 iteration: 29775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23269 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.33802 L1 loss: 0.0000e+00 L2 loss: 0.80458 Learning rate: 0.02 Mask loss: 0.19179 RPN box loss: 0.0522 RPN score loss: 0.00848 RPN total loss: 0.06068 Total loss: 1.39507 timestamp: 1655031008.496699 iteration: 29780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11354 FastRCNN class loss: 0.12416 FastRCNN total loss: 0.23771 L1 loss: 0.0000e+00 L2 loss: 0.80444 Learning rate: 0.02 Mask loss: 0.14732 RPN box loss: 0.04358 RPN score loss: 0.00639 RPN total loss: 0.04997 Total loss: 1.23943 timestamp: 1655031011.7805283 iteration: 29785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17984 FastRCNN class loss: 0.12385 FastRCNN total loss: 0.30369 L1 loss: 0.0000e+00 L2 loss: 0.80431 Learning rate: 0.02 Mask loss: 0.27423 RPN box loss: 0.04305 RPN score loss: 0.00653 RPN total loss: 0.04958 Total loss: 1.43181 timestamp: 1655031015.0392067 iteration: 29790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14413 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.21228 L1 loss: 0.0000e+00 L2 loss: 0.8042 Learning rate: 0.02 Mask loss: 0.1716 RPN box loss: 0.01004 RPN score loss: 0.00334 RPN total loss: 0.01338 Total loss: 1.20146 timestamp: 1655031018.3638616 iteration: 29795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23361 FastRCNN class loss: 0.19799 FastRCNN total loss: 0.4316 L1 loss: 0.0000e+00 L2 loss: 0.80407 Learning rate: 0.02 Mask loss: 0.25835 RPN box loss: 0.09021 RPN score loss: 0.01515 RPN total loss: 0.10536 Total loss: 1.59938 timestamp: 1655031021.6671124 iteration: 29800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11881 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.80394 Learning rate: 0.02 Mask loss: 0.14807 RPN box loss: 0.0449 RPN score loss: 0.00443 RPN total loss: 0.04933 Total loss: 1.19255 timestamp: 1655031024.9592755 iteration: 29805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12234 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.17648 L1 loss: 0.0000e+00 L2 loss: 0.80382 Learning rate: 0.02 Mask loss: 0.11813 RPN box loss: 0.00482 RPN score loss: 0.00404 RPN total loss: 0.00886 Total loss: 1.10729 timestamp: 1655031028.2099397 iteration: 29810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.16411 L1 loss: 0.0000e+00 L2 loss: 0.80368 Learning rate: 0.02 Mask loss: 0.11192 RPN box loss: 0.02697 RPN score loss: 0.00713 RPN total loss: 0.0341 Total loss: 1.11381 timestamp: 1655031031.544347 iteration: 29815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09138 FastRCNN class loss: 0.10235 FastRCNN total loss: 0.19373 L1 loss: 0.0000e+00 L2 loss: 0.80358 Learning rate: 0.02 Mask loss: 0.11131 RPN box loss: 0.04582 RPN score loss: 0.01784 RPN total loss: 0.06366 Total loss: 1.17228 timestamp: 1655031034.884496 iteration: 29820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16813 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.23761 L1 loss: 0.0000e+00 L2 loss: 0.80349 Learning rate: 0.02 Mask loss: 0.22376 RPN box loss: 0.03905 RPN score loss: 0.00858 RPN total loss: 0.04763 Total loss: 1.31249 timestamp: 1655031038.1572688 iteration: 29825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17456 FastRCNN class loss: 0.10152 FastRCNN total loss: 0.27608 L1 loss: 0.0000e+00 L2 loss: 0.80336 Learning rate: 0.02 Mask loss: 0.19325 RPN box loss: 0.01317 RPN score loss: 0.00637 RPN total loss: 0.01953 Total loss: 1.29222 timestamp: 1655031041.4942393 iteration: 29830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.03505 FastRCNN total loss: 0.0917 L1 loss: 0.0000e+00 L2 loss: 0.80325 Learning rate: 0.02 Mask loss: 0.11888 RPN box loss: 0.01221 RPN score loss: 0.01173 RPN total loss: 0.02394 Total loss: 1.03777 timestamp: 1655031044.6506665 iteration: 29835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19095 FastRCNN class loss: 0.11432 FastRCNN total loss: 0.30527 L1 loss: 0.0000e+00 L2 loss: 0.80313 Learning rate: 0.02 Mask loss: 0.24445 RPN box loss: 0.02176 RPN score loss: 0.0047 RPN total loss: 0.02646 Total loss: 1.37931 timestamp: 1655031047.8936818 iteration: 29840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09451 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.16428 L1 loss: 0.0000e+00 L2 loss: 0.80303 Learning rate: 0.02 Mask loss: 0.16906 RPN box loss: 0.01301 RPN score loss: 0.0059 RPN total loss: 0.01891 Total loss: 1.1553 timestamp: 1655031051.1219969 iteration: 29845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12976 FastRCNN class loss: 0.08194 FastRCNN total loss: 0.2117 L1 loss: 0.0000e+00 L2 loss: 0.80292 Learning rate: 0.02 Mask loss: 0.1265 RPN box loss: 0.03337 RPN score loss: 0.01851 RPN total loss: 0.05188 Total loss: 1.193 timestamp: 1655031054.3350022 iteration: 29850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13693 FastRCNN class loss: 0.07767 FastRCNN total loss: 0.2146 L1 loss: 0.0000e+00 L2 loss: 0.80275 Learning rate: 0.02 Mask loss: 0.13391 RPN box loss: 0.07955 RPN score loss: 0.00479 RPN total loss: 0.08434 Total loss: 1.23561 timestamp: 1655031057.6375713 iteration: 29855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13025 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.22373 L1 loss: 0.0000e+00 L2 loss: 0.80262 Learning rate: 0.02 Mask loss: 0.14866 RPN box loss: 0.01406 RPN score loss: 0.00943 RPN total loss: 0.02349 Total loss: 1.1985 timestamp: 1655031060.9626536 iteration: 29860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.16616 L1 loss: 0.0000e+00 L2 loss: 0.8025 Learning rate: 0.02 Mask loss: 0.16407 RPN box loss: 0.03004 RPN score loss: 0.00389 RPN total loss: 0.03393 Total loss: 1.16665 timestamp: 1655031064.253554 iteration: 29865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19136 FastRCNN class loss: 0.10191 FastRCNN total loss: 0.29327 L1 loss: 0.0000e+00 L2 loss: 0.80239 Learning rate: 0.02 Mask loss: 0.20295 RPN box loss: 0.02593 RPN score loss: 0.00255 RPN total loss: 0.02848 Total loss: 1.3271 timestamp: 1655031067.516807 iteration: 29870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14475 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.21982 L1 loss: 0.0000e+00 L2 loss: 0.80229 Learning rate: 0.02 Mask loss: 0.14628 RPN box loss: 0.04777 RPN score loss: 0.01039 RPN total loss: 0.05816 Total loss: 1.22656 timestamp: 1655031070.7858226 iteration: 29875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22431 FastRCNN class loss: 0.08787 FastRCNN total loss: 0.31217 L1 loss: 0.0000e+00 L2 loss: 0.80214 Learning rate: 0.02 Mask loss: 0.16158 RPN box loss: 0.06511 RPN score loss: 0.01939 RPN total loss: 0.0845 Total loss: 1.3604 timestamp: 1655031074.0209134 iteration: 29880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14903 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.20839 L1 loss: 0.0000e+00 L2 loss: 0.80201 Learning rate: 0.02 Mask loss: 0.21227 RPN box loss: 0.02502 RPN score loss: 0.01078 RPN total loss: 0.0358 Total loss: 1.25846 timestamp: 1655031077.3099163 iteration: 29885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15156 FastRCNN class loss: 0.09066 FastRCNN total loss: 0.24222 L1 loss: 0.0000e+00 L2 loss: 0.80188 Learning rate: 0.02 Mask loss: 0.14463 RPN box loss: 0.03739 RPN score loss: 0.00851 RPN total loss: 0.0459 Total loss: 1.23463 timestamp: 1655031080.569229 iteration: 29890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15843 FastRCNN class loss: 0.10521 FastRCNN total loss: 0.26364 L1 loss: 0.0000e+00 L2 loss: 0.80177 Learning rate: 0.02 Mask loss: 0.16343 RPN box loss: 0.0269 RPN score loss: 0.00906 RPN total loss: 0.03596 Total loss: 1.26481 timestamp: 1655031083.8557897 iteration: 29895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15716 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.20677 L1 loss: 0.0000e+00 L2 loss: 0.80167 Learning rate: 0.02 Mask loss: 0.14605 RPN box loss: 0.03648 RPN score loss: 0.00287 RPN total loss: 0.03936 Total loss: 1.19385 timestamp: 1655031087.1691813 iteration: 29900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11846 FastRCNN class loss: 0.11649 FastRCNN total loss: 0.23495 L1 loss: 0.0000e+00 L2 loss: 0.80155 Learning rate: 0.02 Mask loss: 0.18039 RPN box loss: 0.01547 RPN score loss: 0.00449 RPN total loss: 0.01996 Total loss: 1.23686 timestamp: 1655031090.408981 iteration: 29905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30332 FastRCNN class loss: 0.16757 FastRCNN total loss: 0.47089 L1 loss: 0.0000e+00 L2 loss: 0.80142 Learning rate: 0.02 Mask loss: 0.38989 RPN box loss: 0.02836 RPN score loss: 0.01639 RPN total loss: 0.04476 Total loss: 1.70696 timestamp: 1655031093.6672466 iteration: 29910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16315 FastRCNN class loss: 0.09464 FastRCNN total loss: 0.2578 L1 loss: 0.0000e+00 L2 loss: 0.80129 Learning rate: 0.02 Mask loss: 0.18288 RPN box loss: 0.02941 RPN score loss: 0.00566 RPN total loss: 0.03507 Total loss: 1.27704 timestamp: 1655031097.0128791 iteration: 29915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1206 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.19304 L1 loss: 0.0000e+00 L2 loss: 0.80117 Learning rate: 0.02 Mask loss: 0.1869 RPN box loss: 0.06271 RPN score loss: 0.0126 RPN total loss: 0.07532 Total loss: 1.25644 timestamp: 1655031100.233204 iteration: 29920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09601 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.15355 L1 loss: 0.0000e+00 L2 loss: 0.80106 Learning rate: 0.02 Mask loss: 0.09636 RPN box loss: 0.03259 RPN score loss: 0.0067 RPN total loss: 0.03929 Total loss: 1.09026 timestamp: 1655031103.4283864 iteration: 29925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19828 FastRCNN class loss: 0.11137 FastRCNN total loss: 0.30965 L1 loss: 0.0000e+00 L2 loss: 0.80096 Learning rate: 0.02 Mask loss: 0.25779 RPN box loss: 0.04414 RPN score loss: 0.00901 RPN total loss: 0.05316 Total loss: 1.42157 timestamp: 1655031106.7308345 iteration: 29930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21505 FastRCNN class loss: 0.11186 FastRCNN total loss: 0.32691 L1 loss: 0.0000e+00 L2 loss: 0.80085 Learning rate: 0.02 Mask loss: 0.18796 RPN box loss: 0.03414 RPN score loss: 0.01011 RPN total loss: 0.04425 Total loss: 1.35996 timestamp: 1655031110.0106032 iteration: 29935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15808 FastRCNN class loss: 0.06456 FastRCNN total loss: 0.22265 L1 loss: 0.0000e+00 L2 loss: 0.80072 Learning rate: 0.02 Mask loss: 0.16732 RPN box loss: 0.08645 RPN score loss: 0.0054 RPN total loss: 0.09185 Total loss: 1.28254 timestamp: 1655031113.2805731 iteration: 29940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20505 FastRCNN class loss: 0.1494 FastRCNN total loss: 0.35446 L1 loss: 0.0000e+00 L2 loss: 0.8006 Learning rate: 0.02 Mask loss: 0.24632 RPN box loss: 0.02386 RPN score loss: 0.01611 RPN total loss: 0.03997 Total loss: 1.44134 timestamp: 1655031116.533115 iteration: 29945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14056 FastRCNN class loss: 0.06199 FastRCNN total loss: 0.20255 L1 loss: 0.0000e+00 L2 loss: 0.80048 Learning rate: 0.02 Mask loss: 0.13312 RPN box loss: 0.02224 RPN score loss: 0.00543 RPN total loss: 0.02767 Total loss: 1.16382 timestamp: 1655031119.7794254 iteration: 29950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19002 FastRCNN class loss: 0.11383 FastRCNN total loss: 0.30385 L1 loss: 0.0000e+00 L2 loss: 0.80036 Learning rate: 0.02 Mask loss: 0.1784 RPN box loss: 0.03165 RPN score loss: 0.00393 RPN total loss: 0.03559 Total loss: 1.3182 timestamp: 1655031122.9741826 iteration: 29955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12917 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.19953 L1 loss: 0.0000e+00 L2 loss: 0.80025 Learning rate: 0.02 Mask loss: 0.15209 RPN box loss: 0.00659 RPN score loss: 0.00507 RPN total loss: 0.01166 Total loss: 1.16354 timestamp: 1655031126.2344294 iteration: 29960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14089 FastRCNN class loss: 0.06745 FastRCNN total loss: 0.20834 L1 loss: 0.0000e+00 L2 loss: 0.80013 Learning rate: 0.02 Mask loss: 0.1474 RPN box loss: 0.02221 RPN score loss: 0.00676 RPN total loss: 0.02897 Total loss: 1.18484 timestamp: 1655031129.485505 iteration: 29965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.1654 L1 loss: 0.0000e+00 L2 loss: 0.80002 Learning rate: 0.02 Mask loss: 0.11821 RPN box loss: 0.02893 RPN score loss: 0.00437 RPN total loss: 0.0333 Total loss: 1.11692 timestamp: 1655031132.7465427 iteration: 29970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15306 FastRCNN class loss: 0.10589 FastRCNN total loss: 0.25895 L1 loss: 0.0000e+00 L2 loss: 0.79989 Learning rate: 0.02 Mask loss: 0.19168 RPN box loss: 0.06901 RPN score loss: 0.00458 RPN total loss: 0.07358 Total loss: 1.32411 timestamp: 1655031136.0154638 iteration: 29975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08031 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.15081 L1 loss: 0.0000e+00 L2 loss: 0.79975 Learning rate: 0.02 Mask loss: 0.11968 RPN box loss: 0.01529 RPN score loss: 0.00234 RPN total loss: 0.01763 Total loss: 1.08787 timestamp: 1655031139.31811 iteration: 29980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14919 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.24332 L1 loss: 0.0000e+00 L2 loss: 0.79963 Learning rate: 0.02 Mask loss: 0.13283 RPN box loss: 0.04725 RPN score loss: 0.00891 RPN total loss: 0.05616 Total loss: 1.23195 timestamp: 1655031142.6081846 iteration: 29985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12687 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.2111 L1 loss: 0.0000e+00 L2 loss: 0.79951 Learning rate: 0.02 Mask loss: 0.2251 RPN box loss: 0.06474 RPN score loss: 0.00885 RPN total loss: 0.07359 Total loss: 1.30931 timestamp: 1655031145.954315 iteration: 29990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13432 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.22331 L1 loss: 0.0000e+00 L2 loss: 0.79941 Learning rate: 0.02 Mask loss: 0.10509 RPN box loss: 0.0084 RPN score loss: 0.00281 RPN total loss: 0.01121 Total loss: 1.13903 timestamp: 1655031149.295364 iteration: 29995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18678 FastRCNN class loss: 0.11469 FastRCNN total loss: 0.30147 L1 loss: 0.0000e+00 L2 loss: 0.79931 Learning rate: 0.02 Mask loss: 0.2619 RPN box loss: 0.07204 RPN score loss: 0.01772 RPN total loss: 0.08976 Total loss: 1.45244 timestamp: 1655031152.5715444 iteration: 30000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12345 FastRCNN class loss: 0.08682 FastRCNN total loss: 0.21027 L1 loss: 0.0000e+00 L2 loss: 0.79917 Learning rate: 0.02 Mask loss: 0.17783 RPN box loss: 0.02561 RPN score loss: 0.00455 RPN total loss: 0.03015 Total loss: 1.21743 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.7410s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.8419s - Throughput: 4.8 imgs/s Running inference on batch 003/125... - Step Time: 0.7851s - Throughput: 5.1 imgs/s Running inference on batch 004/125... - Step Time: 0.8440s - Throughput: 4.7 imgs/s Running inference on batch 005/125... - Step Time: 0.8204s - Throughput: 4.9 imgs/s Running inference on batch 006/125... - Step Time: 0.7996s - Throughput: 5.0 imgs/s Running inference on batch 007/125... - Step Time: 0.8169s - Throughput: 4.9 imgs/s Running inference on batch 008/125... - Step Time: 0.8686s - Throughput: 4.6 imgs/s Running inference on batch 009/125... - Step Time: 0.8665s - Throughput: 4.6 imgs/s Running inference on batch 010/125... - Step Time: 0.8197s - Throughput: 4.9 imgs/s Running inference on batch 011/125... - Step Time: 0.8316s - Throughput: 4.8 imgs/s Running inference on batch 012/125... - Step Time: 0.8113s - Throughput: 4.9 imgs/s Running inference on batch 013/125... - Step Time: 0.8468s - Throughput: 4.7 imgs/s Running inference on batch 014/125... - Step Time: 0.7945s - Throughput: 5.0 imgs/s Running inference on batch 015/125... - Step Time: 0.8149s - Throughput: 4.9 imgs/s Running inference on batch 016/125... - Step Time: 0.8369s - Throughput: 4.8 imgs/s Running inference on batch 017/125... - Step Time: 0.8120s - Throughput: 4.9 imgs/s Running inference on batch 018/125... - Step Time: 0.8105s - Throughput: 4.9 imgs/s Running inference on batch 019/125... - Step Time: 0.8702s - Throughput: 4.6 imgs/s Running inference on batch 020/125... - Step Time: 0.8132s - Throughput: 4.9 imgs/s Running inference on batch 021/125... - Step Time: 0.8032s - Throughput: 5.0 imgs/s Running inference on batch 022/125... - Step Time: 0.8784s - Throughput: 4.6 imgs/s Running inference on batch 023/125... - Step Time: 0.8397s - Throughput: 4.8 imgs/s Running inference on batch 024/125... - Step Time: 0.7598s - Throughput: 5.3 imgs/s Running inference on batch 025/125... - Step Time: 0.8449s - Throughput: 4.7 imgs/s Running inference on batch 026/125... - Step Time: 0.8158s - Throughput: 4.9 imgs/s Running inference on batch 027/125... - Step Time: 0.7821s - Throughput: 5.1 imgs/s Running inference on batch 028/125... - Step Time: 0.7933s - Throughput: 5.0 imgs/s Running inference on batch 029/125... - Step Time: 0.8324s - Throughput: 4.8 imgs/s Running inference on batch 030/125... - Step Time: 0.8582s - Throughput: 4.7 imgs/s Running inference on batch 031/125... - Step Time: 0.8386s - Throughput: 4.8 imgs/s Running inference on batch 032/125... - Step Time: 0.8661s - Throughput: 4.6 imgs/s Running inference on batch 033/125... - Step Time: 0.8472s - Throughput: 4.7 imgs/s Running inference on batch 034/125... - Step Time: 0.8638s - Throughput: 4.6 imgs/s Running inference on batch 035/125... - Step Time: 0.7936s - Throughput: 5.0 imgs/s Running inference on batch 036/125... - Step Time: 0.8210s - Throughput: 4.9 imgs/s Running inference on batch 037/125... - Step Time: 0.8386s - Throughput: 4.8 imgs/s Running inference on batch 038/125... - Step Time: 0.6495s - Throughput: 6.2 imgs/s Running inference on batch 039/125... - Step Time: 0.8517s - Throughput: 4.7 imgs/s Running inference on batch 040/125... - Step Time: 0.8292s - Throughput: 4.8 imgs/s Running inference on batch 041/125... - Step Time: 0.8497s - Throughput: 4.7 imgs/s Running inference on batch 042/125... - Step Time: 0.8377s - Throughput: 4.8 imgs/s Running inference on batch 043/125... - Step Time: 0.8080s - Throughput: 5.0 imgs/s Running inference on batch 044/125... - Step Time: 0.8247s - Throughput: 4.9 imgs/s Running inference on batch 045/125... - Step Time: 0.7966s - Throughput: 5.0 imgs/s Running inference on batch 046/125... - Step Time: 0.8087s - Throughput: 4.9 imgs/s Running inference on batch 047/125... - Step Time: 0.8027s - Throughput: 5.0 imgs/s Running inference on batch 048/125... - Step Time: 0.8747s - Throughput: 4.6 imgs/s Running inference on batch 049/125... - Step Time: 0.8368s - Throughput: 4.8 imgs/s Running inference on batch 050/125... - Step Time: 0.8499s - Throughput: 4.7 imgs/s Running inference on batch 051/125... - Step Time: 0.8091s - Throughput: 4.9 imgs/s Running inference on batch 052/125... - Step Time: 0.7886s - Throughput: 5.1 imgs/s Running inference on batch 053/125... - Step Time: 0.8728s - Throughput: 4.6 imgs/s Running inference on batch 054/125... - Step Time: 0.8100s - Throughput: 4.9 imgs/s Running inference on batch 055/125... - Step Time: 0.7886s - Throughput: 5.1 imgs/s Running inference on batch 056/125... - Step Time: 0.8185s - Throughput: 4.9 imgs/s Running inference on batch 057/125... - Step Time: 0.8148s - Throughput: 4.9 imgs/s Running inference on batch 058/125... - Step Time: 0.8225s - Throughput: 4.9 imgs/s Running inference on batch 059/125... - Step Time: 0.8034s - Throughput: 5.0 imgs/s Running inference on batch 060/125... - Step Time: 0.7952s - Throughput: 5.0 imgs/s Running inference on batch 061/125... - Step Time: 0.8021s - Throughput: 5.0 imgs/s Running inference on batch 062/125... - Step Time: 0.8480s - Throughput: 4.7 imgs/s Running inference on batch 063/125... - Step Time: 0.8134s - Throughput: 4.9 imgs/s Running inference on batch 064/125... - Step Time: 0.8613s - Throughput: 4.6 imgs/s Running inference on batch 065/125... - Step Time: 0.8788s - Throughput: 4.6 imgs/s Running inference on batch 066/125... - Step Time: 0.8594s - Throughput: 4.7 imgs/s Running inference on batch 067/125... - Step Time: 0.8011s - Throughput: 5.0 imgs/s Running inference on batch 068/125... - Step Time: 0.8304s - Throughput: 4.8 imgs/s Running inference on batch 069/125... - Step Time: 0.8432s - Throughput: 4.7 imgs/s Running inference on batch 070/125... - Step Time: 0.8326s - Throughput: 4.8 imgs/s Running inference on batch 071/125... - Step Time: 0.8074s - Throughput: 5.0 imgs/s Running inference on batch 072/125... - Step Time: 0.8551s - Throughput: 4.7 imgs/s Running inference on batch 073/125... - Step Time: 0.6099s - Throughput: 6.6 imgs/s Running inference on batch 074/125... - Step Time: 0.7905s - Throughput: 5.1 imgs/s Running inference on batch 075/125... - Step Time: 0.8730s - Throughput: 4.6 imgs/s Running inference on batch 076/125... - Step Time: 0.8412s - Throughput: 4.8 imgs/s Running inference on batch 077/125... - Step Time: 0.8331s - Throughput: 4.8 imgs/s Running inference on batch 078/125... - Step Time: 0.8418s - Throughput: 4.8 imgs/s Running inference on batch 079/125... - Step Time: 0.8460s - Throughput: 4.7 imgs/s Running inference on batch 080/125... - Step Time: 0.8626s - Throughput: 4.6 imgs/s Running inference on batch 081/125... - Step Time: 0.8343s - Throughput: 4.8 imgs/s Running inference on batch 082/125... - Step Time: 0.7850s - Throughput: 5.1 imgs/s Running inference on batch 083/125... - Step Time: 0.8010s - Throughput: 5.0 imgs/s Running inference on batch 084/125... - Step Time: 0.8233s - Throughput: 4.9 imgs/s Running inference on batch 085/125... - Step Time: 0.8060s - Throughput: 5.0 imgs/s Running inference on batch 086/125... - Step Time: 0.8049s - Throughput: 5.0 imgs/s Running inference on batch 087/125... - Step Time: 0.8349s - Throughput: 4.8 imgs/s Running inference on batch 088/125... - Step Time: 0.8526s - Throughput: 4.7 imgs/s Running inference on batch 089/125... - Step Time: 0.8662s - Throughput: 4.6 imgs/s Running inference on batch 090/125... - Step Time: 0.7258s - Throughput: 5.5 imgs/s Running inference on batch 091/125... - Step Time: 0.8258s - Throughput: 4.8 imgs/s Running inference on batch 092/125... - Step Time: 0.8722s - Throughput: 4.6 imgs/s Running inference on batch 093/125... - Step Time: 0.8083s - Throughput: 4.9 imgs/s Running inference on batch 094/125... - Step Time: 0.8277s - Throughput: 4.8 imgs/s Running inference on batch 095/125... - Step Time: 0.8167s - Throughput: 4.9 imgs/s Running inference on batch 096/125... - Step Time: 0.8477s - Throughput: 4.7 imgs/s Running inference on batch 097/125... - Step Time: 0.8694s - Throughput: 4.6 imgs/s Running inference on batch 098/125... - Step Time: 0.8292s - Throughput: 4.8 imgs/s Running inference on batch 099/125... - Step Time: 0.8267s - Throughput: 4.8 imgs/s Running inference on batch 100/125... - Step Time: 0.8095s - Throughput: 4.9 imgs/s Running inference on batch 101/125... - Step Time: 0.8306s - Throughput: 4.8 imgs/s Running inference on batch 102/125... - Step Time: 0.8247s - Throughput: 4.9 imgs/s Running inference on batch 103/125... - Step Time: 0.8450s - Throughput: 4.7 imgs/s Running inference on batch 104/125... - Step Time: 0.8351s - Throughput: 4.8 imgs/s Running inference on batch 105/125... - Step Time: 0.8027s - Throughput: 5.0 imgs/s Running inference on batch 106/125... - Step Time: 0.6463s - Throughput: 6.2 imgs/s Running inference on batch 107/125... - Step Time: 0.8418s - Throughput: 4.8 imgs/s Running inference on batch 108/125... - Step Time: 0.8476s - Throughput: 4.7 imgs/s Running inference on batch 109/125... - Step Time: 0.8470s - Throughput: 4.7 imgs/s Running inference on batch 110/125... - Step Time: 0.8756s - Throughput: 4.6 imgs/s Running inference on batch 111/125... - Step Time: 0.8377s - Throughput: 4.8 imgs/s Running inference on batch 112/125... - Step Time: 0.7978s - Throughput: 5.0 imgs/s Running inference on batch 113/125... - Step Time: 0.8185s - Throughput: 4.9 imgs/s Running inference on batch 114/125... - Step Time: 0.7993s - Throughput: 5.0 imgs/s Running inference on batch 115/125... - Step Time: 0.8503s - Throughput: 4.7 imgs/s Running inference on batch 116/125... - Step Time: 0.8368s - Throughput: 4.8 imgs/s Running inference on batch 117/125... - Step Time: 0.8457s - Throughput: 4.7 imgs/s Running inference on batch 118/125... - Step Time: 0.8786s - Throughput: 4.6 imgs/s Running inference on batch 119/125... - Step Time: 0.8421s - Throughput: 4.8 imgs/s Running inference on batch 120/125... - Step Time: 0.8410s - Throughput: 4.8 imgs/s Running inference on batch 121/125... - Step Time: 0.7996s - Throughput: 5.0 imgs/s Running inference on batch 122/125... - Step Time: 0.8148s - Throughput: 4.9 imgs/s Running inference on batch 123/125... - Step Time: 0.8262s - Throughput: 4.8 imgs/s Running inference on batch 124/125... - Step Time: 0.8831s - Throughput: 4.5 imgs/s Running inference on batch 125/125... - Step Time: 0.8002s - Throughput: 5.0 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: 4.8 samples/sec Total processed steps: 125 Total processing time: 0.0h 10m 04s ==================== Metrics ==================== AP: 0.169843480 AP50: 0.269040793 AP75: 0.170629725 APl: 0.202226505 APm: 0.044827878 APs: 0.005015502 ARl: 0.428753197 ARm: 0.093251579 ARmax1: 0.257518232 ARmax10: 0.364201486 ARmax100: 0.368172228 ARs: 0.009126985 mask_AP: 0.134394929 mask_AP50: 0.225112513 mask_AP75: 0.138088167 mask_APl: 0.161780685 mask_APm: 0.014331564 mask_APs: 0.000008801 mask_ARl: 0.285355181 mask_ARm: 0.042334501 mask_ARmax1: 0.191666201 mask_ARmax10: 0.234283119 mask_ARmax100: 0.238751560 mask_ARs: 0.000966184 ================================= 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] 549.0 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: 1655032466.1306422 iteration: 30005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1245 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.18033 L1 loss: 0.0000e+00 L2 loss: 0.79906 Learning rate: 0.02 Mask loss: 0.10309 RPN box loss: 0.02905 RPN score loss: 0.00372 RPN total loss: 0.03277 Total loss: 1.11525 timestamp: 1655032469.385398 iteration: 30010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09908 FastRCNN class loss: 0.08323 FastRCNN total loss: 0.18231 L1 loss: 0.0000e+00 L2 loss: 0.79897 Learning rate: 0.02 Mask loss: 0.16895 RPN box loss: 0.04158 RPN score loss: 0.00373 RPN total loss: 0.04531 Total loss: 1.19554 timestamp: 1655032472.6629896 iteration: 30015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10547 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.15987 L1 loss: 0.0000e+00 L2 loss: 0.79885 Learning rate: 0.02 Mask loss: 0.20077 RPN box loss: 0.00908 RPN score loss: 0.00755 RPN total loss: 0.01663 Total loss: 1.17612 timestamp: 1655032475.8820155 iteration: 30020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20099 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.27277 L1 loss: 0.0000e+00 L2 loss: 0.79871 Learning rate: 0.02 Mask loss: 0.19189 RPN box loss: 0.05909 RPN score loss: 0.00355 RPN total loss: 0.06264 Total loss: 1.32601 timestamp: 1655032479.2230647 iteration: 30025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1055 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.16424 L1 loss: 0.0000e+00 L2 loss: 0.79858 Learning rate: 0.02 Mask loss: 0.16405 RPN box loss: 0.04313 RPN score loss: 0.00422 RPN total loss: 0.04735 Total loss: 1.17422 timestamp: 1655032482.4983306 iteration: 30030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15059 FastRCNN class loss: 0.08769 FastRCNN total loss: 0.23828 L1 loss: 0.0000e+00 L2 loss: 0.79845 Learning rate: 0.02 Mask loss: 0.09884 RPN box loss: 0.01203 RPN score loss: 0.00463 RPN total loss: 0.01665 Total loss: 1.15223 timestamp: 1655032485.752999 iteration: 30035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0789 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.14606 L1 loss: 0.0000e+00 L2 loss: 0.79834 Learning rate: 0.02 Mask loss: 0.18178 RPN box loss: 0.00929 RPN score loss: 0.0067 RPN total loss: 0.01598 Total loss: 1.14217 timestamp: 1655032488.9947326 iteration: 30040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12617 FastRCNN class loss: 0.09905 FastRCNN total loss: 0.22522 L1 loss: 0.0000e+00 L2 loss: 0.79823 Learning rate: 0.02 Mask loss: 0.18248 RPN box loss: 0.00557 RPN score loss: 0.00389 RPN total loss: 0.00946 Total loss: 1.21538 timestamp: 1655032492.3277352 iteration: 30045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19978 FastRCNN class loss: 0.09595 FastRCNN total loss: 0.29573 L1 loss: 0.0000e+00 L2 loss: 0.79812 Learning rate: 0.02 Mask loss: 0.1132 RPN box loss: 0.02709 RPN score loss: 0.0091 RPN total loss: 0.03619 Total loss: 1.24324 timestamp: 1655032495.5933228 iteration: 30050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16351 FastRCNN class loss: 0.09824 FastRCNN total loss: 0.26175 L1 loss: 0.0000e+00 L2 loss: 0.798 Learning rate: 0.02 Mask loss: 0.15754 RPN box loss: 0.01555 RPN score loss: 0.00215 RPN total loss: 0.0177 Total loss: 1.23499 timestamp: 1655032498.9181895 iteration: 30055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12953 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.19064 L1 loss: 0.0000e+00 L2 loss: 0.79789 Learning rate: 0.02 Mask loss: 0.13671 RPN box loss: 0.04011 RPN score loss: 0.00649 RPN total loss: 0.0466 Total loss: 1.17184 timestamp: 1655032502.2141547 iteration: 30060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17338 FastRCNN class loss: 0.15707 FastRCNN total loss: 0.33045 L1 loss: 0.0000e+00 L2 loss: 0.79777 Learning rate: 0.02 Mask loss: 0.25226 RPN box loss: 0.04964 RPN score loss: 0.01045 RPN total loss: 0.06009 Total loss: 1.44056 timestamp: 1655032505.5234342 iteration: 30065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11928 FastRCNN class loss: 0.08196 FastRCNN total loss: 0.20124 L1 loss: 0.0000e+00 L2 loss: 0.79764 Learning rate: 0.02 Mask loss: 0.16853 RPN box loss: 0.05064 RPN score loss: 0.0052 RPN total loss: 0.05585 Total loss: 1.22325 timestamp: 1655032508.8018491 iteration: 30070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1468 FastRCNN class loss: 0.10151 FastRCNN total loss: 0.24831 L1 loss: 0.0000e+00 L2 loss: 0.79752 Learning rate: 0.02 Mask loss: 0.13751 RPN box loss: 0.05669 RPN score loss: 0.00674 RPN total loss: 0.06343 Total loss: 1.24678 timestamp: 1655032512.1478488 iteration: 30075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15542 FastRCNN class loss: 0.10627 FastRCNN total loss: 0.26169 L1 loss: 0.0000e+00 L2 loss: 0.79741 Learning rate: 0.02 Mask loss: 0.15446 RPN box loss: 0.03027 RPN score loss: 0.01224 RPN total loss: 0.04251 Total loss: 1.25607 timestamp: 1655032515.3560405 iteration: 30080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.03024 FastRCNN total loss: 0.10314 L1 loss: 0.0000e+00 L2 loss: 0.79729 Learning rate: 0.02 Mask loss: 0.12114 RPN box loss: 0.02136 RPN score loss: 0.00422 RPN total loss: 0.02558 Total loss: 1.04715 timestamp: 1655032518.6760933 iteration: 30085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.09279 FastRCNN total loss: 0.2157 L1 loss: 0.0000e+00 L2 loss: 0.79718 Learning rate: 0.02 Mask loss: 0.18531 RPN box loss: 0.03619 RPN score loss: 0.00681 RPN total loss: 0.043 Total loss: 1.24119 timestamp: 1655032522.0219862 iteration: 30090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18094 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.28071 L1 loss: 0.0000e+00 L2 loss: 0.79706 Learning rate: 0.02 Mask loss: 0.16397 RPN box loss: 0.03054 RPN score loss: 0.00448 RPN total loss: 0.03502 Total loss: 1.27677 timestamp: 1655032525.2935374 iteration: 30095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08918 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.14476 L1 loss: 0.0000e+00 L2 loss: 0.79692 Learning rate: 0.02 Mask loss: 0.08627 RPN box loss: 0.02802 RPN score loss: 0.00657 RPN total loss: 0.03459 Total loss: 1.06255 timestamp: 1655032528.5787604 iteration: 30100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13658 FastRCNN class loss: 0.0547 FastRCNN total loss: 0.19128 L1 loss: 0.0000e+00 L2 loss: 0.7968 Learning rate: 0.02 Mask loss: 0.1095 RPN box loss: 0.03002 RPN score loss: 0.0079 RPN total loss: 0.03792 Total loss: 1.1355 timestamp: 1655032531.8390603 iteration: 30105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18581 FastRCNN class loss: 0.10281 FastRCNN total loss: 0.28862 L1 loss: 0.0000e+00 L2 loss: 0.79668 Learning rate: 0.02 Mask loss: 0.15031 RPN box loss: 0.04753 RPN score loss: 0.00786 RPN total loss: 0.05538 Total loss: 1.29099 timestamp: 1655032535.1601353 iteration: 30110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12783 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.1897 L1 loss: 0.0000e+00 L2 loss: 0.79656 Learning rate: 0.02 Mask loss: 0.13013 RPN box loss: 0.01058 RPN score loss: 0.01397 RPN total loss: 0.02455 Total loss: 1.14093 timestamp: 1655032538.4145424 iteration: 30115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16977 FastRCNN class loss: 0.07542 FastRCNN total loss: 0.24519 L1 loss: 0.0000e+00 L2 loss: 0.79646 Learning rate: 0.02 Mask loss: 0.19734 RPN box loss: 0.01354 RPN score loss: 0.00853 RPN total loss: 0.02207 Total loss: 1.26107 timestamp: 1655032541.587757 iteration: 30120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06337 FastRCNN class loss: 0.0405 FastRCNN total loss: 0.10387 L1 loss: 0.0000e+00 L2 loss: 0.79633 Learning rate: 0.02 Mask loss: 0.13655 RPN box loss: 0.00431 RPN score loss: 0.002 RPN total loss: 0.00631 Total loss: 1.04306 timestamp: 1655032544.766473 iteration: 30125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10823 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.17452 L1 loss: 0.0000e+00 L2 loss: 0.79621 Learning rate: 0.02 Mask loss: 0.1277 RPN box loss: 0.01413 RPN score loss: 0.00724 RPN total loss: 0.02137 Total loss: 1.1198 timestamp: 1655032548.0607781 iteration: 30130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12821 FastRCNN class loss: 0.07616 FastRCNN total loss: 0.20437 L1 loss: 0.0000e+00 L2 loss: 0.79609 Learning rate: 0.02 Mask loss: 0.19361 RPN box loss: 0.09772 RPN score loss: 0.00732 RPN total loss: 0.10504 Total loss: 1.29911 timestamp: 1655032551.3891559 iteration: 30135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16254 FastRCNN class loss: 0.10498 FastRCNN total loss: 0.26752 L1 loss: 0.0000e+00 L2 loss: 0.79594 Learning rate: 0.02 Mask loss: 0.16812 RPN box loss: 0.03236 RPN score loss: 0.01247 RPN total loss: 0.04484 Total loss: 1.27643 timestamp: 1655032554.66733 iteration: 30140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16788 FastRCNN class loss: 0.10934 FastRCNN total loss: 0.27723 L1 loss: 0.0000e+00 L2 loss: 0.79582 Learning rate: 0.02 Mask loss: 0.13654 RPN box loss: 0.03682 RPN score loss: 0.00385 RPN total loss: 0.04067 Total loss: 1.25026 timestamp: 1655032557.904848 iteration: 30145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11608 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.18745 L1 loss: 0.0000e+00 L2 loss: 0.7957 Learning rate: 0.02 Mask loss: 0.10583 RPN box loss: 0.0076 RPN score loss: 0.00601 RPN total loss: 0.01362 Total loss: 1.1026 timestamp: 1655032561.110104 iteration: 30150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12888 FastRCNN class loss: 0.09292 FastRCNN total loss: 0.22179 L1 loss: 0.0000e+00 L2 loss: 0.79558 Learning rate: 0.02 Mask loss: 0.13584 RPN box loss: 0.03521 RPN score loss: 0.00522 RPN total loss: 0.04043 Total loss: 1.19364 timestamp: 1655032564.392114 iteration: 30155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10181 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.15549 L1 loss: 0.0000e+00 L2 loss: 0.79548 Learning rate: 0.02 Mask loss: 0.10565 RPN box loss: 0.01296 RPN score loss: 0.00363 RPN total loss: 0.01659 Total loss: 1.07321 timestamp: 1655032567.7089322 iteration: 30160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1309 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.20386 L1 loss: 0.0000e+00 L2 loss: 0.79535 Learning rate: 0.02 Mask loss: 0.19179 RPN box loss: 0.00999 RPN score loss: 0.01058 RPN total loss: 0.02058 Total loss: 1.21158 timestamp: 1655032571.0866654 iteration: 30165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.14994 L1 loss: 0.0000e+00 L2 loss: 0.79522 Learning rate: 0.02 Mask loss: 0.15012 RPN box loss: 0.03362 RPN score loss: 0.00517 RPN total loss: 0.03879 Total loss: 1.13407 timestamp: 1655032574.3585675 iteration: 30170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13264 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.21167 L1 loss: 0.0000e+00 L2 loss: 0.79511 Learning rate: 0.02 Mask loss: 0.23375 RPN box loss: 0.05532 RPN score loss: 0.01196 RPN total loss: 0.06729 Total loss: 1.30782 timestamp: 1655032577.6576178 iteration: 30175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12932 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.1971 L1 loss: 0.0000e+00 L2 loss: 0.79499 Learning rate: 0.02 Mask loss: 0.131 RPN box loss: 0.01138 RPN score loss: 0.00694 RPN total loss: 0.01832 Total loss: 1.14141 timestamp: 1655032580.9972756 iteration: 30180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15516 FastRCNN class loss: 0.09215 FastRCNN total loss: 0.24731 L1 loss: 0.0000e+00 L2 loss: 0.79487 Learning rate: 0.02 Mask loss: 0.16924 RPN box loss: 0.03054 RPN score loss: 0.0049 RPN total loss: 0.03544 Total loss: 1.24685 timestamp: 1655032584.3086076 iteration: 30185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14611 FastRCNN class loss: 0.15512 FastRCNN total loss: 0.30123 L1 loss: 0.0000e+00 L2 loss: 0.79476 Learning rate: 0.02 Mask loss: 0.20112 RPN box loss: 0.04543 RPN score loss: 0.01292 RPN total loss: 0.05835 Total loss: 1.35546 timestamp: 1655032587.5962565 iteration: 30190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13904 FastRCNN class loss: 0.09497 FastRCNN total loss: 0.23401 L1 loss: 0.0000e+00 L2 loss: 0.79463 Learning rate: 0.02 Mask loss: 0.16437 RPN box loss: 0.03796 RPN score loss: 0.00614 RPN total loss: 0.0441 Total loss: 1.23712 timestamp: 1655032590.8611193 iteration: 30195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17268 FastRCNN class loss: 0.11371 FastRCNN total loss: 0.28639 L1 loss: 0.0000e+00 L2 loss: 0.79451 Learning rate: 0.02 Mask loss: 0.2279 RPN box loss: 0.03069 RPN score loss: 0.01025 RPN total loss: 0.04094 Total loss: 1.34974 timestamp: 1655032594.145633 iteration: 30200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21479 FastRCNN class loss: 0.11234 FastRCNN total loss: 0.32713 L1 loss: 0.0000e+00 L2 loss: 0.7944 Learning rate: 0.02 Mask loss: 0.1618 RPN box loss: 0.06301 RPN score loss: 0.00652 RPN total loss: 0.06953 Total loss: 1.35286 timestamp: 1655032597.4455492 iteration: 30205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12521 FastRCNN class loss: 0.11128 FastRCNN total loss: 0.23649 L1 loss: 0.0000e+00 L2 loss: 0.79429 Learning rate: 0.02 Mask loss: 0.1507 RPN box loss: 0.03536 RPN score loss: 0.00483 RPN total loss: 0.04019 Total loss: 1.22168 timestamp: 1655032600.768641 iteration: 30210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16035 FastRCNN class loss: 0.09423 FastRCNN total loss: 0.25458 L1 loss: 0.0000e+00 L2 loss: 0.79418 Learning rate: 0.02 Mask loss: 0.26293 RPN box loss: 0.02514 RPN score loss: 0.00728 RPN total loss: 0.03243 Total loss: 1.34411 timestamp: 1655032604.03087 iteration: 30215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1613 FastRCNN class loss: 0.0919 FastRCNN total loss: 0.25319 L1 loss: 0.0000e+00 L2 loss: 0.79404 Learning rate: 0.02 Mask loss: 0.2773 RPN box loss: 0.01643 RPN score loss: 0.00709 RPN total loss: 0.02352 Total loss: 1.34804 timestamp: 1655032607.3329506 iteration: 30220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06684 FastRCNN class loss: 0.05068 FastRCNN total loss: 0.11752 L1 loss: 0.0000e+00 L2 loss: 0.79391 Learning rate: 0.02 Mask loss: 0.10651 RPN box loss: 0.03319 RPN score loss: 0.00614 RPN total loss: 0.03933 Total loss: 1.05727 timestamp: 1655032610.609074 iteration: 30225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12637 FastRCNN class loss: 0.07005 FastRCNN total loss: 0.19642 L1 loss: 0.0000e+00 L2 loss: 0.7938 Learning rate: 0.02 Mask loss: 0.13657 RPN box loss: 0.02602 RPN score loss: 0.00453 RPN total loss: 0.03055 Total loss: 1.15734 timestamp: 1655032613.9235723 iteration: 30230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13457 FastRCNN class loss: 0.10213 FastRCNN total loss: 0.23671 L1 loss: 0.0000e+00 L2 loss: 0.79369 Learning rate: 0.02 Mask loss: 0.30795 RPN box loss: 0.03282 RPN score loss: 0.00914 RPN total loss: 0.04196 Total loss: 1.3803 timestamp: 1655032617.2839432 iteration: 30235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12317 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.18525 L1 loss: 0.0000e+00 L2 loss: 0.7936 Learning rate: 0.02 Mask loss: 0.1159 RPN box loss: 0.00672 RPN score loss: 0.0036 RPN total loss: 0.01032 Total loss: 1.10507 timestamp: 1655032620.5824883 iteration: 30240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15352 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 0.79348 Learning rate: 0.02 Mask loss: 0.11675 RPN box loss: 0.02283 RPN score loss: 0.00326 RPN total loss: 0.02609 Total loss: 1.15864 timestamp: 1655032623.8524234 iteration: 30245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11395 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.19059 L1 loss: 0.0000e+00 L2 loss: 0.79335 Learning rate: 0.02 Mask loss: 0.16213 RPN box loss: 0.03733 RPN score loss: 0.00966 RPN total loss: 0.047 Total loss: 1.19307 timestamp: 1655032627.125411 iteration: 30250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09562 FastRCNN class loss: 0.05851 FastRCNN total loss: 0.15412 L1 loss: 0.0000e+00 L2 loss: 0.79324 Learning rate: 0.02 Mask loss: 0.1233 RPN box loss: 0.00844 RPN score loss: 0.00294 RPN total loss: 0.01138 Total loss: 1.08205 timestamp: 1655032630.4388936 iteration: 30255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14938 FastRCNN class loss: 0.06424 FastRCNN total loss: 0.21362 L1 loss: 0.0000e+00 L2 loss: 0.79314 Learning rate: 0.02 Mask loss: 0.0893 RPN box loss: 0.01612 RPN score loss: 0.00283 RPN total loss: 0.01896 Total loss: 1.11502 timestamp: 1655032633.7451496 iteration: 30260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11557 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.18761 L1 loss: 0.0000e+00 L2 loss: 0.79301 Learning rate: 0.02 Mask loss: 0.13379 RPN box loss: 0.0102 RPN score loss: 0.00361 RPN total loss: 0.0138 Total loss: 1.12822 timestamp: 1655032637.0427344 iteration: 30265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16614 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.24688 L1 loss: 0.0000e+00 L2 loss: 0.79289 Learning rate: 0.02 Mask loss: 0.14578 RPN box loss: 0.05241 RPN score loss: 0.01026 RPN total loss: 0.06267 Total loss: 1.24823 timestamp: 1655032640.3441398 iteration: 30270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13367 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.2127 L1 loss: 0.0000e+00 L2 loss: 0.79278 Learning rate: 0.02 Mask loss: 0.17573 RPN box loss: 0.01932 RPN score loss: 0.00849 RPN total loss: 0.02782 Total loss: 1.20904 timestamp: 1655032643.6083071 iteration: 30275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.137 FastRCNN class loss: 0.1164 FastRCNN total loss: 0.2534 L1 loss: 0.0000e+00 L2 loss: 0.79267 Learning rate: 0.02 Mask loss: 0.1832 RPN box loss: 0.03492 RPN score loss: 0.00442 RPN total loss: 0.03933 Total loss: 1.2686 timestamp: 1655032646.915538 iteration: 30280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18449 FastRCNN class loss: 0.08925 FastRCNN total loss: 0.27374 L1 loss: 0.0000e+00 L2 loss: 0.79255 Learning rate: 0.02 Mask loss: 0.18275 RPN box loss: 0.00654 RPN score loss: 0.0038 RPN total loss: 0.01034 Total loss: 1.25939 timestamp: 1655032650.2596612 iteration: 30285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14606 FastRCNN class loss: 0.05256 FastRCNN total loss: 0.19862 L1 loss: 0.0000e+00 L2 loss: 0.79243 Learning rate: 0.02 Mask loss: 0.10602 RPN box loss: 0.02988 RPN score loss: 0.00558 RPN total loss: 0.03545 Total loss: 1.13252 timestamp: 1655032653.5938091 iteration: 30290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12285 FastRCNN class loss: 0.08556 FastRCNN total loss: 0.20841 L1 loss: 0.0000e+00 L2 loss: 0.79232 Learning rate: 0.02 Mask loss: 0.12247 RPN box loss: 0.01907 RPN score loss: 0.00431 RPN total loss: 0.02338 Total loss: 1.14658 timestamp: 1655032656.8884614 iteration: 30295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1293 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.20161 L1 loss: 0.0000e+00 L2 loss: 0.79221 Learning rate: 0.02 Mask loss: 0.14812 RPN box loss: 0.07467 RPN score loss: 0.00482 RPN total loss: 0.07948 Total loss: 1.22143 timestamp: 1655032660.2226017 iteration: 30300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17414 FastRCNN class loss: 0.11592 FastRCNN total loss: 0.29005 L1 loss: 0.0000e+00 L2 loss: 0.79208 Learning rate: 0.02 Mask loss: 0.18128 RPN box loss: 0.02357 RPN score loss: 0.00729 RPN total loss: 0.03086 Total loss: 1.29427 timestamp: 1655032663.4881094 iteration: 30305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14187 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.21303 L1 loss: 0.0000e+00 L2 loss: 0.79197 Learning rate: 0.02 Mask loss: 0.14789 RPN box loss: 0.02771 RPN score loss: 0.00676 RPN total loss: 0.03447 Total loss: 1.18736 timestamp: 1655032666.7484446 iteration: 30310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16774 FastRCNN class loss: 0.09887 FastRCNN total loss: 0.26661 L1 loss: 0.0000e+00 L2 loss: 0.79185 Learning rate: 0.02 Mask loss: 0.18248 RPN box loss: 0.02919 RPN score loss: 0.00342 RPN total loss: 0.03261 Total loss: 1.27356 timestamp: 1655032670.0184577 iteration: 30315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.18274 L1 loss: 0.0000e+00 L2 loss: 0.79174 Learning rate: 0.02 Mask loss: 0.14758 RPN box loss: 0.03679 RPN score loss: 0.00279 RPN total loss: 0.03958 Total loss: 1.16165 timestamp: 1655032673.3699625 iteration: 30320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16491 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 0.79162 Learning rate: 0.02 Mask loss: 0.19483 RPN box loss: 0.01801 RPN score loss: 0.00131 RPN total loss: 0.01932 Total loss: 1.24296 timestamp: 1655032676.633917 iteration: 30325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.04985 FastRCNN total loss: 0.14981 L1 loss: 0.0000e+00 L2 loss: 0.7915 Learning rate: 0.02 Mask loss: 0.15285 RPN box loss: 0.02594 RPN score loss: 0.00133 RPN total loss: 0.02727 Total loss: 1.12143 timestamp: 1655032679.914937 iteration: 30330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13028 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.21785 L1 loss: 0.0000e+00 L2 loss: 0.79138 Learning rate: 0.02 Mask loss: 0.16304 RPN box loss: 0.0324 RPN score loss: 0.0035 RPN total loss: 0.0359 Total loss: 1.20818 timestamp: 1655032683.2320402 iteration: 30335 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17741 FastRCNN class loss: 0.09584 FastRCNN total loss: 0.27325 L1 loss: 0.0000e+00 L2 loss: 0.79126 Learning rate: 0.02 Mask loss: 0.16263 RPN box loss: 0.0629 RPN score loss: 0.02146 RPN total loss: 0.08436 Total loss: 1.3115 timestamp: 1655032686.5615606 iteration: 30340 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13826 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.2099 L1 loss: 0.0000e+00 L2 loss: 0.79113 Learning rate: 0.02 Mask loss: 0.22115 RPN box loss: 0.01748 RPN score loss: 0.00244 RPN total loss: 0.01992 Total loss: 1.24209 timestamp: 1655032689.9073641 iteration: 30345 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1105 FastRCNN class loss: 0.07642 FastRCNN total loss: 0.18692 L1 loss: 0.0000e+00 L2 loss: 0.79101 Learning rate: 0.02 Mask loss: 0.14124 RPN box loss: 0.01878 RPN score loss: 0.00957 RPN total loss: 0.02835 Total loss: 1.14752 timestamp: 1655032693.202871 iteration: 30350 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17227 FastRCNN class loss: 0.11447 FastRCNN total loss: 0.28674 L1 loss: 0.0000e+00 L2 loss: 0.79089 Learning rate: 0.02 Mask loss: 0.2513 RPN box loss: 0.04219 RPN score loss: 0.01675 RPN total loss: 0.05895 Total loss: 1.38788 timestamp: 1655032696.4715772 iteration: 30355 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12107 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.19039 L1 loss: 0.0000e+00 L2 loss: 0.79076 Learning rate: 0.02 Mask loss: 0.10916 RPN box loss: 0.02038 RPN score loss: 0.00635 RPN total loss: 0.02672 Total loss: 1.11703 timestamp: 1655032699.744223 iteration: 30360 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16726 FastRCNN class loss: 0.14102 FastRCNN total loss: 0.30828 L1 loss: 0.0000e+00 L2 loss: 0.79065 Learning rate: 0.02 Mask loss: 0.19305 RPN box loss: 0.04084 RPN score loss: 0.01088 RPN total loss: 0.05172 Total loss: 1.3437 timestamp: 1655032703.0609033 iteration: 30365 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1269 FastRCNN class loss: 0.06976 FastRCNN total loss: 0.19667 L1 loss: 0.0000e+00 L2 loss: 0.79054 Learning rate: 0.02 Mask loss: 0.12017 RPN box loss: 0.03431 RPN score loss: 0.00689 RPN total loss: 0.0412 Total loss: 1.14857 timestamp: 1655032706.3162334 iteration: 30370 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13532 FastRCNN class loss: 0.08474 FastRCNN total loss: 0.22006 L1 loss: 0.0000e+00 L2 loss: 0.7904 Learning rate: 0.02 Mask loss: 0.11664 RPN box loss: 0.02946 RPN score loss: 0.00299 RPN total loss: 0.03245 Total loss: 1.15955 timestamp: 1655032709.6252353 iteration: 30375 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.08948 FastRCNN total loss: 0.20296 L1 loss: 0.0000e+00 L2 loss: 0.79028 Learning rate: 0.02 Mask loss: 0.22329 RPN box loss: 0.03884 RPN score loss: 0.00396 RPN total loss: 0.0428 Total loss: 1.25934 timestamp: 1655032712.8510199 iteration: 30380 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15543 FastRCNN class loss: 0.10658 FastRCNN total loss: 0.26201 L1 loss: 0.0000e+00 L2 loss: 0.79017 Learning rate: 0.02 Mask loss: 0.22734 RPN box loss: 0.03997 RPN score loss: 0.00847 RPN total loss: 0.04844 Total loss: 1.32796 timestamp: 1655032716.0783563 iteration: 30385 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30937 FastRCNN class loss: 0.16858 FastRCNN total loss: 0.47795 L1 loss: 0.0000e+00 L2 loss: 0.79004 Learning rate: 0.02 Mask loss: 0.22576 RPN box loss: 0.054 RPN score loss: 0.05163 RPN total loss: 0.10563 Total loss: 1.59939 timestamp: 1655032719.361237 iteration: 30390 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11518 FastRCNN class loss: 0.05437 FastRCNN total loss: 0.16955 L1 loss: 0.0000e+00 L2 loss: 0.78994 Learning rate: 0.02 Mask loss: 0.32889 RPN box loss: 0.03367 RPN score loss: 0.00512 RPN total loss: 0.03879 Total loss: 1.32716 timestamp: 1655032722.7323308 iteration: 30395 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11822 FastRCNN class loss: 0.12082 FastRCNN total loss: 0.23904 L1 loss: 0.0000e+00 L2 loss: 0.78983 Learning rate: 0.02 Mask loss: 0.14419 RPN box loss: 0.03775 RPN score loss: 0.00767 RPN total loss: 0.04542 Total loss: 1.21848 timestamp: 1655032726.0848384 iteration: 30400 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.1408 L1 loss: 0.0000e+00 L2 loss: 0.7897 Learning rate: 0.02 Mask loss: 0.11922 RPN box loss: 0.01638 RPN score loss: 0.00496 RPN total loss: 0.02134 Total loss: 1.07106 timestamp: 1655032729.3354669 iteration: 30405 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10932 FastRCNN class loss: 0.09215 FastRCNN total loss: 0.20148 L1 loss: 0.0000e+00 L2 loss: 0.78959 Learning rate: 0.02 Mask loss: 0.12977 RPN box loss: 0.00615 RPN score loss: 0.00497 RPN total loss: 0.01111 Total loss: 1.13196 timestamp: 1655032732.684513 iteration: 30410 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20755 FastRCNN class loss: 0.13937 FastRCNN total loss: 0.34693 L1 loss: 0.0000e+00 L2 loss: 0.78947 Learning rate: 0.02 Mask loss: 0.15275 RPN box loss: 0.03254 RPN score loss: 0.00523 RPN total loss: 0.03777 Total loss: 1.32692 timestamp: 1655032736.0290768 iteration: 30415 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11292 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.18478 L1 loss: 0.0000e+00 L2 loss: 0.78934 Learning rate: 0.02 Mask loss: 0.11618 RPN box loss: 0.0134 RPN score loss: 0.00847 RPN total loss: 0.02187 Total loss: 1.11217 timestamp: 1655032739.2659135 iteration: 30420 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12394 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.18256 L1 loss: 0.0000e+00 L2 loss: 0.7892 Learning rate: 0.02 Mask loss: 0.15943 RPN box loss: 0.05129 RPN score loss: 0.00054 RPN total loss: 0.05183 Total loss: 1.18303 timestamp: 1655032742.593337 iteration: 30425 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16073 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.24003 L1 loss: 0.0000e+00 L2 loss: 0.78908 Learning rate: 0.02 Mask loss: 0.19224 RPN box loss: 0.04302 RPN score loss: 0.01356 RPN total loss: 0.05657 Total loss: 1.27793 timestamp: 1655032745.8623807 iteration: 30430 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18726 FastRCNN class loss: 0.08481 FastRCNN total loss: 0.27207 L1 loss: 0.0000e+00 L2 loss: 0.78896 Learning rate: 0.02 Mask loss: 0.20316 RPN box loss: 0.0238 RPN score loss: 0.00755 RPN total loss: 0.03135 Total loss: 1.29553 timestamp: 1655032749.2053564 iteration: 30435 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17845 FastRCNN class loss: 0.09891 FastRCNN total loss: 0.27736 L1 loss: 0.0000e+00 L2 loss: 0.78881 Learning rate: 0.02 Mask loss: 0.21892 RPN box loss: 0.03621 RPN score loss: 0.01057 RPN total loss: 0.04678 Total loss: 1.33186 timestamp: 1655032752.444712 iteration: 30440 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18518 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.26035 L1 loss: 0.0000e+00 L2 loss: 0.78871 Learning rate: 0.02 Mask loss: 0.21047 RPN box loss: 0.01998 RPN score loss: 0.00345 RPN total loss: 0.02343 Total loss: 1.28295 timestamp: 1655032755.7265816 iteration: 30445 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1468 FastRCNN class loss: 0.09791 FastRCNN total loss: 0.24472 L1 loss: 0.0000e+00 L2 loss: 0.78861 Learning rate: 0.02 Mask loss: 0.1673 RPN box loss: 0.02773 RPN score loss: 0.00676 RPN total loss: 0.03449 Total loss: 1.23511 timestamp: 1655032759.0319986 iteration: 30450 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11551 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.18241 L1 loss: 0.0000e+00 L2 loss: 0.7885 Learning rate: 0.02 Mask loss: 0.18456 RPN box loss: 0.02142 RPN score loss: 0.00997 RPN total loss: 0.03138 Total loss: 1.18685 timestamp: 1655032762.3053381 iteration: 30455 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17275 FastRCNN class loss: 0.18888 FastRCNN total loss: 0.36163 L1 loss: 0.0000e+00 L2 loss: 0.78837 Learning rate: 0.02 Mask loss: 0.20577 RPN box loss: 0.04645 RPN score loss: 0.01577 RPN total loss: 0.06222 Total loss: 1.41799 timestamp: 1655032765.631421 iteration: 30460 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08255 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.13874 L1 loss: 0.0000e+00 L2 loss: 0.78825 Learning rate: 0.02 Mask loss: 0.14101 RPN box loss: 0.06146 RPN score loss: 0.00829 RPN total loss: 0.06976 Total loss: 1.13776 timestamp: 1655032768.918309 iteration: 30465 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13546 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.18565 L1 loss: 0.0000e+00 L2 loss: 0.78812 Learning rate: 0.02 Mask loss: 0.12435 RPN box loss: 0.00273 RPN score loss: 0.0015 RPN total loss: 0.00424 Total loss: 1.10236 timestamp: 1655032772.2693546 iteration: 30470 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0995 FastRCNN class loss: 0.10392 FastRCNN total loss: 0.20342 L1 loss: 0.0000e+00 L2 loss: 0.78801 Learning rate: 0.02 Mask loss: 0.16436 RPN box loss: 0.05958 RPN score loss: 0.02879 RPN total loss: 0.08837 Total loss: 1.24416 timestamp: 1655032775.4658046 iteration: 30475 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20454 FastRCNN class loss: 0.07254 FastRCNN total loss: 0.27707 L1 loss: 0.0000e+00 L2 loss: 0.78787 Learning rate: 0.02 Mask loss: 0.17168 RPN box loss: 0.02995 RPN score loss: 0.0066 RPN total loss: 0.03655 Total loss: 1.27317 timestamp: 1655032778.769744 iteration: 30480 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14074 FastRCNN class loss: 0.12065 FastRCNN total loss: 0.26139 L1 loss: 0.0000e+00 L2 loss: 0.78777 Learning rate: 0.02 Mask loss: 0.17467 RPN box loss: 0.04349 RPN score loss: 0.00745 RPN total loss: 0.05094 Total loss: 1.27477 timestamp: 1655032782.0760276 iteration: 30485 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09292 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.17281 L1 loss: 0.0000e+00 L2 loss: 0.78767 Learning rate: 0.02 Mask loss: 0.15159 RPN box loss: 0.05459 RPN score loss: 0.00757 RPN total loss: 0.06216 Total loss: 1.17423 timestamp: 1655032785.3739254 iteration: 30490 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.04536 FastRCNN total loss: 0.11939 L1 loss: 0.0000e+00 L2 loss: 0.78754 Learning rate: 0.02 Mask loss: 0.14289 RPN box loss: 0.05055 RPN score loss: 0.00821 RPN total loss: 0.05876 Total loss: 1.10859 timestamp: 1655032788.593231 iteration: 30495 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16089 FastRCNN class loss: 0.08688 FastRCNN total loss: 0.24777 L1 loss: 0.0000e+00 L2 loss: 0.78746 Learning rate: 0.02 Mask loss: 0.19207 RPN box loss: 0.02748 RPN score loss: 0.00608 RPN total loss: 0.03356 Total loss: 1.26085 timestamp: 1655032791.900318 iteration: 30500 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20552 FastRCNN class loss: 0.0799 FastRCNN total loss: 0.28542 L1 loss: 0.0000e+00 L2 loss: 0.78735 Learning rate: 0.02 Mask loss: 0.17257 RPN box loss: 0.01221 RPN score loss: 0.0036 RPN total loss: 0.0158 Total loss: 1.26114 timestamp: 1655032795.146969 iteration: 30505 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09239 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.14562 L1 loss: 0.0000e+00 L2 loss: 0.78722 Learning rate: 0.02 Mask loss: 0.14205 RPN box loss: 0.00364 RPN score loss: 0.0026 RPN total loss: 0.00625 Total loss: 1.08114 timestamp: 1655032798.3883104 iteration: 30510 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0949 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.16446 L1 loss: 0.0000e+00 L2 loss: 0.78711 Learning rate: 0.02 Mask loss: 0.16103 RPN box loss: 0.03195 RPN score loss: 0.00478 RPN total loss: 0.03673 Total loss: 1.14933 timestamp: 1655032801.6054237 iteration: 30515 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14578 FastRCNN class loss: 0.10753 FastRCNN total loss: 0.25331 L1 loss: 0.0000e+00 L2 loss: 0.78697 Learning rate: 0.02 Mask loss: 0.16637 RPN box loss: 0.03385 RPN score loss: 0.01098 RPN total loss: 0.04482 Total loss: 1.25149 timestamp: 1655032804.8998263 iteration: 30520 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08344 FastRCNN class loss: 0.04371 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.78684 Learning rate: 0.02 Mask loss: 0.13826 RPN box loss: 0.02224 RPN score loss: 0.0051 RPN total loss: 0.02734 Total loss: 1.07959 timestamp: 1655032808.2025924 iteration: 30525 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13864 FastRCNN class loss: 0.07774 FastRCNN total loss: 0.21637 L1 loss: 0.0000e+00 L2 loss: 0.78671 Learning rate: 0.02 Mask loss: 0.14104 RPN box loss: 0.02462 RPN score loss: 0.00879 RPN total loss: 0.03342 Total loss: 1.17754 timestamp: 1655032811.5037518 iteration: 30530 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13678 FastRCNN class loss: 0.09602 FastRCNN total loss: 0.2328 L1 loss: 0.0000e+00 L2 loss: 0.7866 Learning rate: 0.02 Mask loss: 0.2179 RPN box loss: 0.04752 RPN score loss: 0.00466 RPN total loss: 0.05218 Total loss: 1.28947 timestamp: 1655032814.8381195 iteration: 30535 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13227 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.20769 L1 loss: 0.0000e+00 L2 loss: 0.78649 Learning rate: 0.02 Mask loss: 0.19027 RPN box loss: 0.03046 RPN score loss: 0.00691 RPN total loss: 0.03737 Total loss: 1.22182 timestamp: 1655032818.073371 iteration: 30540 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08359 FastRCNN class loss: 0.04477 FastRCNN total loss: 0.12836 L1 loss: 0.0000e+00 L2 loss: 0.78636 Learning rate: 0.02 Mask loss: 0.0742 RPN box loss: 0.00733 RPN score loss: 0.00261 RPN total loss: 0.00994 Total loss: 0.99887 timestamp: 1655032821.392095 iteration: 30545 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18675 FastRCNN class loss: 0.1068 FastRCNN total loss: 0.29355 L1 loss: 0.0000e+00 L2 loss: 0.7862 Learning rate: 0.02 Mask loss: 0.17293 RPN box loss: 0.05938 RPN score loss: 0.02909 RPN total loss: 0.08847 Total loss: 1.34115 timestamp: 1655032824.6935067 iteration: 30550 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13951 FastRCNN class loss: 0.10198 FastRCNN total loss: 0.24148 L1 loss: 0.0000e+00 L2 loss: 0.78609 Learning rate: 0.02 Mask loss: 0.16506 RPN box loss: 0.02244 RPN score loss: 0.00946 RPN total loss: 0.0319 Total loss: 1.22453 timestamp: 1655032827.977979 iteration: 30555 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09475 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.1686 L1 loss: 0.0000e+00 L2 loss: 0.78601 Learning rate: 0.02 Mask loss: 0.1833 RPN box loss: 0.03526 RPN score loss: 0.007 RPN total loss: 0.04227 Total loss: 1.18018 timestamp: 1655032831.2918363 iteration: 30560 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21283 FastRCNN class loss: 0.11082 FastRCNN total loss: 0.32365 L1 loss: 0.0000e+00 L2 loss: 0.7859 Learning rate: 0.02 Mask loss: 0.21096 RPN box loss: 0.02922 RPN score loss: 0.01728 RPN total loss: 0.04649 Total loss: 1.367 timestamp: 1655032834.5307453 iteration: 30565 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05184 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.11774 L1 loss: 0.0000e+00 L2 loss: 0.78579 Learning rate: 0.02 Mask loss: 0.17297 RPN box loss: 0.01443 RPN score loss: 0.01276 RPN total loss: 0.02719 Total loss: 1.10369 timestamp: 1655032837.7506835 iteration: 30570 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13431 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.20396 L1 loss: 0.0000e+00 L2 loss: 0.78568 Learning rate: 0.02 Mask loss: 0.28716 RPN box loss: 0.02113 RPN score loss: 0.01235 RPN total loss: 0.03348 Total loss: 1.31028 timestamp: 1655032841.0322626 iteration: 30575 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10538 FastRCNN class loss: 0.04341 FastRCNN total loss: 0.14879 L1 loss: 0.0000e+00 L2 loss: 0.78556 Learning rate: 0.02 Mask loss: 0.15556 RPN box loss: 0.04134 RPN score loss: 0.00598 RPN total loss: 0.04732 Total loss: 1.13723 timestamp: 1655032844.2163453 iteration: 30580 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13645 FastRCNN class loss: 0.13256 FastRCNN total loss: 0.26901 L1 loss: 0.0000e+00 L2 loss: 0.78544 Learning rate: 0.02 Mask loss: 0.14513 RPN box loss: 0.02106 RPN score loss: 0.00646 RPN total loss: 0.02752 Total loss: 1.22711 timestamp: 1655032847.4277303 iteration: 30585 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19303 FastRCNN class loss: 0.1193 FastRCNN total loss: 0.31232 L1 loss: 0.0000e+00 L2 loss: 0.78531 Learning rate: 0.02 Mask loss: 0.28546 RPN box loss: 0.0138 RPN score loss: 0.00997 RPN total loss: 0.02377 Total loss: 1.40686 timestamp: 1655032850.7369845 iteration: 30590 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12892 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.2032 L1 loss: 0.0000e+00 L2 loss: 0.78518 Learning rate: 0.02 Mask loss: 0.17929 RPN box loss: 0.02344 RPN score loss: 0.00386 RPN total loss: 0.0273 Total loss: 1.19497 timestamp: 1655032853.9663947 iteration: 30595 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17962 FastRCNN class loss: 0.08467 FastRCNN total loss: 0.2643 L1 loss: 0.0000e+00 L2 loss: 0.78509 Learning rate: 0.02 Mask loss: 0.14445 RPN box loss: 0.02884 RPN score loss: 0.00989 RPN total loss: 0.03874 Total loss: 1.23257 timestamp: 1655032857.187054 iteration: 30600 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24109 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.32262 L1 loss: 0.0000e+00 L2 loss: 0.78497 Learning rate: 0.02 Mask loss: 0.13107 RPN box loss: 0.03836 RPN score loss: 0.00908 RPN total loss: 0.04744 Total loss: 1.2861 timestamp: 1655032860.4253864 iteration: 30605 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18432 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.26295 L1 loss: 0.0000e+00 L2 loss: 0.78487 Learning rate: 0.02 Mask loss: 0.12064 RPN box loss: 0.04003 RPN score loss: 0.01092 RPN total loss: 0.05095 Total loss: 1.21941 timestamp: 1655032863.6476312 iteration: 30610 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14565 FastRCNN class loss: 0.0845 FastRCNN total loss: 0.23015 L1 loss: 0.0000e+00 L2 loss: 0.78474 Learning rate: 0.02 Mask loss: 0.14441 RPN box loss: 0.05935 RPN score loss: 0.0059 RPN total loss: 0.06525 Total loss: 1.22455 timestamp: 1655032867.0367827 iteration: 30615 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19079 FastRCNN class loss: 0.09696 FastRCNN total loss: 0.28775 L1 loss: 0.0000e+00 L2 loss: 0.78462 Learning rate: 0.02 Mask loss: 0.22022 RPN box loss: 0.03599 RPN score loss: 0.00573 RPN total loss: 0.04171 Total loss: 1.3343 timestamp: 1655032870.2644498 iteration: 30620 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13463 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.21896 L1 loss: 0.0000e+00 L2 loss: 0.78449 Learning rate: 0.02 Mask loss: 0.16522 RPN box loss: 0.01544 RPN score loss: 0.00429 RPN total loss: 0.01973 Total loss: 1.1884 timestamp: 1655032873.533408 iteration: 30625 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12436 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.20242 L1 loss: 0.0000e+00 L2 loss: 0.78436 Learning rate: 0.02 Mask loss: 0.14017 RPN box loss: 0.03653 RPN score loss: 0.00307 RPN total loss: 0.0396 Total loss: 1.16655 timestamp: 1655032876.8342772 iteration: 30630 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08852 FastRCNN class loss: 0.05449 FastRCNN total loss: 0.14301 L1 loss: 0.0000e+00 L2 loss: 0.78426 Learning rate: 0.02 Mask loss: 0.10996 RPN box loss: 0.07279 RPN score loss: 0.00893 RPN total loss: 0.08172 Total loss: 1.11896 timestamp: 1655032880.0387475 iteration: 30635 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13161 FastRCNN class loss: 0.07378 FastRCNN total loss: 0.20539 L1 loss: 0.0000e+00 L2 loss: 0.78416 Learning rate: 0.02 Mask loss: 0.13257 RPN box loss: 0.01352 RPN score loss: 0.00234 RPN total loss: 0.01586 Total loss: 1.13799 timestamp: 1655032883.3497014 iteration: 30640 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18564 FastRCNN class loss: 0.11716 FastRCNN total loss: 0.3028 L1 loss: 0.0000e+00 L2 loss: 0.78407 Learning rate: 0.02 Mask loss: 0.1865 RPN box loss: 0.06047 RPN score loss: 0.00397 RPN total loss: 0.06444 Total loss: 1.33781 timestamp: 1655032886.5971437 iteration: 30645 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17215 FastRCNN class loss: 0.0979 FastRCNN total loss: 0.27006 L1 loss: 0.0000e+00 L2 loss: 0.78398 Learning rate: 0.02 Mask loss: 0.18647 RPN box loss: 0.01938 RPN score loss: 0.0052 RPN total loss: 0.02458 Total loss: 1.26508 timestamp: 1655032889.8350437 iteration: 30650 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07674 FastRCNN class loss: 0.05296 FastRCNN total loss: 0.1297 L1 loss: 0.0000e+00 L2 loss: 0.78382 Learning rate: 0.02 Mask loss: 0.1503 RPN box loss: 0.04281 RPN score loss: 0.00924 RPN total loss: 0.05205 Total loss: 1.11588 timestamp: 1655032893.1099784 iteration: 30655 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12529 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.1898 L1 loss: 0.0000e+00 L2 loss: 0.7837 Learning rate: 0.02 Mask loss: 0.14509 RPN box loss: 0.01485 RPN score loss: 0.00234 RPN total loss: 0.01719 Total loss: 1.13579 timestamp: 1655032896.4334712 iteration: 30660 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1334 FastRCNN class loss: 0.09325 FastRCNN total loss: 0.22664 L1 loss: 0.0000e+00 L2 loss: 0.78363 Learning rate: 0.02 Mask loss: 0.19411 RPN box loss: 0.0548 RPN score loss: 0.00604 RPN total loss: 0.06084 Total loss: 1.26522 timestamp: 1655032899.722767 iteration: 30665 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13584 FastRCNN class loss: 0.06941 FastRCNN total loss: 0.20525 L1 loss: 0.0000e+00 L2 loss: 0.78351 Learning rate: 0.02 Mask loss: 0.21074 RPN box loss: 0.01326 RPN score loss: 0.0038 RPN total loss: 0.01706 Total loss: 1.21656 timestamp: 1655032903.0200906 iteration: 30670 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15659 FastRCNN class loss: 0.1091 FastRCNN total loss: 0.26569 L1 loss: 0.0000e+00 L2 loss: 0.78335 Learning rate: 0.02 Mask loss: 0.14469 RPN box loss: 0.0306 RPN score loss: 0.00418 RPN total loss: 0.03479 Total loss: 1.22852 timestamp: 1655032906.267792 iteration: 30675 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1599 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.22641 L1 loss: 0.0000e+00 L2 loss: 0.78325 Learning rate: 0.02 Mask loss: 0.21167 RPN box loss: 0.00348 RPN score loss: 0.0015 RPN total loss: 0.00498 Total loss: 1.22631 timestamp: 1655032909.5135 iteration: 30680 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16907 FastRCNN class loss: 0.07672 FastRCNN total loss: 0.24579 L1 loss: 0.0000e+00 L2 loss: 0.78315 Learning rate: 0.02 Mask loss: 0.10634 RPN box loss: 0.03161 RPN score loss: 0.0041 RPN total loss: 0.03571 Total loss: 1.17099 timestamp: 1655032912.7541478 iteration: 30685 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16236 FastRCNN class loss: 0.06895 FastRCNN total loss: 0.2313 L1 loss: 0.0000e+00 L2 loss: 0.78303 Learning rate: 0.02 Mask loss: 0.17549 RPN box loss: 0.05468 RPN score loss: 0.00632 RPN total loss: 0.061 Total loss: 1.25082 timestamp: 1655032916.03216 iteration: 30690 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19122 FastRCNN class loss: 0.12116 FastRCNN total loss: 0.31238 L1 loss: 0.0000e+00 L2 loss: 0.78291 Learning rate: 0.02 Mask loss: 0.22564 RPN box loss: 0.02584 RPN score loss: 0.00629 RPN total loss: 0.03213 Total loss: 1.35307 timestamp: 1655032919.308297 iteration: 30695 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19092 FastRCNN class loss: 0.11761 FastRCNN total loss: 0.30852 L1 loss: 0.0000e+00 L2 loss: 0.7828 Learning rate: 0.02 Mask loss: 0.28234 RPN box loss: 0.04753 RPN score loss: 0.01224 RPN total loss: 0.05976 Total loss: 1.43343 timestamp: 1655032922.592666 iteration: 30700 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19859 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.27971 L1 loss: 0.0000e+00 L2 loss: 0.78268 Learning rate: 0.02 Mask loss: 0.19754 RPN box loss: 0.02036 RPN score loss: 0.00459 RPN total loss: 0.02495 Total loss: 1.28488 timestamp: 1655032925.865324 iteration: 30705 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09668 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.16522 L1 loss: 0.0000e+00 L2 loss: 0.78257 Learning rate: 0.02 Mask loss: 0.09265 RPN box loss: 0.00506 RPN score loss: 0.00705 RPN total loss: 0.01211 Total loss: 1.05255 timestamp: 1655032929.1267369 iteration: 30710 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10103 FastRCNN class loss: 0.0518 FastRCNN total loss: 0.15283 L1 loss: 0.0000e+00 L2 loss: 0.78244 Learning rate: 0.02 Mask loss: 0.14617 RPN box loss: 0.01761 RPN score loss: 0.00314 RPN total loss: 0.02074 Total loss: 1.10219 timestamp: 1655032932.3731093 iteration: 30715 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11698 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.18257 L1 loss: 0.0000e+00 L2 loss: 0.78233 Learning rate: 0.02 Mask loss: 0.12767 RPN box loss: 0.02761 RPN score loss: 0.00479 RPN total loss: 0.0324 Total loss: 1.12497 timestamp: 1655032935.6137877 iteration: 30720 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.27942 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.35888 L1 loss: 0.0000e+00 L2 loss: 0.78225 Learning rate: 0.02 Mask loss: 0.12127 RPN box loss: 0.0505 RPN score loss: 0.01214 RPN total loss: 0.06264 Total loss: 1.32504 timestamp: 1655032938.9186337 iteration: 30725 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09647 FastRCNN class loss: 0.04654 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.78213 Learning rate: 0.02 Mask loss: 0.15724 RPN box loss: 0.01999 RPN score loss: 0.00285 RPN total loss: 0.02284 Total loss: 1.10522 timestamp: 1655032942.1778958 iteration: 30730 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14252 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.2042 L1 loss: 0.0000e+00 L2 loss: 0.78198 Learning rate: 0.02 Mask loss: 0.15418 RPN box loss: 0.02452 RPN score loss: 0.00625 RPN total loss: 0.03077 Total loss: 1.17113 timestamp: 1655032945.4892778 iteration: 30735 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11723 FastRCNN class loss: 0.0755 FastRCNN total loss: 0.19272 L1 loss: 0.0000e+00 L2 loss: 0.78185 Learning rate: 0.02 Mask loss: 0.10256 RPN box loss: 0.02341 RPN score loss: 0.00578 RPN total loss: 0.0292 Total loss: 1.10633 timestamp: 1655032948.813945 iteration: 30740 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09459 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.14252 L1 loss: 0.0000e+00 L2 loss: 0.78173 Learning rate: 0.02 Mask loss: 0.10749 RPN box loss: 0.02728 RPN score loss: 0.00474 RPN total loss: 0.03202 Total loss: 1.06376 timestamp: 1655032952.054949 iteration: 30745 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09447 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.16478 L1 loss: 0.0000e+00 L2 loss: 0.78163 Learning rate: 0.02 Mask loss: 0.15914 RPN box loss: 0.0332 RPN score loss: 0.00134 RPN total loss: 0.03454 Total loss: 1.14009 timestamp: 1655032955.348156 iteration: 30750 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20713 FastRCNN class loss: 0.13969 FastRCNN total loss: 0.34682 L1 loss: 0.0000e+00 L2 loss: 0.78153 Learning rate: 0.02 Mask loss: 0.19054 RPN box loss: 0.03901 RPN score loss: 0.00976 RPN total loss: 0.04877 Total loss: 1.36765 timestamp: 1655032958.596885 iteration: 30755 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10011 FastRCNN class loss: 0.09837 FastRCNN total loss: 0.19848 L1 loss: 0.0000e+00 L2 loss: 0.7814 Learning rate: 0.02 Mask loss: 0.1658 RPN box loss: 0.03242 RPN score loss: 0.00458 RPN total loss: 0.037 Total loss: 1.18267 timestamp: 1655032961.8334105 iteration: 30760 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12948 FastRCNN class loss: 0.07191 FastRCNN total loss: 0.20139 L1 loss: 0.0000e+00 L2 loss: 0.78126 Learning rate: 0.02 Mask loss: 0.15147 RPN box loss: 0.02635 RPN score loss: 0.00671 RPN total loss: 0.03306 Total loss: 1.16718 timestamp: 1655032965.0664275 iteration: 30765 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25807 FastRCNN class loss: 0.09375 FastRCNN total loss: 0.35183 L1 loss: 0.0000e+00 L2 loss: 0.78114 Learning rate: 0.02 Mask loss: 0.21208 RPN box loss: 0.03922 RPN score loss: 0.00468 RPN total loss: 0.04389 Total loss: 1.38894 timestamp: 1655032968.385728 iteration: 30770 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22358 FastRCNN class loss: 0.09684 FastRCNN total loss: 0.32043 L1 loss: 0.0000e+00 L2 loss: 0.78102 Learning rate: 0.02 Mask loss: 0.17904 RPN box loss: 0.02505 RPN score loss: 0.00397 RPN total loss: 0.02902 Total loss: 1.30951 timestamp: 1655032971.6798248 iteration: 30775 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11301 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.18307 L1 loss: 0.0000e+00 L2 loss: 0.78092 Learning rate: 0.02 Mask loss: 0.14431 RPN box loss: 0.02519 RPN score loss: 0.00833 RPN total loss: 0.03352 Total loss: 1.14181 timestamp: 1655032975.0075927 iteration: 30780 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0492 FastRCNN class loss: 0.03284 FastRCNN total loss: 0.08204 L1 loss: 0.0000e+00 L2 loss: 0.78079 Learning rate: 0.02 Mask loss: 0.19209 RPN box loss: 0.01607 RPN score loss: 0.00452 RPN total loss: 0.02059 Total loss: 1.07551 timestamp: 1655032978.3687153 iteration: 30785 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17028 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.25443 L1 loss: 0.0000e+00 L2 loss: 0.78067 Learning rate: 0.02 Mask loss: 0.19391 RPN box loss: 0.0499 RPN score loss: 0.01857 RPN total loss: 0.06848 Total loss: 1.29749 timestamp: 1655032981.5990834 iteration: 30790 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10379 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.18656 L1 loss: 0.0000e+00 L2 loss: 0.78054 Learning rate: 0.02 Mask loss: 0.13846 RPN box loss: 0.01163 RPN score loss: 0.00622 RPN total loss: 0.01785 Total loss: 1.1234 timestamp: 1655032984.8201394 iteration: 30795 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07282 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.15761 L1 loss: 0.0000e+00 L2 loss: 0.78042 Learning rate: 0.02 Mask loss: 0.16333 RPN box loss: 0.02519 RPN score loss: 0.00268 RPN total loss: 0.02787 Total loss: 1.12923 timestamp: 1655032988.1228018 iteration: 30800 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21939 FastRCNN class loss: 0.06986 FastRCNN total loss: 0.28925 L1 loss: 0.0000e+00 L2 loss: 0.78031 Learning rate: 0.02 Mask loss: 0.18822 RPN box loss: 0.02213 RPN score loss: 0.00535 RPN total loss: 0.02748 Total loss: 1.28527 timestamp: 1655032991.3782203 iteration: 30805 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19735 FastRCNN class loss: 0.08783 FastRCNN total loss: 0.28518 L1 loss: 0.0000e+00 L2 loss: 0.78019 Learning rate: 0.02 Mask loss: 0.25238 RPN box loss: 0.03569 RPN score loss: 0.00467 RPN total loss: 0.04036 Total loss: 1.35811 timestamp: 1655032994.719751 iteration: 30810 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1024 FastRCNN class loss: 0.0425 FastRCNN total loss: 0.1449 L1 loss: 0.0000e+00 L2 loss: 0.78007 Learning rate: 0.02 Mask loss: 0.17513 RPN box loss: 0.00532 RPN score loss: 0.00209 RPN total loss: 0.00741 Total loss: 1.10751 timestamp: 1655032997.9953625 iteration: 30815 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09216 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.16245 L1 loss: 0.0000e+00 L2 loss: 0.77995 Learning rate: 0.02 Mask loss: 0.18182 RPN box loss: 0.06176 RPN score loss: 0.01053 RPN total loss: 0.07228 Total loss: 1.19651 timestamp: 1655033001.3163476 iteration: 30820 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21841 FastRCNN class loss: 0.12315 FastRCNN total loss: 0.34156 L1 loss: 0.0000e+00 L2 loss: 0.77983 Learning rate: 0.02 Mask loss: 0.20393 RPN box loss: 0.01196 RPN score loss: 0.00914 RPN total loss: 0.0211 Total loss: 1.34642 timestamp: 1655033004.6002212 iteration: 30825 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15915 FastRCNN class loss: 0.07764 FastRCNN total loss: 0.2368 L1 loss: 0.0000e+00 L2 loss: 0.77973 Learning rate: 0.02 Mask loss: 0.17872 RPN box loss: 0.03818 RPN score loss: 0.01315 RPN total loss: 0.05133 Total loss: 1.24657 timestamp: 1655033007.894892 iteration: 30830 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12084 FastRCNN class loss: 0.12151 FastRCNN total loss: 0.24235 L1 loss: 0.0000e+00 L2 loss: 0.7796 Learning rate: 0.02 Mask loss: 0.17151 RPN box loss: 0.0189 RPN score loss: 0.00682 RPN total loss: 0.02572 Total loss: 1.21916 timestamp: 1655033011.1180217 iteration: 30835 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.19202 L1 loss: 0.0000e+00 L2 loss: 0.77946 Learning rate: 0.02 Mask loss: 0.12211 RPN box loss: 0.02954 RPN score loss: 0.00798 RPN total loss: 0.03753 Total loss: 1.13112 timestamp: 1655033014.4200554 iteration: 30840 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13491 FastRCNN class loss: 0.0749 FastRCNN total loss: 0.20981 L1 loss: 0.0000e+00 L2 loss: 0.77934 Learning rate: 0.02 Mask loss: 0.15202 RPN box loss: 0.01294 RPN score loss: 0.00836 RPN total loss: 0.0213 Total loss: 1.16246 timestamp: 1655033017.7373216 iteration: 30845 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07451 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.1576 L1 loss: 0.0000e+00 L2 loss: 0.77923 Learning rate: 0.02 Mask loss: 0.10998 RPN box loss: 0.01423 RPN score loss: 0.00269 RPN total loss: 0.01692 Total loss: 1.06374 timestamp: 1655033021.0351284 iteration: 30850 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09083 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.16748 L1 loss: 0.0000e+00 L2 loss: 0.77911 Learning rate: 0.02 Mask loss: 0.11617 RPN box loss: 0.03672 RPN score loss: 0.00409 RPN total loss: 0.04081 Total loss: 1.10357 timestamp: 1655033024.3193684 iteration: 30855 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13486 FastRCNN class loss: 0.09714 FastRCNN total loss: 0.232 L1 loss: 0.0000e+00 L2 loss: 0.77899 Learning rate: 0.02 Mask loss: 0.13299 RPN box loss: 0.01984 RPN score loss: 0.00874 RPN total loss: 0.02858 Total loss: 1.17257 timestamp: 1655033027.611872 iteration: 30860 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10116 FastRCNN class loss: 0.09472 FastRCNN total loss: 0.19587 L1 loss: 0.0000e+00 L2 loss: 0.77886 Learning rate: 0.02 Mask loss: 0.16322 RPN box loss: 0.02357 RPN score loss: 0.0117 RPN total loss: 0.03526 Total loss: 1.17322 timestamp: 1655033030.837543 iteration: 30865 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12376 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.20296 L1 loss: 0.0000e+00 L2 loss: 0.77875 Learning rate: 0.02 Mask loss: 0.17793 RPN box loss: 0.02487 RPN score loss: 0.00345 RPN total loss: 0.02832 Total loss: 1.18796 timestamp: 1655033034.121939 iteration: 30870 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17225 FastRCNN class loss: 0.10873 FastRCNN total loss: 0.28098 L1 loss: 0.0000e+00 L2 loss: 0.77865 Learning rate: 0.02 Mask loss: 0.16561 RPN box loss: 0.0969 RPN score loss: 0.01371 RPN total loss: 0.11061 Total loss: 1.33585 timestamp: 1655033037.3842192 iteration: 30875 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17039 FastRCNN class loss: 0.1303 FastRCNN total loss: 0.30069 L1 loss: 0.0000e+00 L2 loss: 0.77854 Learning rate: 0.02 Mask loss: 0.19401 RPN box loss: 0.02496 RPN score loss: 0.00787 RPN total loss: 0.03283 Total loss: 1.30606 timestamp: 1655033040.6590834 iteration: 30880 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17545 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.26393 L1 loss: 0.0000e+00 L2 loss: 0.77841 Learning rate: 0.02 Mask loss: 0.2478 RPN box loss: 0.05649 RPN score loss: 0.02461 RPN total loss: 0.0811 Total loss: 1.37124 timestamp: 1655033043.9620032 iteration: 30885 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11045 FastRCNN class loss: 0.09259 FastRCNN total loss: 0.20304 L1 loss: 0.0000e+00 L2 loss: 0.77828 Learning rate: 0.02 Mask loss: 0.13076 RPN box loss: 0.03087 RPN score loss: 0.0127 RPN total loss: 0.04357 Total loss: 1.15564 timestamp: 1655033047.2365983 iteration: 30890 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19721 FastRCNN class loss: 0.06089 FastRCNN total loss: 0.25809 L1 loss: 0.0000e+00 L2 loss: 0.77815 Learning rate: 0.02 Mask loss: 0.24807 RPN box loss: 0.04898 RPN score loss: 0.01654 RPN total loss: 0.06552 Total loss: 1.34983 timestamp: 1655033050.486676 iteration: 30895 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13317 FastRCNN class loss: 0.05283 FastRCNN total loss: 0.18601 L1 loss: 0.0000e+00 L2 loss: 0.77805 Learning rate: 0.02 Mask loss: 0.10066 RPN box loss: 0.03591 RPN score loss: 0.00492 RPN total loss: 0.04084 Total loss: 1.10555 timestamp: 1655033053.7008417 iteration: 30900 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08581 FastRCNN class loss: 0.0917 FastRCNN total loss: 0.17751 L1 loss: 0.0000e+00 L2 loss: 0.77796 Learning rate: 0.02 Mask loss: 0.20747 RPN box loss: 0.03355 RPN score loss: 0.02733 RPN total loss: 0.06088 Total loss: 1.22382 timestamp: 1655033056.891297 iteration: 30905 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08962 FastRCNN class loss: 0.04334 FastRCNN total loss: 0.13296 L1 loss: 0.0000e+00 L2 loss: 0.77782 Learning rate: 0.02 Mask loss: 0.10532 RPN box loss: 0.01798 RPN score loss: 0.00725 RPN total loss: 0.02522 Total loss: 1.04133 timestamp: 1655033060.1829 iteration: 30910 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14206 FastRCNN class loss: 0.09846 FastRCNN total loss: 0.24052 L1 loss: 0.0000e+00 L2 loss: 0.7777 Learning rate: 0.02 Mask loss: 0.20261 RPN box loss: 0.05733 RPN score loss: 0.01805 RPN total loss: 0.07538 Total loss: 1.2962 timestamp: 1655033063.5016475 iteration: 30915 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12858 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.21083 L1 loss: 0.0000e+00 L2 loss: 0.77756 Learning rate: 0.02 Mask loss: 0.11452 RPN box loss: 0.07265 RPN score loss: 0.01134 RPN total loss: 0.08399 Total loss: 1.18691 timestamp: 1655033066.7512684 iteration: 30920 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12958 FastRCNN class loss: 0.07844 FastRCNN total loss: 0.20802 L1 loss: 0.0000e+00 L2 loss: 0.77747 Learning rate: 0.02 Mask loss: 0.14253 RPN box loss: 0.01767 RPN score loss: 0.00546 RPN total loss: 0.02313 Total loss: 1.15115 timestamp: 1655033070.0703049 iteration: 30925 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06736 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.12787 L1 loss: 0.0000e+00 L2 loss: 0.77738 Learning rate: 0.02 Mask loss: 0.14548 RPN box loss: 0.01337 RPN score loss: 0.00212 RPN total loss: 0.01549 Total loss: 1.06621 timestamp: 1655033073.3563697 iteration: 30930 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13434 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.19985 L1 loss: 0.0000e+00 L2 loss: 0.77726 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.04423 RPN score loss: 0.00924 RPN total loss: 0.05347 Total loss: 1.17353 timestamp: 1655033076.6331525 iteration: 30935 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23213 FastRCNN class loss: 0.12952 FastRCNN total loss: 0.36165 L1 loss: 0.0000e+00 L2 loss: 0.7771 Learning rate: 0.02 Mask loss: 0.22462 RPN box loss: 0.01339 RPN score loss: 0.0114 RPN total loss: 0.02479 Total loss: 1.38817 timestamp: 1655033079.9678674 iteration: 30940 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15893 FastRCNN class loss: 0.08596 FastRCNN total loss: 0.24489 L1 loss: 0.0000e+00 L2 loss: 0.777 Learning rate: 0.02 Mask loss: 0.14741 RPN box loss: 0.01431 RPN score loss: 0.00488 RPN total loss: 0.01919 Total loss: 1.18849 timestamp: 1655033083.259972 iteration: 30945 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13061 FastRCNN class loss: 0.06365 FastRCNN total loss: 0.19427 L1 loss: 0.0000e+00 L2 loss: 0.7769 Learning rate: 0.02 Mask loss: 0.17035 RPN box loss: 0.00622 RPN score loss: 0.00754 RPN total loss: 0.01376 Total loss: 1.15528 timestamp: 1655033086.520434 iteration: 30950 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1776 FastRCNN class loss: 0.12131 FastRCNN total loss: 0.29891 L1 loss: 0.0000e+00 L2 loss: 0.77677 Learning rate: 0.02 Mask loss: 0.19273 RPN box loss: 0.04105 RPN score loss: 0.02675 RPN total loss: 0.0678 Total loss: 1.33622 timestamp: 1655033089.8080025 iteration: 30955 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1327 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.22028 L1 loss: 0.0000e+00 L2 loss: 0.77667 Learning rate: 0.02 Mask loss: 0.10613 RPN box loss: 0.06306 RPN score loss: 0.01241 RPN total loss: 0.07547 Total loss: 1.17855 timestamp: 1655033093.0914147 iteration: 30960 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16903 FastRCNN class loss: 0.09067 FastRCNN total loss: 0.2597 L1 loss: 0.0000e+00 L2 loss: 0.77656 Learning rate: 0.02 Mask loss: 0.15523 RPN box loss: 0.03147 RPN score loss: 0.01182 RPN total loss: 0.04329 Total loss: 1.23477 timestamp: 1655033096.392608 iteration: 30965 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.07943 FastRCNN total loss: 0.19378 L1 loss: 0.0000e+00 L2 loss: 0.77643 Learning rate: 0.02 Mask loss: 0.18631 RPN box loss: 0.03899 RPN score loss: 0.00743 RPN total loss: 0.04642 Total loss: 1.20294 timestamp: 1655033099.7023194 iteration: 30970 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18231 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.26566 L1 loss: 0.0000e+00 L2 loss: 0.77633 Learning rate: 0.02 Mask loss: 0.18495 RPN box loss: 0.03129 RPN score loss: 0.00973 RPN total loss: 0.04102 Total loss: 1.26796 timestamp: 1655033102.9729283 iteration: 30975 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11074 FastRCNN class loss: 0.08697 FastRCNN total loss: 0.19771 L1 loss: 0.0000e+00 L2 loss: 0.77622 Learning rate: 0.02 Mask loss: 0.13651 RPN box loss: 0.03756 RPN score loss: 0.00579 RPN total loss: 0.04335 Total loss: 1.15379 timestamp: 1655033106.351534 iteration: 30980 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13729 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.21846 L1 loss: 0.0000e+00 L2 loss: 0.77609 Learning rate: 0.02 Mask loss: 0.12516 RPN box loss: 0.02328 RPN score loss: 0.00508 RPN total loss: 0.02836 Total loss: 1.14807 timestamp: 1655033109.5756035 iteration: 30985 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05911 FastRCNN class loss: 0.05105 FastRCNN total loss: 0.11016 L1 loss: 0.0000e+00 L2 loss: 0.77595 Learning rate: 0.02 Mask loss: 0.27821 RPN box loss: 0.00339 RPN score loss: 0.00225 RPN total loss: 0.00564 Total loss: 1.16997 timestamp: 1655033112.8510113 iteration: 30990 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13707 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.23528 L1 loss: 0.0000e+00 L2 loss: 0.77585 Learning rate: 0.02 Mask loss: 0.15054 RPN box loss: 0.01974 RPN score loss: 0.00468 RPN total loss: 0.02442 Total loss: 1.18609 timestamp: 1655033116.1921713 iteration: 30995 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12169 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.2044 L1 loss: 0.0000e+00 L2 loss: 0.77574 Learning rate: 0.02 Mask loss: 0.1795 RPN box loss: 0.04425 RPN score loss: 0.01731 RPN total loss: 0.06156 Total loss: 1.22119 timestamp: 1655033119.4692705 iteration: 31000 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13236 FastRCNN class loss: 0.05331 FastRCNN total loss: 0.18567 L1 loss: 0.0000e+00 L2 loss: 0.77562 Learning rate: 0.02 Mask loss: 0.13935 RPN box loss: 0.03262 RPN score loss: 0.0049 RPN total loss: 0.03752 Total loss: 1.13815 timestamp: 1655033122.7620456 iteration: 31005 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11035 FastRCNN class loss: 0.05553 FastRCNN total loss: 0.16588 L1 loss: 0.0000e+00 L2 loss: 0.77552 Learning rate: 0.02 Mask loss: 0.13547 RPN box loss: 0.06899 RPN score loss: 0.01149 RPN total loss: 0.08049 Total loss: 1.15735 timestamp: 1655033126.1085458 iteration: 31010 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17909 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.24497 L1 loss: 0.0000e+00 L2 loss: 0.77539 Learning rate: 0.02 Mask loss: 0.16775 RPN box loss: 0.06819 RPN score loss: 0.00789 RPN total loss: 0.07608 Total loss: 1.26419 timestamp: 1655033129.3803709 iteration: 31015 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06561 FastRCNN class loss: 0.04015 FastRCNN total loss: 0.10576 L1 loss: 0.0000e+00 L2 loss: 0.77527 Learning rate: 0.02 Mask loss: 0.14948 RPN box loss: 0.00633 RPN score loss: 0.00365 RPN total loss: 0.00998 Total loss: 1.04049 timestamp: 1655033132.6431022 iteration: 31020 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22157 FastRCNN class loss: 0.13618 FastRCNN total loss: 0.35776 L1 loss: 0.0000e+00 L2 loss: 0.77513 Learning rate: 0.02 Mask loss: 0.30567 RPN box loss: 0.02632 RPN score loss: 0.0197 RPN total loss: 0.04603 Total loss: 1.48458 timestamp: 1655033135.936384 iteration: 31025 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.17785 L1 loss: 0.0000e+00 L2 loss: 0.775 Learning rate: 0.02 Mask loss: 0.11444 RPN box loss: 0.019 RPN score loss: 0.00662 RPN total loss: 0.02562 Total loss: 1.09292 timestamp: 1655033139.1823688 iteration: 31030 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.17615 L1 loss: 0.0000e+00 L2 loss: 0.77487 Learning rate: 0.02 Mask loss: 0.18736 RPN box loss: 0.09708 RPN score loss: 0.0126 RPN total loss: 0.10968 Total loss: 1.24806 timestamp: 1655033142.5081317 iteration: 31035 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.09319 FastRCNN total loss: 0.20549 L1 loss: 0.0000e+00 L2 loss: 0.77475 Learning rate: 0.02 Mask loss: 0.14996 RPN box loss: 0.02873 RPN score loss: 0.00997 RPN total loss: 0.03869 Total loss: 1.16889 timestamp: 1655033145.8011758 iteration: 31040 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22255 FastRCNN class loss: 0.11829 FastRCNN total loss: 0.34084 L1 loss: 0.0000e+00 L2 loss: 0.77466 Learning rate: 0.02 Mask loss: 0.21064 RPN box loss: 0.06606 RPN score loss: 0.00887 RPN total loss: 0.07493 Total loss: 1.40107 timestamp: 1655033149.1316082 iteration: 31045 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19915 FastRCNN class loss: 0.06607 FastRCNN total loss: 0.26522 L1 loss: 0.0000e+00 L2 loss: 0.77454 Learning rate: 0.02 Mask loss: 0.16627 RPN box loss: 0.03414 RPN score loss: 0.00598 RPN total loss: 0.04012 Total loss: 1.24616 timestamp: 1655033152.360972 iteration: 31050 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09103 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.1566 L1 loss: 0.0000e+00 L2 loss: 0.77443 Learning rate: 0.02 Mask loss: 0.14561 RPN box loss: 0.03535 RPN score loss: 0.00612 RPN total loss: 0.04147 Total loss: 1.1181 timestamp: 1655033155.6539438 iteration: 31055 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0708 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.11827 L1 loss: 0.0000e+00 L2 loss: 0.77432 Learning rate: 0.02 Mask loss: 0.10038 RPN box loss: 0.03177 RPN score loss: 0.00406 RPN total loss: 0.03584 Total loss: 1.0288 timestamp: 1655033158.8822029 iteration: 31060 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18422 FastRCNN class loss: 0.09992 FastRCNN total loss: 0.28414 L1 loss: 0.0000e+00 L2 loss: 0.7742 Learning rate: 0.02 Mask loss: 0.13014 RPN box loss: 0.01687 RPN score loss: 0.00636 RPN total loss: 0.02323 Total loss: 1.2117 timestamp: 1655033162.1788905 iteration: 31065 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16349 FastRCNN class loss: 0.09464 FastRCNN total loss: 0.25813 L1 loss: 0.0000e+00 L2 loss: 0.77409 Learning rate: 0.02 Mask loss: 0.1496 RPN box loss: 0.02651 RPN score loss: 0.00396 RPN total loss: 0.03047 Total loss: 1.2123 timestamp: 1655033165.4901958 iteration: 31070 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17 FastRCNN class loss: 0.11939 FastRCNN total loss: 0.28939 L1 loss: 0.0000e+00 L2 loss: 0.77398 Learning rate: 0.02 Mask loss: 0.18028 RPN box loss: 0.04863 RPN score loss: 0.01048 RPN total loss: 0.05911 Total loss: 1.30276 timestamp: 1655033168.7962222 iteration: 31075 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14877 FastRCNN class loss: 0.06632 FastRCNN total loss: 0.21509 L1 loss: 0.0000e+00 L2 loss: 0.77388 Learning rate: 0.02 Mask loss: 0.19204 RPN box loss: 0.01801 RPN score loss: 0.00845 RPN total loss: 0.02646 Total loss: 1.20747 timestamp: 1655033172.0790913 iteration: 31080 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13799 FastRCNN class loss: 0.06937 FastRCNN total loss: 0.20736 L1 loss: 0.0000e+00 L2 loss: 0.77377 Learning rate: 0.02 Mask loss: 0.1489 RPN box loss: 0.02144 RPN score loss: 0.00911 RPN total loss: 0.03054 Total loss: 1.16056 timestamp: 1655033175.2981389 iteration: 31085 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17187 FastRCNN class loss: 0.12649 FastRCNN total loss: 0.29836 L1 loss: 0.0000e+00 L2 loss: 0.77362 Learning rate: 0.02 Mask loss: 0.22646 RPN box loss: 0.01 RPN score loss: 0.00378 RPN total loss: 0.01378 Total loss: 1.31222 timestamp: 1655033178.658937 iteration: 31090 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1626 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.24794 L1 loss: 0.0000e+00 L2 loss: 0.77352 Learning rate: 0.02 Mask loss: 0.16083 RPN box loss: 0.02949 RPN score loss: 0.00853 RPN total loss: 0.03802 Total loss: 1.22031 timestamp: 1655033181.9035125 iteration: 31095 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1769 FastRCNN class loss: 0.10299 FastRCNN total loss: 0.27989 L1 loss: 0.0000e+00 L2 loss: 0.77342 Learning rate: 0.02 Mask loss: 0.19679 RPN box loss: 0.08401 RPN score loss: 0.00629 RPN total loss: 0.0903 Total loss: 1.3404 timestamp: 1655033185.2218482 iteration: 31100 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17448 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.23977 L1 loss: 0.0000e+00 L2 loss: 0.77328 Learning rate: 0.02 Mask loss: 0.204 RPN box loss: 0.10921 RPN score loss: 0.01253 RPN total loss: 0.12174 Total loss: 1.33878 timestamp: 1655033188.5499074 iteration: 31105 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10872 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.16983 L1 loss: 0.0000e+00 L2 loss: 0.77317 Learning rate: 0.02 Mask loss: 0.1613 RPN box loss: 0.04571 RPN score loss: 0.00352 RPN total loss: 0.04923 Total loss: 1.15353 timestamp: 1655033191.8220346 iteration: 31110 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17628 FastRCNN class loss: 0.09138 FastRCNN total loss: 0.26766 L1 loss: 0.0000e+00 L2 loss: 0.77305 Learning rate: 0.02 Mask loss: 0.19731 RPN box loss: 0.02831 RPN score loss: 0.01295 RPN total loss: 0.04126 Total loss: 1.27929 timestamp: 1655033195.0921876 iteration: 31115 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21286 FastRCNN class loss: 0.09599 FastRCNN total loss: 0.30885 L1 loss: 0.0000e+00 L2 loss: 0.77293 Learning rate: 0.02 Mask loss: 0.17941 RPN box loss: 0.05345 RPN score loss: 0.00848 RPN total loss: 0.06193 Total loss: 1.32312 timestamp: 1655033198.3951023 iteration: 31120 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11821 FastRCNN class loss: 0.07921 FastRCNN total loss: 0.19742 L1 loss: 0.0000e+00 L2 loss: 0.77284 Learning rate: 0.02 Mask loss: 0.13431 RPN box loss: 0.03897 RPN score loss: 0.00357 RPN total loss: 0.04255 Total loss: 1.14712 timestamp: 1655033201.6317017 iteration: 31125 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14596 FastRCNN class loss: 0.07991 FastRCNN total loss: 0.22586 L1 loss: 0.0000e+00 L2 loss: 0.77275 Learning rate: 0.02 Mask loss: 0.15947 RPN box loss: 0.03825 RPN score loss: 0.00557 RPN total loss: 0.04382 Total loss: 1.2019 timestamp: 1655033204.8555422 iteration: 31130 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13586 FastRCNN class loss: 0.0414 FastRCNN total loss: 0.17726 L1 loss: 0.0000e+00 L2 loss: 0.77262 Learning rate: 0.02 Mask loss: 0.13493 RPN box loss: 0.00714 RPN score loss: 0.0056 RPN total loss: 0.01274 Total loss: 1.09756 timestamp: 1655033208.122463 iteration: 31135 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.15399 L1 loss: 0.0000e+00 L2 loss: 0.77252 Learning rate: 0.02 Mask loss: 0.15644 RPN box loss: 0.02508 RPN score loss: 0.00346 RPN total loss: 0.02854 Total loss: 1.11149 timestamp: 1655033211.409928 iteration: 31140 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12063 FastRCNN class loss: 0.04249 FastRCNN total loss: 0.16312 L1 loss: 0.0000e+00 L2 loss: 0.7724 Learning rate: 0.02 Mask loss: 0.1205 RPN box loss: 0.00659 RPN score loss: 0.00263 RPN total loss: 0.00922 Total loss: 1.06525 timestamp: 1655033214.735611 iteration: 31145 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15182 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.23492 L1 loss: 0.0000e+00 L2 loss: 0.7723 Learning rate: 0.02 Mask loss: 0.10796 RPN box loss: 0.02797 RPN score loss: 0.00403 RPN total loss: 0.032 Total loss: 1.14717 timestamp: 1655033218.0422893 iteration: 31150 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19891 FastRCNN class loss: 0.12718 FastRCNN total loss: 0.32609 L1 loss: 0.0000e+00 L2 loss: 0.77216 Learning rate: 0.02 Mask loss: 0.19872 RPN box loss: 0.03024 RPN score loss: 0.00628 RPN total loss: 0.03651 Total loss: 1.33348 timestamp: 1655033221.322839 iteration: 31155 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17544 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.23477 L1 loss: 0.0000e+00 L2 loss: 0.77203 Learning rate: 0.02 Mask loss: 0.13584 RPN box loss: 0.02041 RPN score loss: 0.00371 RPN total loss: 0.02413 Total loss: 1.16677 timestamp: 1655033224.6347296 iteration: 31160 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14173 FastRCNN class loss: 0.0477 FastRCNN total loss: 0.18943 L1 loss: 0.0000e+00 L2 loss: 0.77194 Learning rate: 0.02 Mask loss: 0.09805 RPN box loss: 0.01915 RPN score loss: 0.00282 RPN total loss: 0.02197 Total loss: 1.08139 timestamp: 1655033227.8022463 iteration: 31165 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14449 FastRCNN class loss: 0.06534 FastRCNN total loss: 0.20982 L1 loss: 0.0000e+00 L2 loss: 0.77183 Learning rate: 0.02 Mask loss: 0.20289 RPN box loss: 0.02348 RPN score loss: 0.00418 RPN total loss: 0.02767 Total loss: 1.21221 timestamp: 1655033231.0850513 iteration: 31170 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.07251 FastRCNN total loss: 0.18412 L1 loss: 0.0000e+00 L2 loss: 0.77172 Learning rate: 0.02 Mask loss: 0.13967 RPN box loss: 0.03369 RPN score loss: 0.00487 RPN total loss: 0.03857 Total loss: 1.13407 timestamp: 1655033234.434511 iteration: 31175 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2019 FastRCNN class loss: 0.09585 FastRCNN total loss: 0.29775 L1 loss: 0.0000e+00 L2 loss: 0.77161 Learning rate: 0.02 Mask loss: 0.17536 RPN box loss: 0.02433 RPN score loss: 0.01153 RPN total loss: 0.03587 Total loss: 1.28058 timestamp: 1655033237.7446587 iteration: 31180 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17951 FastRCNN class loss: 0.11834 FastRCNN total loss: 0.29785 L1 loss: 0.0000e+00 L2 loss: 0.77147 Learning rate: 0.02 Mask loss: 0.1705 RPN box loss: 0.05967 RPN score loss: 0.01338 RPN total loss: 0.07304 Total loss: 1.31286 timestamp: 1655033241.026897 iteration: 31185 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14681 FastRCNN class loss: 0.1198 FastRCNN total loss: 0.26661 L1 loss: 0.0000e+00 L2 loss: 0.77133 Learning rate: 0.02 Mask loss: 0.24013 RPN box loss: 0.01832 RPN score loss: 0.00773 RPN total loss: 0.02605 Total loss: 1.30412 timestamp: 1655033244.3481047 iteration: 31190 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16873 FastRCNN class loss: 0.09201 FastRCNN total loss: 0.26075 L1 loss: 0.0000e+00 L2 loss: 0.77124 Learning rate: 0.02 Mask loss: 0.1186 RPN box loss: 0.03649 RPN score loss: 0.01565 RPN total loss: 0.05213 Total loss: 1.20272 timestamp: 1655033247.6668122 iteration: 31195 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09267 FastRCNN class loss: 0.05263 FastRCNN total loss: 0.14531 L1 loss: 0.0000e+00 L2 loss: 0.77112 Learning rate: 0.02 Mask loss: 0.14537 RPN box loss: 0.07155 RPN score loss: 0.00837 RPN total loss: 0.07992 Total loss: 1.14172 timestamp: 1655033251.0370324 iteration: 31200 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1294 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.19182 L1 loss: 0.0000e+00 L2 loss: 0.77103 Learning rate: 0.02 Mask loss: 0.15607 RPN box loss: 0.01217 RPN score loss: 0.00538 RPN total loss: 0.01754 Total loss: 1.13645 timestamp: 1655033254.3223705 iteration: 31205 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10344 FastRCNN class loss: 0.12053 FastRCNN total loss: 0.22397 L1 loss: 0.0000e+00 L2 loss: 0.77093 Learning rate: 0.02 Mask loss: 0.25549 RPN box loss: 0.03839 RPN score loss: 0.0136 RPN total loss: 0.05199 Total loss: 1.30237 timestamp: 1655033257.5523188 iteration: 31210 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.03886 FastRCNN total loss: 0.131 L1 loss: 0.0000e+00 L2 loss: 0.7708 Learning rate: 0.02 Mask loss: 0.12304 RPN box loss: 0.03436 RPN score loss: 0.00489 RPN total loss: 0.03924 Total loss: 1.06408 timestamp: 1655033260.7863429 iteration: 31215 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13117 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.2036 L1 loss: 0.0000e+00 L2 loss: 0.77064 Learning rate: 0.02 Mask loss: 0.18022 RPN box loss: 0.03654 RPN score loss: 0.00391 RPN total loss: 0.04045 Total loss: 1.19491 timestamp: 1655033264.0554414 iteration: 31220 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13857 FastRCNN class loss: 0.08296 FastRCNN total loss: 0.22153 L1 loss: 0.0000e+00 L2 loss: 0.77054 Learning rate: 0.02 Mask loss: 0.19543 RPN box loss: 0.03473 RPN score loss: 0.00689 RPN total loss: 0.04162 Total loss: 1.22913 timestamp: 1655033267.2739766 iteration: 31225 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13053 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.18375 L1 loss: 0.0000e+00 L2 loss: 0.77042 Learning rate: 0.02 Mask loss: 0.13119 RPN box loss: 0.03064 RPN score loss: 0.00305 RPN total loss: 0.0337 Total loss: 1.11906 timestamp: 1655033270.6063607 iteration: 31230 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11535 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.19132 L1 loss: 0.0000e+00 L2 loss: 0.77033 Learning rate: 0.02 Mask loss: 0.14339 RPN box loss: 0.02663 RPN score loss: 0.01306 RPN total loss: 0.03969 Total loss: 1.14473 timestamp: 1655033273.8281825 iteration: 31235 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14312 FastRCNN class loss: 0.10314 FastRCNN total loss: 0.24626 L1 loss: 0.0000e+00 L2 loss: 0.77024 Learning rate: 0.02 Mask loss: 0.18249 RPN box loss: 0.02827 RPN score loss: 0.01046 RPN total loss: 0.03873 Total loss: 1.23773 timestamp: 1655033277.0447881 iteration: 31240 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21924 FastRCNN class loss: 0.10813 FastRCNN total loss: 0.32737 L1 loss: 0.0000e+00 L2 loss: 0.77011 Learning rate: 0.02 Mask loss: 0.25291 RPN box loss: 0.03543 RPN score loss: 0.0049 RPN total loss: 0.04033 Total loss: 1.39073 timestamp: 1655033280.3490407 iteration: 31245 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1513 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.23431 L1 loss: 0.0000e+00 L2 loss: 0.76999 Learning rate: 0.02 Mask loss: 0.12976 RPN box loss: 0.05087 RPN score loss: 0.00712 RPN total loss: 0.05798 Total loss: 1.19204 timestamp: 1655033283.6447022 iteration: 31250 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12173 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.18622 L1 loss: 0.0000e+00 L2 loss: 0.76987 Learning rate: 0.02 Mask loss: 0.14117 RPN box loss: 0.03102 RPN score loss: 0.00312 RPN total loss: 0.03415 Total loss: 1.13141 timestamp: 1655033286.9233696 iteration: 31255 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17292 FastRCNN class loss: 0.07873 FastRCNN total loss: 0.25165 L1 loss: 0.0000e+00 L2 loss: 0.76976 Learning rate: 0.02 Mask loss: 0.14349 RPN box loss: 0.05532 RPN score loss: 0.00798 RPN total loss: 0.0633 Total loss: 1.2282 timestamp: 1655033290.1535518 iteration: 31260 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17166 FastRCNN class loss: 0.07645 FastRCNN total loss: 0.2481 L1 loss: 0.0000e+00 L2 loss: 0.76966 Learning rate: 0.02 Mask loss: 0.17043 RPN box loss: 0.01935 RPN score loss: 0.00542 RPN total loss: 0.02477 Total loss: 1.21297 timestamp: 1655033293.467629 iteration: 31265 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14083 FastRCNN class loss: 0.1021 FastRCNN total loss: 0.24293 L1 loss: 0.0000e+00 L2 loss: 0.76956 Learning rate: 0.02 Mask loss: 0.17105 RPN box loss: 0.03981 RPN score loss: 0.00599 RPN total loss: 0.0458 Total loss: 1.22934 timestamp: 1655033296.6812353 iteration: 31270 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08812 FastRCNN class loss: 0.05674 FastRCNN total loss: 0.14486 L1 loss: 0.0000e+00 L2 loss: 0.76947 Learning rate: 0.02 Mask loss: 0.10738 RPN box loss: 0.01072 RPN score loss: 0.00375 RPN total loss: 0.01446 Total loss: 1.03618 timestamp: 1655033299.9468777 iteration: 31275 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16244 FastRCNN class loss: 0.08857 FastRCNN total loss: 0.25101 L1 loss: 0.0000e+00 L2 loss: 0.76935 Learning rate: 0.02 Mask loss: 0.12149 RPN box loss: 0.01805 RPN score loss: 0.0057 RPN total loss: 0.02375 Total loss: 1.16561 timestamp: 1655033303.2214458 iteration: 31280 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1815 FastRCNN class loss: 0.09352 FastRCNN total loss: 0.27501 L1 loss: 0.0000e+00 L2 loss: 0.76922 Learning rate: 0.02 Mask loss: 0.19471 RPN box loss: 0.03124 RPN score loss: 0.00659 RPN total loss: 0.03783 Total loss: 1.27678 timestamp: 1655033306.5509787 iteration: 31285 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12874 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.20231 L1 loss: 0.0000e+00 L2 loss: 0.76911 Learning rate: 0.02 Mask loss: 0.19477 RPN box loss: 0.01311 RPN score loss: 0.00251 RPN total loss: 0.01562 Total loss: 1.18182 timestamp: 1655033309.8261874 iteration: 31290 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.76896 Learning rate: 0.02 Mask loss: 0.13338 RPN box loss: 0.02305 RPN score loss: 0.00413 RPN total loss: 0.02717 Total loss: 1.08458 timestamp: 1655033313.1008174 iteration: 31295 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15839 FastRCNN class loss: 0.08557 FastRCNN total loss: 0.24396 L1 loss: 0.0000e+00 L2 loss: 0.76885 Learning rate: 0.02 Mask loss: 0.16254 RPN box loss: 0.02572 RPN score loss: 0.0086 RPN total loss: 0.03432 Total loss: 1.20966 timestamp: 1655033316.2941403 iteration: 31300 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19514 FastRCNN class loss: 0.08273 FastRCNN total loss: 0.27788 L1 loss: 0.0000e+00 L2 loss: 0.76877 Learning rate: 0.02 Mask loss: 0.1155 RPN box loss: 0.01204 RPN score loss: 0.00892 RPN total loss: 0.02096 Total loss: 1.1831 timestamp: 1655033319.6672125 iteration: 31305 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11835 FastRCNN class loss: 0.04651 FastRCNN total loss: 0.16486 L1 loss: 0.0000e+00 L2 loss: 0.76864 Learning rate: 0.02 Mask loss: 0.1131 RPN box loss: 0.01552 RPN score loss: 0.00333 RPN total loss: 0.01884 Total loss: 1.06544 timestamp: 1655033322.9187474 iteration: 31310 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.76854 Learning rate: 0.02 Mask loss: 0.13953 RPN box loss: 0.02889 RPN score loss: 0.00646 RPN total loss: 0.03535 Total loss: 1.1094 timestamp: 1655033326.1979206 iteration: 31315 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17663 FastRCNN class loss: 0.09487 FastRCNN total loss: 0.2715 L1 loss: 0.0000e+00 L2 loss: 0.76844 Learning rate: 0.02 Mask loss: 0.1823 RPN box loss: 0.05385 RPN score loss: 0.01106 RPN total loss: 0.06491 Total loss: 1.28715 timestamp: 1655033329.4353616 iteration: 31320 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08331 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.1499 L1 loss: 0.0000e+00 L2 loss: 0.76833 Learning rate: 0.02 Mask loss: 0.10523 RPN box loss: 0.02455 RPN score loss: 0.00405 RPN total loss: 0.0286 Total loss: 1.05206 timestamp: 1655033332.6939204 iteration: 31325 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18073 FastRCNN class loss: 0.1098 FastRCNN total loss: 0.29052 L1 loss: 0.0000e+00 L2 loss: 0.76819 Learning rate: 0.02 Mask loss: 0.24241 RPN box loss: 0.06279 RPN score loss: 0.01076 RPN total loss: 0.07355 Total loss: 1.37467 timestamp: 1655033336.0261579 iteration: 31330 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20666 FastRCNN class loss: 0.15819 FastRCNN total loss: 0.36486 L1 loss: 0.0000e+00 L2 loss: 0.76808 Learning rate: 0.02 Mask loss: 0.21166 RPN box loss: 0.0111 RPN score loss: 0.00419 RPN total loss: 0.01529 Total loss: 1.35988 timestamp: 1655033339.2575786 iteration: 31335 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11235 FastRCNN class loss: 0.05343 FastRCNN total loss: 0.16578 L1 loss: 0.0000e+00 L2 loss: 0.76796 Learning rate: 0.02 Mask loss: 0.11409 RPN box loss: 0.00844 RPN score loss: 0.00305 RPN total loss: 0.01148 Total loss: 1.05931 timestamp: 1655033342.507252 iteration: 31340 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08793 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.1615 L1 loss: 0.0000e+00 L2 loss: 0.76784 Learning rate: 0.02 Mask loss: 0.10767 RPN box loss: 0.03285 RPN score loss: 0.00588 RPN total loss: 0.03873 Total loss: 1.07573 timestamp: 1655033345.7686503 iteration: 31345 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14702 FastRCNN class loss: 0.1011 FastRCNN total loss: 0.24813 L1 loss: 0.0000e+00 L2 loss: 0.76773 Learning rate: 0.02 Mask loss: 0.25628 RPN box loss: 0.06339 RPN score loss: 0.01028 RPN total loss: 0.07367 Total loss: 1.3458 timestamp: 1655033348.9903045 iteration: 31350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07593 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.12857 L1 loss: 0.0000e+00 L2 loss: 0.76762 Learning rate: 0.02 Mask loss: 0.12296 RPN box loss: 0.04915 RPN score loss: 0.00745 RPN total loss: 0.0566 Total loss: 1.07574 timestamp: 1655033352.3055682 iteration: 31355 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18673 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.25409 L1 loss: 0.0000e+00 L2 loss: 0.7675 Learning rate: 0.02 Mask loss: 0.12809 RPN box loss: 0.0436 RPN score loss: 0.00642 RPN total loss: 0.05002 Total loss: 1.19969 timestamp: 1655033355.5382233 iteration: 31360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11536 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.19856 L1 loss: 0.0000e+00 L2 loss: 0.76739 Learning rate: 0.02 Mask loss: 0.12912 RPN box loss: 0.0232 RPN score loss: 0.00411 RPN total loss: 0.02731 Total loss: 1.12239 timestamp: 1655033358.8076053 iteration: 31365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12301 FastRCNN class loss: 0.03392 FastRCNN total loss: 0.15693 L1 loss: 0.0000e+00 L2 loss: 0.76728 Learning rate: 0.02 Mask loss: 0.09289 RPN box loss: 0.01031 RPN score loss: 0.00322 RPN total loss: 0.01352 Total loss: 1.03062 timestamp: 1655033362.1176398 iteration: 31370 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15404 FastRCNN class loss: 0.10758 FastRCNN total loss: 0.26162 L1 loss: 0.0000e+00 L2 loss: 0.76717 Learning rate: 0.02 Mask loss: 0.14168 RPN box loss: 0.0143 RPN score loss: 0.00428 RPN total loss: 0.01858 Total loss: 1.18906 timestamp: 1655033365.4387765 iteration: 31375 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1927 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.27581 L1 loss: 0.0000e+00 L2 loss: 0.76706 Learning rate: 0.02 Mask loss: 0.18945 RPN box loss: 0.02991 RPN score loss: 0.00825 RPN total loss: 0.03816 Total loss: 1.27049 timestamp: 1655033368.680769 iteration: 31380 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16036 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.22844 L1 loss: 0.0000e+00 L2 loss: 0.76693 Learning rate: 0.02 Mask loss: 0.15482 RPN box loss: 0.04297 RPN score loss: 0.01121 RPN total loss: 0.05418 Total loss: 1.20436 timestamp: 1655033371.905762 iteration: 31385 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12272 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.17205 L1 loss: 0.0000e+00 L2 loss: 0.76679 Learning rate: 0.02 Mask loss: 0.10742 RPN box loss: 0.01231 RPN score loss: 0.00558 RPN total loss: 0.01789 Total loss: 1.06415 timestamp: 1655033375.2064643 iteration: 31390 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07964 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.14091 L1 loss: 0.0000e+00 L2 loss: 0.76668 Learning rate: 0.02 Mask loss: 0.15789 RPN box loss: 0.03442 RPN score loss: 0.00308 RPN total loss: 0.0375 Total loss: 1.10299 timestamp: 1655033378.431661 iteration: 31395 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08519 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.16213 L1 loss: 0.0000e+00 L2 loss: 0.76658 Learning rate: 0.02 Mask loss: 0.15716 RPN box loss: 0.01519 RPN score loss: 0.00398 RPN total loss: 0.01917 Total loss: 1.10504 timestamp: 1655033381.7255926 iteration: 31400 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12646 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.17885 L1 loss: 0.0000e+00 L2 loss: 0.76648 Learning rate: 0.02 Mask loss: 0.14038 RPN box loss: 0.0694 RPN score loss: 0.00792 RPN total loss: 0.07733 Total loss: 1.16304 timestamp: 1655033385.0438912 iteration: 31405 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14812 FastRCNN class loss: 0.10514 FastRCNN total loss: 0.25325 L1 loss: 0.0000e+00 L2 loss: 0.76636 Learning rate: 0.02 Mask loss: 0.22501 RPN box loss: 0.05993 RPN score loss: 0.01413 RPN total loss: 0.07406 Total loss: 1.31868 timestamp: 1655033388.3713202 iteration: 31410 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16941 FastRCNN class loss: 0.08729 FastRCNN total loss: 0.25669 L1 loss: 0.0000e+00 L2 loss: 0.76627 Learning rate: 0.02 Mask loss: 0.14556 RPN box loss: 0.00944 RPN score loss: 0.01387 RPN total loss: 0.02331 Total loss: 1.19184 timestamp: 1655033391.650442 iteration: 31415 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18973 FastRCNN class loss: 0.15579 FastRCNN total loss: 0.34552 L1 loss: 0.0000e+00 L2 loss: 0.76617 Learning rate: 0.02 Mask loss: 0.18322 RPN box loss: 0.05559 RPN score loss: 0.01067 RPN total loss: 0.06626 Total loss: 1.36117 timestamp: 1655033394.956191 iteration: 31420 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12044 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.17348 L1 loss: 0.0000e+00 L2 loss: 0.76607 Learning rate: 0.02 Mask loss: 0.12522 RPN box loss: 0.01863 RPN score loss: 0.00259 RPN total loss: 0.02122 Total loss: 1.08599 timestamp: 1655033398.2238836 iteration: 31425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17727 FastRCNN class loss: 0.10445 FastRCNN total loss: 0.28172 L1 loss: 0.0000e+00 L2 loss: 0.76593 Learning rate: 0.02 Mask loss: 0.16388 RPN box loss: 0.07035 RPN score loss: 0.02063 RPN total loss: 0.09098 Total loss: 1.30251 timestamp: 1655033401.525139 iteration: 31430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18578 FastRCNN class loss: 0.10886 FastRCNN total loss: 0.29465 L1 loss: 0.0000e+00 L2 loss: 0.76579 Learning rate: 0.02 Mask loss: 0.22486 RPN box loss: 0.01828 RPN score loss: 0.00727 RPN total loss: 0.02555 Total loss: 1.31085 timestamp: 1655033404.7569094 iteration: 31435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13155 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.19377 L1 loss: 0.0000e+00 L2 loss: 0.76565 Learning rate: 0.02 Mask loss: 0.14905 RPN box loss: 0.07728 RPN score loss: 0.00481 RPN total loss: 0.08208 Total loss: 1.19055 timestamp: 1655033408.0413365 iteration: 31440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12025 FastRCNN class loss: 0.08839 FastRCNN total loss: 0.20863 L1 loss: 0.0000e+00 L2 loss: 0.76555 Learning rate: 0.02 Mask loss: 0.14617 RPN box loss: 0.01672 RPN score loss: 0.00422 RPN total loss: 0.02093 Total loss: 1.14128 timestamp: 1655033411.300695 iteration: 31445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14685 FastRCNN class loss: 0.09378 FastRCNN total loss: 0.24063 L1 loss: 0.0000e+00 L2 loss: 0.76547 Learning rate: 0.02 Mask loss: 0.177 RPN box loss: 0.02154 RPN score loss: 0.00693 RPN total loss: 0.02848 Total loss: 1.21158 timestamp: 1655033414.5491786 iteration: 31450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12624 FastRCNN class loss: 0.08997 FastRCNN total loss: 0.21621 L1 loss: 0.0000e+00 L2 loss: 0.76536 Learning rate: 0.02 Mask loss: 0.20204 RPN box loss: 0.01965 RPN score loss: 0.0086 RPN total loss: 0.02824 Total loss: 1.21186 timestamp: 1655033417.87017 iteration: 31455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1537 FastRCNN class loss: 0.11341 FastRCNN total loss: 0.26711 L1 loss: 0.0000e+00 L2 loss: 0.76524 Learning rate: 0.02 Mask loss: 0.19385 RPN box loss: 0.02594 RPN score loss: 0.0117 RPN total loss: 0.03764 Total loss: 1.26385 timestamp: 1655033421.1081088 iteration: 31460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16092 FastRCNN class loss: 0.09828 FastRCNN total loss: 0.2592 L1 loss: 0.0000e+00 L2 loss: 0.76512 Learning rate: 0.02 Mask loss: 0.15035 RPN box loss: 0.02693 RPN score loss: 0.00487 RPN total loss: 0.03181 Total loss: 1.20648 timestamp: 1655033424.3756547 iteration: 31465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14689 FastRCNN class loss: 0.10057 FastRCNN total loss: 0.24746 L1 loss: 0.0000e+00 L2 loss: 0.76502 Learning rate: 0.02 Mask loss: 0.18654 RPN box loss: 0.03313 RPN score loss: 0.00416 RPN total loss: 0.03728 Total loss: 1.2363 timestamp: 1655033427.6892664 iteration: 31470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16702 FastRCNN class loss: 0.14164 FastRCNN total loss: 0.30865 L1 loss: 0.0000e+00 L2 loss: 0.76491 Learning rate: 0.02 Mask loss: 0.22468 RPN box loss: 0.04422 RPN score loss: 0.0095 RPN total loss: 0.05373 Total loss: 1.35197 timestamp: 1655033430.943006 iteration: 31475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22535 FastRCNN class loss: 0.08085 FastRCNN total loss: 0.3062 L1 loss: 0.0000e+00 L2 loss: 0.7648 Learning rate: 0.02 Mask loss: 0.1851 RPN box loss: 0.01748 RPN score loss: 0.00298 RPN total loss: 0.02046 Total loss: 1.27656 timestamp: 1655033434.2508588 iteration: 31480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11351 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.18591 L1 loss: 0.0000e+00 L2 loss: 0.76468 Learning rate: 0.02 Mask loss: 0.10855 RPN box loss: 0.03195 RPN score loss: 0.01427 RPN total loss: 0.04621 Total loss: 1.10534 timestamp: 1655033437.513432 iteration: 31485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12615 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.21656 L1 loss: 0.0000e+00 L2 loss: 0.76455 Learning rate: 0.02 Mask loss: 0.16424 RPN box loss: 0.05118 RPN score loss: 0.0076 RPN total loss: 0.05878 Total loss: 1.20414 timestamp: 1655033440.830874 iteration: 31490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.05735 FastRCNN total loss: 0.14175 L1 loss: 0.0000e+00 L2 loss: 0.76446 Learning rate: 0.02 Mask loss: 0.09561 RPN box loss: 0.06732 RPN score loss: 0.00357 RPN total loss: 0.07089 Total loss: 1.0727 timestamp: 1655033444.088612 iteration: 31495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13641 FastRCNN class loss: 0.09125 FastRCNN total loss: 0.22767 L1 loss: 0.0000e+00 L2 loss: 0.76435 Learning rate: 0.02 Mask loss: 0.15679 RPN box loss: 0.01831 RPN score loss: 0.00798 RPN total loss: 0.02629 Total loss: 1.1751 timestamp: 1655033447.3376281 iteration: 31500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19044 FastRCNN class loss: 0.12894 FastRCNN total loss: 0.31938 L1 loss: 0.0000e+00 L2 loss: 0.76425 Learning rate: 0.02 Mask loss: 0.2572 RPN box loss: 0.04557 RPN score loss: 0.01799 RPN total loss: 0.06355 Total loss: 1.40438 timestamp: 1655033450.5380414 iteration: 31505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.076 FastRCNN class loss: 0.0457 FastRCNN total loss: 0.12169 L1 loss: 0.0000e+00 L2 loss: 0.76414 Learning rate: 0.02 Mask loss: 0.13564 RPN box loss: 0.02651 RPN score loss: 0.00213 RPN total loss: 0.02865 Total loss: 1.05012 timestamp: 1655033453.8674474 iteration: 31510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13134 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.21538 L1 loss: 0.0000e+00 L2 loss: 0.76403 Learning rate: 0.02 Mask loss: 0.192 RPN box loss: 0.05272 RPN score loss: 0.01055 RPN total loss: 0.06326 Total loss: 1.23468 timestamp: 1655033457.188171 iteration: 31515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18252 FastRCNN class loss: 0.10109 FastRCNN total loss: 0.28361 L1 loss: 0.0000e+00 L2 loss: 0.76391 Learning rate: 0.02 Mask loss: 0.11858 RPN box loss: 0.01508 RPN score loss: 0.00777 RPN total loss: 0.02285 Total loss: 1.18894 timestamp: 1655033460.4950607 iteration: 31520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14609 FastRCNN class loss: 0.09311 FastRCNN total loss: 0.2392 L1 loss: 0.0000e+00 L2 loss: 0.7638 Learning rate: 0.02 Mask loss: 0.16343 RPN box loss: 0.05475 RPN score loss: 0.01038 RPN total loss: 0.06513 Total loss: 1.23157 timestamp: 1655033463.758329 iteration: 31525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09175 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.14646 L1 loss: 0.0000e+00 L2 loss: 0.76369 Learning rate: 0.02 Mask loss: 0.17837 RPN box loss: 0.01474 RPN score loss: 0.00895 RPN total loss: 0.02369 Total loss: 1.11221 timestamp: 1655033467.091045 iteration: 31530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1019 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.16038 L1 loss: 0.0000e+00 L2 loss: 0.76356 Learning rate: 0.02 Mask loss: 0.16565 RPN box loss: 0.07028 RPN score loss: 0.01076 RPN total loss: 0.08104 Total loss: 1.17062 timestamp: 1655033470.360628 iteration: 31535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14218 FastRCNN class loss: 0.10828 FastRCNN total loss: 0.25046 L1 loss: 0.0000e+00 L2 loss: 0.76342 Learning rate: 0.02 Mask loss: 0.22044 RPN box loss: 0.03711 RPN score loss: 0.00938 RPN total loss: 0.04648 Total loss: 1.28081 timestamp: 1655033473.576267 iteration: 31540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.05045 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.7633 Learning rate: 0.02 Mask loss: 0.21957 RPN box loss: 0.01822 RPN score loss: 0.00658 RPN total loss: 0.0248 Total loss: 1.14753 timestamp: 1655033476.8475783 iteration: 31545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.04629 FastRCNN total loss: 0.16193 L1 loss: 0.0000e+00 L2 loss: 0.76321 Learning rate: 0.02 Mask loss: 0.13291 RPN box loss: 0.01797 RPN score loss: 0.0027 RPN total loss: 0.02067 Total loss: 1.07873 timestamp: 1655033480.083452 iteration: 31550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04939 FastRCNN class loss: 0.02832 FastRCNN total loss: 0.07771 L1 loss: 0.0000e+00 L2 loss: 0.7631 Learning rate: 0.02 Mask loss: 0.11377 RPN box loss: 0.04941 RPN score loss: 0.00464 RPN total loss: 0.05405 Total loss: 1.00864 timestamp: 1655033483.3622713 iteration: 31555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.174 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.24225 L1 loss: 0.0000e+00 L2 loss: 0.76299 Learning rate: 0.02 Mask loss: 0.12958 RPN box loss: 0.0179 RPN score loss: 0.00787 RPN total loss: 0.02577 Total loss: 1.1606 timestamp: 1655033486.605082 iteration: 31560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08259 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.13284 L1 loss: 0.0000e+00 L2 loss: 0.76287 Learning rate: 0.02 Mask loss: 0.1283 RPN box loss: 0.03071 RPN score loss: 0.00973 RPN total loss: 0.04044 Total loss: 1.06445 timestamp: 1655033489.8767347 iteration: 31565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11013 FastRCNN class loss: 0.08527 FastRCNN total loss: 0.1954 L1 loss: 0.0000e+00 L2 loss: 0.76274 Learning rate: 0.02 Mask loss: 0.13491 RPN box loss: 0.02242 RPN score loss: 0.00984 RPN total loss: 0.03227 Total loss: 1.12532 timestamp: 1655033493.2231379 iteration: 31570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15994 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.24855 L1 loss: 0.0000e+00 L2 loss: 0.76263 Learning rate: 0.02 Mask loss: 0.20088 RPN box loss: 0.04496 RPN score loss: 0.00368 RPN total loss: 0.04864 Total loss: 1.26071 timestamp: 1655033496.434553 iteration: 31575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15382 FastRCNN class loss: 0.15506 FastRCNN total loss: 0.30888 L1 loss: 0.0000e+00 L2 loss: 0.76251 Learning rate: 0.02 Mask loss: 0.18902 RPN box loss: 0.0339 RPN score loss: 0.01101 RPN total loss: 0.04491 Total loss: 1.30531 timestamp: 1655033499.685084 iteration: 31580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1476 FastRCNN class loss: 0.07388 FastRCNN total loss: 0.22148 L1 loss: 0.0000e+00 L2 loss: 0.76238 Learning rate: 0.02 Mask loss: 0.15569 RPN box loss: 0.01125 RPN score loss: 0.00618 RPN total loss: 0.01743 Total loss: 1.15698 timestamp: 1655033503.0475607 iteration: 31585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14322 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.76229 Learning rate: 0.02 Mask loss: 0.11501 RPN box loss: 0.06828 RPN score loss: 0.00489 RPN total loss: 0.07317 Total loss: 1.15815 timestamp: 1655033506.3044531 iteration: 31590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11968 FastRCNN class loss: 0.07326 FastRCNN total loss: 0.19294 L1 loss: 0.0000e+00 L2 loss: 0.76218 Learning rate: 0.02 Mask loss: 0.22313 RPN box loss: 0.05055 RPN score loss: 0.00974 RPN total loss: 0.0603 Total loss: 1.23855 timestamp: 1655033509.6262846 iteration: 31595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.1797 L1 loss: 0.0000e+00 L2 loss: 0.76208 Learning rate: 0.02 Mask loss: 0.23988 RPN box loss: 0.01825 RPN score loss: 0.0043 RPN total loss: 0.02255 Total loss: 1.20421 timestamp: 1655033512.90441 iteration: 31600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.12027 FastRCNN total loss: 0.26152 L1 loss: 0.0000e+00 L2 loss: 0.76197 Learning rate: 0.02 Mask loss: 0.22139 RPN box loss: 0.04642 RPN score loss: 0.00468 RPN total loss: 0.05109 Total loss: 1.29598 timestamp: 1655033516.1459677 iteration: 31605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26838 FastRCNN class loss: 0.14842 FastRCNN total loss: 0.4168 L1 loss: 0.0000e+00 L2 loss: 0.76185 Learning rate: 0.02 Mask loss: 0.24382 RPN box loss: 0.04631 RPN score loss: 0.01183 RPN total loss: 0.05814 Total loss: 1.48062 timestamp: 1655033519.3959353 iteration: 31610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21793 FastRCNN class loss: 0.11735 FastRCNN total loss: 0.33527 L1 loss: 0.0000e+00 L2 loss: 0.76173 Learning rate: 0.02 Mask loss: 0.19734 RPN box loss: 0.03279 RPN score loss: 0.00843 RPN total loss: 0.04122 Total loss: 1.33557 timestamp: 1655033522.625947 iteration: 31615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16452 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.2539 L1 loss: 0.0000e+00 L2 loss: 0.76162 Learning rate: 0.02 Mask loss: 0.23748 RPN box loss: 0.02619 RPN score loss: 0.00433 RPN total loss: 0.03052 Total loss: 1.28352 timestamp: 1655033525.8626044 iteration: 31620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16462 FastRCNN class loss: 0.08684 FastRCNN total loss: 0.25145 L1 loss: 0.0000e+00 L2 loss: 0.76155 Learning rate: 0.02 Mask loss: 0.13149 RPN box loss: 0.03198 RPN score loss: 0.00973 RPN total loss: 0.04172 Total loss: 1.18621 timestamp: 1655033529.2006154 iteration: 31625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12555 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.2137 L1 loss: 0.0000e+00 L2 loss: 0.76143 Learning rate: 0.02 Mask loss: 0.16095 RPN box loss: 0.13778 RPN score loss: 0.00985 RPN total loss: 0.14763 Total loss: 1.2837 timestamp: 1655033532.4857104 iteration: 31630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10108 FastRCNN class loss: 0.05083 FastRCNN total loss: 0.1519 L1 loss: 0.0000e+00 L2 loss: 0.76134 Learning rate: 0.02 Mask loss: 0.13385 RPN box loss: 0.08854 RPN score loss: 0.00942 RPN total loss: 0.09796 Total loss: 1.14505 timestamp: 1655033535.8338957 iteration: 31635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09061 FastRCNN class loss: 0.13514 FastRCNN total loss: 0.22575 L1 loss: 0.0000e+00 L2 loss: 0.76124 Learning rate: 0.02 Mask loss: 0.24196 RPN box loss: 0.05058 RPN score loss: 0.09332 RPN total loss: 0.1439 Total loss: 1.37284 timestamp: 1655033539.1644807 iteration: 31640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15699 FastRCNN class loss: 0.12313 FastRCNN total loss: 0.28012 L1 loss: 0.0000e+00 L2 loss: 0.76109 Learning rate: 0.02 Mask loss: 0.19911 RPN box loss: 0.0332 RPN score loss: 0.00572 RPN total loss: 0.03892 Total loss: 1.27925 timestamp: 1655033542.4624925 iteration: 31645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1728 FastRCNN class loss: 0.06812 FastRCNN total loss: 0.24092 L1 loss: 0.0000e+00 L2 loss: 0.761 Learning rate: 0.02 Mask loss: 0.18362 RPN box loss: 0.03136 RPN score loss: 0.00664 RPN total loss: 0.038 Total loss: 1.22353 timestamp: 1655033545.7451367 iteration: 31650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15326 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.21916 L1 loss: 0.0000e+00 L2 loss: 0.76089 Learning rate: 0.02 Mask loss: 0.15751 RPN box loss: 0.0421 RPN score loss: 0.01026 RPN total loss: 0.05236 Total loss: 1.18992 timestamp: 1655033549.0140834 iteration: 31655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17905 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.26464 L1 loss: 0.0000e+00 L2 loss: 0.76076 Learning rate: 0.02 Mask loss: 0.1481 RPN box loss: 0.02327 RPN score loss: 0.00543 RPN total loss: 0.02871 Total loss: 1.2022 timestamp: 1655033552.2301443 iteration: 31660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20279 FastRCNN class loss: 0.10952 FastRCNN total loss: 0.31232 L1 loss: 0.0000e+00 L2 loss: 0.76067 Learning rate: 0.02 Mask loss: 0.21409 RPN box loss: 0.02316 RPN score loss: 0.00946 RPN total loss: 0.03262 Total loss: 1.3197 timestamp: 1655033555.486747 iteration: 31665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.05582 FastRCNN total loss: 0.19691 L1 loss: 0.0000e+00 L2 loss: 0.76059 Learning rate: 0.02 Mask loss: 0.14618 RPN box loss: 0.02202 RPN score loss: 0.00328 RPN total loss: 0.0253 Total loss: 1.12898 timestamp: 1655033558.769648 iteration: 31670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10229 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.18345 L1 loss: 0.0000e+00 L2 loss: 0.76046 Learning rate: 0.02 Mask loss: 0.1619 RPN box loss: 0.01164 RPN score loss: 0.00552 RPN total loss: 0.01716 Total loss: 1.12298 timestamp: 1655033562.0753775 iteration: 31675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19768 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.2686 L1 loss: 0.0000e+00 L2 loss: 0.76033 Learning rate: 0.02 Mask loss: 0.1332 RPN box loss: 0.1015 RPN score loss: 0.00349 RPN total loss: 0.10499 Total loss: 1.26711 timestamp: 1655033565.327637 iteration: 31680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14097 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.20795 L1 loss: 0.0000e+00 L2 loss: 0.76023 Learning rate: 0.02 Mask loss: 0.11312 RPN box loss: 0.02432 RPN score loss: 0.00236 RPN total loss: 0.02668 Total loss: 1.10797 timestamp: 1655033568.6001005 iteration: 31685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1518 FastRCNN class loss: 0.14095 FastRCNN total loss: 0.29275 L1 loss: 0.0000e+00 L2 loss: 0.76014 Learning rate: 0.02 Mask loss: 0.19969 RPN box loss: 0.03601 RPN score loss: 0.00623 RPN total loss: 0.04224 Total loss: 1.29482 timestamp: 1655033571.897327 iteration: 31690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1398 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.2224 L1 loss: 0.0000e+00 L2 loss: 0.76001 Learning rate: 0.02 Mask loss: 0.18271 RPN box loss: 0.05004 RPN score loss: 0.00951 RPN total loss: 0.05955 Total loss: 1.22467 timestamp: 1655033575.2430518 iteration: 31695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14221 FastRCNN class loss: 0.0945 FastRCNN total loss: 0.23671 L1 loss: 0.0000e+00 L2 loss: 0.7599 Learning rate: 0.02 Mask loss: 0.14382 RPN box loss: 0.00899 RPN score loss: 0.00158 RPN total loss: 0.01057 Total loss: 1.151 timestamp: 1655033578.5221865 iteration: 31700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14788 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.24014 L1 loss: 0.0000e+00 L2 loss: 0.75982 Learning rate: 0.02 Mask loss: 0.14162 RPN box loss: 0.01704 RPN score loss: 0.00344 RPN total loss: 0.02048 Total loss: 1.16206 timestamp: 1655033581.7293308 iteration: 31705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19499 FastRCNN class loss: 0.12864 FastRCNN total loss: 0.32363 L1 loss: 0.0000e+00 L2 loss: 0.75971 Learning rate: 0.02 Mask loss: 0.22565 RPN box loss: 0.0167 RPN score loss: 0.01915 RPN total loss: 0.03585 Total loss: 1.34484 timestamp: 1655033585.0538552 iteration: 31710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11378 FastRCNN class loss: 0.11308 FastRCNN total loss: 0.22686 L1 loss: 0.0000e+00 L2 loss: 0.75959 Learning rate: 0.02 Mask loss: 0.14245 RPN box loss: 0.07757 RPN score loss: 0.01558 RPN total loss: 0.09314 Total loss: 1.22204 timestamp: 1655033588.3864005 iteration: 31715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13674 FastRCNN class loss: 0.11409 FastRCNN total loss: 0.25083 L1 loss: 0.0000e+00 L2 loss: 0.75946 Learning rate: 0.02 Mask loss: 0.19833 RPN box loss: 0.02563 RPN score loss: 0.00564 RPN total loss: 0.03128 Total loss: 1.2399 timestamp: 1655033591.5935092 iteration: 31720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14064 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.19037 L1 loss: 0.0000e+00 L2 loss: 0.75936 Learning rate: 0.02 Mask loss: 0.10982 RPN box loss: 0.07308 RPN score loss: 0.0084 RPN total loss: 0.08148 Total loss: 1.14103 timestamp: 1655033594.8370564 iteration: 31725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22832 FastRCNN class loss: 0.11601 FastRCNN total loss: 0.34433 L1 loss: 0.0000e+00 L2 loss: 0.75925 Learning rate: 0.02 Mask loss: 0.2312 RPN box loss: 0.03616 RPN score loss: 0.0152 RPN total loss: 0.05137 Total loss: 1.38615 timestamp: 1655033598.130425 iteration: 31730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13433 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.19509 L1 loss: 0.0000e+00 L2 loss: 0.75915 Learning rate: 0.02 Mask loss: 0.18696 RPN box loss: 0.02344 RPN score loss: 0.00401 RPN total loss: 0.02745 Total loss: 1.16865 timestamp: 1655033601.406482 iteration: 31735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1726 FastRCNN class loss: 0.12546 FastRCNN total loss: 0.29806 L1 loss: 0.0000e+00 L2 loss: 0.75905 Learning rate: 0.02 Mask loss: 0.13881 RPN box loss: 0.04747 RPN score loss: 0.00713 RPN total loss: 0.0546 Total loss: 1.25053 timestamp: 1655033604.6959937 iteration: 31740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18605 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.26026 L1 loss: 0.0000e+00 L2 loss: 0.75894 Learning rate: 0.02 Mask loss: 0.14666 RPN box loss: 0.01696 RPN score loss: 0.00375 RPN total loss: 0.02071 Total loss: 1.18656 timestamp: 1655033607.9815419 iteration: 31745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.06842 FastRCNN total loss: 0.18404 L1 loss: 0.0000e+00 L2 loss: 0.7588 Learning rate: 0.02 Mask loss: 0.10452 RPN box loss: 0.01044 RPN score loss: 0.00486 RPN total loss: 0.0153 Total loss: 1.06266 timestamp: 1655033611.2972045 iteration: 31750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11486 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.16901 L1 loss: 0.0000e+00 L2 loss: 0.75867 Learning rate: 0.02 Mask loss: 0.16874 RPN box loss: 0.02483 RPN score loss: 0.0047 RPN total loss: 0.02953 Total loss: 1.12596 timestamp: 1655033614.5005724 iteration: 31755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07661 FastRCNN class loss: 0.03751 FastRCNN total loss: 0.11412 L1 loss: 0.0000e+00 L2 loss: 0.75857 Learning rate: 0.02 Mask loss: 0.12641 RPN box loss: 0.03667 RPN score loss: 0.00469 RPN total loss: 0.04135 Total loss: 1.04045 timestamp: 1655033617.7435853 iteration: 31760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21507 FastRCNN class loss: 0.15041 FastRCNN total loss: 0.36547 L1 loss: 0.0000e+00 L2 loss: 0.75849 Learning rate: 0.02 Mask loss: 0.12525 RPN box loss: 0.03242 RPN score loss: 0.01138 RPN total loss: 0.0438 Total loss: 1.29301 timestamp: 1655033620.9580348 iteration: 31765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15168 FastRCNN class loss: 0.09161 FastRCNN total loss: 0.24329 L1 loss: 0.0000e+00 L2 loss: 0.75838 Learning rate: 0.02 Mask loss: 0.25447 RPN box loss: 0.07898 RPN score loss: 0.01544 RPN total loss: 0.09442 Total loss: 1.35056 timestamp: 1655033624.233665 iteration: 31770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15143 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.23045 L1 loss: 0.0000e+00 L2 loss: 0.75826 Learning rate: 0.02 Mask loss: 0.16238 RPN box loss: 0.05639 RPN score loss: 0.01161 RPN total loss: 0.068 Total loss: 1.21909 timestamp: 1655033627.51485 iteration: 31775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1215 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.19206 L1 loss: 0.0000e+00 L2 loss: 0.75813 Learning rate: 0.02 Mask loss: 0.18535 RPN box loss: 0.03431 RPN score loss: 0.00486 RPN total loss: 0.03917 Total loss: 1.17471 timestamp: 1655033630.7678468 iteration: 31780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15851 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.2355 L1 loss: 0.0000e+00 L2 loss: 0.75801 Learning rate: 0.02 Mask loss: 0.17584 RPN box loss: 0.1047 RPN score loss: 0.00384 RPN total loss: 0.10855 Total loss: 1.2779 timestamp: 1655033634.0006568 iteration: 31785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11836 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.1663 L1 loss: 0.0000e+00 L2 loss: 0.75789 Learning rate: 0.02 Mask loss: 0.14054 RPN box loss: 0.00839 RPN score loss: 0.00118 RPN total loss: 0.00957 Total loss: 1.0743 timestamp: 1655033637.248276 iteration: 31790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24553 FastRCNN class loss: 0.09687 FastRCNN total loss: 0.34241 L1 loss: 0.0000e+00 L2 loss: 0.75779 Learning rate: 0.02 Mask loss: 0.18706 RPN box loss: 0.07955 RPN score loss: 0.00839 RPN total loss: 0.08794 Total loss: 1.37519 timestamp: 1655033640.5688875 iteration: 31795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.093 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.15224 L1 loss: 0.0000e+00 L2 loss: 0.75766 Learning rate: 0.02 Mask loss: 0.173 RPN box loss: 0.03072 RPN score loss: 0.00589 RPN total loss: 0.03661 Total loss: 1.11951 timestamp: 1655033643.844474 iteration: 31800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22452 FastRCNN class loss: 0.09518 FastRCNN total loss: 0.3197 L1 loss: 0.0000e+00 L2 loss: 0.75753 Learning rate: 0.02 Mask loss: 0.30954 RPN box loss: 0.07416 RPN score loss: 0.01701 RPN total loss: 0.09117 Total loss: 1.47794 timestamp: 1655033647.1151345 iteration: 31805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12734 FastRCNN class loss: 0.08016 FastRCNN total loss: 0.2075 L1 loss: 0.0000e+00 L2 loss: 0.75742 Learning rate: 0.02 Mask loss: 0.14718 RPN box loss: 0.02527 RPN score loss: 0.00295 RPN total loss: 0.02822 Total loss: 1.14032 timestamp: 1655033650.3773446 iteration: 31810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13578 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.2031 L1 loss: 0.0000e+00 L2 loss: 0.75732 Learning rate: 0.02 Mask loss: 0.11313 RPN box loss: 0.00835 RPN score loss: 0.00304 RPN total loss: 0.01139 Total loss: 1.08494 timestamp: 1655033653.6990716 iteration: 31815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12609 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.19063 L1 loss: 0.0000e+00 L2 loss: 0.75716 Learning rate: 0.02 Mask loss: 0.17659 RPN box loss: 0.0455 RPN score loss: 0.00734 RPN total loss: 0.05284 Total loss: 1.17722 timestamp: 1655033656.970591 iteration: 31820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17852 FastRCNN class loss: 0.08238 FastRCNN total loss: 0.26091 L1 loss: 0.0000e+00 L2 loss: 0.75704 Learning rate: 0.02 Mask loss: 0.13601 RPN box loss: 0.02276 RPN score loss: 0.00523 RPN total loss: 0.02799 Total loss: 1.18194 timestamp: 1655033660.2852702 iteration: 31825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1836 FastRCNN class loss: 0.12686 FastRCNN total loss: 0.31046 L1 loss: 0.0000e+00 L2 loss: 0.75695 Learning rate: 0.02 Mask loss: 0.23665 RPN box loss: 0.03595 RPN score loss: 0.0107 RPN total loss: 0.04665 Total loss: 1.3507 timestamp: 1655033663.5143743 iteration: 31830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09713 FastRCNN class loss: 0.04286 FastRCNN total loss: 0.13999 L1 loss: 0.0000e+00 L2 loss: 0.75686 Learning rate: 0.02 Mask loss: 0.11185 RPN box loss: 0.07475 RPN score loss: 0.00895 RPN total loss: 0.08371 Total loss: 1.09241 timestamp: 1655033666.7943916 iteration: 31835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25453 FastRCNN class loss: 0.11167 FastRCNN total loss: 0.3662 L1 loss: 0.0000e+00 L2 loss: 0.75677 Learning rate: 0.02 Mask loss: 0.15193 RPN box loss: 0.02561 RPN score loss: 0.00388 RPN total loss: 0.02949 Total loss: 1.30439 timestamp: 1655033670.109229 iteration: 31840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09002 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.14645 L1 loss: 0.0000e+00 L2 loss: 0.75665 Learning rate: 0.02 Mask loss: 0.0937 RPN box loss: 0.02183 RPN score loss: 0.00274 RPN total loss: 0.02458 Total loss: 1.02138 timestamp: 1655033673.3894672 iteration: 31845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08704 FastRCNN class loss: 0.07877 FastRCNN total loss: 0.16581 L1 loss: 0.0000e+00 L2 loss: 0.75652 Learning rate: 0.02 Mask loss: 0.11626 RPN box loss: 0.02358 RPN score loss: 0.00793 RPN total loss: 0.03151 Total loss: 1.07011 timestamp: 1655033676.6798408 iteration: 31850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13058 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.2054 L1 loss: 0.0000e+00 L2 loss: 0.75639 Learning rate: 0.02 Mask loss: 0.13196 RPN box loss: 0.10487 RPN score loss: 0.01253 RPN total loss: 0.1174 Total loss: 1.21114 timestamp: 1655033679.9313242 iteration: 31855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13149 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.22057 L1 loss: 0.0000e+00 L2 loss: 0.75628 Learning rate: 0.02 Mask loss: 0.14256 RPN box loss: 0.02171 RPN score loss: 0.00263 RPN total loss: 0.02434 Total loss: 1.14375 timestamp: 1655033683.2764432 iteration: 31860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15503 FastRCNN class loss: 0.07854 FastRCNN total loss: 0.23357 L1 loss: 0.0000e+00 L2 loss: 0.7562 Learning rate: 0.02 Mask loss: 0.16924 RPN box loss: 0.03452 RPN score loss: 0.00592 RPN total loss: 0.04045 Total loss: 1.19945 timestamp: 1655033686.4761548 iteration: 31865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20997 FastRCNN class loss: 0.1596 FastRCNN total loss: 0.36957 L1 loss: 0.0000e+00 L2 loss: 0.75608 Learning rate: 0.02 Mask loss: 0.17266 RPN box loss: 0.0359 RPN score loss: 0.01278 RPN total loss: 0.04868 Total loss: 1.34699 timestamp: 1655033689.7349663 iteration: 31870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20896 FastRCNN class loss: 0.11054 FastRCNN total loss: 0.3195 L1 loss: 0.0000e+00 L2 loss: 0.75595 Learning rate: 0.02 Mask loss: 0.16311 RPN box loss: 0.05393 RPN score loss: 0.01187 RPN total loss: 0.0658 Total loss: 1.30436 timestamp: 1655033693.0041926 iteration: 31875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10193 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.16139 L1 loss: 0.0000e+00 L2 loss: 0.75589 Learning rate: 0.02 Mask loss: 0.15878 RPN box loss: 0.02301 RPN score loss: 0.00662 RPN total loss: 0.02963 Total loss: 1.10569 timestamp: 1655033696.282078 iteration: 31880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10643 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.17951 L1 loss: 0.0000e+00 L2 loss: 0.75577 Learning rate: 0.02 Mask loss: 0.19971 RPN box loss: 0.0217 RPN score loss: 0.00758 RPN total loss: 0.02927 Total loss: 1.16426 timestamp: 1655033699.5707736 iteration: 31885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12524 FastRCNN class loss: 0.09052 FastRCNN total loss: 0.21577 L1 loss: 0.0000e+00 L2 loss: 0.75566 Learning rate: 0.02 Mask loss: 0.23437 RPN box loss: 0.01872 RPN score loss: 0.00633 RPN total loss: 0.02504 Total loss: 1.23084 timestamp: 1655033702.8429945 iteration: 31890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10397 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.17903 L1 loss: 0.0000e+00 L2 loss: 0.75554 Learning rate: 0.02 Mask loss: 0.14908 RPN box loss: 0.0135 RPN score loss: 0.00623 RPN total loss: 0.01973 Total loss: 1.10338 timestamp: 1655033706.0689 iteration: 31895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14719 FastRCNN class loss: 0.077 FastRCNN total loss: 0.22419 L1 loss: 0.0000e+00 L2 loss: 0.75545 Learning rate: 0.02 Mask loss: 0.18834 RPN box loss: 0.0693 RPN score loss: 0.00898 RPN total loss: 0.07827 Total loss: 1.24626 timestamp: 1655033709.333175 iteration: 31900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1238 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.19648 L1 loss: 0.0000e+00 L2 loss: 0.75533 Learning rate: 0.02 Mask loss: 0.20217 RPN box loss: 0.04399 RPN score loss: 0.01631 RPN total loss: 0.0603 Total loss: 1.21428 timestamp: 1655033712.5785875 iteration: 31905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12278 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.18884 L1 loss: 0.0000e+00 L2 loss: 0.75521 Learning rate: 0.02 Mask loss: 0.15256 RPN box loss: 0.04887 RPN score loss: 0.00811 RPN total loss: 0.05698 Total loss: 1.1536 timestamp: 1655033715.8195 iteration: 31910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17377 FastRCNN class loss: 0.12653 FastRCNN total loss: 0.30029 L1 loss: 0.0000e+00 L2 loss: 0.7551 Learning rate: 0.02 Mask loss: 0.34008 RPN box loss: 0.0406 RPN score loss: 0.00795 RPN total loss: 0.04855 Total loss: 1.44403 timestamp: 1655033719.1288862 iteration: 31915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11836 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.17154 L1 loss: 0.0000e+00 L2 loss: 0.75501 Learning rate: 0.02 Mask loss: 0.12345 RPN box loss: 0.0667 RPN score loss: 0.00834 RPN total loss: 0.07504 Total loss: 1.12504 timestamp: 1655033722.4155927 iteration: 31920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15399 FastRCNN class loss: 0.07933 FastRCNN total loss: 0.23332 L1 loss: 0.0000e+00 L2 loss: 0.75491 Learning rate: 0.02 Mask loss: 0.13169 RPN box loss: 0.01236 RPN score loss: 0.00415 RPN total loss: 0.01651 Total loss: 1.13643 timestamp: 1655033725.7173507 iteration: 31925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16008 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.23495 L1 loss: 0.0000e+00 L2 loss: 0.75477 Learning rate: 0.02 Mask loss: 0.19669 RPN box loss: 0.03399 RPN score loss: 0.00345 RPN total loss: 0.03745 Total loss: 1.22386 timestamp: 1655033728.9806137 iteration: 31930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15188 FastRCNN class loss: 0.10071 FastRCNN total loss: 0.25259 L1 loss: 0.0000e+00 L2 loss: 0.75465 Learning rate: 0.02 Mask loss: 0.16433 RPN box loss: 0.01057 RPN score loss: 0.00582 RPN total loss: 0.01639 Total loss: 1.18796 timestamp: 1655033732.2144356 iteration: 31935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1879 FastRCNN class loss: 0.11596 FastRCNN total loss: 0.30385 L1 loss: 0.0000e+00 L2 loss: 0.75453 Learning rate: 0.02 Mask loss: 0.19835 RPN box loss: 0.06511 RPN score loss: 0.0214 RPN total loss: 0.08651 Total loss: 1.34325 timestamp: 1655033735.467357 iteration: 31940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12999 FastRCNN class loss: 0.0902 FastRCNN total loss: 0.22018 L1 loss: 0.0000e+00 L2 loss: 0.75438 Learning rate: 0.02 Mask loss: 0.18441 RPN box loss: 0.01832 RPN score loss: 0.00594 RPN total loss: 0.02426 Total loss: 1.18324 timestamp: 1655033738.6788704 iteration: 31945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1202 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.19421 L1 loss: 0.0000e+00 L2 loss: 0.75426 Learning rate: 0.02 Mask loss: 0.12337 RPN box loss: 0.01959 RPN score loss: 0.00219 RPN total loss: 0.02178 Total loss: 1.09362 timestamp: 1655033741.9520252 iteration: 31950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1396 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.20199 L1 loss: 0.0000e+00 L2 loss: 0.75418 Learning rate: 0.02 Mask loss: 0.16974 RPN box loss: 0.07122 RPN score loss: 0.0068 RPN total loss: 0.07802 Total loss: 1.20393 timestamp: 1655033745.1707122 iteration: 31955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18129 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.24978 L1 loss: 0.0000e+00 L2 loss: 0.75406 Learning rate: 0.02 Mask loss: 0.13541 RPN box loss: 0.03539 RPN score loss: 0.00884 RPN total loss: 0.04423 Total loss: 1.18349 timestamp: 1655033748.477725 iteration: 31960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08193 FastRCNN class loss: 0.06515 FastRCNN total loss: 0.14708 L1 loss: 0.0000e+00 L2 loss: 0.75397 Learning rate: 0.02 Mask loss: 0.1203 RPN box loss: 0.01911 RPN score loss: 0.00538 RPN total loss: 0.02448 Total loss: 1.04583 timestamp: 1655033751.7402322 iteration: 31965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.10189 FastRCNN total loss: 0.2248 L1 loss: 0.0000e+00 L2 loss: 0.75386 Learning rate: 0.02 Mask loss: 0.14142 RPN box loss: 0.04453 RPN score loss: 0.00939 RPN total loss: 0.05392 Total loss: 1.17399 timestamp: 1655033755.073509 iteration: 31970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.19485 L1 loss: 0.0000e+00 L2 loss: 0.75373 Learning rate: 0.02 Mask loss: 0.16428 RPN box loss: 0.01962 RPN score loss: 0.00853 RPN total loss: 0.02816 Total loss: 1.14101 timestamp: 1655033758.338849 iteration: 31975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14326 FastRCNN class loss: 0.14485 FastRCNN total loss: 0.2881 L1 loss: 0.0000e+00 L2 loss: 0.75366 Learning rate: 0.02 Mask loss: 0.22966 RPN box loss: 0.03192 RPN score loss: 0.02516 RPN total loss: 0.05708 Total loss: 1.3285 timestamp: 1655033761.5801275 iteration: 31980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08033 FastRCNN class loss: 0.05645 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 0.75358 Learning rate: 0.02 Mask loss: 0.12702 RPN box loss: 0.02217 RPN score loss: 0.01548 RPN total loss: 0.03765 Total loss: 1.05503 timestamp: 1655033764.8582065 iteration: 31985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16992 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.27324 L1 loss: 0.0000e+00 L2 loss: 0.75344 Learning rate: 0.02 Mask loss: 0.17095 RPN box loss: 0.03208 RPN score loss: 0.01689 RPN total loss: 0.04897 Total loss: 1.24661 timestamp: 1655033768.209799 iteration: 31990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16127 FastRCNN class loss: 0.09935 FastRCNN total loss: 0.26062 L1 loss: 0.0000e+00 L2 loss: 0.75331 Learning rate: 0.02 Mask loss: 0.24814 RPN box loss: 0.03125 RPN score loss: 0.00804 RPN total loss: 0.03929 Total loss: 1.30136 timestamp: 1655033771.496592 iteration: 31995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11747 FastRCNN class loss: 0.05218 FastRCNN total loss: 0.16965 L1 loss: 0.0000e+00 L2 loss: 0.7532 Learning rate: 0.02 Mask loss: 0.1449 RPN box loss: 0.06557 RPN score loss: 0.00714 RPN total loss: 0.07272 Total loss: 1.14046 timestamp: 1655033774.7339761 iteration: 32000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11311 FastRCNN class loss: 0.10011 FastRCNN total loss: 0.21322 L1 loss: 0.0000e+00 L2 loss: 0.75309 Learning rate: 0.02 Mask loss: 0.14106 RPN box loss: 0.02829 RPN score loss: 0.00357 RPN total loss: 0.03187 Total loss: 1.13924 timestamp: 1655033778.0527852 iteration: 32005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08637 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.14433 L1 loss: 0.0000e+00 L2 loss: 0.75297 Learning rate: 0.02 Mask loss: 0.20111 RPN box loss: 0.00326 RPN score loss: 0.00465 RPN total loss: 0.0079 Total loss: 1.10631 timestamp: 1655033781.2817185 iteration: 32010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14553 FastRCNN class loss: 0.09127 FastRCNN total loss: 0.2368 L1 loss: 0.0000e+00 L2 loss: 0.75286 Learning rate: 0.02 Mask loss: 0.21946 RPN box loss: 0.01904 RPN score loss: 0.00533 RPN total loss: 0.02437 Total loss: 1.23348 timestamp: 1655033784.6255374 iteration: 32015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15397 FastRCNN class loss: 0.08782 FastRCNN total loss: 0.24178 L1 loss: 0.0000e+00 L2 loss: 0.75276 Learning rate: 0.02 Mask loss: 0.15569 RPN box loss: 0.05853 RPN score loss: 0.01059 RPN total loss: 0.06911 Total loss: 1.21934 timestamp: 1655033787.895862 iteration: 32020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21786 FastRCNN class loss: 0.1252 FastRCNN total loss: 0.34306 L1 loss: 0.0000e+00 L2 loss: 0.75268 Learning rate: 0.02 Mask loss: 0.19195 RPN box loss: 0.07385 RPN score loss: 0.00957 RPN total loss: 0.08342 Total loss: 1.37109 timestamp: 1655033791.1464407 iteration: 32025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16621 FastRCNN class loss: 0.14395 FastRCNN total loss: 0.31015 L1 loss: 0.0000e+00 L2 loss: 0.75255 Learning rate: 0.02 Mask loss: 0.15367 RPN box loss: 0.09165 RPN score loss: 0.00795 RPN total loss: 0.0996 Total loss: 1.31597 timestamp: 1655033794.4056478 iteration: 32030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1866 FastRCNN class loss: 0.10193 FastRCNN total loss: 0.28853 L1 loss: 0.0000e+00 L2 loss: 0.75244 Learning rate: 0.02 Mask loss: 0.18785 RPN box loss: 0.04351 RPN score loss: 0.00809 RPN total loss: 0.0516 Total loss: 1.28042 timestamp: 1655033797.8030996 iteration: 32035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12076 FastRCNN class loss: 0.05046 FastRCNN total loss: 0.17123 L1 loss: 0.0000e+00 L2 loss: 0.75232 Learning rate: 0.02 Mask loss: 0.14695 RPN box loss: 0.01753 RPN score loss: 0.00616 RPN total loss: 0.02369 Total loss: 1.09418 timestamp: 1655033801.0804753 iteration: 32040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09725 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.15684 L1 loss: 0.0000e+00 L2 loss: 0.75223 Learning rate: 0.02 Mask loss: 0.10715 RPN box loss: 0.03926 RPN score loss: 0.00426 RPN total loss: 0.04353 Total loss: 1.05974 timestamp: 1655033804.3558462 iteration: 32045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17422 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.26771 L1 loss: 0.0000e+00 L2 loss: 0.75215 Learning rate: 0.02 Mask loss: 0.17843 RPN box loss: 0.06985 RPN score loss: 0.01047 RPN total loss: 0.08032 Total loss: 1.27861 timestamp: 1655033807.642599 iteration: 32050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15623 FastRCNN class loss: 0.05614 FastRCNN total loss: 0.21237 L1 loss: 0.0000e+00 L2 loss: 0.75204 Learning rate: 0.02 Mask loss: 0.22341 RPN box loss: 0.03354 RPN score loss: 0.00573 RPN total loss: 0.03927 Total loss: 1.2271 timestamp: 1655033810.9176314 iteration: 32055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15135 FastRCNN class loss: 0.1069 FastRCNN total loss: 0.25825 L1 loss: 0.0000e+00 L2 loss: 0.75192 Learning rate: 0.02 Mask loss: 0.15539 RPN box loss: 0.05099 RPN score loss: 0.00709 RPN total loss: 0.05808 Total loss: 1.22364 timestamp: 1655033814.1271088 iteration: 32060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11473 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.1822 L1 loss: 0.0000e+00 L2 loss: 0.7518 Learning rate: 0.02 Mask loss: 0.13483 RPN box loss: 0.01656 RPN score loss: 0.00743 RPN total loss: 0.02399 Total loss: 1.09282 timestamp: 1655033817.4259217 iteration: 32065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15589 FastRCNN class loss: 0.09412 FastRCNN total loss: 0.25001 L1 loss: 0.0000e+00 L2 loss: 0.75168 Learning rate: 0.02 Mask loss: 0.19455 RPN box loss: 0.05589 RPN score loss: 0.00905 RPN total loss: 0.06495 Total loss: 1.26118 timestamp: 1655033820.6830447 iteration: 32070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16374 FastRCNN class loss: 0.05841 FastRCNN total loss: 0.22216 L1 loss: 0.0000e+00 L2 loss: 0.75158 Learning rate: 0.02 Mask loss: 0.12377 RPN box loss: 0.01684 RPN score loss: 0.00523 RPN total loss: 0.02207 Total loss: 1.11958 timestamp: 1655033823.9302363 iteration: 32075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.04771 FastRCNN total loss: 0.1427 L1 loss: 0.0000e+00 L2 loss: 0.75146 Learning rate: 0.02 Mask loss: 0.15184 RPN box loss: 0.01748 RPN score loss: 0.01816 RPN total loss: 0.03564 Total loss: 1.08164 timestamp: 1655033827.1915727 iteration: 32080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09014 FastRCNN class loss: 0.03932 FastRCNN total loss: 0.12945 L1 loss: 0.0000e+00 L2 loss: 0.75136 Learning rate: 0.02 Mask loss: 0.09472 RPN box loss: 0.05427 RPN score loss: 0.00533 RPN total loss: 0.0596 Total loss: 1.03512 timestamp: 1655033830.4474812 iteration: 32085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13415 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.20712 L1 loss: 0.0000e+00 L2 loss: 0.75126 Learning rate: 0.02 Mask loss: 0.17274 RPN box loss: 0.01202 RPN score loss: 0.00395 RPN total loss: 0.01597 Total loss: 1.14709 timestamp: 1655033833.7427917 iteration: 32090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17564 FastRCNN class loss: 0.11582 FastRCNN total loss: 0.29145 L1 loss: 0.0000e+00 L2 loss: 0.75114 Learning rate: 0.02 Mask loss: 0.15551 RPN box loss: 0.04307 RPN score loss: 0.00897 RPN total loss: 0.05204 Total loss: 1.25014 timestamp: 1655033837.0178642 iteration: 32095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1311 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 0.75102 Learning rate: 0.02 Mask loss: 0.19803 RPN box loss: 0.00845 RPN score loss: 0.00231 RPN total loss: 0.01076 Total loss: 1.17273 timestamp: 1655033840.296149 iteration: 32100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14544 FastRCNN class loss: 0.08501 FastRCNN total loss: 0.23044 L1 loss: 0.0000e+00 L2 loss: 0.75091 Learning rate: 0.02 Mask loss: 0.1194 RPN box loss: 0.07194 RPN score loss: 0.01113 RPN total loss: 0.08306 Total loss: 1.18382 timestamp: 1655033843.5516238 iteration: 32105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15494 FastRCNN class loss: 0.09538 FastRCNN total loss: 0.25031 L1 loss: 0.0000e+00 L2 loss: 0.75081 Learning rate: 0.02 Mask loss: 0.20844 RPN box loss: 0.04845 RPN score loss: 0.00689 RPN total loss: 0.05534 Total loss: 1.26491 timestamp: 1655033846.8901536 iteration: 32110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13965 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.20432 L1 loss: 0.0000e+00 L2 loss: 0.75068 Learning rate: 0.02 Mask loss: 0.10666 RPN box loss: 0.04136 RPN score loss: 0.00475 RPN total loss: 0.04611 Total loss: 1.10777 timestamp: 1655033850.1621296 iteration: 32115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19498 FastRCNN class loss: 0.1377 FastRCNN total loss: 0.33268 L1 loss: 0.0000e+00 L2 loss: 0.75052 Learning rate: 0.02 Mask loss: 0.18401 RPN box loss: 0.03547 RPN score loss: 0.00773 RPN total loss: 0.04321 Total loss: 1.31042 timestamp: 1655033853.4249456 iteration: 32120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19063 FastRCNN class loss: 0.10287 FastRCNN total loss: 0.2935 L1 loss: 0.0000e+00 L2 loss: 0.75042 Learning rate: 0.02 Mask loss: 0.1963 RPN box loss: 0.03853 RPN score loss: 0.01304 RPN total loss: 0.05158 Total loss: 1.29179 timestamp: 1655033856.7444496 iteration: 32125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.08429 FastRCNN total loss: 0.17939 L1 loss: 0.0000e+00 L2 loss: 0.75034 Learning rate: 0.02 Mask loss: 0.13481 RPN box loss: 0.07383 RPN score loss: 0.00684 RPN total loss: 0.08067 Total loss: 1.14521 timestamp: 1655033859.91093 iteration: 32130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08366 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.13484 L1 loss: 0.0000e+00 L2 loss: 0.75025 Learning rate: 0.02 Mask loss: 0.08482 RPN box loss: 0.01275 RPN score loss: 0.00249 RPN total loss: 0.01524 Total loss: 0.98515 timestamp: 1655033863.1908972 iteration: 32135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.06027 FastRCNN total loss: 0.1769 L1 loss: 0.0000e+00 L2 loss: 0.75016 Learning rate: 0.02 Mask loss: 0.13155 RPN box loss: 0.01263 RPN score loss: 0.01213 RPN total loss: 0.02477 Total loss: 1.08337 timestamp: 1655033866.4390366 iteration: 32140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19401 FastRCNN class loss: 0.11729 FastRCNN total loss: 0.3113 L1 loss: 0.0000e+00 L2 loss: 0.75003 Learning rate: 0.02 Mask loss: 0.13831 RPN box loss: 0.03212 RPN score loss: 0.00849 RPN total loss: 0.04061 Total loss: 1.24025 timestamp: 1655033869.744259 iteration: 32145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1635 FastRCNN class loss: 0.09108 FastRCNN total loss: 0.25459 L1 loss: 0.0000e+00 L2 loss: 0.74994 Learning rate: 0.02 Mask loss: 0.23579 RPN box loss: 0.0539 RPN score loss: 0.01296 RPN total loss: 0.06686 Total loss: 1.30717 timestamp: 1655033873.068974 iteration: 32150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19404 FastRCNN class loss: 0.08171 FastRCNN total loss: 0.27575 L1 loss: 0.0000e+00 L2 loss: 0.74985 Learning rate: 0.02 Mask loss: 0.21443 RPN box loss: 0.05427 RPN score loss: 0.01533 RPN total loss: 0.0696 Total loss: 1.30963 timestamp: 1655033876.2562726 iteration: 32155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16576 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.2378 L1 loss: 0.0000e+00 L2 loss: 0.74971 Learning rate: 0.02 Mask loss: 0.20609 RPN box loss: 0.04799 RPN score loss: 0.01447 RPN total loss: 0.06246 Total loss: 1.25606 timestamp: 1655033879.5531466 iteration: 32160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09868 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.17305 L1 loss: 0.0000e+00 L2 loss: 0.74963 Learning rate: 0.02 Mask loss: 0.1031 RPN box loss: 0.04078 RPN score loss: 0.0106 RPN total loss: 0.05138 Total loss: 1.07717 timestamp: 1655033882.753943 iteration: 32165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22007 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.29898 L1 loss: 0.0000e+00 L2 loss: 0.74953 Learning rate: 0.02 Mask loss: 0.17447 RPN box loss: 0.01481 RPN score loss: 0.00634 RPN total loss: 0.02115 Total loss: 1.24414 timestamp: 1655033885.970773 iteration: 32170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20113 FastRCNN class loss: 0.08567 FastRCNN total loss: 0.2868 L1 loss: 0.0000e+00 L2 loss: 0.7494 Learning rate: 0.02 Mask loss: 0.16492 RPN box loss: 0.0626 RPN score loss: 0.00711 RPN total loss: 0.06971 Total loss: 1.27083 timestamp: 1655033889.2297764 iteration: 32175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.16275 L1 loss: 0.0000e+00 L2 loss: 0.74929 Learning rate: 0.02 Mask loss: 0.15398 RPN box loss: 0.02638 RPN score loss: 0.00729 RPN total loss: 0.03367 Total loss: 1.09969 timestamp: 1655033892.5084422 iteration: 32180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24361 FastRCNN class loss: 0.17487 FastRCNN total loss: 0.41848 L1 loss: 0.0000e+00 L2 loss: 0.74919 Learning rate: 0.02 Mask loss: 0.16076 RPN box loss: 0.02309 RPN score loss: 0.01071 RPN total loss: 0.0338 Total loss: 1.36223 timestamp: 1655033895.7187867 iteration: 32185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06533 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.11597 L1 loss: 0.0000e+00 L2 loss: 0.74909 Learning rate: 0.02 Mask loss: 0.12553 RPN box loss: 0.02021 RPN score loss: 0.00884 RPN total loss: 0.02904 Total loss: 1.01963 timestamp: 1655033898.9594421 iteration: 32190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15593 FastRCNN class loss: 0.07306 FastRCNN total loss: 0.229 L1 loss: 0.0000e+00 L2 loss: 0.74898 Learning rate: 0.02 Mask loss: 0.15613 RPN box loss: 0.06152 RPN score loss: 0.01167 RPN total loss: 0.07319 Total loss: 1.2073 timestamp: 1655033902.2398677 iteration: 32195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14512 FastRCNN class loss: 0.07415 FastRCNN total loss: 0.21927 L1 loss: 0.0000e+00 L2 loss: 0.74886 Learning rate: 0.02 Mask loss: 0.27851 RPN box loss: 0.01084 RPN score loss: 0.00519 RPN total loss: 0.01603 Total loss: 1.26268 timestamp: 1655033905.5094976 iteration: 32200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07477 FastRCNN class loss: 0.0878 FastRCNN total loss: 0.16257 L1 loss: 0.0000e+00 L2 loss: 0.74877 Learning rate: 0.02 Mask loss: 0.10829 RPN box loss: 0.02074 RPN score loss: 0.00337 RPN total loss: 0.02411 Total loss: 1.04374 timestamp: 1655033908.8201401 iteration: 32205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1227 FastRCNN class loss: 0.04884 FastRCNN total loss: 0.17154 L1 loss: 0.0000e+00 L2 loss: 0.74865 Learning rate: 0.02 Mask loss: 0.14783 RPN box loss: 0.02654 RPN score loss: 0.0043 RPN total loss: 0.03083 Total loss: 1.09885 timestamp: 1655033912.1128893 iteration: 32210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16319 FastRCNN class loss: 0.11519 FastRCNN total loss: 0.27837 L1 loss: 0.0000e+00 L2 loss: 0.74853 Learning rate: 0.02 Mask loss: 0.23985 RPN box loss: 0.04117 RPN score loss: 0.02396 RPN total loss: 0.06512 Total loss: 1.33187 timestamp: 1655033915.4196858 iteration: 32215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13445 FastRCNN class loss: 0.10814 FastRCNN total loss: 0.24259 L1 loss: 0.0000e+00 L2 loss: 0.74842 Learning rate: 0.02 Mask loss: 0.20389 RPN box loss: 0.03128 RPN score loss: 0.00916 RPN total loss: 0.04044 Total loss: 1.23534 timestamp: 1655033918.6425264 iteration: 32220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17084 FastRCNN class loss: 0.07851 FastRCNN total loss: 0.24934 L1 loss: 0.0000e+00 L2 loss: 0.74831 Learning rate: 0.02 Mask loss: 0.13171 RPN box loss: 0.013 RPN score loss: 0.00333 RPN total loss: 0.01633 Total loss: 1.14569 timestamp: 1655033921.9371796 iteration: 32225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19802 FastRCNN class loss: 0.09218 FastRCNN total loss: 0.2902 L1 loss: 0.0000e+00 L2 loss: 0.7482 Learning rate: 0.02 Mask loss: 0.16019 RPN box loss: 0.0589 RPN score loss: 0.01136 RPN total loss: 0.07026 Total loss: 1.26885 timestamp: 1655033925.1914904 iteration: 32230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14763 FastRCNN class loss: 0.05925 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 0.7481 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.04236 RPN score loss: 0.00837 RPN total loss: 0.05073 Total loss: 1.14866 timestamp: 1655033928.4057703 iteration: 32235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12169 FastRCNN class loss: 0.09524 FastRCNN total loss: 0.21693 L1 loss: 0.0000e+00 L2 loss: 0.74795 Learning rate: 0.02 Mask loss: 0.12218 RPN box loss: 0.02737 RPN score loss: 0.01171 RPN total loss: 0.03907 Total loss: 1.12614 timestamp: 1655033931.6458356 iteration: 32240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15361 FastRCNN class loss: 0.10212 FastRCNN total loss: 0.25574 L1 loss: 0.0000e+00 L2 loss: 0.74785 Learning rate: 0.02 Mask loss: 0.22138 RPN box loss: 0.01975 RPN score loss: 0.01049 RPN total loss: 0.03024 Total loss: 1.2552 timestamp: 1655033934.9100769 iteration: 32245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.74775 Learning rate: 0.02 Mask loss: 0.16338 RPN box loss: 0.02017 RPN score loss: 0.00345 RPN total loss: 0.02363 Total loss: 1.10119 timestamp: 1655033938.240693 iteration: 32250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19562 FastRCNN class loss: 0.08215 FastRCNN total loss: 0.27777 L1 loss: 0.0000e+00 L2 loss: 0.74763 Learning rate: 0.02 Mask loss: 0.10909 RPN box loss: 0.06987 RPN score loss: 0.01201 RPN total loss: 0.08188 Total loss: 1.21637 timestamp: 1655033941.5200984 iteration: 32255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09034 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.13362 L1 loss: 0.0000e+00 L2 loss: 0.7475 Learning rate: 0.02 Mask loss: 0.13783 RPN box loss: 0.01251 RPN score loss: 0.00594 RPN total loss: 0.01844 Total loss: 1.0374 timestamp: 1655033944.8008368 iteration: 32260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15455 FastRCNN class loss: 0.11115 FastRCNN total loss: 0.2657 L1 loss: 0.0000e+00 L2 loss: 0.74738 Learning rate: 0.02 Mask loss: 0.20137 RPN box loss: 0.05844 RPN score loss: 0.00845 RPN total loss: 0.06688 Total loss: 1.28134 timestamp: 1655033948.0221229 iteration: 32265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12348 FastRCNN class loss: 0.09668 FastRCNN total loss: 0.22015 L1 loss: 0.0000e+00 L2 loss: 0.74728 Learning rate: 0.02 Mask loss: 0.12511 RPN box loss: 0.10869 RPN score loss: 0.00925 RPN total loss: 0.11794 Total loss: 1.21048 timestamp: 1655033951.2738008 iteration: 32270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.04867 FastRCNN total loss: 0.14299 L1 loss: 0.0000e+00 L2 loss: 0.74718 Learning rate: 0.02 Mask loss: 0.11947 RPN box loss: 0.07031 RPN score loss: 0.00848 RPN total loss: 0.0788 Total loss: 1.08843 timestamp: 1655033954.5459845 iteration: 32275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10186 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.19279 L1 loss: 0.0000e+00 L2 loss: 0.74708 Learning rate: 0.02 Mask loss: 0.14004 RPN box loss: 0.04182 RPN score loss: 0.01159 RPN total loss: 0.05341 Total loss: 1.13331 timestamp: 1655033957.7665086 iteration: 32280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1184 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.1957 L1 loss: 0.0000e+00 L2 loss: 0.74697 Learning rate: 0.02 Mask loss: 0.11511 RPN box loss: 0.02285 RPN score loss: 0.00716 RPN total loss: 0.03 Total loss: 1.08778 timestamp: 1655033961.0597599 iteration: 32285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1429 FastRCNN class loss: 0.10195 FastRCNN total loss: 0.24485 L1 loss: 0.0000e+00 L2 loss: 0.74687 Learning rate: 0.02 Mask loss: 0.17373 RPN box loss: 0.02494 RPN score loss: 0.01119 RPN total loss: 0.03613 Total loss: 1.20159 timestamp: 1655033964.337356 iteration: 32290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18687 FastRCNN class loss: 0.07655 FastRCNN total loss: 0.26342 L1 loss: 0.0000e+00 L2 loss: 0.74674 Learning rate: 0.02 Mask loss: 0.13772 RPN box loss: 0.00818 RPN score loss: 0.00379 RPN total loss: 0.01197 Total loss: 1.15985 timestamp: 1655033967.5291195 iteration: 32295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22208 FastRCNN class loss: 0.08663 FastRCNN total loss: 0.3087 L1 loss: 0.0000e+00 L2 loss: 0.74662 Learning rate: 0.02 Mask loss: 0.23279 RPN box loss: 0.01569 RPN score loss: 0.00651 RPN total loss: 0.02221 Total loss: 1.31033 timestamp: 1655033970.909456 iteration: 32300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14459 FastRCNN class loss: 0.08504 FastRCNN total loss: 0.22963 L1 loss: 0.0000e+00 L2 loss: 0.74649 Learning rate: 0.02 Mask loss: 0.12367 RPN box loss: 0.00845 RPN score loss: 0.00422 RPN total loss: 0.01267 Total loss: 1.11246 timestamp: 1655033974.210969 iteration: 32305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10682 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.18947 L1 loss: 0.0000e+00 L2 loss: 0.74639 Learning rate: 0.02 Mask loss: 0.18542 RPN box loss: 0.06939 RPN score loss: 0.00908 RPN total loss: 0.07847 Total loss: 1.19975 timestamp: 1655033977.4923947 iteration: 32310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05215 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.12107 L1 loss: 0.0000e+00 L2 loss: 0.74629 Learning rate: 0.02 Mask loss: 0.12242 RPN box loss: 0.0583 RPN score loss: 0.00413 RPN total loss: 0.06243 Total loss: 1.0522 timestamp: 1655033980.8239086 iteration: 32315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14419 FastRCNN class loss: 0.09137 FastRCNN total loss: 0.23557 L1 loss: 0.0000e+00 L2 loss: 0.74621 Learning rate: 0.02 Mask loss: 0.11888 RPN box loss: 0.0473 RPN score loss: 0.00753 RPN total loss: 0.05483 Total loss: 1.15548 timestamp: 1655033984.0888598 iteration: 32320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20102 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.2862 L1 loss: 0.0000e+00 L2 loss: 0.74612 Learning rate: 0.02 Mask loss: 0.17583 RPN box loss: 0.03673 RPN score loss: 0.01954 RPN total loss: 0.05627 Total loss: 1.26443 timestamp: 1655033987.4245133 iteration: 32325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1309 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.20195 L1 loss: 0.0000e+00 L2 loss: 0.746 Learning rate: 0.02 Mask loss: 0.15533 RPN box loss: 0.01456 RPN score loss: 0.00742 RPN total loss: 0.02197 Total loss: 1.12525 timestamp: 1655033990.6464975 iteration: 32330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12456 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.20534 L1 loss: 0.0000e+00 L2 loss: 0.7459 Learning rate: 0.02 Mask loss: 0.16284 RPN box loss: 0.04983 RPN score loss: 0.00938 RPN total loss: 0.05921 Total loss: 1.17329 timestamp: 1655033993.869676 iteration: 32335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10691 FastRCNN class loss: 0.04618 FastRCNN total loss: 0.15309 L1 loss: 0.0000e+00 L2 loss: 0.7458 Learning rate: 0.02 Mask loss: 0.13741 RPN box loss: 0.03905 RPN score loss: 0.00813 RPN total loss: 0.04718 Total loss: 1.08348 timestamp: 1655033997.106084 iteration: 32340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12169 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.20848 L1 loss: 0.0000e+00 L2 loss: 0.7457 Learning rate: 0.02 Mask loss: 0.1183 RPN box loss: 0.01694 RPN score loss: 0.00444 RPN total loss: 0.02137 Total loss: 1.09385 timestamp: 1655034000.3814597 iteration: 32345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15676 FastRCNN class loss: 0.0698 FastRCNN total loss: 0.22656 L1 loss: 0.0000e+00 L2 loss: 0.74559 Learning rate: 0.02 Mask loss: 0.19786 RPN box loss: 0.05396 RPN score loss: 0.00762 RPN total loss: 0.06157 Total loss: 1.23158 timestamp: 1655034003.6282816 iteration: 32350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14641 FastRCNN class loss: 0.09604 FastRCNN total loss: 0.24245 L1 loss: 0.0000e+00 L2 loss: 0.74547 Learning rate: 0.02 Mask loss: 0.14027 RPN box loss: 0.01367 RPN score loss: 0.00904 RPN total loss: 0.02271 Total loss: 1.15091 timestamp: 1655034006.9054058 iteration: 32355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20676 FastRCNN class loss: 0.10026 FastRCNN total loss: 0.30703 L1 loss: 0.0000e+00 L2 loss: 0.74538 Learning rate: 0.02 Mask loss: 0.15282 RPN box loss: 0.0361 RPN score loss: 0.01556 RPN total loss: 0.05166 Total loss: 1.25689 timestamp: 1655034010.1916683 iteration: 32360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.05103 FastRCNN total loss: 0.14134 L1 loss: 0.0000e+00 L2 loss: 0.74527 Learning rate: 0.02 Mask loss: 0.3197 RPN box loss: 0.05289 RPN score loss: 0.0033 RPN total loss: 0.05619 Total loss: 1.26251 timestamp: 1655034013.5177624 iteration: 32365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1031 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.17347 L1 loss: 0.0000e+00 L2 loss: 0.74518 Learning rate: 0.02 Mask loss: 0.12411 RPN box loss: 0.03201 RPN score loss: 0.00462 RPN total loss: 0.03663 Total loss: 1.0794 timestamp: 1655034016.7523212 iteration: 32370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0871 FastRCNN class loss: 0.07096 FastRCNN total loss: 0.15806 L1 loss: 0.0000e+00 L2 loss: 0.74507 Learning rate: 0.02 Mask loss: 0.14219 RPN box loss: 0.04224 RPN score loss: 0.01161 RPN total loss: 0.05386 Total loss: 1.09918 timestamp: 1655034019.9767156 iteration: 32375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13125 FastRCNN class loss: 0.09093 FastRCNN total loss: 0.22218 L1 loss: 0.0000e+00 L2 loss: 0.74494 Learning rate: 0.02 Mask loss: 0.17476 RPN box loss: 0.04225 RPN score loss: 0.00471 RPN total loss: 0.04696 Total loss: 1.18884 timestamp: 1655034023.188489 iteration: 32380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15313 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.25152 L1 loss: 0.0000e+00 L2 loss: 0.74482 Learning rate: 0.02 Mask loss: 0.1235 RPN box loss: 0.01462 RPN score loss: 0.00293 RPN total loss: 0.01756 Total loss: 1.1374 timestamp: 1655034026.4827714 iteration: 32385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13375 FastRCNN class loss: 0.07659 FastRCNN total loss: 0.21035 L1 loss: 0.0000e+00 L2 loss: 0.74471 Learning rate: 0.02 Mask loss: 0.13031 RPN box loss: 0.05542 RPN score loss: 0.0127 RPN total loss: 0.06812 Total loss: 1.15349 timestamp: 1655034029.7436802 iteration: 32390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13567 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.19797 L1 loss: 0.0000e+00 L2 loss: 0.7446 Learning rate: 0.02 Mask loss: 0.16496 RPN box loss: 0.02057 RPN score loss: 0.00773 RPN total loss: 0.0283 Total loss: 1.13582 timestamp: 1655034033.1410797 iteration: 32395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10197 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.15467 L1 loss: 0.0000e+00 L2 loss: 0.74453 Learning rate: 0.02 Mask loss: 0.10953 RPN box loss: 0.08466 RPN score loss: 0.00972 RPN total loss: 0.09439 Total loss: 1.10311 timestamp: 1655034036.472665 iteration: 32400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16196 FastRCNN class loss: 0.07964 FastRCNN total loss: 0.2416 L1 loss: 0.0000e+00 L2 loss: 0.74443 Learning rate: 0.02 Mask loss: 0.12786 RPN box loss: 0.04448 RPN score loss: 0.00857 RPN total loss: 0.05305 Total loss: 1.16693 timestamp: 1655034039.784694 iteration: 32405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2066 FastRCNN class loss: 0.115 FastRCNN total loss: 0.3216 L1 loss: 0.0000e+00 L2 loss: 0.74431 Learning rate: 0.02 Mask loss: 0.19873 RPN box loss: 0.0144 RPN score loss: 0.00451 RPN total loss: 0.0189 Total loss: 1.28354 timestamp: 1655034043.1065931 iteration: 32410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20009 FastRCNN class loss: 0.1031 FastRCNN total loss: 0.30319 L1 loss: 0.0000e+00 L2 loss: 0.74423 Learning rate: 0.02 Mask loss: 0.20213 RPN box loss: 0.02975 RPN score loss: 0.00661 RPN total loss: 0.03636 Total loss: 1.28591 timestamp: 1655034046.3805244 iteration: 32415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16074 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.23568 L1 loss: 0.0000e+00 L2 loss: 0.74411 Learning rate: 0.02 Mask loss: 0.13083 RPN box loss: 0.04565 RPN score loss: 0.0087 RPN total loss: 0.05435 Total loss: 1.16498 timestamp: 1655034049.6804585 iteration: 32420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10747 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.19681 L1 loss: 0.0000e+00 L2 loss: 0.74399 Learning rate: 0.02 Mask loss: 0.19365 RPN box loss: 0.02842 RPN score loss: 0.01815 RPN total loss: 0.04657 Total loss: 1.18103 timestamp: 1655034052.9598053 iteration: 32425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11509 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.21718 L1 loss: 0.0000e+00 L2 loss: 0.74387 Learning rate: 0.02 Mask loss: 0.19502 RPN box loss: 0.06601 RPN score loss: 0.0196 RPN total loss: 0.08561 Total loss: 1.24168 timestamp: 1655034056.2318773 iteration: 32430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13866 FastRCNN class loss: 0.08932 FastRCNN total loss: 0.22798 L1 loss: 0.0000e+00 L2 loss: 0.74377 Learning rate: 0.02 Mask loss: 0.14898 RPN box loss: 0.04295 RPN score loss: 0.00749 RPN total loss: 0.05045 Total loss: 1.17119 timestamp: 1655034059.4329395 iteration: 32435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.135 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.19171 L1 loss: 0.0000e+00 L2 loss: 0.74367 Learning rate: 0.02 Mask loss: 0.10637 RPN box loss: 0.00892 RPN score loss: 0.00282 RPN total loss: 0.01174 Total loss: 1.05349 timestamp: 1655034062.7925699 iteration: 32440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17855 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.25357 L1 loss: 0.0000e+00 L2 loss: 0.74357 Learning rate: 0.02 Mask loss: 0.29556 RPN box loss: 0.11599 RPN score loss: 0.00745 RPN total loss: 0.12344 Total loss: 1.41613 timestamp: 1655034066.0731523 iteration: 32445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21995 FastRCNN class loss: 0.10881 FastRCNN total loss: 0.32876 L1 loss: 0.0000e+00 L2 loss: 0.74346 Learning rate: 0.02 Mask loss: 0.21229 RPN box loss: 0.05022 RPN score loss: 0.00454 RPN total loss: 0.05476 Total loss: 1.33927 timestamp: 1655034069.3346455 iteration: 32450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08292 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.1671 L1 loss: 0.0000e+00 L2 loss: 0.74336 Learning rate: 0.02 Mask loss: 0.14789 RPN box loss: 0.04512 RPN score loss: 0.01847 RPN total loss: 0.0636 Total loss: 1.12195 timestamp: 1655034072.621314 iteration: 32455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14418 FastRCNN class loss: 0.07733 FastRCNN total loss: 0.22152 L1 loss: 0.0000e+00 L2 loss: 0.74324 Learning rate: 0.02 Mask loss: 0.19776 RPN box loss: 0.03224 RPN score loss: 0.00962 RPN total loss: 0.04186 Total loss: 1.20437 timestamp: 1655034075.9101758 iteration: 32460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15934 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.25755 L1 loss: 0.0000e+00 L2 loss: 0.74313 Learning rate: 0.02 Mask loss: 0.22731 RPN box loss: 0.0234 RPN score loss: 0.00568 RPN total loss: 0.02909 Total loss: 1.25707 timestamp: 1655034079.1704013 iteration: 32465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15186 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.22062 L1 loss: 0.0000e+00 L2 loss: 0.74303 Learning rate: 0.02 Mask loss: 0.14147 RPN box loss: 0.01405 RPN score loss: 0.00683 RPN total loss: 0.02088 Total loss: 1.126 timestamp: 1655034082.425045 iteration: 32470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.17959 L1 loss: 0.0000e+00 L2 loss: 0.74294 Learning rate: 0.02 Mask loss: 0.14359 RPN box loss: 0.02419 RPN score loss: 0.01161 RPN total loss: 0.0358 Total loss: 1.10192 timestamp: 1655034085.7196543 iteration: 32475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18498 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.26798 L1 loss: 0.0000e+00 L2 loss: 0.74282 Learning rate: 0.02 Mask loss: 0.16431 RPN box loss: 0.02409 RPN score loss: 0.00783 RPN total loss: 0.03192 Total loss: 1.20703 timestamp: 1655034089.0403428 iteration: 32480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14605 FastRCNN class loss: 0.10625 FastRCNN total loss: 0.2523 L1 loss: 0.0000e+00 L2 loss: 0.7427 Learning rate: 0.02 Mask loss: 0.17463 RPN box loss: 0.0519 RPN score loss: 0.00576 RPN total loss: 0.05766 Total loss: 1.22729 timestamp: 1655034092.3200774 iteration: 32485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10817 FastRCNN class loss: 0.06796 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.7426 Learning rate: 0.02 Mask loss: 0.11388 RPN box loss: 0.04358 RPN score loss: 0.00851 RPN total loss: 0.05209 Total loss: 1.0847 timestamp: 1655034095.6426966 iteration: 32490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10591 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.74248 Learning rate: 0.02 Mask loss: 0.10188 RPN box loss: 0.02136 RPN score loss: 0.00189 RPN total loss: 0.02325 Total loss: 1.03236 timestamp: 1655034098.8592682 iteration: 32495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10478 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.16856 L1 loss: 0.0000e+00 L2 loss: 0.74238 Learning rate: 0.02 Mask loss: 0.10865 RPN box loss: 0.01655 RPN score loss: 0.00452 RPN total loss: 0.02107 Total loss: 1.04067 timestamp: 1655034102.148387 iteration: 32500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12903 FastRCNN class loss: 0.09469 FastRCNN total loss: 0.22372 L1 loss: 0.0000e+00 L2 loss: 0.74227 Learning rate: 0.02 Mask loss: 0.09606 RPN box loss: 0.04102 RPN score loss: 0.00753 RPN total loss: 0.04855 Total loss: 1.1106 timestamp: 1655034105.3690493 iteration: 32505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09947 FastRCNN class loss: 0.08046 FastRCNN total loss: 0.17992 L1 loss: 0.0000e+00 L2 loss: 0.74216 Learning rate: 0.02 Mask loss: 0.13784 RPN box loss: 0.04028 RPN score loss: 0.00661 RPN total loss: 0.04689 Total loss: 1.10682 timestamp: 1655034108.6865208 iteration: 32510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.09586 FastRCNN total loss: 0.20391 L1 loss: 0.0000e+00 L2 loss: 0.74205 Learning rate: 0.02 Mask loss: 0.15045 RPN box loss: 0.04702 RPN score loss: 0.00427 RPN total loss: 0.05129 Total loss: 1.1477 timestamp: 1655034111.963388 iteration: 32515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18933 FastRCNN class loss: 0.12652 FastRCNN total loss: 0.31585 L1 loss: 0.0000e+00 L2 loss: 0.74193 Learning rate: 0.02 Mask loss: 0.21306 RPN box loss: 0.05296 RPN score loss: 0.01837 RPN total loss: 0.07133 Total loss: 1.34217 timestamp: 1655034115.1740925 iteration: 32520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1251 FastRCNN class loss: 0.08175 FastRCNN total loss: 0.20685 L1 loss: 0.0000e+00 L2 loss: 0.74184 Learning rate: 0.02 Mask loss: 0.19268 RPN box loss: 0.0341 RPN score loss: 0.01477 RPN total loss: 0.04887 Total loss: 1.19024 timestamp: 1655034118.4670095 iteration: 32525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11811 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.19714 L1 loss: 0.0000e+00 L2 loss: 0.74175 Learning rate: 0.02 Mask loss: 0.22627 RPN box loss: 0.04715 RPN score loss: 0.00394 RPN total loss: 0.05109 Total loss: 1.21625 timestamp: 1655034121.7630806 iteration: 32530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1193 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.19101 L1 loss: 0.0000e+00 L2 loss: 0.74163 Learning rate: 0.02 Mask loss: 0.13695 RPN box loss: 0.01231 RPN score loss: 0.00705 RPN total loss: 0.01936 Total loss: 1.08896 timestamp: 1655034125.0059545 iteration: 32535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14845 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.22008 L1 loss: 0.0000e+00 L2 loss: 0.74153 Learning rate: 0.02 Mask loss: 0.18568 RPN box loss: 0.01834 RPN score loss: 0.00785 RPN total loss: 0.0262 Total loss: 1.17348 timestamp: 1655034128.2651243 iteration: 32540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13674 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.22497 L1 loss: 0.0000e+00 L2 loss: 0.74142 Learning rate: 0.02 Mask loss: 0.25203 RPN box loss: 0.06988 RPN score loss: 0.00382 RPN total loss: 0.0737 Total loss: 1.29212 timestamp: 1655034131.5201237 iteration: 32545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16164 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.21373 L1 loss: 0.0000e+00 L2 loss: 0.74128 Learning rate: 0.02 Mask loss: 0.17866 RPN box loss: 0.05135 RPN score loss: 0.00686 RPN total loss: 0.05821 Total loss: 1.19188 timestamp: 1655034134.780895 iteration: 32550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12109 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.18544 L1 loss: 0.0000e+00 L2 loss: 0.74117 Learning rate: 0.02 Mask loss: 0.16581 RPN box loss: 0.01458 RPN score loss: 0.00702 RPN total loss: 0.0216 Total loss: 1.11403 timestamp: 1655034138.0828962 iteration: 32555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13969 FastRCNN class loss: 0.08847 FastRCNN total loss: 0.22816 L1 loss: 0.0000e+00 L2 loss: 0.74106 Learning rate: 0.02 Mask loss: 0.2269 RPN box loss: 0.03131 RPN score loss: 0.00956 RPN total loss: 0.04087 Total loss: 1.23699 timestamp: 1655034141.3780437 iteration: 32560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12662 FastRCNN class loss: 0.14622 FastRCNN total loss: 0.27284 L1 loss: 0.0000e+00 L2 loss: 0.74095 Learning rate: 0.02 Mask loss: 0.20725 RPN box loss: 0.06421 RPN score loss: 0.01022 RPN total loss: 0.07443 Total loss: 1.29546 timestamp: 1655034144.6362665 iteration: 32565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13741 FastRCNN class loss: 0.11041 FastRCNN total loss: 0.24783 L1 loss: 0.0000e+00 L2 loss: 0.74086 Learning rate: 0.02 Mask loss: 0.16792 RPN box loss: 0.05319 RPN score loss: 0.00803 RPN total loss: 0.06122 Total loss: 1.21782 timestamp: 1655034147.9525914 iteration: 32570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15191 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.21715 L1 loss: 0.0000e+00 L2 loss: 0.74075 Learning rate: 0.02 Mask loss: 0.11222 RPN box loss: 0.00807 RPN score loss: 0.00117 RPN total loss: 0.00923 Total loss: 1.07935 timestamp: 1655034151.1503215 iteration: 32575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15611 FastRCNN class loss: 0.09941 FastRCNN total loss: 0.25552 L1 loss: 0.0000e+00 L2 loss: 0.74063 Learning rate: 0.02 Mask loss: 0.17091 RPN box loss: 0.01164 RPN score loss: 0.00627 RPN total loss: 0.01791 Total loss: 1.18497 timestamp: 1655034154.349819 iteration: 32580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.12828 FastRCNN total loss: 0.2869 L1 loss: 0.0000e+00 L2 loss: 0.74052 Learning rate: 0.02 Mask loss: 0.20156 RPN box loss: 0.06267 RPN score loss: 0.01851 RPN total loss: 0.08118 Total loss: 1.31016 timestamp: 1655034157.6552901 iteration: 32585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13018 FastRCNN class loss: 0.04427 FastRCNN total loss: 0.17444 L1 loss: 0.0000e+00 L2 loss: 0.7404 Learning rate: 0.02 Mask loss: 0.17836 RPN box loss: 0.05141 RPN score loss: 0.00652 RPN total loss: 0.05794 Total loss: 1.15115 timestamp: 1655034160.9403079 iteration: 32590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16109 FastRCNN class loss: 0.05203 FastRCNN total loss: 0.21312 L1 loss: 0.0000e+00 L2 loss: 0.74029 Learning rate: 0.02 Mask loss: 0.12043 RPN box loss: 0.01625 RPN score loss: 0.00315 RPN total loss: 0.01939 Total loss: 1.09323 timestamp: 1655034164.2710288 iteration: 32595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2078 FastRCNN class loss: 0.11603 FastRCNN total loss: 0.32383 L1 loss: 0.0000e+00 L2 loss: 0.7402 Learning rate: 0.02 Mask loss: 0.16604 RPN box loss: 0.09461 RPN score loss: 0.01411 RPN total loss: 0.10871 Total loss: 1.33879 timestamp: 1655034167.5619216 iteration: 32600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14531 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.20646 L1 loss: 0.0000e+00 L2 loss: 0.74011 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.04798 RPN score loss: 0.0066 RPN total loss: 0.05458 Total loss: 1.18426 timestamp: 1655034170.842682 iteration: 32605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13045 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.19833 L1 loss: 0.0000e+00 L2 loss: 0.74003 Learning rate: 0.02 Mask loss: 0.19202 RPN box loss: 0.00862 RPN score loss: 0.00284 RPN total loss: 0.01146 Total loss: 1.14184 timestamp: 1655034174.1097412 iteration: 32610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12014 FastRCNN class loss: 0.0822 FastRCNN total loss: 0.20233 L1 loss: 0.0000e+00 L2 loss: 0.73992 Learning rate: 0.02 Mask loss: 0.10933 RPN box loss: 0.01757 RPN score loss: 0.00214 RPN total loss: 0.0197 Total loss: 1.07129 timestamp: 1655034177.3658135 iteration: 32615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11212 FastRCNN class loss: 0.0831 FastRCNN total loss: 0.19522 L1 loss: 0.0000e+00 L2 loss: 0.73979 Learning rate: 0.02 Mask loss: 0.18434 RPN box loss: 0.02626 RPN score loss: 0.01112 RPN total loss: 0.03738 Total loss: 1.15673 timestamp: 1655034180.6761153 iteration: 32620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16162 FastRCNN class loss: 0.07687 FastRCNN total loss: 0.23849 L1 loss: 0.0000e+00 L2 loss: 0.73968 Learning rate: 0.02 Mask loss: 0.28484 RPN box loss: 0.02734 RPN score loss: 0.00337 RPN total loss: 0.03071 Total loss: 1.29372 timestamp: 1655034183.9522302 iteration: 32625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13751 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.19284 L1 loss: 0.0000e+00 L2 loss: 0.7396 Learning rate: 0.02 Mask loss: 0.14278 RPN box loss: 0.01574 RPN score loss: 0.00776 RPN total loss: 0.02351 Total loss: 1.09873 timestamp: 1655034187.1872678 iteration: 32630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06116 FastRCNN class loss: 0.06702 FastRCNN total loss: 0.12818 L1 loss: 0.0000e+00 L2 loss: 0.73949 Learning rate: 0.02 Mask loss: 0.12834 RPN box loss: 0.02836 RPN score loss: 0.0041 RPN total loss: 0.03247 Total loss: 1.02848 timestamp: 1655034190.4492965 iteration: 32635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11575 FastRCNN class loss: 0.06823 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.73937 Learning rate: 0.02 Mask loss: 0.10693 RPN box loss: 0.00774 RPN score loss: 0.00262 RPN total loss: 0.01035 Total loss: 1.04064 timestamp: 1655034193.6946323 iteration: 32640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17772 FastRCNN class loss: 0.0707 FastRCNN total loss: 0.24842 L1 loss: 0.0000e+00 L2 loss: 0.73926 Learning rate: 0.02 Mask loss: 0.17956 RPN box loss: 0.02971 RPN score loss: 0.00819 RPN total loss: 0.0379 Total loss: 1.20514 timestamp: 1655034196.9903805 iteration: 32645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09788 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.14473 L1 loss: 0.0000e+00 L2 loss: 0.73915 Learning rate: 0.02 Mask loss: 0.10076 RPN box loss: 0.02409 RPN score loss: 0.00765 RPN total loss: 0.03174 Total loss: 1.01638 timestamp: 1655034200.2132218 iteration: 32650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15045 FastRCNN class loss: 0.06213 FastRCNN total loss: 0.21258 L1 loss: 0.0000e+00 L2 loss: 0.73905 Learning rate: 0.02 Mask loss: 0.133 RPN box loss: 0.01479 RPN score loss: 0.00489 RPN total loss: 0.01968 Total loss: 1.10431 timestamp: 1655034203.4860544 iteration: 32655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15072 FastRCNN class loss: 0.05925 FastRCNN total loss: 0.20997 L1 loss: 0.0000e+00 L2 loss: 0.73895 Learning rate: 0.02 Mask loss: 0.1817 RPN box loss: 0.02123 RPN score loss: 0.00565 RPN total loss: 0.02688 Total loss: 1.1575 timestamp: 1655034206.7340696 iteration: 32660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14927 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.23236 L1 loss: 0.0000e+00 L2 loss: 0.73884 Learning rate: 0.02 Mask loss: 0.16224 RPN box loss: 0.01361 RPN score loss: 0.00332 RPN total loss: 0.01693 Total loss: 1.15037 timestamp: 1655034209.9817903 iteration: 32665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18291 FastRCNN class loss: 0.12377 FastRCNN total loss: 0.30668 L1 loss: 0.0000e+00 L2 loss: 0.73873 Learning rate: 0.02 Mask loss: 0.18495 RPN box loss: 0.03853 RPN score loss: 0.01148 RPN total loss: 0.05001 Total loss: 1.28037 timestamp: 1655034213.281915 iteration: 32670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14026 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.21692 L1 loss: 0.0000e+00 L2 loss: 0.7386 Learning rate: 0.02 Mask loss: 0.17117 RPN box loss: 0.05624 RPN score loss: 0.00455 RPN total loss: 0.06079 Total loss: 1.18748 timestamp: 1655034216.584786 iteration: 32675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16451 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.23769 L1 loss: 0.0000e+00 L2 loss: 0.73847 Learning rate: 0.02 Mask loss: 0.1764 RPN box loss: 0.01429 RPN score loss: 0.01171 RPN total loss: 0.02599 Total loss: 1.17856 timestamp: 1655034219.8435502 iteration: 32680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.08246 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 0.73837 Learning rate: 0.02 Mask loss: 0.18267 RPN box loss: 0.03315 RPN score loss: 0.0056 RPN total loss: 0.03875 Total loss: 1.16669 timestamp: 1655034223.1216726 iteration: 32685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0622 FastRCNN class loss: 0.08702 FastRCNN total loss: 0.14922 L1 loss: 0.0000e+00 L2 loss: 0.73827 Learning rate: 0.02 Mask loss: 0.15681 RPN box loss: 0.06482 RPN score loss: 0.00859 RPN total loss: 0.07341 Total loss: 1.11771 timestamp: 1655034226.3696053 iteration: 32690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11999 FastRCNN class loss: 0.14612 FastRCNN total loss: 0.2661 L1 loss: 0.0000e+00 L2 loss: 0.73816 Learning rate: 0.02 Mask loss: 0.18564 RPN box loss: 0.05146 RPN score loss: 0.01508 RPN total loss: 0.06654 Total loss: 1.25644 timestamp: 1655034229.6674657 iteration: 32695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05811 FastRCNN class loss: 0.04536 FastRCNN total loss: 0.10347 L1 loss: 0.0000e+00 L2 loss: 0.73806 Learning rate: 0.02 Mask loss: 0.15148 RPN box loss: 0.0262 RPN score loss: 0.00436 RPN total loss: 0.03055 Total loss: 1.02356 timestamp: 1655034232.8967302 iteration: 32700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10334 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.15774 L1 loss: 0.0000e+00 L2 loss: 0.73794 Learning rate: 0.02 Mask loss: 0.14534 RPN box loss: 0.07373 RPN score loss: 0.00441 RPN total loss: 0.07813 Total loss: 1.11916 timestamp: 1655034236.0903249 iteration: 32705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14293 FastRCNN class loss: 0.10243 FastRCNN total loss: 0.24535 L1 loss: 0.0000e+00 L2 loss: 0.73784 Learning rate: 0.02 Mask loss: 0.1607 RPN box loss: 0.05901 RPN score loss: 0.00694 RPN total loss: 0.06595 Total loss: 1.20984 timestamp: 1655034239.3120553 iteration: 32710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09905 FastRCNN class loss: 0.05385 FastRCNN total loss: 0.1529 L1 loss: 0.0000e+00 L2 loss: 0.73774 Learning rate: 0.02 Mask loss: 0.14078 RPN box loss: 0.02411 RPN score loss: 0.00308 RPN total loss: 0.02719 Total loss: 1.05862 timestamp: 1655034242.551112 iteration: 32715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.1159 FastRCNN total loss: 0.25546 L1 loss: 0.0000e+00 L2 loss: 0.73762 Learning rate: 0.02 Mask loss: 0.10323 RPN box loss: 0.03541 RPN score loss: 0.01016 RPN total loss: 0.04557 Total loss: 1.14187 timestamp: 1655034245.8222826 iteration: 32720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09119 FastRCNN class loss: 0.07801 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 0.73752 Learning rate: 0.02 Mask loss: 0.15569 RPN box loss: 0.04994 RPN score loss: 0.01303 RPN total loss: 0.06296 Total loss: 1.12537 timestamp: 1655034249.0905893 iteration: 32725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10103 FastRCNN class loss: 0.09482 FastRCNN total loss: 0.19585 L1 loss: 0.0000e+00 L2 loss: 0.73742 Learning rate: 0.02 Mask loss: 0.17791 RPN box loss: 0.05702 RPN score loss: 0.00899 RPN total loss: 0.066 Total loss: 1.17719 timestamp: 1655034252.3332915 iteration: 32730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13058 FastRCNN class loss: 0.05923 FastRCNN total loss: 0.18981 L1 loss: 0.0000e+00 L2 loss: 0.73731 Learning rate: 0.02 Mask loss: 0.1026 RPN box loss: 0.03609 RPN score loss: 0.0123 RPN total loss: 0.04839 Total loss: 1.07811 timestamp: 1655034255.5979402 iteration: 32735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13831 FastRCNN class loss: 0.0796 FastRCNN total loss: 0.21791 L1 loss: 0.0000e+00 L2 loss: 0.7372 Learning rate: 0.02 Mask loss: 0.16229 RPN box loss: 0.00832 RPN score loss: 0.00637 RPN total loss: 0.01468 Total loss: 1.13208 timestamp: 1655034258.890349 iteration: 32740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19214 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.27875 L1 loss: 0.0000e+00 L2 loss: 0.73711 Learning rate: 0.02 Mask loss: 0.1715 RPN box loss: 0.05567 RPN score loss: 0.00378 RPN total loss: 0.05945 Total loss: 1.2468 timestamp: 1655034262.212509 iteration: 32745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1974 FastRCNN class loss: 0.12061 FastRCNN total loss: 0.31801 L1 loss: 0.0000e+00 L2 loss: 0.73699 Learning rate: 0.02 Mask loss: 0.18489 RPN box loss: 0.1221 RPN score loss: 0.00792 RPN total loss: 0.13001 Total loss: 1.36991 timestamp: 1655034265.4793053 iteration: 32750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16356 FastRCNN class loss: 0.07322 FastRCNN total loss: 0.23677 L1 loss: 0.0000e+00 L2 loss: 0.73687 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.06213 RPN score loss: 0.00553 RPN total loss: 0.06766 Total loss: 1.18425 timestamp: 1655034268.7165291 iteration: 32755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20857 FastRCNN class loss: 0.07829 FastRCNN total loss: 0.28685 L1 loss: 0.0000e+00 L2 loss: 0.73679 Learning rate: 0.02 Mask loss: 0.23573 RPN box loss: 0.02185 RPN score loss: 0.01004 RPN total loss: 0.03189 Total loss: 1.29127 timestamp: 1655034272.100103 iteration: 32760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14616 FastRCNN class loss: 0.11129 FastRCNN total loss: 0.25745 L1 loss: 0.0000e+00 L2 loss: 0.73671 Learning rate: 0.02 Mask loss: 0.15204 RPN box loss: 0.02637 RPN score loss: 0.00801 RPN total loss: 0.03438 Total loss: 1.18058 timestamp: 1655034275.445902 iteration: 32765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16389 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.24911 L1 loss: 0.0000e+00 L2 loss: 0.7366 Learning rate: 0.02 Mask loss: 0.19079 RPN box loss: 0.03064 RPN score loss: 0.00381 RPN total loss: 0.03445 Total loss: 1.21095 timestamp: 1655034278.767601 iteration: 32770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12787 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.21868 L1 loss: 0.0000e+00 L2 loss: 0.73649 Learning rate: 0.02 Mask loss: 0.14912 RPN box loss: 0.0199 RPN score loss: 0.00394 RPN total loss: 0.02384 Total loss: 1.12812 timestamp: 1655034282.1469598 iteration: 32775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.11909 FastRCNN total loss: 0.23057 L1 loss: 0.0000e+00 L2 loss: 0.73638 Learning rate: 0.02 Mask loss: 0.16105 RPN box loss: 0.02553 RPN score loss: 0.00967 RPN total loss: 0.0352 Total loss: 1.1632 timestamp: 1655034285.4114687 iteration: 32780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09807 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.15675 L1 loss: 0.0000e+00 L2 loss: 0.73626 Learning rate: 0.02 Mask loss: 0.11656 RPN box loss: 0.02611 RPN score loss: 0.00132 RPN total loss: 0.02743 Total loss: 1.03701 timestamp: 1655034288.6674232 iteration: 32785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.17218 L1 loss: 0.0000e+00 L2 loss: 0.73616 Learning rate: 0.02 Mask loss: 0.12816 RPN box loss: 0.04479 RPN score loss: 0.00611 RPN total loss: 0.05089 Total loss: 1.08739 timestamp: 1655034291.8906157 iteration: 32790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1083 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.17239 L1 loss: 0.0000e+00 L2 loss: 0.73605 Learning rate: 0.02 Mask loss: 0.14676 RPN box loss: 0.01625 RPN score loss: 0.00428 RPN total loss: 0.02054 Total loss: 1.07574 timestamp: 1655034295.1925275 iteration: 32795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10495 FastRCNN class loss: 0.04509 FastRCNN total loss: 0.15005 L1 loss: 0.0000e+00 L2 loss: 0.73594 Learning rate: 0.02 Mask loss: 0.17255 RPN box loss: 0.00917 RPN score loss: 0.0043 RPN total loss: 0.01347 Total loss: 1.07201 timestamp: 1655034298.5143092 iteration: 32800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15801 FastRCNN class loss: 0.10902 FastRCNN total loss: 0.26703 L1 loss: 0.0000e+00 L2 loss: 0.73585 Learning rate: 0.02 Mask loss: 0.2285 RPN box loss: 0.03666 RPN score loss: 0.00551 RPN total loss: 0.04216 Total loss: 1.27354 timestamp: 1655034301.8379207 iteration: 32805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08974 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.1609 L1 loss: 0.0000e+00 L2 loss: 0.73574 Learning rate: 0.02 Mask loss: 0.11304 RPN box loss: 0.01421 RPN score loss: 0.00272 RPN total loss: 0.01693 Total loss: 1.0266 timestamp: 1655034305.1526496 iteration: 32810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14387 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.24693 L1 loss: 0.0000e+00 L2 loss: 0.73563 Learning rate: 0.02 Mask loss: 0.21479 RPN box loss: 0.06194 RPN score loss: 0.00939 RPN total loss: 0.07133 Total loss: 1.26869 timestamp: 1655034308.4229338 iteration: 32815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1278 FastRCNN class loss: 0.07103 FastRCNN total loss: 0.19883 L1 loss: 0.0000e+00 L2 loss: 0.73553 Learning rate: 0.02 Mask loss: 0.20563 RPN box loss: 0.03145 RPN score loss: 0.00389 RPN total loss: 0.03533 Total loss: 1.17531 timestamp: 1655034311.685982 iteration: 32820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19362 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.26391 L1 loss: 0.0000e+00 L2 loss: 0.73543 Learning rate: 0.02 Mask loss: 0.12398 RPN box loss: 0.02406 RPN score loss: 0.00266 RPN total loss: 0.02672 Total loss: 1.15004 timestamp: 1655034314.9545014 iteration: 32825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08644 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.15274 L1 loss: 0.0000e+00 L2 loss: 0.73531 Learning rate: 0.02 Mask loss: 0.15364 RPN box loss: 0.0178 RPN score loss: 0.00565 RPN total loss: 0.02345 Total loss: 1.06514 timestamp: 1655034318.2629535 iteration: 32830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11524 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.19143 L1 loss: 0.0000e+00 L2 loss: 0.73521 Learning rate: 0.02 Mask loss: 0.17468 RPN box loss: 0.04483 RPN score loss: 0.00754 RPN total loss: 0.05237 Total loss: 1.15369 timestamp: 1655034321.5610957 iteration: 32835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14285 FastRCNN class loss: 0.09301 FastRCNN total loss: 0.23587 L1 loss: 0.0000e+00 L2 loss: 0.73509 Learning rate: 0.02 Mask loss: 0.11836 RPN box loss: 0.0287 RPN score loss: 0.0024 RPN total loss: 0.03111 Total loss: 1.12042 timestamp: 1655034324.7995927 iteration: 32840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19311 FastRCNN class loss: 0.1224 FastRCNN total loss: 0.31551 L1 loss: 0.0000e+00 L2 loss: 0.73498 Learning rate: 0.02 Mask loss: 0.28381 RPN box loss: 0.03435 RPN score loss: 0.02179 RPN total loss: 0.05614 Total loss: 1.39043 timestamp: 1655034328.1199102 iteration: 32845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.14454 L1 loss: 0.0000e+00 L2 loss: 0.73486 Learning rate: 0.02 Mask loss: 0.11779 RPN box loss: 0.03731 RPN score loss: 0.00892 RPN total loss: 0.04622 Total loss: 1.04342 timestamp: 1655034331.3782418 iteration: 32850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13075 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.1955 L1 loss: 0.0000e+00 L2 loss: 0.73474 Learning rate: 0.02 Mask loss: 0.1599 RPN box loss: 0.0336 RPN score loss: 0.00527 RPN total loss: 0.03887 Total loss: 1.12901 timestamp: 1655034334.594395 iteration: 32855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13862 FastRCNN class loss: 0.10507 FastRCNN total loss: 0.24369 L1 loss: 0.0000e+00 L2 loss: 0.73465 Learning rate: 0.02 Mask loss: 0.16999 RPN box loss: 0.04855 RPN score loss: 0.01453 RPN total loss: 0.06308 Total loss: 1.2114 timestamp: 1655034337.9133332 iteration: 32860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.21691 L1 loss: 0.0000e+00 L2 loss: 0.73456 Learning rate: 0.02 Mask loss: 0.10586 RPN box loss: 0.01962 RPN score loss: 0.00607 RPN total loss: 0.02569 Total loss: 1.08302 timestamp: 1655034341.1863515 iteration: 32865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1084 FastRCNN class loss: 0.06775 FastRCNN total loss: 0.17615 L1 loss: 0.0000e+00 L2 loss: 0.73446 Learning rate: 0.02 Mask loss: 0.16448 RPN box loss: 0.03083 RPN score loss: 0.00173 RPN total loss: 0.03256 Total loss: 1.10766 timestamp: 1655034344.3945508 iteration: 32870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13679 FastRCNN class loss: 0.07794 FastRCNN total loss: 0.21473 L1 loss: 0.0000e+00 L2 loss: 0.73439 Learning rate: 0.02 Mask loss: 0.17164 RPN box loss: 0.07606 RPN score loss: 0.00643 RPN total loss: 0.0825 Total loss: 1.20326 timestamp: 1655034347.6368568 iteration: 32875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13037 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.20615 L1 loss: 0.0000e+00 L2 loss: 0.73427 Learning rate: 0.02 Mask loss: 0.1247 RPN box loss: 0.0351 RPN score loss: 0.0044 RPN total loss: 0.0395 Total loss: 1.10462 timestamp: 1655034350.8447702 iteration: 32880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10143 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.1605 L1 loss: 0.0000e+00 L2 loss: 0.73415 Learning rate: 0.02 Mask loss: 0.12879 RPN box loss: 0.00467 RPN score loss: 0.00242 RPN total loss: 0.00709 Total loss: 1.03053 timestamp: 1655034354.1519585 iteration: 32885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15606 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.22021 L1 loss: 0.0000e+00 L2 loss: 0.73406 Learning rate: 0.02 Mask loss: 0.19079 RPN box loss: 0.01601 RPN score loss: 0.00597 RPN total loss: 0.02198 Total loss: 1.16704 timestamp: 1655034357.3869476 iteration: 32890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19045 FastRCNN class loss: 0.11091 FastRCNN total loss: 0.30136 L1 loss: 0.0000e+00 L2 loss: 0.73395 Learning rate: 0.02 Mask loss: 0.24004 RPN box loss: 0.01582 RPN score loss: 0.00648 RPN total loss: 0.0223 Total loss: 1.29765 timestamp: 1655034360.6497967 iteration: 32895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1292 FastRCNN class loss: 0.08275 FastRCNN total loss: 0.21195 L1 loss: 0.0000e+00 L2 loss: 0.73383 Learning rate: 0.02 Mask loss: 0.14319 RPN box loss: 0.09487 RPN score loss: 0.0098 RPN total loss: 0.10466 Total loss: 1.19363 timestamp: 1655034363.9620042 iteration: 32900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1304 FastRCNN class loss: 0.09508 FastRCNN total loss: 0.22548 L1 loss: 0.0000e+00 L2 loss: 0.73372 Learning rate: 0.02 Mask loss: 0.17952 RPN box loss: 0.05553 RPN score loss: 0.01289 RPN total loss: 0.06843 Total loss: 1.20715 timestamp: 1655034367.2628124 iteration: 32905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13175 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.20833 L1 loss: 0.0000e+00 L2 loss: 0.7336 Learning rate: 0.02 Mask loss: 0.14606 RPN box loss: 0.09785 RPN score loss: 0.01036 RPN total loss: 0.10821 Total loss: 1.1962 timestamp: 1655034370.513248 iteration: 32910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20528 FastRCNN class loss: 0.11969 FastRCNN total loss: 0.32497 L1 loss: 0.0000e+00 L2 loss: 0.7335 Learning rate: 0.02 Mask loss: 0.23523 RPN box loss: 0.04116 RPN score loss: 0.0144 RPN total loss: 0.05556 Total loss: 1.34926 timestamp: 1655034373.688728 iteration: 32915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06095 FastRCNN class loss: 0.03801 FastRCNN total loss: 0.09896 L1 loss: 0.0000e+00 L2 loss: 0.73341 Learning rate: 0.02 Mask loss: 0.10302 RPN box loss: 0.0077 RPN score loss: 0.0021 RPN total loss: 0.00979 Total loss: 0.94519 timestamp: 1655034376.9826798 iteration: 32920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14202 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.21621 L1 loss: 0.0000e+00 L2 loss: 0.7333 Learning rate: 0.02 Mask loss: 0.18599 RPN box loss: 0.05447 RPN score loss: 0.01276 RPN total loss: 0.06723 Total loss: 1.20273 timestamp: 1655034380.2406578 iteration: 32925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2111 FastRCNN class loss: 0.09134 FastRCNN total loss: 0.30244 L1 loss: 0.0000e+00 L2 loss: 0.73318 Learning rate: 0.02 Mask loss: 0.32579 RPN box loss: 0.04804 RPN score loss: 0.00434 RPN total loss: 0.05238 Total loss: 1.41379 timestamp: 1655034383.471749 iteration: 32930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13 FastRCNN class loss: 0.08329 FastRCNN total loss: 0.21329 L1 loss: 0.0000e+00 L2 loss: 0.7331 Learning rate: 0.02 Mask loss: 0.21421 RPN box loss: 0.07352 RPN score loss: 0.00492 RPN total loss: 0.07845 Total loss: 1.23904 timestamp: 1655034386.753383 iteration: 32935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11477 FastRCNN class loss: 0.10131 FastRCNN total loss: 0.21608 L1 loss: 0.0000e+00 L2 loss: 0.73299 Learning rate: 0.02 Mask loss: 0.14184 RPN box loss: 0.02691 RPN score loss: 0.00723 RPN total loss: 0.03414 Total loss: 1.12505 timestamp: 1655034390.013651 iteration: 32940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11258 FastRCNN class loss: 0.04304 FastRCNN total loss: 0.15562 L1 loss: 0.0000e+00 L2 loss: 0.73285 Learning rate: 0.02 Mask loss: 0.3056 RPN box loss: 0.03113 RPN score loss: 0.00395 RPN total loss: 0.03507 Total loss: 1.22913 timestamp: 1655034393.3728704 iteration: 32945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16213 FastRCNN class loss: 0.11395 FastRCNN total loss: 0.27608 L1 loss: 0.0000e+00 L2 loss: 0.73273 Learning rate: 0.02 Mask loss: 0.24737 RPN box loss: 0.03269 RPN score loss: 0.02056 RPN total loss: 0.05325 Total loss: 1.30944 timestamp: 1655034396.7370045 iteration: 32950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11117 FastRCNN class loss: 0.06724 FastRCNN total loss: 0.17841 L1 loss: 0.0000e+00 L2 loss: 0.73263 Learning rate: 0.02 Mask loss: 0.14021 RPN box loss: 0.08926 RPN score loss: 0.00617 RPN total loss: 0.09543 Total loss: 1.14668 timestamp: 1655034400.0815313 iteration: 32955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16219 FastRCNN class loss: 0.10324 FastRCNN total loss: 0.26543 L1 loss: 0.0000e+00 L2 loss: 0.73252 Learning rate: 0.02 Mask loss: 0.1547 RPN box loss: 0.01202 RPN score loss: 0.00496 RPN total loss: 0.01698 Total loss: 1.16963 timestamp: 1655034403.3539546 iteration: 32960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08404 FastRCNN class loss: 0.06381 FastRCNN total loss: 0.14784 L1 loss: 0.0000e+00 L2 loss: 0.73241 Learning rate: 0.02 Mask loss: 0.13088 RPN box loss: 0.01602 RPN score loss: 0.00599 RPN total loss: 0.02201 Total loss: 1.03313 timestamp: 1655034406.5739717 iteration: 32965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16716 FastRCNN class loss: 0.10839 FastRCNN total loss: 0.27555 L1 loss: 0.0000e+00 L2 loss: 0.73231 Learning rate: 0.02 Mask loss: 0.24365 RPN box loss: 0.03304 RPN score loss: 0.00504 RPN total loss: 0.03808 Total loss: 1.28958 timestamp: 1655034409.846946 iteration: 32970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17212 FastRCNN class loss: 0.10206 FastRCNN total loss: 0.27418 L1 loss: 0.0000e+00 L2 loss: 0.73221 Learning rate: 0.02 Mask loss: 0.18806 RPN box loss: 0.02897 RPN score loss: 0.01163 RPN total loss: 0.0406 Total loss: 1.23505 timestamp: 1655034413.107265 iteration: 32975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1407 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.19615 L1 loss: 0.0000e+00 L2 loss: 0.73211 Learning rate: 0.02 Mask loss: 0.14331 RPN box loss: 0.00474 RPN score loss: 0.00538 RPN total loss: 0.01011 Total loss: 1.08169 timestamp: 1655034416.4332275 iteration: 32980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24399 FastRCNN class loss: 0.09102 FastRCNN total loss: 0.335 L1 loss: 0.0000e+00 L2 loss: 0.73201 Learning rate: 0.02 Mask loss: 0.21026 RPN box loss: 0.01316 RPN score loss: 0.00537 RPN total loss: 0.01853 Total loss: 1.2958 timestamp: 1655034419.7276995 iteration: 32985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11771 FastRCNN class loss: 0.08216 FastRCNN total loss: 0.19987 L1 loss: 0.0000e+00 L2 loss: 0.73189 Learning rate: 0.02 Mask loss: 0.16244 RPN box loss: 0.01545 RPN score loss: 0.003 RPN total loss: 0.01844 Total loss: 1.11264 timestamp: 1655034422.9685774 iteration: 32990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12925 FastRCNN class loss: 0.07276 FastRCNN total loss: 0.20201 L1 loss: 0.0000e+00 L2 loss: 0.73179 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.02805 RPN score loss: 0.00474 RPN total loss: 0.03279 Total loss: 1.12084 timestamp: 1655034426.2607906 iteration: 32995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.15775 L1 loss: 0.0000e+00 L2 loss: 0.73169 Learning rate: 0.02 Mask loss: 0.12743 RPN box loss: 0.083 RPN score loss: 0.00624 RPN total loss: 0.08924 Total loss: 1.1061 timestamp: 1655034429.5338607 iteration: 33000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13674 FastRCNN class loss: 0.11307 FastRCNN total loss: 0.24981 L1 loss: 0.0000e+00 L2 loss: 0.73161 Learning rate: 0.02 Mask loss: 0.15691 RPN box loss: 0.03231 RPN score loss: 0.00624 RPN total loss: 0.03855 Total loss: 1.17688 timestamp: 1655034432.8078427 iteration: 33005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12949 FastRCNN class loss: 0.09004 FastRCNN total loss: 0.21953 L1 loss: 0.0000e+00 L2 loss: 0.73152 Learning rate: 0.02 Mask loss: 0.21426 RPN box loss: 0.01353 RPN score loss: 0.01167 RPN total loss: 0.0252 Total loss: 1.19051 timestamp: 1655034436.0934277 iteration: 33010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13002 FastRCNN class loss: 0.13457 FastRCNN total loss: 0.26459 L1 loss: 0.0000e+00 L2 loss: 0.73141 Learning rate: 0.02 Mask loss: 0.30375 RPN box loss: 0.0344 RPN score loss: 0.01374 RPN total loss: 0.04814 Total loss: 1.34789 timestamp: 1655034439.333558 iteration: 33015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17803 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.26236 L1 loss: 0.0000e+00 L2 loss: 0.7313 Learning rate: 0.02 Mask loss: 0.1368 RPN box loss: 0.02157 RPN score loss: 0.00795 RPN total loss: 0.02952 Total loss: 1.15999 timestamp: 1655034442.5330288 iteration: 33020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08919 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.14037 L1 loss: 0.0000e+00 L2 loss: 0.73119 Learning rate: 0.02 Mask loss: 0.13182 RPN box loss: 0.0082 RPN score loss: 0.00276 RPN total loss: 0.01096 Total loss: 1.01433 timestamp: 1655034445.7852848 iteration: 33025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19291 FastRCNN class loss: 0.10805 FastRCNN total loss: 0.30097 L1 loss: 0.0000e+00 L2 loss: 0.73106 Learning rate: 0.02 Mask loss: 0.16788 RPN box loss: 0.03057 RPN score loss: 0.00498 RPN total loss: 0.03556 Total loss: 1.23546 timestamp: 1655034449.0744865 iteration: 33030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10471 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.16888 L1 loss: 0.0000e+00 L2 loss: 0.73097 Learning rate: 0.02 Mask loss: 0.20145 RPN box loss: 0.03562 RPN score loss: 0.01337 RPN total loss: 0.04899 Total loss: 1.15029 timestamp: 1655034452.326223 iteration: 33035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12011 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.18298 L1 loss: 0.0000e+00 L2 loss: 0.73088 Learning rate: 0.02 Mask loss: 0.13613 RPN box loss: 0.01196 RPN score loss: 0.00324 RPN total loss: 0.0152 Total loss: 1.0652 timestamp: 1655034455.595285 iteration: 33040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20336 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.28638 L1 loss: 0.0000e+00 L2 loss: 0.7308 Learning rate: 0.02 Mask loss: 0.16056 RPN box loss: 0.04492 RPN score loss: 0.00817 RPN total loss: 0.05309 Total loss: 1.23083 timestamp: 1655034458.8558269 iteration: 33045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.26964 FastRCNN class loss: 0.09468 FastRCNN total loss: 0.36431 L1 loss: 0.0000e+00 L2 loss: 0.73065 Learning rate: 0.02 Mask loss: 0.18454 RPN box loss: 0.04542 RPN score loss: 0.00805 RPN total loss: 0.05347 Total loss: 1.33298 timestamp: 1655034462.0983927 iteration: 33050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17206 FastRCNN class loss: 0.08824 FastRCNN total loss: 0.2603 L1 loss: 0.0000e+00 L2 loss: 0.73053 Learning rate: 0.02 Mask loss: 0.17832 RPN box loss: 0.04203 RPN score loss: 0.01027 RPN total loss: 0.0523 Total loss: 1.22144 timestamp: 1655034465.3378212 iteration: 33055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10947 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.16422 L1 loss: 0.0000e+00 L2 loss: 0.73042 Learning rate: 0.02 Mask loss: 0.14951 RPN box loss: 0.05426 RPN score loss: 0.01726 RPN total loss: 0.07152 Total loss: 1.11566 timestamp: 1655034468.61926 iteration: 33060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21456 FastRCNN class loss: 0.07657 FastRCNN total loss: 0.29113 L1 loss: 0.0000e+00 L2 loss: 0.7303 Learning rate: 0.02 Mask loss: 0.13947 RPN box loss: 0.02232 RPN score loss: 0.01285 RPN total loss: 0.03517 Total loss: 1.19608 timestamp: 1655034471.9674597 iteration: 33065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16287 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.23233 L1 loss: 0.0000e+00 L2 loss: 0.73021 Learning rate: 0.02 Mask loss: 0.15244 RPN box loss: 0.01541 RPN score loss: 0.00764 RPN total loss: 0.02305 Total loss: 1.13803 timestamp: 1655034475.237763 iteration: 33070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1852 FastRCNN class loss: 0.08703 FastRCNN total loss: 0.27223 L1 loss: 0.0000e+00 L2 loss: 0.73011 Learning rate: 0.02 Mask loss: 0.17944 RPN box loss: 0.04868 RPN score loss: 0.0154 RPN total loss: 0.06408 Total loss: 1.24586 timestamp: 1655034478.5485737 iteration: 33075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15705 FastRCNN class loss: 0.08281 FastRCNN total loss: 0.23986 L1 loss: 0.0000e+00 L2 loss: 0.73005 Learning rate: 0.02 Mask loss: 0.16024 RPN box loss: 0.04609 RPN score loss: 0.00758 RPN total loss: 0.05367 Total loss: 1.18382 timestamp: 1655034481.8243625 iteration: 33080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17039 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.2357 L1 loss: 0.0000e+00 L2 loss: 0.72996 Learning rate: 0.02 Mask loss: 0.15906 RPN box loss: 0.01604 RPN score loss: 0.0052 RPN total loss: 0.02124 Total loss: 1.14596 timestamp: 1655034485.1093292 iteration: 33085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16831 FastRCNN class loss: 0.0997 FastRCNN total loss: 0.26801 L1 loss: 0.0000e+00 L2 loss: 0.72984 Learning rate: 0.02 Mask loss: 0.17266 RPN box loss: 0.04043 RPN score loss: 0.00807 RPN total loss: 0.0485 Total loss: 1.21901 timestamp: 1655034488.415297 iteration: 33090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08921 FastRCNN class loss: 0.04512 FastRCNN total loss: 0.13432 L1 loss: 0.0000e+00 L2 loss: 0.72971 Learning rate: 0.02 Mask loss: 0.13628 RPN box loss: 0.03748 RPN score loss: 0.00462 RPN total loss: 0.0421 Total loss: 1.04242 timestamp: 1655034491.687019 iteration: 33095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15708 FastRCNN class loss: 0.10853 FastRCNN total loss: 0.26561 L1 loss: 0.0000e+00 L2 loss: 0.72959 Learning rate: 0.02 Mask loss: 0.29255 RPN box loss: 0.02576 RPN score loss: 0.0056 RPN total loss: 0.03136 Total loss: 1.31911 timestamp: 1655034494.9343436 iteration: 33100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07194 FastRCNN class loss: 0.0908 FastRCNN total loss: 0.16274 L1 loss: 0.0000e+00 L2 loss: 0.72948 Learning rate: 0.02 Mask loss: 0.18993 RPN box loss: 0.04027 RPN score loss: 0.02474 RPN total loss: 0.06501 Total loss: 1.14716 timestamp: 1655034498.2023604 iteration: 33105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15581 FastRCNN class loss: 0.12028 FastRCNN total loss: 0.27609 L1 loss: 0.0000e+00 L2 loss: 0.72937 Learning rate: 0.02 Mask loss: 0.16819 RPN box loss: 0.11768 RPN score loss: 0.01336 RPN total loss: 0.13104 Total loss: 1.3047 timestamp: 1655034501.4876273 iteration: 33110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20699 FastRCNN class loss: 0.12615 FastRCNN total loss: 0.33314 L1 loss: 0.0000e+00 L2 loss: 0.72925 Learning rate: 0.02 Mask loss: 0.16916 RPN box loss: 0.04693 RPN score loss: 0.00741 RPN total loss: 0.05434 Total loss: 1.28588 timestamp: 1655034504.7160676 iteration: 33115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10484 FastRCNN class loss: 0.05472 FastRCNN total loss: 0.15956 L1 loss: 0.0000e+00 L2 loss: 0.72917 Learning rate: 0.02 Mask loss: 0.11906 RPN box loss: 0.05153 RPN score loss: 0.00852 RPN total loss: 0.06005 Total loss: 1.06785 timestamp: 1655034507.9686491 iteration: 33120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16108 FastRCNN class loss: 0.08191 FastRCNN total loss: 0.24299 L1 loss: 0.0000e+00 L2 loss: 0.72908 Learning rate: 0.02 Mask loss: 0.14775 RPN box loss: 0.03462 RPN score loss: 0.01292 RPN total loss: 0.04754 Total loss: 1.16736 timestamp: 1655034511.2031374 iteration: 33125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10748 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.19705 L1 loss: 0.0000e+00 L2 loss: 0.72898 Learning rate: 0.02 Mask loss: 0.11818 RPN box loss: 0.04549 RPN score loss: 0.00303 RPN total loss: 0.04852 Total loss: 1.09273 timestamp: 1655034514.4453597 iteration: 33130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06823 FastRCNN class loss: 0.02833 FastRCNN total loss: 0.09656 L1 loss: 0.0000e+00 L2 loss: 0.72887 Learning rate: 0.02 Mask loss: 0.09811 RPN box loss: 0.03231 RPN score loss: 0.00199 RPN total loss: 0.0343 Total loss: 0.95784 timestamp: 1655034517.6937058 iteration: 33135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14134 FastRCNN class loss: 0.06487 FastRCNN total loss: 0.20621 L1 loss: 0.0000e+00 L2 loss: 0.72877 Learning rate: 0.02 Mask loss: 0.2008 RPN box loss: 0.05592 RPN score loss: 0.00943 RPN total loss: 0.06535 Total loss: 1.20113 timestamp: 1655034521.0193386 iteration: 33140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15604 FastRCNN class loss: 0.10372 FastRCNN total loss: 0.25976 L1 loss: 0.0000e+00 L2 loss: 0.72866 Learning rate: 0.02 Mask loss: 0.19509 RPN box loss: 0.05539 RPN score loss: 0.017 RPN total loss: 0.07239 Total loss: 1.2559 timestamp: 1655034524.321849 iteration: 33145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19934 FastRCNN class loss: 0.13061 FastRCNN total loss: 0.32995 L1 loss: 0.0000e+00 L2 loss: 0.72855 Learning rate: 0.02 Mask loss: 0.25769 RPN box loss: 0.04309 RPN score loss: 0.01243 RPN total loss: 0.05552 Total loss: 1.37171 timestamp: 1655034527.6642456 iteration: 33150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1532 FastRCNN class loss: 0.12381 FastRCNN total loss: 0.27701 L1 loss: 0.0000e+00 L2 loss: 0.72843 Learning rate: 0.02 Mask loss: 0.2242 RPN box loss: 0.07078 RPN score loss: 0.01397 RPN total loss: 0.08475 Total loss: 1.31439 timestamp: 1655034530.8959718 iteration: 33155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16177 FastRCNN class loss: 0.10559 FastRCNN total loss: 0.26736 L1 loss: 0.0000e+00 L2 loss: 0.72835 Learning rate: 0.02 Mask loss: 0.1827 RPN box loss: 0.03254 RPN score loss: 0.00855 RPN total loss: 0.0411 Total loss: 1.21951 timestamp: 1655034534.2735188 iteration: 33160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13027 FastRCNN class loss: 0.12536 FastRCNN total loss: 0.25563 L1 loss: 0.0000e+00 L2 loss: 0.72824 Learning rate: 0.02 Mask loss: 0.18969 RPN box loss: 0.04914 RPN score loss: 0.0207 RPN total loss: 0.06984 Total loss: 1.24341 timestamp: 1655034537.4438512 iteration: 33165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1818 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.25152 L1 loss: 0.0000e+00 L2 loss: 0.72815 Learning rate: 0.02 Mask loss: 0.17652 RPN box loss: 0.03211 RPN score loss: 0.00856 RPN total loss: 0.04067 Total loss: 1.19686 timestamp: 1655034540.7499938 iteration: 33170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1716 FastRCNN class loss: 0.1037 FastRCNN total loss: 0.2753 L1 loss: 0.0000e+00 L2 loss: 0.72804 Learning rate: 0.02 Mask loss: 0.14828 RPN box loss: 0.07758 RPN score loss: 0.0107 RPN total loss: 0.08827 Total loss: 1.23989 timestamp: 1655034543.997128 iteration: 33175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10034 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.18513 L1 loss: 0.0000e+00 L2 loss: 0.72793 Learning rate: 0.02 Mask loss: 0.16565 RPN box loss: 0.05102 RPN score loss: 0.00906 RPN total loss: 0.06008 Total loss: 1.1388 timestamp: 1655034547.2946568 iteration: 33180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12955 FastRCNN class loss: 0.11932 FastRCNN total loss: 0.24887 L1 loss: 0.0000e+00 L2 loss: 0.72784 Learning rate: 0.02 Mask loss: 0.23163 RPN box loss: 0.03052 RPN score loss: 0.01155 RPN total loss: 0.04207 Total loss: 1.2504 timestamp: 1655034550.5939329 iteration: 33185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14329 FastRCNN class loss: 0.11872 FastRCNN total loss: 0.26201 L1 loss: 0.0000e+00 L2 loss: 0.72774 Learning rate: 0.02 Mask loss: 0.16584 RPN box loss: 0.04306 RPN score loss: 0.01299 RPN total loss: 0.05605 Total loss: 1.21164 timestamp: 1655034553.914494 iteration: 33190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17315 FastRCNN class loss: 0.14862 FastRCNN total loss: 0.32177 L1 loss: 0.0000e+00 L2 loss: 0.72766 Learning rate: 0.02 Mask loss: 0.20015 RPN box loss: 0.03401 RPN score loss: 0.02385 RPN total loss: 0.05786 Total loss: 1.30744 timestamp: 1655034557.2165644 iteration: 33195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14677 FastRCNN class loss: 0.11842 FastRCNN total loss: 0.2652 L1 loss: 0.0000e+00 L2 loss: 0.72754 Learning rate: 0.02 Mask loss: 0.16735 RPN box loss: 0.00663 RPN score loss: 0.00475 RPN total loss: 0.01138 Total loss: 1.17147 timestamp: 1655034560.508444 iteration: 33200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15377 FastRCNN class loss: 0.07747 FastRCNN total loss: 0.23124 L1 loss: 0.0000e+00 L2 loss: 0.72745 Learning rate: 0.02 Mask loss: 0.19587 RPN box loss: 0.03019 RPN score loss: 0.00838 RPN total loss: 0.03857 Total loss: 1.19313 timestamp: 1655034563.7716002 iteration: 33205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1703 FastRCNN class loss: 0.0717 FastRCNN total loss: 0.242 L1 loss: 0.0000e+00 L2 loss: 0.72735 Learning rate: 0.02 Mask loss: 0.17859 RPN box loss: 0.02846 RPN score loss: 0.00763 RPN total loss: 0.03608 Total loss: 1.18402 timestamp: 1655034567.0992084 iteration: 33210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09019 FastRCNN class loss: 0.07179 FastRCNN total loss: 0.16198 L1 loss: 0.0000e+00 L2 loss: 0.72723 Learning rate: 0.02 Mask loss: 0.10628 RPN box loss: 0.01413 RPN score loss: 0.00195 RPN total loss: 0.01608 Total loss: 1.01157 timestamp: 1655034570.3048387 iteration: 33215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16638 FastRCNN class loss: 0.12814 FastRCNN total loss: 0.29452 L1 loss: 0.0000e+00 L2 loss: 0.72713 Learning rate: 0.02 Mask loss: 0.1539 RPN box loss: 0.02094 RPN score loss: 0.0077 RPN total loss: 0.02864 Total loss: 1.20419 timestamp: 1655034573.6671805 iteration: 33220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18358 FastRCNN class loss: 0.12017 FastRCNN total loss: 0.30375 L1 loss: 0.0000e+00 L2 loss: 0.72703 Learning rate: 0.02 Mask loss: 0.228 RPN box loss: 0.06741 RPN score loss: 0.00696 RPN total loss: 0.07437 Total loss: 1.33315 timestamp: 1655034576.88146 iteration: 33225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.1436 L1 loss: 0.0000e+00 L2 loss: 0.7269 Learning rate: 0.02 Mask loss: 0.1688 RPN box loss: 0.03 RPN score loss: 0.00646 RPN total loss: 0.03646 Total loss: 1.07576 timestamp: 1655034580.1329916 iteration: 33230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13291 FastRCNN class loss: 0.08573 FastRCNN total loss: 0.21864 L1 loss: 0.0000e+00 L2 loss: 0.72682 Learning rate: 0.02 Mask loss: 0.09762 RPN box loss: 0.01037 RPN score loss: 0.00158 RPN total loss: 0.01195 Total loss: 1.05502 timestamp: 1655034583.480775 iteration: 33235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.22798 L1 loss: 0.0000e+00 L2 loss: 0.72672 Learning rate: 0.02 Mask loss: 0.25739 RPN box loss: 0.04318 RPN score loss: 0.0056 RPN total loss: 0.04878 Total loss: 1.26087 timestamp: 1655034586.7190588 iteration: 33240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15081 FastRCNN class loss: 0.10068 FastRCNN total loss: 0.25148 L1 loss: 0.0000e+00 L2 loss: 0.7266 Learning rate: 0.02 Mask loss: 0.26036 RPN box loss: 0.02726 RPN score loss: 0.0132 RPN total loss: 0.04046 Total loss: 1.2789 timestamp: 1655034589.9454622 iteration: 33245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14092 FastRCNN class loss: 0.08786 FastRCNN total loss: 0.22877 L1 loss: 0.0000e+00 L2 loss: 0.72648 Learning rate: 0.02 Mask loss: 0.13667 RPN box loss: 0.04748 RPN score loss: 0.01718 RPN total loss: 0.06466 Total loss: 1.15658 timestamp: 1655034593.202404 iteration: 33250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16451 FastRCNN class loss: 0.12138 FastRCNN total loss: 0.28589 L1 loss: 0.0000e+00 L2 loss: 0.72636 Learning rate: 0.02 Mask loss: 0.15062 RPN box loss: 0.03473 RPN score loss: 0.00695 RPN total loss: 0.04168 Total loss: 1.20455 timestamp: 1655034596.5408282 iteration: 33255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18868 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.26335 L1 loss: 0.0000e+00 L2 loss: 0.72626 Learning rate: 0.02 Mask loss: 0.18914 RPN box loss: 0.03893 RPN score loss: 0.00919 RPN total loss: 0.04811 Total loss: 1.22687 timestamp: 1655034599.8328967 iteration: 33260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08237 FastRCNN class loss: 0.07677 FastRCNN total loss: 0.15914 L1 loss: 0.0000e+00 L2 loss: 0.72615 Learning rate: 0.02 Mask loss: 0.11664 RPN box loss: 0.01762 RPN score loss: 0.0041 RPN total loss: 0.02172 Total loss: 1.02365 timestamp: 1655034603.1461873 iteration: 33265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10339 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.17856 L1 loss: 0.0000e+00 L2 loss: 0.72605 Learning rate: 0.02 Mask loss: 0.13835 RPN box loss: 0.01545 RPN score loss: 0.00354 RPN total loss: 0.01899 Total loss: 1.06194 timestamp: 1655034606.389436 iteration: 33270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.1043 FastRCNN total loss: 0.20523 L1 loss: 0.0000e+00 L2 loss: 0.72594 Learning rate: 0.02 Mask loss: 0.1933 RPN box loss: 0.02649 RPN score loss: 0.0124 RPN total loss: 0.03889 Total loss: 1.16336 timestamp: 1655034609.5970562 iteration: 33275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18791 FastRCNN class loss: 0.09199 FastRCNN total loss: 0.2799 L1 loss: 0.0000e+00 L2 loss: 0.72585 Learning rate: 0.02 Mask loss: 0.22687 RPN box loss: 0.0364 RPN score loss: 0.01835 RPN total loss: 0.05475 Total loss: 1.28737 timestamp: 1655034612.8625722 iteration: 33280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10198 FastRCNN class loss: 0.08247 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 0.72575 Learning rate: 0.02 Mask loss: 0.10189 RPN box loss: 0.02283 RPN score loss: 0.00598 RPN total loss: 0.02881 Total loss: 1.0409 timestamp: 1655034616.2272446 iteration: 33285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11581 FastRCNN class loss: 0.0852 FastRCNN total loss: 0.20101 L1 loss: 0.0000e+00 L2 loss: 0.72563 Learning rate: 0.02 Mask loss: 0.17037 RPN box loss: 0.04662 RPN score loss: 0.00903 RPN total loss: 0.05565 Total loss: 1.15266 timestamp: 1655034619.4596026 iteration: 33290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11818 FastRCNN class loss: 0.0855 FastRCNN total loss: 0.20368 L1 loss: 0.0000e+00 L2 loss: 0.72548 Learning rate: 0.02 Mask loss: 0.15987 RPN box loss: 0.04039 RPN score loss: 0.00867 RPN total loss: 0.04906 Total loss: 1.13809 timestamp: 1655034622.8120828 iteration: 33295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1351 FastRCNN class loss: 0.10378 FastRCNN total loss: 0.23888 L1 loss: 0.0000e+00 L2 loss: 0.72536 Learning rate: 0.02 Mask loss: 0.15762 RPN box loss: 0.02144 RPN score loss: 0.0036 RPN total loss: 0.02504 Total loss: 1.1469 timestamp: 1655034626.1207855 iteration: 33300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11934 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.21773 L1 loss: 0.0000e+00 L2 loss: 0.72528 Learning rate: 0.02 Mask loss: 0.11678 RPN box loss: 0.01774 RPN score loss: 0.00825 RPN total loss: 0.026 Total loss: 1.08578 timestamp: 1655034629.4089983 iteration: 33305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13609 FastRCNN class loss: 0.11732 FastRCNN total loss: 0.25341 L1 loss: 0.0000e+00 L2 loss: 0.72521 Learning rate: 0.02 Mask loss: 0.1643 RPN box loss: 0.0189 RPN score loss: 0.01318 RPN total loss: 0.03208 Total loss: 1.17499 timestamp: 1655034632.6074486 iteration: 33310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16012 FastRCNN class loss: 0.11128 FastRCNN total loss: 0.2714 L1 loss: 0.0000e+00 L2 loss: 0.72512 Learning rate: 0.02 Mask loss: 0.24262 RPN box loss: 0.04883 RPN score loss: 0.00832 RPN total loss: 0.05716 Total loss: 1.2963 timestamp: 1655034635.8414955 iteration: 33315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15532 FastRCNN class loss: 0.10997 FastRCNN total loss: 0.26529 L1 loss: 0.0000e+00 L2 loss: 0.72501 Learning rate: 0.02 Mask loss: 0.20599 RPN box loss: 0.02984 RPN score loss: 0.00264 RPN total loss: 0.03248 Total loss: 1.22877 timestamp: 1655034639.0791514 iteration: 33320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16408 FastRCNN class loss: 0.1107 FastRCNN total loss: 0.27478 L1 loss: 0.0000e+00 L2 loss: 0.72491 Learning rate: 0.02 Mask loss: 0.18403 RPN box loss: 0.00756 RPN score loss: 0.00313 RPN total loss: 0.01069 Total loss: 1.19441 timestamp: 1655034642.3416457 iteration: 33325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24878 FastRCNN class loss: 0.11726 FastRCNN total loss: 0.36603 L1 loss: 0.0000e+00 L2 loss: 0.72482 Learning rate: 0.02 Mask loss: 0.19393 RPN box loss: 0.00714 RPN score loss: 0.00799 RPN total loss: 0.01513 Total loss: 1.29991 timestamp: 1655034645.6607196 iteration: 33330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17057 FastRCNN class loss: 0.09604 FastRCNN total loss: 0.26661 L1 loss: 0.0000e+00 L2 loss: 0.72472 Learning rate: 0.02 Mask loss: 0.15037 RPN box loss: 0.04824 RPN score loss: 0.00775 RPN total loss: 0.05599 Total loss: 1.19769 timestamp: 1655034648.9291155 iteration: 33335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14825 FastRCNN class loss: 0.10198 FastRCNN total loss: 0.25023 L1 loss: 0.0000e+00 L2 loss: 0.72462 Learning rate: 0.02 Mask loss: 0.16206 RPN box loss: 0.01537 RPN score loss: 0.00978 RPN total loss: 0.02515 Total loss: 1.16205 timestamp: 1655034652.2186213 iteration: 33340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12102 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.18364 L1 loss: 0.0000e+00 L2 loss: 0.72451 Learning rate: 0.02 Mask loss: 0.13729 RPN box loss: 0.01883 RPN score loss: 0.00554 RPN total loss: 0.02436 Total loss: 1.06981 timestamp: 1655034655.5054095 iteration: 33345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18672 FastRCNN class loss: 0.09116 FastRCNN total loss: 0.27788 L1 loss: 0.0000e+00 L2 loss: 0.72442 Learning rate: 0.02 Mask loss: 0.18224 RPN box loss: 0.01006 RPN score loss: 0.00609 RPN total loss: 0.01616 Total loss: 1.2007 timestamp: 1655034658.768123 iteration: 33350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16588 FastRCNN class loss: 0.1236 FastRCNN total loss: 0.28948 L1 loss: 0.0000e+00 L2 loss: 0.72431 Learning rate: 0.02 Mask loss: 0.17452 RPN box loss: 0.03038 RPN score loss: 0.01004 RPN total loss: 0.04042 Total loss: 1.22873 timestamp: 1655034662.0764253 iteration: 33355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14189 FastRCNN class loss: 0.08536 FastRCNN total loss: 0.22725 L1 loss: 0.0000e+00 L2 loss: 0.7242 Learning rate: 0.02 Mask loss: 0.25443 RPN box loss: 0.05879 RPN score loss: 0.01463 RPN total loss: 0.07342 Total loss: 1.2793 timestamp: 1655034665.3487122 iteration: 33360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13581 FastRCNN class loss: 0.10077 FastRCNN total loss: 0.23658 L1 loss: 0.0000e+00 L2 loss: 0.7241 Learning rate: 0.02 Mask loss: 0.14773 RPN box loss: 0.0754 RPN score loss: 0.01407 RPN total loss: 0.08947 Total loss: 1.19788 timestamp: 1655034668.6373832 iteration: 33365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14727 FastRCNN class loss: 0.11341 FastRCNN total loss: 0.26068 L1 loss: 0.0000e+00 L2 loss: 0.72399 Learning rate: 0.02 Mask loss: 0.20309 RPN box loss: 0.04412 RPN score loss: 0.00807 RPN total loss: 0.0522 Total loss: 1.23995 timestamp: 1655034671.89171 iteration: 33370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13245 FastRCNN class loss: 0.14378 FastRCNN total loss: 0.27624 L1 loss: 0.0000e+00 L2 loss: 0.72387 Learning rate: 0.02 Mask loss: 0.20207 RPN box loss: 0.02567 RPN score loss: 0.01169 RPN total loss: 0.03735 Total loss: 1.23952 timestamp: 1655034675.1726246 iteration: 33375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.15874 L1 loss: 0.0000e+00 L2 loss: 0.72377 Learning rate: 0.02 Mask loss: 0.11445 RPN box loss: 0.03453 RPN score loss: 0.00209 RPN total loss: 0.03662 Total loss: 1.03358 timestamp: 1655034678.4109778 iteration: 33380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11474 FastRCNN class loss: 0.04392 FastRCNN total loss: 0.15865 L1 loss: 0.0000e+00 L2 loss: 0.72366 Learning rate: 0.02 Mask loss: 0.25391 RPN box loss: 0.01063 RPN score loss: 0.0019 RPN total loss: 0.01253 Total loss: 1.14875 timestamp: 1655034681.7847605 iteration: 33385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12062 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.1942 L1 loss: 0.0000e+00 L2 loss: 0.72358 Learning rate: 0.02 Mask loss: 0.14185 RPN box loss: 0.03089 RPN score loss: 0.00772 RPN total loss: 0.0386 Total loss: 1.09824 timestamp: 1655034685.0681088 iteration: 33390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15741 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.23749 L1 loss: 0.0000e+00 L2 loss: 0.72349 Learning rate: 0.02 Mask loss: 0.15376 RPN box loss: 0.01676 RPN score loss: 0.00781 RPN total loss: 0.02457 Total loss: 1.13931 timestamp: 1655034688.3013604 iteration: 33395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21404 FastRCNN class loss: 0.12893 FastRCNN total loss: 0.34297 L1 loss: 0.0000e+00 L2 loss: 0.72338 Learning rate: 0.02 Mask loss: 0.2482 RPN box loss: 0.02973 RPN score loss: 0.00545 RPN total loss: 0.03518 Total loss: 1.34973 timestamp: 1655034691.6201017 iteration: 33400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14456 FastRCNN class loss: 0.06848 FastRCNN total loss: 0.21304 L1 loss: 0.0000e+00 L2 loss: 0.72329 Learning rate: 0.02 Mask loss: 0.18641 RPN box loss: 0.01429 RPN score loss: 0.00398 RPN total loss: 0.01827 Total loss: 1.14101 timestamp: 1655034694.9723134 iteration: 33405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10923 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 0.7232 Learning rate: 0.02 Mask loss: 0.1515 RPN box loss: 0.09174 RPN score loss: 0.00726 RPN total loss: 0.099 Total loss: 1.1529 timestamp: 1655034698.188305 iteration: 33410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.19 L1 loss: 0.0000e+00 L2 loss: 0.72312 Learning rate: 0.02 Mask loss: 0.20131 RPN box loss: 0.02755 RPN score loss: 0.00735 RPN total loss: 0.0349 Total loss: 1.14932 timestamp: 1655034701.4848506 iteration: 33415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11611 FastRCNN class loss: 0.08748 FastRCNN total loss: 0.20359 L1 loss: 0.0000e+00 L2 loss: 0.72301 Learning rate: 0.02 Mask loss: 0.18367 RPN box loss: 0.02279 RPN score loss: 0.01699 RPN total loss: 0.03978 Total loss: 1.15005 timestamp: 1655034704.746732 iteration: 33420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0998 FastRCNN class loss: 0.07448 FastRCNN total loss: 0.17427 L1 loss: 0.0000e+00 L2 loss: 0.72289 Learning rate: 0.02 Mask loss: 0.24647 RPN box loss: 0.02123 RPN score loss: 0.00427 RPN total loss: 0.0255 Total loss: 1.16913 timestamp: 1655034708.0651064 iteration: 33425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18461 FastRCNN class loss: 0.13247 FastRCNN total loss: 0.31709 L1 loss: 0.0000e+00 L2 loss: 0.72278 Learning rate: 0.02 Mask loss: 0.20925 RPN box loss: 0.01853 RPN score loss: 0.01029 RPN total loss: 0.02883 Total loss: 1.27794 timestamp: 1655034711.3266253 iteration: 33430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08909 FastRCNN class loss: 0.05434 FastRCNN total loss: 0.14342 L1 loss: 0.0000e+00 L2 loss: 0.72265 Learning rate: 0.02 Mask loss: 0.08954 RPN box loss: 0.0568 RPN score loss: 0.00853 RPN total loss: 0.06533 Total loss: 1.02094 timestamp: 1655034714.641493 iteration: 33435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10777 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.19471 L1 loss: 0.0000e+00 L2 loss: 0.72253 Learning rate: 0.02 Mask loss: 0.16825 RPN box loss: 0.07802 RPN score loss: 0.01704 RPN total loss: 0.09506 Total loss: 1.18055 timestamp: 1655034717.8542056 iteration: 33440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12109 FastRCNN class loss: 0.09396 FastRCNN total loss: 0.21505 L1 loss: 0.0000e+00 L2 loss: 0.72243 Learning rate: 0.02 Mask loss: 0.20604 RPN box loss: 0.03545 RPN score loss: 0.00465 RPN total loss: 0.0401 Total loss: 1.18362 timestamp: 1655034721.1637058 iteration: 33445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1212 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.18564 L1 loss: 0.0000e+00 L2 loss: 0.72233 Learning rate: 0.02 Mask loss: 0.17252 RPN box loss: 0.01695 RPN score loss: 0.00646 RPN total loss: 0.02341 Total loss: 1.1039 timestamp: 1655034724.439897 iteration: 33450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.05421 FastRCNN total loss: 0.15354 L1 loss: 0.0000e+00 L2 loss: 0.72223 Learning rate: 0.02 Mask loss: 0.15818 RPN box loss: 0.04359 RPN score loss: 0.00208 RPN total loss: 0.04567 Total loss: 1.07963 timestamp: 1655034727.7620401 iteration: 33455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10562 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.18538 L1 loss: 0.0000e+00 L2 loss: 0.72215 Learning rate: 0.02 Mask loss: 0.10762 RPN box loss: 0.01705 RPN score loss: 0.00485 RPN total loss: 0.02189 Total loss: 1.03704 timestamp: 1655034731.1387591 iteration: 33460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16519 FastRCNN class loss: 0.09078 FastRCNN total loss: 0.25597 L1 loss: 0.0000e+00 L2 loss: 0.72203 Learning rate: 0.02 Mask loss: 0.1686 RPN box loss: 0.04578 RPN score loss: 0.00502 RPN total loss: 0.0508 Total loss: 1.1974 timestamp: 1655034734.4441886 iteration: 33465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18495 FastRCNN class loss: 0.09998 FastRCNN total loss: 0.28493 L1 loss: 0.0000e+00 L2 loss: 0.72192 Learning rate: 0.02 Mask loss: 0.19789 RPN box loss: 0.03488 RPN score loss: 0.01228 RPN total loss: 0.04716 Total loss: 1.2519 timestamp: 1655034737.7264957 iteration: 33470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11209 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.17014 L1 loss: 0.0000e+00 L2 loss: 0.72182 Learning rate: 0.02 Mask loss: 0.15636 RPN box loss: 0.01786 RPN score loss: 0.00652 RPN total loss: 0.02438 Total loss: 1.07271 timestamp: 1655034740.969618 iteration: 33475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15611 FastRCNN class loss: 0.13355 FastRCNN total loss: 0.28966 L1 loss: 0.0000e+00 L2 loss: 0.72172 Learning rate: 0.02 Mask loss: 0.22946 RPN box loss: 0.04064 RPN score loss: 0.00841 RPN total loss: 0.04905 Total loss: 1.28989 timestamp: 1655034744.1921754 iteration: 33480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18316 FastRCNN class loss: 0.10432 FastRCNN total loss: 0.28748 L1 loss: 0.0000e+00 L2 loss: 0.72164 Learning rate: 0.02 Mask loss: 0.15249 RPN box loss: 0.07788 RPN score loss: 0.01549 RPN total loss: 0.09337 Total loss: 1.25499 timestamp: 1655034747.4626048 iteration: 33485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15422 FastRCNN class loss: 0.1141 FastRCNN total loss: 0.26832 L1 loss: 0.0000e+00 L2 loss: 0.72153 Learning rate: 0.02 Mask loss: 0.16543 RPN box loss: 0.0214 RPN score loss: 0.00759 RPN total loss: 0.02899 Total loss: 1.18428 timestamp: 1655034750.7542157 iteration: 33490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14908 FastRCNN class loss: 0.10479 FastRCNN total loss: 0.25387 L1 loss: 0.0000e+00 L2 loss: 0.72141 Learning rate: 0.02 Mask loss: 0.14897 RPN box loss: 0.00935 RPN score loss: 0.00972 RPN total loss: 0.01907 Total loss: 1.14332 timestamp: 1655034754.049795 iteration: 33495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.7213 Learning rate: 0.02 Mask loss: 0.12637 RPN box loss: 0.01988 RPN score loss: 0.00777 RPN total loss: 0.02765 Total loss: 1.03971 timestamp: 1655034757.3745584 iteration: 33500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.07923 FastRCNN total loss: 0.20276 L1 loss: 0.0000e+00 L2 loss: 0.7212 Learning rate: 0.02 Mask loss: 0.16826 RPN box loss: 0.02426 RPN score loss: 0.00836 RPN total loss: 0.03263 Total loss: 1.12485 timestamp: 1655034760.7677617 iteration: 33505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10829 FastRCNN class loss: 0.05718 FastRCNN total loss: 0.16547 L1 loss: 0.0000e+00 L2 loss: 0.7211 Learning rate: 0.02 Mask loss: 0.11691 RPN box loss: 0.0173 RPN score loss: 0.00498 RPN total loss: 0.02228 Total loss: 1.02577 timestamp: 1655034763.918515 iteration: 33510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21697 FastRCNN class loss: 0.1395 FastRCNN total loss: 0.35647 L1 loss: 0.0000e+00 L2 loss: 0.721 Learning rate: 0.02 Mask loss: 0.18153 RPN box loss: 0.05702 RPN score loss: 0.0115 RPN total loss: 0.06851 Total loss: 1.32751 timestamp: 1655034767.201893 iteration: 33515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16282 FastRCNN class loss: 0.08482 FastRCNN total loss: 0.24764 L1 loss: 0.0000e+00 L2 loss: 0.72089 Learning rate: 0.02 Mask loss: 0.20751 RPN box loss: 0.01314 RPN score loss: 0.00413 RPN total loss: 0.01728 Total loss: 1.19332 timestamp: 1655034770.496642 iteration: 33520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11476 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 0.72078 Learning rate: 0.02 Mask loss: 0.22083 RPN box loss: 0.01866 RPN score loss: 0.00764 RPN total loss: 0.0263 Total loss: 1.15564 timestamp: 1655034773.8175294 iteration: 33525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11748 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.1943 L1 loss: 0.0000e+00 L2 loss: 0.72069 Learning rate: 0.02 Mask loss: 0.11618 RPN box loss: 0.02576 RPN score loss: 0.00777 RPN total loss: 0.03353 Total loss: 1.0647 timestamp: 1655034777.0881255 iteration: 33530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1437 FastRCNN class loss: 0.07992 FastRCNN total loss: 0.22362 L1 loss: 0.0000e+00 L2 loss: 0.72061 Learning rate: 0.02 Mask loss: 0.17882 RPN box loss: 0.02652 RPN score loss: 0.00418 RPN total loss: 0.0307 Total loss: 1.15374 timestamp: 1655034780.3030505 iteration: 33535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11986 FastRCNN class loss: 0.11201 FastRCNN total loss: 0.23187 L1 loss: 0.0000e+00 L2 loss: 0.72049 Learning rate: 0.02 Mask loss: 0.14191 RPN box loss: 0.04244 RPN score loss: 0.01161 RPN total loss: 0.05405 Total loss: 1.14831 timestamp: 1655034783.5393827 iteration: 33540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17075 FastRCNN class loss: 0.09314 FastRCNN total loss: 0.26389 L1 loss: 0.0000e+00 L2 loss: 0.72039 Learning rate: 0.02 Mask loss: 0.20983 RPN box loss: 0.03479 RPN score loss: 0.00526 RPN total loss: 0.04005 Total loss: 1.23416 timestamp: 1655034786.8089898 iteration: 33545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0966 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.16264 L1 loss: 0.0000e+00 L2 loss: 0.72027 Learning rate: 0.02 Mask loss: 0.13296 RPN box loss: 0.01533 RPN score loss: 0.00274 RPN total loss: 0.01808 Total loss: 1.03395 timestamp: 1655034790.068835 iteration: 33550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14265 FastRCNN class loss: 0.07981 FastRCNN total loss: 0.22246 L1 loss: 0.0000e+00 L2 loss: 0.72018 Learning rate: 0.02 Mask loss: 0.1528 RPN box loss: 0.02139 RPN score loss: 0.00401 RPN total loss: 0.0254 Total loss: 1.12084 timestamp: 1655034793.2973032 iteration: 33555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14193 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.20942 L1 loss: 0.0000e+00 L2 loss: 0.72006 Learning rate: 0.02 Mask loss: 0.22466 RPN box loss: 0.01871 RPN score loss: 0.00242 RPN total loss: 0.02113 Total loss: 1.17527 timestamp: 1655034796.571997 iteration: 33560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.101 FastRCNN class loss: 0.06856 FastRCNN total loss: 0.16955 L1 loss: 0.0000e+00 L2 loss: 0.71998 Learning rate: 0.02 Mask loss: 0.11525 RPN box loss: 0.01892 RPN score loss: 0.0085 RPN total loss: 0.02741 Total loss: 1.0322 timestamp: 1655034799.8364658 iteration: 33565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20973 FastRCNN class loss: 0.10778 FastRCNN total loss: 0.3175 L1 loss: 0.0000e+00 L2 loss: 0.71988 Learning rate: 0.02 Mask loss: 0.15107 RPN box loss: 0.04515 RPN score loss: 0.00827 RPN total loss: 0.05343 Total loss: 1.24188 timestamp: 1655034803.0778997 iteration: 33570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12235 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.20215 L1 loss: 0.0000e+00 L2 loss: 0.71978 Learning rate: 0.02 Mask loss: 0.12225 RPN box loss: 0.05511 RPN score loss: 0.00562 RPN total loss: 0.06073 Total loss: 1.10491 timestamp: 1655034806.3780022 iteration: 33575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14516 FastRCNN class loss: 0.0741 FastRCNN total loss: 0.21927 L1 loss: 0.0000e+00 L2 loss: 0.71969 Learning rate: 0.02 Mask loss: 0.11256 RPN box loss: 0.03761 RPN score loss: 0.00443 RPN total loss: 0.04204 Total loss: 1.09357 timestamp: 1655034809.6366215 iteration: 33580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18451 FastRCNN class loss: 0.09108 FastRCNN total loss: 0.27559 L1 loss: 0.0000e+00 L2 loss: 0.7196 Learning rate: 0.02 Mask loss: 0.14098 RPN box loss: 0.01617 RPN score loss: 0.00364 RPN total loss: 0.01981 Total loss: 1.15598 timestamp: 1655034812.8866868 iteration: 33585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13265 FastRCNN class loss: 0.07286 FastRCNN total loss: 0.20551 L1 loss: 0.0000e+00 L2 loss: 0.71949 Learning rate: 0.02 Mask loss: 0.10441 RPN box loss: 0.05563 RPN score loss: 0.00947 RPN total loss: 0.0651 Total loss: 1.09452 timestamp: 1655034816.2075226 iteration: 33590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06439 FastRCNN class loss: 0.04238 FastRCNN total loss: 0.10678 L1 loss: 0.0000e+00 L2 loss: 0.71938 Learning rate: 0.02 Mask loss: 0.22204 RPN box loss: 0.0108 RPN score loss: 0.00445 RPN total loss: 0.01525 Total loss: 1.06345 timestamp: 1655034819.560962 iteration: 33595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19063 FastRCNN class loss: 0.19926 FastRCNN total loss: 0.38989 L1 loss: 0.0000e+00 L2 loss: 0.71928 Learning rate: 0.02 Mask loss: 0.26552 RPN box loss: 0.02703 RPN score loss: 0.01443 RPN total loss: 0.04145 Total loss: 1.41614 timestamp: 1655034822.8103065 iteration: 33600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10335 FastRCNN class loss: 0.06178 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.71916 Learning rate: 0.02 Mask loss: 0.16159 RPN box loss: 0.04351 RPN score loss: 0.01469 RPN total loss: 0.0582 Total loss: 1.10407 timestamp: 1655034826.0450432 iteration: 33605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08546 FastRCNN class loss: 0.04937 FastRCNN total loss: 0.13482 L1 loss: 0.0000e+00 L2 loss: 0.71906 Learning rate: 0.02 Mask loss: 0.07169 RPN box loss: 0.0097 RPN score loss: 0.00067 RPN total loss: 0.01037 Total loss: 0.93595 timestamp: 1655034829.2630293 iteration: 33610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12604 FastRCNN class loss: 0.05755 FastRCNN total loss: 0.18359 L1 loss: 0.0000e+00 L2 loss: 0.71896 Learning rate: 0.02 Mask loss: 0.16175 RPN box loss: 0.01949 RPN score loss: 0.00332 RPN total loss: 0.0228 Total loss: 1.0871 timestamp: 1655034832.4799483 iteration: 33615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15899 FastRCNN class loss: 0.1483 FastRCNN total loss: 0.30729 L1 loss: 0.0000e+00 L2 loss: 0.71885 Learning rate: 0.02 Mask loss: 0.17875 RPN box loss: 0.0188 RPN score loss: 0.00303 RPN total loss: 0.02183 Total loss: 1.22672 timestamp: 1655034835.7397976 iteration: 33620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18224 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.26342 L1 loss: 0.0000e+00 L2 loss: 0.71873 Learning rate: 0.02 Mask loss: 0.15389 RPN box loss: 0.03332 RPN score loss: 0.00652 RPN total loss: 0.03983 Total loss: 1.17587 timestamp: 1655034839.0393732 iteration: 33625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14644 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.21496 L1 loss: 0.0000e+00 L2 loss: 0.71866 Learning rate: 0.02 Mask loss: 0.15731 RPN box loss: 0.03042 RPN score loss: 0.00398 RPN total loss: 0.0344 Total loss: 1.12533 timestamp: 1655034842.3558486 iteration: 33630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12993 FastRCNN class loss: 0.081 FastRCNN total loss: 0.21093 L1 loss: 0.0000e+00 L2 loss: 0.71857 Learning rate: 0.02 Mask loss: 0.14282 RPN box loss: 0.01608 RPN score loss: 0.00813 RPN total loss: 0.0242 Total loss: 1.09652 timestamp: 1655034845.687645 iteration: 33635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15878 FastRCNN class loss: 0.1274 FastRCNN total loss: 0.28617 L1 loss: 0.0000e+00 L2 loss: 0.71847 Learning rate: 0.02 Mask loss: 0.21732 RPN box loss: 0.13002 RPN score loss: 0.01448 RPN total loss: 0.1445 Total loss: 1.36646 timestamp: 1655034848.959465 iteration: 33640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.122 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.18206 L1 loss: 0.0000e+00 L2 loss: 0.71837 Learning rate: 0.02 Mask loss: 0.14799 RPN box loss: 0.04318 RPN score loss: 0.00387 RPN total loss: 0.04705 Total loss: 1.09546 timestamp: 1655034852.2395108 iteration: 33645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13659 FastRCNN class loss: 0.10678 FastRCNN total loss: 0.24336 L1 loss: 0.0000e+00 L2 loss: 0.71827 Learning rate: 0.02 Mask loss: 0.13489 RPN box loss: 0.03276 RPN score loss: 0.01967 RPN total loss: 0.05243 Total loss: 1.14896 timestamp: 1655034855.500831 iteration: 33650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09682 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.16321 L1 loss: 0.0000e+00 L2 loss: 0.71816 Learning rate: 0.02 Mask loss: 0.16281 RPN box loss: 0.01685 RPN score loss: 0.00885 RPN total loss: 0.0257 Total loss: 1.06987 timestamp: 1655034858.8091083 iteration: 33655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14029 FastRCNN class loss: 0.15613 FastRCNN total loss: 0.29642 L1 loss: 0.0000e+00 L2 loss: 0.71804 Learning rate: 0.02 Mask loss: 0.21083 RPN box loss: 0.03298 RPN score loss: 0.00611 RPN total loss: 0.03909 Total loss: 1.26439 timestamp: 1655034862.1428363 iteration: 33660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18033 FastRCNN class loss: 0.09064 FastRCNN total loss: 0.27096 L1 loss: 0.0000e+00 L2 loss: 0.71791 Learning rate: 0.02 Mask loss: 0.14765 RPN box loss: 0.04347 RPN score loss: 0.02737 RPN total loss: 0.07083 Total loss: 1.20736 timestamp: 1655034865.5026913 iteration: 33665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16835 FastRCNN class loss: 0.11333 FastRCNN total loss: 0.28168 L1 loss: 0.0000e+00 L2 loss: 0.71782 Learning rate: 0.02 Mask loss: 0.14806 RPN box loss: 0.03809 RPN score loss: 0.0072 RPN total loss: 0.04529 Total loss: 1.19285 timestamp: 1655034868.809326 iteration: 33670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18466 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.23725 L1 loss: 0.0000e+00 L2 loss: 0.71772 Learning rate: 0.02 Mask loss: 0.12082 RPN box loss: 0.01752 RPN score loss: 0.00233 RPN total loss: 0.01985 Total loss: 1.09564 timestamp: 1655034872.008915 iteration: 33675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13776 FastRCNN class loss: 0.12702 FastRCNN total loss: 0.26478 L1 loss: 0.0000e+00 L2 loss: 0.7176 Learning rate: 0.02 Mask loss: 0.15449 RPN box loss: 0.02124 RPN score loss: 0.01539 RPN total loss: 0.03663 Total loss: 1.17351 timestamp: 1655034875.2483432 iteration: 33680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11213 FastRCNN class loss: 0.05523 FastRCNN total loss: 0.16737 L1 loss: 0.0000e+00 L2 loss: 0.71752 Learning rate: 0.02 Mask loss: 0.15605 RPN box loss: 0.01307 RPN score loss: 0.00344 RPN total loss: 0.01652 Total loss: 1.05746 timestamp: 1655034878.520395 iteration: 33685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09478 FastRCNN class loss: 0.07074 FastRCNN total loss: 0.16552 L1 loss: 0.0000e+00 L2 loss: 0.71743 Learning rate: 0.02 Mask loss: 0.15058 RPN box loss: 0.02701 RPN score loss: 0.02899 RPN total loss: 0.056 Total loss: 1.08953 timestamp: 1655034881.8503976 iteration: 33690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21742 FastRCNN class loss: 0.12053 FastRCNN total loss: 0.33796 L1 loss: 0.0000e+00 L2 loss: 0.71732 Learning rate: 0.02 Mask loss: 0.19954 RPN box loss: 0.0221 RPN score loss: 0.00224 RPN total loss: 0.02434 Total loss: 1.27915 timestamp: 1655034885.12587 iteration: 33695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14919 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.20587 L1 loss: 0.0000e+00 L2 loss: 0.7172 Learning rate: 0.02 Mask loss: 0.11872 RPN box loss: 0.02299 RPN score loss: 0.00518 RPN total loss: 0.02817 Total loss: 1.06997 timestamp: 1655034888.409439 iteration: 33700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15971 FastRCNN class loss: 0.11685 FastRCNN total loss: 0.27656 L1 loss: 0.0000e+00 L2 loss: 0.71712 Learning rate: 0.02 Mask loss: 0.20756 RPN box loss: 0.03203 RPN score loss: 0.01346 RPN total loss: 0.04549 Total loss: 1.24673 timestamp: 1655034891.653536 iteration: 33705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10279 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.16505 L1 loss: 0.0000e+00 L2 loss: 0.71702 Learning rate: 0.02 Mask loss: 0.09673 RPN box loss: 0.02298 RPN score loss: 0.00328 RPN total loss: 0.02626 Total loss: 1.00505 timestamp: 1655034894.9419477 iteration: 33710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23873 FastRCNN class loss: 0.0843 FastRCNN total loss: 0.32303 L1 loss: 0.0000e+00 L2 loss: 0.71689 Learning rate: 0.02 Mask loss: 0.26582 RPN box loss: 0.01582 RPN score loss: 0.01246 RPN total loss: 0.02828 Total loss: 1.33402 timestamp: 1655034898.124765 iteration: 33715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10858 FastRCNN class loss: 0.06116 FastRCNN total loss: 0.16974 L1 loss: 0.0000e+00 L2 loss: 0.71682 Learning rate: 0.02 Mask loss: 0.13795 RPN box loss: 0.02058 RPN score loss: 0.00512 RPN total loss: 0.02569 Total loss: 1.05021 timestamp: 1655034901.3564599 iteration: 33720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15627 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.25292 L1 loss: 0.0000e+00 L2 loss: 0.71675 Learning rate: 0.02 Mask loss: 0.13954 RPN box loss: 0.04544 RPN score loss: 0.00442 RPN total loss: 0.04986 Total loss: 1.15907 timestamp: 1655034904.5971203 iteration: 33725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14551 FastRCNN class loss: 0.08408 FastRCNN total loss: 0.2296 L1 loss: 0.0000e+00 L2 loss: 0.71665 Learning rate: 0.02 Mask loss: 0.20441 RPN box loss: 0.03366 RPN score loss: 0.02036 RPN total loss: 0.05402 Total loss: 1.20467 timestamp: 1655034907.9241328 iteration: 33730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16511 FastRCNN class loss: 0.07056 FastRCNN total loss: 0.23567 L1 loss: 0.0000e+00 L2 loss: 0.71654 Learning rate: 0.02 Mask loss: 0.21735 RPN box loss: 0.02844 RPN score loss: 0.00645 RPN total loss: 0.03489 Total loss: 1.20446 timestamp: 1655034911.1613317 iteration: 33735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1186 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.21882 L1 loss: 0.0000e+00 L2 loss: 0.71648 Learning rate: 0.02 Mask loss: 0.15347 RPN box loss: 0.02365 RPN score loss: 0.0048 RPN total loss: 0.02845 Total loss: 1.11722 timestamp: 1655034914.4829588 iteration: 33740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12252 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 0.71639 Learning rate: 0.02 Mask loss: 0.14605 RPN box loss: 0.01476 RPN score loss: 0.00203 RPN total loss: 0.01679 Total loss: 1.06887 timestamp: 1655034917.7111206 iteration: 33745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15274 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.22496 L1 loss: 0.0000e+00 L2 loss: 0.71627 Learning rate: 0.02 Mask loss: 0.18592 RPN box loss: 0.0191 RPN score loss: 0.00711 RPN total loss: 0.02621 Total loss: 1.15336 timestamp: 1655034920.9700053 iteration: 33750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18066 FastRCNN class loss: 0.08696 FastRCNN total loss: 0.26761 L1 loss: 0.0000e+00 L2 loss: 0.71616 Learning rate: 0.02 Mask loss: 0.17048 RPN box loss: 0.0491 RPN score loss: 0.00784 RPN total loss: 0.05694 Total loss: 1.21119 timestamp: 1655034924.2665305 iteration: 33755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13247 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.18478 L1 loss: 0.0000e+00 L2 loss: 0.71606 Learning rate: 0.02 Mask loss: 0.16576 RPN box loss: 0.01551 RPN score loss: 0.00399 RPN total loss: 0.0195 Total loss: 1.08609 timestamp: 1655034927.564944 iteration: 33760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08227 FastRCNN class loss: 0.05083 FastRCNN total loss: 0.13311 L1 loss: 0.0000e+00 L2 loss: 0.71595 Learning rate: 0.02 Mask loss: 0.14017 RPN box loss: 0.05268 RPN score loss: 0.00942 RPN total loss: 0.06209 Total loss: 1.05132 timestamp: 1655034930.8189476 iteration: 33765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.08076 FastRCNN total loss: 0.20325 L1 loss: 0.0000e+00 L2 loss: 0.71586 Learning rate: 0.02 Mask loss: 0.17808 RPN box loss: 0.01409 RPN score loss: 0.00618 RPN total loss: 0.02027 Total loss: 1.11746 timestamp: 1655034934.1548676 iteration: 33770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15434 FastRCNN class loss: 0.07646 FastRCNN total loss: 0.2308 L1 loss: 0.0000e+00 L2 loss: 0.71576 Learning rate: 0.02 Mask loss: 0.1534 RPN box loss: 0.03513 RPN score loss: 0.00382 RPN total loss: 0.03896 Total loss: 1.13891 timestamp: 1655034937.501917 iteration: 33775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18125 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.26256 L1 loss: 0.0000e+00 L2 loss: 0.71564 Learning rate: 0.02 Mask loss: 0.1678 RPN box loss: 0.05957 RPN score loss: 0.00739 RPN total loss: 0.06696 Total loss: 1.21297 timestamp: 1655034940.7947626 iteration: 33780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12811 FastRCNN class loss: 0.10194 FastRCNN total loss: 0.23005 L1 loss: 0.0000e+00 L2 loss: 0.71552 Learning rate: 0.02 Mask loss: 0.09866 RPN box loss: 0.02066 RPN score loss: 0.00473 RPN total loss: 0.0254 Total loss: 1.06963 timestamp: 1655034944.1113229 iteration: 33785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14882 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.22933 L1 loss: 0.0000e+00 L2 loss: 0.71542 Learning rate: 0.02 Mask loss: 0.22362 RPN box loss: 0.02611 RPN score loss: 0.00884 RPN total loss: 0.03495 Total loss: 1.20331 timestamp: 1655034947.4108884 iteration: 33790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16107 FastRCNN class loss: 0.11281 FastRCNN total loss: 0.27387 L1 loss: 0.0000e+00 L2 loss: 0.71532 Learning rate: 0.02 Mask loss: 0.1972 RPN box loss: 0.04144 RPN score loss: 0.0081 RPN total loss: 0.04954 Total loss: 1.23592 timestamp: 1655034950.70186 iteration: 33795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2295 FastRCNN class loss: 0.09443 FastRCNN total loss: 0.32393 L1 loss: 0.0000e+00 L2 loss: 0.71521 Learning rate: 0.02 Mask loss: 0.14132 RPN box loss: 0.03633 RPN score loss: 0.01049 RPN total loss: 0.04682 Total loss: 1.22729 timestamp: 1655034953.9951468 iteration: 33800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16736 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.25825 L1 loss: 0.0000e+00 L2 loss: 0.71512 Learning rate: 0.02 Mask loss: 0.17137 RPN box loss: 0.02333 RPN score loss: 0.00516 RPN total loss: 0.02849 Total loss: 1.17323 timestamp: 1655034957.3328357 iteration: 33805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16197 FastRCNN class loss: 0.14637 FastRCNN total loss: 0.30834 L1 loss: 0.0000e+00 L2 loss: 0.71504 Learning rate: 0.02 Mask loss: 0.28439 RPN box loss: 0.09803 RPN score loss: 0.00861 RPN total loss: 0.10664 Total loss: 1.41441 timestamp: 1655034960.561106 iteration: 33810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18174 FastRCNN class loss: 0.1534 FastRCNN total loss: 0.33514 L1 loss: 0.0000e+00 L2 loss: 0.71493 Learning rate: 0.02 Mask loss: 0.13816 RPN box loss: 0.06667 RPN score loss: 0.02168 RPN total loss: 0.08835 Total loss: 1.27658 timestamp: 1655034963.8951159 iteration: 33815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14711 FastRCNN class loss: 0.07939 FastRCNN total loss: 0.2265 L1 loss: 0.0000e+00 L2 loss: 0.71483 Learning rate: 0.02 Mask loss: 0.13924 RPN box loss: 0.03517 RPN score loss: 0.00443 RPN total loss: 0.0396 Total loss: 1.12017 timestamp: 1655034967.180611 iteration: 33820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1548 FastRCNN class loss: 0.10219 FastRCNN total loss: 0.25699 L1 loss: 0.0000e+00 L2 loss: 0.71472 Learning rate: 0.02 Mask loss: 0.18858 RPN box loss: 0.022 RPN score loss: 0.00687 RPN total loss: 0.02886 Total loss: 1.18915 timestamp: 1655034970.506579 iteration: 33825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15284 FastRCNN class loss: 0.12093 FastRCNN total loss: 0.27377 L1 loss: 0.0000e+00 L2 loss: 0.71461 Learning rate: 0.02 Mask loss: 0.16618 RPN box loss: 0.10475 RPN score loss: 0.02246 RPN total loss: 0.12721 Total loss: 1.28177 timestamp: 1655034973.781053 iteration: 33830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08691 FastRCNN class loss: 0.07052 FastRCNN total loss: 0.15743 L1 loss: 0.0000e+00 L2 loss: 0.71453 Learning rate: 0.02 Mask loss: 0.13718 RPN box loss: 0.01712 RPN score loss: 0.00693 RPN total loss: 0.02405 Total loss: 1.03319 timestamp: 1655034977.1003878 iteration: 33835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15859 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.2632 L1 loss: 0.0000e+00 L2 loss: 0.71443 Learning rate: 0.02 Mask loss: 0.12823 RPN box loss: 0.01296 RPN score loss: 0.00522 RPN total loss: 0.01817 Total loss: 1.12404 timestamp: 1655034980.3529835 iteration: 33840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.13215 L1 loss: 0.0000e+00 L2 loss: 0.71432 Learning rate: 0.02 Mask loss: 0.10991 RPN box loss: 0.01678 RPN score loss: 0.00353 RPN total loss: 0.0203 Total loss: 0.97668 timestamp: 1655034983.559909 iteration: 33845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13564 FastRCNN class loss: 0.10089 FastRCNN total loss: 0.23653 L1 loss: 0.0000e+00 L2 loss: 0.71422 Learning rate: 0.02 Mask loss: 0.18774 RPN box loss: 0.0211 RPN score loss: 0.00442 RPN total loss: 0.02552 Total loss: 1.16401 timestamp: 1655034986.8895323 iteration: 33850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19912 FastRCNN class loss: 0.06176 FastRCNN total loss: 0.26088 L1 loss: 0.0000e+00 L2 loss: 0.71412 Learning rate: 0.02 Mask loss: 0.09114 RPN box loss: 0.03157 RPN score loss: 0.004 RPN total loss: 0.03557 Total loss: 1.10171 timestamp: 1655034990.1945524 iteration: 33855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17377 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.24657 L1 loss: 0.0000e+00 L2 loss: 0.71402 Learning rate: 0.02 Mask loss: 0.19305 RPN box loss: 0.00486 RPN score loss: 0.00123 RPN total loss: 0.00608 Total loss: 1.15973 timestamp: 1655034993.4133544 iteration: 33860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0888 FastRCNN class loss: 0.08649 FastRCNN total loss: 0.17529 L1 loss: 0.0000e+00 L2 loss: 0.71392 Learning rate: 0.02 Mask loss: 0.18386 RPN box loss: 0.01895 RPN score loss: 0.00591 RPN total loss: 0.02486 Total loss: 1.09793 timestamp: 1655034996.6419432 iteration: 33865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.17933 L1 loss: 0.0000e+00 L2 loss: 0.71382 Learning rate: 0.02 Mask loss: 0.13608 RPN box loss: 0.02741 RPN score loss: 0.00452 RPN total loss: 0.03193 Total loss: 1.06116 timestamp: 1655034999.8870044 iteration: 33870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.19303 L1 loss: 0.0000e+00 L2 loss: 0.71371 Learning rate: 0.02 Mask loss: 0.17203 RPN box loss: 0.02743 RPN score loss: 0.0028 RPN total loss: 0.03024 Total loss: 1.10901 timestamp: 1655035003.2495985 iteration: 33875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.09242 FastRCNN total loss: 0.21872 L1 loss: 0.0000e+00 L2 loss: 0.71359 Learning rate: 0.02 Mask loss: 0.19197 RPN box loss: 0.05414 RPN score loss: 0.00874 RPN total loss: 0.06289 Total loss: 1.18717 timestamp: 1655035006.502291 iteration: 33880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10476 FastRCNN class loss: 0.06204 FastRCNN total loss: 0.1668 L1 loss: 0.0000e+00 L2 loss: 0.71351 Learning rate: 0.02 Mask loss: 0.23258 RPN box loss: 0.04441 RPN score loss: 0.00925 RPN total loss: 0.05366 Total loss: 1.16655 timestamp: 1655035009.7590113 iteration: 33885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.06102 FastRCNN total loss: 0.17338 L1 loss: 0.0000e+00 L2 loss: 0.71342 Learning rate: 0.02 Mask loss: 0.18843 RPN box loss: 0.01929 RPN score loss: 0.00372 RPN total loss: 0.02301 Total loss: 1.09823 timestamp: 1655035013.0825205 iteration: 33890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.09132 FastRCNN total loss: 0.19615 L1 loss: 0.0000e+00 L2 loss: 0.7133 Learning rate: 0.02 Mask loss: 0.21199 RPN box loss: 0.01663 RPN score loss: 0.00862 RPN total loss: 0.02525 Total loss: 1.14669 timestamp: 1655035016.3637516 iteration: 33895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13334 FastRCNN class loss: 0.07838 FastRCNN total loss: 0.21172 L1 loss: 0.0000e+00 L2 loss: 0.71319 Learning rate: 0.02 Mask loss: 0.17644 RPN box loss: 0.04804 RPN score loss: 0.00475 RPN total loss: 0.05279 Total loss: 1.15414 timestamp: 1655035019.6149774 iteration: 33900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14766 FastRCNN class loss: 0.08029 FastRCNN total loss: 0.22795 L1 loss: 0.0000e+00 L2 loss: 0.71308 Learning rate: 0.02 Mask loss: 0.15851 RPN box loss: 0.07408 RPN score loss: 0.00666 RPN total loss: 0.08074 Total loss: 1.18028 timestamp: 1655035022.8742523 iteration: 33905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15409 FastRCNN class loss: 0.08079 FastRCNN total loss: 0.23488 L1 loss: 0.0000e+00 L2 loss: 0.71297 Learning rate: 0.02 Mask loss: 0.12347 RPN box loss: 0.02566 RPN score loss: 0.00615 RPN total loss: 0.03181 Total loss: 1.10314 timestamp: 1655035026.1479475 iteration: 33910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13899 FastRCNN class loss: 0.08709 FastRCNN total loss: 0.22608 L1 loss: 0.0000e+00 L2 loss: 0.71288 Learning rate: 0.02 Mask loss: 0.1745 RPN box loss: 0.06449 RPN score loss: 0.01073 RPN total loss: 0.07522 Total loss: 1.18868 timestamp: 1655035029.4240873 iteration: 33915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20516 FastRCNN class loss: 0.09506 FastRCNN total loss: 0.30022 L1 loss: 0.0000e+00 L2 loss: 0.71281 Learning rate: 0.02 Mask loss: 0.12886 RPN box loss: 0.02169 RPN score loss: 0.0085 RPN total loss: 0.03019 Total loss: 1.17208 timestamp: 1655035032.714094 iteration: 33920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14877 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.22515 L1 loss: 0.0000e+00 L2 loss: 0.7127 Learning rate: 0.02 Mask loss: 0.18634 RPN box loss: 0.02169 RPN score loss: 0.00646 RPN total loss: 0.02815 Total loss: 1.15234 timestamp: 1655035036.0013685 iteration: 33925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12878 FastRCNN class loss: 0.0766 FastRCNN total loss: 0.20538 L1 loss: 0.0000e+00 L2 loss: 0.7126 Learning rate: 0.02 Mask loss: 0.13405 RPN box loss: 0.01862 RPN score loss: 0.00395 RPN total loss: 0.02257 Total loss: 1.0746 timestamp: 1655035039.4130526 iteration: 33930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09977 FastRCNN class loss: 0.06395 FastRCNN total loss: 0.16372 L1 loss: 0.0000e+00 L2 loss: 0.71248 Learning rate: 0.02 Mask loss: 0.11208 RPN box loss: 0.01961 RPN score loss: 0.00248 RPN total loss: 0.02209 Total loss: 1.01038 timestamp: 1655035042.6753156 iteration: 33935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13211 FastRCNN class loss: 0.07329 FastRCNN total loss: 0.2054 L1 loss: 0.0000e+00 L2 loss: 0.71238 Learning rate: 0.02 Mask loss: 0.21812 RPN box loss: 0.0171 RPN score loss: 0.00942 RPN total loss: 0.02652 Total loss: 1.16242 timestamp: 1655035045.940862 iteration: 33940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12633 FastRCNN class loss: 0.08515 FastRCNN total loss: 0.21149 L1 loss: 0.0000e+00 L2 loss: 0.71226 Learning rate: 0.02 Mask loss: 0.15539 RPN box loss: 0.03834 RPN score loss: 0.00823 RPN total loss: 0.04657 Total loss: 1.12571 timestamp: 1655035049.1943865 iteration: 33945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11583 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.20929 L1 loss: 0.0000e+00 L2 loss: 0.71215 Learning rate: 0.02 Mask loss: 0.20033 RPN box loss: 0.02403 RPN score loss: 0.00548 RPN total loss: 0.02951 Total loss: 1.15128 timestamp: 1655035052.4068222 iteration: 33950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15544 FastRCNN class loss: 0.15125 FastRCNN total loss: 0.30669 L1 loss: 0.0000e+00 L2 loss: 0.71205 Learning rate: 0.02 Mask loss: 0.18027 RPN box loss: 0.02647 RPN score loss: 0.01554 RPN total loss: 0.04201 Total loss: 1.24103 timestamp: 1655035055.6261282 iteration: 33955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14346 FastRCNN class loss: 0.08362 FastRCNN total loss: 0.22709 L1 loss: 0.0000e+00 L2 loss: 0.71196 Learning rate: 0.02 Mask loss: 0.19822 RPN box loss: 0.0216 RPN score loss: 0.01015 RPN total loss: 0.03175 Total loss: 1.16901 timestamp: 1655035058.872457 iteration: 33960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13756 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.20498 L1 loss: 0.0000e+00 L2 loss: 0.71187 Learning rate: 0.02 Mask loss: 0.13681 RPN box loss: 0.02179 RPN score loss: 0.00615 RPN total loss: 0.02794 Total loss: 1.0816 timestamp: 1655035062.164746 iteration: 33965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23352 FastRCNN class loss: 0.132 FastRCNN total loss: 0.36552 L1 loss: 0.0000e+00 L2 loss: 0.71176 Learning rate: 0.02 Mask loss: 0.2638 RPN box loss: 0.03886 RPN score loss: 0.01913 RPN total loss: 0.05799 Total loss: 1.39907 timestamp: 1655035065.4069495 iteration: 33970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15647 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.23754 L1 loss: 0.0000e+00 L2 loss: 0.71162 Learning rate: 0.02 Mask loss: 0.1902 RPN box loss: 0.02779 RPN score loss: 0.00751 RPN total loss: 0.0353 Total loss: 1.17466 timestamp: 1655035068.7222366 iteration: 33975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18427 FastRCNN class loss: 0.10248 FastRCNN total loss: 0.28676 L1 loss: 0.0000e+00 L2 loss: 0.71153 Learning rate: 0.02 Mask loss: 0.15468 RPN box loss: 0.06112 RPN score loss: 0.0147 RPN total loss: 0.07582 Total loss: 1.22879 timestamp: 1655035072.0449598 iteration: 33980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10836 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.1904 L1 loss: 0.0000e+00 L2 loss: 0.71144 Learning rate: 0.02 Mask loss: 0.22672 RPN box loss: 0.05553 RPN score loss: 0.01383 RPN total loss: 0.06936 Total loss: 1.19792 timestamp: 1655035075.270573 iteration: 33985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17178 FastRCNN class loss: 0.05875 FastRCNN total loss: 0.23053 L1 loss: 0.0000e+00 L2 loss: 0.71132 Learning rate: 0.02 Mask loss: 0.10865 RPN box loss: 0.00775 RPN score loss: 0.00219 RPN total loss: 0.00994 Total loss: 1.06044 timestamp: 1655035078.5222607 iteration: 33990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17804 FastRCNN class loss: 0.11116 FastRCNN total loss: 0.2892 L1 loss: 0.0000e+00 L2 loss: 0.7112 Learning rate: 0.02 Mask loss: 0.23414 RPN box loss: 0.01114 RPN score loss: 0.00453 RPN total loss: 0.01566 Total loss: 1.2502 timestamp: 1655035081.7771728 iteration: 33995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07839 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.14554 L1 loss: 0.0000e+00 L2 loss: 0.71113 Learning rate: 0.02 Mask loss: 0.11694 RPN box loss: 0.0588 RPN score loss: 0.00934 RPN total loss: 0.06814 Total loss: 1.04174 timestamp: 1655035085.0662847 iteration: 34000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23252 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.31686 L1 loss: 0.0000e+00 L2 loss: 0.71104 Learning rate: 0.02 Mask loss: 0.14526 RPN box loss: 0.02645 RPN score loss: 0.00719 RPN total loss: 0.03364 Total loss: 1.2068 timestamp: 1655035088.2748823 iteration: 34005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13788 FastRCNN class loss: 0.12527 FastRCNN total loss: 0.26315 L1 loss: 0.0000e+00 L2 loss: 0.71094 Learning rate: 0.02 Mask loss: 0.15664 RPN box loss: 0.02091 RPN score loss: 0.00818 RPN total loss: 0.02909 Total loss: 1.15983 timestamp: 1655035091.506369 iteration: 34010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17135 FastRCNN class loss: 0.10093 FastRCNN total loss: 0.27229 L1 loss: 0.0000e+00 L2 loss: 0.71082 Learning rate: 0.02 Mask loss: 0.14737 RPN box loss: 0.03828 RPN score loss: 0.01264 RPN total loss: 0.05092 Total loss: 1.1814 timestamp: 1655035094.7641165 iteration: 34015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14336 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.19615 L1 loss: 0.0000e+00 L2 loss: 0.71069 Learning rate: 0.02 Mask loss: 0.11277 RPN box loss: 0.02303 RPN score loss: 0.01026 RPN total loss: 0.03329 Total loss: 1.05289 timestamp: 1655035097.984542 iteration: 34020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17499 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.26979 L1 loss: 0.0000e+00 L2 loss: 0.7106 Learning rate: 0.02 Mask loss: 0.19979 RPN box loss: 0.06913 RPN score loss: 0.00872 RPN total loss: 0.07785 Total loss: 1.25803 timestamp: 1655035101.3014119 iteration: 34025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14004 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.22305 L1 loss: 0.0000e+00 L2 loss: 0.71052 Learning rate: 0.02 Mask loss: 0.22109 RPN box loss: 0.02394 RPN score loss: 0.00357 RPN total loss: 0.02751 Total loss: 1.18217 timestamp: 1655035104.5518181 iteration: 34030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19514 FastRCNN class loss: 0.08833 FastRCNN total loss: 0.28348 L1 loss: 0.0000e+00 L2 loss: 0.71042 Learning rate: 0.02 Mask loss: 0.17209 RPN box loss: 0.01063 RPN score loss: 0.00267 RPN total loss: 0.01331 Total loss: 1.1793 timestamp: 1655035107.8179867 iteration: 34035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14446 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.22606 L1 loss: 0.0000e+00 L2 loss: 0.71032 Learning rate: 0.02 Mask loss: 0.13707 RPN box loss: 0.05749 RPN score loss: 0.01153 RPN total loss: 0.06902 Total loss: 1.14247 timestamp: 1655035111.044023 iteration: 34040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1723 FastRCNN class loss: 0.13514 FastRCNN total loss: 0.30743 L1 loss: 0.0000e+00 L2 loss: 0.7102 Learning rate: 0.02 Mask loss: 0.2481 RPN box loss: 0.05967 RPN score loss: 0.01189 RPN total loss: 0.07156 Total loss: 1.3373 timestamp: 1655035114.311653 iteration: 34045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09744 FastRCNN class loss: 0.06998 FastRCNN total loss: 0.16742 L1 loss: 0.0000e+00 L2 loss: 0.71008 Learning rate: 0.02 Mask loss: 0.1958 RPN box loss: 0.0255 RPN score loss: 0.00598 RPN total loss: 0.03149 Total loss: 1.10479 timestamp: 1655035117.555502 iteration: 34050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09051 FastRCNN class loss: 0.03961 FastRCNN total loss: 0.13012 L1 loss: 0.0000e+00 L2 loss: 0.71 Learning rate: 0.02 Mask loss: 0.1045 RPN box loss: 0.01468 RPN score loss: 0.00327 RPN total loss: 0.01794 Total loss: 0.96256 timestamp: 1655035120.7661085 iteration: 34055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14758 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.21422 L1 loss: 0.0000e+00 L2 loss: 0.7099 Learning rate: 0.02 Mask loss: 0.15202 RPN box loss: 0.03931 RPN score loss: 0.0109 RPN total loss: 0.05021 Total loss: 1.12635 timestamp: 1655035124.0220864 iteration: 34060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20005 FastRCNN class loss: 0.08719 FastRCNN total loss: 0.28723 L1 loss: 0.0000e+00 L2 loss: 0.70982 Learning rate: 0.02 Mask loss: 0.14844 RPN box loss: 0.07497 RPN score loss: 0.00541 RPN total loss: 0.08038 Total loss: 1.22587 timestamp: 1655035127.319739 iteration: 34065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10424 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.16697 L1 loss: 0.0000e+00 L2 loss: 0.70971 Learning rate: 0.02 Mask loss: 0.13829 RPN box loss: 0.02239 RPN score loss: 0.00559 RPN total loss: 0.02798 Total loss: 1.04295 timestamp: 1655035130.589158 iteration: 34070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12264 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 0.70961 Learning rate: 0.02 Mask loss: 0.14782 RPN box loss: 0.02606 RPN score loss: 0.00697 RPN total loss: 0.03302 Total loss: 1.07812 timestamp: 1655035133.8348045 iteration: 34075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07921 FastRCNN class loss: 0.06848 FastRCNN total loss: 0.14769 L1 loss: 0.0000e+00 L2 loss: 0.70951 Learning rate: 0.02 Mask loss: 0.16146 RPN box loss: 0.02824 RPN score loss: 0.00671 RPN total loss: 0.03495 Total loss: 1.05361 timestamp: 1655035137.0544612 iteration: 34080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13828 FastRCNN class loss: 0.08234 FastRCNN total loss: 0.22062 L1 loss: 0.0000e+00 L2 loss: 0.70943 Learning rate: 0.02 Mask loss: 0.24431 RPN box loss: 0.05499 RPN score loss: 0.00461 RPN total loss: 0.05959 Total loss: 1.23396 timestamp: 1655035140.4141133 iteration: 34085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23227 FastRCNN class loss: 0.12442 FastRCNN total loss: 0.3567 L1 loss: 0.0000e+00 L2 loss: 0.70931 Learning rate: 0.02 Mask loss: 0.25455 RPN box loss: 0.04779 RPN score loss: 0.011 RPN total loss: 0.05879 Total loss: 1.37935 timestamp: 1655035143.6684227 iteration: 34090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17 FastRCNN class loss: 0.11436 FastRCNN total loss: 0.28437 L1 loss: 0.0000e+00 L2 loss: 0.70919 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.0339 RPN score loss: 0.00999 RPN total loss: 0.04389 Total loss: 1.2041 timestamp: 1655035147.0140626 iteration: 34095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10013 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.17562 L1 loss: 0.0000e+00 L2 loss: 0.70909 Learning rate: 0.02 Mask loss: 0.118 RPN box loss: 0.02276 RPN score loss: 0.00416 RPN total loss: 0.02691 Total loss: 1.02962 timestamp: 1655035150.2474189 iteration: 34100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17899 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.25068 L1 loss: 0.0000e+00 L2 loss: 0.70898 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.04126 RPN score loss: 0.01155 RPN total loss: 0.05281 Total loss: 1.17913 timestamp: 1655035153.5713096 iteration: 34105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17914 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.27775 L1 loss: 0.0000e+00 L2 loss: 0.70889 Learning rate: 0.02 Mask loss: 0.16938 RPN box loss: 0.00843 RPN score loss: 0.00424 RPN total loss: 0.01266 Total loss: 1.16869 timestamp: 1655035156.8256695 iteration: 34110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17769 FastRCNN class loss: 0.0916 FastRCNN total loss: 0.26929 L1 loss: 0.0000e+00 L2 loss: 0.70881 Learning rate: 0.02 Mask loss: 0.16437 RPN box loss: 0.02631 RPN score loss: 0.01017 RPN total loss: 0.03648 Total loss: 1.17894 timestamp: 1655035160.1083272 iteration: 34115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13705 FastRCNN class loss: 0.10039 FastRCNN total loss: 0.23745 L1 loss: 0.0000e+00 L2 loss: 0.7087 Learning rate: 0.02 Mask loss: 0.13583 RPN box loss: 0.04929 RPN score loss: 0.02002 RPN total loss: 0.06931 Total loss: 1.15128 timestamp: 1655035163.4036188 iteration: 34120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12764 FastRCNN class loss: 0.07307 FastRCNN total loss: 0.20071 L1 loss: 0.0000e+00 L2 loss: 0.7086 Learning rate: 0.02 Mask loss: 0.18423 RPN box loss: 0.03593 RPN score loss: 0.01775 RPN total loss: 0.05368 Total loss: 1.14722 timestamp: 1655035166.6830413 iteration: 34125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19504 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.27921 L1 loss: 0.0000e+00 L2 loss: 0.70849 Learning rate: 0.02 Mask loss: 0.17296 RPN box loss: 0.02547 RPN score loss: 0.01157 RPN total loss: 0.03704 Total loss: 1.19771 timestamp: 1655035169.9875426 iteration: 34130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17101 FastRCNN class loss: 0.21604 FastRCNN total loss: 0.38705 L1 loss: 0.0000e+00 L2 loss: 0.70841 Learning rate: 0.02 Mask loss: 0.26838 RPN box loss: 0.05064 RPN score loss: 0.10892 RPN total loss: 0.15956 Total loss: 1.52339 timestamp: 1655035173.2584627 iteration: 34135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.16151 L1 loss: 0.0000e+00 L2 loss: 0.70832 Learning rate: 0.02 Mask loss: 0.12898 RPN box loss: 0.04685 RPN score loss: 0.00766 RPN total loss: 0.05451 Total loss: 1.05333 timestamp: 1655035176.5678778 iteration: 34140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21424 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.29209 L1 loss: 0.0000e+00 L2 loss: 0.70822 Learning rate: 0.02 Mask loss: 0.14623 RPN box loss: 0.03496 RPN score loss: 0.00565 RPN total loss: 0.04061 Total loss: 1.18715 timestamp: 1655035179.80129 iteration: 34145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15054 FastRCNN class loss: 0.07771 FastRCNN total loss: 0.22825 L1 loss: 0.0000e+00 L2 loss: 0.70811 Learning rate: 0.02 Mask loss: 0.14773 RPN box loss: 0.06349 RPN score loss: 0.00683 RPN total loss: 0.07032 Total loss: 1.1544 timestamp: 1655035183.0683389 iteration: 34150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.20315 L1 loss: 0.0000e+00 L2 loss: 0.70799 Learning rate: 0.02 Mask loss: 0.17382 RPN box loss: 0.03478 RPN score loss: 0.00682 RPN total loss: 0.0416 Total loss: 1.12656 timestamp: 1655035186.354607 iteration: 34155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11308 FastRCNN class loss: 0.06866 FastRCNN total loss: 0.18173 L1 loss: 0.0000e+00 L2 loss: 0.70789 Learning rate: 0.02 Mask loss: 0.17391 RPN box loss: 0.05268 RPN score loss: 0.00543 RPN total loss: 0.05811 Total loss: 1.12164 timestamp: 1655035189.6446064 iteration: 34160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.05035 FastRCNN total loss: 0.13919 L1 loss: 0.0000e+00 L2 loss: 0.70779 Learning rate: 0.02 Mask loss: 0.11405 RPN box loss: 0.02815 RPN score loss: 0.00337 RPN total loss: 0.03152 Total loss: 0.99256 timestamp: 1655035192.9037237 iteration: 34165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.13931 L1 loss: 0.0000e+00 L2 loss: 0.70769 Learning rate: 0.02 Mask loss: 0.19958 RPN box loss: 0.05189 RPN score loss: 0.01539 RPN total loss: 0.06729 Total loss: 1.11386 timestamp: 1655035196.1949377 iteration: 34170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18254 FastRCNN class loss: 0.09583 FastRCNN total loss: 0.27837 L1 loss: 0.0000e+00 L2 loss: 0.70757 Learning rate: 0.02 Mask loss: 0.16638 RPN box loss: 0.03652 RPN score loss: 0.0094 RPN total loss: 0.04592 Total loss: 1.19824 timestamp: 1655035199.457485 iteration: 34175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.15605 L1 loss: 0.0000e+00 L2 loss: 0.70746 Learning rate: 0.02 Mask loss: 0.11409 RPN box loss: 0.02949 RPN score loss: 0.00569 RPN total loss: 0.03519 Total loss: 1.01278 timestamp: 1655035202.6906607 iteration: 34180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14866 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.20496 L1 loss: 0.0000e+00 L2 loss: 0.70739 Learning rate: 0.02 Mask loss: 0.16234 RPN box loss: 0.09552 RPN score loss: 0.00484 RPN total loss: 0.10036 Total loss: 1.17504 timestamp: 1655035206.0356503 iteration: 34185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05938 FastRCNN class loss: 0.03704 FastRCNN total loss: 0.09642 L1 loss: 0.0000e+00 L2 loss: 0.7073 Learning rate: 0.02 Mask loss: 0.14995 RPN box loss: 0.00288 RPN score loss: 0.00185 RPN total loss: 0.00473 Total loss: 0.95841 timestamp: 1655035209.302068 iteration: 34190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16188 FastRCNN class loss: 0.11112 FastRCNN total loss: 0.273 L1 loss: 0.0000e+00 L2 loss: 0.70721 Learning rate: 0.02 Mask loss: 0.1946 RPN box loss: 0.04269 RPN score loss: 0.0197 RPN total loss: 0.06239 Total loss: 1.2372 timestamp: 1655035212.6003041 iteration: 34195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17272 FastRCNN class loss: 0.18185 FastRCNN total loss: 0.35457 L1 loss: 0.0000e+00 L2 loss: 0.70713 Learning rate: 0.02 Mask loss: 0.23426 RPN box loss: 0.04995 RPN score loss: 0.01161 RPN total loss: 0.06156 Total loss: 1.35752 timestamp: 1655035215.8875117 iteration: 34200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15634 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.24252 L1 loss: 0.0000e+00 L2 loss: 0.707 Learning rate: 0.02 Mask loss: 0.13914 RPN box loss: 0.03778 RPN score loss: 0.01999 RPN total loss: 0.05777 Total loss: 1.14643 timestamp: 1655035219.1327987 iteration: 34205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1482 FastRCNN class loss: 0.0783 FastRCNN total loss: 0.2265 L1 loss: 0.0000e+00 L2 loss: 0.70687 Learning rate: 0.02 Mask loss: 0.2 RPN box loss: 0.009 RPN score loss: 0.00557 RPN total loss: 0.01457 Total loss: 1.14795 timestamp: 1655035222.3934424 iteration: 34210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.18523 L1 loss: 0.0000e+00 L2 loss: 0.70679 Learning rate: 0.02 Mask loss: 0.14674 RPN box loss: 0.0115 RPN score loss: 0.00804 RPN total loss: 0.01953 Total loss: 1.05829 timestamp: 1655035225.6437914 iteration: 34215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.04815 FastRCNN total loss: 0.14016 L1 loss: 0.0000e+00 L2 loss: 0.70671 Learning rate: 0.02 Mask loss: 0.19127 RPN box loss: 0.00878 RPN score loss: 0.00289 RPN total loss: 0.01167 Total loss: 1.04981 timestamp: 1655035228.9022565 iteration: 34220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11203 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.18182 L1 loss: 0.0000e+00 L2 loss: 0.7066 Learning rate: 0.02 Mask loss: 0.14136 RPN box loss: 0.0246 RPN score loss: 0.00519 RPN total loss: 0.02979 Total loss: 1.05957 timestamp: 1655035232.1470418 iteration: 34225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13605 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.22021 L1 loss: 0.0000e+00 L2 loss: 0.70649 Learning rate: 0.02 Mask loss: 0.1417 RPN box loss: 0.05522 RPN score loss: 0.01404 RPN total loss: 0.06926 Total loss: 1.13765 timestamp: 1655035235.4998937 iteration: 34230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21373 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.29335 L1 loss: 0.0000e+00 L2 loss: 0.70639 Learning rate: 0.02 Mask loss: 0.13255 RPN box loss: 0.01155 RPN score loss: 0.00394 RPN total loss: 0.01548 Total loss: 1.14777 timestamp: 1655035238.7392 iteration: 34235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21546 FastRCNN class loss: 0.08363 FastRCNN total loss: 0.29909 L1 loss: 0.0000e+00 L2 loss: 0.70629 Learning rate: 0.02 Mask loss: 0.15766 RPN box loss: 0.03817 RPN score loss: 0.00419 RPN total loss: 0.04236 Total loss: 1.2054 timestamp: 1655035242.0004053 iteration: 34240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13157 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.22095 L1 loss: 0.0000e+00 L2 loss: 0.70618 Learning rate: 0.02 Mask loss: 0.18116 RPN box loss: 0.01724 RPN score loss: 0.00474 RPN total loss: 0.02198 Total loss: 1.13027 timestamp: 1655035245.253451 iteration: 34245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.17899 L1 loss: 0.0000e+00 L2 loss: 0.70606 Learning rate: 0.02 Mask loss: 0.16293 RPN box loss: 0.02234 RPN score loss: 0.00476 RPN total loss: 0.02709 Total loss: 1.07507 timestamp: 1655035248.4985216 iteration: 34250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06066 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.13584 L1 loss: 0.0000e+00 L2 loss: 0.70596 Learning rate: 0.02 Mask loss: 0.14218 RPN box loss: 0.0086 RPN score loss: 0.0074 RPN total loss: 0.01599 Total loss: 0.99997 timestamp: 1655035251.7820683 iteration: 34255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10891 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.1882 L1 loss: 0.0000e+00 L2 loss: 0.70588 Learning rate: 0.02 Mask loss: 0.097 RPN box loss: 0.02925 RPN score loss: 0.00865 RPN total loss: 0.0379 Total loss: 1.02897 timestamp: 1655035255.0122297 iteration: 34260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14309 FastRCNN class loss: 0.11598 FastRCNN total loss: 0.25906 L1 loss: 0.0000e+00 L2 loss: 0.70578 Learning rate: 0.02 Mask loss: 0.20649 RPN box loss: 0.01814 RPN score loss: 0.00257 RPN total loss: 0.02072 Total loss: 1.19205 timestamp: 1655035258.2860513 iteration: 34265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07185 FastRCNN class loss: 0.10053 FastRCNN total loss: 0.17237 L1 loss: 0.0000e+00 L2 loss: 0.70569 Learning rate: 0.02 Mask loss: 0.12328 RPN box loss: 0.02186 RPN score loss: 0.01702 RPN total loss: 0.03887 Total loss: 1.04021 timestamp: 1655035261.6044412 iteration: 34270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13823 FastRCNN class loss: 0.08875 FastRCNN total loss: 0.22698 L1 loss: 0.0000e+00 L2 loss: 0.70558 Learning rate: 0.02 Mask loss: 0.18471 RPN box loss: 0.02084 RPN score loss: 0.0078 RPN total loss: 0.02864 Total loss: 1.14592 timestamp: 1655035264.894126 iteration: 34275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16201 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.21711 L1 loss: 0.0000e+00 L2 loss: 0.70548 Learning rate: 0.02 Mask loss: 0.14137 RPN box loss: 0.02012 RPN score loss: 0.00362 RPN total loss: 0.02374 Total loss: 1.0877 timestamp: 1655035268.1518946 iteration: 34280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.04818 FastRCNN total loss: 0.15943 L1 loss: 0.0000e+00 L2 loss: 0.70537 Learning rate: 0.02 Mask loss: 0.14024 RPN box loss: 0.0134 RPN score loss: 0.0046 RPN total loss: 0.01801 Total loss: 1.02305 timestamp: 1655035271.467892 iteration: 34285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13163 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.21643 L1 loss: 0.0000e+00 L2 loss: 0.70528 Learning rate: 0.02 Mask loss: 0.22095 RPN box loss: 0.02829 RPN score loss: 0.00558 RPN total loss: 0.03387 Total loss: 1.17652 timestamp: 1655035274.7542791 iteration: 34290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14136 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.2105 L1 loss: 0.0000e+00 L2 loss: 0.70519 Learning rate: 0.02 Mask loss: 0.17182 RPN box loss: 0.05008 RPN score loss: 0.01559 RPN total loss: 0.06567 Total loss: 1.15318 timestamp: 1655035278.0979235 iteration: 34295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14104 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.21914 L1 loss: 0.0000e+00 L2 loss: 0.70509 Learning rate: 0.02 Mask loss: 0.16097 RPN box loss: 0.01907 RPN score loss: 0.00508 RPN total loss: 0.02415 Total loss: 1.10936 timestamp: 1655035281.404754 iteration: 34300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12778 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.18489 L1 loss: 0.0000e+00 L2 loss: 0.70497 Learning rate: 0.02 Mask loss: 0.16282 RPN box loss: 0.02737 RPN score loss: 0.00997 RPN total loss: 0.03734 Total loss: 1.09002 timestamp: 1655035284.6923027 iteration: 34305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0985 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.16261 L1 loss: 0.0000e+00 L2 loss: 0.70487 Learning rate: 0.02 Mask loss: 0.11861 RPN box loss: 0.01323 RPN score loss: 0.00472 RPN total loss: 0.01795 Total loss: 1.00404 timestamp: 1655035287.9755487 iteration: 34310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17101 FastRCNN class loss: 0.09774 FastRCNN total loss: 0.26875 L1 loss: 0.0000e+00 L2 loss: 0.70476 Learning rate: 0.02 Mask loss: 0.15531 RPN box loss: 0.0959 RPN score loss: 0.00987 RPN total loss: 0.10576 Total loss: 1.23458 timestamp: 1655035291.2565122 iteration: 34315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13823 FastRCNN class loss: 0.11231 FastRCNN total loss: 0.25054 L1 loss: 0.0000e+00 L2 loss: 0.70463 Learning rate: 0.02 Mask loss: 0.16691 RPN box loss: 0.06833 RPN score loss: 0.0082 RPN total loss: 0.07653 Total loss: 1.19862 timestamp: 1655035294.565575 iteration: 34320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15362 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.24223 L1 loss: 0.0000e+00 L2 loss: 0.70453 Learning rate: 0.02 Mask loss: 0.14604 RPN box loss: 0.05571 RPN score loss: 0.02043 RPN total loss: 0.07614 Total loss: 1.16895 timestamp: 1655035297.7315273 iteration: 34325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16358 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.23046 L1 loss: 0.0000e+00 L2 loss: 0.70443 Learning rate: 0.02 Mask loss: 0.11018 RPN box loss: 0.05074 RPN score loss: 0.04486 RPN total loss: 0.0956 Total loss: 1.14068 timestamp: 1655035301.0198927 iteration: 34330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11056 FastRCNN class loss: 0.09231 FastRCNN total loss: 0.20287 L1 loss: 0.0000e+00 L2 loss: 0.70433 Learning rate: 0.02 Mask loss: 0.15249 RPN box loss: 0.03388 RPN score loss: 0.00461 RPN total loss: 0.03849 Total loss: 1.09819 timestamp: 1655035304.285984 iteration: 34335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13986 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.21651 L1 loss: 0.0000e+00 L2 loss: 0.70423 Learning rate: 0.02 Mask loss: 0.12987 RPN box loss: 0.04183 RPN score loss: 0.00747 RPN total loss: 0.0493 Total loss: 1.09991 timestamp: 1655035307.516858 iteration: 34340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15203 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.21127 L1 loss: 0.0000e+00 L2 loss: 0.70413 Learning rate: 0.02 Mask loss: 0.09977 RPN box loss: 0.01605 RPN score loss: 0.00239 RPN total loss: 0.01844 Total loss: 1.03361 timestamp: 1655035310.824301 iteration: 34345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11828 FastRCNN class loss: 0.06786 FastRCNN total loss: 0.18614 L1 loss: 0.0000e+00 L2 loss: 0.70402 Learning rate: 0.02 Mask loss: 0.10139 RPN box loss: 0.02971 RPN score loss: 0.00316 RPN total loss: 0.03287 Total loss: 1.02442 timestamp: 1655035314.1157687 iteration: 34350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17427 FastRCNN class loss: 0.15589 FastRCNN total loss: 0.33016 L1 loss: 0.0000e+00 L2 loss: 0.70393 Learning rate: 0.02 Mask loss: 0.25367 RPN box loss: 0.0407 RPN score loss: 0.01329 RPN total loss: 0.05399 Total loss: 1.34174 timestamp: 1655035317.3632915 iteration: 34355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11535 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.18648 L1 loss: 0.0000e+00 L2 loss: 0.70386 Learning rate: 0.02 Mask loss: 0.17942 RPN box loss: 0.01848 RPN score loss: 0.00441 RPN total loss: 0.0229 Total loss: 1.09265 timestamp: 1655035320.7040863 iteration: 34360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12657 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.20665 L1 loss: 0.0000e+00 L2 loss: 0.70375 Learning rate: 0.02 Mask loss: 0.1302 RPN box loss: 0.03369 RPN score loss: 0.00463 RPN total loss: 0.03831 Total loss: 1.07892 timestamp: 1655035323.9803581 iteration: 34365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17928 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.23955 L1 loss: 0.0000e+00 L2 loss: 0.70366 Learning rate: 0.02 Mask loss: 0.14533 RPN box loss: 0.02679 RPN score loss: 0.0055 RPN total loss: 0.03229 Total loss: 1.12083 timestamp: 1655035327.3189032 iteration: 34370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13819 FastRCNN class loss: 0.12457 FastRCNN total loss: 0.26276 L1 loss: 0.0000e+00 L2 loss: 0.70356 Learning rate: 0.02 Mask loss: 0.20898 RPN box loss: 0.01362 RPN score loss: 0.00442 RPN total loss: 0.01805 Total loss: 1.19335 timestamp: 1655035330.6203218 iteration: 34375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18034 FastRCNN class loss: 0.08186 FastRCNN total loss: 0.26221 L1 loss: 0.0000e+00 L2 loss: 0.70342 Learning rate: 0.02 Mask loss: 0.21042 RPN box loss: 0.04196 RPN score loss: 0.00713 RPN total loss: 0.04909 Total loss: 1.22513 timestamp: 1655035333.9013515 iteration: 34380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12399 FastRCNN class loss: 0.08337 FastRCNN total loss: 0.20735 L1 loss: 0.0000e+00 L2 loss: 0.70332 Learning rate: 0.02 Mask loss: 0.13968 RPN box loss: 0.03818 RPN score loss: 0.01166 RPN total loss: 0.04983 Total loss: 1.1002 timestamp: 1655035337.1937888 iteration: 34385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21322 FastRCNN class loss: 0.09377 FastRCNN total loss: 0.30698 L1 loss: 0.0000e+00 L2 loss: 0.70323 Learning rate: 0.02 Mask loss: 0.17546 RPN box loss: 0.03401 RPN score loss: 0.00935 RPN total loss: 0.04336 Total loss: 1.22903 timestamp: 1655035340.5235438 iteration: 34390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12079 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.19132 L1 loss: 0.0000e+00 L2 loss: 0.70312 Learning rate: 0.02 Mask loss: 0.12433 RPN box loss: 0.0332 RPN score loss: 0.00375 RPN total loss: 0.03694 Total loss: 1.05571 timestamp: 1655035343.78327 iteration: 34395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14316 FastRCNN class loss: 0.11543 FastRCNN total loss: 0.25859 L1 loss: 0.0000e+00 L2 loss: 0.70306 Learning rate: 0.02 Mask loss: 0.20339 RPN box loss: 0.0298 RPN score loss: 0.02006 RPN total loss: 0.04986 Total loss: 1.2149 timestamp: 1655035347.0823014 iteration: 34400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13787 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.26297 L1 loss: 0.0000e+00 L2 loss: 0.70296 Learning rate: 0.02 Mask loss: 0.15268 RPN box loss: 0.02023 RPN score loss: 0.00835 RPN total loss: 0.02858 Total loss: 1.1472 timestamp: 1655035350.3006604 iteration: 34405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13871 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.21342 L1 loss: 0.0000e+00 L2 loss: 0.70287 Learning rate: 0.02 Mask loss: 0.28647 RPN box loss: 0.02201 RPN score loss: 0.00201 RPN total loss: 0.02402 Total loss: 1.22679 timestamp: 1655035353.5522194 iteration: 34410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21086 FastRCNN class loss: 0.112 FastRCNN total loss: 0.32287 L1 loss: 0.0000e+00 L2 loss: 0.70279 Learning rate: 0.02 Mask loss: 0.18299 RPN box loss: 0.03941 RPN score loss: 0.00951 RPN total loss: 0.04892 Total loss: 1.25756 timestamp: 1655035356.7886643 iteration: 34415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16097 FastRCNN class loss: 0.10248 FastRCNN total loss: 0.26345 L1 loss: 0.0000e+00 L2 loss: 0.70269 Learning rate: 0.02 Mask loss: 0.19343 RPN box loss: 0.06401 RPN score loss: 0.01173 RPN total loss: 0.07574 Total loss: 1.2353 timestamp: 1655035360.1097927 iteration: 34420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21453 FastRCNN class loss: 0.0974 FastRCNN total loss: 0.31192 L1 loss: 0.0000e+00 L2 loss: 0.7026 Learning rate: 0.02 Mask loss: 0.11677 RPN box loss: 0.00972 RPN score loss: 0.00177 RPN total loss: 0.01149 Total loss: 1.14278 timestamp: 1655035363.4523258 iteration: 34425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1385 FastRCNN class loss: 0.10953 FastRCNN total loss: 0.24802 L1 loss: 0.0000e+00 L2 loss: 0.70249 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.02312 RPN score loss: 0.01208 RPN total loss: 0.0352 Total loss: 1.14308 timestamp: 1655035366.7380452 iteration: 34430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22982 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.29414 L1 loss: 0.0000e+00 L2 loss: 0.70239 Learning rate: 0.02 Mask loss: 0.11898 RPN box loss: 0.03488 RPN score loss: 0.0075 RPN total loss: 0.04238 Total loss: 1.15788 timestamp: 1655035370.0114887 iteration: 34435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16285 FastRCNN class loss: 0.09167 FastRCNN total loss: 0.25452 L1 loss: 0.0000e+00 L2 loss: 0.70229 Learning rate: 0.02 Mask loss: 0.17617 RPN box loss: 0.04806 RPN score loss: 0.01678 RPN total loss: 0.06484 Total loss: 1.19782 timestamp: 1655035373.2706063 iteration: 34440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14318 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.23171 L1 loss: 0.0000e+00 L2 loss: 0.70217 Learning rate: 0.02 Mask loss: 0.18311 RPN box loss: 0.05633 RPN score loss: 0.00935 RPN total loss: 0.06568 Total loss: 1.18267 timestamp: 1655035376.5212388 iteration: 34445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19093 FastRCNN class loss: 0.10752 FastRCNN total loss: 0.29846 L1 loss: 0.0000e+00 L2 loss: 0.70207 Learning rate: 0.02 Mask loss: 0.20049 RPN box loss: 0.04225 RPN score loss: 0.01117 RPN total loss: 0.05342 Total loss: 1.25443 timestamp: 1655035379.7694395 iteration: 34450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13898 FastRCNN class loss: 0.12209 FastRCNN total loss: 0.26107 L1 loss: 0.0000e+00 L2 loss: 0.70197 Learning rate: 0.02 Mask loss: 0.16027 RPN box loss: 0.04651 RPN score loss: 0.02118 RPN total loss: 0.06769 Total loss: 1.191 timestamp: 1655035383.005678 iteration: 34455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13479 FastRCNN class loss: 0.05002 FastRCNN total loss: 0.18482 L1 loss: 0.0000e+00 L2 loss: 0.70185 Learning rate: 0.02 Mask loss: 0.19941 RPN box loss: 0.06524 RPN score loss: 0.01375 RPN total loss: 0.07899 Total loss: 1.16507 timestamp: 1655035386.3250802 iteration: 34460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24553 FastRCNN class loss: 0.10832 FastRCNN total loss: 0.35384 L1 loss: 0.0000e+00 L2 loss: 0.70178 Learning rate: 0.02 Mask loss: 0.18638 RPN box loss: 0.02092 RPN score loss: 0.00338 RPN total loss: 0.02431 Total loss: 1.26632 timestamp: 1655035389.593379 iteration: 34465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.1719 L1 loss: 0.0000e+00 L2 loss: 0.70167 Learning rate: 0.02 Mask loss: 0.13953 RPN box loss: 0.06903 RPN score loss: 0.00607 RPN total loss: 0.0751 Total loss: 1.0882 timestamp: 1655035392.8621264 iteration: 34470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18209 FastRCNN class loss: 0.12267 FastRCNN total loss: 0.30475 L1 loss: 0.0000e+00 L2 loss: 0.70157 Learning rate: 0.02 Mask loss: 0.22193 RPN box loss: 0.01684 RPN score loss: 0.0074 RPN total loss: 0.02424 Total loss: 1.2525 timestamp: 1655035396.1403751 iteration: 34475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15136 FastRCNN class loss: 0.11132 FastRCNN total loss: 0.26268 L1 loss: 0.0000e+00 L2 loss: 0.70147 Learning rate: 0.02 Mask loss: 0.16271 RPN box loss: 0.02636 RPN score loss: 0.01028 RPN total loss: 0.03664 Total loss: 1.1635 timestamp: 1655035399.343377 iteration: 34480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16817 FastRCNN class loss: 0.10124 FastRCNN total loss: 0.2694 L1 loss: 0.0000e+00 L2 loss: 0.70138 Learning rate: 0.02 Mask loss: 0.22314 RPN box loss: 0.02459 RPN score loss: 0.00676 RPN total loss: 0.03135 Total loss: 1.22527 timestamp: 1655035402.588088 iteration: 34485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10805 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.15599 L1 loss: 0.0000e+00 L2 loss: 0.70127 Learning rate: 0.02 Mask loss: 0.08507 RPN box loss: 0.0139 RPN score loss: 0.00263 RPN total loss: 0.01653 Total loss: 0.95885 timestamp: 1655035405.8652177 iteration: 34490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12134 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.19747 L1 loss: 0.0000e+00 L2 loss: 0.70117 Learning rate: 0.02 Mask loss: 0.10116 RPN box loss: 0.04485 RPN score loss: 0.00332 RPN total loss: 0.04817 Total loss: 1.04797 timestamp: 1655035409.178664 iteration: 34495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09956 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.15371 L1 loss: 0.0000e+00 L2 loss: 0.70107 Learning rate: 0.02 Mask loss: 0.12172 RPN box loss: 0.06793 RPN score loss: 0.00551 RPN total loss: 0.07344 Total loss: 1.04994 timestamp: 1655035412.4350138 iteration: 34500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11906 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.17505 L1 loss: 0.0000e+00 L2 loss: 0.70097 Learning rate: 0.02 Mask loss: 0.12853 RPN box loss: 0.01788 RPN score loss: 0.00423 RPN total loss: 0.02211 Total loss: 1.02667 timestamp: 1655035415.725792 iteration: 34505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1838 FastRCNN class loss: 0.14553 FastRCNN total loss: 0.32933 L1 loss: 0.0000e+00 L2 loss: 0.70087 Learning rate: 0.02 Mask loss: 0.21104 RPN box loss: 0.01988 RPN score loss: 0.00582 RPN total loss: 0.0257 Total loss: 1.26694 timestamp: 1655035419.0641346 iteration: 34510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17386 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.25889 L1 loss: 0.0000e+00 L2 loss: 0.70077 Learning rate: 0.02 Mask loss: 0.23983 RPN box loss: 0.02047 RPN score loss: 0.00453 RPN total loss: 0.025 Total loss: 1.22449 timestamp: 1655035422.37316 iteration: 34515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16386 FastRCNN class loss: 0.12283 FastRCNN total loss: 0.28669 L1 loss: 0.0000e+00 L2 loss: 0.70067 Learning rate: 0.02 Mask loss: 0.22522 RPN box loss: 0.03529 RPN score loss: 0.00963 RPN total loss: 0.04492 Total loss: 1.2575 timestamp: 1655035425.661815 iteration: 34520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16097 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.23186 L1 loss: 0.0000e+00 L2 loss: 0.70056 Learning rate: 0.02 Mask loss: 0.15467 RPN box loss: 0.02757 RPN score loss: 0.00963 RPN total loss: 0.0372 Total loss: 1.12429 timestamp: 1655035428.9821446 iteration: 34525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09125 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.15779 L1 loss: 0.0000e+00 L2 loss: 0.70048 Learning rate: 0.02 Mask loss: 0.16251 RPN box loss: 0.04017 RPN score loss: 0.00576 RPN total loss: 0.04592 Total loss: 1.06671 timestamp: 1655035432.2700377 iteration: 34530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10339 FastRCNN class loss: 0.03198 FastRCNN total loss: 0.13537 L1 loss: 0.0000e+00 L2 loss: 0.70038 Learning rate: 0.02 Mask loss: 0.07423 RPN box loss: 0.00721 RPN score loss: 0.00244 RPN total loss: 0.00965 Total loss: 0.91963 timestamp: 1655035435.5738413 iteration: 34535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.70026 Learning rate: 0.02 Mask loss: 0.13804 RPN box loss: 0.04536 RPN score loss: 0.00436 RPN total loss: 0.04972 Total loss: 1.08165 timestamp: 1655035438.8895793 iteration: 34540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13015 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.22096 L1 loss: 0.0000e+00 L2 loss: 0.70019 Learning rate: 0.02 Mask loss: 0.22257 RPN box loss: 0.04449 RPN score loss: 0.03963 RPN total loss: 0.08411 Total loss: 1.22784 timestamp: 1655035442.186927 iteration: 34545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13017 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.21492 L1 loss: 0.0000e+00 L2 loss: 0.7001 Learning rate: 0.02 Mask loss: 0.1217 RPN box loss: 0.0296 RPN score loss: 0.00667 RPN total loss: 0.03627 Total loss: 1.07298 timestamp: 1655035445.4855998 iteration: 34550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16057 FastRCNN class loss: 0.0572 FastRCNN total loss: 0.21776 L1 loss: 0.0000e+00 L2 loss: 0.69997 Learning rate: 0.02 Mask loss: 0.14417 RPN box loss: 0.01116 RPN score loss: 0.00351 RPN total loss: 0.01467 Total loss: 1.07657 timestamp: 1655035448.822866 iteration: 34555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1254 FastRCNN class loss: 0.11824 FastRCNN total loss: 0.24364 L1 loss: 0.0000e+00 L2 loss: 0.6999 Learning rate: 0.02 Mask loss: 0.14482 RPN box loss: 0.04134 RPN score loss: 0.00351 RPN total loss: 0.04485 Total loss: 1.13321 timestamp: 1655035452.081228 iteration: 34560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.30396 FastRCNN class loss: 0.13236 FastRCNN total loss: 0.43631 L1 loss: 0.0000e+00 L2 loss: 0.69983 Learning rate: 0.02 Mask loss: 0.25769 RPN box loss: 0.06157 RPN score loss: 0.01249 RPN total loss: 0.07407 Total loss: 1.4679 timestamp: 1655035455.3809586 iteration: 34565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07494 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.15577 L1 loss: 0.0000e+00 L2 loss: 0.69973 Learning rate: 0.02 Mask loss: 0.17893 RPN box loss: 0.04765 RPN score loss: 0.01747 RPN total loss: 0.06512 Total loss: 1.09955 timestamp: 1655035458.6839368 iteration: 34570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15492 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.22742 L1 loss: 0.0000e+00 L2 loss: 0.69963 Learning rate: 0.02 Mask loss: 0.10501 RPN box loss: 0.06 RPN score loss: 0.00732 RPN total loss: 0.06732 Total loss: 1.09938 timestamp: 1655035462.0181298 iteration: 34575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.17838 L1 loss: 0.0000e+00 L2 loss: 0.69953 Learning rate: 0.02 Mask loss: 0.17469 RPN box loss: 0.01712 RPN score loss: 0.00455 RPN total loss: 0.02168 Total loss: 1.07427 timestamp: 1655035465.254713 iteration: 34580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13715 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.21066 L1 loss: 0.0000e+00 L2 loss: 0.69943 Learning rate: 0.02 Mask loss: 0.13555 RPN box loss: 0.02692 RPN score loss: 0.0065 RPN total loss: 0.03342 Total loss: 1.07907 timestamp: 1655035468.527328 iteration: 34585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.053 FastRCNN total loss: 0.11767 L1 loss: 0.0000e+00 L2 loss: 0.69934 Learning rate: 0.02 Mask loss: 0.10269 RPN box loss: 0.00264 RPN score loss: 0.00252 RPN total loss: 0.00516 Total loss: 0.92486 timestamp: 1655035471.8126564 iteration: 34590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06268 FastRCNN class loss: 0.04206 FastRCNN total loss: 0.10475 L1 loss: 0.0000e+00 L2 loss: 0.69926 Learning rate: 0.02 Mask loss: 0.11393 RPN box loss: 0.01574 RPN score loss: 0.00137 RPN total loss: 0.01711 Total loss: 0.93506 timestamp: 1655035475.0467503 iteration: 34595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16834 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.24012 L1 loss: 0.0000e+00 L2 loss: 0.69916 Learning rate: 0.02 Mask loss: 0.14946 RPN box loss: 0.02771 RPN score loss: 0.00756 RPN total loss: 0.03527 Total loss: 1.12402 timestamp: 1655035478.3260643 iteration: 34600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10075 FastRCNN class loss: 0.07538 FastRCNN total loss: 0.17614 L1 loss: 0.0000e+00 L2 loss: 0.69905 Learning rate: 0.02 Mask loss: 0.13523 RPN box loss: 0.01865 RPN score loss: 0.00713 RPN total loss: 0.02578 Total loss: 1.0362 timestamp: 1655035481.6372905 iteration: 34605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11427 FastRCNN class loss: 0.08353 FastRCNN total loss: 0.1978 L1 loss: 0.0000e+00 L2 loss: 0.69897 Learning rate: 0.02 Mask loss: 0.17658 RPN box loss: 0.02829 RPN score loss: 0.01251 RPN total loss: 0.0408 Total loss: 1.11415 timestamp: 1655035484.8837335 iteration: 34610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15567 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.23529 L1 loss: 0.0000e+00 L2 loss: 0.69887 Learning rate: 0.02 Mask loss: 0.13113 RPN box loss: 0.0187 RPN score loss: 0.01809 RPN total loss: 0.03679 Total loss: 1.10208 timestamp: 1655035488.163674 iteration: 34615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10098 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.18094 L1 loss: 0.0000e+00 L2 loss: 0.69877 Learning rate: 0.02 Mask loss: 0.16465 RPN box loss: 0.06 RPN score loss: 0.01159 RPN total loss: 0.07159 Total loss: 1.11595 timestamp: 1655035491.466062 iteration: 34620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14915 FastRCNN class loss: 0.11469 FastRCNN total loss: 0.26384 L1 loss: 0.0000e+00 L2 loss: 0.69863 Learning rate: 0.02 Mask loss: 0.18466 RPN box loss: 0.02027 RPN score loss: 0.00636 RPN total loss: 0.02663 Total loss: 1.17376 timestamp: 1655035494.6982648 iteration: 34625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20892 FastRCNN class loss: 0.13061 FastRCNN total loss: 0.33953 L1 loss: 0.0000e+00 L2 loss: 0.69853 Learning rate: 0.02 Mask loss: 0.15532 RPN box loss: 0.0213 RPN score loss: 0.00351 RPN total loss: 0.02481 Total loss: 1.21818 timestamp: 1655035498.0029278 iteration: 34630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15811 FastRCNN class loss: 0.10042 FastRCNN total loss: 0.25853 L1 loss: 0.0000e+00 L2 loss: 0.69845 Learning rate: 0.02 Mask loss: 0.18989 RPN box loss: 0.03865 RPN score loss: 0.00811 RPN total loss: 0.04676 Total loss: 1.19363 timestamp: 1655035501.237217 iteration: 34635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12802 FastRCNN class loss: 0.08187 FastRCNN total loss: 0.20989 L1 loss: 0.0000e+00 L2 loss: 0.69836 Learning rate: 0.02 Mask loss: 0.19783 RPN box loss: 0.03367 RPN score loss: 0.00983 RPN total loss: 0.0435 Total loss: 1.14957 timestamp: 1655035504.495255 iteration: 34640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12315 FastRCNN class loss: 0.08325 FastRCNN total loss: 0.2064 L1 loss: 0.0000e+00 L2 loss: 0.69828 Learning rate: 0.02 Mask loss: 0.13773 RPN box loss: 0.04721 RPN score loss: 0.00598 RPN total loss: 0.05319 Total loss: 1.0956 timestamp: 1655035507.8088448 iteration: 34645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07654 FastRCNN class loss: 0.11214 FastRCNN total loss: 0.18868 L1 loss: 0.0000e+00 L2 loss: 0.69817 Learning rate: 0.02 Mask loss: 0.13417 RPN box loss: 0.01404 RPN score loss: 0.00782 RPN total loss: 0.02186 Total loss: 1.04288 timestamp: 1655035511.0448902 iteration: 34650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11879 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.18895 L1 loss: 0.0000e+00 L2 loss: 0.69808 Learning rate: 0.02 Mask loss: 0.1387 RPN box loss: 0.05688 RPN score loss: 0.00458 RPN total loss: 0.06146 Total loss: 1.0872 timestamp: 1655035514.3027833 iteration: 34655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12285 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.17715 L1 loss: 0.0000e+00 L2 loss: 0.698 Learning rate: 0.02 Mask loss: 0.15814 RPN box loss: 0.0125 RPN score loss: 0.00186 RPN total loss: 0.01436 Total loss: 1.04765 timestamp: 1655035517.5801232 iteration: 34660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16545 FastRCNN class loss: 0.11087 FastRCNN total loss: 0.27632 L1 loss: 0.0000e+00 L2 loss: 0.6979 Learning rate: 0.02 Mask loss: 0.11475 RPN box loss: 0.0362 RPN score loss: 0.00777 RPN total loss: 0.04398 Total loss: 1.13295 timestamp: 1655035520.842865 iteration: 34665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13389 FastRCNN class loss: 0.15041 FastRCNN total loss: 0.2843 L1 loss: 0.0000e+00 L2 loss: 0.6978 Learning rate: 0.02 Mask loss: 0.19133 RPN box loss: 0.0298 RPN score loss: 0.01242 RPN total loss: 0.04222 Total loss: 1.21565 timestamp: 1655035524.1441817 iteration: 34670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05148 FastRCNN class loss: 0.03337 FastRCNN total loss: 0.08486 L1 loss: 0.0000e+00 L2 loss: 0.69769 Learning rate: 0.02 Mask loss: 0.10343 RPN box loss: 0.00523 RPN score loss: 0.00205 RPN total loss: 0.00728 Total loss: 0.89326 timestamp: 1655035527.3447568 iteration: 34675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16714 FastRCNN class loss: 0.13728 FastRCNN total loss: 0.30441 L1 loss: 0.0000e+00 L2 loss: 0.6976 Learning rate: 0.02 Mask loss: 0.18673 RPN box loss: 0.05116 RPN score loss: 0.00634 RPN total loss: 0.0575 Total loss: 1.24624 timestamp: 1655035530.53413 iteration: 34680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21938 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.29809 L1 loss: 0.0000e+00 L2 loss: 0.69752 Learning rate: 0.02 Mask loss: 0.16464 RPN box loss: 0.03572 RPN score loss: 0.01303 RPN total loss: 0.04875 Total loss: 1.209 timestamp: 1655035533.750499 iteration: 34685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13739 FastRCNN class loss: 0.11363 FastRCNN total loss: 0.25102 L1 loss: 0.0000e+00 L2 loss: 0.69741 Learning rate: 0.02 Mask loss: 0.22188 RPN box loss: 0.02362 RPN score loss: 0.00599 RPN total loss: 0.02961 Total loss: 1.19992 timestamp: 1655035536.97154 iteration: 34690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0921 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.15632 L1 loss: 0.0000e+00 L2 loss: 0.69733 Learning rate: 0.02 Mask loss: 0.16036 RPN box loss: 0.04118 RPN score loss: 0.00515 RPN total loss: 0.04634 Total loss: 1.06035 timestamp: 1655035540.3068936 iteration: 34695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13187 FastRCNN class loss: 0.11901 FastRCNN total loss: 0.25088 L1 loss: 0.0000e+00 L2 loss: 0.69722 Learning rate: 0.02 Mask loss: 0.15821 RPN box loss: 0.02342 RPN score loss: 0.00705 RPN total loss: 0.03048 Total loss: 1.13679 timestamp: 1655035543.5655165 iteration: 34700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23067 FastRCNN class loss: 0.11189 FastRCNN total loss: 0.34255 L1 loss: 0.0000e+00 L2 loss: 0.69712 Learning rate: 0.02 Mask loss: 0.19543 RPN box loss: 0.04743 RPN score loss: 0.02447 RPN total loss: 0.0719 Total loss: 1.307 timestamp: 1655035546.87444 iteration: 34705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09534 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.14711 L1 loss: 0.0000e+00 L2 loss: 0.697 Learning rate: 0.02 Mask loss: 0.17311 RPN box loss: 0.01586 RPN score loss: 0.00213 RPN total loss: 0.01799 Total loss: 1.03521 timestamp: 1655035550.1799963 iteration: 34710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.09825 FastRCNN total loss: 0.22455 L1 loss: 0.0000e+00 L2 loss: 0.69688 Learning rate: 0.02 Mask loss: 0.14651 RPN box loss: 0.05807 RPN score loss: 0.02729 RPN total loss: 0.08536 Total loss: 1.1533 timestamp: 1655035553.4770062 iteration: 34715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.17351 L1 loss: 0.0000e+00 L2 loss: 0.69678 Learning rate: 0.02 Mask loss: 0.15181 RPN box loss: 0.03055 RPN score loss: 0.00811 RPN total loss: 0.03866 Total loss: 1.06076 timestamp: 1655035556.7179239 iteration: 34720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10011 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.16551 L1 loss: 0.0000e+00 L2 loss: 0.69668 Learning rate: 0.02 Mask loss: 0.13897 RPN box loss: 0.05755 RPN score loss: 0.00696 RPN total loss: 0.06451 Total loss: 1.06568 timestamp: 1655035559.9639428 iteration: 34725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20422 FastRCNN class loss: 0.09479 FastRCNN total loss: 0.29901 L1 loss: 0.0000e+00 L2 loss: 0.69659 Learning rate: 0.02 Mask loss: 0.16152 RPN box loss: 0.02835 RPN score loss: 0.00655 RPN total loss: 0.03489 Total loss: 1.19202 timestamp: 1655035563.281344 iteration: 34730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19547 FastRCNN class loss: 0.14879 FastRCNN total loss: 0.34425 L1 loss: 0.0000e+00 L2 loss: 0.69649 Learning rate: 0.02 Mask loss: 0.19381 RPN box loss: 0.02272 RPN score loss: 0.01295 RPN total loss: 0.03567 Total loss: 1.27023 timestamp: 1655035566.555341 iteration: 34735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0692 FastRCNN class loss: 0.05149 FastRCNN total loss: 0.12069 L1 loss: 0.0000e+00 L2 loss: 0.69638 Learning rate: 0.02 Mask loss: 0.15417 RPN box loss: 0.01351 RPN score loss: 0.00151 RPN total loss: 0.01502 Total loss: 0.98626 timestamp: 1655035569.7942913 iteration: 34740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13892 FastRCNN class loss: 0.08595 FastRCNN total loss: 0.22487 L1 loss: 0.0000e+00 L2 loss: 0.6963 Learning rate: 0.02 Mask loss: 0.13485 RPN box loss: 0.04991 RPN score loss: 0.00496 RPN total loss: 0.05487 Total loss: 1.11088 timestamp: 1655035573.0348396 iteration: 34745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14066 FastRCNN class loss: 0.07409 FastRCNN total loss: 0.21475 L1 loss: 0.0000e+00 L2 loss: 0.69619 Learning rate: 0.02 Mask loss: 0.15817 RPN box loss: 0.03763 RPN score loss: 0.00339 RPN total loss: 0.04102 Total loss: 1.11013 timestamp: 1655035576.3263803 iteration: 34750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.08361 FastRCNN total loss: 0.22468 L1 loss: 0.0000e+00 L2 loss: 0.69609 Learning rate: 0.02 Mask loss: 0.11812 RPN box loss: 0.03171 RPN score loss: 0.00487 RPN total loss: 0.03659 Total loss: 1.07548 timestamp: 1655035579.582937 iteration: 34755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10438 FastRCNN class loss: 0.09537 FastRCNN total loss: 0.19975 L1 loss: 0.0000e+00 L2 loss: 0.69598 Learning rate: 0.02 Mask loss: 0.21135 RPN box loss: 0.03505 RPN score loss: 0.01513 RPN total loss: 0.05018 Total loss: 1.15726 timestamp: 1655035582.915616 iteration: 34760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15441 FastRCNN class loss: 0.08964 FastRCNN total loss: 0.24405 L1 loss: 0.0000e+00 L2 loss: 0.69589 Learning rate: 0.02 Mask loss: 0.22361 RPN box loss: 0.02205 RPN score loss: 0.00658 RPN total loss: 0.02863 Total loss: 1.19219 timestamp: 1655035586.201416 iteration: 34765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08245 FastRCNN class loss: 0.05453 FastRCNN total loss: 0.13698 L1 loss: 0.0000e+00 L2 loss: 0.69581 Learning rate: 0.02 Mask loss: 0.11228 RPN box loss: 0.01948 RPN score loss: 0.00603 RPN total loss: 0.0255 Total loss: 0.97057 timestamp: 1655035589.4373984 iteration: 34770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14678 FastRCNN class loss: 0.15416 FastRCNN total loss: 0.30094 L1 loss: 0.0000e+00 L2 loss: 0.6957 Learning rate: 0.02 Mask loss: 0.23106 RPN box loss: 0.0276 RPN score loss: 0.00798 RPN total loss: 0.03558 Total loss: 1.26328 timestamp: 1655035592.775133 iteration: 34775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16339 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.23819 L1 loss: 0.0000e+00 L2 loss: 0.69561 Learning rate: 0.02 Mask loss: 0.29754 RPN box loss: 0.05447 RPN score loss: 0.00868 RPN total loss: 0.06315 Total loss: 1.29449 timestamp: 1655035596.1024146 iteration: 34780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11037 FastRCNN class loss: 0.07104 FastRCNN total loss: 0.1814 L1 loss: 0.0000e+00 L2 loss: 0.69549 Learning rate: 0.02 Mask loss: 0.1429 RPN box loss: 0.01866 RPN score loss: 0.01195 RPN total loss: 0.03061 Total loss: 1.05041 timestamp: 1655035599.3224175 iteration: 34785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1386 FastRCNN class loss: 0.07515 FastRCNN total loss: 0.21375 L1 loss: 0.0000e+00 L2 loss: 0.6954 Learning rate: 0.02 Mask loss: 0.15914 RPN box loss: 0.08007 RPN score loss: 0.00718 RPN total loss: 0.08724 Total loss: 1.15554 timestamp: 1655035602.6328294 iteration: 34790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11272 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.17755 L1 loss: 0.0000e+00 L2 loss: 0.6953 Learning rate: 0.02 Mask loss: 0.1483 RPN box loss: 0.02044 RPN score loss: 0.00182 RPN total loss: 0.02226 Total loss: 1.04341 timestamp: 1655035605.9432957 iteration: 34795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13191 FastRCNN class loss: 0.0867 FastRCNN total loss: 0.21861 L1 loss: 0.0000e+00 L2 loss: 0.6952 Learning rate: 0.02 Mask loss: 0.21468 RPN box loss: 0.02979 RPN score loss: 0.00417 RPN total loss: 0.03396 Total loss: 1.16246 timestamp: 1655035609.2565985 iteration: 34800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19822 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.29706 L1 loss: 0.0000e+00 L2 loss: 0.69512 Learning rate: 0.02 Mask loss: 0.17822 RPN box loss: 0.04023 RPN score loss: 0.00892 RPN total loss: 0.04916 Total loss: 1.21957 timestamp: 1655035612.5362372 iteration: 34805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14272 FastRCNN class loss: 0.11316 FastRCNN total loss: 0.25588 L1 loss: 0.0000e+00 L2 loss: 0.69502 Learning rate: 0.02 Mask loss: 0.17443 RPN box loss: 0.05102 RPN score loss: 0.00637 RPN total loss: 0.05739 Total loss: 1.18271 timestamp: 1655035615.8190863 iteration: 34810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18365 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.26626 L1 loss: 0.0000e+00 L2 loss: 0.69491 Learning rate: 0.02 Mask loss: 0.14021 RPN box loss: 0.02983 RPN score loss: 0.00497 RPN total loss: 0.03479 Total loss: 1.13616 timestamp: 1655035619.071238 iteration: 34815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.14096 L1 loss: 0.0000e+00 L2 loss: 0.69484 Learning rate: 0.02 Mask loss: 0.12628 RPN box loss: 0.02836 RPN score loss: 0.00809 RPN total loss: 0.03644 Total loss: 0.99852 timestamp: 1655035622.397315 iteration: 34820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08045 FastRCNN class loss: 0.04944 FastRCNN total loss: 0.1299 L1 loss: 0.0000e+00 L2 loss: 0.69474 Learning rate: 0.02 Mask loss: 0.10694 RPN box loss: 0.0147 RPN score loss: 0.00355 RPN total loss: 0.01825 Total loss: 0.94983 timestamp: 1655035625.6664588 iteration: 34825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21035 FastRCNN class loss: 0.12368 FastRCNN total loss: 0.33403 L1 loss: 0.0000e+00 L2 loss: 0.69464 Learning rate: 0.02 Mask loss: 0.26045 RPN box loss: 0.04704 RPN score loss: 0.01423 RPN total loss: 0.06127 Total loss: 1.35038 timestamp: 1655035628.836805 iteration: 34830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13199 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.18236 L1 loss: 0.0000e+00 L2 loss: 0.69454 Learning rate: 0.02 Mask loss: 0.14277 RPN box loss: 0.01681 RPN score loss: 0.00334 RPN total loss: 0.02015 Total loss: 1.03983 timestamp: 1655035632.005684 iteration: 34835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12196 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.20157 L1 loss: 0.0000e+00 L2 loss: 0.69445 Learning rate: 0.02 Mask loss: 0.14848 RPN box loss: 0.05611 RPN score loss: 0.00956 RPN total loss: 0.06567 Total loss: 1.11016 timestamp: 1655035635.2777042 iteration: 34840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08443 FastRCNN class loss: 0.04779 FastRCNN total loss: 0.13222 L1 loss: 0.0000e+00 L2 loss: 0.69435 Learning rate: 0.02 Mask loss: 0.12835 RPN box loss: 0.04227 RPN score loss: 0.00224 RPN total loss: 0.04451 Total loss: 0.99944 timestamp: 1655035638.5770617 iteration: 34845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08019 FastRCNN class loss: 0.03856 FastRCNN total loss: 0.11875 L1 loss: 0.0000e+00 L2 loss: 0.69425 Learning rate: 0.02 Mask loss: 0.13076 RPN box loss: 0.02297 RPN score loss: 0.00239 RPN total loss: 0.02536 Total loss: 0.96912 timestamp: 1655035641.8313754 iteration: 34850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11754 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.19435 L1 loss: 0.0000e+00 L2 loss: 0.69413 Learning rate: 0.02 Mask loss: 0.12178 RPN box loss: 0.03742 RPN score loss: 0.01119 RPN total loss: 0.04861 Total loss: 1.05887 timestamp: 1655035645.1102004 iteration: 34855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1067 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.15808 L1 loss: 0.0000e+00 L2 loss: 0.69403 Learning rate: 0.02 Mask loss: 0.22953 RPN box loss: 0.0299 RPN score loss: 0.00765 RPN total loss: 0.03755 Total loss: 1.11919 timestamp: 1655035648.3991063 iteration: 34860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.08029 FastRCNN total loss: 0.1903 L1 loss: 0.0000e+00 L2 loss: 0.69392 Learning rate: 0.02 Mask loss: 0.15023 RPN box loss: 0.02042 RPN score loss: 0.01161 RPN total loss: 0.03203 Total loss: 1.06648 timestamp: 1655035651.6745498 iteration: 34865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13479 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.22454 L1 loss: 0.0000e+00 L2 loss: 0.69381 Learning rate: 0.02 Mask loss: 0.18718 RPN box loss: 0.02227 RPN score loss: 0.01645 RPN total loss: 0.03873 Total loss: 1.14426 timestamp: 1655035654.9490337 iteration: 34870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13203 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.21939 L1 loss: 0.0000e+00 L2 loss: 0.69374 Learning rate: 0.02 Mask loss: 0.11401 RPN box loss: 0.02119 RPN score loss: 0.00559 RPN total loss: 0.02678 Total loss: 1.05392 timestamp: 1655035658.2997599 iteration: 34875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17491 FastRCNN class loss: 0.10365 FastRCNN total loss: 0.27857 L1 loss: 0.0000e+00 L2 loss: 0.69363 Learning rate: 0.02 Mask loss: 0.2168 RPN box loss: 0.03623 RPN score loss: 0.00714 RPN total loss: 0.04337 Total loss: 1.23237 timestamp: 1655035661.544583 iteration: 34880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.206 FastRCNN class loss: 0.10866 FastRCNN total loss: 0.31466 L1 loss: 0.0000e+00 L2 loss: 0.69353 Learning rate: 0.02 Mask loss: 0.24824 RPN box loss: 0.02036 RPN score loss: 0.00896 RPN total loss: 0.02932 Total loss: 1.28575 timestamp: 1655035664.78915 iteration: 34885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17512 FastRCNN class loss: 0.10556 FastRCNN total loss: 0.28069 L1 loss: 0.0000e+00 L2 loss: 0.69345 Learning rate: 0.02 Mask loss: 0.13983 RPN box loss: 0.05103 RPN score loss: 0.00654 RPN total loss: 0.05757 Total loss: 1.17153 timestamp: 1655035668.0754788 iteration: 34890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12151 FastRCNN class loss: 0.07402 FastRCNN total loss: 0.19553 L1 loss: 0.0000e+00 L2 loss: 0.69334 Learning rate: 0.02 Mask loss: 0.0894 RPN box loss: 0.00791 RPN score loss: 0.00689 RPN total loss: 0.0148 Total loss: 0.99308 timestamp: 1655035671.302128 iteration: 34895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12654 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.18962 L1 loss: 0.0000e+00 L2 loss: 0.69326 Learning rate: 0.02 Mask loss: 0.15622 RPN box loss: 0.02498 RPN score loss: 0.00536 RPN total loss: 0.03034 Total loss: 1.06944 timestamp: 1655035674.5605857 iteration: 34900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19645 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.2814 L1 loss: 0.0000e+00 L2 loss: 0.69317 Learning rate: 0.02 Mask loss: 0.15349 RPN box loss: 0.01275 RPN score loss: 0.00897 RPN total loss: 0.02172 Total loss: 1.14978 timestamp: 1655035677.8076205 iteration: 34905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11953 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.20671 L1 loss: 0.0000e+00 L2 loss: 0.69306 Learning rate: 0.02 Mask loss: 0.16448 RPN box loss: 0.02008 RPN score loss: 0.00654 RPN total loss: 0.02663 Total loss: 1.09086 timestamp: 1655035681.0212212 iteration: 34910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10892 FastRCNN class loss: 0.04798 FastRCNN total loss: 0.15689 L1 loss: 0.0000e+00 L2 loss: 0.69299 Learning rate: 0.02 Mask loss: 0.13545 RPN box loss: 0.01708 RPN score loss: 0.00214 RPN total loss: 0.01922 Total loss: 1.00455 timestamp: 1655035684.2915144 iteration: 34915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14672 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.23422 L1 loss: 0.0000e+00 L2 loss: 0.6929 Learning rate: 0.02 Mask loss: 0.19343 RPN box loss: 0.05662 RPN score loss: 0.01251 RPN total loss: 0.06913 Total loss: 1.18968 timestamp: 1655035687.5346591 iteration: 34920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09255 FastRCNN class loss: 0.04078 FastRCNN total loss: 0.13333 L1 loss: 0.0000e+00 L2 loss: 0.69281 Learning rate: 0.02 Mask loss: 0.11273 RPN box loss: 0.01003 RPN score loss: 0.00825 RPN total loss: 0.01827 Total loss: 0.95714 timestamp: 1655035690.7969003 iteration: 34925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14686 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.6927 Learning rate: 0.02 Mask loss: 0.12211 RPN box loss: 0.01849 RPN score loss: 0.00459 RPN total loss: 0.02308 Total loss: 1.04237 timestamp: 1655035694.0746539 iteration: 34930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10903 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.20663 L1 loss: 0.0000e+00 L2 loss: 0.69262 Learning rate: 0.02 Mask loss: 0.14485 RPN box loss: 0.06216 RPN score loss: 0.00905 RPN total loss: 0.07121 Total loss: 1.11531 timestamp: 1655035697.245419 iteration: 34935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11204 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.17801 L1 loss: 0.0000e+00 L2 loss: 0.69251 Learning rate: 0.02 Mask loss: 0.1502 RPN box loss: 0.07915 RPN score loss: 0.0041 RPN total loss: 0.08325 Total loss: 1.10396 timestamp: 1655035700.464145 iteration: 34940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.184 FastRCNN class loss: 0.04991 FastRCNN total loss: 0.23391 L1 loss: 0.0000e+00 L2 loss: 0.6924 Learning rate: 0.02 Mask loss: 0.15795 RPN box loss: 0.02978 RPN score loss: 0.00493 RPN total loss: 0.03471 Total loss: 1.11896 timestamp: 1655035703.7490935 iteration: 34945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11852 FastRCNN class loss: 0.1054 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 0.69231 Learning rate: 0.02 Mask loss: 0.16965 RPN box loss: 0.06638 RPN score loss: 0.01409 RPN total loss: 0.08046 Total loss: 1.16634 timestamp: 1655035707.0683866 iteration: 34950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18452 FastRCNN class loss: 0.19857 FastRCNN total loss: 0.38309 L1 loss: 0.0000e+00 L2 loss: 0.69223 Learning rate: 0.02 Mask loss: 0.24205 RPN box loss: 0.06913 RPN score loss: 0.02068 RPN total loss: 0.08981 Total loss: 1.40718 timestamp: 1655035710.332365 iteration: 34955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18264 FastRCNN class loss: 0.08564 FastRCNN total loss: 0.26828 L1 loss: 0.0000e+00 L2 loss: 0.69213 Learning rate: 0.02 Mask loss: 0.17092 RPN box loss: 0.00874 RPN score loss: 0.00246 RPN total loss: 0.0112 Total loss: 1.14254 timestamp: 1655035713.647031 iteration: 34960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08864 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.16428 L1 loss: 0.0000e+00 L2 loss: 0.69201 Learning rate: 0.02 Mask loss: 0.14676 RPN box loss: 0.01602 RPN score loss: 0.00369 RPN total loss: 0.01971 Total loss: 1.02276 timestamp: 1655035716.9021292 iteration: 34965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12271 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.18557 L1 loss: 0.0000e+00 L2 loss: 0.69191 Learning rate: 0.02 Mask loss: 0.24434 RPN box loss: 0.0112 RPN score loss: 0.00179 RPN total loss: 0.01299 Total loss: 1.13481 timestamp: 1655035720.086013 iteration: 34970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13933 FastRCNN class loss: 0.10701 FastRCNN total loss: 0.24634 L1 loss: 0.0000e+00 L2 loss: 0.69181 Learning rate: 0.02 Mask loss: 0.13395 RPN box loss: 0.02311 RPN score loss: 0.00461 RPN total loss: 0.02772 Total loss: 1.09983 timestamp: 1655035723.4436483 iteration: 34975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15777 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.24964 L1 loss: 0.0000e+00 L2 loss: 0.69173 Learning rate: 0.02 Mask loss: 0.22008 RPN box loss: 0.04853 RPN score loss: 0.01841 RPN total loss: 0.06694 Total loss: 1.22839 timestamp: 1655035726.6472876 iteration: 34980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15749 FastRCNN class loss: 0.12724 FastRCNN total loss: 0.28473 L1 loss: 0.0000e+00 L2 loss: 0.69165 Learning rate: 0.02 Mask loss: 0.19325 RPN box loss: 0.03641 RPN score loss: 0.00984 RPN total loss: 0.04625 Total loss: 1.21588 timestamp: 1655035730.0052602 iteration: 34985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16023 FastRCNN class loss: 0.09857 FastRCNN total loss: 0.25879 L1 loss: 0.0000e+00 L2 loss: 0.69153 Learning rate: 0.02 Mask loss: 0.18712 RPN box loss: 0.03548 RPN score loss: 0.0067 RPN total loss: 0.04218 Total loss: 1.17962 timestamp: 1655035733.2023084 iteration: 34990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19329 FastRCNN class loss: 0.11147 FastRCNN total loss: 0.30477 L1 loss: 0.0000e+00 L2 loss: 0.69142 Learning rate: 0.02 Mask loss: 0.15843 RPN box loss: 0.05618 RPN score loss: 0.00669 RPN total loss: 0.06287 Total loss: 1.21748 timestamp: 1655035736.5298393 iteration: 34995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15037 FastRCNN class loss: 0.11533 FastRCNN total loss: 0.2657 L1 loss: 0.0000e+00 L2 loss: 0.69134 Learning rate: 0.02 Mask loss: 0.20487 RPN box loss: 0.0145 RPN score loss: 0.00308 RPN total loss: 0.01758 Total loss: 1.17949 timestamp: 1655035739.8158543 iteration: 35000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1297 FastRCNN class loss: 0.08544 FastRCNN total loss: 0.21514 L1 loss: 0.0000e+00 L2 loss: 0.69123 Learning rate: 0.02 Mask loss: 0.20467 RPN box loss: 0.03882 RPN score loss: 0.00282 RPN total loss: 0.04164 Total loss: 1.15269 timestamp: 1655035743.0345452 iteration: 35005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16732 FastRCNN class loss: 0.12812 FastRCNN total loss: 0.29544 L1 loss: 0.0000e+00 L2 loss: 0.69116 Learning rate: 0.02 Mask loss: 0.18003 RPN box loss: 0.03948 RPN score loss: 0.04247 RPN total loss: 0.08195 Total loss: 1.24857 timestamp: 1655035746.3222718 iteration: 35010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1657 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.23941 L1 loss: 0.0000e+00 L2 loss: 0.69108 Learning rate: 0.02 Mask loss: 0.18578 RPN box loss: 0.05719 RPN score loss: 0.00476 RPN total loss: 0.06196 Total loss: 1.17822 timestamp: 1655035749.5845335 iteration: 35015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12856 FastRCNN class loss: 0.08597 FastRCNN total loss: 0.21453 L1 loss: 0.0000e+00 L2 loss: 0.69097 Learning rate: 0.02 Mask loss: 0.22536 RPN box loss: 0.08657 RPN score loss: 0.01469 RPN total loss: 0.10126 Total loss: 1.23211 timestamp: 1655035752.8855588 iteration: 35020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10859 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.16966 L1 loss: 0.0000e+00 L2 loss: 0.69089 Learning rate: 0.02 Mask loss: 0.0872 RPN box loss: 0.00586 RPN score loss: 0.00155 RPN total loss: 0.00741 Total loss: 0.95516 timestamp: 1655035756.128703 iteration: 35025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18184 FastRCNN class loss: 0.09778 FastRCNN total loss: 0.27962 L1 loss: 0.0000e+00 L2 loss: 0.6908 Learning rate: 0.02 Mask loss: 0.21083 RPN box loss: 0.03804 RPN score loss: 0.02012 RPN total loss: 0.05816 Total loss: 1.2394 timestamp: 1655035759.4304502 iteration: 35030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09065 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.14124 L1 loss: 0.0000e+00 L2 loss: 0.69068 Learning rate: 0.02 Mask loss: 0.12227 RPN box loss: 0.00886 RPN score loss: 0.00444 RPN total loss: 0.0133 Total loss: 0.96749 timestamp: 1655035762.7068856 iteration: 35035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12937 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.18282 L1 loss: 0.0000e+00 L2 loss: 0.69057 Learning rate: 0.02 Mask loss: 0.14286 RPN box loss: 0.03629 RPN score loss: 0.00613 RPN total loss: 0.04242 Total loss: 1.05867 timestamp: 1655035765.9600449 iteration: 35040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17241 FastRCNN class loss: 0.13374 FastRCNN total loss: 0.30615 L1 loss: 0.0000e+00 L2 loss: 0.69048 Learning rate: 0.02 Mask loss: 0.18653 RPN box loss: 0.03797 RPN score loss: 0.03272 RPN total loss: 0.07068 Total loss: 1.25383 timestamp: 1655035769.2339432 iteration: 35045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.05752 FastRCNN total loss: 0.15465 L1 loss: 0.0000e+00 L2 loss: 0.69037 Learning rate: 0.02 Mask loss: 0.07803 RPN box loss: 0.04281 RPN score loss: 0.00473 RPN total loss: 0.04754 Total loss: 0.97059 timestamp: 1655035772.5175536 iteration: 35050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09262 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.14872 L1 loss: 0.0000e+00 L2 loss: 0.69025 Learning rate: 0.02 Mask loss: 0.14382 RPN box loss: 0.01293 RPN score loss: 0.00446 RPN total loss: 0.01739 Total loss: 1.00019 timestamp: 1655035775.869349 iteration: 35055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15158 FastRCNN class loss: 0.09218 FastRCNN total loss: 0.24376 L1 loss: 0.0000e+00 L2 loss: 0.69017 Learning rate: 0.02 Mask loss: 0.12466 RPN box loss: 0.01526 RPN score loss: 0.00311 RPN total loss: 0.01838 Total loss: 1.07696 timestamp: 1655035779.1214468 iteration: 35060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14457 FastRCNN class loss: 0.10081 FastRCNN total loss: 0.24538 L1 loss: 0.0000e+00 L2 loss: 0.69009 Learning rate: 0.02 Mask loss: 0.14498 RPN box loss: 0.03509 RPN score loss: 0.01024 RPN total loss: 0.04533 Total loss: 1.12578 timestamp: 1655035782.4198213 iteration: 35065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.152 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.23967 L1 loss: 0.0000e+00 L2 loss: 0.69001 Learning rate: 0.02 Mask loss: 0.15 RPN box loss: 0.02936 RPN score loss: 0.01792 RPN total loss: 0.04728 Total loss: 1.12696 timestamp: 1655035785.7095232 iteration: 35070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13453 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.22518 L1 loss: 0.0000e+00 L2 loss: 0.68992 Learning rate: 0.02 Mask loss: 0.14663 RPN box loss: 0.04909 RPN score loss: 0.00693 RPN total loss: 0.05602 Total loss: 1.11775 timestamp: 1655035788.9744077 iteration: 35075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.10424 FastRCNN total loss: 0.21486 L1 loss: 0.0000e+00 L2 loss: 0.68984 Learning rate: 0.02 Mask loss: 0.15308 RPN box loss: 0.01695 RPN score loss: 0.00206 RPN total loss: 0.01901 Total loss: 1.07679 timestamp: 1655035792.2308626 iteration: 35080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14778 FastRCNN class loss: 0.09894 FastRCNN total loss: 0.24672 L1 loss: 0.0000e+00 L2 loss: 0.68975 Learning rate: 0.02 Mask loss: 0.15035 RPN box loss: 0.0345 RPN score loss: 0.00874 RPN total loss: 0.04324 Total loss: 1.13007 timestamp: 1655035795.5218117 iteration: 35085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09422 FastRCNN class loss: 0.09842 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.68964 Learning rate: 0.02 Mask loss: 0.15934 RPN box loss: 0.02076 RPN score loss: 0.00993 RPN total loss: 0.03068 Total loss: 1.0723 timestamp: 1655035798.8668208 iteration: 35090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12473 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.19678 L1 loss: 0.0000e+00 L2 loss: 0.68953 Learning rate: 0.02 Mask loss: 0.17451 RPN box loss: 0.01458 RPN score loss: 0.0055 RPN total loss: 0.02009 Total loss: 1.0809 timestamp: 1655035802.1539214 iteration: 35095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14107 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.22827 L1 loss: 0.0000e+00 L2 loss: 0.68944 Learning rate: 0.02 Mask loss: 0.15154 RPN box loss: 0.04405 RPN score loss: 0.01846 RPN total loss: 0.06251 Total loss: 1.13176 timestamp: 1655035805.4402997 iteration: 35100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.17591 L1 loss: 0.0000e+00 L2 loss: 0.68932 Learning rate: 0.02 Mask loss: 0.10151 RPN box loss: 0.05744 RPN score loss: 0.0089 RPN total loss: 0.06635 Total loss: 1.03309 timestamp: 1655035808.688062 iteration: 35105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13213 FastRCNN class loss: 0.05142 FastRCNN total loss: 0.18355 L1 loss: 0.0000e+00 L2 loss: 0.68922 Learning rate: 0.02 Mask loss: 0.11678 RPN box loss: 0.00912 RPN score loss: 0.00545 RPN total loss: 0.01457 Total loss: 1.00412 timestamp: 1655035811.9210484 iteration: 35110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11967 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.20302 L1 loss: 0.0000e+00 L2 loss: 0.68913 Learning rate: 0.02 Mask loss: 0.19597 RPN box loss: 0.03872 RPN score loss: 0.00679 RPN total loss: 0.04551 Total loss: 1.13363 timestamp: 1655035815.1735725 iteration: 35115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17738 FastRCNN class loss: 0.12055 FastRCNN total loss: 0.29793 L1 loss: 0.0000e+00 L2 loss: 0.68902 Learning rate: 0.02 Mask loss: 0.18216 RPN box loss: 0.04773 RPN score loss: 0.00363 RPN total loss: 0.05136 Total loss: 1.22046 timestamp: 1655035818.4429522 iteration: 35120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14741 FastRCNN class loss: 0.06799 FastRCNN total loss: 0.21539 L1 loss: 0.0000e+00 L2 loss: 0.68891 Learning rate: 0.02 Mask loss: 0.19929 RPN box loss: 0.019 RPN score loss: 0.01017 RPN total loss: 0.02916 Total loss: 1.13275 timestamp: 1655035821.789836 iteration: 35125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08697 FastRCNN class loss: 0.05878 FastRCNN total loss: 0.14575 L1 loss: 0.0000e+00 L2 loss: 0.68882 Learning rate: 0.02 Mask loss: 0.15627 RPN box loss: 0.0074 RPN score loss: 0.00527 RPN total loss: 0.01268 Total loss: 1.00352 timestamp: 1655035825.0733325 iteration: 35130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.19185 L1 loss: 0.0000e+00 L2 loss: 0.68872 Learning rate: 0.02 Mask loss: 0.14834 RPN box loss: 0.03871 RPN score loss: 0.00819 RPN total loss: 0.0469 Total loss: 1.07581 timestamp: 1655035828.3685758 iteration: 35135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.07862 FastRCNN total loss: 0.18278 L1 loss: 0.0000e+00 L2 loss: 0.68863 Learning rate: 0.02 Mask loss: 0.14872 RPN box loss: 0.03356 RPN score loss: 0.00575 RPN total loss: 0.03931 Total loss: 1.05944 timestamp: 1655035831.5684922 iteration: 35140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15717 FastRCNN class loss: 0.0661 FastRCNN total loss: 0.22326 L1 loss: 0.0000e+00 L2 loss: 0.68854 Learning rate: 0.02 Mask loss: 0.12327 RPN box loss: 0.0074 RPN score loss: 0.00245 RPN total loss: 0.00984 Total loss: 1.04492 timestamp: 1655035834.8302188 iteration: 35145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12271 FastRCNN class loss: 0.09178 FastRCNN total loss: 0.21449 L1 loss: 0.0000e+00 L2 loss: 0.68844 Learning rate: 0.02 Mask loss: 0.16999 RPN box loss: 0.0366 RPN score loss: 0.00671 RPN total loss: 0.04331 Total loss: 1.11624 timestamp: 1655035838.1231737 iteration: 35150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15966 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.25575 L1 loss: 0.0000e+00 L2 loss: 0.68834 Learning rate: 0.02 Mask loss: 0.2083 RPN box loss: 0.02581 RPN score loss: 0.00854 RPN total loss: 0.03434 Total loss: 1.18673 timestamp: 1655035841.4572287 iteration: 35155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12383 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.18479 L1 loss: 0.0000e+00 L2 loss: 0.68823 Learning rate: 0.02 Mask loss: 0.09186 RPN box loss: 0.01803 RPN score loss: 0.00571 RPN total loss: 0.02374 Total loss: 0.98861 timestamp: 1655035844.8213701 iteration: 35160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14072 FastRCNN class loss: 0.09366 FastRCNN total loss: 0.23438 L1 loss: 0.0000e+00 L2 loss: 0.68814 Learning rate: 0.02 Mask loss: 0.11814 RPN box loss: 0.05297 RPN score loss: 0.00796 RPN total loss: 0.06093 Total loss: 1.10159 timestamp: 1655035848.0867126 iteration: 35165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10924 FastRCNN class loss: 0.06782 FastRCNN total loss: 0.17706 L1 loss: 0.0000e+00 L2 loss: 0.68806 Learning rate: 0.02 Mask loss: 0.13515 RPN box loss: 0.01424 RPN score loss: 0.00475 RPN total loss: 0.01899 Total loss: 1.01925 timestamp: 1655035851.3926625 iteration: 35170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21066 FastRCNN class loss: 0.1454 FastRCNN total loss: 0.35607 L1 loss: 0.0000e+00 L2 loss: 0.68798 Learning rate: 0.02 Mask loss: 0.22668 RPN box loss: 0.02459 RPN score loss: 0.01235 RPN total loss: 0.03694 Total loss: 1.30768 timestamp: 1655035854.6600873 iteration: 35175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17278 FastRCNN class loss: 0.098 FastRCNN total loss: 0.27078 L1 loss: 0.0000e+00 L2 loss: 0.68787 Learning rate: 0.02 Mask loss: 0.12778 RPN box loss: 0.04418 RPN score loss: 0.00669 RPN total loss: 0.05087 Total loss: 1.13731 timestamp: 1655035857.9221568 iteration: 35180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21376 FastRCNN class loss: 0.13457 FastRCNN total loss: 0.34833 L1 loss: 0.0000e+00 L2 loss: 0.6878 Learning rate: 0.02 Mask loss: 0.2298 RPN box loss: 0.02165 RPN score loss: 0.00471 RPN total loss: 0.02636 Total loss: 1.29228 timestamp: 1655035861.1969802 iteration: 35185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12937 FastRCNN class loss: 0.06188 FastRCNN total loss: 0.19125 L1 loss: 0.0000e+00 L2 loss: 0.68771 Learning rate: 0.02 Mask loss: 0.15025 RPN box loss: 0.01463 RPN score loss: 0.00557 RPN total loss: 0.0202 Total loss: 1.04941 timestamp: 1655035864.4212115 iteration: 35190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19246 FastRCNN class loss: 0.09678 FastRCNN total loss: 0.28924 L1 loss: 0.0000e+00 L2 loss: 0.68761 Learning rate: 0.02 Mask loss: 0.1972 RPN box loss: 0.01554 RPN score loss: 0.00505 RPN total loss: 0.02058 Total loss: 1.19462 timestamp: 1655035867.6383963 iteration: 35195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14795 FastRCNN class loss: 0.07514 FastRCNN total loss: 0.22309 L1 loss: 0.0000e+00 L2 loss: 0.68751 Learning rate: 0.02 Mask loss: 0.15207 RPN box loss: 0.08794 RPN score loss: 0.00775 RPN total loss: 0.0957 Total loss: 1.15837 timestamp: 1655035870.9375372 iteration: 35200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19162 FastRCNN class loss: 0.07775 FastRCNN total loss: 0.26937 L1 loss: 0.0000e+00 L2 loss: 0.68738 Learning rate: 0.02 Mask loss: 0.19793 RPN box loss: 0.02127 RPN score loss: 0.00429 RPN total loss: 0.02555 Total loss: 1.18024 timestamp: 1655035874.1567879 iteration: 35205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11225 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.19683 L1 loss: 0.0000e+00 L2 loss: 0.68727 Learning rate: 0.02 Mask loss: 0.18683 RPN box loss: 0.00914 RPN score loss: 0.00299 RPN total loss: 0.01213 Total loss: 1.08306 timestamp: 1655035877.4924757 iteration: 35210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16532 FastRCNN class loss: 0.08857 FastRCNN total loss: 0.2539 L1 loss: 0.0000e+00 L2 loss: 0.68719 Learning rate: 0.02 Mask loss: 0.14484 RPN box loss: 0.02889 RPN score loss: 0.00704 RPN total loss: 0.03593 Total loss: 1.12186 timestamp: 1655035880.792269 iteration: 35215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21022 FastRCNN class loss: 0.09637 FastRCNN total loss: 0.30659 L1 loss: 0.0000e+00 L2 loss: 0.68711 Learning rate: 0.02 Mask loss: 0.19398 RPN box loss: 0.02297 RPN score loss: 0.01526 RPN total loss: 0.03823 Total loss: 1.2259 timestamp: 1655035884.0423005 iteration: 35220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22155 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.32134 L1 loss: 0.0000e+00 L2 loss: 0.68704 Learning rate: 0.02 Mask loss: 0.12497 RPN box loss: 0.04908 RPN score loss: 0.01401 RPN total loss: 0.06309 Total loss: 1.19643 timestamp: 1655035887.3109076 iteration: 35225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17157 FastRCNN class loss: 0.12831 FastRCNN total loss: 0.29988 L1 loss: 0.0000e+00 L2 loss: 0.68694 Learning rate: 0.02 Mask loss: 0.21288 RPN box loss: 0.04172 RPN score loss: 0.02378 RPN total loss: 0.0655 Total loss: 1.2652 timestamp: 1655035890.591351 iteration: 35230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09582 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.16974 L1 loss: 0.0000e+00 L2 loss: 0.68684 Learning rate: 0.02 Mask loss: 0.22668 RPN box loss: 0.02733 RPN score loss: 0.00944 RPN total loss: 0.03677 Total loss: 1.12003 timestamp: 1655035893.832452 iteration: 35235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18451 FastRCNN class loss: 0.08265 FastRCNN total loss: 0.26716 L1 loss: 0.0000e+00 L2 loss: 0.68675 Learning rate: 0.02 Mask loss: 0.14048 RPN box loss: 0.01848 RPN score loss: 0.00674 RPN total loss: 0.02522 Total loss: 1.11961 timestamp: 1655035897.0819013 iteration: 35240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09915 FastRCNN class loss: 0.09662 FastRCNN total loss: 0.19578 L1 loss: 0.0000e+00 L2 loss: 0.68663 Learning rate: 0.02 Mask loss: 0.12504 RPN box loss: 0.05572 RPN score loss: 0.00673 RPN total loss: 0.06245 Total loss: 1.0699 timestamp: 1655035900.4207878 iteration: 35245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08797 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.14974 L1 loss: 0.0000e+00 L2 loss: 0.68655 Learning rate: 0.02 Mask loss: 0.13507 RPN box loss: 0.04286 RPN score loss: 0.00696 RPN total loss: 0.04982 Total loss: 1.02117 timestamp: 1655035903.7103016 iteration: 35250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14014 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.22448 L1 loss: 0.0000e+00 L2 loss: 0.68644 Learning rate: 0.02 Mask loss: 0.17241 RPN box loss: 0.06927 RPN score loss: 0.0065 RPN total loss: 0.07577 Total loss: 1.15909 timestamp: 1655035906.9551034 iteration: 35255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18478 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.2577 L1 loss: 0.0000e+00 L2 loss: 0.68633 Learning rate: 0.02 Mask loss: 0.12743 RPN box loss: 0.00618 RPN score loss: 0.00652 RPN total loss: 0.0127 Total loss: 1.08416 timestamp: 1655035910.2818906 iteration: 35260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.08092 FastRCNN total loss: 0.19196 L1 loss: 0.0000e+00 L2 loss: 0.68626 Learning rate: 0.02 Mask loss: 0.18516 RPN box loss: 0.02736 RPN score loss: 0.00631 RPN total loss: 0.03366 Total loss: 1.09705 timestamp: 1655035913.5884902 iteration: 35265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08949 FastRCNN class loss: 0.05724 FastRCNN total loss: 0.14673 L1 loss: 0.0000e+00 L2 loss: 0.68617 Learning rate: 0.02 Mask loss: 0.10585 RPN box loss: 0.01163 RPN score loss: 0.0037 RPN total loss: 0.01532 Total loss: 0.95409 timestamp: 1655035916.7830248 iteration: 35270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09718 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.16672 L1 loss: 0.0000e+00 L2 loss: 0.68608 Learning rate: 0.02 Mask loss: 0.21126 RPN box loss: 0.03752 RPN score loss: 0.00261 RPN total loss: 0.04013 Total loss: 1.10419 timestamp: 1655035920.0615566 iteration: 35275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16388 FastRCNN class loss: 0.0849 FastRCNN total loss: 0.24878 L1 loss: 0.0000e+00 L2 loss: 0.68598 Learning rate: 0.02 Mask loss: 0.14703 RPN box loss: 0.04409 RPN score loss: 0.00762 RPN total loss: 0.05171 Total loss: 1.1335 timestamp: 1655035923.3670375 iteration: 35280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15181 FastRCNN class loss: 0.11222 FastRCNN total loss: 0.26403 L1 loss: 0.0000e+00 L2 loss: 0.68588 Learning rate: 0.02 Mask loss: 0.11579 RPN box loss: 0.0323 RPN score loss: 0.01179 RPN total loss: 0.04408 Total loss: 1.10979 timestamp: 1655035926.7005289 iteration: 35285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20473 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.26358 L1 loss: 0.0000e+00 L2 loss: 0.68578 Learning rate: 0.02 Mask loss: 0.14661 RPN box loss: 0.01856 RPN score loss: 0.00276 RPN total loss: 0.02132 Total loss: 1.11729 timestamp: 1655035929.912266 iteration: 35290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18558 FastRCNN class loss: 0.05068 FastRCNN total loss: 0.23626 L1 loss: 0.0000e+00 L2 loss: 0.68566 Learning rate: 0.02 Mask loss: 0.10644 RPN box loss: 0.01102 RPN score loss: 0.0043 RPN total loss: 0.01533 Total loss: 1.04369 timestamp: 1655035933.1018527 iteration: 35295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.10205 FastRCNN total loss: 0.24199 L1 loss: 0.0000e+00 L2 loss: 0.68558 Learning rate: 0.02 Mask loss: 0.19818 RPN box loss: 0.07029 RPN score loss: 0.00294 RPN total loss: 0.07323 Total loss: 1.19899 timestamp: 1655035936.3671372 iteration: 35300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09767 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.15693 L1 loss: 0.0000e+00 L2 loss: 0.68549 Learning rate: 0.02 Mask loss: 0.17539 RPN box loss: 0.02748 RPN score loss: 0.00673 RPN total loss: 0.03421 Total loss: 1.05202 timestamp: 1655035939.6472244 iteration: 35305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12814 FastRCNN class loss: 0.1078 FastRCNN total loss: 0.23594 L1 loss: 0.0000e+00 L2 loss: 0.6854 Learning rate: 0.02 Mask loss: 0.2237 RPN box loss: 0.03042 RPN score loss: 0.01808 RPN total loss: 0.0485 Total loss: 1.19354 timestamp: 1655035942.9454825 iteration: 35310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07387 FastRCNN class loss: 0.04281 FastRCNN total loss: 0.11668 L1 loss: 0.0000e+00 L2 loss: 0.68528 Learning rate: 0.02 Mask loss: 0.11728 RPN box loss: 0.00424 RPN score loss: 0.00303 RPN total loss: 0.00728 Total loss: 0.92651 timestamp: 1655035946.2100534 iteration: 35315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11961 FastRCNN class loss: 0.06761 FastRCNN total loss: 0.18721 L1 loss: 0.0000e+00 L2 loss: 0.68518 Learning rate: 0.02 Mask loss: 0.18518 RPN box loss: 0.04512 RPN score loss: 0.00376 RPN total loss: 0.04888 Total loss: 1.10646 timestamp: 1655035949.5543149 iteration: 35320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12102 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.19942 L1 loss: 0.0000e+00 L2 loss: 0.68509 Learning rate: 0.02 Mask loss: 0.18238 RPN box loss: 0.02195 RPN score loss: 0.00496 RPN total loss: 0.0269 Total loss: 1.09379 timestamp: 1655035952.8309183 iteration: 35325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13388 FastRCNN class loss: 0.07588 FastRCNN total loss: 0.20975 L1 loss: 0.0000e+00 L2 loss: 0.68499 Learning rate: 0.02 Mask loss: 0.1494 RPN box loss: 0.0427 RPN score loss: 0.00868 RPN total loss: 0.05138 Total loss: 1.09553 timestamp: 1655035956.1397955 iteration: 35330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17692 FastRCNN class loss: 0.14 FastRCNN total loss: 0.31692 L1 loss: 0.0000e+00 L2 loss: 0.68491 Learning rate: 0.02 Mask loss: 0.19056 RPN box loss: 0.01706 RPN score loss: 0.00894 RPN total loss: 0.026 Total loss: 1.21838 timestamp: 1655035959.3455539 iteration: 35335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.18768 L1 loss: 0.0000e+00 L2 loss: 0.68482 Learning rate: 0.02 Mask loss: 0.16623 RPN box loss: 0.03727 RPN score loss: 0.00703 RPN total loss: 0.04429 Total loss: 1.08302 timestamp: 1655035962.5763378 iteration: 35340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10603 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.17289 L1 loss: 0.0000e+00 L2 loss: 0.68474 Learning rate: 0.02 Mask loss: 0.13249 RPN box loss: 0.09844 RPN score loss: 0.00929 RPN total loss: 0.10772 Total loss: 1.09784 timestamp: 1655035965.8589354 iteration: 35345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09117 FastRCNN class loss: 0.06725 FastRCNN total loss: 0.15842 L1 loss: 0.0000e+00 L2 loss: 0.68463 Learning rate: 0.02 Mask loss: 0.17211 RPN box loss: 0.02912 RPN score loss: 0.00804 RPN total loss: 0.03715 Total loss: 1.05231 timestamp: 1655035969.1597588 iteration: 35350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12944 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.20207 L1 loss: 0.0000e+00 L2 loss: 0.6845 Learning rate: 0.02 Mask loss: 0.13637 RPN box loss: 0.03241 RPN score loss: 0.01076 RPN total loss: 0.04317 Total loss: 1.06611 timestamp: 1655035972.4644012 iteration: 35355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19705 FastRCNN class loss: 0.09953 FastRCNN total loss: 0.29658 L1 loss: 0.0000e+00 L2 loss: 0.68439 Learning rate: 0.02 Mask loss: 0.15222 RPN box loss: 0.03725 RPN score loss: 0.03242 RPN total loss: 0.06966 Total loss: 1.20286 timestamp: 1655035975.7282689 iteration: 35360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15724 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.22745 L1 loss: 0.0000e+00 L2 loss: 0.68431 Learning rate: 0.02 Mask loss: 0.1553 RPN box loss: 0.04873 RPN score loss: 0.00312 RPN total loss: 0.05185 Total loss: 1.1189 timestamp: 1655035979.0363023 iteration: 35365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09802 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.14817 L1 loss: 0.0000e+00 L2 loss: 0.68421 Learning rate: 0.02 Mask loss: 0.17274 RPN box loss: 0.00971 RPN score loss: 0.00881 RPN total loss: 0.01852 Total loss: 1.02364 timestamp: 1655035982.3168106 iteration: 35370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15209 FastRCNN class loss: 0.07944 FastRCNN total loss: 0.23152 L1 loss: 0.0000e+00 L2 loss: 0.68412 Learning rate: 0.02 Mask loss: 0.15131 RPN box loss: 0.01904 RPN score loss: 0.00586 RPN total loss: 0.0249 Total loss: 1.09185 timestamp: 1655035985.6395788 iteration: 35375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.10124 FastRCNN total loss: 0.25267 L1 loss: 0.0000e+00 L2 loss: 0.68403 Learning rate: 0.02 Mask loss: 0.21877 RPN box loss: 0.06419 RPN score loss: 0.01331 RPN total loss: 0.0775 Total loss: 1.23296 timestamp: 1655035988.9260721 iteration: 35380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20461 FastRCNN class loss: 0.07798 FastRCNN total loss: 0.28259 L1 loss: 0.0000e+00 L2 loss: 0.68392 Learning rate: 0.02 Mask loss: 0.17737 RPN box loss: 0.02921 RPN score loss: 0.0064 RPN total loss: 0.03562 Total loss: 1.1795 timestamp: 1655035992.2445023 iteration: 35385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10948 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.17925 L1 loss: 0.0000e+00 L2 loss: 0.68384 Learning rate: 0.02 Mask loss: 0.12467 RPN box loss: 0.04397 RPN score loss: 0.00363 RPN total loss: 0.0476 Total loss: 1.03535 timestamp: 1655035995.4647572 iteration: 35390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.11358 FastRCNN total loss: 0.23153 L1 loss: 0.0000e+00 L2 loss: 0.68372 Learning rate: 0.02 Mask loss: 0.16852 RPN box loss: 0.05504 RPN score loss: 0.02091 RPN total loss: 0.07595 Total loss: 1.15973 timestamp: 1655035998.6977496 iteration: 35395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06881 FastRCNN class loss: 0.0595 FastRCNN total loss: 0.12831 L1 loss: 0.0000e+00 L2 loss: 0.68363 Learning rate: 0.02 Mask loss: 0.13343 RPN box loss: 0.05579 RPN score loss: 0.0039 RPN total loss: 0.0597 Total loss: 1.00507 timestamp: 1655036001.998691 iteration: 35400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18353 FastRCNN class loss: 0.06411 FastRCNN total loss: 0.24764 L1 loss: 0.0000e+00 L2 loss: 0.68356 Learning rate: 0.02 Mask loss: 0.17925 RPN box loss: 0.02437 RPN score loss: 0.00273 RPN total loss: 0.02709 Total loss: 1.13755 timestamp: 1655036005.2456906 iteration: 35405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.17527 L1 loss: 0.0000e+00 L2 loss: 0.68347 Learning rate: 0.02 Mask loss: 0.10155 RPN box loss: 0.02394 RPN score loss: 0.00326 RPN total loss: 0.0272 Total loss: 0.9875 timestamp: 1655036008.5623357 iteration: 35410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08903 FastRCNN class loss: 0.05437 FastRCNN total loss: 0.1434 L1 loss: 0.0000e+00 L2 loss: 0.68335 Learning rate: 0.02 Mask loss: 0.13653 RPN box loss: 0.02086 RPN score loss: 0.00175 RPN total loss: 0.02262 Total loss: 0.9859 timestamp: 1655036011.8932467 iteration: 35415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16202 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.22597 L1 loss: 0.0000e+00 L2 loss: 0.68324 Learning rate: 0.02 Mask loss: 0.20164 RPN box loss: 0.03953 RPN score loss: 0.00568 RPN total loss: 0.04521 Total loss: 1.15606 timestamp: 1655036015.223989 iteration: 35420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.04013 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.68315 Learning rate: 0.02 Mask loss: 0.10701 RPN box loss: 0.0262 RPN score loss: 0.00564 RPN total loss: 0.03184 Total loss: 0.98411 timestamp: 1655036018.4889684 iteration: 35425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14611 FastRCNN class loss: 0.09053 FastRCNN total loss: 0.23663 L1 loss: 0.0000e+00 L2 loss: 0.68305 Learning rate: 0.02 Mask loss: 0.19013 RPN box loss: 0.04549 RPN score loss: 0.03094 RPN total loss: 0.07643 Total loss: 1.18625 timestamp: 1655036021.6726787 iteration: 35430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09345 FastRCNN class loss: 0.04232 FastRCNN total loss: 0.13577 L1 loss: 0.0000e+00 L2 loss: 0.68296 Learning rate: 0.02 Mask loss: 0.13927 RPN box loss: 0.01955 RPN score loss: 0.00467 RPN total loss: 0.02422 Total loss: 0.98222 timestamp: 1655036024.9282327 iteration: 35435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11024 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.1657 L1 loss: 0.0000e+00 L2 loss: 0.68288 Learning rate: 0.02 Mask loss: 0.10748 RPN box loss: 0.05101 RPN score loss: 0.00933 RPN total loss: 0.06034 Total loss: 1.0164 timestamp: 1655036028.2342849 iteration: 35440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16323 FastRCNN class loss: 0.09192 FastRCNN total loss: 0.25515 L1 loss: 0.0000e+00 L2 loss: 0.68279 Learning rate: 0.02 Mask loss: 0.22183 RPN box loss: 0.06494 RPN score loss: 0.01546 RPN total loss: 0.08039 Total loss: 1.24017 timestamp: 1655036031.5185509 iteration: 35445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10637 FastRCNN class loss: 0.05473 FastRCNN total loss: 0.1611 L1 loss: 0.0000e+00 L2 loss: 0.68273 Learning rate: 0.02 Mask loss: 0.16522 RPN box loss: 0.02676 RPN score loss: 0.00593 RPN total loss: 0.03269 Total loss: 1.04174 timestamp: 1655036034.7550006 iteration: 35450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.18538 L1 loss: 0.0000e+00 L2 loss: 0.68262 Learning rate: 0.02 Mask loss: 0.11467 RPN box loss: 0.00707 RPN score loss: 0.00385 RPN total loss: 0.01092 Total loss: 0.99359 timestamp: 1655036038.0542188 iteration: 35455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13643 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.20071 L1 loss: 0.0000e+00 L2 loss: 0.68251 Learning rate: 0.02 Mask loss: 0.15247 RPN box loss: 0.03367 RPN score loss: 0.01663 RPN total loss: 0.0503 Total loss: 1.086 timestamp: 1655036041.3539722 iteration: 35460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17672 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.26292 L1 loss: 0.0000e+00 L2 loss: 0.68241 Learning rate: 0.02 Mask loss: 0.11316 RPN box loss: 0.02799 RPN score loss: 0.00459 RPN total loss: 0.03257 Total loss: 1.09106 timestamp: 1655036044.6740913 iteration: 35465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12412 FastRCNN class loss: 0.10217 FastRCNN total loss: 0.2263 L1 loss: 0.0000e+00 L2 loss: 0.68232 Learning rate: 0.02 Mask loss: 0.18848 RPN box loss: 0.03455 RPN score loss: 0.00469 RPN total loss: 0.03924 Total loss: 1.13634 timestamp: 1655036048.0109148 iteration: 35470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17897 FastRCNN class loss: 0.10524 FastRCNN total loss: 0.28421 L1 loss: 0.0000e+00 L2 loss: 0.68223 Learning rate: 0.02 Mask loss: 0.18931 RPN box loss: 0.04061 RPN score loss: 0.00938 RPN total loss: 0.04999 Total loss: 1.20574 timestamp: 1655036051.3135774 iteration: 35475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11207 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.17289 L1 loss: 0.0000e+00 L2 loss: 0.68212 Learning rate: 0.02 Mask loss: 0.13562 RPN box loss: 0.05479 RPN score loss: 0.00758 RPN total loss: 0.06237 Total loss: 1.05299 timestamp: 1655036054.5545104 iteration: 35480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11047 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.16679 L1 loss: 0.0000e+00 L2 loss: 0.68203 Learning rate: 0.02 Mask loss: 0.11467 RPN box loss: 0.03466 RPN score loss: 0.00144 RPN total loss: 0.0361 Total loss: 0.9996 timestamp: 1655036057.8785374 iteration: 35485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17072 FastRCNN class loss: 0.11994 FastRCNN total loss: 0.29066 L1 loss: 0.0000e+00 L2 loss: 0.68196 Learning rate: 0.02 Mask loss: 0.35543 RPN box loss: 0.01629 RPN score loss: 0.00284 RPN total loss: 0.01913 Total loss: 1.34718 timestamp: 1655036061.1109312 iteration: 35490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17909 FastRCNN class loss: 0.12268 FastRCNN total loss: 0.30177 L1 loss: 0.0000e+00 L2 loss: 0.68189 Learning rate: 0.02 Mask loss: 0.16815 RPN box loss: 0.03319 RPN score loss: 0.01114 RPN total loss: 0.04433 Total loss: 1.19614 timestamp: 1655036064.4086204 iteration: 35495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19 FastRCNN class loss: 0.11464 FastRCNN total loss: 0.30464 L1 loss: 0.0000e+00 L2 loss: 0.6818 Learning rate: 0.02 Mask loss: 0.20723 RPN box loss: 0.06031 RPN score loss: 0.01402 RPN total loss: 0.07433 Total loss: 1.268 timestamp: 1655036067.6764224 iteration: 35500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09118 FastRCNN class loss: 0.04072 FastRCNN total loss: 0.1319 L1 loss: 0.0000e+00 L2 loss: 0.6817 Learning rate: 0.02 Mask loss: 0.10631 RPN box loss: 0.00603 RPN score loss: 0.00781 RPN total loss: 0.01384 Total loss: 0.93375 timestamp: 1655036070.9396236 iteration: 35505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.15041 L1 loss: 0.0000e+00 L2 loss: 0.68159 Learning rate: 0.02 Mask loss: 0.1817 RPN box loss: 0.0176 RPN score loss: 0.00136 RPN total loss: 0.01896 Total loss: 1.03267 timestamp: 1655036074.1445408 iteration: 35510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17686 FastRCNN class loss: 0.13034 FastRCNN total loss: 0.3072 L1 loss: 0.0000e+00 L2 loss: 0.68148 Learning rate: 0.02 Mask loss: 0.17959 RPN box loss: 0.03553 RPN score loss: 0.00876 RPN total loss: 0.0443 Total loss: 1.21256 timestamp: 1655036077.4402275 iteration: 35515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16934 FastRCNN class loss: 0.10263 FastRCNN total loss: 0.27196 L1 loss: 0.0000e+00 L2 loss: 0.68138 Learning rate: 0.02 Mask loss: 0.2163 RPN box loss: 0.03059 RPN score loss: 0.01422 RPN total loss: 0.04481 Total loss: 1.21445 timestamp: 1655036080.7275596 iteration: 35520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.154 FastRCNN class loss: 0.09784 FastRCNN total loss: 0.25184 L1 loss: 0.0000e+00 L2 loss: 0.68129 Learning rate: 0.02 Mask loss: 0.19413 RPN box loss: 0.04468 RPN score loss: 0.01409 RPN total loss: 0.05877 Total loss: 1.18603 timestamp: 1655036084.0021474 iteration: 35525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15497 FastRCNN class loss: 0.09196 FastRCNN total loss: 0.24693 L1 loss: 0.0000e+00 L2 loss: 0.6812 Learning rate: 0.02 Mask loss: 0.15416 RPN box loss: 0.00967 RPN score loss: 0.00299 RPN total loss: 0.01266 Total loss: 1.09495 timestamp: 1655036087.2760978 iteration: 35530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15348 FastRCNN class loss: 0.08291 FastRCNN total loss: 0.23639 L1 loss: 0.0000e+00 L2 loss: 0.68108 Learning rate: 0.02 Mask loss: 0.22775 RPN box loss: 0.02561 RPN score loss: 0.00525 RPN total loss: 0.03086 Total loss: 1.17608 timestamp: 1655036090.534443 iteration: 35535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14681 FastRCNN class loss: 0.12757 FastRCNN total loss: 0.27438 L1 loss: 0.0000e+00 L2 loss: 0.68099 Learning rate: 0.02 Mask loss: 0.21585 RPN box loss: 0.05899 RPN score loss: 0.0179 RPN total loss: 0.07689 Total loss: 1.24811 timestamp: 1655036093.756811 iteration: 35540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14086 FastRCNN class loss: 0.09401 FastRCNN total loss: 0.23488 L1 loss: 0.0000e+00 L2 loss: 0.68091 Learning rate: 0.02 Mask loss: 0.15181 RPN box loss: 0.02937 RPN score loss: 0.01392 RPN total loss: 0.04328 Total loss: 1.11089 timestamp: 1655036097.1138446 iteration: 35545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2512 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.35515 L1 loss: 0.0000e+00 L2 loss: 0.68081 Learning rate: 0.02 Mask loss: 0.23735 RPN box loss: 0.04073 RPN score loss: 0.0051 RPN total loss: 0.04583 Total loss: 1.31915 timestamp: 1655036100.332662 iteration: 35550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18077 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.24553 L1 loss: 0.0000e+00 L2 loss: 0.68073 Learning rate: 0.02 Mask loss: 0.09662 RPN box loss: 0.03563 RPN score loss: 0.00345 RPN total loss: 0.03907 Total loss: 1.06196 timestamp: 1655036103.620151 iteration: 35555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20205 FastRCNN class loss: 0.13094 FastRCNN total loss: 0.33299 L1 loss: 0.0000e+00 L2 loss: 0.68064 Learning rate: 0.02 Mask loss: 0.25658 RPN box loss: 0.05693 RPN score loss: 0.01766 RPN total loss: 0.0746 Total loss: 1.34481 timestamp: 1655036106.854666 iteration: 35560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08483 FastRCNN class loss: 0.04462 FastRCNN total loss: 0.12944 L1 loss: 0.0000e+00 L2 loss: 0.68055 Learning rate: 0.02 Mask loss: 0.11824 RPN box loss: 0.01972 RPN score loss: 0.00927 RPN total loss: 0.02899 Total loss: 0.95723 timestamp: 1655036110.116433 iteration: 35565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23578 FastRCNN class loss: 0.09022 FastRCNN total loss: 0.326 L1 loss: 0.0000e+00 L2 loss: 0.68047 Learning rate: 0.02 Mask loss: 0.17307 RPN box loss: 0.02438 RPN score loss: 0.00713 RPN total loss: 0.0315 Total loss: 1.21104 timestamp: 1655036113.4549177 iteration: 35570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0842 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.16099 L1 loss: 0.0000e+00 L2 loss: 0.68038 Learning rate: 0.02 Mask loss: 0.19148 RPN box loss: 0.03529 RPN score loss: 0.01463 RPN total loss: 0.04992 Total loss: 1.08276 timestamp: 1655036116.6891456 iteration: 35575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16649 FastRCNN class loss: 0.14709 FastRCNN total loss: 0.31359 L1 loss: 0.0000e+00 L2 loss: 0.68029 Learning rate: 0.02 Mask loss: 0.12985 RPN box loss: 0.02538 RPN score loss: 0.00877 RPN total loss: 0.03415 Total loss: 1.15788 timestamp: 1655036119.9773014 iteration: 35580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14755 FastRCNN class loss: 0.16528 FastRCNN total loss: 0.31283 L1 loss: 0.0000e+00 L2 loss: 0.68019 Learning rate: 0.02 Mask loss: 0.14788 RPN box loss: 0.04471 RPN score loss: 0.01161 RPN total loss: 0.05632 Total loss: 1.19722 timestamp: 1655036123.1872492 iteration: 35585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12706 FastRCNN class loss: 0.06238 FastRCNN total loss: 0.18944 L1 loss: 0.0000e+00 L2 loss: 0.68006 Learning rate: 0.02 Mask loss: 0.11538 RPN box loss: 0.02258 RPN score loss: 0.00303 RPN total loss: 0.02561 Total loss: 1.0105 timestamp: 1655036126.4735353 iteration: 35590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19121 FastRCNN class loss: 0.08435 FastRCNN total loss: 0.27556 L1 loss: 0.0000e+00 L2 loss: 0.67998 Learning rate: 0.02 Mask loss: 0.15436 RPN box loss: 0.05196 RPN score loss: 0.00961 RPN total loss: 0.06157 Total loss: 1.17147 timestamp: 1655036129.7654364 iteration: 35595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10992 FastRCNN class loss: 0.08273 FastRCNN total loss: 0.19265 L1 loss: 0.0000e+00 L2 loss: 0.67987 Learning rate: 0.02 Mask loss: 0.14469 RPN box loss: 0.05372 RPN score loss: 0.01294 RPN total loss: 0.06666 Total loss: 1.08387 timestamp: 1655036132.9992533 iteration: 35600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15285 FastRCNN class loss: 0.13951 FastRCNN total loss: 0.29236 L1 loss: 0.0000e+00 L2 loss: 0.67977 Learning rate: 0.02 Mask loss: 0.1776 RPN box loss: 0.04236 RPN score loss: 0.00608 RPN total loss: 0.04844 Total loss: 1.19818 timestamp: 1655036136.3331559 iteration: 35605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06919 FastRCNN class loss: 0.03842 FastRCNN total loss: 0.10761 L1 loss: 0.0000e+00 L2 loss: 0.67971 Learning rate: 0.02 Mask loss: 0.1211 RPN box loss: 0.00487 RPN score loss: 0.00312 RPN total loss: 0.008 Total loss: 0.91642 timestamp: 1655036139.5818992 iteration: 35610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13291 FastRCNN class loss: 0.08782 FastRCNN total loss: 0.22073 L1 loss: 0.0000e+00 L2 loss: 0.67962 Learning rate: 0.02 Mask loss: 0.17034 RPN box loss: 0.04255 RPN score loss: 0.00352 RPN total loss: 0.04608 Total loss: 1.11677 timestamp: 1655036142.8530219 iteration: 35615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18415 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.25942 L1 loss: 0.0000e+00 L2 loss: 0.67952 Learning rate: 0.02 Mask loss: 0.21848 RPN box loss: 0.03131 RPN score loss: 0.00788 RPN total loss: 0.03919 Total loss: 1.1966 timestamp: 1655036146.1386163 iteration: 35620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14122 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.21564 L1 loss: 0.0000e+00 L2 loss: 0.67946 Learning rate: 0.02 Mask loss: 0.17205 RPN box loss: 0.04373 RPN score loss: 0.01235 RPN total loss: 0.05607 Total loss: 1.12321 timestamp: 1655036149.390967 iteration: 35625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19322 FastRCNN class loss: 0.10861 FastRCNN total loss: 0.30183 L1 loss: 0.0000e+00 L2 loss: 0.67936 Learning rate: 0.02 Mask loss: 0.14701 RPN box loss: 0.05659 RPN score loss: 0.0048 RPN total loss: 0.06139 Total loss: 1.18959 timestamp: 1655036152.6393182 iteration: 35630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15247 FastRCNN class loss: 0.12585 FastRCNN total loss: 0.27832 L1 loss: 0.0000e+00 L2 loss: 0.67924 Learning rate: 0.02 Mask loss: 0.17424 RPN box loss: 0.01739 RPN score loss: 0.00811 RPN total loss: 0.02551 Total loss: 1.15731 timestamp: 1655036155.9681902 iteration: 35635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18872 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.26913 L1 loss: 0.0000e+00 L2 loss: 0.67914 Learning rate: 0.02 Mask loss: 0.22757 RPN box loss: 0.01401 RPN score loss: 0.00157 RPN total loss: 0.01559 Total loss: 1.19143 timestamp: 1655036159.2665458 iteration: 35640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10667 FastRCNN class loss: 0.07921 FastRCNN total loss: 0.18588 L1 loss: 0.0000e+00 L2 loss: 0.67904 Learning rate: 0.02 Mask loss: 0.13821 RPN box loss: 0.01177 RPN score loss: 0.00339 RPN total loss: 0.01516 Total loss: 1.01829 timestamp: 1655036162.4420526 iteration: 35645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07643 FastRCNN class loss: 0.04341 FastRCNN total loss: 0.11984 L1 loss: 0.0000e+00 L2 loss: 0.67894 Learning rate: 0.02 Mask loss: 0.13919 RPN box loss: 0.01092 RPN score loss: 0.00461 RPN total loss: 0.01553 Total loss: 0.9535 timestamp: 1655036165.7180216 iteration: 35650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10296 FastRCNN class loss: 0.06277 FastRCNN total loss: 0.16572 L1 loss: 0.0000e+00 L2 loss: 0.67885 Learning rate: 0.02 Mask loss: 0.18108 RPN box loss: 0.01861 RPN score loss: 0.00487 RPN total loss: 0.02348 Total loss: 1.04914 timestamp: 1655036169.0566378 iteration: 35655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18611 FastRCNN class loss: 0.10713 FastRCNN total loss: 0.29324 L1 loss: 0.0000e+00 L2 loss: 0.67875 Learning rate: 0.02 Mask loss: 0.24557 RPN box loss: 0.0297 RPN score loss: 0.01246 RPN total loss: 0.04215 Total loss: 1.25971 timestamp: 1655036172.2997599 iteration: 35660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12066 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.19612 L1 loss: 0.0000e+00 L2 loss: 0.67867 Learning rate: 0.02 Mask loss: 0.12269 RPN box loss: 0.0633 RPN score loss: 0.00944 RPN total loss: 0.07274 Total loss: 1.07022 timestamp: 1655036175.5339005 iteration: 35665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1561 FastRCNN class loss: 0.07915 FastRCNN total loss: 0.23525 L1 loss: 0.0000e+00 L2 loss: 0.67857 Learning rate: 0.02 Mask loss: 0.14529 RPN box loss: 0.05708 RPN score loss: 0.02285 RPN total loss: 0.07993 Total loss: 1.13903 timestamp: 1655036178.840946 iteration: 35670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12586 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.17773 L1 loss: 0.0000e+00 L2 loss: 0.67848 Learning rate: 0.02 Mask loss: 0.10167 RPN box loss: 0.0548 RPN score loss: 0.00174 RPN total loss: 0.05654 Total loss: 1.01441 timestamp: 1655036182.087115 iteration: 35675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07035 FastRCNN class loss: 0.09757 FastRCNN total loss: 0.16792 L1 loss: 0.0000e+00 L2 loss: 0.67839 Learning rate: 0.02 Mask loss: 0.20158 RPN box loss: 0.00667 RPN score loss: 0.00318 RPN total loss: 0.00985 Total loss: 1.05773 timestamp: 1655036185.3417678 iteration: 35680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19133 FastRCNN class loss: 0.13172 FastRCNN total loss: 0.32305 L1 loss: 0.0000e+00 L2 loss: 0.67828 Learning rate: 0.02 Mask loss: 0.19566 RPN box loss: 0.0259 RPN score loss: 0.01319 RPN total loss: 0.03909 Total loss: 1.23608 timestamp: 1655036188.5404937 iteration: 35685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18401 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.28542 L1 loss: 0.0000e+00 L2 loss: 0.67817 Learning rate: 0.02 Mask loss: 0.14332 RPN box loss: 0.0319 RPN score loss: 0.00473 RPN total loss: 0.03663 Total loss: 1.14354 timestamp: 1655036191.8122663 iteration: 35690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11997 FastRCNN class loss: 0.11491 FastRCNN total loss: 0.23488 L1 loss: 0.0000e+00 L2 loss: 0.67808 Learning rate: 0.02 Mask loss: 0.13743 RPN box loss: 0.04104 RPN score loss: 0.00456 RPN total loss: 0.0456 Total loss: 1.09599 timestamp: 1655036195.099812 iteration: 35695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12398 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.19551 L1 loss: 0.0000e+00 L2 loss: 0.67797 Learning rate: 0.02 Mask loss: 0.13185 RPN box loss: 0.06274 RPN score loss: 0.00566 RPN total loss: 0.0684 Total loss: 1.07373 timestamp: 1655036198.2483184 iteration: 35700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18542 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.26742 L1 loss: 0.0000e+00 L2 loss: 0.67788 Learning rate: 0.02 Mask loss: 0.13577 RPN box loss: 0.02134 RPN score loss: 0.01159 RPN total loss: 0.03294 Total loss: 1.11401 timestamp: 1655036201.4693363 iteration: 35705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.1206 L1 loss: 0.0000e+00 L2 loss: 0.67777 Learning rate: 0.02 Mask loss: 0.1695 RPN box loss: 0.00575 RPN score loss: 0.00327 RPN total loss: 0.00902 Total loss: 0.97689 timestamp: 1655036204.6498568 iteration: 35710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08104 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.14961 L1 loss: 0.0000e+00 L2 loss: 0.6777 Learning rate: 0.02 Mask loss: 0.18843 RPN box loss: 0.05663 RPN score loss: 0.00943 RPN total loss: 0.06606 Total loss: 1.0818 timestamp: 1655036207.9174426 iteration: 35715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09867 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.17019 L1 loss: 0.0000e+00 L2 loss: 0.67761 Learning rate: 0.02 Mask loss: 0.15058 RPN box loss: 0.04784 RPN score loss: 0.00526 RPN total loss: 0.0531 Total loss: 1.05148 timestamp: 1655036211.2053785 iteration: 35720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11731 FastRCNN class loss: 0.04682 FastRCNN total loss: 0.16413 L1 loss: 0.0000e+00 L2 loss: 0.67755 Learning rate: 0.02 Mask loss: 0.12837 RPN box loss: 0.01859 RPN score loss: 0.00227 RPN total loss: 0.02086 Total loss: 0.99091 timestamp: 1655036214.4134614 iteration: 35725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10686 FastRCNN class loss: 0.04814 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.67749 Learning rate: 0.02 Mask loss: 0.13238 RPN box loss: 0.0302 RPN score loss: 0.00622 RPN total loss: 0.03642 Total loss: 1.00129 timestamp: 1655036217.696466 iteration: 35730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11837 FastRCNN class loss: 0.11057 FastRCNN total loss: 0.22894 L1 loss: 0.0000e+00 L2 loss: 0.67739 Learning rate: 0.02 Mask loss: 0.14248 RPN box loss: 0.04026 RPN score loss: 0.00302 RPN total loss: 0.04328 Total loss: 1.09209 timestamp: 1655036220.9677906 iteration: 35735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11904 FastRCNN class loss: 0.05748 FastRCNN total loss: 0.17651 L1 loss: 0.0000e+00 L2 loss: 0.67727 Learning rate: 0.02 Mask loss: 0.1449 RPN box loss: 0.02762 RPN score loss: 0.00134 RPN total loss: 0.02896 Total loss: 1.02764 timestamp: 1655036224.276853 iteration: 35740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12328 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.20654 L1 loss: 0.0000e+00 L2 loss: 0.67719 Learning rate: 0.02 Mask loss: 0.18319 RPN box loss: 0.0574 RPN score loss: 0.02871 RPN total loss: 0.08611 Total loss: 1.15303 timestamp: 1655036227.580944 iteration: 35745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20807 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.27146 L1 loss: 0.0000e+00 L2 loss: 0.67707 Learning rate: 0.02 Mask loss: 0.22774 RPN box loss: 0.02037 RPN score loss: 0.00561 RPN total loss: 0.02598 Total loss: 1.20225 timestamp: 1655036230.8508053 iteration: 35750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14226 FastRCNN class loss: 0.0839 FastRCNN total loss: 0.22617 L1 loss: 0.0000e+00 L2 loss: 0.67697 Learning rate: 0.02 Mask loss: 0.1645 RPN box loss: 0.02284 RPN score loss: 0.00884 RPN total loss: 0.03168 Total loss: 1.09932 timestamp: 1655036234.1274524 iteration: 35755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.07431 FastRCNN total loss: 0.15522 L1 loss: 0.0000e+00 L2 loss: 0.67688 Learning rate: 0.02 Mask loss: 0.10497 RPN box loss: 0.01891 RPN score loss: 0.00624 RPN total loss: 0.02515 Total loss: 0.96221 timestamp: 1655036237.434978 iteration: 35760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13152 FastRCNN class loss: 0.08558 FastRCNN total loss: 0.2171 L1 loss: 0.0000e+00 L2 loss: 0.6768 Learning rate: 0.02 Mask loss: 0.19338 RPN box loss: 0.01954 RPN score loss: 0.00601 RPN total loss: 0.02555 Total loss: 1.11283 timestamp: 1655036240.6154463 iteration: 35765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11246 FastRCNN class loss: 0.07703 FastRCNN total loss: 0.1895 L1 loss: 0.0000e+00 L2 loss: 0.6767 Learning rate: 0.02 Mask loss: 0.17253 RPN box loss: 0.02743 RPN score loss: 0.00787 RPN total loss: 0.03529 Total loss: 1.07402 timestamp: 1655036243.9229233 iteration: 35770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14256 FastRCNN class loss: 0.10981 FastRCNN total loss: 0.25237 L1 loss: 0.0000e+00 L2 loss: 0.67663 Learning rate: 0.02 Mask loss: 0.18888 RPN box loss: 0.07894 RPN score loss: 0.00698 RPN total loss: 0.08592 Total loss: 1.20379 timestamp: 1655036247.2128441 iteration: 35775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10807 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.1731 L1 loss: 0.0000e+00 L2 loss: 0.67654 Learning rate: 0.02 Mask loss: 0.16995 RPN box loss: 0.01497 RPN score loss: 0.00943 RPN total loss: 0.0244 Total loss: 1.04399 timestamp: 1655036250.4168556 iteration: 35780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09247 FastRCNN class loss: 0.08318 FastRCNN total loss: 0.17565 L1 loss: 0.0000e+00 L2 loss: 0.67643 Learning rate: 0.02 Mask loss: 0.1214 RPN box loss: 0.0431 RPN score loss: 0.00826 RPN total loss: 0.05136 Total loss: 1.02485 timestamp: 1655036253.669592 iteration: 35785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.17924 L1 loss: 0.0000e+00 L2 loss: 0.67632 Learning rate: 0.02 Mask loss: 0.17937 RPN box loss: 0.01512 RPN score loss: 0.00838 RPN total loss: 0.02351 Total loss: 1.05844 timestamp: 1655036256.937303 iteration: 35790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11346 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.17513 L1 loss: 0.0000e+00 L2 loss: 0.67621 Learning rate: 0.02 Mask loss: 0.15214 RPN box loss: 0.05642 RPN score loss: 0.01069 RPN total loss: 0.0671 Total loss: 1.07059 timestamp: 1655036260.2171893 iteration: 35795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.12232 L1 loss: 0.0000e+00 L2 loss: 0.67611 Learning rate: 0.02 Mask loss: 0.15953 RPN box loss: 0.03114 RPN score loss: 0.00221 RPN total loss: 0.03335 Total loss: 0.99131 timestamp: 1655036263.490552 iteration: 35800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21313 FastRCNN class loss: 0.12175 FastRCNN total loss: 0.33488 L1 loss: 0.0000e+00 L2 loss: 0.676 Learning rate: 0.02 Mask loss: 0.21428 RPN box loss: 0.02784 RPN score loss: 0.0113 RPN total loss: 0.03914 Total loss: 1.2643 timestamp: 1655036266.7561672 iteration: 35805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11244 FastRCNN class loss: 0.08431 FastRCNN total loss: 0.19675 L1 loss: 0.0000e+00 L2 loss: 0.67593 Learning rate: 0.02 Mask loss: 0.14059 RPN box loss: 0.07615 RPN score loss: 0.00514 RPN total loss: 0.08129 Total loss: 1.09457 timestamp: 1655036269.9681504 iteration: 35810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16035 FastRCNN class loss: 0.11461 FastRCNN total loss: 0.27495 L1 loss: 0.0000e+00 L2 loss: 0.67587 Learning rate: 0.02 Mask loss: 0.18361 RPN box loss: 0.05072 RPN score loss: 0.01035 RPN total loss: 0.06107 Total loss: 1.19551 timestamp: 1655036273.2635965 iteration: 35815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11937 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.67578 Learning rate: 0.02 Mask loss: 0.21399 RPN box loss: 0.03685 RPN score loss: 0.0193 RPN total loss: 0.05616 Total loss: 1.14861 timestamp: 1655036276.5230503 iteration: 35820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16429 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.26504 L1 loss: 0.0000e+00 L2 loss: 0.6757 Learning rate: 0.02 Mask loss: 0.1668 RPN box loss: 0.01426 RPN score loss: 0.0033 RPN total loss: 0.01756 Total loss: 1.1251 timestamp: 1655036279.7354317 iteration: 35825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07186 FastRCNN class loss: 0.05964 FastRCNN total loss: 0.1315 L1 loss: 0.0000e+00 L2 loss: 0.67559 Learning rate: 0.02 Mask loss: 0.15302 RPN box loss: 0.01928 RPN score loss: 0.00285 RPN total loss: 0.02213 Total loss: 0.98223 timestamp: 1655036282.941357 iteration: 35830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14151 FastRCNN class loss: 0.09039 FastRCNN total loss: 0.2319 L1 loss: 0.0000e+00 L2 loss: 0.67548 Learning rate: 0.02 Mask loss: 0.17263 RPN box loss: 0.04109 RPN score loss: 0.00654 RPN total loss: 0.04763 Total loss: 1.12764 timestamp: 1655036286.202176 iteration: 35835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10486 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.16717 L1 loss: 0.0000e+00 L2 loss: 0.67539 Learning rate: 0.02 Mask loss: 0.14542 RPN box loss: 0.04875 RPN score loss: 0.00243 RPN total loss: 0.05118 Total loss: 1.03916 timestamp: 1655036289.4607847 iteration: 35840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11952 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.19089 L1 loss: 0.0000e+00 L2 loss: 0.67528 Learning rate: 0.02 Mask loss: 0.30149 RPN box loss: 0.08865 RPN score loss: 0.01376 RPN total loss: 0.10241 Total loss: 1.27007 timestamp: 1655036292.723117 iteration: 35845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13363 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.20481 L1 loss: 0.0000e+00 L2 loss: 0.6752 Learning rate: 0.02 Mask loss: 0.14933 RPN box loss: 0.02612 RPN score loss: 0.01044 RPN total loss: 0.03656 Total loss: 1.0659 timestamp: 1655036296.030712 iteration: 35850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14306 FastRCNN class loss: 0.1352 FastRCNN total loss: 0.27827 L1 loss: 0.0000e+00 L2 loss: 0.67513 Learning rate: 0.02 Mask loss: 0.21284 RPN box loss: 0.07854 RPN score loss: 0.0116 RPN total loss: 0.09014 Total loss: 1.25637 timestamp: 1655036299.328229 iteration: 35855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09086 FastRCNN class loss: 0.09167 FastRCNN total loss: 0.18253 L1 loss: 0.0000e+00 L2 loss: 0.67502 Learning rate: 0.02 Mask loss: 0.21319 RPN box loss: 0.04174 RPN score loss: 0.01223 RPN total loss: 0.05397 Total loss: 1.12472 timestamp: 1655036302.5924745 iteration: 35860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10539 FastRCNN class loss: 0.04644 FastRCNN total loss: 0.15183 L1 loss: 0.0000e+00 L2 loss: 0.67492 Learning rate: 0.02 Mask loss: 0.10921 RPN box loss: 0.01057 RPN score loss: 0.00451 RPN total loss: 0.01508 Total loss: 0.95103 timestamp: 1655036305.8317165 iteration: 35865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08153 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.13746 L1 loss: 0.0000e+00 L2 loss: 0.67485 Learning rate: 0.02 Mask loss: 0.10366 RPN box loss: 0.03662 RPN score loss: 0.00527 RPN total loss: 0.04189 Total loss: 0.95786 timestamp: 1655036309.1886792 iteration: 35870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08904 FastRCNN class loss: 0.12539 FastRCNN total loss: 0.21443 L1 loss: 0.0000e+00 L2 loss: 0.67477 Learning rate: 0.02 Mask loss: 0.1034 RPN box loss: 0.0174 RPN score loss: 0.00567 RPN total loss: 0.02308 Total loss: 1.01567 timestamp: 1655036312.5973198 iteration: 35875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11229 FastRCNN class loss: 0.04435 FastRCNN total loss: 0.15664 L1 loss: 0.0000e+00 L2 loss: 0.67466 Learning rate: 0.02 Mask loss: 0.15963 RPN box loss: 0.03702 RPN score loss: 0.01159 RPN total loss: 0.04862 Total loss: 1.03954 timestamp: 1655036315.7961175 iteration: 35880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13543 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.19667 L1 loss: 0.0000e+00 L2 loss: 0.67456 Learning rate: 0.02 Mask loss: 0.134 RPN box loss: 0.02916 RPN score loss: 0.00415 RPN total loss: 0.03331 Total loss: 1.03854 timestamp: 1655036319.0315666 iteration: 35885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15309 FastRCNN class loss: 0.085 FastRCNN total loss: 0.23809 L1 loss: 0.0000e+00 L2 loss: 0.67446 Learning rate: 0.02 Mask loss: 0.22761 RPN box loss: 0.02159 RPN score loss: 0.01685 RPN total loss: 0.03844 Total loss: 1.1786 timestamp: 1655036322.2902627 iteration: 35890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17588 FastRCNN class loss: 0.15463 FastRCNN total loss: 0.33051 L1 loss: 0.0000e+00 L2 loss: 0.67437 Learning rate: 0.02 Mask loss: 0.1548 RPN box loss: 0.02379 RPN score loss: 0.0119 RPN total loss: 0.03569 Total loss: 1.19537 timestamp: 1655036325.5697632 iteration: 35895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24663 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.32751 L1 loss: 0.0000e+00 L2 loss: 0.67429 Learning rate: 0.02 Mask loss: 0.12803 RPN box loss: 0.01577 RPN score loss: 0.00341 RPN total loss: 0.01918 Total loss: 1.14901 timestamp: 1655036328.8401928 iteration: 35900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.21984 L1 loss: 0.0000e+00 L2 loss: 0.67419 Learning rate: 0.02 Mask loss: 0.13703 RPN box loss: 0.01833 RPN score loss: 0.00416 RPN total loss: 0.02249 Total loss: 1.05355 timestamp: 1655036332.08557 iteration: 35905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13555 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.67411 Learning rate: 0.02 Mask loss: 0.19029 RPN box loss: 0.08557 RPN score loss: 0.01186 RPN total loss: 0.09743 Total loss: 1.1663 timestamp: 1655036335.3395867 iteration: 35910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24242 FastRCNN class loss: 0.10398 FastRCNN total loss: 0.3464 L1 loss: 0.0000e+00 L2 loss: 0.67401 Learning rate: 0.02 Mask loss: 0.13883 RPN box loss: 0.03459 RPN score loss: 0.00966 RPN total loss: 0.04425 Total loss: 1.20349 timestamp: 1655036338.685963 iteration: 35915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14975 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.2321 L1 loss: 0.0000e+00 L2 loss: 0.67391 Learning rate: 0.02 Mask loss: 0.18158 RPN box loss: 0.02056 RPN score loss: 0.0077 RPN total loss: 0.02827 Total loss: 1.11586 timestamp: 1655036341.9295628 iteration: 35920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1313 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.21347 L1 loss: 0.0000e+00 L2 loss: 0.67384 Learning rate: 0.02 Mask loss: 0.14716 RPN box loss: 0.0371 RPN score loss: 0.01096 RPN total loss: 0.04806 Total loss: 1.08253 timestamp: 1655036345.281296 iteration: 35925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1279 FastRCNN class loss: 0.09908 FastRCNN total loss: 0.22698 L1 loss: 0.0000e+00 L2 loss: 0.67374 Learning rate: 0.02 Mask loss: 0.13209 RPN box loss: 0.02404 RPN score loss: 0.0091 RPN total loss: 0.03314 Total loss: 1.06594 timestamp: 1655036348.6424918 iteration: 35930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16326 FastRCNN class loss: 0.08849 FastRCNN total loss: 0.25175 L1 loss: 0.0000e+00 L2 loss: 0.67364 Learning rate: 0.02 Mask loss: 0.22085 RPN box loss: 0.04392 RPN score loss: 0.00721 RPN total loss: 0.05113 Total loss: 1.19737 timestamp: 1655036351.814434 iteration: 35935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15326 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.22178 L1 loss: 0.0000e+00 L2 loss: 0.67353 Learning rate: 0.02 Mask loss: 0.14599 RPN box loss: 0.02044 RPN score loss: 0.00538 RPN total loss: 0.02582 Total loss: 1.06712 timestamp: 1655036355.0997217 iteration: 35940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07528 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.15236 L1 loss: 0.0000e+00 L2 loss: 0.67344 Learning rate: 0.02 Mask loss: 0.16973 RPN box loss: 0.04235 RPN score loss: 0.01386 RPN total loss: 0.0562 Total loss: 1.05173 timestamp: 1655036358.41278 iteration: 35945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21023 FastRCNN class loss: 0.14016 FastRCNN total loss: 0.35039 L1 loss: 0.0000e+00 L2 loss: 0.67334 Learning rate: 0.02 Mask loss: 0.21697 RPN box loss: 0.04006 RPN score loss: 0.02436 RPN total loss: 0.06443 Total loss: 1.30511 timestamp: 1655036361.745231 iteration: 35950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14222 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.20665 L1 loss: 0.0000e+00 L2 loss: 0.67326 Learning rate: 0.02 Mask loss: 0.15976 RPN box loss: 0.03498 RPN score loss: 0.00988 RPN total loss: 0.04485 Total loss: 1.08453 timestamp: 1655036365.065111 iteration: 35955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1663 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.24734 L1 loss: 0.0000e+00 L2 loss: 0.6732 Learning rate: 0.02 Mask loss: 0.14576 RPN box loss: 0.0477 RPN score loss: 0.00992 RPN total loss: 0.05762 Total loss: 1.12392 timestamp: 1655036368.301118 iteration: 35960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23228 FastRCNN class loss: 0.08984 FastRCNN total loss: 0.32211 L1 loss: 0.0000e+00 L2 loss: 0.67309 Learning rate: 0.02 Mask loss: 0.13512 RPN box loss: 0.0174 RPN score loss: 0.00726 RPN total loss: 0.02466 Total loss: 1.15498 timestamp: 1655036371.5145864 iteration: 35965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17671 FastRCNN class loss: 0.1101 FastRCNN total loss: 0.28681 L1 loss: 0.0000e+00 L2 loss: 0.673 Learning rate: 0.02 Mask loss: 0.21425 RPN box loss: 0.03593 RPN score loss: 0.02297 RPN total loss: 0.05891 Total loss: 1.23296 timestamp: 1655036374.7278926 iteration: 35970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.1592 L1 loss: 0.0000e+00 L2 loss: 0.67292 Learning rate: 0.02 Mask loss: 0.14972 RPN box loss: 0.00731 RPN score loss: 0.00228 RPN total loss: 0.00958 Total loss: 0.99142 timestamp: 1655036378.0049639 iteration: 35975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15993 FastRCNN class loss: 0.1093 FastRCNN total loss: 0.26924 L1 loss: 0.0000e+00 L2 loss: 0.67282 Learning rate: 0.02 Mask loss: 0.25167 RPN box loss: 0.05852 RPN score loss: 0.00549 RPN total loss: 0.06401 Total loss: 1.25774 timestamp: 1655036381.3037071 iteration: 35980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.14184 L1 loss: 0.0000e+00 L2 loss: 0.67274 Learning rate: 0.02 Mask loss: 0.17181 RPN box loss: 0.05426 RPN score loss: 0.00897 RPN total loss: 0.06324 Total loss: 1.04962 timestamp: 1655036384.633921 iteration: 35985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.18444 L1 loss: 0.0000e+00 L2 loss: 0.67265 Learning rate: 0.02 Mask loss: 0.19914 RPN box loss: 0.03886 RPN score loss: 0.0049 RPN total loss: 0.04377 Total loss: 1.1 timestamp: 1655036387.9227166 iteration: 35990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.151 FastRCNN class loss: 0.09525 FastRCNN total loss: 0.24625 L1 loss: 0.0000e+00 L2 loss: 0.67255 Learning rate: 0.02 Mask loss: 0.13269 RPN box loss: 0.05891 RPN score loss: 0.00475 RPN total loss: 0.06366 Total loss: 1.11515 timestamp: 1655036391.2300735 iteration: 35995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0582 FastRCNN class loss: 0.03237 FastRCNN total loss: 0.09057 L1 loss: 0.0000e+00 L2 loss: 0.67246 Learning rate: 0.02 Mask loss: 0.12326 RPN box loss: 0.00186 RPN score loss: 0.00118 RPN total loss: 0.00304 Total loss: 0.88934 timestamp: 1655036394.5205905 iteration: 36000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.17626 L1 loss: 0.0000e+00 L2 loss: 0.67236 Learning rate: 0.02 Mask loss: 0.20474 RPN box loss: 0.02698 RPN score loss: 0.00375 RPN total loss: 0.03072 Total loss: 1.08409 timestamp: 1655036397.711093 iteration: 36005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14075 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.20181 L1 loss: 0.0000e+00 L2 loss: 0.67225 Learning rate: 0.02 Mask loss: 0.11046 RPN box loss: 0.01921 RPN score loss: 0.00471 RPN total loss: 0.02393 Total loss: 1.00844 timestamp: 1655036400.924999 iteration: 36010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10904 FastRCNN class loss: 0.14549 FastRCNN total loss: 0.25453 L1 loss: 0.0000e+00 L2 loss: 0.67216 Learning rate: 0.02 Mask loss: 0.18289 RPN box loss: 0.03119 RPN score loss: 0.0044 RPN total loss: 0.03559 Total loss: 1.14517 timestamp: 1655036404.172773 iteration: 36015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12432 FastRCNN class loss: 0.08536 FastRCNN total loss: 0.20967 L1 loss: 0.0000e+00 L2 loss: 0.67211 Learning rate: 0.02 Mask loss: 0.15609 RPN box loss: 0.02622 RPN score loss: 0.01163 RPN total loss: 0.03785 Total loss: 1.07572 timestamp: 1655036407.47655 iteration: 36020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16101 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.23048 L1 loss: 0.0000e+00 L2 loss: 0.67201 Learning rate: 0.02 Mask loss: 0.17047 RPN box loss: 0.02758 RPN score loss: 0.00699 RPN total loss: 0.03457 Total loss: 1.10753 timestamp: 1655036410.717633 iteration: 36025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19984 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.25928 L1 loss: 0.0000e+00 L2 loss: 0.67191 Learning rate: 0.02 Mask loss: 0.12435 RPN box loss: 0.03799 RPN score loss: 0.00235 RPN total loss: 0.04035 Total loss: 1.09588 timestamp: 1655036414.0201948 iteration: 36030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1204 FastRCNN class loss: 0.06822 FastRCNN total loss: 0.18862 L1 loss: 0.0000e+00 L2 loss: 0.67182 Learning rate: 0.02 Mask loss: 0.31462 RPN box loss: 0.04783 RPN score loss: 0.00575 RPN total loss: 0.05358 Total loss: 1.22864 timestamp: 1655036417.1975706 iteration: 36035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09542 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.18102 L1 loss: 0.0000e+00 L2 loss: 0.67174 Learning rate: 0.02 Mask loss: 0.14839 RPN box loss: 0.03288 RPN score loss: 0.01709 RPN total loss: 0.04997 Total loss: 1.05113 timestamp: 1655036420.4494283 iteration: 36040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1589 FastRCNN class loss: 0.09685 FastRCNN total loss: 0.25575 L1 loss: 0.0000e+00 L2 loss: 0.67165 Learning rate: 0.02 Mask loss: 0.17053 RPN box loss: 0.0109 RPN score loss: 0.00401 RPN total loss: 0.01491 Total loss: 1.11284 timestamp: 1655036423.6393573 iteration: 36045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1751 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.26619 L1 loss: 0.0000e+00 L2 loss: 0.67154 Learning rate: 0.02 Mask loss: 0.24163 RPN box loss: 0.04577 RPN score loss: 0.00771 RPN total loss: 0.05348 Total loss: 1.23284 timestamp: 1655036426.8545427 iteration: 36050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12219 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.67144 Learning rate: 0.02 Mask loss: 0.15901 RPN box loss: 0.06797 RPN score loss: 0.00413 RPN total loss: 0.0721 Total loss: 1.07809 timestamp: 1655036430.186471 iteration: 36055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09299 FastRCNN class loss: 0.04133 FastRCNN total loss: 0.13432 L1 loss: 0.0000e+00 L2 loss: 0.67134 Learning rate: 0.02 Mask loss: 0.11302 RPN box loss: 0.07644 RPN score loss: 0.00202 RPN total loss: 0.07847 Total loss: 0.99714 timestamp: 1655036433.4744425 iteration: 36060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.06934 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.67124 Learning rate: 0.02 Mask loss: 0.16375 RPN box loss: 0.05074 RPN score loss: 0.01397 RPN total loss: 0.06471 Total loss: 1.1026 timestamp: 1655036436.7707205 iteration: 36065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09636 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.16205 L1 loss: 0.0000e+00 L2 loss: 0.67115 Learning rate: 0.02 Mask loss: 0.14553 RPN box loss: 0.02286 RPN score loss: 0.00204 RPN total loss: 0.0249 Total loss: 1.00363 timestamp: 1655036440.0764008 iteration: 36070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17753 FastRCNN class loss: 0.14965 FastRCNN total loss: 0.32718 L1 loss: 0.0000e+00 L2 loss: 0.67105 Learning rate: 0.02 Mask loss: 0.16416 RPN box loss: 0.05737 RPN score loss: 0.00243 RPN total loss: 0.0598 Total loss: 1.22219 timestamp: 1655036443.2899592 iteration: 36075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14994 FastRCNN class loss: 0.07287 FastRCNN total loss: 0.22281 L1 loss: 0.0000e+00 L2 loss: 0.67094 Learning rate: 0.02 Mask loss: 0.16752 RPN box loss: 0.01986 RPN score loss: 0.00845 RPN total loss: 0.02831 Total loss: 1.08958 timestamp: 1655036446.5231526 iteration: 36080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09786 FastRCNN class loss: 0.0533 FastRCNN total loss: 0.15116 L1 loss: 0.0000e+00 L2 loss: 0.67086 Learning rate: 0.02 Mask loss: 0.12056 RPN box loss: 0.0139 RPN score loss: 0.00252 RPN total loss: 0.01643 Total loss: 0.959 timestamp: 1655036449.766441 iteration: 36085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08744 FastRCNN class loss: 0.05325 FastRCNN total loss: 0.14068 L1 loss: 0.0000e+00 L2 loss: 0.67075 Learning rate: 0.02 Mask loss: 0.15314 RPN box loss: 0.01459 RPN score loss: 0.00706 RPN total loss: 0.02165 Total loss: 0.98623 timestamp: 1655036453.0373833 iteration: 36090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12399 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.19135 L1 loss: 0.0000e+00 L2 loss: 0.67068 Learning rate: 0.02 Mask loss: 0.18707 RPN box loss: 0.02026 RPN score loss: 0.00354 RPN total loss: 0.02381 Total loss: 1.0729 timestamp: 1655036456.3553293 iteration: 36095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14664 FastRCNN class loss: 0.0736 FastRCNN total loss: 0.22025 L1 loss: 0.0000e+00 L2 loss: 0.6706 Learning rate: 0.02 Mask loss: 0.23408 RPN box loss: 0.03668 RPN score loss: 0.00478 RPN total loss: 0.04146 Total loss: 1.16638 timestamp: 1655036459.6093645 iteration: 36100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1827 FastRCNN class loss: 0.09427 FastRCNN total loss: 0.27697 L1 loss: 0.0000e+00 L2 loss: 0.67049 Learning rate: 0.02 Mask loss: 0.17483 RPN box loss: 0.02665 RPN score loss: 0.00807 RPN total loss: 0.03471 Total loss: 1.15701 timestamp: 1655036462.9140708 iteration: 36105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19374 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.26014 L1 loss: 0.0000e+00 L2 loss: 0.67043 Learning rate: 0.02 Mask loss: 0.17399 RPN box loss: 0.07053 RPN score loss: 0.00753 RPN total loss: 0.07805 Total loss: 1.18261 timestamp: 1655036466.232548 iteration: 36110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.67034 Learning rate: 0.02 Mask loss: 0.09405 RPN box loss: 0.01182 RPN score loss: 0.00336 RPN total loss: 0.01518 Total loss: 0.95597 timestamp: 1655036469.511939 iteration: 36115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13198 FastRCNN class loss: 0.06365 FastRCNN total loss: 0.19563 L1 loss: 0.0000e+00 L2 loss: 0.67024 Learning rate: 0.02 Mask loss: 0.14469 RPN box loss: 0.04065 RPN score loss: 0.00584 RPN total loss: 0.04649 Total loss: 1.05705 timestamp: 1655036472.7550654 iteration: 36120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1466 FastRCNN class loss: 0.09194 FastRCNN total loss: 0.23854 L1 loss: 0.0000e+00 L2 loss: 0.67015 Learning rate: 0.02 Mask loss: 0.14015 RPN box loss: 0.04493 RPN score loss: 0.00671 RPN total loss: 0.05164 Total loss: 1.10048 timestamp: 1655036475.9628994 iteration: 36125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12883 FastRCNN class loss: 0.09582 FastRCNN total loss: 0.22465 L1 loss: 0.0000e+00 L2 loss: 0.67002 Learning rate: 0.02 Mask loss: 0.13709 RPN box loss: 0.03329 RPN score loss: 0.00698 RPN total loss: 0.04028 Total loss: 1.07203 timestamp: 1655036479.2244844 iteration: 36130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23495 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.33255 L1 loss: 0.0000e+00 L2 loss: 0.66993 Learning rate: 0.02 Mask loss: 0.17578 RPN box loss: 0.05895 RPN score loss: 0.00842 RPN total loss: 0.06737 Total loss: 1.24563 timestamp: 1655036482.4714108 iteration: 36135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10974 FastRCNN class loss: 0.08929 FastRCNN total loss: 0.19904 L1 loss: 0.0000e+00 L2 loss: 0.66986 Learning rate: 0.02 Mask loss: 0.1395 RPN box loss: 0.03049 RPN score loss: 0.00382 RPN total loss: 0.03431 Total loss: 1.04271 timestamp: 1655036485.7749887 iteration: 36140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10384 FastRCNN class loss: 0.09477 FastRCNN total loss: 0.19861 L1 loss: 0.0000e+00 L2 loss: 0.66975 Learning rate: 0.02 Mask loss: 0.10025 RPN box loss: 0.01671 RPN score loss: 0.0045 RPN total loss: 0.02121 Total loss: 0.98982 timestamp: 1655036489.1256514 iteration: 36145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15013 FastRCNN class loss: 0.0889 FastRCNN total loss: 0.23902 L1 loss: 0.0000e+00 L2 loss: 0.66966 Learning rate: 0.02 Mask loss: 0.14265 RPN box loss: 0.02578 RPN score loss: 0.00232 RPN total loss: 0.0281 Total loss: 1.07943 timestamp: 1655036492.4368515 iteration: 36150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09689 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.17185 L1 loss: 0.0000e+00 L2 loss: 0.66956 Learning rate: 0.02 Mask loss: 0.19124 RPN box loss: 0.01403 RPN score loss: 0.00914 RPN total loss: 0.02317 Total loss: 1.05582 timestamp: 1655036495.7532055 iteration: 36155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11737 FastRCNN class loss: 0.09195 FastRCNN total loss: 0.20932 L1 loss: 0.0000e+00 L2 loss: 0.66945 Learning rate: 0.02 Mask loss: 0.16568 RPN box loss: 0.02045 RPN score loss: 0.00411 RPN total loss: 0.02456 Total loss: 1.06901 timestamp: 1655036499.1508672 iteration: 36160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14936 FastRCNN class loss: 0.06882 FastRCNN total loss: 0.21819 L1 loss: 0.0000e+00 L2 loss: 0.66938 Learning rate: 0.02 Mask loss: 0.12721 RPN box loss: 0.00942 RPN score loss: 0.0058 RPN total loss: 0.01522 Total loss: 1.03 timestamp: 1655036502.4146266 iteration: 36165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10304 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.17531 L1 loss: 0.0000e+00 L2 loss: 0.66931 Learning rate: 0.02 Mask loss: 0.21385 RPN box loss: 0.06314 RPN score loss: 0.01162 RPN total loss: 0.07476 Total loss: 1.13322 timestamp: 1655036505.7650025 iteration: 36170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19994 FastRCNN class loss: 0.13175 FastRCNN total loss: 0.33169 L1 loss: 0.0000e+00 L2 loss: 0.66922 Learning rate: 0.02 Mask loss: 0.15187 RPN box loss: 0.03965 RPN score loss: 0.02044 RPN total loss: 0.06009 Total loss: 1.21287 timestamp: 1655036509.0193887 iteration: 36175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22116 FastRCNN class loss: 0.10964 FastRCNN total loss: 0.3308 L1 loss: 0.0000e+00 L2 loss: 0.66914 Learning rate: 0.02 Mask loss: 0.25409 RPN box loss: 0.04729 RPN score loss: 0.00932 RPN total loss: 0.05661 Total loss: 1.31063 timestamp: 1655036512.3264875 iteration: 36180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11634 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.19129 L1 loss: 0.0000e+00 L2 loss: 0.66903 Learning rate: 0.02 Mask loss: 0.1182 RPN box loss: 0.01487 RPN score loss: 0.00975 RPN total loss: 0.02462 Total loss: 1.00315 timestamp: 1655036515.6169102 iteration: 36185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1714 FastRCNN class loss: 0.1516 FastRCNN total loss: 0.323 L1 loss: 0.0000e+00 L2 loss: 0.66894 Learning rate: 0.02 Mask loss: 0.24065 RPN box loss: 0.05347 RPN score loss: 0.013 RPN total loss: 0.06647 Total loss: 1.29906 timestamp: 1655036518.860211 iteration: 36190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10997 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.18678 L1 loss: 0.0000e+00 L2 loss: 0.66885 Learning rate: 0.02 Mask loss: 0.20197 RPN box loss: 0.03488 RPN score loss: 0.01248 RPN total loss: 0.04736 Total loss: 1.10496 timestamp: 1655036522.1419597 iteration: 36195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0928 FastRCNN class loss: 0.04634 FastRCNN total loss: 0.13914 L1 loss: 0.0000e+00 L2 loss: 0.66878 Learning rate: 0.02 Mask loss: 0.13928 RPN box loss: 0.01755 RPN score loss: 0.00345 RPN total loss: 0.02101 Total loss: 0.96821 timestamp: 1655036525.441512 iteration: 36200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10096 FastRCNN class loss: 0.07005 FastRCNN total loss: 0.17101 L1 loss: 0.0000e+00 L2 loss: 0.66868 Learning rate: 0.02 Mask loss: 0.12289 RPN box loss: 0.0104 RPN score loss: 0.00196 RPN total loss: 0.01236 Total loss: 0.97494 timestamp: 1655036528.6753466 iteration: 36205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08805 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.1503 L1 loss: 0.0000e+00 L2 loss: 0.66858 Learning rate: 0.02 Mask loss: 0.13482 RPN box loss: 0.03772 RPN score loss: 0.00501 RPN total loss: 0.04273 Total loss: 0.99643 timestamp: 1655036531.9011884 iteration: 36210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09688 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.17181 L1 loss: 0.0000e+00 L2 loss: 0.66851 Learning rate: 0.02 Mask loss: 0.1566 RPN box loss: 0.02694 RPN score loss: 0.00897 RPN total loss: 0.0359 Total loss: 1.03283 timestamp: 1655036535.1434038 iteration: 36215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14648 FastRCNN class loss: 0.07288 FastRCNN total loss: 0.21936 L1 loss: 0.0000e+00 L2 loss: 0.66843 Learning rate: 0.02 Mask loss: 0.14182 RPN box loss: 0.07074 RPN score loss: 0.0083 RPN total loss: 0.07904 Total loss: 1.10865 timestamp: 1655036538.37451 iteration: 36220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12102 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.19458 L1 loss: 0.0000e+00 L2 loss: 0.66832 Learning rate: 0.02 Mask loss: 0.16344 RPN box loss: 0.06001 RPN score loss: 0.00735 RPN total loss: 0.06736 Total loss: 1.0937 timestamp: 1655036541.6623979 iteration: 36225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13324 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.19584 L1 loss: 0.0000e+00 L2 loss: 0.66823 Learning rate: 0.02 Mask loss: 0.13757 RPN box loss: 0.02295 RPN score loss: 0.01103 RPN total loss: 0.03398 Total loss: 1.03563 timestamp: 1655036544.9050193 iteration: 36230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18314 FastRCNN class loss: 0.11207 FastRCNN total loss: 0.29521 L1 loss: 0.0000e+00 L2 loss: 0.66815 Learning rate: 0.02 Mask loss: 0.24329 RPN box loss: 0.04723 RPN score loss: 0.01134 RPN total loss: 0.05857 Total loss: 1.26522 timestamp: 1655036548.1663883 iteration: 36235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1194 FastRCNN class loss: 0.09412 FastRCNN total loss: 0.21352 L1 loss: 0.0000e+00 L2 loss: 0.66805 Learning rate: 0.02 Mask loss: 0.18431 RPN box loss: 0.01608 RPN score loss: 0.00961 RPN total loss: 0.02569 Total loss: 1.09157 timestamp: 1655036551.4178097 iteration: 36240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1518 FastRCNN class loss: 0.11734 FastRCNN total loss: 0.26914 L1 loss: 0.0000e+00 L2 loss: 0.66797 Learning rate: 0.02 Mask loss: 0.16675 RPN box loss: 0.02706 RPN score loss: 0.0181 RPN total loss: 0.04516 Total loss: 1.14901 timestamp: 1655036554.6634018 iteration: 36245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15158 FastRCNN class loss: 0.04407 FastRCNN total loss: 0.19565 L1 loss: 0.0000e+00 L2 loss: 0.66786 Learning rate: 0.02 Mask loss: 0.11408 RPN box loss: 0.00795 RPN score loss: 0.00308 RPN total loss: 0.01102 Total loss: 0.98862 timestamp: 1655036557.972779 iteration: 36250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10676 FastRCNN class loss: 0.05423 FastRCNN total loss: 0.16098 L1 loss: 0.0000e+00 L2 loss: 0.66778 Learning rate: 0.02 Mask loss: 0.15258 RPN box loss: 0.01928 RPN score loss: 0.00136 RPN total loss: 0.02064 Total loss: 1.00198 timestamp: 1655036561.274007 iteration: 36255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17535 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.22833 L1 loss: 0.0000e+00 L2 loss: 0.66771 Learning rate: 0.02 Mask loss: 0.13255 RPN box loss: 0.03184 RPN score loss: 0.0066 RPN total loss: 0.03844 Total loss: 1.06702 timestamp: 1655036564.4929862 iteration: 36260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15538 FastRCNN class loss: 0.16598 FastRCNN total loss: 0.32136 L1 loss: 0.0000e+00 L2 loss: 0.66761 Learning rate: 0.02 Mask loss: 0.18179 RPN box loss: 0.05506 RPN score loss: 0.00737 RPN total loss: 0.06243 Total loss: 1.23319 timestamp: 1655036567.73036 iteration: 36265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15453 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.25202 L1 loss: 0.0000e+00 L2 loss: 0.66751 Learning rate: 0.02 Mask loss: 0.18097 RPN box loss: 0.03464 RPN score loss: 0.00746 RPN total loss: 0.04211 Total loss: 1.14261 timestamp: 1655036570.9861407 iteration: 36270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10359 FastRCNN class loss: 0.06123 FastRCNN total loss: 0.16482 L1 loss: 0.0000e+00 L2 loss: 0.66741 Learning rate: 0.02 Mask loss: 0.15085 RPN box loss: 0.04582 RPN score loss: 0.00628 RPN total loss: 0.0521 Total loss: 1.03519 timestamp: 1655036574.2314334 iteration: 36275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11546 FastRCNN class loss: 0.06547 FastRCNN total loss: 0.18092 L1 loss: 0.0000e+00 L2 loss: 0.66732 Learning rate: 0.02 Mask loss: 0.10587 RPN box loss: 0.03208 RPN score loss: 0.0025 RPN total loss: 0.03458 Total loss: 0.98869 timestamp: 1655036577.5087492 iteration: 36280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12857 FastRCNN class loss: 0.06103 FastRCNN total loss: 0.1896 L1 loss: 0.0000e+00 L2 loss: 0.66721 Learning rate: 0.02 Mask loss: 0.16292 RPN box loss: 0.00762 RPN score loss: 0.00345 RPN total loss: 0.01106 Total loss: 1.0308 timestamp: 1655036580.7848554 iteration: 36285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15807 FastRCNN class loss: 0.10004 FastRCNN total loss: 0.25811 L1 loss: 0.0000e+00 L2 loss: 0.66715 Learning rate: 0.02 Mask loss: 0.14636 RPN box loss: 0.01858 RPN score loss: 0.01103 RPN total loss: 0.02961 Total loss: 1.10123 timestamp: 1655036584.1069527 iteration: 36290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13731 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.66709 Learning rate: 0.02 Mask loss: 0.2602 RPN box loss: 0.06222 RPN score loss: 0.00749 RPN total loss: 0.06971 Total loss: 1.19599 timestamp: 1655036587.3572698 iteration: 36295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18497 FastRCNN class loss: 0.08691 FastRCNN total loss: 0.27188 L1 loss: 0.0000e+00 L2 loss: 0.66699 Learning rate: 0.02 Mask loss: 0.15691 RPN box loss: 0.05554 RPN score loss: 0.00771 RPN total loss: 0.06325 Total loss: 1.15903 timestamp: 1655036590.6760752 iteration: 36300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16982 FastRCNN class loss: 0.0905 FastRCNN total loss: 0.26033 L1 loss: 0.0000e+00 L2 loss: 0.66688 Learning rate: 0.02 Mask loss: 0.16923 RPN box loss: 0.05147 RPN score loss: 0.0059 RPN total loss: 0.05736 Total loss: 1.1538 timestamp: 1655036593.9638345 iteration: 36305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14631 FastRCNN class loss: 0.13395 FastRCNN total loss: 0.28026 L1 loss: 0.0000e+00 L2 loss: 0.66679 Learning rate: 0.02 Mask loss: 0.20128 RPN box loss: 0.05503 RPN score loss: 0.01152 RPN total loss: 0.06655 Total loss: 1.21488 timestamp: 1655036597.2448623 iteration: 36310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13354 FastRCNN class loss: 0.10849 FastRCNN total loss: 0.24203 L1 loss: 0.0000e+00 L2 loss: 0.6667 Learning rate: 0.02 Mask loss: 0.21621 RPN box loss: 0.05411 RPN score loss: 0.00815 RPN total loss: 0.06227 Total loss: 1.18721 timestamp: 1655036600.502501 iteration: 36315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13426 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.20605 L1 loss: 0.0000e+00 L2 loss: 0.66661 Learning rate: 0.02 Mask loss: 0.20416 RPN box loss: 0.0192 RPN score loss: 0.0064 RPN total loss: 0.02559 Total loss: 1.10241 timestamp: 1655036603.8756757 iteration: 36320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14919 FastRCNN class loss: 0.1234 FastRCNN total loss: 0.27259 L1 loss: 0.0000e+00 L2 loss: 0.66651 Learning rate: 0.02 Mask loss: 0.17567 RPN box loss: 0.0686 RPN score loss: 0.00408 RPN total loss: 0.07268 Total loss: 1.18745 timestamp: 1655036607.2240944 iteration: 36325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11898 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 0.66642 Learning rate: 0.02 Mask loss: 0.19074 RPN box loss: 0.04 RPN score loss: 0.00786 RPN total loss: 0.04786 Total loss: 1.09049 timestamp: 1655036610.5091684 iteration: 36330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15606 FastRCNN class loss: 0.09315 FastRCNN total loss: 0.24921 L1 loss: 0.0000e+00 L2 loss: 0.66635 Learning rate: 0.02 Mask loss: 0.19896 RPN box loss: 0.04463 RPN score loss: 0.00698 RPN total loss: 0.05162 Total loss: 1.16614 timestamp: 1655036613.8758156 iteration: 36335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.21499 L1 loss: 0.0000e+00 L2 loss: 0.66627 Learning rate: 0.02 Mask loss: 0.17029 RPN box loss: 0.06152 RPN score loss: 0.01362 RPN total loss: 0.07513 Total loss: 1.12668 timestamp: 1655036617.2033932 iteration: 36340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08492 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.14095 L1 loss: 0.0000e+00 L2 loss: 0.66616 Learning rate: 0.02 Mask loss: 0.16594 RPN box loss: 0.00946 RPN score loss: 0.00438 RPN total loss: 0.01383 Total loss: 0.98688 timestamp: 1655036620.4905715 iteration: 36345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16932 FastRCNN class loss: 0.10369 FastRCNN total loss: 0.27301 L1 loss: 0.0000e+00 L2 loss: 0.66608 Learning rate: 0.02 Mask loss: 0.16588 RPN box loss: 0.05157 RPN score loss: 0.00678 RPN total loss: 0.05835 Total loss: 1.16331 timestamp: 1655036623.7350812 iteration: 36350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11974 FastRCNN class loss: 0.08615 FastRCNN total loss: 0.20588 L1 loss: 0.0000e+00 L2 loss: 0.66598 Learning rate: 0.02 Mask loss: 0.16261 RPN box loss: 0.0605 RPN score loss: 0.00669 RPN total loss: 0.06719 Total loss: 1.10166 timestamp: 1655036626.98601 iteration: 36355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17406 FastRCNN class loss: 0.16632 FastRCNN total loss: 0.34038 L1 loss: 0.0000e+00 L2 loss: 0.66583 Learning rate: 0.02 Mask loss: 0.17242 RPN box loss: 0.03214 RPN score loss: 0.01727 RPN total loss: 0.04941 Total loss: 1.22804 timestamp: 1655036630.2234101 iteration: 36360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1632 FastRCNN class loss: 0.05854 FastRCNN total loss: 0.22174 L1 loss: 0.0000e+00 L2 loss: 0.66575 Learning rate: 0.02 Mask loss: 0.14055 RPN box loss: 0.03085 RPN score loss: 0.00548 RPN total loss: 0.03633 Total loss: 1.06436 timestamp: 1655036633.5121737 iteration: 36365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13527 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.19214 L1 loss: 0.0000e+00 L2 loss: 0.6657 Learning rate: 0.02 Mask loss: 0.16039 RPN box loss: 0.08209 RPN score loss: 0.01008 RPN total loss: 0.09216 Total loss: 1.1104 timestamp: 1655036636.7583313 iteration: 36370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14746 FastRCNN class loss: 0.11315 FastRCNN total loss: 0.26062 L1 loss: 0.0000e+00 L2 loss: 0.6656 Learning rate: 0.02 Mask loss: 0.1488 RPN box loss: 0.01157 RPN score loss: 0.00278 RPN total loss: 0.01434 Total loss: 1.08936 timestamp: 1655036640.0458784 iteration: 36375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14989 FastRCNN class loss: 0.05264 FastRCNN total loss: 0.20253 L1 loss: 0.0000e+00 L2 loss: 0.6655 Learning rate: 0.02 Mask loss: 0.11191 RPN box loss: 0.00802 RPN score loss: 0.00548 RPN total loss: 0.0135 Total loss: 0.99344 timestamp: 1655036643.371313 iteration: 36380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16219 FastRCNN class loss: 0.06179 FastRCNN total loss: 0.22398 L1 loss: 0.0000e+00 L2 loss: 0.66542 Learning rate: 0.02 Mask loss: 0.13257 RPN box loss: 0.04259 RPN score loss: 0.00623 RPN total loss: 0.04882 Total loss: 1.07078 timestamp: 1655036646.6545308 iteration: 36385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.06014 FastRCNN total loss: 0.16519 L1 loss: 0.0000e+00 L2 loss: 0.66535 Learning rate: 0.02 Mask loss: 0.19803 RPN box loss: 0.01109 RPN score loss: 0.00384 RPN total loss: 0.01493 Total loss: 1.04349 timestamp: 1655036649.881657 iteration: 36390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.14875 L1 loss: 0.0000e+00 L2 loss: 0.66525 Learning rate: 0.02 Mask loss: 0.16298 RPN box loss: 0.017 RPN score loss: 0.00396 RPN total loss: 0.02095 Total loss: 0.99793 timestamp: 1655036653.1307883 iteration: 36395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09443 FastRCNN class loss: 0.09222 FastRCNN total loss: 0.18665 L1 loss: 0.0000e+00 L2 loss: 0.66515 Learning rate: 0.02 Mask loss: 0.19872 RPN box loss: 0.01291 RPN score loss: 0.01597 RPN total loss: 0.02888 Total loss: 1.07939 timestamp: 1655036656.3797197 iteration: 36400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13753 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.20964 L1 loss: 0.0000e+00 L2 loss: 0.66504 Learning rate: 0.02 Mask loss: 0.17943 RPN box loss: 0.07376 RPN score loss: 0.0077 RPN total loss: 0.08147 Total loss: 1.13558 timestamp: 1655036659.6023107 iteration: 36405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12792 FastRCNN class loss: 0.11074 FastRCNN total loss: 0.23866 L1 loss: 0.0000e+00 L2 loss: 0.66493 Learning rate: 0.02 Mask loss: 0.20379 RPN box loss: 0.05181 RPN score loss: 0.01224 RPN total loss: 0.06405 Total loss: 1.17143 timestamp: 1655036662.8548672 iteration: 36410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.66486 Learning rate: 0.02 Mask loss: 0.15162 RPN box loss: 0.0429 RPN score loss: 0.00713 RPN total loss: 0.05003 Total loss: 1.03959 timestamp: 1655036666.1091177 iteration: 36415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13292 FastRCNN class loss: 0.08776 FastRCNN total loss: 0.22068 L1 loss: 0.0000e+00 L2 loss: 0.66478 Learning rate: 0.02 Mask loss: 0.22194 RPN box loss: 0.0408 RPN score loss: 0.0103 RPN total loss: 0.0511 Total loss: 1.15849 timestamp: 1655036669.4306812 iteration: 36420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08025 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.13999 L1 loss: 0.0000e+00 L2 loss: 0.66468 Learning rate: 0.02 Mask loss: 0.10992 RPN box loss: 0.0295 RPN score loss: 0.00818 RPN total loss: 0.03769 Total loss: 0.95229 timestamp: 1655036672.6721692 iteration: 36425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2266 FastRCNN class loss: 0.12385 FastRCNN total loss: 0.35045 L1 loss: 0.0000e+00 L2 loss: 0.66458 Learning rate: 0.02 Mask loss: 0.22897 RPN box loss: 0.02078 RPN score loss: 0.00483 RPN total loss: 0.02562 Total loss: 1.26961 timestamp: 1655036675.9563637 iteration: 36430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15938 FastRCNN class loss: 0.0954 FastRCNN total loss: 0.25478 L1 loss: 0.0000e+00 L2 loss: 0.66449 Learning rate: 0.02 Mask loss: 0.12954 RPN box loss: 0.01848 RPN score loss: 0.00513 RPN total loss: 0.02361 Total loss: 1.07243 timestamp: 1655036679.1880565 iteration: 36435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15985 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.2546 L1 loss: 0.0000e+00 L2 loss: 0.66439 Learning rate: 0.02 Mask loss: 0.19085 RPN box loss: 0.02201 RPN score loss: 0.00657 RPN total loss: 0.02858 Total loss: 1.13843 timestamp: 1655036682.4157093 iteration: 36440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13119 FastRCNN class loss: 0.0893 FastRCNN total loss: 0.22049 L1 loss: 0.0000e+00 L2 loss: 0.66432 Learning rate: 0.02 Mask loss: 0.16816 RPN box loss: 0.0488 RPN score loss: 0.01074 RPN total loss: 0.05954 Total loss: 1.11251 timestamp: 1655036685.667002 iteration: 36445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20418 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.29086 L1 loss: 0.0000e+00 L2 loss: 0.66423 Learning rate: 0.02 Mask loss: 0.18472 RPN box loss: 0.01512 RPN score loss: 0.00493 RPN total loss: 0.02005 Total loss: 1.15986 timestamp: 1655036688.8200514 iteration: 36450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19382 FastRCNN class loss: 0.14506 FastRCNN total loss: 0.33888 L1 loss: 0.0000e+00 L2 loss: 0.66413 Learning rate: 0.02 Mask loss: 0.2508 RPN box loss: 0.03369 RPN score loss: 0.0076 RPN total loss: 0.0413 Total loss: 1.2951 timestamp: 1655036692.0445328 iteration: 36455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10495 FastRCNN class loss: 0.09844 FastRCNN total loss: 0.20339 L1 loss: 0.0000e+00 L2 loss: 0.66403 Learning rate: 0.02 Mask loss: 0.18305 RPN box loss: 0.0273 RPN score loss: 0.00544 RPN total loss: 0.03273 Total loss: 1.08321 timestamp: 1655036695.3306215 iteration: 36460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20042 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.30575 L1 loss: 0.0000e+00 L2 loss: 0.66392 Learning rate: 0.02 Mask loss: 0.15666 RPN box loss: 0.03738 RPN score loss: 0.00832 RPN total loss: 0.0457 Total loss: 1.17203 timestamp: 1655036698.609315 iteration: 36465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21233 FastRCNN class loss: 0.10287 FastRCNN total loss: 0.3152 L1 loss: 0.0000e+00 L2 loss: 0.66382 Learning rate: 0.02 Mask loss: 0.24624 RPN box loss: 0.02923 RPN score loss: 0.00405 RPN total loss: 0.03329 Total loss: 1.25855 timestamp: 1655036701.8959012 iteration: 36470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.18867 L1 loss: 0.0000e+00 L2 loss: 0.66373 Learning rate: 0.02 Mask loss: 0.19211 RPN box loss: 0.01222 RPN score loss: 0.00214 RPN total loss: 0.01436 Total loss: 1.05888 timestamp: 1655036705.1671453 iteration: 36475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11202 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.66364 Learning rate: 0.02 Mask loss: 0.11368 RPN box loss: 0.05075 RPN score loss: 0.00751 RPN total loss: 0.05826 Total loss: 1.01199 timestamp: 1655036708.4539938 iteration: 36480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1911 FastRCNN class loss: 0.07078 FastRCNN total loss: 0.26189 L1 loss: 0.0000e+00 L2 loss: 0.66356 Learning rate: 0.02 Mask loss: 0.12449 RPN box loss: 0.00829 RPN score loss: 0.00272 RPN total loss: 0.01101 Total loss: 1.06095 timestamp: 1655036711.7133658 iteration: 36485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12102 FastRCNN class loss: 0.06674 FastRCNN total loss: 0.18776 L1 loss: 0.0000e+00 L2 loss: 0.66347 Learning rate: 0.02 Mask loss: 0.1445 RPN box loss: 0.0228 RPN score loss: 0.00308 RPN total loss: 0.02588 Total loss: 1.02162 timestamp: 1655036714.981581 iteration: 36490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14874 FastRCNN class loss: 0.09698 FastRCNN total loss: 0.24572 L1 loss: 0.0000e+00 L2 loss: 0.66339 Learning rate: 0.02 Mask loss: 0.17349 RPN box loss: 0.0518 RPN score loss: 0.01566 RPN total loss: 0.06746 Total loss: 1.15006 timestamp: 1655036718.2342966 iteration: 36495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18022 FastRCNN class loss: 0.08344 FastRCNN total loss: 0.26365 L1 loss: 0.0000e+00 L2 loss: 0.6633 Learning rate: 0.02 Mask loss: 0.13907 RPN box loss: 0.02446 RPN score loss: 0.00572 RPN total loss: 0.03018 Total loss: 1.0962 timestamp: 1655036721.4910007 iteration: 36500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11979 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.17784 L1 loss: 0.0000e+00 L2 loss: 0.66321 Learning rate: 0.02 Mask loss: 0.16384 RPN box loss: 0.03308 RPN score loss: 0.00675 RPN total loss: 0.03983 Total loss: 1.04473 timestamp: 1655036724.6816835 iteration: 36505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.17393 L1 loss: 0.0000e+00 L2 loss: 0.66311 Learning rate: 0.02 Mask loss: 0.19922 RPN box loss: 0.04863 RPN score loss: 0.01059 RPN total loss: 0.05922 Total loss: 1.09548 timestamp: 1655036727.972228 iteration: 36510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17988 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.26468 L1 loss: 0.0000e+00 L2 loss: 0.663 Learning rate: 0.02 Mask loss: 0.1191 RPN box loss: 0.01971 RPN score loss: 0.00958 RPN total loss: 0.02929 Total loss: 1.07607 timestamp: 1655036731.2774487 iteration: 36515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15379 FastRCNN class loss: 0.07754 FastRCNN total loss: 0.23133 L1 loss: 0.0000e+00 L2 loss: 0.66291 Learning rate: 0.02 Mask loss: 0.15586 RPN box loss: 0.01685 RPN score loss: 0.00493 RPN total loss: 0.02178 Total loss: 1.07188 timestamp: 1655036734.574964 iteration: 36520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16337 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.24711 L1 loss: 0.0000e+00 L2 loss: 0.66285 Learning rate: 0.02 Mask loss: 0.14462 RPN box loss: 0.01503 RPN score loss: 0.00343 RPN total loss: 0.01845 Total loss: 1.07304 timestamp: 1655036737.8318257 iteration: 36525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15325 FastRCNN class loss: 0.07607 FastRCNN total loss: 0.22932 L1 loss: 0.0000e+00 L2 loss: 0.66275 Learning rate: 0.02 Mask loss: 0.1924 RPN box loss: 0.01324 RPN score loss: 0.00222 RPN total loss: 0.01546 Total loss: 1.09993 timestamp: 1655036741.1116798 iteration: 36530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16177 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.24082 L1 loss: 0.0000e+00 L2 loss: 0.66268 Learning rate: 0.02 Mask loss: 0.16238 RPN box loss: 0.01657 RPN score loss: 0.01502 RPN total loss: 0.0316 Total loss: 1.09748 timestamp: 1655036744.407512 iteration: 36535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15856 FastRCNN class loss: 0.09738 FastRCNN total loss: 0.25595 L1 loss: 0.0000e+00 L2 loss: 0.6626 Learning rate: 0.02 Mask loss: 0.19057 RPN box loss: 0.0322 RPN score loss: 0.00705 RPN total loss: 0.03924 Total loss: 1.14836 timestamp: 1655036747.7287545 iteration: 36540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16078 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.22848 L1 loss: 0.0000e+00 L2 loss: 0.6625 Learning rate: 0.02 Mask loss: 0.20515 RPN box loss: 0.04179 RPN score loss: 0.01725 RPN total loss: 0.05904 Total loss: 1.15517 timestamp: 1655036750.994174 iteration: 36545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1785 FastRCNN class loss: 0.12519 FastRCNN total loss: 0.30369 L1 loss: 0.0000e+00 L2 loss: 0.66239 Learning rate: 0.02 Mask loss: 0.21017 RPN box loss: 0.09379 RPN score loss: 0.04298 RPN total loss: 0.13677 Total loss: 1.31303 timestamp: 1655036754.341489 iteration: 36550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08767 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.14069 L1 loss: 0.0000e+00 L2 loss: 0.66229 Learning rate: 0.02 Mask loss: 0.13926 RPN box loss: 0.05202 RPN score loss: 0.00467 RPN total loss: 0.05669 Total loss: 0.99893 timestamp: 1655036757.7358544 iteration: 36555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10757 FastRCNN class loss: 0.05494 FastRCNN total loss: 0.16251 L1 loss: 0.0000e+00 L2 loss: 0.6622 Learning rate: 0.02 Mask loss: 0.14103 RPN box loss: 0.01055 RPN score loss: 0.00227 RPN total loss: 0.01282 Total loss: 0.97856 timestamp: 1655036761.0481334 iteration: 36560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11797 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.17909 L1 loss: 0.0000e+00 L2 loss: 0.66214 Learning rate: 0.02 Mask loss: 0.14395 RPN box loss: 0.02344 RPN score loss: 0.00666 RPN total loss: 0.0301 Total loss: 1.01529 timestamp: 1655036764.3738923 iteration: 36565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08059 FastRCNN class loss: 0.06202 FastRCNN total loss: 0.1426 L1 loss: 0.0000e+00 L2 loss: 0.66205 Learning rate: 0.02 Mask loss: 0.13669 RPN box loss: 0.04977 RPN score loss: 0.00467 RPN total loss: 0.05444 Total loss: 0.99578 timestamp: 1655036767.6219926 iteration: 36570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.1542 L1 loss: 0.0000e+00 L2 loss: 0.66194 Learning rate: 0.02 Mask loss: 0.1389 RPN box loss: 0.01752 RPN score loss: 0.00498 RPN total loss: 0.0225 Total loss: 0.97753 timestamp: 1655036770.888801 iteration: 36575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08655 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.13616 L1 loss: 0.0000e+00 L2 loss: 0.66187 Learning rate: 0.02 Mask loss: 0.13585 RPN box loss: 0.02371 RPN score loss: 0.0019 RPN total loss: 0.0256 Total loss: 0.95948 timestamp: 1655036774.1685512 iteration: 36580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08592 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.13716 L1 loss: 0.0000e+00 L2 loss: 0.66177 Learning rate: 0.02 Mask loss: 0.1207 RPN box loss: 0.00613 RPN score loss: 0.00389 RPN total loss: 0.01002 Total loss: 0.92965 timestamp: 1655036777.5539615 iteration: 36585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16407 FastRCNN class loss: 0.11889 FastRCNN total loss: 0.28296 L1 loss: 0.0000e+00 L2 loss: 0.66167 Learning rate: 0.02 Mask loss: 0.14812 RPN box loss: 0.03193 RPN score loss: 0.00816 RPN total loss: 0.04009 Total loss: 1.13284 timestamp: 1655036780.807021 iteration: 36590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11107 FastRCNN class loss: 0.06334 FastRCNN total loss: 0.17441 L1 loss: 0.0000e+00 L2 loss: 0.66157 Learning rate: 0.02 Mask loss: 0.18522 RPN box loss: 0.0213 RPN score loss: 0.00412 RPN total loss: 0.02542 Total loss: 1.04662 timestamp: 1655036784.0872827 iteration: 36595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15517 FastRCNN class loss: 0.06933 FastRCNN total loss: 0.22451 L1 loss: 0.0000e+00 L2 loss: 0.66149 Learning rate: 0.02 Mask loss: 0.16549 RPN box loss: 0.03041 RPN score loss: 0.00641 RPN total loss: 0.03683 Total loss: 1.08832 timestamp: 1655036787.3898358 iteration: 36600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14992 FastRCNN class loss: 0.09976 FastRCNN total loss: 0.24968 L1 loss: 0.0000e+00 L2 loss: 0.6614 Learning rate: 0.02 Mask loss: 0.16065 RPN box loss: 0.0668 RPN score loss: 0.0232 RPN total loss: 0.09 Total loss: 1.16173 timestamp: 1655036790.5908449 iteration: 36605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0805 FastRCNN class loss: 0.05479 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.6613 Learning rate: 0.02 Mask loss: 0.12797 RPN box loss: 0.01348 RPN score loss: 0.00518 RPN total loss: 0.01867 Total loss: 0.94323 timestamp: 1655036793.830776 iteration: 36610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2062 FastRCNN class loss: 0.1114 FastRCNN total loss: 0.31761 L1 loss: 0.0000e+00 L2 loss: 0.6612 Learning rate: 0.02 Mask loss: 0.1636 RPN box loss: 0.04875 RPN score loss: 0.00375 RPN total loss: 0.0525 Total loss: 1.1949 timestamp: 1655036797.1110232 iteration: 36615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11064 FastRCNN class loss: 0.12679 FastRCNN total loss: 0.23743 L1 loss: 0.0000e+00 L2 loss: 0.6611 Learning rate: 0.02 Mask loss: 0.17118 RPN box loss: 0.04595 RPN score loss: 0.02141 RPN total loss: 0.06736 Total loss: 1.13707 timestamp: 1655036800.3740578 iteration: 36620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16454 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.22526 L1 loss: 0.0000e+00 L2 loss: 0.66102 Learning rate: 0.02 Mask loss: 0.13188 RPN box loss: 0.07804 RPN score loss: 0.0053 RPN total loss: 0.08334 Total loss: 1.10151 timestamp: 1655036803.6838508 iteration: 36625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12871 FastRCNN class loss: 0.07654 FastRCNN total loss: 0.20524 L1 loss: 0.0000e+00 L2 loss: 0.66094 Learning rate: 0.02 Mask loss: 0.20523 RPN box loss: 0.07604 RPN score loss: 0.01074 RPN total loss: 0.08678 Total loss: 1.15819 timestamp: 1655036806.9460337 iteration: 36630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09979 FastRCNN class loss: 0.05967 FastRCNN total loss: 0.15946 L1 loss: 0.0000e+00 L2 loss: 0.66084 Learning rate: 0.02 Mask loss: 0.24401 RPN box loss: 0.03425 RPN score loss: 0.00202 RPN total loss: 0.03627 Total loss: 1.10059 timestamp: 1655036810.2612045 iteration: 36635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08866 FastRCNN class loss: 0.04362 FastRCNN total loss: 0.13229 L1 loss: 0.0000e+00 L2 loss: 0.66078 Learning rate: 0.02 Mask loss: 0.08732 RPN box loss: 0.03727 RPN score loss: 0.00829 RPN total loss: 0.04555 Total loss: 0.92594 timestamp: 1655036813.6251097 iteration: 36640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14374 FastRCNN class loss: 0.10558 FastRCNN total loss: 0.24932 L1 loss: 0.0000e+00 L2 loss: 0.6607 Learning rate: 0.02 Mask loss: 0.19061 RPN box loss: 0.06819 RPN score loss: 0.0156 RPN total loss: 0.0838 Total loss: 1.18443 timestamp: 1655036816.9077525 iteration: 36645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16562 FastRCNN class loss: 0.12155 FastRCNN total loss: 0.28717 L1 loss: 0.0000e+00 L2 loss: 0.66058 Learning rate: 0.02 Mask loss: 0.17671 RPN box loss: 0.05094 RPN score loss: 0.01547 RPN total loss: 0.06642 Total loss: 1.19087 timestamp: 1655036820.1896327 iteration: 36650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25143 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.33378 L1 loss: 0.0000e+00 L2 loss: 0.66048 Learning rate: 0.02 Mask loss: 0.13167 RPN box loss: 0.05241 RPN score loss: 0.01604 RPN total loss: 0.06845 Total loss: 1.19438 timestamp: 1655036823.5136185 iteration: 36655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14518 FastRCNN class loss: 0.09048 FastRCNN total loss: 0.23565 L1 loss: 0.0000e+00 L2 loss: 0.66039 Learning rate: 0.02 Mask loss: 0.14785 RPN box loss: 0.02694 RPN score loss: 0.0092 RPN total loss: 0.03613 Total loss: 1.08002 timestamp: 1655036826.8166997 iteration: 36660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12902 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.18727 L1 loss: 0.0000e+00 L2 loss: 0.66032 Learning rate: 0.02 Mask loss: 0.13745 RPN box loss: 0.03514 RPN score loss: 0.00264 RPN total loss: 0.03779 Total loss: 1.02282 timestamp: 1655036830.0790272 iteration: 36665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12859 FastRCNN class loss: 0.09031 FastRCNN total loss: 0.2189 L1 loss: 0.0000e+00 L2 loss: 0.6602 Learning rate: 0.02 Mask loss: 0.18644 RPN box loss: 0.00873 RPN score loss: 0.00226 RPN total loss: 0.011 Total loss: 1.07654 timestamp: 1655036833.3382773 iteration: 36670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19297 FastRCNN class loss: 0.11825 FastRCNN total loss: 0.31122 L1 loss: 0.0000e+00 L2 loss: 0.6601 Learning rate: 0.02 Mask loss: 0.23766 RPN box loss: 0.02076 RPN score loss: 0.00331 RPN total loss: 0.02406 Total loss: 1.23304 timestamp: 1655036836.6335638 iteration: 36675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20231 FastRCNN class loss: 0.12647 FastRCNN total loss: 0.32878 L1 loss: 0.0000e+00 L2 loss: 0.66002 Learning rate: 0.02 Mask loss: 0.16906 RPN box loss: 0.01877 RPN score loss: 0.00628 RPN total loss: 0.02504 Total loss: 1.18291 timestamp: 1655036839.8415408 iteration: 36680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13247 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.18816 L1 loss: 0.0000e+00 L2 loss: 0.65996 Learning rate: 0.02 Mask loss: 0.15232 RPN box loss: 0.01718 RPN score loss: 0.00815 RPN total loss: 0.02534 Total loss: 1.02577 timestamp: 1655036843.1060588 iteration: 36685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.098 FastRCNN total loss: 0.23925 L1 loss: 0.0000e+00 L2 loss: 0.65988 Learning rate: 0.02 Mask loss: 0.21258 RPN box loss: 0.02859 RPN score loss: 0.0087 RPN total loss: 0.0373 Total loss: 1.14901 timestamp: 1655036846.4503453 iteration: 36690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18007 FastRCNN class loss: 0.09444 FastRCNN total loss: 0.27451 L1 loss: 0.0000e+00 L2 loss: 0.6598 Learning rate: 0.02 Mask loss: 0.11491 RPN box loss: 0.06355 RPN score loss: 0.00897 RPN total loss: 0.07252 Total loss: 1.12174 timestamp: 1655036849.730289 iteration: 36695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17691 FastRCNN class loss: 0.09197 FastRCNN total loss: 0.26888 L1 loss: 0.0000e+00 L2 loss: 0.65968 Learning rate: 0.02 Mask loss: 0.29182 RPN box loss: 0.02803 RPN score loss: 0.00954 RPN total loss: 0.03758 Total loss: 1.25795 timestamp: 1655036853.0054247 iteration: 36700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06431 FastRCNN class loss: 0.08614 FastRCNN total loss: 0.15045 L1 loss: 0.0000e+00 L2 loss: 0.65956 Learning rate: 0.02 Mask loss: 0.16321 RPN box loss: 0.02848 RPN score loss: 0.0037 RPN total loss: 0.03217 Total loss: 1.00539 timestamp: 1655036856.2720077 iteration: 36705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1286 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.21774 L1 loss: 0.0000e+00 L2 loss: 0.65945 Learning rate: 0.02 Mask loss: 0.11273 RPN box loss: 0.01537 RPN score loss: 0.00485 RPN total loss: 0.02022 Total loss: 1.01013 timestamp: 1655036859.5827281 iteration: 36710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.13691 L1 loss: 0.0000e+00 L2 loss: 0.65936 Learning rate: 0.02 Mask loss: 0.17359 RPN box loss: 0.17975 RPN score loss: 0.01023 RPN total loss: 0.18998 Total loss: 1.15982 timestamp: 1655036862.8437412 iteration: 36715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12494 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.20493 L1 loss: 0.0000e+00 L2 loss: 0.65928 Learning rate: 0.02 Mask loss: 0.16521 RPN box loss: 0.04117 RPN score loss: 0.00593 RPN total loss: 0.0471 Total loss: 1.07652 timestamp: 1655036866.1489086 iteration: 36720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12464 FastRCNN class loss: 0.10323 FastRCNN total loss: 0.22787 L1 loss: 0.0000e+00 L2 loss: 0.6592 Learning rate: 0.02 Mask loss: 0.15323 RPN box loss: 0.09531 RPN score loss: 0.00418 RPN total loss: 0.09949 Total loss: 1.13979 timestamp: 1655036869.4333851 iteration: 36725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15304 FastRCNN class loss: 0.10335 FastRCNN total loss: 0.25639 L1 loss: 0.0000e+00 L2 loss: 0.65909 Learning rate: 0.02 Mask loss: 0.19884 RPN box loss: 0.03016 RPN score loss: 0.00664 RPN total loss: 0.0368 Total loss: 1.15112 timestamp: 1655036872.7135477 iteration: 36730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21225 FastRCNN class loss: 0.14461 FastRCNN total loss: 0.35686 L1 loss: 0.0000e+00 L2 loss: 0.659 Learning rate: 0.02 Mask loss: 0.24922 RPN box loss: 0.046 RPN score loss: 0.0191 RPN total loss: 0.0651 Total loss: 1.33018 timestamp: 1655036875.9843996 iteration: 36735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14188 FastRCNN class loss: 0.07097 FastRCNN total loss: 0.21285 L1 loss: 0.0000e+00 L2 loss: 0.65894 Learning rate: 0.02 Mask loss: 0.09414 RPN box loss: 0.05086 RPN score loss: 0.00607 RPN total loss: 0.05693 Total loss: 1.02286 timestamp: 1655036879.3153791 iteration: 36740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.20381 L1 loss: 0.0000e+00 L2 loss: 0.65888 Learning rate: 0.02 Mask loss: 0.27889 RPN box loss: 0.02394 RPN score loss: 0.01727 RPN total loss: 0.04121 Total loss: 1.18278 timestamp: 1655036882.5854862 iteration: 36745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14694 FastRCNN class loss: 0.05613 FastRCNN total loss: 0.20308 L1 loss: 0.0000e+00 L2 loss: 0.65877 Learning rate: 0.02 Mask loss: 0.10522 RPN box loss: 0.03739 RPN score loss: 0.00475 RPN total loss: 0.04214 Total loss: 1.0092 timestamp: 1655036885.904523 iteration: 36750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2054 FastRCNN class loss: 0.12134 FastRCNN total loss: 0.32674 L1 loss: 0.0000e+00 L2 loss: 0.65865 Learning rate: 0.02 Mask loss: 0.16569 RPN box loss: 0.01264 RPN score loss: 0.00338 RPN total loss: 0.01602 Total loss: 1.1671 timestamp: 1655036889.1671076 iteration: 36755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13085 FastRCNN class loss: 0.10571 FastRCNN total loss: 0.23656 L1 loss: 0.0000e+00 L2 loss: 0.65857 Learning rate: 0.02 Mask loss: 0.15935 RPN box loss: 0.01815 RPN score loss: 0.0174 RPN total loss: 0.03555 Total loss: 1.09003 timestamp: 1655036892.4439807 iteration: 36760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11409 FastRCNN class loss: 0.04539 FastRCNN total loss: 0.15948 L1 loss: 0.0000e+00 L2 loss: 0.65847 Learning rate: 0.02 Mask loss: 0.12241 RPN box loss: 0.04003 RPN score loss: 0.00451 RPN total loss: 0.04454 Total loss: 0.98491 timestamp: 1655036895.6853147 iteration: 36765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.06653 FastRCNN total loss: 0.18012 L1 loss: 0.0000e+00 L2 loss: 0.65837 Learning rate: 0.02 Mask loss: 0.13314 RPN box loss: 0.03378 RPN score loss: 0.00743 RPN total loss: 0.0412 Total loss: 1.01284 timestamp: 1655036898.983843 iteration: 36770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14932 FastRCNN class loss: 0.08142 FastRCNN total loss: 0.23074 L1 loss: 0.0000e+00 L2 loss: 0.65828 Learning rate: 0.02 Mask loss: 0.14635 RPN box loss: 0.03322 RPN score loss: 0.00753 RPN total loss: 0.04075 Total loss: 1.07611 timestamp: 1655036902.278801 iteration: 36775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12673 FastRCNN class loss: 0.09156 FastRCNN total loss: 0.21829 L1 loss: 0.0000e+00 L2 loss: 0.6582 Learning rate: 0.02 Mask loss: 0.16252 RPN box loss: 0.01617 RPN score loss: 0.00437 RPN total loss: 0.02054 Total loss: 1.05955 timestamp: 1655036905.6460714 iteration: 36780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0526 FastRCNN class loss: 0.04757 FastRCNN total loss: 0.10017 L1 loss: 0.0000e+00 L2 loss: 0.65811 Learning rate: 0.02 Mask loss: 0.23701 RPN box loss: 0.02288 RPN score loss: 0.00354 RPN total loss: 0.02642 Total loss: 1.02172 timestamp: 1655036908.8673823 iteration: 36785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08721 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.16914 L1 loss: 0.0000e+00 L2 loss: 0.65804 Learning rate: 0.02 Mask loss: 0.0917 RPN box loss: 0.0185 RPN score loss: 0.00327 RPN total loss: 0.02178 Total loss: 0.94065 timestamp: 1655036912.2053266 iteration: 36790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1131 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.17253 L1 loss: 0.0000e+00 L2 loss: 0.65797 Learning rate: 0.02 Mask loss: 0.12572 RPN box loss: 0.01695 RPN score loss: 0.0053 RPN total loss: 0.02225 Total loss: 0.97846 timestamp: 1655036915.4681282 iteration: 36795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14701 FastRCNN class loss: 0.09802 FastRCNN total loss: 0.24503 L1 loss: 0.0000e+00 L2 loss: 0.65786 Learning rate: 0.02 Mask loss: 0.13241 RPN box loss: 0.04276 RPN score loss: 0.00893 RPN total loss: 0.05169 Total loss: 1.087 timestamp: 1655036918.7309275 iteration: 36800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12132 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.17666 L1 loss: 0.0000e+00 L2 loss: 0.65778 Learning rate: 0.02 Mask loss: 0.19644 RPN box loss: 0.03281 RPN score loss: 0.0036 RPN total loss: 0.03641 Total loss: 1.06729 timestamp: 1655036922.0187635 iteration: 36805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10958 FastRCNN class loss: 0.07204 FastRCNN total loss: 0.18162 L1 loss: 0.0000e+00 L2 loss: 0.65769 Learning rate: 0.02 Mask loss: 0.1667 RPN box loss: 0.01608 RPN score loss: 0.00799 RPN total loss: 0.02407 Total loss: 1.03009 timestamp: 1655036925.40266 iteration: 36810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06996 FastRCNN class loss: 0.0505 FastRCNN total loss: 0.12045 L1 loss: 0.0000e+00 L2 loss: 0.6576 Learning rate: 0.02 Mask loss: 0.1776 RPN box loss: 0.0286 RPN score loss: 0.0013 RPN total loss: 0.02991 Total loss: 0.98557 timestamp: 1655036928.7382565 iteration: 36815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.11357 FastRCNN total loss: 0.22286 L1 loss: 0.0000e+00 L2 loss: 0.65749 Learning rate: 0.02 Mask loss: 0.20261 RPN box loss: 0.03135 RPN score loss: 0.00653 RPN total loss: 0.03788 Total loss: 1.12084 timestamp: 1655036932.0161288 iteration: 36820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15136 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.20669 L1 loss: 0.0000e+00 L2 loss: 0.65742 Learning rate: 0.02 Mask loss: 0.11603 RPN box loss: 0.01512 RPN score loss: 0.00606 RPN total loss: 0.02118 Total loss: 1.00132 timestamp: 1655036935.3547554 iteration: 36825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13969 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.22449 L1 loss: 0.0000e+00 L2 loss: 0.65735 Learning rate: 0.02 Mask loss: 0.16755 RPN box loss: 0.03801 RPN score loss: 0.00307 RPN total loss: 0.04108 Total loss: 1.09046 timestamp: 1655036938.6565158 iteration: 36830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13145 FastRCNN class loss: 0.10118 FastRCNN total loss: 0.23263 L1 loss: 0.0000e+00 L2 loss: 0.65723 Learning rate: 0.02 Mask loss: 0.11178 RPN box loss: 0.03003 RPN score loss: 0.00871 RPN total loss: 0.03874 Total loss: 1.04039 timestamp: 1655036941.891821 iteration: 36835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13648 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.20687 L1 loss: 0.0000e+00 L2 loss: 0.65715 Learning rate: 0.02 Mask loss: 0.12092 RPN box loss: 0.04469 RPN score loss: 0.00865 RPN total loss: 0.05333 Total loss: 1.03827 timestamp: 1655036945.1627688 iteration: 36840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08318 FastRCNN class loss: 0.08203 FastRCNN total loss: 0.16522 L1 loss: 0.0000e+00 L2 loss: 0.65705 Learning rate: 0.02 Mask loss: 0.17937 RPN box loss: 0.0362 RPN score loss: 0.00363 RPN total loss: 0.03983 Total loss: 1.04148 timestamp: 1655036948.465106 iteration: 36845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14098 FastRCNN class loss: 0.08257 FastRCNN total loss: 0.22355 L1 loss: 0.0000e+00 L2 loss: 0.65694 Learning rate: 0.02 Mask loss: 0.13426 RPN box loss: 0.0218 RPN score loss: 0.00562 RPN total loss: 0.02742 Total loss: 1.04218 timestamp: 1655036951.7599475 iteration: 36850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14186 FastRCNN class loss: 0.06392 FastRCNN total loss: 0.20577 L1 loss: 0.0000e+00 L2 loss: 0.65684 Learning rate: 0.02 Mask loss: 0.14643 RPN box loss: 0.0098 RPN score loss: 0.00337 RPN total loss: 0.01317 Total loss: 1.02222 timestamp: 1655036955.0299814 iteration: 36855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10062 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.15486 L1 loss: 0.0000e+00 L2 loss: 0.65676 Learning rate: 0.02 Mask loss: 0.2262 RPN box loss: 0.01304 RPN score loss: 0.0051 RPN total loss: 0.01813 Total loss: 1.05595 timestamp: 1655036958.3370621 iteration: 36860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09626 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.1589 L1 loss: 0.0000e+00 L2 loss: 0.65665 Learning rate: 0.02 Mask loss: 0.13071 RPN box loss: 0.02074 RPN score loss: 0.00155 RPN total loss: 0.02229 Total loss: 0.96855 timestamp: 1655036961.5533955 iteration: 36865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19403 FastRCNN class loss: 0.0984 FastRCNN total loss: 0.29243 L1 loss: 0.0000e+00 L2 loss: 0.65656 Learning rate: 0.02 Mask loss: 0.2184 RPN box loss: 0.01645 RPN score loss: 0.01189 RPN total loss: 0.02834 Total loss: 1.19573 timestamp: 1655036964.875529 iteration: 36870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1249 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.18708 L1 loss: 0.0000e+00 L2 loss: 0.6565 Learning rate: 0.02 Mask loss: 0.17055 RPN box loss: 0.01336 RPN score loss: 0.00946 RPN total loss: 0.02282 Total loss: 1.03695 timestamp: 1655036968.1677265 iteration: 36875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13623 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.19747 L1 loss: 0.0000e+00 L2 loss: 0.65641 Learning rate: 0.02 Mask loss: 0.13547 RPN box loss: 0.03898 RPN score loss: 0.00347 RPN total loss: 0.04245 Total loss: 1.03179 timestamp: 1655036971.480412 iteration: 36880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13627 FastRCNN class loss: 0.08766 FastRCNN total loss: 0.22392 L1 loss: 0.0000e+00 L2 loss: 0.65631 Learning rate: 0.02 Mask loss: 0.12223 RPN box loss: 0.04226 RPN score loss: 0.01101 RPN total loss: 0.05326 Total loss: 1.05573 timestamp: 1655036974.7387893 iteration: 36885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.04026 FastRCNN total loss: 0.11061 L1 loss: 0.0000e+00 L2 loss: 0.65624 Learning rate: 0.02 Mask loss: 0.12107 RPN box loss: 0.03031 RPN score loss: 0.00588 RPN total loss: 0.03619 Total loss: 0.9241 timestamp: 1655036977.9810407 iteration: 36890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13962 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.22094 L1 loss: 0.0000e+00 L2 loss: 0.65616 Learning rate: 0.02 Mask loss: 0.16983 RPN box loss: 0.01977 RPN score loss: 0.0112 RPN total loss: 0.03097 Total loss: 1.0779 timestamp: 1655036981.279791 iteration: 36895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.08827 FastRCNN total loss: 0.19794 L1 loss: 0.0000e+00 L2 loss: 0.65606 Learning rate: 0.02 Mask loss: 0.19293 RPN box loss: 0.05233 RPN score loss: 0.00947 RPN total loss: 0.06181 Total loss: 1.10874 timestamp: 1655036984.5569508 iteration: 36900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15854 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.23572 L1 loss: 0.0000e+00 L2 loss: 0.65597 Learning rate: 0.02 Mask loss: 0.16642 RPN box loss: 0.04223 RPN score loss: 0.01596 RPN total loss: 0.0582 Total loss: 1.1163 timestamp: 1655036987.8645546 iteration: 36905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09691 FastRCNN class loss: 0.07236 FastRCNN total loss: 0.16927 L1 loss: 0.0000e+00 L2 loss: 0.6559 Learning rate: 0.02 Mask loss: 0.11766 RPN box loss: 0.02168 RPN score loss: 0.00502 RPN total loss: 0.0267 Total loss: 0.96953 timestamp: 1655036991.1129994 iteration: 36910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14021 FastRCNN class loss: 0.09523 FastRCNN total loss: 0.23545 L1 loss: 0.0000e+00 L2 loss: 0.65579 Learning rate: 0.02 Mask loss: 0.13448 RPN box loss: 0.01067 RPN score loss: 0.00272 RPN total loss: 0.01339 Total loss: 1.03911 timestamp: 1655036994.311338 iteration: 36915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21344 FastRCNN class loss: 0.11154 FastRCNN total loss: 0.32498 L1 loss: 0.0000e+00 L2 loss: 0.65572 Learning rate: 0.02 Mask loss: 0.20794 RPN box loss: 0.05959 RPN score loss: 0.01853 RPN total loss: 0.07811 Total loss: 1.26675 timestamp: 1655036997.6052177 iteration: 36920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09253 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.14993 L1 loss: 0.0000e+00 L2 loss: 0.65564 Learning rate: 0.02 Mask loss: 0.13874 RPN box loss: 0.01514 RPN score loss: 0.01094 RPN total loss: 0.02608 Total loss: 0.97038 timestamp: 1655037000.91616 iteration: 36925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11333 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.17401 L1 loss: 0.0000e+00 L2 loss: 0.65555 Learning rate: 0.02 Mask loss: 0.18821 RPN box loss: 0.01782 RPN score loss: 0.00409 RPN total loss: 0.02191 Total loss: 1.03967 timestamp: 1655037004.1748655 iteration: 36930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17174 FastRCNN class loss: 0.11588 FastRCNN total loss: 0.28762 L1 loss: 0.0000e+00 L2 loss: 0.65547 Learning rate: 0.02 Mask loss: 0.22343 RPN box loss: 0.03386 RPN score loss: 0.00667 RPN total loss: 0.04053 Total loss: 1.20705 timestamp: 1655037007.493405 iteration: 36935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.04933 FastRCNN total loss: 0.16436 L1 loss: 0.0000e+00 L2 loss: 0.65539 Learning rate: 0.02 Mask loss: 0.10746 RPN box loss: 0.03395 RPN score loss: 0.00368 RPN total loss: 0.03763 Total loss: 0.96483 timestamp: 1655037010.701683 iteration: 36940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13169 FastRCNN class loss: 0.07559 FastRCNN total loss: 0.20728 L1 loss: 0.0000e+00 L2 loss: 0.6553 Learning rate: 0.02 Mask loss: 0.19552 RPN box loss: 0.06178 RPN score loss: 0.00951 RPN total loss: 0.07129 Total loss: 1.1294 timestamp: 1655037013.916771 iteration: 36945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12682 FastRCNN class loss: 0.10941 FastRCNN total loss: 0.23622 L1 loss: 0.0000e+00 L2 loss: 0.6552 Learning rate: 0.02 Mask loss: 0.19272 RPN box loss: 0.04037 RPN score loss: 0.00988 RPN total loss: 0.05025 Total loss: 1.13438 timestamp: 1655037017.1812892 iteration: 36950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13668 FastRCNN class loss: 0.09733 FastRCNN total loss: 0.23401 L1 loss: 0.0000e+00 L2 loss: 0.65514 Learning rate: 0.02 Mask loss: 0.20979 RPN box loss: 0.03544 RPN score loss: 0.00421 RPN total loss: 0.03965 Total loss: 1.13858 timestamp: 1655037020.4491436 iteration: 36955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09606 FastRCNN class loss: 0.0866 FastRCNN total loss: 0.18267 L1 loss: 0.0000e+00 L2 loss: 0.65506 Learning rate: 0.02 Mask loss: 0.14233 RPN box loss: 0.01275 RPN score loss: 0.00832 RPN total loss: 0.02107 Total loss: 1.00113 timestamp: 1655037023.727868 iteration: 36960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24463 FastRCNN class loss: 0.08883 FastRCNN total loss: 0.33346 L1 loss: 0.0000e+00 L2 loss: 0.65495 Learning rate: 0.02 Mask loss: 0.12975 RPN box loss: 0.04374 RPN score loss: 0.00956 RPN total loss: 0.0533 Total loss: 1.17147 timestamp: 1655037026.9778366 iteration: 36965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17842 FastRCNN class loss: 0.12127 FastRCNN total loss: 0.29969 L1 loss: 0.0000e+00 L2 loss: 0.65487 Learning rate: 0.02 Mask loss: 0.16533 RPN box loss: 0.04118 RPN score loss: 0.01085 RPN total loss: 0.05203 Total loss: 1.17192 timestamp: 1655037030.2236192 iteration: 36970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14889 FastRCNN class loss: 0.13037 FastRCNN total loss: 0.27926 L1 loss: 0.0000e+00 L2 loss: 0.65478 Learning rate: 0.02 Mask loss: 0.17377 RPN box loss: 0.02058 RPN score loss: 0.00461 RPN total loss: 0.02519 Total loss: 1.133 timestamp: 1655037033.5064816 iteration: 36975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09667 FastRCNN class loss: 0.08901 FastRCNN total loss: 0.18568 L1 loss: 0.0000e+00 L2 loss: 0.65469 Learning rate: 0.02 Mask loss: 0.17425 RPN box loss: 0.05141 RPN score loss: 0.00615 RPN total loss: 0.05756 Total loss: 1.07219 timestamp: 1655037036.842462 iteration: 36980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1086 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.17953 L1 loss: 0.0000e+00 L2 loss: 0.65462 Learning rate: 0.02 Mask loss: 0.15629 RPN box loss: 0.02323 RPN score loss: 0.01029 RPN total loss: 0.03352 Total loss: 1.02396 timestamp: 1655037040.043711 iteration: 36985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.0634 FastRCNN total loss: 0.17823 L1 loss: 0.0000e+00 L2 loss: 0.65452 Learning rate: 0.02 Mask loss: 0.15885 RPN box loss: 0.01536 RPN score loss: 0.00579 RPN total loss: 0.02114 Total loss: 1.01275 timestamp: 1655037043.3312714 iteration: 36990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10887 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.17338 L1 loss: 0.0000e+00 L2 loss: 0.65443 Learning rate: 0.02 Mask loss: 0.13464 RPN box loss: 0.03166 RPN score loss: 0.0064 RPN total loss: 0.03807 Total loss: 1.00051 timestamp: 1655037046.6535811 iteration: 36995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20191 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.26643 L1 loss: 0.0000e+00 L2 loss: 0.65434 Learning rate: 0.02 Mask loss: 0.16598 RPN box loss: 0.02914 RPN score loss: 0.00629 RPN total loss: 0.03544 Total loss: 1.1222 timestamp: 1655037049.880805 iteration: 37000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1658 FastRCNN class loss: 0.10538 FastRCNN total loss: 0.27118 L1 loss: 0.0000e+00 L2 loss: 0.65425 Learning rate: 0.02 Mask loss: 0.15886 RPN box loss: 0.02386 RPN score loss: 0.00648 RPN total loss: 0.03034 Total loss: 1.11464 timestamp: 1655037053.163076 iteration: 37005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08869 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.16003 L1 loss: 0.0000e+00 L2 loss: 0.6542 Learning rate: 0.02 Mask loss: 0.12052 RPN box loss: 0.03734 RPN score loss: 0.00327 RPN total loss: 0.04061 Total loss: 0.97536 timestamp: 1655037056.3832967 iteration: 37010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07631 FastRCNN class loss: 0.07768 FastRCNN total loss: 0.154 L1 loss: 0.0000e+00 L2 loss: 0.65411 Learning rate: 0.02 Mask loss: 0.13027 RPN box loss: 0.04284 RPN score loss: 0.00345 RPN total loss: 0.04629 Total loss: 0.98467 timestamp: 1655037059.6707933 iteration: 37015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1388 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.19981 L1 loss: 0.0000e+00 L2 loss: 0.65401 Learning rate: 0.02 Mask loss: 0.10027 RPN box loss: 0.03505 RPN score loss: 0.00892 RPN total loss: 0.04398 Total loss: 0.99806 timestamp: 1655037062.8899224 iteration: 37020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07658 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.1195 L1 loss: 0.0000e+00 L2 loss: 0.65393 Learning rate: 0.02 Mask loss: 0.13617 RPN box loss: 0.03865 RPN score loss: 0.00472 RPN total loss: 0.04337 Total loss: 0.95298 timestamp: 1655037066.2182348 iteration: 37025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15015 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.21034 L1 loss: 0.0000e+00 L2 loss: 0.65384 Learning rate: 0.02 Mask loss: 0.08516 RPN box loss: 0.01254 RPN score loss: 0.00235 RPN total loss: 0.01488 Total loss: 0.96422 timestamp: 1655037069.4727342 iteration: 37030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14925 FastRCNN class loss: 0.09186 FastRCNN total loss: 0.24111 L1 loss: 0.0000e+00 L2 loss: 0.65373 Learning rate: 0.02 Mask loss: 0.144 RPN box loss: 0.01308 RPN score loss: 0.0052 RPN total loss: 0.01828 Total loss: 1.05712 timestamp: 1655037072.758524 iteration: 37035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17963 FastRCNN class loss: 0.11725 FastRCNN total loss: 0.29688 L1 loss: 0.0000e+00 L2 loss: 0.65365 Learning rate: 0.02 Mask loss: 0.16456 RPN box loss: 0.02729 RPN score loss: 0.00856 RPN total loss: 0.03584 Total loss: 1.15093 timestamp: 1655037076.0356278 iteration: 37040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17112 FastRCNN class loss: 0.08146 FastRCNN total loss: 0.25258 L1 loss: 0.0000e+00 L2 loss: 0.65355 Learning rate: 0.02 Mask loss: 0.15684 RPN box loss: 0.02202 RPN score loss: 0.0123 RPN total loss: 0.03432 Total loss: 1.09729 timestamp: 1655037079.317864 iteration: 37045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20147 FastRCNN class loss: 0.12798 FastRCNN total loss: 0.32945 L1 loss: 0.0000e+00 L2 loss: 0.65344 Learning rate: 0.02 Mask loss: 0.24745 RPN box loss: 0.01141 RPN score loss: 0.01767 RPN total loss: 0.02908 Total loss: 1.25943 timestamp: 1655037082.6026657 iteration: 37050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13759 FastRCNN class loss: 0.08518 FastRCNN total loss: 0.22277 L1 loss: 0.0000e+00 L2 loss: 0.65334 Learning rate: 0.02 Mask loss: 0.17082 RPN box loss: 0.04819 RPN score loss: 0.00487 RPN total loss: 0.05307 Total loss: 1.1 timestamp: 1655037085.8575566 iteration: 37055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10657 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.18496 L1 loss: 0.0000e+00 L2 loss: 0.65325 Learning rate: 0.02 Mask loss: 0.14538 RPN box loss: 0.03504 RPN score loss: 0.00489 RPN total loss: 0.03993 Total loss: 1.02351 timestamp: 1655037089.1348345 iteration: 37060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.19578 L1 loss: 0.0000e+00 L2 loss: 0.65318 Learning rate: 0.02 Mask loss: 0.1651 RPN box loss: 0.03574 RPN score loss: 0.00777 RPN total loss: 0.04351 Total loss: 1.05756 timestamp: 1655037092.3734062 iteration: 37065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05838 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.12207 L1 loss: 0.0000e+00 L2 loss: 0.6531 Learning rate: 0.02 Mask loss: 0.19 RPN box loss: 0.01704 RPN score loss: 0.01263 RPN total loss: 0.02968 Total loss: 0.99485 timestamp: 1655037095.6577177 iteration: 37070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15541 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.22486 L1 loss: 0.0000e+00 L2 loss: 0.65301 Learning rate: 0.02 Mask loss: 0.20277 RPN box loss: 0.03135 RPN score loss: 0.00813 RPN total loss: 0.03949 Total loss: 1.12012 timestamp: 1655037098.9312248 iteration: 37075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10194 FastRCNN class loss: 0.06002 FastRCNN total loss: 0.16196 L1 loss: 0.0000e+00 L2 loss: 0.65291 Learning rate: 0.02 Mask loss: 0.20803 RPN box loss: 0.03398 RPN score loss: 0.00769 RPN total loss: 0.04167 Total loss: 1.06457 timestamp: 1655037102.1836717 iteration: 37080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1173 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.17194 L1 loss: 0.0000e+00 L2 loss: 0.65281 Learning rate: 0.02 Mask loss: 0.18025 RPN box loss: 0.00973 RPN score loss: 0.002 RPN total loss: 0.01173 Total loss: 1.01674 timestamp: 1655037105.4176402 iteration: 37085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17181 FastRCNN class loss: 0.1414 FastRCNN total loss: 0.31321 L1 loss: 0.0000e+00 L2 loss: 0.65271 Learning rate: 0.02 Mask loss: 0.21363 RPN box loss: 0.02509 RPN score loss: 0.00723 RPN total loss: 0.03232 Total loss: 1.21187 timestamp: 1655037108.6679924 iteration: 37090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1514 FastRCNN class loss: 0.08892 FastRCNN total loss: 0.24032 L1 loss: 0.0000e+00 L2 loss: 0.65262 Learning rate: 0.02 Mask loss: 0.14374 RPN box loss: 0.03749 RPN score loss: 0.00696 RPN total loss: 0.04446 Total loss: 1.08113 timestamp: 1655037111.977847 iteration: 37095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08225 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.14229 L1 loss: 0.0000e+00 L2 loss: 0.65254 Learning rate: 0.02 Mask loss: 0.14062 RPN box loss: 0.03542 RPN score loss: 0.01212 RPN total loss: 0.04754 Total loss: 0.98299 timestamp: 1655037115.2286658 iteration: 37100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13902 FastRCNN class loss: 0.11444 FastRCNN total loss: 0.25345 L1 loss: 0.0000e+00 L2 loss: 0.65246 Learning rate: 0.02 Mask loss: 0.24774 RPN box loss: 0.04542 RPN score loss: 0.01574 RPN total loss: 0.06116 Total loss: 1.21481 timestamp: 1655037118.5018036 iteration: 37105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08691 FastRCNN class loss: 0.06143 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.65237 Learning rate: 0.02 Mask loss: 0.14405 RPN box loss: 0.0128 RPN score loss: 0.0029 RPN total loss: 0.01571 Total loss: 0.96048 timestamp: 1655037121.7213576 iteration: 37110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08568 FastRCNN class loss: 0.03658 FastRCNN total loss: 0.12227 L1 loss: 0.0000e+00 L2 loss: 0.65226 Learning rate: 0.02 Mask loss: 0.09871 RPN box loss: 0.00368 RPN score loss: 0.00279 RPN total loss: 0.00647 Total loss: 0.87971 timestamp: 1655037125.0058405 iteration: 37115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15553 FastRCNN class loss: 0.07128 FastRCNN total loss: 0.2268 L1 loss: 0.0000e+00 L2 loss: 0.65218 Learning rate: 0.02 Mask loss: 0.14739 RPN box loss: 0.01796 RPN score loss: 0.00252 RPN total loss: 0.02048 Total loss: 1.04684 timestamp: 1655037128.3141325 iteration: 37120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16428 FastRCNN class loss: 0.10735 FastRCNN total loss: 0.27163 L1 loss: 0.0000e+00 L2 loss: 0.65211 Learning rate: 0.02 Mask loss: 0.13806 RPN box loss: 0.04017 RPN score loss: 0.01525 RPN total loss: 0.05542 Total loss: 1.11723 timestamp: 1655037131.57053 iteration: 37125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1549 FastRCNN class loss: 0.08767 FastRCNN total loss: 0.24257 L1 loss: 0.0000e+00 L2 loss: 0.65202 Learning rate: 0.02 Mask loss: 0.19649 RPN box loss: 0.03884 RPN score loss: 0.00235 RPN total loss: 0.04119 Total loss: 1.13227 timestamp: 1655037134.870402 iteration: 37130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13067 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.20098 L1 loss: 0.0000e+00 L2 loss: 0.65196 Learning rate: 0.02 Mask loss: 0.15014 RPN box loss: 0.02305 RPN score loss: 0.00522 RPN total loss: 0.02827 Total loss: 1.03134 timestamp: 1655037138.1538634 iteration: 37135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13763 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.23152 L1 loss: 0.0000e+00 L2 loss: 0.65186 Learning rate: 0.02 Mask loss: 0.13427 RPN box loss: 0.08318 RPN score loss: 0.00695 RPN total loss: 0.09013 Total loss: 1.10779 timestamp: 1655037141.4124603 iteration: 37140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.07777 FastRCNN total loss: 0.1867 L1 loss: 0.0000e+00 L2 loss: 0.65178 Learning rate: 0.02 Mask loss: 0.15945 RPN box loss: 0.0164 RPN score loss: 0.00612 RPN total loss: 0.02252 Total loss: 1.02045 timestamp: 1655037144.6864955 iteration: 37145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15421 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.25397 L1 loss: 0.0000e+00 L2 loss: 0.6517 Learning rate: 0.02 Mask loss: 0.21844 RPN box loss: 0.03395 RPN score loss: 0.00846 RPN total loss: 0.0424 Total loss: 1.16652 timestamp: 1655037147.9382048 iteration: 37150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.06763 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 0.6516 Learning rate: 0.02 Mask loss: 0.15385 RPN box loss: 0.04135 RPN score loss: 0.00598 RPN total loss: 0.04733 Total loss: 1.04439 timestamp: 1655037151.151053 iteration: 37155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13581 FastRCNN class loss: 0.08718 FastRCNN total loss: 0.22299 L1 loss: 0.0000e+00 L2 loss: 0.65152 Learning rate: 0.02 Mask loss: 0.13921 RPN box loss: 0.01386 RPN score loss: 0.00337 RPN total loss: 0.01723 Total loss: 1.03095 timestamp: 1655037154.3898618 iteration: 37160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15164 FastRCNN class loss: 0.18299 FastRCNN total loss: 0.33463 L1 loss: 0.0000e+00 L2 loss: 0.65142 Learning rate: 0.02 Mask loss: 0.17963 RPN box loss: 0.03262 RPN score loss: 0.01251 RPN total loss: 0.04513 Total loss: 1.2108 timestamp: 1655037157.6857781 iteration: 37165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11565 FastRCNN class loss: 0.09676 FastRCNN total loss: 0.21241 L1 loss: 0.0000e+00 L2 loss: 0.65131 Learning rate: 0.02 Mask loss: 0.16845 RPN box loss: 0.03306 RPN score loss: 0.00608 RPN total loss: 0.03914 Total loss: 1.07131 timestamp: 1655037160.9250166 iteration: 37170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12168 FastRCNN class loss: 0.09881 FastRCNN total loss: 0.22048 L1 loss: 0.0000e+00 L2 loss: 0.65121 Learning rate: 0.02 Mask loss: 0.16819 RPN box loss: 0.01743 RPN score loss: 0.0034 RPN total loss: 0.02083 Total loss: 1.06072 timestamp: 1655037164.2185042 iteration: 37175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.09003 FastRCNN total loss: 0.2103 L1 loss: 0.0000e+00 L2 loss: 0.65114 Learning rate: 0.02 Mask loss: 0.1532 RPN box loss: 0.04403 RPN score loss: 0.00844 RPN total loss: 0.05247 Total loss: 1.0671 timestamp: 1655037167.470038 iteration: 37180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16994 FastRCNN class loss: 0.12846 FastRCNN total loss: 0.2984 L1 loss: 0.0000e+00 L2 loss: 0.65106 Learning rate: 0.02 Mask loss: 0.13619 RPN box loss: 0.02108 RPN score loss: 0.00953 RPN total loss: 0.0306 Total loss: 1.11626 timestamp: 1655037170.744722 iteration: 37185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14141 FastRCNN class loss: 0.11111 FastRCNN total loss: 0.25253 L1 loss: 0.0000e+00 L2 loss: 0.65096 Learning rate: 0.02 Mask loss: 0.18212 RPN box loss: 0.03054 RPN score loss: 0.00284 RPN total loss: 0.03337 Total loss: 1.11898 timestamp: 1655037173.8885977 iteration: 37190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.15005 L1 loss: 0.0000e+00 L2 loss: 0.65088 Learning rate: 0.02 Mask loss: 0.1348 RPN box loss: 0.00797 RPN score loss: 0.00367 RPN total loss: 0.01164 Total loss: 0.94737 timestamp: 1655037177.1650846 iteration: 37195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19349 FastRCNN class loss: 0.08185 FastRCNN total loss: 0.27534 L1 loss: 0.0000e+00 L2 loss: 0.65079 Learning rate: 0.02 Mask loss: 0.20717 RPN box loss: 0.0173 RPN score loss: 0.01032 RPN total loss: 0.02763 Total loss: 1.16093 timestamp: 1655037180.4271812 iteration: 37200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12573 FastRCNN class loss: 0.10807 FastRCNN total loss: 0.2338 L1 loss: 0.0000e+00 L2 loss: 0.6507 Learning rate: 0.02 Mask loss: 0.24692 RPN box loss: 0.03051 RPN score loss: 0.00439 RPN total loss: 0.0349 Total loss: 1.16632 timestamp: 1655037183.6842322 iteration: 37205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10487 FastRCNN class loss: 0.19223 FastRCNN total loss: 0.2971 L1 loss: 0.0000e+00 L2 loss: 0.65062 Learning rate: 0.02 Mask loss: 0.12034 RPN box loss: 0.01243 RPN score loss: 0.00175 RPN total loss: 0.01418 Total loss: 1.08223 timestamp: 1655037186.9080925 iteration: 37210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08773 FastRCNN class loss: 0.07479 FastRCNN total loss: 0.16252 L1 loss: 0.0000e+00 L2 loss: 0.65053 Learning rate: 0.02 Mask loss: 0.14556 RPN box loss: 0.02016 RPN score loss: 0.00265 RPN total loss: 0.02282 Total loss: 0.98143 timestamp: 1655037190.1499228 iteration: 37215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13839 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.23433 L1 loss: 0.0000e+00 L2 loss: 0.65044 Learning rate: 0.02 Mask loss: 0.20637 RPN box loss: 0.07429 RPN score loss: 0.01601 RPN total loss: 0.09031 Total loss: 1.18145 timestamp: 1655037193.4368236 iteration: 37220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12146 FastRCNN class loss: 0.09226 FastRCNN total loss: 0.21371 L1 loss: 0.0000e+00 L2 loss: 0.65034 Learning rate: 0.02 Mask loss: 0.36406 RPN box loss: 0.01864 RPN score loss: 0.00934 RPN total loss: 0.02797 Total loss: 1.25609 timestamp: 1655037196.731084 iteration: 37225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17168 FastRCNN class loss: 0.08884 FastRCNN total loss: 0.26052 L1 loss: 0.0000e+00 L2 loss: 0.65022 Learning rate: 0.02 Mask loss: 0.14084 RPN box loss: 0.01812 RPN score loss: 0.00455 RPN total loss: 0.02267 Total loss: 1.07425 timestamp: 1655037200.0205872 iteration: 37230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14693 FastRCNN class loss: 0.0927 FastRCNN total loss: 0.23963 L1 loss: 0.0000e+00 L2 loss: 0.65015 Learning rate: 0.02 Mask loss: 0.20893 RPN box loss: 0.02058 RPN score loss: 0.00416 RPN total loss: 0.02474 Total loss: 1.12345 timestamp: 1655037203.292502 iteration: 37235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15421 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.21769 L1 loss: 0.0000e+00 L2 loss: 0.65008 Learning rate: 0.02 Mask loss: 0.11254 RPN box loss: 0.01262 RPN score loss: 0.00465 RPN total loss: 0.01727 Total loss: 0.99758 timestamp: 1655037206.4712422 iteration: 37240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16507 FastRCNN class loss: 0.21156 FastRCNN total loss: 0.37662 L1 loss: 0.0000e+00 L2 loss: 0.65001 Learning rate: 0.02 Mask loss: 0.24025 RPN box loss: 0.02526 RPN score loss: 0.00917 RPN total loss: 0.03443 Total loss: 1.30132 timestamp: 1655037209.6909044 iteration: 37245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15072 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.22284 L1 loss: 0.0000e+00 L2 loss: 0.64993 Learning rate: 0.02 Mask loss: 0.12829 RPN box loss: 0.03791 RPN score loss: 0.00803 RPN total loss: 0.04594 Total loss: 1.047 timestamp: 1655037212.9673016 iteration: 37250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1494 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.22045 L1 loss: 0.0000e+00 L2 loss: 0.64983 Learning rate: 0.02 Mask loss: 0.21443 RPN box loss: 0.05234 RPN score loss: 0.00292 RPN total loss: 0.05526 Total loss: 1.13997 timestamp: 1655037216.2193806 iteration: 37255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13907 FastRCNN class loss: 0.09987 FastRCNN total loss: 0.23894 L1 loss: 0.0000e+00 L2 loss: 0.64973 Learning rate: 0.02 Mask loss: 0.16641 RPN box loss: 0.01682 RPN score loss: 0.01006 RPN total loss: 0.02688 Total loss: 1.08196 timestamp: 1655037219.5284135 iteration: 37260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1428 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.23977 L1 loss: 0.0000e+00 L2 loss: 0.64963 Learning rate: 0.02 Mask loss: 0.18516 RPN box loss: 0.05603 RPN score loss: 0.00602 RPN total loss: 0.06205 Total loss: 1.13661 timestamp: 1655037222.8209887 iteration: 37265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10988 FastRCNN class loss: 0.05383 FastRCNN total loss: 0.16371 L1 loss: 0.0000e+00 L2 loss: 0.64957 Learning rate: 0.02 Mask loss: 0.11213 RPN box loss: 0.01737 RPN score loss: 0.00385 RPN total loss: 0.02121 Total loss: 0.94662 timestamp: 1655037226.1401799 iteration: 37270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1052 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.17789 L1 loss: 0.0000e+00 L2 loss: 0.6495 Learning rate: 0.02 Mask loss: 0.1748 RPN box loss: 0.01613 RPN score loss: 0.00528 RPN total loss: 0.0214 Total loss: 1.02359 timestamp: 1655037229.337509 iteration: 37275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10062 FastRCNN class loss: 0.10664 FastRCNN total loss: 0.20727 L1 loss: 0.0000e+00 L2 loss: 0.64939 Learning rate: 0.02 Mask loss: 0.15014 RPN box loss: 0.01 RPN score loss: 0.00416 RPN total loss: 0.01416 Total loss: 1.02094 timestamp: 1655037232.6163764 iteration: 37280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14682 FastRCNN class loss: 0.10483 FastRCNN total loss: 0.25165 L1 loss: 0.0000e+00 L2 loss: 0.64931 Learning rate: 0.02 Mask loss: 0.13777 RPN box loss: 0.04435 RPN score loss: 0.01093 RPN total loss: 0.05528 Total loss: 1.09399 timestamp: 1655037235.8400986 iteration: 37285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1514 FastRCNN class loss: 0.06332 FastRCNN total loss: 0.21472 L1 loss: 0.0000e+00 L2 loss: 0.64922 Learning rate: 0.02 Mask loss: 0.11994 RPN box loss: 0.0113 RPN score loss: 0.00275 RPN total loss: 0.01404 Total loss: 0.99792 timestamp: 1655037239.1168857 iteration: 37290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18546 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.24726 L1 loss: 0.0000e+00 L2 loss: 0.64914 Learning rate: 0.02 Mask loss: 0.14711 RPN box loss: 0.02564 RPN score loss: 0.00389 RPN total loss: 0.02952 Total loss: 1.07303 timestamp: 1655037242.3868206 iteration: 37295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06404 FastRCNN class loss: 0.05948 FastRCNN total loss: 0.12352 L1 loss: 0.0000e+00 L2 loss: 0.64906 Learning rate: 0.02 Mask loss: 0.10026 RPN box loss: 0.02533 RPN score loss: 0.01193 RPN total loss: 0.03726 Total loss: 0.91009 timestamp: 1655037245.668315 iteration: 37300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19179 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.29141 L1 loss: 0.0000e+00 L2 loss: 0.64895 Learning rate: 0.02 Mask loss: 0.18697 RPN box loss: 0.04252 RPN score loss: 0.00677 RPN total loss: 0.04929 Total loss: 1.17662 timestamp: 1655037248.9681752 iteration: 37305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17774 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.25257 L1 loss: 0.0000e+00 L2 loss: 0.64887 Learning rate: 0.02 Mask loss: 0.15044 RPN box loss: 0.04278 RPN score loss: 0.00626 RPN total loss: 0.04904 Total loss: 1.10093 timestamp: 1655037252.265322 iteration: 37310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17334 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.23553 L1 loss: 0.0000e+00 L2 loss: 0.6488 Learning rate: 0.02 Mask loss: 0.1409 RPN box loss: 0.02642 RPN score loss: 0.00791 RPN total loss: 0.03433 Total loss: 1.05956 timestamp: 1655037255.4534287 iteration: 37315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11704 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.19494 L1 loss: 0.0000e+00 L2 loss: 0.64873 Learning rate: 0.02 Mask loss: 0.16228 RPN box loss: 0.01511 RPN score loss: 0.00399 RPN total loss: 0.0191 Total loss: 1.02505 timestamp: 1655037258.8367221 iteration: 37320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20518 FastRCNN class loss: 0.08614 FastRCNN total loss: 0.29133 L1 loss: 0.0000e+00 L2 loss: 0.64865 Learning rate: 0.02 Mask loss: 0.20158 RPN box loss: 0.04076 RPN score loss: 0.01319 RPN total loss: 0.05394 Total loss: 1.19551 timestamp: 1655037262.1187823 iteration: 37325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13883 FastRCNN class loss: 0.08727 FastRCNN total loss: 0.2261 L1 loss: 0.0000e+00 L2 loss: 0.64856 Learning rate: 0.02 Mask loss: 0.12694 RPN box loss: 0.02217 RPN score loss: 0.01696 RPN total loss: 0.03913 Total loss: 1.04073 timestamp: 1655037265.4054334 iteration: 37330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19562 FastRCNN class loss: 0.14828 FastRCNN total loss: 0.3439 L1 loss: 0.0000e+00 L2 loss: 0.64845 Learning rate: 0.02 Mask loss: 0.17925 RPN box loss: 0.04361 RPN score loss: 0.01482 RPN total loss: 0.05842 Total loss: 1.23003 timestamp: 1655037268.6974256 iteration: 37335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.17991 L1 loss: 0.0000e+00 L2 loss: 0.64837 Learning rate: 0.02 Mask loss: 0.21246 RPN box loss: 0.01293 RPN score loss: 0.00933 RPN total loss: 0.02226 Total loss: 1.063 timestamp: 1655037272.0001256 iteration: 37340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16025 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.2437 L1 loss: 0.0000e+00 L2 loss: 0.64826 Learning rate: 0.02 Mask loss: 0.14227 RPN box loss: 0.03344 RPN score loss: 0.00767 RPN total loss: 0.04111 Total loss: 1.07533 timestamp: 1655037275.262076 iteration: 37345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11358 FastRCNN class loss: 0.07828 FastRCNN total loss: 0.19186 L1 loss: 0.0000e+00 L2 loss: 0.64817 Learning rate: 0.02 Mask loss: 0.21082 RPN box loss: 0.02663 RPN score loss: 0.00237 RPN total loss: 0.029 Total loss: 1.07985 timestamp: 1655037278.5421817 iteration: 37350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14547 FastRCNN class loss: 0.09633 FastRCNN total loss: 0.2418 L1 loss: 0.0000e+00 L2 loss: 0.64809 Learning rate: 0.02 Mask loss: 0.17597 RPN box loss: 0.03431 RPN score loss: 0.00722 RPN total loss: 0.04153 Total loss: 1.1074 timestamp: 1655037281.8170145 iteration: 37355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22063 FastRCNN class loss: 0.10415 FastRCNN total loss: 0.32478 L1 loss: 0.0000e+00 L2 loss: 0.64799 Learning rate: 0.02 Mask loss: 0.19227 RPN box loss: 0.0153 RPN score loss: 0.00775 RPN total loss: 0.02305 Total loss: 1.1881 timestamp: 1655037285.116401 iteration: 37360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11829 FastRCNN class loss: 0.11305 FastRCNN total loss: 0.23134 L1 loss: 0.0000e+00 L2 loss: 0.6479 Learning rate: 0.02 Mask loss: 0.18285 RPN box loss: 0.03191 RPN score loss: 0.00546 RPN total loss: 0.03737 Total loss: 1.09946 timestamp: 1655037288.445256 iteration: 37365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08422 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.14007 L1 loss: 0.0000e+00 L2 loss: 0.64782 Learning rate: 0.02 Mask loss: 0.15499 RPN box loss: 0.01262 RPN score loss: 0.00654 RPN total loss: 0.01916 Total loss: 0.96203 timestamp: 1655037291.764487 iteration: 37370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15702 FastRCNN class loss: 0.08349 FastRCNN total loss: 0.24051 L1 loss: 0.0000e+00 L2 loss: 0.64772 Learning rate: 0.02 Mask loss: 0.12326 RPN box loss: 0.05697 RPN score loss: 0.01279 RPN total loss: 0.06976 Total loss: 1.08125 timestamp: 1655037295.0691848 iteration: 37375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11554 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.16187 L1 loss: 0.0000e+00 L2 loss: 0.64764 Learning rate: 0.02 Mask loss: 0.17032 RPN box loss: 0.06496 RPN score loss: 0.01408 RPN total loss: 0.07904 Total loss: 1.05888 timestamp: 1655037298.308833 iteration: 37380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11698 FastRCNN class loss: 0.10193 FastRCNN total loss: 0.21891 L1 loss: 0.0000e+00 L2 loss: 0.64755 Learning rate: 0.02 Mask loss: 0.2196 RPN box loss: 0.05744 RPN score loss: 0.0205 RPN total loss: 0.07793 Total loss: 1.16398 timestamp: 1655037301.5900452 iteration: 37385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0952 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 0.64747 Learning rate: 0.02 Mask loss: 0.13515 RPN box loss: 0.06513 RPN score loss: 0.01084 RPN total loss: 0.07596 Total loss: 1.01927 timestamp: 1655037304.833732 iteration: 37390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10751 FastRCNN class loss: 0.07588 FastRCNN total loss: 0.1834 L1 loss: 0.0000e+00 L2 loss: 0.64736 Learning rate: 0.02 Mask loss: 0.19314 RPN box loss: 0.03052 RPN score loss: 0.00723 RPN total loss: 0.03776 Total loss: 1.06166 timestamp: 1655037308.0967135 iteration: 37395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1026 FastRCNN class loss: 0.05709 FastRCNN total loss: 0.15969 L1 loss: 0.0000e+00 L2 loss: 0.64726 Learning rate: 0.02 Mask loss: 0.19744 RPN box loss: 0.00744 RPN score loss: 0.00414 RPN total loss: 0.01158 Total loss: 1.01598 timestamp: 1655037311.409291 iteration: 37400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12662 FastRCNN class loss: 0.06001 FastRCNN total loss: 0.18664 L1 loss: 0.0000e+00 L2 loss: 0.64719 Learning rate: 0.02 Mask loss: 0.16297 RPN box loss: 0.02894 RPN score loss: 0.01171 RPN total loss: 0.04065 Total loss: 1.03745 timestamp: 1655037314.6760654 iteration: 37405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.08686 FastRCNN total loss: 0.20363 L1 loss: 0.0000e+00 L2 loss: 0.64712 Learning rate: 0.02 Mask loss: 0.15345 RPN box loss: 0.05294 RPN score loss: 0.01471 RPN total loss: 0.06765 Total loss: 1.07185 timestamp: 1655037317.9454167 iteration: 37410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13261 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.21736 L1 loss: 0.0000e+00 L2 loss: 0.64703 Learning rate: 0.02 Mask loss: 0.14787 RPN box loss: 0.02163 RPN score loss: 0.0133 RPN total loss: 0.03493 Total loss: 1.04719 timestamp: 1655037321.166177 iteration: 37415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07427 FastRCNN class loss: 0.04325 FastRCNN total loss: 0.11753 L1 loss: 0.0000e+00 L2 loss: 0.64694 Learning rate: 0.02 Mask loss: 0.11564 RPN box loss: 0.00857 RPN score loss: 0.00246 RPN total loss: 0.01103 Total loss: 0.89114 timestamp: 1655037324.462469 iteration: 37420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14612 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.21526 L1 loss: 0.0000e+00 L2 loss: 0.64686 Learning rate: 0.02 Mask loss: 0.136 RPN box loss: 0.02307 RPN score loss: 0.00594 RPN total loss: 0.02901 Total loss: 1.02713 timestamp: 1655037327.7222526 iteration: 37425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07852 FastRCNN class loss: 0.0416 FastRCNN total loss: 0.12012 L1 loss: 0.0000e+00 L2 loss: 0.6468 Learning rate: 0.02 Mask loss: 0.11189 RPN box loss: 0.05878 RPN score loss: 0.01232 RPN total loss: 0.0711 Total loss: 0.94991 timestamp: 1655037330.9458601 iteration: 37430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11384 FastRCNN class loss: 0.05278 FastRCNN total loss: 0.16662 L1 loss: 0.0000e+00 L2 loss: 0.64671 Learning rate: 0.02 Mask loss: 0.13413 RPN box loss: 0.01324 RPN score loss: 0.00976 RPN total loss: 0.023 Total loss: 0.97045 timestamp: 1655037334.1878092 iteration: 37435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19819 FastRCNN class loss: 0.13634 FastRCNN total loss: 0.33453 L1 loss: 0.0000e+00 L2 loss: 0.64662 Learning rate: 0.02 Mask loss: 0.19152 RPN box loss: 0.03643 RPN score loss: 0.01116 RPN total loss: 0.04759 Total loss: 1.22026 timestamp: 1655037337.4743767 iteration: 37440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07224 FastRCNN class loss: 0.05446 FastRCNN total loss: 0.1267 L1 loss: 0.0000e+00 L2 loss: 0.64653 Learning rate: 0.02 Mask loss: 0.09863 RPN box loss: 0.02045 RPN score loss: 0.00759 RPN total loss: 0.02804 Total loss: 0.8999 timestamp: 1655037340.8016424 iteration: 37445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11833 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.17745 L1 loss: 0.0000e+00 L2 loss: 0.6464 Learning rate: 0.02 Mask loss: 0.11324 RPN box loss: 0.03506 RPN score loss: 0.00495 RPN total loss: 0.04001 Total loss: 0.9771 timestamp: 1655037344.1527584 iteration: 37450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13604 FastRCNN class loss: 0.08152 FastRCNN total loss: 0.21755 L1 loss: 0.0000e+00 L2 loss: 0.64632 Learning rate: 0.02 Mask loss: 0.24899 RPN box loss: 0.03614 RPN score loss: 0.00723 RPN total loss: 0.04337 Total loss: 1.15623 timestamp: 1655037347.4652817 iteration: 37455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12621 FastRCNN class loss: 0.06658 FastRCNN total loss: 0.19279 L1 loss: 0.0000e+00 L2 loss: 0.64623 Learning rate: 0.02 Mask loss: 0.1098 RPN box loss: 0.0109 RPN score loss: 0.00306 RPN total loss: 0.01395 Total loss: 0.96277 timestamp: 1655037350.7158737 iteration: 37460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14369 FastRCNN class loss: 0.08113 FastRCNN total loss: 0.22481 L1 loss: 0.0000e+00 L2 loss: 0.64616 Learning rate: 0.02 Mask loss: 0.11799 RPN box loss: 0.02219 RPN score loss: 0.00315 RPN total loss: 0.02534 Total loss: 1.0143 timestamp: 1655037354.0661216 iteration: 37465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15456 FastRCNN class loss: 0.07778 FastRCNN total loss: 0.23234 L1 loss: 0.0000e+00 L2 loss: 0.64608 Learning rate: 0.02 Mask loss: 0.1859 RPN box loss: 0.0161 RPN score loss: 0.00561 RPN total loss: 0.02171 Total loss: 1.08603 timestamp: 1655037357.321145 iteration: 37470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15104 FastRCNN class loss: 0.1264 FastRCNN total loss: 0.27744 L1 loss: 0.0000e+00 L2 loss: 0.64599 Learning rate: 0.02 Mask loss: 0.20487 RPN box loss: 0.0607 RPN score loss: 0.01009 RPN total loss: 0.07079 Total loss: 1.1991 timestamp: 1655037360.5953145 iteration: 37475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13743 FastRCNN class loss: 0.13238 FastRCNN total loss: 0.26981 L1 loss: 0.0000e+00 L2 loss: 0.64592 Learning rate: 0.02 Mask loss: 0.15425 RPN box loss: 0.03385 RPN score loss: 0.00606 RPN total loss: 0.03992 Total loss: 1.10989 timestamp: 1655037363.9092784 iteration: 37480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12092 FastRCNN class loss: 0.09871 FastRCNN total loss: 0.21963 L1 loss: 0.0000e+00 L2 loss: 0.6458 Learning rate: 0.02 Mask loss: 0.19151 RPN box loss: 0.04581 RPN score loss: 0.02164 RPN total loss: 0.06745 Total loss: 1.12438 timestamp: 1655037367.243273 iteration: 37485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14042 FastRCNN class loss: 0.075 FastRCNN total loss: 0.21541 L1 loss: 0.0000e+00 L2 loss: 0.64572 Learning rate: 0.02 Mask loss: 0.15607 RPN box loss: 0.0147 RPN score loss: 0.00563 RPN total loss: 0.02033 Total loss: 1.03753 timestamp: 1655037370.5661926 iteration: 37490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19371 FastRCNN class loss: 0.1076 FastRCNN total loss: 0.30131 L1 loss: 0.0000e+00 L2 loss: 0.64563 Learning rate: 0.02 Mask loss: 0.1995 RPN box loss: 0.03743 RPN score loss: 0.00985 RPN total loss: 0.04728 Total loss: 1.19372 timestamp: 1655037373.7585063 iteration: 37495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13624 FastRCNN class loss: 0.073 FastRCNN total loss: 0.20923 L1 loss: 0.0000e+00 L2 loss: 0.64556 Learning rate: 0.02 Mask loss: 0.1372 RPN box loss: 0.07329 RPN score loss: 0.00834 RPN total loss: 0.08163 Total loss: 1.07362 timestamp: 1655037377.0030074 iteration: 37500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13572 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.19903 L1 loss: 0.0000e+00 L2 loss: 0.64546 Learning rate: 0.02 Mask loss: 0.10782 RPN box loss: 0.0354 RPN score loss: 0.00837 RPN total loss: 0.04378 Total loss: 0.99609 timestamp: 1655037380.257206 iteration: 37505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14143 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.21569 L1 loss: 0.0000e+00 L2 loss: 0.64537 Learning rate: 0.02 Mask loss: 0.1693 RPN box loss: 0.04055 RPN score loss: 0.01051 RPN total loss: 0.05106 Total loss: 1.08142 timestamp: 1655037383.5416996 iteration: 37510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10026 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.1711 L1 loss: 0.0000e+00 L2 loss: 0.64529 Learning rate: 0.02 Mask loss: 0.13736 RPN box loss: 0.03663 RPN score loss: 0.00526 RPN total loss: 0.04189 Total loss: 0.99565 timestamp: 1655037386.8129613 iteration: 37515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15403 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.24687 L1 loss: 0.0000e+00 L2 loss: 0.6452 Learning rate: 0.02 Mask loss: 0.14421 RPN box loss: 0.03793 RPN score loss: 0.01469 RPN total loss: 0.05262 Total loss: 1.0889 timestamp: 1655037390.0466194 iteration: 37520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15133 FastRCNN class loss: 0.08703 FastRCNN total loss: 0.23837 L1 loss: 0.0000e+00 L2 loss: 0.64512 Learning rate: 0.02 Mask loss: 0.12643 RPN box loss: 0.03351 RPN score loss: 0.01239 RPN total loss: 0.0459 Total loss: 1.05581 timestamp: 1655037393.2860248 iteration: 37525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13681 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.18876 L1 loss: 0.0000e+00 L2 loss: 0.64502 Learning rate: 0.02 Mask loss: 0.19193 RPN box loss: 0.01346 RPN score loss: 0.01274 RPN total loss: 0.0262 Total loss: 1.05191 timestamp: 1655037396.6086457 iteration: 37530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18082 FastRCNN class loss: 0.11874 FastRCNN total loss: 0.29955 L1 loss: 0.0000e+00 L2 loss: 0.64493 Learning rate: 0.02 Mask loss: 0.1984 RPN box loss: 0.03506 RPN score loss: 0.02238 RPN total loss: 0.05744 Total loss: 1.20032 timestamp: 1655037399.858625 iteration: 37535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16054 FastRCNN class loss: 0.14195 FastRCNN total loss: 0.30249 L1 loss: 0.0000e+00 L2 loss: 0.64487 Learning rate: 0.02 Mask loss: 0.26048 RPN box loss: 0.03942 RPN score loss: 0.00879 RPN total loss: 0.04822 Total loss: 1.25606 timestamp: 1655037403.1061301 iteration: 37540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12644 FastRCNN class loss: 0.10783 FastRCNN total loss: 0.23427 L1 loss: 0.0000e+00 L2 loss: 0.64479 Learning rate: 0.02 Mask loss: 0.14951 RPN box loss: 0.02197 RPN score loss: 0.00399 RPN total loss: 0.02596 Total loss: 1.05453 timestamp: 1655037406.2687953 iteration: 37545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0892 FastRCNN class loss: 0.077 FastRCNN total loss: 0.1662 L1 loss: 0.0000e+00 L2 loss: 0.6447 Learning rate: 0.02 Mask loss: 0.26699 RPN box loss: 0.06231 RPN score loss: 0.00301 RPN total loss: 0.06532 Total loss: 1.14321 timestamp: 1655037409.4958541 iteration: 37550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09161 FastRCNN class loss: 0.07667 FastRCNN total loss: 0.16828 L1 loss: 0.0000e+00 L2 loss: 0.64462 Learning rate: 0.02 Mask loss: 0.10025 RPN box loss: 0.0399 RPN score loss: 0.00311 RPN total loss: 0.04301 Total loss: 0.95617 timestamp: 1655037412.8178074 iteration: 37555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11016 FastRCNN class loss: 0.09129 FastRCNN total loss: 0.20145 L1 loss: 0.0000e+00 L2 loss: 0.64456 Learning rate: 0.02 Mask loss: 0.20317 RPN box loss: 0.02465 RPN score loss: 0.01102 RPN total loss: 0.03567 Total loss: 1.08485 timestamp: 1655037416.144806 iteration: 37560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1291 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.21267 L1 loss: 0.0000e+00 L2 loss: 0.64449 Learning rate: 0.02 Mask loss: 0.21937 RPN box loss: 0.04719 RPN score loss: 0.01784 RPN total loss: 0.06503 Total loss: 1.14155 timestamp: 1655037419.4022357 iteration: 37565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.06182 FastRCNN total loss: 0.15451 L1 loss: 0.0000e+00 L2 loss: 0.64438 Learning rate: 0.02 Mask loss: 0.13245 RPN box loss: 0.03074 RPN score loss: 0.00928 RPN total loss: 0.04001 Total loss: 0.97135 timestamp: 1655037422.678182 iteration: 37570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.06189 FastRCNN total loss: 0.15459 L1 loss: 0.0000e+00 L2 loss: 0.64431 Learning rate: 0.02 Mask loss: 0.09976 RPN box loss: 0.04703 RPN score loss: 0.00341 RPN total loss: 0.05044 Total loss: 0.94909 timestamp: 1655037425.9302757 iteration: 37575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16126 FastRCNN class loss: 0.09209 FastRCNN total loss: 0.25335 L1 loss: 0.0000e+00 L2 loss: 0.64422 Learning rate: 0.02 Mask loss: 0.15819 RPN box loss: 0.05007 RPN score loss: 0.00664 RPN total loss: 0.05671 Total loss: 1.11247 timestamp: 1655037429.1628284 iteration: 37580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20247 FastRCNN class loss: 0.08361 FastRCNN total loss: 0.28608 L1 loss: 0.0000e+00 L2 loss: 0.64411 Learning rate: 0.02 Mask loss: 0.33998 RPN box loss: 0.049 RPN score loss: 0.00882 RPN total loss: 0.05781 Total loss: 1.32799 timestamp: 1655037432.5410202 iteration: 37585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10712 FastRCNN class loss: 0.09086 FastRCNN total loss: 0.19798 L1 loss: 0.0000e+00 L2 loss: 0.64401 Learning rate: 0.02 Mask loss: 0.16646 RPN box loss: 0.03847 RPN score loss: 0.01125 RPN total loss: 0.04973 Total loss: 1.05818 timestamp: 1655037435.8494625 iteration: 37590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14292 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.21787 L1 loss: 0.0000e+00 L2 loss: 0.64394 Learning rate: 0.02 Mask loss: 0.14424 RPN box loss: 0.02309 RPN score loss: 0.01471 RPN total loss: 0.0378 Total loss: 1.04385 timestamp: 1655037439.0626657 iteration: 37595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15571 FastRCNN class loss: 0.12367 FastRCNN total loss: 0.27938 L1 loss: 0.0000e+00 L2 loss: 0.64387 Learning rate: 0.02 Mask loss: 0.17332 RPN box loss: 0.02734 RPN score loss: 0.03108 RPN total loss: 0.05842 Total loss: 1.15499 timestamp: 1655037442.3613 iteration: 37600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.05557 FastRCNN total loss: 0.1662 L1 loss: 0.0000e+00 L2 loss: 0.64373 Learning rate: 0.02 Mask loss: 0.14252 RPN box loss: 0.01063 RPN score loss: 0.00756 RPN total loss: 0.01819 Total loss: 0.97063 timestamp: 1655037445.6559455 iteration: 37605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07537 FastRCNN class loss: 0.07031 FastRCNN total loss: 0.14568 L1 loss: 0.0000e+00 L2 loss: 0.64364 Learning rate: 0.02 Mask loss: 0.07945 RPN box loss: 0.01674 RPN score loss: 0.00373 RPN total loss: 0.02047 Total loss: 0.88923 timestamp: 1655037448.9919388 iteration: 37610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12755 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.1881 L1 loss: 0.0000e+00 L2 loss: 0.64356 Learning rate: 0.02 Mask loss: 0.08243 RPN box loss: 0.01944 RPN score loss: 0.0013 RPN total loss: 0.02074 Total loss: 0.93483 timestamp: 1655037452.247732 iteration: 37615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15385 FastRCNN class loss: 0.11304 FastRCNN total loss: 0.2669 L1 loss: 0.0000e+00 L2 loss: 0.64348 Learning rate: 0.02 Mask loss: 0.18262 RPN box loss: 0.04046 RPN score loss: 0.00889 RPN total loss: 0.04935 Total loss: 1.14234 timestamp: 1655037455.5311754 iteration: 37620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06164 FastRCNN class loss: 0.04906 FastRCNN total loss: 0.1107 L1 loss: 0.0000e+00 L2 loss: 0.64341 Learning rate: 0.02 Mask loss: 0.13218 RPN box loss: 0.07004 RPN score loss: 0.00883 RPN total loss: 0.07888 Total loss: 0.96518 timestamp: 1655037458.829116 iteration: 37625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11928 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.19415 L1 loss: 0.0000e+00 L2 loss: 0.64334 Learning rate: 0.02 Mask loss: 0.20633 RPN box loss: 0.0426 RPN score loss: 0.01006 RPN total loss: 0.05266 Total loss: 1.09648 timestamp: 1655037462.1085327 iteration: 37630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17825 FastRCNN class loss: 0.11237 FastRCNN total loss: 0.29062 L1 loss: 0.0000e+00 L2 loss: 0.64325 Learning rate: 0.02 Mask loss: 0.19169 RPN box loss: 0.03663 RPN score loss: 0.00903 RPN total loss: 0.04566 Total loss: 1.17122 timestamp: 1655037465.359095 iteration: 37635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18305 FastRCNN class loss: 0.09221 FastRCNN total loss: 0.27526 L1 loss: 0.0000e+00 L2 loss: 0.64321 Learning rate: 0.02 Mask loss: 0.2144 RPN box loss: 0.02298 RPN score loss: 0.01176 RPN total loss: 0.03475 Total loss: 1.16762 timestamp: 1655037468.6508448 iteration: 37640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15993 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.24958 L1 loss: 0.0000e+00 L2 loss: 0.64311 Learning rate: 0.02 Mask loss: 0.15696 RPN box loss: 0.02005 RPN score loss: 0.00502 RPN total loss: 0.02508 Total loss: 1.07472 timestamp: 1655037471.922899 iteration: 37645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06058 FastRCNN class loss: 0.04759 FastRCNN total loss: 0.10817 L1 loss: 0.0000e+00 L2 loss: 0.64304 Learning rate: 0.02 Mask loss: 0.17042 RPN box loss: 0.00853 RPN score loss: 0.00706 RPN total loss: 0.01559 Total loss: 0.93722 timestamp: 1655037475.174116 iteration: 37650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07192 FastRCNN class loss: 0.03268 FastRCNN total loss: 0.1046 L1 loss: 0.0000e+00 L2 loss: 0.64299 Learning rate: 0.02 Mask loss: 0.11986 RPN box loss: 0.00698 RPN score loss: 0.00058 RPN total loss: 0.00756 Total loss: 0.87501 timestamp: 1655037478.4428787 iteration: 37655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14428 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.21701 L1 loss: 0.0000e+00 L2 loss: 0.64282 Learning rate: 0.02 Mask loss: 0.13698 RPN box loss: 0.0281 RPN score loss: 0.00242 RPN total loss: 0.03051 Total loss: 1.02733 timestamp: 1655037481.7509072 iteration: 37660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15633 FastRCNN class loss: 0.08133 FastRCNN total loss: 0.23766 L1 loss: 0.0000e+00 L2 loss: 0.64277 Learning rate: 0.02 Mask loss: 0.17889 RPN box loss: 0.0361 RPN score loss: 0.00504 RPN total loss: 0.04113 Total loss: 1.10044 timestamp: 1655037485.0214322 iteration: 37665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11674 FastRCNN class loss: 0.0561 FastRCNN total loss: 0.17283 L1 loss: 0.0000e+00 L2 loss: 0.64271 Learning rate: 0.02 Mask loss: 0.14689 RPN box loss: 0.0341 RPN score loss: 0.00764 RPN total loss: 0.04174 Total loss: 1.00417 timestamp: 1655037488.2983027 iteration: 37670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12225 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.20762 L1 loss: 0.0000e+00 L2 loss: 0.6426 Learning rate: 0.02 Mask loss: 0.19394 RPN box loss: 0.03568 RPN score loss: 0.01292 RPN total loss: 0.0486 Total loss: 1.09276 timestamp: 1655037491.5495195 iteration: 37675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17291 FastRCNN class loss: 0.10359 FastRCNN total loss: 0.2765 L1 loss: 0.0000e+00 L2 loss: 0.6425 Learning rate: 0.02 Mask loss: 0.19828 RPN box loss: 0.02856 RPN score loss: 0.00346 RPN total loss: 0.03202 Total loss: 1.14931 timestamp: 1655037494.7773826 iteration: 37680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10441 FastRCNN class loss: 0.04133 FastRCNN total loss: 0.14574 L1 loss: 0.0000e+00 L2 loss: 0.64243 Learning rate: 0.02 Mask loss: 0.15469 RPN box loss: 0.06767 RPN score loss: 0.00884 RPN total loss: 0.07651 Total loss: 1.01937 timestamp: 1655037498.0331745 iteration: 37685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08666 FastRCNN class loss: 0.05649 FastRCNN total loss: 0.14315 L1 loss: 0.0000e+00 L2 loss: 0.64234 Learning rate: 0.02 Mask loss: 0.13667 RPN box loss: 0.03982 RPN score loss: 0.00788 RPN total loss: 0.0477 Total loss: 0.96986 timestamp: 1655037501.3559253 iteration: 37690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13511 FastRCNN class loss: 0.12649 FastRCNN total loss: 0.26159 L1 loss: 0.0000e+00 L2 loss: 0.64224 Learning rate: 0.02 Mask loss: 0.19224 RPN box loss: 0.01974 RPN score loss: 0.00491 RPN total loss: 0.02465 Total loss: 1.12073 timestamp: 1655037504.664332 iteration: 37695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13401 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.20896 L1 loss: 0.0000e+00 L2 loss: 0.64216 Learning rate: 0.02 Mask loss: 0.15443 RPN box loss: 0.0319 RPN score loss: 0.00602 RPN total loss: 0.03791 Total loss: 1.04346 timestamp: 1655037507.954561 iteration: 37700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12915 FastRCNN class loss: 0.08843 FastRCNN total loss: 0.21758 L1 loss: 0.0000e+00 L2 loss: 0.64208 Learning rate: 0.02 Mask loss: 0.12727 RPN box loss: 0.01781 RPN score loss: 0.00404 RPN total loss: 0.02185 Total loss: 1.00877 timestamp: 1655037511.2175934 iteration: 37705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12968 FastRCNN class loss: 0.08583 FastRCNN total loss: 0.21551 L1 loss: 0.0000e+00 L2 loss: 0.64199 Learning rate: 0.02 Mask loss: 0.19506 RPN box loss: 0.02513 RPN score loss: 0.01081 RPN total loss: 0.03595 Total loss: 1.08852 timestamp: 1655037514.5351806 iteration: 37710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12579 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.2067 L1 loss: 0.0000e+00 L2 loss: 0.64191 Learning rate: 0.02 Mask loss: 0.24175 RPN box loss: 0.11453 RPN score loss: 0.02026 RPN total loss: 0.13478 Total loss: 1.22513 timestamp: 1655037517.6952605 iteration: 37715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17412 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.25872 L1 loss: 0.0000e+00 L2 loss: 0.64182 Learning rate: 0.02 Mask loss: 0.26214 RPN box loss: 0.01025 RPN score loss: 0.00538 RPN total loss: 0.01563 Total loss: 1.17831 timestamp: 1655037520.999877 iteration: 37720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15764 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.2537 L1 loss: 0.0000e+00 L2 loss: 0.64173 Learning rate: 0.02 Mask loss: 0.18344 RPN box loss: 0.02515 RPN score loss: 0.01008 RPN total loss: 0.03523 Total loss: 1.11409 timestamp: 1655037524.2751453 iteration: 37725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08527 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 0.64163 Learning rate: 0.02 Mask loss: 0.12175 RPN box loss: 0.03292 RPN score loss: 0.01187 RPN total loss: 0.04479 Total loss: 0.95853 timestamp: 1655037527.5692697 iteration: 37730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16582 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.25045 L1 loss: 0.0000e+00 L2 loss: 0.64154 Learning rate: 0.02 Mask loss: 0.17763 RPN box loss: 0.03061 RPN score loss: 0.0296 RPN total loss: 0.06022 Total loss: 1.12984 timestamp: 1655037530.7719824 iteration: 37735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17102 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.24121 L1 loss: 0.0000e+00 L2 loss: 0.64143 Learning rate: 0.02 Mask loss: 0.104 RPN box loss: 0.0239 RPN score loss: 0.00505 RPN total loss: 0.02895 Total loss: 1.01559 timestamp: 1655037534.1065528 iteration: 37740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19504 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.28668 L1 loss: 0.0000e+00 L2 loss: 0.64134 Learning rate: 0.02 Mask loss: 0.09906 RPN box loss: 0.00799 RPN score loss: 0.00412 RPN total loss: 0.01211 Total loss: 1.03919 timestamp: 1655037537.3172283 iteration: 37745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16176 FastRCNN class loss: 0.06375 FastRCNN total loss: 0.22551 L1 loss: 0.0000e+00 L2 loss: 0.64125 Learning rate: 0.02 Mask loss: 0.14428 RPN box loss: 0.0553 RPN score loss: 0.00471 RPN total loss: 0.06001 Total loss: 1.07105 timestamp: 1655037540.6169994 iteration: 37750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14727 FastRCNN class loss: 0.05324 FastRCNN total loss: 0.2005 L1 loss: 0.0000e+00 L2 loss: 0.64118 Learning rate: 0.02 Mask loss: 0.14326 RPN box loss: 0.02903 RPN score loss: 0.00418 RPN total loss: 0.0332 Total loss: 1.01815 timestamp: 1655037543.7913277 iteration: 37755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1209 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.6411 Learning rate: 0.02 Mask loss: 0.1529 RPN box loss: 0.03498 RPN score loss: 0.00797 RPN total loss: 0.04296 Total loss: 1.02961 timestamp: 1655037547.0245302 iteration: 37760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18447 FastRCNN class loss: 0.11198 FastRCNN total loss: 0.29645 L1 loss: 0.0000e+00 L2 loss: 0.641 Learning rate: 0.02 Mask loss: 0.20527 RPN box loss: 0.0657 RPN score loss: 0.0128 RPN total loss: 0.0785 Total loss: 1.22121 timestamp: 1655037550.3188453 iteration: 37765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16233 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.24621 L1 loss: 0.0000e+00 L2 loss: 0.64093 Learning rate: 0.02 Mask loss: 0.13174 RPN box loss: 0.01482 RPN score loss: 0.00575 RPN total loss: 0.02056 Total loss: 1.03945 timestamp: 1655037553.6173613 iteration: 37770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09385 FastRCNN class loss: 0.08179 FastRCNN total loss: 0.17565 L1 loss: 0.0000e+00 L2 loss: 0.64087 Learning rate: 0.02 Mask loss: 0.1073 RPN box loss: 0.03592 RPN score loss: 0.00662 RPN total loss: 0.04254 Total loss: 0.96636 timestamp: 1655037556.9521801 iteration: 37775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11515 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.17784 L1 loss: 0.0000e+00 L2 loss: 0.6408 Learning rate: 0.02 Mask loss: 0.13416 RPN box loss: 0.02355 RPN score loss: 0.00733 RPN total loss: 0.03088 Total loss: 0.98367 timestamp: 1655037560.1742043 iteration: 37780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17486 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.24401 L1 loss: 0.0000e+00 L2 loss: 0.64073 Learning rate: 0.02 Mask loss: 0.16628 RPN box loss: 0.02976 RPN score loss: 0.00726 RPN total loss: 0.03703 Total loss: 1.08805 timestamp: 1655037563.3922968 iteration: 37785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16565 FastRCNN class loss: 0.11466 FastRCNN total loss: 0.28031 L1 loss: 0.0000e+00 L2 loss: 0.64062 Learning rate: 0.02 Mask loss: 0.1511 RPN box loss: 0.02406 RPN score loss: 0.0078 RPN total loss: 0.03186 Total loss: 1.10389 timestamp: 1655037566.6429148 iteration: 37790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10955 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.18067 L1 loss: 0.0000e+00 L2 loss: 0.64054 Learning rate: 0.02 Mask loss: 0.18865 RPN box loss: 0.02123 RPN score loss: 0.00549 RPN total loss: 0.02672 Total loss: 1.03658 timestamp: 1655037569.9418871 iteration: 37795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15436 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.23737 L1 loss: 0.0000e+00 L2 loss: 0.64046 Learning rate: 0.02 Mask loss: 0.12522 RPN box loss: 0.01741 RPN score loss: 0.00387 RPN total loss: 0.02128 Total loss: 1.02432 timestamp: 1655037573.277073 iteration: 37800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11696 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.17014 L1 loss: 0.0000e+00 L2 loss: 0.64037 Learning rate: 0.02 Mask loss: 0.13542 RPN box loss: 0.04122 RPN score loss: 0.00966 RPN total loss: 0.05088 Total loss: 0.99681 timestamp: 1655037576.529906 iteration: 37805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23082 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.30121 L1 loss: 0.0000e+00 L2 loss: 0.64028 Learning rate: 0.02 Mask loss: 0.14161 RPN box loss: 0.03672 RPN score loss: 0.00553 RPN total loss: 0.04225 Total loss: 1.12535 timestamp: 1655037579.672177 iteration: 37810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.14894 L1 loss: 0.0000e+00 L2 loss: 0.64018 Learning rate: 0.02 Mask loss: 0.13158 RPN box loss: 0.0261 RPN score loss: 0.00697 RPN total loss: 0.03308 Total loss: 0.95378 timestamp: 1655037582.9587557 iteration: 37815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12788 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.1964 L1 loss: 0.0000e+00 L2 loss: 0.64008 Learning rate: 0.02 Mask loss: 0.13888 RPN box loss: 0.02636 RPN score loss: 0.00335 RPN total loss: 0.02971 Total loss: 1.00508 timestamp: 1655037586.2135136 iteration: 37820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13198 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 0.64 Learning rate: 0.02 Mask loss: 0.13805 RPN box loss: 0.01923 RPN score loss: 0.00765 RPN total loss: 0.02688 Total loss: 1.0022 timestamp: 1655037589.5121825 iteration: 37825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14218 FastRCNN class loss: 0.11136 FastRCNN total loss: 0.25354 L1 loss: 0.0000e+00 L2 loss: 0.63986 Learning rate: 0.02 Mask loss: 0.26509 RPN box loss: 0.03126 RPN score loss: 0.00601 RPN total loss: 0.03727 Total loss: 1.19576 timestamp: 1655037592.7987788 iteration: 37830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14393 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.20033 L1 loss: 0.0000e+00 L2 loss: 0.63979 Learning rate: 0.02 Mask loss: 0.12741 RPN box loss: 0.02809 RPN score loss: 0.00556 RPN total loss: 0.03365 Total loss: 1.00118 timestamp: 1655037596.0010266 iteration: 37835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14336 FastRCNN class loss: 0.11137 FastRCNN total loss: 0.25473 L1 loss: 0.0000e+00 L2 loss: 0.63975 Learning rate: 0.02 Mask loss: 0.12744 RPN box loss: 0.03052 RPN score loss: 0.00396 RPN total loss: 0.03448 Total loss: 1.0564 timestamp: 1655037599.3349957 iteration: 37840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15682 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.24144 L1 loss: 0.0000e+00 L2 loss: 0.63968 Learning rate: 0.02 Mask loss: 0.15885 RPN box loss: 0.03372 RPN score loss: 0.00763 RPN total loss: 0.04135 Total loss: 1.08132 timestamp: 1655037602.5553741 iteration: 37845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1593 FastRCNN class loss: 0.08527 FastRCNN total loss: 0.24457 L1 loss: 0.0000e+00 L2 loss: 0.63958 Learning rate: 0.02 Mask loss: 0.11457 RPN box loss: 0.02022 RPN score loss: 0.00241 RPN total loss: 0.02263 Total loss: 1.02136 timestamp: 1655037605.8571496 iteration: 37850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16203 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.24735 L1 loss: 0.0000e+00 L2 loss: 0.63949 Learning rate: 0.02 Mask loss: 0.16308 RPN box loss: 0.06238 RPN score loss: 0.00961 RPN total loss: 0.07198 Total loss: 1.1219 timestamp: 1655037609.241207 iteration: 37855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15233 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.21313 L1 loss: 0.0000e+00 L2 loss: 0.63939 Learning rate: 0.02 Mask loss: 0.14393 RPN box loss: 0.02069 RPN score loss: 0.00278 RPN total loss: 0.02347 Total loss: 1.01993 timestamp: 1655037612.5110354 iteration: 37860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10133 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.15938 L1 loss: 0.0000e+00 L2 loss: 0.63932 Learning rate: 0.02 Mask loss: 0.1221 RPN box loss: 0.01597 RPN score loss: 0.00392 RPN total loss: 0.01989 Total loss: 0.94069 timestamp: 1655037615.8634114 iteration: 37865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15274 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.26053 L1 loss: 0.0000e+00 L2 loss: 0.63925 Learning rate: 0.02 Mask loss: 0.15706 RPN box loss: 0.06186 RPN score loss: 0.01132 RPN total loss: 0.07318 Total loss: 1.13002 timestamp: 1655037619.2100506 iteration: 37870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13682 FastRCNN class loss: 0.07437 FastRCNN total loss: 0.21119 L1 loss: 0.0000e+00 L2 loss: 0.63916 Learning rate: 0.02 Mask loss: 0.19924 RPN box loss: 0.02051 RPN score loss: 0.00247 RPN total loss: 0.02298 Total loss: 1.07257 timestamp: 1655037622.4800162 iteration: 37875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14266 FastRCNN class loss: 0.06298 FastRCNN total loss: 0.20564 L1 loss: 0.0000e+00 L2 loss: 0.63906 Learning rate: 0.02 Mask loss: 0.14754 RPN box loss: 0.01963 RPN score loss: 0.00568 RPN total loss: 0.02531 Total loss: 1.01755 timestamp: 1655037625.8024535 iteration: 37880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0986 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.14937 L1 loss: 0.0000e+00 L2 loss: 0.63894 Learning rate: 0.02 Mask loss: 0.17781 RPN box loss: 0.03233 RPN score loss: 0.00884 RPN total loss: 0.04118 Total loss: 1.0073 timestamp: 1655037629.140877 iteration: 37885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13012 FastRCNN class loss: 0.07677 FastRCNN total loss: 0.20689 L1 loss: 0.0000e+00 L2 loss: 0.63885 Learning rate: 0.02 Mask loss: 0.27687 RPN box loss: 0.02348 RPN score loss: 0.00381 RPN total loss: 0.02728 Total loss: 1.14988 timestamp: 1655037632.4813302 iteration: 37890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14373 FastRCNN class loss: 0.05816 FastRCNN total loss: 0.2019 L1 loss: 0.0000e+00 L2 loss: 0.6388 Learning rate: 0.02 Mask loss: 0.16966 RPN box loss: 0.02365 RPN score loss: 0.00366 RPN total loss: 0.02731 Total loss: 1.03766 timestamp: 1655037635.7798111 iteration: 37895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.04824 FastRCNN total loss: 0.20035 L1 loss: 0.0000e+00 L2 loss: 0.63872 Learning rate: 0.02 Mask loss: 0.13192 RPN box loss: 0.03916 RPN score loss: 0.00637 RPN total loss: 0.04554 Total loss: 1.01653 timestamp: 1655037639.0527034 iteration: 37900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.17667 L1 loss: 0.0000e+00 L2 loss: 0.63866 Learning rate: 0.02 Mask loss: 0.16572 RPN box loss: 0.00654 RPN score loss: 0.00124 RPN total loss: 0.00778 Total loss: 0.98882 timestamp: 1655037642.3298795 iteration: 37905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13927 FastRCNN class loss: 0.11616 FastRCNN total loss: 0.25544 L1 loss: 0.0000e+00 L2 loss: 0.63854 Learning rate: 0.02 Mask loss: 0.13886 RPN box loss: 0.0464 RPN score loss: 0.01412 RPN total loss: 0.06052 Total loss: 1.09336 timestamp: 1655037645.5312915 iteration: 37910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07018 FastRCNN class loss: 0.04697 FastRCNN total loss: 0.11715 L1 loss: 0.0000e+00 L2 loss: 0.63846 Learning rate: 0.02 Mask loss: 0.11281 RPN box loss: 0.01549 RPN score loss: 0.00256 RPN total loss: 0.01805 Total loss: 0.88646 timestamp: 1655037648.7746463 iteration: 37915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15214 FastRCNN class loss: 0.08356 FastRCNN total loss: 0.2357 L1 loss: 0.0000e+00 L2 loss: 0.63838 Learning rate: 0.02 Mask loss: 0.14506 RPN box loss: 0.03091 RPN score loss: 0.00805 RPN total loss: 0.03896 Total loss: 1.0581 timestamp: 1655037651.97309 iteration: 37920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11902 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.18376 L1 loss: 0.0000e+00 L2 loss: 0.6383 Learning rate: 0.02 Mask loss: 0.11125 RPN box loss: 0.01025 RPN score loss: 0.00263 RPN total loss: 0.01289 Total loss: 0.9462 timestamp: 1655037655.2011354 iteration: 37925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12969 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.18897 L1 loss: 0.0000e+00 L2 loss: 0.63822 Learning rate: 0.02 Mask loss: 0.15061 RPN box loss: 0.00647 RPN score loss: 0.00198 RPN total loss: 0.00846 Total loss: 0.98626 timestamp: 1655037658.443067 iteration: 37930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13736 FastRCNN class loss: 0.07179 FastRCNN total loss: 0.20915 L1 loss: 0.0000e+00 L2 loss: 0.63813 Learning rate: 0.02 Mask loss: 0.16587 RPN box loss: 0.01887 RPN score loss: 0.00482 RPN total loss: 0.02369 Total loss: 1.03684 timestamp: 1655037661.6400607 iteration: 37935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11702 FastRCNN class loss: 0.08505 FastRCNN total loss: 0.20208 L1 loss: 0.0000e+00 L2 loss: 0.63802 Learning rate: 0.02 Mask loss: 0.12858 RPN box loss: 0.01495 RPN score loss: 0.00381 RPN total loss: 0.01876 Total loss: 0.98744 timestamp: 1655037664.9425383 iteration: 37940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13677 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.21342 L1 loss: 0.0000e+00 L2 loss: 0.63794 Learning rate: 0.02 Mask loss: 0.15307 RPN box loss: 0.00819 RPN score loss: 0.00377 RPN total loss: 0.01195 Total loss: 1.01639 timestamp: 1655037668.2117712 iteration: 37945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13665 FastRCNN class loss: 0.07013 FastRCNN total loss: 0.20678 L1 loss: 0.0000e+00 L2 loss: 0.63785 Learning rate: 0.02 Mask loss: 0.1271 RPN box loss: 0.02348 RPN score loss: 0.00358 RPN total loss: 0.02706 Total loss: 0.99879 timestamp: 1655037671.5015082 iteration: 37950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08578 FastRCNN class loss: 0.05649 FastRCNN total loss: 0.14227 L1 loss: 0.0000e+00 L2 loss: 0.63778 Learning rate: 0.02 Mask loss: 0.11199 RPN box loss: 0.01944 RPN score loss: 0.00433 RPN total loss: 0.02378 Total loss: 0.91581 timestamp: 1655037674.7441313 iteration: 37955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15501 FastRCNN class loss: 0.11156 FastRCNN total loss: 0.26657 L1 loss: 0.0000e+00 L2 loss: 0.63772 Learning rate: 0.02 Mask loss: 0.17439 RPN box loss: 0.04347 RPN score loss: 0.0057 RPN total loss: 0.04917 Total loss: 1.12786 timestamp: 1655037678.0267313 iteration: 37960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15367 FastRCNN class loss: 0.06193 FastRCNN total loss: 0.21559 L1 loss: 0.0000e+00 L2 loss: 0.63765 Learning rate: 0.02 Mask loss: 0.1501 RPN box loss: 0.15377 RPN score loss: 0.01148 RPN total loss: 0.16525 Total loss: 1.16859 timestamp: 1655037681.2740889 iteration: 37965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11134 FastRCNN class loss: 0.04992 FastRCNN total loss: 0.16126 L1 loss: 0.0000e+00 L2 loss: 0.63758 Learning rate: 0.02 Mask loss: 0.09019 RPN box loss: 0.02175 RPN score loss: 0.00652 RPN total loss: 0.02827 Total loss: 0.91729 timestamp: 1655037684.4879718 iteration: 37970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17691 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.24828 L1 loss: 0.0000e+00 L2 loss: 0.63748 Learning rate: 0.02 Mask loss: 0.16652 RPN box loss: 0.03183 RPN score loss: 0.00277 RPN total loss: 0.0346 Total loss: 1.08689 timestamp: 1655037687.7696118 iteration: 37975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15502 FastRCNN class loss: 0.09011 FastRCNN total loss: 0.24513 L1 loss: 0.0000e+00 L2 loss: 0.63737 Learning rate: 0.02 Mask loss: 0.14077 RPN box loss: 0.05611 RPN score loss: 0.0119 RPN total loss: 0.06802 Total loss: 1.09129 timestamp: 1655037691.0021625 iteration: 37980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.18005 L1 loss: 0.0000e+00 L2 loss: 0.63728 Learning rate: 0.02 Mask loss: 0.16139 RPN box loss: 0.04245 RPN score loss: 0.00601 RPN total loss: 0.04846 Total loss: 1.02719 timestamp: 1655037694.2554202 iteration: 37985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15662 FastRCNN class loss: 0.10201 FastRCNN total loss: 0.25863 L1 loss: 0.0000e+00 L2 loss: 0.63719 Learning rate: 0.02 Mask loss: 0.15471 RPN box loss: 0.01818 RPN score loss: 0.00947 RPN total loss: 0.02765 Total loss: 1.07819 timestamp: 1655037697.5779858 iteration: 37990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12601 FastRCNN class loss: 0.0806 FastRCNN total loss: 0.20661 L1 loss: 0.0000e+00 L2 loss: 0.63708 Learning rate: 0.02 Mask loss: 0.12612 RPN box loss: 0.0368 RPN score loss: 0.00673 RPN total loss: 0.04353 Total loss: 1.01334 timestamp: 1655037700.8746562 iteration: 37995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11725 FastRCNN class loss: 0.07344 FastRCNN total loss: 0.19068 L1 loss: 0.0000e+00 L2 loss: 0.63702 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.04827 RPN score loss: 0.0114 RPN total loss: 0.05967 Total loss: 1.03981 timestamp: 1655037704.1839027 iteration: 38000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10106 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.16484 L1 loss: 0.0000e+00 L2 loss: 0.63695 Learning rate: 0.02 Mask loss: 0.1901 RPN box loss: 0.00988 RPN score loss: 0.01273 RPN total loss: 0.02261 Total loss: 1.01451 timestamp: 1655037707.4144685 iteration: 38005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15062 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.21717 L1 loss: 0.0000e+00 L2 loss: 0.63685 Learning rate: 0.02 Mask loss: 0.10178 RPN box loss: 0.02592 RPN score loss: 0.00525 RPN total loss: 0.03117 Total loss: 0.98697 timestamp: 1655037710.6437926 iteration: 38010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.06439 FastRCNN total loss: 0.18984 L1 loss: 0.0000e+00 L2 loss: 0.63678 Learning rate: 0.02 Mask loss: 0.16068 RPN box loss: 0.04426 RPN score loss: 0.00653 RPN total loss: 0.05079 Total loss: 1.03808 timestamp: 1655037713.9452796 iteration: 38015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1187 FastRCNN class loss: 0.09742 FastRCNN total loss: 0.21612 L1 loss: 0.0000e+00 L2 loss: 0.63668 Learning rate: 0.02 Mask loss: 0.13223 RPN box loss: 0.03929 RPN score loss: 0.00568 RPN total loss: 0.04496 Total loss: 1.02999 timestamp: 1655037717.1776989 iteration: 38020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.06933 FastRCNN total loss: 0.18675 L1 loss: 0.0000e+00 L2 loss: 0.6366 Learning rate: 0.02 Mask loss: 0.18629 RPN box loss: 0.02633 RPN score loss: 0.00436 RPN total loss: 0.03069 Total loss: 1.04032 timestamp: 1655037720.5505724 iteration: 38025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17414 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.25645 L1 loss: 0.0000e+00 L2 loss: 0.63652 Learning rate: 0.02 Mask loss: 0.2039 RPN box loss: 0.06264 RPN score loss: 0.00794 RPN total loss: 0.07058 Total loss: 1.16745 timestamp: 1655037723.8557203 iteration: 38030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21385 FastRCNN class loss: 0.09575 FastRCNN total loss: 0.30961 L1 loss: 0.0000e+00 L2 loss: 0.63642 Learning rate: 0.02 Mask loss: 0.12604 RPN box loss: 0.01696 RPN score loss: 0.01468 RPN total loss: 0.03164 Total loss: 1.10371 timestamp: 1655037727.0616007 iteration: 38035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12104 FastRCNN class loss: 0.1123 FastRCNN total loss: 0.23334 L1 loss: 0.0000e+00 L2 loss: 0.63634 Learning rate: 0.02 Mask loss: 0.20313 RPN box loss: 0.0415 RPN score loss: 0.01362 RPN total loss: 0.05512 Total loss: 1.12793 timestamp: 1655037730.2886965 iteration: 38040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.1494 L1 loss: 0.0000e+00 L2 loss: 0.63627 Learning rate: 0.02 Mask loss: 0.08733 RPN box loss: 0.01162 RPN score loss: 0.00359 RPN total loss: 0.01521 Total loss: 0.88822 timestamp: 1655037733.5675597 iteration: 38045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20903 FastRCNN class loss: 0.11367 FastRCNN total loss: 0.3227 L1 loss: 0.0000e+00 L2 loss: 0.63617 Learning rate: 0.02 Mask loss: 0.21373 RPN box loss: 0.01781 RPN score loss: 0.00701 RPN total loss: 0.02482 Total loss: 1.19742 timestamp: 1655037736.8100882 iteration: 38050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1296 FastRCNN class loss: 0.06498 FastRCNN total loss: 0.19459 L1 loss: 0.0000e+00 L2 loss: 0.63609 Learning rate: 0.02 Mask loss: 0.14186 RPN box loss: 0.0092 RPN score loss: 0.00362 RPN total loss: 0.01281 Total loss: 0.98535 timestamp: 1655037740.0873346 iteration: 38055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10177 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.17197 L1 loss: 0.0000e+00 L2 loss: 0.63599 Learning rate: 0.02 Mask loss: 0.17555 RPN box loss: 0.03245 RPN score loss: 0.00238 RPN total loss: 0.03484 Total loss: 1.01835 timestamp: 1655037743.3463948 iteration: 38060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07874 FastRCNN class loss: 0.09374 FastRCNN total loss: 0.17247 L1 loss: 0.0000e+00 L2 loss: 0.63592 Learning rate: 0.02 Mask loss: 0.09689 RPN box loss: 0.01025 RPN score loss: 0.00323 RPN total loss: 0.01348 Total loss: 0.91876 timestamp: 1655037746.6290698 iteration: 38065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17325 FastRCNN class loss: 0.12113 FastRCNN total loss: 0.29438 L1 loss: 0.0000e+00 L2 loss: 0.63582 Learning rate: 0.02 Mask loss: 0.16377 RPN box loss: 0.0523 RPN score loss: 0.00817 RPN total loss: 0.06047 Total loss: 1.15444 timestamp: 1655037749.9104285 iteration: 38070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13223 FastRCNN class loss: 0.12685 FastRCNN total loss: 0.25908 L1 loss: 0.0000e+00 L2 loss: 0.63573 Learning rate: 0.02 Mask loss: 0.21258 RPN box loss: 0.03461 RPN score loss: 0.00842 RPN total loss: 0.04303 Total loss: 1.15042 timestamp: 1655037753.09938 iteration: 38075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15094 FastRCNN class loss: 0.08515 FastRCNN total loss: 0.23609 L1 loss: 0.0000e+00 L2 loss: 0.63563 Learning rate: 0.02 Mask loss: 0.19716 RPN box loss: 0.0153 RPN score loss: 0.00582 RPN total loss: 0.02113 Total loss: 1.09001 timestamp: 1655037756.4343045 iteration: 38080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16748 FastRCNN class loss: 0.11346 FastRCNN total loss: 0.28094 L1 loss: 0.0000e+00 L2 loss: 0.63555 Learning rate: 0.02 Mask loss: 0.20126 RPN box loss: 0.03393 RPN score loss: 0.00359 RPN total loss: 0.03752 Total loss: 1.15528 timestamp: 1655037759.7495165 iteration: 38085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09577 FastRCNN class loss: 0.05357 FastRCNN total loss: 0.14933 L1 loss: 0.0000e+00 L2 loss: 0.63549 Learning rate: 0.02 Mask loss: 0.36906 RPN box loss: 0.03644 RPN score loss: 0.00258 RPN total loss: 0.03901 Total loss: 1.1929 timestamp: 1655037763.0504937 iteration: 38090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11438 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.16675 L1 loss: 0.0000e+00 L2 loss: 0.63543 Learning rate: 0.02 Mask loss: 0.12734 RPN box loss: 0.01747 RPN score loss: 0.00848 RPN total loss: 0.02594 Total loss: 0.95547 timestamp: 1655037766.3865275 iteration: 38095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0868 FastRCNN class loss: 0.07152 FastRCNN total loss: 0.15832 L1 loss: 0.0000e+00 L2 loss: 0.63532 Learning rate: 0.02 Mask loss: 0.12789 RPN box loss: 0.04393 RPN score loss: 0.00607 RPN total loss: 0.04999 Total loss: 0.97153 timestamp: 1655037769.6034675 iteration: 38100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09521 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.14855 L1 loss: 0.0000e+00 L2 loss: 0.63521 Learning rate: 0.02 Mask loss: 0.13259 RPN box loss: 0.03211 RPN score loss: 0.00443 RPN total loss: 0.03654 Total loss: 0.95289 timestamp: 1655037772.837179 iteration: 38105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10881 FastRCNN class loss: 0.10329 FastRCNN total loss: 0.21211 L1 loss: 0.0000e+00 L2 loss: 0.63511 Learning rate: 0.02 Mask loss: 0.31786 RPN box loss: 0.08546 RPN score loss: 0.03069 RPN total loss: 0.11615 Total loss: 1.28123 timestamp: 1655037776.0543358 iteration: 38110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 0.63503 Learning rate: 0.02 Mask loss: 0.17029 RPN box loss: 0.04031 RPN score loss: 0.00806 RPN total loss: 0.04837 Total loss: 1.03449 timestamp: 1655037779.3397117 iteration: 38115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12887 FastRCNN class loss: 0.06465 FastRCNN total loss: 0.19352 L1 loss: 0.0000e+00 L2 loss: 0.63497 Learning rate: 0.02 Mask loss: 0.12961 RPN box loss: 0.0357 RPN score loss: 0.00594 RPN total loss: 0.04164 Total loss: 0.99973 timestamp: 1655037782.627668 iteration: 38120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12536 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.19411 L1 loss: 0.0000e+00 L2 loss: 0.63488 Learning rate: 0.02 Mask loss: 0.159 RPN box loss: 0.04341 RPN score loss: 0.00116 RPN total loss: 0.04456 Total loss: 1.03256 timestamp: 1655037785.9652007 iteration: 38125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24687 FastRCNN class loss: 0.18665 FastRCNN total loss: 0.43352 L1 loss: 0.0000e+00 L2 loss: 0.63481 Learning rate: 0.02 Mask loss: 0.21952 RPN box loss: 0.0578 RPN score loss: 0.02372 RPN total loss: 0.08152 Total loss: 1.36936 timestamp: 1655037789.2751327 iteration: 38130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16566 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.22637 L1 loss: 0.0000e+00 L2 loss: 0.63472 Learning rate: 0.02 Mask loss: 0.09092 RPN box loss: 0.03656 RPN score loss: 0.00709 RPN total loss: 0.04365 Total loss: 0.99565 timestamp: 1655037792.5892382 iteration: 38135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0905 FastRCNN class loss: 0.0508 FastRCNN total loss: 0.1413 L1 loss: 0.0000e+00 L2 loss: 0.63461 Learning rate: 0.02 Mask loss: 0.1541 RPN box loss: 0.01227 RPN score loss: 0.00442 RPN total loss: 0.01669 Total loss: 0.9467 timestamp: 1655037795.8612728 iteration: 38140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.12734 L1 loss: 0.0000e+00 L2 loss: 0.63453 Learning rate: 0.02 Mask loss: 0.09794 RPN box loss: 0.03659 RPN score loss: 0.00873 RPN total loss: 0.04532 Total loss: 0.90513 timestamp: 1655037799.139006 iteration: 38145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.18345 L1 loss: 0.0000e+00 L2 loss: 0.63445 Learning rate: 0.02 Mask loss: 0.31914 RPN box loss: 0.03946 RPN score loss: 0.00805 RPN total loss: 0.04751 Total loss: 1.18456 timestamp: 1655037802.3979182 iteration: 38150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16679 FastRCNN class loss: 0.20669 FastRCNN total loss: 0.37349 L1 loss: 0.0000e+00 L2 loss: 0.63437 Learning rate: 0.02 Mask loss: 0.16298 RPN box loss: 0.03335 RPN score loss: 0.0166 RPN total loss: 0.04995 Total loss: 1.22078 timestamp: 1655037805.667034 iteration: 38155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11448 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.16451 L1 loss: 0.0000e+00 L2 loss: 0.6343 Learning rate: 0.02 Mask loss: 0.14744 RPN box loss: 0.02937 RPN score loss: 0.00688 RPN total loss: 0.03626 Total loss: 0.98251 timestamp: 1655037808.953437 iteration: 38160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22211 FastRCNN class loss: 0.09422 FastRCNN total loss: 0.31633 L1 loss: 0.0000e+00 L2 loss: 0.6342 Learning rate: 0.02 Mask loss: 0.16105 RPN box loss: 0.0328 RPN score loss: 0.00696 RPN total loss: 0.03976 Total loss: 1.15134 timestamp: 1655037812.2360106 iteration: 38165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1095 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.16019 L1 loss: 0.0000e+00 L2 loss: 0.63412 Learning rate: 0.02 Mask loss: 0.1597 RPN box loss: 0.0319 RPN score loss: 0.00839 RPN total loss: 0.04029 Total loss: 0.99431 timestamp: 1655037815.4881058 iteration: 38170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18546 FastRCNN class loss: 0.08914 FastRCNN total loss: 0.27461 L1 loss: 0.0000e+00 L2 loss: 0.63403 Learning rate: 0.02 Mask loss: 0.18332 RPN box loss: 0.03631 RPN score loss: 0.01312 RPN total loss: 0.04942 Total loss: 1.14138 timestamp: 1655037818.8067193 iteration: 38175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1358 FastRCNN class loss: 0.10324 FastRCNN total loss: 0.23904 L1 loss: 0.0000e+00 L2 loss: 0.63396 Learning rate: 0.02 Mask loss: 0.16459 RPN box loss: 0.01552 RPN score loss: 0.00265 RPN total loss: 0.01817 Total loss: 1.05576 timestamp: 1655037822.0995915 iteration: 38180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.13196 FastRCNN total loss: 0.24294 L1 loss: 0.0000e+00 L2 loss: 0.63388 Learning rate: 0.02 Mask loss: 0.15954 RPN box loss: 0.02865 RPN score loss: 0.01117 RPN total loss: 0.03982 Total loss: 1.07618 timestamp: 1655037825.392148 iteration: 38185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13394 FastRCNN class loss: 0.06363 FastRCNN total loss: 0.19756 L1 loss: 0.0000e+00 L2 loss: 0.63378 Learning rate: 0.02 Mask loss: 0.14323 RPN box loss: 0.00847 RPN score loss: 0.0024 RPN total loss: 0.01087 Total loss: 0.98545 timestamp: 1655037828.7039928 iteration: 38190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.1135 FastRCNN total loss: 0.23346 L1 loss: 0.0000e+00 L2 loss: 0.6337 Learning rate: 0.02 Mask loss: 0.1494 RPN box loss: 0.01959 RPN score loss: 0.00717 RPN total loss: 0.02676 Total loss: 1.04333 timestamp: 1655037831.886593 iteration: 38195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.03838 FastRCNN total loss: 0.11749 L1 loss: 0.0000e+00 L2 loss: 0.63365 Learning rate: 0.02 Mask loss: 0.12915 RPN box loss: 0.03028 RPN score loss: 0.00437 RPN total loss: 0.03464 Total loss: 0.91493 timestamp: 1655037835.1296434 iteration: 38200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0828 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.15593 L1 loss: 0.0000e+00 L2 loss: 0.63355 Learning rate: 0.02 Mask loss: 0.12051 RPN box loss: 0.02364 RPN score loss: 0.01315 RPN total loss: 0.03679 Total loss: 0.94678 timestamp: 1655037838.3688414 iteration: 38205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14549 FastRCNN class loss: 0.1012 FastRCNN total loss: 0.24669 L1 loss: 0.0000e+00 L2 loss: 0.63347 Learning rate: 0.02 Mask loss: 0.14472 RPN box loss: 0.07618 RPN score loss: 0.00816 RPN total loss: 0.08434 Total loss: 1.10923 timestamp: 1655037841.697596 iteration: 38210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18349 FastRCNN class loss: 0.07301 FastRCNN total loss: 0.2565 L1 loss: 0.0000e+00 L2 loss: 0.63339 Learning rate: 0.02 Mask loss: 0.15485 RPN box loss: 0.04113 RPN score loss: 0.00621 RPN total loss: 0.04735 Total loss: 1.0921 timestamp: 1655037844.9424205 iteration: 38215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10644 FastRCNN class loss: 0.04392 FastRCNN total loss: 0.15036 L1 loss: 0.0000e+00 L2 loss: 0.63328 Learning rate: 0.02 Mask loss: 0.08515 RPN box loss: 0.03711 RPN score loss: 0.00331 RPN total loss: 0.04042 Total loss: 0.90921 timestamp: 1655037848.213284 iteration: 38220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11853 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 0.6332 Learning rate: 0.02 Mask loss: 0.15952 RPN box loss: 0.02611 RPN score loss: 0.00261 RPN total loss: 0.02872 Total loss: 1.00987 timestamp: 1655037851.5009677 iteration: 38225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08769 FastRCNN class loss: 0.06272 FastRCNN total loss: 0.15042 L1 loss: 0.0000e+00 L2 loss: 0.63314 Learning rate: 0.02 Mask loss: 0.1462 RPN box loss: 0.02557 RPN score loss: 0.01122 RPN total loss: 0.03679 Total loss: 0.96655 timestamp: 1655037854.7917895 iteration: 38230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15069 FastRCNN class loss: 0.08844 FastRCNN total loss: 0.23913 L1 loss: 0.0000e+00 L2 loss: 0.63306 Learning rate: 0.02 Mask loss: 0.15693 RPN box loss: 0.03106 RPN score loss: 0.00563 RPN total loss: 0.03669 Total loss: 1.06581 timestamp: 1655037858.0072994 iteration: 38235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10603 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.17027 L1 loss: 0.0000e+00 L2 loss: 0.63299 Learning rate: 0.02 Mask loss: 0.14876 RPN box loss: 0.03801 RPN score loss: 0.00335 RPN total loss: 0.04136 Total loss: 0.99338 timestamp: 1655037861.2897916 iteration: 38240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12499 FastRCNN class loss: 0.08519 FastRCNN total loss: 0.21018 L1 loss: 0.0000e+00 L2 loss: 0.63289 Learning rate: 0.02 Mask loss: 0.19685 RPN box loss: 0.02446 RPN score loss: 0.00447 RPN total loss: 0.02893 Total loss: 1.06885 timestamp: 1655037864.5813842 iteration: 38245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08747 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.63277 Learning rate: 0.02 Mask loss: 0.12841 RPN box loss: 0.01292 RPN score loss: 0.0039 RPN total loss: 0.01681 Total loss: 0.93305 timestamp: 1655037867.845019 iteration: 38250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19014 FastRCNN class loss: 0.11175 FastRCNN total loss: 0.30189 L1 loss: 0.0000e+00 L2 loss: 0.63268 Learning rate: 0.02 Mask loss: 0.21611 RPN box loss: 0.03601 RPN score loss: 0.01398 RPN total loss: 0.04999 Total loss: 1.20067 timestamp: 1655037871.1662798 iteration: 38255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.04674 FastRCNN total loss: 0.18013 L1 loss: 0.0000e+00 L2 loss: 0.63259 Learning rate: 0.02 Mask loss: 0.12163 RPN box loss: 0.02521 RPN score loss: 0.00542 RPN total loss: 0.03064 Total loss: 0.96499 timestamp: 1655037874.4470944 iteration: 38260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10637 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.18305 L1 loss: 0.0000e+00 L2 loss: 0.6325 Learning rate: 0.02 Mask loss: 0.12873 RPN box loss: 0.02941 RPN score loss: 0.00531 RPN total loss: 0.03472 Total loss: 0.97901 timestamp: 1655037877.6720746 iteration: 38265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15016 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.21871 L1 loss: 0.0000e+00 L2 loss: 0.63242 Learning rate: 0.02 Mask loss: 0.14453 RPN box loss: 0.01941 RPN score loss: 0.0108 RPN total loss: 0.0302 Total loss: 1.02587 timestamp: 1655037880.890631 iteration: 38270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16005 FastRCNN class loss: 0.11665 FastRCNN total loss: 0.2767 L1 loss: 0.0000e+00 L2 loss: 0.63233 Learning rate: 0.02 Mask loss: 0.3115 RPN box loss: 0.04099 RPN score loss: 0.00781 RPN total loss: 0.0488 Total loss: 1.26933 timestamp: 1655037884.126575 iteration: 38275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14085 FastRCNN class loss: 0.08351 FastRCNN total loss: 0.22436 L1 loss: 0.0000e+00 L2 loss: 0.63224 Learning rate: 0.02 Mask loss: 0.1662 RPN box loss: 0.03374 RPN score loss: 0.00833 RPN total loss: 0.04207 Total loss: 1.06487 timestamp: 1655037887.3298085 iteration: 38280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20329 FastRCNN class loss: 0.10396 FastRCNN total loss: 0.30725 L1 loss: 0.0000e+00 L2 loss: 0.63217 Learning rate: 0.02 Mask loss: 0.26728 RPN box loss: 0.01286 RPN score loss: 0.0043 RPN total loss: 0.01716 Total loss: 1.22385 timestamp: 1655037890.5786266 iteration: 38285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13243 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.20042 L1 loss: 0.0000e+00 L2 loss: 0.63207 Learning rate: 0.02 Mask loss: 0.13752 RPN box loss: 0.01332 RPN score loss: 0.00376 RPN total loss: 0.01707 Total loss: 0.98708 timestamp: 1655037893.8388143 iteration: 38290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14491 FastRCNN class loss: 0.09902 FastRCNN total loss: 0.24393 L1 loss: 0.0000e+00 L2 loss: 0.63199 Learning rate: 0.02 Mask loss: 0.2243 RPN box loss: 0.03095 RPN score loss: 0.00385 RPN total loss: 0.0348 Total loss: 1.13503 timestamp: 1655037897.1687615 iteration: 38295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12857 FastRCNN class loss: 0.12263 FastRCNN total loss: 0.2512 L1 loss: 0.0000e+00 L2 loss: 0.63189 Learning rate: 0.02 Mask loss: 0.1999 RPN box loss: 0.03081 RPN score loss: 0.01061 RPN total loss: 0.04143 Total loss: 1.12442 timestamp: 1655037900.4431345 iteration: 38300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15494 FastRCNN class loss: 0.1839 FastRCNN total loss: 0.33883 L1 loss: 0.0000e+00 L2 loss: 0.63181 Learning rate: 0.02 Mask loss: 0.20391 RPN box loss: 0.05183 RPN score loss: 0.01728 RPN total loss: 0.06911 Total loss: 1.24366 timestamp: 1655037903.6964483 iteration: 38305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18205 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.25643 L1 loss: 0.0000e+00 L2 loss: 0.63174 Learning rate: 0.02 Mask loss: 0.11462 RPN box loss: 0.06591 RPN score loss: 0.00703 RPN total loss: 0.07294 Total loss: 1.07573 timestamp: 1655037906.9845176 iteration: 38310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18028 FastRCNN class loss: 0.12706 FastRCNN total loss: 0.30735 L1 loss: 0.0000e+00 L2 loss: 0.63165 Learning rate: 0.02 Mask loss: 0.21644 RPN box loss: 0.05102 RPN score loss: 0.02013 RPN total loss: 0.07115 Total loss: 1.22659 timestamp: 1655037910.2517738 iteration: 38315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18254 FastRCNN class loss: 0.1436 FastRCNN total loss: 0.32613 L1 loss: 0.0000e+00 L2 loss: 0.63158 Learning rate: 0.02 Mask loss: 0.17771 RPN box loss: 0.05159 RPN score loss: 0.01016 RPN total loss: 0.06175 Total loss: 1.19718 timestamp: 1655037913.5308871 iteration: 38320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1456 FastRCNN class loss: 0.11702 FastRCNN total loss: 0.26263 L1 loss: 0.0000e+00 L2 loss: 0.63148 Learning rate: 0.02 Mask loss: 0.15822 RPN box loss: 0.02029 RPN score loss: 0.01037 RPN total loss: 0.03066 Total loss: 1.08299 timestamp: 1655037916.824823 iteration: 38325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10667 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.17697 L1 loss: 0.0000e+00 L2 loss: 0.63142 Learning rate: 0.02 Mask loss: 0.09866 RPN box loss: 0.03414 RPN score loss: 0.00748 RPN total loss: 0.04162 Total loss: 0.94867 timestamp: 1655037920.1052291 iteration: 38330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.08733 FastRCNN total loss: 0.19982 L1 loss: 0.0000e+00 L2 loss: 0.63135 Learning rate: 0.02 Mask loss: 0.14295 RPN box loss: 0.01071 RPN score loss: 0.00291 RPN total loss: 0.01362 Total loss: 0.98775 timestamp: 1655037923.426798 iteration: 38335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10046 FastRCNN class loss: 0.07887 FastRCNN total loss: 0.17933 L1 loss: 0.0000e+00 L2 loss: 0.63126 Learning rate: 0.02 Mask loss: 0.15345 RPN box loss: 0.06154 RPN score loss: 0.01194 RPN total loss: 0.07348 Total loss: 1.03751 timestamp: 1655037926.7020018 iteration: 38340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13202 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.21565 L1 loss: 0.0000e+00 L2 loss: 0.63116 Learning rate: 0.02 Mask loss: 0.19535 RPN box loss: 0.02601 RPN score loss: 0.00454 RPN total loss: 0.03055 Total loss: 1.07272 timestamp: 1655037929.9187481 iteration: 38345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13667 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.23013 L1 loss: 0.0000e+00 L2 loss: 0.63109 Learning rate: 0.02 Mask loss: 0.16862 RPN box loss: 0.02751 RPN score loss: 0.00389 RPN total loss: 0.0314 Total loss: 1.06124 timestamp: 1655037933.1613374 iteration: 38350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19051 FastRCNN class loss: 0.08193 FastRCNN total loss: 0.27244 L1 loss: 0.0000e+00 L2 loss: 0.63103 Learning rate: 0.02 Mask loss: 0.23177 RPN box loss: 0.02385 RPN score loss: 0.00392 RPN total loss: 0.02777 Total loss: 1.16302 timestamp: 1655037936.3908825 iteration: 38355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2125 FastRCNN class loss: 0.07473 FastRCNN total loss: 0.28724 L1 loss: 0.0000e+00 L2 loss: 0.63096 Learning rate: 0.02 Mask loss: 0.1622 RPN box loss: 0.02295 RPN score loss: 0.00743 RPN total loss: 0.03038 Total loss: 1.11078 timestamp: 1655037939.6540487 iteration: 38360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10972 FastRCNN class loss: 0.08854 FastRCNN total loss: 0.19827 L1 loss: 0.0000e+00 L2 loss: 0.63085 Learning rate: 0.02 Mask loss: 0.13365 RPN box loss: 0.01325 RPN score loss: 0.0039 RPN total loss: 0.01715 Total loss: 0.97992 timestamp: 1655037942.9478772 iteration: 38365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.042 FastRCNN total loss: 0.12076 L1 loss: 0.0000e+00 L2 loss: 0.63075 Learning rate: 0.02 Mask loss: 0.11541 RPN box loss: 0.01706 RPN score loss: 0.00312 RPN total loss: 0.02018 Total loss: 0.88711 timestamp: 1655037946.154842 iteration: 38370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13659 FastRCNN class loss: 0.10775 FastRCNN total loss: 0.24433 L1 loss: 0.0000e+00 L2 loss: 0.63065 Learning rate: 0.02 Mask loss: 0.14303 RPN box loss: 0.01222 RPN score loss: 0.00465 RPN total loss: 0.01687 Total loss: 1.0349 timestamp: 1655037949.4481733 iteration: 38375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12082 FastRCNN class loss: 0.05052 FastRCNN total loss: 0.17134 L1 loss: 0.0000e+00 L2 loss: 0.63057 Learning rate: 0.02 Mask loss: 0.14245 RPN box loss: 0.0066 RPN score loss: 0.00403 RPN total loss: 0.01062 Total loss: 0.95499 timestamp: 1655037952.71248 iteration: 38380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13933 FastRCNN class loss: 0.09314 FastRCNN total loss: 0.23247 L1 loss: 0.0000e+00 L2 loss: 0.6305 Learning rate: 0.02 Mask loss: 0.15917 RPN box loss: 0.05862 RPN score loss: 0.01131 RPN total loss: 0.06993 Total loss: 1.09207 timestamp: 1655037956.0257833 iteration: 38385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25779 FastRCNN class loss: 0.09211 FastRCNN total loss: 0.3499 L1 loss: 0.0000e+00 L2 loss: 0.63042 Learning rate: 0.02 Mask loss: 0.19808 RPN box loss: 0.01613 RPN score loss: 0.00975 RPN total loss: 0.02588 Total loss: 1.20428 timestamp: 1655037959.312328 iteration: 38390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1195 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.19373 L1 loss: 0.0000e+00 L2 loss: 0.63037 Learning rate: 0.02 Mask loss: 0.16159 RPN box loss: 0.0341 RPN score loss: 0.01192 RPN total loss: 0.04602 Total loss: 1.0317 timestamp: 1655037962.5966978 iteration: 38395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.03904 FastRCNN total loss: 0.12221 L1 loss: 0.0000e+00 L2 loss: 0.63026 Learning rate: 0.02 Mask loss: 0.09409 RPN box loss: 0.03857 RPN score loss: 0.00494 RPN total loss: 0.0435 Total loss: 0.89006 timestamp: 1655037965.907633 iteration: 38400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20838 FastRCNN class loss: 0.10578 FastRCNN total loss: 0.31416 L1 loss: 0.0000e+00 L2 loss: 0.63016 Learning rate: 0.02 Mask loss: 0.18516 RPN box loss: 0.07677 RPN score loss: 0.01891 RPN total loss: 0.09568 Total loss: 1.22516 timestamp: 1655037969.1657429 iteration: 38405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1181 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.17806 L1 loss: 0.0000e+00 L2 loss: 0.63009 Learning rate: 0.02 Mask loss: 0.10709 RPN box loss: 0.00555 RPN score loss: 0.00351 RPN total loss: 0.00906 Total loss: 0.9243 timestamp: 1655037972.3940828 iteration: 38410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17927 FastRCNN class loss: 0.14636 FastRCNN total loss: 0.32563 L1 loss: 0.0000e+00 L2 loss: 0.63 Learning rate: 0.02 Mask loss: 0.1833 RPN box loss: 0.02324 RPN score loss: 0.02362 RPN total loss: 0.04687 Total loss: 1.18579 timestamp: 1655037975.7120218 iteration: 38415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17805 FastRCNN class loss: 0.14763 FastRCNN total loss: 0.32568 L1 loss: 0.0000e+00 L2 loss: 0.62991 Learning rate: 0.02 Mask loss: 0.21824 RPN box loss: 0.05976 RPN score loss: 0.0068 RPN total loss: 0.06656 Total loss: 1.24039 timestamp: 1655037979.0403192 iteration: 38420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12 FastRCNN class loss: 0.09903 FastRCNN total loss: 0.21903 L1 loss: 0.0000e+00 L2 loss: 0.62984 Learning rate: 0.02 Mask loss: 0.19642 RPN box loss: 0.06289 RPN score loss: 0.01434 RPN total loss: 0.07723 Total loss: 1.12253 timestamp: 1655037982.253537 iteration: 38425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.16307 L1 loss: 0.0000e+00 L2 loss: 0.62977 Learning rate: 0.02 Mask loss: 0.07982 RPN box loss: 0.03788 RPN score loss: 0.00231 RPN total loss: 0.04019 Total loss: 0.91285 timestamp: 1655037985.57021 iteration: 38430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15984 FastRCNN class loss: 0.10069 FastRCNN total loss: 0.26053 L1 loss: 0.0000e+00 L2 loss: 0.6297 Learning rate: 0.02 Mask loss: 0.20695 RPN box loss: 0.02425 RPN score loss: 0.00822 RPN total loss: 0.03247 Total loss: 1.12965 timestamp: 1655037988.811942 iteration: 38435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17319 FastRCNN class loss: 0.07874 FastRCNN total loss: 0.25193 L1 loss: 0.0000e+00 L2 loss: 0.62963 Learning rate: 0.02 Mask loss: 0.19761 RPN box loss: 0.03521 RPN score loss: 0.01351 RPN total loss: 0.04873 Total loss: 1.12789 timestamp: 1655037992.1045785 iteration: 38440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.05839 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 0.62956 Learning rate: 0.02 Mask loss: 0.13535 RPN box loss: 0.00953 RPN score loss: 0.00431 RPN total loss: 0.01384 Total loss: 0.92065 timestamp: 1655037995.3532996 iteration: 38445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13651 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.19079 L1 loss: 0.0000e+00 L2 loss: 0.62944 Learning rate: 0.02 Mask loss: 0.1054 RPN box loss: 0.02536 RPN score loss: 0.00566 RPN total loss: 0.03102 Total loss: 0.95665 timestamp: 1655037998.6273587 iteration: 38450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20433 FastRCNN class loss: 0.08773 FastRCNN total loss: 0.29206 L1 loss: 0.0000e+00 L2 loss: 0.62934 Learning rate: 0.02 Mask loss: 0.20453 RPN box loss: 0.0555 RPN score loss: 0.00528 RPN total loss: 0.06078 Total loss: 1.18671 timestamp: 1655038001.8356435 iteration: 38455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13819 FastRCNN class loss: 0.084 FastRCNN total loss: 0.22219 L1 loss: 0.0000e+00 L2 loss: 0.62925 Learning rate: 0.02 Mask loss: 0.1436 RPN box loss: 0.05837 RPN score loss: 0.01456 RPN total loss: 0.07292 Total loss: 1.06796 timestamp: 1655038005.1207225 iteration: 38460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12647 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.2106 L1 loss: 0.0000e+00 L2 loss: 0.62918 Learning rate: 0.02 Mask loss: 0.30898 RPN box loss: 0.04322 RPN score loss: 0.00657 RPN total loss: 0.04979 Total loss: 1.19856 timestamp: 1655038008.3619359 iteration: 38465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09705 FastRCNN class loss: 0.0521 FastRCNN total loss: 0.14915 L1 loss: 0.0000e+00 L2 loss: 0.62908 Learning rate: 0.02 Mask loss: 0.10922 RPN box loss: 0.01903 RPN score loss: 0.00799 RPN total loss: 0.02701 Total loss: 0.91446 timestamp: 1655038011.63694 iteration: 38470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12112 FastRCNN class loss: 0.05967 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 0.629 Learning rate: 0.02 Mask loss: 0.19458 RPN box loss: 0.04675 RPN score loss: 0.01048 RPN total loss: 0.05723 Total loss: 1.06159 timestamp: 1655038014.8211634 iteration: 38475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.07732 FastRCNN total loss: 0.16547 L1 loss: 0.0000e+00 L2 loss: 0.6289 Learning rate: 0.02 Mask loss: 0.12993 RPN box loss: 0.02475 RPN score loss: 0.00207 RPN total loss: 0.02682 Total loss: 0.95112 timestamp: 1655038018.0176852 iteration: 38480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13936 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.21567 L1 loss: 0.0000e+00 L2 loss: 0.62881 Learning rate: 0.02 Mask loss: 0.17151 RPN box loss: 0.01973 RPN score loss: 0.02101 RPN total loss: 0.04074 Total loss: 1.05673 timestamp: 1655038021.2767546 iteration: 38485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14077 FastRCNN class loss: 0.07582 FastRCNN total loss: 0.21659 L1 loss: 0.0000e+00 L2 loss: 0.62872 Learning rate: 0.02 Mask loss: 0.14981 RPN box loss: 0.05332 RPN score loss: 0.00999 RPN total loss: 0.06331 Total loss: 1.05843 timestamp: 1655038024.505915 iteration: 38490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08279 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.14544 L1 loss: 0.0000e+00 L2 loss: 0.62867 Learning rate: 0.02 Mask loss: 0.10824 RPN box loss: 0.07713 RPN score loss: 0.00497 RPN total loss: 0.0821 Total loss: 0.96444 timestamp: 1655038027.7492926 iteration: 38495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10382 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.1694 L1 loss: 0.0000e+00 L2 loss: 0.62857 Learning rate: 0.02 Mask loss: 0.08415 RPN box loss: 0.01744 RPN score loss: 0.00199 RPN total loss: 0.01943 Total loss: 0.90155 timestamp: 1655038031.0165918 iteration: 38500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12074 FastRCNN class loss: 0.1058 FastRCNN total loss: 0.22655 L1 loss: 0.0000e+00 L2 loss: 0.62845 Learning rate: 0.02 Mask loss: 0.22295 RPN box loss: 0.05931 RPN score loss: 0.00452 RPN total loss: 0.06383 Total loss: 1.14178 timestamp: 1655038034.2869892 iteration: 38505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.1543 L1 loss: 0.0000e+00 L2 loss: 0.62838 Learning rate: 0.02 Mask loss: 0.1788 RPN box loss: 0.01641 RPN score loss: 0.00778 RPN total loss: 0.02419 Total loss: 0.98566 timestamp: 1655038037.5389988 iteration: 38510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18959 FastRCNN class loss: 0.0841 FastRCNN total loss: 0.27369 L1 loss: 0.0000e+00 L2 loss: 0.62832 Learning rate: 0.02 Mask loss: 0.25284 RPN box loss: 0.01012 RPN score loss: 0.00779 RPN total loss: 0.01791 Total loss: 1.17277 timestamp: 1655038040.8057418 iteration: 38515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.05249 FastRCNN total loss: 0.15312 L1 loss: 0.0000e+00 L2 loss: 0.62825 Learning rate: 0.02 Mask loss: 0.10497 RPN box loss: 0.04429 RPN score loss: 0.00483 RPN total loss: 0.04912 Total loss: 0.93546 timestamp: 1655038044.0784214 iteration: 38520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13817 FastRCNN class loss: 0.05109 FastRCNN total loss: 0.18927 L1 loss: 0.0000e+00 L2 loss: 0.62816 Learning rate: 0.02 Mask loss: 0.16504 RPN box loss: 0.00724 RPN score loss: 0.0037 RPN total loss: 0.01094 Total loss: 0.99341 timestamp: 1655038047.380571 iteration: 38525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10741 FastRCNN class loss: 0.05433 FastRCNN total loss: 0.16174 L1 loss: 0.0000e+00 L2 loss: 0.62808 Learning rate: 0.02 Mask loss: 0.1032 RPN box loss: 0.01743 RPN score loss: 0.00232 RPN total loss: 0.01975 Total loss: 0.91277 timestamp: 1655038050.5605712 iteration: 38530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17828 FastRCNN class loss: 0.08735 FastRCNN total loss: 0.26563 L1 loss: 0.0000e+00 L2 loss: 0.62799 Learning rate: 0.02 Mask loss: 0.1483 RPN box loss: 0.01886 RPN score loss: 0.00387 RPN total loss: 0.02273 Total loss: 1.06464 timestamp: 1655038053.8251095 iteration: 38535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11479 FastRCNN class loss: 0.10852 FastRCNN total loss: 0.22331 L1 loss: 0.0000e+00 L2 loss: 0.62788 Learning rate: 0.02 Mask loss: 0.24642 RPN box loss: 0.01968 RPN score loss: 0.00236 RPN total loss: 0.02204 Total loss: 1.11965 timestamp: 1655038057.0272486 iteration: 38540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23957 FastRCNN class loss: 0.08496 FastRCNN total loss: 0.32454 L1 loss: 0.0000e+00 L2 loss: 0.62779 Learning rate: 0.02 Mask loss: 0.17628 RPN box loss: 0.0295 RPN score loss: 0.00191 RPN total loss: 0.03141 Total loss: 1.16001 timestamp: 1655038060.366307 iteration: 38545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09944 FastRCNN class loss: 0.06622 FastRCNN total loss: 0.16566 L1 loss: 0.0000e+00 L2 loss: 0.62769 Learning rate: 0.02 Mask loss: 0.16331 RPN box loss: 0.01329 RPN score loss: 0.00905 RPN total loss: 0.02234 Total loss: 0.97901 timestamp: 1655038063.6066763 iteration: 38550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12966 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.20931 L1 loss: 0.0000e+00 L2 loss: 0.62761 Learning rate: 0.02 Mask loss: 0.18865 RPN box loss: 0.02412 RPN score loss: 0.01288 RPN total loss: 0.037 Total loss: 1.06258 timestamp: 1655038066.9357278 iteration: 38555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17153 FastRCNN class loss: 0.10554 FastRCNN total loss: 0.27707 L1 loss: 0.0000e+00 L2 loss: 0.62754 Learning rate: 0.02 Mask loss: 0.20441 RPN box loss: 0.07505 RPN score loss: 0.01512 RPN total loss: 0.09017 Total loss: 1.19919 timestamp: 1655038070.2497926 iteration: 38560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17859 FastRCNN class loss: 0.1149 FastRCNN total loss: 0.29349 L1 loss: 0.0000e+00 L2 loss: 0.62745 Learning rate: 0.02 Mask loss: 0.26452 RPN box loss: 0.04044 RPN score loss: 0.01354 RPN total loss: 0.05398 Total loss: 1.23944 timestamp: 1655038073.4533982 iteration: 38565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.06863 FastRCNN total loss: 0.16912 L1 loss: 0.0000e+00 L2 loss: 0.62739 Learning rate: 0.02 Mask loss: 0.1409 RPN box loss: 0.0235 RPN score loss: 0.00161 RPN total loss: 0.0251 Total loss: 0.96252 timestamp: 1655038076.7548473 iteration: 38570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11688 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.19762 L1 loss: 0.0000e+00 L2 loss: 0.62733 Learning rate: 0.02 Mask loss: 0.11591 RPN box loss: 0.04671 RPN score loss: 0.00455 RPN total loss: 0.05126 Total loss: 0.99212 timestamp: 1655038080.0862243 iteration: 38575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14337 FastRCNN class loss: 0.08339 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.62724 Learning rate: 0.02 Mask loss: 0.1359 RPN box loss: 0.06256 RPN score loss: 0.00934 RPN total loss: 0.0719 Total loss: 1.0618 timestamp: 1655038083.3856351 iteration: 38580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09993 FastRCNN class loss: 0.09062 FastRCNN total loss: 0.19055 L1 loss: 0.0000e+00 L2 loss: 0.62715 Learning rate: 0.02 Mask loss: 0.1448 RPN box loss: 0.0241 RPN score loss: 0.00915 RPN total loss: 0.03325 Total loss: 0.99575 timestamp: 1655038086.727993 iteration: 38585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13905 FastRCNN class loss: 0.10206 FastRCNN total loss: 0.24111 L1 loss: 0.0000e+00 L2 loss: 0.62707 Learning rate: 0.02 Mask loss: 0.16481 RPN box loss: 0.04398 RPN score loss: 0.01364 RPN total loss: 0.05763 Total loss: 1.09062 timestamp: 1655038090.0290322 iteration: 38590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15159 FastRCNN class loss: 0.1188 FastRCNN total loss: 0.2704 L1 loss: 0.0000e+00 L2 loss: 0.62696 Learning rate: 0.02 Mask loss: 0.23881 RPN box loss: 0.03458 RPN score loss: 0.00458 RPN total loss: 0.03915 Total loss: 1.17533 timestamp: 1655038093.3055623 iteration: 38595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11202 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 0.62689 Learning rate: 0.02 Mask loss: 0.17064 RPN box loss: 0.01022 RPN score loss: 0.00363 RPN total loss: 0.01385 Total loss: 0.99684 timestamp: 1655038096.6487691 iteration: 38600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19814 FastRCNN class loss: 0.14112 FastRCNN total loss: 0.33925 L1 loss: 0.0000e+00 L2 loss: 0.62682 Learning rate: 0.02 Mask loss: 0.21024 RPN box loss: 0.05273 RPN score loss: 0.01617 RPN total loss: 0.0689 Total loss: 1.24521 timestamp: 1655038099.942748 iteration: 38605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.10439 FastRCNN total loss: 0.18622 L1 loss: 0.0000e+00 L2 loss: 0.6267 Learning rate: 0.02 Mask loss: 0.16946 RPN box loss: 0.0233 RPN score loss: 0.01026 RPN total loss: 0.03355 Total loss: 1.01593 timestamp: 1655038103.2290812 iteration: 38610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08165 FastRCNN class loss: 0.05441 FastRCNN total loss: 0.13606 L1 loss: 0.0000e+00 L2 loss: 0.62665 Learning rate: 0.02 Mask loss: 0.13671 RPN box loss: 0.02853 RPN score loss: 0.00802 RPN total loss: 0.03654 Total loss: 0.93595 timestamp: 1655038106.433725 iteration: 38615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.19568 L1 loss: 0.0000e+00 L2 loss: 0.6266 Learning rate: 0.02 Mask loss: 0.14083 RPN box loss: 0.05353 RPN score loss: 0.00882 RPN total loss: 0.06235 Total loss: 1.02545 timestamp: 1655038109.737948 iteration: 38620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10228 FastRCNN class loss: 0.06946 FastRCNN total loss: 0.17174 L1 loss: 0.0000e+00 L2 loss: 0.6265 Learning rate: 0.02 Mask loss: 0.11001 RPN box loss: 0.05698 RPN score loss: 0.00926 RPN total loss: 0.06623 Total loss: 0.97447 timestamp: 1655038112.9892414 iteration: 38625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11917 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.18384 L1 loss: 0.0000e+00 L2 loss: 0.6264 Learning rate: 0.02 Mask loss: 0.19466 RPN box loss: 0.0152 RPN score loss: 0.00602 RPN total loss: 0.02122 Total loss: 1.02612 timestamp: 1655038116.2824504 iteration: 38630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10149 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.158 L1 loss: 0.0000e+00 L2 loss: 0.6263 Learning rate: 0.02 Mask loss: 0.14164 RPN box loss: 0.01179 RPN score loss: 0.00227 RPN total loss: 0.01406 Total loss: 0.94 timestamp: 1655038119.5475488 iteration: 38635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19694 FastRCNN class loss: 0.11785 FastRCNN total loss: 0.31479 L1 loss: 0.0000e+00 L2 loss: 0.62625 Learning rate: 0.02 Mask loss: 0.18252 RPN box loss: 0.11198 RPN score loss: 0.01967 RPN total loss: 0.13165 Total loss: 1.25521 timestamp: 1655038122.804222 iteration: 38640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14385 FastRCNN class loss: 0.08004 FastRCNN total loss: 0.22389 L1 loss: 0.0000e+00 L2 loss: 0.62618 Learning rate: 0.02 Mask loss: 0.15424 RPN box loss: 0.0166 RPN score loss: 0.00581 RPN total loss: 0.02241 Total loss: 1.02672 timestamp: 1655038126.119792 iteration: 38645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11515 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.62612 Learning rate: 0.02 Mask loss: 0.12138 RPN box loss: 0.04393 RPN score loss: 0.01181 RPN total loss: 0.05574 Total loss: 0.97681 timestamp: 1655038129.3881285 iteration: 38650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12206 FastRCNN class loss: 0.09242 FastRCNN total loss: 0.21448 L1 loss: 0.0000e+00 L2 loss: 0.62605 Learning rate: 0.02 Mask loss: 0.1418 RPN box loss: 0.01615 RPN score loss: 0.00238 RPN total loss: 0.01853 Total loss: 1.00086 timestamp: 1655038132.6327598 iteration: 38655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18986 FastRCNN class loss: 0.13381 FastRCNN total loss: 0.32368 L1 loss: 0.0000e+00 L2 loss: 0.62593 Learning rate: 0.02 Mask loss: 0.23035 RPN box loss: 0.02843 RPN score loss: 0.01138 RPN total loss: 0.03981 Total loss: 1.21976 timestamp: 1655038135.9145188 iteration: 38660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.209 FastRCNN class loss: 0.18094 FastRCNN total loss: 0.38994 L1 loss: 0.0000e+00 L2 loss: 0.62583 Learning rate: 0.02 Mask loss: 0.22355 RPN box loss: 0.03219 RPN score loss: 0.01186 RPN total loss: 0.04405 Total loss: 1.28337 timestamp: 1655038139.0825748 iteration: 38665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0765 FastRCNN class loss: 0.04942 FastRCNN total loss: 0.12592 L1 loss: 0.0000e+00 L2 loss: 0.62575 Learning rate: 0.02 Mask loss: 0.12595 RPN box loss: 0.02278 RPN score loss: 0.00335 RPN total loss: 0.02614 Total loss: 0.90376 timestamp: 1655038142.2770958 iteration: 38670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25967 FastRCNN class loss: 0.13306 FastRCNN total loss: 0.39273 L1 loss: 0.0000e+00 L2 loss: 0.62567 Learning rate: 0.02 Mask loss: 0.21729 RPN box loss: 0.02846 RPN score loss: 0.00908 RPN total loss: 0.03754 Total loss: 1.27323 timestamp: 1655038145.5823672 iteration: 38675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17494 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.24742 L1 loss: 0.0000e+00 L2 loss: 0.62557 Learning rate: 0.02 Mask loss: 0.14442 RPN box loss: 0.02274 RPN score loss: 0.00646 RPN total loss: 0.02919 Total loss: 1.0466 timestamp: 1655038148.820206 iteration: 38680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13481 FastRCNN class loss: 0.05221 FastRCNN total loss: 0.18702 L1 loss: 0.0000e+00 L2 loss: 0.62551 Learning rate: 0.02 Mask loss: 0.09203 RPN box loss: 0.01362 RPN score loss: 0.00345 RPN total loss: 0.01707 Total loss: 0.92162 timestamp: 1655038152.1779275 iteration: 38685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18609 FastRCNN class loss: 0.16044 FastRCNN total loss: 0.34652 L1 loss: 0.0000e+00 L2 loss: 0.62544 Learning rate: 0.02 Mask loss: 0.17414 RPN box loss: 0.02996 RPN score loss: 0.00996 RPN total loss: 0.03992 Total loss: 1.18602 timestamp: 1655038155.4990017 iteration: 38690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09904 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.18343 L1 loss: 0.0000e+00 L2 loss: 0.62535 Learning rate: 0.02 Mask loss: 0.14712 RPN box loss: 0.00837 RPN score loss: 0.00264 RPN total loss: 0.01101 Total loss: 0.96691 timestamp: 1655038158.7772408 iteration: 38695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11141 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.1813 L1 loss: 0.0000e+00 L2 loss: 0.62525 Learning rate: 0.02 Mask loss: 0.14575 RPN box loss: 0.01156 RPN score loss: 0.00669 RPN total loss: 0.01826 Total loss: 0.97056 timestamp: 1655038162.064499 iteration: 38700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16201 FastRCNN class loss: 0.08859 FastRCNN total loss: 0.2506 L1 loss: 0.0000e+00 L2 loss: 0.62517 Learning rate: 0.02 Mask loss: 0.16537 RPN box loss: 0.01783 RPN score loss: 0.01166 RPN total loss: 0.02949 Total loss: 1.07063 timestamp: 1655038165.3020823 iteration: 38705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14939 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.22625 L1 loss: 0.0000e+00 L2 loss: 0.6251 Learning rate: 0.02 Mask loss: 0.15323 RPN box loss: 0.02956 RPN score loss: 0.00206 RPN total loss: 0.03161 Total loss: 1.03619 timestamp: 1655038168.5521202 iteration: 38710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11512 FastRCNN class loss: 0.04654 FastRCNN total loss: 0.16166 L1 loss: 0.0000e+00 L2 loss: 0.62502 Learning rate: 0.02 Mask loss: 0.1266 RPN box loss: 0.00483 RPN score loss: 0.00223 RPN total loss: 0.00706 Total loss: 0.92034 timestamp: 1655038171.8139744 iteration: 38715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16814 FastRCNN class loss: 0.0988 FastRCNN total loss: 0.26694 L1 loss: 0.0000e+00 L2 loss: 0.62494 Learning rate: 0.02 Mask loss: 0.17858 RPN box loss: 0.04938 RPN score loss: 0.01509 RPN total loss: 0.06446 Total loss: 1.13493 timestamp: 1655038175.1369953 iteration: 38720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21243 FastRCNN class loss: 0.10243 FastRCNN total loss: 0.31485 L1 loss: 0.0000e+00 L2 loss: 0.62486 Learning rate: 0.02 Mask loss: 0.16516 RPN box loss: 0.03236 RPN score loss: 0.00999 RPN total loss: 0.04235 Total loss: 1.14722 timestamp: 1655038178.42244 iteration: 38725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06571 FastRCNN class loss: 0.06773 FastRCNN total loss: 0.13344 L1 loss: 0.0000e+00 L2 loss: 0.62479 Learning rate: 0.02 Mask loss: 0.10181 RPN box loss: 0.00951 RPN score loss: 0.00414 RPN total loss: 0.01365 Total loss: 0.87369 timestamp: 1655038181.6603205 iteration: 38730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24271 FastRCNN class loss: 0.14592 FastRCNN total loss: 0.38864 L1 loss: 0.0000e+00 L2 loss: 0.62469 Learning rate: 0.02 Mask loss: 0.15255 RPN box loss: 0.03702 RPN score loss: 0.01112 RPN total loss: 0.04814 Total loss: 1.21402 timestamp: 1655038184.9555092 iteration: 38735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11988 FastRCNN class loss: 0.11682 FastRCNN total loss: 0.2367 L1 loss: 0.0000e+00 L2 loss: 0.6246 Learning rate: 0.02 Mask loss: 0.19958 RPN box loss: 0.0479 RPN score loss: 0.00949 RPN total loss: 0.05739 Total loss: 1.11827 timestamp: 1655038188.199122 iteration: 38740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20271 FastRCNN class loss: 0.10542 FastRCNN total loss: 0.30812 L1 loss: 0.0000e+00 L2 loss: 0.62452 Learning rate: 0.02 Mask loss: 0.20337 RPN box loss: 0.05189 RPN score loss: 0.0124 RPN total loss: 0.06429 Total loss: 1.2003 timestamp: 1655038191.5043216 iteration: 38745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.15181 L1 loss: 0.0000e+00 L2 loss: 0.62443 Learning rate: 0.02 Mask loss: 0.13654 RPN box loss: 0.00662 RPN score loss: 0.00714 RPN total loss: 0.01377 Total loss: 0.92654 timestamp: 1655038194.727826 iteration: 38750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10644 FastRCNN class loss: 0.08685 FastRCNN total loss: 0.19329 L1 loss: 0.0000e+00 L2 loss: 0.62433 Learning rate: 0.02 Mask loss: 0.18481 RPN box loss: 0.04479 RPN score loss: 0.01406 RPN total loss: 0.05885 Total loss: 1.06128 timestamp: 1655038197.9744248 iteration: 38755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.127 FastRCNN class loss: 0.08948 FastRCNN total loss: 0.21648 L1 loss: 0.0000e+00 L2 loss: 0.62426 Learning rate: 0.02 Mask loss: 0.12589 RPN box loss: 0.01537 RPN score loss: 0.00257 RPN total loss: 0.01795 Total loss: 0.98458 timestamp: 1655038201.2606215 iteration: 38760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12096 FastRCNN class loss: 0.05774 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.62418 Learning rate: 0.02 Mask loss: 0.13718 RPN box loss: 0.0076 RPN score loss: 0.00515 RPN total loss: 0.01275 Total loss: 0.95281 timestamp: 1655038204.5342183 iteration: 38765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18325 FastRCNN class loss: 0.12169 FastRCNN total loss: 0.30493 L1 loss: 0.0000e+00 L2 loss: 0.6241 Learning rate: 0.02 Mask loss: 0.20042 RPN box loss: 0.03136 RPN score loss: 0.01291 RPN total loss: 0.04427 Total loss: 1.17373 timestamp: 1655038207.7345338 iteration: 38770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1049 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.154 L1 loss: 0.0000e+00 L2 loss: 0.62404 Learning rate: 0.02 Mask loss: 0.14075 RPN box loss: 0.05378 RPN score loss: 0.00416 RPN total loss: 0.05793 Total loss: 0.97672 timestamp: 1655038210.9660935 iteration: 38775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19654 FastRCNN class loss: 0.11453 FastRCNN total loss: 0.31107 L1 loss: 0.0000e+00 L2 loss: 0.62394 Learning rate: 0.02 Mask loss: 0.21949 RPN box loss: 0.05859 RPN score loss: 0.0198 RPN total loss: 0.07838 Total loss: 1.23288 timestamp: 1655038214.1637006 iteration: 38780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1404 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.21078 L1 loss: 0.0000e+00 L2 loss: 0.62385 Learning rate: 0.02 Mask loss: 0.12171 RPN box loss: 0.01141 RPN score loss: 0.00415 RPN total loss: 0.01557 Total loss: 0.97191 timestamp: 1655038217.464403 iteration: 38785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.16967 L1 loss: 0.0000e+00 L2 loss: 0.62376 Learning rate: 0.02 Mask loss: 0.08912 RPN box loss: 0.03548 RPN score loss: 0.00752 RPN total loss: 0.04301 Total loss: 0.92555 timestamp: 1655038220.7491128 iteration: 38790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15731 FastRCNN class loss: 0.09839 FastRCNN total loss: 0.25569 L1 loss: 0.0000e+00 L2 loss: 0.62366 Learning rate: 0.02 Mask loss: 0.19802 RPN box loss: 0.03438 RPN score loss: 0.0109 RPN total loss: 0.04528 Total loss: 1.12266 timestamp: 1655038224.0386436 iteration: 38795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.18262 L1 loss: 0.0000e+00 L2 loss: 0.62357 Learning rate: 0.02 Mask loss: 0.16118 RPN box loss: 0.1061 RPN score loss: 0.01547 RPN total loss: 0.12157 Total loss: 1.08894 timestamp: 1655038227.2787232 iteration: 38800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14261 FastRCNN class loss: 0.0488 FastRCNN total loss: 0.19141 L1 loss: 0.0000e+00 L2 loss: 0.62349 Learning rate: 0.02 Mask loss: 0.11141 RPN box loss: 0.0173 RPN score loss: 0.0059 RPN total loss: 0.0232 Total loss: 0.94952 timestamp: 1655038230.6089964 iteration: 38805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18112 FastRCNN class loss: 0.08049 FastRCNN total loss: 0.2616 L1 loss: 0.0000e+00 L2 loss: 0.62342 Learning rate: 0.02 Mask loss: 0.15825 RPN box loss: 0.02895 RPN score loss: 0.00604 RPN total loss: 0.03499 Total loss: 1.07827 timestamp: 1655038233.8800237 iteration: 38810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09221 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.14544 L1 loss: 0.0000e+00 L2 loss: 0.62334 Learning rate: 0.02 Mask loss: 0.19849 RPN box loss: 0.01721 RPN score loss: 0.00272 RPN total loss: 0.01993 Total loss: 0.98719 timestamp: 1655038237.1789935 iteration: 38815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14245 FastRCNN class loss: 0.08705 FastRCNN total loss: 0.22949 L1 loss: 0.0000e+00 L2 loss: 0.62327 Learning rate: 0.02 Mask loss: 0.19074 RPN box loss: 0.03044 RPN score loss: 0.01838 RPN total loss: 0.04882 Total loss: 1.09232 timestamp: 1655038240.4130964 iteration: 38820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17034 FastRCNN class loss: 0.13031 FastRCNN total loss: 0.30065 L1 loss: 0.0000e+00 L2 loss: 0.62318 Learning rate: 0.02 Mask loss: 0.21712 RPN box loss: 0.02557 RPN score loss: 0.04066 RPN total loss: 0.06623 Total loss: 1.20717 timestamp: 1655038243.7354949 iteration: 38825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13103 FastRCNN class loss: 0.0917 FastRCNN total loss: 0.22273 L1 loss: 0.0000e+00 L2 loss: 0.62306 Learning rate: 0.02 Mask loss: 0.21969 RPN box loss: 0.0063 RPN score loss: 0.00267 RPN total loss: 0.00897 Total loss: 1.07443 timestamp: 1655038246.9602456 iteration: 38830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10475 FastRCNN class loss: 0.04779 FastRCNN total loss: 0.15254 L1 loss: 0.0000e+00 L2 loss: 0.62298 Learning rate: 0.02 Mask loss: 0.16123 RPN box loss: 0.01165 RPN score loss: 0.00288 RPN total loss: 0.01454 Total loss: 0.95129 timestamp: 1655038250.2804883 iteration: 38835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.08871 FastRCNN total loss: 0.20544 L1 loss: 0.0000e+00 L2 loss: 0.6229 Learning rate: 0.02 Mask loss: 0.18793 RPN box loss: 0.03191 RPN score loss: 0.00679 RPN total loss: 0.0387 Total loss: 1.05496 timestamp: 1655038253.5843475 iteration: 38840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18824 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.2585 L1 loss: 0.0000e+00 L2 loss: 0.62281 Learning rate: 0.02 Mask loss: 0.16709 RPN box loss: 0.05083 RPN score loss: 0.00615 RPN total loss: 0.05698 Total loss: 1.10538 timestamp: 1655038256.8105676 iteration: 38845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09699 FastRCNN class loss: 0.06192 FastRCNN total loss: 0.1589 L1 loss: 0.0000e+00 L2 loss: 0.62275 Learning rate: 0.02 Mask loss: 0.17094 RPN box loss: 0.06647 RPN score loss: 0.00472 RPN total loss: 0.07119 Total loss: 1.02379 timestamp: 1655038260.081634 iteration: 38850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15092 FastRCNN class loss: 0.06786 FastRCNN total loss: 0.21878 L1 loss: 0.0000e+00 L2 loss: 0.62266 Learning rate: 0.02 Mask loss: 0.10326 RPN box loss: 0.03112 RPN score loss: 0.00622 RPN total loss: 0.03734 Total loss: 0.98204 timestamp: 1655038263.395882 iteration: 38855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23299 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.31993 L1 loss: 0.0000e+00 L2 loss: 0.62258 Learning rate: 0.02 Mask loss: 0.16937 RPN box loss: 0.09286 RPN score loss: 0.01009 RPN total loss: 0.10295 Total loss: 1.21484 timestamp: 1655038266.6731434 iteration: 38860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15836 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.2223 L1 loss: 0.0000e+00 L2 loss: 0.62253 Learning rate: 0.02 Mask loss: 0.18399 RPN box loss: 0.03937 RPN score loss: 0.00463 RPN total loss: 0.044 Total loss: 1.07282 timestamp: 1655038269.9581513 iteration: 38865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.04664 FastRCNN total loss: 0.16406 L1 loss: 0.0000e+00 L2 loss: 0.62243 Learning rate: 0.02 Mask loss: 0.16666 RPN box loss: 0.03167 RPN score loss: 0.00361 RPN total loss: 0.03529 Total loss: 0.98844 timestamp: 1655038273.3133798 iteration: 38870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16952 FastRCNN class loss: 0.12392 FastRCNN total loss: 0.29344 L1 loss: 0.0000e+00 L2 loss: 0.62234 Learning rate: 0.02 Mask loss: 0.20205 RPN box loss: 0.06436 RPN score loss: 0.01529 RPN total loss: 0.07966 Total loss: 1.19748 timestamp: 1655038276.5758011 iteration: 38875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1102 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.16342 L1 loss: 0.0000e+00 L2 loss: 0.62225 Learning rate: 0.02 Mask loss: 0.11209 RPN box loss: 0.01874 RPN score loss: 0.00303 RPN total loss: 0.02177 Total loss: 0.91953 timestamp: 1655038279.852856 iteration: 38880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11095 FastRCNN class loss: 0.12795 FastRCNN total loss: 0.2389 L1 loss: 0.0000e+00 L2 loss: 0.62216 Learning rate: 0.02 Mask loss: 0.19552 RPN box loss: 0.05074 RPN score loss: 0.02001 RPN total loss: 0.07075 Total loss: 1.12733 timestamp: 1655038283.0582757 iteration: 38885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14099 FastRCNN class loss: 0.0494 FastRCNN total loss: 0.1904 L1 loss: 0.0000e+00 L2 loss: 0.62209 Learning rate: 0.02 Mask loss: 0.09873 RPN box loss: 0.06411 RPN score loss: 0.00736 RPN total loss: 0.07147 Total loss: 0.98269 timestamp: 1655038286.3580616 iteration: 38890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15813 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.2382 L1 loss: 0.0000e+00 L2 loss: 0.62202 Learning rate: 0.02 Mask loss: 0.17553 RPN box loss: 0.03032 RPN score loss: 0.00764 RPN total loss: 0.03796 Total loss: 1.07371 timestamp: 1655038289.6667304 iteration: 38895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14294 FastRCNN class loss: 0.06903 FastRCNN total loss: 0.21197 L1 loss: 0.0000e+00 L2 loss: 0.62194 Learning rate: 0.02 Mask loss: 0.15358 RPN box loss: 0.07266 RPN score loss: 0.00856 RPN total loss: 0.08122 Total loss: 1.06871 timestamp: 1655038292.9659953 iteration: 38900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06904 FastRCNN class loss: 0.06851 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 0.62186 Learning rate: 0.02 Mask loss: 0.12753 RPN box loss: 0.0069 RPN score loss: 0.00669 RPN total loss: 0.01359 Total loss: 0.90053 timestamp: 1655038296.2212722 iteration: 38905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14552 FastRCNN class loss: 0.14718 FastRCNN total loss: 0.2927 L1 loss: 0.0000e+00 L2 loss: 0.62178 Learning rate: 0.02 Mask loss: 0.16285 RPN box loss: 0.02026 RPN score loss: 0.00732 RPN total loss: 0.02758 Total loss: 1.10491 timestamp: 1655038299.4544144 iteration: 38910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09912 FastRCNN class loss: 0.09829 FastRCNN total loss: 0.19741 L1 loss: 0.0000e+00 L2 loss: 0.62169 Learning rate: 0.02 Mask loss: 0.17204 RPN box loss: 0.05214 RPN score loss: 0.02386 RPN total loss: 0.076 Total loss: 1.06714 timestamp: 1655038302.6847613 iteration: 38915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19656 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.26714 L1 loss: 0.0000e+00 L2 loss: 0.62158 Learning rate: 0.02 Mask loss: 0.15398 RPN box loss: 0.02964 RPN score loss: 0.01096 RPN total loss: 0.0406 Total loss: 1.0833 timestamp: 1655038305.9708898 iteration: 38920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12284 FastRCNN class loss: 0.1187 FastRCNN total loss: 0.24154 L1 loss: 0.0000e+00 L2 loss: 0.62149 Learning rate: 0.02 Mask loss: 0.14161 RPN box loss: 0.03278 RPN score loss: 0.00492 RPN total loss: 0.0377 Total loss: 1.04234 timestamp: 1655038309.2785761 iteration: 38925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0719 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.13425 L1 loss: 0.0000e+00 L2 loss: 0.6214 Learning rate: 0.02 Mask loss: 0.12375 RPN box loss: 0.00979 RPN score loss: 0.00415 RPN total loss: 0.01393 Total loss: 0.89333 timestamp: 1655038312.482033 iteration: 38930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10777 FastRCNN class loss: 0.08663 FastRCNN total loss: 0.1944 L1 loss: 0.0000e+00 L2 loss: 0.62134 Learning rate: 0.02 Mask loss: 0.12891 RPN box loss: 0.02187 RPN score loss: 0.00289 RPN total loss: 0.02476 Total loss: 0.96941 timestamp: 1655038315.766355 iteration: 38935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19233 FastRCNN class loss: 0.12085 FastRCNN total loss: 0.31319 L1 loss: 0.0000e+00 L2 loss: 0.62127 Learning rate: 0.02 Mask loss: 0.2852 RPN box loss: 0.04589 RPN score loss: 0.01898 RPN total loss: 0.06486 Total loss: 1.28452 timestamp: 1655038319.0378997 iteration: 38940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11056 FastRCNN class loss: 0.1416 FastRCNN total loss: 0.25217 L1 loss: 0.0000e+00 L2 loss: 0.62118 Learning rate: 0.02 Mask loss: 0.17459 RPN box loss: 0.02932 RPN score loss: 0.00433 RPN total loss: 0.03365 Total loss: 1.08158 timestamp: 1655038322.3746855 iteration: 38945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18778 FastRCNN class loss: 0.10016 FastRCNN total loss: 0.28794 L1 loss: 0.0000e+00 L2 loss: 0.62109 Learning rate: 0.02 Mask loss: 0.28869 RPN box loss: 0.01791 RPN score loss: 0.0048 RPN total loss: 0.0227 Total loss: 1.22042 timestamp: 1655038325.6642652 iteration: 38950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13796 FastRCNN class loss: 0.09754 FastRCNN total loss: 0.23551 L1 loss: 0.0000e+00 L2 loss: 0.62104 Learning rate: 0.02 Mask loss: 0.13358 RPN box loss: 0.03414 RPN score loss: 0.00847 RPN total loss: 0.04262 Total loss: 1.03275 timestamp: 1655038328.991172 iteration: 38955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13766 FastRCNN class loss: 0.072 FastRCNN total loss: 0.20966 L1 loss: 0.0000e+00 L2 loss: 0.62096 Learning rate: 0.02 Mask loss: 0.15369 RPN box loss: 0.02212 RPN score loss: 0.00909 RPN total loss: 0.03121 Total loss: 1.01552 timestamp: 1655038332.324547 iteration: 38960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16106 FastRCNN class loss: 0.1008 FastRCNN total loss: 0.26186 L1 loss: 0.0000e+00 L2 loss: 0.62089 Learning rate: 0.02 Mask loss: 0.17601 RPN box loss: 0.03869 RPN score loss: 0.00525 RPN total loss: 0.04394 Total loss: 1.10271 timestamp: 1655038335.6023397 iteration: 38965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15342 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.21998 L1 loss: 0.0000e+00 L2 loss: 0.62083 Learning rate: 0.02 Mask loss: 0.19116 RPN box loss: 0.07831 RPN score loss: 0.00306 RPN total loss: 0.08137 Total loss: 1.11334 timestamp: 1655038338.8681903 iteration: 38970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.22473 L1 loss: 0.0000e+00 L2 loss: 0.62075 Learning rate: 0.02 Mask loss: 0.15691 RPN box loss: 0.02454 RPN score loss: 0.00295 RPN total loss: 0.02748 Total loss: 1.02988 timestamp: 1655038342.1710231 iteration: 38975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18649 FastRCNN class loss: 0.12883 FastRCNN total loss: 0.31531 L1 loss: 0.0000e+00 L2 loss: 0.62065 Learning rate: 0.02 Mask loss: 0.17203 RPN box loss: 0.02388 RPN score loss: 0.00693 RPN total loss: 0.03081 Total loss: 1.1388 timestamp: 1655038345.4973989 iteration: 38980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.18703 L1 loss: 0.0000e+00 L2 loss: 0.62058 Learning rate: 0.02 Mask loss: 0.11432 RPN box loss: 0.00923 RPN score loss: 0.00562 RPN total loss: 0.01485 Total loss: 0.93678 timestamp: 1655038348.7619472 iteration: 38985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11472 FastRCNN class loss: 0.07276 FastRCNN total loss: 0.18748 L1 loss: 0.0000e+00 L2 loss: 0.62051 Learning rate: 0.02 Mask loss: 0.11385 RPN box loss: 0.02074 RPN score loss: 0.00421 RPN total loss: 0.02495 Total loss: 0.9468 timestamp: 1655038352.031874 iteration: 38990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13946 FastRCNN class loss: 0.0837 FastRCNN total loss: 0.22315 L1 loss: 0.0000e+00 L2 loss: 0.62044 Learning rate: 0.02 Mask loss: 0.1663 RPN box loss: 0.0457 RPN score loss: 0.00428 RPN total loss: 0.04998 Total loss: 1.05988 timestamp: 1655038355.3262389 iteration: 38995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10572 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.18646 L1 loss: 0.0000e+00 L2 loss: 0.62035 Learning rate: 0.02 Mask loss: 0.11704 RPN box loss: 0.04924 RPN score loss: 0.01133 RPN total loss: 0.06057 Total loss: 0.98442 timestamp: 1655038358.6247988 iteration: 39000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14651 FastRCNN class loss: 0.03746 FastRCNN total loss: 0.18397 L1 loss: 0.0000e+00 L2 loss: 0.62024 Learning rate: 0.02 Mask loss: 0.12422 RPN box loss: 0.00728 RPN score loss: 0.00195 RPN total loss: 0.00924 Total loss: 0.93768 timestamp: 1655038361.9253519 iteration: 39005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20358 FastRCNN class loss: 0.10262 FastRCNN total loss: 0.30621 L1 loss: 0.0000e+00 L2 loss: 0.62018 Learning rate: 0.02 Mask loss: 0.17245 RPN box loss: 0.03744 RPN score loss: 0.0042 RPN total loss: 0.04164 Total loss: 1.14048 timestamp: 1655038365.2253113 iteration: 39010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13706 FastRCNN class loss: 0.09573 FastRCNN total loss: 0.23279 L1 loss: 0.0000e+00 L2 loss: 0.62012 Learning rate: 0.02 Mask loss: 0.12317 RPN box loss: 0.01409 RPN score loss: 0.00328 RPN total loss: 0.01737 Total loss: 0.99344 timestamp: 1655038368.4274168 iteration: 39015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1174 FastRCNN class loss: 0.08309 FastRCNN total loss: 0.20049 L1 loss: 0.0000e+00 L2 loss: 0.62005 Learning rate: 0.02 Mask loss: 0.24419 RPN box loss: 0.0205 RPN score loss: 0.0048 RPN total loss: 0.0253 Total loss: 1.09002 timestamp: 1655038371.735295 iteration: 39020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09145 FastRCNN class loss: 0.07162 FastRCNN total loss: 0.16307 L1 loss: 0.0000e+00 L2 loss: 0.61998 Learning rate: 0.02 Mask loss: 0.16014 RPN box loss: 0.06288 RPN score loss: 0.00352 RPN total loss: 0.0664 Total loss: 1.0096 timestamp: 1655038374.932945 iteration: 39025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13177 FastRCNN class loss: 0.10573 FastRCNN total loss: 0.23749 L1 loss: 0.0000e+00 L2 loss: 0.61987 Learning rate: 0.02 Mask loss: 0.20435 RPN box loss: 0.01607 RPN score loss: 0.00489 RPN total loss: 0.02095 Total loss: 1.08267 timestamp: 1655038378.1997273 iteration: 39030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.04801 FastRCNN total loss: 0.12622 L1 loss: 0.0000e+00 L2 loss: 0.61982 Learning rate: 0.02 Mask loss: 0.11485 RPN box loss: 0.01705 RPN score loss: 0.00301 RPN total loss: 0.02006 Total loss: 0.88096 timestamp: 1655038381.4835725 iteration: 39035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21039 FastRCNN class loss: 0.16415 FastRCNN total loss: 0.37454 L1 loss: 0.0000e+00 L2 loss: 0.61976 Learning rate: 0.02 Mask loss: 0.24583 RPN box loss: 0.06353 RPN score loss: 0.00913 RPN total loss: 0.07266 Total loss: 1.31279 timestamp: 1655038384.741668 iteration: 39040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21949 FastRCNN class loss: 0.17309 FastRCNN total loss: 0.39258 L1 loss: 0.0000e+00 L2 loss: 0.61967 Learning rate: 0.02 Mask loss: 0.17648 RPN box loss: 0.0247 RPN score loss: 0.00828 RPN total loss: 0.03298 Total loss: 1.22172 timestamp: 1655038388.063579 iteration: 39045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15162 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.24446 L1 loss: 0.0000e+00 L2 loss: 0.61959 Learning rate: 0.02 Mask loss: 0.1712 RPN box loss: 0.02918 RPN score loss: 0.01098 RPN total loss: 0.04015 Total loss: 1.07541 timestamp: 1655038391.3109705 iteration: 39050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13985 FastRCNN class loss: 0.11412 FastRCNN total loss: 0.25397 L1 loss: 0.0000e+00 L2 loss: 0.6195 Learning rate: 0.02 Mask loss: 0.23404 RPN box loss: 0.03908 RPN score loss: 0.01001 RPN total loss: 0.04909 Total loss: 1.1566 timestamp: 1655038394.5775626 iteration: 39055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12283 FastRCNN class loss: 0.10403 FastRCNN total loss: 0.22687 L1 loss: 0.0000e+00 L2 loss: 0.6194 Learning rate: 0.02 Mask loss: 0.22536 RPN box loss: 0.01103 RPN score loss: 0.00182 RPN total loss: 0.01284 Total loss: 1.08448 timestamp: 1655038397.8334382 iteration: 39060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16709 FastRCNN class loss: 0.09799 FastRCNN total loss: 0.26509 L1 loss: 0.0000e+00 L2 loss: 0.6193 Learning rate: 0.02 Mask loss: 0.13301 RPN box loss: 0.02645 RPN score loss: 0.00653 RPN total loss: 0.03298 Total loss: 1.05038 timestamp: 1655038401.100258 iteration: 39065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18775 FastRCNN class loss: 0.07765 FastRCNN total loss: 0.2654 L1 loss: 0.0000e+00 L2 loss: 0.61924 Learning rate: 0.02 Mask loss: 0.13588 RPN box loss: 0.04072 RPN score loss: 0.00492 RPN total loss: 0.04564 Total loss: 1.06617 timestamp: 1655038404.3672922 iteration: 39070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12391 FastRCNN class loss: 0.07998 FastRCNN total loss: 0.20389 L1 loss: 0.0000e+00 L2 loss: 0.61918 Learning rate: 0.02 Mask loss: 0.15802 RPN box loss: 0.02365 RPN score loss: 0.00166 RPN total loss: 0.02531 Total loss: 1.00641 timestamp: 1655038407.5954406 iteration: 39075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16882 FastRCNN class loss: 0.11214 FastRCNN total loss: 0.28096 L1 loss: 0.0000e+00 L2 loss: 0.61909 Learning rate: 0.02 Mask loss: 0.15736 RPN box loss: 0.03021 RPN score loss: 0.00463 RPN total loss: 0.03484 Total loss: 1.09226 timestamp: 1655038410.902063 iteration: 39080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10911 FastRCNN class loss: 0.08238 FastRCNN total loss: 0.19149 L1 loss: 0.0000e+00 L2 loss: 0.61902 Learning rate: 0.02 Mask loss: 0.13969 RPN box loss: 0.02651 RPN score loss: 0.01713 RPN total loss: 0.04365 Total loss: 0.99385 timestamp: 1655038414.161151 iteration: 39085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19034 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.25425 L1 loss: 0.0000e+00 L2 loss: 0.61896 Learning rate: 0.02 Mask loss: 0.16608 RPN box loss: 0.02493 RPN score loss: 0.00889 RPN total loss: 0.03381 Total loss: 1.07311 timestamp: 1655038417.4046636 iteration: 39090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10276 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.15862 L1 loss: 0.0000e+00 L2 loss: 0.61887 Learning rate: 0.02 Mask loss: 0.18576 RPN box loss: 0.01557 RPN score loss: 0.00766 RPN total loss: 0.02323 Total loss: 0.98648 timestamp: 1655038420.6661613 iteration: 39095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12977 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.20088 L1 loss: 0.0000e+00 L2 loss: 0.61879 Learning rate: 0.02 Mask loss: 0.09076 RPN box loss: 0.02183 RPN score loss: 0.00255 RPN total loss: 0.02438 Total loss: 0.93481 timestamp: 1655038423.9918895 iteration: 39100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.05376 FastRCNN total loss: 0.13575 L1 loss: 0.0000e+00 L2 loss: 0.61871 Learning rate: 0.02 Mask loss: 0.09666 RPN box loss: 0.00912 RPN score loss: 0.00291 RPN total loss: 0.01204 Total loss: 0.86316 timestamp: 1655038427.2564578 iteration: 39105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16888 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.24022 L1 loss: 0.0000e+00 L2 loss: 0.61862 Learning rate: 0.02 Mask loss: 0.17076 RPN box loss: 0.07936 RPN score loss: 0.01368 RPN total loss: 0.09304 Total loss: 1.12264 timestamp: 1655038430.4971216 iteration: 39110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11994 FastRCNN class loss: 0.15598 FastRCNN total loss: 0.27592 L1 loss: 0.0000e+00 L2 loss: 0.61854 Learning rate: 0.02 Mask loss: 0.1511 RPN box loss: 0.06654 RPN score loss: 0.01157 RPN total loss: 0.07811 Total loss: 1.12367 timestamp: 1655038433.7326088 iteration: 39115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15209 FastRCNN class loss: 0.10765 FastRCNN total loss: 0.25973 L1 loss: 0.0000e+00 L2 loss: 0.61847 Learning rate: 0.02 Mask loss: 0.12232 RPN box loss: 0.03464 RPN score loss: 0.00256 RPN total loss: 0.0372 Total loss: 1.03773 timestamp: 1655038436.978838 iteration: 39120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13854 FastRCNN class loss: 0.08138 FastRCNN total loss: 0.21992 L1 loss: 0.0000e+00 L2 loss: 0.61838 Learning rate: 0.02 Mask loss: 0.13737 RPN box loss: 0.0061 RPN score loss: 0.00357 RPN total loss: 0.00967 Total loss: 0.98534 timestamp: 1655038440.2426157 iteration: 39125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12711 FastRCNN class loss: 0.06807 FastRCNN total loss: 0.19518 L1 loss: 0.0000e+00 L2 loss: 0.61829 Learning rate: 0.02 Mask loss: 0.15224 RPN box loss: 0.03421 RPN score loss: 0.00702 RPN total loss: 0.04123 Total loss: 1.00694 timestamp: 1655038443.4844189 iteration: 39130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16435 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.2541 L1 loss: 0.0000e+00 L2 loss: 0.61821 Learning rate: 0.02 Mask loss: 0.23747 RPN box loss: 0.02481 RPN score loss: 0.01291 RPN total loss: 0.03772 Total loss: 1.1475 timestamp: 1655038446.798435 iteration: 39135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.07653 FastRCNN total loss: 0.19065 L1 loss: 0.0000e+00 L2 loss: 0.61814 Learning rate: 0.02 Mask loss: 0.20231 RPN box loss: 0.06972 RPN score loss: 0.00682 RPN total loss: 0.07654 Total loss: 1.08764 timestamp: 1655038450.043536 iteration: 39140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16024 FastRCNN class loss: 0.09544 FastRCNN total loss: 0.25568 L1 loss: 0.0000e+00 L2 loss: 0.61807 Learning rate: 0.02 Mask loss: 0.12115 RPN box loss: 0.02393 RPN score loss: 0.00636 RPN total loss: 0.03028 Total loss: 1.02518 timestamp: 1655038453.3457975 iteration: 39145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12315 FastRCNN class loss: 0.08998 FastRCNN total loss: 0.21313 L1 loss: 0.0000e+00 L2 loss: 0.61799 Learning rate: 0.02 Mask loss: 0.20462 RPN box loss: 0.03599 RPN score loss: 0.00451 RPN total loss: 0.0405 Total loss: 1.07623 timestamp: 1655038456.6404529 iteration: 39150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14305 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.22698 L1 loss: 0.0000e+00 L2 loss: 0.61789 Learning rate: 0.02 Mask loss: 0.26856 RPN box loss: 0.02737 RPN score loss: 0.01472 RPN total loss: 0.04209 Total loss: 1.15552 timestamp: 1655038459.9187262 iteration: 39155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14232 FastRCNN class loss: 0.08669 FastRCNN total loss: 0.22901 L1 loss: 0.0000e+00 L2 loss: 0.61782 Learning rate: 0.02 Mask loss: 0.16475 RPN box loss: 0.00722 RPN score loss: 0.00233 RPN total loss: 0.00954 Total loss: 1.02112 timestamp: 1655038463.1848407 iteration: 39160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09836 FastRCNN class loss: 0.07 FastRCNN total loss: 0.16836 L1 loss: 0.0000e+00 L2 loss: 0.61774 Learning rate: 0.02 Mask loss: 0.16103 RPN box loss: 0.01841 RPN score loss: 0.00308 RPN total loss: 0.02149 Total loss: 0.96862 timestamp: 1655038466.4179802 iteration: 39165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1429 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.21613 L1 loss: 0.0000e+00 L2 loss: 0.61768 Learning rate: 0.02 Mask loss: 0.15823 RPN box loss: 0.06096 RPN score loss: 0.02057 RPN total loss: 0.08153 Total loss: 1.07356 timestamp: 1655038469.6620204 iteration: 39170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09299 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.14652 L1 loss: 0.0000e+00 L2 loss: 0.61759 Learning rate: 0.02 Mask loss: 0.08267 RPN box loss: 0.01051 RPN score loss: 0.00437 RPN total loss: 0.01488 Total loss: 0.86165 timestamp: 1655038472.8942654 iteration: 39175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.17095 L1 loss: 0.0000e+00 L2 loss: 0.6175 Learning rate: 0.02 Mask loss: 0.09271 RPN box loss: 0.01393 RPN score loss: 0.00543 RPN total loss: 0.01936 Total loss: 0.90051 timestamp: 1655038476.2226386 iteration: 39180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0937 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.1741 L1 loss: 0.0000e+00 L2 loss: 0.6174 Learning rate: 0.02 Mask loss: 0.09573 RPN box loss: 0.03072 RPN score loss: 0.00792 RPN total loss: 0.03864 Total loss: 0.92587 timestamp: 1655038479.496497 iteration: 39185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.07328 FastRCNN total loss: 0.18059 L1 loss: 0.0000e+00 L2 loss: 0.61729 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.07584 RPN score loss: 0.01685 RPN total loss: 0.09268 Total loss: 1.06445 timestamp: 1655038482.8509288 iteration: 39190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12194 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.19704 L1 loss: 0.0000e+00 L2 loss: 0.61722 Learning rate: 0.02 Mask loss: 0.20623 RPN box loss: 0.0289 RPN score loss: 0.00769 RPN total loss: 0.03658 Total loss: 1.05707 timestamp: 1655038486.0913162 iteration: 39195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.0655 FastRCNN total loss: 0.15857 L1 loss: 0.0000e+00 L2 loss: 0.61714 Learning rate: 0.02 Mask loss: 0.18494 RPN box loss: 0.02852 RPN score loss: 0.00413 RPN total loss: 0.03264 Total loss: 0.9933 timestamp: 1655038489.354186 iteration: 39200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1994 FastRCNN class loss: 0.19284 FastRCNN total loss: 0.39224 L1 loss: 0.0000e+00 L2 loss: 0.61705 Learning rate: 0.02 Mask loss: 0.12132 RPN box loss: 0.05517 RPN score loss: 0.00929 RPN total loss: 0.06446 Total loss: 1.19507 timestamp: 1655038492.6611197 iteration: 39205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17384 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.23722 L1 loss: 0.0000e+00 L2 loss: 0.61695 Learning rate: 0.02 Mask loss: 0.14713 RPN box loss: 0.06056 RPN score loss: 0.00759 RPN total loss: 0.06815 Total loss: 1.06945 timestamp: 1655038495.8940556 iteration: 39210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1125 FastRCNN class loss: 0.04401 FastRCNN total loss: 0.15652 L1 loss: 0.0000e+00 L2 loss: 0.61685 Learning rate: 0.02 Mask loss: 0.08764 RPN box loss: 0.01212 RPN score loss: 0.00548 RPN total loss: 0.0176 Total loss: 0.87861 timestamp: 1655038499.1470304 iteration: 39215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.21429 L1 loss: 0.0000e+00 L2 loss: 0.61677 Learning rate: 0.02 Mask loss: 0.13155 RPN box loss: 0.01978 RPN score loss: 0.00236 RPN total loss: 0.02214 Total loss: 0.98474 timestamp: 1655038502.3859441 iteration: 39220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21162 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.27069 L1 loss: 0.0000e+00 L2 loss: 0.61671 Learning rate: 0.02 Mask loss: 0.15995 RPN box loss: 0.01667 RPN score loss: 0.00276 RPN total loss: 0.01943 Total loss: 1.06678 timestamp: 1655038505.6795242 iteration: 39225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.19529 L1 loss: 0.0000e+00 L2 loss: 0.61665 Learning rate: 0.02 Mask loss: 0.17389 RPN box loss: 0.0143 RPN score loss: 0.00266 RPN total loss: 0.01695 Total loss: 1.00278 timestamp: 1655038508.9369805 iteration: 39230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13053 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.21141 L1 loss: 0.0000e+00 L2 loss: 0.61657 Learning rate: 0.02 Mask loss: 0.11596 RPN box loss: 0.05329 RPN score loss: 0.0134 RPN total loss: 0.06669 Total loss: 1.01063 timestamp: 1655038512.1537523 iteration: 39235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09679 FastRCNN class loss: 0.044 FastRCNN total loss: 0.14079 L1 loss: 0.0000e+00 L2 loss: 0.61647 Learning rate: 0.02 Mask loss: 0.14144 RPN box loss: 0.00767 RPN score loss: 0.00639 RPN total loss: 0.01406 Total loss: 0.91276 timestamp: 1655038515.4826016 iteration: 39240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12148 FastRCNN class loss: 0.14377 FastRCNN total loss: 0.26524 L1 loss: 0.0000e+00 L2 loss: 0.61639 Learning rate: 0.02 Mask loss: 0.25812 RPN box loss: 0.04299 RPN score loss: 0.04321 RPN total loss: 0.0862 Total loss: 1.22596 timestamp: 1655038518.8641005 iteration: 39245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14654 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.22807 L1 loss: 0.0000e+00 L2 loss: 0.61631 Learning rate: 0.02 Mask loss: 0.16987 RPN box loss: 0.06366 RPN score loss: 0.01203 RPN total loss: 0.07569 Total loss: 1.08994 timestamp: 1655038522.0786376 iteration: 39250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18305 FastRCNN class loss: 0.11654 FastRCNN total loss: 0.29959 L1 loss: 0.0000e+00 L2 loss: 0.61622 Learning rate: 0.02 Mask loss: 0.15947 RPN box loss: 0.04383 RPN score loss: 0.01034 RPN total loss: 0.05418 Total loss: 1.12945 timestamp: 1655038525.3522553 iteration: 39255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10559 FastRCNN class loss: 0.05537 FastRCNN total loss: 0.16095 L1 loss: 0.0000e+00 L2 loss: 0.61613 Learning rate: 0.02 Mask loss: 0.18623 RPN box loss: 0.03606 RPN score loss: 0.00817 RPN total loss: 0.04423 Total loss: 1.00755 timestamp: 1655038528.6057553 iteration: 39260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11496 FastRCNN class loss: 0.09115 FastRCNN total loss: 0.20611 L1 loss: 0.0000e+00 L2 loss: 0.61603 Learning rate: 0.02 Mask loss: 0.19404 RPN box loss: 0.02117 RPN score loss: 0.00865 RPN total loss: 0.02982 Total loss: 1.046 timestamp: 1655038531.8736165 iteration: 39265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06497 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.12739 L1 loss: 0.0000e+00 L2 loss: 0.61598 Learning rate: 0.02 Mask loss: 0.16556 RPN box loss: 0.03262 RPN score loss: 0.01519 RPN total loss: 0.04781 Total loss: 0.95674 timestamp: 1655038535.2186012 iteration: 39270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08876 FastRCNN class loss: 0.07275 FastRCNN total loss: 0.16151 L1 loss: 0.0000e+00 L2 loss: 0.61591 Learning rate: 0.02 Mask loss: 0.1693 RPN box loss: 0.02657 RPN score loss: 0.00452 RPN total loss: 0.03109 Total loss: 0.97781 timestamp: 1655038538.555251 iteration: 39275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10847 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.17831 L1 loss: 0.0000e+00 L2 loss: 0.61582 Learning rate: 0.02 Mask loss: 0.10838 RPN box loss: 0.01599 RPN score loss: 0.00297 RPN total loss: 0.01896 Total loss: 0.92146 timestamp: 1655038541.7808373 iteration: 39280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1209 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.19694 L1 loss: 0.0000e+00 L2 loss: 0.61573 Learning rate: 0.02 Mask loss: 0.12224 RPN box loss: 0.03959 RPN score loss: 0.00226 RPN total loss: 0.04185 Total loss: 0.97676 timestamp: 1655038545.0102315 iteration: 39285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22939 FastRCNN class loss: 0.09906 FastRCNN total loss: 0.32846 L1 loss: 0.0000e+00 L2 loss: 0.61566 Learning rate: 0.02 Mask loss: 0.15984 RPN box loss: 0.05034 RPN score loss: 0.00549 RPN total loss: 0.05583 Total loss: 1.15979 timestamp: 1655038548.308073 iteration: 39290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.18706 L1 loss: 0.0000e+00 L2 loss: 0.61559 Learning rate: 0.02 Mask loss: 0.12563 RPN box loss: 0.00822 RPN score loss: 0.00365 RPN total loss: 0.01188 Total loss: 0.94015 timestamp: 1655038551.6512158 iteration: 39295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.13701 L1 loss: 0.0000e+00 L2 loss: 0.6155 Learning rate: 0.02 Mask loss: 0.11208 RPN box loss: 0.05689 RPN score loss: 0.0082 RPN total loss: 0.06509 Total loss: 0.92968 timestamp: 1655038554.9609346 iteration: 39300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08227 FastRCNN class loss: 0.11311 FastRCNN total loss: 0.19538 L1 loss: 0.0000e+00 L2 loss: 0.6154 Learning rate: 0.02 Mask loss: 0.15097 RPN box loss: 0.04886 RPN score loss: 0.00795 RPN total loss: 0.05681 Total loss: 1.01856 timestamp: 1655038558.1749399 iteration: 39305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07772 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.15376 L1 loss: 0.0000e+00 L2 loss: 0.61532 Learning rate: 0.02 Mask loss: 0.15827 RPN box loss: 0.04202 RPN score loss: 0.00306 RPN total loss: 0.04508 Total loss: 0.97243 timestamp: 1655038561.371064 iteration: 39310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10661 FastRCNN class loss: 0.06012 FastRCNN total loss: 0.16673 L1 loss: 0.0000e+00 L2 loss: 0.61524 Learning rate: 0.02 Mask loss: 0.12307 RPN box loss: 0.04251 RPN score loss: 0.00682 RPN total loss: 0.04933 Total loss: 0.95438 timestamp: 1655038564.6253147 iteration: 39315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.09201 FastRCNN total loss: 0.23235 L1 loss: 0.0000e+00 L2 loss: 0.61514 Learning rate: 0.02 Mask loss: 0.16498 RPN box loss: 0.06723 RPN score loss: 0.01394 RPN total loss: 0.08118 Total loss: 1.09365 timestamp: 1655038567.898614 iteration: 39320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1482 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.21355 L1 loss: 0.0000e+00 L2 loss: 0.61507 Learning rate: 0.02 Mask loss: 0.15106 RPN box loss: 0.0118 RPN score loss: 0.00469 RPN total loss: 0.0165 Total loss: 0.99617 timestamp: 1655038571.217321 iteration: 39325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12749 FastRCNN class loss: 0.07657 FastRCNN total loss: 0.20406 L1 loss: 0.0000e+00 L2 loss: 0.615 Learning rate: 0.02 Mask loss: 0.18298 RPN box loss: 0.01203 RPN score loss: 0.00708 RPN total loss: 0.0191 Total loss: 1.02115 timestamp: 1655038574.5120618 iteration: 39330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10077 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.17607 L1 loss: 0.0000e+00 L2 loss: 0.61491 Learning rate: 0.02 Mask loss: 0.1385 RPN box loss: 0.03727 RPN score loss: 0.00997 RPN total loss: 0.04724 Total loss: 0.97672 timestamp: 1655038577.727308 iteration: 39335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17822 FastRCNN class loss: 0.10178 FastRCNN total loss: 0.28 L1 loss: 0.0000e+00 L2 loss: 0.61485 Learning rate: 0.02 Mask loss: 0.09715 RPN box loss: 0.01653 RPN score loss: 0.00575 RPN total loss: 0.02228 Total loss: 1.01428 timestamp: 1655038580.957915 iteration: 39340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1529 FastRCNN class loss: 0.06561 FastRCNN total loss: 0.21851 L1 loss: 0.0000e+00 L2 loss: 0.61476 Learning rate: 0.02 Mask loss: 0.16868 RPN box loss: 0.04523 RPN score loss: 0.01968 RPN total loss: 0.06491 Total loss: 1.06684 timestamp: 1655038584.236258 iteration: 39345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14858 FastRCNN class loss: 0.10433 FastRCNN total loss: 0.2529 L1 loss: 0.0000e+00 L2 loss: 0.61467 Learning rate: 0.02 Mask loss: 0.20031 RPN box loss: 0.02603 RPN score loss: 0.01225 RPN total loss: 0.03828 Total loss: 1.10616 timestamp: 1655038587.5322034 iteration: 39350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1951 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.26103 L1 loss: 0.0000e+00 L2 loss: 0.61456 Learning rate: 0.02 Mask loss: 0.14872 RPN box loss: 0.02382 RPN score loss: 0.00433 RPN total loss: 0.02815 Total loss: 1.05246 timestamp: 1655038590.7931042 iteration: 39355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1213 FastRCNN class loss: 0.1146 FastRCNN total loss: 0.2359 L1 loss: 0.0000e+00 L2 loss: 0.61447 Learning rate: 0.02 Mask loss: 0.22691 RPN box loss: 0.08009 RPN score loss: 0.01363 RPN total loss: 0.09371 Total loss: 1.17099 timestamp: 1655038594.0436525 iteration: 39360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18034 FastRCNN class loss: 0.06066 FastRCNN total loss: 0.241 L1 loss: 0.0000e+00 L2 loss: 0.61439 Learning rate: 0.02 Mask loss: 0.10221 RPN box loss: 0.01669 RPN score loss: 0.01014 RPN total loss: 0.02683 Total loss: 0.98444 timestamp: 1655038597.3190439 iteration: 39365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13865 FastRCNN class loss: 0.10522 FastRCNN total loss: 0.24387 L1 loss: 0.0000e+00 L2 loss: 0.61436 Learning rate: 0.02 Mask loss: 0.16115 RPN box loss: 0.02138 RPN score loss: 0.0034 RPN total loss: 0.02478 Total loss: 1.04416 timestamp: 1655038600.6219654 iteration: 39370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14036 FastRCNN class loss: 0.08687 FastRCNN total loss: 0.22722 L1 loss: 0.0000e+00 L2 loss: 0.61429 Learning rate: 0.02 Mask loss: 0.26194 RPN box loss: 0.06009 RPN score loss: 0.01133 RPN total loss: 0.07142 Total loss: 1.17487 timestamp: 1655038603.8507583 iteration: 39375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16538 FastRCNN class loss: 0.1085 FastRCNN total loss: 0.27389 L1 loss: 0.0000e+00 L2 loss: 0.61422 Learning rate: 0.02 Mask loss: 0.20065 RPN box loss: 0.02147 RPN score loss: 0.0111 RPN total loss: 0.03257 Total loss: 1.12132 timestamp: 1655038607.1548243 iteration: 39380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19349 FastRCNN class loss: 0.10569 FastRCNN total loss: 0.29918 L1 loss: 0.0000e+00 L2 loss: 0.61415 Learning rate: 0.02 Mask loss: 0.17052 RPN box loss: 0.02055 RPN score loss: 0.02039 RPN total loss: 0.04094 Total loss: 1.12479 timestamp: 1655038610.4495673 iteration: 39385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15708 FastRCNN class loss: 0.12118 FastRCNN total loss: 0.27826 L1 loss: 0.0000e+00 L2 loss: 0.61406 Learning rate: 0.02 Mask loss: 0.19333 RPN box loss: 0.03347 RPN score loss: 0.00605 RPN total loss: 0.03952 Total loss: 1.12516 timestamp: 1655038613.7022412 iteration: 39390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12038 FastRCNN class loss: 0.06352 FastRCNN total loss: 0.1839 L1 loss: 0.0000e+00 L2 loss: 0.61397 Learning rate: 0.02 Mask loss: 0.14019 RPN box loss: 0.03484 RPN score loss: 0.00408 RPN total loss: 0.03892 Total loss: 0.97699 timestamp: 1655038616.9794369 iteration: 39395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1909 FastRCNN class loss: 0.09409 FastRCNN total loss: 0.28499 L1 loss: 0.0000e+00 L2 loss: 0.61389 Learning rate: 0.02 Mask loss: 0.1502 RPN box loss: 0.0384 RPN score loss: 0.04204 RPN total loss: 0.08044 Total loss: 1.12953 timestamp: 1655038620.2787488 iteration: 39400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13694 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.20989 L1 loss: 0.0000e+00 L2 loss: 0.6138 Learning rate: 0.02 Mask loss: 0.24447 RPN box loss: 0.04657 RPN score loss: 0.00241 RPN total loss: 0.04898 Total loss: 1.11713 timestamp: 1655038623.568448 iteration: 39405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.08049 FastRCNN total loss: 0.16551 L1 loss: 0.0000e+00 L2 loss: 0.61373 Learning rate: 0.02 Mask loss: 0.1785 RPN box loss: 0.0326 RPN score loss: 0.00634 RPN total loss: 0.03894 Total loss: 0.99668 timestamp: 1655038626.8161364 iteration: 39410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1387 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.21944 L1 loss: 0.0000e+00 L2 loss: 0.61366 Learning rate: 0.02 Mask loss: 0.12008 RPN box loss: 0.03315 RPN score loss: 0.00772 RPN total loss: 0.04088 Total loss: 0.99405 timestamp: 1655038630.0706286 iteration: 39415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12156 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.17161 L1 loss: 0.0000e+00 L2 loss: 0.61359 Learning rate: 0.02 Mask loss: 0.11958 RPN box loss: 0.00895 RPN score loss: 0.00555 RPN total loss: 0.01449 Total loss: 0.91928 timestamp: 1655038633.3236454 iteration: 39420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13458 FastRCNN class loss: 0.10378 FastRCNN total loss: 0.23836 L1 loss: 0.0000e+00 L2 loss: 0.61353 Learning rate: 0.02 Mask loss: 0.19336 RPN box loss: 0.03822 RPN score loss: 0.01034 RPN total loss: 0.04856 Total loss: 1.09382 timestamp: 1655038636.6039286 iteration: 39425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11027 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.18733 L1 loss: 0.0000e+00 L2 loss: 0.61342 Learning rate: 0.02 Mask loss: 0.17491 RPN box loss: 0.07646 RPN score loss: 0.01366 RPN total loss: 0.09012 Total loss: 1.06578 timestamp: 1655038639.8685904 iteration: 39430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19119 FastRCNN class loss: 0.11609 FastRCNN total loss: 0.30728 L1 loss: 0.0000e+00 L2 loss: 0.61334 Learning rate: 0.02 Mask loss: 0.18492 RPN box loss: 0.06047 RPN score loss: 0.00411 RPN total loss: 0.06459 Total loss: 1.17012 timestamp: 1655038643.1143322 iteration: 39435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2007 FastRCNN class loss: 0.12523 FastRCNN total loss: 0.32593 L1 loss: 0.0000e+00 L2 loss: 0.61327 Learning rate: 0.02 Mask loss: 0.16338 RPN box loss: 0.04096 RPN score loss: 0.01554 RPN total loss: 0.0565 Total loss: 1.15908 timestamp: 1655038646.417196 iteration: 39440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09626 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.16343 L1 loss: 0.0000e+00 L2 loss: 0.61316 Learning rate: 0.02 Mask loss: 0.14568 RPN box loss: 0.03935 RPN score loss: 0.00481 RPN total loss: 0.04416 Total loss: 0.96642 timestamp: 1655038649.6323493 iteration: 39445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19167 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.27113 L1 loss: 0.0000e+00 L2 loss: 0.61306 Learning rate: 0.02 Mask loss: 0.20145 RPN box loss: 0.0904 RPN score loss: 0.00598 RPN total loss: 0.09638 Total loss: 1.18201 timestamp: 1655038652.8825743 iteration: 39450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09572 FastRCNN class loss: 0.05889 FastRCNN total loss: 0.15461 L1 loss: 0.0000e+00 L2 loss: 0.61299 Learning rate: 0.02 Mask loss: 0.0936 RPN box loss: 0.02024 RPN score loss: 0.00501 RPN total loss: 0.02525 Total loss: 0.88645 timestamp: 1655038656.1816943 iteration: 39455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12981 FastRCNN class loss: 0.08609 FastRCNN total loss: 0.2159 L1 loss: 0.0000e+00 L2 loss: 0.61292 Learning rate: 0.02 Mask loss: 0.22181 RPN box loss: 0.0424 RPN score loss: 0.01274 RPN total loss: 0.05513 Total loss: 1.10577 timestamp: 1655038659.4327095 iteration: 39460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12713 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.20702 L1 loss: 0.0000e+00 L2 loss: 0.61286 Learning rate: 0.02 Mask loss: 0.14186 RPN box loss: 0.05527 RPN score loss: 0.00765 RPN total loss: 0.06292 Total loss: 1.02466 timestamp: 1655038662.6750357 iteration: 39465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09812 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.15866 L1 loss: 0.0000e+00 L2 loss: 0.61279 Learning rate: 0.02 Mask loss: 0.10922 RPN box loss: 0.05965 RPN score loss: 0.01772 RPN total loss: 0.07737 Total loss: 0.95804 timestamp: 1655038665.9451573 iteration: 39470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15555 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.21437 L1 loss: 0.0000e+00 L2 loss: 0.6127 Learning rate: 0.02 Mask loss: 0.11089 RPN box loss: 0.03614 RPN score loss: 0.00669 RPN total loss: 0.04283 Total loss: 0.98079 timestamp: 1655038669.239551 iteration: 39475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11602 FastRCNN class loss: 0.16129 FastRCNN total loss: 0.27731 L1 loss: 0.0000e+00 L2 loss: 0.6126 Learning rate: 0.02 Mask loss: 0.28669 RPN box loss: 0.05106 RPN score loss: 0.08933 RPN total loss: 0.14039 Total loss: 1.31699 timestamp: 1655038672.5272474 iteration: 39480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09777 FastRCNN class loss: 0.05261 FastRCNN total loss: 0.15039 L1 loss: 0.0000e+00 L2 loss: 0.61254 Learning rate: 0.02 Mask loss: 0.1752 RPN box loss: 0.01837 RPN score loss: 0.00899 RPN total loss: 0.02736 Total loss: 0.96549 timestamp: 1655038675.8642213 iteration: 39485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12694 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.19726 L1 loss: 0.0000e+00 L2 loss: 0.61247 Learning rate: 0.02 Mask loss: 0.21472 RPN box loss: 0.02393 RPN score loss: 0.00691 RPN total loss: 0.03084 Total loss: 1.0553 timestamp: 1655038679.1428332 iteration: 39490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15465 FastRCNN class loss: 0.06512 FastRCNN total loss: 0.21977 L1 loss: 0.0000e+00 L2 loss: 0.6124 Learning rate: 0.02 Mask loss: 0.18423 RPN box loss: 0.03038 RPN score loss: 0.00454 RPN total loss: 0.03492 Total loss: 1.05132 timestamp: 1655038682.36616 iteration: 39495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20891 FastRCNN class loss: 0.11245 FastRCNN total loss: 0.32136 L1 loss: 0.0000e+00 L2 loss: 0.61229 Learning rate: 0.02 Mask loss: 0.19596 RPN box loss: 0.03517 RPN score loss: 0.00662 RPN total loss: 0.04179 Total loss: 1.1714 timestamp: 1655038685.5980906 iteration: 39500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.239 FastRCNN class loss: 0.111 FastRCNN total loss: 0.34999 L1 loss: 0.0000e+00 L2 loss: 0.6122 Learning rate: 0.02 Mask loss: 0.20777 RPN box loss: 0.03682 RPN score loss: 0.00642 RPN total loss: 0.04324 Total loss: 1.21321 timestamp: 1655038688.9177866 iteration: 39505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14144 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.20046 L1 loss: 0.0000e+00 L2 loss: 0.61215 Learning rate: 0.02 Mask loss: 0.11827 RPN box loss: 0.05044 RPN score loss: 0.00416 RPN total loss: 0.05461 Total loss: 0.98549 timestamp: 1655038692.1930993 iteration: 39510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21382 FastRCNN class loss: 0.06222 FastRCNN total loss: 0.27604 L1 loss: 0.0000e+00 L2 loss: 0.61209 Learning rate: 0.02 Mask loss: 0.12682 RPN box loss: 0.01843 RPN score loss: 0.00128 RPN total loss: 0.0197 Total loss: 1.03466 timestamp: 1655038695.4199116 iteration: 39515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18469 FastRCNN class loss: 0.11142 FastRCNN total loss: 0.29611 L1 loss: 0.0000e+00 L2 loss: 0.61201 Learning rate: 0.02 Mask loss: 0.20274 RPN box loss: 0.02437 RPN score loss: 0.00742 RPN total loss: 0.03179 Total loss: 1.14265 timestamp: 1655038698.6232998 iteration: 39520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06529 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.12512 L1 loss: 0.0000e+00 L2 loss: 0.61193 Learning rate: 0.02 Mask loss: 0.17179 RPN box loss: 0.02313 RPN score loss: 0.00666 RPN total loss: 0.02979 Total loss: 0.93863 timestamp: 1655038701.9280324 iteration: 39525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08516 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.15805 L1 loss: 0.0000e+00 L2 loss: 0.61185 Learning rate: 0.02 Mask loss: 0.13645 RPN box loss: 0.0406 RPN score loss: 0.00632 RPN total loss: 0.04693 Total loss: 0.95328 timestamp: 1655038705.2730465 iteration: 39530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13439 FastRCNN class loss: 0.05338 FastRCNN total loss: 0.18776 L1 loss: 0.0000e+00 L2 loss: 0.6118 Learning rate: 0.02 Mask loss: 0.13909 RPN box loss: 0.07739 RPN score loss: 0.00409 RPN total loss: 0.08148 Total loss: 1.02013 timestamp: 1655038708.56874 iteration: 39535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14488 FastRCNN class loss: 0.11052 FastRCNN total loss: 0.2554 L1 loss: 0.0000e+00 L2 loss: 0.61172 Learning rate: 0.02 Mask loss: 0.16882 RPN box loss: 0.02789 RPN score loss: 0.00685 RPN total loss: 0.03474 Total loss: 1.07068 timestamp: 1655038711.8698893 iteration: 39540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12253 FastRCNN class loss: 0.10041 FastRCNN total loss: 0.22294 L1 loss: 0.0000e+00 L2 loss: 0.61163 Learning rate: 0.02 Mask loss: 0.17792 RPN box loss: 0.01457 RPN score loss: 0.00294 RPN total loss: 0.01751 Total loss: 1.02999 timestamp: 1655038715.189424 iteration: 39545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.09472 FastRCNN total loss: 0.23751 L1 loss: 0.0000e+00 L2 loss: 0.61153 Learning rate: 0.02 Mask loss: 0.18547 RPN box loss: 0.05258 RPN score loss: 0.01062 RPN total loss: 0.06321 Total loss: 1.09772 timestamp: 1655038718.4539497 iteration: 39550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13798 FastRCNN class loss: 0.08978 FastRCNN total loss: 0.22776 L1 loss: 0.0000e+00 L2 loss: 0.61145 Learning rate: 0.02 Mask loss: 0.14572 RPN box loss: 0.02186 RPN score loss: 0.01072 RPN total loss: 0.03258 Total loss: 1.01752 timestamp: 1655038721.7297332 iteration: 39555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16544 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.25261 L1 loss: 0.0000e+00 L2 loss: 0.61137 Learning rate: 0.02 Mask loss: 0.16046 RPN box loss: 0.09463 RPN score loss: 0.00838 RPN total loss: 0.10301 Total loss: 1.12745 timestamp: 1655038724.9559872 iteration: 39560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15885 FastRCNN class loss: 0.10966 FastRCNN total loss: 0.26851 L1 loss: 0.0000e+00 L2 loss: 0.61128 Learning rate: 0.02 Mask loss: 0.13931 RPN box loss: 0.02846 RPN score loss: 0.00799 RPN total loss: 0.03645 Total loss: 1.05556 timestamp: 1655038728.208958 iteration: 39565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10167 FastRCNN class loss: 0.04015 FastRCNN total loss: 0.14182 L1 loss: 0.0000e+00 L2 loss: 0.61121 Learning rate: 0.02 Mask loss: 0.10225 RPN box loss: 0.02234 RPN score loss: 0.00482 RPN total loss: 0.02716 Total loss: 0.88244 timestamp: 1655038731.4848776 iteration: 39570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12657 FastRCNN class loss: 0.09789 FastRCNN total loss: 0.22446 L1 loss: 0.0000e+00 L2 loss: 0.61113 Learning rate: 0.02 Mask loss: 0.16075 RPN box loss: 0.03562 RPN score loss: 0.00754 RPN total loss: 0.04315 Total loss: 1.03949 timestamp: 1655038734.7397082 iteration: 39575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11218 FastRCNN class loss: 0.07576 FastRCNN total loss: 0.18794 L1 loss: 0.0000e+00 L2 loss: 0.61105 Learning rate: 0.02 Mask loss: 0.1224 RPN box loss: 0.03589 RPN score loss: 0.00678 RPN total loss: 0.04266 Total loss: 0.96405 timestamp: 1655038737.986353 iteration: 39580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.06902 FastRCNN total loss: 0.21247 L1 loss: 0.0000e+00 L2 loss: 0.61096 Learning rate: 0.02 Mask loss: 0.13315 RPN box loss: 0.05865 RPN score loss: 0.01008 RPN total loss: 0.06873 Total loss: 1.0253 timestamp: 1655038741.3285162 iteration: 39585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15091 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.22068 L1 loss: 0.0000e+00 L2 loss: 0.61088 Learning rate: 0.02 Mask loss: 0.15179 RPN box loss: 0.0281 RPN score loss: 0.00837 RPN total loss: 0.03647 Total loss: 1.01982 timestamp: 1655038744.5786707 iteration: 39590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10125 FastRCNN class loss: 0.06114 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 0.61081 Learning rate: 0.02 Mask loss: 0.12404 RPN box loss: 0.01282 RPN score loss: 0.00573 RPN total loss: 0.01855 Total loss: 0.9158 timestamp: 1655038747.828748 iteration: 39595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21672 FastRCNN class loss: 0.10436 FastRCNN total loss: 0.32108 L1 loss: 0.0000e+00 L2 loss: 0.61071 Learning rate: 0.02 Mask loss: 0.16156 RPN box loss: 0.03343 RPN score loss: 0.00553 RPN total loss: 0.03896 Total loss: 1.13231 timestamp: 1655038751.1442435 iteration: 39600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10311 FastRCNN class loss: 0.06482 FastRCNN total loss: 0.16793 L1 loss: 0.0000e+00 L2 loss: 0.61062 Learning rate: 0.02 Mask loss: 0.14869 RPN box loss: 0.04896 RPN score loss: 0.00519 RPN total loss: 0.05415 Total loss: 0.9814 timestamp: 1655038754.439856 iteration: 39605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16151 FastRCNN class loss: 0.06775 FastRCNN total loss: 0.22926 L1 loss: 0.0000e+00 L2 loss: 0.61056 Learning rate: 0.02 Mask loss: 0.15537 RPN box loss: 0.04504 RPN score loss: 0.00631 RPN total loss: 0.05134 Total loss: 1.04652 timestamp: 1655038757.8141088 iteration: 39610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16784 FastRCNN class loss: 0.14432 FastRCNN total loss: 0.31216 L1 loss: 0.0000e+00 L2 loss: 0.61048 Learning rate: 0.02 Mask loss: 0.16336 RPN box loss: 0.06249 RPN score loss: 0.01968 RPN total loss: 0.08217 Total loss: 1.16817 timestamp: 1655038761.1184506 iteration: 39615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11499 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.17504 L1 loss: 0.0000e+00 L2 loss: 0.61039 Learning rate: 0.02 Mask loss: 0.09779 RPN box loss: 0.0253 RPN score loss: 0.00292 RPN total loss: 0.02822 Total loss: 0.91145 timestamp: 1655038764.4124882 iteration: 39620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06064 FastRCNN class loss: 0.03301 FastRCNN total loss: 0.09364 L1 loss: 0.0000e+00 L2 loss: 0.61033 Learning rate: 0.02 Mask loss: 0.09731 RPN box loss: 0.0224 RPN score loss: 0.00195 RPN total loss: 0.02435 Total loss: 0.82564 timestamp: 1655038767.6449072 iteration: 39625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10804 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.15775 L1 loss: 0.0000e+00 L2 loss: 0.61022 Learning rate: 0.02 Mask loss: 0.15941 RPN box loss: 0.01116 RPN score loss: 0.00501 RPN total loss: 0.01617 Total loss: 0.94356 timestamp: 1655038770.9613965 iteration: 39630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16782 FastRCNN class loss: 0.09732 FastRCNN total loss: 0.26514 L1 loss: 0.0000e+00 L2 loss: 0.61014 Learning rate: 0.02 Mask loss: 0.18513 RPN box loss: 0.05461 RPN score loss: 0.00708 RPN total loss: 0.06169 Total loss: 1.1221 timestamp: 1655038774.184863 iteration: 39635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14385 FastRCNN class loss: 0.06858 FastRCNN total loss: 0.21243 L1 loss: 0.0000e+00 L2 loss: 0.61008 Learning rate: 0.02 Mask loss: 0.17604 RPN box loss: 0.00756 RPN score loss: 0.01259 RPN total loss: 0.02015 Total loss: 1.0187 timestamp: 1655038777.4830592 iteration: 39640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12203 FastRCNN class loss: 0.05243 FastRCNN total loss: 0.17446 L1 loss: 0.0000e+00 L2 loss: 0.60998 Learning rate: 0.02 Mask loss: 0.1403 RPN box loss: 0.03494 RPN score loss: 0.00406 RPN total loss: 0.03901 Total loss: 0.96375 timestamp: 1655038780.761789 iteration: 39645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13109 FastRCNN class loss: 0.09944 FastRCNN total loss: 0.23053 L1 loss: 0.0000e+00 L2 loss: 0.60987 Learning rate: 0.02 Mask loss: 0.14993 RPN box loss: 0.0231 RPN score loss: 0.00454 RPN total loss: 0.02765 Total loss: 1.01798 timestamp: 1655038784.1024837 iteration: 39650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07805 FastRCNN class loss: 0.07877 FastRCNN total loss: 0.15682 L1 loss: 0.0000e+00 L2 loss: 0.60978 Learning rate: 0.02 Mask loss: 0.16309 RPN box loss: 0.02 RPN score loss: 0.0116 RPN total loss: 0.03161 Total loss: 0.9613 timestamp: 1655038787.3669963 iteration: 39655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12697 FastRCNN class loss: 0.07279 FastRCNN total loss: 0.19976 L1 loss: 0.0000e+00 L2 loss: 0.60972 Learning rate: 0.02 Mask loss: 0.1737 RPN box loss: 0.02344 RPN score loss: 0.00823 RPN total loss: 0.03166 Total loss: 1.01485 timestamp: 1655038790.6237013 iteration: 39660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12519 FastRCNN class loss: 0.15831 FastRCNN total loss: 0.2835 L1 loss: 0.0000e+00 L2 loss: 0.60967 Learning rate: 0.02 Mask loss: 0.16011 RPN box loss: 0.04345 RPN score loss: 0.00468 RPN total loss: 0.04814 Total loss: 1.10142 timestamp: 1655038793.8665316 iteration: 39665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.08031 FastRCNN total loss: 0.18924 L1 loss: 0.0000e+00 L2 loss: 0.60961 Learning rate: 0.02 Mask loss: 0.20036 RPN box loss: 0.07123 RPN score loss: 0.00615 RPN total loss: 0.07739 Total loss: 1.07659 timestamp: 1655038797.1409762 iteration: 39670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10863 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.16993 L1 loss: 0.0000e+00 L2 loss: 0.60953 Learning rate: 0.02 Mask loss: 0.12336 RPN box loss: 0.04817 RPN score loss: 0.00554 RPN total loss: 0.05371 Total loss: 0.95653 timestamp: 1655038800.372374 iteration: 39675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.14594 L1 loss: 0.0000e+00 L2 loss: 0.60944 Learning rate: 0.02 Mask loss: 0.17336 RPN box loss: 0.02234 RPN score loss: 0.00234 RPN total loss: 0.02469 Total loss: 0.95343 timestamp: 1655038803.6921806 iteration: 39680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14282 FastRCNN class loss: 0.05282 FastRCNN total loss: 0.19564 L1 loss: 0.0000e+00 L2 loss: 0.60935 Learning rate: 0.02 Mask loss: 0.14377 RPN box loss: 0.00501 RPN score loss: 0.00562 RPN total loss: 0.01063 Total loss: 0.95939 timestamp: 1655038806.9807916 iteration: 39685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06191 FastRCNN class loss: 0.04578 FastRCNN total loss: 0.10769 L1 loss: 0.0000e+00 L2 loss: 0.60926 Learning rate: 0.02 Mask loss: 0.12762 RPN box loss: 0.03038 RPN score loss: 0.00641 RPN total loss: 0.03678 Total loss: 0.88135 timestamp: 1655038810.2303355 iteration: 39690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.101 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.1822 L1 loss: 0.0000e+00 L2 loss: 0.60917 Learning rate: 0.02 Mask loss: 0.16518 RPN box loss: 0.0296 RPN score loss: 0.00302 RPN total loss: 0.03263 Total loss: 0.98918 timestamp: 1655038813.4720223 iteration: 39695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12229 FastRCNN class loss: 0.0542 FastRCNN total loss: 0.17649 L1 loss: 0.0000e+00 L2 loss: 0.6091 Learning rate: 0.02 Mask loss: 0.13909 RPN box loss: 0.00736 RPN score loss: 0.00216 RPN total loss: 0.00952 Total loss: 0.93419 timestamp: 1655038816.7219658 iteration: 39700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1463 FastRCNN class loss: 0.09683 FastRCNN total loss: 0.24313 L1 loss: 0.0000e+00 L2 loss: 0.60904 Learning rate: 0.02 Mask loss: 0.0737 RPN box loss: 0.01717 RPN score loss: 0.00361 RPN total loss: 0.02078 Total loss: 0.94665 timestamp: 1655038820.0597 iteration: 39705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07201 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.13857 L1 loss: 0.0000e+00 L2 loss: 0.60895 Learning rate: 0.02 Mask loss: 0.12825 RPN box loss: 0.02751 RPN score loss: 0.00406 RPN total loss: 0.03157 Total loss: 0.90735 timestamp: 1655038823.356156 iteration: 39710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13529 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.60888 Learning rate: 0.02 Mask loss: 0.12645 RPN box loss: 0.04838 RPN score loss: 0.00815 RPN total loss: 0.05653 Total loss: 0.98993 timestamp: 1655038826.664289 iteration: 39715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15909 FastRCNN class loss: 0.1131 FastRCNN total loss: 0.27219 L1 loss: 0.0000e+00 L2 loss: 0.60879 Learning rate: 0.02 Mask loss: 0.16771 RPN box loss: 0.03688 RPN score loss: 0.0177 RPN total loss: 0.05458 Total loss: 1.10326 timestamp: 1655038829.958423 iteration: 39720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15984 FastRCNN class loss: 0.09246 FastRCNN total loss: 0.2523 L1 loss: 0.0000e+00 L2 loss: 0.60869 Learning rate: 0.02 Mask loss: 0.18365 RPN box loss: 0.04994 RPN score loss: 0.00934 RPN total loss: 0.05928 Total loss: 1.10392 timestamp: 1655038833.2421737 iteration: 39725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19321 FastRCNN class loss: 0.07862 FastRCNN total loss: 0.27183 L1 loss: 0.0000e+00 L2 loss: 0.60858 Learning rate: 0.02 Mask loss: 0.17434 RPN box loss: 0.03105 RPN score loss: 0.00823 RPN total loss: 0.03927 Total loss: 1.09403 timestamp: 1655038836.5588129 iteration: 39730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04114 FastRCNN class loss: 0.04094 FastRCNN total loss: 0.08208 L1 loss: 0.0000e+00 L2 loss: 0.60849 Learning rate: 0.02 Mask loss: 0.10695 RPN box loss: 0.00349 RPN score loss: 0.00108 RPN total loss: 0.00457 Total loss: 0.8021 timestamp: 1655038839.8562734 iteration: 39735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08182 FastRCNN class loss: 0.05274 FastRCNN total loss: 0.13456 L1 loss: 0.0000e+00 L2 loss: 0.60843 Learning rate: 0.02 Mask loss: 0.1482 RPN box loss: 0.0152 RPN score loss: 0.00235 RPN total loss: 0.01755 Total loss: 0.90874 timestamp: 1655038843.0394194 iteration: 39740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07984 FastRCNN class loss: 0.10529 FastRCNN total loss: 0.18513 L1 loss: 0.0000e+00 L2 loss: 0.60838 Learning rate: 0.02 Mask loss: 0.17566 RPN box loss: 0.07656 RPN score loss: 0.02745 RPN total loss: 0.10401 Total loss: 1.07318 timestamp: 1655038846.336526 iteration: 39745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10956 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.17173 L1 loss: 0.0000e+00 L2 loss: 0.6083 Learning rate: 0.02 Mask loss: 0.20385 RPN box loss: 0.03422 RPN score loss: 0.00802 RPN total loss: 0.04224 Total loss: 1.02613 timestamp: 1655038849.5784461 iteration: 39750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13342 FastRCNN class loss: 0.0823 FastRCNN total loss: 0.21572 L1 loss: 0.0000e+00 L2 loss: 0.60822 Learning rate: 0.02 Mask loss: 0.19496 RPN box loss: 0.04103 RPN score loss: 0.01114 RPN total loss: 0.05217 Total loss: 1.07107 timestamp: 1655038852.8364377 iteration: 39755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06069 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.12962 L1 loss: 0.0000e+00 L2 loss: 0.60817 Learning rate: 0.02 Mask loss: 0.13104 RPN box loss: 0.03655 RPN score loss: 0.00438 RPN total loss: 0.04092 Total loss: 0.90975 timestamp: 1655038856.1408346 iteration: 39760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.08113 FastRCNN total loss: 0.15891 L1 loss: 0.0000e+00 L2 loss: 0.60808 Learning rate: 0.02 Mask loss: 0.1467 RPN box loss: 0.02496 RPN score loss: 0.00811 RPN total loss: 0.03307 Total loss: 0.94676 timestamp: 1655038859.4558 iteration: 39765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11748 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.21963 L1 loss: 0.0000e+00 L2 loss: 0.60802 Learning rate: 0.02 Mask loss: 0.21398 RPN box loss: 0.04576 RPN score loss: 0.01274 RPN total loss: 0.0585 Total loss: 1.10013 timestamp: 1655038862.718043 iteration: 39770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16304 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.23921 L1 loss: 0.0000e+00 L2 loss: 0.60795 Learning rate: 0.02 Mask loss: 0.1582 RPN box loss: 0.01928 RPN score loss: 0.00746 RPN total loss: 0.02674 Total loss: 1.0321 timestamp: 1655038865.9612567 iteration: 39775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19909 FastRCNN class loss: 0.08087 FastRCNN total loss: 0.27997 L1 loss: 0.0000e+00 L2 loss: 0.60789 Learning rate: 0.02 Mask loss: 0.18691 RPN box loss: 0.08335 RPN score loss: 0.00487 RPN total loss: 0.08822 Total loss: 1.16298 timestamp: 1655038869.2529771 iteration: 39780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09837 FastRCNN class loss: 0.12464 FastRCNN total loss: 0.22301 L1 loss: 0.0000e+00 L2 loss: 0.6078 Learning rate: 0.02 Mask loss: 0.12984 RPN box loss: 0.05889 RPN score loss: 0.01454 RPN total loss: 0.07343 Total loss: 1.03407 timestamp: 1655038872.506705 iteration: 39785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15011 FastRCNN class loss: 0.10065 FastRCNN total loss: 0.25076 L1 loss: 0.0000e+00 L2 loss: 0.6077 Learning rate: 0.02 Mask loss: 0.24703 RPN box loss: 0.05065 RPN score loss: 0.01304 RPN total loss: 0.06369 Total loss: 1.16919 timestamp: 1655038875.7661195 iteration: 39790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10754 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.17013 L1 loss: 0.0000e+00 L2 loss: 0.60761 Learning rate: 0.02 Mask loss: 0.15497 RPN box loss: 0.00471 RPN score loss: 0.00233 RPN total loss: 0.00704 Total loss: 0.93975 timestamp: 1655038879.010866 iteration: 39795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21153 FastRCNN class loss: 0.18904 FastRCNN total loss: 0.40057 L1 loss: 0.0000e+00 L2 loss: 0.60753 Learning rate: 0.02 Mask loss: 0.24304 RPN box loss: 0.04926 RPN score loss: 0.01895 RPN total loss: 0.06822 Total loss: 1.31935 timestamp: 1655038882.2243762 iteration: 39800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.18817 L1 loss: 0.0000e+00 L2 loss: 0.60745 Learning rate: 0.02 Mask loss: 0.12238 RPN box loss: 0.04163 RPN score loss: 0.00778 RPN total loss: 0.04941 Total loss: 0.96741 timestamp: 1655038885.4825354 iteration: 39805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12814 FastRCNN class loss: 0.04581 FastRCNN total loss: 0.17394 L1 loss: 0.0000e+00 L2 loss: 0.60738 Learning rate: 0.02 Mask loss: 0.11731 RPN box loss: 0.0044 RPN score loss: 0.0038 RPN total loss: 0.0082 Total loss: 0.90683 timestamp: 1655038888.7306318 iteration: 39810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09781 FastRCNN class loss: 0.06871 FastRCNN total loss: 0.16652 L1 loss: 0.0000e+00 L2 loss: 0.60728 Learning rate: 0.02 Mask loss: 0.10858 RPN box loss: 0.04638 RPN score loss: 0.00594 RPN total loss: 0.05232 Total loss: 0.93471 timestamp: 1655038892.0144267 iteration: 39815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08048 FastRCNN class loss: 0.07392 FastRCNN total loss: 0.1544 L1 loss: 0.0000e+00 L2 loss: 0.60721 Learning rate: 0.02 Mask loss: 0.11468 RPN box loss: 0.03414 RPN score loss: 0.01469 RPN total loss: 0.04882 Total loss: 0.92511 timestamp: 1655038895.2411785 iteration: 39820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15781 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.2334 L1 loss: 0.0000e+00 L2 loss: 0.60715 Learning rate: 0.02 Mask loss: 0.22095 RPN box loss: 0.03286 RPN score loss: 0.01102 RPN total loss: 0.04388 Total loss: 1.10539 timestamp: 1655038898.6341758 iteration: 39825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19598 FastRCNN class loss: 0.08514 FastRCNN total loss: 0.28112 L1 loss: 0.0000e+00 L2 loss: 0.60709 Learning rate: 0.02 Mask loss: 0.19389 RPN box loss: 0.02703 RPN score loss: 0.00559 RPN total loss: 0.03262 Total loss: 1.11472 timestamp: 1655038901.9275672 iteration: 39830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.059 FastRCNN class loss: 0.02897 FastRCNN total loss: 0.08798 L1 loss: 0.0000e+00 L2 loss: 0.60704 Learning rate: 0.02 Mask loss: 0.10797 RPN box loss: 0.01094 RPN score loss: 0.0069 RPN total loss: 0.01785 Total loss: 0.82083 timestamp: 1655038905.2419796 iteration: 39835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14644 FastRCNN class loss: 0.07624 FastRCNN total loss: 0.22268 L1 loss: 0.0000e+00 L2 loss: 0.60697 Learning rate: 0.02 Mask loss: 0.26568 RPN box loss: 0.02525 RPN score loss: 0.00575 RPN total loss: 0.031 Total loss: 1.12633 timestamp: 1655038908.4977322 iteration: 39840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.16782 L1 loss: 0.0000e+00 L2 loss: 0.60689 Learning rate: 0.02 Mask loss: 0.1744 RPN box loss: 0.02028 RPN score loss: 0.00526 RPN total loss: 0.02554 Total loss: 0.97465 timestamp: 1655038911.7874925 iteration: 39845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11892 FastRCNN class loss: 0.07209 FastRCNN total loss: 0.19101 L1 loss: 0.0000e+00 L2 loss: 0.60682 Learning rate: 0.02 Mask loss: 0.12055 RPN box loss: 0.02783 RPN score loss: 0.02684 RPN total loss: 0.05467 Total loss: 0.97304 timestamp: 1655038915.0884233 iteration: 39850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12372 FastRCNN class loss: 0.07581 FastRCNN total loss: 0.19953 L1 loss: 0.0000e+00 L2 loss: 0.60671 Learning rate: 0.02 Mask loss: 0.14582 RPN box loss: 0.08901 RPN score loss: 0.00713 RPN total loss: 0.09613 Total loss: 1.0482 timestamp: 1655038918.3360176 iteration: 39855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14441 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.22733 L1 loss: 0.0000e+00 L2 loss: 0.60663 Learning rate: 0.02 Mask loss: 0.13941 RPN box loss: 0.02409 RPN score loss: 0.00553 RPN total loss: 0.02961 Total loss: 1.00299 timestamp: 1655038921.5678518 iteration: 39860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.05262 FastRCNN total loss: 0.1728 L1 loss: 0.0000e+00 L2 loss: 0.60654 Learning rate: 0.02 Mask loss: 0.13429 RPN box loss: 0.03236 RPN score loss: 0.0051 RPN total loss: 0.03746 Total loss: 0.95109 timestamp: 1655038924.9004004 iteration: 39865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11306 FastRCNN class loss: 0.08769 FastRCNN total loss: 0.20075 L1 loss: 0.0000e+00 L2 loss: 0.60648 Learning rate: 0.02 Mask loss: 0.21389 RPN box loss: 0.01788 RPN score loss: 0.00837 RPN total loss: 0.02625 Total loss: 1.04737 timestamp: 1655038928.1313255 iteration: 39870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13865 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.22086 L1 loss: 0.0000e+00 L2 loss: 0.60639 Learning rate: 0.02 Mask loss: 0.15421 RPN box loss: 0.03085 RPN score loss: 0.00946 RPN total loss: 0.04031 Total loss: 1.02176 timestamp: 1655038931.3959703 iteration: 39875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18135 FastRCNN class loss: 0.0847 FastRCNN total loss: 0.26605 L1 loss: 0.0000e+00 L2 loss: 0.60628 Learning rate: 0.02 Mask loss: 0.15154 RPN box loss: 0.0312 RPN score loss: 0.01351 RPN total loss: 0.04471 Total loss: 1.06858 timestamp: 1655038934.6978335 iteration: 39880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1165 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.17349 L1 loss: 0.0000e+00 L2 loss: 0.60618 Learning rate: 0.02 Mask loss: 0.21251 RPN box loss: 0.01581 RPN score loss: 0.01265 RPN total loss: 0.02846 Total loss: 1.02065 timestamp: 1655038937.9774866 iteration: 39885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13743 FastRCNN class loss: 0.08511 FastRCNN total loss: 0.22254 L1 loss: 0.0000e+00 L2 loss: 0.60612 Learning rate: 0.02 Mask loss: 0.15886 RPN box loss: 0.02657 RPN score loss: 0.00743 RPN total loss: 0.034 Total loss: 1.02153 timestamp: 1655038941.199734 iteration: 39890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.143 FastRCNN class loss: 0.12511 FastRCNN total loss: 0.26811 L1 loss: 0.0000e+00 L2 loss: 0.60607 Learning rate: 0.02 Mask loss: 0.15243 RPN box loss: 0.03068 RPN score loss: 0.00987 RPN total loss: 0.04055 Total loss: 1.06716 timestamp: 1655038944.4886389 iteration: 39895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13378 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.19114 L1 loss: 0.0000e+00 L2 loss: 0.606 Learning rate: 0.02 Mask loss: 0.16665 RPN box loss: 0.02317 RPN score loss: 0.00291 RPN total loss: 0.02608 Total loss: 0.98988 timestamp: 1655038947.7690167 iteration: 39900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.08826 FastRCNN total loss: 0.18128 L1 loss: 0.0000e+00 L2 loss: 0.60591 Learning rate: 0.02 Mask loss: 0.15146 RPN box loss: 0.01572 RPN score loss: 0.01095 RPN total loss: 0.02667 Total loss: 0.96532 timestamp: 1655038951.0677044 iteration: 39905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21305 FastRCNN class loss: 0.16878 FastRCNN total loss: 0.38183 L1 loss: 0.0000e+00 L2 loss: 0.60583 Learning rate: 0.02 Mask loss: 0.34687 RPN box loss: 0.03623 RPN score loss: 0.01705 RPN total loss: 0.05328 Total loss: 1.38783 timestamp: 1655038954.399062 iteration: 39910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1486 FastRCNN class loss: 0.07819 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 0.60575 Learning rate: 0.02 Mask loss: 0.19105 RPN box loss: 0.03654 RPN score loss: 0.00735 RPN total loss: 0.0439 Total loss: 1.06748 timestamp: 1655038957.7004716 iteration: 39915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14468 FastRCNN class loss: 0.06317 FastRCNN total loss: 0.20784 L1 loss: 0.0000e+00 L2 loss: 0.60567 Learning rate: 0.02 Mask loss: 0.18354 RPN box loss: 0.07316 RPN score loss: 0.01135 RPN total loss: 0.08452 Total loss: 1.08157 timestamp: 1655038961.0023725 iteration: 39920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10126 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.16163 L1 loss: 0.0000e+00 L2 loss: 0.60561 Learning rate: 0.02 Mask loss: 0.10979 RPN box loss: 0.01631 RPN score loss: 0.00705 RPN total loss: 0.02336 Total loss: 0.90038 timestamp: 1655038964.3039052 iteration: 39925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19378 FastRCNN class loss: 0.12279 FastRCNN total loss: 0.31657 L1 loss: 0.0000e+00 L2 loss: 0.60554 Learning rate: 0.02 Mask loss: 0.25984 RPN box loss: 0.05977 RPN score loss: 0.01323 RPN total loss: 0.07299 Total loss: 1.25494 timestamp: 1655038967.5786996 iteration: 39930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17715 FastRCNN class loss: 0.09191 FastRCNN total loss: 0.26905 L1 loss: 0.0000e+00 L2 loss: 0.60547 Learning rate: 0.02 Mask loss: 0.20182 RPN box loss: 0.01792 RPN score loss: 0.00932 RPN total loss: 0.02724 Total loss: 1.10357 timestamp: 1655038970.8389773 iteration: 39935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21787 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.29501 L1 loss: 0.0000e+00 L2 loss: 0.60539 Learning rate: 0.02 Mask loss: 0.17833 RPN box loss: 0.02823 RPN score loss: 0.00619 RPN total loss: 0.03442 Total loss: 1.11315 timestamp: 1655038974.1201677 iteration: 39940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18766 FastRCNN class loss: 0.13623 FastRCNN total loss: 0.32389 L1 loss: 0.0000e+00 L2 loss: 0.60529 Learning rate: 0.02 Mask loss: 0.21986 RPN box loss: 0.01833 RPN score loss: 0.00677 RPN total loss: 0.0251 Total loss: 1.17415 timestamp: 1655038977.3817675 iteration: 39945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10803 FastRCNN class loss: 0.07109 FastRCNN total loss: 0.17912 L1 loss: 0.0000e+00 L2 loss: 0.60521 Learning rate: 0.02 Mask loss: 0.1358 RPN box loss: 0.02061 RPN score loss: 0.00355 RPN total loss: 0.02416 Total loss: 0.9443 timestamp: 1655038980.6377826 iteration: 39950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18975 FastRCNN class loss: 0.09223 FastRCNN total loss: 0.28197 L1 loss: 0.0000e+00 L2 loss: 0.60514 Learning rate: 0.02 Mask loss: 0.15777 RPN box loss: 0.02613 RPN score loss: 0.00413 RPN total loss: 0.03026 Total loss: 1.07514 timestamp: 1655038983.8524423 iteration: 39955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13031 FastRCNN class loss: 0.06281 FastRCNN total loss: 0.19312 L1 loss: 0.0000e+00 L2 loss: 0.60506 Learning rate: 0.02 Mask loss: 0.16263 RPN box loss: 0.00513 RPN score loss: 0.00673 RPN total loss: 0.01186 Total loss: 0.97268 timestamp: 1655038987.119084 iteration: 39960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13046 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.19215 L1 loss: 0.0000e+00 L2 loss: 0.60498 Learning rate: 0.02 Mask loss: 0.15043 RPN box loss: 0.03859 RPN score loss: 0.00517 RPN total loss: 0.04376 Total loss: 0.99132 timestamp: 1655038990.360408 iteration: 39965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09387 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.1523 L1 loss: 0.0000e+00 L2 loss: 0.6049 Learning rate: 0.02 Mask loss: 0.10413 RPN box loss: 0.01882 RPN score loss: 0.00311 RPN total loss: 0.02193 Total loss: 0.88326 timestamp: 1655038993.611773 iteration: 39970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12019 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.20826 L1 loss: 0.0000e+00 L2 loss: 0.60482 Learning rate: 0.02 Mask loss: 0.19035 RPN box loss: 0.04568 RPN score loss: 0.00557 RPN total loss: 0.05124 Total loss: 1.05467 timestamp: 1655038996.8581161 iteration: 39975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0764 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.12849 L1 loss: 0.0000e+00 L2 loss: 0.60474 Learning rate: 0.02 Mask loss: 0.11186 RPN box loss: 0.00771 RPN score loss: 0.00103 RPN total loss: 0.00874 Total loss: 0.85383 timestamp: 1655039000.1622844 iteration: 39980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1402 FastRCNN class loss: 0.1061 FastRCNN total loss: 0.2463 L1 loss: 0.0000e+00 L2 loss: 0.60468 Learning rate: 0.02 Mask loss: 0.12763 RPN box loss: 0.06485 RPN score loss: 0.00361 RPN total loss: 0.06846 Total loss: 1.04707 timestamp: 1655039003.456629 iteration: 39985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12796 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.20481 L1 loss: 0.0000e+00 L2 loss: 0.60458 Learning rate: 0.02 Mask loss: 0.21011 RPN box loss: 0.05477 RPN score loss: 0.00919 RPN total loss: 0.06396 Total loss: 1.08346 timestamp: 1655039006.696123 iteration: 39990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14239 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.22825 L1 loss: 0.0000e+00 L2 loss: 0.6045 Learning rate: 0.02 Mask loss: 0.11914 RPN box loss: 0.00987 RPN score loss: 0.00328 RPN total loss: 0.01314 Total loss: 0.96503 timestamp: 1655039010.0351706 iteration: 39995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15237 FastRCNN class loss: 0.11129 FastRCNN total loss: 0.26366 L1 loss: 0.0000e+00 L2 loss: 0.60443 Learning rate: 0.02 Mask loss: 0.29657 RPN box loss: 0.06009 RPN score loss: 0.01164 RPN total loss: 0.07173 Total loss: 1.23638 timestamp: 1655039013.298949 iteration: 40000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11181 FastRCNN class loss: 0.0893 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 0.60435 Learning rate: 0.02 Mask loss: 0.20778 RPN box loss: 0.04357 RPN score loss: 0.00345 RPN total loss: 0.04702 Total loss: 1.06025 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 6.3527s - Throughput: 0.6 imgs/s Running inference on batch 002/125... - Step Time: 0.8316s - Throughput: 4.8 imgs/s Running inference on batch 003/125... - Step Time: 0.8324s - Throughput: 4.8 imgs/s Running inference on batch 004/125... - Step Time: 0.8690s - Throughput: 4.6 imgs/s Running inference on batch 005/125... - Step Time: 0.8582s - Throughput: 4.7 imgs/s Running inference on batch 006/125... - Step Time: 0.8383s - Throughput: 4.8 imgs/s Running inference on batch 007/125... - Step Time: 0.6289s - Throughput: 6.4 imgs/s Running inference on batch 008/125... - Step Time: 0.8756s - Throughput: 4.6 imgs/s Running inference on batch 009/125... - Step Time: 0.8771s - Throughput: 4.6 imgs/s Running inference on batch 010/125... - Step Time: 0.8230s - Throughput: 4.9 imgs/s Running inference on batch 011/125... - Step Time: 0.8733s - Throughput: 4.6 imgs/s Running inference on batch 012/125... - Step Time: 0.8428s - Throughput: 4.7 imgs/s Running inference on batch 013/125... - Step Time: 0.8557s - Throughput: 4.7 imgs/s Running inference on batch 014/125... - Step Time: 0.8263s - Throughput: 4.8 imgs/s Running inference on batch 015/125... - Step Time: 0.8372s - Throughput: 4.8 imgs/s Running inference on batch 016/125... - Step Time: 0.8374s - Throughput: 4.8 imgs/s Running inference on batch 017/125... - Step Time: 0.8569s - Throughput: 4.7 imgs/s Running inference on batch 018/125... - Step Time: 0.7908s - Throughput: 5.1 imgs/s Running inference on batch 019/125... - Step Time: 0.8798s - Throughput: 4.5 imgs/s Running inference on batch 020/125... - Step Time: 0.8434s - Throughput: 4.7 imgs/s Running inference on batch 021/125... - Step Time: 0.8308s - Throughput: 4.8 imgs/s Running inference on batch 022/125... - Step Time: 0.9067s - Throughput: 4.4 imgs/s Running inference on batch 023/125... - Step Time: 0.8657s - Throughput: 4.6 imgs/s Running inference on batch 024/125... - 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Step Time: 0.9073s - Throughput: 4.4 imgs/s Running inference on batch 049/125... - Step Time: 0.8788s - Throughput: 4.6 imgs/s Running inference on batch 050/125... - Step Time: 0.8598s - Throughput: 4.7 imgs/s Running inference on batch 051/125... - Step Time: 0.8634s - Throughput: 4.6 imgs/s Running inference on batch 052/125... - Step Time: 0.8361s - Throughput: 4.8 imgs/s Running inference on batch 053/125... - Step Time: 0.8546s - Throughput: 4.7 imgs/s Running inference on batch 054/125... - Step Time: 0.8597s - Throughput: 4.7 imgs/s Running inference on batch 055/125... - Step Time: 0.8445s - Throughput: 4.7 imgs/s Running inference on batch 056/125... - Step Time: 0.8509s - Throughput: 4.7 imgs/s Running inference on batch 057/125... - Step Time: 0.8189s - Throughput: 4.9 imgs/s Running inference on batch 058/125... - Step Time: 0.8690s - Throughput: 4.6 imgs/s Running inference on batch 059/125... - Step Time: 0.8496s - Throughput: 4.7 imgs/s Running inference on batch 060/125... - 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Step Time: 0.8777s - Throughput: 4.6 imgs/s Running inference on batch 073/125... - Step Time: 0.8417s - Throughput: 4.8 imgs/s Running inference on batch 074/125... - Step Time: 0.8296s - Throughput: 4.8 imgs/s Running inference on batch 075/125... - Step Time: 0.8662s - Throughput: 4.6 imgs/s Running inference on batch 076/125... - Step Time: 0.8435s - Throughput: 4.7 imgs/s Running inference on batch 077/125... - Step Time: 0.8457s - Throughput: 4.7 imgs/s Running inference on batch 078/125... - Step Time: 0.8440s - Throughput: 4.7 imgs/s Running inference on batch 079/125... - Step Time: 0.8520s - Throughput: 4.7 imgs/s Running inference on batch 080/125... - Step Time: 0.8880s - Throughput: 4.5 imgs/s Running inference on batch 081/125... - Step Time: 0.8343s - Throughput: 4.8 imgs/s Running inference on batch 082/125... - Step Time: 0.8305s - Throughput: 4.8 imgs/s Running inference on batch 083/125... - Step Time: 0.8405s - Throughput: 4.8 imgs/s Running inference on batch 084/125... - Step Time: 0.8283s - Throughput: 4.8 imgs/s Running inference on batch 085/125... - Step Time: 0.8319s - Throughput: 4.8 imgs/s Running inference on batch 086/125... - Step Time: 0.8061s - Throughput: 5.0 imgs/s Running inference on batch 087/125... - Step Time: 0.9125s - Throughput: 4.4 imgs/s Running inference on batch 088/125... - Step Time: 0.8640s - Throughput: 4.6 imgs/s Running inference on batch 089/125... - Step Time: 0.8725s - Throughput: 4.6 imgs/s Running inference on batch 090/125... - Step Time: 0.7735s - Throughput: 5.2 imgs/s Running inference on batch 091/125... - Step Time: 0.8689s - Throughput: 4.6 imgs/s Running inference on batch 092/125... - Step Time: 0.8580s - Throughput: 4.7 imgs/s Running inference on batch 093/125... - Step Time: 0.8486s - Throughput: 4.7 imgs/s Running inference on batch 094/125... - Step Time: 0.8559s - Throughput: 4.7 imgs/s Running inference on batch 095/125... - Step Time: 0.8346s - Throughput: 4.8 imgs/s Running inference on batch 096/125... - Step Time: 0.8523s - Throughput: 4.7 imgs/s Running inference on batch 097/125... - Step Time: 0.8805s - Throughput: 4.5 imgs/s Running inference on batch 098/125... - Step Time: 0.8293s - Throughput: 4.8 imgs/s Running inference on batch 099/125... - Step Time: 0.8038s - Throughput: 5.0 imgs/s Running inference on batch 100/125... - Step Time: 0.8121s - Throughput: 4.9 imgs/s Running inference on batch 101/125... - Step Time: 0.8294s - Throughput: 4.8 imgs/s Running inference on batch 102/125... - Step Time: 0.8638s - Throughput: 4.6 imgs/s Running inference on batch 103/125... - Step Time: 0.8507s - Throughput: 4.7 imgs/s Running inference on batch 104/125... - Step Time: 0.8689s - Throughput: 4.6 imgs/s Running inference on batch 105/125... - Step Time: 0.8112s - Throughput: 4.9 imgs/s Running inference on batch 106/125... - Step Time: 0.8712s - Throughput: 4.6 imgs/s Running inference on batch 107/125... - Step Time: 0.8835s - Throughput: 4.5 imgs/s Running inference on batch 108/125... - Step Time: 0.8654s - Throughput: 4.6 imgs/s Running inference on batch 109/125... - Step Time: 0.8745s - Throughput: 4.6 imgs/s Running inference on batch 110/125... - Step Time: 0.8940s - Throughput: 4.5 imgs/s Running inference on batch 111/125... - Step Time: 0.8438s - Throughput: 4.7 imgs/s Running inference on batch 112/125... - Step Time: 0.8572s - Throughput: 4.7 imgs/s Running inference on batch 113/125... - Step Time: 0.8584s - Throughput: 4.7 imgs/s Running inference on batch 114/125... - Step Time: 0.8216s - Throughput: 4.9 imgs/s Running inference on batch 115/125... - Step Time: 0.8662s - Throughput: 4.6 imgs/s Running inference on batch 116/125... - Step Time: 0.8636s - Throughput: 4.6 imgs/s Running inference on batch 117/125... - Step Time: 0.8457s - Throughput: 4.7 imgs/s Running inference on batch 118/125... - Step Time: 0.9233s - Throughput: 4.3 imgs/s Running inference on batch 119/125... - Step Time: 0.8568s - Throughput: 4.7 imgs/s Running inference on batch 120/125... - Step Time: 0.8454s - Throughput: 4.7 imgs/s Running inference on batch 121/125... - Step Time: 0.8425s - Throughput: 4.7 imgs/s Running inference on batch 122/125... - Step Time: 0.7981s - Throughput: 5.0 imgs/s Running inference on batch 123/125... - Step Time: 0.8329s - Throughput: 4.8 imgs/s Running inference on batch 124/125... - Step Time: 0.8853s - Throughput: 4.5 imgs/s Running inference on batch 125/125... - Step Time: 0.8262s - Throughput: 4.8 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: 4.7 samples/sec Total processed steps: 125 Total processing time: 0.0h 09m 45s ==================== Metrics ==================== AP: 0.177689567 AP50: 0.278852522 AP75: 0.169460744 APl: 0.206666782 APm: 0.049649131 APs: 0.015369908 ARl: 0.401424527 ARm: 0.092504114 ARmax1: 0.259330004 ARmax10: 0.335851729 ARmax100: 0.342800736 ARs: 0.018679550 mask_AP: 0.137963399 mask_AP50: 0.230018646 mask_AP75: 0.145899504 mask_APl: 0.163289890 mask_APm: 0.016260672 mask_APs: 0.000935093 mask_ARl: 0.280878246 mask_ARm: 0.041664809 mask_ARmax1: 0.197448522 mask_ARmax10: 0.231901571 mask_ARmax100: 0.235034153 mask_ARs: 0.003703704 ================================= 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] 549.0 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: 1655040248.1261437 iteration: 40005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15006 FastRCNN class loss: 0.03958 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 0.6043 Learning rate: 0.002 Mask loss: 0.1051 RPN box loss: 0.01658 RPN score loss: 0.00269 RPN total loss: 0.01928 Total loss: 0.91832 timestamp: 1655040251.2913232 iteration: 40010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.17904 L1 loss: 0.0000e+00 L2 loss: 0.6043 Learning rate: 0.002 Mask loss: 0.15037 RPN box loss: 0.02513 RPN score loss: 0.00379 RPN total loss: 0.02892 Total loss: 0.96263 timestamp: 1655040254.445752 iteration: 40015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.05993 FastRCNN total loss: 0.18377 L1 loss: 0.0000e+00 L2 loss: 0.60429 Learning rate: 0.002 Mask loss: 0.19914 RPN box loss: 0.00968 RPN score loss: 0.00541 RPN total loss: 0.01509 Total loss: 1.00229 timestamp: 1655040257.6743324 iteration: 40020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13639 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.21903 L1 loss: 0.0000e+00 L2 loss: 0.60429 Learning rate: 0.002 Mask loss: 0.18007 RPN box loss: 0.04664 RPN score loss: 0.00536 RPN total loss: 0.052 Total loss: 1.05539 timestamp: 1655040261.0095367 iteration: 40025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10279 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.16163 L1 loss: 0.0000e+00 L2 loss: 0.60428 Learning rate: 0.002 Mask loss: 0.15146 RPN box loss: 0.05352 RPN score loss: 0.00314 RPN total loss: 0.05665 Total loss: 0.97402 timestamp: 1655040264.1997511 iteration: 40030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11619 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.17717 L1 loss: 0.0000e+00 L2 loss: 0.60428 Learning rate: 0.002 Mask loss: 0.09459 RPN box loss: 0.01302 RPN score loss: 0.0024 RPN total loss: 0.01542 Total loss: 0.89146 timestamp: 1655040267.384038 iteration: 40035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07864 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.15769 L1 loss: 0.0000e+00 L2 loss: 0.60427 Learning rate: 0.002 Mask loss: 0.17823 RPN box loss: 0.01008 RPN score loss: 0.00468 RPN total loss: 0.01476 Total loss: 0.95495 timestamp: 1655040270.6834106 iteration: 40040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11802 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.19855 L1 loss: 0.0000e+00 L2 loss: 0.60426 Learning rate: 0.002 Mask loss: 0.20751 RPN box loss: 0.00722 RPN score loss: 0.00223 RPN total loss: 0.00945 Total loss: 1.01978 timestamp: 1655040273.9567447 iteration: 40045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19547 FastRCNN class loss: 0.08042 FastRCNN total loss: 0.27589 L1 loss: 0.0000e+00 L2 loss: 0.60425 Learning rate: 0.002 Mask loss: 0.10536 RPN box loss: 0.02103 RPN score loss: 0.00412 RPN total loss: 0.02515 Total loss: 1.01065 timestamp: 1655040277.2480195 iteration: 40050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14078 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.21448 L1 loss: 0.0000e+00 L2 loss: 0.60424 Learning rate: 0.002 Mask loss: 0.144 RPN box loss: 0.0156 RPN score loss: 0.00169 RPN total loss: 0.01729 Total loss: 0.98002 timestamp: 1655040280.4752283 iteration: 40055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11865 FastRCNN class loss: 0.0739 FastRCNN total loss: 0.19255 L1 loss: 0.0000e+00 L2 loss: 0.60423 Learning rate: 0.002 Mask loss: 0.13383 RPN box loss: 0.04347 RPN score loss: 0.00814 RPN total loss: 0.05161 Total loss: 0.98223 timestamp: 1655040283.724541 iteration: 40060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13669 FastRCNN class loss: 0.15273 FastRCNN total loss: 0.28942 L1 loss: 0.0000e+00 L2 loss: 0.60422 Learning rate: 0.002 Mask loss: 0.22147 RPN box loss: 0.0357 RPN score loss: 0.00784 RPN total loss: 0.04353 Total loss: 1.15865 timestamp: 1655040286.9919972 iteration: 40065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09882 FastRCNN class loss: 0.05945 FastRCNN total loss: 0.15827 L1 loss: 0.0000e+00 L2 loss: 0.60422 Learning rate: 0.002 Mask loss: 0.14733 RPN box loss: 0.05154 RPN score loss: 0.00404 RPN total loss: 0.05558 Total loss: 0.9654 timestamp: 1655040290.303982 iteration: 40070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12936 FastRCNN class loss: 0.08447 FastRCNN total loss: 0.21383 L1 loss: 0.0000e+00 L2 loss: 0.60421 Learning rate: 0.002 Mask loss: 0.1217 RPN box loss: 0.024 RPN score loss: 0.00481 RPN total loss: 0.02881 Total loss: 0.96854 timestamp: 1655040293.5905657 iteration: 40075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15365 FastRCNN class loss: 0.0881 FastRCNN total loss: 0.24175 L1 loss: 0.0000e+00 L2 loss: 0.6042 Learning rate: 0.002 Mask loss: 0.15959 RPN box loss: 0.02697 RPN score loss: 0.01448 RPN total loss: 0.04145 Total loss: 1.04699 timestamp: 1655040296.796837 iteration: 40080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07324 FastRCNN class loss: 0.03371 FastRCNN total loss: 0.10694 L1 loss: 0.0000e+00 L2 loss: 0.60419 Learning rate: 0.002 Mask loss: 0.11487 RPN box loss: 0.01841 RPN score loss: 0.00243 RPN total loss: 0.02083 Total loss: 0.84683 timestamp: 1655040300.0646808 iteration: 40085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14607 FastRCNN class loss: 0.08744 FastRCNN total loss: 0.23351 L1 loss: 0.0000e+00 L2 loss: 0.60418 Learning rate: 0.002 Mask loss: 0.21372 RPN box loss: 0.02231 RPN score loss: 0.0062 RPN total loss: 0.02851 Total loss: 1.07992 timestamp: 1655040303.3749735 iteration: 40090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15315 FastRCNN class loss: 0.09376 FastRCNN total loss: 0.24691 L1 loss: 0.0000e+00 L2 loss: 0.60417 Learning rate: 0.002 Mask loss: 0.13925 RPN box loss: 0.02813 RPN score loss: 0.00685 RPN total loss: 0.03498 Total loss: 1.02532 timestamp: 1655040306.6430156 iteration: 40095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08659 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.14707 L1 loss: 0.0000e+00 L2 loss: 0.60416 Learning rate: 0.002 Mask loss: 0.08615 RPN box loss: 0.01608 RPN score loss: 0.00238 RPN total loss: 0.01846 Total loss: 0.85584 timestamp: 1655040309.9025192 iteration: 40100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.05376 FastRCNN total loss: 0.13573 L1 loss: 0.0000e+00 L2 loss: 0.60415 Learning rate: 0.002 Mask loss: 0.10062 RPN box loss: 0.03448 RPN score loss: 0.0057 RPN total loss: 0.04018 Total loss: 0.88069 timestamp: 1655040313.2555523 iteration: 40105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13302 FastRCNN class loss: 0.10597 FastRCNN total loss: 0.23898 L1 loss: 0.0000e+00 L2 loss: 0.60414 Learning rate: 0.002 Mask loss: 0.13262 RPN box loss: 0.0325 RPN score loss: 0.00378 RPN total loss: 0.03628 Total loss: 1.01203 timestamp: 1655040316.5190423 iteration: 40110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13872 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.20604 L1 loss: 0.0000e+00 L2 loss: 0.60413 Learning rate: 0.002 Mask loss: 0.1273 RPN box loss: 0.01753 RPN score loss: 0.0058 RPN total loss: 0.02333 Total loss: 0.96081 timestamp: 1655040319.8199997 iteration: 40115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11373 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.18004 L1 loss: 0.0000e+00 L2 loss: 0.60413 Learning rate: 0.002 Mask loss: 0.17397 RPN box loss: 0.02148 RPN score loss: 0.00621 RPN total loss: 0.02768 Total loss: 0.98582 timestamp: 1655040323.05314 iteration: 40120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05585 FastRCNN class loss: 0.03865 FastRCNN total loss: 0.09449 L1 loss: 0.0000e+00 L2 loss: 0.60412 Learning rate: 0.002 Mask loss: 0.10592 RPN box loss: 0.00216 RPN score loss: 0.00097 RPN total loss: 0.00313 Total loss: 0.80767 timestamp: 1655040326.2858827 iteration: 40125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08362 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.15391 L1 loss: 0.0000e+00 L2 loss: 0.60411 Learning rate: 0.002 Mask loss: 0.13864 RPN box loss: 0.01937 RPN score loss: 0.00775 RPN total loss: 0.02712 Total loss: 0.92377 timestamp: 1655040329.47561 iteration: 40130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12055 FastRCNN class loss: 0.09104 FastRCNN total loss: 0.21158 L1 loss: 0.0000e+00 L2 loss: 0.6041 Learning rate: 0.002 Mask loss: 0.15992 RPN box loss: 0.05943 RPN score loss: 0.00948 RPN total loss: 0.06891 Total loss: 1.04452 timestamp: 1655040332.813355 iteration: 40135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.08691 FastRCNN total loss: 0.21452 L1 loss: 0.0000e+00 L2 loss: 0.60409 Learning rate: 0.002 Mask loss: 0.17456 RPN box loss: 0.02997 RPN score loss: 0.01391 RPN total loss: 0.04389 Total loss: 1.03706 timestamp: 1655040336.0720396 iteration: 40140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17096 FastRCNN class loss: 0.09421 FastRCNN total loss: 0.26517 L1 loss: 0.0000e+00 L2 loss: 0.60408 Learning rate: 0.002 Mask loss: 0.12401 RPN box loss: 0.02546 RPN score loss: 0.00478 RPN total loss: 0.03024 Total loss: 1.0235 timestamp: 1655040339.3120317 iteration: 40145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1278 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.18687 L1 loss: 0.0000e+00 L2 loss: 0.60407 Learning rate: 0.002 Mask loss: 0.11377 RPN box loss: 0.00453 RPN score loss: 0.00465 RPN total loss: 0.00918 Total loss: 0.91388 timestamp: 1655040342.6340983 iteration: 40150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.09396 FastRCNN total loss: 0.20676 L1 loss: 0.0000e+00 L2 loss: 0.60407 Learning rate: 0.002 Mask loss: 0.1171 RPN box loss: 0.02064 RPN score loss: 0.00362 RPN total loss: 0.02426 Total loss: 0.95219 timestamp: 1655040345.912267 iteration: 40155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06601 FastRCNN class loss: 0.04608 FastRCNN total loss: 0.11209 L1 loss: 0.0000e+00 L2 loss: 0.60406 Learning rate: 0.002 Mask loss: 0.09288 RPN box loss: 0.01225 RPN score loss: 0.00218 RPN total loss: 0.01443 Total loss: 0.82345 timestamp: 1655040349.2245626 iteration: 40160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09575 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.1684 L1 loss: 0.0000e+00 L2 loss: 0.60405 Learning rate: 0.002 Mask loss: 0.16598 RPN box loss: 0.00969 RPN score loss: 0.00248 RPN total loss: 0.01217 Total loss: 0.9506 timestamp: 1655040352.5286968 iteration: 40165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.04694 FastRCNN total loss: 0.13288 L1 loss: 0.0000e+00 L2 loss: 0.60404 Learning rate: 0.002 Mask loss: 0.12718 RPN box loss: 0.02091 RPN score loss: 0.00301 RPN total loss: 0.02392 Total loss: 0.88802 timestamp: 1655040355.8128033 iteration: 40170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1109 FastRCNN class loss: 0.09116 FastRCNN total loss: 0.20206 L1 loss: 0.0000e+00 L2 loss: 0.60403 Learning rate: 0.002 Mask loss: 0.24893 RPN box loss: 0.0385 RPN score loss: 0.01281 RPN total loss: 0.05131 Total loss: 1.10633 timestamp: 1655040359.1174343 iteration: 40175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11884 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.18308 L1 loss: 0.0000e+00 L2 loss: 0.60402 Learning rate: 0.002 Mask loss: 0.13607 RPN box loss: 0.0099 RPN score loss: 0.00411 RPN total loss: 0.01402 Total loss: 0.93719 timestamp: 1655040362.4238856 iteration: 40180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12596 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.19144 L1 loss: 0.0000e+00 L2 loss: 0.60401 Learning rate: 0.002 Mask loss: 0.14623 RPN box loss: 0.02026 RPN score loss: 0.00754 RPN total loss: 0.0278 Total loss: 0.96948 timestamp: 1655040365.6847105 iteration: 40185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12861 FastRCNN class loss: 0.15333 FastRCNN total loss: 0.28194 L1 loss: 0.0000e+00 L2 loss: 0.604 Learning rate: 0.002 Mask loss: 0.19393 RPN box loss: 0.04322 RPN score loss: 0.01488 RPN total loss: 0.05811 Total loss: 1.13797 timestamp: 1655040369.038388 iteration: 40190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13311 FastRCNN class loss: 0.11516 FastRCNN total loss: 0.24827 L1 loss: 0.0000e+00 L2 loss: 0.60399 Learning rate: 0.002 Mask loss: 0.16771 RPN box loss: 0.02516 RPN score loss: 0.00539 RPN total loss: 0.03055 Total loss: 1.05052 timestamp: 1655040372.2649536 iteration: 40195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12885 FastRCNN class loss: 0.10937 FastRCNN total loss: 0.23822 L1 loss: 0.0000e+00 L2 loss: 0.60398 Learning rate: 0.002 Mask loss: 0.21853 RPN box loss: 0.03382 RPN score loss: 0.00723 RPN total loss: 0.04105 Total loss: 1.10177 timestamp: 1655040375.5975115 iteration: 40200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19444 FastRCNN class loss: 0.09819 FastRCNN total loss: 0.29263 L1 loss: 0.0000e+00 L2 loss: 0.60397 Learning rate: 0.002 Mask loss: 0.1353 RPN box loss: 0.03273 RPN score loss: 0.00725 RPN total loss: 0.03998 Total loss: 1.07188 timestamp: 1655040378.9164052 iteration: 40205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08494 FastRCNN class loss: 0.09928 FastRCNN total loss: 0.18422 L1 loss: 0.0000e+00 L2 loss: 0.60396 Learning rate: 0.002 Mask loss: 0.15122 RPN box loss: 0.02652 RPN score loss: 0.0028 RPN total loss: 0.02932 Total loss: 0.96872 timestamp: 1655040382.2111049 iteration: 40210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14592 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.22554 L1 loss: 0.0000e+00 L2 loss: 0.60395 Learning rate: 0.002 Mask loss: 0.22658 RPN box loss: 0.01315 RPN score loss: 0.00833 RPN total loss: 0.02148 Total loss: 1.07755 timestamp: 1655040385.5218492 iteration: 40215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16622 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.24323 L1 loss: 0.0000e+00 L2 loss: 0.60395 Learning rate: 0.002 Mask loss: 0.21992 RPN box loss: 0.01564 RPN score loss: 0.00317 RPN total loss: 0.01881 Total loss: 1.08591 timestamp: 1655040388.7839234 iteration: 40220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05318 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.09589 L1 loss: 0.0000e+00 L2 loss: 0.60394 Learning rate: 0.002 Mask loss: 0.10001 RPN box loss: 0.02928 RPN score loss: 0.00517 RPN total loss: 0.03445 Total loss: 0.83428 timestamp: 1655040392.0015128 iteration: 40225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06133 FastRCNN class loss: 0.04399 FastRCNN total loss: 0.10531 L1 loss: 0.0000e+00 L2 loss: 0.60393 Learning rate: 0.002 Mask loss: 0.13425 RPN box loss: 0.01951 RPN score loss: 0.00542 RPN total loss: 0.02493 Total loss: 0.86842 timestamp: 1655040395.2956312 iteration: 40230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.09407 FastRCNN total loss: 0.2107 L1 loss: 0.0000e+00 L2 loss: 0.60392 Learning rate: 0.002 Mask loss: 0.25496 RPN box loss: 0.01091 RPN score loss: 0.006 RPN total loss: 0.01691 Total loss: 1.08649 timestamp: 1655040398.5488713 iteration: 40235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13859 FastRCNN class loss: 0.06649 FastRCNN total loss: 0.20509 L1 loss: 0.0000e+00 L2 loss: 0.60391 Learning rate: 0.002 Mask loss: 0.11125 RPN box loss: 0.00635 RPN score loss: 0.00241 RPN total loss: 0.00876 Total loss: 0.92901 timestamp: 1655040401.8650014 iteration: 40240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1407 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.19915 L1 loss: 0.0000e+00 L2 loss: 0.6039 Learning rate: 0.002 Mask loss: 0.11638 RPN box loss: 0.00773 RPN score loss: 0.00655 RPN total loss: 0.01428 Total loss: 0.93371 timestamp: 1655040405.140535 iteration: 40245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10336 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.18987 L1 loss: 0.0000e+00 L2 loss: 0.60389 Learning rate: 0.002 Mask loss: 0.15381 RPN box loss: 0.01725 RPN score loss: 0.00515 RPN total loss: 0.02239 Total loss: 0.96997 timestamp: 1655040408.4559507 iteration: 40250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08504 FastRCNN class loss: 0.04922 FastRCNN total loss: 0.13426 L1 loss: 0.0000e+00 L2 loss: 0.60389 Learning rate: 0.002 Mask loss: 0.11425 RPN box loss: 0.02676 RPN score loss: 0.00754 RPN total loss: 0.0343 Total loss: 0.8867 timestamp: 1655040411.7120361 iteration: 40255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12387 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.17501 L1 loss: 0.0000e+00 L2 loss: 0.60388 Learning rate: 0.002 Mask loss: 0.08984 RPN box loss: 0.00879 RPN score loss: 0.00431 RPN total loss: 0.0131 Total loss: 0.88183 timestamp: 1655040415.0366414 iteration: 40260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08076 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.15964 L1 loss: 0.0000e+00 L2 loss: 0.60387 Learning rate: 0.002 Mask loss: 0.14747 RPN box loss: 0.00971 RPN score loss: 0.00173 RPN total loss: 0.01143 Total loss: 0.92242 timestamp: 1655040418.345363 iteration: 40265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11091 FastRCNN class loss: 0.09247 FastRCNN total loss: 0.20338 L1 loss: 0.0000e+00 L2 loss: 0.60386 Learning rate: 0.002 Mask loss: 0.1422 RPN box loss: 0.04044 RPN score loss: 0.0099 RPN total loss: 0.05034 Total loss: 0.99978 timestamp: 1655040421.607908 iteration: 40270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.18382 L1 loss: 0.0000e+00 L2 loss: 0.60385 Learning rate: 0.002 Mask loss: 0.19581 RPN box loss: 0.01543 RPN score loss: 0.00566 RPN total loss: 0.02109 Total loss: 1.00457 timestamp: 1655040424.9034731 iteration: 40275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12593 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.1951 L1 loss: 0.0000e+00 L2 loss: 0.60384 Learning rate: 0.002 Mask loss: 0.16353 RPN box loss: 0.029 RPN score loss: 0.00315 RPN total loss: 0.03214 Total loss: 0.99462 timestamp: 1655040428.1806583 iteration: 40280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1484 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.21693 L1 loss: 0.0000e+00 L2 loss: 0.60383 Learning rate: 0.002 Mask loss: 0.15503 RPN box loss: 0.00585 RPN score loss: 0.00392 RPN total loss: 0.00978 Total loss: 0.98556 timestamp: 1655040431.4479191 iteration: 40285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12593 FastRCNN class loss: 0.05173 FastRCNN total loss: 0.17766 L1 loss: 0.0000e+00 L2 loss: 0.60381 Learning rate: 0.002 Mask loss: 0.09598 RPN box loss: 0.02906 RPN score loss: 0.00607 RPN total loss: 0.03513 Total loss: 0.91259 timestamp: 1655040434.6731281 iteration: 40290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07458 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.14924 L1 loss: 0.0000e+00 L2 loss: 0.60381 Learning rate: 0.002 Mask loss: 0.11661 RPN box loss: 0.0149 RPN score loss: 0.00203 RPN total loss: 0.01693 Total loss: 0.88659 timestamp: 1655040438.0397897 iteration: 40295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0841 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.14323 L1 loss: 0.0000e+00 L2 loss: 0.6038 Learning rate: 0.002 Mask loss: 0.13797 RPN box loss: 0.07373 RPN score loss: 0.00416 RPN total loss: 0.0779 Total loss: 0.9629 timestamp: 1655040441.2460897 iteration: 40300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.1298 FastRCNN total loss: 0.29251 L1 loss: 0.0000e+00 L2 loss: 0.60379 Learning rate: 0.002 Mask loss: 0.18251 RPN box loss: 0.03744 RPN score loss: 0.0048 RPN total loss: 0.04224 Total loss: 1.12105 timestamp: 1655040444.451714 iteration: 40305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14566 FastRCNN class loss: 0.08365 FastRCNN total loss: 0.22931 L1 loss: 0.0000e+00 L2 loss: 0.60378 Learning rate: 0.002 Mask loss: 0.15314 RPN box loss: 0.01104 RPN score loss: 0.00389 RPN total loss: 0.01493 Total loss: 1.00116 timestamp: 1655040447.8087056 iteration: 40310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11286 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.18834 L1 loss: 0.0000e+00 L2 loss: 0.60377 Learning rate: 0.002 Mask loss: 0.15273 RPN box loss: 0.02046 RPN score loss: 0.00391 RPN total loss: 0.02437 Total loss: 0.96921 timestamp: 1655040451.0995631 iteration: 40315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.06099 FastRCNN total loss: 0.17214 L1 loss: 0.0000e+00 L2 loss: 0.60376 Learning rate: 0.002 Mask loss: 0.15954 RPN box loss: 0.02125 RPN score loss: 0.00106 RPN total loss: 0.02231 Total loss: 0.95776 timestamp: 1655040454.292911 iteration: 40320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15612 FastRCNN class loss: 0.0716 FastRCNN total loss: 0.22771 L1 loss: 0.0000e+00 L2 loss: 0.60375 Learning rate: 0.002 Mask loss: 0.21926 RPN box loss: 0.0169 RPN score loss: 0.00151 RPN total loss: 0.01841 Total loss: 1.06913 timestamp: 1655040457.6000314 iteration: 40325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.04797 FastRCNN total loss: 0.15912 L1 loss: 0.0000e+00 L2 loss: 0.60375 Learning rate: 0.002 Mask loss: 0.15675 RPN box loss: 0.05431 RPN score loss: 0.00132 RPN total loss: 0.05562 Total loss: 0.97524 timestamp: 1655040460.9348812 iteration: 40330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09938 FastRCNN class loss: 0.0694 FastRCNN total loss: 0.16877 L1 loss: 0.0000e+00 L2 loss: 0.60374 Learning rate: 0.002 Mask loss: 0.15169 RPN box loss: 0.02655 RPN score loss: 0.00333 RPN total loss: 0.02988 Total loss: 0.95408 timestamp: 1655040464.282229 iteration: 40335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14448 FastRCNN class loss: 0.10033 FastRCNN total loss: 0.24482 L1 loss: 0.0000e+00 L2 loss: 0.60373 Learning rate: 0.002 Mask loss: 0.15767 RPN box loss: 0.02994 RPN score loss: 0.0194 RPN total loss: 0.04933 Total loss: 1.05555 timestamp: 1655040467.5438693 iteration: 40340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0753 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.13822 L1 loss: 0.0000e+00 L2 loss: 0.60372 Learning rate: 0.002 Mask loss: 0.19665 RPN box loss: 0.01782 RPN score loss: 0.00344 RPN total loss: 0.02126 Total loss: 0.95984 timestamp: 1655040470.8417199 iteration: 40345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07668 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.13398 L1 loss: 0.0000e+00 L2 loss: 0.60371 Learning rate: 0.002 Mask loss: 0.12826 RPN box loss: 0.02254 RPN score loss: 0.01065 RPN total loss: 0.03319 Total loss: 0.89914 timestamp: 1655040474.0607939 iteration: 40350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12734 FastRCNN class loss: 0.11341 FastRCNN total loss: 0.24075 L1 loss: 0.0000e+00 L2 loss: 0.6037 Learning rate: 0.002 Mask loss: 0.2261 RPN box loss: 0.02784 RPN score loss: 0.02004 RPN total loss: 0.04789 Total loss: 1.11843 timestamp: 1655040477.3752835 iteration: 40355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09872 FastRCNN class loss: 0.03628 FastRCNN total loss: 0.135 L1 loss: 0.0000e+00 L2 loss: 0.60369 Learning rate: 0.002 Mask loss: 0.1056 RPN box loss: 0.01907 RPN score loss: 0.00355 RPN total loss: 0.02262 Total loss: 0.86691 timestamp: 1655040480.666753 iteration: 40360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15072 FastRCNN class loss: 0.14337 FastRCNN total loss: 0.2941 L1 loss: 0.0000e+00 L2 loss: 0.60368 Learning rate: 0.002 Mask loss: 0.16679 RPN box loss: 0.03567 RPN score loss: 0.00976 RPN total loss: 0.04543 Total loss: 1.11 timestamp: 1655040483.952924 iteration: 40365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1158 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.17911 L1 loss: 0.0000e+00 L2 loss: 0.60368 Learning rate: 0.002 Mask loss: 0.11251 RPN box loss: 0.0195 RPN score loss: 0.00512 RPN total loss: 0.02462 Total loss: 0.91992 timestamp: 1655040487.2616389 iteration: 40370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09219 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.16249 L1 loss: 0.0000e+00 L2 loss: 0.60366 Learning rate: 0.002 Mask loss: 0.11872 RPN box loss: 0.02248 RPN score loss: 0.00429 RPN total loss: 0.02677 Total loss: 0.91164 timestamp: 1655040490.4876244 iteration: 40375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.15528 L1 loss: 0.0000e+00 L2 loss: 0.60365 Learning rate: 0.002 Mask loss: 0.19762 RPN box loss: 0.03851 RPN score loss: 0.00452 RPN total loss: 0.04303 Total loss: 0.99959 timestamp: 1655040493.7521327 iteration: 40380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11041 FastRCNN class loss: 0.10296 FastRCNN total loss: 0.21337 L1 loss: 0.0000e+00 L2 loss: 0.60364 Learning rate: 0.002 Mask loss: 0.19851 RPN box loss: 0.03247 RPN score loss: 0.00812 RPN total loss: 0.04059 Total loss: 1.05611 timestamp: 1655040497.0760362 iteration: 40385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.23404 FastRCNN class loss: 0.18441 FastRCNN total loss: 0.41844 L1 loss: 0.0000e+00 L2 loss: 0.60363 Learning rate: 0.002 Mask loss: 0.21219 RPN box loss: 0.04399 RPN score loss: 0.05451 RPN total loss: 0.0985 Total loss: 1.33276 timestamp: 1655040500.3968236 iteration: 40390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.60362 Learning rate: 0.002 Mask loss: 0.32838 RPN box loss: 0.00699 RPN score loss: 0.00194 RPN total loss: 0.00892 Total loss: 1.07073 timestamp: 1655040503.643424 iteration: 40395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.11861 FastRCNN total loss: 0.21883 L1 loss: 0.0000e+00 L2 loss: 0.60361 Learning rate: 0.002 Mask loss: 0.13391 RPN box loss: 0.02274 RPN score loss: 0.00729 RPN total loss: 0.03003 Total loss: 0.98637 timestamp: 1655040506.9327323 iteration: 40400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.1489 L1 loss: 0.0000e+00 L2 loss: 0.6036 Learning rate: 0.002 Mask loss: 0.11996 RPN box loss: 0.00927 RPN score loss: 0.00441 RPN total loss: 0.01369 Total loss: 0.88615 timestamp: 1655040510.210176 iteration: 40405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07653 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.14435 L1 loss: 0.0000e+00 L2 loss: 0.60359 Learning rate: 0.002 Mask loss: 0.1374 RPN box loss: 0.00643 RPN score loss: 0.00414 RPN total loss: 0.01057 Total loss: 0.89591 timestamp: 1655040513.4332118 iteration: 40410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13587 FastRCNN class loss: 0.10076 FastRCNN total loss: 0.23663 L1 loss: 0.0000e+00 L2 loss: 0.60358 Learning rate: 0.002 Mask loss: 0.14593 RPN box loss: 0.02301 RPN score loss: 0.00854 RPN total loss: 0.03155 Total loss: 1.01769 timestamp: 1655040516.7942033 iteration: 40415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08434 FastRCNN class loss: 0.07805 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 0.60357 Learning rate: 0.002 Mask loss: 0.11097 RPN box loss: 0.01683 RPN score loss: 0.0058 RPN total loss: 0.02263 Total loss: 0.89956 timestamp: 1655040520.0290225 iteration: 40420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09798 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.1475 L1 loss: 0.0000e+00 L2 loss: 0.60356 Learning rate: 0.002 Mask loss: 0.143 RPN box loss: 0.03611 RPN score loss: 0.00392 RPN total loss: 0.04003 Total loss: 0.93409 timestamp: 1655040523.3084986 iteration: 40425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07946 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 0.60355 Learning rate: 0.002 Mask loss: 0.16157 RPN box loss: 0.05827 RPN score loss: 0.01412 RPN total loss: 0.07239 Total loss: 0.98452 timestamp: 1655040526.584812 iteration: 40430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1974 FastRCNN class loss: 0.09557 FastRCNN total loss: 0.29297 L1 loss: 0.0000e+00 L2 loss: 0.60354 Learning rate: 0.002 Mask loss: 0.18015 RPN box loss: 0.02716 RPN score loss: 0.00494 RPN total loss: 0.0321 Total loss: 1.10876 timestamp: 1655040529.872221 iteration: 40435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10568 FastRCNN class loss: 0.09434 FastRCNN total loss: 0.20001 L1 loss: 0.0000e+00 L2 loss: 0.60353 Learning rate: 0.002 Mask loss: 0.20798 RPN box loss: 0.02614 RPN score loss: 0.00786 RPN total loss: 0.03399 Total loss: 1.04551 timestamp: 1655040533.1435566 iteration: 40440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14647 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.21028 L1 loss: 0.0000e+00 L2 loss: 0.60352 Learning rate: 0.002 Mask loss: 0.16445 RPN box loss: 0.01941 RPN score loss: 0.00385 RPN total loss: 0.02325 Total loss: 1.00151 timestamp: 1655040536.3499508 iteration: 40445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.19791 L1 loss: 0.0000e+00 L2 loss: 0.60352 Learning rate: 0.002 Mask loss: 0.15589 RPN box loss: 0.01862 RPN score loss: 0.00682 RPN total loss: 0.02544 Total loss: 0.98277 timestamp: 1655040539.6213195 iteration: 40450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07059 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.12592 L1 loss: 0.0000e+00 L2 loss: 0.60351 Learning rate: 0.002 Mask loss: 0.15622 RPN box loss: 0.01708 RPN score loss: 0.00514 RPN total loss: 0.02222 Total loss: 0.90787 timestamp: 1655040542.9301069 iteration: 40455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15688 FastRCNN class loss: 0.20631 FastRCNN total loss: 0.36319 L1 loss: 0.0000e+00 L2 loss: 0.6035 Learning rate: 0.002 Mask loss: 0.20105 RPN box loss: 0.03861 RPN score loss: 0.00923 RPN total loss: 0.04784 Total loss: 1.21558 timestamp: 1655040546.1683087 iteration: 40460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07753 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.14147 L1 loss: 0.0000e+00 L2 loss: 0.60349 Learning rate: 0.002 Mask loss: 0.14298 RPN box loss: 0.06461 RPN score loss: 0.00588 RPN total loss: 0.07048 Total loss: 0.95842 timestamp: 1655040549.42688 iteration: 40465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.0417 FastRCNN total loss: 0.15683 L1 loss: 0.0000e+00 L2 loss: 0.60348 Learning rate: 0.002 Mask loss: 0.11274 RPN box loss: 0.00286 RPN score loss: 0.00212 RPN total loss: 0.00497 Total loss: 0.87801 timestamp: 1655040552.6633964 iteration: 40470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11199 FastRCNN class loss: 0.10302 FastRCNN total loss: 0.21501 L1 loss: 0.0000e+00 L2 loss: 0.60347 Learning rate: 0.002 Mask loss: 0.14971 RPN box loss: 0.03695 RPN score loss: 0.01378 RPN total loss: 0.05073 Total loss: 1.01891 timestamp: 1655040555.927027 iteration: 40475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15303 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.22441 L1 loss: 0.0000e+00 L2 loss: 0.60346 Learning rate: 0.002 Mask loss: 0.14121 RPN box loss: 0.01799 RPN score loss: 0.00263 RPN total loss: 0.02061 Total loss: 0.98969 timestamp: 1655040559.1968913 iteration: 40480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13029 FastRCNN class loss: 0.08713 FastRCNN total loss: 0.21742 L1 loss: 0.0000e+00 L2 loss: 0.60345 Learning rate: 0.002 Mask loss: 0.1556 RPN box loss: 0.04154 RPN score loss: 0.00712 RPN total loss: 0.04866 Total loss: 1.02513 timestamp: 1655040562.4368513 iteration: 40485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15238 FastRCNN class loss: 0.07354 FastRCNN total loss: 0.22592 L1 loss: 0.0000e+00 L2 loss: 0.60344 Learning rate: 0.002 Mask loss: 0.13298 RPN box loss: 0.02878 RPN score loss: 0.01053 RPN total loss: 0.03931 Total loss: 1.00165 timestamp: 1655040565.6605914 iteration: 40490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09003 FastRCNN class loss: 0.04996 FastRCNN total loss: 0.13998 L1 loss: 0.0000e+00 L2 loss: 0.60343 Learning rate: 0.002 Mask loss: 0.11471 RPN box loss: 0.04083 RPN score loss: 0.01089 RPN total loss: 0.05172 Total loss: 0.90984 timestamp: 1655040568.9087713 iteration: 40495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15691 FastRCNN class loss: 0.09311 FastRCNN total loss: 0.25002 L1 loss: 0.0000e+00 L2 loss: 0.60342 Learning rate: 0.002 Mask loss: 0.18735 RPN box loss: 0.02316 RPN score loss: 0.00316 RPN total loss: 0.02632 Total loss: 1.06711 timestamp: 1655040572.1573658 iteration: 40500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.23059 L1 loss: 0.0000e+00 L2 loss: 0.60342 Learning rate: 0.002 Mask loss: 0.18233 RPN box loss: 0.01066 RPN score loss: 0.00259 RPN total loss: 0.01325 Total loss: 1.02958 timestamp: 1655040575.3994672 iteration: 40505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07127 FastRCNN class loss: 0.04637 FastRCNN total loss: 0.11764 L1 loss: 0.0000e+00 L2 loss: 0.60341 Learning rate: 0.002 Mask loss: 0.12747 RPN box loss: 0.00478 RPN score loss: 0.00306 RPN total loss: 0.00784 Total loss: 0.85636 timestamp: 1655040578.7120535 iteration: 40510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13311 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.18937 L1 loss: 0.0000e+00 L2 loss: 0.60341 Learning rate: 0.002 Mask loss: 0.13622 RPN box loss: 0.02742 RPN score loss: 0.004 RPN total loss: 0.03143 Total loss: 0.96043 timestamp: 1655040581.9284456 iteration: 40515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13783 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.24063 L1 loss: 0.0000e+00 L2 loss: 0.6034 Learning rate: 0.002 Mask loss: 0.17214 RPN box loss: 0.02407 RPN score loss: 0.00434 RPN total loss: 0.02841 Total loss: 1.04458 timestamp: 1655040585.1755683 iteration: 40520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05629 FastRCNN class loss: 0.03852 FastRCNN total loss: 0.09482 L1 loss: 0.0000e+00 L2 loss: 0.60339 Learning rate: 0.002 Mask loss: 0.13014 RPN box loss: 0.01837 RPN score loss: 0.00557 RPN total loss: 0.02395 Total loss: 0.85229 timestamp: 1655040588.4562333 iteration: 40525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14856 FastRCNN class loss: 0.0954 FastRCNN total loss: 0.24396 L1 loss: 0.0000e+00 L2 loss: 0.60337 Learning rate: 0.002 Mask loss: 0.1411 RPN box loss: 0.03008 RPN score loss: 0.00764 RPN total loss: 0.03772 Total loss: 1.02616 timestamp: 1655040591.6449966 iteration: 40530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12154 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.20593 L1 loss: 0.0000e+00 L2 loss: 0.60336 Learning rate: 0.002 Mask loss: 0.17665 RPN box loss: 0.02424 RPN score loss: 0.00235 RPN total loss: 0.02659 Total loss: 1.01253 timestamp: 1655040594.8664508 iteration: 40535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08825 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.14843 L1 loss: 0.0000e+00 L2 loss: 0.60335 Learning rate: 0.002 Mask loss: 0.15418 RPN box loss: 0.02842 RPN score loss: 0.00666 RPN total loss: 0.03508 Total loss: 0.94105 timestamp: 1655040598.1229737 iteration: 40540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.12308 L1 loss: 0.0000e+00 L2 loss: 0.60335 Learning rate: 0.002 Mask loss: 0.06639 RPN box loss: 0.00536 RPN score loss: 0.00322 RPN total loss: 0.00857 Total loss: 0.80138 timestamp: 1655040601.4019778 iteration: 40545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14135 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.23092 L1 loss: 0.0000e+00 L2 loss: 0.60334 Learning rate: 0.002 Mask loss: 0.17893 RPN box loss: 0.07228 RPN score loss: 0.02493 RPN total loss: 0.09721 Total loss: 1.11039 timestamp: 1655040604.7457588 iteration: 40550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15407 FastRCNN class loss: 0.09078 FastRCNN total loss: 0.24486 L1 loss: 0.0000e+00 L2 loss: 0.60333 Learning rate: 0.002 Mask loss: 0.13298 RPN box loss: 0.02436 RPN score loss: 0.00773 RPN total loss: 0.03209 Total loss: 1.01325 timestamp: 1655040608.0419908 iteration: 40555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08252 FastRCNN class loss: 0.07332 FastRCNN total loss: 0.15584 L1 loss: 0.0000e+00 L2 loss: 0.60332 Learning rate: 0.002 Mask loss: 0.16707 RPN box loss: 0.02566 RPN score loss: 0.00623 RPN total loss: 0.03189 Total loss: 0.95811 timestamp: 1655040611.2850115 iteration: 40560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18388 FastRCNN class loss: 0.11475 FastRCNN total loss: 0.29862 L1 loss: 0.0000e+00 L2 loss: 0.60331 Learning rate: 0.002 Mask loss: 0.2265 RPN box loss: 0.01713 RPN score loss: 0.00819 RPN total loss: 0.02532 Total loss: 1.15375 timestamp: 1655040614.472187 iteration: 40565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05825 FastRCNN class loss: 0.0625 FastRCNN total loss: 0.12074 L1 loss: 0.0000e+00 L2 loss: 0.6033 Learning rate: 0.002 Mask loss: 0.1569 RPN box loss: 0.01805 RPN score loss: 0.00386 RPN total loss: 0.0219 Total loss: 0.90284 timestamp: 1655040617.8142462 iteration: 40570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.18509 L1 loss: 0.0000e+00 L2 loss: 0.60329 Learning rate: 0.002 Mask loss: 0.25015 RPN box loss: 0.0139 RPN score loss: 0.01116 RPN total loss: 0.02506 Total loss: 1.06359 timestamp: 1655040621.0689094 iteration: 40575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08894 FastRCNN class loss: 0.05502 FastRCNN total loss: 0.14396 L1 loss: 0.0000e+00 L2 loss: 0.60328 Learning rate: 0.002 Mask loss: 0.15614 RPN box loss: 0.01156 RPN score loss: 0.00412 RPN total loss: 0.01567 Total loss: 0.91904 timestamp: 1655040624.3444655 iteration: 40580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12109 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.22239 L1 loss: 0.0000e+00 L2 loss: 0.60327 Learning rate: 0.002 Mask loss: 0.15674 RPN box loss: 0.01452 RPN score loss: 0.0049 RPN total loss: 0.01942 Total loss: 1.00182 timestamp: 1655040627.6174836 iteration: 40585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18097 FastRCNN class loss: 0.11585 FastRCNN total loss: 0.29681 L1 loss: 0.0000e+00 L2 loss: 0.60326 Learning rate: 0.002 Mask loss: 0.27784 RPN box loss: 0.0127 RPN score loss: 0.00943 RPN total loss: 0.02213 Total loss: 1.20004 timestamp: 1655040630.8249018 iteration: 40590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10987 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 0.60324 Learning rate: 0.002 Mask loss: 0.14381 RPN box loss: 0.02541 RPN score loss: 0.00609 RPN total loss: 0.03151 Total loss: 0.95104 timestamp: 1655040634.1063697 iteration: 40595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11989 FastRCNN class loss: 0.07641 FastRCNN total loss: 0.1963 L1 loss: 0.0000e+00 L2 loss: 0.60323 Learning rate: 0.002 Mask loss: 0.12378 RPN box loss: 0.01806 RPN score loss: 0.00555 RPN total loss: 0.02361 Total loss: 0.94693 timestamp: 1655040637.423004 iteration: 40600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19929 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.28348 L1 loss: 0.0000e+00 L2 loss: 0.60323 Learning rate: 0.002 Mask loss: 0.12773 RPN box loss: 0.05372 RPN score loss: 0.01207 RPN total loss: 0.06579 Total loss: 1.08022 timestamp: 1655040640.7132132 iteration: 40605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11534 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.183 L1 loss: 0.0000e+00 L2 loss: 0.60322 Learning rate: 0.002 Mask loss: 0.10843 RPN box loss: 0.03272 RPN score loss: 0.01184 RPN total loss: 0.04456 Total loss: 0.93921 timestamp: 1655040643.9484441 iteration: 40610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12834 FastRCNN class loss: 0.07851 FastRCNN total loss: 0.20685 L1 loss: 0.0000e+00 L2 loss: 0.60321 Learning rate: 0.002 Mask loss: 0.12556 RPN box loss: 0.03838 RPN score loss: 0.00805 RPN total loss: 0.04643 Total loss: 0.98204 timestamp: 1655040647.1551685 iteration: 40615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14124 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.21985 L1 loss: 0.0000e+00 L2 loss: 0.6032 Learning rate: 0.002 Mask loss: 0.17496 RPN box loss: 0.035 RPN score loss: 0.01078 RPN total loss: 0.04578 Total loss: 1.04378 timestamp: 1655040650.5317414 iteration: 40620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13507 FastRCNN class loss: 0.06513 FastRCNN total loss: 0.2002 L1 loss: 0.0000e+00 L2 loss: 0.60319 Learning rate: 0.002 Mask loss: 0.15551 RPN box loss: 0.00956 RPN score loss: 0.00453 RPN total loss: 0.01409 Total loss: 0.97299 timestamp: 1655040653.7802603 iteration: 40625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11545 FastRCNN class loss: 0.06035 FastRCNN total loss: 0.1758 L1 loss: 0.0000e+00 L2 loss: 0.60318 Learning rate: 0.002 Mask loss: 0.14093 RPN box loss: 0.01393 RPN score loss: 0.00344 RPN total loss: 0.01737 Total loss: 0.93728 timestamp: 1655040657.0571694 iteration: 40630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07868 FastRCNN class loss: 0.03844 FastRCNN total loss: 0.11713 L1 loss: 0.0000e+00 L2 loss: 0.60317 Learning rate: 0.002 Mask loss: 0.1076 RPN box loss: 0.03152 RPN score loss: 0.01992 RPN total loss: 0.05144 Total loss: 0.87934 timestamp: 1655040660.3016467 iteration: 40635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07672 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.14196 L1 loss: 0.0000e+00 L2 loss: 0.60316 Learning rate: 0.002 Mask loss: 0.11898 RPN box loss: 0.01115 RPN score loss: 0.00371 RPN total loss: 0.01485 Total loss: 0.87896 timestamp: 1655040663.5694427 iteration: 40640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16899 FastRCNN class loss: 0.10872 FastRCNN total loss: 0.27771 L1 loss: 0.0000e+00 L2 loss: 0.60315 Learning rate: 0.002 Mask loss: 0.17956 RPN box loss: 0.03206 RPN score loss: 0.00613 RPN total loss: 0.03818 Total loss: 1.0986 timestamp: 1655040666.7889657 iteration: 40645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16652 FastRCNN class loss: 0.08298 FastRCNN total loss: 0.2495 L1 loss: 0.0000e+00 L2 loss: 0.60314 Learning rate: 0.002 Mask loss: 0.16852 RPN box loss: 0.02285 RPN score loss: 0.0019 RPN total loss: 0.02475 Total loss: 1.04591 timestamp: 1655040670.0415611 iteration: 40650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0844 FastRCNN class loss: 0.05964 FastRCNN total loss: 0.14404 L1 loss: 0.0000e+00 L2 loss: 0.60313 Learning rate: 0.002 Mask loss: 0.13717 RPN box loss: 0.04443 RPN score loss: 0.0079 RPN total loss: 0.05233 Total loss: 0.93667 timestamp: 1655040673.2657511 iteration: 40655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0845 FastRCNN class loss: 0.05838 FastRCNN total loss: 0.14288 L1 loss: 0.0000e+00 L2 loss: 0.60313 Learning rate: 0.002 Mask loss: 0.11285 RPN box loss: 0.01078 RPN score loss: 0.00285 RPN total loss: 0.01363 Total loss: 0.87248 timestamp: 1655040676.4858136 iteration: 40660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.08859 FastRCNN total loss: 0.19506 L1 loss: 0.0000e+00 L2 loss: 0.60312 Learning rate: 0.002 Mask loss: 0.19899 RPN box loss: 0.03527 RPN score loss: 0.00654 RPN total loss: 0.0418 Total loss: 1.03897 timestamp: 1655040679.76476 iteration: 40665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09407 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.15425 L1 loss: 0.0000e+00 L2 loss: 0.60311 Learning rate: 0.002 Mask loss: 0.13213 RPN box loss: 0.02394 RPN score loss: 0.00277 RPN total loss: 0.02671 Total loss: 0.9162 timestamp: 1655040682.9845505 iteration: 40670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13986 FastRCNN class loss: 0.09566 FastRCNN total loss: 0.23553 L1 loss: 0.0000e+00 L2 loss: 0.6031 Learning rate: 0.002 Mask loss: 0.1375 RPN box loss: 0.0222 RPN score loss: 0.00495 RPN total loss: 0.02715 Total loss: 1.00328 timestamp: 1655040686.2945597 iteration: 40675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12484 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.17866 L1 loss: 0.0000e+00 L2 loss: 0.60309 Learning rate: 0.002 Mask loss: 0.16229 RPN box loss: 0.00301 RPN score loss: 0.00357 RPN total loss: 0.00658 Total loss: 0.95061 timestamp: 1655040689.6083157 iteration: 40680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17907 FastRCNN class loss: 0.07144 FastRCNN total loss: 0.25052 L1 loss: 0.0000e+00 L2 loss: 0.60308 Learning rate: 0.002 Mask loss: 0.10592 RPN box loss: 0.02932 RPN score loss: 0.0034 RPN total loss: 0.03272 Total loss: 0.99223 timestamp: 1655040692.7953749 iteration: 40685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13964 FastRCNN class loss: 0.07185 FastRCNN total loss: 0.21149 L1 loss: 0.0000e+00 L2 loss: 0.60307 Learning rate: 0.002 Mask loss: 0.16547 RPN box loss: 0.03972 RPN score loss: 0.00524 RPN total loss: 0.04496 Total loss: 1.025 timestamp: 1655040696.1104176 iteration: 40690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17561 FastRCNN class loss: 0.11891 FastRCNN total loss: 0.29452 L1 loss: 0.0000e+00 L2 loss: 0.60307 Learning rate: 0.002 Mask loss: 0.18921 RPN box loss: 0.02382 RPN score loss: 0.00393 RPN total loss: 0.02776 Total loss: 1.11456 timestamp: 1655040699.4619443 iteration: 40695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14477 FastRCNN class loss: 0.10833 FastRCNN total loss: 0.2531 L1 loss: 0.0000e+00 L2 loss: 0.60306 Learning rate: 0.002 Mask loss: 0.2319 RPN box loss: 0.04157 RPN score loss: 0.00348 RPN total loss: 0.04505 Total loss: 1.13311 timestamp: 1655040702.7100964 iteration: 40700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12211 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.18776 L1 loss: 0.0000e+00 L2 loss: 0.60305 Learning rate: 0.002 Mask loss: 0.17203 RPN box loss: 0.02253 RPN score loss: 0.01171 RPN total loss: 0.03424 Total loss: 0.99708 timestamp: 1655040705.9942558 iteration: 40705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06821 FastRCNN class loss: 0.0521 FastRCNN total loss: 0.12031 L1 loss: 0.0000e+00 L2 loss: 0.60304 Learning rate: 0.002 Mask loss: 0.08131 RPN box loss: 0.00467 RPN score loss: 0.00072 RPN total loss: 0.00539 Total loss: 0.81005 timestamp: 1655040709.2264774 iteration: 40710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09417 FastRCNN class loss: 0.05877 FastRCNN total loss: 0.15294 L1 loss: 0.0000e+00 L2 loss: 0.60303 Learning rate: 0.002 Mask loss: 0.13572 RPN box loss: 0.00868 RPN score loss: 0.00245 RPN total loss: 0.01113 Total loss: 0.90282 timestamp: 1655040712.443387 iteration: 40715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08093 FastRCNN class loss: 0.04086 FastRCNN total loss: 0.12179 L1 loss: 0.0000e+00 L2 loss: 0.60302 Learning rate: 0.002 Mask loss: 0.12231 RPN box loss: 0.02081 RPN score loss: 0.00414 RPN total loss: 0.02495 Total loss: 0.87207 timestamp: 1655040715.6794233 iteration: 40720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.25767 FastRCNN class loss: 0.09744 FastRCNN total loss: 0.35512 L1 loss: 0.0000e+00 L2 loss: 0.60301 Learning rate: 0.002 Mask loss: 0.12313 RPN box loss: 0.03789 RPN score loss: 0.01582 RPN total loss: 0.05371 Total loss: 1.13496 timestamp: 1655040718.9523115 iteration: 40725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07166 FastRCNN class loss: 0.03856 FastRCNN total loss: 0.11022 L1 loss: 0.0000e+00 L2 loss: 0.60301 Learning rate: 0.002 Mask loss: 0.13737 RPN box loss: 0.01408 RPN score loss: 0.001 RPN total loss: 0.01508 Total loss: 0.86568 timestamp: 1655040722.244715 iteration: 40730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10368 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.15409 L1 loss: 0.0000e+00 L2 loss: 0.60299 Learning rate: 0.002 Mask loss: 0.13438 RPN box loss: 0.03073 RPN score loss: 0.00351 RPN total loss: 0.03424 Total loss: 0.92571 timestamp: 1655040725.52028 iteration: 40735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09825 FastRCNN class loss: 0.08047 FastRCNN total loss: 0.17871 L1 loss: 0.0000e+00 L2 loss: 0.60298 Learning rate: 0.002 Mask loss: 0.11488 RPN box loss: 0.01201 RPN score loss: 0.00362 RPN total loss: 0.01563 Total loss: 0.9122 timestamp: 1655040728.8008907 iteration: 40740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08057 FastRCNN class loss: 0.04182 FastRCNN total loss: 0.12239 L1 loss: 0.0000e+00 L2 loss: 0.60297 Learning rate: 0.002 Mask loss: 0.09733 RPN box loss: 0.02071 RPN score loss: 0.00212 RPN total loss: 0.02283 Total loss: 0.84552 timestamp: 1655040732.0392852 iteration: 40745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09203 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.15208 L1 loss: 0.0000e+00 L2 loss: 0.60296 Learning rate: 0.002 Mask loss: 0.14909 RPN box loss: 0.02354 RPN score loss: 0.00367 RPN total loss: 0.02721 Total loss: 0.93135 timestamp: 1655040735.257233 iteration: 40750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13137 FastRCNN class loss: 0.12041 FastRCNN total loss: 0.25178 L1 loss: 0.0000e+00 L2 loss: 0.60295 Learning rate: 0.002 Mask loss: 0.16591 RPN box loss: 0.02382 RPN score loss: 0.01877 RPN total loss: 0.04259 Total loss: 1.06323 timestamp: 1655040738.473721 iteration: 40755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09052 FastRCNN class loss: 0.11022 FastRCNN total loss: 0.20073 L1 loss: 0.0000e+00 L2 loss: 0.60294 Learning rate: 0.002 Mask loss: 0.16123 RPN box loss: 0.02963 RPN score loss: 0.00739 RPN total loss: 0.03702 Total loss: 1.00192 timestamp: 1655040741.7361367 iteration: 40760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1103 FastRCNN class loss: 0.08742 FastRCNN total loss: 0.19772 L1 loss: 0.0000e+00 L2 loss: 0.60293 Learning rate: 0.002 Mask loss: 0.14105 RPN box loss: 0.01596 RPN score loss: 0.00489 RPN total loss: 0.02085 Total loss: 0.96254 timestamp: 1655040744.9526913 iteration: 40765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18663 FastRCNN class loss: 0.08363 FastRCNN total loss: 0.27027 L1 loss: 0.0000e+00 L2 loss: 0.60292 Learning rate: 0.002 Mask loss: 0.21228 RPN box loss: 0.01332 RPN score loss: 0.00336 RPN total loss: 0.01668 Total loss: 1.10215 timestamp: 1655040748.2854993 iteration: 40770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18439 FastRCNN class loss: 0.09139 FastRCNN total loss: 0.27579 L1 loss: 0.0000e+00 L2 loss: 0.60291 Learning rate: 0.002 Mask loss: 0.15832 RPN box loss: 0.02119 RPN score loss: 0.00596 RPN total loss: 0.02715 Total loss: 1.06417 timestamp: 1655040751.5162187 iteration: 40775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07526 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.13206 L1 loss: 0.0000e+00 L2 loss: 0.6029 Learning rate: 0.002 Mask loss: 0.11715 RPN box loss: 0.03053 RPN score loss: 0.00621 RPN total loss: 0.03674 Total loss: 0.88885 timestamp: 1655040754.6830094 iteration: 40780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07458 FastRCNN class loss: 0.04113 FastRCNN total loss: 0.11571 L1 loss: 0.0000e+00 L2 loss: 0.6029 Learning rate: 0.002 Mask loss: 0.18798 RPN box loss: 0.00874 RPN score loss: 0.00192 RPN total loss: 0.01066 Total loss: 0.91724 timestamp: 1655040757.921446 iteration: 40785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12282 FastRCNN class loss: 0.06723 FastRCNN total loss: 0.19005 L1 loss: 0.0000e+00 L2 loss: 0.60288 Learning rate: 0.002 Mask loss: 0.17595 RPN box loss: 0.03511 RPN score loss: 0.01331 RPN total loss: 0.04842 Total loss: 1.01731 timestamp: 1655040761.223226 iteration: 40790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07801 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.16403 L1 loss: 0.0000e+00 L2 loss: 0.60287 Learning rate: 0.002 Mask loss: 0.13378 RPN box loss: 0.01587 RPN score loss: 0.01038 RPN total loss: 0.02624 Total loss: 0.92693 timestamp: 1655040764.4801114 iteration: 40795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07289 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.13702 L1 loss: 0.0000e+00 L2 loss: 0.60286 Learning rate: 0.002 Mask loss: 0.14796 RPN box loss: 0.02457 RPN score loss: 0.00271 RPN total loss: 0.02729 Total loss: 0.91513 timestamp: 1655040767.7943478 iteration: 40800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21084 FastRCNN class loss: 0.07955 FastRCNN total loss: 0.29039 L1 loss: 0.0000e+00 L2 loss: 0.60286 Learning rate: 0.002 Mask loss: 0.14432 RPN box loss: 0.01954 RPN score loss: 0.00347 RPN total loss: 0.02301 Total loss: 1.06057 timestamp: 1655040771.0146506 iteration: 40805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16561 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.25589 L1 loss: 0.0000e+00 L2 loss: 0.60285 Learning rate: 0.002 Mask loss: 0.1653 RPN box loss: 0.03187 RPN score loss: 0.00331 RPN total loss: 0.03518 Total loss: 1.05922 timestamp: 1655040774.2987318 iteration: 40810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10173 FastRCNN class loss: 0.04548 FastRCNN total loss: 0.14721 L1 loss: 0.0000e+00 L2 loss: 0.60284 Learning rate: 0.002 Mask loss: 0.14967 RPN box loss: 0.00313 RPN score loss: 0.00193 RPN total loss: 0.00506 Total loss: 0.90478 timestamp: 1655040777.5992835 iteration: 40815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08536 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.15654 L1 loss: 0.0000e+00 L2 loss: 0.60283 Learning rate: 0.002 Mask loss: 0.17178 RPN box loss: 0.05989 RPN score loss: 0.00566 RPN total loss: 0.06555 Total loss: 0.9967 timestamp: 1655040780.849812 iteration: 40820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15826 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.25172 L1 loss: 0.0000e+00 L2 loss: 0.60282 Learning rate: 0.002 Mask loss: 0.19099 RPN box loss: 0.01196 RPN score loss: 0.00424 RPN total loss: 0.0162 Total loss: 1.06173 timestamp: 1655040784.1262078 iteration: 40825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15053 FastRCNN class loss: 0.09377 FastRCNN total loss: 0.2443 L1 loss: 0.0000e+00 L2 loss: 0.60281 Learning rate: 0.002 Mask loss: 0.17478 RPN box loss: 0.02227 RPN score loss: 0.00577 RPN total loss: 0.02804 Total loss: 1.04994 timestamp: 1655040787.3882964 iteration: 40830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11605 FastRCNN class loss: 0.09775 FastRCNN total loss: 0.21379 L1 loss: 0.0000e+00 L2 loss: 0.6028 Learning rate: 0.002 Mask loss: 0.15497 RPN box loss: 0.01219 RPN score loss: 0.00496 RPN total loss: 0.01715 Total loss: 0.98871 timestamp: 1655040790.6887052 iteration: 40835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07242 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.16323 L1 loss: 0.0000e+00 L2 loss: 0.60279 Learning rate: 0.002 Mask loss: 0.11711 RPN box loss: 0.01451 RPN score loss: 0.00524 RPN total loss: 0.01974 Total loss: 0.90287 timestamp: 1655040793.9316454 iteration: 40840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13422 FastRCNN class loss: 0.06318 FastRCNN total loss: 0.1974 L1 loss: 0.0000e+00 L2 loss: 0.60278 Learning rate: 0.002 Mask loss: 0.13888 RPN box loss: 0.01238 RPN score loss: 0.00321 RPN total loss: 0.0156 Total loss: 0.95465 timestamp: 1655040797.1830738 iteration: 40845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08118 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.15614 L1 loss: 0.0000e+00 L2 loss: 0.60277 Learning rate: 0.002 Mask loss: 0.10629 RPN box loss: 0.01303 RPN score loss: 0.00125 RPN total loss: 0.01428 Total loss: 0.87949 timestamp: 1655040800.461361 iteration: 40850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09328 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.16591 L1 loss: 0.0000e+00 L2 loss: 0.60276 Learning rate: 0.002 Mask loss: 0.11058 RPN box loss: 0.02667 RPN score loss: 0.00462 RPN total loss: 0.0313 Total loss: 0.91055 timestamp: 1655040803.7466211 iteration: 40855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07887 FastRCNN class loss: 0.08999 FastRCNN total loss: 0.16886 L1 loss: 0.0000e+00 L2 loss: 0.60275 Learning rate: 0.002 Mask loss: 0.11932 RPN box loss: 0.01244 RPN score loss: 0.00591 RPN total loss: 0.01835 Total loss: 0.90929 timestamp: 1655040807.0181453 iteration: 40860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11349 FastRCNN class loss: 0.1054 FastRCNN total loss: 0.21889 L1 loss: 0.0000e+00 L2 loss: 0.60274 Learning rate: 0.002 Mask loss: 0.15385 RPN box loss: 0.03153 RPN score loss: 0.01367 RPN total loss: 0.0452 Total loss: 1.02069 timestamp: 1655040810.2603564 iteration: 40865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.08677 FastRCNN total loss: 0.19168 L1 loss: 0.0000e+00 L2 loss: 0.60273 Learning rate: 0.002 Mask loss: 0.1491 RPN box loss: 0.02255 RPN score loss: 0.00145 RPN total loss: 0.02399 Total loss: 0.96751 timestamp: 1655040813.5655944 iteration: 40870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14809 FastRCNN class loss: 0.12732 FastRCNN total loss: 0.2754 L1 loss: 0.0000e+00 L2 loss: 0.60272 Learning rate: 0.002 Mask loss: 0.18607 RPN box loss: 0.0488 RPN score loss: 0.01251 RPN total loss: 0.06131 Total loss: 1.1255 timestamp: 1655040816.8532379 iteration: 40875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13543 FastRCNN class loss: 0.08145 FastRCNN total loss: 0.21687 L1 loss: 0.0000e+00 L2 loss: 0.60271 Learning rate: 0.002 Mask loss: 0.13671 RPN box loss: 0.04738 RPN score loss: 0.0102 RPN total loss: 0.05758 Total loss: 1.01387 timestamp: 1655040820.1430879 iteration: 40880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14554 FastRCNN class loss: 0.09671 FastRCNN total loss: 0.24225 L1 loss: 0.0000e+00 L2 loss: 0.6027 Learning rate: 0.002 Mask loss: 0.2588 RPN box loss: 0.03578 RPN score loss: 0.01386 RPN total loss: 0.04964 Total loss: 1.15339 timestamp: 1655040823.3726397 iteration: 40885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11595 FastRCNN class loss: 0.10759 FastRCNN total loss: 0.22354 L1 loss: 0.0000e+00 L2 loss: 0.60269 Learning rate: 0.002 Mask loss: 0.14609 RPN box loss: 0.01949 RPN score loss: 0.00632 RPN total loss: 0.02581 Total loss: 0.99813 timestamp: 1655040826.5672255 iteration: 40890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10481 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.1754 L1 loss: 0.0000e+00 L2 loss: 0.60268 Learning rate: 0.002 Mask loss: 0.1743 RPN box loss: 0.02598 RPN score loss: 0.01131 RPN total loss: 0.03728 Total loss: 0.98966 timestamp: 1655040829.8947227 iteration: 40895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08206 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.13524 L1 loss: 0.0000e+00 L2 loss: 0.60267 Learning rate: 0.002 Mask loss: 0.09136 RPN box loss: 0.01462 RPN score loss: 0.0052 RPN total loss: 0.01982 Total loss: 0.84909 timestamp: 1655040833.198828 iteration: 40900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11467 FastRCNN class loss: 0.07689 FastRCNN total loss: 0.19156 L1 loss: 0.0000e+00 L2 loss: 0.60267 Learning rate: 0.002 Mask loss: 0.22224 RPN box loss: 0.02727 RPN score loss: 0.0228 RPN total loss: 0.05007 Total loss: 1.06653 timestamp: 1655040836.4324312 iteration: 40905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0882 FastRCNN class loss: 0.0455 FastRCNN total loss: 0.1337 L1 loss: 0.0000e+00 L2 loss: 0.60266 Learning rate: 0.002 Mask loss: 0.10509 RPN box loss: 0.00694 RPN score loss: 0.00458 RPN total loss: 0.01152 Total loss: 0.85297 timestamp: 1655040839.7379122 iteration: 40910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12048 FastRCNN class loss: 0.08067 FastRCNN total loss: 0.20114 L1 loss: 0.0000e+00 L2 loss: 0.60265 Learning rate: 0.002 Mask loss: 0.17905 RPN box loss: 0.03018 RPN score loss: 0.02834 RPN total loss: 0.05852 Total loss: 1.04136 timestamp: 1655040842.9824896 iteration: 40915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05878 FastRCNN class loss: 0.06389 FastRCNN total loss: 0.12267 L1 loss: 0.0000e+00 L2 loss: 0.60264 Learning rate: 0.002 Mask loss: 0.08794 RPN box loss: 0.01892 RPN score loss: 0.02372 RPN total loss: 0.04264 Total loss: 0.85589 timestamp: 1655040846.2264483 iteration: 40920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07151 FastRCNN class loss: 0.05306 FastRCNN total loss: 0.12456 L1 loss: 0.0000e+00 L2 loss: 0.60263 Learning rate: 0.002 Mask loss: 0.09339 RPN box loss: 0.00515 RPN score loss: 0.00219 RPN total loss: 0.00734 Total loss: 0.82793 timestamp: 1655040849.5211596 iteration: 40925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07016 FastRCNN class loss: 0.05421 FastRCNN total loss: 0.12437 L1 loss: 0.0000e+00 L2 loss: 0.60262 Learning rate: 0.002 Mask loss: 0.14857 RPN box loss: 0.00689 RPN score loss: 0.00385 RPN total loss: 0.01074 Total loss: 0.8863 timestamp: 1655040852.8223388 iteration: 40930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07418 FastRCNN class loss: 0.0492 FastRCNN total loss: 0.12338 L1 loss: 0.0000e+00 L2 loss: 0.60261 Learning rate: 0.002 Mask loss: 0.1179 RPN box loss: 0.02172 RPN score loss: 0.0103 RPN total loss: 0.03202 Total loss: 0.87592 timestamp: 1655040856.0473356 iteration: 40935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16174 FastRCNN class loss: 0.10489 FastRCNN total loss: 0.26663 L1 loss: 0.0000e+00 L2 loss: 0.60261 Learning rate: 0.002 Mask loss: 0.18286 RPN box loss: 0.02059 RPN score loss: 0.01234 RPN total loss: 0.03292 Total loss: 1.08502 timestamp: 1655040859.3043945 iteration: 40940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1173 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.18669 L1 loss: 0.0000e+00 L2 loss: 0.6026 Learning rate: 0.002 Mask loss: 0.13005 RPN box loss: 0.01747 RPN score loss: 0.00544 RPN total loss: 0.02291 Total loss: 0.94225 timestamp: 1655040862.552448 iteration: 40945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11109 FastRCNN class loss: 0.05557 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.60259 Learning rate: 0.002 Mask loss: 0.14642 RPN box loss: 0.01823 RPN score loss: 0.00834 RPN total loss: 0.02657 Total loss: 0.94224 timestamp: 1655040865.7839024 iteration: 40950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15243 FastRCNN class loss: 0.11291 FastRCNN total loss: 0.26534 L1 loss: 0.0000e+00 L2 loss: 0.60258 Learning rate: 0.002 Mask loss: 0.20071 RPN box loss: 0.02949 RPN score loss: 0.01408 RPN total loss: 0.04357 Total loss: 1.11218 timestamp: 1655040868.978941 iteration: 40955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10709 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.19348 L1 loss: 0.0000e+00 L2 loss: 0.60257 Learning rate: 0.002 Mask loss: 0.09662 RPN box loss: 0.04056 RPN score loss: 0.00913 RPN total loss: 0.04968 Total loss: 0.94234 timestamp: 1655040872.2920263 iteration: 40960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13989 FastRCNN class loss: 0.08819 FastRCNN total loss: 0.22808 L1 loss: 0.0000e+00 L2 loss: 0.60256 Learning rate: 0.002 Mask loss: 0.14852 RPN box loss: 0.02849 RPN score loss: 0.00707 RPN total loss: 0.03556 Total loss: 1.01473 timestamp: 1655040875.5829065 iteration: 40965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10988 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.18498 L1 loss: 0.0000e+00 L2 loss: 0.60255 Learning rate: 0.002 Mask loss: 0.15634 RPN box loss: 0.03066 RPN score loss: 0.00557 RPN total loss: 0.03623 Total loss: 0.9801 timestamp: 1655040878.8033593 iteration: 40970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14579 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.21798 L1 loss: 0.0000e+00 L2 loss: 0.60254 Learning rate: 0.002 Mask loss: 0.16449 RPN box loss: 0.02571 RPN score loss: 0.0056 RPN total loss: 0.03132 Total loss: 1.01633 timestamp: 1655040882.0798912 iteration: 40975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1169 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.20155 L1 loss: 0.0000e+00 L2 loss: 0.60253 Learning rate: 0.002 Mask loss: 0.13015 RPN box loss: 0.03515 RPN score loss: 0.00257 RPN total loss: 0.03772 Total loss: 0.97195 timestamp: 1655040885.3318753 iteration: 40980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.15008 L1 loss: 0.0000e+00 L2 loss: 0.60252 Learning rate: 0.002 Mask loss: 0.1196 RPN box loss: 0.02312 RPN score loss: 0.00417 RPN total loss: 0.02728 Total loss: 0.89948 timestamp: 1655040888.643618 iteration: 40985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04273 FastRCNN class loss: 0.03861 FastRCNN total loss: 0.08133 L1 loss: 0.0000e+00 L2 loss: 0.60251 Learning rate: 0.002 Mask loss: 0.19172 RPN box loss: 0.00277 RPN score loss: 0.00745 RPN total loss: 0.01021 Total loss: 0.88578 timestamp: 1655040891.8984058 iteration: 40990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09559 FastRCNN class loss: 0.07937 FastRCNN total loss: 0.17496 L1 loss: 0.0000e+00 L2 loss: 0.6025 Learning rate: 0.002 Mask loss: 0.13154 RPN box loss: 0.01629 RPN score loss: 0.00292 RPN total loss: 0.01921 Total loss: 0.92821 timestamp: 1655040895.1757169 iteration: 40995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12823 FastRCNN class loss: 0.07873 FastRCNN total loss: 0.20695 L1 loss: 0.0000e+00 L2 loss: 0.6025 Learning rate: 0.002 Mask loss: 0.14872 RPN box loss: 0.04385 RPN score loss: 0.02018 RPN total loss: 0.06403 Total loss: 1.0222 timestamp: 1655040898.5393906 iteration: 41000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15363 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.21316 L1 loss: 0.0000e+00 L2 loss: 0.60249 Learning rate: 0.002 Mask loss: 0.11809 RPN box loss: 0.0234 RPN score loss: 0.00364 RPN total loss: 0.02704 Total loss: 0.96078 timestamp: 1655040901.812036 iteration: 41005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07519 FastRCNN class loss: 0.05602 FastRCNN total loss: 0.13121 L1 loss: 0.0000e+00 L2 loss: 0.60248 Learning rate: 0.002 Mask loss: 0.1325 RPN box loss: 0.03043 RPN score loss: 0.0051 RPN total loss: 0.03553 Total loss: 0.90173 timestamp: 1655040905.0282583 iteration: 41010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13842 FastRCNN class loss: 0.07835 FastRCNN total loss: 0.21677 L1 loss: 0.0000e+00 L2 loss: 0.60247 Learning rate: 0.002 Mask loss: 0.16779 RPN box loss: 0.04454 RPN score loss: 0.00667 RPN total loss: 0.0512 Total loss: 1.03823 timestamp: 1655040908.3250926 iteration: 41015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06557 FastRCNN class loss: 0.0415 FastRCNN total loss: 0.10707 L1 loss: 0.0000e+00 L2 loss: 0.60246 Learning rate: 0.002 Mask loss: 0.13244 RPN box loss: 0.00284 RPN score loss: 0.00517 RPN total loss: 0.00801 Total loss: 0.84998 timestamp: 1655040911.638811 iteration: 41020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15822 FastRCNN class loss: 0.12754 FastRCNN total loss: 0.28575 L1 loss: 0.0000e+00 L2 loss: 0.60245 Learning rate: 0.002 Mask loss: 0.23511 RPN box loss: 0.02444 RPN score loss: 0.01514 RPN total loss: 0.03957 Total loss: 1.16289 timestamp: 1655040914.9495828 iteration: 41025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09109 FastRCNN class loss: 0.08896 FastRCNN total loss: 0.18005 L1 loss: 0.0000e+00 L2 loss: 0.60243 Learning rate: 0.002 Mask loss: 0.10163 RPN box loss: 0.01492 RPN score loss: 0.00483 RPN total loss: 0.01975 Total loss: 0.90386 timestamp: 1655040918.258038 iteration: 41030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05573 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.12686 L1 loss: 0.0000e+00 L2 loss: 0.60242 Learning rate: 0.002 Mask loss: 0.14848 RPN box loss: 0.06552 RPN score loss: 0.00832 RPN total loss: 0.07384 Total loss: 0.95161 timestamp: 1655040921.5756545 iteration: 41035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10229 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.2037 L1 loss: 0.0000e+00 L2 loss: 0.60241 Learning rate: 0.002 Mask loss: 0.15593 RPN box loss: 0.02648 RPN score loss: 0.01076 RPN total loss: 0.03725 Total loss: 0.99928 timestamp: 1655040924.907338 iteration: 41040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17083 FastRCNN class loss: 0.09627 FastRCNN total loss: 0.2671 L1 loss: 0.0000e+00 L2 loss: 0.6024 Learning rate: 0.002 Mask loss: 0.19197 RPN box loss: 0.02138 RPN score loss: 0.01081 RPN total loss: 0.0322 Total loss: 1.09367 timestamp: 1655040928.2081594 iteration: 41045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13463 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.19698 L1 loss: 0.0000e+00 L2 loss: 0.60239 Learning rate: 0.002 Mask loss: 0.15167 RPN box loss: 0.01627 RPN score loss: 0.00629 RPN total loss: 0.02256 Total loss: 0.97361 timestamp: 1655040931.4516382 iteration: 41050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06635 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.12905 L1 loss: 0.0000e+00 L2 loss: 0.60238 Learning rate: 0.002 Mask loss: 0.15793 RPN box loss: 0.05977 RPN score loss: 0.00497 RPN total loss: 0.06474 Total loss: 0.9541 timestamp: 1655040934.7169068 iteration: 41055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07602 FastRCNN class loss: 0.04968 FastRCNN total loss: 0.12569 L1 loss: 0.0000e+00 L2 loss: 0.60237 Learning rate: 0.002 Mask loss: 0.09262 RPN box loss: 0.01097 RPN score loss: 0.00736 RPN total loss: 0.01833 Total loss: 0.83902 timestamp: 1655040937.92076 iteration: 41060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11706 FastRCNN class loss: 0.08689 FastRCNN total loss: 0.20395 L1 loss: 0.0000e+00 L2 loss: 0.60236 Learning rate: 0.002 Mask loss: 0.12804 RPN box loss: 0.01207 RPN score loss: 0.00505 RPN total loss: 0.01712 Total loss: 0.95148 timestamp: 1655040941.1795871 iteration: 41065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11715 FastRCNN class loss: 0.0775 FastRCNN total loss: 0.19466 L1 loss: 0.0000e+00 L2 loss: 0.60235 Learning rate: 0.002 Mask loss: 0.14793 RPN box loss: 0.02459 RPN score loss: 0.00667 RPN total loss: 0.03126 Total loss: 0.9762 timestamp: 1655040944.3865588 iteration: 41070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12032 FastRCNN class loss: 0.10539 FastRCNN total loss: 0.22571 L1 loss: 0.0000e+00 L2 loss: 0.60234 Learning rate: 0.002 Mask loss: 0.14644 RPN box loss: 0.03678 RPN score loss: 0.01176 RPN total loss: 0.04854 Total loss: 1.02303 timestamp: 1655040947.6811576 iteration: 41075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11543 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.17075 L1 loss: 0.0000e+00 L2 loss: 0.60233 Learning rate: 0.002 Mask loss: 0.14612 RPN box loss: 0.01337 RPN score loss: 0.00363 RPN total loss: 0.017 Total loss: 0.93621 timestamp: 1655040950.9710934 iteration: 41080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11776 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.18155 L1 loss: 0.0000e+00 L2 loss: 0.60232 Learning rate: 0.002 Mask loss: 0.12936 RPN box loss: 0.01627 RPN score loss: 0.00342 RPN total loss: 0.01969 Total loss: 0.93292 timestamp: 1655040954.2158594 iteration: 41085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13972 FastRCNN class loss: 0.1196 FastRCNN total loss: 0.25932 L1 loss: 0.0000e+00 L2 loss: 0.60232 Learning rate: 0.002 Mask loss: 0.17949 RPN box loss: 0.00553 RPN score loss: 0.00697 RPN total loss: 0.01251 Total loss: 1.05363 timestamp: 1655040957.5656447 iteration: 41090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14781 FastRCNN class loss: 0.071 FastRCNN total loss: 0.21882 L1 loss: 0.0000e+00 L2 loss: 0.60231 Learning rate: 0.002 Mask loss: 0.16611 RPN box loss: 0.016 RPN score loss: 0.00631 RPN total loss: 0.02231 Total loss: 1.00954 timestamp: 1655040960.8742256 iteration: 41095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14194 FastRCNN class loss: 0.10209 FastRCNN total loss: 0.24404 L1 loss: 0.0000e+00 L2 loss: 0.6023 Learning rate: 0.002 Mask loss: 0.16962 RPN box loss: 0.03684 RPN score loss: 0.00743 RPN total loss: 0.04427 Total loss: 1.06022 timestamp: 1655040964.1311696 iteration: 41100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13719 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.20335 L1 loss: 0.0000e+00 L2 loss: 0.60229 Learning rate: 0.002 Mask loss: 0.20868 RPN box loss: 0.03972 RPN score loss: 0.00818 RPN total loss: 0.04791 Total loss: 1.06223 timestamp: 1655040967.388049 iteration: 41105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.06526 FastRCNN total loss: 0.15811 L1 loss: 0.0000e+00 L2 loss: 0.60228 Learning rate: 0.002 Mask loss: 0.17421 RPN box loss: 0.02853 RPN score loss: 0.00243 RPN total loss: 0.03095 Total loss: 0.96555 timestamp: 1655040970.694468 iteration: 41110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16747 FastRCNN class loss: 0.07744 FastRCNN total loss: 0.24492 L1 loss: 0.0000e+00 L2 loss: 0.60227 Learning rate: 0.002 Mask loss: 0.16587 RPN box loss: 0.02831 RPN score loss: 0.01277 RPN total loss: 0.04108 Total loss: 1.05414 timestamp: 1655040973.9803638 iteration: 41115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14832 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.23569 L1 loss: 0.0000e+00 L2 loss: 0.60226 Learning rate: 0.002 Mask loss: 0.14728 RPN box loss: 0.04872 RPN score loss: 0.00944 RPN total loss: 0.05816 Total loss: 1.04339 timestamp: 1655040977.263981 iteration: 41120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09422 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.15582 L1 loss: 0.0000e+00 L2 loss: 0.60225 Learning rate: 0.002 Mask loss: 0.1099 RPN box loss: 0.04873 RPN score loss: 0.00681 RPN total loss: 0.05554 Total loss: 0.9235 timestamp: 1655040980.6130836 iteration: 41125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.16098 L1 loss: 0.0000e+00 L2 loss: 0.60225 Learning rate: 0.002 Mask loss: 0.12928 RPN box loss: 0.04605 RPN score loss: 0.0076 RPN total loss: 0.05365 Total loss: 0.94615 timestamp: 1655040983.9068644 iteration: 41130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11169 FastRCNN class loss: 0.03672 FastRCNN total loss: 0.14842 L1 loss: 0.0000e+00 L2 loss: 0.60224 Learning rate: 0.002 Mask loss: 0.09916 RPN box loss: 0.00625 RPN score loss: 0.00088 RPN total loss: 0.00713 Total loss: 0.85694 timestamp: 1655040987.2627084 iteration: 41135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10646 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.17423 L1 loss: 0.0000e+00 L2 loss: 0.60223 Learning rate: 0.002 Mask loss: 0.13854 RPN box loss: 0.01938 RPN score loss: 0.00167 RPN total loss: 0.02106 Total loss: 0.93606 timestamp: 1655040990.5391252 iteration: 41140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08844 FastRCNN class loss: 0.03744 FastRCNN total loss: 0.12587 L1 loss: 0.0000e+00 L2 loss: 0.60222 Learning rate: 0.002 Mask loss: 0.10107 RPN box loss: 0.0065 RPN score loss: 0.00169 RPN total loss: 0.00819 Total loss: 0.83736 timestamp: 1655040993.8164673 iteration: 41145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16246 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.24015 L1 loss: 0.0000e+00 L2 loss: 0.60221 Learning rate: 0.002 Mask loss: 0.10433 RPN box loss: 0.01871 RPN score loss: 0.00471 RPN total loss: 0.02342 Total loss: 0.97011 timestamp: 1655040997.0570133 iteration: 41150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19177 FastRCNN class loss: 0.13782 FastRCNN total loss: 0.32958 L1 loss: 0.0000e+00 L2 loss: 0.6022 Learning rate: 0.002 Mask loss: 0.18343 RPN box loss: 0.02898 RPN score loss: 0.00509 RPN total loss: 0.03407 Total loss: 1.14929 timestamp: 1655041000.3956606 iteration: 41155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14751 FastRCNN class loss: 0.06103 FastRCNN total loss: 0.20854 L1 loss: 0.0000e+00 L2 loss: 0.60219 Learning rate: 0.002 Mask loss: 0.1224 RPN box loss: 0.00563 RPN score loss: 0.00894 RPN total loss: 0.01457 Total loss: 0.94771 timestamp: 1655041003.6966648 iteration: 41160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09424 FastRCNN class loss: 0.05251 FastRCNN total loss: 0.14675 L1 loss: 0.0000e+00 L2 loss: 0.60218 Learning rate: 0.002 Mask loss: 0.10359 RPN box loss: 0.00901 RPN score loss: 0.0026 RPN total loss: 0.01161 Total loss: 0.86413 timestamp: 1655041006.9061272 iteration: 41165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.17358 L1 loss: 0.0000e+00 L2 loss: 0.60218 Learning rate: 0.002 Mask loss: 0.17338 RPN box loss: 0.00921 RPN score loss: 0.00302 RPN total loss: 0.01223 Total loss: 0.96137 timestamp: 1655041010.2190304 iteration: 41170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09812 FastRCNN class loss: 0.07982 FastRCNN total loss: 0.17795 L1 loss: 0.0000e+00 L2 loss: 0.60217 Learning rate: 0.002 Mask loss: 0.13645 RPN box loss: 0.02323 RPN score loss: 0.00408 RPN total loss: 0.0273 Total loss: 0.94387 timestamp: 1655041013.5098078 iteration: 41175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20238 FastRCNN class loss: 0.08467 FastRCNN total loss: 0.28705 L1 loss: 0.0000e+00 L2 loss: 0.60216 Learning rate: 0.002 Mask loss: 0.16476 RPN box loss: 0.0199 RPN score loss: 0.00858 RPN total loss: 0.02848 Total loss: 1.08244 timestamp: 1655041016.8306847 iteration: 41180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14254 FastRCNN class loss: 0.11987 FastRCNN total loss: 0.26241 L1 loss: 0.0000e+00 L2 loss: 0.60215 Learning rate: 0.002 Mask loss: 0.15726 RPN box loss: 0.04003 RPN score loss: 0.00957 RPN total loss: 0.0496 Total loss: 1.07142 timestamp: 1655041020.0854805 iteration: 41185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13036 FastRCNN class loss: 0.11176 FastRCNN total loss: 0.24212 L1 loss: 0.0000e+00 L2 loss: 0.60213 Learning rate: 0.002 Mask loss: 0.17933 RPN box loss: 0.0151 RPN score loss: 0.00309 RPN total loss: 0.01818 Total loss: 1.04176 timestamp: 1655041023.3769808 iteration: 41190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11965 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.20189 L1 loss: 0.0000e+00 L2 loss: 0.60213 Learning rate: 0.002 Mask loss: 0.1175 RPN box loss: 0.01581 RPN score loss: 0.00657 RPN total loss: 0.02238 Total loss: 0.9439 timestamp: 1655041026.6017275 iteration: 41195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.1505 L1 loss: 0.0000e+00 L2 loss: 0.60212 Learning rate: 0.002 Mask loss: 0.14053 RPN box loss: 0.044 RPN score loss: 0.00703 RPN total loss: 0.05104 Total loss: 0.94418 timestamp: 1655041029.8979943 iteration: 41200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.06303 FastRCNN total loss: 0.15978 L1 loss: 0.0000e+00 L2 loss: 0.60211 Learning rate: 0.002 Mask loss: 0.13174 RPN box loss: 0.01097 RPN score loss: 0.00405 RPN total loss: 0.01502 Total loss: 0.90864 timestamp: 1655041033.1965685 iteration: 41205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13275 FastRCNN class loss: 0.10921 FastRCNN total loss: 0.24196 L1 loss: 0.0000e+00 L2 loss: 0.6021 Learning rate: 0.002 Mask loss: 0.24558 RPN box loss: 0.01312 RPN score loss: 0.01792 RPN total loss: 0.03104 Total loss: 1.12068 timestamp: 1655041036.4024177 iteration: 41210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.04313 FastRCNN total loss: 0.12198 L1 loss: 0.0000e+00 L2 loss: 0.60209 Learning rate: 0.002 Mask loss: 0.10471 RPN box loss: 0.00452 RPN score loss: 0.00513 RPN total loss: 0.00965 Total loss: 0.83843 timestamp: 1655041039.693696 iteration: 41215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10138 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.17261 L1 loss: 0.0000e+00 L2 loss: 0.60208 Learning rate: 0.002 Mask loss: 0.16602 RPN box loss: 0.01958 RPN score loss: 0.00446 RPN total loss: 0.02405 Total loss: 0.96476 timestamp: 1655041042.9270387 iteration: 41220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.16925 L1 loss: 0.0000e+00 L2 loss: 0.60207 Learning rate: 0.002 Mask loss: 0.19105 RPN box loss: 0.0246 RPN score loss: 0.00811 RPN total loss: 0.03271 Total loss: 0.99508 timestamp: 1655041046.248446 iteration: 41225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13054 FastRCNN class loss: 0.05893 FastRCNN total loss: 0.18947 L1 loss: 0.0000e+00 L2 loss: 0.60206 Learning rate: 0.002 Mask loss: 0.1484 RPN box loss: 0.01814 RPN score loss: 0.00217 RPN total loss: 0.02031 Total loss: 0.96024 timestamp: 1655041049.543905 iteration: 41230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12589 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.20149 L1 loss: 0.0000e+00 L2 loss: 0.60205 Learning rate: 0.002 Mask loss: 0.14196 RPN box loss: 0.0134 RPN score loss: 0.00858 RPN total loss: 0.02198 Total loss: 0.96748 timestamp: 1655041052.8442512 iteration: 41235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1443 FastRCNN class loss: 0.09416 FastRCNN total loss: 0.23846 L1 loss: 0.0000e+00 L2 loss: 0.60204 Learning rate: 0.002 Mask loss: 0.19147 RPN box loss: 0.02002 RPN score loss: 0.00719 RPN total loss: 0.02721 Total loss: 1.05918 timestamp: 1655041056.1492825 iteration: 41240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15953 FastRCNN class loss: 0.08874 FastRCNN total loss: 0.24827 L1 loss: 0.0000e+00 L2 loss: 0.60203 Learning rate: 0.002 Mask loss: 0.24403 RPN box loss: 0.03219 RPN score loss: 0.0081 RPN total loss: 0.04029 Total loss: 1.13462 timestamp: 1655041059.4222522 iteration: 41245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11318 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.1938 L1 loss: 0.0000e+00 L2 loss: 0.60202 Learning rate: 0.002 Mask loss: 0.13487 RPN box loss: 0.02236 RPN score loss: 0.00422 RPN total loss: 0.02658 Total loss: 0.95728 timestamp: 1655041062.6900134 iteration: 41250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08762 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.14237 L1 loss: 0.0000e+00 L2 loss: 0.60201 Learning rate: 0.002 Mask loss: 0.12057 RPN box loss: 0.01311 RPN score loss: 0.00282 RPN total loss: 0.01593 Total loss: 0.88088 timestamp: 1655041065.9770057 iteration: 41255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13765 FastRCNN class loss: 0.09709 FastRCNN total loss: 0.23474 L1 loss: 0.0000e+00 L2 loss: 0.60201 Learning rate: 0.002 Mask loss: 0.11172 RPN box loss: 0.04245 RPN score loss: 0.00865 RPN total loss: 0.0511 Total loss: 0.99956 timestamp: 1655041069.2392101 iteration: 41260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17144 FastRCNN class loss: 0.08925 FastRCNN total loss: 0.26069 L1 loss: 0.0000e+00 L2 loss: 0.602 Learning rate: 0.002 Mask loss: 0.15473 RPN box loss: 0.0147 RPN score loss: 0.00418 RPN total loss: 0.01888 Total loss: 1.0363 timestamp: 1655041072.5178127 iteration: 41265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11511 FastRCNN class loss: 0.08671 FastRCNN total loss: 0.20182 L1 loss: 0.0000e+00 L2 loss: 0.60198 Learning rate: 0.002 Mask loss: 0.13766 RPN box loss: 0.03672 RPN score loss: 0.00342 RPN total loss: 0.04014 Total loss: 0.9816 timestamp: 1655041075.8573112 iteration: 41270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08883 FastRCNN class loss: 0.05094 FastRCNN total loss: 0.13977 L1 loss: 0.0000e+00 L2 loss: 0.60197 Learning rate: 0.002 Mask loss: 0.09026 RPN box loss: 0.00411 RPN score loss: 0.00357 RPN total loss: 0.00767 Total loss: 0.83968 timestamp: 1655041079.1377692 iteration: 41275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15383 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.23977 L1 loss: 0.0000e+00 L2 loss: 0.60197 Learning rate: 0.002 Mask loss: 0.11649 RPN box loss: 0.01358 RPN score loss: 0.00179 RPN total loss: 0.01537 Total loss: 0.9736 timestamp: 1655041082.3804922 iteration: 41280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12291 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.19684 L1 loss: 0.0000e+00 L2 loss: 0.60196 Learning rate: 0.002 Mask loss: 0.19531 RPN box loss: 0.03028 RPN score loss: 0.00613 RPN total loss: 0.03641 Total loss: 1.03051 timestamp: 1655041085.637473 iteration: 41285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10287 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.16985 L1 loss: 0.0000e+00 L2 loss: 0.60195 Learning rate: 0.002 Mask loss: 0.16012 RPN box loss: 0.01049 RPN score loss: 0.00536 RPN total loss: 0.01584 Total loss: 0.94776 timestamp: 1655041088.9349666 iteration: 41290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09652 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.15915 L1 loss: 0.0000e+00 L2 loss: 0.60194 Learning rate: 0.002 Mask loss: 0.14851 RPN box loss: 0.01026 RPN score loss: 0.00344 RPN total loss: 0.0137 Total loss: 0.9233 timestamp: 1655041092.2157464 iteration: 41295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14063 FastRCNN class loss: 0.0781 FastRCNN total loss: 0.21873 L1 loss: 0.0000e+00 L2 loss: 0.60193 Learning rate: 0.002 Mask loss: 0.11872 RPN box loss: 0.01954 RPN score loss: 0.0109 RPN total loss: 0.03044 Total loss: 0.96982 timestamp: 1655041095.4843435 iteration: 41300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2013 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.28867 L1 loss: 0.0000e+00 L2 loss: 0.60192 Learning rate: 0.002 Mask loss: 0.11461 RPN box loss: 0.00903 RPN score loss: 0.00696 RPN total loss: 0.016 Total loss: 1.02119 timestamp: 1655041098.7571018 iteration: 41305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11667 FastRCNN class loss: 0.05036 FastRCNN total loss: 0.16704 L1 loss: 0.0000e+00 L2 loss: 0.60191 Learning rate: 0.002 Mask loss: 0.09973 RPN box loss: 0.00742 RPN score loss: 0.00352 RPN total loss: 0.01094 Total loss: 0.87962 timestamp: 1655041102.0075474 iteration: 41310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06402 FastRCNN class loss: 0.05918 FastRCNN total loss: 0.1232 L1 loss: 0.0000e+00 L2 loss: 0.6019 Learning rate: 0.002 Mask loss: 0.1271 RPN box loss: 0.01166 RPN score loss: 0.00514 RPN total loss: 0.0168 Total loss: 0.86899 timestamp: 1655041105.2644818 iteration: 41315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16183 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.24397 L1 loss: 0.0000e+00 L2 loss: 0.60189 Learning rate: 0.002 Mask loss: 0.19594 RPN box loss: 0.04776 RPN score loss: 0.01297 RPN total loss: 0.06073 Total loss: 1.10254 timestamp: 1655041108.5277886 iteration: 41320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.17098 L1 loss: 0.0000e+00 L2 loss: 0.60188 Learning rate: 0.002 Mask loss: 0.09439 RPN box loss: 0.01489 RPN score loss: 0.00206 RPN total loss: 0.01695 Total loss: 0.8842 timestamp: 1655041111.7943213 iteration: 41325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.10079 FastRCNN total loss: 0.23245 L1 loss: 0.0000e+00 L2 loss: 0.60187 Learning rate: 0.002 Mask loss: 0.18935 RPN box loss: 0.04185 RPN score loss: 0.00665 RPN total loss: 0.04849 Total loss: 1.07217 timestamp: 1655041115.027723 iteration: 41330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15494 FastRCNN class loss: 0.14384 FastRCNN total loss: 0.29878 L1 loss: 0.0000e+00 L2 loss: 0.60186 Learning rate: 0.002 Mask loss: 0.1875 RPN box loss: 0.01166 RPN score loss: 0.00298 RPN total loss: 0.01463 Total loss: 1.10278 timestamp: 1655041118.2924812 iteration: 41335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04699 FastRCNN class loss: 0.04317 FastRCNN total loss: 0.09016 L1 loss: 0.0000e+00 L2 loss: 0.60185 Learning rate: 0.002 Mask loss: 0.10536 RPN box loss: 0.00778 RPN score loss: 0.00095 RPN total loss: 0.00874 Total loss: 0.80611 timestamp: 1655041121.5190651 iteration: 41340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08629 FastRCNN class loss: 0.07194 FastRCNN total loss: 0.15823 L1 loss: 0.0000e+00 L2 loss: 0.60184 Learning rate: 0.002 Mask loss: 0.11189 RPN box loss: 0.01553 RPN score loss: 0.00264 RPN total loss: 0.01817 Total loss: 0.89013 timestamp: 1655041124.7496767 iteration: 41345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16305 FastRCNN class loss: 0.12191 FastRCNN total loss: 0.28497 L1 loss: 0.0000e+00 L2 loss: 0.60183 Learning rate: 0.002 Mask loss: 0.27802 RPN box loss: 0.02474 RPN score loss: 0.01108 RPN total loss: 0.03583 Total loss: 1.20065 timestamp: 1655041127.957403 iteration: 41350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0807 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.12964 L1 loss: 0.0000e+00 L2 loss: 0.60182 Learning rate: 0.002 Mask loss: 0.11702 RPN box loss: 0.01767 RPN score loss: 0.00163 RPN total loss: 0.01929 Total loss: 0.86777 timestamp: 1655041131.2390685 iteration: 41355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13157 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.20512 L1 loss: 0.0000e+00 L2 loss: 0.60181 Learning rate: 0.002 Mask loss: 0.12456 RPN box loss: 0.01956 RPN score loss: 0.00363 RPN total loss: 0.02319 Total loss: 0.95467 timestamp: 1655041134.529233 iteration: 41360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.17191 L1 loss: 0.0000e+00 L2 loss: 0.6018 Learning rate: 0.002 Mask loss: 0.10955 RPN box loss: 0.01379 RPN score loss: 0.0026 RPN total loss: 0.01639 Total loss: 0.89966 timestamp: 1655041137.7943385 iteration: 41365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08588 FastRCNN class loss: 0.03152 FastRCNN total loss: 0.1174 L1 loss: 0.0000e+00 L2 loss: 0.6018 Learning rate: 0.002 Mask loss: 0.09469 RPN box loss: 0.00695 RPN score loss: 0.00109 RPN total loss: 0.00804 Total loss: 0.82193 timestamp: 1655041141.0801015 iteration: 41370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10037 FastRCNN class loss: 0.06923 FastRCNN total loss: 0.1696 L1 loss: 0.0000e+00 L2 loss: 0.60179 Learning rate: 0.002 Mask loss: 0.12528 RPN box loss: 0.01352 RPN score loss: 0.00373 RPN total loss: 0.01725 Total loss: 0.91392 timestamp: 1655041144.3870094 iteration: 41375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.16886 L1 loss: 0.0000e+00 L2 loss: 0.60178 Learning rate: 0.002 Mask loss: 0.1492 RPN box loss: 0.01497 RPN score loss: 0.00653 RPN total loss: 0.0215 Total loss: 0.94135 timestamp: 1655041147.6218083 iteration: 41380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11764 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.17936 L1 loss: 0.0000e+00 L2 loss: 0.60177 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.02066 RPN score loss: 0.01157 RPN total loss: 0.03223 Total loss: 0.94411 timestamp: 1655041150.9264283 iteration: 41385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09154 FastRCNN class loss: 0.04934 FastRCNN total loss: 0.14088 L1 loss: 0.0000e+00 L2 loss: 0.60176 Learning rate: 0.002 Mask loss: 0.10855 RPN box loss: 0.01072 RPN score loss: 0.00124 RPN total loss: 0.01196 Total loss: 0.86315 timestamp: 1655041154.257598 iteration: 41390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08489 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.14346 L1 loss: 0.0000e+00 L2 loss: 0.60175 Learning rate: 0.002 Mask loss: 0.1183 RPN box loss: 0.03439 RPN score loss: 0.00446 RPN total loss: 0.03884 Total loss: 0.90235 timestamp: 1655041157.5968773 iteration: 41395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07792 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.1575 L1 loss: 0.0000e+00 L2 loss: 0.60174 Learning rate: 0.002 Mask loss: 0.13069 RPN box loss: 0.01203 RPN score loss: 0.00466 RPN total loss: 0.01669 Total loss: 0.90662 timestamp: 1655041160.8201213 iteration: 41400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12657 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.18154 L1 loss: 0.0000e+00 L2 loss: 0.60173 Learning rate: 0.002 Mask loss: 0.11094 RPN box loss: 0.07909 RPN score loss: 0.00414 RPN total loss: 0.08323 Total loss: 0.97744 timestamp: 1655041164.113306 iteration: 41405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1255 FastRCNN class loss: 0.08567 FastRCNN total loss: 0.21117 L1 loss: 0.0000e+00 L2 loss: 0.60172 Learning rate: 0.002 Mask loss: 0.19988 RPN box loss: 0.0534 RPN score loss: 0.0106 RPN total loss: 0.06399 Total loss: 1.07676 timestamp: 1655041167.3980343 iteration: 41410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11031 FastRCNN class loss: 0.09345 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 0.60171 Learning rate: 0.002 Mask loss: 0.12397 RPN box loss: 0.01101 RPN score loss: 0.01109 RPN total loss: 0.0221 Total loss: 0.95154 timestamp: 1655041170.63768 iteration: 41415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14803 FastRCNN class loss: 0.15023 FastRCNN total loss: 0.29825 L1 loss: 0.0000e+00 L2 loss: 0.6017 Learning rate: 0.002 Mask loss: 0.17399 RPN box loss: 0.04901 RPN score loss: 0.00879 RPN total loss: 0.0578 Total loss: 1.13174 timestamp: 1655041173.952971 iteration: 41420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10361 FastRCNN class loss: 0.053 FastRCNN total loss: 0.15661 L1 loss: 0.0000e+00 L2 loss: 0.60169 Learning rate: 0.002 Mask loss: 0.10477 RPN box loss: 0.01397 RPN score loss: 0.00235 RPN total loss: 0.01632 Total loss: 0.87939 timestamp: 1655041177.2159111 iteration: 41425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.08852 FastRCNN total loss: 0.17355 L1 loss: 0.0000e+00 L2 loss: 0.60169 Learning rate: 0.002 Mask loss: 0.15776 RPN box loss: 0.04998 RPN score loss: 0.01636 RPN total loss: 0.06635 Total loss: 0.99934 timestamp: 1655041180.5269926 iteration: 41430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.10567 FastRCNN total loss: 0.23053 L1 loss: 0.0000e+00 L2 loss: 0.60168 Learning rate: 0.002 Mask loss: 0.1868 RPN box loss: 0.01129 RPN score loss: 0.00752 RPN total loss: 0.01881 Total loss: 1.03782 timestamp: 1655041183.7968843 iteration: 41435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.21622 L1 loss: 0.0000e+00 L2 loss: 0.60166 Learning rate: 0.002 Mask loss: 0.13785 RPN box loss: 0.01604 RPN score loss: 0.00761 RPN total loss: 0.02365 Total loss: 0.97939 timestamp: 1655041187.064372 iteration: 41440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07982 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.60165 Learning rate: 0.002 Mask loss: 0.1434 RPN box loss: 0.01202 RPN score loss: 0.00208 RPN total loss: 0.0141 Total loss: 0.90879 timestamp: 1655041190.2983184 iteration: 41445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11575 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.19096 L1 loss: 0.0000e+00 L2 loss: 0.60164 Learning rate: 0.002 Mask loss: 0.14836 RPN box loss: 0.02377 RPN score loss: 0.00328 RPN total loss: 0.02706 Total loss: 0.96802 timestamp: 1655041193.616724 iteration: 41450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.16106 L1 loss: 0.0000e+00 L2 loss: 0.60163 Learning rate: 0.002 Mask loss: 0.18071 RPN box loss: 0.01065 RPN score loss: 0.00643 RPN total loss: 0.01708 Total loss: 0.96048 timestamp: 1655041196.862395 iteration: 41455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.08737 FastRCNN total loss: 0.23336 L1 loss: 0.0000e+00 L2 loss: 0.60162 Learning rate: 0.002 Mask loss: 0.17942 RPN box loss: 0.02502 RPN score loss: 0.01201 RPN total loss: 0.03703 Total loss: 1.05144 timestamp: 1655041200.1357977 iteration: 41460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12504 FastRCNN class loss: 0.0797 FastRCNN total loss: 0.20474 L1 loss: 0.0000e+00 L2 loss: 0.60161 Learning rate: 0.002 Mask loss: 0.13314 RPN box loss: 0.03645 RPN score loss: 0.0044 RPN total loss: 0.04085 Total loss: 0.98035 timestamp: 1655041203.3993316 iteration: 41465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09263 FastRCNN class loss: 0.09528 FastRCNN total loss: 0.18791 L1 loss: 0.0000e+00 L2 loss: 0.6016 Learning rate: 0.002 Mask loss: 0.14873 RPN box loss: 0.03501 RPN score loss: 0.00623 RPN total loss: 0.04124 Total loss: 0.97947 timestamp: 1655041206.5951529 iteration: 41470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14335 FastRCNN class loss: 0.13052 FastRCNN total loss: 0.27387 L1 loss: 0.0000e+00 L2 loss: 0.60159 Learning rate: 0.002 Mask loss: 0.2256 RPN box loss: 0.02607 RPN score loss: 0.00878 RPN total loss: 0.03484 Total loss: 1.1359 timestamp: 1655041209.943753 iteration: 41475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15024 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.21786 L1 loss: 0.0000e+00 L2 loss: 0.60158 Learning rate: 0.002 Mask loss: 0.1721 RPN box loss: 0.01975 RPN score loss: 0.00493 RPN total loss: 0.02468 Total loss: 1.01623 timestamp: 1655041213.200438 iteration: 41480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09978 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.16472 L1 loss: 0.0000e+00 L2 loss: 0.60157 Learning rate: 0.002 Mask loss: 0.09547 RPN box loss: 0.02822 RPN score loss: 0.0081 RPN total loss: 0.03632 Total loss: 0.89808 timestamp: 1655041216.5339262 iteration: 41485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09726 FastRCNN class loss: 0.08752 FastRCNN total loss: 0.18478 L1 loss: 0.0000e+00 L2 loss: 0.60156 Learning rate: 0.002 Mask loss: 0.17732 RPN box loss: 0.03639 RPN score loss: 0.00774 RPN total loss: 0.04413 Total loss: 1.00779 timestamp: 1655041219.788069 iteration: 41490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07609 FastRCNN class loss: 0.06512 FastRCNN total loss: 0.14121 L1 loss: 0.0000e+00 L2 loss: 0.60155 Learning rate: 0.002 Mask loss: 0.0903 RPN box loss: 0.01492 RPN score loss: 0.00169 RPN total loss: 0.0166 Total loss: 0.84966 timestamp: 1655041223.027034 iteration: 41495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12426 FastRCNN class loss: 0.07821 FastRCNN total loss: 0.20247 L1 loss: 0.0000e+00 L2 loss: 0.60154 Learning rate: 0.002 Mask loss: 0.13392 RPN box loss: 0.00748 RPN score loss: 0.00909 RPN total loss: 0.01657 Total loss: 0.9545 timestamp: 1655041226.3144183 iteration: 41500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14412 FastRCNN class loss: 0.1097 FastRCNN total loss: 0.25382 L1 loss: 0.0000e+00 L2 loss: 0.60153 Learning rate: 0.002 Mask loss: 0.25096 RPN box loss: 0.03108 RPN score loss: 0.01427 RPN total loss: 0.04535 Total loss: 1.15167 timestamp: 1655041229.6107035 iteration: 41505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07356 FastRCNN class loss: 0.04581 FastRCNN total loss: 0.11937 L1 loss: 0.0000e+00 L2 loss: 0.60152 Learning rate: 0.002 Mask loss: 0.1263 RPN box loss: 0.02159 RPN score loss: 0.00119 RPN total loss: 0.02278 Total loss: 0.86998 timestamp: 1655041232.8918493 iteration: 41510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09421 FastRCNN class loss: 0.08688 FastRCNN total loss: 0.18109 L1 loss: 0.0000e+00 L2 loss: 0.60152 Learning rate: 0.002 Mask loss: 0.18551 RPN box loss: 0.02243 RPN score loss: 0.0113 RPN total loss: 0.03373 Total loss: 1.00184 timestamp: 1655041236.1396048 iteration: 41515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11624 FastRCNN class loss: 0.06637 FastRCNN total loss: 0.1826 L1 loss: 0.0000e+00 L2 loss: 0.60151 Learning rate: 0.002 Mask loss: 0.09893 RPN box loss: 0.01467 RPN score loss: 0.00231 RPN total loss: 0.01699 Total loss: 0.90003 timestamp: 1655041239.406056 iteration: 41520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13996 FastRCNN class loss: 0.12066 FastRCNN total loss: 0.26062 L1 loss: 0.0000e+00 L2 loss: 0.6015 Learning rate: 0.002 Mask loss: 0.155 RPN box loss: 0.0258 RPN score loss: 0.00674 RPN total loss: 0.03254 Total loss: 1.04967 timestamp: 1655041242.6981263 iteration: 41525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06458 FastRCNN class loss: 0.04615 FastRCNN total loss: 0.11073 L1 loss: 0.0000e+00 L2 loss: 0.6015 Learning rate: 0.002 Mask loss: 0.15094 RPN box loss: 0.0155 RPN score loss: 0.0062 RPN total loss: 0.0217 Total loss: 0.88487 timestamp: 1655041246.0002162 iteration: 41530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09255 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.14874 L1 loss: 0.0000e+00 L2 loss: 0.60149 Learning rate: 0.002 Mask loss: 0.14465 RPN box loss: 0.01641 RPN score loss: 0.00691 RPN total loss: 0.02332 Total loss: 0.9182 timestamp: 1655041249.283057 iteration: 41535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09856 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.18321 L1 loss: 0.0000e+00 L2 loss: 0.60148 Learning rate: 0.002 Mask loss: 0.19177 RPN box loss: 0.03005 RPN score loss: 0.00485 RPN total loss: 0.0349 Total loss: 1.01137 timestamp: 1655041252.5249314 iteration: 41540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10105 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.1563 L1 loss: 0.0000e+00 L2 loss: 0.60147 Learning rate: 0.002 Mask loss: 0.17636 RPN box loss: 0.01315 RPN score loss: 0.00619 RPN total loss: 0.01934 Total loss: 0.95346 timestamp: 1655041255.804822 iteration: 41545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08395 FastRCNN class loss: 0.03928 FastRCNN total loss: 0.12323 L1 loss: 0.0000e+00 L2 loss: 0.60145 Learning rate: 0.002 Mask loss: 0.13499 RPN box loss: 0.01259 RPN score loss: 0.00237 RPN total loss: 0.01496 Total loss: 0.87464 timestamp: 1655041259.1212103 iteration: 41550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03455 FastRCNN class loss: 0.02769 FastRCNN total loss: 0.06224 L1 loss: 0.0000e+00 L2 loss: 0.60144 Learning rate: 0.002 Mask loss: 0.10294 RPN box loss: 0.02198 RPN score loss: 0.00407 RPN total loss: 0.02605 Total loss: 0.79268 timestamp: 1655041262.3823588 iteration: 41555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17698 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.24025 L1 loss: 0.0000e+00 L2 loss: 0.60144 Learning rate: 0.002 Mask loss: 0.11347 RPN box loss: 0.00786 RPN score loss: 0.00281 RPN total loss: 0.01067 Total loss: 0.96583 timestamp: 1655041265.6790962 iteration: 41560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08258 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.14304 L1 loss: 0.0000e+00 L2 loss: 0.60143 Learning rate: 0.002 Mask loss: 0.12016 RPN box loss: 0.02043 RPN score loss: 0.00727 RPN total loss: 0.0277 Total loss: 0.89232 timestamp: 1655041268.9731083 iteration: 41565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.09487 FastRCNN total loss: 0.19125 L1 loss: 0.0000e+00 L2 loss: 0.60142 Learning rate: 0.002 Mask loss: 0.12591 RPN box loss: 0.01805 RPN score loss: 0.01194 RPN total loss: 0.02999 Total loss: 0.94858 timestamp: 1655041272.2432678 iteration: 41570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10798 FastRCNN class loss: 0.07404 FastRCNN total loss: 0.18203 L1 loss: 0.0000e+00 L2 loss: 0.60141 Learning rate: 0.002 Mask loss: 0.17208 RPN box loss: 0.0304 RPN score loss: 0.00771 RPN total loss: 0.03811 Total loss: 0.99362 timestamp: 1655041275.5107465 iteration: 41575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11599 FastRCNN class loss: 0.10064 FastRCNN total loss: 0.21663 L1 loss: 0.0000e+00 L2 loss: 0.6014 Learning rate: 0.002 Mask loss: 0.15752 RPN box loss: 0.0396 RPN score loss: 0.0091 RPN total loss: 0.0487 Total loss: 1.02425 timestamp: 1655041278.770829 iteration: 41580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10198 FastRCNN class loss: 0.06774 FastRCNN total loss: 0.16973 L1 loss: 0.0000e+00 L2 loss: 0.60139 Learning rate: 0.002 Mask loss: 0.12662 RPN box loss: 0.01406 RPN score loss: 0.00564 RPN total loss: 0.01969 Total loss: 0.91743 timestamp: 1655041282.0540833 iteration: 41585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.19167 L1 loss: 0.0000e+00 L2 loss: 0.60138 Learning rate: 0.002 Mask loss: 0.11844 RPN box loss: 0.009 RPN score loss: 0.00461 RPN total loss: 0.01361 Total loss: 0.9251 timestamp: 1655041285.36729 iteration: 41590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12689 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.19183 L1 loss: 0.0000e+00 L2 loss: 0.60137 Learning rate: 0.002 Mask loss: 0.18661 RPN box loss: 0.04886 RPN score loss: 0.01354 RPN total loss: 0.06239 Total loss: 1.0422 timestamp: 1655041288.7031498 iteration: 41595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.14555 L1 loss: 0.0000e+00 L2 loss: 0.60136 Learning rate: 0.002 Mask loss: 0.21526 RPN box loss: 0.02306 RPN score loss: 0.00312 RPN total loss: 0.02617 Total loss: 0.98835 timestamp: 1655041291.9650972 iteration: 41600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.12378 FastRCNN total loss: 0.26653 L1 loss: 0.0000e+00 L2 loss: 0.60136 Learning rate: 0.002 Mask loss: 0.19405 RPN box loss: 0.02722 RPN score loss: 0.00344 RPN total loss: 0.03065 Total loss: 1.09259 timestamp: 1655041295.208883 iteration: 41605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19016 FastRCNN class loss: 0.13009 FastRCNN total loss: 0.32026 L1 loss: 0.0000e+00 L2 loss: 0.60135 Learning rate: 0.002 Mask loss: 0.18075 RPN box loss: 0.0451 RPN score loss: 0.01215 RPN total loss: 0.05724 Total loss: 1.15959 timestamp: 1655041298.4888124 iteration: 41610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17997 FastRCNN class loss: 0.12132 FastRCNN total loss: 0.30129 L1 loss: 0.0000e+00 L2 loss: 0.60134 Learning rate: 0.002 Mask loss: 0.16127 RPN box loss: 0.02015 RPN score loss: 0.00611 RPN total loss: 0.02626 Total loss: 1.09014 timestamp: 1655041301.7164352 iteration: 41615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09745 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.16539 L1 loss: 0.0000e+00 L2 loss: 0.60132 Learning rate: 0.002 Mask loss: 0.16078 RPN box loss: 0.02746 RPN score loss: 0.00101 RPN total loss: 0.02846 Total loss: 0.95595 timestamp: 1655041304.9641836 iteration: 41620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12551 FastRCNN class loss: 0.08441 FastRCNN total loss: 0.20992 L1 loss: 0.0000e+00 L2 loss: 0.60131 Learning rate: 0.002 Mask loss: 0.1229 RPN box loss: 0.02495 RPN score loss: 0.00427 RPN total loss: 0.02921 Total loss: 0.96335 timestamp: 1655041308.2558281 iteration: 41625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12738 FastRCNN class loss: 0.0994 FastRCNN total loss: 0.22678 L1 loss: 0.0000e+00 L2 loss: 0.6013 Learning rate: 0.002 Mask loss: 0.17012 RPN box loss: 0.10044 RPN score loss: 0.0098 RPN total loss: 0.11025 Total loss: 1.10845 timestamp: 1655041311.5043275 iteration: 41630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09506 FastRCNN class loss: 0.04339 FastRCNN total loss: 0.13845 L1 loss: 0.0000e+00 L2 loss: 0.60129 Learning rate: 0.002 Mask loss: 0.12694 RPN box loss: 0.0307 RPN score loss: 0.00374 RPN total loss: 0.03444 Total loss: 0.90112 timestamp: 1655041314.7428024 iteration: 41635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07784 FastRCNN class loss: 0.12357 FastRCNN total loss: 0.20141 L1 loss: 0.0000e+00 L2 loss: 0.60129 Learning rate: 0.002 Mask loss: 0.23308 RPN box loss: 0.03702 RPN score loss: 0.08544 RPN total loss: 0.12246 Total loss: 1.15823 timestamp: 1655041317.9628816 iteration: 41640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08315 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.17065 L1 loss: 0.0000e+00 L2 loss: 0.60128 Learning rate: 0.002 Mask loss: 0.17271 RPN box loss: 0.02973 RPN score loss: 0.0041 RPN total loss: 0.03383 Total loss: 0.97847 timestamp: 1655041321.1973138 iteration: 41645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16511 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.23572 L1 loss: 0.0000e+00 L2 loss: 0.60127 Learning rate: 0.002 Mask loss: 0.20028 RPN box loss: 0.02007 RPN score loss: 0.00427 RPN total loss: 0.02434 Total loss: 1.06161 timestamp: 1655041324.4704819 iteration: 41650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.17969 L1 loss: 0.0000e+00 L2 loss: 0.60126 Learning rate: 0.002 Mask loss: 0.15703 RPN box loss: 0.01595 RPN score loss: 0.01371 RPN total loss: 0.02966 Total loss: 0.96764 timestamp: 1655041327.7326658 iteration: 41655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12864 FastRCNN class loss: 0.07404 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.60125 Learning rate: 0.002 Mask loss: 0.12629 RPN box loss: 0.01892 RPN score loss: 0.0038 RPN total loss: 0.02272 Total loss: 0.95294 timestamp: 1655041331.0646224 iteration: 41660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13367 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.22136 L1 loss: 0.0000e+00 L2 loss: 0.60124 Learning rate: 0.002 Mask loss: 0.19148 RPN box loss: 0.02273 RPN score loss: 0.00898 RPN total loss: 0.03171 Total loss: 1.04578 timestamp: 1655041334.320652 iteration: 41665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.05752 FastRCNN total loss: 0.14775 L1 loss: 0.0000e+00 L2 loss: 0.60123 Learning rate: 0.002 Mask loss: 0.12826 RPN box loss: 0.01072 RPN score loss: 0.00138 RPN total loss: 0.0121 Total loss: 0.88934 timestamp: 1655041337.588096 iteration: 41670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07293 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.13696 L1 loss: 0.0000e+00 L2 loss: 0.60122 Learning rate: 0.002 Mask loss: 0.13075 RPN box loss: 0.02447 RPN score loss: 0.00639 RPN total loss: 0.03086 Total loss: 0.89979 timestamp: 1655041340.8708653 iteration: 41675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18791 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.26129 L1 loss: 0.0000e+00 L2 loss: 0.60121 Learning rate: 0.002 Mask loss: 0.11013 RPN box loss: 0.05385 RPN score loss: 0.00207 RPN total loss: 0.05592 Total loss: 1.02855 timestamp: 1655041344.135977 iteration: 41680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09716 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.1559 L1 loss: 0.0000e+00 L2 loss: 0.6012 Learning rate: 0.002 Mask loss: 0.0914 RPN box loss: 0.02249 RPN score loss: 0.00324 RPN total loss: 0.02573 Total loss: 0.87423 timestamp: 1655041347.4582715 iteration: 41685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09595 FastRCNN class loss: 0.10086 FastRCNN total loss: 0.19681 L1 loss: 0.0000e+00 L2 loss: 0.6012 Learning rate: 0.002 Mask loss: 0.16835 RPN box loss: 0.01766 RPN score loss: 0.00328 RPN total loss: 0.02094 Total loss: 0.98729 timestamp: 1655041350.7258253 iteration: 41690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09713 FastRCNN class loss: 0.09451 FastRCNN total loss: 0.19163 L1 loss: 0.0000e+00 L2 loss: 0.60119 Learning rate: 0.002 Mask loss: 0.15252 RPN box loss: 0.02708 RPN score loss: 0.00512 RPN total loss: 0.0322 Total loss: 0.97754 timestamp: 1655041354.0545788 iteration: 41695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10012 FastRCNN class loss: 0.09558 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 0.60117 Learning rate: 0.002 Mask loss: 0.11634 RPN box loss: 0.00678 RPN score loss: 0.00165 RPN total loss: 0.00843 Total loss: 0.92164 timestamp: 1655041357.312488 iteration: 41700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11055 FastRCNN class loss: 0.0789 FastRCNN total loss: 0.18944 L1 loss: 0.0000e+00 L2 loss: 0.60116 Learning rate: 0.002 Mask loss: 0.13662 RPN box loss: 0.01353 RPN score loss: 0.00259 RPN total loss: 0.01612 Total loss: 0.94335 timestamp: 1655041360.568322 iteration: 41705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17188 FastRCNN class loss: 0.10778 FastRCNN total loss: 0.27967 L1 loss: 0.0000e+00 L2 loss: 0.60116 Learning rate: 0.002 Mask loss: 0.17685 RPN box loss: 0.0276 RPN score loss: 0.01325 RPN total loss: 0.04086 Total loss: 1.09853 timestamp: 1655041363.8056872 iteration: 41710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09065 FastRCNN class loss: 0.07516 FastRCNN total loss: 0.16581 L1 loss: 0.0000e+00 L2 loss: 0.60115 Learning rate: 0.002 Mask loss: 0.12153 RPN box loss: 0.0556 RPN score loss: 0.01071 RPN total loss: 0.06632 Total loss: 0.9548 timestamp: 1655041367.134661 iteration: 41715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10429 FastRCNN class loss: 0.0746 FastRCNN total loss: 0.17888 L1 loss: 0.0000e+00 L2 loss: 0.60114 Learning rate: 0.002 Mask loss: 0.16619 RPN box loss: 0.0167 RPN score loss: 0.00378 RPN total loss: 0.02049 Total loss: 0.9667 timestamp: 1655041370.4189413 iteration: 41720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12316 FastRCNN class loss: 0.055 FastRCNN total loss: 0.17816 L1 loss: 0.0000e+00 L2 loss: 0.60113 Learning rate: 0.002 Mask loss: 0.1129 RPN box loss: 0.0345 RPN score loss: 0.00988 RPN total loss: 0.04438 Total loss: 0.93656 timestamp: 1655041373.7400937 iteration: 41725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18436 FastRCNN class loss: 0.1079 FastRCNN total loss: 0.29226 L1 loss: 0.0000e+00 L2 loss: 0.60112 Learning rate: 0.002 Mask loss: 0.2526 RPN box loss: 0.04065 RPN score loss: 0.01285 RPN total loss: 0.0535 Total loss: 1.19948 timestamp: 1655041376.9897635 iteration: 41730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07289 FastRCNN class loss: 0.05139 FastRCNN total loss: 0.12428 L1 loss: 0.0000e+00 L2 loss: 0.60111 Learning rate: 0.002 Mask loss: 0.15132 RPN box loss: 0.01149 RPN score loss: 0.00406 RPN total loss: 0.01554 Total loss: 0.89225 timestamp: 1655041380.3520029 iteration: 41735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10329 FastRCNN class loss: 0.09514 FastRCNN total loss: 0.19843 L1 loss: 0.0000e+00 L2 loss: 0.6011 Learning rate: 0.002 Mask loss: 0.12029 RPN box loss: 0.03287 RPN score loss: 0.00759 RPN total loss: 0.04046 Total loss: 0.96028 timestamp: 1655041383.6275082 iteration: 41740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.17451 L1 loss: 0.0000e+00 L2 loss: 0.60109 Learning rate: 0.002 Mask loss: 0.14079 RPN box loss: 0.01741 RPN score loss: 0.00421 RPN total loss: 0.02162 Total loss: 0.93801 timestamp: 1655041386.9333916 iteration: 41745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11289 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.17483 L1 loss: 0.0000e+00 L2 loss: 0.60108 Learning rate: 0.002 Mask loss: 0.10814 RPN box loss: 0.02508 RPN score loss: 0.0073 RPN total loss: 0.03238 Total loss: 0.91644 timestamp: 1655041390.1743588 iteration: 41750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1316 FastRCNN class loss: 0.0612 FastRCNN total loss: 0.1928 L1 loss: 0.0000e+00 L2 loss: 0.60107 Learning rate: 0.002 Mask loss: 0.11806 RPN box loss: 0.01041 RPN score loss: 0.00423 RPN total loss: 0.01463 Total loss: 0.92657 timestamp: 1655041393.4782047 iteration: 41755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09755 FastRCNN class loss: 0.0424 FastRCNN total loss: 0.13995 L1 loss: 0.0000e+00 L2 loss: 0.60106 Learning rate: 0.002 Mask loss: 0.11376 RPN box loss: 0.02851 RPN score loss: 0.00591 RPN total loss: 0.03442 Total loss: 0.88919 timestamp: 1655041396.7447417 iteration: 41760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14132 FastRCNN class loss: 0.12451 FastRCNN total loss: 0.26584 L1 loss: 0.0000e+00 L2 loss: 0.60105 Learning rate: 0.002 Mask loss: 0.12496 RPN box loss: 0.01735 RPN score loss: 0.00925 RPN total loss: 0.02659 Total loss: 1.01845 timestamp: 1655041399.9871676 iteration: 41765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10952 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 0.60105 Learning rate: 0.002 Mask loss: 0.20972 RPN box loss: 0.04999 RPN score loss: 0.00859 RPN total loss: 0.05858 Total loss: 1.06147 timestamp: 1655041403.271976 iteration: 41770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14106 FastRCNN class loss: 0.0684 FastRCNN total loss: 0.20946 L1 loss: 0.0000e+00 L2 loss: 0.60104 Learning rate: 0.002 Mask loss: 0.15558 RPN box loss: 0.01749 RPN score loss: 0.01198 RPN total loss: 0.02946 Total loss: 0.99554 timestamp: 1655041406.6025665 iteration: 41775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.0572 FastRCNN total loss: 0.15566 L1 loss: 0.0000e+00 L2 loss: 0.60103 Learning rate: 0.002 Mask loss: 0.15439 RPN box loss: 0.02531 RPN score loss: 0.00184 RPN total loss: 0.02715 Total loss: 0.93823 timestamp: 1655041409.9041352 iteration: 41780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14104 FastRCNN class loss: 0.08401 FastRCNN total loss: 0.22505 L1 loss: 0.0000e+00 L2 loss: 0.60102 Learning rate: 0.002 Mask loss: 0.15438 RPN box loss: 0.03077 RPN score loss: 0.00904 RPN total loss: 0.03981 Total loss: 1.02026 timestamp: 1655041413.2378376 iteration: 41785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10403 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.15748 L1 loss: 0.0000e+00 L2 loss: 0.60101 Learning rate: 0.002 Mask loss: 0.12216 RPN box loss: 0.00482 RPN score loss: 0.00215 RPN total loss: 0.00697 Total loss: 0.88762 timestamp: 1655041416.4419174 iteration: 41790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20385 FastRCNN class loss: 0.08629 FastRCNN total loss: 0.29014 L1 loss: 0.0000e+00 L2 loss: 0.601 Learning rate: 0.002 Mask loss: 0.15918 RPN box loss: 0.04224 RPN score loss: 0.01138 RPN total loss: 0.05363 Total loss: 1.10395 timestamp: 1655041419.7603712 iteration: 41795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09796 FastRCNN class loss: 0.04115 FastRCNN total loss: 0.13911 L1 loss: 0.0000e+00 L2 loss: 0.60099 Learning rate: 0.002 Mask loss: 0.15431 RPN box loss: 0.02537 RPN score loss: 0.00333 RPN total loss: 0.0287 Total loss: 0.9231 timestamp: 1655041422.9996336 iteration: 41800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16403 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.25502 L1 loss: 0.0000e+00 L2 loss: 0.60098 Learning rate: 0.002 Mask loss: 0.18951 RPN box loss: 0.03997 RPN score loss: 0.01147 RPN total loss: 0.05144 Total loss: 1.09695 timestamp: 1655041426.3050935 iteration: 41805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11694 FastRCNN class loss: 0.06653 FastRCNN total loss: 0.18348 L1 loss: 0.0000e+00 L2 loss: 0.60097 Learning rate: 0.002 Mask loss: 0.13632 RPN box loss: 0.00646 RPN score loss: 0.00146 RPN total loss: 0.00792 Total loss: 0.92869 timestamp: 1655041429.5693386 iteration: 41810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13232 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.19338 L1 loss: 0.0000e+00 L2 loss: 0.60096 Learning rate: 0.002 Mask loss: 0.10294 RPN box loss: 0.00731 RPN score loss: 0.0029 RPN total loss: 0.01021 Total loss: 0.9075 timestamp: 1655041432.8092396 iteration: 41815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1371 FastRCNN class loss: 0.06507 FastRCNN total loss: 0.20217 L1 loss: 0.0000e+00 L2 loss: 0.60095 Learning rate: 0.002 Mask loss: 0.16055 RPN box loss: 0.03736 RPN score loss: 0.00706 RPN total loss: 0.04442 Total loss: 1.00809 timestamp: 1655041436.1871343 iteration: 41820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14675 FastRCNN class loss: 0.08394 FastRCNN total loss: 0.23069 L1 loss: 0.0000e+00 L2 loss: 0.60093 Learning rate: 0.002 Mask loss: 0.12349 RPN box loss: 0.0207 RPN score loss: 0.00686 RPN total loss: 0.02757 Total loss: 0.98268 timestamp: 1655041439.4604402 iteration: 41825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.151 FastRCNN class loss: 0.10888 FastRCNN total loss: 0.25988 L1 loss: 0.0000e+00 L2 loss: 0.60092 Learning rate: 0.002 Mask loss: 0.21665 RPN box loss: 0.02139 RPN score loss: 0.00725 RPN total loss: 0.02865 Total loss: 1.1061 timestamp: 1655041442.7151284 iteration: 41830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07802 FastRCNN class loss: 0.04141 FastRCNN total loss: 0.11942 L1 loss: 0.0000e+00 L2 loss: 0.60092 Learning rate: 0.002 Mask loss: 0.11755 RPN box loss: 0.03608 RPN score loss: 0.0041 RPN total loss: 0.04018 Total loss: 0.87807 timestamp: 1655041445.9582705 iteration: 41835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17683 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.25565 L1 loss: 0.0000e+00 L2 loss: 0.60091 Learning rate: 0.002 Mask loss: 0.11303 RPN box loss: 0.01064 RPN score loss: 0.00413 RPN total loss: 0.01477 Total loss: 0.98436 timestamp: 1655041449.278654 iteration: 41840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0985 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.15715 L1 loss: 0.0000e+00 L2 loss: 0.6009 Learning rate: 0.002 Mask loss: 0.09737 RPN box loss: 0.00899 RPN score loss: 0.00209 RPN total loss: 0.01107 Total loss: 0.86649 timestamp: 1655041452.5614283 iteration: 41845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05174 FastRCNN class loss: 0.07101 FastRCNN total loss: 0.12276 L1 loss: 0.0000e+00 L2 loss: 0.60089 Learning rate: 0.002 Mask loss: 0.09497 RPN box loss: 0.01219 RPN score loss: 0.00248 RPN total loss: 0.01467 Total loss: 0.83329 timestamp: 1655041455.834608 iteration: 41850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08453 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.15341 L1 loss: 0.0000e+00 L2 loss: 0.60088 Learning rate: 0.002 Mask loss: 0.11961 RPN box loss: 0.08103 RPN score loss: 0.00971 RPN total loss: 0.09074 Total loss: 0.96465 timestamp: 1655041459.1152883 iteration: 41855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10304 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.17489 L1 loss: 0.0000e+00 L2 loss: 0.60087 Learning rate: 0.002 Mask loss: 0.11707 RPN box loss: 0.01754 RPN score loss: 0.00301 RPN total loss: 0.02055 Total loss: 0.91337 timestamp: 1655041462.366217 iteration: 41860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.06389 FastRCNN total loss: 0.1778 L1 loss: 0.0000e+00 L2 loss: 0.60086 Learning rate: 0.002 Mask loss: 0.14313 RPN box loss: 0.01681 RPN score loss: 0.00387 RPN total loss: 0.02068 Total loss: 0.94247 timestamp: 1655041465.5894368 iteration: 41865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16881 FastRCNN class loss: 0.12885 FastRCNN total loss: 0.29766 L1 loss: 0.0000e+00 L2 loss: 0.60085 Learning rate: 0.002 Mask loss: 0.16637 RPN box loss: 0.04059 RPN score loss: 0.01159 RPN total loss: 0.05218 Total loss: 1.11706 timestamp: 1655041468.8617945 iteration: 41870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12752 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.20561 L1 loss: 0.0000e+00 L2 loss: 0.60084 Learning rate: 0.002 Mask loss: 0.19102 RPN box loss: 0.01532 RPN score loss: 0.00885 RPN total loss: 0.02418 Total loss: 1.02164 timestamp: 1655041472.2065668 iteration: 41875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08555 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.13578 L1 loss: 0.0000e+00 L2 loss: 0.60083 Learning rate: 0.002 Mask loss: 0.13813 RPN box loss: 0.0178 RPN score loss: 0.00207 RPN total loss: 0.01988 Total loss: 0.89461 timestamp: 1655041475.5134633 iteration: 41880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06872 FastRCNN class loss: 0.05605 FastRCNN total loss: 0.12477 L1 loss: 0.0000e+00 L2 loss: 0.60083 Learning rate: 0.002 Mask loss: 0.18457 RPN box loss: 0.01718 RPN score loss: 0.00308 RPN total loss: 0.02026 Total loss: 0.93043 timestamp: 1655041478.7973135 iteration: 41885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07991 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.14239 L1 loss: 0.0000e+00 L2 loss: 0.60082 Learning rate: 0.002 Mask loss: 0.22017 RPN box loss: 0.01831 RPN score loss: 0.00816 RPN total loss: 0.02648 Total loss: 0.98985 timestamp: 1655041482.142389 iteration: 41890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06423 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.12478 L1 loss: 0.0000e+00 L2 loss: 0.60081 Learning rate: 0.002 Mask loss: 0.13262 RPN box loss: 0.02311 RPN score loss: 0.00348 RPN total loss: 0.02659 Total loss: 0.88479 timestamp: 1655041485.4436705 iteration: 41895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11785 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.20151 L1 loss: 0.0000e+00 L2 loss: 0.6008 Learning rate: 0.002 Mask loss: 0.18172 RPN box loss: 0.03171 RPN score loss: 0.00616 RPN total loss: 0.03788 Total loss: 1.0219 timestamp: 1655041488.749914 iteration: 41900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11164 FastRCNN class loss: 0.0493 FastRCNN total loss: 0.16093 L1 loss: 0.0000e+00 L2 loss: 0.60078 Learning rate: 0.002 Mask loss: 0.13618 RPN box loss: 0.01687 RPN score loss: 0.01928 RPN total loss: 0.03615 Total loss: 0.93405 timestamp: 1655041492.037196 iteration: 41905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09838 FastRCNN class loss: 0.05887 FastRCNN total loss: 0.15724 L1 loss: 0.0000e+00 L2 loss: 0.60078 Learning rate: 0.002 Mask loss: 0.13436 RPN box loss: 0.02691 RPN score loss: 0.00749 RPN total loss: 0.0344 Total loss: 0.92677 timestamp: 1655041495.329623 iteration: 41910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15609 FastRCNN class loss: 0.1138 FastRCNN total loss: 0.2699 L1 loss: 0.0000e+00 L2 loss: 0.60077 Learning rate: 0.002 Mask loss: 0.266 RPN box loss: 0.03111 RPN score loss: 0.01694 RPN total loss: 0.04804 Total loss: 1.18471 timestamp: 1655041498.5806546 iteration: 41915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.0515 FastRCNN total loss: 0.16653 L1 loss: 0.0000e+00 L2 loss: 0.60076 Learning rate: 0.002 Mask loss: 0.1098 RPN box loss: 0.09394 RPN score loss: 0.00249 RPN total loss: 0.09643 Total loss: 0.97353 timestamp: 1655041501.8704236 iteration: 41920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09209 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.15067 L1 loss: 0.0000e+00 L2 loss: 0.60075 Learning rate: 0.002 Mask loss: 0.11887 RPN box loss: 0.00614 RPN score loss: 0.00318 RPN total loss: 0.00932 Total loss: 0.87961 timestamp: 1655041505.192736 iteration: 41925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13381 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.19925 L1 loss: 0.0000e+00 L2 loss: 0.60074 Learning rate: 0.002 Mask loss: 0.1659 RPN box loss: 0.01999 RPN score loss: 0.0022 RPN total loss: 0.02218 Total loss: 0.98808 timestamp: 1655041508.433374 iteration: 41930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11506 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.19337 L1 loss: 0.0000e+00 L2 loss: 0.60073 Learning rate: 0.002 Mask loss: 0.14178 RPN box loss: 0.00683 RPN score loss: 0.00359 RPN total loss: 0.01042 Total loss: 0.9463 timestamp: 1655041511.7225106 iteration: 41935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13324 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.21241 L1 loss: 0.0000e+00 L2 loss: 0.60072 Learning rate: 0.002 Mask loss: 0.18767 RPN box loss: 0.04836 RPN score loss: 0.01722 RPN total loss: 0.06558 Total loss: 1.06638 timestamp: 1655041514.9973555 iteration: 41940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.14429 L1 loss: 0.0000e+00 L2 loss: 0.60071 Learning rate: 0.002 Mask loss: 0.14573 RPN box loss: 0.01181 RPN score loss: 0.00526 RPN total loss: 0.01706 Total loss: 0.90779 timestamp: 1655041518.226822 iteration: 41945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.06844 FastRCNN total loss: 0.16032 L1 loss: 0.0000e+00 L2 loss: 0.6007 Learning rate: 0.002 Mask loss: 0.10323 RPN box loss: 0.00544 RPN score loss: 0.00136 RPN total loss: 0.0068 Total loss: 0.87104 timestamp: 1655041521.5239499 iteration: 41950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.05326 FastRCNN total loss: 0.13392 L1 loss: 0.0000e+00 L2 loss: 0.60069 Learning rate: 0.002 Mask loss: 0.1585 RPN box loss: 0.03859 RPN score loss: 0.00643 RPN total loss: 0.04502 Total loss: 0.93813 timestamp: 1655041524.7575688 iteration: 41955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11664 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.1754 L1 loss: 0.0000e+00 L2 loss: 0.60068 Learning rate: 0.002 Mask loss: 0.13193 RPN box loss: 0.02458 RPN score loss: 0.00446 RPN total loss: 0.02904 Total loss: 0.93705 timestamp: 1655041528.0151424 iteration: 41960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06586 FastRCNN class loss: 0.04884 FastRCNN total loss: 0.1147 L1 loss: 0.0000e+00 L2 loss: 0.60068 Learning rate: 0.002 Mask loss: 0.11538 RPN box loss: 0.04419 RPN score loss: 0.00386 RPN total loss: 0.04805 Total loss: 0.8788 timestamp: 1655041531.2593272 iteration: 41965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12775 FastRCNN class loss: 0.09094 FastRCNN total loss: 0.21869 L1 loss: 0.0000e+00 L2 loss: 0.60067 Learning rate: 0.002 Mask loss: 0.15139 RPN box loss: 0.0333 RPN score loss: 0.00621 RPN total loss: 0.03952 Total loss: 1.01027 timestamp: 1655041534.604392 iteration: 41970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10171 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.17527 L1 loss: 0.0000e+00 L2 loss: 0.60066 Learning rate: 0.002 Mask loss: 0.1292 RPN box loss: 0.01278 RPN score loss: 0.00551 RPN total loss: 0.01829 Total loss: 0.92342 timestamp: 1655041537.9466956 iteration: 41975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10671 FastRCNN class loss: 0.12142 FastRCNN total loss: 0.22813 L1 loss: 0.0000e+00 L2 loss: 0.60064 Learning rate: 0.002 Mask loss: 0.19819 RPN box loss: 0.02244 RPN score loss: 0.02219 RPN total loss: 0.04463 Total loss: 1.07159 timestamp: 1655041541.1826193 iteration: 41980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08464 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.16055 L1 loss: 0.0000e+00 L2 loss: 0.60064 Learning rate: 0.002 Mask loss: 0.13553 RPN box loss: 0.02884 RPN score loss: 0.00899 RPN total loss: 0.03783 Total loss: 0.93455 timestamp: 1655041544.503301 iteration: 41985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13177 FastRCNN class loss: 0.09767 FastRCNN total loss: 0.22943 L1 loss: 0.0000e+00 L2 loss: 0.60063 Learning rate: 0.002 Mask loss: 0.16057 RPN box loss: 0.01616 RPN score loss: 0.0091 RPN total loss: 0.02526 Total loss: 1.01589 timestamp: 1655041547.806262 iteration: 41990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12437 FastRCNN class loss: 0.08311 FastRCNN total loss: 0.20748 L1 loss: 0.0000e+00 L2 loss: 0.60062 Learning rate: 0.002 Mask loss: 0.26143 RPN box loss: 0.02835 RPN score loss: 0.00393 RPN total loss: 0.03228 Total loss: 1.10181 timestamp: 1655041551.0728965 iteration: 41995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10506 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.16239 L1 loss: 0.0000e+00 L2 loss: 0.60061 Learning rate: 0.002 Mask loss: 0.13262 RPN box loss: 0.04296 RPN score loss: 0.00657 RPN total loss: 0.04953 Total loss: 0.94514 timestamp: 1655041554.3489556 iteration: 42000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1267 FastRCNN class loss: 0.09155 FastRCNN total loss: 0.21824 L1 loss: 0.0000e+00 L2 loss: 0.6006 Learning rate: 0.002 Mask loss: 0.13887 RPN box loss: 0.02013 RPN score loss: 0.00389 RPN total loss: 0.02401 Total loss: 0.98172 timestamp: 1655041557.6998718 iteration: 42005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.04854 FastRCNN total loss: 0.11973 L1 loss: 0.0000e+00 L2 loss: 0.60059 Learning rate: 0.002 Mask loss: 0.17874 RPN box loss: 0.00323 RPN score loss: 0.00225 RPN total loss: 0.00548 Total loss: 0.90454 timestamp: 1655041560.9630728 iteration: 42010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10769 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.17647 L1 loss: 0.0000e+00 L2 loss: 0.60058 Learning rate: 0.002 Mask loss: 0.23581 RPN box loss: 0.0113 RPN score loss: 0.00379 RPN total loss: 0.0151 Total loss: 1.02796 timestamp: 1655041564.2578604 iteration: 42015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12802 FastRCNN class loss: 0.07863 FastRCNN total loss: 0.20665 L1 loss: 0.0000e+00 L2 loss: 0.60057 Learning rate: 0.002 Mask loss: 0.15309 RPN box loss: 0.04179 RPN score loss: 0.01183 RPN total loss: 0.05362 Total loss: 1.01393 timestamp: 1655041567.4320788 iteration: 42020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14054 FastRCNN class loss: 0.11079 FastRCNN total loss: 0.25133 L1 loss: 0.0000e+00 L2 loss: 0.60057 Learning rate: 0.002 Mask loss: 0.16931 RPN box loss: 0.0485 RPN score loss: 0.0097 RPN total loss: 0.0582 Total loss: 1.07941 timestamp: 1655041570.7057507 iteration: 42025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11858 FastRCNN class loss: 0.11664 FastRCNN total loss: 0.23521 L1 loss: 0.0000e+00 L2 loss: 0.60056 Learning rate: 0.002 Mask loss: 0.1527 RPN box loss: 0.05172 RPN score loss: 0.00495 RPN total loss: 0.05667 Total loss: 1.04515 timestamp: 1655041574.0212405 iteration: 42030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13231 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.22855 L1 loss: 0.0000e+00 L2 loss: 0.60055 Learning rate: 0.002 Mask loss: 0.1697 RPN box loss: 0.02338 RPN score loss: 0.00329 RPN total loss: 0.02667 Total loss: 1.02547 timestamp: 1655041577.3398793 iteration: 42035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.04609 FastRCNN total loss: 0.12206 L1 loss: 0.0000e+00 L2 loss: 0.60054 Learning rate: 0.002 Mask loss: 0.10498 RPN box loss: 0.02723 RPN score loss: 0.00438 RPN total loss: 0.03161 Total loss: 0.85919 timestamp: 1655041580.636015 iteration: 42040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.1372 L1 loss: 0.0000e+00 L2 loss: 0.60053 Learning rate: 0.002 Mask loss: 0.09563 RPN box loss: 0.03359 RPN score loss: 0.00276 RPN total loss: 0.03635 Total loss: 0.8697 timestamp: 1655041583.9517684 iteration: 42045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.23976 L1 loss: 0.0000e+00 L2 loss: 0.60052 Learning rate: 0.002 Mask loss: 0.16227 RPN box loss: 0.05969 RPN score loss: 0.00986 RPN total loss: 0.06955 Total loss: 1.07209 timestamp: 1655041587.255279 iteration: 42050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.04016 FastRCNN total loss: 0.15519 L1 loss: 0.0000e+00 L2 loss: 0.60051 Learning rate: 0.002 Mask loss: 0.16081 RPN box loss: 0.02129 RPN score loss: 0.00707 RPN total loss: 0.02836 Total loss: 0.94487 timestamp: 1655041590.5495453 iteration: 42055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12049 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.20983 L1 loss: 0.0000e+00 L2 loss: 0.6005 Learning rate: 0.002 Mask loss: 0.14627 RPN box loss: 0.01837 RPN score loss: 0.00765 RPN total loss: 0.02603 Total loss: 0.98262 timestamp: 1655041593.85354 iteration: 42060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17392 FastRCNN class loss: 0.08465 FastRCNN total loss: 0.25857 L1 loss: 0.0000e+00 L2 loss: 0.60049 Learning rate: 0.002 Mask loss: 0.12495 RPN box loss: 0.01558 RPN score loss: 0.00643 RPN total loss: 0.02201 Total loss: 1.00602 timestamp: 1655041597.168656 iteration: 42065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1117 FastRCNN class loss: 0.08796 FastRCNN total loss: 0.19966 L1 loss: 0.0000e+00 L2 loss: 0.60049 Learning rate: 0.002 Mask loss: 0.1626 RPN box loss: 0.02664 RPN score loss: 0.00783 RPN total loss: 0.03447 Total loss: 0.99722 timestamp: 1655041600.4499168 iteration: 42070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15101 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.21013 L1 loss: 0.0000e+00 L2 loss: 0.60048 Learning rate: 0.002 Mask loss: 0.12183 RPN box loss: 0.01049 RPN score loss: 0.00283 RPN total loss: 0.01332 Total loss: 0.94575 timestamp: 1655041603.709869 iteration: 42075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09244 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.14057 L1 loss: 0.0000e+00 L2 loss: 0.60046 Learning rate: 0.002 Mask loss: 0.1629 RPN box loss: 0.01529 RPN score loss: 0.01357 RPN total loss: 0.02887 Total loss: 0.93281 timestamp: 1655041606.9888732 iteration: 42080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05819 FastRCNN class loss: 0.03124 FastRCNN total loss: 0.08942 L1 loss: 0.0000e+00 L2 loss: 0.60045 Learning rate: 0.002 Mask loss: 0.08723 RPN box loss: 0.0191 RPN score loss: 0.00229 RPN total loss: 0.02139 Total loss: 0.79849 timestamp: 1655041610.2376409 iteration: 42085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10759 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.18117 L1 loss: 0.0000e+00 L2 loss: 0.60044 Learning rate: 0.002 Mask loss: 0.16599 RPN box loss: 0.02205 RPN score loss: 0.00287 RPN total loss: 0.02493 Total loss: 0.97253 timestamp: 1655041613.6061244 iteration: 42090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10417 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.18854 L1 loss: 0.0000e+00 L2 loss: 0.60043 Learning rate: 0.002 Mask loss: 0.16537 RPN box loss: 0.04291 RPN score loss: 0.01011 RPN total loss: 0.05302 Total loss: 1.00736 timestamp: 1655041616.8558688 iteration: 42095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.13753 L1 loss: 0.0000e+00 L2 loss: 0.60042 Learning rate: 0.002 Mask loss: 0.18457 RPN box loss: 0.00855 RPN score loss: 0.00216 RPN total loss: 0.01071 Total loss: 0.93322 timestamp: 1655041620.190692 iteration: 42100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13904 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.22064 L1 loss: 0.0000e+00 L2 loss: 0.60041 Learning rate: 0.002 Mask loss: 0.14411 RPN box loss: 0.03749 RPN score loss: 0.00827 RPN total loss: 0.04576 Total loss: 1.01092 timestamp: 1655041623.422599 iteration: 42105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.20155 L1 loss: 0.0000e+00 L2 loss: 0.6004 Learning rate: 0.002 Mask loss: 0.18424 RPN box loss: 0.03594 RPN score loss: 0.00643 RPN total loss: 0.04237 Total loss: 1.02857 timestamp: 1655041626.6905942 iteration: 42110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15565 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.23004 L1 loss: 0.0000e+00 L2 loss: 0.60039 Learning rate: 0.002 Mask loss: 0.1128 RPN box loss: 0.04253 RPN score loss: 0.00808 RPN total loss: 0.05061 Total loss: 0.99384 timestamp: 1655041629.93569 iteration: 42115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20154 FastRCNN class loss: 0.11003 FastRCNN total loss: 0.31157 L1 loss: 0.0000e+00 L2 loss: 0.60038 Learning rate: 0.002 Mask loss: 0.15598 RPN box loss: 0.02002 RPN score loss: 0.00519 RPN total loss: 0.02521 Total loss: 1.09315 timestamp: 1655041633.1791666 iteration: 42120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12877 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.20668 L1 loss: 0.0000e+00 L2 loss: 0.60037 Learning rate: 0.002 Mask loss: 0.14598 RPN box loss: 0.015 RPN score loss: 0.00701 RPN total loss: 0.02201 Total loss: 0.97505 timestamp: 1655041636.486799 iteration: 42125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.60036 Learning rate: 0.002 Mask loss: 0.1349 RPN box loss: 0.02865 RPN score loss: 0.00684 RPN total loss: 0.0355 Total loss: 0.94265 timestamp: 1655041639.7693033 iteration: 42130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0582 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.10703 L1 loss: 0.0000e+00 L2 loss: 0.60035 Learning rate: 0.002 Mask loss: 0.08691 RPN box loss: 0.01299 RPN score loss: 0.00481 RPN total loss: 0.0178 Total loss: 0.8121 timestamp: 1655041643.0354865 iteration: 42135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09114 FastRCNN class loss: 0.05072 FastRCNN total loss: 0.14186 L1 loss: 0.0000e+00 L2 loss: 0.60035 Learning rate: 0.002 Mask loss: 0.12599 RPN box loss: 0.01231 RPN score loss: 0.00457 RPN total loss: 0.01688 Total loss: 0.88508 timestamp: 1655041646.259499 iteration: 42140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1237 FastRCNN class loss: 0.10405 FastRCNN total loss: 0.22775 L1 loss: 0.0000e+00 L2 loss: 0.60034 Learning rate: 0.002 Mask loss: 0.13027 RPN box loss: 0.02713 RPN score loss: 0.00494 RPN total loss: 0.03207 Total loss: 0.99042 timestamp: 1655041649.5479388 iteration: 42145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17641 FastRCNN class loss: 0.11448 FastRCNN total loss: 0.29089 L1 loss: 0.0000e+00 L2 loss: 0.60033 Learning rate: 0.002 Mask loss: 0.21423 RPN box loss: 0.02795 RPN score loss: 0.00966 RPN total loss: 0.0376 Total loss: 1.14305 timestamp: 1655041652.772647 iteration: 42150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13871 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.2385 L1 loss: 0.0000e+00 L2 loss: 0.60032 Learning rate: 0.002 Mask loss: 0.13894 RPN box loss: 0.0311 RPN score loss: 0.00939 RPN total loss: 0.04049 Total loss: 1.01824 timestamp: 1655041656.040944 iteration: 42155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11932 FastRCNN class loss: 0.07957 FastRCNN total loss: 0.19889 L1 loss: 0.0000e+00 L2 loss: 0.60031 Learning rate: 0.002 Mask loss: 0.18292 RPN box loss: 0.03362 RPN score loss: 0.00536 RPN total loss: 0.03898 Total loss: 1.0211 timestamp: 1655041659.3024445 iteration: 42160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07827 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.15228 L1 loss: 0.0000e+00 L2 loss: 0.6003 Learning rate: 0.002 Mask loss: 0.0902 RPN box loss: 0.03512 RPN score loss: 0.0104 RPN total loss: 0.04552 Total loss: 0.88831 timestamp: 1655041662.6241546 iteration: 42165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13622 FastRCNN class loss: 0.06317 FastRCNN total loss: 0.19939 L1 loss: 0.0000e+00 L2 loss: 0.60029 Learning rate: 0.002 Mask loss: 0.17454 RPN box loss: 0.00511 RPN score loss: 0.00853 RPN total loss: 0.01364 Total loss: 0.98786 timestamp: 1655041665.8817961 iteration: 42170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13073 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.202 L1 loss: 0.0000e+00 L2 loss: 0.60029 Learning rate: 0.002 Mask loss: 0.13598 RPN box loss: 0.05595 RPN score loss: 0.00843 RPN total loss: 0.06438 Total loss: 1.00264 timestamp: 1655041669.1077225 iteration: 42175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06181 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.12401 L1 loss: 0.0000e+00 L2 loss: 0.60028 Learning rate: 0.002 Mask loss: 0.148 RPN box loss: 0.03093 RPN score loss: 0.00751 RPN total loss: 0.03844 Total loss: 0.91073 timestamp: 1655041672.4041271 iteration: 42180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15314 FastRCNN class loss: 0.14345 FastRCNN total loss: 0.29658 L1 loss: 0.0000e+00 L2 loss: 0.60027 Learning rate: 0.002 Mask loss: 0.12025 RPN box loss: 0.01729 RPN score loss: 0.00577 RPN total loss: 0.02307 Total loss: 1.04018 timestamp: 1655041675.7596636 iteration: 42185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09301 FastRCNN class loss: 0.04394 FastRCNN total loss: 0.13695 L1 loss: 0.0000e+00 L2 loss: 0.60026 Learning rate: 0.002 Mask loss: 0.12236 RPN box loss: 0.01381 RPN score loss: 0.00602 RPN total loss: 0.01983 Total loss: 0.8794 timestamp: 1655041678.9603484 iteration: 42190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13898 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.20642 L1 loss: 0.0000e+00 L2 loss: 0.60025 Learning rate: 0.002 Mask loss: 0.1479 RPN box loss: 0.02267 RPN score loss: 0.00912 RPN total loss: 0.0318 Total loss: 0.98636 timestamp: 1655041682.2857506 iteration: 42195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11936 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.18043 L1 loss: 0.0000e+00 L2 loss: 0.60024 Learning rate: 0.002 Mask loss: 0.2508 RPN box loss: 0.02488 RPN score loss: 0.00451 RPN total loss: 0.02939 Total loss: 1.06086 timestamp: 1655041685.5814157 iteration: 42200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06288 FastRCNN class loss: 0.07836 FastRCNN total loss: 0.14124 L1 loss: 0.0000e+00 L2 loss: 0.60024 Learning rate: 0.002 Mask loss: 0.11192 RPN box loss: 0.00895 RPN score loss: 0.00166 RPN total loss: 0.0106 Total loss: 0.864 timestamp: 1655041688.86261 iteration: 42205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.03855 FastRCNN total loss: 0.12016 L1 loss: 0.0000e+00 L2 loss: 0.60023 Learning rate: 0.002 Mask loss: 0.14454 RPN box loss: 0.02022 RPN score loss: 0.00234 RPN total loss: 0.02256 Total loss: 0.88749 timestamp: 1655041692.102139 iteration: 42210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.135 FastRCNN class loss: 0.11626 FastRCNN total loss: 0.25126 L1 loss: 0.0000e+00 L2 loss: 0.60022 Learning rate: 0.002 Mask loss: 0.22593 RPN box loss: 0.03318 RPN score loss: 0.0193 RPN total loss: 0.05248 Total loss: 1.12989 timestamp: 1655041695.3821423 iteration: 42215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12037 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.21654 L1 loss: 0.0000e+00 L2 loss: 0.60021 Learning rate: 0.002 Mask loss: 0.18348 RPN box loss: 0.01243 RPN score loss: 0.00637 RPN total loss: 0.0188 Total loss: 1.01903 timestamp: 1655041698.6283681 iteration: 42220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11766 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.16382 L1 loss: 0.0000e+00 L2 loss: 0.6002 Learning rate: 0.002 Mask loss: 0.09596 RPN box loss: 0.01464 RPN score loss: 0.00673 RPN total loss: 0.02137 Total loss: 0.88135 timestamp: 1655041701.9884512 iteration: 42225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14786 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.23078 L1 loss: 0.0000e+00 L2 loss: 0.60018 Learning rate: 0.002 Mask loss: 0.13116 RPN box loss: 0.03614 RPN score loss: 0.01272 RPN total loss: 0.04886 Total loss: 1.01098 timestamp: 1655041705.2666297 iteration: 42230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15375 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.22137 L1 loss: 0.0000e+00 L2 loss: 0.60017 Learning rate: 0.002 Mask loss: 0.14189 RPN box loss: 0.02741 RPN score loss: 0.00699 RPN total loss: 0.0344 Total loss: 0.99784 timestamp: 1655041708.5418406 iteration: 42235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09829 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.60016 Learning rate: 0.002 Mask loss: 0.10275 RPN box loss: 0.03051 RPN score loss: 0.00846 RPN total loss: 0.03897 Total loss: 0.9252 timestamp: 1655041711.7590814 iteration: 42240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.10083 FastRCNN total loss: 0.2154 L1 loss: 0.0000e+00 L2 loss: 0.60015 Learning rate: 0.002 Mask loss: 0.20068 RPN box loss: 0.0163 RPN score loss: 0.00511 RPN total loss: 0.02142 Total loss: 1.03765 timestamp: 1655041715.0057423 iteration: 42245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07118 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.13417 L1 loss: 0.0000e+00 L2 loss: 0.60014 Learning rate: 0.002 Mask loss: 0.14716 RPN box loss: 0.01231 RPN score loss: 0.00212 RPN total loss: 0.01442 Total loss: 0.89591 timestamp: 1655041718.2958035 iteration: 42250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14171 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.22303 L1 loss: 0.0000e+00 L2 loss: 0.60013 Learning rate: 0.002 Mask loss: 0.1131 RPN box loss: 0.05845 RPN score loss: 0.00711 RPN total loss: 0.06556 Total loss: 1.00182 timestamp: 1655041721.5045488 iteration: 42255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0825 FastRCNN class loss: 0.04721 FastRCNN total loss: 0.12971 L1 loss: 0.0000e+00 L2 loss: 0.60012 Learning rate: 0.002 Mask loss: 0.11619 RPN box loss: 0.00777 RPN score loss: 0.0055 RPN total loss: 0.01328 Total loss: 0.8593 timestamp: 1655041724.7826824 iteration: 42260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14043 FastRCNN class loss: 0.10968 FastRCNN total loss: 0.25011 L1 loss: 0.0000e+00 L2 loss: 0.60011 Learning rate: 0.002 Mask loss: 0.21929 RPN box loss: 0.02694 RPN score loss: 0.0081 RPN total loss: 0.03504 Total loss: 1.10455 timestamp: 1655041728.002634 iteration: 42265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13407 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.22376 L1 loss: 0.0000e+00 L2 loss: 0.6001 Learning rate: 0.002 Mask loss: 0.12301 RPN box loss: 0.05975 RPN score loss: 0.00932 RPN total loss: 0.06908 Total loss: 1.01595 timestamp: 1655041731.3216074 iteration: 42270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10212 FastRCNN class loss: 0.0524 FastRCNN total loss: 0.15452 L1 loss: 0.0000e+00 L2 loss: 0.60009 Learning rate: 0.002 Mask loss: 0.12007 RPN box loss: 0.03073 RPN score loss: 0.00379 RPN total loss: 0.03452 Total loss: 0.9092 timestamp: 1655041734.5282292 iteration: 42275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07874 FastRCNN class loss: 0.06391 FastRCNN total loss: 0.14265 L1 loss: 0.0000e+00 L2 loss: 0.60008 Learning rate: 0.002 Mask loss: 0.11717 RPN box loss: 0.03198 RPN score loss: 0.00893 RPN total loss: 0.04091 Total loss: 0.90081 timestamp: 1655041737.7203796 iteration: 42280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1015 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.16072 L1 loss: 0.0000e+00 L2 loss: 0.60008 Learning rate: 0.002 Mask loss: 0.12451 RPN box loss: 0.01469 RPN score loss: 0.00188 RPN total loss: 0.01657 Total loss: 0.90187 timestamp: 1655041740.9812477 iteration: 42285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11444 FastRCNN class loss: 0.10713 FastRCNN total loss: 0.22157 L1 loss: 0.0000e+00 L2 loss: 0.60007 Learning rate: 0.002 Mask loss: 0.1695 RPN box loss: 0.01245 RPN score loss: 0.00853 RPN total loss: 0.02098 Total loss: 1.01212 timestamp: 1655041744.251874 iteration: 42290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12888 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.18528 L1 loss: 0.0000e+00 L2 loss: 0.60006 Learning rate: 0.002 Mask loss: 0.11534 RPN box loss: 0.00568 RPN score loss: 0.00468 RPN total loss: 0.01037 Total loss: 0.91105 timestamp: 1655041747.4531262 iteration: 42295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17385 FastRCNN class loss: 0.07975 FastRCNN total loss: 0.2536 L1 loss: 0.0000e+00 L2 loss: 0.60005 Learning rate: 0.002 Mask loss: 0.18759 RPN box loss: 0.01419 RPN score loss: 0.00672 RPN total loss: 0.02091 Total loss: 1.06214 timestamp: 1655041750.7176585 iteration: 42300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13776 FastRCNN class loss: 0.07235 FastRCNN total loss: 0.21012 L1 loss: 0.0000e+00 L2 loss: 0.60004 Learning rate: 0.002 Mask loss: 0.11677 RPN box loss: 0.00773 RPN score loss: 0.00753 RPN total loss: 0.01526 Total loss: 0.94219 timestamp: 1655041753.9933875 iteration: 42305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12091 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.19683 L1 loss: 0.0000e+00 L2 loss: 0.60003 Learning rate: 0.002 Mask loss: 0.16728 RPN box loss: 0.01431 RPN score loss: 0.00511 RPN total loss: 0.01942 Total loss: 0.98356 timestamp: 1655041757.3206322 iteration: 42310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04326 FastRCNN class loss: 0.05116 FastRCNN total loss: 0.09442 L1 loss: 0.0000e+00 L2 loss: 0.60002 Learning rate: 0.002 Mask loss: 0.10261 RPN box loss: 0.02408 RPN score loss: 0.00214 RPN total loss: 0.02621 Total loss: 0.82326 timestamp: 1655041760.6159887 iteration: 42315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.08098 FastRCNN total loss: 0.16415 L1 loss: 0.0000e+00 L2 loss: 0.60001 Learning rate: 0.002 Mask loss: 0.11257 RPN box loss: 0.01985 RPN score loss: 0.00837 RPN total loss: 0.02822 Total loss: 0.90494 timestamp: 1655041763.9322066 iteration: 42320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13917 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.22745 L1 loss: 0.0000e+00 L2 loss: 0.6 Learning rate: 0.002 Mask loss: 0.16098 RPN box loss: 0.02685 RPN score loss: 0.01666 RPN total loss: 0.04352 Total loss: 1.03195 timestamp: 1655041767.2881947 iteration: 42325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.06325 FastRCNN total loss: 0.17717 L1 loss: 0.0000e+00 L2 loss: 0.59999 Learning rate: 0.002 Mask loss: 0.12821 RPN box loss: 0.0122 RPN score loss: 0.00468 RPN total loss: 0.01688 Total loss: 0.92226 timestamp: 1655041770.5745525 iteration: 42330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10557 FastRCNN class loss: 0.08133 FastRCNN total loss: 0.18691 L1 loss: 0.0000e+00 L2 loss: 0.59998 Learning rate: 0.002 Mask loss: 0.16469 RPN box loss: 0.04132 RPN score loss: 0.01115 RPN total loss: 0.05247 Total loss: 1.00404 timestamp: 1655041773.871135 iteration: 42335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09384 FastRCNN class loss: 0.04998 FastRCNN total loss: 0.14382 L1 loss: 0.0000e+00 L2 loss: 0.59996 Learning rate: 0.002 Mask loss: 0.11517 RPN box loss: 0.02112 RPN score loss: 0.00529 RPN total loss: 0.02641 Total loss: 0.88536 timestamp: 1655041777.1535835 iteration: 42340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08872 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.16579 L1 loss: 0.0000e+00 L2 loss: 0.59996 Learning rate: 0.002 Mask loss: 0.09728 RPN box loss: 0.0088 RPN score loss: 0.00763 RPN total loss: 0.01642 Total loss: 0.87946 timestamp: 1655041780.3910766 iteration: 42345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11908 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.17552 L1 loss: 0.0000e+00 L2 loss: 0.59995 Learning rate: 0.002 Mask loss: 0.15406 RPN box loss: 0.0435 RPN score loss: 0.01024 RPN total loss: 0.05374 Total loss: 0.98327 timestamp: 1655041783.6245022 iteration: 42350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15162 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.23835 L1 loss: 0.0000e+00 L2 loss: 0.59994 Learning rate: 0.002 Mask loss: 0.13042 RPN box loss: 0.01547 RPN score loss: 0.01037 RPN total loss: 0.02584 Total loss: 0.99455 timestamp: 1655041786.9637783 iteration: 42355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18798 FastRCNN class loss: 0.10455 FastRCNN total loss: 0.29253 L1 loss: 0.0000e+00 L2 loss: 0.59994 Learning rate: 0.002 Mask loss: 0.15449 RPN box loss: 0.03002 RPN score loss: 0.00824 RPN total loss: 0.03826 Total loss: 1.08521 timestamp: 1655041790.2427115 iteration: 42360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0482 FastRCNN class loss: 0.03899 FastRCNN total loss: 0.08719 L1 loss: 0.0000e+00 L2 loss: 0.59993 Learning rate: 0.002 Mask loss: 0.33181 RPN box loss: 0.04639 RPN score loss: 0.00396 RPN total loss: 0.05036 Total loss: 1.06929 timestamp: 1655041793.5323157 iteration: 42365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07074 FastRCNN class loss: 0.06074 FastRCNN total loss: 0.13148 L1 loss: 0.0000e+00 L2 loss: 0.59992 Learning rate: 0.002 Mask loss: 0.10867 RPN box loss: 0.04245 RPN score loss: 0.00478 RPN total loss: 0.04723 Total loss: 0.8873 timestamp: 1655041796.756164 iteration: 42370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07494 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.13073 L1 loss: 0.0000e+00 L2 loss: 0.59991 Learning rate: 0.002 Mask loss: 0.13103 RPN box loss: 0.01188 RPN score loss: 0.00656 RPN total loss: 0.01845 Total loss: 0.88012 timestamp: 1655041800.0103488 iteration: 42375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0971 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.17023 L1 loss: 0.0000e+00 L2 loss: 0.5999 Learning rate: 0.002 Mask loss: 0.15774 RPN box loss: 0.04232 RPN score loss: 0.00364 RPN total loss: 0.04596 Total loss: 0.97383 timestamp: 1655041803.261284 iteration: 42380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07993 FastRCNN class loss: 0.07479 FastRCNN total loss: 0.15472 L1 loss: 0.0000e+00 L2 loss: 0.59989 Learning rate: 0.002 Mask loss: 0.11378 RPN box loss: 0.00913 RPN score loss: 0.00154 RPN total loss: 0.01066 Total loss: 0.87905 timestamp: 1655041806.5236976 iteration: 42385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08409 FastRCNN class loss: 0.08307 FastRCNN total loss: 0.16716 L1 loss: 0.0000e+00 L2 loss: 0.59988 Learning rate: 0.002 Mask loss: 0.11977 RPN box loss: 0.03663 RPN score loss: 0.00683 RPN total loss: 0.04346 Total loss: 0.93026 timestamp: 1655041809.8680096 iteration: 42390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10217 FastRCNN class loss: 0.05168 FastRCNN total loss: 0.15384 L1 loss: 0.0000e+00 L2 loss: 0.59987 Learning rate: 0.002 Mask loss: 0.13611 RPN box loss: 0.01203 RPN score loss: 0.00259 RPN total loss: 0.01462 Total loss: 0.90444 timestamp: 1655041813.130496 iteration: 42395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11822 FastRCNN class loss: 0.05282 FastRCNN total loss: 0.17104 L1 loss: 0.0000e+00 L2 loss: 0.59986 Learning rate: 0.002 Mask loss: 0.11435 RPN box loss: 0.03892 RPN score loss: 0.01028 RPN total loss: 0.0492 Total loss: 0.93445 timestamp: 1655041816.4339166 iteration: 42400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1174 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.19239 L1 loss: 0.0000e+00 L2 loss: 0.59985 Learning rate: 0.002 Mask loss: 0.12608 RPN box loss: 0.0374 RPN score loss: 0.00661 RPN total loss: 0.04401 Total loss: 0.96233 timestamp: 1655041819.7537637 iteration: 42405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15837 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.22167 L1 loss: 0.0000e+00 L2 loss: 0.59984 Learning rate: 0.002 Mask loss: 0.17152 RPN box loss: 0.01543 RPN score loss: 0.00384 RPN total loss: 0.01927 Total loss: 1.01231 timestamp: 1655041823.0809853 iteration: 42410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11236 FastRCNN class loss: 0.08977 FastRCNN total loss: 0.20213 L1 loss: 0.0000e+00 L2 loss: 0.59983 Learning rate: 0.002 Mask loss: 0.20099 RPN box loss: 0.03758 RPN score loss: 0.00353 RPN total loss: 0.0411 Total loss: 1.04406 timestamp: 1655041826.3507917 iteration: 42415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12309 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.18447 L1 loss: 0.0000e+00 L2 loss: 0.59982 Learning rate: 0.002 Mask loss: 0.12078 RPN box loss: 0.03039 RPN score loss: 0.00443 RPN total loss: 0.03482 Total loss: 0.9399 timestamp: 1655041829.6370897 iteration: 42420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09901 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.16343 L1 loss: 0.0000e+00 L2 loss: 0.59981 Learning rate: 0.002 Mask loss: 0.14346 RPN box loss: 0.02301 RPN score loss: 0.02317 RPN total loss: 0.04618 Total loss: 0.95288 timestamp: 1655041832.939293 iteration: 42425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.09081 FastRCNN total loss: 0.19791 L1 loss: 0.0000e+00 L2 loss: 0.5998 Learning rate: 0.002 Mask loss: 0.1793 RPN box loss: 0.06757 RPN score loss: 0.01076 RPN total loss: 0.07833 Total loss: 1.05534 timestamp: 1655041836.1941092 iteration: 42430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.16411 L1 loss: 0.0000e+00 L2 loss: 0.59979 Learning rate: 0.002 Mask loss: 0.13183 RPN box loss: 0.0182 RPN score loss: 0.00457 RPN total loss: 0.02277 Total loss: 0.9185 timestamp: 1655041839.5099578 iteration: 42435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11358 FastRCNN class loss: 0.05265 FastRCNN total loss: 0.16623 L1 loss: 0.0000e+00 L2 loss: 0.59978 Learning rate: 0.002 Mask loss: 0.10511 RPN box loss: 0.00864 RPN score loss: 0.00227 RPN total loss: 0.01091 Total loss: 0.88203 timestamp: 1655041842.7653332 iteration: 42440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.0662 FastRCNN total loss: 0.17701 L1 loss: 0.0000e+00 L2 loss: 0.59978 Learning rate: 0.002 Mask loss: 0.1975 RPN box loss: 0.06737 RPN score loss: 0.00585 RPN total loss: 0.07322 Total loss: 1.04751 timestamp: 1655041846.0462282 iteration: 42445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15331 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.22548 L1 loss: 0.0000e+00 L2 loss: 0.59977 Learning rate: 0.002 Mask loss: 0.18439 RPN box loss: 0.02971 RPN score loss: 0.00497 RPN total loss: 0.03469 Total loss: 1.04432 timestamp: 1655041849.3773406 iteration: 42450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08052 FastRCNN class loss: 0.08017 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 0.59976 Learning rate: 0.002 Mask loss: 0.1411 RPN box loss: 0.02508 RPN score loss: 0.01627 RPN total loss: 0.04135 Total loss: 0.9429 timestamp: 1655041852.6674185 iteration: 42455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.07094 FastRCNN total loss: 0.20451 L1 loss: 0.0000e+00 L2 loss: 0.59975 Learning rate: 0.002 Mask loss: 0.17978 RPN box loss: 0.02659 RPN score loss: 0.00644 RPN total loss: 0.03304 Total loss: 1.01707 timestamp: 1655041855.947168 iteration: 42460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13143 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.207 L1 loss: 0.0000e+00 L2 loss: 0.59974 Learning rate: 0.002 Mask loss: 0.21369 RPN box loss: 0.01821 RPN score loss: 0.00446 RPN total loss: 0.02267 Total loss: 1.0431 timestamp: 1655041859.1776805 iteration: 42465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.17445 L1 loss: 0.0000e+00 L2 loss: 0.59973 Learning rate: 0.002 Mask loss: 0.12077 RPN box loss: 0.00708 RPN score loss: 0.00768 RPN total loss: 0.01476 Total loss: 0.90971 timestamp: 1655041862.4398956 iteration: 42470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12864 FastRCNN class loss: 0.07232 FastRCNN total loss: 0.20096 L1 loss: 0.0000e+00 L2 loss: 0.59972 Learning rate: 0.002 Mask loss: 0.1531 RPN box loss: 0.02137 RPN score loss: 0.00282 RPN total loss: 0.02418 Total loss: 0.97796 timestamp: 1655041865.7487812 iteration: 42475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11698 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.18131 L1 loss: 0.0000e+00 L2 loss: 0.59971 Learning rate: 0.002 Mask loss: 0.16615 RPN box loss: 0.01547 RPN score loss: 0.00584 RPN total loss: 0.02131 Total loss: 0.96848 timestamp: 1655041869.0471792 iteration: 42480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09302 FastRCNN class loss: 0.10386 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.5997 Learning rate: 0.002 Mask loss: 0.16302 RPN box loss: 0.02656 RPN score loss: 0.00688 RPN total loss: 0.03344 Total loss: 0.99304 timestamp: 1655041872.3263497 iteration: 42485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10137 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.16632 L1 loss: 0.0000e+00 L2 loss: 0.59969 Learning rate: 0.002 Mask loss: 0.10786 RPN box loss: 0.03171 RPN score loss: 0.00396 RPN total loss: 0.03567 Total loss: 0.90954 timestamp: 1655041875.6008737 iteration: 42490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08905 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.14434 L1 loss: 0.0000e+00 L2 loss: 0.59969 Learning rate: 0.002 Mask loss: 0.08338 RPN box loss: 0.0129 RPN score loss: 0.0021 RPN total loss: 0.01501 Total loss: 0.84242 timestamp: 1655041878.8964698 iteration: 42495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10587 FastRCNN class loss: 0.06746 FastRCNN total loss: 0.17334 L1 loss: 0.0000e+00 L2 loss: 0.59968 Learning rate: 0.002 Mask loss: 0.09674 RPN box loss: 0.0179 RPN score loss: 0.00293 RPN total loss: 0.02084 Total loss: 0.89059 timestamp: 1655041882.2321553 iteration: 42500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12445 FastRCNN class loss: 0.08351 FastRCNN total loss: 0.20796 L1 loss: 0.0000e+00 L2 loss: 0.59967 Learning rate: 0.002 Mask loss: 0.08294 RPN box loss: 0.03433 RPN score loss: 0.00554 RPN total loss: 0.03987 Total loss: 0.93043 timestamp: 1655041885.555574 iteration: 42505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.0731 FastRCNN total loss: 0.19694 L1 loss: 0.0000e+00 L2 loss: 0.59966 Learning rate: 0.002 Mask loss: 0.13963 RPN box loss: 0.02666 RPN score loss: 0.00567 RPN total loss: 0.03233 Total loss: 0.96856 timestamp: 1655041888.893944 iteration: 42510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08726 FastRCNN class loss: 0.07674 FastRCNN total loss: 0.164 L1 loss: 0.0000e+00 L2 loss: 0.59965 Learning rate: 0.002 Mask loss: 0.13361 RPN box loss: 0.01548 RPN score loss: 0.00422 RPN total loss: 0.01969 Total loss: 0.91696 timestamp: 1655041892.1776729 iteration: 42515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19218 FastRCNN class loss: 0.11515 FastRCNN total loss: 0.30732 L1 loss: 0.0000e+00 L2 loss: 0.59964 Learning rate: 0.002 Mask loss: 0.21 RPN box loss: 0.05727 RPN score loss: 0.01219 RPN total loss: 0.06946 Total loss: 1.18642 timestamp: 1655041895.4557686 iteration: 42520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.093 FastRCNN class loss: 0.071 FastRCNN total loss: 0.164 L1 loss: 0.0000e+00 L2 loss: 0.59963 Learning rate: 0.002 Mask loss: 0.16472 RPN box loss: 0.02413 RPN score loss: 0.01496 RPN total loss: 0.03909 Total loss: 0.96745 timestamp: 1655041898.757699 iteration: 42525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07235 FastRCNN class loss: 0.06865 FastRCNN total loss: 0.141 L1 loss: 0.0000e+00 L2 loss: 0.59962 Learning rate: 0.002 Mask loss: 0.1601 RPN box loss: 0.02806 RPN score loss: 0.00196 RPN total loss: 0.03002 Total loss: 0.93075 timestamp: 1655041902.0402675 iteration: 42530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08597 FastRCNN class loss: 0.05278 FastRCNN total loss: 0.13875 L1 loss: 0.0000e+00 L2 loss: 0.59961 Learning rate: 0.002 Mask loss: 0.11825 RPN box loss: 0.01045 RPN score loss: 0.00515 RPN total loss: 0.01559 Total loss: 0.8722 timestamp: 1655041905.3004684 iteration: 42535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13073 FastRCNN class loss: 0.06683 FastRCNN total loss: 0.19755 L1 loss: 0.0000e+00 L2 loss: 0.59961 Learning rate: 0.002 Mask loss: 0.14078 RPN box loss: 0.0125 RPN score loss: 0.00499 RPN total loss: 0.0175 Total loss: 0.95543 timestamp: 1655041908.6185718 iteration: 42540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12708 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.21343 L1 loss: 0.0000e+00 L2 loss: 0.5996 Learning rate: 0.002 Mask loss: 0.19836 RPN box loss: 0.04295 RPN score loss: 0.00238 RPN total loss: 0.04533 Total loss: 1.05672 timestamp: 1655041911.871878 iteration: 42545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09428 FastRCNN class loss: 0.05503 FastRCNN total loss: 0.14931 L1 loss: 0.0000e+00 L2 loss: 0.59959 Learning rate: 0.002 Mask loss: 0.16939 RPN box loss: 0.03745 RPN score loss: 0.00698 RPN total loss: 0.04443 Total loss: 0.96271 timestamp: 1655041915.0894632 iteration: 42550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12986 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.21027 L1 loss: 0.0000e+00 L2 loss: 0.59958 Learning rate: 0.002 Mask loss: 0.15338 RPN box loss: 0.01135 RPN score loss: 0.00451 RPN total loss: 0.01585 Total loss: 0.97909 timestamp: 1655041918.3159962 iteration: 42555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12527 FastRCNN class loss: 0.07387 FastRCNN total loss: 0.19914 L1 loss: 0.0000e+00 L2 loss: 0.59957 Learning rate: 0.002 Mask loss: 0.24398 RPN box loss: 0.06391 RPN score loss: 0.00959 RPN total loss: 0.0735 Total loss: 1.1162 timestamp: 1655041921.493012 iteration: 42560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08339 FastRCNN class loss: 0.13215 FastRCNN total loss: 0.21555 L1 loss: 0.0000e+00 L2 loss: 0.59956 Learning rate: 0.002 Mask loss: 0.17081 RPN box loss: 0.04575 RPN score loss: 0.00643 RPN total loss: 0.05219 Total loss: 1.03811 timestamp: 1655041924.699442 iteration: 42565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11473 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.2043 L1 loss: 0.0000e+00 L2 loss: 0.59955 Learning rate: 0.002 Mask loss: 0.15345 RPN box loss: 0.03583 RPN score loss: 0.00651 RPN total loss: 0.04234 Total loss: 0.99964 timestamp: 1655041927.946901 iteration: 42570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09069 FastRCNN class loss: 0.05402 FastRCNN total loss: 0.14471 L1 loss: 0.0000e+00 L2 loss: 0.59954 Learning rate: 0.002 Mask loss: 0.10313 RPN box loss: 0.00695 RPN score loss: 0.00431 RPN total loss: 0.01126 Total loss: 0.85864 timestamp: 1655041931.2755759 iteration: 42575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10146 FastRCNN class loss: 0.09215 FastRCNN total loss: 0.19362 L1 loss: 0.0000e+00 L2 loss: 0.59953 Learning rate: 0.002 Mask loss: 0.14459 RPN box loss: 0.00806 RPN score loss: 0.006 RPN total loss: 0.01406 Total loss: 0.95179 timestamp: 1655041934.5280075 iteration: 42580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12359 FastRCNN class loss: 0.11533 FastRCNN total loss: 0.23893 L1 loss: 0.0000e+00 L2 loss: 0.59952 Learning rate: 0.002 Mask loss: 0.20128 RPN box loss: 0.05144 RPN score loss: 0.02015 RPN total loss: 0.07159 Total loss: 1.11131 timestamp: 1655041937.7431376 iteration: 42585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13168 FastRCNN class loss: 0.05824 FastRCNN total loss: 0.18992 L1 loss: 0.0000e+00 L2 loss: 0.5995 Learning rate: 0.002 Mask loss: 0.1792 RPN box loss: 0.02028 RPN score loss: 0.00513 RPN total loss: 0.02541 Total loss: 0.99404 timestamp: 1655041940.964665 iteration: 42590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17136 FastRCNN class loss: 0.04594 FastRCNN total loss: 0.2173 L1 loss: 0.0000e+00 L2 loss: 0.59949 Learning rate: 0.002 Mask loss: 0.10197 RPN box loss: 0.01541 RPN score loss: 0.00241 RPN total loss: 0.01782 Total loss: 0.93658 timestamp: 1655041944.1892903 iteration: 42595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16346 FastRCNN class loss: 0.10188 FastRCNN total loss: 0.26534 L1 loss: 0.0000e+00 L2 loss: 0.59948 Learning rate: 0.002 Mask loss: 0.14021 RPN box loss: 0.06126 RPN score loss: 0.01239 RPN total loss: 0.07365 Total loss: 1.07867 timestamp: 1655041947.4498045 iteration: 42600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.06246 FastRCNN total loss: 0.16514 L1 loss: 0.0000e+00 L2 loss: 0.59947 Learning rate: 0.002 Mask loss: 0.18706 RPN box loss: 0.0314 RPN score loss: 0.00234 RPN total loss: 0.03374 Total loss: 0.98541 timestamp: 1655041950.7452774 iteration: 42605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10298 FastRCNN class loss: 0.05139 FastRCNN total loss: 0.15437 L1 loss: 0.0000e+00 L2 loss: 0.59947 Learning rate: 0.002 Mask loss: 0.16307 RPN box loss: 0.00399 RPN score loss: 0.00348 RPN total loss: 0.00746 Total loss: 0.92437 timestamp: 1655041954.0203393 iteration: 42610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10671 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.17146 L1 loss: 0.0000e+00 L2 loss: 0.59946 Learning rate: 0.002 Mask loss: 0.09066 RPN box loss: 0.01045 RPN score loss: 0.00289 RPN total loss: 0.01334 Total loss: 0.87492 timestamp: 1655041957.251175 iteration: 42615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.17353 L1 loss: 0.0000e+00 L2 loss: 0.59945 Learning rate: 0.002 Mask loss: 0.17708 RPN box loss: 0.01479 RPN score loss: 0.01257 RPN total loss: 0.02736 Total loss: 0.97741 timestamp: 1655041960.5713935 iteration: 42620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1048 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.17131 L1 loss: 0.0000e+00 L2 loss: 0.59944 Learning rate: 0.002 Mask loss: 0.25045 RPN box loss: 0.02248 RPN score loss: 0.00463 RPN total loss: 0.02711 Total loss: 1.04832 timestamp: 1655041963.8496053 iteration: 42625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13246 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.21174 L1 loss: 0.0000e+00 L2 loss: 0.59943 Learning rate: 0.002 Mask loss: 0.12214 RPN box loss: 0.01366 RPN score loss: 0.00737 RPN total loss: 0.02103 Total loss: 0.95434 timestamp: 1655041967.1603696 iteration: 42630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07184 FastRCNN class loss: 0.07271 FastRCNN total loss: 0.14455 L1 loss: 0.0000e+00 L2 loss: 0.59942 Learning rate: 0.002 Mask loss: 0.12652 RPN box loss: 0.02149 RPN score loss: 0.00546 RPN total loss: 0.02696 Total loss: 0.89745 timestamp: 1655041970.437457 iteration: 42635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09193 FastRCNN class loss: 0.06045 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 0.59942 Learning rate: 0.002 Mask loss: 0.09339 RPN box loss: 0.00566 RPN score loss: 0.00572 RPN total loss: 0.01137 Total loss: 0.85657 timestamp: 1655041973.7105393 iteration: 42640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13288 FastRCNN class loss: 0.06797 FastRCNN total loss: 0.20085 L1 loss: 0.0000e+00 L2 loss: 0.59941 Learning rate: 0.002 Mask loss: 0.13999 RPN box loss: 0.03323 RPN score loss: 0.00259 RPN total loss: 0.03582 Total loss: 0.97607 timestamp: 1655041976.9510918 iteration: 42645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.03716 FastRCNN total loss: 0.11855 L1 loss: 0.0000e+00 L2 loss: 0.5994 Learning rate: 0.002 Mask loss: 0.09287 RPN box loss: 0.03199 RPN score loss: 0.01114 RPN total loss: 0.04313 Total loss: 0.85395 timestamp: 1655041980.1805782 iteration: 42650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0947 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.15044 L1 loss: 0.0000e+00 L2 loss: 0.59939 Learning rate: 0.002 Mask loss: 0.11337 RPN box loss: 0.00819 RPN score loss: 0.00359 RPN total loss: 0.01178 Total loss: 0.87497 timestamp: 1655041983.4931655 iteration: 42655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.17294 L1 loss: 0.0000e+00 L2 loss: 0.59938 Learning rate: 0.002 Mask loss: 0.16125 RPN box loss: 0.01391 RPN score loss: 0.00424 RPN total loss: 0.01814 Total loss: 0.95171 timestamp: 1655041986.7887135 iteration: 42660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12682 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.19904 L1 loss: 0.0000e+00 L2 loss: 0.59937 Learning rate: 0.002 Mask loss: 0.13442 RPN box loss: 0.01142 RPN score loss: 0.00302 RPN total loss: 0.01444 Total loss: 0.94727 timestamp: 1655041990.0488544 iteration: 42665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12288 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.19176 L1 loss: 0.0000e+00 L2 loss: 0.59936 Learning rate: 0.002 Mask loss: 0.12515 RPN box loss: 0.03319 RPN score loss: 0.00725 RPN total loss: 0.04043 Total loss: 0.95671 timestamp: 1655041993.3504934 iteration: 42670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.19803 L1 loss: 0.0000e+00 L2 loss: 0.59936 Learning rate: 0.002 Mask loss: 0.16615 RPN box loss: 0.04695 RPN score loss: 0.00416 RPN total loss: 0.05112 Total loss: 1.01465 timestamp: 1655041996.7502437 iteration: 42675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10528 FastRCNN class loss: 0.0681 FastRCNN total loss: 0.17339 L1 loss: 0.0000e+00 L2 loss: 0.59934 Learning rate: 0.002 Mask loss: 0.14916 RPN box loss: 0.00502 RPN score loss: 0.00157 RPN total loss: 0.00659 Total loss: 0.92848 timestamp: 1655042000.0725918 iteration: 42680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12882 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.19702 L1 loss: 0.0000e+00 L2 loss: 0.59933 Learning rate: 0.002 Mask loss: 0.18182 RPN box loss: 0.01544 RPN score loss: 0.00599 RPN total loss: 0.02143 Total loss: 0.9996 timestamp: 1655042003.3521214 iteration: 42685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0756 FastRCNN class loss: 0.08514 FastRCNN total loss: 0.16074 L1 loss: 0.0000e+00 L2 loss: 0.59933 Learning rate: 0.002 Mask loss: 0.15545 RPN box loss: 0.04939 RPN score loss: 0.00668 RPN total loss: 0.05607 Total loss: 0.97159 timestamp: 1655042006.557764 iteration: 42690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11332 FastRCNN class loss: 0.13148 FastRCNN total loss: 0.2448 L1 loss: 0.0000e+00 L2 loss: 0.59932 Learning rate: 0.002 Mask loss: 0.16281 RPN box loss: 0.04149 RPN score loss: 0.0146 RPN total loss: 0.0561 Total loss: 1.06303 timestamp: 1655042009.9019659 iteration: 42695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0415 FastRCNN class loss: 0.03394 FastRCNN total loss: 0.07543 L1 loss: 0.0000e+00 L2 loss: 0.59931 Learning rate: 0.002 Mask loss: 0.12608 RPN box loss: 0.02554 RPN score loss: 0.00184 RPN total loss: 0.02738 Total loss: 0.8282 timestamp: 1655042013.1842303 iteration: 42700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10043 FastRCNN class loss: 0.06842 FastRCNN total loss: 0.16886 L1 loss: 0.0000e+00 L2 loss: 0.5993 Learning rate: 0.002 Mask loss: 0.13721 RPN box loss: 0.03541 RPN score loss: 0.00505 RPN total loss: 0.04046 Total loss: 0.94582 timestamp: 1655042016.4130487 iteration: 42705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12411 FastRCNN class loss: 0.10313 FastRCNN total loss: 0.22724 L1 loss: 0.0000e+00 L2 loss: 0.59929 Learning rate: 0.002 Mask loss: 0.15659 RPN box loss: 0.03227 RPN score loss: 0.01135 RPN total loss: 0.04362 Total loss: 1.02675 timestamp: 1655042019.7213764 iteration: 42710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07062 FastRCNN class loss: 0.04807 FastRCNN total loss: 0.11869 L1 loss: 0.0000e+00 L2 loss: 0.59928 Learning rate: 0.002 Mask loss: 0.12862 RPN box loss: 0.02018 RPN score loss: 0.00672 RPN total loss: 0.0269 Total loss: 0.87349 timestamp: 1655042023.082617 iteration: 42715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12892 FastRCNN class loss: 0.10416 FastRCNN total loss: 0.23308 L1 loss: 0.0000e+00 L2 loss: 0.59927 Learning rate: 0.002 Mask loss: 0.10749 RPN box loss: 0.01364 RPN score loss: 0.00788 RPN total loss: 0.02153 Total loss: 0.96136 timestamp: 1655042026.385424 iteration: 42720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06476 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.1277 L1 loss: 0.0000e+00 L2 loss: 0.59926 Learning rate: 0.002 Mask loss: 0.13517 RPN box loss: 0.02762 RPN score loss: 0.01476 RPN total loss: 0.04238 Total loss: 0.90451 timestamp: 1655042029.6256034 iteration: 42725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06604 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.14024 L1 loss: 0.0000e+00 L2 loss: 0.59925 Learning rate: 0.002 Mask loss: 0.15548 RPN box loss: 0.03635 RPN score loss: 0.00765 RPN total loss: 0.044 Total loss: 0.93897 timestamp: 1655042032.868635 iteration: 42730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09069 FastRCNN class loss: 0.04833 FastRCNN total loss: 0.13901 L1 loss: 0.0000e+00 L2 loss: 0.59924 Learning rate: 0.002 Mask loss: 0.10323 RPN box loss: 0.03056 RPN score loss: 0.00661 RPN total loss: 0.03717 Total loss: 0.87866 timestamp: 1655042036.0733635 iteration: 42735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0795 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.13983 L1 loss: 0.0000e+00 L2 loss: 0.59923 Learning rate: 0.002 Mask loss: 0.13478 RPN box loss: 0.01488 RPN score loss: 0.00454 RPN total loss: 0.01942 Total loss: 0.89326 timestamp: 1655042039.3634503 iteration: 42740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12997 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.19387 L1 loss: 0.0000e+00 L2 loss: 0.59922 Learning rate: 0.002 Mask loss: 0.16145 RPN box loss: 0.0599 RPN score loss: 0.00299 RPN total loss: 0.06289 Total loss: 1.01744 timestamp: 1655042042.6338015 iteration: 42745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13051 FastRCNN class loss: 0.08191 FastRCNN total loss: 0.21242 L1 loss: 0.0000e+00 L2 loss: 0.59921 Learning rate: 0.002 Mask loss: 0.16825 RPN box loss: 0.09062 RPN score loss: 0.00944 RPN total loss: 0.10006 Total loss: 1.07995 timestamp: 1655042045.8452055 iteration: 42750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15957 FastRCNN class loss: 0.06721 FastRCNN total loss: 0.22678 L1 loss: 0.0000e+00 L2 loss: 0.5992 Learning rate: 0.002 Mask loss: 0.11156 RPN box loss: 0.0359 RPN score loss: 0.00173 RPN total loss: 0.03763 Total loss: 0.97517 timestamp: 1655042049.098173 iteration: 42755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19413 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.26446 L1 loss: 0.0000e+00 L2 loss: 0.59919 Learning rate: 0.002 Mask loss: 0.21611 RPN box loss: 0.02132 RPN score loss: 0.01475 RPN total loss: 0.03607 Total loss: 1.11584 timestamp: 1655042052.4565928 iteration: 42760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.09191 FastRCNN total loss: 0.20679 L1 loss: 0.0000e+00 L2 loss: 0.59918 Learning rate: 0.002 Mask loss: 0.14509 RPN box loss: 0.01548 RPN score loss: 0.0093 RPN total loss: 0.02478 Total loss: 0.97584 timestamp: 1655042055.66215 iteration: 42765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16932 FastRCNN class loss: 0.07591 FastRCNN total loss: 0.24523 L1 loss: 0.0000e+00 L2 loss: 0.59917 Learning rate: 0.002 Mask loss: 0.16875 RPN box loss: 0.01137 RPN score loss: 0.00339 RPN total loss: 0.01476 Total loss: 1.02791 timestamp: 1655042058.9160285 iteration: 42770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06461 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.13192 L1 loss: 0.0000e+00 L2 loss: 0.59917 Learning rate: 0.002 Mask loss: 0.12049 RPN box loss: 0.02804 RPN score loss: 0.00298 RPN total loss: 0.03102 Total loss: 0.88259 timestamp: 1655042062.2452168 iteration: 42775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11305 FastRCNN class loss: 0.11032 FastRCNN total loss: 0.22337 L1 loss: 0.0000e+00 L2 loss: 0.59916 Learning rate: 0.002 Mask loss: 0.15882 RPN box loss: 0.01593 RPN score loss: 0.00397 RPN total loss: 0.0199 Total loss: 1.00125 timestamp: 1655042065.4892244 iteration: 42780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11929 FastRCNN class loss: 0.0524 FastRCNN total loss: 0.17169 L1 loss: 0.0000e+00 L2 loss: 0.59915 Learning rate: 0.002 Mask loss: 0.10569 RPN box loss: 0.02268 RPN score loss: 0.00093 RPN total loss: 0.0236 Total loss: 0.90013 timestamp: 1655042068.8168488 iteration: 42785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10487 FastRCNN class loss: 0.06372 FastRCNN total loss: 0.16858 L1 loss: 0.0000e+00 L2 loss: 0.59914 Learning rate: 0.002 Mask loss: 0.12619 RPN box loss: 0.03427 RPN score loss: 0.00507 RPN total loss: 0.03934 Total loss: 0.93325 timestamp: 1655042072.1021428 iteration: 42790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05705 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.10679 L1 loss: 0.0000e+00 L2 loss: 0.59913 Learning rate: 0.002 Mask loss: 0.14267 RPN box loss: 0.0132 RPN score loss: 0.01007 RPN total loss: 0.02327 Total loss: 0.87186 timestamp: 1655042075.4403167 iteration: 42795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08076 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.12417 L1 loss: 0.0000e+00 L2 loss: 0.59912 Learning rate: 0.002 Mask loss: 0.1515 RPN box loss: 0.00855 RPN score loss: 0.00259 RPN total loss: 0.01113 Total loss: 0.88592 timestamp: 1655042078.6819012 iteration: 42800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.11735 FastRCNN total loss: 0.26905 L1 loss: 0.0000e+00 L2 loss: 0.59911 Learning rate: 0.002 Mask loss: 0.20051 RPN box loss: 0.01482 RPN score loss: 0.00476 RPN total loss: 0.01958 Total loss: 1.08824 timestamp: 1655042081.9796317 iteration: 42805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.15447 L1 loss: 0.0000e+00 L2 loss: 0.5991 Learning rate: 0.002 Mask loss: 0.09618 RPN box loss: 0.00393 RPN score loss: 0.00287 RPN total loss: 0.0068 Total loss: 0.85655 timestamp: 1655042085.2659264 iteration: 42810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11644 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.19526 L1 loss: 0.0000e+00 L2 loss: 0.59909 Learning rate: 0.002 Mask loss: 0.18408 RPN box loss: 0.07044 RPN score loss: 0.00416 RPN total loss: 0.0746 Total loss: 1.05303 timestamp: 1655042088.4061542 iteration: 42815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12789 FastRCNN class loss: 0.0553 FastRCNN total loss: 0.18319 L1 loss: 0.0000e+00 L2 loss: 0.59908 Learning rate: 0.002 Mask loss: 0.13291 RPN box loss: 0.01146 RPN score loss: 0.00638 RPN total loss: 0.01784 Total loss: 0.93302 timestamp: 1655042091.6663752 iteration: 42820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14601 FastRCNN class loss: 0.06703 FastRCNN total loss: 0.21303 L1 loss: 0.0000e+00 L2 loss: 0.59907 Learning rate: 0.002 Mask loss: 0.11252 RPN box loss: 0.01609 RPN score loss: 0.00255 RPN total loss: 0.01864 Total loss: 0.94327 timestamp: 1655042094.7760952 iteration: 42825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10019 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.16237 L1 loss: 0.0000e+00 L2 loss: 0.59906 Learning rate: 0.002 Mask loss: 0.14742 RPN box loss: 0.01812 RPN score loss: 0.00544 RPN total loss: 0.02356 Total loss: 0.93241 timestamp: 1655042098.0847893 iteration: 42830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07613 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.15373 L1 loss: 0.0000e+00 L2 loss: 0.59906 Learning rate: 0.002 Mask loss: 0.18193 RPN box loss: 0.028 RPN score loss: 0.0038 RPN total loss: 0.0318 Total loss: 0.96651 timestamp: 1655042101.369277 iteration: 42835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09709 FastRCNN class loss: 0.09289 FastRCNN total loss: 0.18997 L1 loss: 0.0000e+00 L2 loss: 0.59905 Learning rate: 0.002 Mask loss: 0.1171 RPN box loss: 0.0226 RPN score loss: 0.00562 RPN total loss: 0.02823 Total loss: 0.93434 timestamp: 1655042104.6228197 iteration: 42840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21039 FastRCNN class loss: 0.11722 FastRCNN total loss: 0.32761 L1 loss: 0.0000e+00 L2 loss: 0.59903 Learning rate: 0.002 Mask loss: 0.20397 RPN box loss: 0.02422 RPN score loss: 0.01719 RPN total loss: 0.04141 Total loss: 1.17203 timestamp: 1655042107.8718808 iteration: 42845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05129 FastRCNN class loss: 0.05328 FastRCNN total loss: 0.10456 L1 loss: 0.0000e+00 L2 loss: 0.59902 Learning rate: 0.002 Mask loss: 0.10228 RPN box loss: 0.02945 RPN score loss: 0.00682 RPN total loss: 0.03627 Total loss: 0.84214 timestamp: 1655042111.0952587 iteration: 42850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14566 FastRCNN class loss: 0.06976 FastRCNN total loss: 0.21542 L1 loss: 0.0000e+00 L2 loss: 0.59901 Learning rate: 0.002 Mask loss: 0.14152 RPN box loss: 0.01197 RPN score loss: 0.00437 RPN total loss: 0.01634 Total loss: 0.9723 timestamp: 1655042114.3200653 iteration: 42855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1075 FastRCNN class loss: 0.10859 FastRCNN total loss: 0.21608 L1 loss: 0.0000e+00 L2 loss: 0.599 Learning rate: 0.002 Mask loss: 0.16273 RPN box loss: 0.02566 RPN score loss: 0.0134 RPN total loss: 0.03906 Total loss: 1.01688 timestamp: 1655042117.555616 iteration: 42860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11035 FastRCNN class loss: 0.0836 FastRCNN total loss: 0.19396 L1 loss: 0.0000e+00 L2 loss: 0.59899 Learning rate: 0.002 Mask loss: 0.09681 RPN box loss: 0.02395 RPN score loss: 0.00215 RPN total loss: 0.0261 Total loss: 0.91585 timestamp: 1655042120.7816353 iteration: 42865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.05307 FastRCNN total loss: 0.12629 L1 loss: 0.0000e+00 L2 loss: 0.59898 Learning rate: 0.002 Mask loss: 0.12269 RPN box loss: 0.01562 RPN score loss: 0.00616 RPN total loss: 0.02179 Total loss: 0.86974 timestamp: 1655042124.0595193 iteration: 42870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08195 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.14589 L1 loss: 0.0000e+00 L2 loss: 0.59897 Learning rate: 0.002 Mask loss: 0.17421 RPN box loss: 0.03003 RPN score loss: 0.00252 RPN total loss: 0.03255 Total loss: 0.95162 timestamp: 1655042127.380618 iteration: 42875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12363 FastRCNN class loss: 0.08303 FastRCNN total loss: 0.20666 L1 loss: 0.0000e+00 L2 loss: 0.59896 Learning rate: 0.002 Mask loss: 0.13382 RPN box loss: 0.03101 RPN score loss: 0.00261 RPN total loss: 0.03362 Total loss: 0.97305 timestamp: 1655042130.6163905 iteration: 42880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12534 FastRCNN class loss: 0.05847 FastRCNN total loss: 0.18381 L1 loss: 0.0000e+00 L2 loss: 0.59895 Learning rate: 0.002 Mask loss: 0.11647 RPN box loss: 0.00653 RPN score loss: 0.00431 RPN total loss: 0.01084 Total loss: 0.91007 timestamp: 1655042133.8794987 iteration: 42885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12693 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.18469 L1 loss: 0.0000e+00 L2 loss: 0.59894 Learning rate: 0.002 Mask loss: 0.17118 RPN box loss: 0.01561 RPN score loss: 0.00256 RPN total loss: 0.01817 Total loss: 0.97298 timestamp: 1655042137.146951 iteration: 42890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13166 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.21268 L1 loss: 0.0000e+00 L2 loss: 0.59893 Learning rate: 0.002 Mask loss: 0.1935 RPN box loss: 0.01791 RPN score loss: 0.00433 RPN total loss: 0.02224 Total loss: 1.02736 timestamp: 1655042140.3803973 iteration: 42895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09612 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.16869 L1 loss: 0.0000e+00 L2 loss: 0.59893 Learning rate: 0.002 Mask loss: 0.13901 RPN box loss: 0.07258 RPN score loss: 0.00972 RPN total loss: 0.0823 Total loss: 0.98893 timestamp: 1655042143.6542459 iteration: 42900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10954 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.19893 L1 loss: 0.0000e+00 L2 loss: 0.59892 Learning rate: 0.002 Mask loss: 0.16503 RPN box loss: 0.02629 RPN score loss: 0.00912 RPN total loss: 0.03541 Total loss: 0.99829 timestamp: 1655042146.9433029 iteration: 42905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14674 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.22145 L1 loss: 0.0000e+00 L2 loss: 0.59891 Learning rate: 0.002 Mask loss: 0.15574 RPN box loss: 0.08424 RPN score loss: 0.00797 RPN total loss: 0.09221 Total loss: 1.06831 timestamp: 1655042150.2362146 iteration: 42910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15574 FastRCNN class loss: 0.09029 FastRCNN total loss: 0.24604 L1 loss: 0.0000e+00 L2 loss: 0.5989 Learning rate: 0.002 Mask loss: 0.18083 RPN box loss: 0.02599 RPN score loss: 0.0087 RPN total loss: 0.03469 Total loss: 1.06046 timestamp: 1655042153.4520833 iteration: 42915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04383 FastRCNN class loss: 0.033 FastRCNN total loss: 0.07683 L1 loss: 0.0000e+00 L2 loss: 0.59889 Learning rate: 0.002 Mask loss: 0.0906 RPN box loss: 0.00719 RPN score loss: 0.00061 RPN total loss: 0.0078 Total loss: 0.77413 timestamp: 1655042156.6938152 iteration: 42920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14465 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.21926 L1 loss: 0.0000e+00 L2 loss: 0.59888 Learning rate: 0.002 Mask loss: 0.17947 RPN box loss: 0.05063 RPN score loss: 0.01103 RPN total loss: 0.06165 Total loss: 1.05927 timestamp: 1655042159.9768445 iteration: 42925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17135 FastRCNN class loss: 0.09303 FastRCNN total loss: 0.26437 L1 loss: 0.0000e+00 L2 loss: 0.59887 Learning rate: 0.002 Mask loss: 0.21382 RPN box loss: 0.02921 RPN score loss: 0.00263 RPN total loss: 0.03185 Total loss: 1.10891 timestamp: 1655042163.2233608 iteration: 42930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.1767 L1 loss: 0.0000e+00 L2 loss: 0.59887 Learning rate: 0.002 Mask loss: 0.20888 RPN box loss: 0.04877 RPN score loss: 0.00559 RPN total loss: 0.05436 Total loss: 1.0388 timestamp: 1655042166.492055 iteration: 42935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08742 FastRCNN class loss: 0.07992 FastRCNN total loss: 0.16733 L1 loss: 0.0000e+00 L2 loss: 0.59886 Learning rate: 0.002 Mask loss: 0.13349 RPN box loss: 0.02065 RPN score loss: 0.00568 RPN total loss: 0.02632 Total loss: 0.926 timestamp: 1655042169.7783782 iteration: 42940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07585 FastRCNN class loss: 0.04519 FastRCNN total loss: 0.12104 L1 loss: 0.0000e+00 L2 loss: 0.59885 Learning rate: 0.002 Mask loss: 0.28156 RPN box loss: 0.00284 RPN score loss: 0.00552 RPN total loss: 0.00836 Total loss: 1.00981 timestamp: 1655042173.01716 iteration: 42945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.16217 L1 loss: 0.0000e+00 L2 loss: 0.59884 Learning rate: 0.002 Mask loss: 0.15489 RPN box loss: 0.02369 RPN score loss: 0.01505 RPN total loss: 0.03875 Total loss: 0.95465 timestamp: 1655042176.3001394 iteration: 42950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.06795 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.59883 Learning rate: 0.002 Mask loss: 0.12232 RPN box loss: 0.06638 RPN score loss: 0.00745 RPN total loss: 0.07382 Total loss: 0.95708 timestamp: 1655042179.5277653 iteration: 42955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10418 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.18128 L1 loss: 0.0000e+00 L2 loss: 0.59882 Learning rate: 0.002 Mask loss: 0.13358 RPN box loss: 0.0102 RPN score loss: 0.00591 RPN total loss: 0.01611 Total loss: 0.92979 timestamp: 1655042182.7829144 iteration: 42960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05902 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.1228 L1 loss: 0.0000e+00 L2 loss: 0.59881 Learning rate: 0.002 Mask loss: 0.11481 RPN box loss: 0.01379 RPN score loss: 0.00344 RPN total loss: 0.01723 Total loss: 0.85365 timestamp: 1655042186.066121 iteration: 42965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13828 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.22156 L1 loss: 0.0000e+00 L2 loss: 0.5988 Learning rate: 0.002 Mask loss: 0.13229 RPN box loss: 0.0233 RPN score loss: 0.00661 RPN total loss: 0.02992 Total loss: 0.98257 timestamp: 1655042189.3399997 iteration: 42970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10422 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.17909 L1 loss: 0.0000e+00 L2 loss: 0.59879 Learning rate: 0.002 Mask loss: 0.1279 RPN box loss: 0.02135 RPN score loss: 0.01281 RPN total loss: 0.03416 Total loss: 0.93993 timestamp: 1655042192.6207197 iteration: 42975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06305 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.10756 L1 loss: 0.0000e+00 L2 loss: 0.59878 Learning rate: 0.002 Mask loss: 0.14798 RPN box loss: 0.00245 RPN score loss: 0.00184 RPN total loss: 0.00428 Total loss: 0.8586 timestamp: 1655042195.876642 iteration: 42980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18036 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.25043 L1 loss: 0.0000e+00 L2 loss: 0.59877 Learning rate: 0.002 Mask loss: 0.15885 RPN box loss: 0.00979 RPN score loss: 0.00266 RPN total loss: 0.01245 Total loss: 1.02049 timestamp: 1655042199.209303 iteration: 42985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06805 FastRCNN class loss: 0.06701 FastRCNN total loss: 0.13506 L1 loss: 0.0000e+00 L2 loss: 0.59876 Learning rate: 0.002 Mask loss: 0.14502 RPN box loss: 0.01816 RPN score loss: 0.00301 RPN total loss: 0.02117 Total loss: 0.90001 timestamp: 1655042202.4514415 iteration: 42990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13181 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.59875 Learning rate: 0.002 Mask loss: 0.13094 RPN box loss: 0.01424 RPN score loss: 0.00241 RPN total loss: 0.01665 Total loss: 0.94322 timestamp: 1655042205.7488403 iteration: 42995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08537 FastRCNN class loss: 0.0636 FastRCNN total loss: 0.14897 L1 loss: 0.0000e+00 L2 loss: 0.59874 Learning rate: 0.002 Mask loss: 0.10775 RPN box loss: 0.06699 RPN score loss: 0.00618 RPN total loss: 0.07317 Total loss: 0.92863 timestamp: 1655042209.0408478 iteration: 43000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0861 FastRCNN class loss: 0.08802 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.59873 Learning rate: 0.002 Mask loss: 0.12901 RPN box loss: 0.02514 RPN score loss: 0.00982 RPN total loss: 0.03496 Total loss: 0.93682 timestamp: 1655042212.307539 iteration: 43005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10965 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.1677 L1 loss: 0.0000e+00 L2 loss: 0.59872 Learning rate: 0.002 Mask loss: 0.1589 RPN box loss: 0.0137 RPN score loss: 0.00785 RPN total loss: 0.02155 Total loss: 0.94687 timestamp: 1655042215.5251553 iteration: 43010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11644 FastRCNN class loss: 0.14109 FastRCNN total loss: 0.25753 L1 loss: 0.0000e+00 L2 loss: 0.59871 Learning rate: 0.002 Mask loss: 0.25792 RPN box loss: 0.02993 RPN score loss: 0.00977 RPN total loss: 0.0397 Total loss: 1.15387 timestamp: 1655042218.8284 iteration: 43015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12979 FastRCNN class loss: 0.10054 FastRCNN total loss: 0.23033 L1 loss: 0.0000e+00 L2 loss: 0.5987 Learning rate: 0.002 Mask loss: 0.13188 RPN box loss: 0.01749 RPN score loss: 0.00896 RPN total loss: 0.02645 Total loss: 0.98737 timestamp: 1655042222.0710583 iteration: 43020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09465 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.14103 L1 loss: 0.0000e+00 L2 loss: 0.5987 Learning rate: 0.002 Mask loss: 0.12973 RPN box loss: 0.00557 RPN score loss: 0.00165 RPN total loss: 0.00722 Total loss: 0.87667 timestamp: 1655042225.3407834 iteration: 43025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13684 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.2129 L1 loss: 0.0000e+00 L2 loss: 0.59869 Learning rate: 0.002 Mask loss: 0.13908 RPN box loss: 0.02184 RPN score loss: 0.00322 RPN total loss: 0.02505 Total loss: 0.97572 timestamp: 1655042228.5815127 iteration: 43030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08482 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.13761 L1 loss: 0.0000e+00 L2 loss: 0.59868 Learning rate: 0.002 Mask loss: 0.13799 RPN box loss: 0.01689 RPN score loss: 0.01125 RPN total loss: 0.02814 Total loss: 0.90242 timestamp: 1655042231.8367362 iteration: 43035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07382 FastRCNN class loss: 0.05236 FastRCNN total loss: 0.12618 L1 loss: 0.0000e+00 L2 loss: 0.59867 Learning rate: 0.002 Mask loss: 0.11866 RPN box loss: 0.0119 RPN score loss: 0.00313 RPN total loss: 0.01503 Total loss: 0.85854 timestamp: 1655042235.100931 iteration: 43040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15855 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.24567 L1 loss: 0.0000e+00 L2 loss: 0.59866 Learning rate: 0.002 Mask loss: 0.14505 RPN box loss: 0.02265 RPN score loss: 0.00541 RPN total loss: 0.02806 Total loss: 1.01745 timestamp: 1655042238.3363357 iteration: 43045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19938 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.28606 L1 loss: 0.0000e+00 L2 loss: 0.59865 Learning rate: 0.002 Mask loss: 0.15038 RPN box loss: 0.01078 RPN score loss: 0.00425 RPN total loss: 0.01503 Total loss: 1.05012 timestamp: 1655042241.6488624 iteration: 43050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.20323 L1 loss: 0.0000e+00 L2 loss: 0.59864 Learning rate: 0.002 Mask loss: 0.16092 RPN box loss: 0.03559 RPN score loss: 0.0048 RPN total loss: 0.04039 Total loss: 1.00318 timestamp: 1655042244.8893242 iteration: 43055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09625 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 0.59863 Learning rate: 0.002 Mask loss: 0.12439 RPN box loss: 0.01227 RPN score loss: 0.01571 RPN total loss: 0.02798 Total loss: 0.91089 timestamp: 1655042248.1815445 iteration: 43060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18035 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.25223 L1 loss: 0.0000e+00 L2 loss: 0.59862 Learning rate: 0.002 Mask loss: 0.11927 RPN box loss: 0.01215 RPN score loss: 0.00717 RPN total loss: 0.01932 Total loss: 0.98943 timestamp: 1655042251.4225314 iteration: 43065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11182 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 0.59861 Learning rate: 0.002 Mask loss: 0.13367 RPN box loss: 0.01596 RPN score loss: 0.00174 RPN total loss: 0.0177 Total loss: 0.91534 timestamp: 1655042254.78749 iteration: 43070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14995 FastRCNN class loss: 0.09283 FastRCNN total loss: 0.24279 L1 loss: 0.0000e+00 L2 loss: 0.5986 Learning rate: 0.002 Mask loss: 0.13822 RPN box loss: 0.02365 RPN score loss: 0.01135 RPN total loss: 0.03501 Total loss: 1.01461 timestamp: 1655042258.1246483 iteration: 43075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14648 FastRCNN class loss: 0.07931 FastRCNN total loss: 0.2258 L1 loss: 0.0000e+00 L2 loss: 0.5986 Learning rate: 0.002 Mask loss: 0.13183 RPN box loss: 0.03868 RPN score loss: 0.00207 RPN total loss: 0.04075 Total loss: 0.99697 timestamp: 1655042261.3949435 iteration: 43080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13967 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.1948 L1 loss: 0.0000e+00 L2 loss: 0.59859 Learning rate: 0.002 Mask loss: 0.15116 RPN box loss: 0.01601 RPN score loss: 0.00302 RPN total loss: 0.01904 Total loss: 0.96358 timestamp: 1655042264.6414702 iteration: 43085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09939 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.16309 L1 loss: 0.0000e+00 L2 loss: 0.59858 Learning rate: 0.002 Mask loss: 0.1322 RPN box loss: 0.02548 RPN score loss: 0.01093 RPN total loss: 0.03642 Total loss: 0.93028 timestamp: 1655042268.009043 iteration: 43090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07728 FastRCNN class loss: 0.05767 FastRCNN total loss: 0.13495 L1 loss: 0.0000e+00 L2 loss: 0.59857 Learning rate: 0.002 Mask loss: 0.13352 RPN box loss: 0.03428 RPN score loss: 0.00544 RPN total loss: 0.03971 Total loss: 0.90675 timestamp: 1655042271.2731147 iteration: 43095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13828 FastRCNN class loss: 0.09912 FastRCNN total loss: 0.2374 L1 loss: 0.0000e+00 L2 loss: 0.59856 Learning rate: 0.002 Mask loss: 0.27118 RPN box loss: 0.01234 RPN score loss: 0.00355 RPN total loss: 0.01589 Total loss: 1.12303 timestamp: 1655042274.4917457 iteration: 43100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06126 FastRCNN class loss: 0.0992 FastRCNN total loss: 0.16046 L1 loss: 0.0000e+00 L2 loss: 0.59855 Learning rate: 0.002 Mask loss: 0.15683 RPN box loss: 0.02565 RPN score loss: 0.01197 RPN total loss: 0.03762 Total loss: 0.95346 timestamp: 1655042277.7635891 iteration: 43105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14905 FastRCNN class loss: 0.11651 FastRCNN total loss: 0.26556 L1 loss: 0.0000e+00 L2 loss: 0.59854 Learning rate: 0.002 Mask loss: 0.17008 RPN box loss: 0.03001 RPN score loss: 0.01153 RPN total loss: 0.04154 Total loss: 1.07573 timestamp: 1655042281.0184548 iteration: 43110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1539 FastRCNN class loss: 0.10777 FastRCNN total loss: 0.26167 L1 loss: 0.0000e+00 L2 loss: 0.59853 Learning rate: 0.002 Mask loss: 0.14732 RPN box loss: 0.02205 RPN score loss: 0.00418 RPN total loss: 0.02623 Total loss: 1.03374 timestamp: 1655042284.2917676 iteration: 43115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1331 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.19964 L1 loss: 0.0000e+00 L2 loss: 0.59852 Learning rate: 0.002 Mask loss: 0.14025 RPN box loss: 0.04818 RPN score loss: 0.00736 RPN total loss: 0.05554 Total loss: 0.99395 timestamp: 1655042287.5307817 iteration: 43120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1214 FastRCNN class loss: 0.09424 FastRCNN total loss: 0.21564 L1 loss: 0.0000e+00 L2 loss: 0.59851 Learning rate: 0.002 Mask loss: 0.12829 RPN box loss: 0.01015 RPN score loss: 0.00851 RPN total loss: 0.01866 Total loss: 0.9611 timestamp: 1655042290.8268323 iteration: 43125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06993 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.14311 L1 loss: 0.0000e+00 L2 loss: 0.5985 Learning rate: 0.002 Mask loss: 0.09977 RPN box loss: 0.01378 RPN score loss: 0.00546 RPN total loss: 0.01924 Total loss: 0.86063 timestamp: 1655042294.1383584 iteration: 43130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03538 FastRCNN class loss: 0.02969 FastRCNN total loss: 0.06507 L1 loss: 0.0000e+00 L2 loss: 0.59849 Learning rate: 0.002 Mask loss: 0.08798 RPN box loss: 0.02725 RPN score loss: 0.00155 RPN total loss: 0.0288 Total loss: 0.78034 timestamp: 1655042297.3821461 iteration: 43135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10649 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.1674 L1 loss: 0.0000e+00 L2 loss: 0.59849 Learning rate: 0.002 Mask loss: 0.14938 RPN box loss: 0.02713 RPN score loss: 0.00898 RPN total loss: 0.03611 Total loss: 0.95137 timestamp: 1655042300.709092 iteration: 43140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.07034 FastRCNN total loss: 0.1814 L1 loss: 0.0000e+00 L2 loss: 0.59848 Learning rate: 0.002 Mask loss: 0.16839 RPN box loss: 0.038 RPN score loss: 0.01744 RPN total loss: 0.05544 Total loss: 1.0037 timestamp: 1655042304.0180845 iteration: 43145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15342 FastRCNN class loss: 0.09692 FastRCNN total loss: 0.25034 L1 loss: 0.0000e+00 L2 loss: 0.59847 Learning rate: 0.002 Mask loss: 0.1871 RPN box loss: 0.02337 RPN score loss: 0.00862 RPN total loss: 0.03199 Total loss: 1.0679 timestamp: 1655042307.2712896 iteration: 43150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12958 FastRCNN class loss: 0.08967 FastRCNN total loss: 0.21925 L1 loss: 0.0000e+00 L2 loss: 0.59846 Learning rate: 0.002 Mask loss: 0.142 RPN box loss: 0.01554 RPN score loss: 0.01305 RPN total loss: 0.0286 Total loss: 0.9883 timestamp: 1655042310.5359857 iteration: 43155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10227 FastRCNN class loss: 0.08804 FastRCNN total loss: 0.19032 L1 loss: 0.0000e+00 L2 loss: 0.59845 Learning rate: 0.002 Mask loss: 0.14211 RPN box loss: 0.01171 RPN score loss: 0.00646 RPN total loss: 0.01817 Total loss: 0.94904 timestamp: 1655042313.8101819 iteration: 43160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.10541 FastRCNN total loss: 0.18749 L1 loss: 0.0000e+00 L2 loss: 0.59844 Learning rate: 0.002 Mask loss: 0.15226 RPN box loss: 0.02784 RPN score loss: 0.01829 RPN total loss: 0.04613 Total loss: 0.98433 timestamp: 1655042317.0695949 iteration: 43165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14166 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.21778 L1 loss: 0.0000e+00 L2 loss: 0.59843 Learning rate: 0.002 Mask loss: 0.14623 RPN box loss: 0.02683 RPN score loss: 0.01361 RPN total loss: 0.04044 Total loss: 1.00288 timestamp: 1655042320.4072936 iteration: 43170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1306 FastRCNN class loss: 0.10344 FastRCNN total loss: 0.23404 L1 loss: 0.0000e+00 L2 loss: 0.59841 Learning rate: 0.002 Mask loss: 0.14577 RPN box loss: 0.02103 RPN score loss: 0.00874 RPN total loss: 0.02977 Total loss: 1.00799 timestamp: 1655042323.735137 iteration: 43175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09761 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.19467 L1 loss: 0.0000e+00 L2 loss: 0.5984 Learning rate: 0.002 Mask loss: 0.13965 RPN box loss: 0.0237 RPN score loss: 0.00861 RPN total loss: 0.03231 Total loss: 0.96503 timestamp: 1655042327.032768 iteration: 43180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10893 FastRCNN class loss: 0.10389 FastRCNN total loss: 0.21282 L1 loss: 0.0000e+00 L2 loss: 0.5984 Learning rate: 0.002 Mask loss: 0.20666 RPN box loss: 0.01516 RPN score loss: 0.01002 RPN total loss: 0.02518 Total loss: 1.04304 timestamp: 1655042330.3349173 iteration: 43185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15244 FastRCNN class loss: 0.123 FastRCNN total loss: 0.27544 L1 loss: 0.0000e+00 L2 loss: 0.59839 Learning rate: 0.002 Mask loss: 0.17634 RPN box loss: 0.0402 RPN score loss: 0.01214 RPN total loss: 0.05235 Total loss: 1.10251 timestamp: 1655042333.613921 iteration: 43190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14889 FastRCNN class loss: 0.13838 FastRCNN total loss: 0.28728 L1 loss: 0.0000e+00 L2 loss: 0.59838 Learning rate: 0.002 Mask loss: 0.17243 RPN box loss: 0.0397 RPN score loss: 0.01633 RPN total loss: 0.05603 Total loss: 1.11412 timestamp: 1655042336.930918 iteration: 43195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13419 FastRCNN class loss: 0.10934 FastRCNN total loss: 0.24354 L1 loss: 0.0000e+00 L2 loss: 0.59837 Learning rate: 0.002 Mask loss: 0.149 RPN box loss: 0.0086 RPN score loss: 0.00233 RPN total loss: 0.01092 Total loss: 1.00184 timestamp: 1655042340.241478 iteration: 43200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12277 FastRCNN class loss: 0.07455 FastRCNN total loss: 0.19732 L1 loss: 0.0000e+00 L2 loss: 0.59836 Learning rate: 0.002 Mask loss: 0.16581 RPN box loss: 0.03613 RPN score loss: 0.0071 RPN total loss: 0.04323 Total loss: 1.00473 timestamp: 1655042343.5278902 iteration: 43205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15704 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.22373 L1 loss: 0.0000e+00 L2 loss: 0.59835 Learning rate: 0.002 Mask loss: 0.17769 RPN box loss: 0.02422 RPN score loss: 0.00294 RPN total loss: 0.02716 Total loss: 1.02694 timestamp: 1655042346.8574033 iteration: 43210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06132 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.13295 L1 loss: 0.0000e+00 L2 loss: 0.59834 Learning rate: 0.002 Mask loss: 0.10461 RPN box loss: 0.00303 RPN score loss: 0.00143 RPN total loss: 0.00446 Total loss: 0.84037 timestamp: 1655042350.1645966 iteration: 43215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18583 FastRCNN class loss: 0.10868 FastRCNN total loss: 0.29451 L1 loss: 0.0000e+00 L2 loss: 0.59833 Learning rate: 0.002 Mask loss: 0.14941 RPN box loss: 0.01815 RPN score loss: 0.00351 RPN total loss: 0.02166 Total loss: 1.06391 timestamp: 1655042353.4494781 iteration: 43220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18774 FastRCNN class loss: 0.12353 FastRCNN total loss: 0.31127 L1 loss: 0.0000e+00 L2 loss: 0.59833 Learning rate: 0.002 Mask loss: 0.21708 RPN box loss: 0.0304 RPN score loss: 0.00607 RPN total loss: 0.03647 Total loss: 1.16314 timestamp: 1655042356.7221045 iteration: 43225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.04367 FastRCNN total loss: 0.12284 L1 loss: 0.0000e+00 L2 loss: 0.59832 Learning rate: 0.002 Mask loss: 0.17135 RPN box loss: 0.03946 RPN score loss: 0.00303 RPN total loss: 0.04249 Total loss: 0.935 timestamp: 1655042360.0397313 iteration: 43230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10638 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.18692 L1 loss: 0.0000e+00 L2 loss: 0.5983 Learning rate: 0.002 Mask loss: 0.09609 RPN box loss: 0.00839 RPN score loss: 0.00179 RPN total loss: 0.01018 Total loss: 0.89149 timestamp: 1655042363.2794213 iteration: 43235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10507 FastRCNN class loss: 0.07414 FastRCNN total loss: 0.17921 L1 loss: 0.0000e+00 L2 loss: 0.5983 Learning rate: 0.002 Mask loss: 0.15423 RPN box loss: 0.03725 RPN score loss: 0.00798 RPN total loss: 0.04523 Total loss: 0.97697 timestamp: 1655042366.528678 iteration: 43240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10203 FastRCNN class loss: 0.08054 FastRCNN total loss: 0.18257 L1 loss: 0.0000e+00 L2 loss: 0.59829 Learning rate: 0.002 Mask loss: 0.20916 RPN box loss: 0.02039 RPN score loss: 0.0079 RPN total loss: 0.02829 Total loss: 1.01831 timestamp: 1655042369.8258245 iteration: 43245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11743 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.19346 L1 loss: 0.0000e+00 L2 loss: 0.59828 Learning rate: 0.002 Mask loss: 0.10979 RPN box loss: 0.02216 RPN score loss: 0.00837 RPN total loss: 0.03053 Total loss: 0.93206 timestamp: 1655042373.0498364 iteration: 43250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13778 FastRCNN class loss: 0.10617 FastRCNN total loss: 0.24395 L1 loss: 0.0000e+00 L2 loss: 0.59827 Learning rate: 0.002 Mask loss: 0.14044 RPN box loss: 0.02942 RPN score loss: 0.00806 RPN total loss: 0.03747 Total loss: 1.02013 timestamp: 1655042376.3647869 iteration: 43255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19375 FastRCNN class loss: 0.05717 FastRCNN total loss: 0.25093 L1 loss: 0.0000e+00 L2 loss: 0.59825 Learning rate: 0.002 Mask loss: 0.16205 RPN box loss: 0.01331 RPN score loss: 0.0057 RPN total loss: 0.019 Total loss: 1.03024 timestamp: 1655042379.665923 iteration: 43260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07073 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.13553 L1 loss: 0.0000e+00 L2 loss: 0.59824 Learning rate: 0.002 Mask loss: 0.09752 RPN box loss: 0.02501 RPN score loss: 0.00282 RPN total loss: 0.02783 Total loss: 0.85913 timestamp: 1655042382.914541 iteration: 43265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.14211 L1 loss: 0.0000e+00 L2 loss: 0.59823 Learning rate: 0.002 Mask loss: 0.12398 RPN box loss: 0.01732 RPN score loss: 0.00615 RPN total loss: 0.02347 Total loss: 0.8878 timestamp: 1655042386.1744583 iteration: 43270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.10445 FastRCNN total loss: 0.21373 L1 loss: 0.0000e+00 L2 loss: 0.59822 Learning rate: 0.002 Mask loss: 0.18617 RPN box loss: 0.0224 RPN score loss: 0.013 RPN total loss: 0.0354 Total loss: 1.03353 timestamp: 1655042389.4727192 iteration: 43275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16819 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.26509 L1 loss: 0.0000e+00 L2 loss: 0.59821 Learning rate: 0.002 Mask loss: 0.21893 RPN box loss: 0.0296 RPN score loss: 0.00904 RPN total loss: 0.03864 Total loss: 1.12088 timestamp: 1655042392.7270443 iteration: 43280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07361 FastRCNN class loss: 0.06783 FastRCNN total loss: 0.14144 L1 loss: 0.0000e+00 L2 loss: 0.5982 Learning rate: 0.002 Mask loss: 0.09179 RPN box loss: 0.01505 RPN score loss: 0.0044 RPN total loss: 0.01945 Total loss: 0.85088 timestamp: 1655042396.0645585 iteration: 43285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11429 FastRCNN class loss: 0.08507 FastRCNN total loss: 0.19936 L1 loss: 0.0000e+00 L2 loss: 0.5982 Learning rate: 0.002 Mask loss: 0.1627 RPN box loss: 0.0333 RPN score loss: 0.00736 RPN total loss: 0.04067 Total loss: 1.00093 timestamp: 1655042399.35177 iteration: 43290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11794 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.59819 Learning rate: 0.002 Mask loss: 0.1614 RPN box loss: 0.02089 RPN score loss: 0.01368 RPN total loss: 0.03457 Total loss: 0.99104 timestamp: 1655042402.6340957 iteration: 43295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.10005 FastRCNN total loss: 0.21594 L1 loss: 0.0000e+00 L2 loss: 0.59818 Learning rate: 0.002 Mask loss: 0.13005 RPN box loss: 0.0226 RPN score loss: 0.006 RPN total loss: 0.0286 Total loss: 0.97277 timestamp: 1655042405.9092872 iteration: 43300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12435 FastRCNN class loss: 0.09414 FastRCNN total loss: 0.21849 L1 loss: 0.0000e+00 L2 loss: 0.59817 Learning rate: 0.002 Mask loss: 0.11809 RPN box loss: 0.01486 RPN score loss: 0.0072 RPN total loss: 0.02206 Total loss: 0.95681 timestamp: 1655042409.2026818 iteration: 43305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10839 FastRCNN class loss: 0.0986 FastRCNN total loss: 0.207 L1 loss: 0.0000e+00 L2 loss: 0.59816 Learning rate: 0.002 Mask loss: 0.14754 RPN box loss: 0.0225 RPN score loss: 0.01098 RPN total loss: 0.03348 Total loss: 0.98619 timestamp: 1655042412.477397 iteration: 43310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14809 FastRCNN class loss: 0.09236 FastRCNN total loss: 0.24044 L1 loss: 0.0000e+00 L2 loss: 0.59816 Learning rate: 0.002 Mask loss: 0.24301 RPN box loss: 0.02214 RPN score loss: 0.00493 RPN total loss: 0.02707 Total loss: 1.10868 timestamp: 1655042415.7720432 iteration: 43315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12182 FastRCNN class loss: 0.08693 FastRCNN total loss: 0.20875 L1 loss: 0.0000e+00 L2 loss: 0.59815 Learning rate: 0.002 Mask loss: 0.18712 RPN box loss: 0.00989 RPN score loss: 0.0021 RPN total loss: 0.01199 Total loss: 1.00601 timestamp: 1655042419.0776706 iteration: 43320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16346 FastRCNN class loss: 0.12446 FastRCNN total loss: 0.28792 L1 loss: 0.0000e+00 L2 loss: 0.59814 Learning rate: 0.002 Mask loss: 0.17258 RPN box loss: 0.00457 RPN score loss: 0.00816 RPN total loss: 0.01273 Total loss: 1.07136 timestamp: 1655042422.3324523 iteration: 43325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11664 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.19552 L1 loss: 0.0000e+00 L2 loss: 0.59813 Learning rate: 0.002 Mask loss: 0.16914 RPN box loss: 0.00606 RPN score loss: 0.00471 RPN total loss: 0.01076 Total loss: 0.97356 timestamp: 1655042425.6101663 iteration: 43330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.147 FastRCNN class loss: 0.09974 FastRCNN total loss: 0.24674 L1 loss: 0.0000e+00 L2 loss: 0.59812 Learning rate: 0.002 Mask loss: 0.12481 RPN box loss: 0.0184 RPN score loss: 0.00586 RPN total loss: 0.02427 Total loss: 0.99393 timestamp: 1655042428.8177166 iteration: 43335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.20066 L1 loss: 0.0000e+00 L2 loss: 0.59811 Learning rate: 0.002 Mask loss: 0.13439 RPN box loss: 0.0159 RPN score loss: 0.00641 RPN total loss: 0.0223 Total loss: 0.95547 timestamp: 1655042432.0712423 iteration: 43340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.12912 L1 loss: 0.0000e+00 L2 loss: 0.5981 Learning rate: 0.002 Mask loss: 0.12692 RPN box loss: 0.0136 RPN score loss: 0.00426 RPN total loss: 0.01786 Total loss: 0.872 timestamp: 1655042435.3449693 iteration: 43345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14526 FastRCNN class loss: 0.07835 FastRCNN total loss: 0.22361 L1 loss: 0.0000e+00 L2 loss: 0.59809 Learning rate: 0.002 Mask loss: 0.15345 RPN box loss: 0.01079 RPN score loss: 0.00558 RPN total loss: 0.01637 Total loss: 0.99152 timestamp: 1655042438.5925686 iteration: 43350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10925 FastRCNN class loss: 0.11032 FastRCNN total loss: 0.21957 L1 loss: 0.0000e+00 L2 loss: 0.59809 Learning rate: 0.002 Mask loss: 0.14748 RPN box loss: 0.01881 RPN score loss: 0.0081 RPN total loss: 0.02691 Total loss: 0.99205 timestamp: 1655042441.8931277 iteration: 43355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1022 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.16793 L1 loss: 0.0000e+00 L2 loss: 0.59808 Learning rate: 0.002 Mask loss: 0.27289 RPN box loss: 0.04561 RPN score loss: 0.01305 RPN total loss: 0.05866 Total loss: 1.09755 timestamp: 1655042445.105597 iteration: 43360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0903 FastRCNN class loss: 0.07284 FastRCNN total loss: 0.16314 L1 loss: 0.0000e+00 L2 loss: 0.59807 Learning rate: 0.002 Mask loss: 0.12773 RPN box loss: 0.04857 RPN score loss: 0.00864 RPN total loss: 0.05721 Total loss: 0.94616 timestamp: 1655042448.4111173 iteration: 43365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07959 FastRCNN class loss: 0.0979 FastRCNN total loss: 0.1775 L1 loss: 0.0000e+00 L2 loss: 0.59806 Learning rate: 0.002 Mask loss: 0.18759 RPN box loss: 0.0147 RPN score loss: 0.00775 RPN total loss: 0.02246 Total loss: 0.9856 timestamp: 1655042451.6763709 iteration: 43370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08256 FastRCNN class loss: 0.10097 FastRCNN total loss: 0.18353 L1 loss: 0.0000e+00 L2 loss: 0.59805 Learning rate: 0.002 Mask loss: 0.19964 RPN box loss: 0.01647 RPN score loss: 0.00814 RPN total loss: 0.02461 Total loss: 1.00583 timestamp: 1655042454.9490194 iteration: 43375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12348 FastRCNN class loss: 0.05717 FastRCNN total loss: 0.18065 L1 loss: 0.0000e+00 L2 loss: 0.59803 Learning rate: 0.002 Mask loss: 0.11377 RPN box loss: 0.0277 RPN score loss: 0.00621 RPN total loss: 0.03391 Total loss: 0.92637 timestamp: 1655042458.1491137 iteration: 43380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07952 FastRCNN class loss: 0.0417 FastRCNN total loss: 0.12122 L1 loss: 0.0000e+00 L2 loss: 0.59802 Learning rate: 0.002 Mask loss: 0.12272 RPN box loss: 0.00628 RPN score loss: 0.00285 RPN total loss: 0.00913 Total loss: 0.85109 timestamp: 1655042461.4479396 iteration: 43385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10548 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.16984 L1 loss: 0.0000e+00 L2 loss: 0.59801 Learning rate: 0.002 Mask loss: 0.12617 RPN box loss: 0.01524 RPN score loss: 0.0061 RPN total loss: 0.02133 Total loss: 0.91536 timestamp: 1655042464.662361 iteration: 43390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12168 FastRCNN class loss: 0.07452 FastRCNN total loss: 0.1962 L1 loss: 0.0000e+00 L2 loss: 0.59801 Learning rate: 0.002 Mask loss: 0.1359 RPN box loss: 0.01406 RPN score loss: 0.0071 RPN total loss: 0.02116 Total loss: 0.95127 timestamp: 1655042467.9002154 iteration: 43395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12935 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.2264 L1 loss: 0.0000e+00 L2 loss: 0.598 Learning rate: 0.002 Mask loss: 0.22117 RPN box loss: 0.03156 RPN score loss: 0.00672 RPN total loss: 0.03828 Total loss: 1.08384 timestamp: 1655042471.2333312 iteration: 43400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12754 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.1971 L1 loss: 0.0000e+00 L2 loss: 0.59799 Learning rate: 0.002 Mask loss: 0.18273 RPN box loss: 0.01939 RPN score loss: 0.00207 RPN total loss: 0.02146 Total loss: 0.99928 timestamp: 1655042474.4303427 iteration: 43405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07098 FastRCNN class loss: 0.05629 FastRCNN total loss: 0.12727 L1 loss: 0.0000e+00 L2 loss: 0.59798 Learning rate: 0.002 Mask loss: 0.12345 RPN box loss: 0.07266 RPN score loss: 0.00857 RPN total loss: 0.08122 Total loss: 0.92993 timestamp: 1655042477.6703053 iteration: 43410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.057 FastRCNN total loss: 0.13647 L1 loss: 0.0000e+00 L2 loss: 0.59797 Learning rate: 0.002 Mask loss: 0.13581 RPN box loss: 0.0239 RPN score loss: 0.00593 RPN total loss: 0.02983 Total loss: 0.90008 timestamp: 1655042481.0094872 iteration: 43415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.17251 L1 loss: 0.0000e+00 L2 loss: 0.59797 Learning rate: 0.002 Mask loss: 0.17557 RPN box loss: 0.01475 RPN score loss: 0.01674 RPN total loss: 0.03149 Total loss: 0.97753 timestamp: 1655042484.3424413 iteration: 43420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07486 FastRCNN class loss: 0.06304 FastRCNN total loss: 0.1379 L1 loss: 0.0000e+00 L2 loss: 0.59796 Learning rate: 0.002 Mask loss: 0.22913 RPN box loss: 0.01674 RPN score loss: 0.00822 RPN total loss: 0.02497 Total loss: 0.98996 timestamp: 1655042487.6349442 iteration: 43425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14073 FastRCNN class loss: 0.106 FastRCNN total loss: 0.24673 L1 loss: 0.0000e+00 L2 loss: 0.59795 Learning rate: 0.002 Mask loss: 0.20601 RPN box loss: 0.02077 RPN score loss: 0.0114 RPN total loss: 0.03218 Total loss: 1.08287 timestamp: 1655042490.8956633 iteration: 43430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08962 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.13926 L1 loss: 0.0000e+00 L2 loss: 0.59794 Learning rate: 0.002 Mask loss: 0.1121 RPN box loss: 0.02316 RPN score loss: 0.00569 RPN total loss: 0.02884 Total loss: 0.87814 timestamp: 1655042494.1855133 iteration: 43435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09892 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.17789 L1 loss: 0.0000e+00 L2 loss: 0.59792 Learning rate: 0.002 Mask loss: 0.12748 RPN box loss: 0.01176 RPN score loss: 0.01248 RPN total loss: 0.02424 Total loss: 0.92753 timestamp: 1655042497.5172603 iteration: 43440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07845 FastRCNN class loss: 0.06641 FastRCNN total loss: 0.14486 L1 loss: 0.0000e+00 L2 loss: 0.59791 Learning rate: 0.002 Mask loss: 0.18157 RPN box loss: 0.0185 RPN score loss: 0.00625 RPN total loss: 0.02475 Total loss: 0.94909 timestamp: 1655042500.8157465 iteration: 43445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13378 FastRCNN class loss: 0.07746 FastRCNN total loss: 0.21124 L1 loss: 0.0000e+00 L2 loss: 0.5979 Learning rate: 0.002 Mask loss: 0.18364 RPN box loss: 0.00534 RPN score loss: 0.00835 RPN total loss: 0.01369 Total loss: 1.00647 timestamp: 1655042504.0680885 iteration: 43450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09429 FastRCNN class loss: 0.03837 FastRCNN total loss: 0.13266 L1 loss: 0.0000e+00 L2 loss: 0.59789 Learning rate: 0.002 Mask loss: 0.12667 RPN box loss: 0.00631 RPN score loss: 0.00467 RPN total loss: 0.01098 Total loss: 0.8682 timestamp: 1655042507.3380377 iteration: 43455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10193 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.16244 L1 loss: 0.0000e+00 L2 loss: 0.59788 Learning rate: 0.002 Mask loss: 0.09915 RPN box loss: 0.01312 RPN score loss: 0.00198 RPN total loss: 0.01509 Total loss: 0.87457 timestamp: 1655042510.5878751 iteration: 43460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09582 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.16824 L1 loss: 0.0000e+00 L2 loss: 0.59788 Learning rate: 0.002 Mask loss: 0.15226 RPN box loss: 0.02109 RPN score loss: 0.00731 RPN total loss: 0.0284 Total loss: 0.94678 timestamp: 1655042513.8727903 iteration: 43465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12976 FastRCNN class loss: 0.08139 FastRCNN total loss: 0.21115 L1 loss: 0.0000e+00 L2 loss: 0.59787 Learning rate: 0.002 Mask loss: 0.1879 RPN box loss: 0.02031 RPN score loss: 0.0077 RPN total loss: 0.02801 Total loss: 1.02494 timestamp: 1655042517.1797626 iteration: 43470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11883 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.17912 L1 loss: 0.0000e+00 L2 loss: 0.59786 Learning rate: 0.002 Mask loss: 0.14072 RPN box loss: 0.01066 RPN score loss: 0.00562 RPN total loss: 0.01627 Total loss: 0.93397 timestamp: 1655042520.4845357 iteration: 43475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10656 FastRCNN class loss: 0.11079 FastRCNN total loss: 0.21735 L1 loss: 0.0000e+00 L2 loss: 0.59785 Learning rate: 0.002 Mask loss: 0.20629 RPN box loss: 0.04083 RPN score loss: 0.00579 RPN total loss: 0.04662 Total loss: 1.06812 timestamp: 1655042523.7200372 iteration: 43480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15467 FastRCNN class loss: 0.09197 FastRCNN total loss: 0.24664 L1 loss: 0.0000e+00 L2 loss: 0.59784 Learning rate: 0.002 Mask loss: 0.14897 RPN box loss: 0.03326 RPN score loss: 0.01078 RPN total loss: 0.04404 Total loss: 1.03749 timestamp: 1655042527.0565867 iteration: 43485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10552 FastRCNN class loss: 0.10149 FastRCNN total loss: 0.20701 L1 loss: 0.0000e+00 L2 loss: 0.59783 Learning rate: 0.002 Mask loss: 0.13172 RPN box loss: 0.0196 RPN score loss: 0.00413 RPN total loss: 0.02373 Total loss: 0.96028 timestamp: 1655042530.40148 iteration: 43490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.07374 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 0.59782 Learning rate: 0.002 Mask loss: 0.12774 RPN box loss: 0.00654 RPN score loss: 0.00207 RPN total loss: 0.00861 Total loss: 0.90113 timestamp: 1655042533.684147 iteration: 43495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09729 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.15892 L1 loss: 0.0000e+00 L2 loss: 0.59781 Learning rate: 0.002 Mask loss: 0.10213 RPN box loss: 0.01204 RPN score loss: 0.00599 RPN total loss: 0.01802 Total loss: 0.87689 timestamp: 1655042536.9531522 iteration: 43500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.05985 FastRCNN total loss: 0.14446 L1 loss: 0.0000e+00 L2 loss: 0.59781 Learning rate: 0.002 Mask loss: 0.15857 RPN box loss: 0.01646 RPN score loss: 0.00584 RPN total loss: 0.02229 Total loss: 0.92312 timestamp: 1655042540.247994 iteration: 43505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10403 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.16563 L1 loss: 0.0000e+00 L2 loss: 0.5978 Learning rate: 0.002 Mask loss: 0.11141 RPN box loss: 0.01523 RPN score loss: 0.00358 RPN total loss: 0.01882 Total loss: 0.89365 timestamp: 1655042543.5358543 iteration: 43510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17956 FastRCNN class loss: 0.11662 FastRCNN total loss: 0.29619 L1 loss: 0.0000e+00 L2 loss: 0.59779 Learning rate: 0.002 Mask loss: 0.17248 RPN box loss: 0.04747 RPN score loss: 0.01216 RPN total loss: 0.05962 Total loss: 1.12608 timestamp: 1655042546.82586 iteration: 43515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11692 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.18754 L1 loss: 0.0000e+00 L2 loss: 0.59778 Learning rate: 0.002 Mask loss: 0.16525 RPN box loss: 0.01082 RPN score loss: 0.00543 RPN total loss: 0.01625 Total loss: 0.96682 timestamp: 1655042550.0688615 iteration: 43520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08865 FastRCNN class loss: 0.05756 FastRCNN total loss: 0.14621 L1 loss: 0.0000e+00 L2 loss: 0.59777 Learning rate: 0.002 Mask loss: 0.17954 RPN box loss: 0.02147 RPN score loss: 0.00238 RPN total loss: 0.02385 Total loss: 0.94737 timestamp: 1655042553.3875144 iteration: 43525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10001 FastRCNN class loss: 0.07067 FastRCNN total loss: 0.17068 L1 loss: 0.0000e+00 L2 loss: 0.59776 Learning rate: 0.002 Mask loss: 0.11083 RPN box loss: 0.01119 RPN score loss: 0.0045 RPN total loss: 0.01569 Total loss: 0.89496 timestamp: 1655042556.6983387 iteration: 43530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1199 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.18149 L1 loss: 0.0000e+00 L2 loss: 0.59775 Learning rate: 0.002 Mask loss: 0.1547 RPN box loss: 0.01555 RPN score loss: 0.0049 RPN total loss: 0.02045 Total loss: 0.95438 timestamp: 1655042560.0375068 iteration: 43535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0926 FastRCNN class loss: 0.103 FastRCNN total loss: 0.1956 L1 loss: 0.0000e+00 L2 loss: 0.59774 Learning rate: 0.002 Mask loss: 0.11788 RPN box loss: 0.03858 RPN score loss: 0.00982 RPN total loss: 0.04841 Total loss: 0.95962 timestamp: 1655042563.2448294 iteration: 43540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13076 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.2143 L1 loss: 0.0000e+00 L2 loss: 0.59773 Learning rate: 0.002 Mask loss: 0.18999 RPN box loss: 0.0298 RPN score loss: 0.00351 RPN total loss: 0.0333 Total loss: 1.03532 timestamp: 1655042566.51673 iteration: 43545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0648 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.11623 L1 loss: 0.0000e+00 L2 loss: 0.59773 Learning rate: 0.002 Mask loss: 0.10621 RPN box loss: 0.00941 RPN score loss: 0.00515 RPN total loss: 0.01456 Total loss: 0.83473 timestamp: 1655042569.734918 iteration: 43550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.18883 L1 loss: 0.0000e+00 L2 loss: 0.59772 Learning rate: 0.002 Mask loss: 0.14196 RPN box loss: 0.01342 RPN score loss: 0.00274 RPN total loss: 0.01615 Total loss: 0.94467 timestamp: 1655042573.0323656 iteration: 43555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06378 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.12108 L1 loss: 0.0000e+00 L2 loss: 0.59771 Learning rate: 0.002 Mask loss: 0.16873 RPN box loss: 0.03153 RPN score loss: 0.00273 RPN total loss: 0.03426 Total loss: 0.92179 timestamp: 1655042576.2301283 iteration: 43560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.05744 FastRCNN total loss: 0.17273 L1 loss: 0.0000e+00 L2 loss: 0.5977 Learning rate: 0.002 Mask loss: 0.10922 RPN box loss: 0.00926 RPN score loss: 0.00683 RPN total loss: 0.01609 Total loss: 0.89574 timestamp: 1655042579.5034552 iteration: 43565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14647 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.2385 L1 loss: 0.0000e+00 L2 loss: 0.59769 Learning rate: 0.002 Mask loss: 0.13118 RPN box loss: 0.03692 RPN score loss: 0.00382 RPN total loss: 0.04075 Total loss: 1.00812 timestamp: 1655042582.7558522 iteration: 43570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.18888 L1 loss: 0.0000e+00 L2 loss: 0.59768 Learning rate: 0.002 Mask loss: 0.14002 RPN box loss: 0.05956 RPN score loss: 0.0075 RPN total loss: 0.06706 Total loss: 0.99364 timestamp: 1655042586.0898578 iteration: 43575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09677 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.15524 L1 loss: 0.0000e+00 L2 loss: 0.59767 Learning rate: 0.002 Mask loss: 0.10245 RPN box loss: 0.01734 RPN score loss: 0.00215 RPN total loss: 0.01949 Total loss: 0.87485 timestamp: 1655042589.3405619 iteration: 43580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11147 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.18876 L1 loss: 0.0000e+00 L2 loss: 0.59766 Learning rate: 0.002 Mask loss: 0.1439 RPN box loss: 0.03257 RPN score loss: 0.00386 RPN total loss: 0.03642 Total loss: 0.96674 timestamp: 1655042592.6294882 iteration: 43585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08095 FastRCNN class loss: 0.05755 FastRCNN total loss: 0.1385 L1 loss: 0.0000e+00 L2 loss: 0.59765 Learning rate: 0.002 Mask loss: 0.09422 RPN box loss: 0.03923 RPN score loss: 0.00201 RPN total loss: 0.04123 Total loss: 0.8716 timestamp: 1655042595.8938837 iteration: 43590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.0465 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.59764 Learning rate: 0.002 Mask loss: 0.24074 RPN box loss: 0.0059 RPN score loss: 0.00407 RPN total loss: 0.00997 Total loss: 0.99225 timestamp: 1655042599.1160083 iteration: 43595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12665 FastRCNN class loss: 0.1423 FastRCNN total loss: 0.26895 L1 loss: 0.0000e+00 L2 loss: 0.59763 Learning rate: 0.002 Mask loss: 0.25363 RPN box loss: 0.02636 RPN score loss: 0.01553 RPN total loss: 0.04189 Total loss: 1.16209 timestamp: 1655042602.3804872 iteration: 43600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1306 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.19523 L1 loss: 0.0000e+00 L2 loss: 0.59762 Learning rate: 0.002 Mask loss: 0.17871 RPN box loss: 0.02495 RPN score loss: 0.01746 RPN total loss: 0.0424 Total loss: 1.01397 timestamp: 1655042605.6695511 iteration: 43605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07614 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.12372 L1 loss: 0.0000e+00 L2 loss: 0.59762 Learning rate: 0.002 Mask loss: 0.06517 RPN box loss: 0.01215 RPN score loss: 0.00148 RPN total loss: 0.01363 Total loss: 0.80014 timestamp: 1655042608.95616 iteration: 43610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06142 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.10928 L1 loss: 0.0000e+00 L2 loss: 0.59761 Learning rate: 0.002 Mask loss: 0.1426 RPN box loss: 0.01237 RPN score loss: 0.00209 RPN total loss: 0.01446 Total loss: 0.86395 timestamp: 1655042612.2183356 iteration: 43615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12459 FastRCNN class loss: 0.11662 FastRCNN total loss: 0.24121 L1 loss: 0.0000e+00 L2 loss: 0.59759 Learning rate: 0.002 Mask loss: 0.15442 RPN box loss: 0.0116 RPN score loss: 0.00472 RPN total loss: 0.01632 Total loss: 1.00955 timestamp: 1655042615.5202198 iteration: 43620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17455 FastRCNN class loss: 0.08577 FastRCNN total loss: 0.26032 L1 loss: 0.0000e+00 L2 loss: 0.59758 Learning rate: 0.002 Mask loss: 0.13145 RPN box loss: 0.01759 RPN score loss: 0.00754 RPN total loss: 0.02513 Total loss: 1.01448 timestamp: 1655042618.786327 iteration: 43625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10132 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.15642 L1 loss: 0.0000e+00 L2 loss: 0.59758 Learning rate: 0.002 Mask loss: 0.14166 RPN box loss: 0.03027 RPN score loss: 0.00227 RPN total loss: 0.03253 Total loss: 0.92818 timestamp: 1655042622.0845628 iteration: 43630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10963 FastRCNN class loss: 0.07328 FastRCNN total loss: 0.18291 L1 loss: 0.0000e+00 L2 loss: 0.59756 Learning rate: 0.002 Mask loss: 0.15796 RPN box loss: 0.01126 RPN score loss: 0.00526 RPN total loss: 0.01652 Total loss: 0.95495 timestamp: 1655042625.3479793 iteration: 43635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15079 FastRCNN class loss: 0.11913 FastRCNN total loss: 0.26992 L1 loss: 0.0000e+00 L2 loss: 0.59756 Learning rate: 0.002 Mask loss: 0.21162 RPN box loss: 0.08082 RPN score loss: 0.0146 RPN total loss: 0.09542 Total loss: 1.17452 timestamp: 1655042628.6446164 iteration: 43640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1023 FastRCNN class loss: 0.05891 FastRCNN total loss: 0.16122 L1 loss: 0.0000e+00 L2 loss: 0.59755 Learning rate: 0.002 Mask loss: 0.12331 RPN box loss: 0.02581 RPN score loss: 0.00103 RPN total loss: 0.02684 Total loss: 0.90892 timestamp: 1655042631.954567 iteration: 43645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.09449 FastRCNN total loss: 0.20724 L1 loss: 0.0000e+00 L2 loss: 0.59754 Learning rate: 0.002 Mask loss: 0.13458 RPN box loss: 0.03295 RPN score loss: 0.01285 RPN total loss: 0.04581 Total loss: 0.98516 timestamp: 1655042635.2434452 iteration: 43650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07801 FastRCNN class loss: 0.04644 FastRCNN total loss: 0.12445 L1 loss: 0.0000e+00 L2 loss: 0.59753 Learning rate: 0.002 Mask loss: 0.12183 RPN box loss: 0.01017 RPN score loss: 0.00901 RPN total loss: 0.01918 Total loss: 0.86299 timestamp: 1655042638.5580516 iteration: 43655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11838 FastRCNN class loss: 0.1254 FastRCNN total loss: 0.24379 L1 loss: 0.0000e+00 L2 loss: 0.59753 Learning rate: 0.002 Mask loss: 0.19901 RPN box loss: 0.03119 RPN score loss: 0.011 RPN total loss: 0.04219 Total loss: 1.08251 timestamp: 1655042641.8026412 iteration: 43660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11282 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.18352 L1 loss: 0.0000e+00 L2 loss: 0.59752 Learning rate: 0.002 Mask loss: 0.11476 RPN box loss: 0.03413 RPN score loss: 0.01621 RPN total loss: 0.05035 Total loss: 0.94614 timestamp: 1655042645.117618 iteration: 43665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.09627 FastRCNN total loss: 0.23038 L1 loss: 0.0000e+00 L2 loss: 0.59751 Learning rate: 0.002 Mask loss: 0.1278 RPN box loss: 0.01925 RPN score loss: 0.00904 RPN total loss: 0.02829 Total loss: 0.98398 timestamp: 1655042648.4047015 iteration: 43670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13254 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.18791 L1 loss: 0.0000e+00 L2 loss: 0.59749 Learning rate: 0.002 Mask loss: 0.11858 RPN box loss: 0.01042 RPN score loss: 0.00127 RPN total loss: 0.01169 Total loss: 0.91567 timestamp: 1655042651.6822448 iteration: 43675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10111 FastRCNN class loss: 0.12046 FastRCNN total loss: 0.22157 L1 loss: 0.0000e+00 L2 loss: 0.59748 Learning rate: 0.002 Mask loss: 0.14945 RPN box loss: 0.01597 RPN score loss: 0.0074 RPN total loss: 0.02336 Total loss: 0.99186 timestamp: 1655042654.9161663 iteration: 43680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06451 FastRCNN class loss: 0.04449 FastRCNN total loss: 0.109 L1 loss: 0.0000e+00 L2 loss: 0.59747 Learning rate: 0.002 Mask loss: 0.15528 RPN box loss: 0.0093 RPN score loss: 0.00407 RPN total loss: 0.01338 Total loss: 0.87513 timestamp: 1655042658.1525145 iteration: 43685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07713 FastRCNN class loss: 0.07329 FastRCNN total loss: 0.15042 L1 loss: 0.0000e+00 L2 loss: 0.59746 Learning rate: 0.002 Mask loss: 0.14906 RPN box loss: 0.01873 RPN score loss: 0.01381 RPN total loss: 0.03254 Total loss: 0.92947 timestamp: 1655042661.3747814 iteration: 43690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15087 FastRCNN class loss: 0.08948 FastRCNN total loss: 0.24034 L1 loss: 0.0000e+00 L2 loss: 0.59745 Learning rate: 0.002 Mask loss: 0.16972 RPN box loss: 0.01911 RPN score loss: 0.00363 RPN total loss: 0.02274 Total loss: 1.03025 timestamp: 1655042664.6731217 iteration: 43695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10776 FastRCNN class loss: 0.05259 FastRCNN total loss: 0.16035 L1 loss: 0.0000e+00 L2 loss: 0.59744 Learning rate: 0.002 Mask loss: 0.11066 RPN box loss: 0.0073 RPN score loss: 0.00144 RPN total loss: 0.00874 Total loss: 0.87719 timestamp: 1655042667.8973699 iteration: 43700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12021 FastRCNN class loss: 0.09897 FastRCNN total loss: 0.21917 L1 loss: 0.0000e+00 L2 loss: 0.59743 Learning rate: 0.002 Mask loss: 0.18738 RPN box loss: 0.05237 RPN score loss: 0.01289 RPN total loss: 0.06526 Total loss: 1.06925 timestamp: 1655042671.1747339 iteration: 43705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0793 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.12368 L1 loss: 0.0000e+00 L2 loss: 0.59742 Learning rate: 0.002 Mask loss: 0.09286 RPN box loss: 0.01095 RPN score loss: 0.00614 RPN total loss: 0.01709 Total loss: 0.83105 timestamp: 1655042674.4478288 iteration: 43710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19808 FastRCNN class loss: 0.08335 FastRCNN total loss: 0.28143 L1 loss: 0.0000e+00 L2 loss: 0.59741 Learning rate: 0.002 Mask loss: 0.21579 RPN box loss: 0.01396 RPN score loss: 0.00687 RPN total loss: 0.02083 Total loss: 1.11546 timestamp: 1655042677.7669833 iteration: 43715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08808 FastRCNN class loss: 0.07139 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 0.5974 Learning rate: 0.002 Mask loss: 0.13024 RPN box loss: 0.00924 RPN score loss: 0.00656 RPN total loss: 0.0158 Total loss: 0.90291 timestamp: 1655042681.0379508 iteration: 43720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.17273 L1 loss: 0.0000e+00 L2 loss: 0.59739 Learning rate: 0.002 Mask loss: 0.11876 RPN box loss: 0.03586 RPN score loss: 0.00557 RPN total loss: 0.04142 Total loss: 0.9303 timestamp: 1655042684.265708 iteration: 43725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10148 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.17689 L1 loss: 0.0000e+00 L2 loss: 0.59739 Learning rate: 0.002 Mask loss: 0.20225 RPN box loss: 0.02574 RPN score loss: 0.02339 RPN total loss: 0.04912 Total loss: 1.02565 timestamp: 1655042687.468822 iteration: 43730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12043 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.1976 L1 loss: 0.0000e+00 L2 loss: 0.59738 Learning rate: 0.002 Mask loss: 0.20572 RPN box loss: 0.02322 RPN score loss: 0.00759 RPN total loss: 0.0308 Total loss: 1.0315 timestamp: 1655042690.7075446 iteration: 43735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08696 FastRCNN class loss: 0.08788 FastRCNN total loss: 0.17483 L1 loss: 0.0000e+00 L2 loss: 0.59737 Learning rate: 0.002 Mask loss: 0.14479 RPN box loss: 0.01105 RPN score loss: 0.00641 RPN total loss: 0.01746 Total loss: 0.93446 timestamp: 1655042693.993217 iteration: 43740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1013 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.16387 L1 loss: 0.0000e+00 L2 loss: 0.59736 Learning rate: 0.002 Mask loss: 0.11726 RPN box loss: 0.00807 RPN score loss: 0.0018 RPN total loss: 0.00988 Total loss: 0.88837 timestamp: 1655042697.293131 iteration: 43745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12329 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.19237 L1 loss: 0.0000e+00 L2 loss: 0.59736 Learning rate: 0.002 Mask loss: 0.17706 RPN box loss: 0.01701 RPN score loss: 0.00457 RPN total loss: 0.02158 Total loss: 0.98836 timestamp: 1655042700.5512779 iteration: 43750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19412 FastRCNN class loss: 0.09263 FastRCNN total loss: 0.28675 L1 loss: 0.0000e+00 L2 loss: 0.59735 Learning rate: 0.002 Mask loss: 0.15593 RPN box loss: 0.0226 RPN score loss: 0.00788 RPN total loss: 0.03048 Total loss: 1.07052 timestamp: 1655042703.8482974 iteration: 43755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.04792 FastRCNN total loss: 0.13631 L1 loss: 0.0000e+00 L2 loss: 0.59734 Learning rate: 0.002 Mask loss: 0.13973 RPN box loss: 0.01025 RPN score loss: 0.0017 RPN total loss: 0.01194 Total loss: 0.88532 timestamp: 1655042707.1260314 iteration: 43760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.15153 L1 loss: 0.0000e+00 L2 loss: 0.59733 Learning rate: 0.002 Mask loss: 0.14448 RPN box loss: 0.01755 RPN score loss: 0.00632 RPN total loss: 0.02386 Total loss: 0.9172 timestamp: 1655042710.3823261 iteration: 43765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.16942 L1 loss: 0.0000e+00 L2 loss: 0.59732 Learning rate: 0.002 Mask loss: 0.17328 RPN box loss: 0.01554 RPN score loss: 0.00476 RPN total loss: 0.0203 Total loss: 0.96032 timestamp: 1655042713.5930233 iteration: 43770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12792 FastRCNN class loss: 0.06962 FastRCNN total loss: 0.19754 L1 loss: 0.0000e+00 L2 loss: 0.59731 Learning rate: 0.002 Mask loss: 0.16187 RPN box loss: 0.02051 RPN score loss: 0.00508 RPN total loss: 0.02559 Total loss: 0.98231 timestamp: 1655042716.8350718 iteration: 43775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13687 FastRCNN class loss: 0.08474 FastRCNN total loss: 0.22161 L1 loss: 0.0000e+00 L2 loss: 0.5973 Learning rate: 0.002 Mask loss: 0.14647 RPN box loss: 0.01792 RPN score loss: 0.00561 RPN total loss: 0.02353 Total loss: 0.9889 timestamp: 1655042720.0828748 iteration: 43780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12498 FastRCNN class loss: 0.08218 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 0.59729 Learning rate: 0.002 Mask loss: 0.083 RPN box loss: 0.00926 RPN score loss: 0.00671 RPN total loss: 0.01597 Total loss: 0.90342 timestamp: 1655042723.3795516 iteration: 43785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12206 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.20103 L1 loss: 0.0000e+00 L2 loss: 0.59728 Learning rate: 0.002 Mask loss: 0.18613 RPN box loss: 0.00653 RPN score loss: 0.00632 RPN total loss: 0.01285 Total loss: 0.99729 timestamp: 1655042726.6476734 iteration: 43790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11079 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.20168 L1 loss: 0.0000e+00 L2 loss: 0.59727 Learning rate: 0.002 Mask loss: 0.19275 RPN box loss: 0.02958 RPN score loss: 0.01269 RPN total loss: 0.04228 Total loss: 1.03397 timestamp: 1655042729.9354558 iteration: 43795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14439 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.22707 L1 loss: 0.0000e+00 L2 loss: 0.59726 Learning rate: 0.002 Mask loss: 0.1369 RPN box loss: 0.02324 RPN score loss: 0.00681 RPN total loss: 0.03005 Total loss: 0.99129 timestamp: 1655042733.269161 iteration: 43800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1734 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.25899 L1 loss: 0.0000e+00 L2 loss: 0.59726 Learning rate: 0.002 Mask loss: 0.13727 RPN box loss: 0.01739 RPN score loss: 0.00396 RPN total loss: 0.02136 Total loss: 1.01487 timestamp: 1655042736.5633206 iteration: 43805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12228 FastRCNN class loss: 0.12227 FastRCNN total loss: 0.24455 L1 loss: 0.0000e+00 L2 loss: 0.59725 Learning rate: 0.002 Mask loss: 0.28287 RPN box loss: 0.03614 RPN score loss: 0.0082 RPN total loss: 0.04435 Total loss: 1.16901 timestamp: 1655042739.9060574 iteration: 43810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1263 FastRCNN class loss: 0.11943 FastRCNN total loss: 0.24573 L1 loss: 0.0000e+00 L2 loss: 0.59724 Learning rate: 0.002 Mask loss: 0.11946 RPN box loss: 0.03666 RPN score loss: 0.01415 RPN total loss: 0.05081 Total loss: 1.01324 timestamp: 1655042743.1980329 iteration: 43815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10394 FastRCNN class loss: 0.0797 FastRCNN total loss: 0.18363 L1 loss: 0.0000e+00 L2 loss: 0.59723 Learning rate: 0.002 Mask loss: 0.11999 RPN box loss: 0.03154 RPN score loss: 0.00408 RPN total loss: 0.03563 Total loss: 0.93648 timestamp: 1655042746.4706447 iteration: 43820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10843 FastRCNN class loss: 0.08905 FastRCNN total loss: 0.19748 L1 loss: 0.0000e+00 L2 loss: 0.59722 Learning rate: 0.002 Mask loss: 0.19185 RPN box loss: 0.02184 RPN score loss: 0.0033 RPN total loss: 0.02514 Total loss: 1.01169 timestamp: 1655042749.7989676 iteration: 43825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15198 FastRCNN class loss: 0.10361 FastRCNN total loss: 0.25558 L1 loss: 0.0000e+00 L2 loss: 0.59721 Learning rate: 0.002 Mask loss: 0.1603 RPN box loss: 0.08921 RPN score loss: 0.02027 RPN total loss: 0.10947 Total loss: 1.12256 timestamp: 1655042753.0660098 iteration: 43830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07975 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.15521 L1 loss: 0.0000e+00 L2 loss: 0.5972 Learning rate: 0.002 Mask loss: 0.08907 RPN box loss: 0.01321 RPN score loss: 0.00801 RPN total loss: 0.02122 Total loss: 0.8627 timestamp: 1655042756.350675 iteration: 43835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13833 FastRCNN class loss: 0.09261 FastRCNN total loss: 0.23094 L1 loss: 0.0000e+00 L2 loss: 0.59719 Learning rate: 0.002 Mask loss: 0.10922 RPN box loss: 0.01117 RPN score loss: 0.0018 RPN total loss: 0.01297 Total loss: 0.95032 timestamp: 1655042759.6036952 iteration: 43840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05592 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.10304 L1 loss: 0.0000e+00 L2 loss: 0.59718 Learning rate: 0.002 Mask loss: 0.10893 RPN box loss: 0.01049 RPN score loss: 0.00314 RPN total loss: 0.01363 Total loss: 0.82278 timestamp: 1655042762.8945248 iteration: 43845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11686 FastRCNN class loss: 0.0861 FastRCNN total loss: 0.20296 L1 loss: 0.0000e+00 L2 loss: 0.59717 Learning rate: 0.002 Mask loss: 0.19439 RPN box loss: 0.01075 RPN score loss: 0.00407 RPN total loss: 0.01481 Total loss: 1.00933 timestamp: 1655042766.0759208 iteration: 43850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14305 FastRCNN class loss: 0.06466 FastRCNN total loss: 0.20771 L1 loss: 0.0000e+00 L2 loss: 0.59716 Learning rate: 0.002 Mask loss: 0.09597 RPN box loss: 0.00731 RPN score loss: 0.00364 RPN total loss: 0.01095 Total loss: 0.91179 timestamp: 1655042769.375605 iteration: 43855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.06413 FastRCNN total loss: 0.18173 L1 loss: 0.0000e+00 L2 loss: 0.59715 Learning rate: 0.002 Mask loss: 0.12515 RPN box loss: 0.00586 RPN score loss: 0.0028 RPN total loss: 0.00865 Total loss: 0.91269 timestamp: 1655042772.6351762 iteration: 43860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07397 FastRCNN class loss: 0.07776 FastRCNN total loss: 0.15173 L1 loss: 0.0000e+00 L2 loss: 0.59714 Learning rate: 0.002 Mask loss: 0.17213 RPN box loss: 0.01072 RPN score loss: 0.00172 RPN total loss: 0.01244 Total loss: 0.93344 timestamp: 1655042775.947929 iteration: 43865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09763 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.14841 L1 loss: 0.0000e+00 L2 loss: 0.59713 Learning rate: 0.002 Mask loss: 0.12617 RPN box loss: 0.01713 RPN score loss: 0.00127 RPN total loss: 0.0184 Total loss: 0.89012 timestamp: 1655042779.1907372 iteration: 43870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.08592 FastRCNN total loss: 0.18436 L1 loss: 0.0000e+00 L2 loss: 0.59712 Learning rate: 0.002 Mask loss: 0.17602 RPN box loss: 0.01095 RPN score loss: 0.00363 RPN total loss: 0.01458 Total loss: 0.97208 timestamp: 1655042782.459893 iteration: 43875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10804 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.18286 L1 loss: 0.0000e+00 L2 loss: 0.59711 Learning rate: 0.002 Mask loss: 0.17342 RPN box loss: 0.03309 RPN score loss: 0.00866 RPN total loss: 0.04175 Total loss: 0.99514 timestamp: 1655042785.6997585 iteration: 43880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10663 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.16992 L1 loss: 0.0000e+00 L2 loss: 0.5971 Learning rate: 0.002 Mask loss: 0.21094 RPN box loss: 0.03121 RPN score loss: 0.00907 RPN total loss: 0.04029 Total loss: 1.01825 timestamp: 1655042788.9682443 iteration: 43885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07126 FastRCNN class loss: 0.05144 FastRCNN total loss: 0.1227 L1 loss: 0.0000e+00 L2 loss: 0.5971 Learning rate: 0.002 Mask loss: 0.15785 RPN box loss: 0.00968 RPN score loss: 0.00184 RPN total loss: 0.01152 Total loss: 0.88916 timestamp: 1655042792.309551 iteration: 43890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07939 FastRCNN class loss: 0.0837 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.59709 Learning rate: 0.002 Mask loss: 0.19353 RPN box loss: 0.01451 RPN score loss: 0.00566 RPN total loss: 0.02018 Total loss: 0.97388 timestamp: 1655042795.5878978 iteration: 43895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1157 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.18629 L1 loss: 0.0000e+00 L2 loss: 0.59708 Learning rate: 0.002 Mask loss: 0.17254 RPN box loss: 0.03208 RPN score loss: 0.00401 RPN total loss: 0.03609 Total loss: 0.992 timestamp: 1655042798.898348 iteration: 43900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08451 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.14306 L1 loss: 0.0000e+00 L2 loss: 0.59707 Learning rate: 0.002 Mask loss: 0.1277 RPN box loss: 0.02544 RPN score loss: 0.00459 RPN total loss: 0.03003 Total loss: 0.89786 timestamp: 1655042802.1681395 iteration: 43905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.18968 L1 loss: 0.0000e+00 L2 loss: 0.59706 Learning rate: 0.002 Mask loss: 0.12274 RPN box loss: 0.01999 RPN score loss: 0.00464 RPN total loss: 0.02463 Total loss: 0.93411 timestamp: 1655042805.420934 iteration: 43910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11439 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.19795 L1 loss: 0.0000e+00 L2 loss: 0.59705 Learning rate: 0.002 Mask loss: 0.15989 RPN box loss: 0.0341 RPN score loss: 0.01127 RPN total loss: 0.04537 Total loss: 1.00026 timestamp: 1655042808.6434188 iteration: 43915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14955 FastRCNN class loss: 0.08077 FastRCNN total loss: 0.23032 L1 loss: 0.0000e+00 L2 loss: 0.59704 Learning rate: 0.002 Mask loss: 0.09931 RPN box loss: 0.00867 RPN score loss: 0.00775 RPN total loss: 0.01642 Total loss: 0.94309 timestamp: 1655042811.9277713 iteration: 43920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.191 L1 loss: 0.0000e+00 L2 loss: 0.59703 Learning rate: 0.002 Mask loss: 0.17689 RPN box loss: 0.01084 RPN score loss: 0.00912 RPN total loss: 0.01996 Total loss: 0.98488 timestamp: 1655042815.1722665 iteration: 43925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08235 FastRCNN class loss: 0.07158 FastRCNN total loss: 0.15393 L1 loss: 0.0000e+00 L2 loss: 0.59702 Learning rate: 0.002 Mask loss: 0.12733 RPN box loss: 0.01319 RPN score loss: 0.00831 RPN total loss: 0.0215 Total loss: 0.89978 timestamp: 1655042818.4925876 iteration: 43930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07659 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.14796 L1 loss: 0.0000e+00 L2 loss: 0.59701 Learning rate: 0.002 Mask loss: 0.10105 RPN box loss: 0.01781 RPN score loss: 0.00329 RPN total loss: 0.0211 Total loss: 0.86712 timestamp: 1655042821.7448697 iteration: 43935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15782 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.22993 L1 loss: 0.0000e+00 L2 loss: 0.59701 Learning rate: 0.002 Mask loss: 0.19109 RPN box loss: 0.00976 RPN score loss: 0.00578 RPN total loss: 0.01554 Total loss: 1.03356 timestamp: 1655042824.9985871 iteration: 43940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0862 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.14906 L1 loss: 0.0000e+00 L2 loss: 0.597 Learning rate: 0.002 Mask loss: 0.17229 RPN box loss: 0.03353 RPN score loss: 0.00565 RPN total loss: 0.03917 Total loss: 0.95752 timestamp: 1655042828.2045074 iteration: 43945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09664 FastRCNN class loss: 0.08383 FastRCNN total loss: 0.18047 L1 loss: 0.0000e+00 L2 loss: 0.59699 Learning rate: 0.002 Mask loss: 0.18514 RPN box loss: 0.01816 RPN score loss: 0.00368 RPN total loss: 0.02184 Total loss: 0.98444 timestamp: 1655042831.4757721 iteration: 43950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16053 FastRCNN class loss: 0.12404 FastRCNN total loss: 0.28457 L1 loss: 0.0000e+00 L2 loss: 0.59698 Learning rate: 0.002 Mask loss: 0.16655 RPN box loss: 0.01584 RPN score loss: 0.01066 RPN total loss: 0.02649 Total loss: 1.07459 timestamp: 1655042834.7737305 iteration: 43955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10261 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.18364 L1 loss: 0.0000e+00 L2 loss: 0.59697 Learning rate: 0.002 Mask loss: 0.16986 RPN box loss: 0.00854 RPN score loss: 0.00347 RPN total loss: 0.01201 Total loss: 0.96248 timestamp: 1655042837.9830914 iteration: 43960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13185 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.20208 L1 loss: 0.0000e+00 L2 loss: 0.59696 Learning rate: 0.002 Mask loss: 0.14092 RPN box loss: 0.02843 RPN score loss: 0.00537 RPN total loss: 0.0338 Total loss: 0.97376 timestamp: 1655042841.311357 iteration: 43965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16156 FastRCNN class loss: 0.09169 FastRCNN total loss: 0.25325 L1 loss: 0.0000e+00 L2 loss: 0.59695 Learning rate: 0.002 Mask loss: 0.24091 RPN box loss: 0.02553 RPN score loss: 0.01294 RPN total loss: 0.03847 Total loss: 1.12958 timestamp: 1655042844.6026912 iteration: 43970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09531 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.17837 L1 loss: 0.0000e+00 L2 loss: 0.59695 Learning rate: 0.002 Mask loss: 0.13402 RPN box loss: 0.01716 RPN score loss: 0.00811 RPN total loss: 0.02527 Total loss: 0.93461 timestamp: 1655042847.8761652 iteration: 43975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11013 FastRCNN class loss: 0.09736 FastRCNN total loss: 0.2075 L1 loss: 0.0000e+00 L2 loss: 0.59694 Learning rate: 0.002 Mask loss: 0.14731 RPN box loss: 0.03333 RPN score loss: 0.00914 RPN total loss: 0.04247 Total loss: 0.99422 timestamp: 1655042851.1245704 iteration: 43980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08735 FastRCNN class loss: 0.08087 FastRCNN total loss: 0.16821 L1 loss: 0.0000e+00 L2 loss: 0.59693 Learning rate: 0.002 Mask loss: 0.19152 RPN box loss: 0.03912 RPN score loss: 0.00849 RPN total loss: 0.04761 Total loss: 1.00427 timestamp: 1655042854.3885033 iteration: 43985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16677 FastRCNN class loss: 0.05263 FastRCNN total loss: 0.21939 L1 loss: 0.0000e+00 L2 loss: 0.59692 Learning rate: 0.002 Mask loss: 0.10372 RPN box loss: 0.0069 RPN score loss: 0.00272 RPN total loss: 0.00962 Total loss: 0.92965 timestamp: 1655042857.6375093 iteration: 43990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1394 FastRCNN class loss: 0.09467 FastRCNN total loss: 0.23406 L1 loss: 0.0000e+00 L2 loss: 0.59691 Learning rate: 0.002 Mask loss: 0.1662 RPN box loss: 0.0097 RPN score loss: 0.00284 RPN total loss: 0.01254 Total loss: 1.0097 timestamp: 1655042860.9097712 iteration: 43995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07904 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.14055 L1 loss: 0.0000e+00 L2 loss: 0.59689 Learning rate: 0.002 Mask loss: 0.1103 RPN box loss: 0.01445 RPN score loss: 0.00558 RPN total loss: 0.02003 Total loss: 0.86778 timestamp: 1655042864.2279804 iteration: 44000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19145 FastRCNN class loss: 0.08427 FastRCNN total loss: 0.27572 L1 loss: 0.0000e+00 L2 loss: 0.59688 Learning rate: 0.002 Mask loss: 0.13023 RPN box loss: 0.02337 RPN score loss: 0.00686 RPN total loss: 0.03023 Total loss: 1.03306 timestamp: 1655042867.5318823 iteration: 44005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11108 FastRCNN class loss: 0.13442 FastRCNN total loss: 0.2455 L1 loss: 0.0000e+00 L2 loss: 0.59687 Learning rate: 0.002 Mask loss: 0.16105 RPN box loss: 0.0071 RPN score loss: 0.00455 RPN total loss: 0.01165 Total loss: 1.01507 timestamp: 1655042870.8458037 iteration: 44010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14521 FastRCNN class loss: 0.08628 FastRCNN total loss: 0.2315 L1 loss: 0.0000e+00 L2 loss: 0.59687 Learning rate: 0.002 Mask loss: 0.14274 RPN box loss: 0.0274 RPN score loss: 0.01084 RPN total loss: 0.03824 Total loss: 1.00935 timestamp: 1655042874.074832 iteration: 44015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11951 FastRCNN class loss: 0.05804 FastRCNN total loss: 0.17755 L1 loss: 0.0000e+00 L2 loss: 0.59686 Learning rate: 0.002 Mask loss: 0.11493 RPN box loss: 0.01106 RPN score loss: 0.00739 RPN total loss: 0.01846 Total loss: 0.9078 timestamp: 1655042877.374444 iteration: 44020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.08635 FastRCNN total loss: 0.19634 L1 loss: 0.0000e+00 L2 loss: 0.59684 Learning rate: 0.002 Mask loss: 0.15938 RPN box loss: 0.0625 RPN score loss: 0.00717 RPN total loss: 0.06967 Total loss: 1.02223 timestamp: 1655042880.6558063 iteration: 44025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11957 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.18956 L1 loss: 0.0000e+00 L2 loss: 0.59684 Learning rate: 0.002 Mask loss: 0.16903 RPN box loss: 0.01671 RPN score loss: 0.00641 RPN total loss: 0.02312 Total loss: 0.97855 timestamp: 1655042883.9122186 iteration: 44030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13215 FastRCNN class loss: 0.08883 FastRCNN total loss: 0.22098 L1 loss: 0.0000e+00 L2 loss: 0.59683 Learning rate: 0.002 Mask loss: 0.16463 RPN box loss: 0.01022 RPN score loss: 0.00294 RPN total loss: 0.01316 Total loss: 0.9956 timestamp: 1655042887.1989858 iteration: 44035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11917 FastRCNN class loss: 0.072 FastRCNN total loss: 0.19117 L1 loss: 0.0000e+00 L2 loss: 0.59682 Learning rate: 0.002 Mask loss: 0.12716 RPN box loss: 0.02847 RPN score loss: 0.01009 RPN total loss: 0.03857 Total loss: 0.95372 timestamp: 1655042890.5061548 iteration: 44040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14108 FastRCNN class loss: 0.13722 FastRCNN total loss: 0.27831 L1 loss: 0.0000e+00 L2 loss: 0.59681 Learning rate: 0.002 Mask loss: 0.23494 RPN box loss: 0.02261 RPN score loss: 0.0111 RPN total loss: 0.03371 Total loss: 1.14378 timestamp: 1655042893.776553 iteration: 44045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08121 FastRCNN class loss: 0.05316 FastRCNN total loss: 0.13437 L1 loss: 0.0000e+00 L2 loss: 0.59681 Learning rate: 0.002 Mask loss: 0.17167 RPN box loss: 0.0177 RPN score loss: 0.00435 RPN total loss: 0.02206 Total loss: 0.9249 timestamp: 1655042897.0437493 iteration: 44050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07269 FastRCNN class loss: 0.04122 FastRCNN total loss: 0.11392 L1 loss: 0.0000e+00 L2 loss: 0.5968 Learning rate: 0.002 Mask loss: 0.09792 RPN box loss: 0.00598 RPN score loss: 0.00214 RPN total loss: 0.00813 Total loss: 0.81676 timestamp: 1655042900.3313305 iteration: 44055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09915 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.15152 L1 loss: 0.0000e+00 L2 loss: 0.59679 Learning rate: 0.002 Mask loss: 0.13036 RPN box loss: 0.0384 RPN score loss: 0.01077 RPN total loss: 0.04916 Total loss: 0.92784 timestamp: 1655042903.567179 iteration: 44060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18138 FastRCNN class loss: 0.07235 FastRCNN total loss: 0.25372 L1 loss: 0.0000e+00 L2 loss: 0.59678 Learning rate: 0.002 Mask loss: 0.11733 RPN box loss: 0.04244 RPN score loss: 0.00624 RPN total loss: 0.04868 Total loss: 1.01652 timestamp: 1655042906.8628418 iteration: 44065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12891 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.17894 L1 loss: 0.0000e+00 L2 loss: 0.59677 Learning rate: 0.002 Mask loss: 0.14367 RPN box loss: 0.01884 RPN score loss: 0.00552 RPN total loss: 0.02436 Total loss: 0.94374 timestamp: 1655042910.151902 iteration: 44070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.59676 Learning rate: 0.002 Mask loss: 0.14268 RPN box loss: 0.00649 RPN score loss: 0.00375 RPN total loss: 0.01024 Total loss: 0.92608 timestamp: 1655042913.4720006 iteration: 44075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07796 FastRCNN class loss: 0.06986 FastRCNN total loss: 0.14782 L1 loss: 0.0000e+00 L2 loss: 0.59675 Learning rate: 0.002 Mask loss: 0.15225 RPN box loss: 0.0091 RPN score loss: 0.00391 RPN total loss: 0.01301 Total loss: 0.90983 timestamp: 1655042916.7229056 iteration: 44080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12749 FastRCNN class loss: 0.07077 FastRCNN total loss: 0.19825 L1 loss: 0.0000e+00 L2 loss: 0.59674 Learning rate: 0.002 Mask loss: 0.20656 RPN box loss: 0.03184 RPN score loss: 0.01025 RPN total loss: 0.04209 Total loss: 1.04364 timestamp: 1655042919.8951218 iteration: 44085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15627 FastRCNN class loss: 0.09077 FastRCNN total loss: 0.24704 L1 loss: 0.0000e+00 L2 loss: 0.59673 Learning rate: 0.002 Mask loss: 0.19949 RPN box loss: 0.0247 RPN score loss: 0.01187 RPN total loss: 0.03657 Total loss: 1.07984 timestamp: 1655042923.134092 iteration: 44090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1173 FastRCNN class loss: 0.11577 FastRCNN total loss: 0.23307 L1 loss: 0.0000e+00 L2 loss: 0.59673 Learning rate: 0.002 Mask loss: 0.14961 RPN box loss: 0.01799 RPN score loss: 0.01022 RPN total loss: 0.02821 Total loss: 1.00762 timestamp: 1655042926.3888113 iteration: 44095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07129 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.1415 L1 loss: 0.0000e+00 L2 loss: 0.59672 Learning rate: 0.002 Mask loss: 0.10375 RPN box loss: 0.00829 RPN score loss: 0.00395 RPN total loss: 0.01225 Total loss: 0.85421 timestamp: 1655042929.632158 iteration: 44100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.20724 L1 loss: 0.0000e+00 L2 loss: 0.5967 Learning rate: 0.002 Mask loss: 0.12991 RPN box loss: 0.03234 RPN score loss: 0.0065 RPN total loss: 0.03885 Total loss: 0.9727 timestamp: 1655042932.8768632 iteration: 44105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13561 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.19467 L1 loss: 0.0000e+00 L2 loss: 0.5967 Learning rate: 0.002 Mask loss: 0.17381 RPN box loss: 0.00854 RPN score loss: 0.00552 RPN total loss: 0.01406 Total loss: 0.97923 timestamp: 1655042936.1682637 iteration: 44110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11686 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.19023 L1 loss: 0.0000e+00 L2 loss: 0.59669 Learning rate: 0.002 Mask loss: 0.14297 RPN box loss: 0.03477 RPN score loss: 0.00943 RPN total loss: 0.0442 Total loss: 0.97409 timestamp: 1655042939.4482048 iteration: 44115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.11229 FastRCNN total loss: 0.2127 L1 loss: 0.0000e+00 L2 loss: 0.59668 Learning rate: 0.002 Mask loss: 0.13567 RPN box loss: 0.03134 RPN score loss: 0.01293 RPN total loss: 0.04427 Total loss: 0.98932 timestamp: 1655042942.7297485 iteration: 44120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11795 FastRCNN class loss: 0.06779 FastRCNN total loss: 0.18574 L1 loss: 0.0000e+00 L2 loss: 0.59667 Learning rate: 0.002 Mask loss: 0.16874 RPN box loss: 0.0439 RPN score loss: 0.01759 RPN total loss: 0.06149 Total loss: 1.01264 timestamp: 1655042946.0290937 iteration: 44125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18991 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.27486 L1 loss: 0.0000e+00 L2 loss: 0.59666 Learning rate: 0.002 Mask loss: 0.14219 RPN box loss: 0.02631 RPN score loss: 0.00597 RPN total loss: 0.03228 Total loss: 1.046 timestamp: 1655042949.2770045 iteration: 44130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12195 FastRCNN class loss: 0.1723 FastRCNN total loss: 0.29425 L1 loss: 0.0000e+00 L2 loss: 0.59665 Learning rate: 0.002 Mask loss: 0.23271 RPN box loss: 0.0409 RPN score loss: 0.10702 RPN total loss: 0.14792 Total loss: 1.27153 timestamp: 1655042952.5898576 iteration: 44135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09212 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.1488 L1 loss: 0.0000e+00 L2 loss: 0.59664 Learning rate: 0.002 Mask loss: 0.13006 RPN box loss: 0.01552 RPN score loss: 0.00372 RPN total loss: 0.01925 Total loss: 0.89475 timestamp: 1655042955.8347118 iteration: 44140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15226 FastRCNN class loss: 0.05936 FastRCNN total loss: 0.21163 L1 loss: 0.0000e+00 L2 loss: 0.59663 Learning rate: 0.002 Mask loss: 0.12577 RPN box loss: 0.03547 RPN score loss: 0.00458 RPN total loss: 0.04005 Total loss: 0.97407 timestamp: 1655042959.1236718 iteration: 44145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1591 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.25822 L1 loss: 0.0000e+00 L2 loss: 0.59662 Learning rate: 0.002 Mask loss: 0.16323 RPN box loss: 0.05331 RPN score loss: 0.00706 RPN total loss: 0.06037 Total loss: 1.07844 timestamp: 1655042962.3495803 iteration: 44150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11258 FastRCNN class loss: 0.07317 FastRCNN total loss: 0.18575 L1 loss: 0.0000e+00 L2 loss: 0.59661 Learning rate: 0.002 Mask loss: 0.1633 RPN box loss: 0.02328 RPN score loss: 0.01125 RPN total loss: 0.03453 Total loss: 0.98019 timestamp: 1655042965.6661417 iteration: 44155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.15968 L1 loss: 0.0000e+00 L2 loss: 0.5966 Learning rate: 0.002 Mask loss: 0.18693 RPN box loss: 0.04338 RPN score loss: 0.00435 RPN total loss: 0.04773 Total loss: 0.99093 timestamp: 1655042968.9213216 iteration: 44160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06513 FastRCNN class loss: 0.04723 FastRCNN total loss: 0.11236 L1 loss: 0.0000e+00 L2 loss: 0.59659 Learning rate: 0.002 Mask loss: 0.0862 RPN box loss: 0.02191 RPN score loss: 0.00255 RPN total loss: 0.02446 Total loss: 0.81961 timestamp: 1655042972.2240078 iteration: 44165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09 FastRCNN class loss: 0.04541 FastRCNN total loss: 0.1354 L1 loss: 0.0000e+00 L2 loss: 0.59658 Learning rate: 0.002 Mask loss: 0.17881 RPN box loss: 0.01603 RPN score loss: 0.01639 RPN total loss: 0.03242 Total loss: 0.94321 timestamp: 1655042975.483048 iteration: 44170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09753 FastRCNN class loss: 0.07794 FastRCNN total loss: 0.17547 L1 loss: 0.0000e+00 L2 loss: 0.59657 Learning rate: 0.002 Mask loss: 0.174 RPN box loss: 0.01698 RPN score loss: 0.00793 RPN total loss: 0.02491 Total loss: 0.97094 timestamp: 1655042978.749609 iteration: 44175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06181 FastRCNN class loss: 0.05408 FastRCNN total loss: 0.11589 L1 loss: 0.0000e+00 L2 loss: 0.59656 Learning rate: 0.002 Mask loss: 0.10938 RPN box loss: 0.01135 RPN score loss: 0.00314 RPN total loss: 0.01449 Total loss: 0.83632 timestamp: 1655042982.0870395 iteration: 44180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12941 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.18951 L1 loss: 0.0000e+00 L2 loss: 0.59655 Learning rate: 0.002 Mask loss: 0.15915 RPN box loss: 0.03969 RPN score loss: 0.00798 RPN total loss: 0.04767 Total loss: 0.99288 timestamp: 1655042985.3722124 iteration: 44185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07262 FastRCNN class loss: 0.03061 FastRCNN total loss: 0.10323 L1 loss: 0.0000e+00 L2 loss: 0.59654 Learning rate: 0.002 Mask loss: 0.15239 RPN box loss: 0.00293 RPN score loss: 0.00248 RPN total loss: 0.00541 Total loss: 0.85758 timestamp: 1655042988.640873 iteration: 44190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11831 FastRCNN class loss: 0.08956 FastRCNN total loss: 0.20787 L1 loss: 0.0000e+00 L2 loss: 0.59654 Learning rate: 0.002 Mask loss: 0.16251 RPN box loss: 0.01889 RPN score loss: 0.00748 RPN total loss: 0.02637 Total loss: 0.99328 timestamp: 1655042991.896478 iteration: 44195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16503 FastRCNN class loss: 0.14663 FastRCNN total loss: 0.31166 L1 loss: 0.0000e+00 L2 loss: 0.59653 Learning rate: 0.002 Mask loss: 0.22517 RPN box loss: 0.03528 RPN score loss: 0.01007 RPN total loss: 0.04536 Total loss: 1.17871 timestamp: 1655042995.1614275 iteration: 44200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10375 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.16912 L1 loss: 0.0000e+00 L2 loss: 0.59652 Learning rate: 0.002 Mask loss: 0.12971 RPN box loss: 0.02597 RPN score loss: 0.01777 RPN total loss: 0.04374 Total loss: 0.93909 timestamp: 1655042998.456944 iteration: 44205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08543 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.15561 L1 loss: 0.0000e+00 L2 loss: 0.59651 Learning rate: 0.002 Mask loss: 0.14032 RPN box loss: 0.00993 RPN score loss: 0.00271 RPN total loss: 0.01264 Total loss: 0.90508 timestamp: 1655043001.7093046 iteration: 44210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.04119 FastRCNN total loss: 0.14644 L1 loss: 0.0000e+00 L2 loss: 0.5965 Learning rate: 0.002 Mask loss: 0.11708 RPN box loss: 0.0165 RPN score loss: 0.00678 RPN total loss: 0.02329 Total loss: 0.8833 timestamp: 1655043004.9616702 iteration: 44215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07428 FastRCNN class loss: 0.04863 FastRCNN total loss: 0.1229 L1 loss: 0.0000e+00 L2 loss: 0.59649 Learning rate: 0.002 Mask loss: 0.16036 RPN box loss: 0.00421 RPN score loss: 0.00171 RPN total loss: 0.00592 Total loss: 0.88568 timestamp: 1655043008.2885644 iteration: 44220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.05836 FastRCNN total loss: 0.14601 L1 loss: 0.0000e+00 L2 loss: 0.59648 Learning rate: 0.002 Mask loss: 0.12391 RPN box loss: 0.02009 RPN score loss: 0.00411 RPN total loss: 0.0242 Total loss: 0.89059 timestamp: 1655043011.5484686 iteration: 44225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09022 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.15594 L1 loss: 0.0000e+00 L2 loss: 0.59646 Learning rate: 0.002 Mask loss: 0.11761 RPN box loss: 0.03339 RPN score loss: 0.00818 RPN total loss: 0.04157 Total loss: 0.91158 timestamp: 1655043014.7953782 iteration: 44230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15131 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.22693 L1 loss: 0.0000e+00 L2 loss: 0.59645 Learning rate: 0.002 Mask loss: 0.12992 RPN box loss: 0.01224 RPN score loss: 0.00707 RPN total loss: 0.01931 Total loss: 0.97262 timestamp: 1655043018.0839667 iteration: 44235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21074 FastRCNN class loss: 0.08025 FastRCNN total loss: 0.29099 L1 loss: 0.0000e+00 L2 loss: 0.59645 Learning rate: 0.002 Mask loss: 0.16391 RPN box loss: 0.02124 RPN score loss: 0.00505 RPN total loss: 0.02629 Total loss: 1.07764 timestamp: 1655043021.3761895 iteration: 44240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09307 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.18085 L1 loss: 0.0000e+00 L2 loss: 0.59644 Learning rate: 0.002 Mask loss: 0.18157 RPN box loss: 0.00837 RPN score loss: 0.00385 RPN total loss: 0.01222 Total loss: 0.97108 timestamp: 1655043024.6749823 iteration: 44245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10124 FastRCNN class loss: 0.05991 FastRCNN total loss: 0.16114 L1 loss: 0.0000e+00 L2 loss: 0.59643 Learning rate: 0.002 Mask loss: 0.1841 RPN box loss: 0.01649 RPN score loss: 0.00697 RPN total loss: 0.02346 Total loss: 0.96514 timestamp: 1655043028.01694 iteration: 44250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04943 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.11784 L1 loss: 0.0000e+00 L2 loss: 0.59642 Learning rate: 0.002 Mask loss: 0.12238 RPN box loss: 0.00554 RPN score loss: 0.00656 RPN total loss: 0.0121 Total loss: 0.84874 timestamp: 1655043031.2524815 iteration: 44255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10517 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.16783 L1 loss: 0.0000e+00 L2 loss: 0.59642 Learning rate: 0.002 Mask loss: 0.09833 RPN box loss: 0.03124 RPN score loss: 0.00353 RPN total loss: 0.03477 Total loss: 0.89735 timestamp: 1655043034.4593618 iteration: 44260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07995 FastRCNN class loss: 0.08692 FastRCNN total loss: 0.16687 L1 loss: 0.0000e+00 L2 loss: 0.59641 Learning rate: 0.002 Mask loss: 0.18407 RPN box loss: 0.0122 RPN score loss: 0.00149 RPN total loss: 0.01369 Total loss: 0.96104 timestamp: 1655043037.7458744 iteration: 44265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06076 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.15693 L1 loss: 0.0000e+00 L2 loss: 0.5964 Learning rate: 0.002 Mask loss: 0.11319 RPN box loss: 0.025 RPN score loss: 0.02068 RPN total loss: 0.04568 Total loss: 0.9122 timestamp: 1655043041.0342376 iteration: 44270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12207 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.20092 L1 loss: 0.0000e+00 L2 loss: 0.59639 Learning rate: 0.002 Mask loss: 0.16271 RPN box loss: 0.01329 RPN score loss: 0.00559 RPN total loss: 0.01888 Total loss: 0.9789 timestamp: 1655043044.3441234 iteration: 44275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.18448 L1 loss: 0.0000e+00 L2 loss: 0.59638 Learning rate: 0.002 Mask loss: 0.14118 RPN box loss: 0.01187 RPN score loss: 0.00179 RPN total loss: 0.01366 Total loss: 0.93569 timestamp: 1655043047.6608653 iteration: 44280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09351 FastRCNN class loss: 0.04445 FastRCNN total loss: 0.13796 L1 loss: 0.0000e+00 L2 loss: 0.59637 Learning rate: 0.002 Mask loss: 0.13125 RPN box loss: 0.02779 RPN score loss: 0.00319 RPN total loss: 0.03099 Total loss: 0.89656 timestamp: 1655043051.017266 iteration: 44285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12235 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.20197 L1 loss: 0.0000e+00 L2 loss: 0.59636 Learning rate: 0.002 Mask loss: 0.19013 RPN box loss: 0.01868 RPN score loss: 0.00411 RPN total loss: 0.02279 Total loss: 1.01125 timestamp: 1655043054.1835613 iteration: 44290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09804 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.15872 L1 loss: 0.0000e+00 L2 loss: 0.59635 Learning rate: 0.002 Mask loss: 0.1611 RPN box loss: 0.02789 RPN score loss: 0.01147 RPN total loss: 0.03936 Total loss: 0.95552 timestamp: 1655043057.4675891 iteration: 44295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12887 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.19439 L1 loss: 0.0000e+00 L2 loss: 0.59634 Learning rate: 0.002 Mask loss: 0.1586 RPN box loss: 0.01815 RPN score loss: 0.00711 RPN total loss: 0.02526 Total loss: 0.97459 timestamp: 1655043060.6944087 iteration: 44300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.06172 FastRCNN total loss: 0.14097 L1 loss: 0.0000e+00 L2 loss: 0.59633 Learning rate: 0.002 Mask loss: 0.15216 RPN box loss: 0.01841 RPN score loss: 0.0072 RPN total loss: 0.0256 Total loss: 0.91507 timestamp: 1655043063.931868 iteration: 44305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0701 FastRCNN class loss: 0.07983 FastRCNN total loss: 0.14994 L1 loss: 0.0000e+00 L2 loss: 0.59632 Learning rate: 0.002 Mask loss: 0.12017 RPN box loss: 0.01439 RPN score loss: 0.00491 RPN total loss: 0.0193 Total loss: 0.88573 timestamp: 1655043067.1466334 iteration: 44310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1529 FastRCNN class loss: 0.087 FastRCNN total loss: 0.2399 L1 loss: 0.0000e+00 L2 loss: 0.59631 Learning rate: 0.002 Mask loss: 0.1378 RPN box loss: 0.03251 RPN score loss: 0.00215 RPN total loss: 0.03465 Total loss: 1.00868 timestamp: 1655043070.3802269 iteration: 44315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09868 FastRCNN class loss: 0.08332 FastRCNN total loss: 0.182 L1 loss: 0.0000e+00 L2 loss: 0.59631 Learning rate: 0.002 Mask loss: 0.15872 RPN box loss: 0.05111 RPN score loss: 0.00555 RPN total loss: 0.05666 Total loss: 0.99369 timestamp: 1655043073.6561964 iteration: 44320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16751 FastRCNN class loss: 0.1135 FastRCNN total loss: 0.28102 L1 loss: 0.0000e+00 L2 loss: 0.5963 Learning rate: 0.002 Mask loss: 0.16383 RPN box loss: 0.05029 RPN score loss: 0.01294 RPN total loss: 0.06323 Total loss: 1.10438 timestamp: 1655043076.8997612 iteration: 44325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14494 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.21647 L1 loss: 0.0000e+00 L2 loss: 0.59629 Learning rate: 0.002 Mask loss: 0.11086 RPN box loss: 0.02731 RPN score loss: 0.04037 RPN total loss: 0.06768 Total loss: 0.9913 timestamp: 1655043080.2643611 iteration: 44330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08383 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.59628 Learning rate: 0.002 Mask loss: 0.14566 RPN box loss: 0.03353 RPN score loss: 0.00118 RPN total loss: 0.03471 Total loss: 0.92866 timestamp: 1655043083.4749062 iteration: 44335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13811 FastRCNN class loss: 0.07252 FastRCNN total loss: 0.21063 L1 loss: 0.0000e+00 L2 loss: 0.59627 Learning rate: 0.002 Mask loss: 0.13307 RPN box loss: 0.03184 RPN score loss: 0.00353 RPN total loss: 0.03537 Total loss: 0.97534 timestamp: 1655043086.7767382 iteration: 44340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11595 FastRCNN class loss: 0.04253 FastRCNN total loss: 0.15848 L1 loss: 0.0000e+00 L2 loss: 0.59626 Learning rate: 0.002 Mask loss: 0.09896 RPN box loss: 0.01124 RPN score loss: 0.00609 RPN total loss: 0.01734 Total loss: 0.87104 timestamp: 1655043090.0670676 iteration: 44345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08299 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.15802 L1 loss: 0.0000e+00 L2 loss: 0.59625 Learning rate: 0.002 Mask loss: 0.09354 RPN box loss: 0.02627 RPN score loss: 0.0025 RPN total loss: 0.02877 Total loss: 0.87658 timestamp: 1655043093.3214335 iteration: 44350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19495 FastRCNN class loss: 0.13998 FastRCNN total loss: 0.33492 L1 loss: 0.0000e+00 L2 loss: 0.59625 Learning rate: 0.002 Mask loss: 0.21085 RPN box loss: 0.02504 RPN score loss: 0.00801 RPN total loss: 0.03305 Total loss: 1.17507 timestamp: 1655043096.5401256 iteration: 44355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.18073 L1 loss: 0.0000e+00 L2 loss: 0.59624 Learning rate: 0.002 Mask loss: 0.16875 RPN box loss: 0.01475 RPN score loss: 0.00353 RPN total loss: 0.01828 Total loss: 0.964 timestamp: 1655043099.788362 iteration: 44360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06958 FastRCNN class loss: 0.06426 FastRCNN total loss: 0.13384 L1 loss: 0.0000e+00 L2 loss: 0.59622 Learning rate: 0.002 Mask loss: 0.12061 RPN box loss: 0.01687 RPN score loss: 0.00141 RPN total loss: 0.01829 Total loss: 0.86896 timestamp: 1655043103.0980067 iteration: 44365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.05363 FastRCNN total loss: 0.15729 L1 loss: 0.0000e+00 L2 loss: 0.59621 Learning rate: 0.002 Mask loss: 0.12477 RPN box loss: 0.02173 RPN score loss: 0.00847 RPN total loss: 0.0302 Total loss: 0.90847 timestamp: 1655043106.36274 iteration: 44370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.08924 FastRCNN total loss: 0.19352 L1 loss: 0.0000e+00 L2 loss: 0.59621 Learning rate: 0.002 Mask loss: 0.1601 RPN box loss: 0.00897 RPN score loss: 0.00188 RPN total loss: 0.01085 Total loss: 0.96067 timestamp: 1655043109.5892813 iteration: 44375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17495 FastRCNN class loss: 0.09887 FastRCNN total loss: 0.27382 L1 loss: 0.0000e+00 L2 loss: 0.5962 Learning rate: 0.002 Mask loss: 0.1674 RPN box loss: 0.02294 RPN score loss: 0.00741 RPN total loss: 0.03035 Total loss: 1.06777 timestamp: 1655043112.8505647 iteration: 44380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09724 FastRCNN class loss: 0.07513 FastRCNN total loss: 0.17237 L1 loss: 0.0000e+00 L2 loss: 0.59619 Learning rate: 0.002 Mask loss: 0.12332 RPN box loss: 0.00829 RPN score loss: 0.01106 RPN total loss: 0.01935 Total loss: 0.91122 timestamp: 1655043116.2034533 iteration: 44385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14285 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.21724 L1 loss: 0.0000e+00 L2 loss: 0.59618 Learning rate: 0.002 Mask loss: 0.15485 RPN box loss: 0.01881 RPN score loss: 0.0017 RPN total loss: 0.02051 Total loss: 0.98877 timestamp: 1655043119.4346492 iteration: 44390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07294 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.13246 L1 loss: 0.0000e+00 L2 loss: 0.59617 Learning rate: 0.002 Mask loss: 0.09819 RPN box loss: 0.01649 RPN score loss: 0.00837 RPN total loss: 0.02486 Total loss: 0.85167 timestamp: 1655043122.7237244 iteration: 44395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13924 FastRCNN class loss: 0.12959 FastRCNN total loss: 0.26884 L1 loss: 0.0000e+00 L2 loss: 0.59616 Learning rate: 0.002 Mask loss: 0.17384 RPN box loss: 0.02603 RPN score loss: 0.01562 RPN total loss: 0.04165 Total loss: 1.08048 timestamp: 1655043126.0398934 iteration: 44400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09848 FastRCNN class loss: 0.08839 FastRCNN total loss: 0.18687 L1 loss: 0.0000e+00 L2 loss: 0.59615 Learning rate: 0.002 Mask loss: 0.14187 RPN box loss: 0.01649 RPN score loss: 0.00323 RPN total loss: 0.01971 Total loss: 0.94461 timestamp: 1655043129.3855166 iteration: 44405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0651 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.12367 L1 loss: 0.0000e+00 L2 loss: 0.59614 Learning rate: 0.002 Mask loss: 0.25655 RPN box loss: 0.02687 RPN score loss: 0.00158 RPN total loss: 0.02845 Total loss: 1.00481 timestamp: 1655043132.6880639 iteration: 44410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15767 FastRCNN class loss: 0.10368 FastRCNN total loss: 0.26135 L1 loss: 0.0000e+00 L2 loss: 0.59613 Learning rate: 0.002 Mask loss: 0.1849 RPN box loss: 0.02384 RPN score loss: 0.00227 RPN total loss: 0.02611 Total loss: 1.0685 timestamp: 1655043135.9037771 iteration: 44415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11609 FastRCNN class loss: 0.08154 FastRCNN total loss: 0.19763 L1 loss: 0.0000e+00 L2 loss: 0.59612 Learning rate: 0.002 Mask loss: 0.19647 RPN box loss: 0.03343 RPN score loss: 0.00892 RPN total loss: 0.04234 Total loss: 1.03256 timestamp: 1655043139.1875372 iteration: 44420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12519 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.19487 L1 loss: 0.0000e+00 L2 loss: 0.59611 Learning rate: 0.002 Mask loss: 0.0975 RPN box loss: 0.01318 RPN score loss: 0.00052 RPN total loss: 0.0137 Total loss: 0.90219 timestamp: 1655043142.537927 iteration: 44425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10559 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.17571 L1 loss: 0.0000e+00 L2 loss: 0.5961 Learning rate: 0.002 Mask loss: 0.12148 RPN box loss: 0.01561 RPN score loss: 0.00911 RPN total loss: 0.02472 Total loss: 0.918 timestamp: 1655043145.8320835 iteration: 44430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16385 FastRCNN class loss: 0.06154 FastRCNN total loss: 0.22538 L1 loss: 0.0000e+00 L2 loss: 0.59609 Learning rate: 0.002 Mask loss: 0.11915 RPN box loss: 0.01718 RPN score loss: 0.0042 RPN total loss: 0.02138 Total loss: 0.96201 timestamp: 1655043149.1081984 iteration: 44435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15969 FastRCNN class loss: 0.11212 FastRCNN total loss: 0.27181 L1 loss: 0.0000e+00 L2 loss: 0.59609 Learning rate: 0.002 Mask loss: 0.1986 RPN box loss: 0.05543 RPN score loss: 0.00853 RPN total loss: 0.06396 Total loss: 1.13046 timestamp: 1655043152.4185917 iteration: 44440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10074 FastRCNN class loss: 0.0865 FastRCNN total loss: 0.18723 L1 loss: 0.0000e+00 L2 loss: 0.59608 Learning rate: 0.002 Mask loss: 0.17691 RPN box loss: 0.02504 RPN score loss: 0.00773 RPN total loss: 0.03276 Total loss: 0.99298 timestamp: 1655043155.709623 iteration: 44445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1536 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.24341 L1 loss: 0.0000e+00 L2 loss: 0.59606 Learning rate: 0.002 Mask loss: 0.1648 RPN box loss: 0.041 RPN score loss: 0.00782 RPN total loss: 0.04882 Total loss: 1.05308 timestamp: 1655043158.9602501 iteration: 44450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.18286 L1 loss: 0.0000e+00 L2 loss: 0.59605 Learning rate: 0.002 Mask loss: 0.13854 RPN box loss: 0.0263 RPN score loss: 0.01508 RPN total loss: 0.04139 Total loss: 0.95884 timestamp: 1655043162.317869 iteration: 44455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12911 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.19758 L1 loss: 0.0000e+00 L2 loss: 0.59605 Learning rate: 0.002 Mask loss: 0.18996 RPN box loss: 0.01799 RPN score loss: 0.01025 RPN total loss: 0.02824 Total loss: 1.01182 timestamp: 1655043165.5532508 iteration: 44460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18915 FastRCNN class loss: 0.10055 FastRCNN total loss: 0.28971 L1 loss: 0.0000e+00 L2 loss: 0.59604 Learning rate: 0.002 Mask loss: 0.19068 RPN box loss: 0.01143 RPN score loss: 0.00441 RPN total loss: 0.01585 Total loss: 1.09227 timestamp: 1655043168.7925897 iteration: 44465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14022 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.20209 L1 loss: 0.0000e+00 L2 loss: 0.59603 Learning rate: 0.002 Mask loss: 0.12895 RPN box loss: 0.03738 RPN score loss: 0.00829 RPN total loss: 0.04568 Total loss: 0.97275 timestamp: 1655043172.0505629 iteration: 44470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11708 FastRCNN class loss: 0.09823 FastRCNN total loss: 0.21532 L1 loss: 0.0000e+00 L2 loss: 0.59602 Learning rate: 0.002 Mask loss: 0.18054 RPN box loss: 0.02204 RPN score loss: 0.00449 RPN total loss: 0.02652 Total loss: 1.01841 timestamp: 1655043175.3645308 iteration: 44475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14697 FastRCNN class loss: 0.10698 FastRCNN total loss: 0.25395 L1 loss: 0.0000e+00 L2 loss: 0.59601 Learning rate: 0.002 Mask loss: 0.14881 RPN box loss: 0.01529 RPN score loss: 0.00775 RPN total loss: 0.02304 Total loss: 1.02181 timestamp: 1655043178.6240335 iteration: 44480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.16817 L1 loss: 0.0000e+00 L2 loss: 0.596 Learning rate: 0.002 Mask loss: 0.18557 RPN box loss: 0.0246 RPN score loss: 0.00541 RPN total loss: 0.03001 Total loss: 0.97975 timestamp: 1655043181.8942945 iteration: 44485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09326 FastRCNN class loss: 0.04808 FastRCNN total loss: 0.14134 L1 loss: 0.0000e+00 L2 loss: 0.59599 Learning rate: 0.002 Mask loss: 0.07873 RPN box loss: 0.0117 RPN score loss: 0.00397 RPN total loss: 0.01568 Total loss: 0.83173 timestamp: 1655043185.1406567 iteration: 44490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08542 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.15097 L1 loss: 0.0000e+00 L2 loss: 0.59598 Learning rate: 0.002 Mask loss: 0.09208 RPN box loss: 0.01584 RPN score loss: 0.00183 RPN total loss: 0.01767 Total loss: 0.8567 timestamp: 1655043188.3499415 iteration: 44495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.04057 FastRCNN total loss: 0.13379 L1 loss: 0.0000e+00 L2 loss: 0.59597 Learning rate: 0.002 Mask loss: 0.11519 RPN box loss: 0.02846 RPN score loss: 0.00596 RPN total loss: 0.03442 Total loss: 0.87938 timestamp: 1655043191.6193936 iteration: 44500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12811 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.18854 L1 loss: 0.0000e+00 L2 loss: 0.59597 Learning rate: 0.002 Mask loss: 0.10916 RPN box loss: 0.01157 RPN score loss: 0.00384 RPN total loss: 0.01541 Total loss: 0.90908 timestamp: 1655043194.8581178 iteration: 44505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13372 FastRCNN class loss: 0.12967 FastRCNN total loss: 0.26339 L1 loss: 0.0000e+00 L2 loss: 0.59596 Learning rate: 0.002 Mask loss: 0.17945 RPN box loss: 0.01577 RPN score loss: 0.00374 RPN total loss: 0.01951 Total loss: 1.0583 timestamp: 1655043198.1764743 iteration: 44510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16372 FastRCNN class loss: 0.08622 FastRCNN total loss: 0.24994 L1 loss: 0.0000e+00 L2 loss: 0.59595 Learning rate: 0.002 Mask loss: 0.2349 RPN box loss: 0.01236 RPN score loss: 0.00486 RPN total loss: 0.01722 Total loss: 1.09801 timestamp: 1655043201.4188569 iteration: 44515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15278 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.24812 L1 loss: 0.0000e+00 L2 loss: 0.59594 Learning rate: 0.002 Mask loss: 0.22881 RPN box loss: 0.0283 RPN score loss: 0.00745 RPN total loss: 0.03575 Total loss: 1.10861 timestamp: 1655043204.6836693 iteration: 44520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10303 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.15671 L1 loss: 0.0000e+00 L2 loss: 0.59593 Learning rate: 0.002 Mask loss: 0.14301 RPN box loss: 0.02236 RPN score loss: 0.0109 RPN total loss: 0.03326 Total loss: 0.92891 timestamp: 1655043207.964015 iteration: 44525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13593 FastRCNN class loss: 0.0986 FastRCNN total loss: 0.23453 L1 loss: 0.0000e+00 L2 loss: 0.59592 Learning rate: 0.002 Mask loss: 0.18104 RPN box loss: 0.02177 RPN score loss: 0.00246 RPN total loss: 0.02423 Total loss: 1.03572 timestamp: 1655043211.2193618 iteration: 44530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09762 FastRCNN class loss: 0.05272 FastRCNN total loss: 0.15034 L1 loss: 0.0000e+00 L2 loss: 0.59591 Learning rate: 0.002 Mask loss: 0.07107 RPN box loss: 0.00653 RPN score loss: 0.00173 RPN total loss: 0.00826 Total loss: 0.82559 timestamp: 1655043214.438876 iteration: 44535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1065 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.18157 L1 loss: 0.0000e+00 L2 loss: 0.59591 Learning rate: 0.002 Mask loss: 0.13426 RPN box loss: 0.01987 RPN score loss: 0.00391 RPN total loss: 0.02378 Total loss: 0.93552 timestamp: 1655043217.638286 iteration: 44540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11375 FastRCNN class loss: 0.12581 FastRCNN total loss: 0.23956 L1 loss: 0.0000e+00 L2 loss: 0.5959 Learning rate: 0.002 Mask loss: 0.21494 RPN box loss: 0.03353 RPN score loss: 0.02473 RPN total loss: 0.05825 Total loss: 1.10865 timestamp: 1655043220.9400902 iteration: 44545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0971 FastRCNN class loss: 0.0813 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.59589 Learning rate: 0.002 Mask loss: 0.10908 RPN box loss: 0.0119 RPN score loss: 0.00405 RPN total loss: 0.01595 Total loss: 0.89932 timestamp: 1655043224.132391 iteration: 44550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11032 FastRCNN class loss: 0.04664 FastRCNN total loss: 0.15697 L1 loss: 0.0000e+00 L2 loss: 0.59588 Learning rate: 0.002 Mask loss: 0.12544 RPN box loss: 0.00482 RPN score loss: 0.0055 RPN total loss: 0.01032 Total loss: 0.88861 timestamp: 1655043227.3726518 iteration: 44555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08556 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.16536 L1 loss: 0.0000e+00 L2 loss: 0.59587 Learning rate: 0.002 Mask loss: 0.12668 RPN box loss: 0.02465 RPN score loss: 0.00528 RPN total loss: 0.02993 Total loss: 0.91785 timestamp: 1655043230.5996313 iteration: 44560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17106 FastRCNN class loss: 0.16081 FastRCNN total loss: 0.33186 L1 loss: 0.0000e+00 L2 loss: 0.59587 Learning rate: 0.002 Mask loss: 0.24924 RPN box loss: 0.03001 RPN score loss: 0.01483 RPN total loss: 0.04484 Total loss: 1.22181 timestamp: 1655043233.8881161 iteration: 44565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.15346 L1 loss: 0.0000e+00 L2 loss: 0.59586 Learning rate: 0.002 Mask loss: 0.18249 RPN box loss: 0.02035 RPN score loss: 0.00954 RPN total loss: 0.02989 Total loss: 0.96171 timestamp: 1655043237.155727 iteration: 44570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11903 FastRCNN class loss: 0.05819 FastRCNN total loss: 0.17721 L1 loss: 0.0000e+00 L2 loss: 0.59585 Learning rate: 0.002 Mask loss: 0.10844 RPN box loss: 0.05033 RPN score loss: 0.00574 RPN total loss: 0.05607 Total loss: 0.93757 timestamp: 1655043240.4515898 iteration: 44575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.12952 L1 loss: 0.0000e+00 L2 loss: 0.59584 Learning rate: 0.002 Mask loss: 0.13229 RPN box loss: 0.01896 RPN score loss: 0.0059 RPN total loss: 0.02486 Total loss: 0.8825 timestamp: 1655043243.6910844 iteration: 44580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08107 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.13232 L1 loss: 0.0000e+00 L2 loss: 0.59583 Learning rate: 0.002 Mask loss: 0.12955 RPN box loss: 0.01506 RPN score loss: 0.00249 RPN total loss: 0.01754 Total loss: 0.87524 timestamp: 1655043246.930753 iteration: 44585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0465 FastRCNN class loss: 0.04044 FastRCNN total loss: 0.08694 L1 loss: 0.0000e+00 L2 loss: 0.59582 Learning rate: 0.002 Mask loss: 0.09762 RPN box loss: 0.00229 RPN score loss: 0.0019 RPN total loss: 0.00418 Total loss: 0.78457 timestamp: 1655043250.1787744 iteration: 44590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05832 FastRCNN class loss: 0.04075 FastRCNN total loss: 0.09906 L1 loss: 0.0000e+00 L2 loss: 0.59581 Learning rate: 0.002 Mask loss: 0.08659 RPN box loss: 0.0057 RPN score loss: 0.00183 RPN total loss: 0.00754 Total loss: 0.789 timestamp: 1655043253.431477 iteration: 44595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13176 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.21327 L1 loss: 0.0000e+00 L2 loss: 0.5958 Learning rate: 0.002 Mask loss: 0.15747 RPN box loss: 0.01054 RPN score loss: 0.00503 RPN total loss: 0.01558 Total loss: 0.98212 timestamp: 1655043256.7306619 iteration: 44600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09619 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.16567 L1 loss: 0.0000e+00 L2 loss: 0.59579 Learning rate: 0.002 Mask loss: 0.13198 RPN box loss: 0.01417 RPN score loss: 0.0068 RPN total loss: 0.02097 Total loss: 0.91442 timestamp: 1655043260.032067 iteration: 44605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05991 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.59578 Learning rate: 0.002 Mask loss: 0.13851 RPN box loss: 0.02467 RPN score loss: 0.00692 RPN total loss: 0.03159 Total loss: 0.89857 timestamp: 1655043263.2398882 iteration: 44610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14092 FastRCNN class loss: 0.07773 FastRCNN total loss: 0.21865 L1 loss: 0.0000e+00 L2 loss: 0.59577 Learning rate: 0.002 Mask loss: 0.13949 RPN box loss: 0.01043 RPN score loss: 0.0062 RPN total loss: 0.01664 Total loss: 0.97055 timestamp: 1655043266.4469895 iteration: 44615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07149 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.13602 L1 loss: 0.0000e+00 L2 loss: 0.59577 Learning rate: 0.002 Mask loss: 0.14865 RPN box loss: 0.03614 RPN score loss: 0.01264 RPN total loss: 0.04878 Total loss: 0.92922 timestamp: 1655043269.7332296 iteration: 44620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.0827 FastRCNN total loss: 0.20297 L1 loss: 0.0000e+00 L2 loss: 0.59576 Learning rate: 0.002 Mask loss: 0.14824 RPN box loss: 0.01564 RPN score loss: 0.00551 RPN total loss: 0.02115 Total loss: 0.96812 timestamp: 1655043273.0176833 iteration: 44625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16875 FastRCNN class loss: 0.13112 FastRCNN total loss: 0.29986 L1 loss: 0.0000e+00 L2 loss: 0.59575 Learning rate: 0.002 Mask loss: 0.14073 RPN box loss: 0.01279 RPN score loss: 0.00339 RPN total loss: 0.01618 Total loss: 1.05253 timestamp: 1655043276.2910597 iteration: 44630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15344 FastRCNN class loss: 0.10575 FastRCNN total loss: 0.25919 L1 loss: 0.0000e+00 L2 loss: 0.59574 Learning rate: 0.002 Mask loss: 0.20932 RPN box loss: 0.0216 RPN score loss: 0.00424 RPN total loss: 0.02584 Total loss: 1.09009 timestamp: 1655043279.5825295 iteration: 44635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11761 FastRCNN class loss: 0.06154 FastRCNN total loss: 0.17915 L1 loss: 0.0000e+00 L2 loss: 0.59573 Learning rate: 0.002 Mask loss: 0.16292 RPN box loss: 0.01941 RPN score loss: 0.00632 RPN total loss: 0.02573 Total loss: 0.96354 timestamp: 1655043282.8239853 iteration: 44640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07144 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.14181 L1 loss: 0.0000e+00 L2 loss: 0.59572 Learning rate: 0.002 Mask loss: 0.12909 RPN box loss: 0.01852 RPN score loss: 0.00569 RPN total loss: 0.02421 Total loss: 0.89084 timestamp: 1655043286.0531082 iteration: 44645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06504 FastRCNN class loss: 0.09684 FastRCNN total loss: 0.16188 L1 loss: 0.0000e+00 L2 loss: 0.59571 Learning rate: 0.002 Mask loss: 0.11786 RPN box loss: 0.02915 RPN score loss: 0.00366 RPN total loss: 0.03281 Total loss: 0.90826 timestamp: 1655043289.3180883 iteration: 44650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10436 FastRCNN class loss: 0.06516 FastRCNN total loss: 0.16952 L1 loss: 0.0000e+00 L2 loss: 0.5957 Learning rate: 0.002 Mask loss: 0.11384 RPN box loss: 0.02792 RPN score loss: 0.00368 RPN total loss: 0.0316 Total loss: 0.91067 timestamp: 1655043292.6911733 iteration: 44655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08988 FastRCNN class loss: 0.05074 FastRCNN total loss: 0.14062 L1 loss: 0.0000e+00 L2 loss: 0.59569 Learning rate: 0.002 Mask loss: 0.13298 RPN box loss: 0.01266 RPN score loss: 0.00181 RPN total loss: 0.01446 Total loss: 0.88375 timestamp: 1655043295.9576087 iteration: 44660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11825 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.21687 L1 loss: 0.0000e+00 L2 loss: 0.59568 Learning rate: 0.002 Mask loss: 0.10479 RPN box loss: 0.02649 RPN score loss: 0.0076 RPN total loss: 0.03408 Total loss: 0.95142 timestamp: 1655043299.2325683 iteration: 44665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13598 FastRCNN class loss: 0.15198 FastRCNN total loss: 0.28796 L1 loss: 0.0000e+00 L2 loss: 0.59568 Learning rate: 0.002 Mask loss: 0.17717 RPN box loss: 0.0376 RPN score loss: 0.00707 RPN total loss: 0.04467 Total loss: 1.10548 timestamp: 1655043302.496972 iteration: 44670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07065 FastRCNN class loss: 0.02754 FastRCNN total loss: 0.09819 L1 loss: 0.0000e+00 L2 loss: 0.59567 Learning rate: 0.002 Mask loss: 0.09235 RPN box loss: 0.00872 RPN score loss: 0.00287 RPN total loss: 0.0116 Total loss: 0.7978 timestamp: 1655043305.7783937 iteration: 44675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12475 FastRCNN class loss: 0.09699 FastRCNN total loss: 0.22174 L1 loss: 0.0000e+00 L2 loss: 0.59566 Learning rate: 0.002 Mask loss: 0.14306 RPN box loss: 0.02062 RPN score loss: 0.00576 RPN total loss: 0.02638 Total loss: 0.98684 timestamp: 1655043309.039335 iteration: 44680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18675 FastRCNN class loss: 0.10693 FastRCNN total loss: 0.29368 L1 loss: 0.0000e+00 L2 loss: 0.59565 Learning rate: 0.002 Mask loss: 0.17398 RPN box loss: 0.03192 RPN score loss: 0.01368 RPN total loss: 0.0456 Total loss: 1.10891 timestamp: 1655043312.3481386 iteration: 44685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1425 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.23296 L1 loss: 0.0000e+00 L2 loss: 0.59564 Learning rate: 0.002 Mask loss: 0.19108 RPN box loss: 0.01409 RPN score loss: 0.00489 RPN total loss: 0.01898 Total loss: 1.03866 timestamp: 1655043315.6308572 iteration: 44690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06614 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.1306 L1 loss: 0.0000e+00 L2 loss: 0.59563 Learning rate: 0.002 Mask loss: 0.14236 RPN box loss: 0.0289 RPN score loss: 0.00489 RPN total loss: 0.03379 Total loss: 0.90239 timestamp: 1655043318.9198215 iteration: 44695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10565 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.19533 L1 loss: 0.0000e+00 L2 loss: 0.59562 Learning rate: 0.002 Mask loss: 0.1374 RPN box loss: 0.01783 RPN score loss: 0.00226 RPN total loss: 0.02009 Total loss: 0.94844 timestamp: 1655043322.197647 iteration: 44700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16467 FastRCNN class loss: 0.11119 FastRCNN total loss: 0.27586 L1 loss: 0.0000e+00 L2 loss: 0.59562 Learning rate: 0.002 Mask loss: 0.18246 RPN box loss: 0.04234 RPN score loss: 0.01602 RPN total loss: 0.05836 Total loss: 1.11229 timestamp: 1655043325.5132504 iteration: 44705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06418 FastRCNN class loss: 0.04219 FastRCNN total loss: 0.10637 L1 loss: 0.0000e+00 L2 loss: 0.59561 Learning rate: 0.002 Mask loss: 0.12468 RPN box loss: 0.01096 RPN score loss: 0.00153 RPN total loss: 0.01249 Total loss: 0.83914 timestamp: 1655043328.7476475 iteration: 44710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11104 FastRCNN class loss: 0.08842 FastRCNN total loss: 0.19946 L1 loss: 0.0000e+00 L2 loss: 0.5956 Learning rate: 0.002 Mask loss: 0.14957 RPN box loss: 0.04708 RPN score loss: 0.01459 RPN total loss: 0.06167 Total loss: 1.0063 timestamp: 1655043332.006793 iteration: 44715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06268 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.10938 L1 loss: 0.0000e+00 L2 loss: 0.59559 Learning rate: 0.002 Mask loss: 0.13768 RPN box loss: 0.02302 RPN score loss: 0.00227 RPN total loss: 0.02529 Total loss: 0.86794 timestamp: 1655043335.1966023 iteration: 44720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.17101 L1 loss: 0.0000e+00 L2 loss: 0.59558 Learning rate: 0.002 Mask loss: 0.11896 RPN box loss: 0.02417 RPN score loss: 0.01332 RPN total loss: 0.03749 Total loss: 0.92303 timestamp: 1655043338.5318005 iteration: 44725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18189 FastRCNN class loss: 0.0923 FastRCNN total loss: 0.27419 L1 loss: 0.0000e+00 L2 loss: 0.59557 Learning rate: 0.002 Mask loss: 0.15626 RPN box loss: 0.01788 RPN score loss: 0.00447 RPN total loss: 0.02235 Total loss: 1.04836 timestamp: 1655043341.8531513 iteration: 44730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14111 FastRCNN class loss: 0.13241 FastRCNN total loss: 0.27351 L1 loss: 0.0000e+00 L2 loss: 0.59556 Learning rate: 0.002 Mask loss: 0.17244 RPN box loss: 0.02049 RPN score loss: 0.01052 RPN total loss: 0.03101 Total loss: 1.07253 timestamp: 1655043345.123368 iteration: 44735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07422 FastRCNN class loss: 0.04766 FastRCNN total loss: 0.12188 L1 loss: 0.0000e+00 L2 loss: 0.59555 Learning rate: 0.002 Mask loss: 0.13131 RPN box loss: 0.00993 RPN score loss: 0.00168 RPN total loss: 0.01161 Total loss: 0.86035 timestamp: 1655043348.3216515 iteration: 44740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.22869 L1 loss: 0.0000e+00 L2 loss: 0.59554 Learning rate: 0.002 Mask loss: 0.13581 RPN box loss: 0.02164 RPN score loss: 0.0059 RPN total loss: 0.02754 Total loss: 0.98759 timestamp: 1655043351.5139499 iteration: 44745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09852 FastRCNN class loss: 0.0899 FastRCNN total loss: 0.18841 L1 loss: 0.0000e+00 L2 loss: 0.59553 Learning rate: 0.002 Mask loss: 0.15682 RPN box loss: 0.01548 RPN score loss: 0.00167 RPN total loss: 0.01715 Total loss: 0.95792 timestamp: 1655043354.7035744 iteration: 44750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10917 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.18215 L1 loss: 0.0000e+00 L2 loss: 0.59552 Learning rate: 0.002 Mask loss: 0.10904 RPN box loss: 0.03879 RPN score loss: 0.00583 RPN total loss: 0.04461 Total loss: 0.93133 timestamp: 1655043357.9754832 iteration: 44755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07704 FastRCNN class loss: 0.07834 FastRCNN total loss: 0.15538 L1 loss: 0.0000e+00 L2 loss: 0.59551 Learning rate: 0.002 Mask loss: 0.17903 RPN box loss: 0.02028 RPN score loss: 0.01719 RPN total loss: 0.03747 Total loss: 0.96739 timestamp: 1655043361.2568765 iteration: 44760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.1783 L1 loss: 0.0000e+00 L2 loss: 0.5955 Learning rate: 0.002 Mask loss: 0.19729 RPN box loss: 0.02436 RPN score loss: 0.00466 RPN total loss: 0.02902 Total loss: 1.00012 timestamp: 1655043364.4681053 iteration: 44765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05741 FastRCNN class loss: 0.05332 FastRCNN total loss: 0.11074 L1 loss: 0.0000e+00 L2 loss: 0.59549 Learning rate: 0.002 Mask loss: 0.10431 RPN box loss: 0.00831 RPN score loss: 0.00472 RPN total loss: 0.01302 Total loss: 0.82356 timestamp: 1655043367.7482922 iteration: 44770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.11389 FastRCNN total loss: 0.22846 L1 loss: 0.0000e+00 L2 loss: 0.59548 Learning rate: 0.002 Mask loss: 0.2061 RPN box loss: 0.03901 RPN score loss: 0.01026 RPN total loss: 0.04928 Total loss: 1.07933 timestamp: 1655043371.0558429 iteration: 44775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09288 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.14641 L1 loss: 0.0000e+00 L2 loss: 0.59547 Learning rate: 0.002 Mask loss: 0.23647 RPN box loss: 0.05227 RPN score loss: 0.01179 RPN total loss: 0.06406 Total loss: 1.04241 timestamp: 1655043374.3498328 iteration: 44780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05871 FastRCNN class loss: 0.06748 FastRCNN total loss: 0.1262 L1 loss: 0.0000e+00 L2 loss: 0.59546 Learning rate: 0.002 Mask loss: 0.13692 RPN box loss: 0.01239 RPN score loss: 0.01113 RPN total loss: 0.02352 Total loss: 0.8821 timestamp: 1655043377.6223967 iteration: 44785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1049 FastRCNN class loss: 0.07571 FastRCNN total loss: 0.18061 L1 loss: 0.0000e+00 L2 loss: 0.59546 Learning rate: 0.002 Mask loss: 0.13524 RPN box loss: 0.08024 RPN score loss: 0.00486 RPN total loss: 0.08509 Total loss: 0.9964 timestamp: 1655043380.8947413 iteration: 44790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07996 FastRCNN class loss: 0.05566 FastRCNN total loss: 0.13562 L1 loss: 0.0000e+00 L2 loss: 0.59545 Learning rate: 0.002 Mask loss: 0.15306 RPN box loss: 0.0156 RPN score loss: 0.00224 RPN total loss: 0.01784 Total loss: 0.90197 timestamp: 1655043384.1196856 iteration: 44795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08808 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.15838 L1 loss: 0.0000e+00 L2 loss: 0.59544 Learning rate: 0.002 Mask loss: 0.1941 RPN box loss: 0.02814 RPN score loss: 0.00264 RPN total loss: 0.03077 Total loss: 0.97869 timestamp: 1655043387.4319446 iteration: 44800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1639 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.23859 L1 loss: 0.0000e+00 L2 loss: 0.59543 Learning rate: 0.002 Mask loss: 0.1629 RPN box loss: 0.02738 RPN score loss: 0.00686 RPN total loss: 0.03424 Total loss: 1.03116 timestamp: 1655043390.6395493 iteration: 44805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10866 FastRCNN class loss: 0.08978 FastRCNN total loss: 0.19845 L1 loss: 0.0000e+00 L2 loss: 0.59542 Learning rate: 0.002 Mask loss: 0.15869 RPN box loss: 0.03809 RPN score loss: 0.00567 RPN total loss: 0.04376 Total loss: 0.99632 timestamp: 1655043393.8892646 iteration: 44810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14512 FastRCNN class loss: 0.07082 FastRCNN total loss: 0.21594 L1 loss: 0.0000e+00 L2 loss: 0.59541 Learning rate: 0.002 Mask loss: 0.13692 RPN box loss: 0.01309 RPN score loss: 0.00399 RPN total loss: 0.01708 Total loss: 0.96536 timestamp: 1655043397.1750467 iteration: 44815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.05676 FastRCNN total loss: 0.14346 L1 loss: 0.0000e+00 L2 loss: 0.5954 Learning rate: 0.002 Mask loss: 0.1286 RPN box loss: 0.01942 RPN score loss: 0.00597 RPN total loss: 0.02539 Total loss: 0.89286 timestamp: 1655043400.4234493 iteration: 44820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05954 FastRCNN class loss: 0.04769 FastRCNN total loss: 0.10722 L1 loss: 0.0000e+00 L2 loss: 0.5954 Learning rate: 0.002 Mask loss: 0.10622 RPN box loss: 0.01989 RPN score loss: 0.00371 RPN total loss: 0.02359 Total loss: 0.83243 timestamp: 1655043403.620761 iteration: 44825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19625 FastRCNN class loss: 0.11432 FastRCNN total loss: 0.31057 L1 loss: 0.0000e+00 L2 loss: 0.59538 Learning rate: 0.002 Mask loss: 0.23876 RPN box loss: 0.0293 RPN score loss: 0.01158 RPN total loss: 0.04089 Total loss: 1.1856 timestamp: 1655043406.8044903 iteration: 44830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12423 FastRCNN class loss: 0.04471 FastRCNN total loss: 0.16894 L1 loss: 0.0000e+00 L2 loss: 0.59537 Learning rate: 0.002 Mask loss: 0.11922 RPN box loss: 0.011 RPN score loss: 0.00158 RPN total loss: 0.01258 Total loss: 0.89611 timestamp: 1655043410.0689857 iteration: 44835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10524 FastRCNN class loss: 0.07473 FastRCNN total loss: 0.17997 L1 loss: 0.0000e+00 L2 loss: 0.59536 Learning rate: 0.002 Mask loss: 0.15754 RPN box loss: 0.04192 RPN score loss: 0.00647 RPN total loss: 0.04839 Total loss: 0.98126 timestamp: 1655043413.3690357 iteration: 44840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.11704 L1 loss: 0.0000e+00 L2 loss: 0.59535 Learning rate: 0.002 Mask loss: 0.11203 RPN box loss: 0.01611 RPN score loss: 0.00269 RPN total loss: 0.01881 Total loss: 0.84323 timestamp: 1655043416.6385927 iteration: 44845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06669 FastRCNN class loss: 0.03796 FastRCNN total loss: 0.10466 L1 loss: 0.0000e+00 L2 loss: 0.59534 Learning rate: 0.002 Mask loss: 0.12076 RPN box loss: 0.00638 RPN score loss: 0.00324 RPN total loss: 0.00962 Total loss: 0.83037 timestamp: 1655043419.9805741 iteration: 44850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11265 FastRCNN class loss: 0.08783 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.59534 Learning rate: 0.002 Mask loss: 0.13474 RPN box loss: 0.01964 RPN score loss: 0.01042 RPN total loss: 0.03006 Total loss: 0.96061 timestamp: 1655043423.2348762 iteration: 44855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09451 FastRCNN class loss: 0.04917 FastRCNN total loss: 0.14368 L1 loss: 0.0000e+00 L2 loss: 0.59533 Learning rate: 0.002 Mask loss: 0.16018 RPN box loss: 0.01312 RPN score loss: 0.00422 RPN total loss: 0.01734 Total loss: 0.91653 timestamp: 1655043426.5441303 iteration: 44860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11066 FastRCNN class loss: 0.09665 FastRCNN total loss: 0.20731 L1 loss: 0.0000e+00 L2 loss: 0.59532 Learning rate: 0.002 Mask loss: 0.14652 RPN box loss: 0.0179 RPN score loss: 0.00715 RPN total loss: 0.02504 Total loss: 0.97419 timestamp: 1655043429.8416603 iteration: 44865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13025 FastRCNN class loss: 0.09273 FastRCNN total loss: 0.22298 L1 loss: 0.0000e+00 L2 loss: 0.59531 Learning rate: 0.002 Mask loss: 0.18348 RPN box loss: 0.0102 RPN score loss: 0.01504 RPN total loss: 0.02523 Total loss: 1.027 timestamp: 1655043433.0970967 iteration: 44870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.5953 Learning rate: 0.002 Mask loss: 0.11359 RPN box loss: 0.01231 RPN score loss: 0.00607 RPN total loss: 0.01838 Total loss: 0.89842 timestamp: 1655043436.323471 iteration: 44875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07988 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.15665 L1 loss: 0.0000e+00 L2 loss: 0.59529 Learning rate: 0.002 Mask loss: 0.15597 RPN box loss: 0.02451 RPN score loss: 0.00401 RPN total loss: 0.02851 Total loss: 0.93643 timestamp: 1655043439.5720928 iteration: 44880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1085 FastRCNN class loss: 0.09409 FastRCNN total loss: 0.20259 L1 loss: 0.0000e+00 L2 loss: 0.59528 Learning rate: 0.002 Mask loss: 0.20262 RPN box loss: 0.01627 RPN score loss: 0.0066 RPN total loss: 0.02287 Total loss: 1.02336 timestamp: 1655043442.8781753 iteration: 44885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.08659 FastRCNN total loss: 0.2021 L1 loss: 0.0000e+00 L2 loss: 0.59528 Learning rate: 0.002 Mask loss: 0.12687 RPN box loss: 0.04065 RPN score loss: 0.00426 RPN total loss: 0.04491 Total loss: 0.96917 timestamp: 1655043446.1835408 iteration: 44890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06851 FastRCNN class loss: 0.05281 FastRCNN total loss: 0.12132 L1 loss: 0.0000e+00 L2 loss: 0.59526 Learning rate: 0.002 Mask loss: 0.08154 RPN box loss: 0.00719 RPN score loss: 0.0009 RPN total loss: 0.00809 Total loss: 0.80621 timestamp: 1655043449.4419162 iteration: 44895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11704 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.18413 L1 loss: 0.0000e+00 L2 loss: 0.59525 Learning rate: 0.002 Mask loss: 0.14884 RPN box loss: 0.01173 RPN score loss: 0.00394 RPN total loss: 0.01567 Total loss: 0.94389 timestamp: 1655043452.6748614 iteration: 44900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16123 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.23624 L1 loss: 0.0000e+00 L2 loss: 0.59524 Learning rate: 0.002 Mask loss: 0.15873 RPN box loss: 0.0125 RPN score loss: 0.00571 RPN total loss: 0.01821 Total loss: 1.00843 timestamp: 1655043456.0441885 iteration: 44905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10814 FastRCNN class loss: 0.08665 FastRCNN total loss: 0.19479 L1 loss: 0.0000e+00 L2 loss: 0.59523 Learning rate: 0.002 Mask loss: 0.1548 RPN box loss: 0.06626 RPN score loss: 0.00633 RPN total loss: 0.0726 Total loss: 1.01741 timestamp: 1655043459.3492222 iteration: 44910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10374 FastRCNN class loss: 0.03955 FastRCNN total loss: 0.14329 L1 loss: 0.0000e+00 L2 loss: 0.59522 Learning rate: 0.002 Mask loss: 0.10744 RPN box loss: 0.01974 RPN score loss: 0.00142 RPN total loss: 0.02116 Total loss: 0.86711 timestamp: 1655043462.624991 iteration: 44915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09818 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.18717 L1 loss: 0.0000e+00 L2 loss: 0.59522 Learning rate: 0.002 Mask loss: 0.18607 RPN box loss: 0.02455 RPN score loss: 0.00944 RPN total loss: 0.03398 Total loss: 1.00244 timestamp: 1655043465.8800986 iteration: 44920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08133 FastRCNN class loss: 0.03517 FastRCNN total loss: 0.11649 L1 loss: 0.0000e+00 L2 loss: 0.59521 Learning rate: 0.002 Mask loss: 0.11983 RPN box loss: 0.00687 RPN score loss: 0.00133 RPN total loss: 0.0082 Total loss: 0.83973 timestamp: 1655043469.2182863 iteration: 44925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.04413 FastRCNN total loss: 0.15772 L1 loss: 0.0000e+00 L2 loss: 0.5952 Learning rate: 0.002 Mask loss: 0.10998 RPN box loss: 0.0122 RPN score loss: 0.00227 RPN total loss: 0.01447 Total loss: 0.87737 timestamp: 1655043472.5042772 iteration: 44930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.17302 L1 loss: 0.0000e+00 L2 loss: 0.59519 Learning rate: 0.002 Mask loss: 0.15037 RPN box loss: 0.02447 RPN score loss: 0.00998 RPN total loss: 0.03445 Total loss: 0.95304 timestamp: 1655043475.7931955 iteration: 44935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06983 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.12574 L1 loss: 0.0000e+00 L2 loss: 0.59518 Learning rate: 0.002 Mask loss: 0.14387 RPN box loss: 0.03332 RPN score loss: 0.00478 RPN total loss: 0.03809 Total loss: 0.90288 timestamp: 1655043479.0211847 iteration: 44940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.04022 FastRCNN total loss: 0.16838 L1 loss: 0.0000e+00 L2 loss: 0.59517 Learning rate: 0.002 Mask loss: 0.14101 RPN box loss: 0.01468 RPN score loss: 0.0022 RPN total loss: 0.01688 Total loss: 0.92145 timestamp: 1655043482.3124785 iteration: 44945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10592 FastRCNN class loss: 0.09672 FastRCNN total loss: 0.20264 L1 loss: 0.0000e+00 L2 loss: 0.59516 Learning rate: 0.002 Mask loss: 0.14697 RPN box loss: 0.03039 RPN score loss: 0.00947 RPN total loss: 0.03986 Total loss: 0.98464 timestamp: 1655043485.5552478 iteration: 44950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16394 FastRCNN class loss: 0.17963 FastRCNN total loss: 0.34357 L1 loss: 0.0000e+00 L2 loss: 0.59515 Learning rate: 0.002 Mask loss: 0.24268 RPN box loss: 0.05234 RPN score loss: 0.01378 RPN total loss: 0.06613 Total loss: 1.24754 timestamp: 1655043488.8711536 iteration: 44955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17396 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.23573 L1 loss: 0.0000e+00 L2 loss: 0.59514 Learning rate: 0.002 Mask loss: 0.13942 RPN box loss: 0.00439 RPN score loss: 0.00615 RPN total loss: 0.01054 Total loss: 0.98083 timestamp: 1655043492.152088 iteration: 44960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.1586 L1 loss: 0.0000e+00 L2 loss: 0.59513 Learning rate: 0.002 Mask loss: 0.13858 RPN box loss: 0.0308 RPN score loss: 0.00332 RPN total loss: 0.03412 Total loss: 0.92643 timestamp: 1655043495.4524755 iteration: 44965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08905 FastRCNN class loss: 0.04763 FastRCNN total loss: 0.13668 L1 loss: 0.0000e+00 L2 loss: 0.59512 Learning rate: 0.002 Mask loss: 0.21668 RPN box loss: 0.01009 RPN score loss: 0.00214 RPN total loss: 0.01223 Total loss: 0.96071 timestamp: 1655043498.6732552 iteration: 44970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0976 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.19367 L1 loss: 0.0000e+00 L2 loss: 0.59511 Learning rate: 0.002 Mask loss: 0.12783 RPN box loss: 0.01517 RPN score loss: 0.0061 RPN total loss: 0.02127 Total loss: 0.93788 timestamp: 1655043501.968436 iteration: 44975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13999 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.2092 L1 loss: 0.0000e+00 L2 loss: 0.5951 Learning rate: 0.002 Mask loss: 0.19096 RPN box loss: 0.02639 RPN score loss: 0.01148 RPN total loss: 0.03788 Total loss: 1.03314 timestamp: 1655043505.2394686 iteration: 44980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09196 FastRCNN class loss: 0.10044 FastRCNN total loss: 0.19239 L1 loss: 0.0000e+00 L2 loss: 0.5951 Learning rate: 0.002 Mask loss: 0.18725 RPN box loss: 0.01875 RPN score loss: 0.00519 RPN total loss: 0.02394 Total loss: 0.99868 timestamp: 1655043508.488065 iteration: 44985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10444 FastRCNN class loss: 0.08143 FastRCNN total loss: 0.18587 L1 loss: 0.0000e+00 L2 loss: 0.59509 Learning rate: 0.002 Mask loss: 0.14762 RPN box loss: 0.01729 RPN score loss: 0.00646 RPN total loss: 0.02376 Total loss: 0.95234 timestamp: 1655043511.7509427 iteration: 44990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14675 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.22744 L1 loss: 0.0000e+00 L2 loss: 0.59508 Learning rate: 0.002 Mask loss: 0.14068 RPN box loss: 0.03841 RPN score loss: 0.00888 RPN total loss: 0.04729 Total loss: 1.01049 timestamp: 1655043514.9934874 iteration: 44995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10099 FastRCNN class loss: 0.09576 FastRCNN total loss: 0.19674 L1 loss: 0.0000e+00 L2 loss: 0.59507 Learning rate: 0.002 Mask loss: 0.21313 RPN box loss: 0.01161 RPN score loss: 0.00579 RPN total loss: 0.0174 Total loss: 1.02234 timestamp: 1655043518.2891407 iteration: 45000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.08058 FastRCNN total loss: 0.21414 L1 loss: 0.0000e+00 L2 loss: 0.59506 Learning rate: 0.002 Mask loss: 0.18391 RPN box loss: 0.01916 RPN score loss: 0.00461 RPN total loss: 0.02377 Total loss: 1.01688 timestamp: 1655043521.539649 iteration: 45005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16242 FastRCNN class loss: 0.11883 FastRCNN total loss: 0.28125 L1 loss: 0.0000e+00 L2 loss: 0.59505 Learning rate: 0.002 Mask loss: 0.16339 RPN box loss: 0.02234 RPN score loss: 0.03893 RPN total loss: 0.06126 Total loss: 1.10096 timestamp: 1655043524.78158 iteration: 45010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12011 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.19086 L1 loss: 0.0000e+00 L2 loss: 0.59504 Learning rate: 0.002 Mask loss: 0.16641 RPN box loss: 0.02738 RPN score loss: 0.00422 RPN total loss: 0.03161 Total loss: 0.98392 timestamp: 1655043528.2120214 iteration: 45015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.1173 FastRCNN total loss: 0.23142 L1 loss: 0.0000e+00 L2 loss: 0.59503 Learning rate: 0.002 Mask loss: 0.19768 RPN box loss: 0.07821 RPN score loss: 0.01581 RPN total loss: 0.09401 Total loss: 1.11814 timestamp: 1655043531.4866192 iteration: 45020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09097 FastRCNN class loss: 0.05119 FastRCNN total loss: 0.14216 L1 loss: 0.0000e+00 L2 loss: 0.59502 Learning rate: 0.002 Mask loss: 0.08323 RPN box loss: 0.00621 RPN score loss: 0.00085 RPN total loss: 0.00706 Total loss: 0.82748 timestamp: 1655043534.7133536 iteration: 45025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15449 FastRCNN class loss: 0.0908 FastRCNN total loss: 0.24529 L1 loss: 0.0000e+00 L2 loss: 0.59501 Learning rate: 0.002 Mask loss: 0.19631 RPN box loss: 0.02477 RPN score loss: 0.01143 RPN total loss: 0.0362 Total loss: 1.07282 timestamp: 1655043537.9608428 iteration: 45030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.04083 FastRCNN total loss: 0.13741 L1 loss: 0.0000e+00 L2 loss: 0.59501 Learning rate: 0.002 Mask loss: 0.1094 RPN box loss: 0.00754 RPN score loss: 0.00144 RPN total loss: 0.00898 Total loss: 0.85079 timestamp: 1655043541.2179186 iteration: 45035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08972 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.14274 L1 loss: 0.0000e+00 L2 loss: 0.595 Learning rate: 0.002 Mask loss: 0.13782 RPN box loss: 0.02632 RPN score loss: 0.00535 RPN total loss: 0.03166 Total loss: 0.90722 timestamp: 1655043544.4485695 iteration: 45040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11544 FastRCNN class loss: 0.11632 FastRCNN total loss: 0.23176 L1 loss: 0.0000e+00 L2 loss: 0.59499 Learning rate: 0.002 Mask loss: 0.19443 RPN box loss: 0.02288 RPN score loss: 0.0142 RPN total loss: 0.03708 Total loss: 1.05826 timestamp: 1655043547.6929924 iteration: 45045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06899 FastRCNN class loss: 0.04651 FastRCNN total loss: 0.1155 L1 loss: 0.0000e+00 L2 loss: 0.59498 Learning rate: 0.002 Mask loss: 0.06862 RPN box loss: 0.00693 RPN score loss: 0.00333 RPN total loss: 0.01025 Total loss: 0.78936 timestamp: 1655043550.9887059 iteration: 45050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06935 FastRCNN class loss: 0.05085 FastRCNN total loss: 0.1202 L1 loss: 0.0000e+00 L2 loss: 0.59497 Learning rate: 0.002 Mask loss: 0.14519 RPN box loss: 0.01223 RPN score loss: 0.00334 RPN total loss: 0.01557 Total loss: 0.87592 timestamp: 1655043554.2916825 iteration: 45055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12331 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.20805 L1 loss: 0.0000e+00 L2 loss: 0.59496 Learning rate: 0.002 Mask loss: 0.11781 RPN box loss: 0.01135 RPN score loss: 0.00349 RPN total loss: 0.01483 Total loss: 0.93566 timestamp: 1655043557.5961351 iteration: 45060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10785 FastRCNN class loss: 0.0869 FastRCNN total loss: 0.19475 L1 loss: 0.0000e+00 L2 loss: 0.59495 Learning rate: 0.002 Mask loss: 0.12932 RPN box loss: 0.0202 RPN score loss: 0.0112 RPN total loss: 0.03139 Total loss: 0.95041 timestamp: 1655043560.8381126 iteration: 45065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11553 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.18006 L1 loss: 0.0000e+00 L2 loss: 0.59494 Learning rate: 0.002 Mask loss: 0.12441 RPN box loss: 0.0412 RPN score loss: 0.01325 RPN total loss: 0.05445 Total loss: 0.95386 timestamp: 1655043564.0719955 iteration: 45070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11525 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.59493 Learning rate: 0.002 Mask loss: 0.12531 RPN box loss: 0.04243 RPN score loss: 0.00482 RPN total loss: 0.04725 Total loss: 0.97196 timestamp: 1655043567.3636303 iteration: 45075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08318 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.16542 L1 loss: 0.0000e+00 L2 loss: 0.59492 Learning rate: 0.002 Mask loss: 0.13564 RPN box loss: 0.01426 RPN score loss: 0.00401 RPN total loss: 0.01827 Total loss: 0.91425 timestamp: 1655043570.675495 iteration: 45080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11011 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.16946 L1 loss: 0.0000e+00 L2 loss: 0.59491 Learning rate: 0.002 Mask loss: 0.14664 RPN box loss: 0.01404 RPN score loss: 0.00449 RPN total loss: 0.01853 Total loss: 0.92954 timestamp: 1655043573.969575 iteration: 45085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06596 FastRCNN class loss: 0.08502 FastRCNN total loss: 0.15098 L1 loss: 0.0000e+00 L2 loss: 0.5949 Learning rate: 0.002 Mask loss: 0.14874 RPN box loss: 0.01527 RPN score loss: 0.00575 RPN total loss: 0.02102 Total loss: 0.91564 timestamp: 1655043577.2153873 iteration: 45090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0929 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.15097 L1 loss: 0.0000e+00 L2 loss: 0.59489 Learning rate: 0.002 Mask loss: 0.17714 RPN box loss: 0.01136 RPN score loss: 0.00313 RPN total loss: 0.0145 Total loss: 0.93749 timestamp: 1655043580.511232 iteration: 45095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.18033 L1 loss: 0.0000e+00 L2 loss: 0.59488 Learning rate: 0.002 Mask loss: 0.13821 RPN box loss: 0.02442 RPN score loss: 0.01883 RPN total loss: 0.04325 Total loss: 0.95667 timestamp: 1655043583.7769165 iteration: 45100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09662 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.59487 Learning rate: 0.002 Mask loss: 0.08809 RPN box loss: 0.01492 RPN score loss: 0.0129 RPN total loss: 0.02782 Total loss: 0.86748 timestamp: 1655043587.1610267 iteration: 45105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09545 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.14614 L1 loss: 0.0000e+00 L2 loss: 0.59487 Learning rate: 0.002 Mask loss: 0.10264 RPN box loss: 0.00948 RPN score loss: 0.00102 RPN total loss: 0.0105 Total loss: 0.85415 timestamp: 1655043590.4624906 iteration: 45110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09308 FastRCNN class loss: 0.07556 FastRCNN total loss: 0.16863 L1 loss: 0.0000e+00 L2 loss: 0.59486 Learning rate: 0.002 Mask loss: 0.15727 RPN box loss: 0.0323 RPN score loss: 0.00538 RPN total loss: 0.03768 Total loss: 0.95844 timestamp: 1655043593.7677424 iteration: 45115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.24872 L1 loss: 0.0000e+00 L2 loss: 0.59485 Learning rate: 0.002 Mask loss: 0.16233 RPN box loss: 0.01704 RPN score loss: 0.00353 RPN total loss: 0.02057 Total loss: 1.02647 timestamp: 1655043596.9851055 iteration: 45120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1345 FastRCNN class loss: 0.06874 FastRCNN total loss: 0.20324 L1 loss: 0.0000e+00 L2 loss: 0.59484 Learning rate: 0.002 Mask loss: 0.18716 RPN box loss: 0.00758 RPN score loss: 0.00275 RPN total loss: 0.01033 Total loss: 0.99557 timestamp: 1655043600.2302995 iteration: 45125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05614 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.59483 Learning rate: 0.002 Mask loss: 0.1165 RPN box loss: 0.00811 RPN score loss: 0.00355 RPN total loss: 0.01166 Total loss: 0.83787 timestamp: 1655043603.4484873 iteration: 45130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07598 FastRCNN class loss: 0.07163 FastRCNN total loss: 0.14761 L1 loss: 0.0000e+00 L2 loss: 0.59482 Learning rate: 0.002 Mask loss: 0.12905 RPN box loss: 0.01958 RPN score loss: 0.00475 RPN total loss: 0.02433 Total loss: 0.89581 timestamp: 1655043606.6956904 iteration: 45135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05502 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.12825 L1 loss: 0.0000e+00 L2 loss: 0.59482 Learning rate: 0.002 Mask loss: 0.14656 RPN box loss: 0.01177 RPN score loss: 0.00857 RPN total loss: 0.02033 Total loss: 0.88996 timestamp: 1655043609.9799347 iteration: 45140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10043 FastRCNN class loss: 0.0582 FastRCNN total loss: 0.15863 L1 loss: 0.0000e+00 L2 loss: 0.59481 Learning rate: 0.002 Mask loss: 0.10231 RPN box loss: 0.00614 RPN score loss: 0.00257 RPN total loss: 0.0087 Total loss: 0.86445 timestamp: 1655043613.2142975 iteration: 45145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.14628 L1 loss: 0.0000e+00 L2 loss: 0.5948 Learning rate: 0.002 Mask loss: 0.13874 RPN box loss: 0.02613 RPN score loss: 0.00448 RPN total loss: 0.0306 Total loss: 0.91043 timestamp: 1655043616.4493332 iteration: 45150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10846 FastRCNN class loss: 0.07401 FastRCNN total loss: 0.18246 L1 loss: 0.0000e+00 L2 loss: 0.59479 Learning rate: 0.002 Mask loss: 0.18065 RPN box loss: 0.0172 RPN score loss: 0.00561 RPN total loss: 0.02282 Total loss: 0.98072 timestamp: 1655043619.7056065 iteration: 45155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1145 FastRCNN class loss: 0.06291 FastRCNN total loss: 0.17741 L1 loss: 0.0000e+00 L2 loss: 0.59478 Learning rate: 0.002 Mask loss: 0.09668 RPN box loss: 0.01423 RPN score loss: 0.0046 RPN total loss: 0.01882 Total loss: 0.8877 timestamp: 1655043623.0098956 iteration: 45160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.19075 L1 loss: 0.0000e+00 L2 loss: 0.59477 Learning rate: 0.002 Mask loss: 0.11328 RPN box loss: 0.02454 RPN score loss: 0.00256 RPN total loss: 0.0271 Total loss: 0.9259 timestamp: 1655043626.2508376 iteration: 45165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10431 FastRCNN class loss: 0.055 FastRCNN total loss: 0.15931 L1 loss: 0.0000e+00 L2 loss: 0.59476 Learning rate: 0.002 Mask loss: 0.12503 RPN box loss: 0.00749 RPN score loss: 0.00264 RPN total loss: 0.01013 Total loss: 0.88923 timestamp: 1655043629.4845607 iteration: 45170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1371 FastRCNN class loss: 0.13441 FastRCNN total loss: 0.2715 L1 loss: 0.0000e+00 L2 loss: 0.59475 Learning rate: 0.002 Mask loss: 0.21711 RPN box loss: 0.01962 RPN score loss: 0.0066 RPN total loss: 0.02621 Total loss: 1.10958 timestamp: 1655043632.824468 iteration: 45175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.1965 L1 loss: 0.0000e+00 L2 loss: 0.59474 Learning rate: 0.002 Mask loss: 0.11789 RPN box loss: 0.02812 RPN score loss: 0.00379 RPN total loss: 0.03191 Total loss: 0.94105 timestamp: 1655043636.1139538 iteration: 45180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13897 FastRCNN class loss: 0.12243 FastRCNN total loss: 0.2614 L1 loss: 0.0000e+00 L2 loss: 0.59473 Learning rate: 0.002 Mask loss: 0.20698 RPN box loss: 0.01142 RPN score loss: 0.00444 RPN total loss: 0.01586 Total loss: 1.07898 timestamp: 1655043639.4082277 iteration: 45185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10051 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.16641 L1 loss: 0.0000e+00 L2 loss: 0.59473 Learning rate: 0.002 Mask loss: 0.17644 RPN box loss: 0.0062 RPN score loss: 0.00418 RPN total loss: 0.01038 Total loss: 0.94796 timestamp: 1655043642.6357894 iteration: 45190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11285 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.18924 L1 loss: 0.0000e+00 L2 loss: 0.59472 Learning rate: 0.002 Mask loss: 0.19357 RPN box loss: 0.01292 RPN score loss: 0.00685 RPN total loss: 0.01977 Total loss: 0.99731 timestamp: 1655043645.963042 iteration: 45195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.21447 L1 loss: 0.0000e+00 L2 loss: 0.59471 Learning rate: 0.002 Mask loss: 0.13022 RPN box loss: 0.06994 RPN score loss: 0.00412 RPN total loss: 0.07407 Total loss: 1.01347 timestamp: 1655043649.2566297 iteration: 45200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1634 FastRCNN class loss: 0.06844 FastRCNN total loss: 0.23183 L1 loss: 0.0000e+00 L2 loss: 0.5947 Learning rate: 0.002 Mask loss: 0.1775 RPN box loss: 0.01477 RPN score loss: 0.00963 RPN total loss: 0.0244 Total loss: 1.02844 timestamp: 1655043652.534271 iteration: 45205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.16602 L1 loss: 0.0000e+00 L2 loss: 0.59469 Learning rate: 0.002 Mask loss: 0.16562 RPN box loss: 0.00674 RPN score loss: 0.00221 RPN total loss: 0.00894 Total loss: 0.93527 timestamp: 1655043655.8619225 iteration: 45210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.21176 L1 loss: 0.0000e+00 L2 loss: 0.59468 Learning rate: 0.002 Mask loss: 0.14526 RPN box loss: 0.03279 RPN score loss: 0.00828 RPN total loss: 0.04107 Total loss: 0.99277 timestamp: 1655043659.1479642 iteration: 45215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20427 FastRCNN class loss: 0.09823 FastRCNN total loss: 0.30249 L1 loss: 0.0000e+00 L2 loss: 0.59467 Learning rate: 0.002 Mask loss: 0.16588 RPN box loss: 0.02457 RPN score loss: 0.02155 RPN total loss: 0.04612 Total loss: 1.10916 timestamp: 1655043662.366966 iteration: 45220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18419 FastRCNN class loss: 0.09579 FastRCNN total loss: 0.27998 L1 loss: 0.0000e+00 L2 loss: 0.59466 Learning rate: 0.002 Mask loss: 0.10424 RPN box loss: 0.01872 RPN score loss: 0.0105 RPN total loss: 0.02922 Total loss: 1.0081 timestamp: 1655043665.586242 iteration: 45225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15293 FastRCNN class loss: 0.13318 FastRCNN total loss: 0.28611 L1 loss: 0.0000e+00 L2 loss: 0.59465 Learning rate: 0.002 Mask loss: 0.20343 RPN box loss: 0.02199 RPN score loss: 0.0165 RPN total loss: 0.03849 Total loss: 1.12268 timestamp: 1655043668.81488 iteration: 45230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07083 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.13726 L1 loss: 0.0000e+00 L2 loss: 0.59465 Learning rate: 0.002 Mask loss: 0.21561 RPN box loss: 0.01731 RPN score loss: 0.01125 RPN total loss: 0.02856 Total loss: 0.97608 timestamp: 1655043672.1285832 iteration: 45235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12312 FastRCNN class loss: 0.07709 FastRCNN total loss: 0.20021 L1 loss: 0.0000e+00 L2 loss: 0.59463 Learning rate: 0.002 Mask loss: 0.12663 RPN box loss: 0.0104 RPN score loss: 0.00574 RPN total loss: 0.01614 Total loss: 0.93762 timestamp: 1655043675.3768432 iteration: 45240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07027 FastRCNN class loss: 0.07408 FastRCNN total loss: 0.14435 L1 loss: 0.0000e+00 L2 loss: 0.59462 Learning rate: 0.002 Mask loss: 0.12475 RPN box loss: 0.02485 RPN score loss: 0.01073 RPN total loss: 0.03558 Total loss: 0.89929 timestamp: 1655043678.6492093 iteration: 45245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07666 FastRCNN class loss: 0.05787 FastRCNN total loss: 0.13453 L1 loss: 0.0000e+00 L2 loss: 0.59461 Learning rate: 0.002 Mask loss: 0.12279 RPN box loss: 0.03044 RPN score loss: 0.00388 RPN total loss: 0.03432 Total loss: 0.88625 timestamp: 1655043681.9438741 iteration: 45250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08722 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.15029 L1 loss: 0.0000e+00 L2 loss: 0.5946 Learning rate: 0.002 Mask loss: 0.15561 RPN box loss: 0.01839 RPN score loss: 0.00495 RPN total loss: 0.02335 Total loss: 0.92385 timestamp: 1655043685.2973137 iteration: 45255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1892 FastRCNN class loss: 0.07172 FastRCNN total loss: 0.26092 L1 loss: 0.0000e+00 L2 loss: 0.59459 Learning rate: 0.002 Mask loss: 0.10931 RPN box loss: 0.00437 RPN score loss: 0.00382 RPN total loss: 0.00819 Total loss: 0.97302 timestamp: 1655043688.5451381 iteration: 45260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.17894 L1 loss: 0.0000e+00 L2 loss: 0.59458 Learning rate: 0.002 Mask loss: 0.14262 RPN box loss: 0.01632 RPN score loss: 0.00768 RPN total loss: 0.024 Total loss: 0.94015 timestamp: 1655043691.8791487 iteration: 45265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08302 FastRCNN class loss: 0.04195 FastRCNN total loss: 0.12497 L1 loss: 0.0000e+00 L2 loss: 0.59458 Learning rate: 0.002 Mask loss: 0.06065 RPN box loss: 0.00414 RPN score loss: 0.00147 RPN total loss: 0.00561 Total loss: 0.78581 timestamp: 1655043695.1545303 iteration: 45270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06508 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.12638 L1 loss: 0.0000e+00 L2 loss: 0.59457 Learning rate: 0.002 Mask loss: 0.16003 RPN box loss: 0.02453 RPN score loss: 0.00257 RPN total loss: 0.02709 Total loss: 0.90807 timestamp: 1655043698.4658468 iteration: 45275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.17006 L1 loss: 0.0000e+00 L2 loss: 0.59456 Learning rate: 0.002 Mask loss: 0.11928 RPN box loss: 0.02572 RPN score loss: 0.0073 RPN total loss: 0.03302 Total loss: 0.91692 timestamp: 1655043701.7696042 iteration: 45280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10793 FastRCNN class loss: 0.09153 FastRCNN total loss: 0.19947 L1 loss: 0.0000e+00 L2 loss: 0.59455 Learning rate: 0.002 Mask loss: 0.11225 RPN box loss: 0.02963 RPN score loss: 0.0126 RPN total loss: 0.04224 Total loss: 0.9485 timestamp: 1655043705.0905914 iteration: 45285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12594 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.59454 Learning rate: 0.002 Mask loss: 0.12217 RPN box loss: 0.00565 RPN score loss: 0.00561 RPN total loss: 0.01127 Total loss: 0.91919 timestamp: 1655043708.36148 iteration: 45290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13515 FastRCNN class loss: 0.05625 FastRCNN total loss: 0.1914 L1 loss: 0.0000e+00 L2 loss: 0.59453 Learning rate: 0.002 Mask loss: 0.09475 RPN box loss: 0.01212 RPN score loss: 0.00267 RPN total loss: 0.01479 Total loss: 0.89548 timestamp: 1655043711.5446918 iteration: 45295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12227 FastRCNN class loss: 0.07133 FastRCNN total loss: 0.19361 L1 loss: 0.0000e+00 L2 loss: 0.59452 Learning rate: 0.002 Mask loss: 0.16161 RPN box loss: 0.03742 RPN score loss: 0.00164 RPN total loss: 0.03906 Total loss: 0.9888 timestamp: 1655043714.8831136 iteration: 45300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10734 FastRCNN class loss: 0.05325 FastRCNN total loss: 0.16059 L1 loss: 0.0000e+00 L2 loss: 0.59451 Learning rate: 0.002 Mask loss: 0.17516 RPN box loss: 0.00795 RPN score loss: 0.0054 RPN total loss: 0.01334 Total loss: 0.94361 timestamp: 1655043718.1836019 iteration: 45305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11611 FastRCNN class loss: 0.1033 FastRCNN total loss: 0.21942 L1 loss: 0.0000e+00 L2 loss: 0.5945 Learning rate: 0.002 Mask loss: 0.20492 RPN box loss: 0.02171 RPN score loss: 0.00949 RPN total loss: 0.03121 Total loss: 1.05004 timestamp: 1655043721.4435258 iteration: 45310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05711 FastRCNN class loss: 0.04593 FastRCNN total loss: 0.10304 L1 loss: 0.0000e+00 L2 loss: 0.59449 Learning rate: 0.002 Mask loss: 0.1069 RPN box loss: 0.00358 RPN score loss: 0.0009 RPN total loss: 0.00448 Total loss: 0.80891 timestamp: 1655043724.7519627 iteration: 45315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06902 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.12778 L1 loss: 0.0000e+00 L2 loss: 0.59448 Learning rate: 0.002 Mask loss: 0.17421 RPN box loss: 0.0268 RPN score loss: 0.00701 RPN total loss: 0.0338 Total loss: 0.93027 timestamp: 1655043728.0448108 iteration: 45320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07478 FastRCNN class loss: 0.06342 FastRCNN total loss: 0.1382 L1 loss: 0.0000e+00 L2 loss: 0.59447 Learning rate: 0.002 Mask loss: 0.15333 RPN box loss: 0.03344 RPN score loss: 0.00304 RPN total loss: 0.03647 Total loss: 0.92247 timestamp: 1655043731.376075 iteration: 45325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08784 FastRCNN class loss: 0.06252 FastRCNN total loss: 0.15036 L1 loss: 0.0000e+00 L2 loss: 0.59446 Learning rate: 0.002 Mask loss: 0.13802 RPN box loss: 0.01251 RPN score loss: 0.01228 RPN total loss: 0.02479 Total loss: 0.90762 timestamp: 1655043734.6395524 iteration: 45330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13248 FastRCNN class loss: 0.11184 FastRCNN total loss: 0.24432 L1 loss: 0.0000e+00 L2 loss: 0.59445 Learning rate: 0.002 Mask loss: 0.15929 RPN box loss: 0.01168 RPN score loss: 0.00508 RPN total loss: 0.01676 Total loss: 1.01482 timestamp: 1655043737.8296614 iteration: 45335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10031 FastRCNN class loss: 0.06155 FastRCNN total loss: 0.16186 L1 loss: 0.0000e+00 L2 loss: 0.59444 Learning rate: 0.002 Mask loss: 0.12862 RPN box loss: 0.01608 RPN score loss: 0.00419 RPN total loss: 0.02027 Total loss: 0.90519 timestamp: 1655043741.1036065 iteration: 45340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10571 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.17682 L1 loss: 0.0000e+00 L2 loss: 0.59443 Learning rate: 0.002 Mask loss: 0.12203 RPN box loss: 0.04604 RPN score loss: 0.00516 RPN total loss: 0.05119 Total loss: 0.94448 timestamp: 1655043744.3826516 iteration: 45345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06806 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.11749 L1 loss: 0.0000e+00 L2 loss: 0.59443 Learning rate: 0.002 Mask loss: 0.15367 RPN box loss: 0.0211 RPN score loss: 0.00628 RPN total loss: 0.02738 Total loss: 0.89297 timestamp: 1655043747.6572495 iteration: 45350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07075 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.13681 L1 loss: 0.0000e+00 L2 loss: 0.59442 Learning rate: 0.002 Mask loss: 0.13081 RPN box loss: 0.01972 RPN score loss: 0.01056 RPN total loss: 0.03028 Total loss: 0.89232 timestamp: 1655043750.9445221 iteration: 45355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17847 FastRCNN class loss: 0.09088 FastRCNN total loss: 0.26935 L1 loss: 0.0000e+00 L2 loss: 0.59441 Learning rate: 0.002 Mask loss: 0.16732 RPN box loss: 0.02445 RPN score loss: 0.0238 RPN total loss: 0.04826 Total loss: 1.07934 timestamp: 1655043754.1595798 iteration: 45360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11879 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.17392 L1 loss: 0.0000e+00 L2 loss: 0.5944 Learning rate: 0.002 Mask loss: 0.13042 RPN box loss: 0.03639 RPN score loss: 0.00181 RPN total loss: 0.0382 Total loss: 0.93694 timestamp: 1655043757.4034452 iteration: 45365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07069 FastRCNN class loss: 0.04422 FastRCNN total loss: 0.11491 L1 loss: 0.0000e+00 L2 loss: 0.59439 Learning rate: 0.002 Mask loss: 0.17199 RPN box loss: 0.01158 RPN score loss: 0.00484 RPN total loss: 0.01642 Total loss: 0.89771 timestamp: 1655043760.7079601 iteration: 45370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09733 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.1607 L1 loss: 0.0000e+00 L2 loss: 0.59438 Learning rate: 0.002 Mask loss: 0.13749 RPN box loss: 0.00852 RPN score loss: 0.00175 RPN total loss: 0.01027 Total loss: 0.90285 timestamp: 1655043763.934007 iteration: 45375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15114 FastRCNN class loss: 0.09017 FastRCNN total loss: 0.24131 L1 loss: 0.0000e+00 L2 loss: 0.59437 Learning rate: 0.002 Mask loss: 0.2243 RPN box loss: 0.02454 RPN score loss: 0.01185 RPN total loss: 0.0364 Total loss: 1.09637 timestamp: 1655043767.1746554 iteration: 45380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18507 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.26014 L1 loss: 0.0000e+00 L2 loss: 0.59436 Learning rate: 0.002 Mask loss: 0.16206 RPN box loss: 0.01934 RPN score loss: 0.0104 RPN total loss: 0.02975 Total loss: 1.04631 timestamp: 1655043770.4244552 iteration: 45385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.05531 FastRCNN total loss: 0.15706 L1 loss: 0.0000e+00 L2 loss: 0.59435 Learning rate: 0.002 Mask loss: 0.11216 RPN box loss: 0.02448 RPN score loss: 0.00832 RPN total loss: 0.0328 Total loss: 0.89637 timestamp: 1655043773.604613 iteration: 45390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07924 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.16391 L1 loss: 0.0000e+00 L2 loss: 0.59434 Learning rate: 0.002 Mask loss: 0.14101 RPN box loss: 0.05366 RPN score loss: 0.01068 RPN total loss: 0.06434 Total loss: 0.9636 timestamp: 1655043776.8368824 iteration: 45395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05494 FastRCNN class loss: 0.04526 FastRCNN total loss: 0.10019 L1 loss: 0.0000e+00 L2 loss: 0.59433 Learning rate: 0.002 Mask loss: 0.12666 RPN box loss: 0.03452 RPN score loss: 0.00319 RPN total loss: 0.03771 Total loss: 0.85889 timestamp: 1655043780.0848353 iteration: 45400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15115 FastRCNN class loss: 0.04239 FastRCNN total loss: 0.19354 L1 loss: 0.0000e+00 L2 loss: 0.59432 Learning rate: 0.002 Mask loss: 0.17466 RPN box loss: 0.01083 RPN score loss: 0.00212 RPN total loss: 0.01295 Total loss: 0.97547 timestamp: 1655043783.3418272 iteration: 45405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07215 FastRCNN class loss: 0.0772 FastRCNN total loss: 0.14935 L1 loss: 0.0000e+00 L2 loss: 0.59432 Learning rate: 0.002 Mask loss: 0.09478 RPN box loss: 0.01212 RPN score loss: 0.00248 RPN total loss: 0.0146 Total loss: 0.85304 timestamp: 1655043786.5986547 iteration: 45410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09783 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.14747 L1 loss: 0.0000e+00 L2 loss: 0.59431 Learning rate: 0.002 Mask loss: 0.12404 RPN box loss: 0.00732 RPN score loss: 0.0009 RPN total loss: 0.00822 Total loss: 0.87405 timestamp: 1655043789.901807 iteration: 45415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10772 FastRCNN class loss: 0.05572 FastRCNN total loss: 0.16344 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.002 Mask loss: 0.16918 RPN box loss: 0.0098 RPN score loss: 0.00455 RPN total loss: 0.01436 Total loss: 0.94128 timestamp: 1655043793.177734 iteration: 45420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05683 FastRCNN class loss: 0.04265 FastRCNN total loss: 0.09949 L1 loss: 0.0000e+00 L2 loss: 0.5943 Learning rate: 0.002 Mask loss: 0.09619 RPN box loss: 0.01234 RPN score loss: 0.00689 RPN total loss: 0.01922 Total loss: 0.8092 timestamp: 1655043796.4490833 iteration: 45425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06425 FastRCNN class loss: 0.07534 FastRCNN total loss: 0.13958 L1 loss: 0.0000e+00 L2 loss: 0.59428 Learning rate: 0.002 Mask loss: 0.16691 RPN box loss: 0.03562 RPN score loss: 0.01834 RPN total loss: 0.05396 Total loss: 0.95473 timestamp: 1655043799.7326705 iteration: 45430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.03637 FastRCNN total loss: 0.11983 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.002 Mask loss: 0.12677 RPN box loss: 0.01646 RPN score loss: 0.00676 RPN total loss: 0.02322 Total loss: 0.8641 timestamp: 1655043803.0070145 iteration: 45435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09741 FastRCNN class loss: 0.05332 FastRCNN total loss: 0.15073 L1 loss: 0.0000e+00 L2 loss: 0.59427 Learning rate: 0.002 Mask loss: 0.10471 RPN box loss: 0.02294 RPN score loss: 0.00447 RPN total loss: 0.02742 Total loss: 0.87713 timestamp: 1655043806.2685328 iteration: 45440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14249 FastRCNN class loss: 0.09799 FastRCNN total loss: 0.24048 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.002 Mask loss: 0.21428 RPN box loss: 0.03854 RPN score loss: 0.00886 RPN total loss: 0.0474 Total loss: 1.09642 timestamp: 1655043809.5719905 iteration: 45445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06699 FastRCNN class loss: 0.04245 FastRCNN total loss: 0.10944 L1 loss: 0.0000e+00 L2 loss: 0.59425 Learning rate: 0.002 Mask loss: 0.15356 RPN box loss: 0.01992 RPN score loss: 0.00503 RPN total loss: 0.02495 Total loss: 0.88219 timestamp: 1655043812.8388052 iteration: 45450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09536 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.59424 Learning rate: 0.002 Mask loss: 0.10171 RPN box loss: 0.02157 RPN score loss: 0.00207 RPN total loss: 0.02364 Total loss: 0.87208 timestamp: 1655043816.101558 iteration: 45455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17037 FastRCNN class loss: 0.09189 FastRCNN total loss: 0.26227 L1 loss: 0.0000e+00 L2 loss: 0.59423 Learning rate: 0.002 Mask loss: 0.15245 RPN box loss: 0.02702 RPN score loss: 0.01041 RPN total loss: 0.03743 Total loss: 1.04638 timestamp: 1655043819.383871 iteration: 45460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14217 FastRCNN class loss: 0.08388 FastRCNN total loss: 0.22604 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.002 Mask loss: 0.10269 RPN box loss: 0.01664 RPN score loss: 0.00312 RPN total loss: 0.01977 Total loss: 0.94272 timestamp: 1655043822.661641 iteration: 45465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11762 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.20056 L1 loss: 0.0000e+00 L2 loss: 0.59422 Learning rate: 0.002 Mask loss: 0.17455 RPN box loss: 0.02249 RPN score loss: 0.00608 RPN total loss: 0.02857 Total loss: 0.9979 timestamp: 1655043825.9068863 iteration: 45470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10261 FastRCNN class loss: 0.08483 FastRCNN total loss: 0.18743 L1 loss: 0.0000e+00 L2 loss: 0.59421 Learning rate: 0.002 Mask loss: 0.16901 RPN box loss: 0.02379 RPN score loss: 0.00958 RPN total loss: 0.03337 Total loss: 0.98401 timestamp: 1655043829.1409595 iteration: 45475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10243 FastRCNN class loss: 0.05098 FastRCNN total loss: 0.15341 L1 loss: 0.0000e+00 L2 loss: 0.5942 Learning rate: 0.002 Mask loss: 0.13463 RPN box loss: 0.01499 RPN score loss: 0.00391 RPN total loss: 0.0189 Total loss: 0.90113 timestamp: 1655043832.456787 iteration: 45480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05504 FastRCNN class loss: 0.04517 FastRCNN total loss: 0.10022 L1 loss: 0.0000e+00 L2 loss: 0.59418 Learning rate: 0.002 Mask loss: 0.11645 RPN box loss: 0.02614 RPN score loss: 0.00145 RPN total loss: 0.0276 Total loss: 0.83845 timestamp: 1655043835.7477834 iteration: 45485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13626 FastRCNN class loss: 0.08631 FastRCNN total loss: 0.22257 L1 loss: 0.0000e+00 L2 loss: 0.59417 Learning rate: 0.002 Mask loss: 0.22283 RPN box loss: 0.01215 RPN score loss: 0.00243 RPN total loss: 0.01457 Total loss: 1.05415 timestamp: 1655043839.0244844 iteration: 45490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12994 FastRCNN class loss: 0.13294 FastRCNN total loss: 0.26287 L1 loss: 0.0000e+00 L2 loss: 0.59416 Learning rate: 0.002 Mask loss: 0.15314 RPN box loss: 0.01793 RPN score loss: 0.00857 RPN total loss: 0.0265 Total loss: 1.03667 timestamp: 1655043842.2944858 iteration: 45495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11206 FastRCNN class loss: 0.08658 FastRCNN total loss: 0.19864 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.002 Mask loss: 0.14739 RPN box loss: 0.04452 RPN score loss: 0.00674 RPN total loss: 0.05127 Total loss: 0.99144 timestamp: 1655043845.5861022 iteration: 45500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0641 FastRCNN class loss: 0.04093 FastRCNN total loss: 0.10503 L1 loss: 0.0000e+00 L2 loss: 0.59415 Learning rate: 0.002 Mask loss: 0.09741 RPN box loss: 0.00359 RPN score loss: 0.00298 RPN total loss: 0.00657 Total loss: 0.80315 timestamp: 1655043848.888364 iteration: 45505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06503 FastRCNN class loss: 0.04985 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.59414 Learning rate: 0.002 Mask loss: 0.15932 RPN box loss: 0.01741 RPN score loss: 0.00103 RPN total loss: 0.01843 Total loss: 0.88677 timestamp: 1655043852.154982 iteration: 45510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1071 FastRCNN class loss: 0.10755 FastRCNN total loss: 0.21465 L1 loss: 0.0000e+00 L2 loss: 0.59413 Learning rate: 0.002 Mask loss: 0.15674 RPN box loss: 0.02474 RPN score loss: 0.00527 RPN total loss: 0.03001 Total loss: 0.99553 timestamp: 1655043855.4223804 iteration: 45515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10549 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.18606 L1 loss: 0.0000e+00 L2 loss: 0.59412 Learning rate: 0.002 Mask loss: 0.17657 RPN box loss: 0.02694 RPN score loss: 0.00916 RPN total loss: 0.0361 Total loss: 0.99285 timestamp: 1655043858.6688673 iteration: 45520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1298 FastRCNN class loss: 0.10014 FastRCNN total loss: 0.22994 L1 loss: 0.0000e+00 L2 loss: 0.59411 Learning rate: 0.002 Mask loss: 0.19801 RPN box loss: 0.0212 RPN score loss: 0.00911 RPN total loss: 0.03031 Total loss: 1.05237 timestamp: 1655043861.9617045 iteration: 45525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.06594 FastRCNN total loss: 0.17675 L1 loss: 0.0000e+00 L2 loss: 0.5941 Learning rate: 0.002 Mask loss: 0.09712 RPN box loss: 0.02113 RPN score loss: 0.00303 RPN total loss: 0.02416 Total loss: 0.89213 timestamp: 1655043865.2065575 iteration: 45530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11201 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.59409 Learning rate: 0.002 Mask loss: 0.20253 RPN box loss: 0.01391 RPN score loss: 0.00546 RPN total loss: 0.01938 Total loss: 0.99723 timestamp: 1655043868.4896538 iteration: 45535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11551 FastRCNN class loss: 0.11296 FastRCNN total loss: 0.22847 L1 loss: 0.0000e+00 L2 loss: 0.59408 Learning rate: 0.002 Mask loss: 0.20268 RPN box loss: 0.02474 RPN score loss: 0.01116 RPN total loss: 0.0359 Total loss: 1.06114 timestamp: 1655043871.7788446 iteration: 45540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14893 FastRCNN class loss: 0.07766 FastRCNN total loss: 0.22659 L1 loss: 0.0000e+00 L2 loss: 0.59407 Learning rate: 0.002 Mask loss: 0.14456 RPN box loss: 0.02511 RPN score loss: 0.00892 RPN total loss: 0.03403 Total loss: 0.99925 timestamp: 1655043875.057292 iteration: 45545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17858 FastRCNN class loss: 0.1095 FastRCNN total loss: 0.28808 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.002 Mask loss: 0.18391 RPN box loss: 0.02722 RPN score loss: 0.00423 RPN total loss: 0.03146 Total loss: 1.09752 timestamp: 1655043878.3634784 iteration: 45550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11545 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.17457 L1 loss: 0.0000e+00 L2 loss: 0.59406 Learning rate: 0.002 Mask loss: 0.09536 RPN box loss: 0.01892 RPN score loss: 0.00447 RPN total loss: 0.02339 Total loss: 0.88738 timestamp: 1655043881.6468449 iteration: 45555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15211 FastRCNN class loss: 0.11153 FastRCNN total loss: 0.26363 L1 loss: 0.0000e+00 L2 loss: 0.59404 Learning rate: 0.002 Mask loss: 0.24142 RPN box loss: 0.03083 RPN score loss: 0.0175 RPN total loss: 0.04833 Total loss: 1.14743 timestamp: 1655043884.95169 iteration: 45560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06346 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.10807 L1 loss: 0.0000e+00 L2 loss: 0.59403 Learning rate: 0.002 Mask loss: 0.1221 RPN box loss: 0.02245 RPN score loss: 0.00705 RPN total loss: 0.02951 Total loss: 0.85371 timestamp: 1655043888.1865926 iteration: 45565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17472 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.24626 L1 loss: 0.0000e+00 L2 loss: 0.59402 Learning rate: 0.002 Mask loss: 0.18252 RPN box loss: 0.01594 RPN score loss: 0.00582 RPN total loss: 0.02177 Total loss: 1.04457 timestamp: 1655043891.4271355 iteration: 45570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06819 FastRCNN class loss: 0.06508 FastRCNN total loss: 0.13327 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.002 Mask loss: 0.14579 RPN box loss: 0.0237 RPN score loss: 0.01013 RPN total loss: 0.03383 Total loss: 0.90691 timestamp: 1655043894.6933932 iteration: 45575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14594 FastRCNN class loss: 0.11874 FastRCNN total loss: 0.26468 L1 loss: 0.0000e+00 L2 loss: 0.59401 Learning rate: 0.002 Mask loss: 0.11734 RPN box loss: 0.01744 RPN score loss: 0.00622 RPN total loss: 0.02366 Total loss: 0.99968 timestamp: 1655043897.9652007 iteration: 45580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0759 FastRCNN class loss: 0.12616 FastRCNN total loss: 0.20206 L1 loss: 0.0000e+00 L2 loss: 0.594 Learning rate: 0.002 Mask loss: 0.12565 RPN box loss: 0.03054 RPN score loss: 0.00505 RPN total loss: 0.0356 Total loss: 0.95731 timestamp: 1655043901.236527 iteration: 45585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11038 FastRCNN class loss: 0.05636 FastRCNN total loss: 0.16674 L1 loss: 0.0000e+00 L2 loss: 0.59398 Learning rate: 0.002 Mask loss: 0.10229 RPN box loss: 0.00855 RPN score loss: 0.00096 RPN total loss: 0.0095 Total loss: 0.87251 timestamp: 1655043904.5257494 iteration: 45590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09725 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.16787 L1 loss: 0.0000e+00 L2 loss: 0.59397 Learning rate: 0.002 Mask loss: 0.13617 RPN box loss: 0.04468 RPN score loss: 0.00612 RPN total loss: 0.0508 Total loss: 0.94882 timestamp: 1655043907.87627 iteration: 45595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.17544 L1 loss: 0.0000e+00 L2 loss: 0.59396 Learning rate: 0.002 Mask loss: 0.17163 RPN box loss: 0.02712 RPN score loss: 0.01178 RPN total loss: 0.0389 Total loss: 0.97994 timestamp: 1655043911.1002727 iteration: 45600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15869 FastRCNN class loss: 0.13565 FastRCNN total loss: 0.29434 L1 loss: 0.0000e+00 L2 loss: 0.59395 Learning rate: 0.002 Mask loss: 0.18638 RPN box loss: 0.01714 RPN score loss: 0.0072 RPN total loss: 0.02434 Total loss: 1.09901 timestamp: 1655043914.3863018 iteration: 45605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05489 FastRCNN class loss: 0.03025 FastRCNN total loss: 0.08514 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.002 Mask loss: 0.1096 RPN box loss: 0.0031 RPN score loss: 0.00084 RPN total loss: 0.00394 Total loss: 0.79262 timestamp: 1655043917.6624842 iteration: 45610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07496 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.14209 L1 loss: 0.0000e+00 L2 loss: 0.59394 Learning rate: 0.002 Mask loss: 0.14972 RPN box loss: 0.02638 RPN score loss: 0.00487 RPN total loss: 0.03124 Total loss: 0.91699 timestamp: 1655043920.8365517 iteration: 45615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14688 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.21026 L1 loss: 0.0000e+00 L2 loss: 0.59393 Learning rate: 0.002 Mask loss: 0.19152 RPN box loss: 0.01228 RPN score loss: 0.00695 RPN total loss: 0.01923 Total loss: 1.01493 timestamp: 1655043924.107827 iteration: 45620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12833 FastRCNN class loss: 0.06793 FastRCNN total loss: 0.19626 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.002 Mask loss: 0.15151 RPN box loss: 0.03257 RPN score loss: 0.00749 RPN total loss: 0.04005 Total loss: 0.98175 timestamp: 1655043927.3441124 iteration: 45625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16069 FastRCNN class loss: 0.07719 FastRCNN total loss: 0.23788 L1 loss: 0.0000e+00 L2 loss: 0.59392 Learning rate: 0.002 Mask loss: 0.15761 RPN box loss: 0.04091 RPN score loss: 0.00175 RPN total loss: 0.04265 Total loss: 1.03206 timestamp: 1655043930.6656094 iteration: 45630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12315 FastRCNN class loss: 0.09204 FastRCNN total loss: 0.21519 L1 loss: 0.0000e+00 L2 loss: 0.59391 Learning rate: 0.002 Mask loss: 0.16939 RPN box loss: 0.0146 RPN score loss: 0.00765 RPN total loss: 0.02225 Total loss: 1.00074 timestamp: 1655043933.9637318 iteration: 45635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15931 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.22923 L1 loss: 0.0000e+00 L2 loss: 0.5939 Learning rate: 0.002 Mask loss: 0.17918 RPN box loss: 0.01376 RPN score loss: 0.0024 RPN total loss: 0.01616 Total loss: 1.01847 timestamp: 1655043937.2104185 iteration: 45640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08327 FastRCNN class loss: 0.06302 FastRCNN total loss: 0.14629 L1 loss: 0.0000e+00 L2 loss: 0.59389 Learning rate: 0.002 Mask loss: 0.10164 RPN box loss: 0.00623 RPN score loss: 0.00435 RPN total loss: 0.01059 Total loss: 0.8524 timestamp: 1655043940.432885 iteration: 45645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09281 FastRCNN class loss: 0.03852 FastRCNN total loss: 0.13133 L1 loss: 0.0000e+00 L2 loss: 0.59388 Learning rate: 0.002 Mask loss: 0.12545 RPN box loss: 0.012 RPN score loss: 0.00324 RPN total loss: 0.01524 Total loss: 0.8659 timestamp: 1655043943.7126372 iteration: 45650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07368 FastRCNN class loss: 0.04737 FastRCNN total loss: 0.12105 L1 loss: 0.0000e+00 L2 loss: 0.59387 Learning rate: 0.002 Mask loss: 0.18057 RPN box loss: 0.01485 RPN score loss: 0.0028 RPN total loss: 0.01765 Total loss: 0.91313 timestamp: 1655043946.970828 iteration: 45655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16326 FastRCNN class loss: 0.1207 FastRCNN total loss: 0.28396 L1 loss: 0.0000e+00 L2 loss: 0.59386 Learning rate: 0.002 Mask loss: 0.2121 RPN box loss: 0.01788 RPN score loss: 0.00988 RPN total loss: 0.02776 Total loss: 1.11767 timestamp: 1655043950.2467346 iteration: 45660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09612 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.16362 L1 loss: 0.0000e+00 L2 loss: 0.59385 Learning rate: 0.002 Mask loss: 0.12407 RPN box loss: 0.02713 RPN score loss: 0.00519 RPN total loss: 0.03232 Total loss: 0.91387 timestamp: 1655043953.572285 iteration: 45665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12561 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.20759 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.002 Mask loss: 0.15486 RPN box loss: 0.04308 RPN score loss: 0.01641 RPN total loss: 0.05948 Total loss: 1.01578 timestamp: 1655043956.906274 iteration: 45670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09434 FastRCNN class loss: 0.04184 FastRCNN total loss: 0.13618 L1 loss: 0.0000e+00 L2 loss: 0.59384 Learning rate: 0.002 Mask loss: 0.09456 RPN box loss: 0.05131 RPN score loss: 0.0014 RPN total loss: 0.05271 Total loss: 0.87728 timestamp: 1655043960.1924896 iteration: 45675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06175 FastRCNN class loss: 0.08419 FastRCNN total loss: 0.14594 L1 loss: 0.0000e+00 L2 loss: 0.59383 Learning rate: 0.002 Mask loss: 0.17916 RPN box loss: 0.00485 RPN score loss: 0.00096 RPN total loss: 0.00581 Total loss: 0.92474 timestamp: 1655043963.453693 iteration: 45680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14028 FastRCNN class loss: 0.10769 FastRCNN total loss: 0.24796 L1 loss: 0.0000e+00 L2 loss: 0.59382 Learning rate: 0.002 Mask loss: 0.18457 RPN box loss: 0.02216 RPN score loss: 0.00697 RPN total loss: 0.02913 Total loss: 1.05548 timestamp: 1655043966.602801 iteration: 45685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12112 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.19596 L1 loss: 0.0000e+00 L2 loss: 0.59381 Learning rate: 0.002 Mask loss: 0.14278 RPN box loss: 0.02624 RPN score loss: 0.00329 RPN total loss: 0.02953 Total loss: 0.96209 timestamp: 1655043969.8287609 iteration: 45690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09736 FastRCNN class loss: 0.08103 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.5938 Learning rate: 0.002 Mask loss: 0.12508 RPN box loss: 0.02863 RPN score loss: 0.00935 RPN total loss: 0.03797 Total loss: 0.93525 timestamp: 1655043973.0982907 iteration: 45695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07485 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.13704 L1 loss: 0.0000e+00 L2 loss: 0.59379 Learning rate: 0.002 Mask loss: 0.11991 RPN box loss: 0.0288 RPN score loss: 0.00799 RPN total loss: 0.03679 Total loss: 0.88753 timestamp: 1655043976.4003847 iteration: 45700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14704 FastRCNN class loss: 0.09944 FastRCNN total loss: 0.24648 L1 loss: 0.0000e+00 L2 loss: 0.59378 Learning rate: 0.002 Mask loss: 0.13964 RPN box loss: 0.00707 RPN score loss: 0.00673 RPN total loss: 0.01381 Total loss: 0.99371 timestamp: 1655043979.6977515 iteration: 45705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04851 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.09567 L1 loss: 0.0000e+00 L2 loss: 0.59377 Learning rate: 0.002 Mask loss: 0.18202 RPN box loss: 0.00547 RPN score loss: 0.00547 RPN total loss: 0.01094 Total loss: 0.88241 timestamp: 1655043982.9826803 iteration: 45710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13138 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.20926 L1 loss: 0.0000e+00 L2 loss: 0.59376 Learning rate: 0.002 Mask loss: 0.20855 RPN box loss: 0.0251 RPN score loss: 0.01251 RPN total loss: 0.03761 Total loss: 1.04918 timestamp: 1655043986.2390635 iteration: 45715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.16729 L1 loss: 0.0000e+00 L2 loss: 0.59375 Learning rate: 0.002 Mask loss: 0.15742 RPN box loss: 0.02961 RPN score loss: 0.00383 RPN total loss: 0.03343 Total loss: 0.95189 timestamp: 1655043989.522374 iteration: 45720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.04368 FastRCNN total loss: 0.1304 L1 loss: 0.0000e+00 L2 loss: 0.59374 Learning rate: 0.002 Mask loss: 0.11198 RPN box loss: 0.01524 RPN score loss: 0.0017 RPN total loss: 0.01695 Total loss: 0.85307 timestamp: 1655043992.8810902 iteration: 45725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07604 FastRCNN class loss: 0.04816 FastRCNN total loss: 0.1242 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.002 Mask loss: 0.13355 RPN box loss: 0.02296 RPN score loss: 0.00409 RPN total loss: 0.02705 Total loss: 0.87853 timestamp: 1655043996.1776218 iteration: 45730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10426 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.19162 L1 loss: 0.0000e+00 L2 loss: 0.59373 Learning rate: 0.002 Mask loss: 0.13394 RPN box loss: 0.02818 RPN score loss: 0.00288 RPN total loss: 0.03106 Total loss: 0.95035 timestamp: 1655043999.4640076 iteration: 45735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07046 FastRCNN class loss: 0.0497 FastRCNN total loss: 0.12016 L1 loss: 0.0000e+00 L2 loss: 0.59372 Learning rate: 0.002 Mask loss: 0.12986 RPN box loss: 0.01335 RPN score loss: 0.0052 RPN total loss: 0.01855 Total loss: 0.86229 timestamp: 1655044002.7269657 iteration: 45740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0954 FastRCNN class loss: 0.08588 FastRCNN total loss: 0.18128 L1 loss: 0.0000e+00 L2 loss: 0.59371 Learning rate: 0.002 Mask loss: 0.14879 RPN box loss: 0.03053 RPN score loss: 0.01773 RPN total loss: 0.04826 Total loss: 0.97204 timestamp: 1655044006.0009644 iteration: 45745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12553 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.18547 L1 loss: 0.0000e+00 L2 loss: 0.5937 Learning rate: 0.002 Mask loss: 0.17743 RPN box loss: 0.01126 RPN score loss: 0.00366 RPN total loss: 0.01492 Total loss: 0.97152 timestamp: 1655044009.3312867 iteration: 45750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.1657 L1 loss: 0.0000e+00 L2 loss: 0.59369 Learning rate: 0.002 Mask loss: 0.14222 RPN box loss: 0.01794 RPN score loss: 0.00637 RPN total loss: 0.02431 Total loss: 0.92591 timestamp: 1655044012.6194856 iteration: 45755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06408 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 0.59368 Learning rate: 0.002 Mask loss: 0.10326 RPN box loss: 0.00854 RPN score loss: 0.00379 RPN total loss: 0.01233 Total loss: 0.85628 timestamp: 1655044015.914467 iteration: 45760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08392 FastRCNN class loss: 0.06642 FastRCNN total loss: 0.15034 L1 loss: 0.0000e+00 L2 loss: 0.59367 Learning rate: 0.002 Mask loss: 0.17872 RPN box loss: 0.01752 RPN score loss: 0.00598 RPN total loss: 0.0235 Total loss: 0.94622 timestamp: 1655044019.200512 iteration: 45765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09818 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.16854 L1 loss: 0.0000e+00 L2 loss: 0.59366 Learning rate: 0.002 Mask loss: 0.15872 RPN box loss: 0.00883 RPN score loss: 0.00671 RPN total loss: 0.01555 Total loss: 0.93646 timestamp: 1655044022.5026388 iteration: 45770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10608 FastRCNN class loss: 0.09713 FastRCNN total loss: 0.20321 L1 loss: 0.0000e+00 L2 loss: 0.59365 Learning rate: 0.002 Mask loss: 0.17379 RPN box loss: 0.0665 RPN score loss: 0.00537 RPN total loss: 0.07187 Total loss: 1.04253 timestamp: 1655044025.7586627 iteration: 45775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07202 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.11663 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.002 Mask loss: 0.15455 RPN box loss: 0.00526 RPN score loss: 0.00879 RPN total loss: 0.01405 Total loss: 0.87888 timestamp: 1655044028.9983265 iteration: 45780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06768 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.13694 L1 loss: 0.0000e+00 L2 loss: 0.59364 Learning rate: 0.002 Mask loss: 0.11343 RPN box loss: 0.01077 RPN score loss: 0.0018 RPN total loss: 0.01257 Total loss: 0.85658 timestamp: 1655044032.3026621 iteration: 45785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08331 FastRCNN class loss: 0.05881 FastRCNN total loss: 0.14212 L1 loss: 0.0000e+00 L2 loss: 0.59363 Learning rate: 0.002 Mask loss: 0.15509 RPN box loss: 0.01149 RPN score loss: 0.0043 RPN total loss: 0.0158 Total loss: 0.90663 timestamp: 1655044035.529329 iteration: 45790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.15848 L1 loss: 0.0000e+00 L2 loss: 0.59361 Learning rate: 0.002 Mask loss: 0.15054 RPN box loss: 0.02998 RPN score loss: 0.01088 RPN total loss: 0.04086 Total loss: 0.94349 timestamp: 1655044038.8499641 iteration: 45795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05536 FastRCNN class loss: 0.03944 FastRCNN total loss: 0.0948 L1 loss: 0.0000e+00 L2 loss: 0.5936 Learning rate: 0.002 Mask loss: 0.12223 RPN box loss: 0.01699 RPN score loss: 0.00304 RPN total loss: 0.02003 Total loss: 0.83067 timestamp: 1655044042.1435435 iteration: 45800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1725 FastRCNN class loss: 0.09058 FastRCNN total loss: 0.26308 L1 loss: 0.0000e+00 L2 loss: 0.59359 Learning rate: 0.002 Mask loss: 0.17021 RPN box loss: 0.01826 RPN score loss: 0.00772 RPN total loss: 0.02598 Total loss: 1.05286 timestamp: 1655044045.461776 iteration: 45805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11695 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.20194 L1 loss: 0.0000e+00 L2 loss: 0.59358 Learning rate: 0.002 Mask loss: 0.1444 RPN box loss: 0.05522 RPN score loss: 0.00862 RPN total loss: 0.06384 Total loss: 1.00376 timestamp: 1655044048.7687392 iteration: 45810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11774 FastRCNN class loss: 0.11531 FastRCNN total loss: 0.23305 L1 loss: 0.0000e+00 L2 loss: 0.59357 Learning rate: 0.002 Mask loss: 0.17138 RPN box loss: 0.04416 RPN score loss: 0.01634 RPN total loss: 0.0605 Total loss: 1.0585 timestamp: 1655044052.0204928 iteration: 45815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10564 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.18475 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.002 Mask loss: 0.22272 RPN box loss: 0.02281 RPN score loss: 0.00989 RPN total loss: 0.0327 Total loss: 1.03373 timestamp: 1655044055.2773075 iteration: 45820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13678 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.20909 L1 loss: 0.0000e+00 L2 loss: 0.59356 Learning rate: 0.002 Mask loss: 0.16613 RPN box loss: 0.00852 RPN score loss: 0.00218 RPN total loss: 0.0107 Total loss: 0.97947 timestamp: 1655044058.5095668 iteration: 45825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03545 FastRCNN class loss: 0.04225 FastRCNN total loss: 0.07771 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.002 Mask loss: 0.14946 RPN box loss: 0.00859 RPN score loss: 0.00482 RPN total loss: 0.01341 Total loss: 0.83413 timestamp: 1655044061.7431226 iteration: 45830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12952 FastRCNN class loss: 0.08559 FastRCNN total loss: 0.21511 L1 loss: 0.0000e+00 L2 loss: 0.59355 Learning rate: 0.002 Mask loss: 0.15173 RPN box loss: 0.04205 RPN score loss: 0.00788 RPN total loss: 0.04993 Total loss: 1.01032 timestamp: 1655044065.0402813 iteration: 45835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10048 FastRCNN class loss: 0.06637 FastRCNN total loss: 0.16685 L1 loss: 0.0000e+00 L2 loss: 0.59354 Learning rate: 0.002 Mask loss: 0.13769 RPN box loss: 0.00921 RPN score loss: 0.00359 RPN total loss: 0.0128 Total loss: 0.91088 timestamp: 1655044068.287126 iteration: 45840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11125 FastRCNN class loss: 0.07578 FastRCNN total loss: 0.18704 L1 loss: 0.0000e+00 L2 loss: 0.59353 Learning rate: 0.002 Mask loss: 0.284 RPN box loss: 0.04479 RPN score loss: 0.01098 RPN total loss: 0.05577 Total loss: 1.12034 timestamp: 1655044071.5633438 iteration: 45845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07001 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.13447 L1 loss: 0.0000e+00 L2 loss: 0.59352 Learning rate: 0.002 Mask loss: 0.13557 RPN box loss: 0.01126 RPN score loss: 0.00358 RPN total loss: 0.01484 Total loss: 0.8784 timestamp: 1655044074.864794 iteration: 45850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10533 FastRCNN class loss: 0.12924 FastRCNN total loss: 0.23457 L1 loss: 0.0000e+00 L2 loss: 0.59351 Learning rate: 0.002 Mask loss: 0.1607 RPN box loss: 0.04761 RPN score loss: 0.00711 RPN total loss: 0.05472 Total loss: 1.0435 timestamp: 1655044078.100304 iteration: 45855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07026 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.1377 L1 loss: 0.0000e+00 L2 loss: 0.5935 Learning rate: 0.002 Mask loss: 0.18715 RPN box loss: 0.01847 RPN score loss: 0.0144 RPN total loss: 0.03288 Total loss: 0.95123 timestamp: 1655044081.4188278 iteration: 45860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.04786 FastRCNN total loss: 0.12662 L1 loss: 0.0000e+00 L2 loss: 0.59349 Learning rate: 0.002 Mask loss: 0.09008 RPN box loss: 0.00553 RPN score loss: 0.0024 RPN total loss: 0.00794 Total loss: 0.81812 timestamp: 1655044084.7255862 iteration: 45865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06942 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.1308 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.002 Mask loss: 0.10177 RPN box loss: 0.0121 RPN score loss: 0.00347 RPN total loss: 0.01557 Total loss: 0.84163 timestamp: 1655044088.0325644 iteration: 45870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07356 FastRCNN class loss: 0.09893 FastRCNN total loss: 0.17249 L1 loss: 0.0000e+00 L2 loss: 0.59348 Learning rate: 0.002 Mask loss: 0.09931 RPN box loss: 0.01191 RPN score loss: 0.0035 RPN total loss: 0.01541 Total loss: 0.88069 timestamp: 1655044091.2769287 iteration: 45875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05892 FastRCNN class loss: 0.04247 FastRCNN total loss: 0.10139 L1 loss: 0.0000e+00 L2 loss: 0.59347 Learning rate: 0.002 Mask loss: 0.1375 RPN box loss: 0.01454 RPN score loss: 0.01223 RPN total loss: 0.02677 Total loss: 0.85913 timestamp: 1655044094.5285568 iteration: 45880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10602 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.17267 L1 loss: 0.0000e+00 L2 loss: 0.59346 Learning rate: 0.002 Mask loss: 0.12377 RPN box loss: 0.01924 RPN score loss: 0.00192 RPN total loss: 0.02116 Total loss: 0.91106 timestamp: 1655044097.866605 iteration: 45885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12878 FastRCNN class loss: 0.09722 FastRCNN total loss: 0.226 L1 loss: 0.0000e+00 L2 loss: 0.59345 Learning rate: 0.002 Mask loss: 0.20787 RPN box loss: 0.0143 RPN score loss: 0.01033 RPN total loss: 0.02463 Total loss: 1.05195 timestamp: 1655044101.1901052 iteration: 45890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1305 FastRCNN class loss: 0.12259 FastRCNN total loss: 0.25309 L1 loss: 0.0000e+00 L2 loss: 0.59344 Learning rate: 0.002 Mask loss: 0.1498 RPN box loss: 0.02396 RPN score loss: 0.00715 RPN total loss: 0.03111 Total loss: 1.02744 timestamp: 1655044104.4390886 iteration: 45895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13977 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.21208 L1 loss: 0.0000e+00 L2 loss: 0.59342 Learning rate: 0.002 Mask loss: 0.1179 RPN box loss: 0.02037 RPN score loss: 0.00175 RPN total loss: 0.02212 Total loss: 0.94553 timestamp: 1655044107.6253965 iteration: 45900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.16591 L1 loss: 0.0000e+00 L2 loss: 0.59341 Learning rate: 0.002 Mask loss: 0.13728 RPN box loss: 0.01002 RPN score loss: 0.00152 RPN total loss: 0.01154 Total loss: 0.90813 timestamp: 1655044110.8494132 iteration: 45905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13557 FastRCNN class loss: 0.08379 FastRCNN total loss: 0.21936 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.002 Mask loss: 0.21612 RPN box loss: 0.04161 RPN score loss: 0.00991 RPN total loss: 0.05152 Total loss: 1.0804 timestamp: 1655044114.1408367 iteration: 45910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16982 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.25889 L1 loss: 0.0000e+00 L2 loss: 0.5934 Learning rate: 0.002 Mask loss: 0.13816 RPN box loss: 0.01012 RPN score loss: 0.006 RPN total loss: 0.01612 Total loss: 1.00656 timestamp: 1655044117.4004567 iteration: 45915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.08665 FastRCNN total loss: 0.20791 L1 loss: 0.0000e+00 L2 loss: 0.59339 Learning rate: 0.002 Mask loss: 0.15325 RPN box loss: 0.01612 RPN score loss: 0.00552 RPN total loss: 0.02164 Total loss: 0.97618 timestamp: 1655044120.7242217 iteration: 45920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.07342 FastRCNN total loss: 0.17216 L1 loss: 0.0000e+00 L2 loss: 0.59338 Learning rate: 0.002 Mask loss: 0.1474 RPN box loss: 0.02045 RPN score loss: 0.00845 RPN total loss: 0.02891 Total loss: 0.94185 timestamp: 1655044123.9605358 iteration: 45925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10027 FastRCNN class loss: 0.10174 FastRCNN total loss: 0.20202 L1 loss: 0.0000e+00 L2 loss: 0.59337 Learning rate: 0.002 Mask loss: 0.13397 RPN box loss: 0.01721 RPN score loss: 0.00771 RPN total loss: 0.02493 Total loss: 0.95429 timestamp: 1655044127.2721677 iteration: 45930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15846 FastRCNN class loss: 0.11476 FastRCNN total loss: 0.27321 L1 loss: 0.0000e+00 L2 loss: 0.59336 Learning rate: 0.002 Mask loss: 0.20358 RPN box loss: 0.0194 RPN score loss: 0.00469 RPN total loss: 0.02409 Total loss: 1.09425 timestamp: 1655044130.5500064 iteration: 45935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13351 FastRCNN class loss: 0.05567 FastRCNN total loss: 0.18918 L1 loss: 0.0000e+00 L2 loss: 0.59335 Learning rate: 0.002 Mask loss: 0.12541 RPN box loss: 0.023 RPN score loss: 0.00611 RPN total loss: 0.02911 Total loss: 0.93705 timestamp: 1655044133.778536 iteration: 45940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06267 FastRCNN class loss: 0.0833 FastRCNN total loss: 0.14597 L1 loss: 0.0000e+00 L2 loss: 0.59334 Learning rate: 0.002 Mask loss: 0.18084 RPN box loss: 0.02931 RPN score loss: 0.01084 RPN total loss: 0.04016 Total loss: 0.9603 timestamp: 1655044137.084381 iteration: 45945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14064 FastRCNN class loss: 0.1087 FastRCNN total loss: 0.24934 L1 loss: 0.0000e+00 L2 loss: 0.59333 Learning rate: 0.002 Mask loss: 0.17344 RPN box loss: 0.03508 RPN score loss: 0.02008 RPN total loss: 0.05517 Total loss: 1.07128 timestamp: 1655044140.3962703 iteration: 45950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13835 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.19886 L1 loss: 0.0000e+00 L2 loss: 0.59332 Learning rate: 0.002 Mask loss: 0.14382 RPN box loss: 0.02573 RPN score loss: 0.00375 RPN total loss: 0.02949 Total loss: 0.96549 timestamp: 1655044143.7212546 iteration: 45955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14245 FastRCNN class loss: 0.09142 FastRCNN total loss: 0.23387 L1 loss: 0.0000e+00 L2 loss: 0.59331 Learning rate: 0.002 Mask loss: 0.15817 RPN box loss: 0.01638 RPN score loss: 0.00272 RPN total loss: 0.0191 Total loss: 1.00445 timestamp: 1655044146.9933968 iteration: 45960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16814 FastRCNN class loss: 0.077 FastRCNN total loss: 0.24514 L1 loss: 0.0000e+00 L2 loss: 0.5933 Learning rate: 0.002 Mask loss: 0.13619 RPN box loss: 0.00946 RPN score loss: 0.00605 RPN total loss: 0.01551 Total loss: 0.99013 timestamp: 1655044150.1907036 iteration: 45965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1826 FastRCNN class loss: 0.1265 FastRCNN total loss: 0.3091 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.002 Mask loss: 0.19452 RPN box loss: 0.01915 RPN score loss: 0.01665 RPN total loss: 0.0358 Total loss: 1.13271 timestamp: 1655044153.5022838 iteration: 45970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09575 FastRCNN class loss: 0.04351 FastRCNN total loss: 0.13926 L1 loss: 0.0000e+00 L2 loss: 0.59329 Learning rate: 0.002 Mask loss: 0.12456 RPN box loss: 0.00616 RPN score loss: 0.00106 RPN total loss: 0.00722 Total loss: 0.86433 timestamp: 1655044156.7871346 iteration: 45975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14828 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.23801 L1 loss: 0.0000e+00 L2 loss: 0.59328 Learning rate: 0.002 Mask loss: 0.18681 RPN box loss: 0.02321 RPN score loss: 0.00385 RPN total loss: 0.02706 Total loss: 1.04515 timestamp: 1655044160.0737634 iteration: 45980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04848 FastRCNN class loss: 0.05192 FastRCNN total loss: 0.1004 L1 loss: 0.0000e+00 L2 loss: 0.59327 Learning rate: 0.002 Mask loss: 0.18103 RPN box loss: 0.02271 RPN score loss: 0.00348 RPN total loss: 0.02619 Total loss: 0.90088 timestamp: 1655044163.30144 iteration: 45985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11422 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.18783 L1 loss: 0.0000e+00 L2 loss: 0.59326 Learning rate: 0.002 Mask loss: 0.18917 RPN box loss: 0.01404 RPN score loss: 0.00229 RPN total loss: 0.01633 Total loss: 0.98658 timestamp: 1655044166.5159812 iteration: 45990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11989 FastRCNN class loss: 0.08465 FastRCNN total loss: 0.20454 L1 loss: 0.0000e+00 L2 loss: 0.59325 Learning rate: 0.002 Mask loss: 0.12221 RPN box loss: 0.02845 RPN score loss: 0.00366 RPN total loss: 0.03211 Total loss: 0.95211 timestamp: 1655044169.7802508 iteration: 45995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04134 FastRCNN class loss: 0.02914 FastRCNN total loss: 0.07048 L1 loss: 0.0000e+00 L2 loss: 0.59324 Learning rate: 0.002 Mask loss: 0.13084 RPN box loss: 0.0013 RPN score loss: 0.00177 RPN total loss: 0.00306 Total loss: 0.79763 timestamp: 1655044173.0903578 iteration: 46000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08504 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.14098 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.002 Mask loss: 0.19988 RPN box loss: 0.01336 RPN score loss: 0.00158 RPN total loss: 0.01495 Total loss: 0.94905 timestamp: 1655044176.3356717 iteration: 46005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.17 L1 loss: 0.0000e+00 L2 loss: 0.59323 Learning rate: 0.002 Mask loss: 0.10512 RPN box loss: 0.01282 RPN score loss: 0.00174 RPN total loss: 0.01456 Total loss: 0.88291 timestamp: 1655044179.6622894 iteration: 46010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09237 FastRCNN class loss: 0.13866 FastRCNN total loss: 0.23103 L1 loss: 0.0000e+00 L2 loss: 0.59322 Learning rate: 0.002 Mask loss: 0.17654 RPN box loss: 0.02366 RPN score loss: 0.00404 RPN total loss: 0.0277 Total loss: 1.02849 timestamp: 1655044182.958237 iteration: 46015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12163 FastRCNN class loss: 0.09019 FastRCNN total loss: 0.21182 L1 loss: 0.0000e+00 L2 loss: 0.59321 Learning rate: 0.002 Mask loss: 0.14812 RPN box loss: 0.01074 RPN score loss: 0.00791 RPN total loss: 0.01865 Total loss: 0.9718 timestamp: 1655044186.252789 iteration: 46020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14285 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.21542 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.002 Mask loss: 0.15239 RPN box loss: 0.01537 RPN score loss: 0.00708 RPN total loss: 0.02245 Total loss: 0.98346 timestamp: 1655044189.5334587 iteration: 46025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1701 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.2355 L1 loss: 0.0000e+00 L2 loss: 0.5932 Learning rate: 0.002 Mask loss: 0.12343 RPN box loss: 0.03279 RPN score loss: 0.00488 RPN total loss: 0.03766 Total loss: 0.98978 timestamp: 1655044192.8556921 iteration: 46030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09046 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.16576 L1 loss: 0.0000e+00 L2 loss: 0.59319 Learning rate: 0.002 Mask loss: 0.30825 RPN box loss: 0.03673 RPN score loss: 0.0029 RPN total loss: 0.03962 Total loss: 1.10683 timestamp: 1655044196.1129413 iteration: 46035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.11192 FastRCNN total loss: 0.20462 L1 loss: 0.0000e+00 L2 loss: 0.59318 Learning rate: 0.002 Mask loss: 0.15127 RPN box loss: 0.02006 RPN score loss: 0.0148 RPN total loss: 0.03486 Total loss: 0.98393 timestamp: 1655044199.3922274 iteration: 46040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12898 FastRCNN class loss: 0.09961 FastRCNN total loss: 0.22859 L1 loss: 0.0000e+00 L2 loss: 0.59317 Learning rate: 0.002 Mask loss: 0.16297 RPN box loss: 0.01063 RPN score loss: 0.00655 RPN total loss: 0.01718 Total loss: 1.00191 timestamp: 1655044202.665168 iteration: 46045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13779 FastRCNN class loss: 0.09223 FastRCNN total loss: 0.23001 L1 loss: 0.0000e+00 L2 loss: 0.59316 Learning rate: 0.002 Mask loss: 0.24871 RPN box loss: 0.02539 RPN score loss: 0.0071 RPN total loss: 0.03249 Total loss: 1.10437 timestamp: 1655044205.9263237 iteration: 46050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.21268 L1 loss: 0.0000e+00 L2 loss: 0.59314 Learning rate: 0.002 Mask loss: 0.1477 RPN box loss: 0.06573 RPN score loss: 0.00675 RPN total loss: 0.07247 Total loss: 1.02599 timestamp: 1655044209.2152693 iteration: 46055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05895 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.1058 L1 loss: 0.0000e+00 L2 loss: 0.59313 Learning rate: 0.002 Mask loss: 0.09723 RPN box loss: 0.05494 RPN score loss: 0.00308 RPN total loss: 0.05802 Total loss: 0.85418 timestamp: 1655044212.520152 iteration: 46060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12643 FastRCNN class loss: 0.07838 FastRCNN total loss: 0.20481 L1 loss: 0.0000e+00 L2 loss: 0.59312 Learning rate: 0.002 Mask loss: 0.15056 RPN box loss: 0.02845 RPN score loss: 0.00799 RPN total loss: 0.03645 Total loss: 0.98494 timestamp: 1655044215.7949114 iteration: 46065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07989 FastRCNN class loss: 0.0592 FastRCNN total loss: 0.13909 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.002 Mask loss: 0.13159 RPN box loss: 0.01459 RPN score loss: 0.00344 RPN total loss: 0.01802 Total loss: 0.88182 timestamp: 1655044219.1123555 iteration: 46070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16451 FastRCNN class loss: 0.11299 FastRCNN total loss: 0.27751 L1 loss: 0.0000e+00 L2 loss: 0.59311 Learning rate: 0.002 Mask loss: 0.15549 RPN box loss: 0.01815 RPN score loss: 0.0055 RPN total loss: 0.02365 Total loss: 1.04975 timestamp: 1655044222.3490872 iteration: 46075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13521 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.19788 L1 loss: 0.0000e+00 L2 loss: 0.5931 Learning rate: 0.002 Mask loss: 0.14781 RPN box loss: 0.0109 RPN score loss: 0.00738 RPN total loss: 0.01828 Total loss: 0.95707 timestamp: 1655044225.519768 iteration: 46080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09876 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.14814 L1 loss: 0.0000e+00 L2 loss: 0.59309 Learning rate: 0.002 Mask loss: 0.10813 RPN box loss: 0.00787 RPN score loss: 0.00234 RPN total loss: 0.01021 Total loss: 0.85957 timestamp: 1655044228.7743626 iteration: 46085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06726 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.11943 L1 loss: 0.0000e+00 L2 loss: 0.59308 Learning rate: 0.002 Mask loss: 0.12153 RPN box loss: 0.01281 RPN score loss: 0.00466 RPN total loss: 0.01747 Total loss: 0.85151 timestamp: 1655044232.0359669 iteration: 46090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07288 FastRCNN class loss: 0.04904 FastRCNN total loss: 0.12192 L1 loss: 0.0000e+00 L2 loss: 0.59307 Learning rate: 0.002 Mask loss: 0.1386 RPN box loss: 0.00927 RPN score loss: 0.00277 RPN total loss: 0.01204 Total loss: 0.86563 timestamp: 1655044235.3470945 iteration: 46095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13715 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.22473 L1 loss: 0.0000e+00 L2 loss: 0.59306 Learning rate: 0.002 Mask loss: 0.20637 RPN box loss: 0.0106 RPN score loss: 0.00208 RPN total loss: 0.01268 Total loss: 1.03684 timestamp: 1655044238.6154819 iteration: 46100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0879 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.16231 L1 loss: 0.0000e+00 L2 loss: 0.59305 Learning rate: 0.002 Mask loss: 0.14817 RPN box loss: 0.01669 RPN score loss: 0.00729 RPN total loss: 0.02398 Total loss: 0.9275 timestamp: 1655044241.8492978 iteration: 46105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12567 FastRCNN class loss: 0.05817 FastRCNN total loss: 0.18384 L1 loss: 0.0000e+00 L2 loss: 0.59304 Learning rate: 0.002 Mask loss: 0.17826 RPN box loss: 0.01455 RPN score loss: 0.00228 RPN total loss: 0.01684 Total loss: 0.97198 timestamp: 1655044245.2103727 iteration: 46110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.148 L1 loss: 0.0000e+00 L2 loss: 0.59303 Learning rate: 0.002 Mask loss: 0.08214 RPN box loss: 0.00956 RPN score loss: 0.00309 RPN total loss: 0.01265 Total loss: 0.83582 timestamp: 1655044248.5332265 iteration: 46115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06661 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.12606 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.002 Mask loss: 0.14534 RPN box loss: 0.0214 RPN score loss: 0.00208 RPN total loss: 0.02348 Total loss: 0.8879 timestamp: 1655044251.841086 iteration: 46120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11336 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.1968 L1 loss: 0.0000e+00 L2 loss: 0.59302 Learning rate: 0.002 Mask loss: 0.13353 RPN box loss: 0.02647 RPN score loss: 0.0098 RPN total loss: 0.03627 Total loss: 0.95963 timestamp: 1655044255.1058657 iteration: 46125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.08541 FastRCNN total loss: 0.19051 L1 loss: 0.0000e+00 L2 loss: 0.59301 Learning rate: 0.002 Mask loss: 0.12382 RPN box loss: 0.01689 RPN score loss: 0.0037 RPN total loss: 0.02059 Total loss: 0.92792 timestamp: 1655044258.3057594 iteration: 46130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15944 FastRCNN class loss: 0.10399 FastRCNN total loss: 0.26343 L1 loss: 0.0000e+00 L2 loss: 0.593 Learning rate: 0.002 Mask loss: 0.15066 RPN box loss: 0.04812 RPN score loss: 0.00813 RPN total loss: 0.05625 Total loss: 1.06334 timestamp: 1655044261.5889914 iteration: 46135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07439 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.14074 L1 loss: 0.0000e+00 L2 loss: 0.59299 Learning rate: 0.002 Mask loss: 0.13466 RPN box loss: 0.01549 RPN score loss: 0.003 RPN total loss: 0.0185 Total loss: 0.88689 timestamp: 1655044264.8342295 iteration: 46140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12131 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.18114 L1 loss: 0.0000e+00 L2 loss: 0.59298 Learning rate: 0.002 Mask loss: 0.09463 RPN box loss: 0.01106 RPN score loss: 0.00564 RPN total loss: 0.0167 Total loss: 0.88546 timestamp: 1655044268.1601875 iteration: 46145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13658 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.22033 L1 loss: 0.0000e+00 L2 loss: 0.59297 Learning rate: 0.002 Mask loss: 0.13416 RPN box loss: 0.01108 RPN score loss: 0.00277 RPN total loss: 0.01386 Total loss: 0.96132 timestamp: 1655044271.3487816 iteration: 46150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04906 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.12042 L1 loss: 0.0000e+00 L2 loss: 0.59296 Learning rate: 0.002 Mask loss: 0.12803 RPN box loss: 0.01292 RPN score loss: 0.00501 RPN total loss: 0.01794 Total loss: 0.85934 timestamp: 1655044274.6648514 iteration: 46155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06666 FastRCNN class loss: 0.07557 FastRCNN total loss: 0.14223 L1 loss: 0.0000e+00 L2 loss: 0.59295 Learning rate: 0.002 Mask loss: 0.13111 RPN box loss: 0.01506 RPN score loss: 0.00469 RPN total loss: 0.01976 Total loss: 0.88604 timestamp: 1655044277.8791645 iteration: 46160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14756 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.20854 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.002 Mask loss: 0.10649 RPN box loss: 0.00544 RPN score loss: 0.0012 RPN total loss: 0.00664 Total loss: 0.91462 timestamp: 1655044281.1163833 iteration: 46165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09187 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.15444 L1 loss: 0.0000e+00 L2 loss: 0.59294 Learning rate: 0.002 Mask loss: 0.16568 RPN box loss: 0.03252 RPN score loss: 0.00803 RPN total loss: 0.04056 Total loss: 0.95361 timestamp: 1655044284.3829422 iteration: 46170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14006 FastRCNN class loss: 0.12237 FastRCNN total loss: 0.26243 L1 loss: 0.0000e+00 L2 loss: 0.59293 Learning rate: 0.002 Mask loss: 0.14275 RPN box loss: 0.02909 RPN score loss: 0.01187 RPN total loss: 0.04096 Total loss: 1.03906 timestamp: 1655044287.644644 iteration: 46175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15159 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.24548 L1 loss: 0.0000e+00 L2 loss: 0.59292 Learning rate: 0.002 Mask loss: 0.22916 RPN box loss: 0.01946 RPN score loss: 0.00551 RPN total loss: 0.02497 Total loss: 1.09253 timestamp: 1655044290.9263754 iteration: 46180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08366 FastRCNN class loss: 0.05746 FastRCNN total loss: 0.14111 L1 loss: 0.0000e+00 L2 loss: 0.59291 Learning rate: 0.002 Mask loss: 0.10377 RPN box loss: 0.00664 RPN score loss: 0.00757 RPN total loss: 0.01421 Total loss: 0.85199 timestamp: 1655044294.1888506 iteration: 46185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16527 FastRCNN class loss: 0.15111 FastRCNN total loss: 0.31639 L1 loss: 0.0000e+00 L2 loss: 0.5929 Learning rate: 0.002 Mask loss: 0.23674 RPN box loss: 0.03343 RPN score loss: 0.00573 RPN total loss: 0.03916 Total loss: 1.18519 timestamp: 1655044297.443702 iteration: 46190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 0.59289 Learning rate: 0.002 Mask loss: 0.18832 RPN box loss: 0.01787 RPN score loss: 0.00257 RPN total loss: 0.02044 Total loss: 0.9353 timestamp: 1655044300.6759014 iteration: 46195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12436 FastRCNN class loss: 0.05432 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.59288 Learning rate: 0.002 Mask loss: 0.12205 RPN box loss: 0.01552 RPN score loss: 0.00328 RPN total loss: 0.0188 Total loss: 0.91241 timestamp: 1655044303.9833689 iteration: 46200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04683 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.10011 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.002 Mask loss: 0.09833 RPN box loss: 0.00841 RPN score loss: 0.00221 RPN total loss: 0.01062 Total loss: 0.80193 timestamp: 1655044307.169208 iteration: 46205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08215 FastRCNN class loss: 0.06502 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 0.59287 Learning rate: 0.002 Mask loss: 0.12436 RPN box loss: 0.01276 RPN score loss: 0.00667 RPN total loss: 0.01943 Total loss: 0.88382 timestamp: 1655044310.4943173 iteration: 46210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.15646 L1 loss: 0.0000e+00 L2 loss: 0.59286 Learning rate: 0.002 Mask loss: 0.15456 RPN box loss: 0.0256 RPN score loss: 0.00649 RPN total loss: 0.03209 Total loss: 0.93596 timestamp: 1655044313.6821647 iteration: 46215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12358 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.19179 L1 loss: 0.0000e+00 L2 loss: 0.59285 Learning rate: 0.002 Mask loss: 0.13595 RPN box loss: 0.04385 RPN score loss: 0.00517 RPN total loss: 0.04902 Total loss: 0.96961 timestamp: 1655044316.976442 iteration: 46220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09525 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.16051 L1 loss: 0.0000e+00 L2 loss: 0.59284 Learning rate: 0.002 Mask loss: 0.15403 RPN box loss: 0.02895 RPN score loss: 0.00675 RPN total loss: 0.03569 Total loss: 0.94308 timestamp: 1655044320.2745733 iteration: 46225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11295 FastRCNN class loss: 0.05582 FastRCNN total loss: 0.16876 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.002 Mask loss: 0.12452 RPN box loss: 0.02188 RPN score loss: 0.00833 RPN total loss: 0.03021 Total loss: 0.91633 timestamp: 1655044323.6180348 iteration: 46230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13234 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.21123 L1 loss: 0.0000e+00 L2 loss: 0.59283 Learning rate: 0.002 Mask loss: 0.14996 RPN box loss: 0.04312 RPN score loss: 0.00879 RPN total loss: 0.05191 Total loss: 1.00593 timestamp: 1655044326.843648 iteration: 46235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10679 FastRCNN class loss: 0.10428 FastRCNN total loss: 0.21107 L1 loss: 0.0000e+00 L2 loss: 0.59282 Learning rate: 0.002 Mask loss: 0.15377 RPN box loss: 0.01863 RPN score loss: 0.00717 RPN total loss: 0.0258 Total loss: 0.98347 timestamp: 1655044330.1649368 iteration: 46240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1554 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.24297 L1 loss: 0.0000e+00 L2 loss: 0.59281 Learning rate: 0.002 Mask loss: 0.15378 RPN box loss: 0.01888 RPN score loss: 0.01299 RPN total loss: 0.03187 Total loss: 1.02144 timestamp: 1655044333.4487858 iteration: 46245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14949 FastRCNN class loss: 0.03632 FastRCNN total loss: 0.18581 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.002 Mask loss: 0.10396 RPN box loss: 0.00432 RPN score loss: 0.00181 RPN total loss: 0.00613 Total loss: 0.88871 timestamp: 1655044336.6794739 iteration: 46250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08884 FastRCNN class loss: 0.04068 FastRCNN total loss: 0.12952 L1 loss: 0.0000e+00 L2 loss: 0.5928 Learning rate: 0.002 Mask loss: 0.13824 RPN box loss: 0.01563 RPN score loss: 0.00089 RPN total loss: 0.01652 Total loss: 0.87708 timestamp: 1655044339.9262118 iteration: 46255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10289 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.15345 L1 loss: 0.0000e+00 L2 loss: 0.59279 Learning rate: 0.002 Mask loss: 0.10427 RPN box loss: 0.00646 RPN score loss: 0.00428 RPN total loss: 0.01074 Total loss: 0.86126 timestamp: 1655044343.2097626 iteration: 46260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.13139 FastRCNN total loss: 0.25086 L1 loss: 0.0000e+00 L2 loss: 0.59278 Learning rate: 0.002 Mask loss: 0.17022 RPN box loss: 0.03023 RPN score loss: 0.00531 RPN total loss: 0.03554 Total loss: 1.0494 timestamp: 1655044346.5459452 iteration: 46265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08732 FastRCNN class loss: 0.07432 FastRCNN total loss: 0.16164 L1 loss: 0.0000e+00 L2 loss: 0.59277 Learning rate: 0.002 Mask loss: 0.14537 RPN box loss: 0.02192 RPN score loss: 0.00749 RPN total loss: 0.02942 Total loss: 0.9292 timestamp: 1655044349.8667297 iteration: 46270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09586 FastRCNN class loss: 0.06683 FastRCNN total loss: 0.16269 L1 loss: 0.0000e+00 L2 loss: 0.59276 Learning rate: 0.002 Mask loss: 0.14131 RPN box loss: 0.01215 RPN score loss: 0.00625 RPN total loss: 0.0184 Total loss: 0.91516 timestamp: 1655044353.1346014 iteration: 46275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11462 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.18317 L1 loss: 0.0000e+00 L2 loss: 0.59275 Learning rate: 0.002 Mask loss: 0.09824 RPN box loss: 0.00759 RPN score loss: 0.00403 RPN total loss: 0.01161 Total loss: 0.88578 timestamp: 1655044356.3899229 iteration: 46280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.0487 FastRCNN total loss: 0.13621 L1 loss: 0.0000e+00 L2 loss: 0.59274 Learning rate: 0.002 Mask loss: 0.12127 RPN box loss: 0.00523 RPN score loss: 0.00529 RPN total loss: 0.01052 Total loss: 0.86074 timestamp: 1655044359.6835682 iteration: 46285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.117 FastRCNN class loss: 0.10394 FastRCNN total loss: 0.22094 L1 loss: 0.0000e+00 L2 loss: 0.59273 Learning rate: 0.002 Mask loss: 0.13968 RPN box loss: 0.01414 RPN score loss: 0.01098 RPN total loss: 0.02512 Total loss: 0.97847 timestamp: 1655044362.9181037 iteration: 46290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07071 FastRCNN class loss: 0.05615 FastRCNN total loss: 0.12686 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.002 Mask loss: 0.20849 RPN box loss: 0.02956 RPN score loss: 0.00856 RPN total loss: 0.03812 Total loss: 0.96619 timestamp: 1655044366.1706362 iteration: 46295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14617 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.2154 L1 loss: 0.0000e+00 L2 loss: 0.59272 Learning rate: 0.002 Mask loss: 0.13975 RPN box loss: 0.03301 RPN score loss: 0.00691 RPN total loss: 0.03992 Total loss: 0.98778 timestamp: 1655044369.3954773 iteration: 46300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10882 FastRCNN class loss: 0.06727 FastRCNN total loss: 0.17609 L1 loss: 0.0000e+00 L2 loss: 0.59271 Learning rate: 0.002 Mask loss: 0.16739 RPN box loss: 0.02651 RPN score loss: 0.00536 RPN total loss: 0.03187 Total loss: 0.96805 timestamp: 1655044372.6372356 iteration: 46305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12538 FastRCNN class loss: 0.13312 FastRCNN total loss: 0.2585 L1 loss: 0.0000e+00 L2 loss: 0.5927 Learning rate: 0.002 Mask loss: 0.17969 RPN box loss: 0.03407 RPN score loss: 0.01055 RPN total loss: 0.04463 Total loss: 1.07552 timestamp: 1655044375.9146614 iteration: 46310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12808 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.21652 L1 loss: 0.0000e+00 L2 loss: 0.59269 Learning rate: 0.002 Mask loss: 0.23634 RPN box loss: 0.01818 RPN score loss: 0.00733 RPN total loss: 0.02551 Total loss: 1.07106 timestamp: 1655044379.1690595 iteration: 46315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.1563 L1 loss: 0.0000e+00 L2 loss: 0.59268 Learning rate: 0.002 Mask loss: 0.13242 RPN box loss: 0.0077 RPN score loss: 0.00739 RPN total loss: 0.01509 Total loss: 0.89649 timestamp: 1655044382.4689503 iteration: 46320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12999 FastRCNN class loss: 0.13556 FastRCNN total loss: 0.26556 L1 loss: 0.0000e+00 L2 loss: 0.59267 Learning rate: 0.002 Mask loss: 0.16117 RPN box loss: 0.02303 RPN score loss: 0.00761 RPN total loss: 0.03064 Total loss: 1.05003 timestamp: 1655044385.7586138 iteration: 46325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11994 FastRCNN class loss: 0.05122 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.59266 Learning rate: 0.002 Mask loss: 0.14776 RPN box loss: 0.01024 RPN score loss: 0.00553 RPN total loss: 0.01577 Total loss: 0.92735 timestamp: 1655044388.9971175 iteration: 46330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12041 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.2005 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.002 Mask loss: 0.16684 RPN box loss: 0.02824 RPN score loss: 0.00311 RPN total loss: 0.03135 Total loss: 0.99135 timestamp: 1655044392.2952807 iteration: 46335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12041 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.20306 L1 loss: 0.0000e+00 L2 loss: 0.59265 Learning rate: 0.002 Mask loss: 0.16458 RPN box loss: 0.02373 RPN score loss: 0.00675 RPN total loss: 0.03049 Total loss: 0.99078 timestamp: 1655044395.6155512 iteration: 46340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07294 FastRCNN class loss: 0.04102 FastRCNN total loss: 0.11397 L1 loss: 0.0000e+00 L2 loss: 0.59264 Learning rate: 0.002 Mask loss: 0.11537 RPN box loss: 0.00834 RPN score loss: 0.00239 RPN total loss: 0.01073 Total loss: 0.8327 timestamp: 1655044398.8489966 iteration: 46345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09762 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.1759 L1 loss: 0.0000e+00 L2 loss: 0.59263 Learning rate: 0.002 Mask loss: 0.16195 RPN box loss: 0.0157 RPN score loss: 0.00199 RPN total loss: 0.01769 Total loss: 0.94816 timestamp: 1655044402.0783663 iteration: 46350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.09267 FastRCNN total loss: 0.19177 L1 loss: 0.0000e+00 L2 loss: 0.59262 Learning rate: 0.002 Mask loss: 0.1341 RPN box loss: 0.03604 RPN score loss: 0.00438 RPN total loss: 0.04042 Total loss: 0.9589 timestamp: 1655044405.3071635 iteration: 46355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15691 FastRCNN class loss: 0.13322 FastRCNN total loss: 0.29013 L1 loss: 0.0000e+00 L2 loss: 0.59261 Learning rate: 0.002 Mask loss: 0.1562 RPN box loss: 0.03138 RPN score loss: 0.01658 RPN total loss: 0.04796 Total loss: 1.0869 timestamp: 1655044408.5624776 iteration: 46360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13435 FastRCNN class loss: 0.0638 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 0.59259 Learning rate: 0.002 Mask loss: 0.12599 RPN box loss: 0.01776 RPN score loss: 0.00826 RPN total loss: 0.02603 Total loss: 0.94276 timestamp: 1655044411.9014118 iteration: 46365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13357 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.19642 L1 loss: 0.0000e+00 L2 loss: 0.59258 Learning rate: 0.002 Mask loss: 0.1583 RPN box loss: 0.02268 RPN score loss: 0.00649 RPN total loss: 0.02916 Total loss: 0.97648 timestamp: 1655044415.2257414 iteration: 46370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09366 FastRCNN class loss: 0.06749 FastRCNN total loss: 0.16115 L1 loss: 0.0000e+00 L2 loss: 0.59257 Learning rate: 0.002 Mask loss: 0.14283 RPN box loss: 0.00801 RPN score loss: 0.00121 RPN total loss: 0.00923 Total loss: 0.90578 timestamp: 1655044418.5004516 iteration: 46375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12638 FastRCNN class loss: 0.055 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.002 Mask loss: 0.12148 RPN box loss: 0.00632 RPN score loss: 0.0026 RPN total loss: 0.00892 Total loss: 0.90435 timestamp: 1655044421.7535057 iteration: 46380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10663 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.17443 L1 loss: 0.0000e+00 L2 loss: 0.59256 Learning rate: 0.002 Mask loss: 0.12127 RPN box loss: 0.01685 RPN score loss: 0.00704 RPN total loss: 0.02388 Total loss: 0.91214 timestamp: 1655044425.0247793 iteration: 46385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07208 FastRCNN class loss: 0.05586 FastRCNN total loss: 0.12795 L1 loss: 0.0000e+00 L2 loss: 0.59255 Learning rate: 0.002 Mask loss: 0.17963 RPN box loss: 0.00781 RPN score loss: 0.00594 RPN total loss: 0.01375 Total loss: 0.91387 timestamp: 1655044428.270299 iteration: 46390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07635 FastRCNN class loss: 0.04385 FastRCNN total loss: 0.1202 L1 loss: 0.0000e+00 L2 loss: 0.59254 Learning rate: 0.002 Mask loss: 0.15974 RPN box loss: 0.01142 RPN score loss: 0.00592 RPN total loss: 0.01734 Total loss: 0.88982 timestamp: 1655044431.5400152 iteration: 46395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06809 FastRCNN class loss: 0.09819 FastRCNN total loss: 0.16628 L1 loss: 0.0000e+00 L2 loss: 0.59253 Learning rate: 0.002 Mask loss: 0.14966 RPN box loss: 0.01106 RPN score loss: 0.00878 RPN total loss: 0.01984 Total loss: 0.9283 timestamp: 1655044434.8350186 iteration: 46400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0883 FastRCNN class loss: 0.06017 FastRCNN total loss: 0.14847 L1 loss: 0.0000e+00 L2 loss: 0.59252 Learning rate: 0.002 Mask loss: 0.16564 RPN box loss: 0.05149 RPN score loss: 0.00393 RPN total loss: 0.05542 Total loss: 0.96205 timestamp: 1655044438.1059554 iteration: 46405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.082 FastRCNN total loss: 0.18376 L1 loss: 0.0000e+00 L2 loss: 0.59251 Learning rate: 0.002 Mask loss: 0.16372 RPN box loss: 0.0275 RPN score loss: 0.01596 RPN total loss: 0.04345 Total loss: 0.98344 timestamp: 1655044441.3671336 iteration: 46410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07454 FastRCNN class loss: 0.08521 FastRCNN total loss: 0.15975 L1 loss: 0.0000e+00 L2 loss: 0.5925 Learning rate: 0.002 Mask loss: 0.1329 RPN box loss: 0.0146 RPN score loss: 0.00363 RPN total loss: 0.01823 Total loss: 0.90338 timestamp: 1655044444.6994839 iteration: 46415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08099 FastRCNN class loss: 0.08756 FastRCNN total loss: 0.16855 L1 loss: 0.0000e+00 L2 loss: 0.59249 Learning rate: 0.002 Mask loss: 0.18754 RPN box loss: 0.03315 RPN score loss: 0.01058 RPN total loss: 0.04372 Total loss: 0.9923 timestamp: 1655044447.9816089 iteration: 46420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.084 FastRCNN class loss: 0.06335 FastRCNN total loss: 0.14735 L1 loss: 0.0000e+00 L2 loss: 0.59248 Learning rate: 0.002 Mask loss: 0.11907 RPN box loss: 0.02905 RPN score loss: 0.00189 RPN total loss: 0.03094 Total loss: 0.88984 timestamp: 1655044451.2195053 iteration: 46425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1349 FastRCNN class loss: 0.09247 FastRCNN total loss: 0.22737 L1 loss: 0.0000e+00 L2 loss: 0.59247 Learning rate: 0.002 Mask loss: 0.19527 RPN box loss: 0.01543 RPN score loss: 0.00411 RPN total loss: 0.01954 Total loss: 1.03465 timestamp: 1655044454.4699156 iteration: 46430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11269 FastRCNN class loss: 0.08703 FastRCNN total loss: 0.19973 L1 loss: 0.0000e+00 L2 loss: 0.59246 Learning rate: 0.002 Mask loss: 0.13131 RPN box loss: 0.01257 RPN score loss: 0.00467 RPN total loss: 0.01724 Total loss: 0.94074 timestamp: 1655044457.7953186 iteration: 46435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09773 FastRCNN class loss: 0.07838 FastRCNN total loss: 0.1761 L1 loss: 0.0000e+00 L2 loss: 0.59245 Learning rate: 0.002 Mask loss: 0.18246 RPN box loss: 0.00906 RPN score loss: 0.00534 RPN total loss: 0.0144 Total loss: 0.96541 timestamp: 1655044461.1423364 iteration: 46440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09126 FastRCNN class loss: 0.07372 FastRCNN total loss: 0.16498 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.002 Mask loss: 0.14648 RPN box loss: 0.01625 RPN score loss: 0.00529 RPN total loss: 0.02154 Total loss: 0.92545 timestamp: 1655044464.4716644 iteration: 46445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16416 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.24589 L1 loss: 0.0000e+00 L2 loss: 0.59244 Learning rate: 0.002 Mask loss: 0.17308 RPN box loss: 0.01114 RPN score loss: 0.00268 RPN total loss: 0.01382 Total loss: 1.02522 timestamp: 1655044467.7188828 iteration: 46450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14914 FastRCNN class loss: 0.10675 FastRCNN total loss: 0.2559 L1 loss: 0.0000e+00 L2 loss: 0.59243 Learning rate: 0.002 Mask loss: 0.20513 RPN box loss: 0.02093 RPN score loss: 0.00691 RPN total loss: 0.02784 Total loss: 1.0813 timestamp: 1655044470.9665256 iteration: 46455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.16747 L1 loss: 0.0000e+00 L2 loss: 0.59242 Learning rate: 0.002 Mask loss: 0.15776 RPN box loss: 0.01531 RPN score loss: 0.00466 RPN total loss: 0.01997 Total loss: 0.93762 timestamp: 1655044474.224067 iteration: 46460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14588 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.21204 L1 loss: 0.0000e+00 L2 loss: 0.59241 Learning rate: 0.002 Mask loss: 0.14136 RPN box loss: 0.01932 RPN score loss: 0.00372 RPN total loss: 0.02304 Total loss: 0.96885 timestamp: 1655044477.5103602 iteration: 46465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16742 FastRCNN class loss: 0.08124 FastRCNN total loss: 0.24866 L1 loss: 0.0000e+00 L2 loss: 0.5924 Learning rate: 0.002 Mask loss: 0.16153 RPN box loss: 0.0213 RPN score loss: 0.00623 RPN total loss: 0.02752 Total loss: 1.03012 timestamp: 1655044480.856438 iteration: 46470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09263 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.17059 L1 loss: 0.0000e+00 L2 loss: 0.59239 Learning rate: 0.002 Mask loss: 0.192 RPN box loss: 0.0081 RPN score loss: 0.00334 RPN total loss: 0.01144 Total loss: 0.96642 timestamp: 1655044484.146479 iteration: 46475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.12455 L1 loss: 0.0000e+00 L2 loss: 0.59238 Learning rate: 0.002 Mask loss: 0.11575 RPN box loss: 0.05644 RPN score loss: 0.00819 RPN total loss: 0.06464 Total loss: 0.89732 timestamp: 1655044487.4701474 iteration: 46480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12641 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.19559 L1 loss: 0.0000e+00 L2 loss: 0.59237 Learning rate: 0.002 Mask loss: 0.11208 RPN box loss: 0.00673 RPN score loss: 0.0043 RPN total loss: 0.01103 Total loss: 0.91106 timestamp: 1655044490.7503603 iteration: 46485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10625 FastRCNN class loss: 0.06772 FastRCNN total loss: 0.17397 L1 loss: 0.0000e+00 L2 loss: 0.59236 Learning rate: 0.002 Mask loss: 0.13888 RPN box loss: 0.02346 RPN score loss: 0.00189 RPN total loss: 0.02534 Total loss: 0.93056 timestamp: 1655044494.0459983 iteration: 46490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.08527 FastRCNN total loss: 0.20924 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.002 Mask loss: 0.17053 RPN box loss: 0.02682 RPN score loss: 0.01501 RPN total loss: 0.04183 Total loss: 1.01395 timestamp: 1655044497.3180826 iteration: 46495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17707 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.25785 L1 loss: 0.0000e+00 L2 loss: 0.59235 Learning rate: 0.002 Mask loss: 0.14525 RPN box loss: 0.01911 RPN score loss: 0.00456 RPN total loss: 0.02367 Total loss: 1.01912 timestamp: 1655044500.6329463 iteration: 46500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0853 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.59234 Learning rate: 0.002 Mask loss: 0.13652 RPN box loss: 0.02116 RPN score loss: 0.00413 RPN total loss: 0.02529 Total loss: 0.8896 timestamp: 1655044503.8681092 iteration: 46505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0734 FastRCNN class loss: 0.057 FastRCNN total loss: 0.1304 L1 loss: 0.0000e+00 L2 loss: 0.59233 Learning rate: 0.002 Mask loss: 0.17143 RPN box loss: 0.03165 RPN score loss: 0.00806 RPN total loss: 0.03971 Total loss: 0.93386 timestamp: 1655044507.22057 iteration: 46510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14196 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.22619 L1 loss: 0.0000e+00 L2 loss: 0.59231 Learning rate: 0.002 Mask loss: 0.12406 RPN box loss: 0.01202 RPN score loss: 0.00653 RPN total loss: 0.01855 Total loss: 0.9611 timestamp: 1655044510.43949 iteration: 46515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11508 FastRCNN class loss: 0.0636 FastRCNN total loss: 0.17868 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.002 Mask loss: 0.16273 RPN box loss: 0.00602 RPN score loss: 0.00403 RPN total loss: 0.01005 Total loss: 0.94376 timestamp: 1655044513.6986842 iteration: 46520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11998 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.17993 L1 loss: 0.0000e+00 L2 loss: 0.5923 Learning rate: 0.002 Mask loss: 0.13154 RPN box loss: 0.00762 RPN score loss: 0.00402 RPN total loss: 0.01164 Total loss: 0.91541 timestamp: 1655044516.9555051 iteration: 46525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12306 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.19322 L1 loss: 0.0000e+00 L2 loss: 0.59229 Learning rate: 0.002 Mask loss: 0.18853 RPN box loss: 0.01644 RPN score loss: 0.00334 RPN total loss: 0.01978 Total loss: 0.99381 timestamp: 1655044520.236193 iteration: 46530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11988 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.19387 L1 loss: 0.0000e+00 L2 loss: 0.59228 Learning rate: 0.002 Mask loss: 0.11997 RPN box loss: 0.01319 RPN score loss: 0.00473 RPN total loss: 0.01792 Total loss: 0.92404 timestamp: 1655044523.4989207 iteration: 46535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13666 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.22997 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.002 Mask loss: 0.20817 RPN box loss: 0.02828 RPN score loss: 0.00529 RPN total loss: 0.03357 Total loss: 1.06398 timestamp: 1655044526.7698867 iteration: 46540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10763 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.18304 L1 loss: 0.0000e+00 L2 loss: 0.59227 Learning rate: 0.002 Mask loss: 0.1887 RPN box loss: 0.01428 RPN score loss: 0.01087 RPN total loss: 0.02516 Total loss: 0.98917 timestamp: 1655044530.0237486 iteration: 46545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1484 FastRCNN class loss: 0.11955 FastRCNN total loss: 0.26794 L1 loss: 0.0000e+00 L2 loss: 0.59226 Learning rate: 0.002 Mask loss: 0.20912 RPN box loss: 0.04393 RPN score loss: 0.0363 RPN total loss: 0.08023 Total loss: 1.14955 timestamp: 1655044533.2891977 iteration: 46550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12195 FastRCNN class loss: 0.0458 FastRCNN total loss: 0.16775 L1 loss: 0.0000e+00 L2 loss: 0.59225 Learning rate: 0.002 Mask loss: 0.12862 RPN box loss: 0.02719 RPN score loss: 0.00603 RPN total loss: 0.03321 Total loss: 0.92183 timestamp: 1655044536.5946083 iteration: 46555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05305 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.11039 L1 loss: 0.0000e+00 L2 loss: 0.59224 Learning rate: 0.002 Mask loss: 0.13016 RPN box loss: 0.00688 RPN score loss: 0.0029 RPN total loss: 0.00978 Total loss: 0.84256 timestamp: 1655044539.879708 iteration: 46560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07144 FastRCNN class loss: 0.04578 FastRCNN total loss: 0.11722 L1 loss: 0.0000e+00 L2 loss: 0.59222 Learning rate: 0.002 Mask loss: 0.13161 RPN box loss: 0.02065 RPN score loss: 0.00466 RPN total loss: 0.02531 Total loss: 0.86636 timestamp: 1655044543.1452382 iteration: 46565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06259 FastRCNN class loss: 0.04905 FastRCNN total loss: 0.11164 L1 loss: 0.0000e+00 L2 loss: 0.59221 Learning rate: 0.002 Mask loss: 0.13157 RPN box loss: 0.03283 RPN score loss: 0.00296 RPN total loss: 0.03579 Total loss: 0.87121 timestamp: 1655044546.3600776 iteration: 46570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05992 FastRCNN class loss: 0.06404 FastRCNN total loss: 0.12397 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.002 Mask loss: 0.12925 RPN box loss: 0.01232 RPN score loss: 0.00536 RPN total loss: 0.01768 Total loss: 0.86311 timestamp: 1655044549.6407716 iteration: 46575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04988 FastRCNN class loss: 0.04726 FastRCNN total loss: 0.09714 L1 loss: 0.0000e+00 L2 loss: 0.5922 Learning rate: 0.002 Mask loss: 0.12344 RPN box loss: 0.01959 RPN score loss: 0.00152 RPN total loss: 0.0211 Total loss: 0.83388 timestamp: 1655044552.9634206 iteration: 46580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04153 FastRCNN class loss: 0.03835 FastRCNN total loss: 0.07988 L1 loss: 0.0000e+00 L2 loss: 0.59219 Learning rate: 0.002 Mask loss: 0.11468 RPN box loss: 0.00437 RPN score loss: 0.00349 RPN total loss: 0.00786 Total loss: 0.79461 timestamp: 1655044556.2226427 iteration: 46585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.19899 L1 loss: 0.0000e+00 L2 loss: 0.59218 Learning rate: 0.002 Mask loss: 0.14292 RPN box loss: 0.02121 RPN score loss: 0.01082 RPN total loss: 0.03202 Total loss: 0.96612 timestamp: 1655044559.505072 iteration: 46590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11023 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.16961 L1 loss: 0.0000e+00 L2 loss: 0.59217 Learning rate: 0.002 Mask loss: 0.172 RPN box loss: 0.0365 RPN score loss: 0.00383 RPN total loss: 0.04033 Total loss: 0.9741 timestamp: 1655044562.753648 iteration: 46595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13614 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.21063 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.002 Mask loss: 0.14561 RPN box loss: 0.01538 RPN score loss: 0.00664 RPN total loss: 0.02202 Total loss: 0.97042 timestamp: 1655044566.0487387 iteration: 46600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13629 FastRCNN class loss: 0.10057 FastRCNN total loss: 0.23686 L1 loss: 0.0000e+00 L2 loss: 0.59216 Learning rate: 0.002 Mask loss: 0.14647 RPN box loss: 0.03662 RPN score loss: 0.01357 RPN total loss: 0.0502 Total loss: 1.02567 timestamp: 1655044569.3200858 iteration: 46605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.052 FastRCNN class loss: 0.048 FastRCNN total loss: 0.1 L1 loss: 0.0000e+00 L2 loss: 0.59215 Learning rate: 0.002 Mask loss: 0.11932 RPN box loss: 0.01327 RPN score loss: 0.00253 RPN total loss: 0.0158 Total loss: 0.82726 timestamp: 1655044572.5435286 iteration: 46610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16589 FastRCNN class loss: 0.08063 FastRCNN total loss: 0.24651 L1 loss: 0.0000e+00 L2 loss: 0.59214 Learning rate: 0.002 Mask loss: 0.12286 RPN box loss: 0.01988 RPN score loss: 0.01225 RPN total loss: 0.03214 Total loss: 0.99365 timestamp: 1655044575.8350844 iteration: 46615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1014 FastRCNN class loss: 0.10452 FastRCNN total loss: 0.20593 L1 loss: 0.0000e+00 L2 loss: 0.59213 Learning rate: 0.002 Mask loss: 0.16862 RPN box loss: 0.02016 RPN score loss: 0.01027 RPN total loss: 0.03043 Total loss: 0.9971 timestamp: 1655044579.0771825 iteration: 46620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15965 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.22244 L1 loss: 0.0000e+00 L2 loss: 0.59212 Learning rate: 0.002 Mask loss: 0.11416 RPN box loss: 0.06317 RPN score loss: 0.00322 RPN total loss: 0.06639 Total loss: 0.99511 timestamp: 1655044582.3841176 iteration: 46625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09945 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.16335 L1 loss: 0.0000e+00 L2 loss: 0.59211 Learning rate: 0.002 Mask loss: 0.17304 RPN box loss: 0.03613 RPN score loss: 0.0088 RPN total loss: 0.04492 Total loss: 0.97342 timestamp: 1655044585.6681654 iteration: 46630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07897 FastRCNN class loss: 0.04082 FastRCNN total loss: 0.11979 L1 loss: 0.0000e+00 L2 loss: 0.5921 Learning rate: 0.002 Mask loss: 0.25619 RPN box loss: 0.00958 RPN score loss: 0.00406 RPN total loss: 0.01364 Total loss: 0.98172 timestamp: 1655044588.966975 iteration: 46635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08638 FastRCNN class loss: 0.05166 FastRCNN total loss: 0.13805 L1 loss: 0.0000e+00 L2 loss: 0.59209 Learning rate: 0.002 Mask loss: 0.09847 RPN box loss: 0.0168 RPN score loss: 0.00769 RPN total loss: 0.02449 Total loss: 0.8531 timestamp: 1655044592.224125 iteration: 46640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11319 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.20362 L1 loss: 0.0000e+00 L2 loss: 0.59208 Learning rate: 0.002 Mask loss: 0.15924 RPN box loss: 0.034 RPN score loss: 0.01718 RPN total loss: 0.05118 Total loss: 1.00612 timestamp: 1655044595.491916 iteration: 46645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15356 FastRCNN class loss: 0.12722 FastRCNN total loss: 0.28078 L1 loss: 0.0000e+00 L2 loss: 0.59207 Learning rate: 0.002 Mask loss: 0.16801 RPN box loss: 0.02603 RPN score loss: 0.00792 RPN total loss: 0.03395 Total loss: 1.07481 timestamp: 1655044598.7012227 iteration: 46650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1844 FastRCNN class loss: 0.08514 FastRCNN total loss: 0.26955 L1 loss: 0.0000e+00 L2 loss: 0.59206 Learning rate: 0.002 Mask loss: 0.13205 RPN box loss: 0.03541 RPN score loss: 0.01511 RPN total loss: 0.05053 Total loss: 1.04419 timestamp: 1655044602.0314534 iteration: 46655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10279 FastRCNN class loss: 0.07757 FastRCNN total loss: 0.18035 L1 loss: 0.0000e+00 L2 loss: 0.59205 Learning rate: 0.002 Mask loss: 0.11997 RPN box loss: 0.01345 RPN score loss: 0.00668 RPN total loss: 0.02013 Total loss: 0.91251 timestamp: 1655044605.372541 iteration: 46660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07331 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.1218 L1 loss: 0.0000e+00 L2 loss: 0.59204 Learning rate: 0.002 Mask loss: 0.10745 RPN box loss: 0.03446 RPN score loss: 0.00137 RPN total loss: 0.03583 Total loss: 0.85712 timestamp: 1655044608.617488 iteration: 46665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08925 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.15498 L1 loss: 0.0000e+00 L2 loss: 0.59203 Learning rate: 0.002 Mask loss: 0.17053 RPN box loss: 0.00666 RPN score loss: 0.00486 RPN total loss: 0.01152 Total loss: 0.92907 timestamp: 1655044611.882088 iteration: 46670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13065 FastRCNN class loss: 0.08812 FastRCNN total loss: 0.21876 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.002 Mask loss: 0.16435 RPN box loss: 0.00639 RPN score loss: 0.00345 RPN total loss: 0.00983 Total loss: 0.98497 timestamp: 1655044615.1611085 iteration: 46675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1783 FastRCNN class loss: 0.11178 FastRCNN total loss: 0.29008 L1 loss: 0.0000e+00 L2 loss: 0.59202 Learning rate: 0.002 Mask loss: 0.17259 RPN box loss: 0.00839 RPN score loss: 0.00228 RPN total loss: 0.01067 Total loss: 1.06536 timestamp: 1655044618.3868184 iteration: 46680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12881 FastRCNN class loss: 0.04864 FastRCNN total loss: 0.17746 L1 loss: 0.0000e+00 L2 loss: 0.59201 Learning rate: 0.002 Mask loss: 0.14306 RPN box loss: 0.01836 RPN score loss: 0.00891 RPN total loss: 0.02727 Total loss: 0.9398 timestamp: 1655044621.6667454 iteration: 46685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13335 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.23247 L1 loss: 0.0000e+00 L2 loss: 0.592 Learning rate: 0.002 Mask loss: 0.19083 RPN box loss: 0.01966 RPN score loss: 0.00416 RPN total loss: 0.02381 Total loss: 1.03912 timestamp: 1655044624.9120905 iteration: 46690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18614 FastRCNN class loss: 0.08677 FastRCNN total loss: 0.27291 L1 loss: 0.0000e+00 L2 loss: 0.59199 Learning rate: 0.002 Mask loss: 0.12107 RPN box loss: 0.01711 RPN score loss: 0.00774 RPN total loss: 0.02485 Total loss: 1.01082 timestamp: 1655044628.2567825 iteration: 46695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13003 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.2178 L1 loss: 0.0000e+00 L2 loss: 0.59198 Learning rate: 0.002 Mask loss: 0.22874 RPN box loss: 0.01846 RPN score loss: 0.00732 RPN total loss: 0.02578 Total loss: 1.0643 timestamp: 1655044631.603364 iteration: 46700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07876 FastRCNN class loss: 0.0701 FastRCNN total loss: 0.14887 L1 loss: 0.0000e+00 L2 loss: 0.59197 Learning rate: 0.002 Mask loss: 0.16593 RPN box loss: 0.01669 RPN score loss: 0.00258 RPN total loss: 0.01928 Total loss: 0.92605 timestamp: 1655044634.9662614 iteration: 46705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10884 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.18923 L1 loss: 0.0000e+00 L2 loss: 0.59196 Learning rate: 0.002 Mask loss: 0.10514 RPN box loss: 0.01438 RPN score loss: 0.00413 RPN total loss: 0.01851 Total loss: 0.90483 timestamp: 1655044638.1873434 iteration: 46710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06004 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.11423 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.002 Mask loss: 0.16272 RPN box loss: 0.09264 RPN score loss: 0.00806 RPN total loss: 0.1007 Total loss: 0.96961 timestamp: 1655044641.5479932 iteration: 46715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08343 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.15456 L1 loss: 0.0000e+00 L2 loss: 0.59195 Learning rate: 0.002 Mask loss: 0.15376 RPN box loss: 0.02536 RPN score loss: 0.00305 RPN total loss: 0.02841 Total loss: 0.92867 timestamp: 1655044644.8135607 iteration: 46720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10358 FastRCNN class loss: 0.08405 FastRCNN total loss: 0.18763 L1 loss: 0.0000e+00 L2 loss: 0.59194 Learning rate: 0.002 Mask loss: 0.13671 RPN box loss: 0.03815 RPN score loss: 0.00327 RPN total loss: 0.04142 Total loss: 0.9577 timestamp: 1655044648.151281 iteration: 46725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10838 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.20319 L1 loss: 0.0000e+00 L2 loss: 0.59193 Learning rate: 0.002 Mask loss: 0.16073 RPN box loss: 0.01307 RPN score loss: 0.00377 RPN total loss: 0.01684 Total loss: 0.97268 timestamp: 1655044651.3624332 iteration: 46730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.11081 FastRCNN total loss: 0.25069 L1 loss: 0.0000e+00 L2 loss: 0.59192 Learning rate: 0.002 Mask loss: 0.21498 RPN box loss: 0.03099 RPN score loss: 0.01025 RPN total loss: 0.04124 Total loss: 1.09882 timestamp: 1655044654.6118462 iteration: 46735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10164 FastRCNN class loss: 0.06599 FastRCNN total loss: 0.16763 L1 loss: 0.0000e+00 L2 loss: 0.59191 Learning rate: 0.002 Mask loss: 0.07718 RPN box loss: 0.02535 RPN score loss: 0.00326 RPN total loss: 0.02861 Total loss: 0.86533 timestamp: 1655044657.8400848 iteration: 46740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11476 FastRCNN class loss: 0.06494 FastRCNN total loss: 0.1797 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.002 Mask loss: 0.23288 RPN box loss: 0.02484 RPN score loss: 0.01022 RPN total loss: 0.03506 Total loss: 1.03954 timestamp: 1655044661.1546001 iteration: 46745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11093 FastRCNN class loss: 0.03791 FastRCNN total loss: 0.14884 L1 loss: 0.0000e+00 L2 loss: 0.5919 Learning rate: 0.002 Mask loss: 0.09645 RPN box loss: 0.02672 RPN score loss: 0.00152 RPN total loss: 0.02824 Total loss: 0.86544 timestamp: 1655044664.4453828 iteration: 46750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16881 FastRCNN class loss: 0.09747 FastRCNN total loss: 0.26629 L1 loss: 0.0000e+00 L2 loss: 0.59188 Learning rate: 0.002 Mask loss: 0.12823 RPN box loss: 0.0103 RPN score loss: 0.00265 RPN total loss: 0.01295 Total loss: 0.99935 timestamp: 1655044667.690978 iteration: 46755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09212 FastRCNN class loss: 0.08483 FastRCNN total loss: 0.17695 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.002 Mask loss: 0.14536 RPN box loss: 0.00853 RPN score loss: 0.00496 RPN total loss: 0.01348 Total loss: 0.92766 timestamp: 1655044670.937889 iteration: 46760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07268 FastRCNN class loss: 0.03884 FastRCNN total loss: 0.11152 L1 loss: 0.0000e+00 L2 loss: 0.59187 Learning rate: 0.002 Mask loss: 0.09993 RPN box loss: 0.03438 RPN score loss: 0.00333 RPN total loss: 0.03771 Total loss: 0.84103 timestamp: 1655044674.2523677 iteration: 46765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.076 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.13862 L1 loss: 0.0000e+00 L2 loss: 0.59186 Learning rate: 0.002 Mask loss: 0.13335 RPN box loss: 0.0228 RPN score loss: 0.00428 RPN total loss: 0.02708 Total loss: 0.89091 timestamp: 1655044677.549726 iteration: 46770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.08418 FastRCNN total loss: 0.18511 L1 loss: 0.0000e+00 L2 loss: 0.59185 Learning rate: 0.002 Mask loss: 0.14879 RPN box loss: 0.03118 RPN score loss: 0.0066 RPN total loss: 0.03779 Total loss: 0.96354 timestamp: 1655044680.7941704 iteration: 46775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06946 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.15921 L1 loss: 0.0000e+00 L2 loss: 0.59184 Learning rate: 0.002 Mask loss: 0.17468 RPN box loss: 0.01608 RPN score loss: 0.00534 RPN total loss: 0.02142 Total loss: 0.94715 timestamp: 1655044684.1154342 iteration: 46780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07619 FastRCNN class loss: 0.04759 FastRCNN total loss: 0.12378 L1 loss: 0.0000e+00 L2 loss: 0.59183 Learning rate: 0.002 Mask loss: 0.22803 RPN box loss: 0.00944 RPN score loss: 0.00207 RPN total loss: 0.01151 Total loss: 0.95514 timestamp: 1655044687.3558316 iteration: 46785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09147 FastRCNN class loss: 0.09152 FastRCNN total loss: 0.18299 L1 loss: 0.0000e+00 L2 loss: 0.59182 Learning rate: 0.002 Mask loss: 0.08918 RPN box loss: 0.01013 RPN score loss: 0.0024 RPN total loss: 0.01253 Total loss: 0.87653 timestamp: 1655044690.6503568 iteration: 46790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07867 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.13156 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.002 Mask loss: 0.12183 RPN box loss: 0.00909 RPN score loss: 0.00717 RPN total loss: 0.01626 Total loss: 0.86146 timestamp: 1655044693.9018776 iteration: 46795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14239 FastRCNN class loss: 0.09676 FastRCNN total loss: 0.23915 L1 loss: 0.0000e+00 L2 loss: 0.59181 Learning rate: 0.002 Mask loss: 0.13266 RPN box loss: 0.01694 RPN score loss: 0.0059 RPN total loss: 0.02284 Total loss: 0.98646 timestamp: 1655044697.208416 iteration: 46800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08099 FastRCNN class loss: 0.04584 FastRCNN total loss: 0.12683 L1 loss: 0.0000e+00 L2 loss: 0.5918 Learning rate: 0.002 Mask loss: 0.17394 RPN box loss: 0.01852 RPN score loss: 0.00228 RPN total loss: 0.02079 Total loss: 0.91336 timestamp: 1655044700.480156 iteration: 46805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.04989 FastRCNN total loss: 0.15624 L1 loss: 0.0000e+00 L2 loss: 0.59179 Learning rate: 0.002 Mask loss: 0.15069 RPN box loss: 0.00766 RPN score loss: 0.00615 RPN total loss: 0.01381 Total loss: 0.91253 timestamp: 1655044703.7314491 iteration: 46810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05396 FastRCNN class loss: 0.04602 FastRCNN total loss: 0.09998 L1 loss: 0.0000e+00 L2 loss: 0.59178 Learning rate: 0.002 Mask loss: 0.17669 RPN box loss: 0.0205 RPN score loss: 0.0031 RPN total loss: 0.0236 Total loss: 0.89205 timestamp: 1655044707.0054038 iteration: 46815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08279 FastRCNN class loss: 0.08945 FastRCNN total loss: 0.17224 L1 loss: 0.0000e+00 L2 loss: 0.59177 Learning rate: 0.002 Mask loss: 0.18197 RPN box loss: 0.0203 RPN score loss: 0.00326 RPN total loss: 0.02356 Total loss: 0.96953 timestamp: 1655044710.277851 iteration: 46820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09865 FastRCNN class loss: 0.05962 FastRCNN total loss: 0.15827 L1 loss: 0.0000e+00 L2 loss: 0.59176 Learning rate: 0.002 Mask loss: 0.10349 RPN box loss: 0.00513 RPN score loss: 0.0026 RPN total loss: 0.00773 Total loss: 0.86125 timestamp: 1655044713.5538847 iteration: 46825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11353 FastRCNN class loss: 0.06077 FastRCNN total loss: 0.17431 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.002 Mask loss: 0.13087 RPN box loss: 0.03467 RPN score loss: 0.00303 RPN total loss: 0.0377 Total loss: 0.93462 timestamp: 1655044716.9235902 iteration: 46830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.17288 L1 loss: 0.0000e+00 L2 loss: 0.59175 Learning rate: 0.002 Mask loss: 0.11087 RPN box loss: 0.01471 RPN score loss: 0.00297 RPN total loss: 0.01768 Total loss: 0.89318 timestamp: 1655044720.1484556 iteration: 46835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11369 FastRCNN class loss: 0.08386 FastRCNN total loss: 0.19755 L1 loss: 0.0000e+00 L2 loss: 0.59174 Learning rate: 0.002 Mask loss: 0.13892 RPN box loss: 0.03464 RPN score loss: 0.01001 RPN total loss: 0.04465 Total loss: 0.97285 timestamp: 1655044723.3328702 iteration: 46840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06561 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.12994 L1 loss: 0.0000e+00 L2 loss: 0.59173 Learning rate: 0.002 Mask loss: 0.16662 RPN box loss: 0.01674 RPN score loss: 0.00351 RPN total loss: 0.02025 Total loss: 0.90853 timestamp: 1655044726.6276069 iteration: 46845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.1072 FastRCNN total loss: 0.24126 L1 loss: 0.0000e+00 L2 loss: 0.59172 Learning rate: 0.002 Mask loss: 0.16032 RPN box loss: 0.00765 RPN score loss: 0.0018 RPN total loss: 0.00945 Total loss: 1.00275 timestamp: 1655044729.8393085 iteration: 46850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11302 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.59171 Learning rate: 0.002 Mask loss: 0.13701 RPN box loss: 0.00646 RPN score loss: 0.00208 RPN total loss: 0.00854 Total loss: 0.8988 timestamp: 1655044733.1335163 iteration: 46855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05375 FastRCNN class loss: 0.0452 FastRCNN total loss: 0.09895 L1 loss: 0.0000e+00 L2 loss: 0.5917 Learning rate: 0.002 Mask loss: 0.29496 RPN box loss: 0.02151 RPN score loss: 0.00261 RPN total loss: 0.02412 Total loss: 1.00973 timestamp: 1655044736.443548 iteration: 46860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09343 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.162 L1 loss: 0.0000e+00 L2 loss: 0.59169 Learning rate: 0.002 Mask loss: 0.12688 RPN box loss: 0.02038 RPN score loss: 0.00586 RPN total loss: 0.02625 Total loss: 0.90682 timestamp: 1655044739.6940022 iteration: 46865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2105 FastRCNN class loss: 0.10252 FastRCNN total loss: 0.31301 L1 loss: 0.0000e+00 L2 loss: 0.59168 Learning rate: 0.002 Mask loss: 0.18683 RPN box loss: 0.01324 RPN score loss: 0.00895 RPN total loss: 0.02219 Total loss: 1.11372 timestamp: 1655044742.93854 iteration: 46870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.04993 FastRCNN total loss: 0.15421 L1 loss: 0.0000e+00 L2 loss: 0.59167 Learning rate: 0.002 Mask loss: 0.15888 RPN box loss: 0.01472 RPN score loss: 0.00282 RPN total loss: 0.01754 Total loss: 0.9223 timestamp: 1655044746.1763606 iteration: 46875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11648 FastRCNN class loss: 0.05598 FastRCNN total loss: 0.17247 L1 loss: 0.0000e+00 L2 loss: 0.59166 Learning rate: 0.002 Mask loss: 0.12525 RPN box loss: 0.01859 RPN score loss: 0.00159 RPN total loss: 0.02018 Total loss: 0.90955 timestamp: 1655044749.4122505 iteration: 46880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11527 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.19024 L1 loss: 0.0000e+00 L2 loss: 0.59165 Learning rate: 0.002 Mask loss: 0.1118 RPN box loss: 0.02293 RPN score loss: 0.00708 RPN total loss: 0.03002 Total loss: 0.9237 timestamp: 1655044752.6487381 iteration: 46885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06122 FastRCNN class loss: 0.04191 FastRCNN total loss: 0.10313 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.002 Mask loss: 0.11448 RPN box loss: 0.01865 RPN score loss: 0.00454 RPN total loss: 0.0232 Total loss: 0.83245 timestamp: 1655044755.874264 iteration: 46890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10096 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.16838 L1 loss: 0.0000e+00 L2 loss: 0.59164 Learning rate: 0.002 Mask loss: 0.11328 RPN box loss: 0.01426 RPN score loss: 0.00987 RPN total loss: 0.02413 Total loss: 0.89742 timestamp: 1655044759.1156347 iteration: 46895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09129 FastRCNN class loss: 0.08123 FastRCNN total loss: 0.17252 L1 loss: 0.0000e+00 L2 loss: 0.59163 Learning rate: 0.002 Mask loss: 0.17904 RPN box loss: 0.07497 RPN score loss: 0.00669 RPN total loss: 0.08165 Total loss: 1.02485 timestamp: 1655044762.4334438 iteration: 46900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14313 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.22195 L1 loss: 0.0000e+00 L2 loss: 0.59162 Learning rate: 0.002 Mask loss: 0.17394 RPN box loss: 0.02725 RPN score loss: 0.01718 RPN total loss: 0.04443 Total loss: 1.03194 timestamp: 1655044765.6601455 iteration: 46905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10393 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.16918 L1 loss: 0.0000e+00 L2 loss: 0.59161 Learning rate: 0.002 Mask loss: 0.10678 RPN box loss: 0.02084 RPN score loss: 0.0019 RPN total loss: 0.02274 Total loss: 0.89031 timestamp: 1655044768.8903823 iteration: 46910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09482 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.17655 L1 loss: 0.0000e+00 L2 loss: 0.5916 Learning rate: 0.002 Mask loss: 0.12386 RPN box loss: 0.00859 RPN score loss: 0.001 RPN total loss: 0.00959 Total loss: 0.90159 timestamp: 1655044772.1468463 iteration: 46915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16069 FastRCNN class loss: 0.10253 FastRCNN total loss: 0.26322 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.002 Mask loss: 0.19079 RPN box loss: 0.02182 RPN score loss: 0.00956 RPN total loss: 0.03138 Total loss: 1.07698 timestamp: 1655044775.3864553 iteration: 46920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09444 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.14148 L1 loss: 0.0000e+00 L2 loss: 0.59159 Learning rate: 0.002 Mask loss: 0.13253 RPN box loss: 0.01802 RPN score loss: 0.00897 RPN total loss: 0.027 Total loss: 0.8926 timestamp: 1655044778.66526 iteration: 46925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11209 FastRCNN class loss: 0.05948 FastRCNN total loss: 0.17158 L1 loss: 0.0000e+00 L2 loss: 0.59158 Learning rate: 0.002 Mask loss: 0.16939 RPN box loss: 0.01407 RPN score loss: 0.00201 RPN total loss: 0.01608 Total loss: 0.94862 timestamp: 1655044781.9162915 iteration: 46930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14464 FastRCNN class loss: 0.10799 FastRCNN total loss: 0.25263 L1 loss: 0.0000e+00 L2 loss: 0.59157 Learning rate: 0.002 Mask loss: 0.20122 RPN box loss: 0.02142 RPN score loss: 0.00636 RPN total loss: 0.02778 Total loss: 1.0732 timestamp: 1655044785.1682682 iteration: 46935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10372 FastRCNN class loss: 0.05373 FastRCNN total loss: 0.15745 L1 loss: 0.0000e+00 L2 loss: 0.59156 Learning rate: 0.002 Mask loss: 0.09816 RPN box loss: 0.01576 RPN score loss: 0.00176 RPN total loss: 0.01752 Total loss: 0.86469 timestamp: 1655044788.506805 iteration: 46940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14978 FastRCNN class loss: 0.09005 FastRCNN total loss: 0.23983 L1 loss: 0.0000e+00 L2 loss: 0.59155 Learning rate: 0.002 Mask loss: 0.16698 RPN box loss: 0.04232 RPN score loss: 0.00671 RPN total loss: 0.04904 Total loss: 1.04739 timestamp: 1655044791.836068 iteration: 46945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.08699 FastRCNN total loss: 0.17711 L1 loss: 0.0000e+00 L2 loss: 0.59154 Learning rate: 0.002 Mask loss: 0.14754 RPN box loss: 0.025 RPN score loss: 0.00734 RPN total loss: 0.03234 Total loss: 0.94853 timestamp: 1655044795.1233063 iteration: 46950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12638 FastRCNN class loss: 0.09616 FastRCNN total loss: 0.22254 L1 loss: 0.0000e+00 L2 loss: 0.59153 Learning rate: 0.002 Mask loss: 0.20145 RPN box loss: 0.0104 RPN score loss: 0.0026 RPN total loss: 0.013 Total loss: 1.02853 timestamp: 1655044798.3833714 iteration: 46955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.07427 FastRCNN total loss: 0.1632 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.002 Mask loss: 0.15796 RPN box loss: 0.00514 RPN score loss: 0.0082 RPN total loss: 0.01334 Total loss: 0.92602 timestamp: 1655044801.7168736 iteration: 46960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16977 FastRCNN class loss: 0.06434 FastRCNN total loss: 0.23411 L1 loss: 0.0000e+00 L2 loss: 0.59152 Learning rate: 0.002 Mask loss: 0.12051 RPN box loss: 0.01015 RPN score loss: 0.00575 RPN total loss: 0.01589 Total loss: 0.96203 timestamp: 1655044804.9832947 iteration: 46965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15443 FastRCNN class loss: 0.10633 FastRCNN total loss: 0.26076 L1 loss: 0.0000e+00 L2 loss: 0.59151 Learning rate: 0.002 Mask loss: 0.16264 RPN box loss: 0.03127 RPN score loss: 0.01129 RPN total loss: 0.04256 Total loss: 1.05746 timestamp: 1655044808.2899814 iteration: 46970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.11853 FastRCNN total loss: 0.24765 L1 loss: 0.0000e+00 L2 loss: 0.5915 Learning rate: 0.002 Mask loss: 0.20442 RPN box loss: 0.01618 RPN score loss: 0.00393 RPN total loss: 0.0201 Total loss: 1.06366 timestamp: 1655044811.5616136 iteration: 46975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.14525 L1 loss: 0.0000e+00 L2 loss: 0.59149 Learning rate: 0.002 Mask loss: 0.14796 RPN box loss: 0.00557 RPN score loss: 0.00684 RPN total loss: 0.01241 Total loss: 0.89711 timestamp: 1655044814.9008234 iteration: 46980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13291 FastRCNN class loss: 0.06936 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 0.59148 Learning rate: 0.002 Mask loss: 0.15039 RPN box loss: 0.0216 RPN score loss: 0.00885 RPN total loss: 0.03046 Total loss: 0.9746 timestamp: 1655044818.143563 iteration: 46985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.14225 L1 loss: 0.0000e+00 L2 loss: 0.59147 Learning rate: 0.002 Mask loss: 0.15347 RPN box loss: 0.00591 RPN score loss: 0.00356 RPN total loss: 0.00947 Total loss: 0.89667 timestamp: 1655044821.4726985 iteration: 46990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09437 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.15418 L1 loss: 0.0000e+00 L2 loss: 0.59146 Learning rate: 0.002 Mask loss: 0.15204 RPN box loss: 0.02081 RPN score loss: 0.00607 RPN total loss: 0.02689 Total loss: 0.92457 timestamp: 1655044824.7297003 iteration: 46995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16528 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.22102 L1 loss: 0.0000e+00 L2 loss: 0.59145 Learning rate: 0.002 Mask loss: 0.13099 RPN box loss: 0.01714 RPN score loss: 0.00281 RPN total loss: 0.01995 Total loss: 0.96342 timestamp: 1655044827.994746 iteration: 47000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13947 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.23909 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.002 Mask loss: 0.1216 RPN box loss: 0.01241 RPN score loss: 0.003 RPN total loss: 0.0154 Total loss: 0.96754 timestamp: 1655044831.3033695 iteration: 47005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06621 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.12108 L1 loss: 0.0000e+00 L2 loss: 0.59144 Learning rate: 0.002 Mask loss: 0.10616 RPN box loss: 0.0266 RPN score loss: 0.00696 RPN total loss: 0.03356 Total loss: 0.85223 timestamp: 1655044834.578214 iteration: 47010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05325 FastRCNN class loss: 0.06583 FastRCNN total loss: 0.11908 L1 loss: 0.0000e+00 L2 loss: 0.59143 Learning rate: 0.002 Mask loss: 0.12661 RPN box loss: 0.0305 RPN score loss: 0.0032 RPN total loss: 0.03371 Total loss: 0.87082 timestamp: 1655044837.822467 iteration: 47015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13954 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.19787 L1 loss: 0.0000e+00 L2 loss: 0.59142 Learning rate: 0.002 Mask loss: 0.089 RPN box loss: 0.02364 RPN score loss: 0.00409 RPN total loss: 0.02774 Total loss: 0.90603 timestamp: 1655044841.0078976 iteration: 47020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08432 FastRCNN class loss: 0.04569 FastRCNN total loss: 0.13001 L1 loss: 0.0000e+00 L2 loss: 0.59141 Learning rate: 0.002 Mask loss: 0.13053 RPN box loss: 0.03035 RPN score loss: 0.00355 RPN total loss: 0.0339 Total loss: 0.88585 timestamp: 1655044844.2951314 iteration: 47025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09614 FastRCNN class loss: 0.05715 FastRCNN total loss: 0.1533 L1 loss: 0.0000e+00 L2 loss: 0.5914 Learning rate: 0.002 Mask loss: 0.08356 RPN box loss: 0.01579 RPN score loss: 0.00475 RPN total loss: 0.02054 Total loss: 0.84881 timestamp: 1655044847.520596 iteration: 47030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1119 FastRCNN class loss: 0.07959 FastRCNN total loss: 0.19149 L1 loss: 0.0000e+00 L2 loss: 0.59139 Learning rate: 0.002 Mask loss: 0.12175 RPN box loss: 0.01066 RPN score loss: 0.00151 RPN total loss: 0.01217 Total loss: 0.9168 timestamp: 1655044850.7841952 iteration: 47035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13309 FastRCNN class loss: 0.09955 FastRCNN total loss: 0.23264 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.002 Mask loss: 0.13998 RPN box loss: 0.0183 RPN score loss: 0.00636 RPN total loss: 0.02466 Total loss: 0.98867 timestamp: 1655044854.0143714 iteration: 47040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11077 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.1851 L1 loss: 0.0000e+00 L2 loss: 0.59138 Learning rate: 0.002 Mask loss: 0.1275 RPN box loss: 0.01642 RPN score loss: 0.00623 RPN total loss: 0.02266 Total loss: 0.92664 timestamp: 1655044857.3461351 iteration: 47045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12886 FastRCNN class loss: 0.11576 FastRCNN total loss: 0.24462 L1 loss: 0.0000e+00 L2 loss: 0.59137 Learning rate: 0.002 Mask loss: 0.2233 RPN box loss: 0.00934 RPN score loss: 0.0143 RPN total loss: 0.02364 Total loss: 1.08292 timestamp: 1655044860.54961 iteration: 47050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.08363 FastRCNN total loss: 0.1959 L1 loss: 0.0000e+00 L2 loss: 0.59136 Learning rate: 0.002 Mask loss: 0.14455 RPN box loss: 0.01764 RPN score loss: 0.00434 RPN total loss: 0.02197 Total loss: 0.95378 timestamp: 1655044863.8372755 iteration: 47055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10198 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.17704 L1 loss: 0.0000e+00 L2 loss: 0.59135 Learning rate: 0.002 Mask loss: 0.14431 RPN box loss: 0.02256 RPN score loss: 0.00217 RPN total loss: 0.02473 Total loss: 0.93744 timestamp: 1655044867.1136348 iteration: 47060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09477 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.15803 L1 loss: 0.0000e+00 L2 loss: 0.59134 Learning rate: 0.002 Mask loss: 0.16674 RPN box loss: 0.01442 RPN score loss: 0.00407 RPN total loss: 0.0185 Total loss: 0.93461 timestamp: 1655044870.4404457 iteration: 47065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05361 FastRCNN class loss: 0.05484 FastRCNN total loss: 0.10845 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.002 Mask loss: 0.1524 RPN box loss: 0.01026 RPN score loss: 0.01193 RPN total loss: 0.02219 Total loss: 0.87438 timestamp: 1655044873.7267814 iteration: 47070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10619 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.16507 L1 loss: 0.0000e+00 L2 loss: 0.59133 Learning rate: 0.002 Mask loss: 0.20136 RPN box loss: 0.02476 RPN score loss: 0.00281 RPN total loss: 0.02756 Total loss: 0.98532 timestamp: 1655044876.9901927 iteration: 47075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07329 FastRCNN class loss: 0.06047 FastRCNN total loss: 0.13376 L1 loss: 0.0000e+00 L2 loss: 0.59132 Learning rate: 0.002 Mask loss: 0.20568 RPN box loss: 0.02031 RPN score loss: 0.00533 RPN total loss: 0.02564 Total loss: 0.9564 timestamp: 1655044880.2381365 iteration: 47080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07042 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.12713 L1 loss: 0.0000e+00 L2 loss: 0.59131 Learning rate: 0.002 Mask loss: 0.16274 RPN box loss: 0.00966 RPN score loss: 0.00281 RPN total loss: 0.01247 Total loss: 0.89365 timestamp: 1655044883.543508 iteration: 47085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14484 FastRCNN class loss: 0.12258 FastRCNN total loss: 0.26742 L1 loss: 0.0000e+00 L2 loss: 0.5913 Learning rate: 0.002 Mask loss: 0.197 RPN box loss: 0.02046 RPN score loss: 0.00621 RPN total loss: 0.02667 Total loss: 1.08239 timestamp: 1655044886.8089776 iteration: 47090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1041 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.17752 L1 loss: 0.0000e+00 L2 loss: 0.59129 Learning rate: 0.002 Mask loss: 0.12859 RPN box loss: 0.02224 RPN score loss: 0.00631 RPN total loss: 0.02855 Total loss: 0.92595 timestamp: 1655044890.052194 iteration: 47095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05473 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.11759 L1 loss: 0.0000e+00 L2 loss: 0.59128 Learning rate: 0.002 Mask loss: 0.12168 RPN box loss: 0.02204 RPN score loss: 0.0104 RPN total loss: 0.03244 Total loss: 0.86298 timestamp: 1655044893.3442338 iteration: 47100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08404 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.16938 L1 loss: 0.0000e+00 L2 loss: 0.59127 Learning rate: 0.002 Mask loss: 0.21946 RPN box loss: 0.02264 RPN score loss: 0.01052 RPN total loss: 0.03315 Total loss: 1.01326 timestamp: 1655044896.5700157 iteration: 47105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0583 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.10973 L1 loss: 0.0000e+00 L2 loss: 0.59126 Learning rate: 0.002 Mask loss: 0.13057 RPN box loss: 0.0106 RPN score loss: 0.00583 RPN total loss: 0.01643 Total loss: 0.84798 timestamp: 1655044899.7654285 iteration: 47110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0896 FastRCNN class loss: 0.03574 FastRCNN total loss: 0.12534 L1 loss: 0.0000e+00 L2 loss: 0.59125 Learning rate: 0.002 Mask loss: 0.08717 RPN box loss: 0.00374 RPN score loss: 0.00354 RPN total loss: 0.00728 Total loss: 0.81104 timestamp: 1655044903.015974 iteration: 47115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11952 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.59124 Learning rate: 0.002 Mask loss: 0.13193 RPN box loss: 0.01319 RPN score loss: 0.00262 RPN total loss: 0.01581 Total loss: 0.93706 timestamp: 1655044906.3162775 iteration: 47120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09966 FastRCNN class loss: 0.10362 FastRCNN total loss: 0.20328 L1 loss: 0.0000e+00 L2 loss: 0.59123 Learning rate: 0.002 Mask loss: 0.14523 RPN box loss: 0.02537 RPN score loss: 0.01145 RPN total loss: 0.03683 Total loss: 0.97656 timestamp: 1655044909.6617618 iteration: 47125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12829 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.21227 L1 loss: 0.0000e+00 L2 loss: 0.59122 Learning rate: 0.002 Mask loss: 0.19914 RPN box loss: 0.01202 RPN score loss: 0.00266 RPN total loss: 0.01468 Total loss: 1.0173 timestamp: 1655044912.892186 iteration: 47130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14756 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.21707 L1 loss: 0.0000e+00 L2 loss: 0.59121 Learning rate: 0.002 Mask loss: 0.14202 RPN box loss: 0.01156 RPN score loss: 0.00281 RPN total loss: 0.01437 Total loss: 0.96467 timestamp: 1655044916.0975406 iteration: 47135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.07652 FastRCNN total loss: 0.17658 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.002 Mask loss: 0.12124 RPN box loss: 0.05085 RPN score loss: 0.00654 RPN total loss: 0.05738 Total loss: 0.9464 timestamp: 1655044919.4268296 iteration: 47140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1593 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.23477 L1 loss: 0.0000e+00 L2 loss: 0.5912 Learning rate: 0.002 Mask loss: 0.15777 RPN box loss: 0.01642 RPN score loss: 0.00394 RPN total loss: 0.02036 Total loss: 1.00409 timestamp: 1655044922.762101 iteration: 47145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14204 FastRCNN class loss: 0.09754 FastRCNN total loss: 0.23957 L1 loss: 0.0000e+00 L2 loss: 0.59118 Learning rate: 0.002 Mask loss: 0.19301 RPN box loss: 0.01594 RPN score loss: 0.00799 RPN total loss: 0.02392 Total loss: 1.04769 timestamp: 1655044926.0929708 iteration: 47150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13307 FastRCNN class loss: 0.0669 FastRCNN total loss: 0.19997 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.002 Mask loss: 0.14315 RPN box loss: 0.02234 RPN score loss: 0.00367 RPN total loss: 0.02601 Total loss: 0.9603 timestamp: 1655044929.393759 iteration: 47155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06553 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.13772 L1 loss: 0.0000e+00 L2 loss: 0.59117 Learning rate: 0.002 Mask loss: 0.11604 RPN box loss: 0.00606 RPN score loss: 0.0046 RPN total loss: 0.01066 Total loss: 0.85559 timestamp: 1655044932.6713712 iteration: 47160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1335 FastRCNN class loss: 0.14043 FastRCNN total loss: 0.27392 L1 loss: 0.0000e+00 L2 loss: 0.59116 Learning rate: 0.002 Mask loss: 0.16729 RPN box loss: 0.01518 RPN score loss: 0.0091 RPN total loss: 0.02428 Total loss: 1.05665 timestamp: 1655044935.9046745 iteration: 47165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13884 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.22504 L1 loss: 0.0000e+00 L2 loss: 0.59115 Learning rate: 0.002 Mask loss: 0.15262 RPN box loss: 0.02114 RPN score loss: 0.00434 RPN total loss: 0.02548 Total loss: 0.99429 timestamp: 1655044939.1052754 iteration: 47170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11383 FastRCNN class loss: 0.08306 FastRCNN total loss: 0.19688 L1 loss: 0.0000e+00 L2 loss: 0.59114 Learning rate: 0.002 Mask loss: 0.17062 RPN box loss: 0.0085 RPN score loss: 0.00369 RPN total loss: 0.01219 Total loss: 0.97083 timestamp: 1655044942.3760815 iteration: 47175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13165 FastRCNN class loss: 0.11558 FastRCNN total loss: 0.24723 L1 loss: 0.0000e+00 L2 loss: 0.59113 Learning rate: 0.002 Mask loss: 0.1743 RPN box loss: 0.02818 RPN score loss: 0.00594 RPN total loss: 0.03412 Total loss: 1.04679 timestamp: 1655044945.630927 iteration: 47180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15229 FastRCNN class loss: 0.12828 FastRCNN total loss: 0.28056 L1 loss: 0.0000e+00 L2 loss: 0.59112 Learning rate: 0.002 Mask loss: 0.14692 RPN box loss: 0.02048 RPN score loss: 0.00318 RPN total loss: 0.02367 Total loss: 1.04227 timestamp: 1655044948.8865714 iteration: 47185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10952 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.19543 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.002 Mask loss: 0.15724 RPN box loss: 0.01474 RPN score loss: 0.00273 RPN total loss: 0.01747 Total loss: 0.96125 timestamp: 1655044952.090395 iteration: 47190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05956 FastRCNN class loss: 0.0588 FastRCNN total loss: 0.11836 L1 loss: 0.0000e+00 L2 loss: 0.59111 Learning rate: 0.002 Mask loss: 0.09149 RPN box loss: 0.00501 RPN score loss: 0.00368 RPN total loss: 0.00868 Total loss: 0.80964 timestamp: 1655044955.3728442 iteration: 47195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13969 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.22202 L1 loss: 0.0000e+00 L2 loss: 0.5911 Learning rate: 0.002 Mask loss: 0.19827 RPN box loss: 0.01134 RPN score loss: 0.00315 RPN total loss: 0.01449 Total loss: 1.02588 timestamp: 1655044958.6050947 iteration: 47200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1075 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.20634 L1 loss: 0.0000e+00 L2 loss: 0.59109 Learning rate: 0.002 Mask loss: 0.23024 RPN box loss: 0.00947 RPN score loss: 0.00383 RPN total loss: 0.0133 Total loss: 1.04098 timestamp: 1655044961.835341 iteration: 47205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11173 FastRCNN class loss: 0.15106 FastRCNN total loss: 0.26279 L1 loss: 0.0000e+00 L2 loss: 0.59108 Learning rate: 0.002 Mask loss: 0.11291 RPN box loss: 0.02021 RPN score loss: 0.00477 RPN total loss: 0.02498 Total loss: 0.99176 timestamp: 1655044965.1278892 iteration: 47210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06234 FastRCNN class loss: 0.05958 FastRCNN total loss: 0.12192 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.002 Mask loss: 0.12776 RPN box loss: 0.01039 RPN score loss: 0.00206 RPN total loss: 0.01244 Total loss: 0.8532 timestamp: 1655044968.379706 iteration: 47215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11262 FastRCNN class loss: 0.09571 FastRCNN total loss: 0.20833 L1 loss: 0.0000e+00 L2 loss: 0.59107 Learning rate: 0.002 Mask loss: 0.17512 RPN box loss: 0.03908 RPN score loss: 0.01999 RPN total loss: 0.05908 Total loss: 1.03359 timestamp: 1655044971.6132822 iteration: 47220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.061 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.13235 L1 loss: 0.0000e+00 L2 loss: 0.59106 Learning rate: 0.002 Mask loss: 0.32196 RPN box loss: 0.01267 RPN score loss: 0.00222 RPN total loss: 0.01489 Total loss: 1.06026 timestamp: 1655044974.9572845 iteration: 47225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14117 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.21618 L1 loss: 0.0000e+00 L2 loss: 0.59105 Learning rate: 0.002 Mask loss: 0.12432 RPN box loss: 0.01034 RPN score loss: 0.00584 RPN total loss: 0.01618 Total loss: 0.94773 timestamp: 1655044978.1986475 iteration: 47230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1328 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.23089 L1 loss: 0.0000e+00 L2 loss: 0.59104 Learning rate: 0.002 Mask loss: 0.22373 RPN box loss: 0.0146 RPN score loss: 0.00301 RPN total loss: 0.01762 Total loss: 1.06327 timestamp: 1655044981.5548246 iteration: 47235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14754 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.21569 L1 loss: 0.0000e+00 L2 loss: 0.59103 Learning rate: 0.002 Mask loss: 0.10472 RPN box loss: 0.00753 RPN score loss: 0.00348 RPN total loss: 0.01101 Total loss: 0.92244 timestamp: 1655044984.8546326 iteration: 47240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10807 FastRCNN class loss: 0.14203 FastRCNN total loss: 0.25011 L1 loss: 0.0000e+00 L2 loss: 0.59102 Learning rate: 0.002 Mask loss: 0.20846 RPN box loss: 0.01623 RPN score loss: 0.0041 RPN total loss: 0.02033 Total loss: 1.06991 timestamp: 1655044988.04808 iteration: 47245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13004 FastRCNN class loss: 0.07984 FastRCNN total loss: 0.20988 L1 loss: 0.0000e+00 L2 loss: 0.59101 Learning rate: 0.002 Mask loss: 0.12437 RPN box loss: 0.02339 RPN score loss: 0.00741 RPN total loss: 0.03081 Total loss: 0.95607 timestamp: 1655044991.3271422 iteration: 47250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13515 FastRCNN class loss: 0.07402 FastRCNN total loss: 0.20918 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.002 Mask loss: 0.19125 RPN box loss: 0.02403 RPN score loss: 0.00162 RPN total loss: 0.02565 Total loss: 1.01708 timestamp: 1655044994.5808957 iteration: 47255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10635 FastRCNN class loss: 0.09247 FastRCNN total loss: 0.19882 L1 loss: 0.0000e+00 L2 loss: 0.591 Learning rate: 0.002 Mask loss: 0.15401 RPN box loss: 0.00884 RPN score loss: 0.0056 RPN total loss: 0.01444 Total loss: 0.95827 timestamp: 1655044997.8672988 iteration: 47260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12046 FastRCNN class loss: 0.10602 FastRCNN total loss: 0.22648 L1 loss: 0.0000e+00 L2 loss: 0.59099 Learning rate: 0.002 Mask loss: 0.16813 RPN box loss: 0.0365 RPN score loss: 0.00774 RPN total loss: 0.04424 Total loss: 1.02984 timestamp: 1655045001.1507251 iteration: 47265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.05658 FastRCNN total loss: 0.15949 L1 loss: 0.0000e+00 L2 loss: 0.59098 Learning rate: 0.002 Mask loss: 0.09832 RPN box loss: 0.01625 RPN score loss: 0.00163 RPN total loss: 0.01789 Total loss: 0.86668 timestamp: 1655045004.3805282 iteration: 47270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07645 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.14397 L1 loss: 0.0000e+00 L2 loss: 0.59097 Learning rate: 0.002 Mask loss: 0.17376 RPN box loss: 0.00935 RPN score loss: 0.00404 RPN total loss: 0.01339 Total loss: 0.92209 timestamp: 1655045007.6566467 iteration: 47275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09654 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.18074 L1 loss: 0.0000e+00 L2 loss: 0.59096 Learning rate: 0.002 Mask loss: 0.13748 RPN box loss: 0.01185 RPN score loss: 0.00588 RPN total loss: 0.01773 Total loss: 0.92692 timestamp: 1655045010.9162939 iteration: 47280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15692 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.22657 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.002 Mask loss: 0.11805 RPN box loss: 0.02493 RPN score loss: 0.00938 RPN total loss: 0.03431 Total loss: 0.96988 timestamp: 1655045014.195234 iteration: 47285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10439 FastRCNN class loss: 0.05711 FastRCNN total loss: 0.16151 L1 loss: 0.0000e+00 L2 loss: 0.59095 Learning rate: 0.002 Mask loss: 0.10638 RPN box loss: 0.00964 RPN score loss: 0.00128 RPN total loss: 0.01092 Total loss: 0.86976 timestamp: 1655045017.4856026 iteration: 47290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11607 FastRCNN class loss: 0.05668 FastRCNN total loss: 0.17275 L1 loss: 0.0000e+00 L2 loss: 0.59094 Learning rate: 0.002 Mask loss: 0.13166 RPN box loss: 0.02545 RPN score loss: 0.00212 RPN total loss: 0.02757 Total loss: 0.92293 timestamp: 1655045020.7477908 iteration: 47295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08539 FastRCNN class loss: 0.07675 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.59093 Learning rate: 0.002 Mask loss: 0.1044 RPN box loss: 0.02061 RPN score loss: 0.00637 RPN total loss: 0.02698 Total loss: 0.88445 timestamp: 1655045023.9829383 iteration: 47300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1179 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.19215 L1 loss: 0.0000e+00 L2 loss: 0.59092 Learning rate: 0.002 Mask loss: 0.14405 RPN box loss: 0.01043 RPN score loss: 0.00627 RPN total loss: 0.0167 Total loss: 0.94382 timestamp: 1655045027.258223 iteration: 47305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13384 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.20414 L1 loss: 0.0000e+00 L2 loss: 0.59091 Learning rate: 0.002 Mask loss: 0.12418 RPN box loss: 0.01373 RPN score loss: 0.00435 RPN total loss: 0.01808 Total loss: 0.93731 timestamp: 1655045030.6193259 iteration: 47310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15869 FastRCNN class loss: 0.08233 FastRCNN total loss: 0.24102 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.002 Mask loss: 0.17012 RPN box loss: 0.01587 RPN score loss: 0.00598 RPN total loss: 0.02185 Total loss: 1.02388 timestamp: 1655045033.858296 iteration: 47315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07242 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.12532 L1 loss: 0.0000e+00 L2 loss: 0.59089 Learning rate: 0.002 Mask loss: 0.14978 RPN box loss: 0.0116 RPN score loss: 0.00408 RPN total loss: 0.01567 Total loss: 0.88166 timestamp: 1655045037.1225815 iteration: 47320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16997 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.24868 L1 loss: 0.0000e+00 L2 loss: 0.59088 Learning rate: 0.002 Mask loss: 0.17843 RPN box loss: 0.02553 RPN score loss: 0.01031 RPN total loss: 0.03584 Total loss: 1.05383 timestamp: 1655045040.346283 iteration: 47325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.16138 L1 loss: 0.0000e+00 L2 loss: 0.59087 Learning rate: 0.002 Mask loss: 0.11315 RPN box loss: 0.01925 RPN score loss: 0.01715 RPN total loss: 0.03639 Total loss: 0.90179 timestamp: 1655045043.6404445 iteration: 47330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13116 FastRCNN class loss: 0.1261 FastRCNN total loss: 0.25726 L1 loss: 0.0000e+00 L2 loss: 0.59086 Learning rate: 0.002 Mask loss: 0.17175 RPN box loss: 0.02896 RPN score loss: 0.01338 RPN total loss: 0.04234 Total loss: 1.0622 timestamp: 1655045046.9111116 iteration: 47335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08179 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.13603 L1 loss: 0.0000e+00 L2 loss: 0.59085 Learning rate: 0.002 Mask loss: 0.18488 RPN box loss: 0.0112 RPN score loss: 0.00269 RPN total loss: 0.0139 Total loss: 0.92565 timestamp: 1655045050.181137 iteration: 47340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10282 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.17507 L1 loss: 0.0000e+00 L2 loss: 0.59084 Learning rate: 0.002 Mask loss: 0.11439 RPN box loss: 0.02597 RPN score loss: 0.00814 RPN total loss: 0.03411 Total loss: 0.91441 timestamp: 1655045053.480167 iteration: 47345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11491 FastRCNN class loss: 0.07299 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.59083 Learning rate: 0.002 Mask loss: 0.1586 RPN box loss: 0.01824 RPN score loss: 0.00226 RPN total loss: 0.02051 Total loss: 0.95784 timestamp: 1655045056.7571933 iteration: 47350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07312 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.14573 L1 loss: 0.0000e+00 L2 loss: 0.59082 Learning rate: 0.002 Mask loss: 0.1587 RPN box loss: 0.02116 RPN score loss: 0.00551 RPN total loss: 0.02668 Total loss: 0.92193 timestamp: 1655045060.0233054 iteration: 47355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16755 FastRCNN class loss: 0.10112 FastRCNN total loss: 0.26867 L1 loss: 0.0000e+00 L2 loss: 0.59081 Learning rate: 0.002 Mask loss: 0.17294 RPN box loss: 0.00918 RPN score loss: 0.00517 RPN total loss: 0.01434 Total loss: 1.04676 timestamp: 1655045063.334495 iteration: 47360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09803 FastRCNN class loss: 0.09337 FastRCNN total loss: 0.1914 L1 loss: 0.0000e+00 L2 loss: 0.5908 Learning rate: 0.002 Mask loss: 0.16351 RPN box loss: 0.01761 RPN score loss: 0.00624 RPN total loss: 0.02385 Total loss: 0.96956 timestamp: 1655045066.5786757 iteration: 47365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06644 FastRCNN class loss: 0.03929 FastRCNN total loss: 0.10573 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.002 Mask loss: 0.14338 RPN box loss: 0.00657 RPN score loss: 0.00225 RPN total loss: 0.00882 Total loss: 0.84872 timestamp: 1655045069.8209202 iteration: 47370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13996 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.22672 L1 loss: 0.0000e+00 L2 loss: 0.59079 Learning rate: 0.002 Mask loss: 0.11365 RPN box loss: 0.0445 RPN score loss: 0.00786 RPN total loss: 0.05236 Total loss: 0.98351 timestamp: 1655045073.1053712 iteration: 47375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0782 FastRCNN class loss: 0.04248 FastRCNN total loss: 0.12068 L1 loss: 0.0000e+00 L2 loss: 0.59078 Learning rate: 0.002 Mask loss: 0.14206 RPN box loss: 0.03751 RPN score loss: 0.00522 RPN total loss: 0.04274 Total loss: 0.89626 timestamp: 1655045076.2976277 iteration: 47380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1129 FastRCNN class loss: 0.1046 FastRCNN total loss: 0.21749 L1 loss: 0.0000e+00 L2 loss: 0.59077 Learning rate: 0.002 Mask loss: 0.19493 RPN box loss: 0.03064 RPN score loss: 0.02462 RPN total loss: 0.05526 Total loss: 1.05845 timestamp: 1655045079.5639908 iteration: 47385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10905 FastRCNN class loss: 0.07792 FastRCNN total loss: 0.18696 L1 loss: 0.0000e+00 L2 loss: 0.59076 Learning rate: 0.002 Mask loss: 0.14163 RPN box loss: 0.01473 RPN score loss: 0.0114 RPN total loss: 0.02613 Total loss: 0.94548 timestamp: 1655045082.8580825 iteration: 47390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.06556 FastRCNN total loss: 0.14427 L1 loss: 0.0000e+00 L2 loss: 0.59075 Learning rate: 0.002 Mask loss: 0.14347 RPN box loss: 0.02564 RPN score loss: 0.00763 RPN total loss: 0.03327 Total loss: 0.91176 timestamp: 1655045086.1439342 iteration: 47395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05098 FastRCNN class loss: 0.05407 FastRCNN total loss: 0.10505 L1 loss: 0.0000e+00 L2 loss: 0.59074 Learning rate: 0.002 Mask loss: 0.14074 RPN box loss: 0.00613 RPN score loss: 0.00154 RPN total loss: 0.00767 Total loss: 0.84421 timestamp: 1655045089.4298797 iteration: 47400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.07451 FastRCNN total loss: 0.20806 L1 loss: 0.0000e+00 L2 loss: 0.59073 Learning rate: 0.002 Mask loss: 0.15911 RPN box loss: 0.00936 RPN score loss: 0.00615 RPN total loss: 0.01551 Total loss: 0.97341 timestamp: 1655045092.6676657 iteration: 47405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.123 FastRCNN class loss: 0.09073 FastRCNN total loss: 0.21372 L1 loss: 0.0000e+00 L2 loss: 0.59072 Learning rate: 0.002 Mask loss: 0.1434 RPN box loss: 0.05196 RPN score loss: 0.01355 RPN total loss: 0.06551 Total loss: 1.01335 timestamp: 1655045095.9265058 iteration: 47410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10362 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.17909 L1 loss: 0.0000e+00 L2 loss: 0.59071 Learning rate: 0.002 Mask loss: 0.12984 RPN box loss: 0.0236 RPN score loss: 0.02314 RPN total loss: 0.04674 Total loss: 0.94637 timestamp: 1655045099.18101 iteration: 47415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04665 FastRCNN class loss: 0.03147 FastRCNN total loss: 0.07812 L1 loss: 0.0000e+00 L2 loss: 0.5907 Learning rate: 0.002 Mask loss: 0.09445 RPN box loss: 0.01168 RPN score loss: 0.00128 RPN total loss: 0.01295 Total loss: 0.77622 timestamp: 1655045102.4404125 iteration: 47420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07852 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.12693 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.002 Mask loss: 0.12697 RPN box loss: 0.01761 RPN score loss: 0.00332 RPN total loss: 0.02094 Total loss: 0.86554 timestamp: 1655045105.6963356 iteration: 47425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08808 FastRCNN class loss: 0.04522 FastRCNN total loss: 0.13331 L1 loss: 0.0000e+00 L2 loss: 0.59069 Learning rate: 0.002 Mask loss: 0.11164 RPN box loss: 0.01092 RPN score loss: 0.01416 RPN total loss: 0.02508 Total loss: 0.86072 timestamp: 1655045108.9301555 iteration: 47430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09963 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.1583 L1 loss: 0.0000e+00 L2 loss: 0.59068 Learning rate: 0.002 Mask loss: 0.12378 RPN box loss: 0.01622 RPN score loss: 0.00762 RPN total loss: 0.02384 Total loss: 0.8966 timestamp: 1655045112.201379 iteration: 47435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16669 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.28216 L1 loss: 0.0000e+00 L2 loss: 0.59067 Learning rate: 0.002 Mask loss: 0.19626 RPN box loss: 0.02635 RPN score loss: 0.01169 RPN total loss: 0.03804 Total loss: 1.10713 timestamp: 1655045115.4820528 iteration: 47440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06553 FastRCNN class loss: 0.0696 FastRCNN total loss: 0.13513 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.002 Mask loss: 0.1031 RPN box loss: 0.01216 RPN score loss: 0.00851 RPN total loss: 0.02067 Total loss: 0.84957 timestamp: 1655045118.7970212 iteration: 47445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11494 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.16969 L1 loss: 0.0000e+00 L2 loss: 0.59066 Learning rate: 0.002 Mask loss: 0.10941 RPN box loss: 0.02182 RPN score loss: 0.00172 RPN total loss: 0.02354 Total loss: 0.89329 timestamp: 1655045122.0904088 iteration: 47450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12372 FastRCNN class loss: 0.09786 FastRCNN total loss: 0.22158 L1 loss: 0.0000e+00 L2 loss: 0.59065 Learning rate: 0.002 Mask loss: 0.23828 RPN box loss: 0.03625 RPN score loss: 0.0034 RPN total loss: 0.03965 Total loss: 1.09016 timestamp: 1655045125.323997 iteration: 47455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0583 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.1061 L1 loss: 0.0000e+00 L2 loss: 0.59064 Learning rate: 0.002 Mask loss: 0.07711 RPN box loss: 0.01024 RPN score loss: 0.00642 RPN total loss: 0.01665 Total loss: 0.7905 timestamp: 1655045128.5403779 iteration: 47460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11882 FastRCNN class loss: 0.06238 FastRCNN total loss: 0.1812 L1 loss: 0.0000e+00 L2 loss: 0.59063 Learning rate: 0.002 Mask loss: 0.10755 RPN box loss: 0.01605 RPN score loss: 0.00375 RPN total loss: 0.01981 Total loss: 0.89919 timestamp: 1655045131.783461 iteration: 47465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13303 FastRCNN class loss: 0.07899 FastRCNN total loss: 0.21202 L1 loss: 0.0000e+00 L2 loss: 0.59062 Learning rate: 0.002 Mask loss: 0.1462 RPN box loss: 0.01222 RPN score loss: 0.00272 RPN total loss: 0.01494 Total loss: 0.96378 timestamp: 1655045135.0290337 iteration: 47470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.108 FastRCNN class loss: 0.12996 FastRCNN total loss: 0.23796 L1 loss: 0.0000e+00 L2 loss: 0.59061 Learning rate: 0.002 Mask loss: 0.18653 RPN box loss: 0.02429 RPN score loss: 0.01192 RPN total loss: 0.03621 Total loss: 1.05131 timestamp: 1655045138.338462 iteration: 47475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10749 FastRCNN class loss: 0.10542 FastRCNN total loss: 0.21292 L1 loss: 0.0000e+00 L2 loss: 0.5906 Learning rate: 0.002 Mask loss: 0.14906 RPN box loss: 0.01664 RPN score loss: 0.00476 RPN total loss: 0.0214 Total loss: 0.97398 timestamp: 1655045141.6598697 iteration: 47480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09921 FastRCNN class loss: 0.1039 FastRCNN total loss: 0.20311 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.002 Mask loss: 0.16158 RPN box loss: 0.04405 RPN score loss: 0.01539 RPN total loss: 0.05944 Total loss: 1.01473 timestamp: 1655045144.9037437 iteration: 47485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13908 FastRCNN class loss: 0.08609 FastRCNN total loss: 0.22517 L1 loss: 0.0000e+00 L2 loss: 0.59059 Learning rate: 0.002 Mask loss: 0.13419 RPN box loss: 0.01169 RPN score loss: 0.00241 RPN total loss: 0.0141 Total loss: 0.96404 timestamp: 1655045148.264086 iteration: 47490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1938 FastRCNN class loss: 0.0977 FastRCNN total loss: 0.2915 L1 loss: 0.0000e+00 L2 loss: 0.59058 Learning rate: 0.002 Mask loss: 0.18769 RPN box loss: 0.02838 RPN score loss: 0.00636 RPN total loss: 0.03473 Total loss: 1.10449 timestamp: 1655045151.5581222 iteration: 47495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12322 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.18793 L1 loss: 0.0000e+00 L2 loss: 0.59057 Learning rate: 0.002 Mask loss: 0.13289 RPN box loss: 0.0157 RPN score loss: 0.00305 RPN total loss: 0.01874 Total loss: 0.93014 timestamp: 1655045154.847693 iteration: 47500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.06458 FastRCNN total loss: 0.15957 L1 loss: 0.0000e+00 L2 loss: 0.59056 Learning rate: 0.002 Mask loss: 0.10168 RPN box loss: 0.00934 RPN score loss: 0.004 RPN total loss: 0.01335 Total loss: 0.86515 timestamp: 1655045158.125458 iteration: 47505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13735 FastRCNN class loss: 0.07503 FastRCNN total loss: 0.21238 L1 loss: 0.0000e+00 L2 loss: 0.59055 Learning rate: 0.002 Mask loss: 0.1489 RPN box loss: 0.02006 RPN score loss: 0.00388 RPN total loss: 0.02394 Total loss: 0.97577 timestamp: 1655045161.4074872 iteration: 47510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08165 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.14527 L1 loss: 0.0000e+00 L2 loss: 0.59054 Learning rate: 0.002 Mask loss: 0.12047 RPN box loss: 0.02451 RPN score loss: 0.00228 RPN total loss: 0.02679 Total loss: 0.88306 timestamp: 1655045164.6759934 iteration: 47515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10747 FastRCNN class loss: 0.08112 FastRCNN total loss: 0.18859 L1 loss: 0.0000e+00 L2 loss: 0.59053 Learning rate: 0.002 Mask loss: 0.14166 RPN box loss: 0.01969 RPN score loss: 0.01216 RPN total loss: 0.03186 Total loss: 0.95263 timestamp: 1655045167.972039 iteration: 47520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10789 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.18208 L1 loss: 0.0000e+00 L2 loss: 0.59052 Learning rate: 0.002 Mask loss: 0.12053 RPN box loss: 0.01641 RPN score loss: 0.00687 RPN total loss: 0.02329 Total loss: 0.91642 timestamp: 1655045171.2166317 iteration: 47525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11832 FastRCNN class loss: 0.05186 FastRCNN total loss: 0.17018 L1 loss: 0.0000e+00 L2 loss: 0.59051 Learning rate: 0.002 Mask loss: 0.18178 RPN box loss: 0.01609 RPN score loss: 0.00424 RPN total loss: 0.02033 Total loss: 0.96279 timestamp: 1655045174.5178535 iteration: 47530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18938 FastRCNN class loss: 0.13239 FastRCNN total loss: 0.32177 L1 loss: 0.0000e+00 L2 loss: 0.5905 Learning rate: 0.002 Mask loss: 0.18766 RPN box loss: 0.03 RPN score loss: 0.02119 RPN total loss: 0.05119 Total loss: 1.15111 timestamp: 1655045177.787102 iteration: 47535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11209 FastRCNN class loss: 0.12471 FastRCNN total loss: 0.23679 L1 loss: 0.0000e+00 L2 loss: 0.59049 Learning rate: 0.002 Mask loss: 0.24875 RPN box loss: 0.02715 RPN score loss: 0.00966 RPN total loss: 0.03681 Total loss: 1.11284 timestamp: 1655045181.0368404 iteration: 47540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06186 FastRCNN class loss: 0.0635 FastRCNN total loss: 0.12537 L1 loss: 0.0000e+00 L2 loss: 0.59048 Learning rate: 0.002 Mask loss: 0.12165 RPN box loss: 0.01728 RPN score loss: 0.00328 RPN total loss: 0.02056 Total loss: 0.85806 timestamp: 1655045184.2760751 iteration: 47545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06653 FastRCNN class loss: 0.06587 FastRCNN total loss: 0.1324 L1 loss: 0.0000e+00 L2 loss: 0.59047 Learning rate: 0.002 Mask loss: 0.22603 RPN box loss: 0.03755 RPN score loss: 0.00574 RPN total loss: 0.04329 Total loss: 0.99219 timestamp: 1655045187.5058544 iteration: 47550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10255 FastRCNN class loss: 0.07076 FastRCNN total loss: 0.17331 L1 loss: 0.0000e+00 L2 loss: 0.59046 Learning rate: 0.002 Mask loss: 0.09407 RPN box loss: 0.0259 RPN score loss: 0.0033 RPN total loss: 0.02919 Total loss: 0.88703 timestamp: 1655045190.8249729 iteration: 47555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0745 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.15353 L1 loss: 0.0000e+00 L2 loss: 0.59045 Learning rate: 0.002 Mask loss: 0.17961 RPN box loss: 0.02905 RPN score loss: 0.0067 RPN total loss: 0.03574 Total loss: 0.95934 timestamp: 1655045194.1369836 iteration: 47560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14529 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.23496 L1 loss: 0.0000e+00 L2 loss: 0.59044 Learning rate: 0.002 Mask loss: 0.21523 RPN box loss: 0.03241 RPN score loss: 0.01147 RPN total loss: 0.04388 Total loss: 1.08451 timestamp: 1655045197.413408 iteration: 47565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05755 FastRCNN class loss: 0.04371 FastRCNN total loss: 0.10126 L1 loss: 0.0000e+00 L2 loss: 0.59043 Learning rate: 0.002 Mask loss: 0.12745 RPN box loss: 0.02673 RPN score loss: 0.00563 RPN total loss: 0.03237 Total loss: 0.85151 timestamp: 1655045200.7472596 iteration: 47570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10962 FastRCNN class loss: 0.07466 FastRCNN total loss: 0.18427 L1 loss: 0.0000e+00 L2 loss: 0.59042 Learning rate: 0.002 Mask loss: 0.10282 RPN box loss: 0.02404 RPN score loss: 0.00164 RPN total loss: 0.02568 Total loss: 0.90319 timestamp: 1655045204.0527244 iteration: 47575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1103 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.18566 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.002 Mask loss: 0.15097 RPN box loss: 0.01287 RPN score loss: 0.00512 RPN total loss: 0.01799 Total loss: 0.94504 timestamp: 1655045207.308133 iteration: 47580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17021 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.24041 L1 loss: 0.0000e+00 L2 loss: 0.59041 Learning rate: 0.002 Mask loss: 0.36241 RPN box loss: 0.05922 RPN score loss: 0.00706 RPN total loss: 0.06628 Total loss: 1.25951 timestamp: 1655045210.588159 iteration: 47585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08699 FastRCNN class loss: 0.09122 FastRCNN total loss: 0.17821 L1 loss: 0.0000e+00 L2 loss: 0.59039 Learning rate: 0.002 Mask loss: 0.16487 RPN box loss: 0.02092 RPN score loss: 0.00405 RPN total loss: 0.02497 Total loss: 0.95845 timestamp: 1655045213.8856971 iteration: 47590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1068 FastRCNN class loss: 0.06115 FastRCNN total loss: 0.16796 L1 loss: 0.0000e+00 L2 loss: 0.59038 Learning rate: 0.002 Mask loss: 0.12908 RPN box loss: 0.01664 RPN score loss: 0.01421 RPN total loss: 0.03085 Total loss: 0.91827 timestamp: 1655045217.185881 iteration: 47595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12463 FastRCNN class loss: 0.09997 FastRCNN total loss: 0.2246 L1 loss: 0.0000e+00 L2 loss: 0.59037 Learning rate: 0.002 Mask loss: 0.16926 RPN box loss: 0.01967 RPN score loss: 0.01658 RPN total loss: 0.03625 Total loss: 1.02048 timestamp: 1655045220.3836336 iteration: 47600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15642 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.21586 L1 loss: 0.0000e+00 L2 loss: 0.59036 Learning rate: 0.002 Mask loss: 0.13912 RPN box loss: 0.00782 RPN score loss: 0.00264 RPN total loss: 0.01047 Total loss: 0.95581 timestamp: 1655045223.5921202 iteration: 47605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06314 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.12366 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.002 Mask loss: 0.07642 RPN box loss: 0.00846 RPN score loss: 0.0049 RPN total loss: 0.01336 Total loss: 0.80379 timestamp: 1655045226.9070992 iteration: 47610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08649 FastRCNN class loss: 0.06226 FastRCNN total loss: 0.14876 L1 loss: 0.0000e+00 L2 loss: 0.59035 Learning rate: 0.002 Mask loss: 0.07991 RPN box loss: 0.01794 RPN score loss: 0.00249 RPN total loss: 0.02043 Total loss: 0.83944 timestamp: 1655045230.1118264 iteration: 47615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15679 FastRCNN class loss: 0.11178 FastRCNN total loss: 0.26857 L1 loss: 0.0000e+00 L2 loss: 0.59034 Learning rate: 0.002 Mask loss: 0.15054 RPN box loss: 0.02572 RPN score loss: 0.01043 RPN total loss: 0.03616 Total loss: 1.0456 timestamp: 1655045233.3912632 iteration: 47620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05428 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.10443 L1 loss: 0.0000e+00 L2 loss: 0.59033 Learning rate: 0.002 Mask loss: 0.12468 RPN box loss: 0.03715 RPN score loss: 0.00797 RPN total loss: 0.04511 Total loss: 0.86455 timestamp: 1655045236.6630435 iteration: 47625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08358 FastRCNN class loss: 0.05864 FastRCNN total loss: 0.14221 L1 loss: 0.0000e+00 L2 loss: 0.59032 Learning rate: 0.002 Mask loss: 0.1969 RPN box loss: 0.02486 RPN score loss: 0.00899 RPN total loss: 0.03385 Total loss: 0.96328 timestamp: 1655045239.9158814 iteration: 47630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13324 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.22822 L1 loss: 0.0000e+00 L2 loss: 0.59031 Learning rate: 0.002 Mask loss: 0.15857 RPN box loss: 0.03332 RPN score loss: 0.0092 RPN total loss: 0.04252 Total loss: 1.01962 timestamp: 1655045243.1160474 iteration: 47635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1693 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.2397 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.002 Mask loss: 0.16103 RPN box loss: 0.01622 RPN score loss: 0.00423 RPN total loss: 0.02045 Total loss: 1.01148 timestamp: 1655045246.3670943 iteration: 47640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10435 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.1819 L1 loss: 0.0000e+00 L2 loss: 0.5903 Learning rate: 0.002 Mask loss: 0.12545 RPN box loss: 0.01972 RPN score loss: 0.00508 RPN total loss: 0.0248 Total loss: 0.92245 timestamp: 1655045249.6824238 iteration: 47645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04928 FastRCNN class loss: 0.04137 FastRCNN total loss: 0.09066 L1 loss: 0.0000e+00 L2 loss: 0.59029 Learning rate: 0.002 Mask loss: 0.13426 RPN box loss: 0.01462 RPN score loss: 0.01052 RPN total loss: 0.02513 Total loss: 0.84034 timestamp: 1655045252.940046 iteration: 47650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03643 FastRCNN class loss: 0.02862 FastRCNN total loss: 0.06505 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.002 Mask loss: 0.10752 RPN box loss: 0.00164 RPN score loss: 0.00329 RPN total loss: 0.00493 Total loss: 0.76778 timestamp: 1655045256.2532 iteration: 47655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12502 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.18957 L1 loss: 0.0000e+00 L2 loss: 0.59028 Learning rate: 0.002 Mask loss: 0.11489 RPN box loss: 0.0144 RPN score loss: 0.0056 RPN total loss: 0.02 Total loss: 0.91473 timestamp: 1655045259.5656886 iteration: 47660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10947 FastRCNN class loss: 0.07176 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.59027 Learning rate: 0.002 Mask loss: 0.13428 RPN box loss: 0.02318 RPN score loss: 0.00496 RPN total loss: 0.02813 Total loss: 0.93392 timestamp: 1655045262.792359 iteration: 47665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.04771 FastRCNN total loss: 0.13411 L1 loss: 0.0000e+00 L2 loss: 0.59026 Learning rate: 0.002 Mask loss: 0.14313 RPN box loss: 0.01404 RPN score loss: 0.00554 RPN total loss: 0.01957 Total loss: 0.88707 timestamp: 1655045266.0678186 iteration: 47670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0804 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.1562 L1 loss: 0.0000e+00 L2 loss: 0.59024 Learning rate: 0.002 Mask loss: 0.17249 RPN box loss: 0.01186 RPN score loss: 0.00705 RPN total loss: 0.01891 Total loss: 0.93785 timestamp: 1655045269.3525245 iteration: 47675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16108 FastRCNN class loss: 0.10623 FastRCNN total loss: 0.26731 L1 loss: 0.0000e+00 L2 loss: 0.59023 Learning rate: 0.002 Mask loss: 0.14726 RPN box loss: 0.0183 RPN score loss: 0.00461 RPN total loss: 0.02291 Total loss: 1.02771 timestamp: 1655045272.6558313 iteration: 47680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0919 FastRCNN class loss: 0.04407 FastRCNN total loss: 0.13597 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.002 Mask loss: 0.13536 RPN box loss: 0.05183 RPN score loss: 0.00693 RPN total loss: 0.05876 Total loss: 0.92032 timestamp: 1655045275.9904628 iteration: 47685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.1501 L1 loss: 0.0000e+00 L2 loss: 0.59022 Learning rate: 0.002 Mask loss: 0.13444 RPN box loss: 0.03393 RPN score loss: 0.0088 RPN total loss: 0.04273 Total loss: 0.91749 timestamp: 1655045279.3416507 iteration: 47690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11518 FastRCNN class loss: 0.10512 FastRCNN total loss: 0.2203 L1 loss: 0.0000e+00 L2 loss: 0.59021 Learning rate: 0.002 Mask loss: 0.19231 RPN box loss: 0.01317 RPN score loss: 0.00484 RPN total loss: 0.01801 Total loss: 1.02082 timestamp: 1655045282.606908 iteration: 47695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0957 FastRCNN class loss: 0.08965 FastRCNN total loss: 0.18535 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.002 Mask loss: 0.14483 RPN box loss: 0.01906 RPN score loss: 0.00498 RPN total loss: 0.02404 Total loss: 0.94443 timestamp: 1655045285.9107318 iteration: 47700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11663 FastRCNN class loss: 0.07839 FastRCNN total loss: 0.19502 L1 loss: 0.0000e+00 L2 loss: 0.5902 Learning rate: 0.002 Mask loss: 0.12744 RPN box loss: 0.01069 RPN score loss: 0.0071 RPN total loss: 0.01778 Total loss: 0.93043 timestamp: 1655045289.207529 iteration: 47705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0959 FastRCNN class loss: 0.08268 FastRCNN total loss: 0.17858 L1 loss: 0.0000e+00 L2 loss: 0.59019 Learning rate: 0.002 Mask loss: 0.1771 RPN box loss: 0.01596 RPN score loss: 0.00888 RPN total loss: 0.02484 Total loss: 0.97071 timestamp: 1655045292.4962842 iteration: 47710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09496 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.18058 L1 loss: 0.0000e+00 L2 loss: 0.59018 Learning rate: 0.002 Mask loss: 0.22544 RPN box loss: 0.05478 RPN score loss: 0.01475 RPN total loss: 0.06953 Total loss: 1.06574 timestamp: 1655045295.8000157 iteration: 47715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14335 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.20681 L1 loss: 0.0000e+00 L2 loss: 0.59017 Learning rate: 0.002 Mask loss: 0.21448 RPN box loss: 0.01283 RPN score loss: 0.00263 RPN total loss: 0.01547 Total loss: 1.02693 timestamp: 1655045299.0679615 iteration: 47720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13706 FastRCNN class loss: 0.10052 FastRCNN total loss: 0.23758 L1 loss: 0.0000e+00 L2 loss: 0.59016 Learning rate: 0.002 Mask loss: 0.1687 RPN box loss: 0.01882 RPN score loss: 0.00641 RPN total loss: 0.02524 Total loss: 1.02167 timestamp: 1655045302.4454436 iteration: 47725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05088 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.09959 L1 loss: 0.0000e+00 L2 loss: 0.59015 Learning rate: 0.002 Mask loss: 0.1106 RPN box loss: 0.01049 RPN score loss: 0.01452 RPN total loss: 0.02501 Total loss: 0.82535 timestamp: 1655045305.6568289 iteration: 47730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10641 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.18882 L1 loss: 0.0000e+00 L2 loss: 0.59014 Learning rate: 0.002 Mask loss: 0.15933 RPN box loss: 0.01652 RPN score loss: 0.02381 RPN total loss: 0.04034 Total loss: 0.97863 timestamp: 1655045308.9513016 iteration: 47735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12135 FastRCNN class loss: 0.0416 FastRCNN total loss: 0.16295 L1 loss: 0.0000e+00 L2 loss: 0.59013 Learning rate: 0.002 Mask loss: 0.09839 RPN box loss: 0.02005 RPN score loss: 0.00447 RPN total loss: 0.02452 Total loss: 0.876 timestamp: 1655045312.1755776 iteration: 47740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13328 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.22372 L1 loss: 0.0000e+00 L2 loss: 0.59012 Learning rate: 0.002 Mask loss: 0.09245 RPN box loss: 0.00694 RPN score loss: 0.00287 RPN total loss: 0.00981 Total loss: 0.9161 timestamp: 1655045315.4437597 iteration: 47745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12149 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 0.59011 Learning rate: 0.002 Mask loss: 0.12021 RPN box loss: 0.02616 RPN score loss: 0.00631 RPN total loss: 0.03247 Total loss: 0.93243 timestamp: 1655045318.674289 iteration: 47750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1138 FastRCNN class loss: 0.04464 FastRCNN total loss: 0.15843 L1 loss: 0.0000e+00 L2 loss: 0.5901 Learning rate: 0.002 Mask loss: 0.12448 RPN box loss: 0.01902 RPN score loss: 0.00357 RPN total loss: 0.02259 Total loss: 0.8956 timestamp: 1655045321.9136531 iteration: 47755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08155 FastRCNN class loss: 0.06158 FastRCNN total loss: 0.14312 L1 loss: 0.0000e+00 L2 loss: 0.59009 Learning rate: 0.002 Mask loss: 0.12566 RPN box loss: 0.0167 RPN score loss: 0.0083 RPN total loss: 0.025 Total loss: 0.88387 timestamp: 1655045325.180711 iteration: 47760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13996 FastRCNN class loss: 0.09769 FastRCNN total loss: 0.23765 L1 loss: 0.0000e+00 L2 loss: 0.59008 Learning rate: 0.002 Mask loss: 0.15796 RPN box loss: 0.04027 RPN score loss: 0.01109 RPN total loss: 0.05136 Total loss: 1.03705 timestamp: 1655045328.4471636 iteration: 47765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13123 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.002 Mask loss: 0.12293 RPN box loss: 0.01161 RPN score loss: 0.00305 RPN total loss: 0.01466 Total loss: 0.9327 timestamp: 1655045331.737226 iteration: 47770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05215 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.12271 L1 loss: 0.0000e+00 L2 loss: 0.59007 Learning rate: 0.002 Mask loss: 0.09721 RPN box loss: 0.02262 RPN score loss: 0.00948 RPN total loss: 0.0321 Total loss: 0.84209 timestamp: 1655045335.011889 iteration: 47775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09767 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.16221 L1 loss: 0.0000e+00 L2 loss: 0.59006 Learning rate: 0.002 Mask loss: 0.12731 RPN box loss: 0.01326 RPN score loss: 0.00643 RPN total loss: 0.0197 Total loss: 0.89927 timestamp: 1655045338.2394307 iteration: 47780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15784 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.23202 L1 loss: 0.0000e+00 L2 loss: 0.59005 Learning rate: 0.002 Mask loss: 0.13979 RPN box loss: 0.0118 RPN score loss: 0.00409 RPN total loss: 0.01589 Total loss: 0.97775 timestamp: 1655045341.53592 iteration: 47785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.11028 FastRCNN total loss: 0.23821 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.002 Mask loss: 0.14111 RPN box loss: 0.01123 RPN score loss: 0.01087 RPN total loss: 0.0221 Total loss: 0.99146 timestamp: 1655045344.806908 iteration: 47790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09727 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.16744 L1 loss: 0.0000e+00 L2 loss: 0.59004 Learning rate: 0.002 Mask loss: 0.18556 RPN box loss: 0.00934 RPN score loss: 0.00678 RPN total loss: 0.01612 Total loss: 0.95915 timestamp: 1655045348.1601906 iteration: 47795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.116 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.21046 L1 loss: 0.0000e+00 L2 loss: 0.59003 Learning rate: 0.002 Mask loss: 0.10702 RPN box loss: 0.01477 RPN score loss: 0.00424 RPN total loss: 0.01901 Total loss: 0.92653 timestamp: 1655045351.3810732 iteration: 47800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07874 FastRCNN class loss: 0.04443 FastRCNN total loss: 0.12317 L1 loss: 0.0000e+00 L2 loss: 0.59002 Learning rate: 0.002 Mask loss: 0.13113 RPN box loss: 0.01168 RPN score loss: 0.01016 RPN total loss: 0.02184 Total loss: 0.86616 timestamp: 1655045354.6436327 iteration: 47805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.0651 FastRCNN total loss: 0.19865 L1 loss: 0.0000e+00 L2 loss: 0.59001 Learning rate: 0.002 Mask loss: 0.12389 RPN box loss: 0.03745 RPN score loss: 0.00218 RPN total loss: 0.03964 Total loss: 0.9522 timestamp: 1655045357.908216 iteration: 47810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08328 FastRCNN class loss: 0.0483 FastRCNN total loss: 0.13158 L1 loss: 0.0000e+00 L2 loss: 0.59 Learning rate: 0.002 Mask loss: 0.11548 RPN box loss: 0.01069 RPN score loss: 0.00752 RPN total loss: 0.01821 Total loss: 0.85528 timestamp: 1655045361.18502 iteration: 47815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07787 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.14439 L1 loss: 0.0000e+00 L2 loss: 0.58999 Learning rate: 0.002 Mask loss: 0.11835 RPN box loss: 0.0196 RPN score loss: 0.00549 RPN total loss: 0.02509 Total loss: 0.87782 timestamp: 1655045364.4010024 iteration: 47820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10161 FastRCNN class loss: 0.05513 FastRCNN total loss: 0.15674 L1 loss: 0.0000e+00 L2 loss: 0.58998 Learning rate: 0.002 Mask loss: 0.13164 RPN box loss: 0.01665 RPN score loss: 0.00405 RPN total loss: 0.0207 Total loss: 0.89907 timestamp: 1655045367.6840136 iteration: 47825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10981 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.19757 L1 loss: 0.0000e+00 L2 loss: 0.58997 Learning rate: 0.002 Mask loss: 0.20111 RPN box loss: 0.02371 RPN score loss: 0.00438 RPN total loss: 0.0281 Total loss: 1.01675 timestamp: 1655045370.9410622 iteration: 47830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.16237 L1 loss: 0.0000e+00 L2 loss: 0.58996 Learning rate: 0.002 Mask loss: 0.12728 RPN box loss: 0.01175 RPN score loss: 0.00279 RPN total loss: 0.01454 Total loss: 0.89416 timestamp: 1655045374.1832285 iteration: 47835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08175 FastRCNN class loss: 0.08915 FastRCNN total loss: 0.1709 L1 loss: 0.0000e+00 L2 loss: 0.58995 Learning rate: 0.002 Mask loss: 0.11013 RPN box loss: 0.01403 RPN score loss: 0.00631 RPN total loss: 0.02034 Total loss: 0.89132 timestamp: 1655045377.4793732 iteration: 47840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08899 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.15564 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.002 Mask loss: 0.14185 RPN box loss: 0.01798 RPN score loss: 0.00413 RPN total loss: 0.02211 Total loss: 0.90954 timestamp: 1655045380.686131 iteration: 47845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.08385 FastRCNN total loss: 0.20169 L1 loss: 0.0000e+00 L2 loss: 0.58994 Learning rate: 0.002 Mask loss: 0.12228 RPN box loss: 0.01232 RPN score loss: 0.0031 RPN total loss: 0.01542 Total loss: 0.92932 timestamp: 1655045384.015875 iteration: 47850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10306 FastRCNN class loss: 0.07239 FastRCNN total loss: 0.17545 L1 loss: 0.0000e+00 L2 loss: 0.58993 Learning rate: 0.002 Mask loss: 0.1403 RPN box loss: 0.03257 RPN score loss: 0.0052 RPN total loss: 0.03777 Total loss: 0.94345 timestamp: 1655045387.2509742 iteration: 47855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0771 FastRCNN class loss: 0.04463 FastRCNN total loss: 0.12174 L1 loss: 0.0000e+00 L2 loss: 0.58992 Learning rate: 0.002 Mask loss: 0.11203 RPN box loss: 0.00622 RPN score loss: 0.00286 RPN total loss: 0.00907 Total loss: 0.83276 timestamp: 1655045390.471884 iteration: 47860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.15942 L1 loss: 0.0000e+00 L2 loss: 0.58991 Learning rate: 0.002 Mask loss: 0.11786 RPN box loss: 0.00717 RPN score loss: 0.00242 RPN total loss: 0.0096 Total loss: 0.87679 timestamp: 1655045393.8192098 iteration: 47865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14233 FastRCNN class loss: 0.1023 FastRCNN total loss: 0.24463 L1 loss: 0.0000e+00 L2 loss: 0.5899 Learning rate: 0.002 Mask loss: 0.15458 RPN box loss: 0.02477 RPN score loss: 0.01271 RPN total loss: 0.03748 Total loss: 1.02659 timestamp: 1655045397.0879753 iteration: 47870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08481 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.002 Mask loss: 0.1595 RPN box loss: 0.01349 RPN score loss: 0.00514 RPN total loss: 0.01863 Total loss: 0.91637 timestamp: 1655045400.3715522 iteration: 47875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09592 FastRCNN class loss: 0.05282 FastRCNN total loss: 0.14874 L1 loss: 0.0000e+00 L2 loss: 0.58989 Learning rate: 0.002 Mask loss: 0.12962 RPN box loss: 0.01472 RPN score loss: 0.00943 RPN total loss: 0.02414 Total loss: 0.89239 timestamp: 1655045403.5962875 iteration: 47880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08387 FastRCNN class loss: 0.05096 FastRCNN total loss: 0.13482 L1 loss: 0.0000e+00 L2 loss: 0.58988 Learning rate: 0.002 Mask loss: 0.16815 RPN box loss: 0.02799 RPN score loss: 0.00452 RPN total loss: 0.03251 Total loss: 0.92536 timestamp: 1655045406.8400779 iteration: 47885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10207 FastRCNN class loss: 0.05993 FastRCNN total loss: 0.16201 L1 loss: 0.0000e+00 L2 loss: 0.58987 Learning rate: 0.002 Mask loss: 0.20861 RPN box loss: 0.01733 RPN score loss: 0.00372 RPN total loss: 0.02105 Total loss: 0.98153 timestamp: 1655045410.1291518 iteration: 47890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12079 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.1903 L1 loss: 0.0000e+00 L2 loss: 0.58986 Learning rate: 0.002 Mask loss: 0.14931 RPN box loss: 0.01968 RPN score loss: 0.00536 RPN total loss: 0.02504 Total loss: 0.95451 timestamp: 1655045413.4092252 iteration: 47895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0928 FastRCNN class loss: 0.0484 FastRCNN total loss: 0.1412 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.002 Mask loss: 0.1263 RPN box loss: 0.0405 RPN score loss: 0.00411 RPN total loss: 0.04461 Total loss: 0.90195 timestamp: 1655045416.644876 iteration: 47900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0646 FastRCNN class loss: 0.08241 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 0.58984 Learning rate: 0.002 Mask loss: 0.14974 RPN box loss: 0.00533 RPN score loss: 0.00273 RPN total loss: 0.00806 Total loss: 0.89464 timestamp: 1655045419.9735649 iteration: 47905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11226 FastRCNN class loss: 0.0815 FastRCNN total loss: 0.19375 L1 loss: 0.0000e+00 L2 loss: 0.58982 Learning rate: 0.002 Mask loss: 0.12675 RPN box loss: 0.01835 RPN score loss: 0.01303 RPN total loss: 0.03137 Total loss: 0.9417 timestamp: 1655045423.2268143 iteration: 47910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.04469 FastRCNN total loss: 0.11278 L1 loss: 0.0000e+00 L2 loss: 0.58981 Learning rate: 0.002 Mask loss: 0.11152 RPN box loss: 0.0081 RPN score loss: 0.00262 RPN total loss: 0.01073 Total loss: 0.82484 timestamp: 1655045426.4879339 iteration: 47915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12031 FastRCNN class loss: 0.06348 FastRCNN total loss: 0.1838 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.002 Mask loss: 0.14025 RPN box loss: 0.02835 RPN score loss: 0.00106 RPN total loss: 0.02941 Total loss: 0.94327 timestamp: 1655045429.7614577 iteration: 47920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1256 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.18036 L1 loss: 0.0000e+00 L2 loss: 0.5898 Learning rate: 0.002 Mask loss: 0.11998 RPN box loss: 0.01006 RPN score loss: 0.00142 RPN total loss: 0.01148 Total loss: 0.90162 timestamp: 1655045433.103321 iteration: 47925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08578 FastRCNN class loss: 0.04512 FastRCNN total loss: 0.1309 L1 loss: 0.0000e+00 L2 loss: 0.58979 Learning rate: 0.002 Mask loss: 0.12857 RPN box loss: 0.02215 RPN score loss: 0.00332 RPN total loss: 0.02547 Total loss: 0.87473 timestamp: 1655045436.3710144 iteration: 47930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0873 FastRCNN class loss: 0.07414 FastRCNN total loss: 0.16144 L1 loss: 0.0000e+00 L2 loss: 0.58978 Learning rate: 0.002 Mask loss: 0.14864 RPN box loss: 0.00946 RPN score loss: 0.0047 RPN total loss: 0.01417 Total loss: 0.91402 timestamp: 1655045439.6009042 iteration: 47935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08511 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.1571 L1 loss: 0.0000e+00 L2 loss: 0.58977 Learning rate: 0.002 Mask loss: 0.11223 RPN box loss: 0.01019 RPN score loss: 0.00362 RPN total loss: 0.0138 Total loss: 0.8729 timestamp: 1655045442.8118296 iteration: 47940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07054 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.14552 L1 loss: 0.0000e+00 L2 loss: 0.58976 Learning rate: 0.002 Mask loss: 0.12368 RPN box loss: 0.00381 RPN score loss: 0.00197 RPN total loss: 0.00578 Total loss: 0.86475 timestamp: 1655045446.0729244 iteration: 47945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12395 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.1826 L1 loss: 0.0000e+00 L2 loss: 0.58975 Learning rate: 0.002 Mask loss: 0.12994 RPN box loss: 0.021 RPN score loss: 0.00297 RPN total loss: 0.02398 Total loss: 0.92627 timestamp: 1655045449.4070115 iteration: 47950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06799 FastRCNN class loss: 0.04017 FastRCNN total loss: 0.10816 L1 loss: 0.0000e+00 L2 loss: 0.58974 Learning rate: 0.002 Mask loss: 0.10832 RPN box loss: 0.00996 RPN score loss: 0.00188 RPN total loss: 0.01183 Total loss: 0.81805 timestamp: 1655045452.6228876 iteration: 47955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1138 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.18586 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.002 Mask loss: 0.14288 RPN box loss: 0.01679 RPN score loss: 0.00476 RPN total loss: 0.02156 Total loss: 0.94003 timestamp: 1655045455.8841186 iteration: 47960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16909 FastRCNN class loss: 0.06178 FastRCNN total loss: 0.23086 L1 loss: 0.0000e+00 L2 loss: 0.58973 Learning rate: 0.002 Mask loss: 0.14446 RPN box loss: 0.1029 RPN score loss: 0.00687 RPN total loss: 0.10977 Total loss: 1.07483 timestamp: 1655045459.1918695 iteration: 47965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10283 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.16182 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.002 Mask loss: 0.09995 RPN box loss: 0.01381 RPN score loss: 0.00229 RPN total loss: 0.0161 Total loss: 0.86759 timestamp: 1655045462.417726 iteration: 47970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.05931 FastRCNN total loss: 0.18687 L1 loss: 0.0000e+00 L2 loss: 0.58972 Learning rate: 0.002 Mask loss: 0.14271 RPN box loss: 0.01983 RPN score loss: 0.00266 RPN total loss: 0.0225 Total loss: 0.94179 timestamp: 1655045465.665094 iteration: 47975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09702 FastRCNN class loss: 0.0785 FastRCNN total loss: 0.17552 L1 loss: 0.0000e+00 L2 loss: 0.58971 Learning rate: 0.002 Mask loss: 0.13677 RPN box loss: 0.03008 RPN score loss: 0.00835 RPN total loss: 0.03844 Total loss: 0.94044 timestamp: 1655045468.9603233 iteration: 47980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.07118 FastRCNN total loss: 0.15301 L1 loss: 0.0000e+00 L2 loss: 0.5897 Learning rate: 0.002 Mask loss: 0.13408 RPN box loss: 0.01852 RPN score loss: 0.00478 RPN total loss: 0.0233 Total loss: 0.90009 timestamp: 1655045472.2276177 iteration: 47985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11162 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.18528 L1 loss: 0.0000e+00 L2 loss: 0.58969 Learning rate: 0.002 Mask loss: 0.13973 RPN box loss: 0.00909 RPN score loss: 0.01106 RPN total loss: 0.02015 Total loss: 0.93485 timestamp: 1655045475.5612397 iteration: 47990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14906 FastRCNN class loss: 0.09736 FastRCNN total loss: 0.24641 L1 loss: 0.0000e+00 L2 loss: 0.58968 Learning rate: 0.002 Mask loss: 0.13994 RPN box loss: 0.01426 RPN score loss: 0.01391 RPN total loss: 0.02817 Total loss: 1.0042 timestamp: 1655045478.8648195 iteration: 47995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09151 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.16576 L1 loss: 0.0000e+00 L2 loss: 0.58967 Learning rate: 0.002 Mask loss: 0.14681 RPN box loss: 0.02927 RPN score loss: 0.00562 RPN total loss: 0.0349 Total loss: 0.93714 timestamp: 1655045482.0632374 iteration: 48000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06297 FastRCNN class loss: 0.05321 FastRCNN total loss: 0.11618 L1 loss: 0.0000e+00 L2 loss: 0.58966 Learning rate: 0.002 Mask loss: 0.15292 RPN box loss: 0.01097 RPN score loss: 0.00543 RPN total loss: 0.0164 Total loss: 0.87516 timestamp: 1655045485.279168 iteration: 48005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11578 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.58965 Learning rate: 0.002 Mask loss: 0.10651 RPN box loss: 0.01002 RPN score loss: 0.00301 RPN total loss: 0.01303 Total loss: 0.89252 timestamp: 1655045488.5535665 iteration: 48010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15472 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.22948 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.002 Mask loss: 0.14424 RPN box loss: 0.04017 RPN score loss: 0.00556 RPN total loss: 0.04573 Total loss: 1.00909 timestamp: 1655045491.7459571 iteration: 48015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10153 FastRCNN class loss: 0.09816 FastRCNN total loss: 0.19969 L1 loss: 0.0000e+00 L2 loss: 0.58964 Learning rate: 0.002 Mask loss: 0.10308 RPN box loss: 0.01622 RPN score loss: 0.01229 RPN total loss: 0.02851 Total loss: 0.92092 timestamp: 1655045495.0258017 iteration: 48020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0747 FastRCNN class loss: 0.07591 FastRCNN total loss: 0.1506 L1 loss: 0.0000e+00 L2 loss: 0.58963 Learning rate: 0.002 Mask loss: 0.13776 RPN box loss: 0.01879 RPN score loss: 0.00607 RPN total loss: 0.02487 Total loss: 0.90286 timestamp: 1655045498.2950745 iteration: 48025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13651 FastRCNN class loss: 0.08124 FastRCNN total loss: 0.21775 L1 loss: 0.0000e+00 L2 loss: 0.58962 Learning rate: 0.002 Mask loss: 0.17007 RPN box loss: 0.0409 RPN score loss: 0.00861 RPN total loss: 0.0495 Total loss: 1.02694 timestamp: 1655045501.5906014 iteration: 48030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17884 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.25528 L1 loss: 0.0000e+00 L2 loss: 0.58961 Learning rate: 0.002 Mask loss: 0.12026 RPN box loss: 0.01169 RPN score loss: 0.01185 RPN total loss: 0.02354 Total loss: 0.9887 timestamp: 1655045504.8690104 iteration: 48035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.11323 FastRCNN total loss: 0.21192 L1 loss: 0.0000e+00 L2 loss: 0.5896 Learning rate: 0.002 Mask loss: 0.15771 RPN box loss: 0.03118 RPN score loss: 0.01504 RPN total loss: 0.04623 Total loss: 1.00546 timestamp: 1655045508.1435387 iteration: 48040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08033 FastRCNN class loss: 0.06375 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.58959 Learning rate: 0.002 Mask loss: 0.08336 RPN box loss: 0.00855 RPN score loss: 0.00386 RPN total loss: 0.0124 Total loss: 0.82943 timestamp: 1655045511.450769 iteration: 48045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13722 FastRCNN class loss: 0.09748 FastRCNN total loss: 0.23471 L1 loss: 0.0000e+00 L2 loss: 0.58958 Learning rate: 0.002 Mask loss: 0.15252 RPN box loss: 0.01752 RPN score loss: 0.00528 RPN total loss: 0.0228 Total loss: 0.99961 timestamp: 1655045514.7097425 iteration: 48050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09421 FastRCNN class loss: 0.05465 FastRCNN total loss: 0.14886 L1 loss: 0.0000e+00 L2 loss: 0.58957 Learning rate: 0.002 Mask loss: 0.14028 RPN box loss: 0.00627 RPN score loss: 0.00132 RPN total loss: 0.00758 Total loss: 0.88629 timestamp: 1655045517.9847949 iteration: 48055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10768 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 0.58956 Learning rate: 0.002 Mask loss: 0.16087 RPN box loss: 0.02245 RPN score loss: 0.00493 RPN total loss: 0.02738 Total loss: 0.94937 timestamp: 1655045521.268748 iteration: 48060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0711 FastRCNN class loss: 0.08704 FastRCNN total loss: 0.15814 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.002 Mask loss: 0.09073 RPN box loss: 0.00953 RPN score loss: 0.00199 RPN total loss: 0.01151 Total loss: 0.84993 timestamp: 1655045524.5295506 iteration: 48065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15356 FastRCNN class loss: 0.11862 FastRCNN total loss: 0.27218 L1 loss: 0.0000e+00 L2 loss: 0.58955 Learning rate: 0.002 Mask loss: 0.14923 RPN box loss: 0.03778 RPN score loss: 0.00871 RPN total loss: 0.04649 Total loss: 1.05745 timestamp: 1655045527.770357 iteration: 48070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06724 FastRCNN class loss: 0.09102 FastRCNN total loss: 0.15825 L1 loss: 0.0000e+00 L2 loss: 0.58954 Learning rate: 0.002 Mask loss: 0.18299 RPN box loss: 0.02542 RPN score loss: 0.00618 RPN total loss: 0.0316 Total loss: 0.96238 timestamp: 1655045531.0090294 iteration: 48075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.093 FastRCNN class loss: 0.08634 FastRCNN total loss: 0.17934 L1 loss: 0.0000e+00 L2 loss: 0.58953 Learning rate: 0.002 Mask loss: 0.16635 RPN box loss: 0.01546 RPN score loss: 0.00182 RPN total loss: 0.01728 Total loss: 0.95249 timestamp: 1655045534.2850218 iteration: 48080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10222 FastRCNN class loss: 0.09245 FastRCNN total loss: 0.19468 L1 loss: 0.0000e+00 L2 loss: 0.58952 Learning rate: 0.002 Mask loss: 0.17386 RPN box loss: 0.02015 RPN score loss: 0.00372 RPN total loss: 0.02387 Total loss: 0.98192 timestamp: 1655045537.5128958 iteration: 48085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07262 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.13073 L1 loss: 0.0000e+00 L2 loss: 0.58951 Learning rate: 0.002 Mask loss: 0.31286 RPN box loss: 0.01536 RPN score loss: 0.00428 RPN total loss: 0.01963 Total loss: 1.05274 timestamp: 1655045540.7587755 iteration: 48090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.13923 L1 loss: 0.0000e+00 L2 loss: 0.5895 Learning rate: 0.002 Mask loss: 0.12042 RPN box loss: 0.01148 RPN score loss: 0.00717 RPN total loss: 0.01865 Total loss: 0.8678 timestamp: 1655045544.0363598 iteration: 48095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06914 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.12932 L1 loss: 0.0000e+00 L2 loss: 0.58949 Learning rate: 0.002 Mask loss: 0.11333 RPN box loss: 0.02499 RPN score loss: 0.00659 RPN total loss: 0.03158 Total loss: 0.86372 timestamp: 1655045547.2613997 iteration: 48100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07747 FastRCNN class loss: 0.05307 FastRCNN total loss: 0.13054 L1 loss: 0.0000e+00 L2 loss: 0.58948 Learning rate: 0.002 Mask loss: 0.13198 RPN box loss: 0.01924 RPN score loss: 0.00474 RPN total loss: 0.02397 Total loss: 0.87597 timestamp: 1655045550.6031702 iteration: 48105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10489 FastRCNN class loss: 0.08819 FastRCNN total loss: 0.19308 L1 loss: 0.0000e+00 L2 loss: 0.58947 Learning rate: 0.002 Mask loss: 0.2105 RPN box loss: 0.06432 RPN score loss: 0.01289 RPN total loss: 0.07721 Total loss: 1.07027 timestamp: 1655045553.8810332 iteration: 48110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10628 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.16822 L1 loss: 0.0000e+00 L2 loss: 0.58946 Learning rate: 0.002 Mask loss: 0.13494 RPN box loss: 0.01594 RPN score loss: 0.0041 RPN total loss: 0.02005 Total loss: 0.91267 timestamp: 1655045557.1144135 iteration: 48115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10075 FastRCNN class loss: 0.07727 FastRCNN total loss: 0.17802 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.002 Mask loss: 0.14067 RPN box loss: 0.01178 RPN score loss: 0.00878 RPN total loss: 0.02056 Total loss: 0.9287 timestamp: 1655045560.3754828 iteration: 48120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09977 FastRCNN class loss: 0.06625 FastRCNN total loss: 0.16602 L1 loss: 0.0000e+00 L2 loss: 0.58945 Learning rate: 0.002 Mask loss: 0.15089 RPN box loss: 0.02062 RPN score loss: 0.00364 RPN total loss: 0.02426 Total loss: 0.93062 timestamp: 1655045563.6621883 iteration: 48125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16008 FastRCNN class loss: 0.15023 FastRCNN total loss: 0.31031 L1 loss: 0.0000e+00 L2 loss: 0.58944 Learning rate: 0.002 Mask loss: 0.19179 RPN box loss: 0.04808 RPN score loss: 0.00994 RPN total loss: 0.05801 Total loss: 1.14956 timestamp: 1655045566.9549983 iteration: 48130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11876 FastRCNN class loss: 0.04904 FastRCNN total loss: 0.1678 L1 loss: 0.0000e+00 L2 loss: 0.58943 Learning rate: 0.002 Mask loss: 0.08739 RPN box loss: 0.01994 RPN score loss: 0.00338 RPN total loss: 0.02332 Total loss: 0.86795 timestamp: 1655045570.2262084 iteration: 48135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08435 FastRCNN class loss: 0.04619 FastRCNN total loss: 0.13055 L1 loss: 0.0000e+00 L2 loss: 0.58942 Learning rate: 0.002 Mask loss: 0.13766 RPN box loss: 0.00968 RPN score loss: 0.00315 RPN total loss: 0.01284 Total loss: 0.87047 timestamp: 1655045573.457909 iteration: 48140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0654 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.11389 L1 loss: 0.0000e+00 L2 loss: 0.58941 Learning rate: 0.002 Mask loss: 0.08718 RPN box loss: 0.03054 RPN score loss: 0.00828 RPN total loss: 0.03883 Total loss: 0.82931 timestamp: 1655045576.7141337 iteration: 48145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08913 FastRCNN class loss: 0.08971 FastRCNN total loss: 0.17884 L1 loss: 0.0000e+00 L2 loss: 0.5894 Learning rate: 0.002 Mask loss: 0.28802 RPN box loss: 0.03136 RPN score loss: 0.00453 RPN total loss: 0.03588 Total loss: 1.09214 timestamp: 1655045579.9978006 iteration: 48150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1228 FastRCNN class loss: 0.1893 FastRCNN total loss: 0.3121 L1 loss: 0.0000e+00 L2 loss: 0.58939 Learning rate: 0.002 Mask loss: 0.13628 RPN box loss: 0.01667 RPN score loss: 0.00861 RPN total loss: 0.02528 Total loss: 1.06304 timestamp: 1655045583.293421 iteration: 48155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07953 FastRCNN class loss: 0.03595 FastRCNN total loss: 0.11547 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.002 Mask loss: 0.13373 RPN box loss: 0.01267 RPN score loss: 0.00959 RPN total loss: 0.02226 Total loss: 0.86085 timestamp: 1655045586.4948373 iteration: 48160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15018 FastRCNN class loss: 0.09148 FastRCNN total loss: 0.24166 L1 loss: 0.0000e+00 L2 loss: 0.58938 Learning rate: 0.002 Mask loss: 0.14681 RPN box loss: 0.02266 RPN score loss: 0.00849 RPN total loss: 0.03115 Total loss: 1.00899 timestamp: 1655045589.757844 iteration: 48165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.05105 FastRCNN total loss: 0.1303 L1 loss: 0.0000e+00 L2 loss: 0.58937 Learning rate: 0.002 Mask loss: 0.13505 RPN box loss: 0.01832 RPN score loss: 0.00617 RPN total loss: 0.02449 Total loss: 0.87921 timestamp: 1655045593.0244322 iteration: 48170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14104 FastRCNN class loss: 0.09177 FastRCNN total loss: 0.23281 L1 loss: 0.0000e+00 L2 loss: 0.58936 Learning rate: 0.002 Mask loss: 0.19944 RPN box loss: 0.02079 RPN score loss: 0.01072 RPN total loss: 0.03151 Total loss: 1.05313 timestamp: 1655045596.3190298 iteration: 48175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11417 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.18349 L1 loss: 0.0000e+00 L2 loss: 0.58935 Learning rate: 0.002 Mask loss: 0.11906 RPN box loss: 0.01061 RPN score loss: 0.0047 RPN total loss: 0.01531 Total loss: 0.90721 timestamp: 1655045599.586726 iteration: 48180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09918 FastRCNN class loss: 0.11283 FastRCNN total loss: 0.21201 L1 loss: 0.0000e+00 L2 loss: 0.58934 Learning rate: 0.002 Mask loss: 0.15432 RPN box loss: 0.01182 RPN score loss: 0.00428 RPN total loss: 0.0161 Total loss: 0.97177 timestamp: 1655045602.8455431 iteration: 48185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09539 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.15166 L1 loss: 0.0000e+00 L2 loss: 0.58933 Learning rate: 0.002 Mask loss: 0.1385 RPN box loss: 0.00654 RPN score loss: 0.00212 RPN total loss: 0.00866 Total loss: 0.88815 timestamp: 1655045606.0962055 iteration: 48190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09533 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.16708 L1 loss: 0.0000e+00 L2 loss: 0.58932 Learning rate: 0.002 Mask loss: 0.1222 RPN box loss: 0.01533 RPN score loss: 0.00276 RPN total loss: 0.01809 Total loss: 0.8967 timestamp: 1655045609.3389487 iteration: 48195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.0407 FastRCNN total loss: 0.11157 L1 loss: 0.0000e+00 L2 loss: 0.58931 Learning rate: 0.002 Mask loss: 0.12224 RPN box loss: 0.02526 RPN score loss: 0.00665 RPN total loss: 0.03191 Total loss: 0.85502 timestamp: 1655045612.6028621 iteration: 48200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10523 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.17904 L1 loss: 0.0000e+00 L2 loss: 0.5893 Learning rate: 0.002 Mask loss: 0.12773 RPN box loss: 0.01769 RPN score loss: 0.00842 RPN total loss: 0.0261 Total loss: 0.92217 timestamp: 1655045615.8780236 iteration: 48205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.16975 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.002 Mask loss: 0.13546 RPN box loss: 0.01918 RPN score loss: 0.0108 RPN total loss: 0.02998 Total loss: 0.92447 timestamp: 1655045619.101918 iteration: 48210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10418 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.16489 L1 loss: 0.0000e+00 L2 loss: 0.58929 Learning rate: 0.002 Mask loss: 0.14089 RPN box loss: 0.03331 RPN score loss: 0.00474 RPN total loss: 0.03805 Total loss: 0.93312 timestamp: 1655045622.4011612 iteration: 48215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.0437 FastRCNN total loss: 0.15531 L1 loss: 0.0000e+00 L2 loss: 0.58928 Learning rate: 0.002 Mask loss: 0.0829 RPN box loss: 0.02635 RPN score loss: 0.00281 RPN total loss: 0.02916 Total loss: 0.85665 timestamp: 1655045625.6787636 iteration: 48220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09878 FastRCNN class loss: 0.0729 FastRCNN total loss: 0.17168 L1 loss: 0.0000e+00 L2 loss: 0.58927 Learning rate: 0.002 Mask loss: 0.15506 RPN box loss: 0.01363 RPN score loss: 0.00203 RPN total loss: 0.01566 Total loss: 0.93167 timestamp: 1655045628.96058 iteration: 48225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.05423 FastRCNN total loss: 0.13209 L1 loss: 0.0000e+00 L2 loss: 0.58926 Learning rate: 0.002 Mask loss: 0.14108 RPN box loss: 0.00999 RPN score loss: 0.01155 RPN total loss: 0.02154 Total loss: 0.88397 timestamp: 1655045632.1885424 iteration: 48230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11853 FastRCNN class loss: 0.08807 FastRCNN total loss: 0.2066 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.002 Mask loss: 0.15788 RPN box loss: 0.02112 RPN score loss: 0.00418 RPN total loss: 0.0253 Total loss: 0.97904 timestamp: 1655045635.4913025 iteration: 48235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06353 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.11638 L1 loss: 0.0000e+00 L2 loss: 0.58925 Learning rate: 0.002 Mask loss: 0.11872 RPN box loss: 0.01649 RPN score loss: 0.00198 RPN total loss: 0.01847 Total loss: 0.84282 timestamp: 1655045638.7587996 iteration: 48240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10021 FastRCNN class loss: 0.09088 FastRCNN total loss: 0.19109 L1 loss: 0.0000e+00 L2 loss: 0.58924 Learning rate: 0.002 Mask loss: 0.17019 RPN box loss: 0.01523 RPN score loss: 0.0074 RPN total loss: 0.02263 Total loss: 0.97314 timestamp: 1655045642.0593944 iteration: 48245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07762 FastRCNN class loss: 0.06281 FastRCNN total loss: 0.14043 L1 loss: 0.0000e+00 L2 loss: 0.58923 Learning rate: 0.002 Mask loss: 0.12819 RPN box loss: 0.00797 RPN score loss: 0.00364 RPN total loss: 0.0116 Total loss: 0.86946 timestamp: 1655045645.3036382 iteration: 48250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20632 FastRCNN class loss: 0.1242 FastRCNN total loss: 0.33052 L1 loss: 0.0000e+00 L2 loss: 0.58922 Learning rate: 0.002 Mask loss: 0.24244 RPN box loss: 0.01549 RPN score loss: 0.00931 RPN total loss: 0.0248 Total loss: 1.18698 timestamp: 1655045648.631938 iteration: 48255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07748 FastRCNN class loss: 0.0318 FastRCNN total loss: 0.10927 L1 loss: 0.0000e+00 L2 loss: 0.58921 Learning rate: 0.002 Mask loss: 0.1131 RPN box loss: 0.00868 RPN score loss: 0.0054 RPN total loss: 0.01407 Total loss: 0.82565 timestamp: 1655045651.8483784 iteration: 48260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.17111 L1 loss: 0.0000e+00 L2 loss: 0.5892 Learning rate: 0.002 Mask loss: 0.14447 RPN box loss: 0.01741 RPN score loss: 0.00346 RPN total loss: 0.02087 Total loss: 0.92565 timestamp: 1655045655.1495929 iteration: 48265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11156 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.16725 L1 loss: 0.0000e+00 L2 loss: 0.58919 Learning rate: 0.002 Mask loss: 0.16004 RPN box loss: 0.00699 RPN score loss: 0.0043 RPN total loss: 0.0113 Total loss: 0.92778 timestamp: 1655045658.4751623 iteration: 48270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14864 FastRCNN class loss: 0.10294 FastRCNN total loss: 0.25157 L1 loss: 0.0000e+00 L2 loss: 0.58918 Learning rate: 0.002 Mask loss: 0.27029 RPN box loss: 0.01207 RPN score loss: 0.00615 RPN total loss: 0.01821 Total loss: 1.12926 timestamp: 1655045661.7588966 iteration: 48275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11134 FastRCNN class loss: 0.0903 FastRCNN total loss: 0.20164 L1 loss: 0.0000e+00 L2 loss: 0.58917 Learning rate: 0.002 Mask loss: 0.14895 RPN box loss: 0.01261 RPN score loss: 0.00446 RPN total loss: 0.01707 Total loss: 0.95684 timestamp: 1655045665.0953841 iteration: 48280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13884 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.21666 L1 loss: 0.0000e+00 L2 loss: 0.58916 Learning rate: 0.002 Mask loss: 0.1611 RPN box loss: 0.01042 RPN score loss: 0.00374 RPN total loss: 0.01417 Total loss: 0.98109 timestamp: 1655045668.3794389 iteration: 48285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11903 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.17399 L1 loss: 0.0000e+00 L2 loss: 0.58915 Learning rate: 0.002 Mask loss: 0.12119 RPN box loss: 0.01276 RPN score loss: 0.00217 RPN total loss: 0.01493 Total loss: 0.89925 timestamp: 1655045671.6238558 iteration: 48290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12898 FastRCNN class loss: 0.09053 FastRCNN total loss: 0.21951 L1 loss: 0.0000e+00 L2 loss: 0.58914 Learning rate: 0.002 Mask loss: 0.19853 RPN box loss: 0.02486 RPN score loss: 0.0041 RPN total loss: 0.02896 Total loss: 1.03614 timestamp: 1655045674.8850465 iteration: 48295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13493 FastRCNN class loss: 0.09552 FastRCNN total loss: 0.23045 L1 loss: 0.0000e+00 L2 loss: 0.58913 Learning rate: 0.002 Mask loss: 0.17962 RPN box loss: 0.02342 RPN score loss: 0.01177 RPN total loss: 0.03519 Total loss: 1.0344 timestamp: 1655045678.1466682 iteration: 48300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12111 FastRCNN class loss: 0.1272 FastRCNN total loss: 0.24831 L1 loss: 0.0000e+00 L2 loss: 0.58912 Learning rate: 0.002 Mask loss: 0.18678 RPN box loss: 0.03412 RPN score loss: 0.01129 RPN total loss: 0.04541 Total loss: 1.06961 timestamp: 1655045681.4110396 iteration: 48305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11945 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.1858 L1 loss: 0.0000e+00 L2 loss: 0.58911 Learning rate: 0.002 Mask loss: 0.11225 RPN box loss: 0.0421 RPN score loss: 0.00236 RPN total loss: 0.04446 Total loss: 0.93163 timestamp: 1655045684.6922069 iteration: 48310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1435 FastRCNN class loss: 0.11974 FastRCNN total loss: 0.26324 L1 loss: 0.0000e+00 L2 loss: 0.5891 Learning rate: 0.002 Mask loss: 0.22206 RPN box loss: 0.03434 RPN score loss: 0.02574 RPN total loss: 0.06009 Total loss: 1.13448 timestamp: 1655045687.9860146 iteration: 48315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15828 FastRCNN class loss: 0.14374 FastRCNN total loss: 0.30203 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.002 Mask loss: 0.1551 RPN box loss: 0.0296 RPN score loss: 0.00929 RPN total loss: 0.03889 Total loss: 1.08511 timestamp: 1655045691.2669754 iteration: 48320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11684 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.19803 L1 loss: 0.0000e+00 L2 loss: 0.58909 Learning rate: 0.002 Mask loss: 0.13904 RPN box loss: 0.01435 RPN score loss: 0.00414 RPN total loss: 0.01849 Total loss: 0.94465 timestamp: 1655045694.445001 iteration: 48325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06135 FastRCNN class loss: 0.05777 FastRCNN total loss: 0.11912 L1 loss: 0.0000e+00 L2 loss: 0.58908 Learning rate: 0.002 Mask loss: 0.09366 RPN box loss: 0.00667 RPN score loss: 0.00584 RPN total loss: 0.01251 Total loss: 0.81436 timestamp: 1655045697.6908765 iteration: 48330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07687 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.13261 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.002 Mask loss: 0.13217 RPN box loss: 0.00544 RPN score loss: 0.00068 RPN total loss: 0.00612 Total loss: 0.85998 timestamp: 1655045700.9619536 iteration: 48335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.07593 FastRCNN total loss: 0.15937 L1 loss: 0.0000e+00 L2 loss: 0.58907 Learning rate: 0.002 Mask loss: 0.15315 RPN box loss: 0.02908 RPN score loss: 0.00817 RPN total loss: 0.03725 Total loss: 0.93884 timestamp: 1655045704.258692 iteration: 48340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.16753 L1 loss: 0.0000e+00 L2 loss: 0.58906 Learning rate: 0.002 Mask loss: 0.14842 RPN box loss: 0.02109 RPN score loss: 0.00222 RPN total loss: 0.02331 Total loss: 0.92832 timestamp: 1655045707.5403178 iteration: 48345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07293 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.12789 L1 loss: 0.0000e+00 L2 loss: 0.58905 Learning rate: 0.002 Mask loss: 0.14585 RPN box loss: 0.02604 RPN score loss: 0.00497 RPN total loss: 0.03101 Total loss: 0.8938 timestamp: 1655045710.8774393 iteration: 48350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12939 FastRCNN class loss: 0.07147 FastRCNN total loss: 0.20086 L1 loss: 0.0000e+00 L2 loss: 0.58904 Learning rate: 0.002 Mask loss: 0.17708 RPN box loss: 0.02276 RPN score loss: 0.00363 RPN total loss: 0.02639 Total loss: 0.99337 timestamp: 1655045714.1123781 iteration: 48355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1407 FastRCNN class loss: 0.06336 FastRCNN total loss: 0.20406 L1 loss: 0.0000e+00 L2 loss: 0.58903 Learning rate: 0.002 Mask loss: 0.14711 RPN box loss: 0.03098 RPN score loss: 0.00637 RPN total loss: 0.03735 Total loss: 0.97755 timestamp: 1655045717.4001534 iteration: 48360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07279 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.58902 Learning rate: 0.002 Mask loss: 0.13557 RPN box loss: 0.00989 RPN score loss: 0.00152 RPN total loss: 0.0114 Total loss: 0.87894 timestamp: 1655045720.7528877 iteration: 48365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.03947 FastRCNN total loss: 0.10169 L1 loss: 0.0000e+00 L2 loss: 0.58901 Learning rate: 0.002 Mask loss: 0.12218 RPN box loss: 0.01299 RPN score loss: 0.00082 RPN total loss: 0.01381 Total loss: 0.82669 timestamp: 1655045724.0242732 iteration: 48370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10805 FastRCNN class loss: 0.09016 FastRCNN total loss: 0.19821 L1 loss: 0.0000e+00 L2 loss: 0.589 Learning rate: 0.002 Mask loss: 0.14377 RPN box loss: 0.01264 RPN score loss: 0.00212 RPN total loss: 0.01476 Total loss: 0.94575 timestamp: 1655045727.3009098 iteration: 48375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09872 FastRCNN class loss: 0.0418 FastRCNN total loss: 0.14052 L1 loss: 0.0000e+00 L2 loss: 0.58899 Learning rate: 0.002 Mask loss: 0.12901 RPN box loss: 0.00925 RPN score loss: 0.0044 RPN total loss: 0.01365 Total loss: 0.87217 timestamp: 1655045730.5960739 iteration: 48380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.09921 FastRCNN total loss: 0.21298 L1 loss: 0.0000e+00 L2 loss: 0.58898 Learning rate: 0.002 Mask loss: 0.16517 RPN box loss: 0.0183 RPN score loss: 0.0087 RPN total loss: 0.027 Total loss: 0.99413 timestamp: 1655045733.8824224 iteration: 48385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17924 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.27902 L1 loss: 0.0000e+00 L2 loss: 0.58897 Learning rate: 0.002 Mask loss: 0.15821 RPN box loss: 0.00993 RPN score loss: 0.00721 RPN total loss: 0.01714 Total loss: 1.04334 timestamp: 1655045737.178247 iteration: 48390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.18384 L1 loss: 0.0000e+00 L2 loss: 0.58896 Learning rate: 0.002 Mask loss: 0.15726 RPN box loss: 0.01413 RPN score loss: 0.00615 RPN total loss: 0.02028 Total loss: 0.95034 timestamp: 1655045740.4395628 iteration: 48395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.04121 FastRCNN total loss: 0.12562 L1 loss: 0.0000e+00 L2 loss: 0.58895 Learning rate: 0.002 Mask loss: 0.08915 RPN box loss: 0.01163 RPN score loss: 0.00461 RPN total loss: 0.01625 Total loss: 0.81997 timestamp: 1655045743.652866 iteration: 48400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17444 FastRCNN class loss: 0.11168 FastRCNN total loss: 0.28612 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.002 Mask loss: 0.17744 RPN box loss: 0.04968 RPN score loss: 0.01002 RPN total loss: 0.0597 Total loss: 1.11221 timestamp: 1655045746.9656875 iteration: 48405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07745 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.14132 L1 loss: 0.0000e+00 L2 loss: 0.58894 Learning rate: 0.002 Mask loss: 0.10828 RPN box loss: 0.0053 RPN score loss: 0.00129 RPN total loss: 0.0066 Total loss: 0.84513 timestamp: 1655045750.2507875 iteration: 48410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14231 FastRCNN class loss: 0.16729 FastRCNN total loss: 0.3096 L1 loss: 0.0000e+00 L2 loss: 0.58893 Learning rate: 0.002 Mask loss: 0.15882 RPN box loss: 0.01201 RPN score loss: 0.01853 RPN total loss: 0.03054 Total loss: 1.08789 timestamp: 1655045753.5186317 iteration: 48415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14592 FastRCNN class loss: 0.12364 FastRCNN total loss: 0.26956 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.002 Mask loss: 0.17555 RPN box loss: 0.04263 RPN score loss: 0.00472 RPN total loss: 0.04735 Total loss: 1.08139 timestamp: 1655045756.7553763 iteration: 48420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.0923 FastRCNN total loss: 0.17624 L1 loss: 0.0000e+00 L2 loss: 0.58892 Learning rate: 0.002 Mask loss: 0.1778 RPN box loss: 0.03546 RPN score loss: 0.01472 RPN total loss: 0.05019 Total loss: 0.99314 timestamp: 1655045760.0940676 iteration: 48425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07835 FastRCNN class loss: 0.05549 FastRCNN total loss: 0.13384 L1 loss: 0.0000e+00 L2 loss: 0.58891 Learning rate: 0.002 Mask loss: 0.07781 RPN box loss: 0.01485 RPN score loss: 0.00157 RPN total loss: 0.01642 Total loss: 0.81698 timestamp: 1655045763.330209 iteration: 48430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16123 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.24675 L1 loss: 0.0000e+00 L2 loss: 0.5889 Learning rate: 0.002 Mask loss: 0.19909 RPN box loss: 0.01843 RPN score loss: 0.00757 RPN total loss: 0.026 Total loss: 1.06074 timestamp: 1655045766.6517282 iteration: 48435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17798 FastRCNN class loss: 0.09336 FastRCNN total loss: 0.27134 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.002 Mask loss: 0.17396 RPN box loss: 0.03717 RPN score loss: 0.00679 RPN total loss: 0.04396 Total loss: 1.07815 timestamp: 1655045769.9575393 iteration: 48440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.13302 L1 loss: 0.0000e+00 L2 loss: 0.58889 Learning rate: 0.002 Mask loss: 0.12521 RPN box loss: 0.01503 RPN score loss: 0.00181 RPN total loss: 0.01684 Total loss: 0.86396 timestamp: 1655045773.1607785 iteration: 48445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11981 FastRCNN class loss: 0.06333 FastRCNN total loss: 0.18314 L1 loss: 0.0000e+00 L2 loss: 0.58888 Learning rate: 0.002 Mask loss: 0.0912 RPN box loss: 0.01586 RPN score loss: 0.00367 RPN total loss: 0.01953 Total loss: 0.88275 timestamp: 1655045776.4671817 iteration: 48450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17075 FastRCNN class loss: 0.08773 FastRCNN total loss: 0.25848 L1 loss: 0.0000e+00 L2 loss: 0.58887 Learning rate: 0.002 Mask loss: 0.20006 RPN box loss: 0.01864 RPN score loss: 0.00561 RPN total loss: 0.02426 Total loss: 1.07167 timestamp: 1655045779.7569509 iteration: 48455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.15439 L1 loss: 0.0000e+00 L2 loss: 0.58886 Learning rate: 0.002 Mask loss: 0.13083 RPN box loss: 0.03167 RPN score loss: 0.01134 RPN total loss: 0.04301 Total loss: 0.91709 timestamp: 1655045783.0135202 iteration: 48460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09561 FastRCNN class loss: 0.07502 FastRCNN total loss: 0.17063 L1 loss: 0.0000e+00 L2 loss: 0.58885 Learning rate: 0.002 Mask loss: 0.19871 RPN box loss: 0.02496 RPN score loss: 0.00536 RPN total loss: 0.03033 Total loss: 0.98851 timestamp: 1655045786.2773612 iteration: 48465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.14031 L1 loss: 0.0000e+00 L2 loss: 0.58884 Learning rate: 0.002 Mask loss: 0.1066 RPN box loss: 0.01345 RPN score loss: 0.00553 RPN total loss: 0.01898 Total loss: 0.85473 timestamp: 1655045789.5260556 iteration: 48470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.14419 L1 loss: 0.0000e+00 L2 loss: 0.58883 Learning rate: 0.002 Mask loss: 0.18099 RPN box loss: 0.01348 RPN score loss: 0.00793 RPN total loss: 0.0214 Total loss: 0.93542 timestamp: 1655045792.8420188 iteration: 48475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07396 FastRCNN class loss: 0.068 FastRCNN total loss: 0.14195 L1 loss: 0.0000e+00 L2 loss: 0.58882 Learning rate: 0.002 Mask loss: 0.13605 RPN box loss: 0.01257 RPN score loss: 0.00073 RPN total loss: 0.0133 Total loss: 0.88012 timestamp: 1655045796.1120024 iteration: 48480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11162 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.19426 L1 loss: 0.0000e+00 L2 loss: 0.58881 Learning rate: 0.002 Mask loss: 0.19547 RPN box loss: 0.01264 RPN score loss: 0.01983 RPN total loss: 0.03247 Total loss: 1.01101 timestamp: 1655045799.4239726 iteration: 48485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.16583 L1 loss: 0.0000e+00 L2 loss: 0.5888 Learning rate: 0.002 Mask loss: 0.13967 RPN box loss: 0.04171 RPN score loss: 0.00992 RPN total loss: 0.05163 Total loss: 0.94593 timestamp: 1655045802.7771919 iteration: 48490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07124 FastRCNN class loss: 0.07275 FastRCNN total loss: 0.14398 L1 loss: 0.0000e+00 L2 loss: 0.58879 Learning rate: 0.002 Mask loss: 0.10167 RPN box loss: 0.02175 RPN score loss: 0.00508 RPN total loss: 0.02683 Total loss: 0.86127 timestamp: 1655045806.1240342 iteration: 48495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08698 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.14693 L1 loss: 0.0000e+00 L2 loss: 0.58878 Learning rate: 0.002 Mask loss: 0.0746 RPN box loss: 0.00616 RPN score loss: 0.00149 RPN total loss: 0.00765 Total loss: 0.81797 timestamp: 1655045809.4599617 iteration: 48500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11855 FastRCNN class loss: 0.09005 FastRCNN total loss: 0.2086 L1 loss: 0.0000e+00 L2 loss: 0.58877 Learning rate: 0.002 Mask loss: 0.2177 RPN box loss: 0.0379 RPN score loss: 0.00413 RPN total loss: 0.04204 Total loss: 1.05711 timestamp: 1655045812.7366004 iteration: 48505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11326 FastRCNN class loss: 0.06458 FastRCNN total loss: 0.17784 L1 loss: 0.0000e+00 L2 loss: 0.58876 Learning rate: 0.002 Mask loss: 0.16417 RPN box loss: 0.01747 RPN score loss: 0.00563 RPN total loss: 0.0231 Total loss: 0.95388 timestamp: 1655045816.064879 iteration: 48510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14746 FastRCNN class loss: 0.08622 FastRCNN total loss: 0.23368 L1 loss: 0.0000e+00 L2 loss: 0.58875 Learning rate: 0.002 Mask loss: 0.22979 RPN box loss: 0.00536 RPN score loss: 0.00539 RPN total loss: 0.01075 Total loss: 1.06297 timestamp: 1655045819.2895904 iteration: 48515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09563 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.14718 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.002 Mask loss: 0.09727 RPN box loss: 0.01981 RPN score loss: 0.00712 RPN total loss: 0.02693 Total loss: 0.86012 timestamp: 1655045822.5783386 iteration: 48520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08949 FastRCNN class loss: 0.05408 FastRCNN total loss: 0.14357 L1 loss: 0.0000e+00 L2 loss: 0.58874 Learning rate: 0.002 Mask loss: 0.12808 RPN box loss: 0.00755 RPN score loss: 0.00321 RPN total loss: 0.01075 Total loss: 0.87113 timestamp: 1655045825.834356 iteration: 48525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09839 FastRCNN class loss: 0.05304 FastRCNN total loss: 0.15143 L1 loss: 0.0000e+00 L2 loss: 0.58873 Learning rate: 0.002 Mask loss: 0.09138 RPN box loss: 0.008 RPN score loss: 0.00296 RPN total loss: 0.01096 Total loss: 0.8425 timestamp: 1655045829.0735517 iteration: 48530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18126 FastRCNN class loss: 0.09488 FastRCNN total loss: 0.27614 L1 loss: 0.0000e+00 L2 loss: 0.58872 Learning rate: 0.002 Mask loss: 0.13945 RPN box loss: 0.00837 RPN score loss: 0.00471 RPN total loss: 0.01308 Total loss: 1.01739 timestamp: 1655045832.3121626 iteration: 48535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08364 FastRCNN class loss: 0.09542 FastRCNN total loss: 0.17905 L1 loss: 0.0000e+00 L2 loss: 0.58871 Learning rate: 0.002 Mask loss: 0.22839 RPN box loss: 0.02166 RPN score loss: 0.00184 RPN total loss: 0.0235 Total loss: 1.01965 timestamp: 1655045835.5778408 iteration: 48540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13799 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.23252 L1 loss: 0.0000e+00 L2 loss: 0.5887 Learning rate: 0.002 Mask loss: 0.13383 RPN box loss: 0.00762 RPN score loss: 0.00379 RPN total loss: 0.01141 Total loss: 0.96646 timestamp: 1655045838.8493652 iteration: 48545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07208 FastRCNN class loss: 0.07316 FastRCNN total loss: 0.14525 L1 loss: 0.0000e+00 L2 loss: 0.58869 Learning rate: 0.002 Mask loss: 0.13606 RPN box loss: 0.01227 RPN score loss: 0.00353 RPN total loss: 0.0158 Total loss: 0.88579 timestamp: 1655045842.201934 iteration: 48550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.15505 L1 loss: 0.0000e+00 L2 loss: 0.58868 Learning rate: 0.002 Mask loss: 0.17055 RPN box loss: 0.01417 RPN score loss: 0.00995 RPN total loss: 0.02412 Total loss: 0.9384 timestamp: 1655045845.481606 iteration: 48555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15434 FastRCNN class loss: 0.12489 FastRCNN total loss: 0.27923 L1 loss: 0.0000e+00 L2 loss: 0.58867 Learning rate: 0.002 Mask loss: 0.2086 RPN box loss: 0.03673 RPN score loss: 0.01327 RPN total loss: 0.05001 Total loss: 1.12651 timestamp: 1655045848.7156684 iteration: 48560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10063 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.18009 L1 loss: 0.0000e+00 L2 loss: 0.58866 Learning rate: 0.002 Mask loss: 0.19611 RPN box loss: 0.03023 RPN score loss: 0.01349 RPN total loss: 0.04371 Total loss: 1.00858 timestamp: 1655045851.891744 iteration: 48565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08184 FastRCNN class loss: 0.07026 FastRCNN total loss: 0.15211 L1 loss: 0.0000e+00 L2 loss: 0.58865 Learning rate: 0.002 Mask loss: 0.12401 RPN box loss: 0.01544 RPN score loss: 0.00113 RPN total loss: 0.01657 Total loss: 0.88134 timestamp: 1655045855.1193051 iteration: 48570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07996 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.15238 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.002 Mask loss: 0.11145 RPN box loss: 0.03196 RPN score loss: 0.00852 RPN total loss: 0.04048 Total loss: 0.89295 timestamp: 1655045858.4363 iteration: 48575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12029 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.19615 L1 loss: 0.0000e+00 L2 loss: 0.58864 Learning rate: 0.002 Mask loss: 0.12028 RPN box loss: 0.01766 RPN score loss: 0.00727 RPN total loss: 0.02493 Total loss: 0.93 timestamp: 1655045861.727865 iteration: 48580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0823 FastRCNN class loss: 0.07187 FastRCNN total loss: 0.15417 L1 loss: 0.0000e+00 L2 loss: 0.58863 Learning rate: 0.002 Mask loss: 0.13369 RPN box loss: 0.0168 RPN score loss: 0.004 RPN total loss: 0.0208 Total loss: 0.89728 timestamp: 1655045864.9432456 iteration: 48585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.07956 FastRCNN total loss: 0.18222 L1 loss: 0.0000e+00 L2 loss: 0.58862 Learning rate: 0.002 Mask loss: 0.14455 RPN box loss: 0.03018 RPN score loss: 0.01197 RPN total loss: 0.04214 Total loss: 0.95754 timestamp: 1655045868.1685278 iteration: 48590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12388 FastRCNN class loss: 0.11135 FastRCNN total loss: 0.23524 L1 loss: 0.0000e+00 L2 loss: 0.58861 Learning rate: 0.002 Mask loss: 0.18394 RPN box loss: 0.01453 RPN score loss: 0.00391 RPN total loss: 0.01844 Total loss: 1.02623 timestamp: 1655045871.4379158 iteration: 48595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0731 FastRCNN class loss: 0.05715 FastRCNN total loss: 0.13025 L1 loss: 0.0000e+00 L2 loss: 0.5886 Learning rate: 0.002 Mask loss: 0.15489 RPN box loss: 0.00823 RPN score loss: 0.00164 RPN total loss: 0.00987 Total loss: 0.8836 timestamp: 1655045874.6880763 iteration: 48600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13302 FastRCNN class loss: 0.11644 FastRCNN total loss: 0.24946 L1 loss: 0.0000e+00 L2 loss: 0.58859 Learning rate: 0.002 Mask loss: 0.1894 RPN box loss: 0.02876 RPN score loss: 0.01332 RPN total loss: 0.04209 Total loss: 1.06953 timestamp: 1655045878.0074706 iteration: 48605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0772 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.16084 L1 loss: 0.0000e+00 L2 loss: 0.58858 Learning rate: 0.002 Mask loss: 0.14234 RPN box loss: 0.01131 RPN score loss: 0.00735 RPN total loss: 0.01866 Total loss: 0.91042 timestamp: 1655045881.2778225 iteration: 48610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08623 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.1423 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.002 Mask loss: 0.15758 RPN box loss: 0.01614 RPN score loss: 0.00602 RPN total loss: 0.02215 Total loss: 0.91061 timestamp: 1655045884.5906866 iteration: 48615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09593 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.15521 L1 loss: 0.0000e+00 L2 loss: 0.58857 Learning rate: 0.002 Mask loss: 0.14837 RPN box loss: 0.03305 RPN score loss: 0.0094 RPN total loss: 0.04245 Total loss: 0.9346 timestamp: 1655045887.894017 iteration: 48620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.04993 FastRCNN total loss: 0.1146 L1 loss: 0.0000e+00 L2 loss: 0.58856 Learning rate: 0.002 Mask loss: 0.10104 RPN box loss: 0.01744 RPN score loss: 0.00916 RPN total loss: 0.0266 Total loss: 0.83081 timestamp: 1655045891.1226933 iteration: 48625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08292 FastRCNN class loss: 0.05851 FastRCNN total loss: 0.14143 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.002 Mask loss: 0.17126 RPN box loss: 0.0073 RPN score loss: 0.00233 RPN total loss: 0.00963 Total loss: 0.91088 timestamp: 1655045894.4087944 iteration: 48630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09417 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.14244 L1 loss: 0.0000e+00 L2 loss: 0.58855 Learning rate: 0.002 Mask loss: 0.09818 RPN box loss: 0.01052 RPN score loss: 0.0015 RPN total loss: 0.01202 Total loss: 0.84118 timestamp: 1655045897.7234988 iteration: 48635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18772 FastRCNN class loss: 0.0978 FastRCNN total loss: 0.28552 L1 loss: 0.0000e+00 L2 loss: 0.58854 Learning rate: 0.002 Mask loss: 0.18202 RPN box loss: 0.03064 RPN score loss: 0.01528 RPN total loss: 0.04592 Total loss: 1.10199 timestamp: 1655045901.0029569 iteration: 48640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14463 FastRCNN class loss: 0.09259 FastRCNN total loss: 0.23723 L1 loss: 0.0000e+00 L2 loss: 0.58853 Learning rate: 0.002 Mask loss: 0.1367 RPN box loss: 0.00941 RPN score loss: 0.00569 RPN total loss: 0.01511 Total loss: 0.97756 timestamp: 1655045904.2323785 iteration: 48645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.14071 L1 loss: 0.0000e+00 L2 loss: 0.58852 Learning rate: 0.002 Mask loss: 0.12588 RPN box loss: 0.01908 RPN score loss: 0.00536 RPN total loss: 0.02445 Total loss: 0.87956 timestamp: 1655045907.4295723 iteration: 48650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12994 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.20959 L1 loss: 0.0000e+00 L2 loss: 0.58851 Learning rate: 0.002 Mask loss: 0.1302 RPN box loss: 0.01639 RPN score loss: 0.00495 RPN total loss: 0.02133 Total loss: 0.94963 timestamp: 1655045910.68661 iteration: 48655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11826 FastRCNN class loss: 0.10351 FastRCNN total loss: 0.22176 L1 loss: 0.0000e+00 L2 loss: 0.5885 Learning rate: 0.002 Mask loss: 0.17589 RPN box loss: 0.01827 RPN score loss: 0.00337 RPN total loss: 0.02164 Total loss: 1.0078 timestamp: 1655045913.9365706 iteration: 48660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17393 FastRCNN class loss: 0.12167 FastRCNN total loss: 0.2956 L1 loss: 0.0000e+00 L2 loss: 0.58849 Learning rate: 0.002 Mask loss: 0.19334 RPN box loss: 0.02564 RPN score loss: 0.00941 RPN total loss: 0.03505 Total loss: 1.11248 timestamp: 1655045917.1957881 iteration: 48665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.13868 L1 loss: 0.0000e+00 L2 loss: 0.58848 Learning rate: 0.002 Mask loss: 0.11138 RPN box loss: 0.00968 RPN score loss: 0.00474 RPN total loss: 0.01442 Total loss: 0.85295 timestamp: 1655045920.502888 iteration: 48670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14475 FastRCNN class loss: 0.11055 FastRCNN total loss: 0.25531 L1 loss: 0.0000e+00 L2 loss: 0.58847 Learning rate: 0.002 Mask loss: 0.18217 RPN box loss: 0.01111 RPN score loss: 0.00553 RPN total loss: 0.01664 Total loss: 1.04259 timestamp: 1655045923.7775145 iteration: 48675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09764 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.15159 L1 loss: 0.0000e+00 L2 loss: 0.58846 Learning rate: 0.002 Mask loss: 0.12448 RPN box loss: 0.012 RPN score loss: 0.01203 RPN total loss: 0.02403 Total loss: 0.88855 timestamp: 1655045927.0341454 iteration: 48680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.03569 FastRCNN total loss: 0.12589 L1 loss: 0.0000e+00 L2 loss: 0.58845 Learning rate: 0.002 Mask loss: 0.09462 RPN box loss: 0.01087 RPN score loss: 0.00065 RPN total loss: 0.01153 Total loss: 0.8205 timestamp: 1655045930.322008 iteration: 48685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1532 FastRCNN class loss: 0.12367 FastRCNN total loss: 0.27687 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.002 Mask loss: 0.14986 RPN box loss: 0.01576 RPN score loss: 0.00824 RPN total loss: 0.02401 Total loss: 1.03918 timestamp: 1655045933.5816963 iteration: 48690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08455 FastRCNN class loss: 0.07087 FastRCNN total loss: 0.15542 L1 loss: 0.0000e+00 L2 loss: 0.58844 Learning rate: 0.002 Mask loss: 0.14689 RPN box loss: 0.00722 RPN score loss: 0.00066 RPN total loss: 0.00789 Total loss: 0.89864 timestamp: 1655045936.830009 iteration: 48695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07976 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.13201 L1 loss: 0.0000e+00 L2 loss: 0.58843 Learning rate: 0.002 Mask loss: 0.13965 RPN box loss: 0.00913 RPN score loss: 0.00313 RPN total loss: 0.01226 Total loss: 0.87236 timestamp: 1655045940.1641226 iteration: 48700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11981 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.1907 L1 loss: 0.0000e+00 L2 loss: 0.58842 Learning rate: 0.002 Mask loss: 0.16547 RPN box loss: 0.00832 RPN score loss: 0.00489 RPN total loss: 0.01321 Total loss: 0.9578 timestamp: 1655045943.5319664 iteration: 48705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11197 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.18109 L1 loss: 0.0000e+00 L2 loss: 0.58841 Learning rate: 0.002 Mask loss: 0.13176 RPN box loss: 0.01356 RPN score loss: 0.00168 RPN total loss: 0.01525 Total loss: 0.91651 timestamp: 1655045946.74053 iteration: 48710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13137 FastRCNN class loss: 0.04475 FastRCNN total loss: 0.17612 L1 loss: 0.0000e+00 L2 loss: 0.5884 Learning rate: 0.002 Mask loss: 0.12812 RPN box loss: 0.00301 RPN score loss: 0.00422 RPN total loss: 0.00723 Total loss: 0.89986 timestamp: 1655045950.1129684 iteration: 48715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11483 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.19748 L1 loss: 0.0000e+00 L2 loss: 0.58839 Learning rate: 0.002 Mask loss: 0.14939 RPN box loss: 0.02192 RPN score loss: 0.01311 RPN total loss: 0.03503 Total loss: 0.97028 timestamp: 1655045953.385646 iteration: 48720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14337 FastRCNN class loss: 0.10054 FastRCNN total loss: 0.24391 L1 loss: 0.0000e+00 L2 loss: 0.58838 Learning rate: 0.002 Mask loss: 0.16803 RPN box loss: 0.02124 RPN score loss: 0.00957 RPN total loss: 0.03081 Total loss: 1.03114 timestamp: 1655045956.598932 iteration: 48725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05167 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.10546 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.002 Mask loss: 0.08582 RPN box loss: 0.00981 RPN score loss: 0.00264 RPN total loss: 0.01245 Total loss: 0.7921 timestamp: 1655045959.8288794 iteration: 48730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.185 FastRCNN class loss: 0.0962 FastRCNN total loss: 0.2812 L1 loss: 0.0000e+00 L2 loss: 0.58837 Learning rate: 0.002 Mask loss: 0.1226 RPN box loss: 0.02924 RPN score loss: 0.00503 RPN total loss: 0.03427 Total loss: 1.02643 timestamp: 1655045963.1599305 iteration: 48735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10304 FastRCNN class loss: 0.09427 FastRCNN total loss: 0.19731 L1 loss: 0.0000e+00 L2 loss: 0.58836 Learning rate: 0.002 Mask loss: 0.19192 RPN box loss: 0.02794 RPN score loss: 0.01591 RPN total loss: 0.04385 Total loss: 1.02144 timestamp: 1655045966.4461017 iteration: 48740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18434 FastRCNN class loss: 0.08945 FastRCNN total loss: 0.27379 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.002 Mask loss: 0.20818 RPN box loss: 0.03402 RPN score loss: 0.00581 RPN total loss: 0.03983 Total loss: 1.11016 timestamp: 1655045969.7089336 iteration: 48745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06564 FastRCNN class loss: 0.04055 FastRCNN total loss: 0.10618 L1 loss: 0.0000e+00 L2 loss: 0.58835 Learning rate: 0.002 Mask loss: 0.11603 RPN box loss: 0.00824 RPN score loss: 0.00127 RPN total loss: 0.00951 Total loss: 0.82008 timestamp: 1655045973.0469642 iteration: 48750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0646 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.13242 L1 loss: 0.0000e+00 L2 loss: 0.58834 Learning rate: 0.002 Mask loss: 0.16673 RPN box loss: 0.02268 RPN score loss: 0.01049 RPN total loss: 0.03317 Total loss: 0.92065 timestamp: 1655045976.3165169 iteration: 48755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10405 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.18597 L1 loss: 0.0000e+00 L2 loss: 0.58833 Learning rate: 0.002 Mask loss: 0.13037 RPN box loss: 0.0097 RPN score loss: 0.0025 RPN total loss: 0.0122 Total loss: 0.91687 timestamp: 1655045979.6199977 iteration: 48760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08356 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.13234 L1 loss: 0.0000e+00 L2 loss: 0.58832 Learning rate: 0.002 Mask loss: 0.13302 RPN box loss: 0.00682 RPN score loss: 0.00358 RPN total loss: 0.01041 Total loss: 0.86409 timestamp: 1655045982.9350462 iteration: 48765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12013 FastRCNN class loss: 0.11966 FastRCNN total loss: 0.23979 L1 loss: 0.0000e+00 L2 loss: 0.58831 Learning rate: 0.002 Mask loss: 0.16272 RPN box loss: 0.02056 RPN score loss: 0.00786 RPN total loss: 0.02842 Total loss: 1.01924 timestamp: 1655045986.2360084 iteration: 48770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06153 FastRCNN class loss: 0.04577 FastRCNN total loss: 0.1073 L1 loss: 0.0000e+00 L2 loss: 0.5883 Learning rate: 0.002 Mask loss: 0.10644 RPN box loss: 0.02301 RPN score loss: 0.00661 RPN total loss: 0.02962 Total loss: 0.83166 timestamp: 1655045989.510457 iteration: 48775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16814 FastRCNN class loss: 0.13088 FastRCNN total loss: 0.29902 L1 loss: 0.0000e+00 L2 loss: 0.58829 Learning rate: 0.002 Mask loss: 0.17838 RPN box loss: 0.04369 RPN score loss: 0.00947 RPN total loss: 0.05316 Total loss: 1.11885 timestamp: 1655045992.7494361 iteration: 48780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09181 FastRCNN class loss: 0.06727 FastRCNN total loss: 0.15908 L1 loss: 0.0000e+00 L2 loss: 0.58828 Learning rate: 0.002 Mask loss: 0.10231 RPN box loss: 0.01278 RPN score loss: 0.0019 RPN total loss: 0.01468 Total loss: 0.86435 timestamp: 1655045996.0808835 iteration: 48785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09915 FastRCNN class loss: 0.05194 FastRCNN total loss: 0.15109 L1 loss: 0.0000e+00 L2 loss: 0.58827 Learning rate: 0.002 Mask loss: 0.08019 RPN box loss: 0.02152 RPN score loss: 0.00565 RPN total loss: 0.02717 Total loss: 0.84672 timestamp: 1655045999.3703651 iteration: 48790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11093 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.19396 L1 loss: 0.0000e+00 L2 loss: 0.58826 Learning rate: 0.002 Mask loss: 0.17175 RPN box loss: 0.03552 RPN score loss: 0.0119 RPN total loss: 0.04742 Total loss: 1.0014 timestamp: 1655046002.558097 iteration: 48795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07617 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.13403 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.002 Mask loss: 0.15416 RPN box loss: 0.06973 RPN score loss: 0.00934 RPN total loss: 0.07907 Total loss: 0.9555 timestamp: 1655046005.7995784 iteration: 48800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1305 FastRCNN class loss: 0.05214 FastRCNN total loss: 0.18264 L1 loss: 0.0000e+00 L2 loss: 0.58825 Learning rate: 0.002 Mask loss: 0.11149 RPN box loss: 0.01775 RPN score loss: 0.00347 RPN total loss: 0.02122 Total loss: 0.9036 timestamp: 1655046009.0337923 iteration: 48805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10874 FastRCNN class loss: 0.06617 FastRCNN total loss: 0.17491 L1 loss: 0.0000e+00 L2 loss: 0.58824 Learning rate: 0.002 Mask loss: 0.14476 RPN box loss: 0.01615 RPN score loss: 0.00322 RPN total loss: 0.01937 Total loss: 0.92727 timestamp: 1655046012.2419426 iteration: 48810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06679 FastRCNN class loss: 0.04977 FastRCNN total loss: 0.11656 L1 loss: 0.0000e+00 L2 loss: 0.58823 Learning rate: 0.002 Mask loss: 0.16844 RPN box loss: 0.00675 RPN score loss: 0.0036 RPN total loss: 0.01035 Total loss: 0.88357 timestamp: 1655046015.5621963 iteration: 48815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.18281 L1 loss: 0.0000e+00 L2 loss: 0.58822 Learning rate: 0.002 Mask loss: 0.18001 RPN box loss: 0.01954 RPN score loss: 0.0166 RPN total loss: 0.03615 Total loss: 0.98719 timestamp: 1655046018.8072298 iteration: 48820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11772 FastRCNN class loss: 0.12454 FastRCNN total loss: 0.24226 L1 loss: 0.0000e+00 L2 loss: 0.58821 Learning rate: 0.002 Mask loss: 0.22788 RPN box loss: 0.01906 RPN score loss: 0.04028 RPN total loss: 0.05935 Total loss: 1.1177 timestamp: 1655046022.0916688 iteration: 48825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11462 FastRCNN class loss: 0.08919 FastRCNN total loss: 0.20381 L1 loss: 0.0000e+00 L2 loss: 0.5882 Learning rate: 0.002 Mask loss: 0.15168 RPN box loss: 0.00345 RPN score loss: 0.00114 RPN total loss: 0.00459 Total loss: 0.94828 timestamp: 1655046025.3003175 iteration: 48830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.13497 L1 loss: 0.0000e+00 L2 loss: 0.58819 Learning rate: 0.002 Mask loss: 0.15079 RPN box loss: 0.01056 RPN score loss: 0.00145 RPN total loss: 0.012 Total loss: 0.88595 timestamp: 1655046028.5648856 iteration: 48835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07912 FastRCNN class loss: 0.06328 FastRCNN total loss: 0.1424 L1 loss: 0.0000e+00 L2 loss: 0.58818 Learning rate: 0.002 Mask loss: 0.15229 RPN box loss: 0.02457 RPN score loss: 0.00607 RPN total loss: 0.03064 Total loss: 0.91352 timestamp: 1655046031.8658543 iteration: 48840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1296 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.19905 L1 loss: 0.0000e+00 L2 loss: 0.58817 Learning rate: 0.002 Mask loss: 0.14052 RPN box loss: 0.02049 RPN score loss: 0.00614 RPN total loss: 0.02663 Total loss: 0.95437 timestamp: 1655046035.1441002 iteration: 48845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06675 FastRCNN class loss: 0.06729 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.58816 Learning rate: 0.002 Mask loss: 0.15358 RPN box loss: 0.03732 RPN score loss: 0.00503 RPN total loss: 0.04235 Total loss: 0.91813 timestamp: 1655046038.4860756 iteration: 48850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11543 FastRCNN class loss: 0.049 FastRCNN total loss: 0.16443 L1 loss: 0.0000e+00 L2 loss: 0.58815 Learning rate: 0.002 Mask loss: 0.09695 RPN box loss: 0.06251 RPN score loss: 0.00493 RPN total loss: 0.06744 Total loss: 0.91697 timestamp: 1655046041.7531872 iteration: 48855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18398 FastRCNN class loss: 0.08747 FastRCNN total loss: 0.27144 L1 loss: 0.0000e+00 L2 loss: 0.58814 Learning rate: 0.002 Mask loss: 0.15158 RPN box loss: 0.02189 RPN score loss: 0.01264 RPN total loss: 0.03453 Total loss: 1.04569 timestamp: 1655046045.0246522 iteration: 48860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11576 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.18142 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.002 Mask loss: 0.16208 RPN box loss: 0.01362 RPN score loss: 0.00337 RPN total loss: 0.01699 Total loss: 0.94862 timestamp: 1655046048.317511 iteration: 48865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13724 FastRCNN class loss: 0.05017 FastRCNN total loss: 0.18741 L1 loss: 0.0000e+00 L2 loss: 0.58813 Learning rate: 0.002 Mask loss: 0.1462 RPN box loss: 0.02765 RPN score loss: 0.00502 RPN total loss: 0.03268 Total loss: 0.95441 timestamp: 1655046051.582977 iteration: 48870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10181 FastRCNN class loss: 0.11783 FastRCNN total loss: 0.21964 L1 loss: 0.0000e+00 L2 loss: 0.58812 Learning rate: 0.002 Mask loss: 0.17926 RPN box loss: 0.02586 RPN score loss: 0.00586 RPN total loss: 0.03172 Total loss: 1.01874 timestamp: 1655046054.834482 iteration: 48875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07355 FastRCNN class loss: 0.06228 FastRCNN total loss: 0.13584 L1 loss: 0.0000e+00 L2 loss: 0.58811 Learning rate: 0.002 Mask loss: 0.1042 RPN box loss: 0.02797 RPN score loss: 0.00185 RPN total loss: 0.02982 Total loss: 0.85796 timestamp: 1655046058.0945065 iteration: 48880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.12668 FastRCNN total loss: 0.21681 L1 loss: 0.0000e+00 L2 loss: 0.5881 Learning rate: 0.002 Mask loss: 0.1705 RPN box loss: 0.02742 RPN score loss: 0.02071 RPN total loss: 0.04813 Total loss: 1.02354 timestamp: 1655046061.4051728 iteration: 48885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11169 FastRCNN class loss: 0.05854 FastRCNN total loss: 0.17024 L1 loss: 0.0000e+00 L2 loss: 0.58809 Learning rate: 0.002 Mask loss: 0.11796 RPN box loss: 0.01669 RPN score loss: 0.0065 RPN total loss: 0.0232 Total loss: 0.89948 timestamp: 1655046064.6850736 iteration: 48890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07704 FastRCNN class loss: 0.06369 FastRCNN total loss: 0.14073 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.002 Mask loss: 0.15203 RPN box loss: 0.0121 RPN score loss: 0.00452 RPN total loss: 0.01662 Total loss: 0.89747 timestamp: 1655046067.944606 iteration: 48895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.125 FastRCNN class loss: 0.05841 FastRCNN total loss: 0.18341 L1 loss: 0.0000e+00 L2 loss: 0.58808 Learning rate: 0.002 Mask loss: 0.13596 RPN box loss: 0.06019 RPN score loss: 0.00896 RPN total loss: 0.06915 Total loss: 0.97659 timestamp: 1655046071.2245977 iteration: 48900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05398 FastRCNN class loss: 0.06519 FastRCNN total loss: 0.11917 L1 loss: 0.0000e+00 L2 loss: 0.58807 Learning rate: 0.002 Mask loss: 0.10289 RPN box loss: 0.00698 RPN score loss: 0.00633 RPN total loss: 0.01332 Total loss: 0.82344 timestamp: 1655046074.524482 iteration: 48905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12264 FastRCNN class loss: 0.10658 FastRCNN total loss: 0.22922 L1 loss: 0.0000e+00 L2 loss: 0.58806 Learning rate: 0.002 Mask loss: 0.15373 RPN box loss: 0.02091 RPN score loss: 0.00592 RPN total loss: 0.02683 Total loss: 0.99783 timestamp: 1655046077.7721853 iteration: 48910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13501 FastRCNN class loss: 0.12526 FastRCNN total loss: 0.26027 L1 loss: 0.0000e+00 L2 loss: 0.58805 Learning rate: 0.002 Mask loss: 0.18479 RPN box loss: 0.04524 RPN score loss: 0.02151 RPN total loss: 0.06675 Total loss: 1.09986 timestamp: 1655046081.0095806 iteration: 48915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16747 FastRCNN class loss: 0.07304 FastRCNN total loss: 0.24051 L1 loss: 0.0000e+00 L2 loss: 0.58804 Learning rate: 0.002 Mask loss: 0.1687 RPN box loss: 0.01715 RPN score loss: 0.00644 RPN total loss: 0.02359 Total loss: 1.02085 timestamp: 1655046084.217905 iteration: 48920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12766 FastRCNN class loss: 0.11163 FastRCNN total loss: 0.23929 L1 loss: 0.0000e+00 L2 loss: 0.58803 Learning rate: 0.002 Mask loss: 0.15603 RPN box loss: 0.01579 RPN score loss: 0.00469 RPN total loss: 0.02049 Total loss: 1.00384 timestamp: 1655046087.506995 iteration: 48925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05022 FastRCNN class loss: 0.04142 FastRCNN total loss: 0.09164 L1 loss: 0.0000e+00 L2 loss: 0.58802 Learning rate: 0.002 Mask loss: 0.10197 RPN box loss: 0.00236 RPN score loss: 0.00332 RPN total loss: 0.00568 Total loss: 0.78731 timestamp: 1655046090.7205808 iteration: 48930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.17162 L1 loss: 0.0000e+00 L2 loss: 0.58801 Learning rate: 0.002 Mask loss: 0.10234 RPN box loss: 0.01681 RPN score loss: 0.00274 RPN total loss: 0.01955 Total loss: 0.88152 timestamp: 1655046094.0019956 iteration: 48935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12918 FastRCNN class loss: 0.107 FastRCNN total loss: 0.23618 L1 loss: 0.0000e+00 L2 loss: 0.588 Learning rate: 0.002 Mask loss: 0.22286 RPN box loss: 0.02699 RPN score loss: 0.01705 RPN total loss: 0.04404 Total loss: 1.09108 timestamp: 1655046097.2247422 iteration: 48940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08574 FastRCNN class loss: 0.11733 FastRCNN total loss: 0.20307 L1 loss: 0.0000e+00 L2 loss: 0.58799 Learning rate: 0.002 Mask loss: 0.1456 RPN box loss: 0.02037 RPN score loss: 0.00412 RPN total loss: 0.0245 Total loss: 0.96117 timestamp: 1655046100.5153666 iteration: 48945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14876 FastRCNN class loss: 0.10511 FastRCNN total loss: 0.25386 L1 loss: 0.0000e+00 L2 loss: 0.58798 Learning rate: 0.002 Mask loss: 0.26881 RPN box loss: 0.01089 RPN score loss: 0.0023 RPN total loss: 0.01319 Total loss: 1.12384 timestamp: 1655046103.758885 iteration: 48950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.10222 FastRCNN total loss: 0.21964 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.002 Mask loss: 0.12735 RPN box loss: 0.01704 RPN score loss: 0.0108 RPN total loss: 0.02784 Total loss: 0.96281 timestamp: 1655046107.0625286 iteration: 48955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10884 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.18301 L1 loss: 0.0000e+00 L2 loss: 0.58797 Learning rate: 0.002 Mask loss: 0.13581 RPN box loss: 0.0168 RPN score loss: 0.00883 RPN total loss: 0.02563 Total loss: 0.93242 timestamp: 1655046110.4047809 iteration: 48960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1294 FastRCNN class loss: 0.09348 FastRCNN total loss: 0.22288 L1 loss: 0.0000e+00 L2 loss: 0.58796 Learning rate: 0.002 Mask loss: 0.15875 RPN box loss: 0.0149 RPN score loss: 0.0043 RPN total loss: 0.0192 Total loss: 0.98879 timestamp: 1655046113.6408257 iteration: 48965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13555 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.19686 L1 loss: 0.0000e+00 L2 loss: 0.58795 Learning rate: 0.002 Mask loss: 0.16668 RPN box loss: 0.02138 RPN score loss: 0.00497 RPN total loss: 0.02635 Total loss: 0.97785 timestamp: 1655046116.832801 iteration: 48970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.18729 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.002 Mask loss: 0.13992 RPN box loss: 0.01725 RPN score loss: 0.00254 RPN total loss: 0.01979 Total loss: 0.93494 timestamp: 1655046120.156119 iteration: 48975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.09771 FastRCNN total loss: 0.21268 L1 loss: 0.0000e+00 L2 loss: 0.58794 Learning rate: 0.002 Mask loss: 0.159 RPN box loss: 0.01405 RPN score loss: 0.00202 RPN total loss: 0.01608 Total loss: 0.9757 timestamp: 1655046123.5061595 iteration: 48980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11297 FastRCNN class loss: 0.05494 FastRCNN total loss: 0.16791 L1 loss: 0.0000e+00 L2 loss: 0.58793 Learning rate: 0.002 Mask loss: 0.09364 RPN box loss: 0.00754 RPN score loss: 0.00391 RPN total loss: 0.01145 Total loss: 0.86092 timestamp: 1655046126.7578778 iteration: 48985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14964 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.21162 L1 loss: 0.0000e+00 L2 loss: 0.58792 Learning rate: 0.002 Mask loss: 0.10614 RPN box loss: 0.02258 RPN score loss: 0.00298 RPN total loss: 0.02556 Total loss: 0.93124 timestamp: 1655046130.0087101 iteration: 48990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.17073 L1 loss: 0.0000e+00 L2 loss: 0.58791 Learning rate: 0.002 Mask loss: 0.12299 RPN box loss: 0.02837 RPN score loss: 0.01055 RPN total loss: 0.03892 Total loss: 0.92055 timestamp: 1655046133.2752528 iteration: 48995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06842 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.12667 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.002 Mask loss: 0.12014 RPN box loss: 0.03215 RPN score loss: 0.01265 RPN total loss: 0.0448 Total loss: 0.87951 timestamp: 1655046136.5015476 iteration: 49000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10933 FastRCNN class loss: 0.03007 FastRCNN total loss: 0.1394 L1 loss: 0.0000e+00 L2 loss: 0.5879 Learning rate: 0.002 Mask loss: 0.11081 RPN box loss: 0.03102 RPN score loss: 0.0022 RPN total loss: 0.03321 Total loss: 0.87132 timestamp: 1655046139.7636461 iteration: 49005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15693 FastRCNN class loss: 0.09184 FastRCNN total loss: 0.24876 L1 loss: 0.0000e+00 L2 loss: 0.58789 Learning rate: 0.002 Mask loss: 0.16585 RPN box loss: 0.01215 RPN score loss: 0.00356 RPN total loss: 0.01572 Total loss: 1.01822 timestamp: 1655046143.0266895 iteration: 49010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16951 FastRCNN class loss: 0.09661 FastRCNN total loss: 0.26612 L1 loss: 0.0000e+00 L2 loss: 0.58788 Learning rate: 0.002 Mask loss: 0.11641 RPN box loss: 0.0094 RPN score loss: 0.0054 RPN total loss: 0.0148 Total loss: 0.98521 timestamp: 1655046146.2992778 iteration: 49015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08093 FastRCNN class loss: 0.08503 FastRCNN total loss: 0.16596 L1 loss: 0.0000e+00 L2 loss: 0.58787 Learning rate: 0.002 Mask loss: 0.19261 RPN box loss: 0.0168 RPN score loss: 0.00364 RPN total loss: 0.02044 Total loss: 0.96688 timestamp: 1655046149.5219152 iteration: 49020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07168 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.12792 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.002 Mask loss: 0.14282 RPN box loss: 0.0254 RPN score loss: 0.00602 RPN total loss: 0.03142 Total loss: 0.89002 timestamp: 1655046152.8142195 iteration: 49025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08528 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.16553 L1 loss: 0.0000e+00 L2 loss: 0.58786 Learning rate: 0.002 Mask loss: 0.14867 RPN box loss: 0.01802 RPN score loss: 0.00947 RPN total loss: 0.0275 Total loss: 0.92955 timestamp: 1655046156.0840664 iteration: 49030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04368 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.08562 L1 loss: 0.0000e+00 L2 loss: 0.58785 Learning rate: 0.002 Mask loss: 0.11327 RPN box loss: 0.01172 RPN score loss: 0.0039 RPN total loss: 0.01562 Total loss: 0.80236 timestamp: 1655046159.306098 iteration: 49035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17234 FastRCNN class loss: 0.14135 FastRCNN total loss: 0.31369 L1 loss: 0.0000e+00 L2 loss: 0.58784 Learning rate: 0.002 Mask loss: 0.23413 RPN box loss: 0.02433 RPN score loss: 0.00744 RPN total loss: 0.03176 Total loss: 1.16742 timestamp: 1655046162.5101159 iteration: 49040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16044 FastRCNN class loss: 0.14926 FastRCNN total loss: 0.3097 L1 loss: 0.0000e+00 L2 loss: 0.58783 Learning rate: 0.002 Mask loss: 0.17086 RPN box loss: 0.02234 RPN score loss: 0.00582 RPN total loss: 0.02816 Total loss: 1.09655 timestamp: 1655046165.7719262 iteration: 49045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15624 FastRCNN class loss: 0.08495 FastRCNN total loss: 0.24119 L1 loss: 0.0000e+00 L2 loss: 0.58782 Learning rate: 0.002 Mask loss: 0.16053 RPN box loss: 0.03011 RPN score loss: 0.00974 RPN total loss: 0.03986 Total loss: 1.02941 timestamp: 1655046169.0103252 iteration: 49050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10611 FastRCNN class loss: 0.09808 FastRCNN total loss: 0.20419 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.002 Mask loss: 0.1994 RPN box loss: 0.02344 RPN score loss: 0.00589 RPN total loss: 0.02933 Total loss: 1.02073 timestamp: 1655046172.2448583 iteration: 49055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.09166 FastRCNN total loss: 0.18012 L1 loss: 0.0000e+00 L2 loss: 0.58781 Learning rate: 0.002 Mask loss: 0.16029 RPN box loss: 0.00936 RPN score loss: 0.00188 RPN total loss: 0.01124 Total loss: 0.93945 timestamp: 1655046175.4804523 iteration: 49060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16425 FastRCNN class loss: 0.12312 FastRCNN total loss: 0.28737 L1 loss: 0.0000e+00 L2 loss: 0.58779 Learning rate: 0.002 Mask loss: 0.12699 RPN box loss: 0.03152 RPN score loss: 0.00771 RPN total loss: 0.03923 Total loss: 1.04138 timestamp: 1655046178.74396 iteration: 49065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11623 FastRCNN class loss: 0.05747 FastRCNN total loss: 0.1737 L1 loss: 0.0000e+00 L2 loss: 0.58778 Learning rate: 0.002 Mask loss: 0.1173 RPN box loss: 0.03446 RPN score loss: 0.00564 RPN total loss: 0.04011 Total loss: 0.91889 timestamp: 1655046181.9944136 iteration: 49070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07496 FastRCNN class loss: 0.07204 FastRCNN total loss: 0.147 L1 loss: 0.0000e+00 L2 loss: 0.58777 Learning rate: 0.002 Mask loss: 0.11336 RPN box loss: 0.01036 RPN score loss: 0.00052 RPN total loss: 0.01088 Total loss: 0.85901 timestamp: 1655046185.2536566 iteration: 49075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12407 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.19929 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.002 Mask loss: 0.15134 RPN box loss: 0.01418 RPN score loss: 0.00936 RPN total loss: 0.02354 Total loss: 0.96193 timestamp: 1655046188.5293756 iteration: 49080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08294 FastRCNN class loss: 0.05966 FastRCNN total loss: 0.1426 L1 loss: 0.0000e+00 L2 loss: 0.58776 Learning rate: 0.002 Mask loss: 0.11524 RPN box loss: 0.0101 RPN score loss: 0.01141 RPN total loss: 0.02151 Total loss: 0.86711 timestamp: 1655046191.7750483 iteration: 49085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13847 FastRCNN class loss: 0.04535 FastRCNN total loss: 0.18382 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.002 Mask loss: 0.16327 RPN box loss: 0.0959 RPN score loss: 0.00554 RPN total loss: 0.10144 Total loss: 1.03627 timestamp: 1655046195.040965 iteration: 49090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06381 FastRCNN class loss: 0.03872 FastRCNN total loss: 0.10253 L1 loss: 0.0000e+00 L2 loss: 0.58775 Learning rate: 0.002 Mask loss: 0.14039 RPN box loss: 0.02535 RPN score loss: 0.00259 RPN total loss: 0.02794 Total loss: 0.85861 timestamp: 1655046198.3347416 iteration: 49095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09421 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.16202 L1 loss: 0.0000e+00 L2 loss: 0.58774 Learning rate: 0.002 Mask loss: 0.0839 RPN box loss: 0.00795 RPN score loss: 0.00359 RPN total loss: 0.01154 Total loss: 0.84521 timestamp: 1655046201.5817616 iteration: 49100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05595 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.10975 L1 loss: 0.0000e+00 L2 loss: 0.58773 Learning rate: 0.002 Mask loss: 0.10161 RPN box loss: 0.01026 RPN score loss: 0.00327 RPN total loss: 0.01354 Total loss: 0.81263 timestamp: 1655046204.841789 iteration: 49105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14113 FastRCNN class loss: 0.07849 FastRCNN total loss: 0.21962 L1 loss: 0.0000e+00 L2 loss: 0.58772 Learning rate: 0.002 Mask loss: 0.15619 RPN box loss: 0.06086 RPN score loss: 0.0064 RPN total loss: 0.06726 Total loss: 1.03079 timestamp: 1655046208.0643685 iteration: 49110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.074 FastRCNN class loss: 0.12717 FastRCNN total loss: 0.20117 L1 loss: 0.0000e+00 L2 loss: 0.58771 Learning rate: 0.002 Mask loss: 0.14686 RPN box loss: 0.04235 RPN score loss: 0.00937 RPN total loss: 0.05172 Total loss: 0.98746 timestamp: 1655046211.2875638 iteration: 49115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13662 FastRCNN class loss: 0.08847 FastRCNN total loss: 0.22509 L1 loss: 0.0000e+00 L2 loss: 0.5877 Learning rate: 0.002 Mask loss: 0.12294 RPN box loss: 0.01428 RPN score loss: 0.00308 RPN total loss: 0.01736 Total loss: 0.95309 timestamp: 1655046214.636249 iteration: 49120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.15441 L1 loss: 0.0000e+00 L2 loss: 0.58769 Learning rate: 0.002 Mask loss: 0.12711 RPN box loss: 0.00729 RPN score loss: 0.0022 RPN total loss: 0.00949 Total loss: 0.8787 timestamp: 1655046217.8560805 iteration: 49125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.098 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.14581 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.002 Mask loss: 0.12991 RPN box loss: 0.01286 RPN score loss: 0.00875 RPN total loss: 0.02162 Total loss: 0.88503 timestamp: 1655046221.081402 iteration: 49130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10783 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.20488 L1 loss: 0.0000e+00 L2 loss: 0.58768 Learning rate: 0.002 Mask loss: 0.19529 RPN box loss: 0.01106 RPN score loss: 0.00836 RPN total loss: 0.01942 Total loss: 1.00726 timestamp: 1655046224.2972004 iteration: 49135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10763 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.18554 L1 loss: 0.0000e+00 L2 loss: 0.58767 Learning rate: 0.002 Mask loss: 0.15025 RPN box loss: 0.0587 RPN score loss: 0.01131 RPN total loss: 0.07001 Total loss: 0.99347 timestamp: 1655046227.591905 iteration: 49140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12918 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.20919 L1 loss: 0.0000e+00 L2 loss: 0.58766 Learning rate: 0.002 Mask loss: 0.122 RPN box loss: 0.01352 RPN score loss: 0.00477 RPN total loss: 0.01828 Total loss: 0.93713 timestamp: 1655046230.861186 iteration: 49145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12009 FastRCNN class loss: 0.07579 FastRCNN total loss: 0.19587 L1 loss: 0.0000e+00 L2 loss: 0.58765 Learning rate: 0.002 Mask loss: 0.20279 RPN box loss: 0.02274 RPN score loss: 0.00488 RPN total loss: 0.02762 Total loss: 1.01394 timestamp: 1655046233.9965484 iteration: 49150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11413 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.18619 L1 loss: 0.0000e+00 L2 loss: 0.58764 Learning rate: 0.002 Mask loss: 0.22312 RPN box loss: 0.01022 RPN score loss: 0.00877 RPN total loss: 0.01899 Total loss: 1.01594 timestamp: 1655046237.2689326 iteration: 49155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09983 FastRCNN class loss: 0.05947 FastRCNN total loss: 0.1593 L1 loss: 0.0000e+00 L2 loss: 0.58763 Learning rate: 0.002 Mask loss: 0.13068 RPN box loss: 0.0089 RPN score loss: 0.00223 RPN total loss: 0.01113 Total loss: 0.88875 timestamp: 1655046240.5066867 iteration: 49160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0864 FastRCNN class loss: 0.06297 FastRCNN total loss: 0.14937 L1 loss: 0.0000e+00 L2 loss: 0.58762 Learning rate: 0.002 Mask loss: 0.16163 RPN box loss: 0.00726 RPN score loss: 0.00279 RPN total loss: 0.01005 Total loss: 0.90867 timestamp: 1655046243.8186176 iteration: 49165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11811 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.18084 L1 loss: 0.0000e+00 L2 loss: 0.58761 Learning rate: 0.002 Mask loss: 0.14683 RPN box loss: 0.03367 RPN score loss: 0.01929 RPN total loss: 0.05296 Total loss: 0.96824 timestamp: 1655046247.0754766 iteration: 49170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.05176 FastRCNN total loss: 0.13495 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.002 Mask loss: 0.07101 RPN box loss: 0.00671 RPN score loss: 0.00226 RPN total loss: 0.00896 Total loss: 0.80253 timestamp: 1655046250.3558571 iteration: 49175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.05076 FastRCNN total loss: 0.12163 L1 loss: 0.0000e+00 L2 loss: 0.5876 Learning rate: 0.002 Mask loss: 0.08339 RPN box loss: 0.01341 RPN score loss: 0.00602 RPN total loss: 0.01944 Total loss: 0.81206 timestamp: 1655046253.6220806 iteration: 49180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.07383 FastRCNN total loss: 0.14932 L1 loss: 0.0000e+00 L2 loss: 0.58759 Learning rate: 0.002 Mask loss: 0.0959 RPN box loss: 0.01383 RPN score loss: 0.00154 RPN total loss: 0.01537 Total loss: 0.84818 timestamp: 1655046256.8827791 iteration: 49185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10781 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.17356 L1 loss: 0.0000e+00 L2 loss: 0.58758 Learning rate: 0.002 Mask loss: 0.16681 RPN box loss: 0.02776 RPN score loss: 0.01193 RPN total loss: 0.03968 Total loss: 0.96763 timestamp: 1655046260.1511397 iteration: 49190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08169 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.16227 L1 loss: 0.0000e+00 L2 loss: 0.58757 Learning rate: 0.002 Mask loss: 0.16239 RPN box loss: 0.00663 RPN score loss: 0.00288 RPN total loss: 0.00951 Total loss: 0.92174 timestamp: 1655046263.4066942 iteration: 49195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09958 FastRCNN class loss: 0.0743 FastRCNN total loss: 0.17388 L1 loss: 0.0000e+00 L2 loss: 0.58756 Learning rate: 0.002 Mask loss: 0.16304 RPN box loss: 0.01629 RPN score loss: 0.00267 RPN total loss: 0.01896 Total loss: 0.94344 timestamp: 1655046266.6626523 iteration: 49200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14304 FastRCNN class loss: 0.16486 FastRCNN total loss: 0.30789 L1 loss: 0.0000e+00 L2 loss: 0.58755 Learning rate: 0.002 Mask loss: 0.11994 RPN box loss: 0.02338 RPN score loss: 0.00701 RPN total loss: 0.03038 Total loss: 1.04577 timestamp: 1655046269.8670156 iteration: 49205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13249 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.19227 L1 loss: 0.0000e+00 L2 loss: 0.58754 Learning rate: 0.002 Mask loss: 0.14068 RPN box loss: 0.01392 RPN score loss: 0.00313 RPN total loss: 0.01706 Total loss: 0.93755 timestamp: 1655046273.1201746 iteration: 49210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05703 FastRCNN class loss: 0.03608 FastRCNN total loss: 0.09311 L1 loss: 0.0000e+00 L2 loss: 0.58753 Learning rate: 0.002 Mask loss: 0.08231 RPN box loss: 0.00855 RPN score loss: 0.00515 RPN total loss: 0.0137 Total loss: 0.77665 timestamp: 1655046276.4124331 iteration: 49215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10555 FastRCNN class loss: 0.07318 FastRCNN total loss: 0.17873 L1 loss: 0.0000e+00 L2 loss: 0.58752 Learning rate: 0.002 Mask loss: 0.09891 RPN box loss: 0.00941 RPN score loss: 0.00331 RPN total loss: 0.01273 Total loss: 0.87788 timestamp: 1655046279.6625671 iteration: 49220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16606 FastRCNN class loss: 0.06136 FastRCNN total loss: 0.22742 L1 loss: 0.0000e+00 L2 loss: 0.58751 Learning rate: 0.002 Mask loss: 0.1443 RPN box loss: 0.01916 RPN score loss: 0.0052 RPN total loss: 0.02437 Total loss: 0.9836 timestamp: 1655046282.8828146 iteration: 49225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07324 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.13544 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 0.002 Mask loss: 0.14915 RPN box loss: 0.01031 RPN score loss: 0.00543 RPN total loss: 0.01575 Total loss: 0.88784 timestamp: 1655046286.1253095 iteration: 49230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09358 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.16043 L1 loss: 0.0000e+00 L2 loss: 0.5875 Learning rate: 0.002 Mask loss: 0.11491 RPN box loss: 0.02413 RPN score loss: 0.01235 RPN total loss: 0.03647 Total loss: 0.89931 timestamp: 1655046289.4196236 iteration: 49235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07978 FastRCNN class loss: 0.04275 FastRCNN total loss: 0.12253 L1 loss: 0.0000e+00 L2 loss: 0.58749 Learning rate: 0.002 Mask loss: 0.12722 RPN box loss: 0.00505 RPN score loss: 0.00567 RPN total loss: 0.01072 Total loss: 0.84797 timestamp: 1655046292.6407828 iteration: 49240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.15756 FastRCNN total loss: 0.26122 L1 loss: 0.0000e+00 L2 loss: 0.58748 Learning rate: 0.002 Mask loss: 0.2349 RPN box loss: 0.02174 RPN score loss: 0.03144 RPN total loss: 0.05318 Total loss: 1.13678 timestamp: 1655046295.940456 iteration: 49245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10532 FastRCNN class loss: 0.08547 FastRCNN total loss: 0.19079 L1 loss: 0.0000e+00 L2 loss: 0.58747 Learning rate: 0.002 Mask loss: 0.15066 RPN box loss: 0.01834 RPN score loss: 0.01336 RPN total loss: 0.0317 Total loss: 0.96061 timestamp: 1655046299.2842307 iteration: 49250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11741 FastRCNN class loss: 0.09884 FastRCNN total loss: 0.21625 L1 loss: 0.0000e+00 L2 loss: 0.58746 Learning rate: 0.002 Mask loss: 0.1374 RPN box loss: 0.02084 RPN score loss: 0.00882 RPN total loss: 0.02966 Total loss: 0.97077 timestamp: 1655046302.543767 iteration: 49255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09468 FastRCNN class loss: 0.05443 FastRCNN total loss: 0.1491 L1 loss: 0.0000e+00 L2 loss: 0.58745 Learning rate: 0.002 Mask loss: 0.18573 RPN box loss: 0.01426 RPN score loss: 0.00703 RPN total loss: 0.02129 Total loss: 0.94357 timestamp: 1655046305.7613635 iteration: 49260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12838 FastRCNN class loss: 0.10185 FastRCNN total loss: 0.23023 L1 loss: 0.0000e+00 L2 loss: 0.58744 Learning rate: 0.002 Mask loss: 0.18115 RPN box loss: 0.01692 RPN score loss: 0.01143 RPN total loss: 0.02835 Total loss: 1.02717 timestamp: 1655046308.9868217 iteration: 49265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08546 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.16274 L1 loss: 0.0000e+00 L2 loss: 0.58743 Learning rate: 0.002 Mask loss: 0.1774 RPN box loss: 0.02377 RPN score loss: 0.01358 RPN total loss: 0.03735 Total loss: 0.96492 timestamp: 1655046312.273897 iteration: 49270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07411 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.58742 Learning rate: 0.002 Mask loss: 0.14851 RPN box loss: 0.02518 RPN score loss: 0.00326 RPN total loss: 0.02844 Total loss: 0.91516 timestamp: 1655046315.5586865 iteration: 49275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08894 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.16205 L1 loss: 0.0000e+00 L2 loss: 0.58741 Learning rate: 0.002 Mask loss: 0.10226 RPN box loss: 0.01627 RPN score loss: 0.00214 RPN total loss: 0.01841 Total loss: 0.87012 timestamp: 1655046318.7689958 iteration: 49280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07815 FastRCNN class loss: 0.04744 FastRCNN total loss: 0.12559 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 0.002 Mask loss: 0.10957 RPN box loss: 0.0263 RPN score loss: 0.00136 RPN total loss: 0.02766 Total loss: 0.85022 timestamp: 1655046322.0492873 iteration: 49285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12778 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.20324 L1 loss: 0.0000e+00 L2 loss: 0.5874 Learning rate: 0.002 Mask loss: 0.12729 RPN box loss: 0.01582 RPN score loss: 0.00839 RPN total loss: 0.02421 Total loss: 0.94213 timestamp: 1655046325.2585971 iteration: 49290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12577 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.2024 L1 loss: 0.0000e+00 L2 loss: 0.58739 Learning rate: 0.002 Mask loss: 0.11677 RPN box loss: 0.00418 RPN score loss: 0.00143 RPN total loss: 0.00561 Total loss: 0.91217 timestamp: 1655046328.6100032 iteration: 49295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08764 FastRCNN class loss: 0.05836 FastRCNN total loss: 0.146 L1 loss: 0.0000e+00 L2 loss: 0.58738 Learning rate: 0.002 Mask loss: 0.10874 RPN box loss: 0.01153 RPN score loss: 0.00956 RPN total loss: 0.02109 Total loss: 0.86321 timestamp: 1655046331.8797855 iteration: 49300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07992 FastRCNN class loss: 0.1125 FastRCNN total loss: 0.19241 L1 loss: 0.0000e+00 L2 loss: 0.58737 Learning rate: 0.002 Mask loss: 0.14818 RPN box loss: 0.04375 RPN score loss: 0.0076 RPN total loss: 0.05135 Total loss: 0.97931 timestamp: 1655046335.1095357 iteration: 49305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10446 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.19415 L1 loss: 0.0000e+00 L2 loss: 0.58736 Learning rate: 0.002 Mask loss: 0.14538 RPN box loss: 0.01572 RPN score loss: 0.00338 RPN total loss: 0.01911 Total loss: 0.946 timestamp: 1655046338.3924584 iteration: 49310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06931 FastRCNN class loss: 0.05236 FastRCNN total loss: 0.12167 L1 loss: 0.0000e+00 L2 loss: 0.58735 Learning rate: 0.002 Mask loss: 0.11228 RPN box loss: 0.01342 RPN score loss: 0.00626 RPN total loss: 0.01968 Total loss: 0.84099 timestamp: 1655046341.635371 iteration: 49315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13382 FastRCNN class loss: 0.11115 FastRCNN total loss: 0.24498 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 0.002 Mask loss: 0.17648 RPN box loss: 0.04018 RPN score loss: 0.0116 RPN total loss: 0.05178 Total loss: 1.06059 timestamp: 1655046344.9118228 iteration: 49320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11294 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.58734 Learning rate: 0.002 Mask loss: 0.14539 RPN box loss: 0.00447 RPN score loss: 0.00173 RPN total loss: 0.0062 Total loss: 0.90994 timestamp: 1655046348.1268003 iteration: 49325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07004 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.12639 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 0.002 Mask loss: 0.20639 RPN box loss: 0.01196 RPN score loss: 0.00601 RPN total loss: 0.01797 Total loss: 0.93808 timestamp: 1655046351.3332472 iteration: 49330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.0766 FastRCNN total loss: 0.17819 L1 loss: 0.0000e+00 L2 loss: 0.58733 Learning rate: 0.002 Mask loss: 0.13169 RPN box loss: 0.01713 RPN score loss: 0.0088 RPN total loss: 0.02593 Total loss: 0.92313 timestamp: 1655046354.6759143 iteration: 49335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1264 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.20243 L1 loss: 0.0000e+00 L2 loss: 0.58732 Learning rate: 0.002 Mask loss: 0.0858 RPN box loss: 0.01501 RPN score loss: 0.00303 RPN total loss: 0.01803 Total loss: 0.89358 timestamp: 1655046357.90546 iteration: 49340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12316 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.19283 L1 loss: 0.0000e+00 L2 loss: 0.58731 Learning rate: 0.002 Mask loss: 0.16549 RPN box loss: 0.03173 RPN score loss: 0.00563 RPN total loss: 0.03735 Total loss: 0.98298 timestamp: 1655046361.162626 iteration: 49345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10718 FastRCNN class loss: 0.0806 FastRCNN total loss: 0.18778 L1 loss: 0.0000e+00 L2 loss: 0.5873 Learning rate: 0.002 Mask loss: 0.1691 RPN box loss: 0.01218 RPN score loss: 0.00579 RPN total loss: 0.01798 Total loss: 0.96215 timestamp: 1655046364.3547013 iteration: 49350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14703 FastRCNN class loss: 0.07232 FastRCNN total loss: 0.21935 L1 loss: 0.0000e+00 L2 loss: 0.58729 Learning rate: 0.002 Mask loss: 0.11854 RPN box loss: 0.03439 RPN score loss: 0.0039 RPN total loss: 0.03829 Total loss: 0.96346 timestamp: 1655046367.606678 iteration: 49355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12643 FastRCNN class loss: 0.10644 FastRCNN total loss: 0.23287 L1 loss: 0.0000e+00 L2 loss: 0.58728 Learning rate: 0.002 Mask loss: 0.23119 RPN box loss: 0.02277 RPN score loss: 0.01171 RPN total loss: 0.03448 Total loss: 1.08582 timestamp: 1655046370.7804701 iteration: 49360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13049 FastRCNN class loss: 0.05134 FastRCNN total loss: 0.18183 L1 loss: 0.0000e+00 L2 loss: 0.58727 Learning rate: 0.002 Mask loss: 0.08625 RPN box loss: 0.01151 RPN score loss: 0.00736 RPN total loss: 0.01887 Total loss: 0.87422 timestamp: 1655046374.100475 iteration: 49365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07642 FastRCNN class loss: 0.06948 FastRCNN total loss: 0.14591 L1 loss: 0.0000e+00 L2 loss: 0.58726 Learning rate: 0.002 Mask loss: 0.15241 RPN box loss: 0.00589 RPN score loss: 0.00236 RPN total loss: 0.00825 Total loss: 0.89383 timestamp: 1655046377.3784044 iteration: 49370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09216 FastRCNN class loss: 0.07979 FastRCNN total loss: 0.17195 L1 loss: 0.0000e+00 L2 loss: 0.58725 Learning rate: 0.002 Mask loss: 0.17706 RPN box loss: 0.04171 RPN score loss: 0.00747 RPN total loss: 0.04918 Total loss: 0.98545 timestamp: 1655046380.6776407 iteration: 49375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14794 FastRCNN class loss: 0.12196 FastRCNN total loss: 0.2699 L1 loss: 0.0000e+00 L2 loss: 0.58724 Learning rate: 0.002 Mask loss: 0.16898 RPN box loss: 0.05008 RPN score loss: 0.00821 RPN total loss: 0.05829 Total loss: 1.08441 timestamp: 1655046384.016449 iteration: 49380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14892 FastRCNN class loss: 0.10461 FastRCNN total loss: 0.25353 L1 loss: 0.0000e+00 L2 loss: 0.58723 Learning rate: 0.002 Mask loss: 0.14638 RPN box loss: 0.01622 RPN score loss: 0.01394 RPN total loss: 0.03016 Total loss: 1.0173 timestamp: 1655046387.2883618 iteration: 49385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.09387 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 0.58723 Learning rate: 0.002 Mask loss: 0.14592 RPN box loss: 0.0171 RPN score loss: 0.0032 RPN total loss: 0.02031 Total loss: 0.93078 timestamp: 1655046390.6132057 iteration: 49390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10427 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.16497 L1 loss: 0.0000e+00 L2 loss: 0.58722 Learning rate: 0.002 Mask loss: 0.12752 RPN box loss: 0.01153 RPN score loss: 0.00272 RPN total loss: 0.01425 Total loss: 0.89396 timestamp: 1655046393.8989904 iteration: 49395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13309 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.23204 L1 loss: 0.0000e+00 L2 loss: 0.58721 Learning rate: 0.002 Mask loss: 0.14936 RPN box loss: 0.03307 RPN score loss: 0.03376 RPN total loss: 0.06683 Total loss: 1.03543 timestamp: 1655046397.0548632 iteration: 49400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11801 FastRCNN class loss: 0.05892 FastRCNN total loss: 0.17693 L1 loss: 0.0000e+00 L2 loss: 0.58719 Learning rate: 0.002 Mask loss: 0.19991 RPN box loss: 0.01729 RPN score loss: 0.0039 RPN total loss: 0.02118 Total loss: 0.98521 timestamp: 1655046400.356742 iteration: 49405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06712 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.14403 L1 loss: 0.0000e+00 L2 loss: 0.58718 Learning rate: 0.002 Mask loss: 0.12445 RPN box loss: 0.02775 RPN score loss: 0.00501 RPN total loss: 0.03275 Total loss: 0.88842 timestamp: 1655046403.610157 iteration: 49410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09577 FastRCNN class loss: 0.07615 FastRCNN total loss: 0.17192 L1 loss: 0.0000e+00 L2 loss: 0.58717 Learning rate: 0.002 Mask loss: 0.10284 RPN box loss: 0.00969 RPN score loss: 0.00264 RPN total loss: 0.01234 Total loss: 0.87427 timestamp: 1655046406.9342127 iteration: 49415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06956 FastRCNN class loss: 0.03542 FastRCNN total loss: 0.10498 L1 loss: 0.0000e+00 L2 loss: 0.58717 Learning rate: 0.002 Mask loss: 0.12511 RPN box loss: 0.00755 RPN score loss: 0.0041 RPN total loss: 0.01165 Total loss: 0.8289 timestamp: 1655046410.209922 iteration: 49420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08941 FastRCNN class loss: 0.07807 FastRCNN total loss: 0.16748 L1 loss: 0.0000e+00 L2 loss: 0.58716 Learning rate: 0.002 Mask loss: 0.15196 RPN box loss: 0.03181 RPN score loss: 0.01096 RPN total loss: 0.04276 Total loss: 0.94936 timestamp: 1655046413.394649 iteration: 49425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.06141 FastRCNN total loss: 0.13985 L1 loss: 0.0000e+00 L2 loss: 0.58715 Learning rate: 0.002 Mask loss: 0.15591 RPN box loss: 0.012 RPN score loss: 0.0124 RPN total loss: 0.0244 Total loss: 0.90731 timestamp: 1655046416.6224828 iteration: 49430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16104 FastRCNN class loss: 0.09121 FastRCNN total loss: 0.25225 L1 loss: 0.0000e+00 L2 loss: 0.58714 Learning rate: 0.002 Mask loss: 0.17637 RPN box loss: 0.04427 RPN score loss: 0.00624 RPN total loss: 0.05051 Total loss: 1.06627 timestamp: 1655046419.8498712 iteration: 49435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15309 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.25006 L1 loss: 0.0000e+00 L2 loss: 0.58713 Learning rate: 0.002 Mask loss: 0.15503 RPN box loss: 0.03305 RPN score loss: 0.00824 RPN total loss: 0.04129 Total loss: 1.03351 timestamp: 1655046423.0261111 iteration: 49440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.19226 L1 loss: 0.0000e+00 L2 loss: 0.58712 Learning rate: 0.002 Mask loss: 0.15062 RPN box loss: 0.01328 RPN score loss: 0.00256 RPN total loss: 0.01584 Total loss: 0.94585 timestamp: 1655046426.2437692 iteration: 49445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12222 FastRCNN class loss: 0.05815 FastRCNN total loss: 0.18037 L1 loss: 0.0000e+00 L2 loss: 0.58711 Learning rate: 0.002 Mask loss: 0.19015 RPN box loss: 0.04616 RPN score loss: 0.00911 RPN total loss: 0.05527 Total loss: 1.01291 timestamp: 1655046429.5661721 iteration: 49450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05806 FastRCNN class loss: 0.05719 FastRCNN total loss: 0.11525 L1 loss: 0.0000e+00 L2 loss: 0.5871 Learning rate: 0.002 Mask loss: 0.08735 RPN box loss: 0.00752 RPN score loss: 0.00351 RPN total loss: 0.01103 Total loss: 0.80073 timestamp: 1655046432.8092265 iteration: 49455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11116 FastRCNN class loss: 0.08647 FastRCNN total loss: 0.19762 L1 loss: 0.0000e+00 L2 loss: 0.5871 Learning rate: 0.002 Mask loss: 0.22464 RPN box loss: 0.02051 RPN score loss: 0.00871 RPN total loss: 0.02922 Total loss: 1.03858 timestamp: 1655046436.0596578 iteration: 49460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09263 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 0.58709 Learning rate: 0.002 Mask loss: 0.1407 RPN box loss: 0.02375 RPN score loss: 0.00374 RPN total loss: 0.02749 Total loss: 0.93057 timestamp: 1655046439.3289702 iteration: 49465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.15164 L1 loss: 0.0000e+00 L2 loss: 0.58708 Learning rate: 0.002 Mask loss: 0.12002 RPN box loss: 0.01697 RPN score loss: 0.01276 RPN total loss: 0.02974 Total loss: 0.88847 timestamp: 1655046442.5791445 iteration: 49470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08222 FastRCNN class loss: 0.04859 FastRCNN total loss: 0.13082 L1 loss: 0.0000e+00 L2 loss: 0.58707 Learning rate: 0.002 Mask loss: 0.0868 RPN box loss: 0.00828 RPN score loss: 0.00154 RPN total loss: 0.00982 Total loss: 0.8145 timestamp: 1655046445.874594 iteration: 49475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12593 FastRCNN class loss: 0.14161 FastRCNN total loss: 0.26754 L1 loss: 0.0000e+00 L2 loss: 0.58706 Learning rate: 0.002 Mask loss: 0.24166 RPN box loss: 0.04495 RPN score loss: 0.07507 RPN total loss: 0.12002 Total loss: 1.21628 timestamp: 1655046449.1283374 iteration: 49480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06865 FastRCNN class loss: 0.04084 FastRCNN total loss: 0.10949 L1 loss: 0.0000e+00 L2 loss: 0.58705 Learning rate: 0.002 Mask loss: 0.16883 RPN box loss: 0.00938 RPN score loss: 0.01198 RPN total loss: 0.02137 Total loss: 0.88674 timestamp: 1655046452.3863318 iteration: 49485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09192 FastRCNN class loss: 0.06733 FastRCNN total loss: 0.15925 L1 loss: 0.0000e+00 L2 loss: 0.58705 Learning rate: 0.002 Mask loss: 0.19179 RPN box loss: 0.01428 RPN score loss: 0.00591 RPN total loss: 0.02018 Total loss: 0.95827 timestamp: 1655046455.6295617 iteration: 49490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11865 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.18353 L1 loss: 0.0000e+00 L2 loss: 0.58704 Learning rate: 0.002 Mask loss: 0.16367 RPN box loss: 0.01045 RPN score loss: 0.00466 RPN total loss: 0.01511 Total loss: 0.94935 timestamp: 1655046458.7839317 iteration: 49495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15172 FastRCNN class loss: 0.09849 FastRCNN total loss: 0.25021 L1 loss: 0.0000e+00 L2 loss: 0.58704 Learning rate: 0.002 Mask loss: 0.1778 RPN box loss: 0.01922 RPN score loss: 0.0069 RPN total loss: 0.02612 Total loss: 1.04117 timestamp: 1655046462.0802708 iteration: 49500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15264 FastRCNN class loss: 0.09923 FastRCNN total loss: 0.25187 L1 loss: 0.0000e+00 L2 loss: 0.58703 Learning rate: 0.002 Mask loss: 0.17028 RPN box loss: 0.01021 RPN score loss: 0.00312 RPN total loss: 0.01333 Total loss: 1.0225 timestamp: 1655046465.2938895 iteration: 49505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0898 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.14221 L1 loss: 0.0000e+00 L2 loss: 0.58702 Learning rate: 0.002 Mask loss: 0.1055 RPN box loss: 0.02907 RPN score loss: 0.00445 RPN total loss: 0.03352 Total loss: 0.86825 timestamp: 1655046468.5513694 iteration: 49510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16345 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.21862 L1 loss: 0.0000e+00 L2 loss: 0.58701 Learning rate: 0.002 Mask loss: 0.14019 RPN box loss: 0.01863 RPN score loss: 0.0043 RPN total loss: 0.02293 Total loss: 0.96875 timestamp: 1655046471.8018885 iteration: 49515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13942 FastRCNN class loss: 0.10442 FastRCNN total loss: 0.24384 L1 loss: 0.0000e+00 L2 loss: 0.587 Learning rate: 0.002 Mask loss: 0.17851 RPN box loss: 0.01314 RPN score loss: 0.00441 RPN total loss: 0.01755 Total loss: 1.0269 timestamp: 1655046475.0579584 iteration: 49520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06315 FastRCNN class loss: 0.07853 FastRCNN total loss: 0.14168 L1 loss: 0.0000e+00 L2 loss: 0.58699 Learning rate: 0.002 Mask loss: 0.15741 RPN box loss: 0.00786 RPN score loss: 0.00468 RPN total loss: 0.01254 Total loss: 0.89862 timestamp: 1655046478.3098445 iteration: 49525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0638 FastRCNN class loss: 0.05803 FastRCNN total loss: 0.12183 L1 loss: 0.0000e+00 L2 loss: 0.58698 Learning rate: 0.002 Mask loss: 0.14183 RPN box loss: 0.03001 RPN score loss: 0.00383 RPN total loss: 0.03384 Total loss: 0.88448 timestamp: 1655046481.5890427 iteration: 49530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12936 FastRCNN class loss: 0.06806 FastRCNN total loss: 0.19741 L1 loss: 0.0000e+00 L2 loss: 0.58697 Learning rate: 0.002 Mask loss: 0.13983 RPN box loss: 0.02614 RPN score loss: 0.00311 RPN total loss: 0.02925 Total loss: 0.95347 timestamp: 1655046484.8755589 iteration: 49535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11214 FastRCNN class loss: 0.09132 FastRCNN total loss: 0.20346 L1 loss: 0.0000e+00 L2 loss: 0.58696 Learning rate: 0.002 Mask loss: 0.15727 RPN box loss: 0.01348 RPN score loss: 0.00396 RPN total loss: 0.01745 Total loss: 0.96514 timestamp: 1655046488.2787347 iteration: 49540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09906 FastRCNN class loss: 0.09606 FastRCNN total loss: 0.19512 L1 loss: 0.0000e+00 L2 loss: 0.58696 Learning rate: 0.002 Mask loss: 0.16809 RPN box loss: 0.00799 RPN score loss: 0.00365 RPN total loss: 0.01163 Total loss: 0.9618 timestamp: 1655046491.5370548 iteration: 49545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12651 FastRCNN class loss: 0.08423 FastRCNN total loss: 0.21074 L1 loss: 0.0000e+00 L2 loss: 0.58695 Learning rate: 0.002 Mask loss: 0.16301 RPN box loss: 0.03592 RPN score loss: 0.0061 RPN total loss: 0.04202 Total loss: 1.00272 timestamp: 1655046494.805893 iteration: 49550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12231 FastRCNN class loss: 0.08885 FastRCNN total loss: 0.21116 L1 loss: 0.0000e+00 L2 loss: 0.58694 Learning rate: 0.002 Mask loss: 0.15624 RPN box loss: 0.00966 RPN score loss: 0.00775 RPN total loss: 0.01741 Total loss: 0.97175 timestamp: 1655046498.0657303 iteration: 49555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11087 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.19444 L1 loss: 0.0000e+00 L2 loss: 0.58693 Learning rate: 0.002 Mask loss: 0.14887 RPN box loss: 0.02575 RPN score loss: 0.00713 RPN total loss: 0.03288 Total loss: 0.96312 timestamp: 1655046501.2968323 iteration: 49560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11643 FastRCNN class loss: 0.08194 FastRCNN total loss: 0.19837 L1 loss: 0.0000e+00 L2 loss: 0.58692 Learning rate: 0.002 Mask loss: 0.11603 RPN box loss: 0.0158 RPN score loss: 0.00479 RPN total loss: 0.02059 Total loss: 0.92191 timestamp: 1655046504.4856932 iteration: 49565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12534 FastRCNN class loss: 0.04792 FastRCNN total loss: 0.17326 L1 loss: 0.0000e+00 L2 loss: 0.58691 Learning rate: 0.002 Mask loss: 0.0992 RPN box loss: 0.01331 RPN score loss: 0.00235 RPN total loss: 0.01566 Total loss: 0.87502 timestamp: 1655046507.7891197 iteration: 49570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09813 FastRCNN class loss: 0.0877 FastRCNN total loss: 0.18583 L1 loss: 0.0000e+00 L2 loss: 0.5869 Learning rate: 0.002 Mask loss: 0.15405 RPN box loss: 0.02171 RPN score loss: 0.00779 RPN total loss: 0.0295 Total loss: 0.95628 timestamp: 1655046511.103528 iteration: 49575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06863 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.14484 L1 loss: 0.0000e+00 L2 loss: 0.58689 Learning rate: 0.002 Mask loss: 0.11554 RPN box loss: 0.02901 RPN score loss: 0.00637 RPN total loss: 0.03538 Total loss: 0.88266 timestamp: 1655046514.373596 iteration: 49580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13505 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.20703 L1 loss: 0.0000e+00 L2 loss: 0.58689 Learning rate: 0.002 Mask loss: 0.12127 RPN box loss: 0.02251 RPN score loss: 0.0098 RPN total loss: 0.0323 Total loss: 0.94748 timestamp: 1655046517.6867728 iteration: 49585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13118 FastRCNN class loss: 0.08275 FastRCNN total loss: 0.21393 L1 loss: 0.0000e+00 L2 loss: 0.58688 Learning rate: 0.002 Mask loss: 0.16704 RPN box loss: 0.01097 RPN score loss: 0.00751 RPN total loss: 0.01848 Total loss: 0.98633 timestamp: 1655046520.942604 iteration: 49590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.06965 FastRCNN total loss: 0.17006 L1 loss: 0.0000e+00 L2 loss: 0.58687 Learning rate: 0.002 Mask loss: 0.10992 RPN box loss: 0.00861 RPN score loss: 0.00207 RPN total loss: 0.01068 Total loss: 0.87753 timestamp: 1655046524.1981008 iteration: 49595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15651 FastRCNN class loss: 0.07526 FastRCNN total loss: 0.23177 L1 loss: 0.0000e+00 L2 loss: 0.58685 Learning rate: 0.002 Mask loss: 0.14006 RPN box loss: 0.0179 RPN score loss: 0.00903 RPN total loss: 0.02692 Total loss: 0.98561 timestamp: 1655046527.5121243 iteration: 49600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.082 FastRCNN class loss: 0.07164 FastRCNN total loss: 0.15364 L1 loss: 0.0000e+00 L2 loss: 0.58684 Learning rate: 0.002 Mask loss: 0.15264 RPN box loss: 0.0167 RPN score loss: 0.00492 RPN total loss: 0.02162 Total loss: 0.91474 timestamp: 1655046530.73127 iteration: 49605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11476 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.1701 L1 loss: 0.0000e+00 L2 loss: 0.58683 Learning rate: 0.002 Mask loss: 0.1377 RPN box loss: 0.01224 RPN score loss: 0.00544 RPN total loss: 0.01768 Total loss: 0.91232 timestamp: 1655046533.9783075 iteration: 49610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15386 FastRCNN class loss: 0.11491 FastRCNN total loss: 0.26877 L1 loss: 0.0000e+00 L2 loss: 0.58683 Learning rate: 0.002 Mask loss: 0.17611 RPN box loss: 0.05985 RPN score loss: 0.01768 RPN total loss: 0.07753 Total loss: 1.10924 timestamp: 1655046537.2093842 iteration: 49615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09665 FastRCNN class loss: 0.05135 FastRCNN total loss: 0.148 L1 loss: 0.0000e+00 L2 loss: 0.58682 Learning rate: 0.002 Mask loss: 0.10214 RPN box loss: 0.02359 RPN score loss: 0.00113 RPN total loss: 0.02472 Total loss: 0.86167 timestamp: 1655046540.4624062 iteration: 49620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05401 FastRCNN class loss: 0.02893 FastRCNN total loss: 0.08295 L1 loss: 0.0000e+00 L2 loss: 0.58681 Learning rate: 0.002 Mask loss: 0.0789 RPN box loss: 0.01791 RPN score loss: 0.00327 RPN total loss: 0.02119 Total loss: 0.76985 timestamp: 1655046543.7260282 iteration: 49625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07919 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.13477 L1 loss: 0.0000e+00 L2 loss: 0.58681 Learning rate: 0.002 Mask loss: 0.13807 RPN box loss: 0.00758 RPN score loss: 0.00548 RPN total loss: 0.01307 Total loss: 0.87271 timestamp: 1655046546.9589112 iteration: 49630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19617 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.28449 L1 loss: 0.0000e+00 L2 loss: 0.5868 Learning rate: 0.002 Mask loss: 0.17004 RPN box loss: 0.01703 RPN score loss: 0.00677 RPN total loss: 0.0238 Total loss: 1.06513 timestamp: 1655046550.2300427 iteration: 49635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12483 FastRCNN class loss: 0.06357 FastRCNN total loss: 0.18839 L1 loss: 0.0000e+00 L2 loss: 0.58679 Learning rate: 0.002 Mask loss: 0.14186 RPN box loss: 0.01245 RPN score loss: 0.00695 RPN total loss: 0.0194 Total loss: 0.93645 timestamp: 1655046553.5473933 iteration: 49640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11464 FastRCNN class loss: 0.04434 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.58678 Learning rate: 0.002 Mask loss: 0.14584 RPN box loss: 0.02479 RPN score loss: 0.00154 RPN total loss: 0.02633 Total loss: 0.91794 timestamp: 1655046556.8857465 iteration: 49645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14135 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.22847 L1 loss: 0.0000e+00 L2 loss: 0.58677 Learning rate: 0.002 Mask loss: 0.11863 RPN box loss: 0.01491 RPN score loss: 0.00357 RPN total loss: 0.01848 Total loss: 0.95235 timestamp: 1655046560.1904159 iteration: 49650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05861 FastRCNN class loss: 0.07479 FastRCNN total loss: 0.1334 L1 loss: 0.0000e+00 L2 loss: 0.58676 Learning rate: 0.002 Mask loss: 0.12911 RPN box loss: 0.02001 RPN score loss: 0.00702 RPN total loss: 0.02703 Total loss: 0.8763 timestamp: 1655046563.4837284 iteration: 49655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10026 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.58675 Learning rate: 0.002 Mask loss: 0.15321 RPN box loss: 0.01778 RPN score loss: 0.00169 RPN total loss: 0.01947 Total loss: 0.92097 timestamp: 1655046566.7193298 iteration: 49660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10422 FastRCNN class loss: 0.13152 FastRCNN total loss: 0.23574 L1 loss: 0.0000e+00 L2 loss: 0.58674 Learning rate: 0.002 Mask loss: 0.15477 RPN box loss: 0.02377 RPN score loss: 0.00634 RPN total loss: 0.0301 Total loss: 1.00736 timestamp: 1655046569.9728281 iteration: 49665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11509 FastRCNN class loss: 0.09807 FastRCNN total loss: 0.21317 L1 loss: 0.0000e+00 L2 loss: 0.58673 Learning rate: 0.002 Mask loss: 0.21701 RPN box loss: 0.02825 RPN score loss: 0.00231 RPN total loss: 0.03056 Total loss: 1.04747 timestamp: 1655046573.220195 iteration: 49670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.16139 L1 loss: 0.0000e+00 L2 loss: 0.58673 Learning rate: 0.002 Mask loss: 0.11358 RPN box loss: 0.0117 RPN score loss: 0.00373 RPN total loss: 0.01543 Total loss: 0.87713 timestamp: 1655046576.5123549 iteration: 49675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0747 FastRCNN class loss: 0.0531 FastRCNN total loss: 0.1278 L1 loss: 0.0000e+00 L2 loss: 0.58672 Learning rate: 0.002 Mask loss: 0.14105 RPN box loss: 0.01542 RPN score loss: 0.00211 RPN total loss: 0.01753 Total loss: 0.8731 timestamp: 1655046579.7012305 iteration: 49680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.05025 FastRCNN total loss: 0.15498 L1 loss: 0.0000e+00 L2 loss: 0.58671 Learning rate: 0.002 Mask loss: 0.12311 RPN box loss: 0.00519 RPN score loss: 0.00535 RPN total loss: 0.01054 Total loss: 0.87535 timestamp: 1655046582.9862719 iteration: 49685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08766 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.13371 L1 loss: 0.0000e+00 L2 loss: 0.5867 Learning rate: 0.002 Mask loss: 0.14053 RPN box loss: 0.01962 RPN score loss: 0.0045 RPN total loss: 0.02411 Total loss: 0.88504 timestamp: 1655046586.268384 iteration: 49690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04853 FastRCNN class loss: 0.05942 FastRCNN total loss: 0.10795 L1 loss: 0.0000e+00 L2 loss: 0.58669 Learning rate: 0.002 Mask loss: 0.12916 RPN box loss: 0.02934 RPN score loss: 0.00119 RPN total loss: 0.03053 Total loss: 0.85433 timestamp: 1655046589.5528708 iteration: 49695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09531 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.13802 L1 loss: 0.0000e+00 L2 loss: 0.58668 Learning rate: 0.002 Mask loss: 0.09619 RPN box loss: 0.00327 RPN score loss: 0.00144 RPN total loss: 0.00471 Total loss: 0.8256 timestamp: 1655046592.876369 iteration: 49700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13951 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.21711 L1 loss: 0.0000e+00 L2 loss: 0.58667 Learning rate: 0.002 Mask loss: 0.07503 RPN box loss: 0.0193 RPN score loss: 0.00265 RPN total loss: 0.02194 Total loss: 0.90074 timestamp: 1655046596.0841634 iteration: 49705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05044 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.10871 L1 loss: 0.0000e+00 L2 loss: 0.58666 Learning rate: 0.002 Mask loss: 0.12903 RPN box loss: 0.01013 RPN score loss: 0.00364 RPN total loss: 0.01376 Total loss: 0.83816 timestamp: 1655046599.3437097 iteration: 49710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09698 FastRCNN class loss: 0.06868 FastRCNN total loss: 0.16566 L1 loss: 0.0000e+00 L2 loss: 0.58665 Learning rate: 0.002 Mask loss: 0.10434 RPN box loss: 0.01853 RPN score loss: 0.00374 RPN total loss: 0.02227 Total loss: 0.87892 timestamp: 1655046602.668659 iteration: 49715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09527 FastRCNN class loss: 0.09265 FastRCNN total loss: 0.18792 L1 loss: 0.0000e+00 L2 loss: 0.58664 Learning rate: 0.002 Mask loss: 0.15814 RPN box loss: 0.01363 RPN score loss: 0.01141 RPN total loss: 0.02504 Total loss: 0.95774 timestamp: 1655046605.9064143 iteration: 49720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.08621 FastRCNN total loss: 0.19853 L1 loss: 0.0000e+00 L2 loss: 0.58664 Learning rate: 0.002 Mask loss: 0.15719 RPN box loss: 0.02577 RPN score loss: 0.01061 RPN total loss: 0.03638 Total loss: 0.97873 timestamp: 1655046609.1864185 iteration: 49725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.123 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.19117 L1 loss: 0.0000e+00 L2 loss: 0.58663 Learning rate: 0.002 Mask loss: 0.15512 RPN box loss: 0.01935 RPN score loss: 0.00377 RPN total loss: 0.02312 Total loss: 0.95603 timestamp: 1655046612.533205 iteration: 49730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07287 FastRCNN class loss: 0.04017 FastRCNN total loss: 0.11304 L1 loss: 0.0000e+00 L2 loss: 0.58662 Learning rate: 0.002 Mask loss: 0.09917 RPN box loss: 0.00378 RPN score loss: 0.00084 RPN total loss: 0.00462 Total loss: 0.80345 timestamp: 1655046615.8591201 iteration: 49735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04795 FastRCNN class loss: 0.03847 FastRCNN total loss: 0.08641 L1 loss: 0.0000e+00 L2 loss: 0.58661 Learning rate: 0.002 Mask loss: 0.1226 RPN box loss: 0.00496 RPN score loss: 0.00568 RPN total loss: 0.01064 Total loss: 0.80627 timestamp: 1655046619.168532 iteration: 49740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07466 FastRCNN class loss: 0.10524 FastRCNN total loss: 0.1799 L1 loss: 0.0000e+00 L2 loss: 0.5866 Learning rate: 0.002 Mask loss: 0.15543 RPN box loss: 0.0599 RPN score loss: 0.02088 RPN total loss: 0.08077 Total loss: 1.0027 timestamp: 1655046622.4042728 iteration: 49745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08455 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.15037 L1 loss: 0.0000e+00 L2 loss: 0.58659 Learning rate: 0.002 Mask loss: 0.17527 RPN box loss: 0.02027 RPN score loss: 0.00454 RPN total loss: 0.02481 Total loss: 0.93705 timestamp: 1655046625.724169 iteration: 49750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1226 FastRCNN class loss: 0.09495 FastRCNN total loss: 0.21754 L1 loss: 0.0000e+00 L2 loss: 0.58659 Learning rate: 0.002 Mask loss: 0.19082 RPN box loss: 0.02208 RPN score loss: 0.00968 RPN total loss: 0.03176 Total loss: 1.02671 timestamp: 1655046628.9757743 iteration: 49755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.07099 FastRCNN total loss: 0.13197 L1 loss: 0.0000e+00 L2 loss: 0.58658 Learning rate: 0.002 Mask loss: 0.1427 RPN box loss: 0.03127 RPN score loss: 0.0049 RPN total loss: 0.03617 Total loss: 0.89741 timestamp: 1655046632.2604074 iteration: 49760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07016 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.13127 L1 loss: 0.0000e+00 L2 loss: 0.58657 Learning rate: 0.002 Mask loss: 0.12702 RPN box loss: 0.0119 RPN score loss: 0.009 RPN total loss: 0.0209 Total loss: 0.86576 timestamp: 1655046635.5182807 iteration: 49765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10595 FastRCNN class loss: 0.10908 FastRCNN total loss: 0.21503 L1 loss: 0.0000e+00 L2 loss: 0.58656 Learning rate: 0.002 Mask loss: 0.19709 RPN box loss: 0.01555 RPN score loss: 0.00905 RPN total loss: 0.0246 Total loss: 1.02328 timestamp: 1655046638.7913554 iteration: 49770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12712 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.19421 L1 loss: 0.0000e+00 L2 loss: 0.58655 Learning rate: 0.002 Mask loss: 0.12407 RPN box loss: 0.00942 RPN score loss: 0.00735 RPN total loss: 0.01677 Total loss: 0.9216 timestamp: 1655046641.9922378 iteration: 49775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13208 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.21128 L1 loss: 0.0000e+00 L2 loss: 0.58654 Learning rate: 0.002 Mask loss: 0.14441 RPN box loss: 0.03863 RPN score loss: 0.00924 RPN total loss: 0.04787 Total loss: 0.99011 timestamp: 1655046645.2684784 iteration: 49780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08427 FastRCNN class loss: 0.13381 FastRCNN total loss: 0.21808 L1 loss: 0.0000e+00 L2 loss: 0.58654 Learning rate: 0.002 Mask loss: 0.13383 RPN box loss: 0.03435 RPN score loss: 0.00797 RPN total loss: 0.04232 Total loss: 0.98077 timestamp: 1655046648.4887252 iteration: 49785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.10283 FastRCNN total loss: 0.21842 L1 loss: 0.0000e+00 L2 loss: 0.58653 Learning rate: 0.002 Mask loss: 0.19173 RPN box loss: 0.0307 RPN score loss: 0.00473 RPN total loss: 0.03543 Total loss: 1.03211 timestamp: 1655046651.7853262 iteration: 49790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08885 FastRCNN class loss: 0.05173 FastRCNN total loss: 0.14058 L1 loss: 0.0000e+00 L2 loss: 0.58652 Learning rate: 0.002 Mask loss: 0.13273 RPN box loss: 0.0053 RPN score loss: 0.00365 RPN total loss: 0.00895 Total loss: 0.86878 timestamp: 1655046655.00673 iteration: 49795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17067 FastRCNN class loss: 0.16005 FastRCNN total loss: 0.33072 L1 loss: 0.0000e+00 L2 loss: 0.58651 Learning rate: 0.002 Mask loss: 0.22997 RPN box loss: 0.05725 RPN score loss: 0.01595 RPN total loss: 0.0732 Total loss: 1.2204 timestamp: 1655046658.3101628 iteration: 49800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09326 FastRCNN class loss: 0.08831 FastRCNN total loss: 0.18157 L1 loss: 0.0000e+00 L2 loss: 0.5865 Learning rate: 0.002 Mask loss: 0.12217 RPN box loss: 0.03871 RPN score loss: 0.00344 RPN total loss: 0.04215 Total loss: 0.93239 timestamp: 1655046661.5878053 iteration: 49805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.15007 L1 loss: 0.0000e+00 L2 loss: 0.58649 Learning rate: 0.002 Mask loss: 0.11043 RPN box loss: 0.00311 RPN score loss: 0.0022 RPN total loss: 0.00532 Total loss: 0.85231 timestamp: 1655046664.8065941 iteration: 49810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.073 FastRCNN class loss: 0.05332 FastRCNN total loss: 0.12632 L1 loss: 0.0000e+00 L2 loss: 0.58649 Learning rate: 0.002 Mask loss: 0.10851 RPN box loss: 0.0122 RPN score loss: 0.00385 RPN total loss: 0.01605 Total loss: 0.83738 timestamp: 1655046668.0537753 iteration: 49815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.09719 FastRCNN total loss: 0.18621 L1 loss: 0.0000e+00 L2 loss: 0.58648 Learning rate: 0.002 Mask loss: 0.11706 RPN box loss: 0.02408 RPN score loss: 0.01294 RPN total loss: 0.03702 Total loss: 0.92675 timestamp: 1655046671.3723385 iteration: 49820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09894 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.16606 L1 loss: 0.0000e+00 L2 loss: 0.58647 Learning rate: 0.002 Mask loss: 0.18185 RPN box loss: 0.01926 RPN score loss: 0.01237 RPN total loss: 0.03163 Total loss: 0.966 timestamp: 1655046674.594362 iteration: 49825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15349 FastRCNN class loss: 0.0854 FastRCNN total loss: 0.23889 L1 loss: 0.0000e+00 L2 loss: 0.58646 Learning rate: 0.002 Mask loss: 0.1406 RPN box loss: 0.00949 RPN score loss: 0.00295 RPN total loss: 0.01244 Total loss: 0.97839 timestamp: 1655046677.8155613 iteration: 49830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06504 FastRCNN class loss: 0.03482 FastRCNN total loss: 0.09986 L1 loss: 0.0000e+00 L2 loss: 0.58645 Learning rate: 0.002 Mask loss: 0.1206 RPN box loss: 0.00599 RPN score loss: 0.00558 RPN total loss: 0.01156 Total loss: 0.81846 timestamp: 1655046681.090944 iteration: 49835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15396 FastRCNN class loss: 0.09694 FastRCNN total loss: 0.2509 L1 loss: 0.0000e+00 L2 loss: 0.58644 Learning rate: 0.002 Mask loss: 0.21125 RPN box loss: 0.01831 RPN score loss: 0.00317 RPN total loss: 0.02148 Total loss: 1.07007 timestamp: 1655046684.4222476 iteration: 49840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.13818 L1 loss: 0.0000e+00 L2 loss: 0.58643 Learning rate: 0.002 Mask loss: 0.13657 RPN box loss: 0.01114 RPN score loss: 0.00349 RPN total loss: 0.01463 Total loss: 0.87581 timestamp: 1655046687.7151747 iteration: 49845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09534 FastRCNN class loss: 0.07655 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.58643 Learning rate: 0.002 Mask loss: 0.1119 RPN box loss: 0.01581 RPN score loss: 0.01396 RPN total loss: 0.02977 Total loss: 0.89998 timestamp: 1655046690.946231 iteration: 49850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.06067 FastRCNN total loss: 0.14164 L1 loss: 0.0000e+00 L2 loss: 0.58642 Learning rate: 0.002 Mask loss: 0.12452 RPN box loss: 0.05152 RPN score loss: 0.00692 RPN total loss: 0.05844 Total loss: 0.91103 timestamp: 1655046694.22797 iteration: 49855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11255 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.18495 L1 loss: 0.0000e+00 L2 loss: 0.58641 Learning rate: 0.002 Mask loss: 0.1284 RPN box loss: 0.01533 RPN score loss: 0.00448 RPN total loss: 0.01981 Total loss: 0.91957 timestamp: 1655046697.527036 iteration: 49860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08249 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.13386 L1 loss: 0.0000e+00 L2 loss: 0.5864 Learning rate: 0.002 Mask loss: 0.1368 RPN box loss: 0.0076 RPN score loss: 0.00192 RPN total loss: 0.00952 Total loss: 0.86659 timestamp: 1655046700.802079 iteration: 49865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.19897 L1 loss: 0.0000e+00 L2 loss: 0.58639 Learning rate: 0.002 Mask loss: 0.15707 RPN box loss: 0.02002 RPN score loss: 0.0044 RPN total loss: 0.02442 Total loss: 0.96686 timestamp: 1655046704.0873446 iteration: 49870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11773 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.1912 L1 loss: 0.0000e+00 L2 loss: 0.58638 Learning rate: 0.002 Mask loss: 0.15503 RPN box loss: 0.01237 RPN score loss: 0.01759 RPN total loss: 0.02996 Total loss: 0.96257 timestamp: 1655046707.3737304 iteration: 49875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14509 FastRCNN class loss: 0.07683 FastRCNN total loss: 0.22192 L1 loss: 0.0000e+00 L2 loss: 0.58637 Learning rate: 0.002 Mask loss: 0.14721 RPN box loss: 0.02875 RPN score loss: 0.01832 RPN total loss: 0.04706 Total loss: 1.00256 timestamp: 1655046710.6381803 iteration: 49880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10942 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.17106 L1 loss: 0.0000e+00 L2 loss: 0.58636 Learning rate: 0.002 Mask loss: 0.16583 RPN box loss: 0.00911 RPN score loss: 0.01033 RPN total loss: 0.01944 Total loss: 0.94268 timestamp: 1655046713.8935347 iteration: 49885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08281 FastRCNN class loss: 0.07735 FastRCNN total loss: 0.16016 L1 loss: 0.0000e+00 L2 loss: 0.58635 Learning rate: 0.002 Mask loss: 0.14908 RPN box loss: 0.0107 RPN score loss: 0.00503 RPN total loss: 0.01573 Total loss: 0.91132 timestamp: 1655046717.1849995 iteration: 49890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12423 FastRCNN class loss: 0.12149 FastRCNN total loss: 0.24573 L1 loss: 0.0000e+00 L2 loss: 0.58634 Learning rate: 0.002 Mask loss: 0.14339 RPN box loss: 0.02507 RPN score loss: 0.00904 RPN total loss: 0.03411 Total loss: 1.00956 timestamp: 1655046720.4670758 iteration: 49895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13769 FastRCNN class loss: 0.04995 FastRCNN total loss: 0.18764 L1 loss: 0.0000e+00 L2 loss: 0.58633 Learning rate: 0.002 Mask loss: 0.17975 RPN box loss: 0.01839 RPN score loss: 0.00217 RPN total loss: 0.02056 Total loss: 0.97428 timestamp: 1655046723.7230332 iteration: 49900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09177 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.16723 L1 loss: 0.0000e+00 L2 loss: 0.58632 Learning rate: 0.002 Mask loss: 0.12229 RPN box loss: 0.00914 RPN score loss: 0.00428 RPN total loss: 0.01342 Total loss: 0.88926 timestamp: 1655046726.9758115 iteration: 49905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17294 FastRCNN class loss: 0.12769 FastRCNN total loss: 0.30063 L1 loss: 0.0000e+00 L2 loss: 0.58631 Learning rate: 0.002 Mask loss: 0.26231 RPN box loss: 0.02179 RPN score loss: 0.01 RPN total loss: 0.03178 Total loss: 1.18103 timestamp: 1655046730.3011212 iteration: 49910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09475 FastRCNN class loss: 0.07045 FastRCNN total loss: 0.1652 L1 loss: 0.0000e+00 L2 loss: 0.5863 Learning rate: 0.002 Mask loss: 0.15537 RPN box loss: 0.0309 RPN score loss: 0.01085 RPN total loss: 0.04174 Total loss: 0.94861 timestamp: 1655046733.6047306 iteration: 49915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10354 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.17767 L1 loss: 0.0000e+00 L2 loss: 0.58629 Learning rate: 0.002 Mask loss: 0.17594 RPN box loss: 0.0394 RPN score loss: 0.01141 RPN total loss: 0.05081 Total loss: 0.99071 timestamp: 1655046736.8568766 iteration: 49920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08159 FastRCNN class loss: 0.04843 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 0.58628 Learning rate: 0.002 Mask loss: 0.09727 RPN box loss: 0.01236 RPN score loss: 0.00717 RPN total loss: 0.01954 Total loss: 0.8331 timestamp: 1655046740.1006744 iteration: 49925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18041 FastRCNN class loss: 0.0943 FastRCNN total loss: 0.27471 L1 loss: 0.0000e+00 L2 loss: 0.58627 Learning rate: 0.002 Mask loss: 0.22038 RPN box loss: 0.02512 RPN score loss: 0.00727 RPN total loss: 0.0324 Total loss: 1.11375 timestamp: 1655046743.3913765 iteration: 49930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18067 FastRCNN class loss: 0.09972 FastRCNN total loss: 0.28039 L1 loss: 0.0000e+00 L2 loss: 0.58626 Learning rate: 0.002 Mask loss: 0.18357 RPN box loss: 0.01819 RPN score loss: 0.00684 RPN total loss: 0.02503 Total loss: 1.07526 timestamp: 1655046746.6439347 iteration: 49935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12855 FastRCNN class loss: 0.07878 FastRCNN total loss: 0.20733 L1 loss: 0.0000e+00 L2 loss: 0.58626 Learning rate: 0.002 Mask loss: 0.14603 RPN box loss: 0.02043 RPN score loss: 0.00324 RPN total loss: 0.02367 Total loss: 0.96328 timestamp: 1655046749.9405966 iteration: 49940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1141 FastRCNN class loss: 0.09983 FastRCNN total loss: 0.21393 L1 loss: 0.0000e+00 L2 loss: 0.58625 Learning rate: 0.002 Mask loss: 0.19927 RPN box loss: 0.01336 RPN score loss: 0.00862 RPN total loss: 0.02199 Total loss: 1.02144 timestamp: 1655046753.2204862 iteration: 49945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11718 FastRCNN class loss: 0.06012 FastRCNN total loss: 0.1773 L1 loss: 0.0000e+00 L2 loss: 0.58625 Learning rate: 0.002 Mask loss: 0.12429 RPN box loss: 0.02664 RPN score loss: 0.00175 RPN total loss: 0.02839 Total loss: 0.91622 timestamp: 1655046756.4678915 iteration: 49950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14601 FastRCNN class loss: 0.08981 FastRCNN total loss: 0.23582 L1 loss: 0.0000e+00 L2 loss: 0.58624 Learning rate: 0.002 Mask loss: 0.15178 RPN box loss: 0.01861 RPN score loss: 0.00214 RPN total loss: 0.02076 Total loss: 0.99458 timestamp: 1655046759.7578635 iteration: 49955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10498 FastRCNN class loss: 0.0502 FastRCNN total loss: 0.15518 L1 loss: 0.0000e+00 L2 loss: 0.58623 Learning rate: 0.002 Mask loss: 0.17173 RPN box loss: 0.00511 RPN score loss: 0.00439 RPN total loss: 0.0095 Total loss: 0.92263 timestamp: 1655046762.9879508 iteration: 49960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09334 FastRCNN class loss: 0.04362 FastRCNN total loss: 0.13696 L1 loss: 0.0000e+00 L2 loss: 0.58622 Learning rate: 0.002 Mask loss: 0.13737 RPN box loss: 0.04466 RPN score loss: 0.00289 RPN total loss: 0.04755 Total loss: 0.9081 timestamp: 1655046766.2379217 iteration: 49965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07785 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.1301 L1 loss: 0.0000e+00 L2 loss: 0.58621 Learning rate: 0.002 Mask loss: 0.09931 RPN box loss: 0.01351 RPN score loss: 0.00224 RPN total loss: 0.01575 Total loss: 0.83137 timestamp: 1655046769.5432336 iteration: 49970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.1592 L1 loss: 0.0000e+00 L2 loss: 0.5862 Learning rate: 0.002 Mask loss: 0.17481 RPN box loss: 0.033 RPN score loss: 0.00821 RPN total loss: 0.04122 Total loss: 0.96142 timestamp: 1655046772.7773857 iteration: 49975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05921 FastRCNN class loss: 0.04605 FastRCNN total loss: 0.10526 L1 loss: 0.0000e+00 L2 loss: 0.58619 Learning rate: 0.002 Mask loss: 0.11291 RPN box loss: 0.00817 RPN score loss: 0.00244 RPN total loss: 0.01061 Total loss: 0.81498 timestamp: 1655046776.0573719 iteration: 49980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12878 FastRCNN class loss: 0.09765 FastRCNN total loss: 0.22643 L1 loss: 0.0000e+00 L2 loss: 0.58619 Learning rate: 0.002 Mask loss: 0.12343 RPN box loss: 0.0277 RPN score loss: 0.00424 RPN total loss: 0.03193 Total loss: 0.96799 timestamp: 1655046779.3622549 iteration: 49985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14314 FastRCNN class loss: 0.07895 FastRCNN total loss: 0.22209 L1 loss: 0.0000e+00 L2 loss: 0.58618 Learning rate: 0.002 Mask loss: 0.2008 RPN box loss: 0.03411 RPN score loss: 0.0081 RPN total loss: 0.04221 Total loss: 1.05127 timestamp: 1655046782.7089581 iteration: 49990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10855 FastRCNN class loss: 0.0839 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.58616 Learning rate: 0.002 Mask loss: 0.10527 RPN box loss: 0.00512 RPN score loss: 0.00162 RPN total loss: 0.00674 Total loss: 0.89064 timestamp: 1655046786.021187 iteration: 49995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13015 FastRCNN class loss: 0.08041 FastRCNN total loss: 0.21056 L1 loss: 0.0000e+00 L2 loss: 0.58615 Learning rate: 0.002 Mask loss: 0.23683 RPN box loss: 0.02276 RPN score loss: 0.01123 RPN total loss: 0.03399 Total loss: 1.06754 timestamp: 1655046789.3432772 iteration: 50000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08385 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.16438 L1 loss: 0.0000e+00 L2 loss: 0.58614 Learning rate: 0.002 Mask loss: 0.15804 RPN box loss: 0.01296 RPN score loss: 0.00857 RPN total loss: 0.02153 Total loss: 0.9301 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.5429s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.9206s - Throughput: 4.3 imgs/s Running inference on batch 003/125... - Step Time: 0.9257s - Throughput: 4.3 imgs/s Running inference on batch 004/125... - Step Time: 0.9259s - Throughput: 4.3 imgs/s Running inference on batch 005/125... - Step Time: 0.8891s - Throughput: 4.5 imgs/s Running inference on batch 006/125... - Step Time: 0.8881s - Throughput: 4.5 imgs/s Running inference on batch 007/125... - Step Time: 0.8999s - Throughput: 4.4 imgs/s Running inference on batch 008/125... - Step Time: 0.9333s - Throughput: 4.3 imgs/s Running inference on batch 009/125... - Step Time: 0.9812s - Throughput: 4.1 imgs/s Running inference on batch 010/125... - Step Time: 0.8940s - Throughput: 4.5 imgs/s Running inference on batch 011/125... - Step Time: 0.9588s - Throughput: 4.2 imgs/s Running inference on batch 012/125... - Step Time: 0.9204s - Throughput: 4.3 imgs/s Running inference on batch 013/125... - Step Time: 0.8649s - Throughput: 4.6 imgs/s Running inference on batch 014/125... - Step Time: 0.9032s - Throughput: 4.4 imgs/s Running inference on batch 015/125... - Step Time: 0.9417s - Throughput: 4.2 imgs/s Running inference on batch 016/125... - Step Time: 0.8897s - Throughput: 4.5 imgs/s Running inference on batch 017/125... - Step Time: 0.8858s - Throughput: 4.5 imgs/s Running inference on batch 018/125... - Step Time: 0.8753s - Throughput: 4.6 imgs/s Running inference on batch 019/125... - Step Time: 0.9572s - Throughput: 4.2 imgs/s Running inference on batch 020/125... - Step Time: 0.8839s - Throughput: 4.5 imgs/s Running inference on batch 021/125... - Step Time: 0.9168s - Throughput: 4.4 imgs/s Running inference on batch 022/125... - Step Time: 0.9892s - Throughput: 4.0 imgs/s Running inference on batch 023/125... - Step Time: 0.9222s - Throughput: 4.3 imgs/s Running inference on batch 024/125... - Step Time: 0.9113s - Throughput: 4.4 imgs/s Running inference on batch 025/125... - Step Time: 0.8894s - Throughput: 4.5 imgs/s Running inference on batch 026/125... - Step Time: 0.9080s - Throughput: 4.4 imgs/s Running inference on batch 027/125... - Step Time: 0.8439s - Throughput: 4.7 imgs/s Running inference on batch 028/125... - Step Time: 0.9111s - Throughput: 4.4 imgs/s Running inference on batch 029/125... - Step Time: 0.8995s - Throughput: 4.4 imgs/s Running inference on batch 030/125... - Step Time: 0.9166s - Throughput: 4.4 imgs/s Running inference on batch 031/125... - Step Time: 0.8970s - Throughput: 4.5 imgs/s Running inference on batch 032/125... - Step Time: 0.9311s - Throughput: 4.3 imgs/s Running inference on batch 033/125... - Step Time: 0.9504s - Throughput: 4.2 imgs/s Running inference on batch 034/125... - Step Time: 0.9290s - Throughput: 4.3 imgs/s Running inference on batch 035/125... - Step Time: 0.8317s - Throughput: 4.8 imgs/s Running inference on batch 036/125... - Step Time: 0.9042s - Throughput: 4.4 imgs/s Running inference on batch 037/125... - Step Time: 0.9199s - Throughput: 4.3 imgs/s Running inference on batch 038/125... - Step Time: 0.9211s - Throughput: 4.3 imgs/s Running inference on batch 039/125... - Step Time: 0.9108s - Throughput: 4.4 imgs/s Running inference on batch 040/125... - Step Time: 0.9156s - Throughput: 4.4 imgs/s Running inference on batch 041/125... - Step Time: 0.9459s - Throughput: 4.2 imgs/s Running inference on batch 042/125... - Step Time: 0.9186s - Throughput: 4.4 imgs/s Running inference on batch 043/125... - Step Time: 0.9383s - Throughput: 4.3 imgs/s Running inference on batch 044/125... - Step Time: 0.8967s - Throughput: 4.5 imgs/s Running inference on batch 045/125... - Step Time: 0.8671s - Throughput: 4.6 imgs/s Running inference on batch 046/125... - Step Time: 0.8928s - Throughput: 4.5 imgs/s Running inference on batch 047/125... - Step Time: 0.8932s - Throughput: 4.5 imgs/s Running inference on batch 048/125... - Step Time: 1.0106s - Throughput: 4.0 imgs/s Running inference on batch 049/125... - Step Time: 0.9390s - Throughput: 4.3 imgs/s Running inference on batch 050/125... - Step Time: 0.9453s - Throughput: 4.2 imgs/s Running inference on batch 051/125... - Step Time: 0.7010s - Throughput: 5.7 imgs/s Running inference on batch 052/125... - Step Time: 0.8246s - Throughput: 4.9 imgs/s Running inference on batch 053/125... - Step Time: 0.9296s - Throughput: 4.3 imgs/s Running inference on batch 054/125... - Step Time: 0.9266s - Throughput: 4.3 imgs/s Running inference on batch 055/125... - Step Time: 0.9459s - Throughput: 4.2 imgs/s Running inference on batch 056/125... - Step Time: 0.9064s - Throughput: 4.4 imgs/s Running inference on batch 057/125... - Step Time: 0.9212s - Throughput: 4.3 imgs/s Running inference on batch 058/125... - Step Time: 0.9249s - Throughput: 4.3 imgs/s Running inference on batch 059/125... - Step Time: 0.9257s - Throughput: 4.3 imgs/s Running inference on batch 060/125... - 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Step Time: 0.9100s - Throughput: 4.4 imgs/s Running inference on batch 121/125... - Step Time: 0.8811s - Throughput: 4.5 imgs/s Running inference on batch 122/125... - Step Time: 0.8752s - Throughput: 4.6 imgs/s Running inference on batch 123/125... - Step Time: 0.8821s - Throughput: 4.5 imgs/s Running inference on batch 124/125... - Step Time: 0.9784s - Throughput: 4.1 imgs/s Running inference on batch 125/125... - Step Time: 0.9058s - Throughput: 4.4 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: 4.3 samples/sec Total processed steps: 125 Total processing time: 0.0h 09m 06s ==================== Metrics ==================== AP: 0.190305948 AP50: 0.294876248 AP75: 0.190706030 APl: 0.222959906 APm: 0.044579323 APs: 0.003026481 ARl: 0.440281004 ARm: 0.087965973 ARmax1: 0.289297193 ARmax10: 0.370682567 ARmax100: 0.374650002 ARs: 0.018176328 mask_AP: 0.143473610 mask_AP50: 0.248445198 mask_AP75: 0.145337924 mask_APl: 0.170993537 mask_APm: 0.018988613 mask_APs: 0.000014475 mask_ARl: 0.289985597 mask_ARm: 0.045922916 mask_ARmax1: 0.204110727 mask_ARmax10: 0.238475576 mask_ARmax100: 0.241721421 mask_ARs: 0.000483092 ================================= 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] 549.0 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: 1655048270.0044777 iteration: 50005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11358 FastRCNN class loss: 0.05009 FastRCNN total loss: 0.16367 L1 loss: 0.0000e+00 L2 loss: 0.58614 Learning rate: 0.002 Mask loss: 0.10761 RPN box loss: 0.01936 RPN score loss: 0.00144 RPN total loss: 0.02079 Total loss: 0.87821 timestamp: 1655048273.2825098 iteration: 50010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06872 FastRCNN class loss: 0.06519 FastRCNN total loss: 0.13391 L1 loss: 0.0000e+00 L2 loss: 0.58613 Learning rate: 0.002 Mask loss: 0.13781 RPN box loss: 0.01936 RPN score loss: 0.00126 RPN total loss: 0.02062 Total loss: 0.87847 timestamp: 1655048276.5494294 iteration: 50015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0765 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.13045 L1 loss: 0.0000e+00 L2 loss: 0.58613 Learning rate: 0.002 Mask loss: 0.16729 RPN box loss: 0.00926 RPN score loss: 0.00413 RPN total loss: 0.01339 Total loss: 0.89726 timestamp: 1655048279.8148782 iteration: 50020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14345 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.21253 L1 loss: 0.0000e+00 L2 loss: 0.58612 Learning rate: 0.002 Mask loss: 0.15553 RPN box loss: 0.0192 RPN score loss: 0.00517 RPN total loss: 0.02437 Total loss: 0.97855 timestamp: 1655048283.1043756 iteration: 50025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08924 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.58611 Learning rate: 0.002 Mask loss: 0.12555 RPN box loss: 0.0439 RPN score loss: 0.0031 RPN total loss: 0.047 Total loss: 0.89494 timestamp: 1655048286.395522 iteration: 50030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08425 FastRCNN class loss: 0.06181 FastRCNN total loss: 0.14606 L1 loss: 0.0000e+00 L2 loss: 0.58611 Learning rate: 0.002 Mask loss: 0.08935 RPN box loss: 0.01376 RPN score loss: 0.0037 RPN total loss: 0.01746 Total loss: 0.83897 timestamp: 1655048289.741202 iteration: 50035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07745 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.1495 L1 loss: 0.0000e+00 L2 loss: 0.5861 Learning rate: 0.002 Mask loss: 0.18452 RPN box loss: 0.01143 RPN score loss: 0.00423 RPN total loss: 0.01566 Total loss: 0.93577 timestamp: 1655048293.0055525 iteration: 50040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07787 FastRCNN class loss: 0.0709 FastRCNN total loss: 0.14877 L1 loss: 0.0000e+00 L2 loss: 0.58609 Learning rate: 0.002 Mask loss: 0.17193 RPN box loss: 0.00342 RPN score loss: 0.00296 RPN total loss: 0.00638 Total loss: 0.91317 timestamp: 1655048296.3284118 iteration: 50045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16102 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.22679 L1 loss: 0.0000e+00 L2 loss: 0.58608 Learning rate: 0.002 Mask loss: 0.10407 RPN box loss: 0.01659 RPN score loss: 0.00299 RPN total loss: 0.01958 Total loss: 0.93652 timestamp: 1655048299.6137702 iteration: 50050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09011 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.15495 L1 loss: 0.0000e+00 L2 loss: 0.58607 Learning rate: 0.002 Mask loss: 0.14127 RPN box loss: 0.01144 RPN score loss: 0.00122 RPN total loss: 0.01266 Total loss: 0.89494 timestamp: 1655048302.9062817 iteration: 50055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1014 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.16699 L1 loss: 0.0000e+00 L2 loss: 0.58606 Learning rate: 0.002 Mask loss: 0.12174 RPN box loss: 0.01437 RPN score loss: 0.00626 RPN total loss: 0.02063 Total loss: 0.89542 timestamp: 1655048306.1763015 iteration: 50060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14157 FastRCNN class loss: 0.142 FastRCNN total loss: 0.28357 L1 loss: 0.0000e+00 L2 loss: 0.58605 Learning rate: 0.002 Mask loss: 0.21119 RPN box loss: 0.02079 RPN score loss: 0.00947 RPN total loss: 0.03026 Total loss: 1.11107 timestamp: 1655048309.458381 iteration: 50065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08657 FastRCNN class loss: 0.06434 FastRCNN total loss: 0.15091 L1 loss: 0.0000e+00 L2 loss: 0.58604 Learning rate: 0.002 Mask loss: 0.14706 RPN box loss: 0.03609 RPN score loss: 0.00517 RPN total loss: 0.04126 Total loss: 0.92527 timestamp: 1655048312.7327652 iteration: 50070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.08496 FastRCNN total loss: 0.20515 L1 loss: 0.0000e+00 L2 loss: 0.58603 Learning rate: 0.002 Mask loss: 0.12062 RPN box loss: 0.01332 RPN score loss: 0.00205 RPN total loss: 0.01537 Total loss: 0.92716 timestamp: 1655048316.0126028 iteration: 50075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1282 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.20809 L1 loss: 0.0000e+00 L2 loss: 0.58602 Learning rate: 0.002 Mask loss: 0.1435 RPN box loss: 0.01554 RPN score loss: 0.00715 RPN total loss: 0.02269 Total loss: 0.9603 timestamp: 1655048319.2906234 iteration: 50080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06374 FastRCNN class loss: 0.03805 FastRCNN total loss: 0.10179 L1 loss: 0.0000e+00 L2 loss: 0.58601 Learning rate: 0.002 Mask loss: 0.11827 RPN box loss: 0.00476 RPN score loss: 0.0046 RPN total loss: 0.00936 Total loss: 0.81543 timestamp: 1655048322.5185027 iteration: 50085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10647 FastRCNN class loss: 0.07791 FastRCNN total loss: 0.18438 L1 loss: 0.0000e+00 L2 loss: 0.586 Learning rate: 0.002 Mask loss: 0.19416 RPN box loss: 0.0196 RPN score loss: 0.00554 RPN total loss: 0.02514 Total loss: 0.98968 timestamp: 1655048325.8134313 iteration: 50090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.24369 L1 loss: 0.0000e+00 L2 loss: 0.58599 Learning rate: 0.002 Mask loss: 0.1408 RPN box loss: 0.01692 RPN score loss: 0.00869 RPN total loss: 0.02561 Total loss: 0.99609 timestamp: 1655048329.0805902 iteration: 50095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06238 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.11066 L1 loss: 0.0000e+00 L2 loss: 0.58598 Learning rate: 0.002 Mask loss: 0.09332 RPN box loss: 0.01304 RPN score loss: 0.00637 RPN total loss: 0.01941 Total loss: 0.80937 timestamp: 1655048332.376094 iteration: 50100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09477 FastRCNN class loss: 0.04737 FastRCNN total loss: 0.14214 L1 loss: 0.0000e+00 L2 loss: 0.58597 Learning rate: 0.002 Mask loss: 0.10372 RPN box loss: 0.01645 RPN score loss: 0.00409 RPN total loss: 0.02053 Total loss: 0.85237 timestamp: 1655048335.5772655 iteration: 50105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10068 FastRCNN class loss: 0.0864 FastRCNN total loss: 0.18708 L1 loss: 0.0000e+00 L2 loss: 0.58597 Learning rate: 0.002 Mask loss: 0.11789 RPN box loss: 0.03587 RPN score loss: 0.0056 RPN total loss: 0.04146 Total loss: 0.9324 timestamp: 1655048338.7815905 iteration: 50110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09802 FastRCNN class loss: 0.07177 FastRCNN total loss: 0.16979 L1 loss: 0.0000e+00 L2 loss: 0.58596 Learning rate: 0.002 Mask loss: 0.11922 RPN box loss: 0.00912 RPN score loss: 0.00565 RPN total loss: 0.01477 Total loss: 0.88974 timestamp: 1655048342.0233166 iteration: 50115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1428 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.20677 L1 loss: 0.0000e+00 L2 loss: 0.58595 Learning rate: 0.002 Mask loss: 0.15833 RPN box loss: 0.02476 RPN score loss: 0.00559 RPN total loss: 0.03035 Total loss: 0.9814 timestamp: 1655048345.3219025 iteration: 50120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04958 FastRCNN class loss: 0.03888 FastRCNN total loss: 0.08847 L1 loss: 0.0000e+00 L2 loss: 0.58594 Learning rate: 0.002 Mask loss: 0.09718 RPN box loss: 0.00325 RPN score loss: 0.00089 RPN total loss: 0.00414 Total loss: 0.77573 timestamp: 1655048348.5865934 iteration: 50125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10118 FastRCNN class loss: 0.07147 FastRCNN total loss: 0.17265 L1 loss: 0.0000e+00 L2 loss: 0.58594 Learning rate: 0.002 Mask loss: 0.13302 RPN box loss: 0.00988 RPN score loss: 0.00491 RPN total loss: 0.01479 Total loss: 0.9064 timestamp: 1655048351.8744645 iteration: 50130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.16028 L1 loss: 0.0000e+00 L2 loss: 0.58593 Learning rate: 0.002 Mask loss: 0.17388 RPN box loss: 0.0316 RPN score loss: 0.01327 RPN total loss: 0.04487 Total loss: 0.96496 timestamp: 1655048355.1468494 iteration: 50135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.18529 L1 loss: 0.0000e+00 L2 loss: 0.58592 Learning rate: 0.002 Mask loss: 0.16982 RPN box loss: 0.01587 RPN score loss: 0.00444 RPN total loss: 0.02032 Total loss: 0.96134 timestamp: 1655048358.4497387 iteration: 50140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12393 FastRCNN class loss: 0.08905 FastRCNN total loss: 0.21298 L1 loss: 0.0000e+00 L2 loss: 0.58591 Learning rate: 0.002 Mask loss: 0.12841 RPN box loss: 0.02543 RPN score loss: 0.00259 RPN total loss: 0.02802 Total loss: 0.95532 timestamp: 1655048361.764415 iteration: 50145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10268 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.16288 L1 loss: 0.0000e+00 L2 loss: 0.5859 Learning rate: 0.002 Mask loss: 0.11111 RPN box loss: 0.0048 RPN score loss: 0.00438 RPN total loss: 0.00918 Total loss: 0.86906 timestamp: 1655048364.9658942 iteration: 50150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10492 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.19601 L1 loss: 0.0000e+00 L2 loss: 0.58589 Learning rate: 0.002 Mask loss: 0.11939 RPN box loss: 0.01951 RPN score loss: 0.00469 RPN total loss: 0.0242 Total loss: 0.92549 timestamp: 1655048368.2965567 iteration: 50155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08594 FastRCNN class loss: 0.04603 FastRCNN total loss: 0.13197 L1 loss: 0.0000e+00 L2 loss: 0.58588 Learning rate: 0.002 Mask loss: 0.1012 RPN box loss: 0.00636 RPN score loss: 0.00141 RPN total loss: 0.00777 Total loss: 0.82682 timestamp: 1655048371.5727465 iteration: 50160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10993 FastRCNN class loss: 0.07053 FastRCNN total loss: 0.18046 L1 loss: 0.0000e+00 L2 loss: 0.58587 Learning rate: 0.002 Mask loss: 0.17736 RPN box loss: 0.00919 RPN score loss: 0.00506 RPN total loss: 0.01425 Total loss: 0.95794 timestamp: 1655048374.8766205 iteration: 50165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0972 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.1493 L1 loss: 0.0000e+00 L2 loss: 0.58586 Learning rate: 0.002 Mask loss: 0.1231 RPN box loss: 0.01126 RPN score loss: 0.0081 RPN total loss: 0.01936 Total loss: 0.87762 timestamp: 1655048378.1156592 iteration: 50170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07623 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.15215 L1 loss: 0.0000e+00 L2 loss: 0.58585 Learning rate: 0.002 Mask loss: 0.22891 RPN box loss: 0.01788 RPN score loss: 0.01228 RPN total loss: 0.03016 Total loss: 0.99708 timestamp: 1655048381.4003615 iteration: 50175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08228 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.15149 L1 loss: 0.0000e+00 L2 loss: 0.58584 Learning rate: 0.002 Mask loss: 0.12774 RPN box loss: 0.00726 RPN score loss: 0.00129 RPN total loss: 0.00855 Total loss: 0.87362 timestamp: 1655048384.6233308 iteration: 50180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08646 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.15738 L1 loss: 0.0000e+00 L2 loss: 0.58583 Learning rate: 0.002 Mask loss: 0.15144 RPN box loss: 0.01817 RPN score loss: 0.00648 RPN total loss: 0.02465 Total loss: 0.9193 timestamp: 1655048387.9421022 iteration: 50185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09152 FastRCNN class loss: 0.15234 FastRCNN total loss: 0.24385 L1 loss: 0.0000e+00 L2 loss: 0.58582 Learning rate: 0.002 Mask loss: 0.18568 RPN box loss: 0.0234 RPN score loss: 0.01938 RPN total loss: 0.04278 Total loss: 1.05814 timestamp: 1655048391.2256217 iteration: 50190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10483 FastRCNN class loss: 0.08919 FastRCNN total loss: 0.19402 L1 loss: 0.0000e+00 L2 loss: 0.58581 Learning rate: 0.002 Mask loss: 0.15482 RPN box loss: 0.01551 RPN score loss: 0.00551 RPN total loss: 0.02102 Total loss: 0.95568 timestamp: 1655048394.499281 iteration: 50195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13336 FastRCNN class loss: 0.10081 FastRCNN total loss: 0.23417 L1 loss: 0.0000e+00 L2 loss: 0.5858 Learning rate: 0.002 Mask loss: 0.19488 RPN box loss: 0.02106 RPN score loss: 0.00726 RPN total loss: 0.02832 Total loss: 1.04317 timestamp: 1655048397.769286 iteration: 50200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14385 FastRCNN class loss: 0.10149 FastRCNN total loss: 0.24534 L1 loss: 0.0000e+00 L2 loss: 0.58579 Learning rate: 0.002 Mask loss: 0.128 RPN box loss: 0.01769 RPN score loss: 0.00834 RPN total loss: 0.02603 Total loss: 0.98516 timestamp: 1655048401.0735521 iteration: 50205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09324 FastRCNN class loss: 0.10185 FastRCNN total loss: 0.19508 L1 loss: 0.0000e+00 L2 loss: 0.58578 Learning rate: 0.002 Mask loss: 0.13779 RPN box loss: 0.02802 RPN score loss: 0.00118 RPN total loss: 0.02919 Total loss: 0.94785 timestamp: 1655048404.3567402 iteration: 50210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.07985 FastRCNN total loss: 0.19473 L1 loss: 0.0000e+00 L2 loss: 0.58578 Learning rate: 0.002 Mask loss: 0.2317 RPN box loss: 0.01342 RPN score loss: 0.00659 RPN total loss: 0.02001 Total loss: 1.03221 timestamp: 1655048407.6400304 iteration: 50215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.16168 L1 loss: 0.0000e+00 L2 loss: 0.58577 Learning rate: 0.002 Mask loss: 0.20644 RPN box loss: 0.01167 RPN score loss: 0.0038 RPN total loss: 0.01547 Total loss: 0.96936 timestamp: 1655048410.9534216 iteration: 50220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06296 FastRCNN class loss: 0.04757 FastRCNN total loss: 0.11052 L1 loss: 0.0000e+00 L2 loss: 0.58576 Learning rate: 0.002 Mask loss: 0.08812 RPN box loss: 0.01846 RPN score loss: 0.00319 RPN total loss: 0.02166 Total loss: 0.80606 timestamp: 1655048414.225775 iteration: 50225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0566 FastRCNN class loss: 0.04971 FastRCNN total loss: 0.10631 L1 loss: 0.0000e+00 L2 loss: 0.58575 Learning rate: 0.002 Mask loss: 0.12072 RPN box loss: 0.01194 RPN score loss: 0.00606 RPN total loss: 0.018 Total loss: 0.83077 timestamp: 1655048417.481664 iteration: 50230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.1699 L1 loss: 0.0000e+00 L2 loss: 0.58574 Learning rate: 0.002 Mask loss: 0.21617 RPN box loss: 0.00747 RPN score loss: 0.0058 RPN total loss: 0.01327 Total loss: 0.98508 timestamp: 1655048420.7702818 iteration: 50235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11263 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.17818 L1 loss: 0.0000e+00 L2 loss: 0.58573 Learning rate: 0.002 Mask loss: 0.10435 RPN box loss: 0.00601 RPN score loss: 0.00589 RPN total loss: 0.0119 Total loss: 0.88016 timestamp: 1655048424.0858834 iteration: 50240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12574 FastRCNN class loss: 0.06062 FastRCNN total loss: 0.18636 L1 loss: 0.0000e+00 L2 loss: 0.58572 Learning rate: 0.002 Mask loss: 0.11412 RPN box loss: 0.01884 RPN score loss: 0.00382 RPN total loss: 0.02266 Total loss: 0.90887 timestamp: 1655048427.343044 iteration: 50245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.17164 L1 loss: 0.0000e+00 L2 loss: 0.58571 Learning rate: 0.002 Mask loss: 0.15061 RPN box loss: 0.00998 RPN score loss: 0.00892 RPN total loss: 0.01889 Total loss: 0.92686 timestamp: 1655048430.5735462 iteration: 50250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07049 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.11688 L1 loss: 0.0000e+00 L2 loss: 0.5857 Learning rate: 0.002 Mask loss: 0.10584 RPN box loss: 0.02519 RPN score loss: 0.0009 RPN total loss: 0.02609 Total loss: 0.83451 timestamp: 1655048433.8492572 iteration: 50255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14475 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 0.58569 Learning rate: 0.002 Mask loss: 0.08914 RPN box loss: 0.01177 RPN score loss: 0.00561 RPN total loss: 0.01738 Total loss: 0.89937 timestamp: 1655048437.1065261 iteration: 50260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06251 FastRCNN class loss: 0.06035 FastRCNN total loss: 0.12286 L1 loss: 0.0000e+00 L2 loss: 0.58568 Learning rate: 0.002 Mask loss: 0.13151 RPN box loss: 0.00793 RPN score loss: 0.00124 RPN total loss: 0.00917 Total loss: 0.84922 timestamp: 1655048440.348321 iteration: 50265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10338 FastRCNN class loss: 0.08295 FastRCNN total loss: 0.18633 L1 loss: 0.0000e+00 L2 loss: 0.58567 Learning rate: 0.002 Mask loss: 0.13616 RPN box loss: 0.02565 RPN score loss: 0.00846 RPN total loss: 0.03412 Total loss: 0.94228 timestamp: 1655048443.67396 iteration: 50270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09633 FastRCNN class loss: 0.06651 FastRCNN total loss: 0.16284 L1 loss: 0.0000e+00 L2 loss: 0.58566 Learning rate: 0.002 Mask loss: 0.17925 RPN box loss: 0.01197 RPN score loss: 0.00512 RPN total loss: 0.01709 Total loss: 0.94485 timestamp: 1655048447.020282 iteration: 50275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11821 FastRCNN class loss: 0.0779 FastRCNN total loss: 0.1961 L1 loss: 0.0000e+00 L2 loss: 0.58566 Learning rate: 0.002 Mask loss: 0.16912 RPN box loss: 0.02125 RPN score loss: 0.00256 RPN total loss: 0.02381 Total loss: 0.97469 timestamp: 1655048450.3362956 iteration: 50280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1208 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.18506 L1 loss: 0.0000e+00 L2 loss: 0.58565 Learning rate: 0.002 Mask loss: 0.14189 RPN box loss: 0.00721 RPN score loss: 0.00434 RPN total loss: 0.01156 Total loss: 0.92415 timestamp: 1655048453.56339 iteration: 50285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09736 FastRCNN class loss: 0.0442 FastRCNN total loss: 0.14156 L1 loss: 0.0000e+00 L2 loss: 0.58564 Learning rate: 0.002 Mask loss: 0.09514 RPN box loss: 0.02471 RPN score loss: 0.00566 RPN total loss: 0.03037 Total loss: 0.85271 timestamp: 1655048456.8186245 iteration: 50290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06758 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.13167 L1 loss: 0.0000e+00 L2 loss: 0.58563 Learning rate: 0.002 Mask loss: 0.10985 RPN box loss: 0.0107 RPN score loss: 0.00313 RPN total loss: 0.01383 Total loss: 0.84097 timestamp: 1655048460.077703 iteration: 50295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07039 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.12671 L1 loss: 0.0000e+00 L2 loss: 0.58562 Learning rate: 0.002 Mask loss: 0.14001 RPN box loss: 0.04827 RPN score loss: 0.00901 RPN total loss: 0.05728 Total loss: 0.90962 timestamp: 1655048463.3290462 iteration: 50300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14405 FastRCNN class loss: 0.09759 FastRCNN total loss: 0.24164 L1 loss: 0.0000e+00 L2 loss: 0.58561 Learning rate: 0.002 Mask loss: 0.17134 RPN box loss: 0.0169 RPN score loss: 0.00274 RPN total loss: 0.01964 Total loss: 1.01823 timestamp: 1655048466.6416888 iteration: 50305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11839 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.18146 L1 loss: 0.0000e+00 L2 loss: 0.58561 Learning rate: 0.002 Mask loss: 0.12541 RPN box loss: 0.01334 RPN score loss: 0.00653 RPN total loss: 0.01987 Total loss: 0.91234 timestamp: 1655048469.9564872 iteration: 50310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10668 FastRCNN class loss: 0.07959 FastRCNN total loss: 0.18626 L1 loss: 0.0000e+00 L2 loss: 0.5856 Learning rate: 0.002 Mask loss: 0.15845 RPN box loss: 0.01238 RPN score loss: 0.00243 RPN total loss: 0.01481 Total loss: 0.94512 timestamp: 1655048473.182082 iteration: 50315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.15867 L1 loss: 0.0000e+00 L2 loss: 0.58559 Learning rate: 0.002 Mask loss: 0.15592 RPN box loss: 0.0179 RPN score loss: 0.00125 RPN total loss: 0.01915 Total loss: 0.91933 timestamp: 1655048476.4405591 iteration: 50320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13438 FastRCNN class loss: 0.06793 FastRCNN total loss: 0.20232 L1 loss: 0.0000e+00 L2 loss: 0.58558 Learning rate: 0.002 Mask loss: 0.20676 RPN box loss: 0.01626 RPN score loss: 0.00135 RPN total loss: 0.01762 Total loss: 1.01227 timestamp: 1655048479.7017014 iteration: 50325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07078 FastRCNN class loss: 0.03947 FastRCNN total loss: 0.11025 L1 loss: 0.0000e+00 L2 loss: 0.58557 Learning rate: 0.002 Mask loss: 0.14236 RPN box loss: 0.00978 RPN score loss: 0.00429 RPN total loss: 0.01407 Total loss: 0.85226 timestamp: 1655048482.963768 iteration: 50330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09526 FastRCNN class loss: 0.06001 FastRCNN total loss: 0.15527 L1 loss: 0.0000e+00 L2 loss: 0.58556 Learning rate: 0.002 Mask loss: 0.14548 RPN box loss: 0.01433 RPN score loss: 0.00553 RPN total loss: 0.01986 Total loss: 0.90617 timestamp: 1655048486.299274 iteration: 50335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.09036 FastRCNN total loss: 0.20185 L1 loss: 0.0000e+00 L2 loss: 0.58555 Learning rate: 0.002 Mask loss: 0.14118 RPN box loss: 0.03436 RPN score loss: 0.01718 RPN total loss: 0.05154 Total loss: 0.98012 timestamp: 1655048489.6313405 iteration: 50340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09852 FastRCNN class loss: 0.05406 FastRCNN total loss: 0.15258 L1 loss: 0.0000e+00 L2 loss: 0.58554 Learning rate: 0.002 Mask loss: 0.18795 RPN box loss: 0.01229 RPN score loss: 0.00197 RPN total loss: 0.01426 Total loss: 0.94033 timestamp: 1655048492.8449922 iteration: 50345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06893 FastRCNN class loss: 0.0594 FastRCNN total loss: 0.12833 L1 loss: 0.0000e+00 L2 loss: 0.58553 Learning rate: 0.002 Mask loss: 0.13724 RPN box loss: 0.01115 RPN score loss: 0.00687 RPN total loss: 0.01802 Total loss: 0.86912 timestamp: 1655048496.1146674 iteration: 50350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13595 FastRCNN class loss: 0.13019 FastRCNN total loss: 0.26614 L1 loss: 0.0000e+00 L2 loss: 0.58552 Learning rate: 0.002 Mask loss: 0.25857 RPN box loss: 0.02255 RPN score loss: 0.01221 RPN total loss: 0.03477 Total loss: 1.145 timestamp: 1655048499.4228415 iteration: 50355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07998 FastRCNN class loss: 0.04153 FastRCNN total loss: 0.12151 L1 loss: 0.0000e+00 L2 loss: 0.58552 Learning rate: 0.002 Mask loss: 0.09619 RPN box loss: 0.01045 RPN score loss: 0.0035 RPN total loss: 0.01395 Total loss: 0.81717 timestamp: 1655048502.6914 iteration: 50360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.12437 FastRCNN total loss: 0.2479 L1 loss: 0.0000e+00 L2 loss: 0.58551 Learning rate: 0.002 Mask loss: 0.15786 RPN box loss: 0.02179 RPN score loss: 0.00894 RPN total loss: 0.03073 Total loss: 1.02201 timestamp: 1655048506.0215206 iteration: 50365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11758 FastRCNN class loss: 0.06811 FastRCNN total loss: 0.18569 L1 loss: 0.0000e+00 L2 loss: 0.5855 Learning rate: 0.002 Mask loss: 0.1259 RPN box loss: 0.02038 RPN score loss: 0.00581 RPN total loss: 0.02619 Total loss: 0.92328 timestamp: 1655048509.253885 iteration: 50370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08208 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.15728 L1 loss: 0.0000e+00 L2 loss: 0.58549 Learning rate: 0.002 Mask loss: 0.10225 RPN box loss: 0.01653 RPN score loss: 0.00249 RPN total loss: 0.01902 Total loss: 0.86403 timestamp: 1655048512.576238 iteration: 50375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07636 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.14185 L1 loss: 0.0000e+00 L2 loss: 0.58548 Learning rate: 0.002 Mask loss: 0.18706 RPN box loss: 0.03508 RPN score loss: 0.00365 RPN total loss: 0.03873 Total loss: 0.95312 timestamp: 1655048515.7780633 iteration: 50380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.121 FastRCNN class loss: 0.09813 FastRCNN total loss: 0.21914 L1 loss: 0.0000e+00 L2 loss: 0.58547 Learning rate: 0.002 Mask loss: 0.20368 RPN box loss: 0.03507 RPN score loss: 0.00697 RPN total loss: 0.04204 Total loss: 1.05032 timestamp: 1655048518.9945228 iteration: 50385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18063 FastRCNN class loss: 0.16117 FastRCNN total loss: 0.3418 L1 loss: 0.0000e+00 L2 loss: 0.58546 Learning rate: 0.002 Mask loss: 0.18526 RPN box loss: 0.0277 RPN score loss: 0.02733 RPN total loss: 0.05503 Total loss: 1.16756 timestamp: 1655048522.2747157 iteration: 50390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07053 FastRCNN class loss: 0.04964 FastRCNN total loss: 0.12017 L1 loss: 0.0000e+00 L2 loss: 0.58545 Learning rate: 0.002 Mask loss: 0.27672 RPN box loss: 0.01849 RPN score loss: 0.0016 RPN total loss: 0.02009 Total loss: 1.00243 timestamp: 1655048525.4776394 iteration: 50395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10024 FastRCNN class loss: 0.13654 FastRCNN total loss: 0.23678 L1 loss: 0.0000e+00 L2 loss: 0.58544 Learning rate: 0.002 Mask loss: 0.13722 RPN box loss: 0.01503 RPN score loss: 0.00468 RPN total loss: 0.01971 Total loss: 0.97915 timestamp: 1655048528.7665694 iteration: 50400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07347 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.12485 L1 loss: 0.0000e+00 L2 loss: 0.58543 Learning rate: 0.002 Mask loss: 0.11321 RPN box loss: 0.00609 RPN score loss: 0.00229 RPN total loss: 0.00838 Total loss: 0.83187 timestamp: 1655048532.045235 iteration: 50405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07507 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.15146 L1 loss: 0.0000e+00 L2 loss: 0.58542 Learning rate: 0.002 Mask loss: 0.1359 RPN box loss: 0.00619 RPN score loss: 0.00334 RPN total loss: 0.00952 Total loss: 0.88231 timestamp: 1655048535.3519754 iteration: 50410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11372 FastRCNN class loss: 0.09378 FastRCNN total loss: 0.20751 L1 loss: 0.0000e+00 L2 loss: 0.58541 Learning rate: 0.002 Mask loss: 0.14727 RPN box loss: 0.02872 RPN score loss: 0.00602 RPN total loss: 0.03474 Total loss: 0.97492 timestamp: 1655048538.6280813 iteration: 50415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08557 FastRCNN class loss: 0.07615 FastRCNN total loss: 0.16172 L1 loss: 0.0000e+00 L2 loss: 0.58541 Learning rate: 0.002 Mask loss: 0.11891 RPN box loss: 0.01396 RPN score loss: 0.01222 RPN total loss: 0.02618 Total loss: 0.89222 timestamp: 1655048541.9096086 iteration: 50420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.14664 L1 loss: 0.0000e+00 L2 loss: 0.5854 Learning rate: 0.002 Mask loss: 0.14025 RPN box loss: 0.00846 RPN score loss: 0.00171 RPN total loss: 0.01016 Total loss: 0.88245 timestamp: 1655048545.2042987 iteration: 50425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07664 FastRCNN class loss: 0.06612 FastRCNN total loss: 0.14275 L1 loss: 0.0000e+00 L2 loss: 0.58539 Learning rate: 0.002 Mask loss: 0.15782 RPN box loss: 0.02202 RPN score loss: 0.00983 RPN total loss: 0.03185 Total loss: 0.91781 timestamp: 1655048548.497433 iteration: 50430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17711 FastRCNN class loss: 0.09638 FastRCNN total loss: 0.27349 L1 loss: 0.0000e+00 L2 loss: 0.58538 Learning rate: 0.002 Mask loss: 0.1752 RPN box loss: 0.02179 RPN score loss: 0.00452 RPN total loss: 0.0263 Total loss: 1.06037 timestamp: 1655048551.7236013 iteration: 50435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08992 FastRCNN class loss: 0.07969 FastRCNN total loss: 0.16961 L1 loss: 0.0000e+00 L2 loss: 0.58537 Learning rate: 0.002 Mask loss: 0.19229 RPN box loss: 0.02243 RPN score loss: 0.00662 RPN total loss: 0.02905 Total loss: 0.97632 timestamp: 1655048555.0298138 iteration: 50440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.1664 L1 loss: 0.0000e+00 L2 loss: 0.58536 Learning rate: 0.002 Mask loss: 0.17151 RPN box loss: 0.01131 RPN score loss: 0.00356 RPN total loss: 0.01487 Total loss: 0.93814 timestamp: 1655048558.28941 iteration: 50445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1208 FastRCNN class loss: 0.07169 FastRCNN total loss: 0.19249 L1 loss: 0.0000e+00 L2 loss: 0.58535 Learning rate: 0.002 Mask loss: 0.15357 RPN box loss: 0.01053 RPN score loss: 0.00772 RPN total loss: 0.01825 Total loss: 0.94965 timestamp: 1655048561.5210857 iteration: 50450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07813 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.13645 L1 loss: 0.0000e+00 L2 loss: 0.58535 Learning rate: 0.002 Mask loss: 0.15162 RPN box loss: 0.00958 RPN score loss: 0.00902 RPN total loss: 0.0186 Total loss: 0.89201 timestamp: 1655048564.8612309 iteration: 50455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13838 FastRCNN class loss: 0.18156 FastRCNN total loss: 0.31993 L1 loss: 0.0000e+00 L2 loss: 0.58534 Learning rate: 0.002 Mask loss: 0.18153 RPN box loss: 0.03327 RPN score loss: 0.01284 RPN total loss: 0.04611 Total loss: 1.13291 timestamp: 1655048568.1962907 iteration: 50460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.17236 L1 loss: 0.0000e+00 L2 loss: 0.58533 Learning rate: 0.002 Mask loss: 0.14774 RPN box loss: 0.01956 RPN score loss: 0.00923 RPN total loss: 0.02879 Total loss: 0.93422 timestamp: 1655048571.5053217 iteration: 50465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08382 FastRCNN class loss: 0.03923 FastRCNN total loss: 0.12305 L1 loss: 0.0000e+00 L2 loss: 0.58532 Learning rate: 0.002 Mask loss: 0.11463 RPN box loss: 0.0025 RPN score loss: 0.00207 RPN total loss: 0.00457 Total loss: 0.82757 timestamp: 1655048574.7686732 iteration: 50470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.08569 FastRCNN total loss: 0.18281 L1 loss: 0.0000e+00 L2 loss: 0.58531 Learning rate: 0.002 Mask loss: 0.13667 RPN box loss: 0.01832 RPN score loss: 0.01729 RPN total loss: 0.0356 Total loss: 0.94039 timestamp: 1655048578.0579386 iteration: 50475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08919 FastRCNN class loss: 0.06343 FastRCNN total loss: 0.15262 L1 loss: 0.0000e+00 L2 loss: 0.5853 Learning rate: 0.002 Mask loss: 0.13642 RPN box loss: 0.01423 RPN score loss: 0.00071 RPN total loss: 0.01493 Total loss: 0.88928 timestamp: 1655048581.3181124 iteration: 50480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11799 FastRCNN class loss: 0.10053 FastRCNN total loss: 0.21852 L1 loss: 0.0000e+00 L2 loss: 0.58529 Learning rate: 0.002 Mask loss: 0.1576 RPN box loss: 0.02559 RPN score loss: 0.00923 RPN total loss: 0.03481 Total loss: 0.99623 timestamp: 1655048584.698911 iteration: 50485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.18341 L1 loss: 0.0000e+00 L2 loss: 0.58529 Learning rate: 0.002 Mask loss: 0.1359 RPN box loss: 0.016 RPN score loss: 0.01121 RPN total loss: 0.02722 Total loss: 0.93181 timestamp: 1655048587.9676752 iteration: 50490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0826 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.14189 L1 loss: 0.0000e+00 L2 loss: 0.58528 Learning rate: 0.002 Mask loss: 0.12772 RPN box loss: 0.0299 RPN score loss: 0.00861 RPN total loss: 0.03851 Total loss: 0.89339 timestamp: 1655048591.1870341 iteration: 50495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.08485 FastRCNN total loss: 0.20202 L1 loss: 0.0000e+00 L2 loss: 0.58527 Learning rate: 0.002 Mask loss: 0.16599 RPN box loss: 0.01649 RPN score loss: 0.00343 RPN total loss: 0.01992 Total loss: 0.9732 timestamp: 1655048594.4235213 iteration: 50500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14093 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.21997 L1 loss: 0.0000e+00 L2 loss: 0.58526 Learning rate: 0.002 Mask loss: 0.14981 RPN box loss: 0.01399 RPN score loss: 0.00325 RPN total loss: 0.01723 Total loss: 0.97228 timestamp: 1655048597.7430382 iteration: 50505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07344 FastRCNN class loss: 0.04286 FastRCNN total loss: 0.1163 L1 loss: 0.0000e+00 L2 loss: 0.58526 Learning rate: 0.002 Mask loss: 0.13033 RPN box loss: 0.00367 RPN score loss: 0.00195 RPN total loss: 0.00562 Total loss: 0.8375 timestamp: 1655048600.9462729 iteration: 50510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13565 FastRCNN class loss: 0.08201 FastRCNN total loss: 0.21765 L1 loss: 0.0000e+00 L2 loss: 0.58525 Learning rate: 0.002 Mask loss: 0.13268 RPN box loss: 0.01189 RPN score loss: 0.00445 RPN total loss: 0.01633 Total loss: 0.95191 timestamp: 1655048604.1909845 iteration: 50515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.1277 FastRCNN total loss: 0.26177 L1 loss: 0.0000e+00 L2 loss: 0.58524 Learning rate: 0.002 Mask loss: 0.17041 RPN box loss: 0.01992 RPN score loss: 0.00564 RPN total loss: 0.02557 Total loss: 1.04298 timestamp: 1655048607.4778478 iteration: 50520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0595 FastRCNN class loss: 0.03218 FastRCNN total loss: 0.09168 L1 loss: 0.0000e+00 L2 loss: 0.58523 Learning rate: 0.002 Mask loss: 0.1346 RPN box loss: 0.02155 RPN score loss: 0.00154 RPN total loss: 0.02309 Total loss: 0.8346 timestamp: 1655048610.7784295 iteration: 50525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16269 FastRCNN class loss: 0.08369 FastRCNN total loss: 0.24638 L1 loss: 0.0000e+00 L2 loss: 0.58522 Learning rate: 0.002 Mask loss: 0.13345 RPN box loss: 0.0151 RPN score loss: 0.00276 RPN total loss: 0.01786 Total loss: 0.98291 timestamp: 1655048614.0017018 iteration: 50530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09056 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.16256 L1 loss: 0.0000e+00 L2 loss: 0.58521 Learning rate: 0.002 Mask loss: 0.16031 RPN box loss: 0.021 RPN score loss: 0.00289 RPN total loss: 0.02388 Total loss: 0.93197 timestamp: 1655048617.2765014 iteration: 50535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09818 FastRCNN class loss: 0.06339 FastRCNN total loss: 0.16157 L1 loss: 0.0000e+00 L2 loss: 0.5852 Learning rate: 0.002 Mask loss: 0.15659 RPN box loss: 0.01675 RPN score loss: 0.00231 RPN total loss: 0.01906 Total loss: 0.92242 timestamp: 1655048620.6216397 iteration: 50540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.04292 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.58519 Learning rate: 0.002 Mask loss: 0.06875 RPN box loss: 0.0056 RPN score loss: 0.00266 RPN total loss: 0.00826 Total loss: 0.78228 timestamp: 1655048624.0344584 iteration: 50545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14359 FastRCNN class loss: 0.07064 FastRCNN total loss: 0.21423 L1 loss: 0.0000e+00 L2 loss: 0.58518 Learning rate: 0.002 Mask loss: 0.17522 RPN box loss: 0.04849 RPN score loss: 0.01888 RPN total loss: 0.06737 Total loss: 1.04201 timestamp: 1655048627.3428729 iteration: 50550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10601 FastRCNN class loss: 0.0665 FastRCNN total loss: 0.17251 L1 loss: 0.0000e+00 L2 loss: 0.58517 Learning rate: 0.002 Mask loss: 0.11927 RPN box loss: 0.02037 RPN score loss: 0.00723 RPN total loss: 0.0276 Total loss: 0.90455 timestamp: 1655048630.5909932 iteration: 50555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07863 FastRCNN class loss: 0.06763 FastRCNN total loss: 0.14626 L1 loss: 0.0000e+00 L2 loss: 0.58516 Learning rate: 0.002 Mask loss: 0.16587 RPN box loss: 0.01966 RPN score loss: 0.00678 RPN total loss: 0.02644 Total loss: 0.92373 timestamp: 1655048633.9123166 iteration: 50560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16866 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.29811 L1 loss: 0.0000e+00 L2 loss: 0.58516 Learning rate: 0.002 Mask loss: 0.20754 RPN box loss: 0.01913 RPN score loss: 0.00943 RPN total loss: 0.02856 Total loss: 1.11937 timestamp: 1655048637.1873374 iteration: 50565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06147 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.11791 L1 loss: 0.0000e+00 L2 loss: 0.58515 Learning rate: 0.002 Mask loss: 0.15548 RPN box loss: 0.01118 RPN score loss: 0.00296 RPN total loss: 0.01413 Total loss: 0.87268 timestamp: 1655048640.465754 iteration: 50570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11526 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.19776 L1 loss: 0.0000e+00 L2 loss: 0.58514 Learning rate: 0.002 Mask loss: 0.28606 RPN box loss: 0.00483 RPN score loss: 0.00519 RPN total loss: 0.01002 Total loss: 1.07899 timestamp: 1655048643.7535293 iteration: 50575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06734 FastRCNN class loss: 0.03933 FastRCNN total loss: 0.10667 L1 loss: 0.0000e+00 L2 loss: 0.58513 Learning rate: 0.002 Mask loss: 0.16821 RPN box loss: 0.0224 RPN score loss: 0.0037 RPN total loss: 0.02609 Total loss: 0.88611 timestamp: 1655048646.9848828 iteration: 50580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10778 FastRCNN class loss: 0.08347 FastRCNN total loss: 0.19124 L1 loss: 0.0000e+00 L2 loss: 0.58512 Learning rate: 0.002 Mask loss: 0.14722 RPN box loss: 0.01197 RPN score loss: 0.00274 RPN total loss: 0.01471 Total loss: 0.9383 timestamp: 1655048650.2799864 iteration: 50585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16416 FastRCNN class loss: 0.10931 FastRCNN total loss: 0.27347 L1 loss: 0.0000e+00 L2 loss: 0.58511 Learning rate: 0.002 Mask loss: 0.25488 RPN box loss: 0.00942 RPN score loss: 0.00553 RPN total loss: 0.01495 Total loss: 1.12841 timestamp: 1655048653.603505 iteration: 50590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08553 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.15121 L1 loss: 0.0000e+00 L2 loss: 0.5851 Learning rate: 0.002 Mask loss: 0.15145 RPN box loss: 0.01532 RPN score loss: 0.00361 RPN total loss: 0.01893 Total loss: 0.90671 timestamp: 1655048656.890728 iteration: 50595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12016 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.18224 L1 loss: 0.0000e+00 L2 loss: 0.58509 Learning rate: 0.002 Mask loss: 0.11607 RPN box loss: 0.01835 RPN score loss: 0.00846 RPN total loss: 0.02681 Total loss: 0.91022 timestamp: 1655048660.1850007 iteration: 50600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16595 FastRCNN class loss: 0.07333 FastRCNN total loss: 0.23928 L1 loss: 0.0000e+00 L2 loss: 0.58509 Learning rate: 0.002 Mask loss: 0.12596 RPN box loss: 0.03052 RPN score loss: 0.01108 RPN total loss: 0.0416 Total loss: 0.99193 timestamp: 1655048663.4515014 iteration: 50605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12652 FastRCNN class loss: 0.05716 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 0.58508 Learning rate: 0.002 Mask loss: 0.09858 RPN box loss: 0.01671 RPN score loss: 0.01054 RPN total loss: 0.02725 Total loss: 0.89459 timestamp: 1655048666.730863 iteration: 50610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11807 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.18334 L1 loss: 0.0000e+00 L2 loss: 0.58507 Learning rate: 0.002 Mask loss: 0.1157 RPN box loss: 0.0439 RPN score loss: 0.00886 RPN total loss: 0.05276 Total loss: 0.93687 timestamp: 1655048670.0176518 iteration: 50615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13523 FastRCNN class loss: 0.06907 FastRCNN total loss: 0.2043 L1 loss: 0.0000e+00 L2 loss: 0.58506 Learning rate: 0.002 Mask loss: 0.17634 RPN box loss: 0.04712 RPN score loss: 0.00437 RPN total loss: 0.0515 Total loss: 1.01719 timestamp: 1655048673.3170588 iteration: 50620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08885 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.1765 L1 loss: 0.0000e+00 L2 loss: 0.58505 Learning rate: 0.002 Mask loss: 0.16006 RPN box loss: 0.01137 RPN score loss: 0.00516 RPN total loss: 0.01653 Total loss: 0.93814 timestamp: 1655048676.6689746 iteration: 50625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08078 FastRCNN class loss: 0.05251 FastRCNN total loss: 0.13329 L1 loss: 0.0000e+00 L2 loss: 0.58504 Learning rate: 0.002 Mask loss: 0.1297 RPN box loss: 0.0147 RPN score loss: 0.00296 RPN total loss: 0.01765 Total loss: 0.86568 timestamp: 1655048679.8868685 iteration: 50630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07592 FastRCNN class loss: 0.03725 FastRCNN total loss: 0.11317 L1 loss: 0.0000e+00 L2 loss: 0.58503 Learning rate: 0.002 Mask loss: 0.10858 RPN box loss: 0.02371 RPN score loss: 0.02147 RPN total loss: 0.04518 Total loss: 0.85196 timestamp: 1655048683.1369774 iteration: 50635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0867 FastRCNN class loss: 0.06203 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 0.58502 Learning rate: 0.002 Mask loss: 0.11605 RPN box loss: 0.00876 RPN score loss: 0.00064 RPN total loss: 0.0094 Total loss: 0.85921 timestamp: 1655048686.4649615 iteration: 50640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13112 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.22455 L1 loss: 0.0000e+00 L2 loss: 0.58502 Learning rate: 0.002 Mask loss: 0.17288 RPN box loss: 0.02797 RPN score loss: 0.00346 RPN total loss: 0.03143 Total loss: 1.01387 timestamp: 1655048689.7335796 iteration: 50645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17127 FastRCNN class loss: 0.08183 FastRCNN total loss: 0.25309 L1 loss: 0.0000e+00 L2 loss: 0.58501 Learning rate: 0.002 Mask loss: 0.1662 RPN box loss: 0.0174 RPN score loss: 0.00353 RPN total loss: 0.02093 Total loss: 1.02523 timestamp: 1655048693.0008075 iteration: 50650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08267 FastRCNN class loss: 0.05598 FastRCNN total loss: 0.13864 L1 loss: 0.0000e+00 L2 loss: 0.585 Learning rate: 0.002 Mask loss: 0.15585 RPN box loss: 0.02576 RPN score loss: 0.00441 RPN total loss: 0.03017 Total loss: 0.90966 timestamp: 1655048696.2741911 iteration: 50655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.05565 FastRCNN total loss: 0.11786 L1 loss: 0.0000e+00 L2 loss: 0.58499 Learning rate: 0.002 Mask loss: 0.10868 RPN box loss: 0.0091 RPN score loss: 0.0012 RPN total loss: 0.0103 Total loss: 0.82184 timestamp: 1655048699.5717363 iteration: 50660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09413 FastRCNN class loss: 0.09197 FastRCNN total loss: 0.1861 L1 loss: 0.0000e+00 L2 loss: 0.58498 Learning rate: 0.002 Mask loss: 0.16948 RPN box loss: 0.02915 RPN score loss: 0.00565 RPN total loss: 0.0348 Total loss: 0.97536 timestamp: 1655048702.8970346 iteration: 50665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.05229 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.58498 Learning rate: 0.002 Mask loss: 0.13078 RPN box loss: 0.0155 RPN score loss: 0.00277 RPN total loss: 0.01827 Total loss: 0.87644 timestamp: 1655048706.2041466 iteration: 50670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12951 FastRCNN class loss: 0.08834 FastRCNN total loss: 0.21784 L1 loss: 0.0000e+00 L2 loss: 0.58497 Learning rate: 0.002 Mask loss: 0.12892 RPN box loss: 0.01755 RPN score loss: 0.00215 RPN total loss: 0.01969 Total loss: 0.95143 timestamp: 1655048709.467368 iteration: 50675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11914 FastRCNN class loss: 0.04467 FastRCNN total loss: 0.16381 L1 loss: 0.0000e+00 L2 loss: 0.58496 Learning rate: 0.002 Mask loss: 0.15733 RPN box loss: 0.00301 RPN score loss: 0.00139 RPN total loss: 0.0044 Total loss: 0.9105 timestamp: 1655048712.7498205 iteration: 50680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17234 FastRCNN class loss: 0.07164 FastRCNN total loss: 0.24398 L1 loss: 0.0000e+00 L2 loss: 0.58495 Learning rate: 0.002 Mask loss: 0.10933 RPN box loss: 0.02224 RPN score loss: 0.00277 RPN total loss: 0.02501 Total loss: 0.96327 timestamp: 1655048716.0680535 iteration: 50685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14842 FastRCNN class loss: 0.07101 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.58495 Learning rate: 0.002 Mask loss: 0.16121 RPN box loss: 0.03164 RPN score loss: 0.00564 RPN total loss: 0.03728 Total loss: 1.00288 timestamp: 1655048719.2842479 iteration: 50690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15688 FastRCNN class loss: 0.12113 FastRCNN total loss: 0.27801 L1 loss: 0.0000e+00 L2 loss: 0.58494 Learning rate: 0.002 Mask loss: 0.17443 RPN box loss: 0.02454 RPN score loss: 0.00426 RPN total loss: 0.0288 Total loss: 1.06618 timestamp: 1655048722.5854137 iteration: 50695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11526 FastRCNN class loss: 0.0976 FastRCNN total loss: 0.21287 L1 loss: 0.0000e+00 L2 loss: 0.58493 Learning rate: 0.002 Mask loss: 0.2279 RPN box loss: 0.0267 RPN score loss: 0.00289 RPN total loss: 0.0296 Total loss: 1.0553 timestamp: 1655048725.840508 iteration: 50700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1187 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.18802 L1 loss: 0.0000e+00 L2 loss: 0.58492 Learning rate: 0.002 Mask loss: 0.16577 RPN box loss: 0.01714 RPN score loss: 0.00826 RPN total loss: 0.0254 Total loss: 0.96411 timestamp: 1655048729.1443813 iteration: 50705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05705 FastRCNN class loss: 0.04212 FastRCNN total loss: 0.09917 L1 loss: 0.0000e+00 L2 loss: 0.58492 Learning rate: 0.002 Mask loss: 0.07826 RPN box loss: 0.00378 RPN score loss: 0.00216 RPN total loss: 0.00594 Total loss: 0.76829 timestamp: 1655048732.397715 iteration: 50710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07407 FastRCNN class loss: 0.05337 FastRCNN total loss: 0.12744 L1 loss: 0.0000e+00 L2 loss: 0.58491 Learning rate: 0.002 Mask loss: 0.13277 RPN box loss: 0.00645 RPN score loss: 0.00213 RPN total loss: 0.00857 Total loss: 0.85368 timestamp: 1655048735.626663 iteration: 50715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08938 FastRCNN class loss: 0.04493 FastRCNN total loss: 0.13431 L1 loss: 0.0000e+00 L2 loss: 0.5849 Learning rate: 0.002 Mask loss: 0.12309 RPN box loss: 0.01382 RPN score loss: 0.00254 RPN total loss: 0.01636 Total loss: 0.85866 timestamp: 1655048738.9551435 iteration: 50720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.29825 FastRCNN class loss: 0.08961 FastRCNN total loss: 0.38786 L1 loss: 0.0000e+00 L2 loss: 0.58489 Learning rate: 0.002 Mask loss: 0.13559 RPN box loss: 0.02158 RPN score loss: 0.01281 RPN total loss: 0.03439 Total loss: 1.14273 timestamp: 1655048742.2666645 iteration: 50725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0673 FastRCNN class loss: 0.03546 FastRCNN total loss: 0.10276 L1 loss: 0.0000e+00 L2 loss: 0.58488 Learning rate: 0.002 Mask loss: 0.12292 RPN box loss: 0.01379 RPN score loss: 0.00181 RPN total loss: 0.0156 Total loss: 0.82616 timestamp: 1655048745.5932975 iteration: 50730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08962 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.15068 L1 loss: 0.0000e+00 L2 loss: 0.58487 Learning rate: 0.002 Mask loss: 0.13561 RPN box loss: 0.02691 RPN score loss: 0.00615 RPN total loss: 0.03305 Total loss: 0.90421 timestamp: 1655048748.9260125 iteration: 50735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.07848 FastRCNN total loss: 0.1625 L1 loss: 0.0000e+00 L2 loss: 0.58485 Learning rate: 0.002 Mask loss: 0.10208 RPN box loss: 0.00858 RPN score loss: 0.00232 RPN total loss: 0.0109 Total loss: 0.86033 timestamp: 1655048752.2457178 iteration: 50740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06615 FastRCNN class loss: 0.039 FastRCNN total loss: 0.10515 L1 loss: 0.0000e+00 L2 loss: 0.58484 Learning rate: 0.002 Mask loss: 0.10597 RPN box loss: 0.00897 RPN score loss: 0.00258 RPN total loss: 0.01154 Total loss: 0.8075 timestamp: 1655048755.5373197 iteration: 50745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.05921 FastRCNN total loss: 0.12541 L1 loss: 0.0000e+00 L2 loss: 0.58483 Learning rate: 0.002 Mask loss: 0.13407 RPN box loss: 0.02227 RPN score loss: 0.00336 RPN total loss: 0.02564 Total loss: 0.86995 timestamp: 1655048758.8237076 iteration: 50750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12822 FastRCNN class loss: 0.11872 FastRCNN total loss: 0.24694 L1 loss: 0.0000e+00 L2 loss: 0.58482 Learning rate: 0.002 Mask loss: 0.15402 RPN box loss: 0.02738 RPN score loss: 0.01388 RPN total loss: 0.04126 Total loss: 1.02704 timestamp: 1655048762.1564267 iteration: 50755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09709 FastRCNN class loss: 0.13568 FastRCNN total loss: 0.23277 L1 loss: 0.0000e+00 L2 loss: 0.58481 Learning rate: 0.002 Mask loss: 0.1847 RPN box loss: 0.02609 RPN score loss: 0.00942 RPN total loss: 0.03551 Total loss: 1.0378 timestamp: 1655048765.4683497 iteration: 50760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07723 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.14934 L1 loss: 0.0000e+00 L2 loss: 0.5848 Learning rate: 0.002 Mask loss: 0.13857 RPN box loss: 0.01178 RPN score loss: 0.00515 RPN total loss: 0.01694 Total loss: 0.88966 timestamp: 1655048768.7428944 iteration: 50765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17793 FastRCNN class loss: 0.07792 FastRCNN total loss: 0.25584 L1 loss: 0.0000e+00 L2 loss: 0.5848 Learning rate: 0.002 Mask loss: 0.18416 RPN box loss: 0.02023 RPN score loss: 0.00451 RPN total loss: 0.02473 Total loss: 1.04954 timestamp: 1655048772.0779507 iteration: 50770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20271 FastRCNN class loss: 0.09566 FastRCNN total loss: 0.29838 L1 loss: 0.0000e+00 L2 loss: 0.58479 Learning rate: 0.002 Mask loss: 0.1734 RPN box loss: 0.01793 RPN score loss: 0.00323 RPN total loss: 0.02115 Total loss: 1.07772 timestamp: 1655048775.3700511 iteration: 50775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08506 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.14414 L1 loss: 0.0000e+00 L2 loss: 0.58478 Learning rate: 0.002 Mask loss: 0.11773 RPN box loss: 0.02472 RPN score loss: 0.00705 RPN total loss: 0.03177 Total loss: 0.87842 timestamp: 1655048778.652012 iteration: 50780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06831 FastRCNN class loss: 0.03965 FastRCNN total loss: 0.10796 L1 loss: 0.0000e+00 L2 loss: 0.58477 Learning rate: 0.002 Mask loss: 0.14763 RPN box loss: 0.00721 RPN score loss: 0.00219 RPN total loss: 0.00939 Total loss: 0.84976 timestamp: 1655048781.924312 iteration: 50785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09811 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.1612 L1 loss: 0.0000e+00 L2 loss: 0.58476 Learning rate: 0.002 Mask loss: 0.16618 RPN box loss: 0.01525 RPN score loss: 0.01256 RPN total loss: 0.02781 Total loss: 0.93996 timestamp: 1655048785.1122844 iteration: 50790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07325 FastRCNN class loss: 0.083 FastRCNN total loss: 0.15625 L1 loss: 0.0000e+00 L2 loss: 0.58475 Learning rate: 0.002 Mask loss: 0.12506 RPN box loss: 0.01125 RPN score loss: 0.00791 RPN total loss: 0.01917 Total loss: 0.88523 timestamp: 1655048788.4028397 iteration: 50795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05881 FastRCNN class loss: 0.06928 FastRCNN total loss: 0.12809 L1 loss: 0.0000e+00 L2 loss: 0.58474 Learning rate: 0.002 Mask loss: 0.15895 RPN box loss: 0.01219 RPN score loss: 0.00325 RPN total loss: 0.01544 Total loss: 0.88721 timestamp: 1655048791.701698 iteration: 50800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20069 FastRCNN class loss: 0.07414 FastRCNN total loss: 0.27483 L1 loss: 0.0000e+00 L2 loss: 0.58474 Learning rate: 0.002 Mask loss: 0.11448 RPN box loss: 0.01821 RPN score loss: 0.00282 RPN total loss: 0.02103 Total loss: 0.99508 timestamp: 1655048794.924972 iteration: 50805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14947 FastRCNN class loss: 0.09821 FastRCNN total loss: 0.24767 L1 loss: 0.0000e+00 L2 loss: 0.58473 Learning rate: 0.002 Mask loss: 0.17154 RPN box loss: 0.0196 RPN score loss: 0.00483 RPN total loss: 0.02443 Total loss: 1.02837 timestamp: 1655048798.14966 iteration: 50810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08785 FastRCNN class loss: 0.03648 FastRCNN total loss: 0.12433 L1 loss: 0.0000e+00 L2 loss: 0.58472 Learning rate: 0.002 Mask loss: 0.12485 RPN box loss: 0.00434 RPN score loss: 0.00285 RPN total loss: 0.0072 Total loss: 0.8411 timestamp: 1655048801.439406 iteration: 50815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08594 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.14563 L1 loss: 0.0000e+00 L2 loss: 0.58471 Learning rate: 0.002 Mask loss: 0.16573 RPN box loss: 0.03588 RPN score loss: 0.00734 RPN total loss: 0.04322 Total loss: 0.93929 timestamp: 1655048804.6260035 iteration: 50820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11885 FastRCNN class loss: 0.09798 FastRCNN total loss: 0.21683 L1 loss: 0.0000e+00 L2 loss: 0.5847 Learning rate: 0.002 Mask loss: 0.17217 RPN box loss: 0.01269 RPN score loss: 0.00734 RPN total loss: 0.02003 Total loss: 0.99373 timestamp: 1655048807.8860066 iteration: 50825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15924 FastRCNN class loss: 0.08274 FastRCNN total loss: 0.24197 L1 loss: 0.0000e+00 L2 loss: 0.5847 Learning rate: 0.002 Mask loss: 0.16765 RPN box loss: 0.0214 RPN score loss: 0.00917 RPN total loss: 0.03057 Total loss: 1.02489 timestamp: 1655048811.0979857 iteration: 50830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08978 FastRCNN class loss: 0.08484 FastRCNN total loss: 0.17463 L1 loss: 0.0000e+00 L2 loss: 0.58469 Learning rate: 0.002 Mask loss: 0.14803 RPN box loss: 0.00739 RPN score loss: 0.00693 RPN total loss: 0.01432 Total loss: 0.92167 timestamp: 1655048814.35848 iteration: 50835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05973 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.12632 L1 loss: 0.0000e+00 L2 loss: 0.58468 Learning rate: 0.002 Mask loss: 0.11303 RPN box loss: 0.01143 RPN score loss: 0.00534 RPN total loss: 0.01677 Total loss: 0.84079 timestamp: 1655048817.5527902 iteration: 50840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1208 FastRCNN class loss: 0.06093 FastRCNN total loss: 0.18173 L1 loss: 0.0000e+00 L2 loss: 0.58467 Learning rate: 0.002 Mask loss: 0.13868 RPN box loss: 0.01003 RPN score loss: 0.00386 RPN total loss: 0.01389 Total loss: 0.91896 timestamp: 1655048820.7776046 iteration: 50845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06594 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.12988 L1 loss: 0.0000e+00 L2 loss: 0.58466 Learning rate: 0.002 Mask loss: 0.10663 RPN box loss: 0.00978 RPN score loss: 0.00157 RPN total loss: 0.01135 Total loss: 0.83251 timestamp: 1655048824.0857656 iteration: 50850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06569 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.13704 L1 loss: 0.0000e+00 L2 loss: 0.58465 Learning rate: 0.002 Mask loss: 0.10498 RPN box loss: 0.02406 RPN score loss: 0.004 RPN total loss: 0.02806 Total loss: 0.85473 timestamp: 1655048827.372383 iteration: 50855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09788 FastRCNN class loss: 0.08946 FastRCNN total loss: 0.18734 L1 loss: 0.0000e+00 L2 loss: 0.58464 Learning rate: 0.002 Mask loss: 0.12952 RPN box loss: 0.012 RPN score loss: 0.00222 RPN total loss: 0.01422 Total loss: 0.91572 timestamp: 1655048830.6144836 iteration: 50860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11703 FastRCNN class loss: 0.10624 FastRCNN total loss: 0.22327 L1 loss: 0.0000e+00 L2 loss: 0.58463 Learning rate: 0.002 Mask loss: 0.16039 RPN box loss: 0.02659 RPN score loss: 0.00817 RPN total loss: 0.03476 Total loss: 1.00305 timestamp: 1655048833.9103174 iteration: 50865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.15916 L1 loss: 0.0000e+00 L2 loss: 0.58462 Learning rate: 0.002 Mask loss: 0.15898 RPN box loss: 0.0202 RPN score loss: 0.0012 RPN total loss: 0.02141 Total loss: 0.92417 timestamp: 1655048837.1847513 iteration: 50870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11362 FastRCNN class loss: 0.09789 FastRCNN total loss: 0.21151 L1 loss: 0.0000e+00 L2 loss: 0.58461 Learning rate: 0.002 Mask loss: 0.1819 RPN box loss: 0.02918 RPN score loss: 0.00898 RPN total loss: 0.03816 Total loss: 1.01618 timestamp: 1655048840.458056 iteration: 50875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11766 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.20428 L1 loss: 0.0000e+00 L2 loss: 0.5846 Learning rate: 0.002 Mask loss: 0.14361 RPN box loss: 0.01487 RPN score loss: 0.00497 RPN total loss: 0.01984 Total loss: 0.95233 timestamp: 1655048843.728391 iteration: 50880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13386 FastRCNN class loss: 0.11416 FastRCNN total loss: 0.24802 L1 loss: 0.0000e+00 L2 loss: 0.58459 Learning rate: 0.002 Mask loss: 0.24612 RPN box loss: 0.03391 RPN score loss: 0.01182 RPN total loss: 0.04574 Total loss: 1.12447 timestamp: 1655048846.9617627 iteration: 50885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1115 FastRCNN class loss: 0.11812 FastRCNN total loss: 0.22962 L1 loss: 0.0000e+00 L2 loss: 0.58458 Learning rate: 0.002 Mask loss: 0.13618 RPN box loss: 0.01069 RPN score loss: 0.0067 RPN total loss: 0.01739 Total loss: 0.96778 timestamp: 1655048850.2919407 iteration: 50890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.58458 Learning rate: 0.002 Mask loss: 0.16898 RPN box loss: 0.01327 RPN score loss: 0.01073 RPN total loss: 0.024 Total loss: 0.94229 timestamp: 1655048853.5545273 iteration: 50895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08124 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.14216 L1 loss: 0.0000e+00 L2 loss: 0.58457 Learning rate: 0.002 Mask loss: 0.10001 RPN box loss: 0.00916 RPN score loss: 0.00469 RPN total loss: 0.01385 Total loss: 0.84059 timestamp: 1655048856.868389 iteration: 50900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12027 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.19624 L1 loss: 0.0000e+00 L2 loss: 0.58456 Learning rate: 0.002 Mask loss: 0.19257 RPN box loss: 0.00938 RPN score loss: 0.0232 RPN total loss: 0.03258 Total loss: 1.00596 timestamp: 1655048860.1001325 iteration: 50905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08521 FastRCNN class loss: 0.0375 FastRCNN total loss: 0.12271 L1 loss: 0.0000e+00 L2 loss: 0.58456 Learning rate: 0.002 Mask loss: 0.09157 RPN box loss: 0.00933 RPN score loss: 0.00153 RPN total loss: 0.01086 Total loss: 0.8097 timestamp: 1655048863.3536365 iteration: 50910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.19034 L1 loss: 0.0000e+00 L2 loss: 0.58455 Learning rate: 0.002 Mask loss: 0.1769 RPN box loss: 0.02854 RPN score loss: 0.02278 RPN total loss: 0.05132 Total loss: 1.0031 timestamp: 1655048866.574454 iteration: 50915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07555 FastRCNN class loss: 0.06443 FastRCNN total loss: 0.13998 L1 loss: 0.0000e+00 L2 loss: 0.58454 Learning rate: 0.002 Mask loss: 0.08678 RPN box loss: 0.0279 RPN score loss: 0.01583 RPN total loss: 0.04373 Total loss: 0.85503 timestamp: 1655048869.8831494 iteration: 50920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06093 FastRCNN class loss: 0.04803 FastRCNN total loss: 0.10896 L1 loss: 0.0000e+00 L2 loss: 0.58453 Learning rate: 0.002 Mask loss: 0.09083 RPN box loss: 0.00534 RPN score loss: 0.00349 RPN total loss: 0.00882 Total loss: 0.79315 timestamp: 1655048873.1110933 iteration: 50925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0606 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.10731 L1 loss: 0.0000e+00 L2 loss: 0.58452 Learning rate: 0.002 Mask loss: 0.14748 RPN box loss: 0.00501 RPN score loss: 0.0011 RPN total loss: 0.00612 Total loss: 0.84543 timestamp: 1655048876.3180883 iteration: 50930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0709 FastRCNN class loss: 0.05027 FastRCNN total loss: 0.12117 L1 loss: 0.0000e+00 L2 loss: 0.58452 Learning rate: 0.002 Mask loss: 0.11445 RPN box loss: 0.01609 RPN score loss: 0.00783 RPN total loss: 0.02391 Total loss: 0.84405 timestamp: 1655048879.5915549 iteration: 50935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13033 FastRCNN class loss: 0.098 FastRCNN total loss: 0.22833 L1 loss: 0.0000e+00 L2 loss: 0.58451 Learning rate: 0.002 Mask loss: 0.19427 RPN box loss: 0.01275 RPN score loss: 0.0096 RPN total loss: 0.02235 Total loss: 1.02946 timestamp: 1655048882.8348577 iteration: 50940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.14031 L1 loss: 0.0000e+00 L2 loss: 0.5845 Learning rate: 0.002 Mask loss: 0.12257 RPN box loss: 0.01174 RPN score loss: 0.00627 RPN total loss: 0.01801 Total loss: 0.86539 timestamp: 1655048886.0841696 iteration: 50945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10721 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.15673 L1 loss: 0.0000e+00 L2 loss: 0.58449 Learning rate: 0.002 Mask loss: 0.14996 RPN box loss: 0.00548 RPN score loss: 0.00504 RPN total loss: 0.01052 Total loss: 0.9017 timestamp: 1655048889.379924 iteration: 50950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13912 FastRCNN class loss: 0.12115 FastRCNN total loss: 0.26027 L1 loss: 0.0000e+00 L2 loss: 0.58448 Learning rate: 0.002 Mask loss: 0.1961 RPN box loss: 0.0256 RPN score loss: 0.0155 RPN total loss: 0.0411 Total loss: 1.08194 timestamp: 1655048892.6561508 iteration: 50955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09218 FastRCNN class loss: 0.08894 FastRCNN total loss: 0.18112 L1 loss: 0.0000e+00 L2 loss: 0.58447 Learning rate: 0.002 Mask loss: 0.09971 RPN box loss: 0.02236 RPN score loss: 0.00945 RPN total loss: 0.03182 Total loss: 0.89712 timestamp: 1655048895.9451783 iteration: 50960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17113 FastRCNN class loss: 0.08675 FastRCNN total loss: 0.25788 L1 loss: 0.0000e+00 L2 loss: 0.58446 Learning rate: 0.002 Mask loss: 0.14478 RPN box loss: 0.01155 RPN score loss: 0.00734 RPN total loss: 0.01889 Total loss: 1.00601 timestamp: 1655048899.2650185 iteration: 50965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.0669 FastRCNN total loss: 0.16241 L1 loss: 0.0000e+00 L2 loss: 0.58445 Learning rate: 0.002 Mask loss: 0.15747 RPN box loss: 0.02059 RPN score loss: 0.0084 RPN total loss: 0.02899 Total loss: 0.93332 timestamp: 1655048902.5520728 iteration: 50970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12995 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.1953 L1 loss: 0.0000e+00 L2 loss: 0.58444 Learning rate: 0.002 Mask loss: 0.16054 RPN box loss: 0.01863 RPN score loss: 0.00555 RPN total loss: 0.02418 Total loss: 0.96447 timestamp: 1655048905.8634381 iteration: 50975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08885 FastRCNN class loss: 0.07865 FastRCNN total loss: 0.1675 L1 loss: 0.0000e+00 L2 loss: 0.58444 Learning rate: 0.002 Mask loss: 0.12458 RPN box loss: 0.02367 RPN score loss: 0.00461 RPN total loss: 0.02828 Total loss: 0.90479 timestamp: 1655048909.1081233 iteration: 50980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08851 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.15581 L1 loss: 0.0000e+00 L2 loss: 0.58443 Learning rate: 0.002 Mask loss: 0.1221 RPN box loss: 0.01018 RPN score loss: 0.00178 RPN total loss: 0.01196 Total loss: 0.87429 timestamp: 1655048912.3959284 iteration: 50985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0266 FastRCNN class loss: 0.04159 FastRCNN total loss: 0.06818 L1 loss: 0.0000e+00 L2 loss: 0.58442 Learning rate: 0.002 Mask loss: 0.18776 RPN box loss: 0.0052 RPN score loss: 0.00361 RPN total loss: 0.00881 Total loss: 0.84917 timestamp: 1655048915.639093 iteration: 50990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09264 FastRCNN class loss: 0.07428 FastRCNN total loss: 0.16692 L1 loss: 0.0000e+00 L2 loss: 0.58441 Learning rate: 0.002 Mask loss: 0.12952 RPN box loss: 0.01383 RPN score loss: 0.00507 RPN total loss: 0.0189 Total loss: 0.89974 timestamp: 1655048918.90984 iteration: 50995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12416 FastRCNN class loss: 0.08087 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 0.5844 Learning rate: 0.002 Mask loss: 0.13742 RPN box loss: 0.0353 RPN score loss: 0.01545 RPN total loss: 0.05075 Total loss: 0.9776 timestamp: 1655048922.1733606 iteration: 51000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14273 FastRCNN class loss: 0.05553 FastRCNN total loss: 0.19826 L1 loss: 0.0000e+00 L2 loss: 0.58439 Learning rate: 0.002 Mask loss: 0.12415 RPN box loss: 0.0242 RPN score loss: 0.00406 RPN total loss: 0.02826 Total loss: 0.93506 timestamp: 1655048925.4018397 iteration: 51005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09287 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.14873 L1 loss: 0.0000e+00 L2 loss: 0.58438 Learning rate: 0.002 Mask loss: 0.12596 RPN box loss: 0.01534 RPN score loss: 0.00791 RPN total loss: 0.02325 Total loss: 0.88232 timestamp: 1655048928.6982093 iteration: 51010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13068 FastRCNN class loss: 0.06085 FastRCNN total loss: 0.19153 L1 loss: 0.0000e+00 L2 loss: 0.58437 Learning rate: 0.002 Mask loss: 0.15233 RPN box loss: 0.02598 RPN score loss: 0.00478 RPN total loss: 0.03076 Total loss: 0.959 timestamp: 1655048931.9395761 iteration: 51015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06113 FastRCNN class loss: 0.03858 FastRCNN total loss: 0.09971 L1 loss: 0.0000e+00 L2 loss: 0.58436 Learning rate: 0.002 Mask loss: 0.1357 RPN box loss: 0.00479 RPN score loss: 0.00374 RPN total loss: 0.00854 Total loss: 0.82831 timestamp: 1655048935.2160287 iteration: 51020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.10215 FastRCNN total loss: 0.18986 L1 loss: 0.0000e+00 L2 loss: 0.58435 Learning rate: 0.002 Mask loss: 0.22097 RPN box loss: 0.02591 RPN score loss: 0.00988 RPN total loss: 0.03579 Total loss: 1.03097 timestamp: 1655048938.462265 iteration: 51025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.18081 L1 loss: 0.0000e+00 L2 loss: 0.58434 Learning rate: 0.002 Mask loss: 0.0964 RPN box loss: 0.01461 RPN score loss: 0.00402 RPN total loss: 0.01862 Total loss: 0.88017 timestamp: 1655048941.8330367 iteration: 51030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06394 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.12866 L1 loss: 0.0000e+00 L2 loss: 0.58433 Learning rate: 0.002 Mask loss: 0.13719 RPN box loss: 0.05698 RPN score loss: 0.00984 RPN total loss: 0.06682 Total loss: 0.917 timestamp: 1655048945.1376522 iteration: 51035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1272 FastRCNN class loss: 0.09934 FastRCNN total loss: 0.22653 L1 loss: 0.0000e+00 L2 loss: 0.58432 Learning rate: 0.002 Mask loss: 0.15761 RPN box loss: 0.02461 RPN score loss: 0.00938 RPN total loss: 0.03399 Total loss: 1.00245 timestamp: 1655048948.4466429 iteration: 51040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17532 FastRCNN class loss: 0.09038 FastRCNN total loss: 0.2657 L1 loss: 0.0000e+00 L2 loss: 0.58431 Learning rate: 0.002 Mask loss: 0.17227 RPN box loss: 0.01447 RPN score loss: 0.01264 RPN total loss: 0.02711 Total loss: 1.04939 timestamp: 1655048951.652033 iteration: 51045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11792 FastRCNN class loss: 0.05586 FastRCNN total loss: 0.17378 L1 loss: 0.0000e+00 L2 loss: 0.5843 Learning rate: 0.002 Mask loss: 0.15385 RPN box loss: 0.0072 RPN score loss: 0.00362 RPN total loss: 0.01081 Total loss: 0.92275 timestamp: 1655048954.8967438 iteration: 51050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05107 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.10332 L1 loss: 0.0000e+00 L2 loss: 0.58429 Learning rate: 0.002 Mask loss: 0.14554 RPN box loss: 0.0234 RPN score loss: 0.00536 RPN total loss: 0.02876 Total loss: 0.86191 timestamp: 1655048958.2074397 iteration: 51055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05364 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.09779 L1 loss: 0.0000e+00 L2 loss: 0.58428 Learning rate: 0.002 Mask loss: 0.0856 RPN box loss: 0.01231 RPN score loss: 0.00493 RPN total loss: 0.01724 Total loss: 0.78491 timestamp: 1655048961.447822 iteration: 51060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13831 FastRCNN class loss: 0.07987 FastRCNN total loss: 0.21818 L1 loss: 0.0000e+00 L2 loss: 0.58427 Learning rate: 0.002 Mask loss: 0.12755 RPN box loss: 0.0064 RPN score loss: 0.0016 RPN total loss: 0.008 Total loss: 0.938 timestamp: 1655048964.6418886 iteration: 51065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10785 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.17121 L1 loss: 0.0000e+00 L2 loss: 0.58427 Learning rate: 0.002 Mask loss: 0.15107 RPN box loss: 0.0284 RPN score loss: 0.00437 RPN total loss: 0.03277 Total loss: 0.93932 timestamp: 1655048967.9391046 iteration: 51070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.09451 FastRCNN total loss: 0.19423 L1 loss: 0.0000e+00 L2 loss: 0.58426 Learning rate: 0.002 Mask loss: 0.15724 RPN box loss: 0.03065 RPN score loss: 0.0125 RPN total loss: 0.04315 Total loss: 0.97887 timestamp: 1655048971.2041967 iteration: 51075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08296 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.12794 L1 loss: 0.0000e+00 L2 loss: 0.58425 Learning rate: 0.002 Mask loss: 0.13966 RPN box loss: 0.0146 RPN score loss: 0.00536 RPN total loss: 0.01996 Total loss: 0.87181 timestamp: 1655048974.5061166 iteration: 51080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09135 FastRCNN class loss: 0.06088 FastRCNN total loss: 0.15223 L1 loss: 0.0000e+00 L2 loss: 0.58424 Learning rate: 0.002 Mask loss: 0.1312 RPN box loss: 0.01174 RPN score loss: 0.00523 RPN total loss: 0.01697 Total loss: 0.88465 timestamp: 1655048977.7665136 iteration: 51085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12834 FastRCNN class loss: 0.10188 FastRCNN total loss: 0.23022 L1 loss: 0.0000e+00 L2 loss: 0.58424 Learning rate: 0.002 Mask loss: 0.17124 RPN box loss: 0.00661 RPN score loss: 0.00418 RPN total loss: 0.01079 Total loss: 0.9965 timestamp: 1655048981.044179 iteration: 51090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12251 FastRCNN class loss: 0.07739 FastRCNN total loss: 0.19991 L1 loss: 0.0000e+00 L2 loss: 0.58423 Learning rate: 0.002 Mask loss: 0.17114 RPN box loss: 0.01192 RPN score loss: 0.00648 RPN total loss: 0.0184 Total loss: 0.97367 timestamp: 1655048984.311487 iteration: 51095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12896 FastRCNN class loss: 0.09237 FastRCNN total loss: 0.22132 L1 loss: 0.0000e+00 L2 loss: 0.58422 Learning rate: 0.002 Mask loss: 0.18112 RPN box loss: 0.0322 RPN score loss: 0.00461 RPN total loss: 0.03681 Total loss: 1.02347 timestamp: 1655048987.578483 iteration: 51100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12709 FastRCNN class loss: 0.06005 FastRCNN total loss: 0.18713 L1 loss: 0.0000e+00 L2 loss: 0.58421 Learning rate: 0.002 Mask loss: 0.19406 RPN box loss: 0.06019 RPN score loss: 0.00944 RPN total loss: 0.06963 Total loss: 1.03503 timestamp: 1655048990.91545 iteration: 51105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08065 FastRCNN class loss: 0.06634 FastRCNN total loss: 0.14698 L1 loss: 0.0000e+00 L2 loss: 0.5842 Learning rate: 0.002 Mask loss: 0.14968 RPN box loss: 0.026 RPN score loss: 0.00182 RPN total loss: 0.02782 Total loss: 0.90868 timestamp: 1655048994.1920269 iteration: 51110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17017 FastRCNN class loss: 0.09598 FastRCNN total loss: 0.26615 L1 loss: 0.0000e+00 L2 loss: 0.58419 Learning rate: 0.002 Mask loss: 0.18648 RPN box loss: 0.02413 RPN score loss: 0.01096 RPN total loss: 0.03508 Total loss: 1.07191 timestamp: 1655048997.5569558 iteration: 51115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14718 FastRCNN class loss: 0.08955 FastRCNN total loss: 0.23672 L1 loss: 0.0000e+00 L2 loss: 0.58418 Learning rate: 0.002 Mask loss: 0.14318 RPN box loss: 0.02842 RPN score loss: 0.00836 RPN total loss: 0.03679 Total loss: 1.00088 timestamp: 1655049000.8395538 iteration: 51120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10268 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.17626 L1 loss: 0.0000e+00 L2 loss: 0.58417 Learning rate: 0.002 Mask loss: 0.1194 RPN box loss: 0.03148 RPN score loss: 0.00682 RPN total loss: 0.0383 Total loss: 0.91813 timestamp: 1655049004.2007756 iteration: 51125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0922 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.15137 L1 loss: 0.0000e+00 L2 loss: 0.58417 Learning rate: 0.002 Mask loss: 0.1319 RPN box loss: 0.0275 RPN score loss: 0.00678 RPN total loss: 0.03429 Total loss: 0.90173 timestamp: 1655049007.5705283 iteration: 51130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.03158 FastRCNN total loss: 0.14601 L1 loss: 0.0000e+00 L2 loss: 0.58416 Learning rate: 0.002 Mask loss: 0.0988 RPN box loss: 0.00627 RPN score loss: 0.00166 RPN total loss: 0.00794 Total loss: 0.83691 timestamp: 1655049010.8056195 iteration: 51135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06766 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.13015 L1 loss: 0.0000e+00 L2 loss: 0.58416 Learning rate: 0.002 Mask loss: 0.14332 RPN box loss: 0.00832 RPN score loss: 0.00345 RPN total loss: 0.01177 Total loss: 0.8694 timestamp: 1655049014.096583 iteration: 51140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07175 FastRCNN class loss: 0.04645 FastRCNN total loss: 0.1182 L1 loss: 0.0000e+00 L2 loss: 0.58415 Learning rate: 0.002 Mask loss: 0.1062 RPN box loss: 0.00429 RPN score loss: 0.00132 RPN total loss: 0.00561 Total loss: 0.81415 timestamp: 1655049017.3639414 iteration: 51145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13168 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 0.58414 Learning rate: 0.002 Mask loss: 0.10432 RPN box loss: 0.00964 RPN score loss: 0.00408 RPN total loss: 0.01372 Total loss: 0.89945 timestamp: 1655049020.5443883 iteration: 51150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17315 FastRCNN class loss: 0.10861 FastRCNN total loss: 0.28175 L1 loss: 0.0000e+00 L2 loss: 0.58413 Learning rate: 0.002 Mask loss: 0.1648 RPN box loss: 0.01422 RPN score loss: 0.00155 RPN total loss: 0.01576 Total loss: 1.04644 timestamp: 1655049023.809185 iteration: 51155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13068 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.19706 L1 loss: 0.0000e+00 L2 loss: 0.58412 Learning rate: 0.002 Mask loss: 0.13563 RPN box loss: 0.00593 RPN score loss: 0.00283 RPN total loss: 0.00876 Total loss: 0.92557 timestamp: 1655049027.048869 iteration: 51160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.04314 FastRCNN total loss: 0.12731 L1 loss: 0.0000e+00 L2 loss: 0.58411 Learning rate: 0.002 Mask loss: 0.09711 RPN box loss: 0.01177 RPN score loss: 0.00133 RPN total loss: 0.0131 Total loss: 0.82164 timestamp: 1655049030.3011475 iteration: 51165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12709 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.20629 L1 loss: 0.0000e+00 L2 loss: 0.5841 Learning rate: 0.002 Mask loss: 0.16628 RPN box loss: 0.00943 RPN score loss: 0.0067 RPN total loss: 0.01613 Total loss: 0.9728 timestamp: 1655049033.4813814 iteration: 51170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08845 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.15233 L1 loss: 0.0000e+00 L2 loss: 0.5841 Learning rate: 0.002 Mask loss: 0.13137 RPN box loss: 0.02261 RPN score loss: 0.00297 RPN total loss: 0.02558 Total loss: 0.89338 timestamp: 1655049036.7991264 iteration: 51175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18643 FastRCNN class loss: 0.09804 FastRCNN total loss: 0.28448 L1 loss: 0.0000e+00 L2 loss: 0.58409 Learning rate: 0.002 Mask loss: 0.1596 RPN box loss: 0.01855 RPN score loss: 0.01227 RPN total loss: 0.03082 Total loss: 1.05898 timestamp: 1655049040.119495 iteration: 51180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13376 FastRCNN class loss: 0.11221 FastRCNN total loss: 0.24596 L1 loss: 0.0000e+00 L2 loss: 0.58408 Learning rate: 0.002 Mask loss: 0.16207 RPN box loss: 0.02962 RPN score loss: 0.0087 RPN total loss: 0.03832 Total loss: 1.03043 timestamp: 1655049043.410062 iteration: 51185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14009 FastRCNN class loss: 0.09873 FastRCNN total loss: 0.23881 L1 loss: 0.0000e+00 L2 loss: 0.58407 Learning rate: 0.002 Mask loss: 0.1966 RPN box loss: 0.0093 RPN score loss: 0.00334 RPN total loss: 0.01264 Total loss: 1.03212 timestamp: 1655049046.6534941 iteration: 51190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.20789 L1 loss: 0.0000e+00 L2 loss: 0.58406 Learning rate: 0.002 Mask loss: 0.11428 RPN box loss: 0.01298 RPN score loss: 0.00557 RPN total loss: 0.01855 Total loss: 0.92478 timestamp: 1655049049.8512928 iteration: 51195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0786 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.13127 L1 loss: 0.0000e+00 L2 loss: 0.58405 Learning rate: 0.002 Mask loss: 0.13432 RPN box loss: 0.02465 RPN score loss: 0.00527 RPN total loss: 0.02992 Total loss: 0.87956 timestamp: 1655049053.1209352 iteration: 51200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09367 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.15591 L1 loss: 0.0000e+00 L2 loss: 0.58404 Learning rate: 0.002 Mask loss: 0.12435 RPN box loss: 0.00753 RPN score loss: 0.00363 RPN total loss: 0.01116 Total loss: 0.87545 timestamp: 1655049056.3549063 iteration: 51205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08032 FastRCNN class loss: 0.10454 FastRCNN total loss: 0.18486 L1 loss: 0.0000e+00 L2 loss: 0.58403 Learning rate: 0.002 Mask loss: 0.24308 RPN box loss: 0.01834 RPN score loss: 0.0123 RPN total loss: 0.03064 Total loss: 1.04261 timestamp: 1655049059.5564954 iteration: 51210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07861 FastRCNN class loss: 0.04208 FastRCNN total loss: 0.1207 L1 loss: 0.0000e+00 L2 loss: 0.58403 Learning rate: 0.002 Mask loss: 0.09882 RPN box loss: 0.00533 RPN score loss: 0.00462 RPN total loss: 0.00995 Total loss: 0.81349 timestamp: 1655049062.7971992 iteration: 51215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07986 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.14947 L1 loss: 0.0000e+00 L2 loss: 0.58402 Learning rate: 0.002 Mask loss: 0.15147 RPN box loss: 0.0236 RPN score loss: 0.00332 RPN total loss: 0.02693 Total loss: 0.91189 timestamp: 1655049066.0507271 iteration: 51220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11815 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.18869 L1 loss: 0.0000e+00 L2 loss: 0.58401 Learning rate: 0.002 Mask loss: 0.18501 RPN box loss: 0.02775 RPN score loss: 0.00666 RPN total loss: 0.03441 Total loss: 0.99212 timestamp: 1655049069.3507404 iteration: 51225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11705 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.17087 L1 loss: 0.0000e+00 L2 loss: 0.584 Learning rate: 0.002 Mask loss: 0.1486 RPN box loss: 0.01332 RPN score loss: 0.00585 RPN total loss: 0.01917 Total loss: 0.92264 timestamp: 1655049072.5577369 iteration: 51230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.06991 FastRCNN total loss: 0.14428 L1 loss: 0.0000e+00 L2 loss: 0.58399 Learning rate: 0.002 Mask loss: 0.13994 RPN box loss: 0.01687 RPN score loss: 0.00468 RPN total loss: 0.02155 Total loss: 0.88975 timestamp: 1655049075.881918 iteration: 51235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12128 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.20055 L1 loss: 0.0000e+00 L2 loss: 0.58399 Learning rate: 0.002 Mask loss: 0.19399 RPN box loss: 0.0128 RPN score loss: 0.01009 RPN total loss: 0.02289 Total loss: 1.00142 timestamp: 1655049079.1584728 iteration: 51240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14176 FastRCNN class loss: 0.0865 FastRCNN total loss: 0.22825 L1 loss: 0.0000e+00 L2 loss: 0.58398 Learning rate: 0.002 Mask loss: 0.22783 RPN box loss: 0.02008 RPN score loss: 0.00865 RPN total loss: 0.02873 Total loss: 1.06879 timestamp: 1655049082.4358826 iteration: 51245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13297 FastRCNN class loss: 0.08119 FastRCNN total loss: 0.21416 L1 loss: 0.0000e+00 L2 loss: 0.58397 Learning rate: 0.002 Mask loss: 0.13565 RPN box loss: 0.01615 RPN score loss: 0.00551 RPN total loss: 0.02165 Total loss: 0.95544 timestamp: 1655049085.685528 iteration: 51250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07553 FastRCNN class loss: 0.05683 FastRCNN total loss: 0.13235 L1 loss: 0.0000e+00 L2 loss: 0.58396 Learning rate: 0.002 Mask loss: 0.12311 RPN box loss: 0.01036 RPN score loss: 0.0045 RPN total loss: 0.01486 Total loss: 0.85429 timestamp: 1655049088.927601 iteration: 51255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09177 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.15065 L1 loss: 0.0000e+00 L2 loss: 0.58395 Learning rate: 0.002 Mask loss: 0.12102 RPN box loss: 0.02479 RPN score loss: 0.00662 RPN total loss: 0.03141 Total loss: 0.88703 timestamp: 1655049092.2464995 iteration: 51260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15454 FastRCNN class loss: 0.087 FastRCNN total loss: 0.24154 L1 loss: 0.0000e+00 L2 loss: 0.58394 Learning rate: 0.002 Mask loss: 0.15313 RPN box loss: 0.01007 RPN score loss: 0.00394 RPN total loss: 0.01402 Total loss: 0.99263 timestamp: 1655049095.548273 iteration: 51265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13644 FastRCNN class loss: 0.09568 FastRCNN total loss: 0.23211 L1 loss: 0.0000e+00 L2 loss: 0.58393 Learning rate: 0.002 Mask loss: 0.13889 RPN box loss: 0.02673 RPN score loss: 0.00328 RPN total loss: 0.03001 Total loss: 0.98494 timestamp: 1655049098.8835976 iteration: 51270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07437 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.12315 L1 loss: 0.0000e+00 L2 loss: 0.58392 Learning rate: 0.002 Mask loss: 0.0894 RPN box loss: 0.00279 RPN score loss: 0.00269 RPN total loss: 0.00548 Total loss: 0.80195 timestamp: 1655049102.148095 iteration: 51275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11427 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.19638 L1 loss: 0.0000e+00 L2 loss: 0.58391 Learning rate: 0.002 Mask loss: 0.10973 RPN box loss: 0.00956 RPN score loss: 0.00218 RPN total loss: 0.01174 Total loss: 0.90177 timestamp: 1655049105.4025857 iteration: 51280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11964 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.18555 L1 loss: 0.0000e+00 L2 loss: 0.58391 Learning rate: 0.002 Mask loss: 0.18614 RPN box loss: 0.02938 RPN score loss: 0.00347 RPN total loss: 0.03285 Total loss: 0.98845 timestamp: 1655049108.7129617 iteration: 51285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08636 FastRCNN class loss: 0.06499 FastRCNN total loss: 0.15135 L1 loss: 0.0000e+00 L2 loss: 0.5839 Learning rate: 0.002 Mask loss: 0.15884 RPN box loss: 0.00947 RPN score loss: 0.00745 RPN total loss: 0.01693 Total loss: 0.91101 timestamp: 1655049111.987711 iteration: 51290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08799 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.14296 L1 loss: 0.0000e+00 L2 loss: 0.58389 Learning rate: 0.002 Mask loss: 0.14914 RPN box loss: 0.00866 RPN score loss: 0.00352 RPN total loss: 0.01218 Total loss: 0.88817 timestamp: 1655049115.213853 iteration: 51295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12118 FastRCNN class loss: 0.07148 FastRCNN total loss: 0.19266 L1 loss: 0.0000e+00 L2 loss: 0.58388 Learning rate: 0.002 Mask loss: 0.12199 RPN box loss: 0.01 RPN score loss: 0.00615 RPN total loss: 0.01615 Total loss: 0.91468 timestamp: 1655049118.5457656 iteration: 51300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1846 FastRCNN class loss: 0.08323 FastRCNN total loss: 0.26783 L1 loss: 0.0000e+00 L2 loss: 0.58387 Learning rate: 0.002 Mask loss: 0.1052 RPN box loss: 0.01939 RPN score loss: 0.00613 RPN total loss: 0.02552 Total loss: 0.98241 timestamp: 1655049121.8894694 iteration: 51305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09054 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.1354 L1 loss: 0.0000e+00 L2 loss: 0.58386 Learning rate: 0.002 Mask loss: 0.09746 RPN box loss: 0.01121 RPN score loss: 0.00346 RPN total loss: 0.01468 Total loss: 0.8314 timestamp: 1655049125.1031291 iteration: 51310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.15528 L1 loss: 0.0000e+00 L2 loss: 0.58385 Learning rate: 0.002 Mask loss: 0.12808 RPN box loss: 0.01078 RPN score loss: 0.0046 RPN total loss: 0.01538 Total loss: 0.88258 timestamp: 1655049128.5137815 iteration: 51315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16669 FastRCNN class loss: 0.07293 FastRCNN total loss: 0.23962 L1 loss: 0.0000e+00 L2 loss: 0.58384 Learning rate: 0.002 Mask loss: 0.17432 RPN box loss: 0.0342 RPN score loss: 0.00951 RPN total loss: 0.04371 Total loss: 1.04149 timestamp: 1655049131.7793832 iteration: 51320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07868 FastRCNN class loss: 0.05566 FastRCNN total loss: 0.13433 L1 loss: 0.0000e+00 L2 loss: 0.58383 Learning rate: 0.002 Mask loss: 0.09784 RPN box loss: 0.01801 RPN score loss: 0.00913 RPN total loss: 0.02714 Total loss: 0.84315 timestamp: 1655049135.0481787 iteration: 51325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1326 FastRCNN class loss: 0.08978 FastRCNN total loss: 0.22238 L1 loss: 0.0000e+00 L2 loss: 0.58382 Learning rate: 0.002 Mask loss: 0.21146 RPN box loss: 0.03633 RPN score loss: 0.00806 RPN total loss: 0.04439 Total loss: 1.06206 timestamp: 1655049138.3523695 iteration: 51330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11281 FastRCNN class loss: 0.11605 FastRCNN total loss: 0.22885 L1 loss: 0.0000e+00 L2 loss: 0.58382 Learning rate: 0.002 Mask loss: 0.17852 RPN box loss: 0.02041 RPN score loss: 0.00334 RPN total loss: 0.02375 Total loss: 1.01493 timestamp: 1655049141.587553 iteration: 51335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0553 FastRCNN class loss: 0.04233 FastRCNN total loss: 0.09764 L1 loss: 0.0000e+00 L2 loss: 0.58381 Learning rate: 0.002 Mask loss: 0.10665 RPN box loss: 0.00673 RPN score loss: 0.00103 RPN total loss: 0.00777 Total loss: 0.79586 timestamp: 1655049144.8613462 iteration: 51340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07487 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.14857 L1 loss: 0.0000e+00 L2 loss: 0.5838 Learning rate: 0.002 Mask loss: 0.11999 RPN box loss: 0.00919 RPN score loss: 0.00645 RPN total loss: 0.01564 Total loss: 0.86799 timestamp: 1655049148.0827565 iteration: 51345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13548 FastRCNN class loss: 0.12049 FastRCNN total loss: 0.25596 L1 loss: 0.0000e+00 L2 loss: 0.58379 Learning rate: 0.002 Mask loss: 0.27604 RPN box loss: 0.01876 RPN score loss: 0.01259 RPN total loss: 0.03135 Total loss: 1.14715 timestamp: 1655049151.3219893 iteration: 51350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07406 FastRCNN class loss: 0.05048 FastRCNN total loss: 0.12454 L1 loss: 0.0000e+00 L2 loss: 0.58378 Learning rate: 0.002 Mask loss: 0.11114 RPN box loss: 0.01118 RPN score loss: 0.00795 RPN total loss: 0.01913 Total loss: 0.83858 timestamp: 1655049154.6760342 iteration: 51355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14601 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.21372 L1 loss: 0.0000e+00 L2 loss: 0.58377 Learning rate: 0.002 Mask loss: 0.12495 RPN box loss: 0.01137 RPN score loss: 0.00437 RPN total loss: 0.01575 Total loss: 0.93819 timestamp: 1655049157.986454 iteration: 51360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10524 FastRCNN class loss: 0.08105 FastRCNN total loss: 0.1863 L1 loss: 0.0000e+00 L2 loss: 0.58376 Learning rate: 0.002 Mask loss: 0.11453 RPN box loss: 0.01123 RPN score loss: 0.00205 RPN total loss: 0.01328 Total loss: 0.89788 timestamp: 1655049161.2590754 iteration: 51365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.02735 FastRCNN total loss: 0.12306 L1 loss: 0.0000e+00 L2 loss: 0.58376 Learning rate: 0.002 Mask loss: 0.09361 RPN box loss: 0.01283 RPN score loss: 0.00327 RPN total loss: 0.0161 Total loss: 0.81652 timestamp: 1655049164.46488 iteration: 51370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10385 FastRCNN class loss: 0.07635 FastRCNN total loss: 0.1802 L1 loss: 0.0000e+00 L2 loss: 0.58375 Learning rate: 0.002 Mask loss: 0.13036 RPN box loss: 0.01163 RPN score loss: 0.00288 RPN total loss: 0.01451 Total loss: 0.90881 timestamp: 1655049167.6310863 iteration: 51375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09078 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.16099 L1 loss: 0.0000e+00 L2 loss: 0.58374 Learning rate: 0.002 Mask loss: 0.15209 RPN box loss: 0.01695 RPN score loss: 0.00626 RPN total loss: 0.02321 Total loss: 0.92003 timestamp: 1655049170.9050071 iteration: 51380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10998 FastRCNN class loss: 0.071 FastRCNN total loss: 0.18098 L1 loss: 0.0000e+00 L2 loss: 0.58373 Learning rate: 0.002 Mask loss: 0.12359 RPN box loss: 0.01657 RPN score loss: 0.00844 RPN total loss: 0.02501 Total loss: 0.91332 timestamp: 1655049174.1978626 iteration: 51385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.04688 FastRCNN total loss: 0.15214 L1 loss: 0.0000e+00 L2 loss: 0.58372 Learning rate: 0.002 Mask loss: 0.10778 RPN box loss: 0.00993 RPN score loss: 0.00117 RPN total loss: 0.0111 Total loss: 0.85474 timestamp: 1655049177.532364 iteration: 51390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.03813 FastRCNN total loss: 0.1122 L1 loss: 0.0000e+00 L2 loss: 0.58371 Learning rate: 0.002 Mask loss: 0.11233 RPN box loss: 0.02171 RPN score loss: 0.00258 RPN total loss: 0.02428 Total loss: 0.83253 timestamp: 1655049180.8390243 iteration: 51395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05519 FastRCNN class loss: 0.06254 FastRCNN total loss: 0.11773 L1 loss: 0.0000e+00 L2 loss: 0.5837 Learning rate: 0.002 Mask loss: 0.12625 RPN box loss: 0.00656 RPN score loss: 0.00314 RPN total loss: 0.0097 Total loss: 0.83739 timestamp: 1655049184.1963735 iteration: 51400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12405 FastRCNN class loss: 0.04897 FastRCNN total loss: 0.17302 L1 loss: 0.0000e+00 L2 loss: 0.58369 Learning rate: 0.002 Mask loss: 0.11338 RPN box loss: 0.06508 RPN score loss: 0.00394 RPN total loss: 0.06902 Total loss: 0.93911 timestamp: 1655049187.508062 iteration: 51405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14666 FastRCNN class loss: 0.09945 FastRCNN total loss: 0.24611 L1 loss: 0.0000e+00 L2 loss: 0.58368 Learning rate: 0.002 Mask loss: 0.20404 RPN box loss: 0.04991 RPN score loss: 0.01018 RPN total loss: 0.0601 Total loss: 1.09393 timestamp: 1655049190.769357 iteration: 51410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08548 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.16303 L1 loss: 0.0000e+00 L2 loss: 0.58367 Learning rate: 0.002 Mask loss: 0.12928 RPN box loss: 0.00905 RPN score loss: 0.01166 RPN total loss: 0.02072 Total loss: 0.8967 timestamp: 1655049194.0446558 iteration: 51415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15724 FastRCNN class loss: 0.11419 FastRCNN total loss: 0.27143 L1 loss: 0.0000e+00 L2 loss: 0.58367 Learning rate: 0.002 Mask loss: 0.17659 RPN box loss: 0.02841 RPN score loss: 0.00752 RPN total loss: 0.03593 Total loss: 1.06762 timestamp: 1655049197.2921453 iteration: 51420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.05915 FastRCNN total loss: 0.15554 L1 loss: 0.0000e+00 L2 loss: 0.58366 Learning rate: 0.002 Mask loss: 0.10304 RPN box loss: 0.01301 RPN score loss: 0.00218 RPN total loss: 0.01519 Total loss: 0.85743 timestamp: 1655049200.5894887 iteration: 51425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09738 FastRCNN class loss: 0.08122 FastRCNN total loss: 0.1786 L1 loss: 0.0000e+00 L2 loss: 0.58365 Learning rate: 0.002 Mask loss: 0.155 RPN box loss: 0.04092 RPN score loss: 0.01513 RPN total loss: 0.05606 Total loss: 0.97331 timestamp: 1655049203.9231389 iteration: 51430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11728 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.2026 L1 loss: 0.0000e+00 L2 loss: 0.58364 Learning rate: 0.002 Mask loss: 0.17454 RPN box loss: 0.00965 RPN score loss: 0.00836 RPN total loss: 0.01802 Total loss: 0.9788 timestamp: 1655049207.208432 iteration: 51435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12865 FastRCNN class loss: 0.07567 FastRCNN total loss: 0.20432 L1 loss: 0.0000e+00 L2 loss: 0.58363 Learning rate: 0.002 Mask loss: 0.13116 RPN box loss: 0.01662 RPN score loss: 0.0092 RPN total loss: 0.02582 Total loss: 0.94493 timestamp: 1655049210.4931104 iteration: 51440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07466 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.1379 L1 loss: 0.0000e+00 L2 loss: 0.58362 Learning rate: 0.002 Mask loss: 0.12346 RPN box loss: 0.00858 RPN score loss: 0.00267 RPN total loss: 0.01125 Total loss: 0.85623 timestamp: 1655049213.7394392 iteration: 51445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09895 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.1709 L1 loss: 0.0000e+00 L2 loss: 0.58362 Learning rate: 0.002 Mask loss: 0.14973 RPN box loss: 0.01029 RPN score loss: 0.00357 RPN total loss: 0.01386 Total loss: 0.91811 timestamp: 1655049217.0237553 iteration: 51450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08793 FastRCNN class loss: 0.08333 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 0.58361 Learning rate: 0.002 Mask loss: 0.17679 RPN box loss: 0.01099 RPN score loss: 0.00764 RPN total loss: 0.01862 Total loss: 0.95028 timestamp: 1655049220.2473638 iteration: 51455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13259 FastRCNN class loss: 0.10511 FastRCNN total loss: 0.23769 L1 loss: 0.0000e+00 L2 loss: 0.5836 Learning rate: 0.002 Mask loss: 0.18242 RPN box loss: 0.01202 RPN score loss: 0.01059 RPN total loss: 0.02261 Total loss: 1.02632 timestamp: 1655049223.470684 iteration: 51460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.08019 FastRCNN total loss: 0.18018 L1 loss: 0.0000e+00 L2 loss: 0.58359 Learning rate: 0.002 Mask loss: 0.13681 RPN box loss: 0.03397 RPN score loss: 0.00577 RPN total loss: 0.03974 Total loss: 0.94032 timestamp: 1655049226.8503816 iteration: 51465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09755 FastRCNN class loss: 0.09678 FastRCNN total loss: 0.19433 L1 loss: 0.0000e+00 L2 loss: 0.58358 Learning rate: 0.002 Mask loss: 0.15345 RPN box loss: 0.02248 RPN score loss: 0.00431 RPN total loss: 0.0268 Total loss: 0.95815 timestamp: 1655049230.1282623 iteration: 51470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13046 FastRCNN class loss: 0.13594 FastRCNN total loss: 0.2664 L1 loss: 0.0000e+00 L2 loss: 0.58357 Learning rate: 0.002 Mask loss: 0.22294 RPN box loss: 0.02188 RPN score loss: 0.01505 RPN total loss: 0.03692 Total loss: 1.10984 timestamp: 1655049233.3615706 iteration: 51475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15041 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.22585 L1 loss: 0.0000e+00 L2 loss: 0.58356 Learning rate: 0.002 Mask loss: 0.17328 RPN box loss: 0.01852 RPN score loss: 0.00371 RPN total loss: 0.02224 Total loss: 1.00493 timestamp: 1655049236.6530714 iteration: 51480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09496 FastRCNN class loss: 0.05964 FastRCNN total loss: 0.1546 L1 loss: 0.0000e+00 L2 loss: 0.58355 Learning rate: 0.002 Mask loss: 0.10588 RPN box loss: 0.03187 RPN score loss: 0.00496 RPN total loss: 0.03683 Total loss: 0.88086 timestamp: 1655049239.9185302 iteration: 51485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11124 FastRCNN class loss: 0.08864 FastRCNN total loss: 0.19988 L1 loss: 0.0000e+00 L2 loss: 0.58354 Learning rate: 0.002 Mask loss: 0.16462 RPN box loss: 0.04055 RPN score loss: 0.00592 RPN total loss: 0.04647 Total loss: 0.99451 timestamp: 1655049243.1823204 iteration: 51490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07319 FastRCNN class loss: 0.06288 FastRCNN total loss: 0.13607 L1 loss: 0.0000e+00 L2 loss: 0.58354 Learning rate: 0.002 Mask loss: 0.08503 RPN box loss: 0.01041 RPN score loss: 0.00405 RPN total loss: 0.01446 Total loss: 0.8191 timestamp: 1655049246.3739042 iteration: 51495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12634 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.20832 L1 loss: 0.0000e+00 L2 loss: 0.58353 Learning rate: 0.002 Mask loss: 0.13793 RPN box loss: 0.00801 RPN score loss: 0.00694 RPN total loss: 0.01495 Total loss: 0.94474 timestamp: 1655049249.6549869 iteration: 51500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11896 FastRCNN class loss: 0.10837 FastRCNN total loss: 0.22733 L1 loss: 0.0000e+00 L2 loss: 0.58352 Learning rate: 0.002 Mask loss: 0.25423 RPN box loss: 0.02578 RPN score loss: 0.01392 RPN total loss: 0.03971 Total loss: 1.1048 timestamp: 1655049252.864657 iteration: 51505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07472 FastRCNN class loss: 0.04135 FastRCNN total loss: 0.11607 L1 loss: 0.0000e+00 L2 loss: 0.58352 Learning rate: 0.002 Mask loss: 0.12153 RPN box loss: 0.02169 RPN score loss: 0.00082 RPN total loss: 0.02252 Total loss: 0.84363 timestamp: 1655049256.106255 iteration: 51510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.07316 FastRCNN total loss: 0.15911 L1 loss: 0.0000e+00 L2 loss: 0.58351 Learning rate: 0.002 Mask loss: 0.17674 RPN box loss: 0.01666 RPN score loss: 0.00729 RPN total loss: 0.02396 Total loss: 0.94332 timestamp: 1655049259.367801 iteration: 51515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12353 FastRCNN class loss: 0.06125 FastRCNN total loss: 0.18478 L1 loss: 0.0000e+00 L2 loss: 0.5835 Learning rate: 0.002 Mask loss: 0.09849 RPN box loss: 0.00806 RPN score loss: 0.00178 RPN total loss: 0.00984 Total loss: 0.87661 timestamp: 1655049262.6677432 iteration: 51520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12927 FastRCNN class loss: 0.08951 FastRCNN total loss: 0.21878 L1 loss: 0.0000e+00 L2 loss: 0.58349 Learning rate: 0.002 Mask loss: 0.14656 RPN box loss: 0.02001 RPN score loss: 0.00673 RPN total loss: 0.02674 Total loss: 0.97557 timestamp: 1655049266.0204172 iteration: 51525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06876 FastRCNN class loss: 0.059 FastRCNN total loss: 0.12776 L1 loss: 0.0000e+00 L2 loss: 0.58349 Learning rate: 0.002 Mask loss: 0.14928 RPN box loss: 0.00884 RPN score loss: 0.00431 RPN total loss: 0.01315 Total loss: 0.87368 timestamp: 1655049269.2629755 iteration: 51530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.14253 L1 loss: 0.0000e+00 L2 loss: 0.58348 Learning rate: 0.002 Mask loss: 0.13824 RPN box loss: 0.01653 RPN score loss: 0.00763 RPN total loss: 0.02416 Total loss: 0.88842 timestamp: 1655049272.4779232 iteration: 51535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08278 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.15903 L1 loss: 0.0000e+00 L2 loss: 0.58347 Learning rate: 0.002 Mask loss: 0.1723 RPN box loss: 0.02333 RPN score loss: 0.00751 RPN total loss: 0.03084 Total loss: 0.94563 timestamp: 1655049275.7813702 iteration: 51540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09258 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.14852 L1 loss: 0.0000e+00 L2 loss: 0.58345 Learning rate: 0.002 Mask loss: 0.15221 RPN box loss: 0.00885 RPN score loss: 0.00199 RPN total loss: 0.01084 Total loss: 0.89502 timestamp: 1655049279.0730753 iteration: 51545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07332 FastRCNN class loss: 0.04222 FastRCNN total loss: 0.11554 L1 loss: 0.0000e+00 L2 loss: 0.58344 Learning rate: 0.002 Mask loss: 0.11964 RPN box loss: 0.00632 RPN score loss: 0.00221 RPN total loss: 0.00853 Total loss: 0.82715 timestamp: 1655049282.3011835 iteration: 51550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03187 FastRCNN class loss: 0.02773 FastRCNN total loss: 0.0596 L1 loss: 0.0000e+00 L2 loss: 0.58344 Learning rate: 0.002 Mask loss: 0.10596 RPN box loss: 0.01552 RPN score loss: 0.0034 RPN total loss: 0.01891 Total loss: 0.76791 timestamp: 1655049285.6585505 iteration: 51555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13095 FastRCNN class loss: 0.06809 FastRCNN total loss: 0.19904 L1 loss: 0.0000e+00 L2 loss: 0.58343 Learning rate: 0.002 Mask loss: 0.10507 RPN box loss: 0.01452 RPN score loss: 0.0018 RPN total loss: 0.01631 Total loss: 0.90386 timestamp: 1655049288.9279785 iteration: 51560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09443 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.15114 L1 loss: 0.0000e+00 L2 loss: 0.58342 Learning rate: 0.002 Mask loss: 0.12373 RPN box loss: 0.02042 RPN score loss: 0.00413 RPN total loss: 0.02454 Total loss: 0.88283 timestamp: 1655049292.2137983 iteration: 51565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08449 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.18225 L1 loss: 0.0000e+00 L2 loss: 0.58341 Learning rate: 0.002 Mask loss: 0.12921 RPN box loss: 0.01776 RPN score loss: 0.00499 RPN total loss: 0.02275 Total loss: 0.91762 timestamp: 1655049295.5073864 iteration: 51570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09525 FastRCNN class loss: 0.07329 FastRCNN total loss: 0.16853 L1 loss: 0.0000e+00 L2 loss: 0.5834 Learning rate: 0.002 Mask loss: 0.1803 RPN box loss: 0.02707 RPN score loss: 0.00321 RPN total loss: 0.03028 Total loss: 0.96252 timestamp: 1655049298.8047407 iteration: 51575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12323 FastRCNN class loss: 0.11435 FastRCNN total loss: 0.23759 L1 loss: 0.0000e+00 L2 loss: 0.58339 Learning rate: 0.002 Mask loss: 0.16041 RPN box loss: 0.03403 RPN score loss: 0.01211 RPN total loss: 0.04615 Total loss: 1.02754 timestamp: 1655049302.1127162 iteration: 51580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07646 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.12145 L1 loss: 0.0000e+00 L2 loss: 0.58338 Learning rate: 0.002 Mask loss: 0.13264 RPN box loss: 0.00955 RPN score loss: 0.00391 RPN total loss: 0.01346 Total loss: 0.85093 timestamp: 1655049305.3297882 iteration: 51585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10886 FastRCNN class loss: 0.06045 FastRCNN total loss: 0.16931 L1 loss: 0.0000e+00 L2 loss: 0.58337 Learning rate: 0.002 Mask loss: 0.1259 RPN box loss: 0.00904 RPN score loss: 0.00829 RPN total loss: 0.01733 Total loss: 0.89592 timestamp: 1655049308.5438623 iteration: 51590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13253 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.20303 L1 loss: 0.0000e+00 L2 loss: 0.58337 Learning rate: 0.002 Mask loss: 0.18935 RPN box loss: 0.02924 RPN score loss: 0.01206 RPN total loss: 0.0413 Total loss: 1.01705 timestamp: 1655049311.7906845 iteration: 51595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04003 FastRCNN class loss: 0.04632 FastRCNN total loss: 0.08635 L1 loss: 0.0000e+00 L2 loss: 0.58336 Learning rate: 0.002 Mask loss: 0.17251 RPN box loss: 0.01168 RPN score loss: 0.00073 RPN total loss: 0.01241 Total loss: 0.85463 timestamp: 1655049315.0800543 iteration: 51600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12966 FastRCNN class loss: 0.10806 FastRCNN total loss: 0.23771 L1 loss: 0.0000e+00 L2 loss: 0.58335 Learning rate: 0.002 Mask loss: 0.18893 RPN box loss: 0.01595 RPN score loss: 0.00444 RPN total loss: 0.02039 Total loss: 1.0304 timestamp: 1655049318.3144343 iteration: 51605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20707 FastRCNN class loss: 0.13385 FastRCNN total loss: 0.34091 L1 loss: 0.0000e+00 L2 loss: 0.58334 Learning rate: 0.002 Mask loss: 0.19173 RPN box loss: 0.01874 RPN score loss: 0.00916 RPN total loss: 0.02791 Total loss: 1.14389 timestamp: 1655049321.568032 iteration: 51610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16234 FastRCNN class loss: 0.10021 FastRCNN total loss: 0.26255 L1 loss: 0.0000e+00 L2 loss: 0.58333 Learning rate: 0.002 Mask loss: 0.15499 RPN box loss: 0.01937 RPN score loss: 0.00401 RPN total loss: 0.02338 Total loss: 1.02425 timestamp: 1655049324.9069142 iteration: 51615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13188 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.19929 L1 loss: 0.0000e+00 L2 loss: 0.58332 Learning rate: 0.002 Mask loss: 0.13446 RPN box loss: 0.02392 RPN score loss: 0.00556 RPN total loss: 0.02948 Total loss: 0.94656 timestamp: 1655049328.2047987 iteration: 51620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0995 FastRCNN class loss: 0.08048 FastRCNN total loss: 0.17998 L1 loss: 0.0000e+00 L2 loss: 0.58331 Learning rate: 0.002 Mask loss: 0.12086 RPN box loss: 0.01197 RPN score loss: 0.00483 RPN total loss: 0.0168 Total loss: 0.90096 timestamp: 1655049331.5126424 iteration: 51625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11282 FastRCNN class loss: 0.08845 FastRCNN total loss: 0.20127 L1 loss: 0.0000e+00 L2 loss: 0.5833 Learning rate: 0.002 Mask loss: 0.16492 RPN box loss: 0.07887 RPN score loss: 0.00746 RPN total loss: 0.08633 Total loss: 1.03582 timestamp: 1655049334.7654943 iteration: 51630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07805 FastRCNN class loss: 0.04522 FastRCNN total loss: 0.12328 L1 loss: 0.0000e+00 L2 loss: 0.58329 Learning rate: 0.002 Mask loss: 0.12101 RPN box loss: 0.02239 RPN score loss: 0.00366 RPN total loss: 0.02605 Total loss: 0.85363 timestamp: 1655049338.0056908 iteration: 51635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0699 FastRCNN class loss: 0.11594 FastRCNN total loss: 0.18584 L1 loss: 0.0000e+00 L2 loss: 0.58329 Learning rate: 0.002 Mask loss: 0.22789 RPN box loss: 0.03621 RPN score loss: 0.07153 RPN total loss: 0.10774 Total loss: 1.10476 timestamp: 1655049341.2346334 iteration: 51640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08329 FastRCNN class loss: 0.08968 FastRCNN total loss: 0.17297 L1 loss: 0.0000e+00 L2 loss: 0.58328 Learning rate: 0.002 Mask loss: 0.17363 RPN box loss: 0.02355 RPN score loss: 0.00961 RPN total loss: 0.03316 Total loss: 0.96303 timestamp: 1655049344.5533466 iteration: 51645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.07351 FastRCNN total loss: 0.18631 L1 loss: 0.0000e+00 L2 loss: 0.58327 Learning rate: 0.002 Mask loss: 0.16546 RPN box loss: 0.01662 RPN score loss: 0.00498 RPN total loss: 0.0216 Total loss: 0.95665 timestamp: 1655049347.8267949 iteration: 51650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.07146 FastRCNN total loss: 0.20552 L1 loss: 0.0000e+00 L2 loss: 0.58327 Learning rate: 0.002 Mask loss: 0.16029 RPN box loss: 0.01171 RPN score loss: 0.00906 RPN total loss: 0.02077 Total loss: 0.96985 timestamp: 1655049351.079725 iteration: 51655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14463 FastRCNN class loss: 0.05719 FastRCNN total loss: 0.20182 L1 loss: 0.0000e+00 L2 loss: 0.58326 Learning rate: 0.002 Mask loss: 0.11268 RPN box loss: 0.01602 RPN score loss: 0.00508 RPN total loss: 0.0211 Total loss: 0.91886 timestamp: 1655049354.3328927 iteration: 51660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.22396 L1 loss: 0.0000e+00 L2 loss: 0.58325 Learning rate: 0.002 Mask loss: 0.20084 RPN box loss: 0.01377 RPN score loss: 0.0083 RPN total loss: 0.02207 Total loss: 1.03011 timestamp: 1655049357.5532336 iteration: 51665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08968 FastRCNN class loss: 0.05625 FastRCNN total loss: 0.14593 L1 loss: 0.0000e+00 L2 loss: 0.58324 Learning rate: 0.002 Mask loss: 0.12595 RPN box loss: 0.00672 RPN score loss: 0.00265 RPN total loss: 0.00937 Total loss: 0.86449 timestamp: 1655049360.7907608 iteration: 51670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07006 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.12833 L1 loss: 0.0000e+00 L2 loss: 0.58323 Learning rate: 0.002 Mask loss: 0.10672 RPN box loss: 0.02049 RPN score loss: 0.00263 RPN total loss: 0.02313 Total loss: 0.8414 timestamp: 1655049364.0460167 iteration: 51675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16307 FastRCNN class loss: 0.06692 FastRCNN total loss: 0.22999 L1 loss: 0.0000e+00 L2 loss: 0.58322 Learning rate: 0.002 Mask loss: 0.11259 RPN box loss: 0.05648 RPN score loss: 0.00171 RPN total loss: 0.05818 Total loss: 0.98399 timestamp: 1655049367.3743563 iteration: 51680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09986 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.14976 L1 loss: 0.0000e+00 L2 loss: 0.58321 Learning rate: 0.002 Mask loss: 0.09417 RPN box loss: 0.01595 RPN score loss: 0.00165 RPN total loss: 0.01761 Total loss: 0.84475 timestamp: 1655049370.6053162 iteration: 51685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.10457 FastRCNN total loss: 0.18351 L1 loss: 0.0000e+00 L2 loss: 0.58321 Learning rate: 0.002 Mask loss: 0.17276 RPN box loss: 0.01095 RPN score loss: 0.00373 RPN total loss: 0.01467 Total loss: 0.95415 timestamp: 1655049373.9147375 iteration: 51690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09446 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.16778 L1 loss: 0.0000e+00 L2 loss: 0.5832 Learning rate: 0.002 Mask loss: 0.16027 RPN box loss: 0.01057 RPN score loss: 0.00369 RPN total loss: 0.01426 Total loss: 0.9255 timestamp: 1655049377.1796257 iteration: 51695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07031 FastRCNN class loss: 0.08754 FastRCNN total loss: 0.15785 L1 loss: 0.0000e+00 L2 loss: 0.58319 Learning rate: 0.002 Mask loss: 0.11578 RPN box loss: 0.00639 RPN score loss: 0.00387 RPN total loss: 0.01026 Total loss: 0.86707 timestamp: 1655049380.4662364 iteration: 51700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11144 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.18063 L1 loss: 0.0000e+00 L2 loss: 0.58318 Learning rate: 0.002 Mask loss: 0.12826 RPN box loss: 0.01488 RPN score loss: 0.00259 RPN total loss: 0.01748 Total loss: 0.90955 timestamp: 1655049383.73735 iteration: 51705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14051 FastRCNN class loss: 0.11929 FastRCNN total loss: 0.2598 L1 loss: 0.0000e+00 L2 loss: 0.58317 Learning rate: 0.002 Mask loss: 0.17749 RPN box loss: 0.01726 RPN score loss: 0.01559 RPN total loss: 0.03285 Total loss: 1.05332 timestamp: 1655049387.0175614 iteration: 51710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08087 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.14762 L1 loss: 0.0000e+00 L2 loss: 0.58316 Learning rate: 0.002 Mask loss: 0.1205 RPN box loss: 0.03905 RPN score loss: 0.00749 RPN total loss: 0.04654 Total loss: 0.89782 timestamp: 1655049390.3219059 iteration: 51715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.1677 L1 loss: 0.0000e+00 L2 loss: 0.58315 Learning rate: 0.002 Mask loss: 0.16103 RPN box loss: 0.01407 RPN score loss: 0.00218 RPN total loss: 0.01625 Total loss: 0.92813 timestamp: 1655049393.6181629 iteration: 51720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15162 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.21339 L1 loss: 0.0000e+00 L2 loss: 0.58315 Learning rate: 0.002 Mask loss: 0.10832 RPN box loss: 0.01702 RPN score loss: 0.00673 RPN total loss: 0.02375 Total loss: 0.92861 timestamp: 1655049396.9431367 iteration: 51725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16324 FastRCNN class loss: 0.0897 FastRCNN total loss: 0.25294 L1 loss: 0.0000e+00 L2 loss: 0.58314 Learning rate: 0.002 Mask loss: 0.2211 RPN box loss: 0.02084 RPN score loss: 0.01131 RPN total loss: 0.03215 Total loss: 1.08933 timestamp: 1655049400.2675157 iteration: 51730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06158 FastRCNN class loss: 0.04379 FastRCNN total loss: 0.10536 L1 loss: 0.0000e+00 L2 loss: 0.58313 Learning rate: 0.002 Mask loss: 0.15241 RPN box loss: 0.01107 RPN score loss: 0.00476 RPN total loss: 0.01583 Total loss: 0.85673 timestamp: 1655049403.5659883 iteration: 51735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08697 FastRCNN class loss: 0.08857 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.58312 Learning rate: 0.002 Mask loss: 0.12701 RPN box loss: 0.02794 RPN score loss: 0.00653 RPN total loss: 0.03447 Total loss: 0.92013 timestamp: 1655049406.8391573 iteration: 51740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14517 FastRCNN class loss: 0.07006 FastRCNN total loss: 0.21523 L1 loss: 0.0000e+00 L2 loss: 0.58311 Learning rate: 0.002 Mask loss: 0.15649 RPN box loss: 0.01729 RPN score loss: 0.00403 RPN total loss: 0.02133 Total loss: 0.97616 timestamp: 1655049410.1963243 iteration: 51745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11536 FastRCNN class loss: 0.0562 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 0.5831 Learning rate: 0.002 Mask loss: 0.11096 RPN box loss: 0.00854 RPN score loss: 0.0025 RPN total loss: 0.01104 Total loss: 0.87665 timestamp: 1655049413.4649599 iteration: 51750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1025 FastRCNN class loss: 0.05276 FastRCNN total loss: 0.15526 L1 loss: 0.0000e+00 L2 loss: 0.58309 Learning rate: 0.002 Mask loss: 0.11313 RPN box loss: 0.01403 RPN score loss: 0.00194 RPN total loss: 0.01598 Total loss: 0.86747 timestamp: 1655049416.74838 iteration: 51755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.059 FastRCNN class loss: 0.03971 FastRCNN total loss: 0.09871 L1 loss: 0.0000e+00 L2 loss: 0.58308 Learning rate: 0.002 Mask loss: 0.11194 RPN box loss: 0.01581 RPN score loss: 0.00174 RPN total loss: 0.01755 Total loss: 0.81128 timestamp: 1655049420.0133886 iteration: 51760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1259 FastRCNN class loss: 0.11004 FastRCNN total loss: 0.23594 L1 loss: 0.0000e+00 L2 loss: 0.58307 Learning rate: 0.002 Mask loss: 0.11424 RPN box loss: 0.02496 RPN score loss: 0.00988 RPN total loss: 0.03484 Total loss: 0.96809 timestamp: 1655049423.2615554 iteration: 51765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.16626 L1 loss: 0.0000e+00 L2 loss: 0.58307 Learning rate: 0.002 Mask loss: 0.20868 RPN box loss: 0.01745 RPN score loss: 0.01187 RPN total loss: 0.02932 Total loss: 0.98733 timestamp: 1655049426.5347412 iteration: 51770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16038 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.24001 L1 loss: 0.0000e+00 L2 loss: 0.58306 Learning rate: 0.002 Mask loss: 0.21388 RPN box loss: 0.01341 RPN score loss: 0.01363 RPN total loss: 0.02705 Total loss: 1.064 timestamp: 1655049429.8127947 iteration: 51775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12644 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.18795 L1 loss: 0.0000e+00 L2 loss: 0.58305 Learning rate: 0.002 Mask loss: 0.16721 RPN box loss: 0.0106 RPN score loss: 0.00568 RPN total loss: 0.01628 Total loss: 0.95448 timestamp: 1655049433.0217364 iteration: 51780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16146 FastRCNN class loss: 0.09046 FastRCNN total loss: 0.25191 L1 loss: 0.0000e+00 L2 loss: 0.58304 Learning rate: 0.002 Mask loss: 0.15611 RPN box loss: 0.01799 RPN score loss: 0.00768 RPN total loss: 0.02567 Total loss: 1.01673 timestamp: 1655049436.3468556 iteration: 51785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09971 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.15883 L1 loss: 0.0000e+00 L2 loss: 0.58303 Learning rate: 0.002 Mask loss: 0.13436 RPN box loss: 0.00397 RPN score loss: 0.00119 RPN total loss: 0.00516 Total loss: 0.88138 timestamp: 1655049439.5842505 iteration: 51790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16335 FastRCNN class loss: 0.08648 FastRCNN total loss: 0.24983 L1 loss: 0.0000e+00 L2 loss: 0.58302 Learning rate: 0.002 Mask loss: 0.17367 RPN box loss: 0.03256 RPN score loss: 0.00773 RPN total loss: 0.04029 Total loss: 1.04681 timestamp: 1655049442.8331795 iteration: 51795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07975 FastRCNN class loss: 0.04691 FastRCNN total loss: 0.12666 L1 loss: 0.0000e+00 L2 loss: 0.58301 Learning rate: 0.002 Mask loss: 0.17574 RPN box loss: 0.02202 RPN score loss: 0.00289 RPN total loss: 0.0249 Total loss: 0.91031 timestamp: 1655049446.1848395 iteration: 51800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12527 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.21121 L1 loss: 0.0000e+00 L2 loss: 0.583 Learning rate: 0.002 Mask loss: 0.18554 RPN box loss: 0.02592 RPN score loss: 0.01316 RPN total loss: 0.03908 Total loss: 1.01883 timestamp: 1655049449.4381099 iteration: 51805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07633 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.12865 L1 loss: 0.0000e+00 L2 loss: 0.583 Learning rate: 0.002 Mask loss: 0.13467 RPN box loss: 0.00964 RPN score loss: 0.00185 RPN total loss: 0.01149 Total loss: 0.8578 timestamp: 1655049452.7083914 iteration: 51810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11432 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.17724 L1 loss: 0.0000e+00 L2 loss: 0.58298 Learning rate: 0.002 Mask loss: 0.10426 RPN box loss: 0.00838 RPN score loss: 0.0039 RPN total loss: 0.01228 Total loss: 0.87676 timestamp: 1655049455.9642699 iteration: 51815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10414 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.16753 L1 loss: 0.0000e+00 L2 loss: 0.58297 Learning rate: 0.002 Mask loss: 0.15078 RPN box loss: 0.02042 RPN score loss: 0.00591 RPN total loss: 0.02634 Total loss: 0.92762 timestamp: 1655049459.265753 iteration: 51820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10588 FastRCNN class loss: 0.08183 FastRCNN total loss: 0.18772 L1 loss: 0.0000e+00 L2 loss: 0.58296 Learning rate: 0.002 Mask loss: 0.12769 RPN box loss: 0.01265 RPN score loss: 0.00661 RPN total loss: 0.01926 Total loss: 0.91763 timestamp: 1655049462.540209 iteration: 51825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1606 FastRCNN class loss: 0.093 FastRCNN total loss: 0.25359 L1 loss: 0.0000e+00 L2 loss: 0.58295 Learning rate: 0.002 Mask loss: 0.20546 RPN box loss: 0.01437 RPN score loss: 0.00928 RPN total loss: 0.02365 Total loss: 1.06565 timestamp: 1655049465.8187044 iteration: 51830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07067 FastRCNN class loss: 0.04163 FastRCNN total loss: 0.1123 L1 loss: 0.0000e+00 L2 loss: 0.58295 Learning rate: 0.002 Mask loss: 0.10868 RPN box loss: 0.04125 RPN score loss: 0.0048 RPN total loss: 0.04605 Total loss: 0.84998 timestamp: 1655049469.036525 iteration: 51835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18385 FastRCNN class loss: 0.08668 FastRCNN total loss: 0.27053 L1 loss: 0.0000e+00 L2 loss: 0.58294 Learning rate: 0.002 Mask loss: 0.11751 RPN box loss: 0.01177 RPN score loss: 0.00419 RPN total loss: 0.01596 Total loss: 0.98695 timestamp: 1655049472.3007762 iteration: 51840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.14314 L1 loss: 0.0000e+00 L2 loss: 0.58293 Learning rate: 0.002 Mask loss: 0.0925 RPN box loss: 0.00836 RPN score loss: 0.0023 RPN total loss: 0.01067 Total loss: 0.82924 timestamp: 1655049475.5221395 iteration: 51845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04784 FastRCNN class loss: 0.07107 FastRCNN total loss: 0.11892 L1 loss: 0.0000e+00 L2 loss: 0.58292 Learning rate: 0.002 Mask loss: 0.0987 RPN box loss: 0.00968 RPN score loss: 0.00346 RPN total loss: 0.01313 Total loss: 0.81368 timestamp: 1655049478.7463284 iteration: 51850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08639 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.15361 L1 loss: 0.0000e+00 L2 loss: 0.58291 Learning rate: 0.002 Mask loss: 0.12412 RPN box loss: 0.05377 RPN score loss: 0.00684 RPN total loss: 0.06061 Total loss: 0.92125 timestamp: 1655049482.0193524 iteration: 51855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08147 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.16411 L1 loss: 0.0000e+00 L2 loss: 0.5829 Learning rate: 0.002 Mask loss: 0.13285 RPN box loss: 0.00515 RPN score loss: 0.00579 RPN total loss: 0.01094 Total loss: 0.8908 timestamp: 1655049485.2781465 iteration: 51860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11224 FastRCNN class loss: 0.05215 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.58289 Learning rate: 0.002 Mask loss: 0.13502 RPN box loss: 0.01673 RPN score loss: 0.0039 RPN total loss: 0.02063 Total loss: 0.90294 timestamp: 1655049488.5526562 iteration: 51865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1334 FastRCNN class loss: 0.12054 FastRCNN total loss: 0.25394 L1 loss: 0.0000e+00 L2 loss: 0.58288 Learning rate: 0.002 Mask loss: 0.16127 RPN box loss: 0.02355 RPN score loss: 0.01462 RPN total loss: 0.03817 Total loss: 1.03626 timestamp: 1655049491.833978 iteration: 51870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12069 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.19496 L1 loss: 0.0000e+00 L2 loss: 0.58288 Learning rate: 0.002 Mask loss: 0.19095 RPN box loss: 0.01008 RPN score loss: 0.00616 RPN total loss: 0.01625 Total loss: 0.98503 timestamp: 1655049495.1113083 iteration: 51875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08207 FastRCNN class loss: 0.04931 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.58287 Learning rate: 0.002 Mask loss: 0.14407 RPN box loss: 0.01266 RPN score loss: 0.00201 RPN total loss: 0.01467 Total loss: 0.87299 timestamp: 1655049498.337161 iteration: 51880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05067 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.11043 L1 loss: 0.0000e+00 L2 loss: 0.58286 Learning rate: 0.002 Mask loss: 0.18007 RPN box loss: 0.0133 RPN score loss: 0.0089 RPN total loss: 0.0222 Total loss: 0.89557 timestamp: 1655049501.705422 iteration: 51885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08003 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.13731 L1 loss: 0.0000e+00 L2 loss: 0.58285 Learning rate: 0.002 Mask loss: 0.21915 RPN box loss: 0.01324 RPN score loss: 0.00298 RPN total loss: 0.01622 Total loss: 0.95553 timestamp: 1655049504.967213 iteration: 51890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06138 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.13135 L1 loss: 0.0000e+00 L2 loss: 0.58284 Learning rate: 0.002 Mask loss: 0.16043 RPN box loss: 0.00465 RPN score loss: 0.00322 RPN total loss: 0.00786 Total loss: 0.88249 timestamp: 1655049508.250798 iteration: 51895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13607 FastRCNN class loss: 0.08436 FastRCNN total loss: 0.22043 L1 loss: 0.0000e+00 L2 loss: 0.58283 Learning rate: 0.002 Mask loss: 0.1908 RPN box loss: 0.04167 RPN score loss: 0.00326 RPN total loss: 0.04493 Total loss: 1.03899 timestamp: 1655049511.5267324 iteration: 51900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09662 FastRCNN class loss: 0.04835 FastRCNN total loss: 0.14498 L1 loss: 0.0000e+00 L2 loss: 0.58282 Learning rate: 0.002 Mask loss: 0.13608 RPN box loss: 0.00925 RPN score loss: 0.01849 RPN total loss: 0.02774 Total loss: 0.89163 timestamp: 1655049514.7012205 iteration: 51905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09475 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.15753 L1 loss: 0.0000e+00 L2 loss: 0.58282 Learning rate: 0.002 Mask loss: 0.12845 RPN box loss: 0.02585 RPN score loss: 0.00719 RPN total loss: 0.03304 Total loss: 0.90183 timestamp: 1655049518.009976 iteration: 51910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12911 FastRCNN class loss: 0.11927 FastRCNN total loss: 0.24838 L1 loss: 0.0000e+00 L2 loss: 0.58281 Learning rate: 0.002 Mask loss: 0.25016 RPN box loss: 0.02164 RPN score loss: 0.01503 RPN total loss: 0.03667 Total loss: 1.11802 timestamp: 1655049521.2943187 iteration: 51915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09235 FastRCNN class loss: 0.04542 FastRCNN total loss: 0.13777 L1 loss: 0.0000e+00 L2 loss: 0.5828 Learning rate: 0.002 Mask loss: 0.11409 RPN box loss: 0.02558 RPN score loss: 0.00624 RPN total loss: 0.03182 Total loss: 0.86648 timestamp: 1655049524.5693026 iteration: 51920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1076 FastRCNN class loss: 0.07288 FastRCNN total loss: 0.18048 L1 loss: 0.0000e+00 L2 loss: 0.58279 Learning rate: 0.002 Mask loss: 0.12188 RPN box loss: 0.00559 RPN score loss: 0.00207 RPN total loss: 0.00765 Total loss: 0.89281 timestamp: 1655049527.8442512 iteration: 51925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.20134 L1 loss: 0.0000e+00 L2 loss: 0.58278 Learning rate: 0.002 Mask loss: 0.17737 RPN box loss: 0.01618 RPN score loss: 0.00249 RPN total loss: 0.01867 Total loss: 0.98016 timestamp: 1655049531.1001432 iteration: 51930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.20793 L1 loss: 0.0000e+00 L2 loss: 0.58277 Learning rate: 0.002 Mask loss: 0.15002 RPN box loss: 0.00578 RPN score loss: 0.00885 RPN total loss: 0.01464 Total loss: 0.95536 timestamp: 1655049534.3699036 iteration: 51935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13478 FastRCNN class loss: 0.09617 FastRCNN total loss: 0.23094 L1 loss: 0.0000e+00 L2 loss: 0.58277 Learning rate: 0.002 Mask loss: 0.18885 RPN box loss: 0.03817 RPN score loss: 0.02005 RPN total loss: 0.05822 Total loss: 1.06078 timestamp: 1655049537.5792823 iteration: 51940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07566 FastRCNN class loss: 0.06225 FastRCNN total loss: 0.13791 L1 loss: 0.0000e+00 L2 loss: 0.58276 Learning rate: 0.002 Mask loss: 0.14317 RPN box loss: 0.00857 RPN score loss: 0.00494 RPN total loss: 0.01351 Total loss: 0.87734 timestamp: 1655049540.9079783 iteration: 51945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05137 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.10913 L1 loss: 0.0000e+00 L2 loss: 0.58275 Learning rate: 0.002 Mask loss: 0.09753 RPN box loss: 0.01351 RPN score loss: 0.0057 RPN total loss: 0.01922 Total loss: 0.80862 timestamp: 1655049544.1457925 iteration: 51950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08828 FastRCNN class loss: 0.04924 FastRCNN total loss: 0.13751 L1 loss: 0.0000e+00 L2 loss: 0.58274 Learning rate: 0.002 Mask loss: 0.16092 RPN box loss: 0.02988 RPN score loss: 0.00539 RPN total loss: 0.03527 Total loss: 0.91644 timestamp: 1655049547.3496282 iteration: 51955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09471 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.14886 L1 loss: 0.0000e+00 L2 loss: 0.58273 Learning rate: 0.002 Mask loss: 0.12699 RPN box loss: 0.01344 RPN score loss: 0.00499 RPN total loss: 0.01842 Total loss: 0.877 timestamp: 1655049550.6515872 iteration: 51960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06501 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.14163 L1 loss: 0.0000e+00 L2 loss: 0.58272 Learning rate: 0.002 Mask loss: 0.11751 RPN box loss: 0.01167 RPN score loss: 0.0024 RPN total loss: 0.01407 Total loss: 0.85593 timestamp: 1655049553.9399529 iteration: 51965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.17151 L1 loss: 0.0000e+00 L2 loss: 0.58272 Learning rate: 0.002 Mask loss: 0.13781 RPN box loss: 0.01595 RPN score loss: 0.00694 RPN total loss: 0.02289 Total loss: 0.91493 timestamp: 1655049557.2455556 iteration: 51970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09162 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.1501 L1 loss: 0.0000e+00 L2 loss: 0.58271 Learning rate: 0.002 Mask loss: 0.12318 RPN box loss: 0.01236 RPN score loss: 0.00148 RPN total loss: 0.01384 Total loss: 0.86983 timestamp: 1655049560.5963893 iteration: 51975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09347 FastRCNN class loss: 0.11324 FastRCNN total loss: 0.20671 L1 loss: 0.0000e+00 L2 loss: 0.5827 Learning rate: 0.002 Mask loss: 0.19688 RPN box loss: 0.02014 RPN score loss: 0.02389 RPN total loss: 0.04404 Total loss: 1.03032 timestamp: 1655049563.8292298 iteration: 51980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.16301 L1 loss: 0.0000e+00 L2 loss: 0.58269 Learning rate: 0.002 Mask loss: 0.12886 RPN box loss: 0.01871 RPN score loss: 0.00881 RPN total loss: 0.02752 Total loss: 0.90209 timestamp: 1655049567.047228 iteration: 51985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12464 FastRCNN class loss: 0.08925 FastRCNN total loss: 0.21389 L1 loss: 0.0000e+00 L2 loss: 0.58269 Learning rate: 0.002 Mask loss: 0.16688 RPN box loss: 0.02146 RPN score loss: 0.00774 RPN total loss: 0.02919 Total loss: 0.99265 timestamp: 1655049570.4142687 iteration: 51990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10888 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.19022 L1 loss: 0.0000e+00 L2 loss: 0.58268 Learning rate: 0.002 Mask loss: 0.23078 RPN box loss: 0.02307 RPN score loss: 0.00805 RPN total loss: 0.03112 Total loss: 1.0348 timestamp: 1655049573.6846921 iteration: 51995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08293 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.13006 L1 loss: 0.0000e+00 L2 loss: 0.58267 Learning rate: 0.002 Mask loss: 0.13846 RPN box loss: 0.04404 RPN score loss: 0.00291 RPN total loss: 0.04695 Total loss: 0.89814 timestamp: 1655049576.9233267 iteration: 52000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.09545 FastRCNN total loss: 0.18829 L1 loss: 0.0000e+00 L2 loss: 0.58266 Learning rate: 0.002 Mask loss: 0.11769 RPN box loss: 0.01181 RPN score loss: 0.00406 RPN total loss: 0.01587 Total loss: 0.90451 timestamp: 1655049580.2079487 iteration: 52005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08406 FastRCNN class loss: 0.05273 FastRCNN total loss: 0.13679 L1 loss: 0.0000e+00 L2 loss: 0.58265 Learning rate: 0.002 Mask loss: 0.18706 RPN box loss: 0.00316 RPN score loss: 0.00195 RPN total loss: 0.00511 Total loss: 0.91161 timestamp: 1655049583.5035238 iteration: 52010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11575 FastRCNN class loss: 0.0698 FastRCNN total loss: 0.18555 L1 loss: 0.0000e+00 L2 loss: 0.58264 Learning rate: 0.002 Mask loss: 0.21153 RPN box loss: 0.00894 RPN score loss: 0.00583 RPN total loss: 0.01477 Total loss: 0.99449 timestamp: 1655049586.8205814 iteration: 52015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12009 FastRCNN class loss: 0.07666 FastRCNN total loss: 0.19675 L1 loss: 0.0000e+00 L2 loss: 0.58263 Learning rate: 0.002 Mask loss: 0.1599 RPN box loss: 0.02202 RPN score loss: 0.01223 RPN total loss: 0.03425 Total loss: 0.97354 timestamp: 1655049590.0946925 iteration: 52020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14032 FastRCNN class loss: 0.10421 FastRCNN total loss: 0.24452 L1 loss: 0.0000e+00 L2 loss: 0.58263 Learning rate: 0.002 Mask loss: 0.17183 RPN box loss: 0.03131 RPN score loss: 0.00799 RPN total loss: 0.0393 Total loss: 1.03829 timestamp: 1655049593.340357 iteration: 52025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12193 FastRCNN class loss: 0.12717 FastRCNN total loss: 0.2491 L1 loss: 0.0000e+00 L2 loss: 0.58262 Learning rate: 0.002 Mask loss: 0.1547 RPN box loss: 0.04065 RPN score loss: 0.00483 RPN total loss: 0.04548 Total loss: 1.0319 timestamp: 1655049596.6905372 iteration: 52030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12298 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.20459 L1 loss: 0.0000e+00 L2 loss: 0.58261 Learning rate: 0.002 Mask loss: 0.16198 RPN box loss: 0.0165 RPN score loss: 0.00221 RPN total loss: 0.0187 Total loss: 0.96788 timestamp: 1655049599.9872868 iteration: 52035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0663 FastRCNN class loss: 0.04373 FastRCNN total loss: 0.11002 L1 loss: 0.0000e+00 L2 loss: 0.5826 Learning rate: 0.002 Mask loss: 0.10899 RPN box loss: 0.04994 RPN score loss: 0.00261 RPN total loss: 0.05255 Total loss: 0.85417 timestamp: 1655049603.3233194 iteration: 52040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10713 FastRCNN class loss: 0.05886 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.58259 Learning rate: 0.002 Mask loss: 0.09659 RPN box loss: 0.0213 RPN score loss: 0.00408 RPN total loss: 0.02538 Total loss: 0.87055 timestamp: 1655049606.6233206 iteration: 52045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14108 FastRCNN class loss: 0.08077 FastRCNN total loss: 0.22185 L1 loss: 0.0000e+00 L2 loss: 0.58258 Learning rate: 0.002 Mask loss: 0.16981 RPN box loss: 0.03704 RPN score loss: 0.0072 RPN total loss: 0.04424 Total loss: 1.01848 timestamp: 1655049609.8969276 iteration: 52050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08889 FastRCNN class loss: 0.03897 FastRCNN total loss: 0.12786 L1 loss: 0.0000e+00 L2 loss: 0.58258 Learning rate: 0.002 Mask loss: 0.15047 RPN box loss: 0.01368 RPN score loss: 0.00448 RPN total loss: 0.01815 Total loss: 0.87906 timestamp: 1655049613.2220376 iteration: 52055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07711 FastRCNN class loss: 0.08185 FastRCNN total loss: 0.15896 L1 loss: 0.0000e+00 L2 loss: 0.58257 Learning rate: 0.002 Mask loss: 0.13306 RPN box loss: 0.01749 RPN score loss: 0.00533 RPN total loss: 0.02282 Total loss: 0.89741 timestamp: 1655049616.5269032 iteration: 52060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15967 FastRCNN class loss: 0.08814 FastRCNN total loss: 0.24781 L1 loss: 0.0000e+00 L2 loss: 0.58256 Learning rate: 0.002 Mask loss: 0.11366 RPN box loss: 0.01102 RPN score loss: 0.00356 RPN total loss: 0.01457 Total loss: 0.95861 timestamp: 1655049619.7823691 iteration: 52065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.07945 FastRCNN total loss: 0.18084 L1 loss: 0.0000e+00 L2 loss: 0.58255 Learning rate: 0.002 Mask loss: 0.16617 RPN box loss: 0.01276 RPN score loss: 0.00926 RPN total loss: 0.02203 Total loss: 0.95159 timestamp: 1655049623.0386372 iteration: 52070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.1639 L1 loss: 0.0000e+00 L2 loss: 0.58254 Learning rate: 0.002 Mask loss: 0.10837 RPN box loss: 0.00697 RPN score loss: 0.00278 RPN total loss: 0.00975 Total loss: 0.86456 timestamp: 1655049626.3232796 iteration: 52075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.11758 L1 loss: 0.0000e+00 L2 loss: 0.58253 Learning rate: 0.002 Mask loss: 0.13846 RPN box loss: 0.01282 RPN score loss: 0.00886 RPN total loss: 0.02168 Total loss: 0.86026 timestamp: 1655049629.6553774 iteration: 52080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06359 FastRCNN class loss: 0.03182 FastRCNN total loss: 0.0954 L1 loss: 0.0000e+00 L2 loss: 0.58252 Learning rate: 0.002 Mask loss: 0.09062 RPN box loss: 0.01826 RPN score loss: 0.00478 RPN total loss: 0.02304 Total loss: 0.79159 timestamp: 1655049632.9456065 iteration: 52085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16315 FastRCNN class loss: 0.09588 FastRCNN total loss: 0.25903 L1 loss: 0.0000e+00 L2 loss: 0.58252 Learning rate: 0.002 Mask loss: 0.18269 RPN box loss: 0.00675 RPN score loss: 0.00252 RPN total loss: 0.00927 Total loss: 1.0335 timestamp: 1655049636.14962 iteration: 52090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10396 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.58251 Learning rate: 0.002 Mask loss: 0.14663 RPN box loss: 0.0382 RPN score loss: 0.0105 RPN total loss: 0.0487 Total loss: 0.96116 timestamp: 1655049639.3960884 iteration: 52095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0767 FastRCNN class loss: 0.07284 FastRCNN total loss: 0.14954 L1 loss: 0.0000e+00 L2 loss: 0.5825 Learning rate: 0.002 Mask loss: 0.18609 RPN box loss: 0.00863 RPN score loss: 0.00168 RPN total loss: 0.01032 Total loss: 0.92845 timestamp: 1655049642.6928563 iteration: 52100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14773 FastRCNN class loss: 0.0973 FastRCNN total loss: 0.24504 L1 loss: 0.0000e+00 L2 loss: 0.58249 Learning rate: 0.002 Mask loss: 0.13897 RPN box loss: 0.03003 RPN score loss: 0.00881 RPN total loss: 0.03884 Total loss: 1.00535 timestamp: 1655049645.939875 iteration: 52105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10716 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.16953 L1 loss: 0.0000e+00 L2 loss: 0.58248 Learning rate: 0.002 Mask loss: 0.18222 RPN box loss: 0.02494 RPN score loss: 0.01006 RPN total loss: 0.035 Total loss: 0.96924 timestamp: 1655049649.2683976 iteration: 52110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13738 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.20931 L1 loss: 0.0000e+00 L2 loss: 0.58247 Learning rate: 0.002 Mask loss: 0.11474 RPN box loss: 0.02851 RPN score loss: 0.00349 RPN total loss: 0.032 Total loss: 0.93852 timestamp: 1655049652.5761306 iteration: 52115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17567 FastRCNN class loss: 0.10533 FastRCNN total loss: 0.281 L1 loss: 0.0000e+00 L2 loss: 0.58246 Learning rate: 0.002 Mask loss: 0.15048 RPN box loss: 0.01848 RPN score loss: 0.00326 RPN total loss: 0.02174 Total loss: 1.03568 timestamp: 1655049655.8920543 iteration: 52120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11121 FastRCNN class loss: 0.06852 FastRCNN total loss: 0.17972 L1 loss: 0.0000e+00 L2 loss: 0.58245 Learning rate: 0.002 Mask loss: 0.14404 RPN box loss: 0.01464 RPN score loss: 0.00671 RPN total loss: 0.02135 Total loss: 0.92756 timestamp: 1655049659.151097 iteration: 52125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06894 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.13684 L1 loss: 0.0000e+00 L2 loss: 0.58244 Learning rate: 0.002 Mask loss: 0.13255 RPN box loss: 0.0233 RPN score loss: 0.0041 RPN total loss: 0.0274 Total loss: 0.87923 timestamp: 1655049662.4576995 iteration: 52130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.0442 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.58243 Learning rate: 0.002 Mask loss: 0.08753 RPN box loss: 0.00634 RPN score loss: 0.00292 RPN total loss: 0.00926 Total loss: 0.81061 timestamp: 1655049665.7102928 iteration: 52135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.05372 FastRCNN total loss: 0.14042 L1 loss: 0.0000e+00 L2 loss: 0.58243 Learning rate: 0.002 Mask loss: 0.1231 RPN box loss: 0.01 RPN score loss: 0.00345 RPN total loss: 0.01344 Total loss: 0.8594 timestamp: 1655049668.9749193 iteration: 52140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09344 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.18023 L1 loss: 0.0000e+00 L2 loss: 0.58242 Learning rate: 0.002 Mask loss: 0.12303 RPN box loss: 0.02684 RPN score loss: 0.00389 RPN total loss: 0.03073 Total loss: 0.91641 timestamp: 1655049672.2976556 iteration: 52145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15829 FastRCNN class loss: 0.10881 FastRCNN total loss: 0.2671 L1 loss: 0.0000e+00 L2 loss: 0.58241 Learning rate: 0.002 Mask loss: 0.21142 RPN box loss: 0.02947 RPN score loss: 0.01423 RPN total loss: 0.04371 Total loss: 1.10464 timestamp: 1655049675.5816164 iteration: 52150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11893 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.19363 L1 loss: 0.0000e+00 L2 loss: 0.5824 Learning rate: 0.002 Mask loss: 0.12852 RPN box loss: 0.0358 RPN score loss: 0.0102 RPN total loss: 0.046 Total loss: 0.95056 timestamp: 1655049678.8285544 iteration: 52155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12117 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.20208 L1 loss: 0.0000e+00 L2 loss: 0.58239 Learning rate: 0.002 Mask loss: 0.16885 RPN box loss: 0.03438 RPN score loss: 0.00556 RPN total loss: 0.03994 Total loss: 0.99326 timestamp: 1655049682.1050005 iteration: 52160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.08111 FastRCNN total loss: 0.15433 L1 loss: 0.0000e+00 L2 loss: 0.58238 Learning rate: 0.002 Mask loss: 0.09788 RPN box loss: 0.02089 RPN score loss: 0.00911 RPN total loss: 0.03001 Total loss: 0.8646 timestamp: 1655049685.370824 iteration: 52165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08462 FastRCNN class loss: 0.0459 FastRCNN total loss: 0.13052 L1 loss: 0.0000e+00 L2 loss: 0.58238 Learning rate: 0.002 Mask loss: 0.14808 RPN box loss: 0.00477 RPN score loss: 0.00858 RPN total loss: 0.01335 Total loss: 0.87433 timestamp: 1655049688.6446025 iteration: 52170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1272 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.19708 L1 loss: 0.0000e+00 L2 loss: 0.58237 Learning rate: 0.002 Mask loss: 0.13094 RPN box loss: 0.04269 RPN score loss: 0.00591 RPN total loss: 0.04861 Total loss: 0.959 timestamp: 1655049691.8582501 iteration: 52175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06986 FastRCNN class loss: 0.05692 FastRCNN total loss: 0.12679 L1 loss: 0.0000e+00 L2 loss: 0.58236 Learning rate: 0.002 Mask loss: 0.14379 RPN box loss: 0.01393 RPN score loss: 0.00624 RPN total loss: 0.02017 Total loss: 0.87311 timestamp: 1655049695.1213114 iteration: 52180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1804 FastRCNN class loss: 0.15703 FastRCNN total loss: 0.33743 L1 loss: 0.0000e+00 L2 loss: 0.58236 Learning rate: 0.002 Mask loss: 0.12561 RPN box loss: 0.01269 RPN score loss: 0.00836 RPN total loss: 0.02104 Total loss: 1.06644 timestamp: 1655049698.420815 iteration: 52185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08203 FastRCNN class loss: 0.04428 FastRCNN total loss: 0.12631 L1 loss: 0.0000e+00 L2 loss: 0.58235 Learning rate: 0.002 Mask loss: 0.12606 RPN box loss: 0.00742 RPN score loss: 0.00647 RPN total loss: 0.01389 Total loss: 0.84861 timestamp: 1655049701.6670508 iteration: 52190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1502 FastRCNN class loss: 0.069 FastRCNN total loss: 0.2192 L1 loss: 0.0000e+00 L2 loss: 0.58234 Learning rate: 0.002 Mask loss: 0.15076 RPN box loss: 0.01557 RPN score loss: 0.01083 RPN total loss: 0.0264 Total loss: 0.9787 timestamp: 1655049704.9107904 iteration: 52195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12112 FastRCNN class loss: 0.05479 FastRCNN total loss: 0.17592 L1 loss: 0.0000e+00 L2 loss: 0.58233 Learning rate: 0.002 Mask loss: 0.25638 RPN box loss: 0.01395 RPN score loss: 0.00768 RPN total loss: 0.02163 Total loss: 1.03626 timestamp: 1655049708.1961746 iteration: 52200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06543 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.13823 L1 loss: 0.0000e+00 L2 loss: 0.58232 Learning rate: 0.002 Mask loss: 0.10856 RPN box loss: 0.00569 RPN score loss: 0.00459 RPN total loss: 0.01028 Total loss: 0.83939 timestamp: 1655049711.4500148 iteration: 52205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0697 FastRCNN class loss: 0.04142 FastRCNN total loss: 0.11112 L1 loss: 0.0000e+00 L2 loss: 0.58231 Learning rate: 0.002 Mask loss: 0.12688 RPN box loss: 0.02363 RPN score loss: 0.00138 RPN total loss: 0.02501 Total loss: 0.84533 timestamp: 1655049714.6714208 iteration: 52210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12137 FastRCNN class loss: 0.09465 FastRCNN total loss: 0.21601 L1 loss: 0.0000e+00 L2 loss: 0.58231 Learning rate: 0.002 Mask loss: 0.22538 RPN box loss: 0.02693 RPN score loss: 0.01337 RPN total loss: 0.0403 Total loss: 1.064 timestamp: 1655049717.9532576 iteration: 52215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10187 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.5823 Learning rate: 0.002 Mask loss: 0.17204 RPN box loss: 0.01267 RPN score loss: 0.00932 RPN total loss: 0.02199 Total loss: 0.96031 timestamp: 1655049721.2501538 iteration: 52220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.05314 FastRCNN total loss: 0.15893 L1 loss: 0.0000e+00 L2 loss: 0.58229 Learning rate: 0.002 Mask loss: 0.10359 RPN box loss: 0.0199 RPN score loss: 0.00507 RPN total loss: 0.02498 Total loss: 0.86979 timestamp: 1655049724.5207021 iteration: 52225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12048 FastRCNN class loss: 0.0737 FastRCNN total loss: 0.19418 L1 loss: 0.0000e+00 L2 loss: 0.58228 Learning rate: 0.002 Mask loss: 0.14031 RPN box loss: 0.02456 RPN score loss: 0.01102 RPN total loss: 0.03558 Total loss: 0.95235 timestamp: 1655049727.8178039 iteration: 52230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15612 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.21566 L1 loss: 0.0000e+00 L2 loss: 0.58227 Learning rate: 0.002 Mask loss: 0.13878 RPN box loss: 0.01248 RPN score loss: 0.0039 RPN total loss: 0.01638 Total loss: 0.95308 timestamp: 1655049731.189005 iteration: 52235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08029 FastRCNN class loss: 0.07519 FastRCNN total loss: 0.15548 L1 loss: 0.0000e+00 L2 loss: 0.58226 Learning rate: 0.002 Mask loss: 0.10856 RPN box loss: 0.02179 RPN score loss: 0.00987 RPN total loss: 0.03166 Total loss: 0.87796 timestamp: 1655049734.4082382 iteration: 52240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11696 FastRCNN class loss: 0.11481 FastRCNN total loss: 0.23177 L1 loss: 0.0000e+00 L2 loss: 0.58225 Learning rate: 0.002 Mask loss: 0.20016 RPN box loss: 0.018 RPN score loss: 0.00604 RPN total loss: 0.02404 Total loss: 1.03821 timestamp: 1655049737.634732 iteration: 52245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06382 FastRCNN class loss: 0.05879 FastRCNN total loss: 0.12261 L1 loss: 0.0000e+00 L2 loss: 0.58224 Learning rate: 0.002 Mask loss: 0.14168 RPN box loss: 0.01864 RPN score loss: 0.0023 RPN total loss: 0.02094 Total loss: 0.86747 timestamp: 1655049740.8638008 iteration: 52250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12645 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.20599 L1 loss: 0.0000e+00 L2 loss: 0.58223 Learning rate: 0.002 Mask loss: 0.12127 RPN box loss: 0.04274 RPN score loss: 0.00847 RPN total loss: 0.05121 Total loss: 0.96069 timestamp: 1655049744.1701756 iteration: 52255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05938 FastRCNN class loss: 0.04195 FastRCNN total loss: 0.10133 L1 loss: 0.0000e+00 L2 loss: 0.58222 Learning rate: 0.002 Mask loss: 0.11595 RPN box loss: 0.00795 RPN score loss: 0.00762 RPN total loss: 0.01557 Total loss: 0.81507 timestamp: 1655049747.4200332 iteration: 52260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13407 FastRCNN class loss: 0.1039 FastRCNN total loss: 0.23797 L1 loss: 0.0000e+00 L2 loss: 0.58221 Learning rate: 0.002 Mask loss: 0.21685 RPN box loss: 0.02216 RPN score loss: 0.0125 RPN total loss: 0.03466 Total loss: 1.07169 timestamp: 1655049750.7487483 iteration: 52265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.20347 L1 loss: 0.0000e+00 L2 loss: 0.5822 Learning rate: 0.002 Mask loss: 0.11283 RPN box loss: 0.01822 RPN score loss: 0.0125 RPN total loss: 0.03073 Total loss: 0.92924 timestamp: 1655049754.0008998 iteration: 52270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09552 FastRCNN class loss: 0.04992 FastRCNN total loss: 0.14544 L1 loss: 0.0000e+00 L2 loss: 0.58219 Learning rate: 0.002 Mask loss: 0.11667 RPN box loss: 0.02301 RPN score loss: 0.00433 RPN total loss: 0.02734 Total loss: 0.87163 timestamp: 1655049757.3199046 iteration: 52275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0707 FastRCNN class loss: 0.06244 FastRCNN total loss: 0.13314 L1 loss: 0.0000e+00 L2 loss: 0.58218 Learning rate: 0.002 Mask loss: 0.10952 RPN box loss: 0.02785 RPN score loss: 0.00791 RPN total loss: 0.03576 Total loss: 0.8606 timestamp: 1655049760.5431442 iteration: 52280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08237 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.13965 L1 loss: 0.0000e+00 L2 loss: 0.58217 Learning rate: 0.002 Mask loss: 0.11246 RPN box loss: 0.01282 RPN score loss: 0.00317 RPN total loss: 0.01599 Total loss: 0.85027 timestamp: 1655049763.790728 iteration: 52285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12634 FastRCNN class loss: 0.10733 FastRCNN total loss: 0.23367 L1 loss: 0.0000e+00 L2 loss: 0.58217 Learning rate: 0.002 Mask loss: 0.13836 RPN box loss: 0.01112 RPN score loss: 0.00639 RPN total loss: 0.01751 Total loss: 0.97171 timestamp: 1655049767.0593786 iteration: 52290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14005 FastRCNN class loss: 0.06577 FastRCNN total loss: 0.20581 L1 loss: 0.0000e+00 L2 loss: 0.58216 Learning rate: 0.002 Mask loss: 0.12618 RPN box loss: 0.00511 RPN score loss: 0.00382 RPN total loss: 0.00893 Total loss: 0.92309 timestamp: 1655049770.353756 iteration: 52295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17988 FastRCNN class loss: 0.07322 FastRCNN total loss: 0.25309 L1 loss: 0.0000e+00 L2 loss: 0.58215 Learning rate: 0.002 Mask loss: 0.19904 RPN box loss: 0.01233 RPN score loss: 0.00293 RPN total loss: 0.01526 Total loss: 1.04954 timestamp: 1655049773.7121572 iteration: 52300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11744 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.18686 L1 loss: 0.0000e+00 L2 loss: 0.58214 Learning rate: 0.002 Mask loss: 0.11414 RPN box loss: 0.00735 RPN score loss: 0.00261 RPN total loss: 0.00995 Total loss: 0.8931 timestamp: 1655049776.9743783 iteration: 52305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.07272 FastRCNN total loss: 0.15871 L1 loss: 0.0000e+00 L2 loss: 0.58213 Learning rate: 0.002 Mask loss: 0.16158 RPN box loss: 0.01191 RPN score loss: 0.00346 RPN total loss: 0.01537 Total loss: 0.91778 timestamp: 1655049780.1638162 iteration: 52310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04569 FastRCNN class loss: 0.05379 FastRCNN total loss: 0.09948 L1 loss: 0.0000e+00 L2 loss: 0.58212 Learning rate: 0.002 Mask loss: 0.09879 RPN box loss: 0.01861 RPN score loss: 0.00379 RPN total loss: 0.0224 Total loss: 0.80278 timestamp: 1655049783.4539416 iteration: 52315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07935 FastRCNN class loss: 0.07434 FastRCNN total loss: 0.15369 L1 loss: 0.0000e+00 L2 loss: 0.58211 Learning rate: 0.002 Mask loss: 0.11358 RPN box loss: 0.01697 RPN score loss: 0.006 RPN total loss: 0.02298 Total loss: 0.87236 timestamp: 1655049786.6890204 iteration: 52320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12845 FastRCNN class loss: 0.08512 FastRCNN total loss: 0.21357 L1 loss: 0.0000e+00 L2 loss: 0.5821 Learning rate: 0.002 Mask loss: 0.16139 RPN box loss: 0.02951 RPN score loss: 0.01754 RPN total loss: 0.04705 Total loss: 1.00411 timestamp: 1655049789.914954 iteration: 52325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13141 FastRCNN class loss: 0.05578 FastRCNN total loss: 0.18719 L1 loss: 0.0000e+00 L2 loss: 0.58209 Learning rate: 0.002 Mask loss: 0.13423 RPN box loss: 0.01141 RPN score loss: 0.00291 RPN total loss: 0.01432 Total loss: 0.91783 timestamp: 1655049793.1960678 iteration: 52330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12257 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.20073 L1 loss: 0.0000e+00 L2 loss: 0.58208 Learning rate: 0.002 Mask loss: 0.17494 RPN box loss: 0.02954 RPN score loss: 0.00976 RPN total loss: 0.0393 Total loss: 0.99705 timestamp: 1655049796.4600387 iteration: 52335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07088 FastRCNN class loss: 0.05007 FastRCNN total loss: 0.12095 L1 loss: 0.0000e+00 L2 loss: 0.58207 Learning rate: 0.002 Mask loss: 0.11637 RPN box loss: 0.01899 RPN score loss: 0.00617 RPN total loss: 0.02516 Total loss: 0.84455 timestamp: 1655049799.7437305 iteration: 52340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.07446 FastRCNN total loss: 0.17736 L1 loss: 0.0000e+00 L2 loss: 0.58206 Learning rate: 0.002 Mask loss: 0.10135 RPN box loss: 0.00974 RPN score loss: 0.0066 RPN total loss: 0.01634 Total loss: 0.87712 timestamp: 1655049803.0240405 iteration: 52345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09375 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.1443 L1 loss: 0.0000e+00 L2 loss: 0.58206 Learning rate: 0.002 Mask loss: 0.1514 RPN box loss: 0.00686 RPN score loss: 0.00479 RPN total loss: 0.01166 Total loss: 0.88942 timestamp: 1655049806.336773 iteration: 52350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10654 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.16823 L1 loss: 0.0000e+00 L2 loss: 0.58205 Learning rate: 0.002 Mask loss: 0.12612 RPN box loss: 0.00681 RPN score loss: 0.00684 RPN total loss: 0.01365 Total loss: 0.89005 timestamp: 1655049809.587706 iteration: 52355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13695 FastRCNN class loss: 0.09416 FastRCNN total loss: 0.23111 L1 loss: 0.0000e+00 L2 loss: 0.58204 Learning rate: 0.002 Mask loss: 0.14808 RPN box loss: 0.02387 RPN score loss: 0.00473 RPN total loss: 0.0286 Total loss: 0.98982 timestamp: 1655049812.904813 iteration: 52360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05206 FastRCNN class loss: 0.03675 FastRCNN total loss: 0.0888 L1 loss: 0.0000e+00 L2 loss: 0.58203 Learning rate: 0.002 Mask loss: 0.27953 RPN box loss: 0.04156 RPN score loss: 0.00246 RPN total loss: 0.04401 Total loss: 0.99437 timestamp: 1655049816.1970572 iteration: 52365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05077 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.10553 L1 loss: 0.0000e+00 L2 loss: 0.58203 Learning rate: 0.002 Mask loss: 0.09583 RPN box loss: 0.01845 RPN score loss: 0.00504 RPN total loss: 0.02349 Total loss: 0.80688 timestamp: 1655049819.4380426 iteration: 52370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0656 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.12922 L1 loss: 0.0000e+00 L2 loss: 0.58202 Learning rate: 0.002 Mask loss: 0.12267 RPN box loss: 0.01515 RPN score loss: 0.00612 RPN total loss: 0.02127 Total loss: 0.85518 timestamp: 1655049822.713761 iteration: 52375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.07331 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.58201 Learning rate: 0.002 Mask loss: 0.16227 RPN box loss: 0.03386 RPN score loss: 0.00358 RPN total loss: 0.03744 Total loss: 0.92536 timestamp: 1655049825.9690616 iteration: 52380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0697 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.13559 L1 loss: 0.0000e+00 L2 loss: 0.582 Learning rate: 0.002 Mask loss: 0.11012 RPN box loss: 0.01129 RPN score loss: 0.00139 RPN total loss: 0.01269 Total loss: 0.84039 timestamp: 1655049829.2442954 iteration: 52385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10247 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.18226 L1 loss: 0.0000e+00 L2 loss: 0.58199 Learning rate: 0.002 Mask loss: 0.11742 RPN box loss: 0.03275 RPN score loss: 0.00941 RPN total loss: 0.04216 Total loss: 0.92383 timestamp: 1655049832.5834944 iteration: 52390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07516 FastRCNN class loss: 0.05718 FastRCNN total loss: 0.13233 L1 loss: 0.0000e+00 L2 loss: 0.58198 Learning rate: 0.002 Mask loss: 0.1293 RPN box loss: 0.01245 RPN score loss: 0.00593 RPN total loss: 0.01838 Total loss: 0.86199 timestamp: 1655049835.9131267 iteration: 52395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06936 FastRCNN class loss: 0.04624 FastRCNN total loss: 0.1156 L1 loss: 0.0000e+00 L2 loss: 0.58197 Learning rate: 0.002 Mask loss: 0.10438 RPN box loss: 0.0312 RPN score loss: 0.00701 RPN total loss: 0.03821 Total loss: 0.84016 timestamp: 1655049839.2247615 iteration: 52400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09566 FastRCNN class loss: 0.06481 FastRCNN total loss: 0.16047 L1 loss: 0.0000e+00 L2 loss: 0.58196 Learning rate: 0.002 Mask loss: 0.10774 RPN box loss: 0.03109 RPN score loss: 0.00564 RPN total loss: 0.03673 Total loss: 0.88691 timestamp: 1655049842.5443845 iteration: 52405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1207 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 0.58195 Learning rate: 0.002 Mask loss: 0.16803 RPN box loss: 0.01097 RPN score loss: 0.00746 RPN total loss: 0.01844 Total loss: 0.95609 timestamp: 1655049845.8388765 iteration: 52410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09646 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.16878 L1 loss: 0.0000e+00 L2 loss: 0.58194 Learning rate: 0.002 Mask loss: 0.19811 RPN box loss: 0.01999 RPN score loss: 0.00344 RPN total loss: 0.02343 Total loss: 0.97227 timestamp: 1655049849.1344156 iteration: 52415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.06745 FastRCNN total loss: 0.18335 L1 loss: 0.0000e+00 L2 loss: 0.58194 Learning rate: 0.002 Mask loss: 0.11679 RPN box loss: 0.02199 RPN score loss: 0.00762 RPN total loss: 0.02962 Total loss: 0.91169 timestamp: 1655049852.3672426 iteration: 52420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1091 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.18258 L1 loss: 0.0000e+00 L2 loss: 0.58193 Learning rate: 0.002 Mask loss: 0.14434 RPN box loss: 0.01958 RPN score loss: 0.02098 RPN total loss: 0.04055 Total loss: 0.9494 timestamp: 1655049855.6168916 iteration: 52425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08417 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.16333 L1 loss: 0.0000e+00 L2 loss: 0.58192 Learning rate: 0.002 Mask loss: 0.17202 RPN box loss: 0.04192 RPN score loss: 0.00934 RPN total loss: 0.05126 Total loss: 0.96853 timestamp: 1655049858.8630176 iteration: 52430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09336 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.17475 L1 loss: 0.0000e+00 L2 loss: 0.58191 Learning rate: 0.002 Mask loss: 0.12454 RPN box loss: 0.02671 RPN score loss: 0.00261 RPN total loss: 0.02932 Total loss: 0.91053 timestamp: 1655049862.1538951 iteration: 52435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11843 FastRCNN class loss: 0.05163 FastRCNN total loss: 0.17005 L1 loss: 0.0000e+00 L2 loss: 0.5819 Learning rate: 0.002 Mask loss: 0.10733 RPN box loss: 0.00787 RPN score loss: 0.00404 RPN total loss: 0.01191 Total loss: 0.87119 timestamp: 1655049865.4305885 iteration: 52440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.15901 L1 loss: 0.0000e+00 L2 loss: 0.5819 Learning rate: 0.002 Mask loss: 0.18939 RPN box loss: 0.06892 RPN score loss: 0.00435 RPN total loss: 0.07327 Total loss: 1.00356 timestamp: 1655049868.6427464 iteration: 52445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11379 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.2081 L1 loss: 0.0000e+00 L2 loss: 0.58189 Learning rate: 0.002 Mask loss: 0.17384 RPN box loss: 0.02736 RPN score loss: 0.0061 RPN total loss: 0.03346 Total loss: 0.99729 timestamp: 1655049871.8985796 iteration: 52450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0807 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.16516 L1 loss: 0.0000e+00 L2 loss: 0.58189 Learning rate: 0.002 Mask loss: 0.15442 RPN box loss: 0.01706 RPN score loss: 0.0089 RPN total loss: 0.02596 Total loss: 0.92743 timestamp: 1655049875.1361918 iteration: 52455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0819 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.13247 L1 loss: 0.0000e+00 L2 loss: 0.58188 Learning rate: 0.002 Mask loss: 0.14171 RPN box loss: 0.02375 RPN score loss: 0.00648 RPN total loss: 0.03022 Total loss: 0.88629 timestamp: 1655049878.408661 iteration: 52460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14744 FastRCNN class loss: 0.08246 FastRCNN total loss: 0.2299 L1 loss: 0.0000e+00 L2 loss: 0.58187 Learning rate: 0.002 Mask loss: 0.20092 RPN box loss: 0.01442 RPN score loss: 0.00399 RPN total loss: 0.01841 Total loss: 1.03109 timestamp: 1655049881.664427 iteration: 52465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12365 FastRCNN class loss: 0.05555 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 0.58186 Learning rate: 0.002 Mask loss: 0.11306 RPN box loss: 0.0058 RPN score loss: 0.00278 RPN total loss: 0.00858 Total loss: 0.88269 timestamp: 1655049884.864371 iteration: 52470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 0.58185 Learning rate: 0.002 Mask loss: 0.1667 RPN box loss: 0.01697 RPN score loss: 0.00247 RPN total loss: 0.01944 Total loss: 0.96853 timestamp: 1655049888.1227503 iteration: 52475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13089 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.58184 Learning rate: 0.002 Mask loss: 0.17442 RPN box loss: 0.01403 RPN score loss: 0.00237 RPN total loss: 0.0164 Total loss: 0.98034 timestamp: 1655049891.4193933 iteration: 52480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08752 FastRCNN class loss: 0.0969 FastRCNN total loss: 0.18442 L1 loss: 0.0000e+00 L2 loss: 0.58183 Learning rate: 0.002 Mask loss: 0.15214 RPN box loss: 0.01768 RPN score loss: 0.00743 RPN total loss: 0.02511 Total loss: 0.9435 timestamp: 1655049894.6974082 iteration: 52485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09758 FastRCNN class loss: 0.07042 FastRCNN total loss: 0.168 L1 loss: 0.0000e+00 L2 loss: 0.58182 Learning rate: 0.002 Mask loss: 0.10221 RPN box loss: 0.02235 RPN score loss: 0.00356 RPN total loss: 0.0259 Total loss: 0.87794 timestamp: 1655049897.9241347 iteration: 52490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08966 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.14524 L1 loss: 0.0000e+00 L2 loss: 0.58182 Learning rate: 0.002 Mask loss: 0.08713 RPN box loss: 0.00978 RPN score loss: 0.00155 RPN total loss: 0.01133 Total loss: 0.82552 timestamp: 1655049901.1363423 iteration: 52495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07981 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.14224 L1 loss: 0.0000e+00 L2 loss: 0.58181 Learning rate: 0.002 Mask loss: 0.09811 RPN box loss: 0.01157 RPN score loss: 0.00392 RPN total loss: 0.01549 Total loss: 0.83765 timestamp: 1655049904.4032433 iteration: 52500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.20029 L1 loss: 0.0000e+00 L2 loss: 0.5818 Learning rate: 0.002 Mask loss: 0.08349 RPN box loss: 0.03749 RPN score loss: 0.00811 RPN total loss: 0.04559 Total loss: 0.91118 timestamp: 1655049907.6621644 iteration: 52505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09149 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.17513 L1 loss: 0.0000e+00 L2 loss: 0.58179 Learning rate: 0.002 Mask loss: 0.13942 RPN box loss: 0.01394 RPN score loss: 0.00714 RPN total loss: 0.02109 Total loss: 0.91743 timestamp: 1655049910.9401712 iteration: 52510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0678 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.13389 L1 loss: 0.0000e+00 L2 loss: 0.58179 Learning rate: 0.002 Mask loss: 0.12487 RPN box loss: 0.01155 RPN score loss: 0.00274 RPN total loss: 0.0143 Total loss: 0.85484 timestamp: 1655049914.1783652 iteration: 52515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1486 FastRCNN class loss: 0.1027 FastRCNN total loss: 0.2513 L1 loss: 0.0000e+00 L2 loss: 0.58178 Learning rate: 0.002 Mask loss: 0.19153 RPN box loss: 0.02541 RPN score loss: 0.009 RPN total loss: 0.03441 Total loss: 1.05902 timestamp: 1655049917.3623655 iteration: 52520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09027 FastRCNN class loss: 0.07298 FastRCNN total loss: 0.16325 L1 loss: 0.0000e+00 L2 loss: 0.58177 Learning rate: 0.002 Mask loss: 0.18277 RPN box loss: 0.02067 RPN score loss: 0.0132 RPN total loss: 0.03388 Total loss: 0.96166 timestamp: 1655049920.5813937 iteration: 52525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06947 FastRCNN class loss: 0.06399 FastRCNN total loss: 0.13346 L1 loss: 0.0000e+00 L2 loss: 0.58176 Learning rate: 0.002 Mask loss: 0.13882 RPN box loss: 0.027 RPN score loss: 0.00622 RPN total loss: 0.03322 Total loss: 0.88726 timestamp: 1655049923.8619528 iteration: 52530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1098 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 0.58175 Learning rate: 0.002 Mask loss: 0.11979 RPN box loss: 0.01274 RPN score loss: 0.0025 RPN total loss: 0.01524 Total loss: 0.88265 timestamp: 1655049927.166883 iteration: 52535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15096 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.219 L1 loss: 0.0000e+00 L2 loss: 0.58174 Learning rate: 0.002 Mask loss: 0.14166 RPN box loss: 0.00995 RPN score loss: 0.00463 RPN total loss: 0.01458 Total loss: 0.95699 timestamp: 1655049930.4132614 iteration: 52540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12118 FastRCNN class loss: 0.08613 FastRCNN total loss: 0.20731 L1 loss: 0.0000e+00 L2 loss: 0.58174 Learning rate: 0.002 Mask loss: 0.18982 RPN box loss: 0.01985 RPN score loss: 0.00494 RPN total loss: 0.02479 Total loss: 1.00365 timestamp: 1655049933.6683598 iteration: 52545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.15027 L1 loss: 0.0000e+00 L2 loss: 0.58173 Learning rate: 0.002 Mask loss: 0.17906 RPN box loss: 0.03468 RPN score loss: 0.00426 RPN total loss: 0.03894 Total loss: 0.95 timestamp: 1655049936.8803687 iteration: 52550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.05116 FastRCNN total loss: 0.14033 L1 loss: 0.0000e+00 L2 loss: 0.58172 Learning rate: 0.002 Mask loss: 0.14039 RPN box loss: 0.00906 RPN score loss: 0.00258 RPN total loss: 0.01164 Total loss: 0.87409 timestamp: 1655049940.2066848 iteration: 52555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10332 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.16815 L1 loss: 0.0000e+00 L2 loss: 0.58171 Learning rate: 0.002 Mask loss: 0.22469 RPN box loss: 0.04447 RPN score loss: 0.00578 RPN total loss: 0.05025 Total loss: 1.0248 timestamp: 1655049943.486395 iteration: 52560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07528 FastRCNN class loss: 0.11246 FastRCNN total loss: 0.18774 L1 loss: 0.0000e+00 L2 loss: 0.5817 Learning rate: 0.002 Mask loss: 0.14684 RPN box loss: 0.0199 RPN score loss: 0.00608 RPN total loss: 0.02598 Total loss: 0.94226 timestamp: 1655049946.738948 iteration: 52565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14549 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 0.58169 Learning rate: 0.002 Mask loss: 0.17089 RPN box loss: 0.02368 RPN score loss: 0.00411 RPN total loss: 0.02778 Total loss: 1.02038 timestamp: 1655049950.050778 iteration: 52570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.04941 FastRCNN total loss: 0.14672 L1 loss: 0.0000e+00 L2 loss: 0.58168 Learning rate: 0.002 Mask loss: 0.09937 RPN box loss: 0.00805 RPN score loss: 0.00156 RPN total loss: 0.0096 Total loss: 0.83737 timestamp: 1655049953.3114283 iteration: 52575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09608 FastRCNN class loss: 0.07221 FastRCNN total loss: 0.16829 L1 loss: 0.0000e+00 L2 loss: 0.58167 Learning rate: 0.002 Mask loss: 0.1418 RPN box loss: 0.0072 RPN score loss: 0.00497 RPN total loss: 0.01217 Total loss: 0.90393 timestamp: 1655049956.587123 iteration: 52580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10948 FastRCNN class loss: 0.09682 FastRCNN total loss: 0.2063 L1 loss: 0.0000e+00 L2 loss: 0.58166 Learning rate: 0.002 Mask loss: 0.19401 RPN box loss: 0.03314 RPN score loss: 0.01792 RPN total loss: 0.05106 Total loss: 1.03302 timestamp: 1655049959.9047377 iteration: 52585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.05535 FastRCNN total loss: 0.16301 L1 loss: 0.0000e+00 L2 loss: 0.58165 Learning rate: 0.002 Mask loss: 0.18163 RPN box loss: 0.01883 RPN score loss: 0.0076 RPN total loss: 0.02643 Total loss: 0.95272 timestamp: 1655049963.1778681 iteration: 52590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13801 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.18261 L1 loss: 0.0000e+00 L2 loss: 0.58164 Learning rate: 0.002 Mask loss: 0.09647 RPN box loss: 0.01404 RPN score loss: 0.00356 RPN total loss: 0.0176 Total loss: 0.87832 timestamp: 1655049966.4609876 iteration: 52595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16131 FastRCNN class loss: 0.11828 FastRCNN total loss: 0.27959 L1 loss: 0.0000e+00 L2 loss: 0.58163 Learning rate: 0.002 Mask loss: 0.13617 RPN box loss: 0.02832 RPN score loss: 0.00848 RPN total loss: 0.0368 Total loss: 1.03419 timestamp: 1655049969.7944992 iteration: 52600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10972 FastRCNN class loss: 0.06095 FastRCNN total loss: 0.17067 L1 loss: 0.0000e+00 L2 loss: 0.58162 Learning rate: 0.002 Mask loss: 0.17891 RPN box loss: 0.01832 RPN score loss: 0.00135 RPN total loss: 0.01967 Total loss: 0.95088 timestamp: 1655049973.0996318 iteration: 52605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10923 FastRCNN class loss: 0.051 FastRCNN total loss: 0.16023 L1 loss: 0.0000e+00 L2 loss: 0.58162 Learning rate: 0.002 Mask loss: 0.16007 RPN box loss: 0.00353 RPN score loss: 0.00171 RPN total loss: 0.00524 Total loss: 0.90716 timestamp: 1655049976.389249 iteration: 52610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11002 FastRCNN class loss: 0.07376 FastRCNN total loss: 0.18378 L1 loss: 0.0000e+00 L2 loss: 0.58161 Learning rate: 0.002 Mask loss: 0.08853 RPN box loss: 0.00682 RPN score loss: 0.00366 RPN total loss: 0.01048 Total loss: 0.8644 timestamp: 1655049979.6036122 iteration: 52615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09224 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.5816 Learning rate: 0.002 Mask loss: 0.18343 RPN box loss: 0.01034 RPN score loss: 0.01266 RPN total loss: 0.023 Total loss: 0.95019 timestamp: 1655049982.8601258 iteration: 52620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11035 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.18765 L1 loss: 0.0000e+00 L2 loss: 0.5816 Learning rate: 0.002 Mask loss: 0.26603 RPN box loss: 0.01849 RPN score loss: 0.00373 RPN total loss: 0.02222 Total loss: 1.05749 timestamp: 1655049986.1964087 iteration: 52625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11128 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.18096 L1 loss: 0.0000e+00 L2 loss: 0.58159 Learning rate: 0.002 Mask loss: 0.11699 RPN box loss: 0.00831 RPN score loss: 0.00601 RPN total loss: 0.01431 Total loss: 0.89386 timestamp: 1655049989.480135 iteration: 52630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06652 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.13125 L1 loss: 0.0000e+00 L2 loss: 0.58158 Learning rate: 0.002 Mask loss: 0.11997 RPN box loss: 0.0193 RPN score loss: 0.00471 RPN total loss: 0.02401 Total loss: 0.8568 timestamp: 1655049992.787685 iteration: 52635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09002 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.14679 L1 loss: 0.0000e+00 L2 loss: 0.58157 Learning rate: 0.002 Mask loss: 0.09261 RPN box loss: 0.00384 RPN score loss: 0.00158 RPN total loss: 0.00542 Total loss: 0.82639 timestamp: 1655049996.0753143 iteration: 52640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13137 FastRCNN class loss: 0.0664 FastRCNN total loss: 0.19777 L1 loss: 0.0000e+00 L2 loss: 0.58156 Learning rate: 0.002 Mask loss: 0.1327 RPN box loss: 0.02317 RPN score loss: 0.00749 RPN total loss: 0.03066 Total loss: 0.9427 timestamp: 1655049999.359472 iteration: 52645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05106 FastRCNN class loss: 0.04456 FastRCNN total loss: 0.09562 L1 loss: 0.0000e+00 L2 loss: 0.58155 Learning rate: 0.002 Mask loss: 0.08781 RPN box loss: 0.00364 RPN score loss: 0.00579 RPN total loss: 0.00943 Total loss: 0.77441 timestamp: 1655050002.6888237 iteration: 52650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10676 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.15557 L1 loss: 0.0000e+00 L2 loss: 0.58154 Learning rate: 0.002 Mask loss: 0.11685 RPN box loss: 0.00534 RPN score loss: 0.00225 RPN total loss: 0.00759 Total loss: 0.86156 timestamp: 1655050006.0270023 iteration: 52655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.14577 L1 loss: 0.0000e+00 L2 loss: 0.58154 Learning rate: 0.002 Mask loss: 0.1542 RPN box loss: 0.01041 RPN score loss: 0.00552 RPN total loss: 0.01593 Total loss: 0.89743 timestamp: 1655050009.3330379 iteration: 52660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12254 FastRCNN class loss: 0.07684 FastRCNN total loss: 0.19938 L1 loss: 0.0000e+00 L2 loss: 0.58153 Learning rate: 0.002 Mask loss: 0.12572 RPN box loss: 0.0131 RPN score loss: 0.00277 RPN total loss: 0.01587 Total loss: 0.9225 timestamp: 1655050012.5085456 iteration: 52665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1669 FastRCNN class loss: 0.09092 FastRCNN total loss: 0.25782 L1 loss: 0.0000e+00 L2 loss: 0.58152 Learning rate: 0.002 Mask loss: 0.14211 RPN box loss: 0.02856 RPN score loss: 0.00514 RPN total loss: 0.0337 Total loss: 1.01515 timestamp: 1655050015.7541275 iteration: 52670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13708 FastRCNN class loss: 0.09581 FastRCNN total loss: 0.23289 L1 loss: 0.0000e+00 L2 loss: 0.58152 Learning rate: 0.002 Mask loss: 0.20586 RPN box loss: 0.01548 RPN score loss: 0.00711 RPN total loss: 0.02259 Total loss: 1.04285 timestamp: 1655050019.0276392 iteration: 52675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13249 FastRCNN class loss: 0.06478 FastRCNN total loss: 0.19727 L1 loss: 0.0000e+00 L2 loss: 0.5815 Learning rate: 0.002 Mask loss: 0.13061 RPN box loss: 0.00463 RPN score loss: 0.00185 RPN total loss: 0.00648 Total loss: 0.91587 timestamp: 1655050022.3669393 iteration: 52680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10613 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.17085 L1 loss: 0.0000e+00 L2 loss: 0.58149 Learning rate: 0.002 Mask loss: 0.1771 RPN box loss: 0.01129 RPN score loss: 0.0046 RPN total loss: 0.01589 Total loss: 0.94533 timestamp: 1655050025.628787 iteration: 52685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0687 FastRCNN class loss: 0.08536 FastRCNN total loss: 0.15406 L1 loss: 0.0000e+00 L2 loss: 0.58148 Learning rate: 0.002 Mask loss: 0.15424 RPN box loss: 0.03317 RPN score loss: 0.00673 RPN total loss: 0.0399 Total loss: 0.92967 timestamp: 1655050028.929829 iteration: 52690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07604 FastRCNN class loss: 0.11731 FastRCNN total loss: 0.19334 L1 loss: 0.0000e+00 L2 loss: 0.58148 Learning rate: 0.002 Mask loss: 0.13827 RPN box loss: 0.02208 RPN score loss: 0.01164 RPN total loss: 0.03373 Total loss: 0.94682 timestamp: 1655050032.2173598 iteration: 52695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03371 FastRCNN class loss: 0.04038 FastRCNN total loss: 0.07409 L1 loss: 0.0000e+00 L2 loss: 0.58147 Learning rate: 0.002 Mask loss: 0.13393 RPN box loss: 0.02144 RPN score loss: 0.00089 RPN total loss: 0.02233 Total loss: 0.81183 timestamp: 1655050035.5296245 iteration: 52700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08737 FastRCNN class loss: 0.06453 FastRCNN total loss: 0.15189 L1 loss: 0.0000e+00 L2 loss: 0.58146 Learning rate: 0.002 Mask loss: 0.13359 RPN box loss: 0.02643 RPN score loss: 0.00745 RPN total loss: 0.03389 Total loss: 0.90083 timestamp: 1655050038.762597 iteration: 52705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10465 FastRCNN class loss: 0.08982 FastRCNN total loss: 0.19447 L1 loss: 0.0000e+00 L2 loss: 0.58145 Learning rate: 0.002 Mask loss: 0.15991 RPN box loss: 0.03185 RPN score loss: 0.00649 RPN total loss: 0.03834 Total loss: 0.97418 timestamp: 1655050042.04962 iteration: 52710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05118 FastRCNN class loss: 0.04337 FastRCNN total loss: 0.09455 L1 loss: 0.0000e+00 L2 loss: 0.58144 Learning rate: 0.002 Mask loss: 0.10986 RPN box loss: 0.01657 RPN score loss: 0.00499 RPN total loss: 0.02156 Total loss: 0.80741 timestamp: 1655050045.3303366 iteration: 52715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12642 FastRCNN class loss: 0.10304 FastRCNN total loss: 0.22947 L1 loss: 0.0000e+00 L2 loss: 0.58143 Learning rate: 0.002 Mask loss: 0.10346 RPN box loss: 0.01386 RPN score loss: 0.00561 RPN total loss: 0.01947 Total loss: 0.93383 timestamp: 1655050048.6190462 iteration: 52720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07214 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.14443 L1 loss: 0.0000e+00 L2 loss: 0.58142 Learning rate: 0.002 Mask loss: 0.135 RPN box loss: 0.02113 RPN score loss: 0.01209 RPN total loss: 0.03322 Total loss: 0.89407 timestamp: 1655050051.9023752 iteration: 52725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07724 FastRCNN class loss: 0.07551 FastRCNN total loss: 0.15275 L1 loss: 0.0000e+00 L2 loss: 0.58142 Learning rate: 0.002 Mask loss: 0.17471 RPN box loss: 0.01143 RPN score loss: 0.00654 RPN total loss: 0.01797 Total loss: 0.92684 timestamp: 1655050055.1049838 iteration: 52730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.05789 FastRCNN total loss: 0.16069 L1 loss: 0.0000e+00 L2 loss: 0.58141 Learning rate: 0.002 Mask loss: 0.10869 RPN box loss: 0.02259 RPN score loss: 0.00519 RPN total loss: 0.02777 Total loss: 0.87857 timestamp: 1655050058.440727 iteration: 52735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09305 FastRCNN class loss: 0.05789 FastRCNN total loss: 0.15094 L1 loss: 0.0000e+00 L2 loss: 0.5814 Learning rate: 0.002 Mask loss: 0.13375 RPN box loss: 0.00761 RPN score loss: 0.00253 RPN total loss: 0.01014 Total loss: 0.87622 timestamp: 1655050061.7085044 iteration: 52740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14276 FastRCNN class loss: 0.07172 FastRCNN total loss: 0.21448 L1 loss: 0.0000e+00 L2 loss: 0.58139 Learning rate: 0.002 Mask loss: 0.15339 RPN box loss: 0.05314 RPN score loss: 0.0028 RPN total loss: 0.05594 Total loss: 1.0052 timestamp: 1655050065.0263383 iteration: 52745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1218 FastRCNN class loss: 0.07275 FastRCNN total loss: 0.19455 L1 loss: 0.0000e+00 L2 loss: 0.58138 Learning rate: 0.002 Mask loss: 0.15683 RPN box loss: 0.08083 RPN score loss: 0.00584 RPN total loss: 0.08667 Total loss: 1.01943 timestamp: 1655050068.3082385 iteration: 52750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12245 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.18413 L1 loss: 0.0000e+00 L2 loss: 0.58137 Learning rate: 0.002 Mask loss: 0.12565 RPN box loss: 0.03129 RPN score loss: 0.00172 RPN total loss: 0.03302 Total loss: 0.92417 timestamp: 1655050071.5646207 iteration: 52755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16436 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.22581 L1 loss: 0.0000e+00 L2 loss: 0.58137 Learning rate: 0.002 Mask loss: 0.19109 RPN box loss: 0.021 RPN score loss: 0.00891 RPN total loss: 0.02991 Total loss: 1.02818 timestamp: 1655050074.8002102 iteration: 52760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.10072 FastRCNN total loss: 0.21321 L1 loss: 0.0000e+00 L2 loss: 0.58136 Learning rate: 0.002 Mask loss: 0.15123 RPN box loss: 0.01422 RPN score loss: 0.00546 RPN total loss: 0.01968 Total loss: 0.96548 timestamp: 1655050078.1116352 iteration: 52765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12009 FastRCNN class loss: 0.08501 FastRCNN total loss: 0.2051 L1 loss: 0.0000e+00 L2 loss: 0.58135 Learning rate: 0.002 Mask loss: 0.1655 RPN box loss: 0.02165 RPN score loss: 0.00315 RPN total loss: 0.0248 Total loss: 0.97675 timestamp: 1655050081.3703797 iteration: 52770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05802 FastRCNN class loss: 0.06464 FastRCNN total loss: 0.12266 L1 loss: 0.0000e+00 L2 loss: 0.58134 Learning rate: 0.002 Mask loss: 0.10245 RPN box loss: 0.01671 RPN score loss: 0.002 RPN total loss: 0.0187 Total loss: 0.82516 timestamp: 1655050084.6776505 iteration: 52775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0911 FastRCNN class loss: 0.10747 FastRCNN total loss: 0.19858 L1 loss: 0.0000e+00 L2 loss: 0.58133 Learning rate: 0.002 Mask loss: 0.15325 RPN box loss: 0.01137 RPN score loss: 0.00354 RPN total loss: 0.01491 Total loss: 0.94806 timestamp: 1655050087.9672086 iteration: 52780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11517 FastRCNN class loss: 0.04647 FastRCNN total loss: 0.16164 L1 loss: 0.0000e+00 L2 loss: 0.58133 Learning rate: 0.002 Mask loss: 0.10757 RPN box loss: 0.02191 RPN score loss: 0.0003 RPN total loss: 0.02221 Total loss: 0.87274 timestamp: 1655050091.252207 iteration: 52785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.15617 L1 loss: 0.0000e+00 L2 loss: 0.58132 Learning rate: 0.002 Mask loss: 0.13629 RPN box loss: 0.03367 RPN score loss: 0.00417 RPN total loss: 0.03784 Total loss: 0.91162 timestamp: 1655050094.5472782 iteration: 52790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05799 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.10913 L1 loss: 0.0000e+00 L2 loss: 0.58131 Learning rate: 0.002 Mask loss: 0.12768 RPN box loss: 0.01111 RPN score loss: 0.00487 RPN total loss: 0.01598 Total loss: 0.8341 timestamp: 1655050097.8239388 iteration: 52795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06884 FastRCNN class loss: 0.03556 FastRCNN total loss: 0.10439 L1 loss: 0.0000e+00 L2 loss: 0.5813 Learning rate: 0.002 Mask loss: 0.12152 RPN box loss: 0.00529 RPN score loss: 0.00205 RPN total loss: 0.00733 Total loss: 0.81455 timestamp: 1655050101.028755 iteration: 52800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.09808 FastRCNN total loss: 0.22251 L1 loss: 0.0000e+00 L2 loss: 0.58129 Learning rate: 0.002 Mask loss: 0.17865 RPN box loss: 0.02416 RPN score loss: 0.00368 RPN total loss: 0.02783 Total loss: 1.01028 timestamp: 1655050104.2941806 iteration: 52805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.084 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.14932 L1 loss: 0.0000e+00 L2 loss: 0.58128 Learning rate: 0.002 Mask loss: 0.09535 RPN box loss: 0.00706 RPN score loss: 0.0008 RPN total loss: 0.00787 Total loss: 0.83382 timestamp: 1655050107.5152254 iteration: 52810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10736 FastRCNN class loss: 0.06256 FastRCNN total loss: 0.16993 L1 loss: 0.0000e+00 L2 loss: 0.58127 Learning rate: 0.002 Mask loss: 0.17183 RPN box loss: 0.04885 RPN score loss: 0.00788 RPN total loss: 0.05673 Total loss: 0.97976 timestamp: 1655050110.8240867 iteration: 52815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08542 FastRCNN class loss: 0.05306 FastRCNN total loss: 0.13847 L1 loss: 0.0000e+00 L2 loss: 0.58126 Learning rate: 0.002 Mask loss: 0.12896 RPN box loss: 0.01101 RPN score loss: 0.00322 RPN total loss: 0.01423 Total loss: 0.86292 timestamp: 1655050114.0588071 iteration: 52820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16826 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.23741 L1 loss: 0.0000e+00 L2 loss: 0.58125 Learning rate: 0.002 Mask loss: 0.1074 RPN box loss: 0.01247 RPN score loss: 0.00519 RPN total loss: 0.01766 Total loss: 0.94372 timestamp: 1655050117.3672652 iteration: 52825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09096 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.15145 L1 loss: 0.0000e+00 L2 loss: 0.58124 Learning rate: 0.002 Mask loss: 0.14045 RPN box loss: 0.01394 RPN score loss: 0.00594 RPN total loss: 0.01988 Total loss: 0.89302 timestamp: 1655050120.644352 iteration: 52830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0716 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.14656 L1 loss: 0.0000e+00 L2 loss: 0.58124 Learning rate: 0.002 Mask loss: 0.18746 RPN box loss: 0.02494 RPN score loss: 0.00159 RPN total loss: 0.02653 Total loss: 0.94179 timestamp: 1655050123.8833716 iteration: 52835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10849 FastRCNN class loss: 0.09208 FastRCNN total loss: 0.20057 L1 loss: 0.0000e+00 L2 loss: 0.58123 Learning rate: 0.002 Mask loss: 0.1103 RPN box loss: 0.01771 RPN score loss: 0.00254 RPN total loss: 0.02024 Total loss: 0.91233 timestamp: 1655050127.116009 iteration: 52840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18958 FastRCNN class loss: 0.12643 FastRCNN total loss: 0.31601 L1 loss: 0.0000e+00 L2 loss: 0.58122 Learning rate: 0.002 Mask loss: 0.1955 RPN box loss: 0.0176 RPN score loss: 0.01311 RPN total loss: 0.03071 Total loss: 1.12344 timestamp: 1655050130.300794 iteration: 52845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06994 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.11883 L1 loss: 0.0000e+00 L2 loss: 0.58121 Learning rate: 0.002 Mask loss: 0.10115 RPN box loss: 0.02353 RPN score loss: 0.00759 RPN total loss: 0.03112 Total loss: 0.8323 timestamp: 1655050133.6067924 iteration: 52850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11688 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.17909 L1 loss: 0.0000e+00 L2 loss: 0.5812 Learning rate: 0.002 Mask loss: 0.14344 RPN box loss: 0.01163 RPN score loss: 0.00455 RPN total loss: 0.01617 Total loss: 0.9199 timestamp: 1655050136.9043937 iteration: 52855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09191 FastRCNN class loss: 0.08601 FastRCNN total loss: 0.17791 L1 loss: 0.0000e+00 L2 loss: 0.58119 Learning rate: 0.002 Mask loss: 0.16318 RPN box loss: 0.01414 RPN score loss: 0.01263 RPN total loss: 0.02677 Total loss: 0.94906 timestamp: 1655050140.2085607 iteration: 52860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13001 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.20076 L1 loss: 0.0000e+00 L2 loss: 0.58118 Learning rate: 0.002 Mask loss: 0.09463 RPN box loss: 0.0207 RPN score loss: 0.00228 RPN total loss: 0.02298 Total loss: 0.89956 timestamp: 1655050143.4779718 iteration: 52865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07967 FastRCNN class loss: 0.06132 FastRCNN total loss: 0.14099 L1 loss: 0.0000e+00 L2 loss: 0.58117 Learning rate: 0.002 Mask loss: 0.13032 RPN box loss: 0.01467 RPN score loss: 0.00568 RPN total loss: 0.02035 Total loss: 0.87283 timestamp: 1655050146.8052206 iteration: 52870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.081 FastRCNN class loss: 0.05708 FastRCNN total loss: 0.13808 L1 loss: 0.0000e+00 L2 loss: 0.58116 Learning rate: 0.002 Mask loss: 0.16483 RPN box loss: 0.01651 RPN score loss: 0.01113 RPN total loss: 0.02764 Total loss: 0.91171 timestamp: 1655050150.0805438 iteration: 52875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09853 FastRCNN class loss: 0.07633 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 0.58115 Learning rate: 0.002 Mask loss: 0.12817 RPN box loss: 0.02829 RPN score loss: 0.00278 RPN total loss: 0.03107 Total loss: 0.91525 timestamp: 1655050153.3560522 iteration: 52880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09636 FastRCNN class loss: 0.04749 FastRCNN total loss: 0.14385 L1 loss: 0.0000e+00 L2 loss: 0.58114 Learning rate: 0.002 Mask loss: 0.108 RPN box loss: 0.01168 RPN score loss: 0.00363 RPN total loss: 0.01531 Total loss: 0.8483 timestamp: 1655050156.5854778 iteration: 52885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08987 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.1369 L1 loss: 0.0000e+00 L2 loss: 0.58114 Learning rate: 0.002 Mask loss: 0.17592 RPN box loss: 0.01133 RPN score loss: 0.00354 RPN total loss: 0.01488 Total loss: 0.90883 timestamp: 1655050159.868075 iteration: 52890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11895 FastRCNN class loss: 0.07109 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 0.58113 Learning rate: 0.002 Mask loss: 0.18668 RPN box loss: 0.01081 RPN score loss: 0.00458 RPN total loss: 0.0154 Total loss: 0.97324 timestamp: 1655050163.1462176 iteration: 52895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08005 FastRCNN class loss: 0.07094 FastRCNN total loss: 0.15099 L1 loss: 0.0000e+00 L2 loss: 0.58112 Learning rate: 0.002 Mask loss: 0.13687 RPN box loss: 0.05778 RPN score loss: 0.00984 RPN total loss: 0.06762 Total loss: 0.9366 timestamp: 1655050166.424969 iteration: 52900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.119 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.21508 L1 loss: 0.0000e+00 L2 loss: 0.58111 Learning rate: 0.002 Mask loss: 0.17236 RPN box loss: 0.02019 RPN score loss: 0.0133 RPN total loss: 0.03349 Total loss: 1.00204 timestamp: 1655050169.6861002 iteration: 52905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1283 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 0.5811 Learning rate: 0.002 Mask loss: 0.14359 RPN box loss: 0.08147 RPN score loss: 0.00705 RPN total loss: 0.08852 Total loss: 1.00088 timestamp: 1655050172.9946687 iteration: 52910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14237 FastRCNN class loss: 0.0874 FastRCNN total loss: 0.22976 L1 loss: 0.0000e+00 L2 loss: 0.58109 Learning rate: 0.002 Mask loss: 0.18233 RPN box loss: 0.02647 RPN score loss: 0.00875 RPN total loss: 0.03522 Total loss: 1.02841 timestamp: 1655050176.2905858 iteration: 52915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07473 FastRCNN class loss: 0.0294 FastRCNN total loss: 0.10414 L1 loss: 0.0000e+00 L2 loss: 0.58109 Learning rate: 0.002 Mask loss: 0.09349 RPN box loss: 0.00699 RPN score loss: 0.00243 RPN total loss: 0.00942 Total loss: 0.78813 timestamp: 1655050179.5666342 iteration: 52920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12235 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.19809 L1 loss: 0.0000e+00 L2 loss: 0.58108 Learning rate: 0.002 Mask loss: 0.17869 RPN box loss: 0.04415 RPN score loss: 0.01026 RPN total loss: 0.05441 Total loss: 1.01227 timestamp: 1655050182.8938293 iteration: 52925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18456 FastRCNN class loss: 0.0856 FastRCNN total loss: 0.27015 L1 loss: 0.0000e+00 L2 loss: 0.58107 Learning rate: 0.002 Mask loss: 0.22058 RPN box loss: 0.02219 RPN score loss: 0.00546 RPN total loss: 0.02765 Total loss: 1.09946 timestamp: 1655050186.1708918 iteration: 52930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08936 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.15018 L1 loss: 0.0000e+00 L2 loss: 0.58106 Learning rate: 0.002 Mask loss: 0.20258 RPN box loss: 0.02306 RPN score loss: 0.00221 RPN total loss: 0.02528 Total loss: 0.95909 timestamp: 1655050189.465892 iteration: 52935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10186 FastRCNN class loss: 0.09065 FastRCNN total loss: 0.19252 L1 loss: 0.0000e+00 L2 loss: 0.58105 Learning rate: 0.002 Mask loss: 0.13108 RPN box loss: 0.02181 RPN score loss: 0.00652 RPN total loss: 0.02832 Total loss: 0.93297 timestamp: 1655050192.7332373 iteration: 52940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.03443 FastRCNN total loss: 0.10514 L1 loss: 0.0000e+00 L2 loss: 0.58104 Learning rate: 0.002 Mask loss: 0.26638 RPN box loss: 0.02094 RPN score loss: 0.0016 RPN total loss: 0.02254 Total loss: 0.97511 timestamp: 1655050196.0384889 iteration: 52945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07781 FastRCNN class loss: 0.07034 FastRCNN total loss: 0.14815 L1 loss: 0.0000e+00 L2 loss: 0.58103 Learning rate: 0.002 Mask loss: 0.15547 RPN box loss: 0.02348 RPN score loss: 0.0166 RPN total loss: 0.04007 Total loss: 0.92472 timestamp: 1655050199.3496332 iteration: 52950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09431 FastRCNN class loss: 0.05922 FastRCNN total loss: 0.15352 L1 loss: 0.0000e+00 L2 loss: 0.58102 Learning rate: 0.002 Mask loss: 0.1134 RPN box loss: 0.05826 RPN score loss: 0.00571 RPN total loss: 0.06397 Total loss: 0.91191 timestamp: 1655050202.614852 iteration: 52955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.17383 L1 loss: 0.0000e+00 L2 loss: 0.58102 Learning rate: 0.002 Mask loss: 0.1297 RPN box loss: 0.01144 RPN score loss: 0.00576 RPN total loss: 0.0172 Total loss: 0.90175 timestamp: 1655050205.85458 iteration: 52960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06734 FastRCNN class loss: 0.06529 FastRCNN total loss: 0.13263 L1 loss: 0.0000e+00 L2 loss: 0.58101 Learning rate: 0.002 Mask loss: 0.10967 RPN box loss: 0.00767 RPN score loss: 0.00427 RPN total loss: 0.01194 Total loss: 0.83525 timestamp: 1655050209.1176484 iteration: 52965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11363 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.19419 L1 loss: 0.0000e+00 L2 loss: 0.581 Learning rate: 0.002 Mask loss: 0.127 RPN box loss: 0.02342 RPN score loss: 0.00654 RPN total loss: 0.02996 Total loss: 0.93216 timestamp: 1655050212.3615096 iteration: 52970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13086 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.21502 L1 loss: 0.0000e+00 L2 loss: 0.58099 Learning rate: 0.002 Mask loss: 0.12064 RPN box loss: 0.02297 RPN score loss: 0.01027 RPN total loss: 0.03325 Total loss: 0.9499 timestamp: 1655050215.6707006 iteration: 52975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05523 FastRCNN class loss: 0.04305 FastRCNN total loss: 0.09828 L1 loss: 0.0000e+00 L2 loss: 0.58098 Learning rate: 0.002 Mask loss: 0.13582 RPN box loss: 0.00155 RPN score loss: 0.00059 RPN total loss: 0.00214 Total loss: 0.81723 timestamp: 1655050218.8831723 iteration: 52980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14474 FastRCNN class loss: 0.06839 FastRCNN total loss: 0.21313 L1 loss: 0.0000e+00 L2 loss: 0.58097 Learning rate: 0.002 Mask loss: 0.15098 RPN box loss: 0.01332 RPN score loss: 0.00483 RPN total loss: 0.01815 Total loss: 0.96323 timestamp: 1655050222.1729848 iteration: 52985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06909 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.13555 L1 loss: 0.0000e+00 L2 loss: 0.58097 Learning rate: 0.002 Mask loss: 0.14256 RPN box loss: 0.01335 RPN score loss: 0.00301 RPN total loss: 0.01636 Total loss: 0.87543 timestamp: 1655050225.5086157 iteration: 52990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11497 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.17334 L1 loss: 0.0000e+00 L2 loss: 0.58096 Learning rate: 0.002 Mask loss: 0.13088 RPN box loss: 0.01114 RPN score loss: 0.00493 RPN total loss: 0.01606 Total loss: 0.90125 timestamp: 1655050228.7881534 iteration: 52995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08147 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.14723 L1 loss: 0.0000e+00 L2 loss: 0.58095 Learning rate: 0.002 Mask loss: 0.11047 RPN box loss: 0.06455 RPN score loss: 0.00615 RPN total loss: 0.07071 Total loss: 0.90935 timestamp: 1655050232.0242534 iteration: 53000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09922 FastRCNN class loss: 0.08744 FastRCNN total loss: 0.18667 L1 loss: 0.0000e+00 L2 loss: 0.58094 Learning rate: 0.002 Mask loss: 0.13725 RPN box loss: 0.02113 RPN score loss: 0.00596 RPN total loss: 0.02709 Total loss: 0.93195 timestamp: 1655050235.2546492 iteration: 53005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.14909 L1 loss: 0.0000e+00 L2 loss: 0.58093 Learning rate: 0.002 Mask loss: 0.15552 RPN box loss: 0.01328 RPN score loss: 0.00702 RPN total loss: 0.0203 Total loss: 0.90584 timestamp: 1655050238.495028 iteration: 53010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10499 FastRCNN class loss: 0.11427 FastRCNN total loss: 0.21927 L1 loss: 0.0000e+00 L2 loss: 0.58092 Learning rate: 0.002 Mask loss: 0.26408 RPN box loss: 0.02512 RPN score loss: 0.00812 RPN total loss: 0.03324 Total loss: 1.0975 timestamp: 1655050241.8585756 iteration: 53015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12659 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.21151 L1 loss: 0.0000e+00 L2 loss: 0.58091 Learning rate: 0.002 Mask loss: 0.12659 RPN box loss: 0.0163 RPN score loss: 0.00771 RPN total loss: 0.02401 Total loss: 0.94302 timestamp: 1655050245.137676 iteration: 53020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10802 FastRCNN class loss: 0.04806 FastRCNN total loss: 0.15608 L1 loss: 0.0000e+00 L2 loss: 0.58091 Learning rate: 0.002 Mask loss: 0.1295 RPN box loss: 0.00603 RPN score loss: 0.00208 RPN total loss: 0.00811 Total loss: 0.87461 timestamp: 1655050248.4084296 iteration: 53025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12561 FastRCNN class loss: 0.08296 FastRCNN total loss: 0.20857 L1 loss: 0.0000e+00 L2 loss: 0.5809 Learning rate: 0.002 Mask loss: 0.13149 RPN box loss: 0.02056 RPN score loss: 0.00223 RPN total loss: 0.02279 Total loss: 0.94376 timestamp: 1655050251.626626 iteration: 53030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09992 FastRCNN class loss: 0.06007 FastRCNN total loss: 0.15999 L1 loss: 0.0000e+00 L2 loss: 0.58089 Learning rate: 0.002 Mask loss: 0.13986 RPN box loss: 0.00844 RPN score loss: 0.01252 RPN total loss: 0.02096 Total loss: 0.90171 timestamp: 1655050254.8787336 iteration: 53035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0801 FastRCNN class loss: 0.049 FastRCNN total loss: 0.12909 L1 loss: 0.0000e+00 L2 loss: 0.58088 Learning rate: 0.002 Mask loss: 0.12012 RPN box loss: 0.00783 RPN score loss: 0.00221 RPN total loss: 0.01004 Total loss: 0.84014 timestamp: 1655050258.1109734 iteration: 53040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.2033 FastRCNN class loss: 0.08273 FastRCNN total loss: 0.28603 L1 loss: 0.0000e+00 L2 loss: 0.58088 Learning rate: 0.002 Mask loss: 0.14569 RPN box loss: 0.02617 RPN score loss: 0.0061 RPN total loss: 0.03228 Total loss: 1.04488 timestamp: 1655050261.37436 iteration: 53045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16664 FastRCNN class loss: 0.07696 FastRCNN total loss: 0.2436 L1 loss: 0.0000e+00 L2 loss: 0.58087 Learning rate: 0.002 Mask loss: 0.14626 RPN box loss: 0.01447 RPN score loss: 0.00725 RPN total loss: 0.02172 Total loss: 0.99246 timestamp: 1655050264.685573 iteration: 53050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12411 FastRCNN class loss: 0.08815 FastRCNN total loss: 0.21226 L1 loss: 0.0000e+00 L2 loss: 0.58086 Learning rate: 0.002 Mask loss: 0.17437 RPN box loss: 0.02214 RPN score loss: 0.00781 RPN total loss: 0.02995 Total loss: 0.99744 timestamp: 1655050267.9355736 iteration: 53055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10098 FastRCNN class loss: 0.07292 FastRCNN total loss: 0.17391 L1 loss: 0.0000e+00 L2 loss: 0.58085 Learning rate: 0.002 Mask loss: 0.12257 RPN box loss: 0.01213 RPN score loss: 0.01205 RPN total loss: 0.02418 Total loss: 0.90151 timestamp: 1655050271.1773338 iteration: 53060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17507 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.24754 L1 loss: 0.0000e+00 L2 loss: 0.58084 Learning rate: 0.002 Mask loss: 0.11672 RPN box loss: 0.01013 RPN score loss: 0.00751 RPN total loss: 0.01764 Total loss: 0.96274 timestamp: 1655050274.4797554 iteration: 53065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09556 FastRCNN class loss: 0.05551 FastRCNN total loss: 0.15107 L1 loss: 0.0000e+00 L2 loss: 0.58083 Learning rate: 0.002 Mask loss: 0.1263 RPN box loss: 0.00908 RPN score loss: 0.00475 RPN total loss: 0.01383 Total loss: 0.87202 timestamp: 1655050277.7161624 iteration: 53070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12018 FastRCNN class loss: 0.09551 FastRCNN total loss: 0.2157 L1 loss: 0.0000e+00 L2 loss: 0.58082 Learning rate: 0.002 Mask loss: 0.14538 RPN box loss: 0.00879 RPN score loss: 0.01166 RPN total loss: 0.02045 Total loss: 0.96235 timestamp: 1655050281.1377048 iteration: 53075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12476 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.19711 L1 loss: 0.0000e+00 L2 loss: 0.58082 Learning rate: 0.002 Mask loss: 0.13041 RPN box loss: 0.01757 RPN score loss: 0.00208 RPN total loss: 0.01965 Total loss: 0.92798 timestamp: 1655050284.4483833 iteration: 53080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13242 FastRCNN class loss: 0.05655 FastRCNN total loss: 0.18897 L1 loss: 0.0000e+00 L2 loss: 0.58081 Learning rate: 0.002 Mask loss: 0.14811 RPN box loss: 0.01177 RPN score loss: 0.00237 RPN total loss: 0.01414 Total loss: 0.93203 timestamp: 1655050287.6592402 iteration: 53085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14387 FastRCNN class loss: 0.0766 FastRCNN total loss: 0.22047 L1 loss: 0.0000e+00 L2 loss: 0.5808 Learning rate: 0.002 Mask loss: 0.15138 RPN box loss: 0.02511 RPN score loss: 0.00514 RPN total loss: 0.03024 Total loss: 0.98289 timestamp: 1655050290.9305086 iteration: 53090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07223 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.12408 L1 loss: 0.0000e+00 L2 loss: 0.58079 Learning rate: 0.002 Mask loss: 0.13966 RPN box loss: 0.02473 RPN score loss: 0.00331 RPN total loss: 0.02804 Total loss: 0.87257 timestamp: 1655050294.2550619 iteration: 53095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13851 FastRCNN class loss: 0.11026 FastRCNN total loss: 0.24877 L1 loss: 0.0000e+00 L2 loss: 0.58079 Learning rate: 0.002 Mask loss: 0.27302 RPN box loss: 0.01176 RPN score loss: 0.00608 RPN total loss: 0.01783 Total loss: 1.12041 timestamp: 1655050297.5084727 iteration: 53100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.053 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.13344 L1 loss: 0.0000e+00 L2 loss: 0.58078 Learning rate: 0.002 Mask loss: 0.14576 RPN box loss: 0.01659 RPN score loss: 0.01552 RPN total loss: 0.03211 Total loss: 0.89208 timestamp: 1655050300.8138206 iteration: 53105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14152 FastRCNN class loss: 0.12639 FastRCNN total loss: 0.2679 L1 loss: 0.0000e+00 L2 loss: 0.58077 Learning rate: 0.002 Mask loss: 0.18252 RPN box loss: 0.02208 RPN score loss: 0.0088 RPN total loss: 0.03088 Total loss: 1.06207 timestamp: 1655050304.090484 iteration: 53110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.148 FastRCNN class loss: 0.11071 FastRCNN total loss: 0.25871 L1 loss: 0.0000e+00 L2 loss: 0.58076 Learning rate: 0.002 Mask loss: 0.1411 RPN box loss: 0.02284 RPN score loss: 0.00777 RPN total loss: 0.03061 Total loss: 1.01117 timestamp: 1655050307.3805285 iteration: 53115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14558 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.21447 L1 loss: 0.0000e+00 L2 loss: 0.58074 Learning rate: 0.002 Mask loss: 0.14043 RPN box loss: 0.03815 RPN score loss: 0.00875 RPN total loss: 0.0469 Total loss: 0.98254 timestamp: 1655050310.5736916 iteration: 53120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.08025 FastRCNN total loss: 0.19069 L1 loss: 0.0000e+00 L2 loss: 0.58073 Learning rate: 0.002 Mask loss: 0.12001 RPN box loss: 0.00973 RPN score loss: 0.00676 RPN total loss: 0.01649 Total loss: 0.90793 timestamp: 1655050313.8525262 iteration: 53125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.075 FastRCNN class loss: 0.08768 FastRCNN total loss: 0.16268 L1 loss: 0.0000e+00 L2 loss: 0.58073 Learning rate: 0.002 Mask loss: 0.1032 RPN box loss: 0.01392 RPN score loss: 0.00275 RPN total loss: 0.01667 Total loss: 0.86327 timestamp: 1655050317.1970274 iteration: 53130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03765 FastRCNN class loss: 0.03013 FastRCNN total loss: 0.06778 L1 loss: 0.0000e+00 L2 loss: 0.58072 Learning rate: 0.002 Mask loss: 0.08903 RPN box loss: 0.02776 RPN score loss: 0.0025 RPN total loss: 0.03026 Total loss: 0.76778 timestamp: 1655050320.4762099 iteration: 53135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10811 FastRCNN class loss: 0.05752 FastRCNN total loss: 0.16563 L1 loss: 0.0000e+00 L2 loss: 0.58071 Learning rate: 0.002 Mask loss: 0.15466 RPN box loss: 0.01977 RPN score loss: 0.01128 RPN total loss: 0.03105 Total loss: 0.93205 timestamp: 1655050323.7597914 iteration: 53140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13606 FastRCNN class loss: 0.10104 FastRCNN total loss: 0.2371 L1 loss: 0.0000e+00 L2 loss: 0.5807 Learning rate: 0.002 Mask loss: 0.17906 RPN box loss: 0.02874 RPN score loss: 0.01264 RPN total loss: 0.04138 Total loss: 1.03824 timestamp: 1655050327.0685337 iteration: 53145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13472 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.22487 L1 loss: 0.0000e+00 L2 loss: 0.58069 Learning rate: 0.002 Mask loss: 0.19615 RPN box loss: 0.02116 RPN score loss: 0.00796 RPN total loss: 0.02912 Total loss: 1.03083 timestamp: 1655050330.352736 iteration: 53150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11416 FastRCNN class loss: 0.10167 FastRCNN total loss: 0.21584 L1 loss: 0.0000e+00 L2 loss: 0.58068 Learning rate: 0.002 Mask loss: 0.151 RPN box loss: 0.01812 RPN score loss: 0.01217 RPN total loss: 0.03028 Total loss: 0.97781 timestamp: 1655050333.645627 iteration: 53155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11322 FastRCNN class loss: 0.07562 FastRCNN total loss: 0.18883 L1 loss: 0.0000e+00 L2 loss: 0.58068 Learning rate: 0.002 Mask loss: 0.13603 RPN box loss: 0.01349 RPN score loss: 0.00409 RPN total loss: 0.01758 Total loss: 0.92311 timestamp: 1655050336.8840945 iteration: 53160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09033 FastRCNN class loss: 0.10956 FastRCNN total loss: 0.19989 L1 loss: 0.0000e+00 L2 loss: 0.58066 Learning rate: 0.002 Mask loss: 0.15642 RPN box loss: 0.02334 RPN score loss: 0.01703 RPN total loss: 0.04037 Total loss: 0.97734 timestamp: 1655050340.147391 iteration: 53165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12183 FastRCNN class loss: 0.08227 FastRCNN total loss: 0.20411 L1 loss: 0.0000e+00 L2 loss: 0.58065 Learning rate: 0.002 Mask loss: 0.15531 RPN box loss: 0.02067 RPN score loss: 0.0055 RPN total loss: 0.02617 Total loss: 0.96624 timestamp: 1655050343.4029338 iteration: 53170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11672 FastRCNN class loss: 0.11428 FastRCNN total loss: 0.231 L1 loss: 0.0000e+00 L2 loss: 0.58064 Learning rate: 0.002 Mask loss: 0.13888 RPN box loss: 0.03079 RPN score loss: 0.00885 RPN total loss: 0.03964 Total loss: 0.99016 timestamp: 1655050346.6899393 iteration: 53175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08191 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.58064 Learning rate: 0.002 Mask loss: 0.13731 RPN box loss: 0.02353 RPN score loss: 0.00849 RPN total loss: 0.03202 Total loss: 0.92964 timestamp: 1655050349.96819 iteration: 53180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.10818 FastRCNN total loss: 0.20201 L1 loss: 0.0000e+00 L2 loss: 0.58063 Learning rate: 0.002 Mask loss: 0.20245 RPN box loss: 0.01417 RPN score loss: 0.01011 RPN total loss: 0.02429 Total loss: 1.00937 timestamp: 1655050353.2172184 iteration: 53185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12049 FastRCNN class loss: 0.11305 FastRCNN total loss: 0.23354 L1 loss: 0.0000e+00 L2 loss: 0.58062 Learning rate: 0.002 Mask loss: 0.17021 RPN box loss: 0.03041 RPN score loss: 0.0139 RPN total loss: 0.04431 Total loss: 1.02867 timestamp: 1655050356.4906309 iteration: 53190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.11597 FastRCNN total loss: 0.22763 L1 loss: 0.0000e+00 L2 loss: 0.58062 Learning rate: 0.002 Mask loss: 0.18054 RPN box loss: 0.02634 RPN score loss: 0.01387 RPN total loss: 0.04021 Total loss: 1.029 timestamp: 1655050359.7091649 iteration: 53195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13896 FastRCNN class loss: 0.10045 FastRCNN total loss: 0.2394 L1 loss: 0.0000e+00 L2 loss: 0.58061 Learning rate: 0.002 Mask loss: 0.14525 RPN box loss: 0.00839 RPN score loss: 0.00171 RPN total loss: 0.0101 Total loss: 0.97536 timestamp: 1655050362.9776492 iteration: 53200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13667 FastRCNN class loss: 0.0984 FastRCNN total loss: 0.23507 L1 loss: 0.0000e+00 L2 loss: 0.5806 Learning rate: 0.002 Mask loss: 0.17972 RPN box loss: 0.03486 RPN score loss: 0.00712 RPN total loss: 0.04198 Total loss: 1.03737 timestamp: 1655050366.2555327 iteration: 53205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12994 FastRCNN class loss: 0.07383 FastRCNN total loss: 0.20377 L1 loss: 0.0000e+00 L2 loss: 0.58059 Learning rate: 0.002 Mask loss: 0.16745 RPN box loss: 0.01142 RPN score loss: 0.00388 RPN total loss: 0.01529 Total loss: 0.9671 timestamp: 1655050369.557869 iteration: 53210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05141 FastRCNN class loss: 0.06125 FastRCNN total loss: 0.11266 L1 loss: 0.0000e+00 L2 loss: 0.58058 Learning rate: 0.002 Mask loss: 0.09975 RPN box loss: 0.00303 RPN score loss: 0.00132 RPN total loss: 0.00435 Total loss: 0.79734 timestamp: 1655050372.814777 iteration: 53215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16743 FastRCNN class loss: 0.12372 FastRCNN total loss: 0.29114 L1 loss: 0.0000e+00 L2 loss: 0.58057 Learning rate: 0.002 Mask loss: 0.14513 RPN box loss: 0.01718 RPN score loss: 0.0069 RPN total loss: 0.02407 Total loss: 1.04092 timestamp: 1655050376.0199623 iteration: 53220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1883 FastRCNN class loss: 0.11044 FastRCNN total loss: 0.29874 L1 loss: 0.0000e+00 L2 loss: 0.58057 Learning rate: 0.002 Mask loss: 0.20801 RPN box loss: 0.02251 RPN score loss: 0.00491 RPN total loss: 0.02742 Total loss: 1.11473 timestamp: 1655050379.2723231 iteration: 53225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08906 FastRCNN class loss: 0.05274 FastRCNN total loss: 0.1418 L1 loss: 0.0000e+00 L2 loss: 0.58056 Learning rate: 0.002 Mask loss: 0.16266 RPN box loss: 0.03302 RPN score loss: 0.0044 RPN total loss: 0.03742 Total loss: 0.92243 timestamp: 1655050382.5713832 iteration: 53230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11298 FastRCNN class loss: 0.08145 FastRCNN total loss: 0.19443 L1 loss: 0.0000e+00 L2 loss: 0.58054 Learning rate: 0.002 Mask loss: 0.09392 RPN box loss: 0.00655 RPN score loss: 0.00142 RPN total loss: 0.00797 Total loss: 0.87687 timestamp: 1655050385.8752599 iteration: 53235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.08018 FastRCNN total loss: 0.16769 L1 loss: 0.0000e+00 L2 loss: 0.58054 Learning rate: 0.002 Mask loss: 0.21031 RPN box loss: 0.02642 RPN score loss: 0.00616 RPN total loss: 0.03258 Total loss: 0.99112 timestamp: 1655050389.206892 iteration: 53240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11362 FastRCNN class loss: 0.08797 FastRCNN total loss: 0.20159 L1 loss: 0.0000e+00 L2 loss: 0.58053 Learning rate: 0.002 Mask loss: 0.20912 RPN box loss: 0.01391 RPN score loss: 0.00719 RPN total loss: 0.0211 Total loss: 1.01235 timestamp: 1655050392.4077363 iteration: 53245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10553 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.17003 L1 loss: 0.0000e+00 L2 loss: 0.58052 Learning rate: 0.002 Mask loss: 0.11108 RPN box loss: 0.01393 RPN score loss: 0.01183 RPN total loss: 0.02575 Total loss: 0.88739 timestamp: 1655050395.747382 iteration: 53250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13212 FastRCNN class loss: 0.09807 FastRCNN total loss: 0.23018 L1 loss: 0.0000e+00 L2 loss: 0.58051 Learning rate: 0.002 Mask loss: 0.13191 RPN box loss: 0.02569 RPN score loss: 0.00996 RPN total loss: 0.03566 Total loss: 0.97826 timestamp: 1655050398.9403472 iteration: 53255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17005 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.23139 L1 loss: 0.0000e+00 L2 loss: 0.5805 Learning rate: 0.002 Mask loss: 0.1545 RPN box loss: 0.00911 RPN score loss: 0.00777 RPN total loss: 0.01689 Total loss: 0.98327 timestamp: 1655050402.1411026 iteration: 53260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06391 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.12259 L1 loss: 0.0000e+00 L2 loss: 0.58049 Learning rate: 0.002 Mask loss: 0.09965 RPN box loss: 0.01613 RPN score loss: 0.00302 RPN total loss: 0.01915 Total loss: 0.82188 timestamp: 1655050405.4187825 iteration: 53265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08618 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.1397 L1 loss: 0.0000e+00 L2 loss: 0.58048 Learning rate: 0.002 Mask loss: 0.12636 RPN box loss: 0.01852 RPN score loss: 0.00385 RPN total loss: 0.02237 Total loss: 0.86891 timestamp: 1655050408.6488054 iteration: 53270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09428 FastRCNN class loss: 0.08539 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.58047 Learning rate: 0.002 Mask loss: 0.16733 RPN box loss: 0.01784 RPN score loss: 0.00838 RPN total loss: 0.02622 Total loss: 0.95369 timestamp: 1655050411.9298613 iteration: 53275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1402 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.21802 L1 loss: 0.0000e+00 L2 loss: 0.58046 Learning rate: 0.002 Mask loss: 0.20913 RPN box loss: 0.01796 RPN score loss: 0.01033 RPN total loss: 0.02829 Total loss: 1.0359 timestamp: 1655050415.2249334 iteration: 53280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08258 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.14452 L1 loss: 0.0000e+00 L2 loss: 0.58045 Learning rate: 0.002 Mask loss: 0.09727 RPN box loss: 0.01117 RPN score loss: 0.00326 RPN total loss: 0.01443 Total loss: 0.83667 timestamp: 1655050418.51273 iteration: 53285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10545 FastRCNN class loss: 0.08521 FastRCNN total loss: 0.19067 L1 loss: 0.0000e+00 L2 loss: 0.58045 Learning rate: 0.002 Mask loss: 0.15881 RPN box loss: 0.03028 RPN score loss: 0.00573 RPN total loss: 0.03601 Total loss: 0.96593 timestamp: 1655050421.7624686 iteration: 53290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10362 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.17071 L1 loss: 0.0000e+00 L2 loss: 0.58044 Learning rate: 0.002 Mask loss: 0.15112 RPN box loss: 0.01662 RPN score loss: 0.01312 RPN total loss: 0.02974 Total loss: 0.93201 timestamp: 1655050425.05054 iteration: 53295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11545 FastRCNN class loss: 0.09751 FastRCNN total loss: 0.21296 L1 loss: 0.0000e+00 L2 loss: 0.58043 Learning rate: 0.002 Mask loss: 0.13495 RPN box loss: 0.01507 RPN score loss: 0.00499 RPN total loss: 0.02006 Total loss: 0.94839 timestamp: 1655050428.3035538 iteration: 53300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10139 FastRCNN class loss: 0.09023 FastRCNN total loss: 0.19162 L1 loss: 0.0000e+00 L2 loss: 0.58042 Learning rate: 0.002 Mask loss: 0.1133 RPN box loss: 0.01378 RPN score loss: 0.00747 RPN total loss: 0.02124 Total loss: 0.90658 timestamp: 1655050431.526856 iteration: 53305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09583 FastRCNN class loss: 0.10267 FastRCNN total loss: 0.1985 L1 loss: 0.0000e+00 L2 loss: 0.58041 Learning rate: 0.002 Mask loss: 0.15079 RPN box loss: 0.01578 RPN score loss: 0.00289 RPN total loss: 0.01867 Total loss: 0.94838 timestamp: 1655050434.85284 iteration: 53310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13269 FastRCNN class loss: 0.09115 FastRCNN total loss: 0.22384 L1 loss: 0.0000e+00 L2 loss: 0.58041 Learning rate: 0.002 Mask loss: 0.21701 RPN box loss: 0.01477 RPN score loss: 0.00469 RPN total loss: 0.01947 Total loss: 1.04072 timestamp: 1655050438.122271 iteration: 53315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12111 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.20976 L1 loss: 0.0000e+00 L2 loss: 0.5804 Learning rate: 0.002 Mask loss: 0.16933 RPN box loss: 0.01436 RPN score loss: 0.00351 RPN total loss: 0.01787 Total loss: 0.97737 timestamp: 1655050441.3986542 iteration: 53320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15001 FastRCNN class loss: 0.11735 FastRCNN total loss: 0.26735 L1 loss: 0.0000e+00 L2 loss: 0.58039 Learning rate: 0.002 Mask loss: 0.15513 RPN box loss: 0.00452 RPN score loss: 0.00692 RPN total loss: 0.01144 Total loss: 1.01432 timestamp: 1655050444.6924684 iteration: 53325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15364 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.23663 L1 loss: 0.0000e+00 L2 loss: 0.58039 Learning rate: 0.002 Mask loss: 0.16136 RPN box loss: 0.00578 RPN score loss: 0.00163 RPN total loss: 0.00741 Total loss: 0.98578 timestamp: 1655050447.9349422 iteration: 53330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13025 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.2081 L1 loss: 0.0000e+00 L2 loss: 0.58038 Learning rate: 0.002 Mask loss: 0.12534 RPN box loss: 0.01587 RPN score loss: 0.00504 RPN total loss: 0.02091 Total loss: 0.93472 timestamp: 1655050451.3281298 iteration: 53335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11467 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.18106 L1 loss: 0.0000e+00 L2 loss: 0.58037 Learning rate: 0.002 Mask loss: 0.14296 RPN box loss: 0.01177 RPN score loss: 0.0067 RPN total loss: 0.01847 Total loss: 0.92286 timestamp: 1655050454.6477299 iteration: 53340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08216 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.14403 L1 loss: 0.0000e+00 L2 loss: 0.58036 Learning rate: 0.002 Mask loss: 0.1213 RPN box loss: 0.00635 RPN score loss: 0.00356 RPN total loss: 0.00991 Total loss: 0.85561 timestamp: 1655050457.891676 iteration: 53345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12553 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.20356 L1 loss: 0.0000e+00 L2 loss: 0.58035 Learning rate: 0.002 Mask loss: 0.15103 RPN box loss: 0.03449 RPN score loss: 0.00263 RPN total loss: 0.03712 Total loss: 0.97207 timestamp: 1655050461.1461782 iteration: 53350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1051 FastRCNN class loss: 0.08697 FastRCNN total loss: 0.19206 L1 loss: 0.0000e+00 L2 loss: 0.58035 Learning rate: 0.002 Mask loss: 0.1441 RPN box loss: 0.01932 RPN score loss: 0.00665 RPN total loss: 0.02597 Total loss: 0.94247 timestamp: 1655050464.4380407 iteration: 53355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11915 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.18571 L1 loss: 0.0000e+00 L2 loss: 0.58034 Learning rate: 0.002 Mask loss: 0.27697 RPN box loss: 0.03821 RPN score loss: 0.0138 RPN total loss: 0.05201 Total loss: 1.09502 timestamp: 1655050467.699073 iteration: 53360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10356 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.18186 L1 loss: 0.0000e+00 L2 loss: 0.58033 Learning rate: 0.002 Mask loss: 0.1305 RPN box loss: 0.0382 RPN score loss: 0.00979 RPN total loss: 0.04798 Total loss: 0.94067 timestamp: 1655050471.0073676 iteration: 53365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09078 FastRCNN class loss: 0.10108 FastRCNN total loss: 0.19187 L1 loss: 0.0000e+00 L2 loss: 0.58032 Learning rate: 0.002 Mask loss: 0.18591 RPN box loss: 0.01442 RPN score loss: 0.01002 RPN total loss: 0.02444 Total loss: 0.98254 timestamp: 1655050474.2348924 iteration: 53370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.10275 FastRCNN total loss: 0.19682 L1 loss: 0.0000e+00 L2 loss: 0.58031 Learning rate: 0.002 Mask loss: 0.21405 RPN box loss: 0.01142 RPN score loss: 0.00742 RPN total loss: 0.01884 Total loss: 1.01001 timestamp: 1655050477.5112593 iteration: 53375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1141 FastRCNN class loss: 0.05541 FastRCNN total loss: 0.16952 L1 loss: 0.0000e+00 L2 loss: 0.58029 Learning rate: 0.002 Mask loss: 0.11384 RPN box loss: 0.01859 RPN score loss: 0.00278 RPN total loss: 0.02137 Total loss: 0.88502 timestamp: 1655050480.7523875 iteration: 53380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08734 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.13951 L1 loss: 0.0000e+00 L2 loss: 0.58029 Learning rate: 0.002 Mask loss: 0.12485 RPN box loss: 0.00565 RPN score loss: 0.0016 RPN total loss: 0.00725 Total loss: 0.85189 timestamp: 1655050484.0161703 iteration: 53385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08625 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.14246 L1 loss: 0.0000e+00 L2 loss: 0.58028 Learning rate: 0.002 Mask loss: 0.12273 RPN box loss: 0.00792 RPN score loss: 0.00254 RPN total loss: 0.01046 Total loss: 0.85593 timestamp: 1655050487.4098368 iteration: 53390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13118 FastRCNN class loss: 0.08363 FastRCNN total loss: 0.21482 L1 loss: 0.0000e+00 L2 loss: 0.58027 Learning rate: 0.002 Mask loss: 0.14114 RPN box loss: 0.00879 RPN score loss: 0.00664 RPN total loss: 0.01543 Total loss: 0.95167 timestamp: 1655050490.6756835 iteration: 53395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13465 FastRCNN class loss: 0.10282 FastRCNN total loss: 0.23747 L1 loss: 0.0000e+00 L2 loss: 0.58026 Learning rate: 0.002 Mask loss: 0.21721 RPN box loss: 0.02706 RPN score loss: 0.0027 RPN total loss: 0.02976 Total loss: 1.0647 timestamp: 1655050493.9531777 iteration: 53400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12422 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.19109 L1 loss: 0.0000e+00 L2 loss: 0.58025 Learning rate: 0.002 Mask loss: 0.16494 RPN box loss: 0.01786 RPN score loss: 0.00139 RPN total loss: 0.01926 Total loss: 0.95554 timestamp: 1655050497.2379816 iteration: 53405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.1183 L1 loss: 0.0000e+00 L2 loss: 0.58025 Learning rate: 0.002 Mask loss: 0.12379 RPN box loss: 0.04639 RPN score loss: 0.00377 RPN total loss: 0.05016 Total loss: 0.8725 timestamp: 1655050500.4752362 iteration: 53410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08705 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.14046 L1 loss: 0.0000e+00 L2 loss: 0.58024 Learning rate: 0.002 Mask loss: 0.13475 RPN box loss: 0.01313 RPN score loss: 0.0059 RPN total loss: 0.01903 Total loss: 0.87448 timestamp: 1655050503.7618148 iteration: 53415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.16733 L1 loss: 0.0000e+00 L2 loss: 0.58023 Learning rate: 0.002 Mask loss: 0.15689 RPN box loss: 0.01479 RPN score loss: 0.01609 RPN total loss: 0.03088 Total loss: 0.93532 timestamp: 1655050506.9117362 iteration: 53420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07677 FastRCNN class loss: 0.05731 FastRCNN total loss: 0.13408 L1 loss: 0.0000e+00 L2 loss: 0.58022 Learning rate: 0.002 Mask loss: 0.23463 RPN box loss: 0.01118 RPN score loss: 0.0037 RPN total loss: 0.01488 Total loss: 0.96381 timestamp: 1655050510.2116365 iteration: 53425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1183 FastRCNN class loss: 0.10081 FastRCNN total loss: 0.21911 L1 loss: 0.0000e+00 L2 loss: 0.58022 Learning rate: 0.002 Mask loss: 0.21046 RPN box loss: 0.01673 RPN score loss: 0.0085 RPN total loss: 0.02523 Total loss: 1.03502 timestamp: 1655050513.5167415 iteration: 53430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11448 FastRCNN class loss: 0.05369 FastRCNN total loss: 0.16817 L1 loss: 0.0000e+00 L2 loss: 0.5802 Learning rate: 0.002 Mask loss: 0.11273 RPN box loss: 0.03612 RPN score loss: 0.0064 RPN total loss: 0.04252 Total loss: 0.90363 timestamp: 1655050516.84341 iteration: 53435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11868 FastRCNN class loss: 0.07674 FastRCNN total loss: 0.19542 L1 loss: 0.0000e+00 L2 loss: 0.58019 Learning rate: 0.002 Mask loss: 0.12326 RPN box loss: 0.00802 RPN score loss: 0.01198 RPN total loss: 0.02001 Total loss: 0.91888 timestamp: 1655050520.135704 iteration: 53440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09182 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.16881 L1 loss: 0.0000e+00 L2 loss: 0.58018 Learning rate: 0.002 Mask loss: 0.18364 RPN box loss: 0.01619 RPN score loss: 0.00228 RPN total loss: 0.01847 Total loss: 0.9511 timestamp: 1655050523.4184694 iteration: 53445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09158 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.16078 L1 loss: 0.0000e+00 L2 loss: 0.58017 Learning rate: 0.002 Mask loss: 0.17008 RPN box loss: 0.00816 RPN score loss: 0.00824 RPN total loss: 0.0164 Total loss: 0.92743 timestamp: 1655050526.7166085 iteration: 53450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09056 FastRCNN class loss: 0.04272 FastRCNN total loss: 0.13328 L1 loss: 0.0000e+00 L2 loss: 0.58016 Learning rate: 0.002 Mask loss: 0.13134 RPN box loss: 0.00636 RPN score loss: 0.00128 RPN total loss: 0.00763 Total loss: 0.85242 timestamp: 1655050529.9716644 iteration: 53455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08533 FastRCNN class loss: 0.04915 FastRCNN total loss: 0.13448 L1 loss: 0.0000e+00 L2 loss: 0.58016 Learning rate: 0.002 Mask loss: 0.0881 RPN box loss: 0.01077 RPN score loss: 0.00281 RPN total loss: 0.01358 Total loss: 0.81632 timestamp: 1655050533.24425 iteration: 53460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09885 FastRCNN class loss: 0.05973 FastRCNN total loss: 0.15858 L1 loss: 0.0000e+00 L2 loss: 0.58015 Learning rate: 0.002 Mask loss: 0.13605 RPN box loss: 0.0133 RPN score loss: 0.00572 RPN total loss: 0.01902 Total loss: 0.89379 timestamp: 1655050536.4656615 iteration: 53465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12367 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.20269 L1 loss: 0.0000e+00 L2 loss: 0.58014 Learning rate: 0.002 Mask loss: 0.19218 RPN box loss: 0.01711 RPN score loss: 0.00784 RPN total loss: 0.02495 Total loss: 0.99997 timestamp: 1655050539.7593226 iteration: 53470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12113 FastRCNN class loss: 0.06896 FastRCNN total loss: 0.19008 L1 loss: 0.0000e+00 L2 loss: 0.58013 Learning rate: 0.002 Mask loss: 0.13806 RPN box loss: 0.01236 RPN score loss: 0.00361 RPN total loss: 0.01597 Total loss: 0.92424 timestamp: 1655050543.0899124 iteration: 53475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11126 FastRCNN class loss: 0.10806 FastRCNN total loss: 0.21932 L1 loss: 0.0000e+00 L2 loss: 0.58012 Learning rate: 0.002 Mask loss: 0.1941 RPN box loss: 0.01868 RPN score loss: 0.0107 RPN total loss: 0.02938 Total loss: 1.02292 timestamp: 1655050546.3702743 iteration: 53480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15831 FastRCNN class loss: 0.11847 FastRCNN total loss: 0.27678 L1 loss: 0.0000e+00 L2 loss: 0.58011 Learning rate: 0.002 Mask loss: 0.15349 RPN box loss: 0.03547 RPN score loss: 0.01501 RPN total loss: 0.05048 Total loss: 1.06086 timestamp: 1655050549.637811 iteration: 53485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09407 FastRCNN class loss: 0.08447 FastRCNN total loss: 0.17855 L1 loss: 0.0000e+00 L2 loss: 0.5801 Learning rate: 0.002 Mask loss: 0.12781 RPN box loss: 0.01596 RPN score loss: 0.0038 RPN total loss: 0.01976 Total loss: 0.90622 timestamp: 1655050552.955902 iteration: 53490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09104 FastRCNN class loss: 0.06813 FastRCNN total loss: 0.15918 L1 loss: 0.0000e+00 L2 loss: 0.5801 Learning rate: 0.002 Mask loss: 0.13234 RPN box loss: 0.00601 RPN score loss: 0.00247 RPN total loss: 0.00849 Total loss: 0.8801 timestamp: 1655050556.2271607 iteration: 53495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08328 FastRCNN class loss: 0.05433 FastRCNN total loss: 0.13761 L1 loss: 0.0000e+00 L2 loss: 0.58009 Learning rate: 0.002 Mask loss: 0.09824 RPN box loss: 0.011 RPN score loss: 0.0028 RPN total loss: 0.0138 Total loss: 0.82975 timestamp: 1655050559.429266 iteration: 53500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08658 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.15176 L1 loss: 0.0000e+00 L2 loss: 0.58009 Learning rate: 0.002 Mask loss: 0.1588 RPN box loss: 0.01802 RPN score loss: 0.01113 RPN total loss: 0.02916 Total loss: 0.91981 timestamp: 1655050562.7384589 iteration: 53505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09446 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.1549 L1 loss: 0.0000e+00 L2 loss: 0.58008 Learning rate: 0.002 Mask loss: 0.1105 RPN box loss: 0.01306 RPN score loss: 0.00362 RPN total loss: 0.01668 Total loss: 0.86216 timestamp: 1655050565.9817214 iteration: 53510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18109 FastRCNN class loss: 0.12188 FastRCNN total loss: 0.30297 L1 loss: 0.0000e+00 L2 loss: 0.58007 Learning rate: 0.002 Mask loss: 0.17903 RPN box loss: 0.04441 RPN score loss: 0.01203 RPN total loss: 0.05644 Total loss: 1.11852 timestamp: 1655050569.292586 iteration: 53515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.18306 L1 loss: 0.0000e+00 L2 loss: 0.58006 Learning rate: 0.002 Mask loss: 0.16138 RPN box loss: 0.00891 RPN score loss: 0.00332 RPN total loss: 0.01223 Total loss: 0.93673 timestamp: 1655050572.5611567 iteration: 53520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08289 FastRCNN class loss: 0.05119 FastRCNN total loss: 0.13408 L1 loss: 0.0000e+00 L2 loss: 0.58005 Learning rate: 0.002 Mask loss: 0.17666 RPN box loss: 0.01633 RPN score loss: 0.00322 RPN total loss: 0.01955 Total loss: 0.91034 timestamp: 1655050575.8372028 iteration: 53525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10602 FastRCNN class loss: 0.07349 FastRCNN total loss: 0.17951 L1 loss: 0.0000e+00 L2 loss: 0.58004 Learning rate: 0.002 Mask loss: 0.10596 RPN box loss: 0.01075 RPN score loss: 0.0057 RPN total loss: 0.01645 Total loss: 0.88195 timestamp: 1655050579.1241329 iteration: 53530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11998 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.58003 Learning rate: 0.002 Mask loss: 0.16839 RPN box loss: 0.00829 RPN score loss: 0.00191 RPN total loss: 0.0102 Total loss: 0.94328 timestamp: 1655050582.405387 iteration: 53535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10065 FastRCNN class loss: 0.11119 FastRCNN total loss: 0.21184 L1 loss: 0.0000e+00 L2 loss: 0.58002 Learning rate: 0.002 Mask loss: 0.13925 RPN box loss: 0.02154 RPN score loss: 0.00906 RPN total loss: 0.0306 Total loss: 0.96171 timestamp: 1655050585.617096 iteration: 53540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13592 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.23872 L1 loss: 0.0000e+00 L2 loss: 0.58001 Learning rate: 0.002 Mask loss: 0.19181 RPN box loss: 0.01676 RPN score loss: 0.00486 RPN total loss: 0.02162 Total loss: 1.03217 timestamp: 1655050588.8322723 iteration: 53545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06513 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.11426 L1 loss: 0.0000e+00 L2 loss: 0.58 Learning rate: 0.002 Mask loss: 0.11095 RPN box loss: 0.02624 RPN score loss: 0.0053 RPN total loss: 0.03153 Total loss: 0.83674 timestamp: 1655050592.0851157 iteration: 53550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1119 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.18379 L1 loss: 0.0000e+00 L2 loss: 0.58 Learning rate: 0.002 Mask loss: 0.13867 RPN box loss: 0.0134 RPN score loss: 0.00668 RPN total loss: 0.02008 Total loss: 0.92253 timestamp: 1655050595.3562849 iteration: 53555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0775 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.13611 L1 loss: 0.0000e+00 L2 loss: 0.57999 Learning rate: 0.002 Mask loss: 0.17348 RPN box loss: 0.02769 RPN score loss: 0.00191 RPN total loss: 0.0296 Total loss: 0.91919 timestamp: 1655050598.6317565 iteration: 53560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1027 FastRCNN class loss: 0.04798 FastRCNN total loss: 0.15068 L1 loss: 0.0000e+00 L2 loss: 0.57999 Learning rate: 0.002 Mask loss: 0.10726 RPN box loss: 0.00747 RPN score loss: 0.0053 RPN total loss: 0.01277 Total loss: 0.85069 timestamp: 1655050601.9630003 iteration: 53565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12741 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.21559 L1 loss: 0.0000e+00 L2 loss: 0.57998 Learning rate: 0.002 Mask loss: 0.12127 RPN box loss: 0.02241 RPN score loss: 0.00404 RPN total loss: 0.02645 Total loss: 0.94329 timestamp: 1655050605.274557 iteration: 53570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10307 FastRCNN class loss: 0.07241 FastRCNN total loss: 0.17548 L1 loss: 0.0000e+00 L2 loss: 0.57997 Learning rate: 0.002 Mask loss: 0.14084 RPN box loss: 0.04982 RPN score loss: 0.00582 RPN total loss: 0.05564 Total loss: 0.95193 timestamp: 1655050608.4931734 iteration: 53575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07996 FastRCNN class loss: 0.05706 FastRCNN total loss: 0.13702 L1 loss: 0.0000e+00 L2 loss: 0.57996 Learning rate: 0.002 Mask loss: 0.1022 RPN box loss: 0.01303 RPN score loss: 0.00424 RPN total loss: 0.01727 Total loss: 0.83644 timestamp: 1655050611.672579 iteration: 53580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12612 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.2054 L1 loss: 0.0000e+00 L2 loss: 0.57995 Learning rate: 0.002 Mask loss: 0.13268 RPN box loss: 0.01147 RPN score loss: 0.0032 RPN total loss: 0.01467 Total loss: 0.9327 timestamp: 1655050615.0053396 iteration: 53585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09395 FastRCNN class loss: 0.07551 FastRCNN total loss: 0.16946 L1 loss: 0.0000e+00 L2 loss: 0.57994 Learning rate: 0.002 Mask loss: 0.09721 RPN box loss: 0.04097 RPN score loss: 0.00281 RPN total loss: 0.04378 Total loss: 0.89039 timestamp: 1655050618.26781 iteration: 53590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07429 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.1266 L1 loss: 0.0000e+00 L2 loss: 0.57993 Learning rate: 0.002 Mask loss: 0.21772 RPN box loss: 0.00673 RPN score loss: 0.00573 RPN total loss: 0.01245 Total loss: 0.93671 timestamp: 1655050621.4763033 iteration: 53595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12728 FastRCNN class loss: 0.13144 FastRCNN total loss: 0.25872 L1 loss: 0.0000e+00 L2 loss: 0.57992 Learning rate: 0.002 Mask loss: 0.23258 RPN box loss: 0.02032 RPN score loss: 0.00999 RPN total loss: 0.03031 Total loss: 1.10154 timestamp: 1655050624.768888 iteration: 53600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11766 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.19125 L1 loss: 0.0000e+00 L2 loss: 0.57992 Learning rate: 0.002 Mask loss: 0.19464 RPN box loss: 0.02197 RPN score loss: 0.01516 RPN total loss: 0.03712 Total loss: 1.00293 timestamp: 1655050628.0426207 iteration: 53605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.04609 FastRCNN total loss: 0.12378 L1 loss: 0.0000e+00 L2 loss: 0.57991 Learning rate: 0.002 Mask loss: 0.06731 RPN box loss: 0.01148 RPN score loss: 0.00263 RPN total loss: 0.01411 Total loss: 0.7851 timestamp: 1655050631.2416792 iteration: 53610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06837 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.12853 L1 loss: 0.0000e+00 L2 loss: 0.5799 Learning rate: 0.002 Mask loss: 0.14784 RPN box loss: 0.00982 RPN score loss: 0.00294 RPN total loss: 0.01275 Total loss: 0.86902 timestamp: 1655050634.5558333 iteration: 53615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11022 FastRCNN class loss: 0.10399 FastRCNN total loss: 0.21421 L1 loss: 0.0000e+00 L2 loss: 0.57989 Learning rate: 0.002 Mask loss: 0.15903 RPN box loss: 0.01004 RPN score loss: 0.00404 RPN total loss: 0.01408 Total loss: 0.96721 timestamp: 1655050637.802587 iteration: 53620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1759 FastRCNN class loss: 0.07412 FastRCNN total loss: 0.25002 L1 loss: 0.0000e+00 L2 loss: 0.57988 Learning rate: 0.002 Mask loss: 0.13283 RPN box loss: 0.01252 RPN score loss: 0.00735 RPN total loss: 0.01988 Total loss: 0.98261 timestamp: 1655050641.0529325 iteration: 53625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10232 FastRCNN class loss: 0.05715 FastRCNN total loss: 0.15947 L1 loss: 0.0000e+00 L2 loss: 0.57987 Learning rate: 0.002 Mask loss: 0.136 RPN box loss: 0.02139 RPN score loss: 0.00798 RPN total loss: 0.02937 Total loss: 0.90471 timestamp: 1655050644.390904 iteration: 53630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10792 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.18272 L1 loss: 0.0000e+00 L2 loss: 0.57986 Learning rate: 0.002 Mask loss: 0.15824 RPN box loss: 0.00962 RPN score loss: 0.00414 RPN total loss: 0.01376 Total loss: 0.93458 timestamp: 1655050647.634851 iteration: 53635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12644 FastRCNN class loss: 0.10046 FastRCNN total loss: 0.2269 L1 loss: 0.0000e+00 L2 loss: 0.57985 Learning rate: 0.002 Mask loss: 0.20179 RPN box loss: 0.06456 RPN score loss: 0.01662 RPN total loss: 0.08118 Total loss: 1.08972 timestamp: 1655050650.8701935 iteration: 53640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10272 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.15618 L1 loss: 0.0000e+00 L2 loss: 0.57985 Learning rate: 0.002 Mask loss: 0.11728 RPN box loss: 0.0168 RPN score loss: 0.0011 RPN total loss: 0.0179 Total loss: 0.87121 timestamp: 1655050654.1264896 iteration: 53645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11943 FastRCNN class loss: 0.09213 FastRCNN total loss: 0.21156 L1 loss: 0.0000e+00 L2 loss: 0.57984 Learning rate: 0.002 Mask loss: 0.13424 RPN box loss: 0.02546 RPN score loss: 0.01509 RPN total loss: 0.04055 Total loss: 0.96619 timestamp: 1655050657.3743958 iteration: 53650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09096 FastRCNN class loss: 0.05397 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.57983 Learning rate: 0.002 Mask loss: 0.13643 RPN box loss: 0.00775 RPN score loss: 0.01202 RPN total loss: 0.01977 Total loss: 0.88095 timestamp: 1655050660.6188693 iteration: 53655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.11964 FastRCNN total loss: 0.22661 L1 loss: 0.0000e+00 L2 loss: 0.57982 Learning rate: 0.002 Mask loss: 0.18471 RPN box loss: 0.02909 RPN score loss: 0.00479 RPN total loss: 0.03388 Total loss: 1.02502 timestamp: 1655050663.8419101 iteration: 53660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11227 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.18107 L1 loss: 0.0000e+00 L2 loss: 0.57981 Learning rate: 0.002 Mask loss: 0.10648 RPN box loss: 0.02953 RPN score loss: 0.01481 RPN total loss: 0.04434 Total loss: 0.9117 timestamp: 1655050667.101923 iteration: 53665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1004 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.17721 L1 loss: 0.0000e+00 L2 loss: 0.5798 Learning rate: 0.002 Mask loss: 0.1214 RPN box loss: 0.00681 RPN score loss: 0.00497 RPN total loss: 0.01179 Total loss: 0.8902 timestamp: 1655050670.3226151 iteration: 53670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.04684 FastRCNN total loss: 0.14751 L1 loss: 0.0000e+00 L2 loss: 0.57979 Learning rate: 0.002 Mask loss: 0.12389 RPN box loss: 0.0097 RPN score loss: 0.00124 RPN total loss: 0.01094 Total loss: 0.86213 timestamp: 1655050673.5778878 iteration: 53675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08601 FastRCNN class loss: 0.1184 FastRCNN total loss: 0.2044 L1 loss: 0.0000e+00 L2 loss: 0.57978 Learning rate: 0.002 Mask loss: 0.14669 RPN box loss: 0.01326 RPN score loss: 0.00741 RPN total loss: 0.02067 Total loss: 0.95155 timestamp: 1655050676.833823 iteration: 53680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06438 FastRCNN class loss: 0.04026 FastRCNN total loss: 0.10464 L1 loss: 0.0000e+00 L2 loss: 0.57977 Learning rate: 0.002 Mask loss: 0.14227 RPN box loss: 0.01562 RPN score loss: 0.00052 RPN total loss: 0.01614 Total loss: 0.84283 timestamp: 1655050680.0755455 iteration: 53685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10348 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.17835 L1 loss: 0.0000e+00 L2 loss: 0.57976 Learning rate: 0.002 Mask loss: 0.15233 RPN box loss: 0.01654 RPN score loss: 0.01297 RPN total loss: 0.02951 Total loss: 0.93995 timestamp: 1655050683.3040085 iteration: 53690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16168 FastRCNN class loss: 0.10128 FastRCNN total loss: 0.26296 L1 loss: 0.0000e+00 L2 loss: 0.57976 Learning rate: 0.002 Mask loss: 0.17301 RPN box loss: 0.01515 RPN score loss: 0.00325 RPN total loss: 0.0184 Total loss: 1.03413 timestamp: 1655050686.5403411 iteration: 53695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10352 FastRCNN class loss: 0.04742 FastRCNN total loss: 0.15094 L1 loss: 0.0000e+00 L2 loss: 0.57975 Learning rate: 0.002 Mask loss: 0.11563 RPN box loss: 0.00646 RPN score loss: 0.00146 RPN total loss: 0.00792 Total loss: 0.85424 timestamp: 1655050689.8626833 iteration: 53700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12404 FastRCNN class loss: 0.10953 FastRCNN total loss: 0.23357 L1 loss: 0.0000e+00 L2 loss: 0.57974 Learning rate: 0.002 Mask loss: 0.18565 RPN box loss: 0.02601 RPN score loss: 0.01056 RPN total loss: 0.03657 Total loss: 1.03553 timestamp: 1655050693.1244133 iteration: 53705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0705 FastRCNN class loss: 0.04288 FastRCNN total loss: 0.11338 L1 loss: 0.0000e+00 L2 loss: 0.57973 Learning rate: 0.002 Mask loss: 0.08957 RPN box loss: 0.00905 RPN score loss: 0.00284 RPN total loss: 0.01189 Total loss: 0.79458 timestamp: 1655050696.365826 iteration: 53710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16691 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.24425 L1 loss: 0.0000e+00 L2 loss: 0.57973 Learning rate: 0.002 Mask loss: 0.2222 RPN box loss: 0.01363 RPN score loss: 0.00604 RPN total loss: 0.01967 Total loss: 1.06584 timestamp: 1655050699.584386 iteration: 53715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10628 FastRCNN class loss: 0.05971 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.57972 Learning rate: 0.002 Mask loss: 0.13071 RPN box loss: 0.01398 RPN score loss: 0.00575 RPN total loss: 0.01973 Total loss: 0.89615 timestamp: 1655050702.8059206 iteration: 53720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09493 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.17256 L1 loss: 0.0000e+00 L2 loss: 0.57971 Learning rate: 0.002 Mask loss: 0.1189 RPN box loss: 0.01519 RPN score loss: 0.00632 RPN total loss: 0.02152 Total loss: 0.89268 timestamp: 1655050706.0860388 iteration: 53725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10542 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.1756 L1 loss: 0.0000e+00 L2 loss: 0.5797 Learning rate: 0.002 Mask loss: 0.19922 RPN box loss: 0.02409 RPN score loss: 0.01846 RPN total loss: 0.04256 Total loss: 0.99708 timestamp: 1655050709.4378383 iteration: 53730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12377 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.20429 L1 loss: 0.0000e+00 L2 loss: 0.57969 Learning rate: 0.002 Mask loss: 0.20924 RPN box loss: 0.01565 RPN score loss: 0.00225 RPN total loss: 0.0179 Total loss: 1.01113 timestamp: 1655050712.7068243 iteration: 53735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07454 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.14935 L1 loss: 0.0000e+00 L2 loss: 0.57969 Learning rate: 0.002 Mask loss: 0.14613 RPN box loss: 0.03435 RPN score loss: 0.00318 RPN total loss: 0.03753 Total loss: 0.91269 timestamp: 1655050716.0220535 iteration: 53740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09004 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.14889 L1 loss: 0.0000e+00 L2 loss: 0.57968 Learning rate: 0.002 Mask loss: 0.11882 RPN box loss: 0.00501 RPN score loss: 0.00401 RPN total loss: 0.00902 Total loss: 0.85641 timestamp: 1655050719.371652 iteration: 53745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11293 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.1774 L1 loss: 0.0000e+00 L2 loss: 0.57967 Learning rate: 0.002 Mask loss: 0.16356 RPN box loss: 0.01195 RPN score loss: 0.0049 RPN total loss: 0.01686 Total loss: 0.93748 timestamp: 1655050722.718798 iteration: 53750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17884 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.26281 L1 loss: 0.0000e+00 L2 loss: 0.57967 Learning rate: 0.002 Mask loss: 0.16891 RPN box loss: 0.0135 RPN score loss: 0.01042 RPN total loss: 0.02392 Total loss: 1.0353 timestamp: 1655050725.979425 iteration: 53755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09839 FastRCNN class loss: 0.05336 FastRCNN total loss: 0.15176 L1 loss: 0.0000e+00 L2 loss: 0.57966 Learning rate: 0.002 Mask loss: 0.14345 RPN box loss: 0.012 RPN score loss: 0.00304 RPN total loss: 0.01504 Total loss: 0.8899 timestamp: 1655050729.2058978 iteration: 53760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.05238 FastRCNN total loss: 0.13734 L1 loss: 0.0000e+00 L2 loss: 0.57965 Learning rate: 0.002 Mask loss: 0.14533 RPN box loss: 0.0103 RPN score loss: 0.00437 RPN total loss: 0.01468 Total loss: 0.87699 timestamp: 1655050732.4427412 iteration: 53765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07864 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.14389 L1 loss: 0.0000e+00 L2 loss: 0.57964 Learning rate: 0.002 Mask loss: 0.15773 RPN box loss: 0.00815 RPN score loss: 0.00504 RPN total loss: 0.01319 Total loss: 0.89445 timestamp: 1655050735.7367673 iteration: 53770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12702 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.1971 L1 loss: 0.0000e+00 L2 loss: 0.57963 Learning rate: 0.002 Mask loss: 0.1621 RPN box loss: 0.01924 RPN score loss: 0.00092 RPN total loss: 0.02016 Total loss: 0.95899 timestamp: 1655050738.987399 iteration: 53775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11588 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.19055 L1 loss: 0.0000e+00 L2 loss: 0.57962 Learning rate: 0.002 Mask loss: 0.14212 RPN box loss: 0.01313 RPN score loss: 0.00738 RPN total loss: 0.02052 Total loss: 0.93281 timestamp: 1655050742.2143338 iteration: 53780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08292 FastRCNN class loss: 0.0709 FastRCNN total loss: 0.15382 L1 loss: 0.0000e+00 L2 loss: 0.57961 Learning rate: 0.002 Mask loss: 0.08073 RPN box loss: 0.01384 RPN score loss: 0.00516 RPN total loss: 0.019 Total loss: 0.83316 timestamp: 1655050745.4512746 iteration: 53785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10958 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.19255 L1 loss: 0.0000e+00 L2 loss: 0.57961 Learning rate: 0.002 Mask loss: 0.19322 RPN box loss: 0.00575 RPN score loss: 0.00726 RPN total loss: 0.01301 Total loss: 0.97839 timestamp: 1655050748.761692 iteration: 53790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10252 FastRCNN class loss: 0.08881 FastRCNN total loss: 0.19133 L1 loss: 0.0000e+00 L2 loss: 0.5796 Learning rate: 0.002 Mask loss: 0.18547 RPN box loss: 0.02193 RPN score loss: 0.00849 RPN total loss: 0.03042 Total loss: 0.98682 timestamp: 1655050752.0212004 iteration: 53795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14573 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.2335 L1 loss: 0.0000e+00 L2 loss: 0.57959 Learning rate: 0.002 Mask loss: 0.13808 RPN box loss: 0.02166 RPN score loss: 0.00534 RPN total loss: 0.027 Total loss: 0.97816 timestamp: 1655050755.3220794 iteration: 53800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13532 FastRCNN class loss: 0.07501 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.57958 Learning rate: 0.002 Mask loss: 0.14771 RPN box loss: 0.02087 RPN score loss: 0.00165 RPN total loss: 0.02252 Total loss: 0.96014 timestamp: 1655050758.612923 iteration: 53805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12935 FastRCNN class loss: 0.12519 FastRCNN total loss: 0.25454 L1 loss: 0.0000e+00 L2 loss: 0.57957 Learning rate: 0.002 Mask loss: 0.27734 RPN box loss: 0.02445 RPN score loss: 0.00938 RPN total loss: 0.03383 Total loss: 1.14528 timestamp: 1655050761.9407098 iteration: 53810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13283 FastRCNN class loss: 0.11023 FastRCNN total loss: 0.24305 L1 loss: 0.0000e+00 L2 loss: 0.57956 Learning rate: 0.002 Mask loss: 0.1236 RPN box loss: 0.03503 RPN score loss: 0.0152 RPN total loss: 0.05023 Total loss: 0.99644 timestamp: 1655050765.171215 iteration: 53815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09563 FastRCNN class loss: 0.07927 FastRCNN total loss: 0.17489 L1 loss: 0.0000e+00 L2 loss: 0.57955 Learning rate: 0.002 Mask loss: 0.12019 RPN box loss: 0.02989 RPN score loss: 0.00236 RPN total loss: 0.03225 Total loss: 0.90688 timestamp: 1655050768.4983327 iteration: 53820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08617 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.1586 L1 loss: 0.0000e+00 L2 loss: 0.57954 Learning rate: 0.002 Mask loss: 0.16348 RPN box loss: 0.05291 RPN score loss: 0.00579 RPN total loss: 0.0587 Total loss: 0.96032 timestamp: 1655050771.857076 iteration: 53825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17859 FastRCNN class loss: 0.11183 FastRCNN total loss: 0.29042 L1 loss: 0.0000e+00 L2 loss: 0.57954 Learning rate: 0.002 Mask loss: 0.17363 RPN box loss: 0.07406 RPN score loss: 0.01835 RPN total loss: 0.0924 Total loss: 1.13599 timestamp: 1655050775.111642 iteration: 53830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07126 FastRCNN class loss: 0.07301 FastRCNN total loss: 0.14427 L1 loss: 0.0000e+00 L2 loss: 0.57953 Learning rate: 0.002 Mask loss: 0.09155 RPN box loss: 0.0086 RPN score loss: 0.00739 RPN total loss: 0.01598 Total loss: 0.83133 timestamp: 1655050778.4516761 iteration: 53835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13613 FastRCNN class loss: 0.07551 FastRCNN total loss: 0.21164 L1 loss: 0.0000e+00 L2 loss: 0.57952 Learning rate: 0.002 Mask loss: 0.11349 RPN box loss: 0.00848 RPN score loss: 0.00306 RPN total loss: 0.01154 Total loss: 0.91619 timestamp: 1655050781.716591 iteration: 53840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03909 FastRCNN class loss: 0.0391 FastRCNN total loss: 0.07819 L1 loss: 0.0000e+00 L2 loss: 0.57951 Learning rate: 0.002 Mask loss: 0.09684 RPN box loss: 0.01088 RPN score loss: 0.00407 RPN total loss: 0.01495 Total loss: 0.76949 timestamp: 1655050785.0145822 iteration: 53845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09424 FastRCNN class loss: 0.07618 FastRCNN total loss: 0.17043 L1 loss: 0.0000e+00 L2 loss: 0.5795 Learning rate: 0.002 Mask loss: 0.16733 RPN box loss: 0.00773 RPN score loss: 0.00217 RPN total loss: 0.0099 Total loss: 0.92717 timestamp: 1655050788.285401 iteration: 53850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13408 FastRCNN class loss: 0.05252 FastRCNN total loss: 0.1866 L1 loss: 0.0000e+00 L2 loss: 0.57949 Learning rate: 0.002 Mask loss: 0.08977 RPN box loss: 0.00774 RPN score loss: 0.00595 RPN total loss: 0.01369 Total loss: 0.86955 timestamp: 1655050791.5700235 iteration: 53855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09778 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.15652 L1 loss: 0.0000e+00 L2 loss: 0.57949 Learning rate: 0.002 Mask loss: 0.13346 RPN box loss: 0.00329 RPN score loss: 0.00132 RPN total loss: 0.00461 Total loss: 0.87408 timestamp: 1655050794.726755 iteration: 53860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.08598 FastRCNN total loss: 0.15941 L1 loss: 0.0000e+00 L2 loss: 0.57948 Learning rate: 0.002 Mask loss: 0.16433 RPN box loss: 0.0097 RPN score loss: 0.00265 RPN total loss: 0.01236 Total loss: 0.91557 timestamp: 1655050797.9962535 iteration: 53865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07304 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.12756 L1 loss: 0.0000e+00 L2 loss: 0.57947 Learning rate: 0.002 Mask loss: 0.12388 RPN box loss: 0.01591 RPN score loss: 0.00062 RPN total loss: 0.01654 Total loss: 0.84745 timestamp: 1655050801.2895427 iteration: 53870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0811 FastRCNN class loss: 0.06328 FastRCNN total loss: 0.14438 L1 loss: 0.0000e+00 L2 loss: 0.57946 Learning rate: 0.002 Mask loss: 0.15944 RPN box loss: 0.00896 RPN score loss: 0.00584 RPN total loss: 0.0148 Total loss: 0.89808 timestamp: 1655050804.5339608 iteration: 53875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.18137 L1 loss: 0.0000e+00 L2 loss: 0.57945 Learning rate: 0.002 Mask loss: 0.17032 RPN box loss: 0.02655 RPN score loss: 0.00798 RPN total loss: 0.03452 Total loss: 0.96566 timestamp: 1655050807.8095622 iteration: 53880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 0.57944 Learning rate: 0.002 Mask loss: 0.21107 RPN box loss: 0.03364 RPN score loss: 0.00662 RPN total loss: 0.04026 Total loss: 0.99041 timestamp: 1655050811.064874 iteration: 53885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07475 FastRCNN class loss: 0.06043 FastRCNN total loss: 0.13519 L1 loss: 0.0000e+00 L2 loss: 0.57943 Learning rate: 0.002 Mask loss: 0.16781 RPN box loss: 0.01 RPN score loss: 0.00265 RPN total loss: 0.01265 Total loss: 0.89509 timestamp: 1655050814.395406 iteration: 53890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0735 FastRCNN class loss: 0.07155 FastRCNN total loss: 0.14505 L1 loss: 0.0000e+00 L2 loss: 0.57943 Learning rate: 0.002 Mask loss: 0.19645 RPN box loss: 0.0126 RPN score loss: 0.01225 RPN total loss: 0.02486 Total loss: 0.94578 timestamp: 1655050817.6170788 iteration: 53895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1146 FastRCNN class loss: 0.06154 FastRCNN total loss: 0.17614 L1 loss: 0.0000e+00 L2 loss: 0.57941 Learning rate: 0.002 Mask loss: 0.17938 RPN box loss: 0.03002 RPN score loss: 0.00264 RPN total loss: 0.03265 Total loss: 0.96759 timestamp: 1655050820.8159657 iteration: 53900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08376 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.15325 L1 loss: 0.0000e+00 L2 loss: 0.57941 Learning rate: 0.002 Mask loss: 0.12114 RPN box loss: 0.03093 RPN score loss: 0.0042 RPN total loss: 0.03512 Total loss: 0.88891 timestamp: 1655050824.0807402 iteration: 53905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.17397 L1 loss: 0.0000e+00 L2 loss: 0.5794 Learning rate: 0.002 Mask loss: 0.11401 RPN box loss: 0.01926 RPN score loss: 0.00321 RPN total loss: 0.02247 Total loss: 0.88985 timestamp: 1655050827.344886 iteration: 53910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09873 FastRCNN class loss: 0.08725 FastRCNN total loss: 0.18598 L1 loss: 0.0000e+00 L2 loss: 0.57939 Learning rate: 0.002 Mask loss: 0.15579 RPN box loss: 0.02055 RPN score loss: 0.01064 RPN total loss: 0.03118 Total loss: 0.95235 timestamp: 1655050830.6069357 iteration: 53915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13652 FastRCNN class loss: 0.09189 FastRCNN total loss: 0.22841 L1 loss: 0.0000e+00 L2 loss: 0.57938 Learning rate: 0.002 Mask loss: 0.11328 RPN box loss: 0.00943 RPN score loss: 0.00801 RPN total loss: 0.01744 Total loss: 0.93852 timestamp: 1655050833.8634586 iteration: 53920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14379 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.2185 L1 loss: 0.0000e+00 L2 loss: 0.57937 Learning rate: 0.002 Mask loss: 0.18818 RPN box loss: 0.00966 RPN score loss: 0.00778 RPN total loss: 0.01744 Total loss: 1.00349 timestamp: 1655050837.1793728 iteration: 53925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07553 FastRCNN class loss: 0.04815 FastRCNN total loss: 0.12367 L1 loss: 0.0000e+00 L2 loss: 0.57936 Learning rate: 0.002 Mask loss: 0.12297 RPN box loss: 0.00735 RPN score loss: 0.00189 RPN total loss: 0.00924 Total loss: 0.83525 timestamp: 1655050840.5078254 iteration: 53930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.12916 L1 loss: 0.0000e+00 L2 loss: 0.57936 Learning rate: 0.002 Mask loss: 0.10021 RPN box loss: 0.01803 RPN score loss: 0.00587 RPN total loss: 0.02389 Total loss: 0.83262 timestamp: 1655050843.810864 iteration: 53935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12928 FastRCNN class loss: 0.08066 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 0.57935 Learning rate: 0.002 Mask loss: 0.19893 RPN box loss: 0.00534 RPN score loss: 0.01052 RPN total loss: 0.01587 Total loss: 1.00409 timestamp: 1655050847.078035 iteration: 53940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04718 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.10707 L1 loss: 0.0000e+00 L2 loss: 0.57934 Learning rate: 0.002 Mask loss: 0.15445 RPN box loss: 0.02142 RPN score loss: 0.00568 RPN total loss: 0.02709 Total loss: 0.86795 timestamp: 1655050850.445032 iteration: 53945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10989 FastRCNN class loss: 0.0838 FastRCNN total loss: 0.19369 L1 loss: 0.0000e+00 L2 loss: 0.57933 Learning rate: 0.002 Mask loss: 0.18543 RPN box loss: 0.01018 RPN score loss: 0.00505 RPN total loss: 0.01523 Total loss: 0.97368 timestamp: 1655050853.7132869 iteration: 53950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13627 FastRCNN class loss: 0.12136 FastRCNN total loss: 0.25764 L1 loss: 0.0000e+00 L2 loss: 0.57932 Learning rate: 0.002 Mask loss: 0.15621 RPN box loss: 0.01573 RPN score loss: 0.01289 RPN total loss: 0.02862 Total loss: 1.02179 timestamp: 1655050856.9434242 iteration: 53955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09117 FastRCNN class loss: 0.07844 FastRCNN total loss: 0.16961 L1 loss: 0.0000e+00 L2 loss: 0.57931 Learning rate: 0.002 Mask loss: 0.18155 RPN box loss: 0.00497 RPN score loss: 0.00467 RPN total loss: 0.00964 Total loss: 0.94011 timestamp: 1655050860.2202516 iteration: 53960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11893 FastRCNN class loss: 0.06868 FastRCNN total loss: 0.18761 L1 loss: 0.0000e+00 L2 loss: 0.57931 Learning rate: 0.002 Mask loss: 0.13089 RPN box loss: 0.02277 RPN score loss: 0.00495 RPN total loss: 0.02772 Total loss: 0.92552 timestamp: 1655050863.5238466 iteration: 53965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1495 FastRCNN class loss: 0.09469 FastRCNN total loss: 0.24419 L1 loss: 0.0000e+00 L2 loss: 0.5793 Learning rate: 0.002 Mask loss: 0.24465 RPN box loss: 0.01785 RPN score loss: 0.01852 RPN total loss: 0.03637 Total loss: 1.10451 timestamp: 1655050866.7937388 iteration: 53970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09236 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.17237 L1 loss: 0.0000e+00 L2 loss: 0.57929 Learning rate: 0.002 Mask loss: 0.13769 RPN box loss: 0.00815 RPN score loss: 0.00546 RPN total loss: 0.01361 Total loss: 0.90296 timestamp: 1655050870.012547 iteration: 53975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11612 FastRCNN class loss: 0.09627 FastRCNN total loss: 0.21238 L1 loss: 0.0000e+00 L2 loss: 0.57928 Learning rate: 0.002 Mask loss: 0.13936 RPN box loss: 0.03018 RPN score loss: 0.01239 RPN total loss: 0.04256 Total loss: 0.97358 timestamp: 1655050873.2909453 iteration: 53980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08482 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.16388 L1 loss: 0.0000e+00 L2 loss: 0.57927 Learning rate: 0.002 Mask loss: 0.18704 RPN box loss: 0.02559 RPN score loss: 0.00542 RPN total loss: 0.03101 Total loss: 0.9612 timestamp: 1655050876.540086 iteration: 53985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16575 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.22279 L1 loss: 0.0000e+00 L2 loss: 0.57926 Learning rate: 0.002 Mask loss: 0.09979 RPN box loss: 0.007 RPN score loss: 0.0026 RPN total loss: 0.0096 Total loss: 0.91144 timestamp: 1655050879.7232406 iteration: 53990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14053 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.2324 L1 loss: 0.0000e+00 L2 loss: 0.57925 Learning rate: 0.002 Mask loss: 0.16853 RPN box loss: 0.00866 RPN score loss: 0.00539 RPN total loss: 0.01405 Total loss: 0.99423 timestamp: 1655050883.0101018 iteration: 53995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06235 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.12531 L1 loss: 0.0000e+00 L2 loss: 0.57924 Learning rate: 0.002 Mask loss: 0.11315 RPN box loss: 0.00842 RPN score loss: 0.00398 RPN total loss: 0.0124 Total loss: 0.8301 timestamp: 1655050886.2920039 iteration: 54000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17391 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.25342 L1 loss: 0.0000e+00 L2 loss: 0.57923 Learning rate: 0.002 Mask loss: 0.12 RPN box loss: 0.01657 RPN score loss: 0.00745 RPN total loss: 0.02402 Total loss: 0.97666 timestamp: 1655050889.5538948 iteration: 54005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07644 FastRCNN class loss: 0.11004 FastRCNN total loss: 0.18648 L1 loss: 0.0000e+00 L2 loss: 0.57922 Learning rate: 0.002 Mask loss: 0.13573 RPN box loss: 0.01128 RPN score loss: 0.00646 RPN total loss: 0.01774 Total loss: 0.91918 timestamp: 1655050892.7999997 iteration: 54010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15663 FastRCNN class loss: 0.09972 FastRCNN total loss: 0.25636 L1 loss: 0.0000e+00 L2 loss: 0.57921 Learning rate: 0.002 Mask loss: 0.14501 RPN box loss: 0.02174 RPN score loss: 0.01155 RPN total loss: 0.0333 Total loss: 1.01388 timestamp: 1655050896.0701811 iteration: 54015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10527 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.1523 L1 loss: 0.0000e+00 L2 loss: 0.5792 Learning rate: 0.002 Mask loss: 0.10905 RPN box loss: 0.01075 RPN score loss: 0.00728 RPN total loss: 0.01804 Total loss: 0.85859 timestamp: 1655050899.3583004 iteration: 54020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13889 FastRCNN class loss: 0.0929 FastRCNN total loss: 0.23179 L1 loss: 0.0000e+00 L2 loss: 0.57919 Learning rate: 0.002 Mask loss: 0.16946 RPN box loss: 0.06672 RPN score loss: 0.005 RPN total loss: 0.07173 Total loss: 1.05217 timestamp: 1655050902.6472702 iteration: 54025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10631 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 0.57919 Learning rate: 0.002 Mask loss: 0.14422 RPN box loss: 0.00684 RPN score loss: 0.00326 RPN total loss: 0.0101 Total loss: 0.89276 timestamp: 1655050905.8851209 iteration: 54030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11049 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.1976 L1 loss: 0.0000e+00 L2 loss: 0.57918 Learning rate: 0.002 Mask loss: 0.15855 RPN box loss: 0.00914 RPN score loss: 0.0024 RPN total loss: 0.01154 Total loss: 0.94687 timestamp: 1655050909.1214876 iteration: 54035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12373 FastRCNN class loss: 0.06457 FastRCNN total loss: 0.18829 L1 loss: 0.0000e+00 L2 loss: 0.57918 Learning rate: 0.002 Mask loss: 0.13313 RPN box loss: 0.03095 RPN score loss: 0.0059 RPN total loss: 0.03685 Total loss: 0.93744 timestamp: 1655050912.3806787 iteration: 54040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14856 FastRCNN class loss: 0.1375 FastRCNN total loss: 0.28605 L1 loss: 0.0000e+00 L2 loss: 0.57917 Learning rate: 0.002 Mask loss: 0.22188 RPN box loss: 0.01613 RPN score loss: 0.00959 RPN total loss: 0.02572 Total loss: 1.11282 timestamp: 1655050915.6319273 iteration: 54045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07187 FastRCNN class loss: 0.04878 FastRCNN total loss: 0.12065 L1 loss: 0.0000e+00 L2 loss: 0.57916 Learning rate: 0.002 Mask loss: 0.16775 RPN box loss: 0.01808 RPN score loss: 0.0048 RPN total loss: 0.02288 Total loss: 0.89043 timestamp: 1655050918.8359454 iteration: 54050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06581 FastRCNN class loss: 0.04515 FastRCNN total loss: 0.11096 L1 loss: 0.0000e+00 L2 loss: 0.57915 Learning rate: 0.002 Mask loss: 0.10089 RPN box loss: 0.00353 RPN score loss: 0.00345 RPN total loss: 0.00698 Total loss: 0.79798 timestamp: 1655050922.1508374 iteration: 54055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10519 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.17212 L1 loss: 0.0000e+00 L2 loss: 0.57914 Learning rate: 0.002 Mask loss: 0.1397 RPN box loss: 0.03469 RPN score loss: 0.01136 RPN total loss: 0.04605 Total loss: 0.937 timestamp: 1655050925.4835494 iteration: 54060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19207 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.26694 L1 loss: 0.0000e+00 L2 loss: 0.57913 Learning rate: 0.002 Mask loss: 0.12568 RPN box loss: 0.03435 RPN score loss: 0.00354 RPN total loss: 0.03789 Total loss: 1.00964 timestamp: 1655050928.7853916 iteration: 54065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.105 FastRCNN class loss: 0.04315 FastRCNN total loss: 0.14815 L1 loss: 0.0000e+00 L2 loss: 0.57912 Learning rate: 0.002 Mask loss: 0.14595 RPN box loss: 0.01176 RPN score loss: 0.00537 RPN total loss: 0.01713 Total loss: 0.89036 timestamp: 1655050932.0347526 iteration: 54070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.16316 L1 loss: 0.0000e+00 L2 loss: 0.57912 Learning rate: 0.002 Mask loss: 0.14719 RPN box loss: 0.00687 RPN score loss: 0.00354 RPN total loss: 0.01041 Total loss: 0.89987 timestamp: 1655050935.2585523 iteration: 54075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0734 FastRCNN class loss: 0.05542 FastRCNN total loss: 0.12882 L1 loss: 0.0000e+00 L2 loss: 0.57911 Learning rate: 0.002 Mask loss: 0.15782 RPN box loss: 0.00846 RPN score loss: 0.00401 RPN total loss: 0.01247 Total loss: 0.87822 timestamp: 1655050938.5187488 iteration: 54080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11914 FastRCNN class loss: 0.06824 FastRCNN total loss: 0.18738 L1 loss: 0.0000e+00 L2 loss: 0.5791 Learning rate: 0.002 Mask loss: 0.18888 RPN box loss: 0.02365 RPN score loss: 0.00348 RPN total loss: 0.02713 Total loss: 0.98249 timestamp: 1655050941.718167 iteration: 54085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14829 FastRCNN class loss: 0.10125 FastRCNN total loss: 0.24954 L1 loss: 0.0000e+00 L2 loss: 0.5791 Learning rate: 0.002 Mask loss: 0.1971 RPN box loss: 0.01924 RPN score loss: 0.00473 RPN total loss: 0.02397 Total loss: 1.0497 timestamp: 1655050944.9620826 iteration: 54090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11096 FastRCNN class loss: 0.09053 FastRCNN total loss: 0.2015 L1 loss: 0.0000e+00 L2 loss: 0.57909 Learning rate: 0.002 Mask loss: 0.14433 RPN box loss: 0.00892 RPN score loss: 0.00682 RPN total loss: 0.01573 Total loss: 0.94065 timestamp: 1655050948.3067381 iteration: 54095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09306 FastRCNN class loss: 0.07201 FastRCNN total loss: 0.16507 L1 loss: 0.0000e+00 L2 loss: 0.57908 Learning rate: 0.002 Mask loss: 0.11119 RPN box loss: 0.00666 RPN score loss: 0.00536 RPN total loss: 0.01202 Total loss: 0.86736 timestamp: 1655050951.5728106 iteration: 54100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11887 FastRCNN class loss: 0.05775 FastRCNN total loss: 0.17662 L1 loss: 0.0000e+00 L2 loss: 0.57907 Learning rate: 0.002 Mask loss: 0.13904 RPN box loss: 0.032 RPN score loss: 0.00647 RPN total loss: 0.03847 Total loss: 0.93319 timestamp: 1655050954.791699 iteration: 54105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13431 FastRCNN class loss: 0.08638 FastRCNN total loss: 0.2207 L1 loss: 0.0000e+00 L2 loss: 0.57906 Learning rate: 0.002 Mask loss: 0.17335 RPN box loss: 0.00761 RPN score loss: 0.00467 RPN total loss: 0.01227 Total loss: 0.98538 timestamp: 1655050958.006713 iteration: 54110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11272 FastRCNN class loss: 0.07818 FastRCNN total loss: 0.1909 L1 loss: 0.0000e+00 L2 loss: 0.57905 Learning rate: 0.002 Mask loss: 0.1458 RPN box loss: 0.02708 RPN score loss: 0.00573 RPN total loss: 0.0328 Total loss: 0.94855 timestamp: 1655050961.2415183 iteration: 54115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09157 FastRCNN class loss: 0.09669 FastRCNN total loss: 0.18826 L1 loss: 0.0000e+00 L2 loss: 0.57904 Learning rate: 0.002 Mask loss: 0.12244 RPN box loss: 0.0282 RPN score loss: 0.01333 RPN total loss: 0.04153 Total loss: 0.93127 timestamp: 1655050964.4926095 iteration: 54120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12966 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.20208 L1 loss: 0.0000e+00 L2 loss: 0.57903 Learning rate: 0.002 Mask loss: 0.1842 RPN box loss: 0.04255 RPN score loss: 0.00716 RPN total loss: 0.04971 Total loss: 1.01503 timestamp: 1655050967.7585628 iteration: 54125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18604 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.25994 L1 loss: 0.0000e+00 L2 loss: 0.57902 Learning rate: 0.002 Mask loss: 0.14111 RPN box loss: 0.02477 RPN score loss: 0.00689 RPN total loss: 0.03166 Total loss: 1.01173 timestamp: 1655050971.0483003 iteration: 54130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1118 FastRCNN class loss: 0.16576 FastRCNN total loss: 0.27756 L1 loss: 0.0000e+00 L2 loss: 0.57901 Learning rate: 0.002 Mask loss: 0.23301 RPN box loss: 0.04032 RPN score loss: 0.07512 RPN total loss: 0.11544 Total loss: 1.20503 timestamp: 1655050974.3706708 iteration: 54135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06956 FastRCNN class loss: 0.04531 FastRCNN total loss: 0.11487 L1 loss: 0.0000e+00 L2 loss: 0.579 Learning rate: 0.002 Mask loss: 0.12849 RPN box loss: 0.01193 RPN score loss: 0.00222 RPN total loss: 0.01416 Total loss: 0.83653 timestamp: 1655050977.6621213 iteration: 54140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1639 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.22659 L1 loss: 0.0000e+00 L2 loss: 0.57899 Learning rate: 0.002 Mask loss: 0.12827 RPN box loss: 0.01349 RPN score loss: 0.00445 RPN total loss: 0.01794 Total loss: 0.9518 timestamp: 1655050980.9479413 iteration: 54145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13722 FastRCNN class loss: 0.1028 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 0.57899 Learning rate: 0.002 Mask loss: 0.14872 RPN box loss: 0.0318 RPN score loss: 0.00912 RPN total loss: 0.04092 Total loss: 1.00865 timestamp: 1655050984.3159657 iteration: 54150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12963 FastRCNN class loss: 0.07891 FastRCNN total loss: 0.20855 L1 loss: 0.0000e+00 L2 loss: 0.57898 Learning rate: 0.002 Mask loss: 0.16015 RPN box loss: 0.01354 RPN score loss: 0.00818 RPN total loss: 0.02173 Total loss: 0.9694 timestamp: 1655050987.5745528 iteration: 54155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09598 FastRCNN class loss: 0.0669 FastRCNN total loss: 0.16288 L1 loss: 0.0000e+00 L2 loss: 0.57897 Learning rate: 0.002 Mask loss: 0.17778 RPN box loss: 0.0293 RPN score loss: 0.00292 RPN total loss: 0.03221 Total loss: 0.95184 timestamp: 1655050990.8948996 iteration: 54160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07021 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.11993 L1 loss: 0.0000e+00 L2 loss: 0.57896 Learning rate: 0.002 Mask loss: 0.09099 RPN box loss: 0.00809 RPN score loss: 0.00274 RPN total loss: 0.01083 Total loss: 0.8007 timestamp: 1655050994.2225559 iteration: 54165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.069 FastRCNN class loss: 0.04563 FastRCNN total loss: 0.11463 L1 loss: 0.0000e+00 L2 loss: 0.57895 Learning rate: 0.002 Mask loss: 0.17164 RPN box loss: 0.01434 RPN score loss: 0.01276 RPN total loss: 0.02711 Total loss: 0.89233 timestamp: 1655050997.5183587 iteration: 54170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12831 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.20724 L1 loss: 0.0000e+00 L2 loss: 0.57894 Learning rate: 0.002 Mask loss: 0.16565 RPN box loss: 0.02293 RPN score loss: 0.00935 RPN total loss: 0.03228 Total loss: 0.98411 timestamp: 1655051000.825935 iteration: 54175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06408 FastRCNN class loss: 0.04544 FastRCNN total loss: 0.10952 L1 loss: 0.0000e+00 L2 loss: 0.57893 Learning rate: 0.002 Mask loss: 0.11114 RPN box loss: 0.01032 RPN score loss: 0.00393 RPN total loss: 0.01426 Total loss: 0.81385 timestamp: 1655051004.1821892 iteration: 54180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1539 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.2215 L1 loss: 0.0000e+00 L2 loss: 0.57892 Learning rate: 0.002 Mask loss: 0.16712 RPN box loss: 0.02865 RPN score loss: 0.00444 RPN total loss: 0.03309 Total loss: 1.00063 timestamp: 1655051007.4224715 iteration: 54185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05961 FastRCNN class loss: 0.03042 FastRCNN total loss: 0.09002 L1 loss: 0.0000e+00 L2 loss: 0.57892 Learning rate: 0.002 Mask loss: 0.15103 RPN box loss: 0.00336 RPN score loss: 0.00429 RPN total loss: 0.00764 Total loss: 0.82762 timestamp: 1655051010.7531185 iteration: 54190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12181 FastRCNN class loss: 0.0991 FastRCNN total loss: 0.22091 L1 loss: 0.0000e+00 L2 loss: 0.57891 Learning rate: 0.002 Mask loss: 0.16027 RPN box loss: 0.01572 RPN score loss: 0.01439 RPN total loss: 0.0301 Total loss: 0.9902 timestamp: 1655051013.9796038 iteration: 54195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15837 FastRCNN class loss: 0.13314 FastRCNN total loss: 0.2915 L1 loss: 0.0000e+00 L2 loss: 0.57891 Learning rate: 0.002 Mask loss: 0.2327 RPN box loss: 0.03174 RPN score loss: 0.00838 RPN total loss: 0.04012 Total loss: 1.14323 timestamp: 1655051017.2367167 iteration: 54200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10488 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.17253 L1 loss: 0.0000e+00 L2 loss: 0.5789 Learning rate: 0.002 Mask loss: 0.13054 RPN box loss: 0.02327 RPN score loss: 0.01648 RPN total loss: 0.03975 Total loss: 0.92172 timestamp: 1655051020.4359636 iteration: 54205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11223 FastRCNN class loss: 0.06786 FastRCNN total loss: 0.1801 L1 loss: 0.0000e+00 L2 loss: 0.57889 Learning rate: 0.002 Mask loss: 0.14633 RPN box loss: 0.01092 RPN score loss: 0.00295 RPN total loss: 0.01387 Total loss: 0.91919 timestamp: 1655051023.6911247 iteration: 54210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09271 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.13256 L1 loss: 0.0000e+00 L2 loss: 0.57888 Learning rate: 0.002 Mask loss: 0.11844 RPN box loss: 0.01272 RPN score loss: 0.00455 RPN total loss: 0.01727 Total loss: 0.84715 timestamp: 1655051026.9787424 iteration: 54215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06543 FastRCNN class loss: 0.04152 FastRCNN total loss: 0.10695 L1 loss: 0.0000e+00 L2 loss: 0.57887 Learning rate: 0.002 Mask loss: 0.15033 RPN box loss: 0.00355 RPN score loss: 0.0023 RPN total loss: 0.00585 Total loss: 0.842 timestamp: 1655051030.1885564 iteration: 54220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.05861 FastRCNN total loss: 0.17204 L1 loss: 0.0000e+00 L2 loss: 0.57886 Learning rate: 0.002 Mask loss: 0.12725 RPN box loss: 0.01487 RPN score loss: 0.00358 RPN total loss: 0.01845 Total loss: 0.8966 timestamp: 1655051033.4736016 iteration: 54225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10111 FastRCNN class loss: 0.07557 FastRCNN total loss: 0.17668 L1 loss: 0.0000e+00 L2 loss: 0.57884 Learning rate: 0.002 Mask loss: 0.13457 RPN box loss: 0.04861 RPN score loss: 0.00876 RPN total loss: 0.05738 Total loss: 0.94747 timestamp: 1655051036.7242763 iteration: 54230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14041 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.20709 L1 loss: 0.0000e+00 L2 loss: 0.57884 Learning rate: 0.002 Mask loss: 0.13354 RPN box loss: 0.00659 RPN score loss: 0.00095 RPN total loss: 0.00754 Total loss: 0.92701 timestamp: 1655051039.9891856 iteration: 54235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19578 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.27165 L1 loss: 0.0000e+00 L2 loss: 0.57883 Learning rate: 0.002 Mask loss: 0.15643 RPN box loss: 0.01805 RPN score loss: 0.00447 RPN total loss: 0.02252 Total loss: 1.02943 timestamp: 1655051043.2831316 iteration: 54240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11692 FastRCNN class loss: 0.09251 FastRCNN total loss: 0.20943 L1 loss: 0.0000e+00 L2 loss: 0.57882 Learning rate: 0.002 Mask loss: 0.17988 RPN box loss: 0.01479 RPN score loss: 0.00325 RPN total loss: 0.01804 Total loss: 0.98617 timestamp: 1655051046.516051 iteration: 54245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12516 FastRCNN class loss: 0.05674 FastRCNN total loss: 0.18189 L1 loss: 0.0000e+00 L2 loss: 0.57882 Learning rate: 0.002 Mask loss: 0.17423 RPN box loss: 0.01463 RPN score loss: 0.00628 RPN total loss: 0.02091 Total loss: 0.95584 timestamp: 1655051049.7755742 iteration: 54250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08179 FastRCNN class loss: 0.08936 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.57881 Learning rate: 0.002 Mask loss: 0.12668 RPN box loss: 0.01197 RPN score loss: 0.00831 RPN total loss: 0.02028 Total loss: 0.89692 timestamp: 1655051053.0668724 iteration: 54255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08077 FastRCNN class loss: 0.05548 FastRCNN total loss: 0.13625 L1 loss: 0.0000e+00 L2 loss: 0.5788 Learning rate: 0.002 Mask loss: 0.09579 RPN box loss: 0.03188 RPN score loss: 0.00245 RPN total loss: 0.03434 Total loss: 0.84517 timestamp: 1655051056.2857866 iteration: 54260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08157 FastRCNN class loss: 0.09153 FastRCNN total loss: 0.1731 L1 loss: 0.0000e+00 L2 loss: 0.57879 Learning rate: 0.002 Mask loss: 0.16649 RPN box loss: 0.0074 RPN score loss: 0.00229 RPN total loss: 0.0097 Total loss: 0.92807 timestamp: 1655051059.576798 iteration: 54265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05908 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.14499 L1 loss: 0.0000e+00 L2 loss: 0.57878 Learning rate: 0.002 Mask loss: 0.09682 RPN box loss: 0.01226 RPN score loss: 0.01198 RPN total loss: 0.02424 Total loss: 0.84484 timestamp: 1655051062.8140974 iteration: 54270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10176 FastRCNN class loss: 0.07652 FastRCNN total loss: 0.17828 L1 loss: 0.0000e+00 L2 loss: 0.57877 Learning rate: 0.002 Mask loss: 0.14874 RPN box loss: 0.008 RPN score loss: 0.00842 RPN total loss: 0.01642 Total loss: 0.92222 timestamp: 1655051066.1214883 iteration: 54275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0921 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.14697 L1 loss: 0.0000e+00 L2 loss: 0.57876 Learning rate: 0.002 Mask loss: 0.1286 RPN box loss: 0.01254 RPN score loss: 0.00181 RPN total loss: 0.01434 Total loss: 0.86868 timestamp: 1655051069.4198909 iteration: 54280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08077 FastRCNN class loss: 0.04366 FastRCNN total loss: 0.12443 L1 loss: 0.0000e+00 L2 loss: 0.57875 Learning rate: 0.002 Mask loss: 0.13109 RPN box loss: 0.02213 RPN score loss: 0.00347 RPN total loss: 0.02559 Total loss: 0.85988 timestamp: 1655051072.730936 iteration: 54285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10958 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.18015 L1 loss: 0.0000e+00 L2 loss: 0.57875 Learning rate: 0.002 Mask loss: 0.18047 RPN box loss: 0.01546 RPN score loss: 0.00251 RPN total loss: 0.01796 Total loss: 0.95734 timestamp: 1655051076.0288537 iteration: 54290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.14467 L1 loss: 0.0000e+00 L2 loss: 0.57874 Learning rate: 0.002 Mask loss: 0.14852 RPN box loss: 0.01865 RPN score loss: 0.00756 RPN total loss: 0.02622 Total loss: 0.89815 timestamp: 1655051079.309425 iteration: 54295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12541 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.18689 L1 loss: 0.0000e+00 L2 loss: 0.57873 Learning rate: 0.002 Mask loss: 0.14903 RPN box loss: 0.01876 RPN score loss: 0.00713 RPN total loss: 0.02589 Total loss: 0.94055 timestamp: 1655051082.602499 iteration: 54300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09592 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.16278 L1 loss: 0.0000e+00 L2 loss: 0.57872 Learning rate: 0.002 Mask loss: 0.16134 RPN box loss: 0.01381 RPN score loss: 0.01395 RPN total loss: 0.02777 Total loss: 0.93061 timestamp: 1655051085.9208293 iteration: 54305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0666 FastRCNN class loss: 0.06384 FastRCNN total loss: 0.13044 L1 loss: 0.0000e+00 L2 loss: 0.57871 Learning rate: 0.002 Mask loss: 0.11117 RPN box loss: 0.00595 RPN score loss: 0.00171 RPN total loss: 0.00766 Total loss: 0.82799 timestamp: 1655051089.1981716 iteration: 54310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10009 FastRCNN class loss: 0.08348 FastRCNN total loss: 0.18357 L1 loss: 0.0000e+00 L2 loss: 0.5787 Learning rate: 0.002 Mask loss: 0.14329 RPN box loss: 0.02168 RPN score loss: 0.00372 RPN total loss: 0.0254 Total loss: 0.93096 timestamp: 1655051092.5293553 iteration: 54315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08012 FastRCNN class loss: 0.06823 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.57869 Learning rate: 0.002 Mask loss: 0.15265 RPN box loss: 0.03768 RPN score loss: 0.00603 RPN total loss: 0.04371 Total loss: 0.92341 timestamp: 1655051095.7939572 iteration: 54320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16846 FastRCNN class loss: 0.11195 FastRCNN total loss: 0.2804 L1 loss: 0.0000e+00 L2 loss: 0.57869 Learning rate: 0.002 Mask loss: 0.16865 RPN box loss: 0.0381 RPN score loss: 0.0124 RPN total loss: 0.05049 Total loss: 1.07823 timestamp: 1655051099.014405 iteration: 54325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10451 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.16778 L1 loss: 0.0000e+00 L2 loss: 0.57868 Learning rate: 0.002 Mask loss: 0.10468 RPN box loss: 0.0299 RPN score loss: 0.03694 RPN total loss: 0.06684 Total loss: 0.91798 timestamp: 1655051102.2461417 iteration: 54330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10234 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.16938 L1 loss: 0.0000e+00 L2 loss: 0.57867 Learning rate: 0.002 Mask loss: 0.13739 RPN box loss: 0.02162 RPN score loss: 0.00243 RPN total loss: 0.02405 Total loss: 0.90949 timestamp: 1655051105.4500217 iteration: 54335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11655 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.18128 L1 loss: 0.0000e+00 L2 loss: 0.57866 Learning rate: 0.002 Mask loss: 0.13609 RPN box loss: 0.02364 RPN score loss: 0.00437 RPN total loss: 0.02801 Total loss: 0.92404 timestamp: 1655051108.6700363 iteration: 54340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12074 FastRCNN class loss: 0.04058 FastRCNN total loss: 0.16132 L1 loss: 0.0000e+00 L2 loss: 0.57865 Learning rate: 0.002 Mask loss: 0.09735 RPN box loss: 0.01093 RPN score loss: 0.00204 RPN total loss: 0.01297 Total loss: 0.85029 timestamp: 1655051111.9657347 iteration: 54345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07757 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.14354 L1 loss: 0.0000e+00 L2 loss: 0.57864 Learning rate: 0.002 Mask loss: 0.09047 RPN box loss: 0.01906 RPN score loss: 0.00377 RPN total loss: 0.02283 Total loss: 0.83548 timestamp: 1655051115.2068052 iteration: 54350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15648 FastRCNN class loss: 0.11762 FastRCNN total loss: 0.2741 L1 loss: 0.0000e+00 L2 loss: 0.57864 Learning rate: 0.002 Mask loss: 0.19626 RPN box loss: 0.02046 RPN score loss: 0.00772 RPN total loss: 0.02819 Total loss: 1.07718 timestamp: 1655051118.541576 iteration: 54355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.17238 L1 loss: 0.0000e+00 L2 loss: 0.57863 Learning rate: 0.002 Mask loss: 0.16964 RPN box loss: 0.01407 RPN score loss: 0.00525 RPN total loss: 0.01932 Total loss: 0.93998 timestamp: 1655051121.8018806 iteration: 54360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06991 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.13381 L1 loss: 0.0000e+00 L2 loss: 0.57862 Learning rate: 0.002 Mask loss: 0.12532 RPN box loss: 0.01546 RPN score loss: 0.0037 RPN total loss: 0.01915 Total loss: 0.85691 timestamp: 1655051125.175534 iteration: 54365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0921 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.14814 L1 loss: 0.0000e+00 L2 loss: 0.57861 Learning rate: 0.002 Mask loss: 0.12296 RPN box loss: 0.01484 RPN score loss: 0.00206 RPN total loss: 0.0169 Total loss: 0.86661 timestamp: 1655051128.4413033 iteration: 54370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10706 FastRCNN class loss: 0.12801 FastRCNN total loss: 0.23507 L1 loss: 0.0000e+00 L2 loss: 0.5786 Learning rate: 0.002 Mask loss: 0.15053 RPN box loss: 0.012 RPN score loss: 0.00113 RPN total loss: 0.01313 Total loss: 0.97733 timestamp: 1655051131.7339346 iteration: 54375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1646 FastRCNN class loss: 0.0943 FastRCNN total loss: 0.25891 L1 loss: 0.0000e+00 L2 loss: 0.5786 Learning rate: 0.002 Mask loss: 0.19142 RPN box loss: 0.02569 RPN score loss: 0.00627 RPN total loss: 0.03196 Total loss: 1.06088 timestamp: 1655051134.9360702 iteration: 54380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09962 FastRCNN class loss: 0.06868 FastRCNN total loss: 0.1683 L1 loss: 0.0000e+00 L2 loss: 0.57859 Learning rate: 0.002 Mask loss: 0.11988 RPN box loss: 0.00813 RPN score loss: 0.01332 RPN total loss: 0.02146 Total loss: 0.88822 timestamp: 1655051138.2775333 iteration: 54385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13154 FastRCNN class loss: 0.06356 FastRCNN total loss: 0.1951 L1 loss: 0.0000e+00 L2 loss: 0.57858 Learning rate: 0.002 Mask loss: 0.14959 RPN box loss: 0.01536 RPN score loss: 0.00326 RPN total loss: 0.01862 Total loss: 0.94189 timestamp: 1655051141.5206275 iteration: 54390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07201 FastRCNN class loss: 0.05804 FastRCNN total loss: 0.13006 L1 loss: 0.0000e+00 L2 loss: 0.57857 Learning rate: 0.002 Mask loss: 0.09424 RPN box loss: 0.01219 RPN score loss: 0.00612 RPN total loss: 0.01831 Total loss: 0.82117 timestamp: 1655051144.711765 iteration: 54395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09779 FastRCNN class loss: 0.10459 FastRCNN total loss: 0.20238 L1 loss: 0.0000e+00 L2 loss: 0.57856 Learning rate: 0.002 Mask loss: 0.16353 RPN box loss: 0.02393 RPN score loss: 0.01589 RPN total loss: 0.03982 Total loss: 0.98429 timestamp: 1655051148.0118546 iteration: 54400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08046 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.15291 L1 loss: 0.0000e+00 L2 loss: 0.57855 Learning rate: 0.002 Mask loss: 0.13803 RPN box loss: 0.01294 RPN score loss: 0.00387 RPN total loss: 0.01681 Total loss: 0.8863 timestamp: 1655051151.2717142 iteration: 54405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05607 FastRCNN class loss: 0.06093 FastRCNN total loss: 0.117 L1 loss: 0.0000e+00 L2 loss: 0.57854 Learning rate: 0.002 Mask loss: 0.23961 RPN box loss: 0.02595 RPN score loss: 0.00108 RPN total loss: 0.02703 Total loss: 0.96218 timestamp: 1655051154.5583708 iteration: 54410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12433 FastRCNN class loss: 0.09313 FastRCNN total loss: 0.21746 L1 loss: 0.0000e+00 L2 loss: 0.57853 Learning rate: 0.002 Mask loss: 0.18518 RPN box loss: 0.01693 RPN score loss: 0.00415 RPN total loss: 0.02108 Total loss: 1.00225 timestamp: 1655051157.8791149 iteration: 54415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11034 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.17849 L1 loss: 0.0000e+00 L2 loss: 0.57852 Learning rate: 0.002 Mask loss: 0.19822 RPN box loss: 0.02863 RPN score loss: 0.00967 RPN total loss: 0.0383 Total loss: 0.99353 timestamp: 1655051161.1563025 iteration: 54420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1172 FastRCNN class loss: 0.0696 FastRCNN total loss: 0.1868 L1 loss: 0.0000e+00 L2 loss: 0.57851 Learning rate: 0.002 Mask loss: 0.11107 RPN box loss: 0.00606 RPN score loss: 0.00178 RPN total loss: 0.00784 Total loss: 0.88421 timestamp: 1655051164.393686 iteration: 54425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.16139 L1 loss: 0.0000e+00 L2 loss: 0.5785 Learning rate: 0.002 Mask loss: 0.11719 RPN box loss: 0.0158 RPN score loss: 0.006 RPN total loss: 0.02179 Total loss: 0.87888 timestamp: 1655051167.6654043 iteration: 54430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14326 FastRCNN class loss: 0.06776 FastRCNN total loss: 0.21101 L1 loss: 0.0000e+00 L2 loss: 0.5785 Learning rate: 0.002 Mask loss: 0.12294 RPN box loss: 0.0128 RPN score loss: 0.00677 RPN total loss: 0.01957 Total loss: 0.93201 timestamp: 1655051170.9470906 iteration: 54435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1193 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.1955 L1 loss: 0.0000e+00 L2 loss: 0.57849 Learning rate: 0.002 Mask loss: 0.18776 RPN box loss: 0.03549 RPN score loss: 0.00757 RPN total loss: 0.04306 Total loss: 1.00482 timestamp: 1655051174.1323614 iteration: 54440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09534 FastRCNN class loss: 0.0931 FastRCNN total loss: 0.18843 L1 loss: 0.0000e+00 L2 loss: 0.57848 Learning rate: 0.002 Mask loss: 0.18065 RPN box loss: 0.02174 RPN score loss: 0.00799 RPN total loss: 0.02973 Total loss: 0.97729 timestamp: 1655051177.4136968 iteration: 54445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12925 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.2081 L1 loss: 0.0000e+00 L2 loss: 0.57847 Learning rate: 0.002 Mask loss: 0.16595 RPN box loss: 0.01879 RPN score loss: 0.00962 RPN total loss: 0.02841 Total loss: 0.98093 timestamp: 1655051180.6877723 iteration: 54450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.07545 FastRCNN total loss: 0.1678 L1 loss: 0.0000e+00 L2 loss: 0.57846 Learning rate: 0.002 Mask loss: 0.1399 RPN box loss: 0.01545 RPN score loss: 0.01552 RPN total loss: 0.03097 Total loss: 0.91713 timestamp: 1655051183.926569 iteration: 54455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11804 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.17562 L1 loss: 0.0000e+00 L2 loss: 0.57845 Learning rate: 0.002 Mask loss: 0.19555 RPN box loss: 0.01716 RPN score loss: 0.01341 RPN total loss: 0.03057 Total loss: 0.98019 timestamp: 1655051187.200416 iteration: 54460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15463 FastRCNN class loss: 0.09 FastRCNN total loss: 0.24463 L1 loss: 0.0000e+00 L2 loss: 0.57845 Learning rate: 0.002 Mask loss: 0.17868 RPN box loss: 0.00885 RPN score loss: 0.00275 RPN total loss: 0.01161 Total loss: 1.01337 timestamp: 1655051190.5022109 iteration: 54465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.16042 L1 loss: 0.0000e+00 L2 loss: 0.57844 Learning rate: 0.002 Mask loss: 0.12243 RPN box loss: 0.03933 RPN score loss: 0.00653 RPN total loss: 0.04587 Total loss: 0.90716 timestamp: 1655051193.7721915 iteration: 54470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09968 FastRCNN class loss: 0.10586 FastRCNN total loss: 0.20554 L1 loss: 0.0000e+00 L2 loss: 0.57843 Learning rate: 0.002 Mask loss: 0.17872 RPN box loss: 0.00829 RPN score loss: 0.00323 RPN total loss: 0.01152 Total loss: 0.97421 timestamp: 1655051197.101785 iteration: 54475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14492 FastRCNN class loss: 0.11341 FastRCNN total loss: 0.25833 L1 loss: 0.0000e+00 L2 loss: 0.57842 Learning rate: 0.002 Mask loss: 0.15669 RPN box loss: 0.02029 RPN score loss: 0.00543 RPN total loss: 0.02573 Total loss: 1.01917 timestamp: 1655051200.3357859 iteration: 54480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08408 FastRCNN class loss: 0.07596 FastRCNN total loss: 0.16004 L1 loss: 0.0000e+00 L2 loss: 0.57841 Learning rate: 0.002 Mask loss: 0.17131 RPN box loss: 0.02381 RPN score loss: 0.00657 RPN total loss: 0.03038 Total loss: 0.94014 timestamp: 1655051203.5678997 iteration: 54485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08038 FastRCNN class loss: 0.04607 FastRCNN total loss: 0.12646 L1 loss: 0.0000e+00 L2 loss: 0.5784 Learning rate: 0.002 Mask loss: 0.07913 RPN box loss: 0.01155 RPN score loss: 0.00155 RPN total loss: 0.01309 Total loss: 0.79708 timestamp: 1655051206.830121 iteration: 54490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08095 FastRCNN class loss: 0.053 FastRCNN total loss: 0.13395 L1 loss: 0.0000e+00 L2 loss: 0.57839 Learning rate: 0.002 Mask loss: 0.09958 RPN box loss: 0.01068 RPN score loss: 0.00284 RPN total loss: 0.01352 Total loss: 0.82544 timestamp: 1655051210.0756388 iteration: 54495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07927 FastRCNN class loss: 0.04278 FastRCNN total loss: 0.12205 L1 loss: 0.0000e+00 L2 loss: 0.57839 Learning rate: 0.002 Mask loss: 0.12142 RPN box loss: 0.02207 RPN score loss: 0.00287 RPN total loss: 0.02493 Total loss: 0.84679 timestamp: 1655051213.4735687 iteration: 54500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08564 FastRCNN class loss: 0.05164 FastRCNN total loss: 0.13729 L1 loss: 0.0000e+00 L2 loss: 0.57838 Learning rate: 0.002 Mask loss: 0.11082 RPN box loss: 0.01004 RPN score loss: 0.0068 RPN total loss: 0.01684 Total loss: 0.84333 timestamp: 1655051216.7253723 iteration: 54505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12011 FastRCNN class loss: 0.10911 FastRCNN total loss: 0.22922 L1 loss: 0.0000e+00 L2 loss: 0.57837 Learning rate: 0.002 Mask loss: 0.16702 RPN box loss: 0.01251 RPN score loss: 0.00313 RPN total loss: 0.01564 Total loss: 0.99026 timestamp: 1655051220.0290618 iteration: 54510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15848 FastRCNN class loss: 0.08295 FastRCNN total loss: 0.24142 L1 loss: 0.0000e+00 L2 loss: 0.57836 Learning rate: 0.002 Mask loss: 0.24094 RPN box loss: 0.01323 RPN score loss: 0.00383 RPN total loss: 0.01706 Total loss: 1.07778 timestamp: 1655051223.275534 iteration: 54515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14426 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.23873 L1 loss: 0.0000e+00 L2 loss: 0.57836 Learning rate: 0.002 Mask loss: 0.21768 RPN box loss: 0.01718 RPN score loss: 0.00963 RPN total loss: 0.02681 Total loss: 1.06158 timestamp: 1655051226.5519779 iteration: 54520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12598 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.19326 L1 loss: 0.0000e+00 L2 loss: 0.57835 Learning rate: 0.002 Mask loss: 0.15128 RPN box loss: 0.02058 RPN score loss: 0.01066 RPN total loss: 0.03124 Total loss: 0.95412 timestamp: 1655051229.7830153 iteration: 54525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13459 FastRCNN class loss: 0.09349 FastRCNN total loss: 0.22808 L1 loss: 0.0000e+00 L2 loss: 0.57834 Learning rate: 0.002 Mask loss: 0.18849 RPN box loss: 0.01422 RPN score loss: 0.00323 RPN total loss: 0.01745 Total loss: 1.01235 timestamp: 1655051233.0534596 iteration: 54530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09494 FastRCNN class loss: 0.0406 FastRCNN total loss: 0.13554 L1 loss: 0.0000e+00 L2 loss: 0.57833 Learning rate: 0.002 Mask loss: 0.07452 RPN box loss: 0.00649 RPN score loss: 0.00142 RPN total loss: 0.00791 Total loss: 0.79631 timestamp: 1655051236.346132 iteration: 54535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09627 FastRCNN class loss: 0.07334 FastRCNN total loss: 0.16961 L1 loss: 0.0000e+00 L2 loss: 0.57833 Learning rate: 0.002 Mask loss: 0.13108 RPN box loss: 0.02168 RPN score loss: 0.00192 RPN total loss: 0.0236 Total loss: 0.90262 timestamp: 1655051239.572154 iteration: 54540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11503 FastRCNN class loss: 0.10838 FastRCNN total loss: 0.22341 L1 loss: 0.0000e+00 L2 loss: 0.57832 Learning rate: 0.002 Mask loss: 0.20736 RPN box loss: 0.02744 RPN score loss: 0.02376 RPN total loss: 0.0512 Total loss: 1.06029 timestamp: 1655051242.8303716 iteration: 54545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.1498 L1 loss: 0.0000e+00 L2 loss: 0.57831 Learning rate: 0.002 Mask loss: 0.09766 RPN box loss: 0.00927 RPN score loss: 0.00348 RPN total loss: 0.01275 Total loss: 0.83853 timestamp: 1655051246.0855231 iteration: 54550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10699 FastRCNN class loss: 0.04876 FastRCNN total loss: 0.15575 L1 loss: 0.0000e+00 L2 loss: 0.5783 Learning rate: 0.002 Mask loss: 0.11801 RPN box loss: 0.00471 RPN score loss: 0.00136 RPN total loss: 0.00607 Total loss: 0.85813 timestamp: 1655051249.4444795 iteration: 54555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09312 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.16076 L1 loss: 0.0000e+00 L2 loss: 0.57829 Learning rate: 0.002 Mask loss: 0.12753 RPN box loss: 0.02173 RPN score loss: 0.00629 RPN total loss: 0.02801 Total loss: 0.8946 timestamp: 1655051252.7413576 iteration: 54560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18555 FastRCNN class loss: 0.14749 FastRCNN total loss: 0.33304 L1 loss: 0.0000e+00 L2 loss: 0.57828 Learning rate: 0.002 Mask loss: 0.24699 RPN box loss: 0.01847 RPN score loss: 0.00965 RPN total loss: 0.02812 Total loss: 1.18643 timestamp: 1655051256.0807657 iteration: 54565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06786 FastRCNN class loss: 0.10549 FastRCNN total loss: 0.17335 L1 loss: 0.0000e+00 L2 loss: 0.57828 Learning rate: 0.002 Mask loss: 0.193 RPN box loss: 0.01881 RPN score loss: 0.00762 RPN total loss: 0.02644 Total loss: 0.97106 timestamp: 1655051259.3603604 iteration: 54570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.18044 L1 loss: 0.0000e+00 L2 loss: 0.57827 Learning rate: 0.002 Mask loss: 0.09641 RPN box loss: 0.04547 RPN score loss: 0.00649 RPN total loss: 0.05196 Total loss: 0.90708 timestamp: 1655051262.6944478 iteration: 54575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07691 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.1316 L1 loss: 0.0000e+00 L2 loss: 0.57826 Learning rate: 0.002 Mask loss: 0.13811 RPN box loss: 0.01377 RPN score loss: 0.00453 RPN total loss: 0.01829 Total loss: 0.86626 timestamp: 1655051265.961105 iteration: 54580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09072 FastRCNN class loss: 0.05395 FastRCNN total loss: 0.14467 L1 loss: 0.0000e+00 L2 loss: 0.57825 Learning rate: 0.002 Mask loss: 0.13261 RPN box loss: 0.01303 RPN score loss: 0.00369 RPN total loss: 0.01672 Total loss: 0.87225 timestamp: 1655051269.187375 iteration: 54585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05897 FastRCNN class loss: 0.03781 FastRCNN total loss: 0.09678 L1 loss: 0.0000e+00 L2 loss: 0.57825 Learning rate: 0.002 Mask loss: 0.09829 RPN box loss: 0.00191 RPN score loss: 0.002 RPN total loss: 0.00391 Total loss: 0.77723 timestamp: 1655051272.4559066 iteration: 54590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06199 FastRCNN class loss: 0.03893 FastRCNN total loss: 0.10092 L1 loss: 0.0000e+00 L2 loss: 0.57824 Learning rate: 0.002 Mask loss: 0.09205 RPN box loss: 0.00652 RPN score loss: 0.00103 RPN total loss: 0.00755 Total loss: 0.77876 timestamp: 1655051275.764986 iteration: 54595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0981 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.16859 L1 loss: 0.0000e+00 L2 loss: 0.57823 Learning rate: 0.002 Mask loss: 0.14409 RPN box loss: 0.01108 RPN score loss: 0.00371 RPN total loss: 0.01478 Total loss: 0.90569 timestamp: 1655051278.9533255 iteration: 54600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11284 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.18458 L1 loss: 0.0000e+00 L2 loss: 0.57822 Learning rate: 0.002 Mask loss: 0.13113 RPN box loss: 0.01261 RPN score loss: 0.00586 RPN total loss: 0.01847 Total loss: 0.91241 timestamp: 1655051282.2561703 iteration: 54605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06223 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.13045 L1 loss: 0.0000e+00 L2 loss: 0.57821 Learning rate: 0.002 Mask loss: 0.14125 RPN box loss: 0.01257 RPN score loss: 0.00472 RPN total loss: 0.01729 Total loss: 0.8672 timestamp: 1655051285.5481822 iteration: 54610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13435 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.22053 L1 loss: 0.0000e+00 L2 loss: 0.5782 Learning rate: 0.002 Mask loss: 0.13941 RPN box loss: 0.00877 RPN score loss: 0.00604 RPN total loss: 0.01481 Total loss: 0.95295 timestamp: 1655051288.8447433 iteration: 54615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08109 FastRCNN class loss: 0.08032 FastRCNN total loss: 0.16142 L1 loss: 0.0000e+00 L2 loss: 0.5782 Learning rate: 0.002 Mask loss: 0.1552 RPN box loss: 0.02244 RPN score loss: 0.00996 RPN total loss: 0.0324 Total loss: 0.92721 timestamp: 1655051292.0664215 iteration: 54620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1346 FastRCNN class loss: 0.09154 FastRCNN total loss: 0.22613 L1 loss: 0.0000e+00 L2 loss: 0.57819 Learning rate: 0.002 Mask loss: 0.14865 RPN box loss: 0.01152 RPN score loss: 0.00322 RPN total loss: 0.01474 Total loss: 0.96771 timestamp: 1655051295.3161569 iteration: 54625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14481 FastRCNN class loss: 0.12832 FastRCNN total loss: 0.27313 L1 loss: 0.0000e+00 L2 loss: 0.57818 Learning rate: 0.002 Mask loss: 0.14872 RPN box loss: 0.01474 RPN score loss: 0.00719 RPN total loss: 0.02193 Total loss: 1.02196 timestamp: 1655051298.5916348 iteration: 54630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14828 FastRCNN class loss: 0.08888 FastRCNN total loss: 0.23716 L1 loss: 0.0000e+00 L2 loss: 0.57817 Learning rate: 0.002 Mask loss: 0.19872 RPN box loss: 0.01805 RPN score loss: 0.00563 RPN total loss: 0.02367 Total loss: 1.03772 timestamp: 1655051301.91673 iteration: 54635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10181 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.16149 L1 loss: 0.0000e+00 L2 loss: 0.57816 Learning rate: 0.002 Mask loss: 0.16439 RPN box loss: 0.01649 RPN score loss: 0.00773 RPN total loss: 0.02421 Total loss: 0.92826 timestamp: 1655051305.2248209 iteration: 54640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07441 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.13367 L1 loss: 0.0000e+00 L2 loss: 0.57815 Learning rate: 0.002 Mask loss: 0.12655 RPN box loss: 0.0271 RPN score loss: 0.00422 RPN total loss: 0.03131 Total loss: 0.86969 timestamp: 1655051308.5579684 iteration: 54645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06298 FastRCNN class loss: 0.08692 FastRCNN total loss: 0.14991 L1 loss: 0.0000e+00 L2 loss: 0.57814 Learning rate: 0.002 Mask loss: 0.10749 RPN box loss: 0.00971 RPN score loss: 0.00251 RPN total loss: 0.01222 Total loss: 0.84775 timestamp: 1655051311.8254313 iteration: 54650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07073 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.13082 L1 loss: 0.0000e+00 L2 loss: 0.57813 Learning rate: 0.002 Mask loss: 0.11243 RPN box loss: 0.01873 RPN score loss: 0.00343 RPN total loss: 0.02216 Total loss: 0.84355 timestamp: 1655051315.0773818 iteration: 54655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07182 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.1162 L1 loss: 0.0000e+00 L2 loss: 0.57813 Learning rate: 0.002 Mask loss: 0.12752 RPN box loss: 0.01258 RPN score loss: 0.00152 RPN total loss: 0.0141 Total loss: 0.83595 timestamp: 1655051318.3813424 iteration: 54660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11742 FastRCNN class loss: 0.09826 FastRCNN total loss: 0.21568 L1 loss: 0.0000e+00 L2 loss: 0.57812 Learning rate: 0.002 Mask loss: 0.10921 RPN box loss: 0.01952 RPN score loss: 0.00446 RPN total loss: 0.02398 Total loss: 0.92699 timestamp: 1655051321.6451461 iteration: 54665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1384 FastRCNN class loss: 0.14912 FastRCNN total loss: 0.28752 L1 loss: 0.0000e+00 L2 loss: 0.57811 Learning rate: 0.002 Mask loss: 0.17247 RPN box loss: 0.0268 RPN score loss: 0.00676 RPN total loss: 0.03356 Total loss: 1.07166 timestamp: 1655051324.985858 iteration: 54670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05024 FastRCNN class loss: 0.02945 FastRCNN total loss: 0.07969 L1 loss: 0.0000e+00 L2 loss: 0.5781 Learning rate: 0.002 Mask loss: 0.09012 RPN box loss: 0.0032 RPN score loss: 0.00444 RPN total loss: 0.00764 Total loss: 0.75555 timestamp: 1655051328.2439053 iteration: 54675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.17757 L1 loss: 0.0000e+00 L2 loss: 0.57809 Learning rate: 0.002 Mask loss: 0.13851 RPN box loss: 0.01508 RPN score loss: 0.00757 RPN total loss: 0.02265 Total loss: 0.91682 timestamp: 1655051331.4527912 iteration: 54680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21348 FastRCNN class loss: 0.10017 FastRCNN total loss: 0.31364 L1 loss: 0.0000e+00 L2 loss: 0.57808 Learning rate: 0.002 Mask loss: 0.17064 RPN box loss: 0.03197 RPN score loss: 0.01188 RPN total loss: 0.04385 Total loss: 1.10622 timestamp: 1655051334.7412245 iteration: 54685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13176 FastRCNN class loss: 0.08513 FastRCNN total loss: 0.21688 L1 loss: 0.0000e+00 L2 loss: 0.57807 Learning rate: 0.002 Mask loss: 0.18929 RPN box loss: 0.02337 RPN score loss: 0.00907 RPN total loss: 0.03244 Total loss: 1.01668 timestamp: 1655051338.0382066 iteration: 54690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05124 FastRCNN class loss: 0.05972 FastRCNN total loss: 0.11095 L1 loss: 0.0000e+00 L2 loss: 0.57807 Learning rate: 0.002 Mask loss: 0.12802 RPN box loss: 0.00931 RPN score loss: 0.00552 RPN total loss: 0.01483 Total loss: 0.83187 timestamp: 1655051341.3754208 iteration: 54695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10494 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.19933 L1 loss: 0.0000e+00 L2 loss: 0.57806 Learning rate: 0.002 Mask loss: 0.12882 RPN box loss: 0.01306 RPN score loss: 0.00418 RPN total loss: 0.01725 Total loss: 0.92345 timestamp: 1655051344.6959252 iteration: 54700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16033 FastRCNN class loss: 0.10451 FastRCNN total loss: 0.26485 L1 loss: 0.0000e+00 L2 loss: 0.57805 Learning rate: 0.002 Mask loss: 0.18826 RPN box loss: 0.02838 RPN score loss: 0.01725 RPN total loss: 0.04563 Total loss: 1.07679 timestamp: 1655051347.9692953 iteration: 54705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05394 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.0934 L1 loss: 0.0000e+00 L2 loss: 0.57805 Learning rate: 0.002 Mask loss: 0.11212 RPN box loss: 0.0088 RPN score loss: 0.00126 RPN total loss: 0.01005 Total loss: 0.79362 timestamp: 1655051351.2053304 iteration: 54710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.08471 FastRCNN total loss: 0.1847 L1 loss: 0.0000e+00 L2 loss: 0.57804 Learning rate: 0.002 Mask loss: 0.14452 RPN box loss: 0.03695 RPN score loss: 0.01302 RPN total loss: 0.04997 Total loss: 0.95723 timestamp: 1655051354.5351145 iteration: 54715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07786 FastRCNN class loss: 0.04129 FastRCNN total loss: 0.11916 L1 loss: 0.0000e+00 L2 loss: 0.57803 Learning rate: 0.002 Mask loss: 0.13774 RPN box loss: 0.02419 RPN score loss: 0.00134 RPN total loss: 0.02553 Total loss: 0.86045 timestamp: 1655051357.8424273 iteration: 54720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08058 FastRCNN class loss: 0.06366 FastRCNN total loss: 0.14423 L1 loss: 0.0000e+00 L2 loss: 0.57802 Learning rate: 0.002 Mask loss: 0.12433 RPN box loss: 0.03044 RPN score loss: 0.00552 RPN total loss: 0.03596 Total loss: 0.88254 timestamp: 1655051361.1463087 iteration: 54725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14785 FastRCNN class loss: 0.08583 FastRCNN total loss: 0.23368 L1 loss: 0.0000e+00 L2 loss: 0.57801 Learning rate: 0.002 Mask loss: 0.14625 RPN box loss: 0.02475 RPN score loss: 0.00254 RPN total loss: 0.02729 Total loss: 0.98523 timestamp: 1655051364.4097152 iteration: 54730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.12287 FastRCNN total loss: 0.24967 L1 loss: 0.0000e+00 L2 loss: 0.578 Learning rate: 0.002 Mask loss: 0.17278 RPN box loss: 0.0157 RPN score loss: 0.01544 RPN total loss: 0.03115 Total loss: 1.0316 timestamp: 1655051367.6752439 iteration: 54735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.04371 FastRCNN total loss: 0.11394 L1 loss: 0.0000e+00 L2 loss: 0.57799 Learning rate: 0.002 Mask loss: 0.15715 RPN box loss: 0.00851 RPN score loss: 0.00234 RPN total loss: 0.01085 Total loss: 0.85993 timestamp: 1655051370.882678 iteration: 54740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15251 FastRCNN class loss: 0.09253 FastRCNN total loss: 0.24505 L1 loss: 0.0000e+00 L2 loss: 0.57799 Learning rate: 0.002 Mask loss: 0.13521 RPN box loss: 0.01912 RPN score loss: 0.00274 RPN total loss: 0.02186 Total loss: 0.9801 timestamp: 1655051374.078058 iteration: 54745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07964 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.15076 L1 loss: 0.0000e+00 L2 loss: 0.57798 Learning rate: 0.002 Mask loss: 0.13957 RPN box loss: 0.02059 RPN score loss: 0.00105 RPN total loss: 0.02164 Total loss: 0.88995 timestamp: 1655051377.366603 iteration: 54750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12465 FastRCNN class loss: 0.0735 FastRCNN total loss: 0.19815 L1 loss: 0.0000e+00 L2 loss: 0.57797 Learning rate: 0.002 Mask loss: 0.11112 RPN box loss: 0.03129 RPN score loss: 0.01025 RPN total loss: 0.04155 Total loss: 0.92878 timestamp: 1655051380.6496632 iteration: 54755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06946 FastRCNN class loss: 0.0787 FastRCNN total loss: 0.14816 L1 loss: 0.0000e+00 L2 loss: 0.57796 Learning rate: 0.002 Mask loss: 0.17296 RPN box loss: 0.0164 RPN score loss: 0.01654 RPN total loss: 0.03294 Total loss: 0.93201 timestamp: 1655051383.9206843 iteration: 54760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09692 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.16575 L1 loss: 0.0000e+00 L2 loss: 0.57794 Learning rate: 0.002 Mask loss: 0.19512 RPN box loss: 0.02207 RPN score loss: 0.00406 RPN total loss: 0.02613 Total loss: 0.96495 timestamp: 1655051387.1695685 iteration: 54765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05883 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.11168 L1 loss: 0.0000e+00 L2 loss: 0.57794 Learning rate: 0.002 Mask loss: 0.10153 RPN box loss: 0.0075 RPN score loss: 0.00465 RPN total loss: 0.01216 Total loss: 0.80331 timestamp: 1655051390.4787073 iteration: 54770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11956 FastRCNN class loss: 0.14098 FastRCNN total loss: 0.26054 L1 loss: 0.0000e+00 L2 loss: 0.57793 Learning rate: 0.002 Mask loss: 0.20907 RPN box loss: 0.01587 RPN score loss: 0.00913 RPN total loss: 0.025 Total loss: 1.07254 timestamp: 1655051393.7650707 iteration: 54775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.05618 FastRCNN total loss: 0.15593 L1 loss: 0.0000e+00 L2 loss: 0.57792 Learning rate: 0.002 Mask loss: 0.25606 RPN box loss: 0.04295 RPN score loss: 0.00798 RPN total loss: 0.05094 Total loss: 1.04086 timestamp: 1655051397.0667233 iteration: 54780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06399 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.13596 L1 loss: 0.0000e+00 L2 loss: 0.57792 Learning rate: 0.002 Mask loss: 0.13388 RPN box loss: 0.01064 RPN score loss: 0.00525 RPN total loss: 0.01589 Total loss: 0.86365 timestamp: 1655051400.3491278 iteration: 54785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09667 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.16086 L1 loss: 0.0000e+00 L2 loss: 0.57791 Learning rate: 0.002 Mask loss: 0.14232 RPN box loss: 0.02266 RPN score loss: 0.01046 RPN total loss: 0.03312 Total loss: 0.91421 timestamp: 1655051403.6096087 iteration: 54790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07725 FastRCNN class loss: 0.04954 FastRCNN total loss: 0.12678 L1 loss: 0.0000e+00 L2 loss: 0.5779 Learning rate: 0.002 Mask loss: 0.14348 RPN box loss: 0.01136 RPN score loss: 0.0026 RPN total loss: 0.01396 Total loss: 0.86213 timestamp: 1655051406.7998843 iteration: 54795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07236 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.13873 L1 loss: 0.0000e+00 L2 loss: 0.57789 Learning rate: 0.002 Mask loss: 0.18992 RPN box loss: 0.01478 RPN score loss: 0.0042 RPN total loss: 0.01898 Total loss: 0.92552 timestamp: 1655051410.0847416 iteration: 54800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15175 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.22296 L1 loss: 0.0000e+00 L2 loss: 0.57788 Learning rate: 0.002 Mask loss: 0.1605 RPN box loss: 0.02061 RPN score loss: 0.00662 RPN total loss: 0.02722 Total loss: 0.98856 timestamp: 1655051413.4082973 iteration: 54805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09089 FastRCNN class loss: 0.08117 FastRCNN total loss: 0.17205 L1 loss: 0.0000e+00 L2 loss: 0.57788 Learning rate: 0.002 Mask loss: 0.14425 RPN box loss: 0.02418 RPN score loss: 0.00479 RPN total loss: 0.02897 Total loss: 0.92315 timestamp: 1655051416.7368681 iteration: 54810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17623 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.25067 L1 loss: 0.0000e+00 L2 loss: 0.57787 Learning rate: 0.002 Mask loss: 0.13194 RPN box loss: 0.00638 RPN score loss: 0.00157 RPN total loss: 0.00795 Total loss: 0.96843 timestamp: 1655051419.9813192 iteration: 54815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05939 FastRCNN class loss: 0.0595 FastRCNN total loss: 0.11889 L1 loss: 0.0000e+00 L2 loss: 0.57786 Learning rate: 0.002 Mask loss: 0.1349 RPN box loss: 0.01671 RPN score loss: 0.00516 RPN total loss: 0.02187 Total loss: 0.85351 timestamp: 1655051423.292105 iteration: 54820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05911 FastRCNN class loss: 0.04435 FastRCNN total loss: 0.10346 L1 loss: 0.0000e+00 L2 loss: 0.57785 Learning rate: 0.002 Mask loss: 0.10131 RPN box loss: 0.01521 RPN score loss: 0.00529 RPN total loss: 0.02051 Total loss: 0.80314 timestamp: 1655051426.6051064 iteration: 54825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13482 FastRCNN class loss: 0.09385 FastRCNN total loss: 0.22867 L1 loss: 0.0000e+00 L2 loss: 0.57784 Learning rate: 0.002 Mask loss: 0.21587 RPN box loss: 0.02004 RPN score loss: 0.01089 RPN total loss: 0.03092 Total loss: 1.0533 timestamp: 1655051429.856511 iteration: 54830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.04925 FastRCNN total loss: 0.17658 L1 loss: 0.0000e+00 L2 loss: 0.57783 Learning rate: 0.002 Mask loss: 0.12406 RPN box loss: 0.01173 RPN score loss: 0.00421 RPN total loss: 0.01593 Total loss: 0.89441 timestamp: 1655051433.1467433 iteration: 54835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11307 FastRCNN class loss: 0.08568 FastRCNN total loss: 0.19875 L1 loss: 0.0000e+00 L2 loss: 0.57782 Learning rate: 0.002 Mask loss: 0.15386 RPN box loss: 0.02943 RPN score loss: 0.00767 RPN total loss: 0.03709 Total loss: 0.96752 timestamp: 1655051436.3769264 iteration: 54840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06647 FastRCNN class loss: 0.04188 FastRCNN total loss: 0.10835 L1 loss: 0.0000e+00 L2 loss: 0.57782 Learning rate: 0.002 Mask loss: 0.10856 RPN box loss: 0.02192 RPN score loss: 0.00427 RPN total loss: 0.02618 Total loss: 0.82091 timestamp: 1655051439.6539476 iteration: 54845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08034 FastRCNN class loss: 0.03792 FastRCNN total loss: 0.11826 L1 loss: 0.0000e+00 L2 loss: 0.57781 Learning rate: 0.002 Mask loss: 0.12006 RPN box loss: 0.00438 RPN score loss: 0.00251 RPN total loss: 0.00689 Total loss: 0.82301 timestamp: 1655051442.893627 iteration: 54850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.07437 FastRCNN total loss: 0.15579 L1 loss: 0.0000e+00 L2 loss: 0.5778 Learning rate: 0.002 Mask loss: 0.11924 RPN box loss: 0.00689 RPN score loss: 0.00804 RPN total loss: 0.01493 Total loss: 0.86777 timestamp: 1655051446.1651788 iteration: 54855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11768 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.19874 L1 loss: 0.0000e+00 L2 loss: 0.57779 Learning rate: 0.002 Mask loss: 0.19087 RPN box loss: 0.01551 RPN score loss: 0.00563 RPN total loss: 0.02114 Total loss: 0.98854 timestamp: 1655051449.4347794 iteration: 54860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.08504 FastRCNN total loss: 0.20753 L1 loss: 0.0000e+00 L2 loss: 0.57778 Learning rate: 0.002 Mask loss: 0.13529 RPN box loss: 0.01691 RPN score loss: 0.00774 RPN total loss: 0.02465 Total loss: 0.94525 timestamp: 1655051452.6812856 iteration: 54865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1353 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.20891 L1 loss: 0.0000e+00 L2 loss: 0.57777 Learning rate: 0.002 Mask loss: 0.17479 RPN box loss: 0.0101 RPN score loss: 0.01297 RPN total loss: 0.02307 Total loss: 0.98455 timestamp: 1655051455.9826562 iteration: 54870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08712 FastRCNN class loss: 0.061 FastRCNN total loss: 0.14812 L1 loss: 0.0000e+00 L2 loss: 0.57776 Learning rate: 0.002 Mask loss: 0.11189 RPN box loss: 0.01316 RPN score loss: 0.00552 RPN total loss: 0.01868 Total loss: 0.85645 timestamp: 1655051459.2405074 iteration: 54875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08844 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.1681 L1 loss: 0.0000e+00 L2 loss: 0.57776 Learning rate: 0.002 Mask loss: 0.16508 RPN box loss: 0.02201 RPN score loss: 0.0041 RPN total loss: 0.02611 Total loss: 0.93704 timestamp: 1655051462.5452628 iteration: 54880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10646 FastRCNN class loss: 0.09302 FastRCNN total loss: 0.19949 L1 loss: 0.0000e+00 L2 loss: 0.57775 Learning rate: 0.002 Mask loss: 0.19688 RPN box loss: 0.01485 RPN score loss: 0.00646 RPN total loss: 0.02131 Total loss: 0.99543 timestamp: 1655051465.7596774 iteration: 54885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11613 FastRCNN class loss: 0.08256 FastRCNN total loss: 0.19869 L1 loss: 0.0000e+00 L2 loss: 0.57774 Learning rate: 0.002 Mask loss: 0.11596 RPN box loss: 0.03312 RPN score loss: 0.00309 RPN total loss: 0.03621 Total loss: 0.9286 timestamp: 1655051468.9959836 iteration: 54890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09693 FastRCNN class loss: 0.04874 FastRCNN total loss: 0.14567 L1 loss: 0.0000e+00 L2 loss: 0.57773 Learning rate: 0.002 Mask loss: 0.07549 RPN box loss: 0.00382 RPN score loss: 0.00247 RPN total loss: 0.00629 Total loss: 0.80518 timestamp: 1655051472.2763987 iteration: 54895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09257 FastRCNN class loss: 0.05618 FastRCNN total loss: 0.14875 L1 loss: 0.0000e+00 L2 loss: 0.57772 Learning rate: 0.002 Mask loss: 0.13912 RPN box loss: 0.00667 RPN score loss: 0.00495 RPN total loss: 0.01162 Total loss: 0.8772 timestamp: 1655051475.480623 iteration: 54900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15248 FastRCNN class loss: 0.07581 FastRCNN total loss: 0.22829 L1 loss: 0.0000e+00 L2 loss: 0.57771 Learning rate: 0.002 Mask loss: 0.14018 RPN box loss: 0.00682 RPN score loss: 0.00684 RPN total loss: 0.01367 Total loss: 0.95985 timestamp: 1655051478.7675617 iteration: 54905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.07266 FastRCNN total loss: 0.16724 L1 loss: 0.0000e+00 L2 loss: 0.5777 Learning rate: 0.002 Mask loss: 0.14709 RPN box loss: 0.06524 RPN score loss: 0.00619 RPN total loss: 0.07143 Total loss: 0.96345 timestamp: 1655051482.1022747 iteration: 54910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11666 FastRCNN class loss: 0.04968 FastRCNN total loss: 0.16634 L1 loss: 0.0000e+00 L2 loss: 0.57769 Learning rate: 0.002 Mask loss: 0.1071 RPN box loss: 0.01553 RPN score loss: 0.00222 RPN total loss: 0.01775 Total loss: 0.86888 timestamp: 1655051485.3347275 iteration: 54915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09037 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.16972 L1 loss: 0.0000e+00 L2 loss: 0.57768 Learning rate: 0.002 Mask loss: 0.1726 RPN box loss: 0.021 RPN score loss: 0.00932 RPN total loss: 0.03032 Total loss: 0.95032 timestamp: 1655051488.6275485 iteration: 54920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06074 FastRCNN class loss: 0.03409 FastRCNN total loss: 0.09484 L1 loss: 0.0000e+00 L2 loss: 0.57768 Learning rate: 0.002 Mask loss: 0.11667 RPN box loss: 0.00574 RPN score loss: 0.00172 RPN total loss: 0.00746 Total loss: 0.79664 timestamp: 1655051491.869564 iteration: 54925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1078 FastRCNN class loss: 0.04826 FastRCNN total loss: 0.15606 L1 loss: 0.0000e+00 L2 loss: 0.57767 Learning rate: 0.002 Mask loss: 0.09904 RPN box loss: 0.00984 RPN score loss: 0.00364 RPN total loss: 0.01348 Total loss: 0.84625 timestamp: 1655051495.0993009 iteration: 54930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.06038 FastRCNN total loss: 0.14499 L1 loss: 0.0000e+00 L2 loss: 0.57766 Learning rate: 0.002 Mask loss: 0.13024 RPN box loss: 0.03739 RPN score loss: 0.0073 RPN total loss: 0.04469 Total loss: 0.89758 timestamp: 1655051498.353945 iteration: 54935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06596 FastRCNN class loss: 0.05377 FastRCNN total loss: 0.11972 L1 loss: 0.0000e+00 L2 loss: 0.57765 Learning rate: 0.002 Mask loss: 0.14011 RPN box loss: 0.02129 RPN score loss: 0.00748 RPN total loss: 0.02877 Total loss: 0.86626 timestamp: 1655051501.638866 iteration: 54940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11905 FastRCNN class loss: 0.04141 FastRCNN total loss: 0.16046 L1 loss: 0.0000e+00 L2 loss: 0.57764 Learning rate: 0.002 Mask loss: 0.1563 RPN box loss: 0.01043 RPN score loss: 0.00416 RPN total loss: 0.0146 Total loss: 0.909 timestamp: 1655051504.920273 iteration: 54945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08354 FastRCNN class loss: 0.08457 FastRCNN total loss: 0.16811 L1 loss: 0.0000e+00 L2 loss: 0.57763 Learning rate: 0.002 Mask loss: 0.14967 RPN box loss: 0.02421 RPN score loss: 0.0089 RPN total loss: 0.03311 Total loss: 0.92854 timestamp: 1655051508.2075365 iteration: 54950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15564 FastRCNN class loss: 0.17583 FastRCNN total loss: 0.33147 L1 loss: 0.0000e+00 L2 loss: 0.57763 Learning rate: 0.002 Mask loss: 0.23375 RPN box loss: 0.04429 RPN score loss: 0.01192 RPN total loss: 0.05621 Total loss: 1.19905 timestamp: 1655051511.526375 iteration: 54955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17014 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.23197 L1 loss: 0.0000e+00 L2 loss: 0.57762 Learning rate: 0.002 Mask loss: 0.14391 RPN box loss: 0.00414 RPN score loss: 0.00475 RPN total loss: 0.00889 Total loss: 0.96239 timestamp: 1655051514.7925146 iteration: 54960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05122 FastRCNN class loss: 0.05436 FastRCNN total loss: 0.10558 L1 loss: 0.0000e+00 L2 loss: 0.57761 Learning rate: 0.002 Mask loss: 0.14466 RPN box loss: 0.00867 RPN score loss: 0.00368 RPN total loss: 0.01235 Total loss: 0.8402 timestamp: 1655051518.093067 iteration: 54965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07448 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.12242 L1 loss: 0.0000e+00 L2 loss: 0.5776 Learning rate: 0.002 Mask loss: 0.19315 RPN box loss: 0.00915 RPN score loss: 0.00135 RPN total loss: 0.0105 Total loss: 0.90367 timestamp: 1655051521.3748403 iteration: 54970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12264 FastRCNN class loss: 0.10122 FastRCNN total loss: 0.22386 L1 loss: 0.0000e+00 L2 loss: 0.57759 Learning rate: 0.002 Mask loss: 0.13003 RPN box loss: 0.01005 RPN score loss: 0.0047 RPN total loss: 0.01475 Total loss: 0.94623 timestamp: 1655051524.6845217 iteration: 54975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10343 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.17563 L1 loss: 0.0000e+00 L2 loss: 0.57758 Learning rate: 0.002 Mask loss: 0.16876 RPN box loss: 0.0142 RPN score loss: 0.00908 RPN total loss: 0.02327 Total loss: 0.94526 timestamp: 1655051527.9748423 iteration: 54980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09025 FastRCNN class loss: 0.09781 FastRCNN total loss: 0.18806 L1 loss: 0.0000e+00 L2 loss: 0.57758 Learning rate: 0.002 Mask loss: 0.18256 RPN box loss: 0.01199 RPN score loss: 0.00765 RPN total loss: 0.01964 Total loss: 0.96784 timestamp: 1655051531.2761517 iteration: 54985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1128 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.19094 L1 loss: 0.0000e+00 L2 loss: 0.57757 Learning rate: 0.002 Mask loss: 0.1437 RPN box loss: 0.02405 RPN score loss: 0.00545 RPN total loss: 0.0295 Total loss: 0.94171 timestamp: 1655051534.5746293 iteration: 54990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13342 FastRCNN class loss: 0.08963 FastRCNN total loss: 0.22305 L1 loss: 0.0000e+00 L2 loss: 0.57756 Learning rate: 0.002 Mask loss: 0.14551 RPN box loss: 0.02637 RPN score loss: 0.00632 RPN total loss: 0.03268 Total loss: 0.9788 timestamp: 1655051537.8690925 iteration: 54995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09886 FastRCNN class loss: 0.09453 FastRCNN total loss: 0.19339 L1 loss: 0.0000e+00 L2 loss: 0.57755 Learning rate: 0.002 Mask loss: 0.2007 RPN box loss: 0.00895 RPN score loss: 0.00222 RPN total loss: 0.01118 Total loss: 0.98281 timestamp: 1655051541.1706407 iteration: 55000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.0794 FastRCNN total loss: 0.18 L1 loss: 0.0000e+00 L2 loss: 0.57754 Learning rate: 0.002 Mask loss: 0.17316 RPN box loss: 0.01686 RPN score loss: 0.00383 RPN total loss: 0.02069 Total loss: 0.9514 timestamp: 1655051544.4048374 iteration: 55005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11401 FastRCNN class loss: 0.11281 FastRCNN total loss: 0.22682 L1 loss: 0.0000e+00 L2 loss: 0.57753 Learning rate: 0.002 Mask loss: 0.16582 RPN box loss: 0.01499 RPN score loss: 0.03025 RPN total loss: 0.04525 Total loss: 1.01542 timestamp: 1655051547.6042683 iteration: 55010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09474 FastRCNN class loss: 0.06353 FastRCNN total loss: 0.15827 L1 loss: 0.0000e+00 L2 loss: 0.57752 Learning rate: 0.002 Mask loss: 0.16226 RPN box loss: 0.0194 RPN score loss: 0.00393 RPN total loss: 0.02334 Total loss: 0.92139 timestamp: 1655051550.9140434 iteration: 55015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09871 FastRCNN class loss: 0.0888 FastRCNN total loss: 0.18751 L1 loss: 0.0000e+00 L2 loss: 0.57751 Learning rate: 0.002 Mask loss: 0.19724 RPN box loss: 0.07426 RPN score loss: 0.01268 RPN total loss: 0.08694 Total loss: 1.0492 timestamp: 1655051554.1581414 iteration: 55020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0597 FastRCNN class loss: 0.05177 FastRCNN total loss: 0.11147 L1 loss: 0.0000e+00 L2 loss: 0.57751 Learning rate: 0.002 Mask loss: 0.08098 RPN box loss: 0.00576 RPN score loss: 0.00135 RPN total loss: 0.00712 Total loss: 0.77708 timestamp: 1655051557.518146 iteration: 55025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14202 FastRCNN class loss: 0.12117 FastRCNN total loss: 0.26319 L1 loss: 0.0000e+00 L2 loss: 0.5775 Learning rate: 0.002 Mask loss: 0.20831 RPN box loss: 0.02324 RPN score loss: 0.01647 RPN total loss: 0.03971 Total loss: 1.08871 timestamp: 1655051560.7821093 iteration: 55030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10293 FastRCNN class loss: 0.05412 FastRCNN total loss: 0.15705 L1 loss: 0.0000e+00 L2 loss: 0.5775 Learning rate: 0.002 Mask loss: 0.12858 RPN box loss: 0.00513 RPN score loss: 0.00632 RPN total loss: 0.01145 Total loss: 0.87457 timestamp: 1655051564.0205703 iteration: 55035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09889 FastRCNN class loss: 0.05433 FastRCNN total loss: 0.15322 L1 loss: 0.0000e+00 L2 loss: 0.57749 Learning rate: 0.002 Mask loss: 0.13415 RPN box loss: 0.01169 RPN score loss: 0.00476 RPN total loss: 0.01645 Total loss: 0.8813 timestamp: 1655051567.2496533 iteration: 55040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11429 FastRCNN class loss: 0.10211 FastRCNN total loss: 0.2164 L1 loss: 0.0000e+00 L2 loss: 0.57748 Learning rate: 0.002 Mask loss: 0.19806 RPN box loss: 0.02181 RPN score loss: 0.01521 RPN total loss: 0.03702 Total loss: 1.02895 timestamp: 1655051570.4813764 iteration: 55045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06002 FastRCNN class loss: 0.04299 FastRCNN total loss: 0.10301 L1 loss: 0.0000e+00 L2 loss: 0.57747 Learning rate: 0.002 Mask loss: 0.07217 RPN box loss: 0.01534 RPN score loss: 0.00163 RPN total loss: 0.01697 Total loss: 0.76963 timestamp: 1655051573.756844 iteration: 55050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06203 FastRCNN class loss: 0.05108 FastRCNN total loss: 0.11311 L1 loss: 0.0000e+00 L2 loss: 0.57746 Learning rate: 0.002 Mask loss: 0.14533 RPN box loss: 0.00782 RPN score loss: 0.00146 RPN total loss: 0.00928 Total loss: 0.84518 timestamp: 1655051577.0650134 iteration: 55055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11077 FastRCNN class loss: 0.07625 FastRCNN total loss: 0.18702 L1 loss: 0.0000e+00 L2 loss: 0.57745 Learning rate: 0.002 Mask loss: 0.12118 RPN box loss: 0.00874 RPN score loss: 0.00502 RPN total loss: 0.01377 Total loss: 0.89941 timestamp: 1655051580.2673118 iteration: 55060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11707 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.20722 L1 loss: 0.0000e+00 L2 loss: 0.57744 Learning rate: 0.002 Mask loss: 0.12934 RPN box loss: 0.01332 RPN score loss: 0.0103 RPN total loss: 0.02361 Total loss: 0.9376 timestamp: 1655051583.5516798 iteration: 55065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11515 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.17374 L1 loss: 0.0000e+00 L2 loss: 0.57743 Learning rate: 0.002 Mask loss: 0.14476 RPN box loss: 0.03539 RPN score loss: 0.01471 RPN total loss: 0.0501 Total loss: 0.94603 timestamp: 1655051586.777211 iteration: 55070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11614 FastRCNN class loss: 0.09231 FastRCNN total loss: 0.20845 L1 loss: 0.0000e+00 L2 loss: 0.57742 Learning rate: 0.002 Mask loss: 0.13076 RPN box loss: 0.03788 RPN score loss: 0.00743 RPN total loss: 0.04532 Total loss: 0.96195 timestamp: 1655051590.019435 iteration: 55075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09308 FastRCNN class loss: 0.09228 FastRCNN total loss: 0.18536 L1 loss: 0.0000e+00 L2 loss: 0.57742 Learning rate: 0.002 Mask loss: 0.12783 RPN box loss: 0.01309 RPN score loss: 0.00172 RPN total loss: 0.01481 Total loss: 0.90542 timestamp: 1655051593.3601267 iteration: 55080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12515 FastRCNN class loss: 0.0732 FastRCNN total loss: 0.19835 L1 loss: 0.0000e+00 L2 loss: 0.57741 Learning rate: 0.002 Mask loss: 0.13716 RPN box loss: 0.00998 RPN score loss: 0.00354 RPN total loss: 0.01352 Total loss: 0.92645 timestamp: 1655051596.651791 iteration: 55085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07288 FastRCNN class loss: 0.09246 FastRCNN total loss: 0.16533 L1 loss: 0.0000e+00 L2 loss: 0.5774 Learning rate: 0.002 Mask loss: 0.14148 RPN box loss: 0.01568 RPN score loss: 0.00811 RPN total loss: 0.02379 Total loss: 0.908 timestamp: 1655051599.9969616 iteration: 55090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08827 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.15098 L1 loss: 0.0000e+00 L2 loss: 0.57739 Learning rate: 0.002 Mask loss: 0.18809 RPN box loss: 0.01082 RPN score loss: 0.00096 RPN total loss: 0.01179 Total loss: 0.92824 timestamp: 1655051603.2839835 iteration: 55095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11301 FastRCNN class loss: 0.08211 FastRCNN total loss: 0.19512 L1 loss: 0.0000e+00 L2 loss: 0.57738 Learning rate: 0.002 Mask loss: 0.14506 RPN box loss: 0.02526 RPN score loss: 0.00953 RPN total loss: 0.03479 Total loss: 0.95235 timestamp: 1655051606.5308416 iteration: 55100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09417 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.14633 L1 loss: 0.0000e+00 L2 loss: 0.57737 Learning rate: 0.002 Mask loss: 0.08749 RPN box loss: 0.01284 RPN score loss: 0.01059 RPN total loss: 0.02344 Total loss: 0.83463 timestamp: 1655051609.7986295 iteration: 55105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08228 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.12982 L1 loss: 0.0000e+00 L2 loss: 0.57737 Learning rate: 0.002 Mask loss: 0.10072 RPN box loss: 0.00767 RPN score loss: 0.00195 RPN total loss: 0.00962 Total loss: 0.81753 timestamp: 1655051613.09763 iteration: 55110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11158 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.18623 L1 loss: 0.0000e+00 L2 loss: 0.57736 Learning rate: 0.002 Mask loss: 0.16285 RPN box loss: 0.02093 RPN score loss: 0.00774 RPN total loss: 0.02867 Total loss: 0.95511 timestamp: 1655051616.285835 iteration: 55115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1319 FastRCNN class loss: 0.10307 FastRCNN total loss: 0.23497 L1 loss: 0.0000e+00 L2 loss: 0.57735 Learning rate: 0.002 Mask loss: 0.16467 RPN box loss: 0.02034 RPN score loss: 0.00254 RPN total loss: 0.02288 Total loss: 0.99987 timestamp: 1655051619.520624 iteration: 55120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12334 FastRCNN class loss: 0.06516 FastRCNN total loss: 0.1885 L1 loss: 0.0000e+00 L2 loss: 0.57734 Learning rate: 0.002 Mask loss: 0.18843 RPN box loss: 0.00536 RPN score loss: 0.00151 RPN total loss: 0.00687 Total loss: 0.96114 timestamp: 1655051622.8034103 iteration: 55125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05144 FastRCNN class loss: 0.05048 FastRCNN total loss: 0.10192 L1 loss: 0.0000e+00 L2 loss: 0.57734 Learning rate: 0.002 Mask loss: 0.11868 RPN box loss: 0.00856 RPN score loss: 0.00251 RPN total loss: 0.01107 Total loss: 0.80901 timestamp: 1655051626.0866897 iteration: 55130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07284 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.14268 L1 loss: 0.0000e+00 L2 loss: 0.57733 Learning rate: 0.002 Mask loss: 0.13398 RPN box loss: 0.01113 RPN score loss: 0.00584 RPN total loss: 0.01697 Total loss: 0.87096 timestamp: 1655051629.3900747 iteration: 55135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05912 FastRCNN class loss: 0.06955 FastRCNN total loss: 0.12867 L1 loss: 0.0000e+00 L2 loss: 0.57732 Learning rate: 0.002 Mask loss: 0.14276 RPN box loss: 0.0099 RPN score loss: 0.00611 RPN total loss: 0.01601 Total loss: 0.86476 timestamp: 1655051632.6171036 iteration: 55140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10825 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.1634 L1 loss: 0.0000e+00 L2 loss: 0.57731 Learning rate: 0.002 Mask loss: 0.10239 RPN box loss: 0.00555 RPN score loss: 0.00137 RPN total loss: 0.00693 Total loss: 0.85002 timestamp: 1655051635.8584778 iteration: 55145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06892 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.13925 L1 loss: 0.0000e+00 L2 loss: 0.5773 Learning rate: 0.002 Mask loss: 0.13313 RPN box loss: 0.02503 RPN score loss: 0.00295 RPN total loss: 0.02798 Total loss: 0.87767 timestamp: 1655051639.1587355 iteration: 55150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0847 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.16215 L1 loss: 0.0000e+00 L2 loss: 0.5773 Learning rate: 0.002 Mask loss: 0.18293 RPN box loss: 0.01549 RPN score loss: 0.00324 RPN total loss: 0.01872 Total loss: 0.9411 timestamp: 1655051642.3876803 iteration: 55155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09907 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.15554 L1 loss: 0.0000e+00 L2 loss: 0.57729 Learning rate: 0.002 Mask loss: 0.09015 RPN box loss: 0.00825 RPN score loss: 0.00332 RPN total loss: 0.01156 Total loss: 0.83454 timestamp: 1655051645.69418 iteration: 55160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.0826 FastRCNN total loss: 0.20746 L1 loss: 0.0000e+00 L2 loss: 0.57728 Learning rate: 0.002 Mask loss: 0.10688 RPN box loss: 0.02037 RPN score loss: 0.00271 RPN total loss: 0.02308 Total loss: 0.9147 timestamp: 1655051648.9034476 iteration: 55165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10217 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.1595 L1 loss: 0.0000e+00 L2 loss: 0.57727 Learning rate: 0.002 Mask loss: 0.13278 RPN box loss: 0.0055 RPN score loss: 0.00482 RPN total loss: 0.01031 Total loss: 0.87986 timestamp: 1655051652.1735308 iteration: 55170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13008 FastRCNN class loss: 0.11648 FastRCNN total loss: 0.24656 L1 loss: 0.0000e+00 L2 loss: 0.57726 Learning rate: 0.002 Mask loss: 0.2169 RPN box loss: 0.01693 RPN score loss: 0.00699 RPN total loss: 0.02393 Total loss: 1.06465 timestamp: 1655051655.4653459 iteration: 55175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11494 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.57725 Learning rate: 0.002 Mask loss: 0.11132 RPN box loss: 0.02543 RPN score loss: 0.00521 RPN total loss: 0.03064 Total loss: 0.90044 timestamp: 1655051658.7320664 iteration: 55180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12238 FastRCNN class loss: 0.13378 FastRCNN total loss: 0.25616 L1 loss: 0.0000e+00 L2 loss: 0.57724 Learning rate: 0.002 Mask loss: 0.19365 RPN box loss: 0.01017 RPN score loss: 0.00645 RPN total loss: 0.01661 Total loss: 1.04367 timestamp: 1655051661.9371574 iteration: 55185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10658 FastRCNN class loss: 0.06388 FastRCNN total loss: 0.17046 L1 loss: 0.0000e+00 L2 loss: 0.57723 Learning rate: 0.002 Mask loss: 0.17686 RPN box loss: 0.00567 RPN score loss: 0.00531 RPN total loss: 0.01098 Total loss: 0.93554 timestamp: 1655051665.1957867 iteration: 55190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09099 FastRCNN class loss: 0.06003 FastRCNN total loss: 0.15102 L1 loss: 0.0000e+00 L2 loss: 0.57723 Learning rate: 0.002 Mask loss: 0.16686 RPN box loss: 0.01204 RPN score loss: 0.00238 RPN total loss: 0.01442 Total loss: 0.90953 timestamp: 1655051668.3790355 iteration: 55195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1281 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.20809 L1 loss: 0.0000e+00 L2 loss: 0.57722 Learning rate: 0.002 Mask loss: 0.12151 RPN box loss: 0.04683 RPN score loss: 0.00429 RPN total loss: 0.05112 Total loss: 0.95794 timestamp: 1655051671.6054971 iteration: 55200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15261 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.22386 L1 loss: 0.0000e+00 L2 loss: 0.57721 Learning rate: 0.002 Mask loss: 0.16035 RPN box loss: 0.01127 RPN score loss: 0.00248 RPN total loss: 0.01374 Total loss: 0.97516 timestamp: 1655051674.895836 iteration: 55205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09519 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.17268 L1 loss: 0.0000e+00 L2 loss: 0.5772 Learning rate: 0.002 Mask loss: 0.1613 RPN box loss: 0.00809 RPN score loss: 0.0022 RPN total loss: 0.01029 Total loss: 0.92147 timestamp: 1655051678.1553667 iteration: 55210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12268 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.19351 L1 loss: 0.0000e+00 L2 loss: 0.57719 Learning rate: 0.002 Mask loss: 0.14278 RPN box loss: 0.02391 RPN score loss: 0.0068 RPN total loss: 0.03072 Total loss: 0.9442 timestamp: 1655051681.4286256 iteration: 55215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16018 FastRCNN class loss: 0.06658 FastRCNN total loss: 0.22676 L1 loss: 0.0000e+00 L2 loss: 0.57718 Learning rate: 0.002 Mask loss: 0.14652 RPN box loss: 0.0129 RPN score loss: 0.01888 RPN total loss: 0.03179 Total loss: 0.98225 timestamp: 1655051684.7128408 iteration: 55220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13094 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.21376 L1 loss: 0.0000e+00 L2 loss: 0.57718 Learning rate: 0.002 Mask loss: 0.09821 RPN box loss: 0.02217 RPN score loss: 0.01467 RPN total loss: 0.03684 Total loss: 0.92599 timestamp: 1655051687.9449131 iteration: 55225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13133 FastRCNN class loss: 0.10566 FastRCNN total loss: 0.237 L1 loss: 0.0000e+00 L2 loss: 0.57717 Learning rate: 0.002 Mask loss: 0.19553 RPN box loss: 0.01761 RPN score loss: 0.01941 RPN total loss: 0.03702 Total loss: 1.04672 timestamp: 1655051691.1578257 iteration: 55230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.14968 L1 loss: 0.0000e+00 L2 loss: 0.57716 Learning rate: 0.002 Mask loss: 0.21178 RPN box loss: 0.01405 RPN score loss: 0.00762 RPN total loss: 0.02167 Total loss: 0.96028 timestamp: 1655051694.4614406 iteration: 55235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.06297 FastRCNN total loss: 0.18014 L1 loss: 0.0000e+00 L2 loss: 0.57715 Learning rate: 0.002 Mask loss: 0.12164 RPN box loss: 0.0093 RPN score loss: 0.00731 RPN total loss: 0.01661 Total loss: 0.89553 timestamp: 1655051697.7558575 iteration: 55240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06871 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.13915 L1 loss: 0.0000e+00 L2 loss: 0.57714 Learning rate: 0.002 Mask loss: 0.12171 RPN box loss: 0.02216 RPN score loss: 0.00455 RPN total loss: 0.02671 Total loss: 0.86471 timestamp: 1655051701.012833 iteration: 55245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08195 FastRCNN class loss: 0.06012 FastRCNN total loss: 0.14208 L1 loss: 0.0000e+00 L2 loss: 0.57712 Learning rate: 0.002 Mask loss: 0.13244 RPN box loss: 0.02375 RPN score loss: 0.00533 RPN total loss: 0.02908 Total loss: 0.88072 timestamp: 1655051704.2503378 iteration: 55250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09143 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.16013 L1 loss: 0.0000e+00 L2 loss: 0.57712 Learning rate: 0.002 Mask loss: 0.15555 RPN box loss: 0.01303 RPN score loss: 0.00415 RPN total loss: 0.01719 Total loss: 0.90998 timestamp: 1655051707.5431156 iteration: 55255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12094 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.17952 L1 loss: 0.0000e+00 L2 loss: 0.57711 Learning rate: 0.002 Mask loss: 0.11989 RPN box loss: 0.00556 RPN score loss: 0.00331 RPN total loss: 0.00888 Total loss: 0.88539 timestamp: 1655051710.766782 iteration: 55260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09252 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.5771 Learning rate: 0.002 Mask loss: 0.14855 RPN box loss: 0.01198 RPN score loss: 0.00772 RPN total loss: 0.0197 Total loss: 0.90574 timestamp: 1655051714.025174 iteration: 55265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09031 FastRCNN class loss: 0.04182 FastRCNN total loss: 0.13214 L1 loss: 0.0000e+00 L2 loss: 0.57709 Learning rate: 0.002 Mask loss: 0.05914 RPN box loss: 0.00384 RPN score loss: 0.00342 RPN total loss: 0.00726 Total loss: 0.77563 timestamp: 1655051717.2960408 iteration: 55270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07302 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.13184 L1 loss: 0.0000e+00 L2 loss: 0.57709 Learning rate: 0.002 Mask loss: 0.15768 RPN box loss: 0.01812 RPN score loss: 0.00561 RPN total loss: 0.02373 Total loss: 0.89033 timestamp: 1655051720.614796 iteration: 55275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12231 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.19492 L1 loss: 0.0000e+00 L2 loss: 0.57708 Learning rate: 0.002 Mask loss: 0.11942 RPN box loss: 0.02283 RPN score loss: 0.00496 RPN total loss: 0.02779 Total loss: 0.91921 timestamp: 1655051723.891104 iteration: 55280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09407 FastRCNN class loss: 0.09146 FastRCNN total loss: 0.18553 L1 loss: 0.0000e+00 L2 loss: 0.57707 Learning rate: 0.002 Mask loss: 0.10975 RPN box loss: 0.02404 RPN score loss: 0.01108 RPN total loss: 0.03512 Total loss: 0.90747 timestamp: 1655051727.1307473 iteration: 55285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15806 FastRCNN class loss: 0.07737 FastRCNN total loss: 0.23542 L1 loss: 0.0000e+00 L2 loss: 0.57706 Learning rate: 0.002 Mask loss: 0.13087 RPN box loss: 0.00998 RPN score loss: 0.0018 RPN total loss: 0.01179 Total loss: 0.95515 timestamp: 1655051730.396084 iteration: 55290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.17423 L1 loss: 0.0000e+00 L2 loss: 0.57705 Learning rate: 0.002 Mask loss: 0.09386 RPN box loss: 0.01217 RPN score loss: 0.0047 RPN total loss: 0.01687 Total loss: 0.86201 timestamp: 1655051733.6642947 iteration: 55295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13536 FastRCNN class loss: 0.08634 FastRCNN total loss: 0.22169 L1 loss: 0.0000e+00 L2 loss: 0.57705 Learning rate: 0.002 Mask loss: 0.16708 RPN box loss: 0.01449 RPN score loss: 0.0029 RPN total loss: 0.01739 Total loss: 0.98322 timestamp: 1655051736.9722717 iteration: 55300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08227 FastRCNN class loss: 0.0567 FastRCNN total loss: 0.13897 L1 loss: 0.0000e+00 L2 loss: 0.57704 Learning rate: 0.002 Mask loss: 0.17094 RPN box loss: 0.00971 RPN score loss: 0.00354 RPN total loss: 0.01325 Total loss: 0.9002 timestamp: 1655051740.2719638 iteration: 55305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10648 FastRCNN class loss: 0.09468 FastRCNN total loss: 0.20116 L1 loss: 0.0000e+00 L2 loss: 0.57703 Learning rate: 0.002 Mask loss: 0.20265 RPN box loss: 0.01851 RPN score loss: 0.00892 RPN total loss: 0.02743 Total loss: 1.00826 timestamp: 1655051743.5931845 iteration: 55310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03741 FastRCNN class loss: 0.04266 FastRCNN total loss: 0.08007 L1 loss: 0.0000e+00 L2 loss: 0.57701 Learning rate: 0.002 Mask loss: 0.1046 RPN box loss: 0.00317 RPN score loss: 0.00165 RPN total loss: 0.00482 Total loss: 0.7665 timestamp: 1655051746.8533814 iteration: 55315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10998 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.17954 L1 loss: 0.0000e+00 L2 loss: 0.577 Learning rate: 0.002 Mask loss: 0.1761 RPN box loss: 0.02955 RPN score loss: 0.00237 RPN total loss: 0.03192 Total loss: 0.96456 timestamp: 1655051750.207278 iteration: 55320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07834 FastRCNN class loss: 0.06551 FastRCNN total loss: 0.14385 L1 loss: 0.0000e+00 L2 loss: 0.57699 Learning rate: 0.002 Mask loss: 0.1531 RPN box loss: 0.02168 RPN score loss: 0.0016 RPN total loss: 0.02328 Total loss: 0.89723 timestamp: 1655051753.4881296 iteration: 55325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06455 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.12221 L1 loss: 0.0000e+00 L2 loss: 0.57699 Learning rate: 0.002 Mask loss: 0.13881 RPN box loss: 0.01569 RPN score loss: 0.00641 RPN total loss: 0.0221 Total loss: 0.8601 timestamp: 1655051756.721563 iteration: 55330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15108 FastRCNN class loss: 0.10396 FastRCNN total loss: 0.25504 L1 loss: 0.0000e+00 L2 loss: 0.57698 Learning rate: 0.002 Mask loss: 0.16272 RPN box loss: 0.0134 RPN score loss: 0.00614 RPN total loss: 0.01954 Total loss: 1.01428 timestamp: 1655051759.9538581 iteration: 55335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07559 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.14562 L1 loss: 0.0000e+00 L2 loss: 0.57697 Learning rate: 0.002 Mask loss: 0.12191 RPN box loss: 0.0162 RPN score loss: 0.00184 RPN total loss: 0.01804 Total loss: 0.86254 timestamp: 1655051763.2037432 iteration: 55340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08772 FastRCNN class loss: 0.06773 FastRCNN total loss: 0.15545 L1 loss: 0.0000e+00 L2 loss: 0.57697 Learning rate: 0.002 Mask loss: 0.12519 RPN box loss: 0.03451 RPN score loss: 0.0075 RPN total loss: 0.04202 Total loss: 0.89962 timestamp: 1655051766.3812783 iteration: 55345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06294 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.12405 L1 loss: 0.0000e+00 L2 loss: 0.57696 Learning rate: 0.002 Mask loss: 0.13828 RPN box loss: 0.02501 RPN score loss: 0.00542 RPN total loss: 0.03044 Total loss: 0.86973 timestamp: 1655051769.6588056 iteration: 55350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08207 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.14185 L1 loss: 0.0000e+00 L2 loss: 0.57695 Learning rate: 0.002 Mask loss: 0.1286 RPN box loss: 0.01699 RPN score loss: 0.00776 RPN total loss: 0.02475 Total loss: 0.87215 timestamp: 1655051773.0090237 iteration: 55355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17276 FastRCNN class loss: 0.09544 FastRCNN total loss: 0.2682 L1 loss: 0.0000e+00 L2 loss: 0.57694 Learning rate: 0.002 Mask loss: 0.15945 RPN box loss: 0.02481 RPN score loss: 0.02093 RPN total loss: 0.04574 Total loss: 1.05033 timestamp: 1655051776.231167 iteration: 55360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.15129 L1 loss: 0.0000e+00 L2 loss: 0.57693 Learning rate: 0.002 Mask loss: 0.12476 RPN box loss: 0.0361 RPN score loss: 0.00128 RPN total loss: 0.03738 Total loss: 0.89036 timestamp: 1655051779.5088286 iteration: 55365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04587 FastRCNN class loss: 0.03156 FastRCNN total loss: 0.07743 L1 loss: 0.0000e+00 L2 loss: 0.57692 Learning rate: 0.002 Mask loss: 0.15263 RPN box loss: 0.00838 RPN score loss: 0.00665 RPN total loss: 0.01502 Total loss: 0.82201 timestamp: 1655051782.7805188 iteration: 55370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09029 FastRCNN class loss: 0.05863 FastRCNN total loss: 0.14892 L1 loss: 0.0000e+00 L2 loss: 0.57692 Learning rate: 0.002 Mask loss: 0.12885 RPN box loss: 0.00696 RPN score loss: 0.00132 RPN total loss: 0.00828 Total loss: 0.86296 timestamp: 1655051786.0190823 iteration: 55375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16359 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.23555 L1 loss: 0.0000e+00 L2 loss: 0.5769 Learning rate: 0.002 Mask loss: 0.20734 RPN box loss: 0.02238 RPN score loss: 0.01224 RPN total loss: 0.03462 Total loss: 1.05442 timestamp: 1655051789.2286425 iteration: 55380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15605 FastRCNN class loss: 0.08404 FastRCNN total loss: 0.24009 L1 loss: 0.0000e+00 L2 loss: 0.57689 Learning rate: 0.002 Mask loss: 0.1656 RPN box loss: 0.01478 RPN score loss: 0.00757 RPN total loss: 0.02235 Total loss: 1.00493 timestamp: 1655051792.4974964 iteration: 55385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09934 FastRCNN class loss: 0.05768 FastRCNN total loss: 0.15702 L1 loss: 0.0000e+00 L2 loss: 0.57688 Learning rate: 0.002 Mask loss: 0.11136 RPN box loss: 0.01918 RPN score loss: 0.0025 RPN total loss: 0.02168 Total loss: 0.86694 timestamp: 1655051795.7516944 iteration: 55390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0723 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.15319 L1 loss: 0.0000e+00 L2 loss: 0.57687 Learning rate: 0.002 Mask loss: 0.14446 RPN box loss: 0.04033 RPN score loss: 0.00737 RPN total loss: 0.04771 Total loss: 0.92223 timestamp: 1655051799.036058 iteration: 55395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07833 FastRCNN class loss: 0.05569 FastRCNN total loss: 0.13402 L1 loss: 0.0000e+00 L2 loss: 0.57687 Learning rate: 0.002 Mask loss: 0.12287 RPN box loss: 0.02252 RPN score loss: 0.00498 RPN total loss: 0.0275 Total loss: 0.86126 timestamp: 1655051802.334483 iteration: 55400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11776 FastRCNN class loss: 0.05021 FastRCNN total loss: 0.16797 L1 loss: 0.0000e+00 L2 loss: 0.57686 Learning rate: 0.002 Mask loss: 0.1686 RPN box loss: 0.01036 RPN score loss: 0.00185 RPN total loss: 0.01221 Total loss: 0.92564 timestamp: 1655051805.5569518 iteration: 55405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07323 FastRCNN class loss: 0.07692 FastRCNN total loss: 0.15016 L1 loss: 0.0000e+00 L2 loss: 0.57685 Learning rate: 0.002 Mask loss: 0.09 RPN box loss: 0.01376 RPN score loss: 0.00139 RPN total loss: 0.01515 Total loss: 0.83217 timestamp: 1655051808.793387 iteration: 55410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09835 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.14451 L1 loss: 0.0000e+00 L2 loss: 0.57685 Learning rate: 0.002 Mask loss: 0.12724 RPN box loss: 0.00551 RPN score loss: 0.00194 RPN total loss: 0.00745 Total loss: 0.85606 timestamp: 1655051812.1108665 iteration: 55415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17375 FastRCNN class loss: 0.06385 FastRCNN total loss: 0.2376 L1 loss: 0.0000e+00 L2 loss: 0.57684 Learning rate: 0.002 Mask loss: 0.19792 RPN box loss: 0.01245 RPN score loss: 0.00438 RPN total loss: 0.01684 Total loss: 1.02919 timestamp: 1655051815.3553545 iteration: 55420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05421 FastRCNN class loss: 0.04451 FastRCNN total loss: 0.09872 L1 loss: 0.0000e+00 L2 loss: 0.57683 Learning rate: 0.002 Mask loss: 0.10159 RPN box loss: 0.01895 RPN score loss: 0.0071 RPN total loss: 0.02606 Total loss: 0.8032 timestamp: 1655051818.5907524 iteration: 55425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0664 FastRCNN class loss: 0.08047 FastRCNN total loss: 0.14687 L1 loss: 0.0000e+00 L2 loss: 0.57682 Learning rate: 0.002 Mask loss: 0.17645 RPN box loss: 0.02643 RPN score loss: 0.0121 RPN total loss: 0.03853 Total loss: 0.93867 timestamp: 1655051821.8569093 iteration: 55430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.03747 FastRCNN total loss: 0.12011 L1 loss: 0.0000e+00 L2 loss: 0.57681 Learning rate: 0.002 Mask loss: 0.12284 RPN box loss: 0.01109 RPN score loss: 0.00766 RPN total loss: 0.01875 Total loss: 0.8385 timestamp: 1655051825.174984 iteration: 55435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08859 FastRCNN class loss: 0.05749 FastRCNN total loss: 0.14608 L1 loss: 0.0000e+00 L2 loss: 0.5768 Learning rate: 0.002 Mask loss: 0.12169 RPN box loss: 0.02278 RPN score loss: 0.00291 RPN total loss: 0.02568 Total loss: 0.87026 timestamp: 1655051828.4474819 iteration: 55440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1331 FastRCNN class loss: 0.0964 FastRCNN total loss: 0.22951 L1 loss: 0.0000e+00 L2 loss: 0.57679 Learning rate: 0.002 Mask loss: 0.22252 RPN box loss: 0.03606 RPN score loss: 0.01069 RPN total loss: 0.04675 Total loss: 1.07557 timestamp: 1655051831.625207 iteration: 55445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04753 FastRCNN class loss: 0.04448 FastRCNN total loss: 0.092 L1 loss: 0.0000e+00 L2 loss: 0.57679 Learning rate: 0.002 Mask loss: 0.12971 RPN box loss: 0.01072 RPN score loss: 0.00344 RPN total loss: 0.01417 Total loss: 0.81266 timestamp: 1655051834.904258 iteration: 55450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1046 FastRCNN class loss: 0.05173 FastRCNN total loss: 0.15633 L1 loss: 0.0000e+00 L2 loss: 0.57678 Learning rate: 0.002 Mask loss: 0.09976 RPN box loss: 0.01083 RPN score loss: 0.00071 RPN total loss: 0.01154 Total loss: 0.84442 timestamp: 1655051838.1927366 iteration: 55455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12355 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.19991 L1 loss: 0.0000e+00 L2 loss: 0.57677 Learning rate: 0.002 Mask loss: 0.15853 RPN box loss: 0.02422 RPN score loss: 0.00902 RPN total loss: 0.03325 Total loss: 0.96846 timestamp: 1655051841.378751 iteration: 55460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.128 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.20337 L1 loss: 0.0000e+00 L2 loss: 0.57676 Learning rate: 0.002 Mask loss: 0.09757 RPN box loss: 0.01878 RPN score loss: 0.00153 RPN total loss: 0.02031 Total loss: 0.89801 timestamp: 1655051844.606517 iteration: 55465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08547 FastRCNN class loss: 0.08302 FastRCNN total loss: 0.16848 L1 loss: 0.0000e+00 L2 loss: 0.57675 Learning rate: 0.002 Mask loss: 0.175 RPN box loss: 0.01289 RPN score loss: 0.00542 RPN total loss: 0.01831 Total loss: 0.93855 timestamp: 1655051847.815732 iteration: 55470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10668 FastRCNN class loss: 0.08625 FastRCNN total loss: 0.19293 L1 loss: 0.0000e+00 L2 loss: 0.57674 Learning rate: 0.002 Mask loss: 0.17111 RPN box loss: 0.00995 RPN score loss: 0.00931 RPN total loss: 0.01926 Total loss: 0.96004 timestamp: 1655051851.0553246 iteration: 55475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.04636 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.57674 Learning rate: 0.002 Mask loss: 0.14018 RPN box loss: 0.01183 RPN score loss: 0.00457 RPN total loss: 0.0164 Total loss: 0.90217 timestamp: 1655051854.3610997 iteration: 55480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06266 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.11091 L1 loss: 0.0000e+00 L2 loss: 0.57673 Learning rate: 0.002 Mask loss: 0.11674 RPN box loss: 0.02412 RPN score loss: 0.00253 RPN total loss: 0.02665 Total loss: 0.83102 timestamp: 1655051857.5921943 iteration: 55485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09918 FastRCNN class loss: 0.09066 FastRCNN total loss: 0.18983 L1 loss: 0.0000e+00 L2 loss: 0.57671 Learning rate: 0.002 Mask loss: 0.23666 RPN box loss: 0.01075 RPN score loss: 0.00305 RPN total loss: 0.0138 Total loss: 1.017 timestamp: 1655051860.8335624 iteration: 55490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15367 FastRCNN class loss: 0.11822 FastRCNN total loss: 0.27189 L1 loss: 0.0000e+00 L2 loss: 0.57671 Learning rate: 0.002 Mask loss: 0.16426 RPN box loss: 0.02757 RPN score loss: 0.01217 RPN total loss: 0.03975 Total loss: 1.05261 timestamp: 1655051864.1198766 iteration: 55495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10257 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.17637 L1 loss: 0.0000e+00 L2 loss: 0.5767 Learning rate: 0.002 Mask loss: 0.14098 RPN box loss: 0.02723 RPN score loss: 0.00581 RPN total loss: 0.03304 Total loss: 0.92709 timestamp: 1655051867.395503 iteration: 55500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04968 FastRCNN class loss: 0.03571 FastRCNN total loss: 0.08539 L1 loss: 0.0000e+00 L2 loss: 0.57669 Learning rate: 0.002 Mask loss: 0.0983 RPN box loss: 0.00203 RPN score loss: 0.00185 RPN total loss: 0.00388 Total loss: 0.76426 timestamp: 1655051870.6945975 iteration: 55505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.06018 FastRCNN total loss: 0.14305 L1 loss: 0.0000e+00 L2 loss: 0.57669 Learning rate: 0.002 Mask loss: 0.16877 RPN box loss: 0.01166 RPN score loss: 0.00184 RPN total loss: 0.0135 Total loss: 0.90201 timestamp: 1655051873.981327 iteration: 55510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10121 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.57668 Learning rate: 0.002 Mask loss: 0.16043 RPN box loss: 0.02278 RPN score loss: 0.00349 RPN total loss: 0.02627 Total loss: 0.95398 timestamp: 1655051877.2760596 iteration: 55515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1083 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.17434 L1 loss: 0.0000e+00 L2 loss: 0.57667 Learning rate: 0.002 Mask loss: 0.18726 RPN box loss: 0.0129 RPN score loss: 0.00738 RPN total loss: 0.02028 Total loss: 0.95854 timestamp: 1655051880.5549076 iteration: 55520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12457 FastRCNN class loss: 0.09056 FastRCNN total loss: 0.21513 L1 loss: 0.0000e+00 L2 loss: 0.57666 Learning rate: 0.002 Mask loss: 0.18452 RPN box loss: 0.02132 RPN score loss: 0.01232 RPN total loss: 0.03364 Total loss: 1.00994 timestamp: 1655051883.7745934 iteration: 55525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0916 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.15015 L1 loss: 0.0000e+00 L2 loss: 0.57665 Learning rate: 0.002 Mask loss: 0.10167 RPN box loss: 0.01495 RPN score loss: 0.00219 RPN total loss: 0.01714 Total loss: 0.84562 timestamp: 1655051887.111664 iteration: 55530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1151 FastRCNN class loss: 0.06894 FastRCNN total loss: 0.18405 L1 loss: 0.0000e+00 L2 loss: 0.57664 Learning rate: 0.002 Mask loss: 0.1886 RPN box loss: 0.01252 RPN score loss: 0.00229 RPN total loss: 0.0148 Total loss: 0.96409 timestamp: 1655051890.3254833 iteration: 55535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10688 FastRCNN class loss: 0.10848 FastRCNN total loss: 0.21536 L1 loss: 0.0000e+00 L2 loss: 0.57663 Learning rate: 0.002 Mask loss: 0.19744 RPN box loss: 0.02108 RPN score loss: 0.01145 RPN total loss: 0.03252 Total loss: 1.02195 timestamp: 1655051893.6438048 iteration: 55540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14675 FastRCNN class loss: 0.08155 FastRCNN total loss: 0.2283 L1 loss: 0.0000e+00 L2 loss: 0.57662 Learning rate: 0.002 Mask loss: 0.14328 RPN box loss: 0.01677 RPN score loss: 0.00825 RPN total loss: 0.02503 Total loss: 0.97323 timestamp: 1655051896.9247851 iteration: 55545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16566 FastRCNN class loss: 0.10578 FastRCNN total loss: 0.27144 L1 loss: 0.0000e+00 L2 loss: 0.57662 Learning rate: 0.002 Mask loss: 0.17454 RPN box loss: 0.02739 RPN score loss: 0.00571 RPN total loss: 0.0331 Total loss: 1.05569 timestamp: 1655051900.236628 iteration: 55550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08087 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.13519 L1 loss: 0.0000e+00 L2 loss: 0.57661 Learning rate: 0.002 Mask loss: 0.09268 RPN box loss: 0.01371 RPN score loss: 0.00153 RPN total loss: 0.01524 Total loss: 0.81971 timestamp: 1655051903.5275118 iteration: 55555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1405 FastRCNN class loss: 0.10757 FastRCNN total loss: 0.24807 L1 loss: 0.0000e+00 L2 loss: 0.5766 Learning rate: 0.002 Mask loss: 0.23072 RPN box loss: 0.02456 RPN score loss: 0.01717 RPN total loss: 0.04173 Total loss: 1.09711 timestamp: 1655051906.8133218 iteration: 55560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07714 FastRCNN class loss: 0.05509 FastRCNN total loss: 0.13223 L1 loss: 0.0000e+00 L2 loss: 0.57659 Learning rate: 0.002 Mask loss: 0.13569 RPN box loss: 0.00493 RPN score loss: 0.00833 RPN total loss: 0.01326 Total loss: 0.85777 timestamp: 1655051910.082781 iteration: 55565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13333 FastRCNN class loss: 0.06778 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 0.57658 Learning rate: 0.002 Mask loss: 0.1645 RPN box loss: 0.0156 RPN score loss: 0.00466 RPN total loss: 0.02026 Total loss: 0.96245 timestamp: 1655051913.3558328 iteration: 55570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06683 FastRCNN class loss: 0.0715 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.57657 Learning rate: 0.002 Mask loss: 0.15099 RPN box loss: 0.01639 RPN score loss: 0.00776 RPN total loss: 0.02415 Total loss: 0.89004 timestamp: 1655051916.6112423 iteration: 55575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13013 FastRCNN class loss: 0.1038 FastRCNN total loss: 0.23393 L1 loss: 0.0000e+00 L2 loss: 0.57656 Learning rate: 0.002 Mask loss: 0.11811 RPN box loss: 0.01647 RPN score loss: 0.00491 RPN total loss: 0.02138 Total loss: 0.94999 timestamp: 1655051919.7884138 iteration: 55580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07746 FastRCNN class loss: 0.11719 FastRCNN total loss: 0.19465 L1 loss: 0.0000e+00 L2 loss: 0.57655 Learning rate: 0.002 Mask loss: 0.12874 RPN box loss: 0.0219 RPN score loss: 0.00351 RPN total loss: 0.02542 Total loss: 0.92536 timestamp: 1655051923.0473588 iteration: 55585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08913 FastRCNN class loss: 0.05278 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 0.57654 Learning rate: 0.002 Mask loss: 0.09433 RPN box loss: 0.00947 RPN score loss: 0.00141 RPN total loss: 0.01087 Total loss: 0.82366 timestamp: 1655051926.3282824 iteration: 55590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09154 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.16719 L1 loss: 0.0000e+00 L2 loss: 0.57653 Learning rate: 0.002 Mask loss: 0.13044 RPN box loss: 0.02473 RPN score loss: 0.00658 RPN total loss: 0.03131 Total loss: 0.90546 timestamp: 1655051929.6393003 iteration: 55595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.14755 L1 loss: 0.0000e+00 L2 loss: 0.57653 Learning rate: 0.002 Mask loss: 0.16211 RPN box loss: 0.02339 RPN score loss: 0.01287 RPN total loss: 0.03626 Total loss: 0.92244 timestamp: 1655051932.9345443 iteration: 55600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11508 FastRCNN class loss: 0.12049 FastRCNN total loss: 0.23556 L1 loss: 0.0000e+00 L2 loss: 0.57652 Learning rate: 0.002 Mask loss: 0.1769 RPN box loss: 0.01136 RPN score loss: 0.00493 RPN total loss: 0.01629 Total loss: 1.00528 timestamp: 1655051936.1725326 iteration: 55605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04486 FastRCNN class loss: 0.03888 FastRCNN total loss: 0.08374 L1 loss: 0.0000e+00 L2 loss: 0.57651 Learning rate: 0.002 Mask loss: 0.11269 RPN box loss: 0.00403 RPN score loss: 0.00521 RPN total loss: 0.00924 Total loss: 0.78218 timestamp: 1655051939.5017767 iteration: 55610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07414 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.1406 L1 loss: 0.0000e+00 L2 loss: 0.5765 Learning rate: 0.002 Mask loss: 0.16224 RPN box loss: 0.01959 RPN score loss: 0.00249 RPN total loss: 0.02208 Total loss: 0.90142 timestamp: 1655051942.795424 iteration: 55615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15061 FastRCNN class loss: 0.063 FastRCNN total loss: 0.21361 L1 loss: 0.0000e+00 L2 loss: 0.57649 Learning rate: 0.002 Mask loss: 0.19447 RPN box loss: 0.0103 RPN score loss: 0.00633 RPN total loss: 0.01663 Total loss: 1.0012 timestamp: 1655051946.0514078 iteration: 55620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.15604 L1 loss: 0.0000e+00 L2 loss: 0.57649 Learning rate: 0.002 Mask loss: 0.14516 RPN box loss: 0.04136 RPN score loss: 0.00461 RPN total loss: 0.04597 Total loss: 0.92365 timestamp: 1655051949.2686126 iteration: 55625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16377 FastRCNN class loss: 0.09365 FastRCNN total loss: 0.25742 L1 loss: 0.0000e+00 L2 loss: 0.57648 Learning rate: 0.002 Mask loss: 0.14635 RPN box loss: 0.02851 RPN score loss: 0.00328 RPN total loss: 0.03178 Total loss: 1.01203 timestamp: 1655051952.5772767 iteration: 55630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09477 FastRCNN class loss: 0.07688 FastRCNN total loss: 0.17165 L1 loss: 0.0000e+00 L2 loss: 0.57647 Learning rate: 0.002 Mask loss: 0.16375 RPN box loss: 0.01178 RPN score loss: 0.00628 RPN total loss: 0.01806 Total loss: 0.92993 timestamp: 1655051955.8582344 iteration: 55635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14293 FastRCNN class loss: 0.0537 FastRCNN total loss: 0.19663 L1 loss: 0.0000e+00 L2 loss: 0.57646 Learning rate: 0.002 Mask loss: 0.18098 RPN box loss: 0.01038 RPN score loss: 0.00158 RPN total loss: 0.01197 Total loss: 0.96604 timestamp: 1655051959.1405082 iteration: 55640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0719 FastRCNN class loss: 0.06291 FastRCNN total loss: 0.13481 L1 loss: 0.0000e+00 L2 loss: 0.57645 Learning rate: 0.002 Mask loss: 0.0948 RPN box loss: 0.00659 RPN score loss: 0.00189 RPN total loss: 0.00849 Total loss: 0.81455 timestamp: 1655051962.4218214 iteration: 55645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07852 FastRCNN class loss: 0.03269 FastRCNN total loss: 0.11122 L1 loss: 0.0000e+00 L2 loss: 0.57644 Learning rate: 0.002 Mask loss: 0.1332 RPN box loss: 0.01125 RPN score loss: 0.00509 RPN total loss: 0.01634 Total loss: 0.8372 timestamp: 1655051965.645046 iteration: 55650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07931 FastRCNN class loss: 0.05362 FastRCNN total loss: 0.13293 L1 loss: 0.0000e+00 L2 loss: 0.57643 Learning rate: 0.002 Mask loss: 0.16797 RPN box loss: 0.01071 RPN score loss: 0.00216 RPN total loss: 0.01287 Total loss: 0.8902 timestamp: 1655051968.9743855 iteration: 55655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13554 FastRCNN class loss: 0.10479 FastRCNN total loss: 0.24033 L1 loss: 0.0000e+00 L2 loss: 0.57642 Learning rate: 0.002 Mask loss: 0.18578 RPN box loss: 0.01412 RPN score loss: 0.00261 RPN total loss: 0.01673 Total loss: 1.01926 timestamp: 1655051972.1441088 iteration: 55660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10464 FastRCNN class loss: 0.08852 FastRCNN total loss: 0.19316 L1 loss: 0.0000e+00 L2 loss: 0.57642 Learning rate: 0.002 Mask loss: 0.12884 RPN box loss: 0.02226 RPN score loss: 0.00492 RPN total loss: 0.02718 Total loss: 0.9256 timestamp: 1655051975.4216566 iteration: 55665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10331 FastRCNN class loss: 0.07894 FastRCNN total loss: 0.18225 L1 loss: 0.0000e+00 L2 loss: 0.57641 Learning rate: 0.002 Mask loss: 0.15427 RPN box loss: 0.03359 RPN score loss: 0.02267 RPN total loss: 0.05625 Total loss: 0.96919 timestamp: 1655051978.6807542 iteration: 55670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06732 FastRCNN class loss: 0.03988 FastRCNN total loss: 0.1072 L1 loss: 0.0000e+00 L2 loss: 0.57641 Learning rate: 0.002 Mask loss: 0.09075 RPN box loss: 0.04832 RPN score loss: 0.00268 RPN total loss: 0.05099 Total loss: 0.82535 timestamp: 1655051981.9331884 iteration: 55675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05581 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.13209 L1 loss: 0.0000e+00 L2 loss: 0.5764 Learning rate: 0.002 Mask loss: 0.16979 RPN box loss: 0.0044 RPN score loss: 0.00071 RPN total loss: 0.00511 Total loss: 0.88339 timestamp: 1655051985.225514 iteration: 55680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14219 FastRCNN class loss: 0.12946 FastRCNN total loss: 0.27165 L1 loss: 0.0000e+00 L2 loss: 0.57639 Learning rate: 0.002 Mask loss: 0.1898 RPN box loss: 0.01457 RPN score loss: 0.00821 RPN total loss: 0.02278 Total loss: 1.06062 timestamp: 1655051988.5794795 iteration: 55685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12647 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.21053 L1 loss: 0.0000e+00 L2 loss: 0.57638 Learning rate: 0.002 Mask loss: 0.1397 RPN box loss: 0.01858 RPN score loss: 0.00276 RPN total loss: 0.02134 Total loss: 0.94795 timestamp: 1655051991.8610446 iteration: 55690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0777 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.17519 L1 loss: 0.0000e+00 L2 loss: 0.57637 Learning rate: 0.002 Mask loss: 0.11865 RPN box loss: 0.00964 RPN score loss: 0.01434 RPN total loss: 0.02398 Total loss: 0.89419 timestamp: 1655051995.1183014 iteration: 55695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.1287 L1 loss: 0.0000e+00 L2 loss: 0.57636 Learning rate: 0.002 Mask loss: 0.11898 RPN box loss: 0.01491 RPN score loss: 0.00762 RPN total loss: 0.02253 Total loss: 0.84658 timestamp: 1655051998.3544433 iteration: 55700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14582 FastRCNN class loss: 0.08983 FastRCNN total loss: 0.23565 L1 loss: 0.0000e+00 L2 loss: 0.57635 Learning rate: 0.002 Mask loss: 0.14271 RPN box loss: 0.01033 RPN score loss: 0.0059 RPN total loss: 0.01623 Total loss: 0.97095 timestamp: 1655052001.6142788 iteration: 55705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0442 FastRCNN class loss: 0.04984 FastRCNN total loss: 0.09404 L1 loss: 0.0000e+00 L2 loss: 0.57635 Learning rate: 0.002 Mask loss: 0.15533 RPN box loss: 0.00503 RPN score loss: 0.00327 RPN total loss: 0.00831 Total loss: 0.83403 timestamp: 1655052004.980826 iteration: 55710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10595 FastRCNN class loss: 0.06618 FastRCNN total loss: 0.17213 L1 loss: 0.0000e+00 L2 loss: 0.57634 Learning rate: 0.002 Mask loss: 0.22647 RPN box loss: 0.0355 RPN score loss: 0.00928 RPN total loss: 0.04479 Total loss: 1.01973 timestamp: 1655052008.2748394 iteration: 55715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09395 FastRCNN class loss: 0.06901 FastRCNN total loss: 0.16297 L1 loss: 0.0000e+00 L2 loss: 0.57632 Learning rate: 0.002 Mask loss: 0.15971 RPN box loss: 0.02346 RPN score loss: 0.00359 RPN total loss: 0.02706 Total loss: 0.92606 timestamp: 1655052011.5910673 iteration: 55720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07232 FastRCNN class loss: 0.03745 FastRCNN total loss: 0.10977 L1 loss: 0.0000e+00 L2 loss: 0.57631 Learning rate: 0.002 Mask loss: 0.11163 RPN box loss: 0.01445 RPN score loss: 0.00065 RPN total loss: 0.0151 Total loss: 0.81281 timestamp: 1655052014.8821182 iteration: 55725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08055 FastRCNN class loss: 0.04079 FastRCNN total loss: 0.12134 L1 loss: 0.0000e+00 L2 loss: 0.57631 Learning rate: 0.002 Mask loss: 0.13007 RPN box loss: 0.01205 RPN score loss: 0.00203 RPN total loss: 0.01408 Total loss: 0.84179 timestamp: 1655052018.1300714 iteration: 55730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09821 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.18051 L1 loss: 0.0000e+00 L2 loss: 0.5763 Learning rate: 0.002 Mask loss: 0.10602 RPN box loss: 0.01906 RPN score loss: 0.00372 RPN total loss: 0.02278 Total loss: 0.88561 timestamp: 1655052021.4120522 iteration: 55735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08731 FastRCNN class loss: 0.05347 FastRCNN total loss: 0.14079 L1 loss: 0.0000e+00 L2 loss: 0.5763 Learning rate: 0.002 Mask loss: 0.13102 RPN box loss: 0.01696 RPN score loss: 0.00084 RPN total loss: 0.01779 Total loss: 0.8659 timestamp: 1655052024.696548 iteration: 55740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08151 FastRCNN class loss: 0.0892 FastRCNN total loss: 0.1707 L1 loss: 0.0000e+00 L2 loss: 0.57628 Learning rate: 0.002 Mask loss: 0.15115 RPN box loss: 0.04355 RPN score loss: 0.02049 RPN total loss: 0.06404 Total loss: 0.96218 timestamp: 1655052027.9336963 iteration: 55745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10034 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.15831 L1 loss: 0.0000e+00 L2 loss: 0.57627 Learning rate: 0.002 Mask loss: 0.15275 RPN box loss: 0.01285 RPN score loss: 0.00258 RPN total loss: 0.01544 Total loss: 0.90277 timestamp: 1655052031.146488 iteration: 55750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11277 FastRCNN class loss: 0.0852 FastRCNN total loss: 0.19797 L1 loss: 0.0000e+00 L2 loss: 0.57626 Learning rate: 0.002 Mask loss: 0.16185 RPN box loss: 0.01891 RPN score loss: 0.00468 RPN total loss: 0.02359 Total loss: 0.95967 timestamp: 1655052034.5242636 iteration: 55755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06131 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.13021 L1 loss: 0.0000e+00 L2 loss: 0.57625 Learning rate: 0.002 Mask loss: 0.10298 RPN box loss: 0.02613 RPN score loss: 0.00489 RPN total loss: 0.03103 Total loss: 0.84047 timestamp: 1655052037.8058834 iteration: 55760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09209 FastRCNN class loss: 0.05768 FastRCNN total loss: 0.14977 L1 loss: 0.0000e+00 L2 loss: 0.57625 Learning rate: 0.002 Mask loss: 0.17177 RPN box loss: 0.01093 RPN score loss: 0.00701 RPN total loss: 0.01794 Total loss: 0.91573 timestamp: 1655052041.1262202 iteration: 55765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08507 FastRCNN class loss: 0.058 FastRCNN total loss: 0.14307 L1 loss: 0.0000e+00 L2 loss: 0.57624 Learning rate: 0.002 Mask loss: 0.15999 RPN box loss: 0.00674 RPN score loss: 0.0103 RPN total loss: 0.01704 Total loss: 0.89635 timestamp: 1655052044.395706 iteration: 55770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09588 FastRCNN class loss: 0.09179 FastRCNN total loss: 0.18767 L1 loss: 0.0000e+00 L2 loss: 0.57623 Learning rate: 0.002 Mask loss: 0.18424 RPN box loss: 0.06032 RPN score loss: 0.00473 RPN total loss: 0.06505 Total loss: 1.01319 timestamp: 1655052047.671956 iteration: 55775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05132 FastRCNN class loss: 0.0479 FastRCNN total loss: 0.09921 L1 loss: 0.0000e+00 L2 loss: 0.57622 Learning rate: 0.002 Mask loss: 0.1478 RPN box loss: 0.00934 RPN score loss: 0.01183 RPN total loss: 0.02117 Total loss: 0.8444 timestamp: 1655052051.0081084 iteration: 55780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.07582 FastRCNN total loss: 0.15147 L1 loss: 0.0000e+00 L2 loss: 0.57621 Learning rate: 0.002 Mask loss: 0.11776 RPN box loss: 0.02026 RPN score loss: 0.00408 RPN total loss: 0.02434 Total loss: 0.86978 timestamp: 1655052054.2411335 iteration: 55785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06498 FastRCNN class loss: 0.04937 FastRCNN total loss: 0.11435 L1 loss: 0.0000e+00 L2 loss: 0.57621 Learning rate: 0.002 Mask loss: 0.13942 RPN box loss: 0.00669 RPN score loss: 0.0089 RPN total loss: 0.01559 Total loss: 0.84557 timestamp: 1655052057.5470264 iteration: 55790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09642 FastRCNN class loss: 0.0579 FastRCNN total loss: 0.15433 L1 loss: 0.0000e+00 L2 loss: 0.57619 Learning rate: 0.002 Mask loss: 0.14796 RPN box loss: 0.02073 RPN score loss: 0.01067 RPN total loss: 0.0314 Total loss: 0.90988 timestamp: 1655052060.7958648 iteration: 55795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0438 FastRCNN class loss: 0.03602 FastRCNN total loss: 0.07982 L1 loss: 0.0000e+00 L2 loss: 0.57618 Learning rate: 0.002 Mask loss: 0.12843 RPN box loss: 0.01917 RPN score loss: 0.0025 RPN total loss: 0.02168 Total loss: 0.80611 timestamp: 1655052064.04104 iteration: 55800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16718 FastRCNN class loss: 0.09021 FastRCNN total loss: 0.25739 L1 loss: 0.0000e+00 L2 loss: 0.57617 Learning rate: 0.002 Mask loss: 0.17327 RPN box loss: 0.0185 RPN score loss: 0.00764 RPN total loss: 0.02614 Total loss: 1.03297 timestamp: 1655052067.283404 iteration: 55805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10878 FastRCNN class loss: 0.10319 FastRCNN total loss: 0.21198 L1 loss: 0.0000e+00 L2 loss: 0.57616 Learning rate: 0.002 Mask loss: 0.1423 RPN box loss: 0.06271 RPN score loss: 0.00396 RPN total loss: 0.06666 Total loss: 0.99711 timestamp: 1655052070.565546 iteration: 55810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16017 FastRCNN class loss: 0.11267 FastRCNN total loss: 0.27284 L1 loss: 0.0000e+00 L2 loss: 0.57616 Learning rate: 0.002 Mask loss: 0.17294 RPN box loss: 0.03743 RPN score loss: 0.01401 RPN total loss: 0.05144 Total loss: 1.07337 timestamp: 1655052073.8048844 iteration: 55815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11142 FastRCNN class loss: 0.07931 FastRCNN total loss: 0.19074 L1 loss: 0.0000e+00 L2 loss: 0.57615 Learning rate: 0.002 Mask loss: 0.21959 RPN box loss: 0.02011 RPN score loss: 0.01126 RPN total loss: 0.03137 Total loss: 1.01784 timestamp: 1655052077.0815866 iteration: 55820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.07458 FastRCNN total loss: 0.21453 L1 loss: 0.0000e+00 L2 loss: 0.57614 Learning rate: 0.002 Mask loss: 0.15232 RPN box loss: 0.00736 RPN score loss: 0.0059 RPN total loss: 0.01326 Total loss: 0.95625 timestamp: 1655052080.3485978 iteration: 55825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.05887 FastRCNN total loss: 0.13177 L1 loss: 0.0000e+00 L2 loss: 0.57614 Learning rate: 0.002 Mask loss: 0.1365 RPN box loss: 0.0089 RPN score loss: 0.0034 RPN total loss: 0.0123 Total loss: 0.85671 timestamp: 1655052083.6435637 iteration: 55830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11609 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.19451 L1 loss: 0.0000e+00 L2 loss: 0.57613 Learning rate: 0.002 Mask loss: 0.15758 RPN box loss: 0.02849 RPN score loss: 0.00672 RPN total loss: 0.03521 Total loss: 0.96342 timestamp: 1655052086.8668435 iteration: 55835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09889 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.15802 L1 loss: 0.0000e+00 L2 loss: 0.57613 Learning rate: 0.002 Mask loss: 0.13203 RPN box loss: 0.00871 RPN score loss: 0.00264 RPN total loss: 0.01135 Total loss: 0.87752 timestamp: 1655052090.1260557 iteration: 55840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08729 FastRCNN class loss: 0.06159 FastRCNN total loss: 0.14888 L1 loss: 0.0000e+00 L2 loss: 0.57612 Learning rate: 0.002 Mask loss: 0.2856 RPN box loss: 0.03251 RPN score loss: 0.01239 RPN total loss: 0.04489 Total loss: 1.0555 timestamp: 1655052093.4016185 iteration: 55845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08495 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.15624 L1 loss: 0.0000e+00 L2 loss: 0.57611 Learning rate: 0.002 Mask loss: 0.15367 RPN box loss: 0.02718 RPN score loss: 0.00739 RPN total loss: 0.03457 Total loss: 0.92059 timestamp: 1655052096.6131032 iteration: 55850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13119 FastRCNN class loss: 0.12358 FastRCNN total loss: 0.25477 L1 loss: 0.0000e+00 L2 loss: 0.5761 Learning rate: 0.002 Mask loss: 0.1664 RPN box loss: 0.02644 RPN score loss: 0.00767 RPN total loss: 0.03411 Total loss: 1.03138 timestamp: 1655052099.96901 iteration: 55855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05916 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.12468 L1 loss: 0.0000e+00 L2 loss: 0.57609 Learning rate: 0.002 Mask loss: 0.169 RPN box loss: 0.01374 RPN score loss: 0.01744 RPN total loss: 0.03118 Total loss: 0.90095 timestamp: 1655052103.1649444 iteration: 55860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.04943 FastRCNN total loss: 0.12232 L1 loss: 0.0000e+00 L2 loss: 0.57608 Learning rate: 0.002 Mask loss: 0.09566 RPN box loss: 0.0057 RPN score loss: 0.00178 RPN total loss: 0.00748 Total loss: 0.80155 timestamp: 1655052106.452943 iteration: 55865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06601 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.11923 L1 loss: 0.0000e+00 L2 loss: 0.57608 Learning rate: 0.002 Mask loss: 0.09887 RPN box loss: 0.00496 RPN score loss: 0.00351 RPN total loss: 0.00846 Total loss: 0.80264 timestamp: 1655052109.7001426 iteration: 55870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.09938 FastRCNN total loss: 0.18074 L1 loss: 0.0000e+00 L2 loss: 0.57607 Learning rate: 0.002 Mask loss: 0.09784 RPN box loss: 0.00795 RPN score loss: 0.00313 RPN total loss: 0.01109 Total loss: 0.86574 timestamp: 1655052112.9967175 iteration: 55875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05232 FastRCNN class loss: 0.03853 FastRCNN total loss: 0.09085 L1 loss: 0.0000e+00 L2 loss: 0.57606 Learning rate: 0.002 Mask loss: 0.16062 RPN box loss: 0.01277 RPN score loss: 0.01301 RPN total loss: 0.02578 Total loss: 0.85331 timestamp: 1655052116.2836876 iteration: 55880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.15641 L1 loss: 0.0000e+00 L2 loss: 0.57605 Learning rate: 0.002 Mask loss: 0.13298 RPN box loss: 0.02693 RPN score loss: 0.00469 RPN total loss: 0.03163 Total loss: 0.89706 timestamp: 1655052119.5329337 iteration: 55885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.18942 L1 loss: 0.0000e+00 L2 loss: 0.57605 Learning rate: 0.002 Mask loss: 0.19575 RPN box loss: 0.01383 RPN score loss: 0.01258 RPN total loss: 0.02641 Total loss: 0.98763 timestamp: 1655052122.8287878 iteration: 55890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10408 FastRCNN class loss: 0.11368 FastRCNN total loss: 0.21777 L1 loss: 0.0000e+00 L2 loss: 0.57604 Learning rate: 0.002 Mask loss: 0.14136 RPN box loss: 0.02761 RPN score loss: 0.00653 RPN total loss: 0.03414 Total loss: 0.9693 timestamp: 1655052126.1197138 iteration: 55895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09909 FastRCNN class loss: 0.07459 FastRCNN total loss: 0.17369 L1 loss: 0.0000e+00 L2 loss: 0.57602 Learning rate: 0.002 Mask loss: 0.10913 RPN box loss: 0.01573 RPN score loss: 0.00504 RPN total loss: 0.02077 Total loss: 0.87961 timestamp: 1655052129.3285277 iteration: 55900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.0732 FastRCNN total loss: 0.17099 L1 loss: 0.0000e+00 L2 loss: 0.57601 Learning rate: 0.002 Mask loss: 0.12888 RPN box loss: 0.0096 RPN score loss: 0.00395 RPN total loss: 0.01355 Total loss: 0.88944 timestamp: 1655052132.4931803 iteration: 55905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.19788 L1 loss: 0.0000e+00 L2 loss: 0.576 Learning rate: 0.002 Mask loss: 0.21202 RPN box loss: 0.06015 RPN score loss: 0.00924 RPN total loss: 0.06939 Total loss: 1.05529 timestamp: 1655052135.8190663 iteration: 55910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17054 FastRCNN class loss: 0.09187 FastRCNN total loss: 0.2624 L1 loss: 0.0000e+00 L2 loss: 0.576 Learning rate: 0.002 Mask loss: 0.14182 RPN box loss: 0.00922 RPN score loss: 0.00647 RPN total loss: 0.01569 Total loss: 0.99591 timestamp: 1655052139.1055505 iteration: 55915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09748 FastRCNN class loss: 0.08253 FastRCNN total loss: 0.18001 L1 loss: 0.0000e+00 L2 loss: 0.57599 Learning rate: 0.002 Mask loss: 0.14136 RPN box loss: 0.01394 RPN score loss: 0.00257 RPN total loss: 0.01651 Total loss: 0.91387 timestamp: 1655052142.3848803 iteration: 55920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08737 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.15694 L1 loss: 0.0000e+00 L2 loss: 0.57598 Learning rate: 0.002 Mask loss: 0.13902 RPN box loss: 0.021 RPN score loss: 0.00869 RPN total loss: 0.02969 Total loss: 0.90163 timestamp: 1655052145.6581361 iteration: 55925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09893 FastRCNN class loss: 0.09321 FastRCNN total loss: 0.19214 L1 loss: 0.0000e+00 L2 loss: 0.57597 Learning rate: 0.002 Mask loss: 0.13993 RPN box loss: 0.02899 RPN score loss: 0.01033 RPN total loss: 0.03932 Total loss: 0.94737 timestamp: 1655052148.9221115 iteration: 55930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14796 FastRCNN class loss: 0.11661 FastRCNN total loss: 0.26457 L1 loss: 0.0000e+00 L2 loss: 0.57597 Learning rate: 0.002 Mask loss: 0.1926 RPN box loss: 0.01268 RPN score loss: 0.0043 RPN total loss: 0.01698 Total loss: 1.05012 timestamp: 1655052152.2002964 iteration: 55935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.14934 L1 loss: 0.0000e+00 L2 loss: 0.57596 Learning rate: 0.002 Mask loss: 0.12965 RPN box loss: 0.01428 RPN score loss: 0.00551 RPN total loss: 0.0198 Total loss: 0.87474 timestamp: 1655052155.492812 iteration: 55940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05021 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.1114 L1 loss: 0.0000e+00 L2 loss: 0.57595 Learning rate: 0.002 Mask loss: 0.17781 RPN box loss: 0.02187 RPN score loss: 0.0075 RPN total loss: 0.02937 Total loss: 0.89453 timestamp: 1655052158.7585075 iteration: 55945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12628 FastRCNN class loss: 0.10184 FastRCNN total loss: 0.22812 L1 loss: 0.0000e+00 L2 loss: 0.57594 Learning rate: 0.002 Mask loss: 0.17401 RPN box loss: 0.03572 RPN score loss: 0.01928 RPN total loss: 0.055 Total loss: 1.03308 timestamp: 1655052162.0367186 iteration: 55950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10927 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.16063 L1 loss: 0.0000e+00 L2 loss: 0.57593 Learning rate: 0.002 Mask loss: 0.14827 RPN box loss: 0.01651 RPN score loss: 0.00259 RPN total loss: 0.01911 Total loss: 0.90393 timestamp: 1655052165.2885926 iteration: 55955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14671 FastRCNN class loss: 0.09648 FastRCNN total loss: 0.24319 L1 loss: 0.0000e+00 L2 loss: 0.57592 Learning rate: 0.002 Mask loss: 0.15013 RPN box loss: 0.01315 RPN score loss: 0.00649 RPN total loss: 0.01964 Total loss: 0.98887 timestamp: 1655052168.5265276 iteration: 55960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.06131 FastRCNN total loss: 0.2041 L1 loss: 0.0000e+00 L2 loss: 0.57591 Learning rate: 0.002 Mask loss: 0.13625 RPN box loss: 0.00692 RPN score loss: 0.00563 RPN total loss: 0.01255 Total loss: 0.92881 timestamp: 1655052171.7622344 iteration: 55965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15036 FastRCNN class loss: 0.10151 FastRCNN total loss: 0.25188 L1 loss: 0.0000e+00 L2 loss: 0.5759 Learning rate: 0.002 Mask loss: 0.17909 RPN box loss: 0.01709 RPN score loss: 0.01365 RPN total loss: 0.03073 Total loss: 1.03761 timestamp: 1655052174.9835973 iteration: 55970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09225 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.13572 L1 loss: 0.0000e+00 L2 loss: 0.57589 Learning rate: 0.002 Mask loss: 0.12425 RPN box loss: 0.00592 RPN score loss: 0.0033 RPN total loss: 0.00922 Total loss: 0.84508 timestamp: 1655052178.288584 iteration: 55975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09577 FastRCNN class loss: 0.08885 FastRCNN total loss: 0.18463 L1 loss: 0.0000e+00 L2 loss: 0.57588 Learning rate: 0.002 Mask loss: 0.1996 RPN box loss: 0.0149 RPN score loss: 0.00377 RPN total loss: 0.01868 Total loss: 0.97879 timestamp: 1655052181.5293655 iteration: 55980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08857 FastRCNN class loss: 0.06745 FastRCNN total loss: 0.15602 L1 loss: 0.0000e+00 L2 loss: 0.57588 Learning rate: 0.002 Mask loss: 0.17946 RPN box loss: 0.01176 RPN score loss: 0.00479 RPN total loss: 0.01655 Total loss: 0.92791 timestamp: 1655052184.8069324 iteration: 55985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.07838 FastRCNN total loss: 0.16183 L1 loss: 0.0000e+00 L2 loss: 0.57587 Learning rate: 0.002 Mask loss: 0.19191 RPN box loss: 0.01155 RPN score loss: 0.00322 RPN total loss: 0.01477 Total loss: 0.94438 timestamp: 1655052188.159057 iteration: 55990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12845 FastRCNN class loss: 0.07214 FastRCNN total loss: 0.20059 L1 loss: 0.0000e+00 L2 loss: 0.57586 Learning rate: 0.002 Mask loss: 0.12283 RPN box loss: 0.03511 RPN score loss: 0.00628 RPN total loss: 0.04139 Total loss: 0.94067 timestamp: 1655052191.3940165 iteration: 55995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03309 FastRCNN class loss: 0.02283 FastRCNN total loss: 0.05592 L1 loss: 0.0000e+00 L2 loss: 0.57586 Learning rate: 0.002 Mask loss: 0.11658 RPN box loss: 0.00129 RPN score loss: 0.00401 RPN total loss: 0.0053 Total loss: 0.75365 timestamp: 1655052194.6507683 iteration: 56000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07551 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.13406 L1 loss: 0.0000e+00 L2 loss: 0.57585 Learning rate: 0.002 Mask loss: 0.15971 RPN box loss: 0.00835 RPN score loss: 0.00147 RPN total loss: 0.00982 Total loss: 0.87944 timestamp: 1655052197.82429 iteration: 56005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12111 FastRCNN class loss: 0.05794 FastRCNN total loss: 0.17905 L1 loss: 0.0000e+00 L2 loss: 0.57584 Learning rate: 0.002 Mask loss: 0.09421 RPN box loss: 0.01282 RPN score loss: 0.00133 RPN total loss: 0.01416 Total loss: 0.86326 timestamp: 1655052201.1249568 iteration: 56010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06563 FastRCNN class loss: 0.11313 FastRCNN total loss: 0.17876 L1 loss: 0.0000e+00 L2 loss: 0.57583 Learning rate: 0.002 Mask loss: 0.15322 RPN box loss: 0.02124 RPN score loss: 0.00614 RPN total loss: 0.02738 Total loss: 0.93519 timestamp: 1655052204.369098 iteration: 56015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10023 FastRCNN class loss: 0.08273 FastRCNN total loss: 0.18296 L1 loss: 0.0000e+00 L2 loss: 0.57582 Learning rate: 0.002 Mask loss: 0.14579 RPN box loss: 0.00892 RPN score loss: 0.00676 RPN total loss: 0.01568 Total loss: 0.92025 timestamp: 1655052207.6073751 iteration: 56020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14191 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.21133 L1 loss: 0.0000e+00 L2 loss: 0.57581 Learning rate: 0.002 Mask loss: 0.15345 RPN box loss: 0.01235 RPN score loss: 0.00569 RPN total loss: 0.01804 Total loss: 0.95863 timestamp: 1655052210.9274821 iteration: 56025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17542 FastRCNN class loss: 0.07481 FastRCNN total loss: 0.25022 L1 loss: 0.0000e+00 L2 loss: 0.57581 Learning rate: 0.002 Mask loss: 0.12281 RPN box loss: 0.01435 RPN score loss: 0.00322 RPN total loss: 0.01757 Total loss: 0.96641 timestamp: 1655052214.2069623 iteration: 56030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07483 FastRCNN class loss: 0.07576 FastRCNN total loss: 0.15059 L1 loss: 0.0000e+00 L2 loss: 0.5758 Learning rate: 0.002 Mask loss: 0.27508 RPN box loss: 0.03036 RPN score loss: 0.00261 RPN total loss: 0.03296 Total loss: 1.03444 timestamp: 1655052217.5266836 iteration: 56035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08002 FastRCNN class loss: 0.10412 FastRCNN total loss: 0.18413 L1 loss: 0.0000e+00 L2 loss: 0.57579 Learning rate: 0.002 Mask loss: 0.15519 RPN box loss: 0.01695 RPN score loss: 0.01451 RPN total loss: 0.03146 Total loss: 0.94658 timestamp: 1655052220.7661648 iteration: 56040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12187 FastRCNN class loss: 0.09876 FastRCNN total loss: 0.22063 L1 loss: 0.0000e+00 L2 loss: 0.57578 Learning rate: 0.002 Mask loss: 0.16654 RPN box loss: 0.00894 RPN score loss: 0.00444 RPN total loss: 0.01338 Total loss: 0.97633 timestamp: 1655052223.9746866 iteration: 56045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12221 FastRCNN class loss: 0.08231 FastRCNN total loss: 0.20452 L1 loss: 0.0000e+00 L2 loss: 0.57577 Learning rate: 0.002 Mask loss: 0.22832 RPN box loss: 0.03812 RPN score loss: 0.00352 RPN total loss: 0.04163 Total loss: 1.05024 timestamp: 1655052227.259986 iteration: 56050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08659 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.14255 L1 loss: 0.0000e+00 L2 loss: 0.57576 Learning rate: 0.002 Mask loss: 0.14523 RPN box loss: 0.05249 RPN score loss: 0.0034 RPN total loss: 0.05589 Total loss: 0.91943 timestamp: 1655052230.5468554 iteration: 56055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07308 FastRCNN class loss: 0.04834 FastRCNN total loss: 0.12142 L1 loss: 0.0000e+00 L2 loss: 0.57575 Learning rate: 0.002 Mask loss: 0.10385 RPN box loss: 0.01516 RPN score loss: 0.00236 RPN total loss: 0.01753 Total loss: 0.81855 timestamp: 1655052233.7669463 iteration: 56060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12376 FastRCNN class loss: 0.06758 FastRCNN total loss: 0.19133 L1 loss: 0.0000e+00 L2 loss: 0.57574 Learning rate: 0.002 Mask loss: 0.14941 RPN box loss: 0.02724 RPN score loss: 0.00974 RPN total loss: 0.03698 Total loss: 0.95347 timestamp: 1655052236.9835126 iteration: 56065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09433 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.15673 L1 loss: 0.0000e+00 L2 loss: 0.57573 Learning rate: 0.002 Mask loss: 0.13138 RPN box loss: 0.01046 RPN score loss: 0.00144 RPN total loss: 0.01189 Total loss: 0.87573 timestamp: 1655052240.2945533 iteration: 56070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16562 FastRCNN class loss: 0.1236 FastRCNN total loss: 0.28922 L1 loss: 0.0000e+00 L2 loss: 0.57573 Learning rate: 0.002 Mask loss: 0.16161 RPN box loss: 0.0195 RPN score loss: 0.00341 RPN total loss: 0.02291 Total loss: 1.04947 timestamp: 1655052243.5284908 iteration: 56075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.06466 FastRCNN total loss: 0.16975 L1 loss: 0.0000e+00 L2 loss: 0.57572 Learning rate: 0.002 Mask loss: 0.14385 RPN box loss: 0.00732 RPN score loss: 0.00444 RPN total loss: 0.01176 Total loss: 0.90108 timestamp: 1655052246.7442083 iteration: 56080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08418 FastRCNN class loss: 0.05364 FastRCNN total loss: 0.13782 L1 loss: 0.0000e+00 L2 loss: 0.57571 Learning rate: 0.002 Mask loss: 0.10579 RPN box loss: 0.00751 RPN score loss: 0.00062 RPN total loss: 0.00812 Total loss: 0.82744 timestamp: 1655052250.0898805 iteration: 56085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07839 FastRCNN class loss: 0.05524 FastRCNN total loss: 0.13363 L1 loss: 0.0000e+00 L2 loss: 0.5757 Learning rate: 0.002 Mask loss: 0.11326 RPN box loss: 0.02984 RPN score loss: 0.00487 RPN total loss: 0.03471 Total loss: 0.8573 timestamp: 1655052253.2953038 iteration: 56090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10725 FastRCNN class loss: 0.0597 FastRCNN total loss: 0.16695 L1 loss: 0.0000e+00 L2 loss: 0.57569 Learning rate: 0.002 Mask loss: 0.13418 RPN box loss: 0.01741 RPN score loss: 0.00415 RPN total loss: 0.02156 Total loss: 0.89838 timestamp: 1655052256.5725393 iteration: 56095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11231 FastRCNN class loss: 0.07875 FastRCNN total loss: 0.19106 L1 loss: 0.0000e+00 L2 loss: 0.57568 Learning rate: 0.002 Mask loss: 0.18177 RPN box loss: 0.00924 RPN score loss: 0.00182 RPN total loss: 0.01107 Total loss: 0.95958 timestamp: 1655052259.8262796 iteration: 56100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07491 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.14962 L1 loss: 0.0000e+00 L2 loss: 0.57567 Learning rate: 0.002 Mask loss: 0.1563 RPN box loss: 0.0166 RPN score loss: 0.00773 RPN total loss: 0.02433 Total loss: 0.90592 timestamp: 1655052263.0702446 iteration: 56105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13995 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.19496 L1 loss: 0.0000e+00 L2 loss: 0.57567 Learning rate: 0.002 Mask loss: 0.18412 RPN box loss: 0.01153 RPN score loss: 0.00915 RPN total loss: 0.02068 Total loss: 0.97543 timestamp: 1655052266.3842711 iteration: 56110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07221 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.12237 L1 loss: 0.0000e+00 L2 loss: 0.57566 Learning rate: 0.002 Mask loss: 0.0814 RPN box loss: 0.00993 RPN score loss: 0.00482 RPN total loss: 0.01476 Total loss: 0.79419 timestamp: 1655052269.6632245 iteration: 56115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.05937 FastRCNN total loss: 0.13318 L1 loss: 0.0000e+00 L2 loss: 0.57565 Learning rate: 0.002 Mask loss: 0.14334 RPN box loss: 0.02295 RPN score loss: 0.00339 RPN total loss: 0.02634 Total loss: 0.87851 timestamp: 1655052272.9509366 iteration: 56120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11668 FastRCNN class loss: 0.09048 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 0.57565 Learning rate: 0.002 Mask loss: 0.14359 RPN box loss: 0.01812 RPN score loss: 0.0045 RPN total loss: 0.02262 Total loss: 0.94901 timestamp: 1655052276.2326224 iteration: 56125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10981 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.19378 L1 loss: 0.0000e+00 L2 loss: 0.57564 Learning rate: 0.002 Mask loss: 0.12933 RPN box loss: 0.01306 RPN score loss: 0.00288 RPN total loss: 0.01594 Total loss: 0.91469 timestamp: 1655052279.4397287 iteration: 56130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17488 FastRCNN class loss: 0.08482 FastRCNN total loss: 0.25969 L1 loss: 0.0000e+00 L2 loss: 0.57563 Learning rate: 0.002 Mask loss: 0.14247 RPN box loss: 0.04243 RPN score loss: 0.00606 RPN total loss: 0.04849 Total loss: 1.02628 timestamp: 1655052282.719314 iteration: 56135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07209 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.14193 L1 loss: 0.0000e+00 L2 loss: 0.57562 Learning rate: 0.002 Mask loss: 0.13528 RPN box loss: 0.02649 RPN score loss: 0.00318 RPN total loss: 0.02968 Total loss: 0.8825 timestamp: 1655052285.9759452 iteration: 56140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.0525 FastRCNN total loss: 0.15521 L1 loss: 0.0000e+00 L2 loss: 0.57561 Learning rate: 0.002 Mask loss: 0.09643 RPN box loss: 0.01124 RPN score loss: 0.00397 RPN total loss: 0.01521 Total loss: 0.84247 timestamp: 1655052289.1998374 iteration: 56145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11636 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.18772 L1 loss: 0.0000e+00 L2 loss: 0.5756 Learning rate: 0.002 Mask loss: 0.12921 RPN box loss: 0.00853 RPN score loss: 0.00413 RPN total loss: 0.01266 Total loss: 0.9052 timestamp: 1655052292.589697 iteration: 56150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.17382 L1 loss: 0.0000e+00 L2 loss: 0.57559 Learning rate: 0.002 Mask loss: 0.11639 RPN box loss: 0.01442 RPN score loss: 0.0063 RPN total loss: 0.02071 Total loss: 0.88652 timestamp: 1655052295.893094 iteration: 56155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07674 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.1556 L1 loss: 0.0000e+00 L2 loss: 0.57558 Learning rate: 0.002 Mask loss: 0.14007 RPN box loss: 0.01419 RPN score loss: 0.00559 RPN total loss: 0.01978 Total loss: 0.89104 timestamp: 1655052299.1457703 iteration: 56160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09842 FastRCNN class loss: 0.0473 FastRCNN total loss: 0.14572 L1 loss: 0.0000e+00 L2 loss: 0.57557 Learning rate: 0.002 Mask loss: 0.1029 RPN box loss: 0.00511 RPN score loss: 0.00327 RPN total loss: 0.00837 Total loss: 0.83257 timestamp: 1655052302.4157896 iteration: 56165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08569 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.15568 L1 loss: 0.0000e+00 L2 loss: 0.57556 Learning rate: 0.002 Mask loss: 0.15928 RPN box loss: 0.037 RPN score loss: 0.0105 RPN total loss: 0.04751 Total loss: 0.93803 timestamp: 1655052305.7021575 iteration: 56170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1189 FastRCNN class loss: 0.10939 FastRCNN total loss: 0.22829 L1 loss: 0.0000e+00 L2 loss: 0.57555 Learning rate: 0.002 Mask loss: 0.12981 RPN box loss: 0.01971 RPN score loss: 0.01277 RPN total loss: 0.03248 Total loss: 0.96614 timestamp: 1655052309.0057998 iteration: 56175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09613 FastRCNN class loss: 0.09332 FastRCNN total loss: 0.18945 L1 loss: 0.0000e+00 L2 loss: 0.57555 Learning rate: 0.002 Mask loss: 0.20823 RPN box loss: 0.01261 RPN score loss: 0.00324 RPN total loss: 0.01585 Total loss: 0.98907 timestamp: 1655052312.278095 iteration: 56180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07879 FastRCNN class loss: 0.05444 FastRCNN total loss: 0.13323 L1 loss: 0.0000e+00 L2 loss: 0.57554 Learning rate: 0.002 Mask loss: 0.10201 RPN box loss: 0.00609 RPN score loss: 0.00622 RPN total loss: 0.01232 Total loss: 0.82309 timestamp: 1655052315.5977702 iteration: 56185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13829 FastRCNN class loss: 0.14369 FastRCNN total loss: 0.28198 L1 loss: 0.0000e+00 L2 loss: 0.57553 Learning rate: 0.002 Mask loss: 0.23247 RPN box loss: 0.03662 RPN score loss: 0.00588 RPN total loss: 0.0425 Total loss: 1.13248 timestamp: 1655052318.9038904 iteration: 56190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08517 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.14318 L1 loss: 0.0000e+00 L2 loss: 0.57552 Learning rate: 0.002 Mask loss: 0.19903 RPN box loss: 0.01752 RPN score loss: 0.00607 RPN total loss: 0.02359 Total loss: 0.94133 timestamp: 1655052322.2236853 iteration: 56195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.04204 FastRCNN total loss: 0.14677 L1 loss: 0.0000e+00 L2 loss: 0.57551 Learning rate: 0.002 Mask loss: 0.12917 RPN box loss: 0.01026 RPN score loss: 0.00239 RPN total loss: 0.01265 Total loss: 0.8641 timestamp: 1655052325.486552 iteration: 56200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04805 FastRCNN class loss: 0.05119 FastRCNN total loss: 0.09924 L1 loss: 0.0000e+00 L2 loss: 0.57551 Learning rate: 0.002 Mask loss: 0.09342 RPN box loss: 0.00781 RPN score loss: 0.0034 RPN total loss: 0.01122 Total loss: 0.77939 timestamp: 1655052328.7095745 iteration: 56205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08715 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.16604 L1 loss: 0.0000e+00 L2 loss: 0.5755 Learning rate: 0.002 Mask loss: 0.11883 RPN box loss: 0.0142 RPN score loss: 0.00378 RPN total loss: 0.01797 Total loss: 0.87835 timestamp: 1655052332.009183 iteration: 56210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07522 FastRCNN class loss: 0.06177 FastRCNN total loss: 0.13699 L1 loss: 0.0000e+00 L2 loss: 0.57549 Learning rate: 0.002 Mask loss: 0.14598 RPN box loss: 0.02495 RPN score loss: 0.00367 RPN total loss: 0.02861 Total loss: 0.88708 timestamp: 1655052335.279093 iteration: 56215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11558 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.18643 L1 loss: 0.0000e+00 L2 loss: 0.57549 Learning rate: 0.002 Mask loss: 0.14256 RPN box loss: 0.0414 RPN score loss: 0.00592 RPN total loss: 0.04732 Total loss: 0.95179 timestamp: 1655052338.516189 iteration: 56220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1088 FastRCNN class loss: 0.06981 FastRCNN total loss: 0.17861 L1 loss: 0.0000e+00 L2 loss: 0.57548 Learning rate: 0.002 Mask loss: 0.16375 RPN box loss: 0.01583 RPN score loss: 0.01007 RPN total loss: 0.0259 Total loss: 0.94373 timestamp: 1655052341.810296 iteration: 56225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08981 FastRCNN class loss: 0.05393 FastRCNN total loss: 0.14374 L1 loss: 0.0000e+00 L2 loss: 0.57547 Learning rate: 0.002 Mask loss: 0.11825 RPN box loss: 0.02439 RPN score loss: 0.00663 RPN total loss: 0.03102 Total loss: 0.86849 timestamp: 1655052345.049455 iteration: 56230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11338 FastRCNN class loss: 0.08482 FastRCNN total loss: 0.1982 L1 loss: 0.0000e+00 L2 loss: 0.57546 Learning rate: 0.002 Mask loss: 0.15172 RPN box loss: 0.03901 RPN score loss: 0.00978 RPN total loss: 0.04879 Total loss: 0.97417 timestamp: 1655052348.3237727 iteration: 56235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10793 FastRCNN class loss: 0.09168 FastRCNN total loss: 0.19961 L1 loss: 0.0000e+00 L2 loss: 0.57546 Learning rate: 0.002 Mask loss: 0.15358 RPN box loss: 0.01458 RPN score loss: 0.01109 RPN total loss: 0.02566 Total loss: 0.95431 timestamp: 1655052351.6356025 iteration: 56240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15151 FastRCNN class loss: 0.10167 FastRCNN total loss: 0.25318 L1 loss: 0.0000e+00 L2 loss: 0.57545 Learning rate: 0.002 Mask loss: 0.13862 RPN box loss: 0.012 RPN score loss: 0.00993 RPN total loss: 0.02193 Total loss: 0.98917 timestamp: 1655052354.8827496 iteration: 56245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10566 FastRCNN class loss: 0.03949 FastRCNN total loss: 0.14515 L1 loss: 0.0000e+00 L2 loss: 0.57544 Learning rate: 0.002 Mask loss: 0.09984 RPN box loss: 0.00283 RPN score loss: 0.00195 RPN total loss: 0.00477 Total loss: 0.8252 timestamp: 1655052358.0955489 iteration: 56250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08575 FastRCNN class loss: 0.03784 FastRCNN total loss: 0.12359 L1 loss: 0.0000e+00 L2 loss: 0.57543 Learning rate: 0.002 Mask loss: 0.139 RPN box loss: 0.00986 RPN score loss: 0.004 RPN total loss: 0.01386 Total loss: 0.85189 timestamp: 1655052361.3224223 iteration: 56255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10738 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.15651 L1 loss: 0.0000e+00 L2 loss: 0.57543 Learning rate: 0.002 Mask loss: 0.10653 RPN box loss: 0.00589 RPN score loss: 0.00493 RPN total loss: 0.01083 Total loss: 0.8493 timestamp: 1655052364.5830185 iteration: 56260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.12037 FastRCNN total loss: 0.23094 L1 loss: 0.0000e+00 L2 loss: 0.57542 Learning rate: 0.002 Mask loss: 0.16728 RPN box loss: 0.02417 RPN score loss: 0.0033 RPN total loss: 0.02747 Total loss: 1.00111 timestamp: 1655052367.8601987 iteration: 56265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08497 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.16036 L1 loss: 0.0000e+00 L2 loss: 0.57541 Learning rate: 0.002 Mask loss: 0.15784 RPN box loss: 0.01894 RPN score loss: 0.00686 RPN total loss: 0.0258 Total loss: 0.91941 timestamp: 1655052371.142692 iteration: 56270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11117 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.17976 L1 loss: 0.0000e+00 L2 loss: 0.5754 Learning rate: 0.002 Mask loss: 0.14788 RPN box loss: 0.03246 RPN score loss: 0.00477 RPN total loss: 0.03723 Total loss: 0.94026 timestamp: 1655052374.4177158 iteration: 56275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08646 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.14577 L1 loss: 0.0000e+00 L2 loss: 0.57539 Learning rate: 0.002 Mask loss: 0.09832 RPN box loss: 0.00802 RPN score loss: 0.00503 RPN total loss: 0.01305 Total loss: 0.83254 timestamp: 1655052377.714041 iteration: 56280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06681 FastRCNN class loss: 0.04734 FastRCNN total loss: 0.11415 L1 loss: 0.0000e+00 L2 loss: 0.57538 Learning rate: 0.002 Mask loss: 0.12479 RPN box loss: 0.00488 RPN score loss: 0.00258 RPN total loss: 0.00747 Total loss: 0.82179 timestamp: 1655052381.0003943 iteration: 56285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1168 FastRCNN class loss: 0.11102 FastRCNN total loss: 0.22782 L1 loss: 0.0000e+00 L2 loss: 0.57537 Learning rate: 0.002 Mask loss: 0.14451 RPN box loss: 0.01371 RPN score loss: 0.00888 RPN total loss: 0.02259 Total loss: 0.97029 timestamp: 1655052384.3091211 iteration: 56290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08704 FastRCNN class loss: 0.05402 FastRCNN total loss: 0.14105 L1 loss: 0.0000e+00 L2 loss: 0.57537 Learning rate: 0.002 Mask loss: 0.20808 RPN box loss: 0.02468 RPN score loss: 0.01147 RPN total loss: 0.03615 Total loss: 0.96065 timestamp: 1655052387.5927756 iteration: 56295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16325 FastRCNN class loss: 0.09387 FastRCNN total loss: 0.25712 L1 loss: 0.0000e+00 L2 loss: 0.57536 Learning rate: 0.002 Mask loss: 0.14713 RPN box loss: 0.02944 RPN score loss: 0.00612 RPN total loss: 0.03556 Total loss: 1.01517 timestamp: 1655052390.8321939 iteration: 56300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.18821 L1 loss: 0.0000e+00 L2 loss: 0.57535 Learning rate: 0.002 Mask loss: 0.15971 RPN box loss: 0.02586 RPN score loss: 0.00572 RPN total loss: 0.03158 Total loss: 0.95485 timestamp: 1655052394.1351182 iteration: 56305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13419 FastRCNN class loss: 0.13742 FastRCNN total loss: 0.27161 L1 loss: 0.0000e+00 L2 loss: 0.57534 Learning rate: 0.002 Mask loss: 0.18456 RPN box loss: 0.01233 RPN score loss: 0.01121 RPN total loss: 0.02354 Total loss: 1.05506 timestamp: 1655052397.4235888 iteration: 56310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.09879 FastRCNN total loss: 0.21553 L1 loss: 0.0000e+00 L2 loss: 0.57533 Learning rate: 0.002 Mask loss: 0.24445 RPN box loss: 0.02927 RPN score loss: 0.00649 RPN total loss: 0.03576 Total loss: 1.07107 timestamp: 1655052400.658205 iteration: 56315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.14712 L1 loss: 0.0000e+00 L2 loss: 0.57533 Learning rate: 0.002 Mask loss: 0.13813 RPN box loss: 0.00676 RPN score loss: 0.00749 RPN total loss: 0.01425 Total loss: 0.87483 timestamp: 1655052403.8721354 iteration: 56320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.11553 FastRCNN total loss: 0.23227 L1 loss: 0.0000e+00 L2 loss: 0.57532 Learning rate: 0.002 Mask loss: 0.16182 RPN box loss: 0.03903 RPN score loss: 0.0052 RPN total loss: 0.04423 Total loss: 1.01364 timestamp: 1655052407.2255218 iteration: 56325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11707 FastRCNN class loss: 0.04913 FastRCNN total loss: 0.16621 L1 loss: 0.0000e+00 L2 loss: 0.57531 Learning rate: 0.002 Mask loss: 0.13768 RPN box loss: 0.00682 RPN score loss: 0.00533 RPN total loss: 0.01215 Total loss: 0.89136 timestamp: 1655052410.4467509 iteration: 56330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12055 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.19623 L1 loss: 0.0000e+00 L2 loss: 0.5753 Learning rate: 0.002 Mask loss: 0.15719 RPN box loss: 0.02548 RPN score loss: 0.00485 RPN total loss: 0.03033 Total loss: 0.95905 timestamp: 1655052413.6553757 iteration: 56335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1008 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.17097 L1 loss: 0.0000e+00 L2 loss: 0.57529 Learning rate: 0.002 Mask loss: 0.15592 RPN box loss: 0.03911 RPN score loss: 0.00719 RPN total loss: 0.04631 Total loss: 0.94849 timestamp: 1655052416.94187 iteration: 56340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04755 FastRCNN class loss: 0.0457 FastRCNN total loss: 0.09325 L1 loss: 0.0000e+00 L2 loss: 0.57528 Learning rate: 0.002 Mask loss: 0.1242 RPN box loss: 0.00393 RPN score loss: 0.00229 RPN total loss: 0.00622 Total loss: 0.79895 timestamp: 1655052420.1755543 iteration: 56345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10883 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.18133 L1 loss: 0.0000e+00 L2 loss: 0.57528 Learning rate: 0.002 Mask loss: 0.16181 RPN box loss: 0.02527 RPN score loss: 0.00662 RPN total loss: 0.03188 Total loss: 0.9503 timestamp: 1655052423.3972096 iteration: 56350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09085 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.17238 L1 loss: 0.0000e+00 L2 loss: 0.57527 Learning rate: 0.002 Mask loss: 0.1212 RPN box loss: 0.03233 RPN score loss: 0.00493 RPN total loss: 0.03726 Total loss: 0.90611 timestamp: 1655052426.6661637 iteration: 56355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.13437 FastRCNN total loss: 0.27289 L1 loss: 0.0000e+00 L2 loss: 0.57526 Learning rate: 0.002 Mask loss: 0.14857 RPN box loss: 0.02781 RPN score loss: 0.01399 RPN total loss: 0.0418 Total loss: 1.03852 timestamp: 1655052429.8806877 iteration: 56360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15736 FastRCNN class loss: 0.07125 FastRCNN total loss: 0.2286 L1 loss: 0.0000e+00 L2 loss: 0.57525 Learning rate: 0.002 Mask loss: 0.11751 RPN box loss: 0.01452 RPN score loss: 0.01188 RPN total loss: 0.0264 Total loss: 0.94776 timestamp: 1655052433.184994 iteration: 56365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11589 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.17646 L1 loss: 0.0000e+00 L2 loss: 0.57524 Learning rate: 0.002 Mask loss: 0.16189 RPN box loss: 0.01923 RPN score loss: 0.00663 RPN total loss: 0.02587 Total loss: 0.93946 timestamp: 1655052436.4353752 iteration: 56370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.097 FastRCNN total loss: 0.20636 L1 loss: 0.0000e+00 L2 loss: 0.57523 Learning rate: 0.002 Mask loss: 0.13924 RPN box loss: 0.00764 RPN score loss: 0.00211 RPN total loss: 0.00975 Total loss: 0.93058 timestamp: 1655052439.6928477 iteration: 56375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.05835 FastRCNN total loss: 0.16396 L1 loss: 0.0000e+00 L2 loss: 0.57522 Learning rate: 0.002 Mask loss: 0.12571 RPN box loss: 0.00554 RPN score loss: 0.00167 RPN total loss: 0.00721 Total loss: 0.8721 timestamp: 1655052443.025736 iteration: 56380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09377 FastRCNN class loss: 0.06594 FastRCNN total loss: 0.15971 L1 loss: 0.0000e+00 L2 loss: 0.57521 Learning rate: 0.002 Mask loss: 0.11607 RPN box loss: 0.01548 RPN score loss: 0.0026 RPN total loss: 0.01808 Total loss: 0.86907 timestamp: 1655052446.3128295 iteration: 56385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06594 FastRCNN class loss: 0.0476 FastRCNN total loss: 0.11353 L1 loss: 0.0000e+00 L2 loss: 0.57521 Learning rate: 0.002 Mask loss: 0.18508 RPN box loss: 0.01069 RPN score loss: 0.00481 RPN total loss: 0.0155 Total loss: 0.88931 timestamp: 1655052449.602879 iteration: 56390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06739 FastRCNN class loss: 0.04398 FastRCNN total loss: 0.11136 L1 loss: 0.0000e+00 L2 loss: 0.5752 Learning rate: 0.002 Mask loss: 0.15104 RPN box loss: 0.01135 RPN score loss: 0.00676 RPN total loss: 0.01811 Total loss: 0.85571 timestamp: 1655052452.9150908 iteration: 56395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07143 FastRCNN class loss: 0.08027 FastRCNN total loss: 0.1517 L1 loss: 0.0000e+00 L2 loss: 0.57519 Learning rate: 0.002 Mask loss: 0.14853 RPN box loss: 0.01152 RPN score loss: 0.00941 RPN total loss: 0.02093 Total loss: 0.89635 timestamp: 1655052456.1713145 iteration: 56400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10142 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.16587 L1 loss: 0.0000e+00 L2 loss: 0.57518 Learning rate: 0.002 Mask loss: 0.16776 RPN box loss: 0.01479 RPN score loss: 0.00385 RPN total loss: 0.01864 Total loss: 0.92745 timestamp: 1655052459.4753172 iteration: 56405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.08358 FastRCNN total loss: 0.16875 L1 loss: 0.0000e+00 L2 loss: 0.57517 Learning rate: 0.002 Mask loss: 0.15075 RPN box loss: 0.02449 RPN score loss: 0.01011 RPN total loss: 0.0346 Total loss: 0.92927 timestamp: 1655052462.735417 iteration: 56410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07532 FastRCNN class loss: 0.06924 FastRCNN total loss: 0.14456 L1 loss: 0.0000e+00 L2 loss: 0.57516 Learning rate: 0.002 Mask loss: 0.12093 RPN box loss: 0.0232 RPN score loss: 0.00208 RPN total loss: 0.02527 Total loss: 0.86593 timestamp: 1655052466.0004559 iteration: 56415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09258 FastRCNN class loss: 0.07263 FastRCNN total loss: 0.16521 L1 loss: 0.0000e+00 L2 loss: 0.57515 Learning rate: 0.002 Mask loss: 0.17938 RPN box loss: 0.02887 RPN score loss: 0.00792 RPN total loss: 0.03678 Total loss: 0.95652 timestamp: 1655052469.3050416 iteration: 56420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09365 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.14822 L1 loss: 0.0000e+00 L2 loss: 0.57514 Learning rate: 0.002 Mask loss: 0.112 RPN box loss: 0.02252 RPN score loss: 0.00159 RPN total loss: 0.02411 Total loss: 0.85947 timestamp: 1655052472.597634 iteration: 56425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11269 FastRCNN class loss: 0.09469 FastRCNN total loss: 0.20737 L1 loss: 0.0000e+00 L2 loss: 0.57514 Learning rate: 0.002 Mask loss: 0.19622 RPN box loss: 0.01642 RPN score loss: 0.00358 RPN total loss: 0.02 Total loss: 0.99873 timestamp: 1655052475.9239862 iteration: 56430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.19949 L1 loss: 0.0000e+00 L2 loss: 0.57513 Learning rate: 0.002 Mask loss: 0.12691 RPN box loss: 0.01465 RPN score loss: 0.00259 RPN total loss: 0.01724 Total loss: 0.91876 timestamp: 1655052479.198238 iteration: 56435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10999 FastRCNN class loss: 0.08719 FastRCNN total loss: 0.19718 L1 loss: 0.0000e+00 L2 loss: 0.57512 Learning rate: 0.002 Mask loss: 0.19131 RPN box loss: 0.00836 RPN score loss: 0.00352 RPN total loss: 0.01188 Total loss: 0.97549 timestamp: 1655052482.4766972 iteration: 56440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08443 FastRCNN class loss: 0.07983 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.57512 Learning rate: 0.002 Mask loss: 0.14599 RPN box loss: 0.01362 RPN score loss: 0.00407 RPN total loss: 0.01769 Total loss: 0.90305 timestamp: 1655052485.7735107 iteration: 56445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15668 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.23626 L1 loss: 0.0000e+00 L2 loss: 0.57511 Learning rate: 0.002 Mask loss: 0.1752 RPN box loss: 0.01226 RPN score loss: 0.00256 RPN total loss: 0.01481 Total loss: 1.00138 timestamp: 1655052489.0542812 iteration: 56450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12707 FastRCNN class loss: 0.104 FastRCNN total loss: 0.23107 L1 loss: 0.0000e+00 L2 loss: 0.5751 Learning rate: 0.002 Mask loss: 0.1996 RPN box loss: 0.01239 RPN score loss: 0.00606 RPN total loss: 0.01844 Total loss: 1.02422 timestamp: 1655052492.348651 iteration: 56455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09798 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.17125 L1 loss: 0.0000e+00 L2 loss: 0.57509 Learning rate: 0.002 Mask loss: 0.16255 RPN box loss: 0.0136 RPN score loss: 0.00487 RPN total loss: 0.01847 Total loss: 0.92736 timestamp: 1655052495.6442006 iteration: 56460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1284 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.20243 L1 loss: 0.0000e+00 L2 loss: 0.57508 Learning rate: 0.002 Mask loss: 0.12561 RPN box loss: 0.01718 RPN score loss: 0.0023 RPN total loss: 0.01947 Total loss: 0.9226 timestamp: 1655052498.8528132 iteration: 56465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1872 FastRCNN class loss: 0.0849 FastRCNN total loss: 0.2721 L1 loss: 0.0000e+00 L2 loss: 0.57507 Learning rate: 0.002 Mask loss: 0.15936 RPN box loss: 0.01302 RPN score loss: 0.00317 RPN total loss: 0.0162 Total loss: 1.02273 timestamp: 1655052502.1204085 iteration: 56470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0973 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.16368 L1 loss: 0.0000e+00 L2 loss: 0.57506 Learning rate: 0.002 Mask loss: 0.17991 RPN box loss: 0.00638 RPN score loss: 0.00251 RPN total loss: 0.00889 Total loss: 0.92754 timestamp: 1655052505.376009 iteration: 56475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07633 FastRCNN class loss: 0.05895 FastRCNN total loss: 0.13528 L1 loss: 0.0000e+00 L2 loss: 0.57505 Learning rate: 0.002 Mask loss: 0.11313 RPN box loss: 0.02909 RPN score loss: 0.0097 RPN total loss: 0.03879 Total loss: 0.86225 timestamp: 1655052508.6437402 iteration: 56480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12702 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.19876 L1 loss: 0.0000e+00 L2 loss: 0.57504 Learning rate: 0.002 Mask loss: 0.11196 RPN box loss: 0.0058 RPN score loss: 0.00348 RPN total loss: 0.00928 Total loss: 0.89504 timestamp: 1655052511.9420006 iteration: 56485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09279 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.14564 L1 loss: 0.0000e+00 L2 loss: 0.57504 Learning rate: 0.002 Mask loss: 0.14513 RPN box loss: 0.02052 RPN score loss: 0.00363 RPN total loss: 0.02415 Total loss: 0.88996 timestamp: 1655052515.219379 iteration: 56490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13543 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.22476 L1 loss: 0.0000e+00 L2 loss: 0.57503 Learning rate: 0.002 Mask loss: 0.15631 RPN box loss: 0.01494 RPN score loss: 0.01737 RPN total loss: 0.03231 Total loss: 0.98841 timestamp: 1655052518.4518678 iteration: 56495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16794 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.23023 L1 loss: 0.0000e+00 L2 loss: 0.57502 Learning rate: 0.002 Mask loss: 0.14647 RPN box loss: 0.01012 RPN score loss: 0.00327 RPN total loss: 0.01338 Total loss: 0.96511 timestamp: 1655052521.6787167 iteration: 56500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.079 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.12922 L1 loss: 0.0000e+00 L2 loss: 0.57501 Learning rate: 0.002 Mask loss: 0.13875 RPN box loss: 0.01759 RPN score loss: 0.00235 RPN total loss: 0.01994 Total loss: 0.86292 timestamp: 1655052524.9446008 iteration: 56505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07004 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.575 Learning rate: 0.002 Mask loss: 0.17395 RPN box loss: 0.02772 RPN score loss: 0.00957 RPN total loss: 0.03729 Total loss: 0.92457 timestamp: 1655052528.306723 iteration: 56510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15231 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.22738 L1 loss: 0.0000e+00 L2 loss: 0.57499 Learning rate: 0.002 Mask loss: 0.11833 RPN box loss: 0.01103 RPN score loss: 0.00699 RPN total loss: 0.01801 Total loss: 0.93872 timestamp: 1655052531.626743 iteration: 56515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12295 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.187 L1 loss: 0.0000e+00 L2 loss: 0.57498 Learning rate: 0.002 Mask loss: 0.15714 RPN box loss: 0.01256 RPN score loss: 0.00348 RPN total loss: 0.01604 Total loss: 0.93515 timestamp: 1655052534.9264178 iteration: 56520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10009 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.17191 L1 loss: 0.0000e+00 L2 loss: 0.57498 Learning rate: 0.002 Mask loss: 0.14276 RPN box loss: 0.0085 RPN score loss: 0.00193 RPN total loss: 0.01043 Total loss: 0.90008 timestamp: 1655052538.2200885 iteration: 56525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09358 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.15507 L1 loss: 0.0000e+00 L2 loss: 0.57497 Learning rate: 0.002 Mask loss: 0.1685 RPN box loss: 0.01271 RPN score loss: 0.00451 RPN total loss: 0.01722 Total loss: 0.91576 timestamp: 1655052541.498799 iteration: 56530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.103 FastRCNN class loss: 0.07889 FastRCNN total loss: 0.18189 L1 loss: 0.0000e+00 L2 loss: 0.57496 Learning rate: 0.002 Mask loss: 0.11702 RPN box loss: 0.00957 RPN score loss: 0.00623 RPN total loss: 0.0158 Total loss: 0.88967 timestamp: 1655052544.7087607 iteration: 56535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12987 FastRCNN class loss: 0.09305 FastRCNN total loss: 0.22292 L1 loss: 0.0000e+00 L2 loss: 0.57495 Learning rate: 0.002 Mask loss: 0.18454 RPN box loss: 0.01863 RPN score loss: 0.00416 RPN total loss: 0.02279 Total loss: 1.00521 timestamp: 1655052547.983245 iteration: 56540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09541 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.15956 L1 loss: 0.0000e+00 L2 loss: 0.57495 Learning rate: 0.002 Mask loss: 0.18686 RPN box loss: 0.00853 RPN score loss: 0.00909 RPN total loss: 0.01763 Total loss: 0.93899 timestamp: 1655052551.256748 iteration: 56545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14014 FastRCNN class loss: 0.12907 FastRCNN total loss: 0.26921 L1 loss: 0.0000e+00 L2 loss: 0.57494 Learning rate: 0.002 Mask loss: 0.21056 RPN box loss: 0.03967 RPN score loss: 0.03653 RPN total loss: 0.0762 Total loss: 1.1309 timestamp: 1655052554.5529647 iteration: 56550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09707 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.14422 L1 loss: 0.0000e+00 L2 loss: 0.57493 Learning rate: 0.002 Mask loss: 0.1206 RPN box loss: 0.01283 RPN score loss: 0.01178 RPN total loss: 0.02461 Total loss: 0.86437 timestamp: 1655052557.8256915 iteration: 56555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06253 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.11309 L1 loss: 0.0000e+00 L2 loss: 0.57492 Learning rate: 0.002 Mask loss: 0.11207 RPN box loss: 0.00546 RPN score loss: 0.00073 RPN total loss: 0.00619 Total loss: 0.80628 timestamp: 1655052561.0710585 iteration: 56560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07281 FastRCNN class loss: 0.04903 FastRCNN total loss: 0.12184 L1 loss: 0.0000e+00 L2 loss: 0.57491 Learning rate: 0.002 Mask loss: 0.13819 RPN box loss: 0.01157 RPN score loss: 0.00233 RPN total loss: 0.0139 Total loss: 0.84884 timestamp: 1655052564.3075461 iteration: 56565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05641 FastRCNN class loss: 0.04768 FastRCNN total loss: 0.10408 L1 loss: 0.0000e+00 L2 loss: 0.5749 Learning rate: 0.002 Mask loss: 0.13149 RPN box loss: 0.0279 RPN score loss: 0.00723 RPN total loss: 0.03513 Total loss: 0.8456 timestamp: 1655052567.6244018 iteration: 56570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06174 FastRCNN class loss: 0.05617 FastRCNN total loss: 0.11791 L1 loss: 0.0000e+00 L2 loss: 0.57489 Learning rate: 0.002 Mask loss: 0.12549 RPN box loss: 0.01291 RPN score loss: 0.00245 RPN total loss: 0.01536 Total loss: 0.83365 timestamp: 1655052570.8762944 iteration: 56575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06497 FastRCNN class loss: 0.04706 FastRCNN total loss: 0.11202 L1 loss: 0.0000e+00 L2 loss: 0.57489 Learning rate: 0.002 Mask loss: 0.13836 RPN box loss: 0.01784 RPN score loss: 0.00214 RPN total loss: 0.01998 Total loss: 0.84524 timestamp: 1655052574.1483436 iteration: 56580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05938 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.09884 L1 loss: 0.0000e+00 L2 loss: 0.57488 Learning rate: 0.002 Mask loss: 0.12275 RPN box loss: 0.00469 RPN score loss: 0.00172 RPN total loss: 0.00641 Total loss: 0.80288 timestamp: 1655052577.440856 iteration: 56585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10292 FastRCNN class loss: 0.09236 FastRCNN total loss: 0.19527 L1 loss: 0.0000e+00 L2 loss: 0.57487 Learning rate: 0.002 Mask loss: 0.14025 RPN box loss: 0.01957 RPN score loss: 0.00583 RPN total loss: 0.0254 Total loss: 0.9358 timestamp: 1655052580.7094352 iteration: 56590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10249 FastRCNN class loss: 0.06282 FastRCNN total loss: 0.16531 L1 loss: 0.0000e+00 L2 loss: 0.57486 Learning rate: 0.002 Mask loss: 0.16943 RPN box loss: 0.02039 RPN score loss: 0.00329 RPN total loss: 0.02368 Total loss: 0.93329 timestamp: 1655052584.0081344 iteration: 56595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13653 FastRCNN class loss: 0.07723 FastRCNN total loss: 0.21376 L1 loss: 0.0000e+00 L2 loss: 0.57486 Learning rate: 0.002 Mask loss: 0.15891 RPN box loss: 0.01386 RPN score loss: 0.00653 RPN total loss: 0.02039 Total loss: 0.96792 timestamp: 1655052587.3104925 iteration: 56600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11578 FastRCNN class loss: 0.1017 FastRCNN total loss: 0.21749 L1 loss: 0.0000e+00 L2 loss: 0.57485 Learning rate: 0.002 Mask loss: 0.13883 RPN box loss: 0.03057 RPN score loss: 0.01544 RPN total loss: 0.046 Total loss: 0.97717 timestamp: 1655052590.59811 iteration: 56605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07183 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.12548 L1 loss: 0.0000e+00 L2 loss: 0.57484 Learning rate: 0.002 Mask loss: 0.11434 RPN box loss: 0.00901 RPN score loss: 0.00327 RPN total loss: 0.01227 Total loss: 0.82694 timestamp: 1655052593.8862848 iteration: 56610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13377 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.20639 L1 loss: 0.0000e+00 L2 loss: 0.57484 Learning rate: 0.002 Mask loss: 0.11771 RPN box loss: 0.01588 RPN score loss: 0.00833 RPN total loss: 0.0242 Total loss: 0.92314 timestamp: 1655052597.219013 iteration: 56615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10326 FastRCNN class loss: 0.10594 FastRCNN total loss: 0.2092 L1 loss: 0.0000e+00 L2 loss: 0.57483 Learning rate: 0.002 Mask loss: 0.16793 RPN box loss: 0.02003 RPN score loss: 0.00925 RPN total loss: 0.02928 Total loss: 0.98123 timestamp: 1655052600.5996242 iteration: 56620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15259 FastRCNN class loss: 0.06979 FastRCNN total loss: 0.22238 L1 loss: 0.0000e+00 L2 loss: 0.57482 Learning rate: 0.002 Mask loss: 0.10894 RPN box loss: 0.01248 RPN score loss: 0.00889 RPN total loss: 0.02137 Total loss: 0.9275 timestamp: 1655052603.8532214 iteration: 56625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.1713 L1 loss: 0.0000e+00 L2 loss: 0.57481 Learning rate: 0.002 Mask loss: 0.17786 RPN box loss: 0.01699 RPN score loss: 0.00776 RPN total loss: 0.02476 Total loss: 0.94872 timestamp: 1655052607.2385237 iteration: 56630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08857 FastRCNN class loss: 0.05415 FastRCNN total loss: 0.14273 L1 loss: 0.0000e+00 L2 loss: 0.5748 Learning rate: 0.002 Mask loss: 0.22912 RPN box loss: 0.02015 RPN score loss: 0.00231 RPN total loss: 0.02246 Total loss: 0.96911 timestamp: 1655052610.5196297 iteration: 56635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07146 FastRCNN class loss: 0.04228 FastRCNN total loss: 0.11374 L1 loss: 0.0000e+00 L2 loss: 0.57479 Learning rate: 0.002 Mask loss: 0.11005 RPN box loss: 0.01185 RPN score loss: 0.00594 RPN total loss: 0.01779 Total loss: 0.81637 timestamp: 1655052613.7688081 iteration: 56640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10716 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.18476 L1 loss: 0.0000e+00 L2 loss: 0.57478 Learning rate: 0.002 Mask loss: 0.16182 RPN box loss: 0.02567 RPN score loss: 0.01237 RPN total loss: 0.03804 Total loss: 0.95939 timestamp: 1655052617.0546217 iteration: 56645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11617 FastRCNN class loss: 0.11171 FastRCNN total loss: 0.22788 L1 loss: 0.0000e+00 L2 loss: 0.57477 Learning rate: 0.002 Mask loss: 0.17683 RPN box loss: 0.02651 RPN score loss: 0.01258 RPN total loss: 0.03909 Total loss: 1.01856 timestamp: 1655052620.3086786 iteration: 56650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17978 FastRCNN class loss: 0.08729 FastRCNN total loss: 0.26707 L1 loss: 0.0000e+00 L2 loss: 0.57476 Learning rate: 0.002 Mask loss: 0.13714 RPN box loss: 0.03237 RPN score loss: 0.01024 RPN total loss: 0.04261 Total loss: 1.02158 timestamp: 1655052623.5599134 iteration: 56655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08971 FastRCNN class loss: 0.07678 FastRCNN total loss: 0.16649 L1 loss: 0.0000e+00 L2 loss: 0.57475 Learning rate: 0.002 Mask loss: 0.12514 RPN box loss: 0.01026 RPN score loss: 0.007 RPN total loss: 0.01726 Total loss: 0.88363 timestamp: 1655052626.8688316 iteration: 56660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12819 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.19054 L1 loss: 0.0000e+00 L2 loss: 0.57474 Learning rate: 0.002 Mask loss: 0.10731 RPN box loss: 0.01633 RPN score loss: 0.00345 RPN total loss: 0.01977 Total loss: 0.89236 timestamp: 1655052630.1064765 iteration: 56665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10221 FastRCNN class loss: 0.06069 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.57473 Learning rate: 0.002 Mask loss: 0.15682 RPN box loss: 0.00587 RPN score loss: 0.00156 RPN total loss: 0.00743 Total loss: 0.90189 timestamp: 1655052633.3666878 iteration: 56670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11839 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.19793 L1 loss: 0.0000e+00 L2 loss: 0.57472 Learning rate: 0.002 Mask loss: 0.15934 RPN box loss: 0.00568 RPN score loss: 0.01016 RPN total loss: 0.01584 Total loss: 0.94783 timestamp: 1655052636.715833 iteration: 56675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15253 FastRCNN class loss: 0.11008 FastRCNN total loss: 0.26262 L1 loss: 0.0000e+00 L2 loss: 0.57472 Learning rate: 0.002 Mask loss: 0.16148 RPN box loss: 0.00911 RPN score loss: 0.00246 RPN total loss: 0.01157 Total loss: 1.01038 timestamp: 1655052639.9890935 iteration: 56680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.04001 FastRCNN total loss: 0.115 L1 loss: 0.0000e+00 L2 loss: 0.57471 Learning rate: 0.002 Mask loss: 0.14703 RPN box loss: 0.01088 RPN score loss: 0.00756 RPN total loss: 0.01845 Total loss: 0.85519 timestamp: 1655052643.3165288 iteration: 56685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09448 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.17882 L1 loss: 0.0000e+00 L2 loss: 0.5747 Learning rate: 0.002 Mask loss: 0.16128 RPN box loss: 0.027 RPN score loss: 0.00486 RPN total loss: 0.03186 Total loss: 0.94666 timestamp: 1655052646.5620875 iteration: 56690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1571 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.24302 L1 loss: 0.0000e+00 L2 loss: 0.57469 Learning rate: 0.002 Mask loss: 0.12207 RPN box loss: 0.01516 RPN score loss: 0.00574 RPN total loss: 0.0209 Total loss: 0.96068 timestamp: 1655052649.8092794 iteration: 56695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14978 FastRCNN class loss: 0.08928 FastRCNN total loss: 0.23906 L1 loss: 0.0000e+00 L2 loss: 0.57469 Learning rate: 0.002 Mask loss: 0.21554 RPN box loss: 0.02047 RPN score loss: 0.00454 RPN total loss: 0.02501 Total loss: 1.0543 timestamp: 1655052653.085021 iteration: 56700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06568 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.12604 L1 loss: 0.0000e+00 L2 loss: 0.57468 Learning rate: 0.002 Mask loss: 0.1677 RPN box loss: 0.0128 RPN score loss: 0.00324 RPN total loss: 0.01604 Total loss: 0.88446 timestamp: 1655052656.415329 iteration: 56705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1083 FastRCNN class loss: 0.08761 FastRCNN total loss: 0.19591 L1 loss: 0.0000e+00 L2 loss: 0.57467 Learning rate: 0.002 Mask loss: 0.10471 RPN box loss: 0.00696 RPN score loss: 0.00344 RPN total loss: 0.0104 Total loss: 0.8857 timestamp: 1655052659.7060375 iteration: 56710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0546 FastRCNN class loss: 0.06015 FastRCNN total loss: 0.11475 L1 loss: 0.0000e+00 L2 loss: 0.57466 Learning rate: 0.002 Mask loss: 0.15945 RPN box loss: 0.07246 RPN score loss: 0.00841 RPN total loss: 0.08086 Total loss: 0.92973 timestamp: 1655052662.965106 iteration: 56715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0837 FastRCNN class loss: 0.07627 FastRCNN total loss: 0.15997 L1 loss: 0.0000e+00 L2 loss: 0.57465 Learning rate: 0.002 Mask loss: 0.15719 RPN box loss: 0.0165 RPN score loss: 0.00836 RPN total loss: 0.02485 Total loss: 0.91666 timestamp: 1655052666.1534433 iteration: 56720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09495 FastRCNN class loss: 0.08048 FastRCNN total loss: 0.17543 L1 loss: 0.0000e+00 L2 loss: 0.57464 Learning rate: 0.002 Mask loss: 0.14254 RPN box loss: 0.039 RPN score loss: 0.0015 RPN total loss: 0.0405 Total loss: 0.93312 timestamp: 1655052669.390747 iteration: 56725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08592 FastRCNN class loss: 0.07598 FastRCNN total loss: 0.1619 L1 loss: 0.0000e+00 L2 loss: 0.57464 Learning rate: 0.002 Mask loss: 0.1432 RPN box loss: 0.02252 RPN score loss: 0.0059 RPN total loss: 0.02842 Total loss: 0.90815 timestamp: 1655052672.7094245 iteration: 56730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13438 FastRCNN class loss: 0.09397 FastRCNN total loss: 0.22836 L1 loss: 0.0000e+00 L2 loss: 0.57463 Learning rate: 0.002 Mask loss: 0.22165 RPN box loss: 0.02531 RPN score loss: 0.00837 RPN total loss: 0.03368 Total loss: 1.05831 timestamp: 1655052676.1028206 iteration: 56735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10974 FastRCNN class loss: 0.06831 FastRCNN total loss: 0.17805 L1 loss: 0.0000e+00 L2 loss: 0.57462 Learning rate: 0.002 Mask loss: 0.07761 RPN box loss: 0.02481 RPN score loss: 0.00269 RPN total loss: 0.0275 Total loss: 0.85778 timestamp: 1655052679.2730348 iteration: 56740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09925 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.18601 L1 loss: 0.0000e+00 L2 loss: 0.57461 Learning rate: 0.002 Mask loss: 0.21803 RPN box loss: 0.02571 RPN score loss: 0.005 RPN total loss: 0.03071 Total loss: 1.00936 timestamp: 1655052682.532172 iteration: 56745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.03854 FastRCNN total loss: 0.15294 L1 loss: 0.0000e+00 L2 loss: 0.57461 Learning rate: 0.002 Mask loss: 0.0897 RPN box loss: 0.01 RPN score loss: 0.00475 RPN total loss: 0.01475 Total loss: 0.832 timestamp: 1655052685.8357565 iteration: 56750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15958 FastRCNN class loss: 0.11547 FastRCNN total loss: 0.27505 L1 loss: 0.0000e+00 L2 loss: 0.5746 Learning rate: 0.002 Mask loss: 0.13028 RPN box loss: 0.01357 RPN score loss: 0.00313 RPN total loss: 0.0167 Total loss: 0.99663 timestamp: 1655052689.0944023 iteration: 56755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07001 FastRCNN class loss: 0.08029 FastRCNN total loss: 0.1503 L1 loss: 0.0000e+00 L2 loss: 0.57459 Learning rate: 0.002 Mask loss: 0.12958 RPN box loss: 0.00896 RPN score loss: 0.00513 RPN total loss: 0.01409 Total loss: 0.86856 timestamp: 1655052692.3991358 iteration: 56760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07205 FastRCNN class loss: 0.03325 FastRCNN total loss: 0.1053 L1 loss: 0.0000e+00 L2 loss: 0.57458 Learning rate: 0.002 Mask loss: 0.10238 RPN box loss: 0.02846 RPN score loss: 0.00645 RPN total loss: 0.03491 Total loss: 0.81717 timestamp: 1655052695.6273358 iteration: 56765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09938 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.17611 L1 loss: 0.0000e+00 L2 loss: 0.57457 Learning rate: 0.002 Mask loss: 0.14637 RPN box loss: 0.01949 RPN score loss: 0.00396 RPN total loss: 0.02345 Total loss: 0.92051 timestamp: 1655052698.9967139 iteration: 56770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0886 FastRCNN class loss: 0.07018 FastRCNN total loss: 0.15878 L1 loss: 0.0000e+00 L2 loss: 0.57456 Learning rate: 0.002 Mask loss: 0.14226 RPN box loss: 0.02178 RPN score loss: 0.00672 RPN total loss: 0.0285 Total loss: 0.90411 timestamp: 1655052702.2297623 iteration: 56775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07372 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.17347 L1 loss: 0.0000e+00 L2 loss: 0.57455 Learning rate: 0.002 Mask loss: 0.16518 RPN box loss: 0.01563 RPN score loss: 0.00292 RPN total loss: 0.01855 Total loss: 0.93176 timestamp: 1655052705.4607549 iteration: 56780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05254 FastRCNN class loss: 0.04485 FastRCNN total loss: 0.09739 L1 loss: 0.0000e+00 L2 loss: 0.57454 Learning rate: 0.002 Mask loss: 0.21663 RPN box loss: 0.00536 RPN score loss: 0.00671 RPN total loss: 0.01207 Total loss: 0.90064 timestamp: 1655052708.7472825 iteration: 56785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.08287 FastRCNN total loss: 0.16685 L1 loss: 0.0000e+00 L2 loss: 0.57454 Learning rate: 0.002 Mask loss: 0.09366 RPN box loss: 0.01074 RPN score loss: 0.0024 RPN total loss: 0.01313 Total loss: 0.84818 timestamp: 1655052712.032134 iteration: 56790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08462 FastRCNN class loss: 0.06133 FastRCNN total loss: 0.14595 L1 loss: 0.0000e+00 L2 loss: 0.57453 Learning rate: 0.002 Mask loss: 0.12818 RPN box loss: 0.00837 RPN score loss: 0.00598 RPN total loss: 0.01435 Total loss: 0.86301 timestamp: 1655052715.2998857 iteration: 56795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11626 FastRCNN class loss: 0.10802 FastRCNN total loss: 0.22428 L1 loss: 0.0000e+00 L2 loss: 0.57452 Learning rate: 0.002 Mask loss: 0.1277 RPN box loss: 0.01321 RPN score loss: 0.00627 RPN total loss: 0.01948 Total loss: 0.94599 timestamp: 1655052718.627869 iteration: 56800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0656 FastRCNN class loss: 0.0417 FastRCNN total loss: 0.1073 L1 loss: 0.0000e+00 L2 loss: 0.57451 Learning rate: 0.002 Mask loss: 0.17125 RPN box loss: 0.0154 RPN score loss: 0.00172 RPN total loss: 0.01712 Total loss: 0.87019 timestamp: 1655052721.9296026 iteration: 56805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09401 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.14087 L1 loss: 0.0000e+00 L2 loss: 0.5745 Learning rate: 0.002 Mask loss: 0.14291 RPN box loss: 0.00721 RPN score loss: 0.00234 RPN total loss: 0.00955 Total loss: 0.86784 timestamp: 1655052725.2439852 iteration: 56810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06153 FastRCNN class loss: 0.04672 FastRCNN total loss: 0.10824 L1 loss: 0.0000e+00 L2 loss: 0.57449 Learning rate: 0.002 Mask loss: 0.18524 RPN box loss: 0.02439 RPN score loss: 0.00305 RPN total loss: 0.02744 Total loss: 0.89541 timestamp: 1655052728.4463377 iteration: 56815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08744 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.17788 L1 loss: 0.0000e+00 L2 loss: 0.57448 Learning rate: 0.002 Mask loss: 0.18739 RPN box loss: 0.01367 RPN score loss: 0.01104 RPN total loss: 0.02471 Total loss: 0.96448 timestamp: 1655052731.7690792 iteration: 56820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.05213 FastRCNN total loss: 0.14502 L1 loss: 0.0000e+00 L2 loss: 0.57448 Learning rate: 0.002 Mask loss: 0.10773 RPN box loss: 0.00449 RPN score loss: 0.00632 RPN total loss: 0.01081 Total loss: 0.83804 timestamp: 1655052734.9716275 iteration: 56825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12321 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.18344 L1 loss: 0.0000e+00 L2 loss: 0.57447 Learning rate: 0.002 Mask loss: 0.12966 RPN box loss: 0.03255 RPN score loss: 0.00104 RPN total loss: 0.03359 Total loss: 0.92117 timestamp: 1655052738.2754626 iteration: 56830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.0751 FastRCNN total loss: 0.16524 L1 loss: 0.0000e+00 L2 loss: 0.57446 Learning rate: 0.002 Mask loss: 0.10459 RPN box loss: 0.01497 RPN score loss: 0.00407 RPN total loss: 0.01905 Total loss: 0.86334 timestamp: 1655052741.5353415 iteration: 56835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12333 FastRCNN class loss: 0.09169 FastRCNN total loss: 0.21501 L1 loss: 0.0000e+00 L2 loss: 0.57446 Learning rate: 0.002 Mask loss: 0.14866 RPN box loss: 0.02111 RPN score loss: 0.0062 RPN total loss: 0.02732 Total loss: 0.96545 timestamp: 1655052744.799211 iteration: 56840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04672 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.10647 L1 loss: 0.0000e+00 L2 loss: 0.57445 Learning rate: 0.002 Mask loss: 0.1668 RPN box loss: 0.01443 RPN score loss: 0.00806 RPN total loss: 0.02249 Total loss: 0.87021 timestamp: 1655052748.0474405 iteration: 56845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13816 FastRCNN class loss: 0.09894 FastRCNN total loss: 0.23711 L1 loss: 0.0000e+00 L2 loss: 0.57444 Learning rate: 0.002 Mask loss: 0.1532 RPN box loss: 0.00574 RPN score loss: 0.00149 RPN total loss: 0.00723 Total loss: 0.97198 timestamp: 1655052751.325412 iteration: 56850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13173 FastRCNN class loss: 0.0544 FastRCNN total loss: 0.18613 L1 loss: 0.0000e+00 L2 loss: 0.57443 Learning rate: 0.002 Mask loss: 0.13201 RPN box loss: 0.00418 RPN score loss: 0.00303 RPN total loss: 0.00721 Total loss: 0.89977 timestamp: 1655052754.6005907 iteration: 56855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05607 FastRCNN class loss: 0.04392 FastRCNN total loss: 0.09999 L1 loss: 0.0000e+00 L2 loss: 0.57442 Learning rate: 0.002 Mask loss: 0.25033 RPN box loss: 0.01971 RPN score loss: 0.00214 RPN total loss: 0.02185 Total loss: 0.94658 timestamp: 1655052757.8463318 iteration: 56860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08968 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.15598 L1 loss: 0.0000e+00 L2 loss: 0.57441 Learning rate: 0.002 Mask loss: 0.12831 RPN box loss: 0.02151 RPN score loss: 0.00223 RPN total loss: 0.02374 Total loss: 0.88244 timestamp: 1655052761.058736 iteration: 56865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18261 FastRCNN class loss: 0.10046 FastRCNN total loss: 0.28307 L1 loss: 0.0000e+00 L2 loss: 0.5744 Learning rate: 0.002 Mask loss: 0.18148 RPN box loss: 0.01249 RPN score loss: 0.0079 RPN total loss: 0.02039 Total loss: 1.05934 timestamp: 1655052764.3148828 iteration: 56870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08172 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.1323 L1 loss: 0.0000e+00 L2 loss: 0.57439 Learning rate: 0.002 Mask loss: 0.15171 RPN box loss: 0.00818 RPN score loss: 0.00804 RPN total loss: 0.01622 Total loss: 0.87462 timestamp: 1655052767.6624312 iteration: 56875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09716 FastRCNN class loss: 0.05924 FastRCNN total loss: 0.15639 L1 loss: 0.0000e+00 L2 loss: 0.57438 Learning rate: 0.002 Mask loss: 0.11825 RPN box loss: 0.0153 RPN score loss: 0.00237 RPN total loss: 0.01768 Total loss: 0.8667 timestamp: 1655052770.8671322 iteration: 56880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1233 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.19307 L1 loss: 0.0000e+00 L2 loss: 0.57438 Learning rate: 0.002 Mask loss: 0.11261 RPN box loss: 0.011 RPN score loss: 0.00939 RPN total loss: 0.02039 Total loss: 0.90045 timestamp: 1655052774.1830928 iteration: 56885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07471 FastRCNN class loss: 0.04056 FastRCNN total loss: 0.11527 L1 loss: 0.0000e+00 L2 loss: 0.57437 Learning rate: 0.002 Mask loss: 0.11478 RPN box loss: 0.01614 RPN score loss: 0.00338 RPN total loss: 0.01951 Total loss: 0.82393 timestamp: 1655052777.4940348 iteration: 56890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09375 FastRCNN class loss: 0.06638 FastRCNN total loss: 0.16013 L1 loss: 0.0000e+00 L2 loss: 0.57436 Learning rate: 0.002 Mask loss: 0.10681 RPN box loss: 0.00821 RPN score loss: 0.00989 RPN total loss: 0.01811 Total loss: 0.85941 timestamp: 1655052780.8027627 iteration: 56895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09772 FastRCNN class loss: 0.09362 FastRCNN total loss: 0.19134 L1 loss: 0.0000e+00 L2 loss: 0.57435 Learning rate: 0.002 Mask loss: 0.17486 RPN box loss: 0.05942 RPN score loss: 0.0075 RPN total loss: 0.06693 Total loss: 1.00749 timestamp: 1655052784.0701287 iteration: 56900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0938 FastRCNN class loss: 0.06259 FastRCNN total loss: 0.15639 L1 loss: 0.0000e+00 L2 loss: 0.57434 Learning rate: 0.002 Mask loss: 0.158 RPN box loss: 0.03997 RPN score loss: 0.01812 RPN total loss: 0.05809 Total loss: 0.94683 timestamp: 1655052787.3048365 iteration: 56905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09513 FastRCNN class loss: 0.05962 FastRCNN total loss: 0.15475 L1 loss: 0.0000e+00 L2 loss: 0.57433 Learning rate: 0.002 Mask loss: 0.10632 RPN box loss: 0.01661 RPN score loss: 0.00223 RPN total loss: 0.01884 Total loss: 0.85424 timestamp: 1655052790.5689287 iteration: 56910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08512 FastRCNN class loss: 0.08165 FastRCNN total loss: 0.16677 L1 loss: 0.0000e+00 L2 loss: 0.57433 Learning rate: 0.002 Mask loss: 0.12799 RPN box loss: 0.00936 RPN score loss: 0.00247 RPN total loss: 0.01183 Total loss: 0.88091 timestamp: 1655052793.883947 iteration: 56915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1491 FastRCNN class loss: 0.11028 FastRCNN total loss: 0.25937 L1 loss: 0.0000e+00 L2 loss: 0.57432 Learning rate: 0.002 Mask loss: 0.18523 RPN box loss: 0.02069 RPN score loss: 0.00787 RPN total loss: 0.02856 Total loss: 1.04748 timestamp: 1655052797.0953512 iteration: 56920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06492 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.11344 L1 loss: 0.0000e+00 L2 loss: 0.57431 Learning rate: 0.002 Mask loss: 0.1241 RPN box loss: 0.01343 RPN score loss: 0.00599 RPN total loss: 0.01942 Total loss: 0.83128 timestamp: 1655052800.3273692 iteration: 56925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06293 FastRCNN class loss: 0.04731 FastRCNN total loss: 0.11024 L1 loss: 0.0000e+00 L2 loss: 0.5743 Learning rate: 0.002 Mask loss: 0.13694 RPN box loss: 0.00907 RPN score loss: 0.0042 RPN total loss: 0.01328 Total loss: 0.83476 timestamp: 1655052803.6226623 iteration: 56930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13752 FastRCNN class loss: 0.09402 FastRCNN total loss: 0.23154 L1 loss: 0.0000e+00 L2 loss: 0.57429 Learning rate: 0.002 Mask loss: 0.21336 RPN box loss: 0.01769 RPN score loss: 0.0075 RPN total loss: 0.02519 Total loss: 1.04439 timestamp: 1655052806.9308288 iteration: 56935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10166 FastRCNN class loss: 0.04482 FastRCNN total loss: 0.14647 L1 loss: 0.0000e+00 L2 loss: 0.57429 Learning rate: 0.002 Mask loss: 0.10009 RPN box loss: 0.01363 RPN score loss: 0.00183 RPN total loss: 0.01546 Total loss: 0.83631 timestamp: 1655052810.1713676 iteration: 56940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12914 FastRCNN class loss: 0.06613 FastRCNN total loss: 0.19527 L1 loss: 0.0000e+00 L2 loss: 0.57428 Learning rate: 0.002 Mask loss: 0.16404 RPN box loss: 0.02661 RPN score loss: 0.00815 RPN total loss: 0.03476 Total loss: 0.96835 timestamp: 1655052813.4445155 iteration: 56945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.10076 FastRCNN total loss: 0.17844 L1 loss: 0.0000e+00 L2 loss: 0.57427 Learning rate: 0.002 Mask loss: 0.20228 RPN box loss: 0.01368 RPN score loss: 0.00608 RPN total loss: 0.01976 Total loss: 0.97475 timestamp: 1655052816.6881611 iteration: 56950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11962 FastRCNN class loss: 0.093 FastRCNN total loss: 0.21263 L1 loss: 0.0000e+00 L2 loss: 0.57426 Learning rate: 0.002 Mask loss: 0.2056 RPN box loss: 0.01114 RPN score loss: 0.00832 RPN total loss: 0.01946 Total loss: 1.01195 timestamp: 1655052819.9590898 iteration: 56955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06737 FastRCNN class loss: 0.07091 FastRCNN total loss: 0.13828 L1 loss: 0.0000e+00 L2 loss: 0.57425 Learning rate: 0.002 Mask loss: 0.15856 RPN box loss: 0.00692 RPN score loss: 0.00992 RPN total loss: 0.01683 Total loss: 0.88793 timestamp: 1655052823.157731 iteration: 56960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1778 FastRCNN class loss: 0.06411 FastRCNN total loss: 0.24191 L1 loss: 0.0000e+00 L2 loss: 0.57424 Learning rate: 0.002 Mask loss: 0.11598 RPN box loss: 0.01067 RPN score loss: 0.00318 RPN total loss: 0.01385 Total loss: 0.94598 timestamp: 1655052826.417707 iteration: 56965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15781 FastRCNN class loss: 0.10402 FastRCNN total loss: 0.26183 L1 loss: 0.0000e+00 L2 loss: 0.57423 Learning rate: 0.002 Mask loss: 0.16584 RPN box loss: 0.02855 RPN score loss: 0.01252 RPN total loss: 0.04106 Total loss: 1.04297 timestamp: 1655052829.6520746 iteration: 56970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10466 FastRCNN class loss: 0.10672 FastRCNN total loss: 0.21138 L1 loss: 0.0000e+00 L2 loss: 0.57423 Learning rate: 0.002 Mask loss: 0.1881 RPN box loss: 0.00873 RPN score loss: 0.00213 RPN total loss: 0.01086 Total loss: 0.98457 timestamp: 1655052832.864775 iteration: 56975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07882 FastRCNN class loss: 0.06075 FastRCNN total loss: 0.13957 L1 loss: 0.0000e+00 L2 loss: 0.57422 Learning rate: 0.002 Mask loss: 0.15763 RPN box loss: 0.00947 RPN score loss: 0.00568 RPN total loss: 0.01515 Total loss: 0.88657 timestamp: 1655052836.1557872 iteration: 56980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1054 FastRCNN class loss: 0.06215 FastRCNN total loss: 0.16755 L1 loss: 0.0000e+00 L2 loss: 0.57421 Learning rate: 0.002 Mask loss: 0.14162 RPN box loss: 0.02053 RPN score loss: 0.00523 RPN total loss: 0.02576 Total loss: 0.90915 timestamp: 1655052839.4485292 iteration: 56985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.14374 L1 loss: 0.0000e+00 L2 loss: 0.5742 Learning rate: 0.002 Mask loss: 0.15118 RPN box loss: 0.01056 RPN score loss: 0.01088 RPN total loss: 0.02144 Total loss: 0.89057 timestamp: 1655052842.722103 iteration: 56990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08746 FastRCNN class loss: 0.06269 FastRCNN total loss: 0.15015 L1 loss: 0.0000e+00 L2 loss: 0.57419 Learning rate: 0.002 Mask loss: 0.14712 RPN box loss: 0.01959 RPN score loss: 0.00581 RPN total loss: 0.0254 Total loss: 0.89686 timestamp: 1655052845.8953874 iteration: 56995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16271 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.22685 L1 loss: 0.0000e+00 L2 loss: 0.57418 Learning rate: 0.002 Mask loss: 0.14247 RPN box loss: 0.01735 RPN score loss: 0.00355 RPN total loss: 0.0209 Total loss: 0.96441 timestamp: 1655052849.1637144 iteration: 57000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.09561 FastRCNN total loss: 0.22836 L1 loss: 0.0000e+00 L2 loss: 0.57418 Learning rate: 0.002 Mask loss: 0.12246 RPN box loss: 0.01149 RPN score loss: 0.00525 RPN total loss: 0.01674 Total loss: 0.94174 timestamp: 1655052852.4215975 iteration: 57005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05281 FastRCNN class loss: 0.06068 FastRCNN total loss: 0.11349 L1 loss: 0.0000e+00 L2 loss: 0.57417 Learning rate: 0.002 Mask loss: 0.1037 RPN box loss: 0.02613 RPN score loss: 0.00442 RPN total loss: 0.03055 Total loss: 0.82191 timestamp: 1655052855.71195 iteration: 57010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05572 FastRCNN class loss: 0.0548 FastRCNN total loss: 0.11053 L1 loss: 0.0000e+00 L2 loss: 0.57416 Learning rate: 0.002 Mask loss: 0.11897 RPN box loss: 0.02554 RPN score loss: 0.00395 RPN total loss: 0.02948 Total loss: 0.83314 timestamp: 1655052859.0111234 iteration: 57015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1346 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.18273 L1 loss: 0.0000e+00 L2 loss: 0.57415 Learning rate: 0.002 Mask loss: 0.09246 RPN box loss: 0.02259 RPN score loss: 0.00709 RPN total loss: 0.02969 Total loss: 0.87904 timestamp: 1655052862.29288 iteration: 57020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10577 FastRCNN class loss: 0.04405 FastRCNN total loss: 0.14982 L1 loss: 0.0000e+00 L2 loss: 0.57414 Learning rate: 0.002 Mask loss: 0.12273 RPN box loss: 0.02085 RPN score loss: 0.00338 RPN total loss: 0.02422 Total loss: 0.87092 timestamp: 1655052865.5597758 iteration: 57025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09103 FastRCNN class loss: 0.05988 FastRCNN total loss: 0.15091 L1 loss: 0.0000e+00 L2 loss: 0.57414 Learning rate: 0.002 Mask loss: 0.08213 RPN box loss: 0.01137 RPN score loss: 0.00162 RPN total loss: 0.01299 Total loss: 0.82017 timestamp: 1655052868.8375118 iteration: 57030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1023 FastRCNN class loss: 0.07518 FastRCNN total loss: 0.17748 L1 loss: 0.0000e+00 L2 loss: 0.57413 Learning rate: 0.002 Mask loss: 0.13152 RPN box loss: 0.0069 RPN score loss: 0.00337 RPN total loss: 0.01027 Total loss: 0.89339 timestamp: 1655052872.128595 iteration: 57035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10855 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.20559 L1 loss: 0.0000e+00 L2 loss: 0.57412 Learning rate: 0.002 Mask loss: 0.13959 RPN box loss: 0.01242 RPN score loss: 0.00588 RPN total loss: 0.01831 Total loss: 0.93761 timestamp: 1655052875.4636421 iteration: 57040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10537 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.16761 L1 loss: 0.0000e+00 L2 loss: 0.57411 Learning rate: 0.002 Mask loss: 0.13301 RPN box loss: 0.01199 RPN score loss: 0.00423 RPN total loss: 0.01622 Total loss: 0.89094 timestamp: 1655052878.7217402 iteration: 57045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.10403 FastRCNN total loss: 0.23176 L1 loss: 0.0000e+00 L2 loss: 0.5741 Learning rate: 0.002 Mask loss: 0.20824 RPN box loss: 0.00872 RPN score loss: 0.00976 RPN total loss: 0.01848 Total loss: 1.03259 timestamp: 1655052881.9247413 iteration: 57050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17814 FastRCNN class loss: 0.09004 FastRCNN total loss: 0.26818 L1 loss: 0.0000e+00 L2 loss: 0.57409 Learning rate: 0.002 Mask loss: 0.14989 RPN box loss: 0.02146 RPN score loss: 0.0077 RPN total loss: 0.02915 Total loss: 1.02132 timestamp: 1655052885.236762 iteration: 57055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09914 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.17852 L1 loss: 0.0000e+00 L2 loss: 0.57408 Learning rate: 0.002 Mask loss: 0.13469 RPN box loss: 0.03066 RPN score loss: 0.00677 RPN total loss: 0.03743 Total loss: 0.92472 timestamp: 1655052888.486179 iteration: 57060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11168 FastRCNN class loss: 0.06191 FastRCNN total loss: 0.17359 L1 loss: 0.0000e+00 L2 loss: 0.57408 Learning rate: 0.002 Mask loss: 0.16249 RPN box loss: 0.01255 RPN score loss: 0.00653 RPN total loss: 0.01908 Total loss: 0.92923 timestamp: 1655052891.8335 iteration: 57065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04417 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.09604 L1 loss: 0.0000e+00 L2 loss: 0.57407 Learning rate: 0.002 Mask loss: 0.14742 RPN box loss: 0.00726 RPN score loss: 0.01269 RPN total loss: 0.01996 Total loss: 0.83749 timestamp: 1655052895.1093824 iteration: 57070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.57407 Learning rate: 0.002 Mask loss: 0.21394 RPN box loss: 0.02241 RPN score loss: 0.00321 RPN total loss: 0.02562 Total loss: 0.98248 timestamp: 1655052898.4263482 iteration: 57075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06061 FastRCNN class loss: 0.05397 FastRCNN total loss: 0.11459 L1 loss: 0.0000e+00 L2 loss: 0.57406 Learning rate: 0.002 Mask loss: 0.1618 RPN box loss: 0.019 RPN score loss: 0.00263 RPN total loss: 0.02163 Total loss: 0.87207 timestamp: 1655052901.7197616 iteration: 57080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06736 FastRCNN class loss: 0.05797 FastRCNN total loss: 0.12533 L1 loss: 0.0000e+00 L2 loss: 0.57405 Learning rate: 0.002 Mask loss: 0.17736 RPN box loss: 0.00716 RPN score loss: 0.00499 RPN total loss: 0.01215 Total loss: 0.88889 timestamp: 1655052904.9598305 iteration: 57085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13604 FastRCNN class loss: 0.1204 FastRCNN total loss: 0.25644 L1 loss: 0.0000e+00 L2 loss: 0.57404 Learning rate: 0.002 Mask loss: 0.17794 RPN box loss: 0.01219 RPN score loss: 0.00153 RPN total loss: 0.01373 Total loss: 1.02215 timestamp: 1655052908.2167997 iteration: 57090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1001 FastRCNN class loss: 0.07207 FastRCNN total loss: 0.17218 L1 loss: 0.0000e+00 L2 loss: 0.57403 Learning rate: 0.002 Mask loss: 0.13072 RPN box loss: 0.01914 RPN score loss: 0.00636 RPN total loss: 0.0255 Total loss: 0.90242 timestamp: 1655052911.500307 iteration: 57095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0637 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.12734 L1 loss: 0.0000e+00 L2 loss: 0.57402 Learning rate: 0.002 Mask loss: 0.12536 RPN box loss: 0.01335 RPN score loss: 0.00796 RPN total loss: 0.02131 Total loss: 0.84803 timestamp: 1655052914.7256536 iteration: 57100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08045 FastRCNN class loss: 0.08084 FastRCNN total loss: 0.16129 L1 loss: 0.0000e+00 L2 loss: 0.57401 Learning rate: 0.002 Mask loss: 0.20161 RPN box loss: 0.02116 RPN score loss: 0.01096 RPN total loss: 0.03212 Total loss: 0.96903 timestamp: 1655052917.9574552 iteration: 57105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06576 FastRCNN class loss: 0.05085 FastRCNN total loss: 0.11661 L1 loss: 0.0000e+00 L2 loss: 0.57401 Learning rate: 0.002 Mask loss: 0.14 RPN box loss: 0.00546 RPN score loss: 0.00336 RPN total loss: 0.00882 Total loss: 0.83944 timestamp: 1655052921.253152 iteration: 57110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07952 FastRCNN class loss: 0.03659 FastRCNN total loss: 0.11611 L1 loss: 0.0000e+00 L2 loss: 0.574 Learning rate: 0.002 Mask loss: 0.08499 RPN box loss: 0.00369 RPN score loss: 0.00276 RPN total loss: 0.00645 Total loss: 0.78155 timestamp: 1655052924.5452688 iteration: 57115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12983 FastRCNN class loss: 0.05723 FastRCNN total loss: 0.18706 L1 loss: 0.0000e+00 L2 loss: 0.57399 Learning rate: 0.002 Mask loss: 0.13107 RPN box loss: 0.01333 RPN score loss: 0.01016 RPN total loss: 0.02349 Total loss: 0.9156 timestamp: 1655052927.8363404 iteration: 57120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.1835 L1 loss: 0.0000e+00 L2 loss: 0.57397 Learning rate: 0.002 Mask loss: 0.13932 RPN box loss: 0.02313 RPN score loss: 0.00915 RPN total loss: 0.03228 Total loss: 0.92908 timestamp: 1655052931.1292722 iteration: 57125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10655 FastRCNN class loss: 0.07086 FastRCNN total loss: 0.17741 L1 loss: 0.0000e+00 L2 loss: 0.57397 Learning rate: 0.002 Mask loss: 0.18414 RPN box loss: 0.01161 RPN score loss: 0.00508 RPN total loss: 0.01669 Total loss: 0.95221 timestamp: 1655052934.3870814 iteration: 57130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.06119 FastRCNN total loss: 0.18665 L1 loss: 0.0000e+00 L2 loss: 0.57396 Learning rate: 0.002 Mask loss: 0.14446 RPN box loss: 0.01332 RPN score loss: 0.00421 RPN total loss: 0.01753 Total loss: 0.92259 timestamp: 1655052937.759424 iteration: 57135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1152 FastRCNN class loss: 0.1029 FastRCNN total loss: 0.2181 L1 loss: 0.0000e+00 L2 loss: 0.57395 Learning rate: 0.002 Mask loss: 0.12757 RPN box loss: 0.05238 RPN score loss: 0.00966 RPN total loss: 0.06204 Total loss: 0.98166 timestamp: 1655052941.0665393 iteration: 57140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13745 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.21617 L1 loss: 0.0000e+00 L2 loss: 0.57394 Learning rate: 0.002 Mask loss: 0.15142 RPN box loss: 0.0143 RPN score loss: 0.00525 RPN total loss: 0.01955 Total loss: 0.96108 timestamp: 1655052944.305482 iteration: 57145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15754 FastRCNN class loss: 0.10391 FastRCNN total loss: 0.26145 L1 loss: 0.0000e+00 L2 loss: 0.57393 Learning rate: 0.002 Mask loss: 0.20782 RPN box loss: 0.02426 RPN score loss: 0.00933 RPN total loss: 0.03359 Total loss: 1.07679 timestamp: 1655052947.5551052 iteration: 57150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.06472 FastRCNN total loss: 0.16743 L1 loss: 0.0000e+00 L2 loss: 0.57392 Learning rate: 0.002 Mask loss: 0.13356 RPN box loss: 0.01823 RPN score loss: 0.00252 RPN total loss: 0.02074 Total loss: 0.89566 timestamp: 1655052950.8676193 iteration: 57155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08067 FastRCNN class loss: 0.07101 FastRCNN total loss: 0.15168 L1 loss: 0.0000e+00 L2 loss: 0.57392 Learning rate: 0.002 Mask loss: 0.11523 RPN box loss: 0.00445 RPN score loss: 0.00228 RPN total loss: 0.00673 Total loss: 0.84756 timestamp: 1655052954.118909 iteration: 57160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14307 FastRCNN class loss: 0.13651 FastRCNN total loss: 0.27959 L1 loss: 0.0000e+00 L2 loss: 0.57391 Learning rate: 0.002 Mask loss: 0.16916 RPN box loss: 0.03546 RPN score loss: 0.00911 RPN total loss: 0.04457 Total loss: 1.06723 timestamp: 1655052957.4021375 iteration: 57165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1179 FastRCNN class loss: 0.08139 FastRCNN total loss: 0.19929 L1 loss: 0.0000e+00 L2 loss: 0.5739 Learning rate: 0.002 Mask loss: 0.14527 RPN box loss: 0.01862 RPN score loss: 0.00333 RPN total loss: 0.02194 Total loss: 0.9404 timestamp: 1655052960.6905072 iteration: 57170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08982 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.15383 L1 loss: 0.0000e+00 L2 loss: 0.57389 Learning rate: 0.002 Mask loss: 0.15226 RPN box loss: 0.01001 RPN score loss: 0.00628 RPN total loss: 0.01629 Total loss: 0.89627 timestamp: 1655052963.9860973 iteration: 57175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1033 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.18687 L1 loss: 0.0000e+00 L2 loss: 0.57388 Learning rate: 0.002 Mask loss: 0.17154 RPN box loss: 0.01828 RPN score loss: 0.0071 RPN total loss: 0.02538 Total loss: 0.95768 timestamp: 1655052967.2791395 iteration: 57180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.12648 FastRCNN total loss: 0.24683 L1 loss: 0.0000e+00 L2 loss: 0.57387 Learning rate: 0.002 Mask loss: 0.14133 RPN box loss: 0.02965 RPN score loss: 0.00382 RPN total loss: 0.03347 Total loss: 0.9955 timestamp: 1655052970.5180118 iteration: 57185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10878 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.18559 L1 loss: 0.0000e+00 L2 loss: 0.57387 Learning rate: 0.002 Mask loss: 0.15098 RPN box loss: 0.01404 RPN score loss: 0.00382 RPN total loss: 0.01786 Total loss: 0.9283 timestamp: 1655052973.8515153 iteration: 57190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.064 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.12456 L1 loss: 0.0000e+00 L2 loss: 0.57386 Learning rate: 0.002 Mask loss: 0.10546 RPN box loss: 0.00734 RPN score loss: 0.00706 RPN total loss: 0.01439 Total loss: 0.81828 timestamp: 1655052977.074094 iteration: 57195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09462 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.17561 L1 loss: 0.0000e+00 L2 loss: 0.57385 Learning rate: 0.002 Mask loss: 0.1733 RPN box loss: 0.01435 RPN score loss: 0.00567 RPN total loss: 0.02002 Total loss: 0.94278 timestamp: 1655052980.327928 iteration: 57200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09343 FastRCNN class loss: 0.0933 FastRCNN total loss: 0.18673 L1 loss: 0.0000e+00 L2 loss: 0.57384 Learning rate: 0.002 Mask loss: 0.20372 RPN box loss: 0.00804 RPN score loss: 0.00574 RPN total loss: 0.01378 Total loss: 0.97808 timestamp: 1655052983.6787982 iteration: 57205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10597 FastRCNN class loss: 0.15073 FastRCNN total loss: 0.25671 L1 loss: 0.0000e+00 L2 loss: 0.57384 Learning rate: 0.002 Mask loss: 0.11017 RPN box loss: 0.00669 RPN score loss: 0.00272 RPN total loss: 0.00941 Total loss: 0.95013 timestamp: 1655052986.956049 iteration: 57210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.07536 FastRCNN total loss: 0.15386 L1 loss: 0.0000e+00 L2 loss: 0.57383 Learning rate: 0.002 Mask loss: 0.13361 RPN box loss: 0.00883 RPN score loss: 0.00328 RPN total loss: 0.01211 Total loss: 0.8734 timestamp: 1655052990.187017 iteration: 57215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.09861 FastRCNN total loss: 0.20079 L1 loss: 0.0000e+00 L2 loss: 0.57382 Learning rate: 0.002 Mask loss: 0.17495 RPN box loss: 0.0273 RPN score loss: 0.02225 RPN total loss: 0.04955 Total loss: 0.99911 timestamp: 1655052993.4544778 iteration: 57220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.08143 FastRCNN total loss: 0.15692 L1 loss: 0.0000e+00 L2 loss: 0.57382 Learning rate: 0.002 Mask loss: 0.29812 RPN box loss: 0.01444 RPN score loss: 0.00456 RPN total loss: 0.019 Total loss: 1.04785 timestamp: 1655052996.7196217 iteration: 57225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11405 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.57381 Learning rate: 0.002 Mask loss: 0.12862 RPN box loss: 0.00961 RPN score loss: 0.00301 RPN total loss: 0.01263 Total loss: 0.89532 timestamp: 1655052999.9530804 iteration: 57230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09993 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.18392 L1 loss: 0.0000e+00 L2 loss: 0.5738 Learning rate: 0.002 Mask loss: 0.21376 RPN box loss: 0.02021 RPN score loss: 0.00138 RPN total loss: 0.02159 Total loss: 0.99307 timestamp: 1655053003.2429645 iteration: 57235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15707 FastRCNN class loss: 0.07687 FastRCNN total loss: 0.23394 L1 loss: 0.0000e+00 L2 loss: 0.57379 Learning rate: 0.002 Mask loss: 0.10496 RPN box loss: 0.00568 RPN score loss: 0.00359 RPN total loss: 0.00927 Total loss: 0.92195 timestamp: 1655053006.5226119 iteration: 57240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11258 FastRCNN class loss: 0.15568 FastRCNN total loss: 0.26825 L1 loss: 0.0000e+00 L2 loss: 0.57378 Learning rate: 0.002 Mask loss: 0.21145 RPN box loss: 0.01698 RPN score loss: 0.00329 RPN total loss: 0.02027 Total loss: 1.07375 timestamp: 1655053009.8349907 iteration: 57245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11495 FastRCNN class loss: 0.07672 FastRCNN total loss: 0.19167 L1 loss: 0.0000e+00 L2 loss: 0.57377 Learning rate: 0.002 Mask loss: 0.13165 RPN box loss: 0.01453 RPN score loss: 0.00704 RPN total loss: 0.02157 Total loss: 0.91866 timestamp: 1655053013.122708 iteration: 57250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14027 FastRCNN class loss: 0.06757 FastRCNN total loss: 0.20785 L1 loss: 0.0000e+00 L2 loss: 0.57377 Learning rate: 0.002 Mask loss: 0.20508 RPN box loss: 0.03924 RPN score loss: 0.00118 RPN total loss: 0.04043 Total loss: 1.02713 timestamp: 1655053016.429808 iteration: 57255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.18859 L1 loss: 0.0000e+00 L2 loss: 0.57376 Learning rate: 0.002 Mask loss: 0.13663 RPN box loss: 0.01248 RPN score loss: 0.00606 RPN total loss: 0.01854 Total loss: 0.91752 timestamp: 1655053019.6967535 iteration: 57260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14805 FastRCNN class loss: 0.1058 FastRCNN total loss: 0.25386 L1 loss: 0.0000e+00 L2 loss: 0.57375 Learning rate: 0.002 Mask loss: 0.16289 RPN box loss: 0.04137 RPN score loss: 0.00423 RPN total loss: 0.0456 Total loss: 1.0361 timestamp: 1655053022.952051 iteration: 57265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10396 FastRCNN class loss: 0.05647 FastRCNN total loss: 0.16042 L1 loss: 0.0000e+00 L2 loss: 0.57374 Learning rate: 0.002 Mask loss: 0.10181 RPN box loss: 0.01523 RPN score loss: 0.00509 RPN total loss: 0.02032 Total loss: 0.85629 timestamp: 1655053026.2216818 iteration: 57270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07205 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.13229 L1 loss: 0.0000e+00 L2 loss: 0.57373 Learning rate: 0.002 Mask loss: 0.16864 RPN box loss: 0.00759 RPN score loss: 0.00257 RPN total loss: 0.01016 Total loss: 0.88483 timestamp: 1655053029.4737997 iteration: 57275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08441 FastRCNN class loss: 0.07029 FastRCNN total loss: 0.1547 L1 loss: 0.0000e+00 L2 loss: 0.57373 Learning rate: 0.002 Mask loss: 0.13351 RPN box loss: 0.00997 RPN score loss: 0.00177 RPN total loss: 0.01174 Total loss: 0.87367 timestamp: 1655053032.7264185 iteration: 57280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1198 FastRCNN class loss: 0.07165 FastRCNN total loss: 0.19145 L1 loss: 0.0000e+00 L2 loss: 0.57372 Learning rate: 0.002 Mask loss: 0.117 RPN box loss: 0.01788 RPN score loss: 0.00772 RPN total loss: 0.0256 Total loss: 0.90777 timestamp: 1655053036.0071263 iteration: 57285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09796 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.16493 L1 loss: 0.0000e+00 L2 loss: 0.57371 Learning rate: 0.002 Mask loss: 0.10835 RPN box loss: 0.00521 RPN score loss: 0.0032 RPN total loss: 0.00841 Total loss: 0.8554 timestamp: 1655053039.283846 iteration: 57290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11425 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.16958 L1 loss: 0.0000e+00 L2 loss: 0.5737 Learning rate: 0.002 Mask loss: 0.13706 RPN box loss: 0.0156 RPN score loss: 0.00339 RPN total loss: 0.01899 Total loss: 0.89933 timestamp: 1655053042.4728553 iteration: 57295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.08101 FastRCNN total loss: 0.15547 L1 loss: 0.0000e+00 L2 loss: 0.57369 Learning rate: 0.002 Mask loss: 0.11061 RPN box loss: 0.00757 RPN score loss: 0.00471 RPN total loss: 0.01228 Total loss: 0.85205 timestamp: 1655053045.696196 iteration: 57300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13371 FastRCNN class loss: 0.08064 FastRCNN total loss: 0.21435 L1 loss: 0.0000e+00 L2 loss: 0.57368 Learning rate: 0.002 Mask loss: 0.14581 RPN box loss: 0.01053 RPN score loss: 0.00616 RPN total loss: 0.01669 Total loss: 0.95054 timestamp: 1655053048.9832728 iteration: 57305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.16237 L1 loss: 0.0000e+00 L2 loss: 0.57368 Learning rate: 0.002 Mask loss: 0.13008 RPN box loss: 0.00933 RPN score loss: 0.00392 RPN total loss: 0.01326 Total loss: 0.87938 timestamp: 1655053052.2598639 iteration: 57310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16146 FastRCNN class loss: 0.07723 FastRCNN total loss: 0.23868 L1 loss: 0.0000e+00 L2 loss: 0.57367 Learning rate: 0.002 Mask loss: 0.15612 RPN box loss: 0.01701 RPN score loss: 0.00296 RPN total loss: 0.01997 Total loss: 0.98844 timestamp: 1655053055.5291052 iteration: 57315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05859 FastRCNN class loss: 0.05608 FastRCNN total loss: 0.11467 L1 loss: 0.0000e+00 L2 loss: 0.57366 Learning rate: 0.002 Mask loss: 0.14384 RPN box loss: 0.00878 RPN score loss: 0.00467 RPN total loss: 0.01345 Total loss: 0.84561 timestamp: 1655053058.7659357 iteration: 57320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18354 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.27208 L1 loss: 0.0000e+00 L2 loss: 0.57365 Learning rate: 0.002 Mask loss: 0.17581 RPN box loss: 0.02177 RPN score loss: 0.0099 RPN total loss: 0.03167 Total loss: 1.0532 timestamp: 1655053062.0034013 iteration: 57325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09646 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.16985 L1 loss: 0.0000e+00 L2 loss: 0.57364 Learning rate: 0.002 Mask loss: 0.10748 RPN box loss: 0.01806 RPN score loss: 0.01356 RPN total loss: 0.03162 Total loss: 0.88259 timestamp: 1655053065.2964742 iteration: 57330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15341 FastRCNN class loss: 0.13852 FastRCNN total loss: 0.29192 L1 loss: 0.0000e+00 L2 loss: 0.57363 Learning rate: 0.002 Mask loss: 0.18001 RPN box loss: 0.02502 RPN score loss: 0.01494 RPN total loss: 0.03996 Total loss: 1.08552 timestamp: 1655053068.534005 iteration: 57335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08035 FastRCNN class loss: 0.05747 FastRCNN total loss: 0.13782 L1 loss: 0.0000e+00 L2 loss: 0.57363 Learning rate: 0.002 Mask loss: 0.1945 RPN box loss: 0.00584 RPN score loss: 0.00142 RPN total loss: 0.00725 Total loss: 0.9132 timestamp: 1655053071.8075764 iteration: 57340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09838 FastRCNN class loss: 0.06373 FastRCNN total loss: 0.16211 L1 loss: 0.0000e+00 L2 loss: 0.57362 Learning rate: 0.002 Mask loss: 0.11943 RPN box loss: 0.01596 RPN score loss: 0.00324 RPN total loss: 0.0192 Total loss: 0.87436 timestamp: 1655053075.0551343 iteration: 57345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09811 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.17398 L1 loss: 0.0000e+00 L2 loss: 0.57361 Learning rate: 0.002 Mask loss: 0.16424 RPN box loss: 0.01956 RPN score loss: 0.00797 RPN total loss: 0.02753 Total loss: 0.93935 timestamp: 1655053078.3583112 iteration: 57350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07243 FastRCNN class loss: 0.0762 FastRCNN total loss: 0.14864 L1 loss: 0.0000e+00 L2 loss: 0.5736 Learning rate: 0.002 Mask loss: 0.16396 RPN box loss: 0.02228 RPN score loss: 0.00595 RPN total loss: 0.02823 Total loss: 0.91442 timestamp: 1655053081.5838826 iteration: 57355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16561 FastRCNN class loss: 0.0812 FastRCNN total loss: 0.24681 L1 loss: 0.0000e+00 L2 loss: 0.57359 Learning rate: 0.002 Mask loss: 0.17466 RPN box loss: 0.00726 RPN score loss: 0.00331 RPN total loss: 0.01057 Total loss: 1.00562 timestamp: 1655053084.8737957 iteration: 57360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08338 FastRCNN class loss: 0.07655 FastRCNN total loss: 0.15993 L1 loss: 0.0000e+00 L2 loss: 0.57358 Learning rate: 0.002 Mask loss: 0.16543 RPN box loss: 0.01718 RPN score loss: 0.00594 RPN total loss: 0.02311 Total loss: 0.92205 timestamp: 1655053088.292726 iteration: 57365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06947 FastRCNN class loss: 0.04211 FastRCNN total loss: 0.11159 L1 loss: 0.0000e+00 L2 loss: 0.57357 Learning rate: 0.002 Mask loss: 0.14514 RPN box loss: 0.00871 RPN score loss: 0.00333 RPN total loss: 0.01205 Total loss: 0.84234 timestamp: 1655053091.57633 iteration: 57370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13482 FastRCNN class loss: 0.0841 FastRCNN total loss: 0.21893 L1 loss: 0.0000e+00 L2 loss: 0.57357 Learning rate: 0.002 Mask loss: 0.11925 RPN box loss: 0.04168 RPN score loss: 0.00551 RPN total loss: 0.0472 Total loss: 0.95894 timestamp: 1655053094.8372953 iteration: 57375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10245 FastRCNN class loss: 0.04101 FastRCNN total loss: 0.14346 L1 loss: 0.0000e+00 L2 loss: 0.57356 Learning rate: 0.002 Mask loss: 0.13507 RPN box loss: 0.01662 RPN score loss: 0.009 RPN total loss: 0.02562 Total loss: 0.87772 timestamp: 1655053098.0948422 iteration: 57380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09267 FastRCNN class loss: 0.09023 FastRCNN total loss: 0.18291 L1 loss: 0.0000e+00 L2 loss: 0.57355 Learning rate: 0.002 Mask loss: 0.19137 RPN box loss: 0.0246 RPN score loss: 0.02056 RPN total loss: 0.04515 Total loss: 0.99299 timestamp: 1655053101.3370538 iteration: 57385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08576 FastRCNN class loss: 0.07488 FastRCNN total loss: 0.16063 L1 loss: 0.0000e+00 L2 loss: 0.57354 Learning rate: 0.002 Mask loss: 0.13188 RPN box loss: 0.01426 RPN score loss: 0.01179 RPN total loss: 0.02604 Total loss: 0.8921 timestamp: 1655053104.613398 iteration: 57390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09932 FastRCNN class loss: 0.076 FastRCNN total loss: 0.17532 L1 loss: 0.0000e+00 L2 loss: 0.57353 Learning rate: 0.002 Mask loss: 0.15902 RPN box loss: 0.022 RPN score loss: 0.00631 RPN total loss: 0.02831 Total loss: 0.93619 timestamp: 1655053107.946681 iteration: 57395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04781 FastRCNN class loss: 0.05339 FastRCNN total loss: 0.1012 L1 loss: 0.0000e+00 L2 loss: 0.57352 Learning rate: 0.002 Mask loss: 0.13826 RPN box loss: 0.00768 RPN score loss: 0.0012 RPN total loss: 0.00888 Total loss: 0.82186 timestamp: 1655053111.1868784 iteration: 57400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15474 FastRCNN class loss: 0.07161 FastRCNN total loss: 0.22635 L1 loss: 0.0000e+00 L2 loss: 0.57351 Learning rate: 0.002 Mask loss: 0.15866 RPN box loss: 0.00877 RPN score loss: 0.01287 RPN total loss: 0.02164 Total loss: 0.98017 timestamp: 1655053114.4926069 iteration: 57405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10117 FastRCNN class loss: 0.08368 FastRCNN total loss: 0.18484 L1 loss: 0.0000e+00 L2 loss: 0.5735 Learning rate: 0.002 Mask loss: 0.13516 RPN box loss: 0.03916 RPN score loss: 0.01379 RPN total loss: 0.05294 Total loss: 0.94645 timestamp: 1655053117.7333376 iteration: 57410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09339 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.1688 L1 loss: 0.0000e+00 L2 loss: 0.57349 Learning rate: 0.002 Mask loss: 0.13095 RPN box loss: 0.01663 RPN score loss: 0.01909 RPN total loss: 0.03573 Total loss: 0.90897 timestamp: 1655053120.9928887 iteration: 57415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05323 FastRCNN class loss: 0.03654 FastRCNN total loss: 0.08977 L1 loss: 0.0000e+00 L2 loss: 0.57348 Learning rate: 0.002 Mask loss: 0.08576 RPN box loss: 0.00981 RPN score loss: 0.00058 RPN total loss: 0.01039 Total loss: 0.7594 timestamp: 1655053124.2082512 iteration: 57420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07469 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.13152 L1 loss: 0.0000e+00 L2 loss: 0.57348 Learning rate: 0.002 Mask loss: 0.12237 RPN box loss: 0.01563 RPN score loss: 0.00301 RPN total loss: 0.01864 Total loss: 0.84601 timestamp: 1655053127.4474528 iteration: 57425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.1162 L1 loss: 0.0000e+00 L2 loss: 0.57347 Learning rate: 0.002 Mask loss: 0.11334 RPN box loss: 0.00946 RPN score loss: 0.01558 RPN total loss: 0.02504 Total loss: 0.82805 timestamp: 1655053130.8155093 iteration: 57430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09801 FastRCNN class loss: 0.05324 FastRCNN total loss: 0.15125 L1 loss: 0.0000e+00 L2 loss: 0.57347 Learning rate: 0.002 Mask loss: 0.12318 RPN box loss: 0.00939 RPN score loss: 0.00792 RPN total loss: 0.01731 Total loss: 0.86521 timestamp: 1655053134.0900724 iteration: 57435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1292 FastRCNN class loss: 0.12684 FastRCNN total loss: 0.25605 L1 loss: 0.0000e+00 L2 loss: 0.57346 Learning rate: 0.002 Mask loss: 0.1822 RPN box loss: 0.02691 RPN score loss: 0.00903 RPN total loss: 0.03594 Total loss: 1.04764 timestamp: 1655053137.3776622 iteration: 57440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07244 FastRCNN class loss: 0.05366 FastRCNN total loss: 0.1261 L1 loss: 0.0000e+00 L2 loss: 0.57345 Learning rate: 0.002 Mask loss: 0.10192 RPN box loss: 0.01244 RPN score loss: 0.00666 RPN total loss: 0.0191 Total loss: 0.82057 timestamp: 1655053140.6644647 iteration: 57445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.15814 L1 loss: 0.0000e+00 L2 loss: 0.57344 Learning rate: 0.002 Mask loss: 0.10843 RPN box loss: 0.01722 RPN score loss: 0.0011 RPN total loss: 0.01832 Total loss: 0.85833 timestamp: 1655053143.9754317 iteration: 57450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.0879 FastRCNN total loss: 0.18981 L1 loss: 0.0000e+00 L2 loss: 0.57343 Learning rate: 0.002 Mask loss: 0.21736 RPN box loss: 0.03363 RPN score loss: 0.0046 RPN total loss: 0.03823 Total loss: 1.01884 timestamp: 1655053147.2525496 iteration: 57455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05581 FastRCNN class loss: 0.0463 FastRCNN total loss: 0.1021 L1 loss: 0.0000e+00 L2 loss: 0.57343 Learning rate: 0.002 Mask loss: 0.08573 RPN box loss: 0.00695 RPN score loss: 0.00156 RPN total loss: 0.00852 Total loss: 0.76978 timestamp: 1655053150.516017 iteration: 57460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10467 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 0.57342 Learning rate: 0.002 Mask loss: 0.1115 RPN box loss: 0.01956 RPN score loss: 0.00253 RPN total loss: 0.02209 Total loss: 0.86627 timestamp: 1655053153.8040369 iteration: 57465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13402 FastRCNN class loss: 0.08386 FastRCNN total loss: 0.21787 L1 loss: 0.0000e+00 L2 loss: 0.57341 Learning rate: 0.002 Mask loss: 0.14906 RPN box loss: 0.01068 RPN score loss: 0.00552 RPN total loss: 0.01621 Total loss: 0.95654 timestamp: 1655053157.0472403 iteration: 57470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.11281 FastRCNN total loss: 0.21223 L1 loss: 0.0000e+00 L2 loss: 0.5734 Learning rate: 0.002 Mask loss: 0.18075 RPN box loss: 0.03211 RPN score loss: 0.01241 RPN total loss: 0.04452 Total loss: 1.0109 timestamp: 1655053160.3481545 iteration: 57475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11367 FastRCNN class loss: 0.12037 FastRCNN total loss: 0.23403 L1 loss: 0.0000e+00 L2 loss: 0.57339 Learning rate: 0.002 Mask loss: 0.15218 RPN box loss: 0.01603 RPN score loss: 0.00579 RPN total loss: 0.02182 Total loss: 0.98143 timestamp: 1655053163.682173 iteration: 57480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.08974 FastRCNN total loss: 0.1972 L1 loss: 0.0000e+00 L2 loss: 0.57338 Learning rate: 0.002 Mask loss: 0.1602 RPN box loss: 0.02543 RPN score loss: 0.0117 RPN total loss: 0.03714 Total loss: 0.96792 timestamp: 1655053167.0161097 iteration: 57485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08805 FastRCNN class loss: 0.06735 FastRCNN total loss: 0.1554 L1 loss: 0.0000e+00 L2 loss: 0.57338 Learning rate: 0.002 Mask loss: 0.13594 RPN box loss: 0.00631 RPN score loss: 0.00206 RPN total loss: 0.00837 Total loss: 0.87308 timestamp: 1655053170.3076642 iteration: 57490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19113 FastRCNN class loss: 0.09016 FastRCNN total loss: 0.28128 L1 loss: 0.0000e+00 L2 loss: 0.57337 Learning rate: 0.002 Mask loss: 0.18291 RPN box loss: 0.02619 RPN score loss: 0.00351 RPN total loss: 0.0297 Total loss: 1.06726 timestamp: 1655053173.5597134 iteration: 57495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.21224 L1 loss: 0.0000e+00 L2 loss: 0.57336 Learning rate: 0.002 Mask loss: 0.13685 RPN box loss: 0.01541 RPN score loss: 0.0067 RPN total loss: 0.02211 Total loss: 0.94456 timestamp: 1655053176.873297 iteration: 57500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12282 FastRCNN class loss: 0.08008 FastRCNN total loss: 0.2029 L1 loss: 0.0000e+00 L2 loss: 0.57335 Learning rate: 0.002 Mask loss: 0.11981 RPN box loss: 0.01026 RPN score loss: 0.00481 RPN total loss: 0.01507 Total loss: 0.91112 timestamp: 1655053180.1346586 iteration: 57505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14364 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.22442 L1 loss: 0.0000e+00 L2 loss: 0.57334 Learning rate: 0.002 Mask loss: 0.14944 RPN box loss: 0.01802 RPN score loss: 0.00836 RPN total loss: 0.02638 Total loss: 0.97358 timestamp: 1655053183.3777003 iteration: 57510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06935 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.12257 L1 loss: 0.0000e+00 L2 loss: 0.57333 Learning rate: 0.002 Mask loss: 0.1153 RPN box loss: 0.02833 RPN score loss: 0.00331 RPN total loss: 0.03164 Total loss: 0.84284 timestamp: 1655053186.6263313 iteration: 57515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13193 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.20873 L1 loss: 0.0000e+00 L2 loss: 0.57332 Learning rate: 0.002 Mask loss: 0.13919 RPN box loss: 0.02602 RPN score loss: 0.0156 RPN total loss: 0.04161 Total loss: 0.96286 timestamp: 1655053189.938855 iteration: 57520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1169 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.19894 L1 loss: 0.0000e+00 L2 loss: 0.57331 Learning rate: 0.002 Mask loss: 0.12549 RPN box loss: 0.0195 RPN score loss: 0.00909 RPN total loss: 0.0286 Total loss: 0.92634 timestamp: 1655053193.2317038 iteration: 57525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09835 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.14972 L1 loss: 0.0000e+00 L2 loss: 0.5733 Learning rate: 0.002 Mask loss: 0.16008 RPN box loss: 0.01395 RPN score loss: 0.0059 RPN total loss: 0.01985 Total loss: 0.90294 timestamp: 1655053196.4950707 iteration: 57530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1572 FastRCNN class loss: 0.1164 FastRCNN total loss: 0.2736 L1 loss: 0.0000e+00 L2 loss: 0.57329 Learning rate: 0.002 Mask loss: 0.19097 RPN box loss: 0.0241 RPN score loss: 0.02167 RPN total loss: 0.04577 Total loss: 1.08363 timestamp: 1655053199.665404 iteration: 57535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12637 FastRCNN class loss: 0.10787 FastRCNN total loss: 0.23424 L1 loss: 0.0000e+00 L2 loss: 0.57328 Learning rate: 0.002 Mask loss: 0.24583 RPN box loss: 0.02463 RPN score loss: 0.0089 RPN total loss: 0.03353 Total loss: 1.08689 timestamp: 1655053202.8777251 iteration: 57540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09628 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.15887 L1 loss: 0.0000e+00 L2 loss: 0.57328 Learning rate: 0.002 Mask loss: 0.11163 RPN box loss: 0.01391 RPN score loss: 0.00271 RPN total loss: 0.01662 Total loss: 0.8604 timestamp: 1655053206.099171 iteration: 57545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07999 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.14556 L1 loss: 0.0000e+00 L2 loss: 0.57327 Learning rate: 0.002 Mask loss: 0.27168 RPN box loss: 0.02929 RPN score loss: 0.00736 RPN total loss: 0.03665 Total loss: 1.02716 timestamp: 1655053209.2647948 iteration: 57550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09956 FastRCNN class loss: 0.07567 FastRCNN total loss: 0.17523 L1 loss: 0.0000e+00 L2 loss: 0.57326 Learning rate: 0.002 Mask loss: 0.09482 RPN box loss: 0.0211 RPN score loss: 0.0037 RPN total loss: 0.0248 Total loss: 0.86811 timestamp: 1655053212.6099422 iteration: 57555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07102 FastRCNN class loss: 0.08166 FastRCNN total loss: 0.15268 L1 loss: 0.0000e+00 L2 loss: 0.57325 Learning rate: 0.002 Mask loss: 0.17162 RPN box loss: 0.02407 RPN score loss: 0.00828 RPN total loss: 0.03234 Total loss: 0.9299 timestamp: 1655053215.909244 iteration: 57560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10734 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.19602 L1 loss: 0.0000e+00 L2 loss: 0.57324 Learning rate: 0.002 Mask loss: 0.21796 RPN box loss: 0.0225 RPN score loss: 0.01128 RPN total loss: 0.03378 Total loss: 1.021 timestamp: 1655053219.2476728 iteration: 57565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05864 FastRCNN class loss: 0.04164 FastRCNN total loss: 0.10028 L1 loss: 0.0000e+00 L2 loss: 0.57323 Learning rate: 0.002 Mask loss: 0.12482 RPN box loss: 0.0271 RPN score loss: 0.0059 RPN total loss: 0.033 Total loss: 0.83134 timestamp: 1655053222.556622 iteration: 57570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10431 FastRCNN class loss: 0.06022 FastRCNN total loss: 0.16453 L1 loss: 0.0000e+00 L2 loss: 0.57322 Learning rate: 0.002 Mask loss: 0.10447 RPN box loss: 0.01898 RPN score loss: 0.00174 RPN total loss: 0.02072 Total loss: 0.86295 timestamp: 1655053225.7685823 iteration: 57575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09073 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.15553 L1 loss: 0.0000e+00 L2 loss: 0.57321 Learning rate: 0.002 Mask loss: 0.14306 RPN box loss: 0.02376 RPN score loss: 0.00866 RPN total loss: 0.03242 Total loss: 0.90423 timestamp: 1655053229.0482445 iteration: 57580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.06078 FastRCNN total loss: 0.19677 L1 loss: 0.0000e+00 L2 loss: 0.57321 Learning rate: 0.002 Mask loss: 0.3448 RPN box loss: 0.03387 RPN score loss: 0.00785 RPN total loss: 0.04172 Total loss: 1.1565 timestamp: 1655053232.2948444 iteration: 57585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09129 FastRCNN class loss: 0.09947 FastRCNN total loss: 0.19077 L1 loss: 0.0000e+00 L2 loss: 0.5732 Learning rate: 0.002 Mask loss: 0.15268 RPN box loss: 0.0166 RPN score loss: 0.00437 RPN total loss: 0.02096 Total loss: 0.93761 timestamp: 1655053235.516168 iteration: 57590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07886 FastRCNN class loss: 0.05656 FastRCNN total loss: 0.13543 L1 loss: 0.0000e+00 L2 loss: 0.57319 Learning rate: 0.002 Mask loss: 0.14404 RPN box loss: 0.02161 RPN score loss: 0.00703 RPN total loss: 0.02864 Total loss: 0.8813 timestamp: 1655053238.8580742 iteration: 57595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13113 FastRCNN class loss: 0.1096 FastRCNN total loss: 0.24074 L1 loss: 0.0000e+00 L2 loss: 0.57318 Learning rate: 0.002 Mask loss: 0.16753 RPN box loss: 0.01635 RPN score loss: 0.01265 RPN total loss: 0.029 Total loss: 1.01045 timestamp: 1655053242.141302 iteration: 57600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14046 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.19182 L1 loss: 0.0000e+00 L2 loss: 0.57317 Learning rate: 0.002 Mask loss: 0.12766 RPN box loss: 0.01203 RPN score loss: 0.00238 RPN total loss: 0.01442 Total loss: 0.90707 timestamp: 1655053245.3120234 iteration: 57605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06226 FastRCNN class loss: 0.0596 FastRCNN total loss: 0.12186 L1 loss: 0.0000e+00 L2 loss: 0.57316 Learning rate: 0.002 Mask loss: 0.07103 RPN box loss: 0.00503 RPN score loss: 0.00101 RPN total loss: 0.00604 Total loss: 0.7721 timestamp: 1655053248.5124524 iteration: 57610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11972 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.17904 L1 loss: 0.0000e+00 L2 loss: 0.57316 Learning rate: 0.002 Mask loss: 0.07635 RPN box loss: 0.00894 RPN score loss: 0.00146 RPN total loss: 0.0104 Total loss: 0.83895 timestamp: 1655053251.7778325 iteration: 57615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14585 FastRCNN class loss: 0.09328 FastRCNN total loss: 0.23913 L1 loss: 0.0000e+00 L2 loss: 0.57315 Learning rate: 0.002 Mask loss: 0.16032 RPN box loss: 0.01699 RPN score loss: 0.00992 RPN total loss: 0.02691 Total loss: 0.99952 timestamp: 1655053255.0484507 iteration: 57620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05843 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.11375 L1 loss: 0.0000e+00 L2 loss: 0.57315 Learning rate: 0.002 Mask loss: 0.12753 RPN box loss: 0.03175 RPN score loss: 0.00705 RPN total loss: 0.0388 Total loss: 0.85322 timestamp: 1655053258.383446 iteration: 57625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09377 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.15277 L1 loss: 0.0000e+00 L2 loss: 0.57314 Learning rate: 0.002 Mask loss: 0.18851 RPN box loss: 0.01409 RPN score loss: 0.00874 RPN total loss: 0.02283 Total loss: 0.93725 timestamp: 1655053261.604244 iteration: 57630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1266 FastRCNN class loss: 0.09824 FastRCNN total loss: 0.22483 L1 loss: 0.0000e+00 L2 loss: 0.57313 Learning rate: 0.002 Mask loss: 0.16521 RPN box loss: 0.02544 RPN score loss: 0.00593 RPN total loss: 0.03137 Total loss: 0.99455 timestamp: 1655053264.9002728 iteration: 57635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15132 FastRCNN class loss: 0.07333 FastRCNN total loss: 0.22465 L1 loss: 0.0000e+00 L2 loss: 0.57312 Learning rate: 0.002 Mask loss: 0.15798 RPN box loss: 0.01721 RPN score loss: 0.00308 RPN total loss: 0.0203 Total loss: 0.97605 timestamp: 1655053268.1324103 iteration: 57640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11794 FastRCNN class loss: 0.07887 FastRCNN total loss: 0.19681 L1 loss: 0.0000e+00 L2 loss: 0.57311 Learning rate: 0.002 Mask loss: 0.13007 RPN box loss: 0.01477 RPN score loss: 0.0029 RPN total loss: 0.01767 Total loss: 0.91766 timestamp: 1655053271.3961408 iteration: 57645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0318 FastRCNN class loss: 0.03609 FastRCNN total loss: 0.0679 L1 loss: 0.0000e+00 L2 loss: 0.5731 Learning rate: 0.002 Mask loss: 0.12049 RPN box loss: 0.00956 RPN score loss: 0.01023 RPN total loss: 0.01979 Total loss: 0.78128 timestamp: 1655053274.686282 iteration: 57650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04289 FastRCNN class loss: 0.03188 FastRCNN total loss: 0.07477 L1 loss: 0.0000e+00 L2 loss: 0.5731 Learning rate: 0.002 Mask loss: 0.10373 RPN box loss: 0.00147 RPN score loss: 0.00174 RPN total loss: 0.00321 Total loss: 0.75481 timestamp: 1655053278.0191054 iteration: 57655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.16227 L1 loss: 0.0000e+00 L2 loss: 0.57309 Learning rate: 0.002 Mask loss: 0.11113 RPN box loss: 0.01062 RPN score loss: 0.00397 RPN total loss: 0.01459 Total loss: 0.86108 timestamp: 1655053281.3502376 iteration: 57660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10113 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.16378 L1 loss: 0.0000e+00 L2 loss: 0.57308 Learning rate: 0.002 Mask loss: 0.12049 RPN box loss: 0.01729 RPN score loss: 0.0097 RPN total loss: 0.02698 Total loss: 0.88434 timestamp: 1655053284.6279347 iteration: 57665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06371 FastRCNN class loss: 0.04074 FastRCNN total loss: 0.10445 L1 loss: 0.0000e+00 L2 loss: 0.57307 Learning rate: 0.002 Mask loss: 0.12665 RPN box loss: 0.01091 RPN score loss: 0.00184 RPN total loss: 0.01275 Total loss: 0.81692 timestamp: 1655053287.8944716 iteration: 57670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05673 FastRCNN class loss: 0.06832 FastRCNN total loss: 0.12506 L1 loss: 0.0000e+00 L2 loss: 0.57306 Learning rate: 0.002 Mask loss: 0.15572 RPN box loss: 0.01394 RPN score loss: 0.00835 RPN total loss: 0.0223 Total loss: 0.87613 timestamp: 1655053291.148095 iteration: 57675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13924 FastRCNN class loss: 0.10696 FastRCNN total loss: 0.2462 L1 loss: 0.0000e+00 L2 loss: 0.57305 Learning rate: 0.002 Mask loss: 0.15773 RPN box loss: 0.01985 RPN score loss: 0.00268 RPN total loss: 0.02253 Total loss: 0.9995 timestamp: 1655053294.408009 iteration: 57680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07656 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.12272 L1 loss: 0.0000e+00 L2 loss: 0.57304 Learning rate: 0.002 Mask loss: 0.13738 RPN box loss: 0.04542 RPN score loss: 0.00961 RPN total loss: 0.05503 Total loss: 0.88818 timestamp: 1655053297.6911757 iteration: 57685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08572 FastRCNN class loss: 0.05479 FastRCNN total loss: 0.14051 L1 loss: 0.0000e+00 L2 loss: 0.57304 Learning rate: 0.002 Mask loss: 0.13031 RPN box loss: 0.02068 RPN score loss: 0.0065 RPN total loss: 0.02718 Total loss: 0.87104 timestamp: 1655053300.9406111 iteration: 57690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.09586 FastRCNN total loss: 0.20213 L1 loss: 0.0000e+00 L2 loss: 0.57303 Learning rate: 0.002 Mask loss: 0.18596 RPN box loss: 0.0114 RPN score loss: 0.00286 RPN total loss: 0.01426 Total loss: 0.97538 timestamp: 1655053304.1844852 iteration: 57695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08913 FastRCNN class loss: 0.08339 FastRCNN total loss: 0.17253 L1 loss: 0.0000e+00 L2 loss: 0.57302 Learning rate: 0.002 Mask loss: 0.14226 RPN box loss: 0.01924 RPN score loss: 0.00412 RPN total loss: 0.02336 Total loss: 0.91117 timestamp: 1655053307.500528 iteration: 57700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10439 FastRCNN class loss: 0.06791 FastRCNN total loss: 0.1723 L1 loss: 0.0000e+00 L2 loss: 0.57302 Learning rate: 0.002 Mask loss: 0.11769 RPN box loss: 0.00784 RPN score loss: 0.00692 RPN total loss: 0.01476 Total loss: 0.87776 timestamp: 1655053310.7876728 iteration: 57705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09427 FastRCNN class loss: 0.07792 FastRCNN total loss: 0.17219 L1 loss: 0.0000e+00 L2 loss: 0.57301 Learning rate: 0.002 Mask loss: 0.17984 RPN box loss: 0.01402 RPN score loss: 0.00726 RPN total loss: 0.02128 Total loss: 0.94632 timestamp: 1655053314.04771 iteration: 57710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.06865 FastRCNN total loss: 0.15097 L1 loss: 0.0000e+00 L2 loss: 0.573 Learning rate: 0.002 Mask loss: 0.21505 RPN box loss: 0.04864 RPN score loss: 0.01611 RPN total loss: 0.06475 Total loss: 1.00377 timestamp: 1655053317.335923 iteration: 57715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12864 FastRCNN class loss: 0.05927 FastRCNN total loss: 0.1879 L1 loss: 0.0000e+00 L2 loss: 0.57299 Learning rate: 0.002 Mask loss: 0.20157 RPN box loss: 0.00814 RPN score loss: 0.00506 RPN total loss: 0.01321 Total loss: 0.97566 timestamp: 1655053320.5878184 iteration: 57720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12604 FastRCNN class loss: 0.09269 FastRCNN total loss: 0.21873 L1 loss: 0.0000e+00 L2 loss: 0.57298 Learning rate: 0.002 Mask loss: 0.17601 RPN box loss: 0.01632 RPN score loss: 0.00486 RPN total loss: 0.02118 Total loss: 0.9889 timestamp: 1655053323.8848946 iteration: 57725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05853 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.11464 L1 loss: 0.0000e+00 L2 loss: 0.57297 Learning rate: 0.002 Mask loss: 0.11234 RPN box loss: 0.00354 RPN score loss: 0.00672 RPN total loss: 0.01026 Total loss: 0.81021 timestamp: 1655053327.170279 iteration: 57730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.08804 FastRCNN total loss: 0.21861 L1 loss: 0.0000e+00 L2 loss: 0.57297 Learning rate: 0.002 Mask loss: 0.19023 RPN box loss: 0.0166 RPN score loss: 0.01928 RPN total loss: 0.03588 Total loss: 1.01768 timestamp: 1655053330.4308589 iteration: 57735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12889 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.18786 L1 loss: 0.0000e+00 L2 loss: 0.57296 Learning rate: 0.002 Mask loss: 0.09711 RPN box loss: 0.01207 RPN score loss: 0.00366 RPN total loss: 0.01573 Total loss: 0.87366 timestamp: 1655053333.709733 iteration: 57740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13094 FastRCNN class loss: 0.08711 FastRCNN total loss: 0.21805 L1 loss: 0.0000e+00 L2 loss: 0.57294 Learning rate: 0.002 Mask loss: 0.08725 RPN box loss: 0.00965 RPN score loss: 0.00526 RPN total loss: 0.0149 Total loss: 0.89315 timestamp: 1655053336.9709232 iteration: 57745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15648 FastRCNN class loss: 0.05731 FastRCNN total loss: 0.21379 L1 loss: 0.0000e+00 L2 loss: 0.57293 Learning rate: 0.002 Mask loss: 0.11026 RPN box loss: 0.0213 RPN score loss: 0.00424 RPN total loss: 0.02554 Total loss: 0.92252 timestamp: 1655053340.2899005 iteration: 57750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11231 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.16911 L1 loss: 0.0000e+00 L2 loss: 0.57292 Learning rate: 0.002 Mask loss: 0.11159 RPN box loss: 0.01864 RPN score loss: 0.00422 RPN total loss: 0.02286 Total loss: 0.87649 timestamp: 1655053343.5929327 iteration: 57755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.1372 L1 loss: 0.0000e+00 L2 loss: 0.57291 Learning rate: 0.002 Mask loss: 0.12856 RPN box loss: 0.01435 RPN score loss: 0.00886 RPN total loss: 0.02321 Total loss: 0.86188 timestamp: 1655053346.8753326 iteration: 57760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13183 FastRCNN class loss: 0.10069 FastRCNN total loss: 0.23252 L1 loss: 0.0000e+00 L2 loss: 0.5729 Learning rate: 0.002 Mask loss: 0.15773 RPN box loss: 0.02598 RPN score loss: 0.00601 RPN total loss: 0.03199 Total loss: 0.99514 timestamp: 1655053350.126897 iteration: 57765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13366 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.20889 L1 loss: 0.0000e+00 L2 loss: 0.57289 Learning rate: 0.002 Mask loss: 0.11989 RPN box loss: 0.01162 RPN score loss: 0.00504 RPN total loss: 0.01666 Total loss: 0.91832 timestamp: 1655053353.4128113 iteration: 57770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05669 FastRCNN class loss: 0.07366 FastRCNN total loss: 0.13035 L1 loss: 0.0000e+00 L2 loss: 0.57289 Learning rate: 0.002 Mask loss: 0.09186 RPN box loss: 0.02533 RPN score loss: 0.00331 RPN total loss: 0.02864 Total loss: 0.82373 timestamp: 1655053356.7174168 iteration: 57775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10708 FastRCNN class loss: 0.05646 FastRCNN total loss: 0.16355 L1 loss: 0.0000e+00 L2 loss: 0.57288 Learning rate: 0.002 Mask loss: 0.12707 RPN box loss: 0.01125 RPN score loss: 0.00477 RPN total loss: 0.01602 Total loss: 0.87952 timestamp: 1655053360.021946 iteration: 57780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15396 FastRCNN class loss: 0.06648 FastRCNN total loss: 0.22045 L1 loss: 0.0000e+00 L2 loss: 0.57288 Learning rate: 0.002 Mask loss: 0.14477 RPN box loss: 0.0196 RPN score loss: 0.00309 RPN total loss: 0.02269 Total loss: 0.96079 timestamp: 1655053363.205902 iteration: 57785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12085 FastRCNN class loss: 0.09926 FastRCNN total loss: 0.22011 L1 loss: 0.0000e+00 L2 loss: 0.57287 Learning rate: 0.002 Mask loss: 0.14532 RPN box loss: 0.0076 RPN score loss: 0.01319 RPN total loss: 0.02079 Total loss: 0.95909 timestamp: 1655053366.4944303 iteration: 57790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10119 FastRCNN class loss: 0.06811 FastRCNN total loss: 0.1693 L1 loss: 0.0000e+00 L2 loss: 0.57286 Learning rate: 0.002 Mask loss: 0.17179 RPN box loss: 0.00779 RPN score loss: 0.00766 RPN total loss: 0.01545 Total loss: 0.92941 timestamp: 1655053369.7998106 iteration: 57795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11082 FastRCNN class loss: 0.0851 FastRCNN total loss: 0.19592 L1 loss: 0.0000e+00 L2 loss: 0.57286 Learning rate: 0.002 Mask loss: 0.10425 RPN box loss: 0.01413 RPN score loss: 0.00269 RPN total loss: 0.01683 Total loss: 0.88984 timestamp: 1655053373.0600088 iteration: 57800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07376 FastRCNN class loss: 0.05141 FastRCNN total loss: 0.12517 L1 loss: 0.0000e+00 L2 loss: 0.57285 Learning rate: 0.002 Mask loss: 0.15202 RPN box loss: 0.01022 RPN score loss: 0.00946 RPN total loss: 0.01968 Total loss: 0.86972 timestamp: 1655053376.3635304 iteration: 57805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13924 FastRCNN class loss: 0.06123 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.57284 Learning rate: 0.002 Mask loss: 0.13272 RPN box loss: 0.03702 RPN score loss: 0.00359 RPN total loss: 0.04061 Total loss: 0.94664 timestamp: 1655053379.5805016 iteration: 57810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09503 FastRCNN class loss: 0.05381 FastRCNN total loss: 0.14885 L1 loss: 0.0000e+00 L2 loss: 0.57283 Learning rate: 0.002 Mask loss: 0.11484 RPN box loss: 0.00417 RPN score loss: 0.00705 RPN total loss: 0.01122 Total loss: 0.84774 timestamp: 1655053382.8643544 iteration: 57815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09835 FastRCNN class loss: 0.06911 FastRCNN total loss: 0.16746 L1 loss: 0.0000e+00 L2 loss: 0.57282 Learning rate: 0.002 Mask loss: 0.12025 RPN box loss: 0.00965 RPN score loss: 0.0047 RPN total loss: 0.01435 Total loss: 0.87488 timestamp: 1655053386.1383488 iteration: 57820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0999 FastRCNN class loss: 0.05454 FastRCNN total loss: 0.15443 L1 loss: 0.0000e+00 L2 loss: 0.57281 Learning rate: 0.002 Mask loss: 0.1356 RPN box loss: 0.01526 RPN score loss: 0.00169 RPN total loss: 0.01695 Total loss: 0.8798 timestamp: 1655053389.4002159 iteration: 57825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09056 FastRCNN class loss: 0.07626 FastRCNN total loss: 0.16682 L1 loss: 0.0000e+00 L2 loss: 0.5728 Learning rate: 0.002 Mask loss: 0.19457 RPN box loss: 0.02284 RPN score loss: 0.00392 RPN total loss: 0.02675 Total loss: 0.96094 timestamp: 1655053392.695015 iteration: 57830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09564 FastRCNN class loss: 0.05034 FastRCNN total loss: 0.14598 L1 loss: 0.0000e+00 L2 loss: 0.57279 Learning rate: 0.002 Mask loss: 0.12293 RPN box loss: 0.00868 RPN score loss: 0.00181 RPN total loss: 0.01048 Total loss: 0.85218 timestamp: 1655053395.9330962 iteration: 57835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.07757 FastRCNN total loss: 0.16603 L1 loss: 0.0000e+00 L2 loss: 0.57278 Learning rate: 0.002 Mask loss: 0.11492 RPN box loss: 0.01514 RPN score loss: 0.00195 RPN total loss: 0.01709 Total loss: 0.87083 timestamp: 1655053399.2651067 iteration: 57840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08521 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.14833 L1 loss: 0.0000e+00 L2 loss: 0.57278 Learning rate: 0.002 Mask loss: 0.1507 RPN box loss: 0.02598 RPN score loss: 0.00312 RPN total loss: 0.0291 Total loss: 0.90091 timestamp: 1655053402.5830095 iteration: 57845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11619 FastRCNN class loss: 0.07846 FastRCNN total loss: 0.19465 L1 loss: 0.0000e+00 L2 loss: 0.57277 Learning rate: 0.002 Mask loss: 0.11968 RPN box loss: 0.01158 RPN score loss: 0.00283 RPN total loss: 0.01441 Total loss: 0.9015 timestamp: 1655053405.8931913 iteration: 57850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12433 FastRCNN class loss: 0.08322 FastRCNN total loss: 0.20756 L1 loss: 0.0000e+00 L2 loss: 0.57276 Learning rate: 0.002 Mask loss: 0.15333 RPN box loss: 0.04278 RPN score loss: 0.00579 RPN total loss: 0.04857 Total loss: 0.98221 timestamp: 1655053409.1413994 iteration: 57855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10248 FastRCNN class loss: 0.03932 FastRCNN total loss: 0.1418 L1 loss: 0.0000e+00 L2 loss: 0.57275 Learning rate: 0.002 Mask loss: 0.11822 RPN box loss: 0.00956 RPN score loss: 0.00219 RPN total loss: 0.01175 Total loss: 0.84452 timestamp: 1655053412.4461613 iteration: 57860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09895 FastRCNN class loss: 0.05235 FastRCNN total loss: 0.1513 L1 loss: 0.0000e+00 L2 loss: 0.57274 Learning rate: 0.002 Mask loss: 0.12172 RPN box loss: 0.00662 RPN score loss: 0.00173 RPN total loss: 0.00835 Total loss: 0.85411 timestamp: 1655053415.785294 iteration: 57865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12578 FastRCNN class loss: 0.08553 FastRCNN total loss: 0.21131 L1 loss: 0.0000e+00 L2 loss: 0.57273 Learning rate: 0.002 Mask loss: 0.14395 RPN box loss: 0.02283 RPN score loss: 0.00867 RPN total loss: 0.0315 Total loss: 0.95949 timestamp: 1655053419.0755525 iteration: 57870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.14142 L1 loss: 0.0000e+00 L2 loss: 0.57273 Learning rate: 0.002 Mask loss: 0.14839 RPN box loss: 0.0108 RPN score loss: 0.00629 RPN total loss: 0.01709 Total loss: 0.87963 timestamp: 1655053422.3394823 iteration: 57875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.14804 L1 loss: 0.0000e+00 L2 loss: 0.57272 Learning rate: 0.002 Mask loss: 0.12588 RPN box loss: 0.01566 RPN score loss: 0.00232 RPN total loss: 0.01797 Total loss: 0.86461 timestamp: 1655053425.6278648 iteration: 57880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07463 FastRCNN class loss: 0.05592 FastRCNN total loss: 0.13055 L1 loss: 0.0000e+00 L2 loss: 0.57271 Learning rate: 0.002 Mask loss: 0.17204 RPN box loss: 0.00732 RPN score loss: 0.00368 RPN total loss: 0.011 Total loss: 0.88631 timestamp: 1655053428.9838266 iteration: 57885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.06009 FastRCNN total loss: 0.14636 L1 loss: 0.0000e+00 L2 loss: 0.5727 Learning rate: 0.002 Mask loss: 0.19453 RPN box loss: 0.01772 RPN score loss: 0.00433 RPN total loss: 0.02205 Total loss: 0.93565 timestamp: 1655053432.2688766 iteration: 57890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11635 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.18323 L1 loss: 0.0000e+00 L2 loss: 0.57269 Learning rate: 0.002 Mask loss: 0.14828 RPN box loss: 0.02057 RPN score loss: 0.00192 RPN total loss: 0.02249 Total loss: 0.92669 timestamp: 1655053435.5289035 iteration: 57895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08517 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.13871 L1 loss: 0.0000e+00 L2 loss: 0.57268 Learning rate: 0.002 Mask loss: 0.12488 RPN box loss: 0.02977 RPN score loss: 0.00672 RPN total loss: 0.03649 Total loss: 0.87277 timestamp: 1655053438.7796016 iteration: 57900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07019 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.14981 L1 loss: 0.0000e+00 L2 loss: 0.57268 Learning rate: 0.002 Mask loss: 0.14402 RPN box loss: 0.00501 RPN score loss: 0.00361 RPN total loss: 0.00862 Total loss: 0.87513 timestamp: 1655053442.0705364 iteration: 57905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10373 FastRCNN class loss: 0.09502 FastRCNN total loss: 0.19874 L1 loss: 0.0000e+00 L2 loss: 0.57267 Learning rate: 0.002 Mask loss: 0.13942 RPN box loss: 0.01879 RPN score loss: 0.01196 RPN total loss: 0.03075 Total loss: 0.94158 timestamp: 1655053445.2535286 iteration: 57910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06722 FastRCNN class loss: 0.04356 FastRCNN total loss: 0.11078 L1 loss: 0.0000e+00 L2 loss: 0.57266 Learning rate: 0.002 Mask loss: 0.11597 RPN box loss: 0.00539 RPN score loss: 0.00178 RPN total loss: 0.00717 Total loss: 0.80658 timestamp: 1655053448.5538 iteration: 57915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13461 FastRCNN class loss: 0.0599 FastRCNN total loss: 0.19451 L1 loss: 0.0000e+00 L2 loss: 0.57265 Learning rate: 0.002 Mask loss: 0.13866 RPN box loss: 0.02732 RPN score loss: 0.00228 RPN total loss: 0.0296 Total loss: 0.93542 timestamp: 1655053451.810069 iteration: 57920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10944 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.16406 L1 loss: 0.0000e+00 L2 loss: 0.57264 Learning rate: 0.002 Mask loss: 0.11847 RPN box loss: 0.00916 RPN score loss: 0.00126 RPN total loss: 0.01042 Total loss: 0.86559 timestamp: 1655053455.0458548 iteration: 57925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08499 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.14256 L1 loss: 0.0000e+00 L2 loss: 0.57263 Learning rate: 0.002 Mask loss: 0.13617 RPN box loss: 0.00413 RPN score loss: 0.00358 RPN total loss: 0.00771 Total loss: 0.85908 timestamp: 1655053458.308482 iteration: 57930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09245 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.15854 L1 loss: 0.0000e+00 L2 loss: 0.57262 Learning rate: 0.002 Mask loss: 0.14275 RPN box loss: 0.00871 RPN score loss: 0.00517 RPN total loss: 0.01389 Total loss: 0.8878 timestamp: 1655053461.648487 iteration: 57935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07477 FastRCNN class loss: 0.05831 FastRCNN total loss: 0.13308 L1 loss: 0.0000e+00 L2 loss: 0.57262 Learning rate: 0.002 Mask loss: 0.11274 RPN box loss: 0.0083 RPN score loss: 0.00467 RPN total loss: 0.01297 Total loss: 0.8314 timestamp: 1655053464.9595108 iteration: 57940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.07708 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.57261 Learning rate: 0.002 Mask loss: 0.12101 RPN box loss: 0.00352 RPN score loss: 0.00137 RPN total loss: 0.00489 Total loss: 0.86158 timestamp: 1655053468.2279596 iteration: 57945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09337 FastRCNN class loss: 0.05853 FastRCNN total loss: 0.1519 L1 loss: 0.0000e+00 L2 loss: 0.5726 Learning rate: 0.002 Mask loss: 0.12315 RPN box loss: 0.01785 RPN score loss: 0.00197 RPN total loss: 0.01982 Total loss: 0.86748 timestamp: 1655053471.529952 iteration: 57950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07317 FastRCNN class loss: 0.03915 FastRCNN total loss: 0.11232 L1 loss: 0.0000e+00 L2 loss: 0.57259 Learning rate: 0.002 Mask loss: 0.10665 RPN box loss: 0.00542 RPN score loss: 0.00262 RPN total loss: 0.00804 Total loss: 0.7996 timestamp: 1655053474.7395742 iteration: 57955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12229 FastRCNN class loss: 0.074 FastRCNN total loss: 0.19629 L1 loss: 0.0000e+00 L2 loss: 0.57258 Learning rate: 0.002 Mask loss: 0.14117 RPN box loss: 0.01599 RPN score loss: 0.0046 RPN total loss: 0.02059 Total loss: 0.93064 timestamp: 1655053477.9728642 iteration: 57960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15998 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.22769 L1 loss: 0.0000e+00 L2 loss: 0.57258 Learning rate: 0.002 Mask loss: 0.14906 RPN box loss: 0.05953 RPN score loss: 0.00653 RPN total loss: 0.06606 Total loss: 1.01538 timestamp: 1655053481.2807472 iteration: 57965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09739 FastRCNN class loss: 0.0539 FastRCNN total loss: 0.1513 L1 loss: 0.0000e+00 L2 loss: 0.57257 Learning rate: 0.002 Mask loss: 0.09838 RPN box loss: 0.00491 RPN score loss: 0.0061 RPN total loss: 0.01101 Total loss: 0.83326 timestamp: 1655053484.5811234 iteration: 57970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09124 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.14804 L1 loss: 0.0000e+00 L2 loss: 0.57257 Learning rate: 0.002 Mask loss: 0.14419 RPN box loss: 0.01433 RPN score loss: 0.00561 RPN total loss: 0.01994 Total loss: 0.88473 timestamp: 1655053487.8540375 iteration: 57975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12131 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.19609 L1 loss: 0.0000e+00 L2 loss: 0.57256 Learning rate: 0.002 Mask loss: 0.13549 RPN box loss: 0.02294 RPN score loss: 0.00593 RPN total loss: 0.02887 Total loss: 0.933 timestamp: 1655053491.016027 iteration: 57980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.17023 L1 loss: 0.0000e+00 L2 loss: 0.57255 Learning rate: 0.002 Mask loss: 0.13194 RPN box loss: 0.01566 RPN score loss: 0.00455 RPN total loss: 0.02021 Total loss: 0.89492 timestamp: 1655053494.2595792 iteration: 57985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13732 FastRCNN class loss: 0.07374 FastRCNN total loss: 0.21106 L1 loss: 0.0000e+00 L2 loss: 0.57254 Learning rate: 0.002 Mask loss: 0.14409 RPN box loss: 0.01132 RPN score loss: 0.00514 RPN total loss: 0.01647 Total loss: 0.94416 timestamp: 1655053497.5373683 iteration: 57990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12256 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.20019 L1 loss: 0.0000e+00 L2 loss: 0.57253 Learning rate: 0.002 Mask loss: 0.11713 RPN box loss: 0.02588 RPN score loss: 0.01132 RPN total loss: 0.03719 Total loss: 0.92703 timestamp: 1655053500.8125434 iteration: 57995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.07952 FastRCNN total loss: 0.16554 L1 loss: 0.0000e+00 L2 loss: 0.57252 Learning rate: 0.002 Mask loss: 0.14474 RPN box loss: 0.02435 RPN score loss: 0.00652 RPN total loss: 0.03087 Total loss: 0.91367 timestamp: 1655053504.089618 iteration: 58000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10054 FastRCNN class loss: 0.05204 FastRCNN total loss: 0.15258 L1 loss: 0.0000e+00 L2 loss: 0.57251 Learning rate: 0.002 Mask loss: 0.17139 RPN box loss: 0.00914 RPN score loss: 0.00319 RPN total loss: 0.01232 Total loss: 0.90881 timestamp: 1655053507.3450072 iteration: 58005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.16558 L1 loss: 0.0000e+00 L2 loss: 0.5725 Learning rate: 0.002 Mask loss: 0.09879 RPN box loss: 0.01116 RPN score loss: 0.00175 RPN total loss: 0.01292 Total loss: 0.84979 timestamp: 1655053510.6066887 iteration: 58010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11905 FastRCNN class loss: 0.07127 FastRCNN total loss: 0.19032 L1 loss: 0.0000e+00 L2 loss: 0.5725 Learning rate: 0.002 Mask loss: 0.14142 RPN box loss: 0.04481 RPN score loss: 0.00501 RPN total loss: 0.04982 Total loss: 0.95406 timestamp: 1655053513.865823 iteration: 58015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09413 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.17141 L1 loss: 0.0000e+00 L2 loss: 0.57249 Learning rate: 0.002 Mask loss: 0.09472 RPN box loss: 0.02034 RPN score loss: 0.00454 RPN total loss: 0.02489 Total loss: 0.8635 timestamp: 1655053517.1998675 iteration: 58020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0947 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.16835 L1 loss: 0.0000e+00 L2 loss: 0.57248 Learning rate: 0.002 Mask loss: 0.14336 RPN box loss: 0.01056 RPN score loss: 0.00596 RPN total loss: 0.01652 Total loss: 0.90071 timestamp: 1655053520.443369 iteration: 58025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17142 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.2601 L1 loss: 0.0000e+00 L2 loss: 0.57247 Learning rate: 0.002 Mask loss: 0.16828 RPN box loss: 0.02482 RPN score loss: 0.01145 RPN total loss: 0.03627 Total loss: 1.03712 timestamp: 1655053523.7414715 iteration: 58030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16135 FastRCNN class loss: 0.0818 FastRCNN total loss: 0.24315 L1 loss: 0.0000e+00 L2 loss: 0.57247 Learning rate: 0.002 Mask loss: 0.13391 RPN box loss: 0.01004 RPN score loss: 0.01082 RPN total loss: 0.02085 Total loss: 0.97038 timestamp: 1655053526.9486864 iteration: 58035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09682 FastRCNN class loss: 0.10902 FastRCNN total loss: 0.20584 L1 loss: 0.0000e+00 L2 loss: 0.57246 Learning rate: 0.002 Mask loss: 0.15391 RPN box loss: 0.02926 RPN score loss: 0.0176 RPN total loss: 0.04686 Total loss: 0.97907 timestamp: 1655053530.232135 iteration: 58040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07367 FastRCNN class loss: 0.05321 FastRCNN total loss: 0.12688 L1 loss: 0.0000e+00 L2 loss: 0.57245 Learning rate: 0.002 Mask loss: 0.08722 RPN box loss: 0.00778 RPN score loss: 0.00111 RPN total loss: 0.00889 Total loss: 0.79544 timestamp: 1655053533.4786181 iteration: 58045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12294 FastRCNN class loss: 0.09683 FastRCNN total loss: 0.21977 L1 loss: 0.0000e+00 L2 loss: 0.57244 Learning rate: 0.002 Mask loss: 0.15252 RPN box loss: 0.013 RPN score loss: 0.00566 RPN total loss: 0.01866 Total loss: 0.96339 timestamp: 1655053536.6902306 iteration: 58050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09916 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.15656 L1 loss: 0.0000e+00 L2 loss: 0.57243 Learning rate: 0.002 Mask loss: 0.13625 RPN box loss: 0.00518 RPN score loss: 0.00295 RPN total loss: 0.00814 Total loss: 0.87338 timestamp: 1655053539.9884148 iteration: 58055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08833 FastRCNN class loss: 0.05192 FastRCNN total loss: 0.14025 L1 loss: 0.0000e+00 L2 loss: 0.57242 Learning rate: 0.002 Mask loss: 0.16803 RPN box loss: 0.02273 RPN score loss: 0.00291 RPN total loss: 0.02565 Total loss: 0.90634 timestamp: 1655053543.2710745 iteration: 58060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06533 FastRCNN class loss: 0.07109 FastRCNN total loss: 0.13642 L1 loss: 0.0000e+00 L2 loss: 0.57241 Learning rate: 0.002 Mask loss: 0.08436 RPN box loss: 0.00771 RPN score loss: 0.00161 RPN total loss: 0.00932 Total loss: 0.80251 timestamp: 1655053546.5486207 iteration: 58065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18481 FastRCNN class loss: 0.12181 FastRCNN total loss: 0.30662 L1 loss: 0.0000e+00 L2 loss: 0.57241 Learning rate: 0.002 Mask loss: 0.15923 RPN box loss: 0.03236 RPN score loss: 0.0057 RPN total loss: 0.03806 Total loss: 1.07632 timestamp: 1655053549.819858 iteration: 58070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05324 FastRCNN class loss: 0.08517 FastRCNN total loss: 0.1384 L1 loss: 0.0000e+00 L2 loss: 0.5724 Learning rate: 0.002 Mask loss: 0.17714 RPN box loss: 0.02124 RPN score loss: 0.00633 RPN total loss: 0.02756 Total loss: 0.91551 timestamp: 1655053553.1362154 iteration: 58075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11481 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.19961 L1 loss: 0.0000e+00 L2 loss: 0.57239 Learning rate: 0.002 Mask loss: 0.18242 RPN box loss: 0.01336 RPN score loss: 0.00152 RPN total loss: 0.01488 Total loss: 0.9693 timestamp: 1655053556.4282217 iteration: 58080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11459 FastRCNN class loss: 0.09463 FastRCNN total loss: 0.20922 L1 loss: 0.0000e+00 L2 loss: 0.57238 Learning rate: 0.002 Mask loss: 0.17103 RPN box loss: 0.01964 RPN score loss: 0.00656 RPN total loss: 0.02621 Total loss: 0.97884 timestamp: 1655053559.7152615 iteration: 58085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04606 FastRCNN class loss: 0.05335 FastRCNN total loss: 0.0994 L1 loss: 0.0000e+00 L2 loss: 0.57237 Learning rate: 0.002 Mask loss: 0.30529 RPN box loss: 0.0092 RPN score loss: 0.00106 RPN total loss: 0.01026 Total loss: 0.98733 timestamp: 1655053563.0330641 iteration: 58090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1022 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.15503 L1 loss: 0.0000e+00 L2 loss: 0.57237 Learning rate: 0.002 Mask loss: 0.12165 RPN box loss: 0.01004 RPN score loss: 0.00612 RPN total loss: 0.01615 Total loss: 0.8652 timestamp: 1655053566.292222 iteration: 58095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05529 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.11339 L1 loss: 0.0000e+00 L2 loss: 0.57236 Learning rate: 0.002 Mask loss: 0.10011 RPN box loss: 0.03251 RPN score loss: 0.00628 RPN total loss: 0.03879 Total loss: 0.82465 timestamp: 1655053569.6057723 iteration: 58100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06281 FastRCNN class loss: 0.05542 FastRCNN total loss: 0.11823 L1 loss: 0.0000e+00 L2 loss: 0.57235 Learning rate: 0.002 Mask loss: 0.11106 RPN box loss: 0.01968 RPN score loss: 0.0039 RPN total loss: 0.02358 Total loss: 0.82521 timestamp: 1655053572.8553782 iteration: 58105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10364 FastRCNN class loss: 0.10796 FastRCNN total loss: 0.2116 L1 loss: 0.0000e+00 L2 loss: 0.57234 Learning rate: 0.002 Mask loss: 0.19923 RPN box loss: 0.04539 RPN score loss: 0.01747 RPN total loss: 0.06286 Total loss: 1.04603 timestamp: 1655053576.056884 iteration: 58110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08918 FastRCNN class loss: 0.06328 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 0.57233 Learning rate: 0.002 Mask loss: 0.13584 RPN box loss: 0.01255 RPN score loss: 0.00242 RPN total loss: 0.01497 Total loss: 0.8756 timestamp: 1655053579.3417325 iteration: 58115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09204 FastRCNN class loss: 0.08261 FastRCNN total loss: 0.17465 L1 loss: 0.0000e+00 L2 loss: 0.57232 Learning rate: 0.002 Mask loss: 0.13324 RPN box loss: 0.00918 RPN score loss: 0.00358 RPN total loss: 0.01276 Total loss: 0.89297 timestamp: 1655053582.551016 iteration: 58120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08204 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.13416 L1 loss: 0.0000e+00 L2 loss: 0.57231 Learning rate: 0.002 Mask loss: 0.144 RPN box loss: 0.01402 RPN score loss: 0.00373 RPN total loss: 0.01775 Total loss: 0.86822 timestamp: 1655053585.864549 iteration: 58125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14595 FastRCNN class loss: 0.14078 FastRCNN total loss: 0.28673 L1 loss: 0.0000e+00 L2 loss: 0.57231 Learning rate: 0.002 Mask loss: 0.18889 RPN box loss: 0.04738 RPN score loss: 0.00913 RPN total loss: 0.05651 Total loss: 1.10444 timestamp: 1655053589.1173866 iteration: 58130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11207 FastRCNN class loss: 0.0569 FastRCNN total loss: 0.16897 L1 loss: 0.0000e+00 L2 loss: 0.5723 Learning rate: 0.002 Mask loss: 0.09017 RPN box loss: 0.02022 RPN score loss: 0.00197 RPN total loss: 0.02219 Total loss: 0.85363 timestamp: 1655053592.43753 iteration: 58135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06654 FastRCNN class loss: 0.04236 FastRCNN total loss: 0.1089 L1 loss: 0.0000e+00 L2 loss: 0.57229 Learning rate: 0.002 Mask loss: 0.13609 RPN box loss: 0.01098 RPN score loss: 0.00284 RPN total loss: 0.01382 Total loss: 0.8311 timestamp: 1655053595.7446873 iteration: 58140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05823 FastRCNN class loss: 0.05285 FastRCNN total loss: 0.11109 L1 loss: 0.0000e+00 L2 loss: 0.57228 Learning rate: 0.002 Mask loss: 0.08813 RPN box loss: 0.01851 RPN score loss: 0.01047 RPN total loss: 0.02898 Total loss: 0.80049 timestamp: 1655053599.0382824 iteration: 58145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08117 FastRCNN class loss: 0.0823 FastRCNN total loss: 0.16347 L1 loss: 0.0000e+00 L2 loss: 0.57227 Learning rate: 0.002 Mask loss: 0.25643 RPN box loss: 0.02381 RPN score loss: 0.01078 RPN total loss: 0.03459 Total loss: 1.02675 timestamp: 1655053602.3559434 iteration: 58150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11295 FastRCNN class loss: 0.17238 FastRCNN total loss: 0.28533 L1 loss: 0.0000e+00 L2 loss: 0.57226 Learning rate: 0.002 Mask loss: 0.13349 RPN box loss: 0.01472 RPN score loss: 0.01046 RPN total loss: 0.02518 Total loss: 1.01626 timestamp: 1655053605.5793118 iteration: 58155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.04137 FastRCNN total loss: 0.11318 L1 loss: 0.0000e+00 L2 loss: 0.57225 Learning rate: 0.002 Mask loss: 0.13056 RPN box loss: 0.00927 RPN score loss: 0.00655 RPN total loss: 0.01582 Total loss: 0.83182 timestamp: 1655053608.8440034 iteration: 58160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14911 FastRCNN class loss: 0.09708 FastRCNN total loss: 0.24619 L1 loss: 0.0000e+00 L2 loss: 0.57225 Learning rate: 0.002 Mask loss: 0.14199 RPN box loss: 0.0242 RPN score loss: 0.00683 RPN total loss: 0.03102 Total loss: 0.99145 timestamp: 1655053612.0972962 iteration: 58165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.05248 FastRCNN total loss: 0.1257 L1 loss: 0.0000e+00 L2 loss: 0.57224 Learning rate: 0.002 Mask loss: 0.14102 RPN box loss: 0.02351 RPN score loss: 0.00651 RPN total loss: 0.03003 Total loss: 0.869 timestamp: 1655053615.3093545 iteration: 58170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12793 FastRCNN class loss: 0.08403 FastRCNN total loss: 0.21197 L1 loss: 0.0000e+00 L2 loss: 0.57223 Learning rate: 0.002 Mask loss: 0.19928 RPN box loss: 0.01472 RPN score loss: 0.00936 RPN total loss: 0.02408 Total loss: 1.00755 timestamp: 1655053618.5911782 iteration: 58175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.57222 Learning rate: 0.002 Mask loss: 0.13479 RPN box loss: 0.01179 RPN score loss: 0.00402 RPN total loss: 0.01581 Total loss: 0.88784 timestamp: 1655053621.8131993 iteration: 58180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09455 FastRCNN class loss: 0.10094 FastRCNN total loss: 0.19549 L1 loss: 0.0000e+00 L2 loss: 0.57221 Learning rate: 0.002 Mask loss: 0.15727 RPN box loss: 0.01376 RPN score loss: 0.00331 RPN total loss: 0.01707 Total loss: 0.94204 timestamp: 1655053625.129121 iteration: 58185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10752 FastRCNN class loss: 0.06385 FastRCNN total loss: 0.17137 L1 loss: 0.0000e+00 L2 loss: 0.5722 Learning rate: 0.002 Mask loss: 0.1434 RPN box loss: 0.00483 RPN score loss: 0.002 RPN total loss: 0.00683 Total loss: 0.8938 timestamp: 1655053628.4037547 iteration: 58190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10466 FastRCNN class loss: 0.07545 FastRCNN total loss: 0.18011 L1 loss: 0.0000e+00 L2 loss: 0.57219 Learning rate: 0.002 Mask loss: 0.13235 RPN box loss: 0.01575 RPN score loss: 0.00193 RPN total loss: 0.01768 Total loss: 0.90233 timestamp: 1655053631.6247149 iteration: 58195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06862 FastRCNN class loss: 0.03694 FastRCNN total loss: 0.10557 L1 loss: 0.0000e+00 L2 loss: 0.57218 Learning rate: 0.002 Mask loss: 0.12672 RPN box loss: 0.02031 RPN score loss: 0.00702 RPN total loss: 0.02733 Total loss: 0.8318 timestamp: 1655053634.909869 iteration: 58200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10351 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.1797 L1 loss: 0.0000e+00 L2 loss: 0.57217 Learning rate: 0.002 Mask loss: 0.13101 RPN box loss: 0.01739 RPN score loss: 0.00822 RPN total loss: 0.02561 Total loss: 0.90849 timestamp: 1655053638.1475673 iteration: 58205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09588 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.17494 L1 loss: 0.0000e+00 L2 loss: 0.57217 Learning rate: 0.002 Mask loss: 0.12942 RPN box loss: 0.01888 RPN score loss: 0.0053 RPN total loss: 0.02418 Total loss: 0.90071 timestamp: 1655053641.4676216 iteration: 58210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11157 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 0.57216 Learning rate: 0.002 Mask loss: 0.14933 RPN box loss: 0.02261 RPN score loss: 0.00315 RPN total loss: 0.02576 Total loss: 0.92456 timestamp: 1655053644.6850793 iteration: 58215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10228 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.1452 L1 loss: 0.0000e+00 L2 loss: 0.57215 Learning rate: 0.002 Mask loss: 0.08159 RPN box loss: 0.02299 RPN score loss: 0.00209 RPN total loss: 0.02507 Total loss: 0.82401 timestamp: 1655053647.8975563 iteration: 58220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10358 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.16811 L1 loss: 0.0000e+00 L2 loss: 0.57214 Learning rate: 0.002 Mask loss: 0.1516 RPN box loss: 0.01246 RPN score loss: 0.00606 RPN total loss: 0.01852 Total loss: 0.91037 timestamp: 1655053651.1051307 iteration: 58225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0614 FastRCNN class loss: 0.05646 FastRCNN total loss: 0.11786 L1 loss: 0.0000e+00 L2 loss: 0.57214 Learning rate: 0.002 Mask loss: 0.13636 RPN box loss: 0.01369 RPN score loss: 0.01039 RPN total loss: 0.02407 Total loss: 0.85043 timestamp: 1655053654.3708513 iteration: 58230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10299 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.1814 L1 loss: 0.0000e+00 L2 loss: 0.57213 Learning rate: 0.002 Mask loss: 0.15062 RPN box loss: 0.00832 RPN score loss: 0.00407 RPN total loss: 0.01239 Total loss: 0.91654 timestamp: 1655053657.5590215 iteration: 58235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06145 FastRCNN class loss: 0.04342 FastRCNN total loss: 0.10487 L1 loss: 0.0000e+00 L2 loss: 0.57212 Learning rate: 0.002 Mask loss: 0.12668 RPN box loss: 0.01647 RPN score loss: 0.00202 RPN total loss: 0.01848 Total loss: 0.82215 timestamp: 1655053660.8313832 iteration: 58240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09944 FastRCNN class loss: 0.08622 FastRCNN total loss: 0.18566 L1 loss: 0.0000e+00 L2 loss: 0.57211 Learning rate: 0.002 Mask loss: 0.15114 RPN box loss: 0.02209 RPN score loss: 0.00335 RPN total loss: 0.02544 Total loss: 0.93435 timestamp: 1655053664.1394134 iteration: 58245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0686 FastRCNN class loss: 0.05681 FastRCNN total loss: 0.1254 L1 loss: 0.0000e+00 L2 loss: 0.5721 Learning rate: 0.002 Mask loss: 0.12002 RPN box loss: 0.00993 RPN score loss: 0.0009 RPN total loss: 0.01083 Total loss: 0.82835 timestamp: 1655053667.3412113 iteration: 58250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17603 FastRCNN class loss: 0.12096 FastRCNN total loss: 0.29699 L1 loss: 0.0000e+00 L2 loss: 0.5721 Learning rate: 0.002 Mask loss: 0.23185 RPN box loss: 0.01065 RPN score loss: 0.01232 RPN total loss: 0.02297 Total loss: 1.1239 timestamp: 1655053670.605484 iteration: 58255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08728 FastRCNN class loss: 0.03618 FastRCNN total loss: 0.12347 L1 loss: 0.0000e+00 L2 loss: 0.57209 Learning rate: 0.002 Mask loss: 0.11647 RPN box loss: 0.00911 RPN score loss: 0.01018 RPN total loss: 0.01929 Total loss: 0.83132 timestamp: 1655053673.854194 iteration: 58260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.06675 FastRCNN total loss: 0.17087 L1 loss: 0.0000e+00 L2 loss: 0.57208 Learning rate: 0.002 Mask loss: 0.13686 RPN box loss: 0.01453 RPN score loss: 0.00661 RPN total loss: 0.02114 Total loss: 0.90094 timestamp: 1655053677.085217 iteration: 58265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14461 FastRCNN class loss: 0.05543 FastRCNN total loss: 0.20004 L1 loss: 0.0000e+00 L2 loss: 0.57207 Learning rate: 0.002 Mask loss: 0.15148 RPN box loss: 0.00551 RPN score loss: 0.00412 RPN total loss: 0.00963 Total loss: 0.93322 timestamp: 1655053680.3370123 iteration: 58270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.09056 FastRCNN total loss: 0.23587 L1 loss: 0.0000e+00 L2 loss: 0.57206 Learning rate: 0.002 Mask loss: 0.25072 RPN box loss: 0.01208 RPN score loss: 0.01054 RPN total loss: 0.02262 Total loss: 1.08127 timestamp: 1655053683.6220996 iteration: 58275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09572 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.17762 L1 loss: 0.0000e+00 L2 loss: 0.57205 Learning rate: 0.002 Mask loss: 0.14206 RPN box loss: 0.01383 RPN score loss: 0.00858 RPN total loss: 0.02241 Total loss: 0.91413 timestamp: 1655053686.933803 iteration: 58280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.17915 L1 loss: 0.0000e+00 L2 loss: 0.57204 Learning rate: 0.002 Mask loss: 0.16021 RPN box loss: 0.00876 RPN score loss: 0.00535 RPN total loss: 0.01411 Total loss: 0.9255 timestamp: 1655053690.2245202 iteration: 58285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10235 FastRCNN class loss: 0.04226 FastRCNN total loss: 0.14461 L1 loss: 0.0000e+00 L2 loss: 0.57203 Learning rate: 0.002 Mask loss: 0.11706 RPN box loss: 0.01133 RPN score loss: 0.00344 RPN total loss: 0.01477 Total loss: 0.84848 timestamp: 1655053693.3981605 iteration: 58290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13262 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.22413 L1 loss: 0.0000e+00 L2 loss: 0.57202 Learning rate: 0.002 Mask loss: 0.18197 RPN box loss: 0.02419 RPN score loss: 0.00215 RPN total loss: 0.02634 Total loss: 1.00446 timestamp: 1655053696.714138 iteration: 58295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1115 FastRCNN class loss: 0.10002 FastRCNN total loss: 0.21153 L1 loss: 0.0000e+00 L2 loss: 0.57202 Learning rate: 0.002 Mask loss: 0.1709 RPN box loss: 0.01358 RPN score loss: 0.01034 RPN total loss: 0.02391 Total loss: 0.97836 timestamp: 1655053700.024742 iteration: 58300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11745 FastRCNN class loss: 0.12527 FastRCNN total loss: 0.24272 L1 loss: 0.0000e+00 L2 loss: 0.57201 Learning rate: 0.002 Mask loss: 0.19805 RPN box loss: 0.03054 RPN score loss: 0.01281 RPN total loss: 0.04336 Total loss: 1.05614 timestamp: 1655053703.2924848 iteration: 58305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13432 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 0.572 Learning rate: 0.002 Mask loss: 0.10582 RPN box loss: 0.02934 RPN score loss: 0.00122 RPN total loss: 0.03056 Total loss: 0.9095 timestamp: 1655053706.4810593 iteration: 58310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12645 FastRCNN class loss: 0.1109 FastRCNN total loss: 0.23735 L1 loss: 0.0000e+00 L2 loss: 0.57199 Learning rate: 0.002 Mask loss: 0.2207 RPN box loss: 0.02623 RPN score loss: 0.02146 RPN total loss: 0.0477 Total loss: 1.07774 timestamp: 1655053709.7728868 iteration: 58315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16142 FastRCNN class loss: 0.11865 FastRCNN total loss: 0.28007 L1 loss: 0.0000e+00 L2 loss: 0.57198 Learning rate: 0.002 Mask loss: 0.15505 RPN box loss: 0.02437 RPN score loss: 0.01148 RPN total loss: 0.03585 Total loss: 1.04296 timestamp: 1655053713.1452394 iteration: 58320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09016 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.57198 Learning rate: 0.002 Mask loss: 0.13411 RPN box loss: 0.01271 RPN score loss: 0.0036 RPN total loss: 0.01631 Total loss: 0.88678 timestamp: 1655053716.4118886 iteration: 58325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05924 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.11513 L1 loss: 0.0000e+00 L2 loss: 0.57197 Learning rate: 0.002 Mask loss: 0.08929 RPN box loss: 0.00738 RPN score loss: 0.00728 RPN total loss: 0.01466 Total loss: 0.79105 timestamp: 1655053719.7047162 iteration: 58330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.57196 Learning rate: 0.002 Mask loss: 0.1343 RPN box loss: 0.00644 RPN score loss: 0.00281 RPN total loss: 0.00925 Total loss: 0.86386 timestamp: 1655053723.0465899 iteration: 58335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08604 FastRCNN class loss: 0.07704 FastRCNN total loss: 0.16309 L1 loss: 0.0000e+00 L2 loss: 0.57196 Learning rate: 0.002 Mask loss: 0.15254 RPN box loss: 0.02122 RPN score loss: 0.011 RPN total loss: 0.03222 Total loss: 0.91981 timestamp: 1655053726.332014 iteration: 58340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09313 FastRCNN class loss: 0.0693 FastRCNN total loss: 0.16243 L1 loss: 0.0000e+00 L2 loss: 0.57195 Learning rate: 0.002 Mask loss: 0.1558 RPN box loss: 0.01974 RPN score loss: 0.00172 RPN total loss: 0.02146 Total loss: 0.91164 timestamp: 1655053729.5837057 iteration: 58345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07768 FastRCNN class loss: 0.05159 FastRCNN total loss: 0.12927 L1 loss: 0.0000e+00 L2 loss: 0.57194 Learning rate: 0.002 Mask loss: 0.16533 RPN box loss: 0.01401 RPN score loss: 0.00541 RPN total loss: 0.01942 Total loss: 0.88597 timestamp: 1655053732.8604522 iteration: 58350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13886 FastRCNN class loss: 0.08433 FastRCNN total loss: 0.22319 L1 loss: 0.0000e+00 L2 loss: 0.57193 Learning rate: 0.002 Mask loss: 0.17313 RPN box loss: 0.01336 RPN score loss: 0.00405 RPN total loss: 0.01741 Total loss: 0.98565 timestamp: 1655053736.126188 iteration: 58355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13967 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.2014 L1 loss: 0.0000e+00 L2 loss: 0.57192 Learning rate: 0.002 Mask loss: 0.14448 RPN box loss: 0.02601 RPN score loss: 0.00695 RPN total loss: 0.03296 Total loss: 0.95076 timestamp: 1655053739.3985007 iteration: 58360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.07269 FastRCNN total loss: 0.1832 L1 loss: 0.0000e+00 L2 loss: 0.57191 Learning rate: 0.002 Mask loss: 0.14819 RPN box loss: 0.01674 RPN score loss: 0.00537 RPN total loss: 0.02211 Total loss: 0.92542 timestamp: 1655053742.6548843 iteration: 58365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05843 FastRCNN class loss: 0.03961 FastRCNN total loss: 0.09803 L1 loss: 0.0000e+00 L2 loss: 0.5719 Learning rate: 0.002 Mask loss: 0.14003 RPN box loss: 0.01453 RPN score loss: 0.00216 RPN total loss: 0.0167 Total loss: 0.82667 timestamp: 1655053745.8846002 iteration: 58370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10627 FastRCNN class loss: 0.09135 FastRCNN total loss: 0.19761 L1 loss: 0.0000e+00 L2 loss: 0.57189 Learning rate: 0.002 Mask loss: 0.14396 RPN box loss: 0.00963 RPN score loss: 0.00244 RPN total loss: 0.01207 Total loss: 0.92553 timestamp: 1655053749.2600687 iteration: 58375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.04776 FastRCNN total loss: 0.15521 L1 loss: 0.0000e+00 L2 loss: 0.57189 Learning rate: 0.002 Mask loss: 0.14024 RPN box loss: 0.00989 RPN score loss: 0.00421 RPN total loss: 0.0141 Total loss: 0.88144 timestamp: 1655053752.5587807 iteration: 58380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11643 FastRCNN class loss: 0.08517 FastRCNN total loss: 0.2016 L1 loss: 0.0000e+00 L2 loss: 0.57188 Learning rate: 0.002 Mask loss: 0.16089 RPN box loss: 0.01636 RPN score loss: 0.00778 RPN total loss: 0.02414 Total loss: 0.95851 timestamp: 1655053755.8064952 iteration: 58385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18462 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.27183 L1 loss: 0.0000e+00 L2 loss: 0.57187 Learning rate: 0.002 Mask loss: 0.16756 RPN box loss: 0.00814 RPN score loss: 0.00285 RPN total loss: 0.01099 Total loss: 1.02224 timestamp: 1655053759.0855093 iteration: 58390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.08626 FastRCNN total loss: 0.18916 L1 loss: 0.0000e+00 L2 loss: 0.57186 Learning rate: 0.002 Mask loss: 0.15321 RPN box loss: 0.01218 RPN score loss: 0.00594 RPN total loss: 0.01812 Total loss: 0.93235 timestamp: 1655053762.3421626 iteration: 58395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07451 FastRCNN class loss: 0.04424 FastRCNN total loss: 0.11875 L1 loss: 0.0000e+00 L2 loss: 0.57185 Learning rate: 0.002 Mask loss: 0.09207 RPN box loss: 0.02317 RPN score loss: 0.00446 RPN total loss: 0.02763 Total loss: 0.81029 timestamp: 1655053765.6323981 iteration: 58400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16239 FastRCNN class loss: 0.12008 FastRCNN total loss: 0.28247 L1 loss: 0.0000e+00 L2 loss: 0.57184 Learning rate: 0.002 Mask loss: 0.19374 RPN box loss: 0.05873 RPN score loss: 0.01432 RPN total loss: 0.07305 Total loss: 1.1211 timestamp: 1655053768.9057276 iteration: 58405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06425 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.13105 L1 loss: 0.0000e+00 L2 loss: 0.57183 Learning rate: 0.002 Mask loss: 0.10762 RPN box loss: 0.00547 RPN score loss: 0.00103 RPN total loss: 0.0065 Total loss: 0.817 timestamp: 1655053772.1235847 iteration: 58410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12084 FastRCNN class loss: 0.15324 FastRCNN total loss: 0.27408 L1 loss: 0.0000e+00 L2 loss: 0.57182 Learning rate: 0.002 Mask loss: 0.15226 RPN box loss: 0.01134 RPN score loss: 0.0198 RPN total loss: 0.03114 Total loss: 1.02931 timestamp: 1655053775.3360155 iteration: 58415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15918 FastRCNN class loss: 0.13496 FastRCNN total loss: 0.29414 L1 loss: 0.0000e+00 L2 loss: 0.57182 Learning rate: 0.002 Mask loss: 0.18214 RPN box loss: 0.04082 RPN score loss: 0.00416 RPN total loss: 0.04498 Total loss: 1.09308 timestamp: 1655053778.63534 iteration: 58420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08292 FastRCNN class loss: 0.08911 FastRCNN total loss: 0.17203 L1 loss: 0.0000e+00 L2 loss: 0.57181 Learning rate: 0.002 Mask loss: 0.18555 RPN box loss: 0.02708 RPN score loss: 0.01545 RPN total loss: 0.04253 Total loss: 0.97192 timestamp: 1655053781.9451728 iteration: 58425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.04592 FastRCNN total loss: 0.12165 L1 loss: 0.0000e+00 L2 loss: 0.5718 Learning rate: 0.002 Mask loss: 0.07497 RPN box loss: 0.01272 RPN score loss: 0.00098 RPN total loss: 0.0137 Total loss: 0.78213 timestamp: 1655053785.2094452 iteration: 58430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16327 FastRCNN class loss: 0.09397 FastRCNN total loss: 0.25724 L1 loss: 0.0000e+00 L2 loss: 0.57179 Learning rate: 0.002 Mask loss: 0.18455 RPN box loss: 0.02265 RPN score loss: 0.00675 RPN total loss: 0.0294 Total loss: 1.04298 timestamp: 1655053788.5142539 iteration: 58435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12307 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.19851 L1 loss: 0.0000e+00 L2 loss: 0.57179 Learning rate: 0.002 Mask loss: 0.18817 RPN box loss: 0.01637 RPN score loss: 0.00994 RPN total loss: 0.02631 Total loss: 0.98477 timestamp: 1655053791.756192 iteration: 58440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.12956 L1 loss: 0.0000e+00 L2 loss: 0.57178 Learning rate: 0.002 Mask loss: 0.13599 RPN box loss: 0.00725 RPN score loss: 0.00347 RPN total loss: 0.01072 Total loss: 0.84806 timestamp: 1655053795.034584 iteration: 58445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07938 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.14193 L1 loss: 0.0000e+00 L2 loss: 0.57178 Learning rate: 0.002 Mask loss: 0.09541 RPN box loss: 0.01728 RPN score loss: 0.00989 RPN total loss: 0.02717 Total loss: 0.83629 timestamp: 1655053798.3239157 iteration: 58450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1981 FastRCNN class loss: 0.08 FastRCNN total loss: 0.27809 L1 loss: 0.0000e+00 L2 loss: 0.57177 Learning rate: 0.002 Mask loss: 0.17641 RPN box loss: 0.01438 RPN score loss: 0.00348 RPN total loss: 0.01786 Total loss: 1.04412 timestamp: 1655053801.5568826 iteration: 58455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09221 FastRCNN class loss: 0.07664 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.57176 Learning rate: 0.002 Mask loss: 0.12955 RPN box loss: 0.03049 RPN score loss: 0.01162 RPN total loss: 0.04211 Total loss: 0.91227 timestamp: 1655053804.8229148 iteration: 58460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08542 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.16293 L1 loss: 0.0000e+00 L2 loss: 0.57175 Learning rate: 0.002 Mask loss: 0.20486 RPN box loss: 0.02463 RPN score loss: 0.00521 RPN total loss: 0.02984 Total loss: 0.96938 timestamp: 1655053808.1214437 iteration: 58465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0865 FastRCNN class loss: 0.04618 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.57174 Learning rate: 0.002 Mask loss: 0.10924 RPN box loss: 0.01128 RPN score loss: 0.00339 RPN total loss: 0.01468 Total loss: 0.82833 timestamp: 1655053811.4342756 iteration: 58470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10452 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.18736 L1 loss: 0.0000e+00 L2 loss: 0.57173 Learning rate: 0.002 Mask loss: 0.20987 RPN box loss: 0.01384 RPN score loss: 0.00804 RPN total loss: 0.02189 Total loss: 0.99084 timestamp: 1655053814.7346723 iteration: 58475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07494 FastRCNN class loss: 0.06457 FastRCNN total loss: 0.13951 L1 loss: 0.0000e+00 L2 loss: 0.57172 Learning rate: 0.002 Mask loss: 0.1234 RPN box loss: 0.01297 RPN score loss: 0.00155 RPN total loss: 0.01451 Total loss: 0.84914 timestamp: 1655053818.022436 iteration: 58480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11561 FastRCNN class loss: 0.07356 FastRCNN total loss: 0.18917 L1 loss: 0.0000e+00 L2 loss: 0.57171 Learning rate: 0.002 Mask loss: 0.18905 RPN box loss: 0.01104 RPN score loss: 0.01714 RPN total loss: 0.02818 Total loss: 0.97812 timestamp: 1655053821.2651234 iteration: 58485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10982 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.17333 L1 loss: 0.0000e+00 L2 loss: 0.5717 Learning rate: 0.002 Mask loss: 0.14199 RPN box loss: 0.03754 RPN score loss: 0.00694 RPN total loss: 0.04448 Total loss: 0.9315 timestamp: 1655053824.5145905 iteration: 58490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07388 FastRCNN class loss: 0.07779 FastRCNN total loss: 0.15168 L1 loss: 0.0000e+00 L2 loss: 0.57169 Learning rate: 0.002 Mask loss: 0.10587 RPN box loss: 0.0143 RPN score loss: 0.00363 RPN total loss: 0.01793 Total loss: 0.84717 timestamp: 1655053827.8644304 iteration: 58495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09142 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.15665 L1 loss: 0.0000e+00 L2 loss: 0.57168 Learning rate: 0.002 Mask loss: 0.07631 RPN box loss: 0.008 RPN score loss: 0.0022 RPN total loss: 0.01019 Total loss: 0.81484 timestamp: 1655053831.1701767 iteration: 58500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0991 FastRCNN class loss: 0.08952 FastRCNN total loss: 0.18862 L1 loss: 0.0000e+00 L2 loss: 0.57168 Learning rate: 0.002 Mask loss: 0.20967 RPN box loss: 0.03674 RPN score loss: 0.00544 RPN total loss: 0.04218 Total loss: 1.01214 timestamp: 1655053834.475996 iteration: 58505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05555 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.11798 L1 loss: 0.0000e+00 L2 loss: 0.57167 Learning rate: 0.002 Mask loss: 0.16008 RPN box loss: 0.01259 RPN score loss: 0.00373 RPN total loss: 0.01631 Total loss: 0.86605 timestamp: 1655053837.7959828 iteration: 58510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16501 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.246 L1 loss: 0.0000e+00 L2 loss: 0.57166 Learning rate: 0.002 Mask loss: 0.22348 RPN box loss: 0.00694 RPN score loss: 0.00369 RPN total loss: 0.01063 Total loss: 1.05177 timestamp: 1655053841.0092216 iteration: 58515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.0467 FastRCNN total loss: 0.14465 L1 loss: 0.0000e+00 L2 loss: 0.57165 Learning rate: 0.002 Mask loss: 0.09762 RPN box loss: 0.06439 RPN score loss: 0.00239 RPN total loss: 0.06678 Total loss: 0.88069 timestamp: 1655053844.2875128 iteration: 58520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08588 FastRCNN class loss: 0.04649 FastRCNN total loss: 0.13237 L1 loss: 0.0000e+00 L2 loss: 0.57165 Learning rate: 0.002 Mask loss: 0.13028 RPN box loss: 0.00769 RPN score loss: 0.00278 RPN total loss: 0.01047 Total loss: 0.84477 timestamp: 1655053847.5660858 iteration: 58525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07308 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.13157 L1 loss: 0.0000e+00 L2 loss: 0.57164 Learning rate: 0.002 Mask loss: 0.08977 RPN box loss: 0.00896 RPN score loss: 0.0015 RPN total loss: 0.01046 Total loss: 0.80343 timestamp: 1655053850.7677333 iteration: 58530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12247 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.19921 L1 loss: 0.0000e+00 L2 loss: 0.57163 Learning rate: 0.002 Mask loss: 0.13062 RPN box loss: 0.00767 RPN score loss: 0.00364 RPN total loss: 0.01131 Total loss: 0.91277 timestamp: 1655053854.0527885 iteration: 58535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07341 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.15625 L1 loss: 0.0000e+00 L2 loss: 0.57162 Learning rate: 0.002 Mask loss: 0.21585 RPN box loss: 0.01617 RPN score loss: 0.00167 RPN total loss: 0.01784 Total loss: 0.96157 timestamp: 1655053857.3108037 iteration: 58540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13569 FastRCNN class loss: 0.09429 FastRCNN total loss: 0.22998 L1 loss: 0.0000e+00 L2 loss: 0.57161 Learning rate: 0.002 Mask loss: 0.12987 RPN box loss: 0.00773 RPN score loss: 0.00412 RPN total loss: 0.01185 Total loss: 0.94331 timestamp: 1655053860.5847564 iteration: 58545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08617 FastRCNN class loss: 0.076 FastRCNN total loss: 0.16217 L1 loss: 0.0000e+00 L2 loss: 0.5716 Learning rate: 0.002 Mask loss: 0.15806 RPN box loss: 0.01486 RPN score loss: 0.00313 RPN total loss: 0.01799 Total loss: 0.90983 timestamp: 1655053863.8316777 iteration: 58550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0912 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.1729 L1 loss: 0.0000e+00 L2 loss: 0.57159 Learning rate: 0.002 Mask loss: 0.17449 RPN box loss: 0.00974 RPN score loss: 0.01075 RPN total loss: 0.02049 Total loss: 0.93947 timestamp: 1655053867.1024382 iteration: 58555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1401 FastRCNN class loss: 0.11406 FastRCNN total loss: 0.25416 L1 loss: 0.0000e+00 L2 loss: 0.57158 Learning rate: 0.002 Mask loss: 0.21199 RPN box loss: 0.0266 RPN score loss: 0.01091 RPN total loss: 0.03752 Total loss: 1.07525 timestamp: 1655053870.3884456 iteration: 58560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08595 FastRCNN class loss: 0.07798 FastRCNN total loss: 0.16393 L1 loss: 0.0000e+00 L2 loss: 0.57157 Learning rate: 0.002 Mask loss: 0.19902 RPN box loss: 0.02455 RPN score loss: 0.01451 RPN total loss: 0.03907 Total loss: 0.97359 timestamp: 1655053873.7360082 iteration: 58565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.13386 L1 loss: 0.0000e+00 L2 loss: 0.57156 Learning rate: 0.002 Mask loss: 0.12568 RPN box loss: 0.01628 RPN score loss: 0.00146 RPN total loss: 0.01774 Total loss: 0.84885 timestamp: 1655053877.0483413 iteration: 58570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.57155 Learning rate: 0.002 Mask loss: 0.12059 RPN box loss: 0.01013 RPN score loss: 0.0043 RPN total loss: 0.01443 Total loss: 0.86679 timestamp: 1655053880.306688 iteration: 58575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.06511 FastRCNN total loss: 0.18372 L1 loss: 0.0000e+00 L2 loss: 0.57155 Learning rate: 0.002 Mask loss: 0.11896 RPN box loss: 0.01632 RPN score loss: 0.00966 RPN total loss: 0.02597 Total loss: 0.9002 timestamp: 1655053883.6246526 iteration: 58580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.07707 FastRCNN total loss: 0.15171 L1 loss: 0.0000e+00 L2 loss: 0.57154 Learning rate: 0.002 Mask loss: 0.12527 RPN box loss: 0.01517 RPN score loss: 0.00451 RPN total loss: 0.01968 Total loss: 0.86819 timestamp: 1655053886.8905027 iteration: 58585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.08604 FastRCNN total loss: 0.17584 L1 loss: 0.0000e+00 L2 loss: 0.57153 Learning rate: 0.002 Mask loss: 0.13655 RPN box loss: 0.01913 RPN score loss: 0.01088 RPN total loss: 0.03001 Total loss: 0.91392 timestamp: 1655053890.1714683 iteration: 58590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10515 FastRCNN class loss: 0.09891 FastRCNN total loss: 0.20406 L1 loss: 0.0000e+00 L2 loss: 0.57152 Learning rate: 0.002 Mask loss: 0.20084 RPN box loss: 0.02152 RPN score loss: 0.0032 RPN total loss: 0.02472 Total loss: 1.00114 timestamp: 1655053893.4217052 iteration: 58595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08414 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.13683 L1 loss: 0.0000e+00 L2 loss: 0.57151 Learning rate: 0.002 Mask loss: 0.16308 RPN box loss: 0.00556 RPN score loss: 0.00216 RPN total loss: 0.00772 Total loss: 0.87914 timestamp: 1655053896.726456 iteration: 58600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14197 FastRCNN class loss: 0.12366 FastRCNN total loss: 0.26563 L1 loss: 0.0000e+00 L2 loss: 0.57151 Learning rate: 0.002 Mask loss: 0.18186 RPN box loss: 0.02201 RPN score loss: 0.01651 RPN total loss: 0.03851 Total loss: 1.05751 timestamp: 1655053899.9769235 iteration: 58605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06896 FastRCNN class loss: 0.07694 FastRCNN total loss: 0.1459 L1 loss: 0.0000e+00 L2 loss: 0.5715 Learning rate: 0.002 Mask loss: 0.13096 RPN box loss: 0.01717 RPN score loss: 0.01028 RPN total loss: 0.02745 Total loss: 0.87581 timestamp: 1655053903.2537594 iteration: 58610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.04861 FastRCNN total loss: 0.13003 L1 loss: 0.0000e+00 L2 loss: 0.57149 Learning rate: 0.002 Mask loss: 0.15669 RPN box loss: 0.00951 RPN score loss: 0.00664 RPN total loss: 0.01616 Total loss: 0.87436 timestamp: 1655053906.4977207 iteration: 58615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08525 FastRCNN class loss: 0.06023 FastRCNN total loss: 0.14548 L1 loss: 0.0000e+00 L2 loss: 0.57148 Learning rate: 0.002 Mask loss: 0.14514 RPN box loss: 0.02559 RPN score loss: 0.01189 RPN total loss: 0.03748 Total loss: 0.89958 timestamp: 1655053909.6770575 iteration: 58620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0775 FastRCNN class loss: 0.07503 FastRCNN total loss: 0.15254 L1 loss: 0.0000e+00 L2 loss: 0.57148 Learning rate: 0.002 Mask loss: 0.10244 RPN box loss: 0.01614 RPN score loss: 0.00603 RPN total loss: 0.02217 Total loss: 0.84862 timestamp: 1655053912.9433196 iteration: 58625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09975 FastRCNN class loss: 0.05868 FastRCNN total loss: 0.15843 L1 loss: 0.0000e+00 L2 loss: 0.57147 Learning rate: 0.002 Mask loss: 0.16138 RPN box loss: 0.00792 RPN score loss: 0.00558 RPN total loss: 0.0135 Total loss: 0.90478 timestamp: 1655053916.1499035 iteration: 58630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07861 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.13241 L1 loss: 0.0000e+00 L2 loss: 0.57146 Learning rate: 0.002 Mask loss: 0.10195 RPN box loss: 0.01038 RPN score loss: 0.00291 RPN total loss: 0.01329 Total loss: 0.81911 timestamp: 1655053919.4010122 iteration: 58635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15124 FastRCNN class loss: 0.08569 FastRCNN total loss: 0.23694 L1 loss: 0.0000e+00 L2 loss: 0.57145 Learning rate: 0.002 Mask loss: 0.1604 RPN box loss: 0.02951 RPN score loss: 0.01398 RPN total loss: 0.04348 Total loss: 1.01228 timestamp: 1655053922.6426582 iteration: 58640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.08746 FastRCNN total loss: 0.21728 L1 loss: 0.0000e+00 L2 loss: 0.57144 Learning rate: 0.002 Mask loss: 0.1321 RPN box loss: 0.00831 RPN score loss: 0.00389 RPN total loss: 0.01219 Total loss: 0.93302 timestamp: 1655053925.9067016 iteration: 58645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.06123 FastRCNN total loss: 0.13568 L1 loss: 0.0000e+00 L2 loss: 0.57144 Learning rate: 0.002 Mask loss: 0.12199 RPN box loss: 0.03732 RPN score loss: 0.00551 RPN total loss: 0.04283 Total loss: 0.87193 timestamp: 1655053929.1877708 iteration: 58650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10419 FastRCNN class loss: 0.0864 FastRCNN total loss: 0.19059 L1 loss: 0.0000e+00 L2 loss: 0.57143 Learning rate: 0.002 Mask loss: 0.13074 RPN box loss: 0.01321 RPN score loss: 0.0017 RPN total loss: 0.0149 Total loss: 0.90766 timestamp: 1655053932.4879196 iteration: 58655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12028 FastRCNN class loss: 0.09066 FastRCNN total loss: 0.21094 L1 loss: 0.0000e+00 L2 loss: 0.57142 Learning rate: 0.002 Mask loss: 0.17393 RPN box loss: 0.01569 RPN score loss: 0.00392 RPN total loss: 0.01961 Total loss: 0.9759 timestamp: 1655053935.7379894 iteration: 58660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16171 FastRCNN class loss: 0.11093 FastRCNN total loss: 0.27264 L1 loss: 0.0000e+00 L2 loss: 0.57141 Learning rate: 0.002 Mask loss: 0.18964 RPN box loss: 0.02586 RPN score loss: 0.01004 RPN total loss: 0.0359 Total loss: 1.06959 timestamp: 1655053939.0301764 iteration: 58665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06569 FastRCNN class loss: 0.04449 FastRCNN total loss: 0.11017 L1 loss: 0.0000e+00 L2 loss: 0.5714 Learning rate: 0.002 Mask loss: 0.11482 RPN box loss: 0.01092 RPN score loss: 0.00297 RPN total loss: 0.01389 Total loss: 0.81029 timestamp: 1655053942.3282883 iteration: 58670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12676 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.22426 L1 loss: 0.0000e+00 L2 loss: 0.57139 Learning rate: 0.002 Mask loss: 0.19105 RPN box loss: 0.01174 RPN score loss: 0.00689 RPN total loss: 0.01863 Total loss: 1.00533 timestamp: 1655053945.6465013 iteration: 58675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.05535 FastRCNN total loss: 0.16912 L1 loss: 0.0000e+00 L2 loss: 0.57138 Learning rate: 0.002 Mask loss: 0.12566 RPN box loss: 0.01207 RPN score loss: 0.01197 RPN total loss: 0.02405 Total loss: 0.89021 timestamp: 1655053948.9074342 iteration: 58680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09756 FastRCNN class loss: 0.03465 FastRCNN total loss: 0.13221 L1 loss: 0.0000e+00 L2 loss: 0.57138 Learning rate: 0.002 Mask loss: 0.08776 RPN box loss: 0.00429 RPN score loss: 0.00316 RPN total loss: 0.00744 Total loss: 0.79879 timestamp: 1655053952.192379 iteration: 58685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14444 FastRCNN class loss: 0.11313 FastRCNN total loss: 0.25757 L1 loss: 0.0000e+00 L2 loss: 0.57137 Learning rate: 0.002 Mask loss: 0.15062 RPN box loss: 0.01228 RPN score loss: 0.00542 RPN total loss: 0.0177 Total loss: 0.99727 timestamp: 1655053955.4545395 iteration: 58690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07173 FastRCNN class loss: 0.06605 FastRCNN total loss: 0.13778 L1 loss: 0.0000e+00 L2 loss: 0.57136 Learning rate: 0.002 Mask loss: 0.13788 RPN box loss: 0.00777 RPN score loss: 0.00127 RPN total loss: 0.00904 Total loss: 0.85607 timestamp: 1655053958.7027223 iteration: 58695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08525 FastRCNN class loss: 0.05604 FastRCNN total loss: 0.14129 L1 loss: 0.0000e+00 L2 loss: 0.57135 Learning rate: 0.002 Mask loss: 0.13819 RPN box loss: 0.00921 RPN score loss: 0.00653 RPN total loss: 0.01574 Total loss: 0.86657 timestamp: 1655053961.9590666 iteration: 58700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1257 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.2086 L1 loss: 0.0000e+00 L2 loss: 0.57134 Learning rate: 0.002 Mask loss: 0.1677 RPN box loss: 0.0092 RPN score loss: 0.00701 RPN total loss: 0.0162 Total loss: 0.96385 timestamp: 1655053965.2692087 iteration: 58705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09887 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.16496 L1 loss: 0.0000e+00 L2 loss: 0.57133 Learning rate: 0.002 Mask loss: 0.12777 RPN box loss: 0.01156 RPN score loss: 0.00147 RPN total loss: 0.01303 Total loss: 0.8771 timestamp: 1655053968.499282 iteration: 58710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11788 FastRCNN class loss: 0.04397 FastRCNN total loss: 0.16185 L1 loss: 0.0000e+00 L2 loss: 0.57133 Learning rate: 0.002 Mask loss: 0.11378 RPN box loss: 0.00384 RPN score loss: 0.00301 RPN total loss: 0.00684 Total loss: 0.8538 timestamp: 1655053971.8228889 iteration: 58715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.08462 FastRCNN total loss: 0.20948 L1 loss: 0.0000e+00 L2 loss: 0.57132 Learning rate: 0.002 Mask loss: 0.16075 RPN box loss: 0.02237 RPN score loss: 0.01298 RPN total loss: 0.03534 Total loss: 0.97689 timestamp: 1655053975.0500536 iteration: 58720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13375 FastRCNN class loss: 0.09531 FastRCNN total loss: 0.22906 L1 loss: 0.0000e+00 L2 loss: 0.57131 Learning rate: 0.002 Mask loss: 0.16696 RPN box loss: 0.01766 RPN score loss: 0.01366 RPN total loss: 0.03132 Total loss: 0.99865 timestamp: 1655053978.2705677 iteration: 58725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04687 FastRCNN class loss: 0.04485 FastRCNN total loss: 0.09172 L1 loss: 0.0000e+00 L2 loss: 0.5713 Learning rate: 0.002 Mask loss: 0.0903 RPN box loss: 0.00689 RPN score loss: 0.00308 RPN total loss: 0.00997 Total loss: 0.76329 timestamp: 1655053981.5763412 iteration: 58730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21315 FastRCNN class loss: 0.10324 FastRCNN total loss: 0.31638 L1 loss: 0.0000e+00 L2 loss: 0.57129 Learning rate: 0.002 Mask loss: 0.12643 RPN box loss: 0.02937 RPN score loss: 0.00792 RPN total loss: 0.0373 Total loss: 1.0514 timestamp: 1655053984.8327038 iteration: 58735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.1007 FastRCNN total loss: 0.20435 L1 loss: 0.0000e+00 L2 loss: 0.57129 Learning rate: 0.002 Mask loss: 0.17757 RPN box loss: 0.03022 RPN score loss: 0.0069 RPN total loss: 0.03712 Total loss: 0.99033 timestamp: 1655053988.0713258 iteration: 58740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17934 FastRCNN class loss: 0.09205 FastRCNN total loss: 0.27139 L1 loss: 0.0000e+00 L2 loss: 0.57128 Learning rate: 0.002 Mask loss: 0.1948 RPN box loss: 0.03443 RPN score loss: 0.0057 RPN total loss: 0.04013 Total loss: 1.0776 timestamp: 1655053991.3838358 iteration: 58745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0738 FastRCNN class loss: 0.0458 FastRCNN total loss: 0.11959 L1 loss: 0.0000e+00 L2 loss: 0.57128 Learning rate: 0.002 Mask loss: 0.11787 RPN box loss: 0.00547 RPN score loss: 0.002 RPN total loss: 0.00747 Total loss: 0.81621 timestamp: 1655053994.6291 iteration: 58750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05799 FastRCNN class loss: 0.06934 FastRCNN total loss: 0.12733 L1 loss: 0.0000e+00 L2 loss: 0.57127 Learning rate: 0.002 Mask loss: 0.15781 RPN box loss: 0.00948 RPN score loss: 0.00993 RPN total loss: 0.01941 Total loss: 0.87582 timestamp: 1655053997.9127676 iteration: 58755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07601 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.14906 L1 loss: 0.0000e+00 L2 loss: 0.57126 Learning rate: 0.002 Mask loss: 0.1203 RPN box loss: 0.01102 RPN score loss: 0.00417 RPN total loss: 0.01519 Total loss: 0.85581 timestamp: 1655054001.1105974 iteration: 58760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.12886 L1 loss: 0.0000e+00 L2 loss: 0.57125 Learning rate: 0.002 Mask loss: 0.13047 RPN box loss: 0.00847 RPN score loss: 0.0013 RPN total loss: 0.00977 Total loss: 0.84034 timestamp: 1655054004.4342465 iteration: 58765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11517 FastRCNN class loss: 0.11031 FastRCNN total loss: 0.22547 L1 loss: 0.0000e+00 L2 loss: 0.57124 Learning rate: 0.002 Mask loss: 0.17181 RPN box loss: 0.02061 RPN score loss: 0.00446 RPN total loss: 0.02507 Total loss: 0.9936 timestamp: 1655054007.7462983 iteration: 58770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07548 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.12529 L1 loss: 0.0000e+00 L2 loss: 0.57123 Learning rate: 0.002 Mask loss: 0.11263 RPN box loss: 0.00971 RPN score loss: 0.00222 RPN total loss: 0.01193 Total loss: 0.82108 timestamp: 1655054011.0585659 iteration: 58775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15503 FastRCNN class loss: 0.12491 FastRCNN total loss: 0.27994 L1 loss: 0.0000e+00 L2 loss: 0.57122 Learning rate: 0.002 Mask loss: 0.16988 RPN box loss: 0.02993 RPN score loss: 0.01103 RPN total loss: 0.04096 Total loss: 1.062 timestamp: 1655054014.2843368 iteration: 58780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10939 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.17496 L1 loss: 0.0000e+00 L2 loss: 0.57121 Learning rate: 0.002 Mask loss: 0.10045 RPN box loss: 0.01616 RPN score loss: 0.00338 RPN total loss: 0.01955 Total loss: 0.86617 timestamp: 1655054017.5697587 iteration: 58785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07773 FastRCNN class loss: 0.05403 FastRCNN total loss: 0.13176 L1 loss: 0.0000e+00 L2 loss: 0.57121 Learning rate: 0.002 Mask loss: 0.0868 RPN box loss: 0.01607 RPN score loss: 0.00447 RPN total loss: 0.02053 Total loss: 0.81031 timestamp: 1655054020.8300693 iteration: 58790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11023 FastRCNN class loss: 0.08244 FastRCNN total loss: 0.19267 L1 loss: 0.0000e+00 L2 loss: 0.5712 Learning rate: 0.002 Mask loss: 0.17566 RPN box loss: 0.02915 RPN score loss: 0.01428 RPN total loss: 0.04342 Total loss: 0.98295 timestamp: 1655054024.138053 iteration: 58795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.14786 L1 loss: 0.0000e+00 L2 loss: 0.57119 Learning rate: 0.002 Mask loss: 0.14219 RPN box loss: 0.06464 RPN score loss: 0.00716 RPN total loss: 0.0718 Total loss: 0.93304 timestamp: 1655054027.4181223 iteration: 58800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12247 FastRCNN class loss: 0.05135 FastRCNN total loss: 0.17382 L1 loss: 0.0000e+00 L2 loss: 0.57118 Learning rate: 0.002 Mask loss: 0.11237 RPN box loss: 0.01454 RPN score loss: 0.00285 RPN total loss: 0.01739 Total loss: 0.87476 timestamp: 1655054030.693961 iteration: 58805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1083 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.1775 L1 loss: 0.0000e+00 L2 loss: 0.57117 Learning rate: 0.002 Mask loss: 0.14734 RPN box loss: 0.01312 RPN score loss: 0.00399 RPN total loss: 0.01711 Total loss: 0.91312 timestamp: 1655054034.0480473 iteration: 58810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05682 FastRCNN class loss: 0.04636 FastRCNN total loss: 0.10319 L1 loss: 0.0000e+00 L2 loss: 0.57117 Learning rate: 0.002 Mask loss: 0.16783 RPN box loss: 0.00748 RPN score loss: 0.00177 RPN total loss: 0.00925 Total loss: 0.85144 timestamp: 1655054037.2902484 iteration: 58815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09234 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.16677 L1 loss: 0.0000e+00 L2 loss: 0.57116 Learning rate: 0.002 Mask loss: 0.18152 RPN box loss: 0.01723 RPN score loss: 0.0144 RPN total loss: 0.03163 Total loss: 0.95109 timestamp: 1655054040.5336637 iteration: 58820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11226 FastRCNN class loss: 0.1192 FastRCNN total loss: 0.23146 L1 loss: 0.0000e+00 L2 loss: 0.57115 Learning rate: 0.002 Mask loss: 0.22209 RPN box loss: 0.01733 RPN score loss: 0.04071 RPN total loss: 0.05804 Total loss: 1.08274 timestamp: 1655054043.8186135 iteration: 58825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10326 FastRCNN class loss: 0.0934 FastRCNN total loss: 0.19666 L1 loss: 0.0000e+00 L2 loss: 0.57114 Learning rate: 0.002 Mask loss: 0.1597 RPN box loss: 0.00335 RPN score loss: 0.00098 RPN total loss: 0.00433 Total loss: 0.93183 timestamp: 1655054047.101941 iteration: 58830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07209 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.11913 L1 loss: 0.0000e+00 L2 loss: 0.57113 Learning rate: 0.002 Mask loss: 0.14434 RPN box loss: 0.00919 RPN score loss: 0.00094 RPN total loss: 0.01013 Total loss: 0.84473 timestamp: 1655054050.3370917 iteration: 58835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.07 FastRCNN total loss: 0.1413 L1 loss: 0.0000e+00 L2 loss: 0.57112 Learning rate: 0.002 Mask loss: 0.17615 RPN box loss: 0.00811 RPN score loss: 0.00527 RPN total loss: 0.01338 Total loss: 0.90194 timestamp: 1655054053.6405613 iteration: 58840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1106 FastRCNN class loss: 0.07252 FastRCNN total loss: 0.18312 L1 loss: 0.0000e+00 L2 loss: 0.57111 Learning rate: 0.002 Mask loss: 0.13953 RPN box loss: 0.01212 RPN score loss: 0.00562 RPN total loss: 0.01774 Total loss: 0.9115 timestamp: 1655054056.94807 iteration: 58845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.14335 L1 loss: 0.0000e+00 L2 loss: 0.5711 Learning rate: 0.002 Mask loss: 0.17538 RPN box loss: 0.02064 RPN score loss: 0.00363 RPN total loss: 0.02427 Total loss: 0.9141 timestamp: 1655054060.3112571 iteration: 58850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11413 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.17402 L1 loss: 0.0000e+00 L2 loss: 0.5711 Learning rate: 0.002 Mask loss: 0.09676 RPN box loss: 0.02035 RPN score loss: 0.00977 RPN total loss: 0.03012 Total loss: 0.872 timestamp: 1655054063.5054138 iteration: 58855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17165 FastRCNN class loss: 0.10013 FastRCNN total loss: 0.27178 L1 loss: 0.0000e+00 L2 loss: 0.57109 Learning rate: 0.002 Mask loss: 0.14894 RPN box loss: 0.02177 RPN score loss: 0.00954 RPN total loss: 0.03131 Total loss: 1.02312 timestamp: 1655054066.8299913 iteration: 58860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07325 FastRCNN class loss: 0.05972 FastRCNN total loss: 0.13297 L1 loss: 0.0000e+00 L2 loss: 0.57108 Learning rate: 0.002 Mask loss: 0.16121 RPN box loss: 0.01659 RPN score loss: 0.00584 RPN total loss: 0.02243 Total loss: 0.88769 timestamp: 1655054070.1176167 iteration: 58865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12254 FastRCNN class loss: 0.0444 FastRCNN total loss: 0.16694 L1 loss: 0.0000e+00 L2 loss: 0.57107 Learning rate: 0.002 Mask loss: 0.1428 RPN box loss: 0.02294 RPN score loss: 0.00812 RPN total loss: 0.03106 Total loss: 0.91188 timestamp: 1655054073.3737078 iteration: 58870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12364 FastRCNN class loss: 0.13346 FastRCNN total loss: 0.2571 L1 loss: 0.0000e+00 L2 loss: 0.57106 Learning rate: 0.002 Mask loss: 0.15743 RPN box loss: 0.02504 RPN score loss: 0.00776 RPN total loss: 0.0328 Total loss: 1.0184 timestamp: 1655054076.6484787 iteration: 58875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06773 FastRCNN class loss: 0.05496 FastRCNN total loss: 0.12269 L1 loss: 0.0000e+00 L2 loss: 0.57106 Learning rate: 0.002 Mask loss: 0.11106 RPN box loss: 0.03096 RPN score loss: 0.00828 RPN total loss: 0.03924 Total loss: 0.84404 timestamp: 1655054079.9208279 iteration: 58880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09231 FastRCNN class loss: 0.11215 FastRCNN total loss: 0.20447 L1 loss: 0.0000e+00 L2 loss: 0.57105 Learning rate: 0.002 Mask loss: 0.16315 RPN box loss: 0.02417 RPN score loss: 0.02284 RPN total loss: 0.04702 Total loss: 0.98568 timestamp: 1655054083.157044 iteration: 58885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06472 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.11189 L1 loss: 0.0000e+00 L2 loss: 0.57104 Learning rate: 0.002 Mask loss: 0.11039 RPN box loss: 0.01459 RPN score loss: 0.00622 RPN total loss: 0.02081 Total loss: 0.81413 timestamp: 1655054086.4009812 iteration: 58890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07408 FastRCNN class loss: 0.05696 FastRCNN total loss: 0.13103 L1 loss: 0.0000e+00 L2 loss: 0.57103 Learning rate: 0.002 Mask loss: 0.14154 RPN box loss: 0.01198 RPN score loss: 0.00374 RPN total loss: 0.01572 Total loss: 0.85932 timestamp: 1655054089.7121327 iteration: 58895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12621 FastRCNN class loss: 0.07002 FastRCNN total loss: 0.19624 L1 loss: 0.0000e+00 L2 loss: 0.57103 Learning rate: 0.002 Mask loss: 0.14765 RPN box loss: 0.04295 RPN score loss: 0.00552 RPN total loss: 0.04847 Total loss: 0.96338 timestamp: 1655054093.016706 iteration: 58900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05634 FastRCNN class loss: 0.062 FastRCNN total loss: 0.11834 L1 loss: 0.0000e+00 L2 loss: 0.57102 Learning rate: 0.002 Mask loss: 0.10897 RPN box loss: 0.00709 RPN score loss: 0.0025 RPN total loss: 0.00959 Total loss: 0.80793 timestamp: 1655054096.325726 iteration: 58905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07409 FastRCNN class loss: 0.09692 FastRCNN total loss: 0.171 L1 loss: 0.0000e+00 L2 loss: 0.57101 Learning rate: 0.002 Mask loss: 0.14433 RPN box loss: 0.01788 RPN score loss: 0.00561 RPN total loss: 0.02348 Total loss: 0.90982 timestamp: 1655054099.6371305 iteration: 58910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10774 FastRCNN class loss: 0.09404 FastRCNN total loss: 0.20178 L1 loss: 0.0000e+00 L2 loss: 0.571 Learning rate: 0.002 Mask loss: 0.15968 RPN box loss: 0.03302 RPN score loss: 0.01793 RPN total loss: 0.05095 Total loss: 0.98341 timestamp: 1655054102.917438 iteration: 58915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17643 FastRCNN class loss: 0.06886 FastRCNN total loss: 0.24528 L1 loss: 0.0000e+00 L2 loss: 0.57099 Learning rate: 0.002 Mask loss: 0.1685 RPN box loss: 0.0205 RPN score loss: 0.00437 RPN total loss: 0.02487 Total loss: 1.00965 timestamp: 1655054106.1761696 iteration: 58920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09324 FastRCNN class loss: 0.09842 FastRCNN total loss: 0.19165 L1 loss: 0.0000e+00 L2 loss: 0.57098 Learning rate: 0.002 Mask loss: 0.13415 RPN box loss: 0.02594 RPN score loss: 0.00346 RPN total loss: 0.0294 Total loss: 0.92619 timestamp: 1655054109.470527 iteration: 58925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06239 FastRCNN class loss: 0.05256 FastRCNN total loss: 0.11495 L1 loss: 0.0000e+00 L2 loss: 0.57097 Learning rate: 0.002 Mask loss: 0.11424 RPN box loss: 0.00279 RPN score loss: 0.00293 RPN total loss: 0.00572 Total loss: 0.80589 timestamp: 1655054112.743386 iteration: 58930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06782 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.13771 L1 loss: 0.0000e+00 L2 loss: 0.57096 Learning rate: 0.002 Mask loss: 0.10174 RPN box loss: 0.01044 RPN score loss: 0.00679 RPN total loss: 0.01722 Total loss: 0.82764 timestamp: 1655054115.987756 iteration: 58935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.144 FastRCNN class loss: 0.12857 FastRCNN total loss: 0.27257 L1 loss: 0.0000e+00 L2 loss: 0.57095 Learning rate: 0.002 Mask loss: 0.22806 RPN box loss: 0.02073 RPN score loss: 0.01725 RPN total loss: 0.03797 Total loss: 1.10956 timestamp: 1655054119.23096 iteration: 58940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0833 FastRCNN class loss: 0.09342 FastRCNN total loss: 0.17672 L1 loss: 0.0000e+00 L2 loss: 0.57095 Learning rate: 0.002 Mask loss: 0.14859 RPN box loss: 0.02562 RPN score loss: 0.00345 RPN total loss: 0.02908 Total loss: 0.92533 timestamp: 1655054122.4704037 iteration: 58945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13 FastRCNN class loss: 0.0918 FastRCNN total loss: 0.2218 L1 loss: 0.0000e+00 L2 loss: 0.57094 Learning rate: 0.002 Mask loss: 0.2595 RPN box loss: 0.0123 RPN score loss: 0.00689 RPN total loss: 0.01918 Total loss: 1.07142 timestamp: 1655054125.7036886 iteration: 58950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.08683 FastRCNN total loss: 0.17402 L1 loss: 0.0000e+00 L2 loss: 0.57093 Learning rate: 0.002 Mask loss: 0.13394 RPN box loss: 0.01383 RPN score loss: 0.00826 RPN total loss: 0.02209 Total loss: 0.90097 timestamp: 1655054128.9999645 iteration: 58955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10287 FastRCNN class loss: 0.07485 FastRCNN total loss: 0.17772 L1 loss: 0.0000e+00 L2 loss: 0.57092 Learning rate: 0.002 Mask loss: 0.14647 RPN box loss: 0.00852 RPN score loss: 0.00625 RPN total loss: 0.01476 Total loss: 0.90988 timestamp: 1655054132.2460978 iteration: 58960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14905 FastRCNN class loss: 0.08375 FastRCNN total loss: 0.2328 L1 loss: 0.0000e+00 L2 loss: 0.57091 Learning rate: 0.002 Mask loss: 0.15399 RPN box loss: 0.01268 RPN score loss: 0.00176 RPN total loss: 0.01444 Total loss: 0.97214 timestamp: 1655054135.5729392 iteration: 58965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10206 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.15529 L1 loss: 0.0000e+00 L2 loss: 0.57091 Learning rate: 0.002 Mask loss: 0.15261 RPN box loss: 0.0453 RPN score loss: 0.00269 RPN total loss: 0.048 Total loss: 0.92681 timestamp: 1655054138.8636644 iteration: 58970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10639 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.16968 L1 loss: 0.0000e+00 L2 loss: 0.5709 Learning rate: 0.002 Mask loss: 0.14466 RPN box loss: 0.01614 RPN score loss: 0.00303 RPN total loss: 0.01917 Total loss: 0.90442 timestamp: 1655054142.178026 iteration: 58975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10671 FastRCNN class loss: 0.10523 FastRCNN total loss: 0.21194 L1 loss: 0.0000e+00 L2 loss: 0.5709 Learning rate: 0.002 Mask loss: 0.16219 RPN box loss: 0.01232 RPN score loss: 0.00372 RPN total loss: 0.01604 Total loss: 0.96107 timestamp: 1655054145.4350069 iteration: 58980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08387 FastRCNN class loss: 0.04261 FastRCNN total loss: 0.12648 L1 loss: 0.0000e+00 L2 loss: 0.57089 Learning rate: 0.002 Mask loss: 0.09098 RPN box loss: 0.00737 RPN score loss: 0.00257 RPN total loss: 0.00995 Total loss: 0.79829 timestamp: 1655054148.742529 iteration: 58985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13879 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.20047 L1 loss: 0.0000e+00 L2 loss: 0.57088 Learning rate: 0.002 Mask loss: 0.10686 RPN box loss: 0.0202 RPN score loss: 0.00154 RPN total loss: 0.02173 Total loss: 0.89994 timestamp: 1655054152.0255487 iteration: 58990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1366 FastRCNN class loss: 0.08224 FastRCNN total loss: 0.21884 L1 loss: 0.0000e+00 L2 loss: 0.57087 Learning rate: 0.002 Mask loss: 0.15754 RPN box loss: 0.01757 RPN score loss: 0.00609 RPN total loss: 0.02365 Total loss: 0.9709 timestamp: 1655054155.2556808 iteration: 58995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05876 FastRCNN class loss: 0.061 FastRCNN total loss: 0.11976 L1 loss: 0.0000e+00 L2 loss: 0.57086 Learning rate: 0.002 Mask loss: 0.11605 RPN box loss: 0.02742 RPN score loss: 0.00982 RPN total loss: 0.03724 Total loss: 0.84391 timestamp: 1655054158.490626 iteration: 59000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10162 FastRCNN class loss: 0.0333 FastRCNN total loss: 0.13492 L1 loss: 0.0000e+00 L2 loss: 0.57085 Learning rate: 0.002 Mask loss: 0.11282 RPN box loss: 0.02697 RPN score loss: 0.00245 RPN total loss: 0.02941 Total loss: 0.84801 timestamp: 1655054161.813727 iteration: 59005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15904 FastRCNN class loss: 0.09752 FastRCNN total loss: 0.25656 L1 loss: 0.0000e+00 L2 loss: 0.57084 Learning rate: 0.002 Mask loss: 0.15922 RPN box loss: 0.01485 RPN score loss: 0.00278 RPN total loss: 0.01763 Total loss: 1.00426 timestamp: 1655054165.0883796 iteration: 59010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12157 FastRCNN class loss: 0.09554 FastRCNN total loss: 0.21711 L1 loss: 0.0000e+00 L2 loss: 0.57084 Learning rate: 0.002 Mask loss: 0.11871 RPN box loss: 0.01416 RPN score loss: 0.0024 RPN total loss: 0.01656 Total loss: 0.92322 timestamp: 1655054168.3383248 iteration: 59015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07588 FastRCNN class loss: 0.09114 FastRCNN total loss: 0.16702 L1 loss: 0.0000e+00 L2 loss: 0.57083 Learning rate: 0.002 Mask loss: 0.17709 RPN box loss: 0.0171 RPN score loss: 0.00187 RPN total loss: 0.01897 Total loss: 0.9339 timestamp: 1655054171.6416361 iteration: 59020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.0517 FastRCNN total loss: 0.12551 L1 loss: 0.0000e+00 L2 loss: 0.57083 Learning rate: 0.002 Mask loss: 0.14868 RPN box loss: 0.01739 RPN score loss: 0.00598 RPN total loss: 0.02337 Total loss: 0.86839 timestamp: 1655054174.9912355 iteration: 59025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08375 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.16281 L1 loss: 0.0000e+00 L2 loss: 0.57082 Learning rate: 0.002 Mask loss: 0.13664 RPN box loss: 0.0173 RPN score loss: 0.00827 RPN total loss: 0.02557 Total loss: 0.89584 timestamp: 1655054178.3301234 iteration: 59030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05712 FastRCNN class loss: 0.03559 FastRCNN total loss: 0.09271 L1 loss: 0.0000e+00 L2 loss: 0.57081 Learning rate: 0.002 Mask loss: 0.12449 RPN box loss: 0.00996 RPN score loss: 0.00454 RPN total loss: 0.0145 Total loss: 0.80251 timestamp: 1655054181.5358286 iteration: 59035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14188 FastRCNN class loss: 0.15224 FastRCNN total loss: 0.29412 L1 loss: 0.0000e+00 L2 loss: 0.5708 Learning rate: 0.002 Mask loss: 0.26213 RPN box loss: 0.02169 RPN score loss: 0.00965 RPN total loss: 0.03134 Total loss: 1.15839 timestamp: 1655054184.8875182 iteration: 59040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15656 FastRCNN class loss: 0.15037 FastRCNN total loss: 0.30693 L1 loss: 0.0000e+00 L2 loss: 0.57079 Learning rate: 0.002 Mask loss: 0.18939 RPN box loss: 0.01453 RPN score loss: 0.00406 RPN total loss: 0.01859 Total loss: 1.0857 timestamp: 1655054188.137067 iteration: 59045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12133 FastRCNN class loss: 0.08344 FastRCNN total loss: 0.20477 L1 loss: 0.0000e+00 L2 loss: 0.57078 Learning rate: 0.002 Mask loss: 0.16789 RPN box loss: 0.02016 RPN score loss: 0.01132 RPN total loss: 0.03148 Total loss: 0.97492 timestamp: 1655054191.436671 iteration: 59050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12683 FastRCNN class loss: 0.09809 FastRCNN total loss: 0.22492 L1 loss: 0.0000e+00 L2 loss: 0.57078 Learning rate: 0.002 Mask loss: 0.21085 RPN box loss: 0.02032 RPN score loss: 0.0072 RPN total loss: 0.02752 Total loss: 1.03406 timestamp: 1655054194.7063587 iteration: 59055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06927 FastRCNN class loss: 0.08786 FastRCNN total loss: 0.15713 L1 loss: 0.0000e+00 L2 loss: 0.57077 Learning rate: 0.002 Mask loss: 0.15321 RPN box loss: 0.00792 RPN score loss: 0.00165 RPN total loss: 0.00957 Total loss: 0.89067 timestamp: 1655054197.9492009 iteration: 59060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16281 FastRCNN class loss: 0.13934 FastRCNN total loss: 0.30215 L1 loss: 0.0000e+00 L2 loss: 0.57076 Learning rate: 0.002 Mask loss: 0.12444 RPN box loss: 0.01099 RPN score loss: 0.00781 RPN total loss: 0.0188 Total loss: 1.01614 timestamp: 1655054201.2080743 iteration: 59065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1037 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.15851 L1 loss: 0.0000e+00 L2 loss: 0.57075 Learning rate: 0.002 Mask loss: 0.12344 RPN box loss: 0.0223 RPN score loss: 0.00326 RPN total loss: 0.02557 Total loss: 0.87827 timestamp: 1655054204.4971232 iteration: 59070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07797 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.14367 L1 loss: 0.0000e+00 L2 loss: 0.57074 Learning rate: 0.002 Mask loss: 0.10848 RPN box loss: 0.01264 RPN score loss: 0.00077 RPN total loss: 0.01341 Total loss: 0.8363 timestamp: 1655054207.8038065 iteration: 59075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13116 FastRCNN class loss: 0.08709 FastRCNN total loss: 0.21824 L1 loss: 0.0000e+00 L2 loss: 0.57073 Learning rate: 0.002 Mask loss: 0.15861 RPN box loss: 0.01295 RPN score loss: 0.00897 RPN total loss: 0.02191 Total loss: 0.9695 timestamp: 1655054211.157017 iteration: 59080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07377 FastRCNN class loss: 0.05628 FastRCNN total loss: 0.13004 L1 loss: 0.0000e+00 L2 loss: 0.57073 Learning rate: 0.002 Mask loss: 0.11101 RPN box loss: 0.0089 RPN score loss: 0.01651 RPN total loss: 0.02541 Total loss: 0.83718 timestamp: 1655054214.476433 iteration: 59085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13974 FastRCNN class loss: 0.04724 FastRCNN total loss: 0.18698 L1 loss: 0.0000e+00 L2 loss: 0.57072 Learning rate: 0.002 Mask loss: 0.15904 RPN box loss: 0.08659 RPN score loss: 0.00695 RPN total loss: 0.09354 Total loss: 1.01028 timestamp: 1655054217.7188444 iteration: 59090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05116 FastRCNN class loss: 0.03865 FastRCNN total loss: 0.08981 L1 loss: 0.0000e+00 L2 loss: 0.57071 Learning rate: 0.002 Mask loss: 0.13522 RPN box loss: 0.01817 RPN score loss: 0.00083 RPN total loss: 0.019 Total loss: 0.81474 timestamp: 1655054220.963841 iteration: 59095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09858 FastRCNN class loss: 0.04948 FastRCNN total loss: 0.14806 L1 loss: 0.0000e+00 L2 loss: 0.57071 Learning rate: 0.002 Mask loss: 0.08058 RPN box loss: 0.02049 RPN score loss: 0.00412 RPN total loss: 0.0246 Total loss: 0.82394 timestamp: 1655054224.2298872 iteration: 59100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05105 FastRCNN class loss: 0.05818 FastRCNN total loss: 0.10922 L1 loss: 0.0000e+00 L2 loss: 0.5707 Learning rate: 0.002 Mask loss: 0.09673 RPN box loss: 0.00738 RPN score loss: 0.00282 RPN total loss: 0.0102 Total loss: 0.78685 timestamp: 1655054227.46261 iteration: 59105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14887 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.22579 L1 loss: 0.0000e+00 L2 loss: 0.57069 Learning rate: 0.002 Mask loss: 0.15143 RPN box loss: 0.04874 RPN score loss: 0.00969 RPN total loss: 0.05843 Total loss: 1.00634 timestamp: 1655054230.7457628 iteration: 59110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.11331 FastRCNN total loss: 0.20762 L1 loss: 0.0000e+00 L2 loss: 0.57068 Learning rate: 0.002 Mask loss: 0.14159 RPN box loss: 0.06346 RPN score loss: 0.01471 RPN total loss: 0.07817 Total loss: 0.99806 timestamp: 1655054233.9716947 iteration: 59115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10684 FastRCNN class loss: 0.0988 FastRCNN total loss: 0.20564 L1 loss: 0.0000e+00 L2 loss: 0.57067 Learning rate: 0.002 Mask loss: 0.11854 RPN box loss: 0.01797 RPN score loss: 0.00144 RPN total loss: 0.01941 Total loss: 0.91427 timestamp: 1655054237.2132206 iteration: 59120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07845 FastRCNN class loss: 0.05932 FastRCNN total loss: 0.13777 L1 loss: 0.0000e+00 L2 loss: 0.57067 Learning rate: 0.002 Mask loss: 0.12304 RPN box loss: 0.00924 RPN score loss: 0.00154 RPN total loss: 0.01078 Total loss: 0.84225 timestamp: 1655054240.4987004 iteration: 59125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.04614 FastRCNN total loss: 0.14029 L1 loss: 0.0000e+00 L2 loss: 0.57066 Learning rate: 0.002 Mask loss: 0.12384 RPN box loss: 0.01114 RPN score loss: 0.00435 RPN total loss: 0.01549 Total loss: 0.85028 timestamp: 1655054243.7233622 iteration: 59130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11531 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.19739 L1 loss: 0.0000e+00 L2 loss: 0.57065 Learning rate: 0.002 Mask loss: 0.2061 RPN box loss: 0.00755 RPN score loss: 0.00896 RPN total loss: 0.01651 Total loss: 0.99065 timestamp: 1655054247.0027041 iteration: 59135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09096 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.14918 L1 loss: 0.0000e+00 L2 loss: 0.57064 Learning rate: 0.002 Mask loss: 0.13198 RPN box loss: 0.02377 RPN score loss: 0.00662 RPN total loss: 0.03039 Total loss: 0.88218 timestamp: 1655054250.2618697 iteration: 59140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13518 FastRCNN class loss: 0.08666 FastRCNN total loss: 0.22183 L1 loss: 0.0000e+00 L2 loss: 0.57063 Learning rate: 0.002 Mask loss: 0.12004 RPN box loss: 0.01555 RPN score loss: 0.00318 RPN total loss: 0.01872 Total loss: 0.93123 timestamp: 1655054253.573356 iteration: 59145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10472 FastRCNN class loss: 0.07447 FastRCNN total loss: 0.17919 L1 loss: 0.0000e+00 L2 loss: 0.57063 Learning rate: 0.002 Mask loss: 0.20964 RPN box loss: 0.02394 RPN score loss: 0.00503 RPN total loss: 0.02897 Total loss: 0.98842 timestamp: 1655054256.8150475 iteration: 59150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.15643 L1 loss: 0.0000e+00 L2 loss: 0.57062 Learning rate: 0.002 Mask loss: 0.20978 RPN box loss: 0.00896 RPN score loss: 0.01087 RPN total loss: 0.01983 Total loss: 0.95665 timestamp: 1655054260.0472548 iteration: 59155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08164 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.15676 L1 loss: 0.0000e+00 L2 loss: 0.57061 Learning rate: 0.002 Mask loss: 0.13132 RPN box loss: 0.00938 RPN score loss: 0.00139 RPN total loss: 0.01078 Total loss: 0.86947 timestamp: 1655054263.3640928 iteration: 59160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07741 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.14528 L1 loss: 0.0000e+00 L2 loss: 0.5706 Learning rate: 0.002 Mask loss: 0.15365 RPN box loss: 0.0115 RPN score loss: 0.00195 RPN total loss: 0.01345 Total loss: 0.88297 timestamp: 1655054266.6423166 iteration: 59165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12322 FastRCNN class loss: 0.06723 FastRCNN total loss: 0.19045 L1 loss: 0.0000e+00 L2 loss: 0.57059 Learning rate: 0.002 Mask loss: 0.15907 RPN box loss: 0.02102 RPN score loss: 0.01832 RPN total loss: 0.03934 Total loss: 0.95944 timestamp: 1655054269.8780847 iteration: 59170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07032 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.12251 L1 loss: 0.0000e+00 L2 loss: 0.57059 Learning rate: 0.002 Mask loss: 0.06722 RPN box loss: 0.00756 RPN score loss: 0.00143 RPN total loss: 0.00898 Total loss: 0.7693 timestamp: 1655054273.1592736 iteration: 59175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09452 FastRCNN class loss: 0.04827 FastRCNN total loss: 0.14279 L1 loss: 0.0000e+00 L2 loss: 0.57058 Learning rate: 0.002 Mask loss: 0.08498 RPN box loss: 0.00963 RPN score loss: 0.00665 RPN total loss: 0.01628 Total loss: 0.81463 timestamp: 1655054276.443743 iteration: 59180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06153 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.13342 L1 loss: 0.0000e+00 L2 loss: 0.57057 Learning rate: 0.002 Mask loss: 0.09791 RPN box loss: 0.00893 RPN score loss: 0.00502 RPN total loss: 0.01395 Total loss: 0.81585 timestamp: 1655054279.725729 iteration: 59185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10497 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.17613 L1 loss: 0.0000e+00 L2 loss: 0.57056 Learning rate: 0.002 Mask loss: 0.17277 RPN box loss: 0.0287 RPN score loss: 0.01078 RPN total loss: 0.03948 Total loss: 0.95894 timestamp: 1655054282.9547327 iteration: 59190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06288 FastRCNN class loss: 0.07267 FastRCNN total loss: 0.13554 L1 loss: 0.0000e+00 L2 loss: 0.57056 Learning rate: 0.002 Mask loss: 0.1406 RPN box loss: 0.00811 RPN score loss: 0.00453 RPN total loss: 0.01264 Total loss: 0.85934 timestamp: 1655054286.2370298 iteration: 59195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09644 FastRCNN class loss: 0.06973 FastRCNN total loss: 0.16617 L1 loss: 0.0000e+00 L2 loss: 0.57054 Learning rate: 0.002 Mask loss: 0.16153 RPN box loss: 0.01466 RPN score loss: 0.00628 RPN total loss: 0.02094 Total loss: 0.91918 timestamp: 1655054289.4003072 iteration: 59200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1343 FastRCNN class loss: 0.17109 FastRCNN total loss: 0.30539 L1 loss: 0.0000e+00 L2 loss: 0.57053 Learning rate: 0.002 Mask loss: 0.11729 RPN box loss: 0.01234 RPN score loss: 0.00914 RPN total loss: 0.02148 Total loss: 1.01469 timestamp: 1655054292.6065254 iteration: 59205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13114 FastRCNN class loss: 0.06425 FastRCNN total loss: 0.19539 L1 loss: 0.0000e+00 L2 loss: 0.57052 Learning rate: 0.002 Mask loss: 0.14119 RPN box loss: 0.01128 RPN score loss: 0.00438 RPN total loss: 0.01566 Total loss: 0.92277 timestamp: 1655054295.8587244 iteration: 59210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06211 FastRCNN class loss: 0.0381 FastRCNN total loss: 0.10021 L1 loss: 0.0000e+00 L2 loss: 0.57052 Learning rate: 0.002 Mask loss: 0.08164 RPN box loss: 0.00778 RPN score loss: 0.00668 RPN total loss: 0.01446 Total loss: 0.76683 timestamp: 1655054299.0710504 iteration: 59215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09339 FastRCNN class loss: 0.07546 FastRCNN total loss: 0.16885 L1 loss: 0.0000e+00 L2 loss: 0.5705 Learning rate: 0.002 Mask loss: 0.0985 RPN box loss: 0.00833 RPN score loss: 0.00261 RPN total loss: 0.01094 Total loss: 0.8488 timestamp: 1655054302.322005 iteration: 59220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1435 FastRCNN class loss: 0.05756 FastRCNN total loss: 0.20107 L1 loss: 0.0000e+00 L2 loss: 0.5705 Learning rate: 0.002 Mask loss: 0.1396 RPN box loss: 0.01655 RPN score loss: 0.00244 RPN total loss: 0.01898 Total loss: 0.93015 timestamp: 1655054305.4677172 iteration: 59225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.11982 L1 loss: 0.0000e+00 L2 loss: 0.57049 Learning rate: 0.002 Mask loss: 0.13977 RPN box loss: 0.00999 RPN score loss: 0.00322 RPN total loss: 0.01321 Total loss: 0.84329 timestamp: 1655054308.6993876 iteration: 59230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07585 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.13622 L1 loss: 0.0000e+00 L2 loss: 0.57048 Learning rate: 0.002 Mask loss: 0.10659 RPN box loss: 0.02198 RPN score loss: 0.00549 RPN total loss: 0.02747 Total loss: 0.84076 timestamp: 1655054311.9406412 iteration: 59235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09386 FastRCNN class loss: 0.04761 FastRCNN total loss: 0.14147 L1 loss: 0.0000e+00 L2 loss: 0.57048 Learning rate: 0.002 Mask loss: 0.1174 RPN box loss: 0.00509 RPN score loss: 0.00284 RPN total loss: 0.00793 Total loss: 0.83728 timestamp: 1655054315.1914718 iteration: 59240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.1178 FastRCNN total loss: 0.20994 L1 loss: 0.0000e+00 L2 loss: 0.57047 Learning rate: 0.002 Mask loss: 0.22316 RPN box loss: 0.02395 RPN score loss: 0.02936 RPN total loss: 0.05331 Total loss: 1.05687 timestamp: 1655054318.4153547 iteration: 59245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14611 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.22775 L1 loss: 0.0000e+00 L2 loss: 0.57046 Learning rate: 0.002 Mask loss: 0.15033 RPN box loss: 0.02704 RPN score loss: 0.00995 RPN total loss: 0.03699 Total loss: 0.98553 timestamp: 1655054321.625402 iteration: 59250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11316 FastRCNN class loss: 0.09793 FastRCNN total loss: 0.21109 L1 loss: 0.0000e+00 L2 loss: 0.57045 Learning rate: 0.002 Mask loss: 0.13466 RPN box loss: 0.01668 RPN score loss: 0.01069 RPN total loss: 0.02737 Total loss: 0.94357 timestamp: 1655054324.8981848 iteration: 59255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.05167 FastRCNN total loss: 0.12275 L1 loss: 0.0000e+00 L2 loss: 0.57044 Learning rate: 0.002 Mask loss: 0.1725 RPN box loss: 0.00734 RPN score loss: 0.00877 RPN total loss: 0.01611 Total loss: 0.88181 timestamp: 1655054328.238739 iteration: 59260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11962 FastRCNN class loss: 0.0874 FastRCNN total loss: 0.20702 L1 loss: 0.0000e+00 L2 loss: 0.57043 Learning rate: 0.002 Mask loss: 0.16816 RPN box loss: 0.01286 RPN score loss: 0.00855 RPN total loss: 0.02142 Total loss: 0.96703 timestamp: 1655054331.5485818 iteration: 59265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.13673 L1 loss: 0.0000e+00 L2 loss: 0.57043 Learning rate: 0.002 Mask loss: 0.1649 RPN box loss: 0.01875 RPN score loss: 0.01337 RPN total loss: 0.03212 Total loss: 0.90417 timestamp: 1655054334.8352246 iteration: 59270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07319 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.13443 L1 loss: 0.0000e+00 L2 loss: 0.57042 Learning rate: 0.002 Mask loss: 0.13549 RPN box loss: 0.01597 RPN score loss: 0.00464 RPN total loss: 0.02061 Total loss: 0.86095 timestamp: 1655054338.1143398 iteration: 59275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.06802 FastRCNN total loss: 0.14261 L1 loss: 0.0000e+00 L2 loss: 0.57041 Learning rate: 0.002 Mask loss: 0.09664 RPN box loss: 0.01923 RPN score loss: 0.001 RPN total loss: 0.02023 Total loss: 0.82989 timestamp: 1655054341.2725475 iteration: 59280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10411 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.1672 L1 loss: 0.0000e+00 L2 loss: 0.5704 Learning rate: 0.002 Mask loss: 0.12423 RPN box loss: 0.02698 RPN score loss: 0.00262 RPN total loss: 0.0296 Total loss: 0.89143 timestamp: 1655054344.44073 iteration: 59285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1542 FastRCNN class loss: 0.07063 FastRCNN total loss: 0.22483 L1 loss: 0.0000e+00 L2 loss: 0.57039 Learning rate: 0.002 Mask loss: 0.12479 RPN box loss: 0.0173 RPN score loss: 0.00661 RPN total loss: 0.02391 Total loss: 0.94392 timestamp: 1655054347.7090294 iteration: 59290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14061 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.21762 L1 loss: 0.0000e+00 L2 loss: 0.57038 Learning rate: 0.002 Mask loss: 0.12344 RPN box loss: 0.00437 RPN score loss: 0.00187 RPN total loss: 0.00624 Total loss: 0.91768 timestamp: 1655054350.9593265 iteration: 59295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08317 FastRCNN class loss: 0.058 FastRCNN total loss: 0.14117 L1 loss: 0.0000e+00 L2 loss: 0.57038 Learning rate: 0.002 Mask loss: 0.11166 RPN box loss: 0.00834 RPN score loss: 0.00616 RPN total loss: 0.0145 Total loss: 0.8377 timestamp: 1655054354.2879453 iteration: 59300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.10225 FastRCNN total loss: 0.17796 L1 loss: 0.0000e+00 L2 loss: 0.57037 Learning rate: 0.002 Mask loss: 0.14191 RPN box loss: 0.02362 RPN score loss: 0.00503 RPN total loss: 0.02865 Total loss: 0.91889 timestamp: 1655054357.4934492 iteration: 59305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07959 FastRCNN class loss: 0.06544 FastRCNN total loss: 0.14503 L1 loss: 0.0000e+00 L2 loss: 0.57036 Learning rate: 0.002 Mask loss: 0.12797 RPN box loss: 0.008 RPN score loss: 0.0054 RPN total loss: 0.0134 Total loss: 0.85676 timestamp: 1655054360.7371755 iteration: 59310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.04538 FastRCNN total loss: 0.11895 L1 loss: 0.0000e+00 L2 loss: 0.57035 Learning rate: 0.002 Mask loss: 0.11785 RPN box loss: 0.01467 RPN score loss: 0.00518 RPN total loss: 0.01985 Total loss: 0.827 timestamp: 1655054363.9842298 iteration: 59315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15257 FastRCNN class loss: 0.10823 FastRCNN total loss: 0.26079 L1 loss: 0.0000e+00 L2 loss: 0.57034 Learning rate: 0.002 Mask loss: 0.18755 RPN box loss: 0.02528 RPN score loss: 0.00864 RPN total loss: 0.03392 Total loss: 1.05261 timestamp: 1655054367.294526 iteration: 59320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10991 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.1714 L1 loss: 0.0000e+00 L2 loss: 0.57034 Learning rate: 0.002 Mask loss: 0.13959 RPN box loss: 0.00307 RPN score loss: 0.00271 RPN total loss: 0.00577 Total loss: 0.8871 timestamp: 1655054370.5500078 iteration: 59325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08002 FastRCNN class loss: 0.06979 FastRCNN total loss: 0.14981 L1 loss: 0.0000e+00 L2 loss: 0.57033 Learning rate: 0.002 Mask loss: 0.22137 RPN box loss: 0.00831 RPN score loss: 0.00672 RPN total loss: 0.01503 Total loss: 0.95654 timestamp: 1655054373.7935202 iteration: 59330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10728 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.18898 L1 loss: 0.0000e+00 L2 loss: 0.57032 Learning rate: 0.002 Mask loss: 0.13174 RPN box loss: 0.01522 RPN score loss: 0.00784 RPN total loss: 0.02306 Total loss: 0.9141 timestamp: 1655054377.1226575 iteration: 59335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11394 FastRCNN class loss: 0.06482 FastRCNN total loss: 0.17876 L1 loss: 0.0000e+00 L2 loss: 0.57032 Learning rate: 0.002 Mask loss: 0.0841 RPN box loss: 0.01403 RPN score loss: 0.00579 RPN total loss: 0.01982 Total loss: 0.853 timestamp: 1655054380.3693912 iteration: 59340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11885 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.18457 L1 loss: 0.0000e+00 L2 loss: 0.5703 Learning rate: 0.002 Mask loss: 0.16982 RPN box loss: 0.01887 RPN score loss: 0.00912 RPN total loss: 0.02799 Total loss: 0.95269 timestamp: 1655054383.6267884 iteration: 59345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1006 FastRCNN class loss: 0.08592 FastRCNN total loss: 0.18652 L1 loss: 0.0000e+00 L2 loss: 0.57029 Learning rate: 0.002 Mask loss: 0.15976 RPN box loss: 0.01431 RPN score loss: 0.00947 RPN total loss: 0.02379 Total loss: 0.94036 timestamp: 1655054386.9256785 iteration: 59350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13539 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.20972 L1 loss: 0.0000e+00 L2 loss: 0.57029 Learning rate: 0.002 Mask loss: 0.11466 RPN box loss: 0.01871 RPN score loss: 0.00446 RPN total loss: 0.02317 Total loss: 0.91784 timestamp: 1655054390.2225893 iteration: 59355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12077 FastRCNN class loss: 0.10594 FastRCNN total loss: 0.22671 L1 loss: 0.0000e+00 L2 loss: 0.57028 Learning rate: 0.002 Mask loss: 0.19997 RPN box loss: 0.02389 RPN score loss: 0.0149 RPN total loss: 0.03879 Total loss: 1.03575 timestamp: 1655054393.4759305 iteration: 59360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12875 FastRCNN class loss: 0.05316 FastRCNN total loss: 0.18191 L1 loss: 0.0000e+00 L2 loss: 0.57027 Learning rate: 0.002 Mask loss: 0.08492 RPN box loss: 0.00962 RPN score loss: 0.00721 RPN total loss: 0.01683 Total loss: 0.85393 timestamp: 1655054396.7072294 iteration: 59365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08425 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.15655 L1 loss: 0.0000e+00 L2 loss: 0.57026 Learning rate: 0.002 Mask loss: 0.14704 RPN box loss: 0.01059 RPN score loss: 0.00413 RPN total loss: 0.01472 Total loss: 0.88857 timestamp: 1655054399.9936469 iteration: 59370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08775 FastRCNN class loss: 0.0652 FastRCNN total loss: 0.15295 L1 loss: 0.0000e+00 L2 loss: 0.57025 Learning rate: 0.002 Mask loss: 0.17718 RPN box loss: 0.03652 RPN score loss: 0.01105 RPN total loss: 0.04757 Total loss: 0.94795 timestamp: 1655054403.2857144 iteration: 59375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12862 FastRCNN class loss: 0.11265 FastRCNN total loss: 0.24128 L1 loss: 0.0000e+00 L2 loss: 0.57024 Learning rate: 0.002 Mask loss: 0.15266 RPN box loss: 0.01249 RPN score loss: 0.00558 RPN total loss: 0.01806 Total loss: 0.98225 timestamp: 1655054406.5317822 iteration: 59380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14343 FastRCNN class loss: 0.1007 FastRCNN total loss: 0.24414 L1 loss: 0.0000e+00 L2 loss: 0.57024 Learning rate: 0.002 Mask loss: 0.13995 RPN box loss: 0.01675 RPN score loss: 0.01482 RPN total loss: 0.03157 Total loss: 0.98589 timestamp: 1655054409.779874 iteration: 59385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08766 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.17129 L1 loss: 0.0000e+00 L2 loss: 0.57023 Learning rate: 0.002 Mask loss: 0.14869 RPN box loss: 0.01731 RPN score loss: 0.00691 RPN total loss: 0.02422 Total loss: 0.91444 timestamp: 1655054412.9959688 iteration: 59390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.05269 FastRCNN total loss: 0.14538 L1 loss: 0.0000e+00 L2 loss: 0.57022 Learning rate: 0.002 Mask loss: 0.12489 RPN box loss: 0.01019 RPN score loss: 0.00198 RPN total loss: 0.01217 Total loss: 0.85266 timestamp: 1655054416.24291 iteration: 59395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13203 FastRCNN class loss: 0.10795 FastRCNN total loss: 0.23997 L1 loss: 0.0000e+00 L2 loss: 0.57021 Learning rate: 0.002 Mask loss: 0.14913 RPN box loss: 0.02212 RPN score loss: 0.03047 RPN total loss: 0.0526 Total loss: 1.01192 timestamp: 1655054419.477347 iteration: 59400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08228 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.13927 L1 loss: 0.0000e+00 L2 loss: 0.5702 Learning rate: 0.002 Mask loss: 0.22712 RPN box loss: 0.0243 RPN score loss: 0.00241 RPN total loss: 0.02671 Total loss: 0.9633 timestamp: 1655054422.811761 iteration: 59405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06053 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.12617 L1 loss: 0.0000e+00 L2 loss: 0.57019 Learning rate: 0.002 Mask loss: 0.1366 RPN box loss: 0.0247 RPN score loss: 0.00478 RPN total loss: 0.02948 Total loss: 0.86245 timestamp: 1655054426.1401026 iteration: 59410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0744 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.14372 L1 loss: 0.0000e+00 L2 loss: 0.57018 Learning rate: 0.002 Mask loss: 0.10133 RPN box loss: 0.01781 RPN score loss: 0.00442 RPN total loss: 0.02223 Total loss: 0.83746 timestamp: 1655054429.4554374 iteration: 59415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08128 FastRCNN class loss: 0.03423 FastRCNN total loss: 0.11551 L1 loss: 0.0000e+00 L2 loss: 0.57018 Learning rate: 0.002 Mask loss: 0.11823 RPN box loss: 0.00607 RPN score loss: 0.00241 RPN total loss: 0.00849 Total loss: 0.81241 timestamp: 1655054432.71603 iteration: 59420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07888 FastRCNN class loss: 0.07597 FastRCNN total loss: 0.15485 L1 loss: 0.0000e+00 L2 loss: 0.57017 Learning rate: 0.002 Mask loss: 0.1516 RPN box loss: 0.0273 RPN score loss: 0.00974 RPN total loss: 0.03704 Total loss: 0.91366 timestamp: 1655054435.9643078 iteration: 59425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10248 FastRCNN class loss: 0.07352 FastRCNN total loss: 0.176 L1 loss: 0.0000e+00 L2 loss: 0.57016 Learning rate: 0.002 Mask loss: 0.16225 RPN box loss: 0.01646 RPN score loss: 0.01393 RPN total loss: 0.03038 Total loss: 0.9388 timestamp: 1655054439.1780674 iteration: 59430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14805 FastRCNN class loss: 0.09166 FastRCNN total loss: 0.23971 L1 loss: 0.0000e+00 L2 loss: 0.57015 Learning rate: 0.002 Mask loss: 0.1824 RPN box loss: 0.03531 RPN score loss: 0.00375 RPN total loss: 0.03906 Total loss: 1.03132 timestamp: 1655054442.4421308 iteration: 59435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15894 FastRCNN class loss: 0.08476 FastRCNN total loss: 0.2437 L1 loss: 0.0000e+00 L2 loss: 0.57014 Learning rate: 0.002 Mask loss: 0.16366 RPN box loss: 0.02115 RPN score loss: 0.00538 RPN total loss: 0.02653 Total loss: 1.00403 timestamp: 1655054445.6977744 iteration: 59440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09553 FastRCNN class loss: 0.06896 FastRCNN total loss: 0.16449 L1 loss: 0.0000e+00 L2 loss: 0.57013 Learning rate: 0.002 Mask loss: 0.14573 RPN box loss: 0.01309 RPN score loss: 0.00215 RPN total loss: 0.01524 Total loss: 0.8956 timestamp: 1655054448.9194758 iteration: 59445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11485 FastRCNN class loss: 0.06889 FastRCNN total loss: 0.18374 L1 loss: 0.0000e+00 L2 loss: 0.57012 Learning rate: 0.002 Mask loss: 0.17895 RPN box loss: 0.03832 RPN score loss: 0.00649 RPN total loss: 0.04481 Total loss: 0.97763 timestamp: 1655054452.1641378 iteration: 59450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0532 FastRCNN class loss: 0.05772 FastRCNN total loss: 0.11091 L1 loss: 0.0000e+00 L2 loss: 0.57012 Learning rate: 0.002 Mask loss: 0.09005 RPN box loss: 0.01035 RPN score loss: 0.00328 RPN total loss: 0.01363 Total loss: 0.78471 timestamp: 1655054455.477592 iteration: 59455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.17312 L1 loss: 0.0000e+00 L2 loss: 0.57011 Learning rate: 0.002 Mask loss: 0.21207 RPN box loss: 0.02084 RPN score loss: 0.0081 RPN total loss: 0.02893 Total loss: 0.98423 timestamp: 1655054458.7345443 iteration: 59460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08697 FastRCNN class loss: 0.06513 FastRCNN total loss: 0.1521 L1 loss: 0.0000e+00 L2 loss: 0.5701 Learning rate: 0.002 Mask loss: 0.13829 RPN box loss: 0.01924 RPN score loss: 0.0081 RPN total loss: 0.02734 Total loss: 0.88783 timestamp: 1655054462.0093153 iteration: 59465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08336 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.14786 L1 loss: 0.0000e+00 L2 loss: 0.57009 Learning rate: 0.002 Mask loss: 0.11665 RPN box loss: 0.01662 RPN score loss: 0.00974 RPN total loss: 0.02636 Total loss: 0.86096 timestamp: 1655054465.289221 iteration: 59470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09816 FastRCNN class loss: 0.06181 FastRCNN total loss: 0.15998 L1 loss: 0.0000e+00 L2 loss: 0.57008 Learning rate: 0.002 Mask loss: 0.09265 RPN box loss: 0.00846 RPN score loss: 0.00218 RPN total loss: 0.01064 Total loss: 0.83336 timestamp: 1655054468.5118792 iteration: 59475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12982 FastRCNN class loss: 0.14136 FastRCNN total loss: 0.27118 L1 loss: 0.0000e+00 L2 loss: 0.57008 Learning rate: 0.002 Mask loss: 0.24896 RPN box loss: 0.03951 RPN score loss: 0.09064 RPN total loss: 0.13016 Total loss: 1.22038 timestamp: 1655054471.6997237 iteration: 59480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.11982 L1 loss: 0.0000e+00 L2 loss: 0.57007 Learning rate: 0.002 Mask loss: 0.1691 RPN box loss: 0.01209 RPN score loss: 0.00816 RPN total loss: 0.02025 Total loss: 0.87924 timestamp: 1655054474.988933 iteration: 59485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08336 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.15152 L1 loss: 0.0000e+00 L2 loss: 0.57006 Learning rate: 0.002 Mask loss: 0.20136 RPN box loss: 0.01401 RPN score loss: 0.00378 RPN total loss: 0.01779 Total loss: 0.94074 timestamp: 1655054478.2325764 iteration: 59490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09627 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.15868 L1 loss: 0.0000e+00 L2 loss: 0.57006 Learning rate: 0.002 Mask loss: 0.16373 RPN box loss: 0.0097 RPN score loss: 0.00256 RPN total loss: 0.01226 Total loss: 0.90473 timestamp: 1655054481.495595 iteration: 59495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15142 FastRCNN class loss: 0.09987 FastRCNN total loss: 0.25129 L1 loss: 0.0000e+00 L2 loss: 0.57005 Learning rate: 0.002 Mask loss: 0.1728 RPN box loss: 0.01609 RPN score loss: 0.00622 RPN total loss: 0.02231 Total loss: 1.01646 timestamp: 1655054484.7378654 iteration: 59500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15045 FastRCNN class loss: 0.08946 FastRCNN total loss: 0.23991 L1 loss: 0.0000e+00 L2 loss: 0.57004 Learning rate: 0.002 Mask loss: 0.17417 RPN box loss: 0.0146 RPN score loss: 0.00353 RPN total loss: 0.01813 Total loss: 1.00225 timestamp: 1655054487.9281712 iteration: 59505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07428 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.14088 L1 loss: 0.0000e+00 L2 loss: 0.57003 Learning rate: 0.002 Mask loss: 0.11228 RPN box loss: 0.01917 RPN score loss: 0.0021 RPN total loss: 0.02128 Total loss: 0.84447 timestamp: 1655054491.175467 iteration: 59510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14806 FastRCNN class loss: 0.05086 FastRCNN total loss: 0.19893 L1 loss: 0.0000e+00 L2 loss: 0.57003 Learning rate: 0.002 Mask loss: 0.13473 RPN box loss: 0.01754 RPN score loss: 0.00292 RPN total loss: 0.02046 Total loss: 0.92414 timestamp: 1655054494.4871817 iteration: 59515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11401 FastRCNN class loss: 0.09654 FastRCNN total loss: 0.21054 L1 loss: 0.0000e+00 L2 loss: 0.57002 Learning rate: 0.002 Mask loss: 0.16723 RPN box loss: 0.01419 RPN score loss: 0.00269 RPN total loss: 0.01688 Total loss: 0.96467 timestamp: 1655054497.7601428 iteration: 59520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05613 FastRCNN class loss: 0.07122 FastRCNN total loss: 0.12735 L1 loss: 0.0000e+00 L2 loss: 0.57001 Learning rate: 0.002 Mask loss: 0.13837 RPN box loss: 0.00746 RPN score loss: 0.00676 RPN total loss: 0.01422 Total loss: 0.84995 timestamp: 1655054501.0212798 iteration: 59525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.077 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.13807 L1 loss: 0.0000e+00 L2 loss: 0.57 Learning rate: 0.002 Mask loss: 0.12468 RPN box loss: 0.01654 RPN score loss: 0.01089 RPN total loss: 0.02743 Total loss: 0.86018 timestamp: 1655054504.331924 iteration: 59530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1214 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.19393 L1 loss: 0.0000e+00 L2 loss: 0.57 Learning rate: 0.002 Mask loss: 0.1371 RPN box loss: 0.02037 RPN score loss: 0.00344 RPN total loss: 0.02381 Total loss: 0.92483 timestamp: 1655054507.6328318 iteration: 59535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.16916 L1 loss: 0.0000e+00 L2 loss: 0.56999 Learning rate: 0.002 Mask loss: 0.15387 RPN box loss: 0.0115 RPN score loss: 0.00163 RPN total loss: 0.01312 Total loss: 0.90614 timestamp: 1655054510.888236 iteration: 59540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11809 FastRCNN class loss: 0.09912 FastRCNN total loss: 0.21721 L1 loss: 0.0000e+00 L2 loss: 0.56998 Learning rate: 0.002 Mask loss: 0.15837 RPN box loss: 0.01063 RPN score loss: 0.0021 RPN total loss: 0.01273 Total loss: 0.95828 timestamp: 1655054514.1136417 iteration: 59545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12134 FastRCNN class loss: 0.07535 FastRCNN total loss: 0.19669 L1 loss: 0.0000e+00 L2 loss: 0.56997 Learning rate: 0.002 Mask loss: 0.15723 RPN box loss: 0.02882 RPN score loss: 0.00769 RPN total loss: 0.03651 Total loss: 0.9604 timestamp: 1655054517.4205801 iteration: 59550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12459 FastRCNN class loss: 0.09443 FastRCNN total loss: 0.21901 L1 loss: 0.0000e+00 L2 loss: 0.56996 Learning rate: 0.002 Mask loss: 0.15 RPN box loss: 0.0083 RPN score loss: 0.00795 RPN total loss: 0.01625 Total loss: 0.95523 timestamp: 1655054520.6325657 iteration: 59555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11191 FastRCNN class loss: 0.07846 FastRCNN total loss: 0.19037 L1 loss: 0.0000e+00 L2 loss: 0.56995 Learning rate: 0.002 Mask loss: 0.14458 RPN box loss: 0.01947 RPN score loss: 0.00817 RPN total loss: 0.02764 Total loss: 0.93254 timestamp: 1655054523.852938 iteration: 59560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.07637 FastRCNN total loss: 0.20054 L1 loss: 0.0000e+00 L2 loss: 0.56994 Learning rate: 0.002 Mask loss: 0.11841 RPN box loss: 0.01464 RPN score loss: 0.0027 RPN total loss: 0.01733 Total loss: 0.90622 timestamp: 1655054527.1370609 iteration: 59565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0902 FastRCNN class loss: 0.04341 FastRCNN total loss: 0.1336 L1 loss: 0.0000e+00 L2 loss: 0.56994 Learning rate: 0.002 Mask loss: 0.09454 RPN box loss: 0.01015 RPN score loss: 0.00314 RPN total loss: 0.01329 Total loss: 0.81137 timestamp: 1655054530.4594004 iteration: 59570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.09658 FastRCNN total loss: 0.19937 L1 loss: 0.0000e+00 L2 loss: 0.56993 Learning rate: 0.002 Mask loss: 0.16556 RPN box loss: 0.02012 RPN score loss: 0.00726 RPN total loss: 0.02738 Total loss: 0.96224 timestamp: 1655054533.7269187 iteration: 59575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07307 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.1477 L1 loss: 0.0000e+00 L2 loss: 0.56992 Learning rate: 0.002 Mask loss: 0.12125 RPN box loss: 0.02032 RPN score loss: 0.00469 RPN total loss: 0.02501 Total loss: 0.86388 timestamp: 1655054536.9834428 iteration: 59580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13907 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.21105 L1 loss: 0.0000e+00 L2 loss: 0.56991 Learning rate: 0.002 Mask loss: 0.12307 RPN box loss: 0.01759 RPN score loss: 0.00651 RPN total loss: 0.0241 Total loss: 0.92814 timestamp: 1655054540.2349405 iteration: 59585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.08067 FastRCNN total loss: 0.1724 L1 loss: 0.0000e+00 L2 loss: 0.5699 Learning rate: 0.002 Mask loss: 0.16133 RPN box loss: 0.0087 RPN score loss: 0.00919 RPN total loss: 0.01789 Total loss: 0.92152 timestamp: 1655054543.4123745 iteration: 59590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09501 FastRCNN class loss: 0.06831 FastRCNN total loss: 0.16332 L1 loss: 0.0000e+00 L2 loss: 0.56989 Learning rate: 0.002 Mask loss: 0.11375 RPN box loss: 0.00687 RPN score loss: 0.00215 RPN total loss: 0.00901 Total loss: 0.85598 timestamp: 1655054546.6350904 iteration: 59595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13968 FastRCNN class loss: 0.07262 FastRCNN total loss: 0.2123 L1 loss: 0.0000e+00 L2 loss: 0.56988 Learning rate: 0.002 Mask loss: 0.13373 RPN box loss: 0.01283 RPN score loss: 0.00512 RPN total loss: 0.01795 Total loss: 0.93386 timestamp: 1655054549.8881936 iteration: 59600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09379 FastRCNN class loss: 0.07833 FastRCNN total loss: 0.17212 L1 loss: 0.0000e+00 L2 loss: 0.56987 Learning rate: 0.002 Mask loss: 0.1457 RPN box loss: 0.02176 RPN score loss: 0.00506 RPN total loss: 0.02682 Total loss: 0.91452 timestamp: 1655054553.2127473 iteration: 59605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1191 FastRCNN class loss: 0.05644 FastRCNN total loss: 0.17555 L1 loss: 0.0000e+00 L2 loss: 0.56986 Learning rate: 0.002 Mask loss: 0.13984 RPN box loss: 0.00793 RPN score loss: 0.0027 RPN total loss: 0.01063 Total loss: 0.89589 timestamp: 1655054556.503755 iteration: 59610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14113 FastRCNN class loss: 0.11103 FastRCNN total loss: 0.25215 L1 loss: 0.0000e+00 L2 loss: 0.56986 Learning rate: 0.002 Mask loss: 0.16143 RPN box loss: 0.03971 RPN score loss: 0.01845 RPN total loss: 0.05816 Total loss: 1.04159 timestamp: 1655054559.783868 iteration: 59615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09566 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.14775 L1 loss: 0.0000e+00 L2 loss: 0.56985 Learning rate: 0.002 Mask loss: 0.10031 RPN box loss: 0.02257 RPN score loss: 0.00236 RPN total loss: 0.02492 Total loss: 0.84283 timestamp: 1655054563.0573857 iteration: 59620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05388 FastRCNN class loss: 0.02766 FastRCNN total loss: 0.08154 L1 loss: 0.0000e+00 L2 loss: 0.56984 Learning rate: 0.002 Mask loss: 0.0918 RPN box loss: 0.01556 RPN score loss: 0.00131 RPN total loss: 0.01687 Total loss: 0.76005 timestamp: 1655054566.3728907 iteration: 59625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07359 FastRCNN class loss: 0.05735 FastRCNN total loss: 0.13094 L1 loss: 0.0000e+00 L2 loss: 0.56984 Learning rate: 0.002 Mask loss: 0.13212 RPN box loss: 0.00576 RPN score loss: 0.00417 RPN total loss: 0.00993 Total loss: 0.84282 timestamp: 1655054569.6880727 iteration: 59630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18548 FastRCNN class loss: 0.09756 FastRCNN total loss: 0.28305 L1 loss: 0.0000e+00 L2 loss: 0.56983 Learning rate: 0.002 Mask loss: 0.17419 RPN box loss: 0.01341 RPN score loss: 0.00589 RPN total loss: 0.01931 Total loss: 1.04638 timestamp: 1655054572.9784539 iteration: 59635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12397 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.1957 L1 loss: 0.0000e+00 L2 loss: 0.56982 Learning rate: 0.002 Mask loss: 0.1495 RPN box loss: 0.01073 RPN score loss: 0.00463 RPN total loss: 0.01536 Total loss: 0.93038 timestamp: 1655054576.2842796 iteration: 59640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12451 FastRCNN class loss: 0.04684 FastRCNN total loss: 0.17135 L1 loss: 0.0000e+00 L2 loss: 0.56981 Learning rate: 0.002 Mask loss: 0.15447 RPN box loss: 0.01915 RPN score loss: 0.00281 RPN total loss: 0.02196 Total loss: 0.9176 timestamp: 1655054579.5057962 iteration: 59645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13534 FastRCNN class loss: 0.07062 FastRCNN total loss: 0.20596 L1 loss: 0.0000e+00 L2 loss: 0.56981 Learning rate: 0.002 Mask loss: 0.11222 RPN box loss: 0.01168 RPN score loss: 0.00524 RPN total loss: 0.01692 Total loss: 0.90491 timestamp: 1655054582.804729 iteration: 59650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06024 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.12713 L1 loss: 0.0000e+00 L2 loss: 0.56979 Learning rate: 0.002 Mask loss: 0.12644 RPN box loss: 0.01741 RPN score loss: 0.00547 RPN total loss: 0.02288 Total loss: 0.84625 timestamp: 1655054586.059757 iteration: 59655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09792 FastRCNN class loss: 0.05362 FastRCNN total loss: 0.15154 L1 loss: 0.0000e+00 L2 loss: 0.56978 Learning rate: 0.002 Mask loss: 0.15122 RPN box loss: 0.01023 RPN score loss: 0.00219 RPN total loss: 0.01242 Total loss: 0.88496 timestamp: 1655054589.2614322 iteration: 59660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0969 FastRCNN class loss: 0.13596 FastRCNN total loss: 0.23287 L1 loss: 0.0000e+00 L2 loss: 0.56977 Learning rate: 0.002 Mask loss: 0.1498 RPN box loss: 0.02036 RPN score loss: 0.00247 RPN total loss: 0.02284 Total loss: 0.97528 timestamp: 1655054592.650322 iteration: 59665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11024 FastRCNN class loss: 0.0833 FastRCNN total loss: 0.19353 L1 loss: 0.0000e+00 L2 loss: 0.56977 Learning rate: 0.002 Mask loss: 0.2126 RPN box loss: 0.01859 RPN score loss: 0.00613 RPN total loss: 0.02472 Total loss: 1.00063 timestamp: 1655054595.9197128 iteration: 59670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.04836 FastRCNN total loss: 0.14988 L1 loss: 0.0000e+00 L2 loss: 0.56976 Learning rate: 0.002 Mask loss: 0.12434 RPN box loss: 0.00681 RPN score loss: 0.00295 RPN total loss: 0.00976 Total loss: 0.85374 timestamp: 1655054599.202865 iteration: 59675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0701 FastRCNN class loss: 0.04828 FastRCNN total loss: 0.11837 L1 loss: 0.0000e+00 L2 loss: 0.56976 Learning rate: 0.002 Mask loss: 0.14253 RPN box loss: 0.0155 RPN score loss: 0.00197 RPN total loss: 0.01747 Total loss: 0.84813 timestamp: 1655054602.5179007 iteration: 59680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11703 FastRCNN class loss: 0.04553 FastRCNN total loss: 0.16255 L1 loss: 0.0000e+00 L2 loss: 0.56975 Learning rate: 0.002 Mask loss: 0.11865 RPN box loss: 0.00524 RPN score loss: 0.00409 RPN total loss: 0.00933 Total loss: 0.86028 timestamp: 1655054605.8656008 iteration: 59685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06695 FastRCNN class loss: 0.03514 FastRCNN total loss: 0.10209 L1 loss: 0.0000e+00 L2 loss: 0.56974 Learning rate: 0.002 Mask loss: 0.13063 RPN box loss: 0.0274 RPN score loss: 0.00407 RPN total loss: 0.03147 Total loss: 0.83393 timestamp: 1655054609.1427813 iteration: 59690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05229 FastRCNN class loss: 0.05574 FastRCNN total loss: 0.10803 L1 loss: 0.0000e+00 L2 loss: 0.56973 Learning rate: 0.002 Mask loss: 0.12694 RPN box loss: 0.01448 RPN score loss: 0.00307 RPN total loss: 0.01754 Total loss: 0.82225 timestamp: 1655054612.4490547 iteration: 59695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11832 FastRCNN class loss: 0.04713 FastRCNN total loss: 0.16544 L1 loss: 0.0000e+00 L2 loss: 0.56972 Learning rate: 0.002 Mask loss: 0.10011 RPN box loss: 0.00423 RPN score loss: 0.0041 RPN total loss: 0.00833 Total loss: 0.8436 timestamp: 1655054615.7652092 iteration: 59700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14839 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.23123 L1 loss: 0.0000e+00 L2 loss: 0.56971 Learning rate: 0.002 Mask loss: 0.07423 RPN box loss: 0.00626 RPN score loss: 0.00204 RPN total loss: 0.00829 Total loss: 0.88346 timestamp: 1655054619.0452473 iteration: 59705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06806 FastRCNN class loss: 0.07364 FastRCNN total loss: 0.1417 L1 loss: 0.0000e+00 L2 loss: 0.5697 Learning rate: 0.002 Mask loss: 0.12972 RPN box loss: 0.00667 RPN score loss: 0.00425 RPN total loss: 0.01092 Total loss: 0.85204 timestamp: 1655054622.2562182 iteration: 59710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08644 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.14263 L1 loss: 0.0000e+00 L2 loss: 0.56969 Learning rate: 0.002 Mask loss: 0.1029 RPN box loss: 0.01859 RPN score loss: 0.00464 RPN total loss: 0.02324 Total loss: 0.83846 timestamp: 1655054625.4930754 iteration: 59715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10746 FastRCNN class loss: 0.09019 FastRCNN total loss: 0.19765 L1 loss: 0.0000e+00 L2 loss: 0.56969 Learning rate: 0.002 Mask loss: 0.16089 RPN box loss: 0.02169 RPN score loss: 0.01036 RPN total loss: 0.03205 Total loss: 0.96027 timestamp: 1655054628.793155 iteration: 59720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13421 FastRCNN class loss: 0.09611 FastRCNN total loss: 0.23032 L1 loss: 0.0000e+00 L2 loss: 0.56968 Learning rate: 0.002 Mask loss: 0.16839 RPN box loss: 0.02071 RPN score loss: 0.0107 RPN total loss: 0.03141 Total loss: 0.9998 timestamp: 1655054632.0783305 iteration: 59725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11272 FastRCNN class loss: 0.06896 FastRCNN total loss: 0.18168 L1 loss: 0.0000e+00 L2 loss: 0.56967 Learning rate: 0.002 Mask loss: 0.15509 RPN box loss: 0.02114 RPN score loss: 0.00499 RPN total loss: 0.02613 Total loss: 0.93257 timestamp: 1655054635.3649116 iteration: 59730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06751 FastRCNN class loss: 0.03311 FastRCNN total loss: 0.10063 L1 loss: 0.0000e+00 L2 loss: 0.56966 Learning rate: 0.002 Mask loss: 0.10008 RPN box loss: 0.00375 RPN score loss: 0.00075 RPN total loss: 0.0045 Total loss: 0.77487 timestamp: 1655054638.645431 iteration: 59735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04719 FastRCNN class loss: 0.03774 FastRCNN total loss: 0.08493 L1 loss: 0.0000e+00 L2 loss: 0.56965 Learning rate: 0.002 Mask loss: 0.12661 RPN box loss: 0.00455 RPN score loss: 0.0042 RPN total loss: 0.00875 Total loss: 0.78994 timestamp: 1655054641.9771056 iteration: 59740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07364 FastRCNN class loss: 0.10677 FastRCNN total loss: 0.18041 L1 loss: 0.0000e+00 L2 loss: 0.56965 Learning rate: 0.002 Mask loss: 0.15804 RPN box loss: 0.05717 RPN score loss: 0.01797 RPN total loss: 0.07514 Total loss: 0.98324 timestamp: 1655054645.2008562 iteration: 59745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08251 FastRCNN class loss: 0.06499 FastRCNN total loss: 0.14751 L1 loss: 0.0000e+00 L2 loss: 0.56964 Learning rate: 0.002 Mask loss: 0.1778 RPN box loss: 0.01521 RPN score loss: 0.00392 RPN total loss: 0.01913 Total loss: 0.91408 timestamp: 1655054648.4358594 iteration: 59750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10837 FastRCNN class loss: 0.08665 FastRCNN total loss: 0.19503 L1 loss: 0.0000e+00 L2 loss: 0.56963 Learning rate: 0.002 Mask loss: 0.18409 RPN box loss: 0.02199 RPN score loss: 0.00984 RPN total loss: 0.03183 Total loss: 0.98057 timestamp: 1655054651.7288978 iteration: 59755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05216 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.11827 L1 loss: 0.0000e+00 L2 loss: 0.56962 Learning rate: 0.002 Mask loss: 0.14083 RPN box loss: 0.02181 RPN score loss: 0.00933 RPN total loss: 0.03115 Total loss: 0.85987 timestamp: 1655054654.989508 iteration: 59760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05747 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.12319 L1 loss: 0.0000e+00 L2 loss: 0.56961 Learning rate: 0.002 Mask loss: 0.12757 RPN box loss: 0.00845 RPN score loss: 0.00531 RPN total loss: 0.01376 Total loss: 0.83413 timestamp: 1655054658.2741268 iteration: 59765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09725 FastRCNN class loss: 0.11233 FastRCNN total loss: 0.20958 L1 loss: 0.0000e+00 L2 loss: 0.5696 Learning rate: 0.002 Mask loss: 0.20031 RPN box loss: 0.01381 RPN score loss: 0.00883 RPN total loss: 0.02264 Total loss: 1.00214 timestamp: 1655054661.5131686 iteration: 59770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14211 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.21068 L1 loss: 0.0000e+00 L2 loss: 0.5696 Learning rate: 0.002 Mask loss: 0.12771 RPN box loss: 0.01038 RPN score loss: 0.00615 RPN total loss: 0.01653 Total loss: 0.92452 timestamp: 1655054664.7612386 iteration: 59775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14871 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.2264 L1 loss: 0.0000e+00 L2 loss: 0.56959 Learning rate: 0.002 Mask loss: 0.17135 RPN box loss: 0.04302 RPN score loss: 0.00365 RPN total loss: 0.04667 Total loss: 1.01401 timestamp: 1655054668.0109556 iteration: 59780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.12484 FastRCNN total loss: 0.23121 L1 loss: 0.0000e+00 L2 loss: 0.56959 Learning rate: 0.002 Mask loss: 0.14237 RPN box loss: 0.02601 RPN score loss: 0.00523 RPN total loss: 0.03124 Total loss: 0.9744 timestamp: 1655054671.2342026 iteration: 59785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11686 FastRCNN class loss: 0.10067 FastRCNN total loss: 0.21753 L1 loss: 0.0000e+00 L2 loss: 0.56958 Learning rate: 0.002 Mask loss: 0.1799 RPN box loss: 0.03091 RPN score loss: 0.00609 RPN total loss: 0.037 Total loss: 1.004 timestamp: 1655054674.496128 iteration: 59790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.05035 FastRCNN total loss: 0.13635 L1 loss: 0.0000e+00 L2 loss: 0.56957 Learning rate: 0.002 Mask loss: 0.13 RPN box loss: 0.00452 RPN score loss: 0.00303 RPN total loss: 0.00755 Total loss: 0.84347 timestamp: 1655054677.7566485 iteration: 59795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17513 FastRCNN class loss: 0.15323 FastRCNN total loss: 0.32837 L1 loss: 0.0000e+00 L2 loss: 0.56956 Learning rate: 0.002 Mask loss: 0.22586 RPN box loss: 0.04478 RPN score loss: 0.01775 RPN total loss: 0.06253 Total loss: 1.18632 timestamp: 1655054681.0754642 iteration: 59800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07665 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.14311 L1 loss: 0.0000e+00 L2 loss: 0.56955 Learning rate: 0.002 Mask loss: 0.11173 RPN box loss: 0.04044 RPN score loss: 0.00476 RPN total loss: 0.04519 Total loss: 0.86959 timestamp: 1655054684.3700876 iteration: 59805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08886 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.1308 L1 loss: 0.0000e+00 L2 loss: 0.56955 Learning rate: 0.002 Mask loss: 0.10029 RPN box loss: 0.00363 RPN score loss: 0.00312 RPN total loss: 0.00675 Total loss: 0.80739 timestamp: 1655054687.6942556 iteration: 59810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07437 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.12889 L1 loss: 0.0000e+00 L2 loss: 0.56954 Learning rate: 0.002 Mask loss: 0.10696 RPN box loss: 0.0087 RPN score loss: 0.00528 RPN total loss: 0.01398 Total loss: 0.81937 timestamp: 1655054690.9144154 iteration: 59815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07455 FastRCNN class loss: 0.09677 FastRCNN total loss: 0.17131 L1 loss: 0.0000e+00 L2 loss: 0.56953 Learning rate: 0.002 Mask loss: 0.1189 RPN box loss: 0.01899 RPN score loss: 0.01341 RPN total loss: 0.0324 Total loss: 0.89215 timestamp: 1655054694.2129433 iteration: 59820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11079 FastRCNN class loss: 0.06962 FastRCNN total loss: 0.18041 L1 loss: 0.0000e+00 L2 loss: 0.56952 Learning rate: 0.002 Mask loss: 0.17865 RPN box loss: 0.03617 RPN score loss: 0.00431 RPN total loss: 0.04048 Total loss: 0.96906 timestamp: 1655054697.4777904 iteration: 59825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13161 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.21492 L1 loss: 0.0000e+00 L2 loss: 0.56951 Learning rate: 0.002 Mask loss: 0.14663 RPN box loss: 0.00939 RPN score loss: 0.00465 RPN total loss: 0.01404 Total loss: 0.9451 timestamp: 1655054700.7022254 iteration: 59830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05645 FastRCNN class loss: 0.03363 FastRCNN total loss: 0.09008 L1 loss: 0.0000e+00 L2 loss: 0.5695 Learning rate: 0.002 Mask loss: 0.11429 RPN box loss: 0.00358 RPN score loss: 0.00439 RPN total loss: 0.00797 Total loss: 0.78185 timestamp: 1655054704.0235312 iteration: 59835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.166 FastRCNN class loss: 0.08871 FastRCNN total loss: 0.25472 L1 loss: 0.0000e+00 L2 loss: 0.5695 Learning rate: 0.002 Mask loss: 0.21833 RPN box loss: 0.01465 RPN score loss: 0.00323 RPN total loss: 0.01788 Total loss: 1.06042 timestamp: 1655054707.3089142 iteration: 59840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07246 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.13429 L1 loss: 0.0000e+00 L2 loss: 0.56949 Learning rate: 0.002 Mask loss: 0.13904 RPN box loss: 0.00749 RPN score loss: 0.00633 RPN total loss: 0.01382 Total loss: 0.85665 timestamp: 1655054710.582047 iteration: 59845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11994 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.20468 L1 loss: 0.0000e+00 L2 loss: 0.56949 Learning rate: 0.002 Mask loss: 0.11524 RPN box loss: 0.01561 RPN score loss: 0.01264 RPN total loss: 0.02825 Total loss: 0.91766 timestamp: 1655054713.9534223 iteration: 59850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08379 FastRCNN class loss: 0.06317 FastRCNN total loss: 0.14695 L1 loss: 0.0000e+00 L2 loss: 0.56948 Learning rate: 0.002 Mask loss: 0.13125 RPN box loss: 0.03698 RPN score loss: 0.00741 RPN total loss: 0.0444 Total loss: 0.89208 timestamp: 1655054717.2166138 iteration: 59855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11649 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.19689 L1 loss: 0.0000e+00 L2 loss: 0.56947 Learning rate: 0.002 Mask loss: 0.1402 RPN box loss: 0.0098 RPN score loss: 0.00394 RPN total loss: 0.01374 Total loss: 0.9203 timestamp: 1655054720.5368853 iteration: 59860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07177 FastRCNN class loss: 0.05502 FastRCNN total loss: 0.12679 L1 loss: 0.0000e+00 L2 loss: 0.56946 Learning rate: 0.002 Mask loss: 0.13623 RPN box loss: 0.00579 RPN score loss: 0.00202 RPN total loss: 0.00781 Total loss: 0.8403 timestamp: 1655054723.7405393 iteration: 59865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1098 FastRCNN class loss: 0.07838 FastRCNN total loss: 0.18819 L1 loss: 0.0000e+00 L2 loss: 0.56945 Learning rate: 0.002 Mask loss: 0.16339 RPN box loss: 0.01397 RPN score loss: 0.00288 RPN total loss: 0.01685 Total loss: 0.93788 timestamp: 1655054726.9669485 iteration: 59870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10413 FastRCNN class loss: 0.06491 FastRCNN total loss: 0.16903 L1 loss: 0.0000e+00 L2 loss: 0.56944 Learning rate: 0.002 Mask loss: 0.15093 RPN box loss: 0.02127 RPN score loss: 0.00476 RPN total loss: 0.02603 Total loss: 0.91542 timestamp: 1655054730.2810137 iteration: 59875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13764 FastRCNN class loss: 0.08178 FastRCNN total loss: 0.21941 L1 loss: 0.0000e+00 L2 loss: 0.56943 Learning rate: 0.002 Mask loss: 0.1512 RPN box loss: 0.00839 RPN score loss: 0.01227 RPN total loss: 0.02066 Total loss: 0.96071 timestamp: 1655054733.5686572 iteration: 59880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08799 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.14021 L1 loss: 0.0000e+00 L2 loss: 0.56942 Learning rate: 0.002 Mask loss: 0.16684 RPN box loss: 0.00484 RPN score loss: 0.00912 RPN total loss: 0.01395 Total loss: 0.89042 timestamp: 1655054736.842374 iteration: 59885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09271 FastRCNN class loss: 0.08576 FastRCNN total loss: 0.17847 L1 loss: 0.0000e+00 L2 loss: 0.56941 Learning rate: 0.002 Mask loss: 0.14472 RPN box loss: 0.01249 RPN score loss: 0.00444 RPN total loss: 0.01693 Total loss: 0.90953 timestamp: 1655054740.1158924 iteration: 59890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13344 FastRCNN class loss: 0.11811 FastRCNN total loss: 0.25155 L1 loss: 0.0000e+00 L2 loss: 0.5694 Learning rate: 0.002 Mask loss: 0.13845 RPN box loss: 0.02526 RPN score loss: 0.00787 RPN total loss: 0.03313 Total loss: 0.99253 timestamp: 1655054743.420313 iteration: 59895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12717 FastRCNN class loss: 0.04697 FastRCNN total loss: 0.17414 L1 loss: 0.0000e+00 L2 loss: 0.56939 Learning rate: 0.002 Mask loss: 0.1699 RPN box loss: 0.00565 RPN score loss: 0.00459 RPN total loss: 0.01024 Total loss: 0.92368 timestamp: 1655054746.7239327 iteration: 59900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06292 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.13424 L1 loss: 0.0000e+00 L2 loss: 0.56939 Learning rate: 0.002 Mask loss: 0.11715 RPN box loss: 0.00926 RPN score loss: 0.00383 RPN total loss: 0.01309 Total loss: 0.83386 timestamp: 1655054750.0392487 iteration: 59905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14698 FastRCNN class loss: 0.11256 FastRCNN total loss: 0.25954 L1 loss: 0.0000e+00 L2 loss: 0.56938 Learning rate: 0.002 Mask loss: 0.25225 RPN box loss: 0.01829 RPN score loss: 0.0101 RPN total loss: 0.02839 Total loss: 1.10956 timestamp: 1655054753.3267384 iteration: 59910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14381 FastRCNN class loss: 0.06976 FastRCNN total loss: 0.21356 L1 loss: 0.0000e+00 L2 loss: 0.56937 Learning rate: 0.002 Mask loss: 0.15654 RPN box loss: 0.00641 RPN score loss: 0.00378 RPN total loss: 0.01019 Total loss: 0.94966 timestamp: 1655054756.6086512 iteration: 59915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10884 FastRCNN class loss: 0.06228 FastRCNN total loss: 0.17112 L1 loss: 0.0000e+00 L2 loss: 0.56936 Learning rate: 0.002 Mask loss: 0.19122 RPN box loss: 0.04126 RPN score loss: 0.00841 RPN total loss: 0.04967 Total loss: 0.98137 timestamp: 1655054759.837455 iteration: 59920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07697 FastRCNN class loss: 0.04266 FastRCNN total loss: 0.11963 L1 loss: 0.0000e+00 L2 loss: 0.56935 Learning rate: 0.002 Mask loss: 0.10054 RPN box loss: 0.00622 RPN score loss: 0.00822 RPN total loss: 0.01443 Total loss: 0.80396 timestamp: 1655054763.037126 iteration: 59925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17564 FastRCNN class loss: 0.11261 FastRCNN total loss: 0.28825 L1 loss: 0.0000e+00 L2 loss: 0.56934 Learning rate: 0.002 Mask loss: 0.22141 RPN box loss: 0.02066 RPN score loss: 0.00548 RPN total loss: 0.02613 Total loss: 1.10514 timestamp: 1655054766.3615525 iteration: 59930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.19657 L1 loss: 0.0000e+00 L2 loss: 0.56934 Learning rate: 0.002 Mask loss: 0.16024 RPN box loss: 0.01363 RPN score loss: 0.00428 RPN total loss: 0.0179 Total loss: 0.94405 timestamp: 1655054769.57488 iteration: 59935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12639 FastRCNN class loss: 0.07141 FastRCNN total loss: 0.1978 L1 loss: 0.0000e+00 L2 loss: 0.56933 Learning rate: 0.002 Mask loss: 0.14789 RPN box loss: 0.01522 RPN score loss: 0.0022 RPN total loss: 0.01742 Total loss: 0.93244 timestamp: 1655054772.863235 iteration: 59940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10894 FastRCNN class loss: 0.09328 FastRCNN total loss: 0.20222 L1 loss: 0.0000e+00 L2 loss: 0.56932 Learning rate: 0.002 Mask loss: 0.19731 RPN box loss: 0.01107 RPN score loss: 0.00495 RPN total loss: 0.01602 Total loss: 0.98487 timestamp: 1655054776.1291635 iteration: 59945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08203 FastRCNN class loss: 0.05533 FastRCNN total loss: 0.13736 L1 loss: 0.0000e+00 L2 loss: 0.56931 Learning rate: 0.002 Mask loss: 0.12074 RPN box loss: 0.00983 RPN score loss: 0.00253 RPN total loss: 0.01235 Total loss: 0.83977 timestamp: 1655054779.443986 iteration: 59950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12205 FastRCNN class loss: 0.08092 FastRCNN total loss: 0.20297 L1 loss: 0.0000e+00 L2 loss: 0.56931 Learning rate: 0.002 Mask loss: 0.13925 RPN box loss: 0.01715 RPN score loss: 0.00491 RPN total loss: 0.02206 Total loss: 0.93358 timestamp: 1655054782.6888273 iteration: 59955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0849 FastRCNN class loss: 0.04049 FastRCNN total loss: 0.12539 L1 loss: 0.0000e+00 L2 loss: 0.5693 Learning rate: 0.002 Mask loss: 0.15643 RPN box loss: 0.008 RPN score loss: 0.0063 RPN total loss: 0.0143 Total loss: 0.86542 timestamp: 1655054786.0041893 iteration: 59960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10562 FastRCNN class loss: 0.04144 FastRCNN total loss: 0.14705 L1 loss: 0.0000e+00 L2 loss: 0.56929 Learning rate: 0.002 Mask loss: 0.12838 RPN box loss: 0.03317 RPN score loss: 0.00282 RPN total loss: 0.03599 Total loss: 0.88071 timestamp: 1655054789.2348228 iteration: 59965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07777 FastRCNN class loss: 0.05273 FastRCNN total loss: 0.1305 L1 loss: 0.0000e+00 L2 loss: 0.56929 Learning rate: 0.002 Mask loss: 0.10543 RPN box loss: 0.01041 RPN score loss: 0.00266 RPN total loss: 0.01307 Total loss: 0.81828 timestamp: 1655054792.5147777 iteration: 59970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10532 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.17786 L1 loss: 0.0000e+00 L2 loss: 0.56928 Learning rate: 0.002 Mask loss: 0.18012 RPN box loss: 0.03849 RPN score loss: 0.00629 RPN total loss: 0.04477 Total loss: 0.97203 timestamp: 1655054795.8344924 iteration: 59975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0674 FastRCNN class loss: 0.04316 FastRCNN total loss: 0.11056 L1 loss: 0.0000e+00 L2 loss: 0.56927 Learning rate: 0.002 Mask loss: 0.10483 RPN box loss: 0.00667 RPN score loss: 0.00224 RPN total loss: 0.0089 Total loss: 0.79356 timestamp: 1655054799.0840926 iteration: 59980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12864 FastRCNN class loss: 0.08144 FastRCNN total loss: 0.21008 L1 loss: 0.0000e+00 L2 loss: 0.56926 Learning rate: 0.002 Mask loss: 0.12068 RPN box loss: 0.01324 RPN score loss: 0.00309 RPN total loss: 0.01633 Total loss: 0.91636 timestamp: 1655054802.3952081 iteration: 59985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.17622 L1 loss: 0.0000e+00 L2 loss: 0.56925 Learning rate: 0.002 Mask loss: 0.20179 RPN box loss: 0.01599 RPN score loss: 0.00673 RPN total loss: 0.02272 Total loss: 0.96998 timestamp: 1655054805.6230912 iteration: 59990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11169 FastRCNN class loss: 0.06911 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 0.56924 Learning rate: 0.002 Mask loss: 0.10341 RPN box loss: 0.00524 RPN score loss: 0.00127 RPN total loss: 0.00651 Total loss: 0.85995 timestamp: 1655054808.9029114 iteration: 59995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11276 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.19982 L1 loss: 0.0000e+00 L2 loss: 0.56923 Learning rate: 0.002 Mask loss: 0.2072 RPN box loss: 0.01244 RPN score loss: 0.00855 RPN total loss: 0.02098 Total loss: 0.99723 timestamp: 1655054812.1569684 iteration: 60000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09555 FastRCNN class loss: 0.09191 FastRCNN total loss: 0.18746 L1 loss: 0.0000e+00 L2 loss: 0.56922 Learning rate: 0.002 Mask loss: 0.17966 RPN box loss: 0.01024 RPN score loss: 0.00218 RPN total loss: 0.01242 Total loss: 0.94876 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 6.4747s - Throughput: 0.6 imgs/s Running inference on batch 002/125... - Step Time: 0.9513s - Throughput: 4.2 imgs/s Running inference on batch 003/125... - Step Time: 0.9024s - Throughput: 4.4 imgs/s Running inference on batch 004/125... - Step Time: 0.9739s - Throughput: 4.1 imgs/s Running inference on batch 005/125... - Step Time: 0.9608s - Throughput: 4.2 imgs/s Running inference on batch 006/125... - Step Time: 0.9185s - Throughput: 4.4 imgs/s Running inference on batch 007/125... - Step Time: 0.6991s - Throughput: 5.7 imgs/s Running inference on batch 008/125... - Step Time: 0.7278s - Throughput: 5.5 imgs/s Running inference on batch 009/125... - Step Time: 1.0282s - Throughput: 3.9 imgs/s Running inference on batch 010/125... - Step Time: 0.9070s - Throughput: 4.4 imgs/s Running inference on batch 011/125... - Step Time: 0.9781s - Throughput: 4.1 imgs/s Running inference on batch 012/125... - Step Time: 0.9366s - Throughput: 4.3 imgs/s Running inference on batch 013/125... - Step Time: 0.8913s - Throughput: 4.5 imgs/s Running inference on batch 014/125... - Step Time: 0.9194s - Throughput: 4.4 imgs/s Running inference on batch 015/125... - Step Time: 0.9551s - Throughput: 4.2 imgs/s Running inference on batch 016/125... - Step Time: 0.9041s - Throughput: 4.4 imgs/s Running inference on batch 017/125... - Step Time: 0.8577s - Throughput: 4.7 imgs/s Running inference on batch 018/125... - Step Time: 0.8900s - Throughput: 4.5 imgs/s Running inference on batch 019/125... - Step Time: 0.9816s - Throughput: 4.1 imgs/s Running inference on batch 020/125... - Step Time: 0.8988s - Throughput: 4.5 imgs/s Running inference on batch 021/125... - Step Time: 0.9438s - Throughput: 4.2 imgs/s Running inference on batch 022/125... - Step Time: 1.0205s - Throughput: 3.9 imgs/s Running inference on batch 023/125... - Step Time: 0.9412s - Throughput: 4.2 imgs/s Running inference on batch 024/125... - Step Time: 0.9159s - Throughput: 4.4 imgs/s Running inference on batch 025/125... - Step Time: 0.9209s - Throughput: 4.3 imgs/s Running inference on batch 026/125... - Step Time: 0.9206s - Throughput: 4.3 imgs/s Running inference on batch 027/125... - Step Time: 0.8426s - Throughput: 4.7 imgs/s Running inference on batch 028/125... - Step Time: 0.8978s - Throughput: 4.5 imgs/s Running inference on batch 029/125... - Step Time: 0.9352s - Throughput: 4.3 imgs/s Running inference on batch 030/125... - Step Time: 0.9540s - Throughput: 4.2 imgs/s Running inference on batch 031/125... - Step Time: 0.9094s - Throughput: 4.4 imgs/s Running inference on batch 032/125... - Step Time: 0.9543s - Throughput: 4.2 imgs/s Running inference on batch 033/125... - Step Time: 0.9684s - Throughput: 4.1 imgs/s Running inference on batch 034/125... - Step Time: 0.9779s - Throughput: 4.1 imgs/s Running inference on batch 035/125... - Step Time: 0.8467s - Throughput: 4.7 imgs/s Running inference on batch 036/125... - Step Time: 0.9454s - Throughput: 4.2 imgs/s Running inference on batch 037/125... - Step Time: 0.9859s - Throughput: 4.1 imgs/s Running inference on batch 038/125... - Step Time: 0.9629s - Throughput: 4.2 imgs/s Running inference on batch 039/125... - Step Time: 0.9137s - Throughput: 4.4 imgs/s Running inference on batch 040/125... - Step Time: 0.9509s - Throughput: 4.2 imgs/s Running inference on batch 041/125... - Step Time: 0.9955s - Throughput: 4.0 imgs/s Running inference on batch 042/125... - Step Time: 0.9577s - Throughput: 4.2 imgs/s Running inference on batch 043/125... - Step Time: 0.9490s - Throughput: 4.2 imgs/s Running inference on batch 044/125... - Step Time: 0.9305s - Throughput: 4.3 imgs/s Running inference on batch 045/125... - Step Time: 0.9126s - Throughput: 4.4 imgs/s Running inference on batch 046/125... - Step Time: 0.9228s - Throughput: 4.3 imgs/s Running inference on batch 047/125... - Step Time: 0.9219s - Throughput: 4.3 imgs/s Running inference on batch 048/125... - Step Time: 1.0247s - Throughput: 3.9 imgs/s Running inference on batch 049/125... - Step Time: 0.9336s - Throughput: 4.3 imgs/s Running inference on batch 050/125... - Step Time: 0.9716s - Throughput: 4.1 imgs/s Running inference on batch 051/125... - Step Time: 0.9309s - Throughput: 4.3 imgs/s Running inference on batch 052/125... - Step Time: 0.8663s - Throughput: 4.6 imgs/s Running inference on batch 053/125... - Step Time: 0.9674s - Throughput: 4.1 imgs/s Running inference on batch 054/125... - Step Time: 0.9093s - Throughput: 4.4 imgs/s Running inference on batch 055/125... - Step Time: 0.9591s - Throughput: 4.2 imgs/s Running inference on batch 056/125... - Step Time: 0.9477s - Throughput: 4.2 imgs/s Running inference on batch 057/125... - Step Time: 0.9320s - Throughput: 4.3 imgs/s Running inference on batch 058/125... - Step Time: 0.9608s - Throughput: 4.2 imgs/s Running inference on batch 059/125... - Step Time: 0.9522s - Throughput: 4.2 imgs/s Running inference on batch 060/125... - 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Step Time: 0.9977s - Throughput: 4.0 imgs/s Running inference on batch 097/125... - Step Time: 1.0014s - Throughput: 4.0 imgs/s Running inference on batch 098/125... - Step Time: 0.9561s - Throughput: 4.2 imgs/s Running inference on batch 099/125... - Step Time: 0.9214s - Throughput: 4.3 imgs/s Running inference on batch 100/125... - Step Time: 0.8803s - Throughput: 4.5 imgs/s Running inference on batch 101/125... - Step Time: 0.9865s - Throughput: 4.1 imgs/s Running inference on batch 102/125... - Step Time: 0.9211s - Throughput: 4.3 imgs/s Running inference on batch 103/125... - Step Time: 0.9883s - Throughput: 4.0 imgs/s Running inference on batch 104/125... - Step Time: 0.9503s - Throughput: 4.2 imgs/s Running inference on batch 105/125... - Step Time: 0.9123s - Throughput: 4.4 imgs/s Running inference on batch 106/125... - Step Time: 0.9947s - Throughput: 4.0 imgs/s Running inference on batch 107/125... - Step Time: 0.9392s - Throughput: 4.3 imgs/s Running inference on batch 108/125... - Step Time: 0.9824s - Throughput: 4.1 imgs/s Running inference on batch 109/125... - Step Time: 0.9682s - Throughput: 4.1 imgs/s Running inference on batch 110/125... - Step Time: 0.9722s - Throughput: 4.1 imgs/s Running inference on batch 111/125... - Step Time: 0.9267s - Throughput: 4.3 imgs/s Running inference on batch 112/125... - Step Time: 0.9646s - Throughput: 4.1 imgs/s Running inference on batch 113/125... - Step Time: 0.9433s - Throughput: 4.2 imgs/s Running inference on batch 114/125... - Step Time: 0.9218s - Throughput: 4.3 imgs/s Running inference on batch 115/125... - Step Time: 0.9283s - Throughput: 4.3 imgs/s Running inference on batch 116/125... - Step Time: 0.9002s - Throughput: 4.4 imgs/s Running inference on batch 117/125... - Step Time: 0.9631s - Throughput: 4.2 imgs/s Running inference on batch 118/125... - Step Time: 1.0128s - Throughput: 3.9 imgs/s Running inference on batch 119/125... - Step Time: 0.9901s - Throughput: 4.0 imgs/s Running inference on batch 120/125... - Step Time: 0.9712s - Throughput: 4.1 imgs/s Running inference on batch 121/125... - Step Time: 0.9156s - Throughput: 4.4 imgs/s Running inference on batch 122/125... - Step Time: 0.9154s - Throughput: 4.4 imgs/s Running inference on batch 123/125... - Step Time: 0.9108s - Throughput: 4.4 imgs/s Running inference on batch 124/125... - Step Time: 1.0146s - Throughput: 3.9 imgs/s Running inference on batch 125/125... - Step Time: 0.9318s - Throughput: 4.3 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: 4.2 samples/sec Total processed steps: 125 Total processing time: 0.0h 08m 50s ==================== Metrics ==================== AP: 0.189675316 AP50: 0.292981356 AP75: 0.189532906 APl: 0.223368853 APm: 0.039626870 APs: 0.005799307 ARl: 0.446210176 ARm: 0.088296436 ARmax1: 0.283642262 ARmax10: 0.381570160 ARmax100: 0.384100318 ARs: 0.014371981 mask_AP: 0.142496720 mask_AP50: 0.243690401 mask_AP75: 0.142769367 mask_APl: 0.171349406 mask_APm: 0.015089178 mask_APs: 0.000000000 mask_ARl: 0.293224573 mask_ARm: 0.045672614 mask_ARmax1: 0.204494566 mask_ARmax10: 0.242992818 mask_ARmax100: 0.245929554 mask_ARs: 0.000000000 ================================= 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] 549.0 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: 1655056188.0693488 iteration: 60005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09414 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.14272 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.0966 RPN box loss: 0.02042 RPN score loss: 0.00199 RPN total loss: 0.02241 Total loss: 0.83095 timestamp: 1655056191.3066297 iteration: 60010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0811 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.14607 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.13533 RPN box loss: 0.01668 RPN score loss: 0.00455 RPN total loss: 0.02123 Total loss: 0.87184 timestamp: 1655056194.5091934 iteration: 60015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08745 FastRCNN class loss: 0.05159 FastRCNN total loss: 0.13904 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.16648 RPN box loss: 0.00796 RPN score loss: 0.00242 RPN total loss: 0.01038 Total loss: 0.88511 timestamp: 1655056197.7431562 iteration: 60020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.05828 FastRCNN total loss: 0.19604 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.14802 RPN box loss: 0.01322 RPN score loss: 0.00271 RPN total loss: 0.01592 Total loss: 0.9292 timestamp: 1655056201.0336568 iteration: 60025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11541 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.17772 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.14753 RPN box loss: 0.02454 RPN score loss: 0.002 RPN total loss: 0.02654 Total loss: 0.921 timestamp: 1655056204.3092804 iteration: 60030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08499 FastRCNN class loss: 0.06879 FastRCNN total loss: 0.15378 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.09496 RPN box loss: 0.01054 RPN score loss: 0.00519 RPN total loss: 0.01573 Total loss: 0.83368 timestamp: 1655056207.5822701 iteration: 60035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08058 FastRCNN class loss: 0.07437 FastRCNN total loss: 0.15495 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.19045 RPN box loss: 0.01031 RPN score loss: 0.00379 RPN total loss: 0.01411 Total loss: 0.92871 timestamp: 1655056210.845016 iteration: 60040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.1585 L1 loss: 0.0000e+00 L2 loss: 0.56921 Learning rate: 0.0004 Mask loss: 0.16763 RPN box loss: 0.00369 RPN score loss: 0.00213 RPN total loss: 0.00582 Total loss: 0.90115 timestamp: 1655056214.1220467 iteration: 60045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14578 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.21573 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.10304 RPN box loss: 0.0175 RPN score loss: 0.00293 RPN total loss: 0.02043 Total loss: 0.90841 timestamp: 1655056217.3478272 iteration: 60050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10508 FastRCNN class loss: 0.06581 FastRCNN total loss: 0.17089 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.13245 RPN box loss: 0.01276 RPN score loss: 0.00122 RPN total loss: 0.01398 Total loss: 0.88653 timestamp: 1655056220.5935671 iteration: 60055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08033 FastRCNN class loss: 0.06597 FastRCNN total loss: 0.1463 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.11711 RPN box loss: 0.01473 RPN score loss: 0.00528 RPN total loss: 0.02001 Total loss: 0.85262 timestamp: 1655056223.821689 iteration: 60060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11965 FastRCNN class loss: 0.12278 FastRCNN total loss: 0.24243 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.21035 RPN box loss: 0.01691 RPN score loss: 0.00965 RPN total loss: 0.02656 Total loss: 1.04854 timestamp: 1655056227.1012633 iteration: 60065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07063 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.12564 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.14463 RPN box loss: 0.02828 RPN score loss: 0.00151 RPN total loss: 0.02978 Total loss: 0.86926 timestamp: 1655056230.4184985 iteration: 60070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10685 FastRCNN class loss: 0.08177 FastRCNN total loss: 0.18862 L1 loss: 0.0000e+00 L2 loss: 0.5692 Learning rate: 0.0004 Mask loss: 0.11846 RPN box loss: 0.01466 RPN score loss: 0.0041 RPN total loss: 0.01876 Total loss: 0.89503 timestamp: 1655056233.6761343 iteration: 60075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10286 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.17508 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.14059 RPN box loss: 0.01436 RPN score loss: 0.00701 RPN total loss: 0.02137 Total loss: 0.90623 timestamp: 1655056236.974949 iteration: 60080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05983 FastRCNN class loss: 0.03277 FastRCNN total loss: 0.0926 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.12129 RPN box loss: 0.00471 RPN score loss: 0.00362 RPN total loss: 0.00832 Total loss: 0.7914 timestamp: 1655056240.278263 iteration: 60085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.06991 FastRCNN total loss: 0.16478 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.19145 RPN box loss: 0.02046 RPN score loss: 0.00444 RPN total loss: 0.0249 Total loss: 0.95032 timestamp: 1655056243.5173175 iteration: 60090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10177 FastRCNN class loss: 0.08069 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.12959 RPN box loss: 0.01172 RPN score loss: 0.00884 RPN total loss: 0.02056 Total loss: 0.90181 timestamp: 1655056246.8677688 iteration: 60095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06055 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.11013 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.08614 RPN box loss: 0.00904 RPN score loss: 0.00587 RPN total loss: 0.01491 Total loss: 0.78036 timestamp: 1655056250.1983616 iteration: 60100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08661 FastRCNN class loss: 0.04162 FastRCNN total loss: 0.12822 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.09658 RPN box loss: 0.0162 RPN score loss: 0.01061 RPN total loss: 0.02681 Total loss: 0.82079 timestamp: 1655056253.427298 iteration: 60105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10475 FastRCNN class loss: 0.08586 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.56919 Learning rate: 0.0004 Mask loss: 0.1207 RPN box loss: 0.03056 RPN score loss: 0.00346 RPN total loss: 0.03403 Total loss: 0.91453 timestamp: 1655056256.6921628 iteration: 60110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09917 FastRCNN class loss: 0.06246 FastRCNN total loss: 0.16163 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.11391 RPN box loss: 0.01042 RPN score loss: 0.00537 RPN total loss: 0.01579 Total loss: 0.86051 timestamp: 1655056259.976485 iteration: 60115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1002 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.16379 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.17387 RPN box loss: 0.01288 RPN score loss: 0.00477 RPN total loss: 0.01764 Total loss: 0.92448 timestamp: 1655056263.3305745 iteration: 60120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03513 FastRCNN class loss: 0.03206 FastRCNN total loss: 0.0672 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.09412 RPN box loss: 0.00319 RPN score loss: 0.00156 RPN total loss: 0.00475 Total loss: 0.73525 timestamp: 1655056266.5725691 iteration: 60125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0604 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.12447 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.12326 RPN box loss: 0.00758 RPN score loss: 0.00501 RPN total loss: 0.01259 Total loss: 0.8295 timestamp: 1655056269.8095808 iteration: 60130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10157 FastRCNN class loss: 0.07317 FastRCNN total loss: 0.17475 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.1679 RPN box loss: 0.03631 RPN score loss: 0.0093 RPN total loss: 0.04561 Total loss: 0.95743 timestamp: 1655056273.113245 iteration: 60135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10035 FastRCNN class loss: 0.06447 FastRCNN total loss: 0.16482 L1 loss: 0.0000e+00 L2 loss: 0.56918 Learning rate: 0.0004 Mask loss: 0.16184 RPN box loss: 0.00826 RPN score loss: 0.00498 RPN total loss: 0.01323 Total loss: 0.90907 timestamp: 1655056276.3703084 iteration: 60140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13039 FastRCNN class loss: 0.0943 FastRCNN total loss: 0.22468 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.13055 RPN box loss: 0.01637 RPN score loss: 0.00351 RPN total loss: 0.01988 Total loss: 0.9443 timestamp: 1655056279.5491223 iteration: 60145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08075 FastRCNN class loss: 0.05914 FastRCNN total loss: 0.13989 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.10451 RPN box loss: 0.0049 RPN score loss: 0.00439 RPN total loss: 0.00929 Total loss: 0.82287 timestamp: 1655056282.8251996 iteration: 60150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11226 FastRCNN class loss: 0.0949 FastRCNN total loss: 0.20716 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.11922 RPN box loss: 0.02933 RPN score loss: 0.00279 RPN total loss: 0.03212 Total loss: 0.92767 timestamp: 1655056286.155035 iteration: 60155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08905 FastRCNN class loss: 0.04618 FastRCNN total loss: 0.13523 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.08759 RPN box loss: 0.00697 RPN score loss: 0.00267 RPN total loss: 0.00964 Total loss: 0.80163 timestamp: 1655056289.4548194 iteration: 60160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07895 FastRCNN class loss: 0.06994 FastRCNN total loss: 0.14889 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.14721 RPN box loss: 0.00596 RPN score loss: 0.00617 RPN total loss: 0.01213 Total loss: 0.87739 timestamp: 1655056292.7593153 iteration: 60165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07536 FastRCNN class loss: 0.04848 FastRCNN total loss: 0.12384 L1 loss: 0.0000e+00 L2 loss: 0.56917 Learning rate: 0.0004 Mask loss: 0.12291 RPN box loss: 0.01383 RPN score loss: 0.00438 RPN total loss: 0.01821 Total loss: 0.83413 timestamp: 1655056296.0248206 iteration: 60170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07528 FastRCNN class loss: 0.0788 FastRCNN total loss: 0.15407 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.22485 RPN box loss: 0.03761 RPN score loss: 0.00912 RPN total loss: 0.04674 Total loss: 0.99482 timestamp: 1655056299.2680721 iteration: 60175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11202 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.18525 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.13028 RPN box loss: 0.00806 RPN score loss: 0.00387 RPN total loss: 0.01192 Total loss: 0.89661 timestamp: 1655056302.6374624 iteration: 60180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11849 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.19377 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.14565 RPN box loss: 0.01506 RPN score loss: 0.00355 RPN total loss: 0.01861 Total loss: 0.92719 timestamp: 1655056305.8502157 iteration: 60185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09253 FastRCNN class loss: 0.14877 FastRCNN total loss: 0.24129 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.17708 RPN box loss: 0.0177 RPN score loss: 0.0152 RPN total loss: 0.0329 Total loss: 1.02043 timestamp: 1655056309.143828 iteration: 60190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08364 FastRCNN class loss: 0.08432 FastRCNN total loss: 0.16796 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.15084 RPN box loss: 0.01174 RPN score loss: 0.00831 RPN total loss: 0.02005 Total loss: 0.90801 timestamp: 1655056312.4396806 iteration: 60195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11791 FastRCNN class loss: 0.10675 FastRCNN total loss: 0.22466 L1 loss: 0.0000e+00 L2 loss: 0.56916 Learning rate: 0.0004 Mask loss: 0.19415 RPN box loss: 0.03107 RPN score loss: 0.00718 RPN total loss: 0.03825 Total loss: 1.02622 timestamp: 1655056315.7677104 iteration: 60200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12941 FastRCNN class loss: 0.09222 FastRCNN total loss: 0.22162 L1 loss: 0.0000e+00 L2 loss: 0.56915 Learning rate: 0.0004 Mask loss: 0.11456 RPN box loss: 0.02791 RPN score loss: 0.00586 RPN total loss: 0.03377 Total loss: 0.93911 timestamp: 1655056319.053493 iteration: 60205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06864 FastRCNN class loss: 0.09592 FastRCNN total loss: 0.16455 L1 loss: 0.0000e+00 L2 loss: 0.56915 Learning rate: 0.0004 Mask loss: 0.13372 RPN box loss: 0.01355 RPN score loss: 0.00262 RPN total loss: 0.01617 Total loss: 0.88359 timestamp: 1655056322.4102085 iteration: 60210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09075 FastRCNN class loss: 0.07014 FastRCNN total loss: 0.16089 L1 loss: 0.0000e+00 L2 loss: 0.56915 Learning rate: 0.0004 Mask loss: 0.20909 RPN box loss: 0.01241 RPN score loss: 0.01201 RPN total loss: 0.02442 Total loss: 0.96355 timestamp: 1655056325.7038724 iteration: 60215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10392 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.17155 L1 loss: 0.0000e+00 L2 loss: 0.56915 Learning rate: 0.0004 Mask loss: 0.19943 RPN box loss: 0.00956 RPN score loss: 0.00404 RPN total loss: 0.01361 Total loss: 0.95373 timestamp: 1655056328.9683022 iteration: 60220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06149 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.10864 L1 loss: 0.0000e+00 L2 loss: 0.56915 Learning rate: 0.0004 Mask loss: 0.08806 RPN box loss: 0.01669 RPN score loss: 0.00219 RPN total loss: 0.01889 Total loss: 0.78474 timestamp: 1655056332.2047508 iteration: 60225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06434 FastRCNN class loss: 0.05265 FastRCNN total loss: 0.11699 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.12874 RPN box loss: 0.01205 RPN score loss: 0.00689 RPN total loss: 0.01894 Total loss: 0.83382 timestamp: 1655056335.4566095 iteration: 60230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0793 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.16868 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.2324 RPN box loss: 0.00681 RPN score loss: 0.00382 RPN total loss: 0.01064 Total loss: 0.98087 timestamp: 1655056338.651965 iteration: 60235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06812 FastRCNN class loss: 0.07107 FastRCNN total loss: 0.13919 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.09484 RPN box loss: 0.00806 RPN score loss: 0.00284 RPN total loss: 0.0109 Total loss: 0.81408 timestamp: 1655056341.957184 iteration: 60240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13313 FastRCNN class loss: 0.05597 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.11467 RPN box loss: 0.0188 RPN score loss: 0.0023 RPN total loss: 0.0211 Total loss: 0.89401 timestamp: 1655056345.2730348 iteration: 60245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10007 FastRCNN class loss: 0.07741 FastRCNN total loss: 0.17748 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.14141 RPN box loss: 0.00729 RPN score loss: 0.00421 RPN total loss: 0.0115 Total loss: 0.89953 timestamp: 1655056348.577906 iteration: 60250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06344 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.10615 L1 loss: 0.0000e+00 L2 loss: 0.56914 Learning rate: 0.0004 Mask loss: 0.10651 RPN box loss: 0.0222 RPN score loss: 0.00311 RPN total loss: 0.02532 Total loss: 0.80712 timestamp: 1655056351.8945165 iteration: 60255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.05646 FastRCNN total loss: 0.16177 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.08665 RPN box loss: 0.0099 RPN score loss: 0.00359 RPN total loss: 0.01349 Total loss: 0.83105 timestamp: 1655056355.115023 iteration: 60260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05312 FastRCNN class loss: 0.06121 FastRCNN total loss: 0.11432 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.12425 RPN box loss: 0.00888 RPN score loss: 0.00127 RPN total loss: 0.01014 Total loss: 0.81785 timestamp: 1655056358.4213352 iteration: 60265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09805 FastRCNN class loss: 0.0831 FastRCNN total loss: 0.18115 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.14207 RPN box loss: 0.0159 RPN score loss: 0.00603 RPN total loss: 0.02193 Total loss: 0.91427 timestamp: 1655056361.6775467 iteration: 60270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.17986 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.16859 RPN box loss: 0.0093 RPN score loss: 0.00605 RPN total loss: 0.01535 Total loss: 0.93293 timestamp: 1655056364.9775207 iteration: 60275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1013 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.16625 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.15607 RPN box loss: 0.02268 RPN score loss: 0.00232 RPN total loss: 0.025 Total loss: 0.91645 timestamp: 1655056368.2058196 iteration: 60280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12076 FastRCNN class loss: 0.06243 FastRCNN total loss: 0.18319 L1 loss: 0.0000e+00 L2 loss: 0.56913 Learning rate: 0.0004 Mask loss: 0.14501 RPN box loss: 0.0052 RPN score loss: 0.00133 RPN total loss: 0.00652 Total loss: 0.90384 timestamp: 1655056371.5520554 iteration: 60285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09394 FastRCNN class loss: 0.05382 FastRCNN total loss: 0.14776 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.08712 RPN box loss: 0.01503 RPN score loss: 0.00455 RPN total loss: 0.01957 Total loss: 0.82358 timestamp: 1655056374.8206089 iteration: 60290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07349 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.1396 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.11301 RPN box loss: 0.00664 RPN score loss: 0.00419 RPN total loss: 0.01084 Total loss: 0.83257 timestamp: 1655056378.082824 iteration: 60295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07526 FastRCNN class loss: 0.0451 FastRCNN total loss: 0.12035 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.13683 RPN box loss: 0.03279 RPN score loss: 0.00526 RPN total loss: 0.03805 Total loss: 0.86435 timestamp: 1655056381.3332798 iteration: 60300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15465 FastRCNN class loss: 0.11913 FastRCNN total loss: 0.27379 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.17277 RPN box loss: 0.02796 RPN score loss: 0.00647 RPN total loss: 0.03442 Total loss: 1.05009 timestamp: 1655056384.6000829 iteration: 60305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10338 FastRCNN class loss: 0.07392 FastRCNN total loss: 0.1773 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.13155 RPN box loss: 0.00657 RPN score loss: 0.00593 RPN total loss: 0.01249 Total loss: 0.89046 timestamp: 1655056387.8756144 iteration: 60310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09419 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.1673 L1 loss: 0.0000e+00 L2 loss: 0.56912 Learning rate: 0.0004 Mask loss: 0.14242 RPN box loss: 0.00785 RPN score loss: 0.00299 RPN total loss: 0.01084 Total loss: 0.88968 timestamp: 1655056391.1283472 iteration: 60315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11232 FastRCNN class loss: 0.05518 FastRCNN total loss: 0.1675 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.15721 RPN box loss: 0.02053 RPN score loss: 0.00411 RPN total loss: 0.02464 Total loss: 0.91846 timestamp: 1655056394.3756206 iteration: 60320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13357 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.20053 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.18898 RPN box loss: 0.00817 RPN score loss: 0.00196 RPN total loss: 0.01013 Total loss: 0.96876 timestamp: 1655056397.6874 iteration: 60325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.1319 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.14585 RPN box loss: 0.00914 RPN score loss: 0.00333 RPN total loss: 0.01247 Total loss: 0.85932 timestamp: 1655056400.9890013 iteration: 60330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.05757 FastRCNN total loss: 0.14138 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.14412 RPN box loss: 0.00941 RPN score loss: 0.00184 RPN total loss: 0.01126 Total loss: 0.86587 timestamp: 1655056404.2309706 iteration: 60335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10072 FastRCNN class loss: 0.08393 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.14266 RPN box loss: 0.03044 RPN score loss: 0.01446 RPN total loss: 0.0449 Total loss: 0.94131 timestamp: 1655056407.5350645 iteration: 60340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05789 FastRCNN class loss: 0.05849 FastRCNN total loss: 0.11638 L1 loss: 0.0000e+00 L2 loss: 0.56911 Learning rate: 0.0004 Mask loss: 0.16998 RPN box loss: 0.01209 RPN score loss: 0.00183 RPN total loss: 0.01393 Total loss: 0.86939 timestamp: 1655056410.748931 iteration: 60345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0464 FastRCNN class loss: 0.04972 FastRCNN total loss: 0.09612 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.13174 RPN box loss: 0.00961 RPN score loss: 0.00639 RPN total loss: 0.016 Total loss: 0.81295 timestamp: 1655056414.0452073 iteration: 60350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12132 FastRCNN class loss: 0.09421 FastRCNN total loss: 0.21553 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.22637 RPN box loss: 0.0171 RPN score loss: 0.00963 RPN total loss: 0.02673 Total loss: 1.03772 timestamp: 1655056417.443455 iteration: 60355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07928 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.12768 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.08485 RPN box loss: 0.00895 RPN score loss: 0.00445 RPN total loss: 0.0134 Total loss: 0.79503 timestamp: 1655056420.6806326 iteration: 60360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08691 FastRCNN class loss: 0.09848 FastRCNN total loss: 0.18539 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.16004 RPN box loss: 0.01669 RPN score loss: 0.00744 RPN total loss: 0.02413 Total loss: 0.93866 timestamp: 1655056424.0021374 iteration: 60365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13624 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.19481 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.1191 RPN box loss: 0.01516 RPN score loss: 0.0048 RPN total loss: 0.01995 Total loss: 0.90296 timestamp: 1655056427.2460697 iteration: 60370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0699 FastRCNN class loss: 0.06419 FastRCNN total loss: 0.13408 L1 loss: 0.0000e+00 L2 loss: 0.5691 Learning rate: 0.0004 Mask loss: 0.10206 RPN box loss: 0.01656 RPN score loss: 0.00178 RPN total loss: 0.01834 Total loss: 0.82358 timestamp: 1655056430.5322464 iteration: 60375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07817 FastRCNN class loss: 0.05485 FastRCNN total loss: 0.13302 L1 loss: 0.0000e+00 L2 loss: 0.56909 Learning rate: 0.0004 Mask loss: 0.18878 RPN box loss: 0.02827 RPN score loss: 0.0032 RPN total loss: 0.03147 Total loss: 0.92236 timestamp: 1655056433.8202562 iteration: 60380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10907 FastRCNN class loss: 0.10159 FastRCNN total loss: 0.21066 L1 loss: 0.0000e+00 L2 loss: 0.56909 Learning rate: 0.0004 Mask loss: 0.18232 RPN box loss: 0.032 RPN score loss: 0.00457 RPN total loss: 0.03657 Total loss: 0.99864 timestamp: 1655056437.0852792 iteration: 60385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17787 FastRCNN class loss: 0.15257 FastRCNN total loss: 0.33044 L1 loss: 0.0000e+00 L2 loss: 0.56909 Learning rate: 0.0004 Mask loss: 0.17566 RPN box loss: 0.0294 RPN score loss: 0.03844 RPN total loss: 0.06784 Total loss: 1.14304 timestamp: 1655056440.365597 iteration: 60390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08013 FastRCNN class loss: 0.05541 FastRCNN total loss: 0.13553 L1 loss: 0.0000e+00 L2 loss: 0.56909 Learning rate: 0.0004 Mask loss: 0.25308 RPN box loss: 0.01785 RPN score loss: 0.00253 RPN total loss: 0.02038 Total loss: 0.97808 timestamp: 1655056443.6091626 iteration: 60395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07226 FastRCNN class loss: 0.09845 FastRCNN total loss: 0.17071 L1 loss: 0.0000e+00 L2 loss: 0.56909 Learning rate: 0.0004 Mask loss: 0.13382 RPN box loss: 0.01013 RPN score loss: 0.00519 RPN total loss: 0.01533 Total loss: 0.88894 timestamp: 1655056446.9021583 iteration: 60400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07539 FastRCNN class loss: 0.05053 FastRCNN total loss: 0.12592 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.11856 RPN box loss: 0.00217 RPN score loss: 0.0011 RPN total loss: 0.00327 Total loss: 0.81683 timestamp: 1655056450.1883307 iteration: 60405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06727 FastRCNN class loss: 0.06976 FastRCNN total loss: 0.13704 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.12833 RPN box loss: 0.00612 RPN score loss: 0.00263 RPN total loss: 0.00875 Total loss: 0.84319 timestamp: 1655056453.4203377 iteration: 60410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.0959 FastRCNN total loss: 0.22362 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.14183 RPN box loss: 0.01835 RPN score loss: 0.00912 RPN total loss: 0.02747 Total loss: 0.96201 timestamp: 1655056456.6587052 iteration: 60415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.06287 FastRCNN total loss: 0.13871 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.1054 RPN box loss: 0.01024 RPN score loss: 0.00501 RPN total loss: 0.01524 Total loss: 0.82844 timestamp: 1655056459.9251335 iteration: 60420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1007 FastRCNN class loss: 0.04787 FastRCNN total loss: 0.14856 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.13774 RPN box loss: 0.03009 RPN score loss: 0.00423 RPN total loss: 0.03432 Total loss: 0.88971 timestamp: 1655056463.184043 iteration: 60425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0624 FastRCNN class loss: 0.05777 FastRCNN total loss: 0.12018 L1 loss: 0.0000e+00 L2 loss: 0.56908 Learning rate: 0.0004 Mask loss: 0.1588 RPN box loss: 0.01173 RPN score loss: 0.01156 RPN total loss: 0.02329 Total loss: 0.87135 timestamp: 1655056466.4098337 iteration: 60430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14672 FastRCNN class loss: 0.08852 FastRCNN total loss: 0.23524 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.16566 RPN box loss: 0.00658 RPN score loss: 0.00557 RPN total loss: 0.01215 Total loss: 0.98212 timestamp: 1655056469.6373386 iteration: 60435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09051 FastRCNN class loss: 0.07051 FastRCNN total loss: 0.16101 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.19188 RPN box loss: 0.01965 RPN score loss: 0.00499 RPN total loss: 0.02464 Total loss: 0.9466 timestamp: 1655056473.0000749 iteration: 60440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10314 FastRCNN class loss: 0.059 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.17106 RPN box loss: 0.00596 RPN score loss: 0.00186 RPN total loss: 0.00781 Total loss: 0.91008 timestamp: 1655056476.2615902 iteration: 60445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08433 FastRCNN class loss: 0.04705 FastRCNN total loss: 0.13137 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.15163 RPN box loss: 0.00825 RPN score loss: 0.0064 RPN total loss: 0.01465 Total loss: 0.86673 timestamp: 1655056479.6034815 iteration: 60450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08169 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.13392 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.15408 RPN box loss: 0.01245 RPN score loss: 0.00448 RPN total loss: 0.01693 Total loss: 0.874 timestamp: 1655056482.8044047 iteration: 60455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13679 FastRCNN class loss: 0.17415 FastRCNN total loss: 0.31094 L1 loss: 0.0000e+00 L2 loss: 0.56907 Learning rate: 0.0004 Mask loss: 0.17299 RPN box loss: 0.02812 RPN score loss: 0.01351 RPN total loss: 0.04163 Total loss: 1.09463 timestamp: 1655056486.0741167 iteration: 60460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0806 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.14663 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.15626 RPN box loss: 0.01228 RPN score loss: 0.00479 RPN total loss: 0.01706 Total loss: 0.88902 timestamp: 1655056489.385265 iteration: 60465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.03496 FastRCNN total loss: 0.12398 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.11196 RPN box loss: 0.00234 RPN score loss: 0.00135 RPN total loss: 0.00368 Total loss: 0.80869 timestamp: 1655056492.6275697 iteration: 60470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10852 FastRCNN class loss: 0.08943 FastRCNN total loss: 0.19796 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.15307 RPN box loss: 0.01896 RPN score loss: 0.01151 RPN total loss: 0.03047 Total loss: 0.95055 timestamp: 1655056495.8782446 iteration: 60475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13009 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.12996 RPN box loss: 0.01399 RPN score loss: 0.00142 RPN total loss: 0.01541 Total loss: 0.90504 timestamp: 1655056499.163415 iteration: 60480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08513 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.16915 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.13888 RPN box loss: 0.02902 RPN score loss: 0.00338 RPN total loss: 0.0324 Total loss: 0.90949 timestamp: 1655056502.4367187 iteration: 60485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13158 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.20485 L1 loss: 0.0000e+00 L2 loss: 0.56906 Learning rate: 0.0004 Mask loss: 0.13358 RPN box loss: 0.01468 RPN score loss: 0.00938 RPN total loss: 0.02406 Total loss: 0.93155 timestamp: 1655056505.6907108 iteration: 60490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07226 FastRCNN class loss: 0.04172 FastRCNN total loss: 0.11398 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.10992 RPN box loss: 0.01207 RPN score loss: 0.009 RPN total loss: 0.02107 Total loss: 0.81402 timestamp: 1655056508.9380667 iteration: 60495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13491 FastRCNN class loss: 0.07248 FastRCNN total loss: 0.20739 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.17828 RPN box loss: 0.01565 RPN score loss: 0.00359 RPN total loss: 0.01924 Total loss: 0.97397 timestamp: 1655056512.194699 iteration: 60500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14946 FastRCNN class loss: 0.06822 FastRCNN total loss: 0.21768 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.14761 RPN box loss: 0.01366 RPN score loss: 0.00164 RPN total loss: 0.0153 Total loss: 0.94965 timestamp: 1655056515.5025892 iteration: 60505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06674 FastRCNN class loss: 0.03816 FastRCNN total loss: 0.1049 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.1208 RPN box loss: 0.00375 RPN score loss: 0.00795 RPN total loss: 0.01169 Total loss: 0.80644 timestamp: 1655056518.812969 iteration: 60510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12873 FastRCNN class loss: 0.09035 FastRCNN total loss: 0.21908 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.13543 RPN box loss: 0.00816 RPN score loss: 0.0031 RPN total loss: 0.01126 Total loss: 0.93482 timestamp: 1655056522.1403415 iteration: 60515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09256 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.16862 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.14662 RPN box loss: 0.01687 RPN score loss: 0.00496 RPN total loss: 0.02183 Total loss: 0.90611 timestamp: 1655056525.376817 iteration: 60520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05718 FastRCNN class loss: 0.0306 FastRCNN total loss: 0.08778 L1 loss: 0.0000e+00 L2 loss: 0.56905 Learning rate: 0.0004 Mask loss: 0.13008 RPN box loss: 0.02106 RPN score loss: 0.0015 RPN total loss: 0.02256 Total loss: 0.80947 timestamp: 1655056528.7111394 iteration: 60525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10876 FastRCNN class loss: 0.07504 FastRCNN total loss: 0.1838 L1 loss: 0.0000e+00 L2 loss: 0.56904 Learning rate: 0.0004 Mask loss: 0.13787 RPN box loss: 0.00844 RPN score loss: 0.00257 RPN total loss: 0.011 Total loss: 0.90172 timestamp: 1655056531.959746 iteration: 60530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.16052 L1 loss: 0.0000e+00 L2 loss: 0.56904 Learning rate: 0.0004 Mask loss: 0.16266 RPN box loss: 0.01629 RPN score loss: 0.00519 RPN total loss: 0.02147 Total loss: 0.91369 timestamp: 1655056535.257276 iteration: 60535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.14121 L1 loss: 0.0000e+00 L2 loss: 0.56904 Learning rate: 0.0004 Mask loss: 0.16351 RPN box loss: 0.0105 RPN score loss: 0.0024 RPN total loss: 0.0129 Total loss: 0.88666 timestamp: 1655056538.4822383 iteration: 60540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08269 FastRCNN class loss: 0.04043 FastRCNN total loss: 0.12312 L1 loss: 0.0000e+00 L2 loss: 0.56904 Learning rate: 0.0004 Mask loss: 0.06861 RPN box loss: 0.00442 RPN score loss: 0.0014 RPN total loss: 0.00582 Total loss: 0.76659 timestamp: 1655056541.78301 iteration: 60545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.20979 L1 loss: 0.0000e+00 L2 loss: 0.56904 Learning rate: 0.0004 Mask loss: 0.18507 RPN box loss: 0.04102 RPN score loss: 0.02165 RPN total loss: 0.06267 Total loss: 1.02657 timestamp: 1655056545.1098258 iteration: 60550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10596 FastRCNN class loss: 0.07799 FastRCNN total loss: 0.18395 L1 loss: 0.0000e+00 L2 loss: 0.56903 Learning rate: 0.0004 Mask loss: 0.12941 RPN box loss: 0.01524 RPN score loss: 0.00457 RPN total loss: 0.01981 Total loss: 0.9022 timestamp: 1655056548.4233954 iteration: 60555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06688 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.12899 L1 loss: 0.0000e+00 L2 loss: 0.56903 Learning rate: 0.0004 Mask loss: 0.16782 RPN box loss: 0.01391 RPN score loss: 0.00815 RPN total loss: 0.02206 Total loss: 0.88791 timestamp: 1655056551.7467396 iteration: 60560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14212 FastRCNN class loss: 0.10862 FastRCNN total loss: 0.25075 L1 loss: 0.0000e+00 L2 loss: 0.56903 Learning rate: 0.0004 Mask loss: 0.20999 RPN box loss: 0.01396 RPN score loss: 0.007 RPN total loss: 0.02096 Total loss: 1.05073 timestamp: 1655056555.017334 iteration: 60565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05471 FastRCNN class loss: 0.0525 FastRCNN total loss: 0.10721 L1 loss: 0.0000e+00 L2 loss: 0.56903 Learning rate: 0.0004 Mask loss: 0.15019 RPN box loss: 0.00906 RPN score loss: 0.00311 RPN total loss: 0.01218 Total loss: 0.8386 timestamp: 1655056558.289504 iteration: 60570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08712 FastRCNN class loss: 0.07396 FastRCNN total loss: 0.16107 L1 loss: 0.0000e+00 L2 loss: 0.56903 Learning rate: 0.0004 Mask loss: 0.25051 RPN box loss: 0.00449 RPN score loss: 0.00649 RPN total loss: 0.01098 Total loss: 0.99159 timestamp: 1655056561.4782243 iteration: 60575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0763 FastRCNN class loss: 0.04369 FastRCNN total loss: 0.12 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.15681 RPN box loss: 0.00592 RPN score loss: 0.00479 RPN total loss: 0.01071 Total loss: 0.85654 timestamp: 1655056564.7571008 iteration: 60580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08845 FastRCNN class loss: 0.07479 FastRCNN total loss: 0.16324 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.13499 RPN box loss: 0.01289 RPN score loss: 0.00138 RPN total loss: 0.01427 Total loss: 0.88152 timestamp: 1655056568.0399916 iteration: 60585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13908 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.2174 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.25271 RPN box loss: 0.00964 RPN score loss: 0.00446 RPN total loss: 0.0141 Total loss: 1.05322 timestamp: 1655056571.311446 iteration: 60590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09258 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.15418 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.14449 RPN box loss: 0.01915 RPN score loss: 0.00675 RPN total loss: 0.02589 Total loss: 0.89357 timestamp: 1655056574.565858 iteration: 60595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11426 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.18164 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.12442 RPN box loss: 0.01109 RPN score loss: 0.00516 RPN total loss: 0.01625 Total loss: 0.89133 timestamp: 1655056577.8409693 iteration: 60600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17215 FastRCNN class loss: 0.07522 FastRCNN total loss: 0.24737 L1 loss: 0.0000e+00 L2 loss: 0.56902 Learning rate: 0.0004 Mask loss: 0.12698 RPN box loss: 0.02799 RPN score loss: 0.01218 RPN total loss: 0.04017 Total loss: 0.98353 timestamp: 1655056581.1352766 iteration: 60605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08563 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.1461 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.0966 RPN box loss: 0.00965 RPN score loss: 0.0111 RPN total loss: 0.02075 Total loss: 0.83246 timestamp: 1655056584.3890095 iteration: 60610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11008 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.19786 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.12695 RPN box loss: 0.02595 RPN score loss: 0.00622 RPN total loss: 0.03217 Total loss: 0.92599 timestamp: 1655056587.7408252 iteration: 60615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11964 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.19773 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.15958 RPN box loss: 0.04194 RPN score loss: 0.00417 RPN total loss: 0.04611 Total loss: 0.97244 timestamp: 1655056591.041944 iteration: 60620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10813 FastRCNN class loss: 0.09013 FastRCNN total loss: 0.19826 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.15593 RPN box loss: 0.00975 RPN score loss: 0.0039 RPN total loss: 0.01364 Total loss: 0.93685 timestamp: 1655056594.3620803 iteration: 60625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08841 FastRCNN class loss: 0.05724 FastRCNN total loss: 0.14565 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.13506 RPN box loss: 0.00889 RPN score loss: 0.00336 RPN total loss: 0.01225 Total loss: 0.86196 timestamp: 1655056597.5800543 iteration: 60630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.04791 FastRCNN total loss: 0.12165 L1 loss: 0.0000e+00 L2 loss: 0.56901 Learning rate: 0.0004 Mask loss: 0.11246 RPN box loss: 0.02192 RPN score loss: 0.01538 RPN total loss: 0.0373 Total loss: 0.84042 timestamp: 1655056600.827521 iteration: 60635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06283 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.12819 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.11443 RPN box loss: 0.00752 RPN score loss: 0.00259 RPN total loss: 0.01011 Total loss: 0.82173 timestamp: 1655056604.11004 iteration: 60640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11871 FastRCNN class loss: 0.1041 FastRCNN total loss: 0.22282 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.16631 RPN box loss: 0.02564 RPN score loss: 0.00317 RPN total loss: 0.02882 Total loss: 0.98695 timestamp: 1655056607.3553543 iteration: 60645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15184 FastRCNN class loss: 0.07247 FastRCNN total loss: 0.2243 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.1518 RPN box loss: 0.04284 RPN score loss: 0.00295 RPN total loss: 0.04579 Total loss: 0.99089 timestamp: 1655056610.6427624 iteration: 60650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06282 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.12081 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.15175 RPN box loss: 0.01443 RPN score loss: 0.0075 RPN total loss: 0.02193 Total loss: 0.86349 timestamp: 1655056613.834223 iteration: 60655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04761 FastRCNN class loss: 0.05114 FastRCNN total loss: 0.09875 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.10438 RPN box loss: 0.00591 RPN score loss: 0.00677 RPN total loss: 0.01268 Total loss: 0.78481 timestamp: 1655056617.0856693 iteration: 60660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11397 FastRCNN class loss: 0.10395 FastRCNN total loss: 0.21792 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.16967 RPN box loss: 0.02502 RPN score loss: 0.01042 RPN total loss: 0.03545 Total loss: 0.99203 timestamp: 1655056620.2735238 iteration: 60665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08338 FastRCNN class loss: 0.05353 FastRCNN total loss: 0.13691 L1 loss: 0.0000e+00 L2 loss: 0.569 Learning rate: 0.0004 Mask loss: 0.13723 RPN box loss: 0.00922 RPN score loss: 0.00279 RPN total loss: 0.01201 Total loss: 0.85515 timestamp: 1655056623.5452614 iteration: 60670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1048 FastRCNN class loss: 0.08913 FastRCNN total loss: 0.19393 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.12247 RPN box loss: 0.01576 RPN score loss: 0.00209 RPN total loss: 0.01785 Total loss: 0.90325 timestamp: 1655056626.7419696 iteration: 60675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08911 FastRCNN class loss: 0.04446 FastRCNN total loss: 0.13358 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.14963 RPN box loss: 0.00338 RPN score loss: 0.00369 RPN total loss: 0.00706 Total loss: 0.85926 timestamp: 1655056630.0189514 iteration: 60680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17208 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.24462 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.11018 RPN box loss: 0.01507 RPN score loss: 0.00597 RPN total loss: 0.02104 Total loss: 0.94483 timestamp: 1655056633.2330365 iteration: 60685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11849 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.18265 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.1486 RPN box loss: 0.02926 RPN score loss: 0.00682 RPN total loss: 0.03608 Total loss: 0.93633 timestamp: 1655056636.5218577 iteration: 60690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13634 FastRCNN class loss: 0.10084 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.17991 RPN box loss: 0.01582 RPN score loss: 0.00491 RPN total loss: 0.02073 Total loss: 1.00681 timestamp: 1655056639.8076475 iteration: 60695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1032 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.19995 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.18089 RPN box loss: 0.02646 RPN score loss: 0.00208 RPN total loss: 0.02854 Total loss: 0.97837 timestamp: 1655056643.161294 iteration: 60700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15171 FastRCNN class loss: 0.07928 FastRCNN total loss: 0.23099 L1 loss: 0.0000e+00 L2 loss: 0.56899 Learning rate: 0.0004 Mask loss: 0.16179 RPN box loss: 0.01212 RPN score loss: 0.00261 RPN total loss: 0.01473 Total loss: 0.97649 timestamp: 1655056646.4172356 iteration: 60705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05018 FastRCNN class loss: 0.03912 FastRCNN total loss: 0.0893 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.08124 RPN box loss: 0.00392 RPN score loss: 0.0039 RPN total loss: 0.00782 Total loss: 0.74733 timestamp: 1655056649.6710784 iteration: 60710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07019 FastRCNN class loss: 0.04398 FastRCNN total loss: 0.11417 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.13761 RPN box loss: 0.00548 RPN score loss: 0.0059 RPN total loss: 0.01138 Total loss: 0.83214 timestamp: 1655056652.9929602 iteration: 60715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.12775 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.12905 RPN box loss: 0.0124 RPN score loss: 0.00423 RPN total loss: 0.01662 Total loss: 0.84241 timestamp: 1655056656.2993195 iteration: 60720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.22351 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.29406 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.11889 RPN box loss: 0.02223 RPN score loss: 0.01319 RPN total loss: 0.03542 Total loss: 1.01735 timestamp: 1655056659.52699 iteration: 60725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06624 FastRCNN class loss: 0.03495 FastRCNN total loss: 0.10118 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.1309 RPN box loss: 0.01245 RPN score loss: 0.00131 RPN total loss: 0.01375 Total loss: 0.81482 timestamp: 1655056662.7924638 iteration: 60730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0606 FastRCNN class loss: 0.05309 FastRCNN total loss: 0.11369 L1 loss: 0.0000e+00 L2 loss: 0.56898 Learning rate: 0.0004 Mask loss: 0.13046 RPN box loss: 0.01105 RPN score loss: 0.00564 RPN total loss: 0.0167 Total loss: 0.82982 timestamp: 1655056666.0808296 iteration: 60735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06332 FastRCNN class loss: 0.07643 FastRCNN total loss: 0.13976 L1 loss: 0.0000e+00 L2 loss: 0.56897 Learning rate: 0.0004 Mask loss: 0.09978 RPN box loss: 0.00699 RPN score loss: 0.00288 RPN total loss: 0.00986 Total loss: 0.81838 timestamp: 1655056669.4151747 iteration: 60740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0619 FastRCNN class loss: 0.03354 FastRCNN total loss: 0.09544 L1 loss: 0.0000e+00 L2 loss: 0.56897 Learning rate: 0.0004 Mask loss: 0.0952 RPN box loss: 0.00656 RPN score loss: 0.00278 RPN total loss: 0.00934 Total loss: 0.76895 timestamp: 1655056672.6909676 iteration: 60745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08405 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.15749 L1 loss: 0.0000e+00 L2 loss: 0.56897 Learning rate: 0.0004 Mask loss: 0.14025 RPN box loss: 0.02347 RPN score loss: 0.00239 RPN total loss: 0.02586 Total loss: 0.89256 timestamp: 1655056675.9581828 iteration: 60750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11485 FastRCNN class loss: 0.09872 FastRCNN total loss: 0.21357 L1 loss: 0.0000e+00 L2 loss: 0.56897 Learning rate: 0.0004 Mask loss: 0.15511 RPN box loss: 0.02319 RPN score loss: 0.01056 RPN total loss: 0.03375 Total loss: 0.9714 timestamp: 1655056679.2606952 iteration: 60755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08181 FastRCNN class loss: 0.0981 FastRCNN total loss: 0.17991 L1 loss: 0.0000e+00 L2 loss: 0.56897 Learning rate: 0.0004 Mask loss: 0.15944 RPN box loss: 0.01734 RPN score loss: 0.00514 RPN total loss: 0.02248 Total loss: 0.9308 timestamp: 1655056682.5710833 iteration: 60760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07761 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.15804 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.1308 RPN box loss: 0.01128 RPN score loss: 0.00347 RPN total loss: 0.01475 Total loss: 0.87256 timestamp: 1655056685.6968668 iteration: 60765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1443 FastRCNN class loss: 0.06742 FastRCNN total loss: 0.21171 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.18051 RPN box loss: 0.01273 RPN score loss: 0.00256 RPN total loss: 0.0153 Total loss: 0.97648 timestamp: 1655056688.9051418 iteration: 60770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15843 FastRCNN class loss: 0.08572 FastRCNN total loss: 0.24415 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.16343 RPN box loss: 0.01508 RPN score loss: 0.00252 RPN total loss: 0.01761 Total loss: 0.99415 timestamp: 1655056692.0957909 iteration: 60775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06505 FastRCNN class loss: 0.06081 FastRCNN total loss: 0.12586 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.11721 RPN box loss: 0.02022 RPN score loss: 0.00334 RPN total loss: 0.02356 Total loss: 0.83559 timestamp: 1655056695.3666399 iteration: 60780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05457 FastRCNN class loss: 0.03089 FastRCNN total loss: 0.08546 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.14208 RPN box loss: 0.0069 RPN score loss: 0.00127 RPN total loss: 0.00817 Total loss: 0.80467 timestamp: 1655056698.6832607 iteration: 60785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13275 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.21749 L1 loss: 0.0000e+00 L2 loss: 0.56896 Learning rate: 0.0004 Mask loss: 0.20359 RPN box loss: 0.0266 RPN score loss: 0.0067 RPN total loss: 0.0333 Total loss: 1.02334 timestamp: 1655056701.9996402 iteration: 60790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07544 FastRCNN class loss: 0.07885 FastRCNN total loss: 0.15429 L1 loss: 0.0000e+00 L2 loss: 0.56895 Learning rate: 0.0004 Mask loss: 0.12382 RPN box loss: 0.0084 RPN score loss: 0.00695 RPN total loss: 0.01536 Total loss: 0.86243 timestamp: 1655056705.2547646 iteration: 60795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06421 FastRCNN class loss: 0.06445 FastRCNN total loss: 0.12866 L1 loss: 0.0000e+00 L2 loss: 0.56895 Learning rate: 0.0004 Mask loss: 0.14981 RPN box loss: 0.00848 RPN score loss: 0.00296 RPN total loss: 0.01144 Total loss: 0.85886 timestamp: 1655056708.5389497 iteration: 60800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19749 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.27676 L1 loss: 0.0000e+00 L2 loss: 0.56895 Learning rate: 0.0004 Mask loss: 0.11041 RPN box loss: 0.01573 RPN score loss: 0.00255 RPN total loss: 0.01828 Total loss: 0.9744 timestamp: 1655056711.8419058 iteration: 60805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15483 FastRCNN class loss: 0.09075 FastRCNN total loss: 0.24558 L1 loss: 0.0000e+00 L2 loss: 0.56895 Learning rate: 0.0004 Mask loss: 0.17467 RPN box loss: 0.0177 RPN score loss: 0.00587 RPN total loss: 0.02357 Total loss: 1.01277 timestamp: 1655056715.1451156 iteration: 60810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08152 FastRCNN class loss: 0.04279 FastRCNN total loss: 0.12431 L1 loss: 0.0000e+00 L2 loss: 0.56895 Learning rate: 0.0004 Mask loss: 0.133 RPN box loss: 0.00325 RPN score loss: 0.00208 RPN total loss: 0.00532 Total loss: 0.83158 timestamp: 1655056718.3115785 iteration: 60815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09607 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.16712 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.16727 RPN box loss: 0.01217 RPN score loss: 0.00768 RPN total loss: 0.01985 Total loss: 0.92318 timestamp: 1655056721.591833 iteration: 60820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13581 FastRCNN class loss: 0.10943 FastRCNN total loss: 0.24525 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.18191 RPN box loss: 0.00976 RPN score loss: 0.00345 RPN total loss: 0.01321 Total loss: 1.00931 timestamp: 1655056724.817777 iteration: 60825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13529 FastRCNN class loss: 0.07174 FastRCNN total loss: 0.20704 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.14573 RPN box loss: 0.01205 RPN score loss: 0.0111 RPN total loss: 0.02315 Total loss: 0.94486 timestamp: 1655056728.0646448 iteration: 60830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09366 FastRCNN class loss: 0.08882 FastRCNN total loss: 0.18249 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.14603 RPN box loss: 0.00349 RPN score loss: 0.0027 RPN total loss: 0.00618 Total loss: 0.90364 timestamp: 1655056731.3724573 iteration: 60835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0527 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.10881 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.10929 RPN box loss: 0.00889 RPN score loss: 0.00521 RPN total loss: 0.0141 Total loss: 0.80114 timestamp: 1655056734.6147637 iteration: 60840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11837 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.18271 L1 loss: 0.0000e+00 L2 loss: 0.56894 Learning rate: 0.0004 Mask loss: 0.12777 RPN box loss: 0.00889 RPN score loss: 0.00356 RPN total loss: 0.01245 Total loss: 0.89186 timestamp: 1655056737.8736618 iteration: 60845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07679 FastRCNN class loss: 0.06558 FastRCNN total loss: 0.14237 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.10894 RPN box loss: 0.01001 RPN score loss: 0.0066 RPN total loss: 0.01661 Total loss: 0.83685 timestamp: 1655056741.0892677 iteration: 60850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06173 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.12841 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.10425 RPN box loss: 0.01983 RPN score loss: 0.00247 RPN total loss: 0.0223 Total loss: 0.8239 timestamp: 1655056744.3659647 iteration: 60855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08899 FastRCNN class loss: 0.07558 FastRCNN total loss: 0.16457 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.11786 RPN box loss: 0.00872 RPN score loss: 0.0058 RPN total loss: 0.01452 Total loss: 0.86589 timestamp: 1655056747.6341658 iteration: 60860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08476 FastRCNN class loss: 0.07975 FastRCNN total loss: 0.1645 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.13036 RPN box loss: 0.00997 RPN score loss: 0.00928 RPN total loss: 0.01924 Total loss: 0.88304 timestamp: 1655056750.962605 iteration: 60865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08867 FastRCNN class loss: 0.07569 FastRCNN total loss: 0.16437 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.15705 RPN box loss: 0.01855 RPN score loss: 0.00233 RPN total loss: 0.02088 Total loss: 0.91123 timestamp: 1655056754.1665466 iteration: 60870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08753 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.16341 L1 loss: 0.0000e+00 L2 loss: 0.56893 Learning rate: 0.0004 Mask loss: 0.14017 RPN box loss: 0.01207 RPN score loss: 0.00697 RPN total loss: 0.01903 Total loss: 0.89154 timestamp: 1655056757.45158 iteration: 60875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12959 FastRCNN class loss: 0.0848 FastRCNN total loss: 0.21438 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.13307 RPN box loss: 0.00984 RPN score loss: 0.00845 RPN total loss: 0.0183 Total loss: 0.93467 timestamp: 1655056760.628595 iteration: 60880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15188 FastRCNN class loss: 0.12592 FastRCNN total loss: 0.2778 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.24108 RPN box loss: 0.01828 RPN score loss: 0.01199 RPN total loss: 0.03027 Total loss: 1.11807 timestamp: 1655056763.8733337 iteration: 60885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.11106 FastRCNN total loss: 0.20947 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.13868 RPN box loss: 0.0105 RPN score loss: 0.00693 RPN total loss: 0.01743 Total loss: 0.93449 timestamp: 1655056767.1079187 iteration: 60890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08569 FastRCNN class loss: 0.05839 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.19307 RPN box loss: 0.01147 RPN score loss: 0.00943 RPN total loss: 0.02091 Total loss: 0.92698 timestamp: 1655056770.383459 iteration: 60895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.12372 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.0871 RPN box loss: 0.00791 RPN score loss: 0.00434 RPN total loss: 0.01226 Total loss: 0.792 timestamp: 1655056773.691597 iteration: 60900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08006 FastRCNN class loss: 0.06848 FastRCNN total loss: 0.14854 L1 loss: 0.0000e+00 L2 loss: 0.56892 Learning rate: 0.0004 Mask loss: 0.18266 RPN box loss: 0.01936 RPN score loss: 0.0243 RPN total loss: 0.04366 Total loss: 0.94378 timestamp: 1655056776.9861782 iteration: 60905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.03172 FastRCNN total loss: 0.10153 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.09429 RPN box loss: 0.00636 RPN score loss: 0.00823 RPN total loss: 0.01459 Total loss: 0.77933 timestamp: 1655056780.2242122 iteration: 60910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13376 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.20315 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.17201 RPN box loss: 0.02537 RPN score loss: 0.01921 RPN total loss: 0.04458 Total loss: 0.98865 timestamp: 1655056783.4139986 iteration: 60915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05587 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.12168 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.08358 RPN box loss: 0.01127 RPN score loss: 0.02014 RPN total loss: 0.03142 Total loss: 0.80559 timestamp: 1655056786.6681864 iteration: 60920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05497 FastRCNN class loss: 0.04125 FastRCNN total loss: 0.09622 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.0817 RPN box loss: 0.03898 RPN score loss: 0.00162 RPN total loss: 0.0406 Total loss: 0.78744 timestamp: 1655056789.9417746 iteration: 60925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05158 FastRCNN class loss: 0.0415 FastRCNN total loss: 0.09308 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.14156 RPN box loss: 0.00381 RPN score loss: 0.00118 RPN total loss: 0.00499 Total loss: 0.80853 timestamp: 1655056793.2316349 iteration: 60930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05914 FastRCNN class loss: 0.04666 FastRCNN total loss: 0.1058 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.1158 RPN box loss: 0.01132 RPN score loss: 0.00313 RPN total loss: 0.01445 Total loss: 0.80496 timestamp: 1655056796.5350106 iteration: 60935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14625 FastRCNN class loss: 0.10175 FastRCNN total loss: 0.248 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.16757 RPN box loss: 0.01987 RPN score loss: 0.00975 RPN total loss: 0.02961 Total loss: 1.01409 timestamp: 1655056799.7467399 iteration: 60940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11001 FastRCNN class loss: 0.07186 FastRCNN total loss: 0.18187 L1 loss: 0.0000e+00 L2 loss: 0.56891 Learning rate: 0.0004 Mask loss: 0.12865 RPN box loss: 0.0079 RPN score loss: 0.0044 RPN total loss: 0.0123 Total loss: 0.89172 timestamp: 1655056803.0571682 iteration: 60945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08966 FastRCNN class loss: 0.05682 FastRCNN total loss: 0.14648 L1 loss: 0.0000e+00 L2 loss: 0.5689 Learning rate: 0.0004 Mask loss: 0.14433 RPN box loss: 0.00314 RPN score loss: 0.00574 RPN total loss: 0.00888 Total loss: 0.8686 timestamp: 1655056806.2781706 iteration: 60950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14036 FastRCNN class loss: 0.12111 FastRCNN total loss: 0.26146 L1 loss: 0.0000e+00 L2 loss: 0.5689 Learning rate: 0.0004 Mask loss: 0.19131 RPN box loss: 0.02272 RPN score loss: 0.01088 RPN total loss: 0.0336 Total loss: 1.05528 timestamp: 1655056809.5083356 iteration: 60955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08125 FastRCNN class loss: 0.07235 FastRCNN total loss: 0.1536 L1 loss: 0.0000e+00 L2 loss: 0.5689 Learning rate: 0.0004 Mask loss: 0.10728 RPN box loss: 0.01988 RPN score loss: 0.00594 RPN total loss: 0.02582 Total loss: 0.8556 timestamp: 1655056812.8194082 iteration: 60960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13093 FastRCNN class loss: 0.08818 FastRCNN total loss: 0.21911 L1 loss: 0.0000e+00 L2 loss: 0.5689 Learning rate: 0.0004 Mask loss: 0.15417 RPN box loss: 0.01147 RPN score loss: 0.00735 RPN total loss: 0.01882 Total loss: 0.961 timestamp: 1655056816.0878158 iteration: 60965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08678 FastRCNN class loss: 0.06962 FastRCNN total loss: 0.1564 L1 loss: 0.0000e+00 L2 loss: 0.5689 Learning rate: 0.0004 Mask loss: 0.15771 RPN box loss: 0.01366 RPN score loss: 0.00784 RPN total loss: 0.0215 Total loss: 0.9045 timestamp: 1655056819.3250048 iteration: 60970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10803 FastRCNN class loss: 0.05095 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.14624 RPN box loss: 0.01659 RPN score loss: 0.00725 RPN total loss: 0.02384 Total loss: 0.89796 timestamp: 1655056822.6113546 iteration: 60975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09477 FastRCNN class loss: 0.07077 FastRCNN total loss: 0.16554 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.12116 RPN box loss: 0.02164 RPN score loss: 0.00547 RPN total loss: 0.02711 Total loss: 0.88271 timestamp: 1655056825.8627803 iteration: 60980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06737 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.13401 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.11863 RPN box loss: 0.00585 RPN score loss: 0.00181 RPN total loss: 0.00766 Total loss: 0.82919 timestamp: 1655056829.2125857 iteration: 60985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0279 FastRCNN class loss: 0.0423 FastRCNN total loss: 0.07019 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.18114 RPN box loss: 0.003 RPN score loss: 0.00427 RPN total loss: 0.00726 Total loss: 0.82749 timestamp: 1655056832.4983983 iteration: 60990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08932 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.15366 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.12165 RPN box loss: 0.00951 RPN score loss: 0.00308 RPN total loss: 0.01259 Total loss: 0.85678 timestamp: 1655056835.8105438 iteration: 60995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10593 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.1881 L1 loss: 0.0000e+00 L2 loss: 0.56889 Learning rate: 0.0004 Mask loss: 0.15727 RPN box loss: 0.02579 RPN score loss: 0.01251 RPN total loss: 0.0383 Total loss: 0.95256 timestamp: 1655056839.045988 iteration: 61000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11346 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.16668 L1 loss: 0.0000e+00 L2 loss: 0.56888 Learning rate: 0.0004 Mask loss: 0.11281 RPN box loss: 0.01951 RPN score loss: 0.00383 RPN total loss: 0.02334 Total loss: 0.87172 timestamp: 1655056842.343716 iteration: 61005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07591 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.13108 L1 loss: 0.0000e+00 L2 loss: 0.56888 Learning rate: 0.0004 Mask loss: 0.13016 RPN box loss: 0.01002 RPN score loss: 0.00335 RPN total loss: 0.01337 Total loss: 0.84349 timestamp: 1655056845.58249 iteration: 61010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1564 FastRCNN class loss: 0.06906 FastRCNN total loss: 0.22546 L1 loss: 0.0000e+00 L2 loss: 0.56888 Learning rate: 0.0004 Mask loss: 0.16255 RPN box loss: 0.02335 RPN score loss: 0.005 RPN total loss: 0.02835 Total loss: 0.98525 timestamp: 1655056848.8882716 iteration: 61015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06085 FastRCNN class loss: 0.03841 FastRCNN total loss: 0.09925 L1 loss: 0.0000e+00 L2 loss: 0.56888 Learning rate: 0.0004 Mask loss: 0.12829 RPN box loss: 0.00233 RPN score loss: 0.00312 RPN total loss: 0.00545 Total loss: 0.80188 timestamp: 1655056852.215468 iteration: 61020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09588 FastRCNN class loss: 0.09695 FastRCNN total loss: 0.19283 L1 loss: 0.0000e+00 L2 loss: 0.56888 Learning rate: 0.0004 Mask loss: 0.23037 RPN box loss: 0.02419 RPN score loss: 0.00753 RPN total loss: 0.03172 Total loss: 1.0238 timestamp: 1655056855.3996315 iteration: 61025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08654 FastRCNN class loss: 0.08355 FastRCNN total loss: 0.1701 L1 loss: 0.0000e+00 L2 loss: 0.56887 Learning rate: 0.0004 Mask loss: 0.0887 RPN box loss: 0.01934 RPN score loss: 0.00506 RPN total loss: 0.0244 Total loss: 0.85207 timestamp: 1655056858.6102185 iteration: 61030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05239 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.11444 L1 loss: 0.0000e+00 L2 loss: 0.56887 Learning rate: 0.0004 Mask loss: 0.1459 RPN box loss: 0.01723 RPN score loss: 0.0112 RPN total loss: 0.02843 Total loss: 0.85764 timestamp: 1655056861.9252071 iteration: 61035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09003 FastRCNN class loss: 0.10326 FastRCNN total loss: 0.19329 L1 loss: 0.0000e+00 L2 loss: 0.56887 Learning rate: 0.0004 Mask loss: 0.15253 RPN box loss: 0.02434 RPN score loss: 0.00757 RPN total loss: 0.0319 Total loss: 0.94659 timestamp: 1655056865.255133 iteration: 61040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16731 FastRCNN class loss: 0.08823 FastRCNN total loss: 0.25554 L1 loss: 0.0000e+00 L2 loss: 0.56887 Learning rate: 0.0004 Mask loss: 0.16856 RPN box loss: 0.01437 RPN score loss: 0.00876 RPN total loss: 0.02314 Total loss: 1.0161 timestamp: 1655056868.4814684 iteration: 61045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10911 FastRCNN class loss: 0.04797 FastRCNN total loss: 0.15708 L1 loss: 0.0000e+00 L2 loss: 0.56887 Learning rate: 0.0004 Mask loss: 0.13389 RPN box loss: 0.01166 RPN score loss: 0.00342 RPN total loss: 0.01508 Total loss: 0.87492 timestamp: 1655056871.714197 iteration: 61050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07987 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.13111 L1 loss: 0.0000e+00 L2 loss: 0.56886 Learning rate: 0.0004 Mask loss: 0.16047 RPN box loss: 0.06307 RPN score loss: 0.00412 RPN total loss: 0.06719 Total loss: 0.92763 timestamp: 1655056875.0261433 iteration: 61055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05311 FastRCNN class loss: 0.03756 FastRCNN total loss: 0.09068 L1 loss: 0.0000e+00 L2 loss: 0.56886 Learning rate: 0.0004 Mask loss: 0.09008 RPN box loss: 0.01082 RPN score loss: 0.00258 RPN total loss: 0.0134 Total loss: 0.76302 timestamp: 1655056878.2504735 iteration: 61060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09495 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.16729 L1 loss: 0.0000e+00 L2 loss: 0.56886 Learning rate: 0.0004 Mask loss: 0.12529 RPN box loss: 0.00847 RPN score loss: 0.00483 RPN total loss: 0.0133 Total loss: 0.87474 timestamp: 1655056881.551414 iteration: 61065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10888 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.17927 L1 loss: 0.0000e+00 L2 loss: 0.56886 Learning rate: 0.0004 Mask loss: 0.14828 RPN box loss: 0.02015 RPN score loss: 0.00404 RPN total loss: 0.0242 Total loss: 0.92061 timestamp: 1655056884.8460996 iteration: 61070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07259 FastRCNN class loss: 0.08979 FastRCNN total loss: 0.16238 L1 loss: 0.0000e+00 L2 loss: 0.56886 Learning rate: 0.0004 Mask loss: 0.15104 RPN box loss: 0.02283 RPN score loss: 0.01039 RPN total loss: 0.03322 Total loss: 0.9155 timestamp: 1655056888.1184156 iteration: 61075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1095 FastRCNN class loss: 0.04013 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.15956 RPN box loss: 0.01361 RPN score loss: 0.00851 RPN total loss: 0.02212 Total loss: 0.90017 timestamp: 1655056891.3932772 iteration: 61080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11625 FastRCNN class loss: 0.06554 FastRCNN total loss: 0.18179 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.14277 RPN box loss: 0.00567 RPN score loss: 0.00461 RPN total loss: 0.01027 Total loss: 0.90369 timestamp: 1655056894.6829817 iteration: 61085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12151 FastRCNN class loss: 0.09475 FastRCNN total loss: 0.21626 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.17699 RPN box loss: 0.00566 RPN score loss: 0.00334 RPN total loss: 0.009 Total loss: 0.97111 timestamp: 1655056897.9557238 iteration: 61090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.1732 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.16815 RPN box loss: 0.01793 RPN score loss: 0.01013 RPN total loss: 0.02806 Total loss: 0.93826 timestamp: 1655056901.2346132 iteration: 61095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14165 FastRCNN class loss: 0.09241 FastRCNN total loss: 0.23406 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.17703 RPN box loss: 0.02826 RPN score loss: 0.00842 RPN total loss: 0.03669 Total loss: 1.01663 timestamp: 1655056904.540969 iteration: 61100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10087 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.17719 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.19701 RPN box loss: 0.03027 RPN score loss: 0.00636 RPN total loss: 0.03663 Total loss: 0.97968 timestamp: 1655056907.75462 iteration: 61105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08401 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.14283 L1 loss: 0.0000e+00 L2 loss: 0.56885 Learning rate: 0.0004 Mask loss: 0.1504 RPN box loss: 0.02299 RPN score loss: 0.00478 RPN total loss: 0.02776 Total loss: 0.88984 timestamp: 1655056910.9378157 iteration: 61110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12858 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.21188 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.18153 RPN box loss: 0.01888 RPN score loss: 0.00754 RPN total loss: 0.02642 Total loss: 0.98867 timestamp: 1655056914.1571472 iteration: 61115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13436 FastRCNN class loss: 0.08804 FastRCNN total loss: 0.2224 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.14767 RPN box loss: 0.01394 RPN score loss: 0.00384 RPN total loss: 0.01778 Total loss: 0.9567 timestamp: 1655056917.4649222 iteration: 61120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09445 FastRCNN class loss: 0.05782 FastRCNN total loss: 0.15227 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.10144 RPN box loss: 0.01753 RPN score loss: 0.00244 RPN total loss: 0.01997 Total loss: 0.84252 timestamp: 1655056920.7043087 iteration: 61125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07517 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.13062 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.13816 RPN box loss: 0.00746 RPN score loss: 0.00583 RPN total loss: 0.0133 Total loss: 0.85091 timestamp: 1655056924.0083 iteration: 61130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12015 FastRCNN class loss: 0.02914 FastRCNN total loss: 0.14929 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.09113 RPN box loss: 0.00628 RPN score loss: 0.00409 RPN total loss: 0.01036 Total loss: 0.81963 timestamp: 1655056927.3564038 iteration: 61135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08083 FastRCNN class loss: 0.05665 FastRCNN total loss: 0.13748 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.13681 RPN box loss: 0.01861 RPN score loss: 0.00207 RPN total loss: 0.02068 Total loss: 0.86381 timestamp: 1655056930.5746775 iteration: 61140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07045 FastRCNN class loss: 0.04927 FastRCNN total loss: 0.11972 L1 loss: 0.0000e+00 L2 loss: 0.56884 Learning rate: 0.0004 Mask loss: 0.09291 RPN box loss: 0.00371 RPN score loss: 0.00357 RPN total loss: 0.00728 Total loss: 0.78875 timestamp: 1655056933.8299015 iteration: 61145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11878 FastRCNN class loss: 0.0598 FastRCNN total loss: 0.17858 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.09722 RPN box loss: 0.00753 RPN score loss: 0.00294 RPN total loss: 0.01047 Total loss: 0.85509 timestamp: 1655056937.1294537 iteration: 61150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.146 FastRCNN class loss: 0.11371 FastRCNN total loss: 0.2597 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.17161 RPN box loss: 0.01094 RPN score loss: 0.00293 RPN total loss: 0.01387 Total loss: 1.01402 timestamp: 1655056940.4130871 iteration: 61155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11857 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.18076 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.12561 RPN box loss: 0.00664 RPN score loss: 0.002 RPN total loss: 0.00864 Total loss: 0.88384 timestamp: 1655056943.6883376 iteration: 61160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08451 FastRCNN class loss: 0.04294 FastRCNN total loss: 0.12744 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.09691 RPN box loss: 0.01041 RPN score loss: 0.00249 RPN total loss: 0.0129 Total loss: 0.80608 timestamp: 1655056947.0172145 iteration: 61165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.06108 FastRCNN total loss: 0.15224 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.16666 RPN box loss: 0.00674 RPN score loss: 0.00374 RPN total loss: 0.01048 Total loss: 0.8982 timestamp: 1655056950.2612092 iteration: 61170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11206 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.17993 L1 loss: 0.0000e+00 L2 loss: 0.56883 Learning rate: 0.0004 Mask loss: 0.12849 RPN box loss: 0.01989 RPN score loss: 0.00203 RPN total loss: 0.02192 Total loss: 0.89917 timestamp: 1655056953.5642633 iteration: 61175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18392 FastRCNN class loss: 0.09628 FastRCNN total loss: 0.2802 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.17276 RPN box loss: 0.01833 RPN score loss: 0.00975 RPN total loss: 0.02808 Total loss: 1.04987 timestamp: 1655056956.845992 iteration: 61180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11676 FastRCNN class loss: 0.10358 FastRCNN total loss: 0.22035 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.16021 RPN box loss: 0.02227 RPN score loss: 0.00892 RPN total loss: 0.03119 Total loss: 0.98058 timestamp: 1655056960.1278505 iteration: 61185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11678 FastRCNN class loss: 0.09638 FastRCNN total loss: 0.21316 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.15458 RPN box loss: 0.01273 RPN score loss: 0.00565 RPN total loss: 0.01837 Total loss: 0.95494 timestamp: 1655056963.4161186 iteration: 61190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11335 FastRCNN class loss: 0.0855 FastRCNN total loss: 0.19885 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.11662 RPN box loss: 0.01243 RPN score loss: 0.00581 RPN total loss: 0.01824 Total loss: 0.90253 timestamp: 1655056966.7559605 iteration: 61195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06573 FastRCNN class loss: 0.04739 FastRCNN total loss: 0.11312 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.13804 RPN box loss: 0.01755 RPN score loss: 0.00527 RPN total loss: 0.02282 Total loss: 0.8428 timestamp: 1655056969.9881103 iteration: 61200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.06146 FastRCNN total loss: 0.15941 L1 loss: 0.0000e+00 L2 loss: 0.56882 Learning rate: 0.0004 Mask loss: 0.12774 RPN box loss: 0.00536 RPN score loss: 0.00529 RPN total loss: 0.01065 Total loss: 0.86661 timestamp: 1655056973.2239122 iteration: 61205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09803 FastRCNN class loss: 0.09825 FastRCNN total loss: 0.19628 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.22559 RPN box loss: 0.00946 RPN score loss: 0.01412 RPN total loss: 0.02358 Total loss: 1.01426 timestamp: 1655056976.4605515 iteration: 61210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05505 FastRCNN class loss: 0.0412 FastRCNN total loss: 0.09625 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.10408 RPN box loss: 0.00869 RPN score loss: 0.00141 RPN total loss: 0.0101 Total loss: 0.77924 timestamp: 1655056979.7296703 iteration: 61215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0846 FastRCNN class loss: 0.06334 FastRCNN total loss: 0.14794 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.154 RPN box loss: 0.019 RPN score loss: 0.00323 RPN total loss: 0.02224 Total loss: 0.89298 timestamp: 1655056982.9785867 iteration: 61220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12761 FastRCNN class loss: 0.08594 FastRCNN total loss: 0.21355 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.19163 RPN box loss: 0.01791 RPN score loss: 0.01087 RPN total loss: 0.02878 Total loss: 1.00277 timestamp: 1655056986.260441 iteration: 61225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.04779 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.13169 RPN box loss: 0.00779 RPN score loss: 0.00349 RPN total loss: 0.01128 Total loss: 0.8594 timestamp: 1655056989.5327306 iteration: 61230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07641 FastRCNN class loss: 0.05149 FastRCNN total loss: 0.1279 L1 loss: 0.0000e+00 L2 loss: 0.56881 Learning rate: 0.0004 Mask loss: 0.14071 RPN box loss: 0.01535 RPN score loss: 0.01048 RPN total loss: 0.02583 Total loss: 0.86324 timestamp: 1655056992.80406 iteration: 61235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11734 FastRCNN class loss: 0.07888 FastRCNN total loss: 0.19622 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.17677 RPN box loss: 0.00899 RPN score loss: 0.00925 RPN total loss: 0.01825 Total loss: 0.96005 timestamp: 1655056996.0898023 iteration: 61240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12773 FastRCNN class loss: 0.0801 FastRCNN total loss: 0.20783 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.22174 RPN box loss: 0.01087 RPN score loss: 0.00276 RPN total loss: 0.01363 Total loss: 1.012 timestamp: 1655056999.38224 iteration: 61245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09893 FastRCNN class loss: 0.07084 FastRCNN total loss: 0.16977 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.12916 RPN box loss: 0.01433 RPN score loss: 0.0049 RPN total loss: 0.01923 Total loss: 0.88697 timestamp: 1655057002.7149365 iteration: 61250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05909 FastRCNN class loss: 0.05062 FastRCNN total loss: 0.10971 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.11759 RPN box loss: 0.00891 RPN score loss: 0.00149 RPN total loss: 0.0104 Total loss: 0.8065 timestamp: 1655057006.0269322 iteration: 61255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07907 FastRCNN class loss: 0.07352 FastRCNN total loss: 0.15259 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.10092 RPN box loss: 0.02207 RPN score loss: 0.00868 RPN total loss: 0.03075 Total loss: 0.85306 timestamp: 1655057009.2755435 iteration: 61260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.08707 FastRCNN total loss: 0.23524 L1 loss: 0.0000e+00 L2 loss: 0.5688 Learning rate: 0.0004 Mask loss: 0.14934 RPN box loss: 0.00439 RPN score loss: 0.00464 RPN total loss: 0.00902 Total loss: 0.96239 timestamp: 1655057012.5113845 iteration: 61265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.08976 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.13556 RPN box loss: 0.01774 RPN score loss: 0.00585 RPN total loss: 0.02358 Total loss: 0.92516 timestamp: 1655057015.7775247 iteration: 61270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07089 FastRCNN class loss: 0.0421 FastRCNN total loss: 0.11299 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.09177 RPN box loss: 0.00302 RPN score loss: 0.00158 RPN total loss: 0.0046 Total loss: 0.77815 timestamp: 1655057019.1191242 iteration: 61275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09401 FastRCNN class loss: 0.0723 FastRCNN total loss: 0.16631 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.10156 RPN box loss: 0.00702 RPN score loss: 0.00153 RPN total loss: 0.00855 Total loss: 0.84521 timestamp: 1655057022.3851256 iteration: 61280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11726 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.18077 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.19083 RPN box loss: 0.01652 RPN score loss: 0.00308 RPN total loss: 0.01961 Total loss: 0.96 timestamp: 1655057025.6670897 iteration: 61285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.05883 FastRCNN total loss: 0.12906 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.16217 RPN box loss: 0.00877 RPN score loss: 0.00102 RPN total loss: 0.00978 Total loss: 0.86979 timestamp: 1655057028.8849106 iteration: 61290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07774 FastRCNN class loss: 0.04776 FastRCNN total loss: 0.1255 L1 loss: 0.0000e+00 L2 loss: 0.56879 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.01753 RPN score loss: 0.00197 RPN total loss: 0.0195 Total loss: 0.83997 timestamp: 1655057032.0990467 iteration: 61295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.07159 FastRCNN total loss: 0.16694 L1 loss: 0.0000e+00 L2 loss: 0.56878 Learning rate: 0.0004 Mask loss: 0.10788 RPN box loss: 0.00768 RPN score loss: 0.00544 RPN total loss: 0.01312 Total loss: 0.85673 timestamp: 1655057035.384682 iteration: 61300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17141 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.24913 L1 loss: 0.0000e+00 L2 loss: 0.56878 Learning rate: 0.0004 Mask loss: 0.10266 RPN box loss: 0.01445 RPN score loss: 0.00503 RPN total loss: 0.01948 Total loss: 0.94005 timestamp: 1655057038.6041927 iteration: 61305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.04578 FastRCNN total loss: 0.1352 L1 loss: 0.0000e+00 L2 loss: 0.56878 Learning rate: 0.0004 Mask loss: 0.0976 RPN box loss: 0.01055 RPN score loss: 0.0025 RPN total loss: 0.01305 Total loss: 0.81464 timestamp: 1655057041.851716 iteration: 61310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.13349 L1 loss: 0.0000e+00 L2 loss: 0.56878 Learning rate: 0.0004 Mask loss: 0.13831 RPN box loss: 0.01026 RPN score loss: 0.00556 RPN total loss: 0.01582 Total loss: 0.8564 timestamp: 1655057045.0745816 iteration: 61315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16821 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.25308 L1 loss: 0.0000e+00 L2 loss: 0.56878 Learning rate: 0.0004 Mask loss: 0.18134 RPN box loss: 0.03011 RPN score loss: 0.00907 RPN total loss: 0.03918 Total loss: 1.04238 timestamp: 1655057048.3185024 iteration: 61320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.05566 FastRCNN total loss: 0.13981 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.09764 RPN box loss: 0.0168 RPN score loss: 0.00729 RPN total loss: 0.02409 Total loss: 0.83032 timestamp: 1655057051.616742 iteration: 61325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14957 FastRCNN class loss: 0.09872 FastRCNN total loss: 0.24829 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.20139 RPN box loss: 0.03276 RPN score loss: 0.0105 RPN total loss: 0.04326 Total loss: 1.06172 timestamp: 1655057054.8743806 iteration: 61330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11676 FastRCNN class loss: 0.13752 FastRCNN total loss: 0.25428 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.18623 RPN box loss: 0.00783 RPN score loss: 0.00147 RPN total loss: 0.0093 Total loss: 1.01858 timestamp: 1655057058.0648215 iteration: 61335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06035 FastRCNN class loss: 0.03205 FastRCNN total loss: 0.09241 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.10142 RPN box loss: 0.00661 RPN score loss: 0.00156 RPN total loss: 0.00817 Total loss: 0.77076 timestamp: 1655057061.3487682 iteration: 61340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.15775 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.11402 RPN box loss: 0.01625 RPN score loss: 0.00358 RPN total loss: 0.01983 Total loss: 0.86037 timestamp: 1655057064.5454736 iteration: 61345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12048 FastRCNN class loss: 0.10545 FastRCNN total loss: 0.22593 L1 loss: 0.0000e+00 L2 loss: 0.56877 Learning rate: 0.0004 Mask loss: 0.22577 RPN box loss: 0.01443 RPN score loss: 0.00594 RPN total loss: 0.02037 Total loss: 1.04084 timestamp: 1655057067.812811 iteration: 61350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07343 FastRCNN class loss: 0.05085 FastRCNN total loss: 0.12429 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.10195 RPN box loss: 0.01145 RPN score loss: 0.00604 RPN total loss: 0.01749 Total loss: 0.8125 timestamp: 1655057071.0871189 iteration: 61355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12816 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.1976 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.12502 RPN box loss: 0.0044 RPN score loss: 0.00644 RPN total loss: 0.01085 Total loss: 0.90223 timestamp: 1655057074.3360796 iteration: 61360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.15403 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.10355 RPN box loss: 0.0052 RPN score loss: 0.00178 RPN total loss: 0.00698 Total loss: 0.83333 timestamp: 1655057077.70904 iteration: 61365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04342 FastRCNN class loss: 0.02115 FastRCNN total loss: 0.06457 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.0956 RPN box loss: 0.00538 RPN score loss: 0.00273 RPN total loss: 0.00811 Total loss: 0.73704 timestamp: 1655057081.0178142 iteration: 61370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09961 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.12818 RPN box loss: 0.0083 RPN score loss: 0.00173 RPN total loss: 0.01004 Total loss: 0.87983 timestamp: 1655057084.258726 iteration: 61375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08072 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.14767 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.14353 RPN box loss: 0.0099 RPN score loss: 0.00603 RPN total loss: 0.01593 Total loss: 0.87589 timestamp: 1655057087.444552 iteration: 61380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10353 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.16619 L1 loss: 0.0000e+00 L2 loss: 0.56876 Learning rate: 0.0004 Mask loss: 0.12832 RPN box loss: 0.01344 RPN score loss: 0.0076 RPN total loss: 0.02103 Total loss: 0.88431 timestamp: 1655057090.74703 iteration: 61385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11712 FastRCNN class loss: 0.05015 FastRCNN total loss: 0.16727 L1 loss: 0.0000e+00 L2 loss: 0.56875 Learning rate: 0.0004 Mask loss: 0.10595 RPN box loss: 0.00939 RPN score loss: 0.0015 RPN total loss: 0.01089 Total loss: 0.85286 timestamp: 1655057093.9898083 iteration: 61390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06925 FastRCNN class loss: 0.04987 FastRCNN total loss: 0.11912 L1 loss: 0.0000e+00 L2 loss: 0.56875 Learning rate: 0.0004 Mask loss: 0.11041 RPN box loss: 0.02303 RPN score loss: 0.00258 RPN total loss: 0.02561 Total loss: 0.82388 timestamp: 1655057097.2466378 iteration: 61395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.14189 L1 loss: 0.0000e+00 L2 loss: 0.56875 Learning rate: 0.0004 Mask loss: 0.12987 RPN box loss: 0.00563 RPN score loss: 0.00107 RPN total loss: 0.0067 Total loss: 0.84721 timestamp: 1655057100.5189197 iteration: 61400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.16851 L1 loss: 0.0000e+00 L2 loss: 0.56875 Learning rate: 0.0004 Mask loss: 0.11943 RPN box loss: 0.06017 RPN score loss: 0.0023 RPN total loss: 0.06248 Total loss: 0.91916 timestamp: 1655057103.8406181 iteration: 61405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12193 FastRCNN class loss: 0.09309 FastRCNN total loss: 0.21501 L1 loss: 0.0000e+00 L2 loss: 0.56875 Learning rate: 0.0004 Mask loss: 0.19603 RPN box loss: 0.04821 RPN score loss: 0.01106 RPN total loss: 0.05927 Total loss: 1.03906 timestamp: 1655057107.05947 iteration: 61410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11164 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.19238 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.13579 RPN box loss: 0.0069 RPN score loss: 0.00944 RPN total loss: 0.01633 Total loss: 0.91325 timestamp: 1655057110.3129447 iteration: 61415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12176 FastRCNN class loss: 0.12619 FastRCNN total loss: 0.24795 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.17431 RPN box loss: 0.02592 RPN score loss: 0.00792 RPN total loss: 0.03383 Total loss: 1.02484 timestamp: 1655057113.5822027 iteration: 61420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09288 FastRCNN class loss: 0.05352 FastRCNN total loss: 0.1464 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.10249 RPN box loss: 0.0137 RPN score loss: 0.00073 RPN total loss: 0.01442 Total loss: 0.83205 timestamp: 1655057116.8803396 iteration: 61425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12549 FastRCNN class loss: 0.09217 FastRCNN total loss: 0.21767 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.17118 RPN box loss: 0.04679 RPN score loss: 0.01873 RPN total loss: 0.06553 Total loss: 1.02311 timestamp: 1655057120.1623728 iteration: 61430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.08204 FastRCNN total loss: 0.18297 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.16983 RPN box loss: 0.00867 RPN score loss: 0.00714 RPN total loss: 0.01582 Total loss: 0.93736 timestamp: 1655057123.438692 iteration: 61435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12365 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.19782 L1 loss: 0.0000e+00 L2 loss: 0.56874 Learning rate: 0.0004 Mask loss: 0.12758 RPN box loss: 0.01463 RPN score loss: 0.00853 RPN total loss: 0.02315 Total loss: 0.91729 timestamp: 1655057126.7054226 iteration: 61440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08147 FastRCNN class loss: 0.06093 FastRCNN total loss: 0.1424 L1 loss: 0.0000e+00 L2 loss: 0.56873 Learning rate: 0.0004 Mask loss: 0.12027 RPN box loss: 0.00856 RPN score loss: 0.00306 RPN total loss: 0.01162 Total loss: 0.84303 timestamp: 1655057129.9488678 iteration: 61445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1037 FastRCNN class loss: 0.06936 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.56873 Learning rate: 0.0004 Mask loss: 0.14525 RPN box loss: 0.01063 RPN score loss: 0.00307 RPN total loss: 0.0137 Total loss: 0.90074 timestamp: 1655057133.293587 iteration: 61450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08116 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.15756 L1 loss: 0.0000e+00 L2 loss: 0.56873 Learning rate: 0.0004 Mask loss: 0.17801 RPN box loss: 0.00826 RPN score loss: 0.00531 RPN total loss: 0.01357 Total loss: 0.91787 timestamp: 1655057136.5987482 iteration: 61455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11553 FastRCNN class loss: 0.07739 FastRCNN total loss: 0.19292 L1 loss: 0.0000e+00 L2 loss: 0.56873 Learning rate: 0.0004 Mask loss: 0.16953 RPN box loss: 0.01334 RPN score loss: 0.01172 RPN total loss: 0.02507 Total loss: 0.95624 timestamp: 1655057139.9512684 iteration: 61460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08791 FastRCNN class loss: 0.07068 FastRCNN total loss: 0.15859 L1 loss: 0.0000e+00 L2 loss: 0.56873 Learning rate: 0.0004 Mask loss: 0.13866 RPN box loss: 0.02585 RPN score loss: 0.00373 RPN total loss: 0.02957 Total loss: 0.89555 timestamp: 1655057143.21571 iteration: 61465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08489 FastRCNN class loss: 0.09976 FastRCNN total loss: 0.18465 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.15413 RPN box loss: 0.01371 RPN score loss: 0.00384 RPN total loss: 0.01755 Total loss: 0.92505 timestamp: 1655057146.4933445 iteration: 61470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09422 FastRCNN class loss: 0.12121 FastRCNN total loss: 0.21543 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.20705 RPN box loss: 0.01869 RPN score loss: 0.00838 RPN total loss: 0.02707 Total loss: 1.01827 timestamp: 1655057149.7639706 iteration: 61475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13595 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.20818 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.15469 RPN box loss: 0.01493 RPN score loss: 0.00612 RPN total loss: 0.02105 Total loss: 0.95264 timestamp: 1655057153.010068 iteration: 61480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06511 FastRCNN class loss: 0.07667 FastRCNN total loss: 0.14178 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.10007 RPN box loss: 0.02205 RPN score loss: 0.00781 RPN total loss: 0.02986 Total loss: 0.84043 timestamp: 1655057156.3012354 iteration: 61485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07276 FastRCNN class loss: 0.08247 FastRCNN total loss: 0.15523 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.16629 RPN box loss: 0.03056 RPN score loss: 0.01079 RPN total loss: 0.04135 Total loss: 0.93159 timestamp: 1655057159.5258925 iteration: 61490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05814 FastRCNN class loss: 0.06043 FastRCNN total loss: 0.11858 L1 loss: 0.0000e+00 L2 loss: 0.56872 Learning rate: 0.0004 Mask loss: 0.08259 RPN box loss: 0.01026 RPN score loss: 0.00107 RPN total loss: 0.01133 Total loss: 0.78122 timestamp: 1655057162.7495668 iteration: 61495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11162 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.18272 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.13104 RPN box loss: 0.00714 RPN score loss: 0.00763 RPN total loss: 0.01477 Total loss: 0.89725 timestamp: 1655057165.9180927 iteration: 61500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1296 FastRCNN class loss: 0.11815 FastRCNN total loss: 0.24775 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.23389 RPN box loss: 0.03492 RPN score loss: 0.01329 RPN total loss: 0.0482 Total loss: 1.09856 timestamp: 1655057169.1705935 iteration: 61505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0614 FastRCNN class loss: 0.0382 FastRCNN total loss: 0.0996 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.11241 RPN box loss: 0.02308 RPN score loss: 0.00102 RPN total loss: 0.02411 Total loss: 0.80483 timestamp: 1655057172.4485493 iteration: 61510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06086 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.12043 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.17297 RPN box loss: 0.01337 RPN score loss: 0.00615 RPN total loss: 0.01952 Total loss: 0.88163 timestamp: 1655057175.7569757 iteration: 61515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09487 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.15983 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.10078 RPN box loss: 0.00715 RPN score loss: 0.00085 RPN total loss: 0.008 Total loss: 0.83732 timestamp: 1655057179.0557115 iteration: 61520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09667 FastRCNN class loss: 0.08709 FastRCNN total loss: 0.18376 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.15129 RPN box loss: 0.01059 RPN score loss: 0.00614 RPN total loss: 0.01673 Total loss: 0.92049 timestamp: 1655057182.3456159 iteration: 61525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05392 FastRCNN class loss: 0.04404 FastRCNN total loss: 0.09796 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.1423 RPN box loss: 0.00758 RPN score loss: 0.00532 RPN total loss: 0.0129 Total loss: 0.82186 timestamp: 1655057185.687741 iteration: 61530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.13615 L1 loss: 0.0000e+00 L2 loss: 0.56871 Learning rate: 0.0004 Mask loss: 0.13139 RPN box loss: 0.01416 RPN score loss: 0.00791 RPN total loss: 0.02206 Total loss: 0.85831 timestamp: 1655057188.9861796 iteration: 61535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.16129 L1 loss: 0.0000e+00 L2 loss: 0.5687 Learning rate: 0.0004 Mask loss: 0.16113 RPN box loss: 0.01529 RPN score loss: 0.00371 RPN total loss: 0.019 Total loss: 0.91012 timestamp: 1655057192.2716293 iteration: 61540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08863 FastRCNN class loss: 0.05131 FastRCNN total loss: 0.13994 L1 loss: 0.0000e+00 L2 loss: 0.5687 Learning rate: 0.0004 Mask loss: 0.16683 RPN box loss: 0.00433 RPN score loss: 0.00169 RPN total loss: 0.00602 Total loss: 0.8815 timestamp: 1655057195.5151467 iteration: 61545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07941 FastRCNN class loss: 0.05032 FastRCNN total loss: 0.12973 L1 loss: 0.0000e+00 L2 loss: 0.5687 Learning rate: 0.0004 Mask loss: 0.11381 RPN box loss: 0.01066 RPN score loss: 0.00187 RPN total loss: 0.01253 Total loss: 0.82477 timestamp: 1655057198.7758512 iteration: 61550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0361 FastRCNN class loss: 0.02925 FastRCNN total loss: 0.06536 L1 loss: 0.0000e+00 L2 loss: 0.5687 Learning rate: 0.0004 Mask loss: 0.09753 RPN box loss: 0.0138 RPN score loss: 0.00131 RPN total loss: 0.01511 Total loss: 0.7467 timestamp: 1655057202.037779 iteration: 61555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18704 FastRCNN class loss: 0.07283 FastRCNN total loss: 0.25988 L1 loss: 0.0000e+00 L2 loss: 0.56869 Learning rate: 0.0004 Mask loss: 0.10565 RPN box loss: 0.00865 RPN score loss: 0.00311 RPN total loss: 0.01176 Total loss: 0.94599 timestamp: 1655057205.3527353 iteration: 61560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10715 FastRCNN class loss: 0.05209 FastRCNN total loss: 0.15924 L1 loss: 0.0000e+00 L2 loss: 0.56869 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.01291 RPN score loss: 0.00565 RPN total loss: 0.01856 Total loss: 0.86453 timestamp: 1655057208.6677978 iteration: 61565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08416 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.16624 L1 loss: 0.0000e+00 L2 loss: 0.56869 Learning rate: 0.0004 Mask loss: 0.12121 RPN box loss: 0.0146 RPN score loss: 0.00707 RPN total loss: 0.02168 Total loss: 0.87781 timestamp: 1655057211.8528926 iteration: 61570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08575 FastRCNN class loss: 0.06777 FastRCNN total loss: 0.15353 L1 loss: 0.0000e+00 L2 loss: 0.56869 Learning rate: 0.0004 Mask loss: 0.16509 RPN box loss: 0.02152 RPN score loss: 0.00649 RPN total loss: 0.02801 Total loss: 0.91532 timestamp: 1655057215.083786 iteration: 61575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13079 FastRCNN class loss: 0.10719 FastRCNN total loss: 0.23798 L1 loss: 0.0000e+00 L2 loss: 0.56869 Learning rate: 0.0004 Mask loss: 0.1622 RPN box loss: 0.03253 RPN score loss: 0.00845 RPN total loss: 0.04098 Total loss: 1.00984 timestamp: 1655057218.3574402 iteration: 61580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07574 FastRCNN class loss: 0.04901 FastRCNN total loss: 0.12475 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.13384 RPN box loss: 0.01103 RPN score loss: 0.00565 RPN total loss: 0.01668 Total loss: 0.84395 timestamp: 1655057221.6395736 iteration: 61585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08632 FastRCNN class loss: 0.05627 FastRCNN total loss: 0.14259 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.11641 RPN box loss: 0.00641 RPN score loss: 0.00431 RPN total loss: 0.01072 Total loss: 0.8384 timestamp: 1655057224.9245389 iteration: 61590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09806 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.16047 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.18401 RPN box loss: 0.04394 RPN score loss: 0.00723 RPN total loss: 0.05117 Total loss: 0.96433 timestamp: 1655057228.1926398 iteration: 61595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04974 FastRCNN class loss: 0.04905 FastRCNN total loss: 0.09879 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.16688 RPN box loss: 0.01061 RPN score loss: 0.00474 RPN total loss: 0.01534 Total loss: 0.84969 timestamp: 1655057231.4420726 iteration: 61600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12618 FastRCNN class loss: 0.10552 FastRCNN total loss: 0.2317 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.17002 RPN box loss: 0.01262 RPN score loss: 0.0017 RPN total loss: 0.01432 Total loss: 0.98473 timestamp: 1655057234.7008848 iteration: 61605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.24031 FastRCNN class loss: 0.12965 FastRCNN total loss: 0.36995 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.18786 RPN box loss: 0.01773 RPN score loss: 0.00631 RPN total loss: 0.02403 Total loss: 1.15052 timestamp: 1655057237.9034786 iteration: 61610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12959 FastRCNN class loss: 0.08712 FastRCNN total loss: 0.21671 L1 loss: 0.0000e+00 L2 loss: 0.56868 Learning rate: 0.0004 Mask loss: 0.15143 RPN box loss: 0.01714 RPN score loss: 0.00472 RPN total loss: 0.02186 Total loss: 0.95868 timestamp: 1655057241.214907 iteration: 61615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07299 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.12435 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.13008 RPN box loss: 0.0204 RPN score loss: 0.00204 RPN total loss: 0.02244 Total loss: 0.84555 timestamp: 1655057244.5055482 iteration: 61620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11279 FastRCNN class loss: 0.08953 FastRCNN total loss: 0.20232 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.12161 RPN box loss: 0.00916 RPN score loss: 0.00488 RPN total loss: 0.01404 Total loss: 0.90665 timestamp: 1655057247.8242712 iteration: 61625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10156 FastRCNN class loss: 0.09864 FastRCNN total loss: 0.2002 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.16895 RPN box loss: 0.08151 RPN score loss: 0.01269 RPN total loss: 0.09419 Total loss: 1.03202 timestamp: 1655057251.0580137 iteration: 61630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07395 FastRCNN class loss: 0.04684 FastRCNN total loss: 0.12078 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.12954 RPN box loss: 0.01409 RPN score loss: 0.00452 RPN total loss: 0.01861 Total loss: 0.8376 timestamp: 1655057254.3172958 iteration: 61635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08413 FastRCNN class loss: 0.1288 FastRCNN total loss: 0.21293 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.2305 RPN box loss: 0.03693 RPN score loss: 0.07208 RPN total loss: 0.109 Total loss: 1.1211 timestamp: 1655057257.570214 iteration: 61640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10123 FastRCNN class loss: 0.08825 FastRCNN total loss: 0.18948 L1 loss: 0.0000e+00 L2 loss: 0.56867 Learning rate: 0.0004 Mask loss: 0.17446 RPN box loss: 0.02135 RPN score loss: 0.00611 RPN total loss: 0.02745 Total loss: 0.96005 timestamp: 1655057260.813362 iteration: 61645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12788 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.19499 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.14903 RPN box loss: 0.01328 RPN score loss: 0.0069 RPN total loss: 0.02019 Total loss: 0.93287 timestamp: 1655057264.0740576 iteration: 61650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10544 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.16961 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.16669 RPN box loss: 0.01141 RPN score loss: 0.00854 RPN total loss: 0.01994 Total loss: 0.92491 timestamp: 1655057267.3875892 iteration: 61655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13507 FastRCNN class loss: 0.06288 FastRCNN total loss: 0.19795 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.11142 RPN box loss: 0.01519 RPN score loss: 0.0042 RPN total loss: 0.0194 Total loss: 0.89742 timestamp: 1655057270.613616 iteration: 61660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10474 FastRCNN class loss: 0.08603 FastRCNN total loss: 0.19077 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.16082 RPN box loss: 0.01193 RPN score loss: 0.01094 RPN total loss: 0.02287 Total loss: 0.94311 timestamp: 1655057273.8492308 iteration: 61665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08483 FastRCNN class loss: 0.05155 FastRCNN total loss: 0.13638 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.12599 RPN box loss: 0.00409 RPN score loss: 0.00259 RPN total loss: 0.00667 Total loss: 0.8377 timestamp: 1655057277.0510128 iteration: 61670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04851 FastRCNN class loss: 0.04788 FastRCNN total loss: 0.09639 L1 loss: 0.0000e+00 L2 loss: 0.56866 Learning rate: 0.0004 Mask loss: 0.115 RPN box loss: 0.01408 RPN score loss: 0.00546 RPN total loss: 0.01954 Total loss: 0.79959 timestamp: 1655057280.2091594 iteration: 61675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10706 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.17902 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.11025 RPN box loss: 0.03622 RPN score loss: 0.00233 RPN total loss: 0.03855 Total loss: 0.89647 timestamp: 1655057283.4519951 iteration: 61680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08168 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.13279 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.09617 RPN box loss: 0.02141 RPN score loss: 0.00161 RPN total loss: 0.02302 Total loss: 0.82063 timestamp: 1655057286.706534 iteration: 61685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.09718 FastRCNN total loss: 0.17644 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.16732 RPN box loss: 0.0094 RPN score loss: 0.00715 RPN total loss: 0.01655 Total loss: 0.92896 timestamp: 1655057289.9503858 iteration: 61690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07955 FastRCNN class loss: 0.08259 FastRCNN total loss: 0.16214 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.16412 RPN box loss: 0.01863 RPN score loss: 0.00711 RPN total loss: 0.02575 Total loss: 0.92065 timestamp: 1655057293.1851418 iteration: 61695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08575 FastRCNN class loss: 0.08811 FastRCNN total loss: 0.17386 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.12034 RPN box loss: 0.0085 RPN score loss: 0.00398 RPN total loss: 0.01248 Total loss: 0.87534 timestamp: 1655057296.448529 iteration: 61700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10362 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.17664 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.13362 RPN box loss: 0.01414 RPN score loss: 0.00179 RPN total loss: 0.01593 Total loss: 0.89483 timestamp: 1655057299.623014 iteration: 61705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14195 FastRCNN class loss: 0.12142 FastRCNN total loss: 0.26336 L1 loss: 0.0000e+00 L2 loss: 0.56865 Learning rate: 0.0004 Mask loss: 0.19074 RPN box loss: 0.00862 RPN score loss: 0.01543 RPN total loss: 0.02405 Total loss: 1.0468 timestamp: 1655057302.9842 iteration: 61710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.14228 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.12416 RPN box loss: 0.02561 RPN score loss: 0.00996 RPN total loss: 0.03557 Total loss: 0.87067 timestamp: 1655057306.2772636 iteration: 61715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.07568 FastRCNN total loss: 0.17139 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.15363 RPN box loss: 0.00923 RPN score loss: 0.00356 RPN total loss: 0.01278 Total loss: 0.90645 timestamp: 1655057309.6087449 iteration: 61720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08473 FastRCNN class loss: 0.04398 FastRCNN total loss: 0.12871 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.10677 RPN box loss: 0.01508 RPN score loss: 0.00512 RPN total loss: 0.0202 Total loss: 0.82433 timestamp: 1655057312.8546486 iteration: 61725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14409 FastRCNN class loss: 0.08632 FastRCNN total loss: 0.23041 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.21436 RPN box loss: 0.02202 RPN score loss: 0.01009 RPN total loss: 0.03211 Total loss: 1.04552 timestamp: 1655057316.070099 iteration: 61730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05063 FastRCNN class loss: 0.03694 FastRCNN total loss: 0.08758 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.1497 RPN box loss: 0.01841 RPN score loss: 0.00127 RPN total loss: 0.01969 Total loss: 0.8256 timestamp: 1655057319.3368566 iteration: 61735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09864 FastRCNN class loss: 0.09445 FastRCNN total loss: 0.19309 L1 loss: 0.0000e+00 L2 loss: 0.56864 Learning rate: 0.0004 Mask loss: 0.12276 RPN box loss: 0.02466 RPN score loss: 0.0117 RPN total loss: 0.03637 Total loss: 0.92085 timestamp: 1655057322.7105935 iteration: 61740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12948 FastRCNN class loss: 0.0652 FastRCNN total loss: 0.19468 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.1504 RPN box loss: 0.0161 RPN score loss: 0.0049 RPN total loss: 0.021 Total loss: 0.93472 timestamp: 1655057325.9630182 iteration: 61745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08993 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.15212 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.11846 RPN box loss: 0.00875 RPN score loss: 0.00244 RPN total loss: 0.01119 Total loss: 0.8504 timestamp: 1655057329.1715477 iteration: 61750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11052 FastRCNN class loss: 0.06258 FastRCNN total loss: 0.1731 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.12271 RPN box loss: 0.00567 RPN score loss: 0.00215 RPN total loss: 0.00782 Total loss: 0.87227 timestamp: 1655057332.4260445 iteration: 61755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04717 FastRCNN class loss: 0.04548 FastRCNN total loss: 0.09265 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.11018 RPN box loss: 0.02395 RPN score loss: 0.00348 RPN total loss: 0.02742 Total loss: 0.79888 timestamp: 1655057335.684151 iteration: 61760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11687 FastRCNN class loss: 0.11054 FastRCNN total loss: 0.22741 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.11027 RPN box loss: 0.02352 RPN score loss: 0.00708 RPN total loss: 0.0306 Total loss: 0.9369 timestamp: 1655057338.9322257 iteration: 61765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09243 FastRCNN class loss: 0.08792 FastRCNN total loss: 0.18036 L1 loss: 0.0000e+00 L2 loss: 0.56863 Learning rate: 0.0004 Mask loss: 0.20823 RPN box loss: 0.01724 RPN score loss: 0.00421 RPN total loss: 0.02145 Total loss: 0.97866 timestamp: 1655057342.2124352 iteration: 61770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14493 FastRCNN class loss: 0.07551 FastRCNN total loss: 0.22045 L1 loss: 0.0000e+00 L2 loss: 0.56862 Learning rate: 0.0004 Mask loss: 0.18257 RPN box loss: 0.01092 RPN score loss: 0.01291 RPN total loss: 0.02384 Total loss: 0.99548 timestamp: 1655057345.5170977 iteration: 61775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.05358 FastRCNN total loss: 0.13704 L1 loss: 0.0000e+00 L2 loss: 0.56862 Learning rate: 0.0004 Mask loss: 0.15239 RPN box loss: 0.01723 RPN score loss: 0.00275 RPN total loss: 0.01997 Total loss: 0.87803 timestamp: 1655057348.784251 iteration: 61780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12319 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.20312 L1 loss: 0.0000e+00 L2 loss: 0.56862 Learning rate: 0.0004 Mask loss: 0.14397 RPN box loss: 0.01847 RPN score loss: 0.00488 RPN total loss: 0.02336 Total loss: 0.93907 timestamp: 1655057352.073308 iteration: 61785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.04527 FastRCNN total loss: 0.1303 L1 loss: 0.0000e+00 L2 loss: 0.56862 Learning rate: 0.0004 Mask loss: 0.12367 RPN box loss: 0.00414 RPN score loss: 0.00298 RPN total loss: 0.00712 Total loss: 0.82972 timestamp: 1655057355.4407797 iteration: 61790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14283 FastRCNN class loss: 0.08015 FastRCNN total loss: 0.22298 L1 loss: 0.0000e+00 L2 loss: 0.56862 Learning rate: 0.0004 Mask loss: 0.17021 RPN box loss: 0.03168 RPN score loss: 0.00658 RPN total loss: 0.03826 Total loss: 1.00006 timestamp: 1655057358.72065 iteration: 61795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05545 FastRCNN class loss: 0.04692 FastRCNN total loss: 0.10237 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.14563 RPN box loss: 0.02061 RPN score loss: 0.00398 RPN total loss: 0.02459 Total loss: 0.8412 timestamp: 1655057361.976882 iteration: 61800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11477 FastRCNN class loss: 0.07735 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.1828 RPN box loss: 0.01932 RPN score loss: 0.0074 RPN total loss: 0.02672 Total loss: 0.97026 timestamp: 1655057365.3168519 iteration: 61805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05935 FastRCNN class loss: 0.05308 FastRCNN total loss: 0.11244 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.13708 RPN box loss: 0.00745 RPN score loss: 0.00081 RPN total loss: 0.00826 Total loss: 0.82639 timestamp: 1655057368.6036043 iteration: 61810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10626 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.15865 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.09972 RPN box loss: 0.00541 RPN score loss: 0.00442 RPN total loss: 0.00983 Total loss: 0.83681 timestamp: 1655057371.880822 iteration: 61815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11323 FastRCNN class loss: 0.06739 FastRCNN total loss: 0.18062 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.14673 RPN box loss: 0.01232 RPN score loss: 0.00692 RPN total loss: 0.01925 Total loss: 0.9152 timestamp: 1655057375.1656528 iteration: 61820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.08451 FastRCNN total loss: 0.19401 L1 loss: 0.0000e+00 L2 loss: 0.56861 Learning rate: 0.0004 Mask loss: 0.1318 RPN box loss: 0.01337 RPN score loss: 0.00313 RPN total loss: 0.0165 Total loss: 0.91091 timestamp: 1655057378.5029292 iteration: 61825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11261 FastRCNN class loss: 0.08838 FastRCNN total loss: 0.201 L1 loss: 0.0000e+00 L2 loss: 0.5686 Learning rate: 0.0004 Mask loss: 0.20221 RPN box loss: 0.01616 RPN score loss: 0.00579 RPN total loss: 0.02195 Total loss: 0.99376 timestamp: 1655057381.8145285 iteration: 61830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08893 FastRCNN class loss: 0.04598 FastRCNN total loss: 0.13491 L1 loss: 0.0000e+00 L2 loss: 0.5686 Learning rate: 0.0004 Mask loss: 0.11995 RPN box loss: 0.01742 RPN score loss: 0.00484 RPN total loss: 0.02226 Total loss: 0.84572 timestamp: 1655057385.0827737 iteration: 61835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17329 FastRCNN class loss: 0.07942 FastRCNN total loss: 0.25271 L1 loss: 0.0000e+00 L2 loss: 0.5686 Learning rate: 0.0004 Mask loss: 0.111 RPN box loss: 0.009 RPN score loss: 0.00569 RPN total loss: 0.01469 Total loss: 0.947 timestamp: 1655057388.3551695 iteration: 61840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08094 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.13279 L1 loss: 0.0000e+00 L2 loss: 0.5686 Learning rate: 0.0004 Mask loss: 0.09751 RPN box loss: 0.0051 RPN score loss: 0.00455 RPN total loss: 0.00965 Total loss: 0.80854 timestamp: 1655057391.5867321 iteration: 61845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04674 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.12277 L1 loss: 0.0000e+00 L2 loss: 0.5686 Learning rate: 0.0004 Mask loss: 0.09263 RPN box loss: 0.00552 RPN score loss: 0.00142 RPN total loss: 0.00694 Total loss: 0.79094 timestamp: 1655057394.8286653 iteration: 61850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07984 FastRCNN class loss: 0.06913 FastRCNN total loss: 0.14898 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.12975 RPN box loss: 0.06234 RPN score loss: 0.00675 RPN total loss: 0.06909 Total loss: 0.91642 timestamp: 1655057398.0696783 iteration: 61855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.14845 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.12573 RPN box loss: 0.01101 RPN score loss: 0.00436 RPN total loss: 0.01537 Total loss: 0.85815 timestamp: 1655057401.3403141 iteration: 61860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10582 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.16577 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.13491 RPN box loss: 0.01461 RPN score loss: 0.00421 RPN total loss: 0.01881 Total loss: 0.88809 timestamp: 1655057404.5332437 iteration: 61865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.09671 FastRCNN total loss: 0.18988 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.14881 RPN box loss: 0.01082 RPN score loss: 0.00803 RPN total loss: 0.01886 Total loss: 0.92614 timestamp: 1655057407.7227604 iteration: 61870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10633 FastRCNN class loss: 0.06876 FastRCNN total loss: 0.17509 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.17275 RPN box loss: 0.00609 RPN score loss: 0.00647 RPN total loss: 0.01256 Total loss: 0.92899 timestamp: 1655057410.9165425 iteration: 61875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08557 FastRCNN class loss: 0.04263 FastRCNN total loss: 0.1282 L1 loss: 0.0000e+00 L2 loss: 0.56859 Learning rate: 0.0004 Mask loss: 0.13055 RPN box loss: 0.01116 RPN score loss: 0.00465 RPN total loss: 0.01582 Total loss: 0.84315 timestamp: 1655057414.2102182 iteration: 61880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05183 FastRCNN class loss: 0.05437 FastRCNN total loss: 0.1062 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.17556 RPN box loss: 0.01145 RPN score loss: 0.00313 RPN total loss: 0.01458 Total loss: 0.86492 timestamp: 1655057417.4686446 iteration: 61885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06953 FastRCNN class loss: 0.05119 FastRCNN total loss: 0.12072 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.19247 RPN box loss: 0.01218 RPN score loss: 0.00181 RPN total loss: 0.01399 Total loss: 0.89576 timestamp: 1655057420.7397194 iteration: 61890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06367 FastRCNN class loss: 0.06973 FastRCNN total loss: 0.1334 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.14258 RPN box loss: 0.01163 RPN score loss: 0.00118 RPN total loss: 0.01281 Total loss: 0.85737 timestamp: 1655057424.0584817 iteration: 61895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.17815 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.16739 RPN box loss: 0.01652 RPN score loss: 0.00215 RPN total loss: 0.01867 Total loss: 0.93279 timestamp: 1655057427.382849 iteration: 61900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08932 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.14833 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.12253 RPN box loss: 0.00885 RPN score loss: 0.01507 RPN total loss: 0.02392 Total loss: 0.86335 timestamp: 1655057430.668452 iteration: 61905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07977 FastRCNN class loss: 0.0551 FastRCNN total loss: 0.13487 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.12488 RPN box loss: 0.01606 RPN score loss: 0.00809 RPN total loss: 0.02415 Total loss: 0.85247 timestamp: 1655057433.9065247 iteration: 61910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10935 FastRCNN class loss: 0.10195 FastRCNN total loss: 0.2113 L1 loss: 0.0000e+00 L2 loss: 0.56858 Learning rate: 0.0004 Mask loss: 0.23341 RPN box loss: 0.01849 RPN score loss: 0.00464 RPN total loss: 0.02314 Total loss: 1.03643 timestamp: 1655057437.2040074 iteration: 61915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.04322 FastRCNN total loss: 0.11302 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.10831 RPN box loss: 0.02354 RPN score loss: 0.00425 RPN total loss: 0.0278 Total loss: 0.8177 timestamp: 1655057440.5778005 iteration: 61920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10183 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.17276 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.12209 RPN box loss: 0.00644 RPN score loss: 0.00524 RPN total loss: 0.01167 Total loss: 0.87509 timestamp: 1655057443.7916074 iteration: 61925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13431 FastRCNN class loss: 0.06706 FastRCNN total loss: 0.20137 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.17321 RPN box loss: 0.01799 RPN score loss: 0.00551 RPN total loss: 0.02351 Total loss: 0.96666 timestamp: 1655057447.023826 iteration: 61930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10565 FastRCNN class loss: 0.08238 FastRCNN total loss: 0.18803 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.01328 RPN score loss: 0.00902 RPN total loss: 0.0223 Total loss: 0.92366 timestamp: 1655057450.29643 iteration: 61935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10963 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.20238 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.1862 RPN box loss: 0.03107 RPN score loss: 0.0238 RPN total loss: 0.05487 Total loss: 1.01202 timestamp: 1655057453.5843492 iteration: 61940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07781 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.56857 Learning rate: 0.0004 Mask loss: 0.16519 RPN box loss: 0.00857 RPN score loss: 0.00409 RPN total loss: 0.01266 Total loss: 0.89404 timestamp: 1655057456.7844849 iteration: 61945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06133 FastRCNN class loss: 0.05555 FastRCNN total loss: 0.11688 L1 loss: 0.0000e+00 L2 loss: 0.56856 Learning rate: 0.0004 Mask loss: 0.08616 RPN box loss: 0.01247 RPN score loss: 0.00061 RPN total loss: 0.01309 Total loss: 0.78469 timestamp: 1655057460.0711095 iteration: 61950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06658 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.11375 L1 loss: 0.0000e+00 L2 loss: 0.56856 Learning rate: 0.0004 Mask loss: 0.14113 RPN box loss: 0.02159 RPN score loss: 0.00864 RPN total loss: 0.03024 Total loss: 0.85369 timestamp: 1655057463.3821726 iteration: 61955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08915 FastRCNN class loss: 0.06591 FastRCNN total loss: 0.15507 L1 loss: 0.0000e+00 L2 loss: 0.56856 Learning rate: 0.0004 Mask loss: 0.12613 RPN box loss: 0.00757 RPN score loss: 0.00463 RPN total loss: 0.0122 Total loss: 0.86195 timestamp: 1655057466.6859162 iteration: 61960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08463 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.13314 L1 loss: 0.0000e+00 L2 loss: 0.56856 Learning rate: 0.0004 Mask loss: 0.12161 RPN box loss: 0.02886 RPN score loss: 0.00618 RPN total loss: 0.03503 Total loss: 0.85834 timestamp: 1655057470.0080605 iteration: 61965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07418 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.15198 L1 loss: 0.0000e+00 L2 loss: 0.56856 Learning rate: 0.0004 Mask loss: 0.13466 RPN box loss: 0.01289 RPN score loss: 0.00888 RPN total loss: 0.02177 Total loss: 0.87696 timestamp: 1655057473.2968469 iteration: 61970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08785 FastRCNN class loss: 0.06404 FastRCNN total loss: 0.15189 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.11812 RPN box loss: 0.00898 RPN score loss: 0.00163 RPN total loss: 0.01062 Total loss: 0.84919 timestamp: 1655057476.573604 iteration: 61975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08054 FastRCNN class loss: 0.10781 FastRCNN total loss: 0.18835 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.19458 RPN box loss: 0.01377 RPN score loss: 0.01483 RPN total loss: 0.0286 Total loss: 0.98008 timestamp: 1655057479.8345249 iteration: 61980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08496 FastRCNN class loss: 0.06881 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.13462 RPN box loss: 0.01131 RPN score loss: 0.00731 RPN total loss: 0.01862 Total loss: 0.87557 timestamp: 1655057483.0905983 iteration: 61985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1473 FastRCNN class loss: 0.08612 FastRCNN total loss: 0.23342 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.16347 RPN box loss: 0.01662 RPN score loss: 0.00983 RPN total loss: 0.02645 Total loss: 0.99189 timestamp: 1655057486.3389578 iteration: 61990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0822 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.16154 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.23282 RPN box loss: 0.01983 RPN score loss: 0.00775 RPN total loss: 0.02758 Total loss: 0.99049 timestamp: 1655057489.5702846 iteration: 61995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06695 FastRCNN class loss: 0.04635 FastRCNN total loss: 0.1133 L1 loss: 0.0000e+00 L2 loss: 0.56855 Learning rate: 0.0004 Mask loss: 0.13589 RPN box loss: 0.02324 RPN score loss: 0.00449 RPN total loss: 0.02772 Total loss: 0.84545 timestamp: 1655057492.889291 iteration: 62000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10583 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.18582 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.13025 RPN box loss: 0.01007 RPN score loss: 0.00333 RPN total loss: 0.0134 Total loss: 0.89802 timestamp: 1655057496.2634118 iteration: 62005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08028 FastRCNN class loss: 0.04267 FastRCNN total loss: 0.12295 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.1772 RPN box loss: 0.00445 RPN score loss: 0.00393 RPN total loss: 0.00838 Total loss: 0.87707 timestamp: 1655057499.6067939 iteration: 62010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.08551 FastRCNN total loss: 0.22076 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.23279 RPN box loss: 0.01895 RPN score loss: 0.00404 RPN total loss: 0.02299 Total loss: 1.04509 timestamp: 1655057502.8859138 iteration: 62015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11622 FastRCNN class loss: 0.08207 FastRCNN total loss: 0.19829 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.14771 RPN box loss: 0.01779 RPN score loss: 0.01018 RPN total loss: 0.02797 Total loss: 0.94252 timestamp: 1655057506.1339853 iteration: 62020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.08973 FastRCNN total loss: 0.19925 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.16337 RPN box loss: 0.02437 RPN score loss: 0.00984 RPN total loss: 0.03421 Total loss: 0.96536 timestamp: 1655057509.3543465 iteration: 62025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07952 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.16223 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.15135 RPN box loss: 0.02456 RPN score loss: 0.00732 RPN total loss: 0.03188 Total loss: 0.91401 timestamp: 1655057512.6924145 iteration: 62030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11939 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.19013 L1 loss: 0.0000e+00 L2 loss: 0.56854 Learning rate: 0.0004 Mask loss: 0.16319 RPN box loss: 0.01354 RPN score loss: 0.00591 RPN total loss: 0.01945 Total loss: 0.9413 timestamp: 1655057516.0022156 iteration: 62035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07631 FastRCNN class loss: 0.04286 FastRCNN total loss: 0.11917 L1 loss: 0.0000e+00 L2 loss: 0.56853 Learning rate: 0.0004 Mask loss: 0.10391 RPN box loss: 0.00905 RPN score loss: 0.0046 RPN total loss: 0.01365 Total loss: 0.80526 timestamp: 1655057519.2758567 iteration: 62040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10921 FastRCNN class loss: 0.05283 FastRCNN total loss: 0.16204 L1 loss: 0.0000e+00 L2 loss: 0.56853 Learning rate: 0.0004 Mask loss: 0.09365 RPN box loss: 0.01425 RPN score loss: 0.0039 RPN total loss: 0.01816 Total loss: 0.84238 timestamp: 1655057522.514298 iteration: 62045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11009 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.19011 L1 loss: 0.0000e+00 L2 loss: 0.56853 Learning rate: 0.0004 Mask loss: 0.146 RPN box loss: 0.04871 RPN score loss: 0.00841 RPN total loss: 0.05712 Total loss: 0.96177 timestamp: 1655057525.801808 iteration: 62050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1142 FastRCNN class loss: 0.03865 FastRCNN total loss: 0.15285 L1 loss: 0.0000e+00 L2 loss: 0.56853 Learning rate: 0.0004 Mask loss: 0.13603 RPN box loss: 0.00677 RPN score loss: 0.00404 RPN total loss: 0.01081 Total loss: 0.86822 timestamp: 1655057529.1035428 iteration: 62055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06825 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.14047 L1 loss: 0.0000e+00 L2 loss: 0.56853 Learning rate: 0.0004 Mask loss: 0.13813 RPN box loss: 0.01495 RPN score loss: 0.00626 RPN total loss: 0.02121 Total loss: 0.86833 timestamp: 1655057532.386724 iteration: 62060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13657 FastRCNN class loss: 0.09472 FastRCNN total loss: 0.23129 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.1295 RPN box loss: 0.00592 RPN score loss: 0.0069 RPN total loss: 0.01281 Total loss: 0.94213 timestamp: 1655057535.617607 iteration: 62065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08231 FastRCNN class loss: 0.07894 FastRCNN total loss: 0.16126 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.14961 RPN box loss: 0.0063 RPN score loss: 0.01168 RPN total loss: 0.01798 Total loss: 0.89737 timestamp: 1655057538.9041636 iteration: 62070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09416 FastRCNN class loss: 0.05292 FastRCNN total loss: 0.14708 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.13102 RPN box loss: 0.00317 RPN score loss: 0.00184 RPN total loss: 0.005 Total loss: 0.85163 timestamp: 1655057542.229225 iteration: 62075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05815 FastRCNN class loss: 0.04045 FastRCNN total loss: 0.09859 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.13509 RPN box loss: 0.0091 RPN score loss: 0.00938 RPN total loss: 0.01848 Total loss: 0.82069 timestamp: 1655057545.5198994 iteration: 62080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06311 FastRCNN class loss: 0.03259 FastRCNN total loss: 0.09569 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.09536 RPN box loss: 0.01078 RPN score loss: 0.00292 RPN total loss: 0.0137 Total loss: 0.77327 timestamp: 1655057548.7696793 iteration: 62085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13011 FastRCNN class loss: 0.08272 FastRCNN total loss: 0.21283 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.18245 RPN box loss: 0.00386 RPN score loss: 0.00614 RPN total loss: 0.01 Total loss: 0.97379 timestamp: 1655057552.0351558 iteration: 62090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10343 FastRCNN class loss: 0.08498 FastRCNN total loss: 0.18841 L1 loss: 0.0000e+00 L2 loss: 0.56852 Learning rate: 0.0004 Mask loss: 0.14315 RPN box loss: 0.02745 RPN score loss: 0.01183 RPN total loss: 0.03928 Total loss: 0.93935 timestamp: 1655057555.313202 iteration: 62095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0794 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.14999 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.18848 RPN box loss: 0.00729 RPN score loss: 0.00412 RPN total loss: 0.01141 Total loss: 0.9184 timestamp: 1655057558.5821548 iteration: 62100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10394 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.19199 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.13402 RPN box loss: 0.03113 RPN score loss: 0.00795 RPN total loss: 0.03907 Total loss: 0.9336 timestamp: 1655057561.8150244 iteration: 62105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09262 FastRCNN class loss: 0.05559 FastRCNN total loss: 0.14821 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.1675 RPN box loss: 0.01687 RPN score loss: 0.00341 RPN total loss: 0.02028 Total loss: 0.90451 timestamp: 1655057565.0693223 iteration: 62110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10463 FastRCNN class loss: 0.06338 FastRCNN total loss: 0.16801 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.10504 RPN box loss: 0.02339 RPN score loss: 0.00355 RPN total loss: 0.02694 Total loss: 0.8685 timestamp: 1655057568.2894592 iteration: 62115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15978 FastRCNN class loss: 0.09919 FastRCNN total loss: 0.25897 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.01537 RPN score loss: 0.00412 RPN total loss: 0.01949 Total loss: 0.99172 timestamp: 1655057571.5679843 iteration: 62120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10873 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.17461 L1 loss: 0.0000e+00 L2 loss: 0.56851 Learning rate: 0.0004 Mask loss: 0.13777 RPN box loss: 0.0092 RPN score loss: 0.00742 RPN total loss: 0.01662 Total loss: 0.89749 timestamp: 1655057574.8136904 iteration: 62125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06351 FastRCNN class loss: 0.0687 FastRCNN total loss: 0.13221 L1 loss: 0.0000e+00 L2 loss: 0.5685 Learning rate: 0.0004 Mask loss: 0.13045 RPN box loss: 0.02695 RPN score loss: 0.0107 RPN total loss: 0.03765 Total loss: 0.86881 timestamp: 1655057578.0402734 iteration: 62130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06194 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.10522 L1 loss: 0.0000e+00 L2 loss: 0.5685 Learning rate: 0.0004 Mask loss: 0.08593 RPN box loss: 0.00852 RPN score loss: 0.00145 RPN total loss: 0.00997 Total loss: 0.76962 timestamp: 1655057581.3759599 iteration: 62135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07726 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.12921 L1 loss: 0.0000e+00 L2 loss: 0.5685 Learning rate: 0.0004 Mask loss: 0.11549 RPN box loss: 0.01047 RPN score loss: 0.00448 RPN total loss: 0.01495 Total loss: 0.82815 timestamp: 1655057584.639359 iteration: 62140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09871 FastRCNN class loss: 0.08402 FastRCNN total loss: 0.18273 L1 loss: 0.0000e+00 L2 loss: 0.5685 Learning rate: 0.0004 Mask loss: 0.12408 RPN box loss: 0.02325 RPN score loss: 0.00427 RPN total loss: 0.02751 Total loss: 0.90281 timestamp: 1655057587.8621354 iteration: 62145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16229 FastRCNN class loss: 0.09771 FastRCNN total loss: 0.26 L1 loss: 0.0000e+00 L2 loss: 0.5685 Learning rate: 0.0004 Mask loss: 0.19726 RPN box loss: 0.01526 RPN score loss: 0.00848 RPN total loss: 0.02374 Total loss: 1.0495 timestamp: 1655057591.119766 iteration: 62150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11512 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.18701 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.11758 RPN box loss: 0.02709 RPN score loss: 0.00922 RPN total loss: 0.0363 Total loss: 0.90939 timestamp: 1655057594.3631413 iteration: 62155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10458 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.18424 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.15976 RPN box loss: 0.02682 RPN score loss: 0.00382 RPN total loss: 0.03063 Total loss: 0.94313 timestamp: 1655057597.6293783 iteration: 62160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06092 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.1323 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.09215 RPN box loss: 0.02731 RPN score loss: 0.00939 RPN total loss: 0.0367 Total loss: 0.82965 timestamp: 1655057600.8695846 iteration: 62165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1077 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.15423 RPN box loss: 0.00388 RPN score loss: 0.00389 RPN total loss: 0.00777 Total loss: 0.90004 timestamp: 1655057604.1491373 iteration: 62170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1241 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.19315 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.12474 RPN box loss: 0.03195 RPN score loss: 0.0075 RPN total loss: 0.03945 Total loss: 0.92583 timestamp: 1655057607.456128 iteration: 62175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05712 FastRCNN class loss: 0.05428 FastRCNN total loss: 0.1114 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.13503 RPN box loss: 0.01065 RPN score loss: 0.00868 RPN total loss: 0.01933 Total loss: 0.83425 timestamp: 1655057610.7197294 iteration: 62180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17063 FastRCNN class loss: 0.14906 FastRCNN total loss: 0.31969 L1 loss: 0.0000e+00 L2 loss: 0.56849 Learning rate: 0.0004 Mask loss: 0.12169 RPN box loss: 0.01063 RPN score loss: 0.00492 RPN total loss: 0.01555 Total loss: 1.02541 timestamp: 1655057613.9736705 iteration: 62185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0637 FastRCNN class loss: 0.03942 FastRCNN total loss: 0.10311 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.11967 RPN box loss: 0.00805 RPN score loss: 0.0051 RPN total loss: 0.01315 Total loss: 0.80442 timestamp: 1655057617.2910972 iteration: 62190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12516 FastRCNN class loss: 0.0729 FastRCNN total loss: 0.19806 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.14842 RPN box loss: 0.01392 RPN score loss: 0.00786 RPN total loss: 0.02177 Total loss: 0.93674 timestamp: 1655057620.5852964 iteration: 62195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.15529 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.25825 RPN box loss: 0.01304 RPN score loss: 0.007 RPN total loss: 0.02004 Total loss: 1.00207 timestamp: 1655057623.8423128 iteration: 62200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06265 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.13238 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.10842 RPN box loss: 0.00798 RPN score loss: 0.00259 RPN total loss: 0.01057 Total loss: 0.81984 timestamp: 1655057627.1140785 iteration: 62205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05312 FastRCNN class loss: 0.03257 FastRCNN total loss: 0.08569 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.12323 RPN box loss: 0.02092 RPN score loss: 0.0038 RPN total loss: 0.02473 Total loss: 0.80213 timestamp: 1655057630.4200633 iteration: 62210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13148 FastRCNN class loss: 0.10254 FastRCNN total loss: 0.23403 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.21854 RPN box loss: 0.03429 RPN score loss: 0.01986 RPN total loss: 0.05415 Total loss: 1.0752 timestamp: 1655057633.7233608 iteration: 62215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09587 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.17799 L1 loss: 0.0000e+00 L2 loss: 0.56848 Learning rate: 0.0004 Mask loss: 0.18523 RPN box loss: 0.01008 RPN score loss: 0.00544 RPN total loss: 0.01552 Total loss: 0.94721 timestamp: 1655057637.019802 iteration: 62220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.123 FastRCNN class loss: 0.06434 FastRCNN total loss: 0.18734 L1 loss: 0.0000e+00 L2 loss: 0.56847 Learning rate: 0.0004 Mask loss: 0.10061 RPN box loss: 0.0166 RPN score loss: 0.00419 RPN total loss: 0.02079 Total loss: 0.87722 timestamp: 1655057640.3484101 iteration: 62225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10908 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.18869 L1 loss: 0.0000e+00 L2 loss: 0.56847 Learning rate: 0.0004 Mask loss: 0.13727 RPN box loss: 0.01501 RPN score loss: 0.0105 RPN total loss: 0.02551 Total loss: 0.91995 timestamp: 1655057643.6450942 iteration: 62230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14319 FastRCNN class loss: 0.06657 FastRCNN total loss: 0.20975 L1 loss: 0.0000e+00 L2 loss: 0.56847 Learning rate: 0.0004 Mask loss: 0.14507 RPN box loss: 0.00633 RPN score loss: 0.00218 RPN total loss: 0.00851 Total loss: 0.93181 timestamp: 1655057646.9092555 iteration: 62235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08694 FastRCNN class loss: 0.08331 FastRCNN total loss: 0.17025 L1 loss: 0.0000e+00 L2 loss: 0.56847 Learning rate: 0.0004 Mask loss: 0.11679 RPN box loss: 0.01585 RPN score loss: 0.00694 RPN total loss: 0.02278 Total loss: 0.8783 timestamp: 1655057650.1626039 iteration: 62240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08265 FastRCNN class loss: 0.10115 FastRCNN total loss: 0.18381 L1 loss: 0.0000e+00 L2 loss: 0.56847 Learning rate: 0.0004 Mask loss: 0.17486 RPN box loss: 0.00952 RPN score loss: 0.0052 RPN total loss: 0.01472 Total loss: 0.94185 timestamp: 1655057653.418463 iteration: 62245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06282 FastRCNN class loss: 0.04989 FastRCNN total loss: 0.11271 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.14266 RPN box loss: 0.00871 RPN score loss: 0.00161 RPN total loss: 0.01033 Total loss: 0.83416 timestamp: 1655057656.6725564 iteration: 62250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1101 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.1714 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.11071 RPN box loss: 0.03255 RPN score loss: 0.01219 RPN total loss: 0.04474 Total loss: 0.89531 timestamp: 1655057659.9412923 iteration: 62255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05141 FastRCNN class loss: 0.03859 FastRCNN total loss: 0.09 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.11099 RPN box loss: 0.00435 RPN score loss: 0.00599 RPN total loss: 0.01034 Total loss: 0.77979 timestamp: 1655057663.2494318 iteration: 62260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11719 FastRCNN class loss: 0.09913 FastRCNN total loss: 0.21632 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.21807 RPN box loss: 0.01773 RPN score loss: 0.00901 RPN total loss: 0.02673 Total loss: 1.02958 timestamp: 1655057666.5499845 iteration: 62265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12429 FastRCNN class loss: 0.07766 FastRCNN total loss: 0.20196 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.11472 RPN box loss: 0.01492 RPN score loss: 0.01026 RPN total loss: 0.02518 Total loss: 0.91031 timestamp: 1655057669.8308358 iteration: 62270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08657 FastRCNN class loss: 0.04819 FastRCNN total loss: 0.13476 L1 loss: 0.0000e+00 L2 loss: 0.56846 Learning rate: 0.0004 Mask loss: 0.12209 RPN box loss: 0.01586 RPN score loss: 0.00581 RPN total loss: 0.02167 Total loss: 0.84697 timestamp: 1655057673.0721138 iteration: 62275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07006 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.13056 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.10846 RPN box loss: 0.02653 RPN score loss: 0.00961 RPN total loss: 0.03614 Total loss: 0.84361 timestamp: 1655057676.3811347 iteration: 62280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0727 FastRCNN class loss: 0.05998 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.1152 RPN box loss: 0.01094 RPN score loss: 0.00225 RPN total loss: 0.01318 Total loss: 0.82951 timestamp: 1655057679.6403785 iteration: 62285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.10814 FastRCNN total loss: 0.21377 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.153 RPN box loss: 0.01071 RPN score loss: 0.00591 RPN total loss: 0.01662 Total loss: 0.95184 timestamp: 1655057682.8895524 iteration: 62290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12688 FastRCNN class loss: 0.05822 FastRCNN total loss: 0.1851 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.12057 RPN box loss: 0.00527 RPN score loss: 0.0038 RPN total loss: 0.00907 Total loss: 0.8832 timestamp: 1655057686.231771 iteration: 62295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1709 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.23949 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.19134 RPN box loss: 0.00883 RPN score loss: 0.00341 RPN total loss: 0.01225 Total loss: 1.01152 timestamp: 1655057689.49246 iteration: 62300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10224 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.16659 L1 loss: 0.0000e+00 L2 loss: 0.56845 Learning rate: 0.0004 Mask loss: 0.11422 RPN box loss: 0.00687 RPN score loss: 0.00276 RPN total loss: 0.00963 Total loss: 0.85889 timestamp: 1655057692.750228 iteration: 62305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.07387 FastRCNN total loss: 0.18539 L1 loss: 0.0000e+00 L2 loss: 0.56844 Learning rate: 0.0004 Mask loss: 0.15945 RPN box loss: 0.02126 RPN score loss: 0.00596 RPN total loss: 0.02722 Total loss: 0.94051 timestamp: 1655057696.0187285 iteration: 62310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04126 FastRCNN class loss: 0.05993 FastRCNN total loss: 0.10119 L1 loss: 0.0000e+00 L2 loss: 0.56844 Learning rate: 0.0004 Mask loss: 0.10383 RPN box loss: 0.013 RPN score loss: 0.00319 RPN total loss: 0.01619 Total loss: 0.78966 timestamp: 1655057699.280873 iteration: 62315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07828 FastRCNN class loss: 0.06903 FastRCNN total loss: 0.14731 L1 loss: 0.0000e+00 L2 loss: 0.56844 Learning rate: 0.0004 Mask loss: 0.10403 RPN box loss: 0.0181 RPN score loss: 0.00666 RPN total loss: 0.02476 Total loss: 0.84453 timestamp: 1655057702.5197408 iteration: 62320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.18624 L1 loss: 0.0000e+00 L2 loss: 0.56844 Learning rate: 0.0004 Mask loss: 0.15592 RPN box loss: 0.0183 RPN score loss: 0.01686 RPN total loss: 0.03516 Total loss: 0.94576 timestamp: 1655057705.7214942 iteration: 62325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11827 FastRCNN class loss: 0.07063 FastRCNN total loss: 0.1889 L1 loss: 0.0000e+00 L2 loss: 0.56844 Learning rate: 0.0004 Mask loss: 0.12619 RPN box loss: 0.01283 RPN score loss: 0.00207 RPN total loss: 0.0149 Total loss: 0.89842 timestamp: 1655057708.9986248 iteration: 62330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09733 FastRCNN class loss: 0.06203 FastRCNN total loss: 0.15936 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.16325 RPN box loss: 0.01518 RPN score loss: 0.00481 RPN total loss: 0.01999 Total loss: 0.91103 timestamp: 1655057712.2539685 iteration: 62335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06055 FastRCNN class loss: 0.05102 FastRCNN total loss: 0.11158 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.11886 RPN box loss: 0.01724 RPN score loss: 0.00774 RPN total loss: 0.02498 Total loss: 0.82385 timestamp: 1655057715.540246 iteration: 62340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06496 FastRCNN class loss: 0.07562 FastRCNN total loss: 0.14058 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.10068 RPN box loss: 0.00987 RPN score loss: 0.0042 RPN total loss: 0.01407 Total loss: 0.82376 timestamp: 1655057718.8534234 iteration: 62345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09043 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.1399 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.15085 RPN box loss: 0.02829 RPN score loss: 0.00501 RPN total loss: 0.03329 Total loss: 0.89247 timestamp: 1655057722.1248655 iteration: 62350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11627 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.18611 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.12226 RPN box loss: 0.01287 RPN score loss: 0.00477 RPN total loss: 0.01765 Total loss: 0.89445 timestamp: 1655057725.4085488 iteration: 62355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14557 FastRCNN class loss: 0.0949 FastRCNN total loss: 0.24047 L1 loss: 0.0000e+00 L2 loss: 0.56843 Learning rate: 0.0004 Mask loss: 0.1468 RPN box loss: 0.02471 RPN score loss: 0.00503 RPN total loss: 0.02975 Total loss: 0.98544 timestamp: 1655057728.6659026 iteration: 62360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05482 FastRCNN class loss: 0.04234 FastRCNN total loss: 0.09716 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.21886 RPN box loss: 0.0379 RPN score loss: 0.00283 RPN total loss: 0.04073 Total loss: 0.92517 timestamp: 1655057731.921076 iteration: 62365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04742 FastRCNN class loss: 0.04283 FastRCNN total loss: 0.09025 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.09567 RPN box loss: 0.01113 RPN score loss: 0.00258 RPN total loss: 0.01371 Total loss: 0.76806 timestamp: 1655057735.1321976 iteration: 62370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.12313 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.12034 RPN box loss: 0.01105 RPN score loss: 0.00639 RPN total loss: 0.01744 Total loss: 0.82933 timestamp: 1655057738.3652387 iteration: 62375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08228 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.1515 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.15682 RPN box loss: 0.02743 RPN score loss: 0.00203 RPN total loss: 0.02945 Total loss: 0.9062 timestamp: 1655057741.6004465 iteration: 62380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.06815 FastRCNN total loss: 0.13056 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.10016 RPN box loss: 0.01053 RPN score loss: 0.00152 RPN total loss: 0.01205 Total loss: 0.81119 timestamp: 1655057744.865505 iteration: 62385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10343 FastRCNN class loss: 0.08618 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 0.56842 Learning rate: 0.0004 Mask loss: 0.11551 RPN box loss: 0.07216 RPN score loss: 0.00473 RPN total loss: 0.0769 Total loss: 0.95043 timestamp: 1655057748.1306314 iteration: 62390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.06104 FastRCNN total loss: 0.14391 L1 loss: 0.0000e+00 L2 loss: 0.56841 Learning rate: 0.0004 Mask loss: 0.12963 RPN box loss: 0.00822 RPN score loss: 0.00189 RPN total loss: 0.0101 Total loss: 0.85205 timestamp: 1655057751.2976303 iteration: 62395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07503 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.12459 L1 loss: 0.0000e+00 L2 loss: 0.56841 Learning rate: 0.0004 Mask loss: 0.10905 RPN box loss: 0.01849 RPN score loss: 0.00491 RPN total loss: 0.02339 Total loss: 0.82545 timestamp: 1655057754.600487 iteration: 62400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11179 FastRCNN class loss: 0.06952 FastRCNN total loss: 0.18131 L1 loss: 0.0000e+00 L2 loss: 0.56841 Learning rate: 0.0004 Mask loss: 0.11811 RPN box loss: 0.05818 RPN score loss: 0.00624 RPN total loss: 0.06441 Total loss: 0.93225 timestamp: 1655057757.8974047 iteration: 62405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11946 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.17615 L1 loss: 0.0000e+00 L2 loss: 0.56841 Learning rate: 0.0004 Mask loss: 0.16 RPN box loss: 0.00956 RPN score loss: 0.0073 RPN total loss: 0.01686 Total loss: 0.92141 timestamp: 1655057761.208691 iteration: 62410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1018 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.17783 L1 loss: 0.0000e+00 L2 loss: 0.56841 Learning rate: 0.0004 Mask loss: 0.1979 RPN box loss: 0.01584 RPN score loss: 0.0035 RPN total loss: 0.01934 Total loss: 0.96348 timestamp: 1655057764.4889593 iteration: 62415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.104 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.16456 L1 loss: 0.0000e+00 L2 loss: 0.5684 Learning rate: 0.0004 Mask loss: 0.11925 RPN box loss: 0.01906 RPN score loss: 0.00366 RPN total loss: 0.02272 Total loss: 0.87493 timestamp: 1655057767.7986917 iteration: 62420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09181 FastRCNN class loss: 0.0656 FastRCNN total loss: 0.15741 L1 loss: 0.0000e+00 L2 loss: 0.5684 Learning rate: 0.0004 Mask loss: 0.14182 RPN box loss: 0.01608 RPN score loss: 0.01853 RPN total loss: 0.03461 Total loss: 0.90224 timestamp: 1655057771.0878236 iteration: 62425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08291 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.15704 L1 loss: 0.0000e+00 L2 loss: 0.5684 Learning rate: 0.0004 Mask loss: 0.16617 RPN box loss: 0.0318 RPN score loss: 0.00827 RPN total loss: 0.04007 Total loss: 0.93169 timestamp: 1655057774.3457212 iteration: 62430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09689 FastRCNN class loss: 0.07547 FastRCNN total loss: 0.17235 L1 loss: 0.0000e+00 L2 loss: 0.5684 Learning rate: 0.0004 Mask loss: 0.1244 RPN box loss: 0.02979 RPN score loss: 0.00193 RPN total loss: 0.03172 Total loss: 0.89687 timestamp: 1655057777.5670247 iteration: 62435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10908 FastRCNN class loss: 0.05021 FastRCNN total loss: 0.15929 L1 loss: 0.0000e+00 L2 loss: 0.5684 Learning rate: 0.0004 Mask loss: 0.10613 RPN box loss: 0.00713 RPN score loss: 0.0014 RPN total loss: 0.00853 Total loss: 0.84235 timestamp: 1655057780.7892902 iteration: 62440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10939 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.17361 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.18558 RPN box loss: 0.05772 RPN score loss: 0.00362 RPN total loss: 0.06134 Total loss: 0.98892 timestamp: 1655057784.0764205 iteration: 62445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.07422 FastRCNN total loss: 0.19417 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.17173 RPN box loss: 0.02748 RPN score loss: 0.00511 RPN total loss: 0.03259 Total loss: 0.96688 timestamp: 1655057787.332182 iteration: 62450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.14313 RPN box loss: 0.0113 RPN score loss: 0.01222 RPN total loss: 0.02352 Total loss: 0.89174 timestamp: 1655057790.6003597 iteration: 62455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09983 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.15182 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.14658 RPN box loss: 0.01903 RPN score loss: 0.00313 RPN total loss: 0.02215 Total loss: 0.88894 timestamp: 1655057793.888593 iteration: 62460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09784 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.16113 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.18489 RPN box loss: 0.01196 RPN score loss: 0.00413 RPN total loss: 0.01609 Total loss: 0.93051 timestamp: 1655057797.1457326 iteration: 62465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07503 FastRCNN class loss: 0.04984 FastRCNN total loss: 0.12487 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.11156 RPN box loss: 0.0073 RPN score loss: 0.00202 RPN total loss: 0.00933 Total loss: 0.81415 timestamp: 1655057800.3710437 iteration: 62470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10128 FastRCNN class loss: 0.06492 FastRCNN total loss: 0.16619 L1 loss: 0.0000e+00 L2 loss: 0.56839 Learning rate: 0.0004 Mask loss: 0.14914 RPN box loss: 0.01452 RPN score loss: 0.00568 RPN total loss: 0.0202 Total loss: 0.90393 timestamp: 1655057803.6430695 iteration: 62475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13313 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.21056 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.17286 RPN box loss: 0.02214 RPN score loss: 0.00634 RPN total loss: 0.02848 Total loss: 0.98029 timestamp: 1655057806.992297 iteration: 62480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07966 FastRCNN class loss: 0.08837 FastRCNN total loss: 0.16803 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.14783 RPN box loss: 0.0104 RPN score loss: 0.00617 RPN total loss: 0.01658 Total loss: 0.90082 timestamp: 1655057810.3157911 iteration: 62485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07743 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.14396 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.10492 RPN box loss: 0.01678 RPN score loss: 0.00252 RPN total loss: 0.0193 Total loss: 0.83656 timestamp: 1655057813.5641239 iteration: 62490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09182 FastRCNN class loss: 0.06282 FastRCNN total loss: 0.15464 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.08642 RPN box loss: 0.00865 RPN score loss: 0.00284 RPN total loss: 0.01149 Total loss: 0.82093 timestamp: 1655057816.858212 iteration: 62495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07897 FastRCNN class loss: 0.06174 FastRCNN total loss: 0.14071 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.09687 RPN box loss: 0.01601 RPN score loss: 0.00342 RPN total loss: 0.01943 Total loss: 0.82538 timestamp: 1655057820.1321483 iteration: 62500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07825 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.15614 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.09722 RPN box loss: 0.02175 RPN score loss: 0.00721 RPN total loss: 0.02896 Total loss: 0.8507 timestamp: 1655057823.4159012 iteration: 62505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07107 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.15499 L1 loss: 0.0000e+00 L2 loss: 0.56838 Learning rate: 0.0004 Mask loss: 0.13763 RPN box loss: 0.01677 RPN score loss: 0.00782 RPN total loss: 0.0246 Total loss: 0.88559 timestamp: 1655057826.7315714 iteration: 62510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07995 FastRCNN class loss: 0.06795 FastRCNN total loss: 0.1479 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.13194 RPN box loss: 0.01009 RPN score loss: 0.00335 RPN total loss: 0.01343 Total loss: 0.86166 timestamp: 1655057830.0042906 iteration: 62515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.08879 FastRCNN total loss: 0.24052 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.18997 RPN box loss: 0.01938 RPN score loss: 0.0082 RPN total loss: 0.02758 Total loss: 1.02644 timestamp: 1655057833.2398772 iteration: 62520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09971 FastRCNN class loss: 0.07305 FastRCNN total loss: 0.17275 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.18821 RPN box loss: 0.01786 RPN score loss: 0.01117 RPN total loss: 0.02903 Total loss: 0.95836 timestamp: 1655057836.5136178 iteration: 62525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06211 FastRCNN class loss: 0.06673 FastRCNN total loss: 0.12884 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.14418 RPN box loss: 0.02117 RPN score loss: 0.00277 RPN total loss: 0.02395 Total loss: 0.86534 timestamp: 1655057839.7263188 iteration: 62530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10532 FastRCNN class loss: 0.05311 FastRCNN total loss: 0.15843 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.12472 RPN box loss: 0.00966 RPN score loss: 0.00286 RPN total loss: 0.01252 Total loss: 0.86405 timestamp: 1655057842.9835658 iteration: 62535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14141 FastRCNN class loss: 0.07373 FastRCNN total loss: 0.21514 L1 loss: 0.0000e+00 L2 loss: 0.56837 Learning rate: 0.0004 Mask loss: 0.16493 RPN box loss: 0.00847 RPN score loss: 0.00524 RPN total loss: 0.01371 Total loss: 0.96214 timestamp: 1655057846.2295296 iteration: 62540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08752 FastRCNN class loss: 0.0681 FastRCNN total loss: 0.15561 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.18562 RPN box loss: 0.02624 RPN score loss: 0.00347 RPN total loss: 0.02971 Total loss: 0.93931 timestamp: 1655057849.538971 iteration: 62545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.04579 FastRCNN total loss: 0.12159 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.16704 RPN box loss: 0.00874 RPN score loss: 0.00538 RPN total loss: 0.01412 Total loss: 0.87111 timestamp: 1655057852.8081632 iteration: 62550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09827 FastRCNN class loss: 0.05633 FastRCNN total loss: 0.1546 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.15027 RPN box loss: 0.00858 RPN score loss: 0.0043 RPN total loss: 0.01289 Total loss: 0.88612 timestamp: 1655057856.1235447 iteration: 62555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.16839 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.21062 RPN box loss: 0.02181 RPN score loss: 0.00702 RPN total loss: 0.02883 Total loss: 0.9762 timestamp: 1655057859.3769898 iteration: 62560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06842 FastRCNN class loss: 0.10138 FastRCNN total loss: 0.1698 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.15912 RPN box loss: 0.02729 RPN score loss: 0.01013 RPN total loss: 0.03742 Total loss: 0.93471 timestamp: 1655057862.6380856 iteration: 62565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12406 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.20401 L1 loss: 0.0000e+00 L2 loss: 0.56836 Learning rate: 0.0004 Mask loss: 0.15237 RPN box loss: 0.01778 RPN score loss: 0.00885 RPN total loss: 0.02663 Total loss: 0.95137 timestamp: 1655057865.9286988 iteration: 62570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08052 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.13074 L1 loss: 0.0000e+00 L2 loss: 0.56835 Learning rate: 0.0004 Mask loss: 0.10027 RPN box loss: 0.00576 RPN score loss: 0.0015 RPN total loss: 0.00726 Total loss: 0.80662 timestamp: 1655057869.1509674 iteration: 62575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08354 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.14472 L1 loss: 0.0000e+00 L2 loss: 0.56835 Learning rate: 0.0004 Mask loss: 0.13069 RPN box loss: 0.00796 RPN score loss: 0.00312 RPN total loss: 0.01108 Total loss: 0.85484 timestamp: 1655057872.3404422 iteration: 62580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10473 FastRCNN class loss: 0.10586 FastRCNN total loss: 0.21059 L1 loss: 0.0000e+00 L2 loss: 0.56835 Learning rate: 0.0004 Mask loss: 0.1806 RPN box loss: 0.02723 RPN score loss: 0.0134 RPN total loss: 0.04063 Total loss: 1.00018 timestamp: 1655057875.6408553 iteration: 62585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11428 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.17212 L1 loss: 0.0000e+00 L2 loss: 0.56835 Learning rate: 0.0004 Mask loss: 0.1695 RPN box loss: 0.01115 RPN score loss: 0.00542 RPN total loss: 0.01657 Total loss: 0.92654 timestamp: 1655057878.8741481 iteration: 62590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14816 FastRCNN class loss: 0.04738 FastRCNN total loss: 0.19554 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.10175 RPN box loss: 0.01309 RPN score loss: 0.00271 RPN total loss: 0.01581 Total loss: 0.88144 timestamp: 1655057882.1529553 iteration: 62595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1407 FastRCNN class loss: 0.1276 FastRCNN total loss: 0.2683 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.14788 RPN box loss: 0.02416 RPN score loss: 0.00606 RPN total loss: 0.03022 Total loss: 1.01473 timestamp: 1655057885.4170778 iteration: 62600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08974 FastRCNN class loss: 0.0536 FastRCNN total loss: 0.14334 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.16887 RPN box loss: 0.01591 RPN score loss: 0.00163 RPN total loss: 0.01754 Total loss: 0.89809 timestamp: 1655057888.633266 iteration: 62605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10628 FastRCNN class loss: 0.05552 FastRCNN total loss: 0.1618 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.15357 RPN box loss: 0.00354 RPN score loss: 0.00355 RPN total loss: 0.00709 Total loss: 0.8908 timestamp: 1655057891.937829 iteration: 62610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1017 FastRCNN class loss: 0.07516 FastRCNN total loss: 0.17685 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.08362 RPN box loss: 0.00848 RPN score loss: 0.0029 RPN total loss: 0.01138 Total loss: 0.84019 timestamp: 1655057895.1630974 iteration: 62615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12344 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.20405 L1 loss: 0.0000e+00 L2 loss: 0.56834 Learning rate: 0.0004 Mask loss: 0.18483 RPN box loss: 0.01129 RPN score loss: 0.01019 RPN total loss: 0.02149 Total loss: 0.97871 timestamp: 1655057898.4380505 iteration: 62620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12805 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.19848 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.25333 RPN box loss: 0.00525 RPN score loss: 0.00328 RPN total loss: 0.00853 Total loss: 1.02867 timestamp: 1655057901.7098393 iteration: 62625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1049 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.17028 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.10235 RPN box loss: 0.0071 RPN score loss: 0.00828 RPN total loss: 0.01538 Total loss: 0.85635 timestamp: 1655057904.9560318 iteration: 62630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0639 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.13596 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.13234 RPN box loss: 0.01682 RPN score loss: 0.00366 RPN total loss: 0.02048 Total loss: 0.8571 timestamp: 1655057908.2450874 iteration: 62635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10271 FastRCNN class loss: 0.05255 FastRCNN total loss: 0.15526 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.09042 RPN box loss: 0.00442 RPN score loss: 0.0018 RPN total loss: 0.00622 Total loss: 0.82022 timestamp: 1655057911.5154684 iteration: 62640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.1816 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.13593 RPN box loss: 0.01943 RPN score loss: 0.00635 RPN total loss: 0.02578 Total loss: 0.91163 timestamp: 1655057914.8194308 iteration: 62645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06802 FastRCNN class loss: 0.04327 FastRCNN total loss: 0.11128 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.08927 RPN box loss: 0.00266 RPN score loss: 0.0068 RPN total loss: 0.00946 Total loss: 0.77834 timestamp: 1655057918.0860908 iteration: 62650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.14502 L1 loss: 0.0000e+00 L2 loss: 0.56833 Learning rate: 0.0004 Mask loss: 0.11637 RPN box loss: 0.00544 RPN score loss: 0.00098 RPN total loss: 0.00642 Total loss: 0.83613 timestamp: 1655057921.309936 iteration: 62655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05899 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.11017 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.15351 RPN box loss: 0.011 RPN score loss: 0.00188 RPN total loss: 0.01288 Total loss: 0.84488 timestamp: 1655057924.529831 iteration: 62660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.06604 FastRCNN total loss: 0.17947 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.12669 RPN box loss: 0.0147 RPN score loss: 0.0038 RPN total loss: 0.0185 Total loss: 0.89298 timestamp: 1655057927.8635058 iteration: 62665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13309 FastRCNN class loss: 0.09135 FastRCNN total loss: 0.22444 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.14646 RPN box loss: 0.03256 RPN score loss: 0.01104 RPN total loss: 0.0436 Total loss: 0.98282 timestamp: 1655057931.120238 iteration: 62670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11401 FastRCNN class loss: 0.07222 FastRCNN total loss: 0.18623 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.1693 RPN box loss: 0.02428 RPN score loss: 0.00457 RPN total loss: 0.02885 Total loss: 0.9527 timestamp: 1655057934.4519994 iteration: 62675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11687 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.17593 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.14468 RPN box loss: 0.0058 RPN score loss: 0.00324 RPN total loss: 0.00903 Total loss: 0.89797 timestamp: 1655057937.7422874 iteration: 62680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09108 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.15379 L1 loss: 0.0000e+00 L2 loss: 0.56832 Learning rate: 0.0004 Mask loss: 0.16405 RPN box loss: 0.01032 RPN score loss: 0.00481 RPN total loss: 0.01513 Total loss: 0.90129 timestamp: 1655057940.973349 iteration: 62685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06223 FastRCNN class loss: 0.07286 FastRCNN total loss: 0.1351 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.1366 RPN box loss: 0.06049 RPN score loss: 0.00584 RPN total loss: 0.06633 Total loss: 0.90634 timestamp: 1655057944.2154677 iteration: 62690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10728 FastRCNN class loss: 0.12205 FastRCNN total loss: 0.22933 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.15224 RPN box loss: 0.03445 RPN score loss: 0.01236 RPN total loss: 0.04681 Total loss: 0.9967 timestamp: 1655057947.5470443 iteration: 62695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03658 FastRCNN class loss: 0.03747 FastRCNN total loss: 0.07405 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.01664 RPN score loss: 0.00327 RPN total loss: 0.01991 Total loss: 0.78845 timestamp: 1655057950.8479905 iteration: 62700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0659 FastRCNN class loss: 0.05417 FastRCNN total loss: 0.12007 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.12758 RPN box loss: 0.02016 RPN score loss: 0.00583 RPN total loss: 0.02599 Total loss: 0.84195 timestamp: 1655057954.1261015 iteration: 62705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08024 FastRCNN class loss: 0.0761 FastRCNN total loss: 0.15634 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.13713 RPN box loss: 0.02263 RPN score loss: 0.00999 RPN total loss: 0.03262 Total loss: 0.8944 timestamp: 1655057957.4188373 iteration: 62710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04612 FastRCNN class loss: 0.04161 FastRCNN total loss: 0.08772 L1 loss: 0.0000e+00 L2 loss: 0.56831 Learning rate: 0.0004 Mask loss: 0.11196 RPN box loss: 0.01478 RPN score loss: 0.00311 RPN total loss: 0.01788 Total loss: 0.78587 timestamp: 1655057960.6850297 iteration: 62715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11403 FastRCNN class loss: 0.09689 FastRCNN total loss: 0.21092 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.10243 RPN box loss: 0.00871 RPN score loss: 0.00725 RPN total loss: 0.01597 Total loss: 0.89762 timestamp: 1655057963.995379 iteration: 62720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06666 FastRCNN class loss: 0.07453 FastRCNN total loss: 0.14118 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.14036 RPN box loss: 0.0166 RPN score loss: 0.01156 RPN total loss: 0.02816 Total loss: 0.87801 timestamp: 1655057967.2680683 iteration: 62725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07074 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.14269 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.16792 RPN box loss: 0.02175 RPN score loss: 0.00659 RPN total loss: 0.02833 Total loss: 0.90725 timestamp: 1655057970.5928059 iteration: 62730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11865 FastRCNN class loss: 0.06923 FastRCNN total loss: 0.18789 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.11139 RPN box loss: 0.01891 RPN score loss: 0.00867 RPN total loss: 0.02758 Total loss: 0.89515 timestamp: 1655057973.8418813 iteration: 62735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09403 FastRCNN class loss: 0.05841 FastRCNN total loss: 0.15243 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.13467 RPN box loss: 0.00711 RPN score loss: 0.00302 RPN total loss: 0.01012 Total loss: 0.86553 timestamp: 1655057977.1180246 iteration: 62740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11354 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.17211 L1 loss: 0.0000e+00 L2 loss: 0.5683 Learning rate: 0.0004 Mask loss: 0.15493 RPN box loss: 0.03101 RPN score loss: 0.0019 RPN total loss: 0.0329 Total loss: 0.92824 timestamp: 1655057980.4005291 iteration: 62745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12506 FastRCNN class loss: 0.07709 FastRCNN total loss: 0.20215 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.15112 RPN box loss: 0.06459 RPN score loss: 0.00707 RPN total loss: 0.07166 Total loss: 0.99323 timestamp: 1655057983.6553032 iteration: 62750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1446 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.20556 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.11586 RPN box loss: 0.03223 RPN score loss: 0.00212 RPN total loss: 0.03435 Total loss: 0.92406 timestamp: 1655057986.8858025 iteration: 62755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15146 FastRCNN class loss: 0.05796 FastRCNN total loss: 0.20942 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.18311 RPN box loss: 0.02063 RPN score loss: 0.00637 RPN total loss: 0.027 Total loss: 0.98783 timestamp: 1655057990.191418 iteration: 62760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10099 FastRCNN class loss: 0.10282 FastRCNN total loss: 0.20381 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.15115 RPN box loss: 0.01137 RPN score loss: 0.00562 RPN total loss: 0.01699 Total loss: 0.94024 timestamp: 1655057993.535935 iteration: 62765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13269 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.20955 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.16195 RPN box loss: 0.02346 RPN score loss: 0.00254 RPN total loss: 0.026 Total loss: 0.96579 timestamp: 1655057996.8072956 iteration: 62770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.0546 FastRCNN total loss: 0.10802 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.1032 RPN box loss: 0.01609 RPN score loss: 0.00138 RPN total loss: 0.01747 Total loss: 0.79699 timestamp: 1655058000.0154006 iteration: 62775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08668 FastRCNN class loss: 0.10742 FastRCNN total loss: 0.1941 L1 loss: 0.0000e+00 L2 loss: 0.56829 Learning rate: 0.0004 Mask loss: 0.15086 RPN box loss: 0.00976 RPN score loss: 0.00483 RPN total loss: 0.01459 Total loss: 0.92784 timestamp: 1655058003.2996151 iteration: 62780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10947 FastRCNN class loss: 0.05201 FastRCNN total loss: 0.16147 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.10533 RPN box loss: 0.02107 RPN score loss: 0.00085 RPN total loss: 0.02193 Total loss: 0.85701 timestamp: 1655058006.557122 iteration: 62785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08759 FastRCNN class loss: 0.0533 FastRCNN total loss: 0.14089 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.12027 RPN box loss: 0.02594 RPN score loss: 0.00488 RPN total loss: 0.03083 Total loss: 0.86027 timestamp: 1655058009.8845048 iteration: 62790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04175 FastRCNN class loss: 0.04646 FastRCNN total loss: 0.08821 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.12537 RPN box loss: 0.00754 RPN score loss: 0.00289 RPN total loss: 0.01044 Total loss: 0.7923 timestamp: 1655058013.1722703 iteration: 62795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0704 FastRCNN class loss: 0.03601 FastRCNN total loss: 0.10641 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.13465 RPN box loss: 0.00756 RPN score loss: 0.0035 RPN total loss: 0.01105 Total loss: 0.8204 timestamp: 1655058016.4260232 iteration: 62800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11989 FastRCNN class loss: 0.10907 FastRCNN total loss: 0.22896 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.19073 RPN box loss: 0.0103 RPN score loss: 0.00671 RPN total loss: 0.01701 Total loss: 1.00498 timestamp: 1655058019.6984973 iteration: 62805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06184 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.12341 L1 loss: 0.0000e+00 L2 loss: 0.56828 Learning rate: 0.0004 Mask loss: 0.09664 RPN box loss: 0.00556 RPN score loss: 0.00122 RPN total loss: 0.00678 Total loss: 0.79511 timestamp: 1655058022.9129882 iteration: 62810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.16438 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.16582 RPN box loss: 0.03346 RPN score loss: 0.00707 RPN total loss: 0.04052 Total loss: 0.93899 timestamp: 1655058026.1056392 iteration: 62815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08543 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.14441 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.11915 RPN box loss: 0.00662 RPN score loss: 0.00288 RPN total loss: 0.0095 Total loss: 0.84134 timestamp: 1655058029.3272307 iteration: 62820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15712 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.23157 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.10477 RPN box loss: 0.01529 RPN score loss: 0.00801 RPN total loss: 0.02329 Total loss: 0.9279 timestamp: 1655058032.5968919 iteration: 62825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08334 FastRCNN class loss: 0.05665 FastRCNN total loss: 0.13999 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.13703 RPN box loss: 0.0085 RPN score loss: 0.00512 RPN total loss: 0.01361 Total loss: 0.8589 timestamp: 1655058035.9589152 iteration: 62830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08284 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.15504 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.19353 RPN box loss: 0.00863 RPN score loss: 0.00423 RPN total loss: 0.01286 Total loss: 0.92969 timestamp: 1655058039.213112 iteration: 62835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11013 FastRCNN class loss: 0.07882 FastRCNN total loss: 0.18895 L1 loss: 0.0000e+00 L2 loss: 0.56827 Learning rate: 0.0004 Mask loss: 0.10837 RPN box loss: 0.01365 RPN score loss: 0.00224 RPN total loss: 0.01589 Total loss: 0.88148 timestamp: 1655058042.492202 iteration: 62840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17893 FastRCNN class loss: 0.11504 FastRCNN total loss: 0.29397 L1 loss: 0.0000e+00 L2 loss: 0.56826 Learning rate: 0.0004 Mask loss: 0.20595 RPN box loss: 0.01354 RPN score loss: 0.01225 RPN total loss: 0.02579 Total loss: 1.09397 timestamp: 1655058045.7688448 iteration: 62845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07164 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.1318 L1 loss: 0.0000e+00 L2 loss: 0.56826 Learning rate: 0.0004 Mask loss: 0.09969 RPN box loss: 0.01702 RPN score loss: 0.00565 RPN total loss: 0.02267 Total loss: 0.82243 timestamp: 1655058048.996121 iteration: 62850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10673 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.16784 L1 loss: 0.0000e+00 L2 loss: 0.56826 Learning rate: 0.0004 Mask loss: 0.14029 RPN box loss: 0.01109 RPN score loss: 0.00288 RPN total loss: 0.01397 Total loss: 0.89037 timestamp: 1655058052.2466571 iteration: 62855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06871 FastRCNN class loss: 0.08292 FastRCNN total loss: 0.15164 L1 loss: 0.0000e+00 L2 loss: 0.56826 Learning rate: 0.0004 Mask loss: 0.15856 RPN box loss: 0.00841 RPN score loss: 0.0133 RPN total loss: 0.02171 Total loss: 0.90017 timestamp: 1655058055.4954507 iteration: 62860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13101 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.19871 L1 loss: 0.0000e+00 L2 loss: 0.56826 Learning rate: 0.0004 Mask loss: 0.0922 RPN box loss: 0.01157 RPN score loss: 0.00194 RPN total loss: 0.01352 Total loss: 0.87268 timestamp: 1655058058.750615 iteration: 62865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07405 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.1393 L1 loss: 0.0000e+00 L2 loss: 0.56825 Learning rate: 0.0004 Mask loss: 0.12052 RPN box loss: 0.00342 RPN score loss: 0.00141 RPN total loss: 0.00482 Total loss: 0.83289 timestamp: 1655058062.0985367 iteration: 62870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08554 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.14093 L1 loss: 0.0000e+00 L2 loss: 0.56825 Learning rate: 0.0004 Mask loss: 0.14902 RPN box loss: 0.01296 RPN score loss: 0.00835 RPN total loss: 0.02131 Total loss: 0.87952 timestamp: 1655058065.3535666 iteration: 62875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.07898 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.56825 Learning rate: 0.0004 Mask loss: 0.12763 RPN box loss: 0.0231 RPN score loss: 0.00468 RPN total loss: 0.02778 Total loss: 0.89033 timestamp: 1655058068.6236775 iteration: 62880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.05581 FastRCNN total loss: 0.15422 L1 loss: 0.0000e+00 L2 loss: 0.56825 Learning rate: 0.0004 Mask loss: 0.11008 RPN box loss: 0.00634 RPN score loss: 0.00235 RPN total loss: 0.00869 Total loss: 0.84124 timestamp: 1655058071.9037979 iteration: 62885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10564 FastRCNN class loss: 0.05543 FastRCNN total loss: 0.16107 L1 loss: 0.0000e+00 L2 loss: 0.56825 Learning rate: 0.0004 Mask loss: 0.17452 RPN box loss: 0.0142 RPN score loss: 0.00237 RPN total loss: 0.01658 Total loss: 0.92041 timestamp: 1655058075.161885 iteration: 62890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12108 FastRCNN class loss: 0.08109 FastRCNN total loss: 0.20217 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.1776 RPN box loss: 0.00947 RPN score loss: 0.00613 RPN total loss: 0.0156 Total loss: 0.96361 timestamp: 1655058078.3963556 iteration: 62895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07819 FastRCNN class loss: 0.07465 FastRCNN total loss: 0.15284 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.14526 RPN box loss: 0.05206 RPN score loss: 0.00924 RPN total loss: 0.06129 Total loss: 0.92764 timestamp: 1655058081.6830916 iteration: 62900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09607 FastRCNN class loss: 0.09141 FastRCNN total loss: 0.18748 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.16948 RPN box loss: 0.01759 RPN score loss: 0.01143 RPN total loss: 0.02902 Total loss: 0.95422 timestamp: 1655058084.9767299 iteration: 62905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10803 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.17691 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.14013 RPN box loss: 0.00702 RPN score loss: 0.0141 RPN total loss: 0.02112 Total loss: 0.90639 timestamp: 1655058088.2098353 iteration: 62910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11485 FastRCNN class loss: 0.07947 FastRCNN total loss: 0.19433 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.1737 RPN box loss: 0.01277 RPN score loss: 0.00826 RPN total loss: 0.02103 Total loss: 0.95729 timestamp: 1655058091.435442 iteration: 62915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08721 FastRCNN class loss: 0.02648 FastRCNN total loss: 0.11369 L1 loss: 0.0000e+00 L2 loss: 0.56824 Learning rate: 0.0004 Mask loss: 0.0977 RPN box loss: 0.00691 RPN score loss: 0.00151 RPN total loss: 0.00842 Total loss: 0.78804 timestamp: 1655058094.7982533 iteration: 62920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10883 FastRCNN class loss: 0.06972 FastRCNN total loss: 0.17854 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.17271 RPN box loss: 0.02119 RPN score loss: 0.00569 RPN total loss: 0.02688 Total loss: 0.94637 timestamp: 1655058098.064659 iteration: 62925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15338 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.23299 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.20107 RPN box loss: 0.01382 RPN score loss: 0.00225 RPN total loss: 0.01606 Total loss: 1.01835 timestamp: 1655058101.4033 iteration: 62930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.093 FastRCNN class loss: 0.05543 FastRCNN total loss: 0.14843 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.20563 RPN box loss: 0.043 RPN score loss: 0.00328 RPN total loss: 0.04628 Total loss: 0.96857 timestamp: 1655058104.7281857 iteration: 62935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07596 FastRCNN class loss: 0.07048 FastRCNN total loss: 0.14644 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.12577 RPN box loss: 0.01862 RPN score loss: 0.00455 RPN total loss: 0.02316 Total loss: 0.8636 timestamp: 1655058107.97748 iteration: 62940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05495 FastRCNN class loss: 0.0318 FastRCNN total loss: 0.08675 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.3116 RPN box loss: 0.01611 RPN score loss: 0.00568 RPN total loss: 0.02179 Total loss: 0.98836 timestamp: 1655058111.2652285 iteration: 62945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05852 FastRCNN class loss: 0.06161 FastRCNN total loss: 0.12012 L1 loss: 0.0000e+00 L2 loss: 0.56823 Learning rate: 0.0004 Mask loss: 0.15291 RPN box loss: 0.02142 RPN score loss: 0.01459 RPN total loss: 0.03602 Total loss: 0.87728 timestamp: 1655058114.6030545 iteration: 62950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.079 FastRCNN class loss: 0.05726 FastRCNN total loss: 0.13626 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.10897 RPN box loss: 0.05806 RPN score loss: 0.00723 RPN total loss: 0.06529 Total loss: 0.87874 timestamp: 1655058117.8458583 iteration: 62955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08432 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.15476 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.1343 RPN box loss: 0.00857 RPN score loss: 0.00554 RPN total loss: 0.01411 Total loss: 0.87139 timestamp: 1655058121.2142267 iteration: 62960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07636 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.13798 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.11194 RPN box loss: 0.00678 RPN score loss: 0.0034 RPN total loss: 0.01018 Total loss: 0.82832 timestamp: 1655058124.5127869 iteration: 62965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11672 FastRCNN class loss: 0.08 FastRCNN total loss: 0.19672 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.11851 RPN box loss: 0.02127 RPN score loss: 0.00693 RPN total loss: 0.0282 Total loss: 0.91165 timestamp: 1655058127.8724616 iteration: 62970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09557 FastRCNN class loss: 0.07458 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.11892 RPN box loss: 0.02 RPN score loss: 0.00641 RPN total loss: 0.0264 Total loss: 0.8837 timestamp: 1655058131.0903904 iteration: 62975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07725 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.12394 L1 loss: 0.0000e+00 L2 loss: 0.56822 Learning rate: 0.0004 Mask loss: 0.13128 RPN box loss: 0.0024 RPN score loss: 0.00068 RPN total loss: 0.00307 Total loss: 0.82652 timestamp: 1655058134.3937824 iteration: 62980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13493 FastRCNN class loss: 0.07144 FastRCNN total loss: 0.20637 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.14936 RPN box loss: 0.00875 RPN score loss: 0.00548 RPN total loss: 0.01423 Total loss: 0.93818 timestamp: 1655058137.6780024 iteration: 62985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08882 FastRCNN class loss: 0.05294 FastRCNN total loss: 0.14176 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.13885 RPN box loss: 0.00731 RPN score loss: 0.00568 RPN total loss: 0.01299 Total loss: 0.86182 timestamp: 1655058140.965312 iteration: 62990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09481 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.14997 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.13244 RPN box loss: 0.009 RPN score loss: 0.00283 RPN total loss: 0.01183 Total loss: 0.86246 timestamp: 1655058144.2238343 iteration: 62995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08435 FastRCNN class loss: 0.0679 FastRCNN total loss: 0.15225 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.1145 RPN box loss: 0.06225 RPN score loss: 0.00437 RPN total loss: 0.06662 Total loss: 0.90158 timestamp: 1655058147.52713 iteration: 63000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07718 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.16334 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.14047 RPN box loss: 0.01571 RPN score loss: 0.00387 RPN total loss: 0.01957 Total loss: 0.89159 timestamp: 1655058150.8798444 iteration: 63005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07906 FastRCNN class loss: 0.04977 FastRCNN total loss: 0.12884 L1 loss: 0.0000e+00 L2 loss: 0.56821 Learning rate: 0.0004 Mask loss: 0.15024 RPN box loss: 0.01047 RPN score loss: 0.00464 RPN total loss: 0.01511 Total loss: 0.86239 timestamp: 1655058154.056551 iteration: 63010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10267 FastRCNN class loss: 0.12244 FastRCNN total loss: 0.22511 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.24607 RPN box loss: 0.02375 RPN score loss: 0.0086 RPN total loss: 0.03236 Total loss: 1.07174 timestamp: 1655058157.3691163 iteration: 63015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11766 FastRCNN class loss: 0.08107 FastRCNN total loss: 0.19874 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.12173 RPN box loss: 0.01311 RPN score loss: 0.01062 RPN total loss: 0.02373 Total loss: 0.9124 timestamp: 1655058160.6359336 iteration: 63020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0937 FastRCNN class loss: 0.04929 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.11825 RPN box loss: 0.00487 RPN score loss: 0.00321 RPN total loss: 0.00808 Total loss: 0.83753 timestamp: 1655058163.8302407 iteration: 63025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11763 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.2026 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.13837 RPN box loss: 0.01955 RPN score loss: 0.00526 RPN total loss: 0.0248 Total loss: 0.93397 timestamp: 1655058167.0833879 iteration: 63030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07373 FastRCNN class loss: 0.04747 FastRCNN total loss: 0.1212 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.14223 RPN box loss: 0.0101 RPN score loss: 0.0113 RPN total loss: 0.02139 Total loss: 0.85302 timestamp: 1655058170.2808108 iteration: 63035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06885 FastRCNN class loss: 0.03906 FastRCNN total loss: 0.1079 L1 loss: 0.0000e+00 L2 loss: 0.5682 Learning rate: 0.0004 Mask loss: 0.11261 RPN box loss: 0.00995 RPN score loss: 0.0016 RPN total loss: 0.01156 Total loss: 0.80027 timestamp: 1655058173.5578573 iteration: 63040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16157 FastRCNN class loss: 0.07594 FastRCNN total loss: 0.23751 L1 loss: 0.0000e+00 L2 loss: 0.56819 Learning rate: 0.0004 Mask loss: 0.1311 RPN box loss: 0.02137 RPN score loss: 0.0054 RPN total loss: 0.02677 Total loss: 0.96357 timestamp: 1655058176.860027 iteration: 63045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16352 FastRCNN class loss: 0.07391 FastRCNN total loss: 0.23743 L1 loss: 0.0000e+00 L2 loss: 0.56819 Learning rate: 0.0004 Mask loss: 0.13841 RPN box loss: 0.00925 RPN score loss: 0.0025 RPN total loss: 0.01175 Total loss: 0.95578 timestamp: 1655058180.1151726 iteration: 63050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13224 FastRCNN class loss: 0.06995 FastRCNN total loss: 0.2022 L1 loss: 0.0000e+00 L2 loss: 0.56819 Learning rate: 0.0004 Mask loss: 0.15512 RPN box loss: 0.0141 RPN score loss: 0.01256 RPN total loss: 0.02666 Total loss: 0.95217 timestamp: 1655058183.4103131 iteration: 63055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07697 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.14926 L1 loss: 0.0000e+00 L2 loss: 0.56819 Learning rate: 0.0004 Mask loss: 0.119 RPN box loss: 0.00906 RPN score loss: 0.00716 RPN total loss: 0.01622 Total loss: 0.85267 timestamp: 1655058186.661511 iteration: 63060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18249 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.24203 L1 loss: 0.0000e+00 L2 loss: 0.56819 Learning rate: 0.0004 Mask loss: 0.11652 RPN box loss: 0.01177 RPN score loss: 0.00678 RPN total loss: 0.01855 Total loss: 0.94529 timestamp: 1655058189.9383652 iteration: 63065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10087 FastRCNN class loss: 0.05094 FastRCNN total loss: 0.15181 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.13089 RPN box loss: 0.00619 RPN score loss: 0.00124 RPN total loss: 0.00743 Total loss: 0.85832 timestamp: 1655058193.1903214 iteration: 63070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1158 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.20621 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.14315 RPN box loss: 0.01036 RPN score loss: 0.01254 RPN total loss: 0.0229 Total loss: 0.94045 timestamp: 1655058196.3982692 iteration: 63075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11115 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.1788 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.13366 RPN box loss: 0.01299 RPN score loss: 0.00284 RPN total loss: 0.01583 Total loss: 0.89647 timestamp: 1655058199.7054613 iteration: 63080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10846 FastRCNN class loss: 0.04121 FastRCNN total loss: 0.14967 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.14322 RPN box loss: 0.00898 RPN score loss: 0.00486 RPN total loss: 0.01384 Total loss: 0.87491 timestamp: 1655058202.9450786 iteration: 63085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13459 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.20378 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.1517 RPN box loss: 0.02415 RPN score loss: 0.00536 RPN total loss: 0.02951 Total loss: 0.95318 timestamp: 1655058206.1895742 iteration: 63090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06877 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.1176 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.1516 RPN box loss: 0.01292 RPN score loss: 0.00293 RPN total loss: 0.01585 Total loss: 0.85322 timestamp: 1655058209.4610476 iteration: 63095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11107 FastRCNN class loss: 0.08336 FastRCNN total loss: 0.19443 L1 loss: 0.0000e+00 L2 loss: 0.56818 Learning rate: 0.0004 Mask loss: 0.2633 RPN box loss: 0.01208 RPN score loss: 0.0024 RPN total loss: 0.01448 Total loss: 1.04039 timestamp: 1655058212.7079148 iteration: 63100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03974 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.11031 L1 loss: 0.0000e+00 L2 loss: 0.56817 Learning rate: 0.0004 Mask loss: 0.15202 RPN box loss: 0.01006 RPN score loss: 0.00858 RPN total loss: 0.01864 Total loss: 0.84914 timestamp: 1655058216.0216527 iteration: 63105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12592 FastRCNN class loss: 0.11423 FastRCNN total loss: 0.24015 L1 loss: 0.0000e+00 L2 loss: 0.56817 Learning rate: 0.0004 Mask loss: 0.17289 RPN box loss: 0.02248 RPN score loss: 0.00937 RPN total loss: 0.03185 Total loss: 1.01306 timestamp: 1655058219.2837734 iteration: 63110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12824 FastRCNN class loss: 0.10949 FastRCNN total loss: 0.23773 L1 loss: 0.0000e+00 L2 loss: 0.56817 Learning rate: 0.0004 Mask loss: 0.15293 RPN box loss: 0.01961 RPN score loss: 0.00408 RPN total loss: 0.0237 Total loss: 0.98252 timestamp: 1655058222.5221238 iteration: 63115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11828 FastRCNN class loss: 0.07166 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 0.56817 Learning rate: 0.0004 Mask loss: 0.1375 RPN box loss: 0.02525 RPN score loss: 0.00896 RPN total loss: 0.03421 Total loss: 0.92982 timestamp: 1655058225.7896955 iteration: 63120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10925 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.1868 L1 loss: 0.0000e+00 L2 loss: 0.56817 Learning rate: 0.0004 Mask loss: 0.11628 RPN box loss: 0.00839 RPN score loss: 0.00637 RPN total loss: 0.01476 Total loss: 0.88601 timestamp: 1655058229.0230138 iteration: 63125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07626 FastRCNN class loss: 0.07279 FastRCNN total loss: 0.14905 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.10061 RPN box loss: 0.01133 RPN score loss: 0.00248 RPN total loss: 0.01381 Total loss: 0.83164 timestamp: 1655058232.278008 iteration: 63130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03965 FastRCNN class loss: 0.02951 FastRCNN total loss: 0.06916 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.08971 RPN box loss: 0.02577 RPN score loss: 0.00085 RPN total loss: 0.02663 Total loss: 0.75367 timestamp: 1655058235.5520105 iteration: 63135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07531 FastRCNN class loss: 0.05112 FastRCNN total loss: 0.12643 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.144 RPN box loss: 0.00995 RPN score loss: 0.01217 RPN total loss: 0.02211 Total loss: 0.8607 timestamp: 1655058238.8789885 iteration: 63140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.08259 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.17849 RPN box loss: 0.02647 RPN score loss: 0.01506 RPN total loss: 0.04153 Total loss: 0.97938 timestamp: 1655058242.0813298 iteration: 63145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11788 FastRCNN class loss: 0.08599 FastRCNN total loss: 0.20387 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.17257 RPN box loss: 0.01267 RPN score loss: 0.00957 RPN total loss: 0.02223 Total loss: 0.96683 timestamp: 1655058245.3271616 iteration: 63150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11464 FastRCNN class loss: 0.0891 FastRCNN total loss: 0.20374 L1 loss: 0.0000e+00 L2 loss: 0.56816 Learning rate: 0.0004 Mask loss: 0.14863 RPN box loss: 0.00968 RPN score loss: 0.01109 RPN total loss: 0.02077 Total loss: 0.9413 timestamp: 1655058248.6225321 iteration: 63155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11117 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.1883 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.14421 RPN box loss: 0.00905 RPN score loss: 0.00472 RPN total loss: 0.01377 Total loss: 0.91443 timestamp: 1655058251.8195372 iteration: 63160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.09887 FastRCNN total loss: 0.17457 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.15585 RPN box loss: 0.0239 RPN score loss: 0.01452 RPN total loss: 0.03841 Total loss: 0.93699 timestamp: 1655058255.1165226 iteration: 63165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10731 FastRCNN class loss: 0.07523 FastRCNN total loss: 0.18254 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.15421 RPN box loss: 0.00692 RPN score loss: 0.00772 RPN total loss: 0.01464 Total loss: 0.91954 timestamp: 1655058258.429955 iteration: 63170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12901 FastRCNN class loss: 0.10565 FastRCNN total loss: 0.23466 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.14368 RPN box loss: 0.02498 RPN score loss: 0.01187 RPN total loss: 0.03684 Total loss: 0.98334 timestamp: 1655058261.728139 iteration: 63175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06032 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.13313 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.14282 RPN box loss: 0.02252 RPN score loss: 0.00608 RPN total loss: 0.0286 Total loss: 0.87269 timestamp: 1655058265.0048857 iteration: 63180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09013 FastRCNN class loss: 0.09902 FastRCNN total loss: 0.18914 L1 loss: 0.0000e+00 L2 loss: 0.56815 Learning rate: 0.0004 Mask loss: 0.19984 RPN box loss: 0.0166 RPN score loss: 0.00642 RPN total loss: 0.02302 Total loss: 0.98014 timestamp: 1655058268.2809582 iteration: 63185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13993 FastRCNN class loss: 0.11293 FastRCNN total loss: 0.25286 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.16838 RPN box loss: 0.02637 RPN score loss: 0.00704 RPN total loss: 0.03341 Total loss: 1.0228 timestamp: 1655058271.5488834 iteration: 63190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14791 FastRCNN class loss: 0.13207 FastRCNN total loss: 0.27998 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.17271 RPN box loss: 0.03286 RPN score loss: 0.0138 RPN total loss: 0.04666 Total loss: 1.0675 timestamp: 1655058274.7723203 iteration: 63195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12531 FastRCNN class loss: 0.10205 FastRCNN total loss: 0.22736 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.13943 RPN box loss: 0.0083 RPN score loss: 0.00349 RPN total loss: 0.01179 Total loss: 0.94671 timestamp: 1655058278.0712752 iteration: 63200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13007 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.21284 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.17375 RPN box loss: 0.02616 RPN score loss: 0.00513 RPN total loss: 0.03128 Total loss: 0.98602 timestamp: 1655058281.348645 iteration: 63205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10985 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.17268 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.18484 RPN box loss: 0.01227 RPN score loss: 0.00272 RPN total loss: 0.015 Total loss: 0.94066 timestamp: 1655058284.7323287 iteration: 63210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05097 FastRCNN class loss: 0.06064 FastRCNN total loss: 0.1116 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.10095 RPN box loss: 0.0032 RPN score loss: 0.0013 RPN total loss: 0.0045 Total loss: 0.78519 timestamp: 1655058287.9876442 iteration: 63215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12847 FastRCNN class loss: 0.11325 FastRCNN total loss: 0.24172 L1 loss: 0.0000e+00 L2 loss: 0.56814 Learning rate: 0.0004 Mask loss: 0.14627 RPN box loss: 0.01711 RPN score loss: 0.00316 RPN total loss: 0.02027 Total loss: 0.97639 timestamp: 1655058291.2294104 iteration: 63220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11921 FastRCNN class loss: 0.09787 FastRCNN total loss: 0.21708 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.20624 RPN box loss: 0.02071 RPN score loss: 0.0081 RPN total loss: 0.02881 Total loss: 1.02027 timestamp: 1655058294.5084534 iteration: 63225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08381 FastRCNN class loss: 0.04593 FastRCNN total loss: 0.12973 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.13968 RPN box loss: 0.01138 RPN score loss: 0.0029 RPN total loss: 0.01427 Total loss: 0.85182 timestamp: 1655058297.7555177 iteration: 63230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.16874 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.09157 RPN box loss: 0.0068 RPN score loss: 0.00278 RPN total loss: 0.00958 Total loss: 0.83802 timestamp: 1655058300.9985232 iteration: 63235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0703 FastRCNN class loss: 0.0671 FastRCNN total loss: 0.13739 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.18785 RPN box loss: 0.02644 RPN score loss: 0.00565 RPN total loss: 0.0321 Total loss: 0.92547 timestamp: 1655058304.28369 iteration: 63240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.094 FastRCNN class loss: 0.08167 FastRCNN total loss: 0.17567 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.20244 RPN box loss: 0.01177 RPN score loss: 0.00861 RPN total loss: 0.02038 Total loss: 0.96661 timestamp: 1655058307.5574539 iteration: 63245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08032 FastRCNN class loss: 0.06872 FastRCNN total loss: 0.14904 L1 loss: 0.0000e+00 L2 loss: 0.56813 Learning rate: 0.0004 Mask loss: 0.10231 RPN box loss: 0.01277 RPN score loss: 0.0112 RPN total loss: 0.02397 Total loss: 0.84344 timestamp: 1655058310.8189912 iteration: 63250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12846 FastRCNN class loss: 0.09545 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 0.56812 Learning rate: 0.0004 Mask loss: 0.13875 RPN box loss: 0.02101 RPN score loss: 0.00752 RPN total loss: 0.02853 Total loss: 0.95931 timestamp: 1655058314.1507292 iteration: 63255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12572 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.17814 L1 loss: 0.0000e+00 L2 loss: 0.56812 Learning rate: 0.0004 Mask loss: 0.15044 RPN box loss: 0.00701 RPN score loss: 0.00709 RPN total loss: 0.0141 Total loss: 0.9108 timestamp: 1655058317.4340665 iteration: 63260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06925 FastRCNN class loss: 0.05584 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.56812 Learning rate: 0.0004 Mask loss: 0.09404 RPN box loss: 0.01069 RPN score loss: 0.0023 RPN total loss: 0.013 Total loss: 0.80025 timestamp: 1655058320.6853704 iteration: 63265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07834 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.12672 L1 loss: 0.0000e+00 L2 loss: 0.56812 Learning rate: 0.0004 Mask loss: 0.11968 RPN box loss: 0.01406 RPN score loss: 0.00146 RPN total loss: 0.01552 Total loss: 0.83003 timestamp: 1655058323.9508424 iteration: 63270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08297 FastRCNN class loss: 0.0889 FastRCNN total loss: 0.17187 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.16556 RPN box loss: 0.01443 RPN score loss: 0.00861 RPN total loss: 0.02304 Total loss: 0.92858 timestamp: 1655058327.3432913 iteration: 63275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11712 FastRCNN class loss: 0.0721 FastRCNN total loss: 0.18922 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.19499 RPN box loss: 0.02305 RPN score loss: 0.0094 RPN total loss: 0.03245 Total loss: 0.98478 timestamp: 1655058330.571666 iteration: 63280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06096 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.13329 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.09833 RPN box loss: 0.00658 RPN score loss: 0.0064 RPN total loss: 0.01298 Total loss: 0.81271 timestamp: 1655058333.9452698 iteration: 63285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07182 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.13467 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.14836 RPN box loss: 0.02222 RPN score loss: 0.00386 RPN total loss: 0.02608 Total loss: 0.87721 timestamp: 1655058337.2134597 iteration: 63290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08867 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.16628 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.14576 RPN box loss: 0.0206 RPN score loss: 0.01355 RPN total loss: 0.03415 Total loss: 0.9143 timestamp: 1655058340.5289946 iteration: 63295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11148 FastRCNN class loss: 0.0844 FastRCNN total loss: 0.19588 L1 loss: 0.0000e+00 L2 loss: 0.56811 Learning rate: 0.0004 Mask loss: 0.12438 RPN box loss: 0.0093 RPN score loss: 0.00406 RPN total loss: 0.01336 Total loss: 0.90173 timestamp: 1655058343.8100667 iteration: 63300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10108 FastRCNN class loss: 0.08529 FastRCNN total loss: 0.18637 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.11341 RPN box loss: 0.00992 RPN score loss: 0.0068 RPN total loss: 0.01672 Total loss: 0.88461 timestamp: 1655058347.0887604 iteration: 63305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1184 FastRCNN class loss: 0.10715 FastRCNN total loss: 0.22555 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.15552 RPN box loss: 0.01421 RPN score loss: 0.00823 RPN total loss: 0.02244 Total loss: 0.97161 timestamp: 1655058350.3515775 iteration: 63310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1118 FastRCNN class loss: 0.08715 FastRCNN total loss: 0.19895 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.21857 RPN box loss: 0.02913 RPN score loss: 0.00312 RPN total loss: 0.03224 Total loss: 1.01786 timestamp: 1655058353.5572503 iteration: 63315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09889 FastRCNN class loss: 0.09362 FastRCNN total loss: 0.19251 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.17302 RPN box loss: 0.01086 RPN score loss: 0.00175 RPN total loss: 0.01261 Total loss: 0.94625 timestamp: 1655058356.8169584 iteration: 63320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16175 FastRCNN class loss: 0.09457 FastRCNN total loss: 0.25632 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.16029 RPN box loss: 0.00405 RPN score loss: 0.00675 RPN total loss: 0.01081 Total loss: 0.99552 timestamp: 1655058360.0622923 iteration: 63325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11903 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.18986 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.16681 RPN box loss: 0.00644 RPN score loss: 0.00135 RPN total loss: 0.00779 Total loss: 0.93256 timestamp: 1655058363.300641 iteration: 63330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13569 FastRCNN class loss: 0.0806 FastRCNN total loss: 0.21629 L1 loss: 0.0000e+00 L2 loss: 0.5681 Learning rate: 0.0004 Mask loss: 0.13361 RPN box loss: 0.01376 RPN score loss: 0.00444 RPN total loss: 0.0182 Total loss: 0.93619 timestamp: 1655058366.65372 iteration: 63335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12665 FastRCNN class loss: 0.06714 FastRCNN total loss: 0.19379 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.14018 RPN box loss: 0.01081 RPN score loss: 0.00684 RPN total loss: 0.01765 Total loss: 0.91971 timestamp: 1655058369.8499231 iteration: 63340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07252 FastRCNN class loss: 0.05646 FastRCNN total loss: 0.12897 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.11851 RPN box loss: 0.00659 RPN score loss: 0.00459 RPN total loss: 0.01117 Total loss: 0.82675 timestamp: 1655058373.1397665 iteration: 63345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13822 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.20614 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.13929 RPN box loss: 0.00898 RPN score loss: 0.00567 RPN total loss: 0.01466 Total loss: 0.92818 timestamp: 1655058376.4143498 iteration: 63350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.09329 FastRCNN total loss: 0.19313 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.13982 RPN box loss: 0.01677 RPN score loss: 0.0065 RPN total loss: 0.02327 Total loss: 0.92431 timestamp: 1655058379.7353156 iteration: 63355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10896 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.17878 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.2686 RPN box loss: 0.03417 RPN score loss: 0.00999 RPN total loss: 0.04416 Total loss: 1.05962 timestamp: 1655058382.980932 iteration: 63360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11938 FastRCNN class loss: 0.09863 FastRCNN total loss: 0.21802 L1 loss: 0.0000e+00 L2 loss: 0.56809 Learning rate: 0.0004 Mask loss: 0.14558 RPN box loss: 0.02893 RPN score loss: 0.00808 RPN total loss: 0.037 Total loss: 0.96869 timestamp: 1655058386.2352927 iteration: 63365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08933 FastRCNN class loss: 0.09983 FastRCNN total loss: 0.18916 L1 loss: 0.0000e+00 L2 loss: 0.56808 Learning rate: 0.0004 Mask loss: 0.18665 RPN box loss: 0.00964 RPN score loss: 0.00584 RPN total loss: 0.01548 Total loss: 0.95937 timestamp: 1655058389.4212747 iteration: 63370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07794 FastRCNN class loss: 0.0963 FastRCNN total loss: 0.17424 L1 loss: 0.0000e+00 L2 loss: 0.56808 Learning rate: 0.0004 Mask loss: 0.19156 RPN box loss: 0.01731 RPN score loss: 0.00744 RPN total loss: 0.02475 Total loss: 0.95863 timestamp: 1655058392.7425401 iteration: 63375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09233 FastRCNN class loss: 0.06198 FastRCNN total loss: 0.15432 L1 loss: 0.0000e+00 L2 loss: 0.56808 Learning rate: 0.0004 Mask loss: 0.11626 RPN box loss: 0.01754 RPN score loss: 0.00149 RPN total loss: 0.01903 Total loss: 0.85768 timestamp: 1655058396.029072 iteration: 63380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09822 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.14603 L1 loss: 0.0000e+00 L2 loss: 0.56808 Learning rate: 0.0004 Mask loss: 0.12235 RPN box loss: 0.00619 RPN score loss: 0.00188 RPN total loss: 0.00806 Total loss: 0.84452 timestamp: 1655058399.312502 iteration: 63385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08079 FastRCNN class loss: 0.05498 FastRCNN total loss: 0.13577 L1 loss: 0.0000e+00 L2 loss: 0.56808 Learning rate: 0.0004 Mask loss: 0.11793 RPN box loss: 0.00542 RPN score loss: 0.0051 RPN total loss: 0.01052 Total loss: 0.8323 timestamp: 1655058402.5702474 iteration: 63390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10117 FastRCNN class loss: 0.07471 FastRCNN total loss: 0.17588 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.13259 RPN box loss: 0.00707 RPN score loss: 0.00574 RPN total loss: 0.01281 Total loss: 0.88936 timestamp: 1655058405.849232 iteration: 63395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12484 FastRCNN class loss: 0.1024 FastRCNN total loss: 0.22724 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.2274 RPN box loss: 0.02576 RPN score loss: 0.00316 RPN total loss: 0.02892 Total loss: 1.05164 timestamp: 1655058409.16171 iteration: 63400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09921 FastRCNN class loss: 0.06117 FastRCNN total loss: 0.16038 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.18951 RPN box loss: 0.0117 RPN score loss: 0.00147 RPN total loss: 0.01317 Total loss: 0.93113 timestamp: 1655058412.4039104 iteration: 63405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05559 FastRCNN class loss: 0.05616 FastRCNN total loss: 0.11175 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.12617 RPN box loss: 0.04316 RPN score loss: 0.00574 RPN total loss: 0.0489 Total loss: 0.8549 timestamp: 1655058415.725735 iteration: 63410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06527 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.11198 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.12673 RPN box loss: 0.01007 RPN score loss: 0.00395 RPN total loss: 0.01402 Total loss: 0.82079 timestamp: 1655058418.9396915 iteration: 63415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07795 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.13777 L1 loss: 0.0000e+00 L2 loss: 0.56807 Learning rate: 0.0004 Mask loss: 0.14827 RPN box loss: 0.01553 RPN score loss: 0.01283 RPN total loss: 0.02836 Total loss: 0.88246 timestamp: 1655058422.2075999 iteration: 63420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06513 FastRCNN class loss: 0.06532 FastRCNN total loss: 0.13046 L1 loss: 0.0000e+00 L2 loss: 0.56806 Learning rate: 0.0004 Mask loss: 0.2451 RPN box loss: 0.00934 RPN score loss: 0.00395 RPN total loss: 0.01329 Total loss: 0.95691 timestamp: 1655058425.4724853 iteration: 63425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12318 FastRCNN class loss: 0.0912 FastRCNN total loss: 0.21438 L1 loss: 0.0000e+00 L2 loss: 0.56806 Learning rate: 0.0004 Mask loss: 0.19001 RPN box loss: 0.01351 RPN score loss: 0.00908 RPN total loss: 0.02259 Total loss: 0.99504 timestamp: 1655058428.7578995 iteration: 63430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10654 FastRCNN class loss: 0.04976 FastRCNN total loss: 0.15629 L1 loss: 0.0000e+00 L2 loss: 0.56806 Learning rate: 0.0004 Mask loss: 0.11105 RPN box loss: 0.02101 RPN score loss: 0.00467 RPN total loss: 0.02568 Total loss: 0.86108 timestamp: 1655058432.0264208 iteration: 63435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10819 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.18871 L1 loss: 0.0000e+00 L2 loss: 0.56806 Learning rate: 0.0004 Mask loss: 0.1172 RPN box loss: 0.00672 RPN score loss: 0.01102 RPN total loss: 0.01774 Total loss: 0.89172 timestamp: 1655058435.3019466 iteration: 63440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09793 FastRCNN class loss: 0.07325 FastRCNN total loss: 0.17117 L1 loss: 0.0000e+00 L2 loss: 0.56806 Learning rate: 0.0004 Mask loss: 0.18152 RPN box loss: 0.01535 RPN score loss: 0.00225 RPN total loss: 0.0176 Total loss: 0.93836 timestamp: 1655058438.6169481 iteration: 63445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07995 FastRCNN class loss: 0.06428 FastRCNN total loss: 0.14423 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.17431 RPN box loss: 0.00717 RPN score loss: 0.00509 RPN total loss: 0.01226 Total loss: 0.89886 timestamp: 1655058441.8734481 iteration: 63450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08272 FastRCNN class loss: 0.03474 FastRCNN total loss: 0.11746 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.11549 RPN box loss: 0.00245 RPN score loss: 0.00102 RPN total loss: 0.00347 Total loss: 0.80447 timestamp: 1655058445.1923966 iteration: 63455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08384 FastRCNN class loss: 0.05019 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.09327 RPN box loss: 0.01165 RPN score loss: 0.00276 RPN total loss: 0.01442 Total loss: 0.80977 timestamp: 1655058448.4227812 iteration: 63460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.06187 FastRCNN total loss: 0.14279 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.13746 RPN box loss: 0.01293 RPN score loss: 0.00496 RPN total loss: 0.01789 Total loss: 0.86619 timestamp: 1655058451.7149675 iteration: 63465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11794 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.19881 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.18815 RPN box loss: 0.01437 RPN score loss: 0.00642 RPN total loss: 0.02079 Total loss: 0.9758 timestamp: 1655058454.9998276 iteration: 63470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12496 FastRCNN class loss: 0.07075 FastRCNN total loss: 0.19572 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.1381 RPN box loss: 0.00956 RPN score loss: 0.00386 RPN total loss: 0.01342 Total loss: 0.91528 timestamp: 1655058458.2590706 iteration: 63475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09876 FastRCNN class loss: 0.08769 FastRCNN total loss: 0.18644 L1 loss: 0.0000e+00 L2 loss: 0.56805 Learning rate: 0.0004 Mask loss: 0.21228 RPN box loss: 0.02491 RPN score loss: 0.00626 RPN total loss: 0.03117 Total loss: 0.99794 timestamp: 1655058461.5138898 iteration: 63480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13478 FastRCNN class loss: 0.09767 FastRCNN total loss: 0.23245 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.14693 RPN box loss: 0.02345 RPN score loss: 0.00979 RPN total loss: 0.03325 Total loss: 0.98067 timestamp: 1655058464.782859 iteration: 63485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07626 FastRCNN class loss: 0.07359 FastRCNN total loss: 0.14986 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.12506 RPN box loss: 0.01356 RPN score loss: 0.00718 RPN total loss: 0.02075 Total loss: 0.86371 timestamp: 1655058468.0480072 iteration: 63490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08537 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.15292 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.13229 RPN box loss: 0.00615 RPN score loss: 0.00318 RPN total loss: 0.00934 Total loss: 0.86259 timestamp: 1655058471.305975 iteration: 63495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.1405 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.09996 RPN box loss: 0.00659 RPN score loss: 0.0054 RPN total loss: 0.01199 Total loss: 0.82049 timestamp: 1655058474.5695424 iteration: 63500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06336 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.12474 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.14485 RPN box loss: 0.01516 RPN score loss: 0.01091 RPN total loss: 0.02607 Total loss: 0.8637 timestamp: 1655058477.8291388 iteration: 63505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07563 FastRCNN class loss: 0.04908 FastRCNN total loss: 0.12471 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.1081 RPN box loss: 0.01277 RPN score loss: 0.00225 RPN total loss: 0.01503 Total loss: 0.81587 timestamp: 1655058481.042108 iteration: 63510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14313 FastRCNN class loss: 0.10471 FastRCNN total loss: 0.24784 L1 loss: 0.0000e+00 L2 loss: 0.56804 Learning rate: 0.0004 Mask loss: 0.15925 RPN box loss: 0.03602 RPN score loss: 0.01603 RPN total loss: 0.05206 Total loss: 1.02718 timestamp: 1655058484.2999492 iteration: 63515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09572 FastRCNN class loss: 0.07463 FastRCNN total loss: 0.17035 L1 loss: 0.0000e+00 L2 loss: 0.56803 Learning rate: 0.0004 Mask loss: 0.15462 RPN box loss: 0.00955 RPN score loss: 0.00155 RPN total loss: 0.0111 Total loss: 0.9041 timestamp: 1655058487.5421226 iteration: 63520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06393 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.11384 L1 loss: 0.0000e+00 L2 loss: 0.56803 Learning rate: 0.0004 Mask loss: 0.16862 RPN box loss: 0.01571 RPN score loss: 0.00155 RPN total loss: 0.01726 Total loss: 0.86775 timestamp: 1655058490.8222418 iteration: 63525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08502 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.1464 L1 loss: 0.0000e+00 L2 loss: 0.56803 Learning rate: 0.0004 Mask loss: 0.10286 RPN box loss: 0.01728 RPN score loss: 0.00311 RPN total loss: 0.02039 Total loss: 0.83768 timestamp: 1655058494.0639746 iteration: 63530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.56803 Learning rate: 0.0004 Mask loss: 0.15248 RPN box loss: 0.00865 RPN score loss: 0.00705 RPN total loss: 0.0157 Total loss: 0.90668 timestamp: 1655058497.255784 iteration: 63535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.09853 FastRCNN total loss: 0.19142 L1 loss: 0.0000e+00 L2 loss: 0.56803 Learning rate: 0.0004 Mask loss: 0.1247 RPN box loss: 0.02438 RPN score loss: 0.00956 RPN total loss: 0.03394 Total loss: 0.91808 timestamp: 1655058500.5076656 iteration: 63540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11112 FastRCNN class loss: 0.10038 FastRCNN total loss: 0.2115 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.17703 RPN box loss: 0.01751 RPN score loss: 0.00238 RPN total loss: 0.01989 Total loss: 0.97645 timestamp: 1655058503.7856047 iteration: 63545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07601 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.13131 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.11493 RPN box loss: 0.02592 RPN score loss: 0.00285 RPN total loss: 0.02877 Total loss: 0.84303 timestamp: 1655058507.0026095 iteration: 63550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.06465 FastRCNN total loss: 0.16245 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.12872 RPN box loss: 0.01089 RPN score loss: 0.00313 RPN total loss: 0.01402 Total loss: 0.87321 timestamp: 1655058510.2675753 iteration: 63555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07015 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.16518 RPN box loss: 0.02345 RPN score loss: 0.00234 RPN total loss: 0.02579 Total loss: 0.88643 timestamp: 1655058513.5453467 iteration: 63560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08719 FastRCNN class loss: 0.05363 FastRCNN total loss: 0.14082 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.10887 RPN box loss: 0.0074 RPN score loss: 0.00602 RPN total loss: 0.01342 Total loss: 0.83113 timestamp: 1655058516.8185673 iteration: 63565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11488 FastRCNN class loss: 0.08889 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.12646 RPN box loss: 0.01788 RPN score loss: 0.00399 RPN total loss: 0.02187 Total loss: 0.92011 timestamp: 1655058520.061065 iteration: 63570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08466 FastRCNN class loss: 0.06498 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.56802 Learning rate: 0.0004 Mask loss: 0.13311 RPN box loss: 0.02667 RPN score loss: 0.00418 RPN total loss: 0.03085 Total loss: 0.88162 timestamp: 1655058523.3347647 iteration: 63575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06996 FastRCNN class loss: 0.05649 FastRCNN total loss: 0.12645 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.10543 RPN box loss: 0.01997 RPN score loss: 0.00315 RPN total loss: 0.02312 Total loss: 0.82302 timestamp: 1655058526.629463 iteration: 63580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.0774 FastRCNN total loss: 0.19153 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.13697 RPN box loss: 0.02441 RPN score loss: 0.00497 RPN total loss: 0.02937 Total loss: 0.92588 timestamp: 1655058529.8981366 iteration: 63585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09827 FastRCNN class loss: 0.06871 FastRCNN total loss: 0.16698 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.09511 RPN box loss: 0.03199 RPN score loss: 0.00272 RPN total loss: 0.03471 Total loss: 0.86482 timestamp: 1655058533.0716994 iteration: 63590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06792 FastRCNN class loss: 0.04651 FastRCNN total loss: 0.11443 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.16944 RPN box loss: 0.00594 RPN score loss: 0.00676 RPN total loss: 0.0127 Total loss: 0.86459 timestamp: 1655058536.2851052 iteration: 63595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1149 FastRCNN class loss: 0.12192 FastRCNN total loss: 0.23682 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.22829 RPN box loss: 0.01674 RPN score loss: 0.01214 RPN total loss: 0.02888 Total loss: 1.062 timestamp: 1655058539.5509322 iteration: 63600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.086 FastRCNN class loss: 0.0631 FastRCNN total loss: 0.1491 L1 loss: 0.0000e+00 L2 loss: 0.56801 Learning rate: 0.0004 Mask loss: 0.18253 RPN box loss: 0.01694 RPN score loss: 0.01124 RPN total loss: 0.02818 Total loss: 0.92782 timestamp: 1655058542.852566 iteration: 63605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0617 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.10983 L1 loss: 0.0000e+00 L2 loss: 0.568 Learning rate: 0.0004 Mask loss: 0.06131 RPN box loss: 0.01354 RPN score loss: 0.00274 RPN total loss: 0.01629 Total loss: 0.75543 timestamp: 1655058546.0976682 iteration: 63610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07453 FastRCNN class loss: 0.05168 FastRCNN total loss: 0.12621 L1 loss: 0.0000e+00 L2 loss: 0.568 Learning rate: 0.0004 Mask loss: 0.13996 RPN box loss: 0.00902 RPN score loss: 0.00144 RPN total loss: 0.01046 Total loss: 0.84464 timestamp: 1655058549.3999896 iteration: 63615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11979 FastRCNN class loss: 0.1065 FastRCNN total loss: 0.22629 L1 loss: 0.0000e+00 L2 loss: 0.568 Learning rate: 0.0004 Mask loss: 0.15825 RPN box loss: 0.00883 RPN score loss: 0.00667 RPN total loss: 0.0155 Total loss: 0.96805 timestamp: 1655058552.715032 iteration: 63620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.19937 L1 loss: 0.0000e+00 L2 loss: 0.568 Learning rate: 0.0004 Mask loss: 0.12925 RPN box loss: 0.0132 RPN score loss: 0.00506 RPN total loss: 0.01825 Total loss: 0.91487 timestamp: 1655058556.0110455 iteration: 63625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10648 FastRCNN class loss: 0.06178 FastRCNN total loss: 0.16826 L1 loss: 0.0000e+00 L2 loss: 0.568 Learning rate: 0.0004 Mask loss: 0.12987 RPN box loss: 0.01903 RPN score loss: 0.00181 RPN total loss: 0.02084 Total loss: 0.88697 timestamp: 1655058559.2772164 iteration: 63630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.1618 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.14859 RPN box loss: 0.00894 RPN score loss: 0.00521 RPN total loss: 0.01415 Total loss: 0.89254 timestamp: 1655058562.5783324 iteration: 63635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16012 FastRCNN class loss: 0.11926 FastRCNN total loss: 0.27938 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.19645 RPN box loss: 0.0488 RPN score loss: 0.01407 RPN total loss: 0.06287 Total loss: 1.1067 timestamp: 1655058565.7423484 iteration: 63640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07981 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.13877 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.12521 RPN box loss: 0.01661 RPN score loss: 0.00096 RPN total loss: 0.01757 Total loss: 0.84954 timestamp: 1655058569.0981371 iteration: 63645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08238 FastRCNN class loss: 0.08823 FastRCNN total loss: 0.1706 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.13461 RPN box loss: 0.02164 RPN score loss: 0.01478 RPN total loss: 0.03642 Total loss: 0.90963 timestamp: 1655058572.334553 iteration: 63650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0726 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.1211 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.11997 RPN box loss: 0.00576 RPN score loss: 0.00865 RPN total loss: 0.01441 Total loss: 0.82347 timestamp: 1655058575.582093 iteration: 63655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11014 FastRCNN class loss: 0.10536 FastRCNN total loss: 0.2155 L1 loss: 0.0000e+00 L2 loss: 0.56799 Learning rate: 0.0004 Mask loss: 0.18214 RPN box loss: 0.02492 RPN score loss: 0.00605 RPN total loss: 0.03097 Total loss: 0.9966 timestamp: 1655058578.896708 iteration: 63660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0988 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.18147 L1 loss: 0.0000e+00 L2 loss: 0.56798 Learning rate: 0.0004 Mask loss: 0.11833 RPN box loss: 0.0144 RPN score loss: 0.01905 RPN total loss: 0.03345 Total loss: 0.90123 timestamp: 1655058582.2400084 iteration: 63665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.09766 FastRCNN total loss: 0.22544 L1 loss: 0.0000e+00 L2 loss: 0.56798 Learning rate: 0.0004 Mask loss: 0.12222 RPN box loss: 0.01108 RPN score loss: 0.00657 RPN total loss: 0.01765 Total loss: 0.93329 timestamp: 1655058585.553918 iteration: 63670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11379 FastRCNN class loss: 0.04756 FastRCNN total loss: 0.16135 L1 loss: 0.0000e+00 L2 loss: 0.56798 Learning rate: 0.0004 Mask loss: 0.12438 RPN box loss: 0.00959 RPN score loss: 0.00316 RPN total loss: 0.01275 Total loss: 0.86646 timestamp: 1655058588.8222904 iteration: 63675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.11814 FastRCNN total loss: 0.21276 L1 loss: 0.0000e+00 L2 loss: 0.56798 Learning rate: 0.0004 Mask loss: 0.14897 RPN box loss: 0.01361 RPN score loss: 0.0061 RPN total loss: 0.01971 Total loss: 0.94942 timestamp: 1655058592.14509 iteration: 63680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05269 FastRCNN class loss: 0.04196 FastRCNN total loss: 0.09465 L1 loss: 0.0000e+00 L2 loss: 0.56798 Learning rate: 0.0004 Mask loss: 0.14791 RPN box loss: 0.01133 RPN score loss: 0.00471 RPN total loss: 0.01605 Total loss: 0.82658 timestamp: 1655058595.3712935 iteration: 63685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.14257 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.13738 RPN box loss: 0.01518 RPN score loss: 0.00948 RPN total loss: 0.02467 Total loss: 0.87259 timestamp: 1655058598.5835023 iteration: 63690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13087 FastRCNN class loss: 0.10658 FastRCNN total loss: 0.23745 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.1652 RPN box loss: 0.01798 RPN score loss: 0.00142 RPN total loss: 0.0194 Total loss: 0.99003 timestamp: 1655058601.8524115 iteration: 63695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08703 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.14067 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.10456 RPN box loss: 0.00619 RPN score loss: 0.00388 RPN total loss: 0.01007 Total loss: 0.82328 timestamp: 1655058605.1588707 iteration: 63700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11463 FastRCNN class loss: 0.10611 FastRCNN total loss: 0.22074 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.16863 RPN box loss: 0.0195 RPN score loss: 0.00965 RPN total loss: 0.02915 Total loss: 0.98649 timestamp: 1655058608.512941 iteration: 63705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06599 FastRCNN class loss: 0.04084 FastRCNN total loss: 0.10684 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.08894 RPN box loss: 0.00778 RPN score loss: 0.00335 RPN total loss: 0.01113 Total loss: 0.77487 timestamp: 1655058611.7556858 iteration: 63710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13638 FastRCNN class loss: 0.07454 FastRCNN total loss: 0.21092 L1 loss: 0.0000e+00 L2 loss: 0.56797 Learning rate: 0.0004 Mask loss: 0.21425 RPN box loss: 0.01314 RPN score loss: 0.00544 RPN total loss: 0.01858 Total loss: 1.01171 timestamp: 1655058614.9837523 iteration: 63715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08319 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.14156 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.12135 RPN box loss: 0.01093 RPN score loss: 0.0071 RPN total loss: 0.01802 Total loss: 0.84889 timestamp: 1655058618.2287383 iteration: 63720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09706 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.17375 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.12526 RPN box loss: 0.00851 RPN score loss: 0.00473 RPN total loss: 0.01324 Total loss: 0.8802 timestamp: 1655058621.509374 iteration: 63725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08787 FastRCNN class loss: 0.07344 FastRCNN total loss: 0.16131 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.20202 RPN box loss: 0.02066 RPN score loss: 0.02051 RPN total loss: 0.04117 Total loss: 0.97247 timestamp: 1655058624.8090668 iteration: 63730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10925 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.19056 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.19671 RPN box loss: 0.01339 RPN score loss: 0.00377 RPN total loss: 0.01715 Total loss: 0.97238 timestamp: 1655058628.0644073 iteration: 63735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07478 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.1526 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.14269 RPN box loss: 0.00717 RPN score loss: 0.00283 RPN total loss: 0.01 Total loss: 0.87325 timestamp: 1655058631.3105888 iteration: 63740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08889 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.14241 L1 loss: 0.0000e+00 L2 loss: 0.56796 Learning rate: 0.0004 Mask loss: 0.11288 RPN box loss: 0.00402 RPN score loss: 0.00202 RPN total loss: 0.00604 Total loss: 0.82928 timestamp: 1655058634.6579626 iteration: 63745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.14828 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.15898 RPN box loss: 0.00677 RPN score loss: 0.00236 RPN total loss: 0.00913 Total loss: 0.88434 timestamp: 1655058637.9004786 iteration: 63750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14055 FastRCNN class loss: 0.08139 FastRCNN total loss: 0.22195 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.16388 RPN box loss: 0.01984 RPN score loss: 0.009 RPN total loss: 0.02884 Total loss: 0.98263 timestamp: 1655058641.1011393 iteration: 63755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.04698 FastRCNN total loss: 0.16139 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.16653 RPN box loss: 0.01199 RPN score loss: 0.00156 RPN total loss: 0.01356 Total loss: 0.90943 timestamp: 1655058644.3651586 iteration: 63760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08052 FastRCNN class loss: 0.05658 FastRCNN total loss: 0.1371 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.14838 RPN box loss: 0.00834 RPN score loss: 0.00427 RPN total loss: 0.01261 Total loss: 0.86604 timestamp: 1655058647.6065326 iteration: 63765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.14507 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.1547 RPN box loss: 0.00724 RPN score loss: 0.00469 RPN total loss: 0.01194 Total loss: 0.87965 timestamp: 1655058650.9052446 iteration: 63770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11471 FastRCNN class loss: 0.0591 FastRCNN total loss: 0.17381 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.16106 RPN box loss: 0.02401 RPN score loss: 0.00252 RPN total loss: 0.02652 Total loss: 0.92935 timestamp: 1655058654.1623564 iteration: 63775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.17497 L1 loss: 0.0000e+00 L2 loss: 0.56795 Learning rate: 0.0004 Mask loss: 0.13903 RPN box loss: 0.01394 RPN score loss: 0.00671 RPN total loss: 0.02065 Total loss: 0.90259 timestamp: 1655058657.448021 iteration: 63780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07283 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.14137 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.07519 RPN box loss: 0.01498 RPN score loss: 0.00525 RPN total loss: 0.02023 Total loss: 0.80473 timestamp: 1655058660.7565653 iteration: 63785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09222 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.16969 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.17767 RPN box loss: 0.00447 RPN score loss: 0.00457 RPN total loss: 0.00903 Total loss: 0.92434 timestamp: 1655058664.0169582 iteration: 63790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09659 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.18356 RPN box loss: 0.01754 RPN score loss: 0.00918 RPN total loss: 0.02672 Total loss: 0.95308 timestamp: 1655058667.2891529 iteration: 63795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13729 FastRCNN class loss: 0.07715 FastRCNN total loss: 0.21444 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.12971 RPN box loss: 0.021 RPN score loss: 0.00633 RPN total loss: 0.02733 Total loss: 0.93942 timestamp: 1655058670.5510335 iteration: 63800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1261 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.19198 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.14755 RPN box loss: 0.01737 RPN score loss: 0.00218 RPN total loss: 0.01955 Total loss: 0.92702 timestamp: 1655058673.8215947 iteration: 63805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12941 FastRCNN class loss: 0.12412 FastRCNN total loss: 0.25354 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.26341 RPN box loss: 0.02095 RPN score loss: 0.0102 RPN total loss: 0.03115 Total loss: 1.11604 timestamp: 1655058677.030634 iteration: 63810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12486 FastRCNN class loss: 0.11584 FastRCNN total loss: 0.2407 L1 loss: 0.0000e+00 L2 loss: 0.56794 Learning rate: 0.0004 Mask loss: 0.12848 RPN box loss: 0.02408 RPN score loss: 0.01316 RPN total loss: 0.03724 Total loss: 0.97436 timestamp: 1655058680.3190157 iteration: 63815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08134 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.15627 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.11099 RPN box loss: 0.02622 RPN score loss: 0.00332 RPN total loss: 0.02954 Total loss: 0.86473 timestamp: 1655058683.575412 iteration: 63820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.16642 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.17866 RPN box loss: 0.00925 RPN score loss: 0.00265 RPN total loss: 0.01189 Total loss: 0.9249 timestamp: 1655058686.869254 iteration: 63825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16004 FastRCNN class loss: 0.08216 FastRCNN total loss: 0.2422 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.17238 RPN box loss: 0.07516 RPN score loss: 0.01894 RPN total loss: 0.0941 Total loss: 1.07661 timestamp: 1655058690.0969017 iteration: 63830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.06491 FastRCNN total loss: 0.13894 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.08273 RPN box loss: 0.00915 RPN score loss: 0.00457 RPN total loss: 0.01372 Total loss: 0.80333 timestamp: 1655058693.3796153 iteration: 63835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1165 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.19286 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.11171 RPN box loss: 0.00833 RPN score loss: 0.00572 RPN total loss: 0.01405 Total loss: 0.88655 timestamp: 1655058696.684788 iteration: 63840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06433 FastRCNN class loss: 0.03463 FastRCNN total loss: 0.09896 L1 loss: 0.0000e+00 L2 loss: 0.56793 Learning rate: 0.0004 Mask loss: 0.09092 RPN box loss: 0.00767 RPN score loss: 0.00353 RPN total loss: 0.0112 Total loss: 0.769 timestamp: 1655058699.970377 iteration: 63845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07526 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.15314 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.17042 RPN box loss: 0.00874 RPN score loss: 0.00265 RPN total loss: 0.01139 Total loss: 0.90288 timestamp: 1655058703.2104542 iteration: 63850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11621 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.09064 RPN box loss: 0.00283 RPN score loss: 0.00486 RPN total loss: 0.00769 Total loss: 0.83224 timestamp: 1655058706.5362084 iteration: 63855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13339 FastRCNN class loss: 0.06309 FastRCNN total loss: 0.19648 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.14474 RPN box loss: 0.00551 RPN score loss: 0.0024 RPN total loss: 0.00791 Total loss: 0.91705 timestamp: 1655058709.7983463 iteration: 63860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07533 FastRCNN class loss: 0.07659 FastRCNN total loss: 0.15193 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.15051 RPN box loss: 0.00902 RPN score loss: 0.00315 RPN total loss: 0.01216 Total loss: 0.88252 timestamp: 1655058713.0472379 iteration: 63865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07304 FastRCNN class loss: 0.05229 FastRCNN total loss: 0.12533 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.12114 RPN box loss: 0.01563 RPN score loss: 0.00578 RPN total loss: 0.02141 Total loss: 0.8358 timestamp: 1655058716.3604643 iteration: 63870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09197 FastRCNN class loss: 0.08258 FastRCNN total loss: 0.17455 L1 loss: 0.0000e+00 L2 loss: 0.56792 Learning rate: 0.0004 Mask loss: 0.19753 RPN box loss: 0.00834 RPN score loss: 0.00303 RPN total loss: 0.01137 Total loss: 0.95137 timestamp: 1655058719.6316028 iteration: 63875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11658 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.19489 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.15666 RPN box loss: 0.0218 RPN score loss: 0.0086 RPN total loss: 0.0304 Total loss: 0.94986 timestamp: 1655058722.869393 iteration: 63880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11994 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.20265 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.19392 RPN box loss: 0.01827 RPN score loss: 0.00661 RPN total loss: 0.02488 Total loss: 0.98937 timestamp: 1655058726.1227725 iteration: 63885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06936 FastRCNN class loss: 0.05943 FastRCNN total loss: 0.12878 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.16486 RPN box loss: 0.00953 RPN score loss: 0.00211 RPN total loss: 0.01164 Total loss: 0.8732 timestamp: 1655058729.4299679 iteration: 63890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05019 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.10896 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.17618 RPN box loss: 0.01311 RPN score loss: 0.00603 RPN total loss: 0.01914 Total loss: 0.8722 timestamp: 1655058732.7061672 iteration: 63895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11591 FastRCNN class loss: 0.06944 FastRCNN total loss: 0.18535 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.17565 RPN box loss: 0.02639 RPN score loss: 0.00322 RPN total loss: 0.02961 Total loss: 0.95851 timestamp: 1655058735.907832 iteration: 63900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07799 FastRCNN class loss: 0.05919 FastRCNN total loss: 0.13718 L1 loss: 0.0000e+00 L2 loss: 0.56791 Learning rate: 0.0004 Mask loss: 0.12713 RPN box loss: 0.0106 RPN score loss: 0.00362 RPN total loss: 0.01422 Total loss: 0.84643 timestamp: 1655058739.0899796 iteration: 63905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11711 FastRCNN class loss: 0.07657 FastRCNN total loss: 0.19368 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.12657 RPN box loss: 0.01431 RPN score loss: 0.00632 RPN total loss: 0.02063 Total loss: 0.90878 timestamp: 1655058742.321699 iteration: 63910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1131 FastRCNN class loss: 0.07712 FastRCNN total loss: 0.19022 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.15625 RPN box loss: 0.01641 RPN score loss: 0.01049 RPN total loss: 0.0269 Total loss: 0.94128 timestamp: 1655058745.543937 iteration: 63915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11894 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.20035 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.10217 RPN box loss: 0.00582 RPN score loss: 0.00696 RPN total loss: 0.01278 Total loss: 0.8832 timestamp: 1655058748.7551024 iteration: 63920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15173 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.21989 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.17745 RPN box loss: 0.01099 RPN score loss: 0.0057 RPN total loss: 0.01668 Total loss: 0.98192 timestamp: 1655058752.0134048 iteration: 63925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08281 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.14193 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.12407 RPN box loss: 0.00848 RPN score loss: 0.00344 RPN total loss: 0.01192 Total loss: 0.84581 timestamp: 1655058755.268613 iteration: 63930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04568 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.1065 L1 loss: 0.0000e+00 L2 loss: 0.5679 Learning rate: 0.0004 Mask loss: 0.10548 RPN box loss: 0.01618 RPN score loss: 0.00309 RPN total loss: 0.01927 Total loss: 0.79915 timestamp: 1655058758.5207798 iteration: 63935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11696 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.20027 RPN box loss: 0.00418 RPN score loss: 0.00823 RPN total loss: 0.01241 Total loss: 0.97178 timestamp: 1655058761.7984858 iteration: 63940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04009 FastRCNN class loss: 0.06727 FastRCNN total loss: 0.10736 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.16426 RPN box loss: 0.01591 RPN score loss: 0.00908 RPN total loss: 0.02499 Total loss: 0.8645 timestamp: 1655058764.9932263 iteration: 63945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09516 FastRCNN class loss: 0.08502 FastRCNN total loss: 0.18018 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.17573 RPN box loss: 0.00804 RPN score loss: 0.00327 RPN total loss: 0.0113 Total loss: 0.93511 timestamp: 1655058768.227049 iteration: 63950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1265 FastRCNN class loss: 0.10981 FastRCNN total loss: 0.23631 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.15695 RPN box loss: 0.01387 RPN score loss: 0.01032 RPN total loss: 0.02418 Total loss: 0.98533 timestamp: 1655058771.5042934 iteration: 63955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.0616 FastRCNN total loss: 0.16034 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.1874 RPN box loss: 0.00451 RPN score loss: 0.00281 RPN total loss: 0.00732 Total loss: 0.92294 timestamp: 1655058774.7558005 iteration: 63960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11702 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.184 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.13152 RPN box loss: 0.00952 RPN score loss: 0.00292 RPN total loss: 0.01245 Total loss: 0.89585 timestamp: 1655058778.036979 iteration: 63965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12857 FastRCNN class loss: 0.0992 FastRCNN total loss: 0.22777 L1 loss: 0.0000e+00 L2 loss: 0.56789 Learning rate: 0.0004 Mask loss: 0.22987 RPN box loss: 0.01869 RPN score loss: 0.01141 RPN total loss: 0.03011 Total loss: 1.05563 timestamp: 1655058781.3272889 iteration: 63970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11515 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.1926 L1 loss: 0.0000e+00 L2 loss: 0.56788 Learning rate: 0.0004 Mask loss: 0.1309 RPN box loss: 0.00891 RPN score loss: 0.00862 RPN total loss: 0.01753 Total loss: 0.90891 timestamp: 1655058784.5704103 iteration: 63975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10606 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.19474 L1 loss: 0.0000e+00 L2 loss: 0.56788 Learning rate: 0.0004 Mask loss: 0.12798 RPN box loss: 0.02433 RPN score loss: 0.0129 RPN total loss: 0.03724 Total loss: 0.92784 timestamp: 1655058787.8449779 iteration: 63980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06784 FastRCNN class loss: 0.06752 FastRCNN total loss: 0.13536 L1 loss: 0.0000e+00 L2 loss: 0.56788 Learning rate: 0.0004 Mask loss: 0.18387 RPN box loss: 0.0216 RPN score loss: 0.00459 RPN total loss: 0.02619 Total loss: 0.9133 timestamp: 1655058791.0876777 iteration: 63985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14191 FastRCNN class loss: 0.05422 FastRCNN total loss: 0.19613 L1 loss: 0.0000e+00 L2 loss: 0.56788 Learning rate: 0.0004 Mask loss: 0.10101 RPN box loss: 0.00691 RPN score loss: 0.00141 RPN total loss: 0.00833 Total loss: 0.87336 timestamp: 1655058794.288576 iteration: 63990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12337 FastRCNN class loss: 0.08043 FastRCNN total loss: 0.2038 L1 loss: 0.0000e+00 L2 loss: 0.56788 Learning rate: 0.0004 Mask loss: 0.15917 RPN box loss: 0.00842 RPN score loss: 0.0026 RPN total loss: 0.01102 Total loss: 0.94187 timestamp: 1655058797.4974887 iteration: 63995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05201 FastRCNN class loss: 0.05502 FastRCNN total loss: 0.10703 L1 loss: 0.0000e+00 L2 loss: 0.56787 Learning rate: 0.0004 Mask loss: 0.10847 RPN box loss: 0.00637 RPN score loss: 0.00652 RPN total loss: 0.01289 Total loss: 0.79626 timestamp: 1655058800.784295 iteration: 64000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15911 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.22491 L1 loss: 0.0000e+00 L2 loss: 0.56787 Learning rate: 0.0004 Mask loss: 0.12674 RPN box loss: 0.00952 RPN score loss: 0.00921 RPN total loss: 0.01873 Total loss: 0.93825 timestamp: 1655058804.0190659 iteration: 64005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09361 FastRCNN class loss: 0.11319 FastRCNN total loss: 0.2068 L1 loss: 0.0000e+00 L2 loss: 0.56787 Learning rate: 0.0004 Mask loss: 0.13631 RPN box loss: 0.00672 RPN score loss: 0.0045 RPN total loss: 0.01122 Total loss: 0.9222 timestamp: 1655058807.179406 iteration: 64010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11402 FastRCNN class loss: 0.08155 FastRCNN total loss: 0.19558 L1 loss: 0.0000e+00 L2 loss: 0.56787 Learning rate: 0.0004 Mask loss: 0.14814 RPN box loss: 0.02238 RPN score loss: 0.00954 RPN total loss: 0.03192 Total loss: 0.94351 timestamp: 1655058810.454987 iteration: 64015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09167 FastRCNN class loss: 0.0477 FastRCNN total loss: 0.13937 L1 loss: 0.0000e+00 L2 loss: 0.56787 Learning rate: 0.0004 Mask loss: 0.10821 RPN box loss: 0.00633 RPN score loss: 0.00688 RPN total loss: 0.01321 Total loss: 0.82866 timestamp: 1655058813.7094681 iteration: 64020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0927 FastRCNN class loss: 0.07538 FastRCNN total loss: 0.16808 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.15746 RPN box loss: 0.0325 RPN score loss: 0.0023 RPN total loss: 0.0348 Total loss: 0.9282 timestamp: 1655058817.0214262 iteration: 64025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.15684 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.14068 RPN box loss: 0.00644 RPN score loss: 0.00407 RPN total loss: 0.01051 Total loss: 0.87589 timestamp: 1655058820.3392582 iteration: 64030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11634 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.20399 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.15646 RPN box loss: 0.00964 RPN score loss: 0.0015 RPN total loss: 0.01114 Total loss: 0.93945 timestamp: 1655058823.5689414 iteration: 64035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10265 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.17106 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.13125 RPN box loss: 0.02586 RPN score loss: 0.00696 RPN total loss: 0.03283 Total loss: 0.903 timestamp: 1655058826.8202531 iteration: 64040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12466 FastRCNN class loss: 0.13664 FastRCNN total loss: 0.26131 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.22107 RPN box loss: 0.01041 RPN score loss: 0.01002 RPN total loss: 0.02043 Total loss: 1.07067 timestamp: 1655058830.128322 iteration: 64045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08443 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.14299 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.18053 RPN box loss: 0.01115 RPN score loss: 0.00394 RPN total loss: 0.01509 Total loss: 0.90647 timestamp: 1655058833.4202743 iteration: 64050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05972 FastRCNN class loss: 0.03304 FastRCNN total loss: 0.09276 L1 loss: 0.0000e+00 L2 loss: 0.56786 Learning rate: 0.0004 Mask loss: 0.09446 RPN box loss: 0.00363 RPN score loss: 0.00202 RPN total loss: 0.00565 Total loss: 0.76072 timestamp: 1655058836.6586218 iteration: 64055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.15087 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.13683 RPN box loss: 0.03347 RPN score loss: 0.00897 RPN total loss: 0.04245 Total loss: 0.898 timestamp: 1655058839.9459894 iteration: 64060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16922 FastRCNN class loss: 0.06821 FastRCNN total loss: 0.23744 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.12609 RPN box loss: 0.03166 RPN score loss: 0.00278 RPN total loss: 0.03443 Total loss: 0.96581 timestamp: 1655058843.2089083 iteration: 64065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09089 FastRCNN class loss: 0.04145 FastRCNN total loss: 0.13234 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.138 RPN box loss: 0.01037 RPN score loss: 0.00458 RPN total loss: 0.01495 Total loss: 0.85314 timestamp: 1655058846.505834 iteration: 64070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08709 FastRCNN class loss: 0.06008 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.14361 RPN box loss: 0.00656 RPN score loss: 0.00532 RPN total loss: 0.01188 Total loss: 0.87051 timestamp: 1655058849.7825484 iteration: 64075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05459 FastRCNN class loss: 0.06478 FastRCNN total loss: 0.11937 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.15213 RPN box loss: 0.00875 RPN score loss: 0.00682 RPN total loss: 0.01556 Total loss: 0.85491 timestamp: 1655058852.9823852 iteration: 64080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10919 FastRCNN class loss: 0.06288 FastRCNN total loss: 0.17207 L1 loss: 0.0000e+00 L2 loss: 0.56785 Learning rate: 0.0004 Mask loss: 0.18249 RPN box loss: 0.01917 RPN score loss: 0.00439 RPN total loss: 0.02356 Total loss: 0.94597 timestamp: 1655058856.2138734 iteration: 64085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15631 FastRCNN class loss: 0.10673 FastRCNN total loss: 0.26304 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.19759 RPN box loss: 0.0154 RPN score loss: 0.008 RPN total loss: 0.0234 Total loss: 1.05187 timestamp: 1655058859.4914594 iteration: 64090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12738 FastRCNN class loss: 0.12588 FastRCNN total loss: 0.25326 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.14237 RPN box loss: 0.0087 RPN score loss: 0.00425 RPN total loss: 0.01296 Total loss: 0.97643 timestamp: 1655058862.7783918 iteration: 64095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09604 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.17886 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.10905 RPN box loss: 0.00568 RPN score loss: 0.0016 RPN total loss: 0.00729 Total loss: 0.86304 timestamp: 1655058866.0048301 iteration: 64100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15282 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.22149 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.14212 RPN box loss: 0.02422 RPN score loss: 0.00375 RPN total loss: 0.02797 Total loss: 0.95941 timestamp: 1655058869.298989 iteration: 64105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11555 FastRCNN class loss: 0.08173 FastRCNN total loss: 0.19728 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.15521 RPN box loss: 0.00541 RPN score loss: 0.00342 RPN total loss: 0.00882 Total loss: 0.92915 timestamp: 1655058872.583361 iteration: 64110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10541 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.1733 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.15185 RPN box loss: 0.03254 RPN score loss: 0.00541 RPN total loss: 0.03795 Total loss: 0.93094 timestamp: 1655058875.894432 iteration: 64115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07448 FastRCNN class loss: 0.0887 FastRCNN total loss: 0.16318 L1 loss: 0.0000e+00 L2 loss: 0.56784 Learning rate: 0.0004 Mask loss: 0.1255 RPN box loss: 0.02335 RPN score loss: 0.01187 RPN total loss: 0.03522 Total loss: 0.89174 timestamp: 1655058879.1853619 iteration: 64120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13829 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.22146 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.17694 RPN box loss: 0.03789 RPN score loss: 0.00681 RPN total loss: 0.04471 Total loss: 1.01094 timestamp: 1655058882.4329057 iteration: 64125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18013 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.25216 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.13307 RPN box loss: 0.02249 RPN score loss: 0.00594 RPN total loss: 0.02842 Total loss: 0.98148 timestamp: 1655058885.7101421 iteration: 64130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11354 FastRCNN class loss: 0.16451 FastRCNN total loss: 0.27805 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.23596 RPN box loss: 0.04107 RPN score loss: 0.06925 RPN total loss: 0.11031 Total loss: 1.19215 timestamp: 1655058888.9941406 iteration: 64135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06676 FastRCNN class loss: 0.04921 FastRCNN total loss: 0.11597 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.11887 RPN box loss: 0.00855 RPN score loss: 0.00105 RPN total loss: 0.0096 Total loss: 0.81227 timestamp: 1655058892.2980375 iteration: 64140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14354 FastRCNN class loss: 0.06746 FastRCNN total loss: 0.211 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.13243 RPN box loss: 0.01345 RPN score loss: 0.00297 RPN total loss: 0.01642 Total loss: 0.92768 timestamp: 1655058895.5319445 iteration: 64145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12924 FastRCNN class loss: 0.09948 FastRCNN total loss: 0.22872 L1 loss: 0.0000e+00 L2 loss: 0.56783 Learning rate: 0.0004 Mask loss: 0.1495 RPN box loss: 0.0147 RPN score loss: 0.00488 RPN total loss: 0.01958 Total loss: 0.96562 timestamp: 1655058898.7762084 iteration: 64150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12306 FastRCNN class loss: 0.07702 FastRCNN total loss: 0.20008 L1 loss: 0.0000e+00 L2 loss: 0.56782 Learning rate: 0.0004 Mask loss: 0.16582 RPN box loss: 0.01564 RPN score loss: 0.00749 RPN total loss: 0.02314 Total loss: 0.95687 timestamp: 1655058902.0955403 iteration: 64155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0906 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.15355 L1 loss: 0.0000e+00 L2 loss: 0.56782 Learning rate: 0.0004 Mask loss: 0.13911 RPN box loss: 0.0104 RPN score loss: 0.00464 RPN total loss: 0.01504 Total loss: 0.87552 timestamp: 1655058905.3298876 iteration: 64160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07275 FastRCNN class loss: 0.04994 FastRCNN total loss: 0.12269 L1 loss: 0.0000e+00 L2 loss: 0.56782 Learning rate: 0.0004 Mask loss: 0.09331 RPN box loss: 0.00674 RPN score loss: 0.00167 RPN total loss: 0.00841 Total loss: 0.79223 timestamp: 1655058908.618701 iteration: 64165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09165 FastRCNN class loss: 0.04905 FastRCNN total loss: 0.14071 L1 loss: 0.0000e+00 L2 loss: 0.56782 Learning rate: 0.0004 Mask loss: 0.18103 RPN box loss: 0.00856 RPN score loss: 0.01123 RPN total loss: 0.01978 Total loss: 0.90934 timestamp: 1655058911.904641 iteration: 64170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11537 FastRCNN class loss: 0.08907 FastRCNN total loss: 0.20444 L1 loss: 0.0000e+00 L2 loss: 0.56782 Learning rate: 0.0004 Mask loss: 0.17514 RPN box loss: 0.01066 RPN score loss: 0.00808 RPN total loss: 0.01874 Total loss: 0.96614 timestamp: 1655058915.2156098 iteration: 64175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06924 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.12613 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.10982 RPN box loss: 0.0092 RPN score loss: 0.00214 RPN total loss: 0.01134 Total loss: 0.8151 timestamp: 1655058918.4802299 iteration: 64180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15518 FastRCNN class loss: 0.06195 FastRCNN total loss: 0.21713 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.16516 RPN box loss: 0.0153 RPN score loss: 0.00474 RPN total loss: 0.02004 Total loss: 0.97014 timestamp: 1655058921.6950133 iteration: 64185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05708 FastRCNN class loss: 0.02435 FastRCNN total loss: 0.08144 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.1406 RPN box loss: 0.00246 RPN score loss: 0.00309 RPN total loss: 0.00555 Total loss: 0.7954 timestamp: 1655058924.8976479 iteration: 64190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1199 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.20552 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.19043 RPN box loss: 0.01335 RPN score loss: 0.00706 RPN total loss: 0.02041 Total loss: 0.98417 timestamp: 1655058928.2311463 iteration: 64195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14857 FastRCNN class loss: 0.14956 FastRCNN total loss: 0.29813 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.2235 RPN box loss: 0.02757 RPN score loss: 0.00641 RPN total loss: 0.03397 Total loss: 1.12341 timestamp: 1655058931.5119987 iteration: 64200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10526 FastRCNN class loss: 0.07064 FastRCNN total loss: 0.1759 L1 loss: 0.0000e+00 L2 loss: 0.56781 Learning rate: 0.0004 Mask loss: 0.13324 RPN box loss: 0.01964 RPN score loss: 0.01589 RPN total loss: 0.03553 Total loss: 0.91248 timestamp: 1655058934.7655866 iteration: 64205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10682 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.17342 L1 loss: 0.0000e+00 L2 loss: 0.5678 Learning rate: 0.0004 Mask loss: 0.14012 RPN box loss: 0.01041 RPN score loss: 0.00339 RPN total loss: 0.0138 Total loss: 0.89515 timestamp: 1655058938.0390556 iteration: 64210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09529 FastRCNN class loss: 0.03923 FastRCNN total loss: 0.13453 L1 loss: 0.0000e+00 L2 loss: 0.5678 Learning rate: 0.0004 Mask loss: 0.11523 RPN box loss: 0.0108 RPN score loss: 0.00417 RPN total loss: 0.01497 Total loss: 0.83253 timestamp: 1655058941.2798715 iteration: 64215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06814 FastRCNN class loss: 0.04207 FastRCNN total loss: 0.11021 L1 loss: 0.0000e+00 L2 loss: 0.5678 Learning rate: 0.0004 Mask loss: 0.15494 RPN box loss: 0.00381 RPN score loss: 0.00129 RPN total loss: 0.0051 Total loss: 0.83804 timestamp: 1655058944.593056 iteration: 64220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10183 FastRCNN class loss: 0.05156 FastRCNN total loss: 0.15339 L1 loss: 0.0000e+00 L2 loss: 0.5678 Learning rate: 0.0004 Mask loss: 0.11815 RPN box loss: 0.00977 RPN score loss: 0.00267 RPN total loss: 0.01244 Total loss: 0.85178 timestamp: 1655058947.8295178 iteration: 64225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10862 FastRCNN class loss: 0.07531 FastRCNN total loss: 0.18393 L1 loss: 0.0000e+00 L2 loss: 0.5678 Learning rate: 0.0004 Mask loss: 0.13444 RPN box loss: 0.02567 RPN score loss: 0.0083 RPN total loss: 0.03397 Total loss: 0.92014 timestamp: 1655058951.1134124 iteration: 64230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13653 FastRCNN class loss: 0.06527 FastRCNN total loss: 0.2018 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.13212 RPN box loss: 0.00377 RPN score loss: 0.00108 RPN total loss: 0.00485 Total loss: 0.90656 timestamp: 1655058954.3737729 iteration: 64235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17987 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.25608 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.14872 RPN box loss: 0.01531 RPN score loss: 0.00288 RPN total loss: 0.0182 Total loss: 0.99078 timestamp: 1655058957.6019533 iteration: 64240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10466 FastRCNN class loss: 0.08432 FastRCNN total loss: 0.18898 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.1807 RPN box loss: 0.01284 RPN score loss: 0.00337 RPN total loss: 0.01621 Total loss: 0.95368 timestamp: 1655058960.8797877 iteration: 64245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07687 FastRCNN class loss: 0.04412 FastRCNN total loss: 0.12098 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.1607 RPN box loss: 0.01593 RPN score loss: 0.00585 RPN total loss: 0.02178 Total loss: 0.87125 timestamp: 1655058964.0989075 iteration: 64250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08478 FastRCNN class loss: 0.07243 FastRCNN total loss: 0.15721 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.11472 RPN box loss: 0.0096 RPN score loss: 0.00903 RPN total loss: 0.01863 Total loss: 0.85835 timestamp: 1655058967.3571389 iteration: 64255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08184 FastRCNN class loss: 0.0609 FastRCNN total loss: 0.14274 L1 loss: 0.0000e+00 L2 loss: 0.56779 Learning rate: 0.0004 Mask loss: 0.09243 RPN box loss: 0.01876 RPN score loss: 0.00654 RPN total loss: 0.02531 Total loss: 0.82826 timestamp: 1655058970.62086 iteration: 64260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0812 FastRCNN class loss: 0.08645 FastRCNN total loss: 0.16764 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.15804 RPN box loss: 0.00747 RPN score loss: 0.00135 RPN total loss: 0.00882 Total loss: 0.90229 timestamp: 1655058973.8568418 iteration: 64265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05644 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.12493 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.08677 RPN box loss: 0.01377 RPN score loss: 0.01778 RPN total loss: 0.03155 Total loss: 0.81103 timestamp: 1655058977.097915 iteration: 64270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09158 FastRCNN class loss: 0.06999 FastRCNN total loss: 0.16157 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.15353 RPN box loss: 0.00627 RPN score loss: 0.00359 RPN total loss: 0.00985 Total loss: 0.89273 timestamp: 1655058980.282132 iteration: 64275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07404 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.13271 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.12712 RPN box loss: 0.01127 RPN score loss: 0.0018 RPN total loss: 0.01307 Total loss: 0.84069 timestamp: 1655058983.6004016 iteration: 64280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07126 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.11984 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.12748 RPN box loss: 0.01657 RPN score loss: 0.00339 RPN total loss: 0.01996 Total loss: 0.83505 timestamp: 1655058986.8947773 iteration: 64285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09884 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.17896 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.19114 RPN box loss: 0.00963 RPN score loss: 0.00265 RPN total loss: 0.01229 Total loss: 0.95016 timestamp: 1655058990.22622 iteration: 64290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07625 FastRCNN class loss: 0.04856 FastRCNN total loss: 0.12481 L1 loss: 0.0000e+00 L2 loss: 0.56778 Learning rate: 0.0004 Mask loss: 0.13868 RPN box loss: 0.01864 RPN score loss: 0.01044 RPN total loss: 0.02908 Total loss: 0.86035 timestamp: 1655058993.5300543 iteration: 64295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09738 FastRCNN class loss: 0.0507 FastRCNN total loss: 0.14808 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.14648 RPN box loss: 0.01356 RPN score loss: 0.00219 RPN total loss: 0.01575 Total loss: 0.87808 timestamp: 1655058996.7919326 iteration: 64300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07593 FastRCNN class loss: 0.05259 FastRCNN total loss: 0.12852 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.15737 RPN box loss: 0.00926 RPN score loss: 0.00912 RPN total loss: 0.01838 Total loss: 0.87205 timestamp: 1655059000.048565 iteration: 64305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07391 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.1402 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.12377 RPN box loss: 0.00929 RPN score loss: 0.00822 RPN total loss: 0.01751 Total loss: 0.84925 timestamp: 1655059003.3981926 iteration: 64310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09984 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.18845 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.13559 RPN box loss: 0.01671 RPN score loss: 0.00202 RPN total loss: 0.01873 Total loss: 0.91054 timestamp: 1655059006.7189863 iteration: 64315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09565 FastRCNN class loss: 0.07989 FastRCNN total loss: 0.17554 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.15865 RPN box loss: 0.02806 RPN score loss: 0.00543 RPN total loss: 0.03349 Total loss: 0.93545 timestamp: 1655059009.969617 iteration: 64320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14203 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.2424 L1 loss: 0.0000e+00 L2 loss: 0.56777 Learning rate: 0.0004 Mask loss: 0.1661 RPN box loss: 0.03058 RPN score loss: 0.01064 RPN total loss: 0.04123 Total loss: 1.01749 timestamp: 1655059013.1976755 iteration: 64325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.18386 L1 loss: 0.0000e+00 L2 loss: 0.56776 Learning rate: 0.0004 Mask loss: 0.11641 RPN box loss: 0.02698 RPN score loss: 0.03205 RPN total loss: 0.05902 Total loss: 0.92706 timestamp: 1655059016.441454 iteration: 64330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0885 FastRCNN class loss: 0.05348 FastRCNN total loss: 0.14198 L1 loss: 0.0000e+00 L2 loss: 0.56776 Learning rate: 0.0004 Mask loss: 0.14205 RPN box loss: 0.01449 RPN score loss: 0.00399 RPN total loss: 0.01847 Total loss: 0.87026 timestamp: 1655059019.6980643 iteration: 64335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11537 FastRCNN class loss: 0.06461 FastRCNN total loss: 0.17998 L1 loss: 0.0000e+00 L2 loss: 0.56776 Learning rate: 0.0004 Mask loss: 0.13243 RPN box loss: 0.02113 RPN score loss: 0.00773 RPN total loss: 0.02886 Total loss: 0.90903 timestamp: 1655059022.9841917 iteration: 64340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11283 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.15611 L1 loss: 0.0000e+00 L2 loss: 0.56776 Learning rate: 0.0004 Mask loss: 0.09594 RPN box loss: 0.00799 RPN score loss: 0.002 RPN total loss: 0.00999 Total loss: 0.82979 timestamp: 1655059026.3231392 iteration: 64345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07297 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.13023 L1 loss: 0.0000e+00 L2 loss: 0.56776 Learning rate: 0.0004 Mask loss: 0.08273 RPN box loss: 0.00869 RPN score loss: 0.00197 RPN total loss: 0.01066 Total loss: 0.79138 timestamp: 1655059029.6238701 iteration: 64350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1427 FastRCNN class loss: 0.09622 FastRCNN total loss: 0.23892 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.2055 RPN box loss: 0.01805 RPN score loss: 0.00858 RPN total loss: 0.02664 Total loss: 1.03881 timestamp: 1655059032.946072 iteration: 64355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09501 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.15735 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.17509 RPN box loss: 0.01389 RPN score loss: 0.00186 RPN total loss: 0.01575 Total loss: 0.91594 timestamp: 1655059036.2726386 iteration: 64360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07543 FastRCNN class loss: 0.06268 FastRCNN total loss: 0.1381 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.12831 RPN box loss: 0.00986 RPN score loss: 0.00353 RPN total loss: 0.0134 Total loss: 0.84756 timestamp: 1655059039.5841584 iteration: 64365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0751 FastRCNN class loss: 0.04418 FastRCNN total loss: 0.11927 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.12434 RPN box loss: 0.022 RPN score loss: 0.0063 RPN total loss: 0.0283 Total loss: 0.83966 timestamp: 1655059042.8728428 iteration: 64370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09188 FastRCNN class loss: 0.0989 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.16025 RPN box loss: 0.0091 RPN score loss: 0.00414 RPN total loss: 0.01324 Total loss: 0.93201 timestamp: 1655059046.1287327 iteration: 64375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12775 FastRCNN class loss: 0.06942 FastRCNN total loss: 0.19717 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.17539 RPN box loss: 0.01438 RPN score loss: 0.00518 RPN total loss: 0.01957 Total loss: 0.95987 timestamp: 1655059049.4520977 iteration: 64380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08433 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.14334 L1 loss: 0.0000e+00 L2 loss: 0.56775 Learning rate: 0.0004 Mask loss: 0.12179 RPN box loss: 0.00708 RPN score loss: 0.01161 RPN total loss: 0.01868 Total loss: 0.85156 timestamp: 1655059052.7198699 iteration: 64385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12157 FastRCNN class loss: 0.07194 FastRCNN total loss: 0.19351 L1 loss: 0.0000e+00 L2 loss: 0.56774 Learning rate: 0.0004 Mask loss: 0.14786 RPN box loss: 0.00929 RPN score loss: 0.00335 RPN total loss: 0.01265 Total loss: 0.92176 timestamp: 1655059056.023914 iteration: 64390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07116 FastRCNN class loss: 0.05266 FastRCNN total loss: 0.12382 L1 loss: 0.0000e+00 L2 loss: 0.56774 Learning rate: 0.0004 Mask loss: 0.09852 RPN box loss: 0.01013 RPN score loss: 0.00557 RPN total loss: 0.0157 Total loss: 0.80578 timestamp: 1655059059.2857833 iteration: 64395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08802 FastRCNN class loss: 0.09119 FastRCNN total loss: 0.1792 L1 loss: 0.0000e+00 L2 loss: 0.56774 Learning rate: 0.0004 Mask loss: 0.15963 RPN box loss: 0.01963 RPN score loss: 0.00833 RPN total loss: 0.02796 Total loss: 0.93454 timestamp: 1655059062.6001382 iteration: 64400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07497 FastRCNN class loss: 0.07888 FastRCNN total loss: 0.15385 L1 loss: 0.0000e+00 L2 loss: 0.56774 Learning rate: 0.0004 Mask loss: 0.13652 RPN box loss: 0.00972 RPN score loss: 0.00477 RPN total loss: 0.01449 Total loss: 0.87259 timestamp: 1655059065.90079 iteration: 64405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.06324 FastRCNN total loss: 0.13666 L1 loss: 0.0000e+00 L2 loss: 0.56774 Learning rate: 0.0004 Mask loss: 0.23363 RPN box loss: 0.02403 RPN score loss: 0.00268 RPN total loss: 0.02672 Total loss: 0.96475 timestamp: 1655059069.2564182 iteration: 64410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11091 FastRCNN class loss: 0.08135 FastRCNN total loss: 0.19227 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.18766 RPN box loss: 0.01105 RPN score loss: 0.00231 RPN total loss: 0.01336 Total loss: 0.96103 timestamp: 1655059072.5130823 iteration: 64415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10407 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.18369 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.18637 RPN box loss: 0.0242 RPN score loss: 0.00904 RPN total loss: 0.03323 Total loss: 0.97102 timestamp: 1655059075.8072171 iteration: 64420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12203 FastRCNN class loss: 0.06129 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.11863 RPN box loss: 0.00456 RPN score loss: 0.00184 RPN total loss: 0.0064 Total loss: 0.87608 timestamp: 1655059079.0930297 iteration: 64425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09056 FastRCNN class loss: 0.05298 FastRCNN total loss: 0.14354 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.11548 RPN box loss: 0.01009 RPN score loss: 0.00666 RPN total loss: 0.01675 Total loss: 0.8435 timestamp: 1655059082.385587 iteration: 64430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16216 FastRCNN class loss: 0.06071 FastRCNN total loss: 0.22287 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.13106 RPN box loss: 0.01258 RPN score loss: 0.00448 RPN total loss: 0.01706 Total loss: 0.93873 timestamp: 1655059085.6905718 iteration: 64435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11163 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.18474 L1 loss: 0.0000e+00 L2 loss: 0.56773 Learning rate: 0.0004 Mask loss: 0.16904 RPN box loss: 0.01364 RPN score loss: 0.01113 RPN total loss: 0.02477 Total loss: 0.94628 timestamp: 1655059088.9102418 iteration: 64440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07167 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.14515 L1 loss: 0.0000e+00 L2 loss: 0.56772 Learning rate: 0.0004 Mask loss: 0.15523 RPN box loss: 0.00824 RPN score loss: 0.00938 RPN total loss: 0.01762 Total loss: 0.88572 timestamp: 1655059092.1015515 iteration: 64445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12717 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.21664 L1 loss: 0.0000e+00 L2 loss: 0.56772 Learning rate: 0.0004 Mask loss: 0.16096 RPN box loss: 0.03915 RPN score loss: 0.00768 RPN total loss: 0.04683 Total loss: 0.99215 timestamp: 1655059095.4169977 iteration: 64450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08534 FastRCNN class loss: 0.08397 FastRCNN total loss: 0.16931 L1 loss: 0.0000e+00 L2 loss: 0.56772 Learning rate: 0.0004 Mask loss: 0.14102 RPN box loss: 0.01229 RPN score loss: 0.0146 RPN total loss: 0.0269 Total loss: 0.90495 timestamp: 1655059098.7015011 iteration: 64455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09734 FastRCNN class loss: 0.05885 FastRCNN total loss: 0.15619 L1 loss: 0.0000e+00 L2 loss: 0.56772 Learning rate: 0.0004 Mask loss: 0.18079 RPN box loss: 0.03096 RPN score loss: 0.00797 RPN total loss: 0.03893 Total loss: 0.94363 timestamp: 1655059101.9114723 iteration: 64460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17666 FastRCNN class loss: 0.08854 FastRCNN total loss: 0.2652 L1 loss: 0.0000e+00 L2 loss: 0.56772 Learning rate: 0.0004 Mask loss: 0.18365 RPN box loss: 0.00769 RPN score loss: 0.00528 RPN total loss: 0.01297 Total loss: 1.02954 timestamp: 1655059105.179569 iteration: 64465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09645 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.56771 Learning rate: 0.0004 Mask loss: 0.12883 RPN box loss: 0.02843 RPN score loss: 0.00643 RPN total loss: 0.03486 Total loss: 0.89256 timestamp: 1655059108.4606352 iteration: 64470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1046 FastRCNN class loss: 0.09423 FastRCNN total loss: 0.19883 L1 loss: 0.0000e+00 L2 loss: 0.56771 Learning rate: 0.0004 Mask loss: 0.17978 RPN box loss: 0.01041 RPN score loss: 0.00431 RPN total loss: 0.01473 Total loss: 0.96105 timestamp: 1655059111.6852515 iteration: 64475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12543 FastRCNN class loss: 0.09681 FastRCNN total loss: 0.22224 L1 loss: 0.0000e+00 L2 loss: 0.56771 Learning rate: 0.0004 Mask loss: 0.14349 RPN box loss: 0.01575 RPN score loss: 0.00504 RPN total loss: 0.02078 Total loss: 0.95423 timestamp: 1655059115.015036 iteration: 64480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06372 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.13037 L1 loss: 0.0000e+00 L2 loss: 0.56771 Learning rate: 0.0004 Mask loss: 0.17271 RPN box loss: 0.02048 RPN score loss: 0.0071 RPN total loss: 0.02758 Total loss: 0.89837 timestamp: 1655059118.2796874 iteration: 64485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0817 FastRCNN class loss: 0.03527 FastRCNN total loss: 0.11698 L1 loss: 0.0000e+00 L2 loss: 0.56771 Learning rate: 0.0004 Mask loss: 0.07317 RPN box loss: 0.01868 RPN score loss: 0.00147 RPN total loss: 0.02015 Total loss: 0.778 timestamp: 1655059121.5215771 iteration: 64490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07077 FastRCNN class loss: 0.05208 FastRCNN total loss: 0.12285 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.08868 RPN box loss: 0.00808 RPN score loss: 0.00226 RPN total loss: 0.01033 Total loss: 0.78957 timestamp: 1655059124.800003 iteration: 64495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.073 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.12516 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.12624 RPN box loss: 0.02385 RPN score loss: 0.00359 RPN total loss: 0.02744 Total loss: 0.84654 timestamp: 1655059127.9837482 iteration: 64500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11389 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.11088 RPN box loss: 0.00714 RPN score loss: 0.0019 RPN total loss: 0.00905 Total loss: 0.85189 timestamp: 1655059131.2962286 iteration: 64505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10146 FastRCNN class loss: 0.11203 FastRCNN total loss: 0.2135 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.17624 RPN box loss: 0.01771 RPN score loss: 0.00295 RPN total loss: 0.02066 Total loss: 0.9781 timestamp: 1655059134.5957346 iteration: 64510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14019 FastRCNN class loss: 0.07924 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.21218 RPN box loss: 0.01347 RPN score loss: 0.00597 RPN total loss: 0.01944 Total loss: 1.01876 timestamp: 1655059137.8733482 iteration: 64515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15417 FastRCNN class loss: 0.09273 FastRCNN total loss: 0.24689 L1 loss: 0.0000e+00 L2 loss: 0.5677 Learning rate: 0.0004 Mask loss: 0.22304 RPN box loss: 0.01932 RPN score loss: 0.01068 RPN total loss: 0.03001 Total loss: 1.06763 timestamp: 1655059141.195914 iteration: 64520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13691 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.19516 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.1562 RPN box loss: 0.01366 RPN score loss: 0.00853 RPN total loss: 0.02219 Total loss: 0.94124 timestamp: 1655059144.4758186 iteration: 64525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.07748 FastRCNN total loss: 0.16052 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.16882 RPN box loss: 0.01701 RPN score loss: 0.00261 RPN total loss: 0.01962 Total loss: 0.91665 timestamp: 1655059147.7911596 iteration: 64530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08791 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.1329 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.07365 RPN box loss: 0.00642 RPN score loss: 0.00069 RPN total loss: 0.00711 Total loss: 0.78134 timestamp: 1655059151.006244 iteration: 64535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10395 FastRCNN class loss: 0.07658 FastRCNN total loss: 0.18052 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.13107 RPN box loss: 0.02088 RPN score loss: 0.00515 RPN total loss: 0.02603 Total loss: 0.90532 timestamp: 1655059154.260016 iteration: 64540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10119 FastRCNN class loss: 0.10276 FastRCNN total loss: 0.20396 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.19879 RPN box loss: 0.02347 RPN score loss: 0.02179 RPN total loss: 0.04527 Total loss: 1.0157 timestamp: 1655059157.5294697 iteration: 64545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06073 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.12052 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.10182 RPN box loss: 0.00889 RPN score loss: 0.00547 RPN total loss: 0.01436 Total loss: 0.80438 timestamp: 1655059160.7652538 iteration: 64550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08338 FastRCNN class loss: 0.04151 FastRCNN total loss: 0.12488 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.11637 RPN box loss: 0.00448 RPN score loss: 0.00626 RPN total loss: 0.01074 Total loss: 0.81967 timestamp: 1655059164.0536 iteration: 64555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07045 FastRCNN class loss: 0.05594 FastRCNN total loss: 0.12639 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.12056 RPN box loss: 0.0176 RPN score loss: 0.00335 RPN total loss: 0.02095 Total loss: 0.83559 timestamp: 1655059167.338624 iteration: 64560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18157 FastRCNN class loss: 0.15252 FastRCNN total loss: 0.3341 L1 loss: 0.0000e+00 L2 loss: 0.56769 Learning rate: 0.0004 Mask loss: 0.24577 RPN box loss: 0.02176 RPN score loss: 0.01142 RPN total loss: 0.03318 Total loss: 1.18073 timestamp: 1655059170.585275 iteration: 64565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05344 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.1437 L1 loss: 0.0000e+00 L2 loss: 0.56768 Learning rate: 0.0004 Mask loss: 0.17682 RPN box loss: 0.01528 RPN score loss: 0.00979 RPN total loss: 0.02507 Total loss: 0.91327 timestamp: 1655059173.8598702 iteration: 64570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13265 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.19203 L1 loss: 0.0000e+00 L2 loss: 0.56768 Learning rate: 0.0004 Mask loss: 0.09873 RPN box loss: 0.02817 RPN score loss: 0.00612 RPN total loss: 0.03428 Total loss: 0.89273 timestamp: 1655059177.13158 iteration: 64575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0998 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.15836 L1 loss: 0.0000e+00 L2 loss: 0.56768 Learning rate: 0.0004 Mask loss: 0.1407 RPN box loss: 0.01025 RPN score loss: 0.00434 RPN total loss: 0.01459 Total loss: 0.88133 timestamp: 1655059180.425333 iteration: 64580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06635 FastRCNN class loss: 0.04451 FastRCNN total loss: 0.11086 L1 loss: 0.0000e+00 L2 loss: 0.56768 Learning rate: 0.0004 Mask loss: 0.13325 RPN box loss: 0.01148 RPN score loss: 0.0037 RPN total loss: 0.01518 Total loss: 0.82696 timestamp: 1655059183.694362 iteration: 64585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04593 FastRCNN class loss: 0.03941 FastRCNN total loss: 0.08534 L1 loss: 0.0000e+00 L2 loss: 0.56768 Learning rate: 0.0004 Mask loss: 0.09132 RPN box loss: 0.00253 RPN score loss: 0.00105 RPN total loss: 0.00358 Total loss: 0.74792 timestamp: 1655059186.9907174 iteration: 64590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05236 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.10289 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.08742 RPN box loss: 0.00504 RPN score loss: 0.00238 RPN total loss: 0.00742 Total loss: 0.76541 timestamp: 1655059190.2670138 iteration: 64595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08122 FastRCNN class loss: 0.06 FastRCNN total loss: 0.14122 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.13967 RPN box loss: 0.01002 RPN score loss: 0.00925 RPN total loss: 0.01927 Total loss: 0.86784 timestamp: 1655059193.5497997 iteration: 64600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11195 FastRCNN class loss: 0.0572 FastRCNN total loss: 0.16915 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.1203 RPN box loss: 0.00881 RPN score loss: 0.00614 RPN total loss: 0.01496 Total loss: 0.87208 timestamp: 1655059196.7846107 iteration: 64605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05725 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.1231 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.14005 RPN box loss: 0.00637 RPN score loss: 0.00581 RPN total loss: 0.01219 Total loss: 0.843 timestamp: 1655059200.0409026 iteration: 64610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12151 FastRCNN class loss: 0.07751 FastRCNN total loss: 0.19902 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.14626 RPN box loss: 0.00772 RPN score loss: 0.00745 RPN total loss: 0.01517 Total loss: 0.92811 timestamp: 1655059203.2726922 iteration: 64615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08889 FastRCNN class loss: 0.07642 FastRCNN total loss: 0.16531 L1 loss: 0.0000e+00 L2 loss: 0.56767 Learning rate: 0.0004 Mask loss: 0.15928 RPN box loss: 0.01779 RPN score loss: 0.01018 RPN total loss: 0.02797 Total loss: 0.92023 timestamp: 1655059206.576158 iteration: 64620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10941 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.20258 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.14175 RPN box loss: 0.00965 RPN score loss: 0.00795 RPN total loss: 0.01761 Total loss: 0.9296 timestamp: 1655059209.9033568 iteration: 64625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14935 FastRCNN class loss: 0.14451 FastRCNN total loss: 0.29386 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.14999 RPN box loss: 0.00784 RPN score loss: 0.00472 RPN total loss: 0.01256 Total loss: 1.02408 timestamp: 1655059213.1583953 iteration: 64630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12215 FastRCNN class loss: 0.08801 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.18063 RPN box loss: 0.01679 RPN score loss: 0.00566 RPN total loss: 0.02246 Total loss: 0.9809 timestamp: 1655059216.440899 iteration: 64635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07233 FastRCNN class loss: 0.05156 FastRCNN total loss: 0.12388 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.1615 RPN box loss: 0.01587 RPN score loss: 0.00815 RPN total loss: 0.02402 Total loss: 0.87706 timestamp: 1655059219.6595786 iteration: 64640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08391 FastRCNN class loss: 0.07586 FastRCNN total loss: 0.15977 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.13883 RPN box loss: 0.01477 RPN score loss: 0.00578 RPN total loss: 0.02055 Total loss: 0.88681 timestamp: 1655059222.8241656 iteration: 64645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07174 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.15441 L1 loss: 0.0000e+00 L2 loss: 0.56766 Learning rate: 0.0004 Mask loss: 0.11741 RPN box loss: 0.01985 RPN score loss: 0.0025 RPN total loss: 0.02235 Total loss: 0.86182 timestamp: 1655059226.053386 iteration: 64650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08526 FastRCNN class loss: 0.06869 FastRCNN total loss: 0.15395 L1 loss: 0.0000e+00 L2 loss: 0.56765 Learning rate: 0.0004 Mask loss: 0.1233 RPN box loss: 0.01496 RPN score loss: 0.00589 RPN total loss: 0.02084 Total loss: 0.86575 timestamp: 1655059229.3764377 iteration: 64655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06497 FastRCNN class loss: 0.04326 FastRCNN total loss: 0.10824 L1 loss: 0.0000e+00 L2 loss: 0.56765 Learning rate: 0.0004 Mask loss: 0.12281 RPN box loss: 0.01129 RPN score loss: 0.00237 RPN total loss: 0.01366 Total loss: 0.81236 timestamp: 1655059232.641243 iteration: 64660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.08723 FastRCNN total loss: 0.19302 L1 loss: 0.0000e+00 L2 loss: 0.56765 Learning rate: 0.0004 Mask loss: 0.10915 RPN box loss: 0.01466 RPN score loss: 0.00671 RPN total loss: 0.02137 Total loss: 0.89119 timestamp: 1655059235.9515173 iteration: 64665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14149 FastRCNN class loss: 0.14231 FastRCNN total loss: 0.2838 L1 loss: 0.0000e+00 L2 loss: 0.56765 Learning rate: 0.0004 Mask loss: 0.16923 RPN box loss: 0.02204 RPN score loss: 0.00711 RPN total loss: 0.02915 Total loss: 1.04983 timestamp: 1655059239.26184 iteration: 64670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05361 FastRCNN class loss: 0.02838 FastRCNN total loss: 0.08199 L1 loss: 0.0000e+00 L2 loss: 0.56765 Learning rate: 0.0004 Mask loss: 0.0943 RPN box loss: 0.004 RPN score loss: 0.00175 RPN total loss: 0.00575 Total loss: 0.74969 timestamp: 1655059242.464255 iteration: 64675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09756 FastRCNN class loss: 0.08442 FastRCNN total loss: 0.18198 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.13735 RPN box loss: 0.0127 RPN score loss: 0.00736 RPN total loss: 0.02006 Total loss: 0.90704 timestamp: 1655059245.7823207 iteration: 64680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18096 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.28012 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.15715 RPN box loss: 0.02161 RPN score loss: 0.01044 RPN total loss: 0.03205 Total loss: 1.03696 timestamp: 1655059249.1910152 iteration: 64685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.08398 FastRCNN total loss: 0.18743 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.17577 RPN box loss: 0.01346 RPN score loss: 0.00544 RPN total loss: 0.01891 Total loss: 0.94975 timestamp: 1655059252.495996 iteration: 64690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05181 FastRCNN class loss: 0.0632 FastRCNN total loss: 0.115 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.13898 RPN box loss: 0.02641 RPN score loss: 0.00359 RPN total loss: 0.02999 Total loss: 0.85161 timestamp: 1655059255.8106306 iteration: 64695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11531 FastRCNN class loss: 0.10861 FastRCNN total loss: 0.22392 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.14821 RPN box loss: 0.007 RPN score loss: 0.00526 RPN total loss: 0.01226 Total loss: 0.95203 timestamp: 1655059259.099936 iteration: 64700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1756 FastRCNN class loss: 0.11417 FastRCNN total loss: 0.28977 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.18792 RPN box loss: 0.01947 RPN score loss: 0.014 RPN total loss: 0.03347 Total loss: 1.0788 timestamp: 1655059262.3981748 iteration: 64705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05953 FastRCNN class loss: 0.04263 FastRCNN total loss: 0.10216 L1 loss: 0.0000e+00 L2 loss: 0.56764 Learning rate: 0.0004 Mask loss: 0.11927 RPN box loss: 0.0066 RPN score loss: 0.00308 RPN total loss: 0.00968 Total loss: 0.79874 timestamp: 1655059265.7240064 iteration: 64710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10625 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.1888 L1 loss: 0.0000e+00 L2 loss: 0.56763 Learning rate: 0.0004 Mask loss: 0.14453 RPN box loss: 0.02872 RPN score loss: 0.01274 RPN total loss: 0.04147 Total loss: 0.94242 timestamp: 1655059268.9739404 iteration: 64715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07685 FastRCNN class loss: 0.04621 FastRCNN total loss: 0.12306 L1 loss: 0.0000e+00 L2 loss: 0.56763 Learning rate: 0.0004 Mask loss: 0.14089 RPN box loss: 0.00996 RPN score loss: 0.00263 RPN total loss: 0.0126 Total loss: 0.84418 timestamp: 1655059272.1987221 iteration: 64720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06595 FastRCNN class loss: 0.05319 FastRCNN total loss: 0.11914 L1 loss: 0.0000e+00 L2 loss: 0.56763 Learning rate: 0.0004 Mask loss: 0.11654 RPN box loss: 0.02735 RPN score loss: 0.00734 RPN total loss: 0.03469 Total loss: 0.838 timestamp: 1655059275.4210632 iteration: 64725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12553 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.20322 L1 loss: 0.0000e+00 L2 loss: 0.56763 Learning rate: 0.0004 Mask loss: 0.1404 RPN box loss: 0.01343 RPN score loss: 0.00538 RPN total loss: 0.01881 Total loss: 0.93006 timestamp: 1655059278.750785 iteration: 64730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.126 FastRCNN class loss: 0.11511 FastRCNN total loss: 0.2411 L1 loss: 0.0000e+00 L2 loss: 0.56763 Learning rate: 0.0004 Mask loss: 0.16582 RPN box loss: 0.01613 RPN score loss: 0.01008 RPN total loss: 0.02621 Total loss: 1.00075 timestamp: 1655059281.9437194 iteration: 64735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05166 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.0987 L1 loss: 0.0000e+00 L2 loss: 0.56762 Learning rate: 0.0004 Mask loss: 0.14636 RPN box loss: 0.00798 RPN score loss: 0.006 RPN total loss: 0.01398 Total loss: 0.82666 timestamp: 1655059285.2580721 iteration: 64740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12393 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.20959 L1 loss: 0.0000e+00 L2 loss: 0.56762 Learning rate: 0.0004 Mask loss: 0.11825 RPN box loss: 0.0071 RPN score loss: 0.003 RPN total loss: 0.0101 Total loss: 0.90555 timestamp: 1655059288.5827425 iteration: 64745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11973 FastRCNN class loss: 0.08319 FastRCNN total loss: 0.20292 L1 loss: 0.0000e+00 L2 loss: 0.56762 Learning rate: 0.0004 Mask loss: 0.15007 RPN box loss: 0.01465 RPN score loss: 0.00449 RPN total loss: 0.01915 Total loss: 0.93976 timestamp: 1655059291.841346 iteration: 64750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11498 FastRCNN class loss: 0.07544 FastRCNN total loss: 0.19041 L1 loss: 0.0000e+00 L2 loss: 0.56762 Learning rate: 0.0004 Mask loss: 0.10903 RPN box loss: 0.01756 RPN score loss: 0.00465 RPN total loss: 0.02221 Total loss: 0.88927 timestamp: 1655059295.1466348 iteration: 64755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.062 FastRCNN class loss: 0.06899 FastRCNN total loss: 0.13098 L1 loss: 0.0000e+00 L2 loss: 0.56762 Learning rate: 0.0004 Mask loss: 0.16363 RPN box loss: 0.02304 RPN score loss: 0.01811 RPN total loss: 0.04115 Total loss: 0.90338 timestamp: 1655059298.3441052 iteration: 64760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13295 FastRCNN class loss: 0.08648 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.19659 RPN box loss: 0.02002 RPN score loss: 0.00438 RPN total loss: 0.0244 Total loss: 1.00803 timestamp: 1655059301.6359224 iteration: 64765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04488 FastRCNN class loss: 0.04109 FastRCNN total loss: 0.08597 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.103 RPN box loss: 0.00801 RPN score loss: 0.00598 RPN total loss: 0.01399 Total loss: 0.77057 timestamp: 1655059304.8893065 iteration: 64770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12407 FastRCNN class loss: 0.12387 FastRCNN total loss: 0.24795 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.20428 RPN box loss: 0.02278 RPN score loss: 0.00973 RPN total loss: 0.03251 Total loss: 1.05235 timestamp: 1655059308.1939673 iteration: 64775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11631 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.16822 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.23578 RPN box loss: 0.03636 RPN score loss: 0.00738 RPN total loss: 0.04374 Total loss: 1.01535 timestamp: 1655059311.4252903 iteration: 64780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06596 FastRCNN class loss: 0.057 FastRCNN total loss: 0.12297 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.12965 RPN box loss: 0.01262 RPN score loss: 0.01094 RPN total loss: 0.02356 Total loss: 0.84379 timestamp: 1655059314.6218953 iteration: 64785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08878 FastRCNN class loss: 0.0637 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.56761 Learning rate: 0.0004 Mask loss: 0.13951 RPN box loss: 0.01888 RPN score loss: 0.00778 RPN total loss: 0.02666 Total loss: 0.88626 timestamp: 1655059317.8865087 iteration: 64790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07406 FastRCNN class loss: 0.04634 FastRCNN total loss: 0.1204 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.15642 RPN box loss: 0.00712 RPN score loss: 0.00237 RPN total loss: 0.00949 Total loss: 0.85391 timestamp: 1655059321.0842168 iteration: 64795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09794 FastRCNN class loss: 0.06746 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.21185 RPN box loss: 0.01572 RPN score loss: 0.00456 RPN total loss: 0.02028 Total loss: 0.96514 timestamp: 1655059324.3910768 iteration: 64800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13987 FastRCNN class loss: 0.07632 FastRCNN total loss: 0.21619 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.16357 RPN box loss: 0.01188 RPN score loss: 0.00452 RPN total loss: 0.01639 Total loss: 0.96376 timestamp: 1655059327.688933 iteration: 64805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09773 FastRCNN class loss: 0.08129 FastRCNN total loss: 0.17902 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.1438 RPN box loss: 0.02086 RPN score loss: 0.00498 RPN total loss: 0.02584 Total loss: 0.91626 timestamp: 1655059331.0322566 iteration: 64810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11741 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.19102 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.12631 RPN box loss: 0.0111 RPN score loss: 0.0034 RPN total loss: 0.0145 Total loss: 0.89943 timestamp: 1655059334.3803248 iteration: 64815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04221 FastRCNN class loss: 0.04923 FastRCNN total loss: 0.09145 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.12624 RPN box loss: 0.00475 RPN score loss: 0.00732 RPN total loss: 0.01207 Total loss: 0.79735 timestamp: 1655059337.757485 iteration: 64820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04588 FastRCNN class loss: 0.03876 FastRCNN total loss: 0.08464 L1 loss: 0.0000e+00 L2 loss: 0.5676 Learning rate: 0.0004 Mask loss: 0.10018 RPN box loss: 0.01277 RPN score loss: 0.00305 RPN total loss: 0.01581 Total loss: 0.76824 timestamp: 1655059341.0147202 iteration: 64825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14118 FastRCNN class loss: 0.09605 FastRCNN total loss: 0.23723 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.23722 RPN box loss: 0.01316 RPN score loss: 0.01616 RPN total loss: 0.02933 Total loss: 1.07137 timestamp: 1655059344.3047452 iteration: 64830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10084 FastRCNN class loss: 0.04633 FastRCNN total loss: 0.14717 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.10947 RPN box loss: 0.00675 RPN score loss: 0.00921 RPN total loss: 0.01596 Total loss: 0.84019 timestamp: 1655059347.5516315 iteration: 64835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12272 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.20498 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.14462 RPN box loss: 0.02708 RPN score loss: 0.00505 RPN total loss: 0.03213 Total loss: 0.94933 timestamp: 1655059350.847809 iteration: 64840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05937 FastRCNN class loss: 0.04024 FastRCNN total loss: 0.09961 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.11664 RPN box loss: 0.02121 RPN score loss: 0.00162 RPN total loss: 0.02283 Total loss: 0.80667 timestamp: 1655059354.1636055 iteration: 64845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08332 FastRCNN class loss: 0.03085 FastRCNN total loss: 0.11416 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.11696 RPN box loss: 0.00343 RPN score loss: 0.00462 RPN total loss: 0.00805 Total loss: 0.80676 timestamp: 1655059357.4173133 iteration: 64850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09277 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.16445 L1 loss: 0.0000e+00 L2 loss: 0.56759 Learning rate: 0.0004 Mask loss: 0.13513 RPN box loss: 0.00733 RPN score loss: 0.00998 RPN total loss: 0.01732 Total loss: 0.88448 timestamp: 1655059360.6708443 iteration: 64855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09208 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.1405 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.15961 RPN box loss: 0.01535 RPN score loss: 0.00385 RPN total loss: 0.0192 Total loss: 0.88689 timestamp: 1655059363.9423687 iteration: 64860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10623 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.18874 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.1344 RPN box loss: 0.01528 RPN score loss: 0.00954 RPN total loss: 0.02481 Total loss: 0.91553 timestamp: 1655059367.216606 iteration: 64865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13908 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.21694 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.17947 RPN box loss: 0.00913 RPN score loss: 0.01059 RPN total loss: 0.01973 Total loss: 0.98372 timestamp: 1655059370.4933372 iteration: 64870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0677 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.12171 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.10226 RPN box loss: 0.01562 RPN score loss: 0.00419 RPN total loss: 0.01981 Total loss: 0.81135 timestamp: 1655059373.796505 iteration: 64875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10278 FastRCNN class loss: 0.07608 FastRCNN total loss: 0.17885 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.1464 RPN box loss: 0.02063 RPN score loss: 0.00484 RPN total loss: 0.02547 Total loss: 0.91831 timestamp: 1655059377.063864 iteration: 64880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.10166 FastRCNN total loss: 0.1984 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.18264 RPN box loss: 0.0118 RPN score loss: 0.00504 RPN total loss: 0.01685 Total loss: 0.96547 timestamp: 1655059380.3349786 iteration: 64885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12947 FastRCNN class loss: 0.078 FastRCNN total loss: 0.20747 L1 loss: 0.0000e+00 L2 loss: 0.56758 Learning rate: 0.0004 Mask loss: 0.11886 RPN box loss: 0.03214 RPN score loss: 0.00212 RPN total loss: 0.03426 Total loss: 0.92816 timestamp: 1655059383.5924022 iteration: 64890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09112 FastRCNN class loss: 0.05241 FastRCNN total loss: 0.14352 L1 loss: 0.0000e+00 L2 loss: 0.56757 Learning rate: 0.0004 Mask loss: 0.07623 RPN box loss: 0.00396 RPN score loss: 0.0032 RPN total loss: 0.00717 Total loss: 0.79449 timestamp: 1655059386.8957844 iteration: 64895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09164 FastRCNN class loss: 0.05723 FastRCNN total loss: 0.14887 L1 loss: 0.0000e+00 L2 loss: 0.56757 Learning rate: 0.0004 Mask loss: 0.1448 RPN box loss: 0.00419 RPN score loss: 0.00308 RPN total loss: 0.00727 Total loss: 0.86852 timestamp: 1655059390.1308432 iteration: 64900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.18548 L1 loss: 0.0000e+00 L2 loss: 0.56757 Learning rate: 0.0004 Mask loss: 0.13288 RPN box loss: 0.00735 RPN score loss: 0.00789 RPN total loss: 0.01524 Total loss: 0.90117 timestamp: 1655059393.3639297 iteration: 64905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07517 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.1408 L1 loss: 0.0000e+00 L2 loss: 0.56757 Learning rate: 0.0004 Mask loss: 0.12342 RPN box loss: 0.00593 RPN score loss: 0.00221 RPN total loss: 0.00815 Total loss: 0.83993 timestamp: 1655059396.6175158 iteration: 64910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12277 FastRCNN class loss: 0.03898 FastRCNN total loss: 0.16175 L1 loss: 0.0000e+00 L2 loss: 0.56757 Learning rate: 0.0004 Mask loss: 0.11049 RPN box loss: 0.0131 RPN score loss: 0.00243 RPN total loss: 0.01552 Total loss: 0.85533 timestamp: 1655059399.9226751 iteration: 64915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0867 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.16199 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.16445 RPN box loss: 0.01104 RPN score loss: 0.00909 RPN total loss: 0.02013 Total loss: 0.91414 timestamp: 1655059403.223259 iteration: 64920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05841 FastRCNN class loss: 0.0367 FastRCNN total loss: 0.09511 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.11967 RPN box loss: 0.00554 RPN score loss: 0.00089 RPN total loss: 0.00643 Total loss: 0.78878 timestamp: 1655059406.4811313 iteration: 64925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10986 FastRCNN class loss: 0.04192 FastRCNN total loss: 0.15178 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.10374 RPN box loss: 0.00964 RPN score loss: 0.00251 RPN total loss: 0.01214 Total loss: 0.83522 timestamp: 1655059409.7458923 iteration: 64930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07696 FastRCNN class loss: 0.06308 FastRCNN total loss: 0.14003 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.13185 RPN box loss: 0.03129 RPN score loss: 0.00521 RPN total loss: 0.0365 Total loss: 0.87594 timestamp: 1655059413.0017517 iteration: 64935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.17587 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.13636 RPN box loss: 0.01611 RPN score loss: 0.0072 RPN total loss: 0.02331 Total loss: 0.90309 timestamp: 1655059416.2498226 iteration: 64940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10781 FastRCNN class loss: 0.04213 FastRCNN total loss: 0.14994 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.16005 RPN box loss: 0.01077 RPN score loss: 0.0042 RPN total loss: 0.01497 Total loss: 0.89252 timestamp: 1655059419.4872425 iteration: 64945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09177 FastRCNN class loss: 0.10529 FastRCNN total loss: 0.19706 L1 loss: 0.0000e+00 L2 loss: 0.56756 Learning rate: 0.0004 Mask loss: 0.15646 RPN box loss: 0.01798 RPN score loss: 0.00917 RPN total loss: 0.02715 Total loss: 0.94822 timestamp: 1655059422.7939456 iteration: 64950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15742 FastRCNN class loss: 0.17397 FastRCNN total loss: 0.33139 L1 loss: 0.0000e+00 L2 loss: 0.56755 Learning rate: 0.0004 Mask loss: 0.21578 RPN box loss: 0.03331 RPN score loss: 0.01718 RPN total loss: 0.05049 Total loss: 1.16521 timestamp: 1655059426.0623639 iteration: 64955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18373 FastRCNN class loss: 0.06274 FastRCNN total loss: 0.24647 L1 loss: 0.0000e+00 L2 loss: 0.56755 Learning rate: 0.0004 Mask loss: 0.14877 RPN box loss: 0.00764 RPN score loss: 0.00167 RPN total loss: 0.0093 Total loss: 0.97209 timestamp: 1655059429.2937412 iteration: 64960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0489 FastRCNN class loss: 0.05957 FastRCNN total loss: 0.10847 L1 loss: 0.0000e+00 L2 loss: 0.56755 Learning rate: 0.0004 Mask loss: 0.13946 RPN box loss: 0.00834 RPN score loss: 0.00266 RPN total loss: 0.011 Total loss: 0.82648 timestamp: 1655059432.5414326 iteration: 64965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0778 FastRCNN class loss: 0.03729 FastRCNN total loss: 0.11509 L1 loss: 0.0000e+00 L2 loss: 0.56755 Learning rate: 0.0004 Mask loss: 0.1769 RPN box loss: 0.00806 RPN score loss: 0.00105 RPN total loss: 0.00911 Total loss: 0.86865 timestamp: 1655059435.8000445 iteration: 64970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08985 FastRCNN class loss: 0.09744 FastRCNN total loss: 0.18729 L1 loss: 0.0000e+00 L2 loss: 0.56755 Learning rate: 0.0004 Mask loss: 0.13041 RPN box loss: 0.00894 RPN score loss: 0.0033 RPN total loss: 0.01224 Total loss: 0.89748 timestamp: 1655059439.082185 iteration: 64975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.06738 FastRCNN total loss: 0.16361 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.16313 RPN box loss: 0.01029 RPN score loss: 0.00884 RPN total loss: 0.01914 Total loss: 0.91342 timestamp: 1655059442.2915218 iteration: 64980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08778 FastRCNN class loss: 0.10749 FastRCNN total loss: 0.19527 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.18218 RPN box loss: 0.01407 RPN score loss: 0.0061 RPN total loss: 0.02017 Total loss: 0.96516 timestamp: 1655059445.5595157 iteration: 64985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09447 FastRCNN class loss: 0.08357 FastRCNN total loss: 0.17804 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.14743 RPN box loss: 0.02215 RPN score loss: 0.00376 RPN total loss: 0.02591 Total loss: 0.91893 timestamp: 1655059448.8698304 iteration: 64990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.09077 FastRCNN total loss: 0.23111 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.14531 RPN box loss: 0.02231 RPN score loss: 0.00573 RPN total loss: 0.02804 Total loss: 0.972 timestamp: 1655059452.1407433 iteration: 64995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08967 FastRCNN class loss: 0.08868 FastRCNN total loss: 0.17835 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.19597 RPN box loss: 0.01346 RPN score loss: 0.00217 RPN total loss: 0.01563 Total loss: 0.95749 timestamp: 1655059455.4200995 iteration: 65000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08753 FastRCNN class loss: 0.0764 FastRCNN total loss: 0.16393 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.16232 RPN box loss: 0.01385 RPN score loss: 0.00349 RPN total loss: 0.01733 Total loss: 0.91112 timestamp: 1655059458.7202785 iteration: 65005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1272 FastRCNN class loss: 0.095 FastRCNN total loss: 0.2222 L1 loss: 0.0000e+00 L2 loss: 0.56754 Learning rate: 0.0004 Mask loss: 0.15912 RPN box loss: 0.01895 RPN score loss: 0.03453 RPN total loss: 0.05348 Total loss: 1.00234 timestamp: 1655059462.0582428 iteration: 65010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.065 FastRCNN total loss: 0.16541 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.16569 RPN box loss: 0.01481 RPN score loss: 0.00249 RPN total loss: 0.0173 Total loss: 0.91593 timestamp: 1655059465.4099 iteration: 65015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.15832 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.17944 RPN box loss: 0.05288 RPN score loss: 0.01673 RPN total loss: 0.06961 Total loss: 0.9749 timestamp: 1655059468.675792 iteration: 65020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07163 FastRCNN class loss: 0.0451 FastRCNN total loss: 0.11674 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.08 RPN box loss: 0.0075 RPN score loss: 0.00463 RPN total loss: 0.01213 Total loss: 0.77639 timestamp: 1655059471.9856002 iteration: 65025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13148 FastRCNN class loss: 0.11446 FastRCNN total loss: 0.24594 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.21557 RPN box loss: 0.02202 RPN score loss: 0.01382 RPN total loss: 0.03584 Total loss: 1.06488 timestamp: 1655059475.2264528 iteration: 65030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0824 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.12939 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.12838 RPN box loss: 0.00471 RPN score loss: 0.00212 RPN total loss: 0.00682 Total loss: 0.83212 timestamp: 1655059478.5076234 iteration: 65035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08982 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.14271 L1 loss: 0.0000e+00 L2 loss: 0.56753 Learning rate: 0.0004 Mask loss: 0.13213 RPN box loss: 0.00909 RPN score loss: 0.00475 RPN total loss: 0.01384 Total loss: 0.8562 timestamp: 1655059481.819305 iteration: 65040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13174 FastRCNN class loss: 0.11679 FastRCNN total loss: 0.24853 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.21795 RPN box loss: 0.01993 RPN score loss: 0.00966 RPN total loss: 0.02959 Total loss: 1.06359 timestamp: 1655059485.048206 iteration: 65045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.12677 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.06725 RPN box loss: 0.01259 RPN score loss: 0.00579 RPN total loss: 0.01837 Total loss: 0.77992 timestamp: 1655059488.3094532 iteration: 65050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05196 FastRCNN class loss: 0.04612 FastRCNN total loss: 0.09808 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.13989 RPN box loss: 0.0063 RPN score loss: 0.00223 RPN total loss: 0.00853 Total loss: 0.81401 timestamp: 1655059491.5517411 iteration: 65055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11359 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.18306 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.12193 RPN box loss: 0.00839 RPN score loss: 0.00256 RPN total loss: 0.01095 Total loss: 0.88347 timestamp: 1655059494.7918653 iteration: 65060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11178 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.18359 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.12649 RPN box loss: 0.02288 RPN score loss: 0.00782 RPN total loss: 0.0307 Total loss: 0.9083 timestamp: 1655059497.9841928 iteration: 65065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10872 FastRCNN class loss: 0.0553 FastRCNN total loss: 0.16402 L1 loss: 0.0000e+00 L2 loss: 0.56752 Learning rate: 0.0004 Mask loss: 0.14231 RPN box loss: 0.03151 RPN score loss: 0.01278 RPN total loss: 0.04429 Total loss: 0.91814 timestamp: 1655059501.2606406 iteration: 65070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12293 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.20576 L1 loss: 0.0000e+00 L2 loss: 0.56751 Learning rate: 0.0004 Mask loss: 0.13173 RPN box loss: 0.03679 RPN score loss: 0.00632 RPN total loss: 0.04311 Total loss: 0.94811 timestamp: 1655059504.5037975 iteration: 65075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08309 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.17681 L1 loss: 0.0000e+00 L2 loss: 0.56751 Learning rate: 0.0004 Mask loss: 0.12782 RPN box loss: 0.00972 RPN score loss: 0.00116 RPN total loss: 0.01088 Total loss: 0.88302 timestamp: 1655059507.7653708 iteration: 65080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11128 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.1754 L1 loss: 0.0000e+00 L2 loss: 0.56751 Learning rate: 0.0004 Mask loss: 0.1365 RPN box loss: 0.00791 RPN score loss: 0.00615 RPN total loss: 0.01406 Total loss: 0.89347 timestamp: 1655059510.9750323 iteration: 65085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06825 FastRCNN class loss: 0.0811 FastRCNN total loss: 0.14935 L1 loss: 0.0000e+00 L2 loss: 0.56751 Learning rate: 0.0004 Mask loss: 0.1322 RPN box loss: 0.01508 RPN score loss: 0.00554 RPN total loss: 0.02062 Total loss: 0.86968 timestamp: 1655059514.2388532 iteration: 65090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08468 FastRCNN class loss: 0.0505 FastRCNN total loss: 0.13518 L1 loss: 0.0000e+00 L2 loss: 0.56751 Learning rate: 0.0004 Mask loss: 0.16305 RPN box loss: 0.01191 RPN score loss: 0.00465 RPN total loss: 0.01656 Total loss: 0.88229 timestamp: 1655059517.5082169 iteration: 65095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09286 FastRCNN class loss: 0.08158 FastRCNN total loss: 0.17443 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.14449 RPN box loss: 0.02157 RPN score loss: 0.00919 RPN total loss: 0.03076 Total loss: 0.91719 timestamp: 1655059520.7425125 iteration: 65100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08287 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.08385 RPN box loss: 0.01105 RPN score loss: 0.01086 RPN total loss: 0.02191 Total loss: 0.80691 timestamp: 1655059524.0689943 iteration: 65105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0572 FastRCNN class loss: 0.03891 FastRCNN total loss: 0.09611 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.09884 RPN box loss: 0.00683 RPN score loss: 0.00217 RPN total loss: 0.009 Total loss: 0.77146 timestamp: 1655059527.3757553 iteration: 65110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10016 FastRCNN class loss: 0.07886 FastRCNN total loss: 0.17901 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.15939 RPN box loss: 0.02081 RPN score loss: 0.00385 RPN total loss: 0.02466 Total loss: 0.93056 timestamp: 1655059530.6369731 iteration: 65115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13992 FastRCNN class loss: 0.08874 FastRCNN total loss: 0.22866 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.15303 RPN box loss: 0.01439 RPN score loss: 0.00359 RPN total loss: 0.01798 Total loss: 0.96717 timestamp: 1655059533.9236398 iteration: 65120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10132 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.15859 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.18327 RPN box loss: 0.00518 RPN score loss: 0.00242 RPN total loss: 0.00759 Total loss: 0.91695 timestamp: 1655059537.1813734 iteration: 65125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0565 FastRCNN class loss: 0.05255 FastRCNN total loss: 0.10905 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.11836 RPN box loss: 0.00811 RPN score loss: 0.00076 RPN total loss: 0.00888 Total loss: 0.80379 timestamp: 1655059540.4545054 iteration: 65130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06481 FastRCNN class loss: 0.07011 FastRCNN total loss: 0.13492 L1 loss: 0.0000e+00 L2 loss: 0.5675 Learning rate: 0.0004 Mask loss: 0.12852 RPN box loss: 0.0107 RPN score loss: 0.00579 RPN total loss: 0.01649 Total loss: 0.84742 timestamp: 1655059543.7572262 iteration: 65135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04522 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.10423 L1 loss: 0.0000e+00 L2 loss: 0.56749 Learning rate: 0.0004 Mask loss: 0.13097 RPN box loss: 0.00778 RPN score loss: 0.00583 RPN total loss: 0.01361 Total loss: 0.81631 timestamp: 1655059547.0203397 iteration: 65140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10123 FastRCNN class loss: 0.05503 FastRCNN total loss: 0.15625 L1 loss: 0.0000e+00 L2 loss: 0.56749 Learning rate: 0.0004 Mask loss: 0.09991 RPN box loss: 0.00559 RPN score loss: 0.00185 RPN total loss: 0.00744 Total loss: 0.8311 timestamp: 1655059550.2176695 iteration: 65145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08154 FastRCNN class loss: 0.05599 FastRCNN total loss: 0.13753 L1 loss: 0.0000e+00 L2 loss: 0.56749 Learning rate: 0.0004 Mask loss: 0.13252 RPN box loss: 0.00822 RPN score loss: 0.00421 RPN total loss: 0.01242 Total loss: 0.84997 timestamp: 1655059553.527965 iteration: 65150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09585 FastRCNN class loss: 0.0763 FastRCNN total loss: 0.17215 L1 loss: 0.0000e+00 L2 loss: 0.56749 Learning rate: 0.0004 Mask loss: 0.17728 RPN box loss: 0.01391 RPN score loss: 0.00413 RPN total loss: 0.01803 Total loss: 0.93496 timestamp: 1655059556.7231805 iteration: 65155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08369 FastRCNN class loss: 0.05808 FastRCNN total loss: 0.14178 L1 loss: 0.0000e+00 L2 loss: 0.56749 Learning rate: 0.0004 Mask loss: 0.09129 RPN box loss: 0.00543 RPN score loss: 0.00352 RPN total loss: 0.00895 Total loss: 0.8095 timestamp: 1655059560.0357978 iteration: 65160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11444 FastRCNN class loss: 0.09148 FastRCNN total loss: 0.20592 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.10698 RPN box loss: 0.01997 RPN score loss: 0.00217 RPN total loss: 0.02214 Total loss: 0.90252 timestamp: 1655059563.3043842 iteration: 65165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08057 FastRCNN class loss: 0.04713 FastRCNN total loss: 0.1277 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.13169 RPN box loss: 0.00301 RPN score loss: 0.004 RPN total loss: 0.00701 Total loss: 0.83389 timestamp: 1655059566.6103215 iteration: 65170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.11121 FastRCNN total loss: 0.24477 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.20971 RPN box loss: 0.01405 RPN score loss: 0.00479 RPN total loss: 0.01884 Total loss: 1.0408 timestamp: 1655059569.9772243 iteration: 65175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10541 FastRCNN class loss: 0.07333 FastRCNN total loss: 0.17874 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.11389 RPN box loss: 0.0195 RPN score loss: 0.00331 RPN total loss: 0.02281 Total loss: 0.88291 timestamp: 1655059573.2810175 iteration: 65180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13825 FastRCNN class loss: 0.12473 FastRCNN total loss: 0.26298 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.17846 RPN box loss: 0.00884 RPN score loss: 0.00538 RPN total loss: 0.01422 Total loss: 1.02314 timestamp: 1655059576.4685533 iteration: 65185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.114 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.19076 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.15328 RPN box loss: 0.00439 RPN score loss: 0.00757 RPN total loss: 0.01196 Total loss: 0.92347 timestamp: 1655059579.70009 iteration: 65190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09493 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.15399 L1 loss: 0.0000e+00 L2 loss: 0.56748 Learning rate: 0.0004 Mask loss: 0.15432 RPN box loss: 0.00753 RPN score loss: 0.00125 RPN total loss: 0.00878 Total loss: 0.88457 timestamp: 1655059582.8971372 iteration: 65195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15239 FastRCNN class loss: 0.0722 FastRCNN total loss: 0.22458 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.14698 RPN box loss: 0.04212 RPN score loss: 0.00559 RPN total loss: 0.04771 Total loss: 0.98675 timestamp: 1655059586.1392176 iteration: 65200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20338 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.28304 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.16846 RPN box loss: 0.00793 RPN score loss: 0.00399 RPN total loss: 0.01191 Total loss: 1.03089 timestamp: 1655059589.4425385 iteration: 65205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08807 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.15562 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.1535 RPN box loss: 0.00734 RPN score loss: 0.00073 RPN total loss: 0.00807 Total loss: 0.88466 timestamp: 1655059592.7079313 iteration: 65210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11815 FastRCNN class loss: 0.09242 FastRCNN total loss: 0.21057 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.14243 RPN box loss: 0.01747 RPN score loss: 0.00408 RPN total loss: 0.02154 Total loss: 0.942 timestamp: 1655059595.8926277 iteration: 65215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14357 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.20519 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.14506 RPN box loss: 0.01042 RPN score loss: 0.01542 RPN total loss: 0.02584 Total loss: 0.94355 timestamp: 1655059599.2374935 iteration: 65220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14273 FastRCNN class loss: 0.08283 FastRCNN total loss: 0.22556 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.09242 RPN box loss: 0.01614 RPN score loss: 0.0155 RPN total loss: 0.03163 Total loss: 0.91709 timestamp: 1655059602.554692 iteration: 65225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13323 FastRCNN class loss: 0.11803 FastRCNN total loss: 0.25126 L1 loss: 0.0000e+00 L2 loss: 0.56747 Learning rate: 0.0004 Mask loss: 0.19963 RPN box loss: 0.01525 RPN score loss: 0.02301 RPN total loss: 0.03826 Total loss: 1.05662 timestamp: 1655059605.8048377 iteration: 65230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05721 FastRCNN class loss: 0.05616 FastRCNN total loss: 0.11337 L1 loss: 0.0000e+00 L2 loss: 0.56746 Learning rate: 0.0004 Mask loss: 0.20014 RPN box loss: 0.01429 RPN score loss: 0.01336 RPN total loss: 0.02766 Total loss: 0.90863 timestamp: 1655059609.1644242 iteration: 65235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11145 FastRCNN class loss: 0.07123 FastRCNN total loss: 0.18268 L1 loss: 0.0000e+00 L2 loss: 0.56746 Learning rate: 0.0004 Mask loss: 0.13394 RPN box loss: 0.02215 RPN score loss: 0.00892 RPN total loss: 0.03107 Total loss: 0.91515 timestamp: 1655059612.4523602 iteration: 65240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04954 FastRCNN class loss: 0.05851 FastRCNN total loss: 0.10805 L1 loss: 0.0000e+00 L2 loss: 0.56746 Learning rate: 0.0004 Mask loss: 0.11758 RPN box loss: 0.01077 RPN score loss: 0.01099 RPN total loss: 0.02176 Total loss: 0.81485 timestamp: 1655059615.6556752 iteration: 65245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.067 FastRCNN class loss: 0.05381 FastRCNN total loss: 0.12081 L1 loss: 0.0000e+00 L2 loss: 0.56746 Learning rate: 0.0004 Mask loss: 0.13056 RPN box loss: 0.01847 RPN score loss: 0.00576 RPN total loss: 0.02423 Total loss: 0.84306 timestamp: 1655059618.9835517 iteration: 65250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.14874 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.15251 RPN box loss: 0.01081 RPN score loss: 0.00352 RPN total loss: 0.01434 Total loss: 0.88303 timestamp: 1655059622.2261379 iteration: 65255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16951 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.24355 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.11832 RPN box loss: 0.00468 RPN score loss: 0.00651 RPN total loss: 0.01118 Total loss: 0.94051 timestamp: 1655059625.4850585 iteration: 65260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07097 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.13504 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.14183 RPN box loss: 0.00982 RPN score loss: 0.00726 RPN total loss: 0.01708 Total loss: 0.8614 timestamp: 1655059628.7777164 iteration: 65265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0689 FastRCNN class loss: 0.04507 FastRCNN total loss: 0.11397 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.06155 RPN box loss: 0.00302 RPN score loss: 0.0019 RPN total loss: 0.00492 Total loss: 0.74789 timestamp: 1655059631.9318237 iteration: 65270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07484 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.14112 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.16375 RPN box loss: 0.01224 RPN score loss: 0.0044 RPN total loss: 0.01664 Total loss: 0.88896 timestamp: 1655059635.2020934 iteration: 65275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09795 FastRCNN class loss: 0.07706 FastRCNN total loss: 0.17501 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.13351 RPN box loss: 0.01377 RPN score loss: 0.0059 RPN total loss: 0.01967 Total loss: 0.89563 timestamp: 1655059638.4374757 iteration: 65280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09538 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.18161 L1 loss: 0.0000e+00 L2 loss: 0.56745 Learning rate: 0.0004 Mask loss: 0.10803 RPN box loss: 0.02135 RPN score loss: 0.01237 RPN total loss: 0.03372 Total loss: 0.89081 timestamp: 1655059641.6996088 iteration: 65285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13058 FastRCNN class loss: 0.05763 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 0.56744 Learning rate: 0.0004 Mask loss: 0.12093 RPN box loss: 0.00796 RPN score loss: 0.00414 RPN total loss: 0.0121 Total loss: 0.88869 timestamp: 1655059644.9696987 iteration: 65290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11936 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.1694 L1 loss: 0.0000e+00 L2 loss: 0.56744 Learning rate: 0.0004 Mask loss: 0.09266 RPN box loss: 0.0114 RPN score loss: 0.00866 RPN total loss: 0.02005 Total loss: 0.84956 timestamp: 1655059648.2258875 iteration: 65295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11616 FastRCNN class loss: 0.08519 FastRCNN total loss: 0.20135 L1 loss: 0.0000e+00 L2 loss: 0.56744 Learning rate: 0.0004 Mask loss: 0.17227 RPN box loss: 0.0096 RPN score loss: 0.00227 RPN total loss: 0.01187 Total loss: 0.95293 timestamp: 1655059651.5683491 iteration: 65300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07928 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.12256 L1 loss: 0.0000e+00 L2 loss: 0.56744 Learning rate: 0.0004 Mask loss: 0.15642 RPN box loss: 0.01183 RPN score loss: 0.00515 RPN total loss: 0.01698 Total loss: 0.8634 timestamp: 1655059654.864108 iteration: 65305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0974 FastRCNN class loss: 0.0828 FastRCNN total loss: 0.1802 L1 loss: 0.0000e+00 L2 loss: 0.56744 Learning rate: 0.0004 Mask loss: 0.20321 RPN box loss: 0.01823 RPN score loss: 0.01334 RPN total loss: 0.03157 Total loss: 0.98242 timestamp: 1655059658.175818 iteration: 65310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04673 FastRCNN class loss: 0.04066 FastRCNN total loss: 0.08739 L1 loss: 0.0000e+00 L2 loss: 0.56743 Learning rate: 0.0004 Mask loss: 0.10519 RPN box loss: 0.00304 RPN score loss: 0.00108 RPN total loss: 0.00412 Total loss: 0.76413 timestamp: 1655059661.447752 iteration: 65315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0667 FastRCNN class loss: 0.0456 FastRCNN total loss: 0.11231 L1 loss: 0.0000e+00 L2 loss: 0.56743 Learning rate: 0.0004 Mask loss: 0.15664 RPN box loss: 0.01614 RPN score loss: 0.002 RPN total loss: 0.01814 Total loss: 0.85452 timestamp: 1655059664.7415447 iteration: 65320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08428 FastRCNN class loss: 0.07962 FastRCNN total loss: 0.1639 L1 loss: 0.0000e+00 L2 loss: 0.56743 Learning rate: 0.0004 Mask loss: 0.16326 RPN box loss: 0.01842 RPN score loss: 0.00378 RPN total loss: 0.0222 Total loss: 0.91679 timestamp: 1655059667.9994621 iteration: 65325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.16281 L1 loss: 0.0000e+00 L2 loss: 0.56743 Learning rate: 0.0004 Mask loss: 0.14167 RPN box loss: 0.00959 RPN score loss: 0.00771 RPN total loss: 0.01731 Total loss: 0.88921 timestamp: 1655059671.2644272 iteration: 65330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13051 FastRCNN class loss: 0.0982 FastRCNN total loss: 0.22872 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.14573 RPN box loss: 0.01364 RPN score loss: 0.00501 RPN total loss: 0.01864 Total loss: 0.96051 timestamp: 1655059674.56756 iteration: 65335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.063 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.12712 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.11134 RPN box loss: 0.01184 RPN score loss: 0.00496 RPN total loss: 0.01681 Total loss: 0.82268 timestamp: 1655059677.810293 iteration: 65340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07991 FastRCNN class loss: 0.06964 FastRCNN total loss: 0.14956 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.1273 RPN box loss: 0.03621 RPN score loss: 0.00531 RPN total loss: 0.04152 Total loss: 0.8858 timestamp: 1655059681.0086641 iteration: 65345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04438 FastRCNN class loss: 0.05522 FastRCNN total loss: 0.0996 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.13195 RPN box loss: 0.02056 RPN score loss: 0.00379 RPN total loss: 0.02436 Total loss: 0.82333 timestamp: 1655059684.2603614 iteration: 65350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09442 FastRCNN class loss: 0.06834 FastRCNN total loss: 0.16276 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.12059 RPN box loss: 0.00787 RPN score loss: 0.01169 RPN total loss: 0.01955 Total loss: 0.87032 timestamp: 1655059687.604769 iteration: 65355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14221 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.22457 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.13883 RPN box loss: 0.01963 RPN score loss: 0.01683 RPN total loss: 0.03646 Total loss: 0.96728 timestamp: 1655059690.8520408 iteration: 65360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09625 FastRCNN class loss: 0.0468 FastRCNN total loss: 0.14305 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.11931 RPN box loss: 0.03434 RPN score loss: 0.00423 RPN total loss: 0.03858 Total loss: 0.86835 timestamp: 1655059694.1062114 iteration: 65365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04966 FastRCNN class loss: 0.03792 FastRCNN total loss: 0.08758 L1 loss: 0.0000e+00 L2 loss: 0.56742 Learning rate: 0.0004 Mask loss: 0.15519 RPN box loss: 0.00687 RPN score loss: 0.00546 RPN total loss: 0.01232 Total loss: 0.82251 timestamp: 1655059697.306326 iteration: 65370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.15655 L1 loss: 0.0000e+00 L2 loss: 0.56741 Learning rate: 0.0004 Mask loss: 0.13045 RPN box loss: 0.00772 RPN score loss: 0.00361 RPN total loss: 0.01133 Total loss: 0.86575 timestamp: 1655059700.550057 iteration: 65375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12792 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.2028 L1 loss: 0.0000e+00 L2 loss: 0.56741 Learning rate: 0.0004 Mask loss: 0.19321 RPN box loss: 0.01551 RPN score loss: 0.01474 RPN total loss: 0.03025 Total loss: 0.99367 timestamp: 1655059703.813858 iteration: 65380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16176 FastRCNN class loss: 0.07089 FastRCNN total loss: 0.23265 L1 loss: 0.0000e+00 L2 loss: 0.56741 Learning rate: 0.0004 Mask loss: 0.14329 RPN box loss: 0.01585 RPN score loss: 0.00863 RPN total loss: 0.02448 Total loss: 0.96782 timestamp: 1655059707.07698 iteration: 65385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09643 FastRCNN class loss: 0.05413 FastRCNN total loss: 0.15056 L1 loss: 0.0000e+00 L2 loss: 0.56741 Learning rate: 0.0004 Mask loss: 0.1094 RPN box loss: 0.01845 RPN score loss: 0.00302 RPN total loss: 0.02146 Total loss: 0.84883 timestamp: 1655059710.2944412 iteration: 65390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06811 FastRCNN class loss: 0.07745 FastRCNN total loss: 0.14556 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.13625 RPN box loss: 0.02625 RPN score loss: 0.00626 RPN total loss: 0.03251 Total loss: 0.88173 timestamp: 1655059713.5240474 iteration: 65395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06813 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.11817 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.12265 RPN box loss: 0.02102 RPN score loss: 0.00606 RPN total loss: 0.02708 Total loss: 0.83531 timestamp: 1655059716.8129792 iteration: 65400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13353 FastRCNN class loss: 0.04963 FastRCNN total loss: 0.18317 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.14507 RPN box loss: 0.01577 RPN score loss: 0.00243 RPN total loss: 0.0182 Total loss: 0.91384 timestamp: 1655059720.0494108 iteration: 65405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0632 FastRCNN class loss: 0.06381 FastRCNN total loss: 0.127 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.08804 RPN box loss: 0.01204 RPN score loss: 0.00347 RPN total loss: 0.01551 Total loss: 0.79795 timestamp: 1655059723.2854648 iteration: 65410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06636 FastRCNN class loss: 0.04184 FastRCNN total loss: 0.1082 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.12485 RPN box loss: 0.00446 RPN score loss: 0.00071 RPN total loss: 0.00517 Total loss: 0.80562 timestamp: 1655059726.553405 iteration: 65415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12758 FastRCNN class loss: 0.05302 FastRCNN total loss: 0.1806 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.17924 RPN box loss: 0.00902 RPN score loss: 0.00606 RPN total loss: 0.01508 Total loss: 0.94232 timestamp: 1655059729.7810307 iteration: 65420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0597 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.10384 L1 loss: 0.0000e+00 L2 loss: 0.5674 Learning rate: 0.0004 Mask loss: 0.10238 RPN box loss: 0.01406 RPN score loss: 0.00794 RPN total loss: 0.022 Total loss: 0.79562 timestamp: 1655059733.0532293 iteration: 65425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06839 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.14912 L1 loss: 0.0000e+00 L2 loss: 0.56739 Learning rate: 0.0004 Mask loss: 0.1592 RPN box loss: 0.01666 RPN score loss: 0.01169 RPN total loss: 0.02835 Total loss: 0.90407 timestamp: 1655059736.3068776 iteration: 65430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07188 FastRCNN class loss: 0.03322 FastRCNN total loss: 0.1051 L1 loss: 0.0000e+00 L2 loss: 0.56739 Learning rate: 0.0004 Mask loss: 0.12492 RPN box loss: 0.00772 RPN score loss: 0.00141 RPN total loss: 0.00913 Total loss: 0.80654 timestamp: 1655059739.5609822 iteration: 65435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08068 FastRCNN class loss: 0.05458 FastRCNN total loss: 0.13526 L1 loss: 0.0000e+00 L2 loss: 0.56739 Learning rate: 0.0004 Mask loss: 0.10805 RPN box loss: 0.01261 RPN score loss: 0.00134 RPN total loss: 0.01395 Total loss: 0.82464 timestamp: 1655059742.7593253 iteration: 65440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11953 FastRCNN class loss: 0.07824 FastRCNN total loss: 0.19777 L1 loss: 0.0000e+00 L2 loss: 0.56739 Learning rate: 0.0004 Mask loss: 0.22188 RPN box loss: 0.02604 RPN score loss: 0.01189 RPN total loss: 0.03793 Total loss: 1.02497 timestamp: 1655059746.1146445 iteration: 65445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04682 FastRCNN class loss: 0.04181 FastRCNN total loss: 0.08863 L1 loss: 0.0000e+00 L2 loss: 0.56739 Learning rate: 0.0004 Mask loss: 0.12804 RPN box loss: 0.00747 RPN score loss: 0.0015 RPN total loss: 0.00896 Total loss: 0.79301 timestamp: 1655059749.4059818 iteration: 65450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08344 FastRCNN class loss: 0.05022 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.09336 RPN box loss: 0.00892 RPN score loss: 0.00109 RPN total loss: 0.01 Total loss: 0.8044 timestamp: 1655059752.6807098 iteration: 65455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11922 FastRCNN class loss: 0.08611 FastRCNN total loss: 0.20534 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.14707 RPN box loss: 0.01413 RPN score loss: 0.00623 RPN total loss: 0.02036 Total loss: 0.94015 timestamp: 1655059755.9160333 iteration: 65460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12591 FastRCNN class loss: 0.07657 FastRCNN total loss: 0.20248 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.10179 RPN box loss: 0.01657 RPN score loss: 0.00236 RPN total loss: 0.01892 Total loss: 0.89058 timestamp: 1655059759.084102 iteration: 65465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11507 FastRCNN class loss: 0.09198 FastRCNN total loss: 0.20705 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.17873 RPN box loss: 0.01031 RPN score loss: 0.00864 RPN total loss: 0.01894 Total loss: 0.97211 timestamp: 1655059762.3213139 iteration: 65470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10632 FastRCNN class loss: 0.07504 FastRCNN total loss: 0.18136 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.17978 RPN box loss: 0.00988 RPN score loss: 0.01211 RPN total loss: 0.02198 Total loss: 0.95051 timestamp: 1655059765.6103585 iteration: 65475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.04079 FastRCNN total loss: 0.14009 L1 loss: 0.0000e+00 L2 loss: 0.56738 Learning rate: 0.0004 Mask loss: 0.13026 RPN box loss: 0.01025 RPN score loss: 0.00504 RPN total loss: 0.01528 Total loss: 0.85301 timestamp: 1655059768.946549 iteration: 65480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04491 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.08779 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.10838 RPN box loss: 0.02125 RPN score loss: 0.00532 RPN total loss: 0.02657 Total loss: 0.79011 timestamp: 1655059772.1760602 iteration: 65485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.20816 RPN box loss: 0.01048 RPN score loss: 0.00282 RPN total loss: 0.0133 Total loss: 0.95418 timestamp: 1655059775.5077593 iteration: 65490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13081 FastRCNN class loss: 0.09975 FastRCNN total loss: 0.23056 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.15964 RPN box loss: 0.01082 RPN score loss: 0.00341 RPN total loss: 0.01423 Total loss: 0.97181 timestamp: 1655059778.7495716 iteration: 65495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12174 FastRCNN class loss: 0.09371 FastRCNN total loss: 0.21545 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.14629 RPN box loss: 0.04039 RPN score loss: 0.00551 RPN total loss: 0.04589 Total loss: 0.975 timestamp: 1655059781.996009 iteration: 65500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05134 FastRCNN class loss: 0.02935 FastRCNN total loss: 0.08069 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.09548 RPN box loss: 0.00165 RPN score loss: 0.00328 RPN total loss: 0.00493 Total loss: 0.74846 timestamp: 1655059785.2638662 iteration: 65505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05529 FastRCNN class loss: 0.05982 FastRCNN total loss: 0.11511 L1 loss: 0.0000e+00 L2 loss: 0.56737 Learning rate: 0.0004 Mask loss: 0.15334 RPN box loss: 0.01037 RPN score loss: 0.00103 RPN total loss: 0.01139 Total loss: 0.84721 timestamp: 1655059788.5560446 iteration: 65510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09409 FastRCNN class loss: 0.09087 FastRCNN total loss: 0.18496 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.154 RPN box loss: 0.01827 RPN score loss: 0.00305 RPN total loss: 0.02132 Total loss: 0.92765 timestamp: 1655059791.778732 iteration: 65515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07908 FastRCNN class loss: 0.06706 FastRCNN total loss: 0.14614 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.18447 RPN box loss: 0.01937 RPN score loss: 0.00607 RPN total loss: 0.02544 Total loss: 0.92341 timestamp: 1655059794.9843838 iteration: 65520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1235 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.21116 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.18647 RPN box loss: 0.01678 RPN score loss: 0.01226 RPN total loss: 0.02904 Total loss: 0.99403 timestamp: 1655059798.2485285 iteration: 65525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07993 FastRCNN class loss: 0.06317 FastRCNN total loss: 0.1431 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.09888 RPN box loss: 0.00844 RPN score loss: 0.00279 RPN total loss: 0.01123 Total loss: 0.82057 timestamp: 1655059801.4999967 iteration: 65530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.07399 FastRCNN total loss: 0.16535 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.17623 RPN box loss: 0.00948 RPN score loss: 0.0013 RPN total loss: 0.01079 Total loss: 0.91972 timestamp: 1655059804.7738526 iteration: 65535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10375 FastRCNN class loss: 0.11429 FastRCNN total loss: 0.21805 L1 loss: 0.0000e+00 L2 loss: 0.56736 Learning rate: 0.0004 Mask loss: 0.19305 RPN box loss: 0.01704 RPN score loss: 0.01014 RPN total loss: 0.02718 Total loss: 1.00564 timestamp: 1655059808.0699801 iteration: 65540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12932 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.19507 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.14139 RPN box loss: 0.00614 RPN score loss: 0.00935 RPN total loss: 0.01549 Total loss: 0.91931 timestamp: 1655059811.363488 iteration: 65545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15252 FastRCNN class loss: 0.1025 FastRCNN total loss: 0.25503 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.17374 RPN box loss: 0.0251 RPN score loss: 0.00517 RPN total loss: 0.03027 Total loss: 1.02639 timestamp: 1655059814.589009 iteration: 65550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07549 FastRCNN class loss: 0.04678 FastRCNN total loss: 0.12227 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.09097 RPN box loss: 0.01326 RPN score loss: 0.00405 RPN total loss: 0.0173 Total loss: 0.7979 timestamp: 1655059817.809209 iteration: 65555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14377 FastRCNN class loss: 0.11749 FastRCNN total loss: 0.26126 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.22033 RPN box loss: 0.01797 RPN score loss: 0.01451 RPN total loss: 0.03248 Total loss: 1.08142 timestamp: 1655059821.0522647 iteration: 65560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06241 FastRCNN class loss: 0.04821 FastRCNN total loss: 0.11062 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.12205 RPN box loss: 0.00588 RPN score loss: 0.00598 RPN total loss: 0.01186 Total loss: 0.81188 timestamp: 1655059824.3413177 iteration: 65565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15527 FastRCNN class loss: 0.06473 FastRCNN total loss: 0.22 L1 loss: 0.0000e+00 L2 loss: 0.56735 Learning rate: 0.0004 Mask loss: 0.18026 RPN box loss: 0.01814 RPN score loss: 0.00467 RPN total loss: 0.02281 Total loss: 0.99041 timestamp: 1655059827.5881994 iteration: 65570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04556 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.10348 L1 loss: 0.0000e+00 L2 loss: 0.56734 Learning rate: 0.0004 Mask loss: 0.13172 RPN box loss: 0.00877 RPN score loss: 0.00698 RPN total loss: 0.01575 Total loss: 0.81829 timestamp: 1655059830.8417194 iteration: 65575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12393 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.21331 L1 loss: 0.0000e+00 L2 loss: 0.56734 Learning rate: 0.0004 Mask loss: 0.11359 RPN box loss: 0.01099 RPN score loss: 0.00541 RPN total loss: 0.01641 Total loss: 0.91064 timestamp: 1655059834.1600246 iteration: 65580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06655 FastRCNN class loss: 0.10874 FastRCNN total loss: 0.17529 L1 loss: 0.0000e+00 L2 loss: 0.56734 Learning rate: 0.0004 Mask loss: 0.12834 RPN box loss: 0.01854 RPN score loss: 0.00352 RPN total loss: 0.02206 Total loss: 0.89303 timestamp: 1655059837.4577584 iteration: 65585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.05424 FastRCNN total loss: 0.14808 L1 loss: 0.0000e+00 L2 loss: 0.56734 Learning rate: 0.0004 Mask loss: 0.09455 RPN box loss: 0.00972 RPN score loss: 0.00142 RPN total loss: 0.01114 Total loss: 0.82111 timestamp: 1655059840.7580652 iteration: 65590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09001 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.16058 L1 loss: 0.0000e+00 L2 loss: 0.56734 Learning rate: 0.0004 Mask loss: 0.12872 RPN box loss: 0.02147 RPN score loss: 0.00609 RPN total loss: 0.02756 Total loss: 0.88419 timestamp: 1655059844.0315495 iteration: 65595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08442 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.15202 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.16845 RPN box loss: 0.01883 RPN score loss: 0.00963 RPN total loss: 0.02846 Total loss: 0.91626 timestamp: 1655059847.2750711 iteration: 65600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11657 FastRCNN class loss: 0.12097 FastRCNN total loss: 0.23754 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.1794 RPN box loss: 0.00698 RPN score loss: 0.00473 RPN total loss: 0.01171 Total loss: 0.99598 timestamp: 1655059850.5514147 iteration: 65605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04094 FastRCNN class loss: 0.03879 FastRCNN total loss: 0.07972 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.10956 RPN box loss: 0.00399 RPN score loss: 0.00104 RPN total loss: 0.00503 Total loss: 0.76164 timestamp: 1655059853.796889 iteration: 65610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0488 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.11028 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.14984 RPN box loss: 0.01409 RPN score loss: 0.00442 RPN total loss: 0.01851 Total loss: 0.84597 timestamp: 1655059857.1359384 iteration: 65615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12021 FastRCNN class loss: 0.05744 FastRCNN total loss: 0.17765 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.16102 RPN box loss: 0.00904 RPN score loss: 0.00681 RPN total loss: 0.01585 Total loss: 0.92184 timestamp: 1655059860.3861258 iteration: 65620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11309 FastRCNN class loss: 0.05965 FastRCNN total loss: 0.17274 L1 loss: 0.0000e+00 L2 loss: 0.56733 Learning rate: 0.0004 Mask loss: 0.1323 RPN box loss: 0.02585 RPN score loss: 0.00981 RPN total loss: 0.03566 Total loss: 0.90802 timestamp: 1655059863.6110108 iteration: 65625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13257 FastRCNN class loss: 0.07789 FastRCNN total loss: 0.21047 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.15377 RPN box loss: 0.02278 RPN score loss: 0.00525 RPN total loss: 0.02803 Total loss: 0.9596 timestamp: 1655059866.9320464 iteration: 65630 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09768 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.17744 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.15981 RPN box loss: 0.0093 RPN score loss: 0.00628 RPN total loss: 0.01558 Total loss: 0.92015 timestamp: 1655059870.1892958 iteration: 65635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11576 FastRCNN class loss: 0.06731 FastRCNN total loss: 0.18306 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.17103 RPN box loss: 0.01076 RPN score loss: 0.00447 RPN total loss: 0.01523 Total loss: 0.93665 timestamp: 1655059873.4397905 iteration: 65640 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05808 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.11127 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.08932 RPN box loss: 0.00496 RPN score loss: 0.00228 RPN total loss: 0.00724 Total loss: 0.77514 timestamp: 1655059876.6954246 iteration: 65645 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0852 FastRCNN class loss: 0.03735 FastRCNN total loss: 0.12255 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.12862 RPN box loss: 0.01255 RPN score loss: 0.0013 RPN total loss: 0.01386 Total loss: 0.83235 timestamp: 1655059879.9211528 iteration: 65650 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06112 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.10599 L1 loss: 0.0000e+00 L2 loss: 0.56732 Learning rate: 0.0004 Mask loss: 0.16877 RPN box loss: 0.00966 RPN score loss: 0.00357 RPN total loss: 0.01323 Total loss: 0.8553 timestamp: 1655059883.2361004 iteration: 65655 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11978 FastRCNN class loss: 0.08917 FastRCNN total loss: 0.20895 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.1834 RPN box loss: 0.02218 RPN score loss: 0.00351 RPN total loss: 0.02569 Total loss: 0.98535 timestamp: 1655059886.5263462 iteration: 65660 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0705 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.13897 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.12538 RPN box loss: 0.01137 RPN score loss: 0.00638 RPN total loss: 0.01775 Total loss: 0.84941 timestamp: 1655059889.811921 iteration: 65665 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11124 FastRCNN class loss: 0.08168 FastRCNN total loss: 0.19293 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.15378 RPN box loss: 0.02607 RPN score loss: 0.02141 RPN total loss: 0.04748 Total loss: 0.9615 timestamp: 1655059893.1115446 iteration: 65670 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06327 FastRCNN class loss: 0.03945 FastRCNN total loss: 0.10272 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.097 RPN box loss: 0.04105 RPN score loss: 0.00136 RPN total loss: 0.04241 Total loss: 0.80944 timestamp: 1655059896.3951285 iteration: 65675 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05452 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.12685 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.16885 RPN box loss: 0.0044 RPN score loss: 0.00152 RPN total loss: 0.00593 Total loss: 0.86893 timestamp: 1655059899.637889 iteration: 65680 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11356 FastRCNN class loss: 0.10148 FastRCNN total loss: 0.21504 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.17572 RPN box loss: 0.01564 RPN score loss: 0.0092 RPN total loss: 0.02484 Total loss: 0.98292 timestamp: 1655059902.8114903 iteration: 65685 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11579 FastRCNN class loss: 0.08178 FastRCNN total loss: 0.19756 L1 loss: 0.0000e+00 L2 loss: 0.56731 Learning rate: 0.0004 Mask loss: 0.14408 RPN box loss: 0.01644 RPN score loss: 0.00357 RPN total loss: 0.02002 Total loss: 0.92896 timestamp: 1655059906.096651 iteration: 65690 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09213 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.1812 L1 loss: 0.0000e+00 L2 loss: 0.5673 Learning rate: 0.0004 Mask loss: 0.1344 RPN box loss: 0.01213 RPN score loss: 0.00839 RPN total loss: 0.02052 Total loss: 0.90343 timestamp: 1655059909.383287 iteration: 65695 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09063 FastRCNN class loss: 0.06053 FastRCNN total loss: 0.15117 L1 loss: 0.0000e+00 L2 loss: 0.5673 Learning rate: 0.0004 Mask loss: 0.11257 RPN box loss: 0.01513 RPN score loss: 0.00769 RPN total loss: 0.02282 Total loss: 0.85386 timestamp: 1655059912.6291294 iteration: 65700 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15296 FastRCNN class loss: 0.08993 FastRCNN total loss: 0.24289 L1 loss: 0.0000e+00 L2 loss: 0.5673 Learning rate: 0.0004 Mask loss: 0.13366 RPN box loss: 0.00627 RPN score loss: 0.00624 RPN total loss: 0.0125 Total loss: 0.95636 timestamp: 1655059915.9351654 iteration: 65705 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06403 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.11929 L1 loss: 0.0000e+00 L2 loss: 0.5673 Learning rate: 0.0004 Mask loss: 0.1596 RPN box loss: 0.00476 RPN score loss: 0.00373 RPN total loss: 0.00849 Total loss: 0.85468 timestamp: 1655059919.2076693 iteration: 65710 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10923 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.17842 L1 loss: 0.0000e+00 L2 loss: 0.5673 Learning rate: 0.0004 Mask loss: 0.20019 RPN box loss: 0.0259 RPN score loss: 0.00622 RPN total loss: 0.03212 Total loss: 0.97803 timestamp: 1655059922.452308 iteration: 65715 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06859 FastRCNN class loss: 0.06293 FastRCNN total loss: 0.13152 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.1522 RPN box loss: 0.01928 RPN score loss: 0.00375 RPN total loss: 0.02303 Total loss: 0.87405 timestamp: 1655059925.6945362 iteration: 65720 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10573 FastRCNN class loss: 0.03686 FastRCNN total loss: 0.14259 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.114 RPN box loss: 0.01441 RPN score loss: 0.00285 RPN total loss: 0.01726 Total loss: 0.84114 timestamp: 1655059928.9228656 iteration: 65725 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.04616 FastRCNN total loss: 0.12212 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.13285 RPN box loss: 0.00721 RPN score loss: 0.00159 RPN total loss: 0.00879 Total loss: 0.83106 timestamp: 1655059932.196946 iteration: 65730 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.1713 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.1207 RPN box loss: 0.01986 RPN score loss: 0.00257 RPN total loss: 0.02243 Total loss: 0.88172 timestamp: 1655059935.4177105 iteration: 65735 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08414 FastRCNN class loss: 0.0516 FastRCNN total loss: 0.13574 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.13958 RPN box loss: 0.03286 RPN score loss: 0.00173 RPN total loss: 0.03459 Total loss: 0.8772 timestamp: 1655059938.767579 iteration: 65740 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09912 FastRCNN class loss: 0.0837 FastRCNN total loss: 0.18282 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.15155 RPN box loss: 0.02635 RPN score loss: 0.01621 RPN total loss: 0.04256 Total loss: 0.94423 timestamp: 1655059942.0320973 iteration: 65745 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09914 FastRCNN class loss: 0.04941 FastRCNN total loss: 0.14854 L1 loss: 0.0000e+00 L2 loss: 0.56729 Learning rate: 0.0004 Mask loss: 0.1633 RPN box loss: 0.00814 RPN score loss: 0.00368 RPN total loss: 0.01182 Total loss: 0.89094 timestamp: 1655059945.3291025 iteration: 65750 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09499 FastRCNN class loss: 0.092 FastRCNN total loss: 0.18699 L1 loss: 0.0000e+00 L2 loss: 0.56728 Learning rate: 0.0004 Mask loss: 0.16422 RPN box loss: 0.01584 RPN score loss: 0.00753 RPN total loss: 0.02338 Total loss: 0.94187 timestamp: 1655059948.5642047 iteration: 65755 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07178 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.1449 L1 loss: 0.0000e+00 L2 loss: 0.56728 Learning rate: 0.0004 Mask loss: 0.11724 RPN box loss: 0.01866 RPN score loss: 0.00339 RPN total loss: 0.02204 Total loss: 0.85147 timestamp: 1655059951.7522624 iteration: 65760 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.15267 L1 loss: 0.0000e+00 L2 loss: 0.56728 Learning rate: 0.0004 Mask loss: 0.17993 RPN box loss: 0.01137 RPN score loss: 0.00648 RPN total loss: 0.01785 Total loss: 0.91772 timestamp: 1655059955.0106096 iteration: 65765 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08871 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.56728 Learning rate: 0.0004 Mask loss: 0.16755 RPN box loss: 0.00317 RPN score loss: 0.00411 RPN total loss: 0.00728 Total loss: 0.90877 timestamp: 1655059958.3265805 iteration: 65770 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09954 FastRCNN class loss: 0.09696 FastRCNN total loss: 0.19649 L1 loss: 0.0000e+00 L2 loss: 0.56728 Learning rate: 0.0004 Mask loss: 0.1589 RPN box loss: 0.05114 RPN score loss: 0.00518 RPN total loss: 0.05631 Total loss: 0.97899 timestamp: 1655059961.5476632 iteration: 65775 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05219 FastRCNN class loss: 0.04645 FastRCNN total loss: 0.09864 L1 loss: 0.0000e+00 L2 loss: 0.56727 Learning rate: 0.0004 Mask loss: 0.15131 RPN box loss: 0.00639 RPN score loss: 0.00921 RPN total loss: 0.0156 Total loss: 0.83282 timestamp: 1655059964.777317 iteration: 65780 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07342 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.14362 L1 loss: 0.0000e+00 L2 loss: 0.56727 Learning rate: 0.0004 Mask loss: 0.12035 RPN box loss: 0.01444 RPN score loss: 0.00154 RPN total loss: 0.01598 Total loss: 0.84722 timestamp: 1655059968.0709999 iteration: 65785 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.1227 L1 loss: 0.0000e+00 L2 loss: 0.56727 Learning rate: 0.0004 Mask loss: 0.13501 RPN box loss: 0.00592 RPN score loss: 0.00612 RPN total loss: 0.01203 Total loss: 0.83702 timestamp: 1655059971.3060844 iteration: 65790 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10363 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.16776 L1 loss: 0.0000e+00 L2 loss: 0.56727 Learning rate: 0.0004 Mask loss: 0.1474 RPN box loss: 0.02066 RPN score loss: 0.01195 RPN total loss: 0.03261 Total loss: 0.91504 timestamp: 1655059974.5870535 iteration: 65795 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03978 FastRCNN class loss: 0.04351 FastRCNN total loss: 0.08329 L1 loss: 0.0000e+00 L2 loss: 0.56727 Learning rate: 0.0004 Mask loss: 0.12367 RPN box loss: 0.01211 RPN score loss: 0.00131 RPN total loss: 0.01341 Total loss: 0.78764 timestamp: 1655059977.894148 iteration: 65800 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13536 FastRCNN class loss: 0.08282 FastRCNN total loss: 0.21818 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.17293 RPN box loss: 0.01646 RPN score loss: 0.00734 RPN total loss: 0.0238 Total loss: 0.98217 timestamp: 1655059981.1774364 iteration: 65805 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0851 FastRCNN class loss: 0.07732 FastRCNN total loss: 0.16242 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.12652 RPN box loss: 0.02385 RPN score loss: 0.00873 RPN total loss: 0.03258 Total loss: 0.88879 timestamp: 1655059984.4993706 iteration: 65810 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12715 FastRCNN class loss: 0.09994 FastRCNN total loss: 0.22709 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.17384 RPN box loss: 0.05274 RPN score loss: 0.01051 RPN total loss: 0.06325 Total loss: 1.03143 timestamp: 1655059987.7513547 iteration: 65815 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08563 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.15103 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.1989 RPN box loss: 0.02031 RPN score loss: 0.00828 RPN total loss: 0.02859 Total loss: 0.94578 timestamp: 1655059991.0074112 iteration: 65820 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15151 FastRCNN class loss: 0.0724 FastRCNN total loss: 0.22391 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.14844 RPN box loss: 0.00756 RPN score loss: 0.00101 RPN total loss: 0.00857 Total loss: 0.94818 timestamp: 1655059994.306216 iteration: 65825 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05688 FastRCNN class loss: 0.04606 FastRCNN total loss: 0.10294 L1 loss: 0.0000e+00 L2 loss: 0.56726 Learning rate: 0.0004 Mask loss: 0.14197 RPN box loss: 0.00883 RPN score loss: 0.00174 RPN total loss: 0.01058 Total loss: 0.82274 timestamp: 1655059997.5965803 iteration: 65830 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11938 FastRCNN class loss: 0.06498 FastRCNN total loss: 0.18435 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.15271 RPN box loss: 0.02661 RPN score loss: 0.00455 RPN total loss: 0.03116 Total loss: 0.93548 timestamp: 1655060000.788331 iteration: 65835 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11008 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.1822 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.13077 RPN box loss: 0.00675 RPN score loss: 0.00158 RPN total loss: 0.00833 Total loss: 0.88855 timestamp: 1655060004.082143 iteration: 65840 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0858 FastRCNN class loss: 0.06022 FastRCNN total loss: 0.14602 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.30489 RPN box loss: 0.03503 RPN score loss: 0.01539 RPN total loss: 0.05042 Total loss: 1.06859 timestamp: 1655060007.3682995 iteration: 65845 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08095 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.15314 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.138 RPN box loss: 0.00936 RPN score loss: 0.00413 RPN total loss: 0.01349 Total loss: 0.87187 timestamp: 1655060010.6194248 iteration: 65850 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11028 FastRCNN class loss: 0.10863 FastRCNN total loss: 0.21891 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.16151 RPN box loss: 0.0202 RPN score loss: 0.00677 RPN total loss: 0.02697 Total loss: 0.97463 timestamp: 1655060013.897728 iteration: 65855 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06882 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.13051 L1 loss: 0.0000e+00 L2 loss: 0.56725 Learning rate: 0.0004 Mask loss: 0.1764 RPN box loss: 0.01267 RPN score loss: 0.01541 RPN total loss: 0.02808 Total loss: 0.90224 timestamp: 1655060017.2695057 iteration: 65860 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06831 FastRCNN class loss: 0.05154 FastRCNN total loss: 0.11985 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.08405 RPN box loss: 0.00587 RPN score loss: 0.00257 RPN total loss: 0.00844 Total loss: 0.77959 timestamp: 1655060020.5325627 iteration: 65865 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06978 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.12449 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.09791 RPN box loss: 0.00474 RPN score loss: 0.00324 RPN total loss: 0.00798 Total loss: 0.79761 timestamp: 1655060023.8339903 iteration: 65870 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05674 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.14041 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.10622 RPN box loss: 0.01113 RPN score loss: 0.0027 RPN total loss: 0.01382 Total loss: 0.8277 timestamp: 1655060027.1510146 iteration: 65875 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04611 FastRCNN class loss: 0.03904 FastRCNN total loss: 0.08515 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.13371 RPN box loss: 0.00618 RPN score loss: 0.01373 RPN total loss: 0.01991 Total loss: 0.80601 timestamp: 1655060030.4222856 iteration: 65880 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08369 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.14534 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.13206 RPN box loss: 0.02164 RPN score loss: 0.00133 RPN total loss: 0.02297 Total loss: 0.86762 timestamp: 1655060033.711609 iteration: 65885 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0948 FastRCNN class loss: 0.07064 FastRCNN total loss: 0.16544 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.19836 RPN box loss: 0.01117 RPN score loss: 0.01509 RPN total loss: 0.02626 Total loss: 0.95729 timestamp: 1655060036.9917297 iteration: 65890 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11642 FastRCNN class loss: 0.12265 FastRCNN total loss: 0.23907 L1 loss: 0.0000e+00 L2 loss: 0.56724 Learning rate: 0.0004 Mask loss: 0.1378 RPN box loss: 0.01733 RPN score loss: 0.00531 RPN total loss: 0.02265 Total loss: 0.96676 timestamp: 1655060040.2706456 iteration: 65895 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11252 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.17559 L1 loss: 0.0000e+00 L2 loss: 0.56723 Learning rate: 0.0004 Mask loss: 0.10756 RPN box loss: 0.01295 RPN score loss: 0.00382 RPN total loss: 0.01677 Total loss: 0.86715 timestamp: 1655060043.538835 iteration: 65900 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08779 FastRCNN class loss: 0.07077 FastRCNN total loss: 0.15857 L1 loss: 0.0000e+00 L2 loss: 0.56723 Learning rate: 0.0004 Mask loss: 0.12744 RPN box loss: 0.00706 RPN score loss: 0.00162 RPN total loss: 0.00867 Total loss: 0.86191 timestamp: 1655060046.718996 iteration: 65905 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09447 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.1694 L1 loss: 0.0000e+00 L2 loss: 0.56723 Learning rate: 0.0004 Mask loss: 0.21319 RPN box loss: 0.02917 RPN score loss: 0.00906 RPN total loss: 0.03822 Total loss: 0.98804 timestamp: 1655060050.0356386 iteration: 65910 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16124 FastRCNN class loss: 0.09559 FastRCNN total loss: 0.25682 L1 loss: 0.0000e+00 L2 loss: 0.56723 Learning rate: 0.0004 Mask loss: 0.15625 RPN box loss: 0.00938 RPN score loss: 0.00586 RPN total loss: 0.01524 Total loss: 0.99554 timestamp: 1655060053.2835646 iteration: 65915 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09823 FastRCNN class loss: 0.07738 FastRCNN total loss: 0.17561 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.13722 RPN box loss: 0.01201 RPN score loss: 0.00589 RPN total loss: 0.0179 Total loss: 0.89796 timestamp: 1655060056.5622346 iteration: 65920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0862 FastRCNN class loss: 0.06109 FastRCNN total loss: 0.1473 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.13688 RPN box loss: 0.012 RPN score loss: 0.00723 RPN total loss: 0.01923 Total loss: 0.87063 timestamp: 1655060059.8693879 iteration: 65925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08655 FastRCNN class loss: 0.09008 FastRCNN total loss: 0.17663 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.11919 RPN box loss: 0.01364 RPN score loss: 0.00745 RPN total loss: 0.02109 Total loss: 0.88414 timestamp: 1655060063.137348 iteration: 65930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12421 FastRCNN class loss: 0.11071 FastRCNN total loss: 0.23491 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.18279 RPN box loss: 0.00782 RPN score loss: 0.00555 RPN total loss: 0.01337 Total loss: 0.99829 timestamp: 1655060066.3766882 iteration: 65935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09647 FastRCNN class loss: 0.05188 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.12461 RPN box loss: 0.02322 RPN score loss: 0.0031 RPN total loss: 0.02631 Total loss: 0.86649 timestamp: 1655060069.6375337 iteration: 65940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05072 FastRCNN class loss: 0.05331 FastRCNN total loss: 0.10403 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.16322 RPN box loss: 0.01747 RPN score loss: 0.00991 RPN total loss: 0.02737 Total loss: 0.86184 timestamp: 1655060072.9398675 iteration: 65945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11379 FastRCNN class loss: 0.10789 FastRCNN total loss: 0.22168 L1 loss: 0.0000e+00 L2 loss: 0.56722 Learning rate: 0.0004 Mask loss: 0.16007 RPN box loss: 0.02445 RPN score loss: 0.02114 RPN total loss: 0.04559 Total loss: 0.99455 timestamp: 1655060076.1927843 iteration: 65950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13418 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.19622 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.15794 RPN box loss: 0.0166 RPN score loss: 0.00592 RPN total loss: 0.02252 Total loss: 0.9439 timestamp: 1655060079.4286947 iteration: 65955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1219 FastRCNN class loss: 0.07565 FastRCNN total loss: 0.19756 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.13692 RPN box loss: 0.01693 RPN score loss: 0.00693 RPN total loss: 0.02386 Total loss: 0.92555 timestamp: 1655060082.7365456 iteration: 65960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11977 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.18189 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.12386 RPN box loss: 0.00914 RPN score loss: 0.0039 RPN total loss: 0.01304 Total loss: 0.88599 timestamp: 1655060085.9929092 iteration: 65965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14038 FastRCNN class loss: 0.09347 FastRCNN total loss: 0.23385 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.17492 RPN box loss: 0.01459 RPN score loss: 0.0078 RPN total loss: 0.02238 Total loss: 0.99837 timestamp: 1655060089.2334871 iteration: 65970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07643 FastRCNN class loss: 0.03612 FastRCNN total loss: 0.11255 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.11315 RPN box loss: 0.0074 RPN score loss: 0.00238 RPN total loss: 0.00978 Total loss: 0.80269 timestamp: 1655060092.514272 iteration: 65975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10806 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.19443 L1 loss: 0.0000e+00 L2 loss: 0.56721 Learning rate: 0.0004 Mask loss: 0.18676 RPN box loss: 0.01025 RPN score loss: 0.00754 RPN total loss: 0.01779 Total loss: 0.96619 timestamp: 1655060095.8175457 iteration: 65980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07982 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.14433 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.17767 RPN box loss: 0.009 RPN score loss: 0.00467 RPN total loss: 0.01367 Total loss: 0.90288 timestamp: 1655060099.0718186 iteration: 65985 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.13252 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.19639 RPN box loss: 0.00896 RPN score loss: 0.00533 RPN total loss: 0.01429 Total loss: 0.9104 timestamp: 1655060102.3264785 iteration: 65990 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11043 FastRCNN class loss: 0.0819 FastRCNN total loss: 0.19234 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.11642 RPN box loss: 0.03925 RPN score loss: 0.00502 RPN total loss: 0.04427 Total loss: 0.92023 timestamp: 1655060105.6069055 iteration: 65995 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03784 FastRCNN class loss: 0.02427 FastRCNN total loss: 0.06211 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.10933 RPN box loss: 0.00113 RPN score loss: 0.00275 RPN total loss: 0.00388 Total loss: 0.74251 timestamp: 1655060108.929536 iteration: 66000 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.05842 FastRCNN total loss: 0.13497 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.16723 RPN box loss: 0.00955 RPN score loss: 0.00195 RPN total loss: 0.0115 Total loss: 0.8809 timestamp: 1655060112.1753397 iteration: 66005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11521 FastRCNN class loss: 0.04399 FastRCNN total loss: 0.1592 L1 loss: 0.0000e+00 L2 loss: 0.5672 Learning rate: 0.0004 Mask loss: 0.10325 RPN box loss: 0.01145 RPN score loss: 0.00109 RPN total loss: 0.01254 Total loss: 0.84219 timestamp: 1655060115.4607353 iteration: 66010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.13512 FastRCNN total loss: 0.21672 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.16786 RPN box loss: 0.01736 RPN score loss: 0.00346 RPN total loss: 0.02082 Total loss: 0.9726 timestamp: 1655060118.7661471 iteration: 66015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11536 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.19952 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.13543 RPN box loss: 0.00744 RPN score loss: 0.00639 RPN total loss: 0.01383 Total loss: 0.91596 timestamp: 1655060122.0109518 iteration: 66020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12728 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.19392 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.15517 RPN box loss: 0.01376 RPN score loss: 0.00474 RPN total loss: 0.0185 Total loss: 0.93478 timestamp: 1655060125.2375503 iteration: 66025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15112 FastRCNN class loss: 0.06111 FastRCNN total loss: 0.21222 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.12712 RPN box loss: 0.01339 RPN score loss: 0.00148 RPN total loss: 0.01487 Total loss: 0.92141 timestamp: 1655060128.4678426 iteration: 66030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06191 FastRCNN class loss: 0.0712 FastRCNN total loss: 0.13311 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.29392 RPN box loss: 0.02766 RPN score loss: 0.0046 RPN total loss: 0.03226 Total loss: 1.02649 timestamp: 1655060131.808271 iteration: 66035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07764 FastRCNN class loss: 0.09915 FastRCNN total loss: 0.17679 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.15323 RPN box loss: 0.01736 RPN score loss: 0.01146 RPN total loss: 0.02882 Total loss: 0.92603 timestamp: 1655060135.031517 iteration: 66040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11638 FastRCNN class loss: 0.09703 FastRCNN total loss: 0.21341 L1 loss: 0.0000e+00 L2 loss: 0.56719 Learning rate: 0.0004 Mask loss: 0.16055 RPN box loss: 0.0097 RPN score loss: 0.00517 RPN total loss: 0.01487 Total loss: 0.95601 timestamp: 1655060138.305842 iteration: 66045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12684 FastRCNN class loss: 0.08887 FastRCNN total loss: 0.21571 L1 loss: 0.0000e+00 L2 loss: 0.56718 Learning rate: 0.0004 Mask loss: 0.22474 RPN box loss: 0.02805 RPN score loss: 0.00471 RPN total loss: 0.03276 Total loss: 1.04039 timestamp: 1655060141.5666974 iteration: 66050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10028 FastRCNN class loss: 0.06629 FastRCNN total loss: 0.16658 L1 loss: 0.0000e+00 L2 loss: 0.56718 Learning rate: 0.0004 Mask loss: 0.14371 RPN box loss: 0.0432 RPN score loss: 0.00838 RPN total loss: 0.05158 Total loss: 0.92905 timestamp: 1655060144.7872703 iteration: 66055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04962 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.09247 L1 loss: 0.0000e+00 L2 loss: 0.56718 Learning rate: 0.0004 Mask loss: 0.09445 RPN box loss: 0.04566 RPN score loss: 0.00138 RPN total loss: 0.04704 Total loss: 0.80115 timestamp: 1655060148.037683 iteration: 66060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.18368 L1 loss: 0.0000e+00 L2 loss: 0.56718 Learning rate: 0.0004 Mask loss: 0.15004 RPN box loss: 0.02395 RPN score loss: 0.00763 RPN total loss: 0.03158 Total loss: 0.93248 timestamp: 1655060151.3050308 iteration: 66065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06472 FastRCNN class loss: 0.04731 FastRCNN total loss: 0.11203 L1 loss: 0.0000e+00 L2 loss: 0.56718 Learning rate: 0.0004 Mask loss: 0.12215 RPN box loss: 0.01112 RPN score loss: 0.00233 RPN total loss: 0.01345 Total loss: 0.81481 timestamp: 1655060154.544241 iteration: 66070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14824 FastRCNN class loss: 0.11213 FastRCNN total loss: 0.26037 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.14314 RPN box loss: 0.01928 RPN score loss: 0.00713 RPN total loss: 0.02642 Total loss: 0.9971 timestamp: 1655060157.7934587 iteration: 66075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12441 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.18877 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.1401 RPN box loss: 0.00765 RPN score loss: 0.00786 RPN total loss: 0.01551 Total loss: 0.91156 timestamp: 1655060161.030454 iteration: 66080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08153 FastRCNN class loss: 0.04738 FastRCNN total loss: 0.12891 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.10825 RPN box loss: 0.00886 RPN score loss: 0.00662 RPN total loss: 0.01548 Total loss: 0.81981 timestamp: 1655060164.3425617 iteration: 66085 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06091 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.11282 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.11131 RPN box loss: 0.00678 RPN score loss: 0.00618 RPN total loss: 0.01296 Total loss: 0.80427 timestamp: 1655060167.6261082 iteration: 66090 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.04369 FastRCNN total loss: 0.11607 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.13851 RPN box loss: 0.00735 RPN score loss: 0.00209 RPN total loss: 0.00944 Total loss: 0.83119 timestamp: 1655060170.892502 iteration: 66095 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09598 FastRCNN class loss: 0.07552 FastRCNN total loss: 0.17149 L1 loss: 0.0000e+00 L2 loss: 0.56717 Learning rate: 0.0004 Mask loss: 0.17808 RPN box loss: 0.00801 RPN score loss: 0.00248 RPN total loss: 0.01048 Total loss: 0.92723 timestamp: 1655060174.2334497 iteration: 66100 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.0672 FastRCNN total loss: 0.14317 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.14837 RPN box loss: 0.0098 RPN score loss: 0.00743 RPN total loss: 0.01723 Total loss: 0.87594 timestamp: 1655060177.5148365 iteration: 66105 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10294 FastRCNN class loss: 0.06179 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.17094 RPN box loss: 0.01008 RPN score loss: 0.00741 RPN total loss: 0.01749 Total loss: 0.92032 timestamp: 1655060180.7511542 iteration: 66110 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06976 FastRCNN class loss: 0.04936 FastRCNN total loss: 0.11912 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.08051 RPN box loss: 0.0081 RPN score loss: 0.00144 RPN total loss: 0.00954 Total loss: 0.77634 timestamp: 1655060184.047864 iteration: 66115 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05682 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.11262 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.14474 RPN box loss: 0.01903 RPN score loss: 0.00289 RPN total loss: 0.02193 Total loss: 0.84645 timestamp: 1655060187.3203995 iteration: 66120 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.08821 FastRCNN total loss: 0.19457 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.13297 RPN box loss: 0.01383 RPN score loss: 0.00547 RPN total loss: 0.0193 Total loss: 0.914 timestamp: 1655060190.5076735 iteration: 66125 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.08049 FastRCNN total loss: 0.1783 L1 loss: 0.0000e+00 L2 loss: 0.56716 Learning rate: 0.0004 Mask loss: 0.12656 RPN box loss: 0.01245 RPN score loss: 0.00456 RPN total loss: 0.01701 Total loss: 0.88901 timestamp: 1655060193.713872 iteration: 66130 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15006 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.23272 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.14133 RPN box loss: 0.03515 RPN score loss: 0.00552 RPN total loss: 0.04067 Total loss: 0.98187 timestamp: 1655060196.95698 iteration: 66135 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06803 FastRCNN class loss: 0.0584 FastRCNN total loss: 0.12643 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.13134 RPN box loss: 0.02679 RPN score loss: 0.00546 RPN total loss: 0.03225 Total loss: 0.85717 timestamp: 1655060200.2435844 iteration: 66140 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09555 FastRCNN class loss: 0.05392 FastRCNN total loss: 0.14947 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.09345 RPN box loss: 0.01071 RPN score loss: 0.00222 RPN total loss: 0.01293 Total loss: 0.823 timestamp: 1655060203.5301092 iteration: 66145 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12249 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.1845 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.12436 RPN box loss: 0.00716 RPN score loss: 0.00503 RPN total loss: 0.01219 Total loss: 0.88821 timestamp: 1655060206.7849994 iteration: 66150 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06884 FastRCNN class loss: 0.07335 FastRCNN total loss: 0.14219 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.12163 RPN box loss: 0.01484 RPN score loss: 0.00225 RPN total loss: 0.01709 Total loss: 0.84806 timestamp: 1655060210.0781293 iteration: 66155 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06516 FastRCNN class loss: 0.07011 FastRCNN total loss: 0.13527 L1 loss: 0.0000e+00 L2 loss: 0.56715 Learning rate: 0.0004 Mask loss: 0.12325 RPN box loss: 0.01429 RPN score loss: 0.00635 RPN total loss: 0.02065 Total loss: 0.84632 timestamp: 1655060213.2779598 iteration: 66160 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09407 FastRCNN class loss: 0.05323 FastRCNN total loss: 0.1473 L1 loss: 0.0000e+00 L2 loss: 0.56714 Learning rate: 0.0004 Mask loss: 0.1051 RPN box loss: 0.00635 RPN score loss: 0.00076 RPN total loss: 0.00711 Total loss: 0.82665 timestamp: 1655060216.5539696 iteration: 66165 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07696 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.14101 L1 loss: 0.0000e+00 L2 loss: 0.56714 Learning rate: 0.0004 Mask loss: 0.14764 RPN box loss: 0.02701 RPN score loss: 0.01367 RPN total loss: 0.04067 Total loss: 0.89646 timestamp: 1655060219.8287396 iteration: 66170 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11913 FastRCNN class loss: 0.11887 FastRCNN total loss: 0.23799 L1 loss: 0.0000e+00 L2 loss: 0.56714 Learning rate: 0.0004 Mask loss: 0.13043 RPN box loss: 0.01765 RPN score loss: 0.00858 RPN total loss: 0.02623 Total loss: 0.96179 timestamp: 1655060223.100635 iteration: 66175 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.08104 FastRCNN total loss: 0.20943 L1 loss: 0.0000e+00 L2 loss: 0.56714 Learning rate: 0.0004 Mask loss: 0.22338 RPN box loss: 0.01468 RPN score loss: 0.0042 RPN total loss: 0.01888 Total loss: 1.01882 timestamp: 1655060226.349574 iteration: 66180 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0767 FastRCNN class loss: 0.05507 FastRCNN total loss: 0.13177 L1 loss: 0.0000e+00 L2 loss: 0.56714 Learning rate: 0.0004 Mask loss: 0.10463 RPN box loss: 0.00484 RPN score loss: 0.00841 RPN total loss: 0.01325 Total loss: 0.81679 timestamp: 1655060229.558574 iteration: 66185 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12758 FastRCNN class loss: 0.12892 FastRCNN total loss: 0.2565 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.20278 RPN box loss: 0.02979 RPN score loss: 0.00783 RPN total loss: 0.03761 Total loss: 1.06403 timestamp: 1655060232.9021368 iteration: 66190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06373 FastRCNN class loss: 0.05894 FastRCNN total loss: 0.12267 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.19477 RPN box loss: 0.0128 RPN score loss: 0.0023 RPN total loss: 0.01509 Total loss: 0.89967 timestamp: 1655060236.1632757 iteration: 66195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09029 FastRCNN class loss: 0.03955 FastRCNN total loss: 0.12985 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.12605 RPN box loss: 0.00902 RPN score loss: 0.00174 RPN total loss: 0.01076 Total loss: 0.83379 timestamp: 1655060239.4565976 iteration: 66200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04216 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.09341 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.09362 RPN box loss: 0.00447 RPN score loss: 0.00255 RPN total loss: 0.00702 Total loss: 0.76119 timestamp: 1655060242.7121522 iteration: 66205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07715 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.12631 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.10716 RPN box loss: 0.02206 RPN score loss: 0.0089 RPN total loss: 0.03096 Total loss: 0.83156 timestamp: 1655060245.9947636 iteration: 66210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07203 FastRCNN class loss: 0.05999 FastRCNN total loss: 0.13202 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.14898 RPN box loss: 0.02555 RPN score loss: 0.00443 RPN total loss: 0.02998 Total loss: 0.87811 timestamp: 1655060249.220586 iteration: 66215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08848 FastRCNN class loss: 0.06535 FastRCNN total loss: 0.15383 L1 loss: 0.0000e+00 L2 loss: 0.56713 Learning rate: 0.0004 Mask loss: 0.1398 RPN box loss: 0.02158 RPN score loss: 0.00419 RPN total loss: 0.02578 Total loss: 0.88653 timestamp: 1655060252.4683712 iteration: 66220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08192 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.14767 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.16269 RPN box loss: 0.02561 RPN score loss: 0.00804 RPN total loss: 0.03365 Total loss: 0.91113 timestamp: 1655060255.7867584 iteration: 66225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.15042 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.12132 RPN box loss: 0.02027 RPN score loss: 0.01318 RPN total loss: 0.03345 Total loss: 0.8723 timestamp: 1655060259.0860136 iteration: 66230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1082 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.18325 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.15635 RPN box loss: 0.03449 RPN score loss: 0.00741 RPN total loss: 0.0419 Total loss: 0.94862 timestamp: 1655060262.4255145 iteration: 66235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08439 FastRCNN class loss: 0.10557 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.15346 RPN box loss: 0.0128 RPN score loss: 0.00932 RPN total loss: 0.02213 Total loss: 0.93266 timestamp: 1655060265.6810083 iteration: 66240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10148 FastRCNN class loss: 0.0967 FastRCNN total loss: 0.19818 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.13827 RPN box loss: 0.0107 RPN score loss: 0.00732 RPN total loss: 0.01802 Total loss: 0.92158 timestamp: 1655060268.9333355 iteration: 66245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11501 FastRCNN class loss: 0.03567 FastRCNN total loss: 0.15068 L1 loss: 0.0000e+00 L2 loss: 0.56712 Learning rate: 0.0004 Mask loss: 0.10626 RPN box loss: 0.00548 RPN score loss: 0.00049 RPN total loss: 0.00597 Total loss: 0.83003 timestamp: 1655060272.2105813 iteration: 66250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.03899 FastRCNN total loss: 0.12357 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.1379 RPN box loss: 0.01023 RPN score loss: 0.00143 RPN total loss: 0.01166 Total loss: 0.84024 timestamp: 1655060275.4915202 iteration: 66255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0981 FastRCNN class loss: 0.04777 FastRCNN total loss: 0.14587 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.10725 RPN box loss: 0.00738 RPN score loss: 0.0028 RPN total loss: 0.01018 Total loss: 0.83042 timestamp: 1655060278.771597 iteration: 66260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11016 FastRCNN class loss: 0.10622 FastRCNN total loss: 0.21638 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.15542 RPN box loss: 0.01758 RPN score loss: 0.00631 RPN total loss: 0.02389 Total loss: 0.96281 timestamp: 1655060282.0173912 iteration: 66265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.17195 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.16221 RPN box loss: 0.0156 RPN score loss: 0.00715 RPN total loss: 0.02275 Total loss: 0.92402 timestamp: 1655060285.3185818 iteration: 66270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09548 FastRCNN class loss: 0.05927 FastRCNN total loss: 0.15475 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.14089 RPN box loss: 0.02204 RPN score loss: 0.00623 RPN total loss: 0.02827 Total loss: 0.89103 timestamp: 1655060288.5872421 iteration: 66275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07789 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.13446 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.11157 RPN box loss: 0.01148 RPN score loss: 0.00215 RPN total loss: 0.01362 Total loss: 0.82676 timestamp: 1655060291.827736 iteration: 66280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0689 FastRCNN class loss: 0.05246 FastRCNN total loss: 0.12136 L1 loss: 0.0000e+00 L2 loss: 0.56711 Learning rate: 0.0004 Mask loss: 0.12401 RPN box loss: 0.0046 RPN score loss: 0.00241 RPN total loss: 0.00701 Total loss: 0.81948 timestamp: 1655060295.0385373 iteration: 66285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.10938 FastRCNN total loss: 0.22934 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.14359 RPN box loss: 0.01337 RPN score loss: 0.00784 RPN total loss: 0.02121 Total loss: 0.96125 timestamp: 1655060298.26661 iteration: 66290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05489 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.10699 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.21294 RPN box loss: 0.02047 RPN score loss: 0.00664 RPN total loss: 0.02711 Total loss: 0.91415 timestamp: 1655060301.5752892 iteration: 66295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16464 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.25402 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.16277 RPN box loss: 0.03179 RPN score loss: 0.00724 RPN total loss: 0.03903 Total loss: 1.02292 timestamp: 1655060304.8499975 iteration: 66300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12915 FastRCNN class loss: 0.06632 FastRCNN total loss: 0.19547 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.16988 RPN box loss: 0.02075 RPN score loss: 0.00143 RPN total loss: 0.02217 Total loss: 0.95462 timestamp: 1655060308.0981288 iteration: 66305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.1163 FastRCNN total loss: 0.21995 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.16298 RPN box loss: 0.01973 RPN score loss: 0.00803 RPN total loss: 0.02776 Total loss: 0.97779 timestamp: 1655060311.3837578 iteration: 66310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1176 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.21319 L1 loss: 0.0000e+00 L2 loss: 0.5671 Learning rate: 0.0004 Mask loss: 0.26032 RPN box loss: 0.02002 RPN score loss: 0.00646 RPN total loss: 0.02648 Total loss: 1.06709 timestamp: 1655060314.6480517 iteration: 66315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07007 FastRCNN class loss: 0.06377 FastRCNN total loss: 0.13383 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.12461 RPN box loss: 0.00862 RPN score loss: 0.00665 RPN total loss: 0.01527 Total loss: 0.8408 timestamp: 1655060317.8892953 iteration: 66320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10596 FastRCNN class loss: 0.107 FastRCNN total loss: 0.21295 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.15731 RPN box loss: 0.01627 RPN score loss: 0.00515 RPN total loss: 0.02142 Total loss: 0.95878 timestamp: 1655060321.2415266 iteration: 66325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.0474 FastRCNN total loss: 0.1503 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.13318 RPN box loss: 0.00618 RPN score loss: 0.00754 RPN total loss: 0.01372 Total loss: 0.86429 timestamp: 1655060324.530113 iteration: 66330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1276 FastRCNN class loss: 0.07968 FastRCNN total loss: 0.20729 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.17856 RPN box loss: 0.02041 RPN score loss: 0.00239 RPN total loss: 0.0228 Total loss: 0.97574 timestamp: 1655060327.8113265 iteration: 66335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10877 FastRCNN class loss: 0.08706 FastRCNN total loss: 0.19583 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.15917 RPN box loss: 0.02799 RPN score loss: 0.0127 RPN total loss: 0.04068 Total loss: 0.96277 timestamp: 1655060331.0921748 iteration: 66340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0571 FastRCNN class loss: 0.04129 FastRCNN total loss: 0.09839 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.12873 RPN box loss: 0.00384 RPN score loss: 0.00422 RPN total loss: 0.00806 Total loss: 0.80227 timestamp: 1655060334.2966616 iteration: 66345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09288 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.16522 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.16644 RPN box loss: 0.02241 RPN score loss: 0.00436 RPN total loss: 0.02676 Total loss: 0.92551 timestamp: 1655060337.52067 iteration: 66350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08633 FastRCNN class loss: 0.08295 FastRCNN total loss: 0.16928 L1 loss: 0.0000e+00 L2 loss: 0.56709 Learning rate: 0.0004 Mask loss: 0.13086 RPN box loss: 0.02321 RPN score loss: 0.0052 RPN total loss: 0.02841 Total loss: 0.89563 timestamp: 1655060340.741342 iteration: 66355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11429 FastRCNN class loss: 0.11569 FastRCNN total loss: 0.22998 L1 loss: 0.0000e+00 L2 loss: 0.56708 Learning rate: 0.0004 Mask loss: 0.14604 RPN box loss: 0.02086 RPN score loss: 0.00485 RPN total loss: 0.02571 Total loss: 0.96881 timestamp: 1655060344.0290709 iteration: 66360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13349 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.20154 L1 loss: 0.0000e+00 L2 loss: 0.56708 Learning rate: 0.0004 Mask loss: 0.12481 RPN box loss: 0.00783 RPN score loss: 0.00469 RPN total loss: 0.01252 Total loss: 0.90596 timestamp: 1655060347.284769 iteration: 66365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10487 FastRCNN class loss: 0.06066 FastRCNN total loss: 0.16552 L1 loss: 0.0000e+00 L2 loss: 0.56708 Learning rate: 0.0004 Mask loss: 0.15037 RPN box loss: 0.01788 RPN score loss: 0.00594 RPN total loss: 0.02382 Total loss: 0.90679 timestamp: 1655060350.5719733 iteration: 66370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0891 FastRCNN class loss: 0.07233 FastRCNN total loss: 0.16142 L1 loss: 0.0000e+00 L2 loss: 0.56708 Learning rate: 0.0004 Mask loss: 0.14115 RPN box loss: 0.00639 RPN score loss: 0.00263 RPN total loss: 0.00903 Total loss: 0.87867 timestamp: 1655060353.8676183 iteration: 66375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1032 FastRCNN class loss: 0.0576 FastRCNN total loss: 0.1608 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.11691 RPN box loss: 0.00476 RPN score loss: 0.00119 RPN total loss: 0.00595 Total loss: 0.85073 timestamp: 1655060357.0805159 iteration: 66380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10946 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.17147 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.1197 RPN box loss: 0.01373 RPN score loss: 0.00533 RPN total loss: 0.01906 Total loss: 0.8773 timestamp: 1655060360.3908448 iteration: 66385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05451 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.1069 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.16813 RPN box loss: 0.01165 RPN score loss: 0.00326 RPN total loss: 0.01491 Total loss: 0.85702 timestamp: 1655060363.6754048 iteration: 66390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05392 FastRCNN class loss: 0.04661 FastRCNN total loss: 0.10053 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.14968 RPN box loss: 0.00913 RPN score loss: 0.00805 RPN total loss: 0.01718 Total loss: 0.83447 timestamp: 1655060366.9646082 iteration: 66395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07137 FastRCNN class loss: 0.07255 FastRCNN total loss: 0.14392 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.14707 RPN box loss: 0.00867 RPN score loss: 0.00714 RPN total loss: 0.0158 Total loss: 0.87386 timestamp: 1655060370.2203395 iteration: 66400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07685 FastRCNN class loss: 0.0692 FastRCNN total loss: 0.14606 L1 loss: 0.0000e+00 L2 loss: 0.56707 Learning rate: 0.0004 Mask loss: 0.14786 RPN box loss: 0.00787 RPN score loss: 0.00277 RPN total loss: 0.01064 Total loss: 0.87162 timestamp: 1655060373.429327 iteration: 66405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08569 FastRCNN class loss: 0.07367 FastRCNN total loss: 0.15937 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.14859 RPN box loss: 0.0214 RPN score loss: 0.01015 RPN total loss: 0.03155 Total loss: 0.90657 timestamp: 1655060376.7074416 iteration: 66410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06443 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.13481 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.11709 RPN box loss: 0.0192 RPN score loss: 0.00293 RPN total loss: 0.02213 Total loss: 0.84109 timestamp: 1655060379.929757 iteration: 66415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08233 FastRCNN class loss: 0.08617 FastRCNN total loss: 0.1685 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.1778 RPN box loss: 0.01943 RPN score loss: 0.00671 RPN total loss: 0.02614 Total loss: 0.9395 timestamp: 1655060383.1828995 iteration: 66420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11003 FastRCNN class loss: 0.05525 FastRCNN total loss: 0.16528 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.12164 RPN box loss: 0.01401 RPN score loss: 0.00185 RPN total loss: 0.01586 Total loss: 0.86984 timestamp: 1655060386.4134672 iteration: 66425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11095 FastRCNN class loss: 0.08921 FastRCNN total loss: 0.20016 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.18253 RPN box loss: 0.01455 RPN score loss: 0.01161 RPN total loss: 0.02615 Total loss: 0.9759 timestamp: 1655060389.6738386 iteration: 66430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09267 FastRCNN class loss: 0.0805 FastRCNN total loss: 0.17317 L1 loss: 0.0000e+00 L2 loss: 0.56706 Learning rate: 0.0004 Mask loss: 0.12118 RPN box loss: 0.01074 RPN score loss: 0.00835 RPN total loss: 0.01909 Total loss: 0.88051 timestamp: 1655060392.9427383 iteration: 66435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08874 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.17969 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.1729 RPN box loss: 0.0074 RPN score loss: 0.00643 RPN total loss: 0.01382 Total loss: 0.93346 timestamp: 1655060396.1754813 iteration: 66440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08208 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.15229 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.1442 RPN box loss: 0.01415 RPN score loss: 0.00251 RPN total loss: 0.01665 Total loss: 0.8802 timestamp: 1655060399.427157 iteration: 66445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12695 FastRCNN class loss: 0.07978 FastRCNN total loss: 0.20673 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.17019 RPN box loss: 0.01117 RPN score loss: 0.0033 RPN total loss: 0.01447 Total loss: 0.95845 timestamp: 1655060402.7550232 iteration: 66450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.11292 FastRCNN total loss: 0.21633 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.19877 RPN box loss: 0.00964 RPN score loss: 0.00782 RPN total loss: 0.01746 Total loss: 0.99961 timestamp: 1655060406.0208175 iteration: 66455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07243 FastRCNN class loss: 0.06291 FastRCNN total loss: 0.13534 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.15595 RPN box loss: 0.01001 RPN score loss: 0.00627 RPN total loss: 0.01628 Total loss: 0.87462 timestamp: 1655060409.3277802 iteration: 66460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13763 FastRCNN class loss: 0.0746 FastRCNN total loss: 0.21222 L1 loss: 0.0000e+00 L2 loss: 0.56705 Learning rate: 0.0004 Mask loss: 0.13441 RPN box loss: 0.01658 RPN score loss: 0.00451 RPN total loss: 0.02109 Total loss: 0.93476 timestamp: 1655060412.5586708 iteration: 66465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14703 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.22756 L1 loss: 0.0000e+00 L2 loss: 0.56704 Learning rate: 0.0004 Mask loss: 0.1555 RPN box loss: 0.01336 RPN score loss: 0.00166 RPN total loss: 0.01501 Total loss: 0.96512 timestamp: 1655060415.8092551 iteration: 66470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08469 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.15677 L1 loss: 0.0000e+00 L2 loss: 0.56704 Learning rate: 0.0004 Mask loss: 0.18609 RPN box loss: 0.00722 RPN score loss: 0.00078 RPN total loss: 0.008 Total loss: 0.9179 timestamp: 1655060419.1062093 iteration: 66475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.0543 FastRCNN total loss: 0.13341 L1 loss: 0.0000e+00 L2 loss: 0.56704 Learning rate: 0.0004 Mask loss: 0.11093 RPN box loss: 0.01566 RPN score loss: 0.00982 RPN total loss: 0.02549 Total loss: 0.83687 timestamp: 1655060422.3898795 iteration: 66480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10239 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.16169 L1 loss: 0.0000e+00 L2 loss: 0.56704 Learning rate: 0.0004 Mask loss: 0.10875 RPN box loss: 0.00352 RPN score loss: 0.0052 RPN total loss: 0.00872 Total loss: 0.8462 timestamp: 1655060425.6743598 iteration: 66485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08095 FastRCNN class loss: 0.05311 FastRCNN total loss: 0.13405 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.13908 RPN box loss: 0.01212 RPN score loss: 0.0034 RPN total loss: 0.01552 Total loss: 0.85569 timestamp: 1655060429.0172834 iteration: 66490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14527 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.22919 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.15189 RPN box loss: 0.01629 RPN score loss: 0.01279 RPN total loss: 0.02908 Total loss: 0.97719 timestamp: 1655060432.2728791 iteration: 66495 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17782 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.24447 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.14176 RPN box loss: 0.01688 RPN score loss: 0.00443 RPN total loss: 0.02131 Total loss: 0.97457 timestamp: 1655060435.6146274 iteration: 66500 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.1215 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.13826 RPN box loss: 0.01741 RPN score loss: 0.00525 RPN total loss: 0.02266 Total loss: 0.84945 timestamp: 1655060438.9174743 iteration: 66505 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06606 FastRCNN class loss: 0.06251 FastRCNN total loss: 0.12856 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.15942 RPN box loss: 0.03396 RPN score loss: 0.00623 RPN total loss: 0.04019 Total loss: 0.8952 timestamp: 1655060442.1984138 iteration: 66510 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11137 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.18773 L1 loss: 0.0000e+00 L2 loss: 0.56703 Learning rate: 0.0004 Mask loss: 0.1146 RPN box loss: 0.00596 RPN score loss: 0.00751 RPN total loss: 0.01347 Total loss: 0.88282 timestamp: 1655060445.5139372 iteration: 66515 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10476 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.1704 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.1445 RPN box loss: 0.01105 RPN score loss: 0.00192 RPN total loss: 0.01297 Total loss: 0.89489 timestamp: 1655060448.776021 iteration: 66520 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12915 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.19912 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.13748 RPN box loss: 0.00772 RPN score loss: 0.00232 RPN total loss: 0.01004 Total loss: 0.91367 timestamp: 1655060452.0746577 iteration: 66525 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09942 FastRCNN class loss: 0.06757 FastRCNN total loss: 0.16698 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.16449 RPN box loss: 0.00999 RPN score loss: 0.00368 RPN total loss: 0.01368 Total loss: 0.91217 timestamp: 1655060455.395835 iteration: 66530 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08286 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.147 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.11926 RPN box loss: 0.00759 RPN score loss: 0.00629 RPN total loss: 0.01387 Total loss: 0.84716 timestamp: 1655060458.6780927 iteration: 66535 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1086 FastRCNN class loss: 0.08672 FastRCNN total loss: 0.19531 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.17641 RPN box loss: 0.01553 RPN score loss: 0.00819 RPN total loss: 0.02372 Total loss: 0.96247 timestamp: 1655060461.96408 iteration: 66540 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11067 FastRCNN class loss: 0.07431 FastRCNN total loss: 0.18498 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.17252 RPN box loss: 0.01058 RPN score loss: 0.0089 RPN total loss: 0.01948 Total loss: 0.944 timestamp: 1655060465.2485192 iteration: 66545 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12924 FastRCNN class loss: 0.12901 FastRCNN total loss: 0.25825 L1 loss: 0.0000e+00 L2 loss: 0.56702 Learning rate: 0.0004 Mask loss: 0.21524 RPN box loss: 0.03953 RPN score loss: 0.03247 RPN total loss: 0.072 Total loss: 1.1125 timestamp: 1655060468.5255568 iteration: 66550 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06739 FastRCNN class loss: 0.04385 FastRCNN total loss: 0.11124 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.11455 RPN box loss: 0.00602 RPN score loss: 0.00531 RPN total loss: 0.01133 Total loss: 0.80413 timestamp: 1655060471.7676535 iteration: 66555 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04496 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.0947 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.11867 RPN box loss: 0.00446 RPN score loss: 0.00337 RPN total loss: 0.00784 Total loss: 0.78822 timestamp: 1655060475.0713832 iteration: 66560 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06858 FastRCNN class loss: 0.05818 FastRCNN total loss: 0.12676 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.14059 RPN box loss: 0.00825 RPN score loss: 0.00172 RPN total loss: 0.00997 Total loss: 0.84432 timestamp: 1655060478.3640215 iteration: 66565 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05276 FastRCNN class loss: 0.04354 FastRCNN total loss: 0.09629 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.12559 RPN box loss: 0.01939 RPN score loss: 0.00526 RPN total loss: 0.02465 Total loss: 0.81355 timestamp: 1655060481.6397283 iteration: 66570 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04696 FastRCNN class loss: 0.05251 FastRCNN total loss: 0.09947 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.12423 RPN box loss: 0.00988 RPN score loss: 0.00134 RPN total loss: 0.01122 Total loss: 0.80192 timestamp: 1655060484.92881 iteration: 66575 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05096 FastRCNN class loss: 0.0415 FastRCNN total loss: 0.09246 L1 loss: 0.0000e+00 L2 loss: 0.56701 Learning rate: 0.0004 Mask loss: 0.1268 RPN box loss: 0.01723 RPN score loss: 0.00176 RPN total loss: 0.01898 Total loss: 0.80524 timestamp: 1655060488.23028 iteration: 66580 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06437 FastRCNN class loss: 0.03242 FastRCNN total loss: 0.09679 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.12073 RPN box loss: 0.00508 RPN score loss: 0.00119 RPN total loss: 0.00626 Total loss: 0.79079 timestamp: 1655060491.4800084 iteration: 66585 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10278 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.17702 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.13307 RPN box loss: 0.01701 RPN score loss: 0.00487 RPN total loss: 0.02188 Total loss: 0.89898 timestamp: 1655060494.7375486 iteration: 66590 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08332 FastRCNN class loss: 0.06537 FastRCNN total loss: 0.14869 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.17042 RPN box loss: 0.01018 RPN score loss: 0.00302 RPN total loss: 0.0132 Total loss: 0.89931 timestamp: 1655060498.0157597 iteration: 66595 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13189 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.2095 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.1572 RPN box loss: 0.01138 RPN score loss: 0.00588 RPN total loss: 0.01726 Total loss: 0.95096 timestamp: 1655060501.2477388 iteration: 66600 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08852 FastRCNN class loss: 0.08251 FastRCNN total loss: 0.17104 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.13627 RPN box loss: 0.0194 RPN score loss: 0.01784 RPN total loss: 0.03724 Total loss: 0.91155 timestamp: 1655060504.4492798 iteration: 66605 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0513 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.10091 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.11584 RPN box loss: 0.00627 RPN score loss: 0.00211 RPN total loss: 0.00838 Total loss: 0.79212 timestamp: 1655060507.748309 iteration: 66610 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.21271 L1 loss: 0.0000e+00 L2 loss: 0.567 Learning rate: 0.0004 Mask loss: 0.11667 RPN box loss: 0.01683 RPN score loss: 0.00385 RPN total loss: 0.02068 Total loss: 0.91706 timestamp: 1655060511.0285044 iteration: 66615 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08898 FastRCNN class loss: 0.10497 FastRCNN total loss: 0.19395 L1 loss: 0.0000e+00 L2 loss: 0.56699 Learning rate: 0.0004 Mask loss: 0.17067 RPN box loss: 0.01454 RPN score loss: 0.01139 RPN total loss: 0.02593 Total loss: 0.95754 timestamp: 1655060514.3494549 iteration: 66620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10797 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.17834 L1 loss: 0.0000e+00 L2 loss: 0.56699 Learning rate: 0.0004 Mask loss: 0.11549 RPN box loss: 0.05769 RPN score loss: 0.00353 RPN total loss: 0.06122 Total loss: 0.92204 timestamp: 1655060517.635857 iteration: 66625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08544 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.14872 L1 loss: 0.0000e+00 L2 loss: 0.56699 Learning rate: 0.0004 Mask loss: 0.18335 RPN box loss: 0.00998 RPN score loss: 0.00671 RPN total loss: 0.01669 Total loss: 0.91576 timestamp: 1655060520.9405494 iteration: 66630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07054 FastRCNN class loss: 0.05589 FastRCNN total loss: 0.12643 L1 loss: 0.0000e+00 L2 loss: 0.56699 Learning rate: 0.0004 Mask loss: 0.21534 RPN box loss: 0.01532 RPN score loss: 0.00082 RPN total loss: 0.01614 Total loss: 0.9249 timestamp: 1655060524.1733074 iteration: 66635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0517 FastRCNN class loss: 0.0435 FastRCNN total loss: 0.0952 L1 loss: 0.0000e+00 L2 loss: 0.56699 Learning rate: 0.0004 Mask loss: 0.1044 RPN box loss: 0.00849 RPN score loss: 0.00595 RPN total loss: 0.01445 Total loss: 0.78104 timestamp: 1655060527.4632819 iteration: 66640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09656 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.1726 L1 loss: 0.0000e+00 L2 loss: 0.56698 Learning rate: 0.0004 Mask loss: 0.15821 RPN box loss: 0.0239 RPN score loss: 0.0146 RPN total loss: 0.03851 Total loss: 0.9363 timestamp: 1655060530.7622385 iteration: 66645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.0973 FastRCNN total loss: 0.19584 L1 loss: 0.0000e+00 L2 loss: 0.56698 Learning rate: 0.0004 Mask loss: 0.15536 RPN box loss: 0.01743 RPN score loss: 0.0138 RPN total loss: 0.03123 Total loss: 0.9494 timestamp: 1655060534.0257723 iteration: 66650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1463 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.22642 L1 loss: 0.0000e+00 L2 loss: 0.56698 Learning rate: 0.0004 Mask loss: 0.12794 RPN box loss: 0.02822 RPN score loss: 0.01175 RPN total loss: 0.03997 Total loss: 0.96131 timestamp: 1655060537.3000057 iteration: 66655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08802 FastRCNN class loss: 0.07315 FastRCNN total loss: 0.16117 L1 loss: 0.0000e+00 L2 loss: 0.56698 Learning rate: 0.0004 Mask loss: 0.1214 RPN box loss: 0.00926 RPN score loss: 0.00595 RPN total loss: 0.0152 Total loss: 0.86475 timestamp: 1655060540.5048118 iteration: 66660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07762 FastRCNN class loss: 0.05506 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.56698 Learning rate: 0.0004 Mask loss: 0.10707 RPN box loss: 0.03368 RPN score loss: 0.00224 RPN total loss: 0.03591 Total loss: 0.84264 timestamp: 1655060543.800698 iteration: 66665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05349 FastRCNN class loss: 0.05432 FastRCNN total loss: 0.10781 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.15321 RPN box loss: 0.00584 RPN score loss: 0.00229 RPN total loss: 0.00812 Total loss: 0.83612 timestamp: 1655060547.084569 iteration: 66670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10057 FastRCNN class loss: 0.07217 FastRCNN total loss: 0.17274 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.15724 RPN box loss: 0.00605 RPN score loss: 0.00421 RPN total loss: 0.01026 Total loss: 0.90722 timestamp: 1655060550.3048406 iteration: 66675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14836 FastRCNN class loss: 0.09426 FastRCNN total loss: 0.24262 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.15474 RPN box loss: 0.00732 RPN score loss: 0.00177 RPN total loss: 0.00909 Total loss: 0.97342 timestamp: 1655060553.5168095 iteration: 66680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09005 FastRCNN class loss: 0.04729 FastRCNN total loss: 0.13734 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.14737 RPN box loss: 0.00581 RPN score loss: 0.00786 RPN total loss: 0.01367 Total loss: 0.86535 timestamp: 1655060556.8060627 iteration: 66685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1108 FastRCNN class loss: 0.09688 FastRCNN total loss: 0.20769 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.15687 RPN box loss: 0.02745 RPN score loss: 0.00923 RPN total loss: 0.03669 Total loss: 0.9682 timestamp: 1655060560.0957482 iteration: 66690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12009 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.19796 L1 loss: 0.0000e+00 L2 loss: 0.56697 Learning rate: 0.0004 Mask loss: 0.11653 RPN box loss: 0.01034 RPN score loss: 0.00475 RPN total loss: 0.01508 Total loss: 0.89654 timestamp: 1655060563.392467 iteration: 66695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1287 FastRCNN class loss: 0.08221 FastRCNN total loss: 0.21091 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.22496 RPN box loss: 0.01858 RPN score loss: 0.00312 RPN total loss: 0.0217 Total loss: 1.02453 timestamp: 1655060566.683735 iteration: 66700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08745 FastRCNN class loss: 0.0621 FastRCNN total loss: 0.14954 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.1737 RPN box loss: 0.01239 RPN score loss: 0.0017 RPN total loss: 0.01409 Total loss: 0.9043 timestamp: 1655060570.0258074 iteration: 66705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08486 FastRCNN class loss: 0.07761 FastRCNN total loss: 0.16247 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.10898 RPN box loss: 0.01098 RPN score loss: 0.00711 RPN total loss: 0.01809 Total loss: 0.8565 timestamp: 1655060573.3200397 iteration: 66710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.06431 FastRCNN total loss: 0.13847 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.16906 RPN box loss: 0.07417 RPN score loss: 0.00684 RPN total loss: 0.08102 Total loss: 0.95551 timestamp: 1655060576.6292005 iteration: 66715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06071 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.12134 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.14305 RPN box loss: 0.00831 RPN score loss: 0.00394 RPN total loss: 0.01224 Total loss: 0.84359 timestamp: 1655060579.871238 iteration: 66720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.088 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.15209 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.13794 RPN box loss: 0.02064 RPN score loss: 0.00493 RPN total loss: 0.02557 Total loss: 0.88255 timestamp: 1655060583.0619187 iteration: 66725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11052 FastRCNN class loss: 0.0839 FastRCNN total loss: 0.19442 L1 loss: 0.0000e+00 L2 loss: 0.56696 Learning rate: 0.0004 Mask loss: 0.14916 RPN box loss: 0.01913 RPN score loss: 0.00512 RPN total loss: 0.02425 Total loss: 0.93479 timestamp: 1655060586.3013687 iteration: 66730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13482 FastRCNN class loss: 0.1046 FastRCNN total loss: 0.23942 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.22189 RPN box loss: 0.016 RPN score loss: 0.01017 RPN total loss: 0.02617 Total loss: 1.05444 timestamp: 1655060589.5621457 iteration: 66735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10697 FastRCNN class loss: 0.06299 FastRCNN total loss: 0.16996 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.08493 RPN box loss: 0.01877 RPN score loss: 0.00313 RPN total loss: 0.0219 Total loss: 0.84375 timestamp: 1655060592.8283372 iteration: 66740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09897 FastRCNN class loss: 0.07966 FastRCNN total loss: 0.17863 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.23405 RPN box loss: 0.02649 RPN score loss: 0.00729 RPN total loss: 0.03379 Total loss: 1.01342 timestamp: 1655060596.097847 iteration: 66745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09888 FastRCNN class loss: 0.044 FastRCNN total loss: 0.14288 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.09502 RPN box loss: 0.0236 RPN score loss: 0.00512 RPN total loss: 0.02872 Total loss: 0.83357 timestamp: 1655060599.378013 iteration: 66750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13525 FastRCNN class loss: 0.09592 FastRCNN total loss: 0.23117 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.13074 RPN box loss: 0.00776 RPN score loss: 0.00115 RPN total loss: 0.00892 Total loss: 0.93777 timestamp: 1655060602.6782987 iteration: 66755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08374 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.15895 L1 loss: 0.0000e+00 L2 loss: 0.56695 Learning rate: 0.0004 Mask loss: 0.13595 RPN box loss: 0.00706 RPN score loss: 0.00545 RPN total loss: 0.01252 Total loss: 0.87437 timestamp: 1655060605.8916755 iteration: 66760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07368 FastRCNN class loss: 0.03993 FastRCNN total loss: 0.11361 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.10562 RPN box loss: 0.02807 RPN score loss: 0.00108 RPN total loss: 0.02916 Total loss: 0.81533 timestamp: 1655060609.2407722 iteration: 66765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07407 FastRCNN class loss: 0.06114 FastRCNN total loss: 0.13521 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.1287 RPN box loss: 0.01705 RPN score loss: 0.00799 RPN total loss: 0.02504 Total loss: 0.85589 timestamp: 1655060612.5332978 iteration: 66770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.0704 FastRCNN total loss: 0.16072 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.14677 RPN box loss: 0.01389 RPN score loss: 0.00531 RPN total loss: 0.0192 Total loss: 0.89363 timestamp: 1655060615.8761387 iteration: 66775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08057 FastRCNN class loss: 0.08435 FastRCNN total loss: 0.16492 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.14535 RPN box loss: 0.01164 RPN score loss: 0.00252 RPN total loss: 0.01416 Total loss: 0.89137 timestamp: 1655060619.1896384 iteration: 66780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08036 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.13035 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.22035 RPN box loss: 0.00802 RPN score loss: 0.00302 RPN total loss: 0.01104 Total loss: 0.92867 timestamp: 1655060622.486242 iteration: 66785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0879 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.1773 L1 loss: 0.0000e+00 L2 loss: 0.56694 Learning rate: 0.0004 Mask loss: 0.09049 RPN box loss: 0.00896 RPN score loss: 0.00376 RPN total loss: 0.01272 Total loss: 0.84745 timestamp: 1655060625.7449749 iteration: 66790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07059 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.11954 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.11734 RPN box loss: 0.00838 RPN score loss: 0.00373 RPN total loss: 0.01211 Total loss: 0.81592 timestamp: 1655060629.0663004 iteration: 66795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.09247 FastRCNN total loss: 0.20543 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.13038 RPN box loss: 0.00957 RPN score loss: 0.00397 RPN total loss: 0.01355 Total loss: 0.91629 timestamp: 1655060632.307829 iteration: 66800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08723 FastRCNN class loss: 0.04699 FastRCNN total loss: 0.13422 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.17194 RPN box loss: 0.01403 RPN score loss: 0.00547 RPN total loss: 0.0195 Total loss: 0.89259 timestamp: 1655060635.6300569 iteration: 66805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07635 FastRCNN class loss: 0.05535 FastRCNN total loss: 0.13169 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.1258 RPN box loss: 0.01405 RPN score loss: 0.00347 RPN total loss: 0.01752 Total loss: 0.84195 timestamp: 1655060638.8816254 iteration: 66810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05048 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.105 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.16057 RPN box loss: 0.01885 RPN score loss: 0.00107 RPN total loss: 0.01992 Total loss: 0.85242 timestamp: 1655060642.1811223 iteration: 66815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07346 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.15685 L1 loss: 0.0000e+00 L2 loss: 0.56693 Learning rate: 0.0004 Mask loss: 0.18728 RPN box loss: 0.01955 RPN score loss: 0.00592 RPN total loss: 0.02547 Total loss: 0.93652 timestamp: 1655060645.475271 iteration: 66820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07972 FastRCNN class loss: 0.04689 FastRCNN total loss: 0.12662 L1 loss: 0.0000e+00 L2 loss: 0.56692 Learning rate: 0.0004 Mask loss: 0.1023 RPN box loss: 0.00449 RPN score loss: 0.00525 RPN total loss: 0.00975 Total loss: 0.80558 timestamp: 1655060648.8037877 iteration: 66825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.06555 FastRCNN total loss: 0.17653 L1 loss: 0.0000e+00 L2 loss: 0.56692 Learning rate: 0.0004 Mask loss: 0.13101 RPN box loss: 0.02645 RPN score loss: 0.00649 RPN total loss: 0.03294 Total loss: 0.9074 timestamp: 1655060652.1122663 iteration: 66830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.18824 L1 loss: 0.0000e+00 L2 loss: 0.56692 Learning rate: 0.0004 Mask loss: 0.11866 RPN box loss: 0.01269 RPN score loss: 0.00459 RPN total loss: 0.01728 Total loss: 0.89109 timestamp: 1655060655.396215 iteration: 66835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10218 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.19631 L1 loss: 0.0000e+00 L2 loss: 0.56692 Learning rate: 0.0004 Mask loss: 0.14351 RPN box loss: 0.02043 RPN score loss: 0.00881 RPN total loss: 0.02924 Total loss: 0.93598 timestamp: 1655060658.6804316 iteration: 66840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07244 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.13315 L1 loss: 0.0000e+00 L2 loss: 0.56692 Learning rate: 0.0004 Mask loss: 0.16447 RPN box loss: 0.0111 RPN score loss: 0.00546 RPN total loss: 0.01656 Total loss: 0.8811 timestamp: 1655060661.9593582 iteration: 66845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13434 FastRCNN class loss: 0.09741 FastRCNN total loss: 0.23174 L1 loss: 0.0000e+00 L2 loss: 0.56691 Learning rate: 0.0004 Mask loss: 0.14724 RPN box loss: 0.00498 RPN score loss: 0.0023 RPN total loss: 0.00729 Total loss: 0.95319 timestamp: 1655060665.240008 iteration: 66850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09392 FastRCNN class loss: 0.05457 FastRCNN total loss: 0.14849 L1 loss: 0.0000e+00 L2 loss: 0.56691 Learning rate: 0.0004 Mask loss: 0.12828 RPN box loss: 0.00363 RPN score loss: 0.00276 RPN total loss: 0.00639 Total loss: 0.85008 timestamp: 1655060668.4937863 iteration: 66855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05276 FastRCNN class loss: 0.04619 FastRCNN total loss: 0.09895 L1 loss: 0.0000e+00 L2 loss: 0.56691 Learning rate: 0.0004 Mask loss: 0.24629 RPN box loss: 0.01666 RPN score loss: 0.0051 RPN total loss: 0.02176 Total loss: 0.93391 timestamp: 1655060671.8120546 iteration: 66860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06933 FastRCNN class loss: 0.06224 FastRCNN total loss: 0.13157 L1 loss: 0.0000e+00 L2 loss: 0.56691 Learning rate: 0.0004 Mask loss: 0.13009 RPN box loss: 0.01036 RPN score loss: 0.00433 RPN total loss: 0.01469 Total loss: 0.84326 timestamp: 1655060675.0659428 iteration: 66865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14593 FastRCNN class loss: 0.08065 FastRCNN total loss: 0.22658 L1 loss: 0.0000e+00 L2 loss: 0.56691 Learning rate: 0.0004 Mask loss: 0.17843 RPN box loss: 0.01179 RPN score loss: 0.00866 RPN total loss: 0.02046 Total loss: 0.99237 timestamp: 1655060678.3244889 iteration: 66870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09017 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.14208 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.15942 RPN box loss: 0.01003 RPN score loss: 0.00663 RPN total loss: 0.01666 Total loss: 0.88507 timestamp: 1655060681.6266081 iteration: 66875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07091 FastRCNN class loss: 0.0424 FastRCNN total loss: 0.11331 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.102 RPN box loss: 0.00763 RPN score loss: 0.00128 RPN total loss: 0.00891 Total loss: 0.79112 timestamp: 1655060684.921233 iteration: 66880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.16577 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.1082 RPN box loss: 0.01036 RPN score loss: 0.00819 RPN total loss: 0.01855 Total loss: 0.85942 timestamp: 1655060688.2008483 iteration: 66885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07688 FastRCNN class loss: 0.04808 FastRCNN total loss: 0.12496 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.11901 RPN box loss: 0.00869 RPN score loss: 0.00548 RPN total loss: 0.01416 Total loss: 0.82503 timestamp: 1655060691.4754055 iteration: 66890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09822 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.1573 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.105 RPN box loss: 0.00476 RPN score loss: 0.00784 RPN total loss: 0.0126 Total loss: 0.84179 timestamp: 1655060694.65942 iteration: 66895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08037 FastRCNN class loss: 0.07816 FastRCNN total loss: 0.15852 L1 loss: 0.0000e+00 L2 loss: 0.5669 Learning rate: 0.0004 Mask loss: 0.16321 RPN box loss: 0.04862 RPN score loss: 0.006 RPN total loss: 0.05462 Total loss: 0.94325 timestamp: 1655060697.897534 iteration: 66900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09664 FastRCNN class loss: 0.06181 FastRCNN total loss: 0.15845 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.15776 RPN box loss: 0.03845 RPN score loss: 0.01275 RPN total loss: 0.05121 Total loss: 0.93431 timestamp: 1655060701.192464 iteration: 66905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07817 FastRCNN class loss: 0.06145 FastRCNN total loss: 0.13961 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.1048 RPN box loss: 0.01733 RPN score loss: 0.00301 RPN total loss: 0.02034 Total loss: 0.83164 timestamp: 1655060704.4316435 iteration: 66910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09738 FastRCNN class loss: 0.08131 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.13948 RPN box loss: 0.00907 RPN score loss: 0.00454 RPN total loss: 0.01362 Total loss: 0.89867 timestamp: 1655060707.6123228 iteration: 66915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14791 FastRCNN class loss: 0.11517 FastRCNN total loss: 0.26308 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.19332 RPN box loss: 0.01656 RPN score loss: 0.00714 RPN total loss: 0.0237 Total loss: 1.04699 timestamp: 1655060710.8602407 iteration: 66920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06283 FastRCNN class loss: 0.04026 FastRCNN total loss: 0.10309 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.12615 RPN box loss: 0.01118 RPN score loss: 0.00722 RPN total loss: 0.01841 Total loss: 0.81454 timestamp: 1655060714.1283004 iteration: 66925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06274 FastRCNN class loss: 0.04233 FastRCNN total loss: 0.10507 L1 loss: 0.0000e+00 L2 loss: 0.56689 Learning rate: 0.0004 Mask loss: 0.1352 RPN box loss: 0.00958 RPN score loss: 0.00502 RPN total loss: 0.0146 Total loss: 0.82176 timestamp: 1655060717.4198782 iteration: 66930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.09811 FastRCNN total loss: 0.21128 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.19581 RPN box loss: 0.01462 RPN score loss: 0.00726 RPN total loss: 0.02188 Total loss: 0.99586 timestamp: 1655060720.7179654 iteration: 66935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09327 FastRCNN class loss: 0.05018 FastRCNN total loss: 0.14345 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.10211 RPN box loss: 0.00703 RPN score loss: 0.00483 RPN total loss: 0.01186 Total loss: 0.8243 timestamp: 1655060723.9968643 iteration: 66940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14199 FastRCNN class loss: 0.08049 FastRCNN total loss: 0.22247 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.18786 RPN box loss: 0.02947 RPN score loss: 0.00704 RPN total loss: 0.03651 Total loss: 1.01372 timestamp: 1655060727.3055046 iteration: 66945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.08299 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.16289 RPN box loss: 0.02295 RPN score loss: 0.01023 RPN total loss: 0.03319 Total loss: 0.92735 timestamp: 1655060730.5810575 iteration: 66950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08252 FastRCNN class loss: 0.07769 FastRCNN total loss: 0.1602 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.17926 RPN box loss: 0.01287 RPN score loss: 0.0031 RPN total loss: 0.01597 Total loss: 0.92231 timestamp: 1655060733.8657968 iteration: 66955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05616 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.1203 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.1396 RPN box loss: 0.00315 RPN score loss: 0.00936 RPN total loss: 0.01251 Total loss: 0.83929 timestamp: 1655060737.10613 iteration: 66960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16746 FastRCNN class loss: 0.05806 FastRCNN total loss: 0.22552 L1 loss: 0.0000e+00 L2 loss: 0.56688 Learning rate: 0.0004 Mask loss: 0.11177 RPN box loss: 0.00672 RPN score loss: 0.00522 RPN total loss: 0.01194 Total loss: 0.91611 timestamp: 1655060740.3338513 iteration: 66965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16009 FastRCNN class loss: 0.11056 FastRCNN total loss: 0.27065 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.17695 RPN box loss: 0.01911 RPN score loss: 0.00831 RPN total loss: 0.02742 Total loss: 1.04189 timestamp: 1655060743.6179266 iteration: 66970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12721 FastRCNN class loss: 0.11199 FastRCNN total loss: 0.23921 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.18977 RPN box loss: 0.01139 RPN score loss: 0.00345 RPN total loss: 0.01484 Total loss: 1.01068 timestamp: 1655060746.8253422 iteration: 66975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0744 FastRCNN class loss: 0.06244 FastRCNN total loss: 0.13683 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.15834 RPN box loss: 0.00624 RPN score loss: 0.00699 RPN total loss: 0.01324 Total loss: 0.87528 timestamp: 1655060750.1270149 iteration: 66980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.05863 FastRCNN total loss: 0.16007 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.1376 RPN box loss: 0.01728 RPN score loss: 0.00595 RPN total loss: 0.02323 Total loss: 0.88777 timestamp: 1655060753.3321319 iteration: 66985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05456 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.10961 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.14869 RPN box loss: 0.00717 RPN score loss: 0.00315 RPN total loss: 0.01032 Total loss: 0.83548 timestamp: 1655060756.5952773 iteration: 66990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07702 FastRCNN class loss: 0.06768 FastRCNN total loss: 0.1447 L1 loss: 0.0000e+00 L2 loss: 0.56687 Learning rate: 0.0004 Mask loss: 0.14654 RPN box loss: 0.01353 RPN score loss: 0.00415 RPN total loss: 0.01768 Total loss: 0.87578 timestamp: 1655060759.884074 iteration: 66995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15883 FastRCNN class loss: 0.05617 FastRCNN total loss: 0.215 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.13485 RPN box loss: 0.01516 RPN score loss: 0.00275 RPN total loss: 0.01791 Total loss: 0.93463 timestamp: 1655060763.141352 iteration: 67000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14924 FastRCNN class loss: 0.09612 FastRCNN total loss: 0.24536 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.11665 RPN box loss: 0.01111 RPN score loss: 0.0068 RPN total loss: 0.01792 Total loss: 0.94678 timestamp: 1655060766.4185297 iteration: 67005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06106 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.10531 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.10599 RPN box loss: 0.01511 RPN score loss: 0.00144 RPN total loss: 0.01655 Total loss: 0.79471 timestamp: 1655060769.6945703 iteration: 67010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05711 FastRCNN class loss: 0.05618 FastRCNN total loss: 0.11329 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.12589 RPN box loss: 0.01639 RPN score loss: 0.00217 RPN total loss: 0.01856 Total loss: 0.8246 timestamp: 1655060773.0553434 iteration: 67015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12445 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.17316 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.08949 RPN box loss: 0.02115 RPN score loss: 0.00418 RPN total loss: 0.02534 Total loss: 0.85484 timestamp: 1655060776.2789328 iteration: 67020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0846 FastRCNN class loss: 0.03659 FastRCNN total loss: 0.12119 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.12748 RPN box loss: 0.01613 RPN score loss: 0.00431 RPN total loss: 0.02044 Total loss: 0.83597 timestamp: 1655060779.603749 iteration: 67025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09978 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.15823 L1 loss: 0.0000e+00 L2 loss: 0.56686 Learning rate: 0.0004 Mask loss: 0.08633 RPN box loss: 0.0073 RPN score loss: 0.00149 RPN total loss: 0.00879 Total loss: 0.82021 timestamp: 1655060782.8573875 iteration: 67030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09952 FastRCNN class loss: 0.08039 FastRCNN total loss: 0.17992 L1 loss: 0.0000e+00 L2 loss: 0.56685 Learning rate: 0.0004 Mask loss: 0.13147 RPN box loss: 0.00611 RPN score loss: 0.00153 RPN total loss: 0.00764 Total loss: 0.88587 timestamp: 1655060786.2113178 iteration: 67035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12052 FastRCNN class loss: 0.10023 FastRCNN total loss: 0.22075 L1 loss: 0.0000e+00 L2 loss: 0.56685 Learning rate: 0.0004 Mask loss: 0.1328 RPN box loss: 0.01226 RPN score loss: 0.00763 RPN total loss: 0.01989 Total loss: 0.94029 timestamp: 1655060789.5022633 iteration: 67040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08384 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.13899 L1 loss: 0.0000e+00 L2 loss: 0.56685 Learning rate: 0.0004 Mask loss: 0.1325 RPN box loss: 0.01258 RPN score loss: 0.00421 RPN total loss: 0.01678 Total loss: 0.85512 timestamp: 1655060792.7684214 iteration: 67045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11041 FastRCNN class loss: 0.08445 FastRCNN total loss: 0.19486 L1 loss: 0.0000e+00 L2 loss: 0.56685 Learning rate: 0.0004 Mask loss: 0.18976 RPN box loss: 0.00846 RPN score loss: 0.00598 RPN total loss: 0.01444 Total loss: 0.9659 timestamp: 1655060796.0003803 iteration: 67050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10196 FastRCNN class loss: 0.07543 FastRCNN total loss: 0.17739 L1 loss: 0.0000e+00 L2 loss: 0.56685 Learning rate: 0.0004 Mask loss: 0.14122 RPN box loss: 0.01382 RPN score loss: 0.00545 RPN total loss: 0.01927 Total loss: 0.90473 timestamp: 1655060799.2899957 iteration: 67055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10597 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.17809 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.13086 RPN box loss: 0.03058 RPN score loss: 0.00539 RPN total loss: 0.03597 Total loss: 0.91176 timestamp: 1655060802.60904 iteration: 67060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.05974 FastRCNN total loss: 0.14237 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.16025 RPN box loss: 0.00856 RPN score loss: 0.00251 RPN total loss: 0.01108 Total loss: 0.88055 timestamp: 1655060805.8347054 iteration: 67065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03474 FastRCNN class loss: 0.04496 FastRCNN total loss: 0.0797 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.13855 RPN box loss: 0.00658 RPN score loss: 0.01192 RPN total loss: 0.0185 Total loss: 0.80359 timestamp: 1655060809.0856857 iteration: 67070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10659 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.1681 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.20032 RPN box loss: 0.02242 RPN score loss: 0.00312 RPN total loss: 0.02554 Total loss: 0.9608 timestamp: 1655060812.4510996 iteration: 67075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06622 FastRCNN class loss: 0.04539 FastRCNN total loss: 0.11161 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.20195 RPN box loss: 0.01391 RPN score loss: 0.00784 RPN total loss: 0.02175 Total loss: 0.90216 timestamp: 1655060815.7257257 iteration: 67080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06229 FastRCNN class loss: 0.05095 FastRCNN total loss: 0.11323 L1 loss: 0.0000e+00 L2 loss: 0.56684 Learning rate: 0.0004 Mask loss: 0.16441 RPN box loss: 0.00927 RPN score loss: 0.00244 RPN total loss: 0.01171 Total loss: 0.8562 timestamp: 1655060818.956536 iteration: 67085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14663 FastRCNN class loss: 0.11535 FastRCNN total loss: 0.26197 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.19343 RPN box loss: 0.01313 RPN score loss: 0.00368 RPN total loss: 0.0168 Total loss: 1.03904 timestamp: 1655060822.1779623 iteration: 67090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09427 FastRCNN class loss: 0.07106 FastRCNN total loss: 0.16533 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.12325 RPN box loss: 0.01764 RPN score loss: 0.00689 RPN total loss: 0.02453 Total loss: 0.87995 timestamp: 1655060825.3749583 iteration: 67095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05917 FastRCNN class loss: 0.06035 FastRCNN total loss: 0.11952 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.12559 RPN box loss: 0.011 RPN score loss: 0.00839 RPN total loss: 0.01938 Total loss: 0.83132 timestamp: 1655060828.6591487 iteration: 67100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06387 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.13419 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.21697 RPN box loss: 0.01762 RPN score loss: 0.00808 RPN total loss: 0.0257 Total loss: 0.94368 timestamp: 1655060831.9317045 iteration: 67105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06673 FastRCNN class loss: 0.04376 FastRCNN total loss: 0.1105 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.14321 RPN box loss: 0.00547 RPN score loss: 0.00437 RPN total loss: 0.00984 Total loss: 0.83038 timestamp: 1655060835.1877723 iteration: 67110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05272 FastRCNN class loss: 0.03546 FastRCNN total loss: 0.08818 L1 loss: 0.0000e+00 L2 loss: 0.56683 Learning rate: 0.0004 Mask loss: 0.08889 RPN box loss: 0.00359 RPN score loss: 0.00124 RPN total loss: 0.00483 Total loss: 0.74873 timestamp: 1655060838.5026355 iteration: 67115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12585 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.19196 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.13009 RPN box loss: 0.01116 RPN score loss: 0.00275 RPN total loss: 0.01391 Total loss: 0.90278 timestamp: 1655060841.729802 iteration: 67120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10785 FastRCNN class loss: 0.09033 FastRCNN total loss: 0.19818 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.14531 RPN box loss: 0.02095 RPN score loss: 0.01175 RPN total loss: 0.0327 Total loss: 0.94301 timestamp: 1655060845.0536025 iteration: 67125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.0682 FastRCNN total loss: 0.17871 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.1556 RPN box loss: 0.00837 RPN score loss: 0.00184 RPN total loss: 0.01021 Total loss: 0.91134 timestamp: 1655060848.354498 iteration: 67130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12188 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.18445 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.13995 RPN box loss: 0.00975 RPN score loss: 0.0036 RPN total loss: 0.01336 Total loss: 0.90457 timestamp: 1655060851.6204705 iteration: 67135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10104 FastRCNN class loss: 0.08558 FastRCNN total loss: 0.18662 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.11987 RPN box loss: 0.04406 RPN score loss: 0.00798 RPN total loss: 0.05204 Total loss: 0.92535 timestamp: 1655060854.8946788 iteration: 67140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06878 FastRCNN class loss: 0.06879 FastRCNN total loss: 0.13757 L1 loss: 0.0000e+00 L2 loss: 0.56682 Learning rate: 0.0004 Mask loss: 0.14832 RPN box loss: 0.0082 RPN score loss: 0.0058 RPN total loss: 0.01401 Total loss: 0.8667 timestamp: 1655060858.151882 iteration: 67145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1496 FastRCNN class loss: 0.09693 FastRCNN total loss: 0.24653 L1 loss: 0.0000e+00 L2 loss: 0.56681 Learning rate: 0.0004 Mask loss: 0.19543 RPN box loss: 0.02013 RPN score loss: 0.00599 RPN total loss: 0.02612 Total loss: 1.03489 timestamp: 1655060861.4266872 iteration: 67150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11218 FastRCNN class loss: 0.06637 FastRCNN total loss: 0.17855 L1 loss: 0.0000e+00 L2 loss: 0.56681 Learning rate: 0.0004 Mask loss: 0.14035 RPN box loss: 0.01485 RPN score loss: 0.00246 RPN total loss: 0.01731 Total loss: 0.90302 timestamp: 1655060864.7669823 iteration: 67155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05729 FastRCNN class loss: 0.06492 FastRCNN total loss: 0.12221 L1 loss: 0.0000e+00 L2 loss: 0.56681 Learning rate: 0.0004 Mask loss: 0.10699 RPN box loss: 0.0058 RPN score loss: 0.00191 RPN total loss: 0.00771 Total loss: 0.80372 timestamp: 1655060868.0082116 iteration: 67160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12389 FastRCNN class loss: 0.14461 FastRCNN total loss: 0.2685 L1 loss: 0.0000e+00 L2 loss: 0.56681 Learning rate: 0.0004 Mask loss: 0.16884 RPN box loss: 0.01471 RPN score loss: 0.00625 RPN total loss: 0.02096 Total loss: 1.0251 timestamp: 1655060871.3243067 iteration: 67165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11102 FastRCNN class loss: 0.07517 FastRCNN total loss: 0.1862 L1 loss: 0.0000e+00 L2 loss: 0.56681 Learning rate: 0.0004 Mask loss: 0.14624 RPN box loss: 0.01527 RPN score loss: 0.00285 RPN total loss: 0.01812 Total loss: 0.91736 timestamp: 1655060874.6307626 iteration: 67170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09382 FastRCNN class loss: 0.07545 FastRCNN total loss: 0.16927 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.17043 RPN box loss: 0.00919 RPN score loss: 0.00309 RPN total loss: 0.01229 Total loss: 0.91879 timestamp: 1655060877.9341128 iteration: 67175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10197 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.18079 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.16377 RPN box loss: 0.016 RPN score loss: 0.00808 RPN total loss: 0.02409 Total loss: 0.93544 timestamp: 1655060881.1878355 iteration: 67180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11261 FastRCNN class loss: 0.12281 FastRCNN total loss: 0.23542 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.14663 RPN box loss: 0.02772 RPN score loss: 0.00518 RPN total loss: 0.0329 Total loss: 0.98176 timestamp: 1655060884.4813006 iteration: 67185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0984 FastRCNN class loss: 0.08729 FastRCNN total loss: 0.18569 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.15154 RPN box loss: 0.01253 RPN score loss: 0.00526 RPN total loss: 0.01779 Total loss: 0.92182 timestamp: 1655060887.7496219 iteration: 67190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05909 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.11735 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.09858 RPN box loss: 0.00656 RPN score loss: 0.00379 RPN total loss: 0.01035 Total loss: 0.79308 timestamp: 1655060890.9990897 iteration: 67195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09308 FastRCNN class loss: 0.0689 FastRCNN total loss: 0.16198 L1 loss: 0.0000e+00 L2 loss: 0.5668 Learning rate: 0.0004 Mask loss: 0.18507 RPN box loss: 0.01053 RPN score loss: 0.01077 RPN total loss: 0.0213 Total loss: 0.93515 timestamp: 1655060894.2320344 iteration: 67200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07916 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.16539 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.19506 RPN box loss: 0.00491 RPN score loss: 0.00339 RPN total loss: 0.0083 Total loss: 0.93555 timestamp: 1655060897.5238316 iteration: 67205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1057 FastRCNN class loss: 0.12942 FastRCNN total loss: 0.23513 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.11088 RPN box loss: 0.00605 RPN score loss: 0.00426 RPN total loss: 0.01031 Total loss: 0.92311 timestamp: 1655060900.8236337 iteration: 67210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06049 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.12618 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.13488 RPN box loss: 0.01013 RPN score loss: 0.00404 RPN total loss: 0.01417 Total loss: 0.84202 timestamp: 1655060904.0923822 iteration: 67215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0739 FastRCNN class loss: 0.08827 FastRCNN total loss: 0.16218 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.16508 RPN box loss: 0.0278 RPN score loss: 0.01951 RPN total loss: 0.04732 Total loss: 0.94137 timestamp: 1655060907.3746388 iteration: 67220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06811 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.14566 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.277 RPN box loss: 0.01303 RPN score loss: 0.00286 RPN total loss: 0.01589 Total loss: 1.00535 timestamp: 1655060910.6355453 iteration: 67225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12402 FastRCNN class loss: 0.07367 FastRCNN total loss: 0.19769 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.12972 RPN box loss: 0.01002 RPN score loss: 0.00232 RPN total loss: 0.01234 Total loss: 0.90654 timestamp: 1655060913.9743934 iteration: 67230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08018 FastRCNN class loss: 0.07202 FastRCNN total loss: 0.1522 L1 loss: 0.0000e+00 L2 loss: 0.56679 Learning rate: 0.0004 Mask loss: 0.19603 RPN box loss: 0.01246 RPN score loss: 0.002 RPN total loss: 0.01446 Total loss: 0.92948 timestamp: 1655060917.2304587 iteration: 67235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13197 FastRCNN class loss: 0.06496 FastRCNN total loss: 0.19692 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.10167 RPN box loss: 0.0038 RPN score loss: 0.00348 RPN total loss: 0.00727 Total loss: 0.87266 timestamp: 1655060920.536212 iteration: 67240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10843 FastRCNN class loss: 0.15133 FastRCNN total loss: 0.25975 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.21575 RPN box loss: 0.01073 RPN score loss: 0.00368 RPN total loss: 0.01441 Total loss: 1.05669 timestamp: 1655060923.7710316 iteration: 67245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10758 FastRCNN class loss: 0.07991 FastRCNN total loss: 0.18749 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.13149 RPN box loss: 0.01709 RPN score loss: 0.00827 RPN total loss: 0.02537 Total loss: 0.91113 timestamp: 1655060927.0836952 iteration: 67250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12339 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.19052 RPN box loss: 0.03527 RPN score loss: 0.00269 RPN total loss: 0.03796 Total loss: 0.98529 timestamp: 1655060930.3922741 iteration: 67255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11234 FastRCNN class loss: 0.07628 FastRCNN total loss: 0.18862 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.13757 RPN box loss: 0.00877 RPN score loss: 0.00507 RPN total loss: 0.01384 Total loss: 0.90681 timestamp: 1655060933.69188 iteration: 67260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11676 FastRCNN class loss: 0.10076 FastRCNN total loss: 0.21752 L1 loss: 0.0000e+00 L2 loss: 0.56678 Learning rate: 0.0004 Mask loss: 0.15807 RPN box loss: 0.03542 RPN score loss: 0.00611 RPN total loss: 0.04153 Total loss: 0.98389 timestamp: 1655060936.897304 iteration: 67265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08099 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.13367 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.09986 RPN box loss: 0.01107 RPN score loss: 0.00415 RPN total loss: 0.01522 Total loss: 0.81552 timestamp: 1655060940.1421518 iteration: 67270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06546 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.12565 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.14647 RPN box loss: 0.01082 RPN score loss: 0.00286 RPN total loss: 0.01368 Total loss: 0.85257 timestamp: 1655060943.3982682 iteration: 67275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06773 FastRCNN class loss: 0.07216 FastRCNN total loss: 0.13989 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.13268 RPN box loss: 0.00842 RPN score loss: 0.00209 RPN total loss: 0.01051 Total loss: 0.84985 timestamp: 1655060946.6470923 iteration: 67280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11361 FastRCNN class loss: 0.08634 FastRCNN total loss: 0.19996 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.11854 RPN box loss: 0.01888 RPN score loss: 0.0122 RPN total loss: 0.03108 Total loss: 0.91635 timestamp: 1655060949.9535258 iteration: 67285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08747 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.14909 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.10681 RPN box loss: 0.00745 RPN score loss: 0.00202 RPN total loss: 0.00947 Total loss: 0.83213 timestamp: 1655060953.2383752 iteration: 67290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.0497 FastRCNN total loss: 0.13364 L1 loss: 0.0000e+00 L2 loss: 0.56677 Learning rate: 0.0004 Mask loss: 0.12383 RPN box loss: 0.01683 RPN score loss: 0.00127 RPN total loss: 0.01809 Total loss: 0.84233 timestamp: 1655060956.4453757 iteration: 67295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08377 FastRCNN class loss: 0.08127 FastRCNN total loss: 0.16504 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.11221 RPN box loss: 0.01507 RPN score loss: 0.00584 RPN total loss: 0.02091 Total loss: 0.86493 timestamp: 1655060959.7399457 iteration: 67300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11992 FastRCNN class loss: 0.08444 FastRCNN total loss: 0.20436 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.14841 RPN box loss: 0.00672 RPN score loss: 0.01025 RPN total loss: 0.01697 Total loss: 0.93651 timestamp: 1655060963.048512 iteration: 67305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09319 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.15754 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.13158 RPN box loss: 0.00772 RPN score loss: 0.00387 RPN total loss: 0.01159 Total loss: 0.86747 timestamp: 1655060966.266027 iteration: 67310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10934 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.17923 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.16044 RPN box loss: 0.01565 RPN score loss: 0.00286 RPN total loss: 0.01851 Total loss: 0.92494 timestamp: 1655060969.5739682 iteration: 67315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06541 FastRCNN class loss: 0.05216 FastRCNN total loss: 0.11757 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.14878 RPN box loss: 0.00622 RPN score loss: 0.00557 RPN total loss: 0.01179 Total loss: 0.8449 timestamp: 1655060972.8693292 iteration: 67320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16735 FastRCNN class loss: 0.08873 FastRCNN total loss: 0.25608 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.18458 RPN box loss: 0.01498 RPN score loss: 0.01109 RPN total loss: 0.02608 Total loss: 1.03349 timestamp: 1655060976.1327767 iteration: 67325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09732 FastRCNN class loss: 0.07309 FastRCNN total loss: 0.17041 L1 loss: 0.0000e+00 L2 loss: 0.56676 Learning rate: 0.0004 Mask loss: 0.12315 RPN box loss: 0.02734 RPN score loss: 0.01449 RPN total loss: 0.04183 Total loss: 0.90215 timestamp: 1655060979.4110148 iteration: 67330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15688 FastRCNN class loss: 0.1342 FastRCNN total loss: 0.29108 L1 loss: 0.0000e+00 L2 loss: 0.56675 Learning rate: 0.0004 Mask loss: 0.17901 RPN box loss: 0.02176 RPN score loss: 0.0125 RPN total loss: 0.03427 Total loss: 1.0711 timestamp: 1655060982.6874478 iteration: 67335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08074 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.14118 L1 loss: 0.0000e+00 L2 loss: 0.56675 Learning rate: 0.0004 Mask loss: 0.18768 RPN box loss: 0.00404 RPN score loss: 0.00259 RPN total loss: 0.00663 Total loss: 0.90224 timestamp: 1655060985.9802287 iteration: 67340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.05705 FastRCNN total loss: 0.15889 L1 loss: 0.0000e+00 L2 loss: 0.56675 Learning rate: 0.0004 Mask loss: 0.11899 RPN box loss: 0.01579 RPN score loss: 0.00375 RPN total loss: 0.01954 Total loss: 0.86416 timestamp: 1655060989.219316 iteration: 67345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10065 FastRCNN class loss: 0.07124 FastRCNN total loss: 0.17189 L1 loss: 0.0000e+00 L2 loss: 0.56675 Learning rate: 0.0004 Mask loss: 0.16019 RPN box loss: 0.01299 RPN score loss: 0.00319 RPN total loss: 0.01617 Total loss: 0.915 timestamp: 1655060992.47992 iteration: 67350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09977 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.1883 L1 loss: 0.0000e+00 L2 loss: 0.56675 Learning rate: 0.0004 Mask loss: 0.16309 RPN box loss: 0.04087 RPN score loss: 0.00152 RPN total loss: 0.0424 Total loss: 0.96053 timestamp: 1655060995.7988093 iteration: 67355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13487 FastRCNN class loss: 0.08127 FastRCNN total loss: 0.21614 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.16564 RPN box loss: 0.03209 RPN score loss: 0.00191 RPN total loss: 0.034 Total loss: 0.98253 timestamp: 1655060999.1250522 iteration: 67360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07486 FastRCNN class loss: 0.08379 FastRCNN total loss: 0.15865 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.16319 RPN box loss: 0.01585 RPN score loss: 0.00114 RPN total loss: 0.01699 Total loss: 0.90557 timestamp: 1655061002.3843503 iteration: 67365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07606 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.12431 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.1414 RPN box loss: 0.00499 RPN score loss: 0.00493 RPN total loss: 0.00991 Total loss: 0.84236 timestamp: 1655061005.6843362 iteration: 67370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13031 FastRCNN class loss: 0.0767 FastRCNN total loss: 0.20701 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.11458 RPN box loss: 0.03986 RPN score loss: 0.00954 RPN total loss: 0.0494 Total loss: 0.93773 timestamp: 1655061008.9893634 iteration: 67375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06242 FastRCNN class loss: 0.04606 FastRCNN total loss: 0.10848 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.13422 RPN box loss: 0.01925 RPN score loss: 0.00433 RPN total loss: 0.02358 Total loss: 0.83302 timestamp: 1655061012.275701 iteration: 67380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08761 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.17456 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.18443 RPN box loss: 0.02911 RPN score loss: 0.02161 RPN total loss: 0.05072 Total loss: 0.97645 timestamp: 1655061015.5452344 iteration: 67385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.0893 FastRCNN total loss: 0.20482 L1 loss: 0.0000e+00 L2 loss: 0.56674 Learning rate: 0.0004 Mask loss: 0.14769 RPN box loss: 0.01301 RPN score loss: 0.01023 RPN total loss: 0.02324 Total loss: 0.94249 timestamp: 1655061018.7790086 iteration: 67390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08834 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.14617 L1 loss: 0.0000e+00 L2 loss: 0.56673 Learning rate: 0.0004 Mask loss: 0.13876 RPN box loss: 0.02099 RPN score loss: 0.00639 RPN total loss: 0.02738 Total loss: 0.87905 timestamp: 1655061022.0697505 iteration: 67395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06848 FastRCNN class loss: 0.05398 FastRCNN total loss: 0.12246 L1 loss: 0.0000e+00 L2 loss: 0.56673 Learning rate: 0.0004 Mask loss: 0.13573 RPN box loss: 0.00357 RPN score loss: 0.00178 RPN total loss: 0.00535 Total loss: 0.83028 timestamp: 1655061025.3738384 iteration: 67400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11794 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.18756 L1 loss: 0.0000e+00 L2 loss: 0.56673 Learning rate: 0.0004 Mask loss: 0.13976 RPN box loss: 0.00561 RPN score loss: 0.00473 RPN total loss: 0.01034 Total loss: 0.90439 timestamp: 1655061028.5985746 iteration: 67405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09928 FastRCNN class loss: 0.09118 FastRCNN total loss: 0.19046 L1 loss: 0.0000e+00 L2 loss: 0.56673 Learning rate: 0.0004 Mask loss: 0.12784 RPN box loss: 0.04136 RPN score loss: 0.01627 RPN total loss: 0.05763 Total loss: 0.94266 timestamp: 1655061031.8571498 iteration: 67410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07858 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.15294 L1 loss: 0.0000e+00 L2 loss: 0.56673 Learning rate: 0.0004 Mask loss: 0.1267 RPN box loss: 0.01489 RPN score loss: 0.01563 RPN total loss: 0.03052 Total loss: 0.87688 timestamp: 1655061035.1483178 iteration: 67415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0436 FastRCNN class loss: 0.03226 FastRCNN total loss: 0.07586 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.09392 RPN box loss: 0.00967 RPN score loss: 0.00067 RPN total loss: 0.01034 Total loss: 0.74685 timestamp: 1655061038.3965025 iteration: 67420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07487 FastRCNN class loss: 0.04988 FastRCNN total loss: 0.12475 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.12493 RPN box loss: 0.01543 RPN score loss: 0.00211 RPN total loss: 0.01754 Total loss: 0.83394 timestamp: 1655061041.6274073 iteration: 67425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06153 FastRCNN class loss: 0.0393 FastRCNN total loss: 0.10082 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.10854 RPN box loss: 0.0061 RPN score loss: 0.01402 RPN total loss: 0.02012 Total loss: 0.7962 timestamp: 1655061044.9618936 iteration: 67430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08906 FastRCNN class loss: 0.04613 FastRCNN total loss: 0.13519 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.1302 RPN box loss: 0.00672 RPN score loss: 0.00679 RPN total loss: 0.01351 Total loss: 0.84562 timestamp: 1655061048.2501247 iteration: 67435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15008 FastRCNN class loss: 0.11409 FastRCNN total loss: 0.26417 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.18564 RPN box loss: 0.02094 RPN score loss: 0.01023 RPN total loss: 0.03117 Total loss: 1.04769 timestamp: 1655061051.4855602 iteration: 67440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06344 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.12145 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.1004 RPN box loss: 0.00511 RPN score loss: 0.00688 RPN total loss: 0.01199 Total loss: 0.80055 timestamp: 1655061054.766195 iteration: 67445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09783 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.1484 L1 loss: 0.0000e+00 L2 loss: 0.56672 Learning rate: 0.0004 Mask loss: 0.10476 RPN box loss: 0.00484 RPN score loss: 0.00389 RPN total loss: 0.00873 Total loss: 0.82861 timestamp: 1655061058.0638905 iteration: 67450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08598 FastRCNN class loss: 0.08493 FastRCNN total loss: 0.17091 L1 loss: 0.0000e+00 L2 loss: 0.56671 Learning rate: 0.0004 Mask loss: 0.2321 RPN box loss: 0.02262 RPN score loss: 0.02249 RPN total loss: 0.04511 Total loss: 1.01483 timestamp: 1655061061.3241196 iteration: 67455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05668 FastRCNN class loss: 0.04111 FastRCNN total loss: 0.09779 L1 loss: 0.0000e+00 L2 loss: 0.56671 Learning rate: 0.0004 Mask loss: 0.08304 RPN box loss: 0.00521 RPN score loss: 0.00311 RPN total loss: 0.00832 Total loss: 0.75586 timestamp: 1655061064.5763452 iteration: 67460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.06222 FastRCNN total loss: 0.17981 L1 loss: 0.0000e+00 L2 loss: 0.56671 Learning rate: 0.0004 Mask loss: 0.1118 RPN box loss: 0.01693 RPN score loss: 0.00187 RPN total loss: 0.0188 Total loss: 0.87713 timestamp: 1655061067.8413637 iteration: 67465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12799 FastRCNN class loss: 0.08137 FastRCNN total loss: 0.20936 L1 loss: 0.0000e+00 L2 loss: 0.56671 Learning rate: 0.0004 Mask loss: 0.1351 RPN box loss: 0.01255 RPN score loss: 0.00378 RPN total loss: 0.01633 Total loss: 0.92749 timestamp: 1655061071.165149 iteration: 67470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09922 FastRCNN class loss: 0.12018 FastRCNN total loss: 0.2194 L1 loss: 0.0000e+00 L2 loss: 0.56671 Learning rate: 0.0004 Mask loss: 0.18364 RPN box loss: 0.01879 RPN score loss: 0.01527 RPN total loss: 0.03406 Total loss: 1.00381 timestamp: 1655061074.4178412 iteration: 67475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10569 FastRCNN class loss: 0.11093 FastRCNN total loss: 0.21661 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.13988 RPN box loss: 0.01573 RPN score loss: 0.00639 RPN total loss: 0.02212 Total loss: 0.94532 timestamp: 1655061077.685368 iteration: 67480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.09893 FastRCNN total loss: 0.18793 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.15863 RPN box loss: 0.02881 RPN score loss: 0.0154 RPN total loss: 0.04421 Total loss: 0.95748 timestamp: 1655061080.9938476 iteration: 67485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11092 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.18082 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.13466 RPN box loss: 0.00526 RPN score loss: 0.00161 RPN total loss: 0.00687 Total loss: 0.88905 timestamp: 1655061084.3267028 iteration: 67490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16667 FastRCNN class loss: 0.08866 FastRCNN total loss: 0.25533 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.18356 RPN box loss: 0.02532 RPN score loss: 0.0063 RPN total loss: 0.03162 Total loss: 1.03721 timestamp: 1655061087.5954924 iteration: 67495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1141 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.17951 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.13153 RPN box loss: 0.01203 RPN score loss: 0.00383 RPN total loss: 0.01587 Total loss: 0.89362 timestamp: 1655061090.799692 iteration: 67500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09298 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.15862 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.10691 RPN box loss: 0.00612 RPN score loss: 0.0026 RPN total loss: 0.00872 Total loss: 0.84095 timestamp: 1655061094.0063684 iteration: 67505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10044 FastRCNN class loss: 0.0686 FastRCNN total loss: 0.16904 L1 loss: 0.0000e+00 L2 loss: 0.5667 Learning rate: 0.0004 Mask loss: 0.14763 RPN box loss: 0.03003 RPN score loss: 0.00327 RPN total loss: 0.0333 Total loss: 0.91666 timestamp: 1655061097.2869627 iteration: 67510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07249 FastRCNN class loss: 0.05793 FastRCNN total loss: 0.13042 L1 loss: 0.0000e+00 L2 loss: 0.56669 Learning rate: 0.0004 Mask loss: 0.11568 RPN box loss: 0.02202 RPN score loss: 0.00463 RPN total loss: 0.02665 Total loss: 0.83944 timestamp: 1655061100.6046672 iteration: 67515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11548 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.19186 L1 loss: 0.0000e+00 L2 loss: 0.56669 Learning rate: 0.0004 Mask loss: 0.15775 RPN box loss: 0.01862 RPN score loss: 0.00612 RPN total loss: 0.02475 Total loss: 0.94105 timestamp: 1655061103.909329 iteration: 67520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12053 FastRCNN class loss: 0.08338 FastRCNN total loss: 0.20391 L1 loss: 0.0000e+00 L2 loss: 0.56669 Learning rate: 0.0004 Mask loss: 0.13406 RPN box loss: 0.01927 RPN score loss: 0.0069 RPN total loss: 0.02617 Total loss: 0.93083 timestamp: 1655061107.198877 iteration: 67525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1069 FastRCNN class loss: 0.05491 FastRCNN total loss: 0.16181 L1 loss: 0.0000e+00 L2 loss: 0.56669 Learning rate: 0.0004 Mask loss: 0.16766 RPN box loss: 0.0093 RPN score loss: 0.00258 RPN total loss: 0.01188 Total loss: 0.90804 timestamp: 1655061110.4703898 iteration: 67530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17143 FastRCNN class loss: 0.12016 FastRCNN total loss: 0.29158 L1 loss: 0.0000e+00 L2 loss: 0.56669 Learning rate: 0.0004 Mask loss: 0.19676 RPN box loss: 0.01763 RPN score loss: 0.01765 RPN total loss: 0.03528 Total loss: 1.0903 timestamp: 1655061113.7464924 iteration: 67535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10752 FastRCNN class loss: 0.09837 FastRCNN total loss: 0.20588 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.24776 RPN box loss: 0.02686 RPN score loss: 0.00735 RPN total loss: 0.03421 Total loss: 1.05453 timestamp: 1655061116.9615982 iteration: 67540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08768 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.1513 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.11213 RPN box loss: 0.01002 RPN score loss: 0.0028 RPN total loss: 0.01282 Total loss: 0.84293 timestamp: 1655061120.2320914 iteration: 67545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0841 FastRCNN class loss: 0.07345 FastRCNN total loss: 0.15755 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.2552 RPN box loss: 0.02073 RPN score loss: 0.00414 RPN total loss: 0.02487 Total loss: 1.00431 timestamp: 1655061123.5639274 iteration: 67550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08656 FastRCNN class loss: 0.06412 FastRCNN total loss: 0.15067 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.09206 RPN box loss: 0.01763 RPN score loss: 0.00195 RPN total loss: 0.01958 Total loss: 0.829 timestamp: 1655061126.8247676 iteration: 67555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.065 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.13408 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.1714 RPN box loss: 0.0157 RPN score loss: 0.01115 RPN total loss: 0.02684 Total loss: 0.89901 timestamp: 1655061130.1103508 iteration: 67560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1255 FastRCNN class loss: 0.09265 FastRCNN total loss: 0.21815 L1 loss: 0.0000e+00 L2 loss: 0.56668 Learning rate: 0.0004 Mask loss: 0.23937 RPN box loss: 0.02614 RPN score loss: 0.01422 RPN total loss: 0.04036 Total loss: 1.06455 timestamp: 1655061133.415676 iteration: 67565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06012 FastRCNN class loss: 0.0432 FastRCNN total loss: 0.10332 L1 loss: 0.0000e+00 L2 loss: 0.56667 Learning rate: 0.0004 Mask loss: 0.12856 RPN box loss: 0.022 RPN score loss: 0.00526 RPN total loss: 0.02726 Total loss: 0.82581 timestamp: 1655061136.6535435 iteration: 67570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07068 FastRCNN class loss: 0.06084 FastRCNN total loss: 0.13152 L1 loss: 0.0000e+00 L2 loss: 0.56667 Learning rate: 0.0004 Mask loss: 0.10494 RPN box loss: 0.01641 RPN score loss: 0.00457 RPN total loss: 0.02098 Total loss: 0.82411 timestamp: 1655061139.8838527 iteration: 67575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09732 FastRCNN class loss: 0.07335 FastRCNN total loss: 0.17066 L1 loss: 0.0000e+00 L2 loss: 0.56667 Learning rate: 0.0004 Mask loss: 0.14388 RPN box loss: 0.00943 RPN score loss: 0.0045 RPN total loss: 0.01393 Total loss: 0.89515 timestamp: 1655061143.2212412 iteration: 67580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16729 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.24122 L1 loss: 0.0000e+00 L2 loss: 0.56667 Learning rate: 0.0004 Mask loss: 0.38093 RPN box loss: 0.03028 RPN score loss: 0.00599 RPN total loss: 0.03627 Total loss: 1.2251 timestamp: 1655061146.4649363 iteration: 67585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08157 FastRCNN class loss: 0.09666 FastRCNN total loss: 0.17823 L1 loss: 0.0000e+00 L2 loss: 0.56667 Learning rate: 0.0004 Mask loss: 0.154 RPN box loss: 0.01038 RPN score loss: 0.00746 RPN total loss: 0.01784 Total loss: 0.91674 timestamp: 1655061149.7428668 iteration: 67590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06761 FastRCNN class loss: 0.05839 FastRCNN total loss: 0.126 L1 loss: 0.0000e+00 L2 loss: 0.56666 Learning rate: 0.0004 Mask loss: 0.13442 RPN box loss: 0.01621 RPN score loss: 0.0136 RPN total loss: 0.02982 Total loss: 0.8569 timestamp: 1655061153.0298479 iteration: 67595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1144 FastRCNN class loss: 0.11941 FastRCNN total loss: 0.2338 L1 loss: 0.0000e+00 L2 loss: 0.56666 Learning rate: 0.0004 Mask loss: 0.16951 RPN box loss: 0.01567 RPN score loss: 0.01352 RPN total loss: 0.02919 Total loss: 0.99916 timestamp: 1655061156.3383074 iteration: 67600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13031 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.18085 L1 loss: 0.0000e+00 L2 loss: 0.56666 Learning rate: 0.0004 Mask loss: 0.12498 RPN box loss: 0.01198 RPN score loss: 0.00279 RPN total loss: 0.01477 Total loss: 0.88725 timestamp: 1655061159.6390197 iteration: 67605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06081 FastRCNN class loss: 0.05142 FastRCNN total loss: 0.11223 L1 loss: 0.0000e+00 L2 loss: 0.56666 Learning rate: 0.0004 Mask loss: 0.07124 RPN box loss: 0.00491 RPN score loss: 0.00896 RPN total loss: 0.01387 Total loss: 0.764 timestamp: 1655061162.8561542 iteration: 67610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09132 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.14673 L1 loss: 0.0000e+00 L2 loss: 0.56666 Learning rate: 0.0004 Mask loss: 0.07255 RPN box loss: 0.01489 RPN score loss: 0.00116 RPN total loss: 0.01605 Total loss: 0.80198 timestamp: 1655061166.166174 iteration: 67615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14932 FastRCNN class loss: 0.09831 FastRCNN total loss: 0.24763 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.16776 RPN box loss: 0.01517 RPN score loss: 0.00634 RPN total loss: 0.02151 Total loss: 1.00355 timestamp: 1655061169.4543564 iteration: 67620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06114 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.11066 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.12084 RPN box loss: 0.02265 RPN score loss: 0.00641 RPN total loss: 0.02906 Total loss: 0.82722 timestamp: 1655061172.750449 iteration: 67625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09966 FastRCNN class loss: 0.05867 FastRCNN total loss: 0.15833 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.18626 RPN box loss: 0.01451 RPN score loss: 0.00869 RPN total loss: 0.02321 Total loss: 0.93445 timestamp: 1655061176.0062273 iteration: 67630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13345 FastRCNN class loss: 0.09322 FastRCNN total loss: 0.22667 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.16042 RPN box loss: 0.01684 RPN score loss: 0.00815 RPN total loss: 0.02498 Total loss: 0.97873 timestamp: 1655061179.2170868 iteration: 67635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14786 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.21454 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.16303 RPN box loss: 0.01379 RPN score loss: 0.00211 RPN total loss: 0.0159 Total loss: 0.96012 timestamp: 1655061182.5259748 iteration: 67640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09176 FastRCNN class loss: 0.06887 FastRCNN total loss: 0.16063 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.13276 RPN box loss: 0.01655 RPN score loss: 0.00328 RPN total loss: 0.01983 Total loss: 0.87987 timestamp: 1655061185.820281 iteration: 67645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03855 FastRCNN class loss: 0.034 FastRCNN total loss: 0.07255 L1 loss: 0.0000e+00 L2 loss: 0.56665 Learning rate: 0.0004 Mask loss: 0.13173 RPN box loss: 0.0066 RPN score loss: 0.00735 RPN total loss: 0.01395 Total loss: 0.78487 timestamp: 1655061189.0690887 iteration: 67650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05067 FastRCNN class loss: 0.0281 FastRCNN total loss: 0.07877 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.10343 RPN box loss: 0.00146 RPN score loss: 0.00261 RPN total loss: 0.00407 Total loss: 0.75291 timestamp: 1655061192.4323847 iteration: 67655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.05365 FastRCNN total loss: 0.1457 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.11177 RPN box loss: 0.00202 RPN score loss: 0.00206 RPN total loss: 0.00409 Total loss: 0.8282 timestamp: 1655061195.7042692 iteration: 67660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10162 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.16238 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.11283 RPN box loss: 0.01525 RPN score loss: 0.0042 RPN total loss: 0.01945 Total loss: 0.8613 timestamp: 1655061198.9015477 iteration: 67665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07116 FastRCNN class loss: 0.04793 FastRCNN total loss: 0.1191 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.12436 RPN box loss: 0.01149 RPN score loss: 0.00138 RPN total loss: 0.01288 Total loss: 0.82297 timestamp: 1655061202.1090086 iteration: 67670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08065 FastRCNN class loss: 0.08159 FastRCNN total loss: 0.16224 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.17334 RPN box loss: 0.01551 RPN score loss: 0.00761 RPN total loss: 0.02312 Total loss: 0.92534 timestamp: 1655061205.3738086 iteration: 67675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12154 FastRCNN class loss: 0.09749 FastRCNN total loss: 0.21903 L1 loss: 0.0000e+00 L2 loss: 0.56664 Learning rate: 0.0004 Mask loss: 0.14561 RPN box loss: 0.01742 RPN score loss: 0.00212 RPN total loss: 0.01955 Total loss: 0.95083 timestamp: 1655061208.675306 iteration: 67680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.04232 FastRCNN total loss: 0.12009 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.13824 RPN box loss: 0.03915 RPN score loss: 0.00659 RPN total loss: 0.04574 Total loss: 0.87071 timestamp: 1655061211.9326541 iteration: 67685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09586 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.15634 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.13263 RPN box loss: 0.02793 RPN score loss: 0.00654 RPN total loss: 0.03447 Total loss: 0.89008 timestamp: 1655061215.2270856 iteration: 67690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1245 FastRCNN class loss: 0.08183 FastRCNN total loss: 0.20632 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.19221 RPN box loss: 0.02367 RPN score loss: 0.00264 RPN total loss: 0.02631 Total loss: 0.99147 timestamp: 1655061218.4907322 iteration: 67695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07896 FastRCNN class loss: 0.0844 FastRCNN total loss: 0.16336 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.14799 RPN box loss: 0.0135 RPN score loss: 0.00517 RPN total loss: 0.01867 Total loss: 0.89665 timestamp: 1655061221.7661383 iteration: 67700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09026 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.15107 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.11477 RPN box loss: 0.00594 RPN score loss: 0.00742 RPN total loss: 0.01336 Total loss: 0.84583 timestamp: 1655061225.0456994 iteration: 67705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0802 FastRCNN class loss: 0.07128 FastRCNN total loss: 0.15148 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.17253 RPN box loss: 0.0149 RPN score loss: 0.00705 RPN total loss: 0.02195 Total loss: 0.91259 timestamp: 1655061228.3385353 iteration: 67710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.15676 L1 loss: 0.0000e+00 L2 loss: 0.56663 Learning rate: 0.0004 Mask loss: 0.20971 RPN box loss: 0.04017 RPN score loss: 0.01428 RPN total loss: 0.05445 Total loss: 0.98755 timestamp: 1655061231.6153896 iteration: 67715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12715 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.18477 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.18528 RPN box loss: 0.00818 RPN score loss: 0.002 RPN total loss: 0.01018 Total loss: 0.94686 timestamp: 1655061234.9674273 iteration: 67720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09258 FastRCNN class loss: 0.092 FastRCNN total loss: 0.18458 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.16507 RPN box loss: 0.01598 RPN score loss: 0.00413 RPN total loss: 0.02011 Total loss: 0.93639 timestamp: 1655061238.2402651 iteration: 67725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04642 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.0962 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.11056 RPN box loss: 0.0033 RPN score loss: 0.00897 RPN total loss: 0.01227 Total loss: 0.78566 timestamp: 1655061241.5232372 iteration: 67730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09355 FastRCNN class loss: 0.07404 FastRCNN total loss: 0.16759 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.17103 RPN box loss: 0.01004 RPN score loss: 0.02103 RPN total loss: 0.03107 Total loss: 0.93631 timestamp: 1655061244.7743325 iteration: 67735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09812 FastRCNN class loss: 0.04912 FastRCNN total loss: 0.14724 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.0963 RPN box loss: 0.01236 RPN score loss: 0.00369 RPN total loss: 0.01606 Total loss: 0.82622 timestamp: 1655061248.0562181 iteration: 67740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11979 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.19177 L1 loss: 0.0000e+00 L2 loss: 0.56662 Learning rate: 0.0004 Mask loss: 0.08893 RPN box loss: 0.00631 RPN score loss: 0.00247 RPN total loss: 0.00878 Total loss: 0.8561 timestamp: 1655061251.3154786 iteration: 67745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13375 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.19523 L1 loss: 0.0000e+00 L2 loss: 0.56661 Learning rate: 0.0004 Mask loss: 0.10419 RPN box loss: 0.00511 RPN score loss: 0.00499 RPN total loss: 0.0101 Total loss: 0.87614 timestamp: 1655061254.625605 iteration: 67750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.14122 L1 loss: 0.0000e+00 L2 loss: 0.56661 Learning rate: 0.0004 Mask loss: 0.10939 RPN box loss: 0.01541 RPN score loss: 0.0033 RPN total loss: 0.01871 Total loss: 0.83593 timestamp: 1655061257.9163795 iteration: 67755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07616 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.13952 L1 loss: 0.0000e+00 L2 loss: 0.56661 Learning rate: 0.0004 Mask loss: 0.13069 RPN box loss: 0.01336 RPN score loss: 0.00851 RPN total loss: 0.02188 Total loss: 0.8587 timestamp: 1655061261.1746106 iteration: 67760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12132 FastRCNN class loss: 0.08377 FastRCNN total loss: 0.20509 L1 loss: 0.0000e+00 L2 loss: 0.56661 Learning rate: 0.0004 Mask loss: 0.14004 RPN box loss: 0.03865 RPN score loss: 0.01297 RPN total loss: 0.05162 Total loss: 0.96335 timestamp: 1655061264.4081738 iteration: 67765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11631 FastRCNN class loss: 0.06663 FastRCNN total loss: 0.18294 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.11663 RPN box loss: 0.01168 RPN score loss: 0.00799 RPN total loss: 0.01967 Total loss: 0.88585 timestamp: 1655061267.683851 iteration: 67770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.07405 FastRCNN total loss: 0.13919 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.10219 RPN box loss: 0.01042 RPN score loss: 0.00955 RPN total loss: 0.01997 Total loss: 0.82795 timestamp: 1655061270.9935787 iteration: 67775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10545 FastRCNN class loss: 0.04656 FastRCNN total loss: 0.15201 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.11862 RPN box loss: 0.01768 RPN score loss: 0.00279 RPN total loss: 0.02047 Total loss: 0.8577 timestamp: 1655061274.238153 iteration: 67780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12258 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.18851 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.14721 RPN box loss: 0.01736 RPN score loss: 0.00496 RPN total loss: 0.02232 Total loss: 0.92464 timestamp: 1655061277.5015657 iteration: 67785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10834 FastRCNN class loss: 0.09083 FastRCNN total loss: 0.19917 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.1413 RPN box loss: 0.00601 RPN score loss: 0.00961 RPN total loss: 0.01562 Total loss: 0.92269 timestamp: 1655061280.7934191 iteration: 67790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.06806 FastRCNN total loss: 0.13878 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.18192 RPN box loss: 0.01094 RPN score loss: 0.00454 RPN total loss: 0.01549 Total loss: 0.90278 timestamp: 1655061284.0293825 iteration: 67795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11672 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.18963 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.10438 RPN box loss: 0.01205 RPN score loss: 0.00533 RPN total loss: 0.01738 Total loss: 0.87798 timestamp: 1655061287.2970371 iteration: 67800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0543 FastRCNN class loss: 0.0444 FastRCNN total loss: 0.0987 L1 loss: 0.0000e+00 L2 loss: 0.5666 Learning rate: 0.0004 Mask loss: 0.11703 RPN box loss: 0.00381 RPN score loss: 0.00922 RPN total loss: 0.01303 Total loss: 0.79536 timestamp: 1655061290.534194 iteration: 67805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1219 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.18896 L1 loss: 0.0000e+00 L2 loss: 0.56659 Learning rate: 0.0004 Mask loss: 0.13246 RPN box loss: 0.03697 RPN score loss: 0.00321 RPN total loss: 0.04018 Total loss: 0.92819 timestamp: 1655061293.8240342 iteration: 67810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07153 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.12069 L1 loss: 0.0000e+00 L2 loss: 0.56659 Learning rate: 0.0004 Mask loss: 0.11468 RPN box loss: 0.01558 RPN score loss: 0.0077 RPN total loss: 0.02328 Total loss: 0.82524 timestamp: 1655061297.1406007 iteration: 67815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0874 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.1618 L1 loss: 0.0000e+00 L2 loss: 0.56659 Learning rate: 0.0004 Mask loss: 0.11581 RPN box loss: 0.0101 RPN score loss: 0.00618 RPN total loss: 0.01628 Total loss: 0.86049 timestamp: 1655061300.43178 iteration: 67820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10011 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.1542 L1 loss: 0.0000e+00 L2 loss: 0.56659 Learning rate: 0.0004 Mask loss: 0.13125 RPN box loss: 0.01476 RPN score loss: 0.0039 RPN total loss: 0.01866 Total loss: 0.8707 timestamp: 1655061303.6844034 iteration: 67825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0776 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.15187 L1 loss: 0.0000e+00 L2 loss: 0.56659 Learning rate: 0.0004 Mask loss: 0.18572 RPN box loss: 0.02094 RPN score loss: 0.00655 RPN total loss: 0.02749 Total loss: 0.93166 timestamp: 1655061307.0052848 iteration: 67830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09105 FastRCNN class loss: 0.0545 FastRCNN total loss: 0.14555 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.12501 RPN box loss: 0.01192 RPN score loss: 0.00492 RPN total loss: 0.01685 Total loss: 0.85399 timestamp: 1655061310.3523746 iteration: 67835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07751 FastRCNN class loss: 0.07069 FastRCNN total loss: 0.14821 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.11198 RPN box loss: 0.01017 RPN score loss: 0.00244 RPN total loss: 0.01261 Total loss: 0.83938 timestamp: 1655061313.686111 iteration: 67840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09074 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.15135 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.13707 RPN box loss: 0.03334 RPN score loss: 0.00389 RPN total loss: 0.03724 Total loss: 0.89223 timestamp: 1655061317.0041146 iteration: 67845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.08657 FastRCNN total loss: 0.19945 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.11305 RPN box loss: 0.01065 RPN score loss: 0.00237 RPN total loss: 0.01302 Total loss: 0.8921 timestamp: 1655061320.2999294 iteration: 67850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.18265 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.1513 RPN box loss: 0.0351 RPN score loss: 0.00312 RPN total loss: 0.03822 Total loss: 0.93875 timestamp: 1655061323.6469476 iteration: 67855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0947 FastRCNN class loss: 0.04005 FastRCNN total loss: 0.13474 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.11951 RPN box loss: 0.00857 RPN score loss: 0.00367 RPN total loss: 0.01224 Total loss: 0.83306 timestamp: 1655061326.8918712 iteration: 67860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08917 FastRCNN class loss: 0.04184 FastRCNN total loss: 0.13101 L1 loss: 0.0000e+00 L2 loss: 0.56658 Learning rate: 0.0004 Mask loss: 0.11389 RPN box loss: 0.01473 RPN score loss: 0.00308 RPN total loss: 0.01781 Total loss: 0.82928 timestamp: 1655061330.1841977 iteration: 67865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.117 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.21232 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.15647 RPN box loss: 0.01713 RPN score loss: 0.0082 RPN total loss: 0.02533 Total loss: 0.96071 timestamp: 1655061333.4586117 iteration: 67870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.13081 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.14275 RPN box loss: 0.00992 RPN score loss: 0.00308 RPN total loss: 0.013 Total loss: 0.85313 timestamp: 1655061336.8116372 iteration: 67875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0841 FastRCNN class loss: 0.05274 FastRCNN total loss: 0.13684 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.11773 RPN box loss: 0.0128 RPN score loss: 0.00931 RPN total loss: 0.02211 Total loss: 0.84326 timestamp: 1655061340.179078 iteration: 67880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.12618 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.15561 RPN box loss: 0.02197 RPN score loss: 0.00387 RPN total loss: 0.02584 Total loss: 0.8742 timestamp: 1655061343.4384494 iteration: 67885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08841 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.14837 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.1925 RPN box loss: 0.01596 RPN score loss: 0.00389 RPN total loss: 0.01985 Total loss: 0.92729 timestamp: 1655061346.6845207 iteration: 67890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1075 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.16959 L1 loss: 0.0000e+00 L2 loss: 0.56657 Learning rate: 0.0004 Mask loss: 0.15277 RPN box loss: 0.02027 RPN score loss: 0.00644 RPN total loss: 0.02671 Total loss: 0.91563 timestamp: 1655061349.997696 iteration: 67895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07648 FastRCNN class loss: 0.05089 FastRCNN total loss: 0.12737 L1 loss: 0.0000e+00 L2 loss: 0.56656 Learning rate: 0.0004 Mask loss: 0.12261 RPN box loss: 0.02729 RPN score loss: 0.00543 RPN total loss: 0.03272 Total loss: 0.84926 timestamp: 1655061353.31144 iteration: 67900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06732 FastRCNN class loss: 0.06512 FastRCNN total loss: 0.13245 L1 loss: 0.0000e+00 L2 loss: 0.56656 Learning rate: 0.0004 Mask loss: 0.15251 RPN box loss: 0.00485 RPN score loss: 0.00071 RPN total loss: 0.00556 Total loss: 0.85707 timestamp: 1655061356.5429726 iteration: 67905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10073 FastRCNN class loss: 0.08475 FastRCNN total loss: 0.18548 L1 loss: 0.0000e+00 L2 loss: 0.56656 Learning rate: 0.0004 Mask loss: 0.12236 RPN box loss: 0.0176 RPN score loss: 0.01426 RPN total loss: 0.03186 Total loss: 0.90625 timestamp: 1655061359.8120492 iteration: 67910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.10511 L1 loss: 0.0000e+00 L2 loss: 0.56656 Learning rate: 0.0004 Mask loss: 0.10772 RPN box loss: 0.00796 RPN score loss: 0.00397 RPN total loss: 0.01193 Total loss: 0.79132 timestamp: 1655061363.0787077 iteration: 67915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11577 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.18149 L1 loss: 0.0000e+00 L2 loss: 0.56656 Learning rate: 0.0004 Mask loss: 0.14469 RPN box loss: 0.0145 RPN score loss: 0.00417 RPN total loss: 0.01866 Total loss: 0.91139 timestamp: 1655061366.417871 iteration: 67920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10759 FastRCNN class loss: 0.06329 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.11467 RPN box loss: 0.00829 RPN score loss: 0.00264 RPN total loss: 0.01093 Total loss: 0.86304 timestamp: 1655061369.7094636 iteration: 67925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05026 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.09373 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.12954 RPN box loss: 0.01992 RPN score loss: 0.00463 RPN total loss: 0.02455 Total loss: 0.81437 timestamp: 1655061373.0002007 iteration: 67930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07937 FastRCNN class loss: 0.06568 FastRCNN total loss: 0.14505 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.1405 RPN box loss: 0.01411 RPN score loss: 0.00297 RPN total loss: 0.01708 Total loss: 0.86919 timestamp: 1655061376.2572577 iteration: 67935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07586 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.10259 RPN box loss: 0.00795 RPN score loss: 0.00306 RPN total loss: 0.01101 Total loss: 0.82716 timestamp: 1655061379.502542 iteration: 67940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07387 FastRCNN class loss: 0.07418 FastRCNN total loss: 0.14805 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.11749 RPN box loss: 0.00444 RPN score loss: 0.00471 RPN total loss: 0.00915 Total loss: 0.84124 timestamp: 1655061382.7613945 iteration: 67945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09323 FastRCNN class loss: 0.05193 FastRCNN total loss: 0.14516 L1 loss: 0.0000e+00 L2 loss: 0.56655 Learning rate: 0.0004 Mask loss: 0.11537 RPN box loss: 0.01381 RPN score loss: 0.00205 RPN total loss: 0.01586 Total loss: 0.84293 timestamp: 1655061385.9766746 iteration: 67950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06363 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.10348 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.11127 RPN box loss: 0.00769 RPN score loss: 0.00136 RPN total loss: 0.00905 Total loss: 0.79034 timestamp: 1655061389.1635237 iteration: 67955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09715 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.16362 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.12868 RPN box loss: 0.01438 RPN score loss: 0.00786 RPN total loss: 0.02224 Total loss: 0.88108 timestamp: 1655061392.3650975 iteration: 67960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14372 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.20365 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.14641 RPN box loss: 0.05099 RPN score loss: 0.00746 RPN total loss: 0.05846 Total loss: 0.97505 timestamp: 1655061395.6518815 iteration: 67965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05948 FastRCNN class loss: 0.04565 FastRCNN total loss: 0.10512 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.09791 RPN box loss: 0.00644 RPN score loss: 0.00416 RPN total loss: 0.0106 Total loss: 0.78016 timestamp: 1655061398.9418576 iteration: 67970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10535 FastRCNN class loss: 0.05756 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.13422 RPN box loss: 0.01624 RPN score loss: 0.00251 RPN total loss: 0.01875 Total loss: 0.88241 timestamp: 1655061402.2264826 iteration: 67975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09902 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.16794 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.13255 RPN box loss: 0.01749 RPN score loss: 0.00568 RPN total loss: 0.02318 Total loss: 0.8902 timestamp: 1655061405.508168 iteration: 67980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09455 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.56654 Learning rate: 0.0004 Mask loss: 0.14328 RPN box loss: 0.0059 RPN score loss: 0.00343 RPN total loss: 0.00933 Total loss: 0.88962 timestamp: 1655061408.7295876 iteration: 67985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10577 FastRCNN class loss: 0.07709 FastRCNN total loss: 0.18285 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.13378 RPN box loss: 0.00674 RPN score loss: 0.00911 RPN total loss: 0.01585 Total loss: 0.89902 timestamp: 1655061412.0849102 iteration: 67990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11152 FastRCNN class loss: 0.09476 FastRCNN total loss: 0.20628 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.13177 RPN box loss: 0.01467 RPN score loss: 0.00332 RPN total loss: 0.01798 Total loss: 0.92257 timestamp: 1655061415.371923 iteration: 67995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09061 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.16315 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.14072 RPN box loss: 0.01907 RPN score loss: 0.00553 RPN total loss: 0.0246 Total loss: 0.895 timestamp: 1655061418.6208086 iteration: 68000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07051 FastRCNN class loss: 0.04746 FastRCNN total loss: 0.11797 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.17032 RPN box loss: 0.00814 RPN score loss: 0.00224 RPN total loss: 0.01038 Total loss: 0.8652 timestamp: 1655061421.9438612 iteration: 68005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10309 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.16109 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.09387 RPN box loss: 0.00829 RPN score loss: 0.00117 RPN total loss: 0.00947 Total loss: 0.83095 timestamp: 1655061425.1939673 iteration: 68010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09055 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.15629 L1 loss: 0.0000e+00 L2 loss: 0.56653 Learning rate: 0.0004 Mask loss: 0.14194 RPN box loss: 0.03852 RPN score loss: 0.00511 RPN total loss: 0.04363 Total loss: 0.90839 timestamp: 1655061428.4414465 iteration: 68015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10092 FastRCNN class loss: 0.08886 FastRCNN total loss: 0.18977 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.09544 RPN box loss: 0.01631 RPN score loss: 0.00709 RPN total loss: 0.0234 Total loss: 0.87513 timestamp: 1655061431.701805 iteration: 68020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.06471 FastRCNN total loss: 0.14054 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.13315 RPN box loss: 0.01372 RPN score loss: 0.00343 RPN total loss: 0.01715 Total loss: 0.85737 timestamp: 1655061435.0043974 iteration: 68025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11081 FastRCNN class loss: 0.06601 FastRCNN total loss: 0.17682 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.11864 RPN box loss: 0.01381 RPN score loss: 0.0079 RPN total loss: 0.02171 Total loss: 0.88369 timestamp: 1655061438.2019417 iteration: 68030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1511 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.22475 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.1173 RPN box loss: 0.0089 RPN score loss: 0.01452 RPN total loss: 0.02341 Total loss: 0.93199 timestamp: 1655061441.4899583 iteration: 68035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07931 FastRCNN class loss: 0.10955 FastRCNN total loss: 0.18886 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.15334 RPN box loss: 0.02725 RPN score loss: 0.01323 RPN total loss: 0.04047 Total loss: 0.9492 timestamp: 1655061444.8002813 iteration: 68040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07157 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.12841 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.08351 RPN box loss: 0.00783 RPN score loss: 0.00377 RPN total loss: 0.0116 Total loss: 0.79004 timestamp: 1655061448.0740304 iteration: 68045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12069 FastRCNN class loss: 0.0877 FastRCNN total loss: 0.20839 L1 loss: 0.0000e+00 L2 loss: 0.56652 Learning rate: 0.0004 Mask loss: 0.15494 RPN box loss: 0.0135 RPN score loss: 0.00497 RPN total loss: 0.01847 Total loss: 0.94833 timestamp: 1655061451.3180237 iteration: 68050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06229 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.11209 L1 loss: 0.0000e+00 L2 loss: 0.56651 Learning rate: 0.0004 Mask loss: 0.1331 RPN box loss: 0.0046 RPN score loss: 0.00393 RPN total loss: 0.00853 Total loss: 0.82024 timestamp: 1655061454.6743863 iteration: 68055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08721 FastRCNN class loss: 0.05587 FastRCNN total loss: 0.14309 L1 loss: 0.0000e+00 L2 loss: 0.56651 Learning rate: 0.0004 Mask loss: 0.16192 RPN box loss: 0.01888 RPN score loss: 0.00413 RPN total loss: 0.02301 Total loss: 0.89453 timestamp: 1655061457.9470937 iteration: 68060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06024 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.1353 L1 loss: 0.0000e+00 L2 loss: 0.56651 Learning rate: 0.0004 Mask loss: 0.08993 RPN box loss: 0.0092 RPN score loss: 0.00583 RPN total loss: 0.01503 Total loss: 0.80677 timestamp: 1655061461.22114 iteration: 68065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15609 FastRCNN class loss: 0.12667 FastRCNN total loss: 0.28277 L1 loss: 0.0000e+00 L2 loss: 0.56651 Learning rate: 0.0004 Mask loss: 0.16674 RPN box loss: 0.02886 RPN score loss: 0.00989 RPN total loss: 0.03876 Total loss: 1.05477 timestamp: 1655061464.4491775 iteration: 68070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07243 FastRCNN class loss: 0.09713 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 0.56651 Learning rate: 0.0004 Mask loss: 0.19297 RPN box loss: 0.02177 RPN score loss: 0.00357 RPN total loss: 0.02534 Total loss: 0.95438 timestamp: 1655061467.7557878 iteration: 68075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08749 FastRCNN class loss: 0.08828 FastRCNN total loss: 0.17577 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.17191 RPN box loss: 0.01324 RPN score loss: 0.00521 RPN total loss: 0.01845 Total loss: 0.93264 timestamp: 1655061471.048966 iteration: 68080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10165 FastRCNN class loss: 0.08698 FastRCNN total loss: 0.18863 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.16276 RPN box loss: 0.0129 RPN score loss: 0.00153 RPN total loss: 0.01443 Total loss: 0.93232 timestamp: 1655061474.2719631 iteration: 68085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.06294 FastRCNN total loss: 0.16291 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.26047 RPN box loss: 0.00246 RPN score loss: 0.00184 RPN total loss: 0.0043 Total loss: 0.99417 timestamp: 1655061477.6184754 iteration: 68090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09308 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.14965 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.11522 RPN box loss: 0.01206 RPN score loss: 0.00189 RPN total loss: 0.01394 Total loss: 0.84531 timestamp: 1655061480.8446827 iteration: 68095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05967 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.134 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.10502 RPN box loss: 0.02141 RPN score loss: 0.00464 RPN total loss: 0.02605 Total loss: 0.83157 timestamp: 1655061484.0531616 iteration: 68100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06795 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.12028 L1 loss: 0.0000e+00 L2 loss: 0.5665 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.01238 RPN score loss: 0.00591 RPN total loss: 0.01829 Total loss: 0.83419 timestamp: 1655061487.3678086 iteration: 68105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08992 FastRCNN class loss: 0.08198 FastRCNN total loss: 0.1719 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.189 RPN box loss: 0.04389 RPN score loss: 0.01225 RPN total loss: 0.05614 Total loss: 0.98353 timestamp: 1655061490.6806462 iteration: 68110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08041 FastRCNN class loss: 0.0636 FastRCNN total loss: 0.14401 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.12733 RPN box loss: 0.01399 RPN score loss: 0.00433 RPN total loss: 0.01832 Total loss: 0.85615 timestamp: 1655061493.9502163 iteration: 68115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08263 FastRCNN class loss: 0.06218 FastRCNN total loss: 0.14481 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.12928 RPN box loss: 0.00689 RPN score loss: 0.00404 RPN total loss: 0.01093 Total loss: 0.85151 timestamp: 1655061497.2369206 iteration: 68120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09438 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.1506 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.14531 RPN box loss: 0.01091 RPN score loss: 0.00568 RPN total loss: 0.0166 Total loss: 0.879 timestamp: 1655061500.597727 iteration: 68125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15417 FastRCNN class loss: 0.1349 FastRCNN total loss: 0.28907 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.18904 RPN box loss: 0.04512 RPN score loss: 0.00962 RPN total loss: 0.05474 Total loss: 1.09933 timestamp: 1655061503.79683 iteration: 68130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09199 FastRCNN class loss: 0.05099 FastRCNN total loss: 0.14298 L1 loss: 0.0000e+00 L2 loss: 0.56649 Learning rate: 0.0004 Mask loss: 0.08377 RPN box loss: 0.01586 RPN score loss: 0.00216 RPN total loss: 0.01802 Total loss: 0.81125 timestamp: 1655061507.1195571 iteration: 68135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05635 FastRCNN class loss: 0.04785 FastRCNN total loss: 0.1042 L1 loss: 0.0000e+00 L2 loss: 0.56648 Learning rate: 0.0004 Mask loss: 0.12641 RPN box loss: 0.01104 RPN score loss: 0.00143 RPN total loss: 0.01247 Total loss: 0.80956 timestamp: 1655061510.3799393 iteration: 68140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05762 FastRCNN class loss: 0.05564 FastRCNN total loss: 0.11326 L1 loss: 0.0000e+00 L2 loss: 0.56648 Learning rate: 0.0004 Mask loss: 0.09274 RPN box loss: 0.01705 RPN score loss: 0.00892 RPN total loss: 0.02596 Total loss: 0.79845 timestamp: 1655061513.653328 iteration: 68145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09395 FastRCNN class loss: 0.07532 FastRCNN total loss: 0.16928 L1 loss: 0.0000e+00 L2 loss: 0.56648 Learning rate: 0.0004 Mask loss: 0.24763 RPN box loss: 0.01232 RPN score loss: 0.00488 RPN total loss: 0.0172 Total loss: 1.00059 timestamp: 1655061516.9011033 iteration: 68150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12315 FastRCNN class loss: 0.1687 FastRCNN total loss: 0.29185 L1 loss: 0.0000e+00 L2 loss: 0.56648 Learning rate: 0.0004 Mask loss: 0.13412 RPN box loss: 0.00937 RPN score loss: 0.00914 RPN total loss: 0.01851 Total loss: 1.01095 timestamp: 1655061520.2016072 iteration: 68155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0836 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.13046 L1 loss: 0.0000e+00 L2 loss: 0.56648 Learning rate: 0.0004 Mask loss: 0.13209 RPN box loss: 0.0071 RPN score loss: 0.00598 RPN total loss: 0.01308 Total loss: 0.84211 timestamp: 1655061523.5428905 iteration: 68160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13229 FastRCNN class loss: 0.08991 FastRCNN total loss: 0.22219 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.15199 RPN box loss: 0.01722 RPN score loss: 0.00798 RPN total loss: 0.0252 Total loss: 0.96585 timestamp: 1655061526.7986758 iteration: 68165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07382 FastRCNN class loss: 0.04856 FastRCNN total loss: 0.12238 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.1433 RPN box loss: 0.02089 RPN score loss: 0.00681 RPN total loss: 0.0277 Total loss: 0.85985 timestamp: 1655061529.976024 iteration: 68170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09894 FastRCNN class loss: 0.07636 FastRCNN total loss: 0.17529 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.18015 RPN box loss: 0.01054 RPN score loss: 0.00795 RPN total loss: 0.01849 Total loss: 0.9404 timestamp: 1655061533.1834495 iteration: 68175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09648 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.15758 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.11674 RPN box loss: 0.00882 RPN score loss: 0.00434 RPN total loss: 0.01316 Total loss: 0.85395 timestamp: 1655061536.407556 iteration: 68180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08713 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.17998 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.15284 RPN box loss: 0.01128 RPN score loss: 0.00298 RPN total loss: 0.01426 Total loss: 0.91354 timestamp: 1655061539.6265714 iteration: 68185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.05732 FastRCNN total loss: 0.14403 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.13189 RPN box loss: 0.01214 RPN score loss: 0.00437 RPN total loss: 0.01651 Total loss: 0.85889 timestamp: 1655061542.8644185 iteration: 68190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09696 FastRCNN class loss: 0.07313 FastRCNN total loss: 0.17008 L1 loss: 0.0000e+00 L2 loss: 0.56647 Learning rate: 0.0004 Mask loss: 0.12421 RPN box loss: 0.01522 RPN score loss: 0.00159 RPN total loss: 0.01681 Total loss: 0.87757 timestamp: 1655061546.0923462 iteration: 68195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0584 FastRCNN class loss: 0.04327 FastRCNN total loss: 0.10168 L1 loss: 0.0000e+00 L2 loss: 0.56646 Learning rate: 0.0004 Mask loss: 0.11722 RPN box loss: 0.00974 RPN score loss: 0.00459 RPN total loss: 0.01433 Total loss: 0.79969 timestamp: 1655061549.271515 iteration: 68200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09998 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.1725 L1 loss: 0.0000e+00 L2 loss: 0.56646 Learning rate: 0.0004 Mask loss: 0.13203 RPN box loss: 0.01515 RPN score loss: 0.00648 RPN total loss: 0.02163 Total loss: 0.89263 timestamp: 1655061552.5956767 iteration: 68205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13177 FastRCNN class loss: 0.08565 FastRCNN total loss: 0.21742 L1 loss: 0.0000e+00 L2 loss: 0.56646 Learning rate: 0.0004 Mask loss: 0.13576 RPN box loss: 0.0171 RPN score loss: 0.00636 RPN total loss: 0.02346 Total loss: 0.9431 timestamp: 1655061555.8818176 iteration: 68210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11771 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.18129 L1 loss: 0.0000e+00 L2 loss: 0.56646 Learning rate: 0.0004 Mask loss: 0.14499 RPN box loss: 0.02165 RPN score loss: 0.00425 RPN total loss: 0.0259 Total loss: 0.91864 timestamp: 1655061559.2009916 iteration: 68215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09263 FastRCNN class loss: 0.03957 FastRCNN total loss: 0.1322 L1 loss: 0.0000e+00 L2 loss: 0.56646 Learning rate: 0.0004 Mask loss: 0.07693 RPN box loss: 0.01816 RPN score loss: 0.00152 RPN total loss: 0.01968 Total loss: 0.79526 timestamp: 1655061562.5159342 iteration: 68220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09878 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.15897 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.13213 RPN box loss: 0.01088 RPN score loss: 0.00333 RPN total loss: 0.01421 Total loss: 0.87176 timestamp: 1655061565.7399578 iteration: 68225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07347 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.12892 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.13759 RPN box loss: 0.01266 RPN score loss: 0.00636 RPN total loss: 0.01902 Total loss: 0.85198 timestamp: 1655061569.0009844 iteration: 68230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.08084 FastRCNN total loss: 0.18275 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.13678 RPN box loss: 0.00989 RPN score loss: 0.00266 RPN total loss: 0.01256 Total loss: 0.89853 timestamp: 1655061572.2783816 iteration: 68235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06162 FastRCNN class loss: 0.05838 FastRCNN total loss: 0.12 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.12491 RPN box loss: 0.01539 RPN score loss: 0.00181 RPN total loss: 0.0172 Total loss: 0.82856 timestamp: 1655061575.6139505 iteration: 68240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10113 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.18108 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.16583 RPN box loss: 0.02093 RPN score loss: 0.00257 RPN total loss: 0.02351 Total loss: 0.93687 timestamp: 1655061578.915521 iteration: 68245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06418 FastRCNN class loss: 0.049 FastRCNN total loss: 0.11318 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.12974 RPN box loss: 0.00872 RPN score loss: 0.00301 RPN total loss: 0.01173 Total loss: 0.8211 timestamp: 1655061582.2025359 iteration: 68250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16053 FastRCNN class loss: 0.11644 FastRCNN total loss: 0.27697 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.23158 RPN box loss: 0.00729 RPN score loss: 0.00959 RPN total loss: 0.01688 Total loss: 1.09187 timestamp: 1655061585.4698133 iteration: 68255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06615 FastRCNN class loss: 0.03449 FastRCNN total loss: 0.10065 L1 loss: 0.0000e+00 L2 loss: 0.56645 Learning rate: 0.0004 Mask loss: 0.10531 RPN box loss: 0.00659 RPN score loss: 0.00332 RPN total loss: 0.00991 Total loss: 0.78231 timestamp: 1655061588.7077446 iteration: 68260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10164 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.16009 L1 loss: 0.0000e+00 L2 loss: 0.56644 Learning rate: 0.0004 Mask loss: 0.12971 RPN box loss: 0.01344 RPN score loss: 0.0037 RPN total loss: 0.01714 Total loss: 0.87339 timestamp: 1655061591.9479764 iteration: 68265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12239 FastRCNN class loss: 0.05977 FastRCNN total loss: 0.18216 L1 loss: 0.0000e+00 L2 loss: 0.56644 Learning rate: 0.0004 Mask loss: 0.15186 RPN box loss: 0.00754 RPN score loss: 0.00286 RPN total loss: 0.0104 Total loss: 0.91087 timestamp: 1655061595.1691902 iteration: 68270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12619 FastRCNN class loss: 0.08298 FastRCNN total loss: 0.20917 L1 loss: 0.0000e+00 L2 loss: 0.56644 Learning rate: 0.0004 Mask loss: 0.25348 RPN box loss: 0.01052 RPN score loss: 0.01179 RPN total loss: 0.02231 Total loss: 1.05141 timestamp: 1655061598.4689877 iteration: 68275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09532 FastRCNN class loss: 0.07946 FastRCNN total loss: 0.17478 L1 loss: 0.0000e+00 L2 loss: 0.56644 Learning rate: 0.0004 Mask loss: 0.13888 RPN box loss: 0.00863 RPN score loss: 0.00229 RPN total loss: 0.01092 Total loss: 0.89102 timestamp: 1655061601.740161 iteration: 68280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11744 FastRCNN class loss: 0.06902 FastRCNN total loss: 0.18646 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.14407 RPN box loss: 0.00739 RPN score loss: 0.0029 RPN total loss: 0.01029 Total loss: 0.90725 timestamp: 1655061605.080859 iteration: 68285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10563 FastRCNN class loss: 0.046 FastRCNN total loss: 0.15163 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.1157 RPN box loss: 0.00921 RPN score loss: 0.00211 RPN total loss: 0.01131 Total loss: 0.84507 timestamp: 1655061608.4293168 iteration: 68290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13886 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.22349 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.19997 RPN box loss: 0.02156 RPN score loss: 0.00242 RPN total loss: 0.02398 Total loss: 1.01387 timestamp: 1655061611.7604444 iteration: 68295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06938 FastRCNN class loss: 0.07982 FastRCNN total loss: 0.1492 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.17011 RPN box loss: 0.01324 RPN score loss: 0.00874 RPN total loss: 0.02199 Total loss: 0.90772 timestamp: 1655061615.028455 iteration: 68300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13409 FastRCNN class loss: 0.139 FastRCNN total loss: 0.27309 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.18549 RPN box loss: 0.02454 RPN score loss: 0.00985 RPN total loss: 0.03438 Total loss: 1.05939 timestamp: 1655061618.3450122 iteration: 68305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13981 FastRCNN class loss: 0.06355 FastRCNN total loss: 0.20336 L1 loss: 0.0000e+00 L2 loss: 0.56643 Learning rate: 0.0004 Mask loss: 0.10583 RPN box loss: 0.03969 RPN score loss: 0.0013 RPN total loss: 0.04099 Total loss: 0.9166 timestamp: 1655061621.6475515 iteration: 68310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.10888 FastRCNN total loss: 0.22565 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.21771 RPN box loss: 0.02057 RPN score loss: 0.0225 RPN total loss: 0.04307 Total loss: 1.05285 timestamp: 1655061624.9162736 iteration: 68315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11875 FastRCNN class loss: 0.12462 FastRCNN total loss: 0.24337 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.1494 RPN box loss: 0.01927 RPN score loss: 0.00804 RPN total loss: 0.02731 Total loss: 0.9865 timestamp: 1655061628.209585 iteration: 68320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07998 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.15382 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.13516 RPN box loss: 0.01192 RPN score loss: 0.00499 RPN total loss: 0.0169 Total loss: 0.8723 timestamp: 1655061631.5211563 iteration: 68325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06003 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.11954 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.10013 RPN box loss: 0.00887 RPN score loss: 0.00241 RPN total loss: 0.01128 Total loss: 0.79737 timestamp: 1655061634.7621272 iteration: 68330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08109 FastRCNN class loss: 0.05715 FastRCNN total loss: 0.13824 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.14175 RPN box loss: 0.00534 RPN score loss: 0.00089 RPN total loss: 0.00623 Total loss: 0.85263 timestamp: 1655061637.991795 iteration: 68335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07377 FastRCNN class loss: 0.07156 FastRCNN total loss: 0.14532 L1 loss: 0.0000e+00 L2 loss: 0.56642 Learning rate: 0.0004 Mask loss: 0.14347 RPN box loss: 0.01461 RPN score loss: 0.00351 RPN total loss: 0.01812 Total loss: 0.87333 timestamp: 1655061641.2091544 iteration: 68340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07518 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.14876 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.13971 RPN box loss: 0.01513 RPN score loss: 0.00095 RPN total loss: 0.01608 Total loss: 0.87096 timestamp: 1655061644.4703228 iteration: 68345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07834 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.13481 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.15807 RPN box loss: 0.01202 RPN score loss: 0.00441 RPN total loss: 0.01643 Total loss: 0.87572 timestamp: 1655061647.758317 iteration: 68350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09512 FastRCNN class loss: 0.0719 FastRCNN total loss: 0.16701 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.17366 RPN box loss: 0.0099 RPN score loss: 0.00441 RPN total loss: 0.01431 Total loss: 0.9214 timestamp: 1655061651.0842676 iteration: 68355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11728 FastRCNN class loss: 0.05678 FastRCNN total loss: 0.17406 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.14411 RPN box loss: 0.02675 RPN score loss: 0.00655 RPN total loss: 0.0333 Total loss: 0.91788 timestamp: 1655061654.4638016 iteration: 68360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05457 FastRCNN class loss: 0.06545 FastRCNN total loss: 0.12003 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.13422 RPN box loss: 0.00784 RPN score loss: 0.00134 RPN total loss: 0.00918 Total loss: 0.82983 timestamp: 1655061657.7275212 iteration: 68365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0429 FastRCNN class loss: 0.0425 FastRCNN total loss: 0.08541 L1 loss: 0.0000e+00 L2 loss: 0.56641 Learning rate: 0.0004 Mask loss: 0.13734 RPN box loss: 0.00997 RPN score loss: 0.00079 RPN total loss: 0.01076 Total loss: 0.79991 timestamp: 1655061660.9751446 iteration: 68370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08654 FastRCNN class loss: 0.08301 FastRCNN total loss: 0.16956 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.13891 RPN box loss: 0.01051 RPN score loss: 0.00569 RPN total loss: 0.01621 Total loss: 0.89108 timestamp: 1655061664.2038763 iteration: 68375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10091 FastRCNN class loss: 0.04242 FastRCNN total loss: 0.14333 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.13661 RPN box loss: 0.01048 RPN score loss: 0.00122 RPN total loss: 0.01171 Total loss: 0.85804 timestamp: 1655061667.4541025 iteration: 68380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09904 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.18644 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.15216 RPN box loss: 0.0239 RPN score loss: 0.00969 RPN total loss: 0.03359 Total loss: 0.93859 timestamp: 1655061670.659249 iteration: 68385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15455 FastRCNN class loss: 0.07646 FastRCNN total loss: 0.23101 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.15556 RPN box loss: 0.00687 RPN score loss: 0.00653 RPN total loss: 0.0134 Total loss: 0.96636 timestamp: 1655061673.9003618 iteration: 68390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09834 FastRCNN class loss: 0.078 FastRCNN total loss: 0.17634 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.14826 RPN box loss: 0.01042 RPN score loss: 0.00528 RPN total loss: 0.0157 Total loss: 0.90669 timestamp: 1655061677.172573 iteration: 68395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06945 FastRCNN class loss: 0.04241 FastRCNN total loss: 0.11186 L1 loss: 0.0000e+00 L2 loss: 0.5664 Learning rate: 0.0004 Mask loss: 0.08964 RPN box loss: 0.01979 RPN score loss: 0.00142 RPN total loss: 0.02122 Total loss: 0.78911 timestamp: 1655061680.514157 iteration: 68400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1348 FastRCNN class loss: 0.1092 FastRCNN total loss: 0.244 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.19174 RPN box loss: 0.04865 RPN score loss: 0.01372 RPN total loss: 0.06236 Total loss: 1.0645 timestamp: 1655061683.75083 iteration: 68405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04953 FastRCNN class loss: 0.06085 FastRCNN total loss: 0.11039 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.10142 RPN box loss: 0.00403 RPN score loss: 0.00171 RPN total loss: 0.00574 Total loss: 0.78394 timestamp: 1655061687.0248022 iteration: 68410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12411 FastRCNN class loss: 0.15371 FastRCNN total loss: 0.27782 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.15197 RPN box loss: 0.01029 RPN score loss: 0.01416 RPN total loss: 0.02446 Total loss: 1.02063 timestamp: 1655061690.3564768 iteration: 68415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12965 FastRCNN class loss: 0.10779 FastRCNN total loss: 0.23744 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.1685 RPN box loss: 0.03679 RPN score loss: 0.0046 RPN total loss: 0.04138 Total loss: 1.01372 timestamp: 1655061693.5329368 iteration: 68420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06575 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.14787 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.18194 RPN box loss: 0.02231 RPN score loss: 0.01216 RPN total loss: 0.03446 Total loss: 0.93066 timestamp: 1655061696.8028705 iteration: 68425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07708 FastRCNN class loss: 0.04612 FastRCNN total loss: 0.1232 L1 loss: 0.0000e+00 L2 loss: 0.56639 Learning rate: 0.0004 Mask loss: 0.08054 RPN box loss: 0.02925 RPN score loss: 0.00171 RPN total loss: 0.03095 Total loss: 0.80108 timestamp: 1655061700.0278165 iteration: 68430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14704 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.22929 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.1959 RPN box loss: 0.01912 RPN score loss: 0.00784 RPN total loss: 0.02697 Total loss: 1.01854 timestamp: 1655061703.2862697 iteration: 68435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11463 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.18229 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.17419 RPN box loss: 0.01446 RPN score loss: 0.01345 RPN total loss: 0.02791 Total loss: 0.95078 timestamp: 1655061706.5245225 iteration: 68440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06825 FastRCNN class loss: 0.04743 FastRCNN total loss: 0.11568 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.13119 RPN box loss: 0.01372 RPN score loss: 0.00349 RPN total loss: 0.01721 Total loss: 0.83046 timestamp: 1655061709.8901565 iteration: 68445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09361 FastRCNN class loss: 0.0504 FastRCNN total loss: 0.14401 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.09615 RPN box loss: 0.01487 RPN score loss: 0.00264 RPN total loss: 0.01751 Total loss: 0.82406 timestamp: 1655061713.1736028 iteration: 68450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19572 FastRCNN class loss: 0.08875 FastRCNN total loss: 0.28447 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.16668 RPN box loss: 0.01292 RPN score loss: 0.00324 RPN total loss: 0.01616 Total loss: 1.03369 timestamp: 1655061716.4968724 iteration: 68455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09862 FastRCNN class loss: 0.08334 FastRCNN total loss: 0.18197 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.12525 RPN box loss: 0.02567 RPN score loss: 0.01266 RPN total loss: 0.03833 Total loss: 0.91193 timestamp: 1655061719.7924442 iteration: 68460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08147 FastRCNN class loss: 0.08813 FastRCNN total loss: 0.1696 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.20451 RPN box loss: 0.0246 RPN score loss: 0.00239 RPN total loss: 0.02699 Total loss: 0.96748 timestamp: 1655061723.0960083 iteration: 68465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.05201 FastRCNN total loss: 0.1341 L1 loss: 0.0000e+00 L2 loss: 0.56638 Learning rate: 0.0004 Mask loss: 0.10424 RPN box loss: 0.01338 RPN score loss: 0.00114 RPN total loss: 0.01452 Total loss: 0.81924 timestamp: 1655061726.39064 iteration: 68470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08073 FastRCNN class loss: 0.06665 FastRCNN total loss: 0.14738 L1 loss: 0.0000e+00 L2 loss: 0.56637 Learning rate: 0.0004 Mask loss: 0.19227 RPN box loss: 0.01218 RPN score loss: 0.00537 RPN total loss: 0.01755 Total loss: 0.92357 timestamp: 1655061729.7184796 iteration: 68475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05955 FastRCNN class loss: 0.07013 FastRCNN total loss: 0.12968 L1 loss: 0.0000e+00 L2 loss: 0.56637 Learning rate: 0.0004 Mask loss: 0.11806 RPN box loss: 0.01447 RPN score loss: 0.00266 RPN total loss: 0.01713 Total loss: 0.83125 timestamp: 1655061732.9886863 iteration: 68480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11532 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.19567 L1 loss: 0.0000e+00 L2 loss: 0.56637 Learning rate: 0.0004 Mask loss: 0.19329 RPN box loss: 0.01263 RPN score loss: 0.01574 RPN total loss: 0.02838 Total loss: 0.98371 timestamp: 1655061736.2715147 iteration: 68485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07757 FastRCNN class loss: 0.05751 FastRCNN total loss: 0.13508 L1 loss: 0.0000e+00 L2 loss: 0.56637 Learning rate: 0.0004 Mask loss: 0.13398 RPN box loss: 0.04149 RPN score loss: 0.00659 RPN total loss: 0.04808 Total loss: 0.88351 timestamp: 1655061739.5413601 iteration: 68490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06391 FastRCNN class loss: 0.06133 FastRCNN total loss: 0.12524 L1 loss: 0.0000e+00 L2 loss: 0.56637 Learning rate: 0.0004 Mask loss: 0.09808 RPN box loss: 0.01788 RPN score loss: 0.00255 RPN total loss: 0.02043 Total loss: 0.81012 timestamp: 1655061742.863381 iteration: 68495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07097 FastRCNN class loss: 0.05466 FastRCNN total loss: 0.12563 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.07799 RPN box loss: 0.00447 RPN score loss: 0.00146 RPN total loss: 0.00592 Total loss: 0.7759 timestamp: 1655061746.1936584 iteration: 68500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11534 FastRCNN class loss: 0.07763 FastRCNN total loss: 0.19296 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.20832 RPN box loss: 0.02666 RPN score loss: 0.00168 RPN total loss: 0.02834 Total loss: 0.99598 timestamp: 1655061749.477585 iteration: 68505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06486 FastRCNN class loss: 0.06249 FastRCNN total loss: 0.12735 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.15243 RPN box loss: 0.01148 RPN score loss: 0.00473 RPN total loss: 0.01621 Total loss: 0.86234 timestamp: 1655061752.6631134 iteration: 68510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13273 FastRCNN class loss: 0.09139 FastRCNN total loss: 0.22412 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.20413 RPN box loss: 0.00487 RPN score loss: 0.00467 RPN total loss: 0.00954 Total loss: 1.00415 timestamp: 1655061755.9339666 iteration: 68515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10046 FastRCNN class loss: 0.04662 FastRCNN total loss: 0.14708 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.095 RPN box loss: 0.01114 RPN score loss: 0.00959 RPN total loss: 0.02073 Total loss: 0.82917 timestamp: 1655061759.2118855 iteration: 68520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0771 FastRCNN class loss: 0.048 FastRCNN total loss: 0.1251 L1 loss: 0.0000e+00 L2 loss: 0.56636 Learning rate: 0.0004 Mask loss: 0.12333 RPN box loss: 0.00686 RPN score loss: 0.00201 RPN total loss: 0.00887 Total loss: 0.82365 timestamp: 1655061762.4543667 iteration: 68525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07813 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.1331 L1 loss: 0.0000e+00 L2 loss: 0.56635 Learning rate: 0.0004 Mask loss: 0.08466 RPN box loss: 0.00877 RPN score loss: 0.00085 RPN total loss: 0.00962 Total loss: 0.79373 timestamp: 1655061765.707357 iteration: 68530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09817 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.16854 L1 loss: 0.0000e+00 L2 loss: 0.56635 Learning rate: 0.0004 Mask loss: 0.14064 RPN box loss: 0.00552 RPN score loss: 0.00211 RPN total loss: 0.00763 Total loss: 0.88316 timestamp: 1655061768.9269178 iteration: 68535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09074 FastRCNN class loss: 0.07797 FastRCNN total loss: 0.1687 L1 loss: 0.0000e+00 L2 loss: 0.56635 Learning rate: 0.0004 Mask loss: 0.22724 RPN box loss: 0.01328 RPN score loss: 0.00602 RPN total loss: 0.0193 Total loss: 0.98159 timestamp: 1655061772.227338 iteration: 68540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13106 FastRCNN class loss: 0.0742 FastRCNN total loss: 0.20526 L1 loss: 0.0000e+00 L2 loss: 0.56635 Learning rate: 0.0004 Mask loss: 0.12055 RPN box loss: 0.01901 RPN score loss: 0.00269 RPN total loss: 0.02171 Total loss: 0.91387 timestamp: 1655061775.502111 iteration: 68545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08929 FastRCNN class loss: 0.08601 FastRCNN total loss: 0.17529 L1 loss: 0.0000e+00 L2 loss: 0.56635 Learning rate: 0.0004 Mask loss: 0.13333 RPN box loss: 0.00777 RPN score loss: 0.00366 RPN total loss: 0.01143 Total loss: 0.88639 timestamp: 1655061778.7546253 iteration: 68550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08039 FastRCNN class loss: 0.06805 FastRCNN total loss: 0.14844 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.17134 RPN box loss: 0.00733 RPN score loss: 0.00974 RPN total loss: 0.01707 Total loss: 0.9032 timestamp: 1655061782.1025894 iteration: 68555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12047 FastRCNN class loss: 0.10679 FastRCNN total loss: 0.22726 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.18915 RPN box loss: 0.02411 RPN score loss: 0.01174 RPN total loss: 0.03585 Total loss: 1.0186 timestamp: 1655061785.3522542 iteration: 68560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.07066 FastRCNN total loss: 0.1606 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.18438 RPN box loss: 0.02202 RPN score loss: 0.01155 RPN total loss: 0.03357 Total loss: 0.94489 timestamp: 1655061788.6587079 iteration: 68565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06844 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.13812 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.12671 RPN box loss: 0.01544 RPN score loss: 0.00111 RPN total loss: 0.01656 Total loss: 0.84773 timestamp: 1655061791.9332664 iteration: 68570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0966 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.16217 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.11415 RPN box loss: 0.00778 RPN score loss: 0.00795 RPN total loss: 0.01573 Total loss: 0.85839 timestamp: 1655061795.2010572 iteration: 68575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11134 FastRCNN class loss: 0.08276 FastRCNN total loss: 0.1941 L1 loss: 0.0000e+00 L2 loss: 0.56634 Learning rate: 0.0004 Mask loss: 0.12211 RPN box loss: 0.01401 RPN score loss: 0.00879 RPN total loss: 0.0228 Total loss: 0.90535 timestamp: 1655061798.5026948 iteration: 68580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06778 FastRCNN class loss: 0.06833 FastRCNN total loss: 0.13611 L1 loss: 0.0000e+00 L2 loss: 0.56633 Learning rate: 0.0004 Mask loss: 0.12166 RPN box loss: 0.01138 RPN score loss: 0.0027 RPN total loss: 0.01408 Total loss: 0.83819 timestamp: 1655061801.7907588 iteration: 68585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09328 FastRCNN class loss: 0.07812 FastRCNN total loss: 0.1714 L1 loss: 0.0000e+00 L2 loss: 0.56633 Learning rate: 0.0004 Mask loss: 0.1459 RPN box loss: 0.0333 RPN score loss: 0.01033 RPN total loss: 0.04363 Total loss: 0.92726 timestamp: 1655061804.9754765 iteration: 68590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10841 FastRCNN class loss: 0.10666 FastRCNN total loss: 0.21507 L1 loss: 0.0000e+00 L2 loss: 0.56633 Learning rate: 0.0004 Mask loss: 0.19399 RPN box loss: 0.01171 RPN score loss: 0.00494 RPN total loss: 0.01665 Total loss: 0.99204 timestamp: 1655061808.2857983 iteration: 68595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08964 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.16749 L1 loss: 0.0000e+00 L2 loss: 0.56633 Learning rate: 0.0004 Mask loss: 0.15574 RPN box loss: 0.01481 RPN score loss: 0.00306 RPN total loss: 0.01787 Total loss: 0.90743 timestamp: 1655061811.5163605 iteration: 68600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10809 FastRCNN class loss: 0.12877 FastRCNN total loss: 0.23686 L1 loss: 0.0000e+00 L2 loss: 0.56633 Learning rate: 0.0004 Mask loss: 0.17567 RPN box loss: 0.02914 RPN score loss: 0.00978 RPN total loss: 0.03892 Total loss: 1.01778 timestamp: 1655061814.816305 iteration: 68605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07283 FastRCNN class loss: 0.08381 FastRCNN total loss: 0.15663 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.14685 RPN box loss: 0.00943 RPN score loss: 0.00775 RPN total loss: 0.01719 Total loss: 0.887 timestamp: 1655061818.163532 iteration: 68610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07022 FastRCNN class loss: 0.0474 FastRCNN total loss: 0.11762 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.14903 RPN box loss: 0.00637 RPN score loss: 0.00476 RPN total loss: 0.01112 Total loss: 0.8441 timestamp: 1655061821.4274645 iteration: 68615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08075 FastRCNN class loss: 0.05739 FastRCNN total loss: 0.13814 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.1384 RPN box loss: 0.02307 RPN score loss: 0.00867 RPN total loss: 0.03174 Total loss: 0.8746 timestamp: 1655061824.7090032 iteration: 68620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05122 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.10811 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.09888 RPN box loss: 0.01471 RPN score loss: 0.00859 RPN total loss: 0.0233 Total loss: 0.79661 timestamp: 1655061827.9517388 iteration: 68625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07857 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.13402 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.15901 RPN box loss: 0.00786 RPN score loss: 0.00411 RPN total loss: 0.01196 Total loss: 0.87131 timestamp: 1655061831.1733387 iteration: 68630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06625 FastRCNN class loss: 0.05123 FastRCNN total loss: 0.11748 L1 loss: 0.0000e+00 L2 loss: 0.56632 Learning rate: 0.0004 Mask loss: 0.09612 RPN box loss: 0.01002 RPN score loss: 0.00125 RPN total loss: 0.01127 Total loss: 0.79118 timestamp: 1655061834.4938147 iteration: 68635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12856 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.21945 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.17024 RPN box loss: 0.02615 RPN score loss: 0.01309 RPN total loss: 0.03924 Total loss: 0.99525 timestamp: 1655061837.81674 iteration: 68640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.084 FastRCNN total loss: 0.20077 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.13407 RPN box loss: 0.00795 RPN score loss: 0.00559 RPN total loss: 0.01353 Total loss: 0.91469 timestamp: 1655061841.1327422 iteration: 68645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0649 FastRCNN class loss: 0.05506 FastRCNN total loss: 0.11997 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.12118 RPN box loss: 0.01197 RPN score loss: 0.00819 RPN total loss: 0.02016 Total loss: 0.82762 timestamp: 1655061844.4538581 iteration: 68650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09494 FastRCNN class loss: 0.08011 FastRCNN total loss: 0.17504 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.1304 RPN box loss: 0.01318 RPN score loss: 0.00394 RPN total loss: 0.01713 Total loss: 0.88887 timestamp: 1655061847.786896 iteration: 68655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10361 FastRCNN class loss: 0.08484 FastRCNN total loss: 0.18845 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.16824 RPN box loss: 0.02196 RPN score loss: 0.00387 RPN total loss: 0.02583 Total loss: 0.94884 timestamp: 1655061851.1109009 iteration: 68660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16477 FastRCNN class loss: 0.14287 FastRCNN total loss: 0.30763 L1 loss: 0.0000e+00 L2 loss: 0.56631 Learning rate: 0.0004 Mask loss: 0.19177 RPN box loss: 0.02413 RPN score loss: 0.00889 RPN total loss: 0.03302 Total loss: 1.09873 timestamp: 1655061854.348168 iteration: 68665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05866 FastRCNN class loss: 0.04083 FastRCNN total loss: 0.0995 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.1129 RPN box loss: 0.00671 RPN score loss: 0.00336 RPN total loss: 0.01008 Total loss: 0.78878 timestamp: 1655061857.6923845 iteration: 68670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11032 FastRCNN class loss: 0.10075 FastRCNN total loss: 0.21107 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.19074 RPN box loss: 0.01187 RPN score loss: 0.00433 RPN total loss: 0.0162 Total loss: 0.98431 timestamp: 1655061860.9937558 iteration: 68675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08796 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.14692 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.13385 RPN box loss: 0.00795 RPN score loss: 0.0043 RPN total loss: 0.01225 Total loss: 0.85933 timestamp: 1655061864.2173035 iteration: 68680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07683 FastRCNN class loss: 0.03214 FastRCNN total loss: 0.10897 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.09443 RPN box loss: 0.00978 RPN score loss: 0.00176 RPN total loss: 0.01153 Total loss: 0.78123 timestamp: 1655061867.5189345 iteration: 68685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13244 FastRCNN class loss: 0.10755 FastRCNN total loss: 0.24 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.1488 RPN box loss: 0.01275 RPN score loss: 0.00408 RPN total loss: 0.01683 Total loss: 0.97191 timestamp: 1655061870.7831001 iteration: 68690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05837 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.12385 L1 loss: 0.0000e+00 L2 loss: 0.5663 Learning rate: 0.0004 Mask loss: 0.14149 RPN box loss: 0.00782 RPN score loss: 0.0005 RPN total loss: 0.00832 Total loss: 0.83995 timestamp: 1655061874.0510798 iteration: 68695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0706 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.12234 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.13729 RPN box loss: 0.0079 RPN score loss: 0.00188 RPN total loss: 0.00978 Total loss: 0.83571 timestamp: 1655061877.3554897 iteration: 68700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11 FastRCNN class loss: 0.06783 FastRCNN total loss: 0.17783 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.1603 RPN box loss: 0.00899 RPN score loss: 0.00494 RPN total loss: 0.01393 Total loss: 0.91835 timestamp: 1655061880.6606352 iteration: 68705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.07368 FastRCNN total loss: 0.17992 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.12443 RPN box loss: 0.01113 RPN score loss: 0.01036 RPN total loss: 0.02149 Total loss: 0.89214 timestamp: 1655061883.961343 iteration: 68710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11757 FastRCNN class loss: 0.04623 FastRCNN total loss: 0.1638 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.12406 RPN box loss: 0.00196 RPN score loss: 0.00146 RPN total loss: 0.00342 Total loss: 0.85757 timestamp: 1655061887.14308 iteration: 68715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.19412 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.15582 RPN box loss: 0.01935 RPN score loss: 0.01264 RPN total loss: 0.03199 Total loss: 0.94822 timestamp: 1655061890.3655448 iteration: 68720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.08878 FastRCNN total loss: 0.2341 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.16204 RPN box loss: 0.01323 RPN score loss: 0.00368 RPN total loss: 0.01692 Total loss: 0.97934 timestamp: 1655061893.6486115 iteration: 68725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04802 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.09518 L1 loss: 0.0000e+00 L2 loss: 0.56629 Learning rate: 0.0004 Mask loss: 0.08923 RPN box loss: 0.0063 RPN score loss: 0.00117 RPN total loss: 0.00747 Total loss: 0.75816 timestamp: 1655061896.9314134 iteration: 68730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17565 FastRCNN class loss: 0.09671 FastRCNN total loss: 0.27237 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.13109 RPN box loss: 0.02937 RPN score loss: 0.00902 RPN total loss: 0.03839 Total loss: 1.00813 timestamp: 1655061900.219719 iteration: 68735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09063 FastRCNN class loss: 0.09652 FastRCNN total loss: 0.18715 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.19174 RPN box loss: 0.01752 RPN score loss: 0.01094 RPN total loss: 0.02847 Total loss: 0.97364 timestamp: 1655061903.4892094 iteration: 68740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14991 FastRCNN class loss: 0.09118 FastRCNN total loss: 0.24109 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.18973 RPN box loss: 0.02941 RPN score loss: 0.00659 RPN total loss: 0.036 Total loss: 1.03309 timestamp: 1655061906.7881484 iteration: 68745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06538 FastRCNN class loss: 0.04466 FastRCNN total loss: 0.11004 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.11988 RPN box loss: 0.00423 RPN score loss: 0.0037 RPN total loss: 0.00793 Total loss: 0.80413 timestamp: 1655061910.1150937 iteration: 68750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04848 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.11424 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.15588 RPN box loss: 0.00755 RPN score loss: 0.0105 RPN total loss: 0.01805 Total loss: 0.85445 timestamp: 1655061913.3943367 iteration: 68755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09876 FastRCNN class loss: 0.08027 FastRCNN total loss: 0.17903 L1 loss: 0.0000e+00 L2 loss: 0.56628 Learning rate: 0.0004 Mask loss: 0.11566 RPN box loss: 0.00999 RPN score loss: 0.00238 RPN total loss: 0.01237 Total loss: 0.87334 timestamp: 1655061916.661607 iteration: 68760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08629 FastRCNN class loss: 0.0418 FastRCNN total loss: 0.12809 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.13853 RPN box loss: 0.00607 RPN score loss: 0.00285 RPN total loss: 0.00893 Total loss: 0.84182 timestamp: 1655061919.9640727 iteration: 68765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1117 FastRCNN class loss: 0.11006 FastRCNN total loss: 0.22176 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.16839 RPN box loss: 0.01662 RPN score loss: 0.00939 RPN total loss: 0.02602 Total loss: 0.98244 timestamp: 1655061923.2608461 iteration: 68770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06231 FastRCNN class loss: 0.0578 FastRCNN total loss: 0.12011 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.1114 RPN box loss: 0.01211 RPN score loss: 0.0032 RPN total loss: 0.01531 Total loss: 0.81309 timestamp: 1655061926.4709074 iteration: 68775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13539 FastRCNN class loss: 0.11521 FastRCNN total loss: 0.25061 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.18106 RPN box loss: 0.0278 RPN score loss: 0.00985 RPN total loss: 0.03765 Total loss: 1.03559 timestamp: 1655061929.6841848 iteration: 68780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08259 FastRCNN class loss: 0.06718 FastRCNN total loss: 0.14977 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.103 RPN box loss: 0.00366 RPN score loss: 0.0034 RPN total loss: 0.00707 Total loss: 0.8261 timestamp: 1655061932.926019 iteration: 68785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07255 FastRCNN class loss: 0.05507 FastRCNN total loss: 0.12762 L1 loss: 0.0000e+00 L2 loss: 0.56627 Learning rate: 0.0004 Mask loss: 0.08863 RPN box loss: 0.01833 RPN score loss: 0.0076 RPN total loss: 0.02593 Total loss: 0.80845 timestamp: 1655061936.195755 iteration: 68790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0973 FastRCNN class loss: 0.09215 FastRCNN total loss: 0.18945 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.17602 RPN box loss: 0.01807 RPN score loss: 0.00673 RPN total loss: 0.0248 Total loss: 0.95653 timestamp: 1655061939.4967513 iteration: 68795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09641 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.15636 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.14398 RPN box loss: 0.05158 RPN score loss: 0.00798 RPN total loss: 0.05956 Total loss: 0.92616 timestamp: 1655061942.734466 iteration: 68800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0807 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.12921 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.11179 RPN box loss: 0.00913 RPN score loss: 0.00503 RPN total loss: 0.01417 Total loss: 0.82142 timestamp: 1655061946.0599282 iteration: 68805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12051 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.19374 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.15995 RPN box loss: 0.01212 RPN score loss: 0.00321 RPN total loss: 0.01534 Total loss: 0.93528 timestamp: 1655061949.326264 iteration: 68810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04007 FastRCNN class loss: 0.04047 FastRCNN total loss: 0.08055 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.18075 RPN box loss: 0.00703 RPN score loss: 0.00163 RPN total loss: 0.00867 Total loss: 0.83622 timestamp: 1655061952.6357174 iteration: 68815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09587 FastRCNN class loss: 0.06802 FastRCNN total loss: 0.16389 L1 loss: 0.0000e+00 L2 loss: 0.56626 Learning rate: 0.0004 Mask loss: 0.18241 RPN box loss: 0.01606 RPN score loss: 0.01205 RPN total loss: 0.02811 Total loss: 0.94067 timestamp: 1655061955.8399441 iteration: 68820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08904 FastRCNN class loss: 0.10942 FastRCNN total loss: 0.19846 L1 loss: 0.0000e+00 L2 loss: 0.56625 Learning rate: 0.0004 Mask loss: 0.21078 RPN box loss: 0.01684 RPN score loss: 0.04005 RPN total loss: 0.05689 Total loss: 1.03238 timestamp: 1655061959.0451615 iteration: 68825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09326 FastRCNN class loss: 0.08889 FastRCNN total loss: 0.18215 L1 loss: 0.0000e+00 L2 loss: 0.56625 Learning rate: 0.0004 Mask loss: 0.15144 RPN box loss: 0.00373 RPN score loss: 0.00212 RPN total loss: 0.00585 Total loss: 0.90569 timestamp: 1655061962.3599026 iteration: 68830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08186 FastRCNN class loss: 0.04205 FastRCNN total loss: 0.12391 L1 loss: 0.0000e+00 L2 loss: 0.56625 Learning rate: 0.0004 Mask loss: 0.14701 RPN box loss: 0.00952 RPN score loss: 0.00287 RPN total loss: 0.01239 Total loss: 0.84956 timestamp: 1655061965.6343231 iteration: 68835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07147 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.13441 L1 loss: 0.0000e+00 L2 loss: 0.56625 Learning rate: 0.0004 Mask loss: 0.13753 RPN box loss: 0.02558 RPN score loss: 0.00379 RPN total loss: 0.02937 Total loss: 0.86756 timestamp: 1655061968.9074135 iteration: 68840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12293 FastRCNN class loss: 0.05711 FastRCNN total loss: 0.18004 L1 loss: 0.0000e+00 L2 loss: 0.56625 Learning rate: 0.0004 Mask loss: 0.14126 RPN box loss: 0.01389 RPN score loss: 0.00667 RPN total loss: 0.02055 Total loss: 0.9081 timestamp: 1655061972.2253368 iteration: 68845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06693 FastRCNN class loss: 0.06962 FastRCNN total loss: 0.13655 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.17554 RPN box loss: 0.01507 RPN score loss: 0.00404 RPN total loss: 0.01911 Total loss: 0.89744 timestamp: 1655061975.5172384 iteration: 68850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12827 FastRCNN class loss: 0.04962 FastRCNN total loss: 0.17789 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.09472 RPN box loss: 0.0483 RPN score loss: 0.00182 RPN total loss: 0.05012 Total loss: 0.88898 timestamp: 1655061978.7396176 iteration: 68855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.10247 FastRCNN total loss: 0.24526 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.15093 RPN box loss: 0.01212 RPN score loss: 0.00841 RPN total loss: 0.02053 Total loss: 0.98296 timestamp: 1655061982.0060947 iteration: 68860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10052 FastRCNN class loss: 0.06011 FastRCNN total loss: 0.16063 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.15573 RPN box loss: 0.00579 RPN score loss: 0.00269 RPN total loss: 0.00848 Total loss: 0.89108 timestamp: 1655061985.302869 iteration: 68865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09453 FastRCNN class loss: 0.03971 FastRCNN total loss: 0.13423 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.01954 RPN score loss: 0.00471 RPN total loss: 0.02425 Total loss: 0.86947 timestamp: 1655061988.6174662 iteration: 68870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09655 FastRCNN class loss: 0.10746 FastRCNN total loss: 0.20401 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.18102 RPN box loss: 0.02234 RPN score loss: 0.00476 RPN total loss: 0.0271 Total loss: 0.97836 timestamp: 1655061991.850983 iteration: 68875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06863 FastRCNN class loss: 0.04689 FastRCNN total loss: 0.11552 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.10583 RPN box loss: 0.01383 RPN score loss: 0.0012 RPN total loss: 0.01503 Total loss: 0.80261 timestamp: 1655061995.1192694 iteration: 68880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09441 FastRCNN class loss: 0.11021 FastRCNN total loss: 0.20462 L1 loss: 0.0000e+00 L2 loss: 0.56624 Learning rate: 0.0004 Mask loss: 0.1682 RPN box loss: 0.02381 RPN score loss: 0.01796 RPN total loss: 0.04177 Total loss: 0.98083 timestamp: 1655061998.377724 iteration: 68885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06939 FastRCNN class loss: 0.05137 FastRCNN total loss: 0.12076 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.11133 RPN box loss: 0.01135 RPN score loss: 0.00305 RPN total loss: 0.0144 Total loss: 0.81273 timestamp: 1655062001.6419024 iteration: 68890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11364 FastRCNN class loss: 0.08356 FastRCNN total loss: 0.19721 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.16899 RPN box loss: 0.02686 RPN score loss: 0.00408 RPN total loss: 0.03094 Total loss: 0.96337 timestamp: 1655062004.877907 iteration: 68895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11566 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.1796 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.15318 RPN box loss: 0.01614 RPN score loss: 0.00645 RPN total loss: 0.02259 Total loss: 0.92159 timestamp: 1655062008.1857896 iteration: 68900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03888 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.09024 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.09906 RPN box loss: 0.0066 RPN score loss: 0.00235 RPN total loss: 0.00895 Total loss: 0.76448 timestamp: 1655062011.4391215 iteration: 68905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09357 FastRCNN class loss: 0.09673 FastRCNN total loss: 0.1903 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.1507 RPN box loss: 0.00947 RPN score loss: 0.00994 RPN total loss: 0.01941 Total loss: 0.92664 timestamp: 1655062014.6660547 iteration: 68910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12144 FastRCNN class loss: 0.11891 FastRCNN total loss: 0.24035 L1 loss: 0.0000e+00 L2 loss: 0.56623 Learning rate: 0.0004 Mask loss: 0.18378 RPN box loss: 0.03936 RPN score loss: 0.02033 RPN total loss: 0.05969 Total loss: 1.05005 timestamp: 1655062017.8599033 iteration: 68915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15503 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.22716 L1 loss: 0.0000e+00 L2 loss: 0.56622 Learning rate: 0.0004 Mask loss: 0.16086 RPN box loss: 0.01153 RPN score loss: 0.00794 RPN total loss: 0.01947 Total loss: 0.97372 timestamp: 1655062021.1337895 iteration: 68920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09792 FastRCNN class loss: 0.10614 FastRCNN total loss: 0.20407 L1 loss: 0.0000e+00 L2 loss: 0.56622 Learning rate: 0.0004 Mask loss: 0.13699 RPN box loss: 0.02067 RPN score loss: 0.00296 RPN total loss: 0.02363 Total loss: 0.93091 timestamp: 1655062024.3659081 iteration: 68925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04791 FastRCNN class loss: 0.04004 FastRCNN total loss: 0.08795 L1 loss: 0.0000e+00 L2 loss: 0.56622 Learning rate: 0.0004 Mask loss: 0.10356 RPN box loss: 0.0025 RPN score loss: 0.00332 RPN total loss: 0.00582 Total loss: 0.76355 timestamp: 1655062027.6247923 iteration: 68930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0918 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.56622 Learning rate: 0.0004 Mask loss: 0.10383 RPN box loss: 0.01252 RPN score loss: 0.00368 RPN total loss: 0.0162 Total loss: 0.85291 timestamp: 1655062030.8366542 iteration: 68935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13056 FastRCNN class loss: 0.12569 FastRCNN total loss: 0.25626 L1 loss: 0.0000e+00 L2 loss: 0.56622 Learning rate: 0.0004 Mask loss: 0.22296 RPN box loss: 0.01461 RPN score loss: 0.01672 RPN total loss: 0.03133 Total loss: 1.07676 timestamp: 1655062034.057711 iteration: 68940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07818 FastRCNN class loss: 0.10954 FastRCNN total loss: 0.18772 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.14259 RPN box loss: 0.0178 RPN score loss: 0.00441 RPN total loss: 0.02221 Total loss: 0.91873 timestamp: 1655062037.350067 iteration: 68945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15386 FastRCNN class loss: 0.08472 FastRCNN total loss: 0.23857 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.29044 RPN box loss: 0.01108 RPN score loss: 0.00467 RPN total loss: 0.01575 Total loss: 1.11098 timestamp: 1655062040.6239095 iteration: 68950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08716 FastRCNN class loss: 0.08682 FastRCNN total loss: 0.17398 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.13293 RPN box loss: 0.00941 RPN score loss: 0.00506 RPN total loss: 0.01447 Total loss: 0.88759 timestamp: 1655062043.8684335 iteration: 68955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10531 FastRCNN class loss: 0.0755 FastRCNN total loss: 0.18081 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.13981 RPN box loss: 0.00618 RPN score loss: 0.00594 RPN total loss: 0.01213 Total loss: 0.89896 timestamp: 1655062047.160039 iteration: 68960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14479 FastRCNN class loss: 0.10712 FastRCNN total loss: 0.25191 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.15978 RPN box loss: 0.01019 RPN score loss: 0.00194 RPN total loss: 0.01214 Total loss: 0.99004 timestamp: 1655062050.4108071 iteration: 68965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11763 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.17233 L1 loss: 0.0000e+00 L2 loss: 0.56621 Learning rate: 0.0004 Mask loss: 0.15676 RPN box loss: 0.01916 RPN score loss: 0.00351 RPN total loss: 0.02267 Total loss: 0.91796 timestamp: 1655062053.711736 iteration: 68970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10019 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.17069 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.1413 RPN box loss: 0.01563 RPN score loss: 0.00086 RPN total loss: 0.01649 Total loss: 0.89469 timestamp: 1655062057.0094886 iteration: 68975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.12934 FastRCNN total loss: 0.24391 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.14001 RPN box loss: 0.01105 RPN score loss: 0.00482 RPN total loss: 0.01587 Total loss: 0.96599 timestamp: 1655062060.301658 iteration: 68980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08551 FastRCNN class loss: 0.04384 FastRCNN total loss: 0.12936 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.09924 RPN box loss: 0.00805 RPN score loss: 0.0045 RPN total loss: 0.01255 Total loss: 0.80735 timestamp: 1655062063.6379232 iteration: 68985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08644 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.13699 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.10278 RPN box loss: 0.01896 RPN score loss: 0.00129 RPN total loss: 0.02026 Total loss: 0.82623 timestamp: 1655062066.8872495 iteration: 68990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09216 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.16518 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.11837 RPN box loss: 0.01517 RPN score loss: 0.00809 RPN total loss: 0.02326 Total loss: 0.87301 timestamp: 1655062070.1929808 iteration: 68995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05433 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.114 L1 loss: 0.0000e+00 L2 loss: 0.5662 Learning rate: 0.0004 Mask loss: 0.1212 RPN box loss: 0.02227 RPN score loss: 0.00983 RPN total loss: 0.0321 Total loss: 0.8335 timestamp: 1655062073.3751435 iteration: 69000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09663 FastRCNN class loss: 0.03234 FastRCNN total loss: 0.12898 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.11429 RPN box loss: 0.02455 RPN score loss: 0.00129 RPN total loss: 0.02584 Total loss: 0.8353 timestamp: 1655062076.6232352 iteration: 69005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16841 FastRCNN class loss: 0.08723 FastRCNN total loss: 0.25564 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.15993 RPN box loss: 0.0094 RPN score loss: 0.00495 RPN total loss: 0.01435 Total loss: 0.99611 timestamp: 1655062079.8810787 iteration: 69010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13139 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.21241 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.11598 RPN box loss: 0.01167 RPN score loss: 0.00275 RPN total loss: 0.01442 Total loss: 0.909 timestamp: 1655062083.1531863 iteration: 69015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.07979 FastRCNN total loss: 0.1644 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.17786 RPN box loss: 0.01289 RPN score loss: 0.00521 RPN total loss: 0.01809 Total loss: 0.92654 timestamp: 1655062086.4388633 iteration: 69020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07605 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.12585 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.14361 RPN box loss: 0.01671 RPN score loss: 0.00326 RPN total loss: 0.01997 Total loss: 0.85561 timestamp: 1655062089.6500833 iteration: 69025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06735 FastRCNN class loss: 0.07783 FastRCNN total loss: 0.14518 L1 loss: 0.0000e+00 L2 loss: 0.56619 Learning rate: 0.0004 Mask loss: 0.13067 RPN box loss: 0.01416 RPN score loss: 0.00796 RPN total loss: 0.02212 Total loss: 0.86416 timestamp: 1655062092.881752 iteration: 69030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05839 FastRCNN class loss: 0.04267 FastRCNN total loss: 0.10106 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.1146 RPN box loss: 0.01079 RPN score loss: 0.00254 RPN total loss: 0.01332 Total loss: 0.79517 timestamp: 1655062096.172895 iteration: 69035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.143 FastRCNN class loss: 0.13111 FastRCNN total loss: 0.27411 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.22496 RPN box loss: 0.01914 RPN score loss: 0.0072 RPN total loss: 0.02634 Total loss: 1.0916 timestamp: 1655062099.4559817 iteration: 69040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15525 FastRCNN class loss: 0.15016 FastRCNN total loss: 0.30541 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.19374 RPN box loss: 0.01478 RPN score loss: 0.00729 RPN total loss: 0.02207 Total loss: 1.0874 timestamp: 1655062102.739347 iteration: 69045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13997 FastRCNN class loss: 0.07925 FastRCNN total loss: 0.21922 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.16367 RPN box loss: 0.02156 RPN score loss: 0.00841 RPN total loss: 0.02997 Total loss: 0.97904 timestamp: 1655062105.9725683 iteration: 69050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10509 FastRCNN class loss: 0.08429 FastRCNN total loss: 0.18938 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.18746 RPN box loss: 0.02097 RPN score loss: 0.00604 RPN total loss: 0.02701 Total loss: 0.97003 timestamp: 1655062109.3046458 iteration: 69055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06347 FastRCNN class loss: 0.06708 FastRCNN total loss: 0.13055 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.13858 RPN box loss: 0.00711 RPN score loss: 0.00133 RPN total loss: 0.00844 Total loss: 0.84374 timestamp: 1655062112.5942047 iteration: 69060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16027 FastRCNN class loss: 0.10906 FastRCNN total loss: 0.26933 L1 loss: 0.0000e+00 L2 loss: 0.56618 Learning rate: 0.0004 Mask loss: 0.12158 RPN box loss: 0.00907 RPN score loss: 0.00382 RPN total loss: 0.01289 Total loss: 0.96997 timestamp: 1655062115.881062 iteration: 69065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09841 FastRCNN class loss: 0.05385 FastRCNN total loss: 0.15226 L1 loss: 0.0000e+00 L2 loss: 0.56617 Learning rate: 0.0004 Mask loss: 0.11889 RPN box loss: 0.01938 RPN score loss: 0.0027 RPN total loss: 0.02208 Total loss: 0.85941 timestamp: 1655062119.0906994 iteration: 69070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06529 FastRCNN class loss: 0.06304 FastRCNN total loss: 0.12833 L1 loss: 0.0000e+00 L2 loss: 0.56617 Learning rate: 0.0004 Mask loss: 0.10811 RPN box loss: 0.01645 RPN score loss: 0.00244 RPN total loss: 0.01889 Total loss: 0.8215 timestamp: 1655062122.4087172 iteration: 69075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12559 FastRCNN class loss: 0.09138 FastRCNN total loss: 0.21697 L1 loss: 0.0000e+00 L2 loss: 0.56617 Learning rate: 0.0004 Mask loss: 0.15177 RPN box loss: 0.01156 RPN score loss: 0.00316 RPN total loss: 0.01472 Total loss: 0.94963 timestamp: 1655062125.6962612 iteration: 69080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06957 FastRCNN class loss: 0.04678 FastRCNN total loss: 0.11635 L1 loss: 0.0000e+00 L2 loss: 0.56617 Learning rate: 0.0004 Mask loss: 0.10411 RPN box loss: 0.00677 RPN score loss: 0.0092 RPN total loss: 0.01596 Total loss: 0.80259 timestamp: 1655062128.9720242 iteration: 69085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12912 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.17496 L1 loss: 0.0000e+00 L2 loss: 0.56617 Learning rate: 0.0004 Mask loss: 0.15016 RPN box loss: 0.08449 RPN score loss: 0.00616 RPN total loss: 0.09065 Total loss: 0.98193 timestamp: 1655062132.2190595 iteration: 69090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04557 FastRCNN class loss: 0.03471 FastRCNN total loss: 0.08028 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.12848 RPN box loss: 0.0153 RPN score loss: 0.00085 RPN total loss: 0.01615 Total loss: 0.79107 timestamp: 1655062135.4313867 iteration: 69095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09485 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.17219 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.08567 RPN box loss: 0.00912 RPN score loss: 0.00179 RPN total loss: 0.01091 Total loss: 0.83494 timestamp: 1655062138.7107863 iteration: 69100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04781 FastRCNN class loss: 0.06045 FastRCNN total loss: 0.10826 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.09142 RPN box loss: 0.00647 RPN score loss: 0.00232 RPN total loss: 0.00879 Total loss: 0.77464 timestamp: 1655062142.002259 iteration: 69105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11736 FastRCNN class loss: 0.08044 FastRCNN total loss: 0.1978 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.15078 RPN box loss: 0.04558 RPN score loss: 0.00624 RPN total loss: 0.05182 Total loss: 0.96656 timestamp: 1655062145.2443087 iteration: 69110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07481 FastRCNN class loss: 0.11978 FastRCNN total loss: 0.19458 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.14955 RPN box loss: 0.03109 RPN score loss: 0.00868 RPN total loss: 0.03977 Total loss: 0.95006 timestamp: 1655062148.530541 iteration: 69115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10151 FastRCNN class loss: 0.07866 FastRCNN total loss: 0.18017 L1 loss: 0.0000e+00 L2 loss: 0.56616 Learning rate: 0.0004 Mask loss: 0.12868 RPN box loss: 0.01516 RPN score loss: 0.00682 RPN total loss: 0.02198 Total loss: 0.89699 timestamp: 1655062151.7862008 iteration: 69120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0728 FastRCNN class loss: 0.05286 FastRCNN total loss: 0.12565 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.12084 RPN box loss: 0.0068 RPN score loss: 0.00588 RPN total loss: 0.01268 Total loss: 0.82533 timestamp: 1655062155.0460966 iteration: 69125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09347 FastRCNN class loss: 0.04639 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.11657 RPN box loss: 0.00976 RPN score loss: 0.00316 RPN total loss: 0.01291 Total loss: 0.8355 timestamp: 1655062158.3545794 iteration: 69130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09358 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.17821 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.18789 RPN box loss: 0.0063 RPN score loss: 0.00964 RPN total loss: 0.01593 Total loss: 0.94819 timestamp: 1655062161.60348 iteration: 69135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08639 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.15398 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.13892 RPN box loss: 0.01626 RPN score loss: 0.00387 RPN total loss: 0.02013 Total loss: 0.87918 timestamp: 1655062164.8980365 iteration: 69140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13318 FastRCNN class loss: 0.07214 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.11305 RPN box loss: 0.01312 RPN score loss: 0.00461 RPN total loss: 0.01773 Total loss: 0.90224 timestamp: 1655062168.161355 iteration: 69145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07459 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.14106 L1 loss: 0.0000e+00 L2 loss: 0.56615 Learning rate: 0.0004 Mask loss: 0.1997 RPN box loss: 0.04653 RPN score loss: 0.00661 RPN total loss: 0.05314 Total loss: 0.96004 timestamp: 1655062171.470182 iteration: 69150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09963 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.15677 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.20191 RPN box loss: 0.00751 RPN score loss: 0.00711 RPN total loss: 0.01462 Total loss: 0.93945 timestamp: 1655062174.7351472 iteration: 69155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.16472 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.14387 RPN box loss: 0.00673 RPN score loss: 0.00548 RPN total loss: 0.01221 Total loss: 0.88695 timestamp: 1655062178.0442357 iteration: 69160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06708 FastRCNN class loss: 0.06998 FastRCNN total loss: 0.13705 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.15147 RPN box loss: 0.00665 RPN score loss: 0.001 RPN total loss: 0.00765 Total loss: 0.86231 timestamp: 1655062181.3213391 iteration: 69165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12199 FastRCNN class loss: 0.07465 FastRCNN total loss: 0.19665 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.14272 RPN box loss: 0.01604 RPN score loss: 0.01064 RPN total loss: 0.02668 Total loss: 0.93219 timestamp: 1655062184.570165 iteration: 69170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0749 FastRCNN class loss: 0.05073 FastRCNN total loss: 0.12563 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.07144 RPN box loss: 0.007 RPN score loss: 0.00117 RPN total loss: 0.00817 Total loss: 0.77138 timestamp: 1655062187.82112 iteration: 69175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.04576 FastRCNN total loss: 0.13947 L1 loss: 0.0000e+00 L2 loss: 0.56614 Learning rate: 0.0004 Mask loss: 0.09063 RPN box loss: 0.00766 RPN score loss: 0.00827 RPN total loss: 0.01593 Total loss: 0.81216 timestamp: 1655062191.0688624 iteration: 69180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07276 FastRCNN class loss: 0.07648 FastRCNN total loss: 0.14924 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.09746 RPN box loss: 0.00822 RPN score loss: 0.00273 RPN total loss: 0.01095 Total loss: 0.82379 timestamp: 1655062194.3504665 iteration: 69185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12896 FastRCNN class loss: 0.07369 FastRCNN total loss: 0.20265 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.17602 RPN box loss: 0.02366 RPN score loss: 0.01275 RPN total loss: 0.03642 Total loss: 0.98122 timestamp: 1655062197.5578945 iteration: 69190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06554 FastRCNN class loss: 0.0697 FastRCNN total loss: 0.13524 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.15602 RPN box loss: 0.00575 RPN score loss: 0.00373 RPN total loss: 0.00948 Total loss: 0.86687 timestamp: 1655062200.7928078 iteration: 69195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07766 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.13639 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.13921 RPN box loss: 0.01527 RPN score loss: 0.00412 RPN total loss: 0.0194 Total loss: 0.86113 timestamp: 1655062204.111568 iteration: 69200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12772 FastRCNN class loss: 0.15801 FastRCNN total loss: 0.28573 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.11402 RPN box loss: 0.01669 RPN score loss: 0.00577 RPN total loss: 0.02245 Total loss: 0.98833 timestamp: 1655062207.4472585 iteration: 69205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10562 FastRCNN class loss: 0.06488 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.13296 RPN box loss: 0.02805 RPN score loss: 0.00362 RPN total loss: 0.03166 Total loss: 0.90125 timestamp: 1655062210.7616913 iteration: 69210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07391 FastRCNN class loss: 0.04032 FastRCNN total loss: 0.11422 L1 loss: 0.0000e+00 L2 loss: 0.56613 Learning rate: 0.0004 Mask loss: 0.07726 RPN box loss: 0.01134 RPN score loss: 0.00664 RPN total loss: 0.01797 Total loss: 0.77558 timestamp: 1655062214.0114357 iteration: 69215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09506 FastRCNN class loss: 0.07236 FastRCNN total loss: 0.16743 L1 loss: 0.0000e+00 L2 loss: 0.56612 Learning rate: 0.0004 Mask loss: 0.10308 RPN box loss: 0.00755 RPN score loss: 0.00184 RPN total loss: 0.00939 Total loss: 0.84602 timestamp: 1655062217.2704434 iteration: 69220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12156 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.18248 L1 loss: 0.0000e+00 L2 loss: 0.56612 Learning rate: 0.0004 Mask loss: 0.13154 RPN box loss: 0.0159 RPN score loss: 0.00214 RPN total loss: 0.01804 Total loss: 0.89817 timestamp: 1655062220.5542593 iteration: 69225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07835 FastRCNN class loss: 0.0622 FastRCNN total loss: 0.14055 L1 loss: 0.0000e+00 L2 loss: 0.56612 Learning rate: 0.0004 Mask loss: 0.14099 RPN box loss: 0.00923 RPN score loss: 0.001 RPN total loss: 0.01023 Total loss: 0.85789 timestamp: 1655062223.7946942 iteration: 69230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08773 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.14938 L1 loss: 0.0000e+00 L2 loss: 0.56612 Learning rate: 0.0004 Mask loss: 0.111 RPN box loss: 0.01286 RPN score loss: 0.00732 RPN total loss: 0.02018 Total loss: 0.84668 timestamp: 1655062227.0076077 iteration: 69235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08071 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.12523 L1 loss: 0.0000e+00 L2 loss: 0.56612 Learning rate: 0.0004 Mask loss: 0.12369 RPN box loss: 0.00558 RPN score loss: 0.00248 RPN total loss: 0.00806 Total loss: 0.8231 timestamp: 1655062230.2900996 iteration: 69240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.13924 FastRCNN total loss: 0.26657 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.22724 RPN box loss: 0.02166 RPN score loss: 0.04496 RPN total loss: 0.06662 Total loss: 1.12655 timestamp: 1655062233.498751 iteration: 69245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12965 FastRCNN class loss: 0.08271 FastRCNN total loss: 0.21236 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.15297 RPN box loss: 0.02113 RPN score loss: 0.0063 RPN total loss: 0.02742 Total loss: 0.95886 timestamp: 1655062236.7796044 iteration: 69250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09782 FastRCNN class loss: 0.10114 FastRCNN total loss: 0.19896 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.13475 RPN box loss: 0.02785 RPN score loss: 0.01334 RPN total loss: 0.04119 Total loss: 0.94101 timestamp: 1655062240.044648 iteration: 69255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06707 FastRCNN class loss: 0.0476 FastRCNN total loss: 0.11467 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.16667 RPN box loss: 0.00676 RPN score loss: 0.00769 RPN total loss: 0.01446 Total loss: 0.86191 timestamp: 1655062243.3113317 iteration: 69260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13896 FastRCNN class loss: 0.10568 FastRCNN total loss: 0.24464 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.18102 RPN box loss: 0.00902 RPN score loss: 0.0063 RPN total loss: 0.01532 Total loss: 1.00709 timestamp: 1655062246.556577 iteration: 69265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10534 FastRCNN class loss: 0.07112 FastRCNN total loss: 0.17646 L1 loss: 0.0000e+00 L2 loss: 0.56611 Learning rate: 0.0004 Mask loss: 0.17839 RPN box loss: 0.01725 RPN score loss: 0.01447 RPN total loss: 0.03172 Total loss: 0.95268 timestamp: 1655062249.852805 iteration: 69270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.07589 FastRCNN total loss: 0.15053 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.14529 RPN box loss: 0.02228 RPN score loss: 0.00241 RPN total loss: 0.0247 Total loss: 0.88662 timestamp: 1655062253.1778424 iteration: 69275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07563 FastRCNN class loss: 0.06545 FastRCNN total loss: 0.14108 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.09286 RPN box loss: 0.01307 RPN score loss: 0.00267 RPN total loss: 0.01574 Total loss: 0.81578 timestamp: 1655062256.462692 iteration: 69280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.05418 FastRCNN total loss: 0.13815 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.10858 RPN box loss: 0.02622 RPN score loss: 0.00167 RPN total loss: 0.02789 Total loss: 0.84072 timestamp: 1655062259.6338918 iteration: 69285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13824 FastRCNN class loss: 0.07908 FastRCNN total loss: 0.21732 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.13485 RPN box loss: 0.00919 RPN score loss: 0.00661 RPN total loss: 0.0158 Total loss: 0.93407 timestamp: 1655062262.904886 iteration: 69290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10255 FastRCNN class loss: 0.07023 FastRCNN total loss: 0.17278 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.11695 RPN box loss: 0.00382 RPN score loss: 0.00343 RPN total loss: 0.00724 Total loss: 0.86307 timestamp: 1655062266.2062712 iteration: 69295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06392 FastRCNN class loss: 0.04736 FastRCNN total loss: 0.11128 L1 loss: 0.0000e+00 L2 loss: 0.5661 Learning rate: 0.0004 Mask loss: 0.10887 RPN box loss: 0.0081 RPN score loss: 0.0058 RPN total loss: 0.01391 Total loss: 0.80016 timestamp: 1655062269.5017858 iteration: 69300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07319 FastRCNN class loss: 0.11266 FastRCNN total loss: 0.18585 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.13918 RPN box loss: 0.02323 RPN score loss: 0.00663 RPN total loss: 0.02986 Total loss: 0.92098 timestamp: 1655062272.7271798 iteration: 69305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07718 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.15079 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.12919 RPN box loss: 0.00573 RPN score loss: 0.00219 RPN total loss: 0.00792 Total loss: 0.85399 timestamp: 1655062275.9919972 iteration: 69310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06423 FastRCNN class loss: 0.04434 FastRCNN total loss: 0.10858 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.11111 RPN box loss: 0.04861 RPN score loss: 0.00504 RPN total loss: 0.05365 Total loss: 0.83943 timestamp: 1655062279.2693012 iteration: 69315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.10891 FastRCNN total loss: 0.24302 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.17382 RPN box loss: 0.01476 RPN score loss: 0.01045 RPN total loss: 0.02521 Total loss: 1.00814 timestamp: 1655062282.531165 iteration: 69320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.16721 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.13933 RPN box loss: 0.0029 RPN score loss: 0.00277 RPN total loss: 0.00567 Total loss: 0.87831 timestamp: 1655062285.8761218 iteration: 69325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05993 FastRCNN class loss: 0.06833 FastRCNN total loss: 0.12826 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.23277 RPN box loss: 0.0054 RPN score loss: 0.01112 RPN total loss: 0.01652 Total loss: 0.94364 timestamp: 1655062289.1493554 iteration: 69330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08849 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.16152 L1 loss: 0.0000e+00 L2 loss: 0.56609 Learning rate: 0.0004 Mask loss: 0.13198 RPN box loss: 0.01499 RPN score loss: 0.00656 RPN total loss: 0.02155 Total loss: 0.88113 timestamp: 1655062292.4088821 iteration: 69335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10798 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.18042 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.08108 RPN box loss: 0.01026 RPN score loss: 0.0013 RPN total loss: 0.01156 Total loss: 0.83915 timestamp: 1655062295.634115 iteration: 69340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11469 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.18307 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.16053 RPN box loss: 0.01211 RPN score loss: 0.00638 RPN total loss: 0.01849 Total loss: 0.92817 timestamp: 1655062298.9322243 iteration: 69345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10846 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.19745 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.16214 RPN box loss: 0.01433 RPN score loss: 0.00775 RPN total loss: 0.02208 Total loss: 0.94776 timestamp: 1655062302.1799283 iteration: 69350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12265 FastRCNN class loss: 0.06966 FastRCNN total loss: 0.19231 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.11389 RPN box loss: 0.01772 RPN score loss: 0.00113 RPN total loss: 0.01885 Total loss: 0.89113 timestamp: 1655062305.4542682 iteration: 69355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10803 FastRCNN class loss: 0.11306 FastRCNN total loss: 0.22109 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.20041 RPN box loss: 0.01949 RPN score loss: 0.01351 RPN total loss: 0.033 Total loss: 1.02058 timestamp: 1655062308.7004004 iteration: 69360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.0605 FastRCNN total loss: 0.16392 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.08242 RPN box loss: 0.00757 RPN score loss: 0.00599 RPN total loss: 0.01356 Total loss: 0.82598 timestamp: 1655062311.9331238 iteration: 69365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07298 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.15028 L1 loss: 0.0000e+00 L2 loss: 0.56608 Learning rate: 0.0004 Mask loss: 0.14461 RPN box loss: 0.0101 RPN score loss: 0.00273 RPN total loss: 0.01283 Total loss: 0.8738 timestamp: 1655062315.169826 iteration: 69370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07394 FastRCNN class loss: 0.06234 FastRCNN total loss: 0.13628 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.16304 RPN box loss: 0.03111 RPN score loss: 0.00748 RPN total loss: 0.03859 Total loss: 0.90399 timestamp: 1655062318.4797611 iteration: 69375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10717 FastRCNN class loss: 0.10703 FastRCNN total loss: 0.21419 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.15847 RPN box loss: 0.00889 RPN score loss: 0.00472 RPN total loss: 0.01362 Total loss: 0.95235 timestamp: 1655062321.8015962 iteration: 69380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15334 FastRCNN class loss: 0.10099 FastRCNN total loss: 0.25433 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.15574 RPN box loss: 0.01494 RPN score loss: 0.0134 RPN total loss: 0.02834 Total loss: 1.00448 timestamp: 1655062325.029636 iteration: 69385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0657 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.14781 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.14757 RPN box loss: 0.0144 RPN score loss: 0.00329 RPN total loss: 0.01768 Total loss: 0.87914 timestamp: 1655062328.3339715 iteration: 69390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09309 FastRCNN class loss: 0.06019 FastRCNN total loss: 0.15328 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.12502 RPN box loss: 0.00987 RPN score loss: 0.00157 RPN total loss: 0.01144 Total loss: 0.8558 timestamp: 1655062331.6426823 iteration: 69395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1336 FastRCNN class loss: 0.09413 FastRCNN total loss: 0.22773 L1 loss: 0.0000e+00 L2 loss: 0.56607 Learning rate: 0.0004 Mask loss: 0.16185 RPN box loss: 0.01511 RPN score loss: 0.01971 RPN total loss: 0.03483 Total loss: 0.99047 timestamp: 1655062334.841392 iteration: 69400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0702 FastRCNN class loss: 0.06062 FastRCNN total loss: 0.13083 L1 loss: 0.0000e+00 L2 loss: 0.56606 Learning rate: 0.0004 Mask loss: 0.21532 RPN box loss: 0.02156 RPN score loss: 0.00518 RPN total loss: 0.02673 Total loss: 0.93894 timestamp: 1655062338.062474 iteration: 69405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04742 FastRCNN class loss: 0.06025 FastRCNN total loss: 0.10767 L1 loss: 0.0000e+00 L2 loss: 0.56606 Learning rate: 0.0004 Mask loss: 0.14681 RPN box loss: 0.0106 RPN score loss: 0.00591 RPN total loss: 0.01651 Total loss: 0.83705 timestamp: 1655062341.3678417 iteration: 69410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09185 FastRCNN class loss: 0.07253 FastRCNN total loss: 0.16439 L1 loss: 0.0000e+00 L2 loss: 0.56606 Learning rate: 0.0004 Mask loss: 0.10882 RPN box loss: 0.01264 RPN score loss: 0.00191 RPN total loss: 0.01455 Total loss: 0.85381 timestamp: 1655062344.6585517 iteration: 69415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06853 FastRCNN class loss: 0.03647 FastRCNN total loss: 0.105 L1 loss: 0.0000e+00 L2 loss: 0.56606 Learning rate: 0.0004 Mask loss: 0.11903 RPN box loss: 0.00552 RPN score loss: 0.00143 RPN total loss: 0.00695 Total loss: 0.79704 timestamp: 1655062347.9613342 iteration: 69420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07416 FastRCNN class loss: 0.07482 FastRCNN total loss: 0.14899 L1 loss: 0.0000e+00 L2 loss: 0.56606 Learning rate: 0.0004 Mask loss: 0.16536 RPN box loss: 0.02567 RPN score loss: 0.00573 RPN total loss: 0.03139 Total loss: 0.9118 timestamp: 1655062351.2331266 iteration: 69425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10262 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.56605 Learning rate: 0.0004 Mask loss: 0.15764 RPN box loss: 0.01668 RPN score loss: 0.01103 RPN total loss: 0.02771 Total loss: 0.92156 timestamp: 1655062354.5000963 iteration: 69430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15005 FastRCNN class loss: 0.08707 FastRCNN total loss: 0.23713 L1 loss: 0.0000e+00 L2 loss: 0.56605 Learning rate: 0.0004 Mask loss: 0.17178 RPN box loss: 0.03378 RPN score loss: 0.00398 RPN total loss: 0.03776 Total loss: 1.01272 timestamp: 1655062357.786367 iteration: 69435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15458 FastRCNN class loss: 0.08837 FastRCNN total loss: 0.24295 L1 loss: 0.0000e+00 L2 loss: 0.56605 Learning rate: 0.0004 Mask loss: 0.16375 RPN box loss: 0.01677 RPN score loss: 0.00501 RPN total loss: 0.02178 Total loss: 0.99453 timestamp: 1655062361.0806189 iteration: 69440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07451 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.13082 L1 loss: 0.0000e+00 L2 loss: 0.56605 Learning rate: 0.0004 Mask loss: 0.14188 RPN box loss: 0.01254 RPN score loss: 0.00205 RPN total loss: 0.01459 Total loss: 0.85335 timestamp: 1655062364.360564 iteration: 69445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10617 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.17549 L1 loss: 0.0000e+00 L2 loss: 0.56605 Learning rate: 0.0004 Mask loss: 0.18635 RPN box loss: 0.03621 RPN score loss: 0.00734 RPN total loss: 0.04355 Total loss: 0.97144 timestamp: 1655062367.575148 iteration: 69450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05266 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.10491 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.09182 RPN box loss: 0.0074 RPN score loss: 0.00296 RPN total loss: 0.01036 Total loss: 0.77314 timestamp: 1655062370.8335176 iteration: 69455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08842 FastRCNN class loss: 0.08075 FastRCNN total loss: 0.16917 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.19916 RPN box loss: 0.02028 RPN score loss: 0.00768 RPN total loss: 0.02796 Total loss: 0.96234 timestamp: 1655062374.1238203 iteration: 69460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09725 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.16405 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.13817 RPN box loss: 0.02439 RPN score loss: 0.0048 RPN total loss: 0.02919 Total loss: 0.89744 timestamp: 1655062377.3984218 iteration: 69465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10403 FastRCNN class loss: 0.06847 FastRCNN total loss: 0.17249 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.12956 RPN box loss: 0.01506 RPN score loss: 0.00965 RPN total loss: 0.0247 Total loss: 0.8928 timestamp: 1655062380.663524 iteration: 69470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11019 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.16496 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.08773 RPN box loss: 0.00605 RPN score loss: 0.00567 RPN total loss: 0.01172 Total loss: 0.83045 timestamp: 1655062383.9124196 iteration: 69475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09861 FastRCNN class loss: 0.13075 FastRCNN total loss: 0.22936 L1 loss: 0.0000e+00 L2 loss: 0.56604 Learning rate: 0.0004 Mask loss: 0.23785 RPN box loss: 0.04548 RPN score loss: 0.07045 RPN total loss: 0.11593 Total loss: 1.14918 timestamp: 1655062387.2133434 iteration: 69480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05506 FastRCNN class loss: 0.04059 FastRCNN total loss: 0.09565 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.15988 RPN box loss: 0.00419 RPN score loss: 0.00628 RPN total loss: 0.01047 Total loss: 0.83203 timestamp: 1655062390.47165 iteration: 69485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0795 FastRCNN class loss: 0.06385 FastRCNN total loss: 0.14335 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.19581 RPN box loss: 0.01108 RPN score loss: 0.00631 RPN total loss: 0.01739 Total loss: 0.92259 timestamp: 1655062393.6672206 iteration: 69490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07977 FastRCNN class loss: 0.06052 FastRCNN total loss: 0.14029 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.17033 RPN box loss: 0.00573 RPN score loss: 0.00267 RPN total loss: 0.0084 Total loss: 0.88505 timestamp: 1655062396.9615498 iteration: 69495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14431 FastRCNN class loss: 0.09207 FastRCNN total loss: 0.23638 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.16506 RPN box loss: 0.01162 RPN score loss: 0.00553 RPN total loss: 0.01715 Total loss: 0.98462 timestamp: 1655062400.189439 iteration: 69500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13125 FastRCNN class loss: 0.08482 FastRCNN total loss: 0.21607 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.14515 RPN box loss: 0.00819 RPN score loss: 0.00135 RPN total loss: 0.00954 Total loss: 0.93679 timestamp: 1655062403.4894772 iteration: 69505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07705 FastRCNN class loss: 0.04784 FastRCNN total loss: 0.12489 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.10511 RPN box loss: 0.01669 RPN score loss: 0.00129 RPN total loss: 0.01798 Total loss: 0.81401 timestamp: 1655062406.8090866 iteration: 69510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14769 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.20654 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.12976 RPN box loss: 0.01043 RPN score loss: 0.00238 RPN total loss: 0.01281 Total loss: 0.91513 timestamp: 1655062410.0646124 iteration: 69515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12925 FastRCNN class loss: 0.10332 FastRCNN total loss: 0.23256 L1 loss: 0.0000e+00 L2 loss: 0.56603 Learning rate: 0.0004 Mask loss: 0.16277 RPN box loss: 0.01264 RPN score loss: 0.00371 RPN total loss: 0.01635 Total loss: 0.97771 timestamp: 1655062413.3578458 iteration: 69520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0662 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.14069 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.14186 RPN box loss: 0.00681 RPN score loss: 0.00399 RPN total loss: 0.0108 Total loss: 0.85937 timestamp: 1655062416.579971 iteration: 69525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07406 FastRCNN class loss: 0.05537 FastRCNN total loss: 0.12943 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.13065 RPN box loss: 0.02949 RPN score loss: 0.0052 RPN total loss: 0.03469 Total loss: 0.86078 timestamp: 1655062419.865399 iteration: 69530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11239 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.17337 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.02077 RPN score loss: 0.00155 RPN total loss: 0.02232 Total loss: 0.9 timestamp: 1655062423.151464 iteration: 69535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0816 FastRCNN class loss: 0.08192 FastRCNN total loss: 0.16353 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.15951 RPN box loss: 0.01037 RPN score loss: 0.00405 RPN total loss: 0.01441 Total loss: 0.90347 timestamp: 1655062426.529078 iteration: 69540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10888 FastRCNN class loss: 0.09938 FastRCNN total loss: 0.20825 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.16488 RPN box loss: 0.00757 RPN score loss: 0.00225 RPN total loss: 0.00982 Total loss: 0.94897 timestamp: 1655062429.8697639 iteration: 69545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10854 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.17971 L1 loss: 0.0000e+00 L2 loss: 0.56602 Learning rate: 0.0004 Mask loss: 0.146 RPN box loss: 0.03138 RPN score loss: 0.00544 RPN total loss: 0.03683 Total loss: 0.92856 timestamp: 1655062433.133022 iteration: 69550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12481 FastRCNN class loss: 0.09816 FastRCNN total loss: 0.22297 L1 loss: 0.0000e+00 L2 loss: 0.56601 Learning rate: 0.0004 Mask loss: 0.13785 RPN box loss: 0.00691 RPN score loss: 0.00829 RPN total loss: 0.01519 Total loss: 0.94203 timestamp: 1655062436.4323497 iteration: 69555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10216 FastRCNN class loss: 0.08862 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.56601 Learning rate: 0.0004 Mask loss: 0.14307 RPN box loss: 0.022 RPN score loss: 0.00948 RPN total loss: 0.03148 Total loss: 0.93134 timestamp: 1655062439.6874702 iteration: 69560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12022 FastRCNN class loss: 0.08584 FastRCNN total loss: 0.20606 L1 loss: 0.0000e+00 L2 loss: 0.56601 Learning rate: 0.0004 Mask loss: 0.11676 RPN box loss: 0.01291 RPN score loss: 0.00612 RPN total loss: 0.01903 Total loss: 0.90785 timestamp: 1655062442.882879 iteration: 69565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.0533 FastRCNN total loss: 0.13527 L1 loss: 0.0000e+00 L2 loss: 0.56601 Learning rate: 0.0004 Mask loss: 0.10542 RPN box loss: 0.01066 RPN score loss: 0.00148 RPN total loss: 0.01214 Total loss: 0.81883 timestamp: 1655062446.182863 iteration: 69570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09549 FastRCNN class loss: 0.09096 FastRCNN total loss: 0.18645 L1 loss: 0.0000e+00 L2 loss: 0.56601 Learning rate: 0.0004 Mask loss: 0.15623 RPN box loss: 0.0168 RPN score loss: 0.00655 RPN total loss: 0.02334 Total loss: 0.93203 timestamp: 1655062449.4953892 iteration: 69575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0628 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.13721 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.11621 RPN box loss: 0.01845 RPN score loss: 0.0047 RPN total loss: 0.02315 Total loss: 0.84258 timestamp: 1655062452.7355719 iteration: 69580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13257 FastRCNN class loss: 0.07105 FastRCNN total loss: 0.20362 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.12078 RPN box loss: 0.01727 RPN score loss: 0.01232 RPN total loss: 0.02959 Total loss: 0.92 timestamp: 1655062456.0323482 iteration: 69585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.07304 FastRCNN total loss: 0.16856 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.15669 RPN box loss: 0.00719 RPN score loss: 0.00915 RPN total loss: 0.01634 Total loss: 0.90759 timestamp: 1655062459.3070107 iteration: 69590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09466 FastRCNN class loss: 0.06186 FastRCNN total loss: 0.15652 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.12372 RPN box loss: 0.00821 RPN score loss: 0.00281 RPN total loss: 0.01102 Total loss: 0.85726 timestamp: 1655062462.5678368 iteration: 69595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12733 FastRCNN class loss: 0.06717 FastRCNN total loss: 0.1945 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.13459 RPN box loss: 0.00996 RPN score loss: 0.00825 RPN total loss: 0.01821 Total loss: 0.9133 timestamp: 1655062465.8695328 iteration: 69600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04317 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.09918 L1 loss: 0.0000e+00 L2 loss: 0.566 Learning rate: 0.0004 Mask loss: 0.13408 RPN box loss: 0.00699 RPN score loss: 0.00712 RPN total loss: 0.01411 Total loss: 0.81337 timestamp: 1655062469.1565793 iteration: 69605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08929 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.13781 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.13705 RPN box loss: 0.00623 RPN score loss: 0.00394 RPN total loss: 0.01017 Total loss: 0.85103 timestamp: 1655062472.4235916 iteration: 69610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1322 FastRCNN class loss: 0.10796 FastRCNN total loss: 0.24016 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.16922 RPN box loss: 0.01751 RPN score loss: 0.0167 RPN total loss: 0.03421 Total loss: 1.00959 timestamp: 1655062475.67162 iteration: 69615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08039 FastRCNN class loss: 0.05591 FastRCNN total loss: 0.1363 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.09663 RPN box loss: 0.00914 RPN score loss: 0.00176 RPN total loss: 0.0109 Total loss: 0.80982 timestamp: 1655062478.9469361 iteration: 69620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05173 FastRCNN class loss: 0.02381 FastRCNN total loss: 0.07554 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.07863 RPN box loss: 0.01828 RPN score loss: 0.00236 RPN total loss: 0.02064 Total loss: 0.7408 timestamp: 1655062482.2438836 iteration: 69625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06971 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.12416 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.14221 RPN box loss: 0.00549 RPN score loss: 0.00652 RPN total loss: 0.01201 Total loss: 0.84437 timestamp: 1655062485.5110595 iteration: 69630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14377 FastRCNN class loss: 0.09138 FastRCNN total loss: 0.23514 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.16852 RPN box loss: 0.02087 RPN score loss: 0.00668 RPN total loss: 0.02755 Total loss: 0.9972 timestamp: 1655062488.8154042 iteration: 69635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10932 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.17623 L1 loss: 0.0000e+00 L2 loss: 0.56599 Learning rate: 0.0004 Mask loss: 0.17459 RPN box loss: 0.00425 RPN score loss: 0.0025 RPN total loss: 0.00675 Total loss: 0.92355 timestamp: 1655062492.0826278 iteration: 69640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10608 FastRCNN class loss: 0.0533 FastRCNN total loss: 0.15939 L1 loss: 0.0000e+00 L2 loss: 0.56598 Learning rate: 0.0004 Mask loss: 0.15419 RPN box loss: 0.01717 RPN score loss: 0.00445 RPN total loss: 0.02162 Total loss: 0.90118 timestamp: 1655062495.3652086 iteration: 69645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12571 FastRCNN class loss: 0.08606 FastRCNN total loss: 0.21177 L1 loss: 0.0000e+00 L2 loss: 0.56598 Learning rate: 0.0004 Mask loss: 0.11769 RPN box loss: 0.01237 RPN score loss: 0.0064 RPN total loss: 0.01877 Total loss: 0.91422 timestamp: 1655062498.6332798 iteration: 69650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06251 FastRCNN class loss: 0.06686 FastRCNN total loss: 0.12938 L1 loss: 0.0000e+00 L2 loss: 0.56598 Learning rate: 0.0004 Mask loss: 0.1369 RPN box loss: 0.01498 RPN score loss: 0.00798 RPN total loss: 0.02296 Total loss: 0.85522 timestamp: 1655062501.9087281 iteration: 69655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.0549 FastRCNN total loss: 0.14822 L1 loss: 0.0000e+00 L2 loss: 0.56598 Learning rate: 0.0004 Mask loss: 0.14706 RPN box loss: 0.00807 RPN score loss: 0.00157 RPN total loss: 0.00964 Total loss: 0.8709 timestamp: 1655062505.210958 iteration: 69660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09871 FastRCNN class loss: 0.14026 FastRCNN total loss: 0.23897 L1 loss: 0.0000e+00 L2 loss: 0.56598 Learning rate: 0.0004 Mask loss: 0.15389 RPN box loss: 0.01986 RPN score loss: 0.00264 RPN total loss: 0.0225 Total loss: 0.98133 timestamp: 1655062508.438335 iteration: 69665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.17139 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.19102 RPN box loss: 0.01843 RPN score loss: 0.00313 RPN total loss: 0.02156 Total loss: 0.94993 timestamp: 1655062511.6522934 iteration: 69670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11556 FastRCNN class loss: 0.07453 FastRCNN total loss: 0.1901 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.1165 RPN box loss: 0.01149 RPN score loss: 0.00541 RPN total loss: 0.0169 Total loss: 0.88947 timestamp: 1655062514.9023764 iteration: 69675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.05138 FastRCNN total loss: 0.15012 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.1376 RPN box loss: 0.01242 RPN score loss: 0.00152 RPN total loss: 0.01393 Total loss: 0.86762 timestamp: 1655062518.182144 iteration: 69680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07512 FastRCNN class loss: 0.03959 FastRCNN total loss: 0.11471 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.12185 RPN box loss: 0.00395 RPN score loss: 0.00913 RPN total loss: 0.01308 Total loss: 0.81561 timestamp: 1655062521.4658039 iteration: 69685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05145 FastRCNN class loss: 0.03651 FastRCNN total loss: 0.08796 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.14157 RPN box loss: 0.03037 RPN score loss: 0.00317 RPN total loss: 0.03354 Total loss: 0.82904 timestamp: 1655062524.704544 iteration: 69690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05186 FastRCNN class loss: 0.05638 FastRCNN total loss: 0.10824 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.12926 RPN box loss: 0.00941 RPN score loss: 0.00172 RPN total loss: 0.01113 Total loss: 0.8146 timestamp: 1655062527.9370224 iteration: 69695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11086 FastRCNN class loss: 0.05971 FastRCNN total loss: 0.17058 L1 loss: 0.0000e+00 L2 loss: 0.56597 Learning rate: 0.0004 Mask loss: 0.0939 RPN box loss: 0.00285 RPN score loss: 0.00148 RPN total loss: 0.00433 Total loss: 0.83478 timestamp: 1655062531.2064698 iteration: 69700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13951 FastRCNN class loss: 0.09673 FastRCNN total loss: 0.23624 L1 loss: 0.0000e+00 L2 loss: 0.56596 Learning rate: 0.0004 Mask loss: 0.07304 RPN box loss: 0.0038 RPN score loss: 0.00192 RPN total loss: 0.00572 Total loss: 0.88097 timestamp: 1655062534.5682747 iteration: 69705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06121 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.12757 L1 loss: 0.0000e+00 L2 loss: 0.56596 Learning rate: 0.0004 Mask loss: 0.122 RPN box loss: 0.00851 RPN score loss: 0.00228 RPN total loss: 0.01078 Total loss: 0.82631 timestamp: 1655062537.8832903 iteration: 69710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08556 FastRCNN class loss: 0.06065 FastRCNN total loss: 0.14621 L1 loss: 0.0000e+00 L2 loss: 0.56596 Learning rate: 0.0004 Mask loss: 0.10436 RPN box loss: 0.01325 RPN score loss: 0.00355 RPN total loss: 0.0168 Total loss: 0.83333 timestamp: 1655062541.1719718 iteration: 69715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06793 FastRCNN class loss: 0.09005 FastRCNN total loss: 0.15798 L1 loss: 0.0000e+00 L2 loss: 0.56596 Learning rate: 0.0004 Mask loss: 0.17349 RPN box loss: 0.01635 RPN score loss: 0.01118 RPN total loss: 0.02753 Total loss: 0.92496 timestamp: 1655062544.50106 iteration: 69720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15383 FastRCNN class loss: 0.09188 FastRCNN total loss: 0.24572 L1 loss: 0.0000e+00 L2 loss: 0.56596 Learning rate: 0.0004 Mask loss: 0.16816 RPN box loss: 0.02084 RPN score loss: 0.01494 RPN total loss: 0.03578 Total loss: 1.01561 timestamp: 1655062547.6720166 iteration: 69725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10753 FastRCNN class loss: 0.06276 FastRCNN total loss: 0.17029 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.13644 RPN box loss: 0.0178 RPN score loss: 0.00398 RPN total loss: 0.02178 Total loss: 0.89446 timestamp: 1655062550.862353 iteration: 69730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.056 FastRCNN class loss: 0.03759 FastRCNN total loss: 0.09359 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.09963 RPN box loss: 0.00372 RPN score loss: 0.00224 RPN total loss: 0.00595 Total loss: 0.76513 timestamp: 1655062554.1543078 iteration: 69735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04623 FastRCNN class loss: 0.03826 FastRCNN total loss: 0.08449 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.12086 RPN box loss: 0.00447 RPN score loss: 0.00246 RPN total loss: 0.00694 Total loss: 0.77823 timestamp: 1655062557.455875 iteration: 69740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07195 FastRCNN class loss: 0.10162 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.15896 RPN box loss: 0.0549 RPN score loss: 0.01387 RPN total loss: 0.06877 Total loss: 0.96724 timestamp: 1655062560.775722 iteration: 69745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07679 FastRCNN class loss: 0.05441 FastRCNN total loss: 0.1312 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.16858 RPN box loss: 0.01376 RPN score loss: 0.00499 RPN total loss: 0.01876 Total loss: 0.88449 timestamp: 1655062564.0163991 iteration: 69750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10113 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.17557 L1 loss: 0.0000e+00 L2 loss: 0.56595 Learning rate: 0.0004 Mask loss: 0.17835 RPN box loss: 0.01956 RPN score loss: 0.00931 RPN total loss: 0.02888 Total loss: 0.94875 timestamp: 1655062567.3518512 iteration: 69755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03459 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.09212 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.12437 RPN box loss: 0.0133 RPN score loss: 0.00465 RPN total loss: 0.01795 Total loss: 0.80039 timestamp: 1655062570.621615 iteration: 69760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06594 FastRCNN class loss: 0.06804 FastRCNN total loss: 0.13398 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.13514 RPN box loss: 0.00682 RPN score loss: 0.00535 RPN total loss: 0.01217 Total loss: 0.84724 timestamp: 1655062573.8622403 iteration: 69765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1046 FastRCNN class loss: 0.12492 FastRCNN total loss: 0.22952 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.17923 RPN box loss: 0.01194 RPN score loss: 0.01014 RPN total loss: 0.02208 Total loss: 0.99676 timestamp: 1655062577.0819402 iteration: 69770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11654 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.12946 RPN box loss: 0.00693 RPN score loss: 0.00394 RPN total loss: 0.01086 Total loss: 0.88765 timestamp: 1655062580.3174906 iteration: 69775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13182 FastRCNN class loss: 0.07828 FastRCNN total loss: 0.2101 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.16464 RPN box loss: 0.03636 RPN score loss: 0.00473 RPN total loss: 0.0411 Total loss: 0.98178 timestamp: 1655062583.5267887 iteration: 69780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.12432 FastRCNN total loss: 0.22603 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.13853 RPN box loss: 0.01969 RPN score loss: 0.00778 RPN total loss: 0.02747 Total loss: 0.95797 timestamp: 1655062586.8425503 iteration: 69785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10951 FastRCNN class loss: 0.09637 FastRCNN total loss: 0.20588 L1 loss: 0.0000e+00 L2 loss: 0.56594 Learning rate: 0.0004 Mask loss: 0.19074 RPN box loss: 0.02988 RPN score loss: 0.00786 RPN total loss: 0.03774 Total loss: 1.00029 timestamp: 1655062590.138482 iteration: 69790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08101 FastRCNN class loss: 0.05456 FastRCNN total loss: 0.13557 L1 loss: 0.0000e+00 L2 loss: 0.56593 Learning rate: 0.0004 Mask loss: 0.12718 RPN box loss: 0.00535 RPN score loss: 0.00202 RPN total loss: 0.00737 Total loss: 0.83605 timestamp: 1655062593.4421344 iteration: 69795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14974 FastRCNN class loss: 0.14229 FastRCNN total loss: 0.29203 L1 loss: 0.0000e+00 L2 loss: 0.56593 Learning rate: 0.0004 Mask loss: 0.23344 RPN box loss: 0.03391 RPN score loss: 0.01806 RPN total loss: 0.05197 Total loss: 1.14338 timestamp: 1655062596.6950152 iteration: 69800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.56593 Learning rate: 0.0004 Mask loss: 0.11353 RPN box loss: 0.00669 RPN score loss: 0.00322 RPN total loss: 0.00991 Total loss: 0.87363 timestamp: 1655062600.013292 iteration: 69805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08467 FastRCNN class loss: 0.04583 FastRCNN total loss: 0.1305 L1 loss: 0.0000e+00 L2 loss: 0.56593 Learning rate: 0.0004 Mask loss: 0.11063 RPN box loss: 0.00311 RPN score loss: 0.00373 RPN total loss: 0.00684 Total loss: 0.8139 timestamp: 1655062603.2986066 iteration: 69810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04538 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.09985 L1 loss: 0.0000e+00 L2 loss: 0.56593 Learning rate: 0.0004 Mask loss: 0.09792 RPN box loss: 0.00671 RPN score loss: 0.00429 RPN total loss: 0.011 Total loss: 0.7747 timestamp: 1655062606.587473 iteration: 69815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06182 FastRCNN class loss: 0.10906 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.12429 RPN box loss: 0.01225 RPN score loss: 0.0153 RPN total loss: 0.02755 Total loss: 0.88864 timestamp: 1655062609.7806318 iteration: 69820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09113 FastRCNN class loss: 0.05671 FastRCNN total loss: 0.14784 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.17857 RPN box loss: 0.01827 RPN score loss: 0.01112 RPN total loss: 0.02939 Total loss: 0.92172 timestamp: 1655062613.0758893 iteration: 69825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11063 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.19179 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.13728 RPN box loss: 0.00809 RPN score loss: 0.00131 RPN total loss: 0.00939 Total loss: 0.90439 timestamp: 1655062616.3563812 iteration: 69830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04812 FastRCNN class loss: 0.03434 FastRCNN total loss: 0.08246 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.11909 RPN box loss: 0.00356 RPN score loss: 0.00332 RPN total loss: 0.00689 Total loss: 0.77436 timestamp: 1655062619.6823547 iteration: 69835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17137 FastRCNN class loss: 0.09165 FastRCNN total loss: 0.26302 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.20893 RPN box loss: 0.01758 RPN score loss: 0.00201 RPN total loss: 0.01959 Total loss: 1.05746 timestamp: 1655062622.9822547 iteration: 69840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06165 FastRCNN class loss: 0.0711 FastRCNN total loss: 0.13275 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.13879 RPN box loss: 0.00467 RPN score loss: 0.00561 RPN total loss: 0.01027 Total loss: 0.84772 timestamp: 1655062626.2800035 iteration: 69845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09292 FastRCNN class loss: 0.0694 FastRCNN total loss: 0.16231 L1 loss: 0.0000e+00 L2 loss: 0.56592 Learning rate: 0.0004 Mask loss: 0.11133 RPN box loss: 0.01358 RPN score loss: 0.00869 RPN total loss: 0.02227 Total loss: 0.86184 timestamp: 1655062629.6012418 iteration: 69850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09524 FastRCNN class loss: 0.07564 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.13142 RPN box loss: 0.02725 RPN score loss: 0.00596 RPN total loss: 0.03322 Total loss: 0.90142 timestamp: 1655062632.8869495 iteration: 69855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10461 FastRCNN class loss: 0.06837 FastRCNN total loss: 0.17298 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.12973 RPN box loss: 0.00869 RPN score loss: 0.00645 RPN total loss: 0.01514 Total loss: 0.88376 timestamp: 1655062636.1752343 iteration: 69860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06416 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.11955 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.1362 RPN box loss: 0.00587 RPN score loss: 0.00227 RPN total loss: 0.00814 Total loss: 0.8298 timestamp: 1655062639.4770327 iteration: 69865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08082 FastRCNN class loss: 0.07071 FastRCNN total loss: 0.15153 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.15397 RPN box loss: 0.01045 RPN score loss: 0.00263 RPN total loss: 0.01308 Total loss: 0.8845 timestamp: 1655062642.7411675 iteration: 69870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11919 FastRCNN class loss: 0.08319 FastRCNN total loss: 0.20239 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.15468 RPN box loss: 0.00975 RPN score loss: 0.01278 RPN total loss: 0.02252 Total loss: 0.9455 timestamp: 1655062646.0693913 iteration: 69875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12002 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.56591 Learning rate: 0.0004 Mask loss: 0.15111 RPN box loss: 0.00779 RPN score loss: 0.01152 RPN total loss: 0.01931 Total loss: 0.92543 timestamp: 1655062649.2924335 iteration: 69880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10333 FastRCNN class loss: 0.06454 FastRCNN total loss: 0.16787 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.15787 RPN box loss: 0.00363 RPN score loss: 0.01037 RPN total loss: 0.014 Total loss: 0.90564 timestamp: 1655062652.528119 iteration: 69885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07139 FastRCNN class loss: 0.07156 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.13461 RPN box loss: 0.0063 RPN score loss: 0.00422 RPN total loss: 0.01052 Total loss: 0.85398 timestamp: 1655062655.7761064 iteration: 69890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.18034 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.14012 RPN box loss: 0.01468 RPN score loss: 0.00952 RPN total loss: 0.02419 Total loss: 0.91055 timestamp: 1655062659.0724437 iteration: 69895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1234 FastRCNN class loss: 0.04451 FastRCNN total loss: 0.1679 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.17434 RPN box loss: 0.01278 RPN score loss: 0.00333 RPN total loss: 0.01611 Total loss: 0.92425 timestamp: 1655062662.3642817 iteration: 69900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.06489 FastRCNN total loss: 0.12957 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.11312 RPN box loss: 0.00957 RPN score loss: 0.00273 RPN total loss: 0.0123 Total loss: 0.82089 timestamp: 1655062665.5923314 iteration: 69905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1681 FastRCNN class loss: 0.12325 FastRCNN total loss: 0.29135 L1 loss: 0.0000e+00 L2 loss: 0.5659 Learning rate: 0.0004 Mask loss: 0.28044 RPN box loss: 0.01789 RPN score loss: 0.01403 RPN total loss: 0.03192 Total loss: 1.16961 timestamp: 1655062668.843044 iteration: 69910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1626 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.23942 L1 loss: 0.0000e+00 L2 loss: 0.56589 Learning rate: 0.0004 Mask loss: 0.16005 RPN box loss: 0.0048 RPN score loss: 0.00445 RPN total loss: 0.00924 Total loss: 0.9746 timestamp: 1655062672.1328118 iteration: 69915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11935 FastRCNN class loss: 0.0602 FastRCNN total loss: 0.17955 L1 loss: 0.0000e+00 L2 loss: 0.56589 Learning rate: 0.0004 Mask loss: 0.18238 RPN box loss: 0.03144 RPN score loss: 0.00964 RPN total loss: 0.04108 Total loss: 0.9689 timestamp: 1655062675.33946 iteration: 69920 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06816 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.11207 L1 loss: 0.0000e+00 L2 loss: 0.56589 Learning rate: 0.0004 Mask loss: 0.10048 RPN box loss: 0.00541 RPN score loss: 0.00752 RPN total loss: 0.01294 Total loss: 0.79138 timestamp: 1655062678.60475 iteration: 69925 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16432 FastRCNN class loss: 0.1059 FastRCNN total loss: 0.27022 L1 loss: 0.0000e+00 L2 loss: 0.56589 Learning rate: 0.0004 Mask loss: 0.20539 RPN box loss: 0.01284 RPN score loss: 0.00812 RPN total loss: 0.02097 Total loss: 1.06247 timestamp: 1655062681.89698 iteration: 69930 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13976 FastRCNN class loss: 0.09289 FastRCNN total loss: 0.23264 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.17491 RPN box loss: 0.01194 RPN score loss: 0.00542 RPN total loss: 0.01735 Total loss: 0.99079 timestamp: 1655062685.1569555 iteration: 69935 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09151 FastRCNN class loss: 0.05276 FastRCNN total loss: 0.14427 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.1473 RPN box loss: 0.00969 RPN score loss: 0.00325 RPN total loss: 0.01294 Total loss: 0.87039 timestamp: 1655062688.3908374 iteration: 69940 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09807 FastRCNN class loss: 0.08235 FastRCNN total loss: 0.18041 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.20592 RPN box loss: 0.00968 RPN score loss: 0.00392 RPN total loss: 0.0136 Total loss: 0.96581 timestamp: 1655062691.7451103 iteration: 69945 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10966 FastRCNN class loss: 0.06358 FastRCNN total loss: 0.17325 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.12025 RPN box loss: 0.01875 RPN score loss: 0.00148 RPN total loss: 0.02023 Total loss: 0.87961 timestamp: 1655062695.0295079 iteration: 69950 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12475 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.20791 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.14668 RPN box loss: 0.01471 RPN score loss: 0.00312 RPN total loss: 0.01783 Total loss: 0.93831 timestamp: 1655062698.2703686 iteration: 69955 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05966 FastRCNN class loss: 0.03944 FastRCNN total loss: 0.0991 L1 loss: 0.0000e+00 L2 loss: 0.56588 Learning rate: 0.0004 Mask loss: 0.15786 RPN box loss: 0.0044 RPN score loss: 0.00228 RPN total loss: 0.00668 Total loss: 0.82952 timestamp: 1655062701.6291804 iteration: 69960 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.04818 FastRCNN total loss: 0.15423 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.13171 RPN box loss: 0.02974 RPN score loss: 0.00338 RPN total loss: 0.03312 Total loss: 0.88494 timestamp: 1655062704.8668606 iteration: 69965 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06636 FastRCNN class loss: 0.04623 FastRCNN total loss: 0.11259 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.09843 RPN box loss: 0.00888 RPN score loss: 0.00262 RPN total loss: 0.01151 Total loss: 0.7884 timestamp: 1655062708.0953627 iteration: 69970 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09589 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.16132 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.18783 RPN box loss: 0.03354 RPN score loss: 0.00454 RPN total loss: 0.03808 Total loss: 0.9531 timestamp: 1655062711.3667488 iteration: 69975 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05236 FastRCNN class loss: 0.04626 FastRCNN total loss: 0.09862 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.10733 RPN box loss: 0.00625 RPN score loss: 0.00168 RPN total loss: 0.00793 Total loss: 0.77974 timestamp: 1655062714.7216418 iteration: 69980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12096 FastRCNN class loss: 0.09431 FastRCNN total loss: 0.21527 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.11803 RPN box loss: 0.02017 RPN score loss: 0.00527 RPN total loss: 0.02544 Total loss: 0.92461 timestamp: 1655062717.9579859 iteration: 69985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13984 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.21114 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.20557 RPN box loss: 0.02355 RPN score loss: 0.00861 RPN total loss: 0.03216 Total loss: 1.01474 timestamp: 1655062721.2807074 iteration: 69990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10383 FastRCNN class loss: 0.07856 FastRCNN total loss: 0.18239 L1 loss: 0.0000e+00 L2 loss: 0.56587 Learning rate: 0.0004 Mask loss: 0.09986 RPN box loss: 0.00424 RPN score loss: 0.00269 RPN total loss: 0.00693 Total loss: 0.85505 timestamp: 1655062724.5712616 iteration: 69995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12514 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.20113 L1 loss: 0.0000e+00 L2 loss: 0.56586 Learning rate: 0.0004 Mask loss: 0.22898 RPN box loss: 0.0174 RPN score loss: 0.01393 RPN total loss: 0.03133 Total loss: 1.0273 timestamp: 1655062727.8416905 iteration: 70000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07944 FastRCNN class loss: 0.07804 FastRCNN total loss: 0.15748 L1 loss: 0.0000e+00 L2 loss: 0.56586 Learning rate: 0.0004 Mask loss: 0.1636 RPN box loss: 0.00986 RPN score loss: 0.00539 RPN total loss: 0.01525 Total loss: 0.90219 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 6.0302s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.9544s - Throughput: 4.2 imgs/s Running inference on batch 003/125... - Step Time: 0.9245s - Throughput: 4.3 imgs/s Running inference on batch 004/125... - Step Time: 0.9583s - Throughput: 4.2 imgs/s Running inference on batch 005/125... - Step Time: 0.9070s - Throughput: 4.4 imgs/s Running inference on batch 006/125... - Step Time: 0.8892s - Throughput: 4.5 imgs/s Running inference on batch 007/125... - Step Time: 0.9190s - Throughput: 4.4 imgs/s Running inference on batch 008/125... - Step Time: 0.7134s - Throughput: 5.6 imgs/s Running inference on batch 009/125... - Step Time: 1.0078s - Throughput: 4.0 imgs/s Running inference on batch 010/125... - Step Time: 0.9292s - Throughput: 4.3 imgs/s Running inference on batch 011/125... - Step Time: 0.9577s - Throughput: 4.2 imgs/s Running inference on batch 012/125... - Step Time: 0.8876s - Throughput: 4.5 imgs/s Running inference on batch 013/125... - Step Time: 0.8927s - Throughput: 4.5 imgs/s Running inference on batch 014/125... - Step Time: 0.9300s - Throughput: 4.3 imgs/s Running inference on batch 015/125... - Step Time: 0.9439s - Throughput: 4.2 imgs/s Running inference on batch 016/125... - Step Time: 0.9006s - Throughput: 4.4 imgs/s Running inference on batch 017/125... - Step Time: 0.8968s - Throughput: 4.5 imgs/s Running inference on batch 018/125... - Step Time: 0.8967s - Throughput: 4.5 imgs/s Running inference on batch 019/125... - Step Time: 0.9637s - Throughput: 4.2 imgs/s Running inference on batch 020/125... - Step Time: 0.9070s - Throughput: 4.4 imgs/s Running inference on batch 021/125... - Step Time: 0.9165s - Throughput: 4.4 imgs/s Running inference on batch 022/125... - Step Time: 1.0300s - Throughput: 3.9 imgs/s Running inference on batch 023/125... - Step Time: 0.9282s - Throughput: 4.3 imgs/s Running inference on batch 024/125... - Step Time: 0.9153s - Throughput: 4.4 imgs/s Running inference on batch 025/125... - Step Time: 0.9062s - Throughput: 4.4 imgs/s Running inference on batch 026/125... - Step Time: 0.9106s - Throughput: 4.4 imgs/s Running inference on batch 027/125... - Step Time: 0.8444s - Throughput: 4.7 imgs/s Running inference on batch 028/125... - Step Time: 0.9128s - Throughput: 4.4 imgs/s Running inference on batch 029/125... - Step Time: 0.9367s - Throughput: 4.3 imgs/s Running inference on batch 030/125... - Step Time: 0.9590s - Throughput: 4.2 imgs/s Running inference on batch 031/125... - Step Time: 0.9247s - Throughput: 4.3 imgs/s Running inference on batch 032/125... - Step Time: 0.9706s - Throughput: 4.1 imgs/s Running inference on batch 033/125... - Step Time: 0.9809s - Throughput: 4.1 imgs/s Running inference on batch 034/125... - Step Time: 1.0020s - Throughput: 4.0 imgs/s Running inference on batch 035/125... - Step Time: 0.8849s - Throughput: 4.5 imgs/s Running inference on batch 036/125... - Step Time: 0.9594s - Throughput: 4.2 imgs/s Running inference on batch 037/125... - Step Time: 0.9641s - Throughput: 4.1 imgs/s Running inference on batch 038/125... - Step Time: 0.9459s - Throughput: 4.2 imgs/s Running inference on batch 039/125... - Step Time: 0.9371s - Throughput: 4.3 imgs/s Running inference on batch 040/125... - Step Time: 0.9064s - Throughput: 4.4 imgs/s Running inference on batch 041/125... - Step Time: 0.9919s - Throughput: 4.0 imgs/s Running inference on batch 042/125... - Step Time: 0.9515s - Throughput: 4.2 imgs/s Running inference on batch 043/125... - Step Time: 0.8955s - Throughput: 4.5 imgs/s Running inference on batch 044/125... - Step Time: 0.9436s - Throughput: 4.2 imgs/s Running inference on batch 045/125... - Step Time: 0.9016s - Throughput: 4.4 imgs/s Running inference on batch 046/125... - Step Time: 0.9076s - Throughput: 4.4 imgs/s Running inference on batch 047/125... - Step Time: 0.9092s - Throughput: 4.4 imgs/s Running inference on batch 048/125... - 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Step Time: 0.8903s - Throughput: 4.5 imgs/s Running inference on batch 121/125... - Step Time: 0.8836s - Throughput: 4.5 imgs/s Running inference on batch 122/125... - Step Time: 0.9106s - Throughput: 4.4 imgs/s Running inference on batch 123/125... - Step Time: 0.9009s - Throughput: 4.4 imgs/s Running inference on batch 124/125... - Step Time: 0.9936s - Throughput: 4.0 imgs/s Running inference on batch 125/125... - Step Time: 0.9147s - Throughput: 4.4 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: 4.3 samples/sec Total processed steps: 125 Total processing time: 0.0h 09m 01s ==================== Metrics ==================== AP: 0.194506213 AP50: 0.306661576 AP75: 0.192121819 APl: 0.225956649 APm: 0.044930797 APs: 0.002319229 ARl: 0.443233430 ARm: 0.090983436 ARmax1: 0.285275370 ARmax10: 0.377859324 ARmax100: 0.382747799 ARs: 0.013466184 mask_AP: 0.145584360 mask_AP50: 0.253788620 mask_AP75: 0.148174003 mask_APl: 0.171585828 mask_APm: 0.016477333 mask_APs: 0.000000000 mask_ARl: 0.297661006 mask_ARm: 0.043113288 mask_ARmax1: 0.201491609 mask_ARmax10: 0.247444913 mask_ARmax100: 0.250288785 mask_ARs: 0.000000000 ================================= 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] 549.0 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: 1655064040.4571648 iteration: 70005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10077 FastRCNN class loss: 0.04806 FastRCNN total loss: 0.14884 L1 loss: 0.0000e+00 L2 loss: 0.56586 Learning rate: 0.0004 Mask loss: 0.10197 RPN box loss: 0.01339 RPN score loss: 0.00672 RPN total loss: 0.02011 Total loss: 0.83677 timestamp: 1655064043.7413204 iteration: 70010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06473 FastRCNN class loss: 0.06497 FastRCNN total loss: 0.1297 L1 loss: 0.0000e+00 L2 loss: 0.56586 Learning rate: 0.0004 Mask loss: 0.13357 RPN box loss: 0.01518 RPN score loss: 0.00515 RPN total loss: 0.02032 Total loss: 0.84945 timestamp: 1655064046.990276 iteration: 70015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08798 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.14794 L1 loss: 0.0000e+00 L2 loss: 0.56586 Learning rate: 0.0004 Mask loss: 0.16783 RPN box loss: 0.00859 RPN score loss: 0.00289 RPN total loss: 0.01148 Total loss: 0.8931 timestamp: 1655064050.192471 iteration: 70020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1151 FastRCNN class loss: 0.06595 FastRCNN total loss: 0.18105 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.14847 RPN box loss: 0.00893 RPN score loss: 0.00263 RPN total loss: 0.01156 Total loss: 0.90693 timestamp: 1655064053.466613 iteration: 70025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12045 FastRCNN class loss: 0.05719 FastRCNN total loss: 0.17764 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.14308 RPN box loss: 0.02222 RPN score loss: 0.00273 RPN total loss: 0.02496 Total loss: 0.91153 timestamp: 1655064056.78432 iteration: 70030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0852 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.14721 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.08706 RPN box loss: 0.01271 RPN score loss: 0.00575 RPN total loss: 0.01846 Total loss: 0.81858 timestamp: 1655064060.0788214 iteration: 70035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06225 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.12327 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.17713 RPN box loss: 0.00826 RPN score loss: 0.00199 RPN total loss: 0.01024 Total loss: 0.87649 timestamp: 1655064063.382203 iteration: 70040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08297 FastRCNN class loss: 0.06485 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.16138 RPN box loss: 0.00302 RPN score loss: 0.00142 RPN total loss: 0.00444 Total loss: 0.87949 timestamp: 1655064066.6237972 iteration: 70045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17992 FastRCNN class loss: 0.0765 FastRCNN total loss: 0.25641 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.09084 RPN box loss: 0.00902 RPN score loss: 0.00584 RPN total loss: 0.01486 Total loss: 0.92796 timestamp: 1655064069.8405085 iteration: 70050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11199 FastRCNN class loss: 0.05475 FastRCNN total loss: 0.16675 L1 loss: 0.0000e+00 L2 loss: 0.56585 Learning rate: 0.0004 Mask loss: 0.13253 RPN box loss: 0.01342 RPN score loss: 0.00095 RPN total loss: 0.01437 Total loss: 0.87949 timestamp: 1655064073.1301103 iteration: 70055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.05832 FastRCNN total loss: 0.15629 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.10546 RPN box loss: 0.01461 RPN score loss: 0.00603 RPN total loss: 0.02063 Total loss: 0.84823 timestamp: 1655064076.3762934 iteration: 70060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13256 FastRCNN class loss: 0.13713 FastRCNN total loss: 0.2697 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.19312 RPN box loss: 0.02067 RPN score loss: 0.00687 RPN total loss: 0.02755 Total loss: 1.0562 timestamp: 1655064079.6400528 iteration: 70065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07933 FastRCNN class loss: 0.0626 FastRCNN total loss: 0.14193 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.14837 RPN box loss: 0.01244 RPN score loss: 0.00757 RPN total loss: 0.02001 Total loss: 0.87615 timestamp: 1655064082.854243 iteration: 70070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11105 FastRCNN class loss: 0.09009 FastRCNN total loss: 0.20114 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.11514 RPN box loss: 0.01086 RPN score loss: 0.00374 RPN total loss: 0.0146 Total loss: 0.89672 timestamp: 1655064086.1293705 iteration: 70075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10125 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.16785 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.14194 RPN box loss: 0.01255 RPN score loss: 0.00571 RPN total loss: 0.01826 Total loss: 0.89389 timestamp: 1655064089.4434338 iteration: 70080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05887 FastRCNN class loss: 0.03272 FastRCNN total loss: 0.09159 L1 loss: 0.0000e+00 L2 loss: 0.56584 Learning rate: 0.0004 Mask loss: 0.12144 RPN box loss: 0.0042 RPN score loss: 0.00548 RPN total loss: 0.00969 Total loss: 0.78855 timestamp: 1655064092.7685318 iteration: 70085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.08146 FastRCNN total loss: 0.20018 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.18406 RPN box loss: 0.01044 RPN score loss: 0.00391 RPN total loss: 0.01435 Total loss: 0.96443 timestamp: 1655064096.0137424 iteration: 70090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10164 FastRCNN class loss: 0.08364 FastRCNN total loss: 0.18529 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.13116 RPN box loss: 0.01091 RPN score loss: 0.00615 RPN total loss: 0.01706 Total loss: 0.89934 timestamp: 1655064099.2852757 iteration: 70095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05444 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.10424 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.09433 RPN box loss: 0.01098 RPN score loss: 0.00376 RPN total loss: 0.01474 Total loss: 0.77914 timestamp: 1655064102.5790448 iteration: 70100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.03802 FastRCNN total loss: 0.12617 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.09653 RPN box loss: 0.02134 RPN score loss: 0.0045 RPN total loss: 0.02585 Total loss: 0.81438 timestamp: 1655064105.8082032 iteration: 70105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08088 FastRCNN class loss: 0.06625 FastRCNN total loss: 0.14713 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.11584 RPN box loss: 0.03102 RPN score loss: 0.00579 RPN total loss: 0.03681 Total loss: 0.86561 timestamp: 1655064109.0130112 iteration: 70110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10277 FastRCNN class loss: 0.08029 FastRCNN total loss: 0.18306 L1 loss: 0.0000e+00 L2 loss: 0.56583 Learning rate: 0.0004 Mask loss: 0.11606 RPN box loss: 0.00823 RPN score loss: 0.00471 RPN total loss: 0.01293 Total loss: 0.87787 timestamp: 1655064112.2960453 iteration: 70115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11897 FastRCNN class loss: 0.0645 FastRCNN total loss: 0.18347 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.16354 RPN box loss: 0.01653 RPN score loss: 0.0054 RPN total loss: 0.02193 Total loss: 0.93477 timestamp: 1655064115.5011 iteration: 70120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03582 FastRCNN class loss: 0.03735 FastRCNN total loss: 0.07317 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.09346 RPN box loss: 0.00299 RPN score loss: 0.00392 RPN total loss: 0.0069 Total loss: 0.73936 timestamp: 1655064118.8408847 iteration: 70125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.06371 FastRCNN total loss: 0.13732 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.12238 RPN box loss: 0.0077 RPN score loss: 0.0061 RPN total loss: 0.0138 Total loss: 0.83932 timestamp: 1655064122.1504393 iteration: 70130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13261 FastRCNN class loss: 0.10676 FastRCNN total loss: 0.23937 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.18022 RPN box loss: 0.03497 RPN score loss: 0.00592 RPN total loss: 0.04089 Total loss: 1.0263 timestamp: 1655064125.418488 iteration: 70135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10936 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.17627 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.16979 RPN box loss: 0.00731 RPN score loss: 0.00483 RPN total loss: 0.01214 Total loss: 0.92402 timestamp: 1655064128.7114115 iteration: 70140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.08589 FastRCNN total loss: 0.20031 L1 loss: 0.0000e+00 L2 loss: 0.56582 Learning rate: 0.0004 Mask loss: 0.12531 RPN box loss: 0.01685 RPN score loss: 0.00122 RPN total loss: 0.01807 Total loss: 0.90951 timestamp: 1655064131.9684715 iteration: 70145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08369 FastRCNN class loss: 0.05235 FastRCNN total loss: 0.13605 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.10887 RPN box loss: 0.00478 RPN score loss: 0.00783 RPN total loss: 0.01261 Total loss: 0.82334 timestamp: 1655064135.239752 iteration: 70150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09183 FastRCNN class loss: 0.09142 FastRCNN total loss: 0.18325 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.11846 RPN box loss: 0.02395 RPN score loss: 0.00335 RPN total loss: 0.02729 Total loss: 0.89482 timestamp: 1655064138.5714655 iteration: 70155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09058 FastRCNN class loss: 0.04562 FastRCNN total loss: 0.1362 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.08619 RPN box loss: 0.00631 RPN score loss: 0.00347 RPN total loss: 0.00978 Total loss: 0.79798 timestamp: 1655064141.8757463 iteration: 70160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.15796 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.15339 RPN box loss: 0.00601 RPN score loss: 0.00445 RPN total loss: 0.01046 Total loss: 0.88762 timestamp: 1655064145.1996062 iteration: 70165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09621 FastRCNN class loss: 0.04974 FastRCNN total loss: 0.14595 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.11573 RPN box loss: 0.00755 RPN score loss: 0.00511 RPN total loss: 0.01266 Total loss: 0.84015 timestamp: 1655064148.528215 iteration: 70170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06661 FastRCNN class loss: 0.07403 FastRCNN total loss: 0.14065 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.22455 RPN box loss: 0.01253 RPN score loss: 0.01186 RPN total loss: 0.02439 Total loss: 0.9554 timestamp: 1655064151.7891223 iteration: 70175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11137 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.17641 L1 loss: 0.0000e+00 L2 loss: 0.56581 Learning rate: 0.0004 Mask loss: 0.1286 RPN box loss: 0.00719 RPN score loss: 0.00281 RPN total loss: 0.01 Total loss: 0.88082 timestamp: 1655064155.0214453 iteration: 70180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11095 FastRCNN class loss: 0.06346 FastRCNN total loss: 0.17441 L1 loss: 0.0000e+00 L2 loss: 0.5658 Learning rate: 0.0004 Mask loss: 0.14397 RPN box loss: 0.01152 RPN score loss: 0.00319 RPN total loss: 0.01471 Total loss: 0.89889 timestamp: 1655064158.2723536 iteration: 70185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10035 FastRCNN class loss: 0.11075 FastRCNN total loss: 0.2111 L1 loss: 0.0000e+00 L2 loss: 0.5658 Learning rate: 0.0004 Mask loss: 0.17383 RPN box loss: 0.01957 RPN score loss: 0.01612 RPN total loss: 0.03569 Total loss: 0.98642 timestamp: 1655064161.5689824 iteration: 70190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.0867 FastRCNN total loss: 0.1603 L1 loss: 0.0000e+00 L2 loss: 0.5658 Learning rate: 0.0004 Mask loss: 0.15518 RPN box loss: 0.01098 RPN score loss: 0.00592 RPN total loss: 0.0169 Total loss: 0.89818 timestamp: 1655064164.8257074 iteration: 70195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13993 FastRCNN class loss: 0.10519 FastRCNN total loss: 0.24512 L1 loss: 0.0000e+00 L2 loss: 0.5658 Learning rate: 0.0004 Mask loss: 0.19437 RPN box loss: 0.02415 RPN score loss: 0.00543 RPN total loss: 0.02958 Total loss: 1.03487 timestamp: 1655064168.1122413 iteration: 70200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.09943 FastRCNN total loss: 0.22368 L1 loss: 0.0000e+00 L2 loss: 0.5658 Learning rate: 0.0004 Mask loss: 0.12866 RPN box loss: 0.01091 RPN score loss: 0.0064 RPN total loss: 0.01731 Total loss: 0.93544 timestamp: 1655064171.37001 iteration: 70205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06531 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.15681 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.13326 RPN box loss: 0.01379 RPN score loss: 0.0028 RPN total loss: 0.01659 Total loss: 0.87245 timestamp: 1655064174.6355462 iteration: 70210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09003 FastRCNN class loss: 0.05931 FastRCNN total loss: 0.14934 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.19295 RPN box loss: 0.01365 RPN score loss: 0.00701 RPN total loss: 0.02065 Total loss: 0.92874 timestamp: 1655064177.9404888 iteration: 70215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09934 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.17021 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.17795 RPN box loss: 0.0082 RPN score loss: 0.00349 RPN total loss: 0.01169 Total loss: 0.92564 timestamp: 1655064181.1108007 iteration: 70220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05799 FastRCNN class loss: 0.04833 FastRCNN total loss: 0.10631 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.08716 RPN box loss: 0.01531 RPN score loss: 0.00564 RPN total loss: 0.02094 Total loss: 0.78021 timestamp: 1655064184.3606157 iteration: 70225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0548 FastRCNN class loss: 0.03665 FastRCNN total loss: 0.09145 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.10994 RPN box loss: 0.01139 RPN score loss: 0.00573 RPN total loss: 0.01712 Total loss: 0.7843 timestamp: 1655064187.6235995 iteration: 70230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07307 FastRCNN class loss: 0.07787 FastRCNN total loss: 0.15093 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.20116 RPN box loss: 0.00692 RPN score loss: 0.00582 RPN total loss: 0.01274 Total loss: 0.93063 timestamp: 1655064190.8821492 iteration: 70235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07614 FastRCNN class loss: 0.0613 FastRCNN total loss: 0.13745 L1 loss: 0.0000e+00 L2 loss: 0.56579 Learning rate: 0.0004 Mask loss: 0.09481 RPN box loss: 0.00703 RPN score loss: 0.00267 RPN total loss: 0.0097 Total loss: 0.80774 timestamp: 1655064194.1578074 iteration: 70240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13599 FastRCNN class loss: 0.05791 FastRCNN total loss: 0.1939 L1 loss: 0.0000e+00 L2 loss: 0.56578 Learning rate: 0.0004 Mask loss: 0.11248 RPN box loss: 0.01904 RPN score loss: 0.00576 RPN total loss: 0.0248 Total loss: 0.89696 timestamp: 1655064197.4840205 iteration: 70245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08925 FastRCNN class loss: 0.07206 FastRCNN total loss: 0.16131 L1 loss: 0.0000e+00 L2 loss: 0.56578 Learning rate: 0.0004 Mask loss: 0.14805 RPN box loss: 0.00643 RPN score loss: 0.00586 RPN total loss: 0.0123 Total loss: 0.88743 timestamp: 1655064200.6910586 iteration: 70250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0624 FastRCNN class loss: 0.04156 FastRCNN total loss: 0.10397 L1 loss: 0.0000e+00 L2 loss: 0.56578 Learning rate: 0.0004 Mask loss: 0.10309 RPN box loss: 0.0117 RPN score loss: 0.00162 RPN total loss: 0.01333 Total loss: 0.78616 timestamp: 1655064203.9525802 iteration: 70255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1055 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.16407 L1 loss: 0.0000e+00 L2 loss: 0.56578 Learning rate: 0.0004 Mask loss: 0.08879 RPN box loss: 0.01013 RPN score loss: 0.00309 RPN total loss: 0.01322 Total loss: 0.83186 timestamp: 1655064207.2816696 iteration: 70260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04792 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.10746 L1 loss: 0.0000e+00 L2 loss: 0.56578 Learning rate: 0.0004 Mask loss: 0.12528 RPN box loss: 0.00742 RPN score loss: 0.00356 RPN total loss: 0.01098 Total loss: 0.80949 timestamp: 1655064210.551247 iteration: 70265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10502 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.19089 L1 loss: 0.0000e+00 L2 loss: 0.56577 Learning rate: 0.0004 Mask loss: 0.14237 RPN box loss: 0.01457 RPN score loss: 0.01157 RPN total loss: 0.02614 Total loss: 0.92517 timestamp: 1655064213.7910936 iteration: 70270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10126 FastRCNN class loss: 0.07022 FastRCNN total loss: 0.17147 L1 loss: 0.0000e+00 L2 loss: 0.56577 Learning rate: 0.0004 Mask loss: 0.16097 RPN box loss: 0.01017 RPN score loss: 0.00386 RPN total loss: 0.01403 Total loss: 0.91225 timestamp: 1655064217.1179035 iteration: 70275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08745 FastRCNN class loss: 0.07326 FastRCNN total loss: 0.16071 L1 loss: 0.0000e+00 L2 loss: 0.56577 Learning rate: 0.0004 Mask loss: 0.15376 RPN box loss: 0.0202 RPN score loss: 0.00156 RPN total loss: 0.02177 Total loss: 0.90201 timestamp: 1655064220.342779 iteration: 70280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.17174 L1 loss: 0.0000e+00 L2 loss: 0.56577 Learning rate: 0.0004 Mask loss: 0.14536 RPN box loss: 0.00573 RPN score loss: 0.0032 RPN total loss: 0.00893 Total loss: 0.89179 timestamp: 1655064223.6179621 iteration: 70285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09064 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.56577 Learning rate: 0.0004 Mask loss: 0.08947 RPN box loss: 0.01436 RPN score loss: 0.00337 RPN total loss: 0.01774 Total loss: 0.81688 timestamp: 1655064226.8967905 iteration: 70290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.15395 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.11021 RPN box loss: 0.01025 RPN score loss: 0.0058 RPN total loss: 0.01606 Total loss: 0.84599 timestamp: 1655064230.1124368 iteration: 70295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06693 FastRCNN class loss: 0.05548 FastRCNN total loss: 0.12241 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.13701 RPN box loss: 0.03834 RPN score loss: 0.00957 RPN total loss: 0.0479 Total loss: 0.87308 timestamp: 1655064233.394835 iteration: 70300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15541 FastRCNN class loss: 0.11609 FastRCNN total loss: 0.2715 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.17034 RPN box loss: 0.02505 RPN score loss: 0.0042 RPN total loss: 0.02925 Total loss: 1.03685 timestamp: 1655064236.6278293 iteration: 70305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.16709 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.13126 RPN box loss: 0.00677 RPN score loss: 0.00451 RPN total loss: 0.01128 Total loss: 0.87538 timestamp: 1655064239.876131 iteration: 70310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09222 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.15797 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.14374 RPN box loss: 0.00786 RPN score loss: 0.00303 RPN total loss: 0.01089 Total loss: 0.87836 timestamp: 1655064243.1275446 iteration: 70315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.17383 L1 loss: 0.0000e+00 L2 loss: 0.56576 Learning rate: 0.0004 Mask loss: 0.15863 RPN box loss: 0.019 RPN score loss: 0.00496 RPN total loss: 0.02396 Total loss: 0.92218 timestamp: 1655064246.3631191 iteration: 70320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14645 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.21462 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.19747 RPN box loss: 0.01349 RPN score loss: 0.00248 RPN total loss: 0.01597 Total loss: 0.99382 timestamp: 1655064249.6296315 iteration: 70325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10512 FastRCNN class loss: 0.04134 FastRCNN total loss: 0.14646 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.14549 RPN box loss: 0.00947 RPN score loss: 0.00318 RPN total loss: 0.01265 Total loss: 0.87036 timestamp: 1655064252.914154 iteration: 70330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10607 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.17321 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.1334 RPN box loss: 0.00955 RPN score loss: 0.00176 RPN total loss: 0.01131 Total loss: 0.88367 timestamp: 1655064256.2000363 iteration: 70335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11848 FastRCNN class loss: 0.09724 FastRCNN total loss: 0.21572 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.15242 RPN box loss: 0.01608 RPN score loss: 0.01093 RPN total loss: 0.027 Total loss: 0.96089 timestamp: 1655064259.4547641 iteration: 70340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05843 FastRCNN class loss: 0.0507 FastRCNN total loss: 0.10912 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.16379 RPN box loss: 0.01148 RPN score loss: 0.00159 RPN total loss: 0.01307 Total loss: 0.85173 timestamp: 1655064262.7290123 iteration: 70345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05615 FastRCNN class loss: 0.05049 FastRCNN total loss: 0.10664 L1 loss: 0.0000e+00 L2 loss: 0.56575 Learning rate: 0.0004 Mask loss: 0.12942 RPN box loss: 0.00816 RPN score loss: 0.00933 RPN total loss: 0.0175 Total loss: 0.8193 timestamp: 1655064266.0617816 iteration: 70350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14166 FastRCNN class loss: 0.11018 FastRCNN total loss: 0.25184 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.24615 RPN box loss: 0.01438 RPN score loss: 0.01046 RPN total loss: 0.02483 Total loss: 1.08857 timestamp: 1655064269.3711414 iteration: 70355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.094 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.14181 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.10782 RPN box loss: 0.00605 RPN score loss: 0.00368 RPN total loss: 0.00973 Total loss: 0.8251 timestamp: 1655064272.6876767 iteration: 70360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.10095 FastRCNN total loss: 0.17673 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.15933 RPN box loss: 0.01501 RPN score loss: 0.00749 RPN total loss: 0.02249 Total loss: 0.92429 timestamp: 1655064275.971398 iteration: 70365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12989 FastRCNN class loss: 0.05413 FastRCNN total loss: 0.18403 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.11648 RPN box loss: 0.01423 RPN score loss: 0.00658 RPN total loss: 0.02081 Total loss: 0.88705 timestamp: 1655064279.2118275 iteration: 70370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06858 FastRCNN class loss: 0.0633 FastRCNN total loss: 0.13188 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.09949 RPN box loss: 0.01718 RPN score loss: 0.00625 RPN total loss: 0.02343 Total loss: 0.82055 timestamp: 1655064282.5413623 iteration: 70375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06816 FastRCNN class loss: 0.0554 FastRCNN total loss: 0.12356 L1 loss: 0.0000e+00 L2 loss: 0.56574 Learning rate: 0.0004 Mask loss: 0.17537 RPN box loss: 0.02545 RPN score loss: 0.007 RPN total loss: 0.03245 Total loss: 0.89712 timestamp: 1655064285.8230982 iteration: 70380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09202 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.18149 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.17774 RPN box loss: 0.03122 RPN score loss: 0.00804 RPN total loss: 0.03926 Total loss: 0.96422 timestamp: 1655064289.1017714 iteration: 70385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15202 FastRCNN class loss: 0.14395 FastRCNN total loss: 0.29597 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.17119 RPN box loss: 0.02113 RPN score loss: 0.01374 RPN total loss: 0.03488 Total loss: 1.06776 timestamp: 1655064292.4232929 iteration: 70390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07868 FastRCNN class loss: 0.05217 FastRCNN total loss: 0.13084 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.23301 RPN box loss: 0.0173 RPN score loss: 0.00207 RPN total loss: 0.01937 Total loss: 0.94896 timestamp: 1655064295.6283104 iteration: 70395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.12265 FastRCNN total loss: 0.22771 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.1259 RPN box loss: 0.00845 RPN score loss: 0.005 RPN total loss: 0.01345 Total loss: 0.93279 timestamp: 1655064298.8802133 iteration: 70400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07824 FastRCNN class loss: 0.04551 FastRCNN total loss: 0.12375 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.1123 RPN box loss: 0.00656 RPN score loss: 0.00169 RPN total loss: 0.00826 Total loss: 0.81003 timestamp: 1655064302.1745126 iteration: 70405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06893 FastRCNN class loss: 0.0694 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.56573 Learning rate: 0.0004 Mask loss: 0.13438 RPN box loss: 0.00718 RPN score loss: 0.00116 RPN total loss: 0.00834 Total loss: 0.84677 timestamp: 1655064305.4797974 iteration: 70410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11629 FastRCNN class loss: 0.09192 FastRCNN total loss: 0.20821 L1 loss: 0.0000e+00 L2 loss: 0.56572 Learning rate: 0.0004 Mask loss: 0.13719 RPN box loss: 0.01801 RPN score loss: 0.0086 RPN total loss: 0.02661 Total loss: 0.93773 timestamp: 1655064308.7888913 iteration: 70415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08298 FastRCNN class loss: 0.06625 FastRCNN total loss: 0.14923 L1 loss: 0.0000e+00 L2 loss: 0.56572 Learning rate: 0.0004 Mask loss: 0.11296 RPN box loss: 0.01159 RPN score loss: 0.00398 RPN total loss: 0.01557 Total loss: 0.84348 timestamp: 1655064312.074287 iteration: 70420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08592 FastRCNN class loss: 0.04811 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.56572 Learning rate: 0.0004 Mask loss: 0.12829 RPN box loss: 0.02757 RPN score loss: 0.00226 RPN total loss: 0.02984 Total loss: 0.85789 timestamp: 1655064315.3501952 iteration: 70425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.06616 FastRCNN total loss: 0.13146 L1 loss: 0.0000e+00 L2 loss: 0.56572 Learning rate: 0.0004 Mask loss: 0.15777 RPN box loss: 0.00833 RPN score loss: 0.01096 RPN total loss: 0.01929 Total loss: 0.87423 timestamp: 1655064318.5445602 iteration: 70430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17885 FastRCNN class loss: 0.08717 FastRCNN total loss: 0.26602 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.16369 RPN box loss: 0.01722 RPN score loss: 0.00475 RPN total loss: 0.02196 Total loss: 1.01739 timestamp: 1655064321.8375459 iteration: 70435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07802 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.15374 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.1831 RPN box loss: 0.01722 RPN score loss: 0.00726 RPN total loss: 0.02448 Total loss: 0.92704 timestamp: 1655064325.1186717 iteration: 70440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11327 FastRCNN class loss: 0.05988 FastRCNN total loss: 0.17315 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.16952 RPN box loss: 0.00474 RPN score loss: 0.00258 RPN total loss: 0.00732 Total loss: 0.91569 timestamp: 1655064328.3650863 iteration: 70445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09194 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.14043 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.1573 RPN box loss: 0.00847 RPN score loss: 0.00651 RPN total loss: 0.01498 Total loss: 0.87842 timestamp: 1655064331.5932157 iteration: 70450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0775 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.12696 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.14503 RPN box loss: 0.011 RPN score loss: 0.00928 RPN total loss: 0.02028 Total loss: 0.85798 timestamp: 1655064334.8961728 iteration: 70455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13383 FastRCNN class loss: 0.16676 FastRCNN total loss: 0.30059 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.18281 RPN box loss: 0.02705 RPN score loss: 0.0155 RPN total loss: 0.04255 Total loss: 1.09166 timestamp: 1655064338.1474454 iteration: 70460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.07194 FastRCNN total loss: 0.16206 L1 loss: 0.0000e+00 L2 loss: 0.56571 Learning rate: 0.0004 Mask loss: 0.15973 RPN box loss: 0.01361 RPN score loss: 0.01093 RPN total loss: 0.02454 Total loss: 0.91204 timestamp: 1655064341.4097486 iteration: 70465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.03574 FastRCNN total loss: 0.1144 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.13474 RPN box loss: 0.00261 RPN score loss: 0.00135 RPN total loss: 0.00396 Total loss: 0.8188 timestamp: 1655064344.7018683 iteration: 70470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.15552 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.14011 RPN box loss: 0.01779 RPN score loss: 0.01264 RPN total loss: 0.03043 Total loss: 0.89177 timestamp: 1655064348.0111516 iteration: 70475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0969 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.15176 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.13644 RPN box loss: 0.01148 RPN score loss: 0.002 RPN total loss: 0.01347 Total loss: 0.86737 timestamp: 1655064351.2831576 iteration: 70480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11155 FastRCNN class loss: 0.08742 FastRCNN total loss: 0.19897 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.14752 RPN box loss: 0.01962 RPN score loss: 0.00605 RPN total loss: 0.02568 Total loss: 0.93786 timestamp: 1655064354.5652947 iteration: 70485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10907 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.17573 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.13419 RPN box loss: 0.01268 RPN score loss: 0.00798 RPN total loss: 0.02066 Total loss: 0.89627 timestamp: 1655064357.8166027 iteration: 70490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.03942 FastRCNN total loss: 0.11014 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.10924 RPN box loss: 0.01143 RPN score loss: 0.01064 RPN total loss: 0.02207 Total loss: 0.80714 timestamp: 1655064361.0966556 iteration: 70495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11653 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.19326 L1 loss: 0.0000e+00 L2 loss: 0.5657 Learning rate: 0.0004 Mask loss: 0.16569 RPN box loss: 0.01579 RPN score loss: 0.00738 RPN total loss: 0.02317 Total loss: 0.94781 timestamp: 1655064364.394591 iteration: 70500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.20977 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.14176 RPN box loss: 0.01433 RPN score loss: 0.00114 RPN total loss: 0.01547 Total loss: 0.93269 timestamp: 1655064367.8243837 iteration: 70505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08711 FastRCNN class loss: 0.04068 FastRCNN total loss: 0.12778 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.13272 RPN box loss: 0.00327 RPN score loss: 0.00244 RPN total loss: 0.00571 Total loss: 0.83191 timestamp: 1655064371.0883906 iteration: 70510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09858 FastRCNN class loss: 0.08487 FastRCNN total loss: 0.18345 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.12992 RPN box loss: 0.00935 RPN score loss: 0.00642 RPN total loss: 0.01577 Total loss: 0.89483 timestamp: 1655064374.4155765 iteration: 70515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10371 FastRCNN class loss: 0.10331 FastRCNN total loss: 0.20701 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.16598 RPN box loss: 0.018 RPN score loss: 0.00437 RPN total loss: 0.02237 Total loss: 0.96105 timestamp: 1655064377.6353567 iteration: 70520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05745 FastRCNN class loss: 0.03227 FastRCNN total loss: 0.08973 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.1297 RPN box loss: 0.02125 RPN score loss: 0.00217 RPN total loss: 0.02342 Total loss: 0.80853 timestamp: 1655064380.9118211 iteration: 70525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13354 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.20527 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.12361 RPN box loss: 0.01457 RPN score loss: 0.00328 RPN total loss: 0.01784 Total loss: 0.91241 timestamp: 1655064384.1714258 iteration: 70530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08015 FastRCNN class loss: 0.07784 FastRCNN total loss: 0.15799 L1 loss: 0.0000e+00 L2 loss: 0.56569 Learning rate: 0.0004 Mask loss: 0.1541 RPN box loss: 0.01495 RPN score loss: 0.00284 RPN total loss: 0.01778 Total loss: 0.89556 timestamp: 1655064387.438203 iteration: 70535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.13478 L1 loss: 0.0000e+00 L2 loss: 0.56568 Learning rate: 0.0004 Mask loss: 0.16081 RPN box loss: 0.0102 RPN score loss: 0.00244 RPN total loss: 0.01264 Total loss: 0.87392 timestamp: 1655064390.7953522 iteration: 70540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07583 FastRCNN class loss: 0.04459 FastRCNN total loss: 0.12042 L1 loss: 0.0000e+00 L2 loss: 0.56568 Learning rate: 0.0004 Mask loss: 0.06646 RPN box loss: 0.00461 RPN score loss: 0.00164 RPN total loss: 0.00625 Total loss: 0.7588 timestamp: 1655064394.0812829 iteration: 70545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1124 FastRCNN class loss: 0.06584 FastRCNN total loss: 0.17824 L1 loss: 0.0000e+00 L2 loss: 0.56568 Learning rate: 0.0004 Mask loss: 0.1693 RPN box loss: 0.03808 RPN score loss: 0.01744 RPN total loss: 0.05552 Total loss: 0.96874 timestamp: 1655064397.4165232 iteration: 70550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10454 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.17608 L1 loss: 0.0000e+00 L2 loss: 0.56568 Learning rate: 0.0004 Mask loss: 0.1225 RPN box loss: 0.01634 RPN score loss: 0.00547 RPN total loss: 0.02181 Total loss: 0.88607 timestamp: 1655064400.8157275 iteration: 70555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07277 FastRCNN class loss: 0.06349 FastRCNN total loss: 0.13626 L1 loss: 0.0000e+00 L2 loss: 0.56568 Learning rate: 0.0004 Mask loss: 0.15004 RPN box loss: 0.01888 RPN score loss: 0.00278 RPN total loss: 0.02167 Total loss: 0.87364 timestamp: 1655064404.002987 iteration: 70560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14514 FastRCNN class loss: 0.11465 FastRCNN total loss: 0.25978 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.20777 RPN box loss: 0.01535 RPN score loss: 0.00966 RPN total loss: 0.02502 Total loss: 1.05825 timestamp: 1655064407.2431257 iteration: 70565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05672 FastRCNN class loss: 0.05358 FastRCNN total loss: 0.1103 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.14283 RPN box loss: 0.00829 RPN score loss: 0.00385 RPN total loss: 0.01214 Total loss: 0.83095 timestamp: 1655064410.5891664 iteration: 70570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08242 FastRCNN class loss: 0.06655 FastRCNN total loss: 0.14896 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.25567 RPN box loss: 0.0045 RPN score loss: 0.007 RPN total loss: 0.0115 Total loss: 0.9818 timestamp: 1655064413.9026 iteration: 70575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06891 FastRCNN class loss: 0.03908 FastRCNN total loss: 0.108 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.14587 RPN box loss: 0.00774 RPN score loss: 0.00589 RPN total loss: 0.01363 Total loss: 0.83316 timestamp: 1655064417.136397 iteration: 70580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08311 FastRCNN class loss: 0.08022 FastRCNN total loss: 0.16332 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.14035 RPN box loss: 0.01218 RPN score loss: 0.00325 RPN total loss: 0.01543 Total loss: 0.88477 timestamp: 1655064420.4402072 iteration: 70585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11994 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.18969 L1 loss: 0.0000e+00 L2 loss: 0.56567 Learning rate: 0.0004 Mask loss: 0.22754 RPN box loss: 0.00617 RPN score loss: 0.00525 RPN total loss: 0.01142 Total loss: 0.99432 timestamp: 1655064423.698084 iteration: 70590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0671 FastRCNN class loss: 0.05181 FastRCNN total loss: 0.11891 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.13985 RPN box loss: 0.01219 RPN score loss: 0.00314 RPN total loss: 0.01532 Total loss: 0.83974 timestamp: 1655064426.9473364 iteration: 70595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09641 FastRCNN class loss: 0.07067 FastRCNN total loss: 0.16708 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.12787 RPN box loss: 0.01223 RPN score loss: 0.00631 RPN total loss: 0.01853 Total loss: 0.87914 timestamp: 1655064430.1812396 iteration: 70600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18026 FastRCNN class loss: 0.08305 FastRCNN total loss: 0.26331 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.12953 RPN box loss: 0.02105 RPN score loss: 0.00826 RPN total loss: 0.02932 Total loss: 0.98782 timestamp: 1655064433.516068 iteration: 70605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10592 FastRCNN class loss: 0.06684 FastRCNN total loss: 0.17275 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.0991 RPN box loss: 0.00728 RPN score loss: 0.01106 RPN total loss: 0.01834 Total loss: 0.85584 timestamp: 1655064436.7446396 iteration: 70610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10491 FastRCNN class loss: 0.07651 FastRCNN total loss: 0.18142 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.11376 RPN box loss: 0.02655 RPN score loss: 0.00569 RPN total loss: 0.03224 Total loss: 0.89308 timestamp: 1655064440.0320082 iteration: 70615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09433 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.15291 L1 loss: 0.0000e+00 L2 loss: 0.56566 Learning rate: 0.0004 Mask loss: 0.16016 RPN box loss: 0.02391 RPN score loss: 0.00404 RPN total loss: 0.02795 Total loss: 0.90668 timestamp: 1655064443.267513 iteration: 70620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.10251 FastRCNN total loss: 0.19534 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.16391 RPN box loss: 0.01074 RPN score loss: 0.00576 RPN total loss: 0.0165 Total loss: 0.9414 timestamp: 1655064446.5701013 iteration: 70625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09319 FastRCNN class loss: 0.06059 FastRCNN total loss: 0.15377 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.1459 RPN box loss: 0.00758 RPN score loss: 0.00154 RPN total loss: 0.00913 Total loss: 0.87445 timestamp: 1655064449.8128707 iteration: 70630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08922 FastRCNN class loss: 0.04606 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.11041 RPN box loss: 0.02959 RPN score loss: 0.00314 RPN total loss: 0.03273 Total loss: 0.84408 timestamp: 1655064453.1396086 iteration: 70635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08046 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.13952 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.10641 RPN box loss: 0.00714 RPN score loss: 0.00295 RPN total loss: 0.01009 Total loss: 0.82166 timestamp: 1655064456.4026887 iteration: 70640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1258 FastRCNN class loss: 0.09414 FastRCNN total loss: 0.21993 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.16639 RPN box loss: 0.02451 RPN score loss: 0.00388 RPN total loss: 0.02839 Total loss: 0.98036 timestamp: 1655064459.5989175 iteration: 70645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1441 FastRCNN class loss: 0.07922 FastRCNN total loss: 0.22332 L1 loss: 0.0000e+00 L2 loss: 0.56565 Learning rate: 0.0004 Mask loss: 0.15856 RPN box loss: 0.00772 RPN score loss: 0.00227 RPN total loss: 0.00999 Total loss: 0.95752 timestamp: 1655064462.7741995 iteration: 70650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0767 FastRCNN class loss: 0.04971 FastRCNN total loss: 0.12641 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.15972 RPN box loss: 0.01318 RPN score loss: 0.005 RPN total loss: 0.01818 Total loss: 0.86995 timestamp: 1655064466.0474637 iteration: 70655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04844 FastRCNN class loss: 0.05735 FastRCNN total loss: 0.10578 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.10446 RPN box loss: 0.00326 RPN score loss: 0.0034 RPN total loss: 0.00666 Total loss: 0.78254 timestamp: 1655064469.3120775 iteration: 70660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1028 FastRCNN class loss: 0.08602 FastRCNN total loss: 0.18881 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.16125 RPN box loss: 0.01436 RPN score loss: 0.0051 RPN total loss: 0.01946 Total loss: 0.93517 timestamp: 1655064472.5650403 iteration: 70665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06782 FastRCNN class loss: 0.05439 FastRCNN total loss: 0.12222 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.13418 RPN box loss: 0.00965 RPN score loss: 0.00749 RPN total loss: 0.01714 Total loss: 0.83918 timestamp: 1655064475.8000078 iteration: 70670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08642 FastRCNN class loss: 0.08428 FastRCNN total loss: 0.1707 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.11863 RPN box loss: 0.01045 RPN score loss: 0.00141 RPN total loss: 0.01186 Total loss: 0.86683 timestamp: 1655064479.0186388 iteration: 70675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07682 FastRCNN class loss: 0.04109 FastRCNN total loss: 0.11791 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.14105 RPN box loss: 0.00276 RPN score loss: 0.00053 RPN total loss: 0.00329 Total loss: 0.82789 timestamp: 1655064482.2761366 iteration: 70680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17896 FastRCNN class loss: 0.07473 FastRCNN total loss: 0.25369 L1 loss: 0.0000e+00 L2 loss: 0.56564 Learning rate: 0.0004 Mask loss: 0.11099 RPN box loss: 0.01361 RPN score loss: 0.00313 RPN total loss: 0.01674 Total loss: 0.94706 timestamp: 1655064485.6195693 iteration: 70685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.18332 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.14635 RPN box loss: 0.02749 RPN score loss: 0.00657 RPN total loss: 0.03405 Total loss: 0.92935 timestamp: 1655064488.9447377 iteration: 70690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12741 FastRCNN class loss: 0.10594 FastRCNN total loss: 0.23335 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.17716 RPN box loss: 0.01391 RPN score loss: 0.01033 RPN total loss: 0.02424 Total loss: 1.00039 timestamp: 1655064492.25576 iteration: 70695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10654 FastRCNN class loss: 0.09663 FastRCNN total loss: 0.20318 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.18548 RPN box loss: 0.02709 RPN score loss: 0.00168 RPN total loss: 0.02877 Total loss: 0.98305 timestamp: 1655064495.572282 iteration: 70700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14521 FastRCNN class loss: 0.07988 FastRCNN total loss: 0.22509 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.173 RPN box loss: 0.00939 RPN score loss: 0.00226 RPN total loss: 0.01164 Total loss: 0.97537 timestamp: 1655064498.8195145 iteration: 70705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05042 FastRCNN class loss: 0.03873 FastRCNN total loss: 0.08915 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.08085 RPN box loss: 0.00369 RPN score loss: 0.0032 RPN total loss: 0.00689 Total loss: 0.74251 timestamp: 1655064502.0787592 iteration: 70710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.04427 FastRCNN total loss: 0.10992 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.12675 RPN box loss: 0.00519 RPN score loss: 0.00649 RPN total loss: 0.01168 Total loss: 0.81398 timestamp: 1655064505.3867679 iteration: 70715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06651 FastRCNN class loss: 0.04619 FastRCNN total loss: 0.1127 L1 loss: 0.0000e+00 L2 loss: 0.56563 Learning rate: 0.0004 Mask loss: 0.11776 RPN box loss: 0.00914 RPN score loss: 0.00491 RPN total loss: 0.01405 Total loss: 0.81013 timestamp: 1655064508.67621 iteration: 70720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17671 FastRCNN class loss: 0.07832 FastRCNN total loss: 0.25503 L1 loss: 0.0000e+00 L2 loss: 0.56562 Learning rate: 0.0004 Mask loss: 0.13118 RPN box loss: 0.02085 RPN score loss: 0.01204 RPN total loss: 0.03289 Total loss: 0.98472 timestamp: 1655064511.952098 iteration: 70725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07912 FastRCNN class loss: 0.0394 FastRCNN total loss: 0.11851 L1 loss: 0.0000e+00 L2 loss: 0.56562 Learning rate: 0.0004 Mask loss: 0.12174 RPN box loss: 0.00978 RPN score loss: 0.00117 RPN total loss: 0.01095 Total loss: 0.81682 timestamp: 1655064515.2304845 iteration: 70730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.05332 FastRCNN total loss: 0.13202 L1 loss: 0.0000e+00 L2 loss: 0.56562 Learning rate: 0.0004 Mask loss: 0.12834 RPN box loss: 0.0239 RPN score loss: 0.00319 RPN total loss: 0.02709 Total loss: 0.85307 timestamp: 1655064518.5525365 iteration: 70735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07465 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.14619 L1 loss: 0.0000e+00 L2 loss: 0.56562 Learning rate: 0.0004 Mask loss: 0.10131 RPN box loss: 0.00687 RPN score loss: 0.0026 RPN total loss: 0.00947 Total loss: 0.82258 timestamp: 1655064521.8037348 iteration: 70740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06591 FastRCNN class loss: 0.03672 FastRCNN total loss: 0.10262 L1 loss: 0.0000e+00 L2 loss: 0.56562 Learning rate: 0.0004 Mask loss: 0.10361 RPN box loss: 0.00498 RPN score loss: 0.00196 RPN total loss: 0.00695 Total loss: 0.77879 timestamp: 1655064525.0270805 iteration: 70745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07019 FastRCNN class loss: 0.0546 FastRCNN total loss: 0.12479 L1 loss: 0.0000e+00 L2 loss: 0.56561 Learning rate: 0.0004 Mask loss: 0.13337 RPN box loss: 0.02014 RPN score loss: 0.00253 RPN total loss: 0.02268 Total loss: 0.84645 timestamp: 1655064528.3024027 iteration: 70750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11716 FastRCNN class loss: 0.1125 FastRCNN total loss: 0.22966 L1 loss: 0.0000e+00 L2 loss: 0.56561 Learning rate: 0.0004 Mask loss: 0.15265 RPN box loss: 0.02272 RPN score loss: 0.00886 RPN total loss: 0.03158 Total loss: 0.9795 timestamp: 1655064531.539516 iteration: 70755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07083 FastRCNN class loss: 0.09898 FastRCNN total loss: 0.16981 L1 loss: 0.0000e+00 L2 loss: 0.56561 Learning rate: 0.0004 Mask loss: 0.15283 RPN box loss: 0.01756 RPN score loss: 0.00466 RPN total loss: 0.02222 Total loss: 0.91047 timestamp: 1655064534.811396 iteration: 70760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07009 FastRCNN class loss: 0.08437 FastRCNN total loss: 0.15446 L1 loss: 0.0000e+00 L2 loss: 0.56561 Learning rate: 0.0004 Mask loss: 0.1357 RPN box loss: 0.00972 RPN score loss: 0.0064 RPN total loss: 0.01613 Total loss: 0.87189 timestamp: 1655064538.0647676 iteration: 70765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14148 FastRCNN class loss: 0.06143 FastRCNN total loss: 0.20291 L1 loss: 0.0000e+00 L2 loss: 0.56561 Learning rate: 0.0004 Mask loss: 0.173 RPN box loss: 0.00762 RPN score loss: 0.00679 RPN total loss: 0.01441 Total loss: 0.95592 timestamp: 1655064541.3225632 iteration: 70770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15723 FastRCNN class loss: 0.08991 FastRCNN total loss: 0.24715 L1 loss: 0.0000e+00 L2 loss: 0.5656 Learning rate: 0.0004 Mask loss: 0.16094 RPN box loss: 0.01298 RPN score loss: 0.00253 RPN total loss: 0.01551 Total loss: 0.9892 timestamp: 1655064544.692311 iteration: 70775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0657 FastRCNN class loss: 0.05682 FastRCNN total loss: 0.12251 L1 loss: 0.0000e+00 L2 loss: 0.5656 Learning rate: 0.0004 Mask loss: 0.11606 RPN box loss: 0.01969 RPN score loss: 0.00453 RPN total loss: 0.02422 Total loss: 0.8284 timestamp: 1655064548.0355346 iteration: 70780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05367 FastRCNN class loss: 0.03291 FastRCNN total loss: 0.08659 L1 loss: 0.0000e+00 L2 loss: 0.5656 Learning rate: 0.0004 Mask loss: 0.14303 RPN box loss: 0.00667 RPN score loss: 0.00323 RPN total loss: 0.00989 Total loss: 0.80511 timestamp: 1655064551.2869964 iteration: 70785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10312 FastRCNN class loss: 0.0701 FastRCNN total loss: 0.17322 L1 loss: 0.0000e+00 L2 loss: 0.5656 Learning rate: 0.0004 Mask loss: 0.16993 RPN box loss: 0.01274 RPN score loss: 0.00984 RPN total loss: 0.02259 Total loss: 0.93134 timestamp: 1655064554.4742656 iteration: 70790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07343 FastRCNN class loss: 0.08132 FastRCNN total loss: 0.15475 L1 loss: 0.0000e+00 L2 loss: 0.5656 Learning rate: 0.0004 Mask loss: 0.1247 RPN box loss: 0.00725 RPN score loss: 0.00785 RPN total loss: 0.0151 Total loss: 0.86014 timestamp: 1655064557.8093185 iteration: 70795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06663 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.13379 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.15358 RPN box loss: 0.00862 RPN score loss: 0.00369 RPN total loss: 0.01231 Total loss: 0.86527 timestamp: 1655064561.061901 iteration: 70800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12907 FastRCNN class loss: 0.06174 FastRCNN total loss: 0.19081 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.11011 RPN box loss: 0.02094 RPN score loss: 0.0056 RPN total loss: 0.02654 Total loss: 0.89305 timestamp: 1655064564.3539865 iteration: 70805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12293 FastRCNN class loss: 0.07042 FastRCNN total loss: 0.19335 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.15329 RPN box loss: 0.02532 RPN score loss: 0.0039 RPN total loss: 0.02923 Total loss: 0.94146 timestamp: 1655064567.5699518 iteration: 70810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07684 FastRCNN class loss: 0.03529 FastRCNN total loss: 0.11212 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.13305 RPN box loss: 0.00303 RPN score loss: 0.00136 RPN total loss: 0.00439 Total loss: 0.81516 timestamp: 1655064570.8203177 iteration: 70815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09926 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.17009 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.17137 RPN box loss: 0.01605 RPN score loss: 0.00408 RPN total loss: 0.02013 Total loss: 0.92718 timestamp: 1655064574.0877733 iteration: 70820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12482 FastRCNN class loss: 0.10243 FastRCNN total loss: 0.22724 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.17326 RPN box loss: 0.01126 RPN score loss: 0.00662 RPN total loss: 0.01788 Total loss: 0.98397 timestamp: 1655064577.2758524 iteration: 70825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13281 FastRCNN class loss: 0.07579 FastRCNN total loss: 0.20861 L1 loss: 0.0000e+00 L2 loss: 0.56559 Learning rate: 0.0004 Mask loss: 0.14859 RPN box loss: 0.01292 RPN score loss: 0.00903 RPN total loss: 0.02195 Total loss: 0.94473 timestamp: 1655064580.5318105 iteration: 70830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.17571 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.13821 RPN box loss: 0.00313 RPN score loss: 0.00396 RPN total loss: 0.0071 Total loss: 0.8866 timestamp: 1655064583.775316 iteration: 70835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05251 FastRCNN class loss: 0.05833 FastRCNN total loss: 0.11084 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.1153 RPN box loss: 0.0097 RPN score loss: 0.00548 RPN total loss: 0.01517 Total loss: 0.8069 timestamp: 1655064586.9998636 iteration: 70840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11996 FastRCNN class loss: 0.06381 FastRCNN total loss: 0.18377 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.13981 RPN box loss: 0.01077 RPN score loss: 0.005 RPN total loss: 0.01577 Total loss: 0.90493 timestamp: 1655064590.1800368 iteration: 70845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05977 FastRCNN class loss: 0.06407 FastRCNN total loss: 0.12384 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.10378 RPN box loss: 0.01 RPN score loss: 0.00639 RPN total loss: 0.01639 Total loss: 0.80959 timestamp: 1655064593.484266 iteration: 70850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05313 FastRCNN class loss: 0.06681 FastRCNN total loss: 0.11995 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.10415 RPN box loss: 0.00678 RPN score loss: 0.00344 RPN total loss: 0.01021 Total loss: 0.79989 timestamp: 1655064596.7712603 iteration: 70855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09629 FastRCNN class loss: 0.0754 FastRCNN total loss: 0.17169 L1 loss: 0.0000e+00 L2 loss: 0.56558 Learning rate: 0.0004 Mask loss: 0.12029 RPN box loss: 0.00847 RPN score loss: 0.00241 RPN total loss: 0.01089 Total loss: 0.86844 timestamp: 1655064600.0348063 iteration: 70860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0933 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.1765 L1 loss: 0.0000e+00 L2 loss: 0.56557 Learning rate: 0.0004 Mask loss: 0.13517 RPN box loss: 0.01174 RPN score loss: 0.00987 RPN total loss: 0.02161 Total loss: 0.89885 timestamp: 1655064603.3386805 iteration: 70865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07426 FastRCNN class loss: 0.07337 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.56557 Learning rate: 0.0004 Mask loss: 0.14081 RPN box loss: 0.01019 RPN score loss: 0.00497 RPN total loss: 0.01515 Total loss: 0.86917 timestamp: 1655064606.658168 iteration: 70870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08601 FastRCNN class loss: 0.0865 FastRCNN total loss: 0.17252 L1 loss: 0.0000e+00 L2 loss: 0.56557 Learning rate: 0.0004 Mask loss: 0.14273 RPN box loss: 0.01383 RPN score loss: 0.0076 RPN total loss: 0.02143 Total loss: 0.90225 timestamp: 1655064609.9653435 iteration: 70875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12797 FastRCNN class loss: 0.07618 FastRCNN total loss: 0.20415 L1 loss: 0.0000e+00 L2 loss: 0.56557 Learning rate: 0.0004 Mask loss: 0.13409 RPN box loss: 0.00963 RPN score loss: 0.00824 RPN total loss: 0.01787 Total loss: 0.92169 timestamp: 1655064613.1764812 iteration: 70880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13594 FastRCNN class loss: 0.12328 FastRCNN total loss: 0.25922 L1 loss: 0.0000e+00 L2 loss: 0.56557 Learning rate: 0.0004 Mask loss: 0.24499 RPN box loss: 0.01777 RPN score loss: 0.01103 RPN total loss: 0.02881 Total loss: 1.09858 timestamp: 1655064616.4627407 iteration: 70885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0847 FastRCNN class loss: 0.09107 FastRCNN total loss: 0.17578 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.14378 RPN box loss: 0.01513 RPN score loss: 0.00623 RPN total loss: 0.02136 Total loss: 0.90648 timestamp: 1655064619.751588 iteration: 70890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09014 FastRCNN class loss: 0.059 FastRCNN total loss: 0.14914 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.1895 RPN box loss: 0.01077 RPN score loss: 0.00922 RPN total loss: 0.01999 Total loss: 0.92419 timestamp: 1655064623.0527847 iteration: 70895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07537 FastRCNN class loss: 0.05211 FastRCNN total loss: 0.12747 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.09484 RPN box loss: 0.01283 RPN score loss: 0.00478 RPN total loss: 0.01761 Total loss: 0.80548 timestamp: 1655064626.3523235 iteration: 70900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07724 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.152 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.20921 RPN box loss: 0.01927 RPN score loss: 0.01916 RPN total loss: 0.03843 Total loss: 0.9652 timestamp: 1655064629.6235092 iteration: 70905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07852 FastRCNN class loss: 0.04383 FastRCNN total loss: 0.12235 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.09521 RPN box loss: 0.00555 RPN score loss: 0.00374 RPN total loss: 0.00929 Total loss: 0.79241 timestamp: 1655064632.9091566 iteration: 70910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1133 FastRCNN class loss: 0.06932 FastRCNN total loss: 0.18262 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.16894 RPN box loss: 0.02685 RPN score loss: 0.015 RPN total loss: 0.04185 Total loss: 0.95897 timestamp: 1655064636.2345247 iteration: 70915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07557 FastRCNN class loss: 0.07153 FastRCNN total loss: 0.1471 L1 loss: 0.0000e+00 L2 loss: 0.56556 Learning rate: 0.0004 Mask loss: 0.09244 RPN box loss: 0.0194 RPN score loss: 0.01156 RPN total loss: 0.03096 Total loss: 0.83605 timestamp: 1655064639.514911 iteration: 70920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05072 FastRCNN class loss: 0.04705 FastRCNN total loss: 0.09777 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.08436 RPN box loss: 0.00463 RPN score loss: 0.00149 RPN total loss: 0.00613 Total loss: 0.75381 timestamp: 1655064642.8454287 iteration: 70925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05443 FastRCNN class loss: 0.04372 FastRCNN total loss: 0.09815 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.14341 RPN box loss: 0.00365 RPN score loss: 0.00909 RPN total loss: 0.01273 Total loss: 0.81985 timestamp: 1655064646.1284814 iteration: 70930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07127 FastRCNN class loss: 0.05144 FastRCNN total loss: 0.12271 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.11391 RPN box loss: 0.01026 RPN score loss: 0.00517 RPN total loss: 0.01543 Total loss: 0.81761 timestamp: 1655064649.4615388 iteration: 70935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15667 FastRCNN class loss: 0.10231 FastRCNN total loss: 0.25898 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.16567 RPN box loss: 0.01917 RPN score loss: 0.01057 RPN total loss: 0.02974 Total loss: 1.01993 timestamp: 1655064652.6991007 iteration: 70940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1131 FastRCNN class loss: 0.07227 FastRCNN total loss: 0.18537 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.13553 RPN box loss: 0.00741 RPN score loss: 0.00543 RPN total loss: 0.01284 Total loss: 0.89928 timestamp: 1655064655.9536345 iteration: 70945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08206 FastRCNN class loss: 0.05472 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 0.56555 Learning rate: 0.0004 Mask loss: 0.13989 RPN box loss: 0.00311 RPN score loss: 0.0034 RPN total loss: 0.00651 Total loss: 0.84873 timestamp: 1655064659.2366097 iteration: 70950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1126 FastRCNN class loss: 0.12002 FastRCNN total loss: 0.23262 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.19159 RPN box loss: 0.02224 RPN score loss: 0.00595 RPN total loss: 0.02819 Total loss: 1.01795 timestamp: 1655064662.5537825 iteration: 70955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07635 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.14819 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.09429 RPN box loss: 0.02241 RPN score loss: 0.00628 RPN total loss: 0.02869 Total loss: 0.83672 timestamp: 1655064665.8468535 iteration: 70960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12207 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.21074 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.01093 RPN score loss: 0.01131 RPN total loss: 0.02224 Total loss: 0.94327 timestamp: 1655064669.0661879 iteration: 70965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08177 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.14871 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.15313 RPN box loss: 0.01174 RPN score loss: 0.00501 RPN total loss: 0.01675 Total loss: 0.88414 timestamp: 1655064672.3521876 iteration: 70970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09028 FastRCNN class loss: 0.06235 FastRCNN total loss: 0.15263 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.1507 RPN box loss: 0.01497 RPN score loss: 0.01278 RPN total loss: 0.02775 Total loss: 0.89662 timestamp: 1655064675.625737 iteration: 70975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09006 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.15952 L1 loss: 0.0000e+00 L2 loss: 0.56554 Learning rate: 0.0004 Mask loss: 0.11634 RPN box loss: 0.01052 RPN score loss: 0.00338 RPN total loss: 0.0139 Total loss: 0.8553 timestamp: 1655064678.870089 iteration: 70980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07695 FastRCNN class loss: 0.05837 FastRCNN total loss: 0.13532 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.11517 RPN box loss: 0.00646 RPN score loss: 0.00402 RPN total loss: 0.01048 Total loss: 0.8265 timestamp: 1655064682.1535234 iteration: 70985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0237 FastRCNN class loss: 0.03716 FastRCNN total loss: 0.06086 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.18426 RPN box loss: 0.00595 RPN score loss: 0.00713 RPN total loss: 0.01309 Total loss: 0.82374 timestamp: 1655064685.4205155 iteration: 70990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09085 FastRCNN class loss: 0.06368 FastRCNN total loss: 0.15453 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.12134 RPN box loss: 0.00951 RPN score loss: 0.00288 RPN total loss: 0.01239 Total loss: 0.8538 timestamp: 1655064688.7269866 iteration: 70995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11966 FastRCNN class loss: 0.07419 FastRCNN total loss: 0.19385 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.15558 RPN box loss: 0.02567 RPN score loss: 0.01122 RPN total loss: 0.03689 Total loss: 0.95185 timestamp: 1655064691.953163 iteration: 71000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12289 FastRCNN class loss: 0.05583 FastRCNN total loss: 0.17872 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.10725 RPN box loss: 0.02002 RPN score loss: 0.00669 RPN total loss: 0.02671 Total loss: 0.87822 timestamp: 1655064695.2413514 iteration: 71005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07154 FastRCNN class loss: 0.05479 FastRCNN total loss: 0.12633 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.1273 RPN box loss: 0.02121 RPN score loss: 0.00715 RPN total loss: 0.02836 Total loss: 0.84751 timestamp: 1655064698.5790002 iteration: 71010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12576 FastRCNN class loss: 0.06458 FastRCNN total loss: 0.19034 L1 loss: 0.0000e+00 L2 loss: 0.56553 Learning rate: 0.0004 Mask loss: 0.16023 RPN box loss: 0.01936 RPN score loss: 0.00444 RPN total loss: 0.0238 Total loss: 0.93989 timestamp: 1655064701.874694 iteration: 71015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05262 FastRCNN class loss: 0.03699 FastRCNN total loss: 0.08962 L1 loss: 0.0000e+00 L2 loss: 0.56552 Learning rate: 0.0004 Mask loss: 0.13003 RPN box loss: 0.00268 RPN score loss: 0.00526 RPN total loss: 0.00794 Total loss: 0.79311 timestamp: 1655064705.1590912 iteration: 71020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13047 FastRCNN class loss: 0.10095 FastRCNN total loss: 0.23142 L1 loss: 0.0000e+00 L2 loss: 0.56552 Learning rate: 0.0004 Mask loss: 0.24593 RPN box loss: 0.01642 RPN score loss: 0.00904 RPN total loss: 0.02546 Total loss: 1.06833 timestamp: 1655064708.4370298 iteration: 71025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07826 FastRCNN class loss: 0.08024 FastRCNN total loss: 0.1585 L1 loss: 0.0000e+00 L2 loss: 0.56552 Learning rate: 0.0004 Mask loss: 0.09834 RPN box loss: 0.01147 RPN score loss: 0.00581 RPN total loss: 0.01728 Total loss: 0.83964 timestamp: 1655064711.7036765 iteration: 71030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04855 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.11028 L1 loss: 0.0000e+00 L2 loss: 0.56552 Learning rate: 0.0004 Mask loss: 0.13963 RPN box loss: 0.04562 RPN score loss: 0.00989 RPN total loss: 0.05551 Total loss: 0.87093 timestamp: 1655064714.9723482 iteration: 71035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.08214 FastRCNN total loss: 0.18625 L1 loss: 0.0000e+00 L2 loss: 0.56551 Learning rate: 0.0004 Mask loss: 0.15612 RPN box loss: 0.02311 RPN score loss: 0.01004 RPN total loss: 0.03315 Total loss: 0.94103 timestamp: 1655064718.2528906 iteration: 71040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15399 FastRCNN class loss: 0.0773 FastRCNN total loss: 0.23129 L1 loss: 0.0000e+00 L2 loss: 0.56551 Learning rate: 0.0004 Mask loss: 0.15561 RPN box loss: 0.00941 RPN score loss: 0.00925 RPN total loss: 0.01866 Total loss: 0.97108 timestamp: 1655064721.5092518 iteration: 71045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09189 FastRCNN class loss: 0.05147 FastRCNN total loss: 0.14335 L1 loss: 0.0000e+00 L2 loss: 0.56551 Learning rate: 0.0004 Mask loss: 0.13805 RPN box loss: 0.01175 RPN score loss: 0.0028 RPN total loss: 0.01455 Total loss: 0.86147 timestamp: 1655064724.7469563 iteration: 71050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07643 FastRCNN class loss: 0.06381 FastRCNN total loss: 0.14024 L1 loss: 0.0000e+00 L2 loss: 0.56551 Learning rate: 0.0004 Mask loss: 0.1661 RPN box loss: 0.01126 RPN score loss: 0.00337 RPN total loss: 0.01463 Total loss: 0.88648 timestamp: 1655064727.984668 iteration: 71055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05884 FastRCNN class loss: 0.04252 FastRCNN total loss: 0.10137 L1 loss: 0.0000e+00 L2 loss: 0.56551 Learning rate: 0.0004 Mask loss: 0.0922 RPN box loss: 0.0085 RPN score loss: 0.00285 RPN total loss: 0.01135 Total loss: 0.77042 timestamp: 1655064731.2932136 iteration: 71060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.19027 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.12774 RPN box loss: 0.00797 RPN score loss: 0.00215 RPN total loss: 0.01013 Total loss: 0.89363 timestamp: 1655064734.5720868 iteration: 71065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10477 FastRCNN class loss: 0.05881 FastRCNN total loss: 0.16359 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.15379 RPN box loss: 0.01956 RPN score loss: 0.00348 RPN total loss: 0.02304 Total loss: 0.90592 timestamp: 1655064737.843625 iteration: 71070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07198 FastRCNN class loss: 0.08695 FastRCNN total loss: 0.15894 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.15477 RPN box loss: 0.04082 RPN score loss: 0.01269 RPN total loss: 0.05351 Total loss: 0.93272 timestamp: 1655064741.156074 iteration: 71075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11757 FastRCNN class loss: 0.04543 FastRCNN total loss: 0.163 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.15977 RPN box loss: 0.01372 RPN score loss: 0.00287 RPN total loss: 0.0166 Total loss: 0.90487 timestamp: 1655064744.4550982 iteration: 71080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07404 FastRCNN class loss: 0.05578 FastRCNN total loss: 0.12982 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.12193 RPN box loss: 0.00565 RPN score loss: 0.0029 RPN total loss: 0.00855 Total loss: 0.8258 timestamp: 1655064747.6537898 iteration: 71085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11997 FastRCNN class loss: 0.0924 FastRCNN total loss: 0.21237 L1 loss: 0.0000e+00 L2 loss: 0.5655 Learning rate: 0.0004 Mask loss: 0.17943 RPN box loss: 0.00535 RPN score loss: 0.0022 RPN total loss: 0.00756 Total loss: 0.96486 timestamp: 1655064750.99273 iteration: 71090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09781 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.16954 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.17123 RPN box loss: 0.00925 RPN score loss: 0.0081 RPN total loss: 0.01736 Total loss: 0.92362 timestamp: 1655064754.2983124 iteration: 71095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14371 FastRCNN class loss: 0.105 FastRCNN total loss: 0.24871 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.19761 RPN box loss: 0.01612 RPN score loss: 0.00356 RPN total loss: 0.01968 Total loss: 1.0315 timestamp: 1655064757.6299787 iteration: 71100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13708 FastRCNN class loss: 0.06017 FastRCNN total loss: 0.19725 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.19339 RPN box loss: 0.02659 RPN score loss: 0.01071 RPN total loss: 0.0373 Total loss: 0.99343 timestamp: 1655064760.9200323 iteration: 71105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0838 FastRCNN class loss: 0.05725 FastRCNN total loss: 0.14105 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.15962 RPN box loss: 0.02214 RPN score loss: 0.00378 RPN total loss: 0.02592 Total loss: 0.89208 timestamp: 1655064764.1234212 iteration: 71110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1318 FastRCNN class loss: 0.06663 FastRCNN total loss: 0.19842 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.17658 RPN box loss: 0.01908 RPN score loss: 0.00922 RPN total loss: 0.0283 Total loss: 0.96879 timestamp: 1655064767.4355717 iteration: 71115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1177 FastRCNN class loss: 0.08701 FastRCNN total loss: 0.2047 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.14308 RPN box loss: 0.01166 RPN score loss: 0.00415 RPN total loss: 0.01582 Total loss: 0.92909 timestamp: 1655064770.7265747 iteration: 71120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.15294 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.11275 RPN box loss: 0.0146 RPN score loss: 0.00217 RPN total loss: 0.01677 Total loss: 0.84794 timestamp: 1655064773.9731455 iteration: 71125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09508 FastRCNN class loss: 0.06232 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.1362 RPN box loss: 0.00866 RPN score loss: 0.00677 RPN total loss: 0.01543 Total loss: 0.87451 timestamp: 1655064777.274366 iteration: 71130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11893 FastRCNN class loss: 0.02974 FastRCNN total loss: 0.14867 L1 loss: 0.0000e+00 L2 loss: 0.56549 Learning rate: 0.0004 Mask loss: 0.09751 RPN box loss: 0.00644 RPN score loss: 0.0018 RPN total loss: 0.00824 Total loss: 0.8199 timestamp: 1655064780.5184984 iteration: 71135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06492 FastRCNN class loss: 0.06112 FastRCNN total loss: 0.12604 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.14245 RPN box loss: 0.0212 RPN score loss: 0.00378 RPN total loss: 0.02497 Total loss: 0.85894 timestamp: 1655064783.7824109 iteration: 71140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09218 FastRCNN class loss: 0.04096 FastRCNN total loss: 0.13314 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.10814 RPN box loss: 0.00404 RPN score loss: 0.00108 RPN total loss: 0.00513 Total loss: 0.8119 timestamp: 1655064787.0102334 iteration: 71145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13512 FastRCNN class loss: 0.07014 FastRCNN total loss: 0.20526 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.09868 RPN box loss: 0.00836 RPN score loss: 0.00548 RPN total loss: 0.01384 Total loss: 0.88325 timestamp: 1655064790.2964888 iteration: 71150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15568 FastRCNN class loss: 0.10141 FastRCNN total loss: 0.2571 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.17081 RPN box loss: 0.01914 RPN score loss: 0.00653 RPN total loss: 0.02567 Total loss: 1.01906 timestamp: 1655064793.4964836 iteration: 71155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12119 FastRCNN class loss: 0.05402 FastRCNN total loss: 0.17521 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.12927 RPN box loss: 0.00988 RPN score loss: 0.00298 RPN total loss: 0.01286 Total loss: 0.88282 timestamp: 1655064796.7619398 iteration: 71160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07267 FastRCNN class loss: 0.0394 FastRCNN total loss: 0.11207 L1 loss: 0.0000e+00 L2 loss: 0.56548 Learning rate: 0.0004 Mask loss: 0.09543 RPN box loss: 0.01009 RPN score loss: 0.00152 RPN total loss: 0.01161 Total loss: 0.78458 timestamp: 1655064800.0515933 iteration: 71165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08557 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.14935 L1 loss: 0.0000e+00 L2 loss: 0.56547 Learning rate: 0.0004 Mask loss: 0.16407 RPN box loss: 0.00664 RPN score loss: 0.00305 RPN total loss: 0.00969 Total loss: 0.88858 timestamp: 1655064803.2792695 iteration: 71170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10644 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.16914 L1 loss: 0.0000e+00 L2 loss: 0.56547 Learning rate: 0.0004 Mask loss: 0.12358 RPN box loss: 0.01949 RPN score loss: 0.00304 RPN total loss: 0.02253 Total loss: 0.88072 timestamp: 1655064806.5640535 iteration: 71175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17628 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.26279 L1 loss: 0.0000e+00 L2 loss: 0.56547 Learning rate: 0.0004 Mask loss: 0.16824 RPN box loss: 0.01858 RPN score loss: 0.0101 RPN total loss: 0.02869 Total loss: 1.02519 timestamp: 1655064809.8801956 iteration: 71180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12428 FastRCNN class loss: 0.12324 FastRCNN total loss: 0.24752 L1 loss: 0.0000e+00 L2 loss: 0.56547 Learning rate: 0.0004 Mask loss: 0.16407 RPN box loss: 0.0252 RPN score loss: 0.00981 RPN total loss: 0.03501 Total loss: 1.01206 timestamp: 1655064813.12779 iteration: 71185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.19289 L1 loss: 0.0000e+00 L2 loss: 0.56547 Learning rate: 0.0004 Mask loss: 0.15008 RPN box loss: 0.01256 RPN score loss: 0.00547 RPN total loss: 0.01802 Total loss: 0.92646 timestamp: 1655064816.3780513 iteration: 71190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.08479 FastRCNN total loss: 0.19457 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.11664 RPN box loss: 0.01314 RPN score loss: 0.00563 RPN total loss: 0.01877 Total loss: 0.89545 timestamp: 1655064819.6985347 iteration: 71195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06227 FastRCNN class loss: 0.04713 FastRCNN total loss: 0.1094 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.14149 RPN box loss: 0.0179 RPN score loss: 0.00807 RPN total loss: 0.02596 Total loss: 0.84232 timestamp: 1655064823.0025678 iteration: 71200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08019 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.13723 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.1204 RPN box loss: 0.00487 RPN score loss: 0.00258 RPN total loss: 0.00745 Total loss: 0.83054 timestamp: 1655064826.210533 iteration: 71205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09454 FastRCNN class loss: 0.09027 FastRCNN total loss: 0.18481 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.2233 RPN box loss: 0.00604 RPN score loss: 0.01485 RPN total loss: 0.02089 Total loss: 0.99445 timestamp: 1655064829.4868546 iteration: 71210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07988 FastRCNN class loss: 0.03853 FastRCNN total loss: 0.11841 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.09819 RPN box loss: 0.00386 RPN score loss: 0.00111 RPN total loss: 0.00497 Total loss: 0.78702 timestamp: 1655064832.7637522 iteration: 71215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06612 FastRCNN class loss: 0.05969 FastRCNN total loss: 0.12581 L1 loss: 0.0000e+00 L2 loss: 0.56546 Learning rate: 0.0004 Mask loss: 0.1471 RPN box loss: 0.01193 RPN score loss: 0.00298 RPN total loss: 0.01491 Total loss: 0.85327 timestamp: 1655064836.0194442 iteration: 71220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13383 FastRCNN class loss: 0.0884 FastRCNN total loss: 0.22223 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.18215 RPN box loss: 0.01742 RPN score loss: 0.00626 RPN total loss: 0.02368 Total loss: 0.99352 timestamp: 1655064839.260401 iteration: 71225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.04638 FastRCNN total loss: 0.14643 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.13426 RPN box loss: 0.0063 RPN score loss: 0.0015 RPN total loss: 0.0078 Total loss: 0.85394 timestamp: 1655064842.621194 iteration: 71230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08216 FastRCNN class loss: 0.055 FastRCNN total loss: 0.13715 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.14242 RPN box loss: 0.01409 RPN score loss: 0.00963 RPN total loss: 0.02372 Total loss: 0.86874 timestamp: 1655064845.8809159 iteration: 71235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10241 FastRCNN class loss: 0.07064 FastRCNN total loss: 0.17305 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.17923 RPN box loss: 0.00858 RPN score loss: 0.00872 RPN total loss: 0.0173 Total loss: 0.93503 timestamp: 1655064849.1491723 iteration: 71240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13903 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.22548 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.22926 RPN box loss: 0.0165 RPN score loss: 0.00383 RPN total loss: 0.02033 Total loss: 1.04051 timestamp: 1655064852.4862928 iteration: 71245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11637 FastRCNN class loss: 0.07523 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 0.56545 Learning rate: 0.0004 Mask loss: 0.13146 RPN box loss: 0.01257 RPN score loss: 0.00394 RPN total loss: 0.01651 Total loss: 0.90502 timestamp: 1655064855.7545526 iteration: 71250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07919 FastRCNN class loss: 0.05219 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.11657 RPN box loss: 0.00957 RPN score loss: 0.00082 RPN total loss: 0.01039 Total loss: 0.82379 timestamp: 1655064859.0489378 iteration: 71255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10135 FastRCNN class loss: 0.08684 FastRCNN total loss: 0.1882 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.11294 RPN box loss: 0.01784 RPN score loss: 0.00585 RPN total loss: 0.0237 Total loss: 0.89027 timestamp: 1655064862.2857995 iteration: 71260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15435 FastRCNN class loss: 0.08455 FastRCNN total loss: 0.2389 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.13996 RPN box loss: 0.0108 RPN score loss: 0.00206 RPN total loss: 0.01286 Total loss: 0.95716 timestamp: 1655064865.5998726 iteration: 71265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10701 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.19773 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.13557 RPN box loss: 0.01762 RPN score loss: 0.00209 RPN total loss: 0.0197 Total loss: 0.91845 timestamp: 1655064868.8285074 iteration: 71270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05355 FastRCNN class loss: 0.04796 FastRCNN total loss: 0.1015 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.08785 RPN box loss: 0.00535 RPN score loss: 0.00236 RPN total loss: 0.00771 Total loss: 0.7625 timestamp: 1655064872.114681 iteration: 71275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0983 FastRCNN class loss: 0.07103 FastRCNN total loss: 0.16933 L1 loss: 0.0000e+00 L2 loss: 0.56544 Learning rate: 0.0004 Mask loss: 0.10757 RPN box loss: 0.00548 RPN score loss: 0.00433 RPN total loss: 0.00981 Total loss: 0.85215 timestamp: 1655064875.4542208 iteration: 71280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12244 FastRCNN class loss: 0.06509 FastRCNN total loss: 0.18753 L1 loss: 0.0000e+00 L2 loss: 0.56543 Learning rate: 0.0004 Mask loss: 0.18653 RPN box loss: 0.01582 RPN score loss: 0.00464 RPN total loss: 0.02046 Total loss: 0.95996 timestamp: 1655064878.7056916 iteration: 71285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07844 FastRCNN class loss: 0.06921 FastRCNN total loss: 0.14765 L1 loss: 0.0000e+00 L2 loss: 0.56543 Learning rate: 0.0004 Mask loss: 0.16507 RPN box loss: 0.0077 RPN score loss: 0.00334 RPN total loss: 0.01104 Total loss: 0.88919 timestamp: 1655064882.0329309 iteration: 71290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08272 FastRCNN class loss: 0.04533 FastRCNN total loss: 0.12805 L1 loss: 0.0000e+00 L2 loss: 0.56543 Learning rate: 0.0004 Mask loss: 0.13493 RPN box loss: 0.01733 RPN score loss: 0.00289 RPN total loss: 0.02023 Total loss: 0.84864 timestamp: 1655064885.2979145 iteration: 71295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1079 FastRCNN class loss: 0.0708 FastRCNN total loss: 0.1787 L1 loss: 0.0000e+00 L2 loss: 0.56543 Learning rate: 0.0004 Mask loss: 0.11705 RPN box loss: 0.00892 RPN score loss: 0.00463 RPN total loss: 0.01355 Total loss: 0.87473 timestamp: 1655064888.518689 iteration: 71300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1678 FastRCNN class loss: 0.08127 FastRCNN total loss: 0.24907 L1 loss: 0.0000e+00 L2 loss: 0.56543 Learning rate: 0.0004 Mask loss: 0.10582 RPN box loss: 0.01362 RPN score loss: 0.00722 RPN total loss: 0.02084 Total loss: 0.94116 timestamp: 1655064891.8182144 iteration: 71305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.0394 FastRCNN total loss: 0.12244 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.09525 RPN box loss: 0.01065 RPN score loss: 0.0023 RPN total loss: 0.01295 Total loss: 0.79607 timestamp: 1655064895.124074 iteration: 71310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06618 FastRCNN class loss: 0.07273 FastRCNN total loss: 0.13891 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.14442 RPN box loss: 0.00994 RPN score loss: 0.00745 RPN total loss: 0.01739 Total loss: 0.86615 timestamp: 1655064898.3201008 iteration: 71315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15861 FastRCNN class loss: 0.07859 FastRCNN total loss: 0.23721 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.18114 RPN box loss: 0.02912 RPN score loss: 0.00947 RPN total loss: 0.03859 Total loss: 1.02236 timestamp: 1655064901.5979555 iteration: 71320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06526 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.1263 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.09963 RPN box loss: 0.01674 RPN score loss: 0.00398 RPN total loss: 0.02071 Total loss: 0.81207 timestamp: 1655064904.8613496 iteration: 71325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14695 FastRCNN class loss: 0.10144 FastRCNN total loss: 0.24839 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.20281 RPN box loss: 0.03257 RPN score loss: 0.00985 RPN total loss: 0.04243 Total loss: 1.05904 timestamp: 1655064908.0845668 iteration: 71330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12977 FastRCNN class loss: 0.11298 FastRCNN total loss: 0.24275 L1 loss: 0.0000e+00 L2 loss: 0.56542 Learning rate: 0.0004 Mask loss: 0.178 RPN box loss: 0.01944 RPN score loss: 0.00269 RPN total loss: 0.02213 Total loss: 1.0083 timestamp: 1655064911.3257072 iteration: 71335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03769 FastRCNN class loss: 0.04027 FastRCNN total loss: 0.07796 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.0999 RPN box loss: 0.01005 RPN score loss: 0.00081 RPN total loss: 0.01086 Total loss: 0.75414 timestamp: 1655064914.570144 iteration: 71340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.08037 FastRCNN total loss: 0.15752 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.1177 RPN box loss: 0.00613 RPN score loss: 0.00534 RPN total loss: 0.01147 Total loss: 0.8521 timestamp: 1655064917.868445 iteration: 71345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11528 FastRCNN class loss: 0.10585 FastRCNN total loss: 0.22114 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.25821 RPN box loss: 0.01196 RPN score loss: 0.00881 RPN total loss: 0.02076 Total loss: 1.06551 timestamp: 1655064921.1305544 iteration: 71350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06885 FastRCNN class loss: 0.05199 FastRCNN total loss: 0.12083 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.10758 RPN box loss: 0.00889 RPN score loss: 0.0052 RPN total loss: 0.01409 Total loss: 0.80791 timestamp: 1655064924.4144495 iteration: 71355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11284 FastRCNN class loss: 0.06898 FastRCNN total loss: 0.18182 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.12658 RPN box loss: 0.00602 RPN score loss: 0.00302 RPN total loss: 0.00903 Total loss: 0.88284 timestamp: 1655064927.6616845 iteration: 71360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09228 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.15787 L1 loss: 0.0000e+00 L2 loss: 0.56541 Learning rate: 0.0004 Mask loss: 0.1074 RPN box loss: 0.00452 RPN score loss: 0.00205 RPN total loss: 0.00658 Total loss: 0.83725 timestamp: 1655064930.906305 iteration: 71365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06838 FastRCNN class loss: 0.02552 FastRCNN total loss: 0.09391 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.09587 RPN box loss: 0.0055 RPN score loss: 0.00397 RPN total loss: 0.00947 Total loss: 0.76465 timestamp: 1655064934.2414734 iteration: 71370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10612 FastRCNN class loss: 0.07514 FastRCNN total loss: 0.18126 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.12671 RPN box loss: 0.00811 RPN score loss: 0.0065 RPN total loss: 0.01462 Total loss: 0.88799 timestamp: 1655064937.4652915 iteration: 71375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07855 FastRCNN class loss: 0.06961 FastRCNN total loss: 0.14816 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.1443 RPN box loss: 0.00943 RPN score loss: 0.00454 RPN total loss: 0.01397 Total loss: 0.87183 timestamp: 1655064940.7362573 iteration: 71380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09028 FastRCNN class loss: 0.05872 FastRCNN total loss: 0.14899 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.13911 RPN box loss: 0.01365 RPN score loss: 0.00694 RPN total loss: 0.02059 Total loss: 0.87408 timestamp: 1655064944.024032 iteration: 71385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11831 FastRCNN class loss: 0.04681 FastRCNN total loss: 0.16513 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.10104 RPN box loss: 0.00842 RPN score loss: 0.00165 RPN total loss: 0.01008 Total loss: 0.84164 timestamp: 1655064947.2729917 iteration: 71390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06607 FastRCNN class loss: 0.045 FastRCNN total loss: 0.11107 L1 loss: 0.0000e+00 L2 loss: 0.5654 Learning rate: 0.0004 Mask loss: 0.11317 RPN box loss: 0.01912 RPN score loss: 0.00217 RPN total loss: 0.02128 Total loss: 0.81092 timestamp: 1655064950.516647 iteration: 71395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07775 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.14081 L1 loss: 0.0000e+00 L2 loss: 0.56539 Learning rate: 0.0004 Mask loss: 0.13159 RPN box loss: 0.00533 RPN score loss: 0.00215 RPN total loss: 0.00748 Total loss: 0.84527 timestamp: 1655064953.8115976 iteration: 71400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09554 FastRCNN class loss: 0.05612 FastRCNN total loss: 0.15165 L1 loss: 0.0000e+00 L2 loss: 0.56539 Learning rate: 0.0004 Mask loss: 0.11588 RPN box loss: 0.01977 RPN score loss: 0.0037 RPN total loss: 0.02347 Total loss: 0.85639 timestamp: 1655064957.0155804 iteration: 71405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12958 FastRCNN class loss: 0.08794 FastRCNN total loss: 0.21752 L1 loss: 0.0000e+00 L2 loss: 0.56539 Learning rate: 0.0004 Mask loss: 0.19557 RPN box loss: 0.04583 RPN score loss: 0.00741 RPN total loss: 0.05324 Total loss: 1.03172 timestamp: 1655064960.3105748 iteration: 71410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.095 FastRCNN class loss: 0.08099 FastRCNN total loss: 0.176 L1 loss: 0.0000e+00 L2 loss: 0.56539 Learning rate: 0.0004 Mask loss: 0.12809 RPN box loss: 0.00692 RPN score loss: 0.00965 RPN total loss: 0.01657 Total loss: 0.88604 timestamp: 1655064963.5470767 iteration: 71415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17403 FastRCNN class loss: 0.12685 FastRCNN total loss: 0.30088 L1 loss: 0.0000e+00 L2 loss: 0.56539 Learning rate: 0.0004 Mask loss: 0.17554 RPN box loss: 0.01879 RPN score loss: 0.00853 RPN total loss: 0.02732 Total loss: 1.06913 timestamp: 1655064966.8208485 iteration: 71420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09786 FastRCNN class loss: 0.05355 FastRCNN total loss: 0.15141 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.10447 RPN box loss: 0.01358 RPN score loss: 0.00136 RPN total loss: 0.01495 Total loss: 0.83621 timestamp: 1655064970.0996068 iteration: 71425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13392 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.22574 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.17131 RPN box loss: 0.04565 RPN score loss: 0.01599 RPN total loss: 0.06164 Total loss: 1.02407 timestamp: 1655064973.39709 iteration: 71430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10566 FastRCNN class loss: 0.08072 FastRCNN total loss: 0.18637 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.17643 RPN box loss: 0.0079 RPN score loss: 0.00472 RPN total loss: 0.01261 Total loss: 0.9408 timestamp: 1655064976.6610372 iteration: 71435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12759 FastRCNN class loss: 0.07184 FastRCNN total loss: 0.19943 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.13208 RPN box loss: 0.01384 RPN score loss: 0.00738 RPN total loss: 0.02122 Total loss: 0.91811 timestamp: 1655064979.9694061 iteration: 71440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.12075 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.12176 RPN box loss: 0.00925 RPN score loss: 0.00239 RPN total loss: 0.01164 Total loss: 0.81953 timestamp: 1655064983.296197 iteration: 71445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.06378 FastRCNN total loss: 0.17268 L1 loss: 0.0000e+00 L2 loss: 0.56538 Learning rate: 0.0004 Mask loss: 0.14744 RPN box loss: 0.00925 RPN score loss: 0.00488 RPN total loss: 0.01413 Total loss: 0.89962 timestamp: 1655064986.5676768 iteration: 71450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07885 FastRCNN class loss: 0.0739 FastRCNN total loss: 0.15276 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.17716 RPN box loss: 0.0079 RPN score loss: 0.00493 RPN total loss: 0.01283 Total loss: 0.90812 timestamp: 1655064989.8525414 iteration: 71455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1088 FastRCNN class loss: 0.09758 FastRCNN total loss: 0.20638 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.17567 RPN box loss: 0.01373 RPN score loss: 0.00866 RPN total loss: 0.02239 Total loss: 0.96981 timestamp: 1655064993.1593585 iteration: 71460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10133 FastRCNN class loss: 0.07192 FastRCNN total loss: 0.17325 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.13486 RPN box loss: 0.02513 RPN score loss: 0.00772 RPN total loss: 0.03285 Total loss: 0.90633 timestamp: 1655064996.4294984 iteration: 71465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08412 FastRCNN class loss: 0.10093 FastRCNN total loss: 0.18505 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.15376 RPN box loss: 0.01261 RPN score loss: 0.00483 RPN total loss: 0.01744 Total loss: 0.92162 timestamp: 1655064999.7958403 iteration: 71470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11259 FastRCNN class loss: 0.12262 FastRCNN total loss: 0.23521 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.21393 RPN box loss: 0.01766 RPN score loss: 0.01578 RPN total loss: 0.03344 Total loss: 1.04794 timestamp: 1655065003.0648274 iteration: 71475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13081 FastRCNN class loss: 0.06912 FastRCNN total loss: 0.19994 L1 loss: 0.0000e+00 L2 loss: 0.56537 Learning rate: 0.0004 Mask loss: 0.15945 RPN box loss: 0.01426 RPN score loss: 0.00386 RPN total loss: 0.01812 Total loss: 0.94287 timestamp: 1655065006.3066242 iteration: 71480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07188 FastRCNN class loss: 0.07303 FastRCNN total loss: 0.14492 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.10123 RPN box loss: 0.02008 RPN score loss: 0.00687 RPN total loss: 0.02695 Total loss: 0.83846 timestamp: 1655065009.607528 iteration: 71485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09518 FastRCNN class loss: 0.08797 FastRCNN total loss: 0.18316 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.17087 RPN box loss: 0.02867 RPN score loss: 0.00782 RPN total loss: 0.03649 Total loss: 0.95588 timestamp: 1655065012.883056 iteration: 71490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05351 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.11096 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.0809 RPN box loss: 0.00973 RPN score loss: 0.00329 RPN total loss: 0.01303 Total loss: 0.77025 timestamp: 1655065016.1923707 iteration: 71495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12652 FastRCNN class loss: 0.07239 FastRCNN total loss: 0.19891 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.13248 RPN box loss: 0.00609 RPN score loss: 0.00844 RPN total loss: 0.01453 Total loss: 0.91127 timestamp: 1655065019.5302777 iteration: 71500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.10602 FastRCNN total loss: 0.2141 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.24343 RPN box loss: 0.03395 RPN score loss: 0.01305 RPN total loss: 0.047 Total loss: 1.0699 timestamp: 1655065022.8026597 iteration: 71505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06097 FastRCNN class loss: 0.0353 FastRCNN total loss: 0.09627 L1 loss: 0.0000e+00 L2 loss: 0.56536 Learning rate: 0.0004 Mask loss: 0.11239 RPN box loss: 0.02401 RPN score loss: 0.00097 RPN total loss: 0.02499 Total loss: 0.799 timestamp: 1655065026.0993538 iteration: 71510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05783 FastRCNN class loss: 0.06124 FastRCNN total loss: 0.11907 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.16608 RPN box loss: 0.01591 RPN score loss: 0.00635 RPN total loss: 0.02226 Total loss: 0.87276 timestamp: 1655065029.3036344 iteration: 71515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11241 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.17548 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.10462 RPN box loss: 0.00678 RPN score loss: 0.00143 RPN total loss: 0.0082 Total loss: 0.85366 timestamp: 1655065032.5818691 iteration: 71520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09252 FastRCNN class loss: 0.08162 FastRCNN total loss: 0.17413 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.15367 RPN box loss: 0.01091 RPN score loss: 0.00678 RPN total loss: 0.0177 Total loss: 0.91085 timestamp: 1655065035.8395092 iteration: 71525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06181 FastRCNN class loss: 0.0426 FastRCNN total loss: 0.10441 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.14943 RPN box loss: 0.00822 RPN score loss: 0.00712 RPN total loss: 0.01534 Total loss: 0.83453 timestamp: 1655065039.1050494 iteration: 71530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07285 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.1313 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.13558 RPN box loss: 0.01128 RPN score loss: 0.0084 RPN total loss: 0.01968 Total loss: 0.85191 timestamp: 1655065042.333925 iteration: 71535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09486 FastRCNN class loss: 0.06797 FastRCNN total loss: 0.16282 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.1817 RPN box loss: 0.02239 RPN score loss: 0.00502 RPN total loss: 0.02741 Total loss: 0.93728 timestamp: 1655065045.579878 iteration: 71540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10238 FastRCNN class loss: 0.0536 FastRCNN total loss: 0.15599 L1 loss: 0.0000e+00 L2 loss: 0.56535 Learning rate: 0.0004 Mask loss: 0.15216 RPN box loss: 0.0092 RPN score loss: 0.00441 RPN total loss: 0.01361 Total loss: 0.88711 timestamp: 1655065048.8816342 iteration: 71545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09599 FastRCNN class loss: 0.03925 FastRCNN total loss: 0.13524 L1 loss: 0.0000e+00 L2 loss: 0.56534 Learning rate: 0.0004 Mask loss: 0.11926 RPN box loss: 0.00721 RPN score loss: 0.0045 RPN total loss: 0.01171 Total loss: 0.83155 timestamp: 1655065052.118287 iteration: 71550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03784 FastRCNN class loss: 0.02672 FastRCNN total loss: 0.06456 L1 loss: 0.0000e+00 L2 loss: 0.56534 Learning rate: 0.0004 Mask loss: 0.10684 RPN box loss: 0.01202 RPN score loss: 0.0045 RPN total loss: 0.01652 Total loss: 0.75326 timestamp: 1655065055.3653576 iteration: 71555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11695 FastRCNN class loss: 0.06401 FastRCNN total loss: 0.18096 L1 loss: 0.0000e+00 L2 loss: 0.56534 Learning rate: 0.0004 Mask loss: 0.10108 RPN box loss: 0.01261 RPN score loss: 0.00203 RPN total loss: 0.01464 Total loss: 0.86202 timestamp: 1655065058.6691236 iteration: 71560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10641 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.1606 L1 loss: 0.0000e+00 L2 loss: 0.56534 Learning rate: 0.0004 Mask loss: 0.12008 RPN box loss: 0.01251 RPN score loss: 0.00612 RPN total loss: 0.01864 Total loss: 0.86465 timestamp: 1655065061.929894 iteration: 71565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08912 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.17286 L1 loss: 0.0000e+00 L2 loss: 0.56534 Learning rate: 0.0004 Mask loss: 0.12292 RPN box loss: 0.01545 RPN score loss: 0.00751 RPN total loss: 0.02296 Total loss: 0.88408 timestamp: 1655065065.2593818 iteration: 71570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09278 FastRCNN class loss: 0.09109 FastRCNN total loss: 0.18387 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.18641 RPN box loss: 0.02272 RPN score loss: 0.00348 RPN total loss: 0.02621 Total loss: 0.96182 timestamp: 1655065068.5576282 iteration: 71575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12304 FastRCNN class loss: 0.09783 FastRCNN total loss: 0.22087 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.16257 RPN box loss: 0.0311 RPN score loss: 0.01042 RPN total loss: 0.04153 Total loss: 0.9903 timestamp: 1655065071.8173525 iteration: 71580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09031 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.14353 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.1417 RPN box loss: 0.01192 RPN score loss: 0.00758 RPN total loss: 0.0195 Total loss: 0.87005 timestamp: 1655065075.0806358 iteration: 71585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09533 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.15261 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.12537 RPN box loss: 0.00561 RPN score loss: 0.00756 RPN total loss: 0.01318 Total loss: 0.85648 timestamp: 1655065078.3809671 iteration: 71590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10423 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.16181 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.16626 RPN box loss: 0.04373 RPN score loss: 0.00767 RPN total loss: 0.05139 Total loss: 0.94479 timestamp: 1655065081.6792696 iteration: 71595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04319 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.09318 L1 loss: 0.0000e+00 L2 loss: 0.56533 Learning rate: 0.0004 Mask loss: 0.16421 RPN box loss: 0.00894 RPN score loss: 0.00258 RPN total loss: 0.01152 Total loss: 0.83424 timestamp: 1655065084.9046443 iteration: 71600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12647 FastRCNN class loss: 0.10509 FastRCNN total loss: 0.23157 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.17036 RPN box loss: 0.01245 RPN score loss: 0.00124 RPN total loss: 0.01369 Total loss: 0.98094 timestamp: 1655065088.1486123 iteration: 71605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.21778 FastRCNN class loss: 0.13871 FastRCNN total loss: 0.35649 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.192 RPN box loss: 0.01445 RPN score loss: 0.0106 RPN total loss: 0.02504 Total loss: 1.13886 timestamp: 1655065091.4416068 iteration: 71610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1185 FastRCNN class loss: 0.09346 FastRCNN total loss: 0.21196 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.15236 RPN box loss: 0.01872 RPN score loss: 0.00589 RPN total loss: 0.0246 Total loss: 0.95424 timestamp: 1655065094.6794033 iteration: 71615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.06298 FastRCNN total loss: 0.16044 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.13311 RPN box loss: 0.02323 RPN score loss: 0.00295 RPN total loss: 0.02618 Total loss: 0.88505 timestamp: 1655065097.9795172 iteration: 71620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09869 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.18335 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.11825 RPN box loss: 0.00868 RPN score loss: 0.00439 RPN total loss: 0.01306 Total loss: 0.87999 timestamp: 1655065101.3116007 iteration: 71625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12437 FastRCNN class loss: 0.09926 FastRCNN total loss: 0.22363 L1 loss: 0.0000e+00 L2 loss: 0.56532 Learning rate: 0.0004 Mask loss: 0.16316 RPN box loss: 0.06163 RPN score loss: 0.0051 RPN total loss: 0.06674 Total loss: 1.01885 timestamp: 1655065104.5657737 iteration: 71630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06681 FastRCNN class loss: 0.04527 FastRCNN total loss: 0.11208 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.12795 RPN box loss: 0.00951 RPN score loss: 0.00347 RPN total loss: 0.01298 Total loss: 0.81833 timestamp: 1655065107.8908963 iteration: 71635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07918 FastRCNN class loss: 0.12614 FastRCNN total loss: 0.20533 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.23775 RPN box loss: 0.03684 RPN score loss: 0.06838 RPN total loss: 0.10522 Total loss: 1.11361 timestamp: 1655065111.1651707 iteration: 71640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09535 FastRCNN class loss: 0.08616 FastRCNN total loss: 0.18151 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.16942 RPN box loss: 0.02326 RPN score loss: 0.00513 RPN total loss: 0.02838 Total loss: 0.94462 timestamp: 1655065114.4435987 iteration: 71645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12785 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.20049 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.16095 RPN box loss: 0.01874 RPN score loss: 0.0031 RPN total loss: 0.02185 Total loss: 0.9486 timestamp: 1655065117.6799629 iteration: 71650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0971 FastRCNN class loss: 0.0628 FastRCNN total loss: 0.1599 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.16526 RPN box loss: 0.00917 RPN score loss: 0.00779 RPN total loss: 0.01696 Total loss: 0.90743 timestamp: 1655065120.9418812 iteration: 71655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1201 FastRCNN class loss: 0.07436 FastRCNN total loss: 0.19446 L1 loss: 0.0000e+00 L2 loss: 0.56531 Learning rate: 0.0004 Mask loss: 0.11587 RPN box loss: 0.01566 RPN score loss: 0.00293 RPN total loss: 0.01859 Total loss: 0.89423 timestamp: 1655065124.2217426 iteration: 71660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10973 FastRCNN class loss: 0.08935 FastRCNN total loss: 0.19908 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.1645 RPN box loss: 0.01359 RPN score loss: 0.0084 RPN total loss: 0.02198 Total loss: 0.95086 timestamp: 1655065127.478056 iteration: 71665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09479 FastRCNN class loss: 0.05115 FastRCNN total loss: 0.14593 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.12936 RPN box loss: 0.00388 RPN score loss: 0.00251 RPN total loss: 0.00638 Total loss: 0.84697 timestamp: 1655065130.706938 iteration: 71670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04749 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.10745 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.10674 RPN box loss: 0.01231 RPN score loss: 0.00461 RPN total loss: 0.01693 Total loss: 0.79642 timestamp: 1655065133.9790537 iteration: 71675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.17405 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.12278 RPN box loss: 0.04079 RPN score loss: 0.00428 RPN total loss: 0.04506 Total loss: 0.90719 timestamp: 1655065137.20113 iteration: 71680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07793 FastRCNN class loss: 0.04316 FastRCNN total loss: 0.1211 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.09101 RPN box loss: 0.01596 RPN score loss: 0.00089 RPN total loss: 0.01686 Total loss: 0.79427 timestamp: 1655065140.4925249 iteration: 71685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06578 FastRCNN class loss: 0.09279 FastRCNN total loss: 0.15858 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.1637 RPN box loss: 0.01114 RPN score loss: 0.00243 RPN total loss: 0.01356 Total loss: 0.90114 timestamp: 1655065143.748294 iteration: 71690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07533 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.14523 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.16722 RPN box loss: 0.01768 RPN score loss: 0.00726 RPN total loss: 0.02494 Total loss: 0.90267 timestamp: 1655065146.9959717 iteration: 71695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0735 FastRCNN class loss: 0.08381 FastRCNN total loss: 0.15731 L1 loss: 0.0000e+00 L2 loss: 0.5653 Learning rate: 0.0004 Mask loss: 0.11678 RPN box loss: 0.00596 RPN score loss: 0.00126 RPN total loss: 0.00721 Total loss: 0.8466 timestamp: 1655065150.3450866 iteration: 71700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09782 FastRCNN class loss: 0.06049 FastRCNN total loss: 0.15831 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.12743 RPN box loss: 0.01391 RPN score loss: 0.00383 RPN total loss: 0.01774 Total loss: 0.86878 timestamp: 1655065153.5603008 iteration: 71705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1381 FastRCNN class loss: 0.10567 FastRCNN total loss: 0.24377 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.17973 RPN box loss: 0.00791 RPN score loss: 0.01597 RPN total loss: 0.02388 Total loss: 1.01267 timestamp: 1655065156.8096101 iteration: 71710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10513 FastRCNN class loss: 0.07733 FastRCNN total loss: 0.18246 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.12992 RPN box loss: 0.05524 RPN score loss: 0.00995 RPN total loss: 0.06519 Total loss: 0.94286 timestamp: 1655065160.1064754 iteration: 71715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09377 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.16818 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.16095 RPN box loss: 0.00846 RPN score loss: 0.00289 RPN total loss: 0.01135 Total loss: 0.90577 timestamp: 1655065163.3817647 iteration: 71720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0702 FastRCNN class loss: 0.05055 FastRCNN total loss: 0.12075 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.10556 RPN box loss: 0.01079 RPN score loss: 0.00862 RPN total loss: 0.01941 Total loss: 0.81101 timestamp: 1655065166.6582549 iteration: 71725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12557 FastRCNN class loss: 0.07931 FastRCNN total loss: 0.20489 L1 loss: 0.0000e+00 L2 loss: 0.56529 Learning rate: 0.0004 Mask loss: 0.21146 RPN box loss: 0.01816 RPN score loss: 0.0134 RPN total loss: 0.03155 Total loss: 1.01318 timestamp: 1655065169.8970563 iteration: 71730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0647 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.11494 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.14841 RPN box loss: 0.01928 RPN score loss: 0.00343 RPN total loss: 0.02272 Total loss: 0.85135 timestamp: 1655065173.1886513 iteration: 71735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08902 FastRCNN class loss: 0.09054 FastRCNN total loss: 0.17956 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.1247 RPN box loss: 0.02479 RPN score loss: 0.00543 RPN total loss: 0.03022 Total loss: 0.89976 timestamp: 1655065176.4569764 iteration: 71740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13755 FastRCNN class loss: 0.06566 FastRCNN total loss: 0.20321 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.13795 RPN box loss: 0.01509 RPN score loss: 0.00332 RPN total loss: 0.01841 Total loss: 0.92485 timestamp: 1655065179.7111182 iteration: 71745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07829 FastRCNN class loss: 0.04993 FastRCNN total loss: 0.12822 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.1104 RPN box loss: 0.00433 RPN score loss: 0.00257 RPN total loss: 0.0069 Total loss: 0.8108 timestamp: 1655065183.014643 iteration: 71750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09448 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.15726 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.1323 RPN box loss: 0.00327 RPN score loss: 0.00522 RPN total loss: 0.00849 Total loss: 0.86333 timestamp: 1655065186.3467932 iteration: 71755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05759 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.10104 L1 loss: 0.0000e+00 L2 loss: 0.56528 Learning rate: 0.0004 Mask loss: 0.10928 RPN box loss: 0.0085 RPN score loss: 0.00092 RPN total loss: 0.00943 Total loss: 0.78503 timestamp: 1655065189.6478739 iteration: 71760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11931 FastRCNN class loss: 0.09746 FastRCNN total loss: 0.21677 L1 loss: 0.0000e+00 L2 loss: 0.56527 Learning rate: 0.0004 Mask loss: 0.11021 RPN box loss: 0.02277 RPN score loss: 0.00647 RPN total loss: 0.02925 Total loss: 0.9215 timestamp: 1655065192.9336169 iteration: 71765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.07756 FastRCNN total loss: 0.16383 L1 loss: 0.0000e+00 L2 loss: 0.56527 Learning rate: 0.0004 Mask loss: 0.21258 RPN box loss: 0.01045 RPN score loss: 0.00928 RPN total loss: 0.01974 Total loss: 0.96142 timestamp: 1655065196.1831224 iteration: 71770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13871 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.21082 L1 loss: 0.0000e+00 L2 loss: 0.56527 Learning rate: 0.0004 Mask loss: 0.13975 RPN box loss: 0.00606 RPN score loss: 0.01103 RPN total loss: 0.01709 Total loss: 0.93293 timestamp: 1655065199.5264382 iteration: 71775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09936 FastRCNN class loss: 0.06063 FastRCNN total loss: 0.15999 L1 loss: 0.0000e+00 L2 loss: 0.56527 Learning rate: 0.0004 Mask loss: 0.15485 RPN box loss: 0.00832 RPN score loss: 0.00764 RPN total loss: 0.01596 Total loss: 0.89607 timestamp: 1655065202.8782947 iteration: 71780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12363 FastRCNN class loss: 0.07879 FastRCNN total loss: 0.20242 L1 loss: 0.0000e+00 L2 loss: 0.56527 Learning rate: 0.0004 Mask loss: 0.15495 RPN box loss: 0.01252 RPN score loss: 0.00593 RPN total loss: 0.01845 Total loss: 0.9411 timestamp: 1655065206.191697 iteration: 71785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07527 FastRCNN class loss: 0.04994 FastRCNN total loss: 0.12522 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.12381 RPN box loss: 0.00405 RPN score loss: 0.00216 RPN total loss: 0.0062 Total loss: 0.82049 timestamp: 1655065209.4254816 iteration: 71790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14361 FastRCNN class loss: 0.06941 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.16525 RPN box loss: 0.02785 RPN score loss: 0.00413 RPN total loss: 0.03198 Total loss: 0.97551 timestamp: 1655065212.7576294 iteration: 71795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07119 FastRCNN class loss: 0.05606 FastRCNN total loss: 0.12724 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.16736 RPN box loss: 0.01871 RPN score loss: 0.00503 RPN total loss: 0.02374 Total loss: 0.8836 timestamp: 1655065215.9759672 iteration: 71800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11686 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.19962 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.18482 RPN box loss: 0.01685 RPN score loss: 0.00713 RPN total loss: 0.02398 Total loss: 0.97369 timestamp: 1655065219.2283564 iteration: 71805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05473 FastRCNN class loss: 0.0503 FastRCNN total loss: 0.10503 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.13006 RPN box loss: 0.0104 RPN score loss: 0.00219 RPN total loss: 0.01259 Total loss: 0.81294 timestamp: 1655065222.4128847 iteration: 71810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12145 FastRCNN class loss: 0.05663 FastRCNN total loss: 0.17808 L1 loss: 0.0000e+00 L2 loss: 0.56526 Learning rate: 0.0004 Mask loss: 0.09973 RPN box loss: 0.00572 RPN score loss: 0.00274 RPN total loss: 0.00845 Total loss: 0.85152 timestamp: 1655065225.644103 iteration: 71815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0988 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.16203 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.14294 RPN box loss: 0.01112 RPN score loss: 0.00621 RPN total loss: 0.01734 Total loss: 0.88756 timestamp: 1655065228.81071 iteration: 71820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09935 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.17357 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.12322 RPN box loss: 0.00763 RPN score loss: 0.00453 RPN total loss: 0.01216 Total loss: 0.87421 timestamp: 1655065232.114226 iteration: 71825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.1748 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.18785 RPN box loss: 0.01415 RPN score loss: 0.0054 RPN total loss: 0.01955 Total loss: 0.94745 timestamp: 1655065235.3849165 iteration: 71830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09053 FastRCNN class loss: 0.04273 FastRCNN total loss: 0.13326 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.11409 RPN box loss: 0.03339 RPN score loss: 0.00434 RPN total loss: 0.03773 Total loss: 0.85033 timestamp: 1655065238.6437447 iteration: 71835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16282 FastRCNN class loss: 0.0789 FastRCNN total loss: 0.24172 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.10491 RPN box loss: 0.01856 RPN score loss: 0.00373 RPN total loss: 0.0223 Total loss: 0.93418 timestamp: 1655065241.9080005 iteration: 71840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06746 FastRCNN class loss: 0.05575 FastRCNN total loss: 0.12322 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.10056 RPN box loss: 0.00481 RPN score loss: 0.00102 RPN total loss: 0.00583 Total loss: 0.79486 timestamp: 1655065245.1158795 iteration: 71845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05932 FastRCNN class loss: 0.0791 FastRCNN total loss: 0.13842 L1 loss: 0.0000e+00 L2 loss: 0.56525 Learning rate: 0.0004 Mask loss: 0.09334 RPN box loss: 0.00749 RPN score loss: 0.00225 RPN total loss: 0.00974 Total loss: 0.80675 timestamp: 1655065248.4104264 iteration: 71850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08275 FastRCNN class loss: 0.06503 FastRCNN total loss: 0.14778 L1 loss: 0.0000e+00 L2 loss: 0.56524 Learning rate: 0.0004 Mask loss: 0.13861 RPN box loss: 0.06055 RPN score loss: 0.00551 RPN total loss: 0.06606 Total loss: 0.91769 timestamp: 1655065251.6769705 iteration: 71855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08906 FastRCNN class loss: 0.07344 FastRCNN total loss: 0.1625 L1 loss: 0.0000e+00 L2 loss: 0.56524 Learning rate: 0.0004 Mask loss: 0.11793 RPN box loss: 0.00789 RPN score loss: 0.00411 RPN total loss: 0.01201 Total loss: 0.85769 timestamp: 1655065254.9128675 iteration: 71860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10694 FastRCNN class loss: 0.06397 FastRCNN total loss: 0.17091 L1 loss: 0.0000e+00 L2 loss: 0.56524 Learning rate: 0.0004 Mask loss: 0.13852 RPN box loss: 0.01646 RPN score loss: 0.00311 RPN total loss: 0.01957 Total loss: 0.89424 timestamp: 1655065258.1310008 iteration: 71865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09577 FastRCNN class loss: 0.09451 FastRCNN total loss: 0.19028 L1 loss: 0.0000e+00 L2 loss: 0.56524 Learning rate: 0.0004 Mask loss: 0.14984 RPN box loss: 0.01275 RPN score loss: 0.0042 RPN total loss: 0.01695 Total loss: 0.92231 timestamp: 1655065261.36796 iteration: 71870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11555 FastRCNN class loss: 0.09333 FastRCNN total loss: 0.20887 L1 loss: 0.0000e+00 L2 loss: 0.56524 Learning rate: 0.0004 Mask loss: 0.19356 RPN box loss: 0.00789 RPN score loss: 0.00864 RPN total loss: 0.01653 Total loss: 0.9842 timestamp: 1655065264.660853 iteration: 71875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08226 FastRCNN class loss: 0.04517 FastRCNN total loss: 0.12744 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.13198 RPN box loss: 0.01009 RPN score loss: 0.00155 RPN total loss: 0.01165 Total loss: 0.83629 timestamp: 1655065267.9584572 iteration: 71880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05102 FastRCNN class loss: 0.04879 FastRCNN total loss: 0.09981 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.16847 RPN box loss: 0.00927 RPN score loss: 0.00774 RPN total loss: 0.01701 Total loss: 0.85052 timestamp: 1655065271.2864413 iteration: 71885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06361 FastRCNN class loss: 0.04711 FastRCNN total loss: 0.11071 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.2057 RPN box loss: 0.01306 RPN score loss: 0.00204 RPN total loss: 0.01511 Total loss: 0.89675 timestamp: 1655065274.5458288 iteration: 71890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06498 FastRCNN class loss: 0.06607 FastRCNN total loss: 0.13105 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.14682 RPN box loss: 0.01109 RPN score loss: 0.00104 RPN total loss: 0.01213 Total loss: 0.85524 timestamp: 1655065277.857649 iteration: 71895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11847 FastRCNN class loss: 0.0702 FastRCNN total loss: 0.18866 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.17031 RPN box loss: 0.0153 RPN score loss: 0.00653 RPN total loss: 0.02183 Total loss: 0.94603 timestamp: 1655065280.9869215 iteration: 71900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09099 FastRCNN class loss: 0.05408 FastRCNN total loss: 0.14507 L1 loss: 0.0000e+00 L2 loss: 0.56523 Learning rate: 0.0004 Mask loss: 0.11784 RPN box loss: 0.01003 RPN score loss: 0.01386 RPN total loss: 0.02389 Total loss: 0.85202 timestamp: 1655065284.2566736 iteration: 71905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08555 FastRCNN class loss: 0.05532 FastRCNN total loss: 0.14087 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.12624 RPN box loss: 0.01497 RPN score loss: 0.00716 RPN total loss: 0.02213 Total loss: 0.85447 timestamp: 1655065287.4627037 iteration: 71910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12665 FastRCNN class loss: 0.10193 FastRCNN total loss: 0.22858 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.24051 RPN box loss: 0.02054 RPN score loss: 0.01561 RPN total loss: 0.03615 Total loss: 1.07046 timestamp: 1655065290.7662773 iteration: 71915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07618 FastRCNN class loss: 0.04045 FastRCNN total loss: 0.11663 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.10729 RPN box loss: 0.01995 RPN score loss: 0.00639 RPN total loss: 0.02634 Total loss: 0.81548 timestamp: 1655065294.0383065 iteration: 71920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10503 FastRCNN class loss: 0.06524 FastRCNN total loss: 0.17027 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.11927 RPN box loss: 0.00643 RPN score loss: 0.00329 RPN total loss: 0.00972 Total loss: 0.86448 timestamp: 1655065297.3382046 iteration: 71925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11472 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.18244 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.177 RPN box loss: 0.01835 RPN score loss: 0.00186 RPN total loss: 0.02021 Total loss: 0.94486 timestamp: 1655065300.6288853 iteration: 71930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12853 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.21173 L1 loss: 0.0000e+00 L2 loss: 0.56522 Learning rate: 0.0004 Mask loss: 0.14473 RPN box loss: 0.01327 RPN score loss: 0.00228 RPN total loss: 0.01555 Total loss: 0.93722 timestamp: 1655065303.9213972 iteration: 71935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.10132 FastRCNN total loss: 0.21567 L1 loss: 0.0000e+00 L2 loss: 0.56521 Learning rate: 0.0004 Mask loss: 0.18449 RPN box loss: 0.03007 RPN score loss: 0.01954 RPN total loss: 0.04961 Total loss: 1.01499 timestamp: 1655065307.2061672 iteration: 71940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07315 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.13873 L1 loss: 0.0000e+00 L2 loss: 0.56521 Learning rate: 0.0004 Mask loss: 0.14125 RPN box loss: 0.00608 RPN score loss: 0.00531 RPN total loss: 0.01139 Total loss: 0.85658 timestamp: 1655065310.4304318 iteration: 71945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06869 FastRCNN class loss: 0.05764 FastRCNN total loss: 0.12634 L1 loss: 0.0000e+00 L2 loss: 0.56521 Learning rate: 0.0004 Mask loss: 0.08383 RPN box loss: 0.01162 RPN score loss: 0.00122 RPN total loss: 0.01284 Total loss: 0.78822 timestamp: 1655065313.72942 iteration: 71950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0712 FastRCNN class loss: 0.04717 FastRCNN total loss: 0.11838 L1 loss: 0.0000e+00 L2 loss: 0.56521 Learning rate: 0.0004 Mask loss: 0.14533 RPN box loss: 0.0205 RPN score loss: 0.00501 RPN total loss: 0.02552 Total loss: 0.85443 timestamp: 1655065317.0299263 iteration: 71955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08104 FastRCNN class loss: 0.05242 FastRCNN total loss: 0.13346 L1 loss: 0.0000e+00 L2 loss: 0.56521 Learning rate: 0.0004 Mask loss: 0.1476 RPN box loss: 0.01143 RPN score loss: 0.00375 RPN total loss: 0.01518 Total loss: 0.86144 timestamp: 1655065320.3180907 iteration: 71960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06879 FastRCNN class loss: 0.0521 FastRCNN total loss: 0.1209 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.12004 RPN box loss: 0.02643 RPN score loss: 0.00411 RPN total loss: 0.03054 Total loss: 0.83669 timestamp: 1655065323.5868912 iteration: 71965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09489 FastRCNN class loss: 0.08077 FastRCNN total loss: 0.17565 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.1448 RPN box loss: 0.02156 RPN score loss: 0.00302 RPN total loss: 0.02458 Total loss: 0.91024 timestamp: 1655065326.8952541 iteration: 71970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.13732 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.12069 RPN box loss: 0.00934 RPN score loss: 0.0024 RPN total loss: 0.01174 Total loss: 0.83495 timestamp: 1655065330.1721618 iteration: 71975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09074 FastRCNN class loss: 0.11447 FastRCNN total loss: 0.20521 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.20584 RPN box loss: 0.01645 RPN score loss: 0.02841 RPN total loss: 0.04486 Total loss: 1.02111 timestamp: 1655065333.4315295 iteration: 71980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09832 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.17203 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.14004 RPN box loss: 0.0038 RPN score loss: 0.00896 RPN total loss: 0.01276 Total loss: 0.89002 timestamp: 1655065336.6414034 iteration: 71985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1383 FastRCNN class loss: 0.08667 FastRCNN total loss: 0.22496 L1 loss: 0.0000e+00 L2 loss: 0.5652 Learning rate: 0.0004 Mask loss: 0.162 RPN box loss: 0.01552 RPN score loss: 0.0096 RPN total loss: 0.02512 Total loss: 0.97728 timestamp: 1655065339.954623 iteration: 71990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08544 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.16794 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.22136 RPN box loss: 0.02217 RPN score loss: 0.00346 RPN total loss: 0.02562 Total loss: 0.98012 timestamp: 1655065343.2846668 iteration: 71995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05916 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.1073 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.13173 RPN box loss: 0.02155 RPN score loss: 0.00347 RPN total loss: 0.02503 Total loss: 0.82924 timestamp: 1655065346.4901407 iteration: 72000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11138 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.18667 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.12814 RPN box loss: 0.00884 RPN score loss: 0.00491 RPN total loss: 0.01376 Total loss: 0.89376 timestamp: 1655065349.7844355 iteration: 72005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06779 FastRCNN class loss: 0.04754 FastRCNN total loss: 0.11533 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.1844 RPN box loss: 0.00346 RPN score loss: 0.00151 RPN total loss: 0.00497 Total loss: 0.86988 timestamp: 1655065353.0756176 iteration: 72010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12213 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.18907 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.21655 RPN box loss: 0.00847 RPN score loss: 0.00947 RPN total loss: 0.01793 Total loss: 0.98874 timestamp: 1655065356.3171601 iteration: 72015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12668 FastRCNN class loss: 0.08312 FastRCNN total loss: 0.20981 L1 loss: 0.0000e+00 L2 loss: 0.56519 Learning rate: 0.0004 Mask loss: 0.14477 RPN box loss: 0.01724 RPN score loss: 0.00956 RPN total loss: 0.02679 Total loss: 0.94656 timestamp: 1655065359.5370705 iteration: 72020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.09099 FastRCNN total loss: 0.20348 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.16083 RPN box loss: 0.02383 RPN score loss: 0.0081 RPN total loss: 0.03193 Total loss: 0.96142 timestamp: 1655065362.7453985 iteration: 72025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10172 FastRCNN class loss: 0.10158 FastRCNN total loss: 0.2033 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.152 RPN box loss: 0.04161 RPN score loss: 0.00596 RPN total loss: 0.04757 Total loss: 0.96805 timestamp: 1655065366.0414546 iteration: 72030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11237 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.18647 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.16177 RPN box loss: 0.01243 RPN score loss: 0.00765 RPN total loss: 0.02008 Total loss: 0.9335 timestamp: 1655065369.2995594 iteration: 72035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07391 FastRCNN class loss: 0.0398 FastRCNN total loss: 0.11371 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.09734 RPN box loss: 0.0366 RPN score loss: 0.00161 RPN total loss: 0.03821 Total loss: 0.81444 timestamp: 1655065372.5364752 iteration: 72040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10735 FastRCNN class loss: 0.05547 FastRCNN total loss: 0.16282 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.09299 RPN box loss: 0.01347 RPN score loss: 0.00464 RPN total loss: 0.01811 Total loss: 0.8391 timestamp: 1655065375.8054845 iteration: 72045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13741 FastRCNN class loss: 0.08904 FastRCNN total loss: 0.22645 L1 loss: 0.0000e+00 L2 loss: 0.56518 Learning rate: 0.0004 Mask loss: 0.17439 RPN box loss: 0.04904 RPN score loss: 0.0097 RPN total loss: 0.05875 Total loss: 1.02476 timestamp: 1655065379.0334196 iteration: 72050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.03705 FastRCNN total loss: 0.15082 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.14073 RPN box loss: 0.00618 RPN score loss: 0.00172 RPN total loss: 0.0079 Total loss: 0.86462 timestamp: 1655065382.3105388 iteration: 72055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06871 FastRCNN class loss: 0.07788 FastRCNN total loss: 0.14659 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.14263 RPN box loss: 0.01401 RPN score loss: 0.00623 RPN total loss: 0.02024 Total loss: 0.87463 timestamp: 1655065385.6258981 iteration: 72060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1684 FastRCNN class loss: 0.08134 FastRCNN total loss: 0.24974 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.11582 RPN box loss: 0.0128 RPN score loss: 0.00207 RPN total loss: 0.01487 Total loss: 0.94561 timestamp: 1655065388.8676577 iteration: 72065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07879 FastRCNN class loss: 0.0833 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.16057 RPN box loss: 0.00705 RPN score loss: 0.00638 RPN total loss: 0.01343 Total loss: 0.90126 timestamp: 1655065392.1019883 iteration: 72070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1102 FastRCNN class loss: 0.05047 FastRCNN total loss: 0.16067 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.10665 RPN box loss: 0.0057 RPN score loss: 0.00651 RPN total loss: 0.01221 Total loss: 0.84471 timestamp: 1655065395.41501 iteration: 72075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06344 FastRCNN class loss: 0.0491 FastRCNN total loss: 0.11255 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.14717 RPN box loss: 0.0083 RPN score loss: 0.00828 RPN total loss: 0.01658 Total loss: 0.84146 timestamp: 1655065398.7505028 iteration: 72080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04711 FastRCNN class loss: 0.03774 FastRCNN total loss: 0.08485 L1 loss: 0.0000e+00 L2 loss: 0.56517 Learning rate: 0.0004 Mask loss: 0.09085 RPN box loss: 0.01449 RPN score loss: 0.00182 RPN total loss: 0.01631 Total loss: 0.75718 timestamp: 1655065402.0366297 iteration: 72085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11144 FastRCNN class loss: 0.07912 FastRCNN total loss: 0.19056 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.17627 RPN box loss: 0.0039 RPN score loss: 0.00137 RPN total loss: 0.00527 Total loss: 0.93725 timestamp: 1655065405.24178 iteration: 72090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09933 FastRCNN class loss: 0.08541 FastRCNN total loss: 0.18474 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.14115 RPN box loss: 0.02663 RPN score loss: 0.01439 RPN total loss: 0.04102 Total loss: 0.93206 timestamp: 1655065408.5647705 iteration: 72095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.06599 FastRCNN total loss: 0.15284 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.18705 RPN box loss: 0.007 RPN score loss: 0.00194 RPN total loss: 0.00894 Total loss: 0.91399 timestamp: 1655065411.7643945 iteration: 72100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11467 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.19887 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.1382 RPN box loss: 0.02045 RPN score loss: 0.00825 RPN total loss: 0.0287 Total loss: 0.93093 timestamp: 1655065415.0289886 iteration: 72105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11457 FastRCNN class loss: 0.06455 FastRCNN total loss: 0.17912 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.17504 RPN box loss: 0.02228 RPN score loss: 0.004 RPN total loss: 0.02628 Total loss: 0.9456 timestamp: 1655065418.2993739 iteration: 72110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10447 FastRCNN class loss: 0.07364 FastRCNN total loss: 0.17811 L1 loss: 0.0000e+00 L2 loss: 0.56516 Learning rate: 0.0004 Mask loss: 0.11414 RPN box loss: 0.02418 RPN score loss: 0.00685 RPN total loss: 0.03104 Total loss: 0.88844 timestamp: 1655065421.5379105 iteration: 72115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16186 FastRCNN class loss: 0.09632 FastRCNN total loss: 0.25817 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.14182 RPN box loss: 0.0159 RPN score loss: 0.00408 RPN total loss: 0.01998 Total loss: 0.98514 timestamp: 1655065424.7821705 iteration: 72120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10835 FastRCNN class loss: 0.06953 FastRCNN total loss: 0.17788 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.14038 RPN box loss: 0.01172 RPN score loss: 0.00727 RPN total loss: 0.019 Total loss: 0.90241 timestamp: 1655065428.064463 iteration: 72125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05605 FastRCNN class loss: 0.0666 FastRCNN total loss: 0.12265 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.12653 RPN box loss: 0.01818 RPN score loss: 0.00396 RPN total loss: 0.02214 Total loss: 0.83647 timestamp: 1655065431.333214 iteration: 72130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06551 FastRCNN class loss: 0.04149 FastRCNN total loss: 0.107 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.08293 RPN box loss: 0.00833 RPN score loss: 0.00136 RPN total loss: 0.00969 Total loss: 0.76477 timestamp: 1655065434.6156392 iteration: 72135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08508 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.14319 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.11958 RPN box loss: 0.00873 RPN score loss: 0.00122 RPN total loss: 0.00995 Total loss: 0.83787 timestamp: 1655065437.942646 iteration: 72140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10254 FastRCNN class loss: 0.0986 FastRCNN total loss: 0.20113 L1 loss: 0.0000e+00 L2 loss: 0.56515 Learning rate: 0.0004 Mask loss: 0.14157 RPN box loss: 0.02179 RPN score loss: 0.00581 RPN total loss: 0.0276 Total loss: 0.93545 timestamp: 1655065441.2320933 iteration: 72145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15123 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.24556 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.19716 RPN box loss: 0.01434 RPN score loss: 0.00885 RPN total loss: 0.02318 Total loss: 1.03105 timestamp: 1655065444.5251222 iteration: 72150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10571 FastRCNN class loss: 0.07483 FastRCNN total loss: 0.18054 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.11754 RPN box loss: 0.02987 RPN score loss: 0.00803 RPN total loss: 0.0379 Total loss: 0.90113 timestamp: 1655065447.8209498 iteration: 72155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09823 FastRCNN class loss: 0.07661 FastRCNN total loss: 0.17484 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.16159 RPN box loss: 0.02851 RPN score loss: 0.00449 RPN total loss: 0.033 Total loss: 0.93457 timestamp: 1655065451.1631198 iteration: 72160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05547 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.12842 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.09252 RPN box loss: 0.02022 RPN score loss: 0.00977 RPN total loss: 0.02999 Total loss: 0.81606 timestamp: 1655065454.462957 iteration: 72165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08643 FastRCNN class loss: 0.04734 FastRCNN total loss: 0.13377 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.14964 RPN box loss: 0.00415 RPN score loss: 0.00714 RPN total loss: 0.01129 Total loss: 0.85984 timestamp: 1655065457.7922053 iteration: 72170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.111 FastRCNN class loss: 0.06481 FastRCNN total loss: 0.17581 L1 loss: 0.0000e+00 L2 loss: 0.56514 Learning rate: 0.0004 Mask loss: 0.11509 RPN box loss: 0.03168 RPN score loss: 0.00931 RPN total loss: 0.04099 Total loss: 0.89703 timestamp: 1655065461.009765 iteration: 72175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05043 FastRCNN class loss: 0.05296 FastRCNN total loss: 0.10338 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.13903 RPN box loss: 0.01096 RPN score loss: 0.003 RPN total loss: 0.01396 Total loss: 0.82151 timestamp: 1655065464.2419982 iteration: 72180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15331 FastRCNN class loss: 0.13748 FastRCNN total loss: 0.29079 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.12007 RPN box loss: 0.01046 RPN score loss: 0.00525 RPN total loss: 0.01571 Total loss: 0.9917 timestamp: 1655065467.4588861 iteration: 72185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06638 FastRCNN class loss: 0.04237 FastRCNN total loss: 0.10875 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.12258 RPN box loss: 0.00632 RPN score loss: 0.00396 RPN total loss: 0.01028 Total loss: 0.80675 timestamp: 1655065470.7124164 iteration: 72190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11801 FastRCNN class loss: 0.07944 FastRCNN total loss: 0.19745 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.14139 RPN box loss: 0.01358 RPN score loss: 0.00843 RPN total loss: 0.02201 Total loss: 0.92599 timestamp: 1655065474.002848 iteration: 72195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10242 FastRCNN class loss: 0.06402 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.25352 RPN box loss: 0.01152 RPN score loss: 0.00477 RPN total loss: 0.01629 Total loss: 1.00138 timestamp: 1655065477.3153303 iteration: 72200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06076 FastRCNN class loss: 0.0685 FastRCNN total loss: 0.12927 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.10406 RPN box loss: 0.00748 RPN score loss: 0.00329 RPN total loss: 0.01077 Total loss: 0.80923 timestamp: 1655065480.5753393 iteration: 72205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05937 FastRCNN class loss: 0.03739 FastRCNN total loss: 0.09675 L1 loss: 0.0000e+00 L2 loss: 0.56513 Learning rate: 0.0004 Mask loss: 0.1253 RPN box loss: 0.02116 RPN score loss: 0.0016 RPN total loss: 0.02276 Total loss: 0.80994 timestamp: 1655065483.7710803 iteration: 72210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12164 FastRCNN class loss: 0.10458 FastRCNN total loss: 0.22622 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.22888 RPN box loss: 0.03413 RPN score loss: 0.01539 RPN total loss: 0.04952 Total loss: 1.06974 timestamp: 1655065487.0395446 iteration: 72215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09734 FastRCNN class loss: 0.08001 FastRCNN total loss: 0.17735 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.16756 RPN box loss: 0.00645 RPN score loss: 0.006 RPN total loss: 0.01244 Total loss: 0.92248 timestamp: 1655065490.3583376 iteration: 72220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12339 FastRCNN class loss: 0.06739 FastRCNN total loss: 0.19079 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.10135 RPN box loss: 0.02199 RPN score loss: 0.00201 RPN total loss: 0.024 Total loss: 0.88126 timestamp: 1655065493.6089842 iteration: 72225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.07467 FastRCNN total loss: 0.18511 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.13519 RPN box loss: 0.01314 RPN score loss: 0.01086 RPN total loss: 0.02399 Total loss: 0.90942 timestamp: 1655065496.8792355 iteration: 72230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14163 FastRCNN class loss: 0.06545 FastRCNN total loss: 0.20707 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.14746 RPN box loss: 0.00558 RPN score loss: 0.00291 RPN total loss: 0.00849 Total loss: 0.92814 timestamp: 1655065500.156511 iteration: 72235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08708 FastRCNN class loss: 0.08021 FastRCNN total loss: 0.16729 L1 loss: 0.0000e+00 L2 loss: 0.56512 Learning rate: 0.0004 Mask loss: 0.11776 RPN box loss: 0.01467 RPN score loss: 0.00687 RPN total loss: 0.02154 Total loss: 0.8717 timestamp: 1655065503.3627899 iteration: 72240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10042 FastRCNN class loss: 0.10457 FastRCNN total loss: 0.205 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.18597 RPN box loss: 0.01282 RPN score loss: 0.00649 RPN total loss: 0.01931 Total loss: 0.97539 timestamp: 1655065506.6148698 iteration: 72245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06922 FastRCNN class loss: 0.05037 FastRCNN total loss: 0.11959 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.14031 RPN box loss: 0.01535 RPN score loss: 0.00448 RPN total loss: 0.01983 Total loss: 0.84484 timestamp: 1655065509.860904 iteration: 72250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09229 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.16104 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.10628 RPN box loss: 0.03268 RPN score loss: 0.00971 RPN total loss: 0.04239 Total loss: 0.87482 timestamp: 1655065513.0775235 iteration: 72255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04394 FastRCNN class loss: 0.03223 FastRCNN total loss: 0.07618 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.11089 RPN box loss: 0.00506 RPN score loss: 0.00367 RPN total loss: 0.00873 Total loss: 0.7609 timestamp: 1655065516.4046369 iteration: 72260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11511 FastRCNN class loss: 0.10579 FastRCNN total loss: 0.2209 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.21371 RPN box loss: 0.01678 RPN score loss: 0.00766 RPN total loss: 0.02444 Total loss: 1.02416 timestamp: 1655065519.704493 iteration: 72265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11869 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.18443 L1 loss: 0.0000e+00 L2 loss: 0.56511 Learning rate: 0.0004 Mask loss: 0.11787 RPN box loss: 0.00975 RPN score loss: 0.0097 RPN total loss: 0.01945 Total loss: 0.88685 timestamp: 1655065522.9844885 iteration: 72270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07291 FastRCNN class loss: 0.03668 FastRCNN total loss: 0.10959 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.12162 RPN box loss: 0.00858 RPN score loss: 0.00312 RPN total loss: 0.0117 Total loss: 0.80801 timestamp: 1655065526.2756197 iteration: 72275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06419 FastRCNN class loss: 0.05261 FastRCNN total loss: 0.1168 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.11001 RPN box loss: 0.0249 RPN score loss: 0.00772 RPN total loss: 0.03262 Total loss: 0.82453 timestamp: 1655065529.5742233 iteration: 72280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07305 FastRCNN class loss: 0.06164 FastRCNN total loss: 0.13468 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.10937 RPN box loss: 0.01123 RPN score loss: 0.00344 RPN total loss: 0.01467 Total loss: 0.82382 timestamp: 1655065532.795138 iteration: 72285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11016 FastRCNN class loss: 0.1122 FastRCNN total loss: 0.22235 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.15193 RPN box loss: 0.00941 RPN score loss: 0.00549 RPN total loss: 0.01489 Total loss: 0.95428 timestamp: 1655065536.023455 iteration: 72290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11646 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.17625 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.11905 RPN box loss: 0.00497 RPN score loss: 0.00616 RPN total loss: 0.01113 Total loss: 0.87153 timestamp: 1655065539.3343499 iteration: 72295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16613 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.23183 L1 loss: 0.0000e+00 L2 loss: 0.5651 Learning rate: 0.0004 Mask loss: 0.189 RPN box loss: 0.00816 RPN score loss: 0.00214 RPN total loss: 0.01029 Total loss: 0.99621 timestamp: 1655065542.5572824 iteration: 72300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11084 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.18085 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.11952 RPN box loss: 0.00696 RPN score loss: 0.00426 RPN total loss: 0.01122 Total loss: 0.87669 timestamp: 1655065545.8937416 iteration: 72305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11272 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.19006 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.16062 RPN box loss: 0.01912 RPN score loss: 0.00779 RPN total loss: 0.02692 Total loss: 0.9427 timestamp: 1655065549.1305163 iteration: 72310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03699 FastRCNN class loss: 0.05423 FastRCNN total loss: 0.09122 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.09842 RPN box loss: 0.01231 RPN score loss: 0.0031 RPN total loss: 0.0154 Total loss: 0.77013 timestamp: 1655065552.418791 iteration: 72315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06556 FastRCNN class loss: 0.07435 FastRCNN total loss: 0.1399 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.09825 RPN box loss: 0.01651 RPN score loss: 0.00853 RPN total loss: 0.02504 Total loss: 0.82828 timestamp: 1655065555.7158444 iteration: 72320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10197 FastRCNN class loss: 0.07439 FastRCNN total loss: 0.17636 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.15632 RPN box loss: 0.01872 RPN score loss: 0.00796 RPN total loss: 0.02668 Total loss: 0.92445 timestamp: 1655065558.9465716 iteration: 72325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12298 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.19386 L1 loss: 0.0000e+00 L2 loss: 0.56509 Learning rate: 0.0004 Mask loss: 0.12067 RPN box loss: 0.00762 RPN score loss: 0.00614 RPN total loss: 0.01376 Total loss: 0.89337 timestamp: 1655065562.2269118 iteration: 72330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08921 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.15455 L1 loss: 0.0000e+00 L2 loss: 0.56508 Learning rate: 0.0004 Mask loss: 0.16117 RPN box loss: 0.01187 RPN score loss: 0.00352 RPN total loss: 0.01539 Total loss: 0.89619 timestamp: 1655065565.4842355 iteration: 72335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07176 FastRCNN class loss: 0.04727 FastRCNN total loss: 0.11902 L1 loss: 0.0000e+00 L2 loss: 0.56508 Learning rate: 0.0004 Mask loss: 0.11651 RPN box loss: 0.01123 RPN score loss: 0.00719 RPN total loss: 0.01842 Total loss: 0.81904 timestamp: 1655065568.679145 iteration: 72340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06072 FastRCNN class loss: 0.0706 FastRCNN total loss: 0.13132 L1 loss: 0.0000e+00 L2 loss: 0.56508 Learning rate: 0.0004 Mask loss: 0.09347 RPN box loss: 0.00983 RPN score loss: 0.00306 RPN total loss: 0.01289 Total loss: 0.80275 timestamp: 1655065571.9370975 iteration: 72345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08365 FastRCNN class loss: 0.04044 FastRCNN total loss: 0.12409 L1 loss: 0.0000e+00 L2 loss: 0.56508 Learning rate: 0.0004 Mask loss: 0.14845 RPN box loss: 0.02475 RPN score loss: 0.00437 RPN total loss: 0.02912 Total loss: 0.86674 timestamp: 1655065575.2817771 iteration: 72350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10826 FastRCNN class loss: 0.07571 FastRCNN total loss: 0.18397 L1 loss: 0.0000e+00 L2 loss: 0.56508 Learning rate: 0.0004 Mask loss: 0.12446 RPN box loss: 0.0126 RPN score loss: 0.00451 RPN total loss: 0.01712 Total loss: 0.89062 timestamp: 1655065578.56465 iteration: 72355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13305 FastRCNN class loss: 0.09661 FastRCNN total loss: 0.22966 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.14163 RPN box loss: 0.02417 RPN score loss: 0.00429 RPN total loss: 0.02846 Total loss: 0.96483 timestamp: 1655065581.8209765 iteration: 72360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04284 FastRCNN class loss: 0.04056 FastRCNN total loss: 0.0834 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.23165 RPN box loss: 0.03329 RPN score loss: 0.00306 RPN total loss: 0.03636 Total loss: 0.91647 timestamp: 1655065585.1197095 iteration: 72365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04768 FastRCNN class loss: 0.04677 FastRCNN total loss: 0.09445 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.09897 RPN box loss: 0.01085 RPN score loss: 0.00284 RPN total loss: 0.0137 Total loss: 0.77219 timestamp: 1655065588.4160173 iteration: 72370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07905 FastRCNN class loss: 0.05325 FastRCNN total loss: 0.1323 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.12546 RPN box loss: 0.00733 RPN score loss: 0.00615 RPN total loss: 0.01348 Total loss: 0.83631 timestamp: 1655065591.6511133 iteration: 72375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05648 FastRCNN class loss: 0.06362 FastRCNN total loss: 0.1201 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.15012 RPN box loss: 0.02743 RPN score loss: 0.00281 RPN total loss: 0.03024 Total loss: 0.86552 timestamp: 1655065594.9057114 iteration: 72380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09313 FastRCNN class loss: 0.06364 FastRCNN total loss: 0.15677 L1 loss: 0.0000e+00 L2 loss: 0.56507 Learning rate: 0.0004 Mask loss: 0.0992 RPN box loss: 0.00644 RPN score loss: 0.00243 RPN total loss: 0.00887 Total loss: 0.82991 timestamp: 1655065598.1817443 iteration: 72385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0848 FastRCNN class loss: 0.07667 FastRCNN total loss: 0.16147 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.1155 RPN box loss: 0.02715 RPN score loss: 0.00672 RPN total loss: 0.03387 Total loss: 0.8759 timestamp: 1655065601.4040146 iteration: 72390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07271 FastRCNN class loss: 0.04925 FastRCNN total loss: 0.12196 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.13017 RPN box loss: 0.01154 RPN score loss: 0.00219 RPN total loss: 0.01373 Total loss: 0.83092 timestamp: 1655065604.6610508 iteration: 72395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07815 FastRCNN class loss: 0.04076 FastRCNN total loss: 0.11891 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.11769 RPN box loss: 0.02058 RPN score loss: 0.00842 RPN total loss: 0.02901 Total loss: 0.83067 timestamp: 1655065607.9523497 iteration: 72400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11522 FastRCNN class loss: 0.07354 FastRCNN total loss: 0.18877 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.12249 RPN box loss: 0.05715 RPN score loss: 0.00721 RPN total loss: 0.06436 Total loss: 0.94068 timestamp: 1655065611.2135339 iteration: 72405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11274 FastRCNN class loss: 0.05348 FastRCNN total loss: 0.16622 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.16286 RPN box loss: 0.0089 RPN score loss: 0.00232 RPN total loss: 0.01122 Total loss: 0.90536 timestamp: 1655065614.4631343 iteration: 72410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12077 FastRCNN class loss: 0.07934 FastRCNN total loss: 0.20011 L1 loss: 0.0000e+00 L2 loss: 0.56506 Learning rate: 0.0004 Mask loss: 0.19583 RPN box loss: 0.01203 RPN score loss: 0.00295 RPN total loss: 0.01498 Total loss: 0.97598 timestamp: 1655065617.840341 iteration: 72415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09518 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.15614 L1 loss: 0.0000e+00 L2 loss: 0.56505 Learning rate: 0.0004 Mask loss: 0.11457 RPN box loss: 0.01802 RPN score loss: 0.00446 RPN total loss: 0.02247 Total loss: 0.85824 timestamp: 1655065621.0639343 iteration: 72420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08141 FastRCNN class loss: 0.06118 FastRCNN total loss: 0.14259 L1 loss: 0.0000e+00 L2 loss: 0.56505 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.01595 RPN score loss: 0.01701 RPN total loss: 0.03296 Total loss: 0.87889 timestamp: 1655065624.35357 iteration: 72425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09458 FastRCNN class loss: 0.08294 FastRCNN total loss: 0.17751 L1 loss: 0.0000e+00 L2 loss: 0.56505 Learning rate: 0.0004 Mask loss: 0.18725 RPN box loss: 0.05891 RPN score loss: 0.01054 RPN total loss: 0.06945 Total loss: 0.99926 timestamp: 1655065627.600278 iteration: 72430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10376 FastRCNN class loss: 0.07702 FastRCNN total loss: 0.18078 L1 loss: 0.0000e+00 L2 loss: 0.56505 Learning rate: 0.0004 Mask loss: 0.13617 RPN box loss: 0.02894 RPN score loss: 0.00248 RPN total loss: 0.03142 Total loss: 0.91342 timestamp: 1655065630.8745525 iteration: 72435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11174 FastRCNN class loss: 0.0506 FastRCNN total loss: 0.16234 L1 loss: 0.0000e+00 L2 loss: 0.56505 Learning rate: 0.0004 Mask loss: 0.10816 RPN box loss: 0.00737 RPN score loss: 0.00486 RPN total loss: 0.01223 Total loss: 0.84777 timestamp: 1655065634.1302757 iteration: 72440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14066 FastRCNN class loss: 0.06819 FastRCNN total loss: 0.20885 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.18254 RPN box loss: 0.05528 RPN score loss: 0.01124 RPN total loss: 0.06652 Total loss: 1.02296 timestamp: 1655065637.3669212 iteration: 72445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.08765 FastRCNN total loss: 0.20457 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.17319 RPN box loss: 0.01797 RPN score loss: 0.00584 RPN total loss: 0.0238 Total loss: 0.96661 timestamp: 1655065640.7121568 iteration: 72450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08671 FastRCNN class loss: 0.08104 FastRCNN total loss: 0.16775 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.15749 RPN box loss: 0.0115 RPN score loss: 0.00803 RPN total loss: 0.01953 Total loss: 0.90982 timestamp: 1655065644.0365648 iteration: 72455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.06045 FastRCNN total loss: 0.18171 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.18191 RPN box loss: 0.02423 RPN score loss: 0.00424 RPN total loss: 0.02847 Total loss: 0.95714 timestamp: 1655065647.3292968 iteration: 72460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.16896 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.18354 RPN box loss: 0.01617 RPN score loss: 0.00386 RPN total loss: 0.02004 Total loss: 0.93758 timestamp: 1655065650.5897162 iteration: 72465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.05028 FastRCNN total loss: 0.13841 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.11835 RPN box loss: 0.00548 RPN score loss: 0.0019 RPN total loss: 0.00738 Total loss: 0.82918 timestamp: 1655065653.8875513 iteration: 72470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1011 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.56504 Learning rate: 0.0004 Mask loss: 0.14477 RPN box loss: 0.01409 RPN score loss: 0.01461 RPN total loss: 0.0287 Total loss: 0.89966 timestamp: 1655065657.1570795 iteration: 72475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13445 FastRCNN class loss: 0.07665 FastRCNN total loss: 0.21109 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.17645 RPN box loss: 0.02113 RPN score loss: 0.00391 RPN total loss: 0.02505 Total loss: 0.97763 timestamp: 1655065660.4170053 iteration: 72480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07445 FastRCNN class loss: 0.0735 FastRCNN total loss: 0.14795 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.14466 RPN box loss: 0.00904 RPN score loss: 0.00614 RPN total loss: 0.01518 Total loss: 0.87282 timestamp: 1655065663.776799 iteration: 72485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.06518 FastRCNN total loss: 0.14963 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.10568 RPN box loss: 0.01568 RPN score loss: 0.00212 RPN total loss: 0.0178 Total loss: 0.83813 timestamp: 1655065667.0426552 iteration: 72490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09602 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.16125 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.08668 RPN box loss: 0.00863 RPN score loss: 0.00458 RPN total loss: 0.01322 Total loss: 0.82618 timestamp: 1655065670.2920573 iteration: 72495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07658 FastRCNN class loss: 0.05227 FastRCNN total loss: 0.12886 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.09607 RPN box loss: 0.00912 RPN score loss: 0.00385 RPN total loss: 0.01297 Total loss: 0.80293 timestamp: 1655065673.5897064 iteration: 72500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.09085 FastRCNN total loss: 0.19193 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.08356 RPN box loss: 0.02061 RPN score loss: 0.00395 RPN total loss: 0.02455 Total loss: 0.86507 timestamp: 1655065676.9632382 iteration: 72505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09015 FastRCNN class loss: 0.08745 FastRCNN total loss: 0.1776 L1 loss: 0.0000e+00 L2 loss: 0.56503 Learning rate: 0.0004 Mask loss: 0.14627 RPN box loss: 0.01702 RPN score loss: 0.00601 RPN total loss: 0.02303 Total loss: 0.91194 timestamp: 1655065680.2274752 iteration: 72510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07469 FastRCNN class loss: 0.07154 FastRCNN total loss: 0.14624 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.12739 RPN box loss: 0.00942 RPN score loss: 0.00348 RPN total loss: 0.01291 Total loss: 0.85156 timestamp: 1655065683.5803967 iteration: 72515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13622 FastRCNN class loss: 0.10096 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.20563 RPN box loss: 0.02274 RPN score loss: 0.01084 RPN total loss: 0.03357 Total loss: 1.0414 timestamp: 1655065686.9288185 iteration: 72520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08101 FastRCNN class loss: 0.079 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.19005 RPN box loss: 0.01887 RPN score loss: 0.0118 RPN total loss: 0.03067 Total loss: 0.94574 timestamp: 1655065690.2057326 iteration: 72525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09244 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.16912 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.13317 RPN box loss: 0.03639 RPN score loss: 0.0054 RPN total loss: 0.04179 Total loss: 0.9091 timestamp: 1655065693.4341896 iteration: 72530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10236 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.15815 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.12466 RPN box loss: 0.00919 RPN score loss: 0.00224 RPN total loss: 0.01143 Total loss: 0.85925 timestamp: 1655065696.7362778 iteration: 72535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15618 FastRCNN class loss: 0.07811 FastRCNN total loss: 0.23429 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.16297 RPN box loss: 0.00866 RPN score loss: 0.00481 RPN total loss: 0.01347 Total loss: 0.97574 timestamp: 1655065700.0381572 iteration: 72540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09346 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.16951 L1 loss: 0.0000e+00 L2 loss: 0.56502 Learning rate: 0.0004 Mask loss: 0.18098 RPN box loss: 0.01783 RPN score loss: 0.00589 RPN total loss: 0.02371 Total loss: 0.93922 timestamp: 1655065703.3200452 iteration: 72545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09377 FastRCNN class loss: 0.04093 FastRCNN total loss: 0.1347 L1 loss: 0.0000e+00 L2 loss: 0.56501 Learning rate: 0.0004 Mask loss: 0.16481 RPN box loss: 0.03129 RPN score loss: 0.00386 RPN total loss: 0.03515 Total loss: 0.89968 timestamp: 1655065706.6003866 iteration: 72550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08242 FastRCNN class loss: 0.0532 FastRCNN total loss: 0.13562 L1 loss: 0.0000e+00 L2 loss: 0.56501 Learning rate: 0.0004 Mask loss: 0.14426 RPN box loss: 0.00844 RPN score loss: 0.00167 RPN total loss: 0.0101 Total loss: 0.855 timestamp: 1655065709.902676 iteration: 72555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10099 FastRCNN class loss: 0.06692 FastRCNN total loss: 0.16791 L1 loss: 0.0000e+00 L2 loss: 0.56501 Learning rate: 0.0004 Mask loss: 0.19658 RPN box loss: 0.01919 RPN score loss: 0.00782 RPN total loss: 0.02701 Total loss: 0.95651 timestamp: 1655065713.1397655 iteration: 72560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07015 FastRCNN class loss: 0.09675 FastRCNN total loss: 0.1669 L1 loss: 0.0000e+00 L2 loss: 0.56501 Learning rate: 0.0004 Mask loss: 0.15866 RPN box loss: 0.02918 RPN score loss: 0.00826 RPN total loss: 0.03744 Total loss: 0.92801 timestamp: 1655065716.4475234 iteration: 72565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15359 FastRCNN class loss: 0.10632 FastRCNN total loss: 0.25991 L1 loss: 0.0000e+00 L2 loss: 0.56501 Learning rate: 0.0004 Mask loss: 0.15083 RPN box loss: 0.02451 RPN score loss: 0.00766 RPN total loss: 0.03218 Total loss: 1.00792 timestamp: 1655065719.7367396 iteration: 72570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07295 FastRCNN class loss: 0.04884 FastRCNN total loss: 0.12179 L1 loss: 0.0000e+00 L2 loss: 0.565 Learning rate: 0.0004 Mask loss: 0.09568 RPN box loss: 0.00475 RPN score loss: 0.00138 RPN total loss: 0.00613 Total loss: 0.78861 timestamp: 1655065722.969476 iteration: 72575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07716 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.13812 L1 loss: 0.0000e+00 L2 loss: 0.565 Learning rate: 0.0004 Mask loss: 0.12784 RPN box loss: 0.00666 RPN score loss: 0.0035 RPN total loss: 0.01016 Total loss: 0.84113 timestamp: 1655065726.2070262 iteration: 72580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09953 FastRCNN class loss: 0.09855 FastRCNN total loss: 0.19808 L1 loss: 0.0000e+00 L2 loss: 0.565 Learning rate: 0.0004 Mask loss: 0.17937 RPN box loss: 0.02505 RPN score loss: 0.01433 RPN total loss: 0.03938 Total loss: 0.98182 timestamp: 1655065729.5361009 iteration: 72585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09688 FastRCNN class loss: 0.05595 FastRCNN total loss: 0.15284 L1 loss: 0.0000e+00 L2 loss: 0.565 Learning rate: 0.0004 Mask loss: 0.17385 RPN box loss: 0.01189 RPN score loss: 0.00191 RPN total loss: 0.0138 Total loss: 0.90548 timestamp: 1655065732.751742 iteration: 72590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1308 FastRCNN class loss: 0.04728 FastRCNN total loss: 0.17808 L1 loss: 0.0000e+00 L2 loss: 0.565 Learning rate: 0.0004 Mask loss: 0.09707 RPN box loss: 0.01293 RPN score loss: 0.00432 RPN total loss: 0.01725 Total loss: 0.85739 timestamp: 1655065735.9562657 iteration: 72595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1472 FastRCNN class loss: 0.10606 FastRCNN total loss: 0.25326 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.1399 RPN box loss: 0.01887 RPN score loss: 0.00828 RPN total loss: 0.02715 Total loss: 0.98531 timestamp: 1655065739.2662182 iteration: 72600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0781 FastRCNN class loss: 0.05931 FastRCNN total loss: 0.1374 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.18122 RPN box loss: 0.01534 RPN score loss: 0.00226 RPN total loss: 0.0176 Total loss: 0.90122 timestamp: 1655065742.507451 iteration: 72605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09558 FastRCNN class loss: 0.05222 FastRCNN total loss: 0.1478 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.16209 RPN box loss: 0.0082 RPN score loss: 0.00486 RPN total loss: 0.01306 Total loss: 0.88793 timestamp: 1655065745.7942226 iteration: 72610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09055 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.16253 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.08353 RPN box loss: 0.00831 RPN score loss: 0.00312 RPN total loss: 0.01143 Total loss: 0.82248 timestamp: 1655065749.0907352 iteration: 72615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08484 FastRCNN class loss: 0.06748 FastRCNN total loss: 0.15232 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.17838 RPN box loss: 0.00828 RPN score loss: 0.00968 RPN total loss: 0.01796 Total loss: 0.91365 timestamp: 1655065752.2995734 iteration: 72620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08439 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.14905 L1 loss: 0.0000e+00 L2 loss: 0.56499 Learning rate: 0.0004 Mask loss: 0.2341 RPN box loss: 0.01569 RPN score loss: 0.00086 RPN total loss: 0.01656 Total loss: 0.9647 timestamp: 1655065755.5063667 iteration: 72625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10251 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.16493 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.10838 RPN box loss: 0.00708 RPN score loss: 0.0051 RPN total loss: 0.01218 Total loss: 0.85047 timestamp: 1655065758.801828 iteration: 72630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04561 FastRCNN class loss: 0.05953 FastRCNN total loss: 0.10514 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.1216 RPN box loss: 0.01626 RPN score loss: 0.00461 RPN total loss: 0.02086 Total loss: 0.81259 timestamp: 1655065762.0780995 iteration: 72635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08988 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.13978 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.09177 RPN box loss: 0.00368 RPN score loss: 0.0032 RPN total loss: 0.00688 Total loss: 0.80341 timestamp: 1655065765.378138 iteration: 72640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11758 FastRCNN class loss: 0.06282 FastRCNN total loss: 0.18041 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.14001 RPN box loss: 0.02758 RPN score loss: 0.00231 RPN total loss: 0.02989 Total loss: 0.91529 timestamp: 1655065768.6317585 iteration: 72645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06781 FastRCNN class loss: 0.04394 FastRCNN total loss: 0.11175 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.0885 RPN box loss: 0.00265 RPN score loss: 0.0051 RPN total loss: 0.00775 Total loss: 0.77298 timestamp: 1655065771.9387264 iteration: 72650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08887 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.13891 L1 loss: 0.0000e+00 L2 loss: 0.56498 Learning rate: 0.0004 Mask loss: 0.1083 RPN box loss: 0.0073 RPN score loss: 0.0045 RPN total loss: 0.0118 Total loss: 0.82399 timestamp: 1655065775.2243922 iteration: 72655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0556 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.11698 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.14536 RPN box loss: 0.00767 RPN score loss: 0.00363 RPN total loss: 0.01131 Total loss: 0.83862 timestamp: 1655065778.515244 iteration: 72660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10044 FastRCNN class loss: 0.06505 FastRCNN total loss: 0.16549 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.12616 RPN box loss: 0.01352 RPN score loss: 0.00314 RPN total loss: 0.01666 Total loss: 0.87328 timestamp: 1655065781.803041 iteration: 72665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13405 FastRCNN class loss: 0.09478 FastRCNN total loss: 0.22883 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.1397 RPN box loss: 0.03004 RPN score loss: 0.00989 RPN total loss: 0.03993 Total loss: 0.97343 timestamp: 1655065785.08436 iteration: 72670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12769 FastRCNN class loss: 0.07619 FastRCNN total loss: 0.20388 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.16505 RPN box loss: 0.02543 RPN score loss: 0.00498 RPN total loss: 0.03041 Total loss: 0.96431 timestamp: 1655065788.3475335 iteration: 72675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09728 FastRCNN class loss: 0.06011 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.14868 RPN box loss: 0.0059 RPN score loss: 0.00148 RPN total loss: 0.00739 Total loss: 0.87842 timestamp: 1655065791.658856 iteration: 72680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08554 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.15133 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.16116 RPN box loss: 0.00963 RPN score loss: 0.00379 RPN total loss: 0.01342 Total loss: 0.89087 timestamp: 1655065794.9018624 iteration: 72685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04815 FastRCNN class loss: 0.06762 FastRCNN total loss: 0.11577 L1 loss: 0.0000e+00 L2 loss: 0.56497 Learning rate: 0.0004 Mask loss: 0.13648 RPN box loss: 0.01167 RPN score loss: 0.00662 RPN total loss: 0.01828 Total loss: 0.8355 timestamp: 1655065798.136554 iteration: 72690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09494 FastRCNN class loss: 0.11351 FastRCNN total loss: 0.20846 L1 loss: 0.0000e+00 L2 loss: 0.56496 Learning rate: 0.0004 Mask loss: 0.14951 RPN box loss: 0.02657 RPN score loss: 0.01306 RPN total loss: 0.03964 Total loss: 0.96256 timestamp: 1655065801.3823075 iteration: 72695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02996 FastRCNN class loss: 0.03596 FastRCNN total loss: 0.06592 L1 loss: 0.0000e+00 L2 loss: 0.56496 Learning rate: 0.0004 Mask loss: 0.13667 RPN box loss: 0.01452 RPN score loss: 0.00352 RPN total loss: 0.01804 Total loss: 0.78559 timestamp: 1655065804.6076567 iteration: 72700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0787 FastRCNN class loss: 0.04689 FastRCNN total loss: 0.12559 L1 loss: 0.0000e+00 L2 loss: 0.56496 Learning rate: 0.0004 Mask loss: 0.12178 RPN box loss: 0.03887 RPN score loss: 0.00724 RPN total loss: 0.04611 Total loss: 0.85844 timestamp: 1655065807.9240096 iteration: 72705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11698 FastRCNN class loss: 0.10817 FastRCNN total loss: 0.22515 L1 loss: 0.0000e+00 L2 loss: 0.56496 Learning rate: 0.0004 Mask loss: 0.15479 RPN box loss: 0.02369 RPN score loss: 0.01017 RPN total loss: 0.03386 Total loss: 0.97876 timestamp: 1655065811.243468 iteration: 72710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06835 FastRCNN class loss: 0.04207 FastRCNN total loss: 0.11042 L1 loss: 0.0000e+00 L2 loss: 0.56496 Learning rate: 0.0004 Mask loss: 0.12025 RPN box loss: 0.02074 RPN score loss: 0.00184 RPN total loss: 0.02259 Total loss: 0.81822 timestamp: 1655065814.5415082 iteration: 72715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13441 FastRCNN class loss: 0.10022 FastRCNN total loss: 0.23464 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.10442 RPN box loss: 0.00954 RPN score loss: 0.00576 RPN total loss: 0.0153 Total loss: 0.91931 timestamp: 1655065817.8781815 iteration: 72720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05306 FastRCNN class loss: 0.06732 FastRCNN total loss: 0.12038 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.13384 RPN box loss: 0.01705 RPN score loss: 0.01113 RPN total loss: 0.02819 Total loss: 0.84736 timestamp: 1655065821.1439621 iteration: 72725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05847 FastRCNN class loss: 0.06593 FastRCNN total loss: 0.1244 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.16099 RPN box loss: 0.01935 RPN score loss: 0.00824 RPN total loss: 0.0276 Total loss: 0.87794 timestamp: 1655065824.4492683 iteration: 72730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12641 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.19321 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.11152 RPN box loss: 0.01886 RPN score loss: 0.00759 RPN total loss: 0.02645 Total loss: 0.89613 timestamp: 1655065827.705488 iteration: 72735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08135 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.13469 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.13562 RPN box loss: 0.00648 RPN score loss: 0.00393 RPN total loss: 0.01041 Total loss: 0.84567 timestamp: 1655065830.9571311 iteration: 72740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14454 FastRCNN class loss: 0.06559 FastRCNN total loss: 0.21013 L1 loss: 0.0000e+00 L2 loss: 0.56495 Learning rate: 0.0004 Mask loss: 0.15574 RPN box loss: 0.05033 RPN score loss: 0.00486 RPN total loss: 0.05518 Total loss: 0.986 timestamp: 1655065834.2356594 iteration: 72745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11627 FastRCNN class loss: 0.07119 FastRCNN total loss: 0.18746 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.15173 RPN box loss: 0.06096 RPN score loss: 0.00374 RPN total loss: 0.06469 Total loss: 0.96883 timestamp: 1655065837.5451248 iteration: 72750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13205 FastRCNN class loss: 0.06906 FastRCNN total loss: 0.20111 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.1127 RPN box loss: 0.02095 RPN score loss: 0.00158 RPN total loss: 0.02253 Total loss: 0.90128 timestamp: 1655065840.7862895 iteration: 72755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16691 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.22946 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.18474 RPN box loss: 0.02058 RPN score loss: 0.0121 RPN total loss: 0.03268 Total loss: 1.01183 timestamp: 1655065844.0371559 iteration: 72760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09915 FastRCNN class loss: 0.10024 FastRCNN total loss: 0.19939 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.152 RPN box loss: 0.01088 RPN score loss: 0.00609 RPN total loss: 0.01697 Total loss: 0.9333 timestamp: 1655065847.2842755 iteration: 72765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1412 FastRCNN class loss: 0.07651 FastRCNN total loss: 0.21771 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.15095 RPN box loss: 0.00853 RPN score loss: 0.00292 RPN total loss: 0.01145 Total loss: 0.94505 timestamp: 1655065850.5086417 iteration: 72770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06112 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.12522 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.11379 RPN box loss: 0.03164 RPN score loss: 0.00299 RPN total loss: 0.03463 Total loss: 0.83857 timestamp: 1655065853.7283034 iteration: 72775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10152 FastRCNN class loss: 0.10982 FastRCNN total loss: 0.21135 L1 loss: 0.0000e+00 L2 loss: 0.56494 Learning rate: 0.0004 Mask loss: 0.17321 RPN box loss: 0.00957 RPN score loss: 0.00478 RPN total loss: 0.01435 Total loss: 0.96385 timestamp: 1655065857.023248 iteration: 72780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10754 FastRCNN class loss: 0.05017 FastRCNN total loss: 0.15771 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.10567 RPN box loss: 0.02002 RPN score loss: 0.00046 RPN total loss: 0.02048 Total loss: 0.84879 timestamp: 1655065860.3506324 iteration: 72785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08723 FastRCNN class loss: 0.05483 FastRCNN total loss: 0.14206 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.12678 RPN box loss: 0.00758 RPN score loss: 0.00585 RPN total loss: 0.01343 Total loss: 0.8472 timestamp: 1655065863.693931 iteration: 72790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03794 FastRCNN class loss: 0.04377 FastRCNN total loss: 0.08171 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.12911 RPN box loss: 0.00709 RPN score loss: 0.0032 RPN total loss: 0.01029 Total loss: 0.78604 timestamp: 1655065866.984285 iteration: 72795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07907 FastRCNN class loss: 0.03862 FastRCNN total loss: 0.11769 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.13643 RPN box loss: 0.00746 RPN score loss: 0.00246 RPN total loss: 0.00992 Total loss: 0.82896 timestamp: 1655065870.2411792 iteration: 72800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11012 FastRCNN class loss: 0.10648 FastRCNN total loss: 0.2166 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.18969 RPN box loss: 0.01023 RPN score loss: 0.0034 RPN total loss: 0.01363 Total loss: 0.98485 timestamp: 1655065873.5221493 iteration: 72805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06995 FastRCNN class loss: 0.06109 FastRCNN total loss: 0.13103 L1 loss: 0.0000e+00 L2 loss: 0.56493 Learning rate: 0.0004 Mask loss: 0.10034 RPN box loss: 0.00836 RPN score loss: 0.00252 RPN total loss: 0.01088 Total loss: 0.80718 timestamp: 1655065876.7769127 iteration: 72810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08276 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.1537 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.16236 RPN box loss: 0.03942 RPN score loss: 0.00297 RPN total loss: 0.04239 Total loss: 0.92337 timestamp: 1655065880.108166 iteration: 72815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08183 FastRCNN class loss: 0.05178 FastRCNN total loss: 0.13361 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.1219 RPN box loss: 0.00649 RPN score loss: 0.00138 RPN total loss: 0.00786 Total loss: 0.82829 timestamp: 1655065883.3458676 iteration: 72820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11269 FastRCNN class loss: 0.05865 FastRCNN total loss: 0.17135 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.10073 RPN box loss: 0.00994 RPN score loss: 0.00204 RPN total loss: 0.01198 Total loss: 0.84898 timestamp: 1655065886.630711 iteration: 72825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08899 FastRCNN class loss: 0.05694 FastRCNN total loss: 0.14593 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.13729 RPN box loss: 0.00973 RPN score loss: 0.00527 RPN total loss: 0.015 Total loss: 0.86314 timestamp: 1655065889.9629757 iteration: 72830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07858 FastRCNN class loss: 0.06826 FastRCNN total loss: 0.14684 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.1919 RPN box loss: 0.00956 RPN score loss: 0.00212 RPN total loss: 0.01168 Total loss: 0.91534 timestamp: 1655065893.2024982 iteration: 72835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07224 FastRCNN class loss: 0.07779 FastRCNN total loss: 0.15004 L1 loss: 0.0000e+00 L2 loss: 0.56492 Learning rate: 0.0004 Mask loss: 0.11099 RPN box loss: 0.02881 RPN score loss: 0.00298 RPN total loss: 0.0318 Total loss: 0.85774 timestamp: 1655065896.5086954 iteration: 72840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1531 FastRCNN class loss: 0.11019 FastRCNN total loss: 0.26329 L1 loss: 0.0000e+00 L2 loss: 0.56491 Learning rate: 0.0004 Mask loss: 0.19412 RPN box loss: 0.01264 RPN score loss: 0.0099 RPN total loss: 0.02254 Total loss: 1.04487 timestamp: 1655065899.7752972 iteration: 72845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06848 FastRCNN class loss: 0.05576 FastRCNN total loss: 0.12425 L1 loss: 0.0000e+00 L2 loss: 0.56491 Learning rate: 0.0004 Mask loss: 0.10097 RPN box loss: 0.01639 RPN score loss: 0.00536 RPN total loss: 0.02175 Total loss: 0.81187 timestamp: 1655065902.985559 iteration: 72850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10431 FastRCNN class loss: 0.06609 FastRCNN total loss: 0.1704 L1 loss: 0.0000e+00 L2 loss: 0.56491 Learning rate: 0.0004 Mask loss: 0.14505 RPN box loss: 0.01087 RPN score loss: 0.00426 RPN total loss: 0.01513 Total loss: 0.89548 timestamp: 1655065906.2065613 iteration: 72855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06994 FastRCNN class loss: 0.09005 FastRCNN total loss: 0.15999 L1 loss: 0.0000e+00 L2 loss: 0.56491 Learning rate: 0.0004 Mask loss: 0.1633 RPN box loss: 0.00745 RPN score loss: 0.01105 RPN total loss: 0.0185 Total loss: 0.90669 timestamp: 1655065909.5079386 iteration: 72860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11319 FastRCNN class loss: 0.06795 FastRCNN total loss: 0.18114 L1 loss: 0.0000e+00 L2 loss: 0.56491 Learning rate: 0.0004 Mask loss: 0.09436 RPN box loss: 0.01456 RPN score loss: 0.00217 RPN total loss: 0.01673 Total loss: 0.85715 timestamp: 1655065912.7597506 iteration: 72865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0682 FastRCNN class loss: 0.06386 FastRCNN total loss: 0.13206 L1 loss: 0.0000e+00 L2 loss: 0.5649 Learning rate: 0.0004 Mask loss: 0.11979 RPN box loss: 0.00351 RPN score loss: 0.00397 RPN total loss: 0.00748 Total loss: 0.82423 timestamp: 1655065916.036672 iteration: 72870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07941 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.13357 L1 loss: 0.0000e+00 L2 loss: 0.5649 Learning rate: 0.0004 Mask loss: 0.14921 RPN box loss: 0.0117 RPN score loss: 0.00536 RPN total loss: 0.01706 Total loss: 0.86473 timestamp: 1655065919.2841885 iteration: 72875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09428 FastRCNN class loss: 0.07977 FastRCNN total loss: 0.17405 L1 loss: 0.0000e+00 L2 loss: 0.5649 Learning rate: 0.0004 Mask loss: 0.13091 RPN box loss: 0.02214 RPN score loss: 0.00226 RPN total loss: 0.0244 Total loss: 0.89426 timestamp: 1655065922.539853 iteration: 72880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07297 FastRCNN class loss: 0.04959 FastRCNN total loss: 0.12257 L1 loss: 0.0000e+00 L2 loss: 0.5649 Learning rate: 0.0004 Mask loss: 0.11122 RPN box loss: 0.01039 RPN score loss: 0.00096 RPN total loss: 0.01135 Total loss: 0.81003 timestamp: 1655065925.807251 iteration: 72885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09782 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.14595 L1 loss: 0.0000e+00 L2 loss: 0.5649 Learning rate: 0.0004 Mask loss: 0.17573 RPN box loss: 0.01392 RPN score loss: 0.00408 RPN total loss: 0.01799 Total loss: 0.90457 timestamp: 1655065929.0187776 iteration: 72890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10428 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.17485 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.17652 RPN box loss: 0.00928 RPN score loss: 0.00282 RPN total loss: 0.01211 Total loss: 0.92837 timestamp: 1655065932.283111 iteration: 72895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09328 FastRCNN class loss: 0.07478 FastRCNN total loss: 0.16806 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.14729 RPN box loss: 0.04957 RPN score loss: 0.00863 RPN total loss: 0.0582 Total loss: 0.93845 timestamp: 1655065935.5937824 iteration: 72900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09043 FastRCNN class loss: 0.08322 FastRCNN total loss: 0.17366 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.15844 RPN box loss: 0.01842 RPN score loss: 0.00564 RPN total loss: 0.02406 Total loss: 0.92105 timestamp: 1655065938.8683517 iteration: 72905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13915 FastRCNN class loss: 0.07101 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.13532 RPN box loss: 0.0188 RPN score loss: 0.01113 RPN total loss: 0.02993 Total loss: 0.9403 timestamp: 1655065942.0891812 iteration: 72910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11416 FastRCNN class loss: 0.08298 FastRCNN total loss: 0.19714 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.17596 RPN box loss: 0.01198 RPN score loss: 0.00587 RPN total loss: 0.01785 Total loss: 0.95584 timestamp: 1655065945.2674196 iteration: 72915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04161 FastRCNN class loss: 0.03218 FastRCNN total loss: 0.07379 L1 loss: 0.0000e+00 L2 loss: 0.56489 Learning rate: 0.0004 Mask loss: 0.09658 RPN box loss: 0.00555 RPN score loss: 0.00107 RPN total loss: 0.00662 Total loss: 0.74188 timestamp: 1655065948.5239198 iteration: 72920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14137 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.21477 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.1716 RPN box loss: 0.03954 RPN score loss: 0.01089 RPN total loss: 0.05043 Total loss: 1.00169 timestamp: 1655065951.818561 iteration: 72925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16502 FastRCNN class loss: 0.07635 FastRCNN total loss: 0.24136 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.2116 RPN box loss: 0.0133 RPN score loss: 0.0024 RPN total loss: 0.01571 Total loss: 1.03356 timestamp: 1655065955.059933 iteration: 72930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07169 FastRCNN class loss: 0.0523 FastRCNN total loss: 0.12399 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.20243 RPN box loss: 0.02486 RPN score loss: 0.00237 RPN total loss: 0.02724 Total loss: 0.91854 timestamp: 1655065958.3395424 iteration: 72935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08375 FastRCNN class loss: 0.07215 FastRCNN total loss: 0.1559 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.12513 RPN box loss: 0.01817 RPN score loss: 0.00503 RPN total loss: 0.0232 Total loss: 0.86911 timestamp: 1655065961.593079 iteration: 72940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07305 FastRCNN class loss: 0.04297 FastRCNN total loss: 0.11602 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.2791 RPN box loss: 0.00575 RPN score loss: 0.00402 RPN total loss: 0.00977 Total loss: 0.96977 timestamp: 1655065964.8507354 iteration: 72945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11732 FastRCNN class loss: 0.07244 FastRCNN total loss: 0.18976 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.16308 RPN box loss: 0.01723 RPN score loss: 0.01406 RPN total loss: 0.0313 Total loss: 0.94902 timestamp: 1655065968.1131418 iteration: 72950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.13723 L1 loss: 0.0000e+00 L2 loss: 0.56488 Learning rate: 0.0004 Mask loss: 0.11461 RPN box loss: 0.0129 RPN score loss: 0.00386 RPN total loss: 0.01676 Total loss: 0.83347 timestamp: 1655065971.321713 iteration: 72955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07916 FastRCNN class loss: 0.06568 FastRCNN total loss: 0.14484 L1 loss: 0.0000e+00 L2 loss: 0.56487 Learning rate: 0.0004 Mask loss: 0.13385 RPN box loss: 0.00883 RPN score loss: 0.00408 RPN total loss: 0.01291 Total loss: 0.85647 timestamp: 1655065974.536407 iteration: 72960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05411 FastRCNN class loss: 0.05537 FastRCNN total loss: 0.10947 L1 loss: 0.0000e+00 L2 loss: 0.56487 Learning rate: 0.0004 Mask loss: 0.11096 RPN box loss: 0.00856 RPN score loss: 0.00268 RPN total loss: 0.01124 Total loss: 0.79654 timestamp: 1655065977.7910259 iteration: 72965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1105 FastRCNN class loss: 0.07328 FastRCNN total loss: 0.18378 L1 loss: 0.0000e+00 L2 loss: 0.56487 Learning rate: 0.0004 Mask loss: 0.11432 RPN box loss: 0.02141 RPN score loss: 0.00422 RPN total loss: 0.02563 Total loss: 0.8886 timestamp: 1655065981.0000973 iteration: 72970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10171 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.17122 L1 loss: 0.0000e+00 L2 loss: 0.56487 Learning rate: 0.0004 Mask loss: 0.11774 RPN box loss: 0.01989 RPN score loss: 0.00891 RPN total loss: 0.0288 Total loss: 0.88263 timestamp: 1655065984.200782 iteration: 72975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08562 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.13384 L1 loss: 0.0000e+00 L2 loss: 0.56487 Learning rate: 0.0004 Mask loss: 0.13153 RPN box loss: 0.00243 RPN score loss: 0.0013 RPN total loss: 0.00373 Total loss: 0.83397 timestamp: 1655065987.4350839 iteration: 72980 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15314 FastRCNN class loss: 0.06945 FastRCNN total loss: 0.2226 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.15388 RPN box loss: 0.01269 RPN score loss: 0.00385 RPN total loss: 0.01654 Total loss: 0.95787 timestamp: 1655065990.8315144 iteration: 72985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.1191 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.14714 RPN box loss: 0.00779 RPN score loss: 0.00293 RPN total loss: 0.01072 Total loss: 0.84182 timestamp: 1655065994.098205 iteration: 72990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0943 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.15958 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.13034 RPN box loss: 0.00806 RPN score loss: 0.0032 RPN total loss: 0.01126 Total loss: 0.86604 timestamp: 1655065997.3458302 iteration: 72995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08372 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.1507 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.1158 RPN box loss: 0.06253 RPN score loss: 0.00579 RPN total loss: 0.06832 Total loss: 0.89967 timestamp: 1655066000.627318 iteration: 73000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07737 FastRCNN class loss: 0.09558 FastRCNN total loss: 0.17295 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.15184 RPN box loss: 0.01545 RPN score loss: 0.00689 RPN total loss: 0.02234 Total loss: 0.91198 timestamp: 1655066003.938855 iteration: 73005 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08318 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.13701 L1 loss: 0.0000e+00 L2 loss: 0.56486 Learning rate: 0.0004 Mask loss: 0.15438 RPN box loss: 0.00909 RPN score loss: 0.00588 RPN total loss: 0.01497 Total loss: 0.87123 timestamp: 1655066007.2027323 iteration: 73010 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09981 FastRCNN class loss: 0.1136 FastRCNN total loss: 0.21341 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.24595 RPN box loss: 0.02357 RPN score loss: 0.00963 RPN total loss: 0.0332 Total loss: 1.05742 timestamp: 1655066010.4634988 iteration: 73015 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10388 FastRCNN class loss: 0.08673 FastRCNN total loss: 0.19061 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.13311 RPN box loss: 0.01677 RPN score loss: 0.00832 RPN total loss: 0.02509 Total loss: 0.91366 timestamp: 1655066013.7802436 iteration: 73020 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0794 FastRCNN class loss: 0.04343 FastRCNN total loss: 0.12283 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.12226 RPN box loss: 0.00524 RPN score loss: 0.00173 RPN total loss: 0.00698 Total loss: 0.81692 timestamp: 1655066017.0429595 iteration: 73025 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11768 FastRCNN class loss: 0.08083 FastRCNN total loss: 0.19851 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.13755 RPN box loss: 0.01972 RPN score loss: 0.00249 RPN total loss: 0.02221 Total loss: 0.92312 timestamp: 1655066020.3288743 iteration: 73030 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07532 FastRCNN class loss: 0.05346 FastRCNN total loss: 0.12878 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.14552 RPN box loss: 0.00862 RPN score loss: 0.01296 RPN total loss: 0.02157 Total loss: 0.86072 timestamp: 1655066023.5923755 iteration: 73035 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0771 FastRCNN class loss: 0.04658 FastRCNN total loss: 0.12368 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.12192 RPN box loss: 0.00831 RPN score loss: 0.00153 RPN total loss: 0.00984 Total loss: 0.82029 timestamp: 1655066026.8718827 iteration: 73040 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.06182 FastRCNN total loss: 0.21031 L1 loss: 0.0000e+00 L2 loss: 0.56485 Learning rate: 0.0004 Mask loss: 0.13732 RPN box loss: 0.01272 RPN score loss: 0.00267 RPN total loss: 0.01539 Total loss: 0.92786 timestamp: 1655066030.1208081 iteration: 73045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1751 FastRCNN class loss: 0.07779 FastRCNN total loss: 0.25289 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.14225 RPN box loss: 0.01461 RPN score loss: 0.00387 RPN total loss: 0.01848 Total loss: 0.97846 timestamp: 1655066033.3559918 iteration: 73050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10998 FastRCNN class loss: 0.08571 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.1736 RPN box loss: 0.01499 RPN score loss: 0.01054 RPN total loss: 0.02553 Total loss: 0.95966 timestamp: 1655066036.609272 iteration: 73055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1035 FastRCNN class loss: 0.07574 FastRCNN total loss: 0.17924 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.11558 RPN box loss: 0.01097 RPN score loss: 0.00847 RPN total loss: 0.01944 Total loss: 0.87911 timestamp: 1655066039.9432812 iteration: 73060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17095 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.24771 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.10609 RPN box loss: 0.01136 RPN score loss: 0.00752 RPN total loss: 0.01888 Total loss: 0.93752 timestamp: 1655066043.2061884 iteration: 73065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.05506 FastRCNN total loss: 0.14207 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.13244 RPN box loss: 0.01165 RPN score loss: 0.0012 RPN total loss: 0.01286 Total loss: 0.85221 timestamp: 1655066046.469817 iteration: 73070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12248 FastRCNN class loss: 0.09074 FastRCNN total loss: 0.21322 L1 loss: 0.0000e+00 L2 loss: 0.56484 Learning rate: 0.0004 Mask loss: 0.14795 RPN box loss: 0.00563 RPN score loss: 0.00971 RPN total loss: 0.01533 Total loss: 0.94134 timestamp: 1655066049.7325895 iteration: 73075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.0715 FastRCNN total loss: 0.15868 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.1191 RPN box loss: 0.01557 RPN score loss: 0.00256 RPN total loss: 0.01813 Total loss: 0.86074 timestamp: 1655066052.9846387 iteration: 73080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10394 FastRCNN class loss: 0.04276 FastRCNN total loss: 0.1467 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.14677 RPN box loss: 0.00688 RPN score loss: 0.00287 RPN total loss: 0.00975 Total loss: 0.86806 timestamp: 1655066056.2315319 iteration: 73085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09678 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.14017 RPN box loss: 0.02022 RPN score loss: 0.005 RPN total loss: 0.02522 Total loss: 0.89134 timestamp: 1655066059.5024536 iteration: 73090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.13343 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.13717 RPN box loss: 0.01579 RPN score loss: 0.00518 RPN total loss: 0.02096 Total loss: 0.85639 timestamp: 1655066062.8096998 iteration: 73095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10662 FastRCNN class loss: 0.08605 FastRCNN total loss: 0.19267 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.25868 RPN box loss: 0.01041 RPN score loss: 0.00458 RPN total loss: 0.01499 Total loss: 1.03117 timestamp: 1655066066.1139038 iteration: 73100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04789 FastRCNN class loss: 0.06817 FastRCNN total loss: 0.11606 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.15684 RPN box loss: 0.0094 RPN score loss: 0.00549 RPN total loss: 0.01489 Total loss: 0.85262 timestamp: 1655066069.3664646 iteration: 73105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13021 FastRCNN class loss: 0.11357 FastRCNN total loss: 0.24378 L1 loss: 0.0000e+00 L2 loss: 0.56483 Learning rate: 0.0004 Mask loss: 0.18031 RPN box loss: 0.0159 RPN score loss: 0.00811 RPN total loss: 0.02402 Total loss: 1.01293 timestamp: 1655066072.6600785 iteration: 73110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14353 FastRCNN class loss: 0.12236 FastRCNN total loss: 0.26588 L1 loss: 0.0000e+00 L2 loss: 0.56482 Learning rate: 0.0004 Mask loss: 0.1466 RPN box loss: 0.01736 RPN score loss: 0.00428 RPN total loss: 0.02164 Total loss: 0.99895 timestamp: 1655066075.9430554 iteration: 73115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12549 FastRCNN class loss: 0.08102 FastRCNN total loss: 0.20651 L1 loss: 0.0000e+00 L2 loss: 0.56482 Learning rate: 0.0004 Mask loss: 0.14112 RPN box loss: 0.0234 RPN score loss: 0.00763 RPN total loss: 0.03102 Total loss: 0.94348 timestamp: 1655066079.2420573 iteration: 73120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0881 FastRCNN class loss: 0.07491 FastRCNN total loss: 0.16301 L1 loss: 0.0000e+00 L2 loss: 0.56482 Learning rate: 0.0004 Mask loss: 0.11746 RPN box loss: 0.01259 RPN score loss: 0.00615 RPN total loss: 0.01874 Total loss: 0.86403 timestamp: 1655066082.4784167 iteration: 73125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07884 FastRCNN class loss: 0.07935 FastRCNN total loss: 0.15818 L1 loss: 0.0000e+00 L2 loss: 0.56482 Learning rate: 0.0004 Mask loss: 0.10021 RPN box loss: 0.009 RPN score loss: 0.00301 RPN total loss: 0.01201 Total loss: 0.83522 timestamp: 1655066085.7465036 iteration: 73130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04838 FastRCNN class loss: 0.02771 FastRCNN total loss: 0.0761 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.09411 RPN box loss: 0.01615 RPN score loss: 0.00175 RPN total loss: 0.01789 Total loss: 0.75291 timestamp: 1655066089.04939 iteration: 73135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11123 FastRCNN class loss: 0.0588 FastRCNN total loss: 0.17004 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.14909 RPN box loss: 0.00921 RPN score loss: 0.00787 RPN total loss: 0.01708 Total loss: 0.90102 timestamp: 1655066092.3296702 iteration: 73140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10614 FastRCNN class loss: 0.08923 FastRCNN total loss: 0.19537 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.18524 RPN box loss: 0.02595 RPN score loss: 0.01406 RPN total loss: 0.04001 Total loss: 0.98544 timestamp: 1655066095.5971038 iteration: 73145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10021 FastRCNN class loss: 0.0782 FastRCNN total loss: 0.17841 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.17585 RPN box loss: 0.01199 RPN score loss: 0.00852 RPN total loss: 0.02051 Total loss: 0.93959 timestamp: 1655066098.8778005 iteration: 73150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12601 FastRCNN class loss: 0.09433 FastRCNN total loss: 0.22034 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.16321 RPN box loss: 0.00981 RPN score loss: 0.00822 RPN total loss: 0.01802 Total loss: 0.96638 timestamp: 1655066102.130895 iteration: 73155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09595 FastRCNN class loss: 0.07552 FastRCNN total loss: 0.17146 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.13808 RPN box loss: 0.01163 RPN score loss: 0.00752 RPN total loss: 0.01915 Total loss: 0.8935 timestamp: 1655066105.4134533 iteration: 73160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07383 FastRCNN class loss: 0.09895 FastRCNN total loss: 0.17278 L1 loss: 0.0000e+00 L2 loss: 0.56481 Learning rate: 0.0004 Mask loss: 0.15716 RPN box loss: 0.02006 RPN score loss: 0.01947 RPN total loss: 0.03953 Total loss: 0.93427 timestamp: 1655066108.6717565 iteration: 73165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11811 FastRCNN class loss: 0.07914 FastRCNN total loss: 0.19725 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.16286 RPN box loss: 0.00677 RPN score loss: 0.01012 RPN total loss: 0.01689 Total loss: 0.94181 timestamp: 1655066111.886403 iteration: 73170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.09993 FastRCNN total loss: 0.21435 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.14161 RPN box loss: 0.02076 RPN score loss: 0.01012 RPN total loss: 0.03088 Total loss: 0.95165 timestamp: 1655066115.1103508 iteration: 73175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06794 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.14367 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.14356 RPN box loss: 0.0216 RPN score loss: 0.00653 RPN total loss: 0.02813 Total loss: 0.88016 timestamp: 1655066118.387871 iteration: 73180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08272 FastRCNN class loss: 0.10249 FastRCNN total loss: 0.18522 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.19685 RPN box loss: 0.01342 RPN score loss: 0.00418 RPN total loss: 0.0176 Total loss: 0.96447 timestamp: 1655066121.695501 iteration: 73185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12578 FastRCNN class loss: 0.10601 FastRCNN total loss: 0.23179 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.17909 RPN box loss: 0.02275 RPN score loss: 0.00798 RPN total loss: 0.03073 Total loss: 1.00641 timestamp: 1655066124.8936102 iteration: 73190 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1336 FastRCNN class loss: 0.1273 FastRCNN total loss: 0.2609 L1 loss: 0.0000e+00 L2 loss: 0.5648 Learning rate: 0.0004 Mask loss: 0.17633 RPN box loss: 0.03436 RPN score loss: 0.01123 RPN total loss: 0.04558 Total loss: 1.04761 timestamp: 1655066128.1450033 iteration: 73195 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1242 FastRCNN class loss: 0.10692 FastRCNN total loss: 0.23112 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.14153 RPN box loss: 0.00816 RPN score loss: 0.00114 RPN total loss: 0.0093 Total loss: 0.94675 timestamp: 1655066131.4421527 iteration: 73200 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10312 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.18195 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.18304 RPN box loss: 0.02745 RPN score loss: 0.00364 RPN total loss: 0.03108 Total loss: 0.96087 timestamp: 1655066134.688722 iteration: 73205 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10848 FastRCNN class loss: 0.06866 FastRCNN total loss: 0.17714 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.18363 RPN box loss: 0.01213 RPN score loss: 0.0033 RPN total loss: 0.01543 Total loss: 0.941 timestamp: 1655066137.9352906 iteration: 73210 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04918 FastRCNN class loss: 0.05742 FastRCNN total loss: 0.1066 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.10408 RPN box loss: 0.00276 RPN score loss: 0.00278 RPN total loss: 0.00554 Total loss: 0.78101 timestamp: 1655066141.194789 iteration: 73215 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11174 FastRCNN class loss: 0.1061 FastRCNN total loss: 0.21784 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.14802 RPN box loss: 0.01367 RPN score loss: 0.00349 RPN total loss: 0.01716 Total loss: 0.94781 timestamp: 1655066144.461578 iteration: 73220 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11196 FastRCNN class loss: 0.08912 FastRCNN total loss: 0.20109 L1 loss: 0.0000e+00 L2 loss: 0.56479 Learning rate: 0.0004 Mask loss: 0.19985 RPN box loss: 0.01761 RPN score loss: 0.00523 RPN total loss: 0.02284 Total loss: 0.98856 timestamp: 1655066147.7102587 iteration: 73225 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05753 FastRCNN class loss: 0.04224 FastRCNN total loss: 0.09977 L1 loss: 0.0000e+00 L2 loss: 0.56478 Learning rate: 0.0004 Mask loss: 0.1379 RPN box loss: 0.00993 RPN score loss: 0.00422 RPN total loss: 0.01415 Total loss: 0.81661 timestamp: 1655066151.0040598 iteration: 73230 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10902 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.1843 L1 loss: 0.0000e+00 L2 loss: 0.56478 Learning rate: 0.0004 Mask loss: 0.08843 RPN box loss: 0.00468 RPN score loss: 0.00257 RPN total loss: 0.00725 Total loss: 0.84476 timestamp: 1655066154.2286005 iteration: 73235 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07169 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.13548 L1 loss: 0.0000e+00 L2 loss: 0.56478 Learning rate: 0.0004 Mask loss: 0.17514 RPN box loss: 0.0247 RPN score loss: 0.00359 RPN total loss: 0.02829 Total loss: 0.90368 timestamp: 1655066157.467373 iteration: 73240 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09174 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.17081 L1 loss: 0.0000e+00 L2 loss: 0.56478 Learning rate: 0.0004 Mask loss: 0.20658 RPN box loss: 0.01109 RPN score loss: 0.00765 RPN total loss: 0.01874 Total loss: 0.9609 timestamp: 1655066160.7305615 iteration: 73245 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08445 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.15035 L1 loss: 0.0000e+00 L2 loss: 0.56478 Learning rate: 0.0004 Mask loss: 0.11069 RPN box loss: 0.00722 RPN score loss: 0.01003 RPN total loss: 0.01725 Total loss: 0.84306 timestamp: 1655066164.0055187 iteration: 73250 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12236 FastRCNN class loss: 0.093 FastRCNN total loss: 0.21536 L1 loss: 0.0000e+00 L2 loss: 0.56477 Learning rate: 0.0004 Mask loss: 0.13675 RPN box loss: 0.02025 RPN score loss: 0.00468 RPN total loss: 0.02493 Total loss: 0.94182 timestamp: 1655066167.2613392 iteration: 73255 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13616 FastRCNN class loss: 0.05096 FastRCNN total loss: 0.18712 L1 loss: 0.0000e+00 L2 loss: 0.56477 Learning rate: 0.0004 Mask loss: 0.14844 RPN box loss: 0.00636 RPN score loss: 0.00625 RPN total loss: 0.01262 Total loss: 0.91295 timestamp: 1655066170.5057685 iteration: 73260 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06014 FastRCNN class loss: 0.05807 FastRCNN total loss: 0.11821 L1 loss: 0.0000e+00 L2 loss: 0.56477 Learning rate: 0.0004 Mask loss: 0.09823 RPN box loss: 0.03323 RPN score loss: 0.00335 RPN total loss: 0.03658 Total loss: 0.81778 timestamp: 1655066173.812663 iteration: 73265 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07573 FastRCNN class loss: 0.04656 FastRCNN total loss: 0.12228 L1 loss: 0.0000e+00 L2 loss: 0.56477 Learning rate: 0.0004 Mask loss: 0.11778 RPN box loss: 0.01357 RPN score loss: 0.00236 RPN total loss: 0.01593 Total loss: 0.82076 timestamp: 1655066177.0308669 iteration: 73270 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1005 FastRCNN class loss: 0.10315 FastRCNN total loss: 0.20364 L1 loss: 0.0000e+00 L2 loss: 0.56477 Learning rate: 0.0004 Mask loss: 0.17333 RPN box loss: 0.01938 RPN score loss: 0.0155 RPN total loss: 0.03488 Total loss: 0.97663 timestamp: 1655066180.2912216 iteration: 73275 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12225 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.19214 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.18813 RPN box loss: 0.02267 RPN score loss: 0.01351 RPN total loss: 0.03618 Total loss: 0.98121 timestamp: 1655066183.5987318 iteration: 73280 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.13639 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.09573 RPN box loss: 0.00609 RPN score loss: 0.00448 RPN total loss: 0.01057 Total loss: 0.80746 timestamp: 1655066186.931772 iteration: 73285 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.075 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.13986 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.14974 RPN box loss: 0.02112 RPN score loss: 0.00385 RPN total loss: 0.02496 Total loss: 0.87932 timestamp: 1655066190.1505864 iteration: 73290 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09574 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.17302 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.1425 RPN box loss: 0.02294 RPN score loss: 0.01425 RPN total loss: 0.03719 Total loss: 0.91747 timestamp: 1655066193.4448154 iteration: 73295 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10881 FastRCNN class loss: 0.09417 FastRCNN total loss: 0.20299 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.12998 RPN box loss: 0.01469 RPN score loss: 0.00221 RPN total loss: 0.0169 Total loss: 0.91463 timestamp: 1655066196.7456546 iteration: 73300 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.0813 FastRCNN total loss: 0.18472 L1 loss: 0.0000e+00 L2 loss: 0.56476 Learning rate: 0.0004 Mask loss: 0.11202 RPN box loss: 0.0133 RPN score loss: 0.00678 RPN total loss: 0.02008 Total loss: 0.88157 timestamp: 1655066200.0737684 iteration: 73305 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10097 FastRCNN class loss: 0.1048 FastRCNN total loss: 0.20577 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.14889 RPN box loss: 0.01356 RPN score loss: 0.00159 RPN total loss: 0.01516 Total loss: 0.93458 timestamp: 1655066203.3961864 iteration: 73310 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11758 FastRCNN class loss: 0.08461 FastRCNN total loss: 0.20219 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.20779 RPN box loss: 0.02786 RPN score loss: 0.00335 RPN total loss: 0.03122 Total loss: 1.00594 timestamp: 1655066206.6983457 iteration: 73315 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10494 FastRCNN class loss: 0.08642 FastRCNN total loss: 0.19136 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.17455 RPN box loss: 0.011 RPN score loss: 0.00375 RPN total loss: 0.01475 Total loss: 0.94541 timestamp: 1655066209.9310288 iteration: 73320 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1603 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.24148 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.14992 RPN box loss: 0.00587 RPN score loss: 0.00369 RPN total loss: 0.00955 Total loss: 0.96571 timestamp: 1655066213.2193894 iteration: 73325 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13016 FastRCNN class loss: 0.06615 FastRCNN total loss: 0.19631 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.16537 RPN box loss: 0.00656 RPN score loss: 0.00196 RPN total loss: 0.00852 Total loss: 0.93495 timestamp: 1655066216.4581404 iteration: 73330 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14048 FastRCNN class loss: 0.08714 FastRCNN total loss: 0.22763 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.13139 RPN box loss: 0.01306 RPN score loss: 0.00689 RPN total loss: 0.01995 Total loss: 0.94372 timestamp: 1655066219.6942956 iteration: 73335 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11543 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.17728 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.13773 RPN box loss: 0.01089 RPN score loss: 0.00681 RPN total loss: 0.0177 Total loss: 0.89746 timestamp: 1655066222.954304 iteration: 73340 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06886 FastRCNN class loss: 0.05857 FastRCNN total loss: 0.12743 L1 loss: 0.0000e+00 L2 loss: 0.56475 Learning rate: 0.0004 Mask loss: 0.12098 RPN box loss: 0.00574 RPN score loss: 0.00325 RPN total loss: 0.00899 Total loss: 0.82214 timestamp: 1655066226.1994994 iteration: 73345 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12997 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.2055 L1 loss: 0.0000e+00 L2 loss: 0.56474 Learning rate: 0.0004 Mask loss: 0.13662 RPN box loss: 0.00651 RPN score loss: 0.00185 RPN total loss: 0.00836 Total loss: 0.91522 timestamp: 1655066229.501832 iteration: 73350 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07528 FastRCNN class loss: 0.0894 FastRCNN total loss: 0.16468 L1 loss: 0.0000e+00 L2 loss: 0.56474 Learning rate: 0.0004 Mask loss: 0.14689 RPN box loss: 0.01468 RPN score loss: 0.00651 RPN total loss: 0.02119 Total loss: 0.8975 timestamp: 1655066232.8027315 iteration: 73355 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.07496 FastRCNN total loss: 0.18999 L1 loss: 0.0000e+00 L2 loss: 0.56474 Learning rate: 0.0004 Mask loss: 0.26757 RPN box loss: 0.03426 RPN score loss: 0.01019 RPN total loss: 0.04445 Total loss: 1.06676 timestamp: 1655066236.029176 iteration: 73360 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11078 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.20048 L1 loss: 0.0000e+00 L2 loss: 0.56474 Learning rate: 0.0004 Mask loss: 0.14496 RPN box loss: 0.02519 RPN score loss: 0.01136 RPN total loss: 0.03655 Total loss: 0.94673 timestamp: 1655066239.289442 iteration: 73365 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08692 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.18009 L1 loss: 0.0000e+00 L2 loss: 0.56474 Learning rate: 0.0004 Mask loss: 0.17409 RPN box loss: 0.03022 RPN score loss: 0.00763 RPN total loss: 0.03786 Total loss: 0.95678 timestamp: 1655066242.5830095 iteration: 73370 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08172 FastRCNN class loss: 0.09811 FastRCNN total loss: 0.17984 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.18363 RPN box loss: 0.01774 RPN score loss: 0.00895 RPN total loss: 0.02669 Total loss: 0.95489 timestamp: 1655066245.8087723 iteration: 73375 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08669 FastRCNN class loss: 0.05895 FastRCNN total loss: 0.14564 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.11485 RPN box loss: 0.01632 RPN score loss: 0.00244 RPN total loss: 0.01876 Total loss: 0.84398 timestamp: 1655066249.0805411 iteration: 73380 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08556 FastRCNN class loss: 0.04279 FastRCNN total loss: 0.12834 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.11708 RPN box loss: 0.00609 RPN score loss: 0.00485 RPN total loss: 0.01094 Total loss: 0.82109 timestamp: 1655066252.3776278 iteration: 73385 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08679 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.15444 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.13478 RPN box loss: 0.02035 RPN score loss: 0.0063 RPN total loss: 0.02665 Total loss: 0.8806 timestamp: 1655066255.6488864 iteration: 73390 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.17862 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.1367 RPN box loss: 0.0068 RPN score loss: 0.01044 RPN total loss: 0.01724 Total loss: 0.89729 timestamp: 1655066258.844902 iteration: 73395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10976 FastRCNN class loss: 0.09042 FastRCNN total loss: 0.20018 L1 loss: 0.0000e+00 L2 loss: 0.56473 Learning rate: 0.0004 Mask loss: 0.2106 RPN box loss: 0.01907 RPN score loss: 0.00251 RPN total loss: 0.02157 Total loss: 0.99708 timestamp: 1655066262.1226716 iteration: 73400 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10259 FastRCNN class loss: 0.06361 FastRCNN total loss: 0.16621 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.18718 RPN box loss: 0.01226 RPN score loss: 0.00354 RPN total loss: 0.0158 Total loss: 0.9339 timestamp: 1655066265.4519303 iteration: 73405 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06213 FastRCNN class loss: 0.04898 FastRCNN total loss: 0.1111 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.11956 RPN box loss: 0.03881 RPN score loss: 0.00286 RPN total loss: 0.04168 Total loss: 0.83707 timestamp: 1655066268.68099 iteration: 73410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.05014 FastRCNN total loss: 0.12336 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.13108 RPN box loss: 0.00723 RPN score loss: 0.00541 RPN total loss: 0.01264 Total loss: 0.8318 timestamp: 1655066271.992948 iteration: 73415 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.14852 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.14288 RPN box loss: 0.01294 RPN score loss: 0.01669 RPN total loss: 0.02964 Total loss: 0.88576 timestamp: 1655066275.313059 iteration: 73420 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05819 FastRCNN class loss: 0.05571 FastRCNN total loss: 0.1139 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.23328 RPN box loss: 0.00693 RPN score loss: 0.002 RPN total loss: 0.00893 Total loss: 0.92083 timestamp: 1655066278.5752711 iteration: 73425 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.08539 FastRCNN total loss: 0.18179 L1 loss: 0.0000e+00 L2 loss: 0.56472 Learning rate: 0.0004 Mask loss: 0.19557 RPN box loss: 0.01088 RPN score loss: 0.00986 RPN total loss: 0.02074 Total loss: 0.96281 timestamp: 1655066281.8909125 iteration: 73430 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12566 FastRCNN class loss: 0.05909 FastRCNN total loss: 0.18475 L1 loss: 0.0000e+00 L2 loss: 0.56471 Learning rate: 0.0004 Mask loss: 0.1158 RPN box loss: 0.01673 RPN score loss: 0.00335 RPN total loss: 0.02008 Total loss: 0.88534 timestamp: 1655066285.203383 iteration: 73435 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0901 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.16474 L1 loss: 0.0000e+00 L2 loss: 0.56471 Learning rate: 0.0004 Mask loss: 0.11636 RPN box loss: 0.00704 RPN score loss: 0.01185 RPN total loss: 0.01889 Total loss: 0.8647 timestamp: 1655066288.4693089 iteration: 73440 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0581 FastRCNN class loss: 0.06764 FastRCNN total loss: 0.12574 L1 loss: 0.0000e+00 L2 loss: 0.56471 Learning rate: 0.0004 Mask loss: 0.16844 RPN box loss: 0.00852 RPN score loss: 0.00323 RPN total loss: 0.01175 Total loss: 0.87063 timestamp: 1655066291.8136873 iteration: 73445 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08148 FastRCNN class loss: 0.068 FastRCNN total loss: 0.14947 L1 loss: 0.0000e+00 L2 loss: 0.56471 Learning rate: 0.0004 Mask loss: 0.1772 RPN box loss: 0.0069 RPN score loss: 0.00889 RPN total loss: 0.01578 Total loss: 0.90716 timestamp: 1655066295.0785449 iteration: 73450 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07875 FastRCNN class loss: 0.03778 FastRCNN total loss: 0.11652 L1 loss: 0.0000e+00 L2 loss: 0.56471 Learning rate: 0.0004 Mask loss: 0.12193 RPN box loss: 0.00463 RPN score loss: 0.00133 RPN total loss: 0.00596 Total loss: 0.80912 timestamp: 1655066298.3454041 iteration: 73455 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0878 FastRCNN class loss: 0.0501 FastRCNN total loss: 0.1379 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.09195 RPN box loss: 0.01106 RPN score loss: 0.00523 RPN total loss: 0.01629 Total loss: 0.81085 timestamp: 1655066301.6676557 iteration: 73460 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10465 FastRCNN class loss: 0.06929 FastRCNN total loss: 0.17394 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.15366 RPN box loss: 0.01357 RPN score loss: 0.01145 RPN total loss: 0.02502 Total loss: 0.91732 timestamp: 1655066304.9477153 iteration: 73465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14769 FastRCNN class loss: 0.09206 FastRCNN total loss: 0.23976 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.18888 RPN box loss: 0.0155 RPN score loss: 0.00534 RPN total loss: 0.02084 Total loss: 1.01418 timestamp: 1655066308.2147303 iteration: 73470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11759 FastRCNN class loss: 0.06784 FastRCNN total loss: 0.18543 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.14131 RPN box loss: 0.00928 RPN score loss: 0.00345 RPN total loss: 0.01273 Total loss: 0.90417 timestamp: 1655066311.4757392 iteration: 73475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08731 FastRCNN class loss: 0.09454 FastRCNN total loss: 0.18185 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.19797 RPN box loss: 0.02048 RPN score loss: 0.00805 RPN total loss: 0.02853 Total loss: 0.97305 timestamp: 1655066314.7831407 iteration: 73480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11041 FastRCNN class loss: 0.09154 FastRCNN total loss: 0.20194 L1 loss: 0.0000e+00 L2 loss: 0.5647 Learning rate: 0.0004 Mask loss: 0.15713 RPN box loss: 0.02003 RPN score loss: 0.00944 RPN total loss: 0.02947 Total loss: 0.95324 timestamp: 1655066318.0161357 iteration: 73485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07535 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.1632 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.12638 RPN box loss: 0.0093 RPN score loss: 0.00537 RPN total loss: 0.01467 Total loss: 0.86894 timestamp: 1655066321.3251503 iteration: 73490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07888 FastRCNN class loss: 0.06716 FastRCNN total loss: 0.14604 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.1291 RPN box loss: 0.00598 RPN score loss: 0.00467 RPN total loss: 0.01065 Total loss: 0.85048 timestamp: 1655066324.593499 iteration: 73495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0756 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.13289 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.10083 RPN box loss: 0.00879 RPN score loss: 0.00274 RPN total loss: 0.01153 Total loss: 0.80994 timestamp: 1655066327.8858337 iteration: 73500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06948 FastRCNN class loss: 0.05489 FastRCNN total loss: 0.12436 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.14677 RPN box loss: 0.01468 RPN score loss: 0.00573 RPN total loss: 0.02041 Total loss: 0.85623 timestamp: 1655066331.1274283 iteration: 73505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08188 FastRCNN class loss: 0.04924 FastRCNN total loss: 0.13111 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.10449 RPN box loss: 0.01197 RPN score loss: 0.00241 RPN total loss: 0.01437 Total loss: 0.81467 timestamp: 1655066334.4159234 iteration: 73510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11746 FastRCNN class loss: 0.10772 FastRCNN total loss: 0.22517 L1 loss: 0.0000e+00 L2 loss: 0.56469 Learning rate: 0.0004 Mask loss: 0.16361 RPN box loss: 0.03881 RPN score loss: 0.01348 RPN total loss: 0.05229 Total loss: 1.00576 timestamp: 1655066337.671108 iteration: 73515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1039 FastRCNN class loss: 0.07605 FastRCNN total loss: 0.17995 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.15705 RPN box loss: 0.00661 RPN score loss: 0.00375 RPN total loss: 0.01036 Total loss: 0.91205 timestamp: 1655066340.9309876 iteration: 73520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06112 FastRCNN class loss: 0.0496 FastRCNN total loss: 0.11072 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.17048 RPN box loss: 0.01448 RPN score loss: 0.0014 RPN total loss: 0.01588 Total loss: 0.86176 timestamp: 1655066344.2385898 iteration: 73525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07611 FastRCNN class loss: 0.05182 FastRCNN total loss: 0.12793 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.10462 RPN box loss: 0.01427 RPN score loss: 0.00324 RPN total loss: 0.01751 Total loss: 0.81474 timestamp: 1655066347.580985 iteration: 73530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11268 FastRCNN class loss: 0.06072 FastRCNN total loss: 0.1734 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.14836 RPN box loss: 0.00768 RPN score loss: 0.00495 RPN total loss: 0.01263 Total loss: 0.89907 timestamp: 1655066350.8464115 iteration: 73535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09228 FastRCNN class loss: 0.10455 FastRCNN total loss: 0.19683 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.13563 RPN box loss: 0.02154 RPN score loss: 0.00789 RPN total loss: 0.02943 Total loss: 0.92658 timestamp: 1655066354.1084979 iteration: 73540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11645 FastRCNN class loss: 0.09751 FastRCNN total loss: 0.21396 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.18041 RPN box loss: 0.01774 RPN score loss: 0.00358 RPN total loss: 0.02132 Total loss: 0.98037 timestamp: 1655066357.375144 iteration: 73545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05722 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.11132 L1 loss: 0.0000e+00 L2 loss: 0.56468 Learning rate: 0.0004 Mask loss: 0.10586 RPN box loss: 0.024 RPN score loss: 0.0036 RPN total loss: 0.0276 Total loss: 0.80945 timestamp: 1655066360.62048 iteration: 73550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09726 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.16033 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.12705 RPN box loss: 0.00987 RPN score loss: 0.00339 RPN total loss: 0.01326 Total loss: 0.86532 timestamp: 1655066363.8973324 iteration: 73555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07173 FastRCNN class loss: 0.05983 FastRCNN total loss: 0.13157 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.16219 RPN box loss: 0.02198 RPN score loss: 0.00271 RPN total loss: 0.02469 Total loss: 0.88312 timestamp: 1655066367.1683438 iteration: 73560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0915 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.14434 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.10988 RPN box loss: 0.00722 RPN score loss: 0.00566 RPN total loss: 0.01288 Total loss: 0.83177 timestamp: 1655066370.4728804 iteration: 73565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12389 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.2122 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.11775 RPN box loss: 0.02188 RPN score loss: 0.00418 RPN total loss: 0.02606 Total loss: 0.92068 timestamp: 1655066373.8142579 iteration: 73570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09136 FastRCNN class loss: 0.07043 FastRCNN total loss: 0.16178 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.13555 RPN box loss: 0.04983 RPN score loss: 0.0098 RPN total loss: 0.05962 Total loss: 0.92163 timestamp: 1655066377.0913653 iteration: 73575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06661 FastRCNN class loss: 0.0557 FastRCNN total loss: 0.12231 L1 loss: 0.0000e+00 L2 loss: 0.56467 Learning rate: 0.0004 Mask loss: 0.10344 RPN box loss: 0.01848 RPN score loss: 0.00265 RPN total loss: 0.02113 Total loss: 0.81155 timestamp: 1655066380.2806768 iteration: 73580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.19374 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.12466 RPN box loss: 0.02187 RPN score loss: 0.00872 RPN total loss: 0.03059 Total loss: 0.91366 timestamp: 1655066383.5681894 iteration: 73585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08993 FastRCNN class loss: 0.06278 FastRCNN total loss: 0.1527 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.0948 RPN box loss: 0.03333 RPN score loss: 0.00213 RPN total loss: 0.03546 Total loss: 0.84762 timestamp: 1655066386.8153932 iteration: 73590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06726 FastRCNN class loss: 0.04968 FastRCNN total loss: 0.11694 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.1807 RPN box loss: 0.00403 RPN score loss: 0.0015 RPN total loss: 0.00553 Total loss: 0.86783 timestamp: 1655066390.019694 iteration: 73595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11151 FastRCNN class loss: 0.121 FastRCNN total loss: 0.23251 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.2259 RPN box loss: 0.01653 RPN score loss: 0.01101 RPN total loss: 0.02755 Total loss: 1.05061 timestamp: 1655066393.2374306 iteration: 73600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1034 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.17344 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.17309 RPN box loss: 0.01328 RPN score loss: 0.01086 RPN total loss: 0.02414 Total loss: 0.93533 timestamp: 1655066396.478254 iteration: 73605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05547 FastRCNN class loss: 0.04099 FastRCNN total loss: 0.09646 L1 loss: 0.0000e+00 L2 loss: 0.56466 Learning rate: 0.0004 Mask loss: 0.06885 RPN box loss: 0.00342 RPN score loss: 0.00204 RPN total loss: 0.00546 Total loss: 0.73541 timestamp: 1655066399.7188413 iteration: 73610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06463 FastRCNN class loss: 0.05449 FastRCNN total loss: 0.11913 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.13752 RPN box loss: 0.01031 RPN score loss: 0.00216 RPN total loss: 0.01247 Total loss: 0.83377 timestamp: 1655066403.0056643 iteration: 73615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10523 FastRCNN class loss: 0.10422 FastRCNN total loss: 0.20944 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.15975 RPN box loss: 0.00865 RPN score loss: 0.00184 RPN total loss: 0.01049 Total loss: 0.94434 timestamp: 1655066406.2770903 iteration: 73620 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12999 FastRCNN class loss: 0.06915 FastRCNN total loss: 0.19914 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.12522 RPN box loss: 0.01338 RPN score loss: 0.00537 RPN total loss: 0.01875 Total loss: 0.90776 timestamp: 1655066409.574333 iteration: 73625 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09759 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.15338 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.13204 RPN box loss: 0.01955 RPN score loss: 0.00224 RPN total loss: 0.02179 Total loss: 0.87186 timestamp: 1655066412.835789 iteration: 73630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08178 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.14932 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.13526 RPN box loss: 0.00998 RPN score loss: 0.00652 RPN total loss: 0.0165 Total loss: 0.86573 timestamp: 1655066416.1184993 iteration: 73635 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15224 FastRCNN class loss: 0.12252 FastRCNN total loss: 0.27476 L1 loss: 0.0000e+00 L2 loss: 0.56465 Learning rate: 0.0004 Mask loss: 0.19517 RPN box loss: 0.04655 RPN score loss: 0.01507 RPN total loss: 0.06162 Total loss: 1.0962 timestamp: 1655066419.354615 iteration: 73640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09623 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.16106 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.11996 RPN box loss: 0.01657 RPN score loss: 0.00138 RPN total loss: 0.01795 Total loss: 0.86362 timestamp: 1655066422.7084432 iteration: 73645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0825 FastRCNN class loss: 0.09967 FastRCNN total loss: 0.18217 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.12811 RPN box loss: 0.01957 RPN score loss: 0.01379 RPN total loss: 0.03335 Total loss: 0.90827 timestamp: 1655066425.9474924 iteration: 73650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06847 FastRCNN class loss: 0.05314 FastRCNN total loss: 0.12161 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.13038 RPN box loss: 0.00582 RPN score loss: 0.00733 RPN total loss: 0.01315 Total loss: 0.82977 timestamp: 1655066429.2374551 iteration: 73655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10412 FastRCNN class loss: 0.10609 FastRCNN total loss: 0.21021 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.17762 RPN box loss: 0.02469 RPN score loss: 0.00607 RPN total loss: 0.03076 Total loss: 0.98323 timestamp: 1655066432.516316 iteration: 73660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10611 FastRCNN class loss: 0.07339 FastRCNN total loss: 0.1795 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.11376 RPN box loss: 0.02484 RPN score loss: 0.01785 RPN total loss: 0.04269 Total loss: 0.90058 timestamp: 1655066435.790274 iteration: 73665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13338 FastRCNN class loss: 0.09516 FastRCNN total loss: 0.22854 L1 loss: 0.0000e+00 L2 loss: 0.56464 Learning rate: 0.0004 Mask loss: 0.12344 RPN box loss: 0.01054 RPN score loss: 0.00684 RPN total loss: 0.01738 Total loss: 0.93399 timestamp: 1655066439.036173 iteration: 73670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12035 FastRCNN class loss: 0.05069 FastRCNN total loss: 0.17105 L1 loss: 0.0000e+00 L2 loss: 0.56463 Learning rate: 0.0004 Mask loss: 0.12602 RPN box loss: 0.0106 RPN score loss: 0.00131 RPN total loss: 0.0119 Total loss: 0.87361 timestamp: 1655066442.3492353 iteration: 73675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09227 FastRCNN class loss: 0.10638 FastRCNN total loss: 0.19866 L1 loss: 0.0000e+00 L2 loss: 0.56463 Learning rate: 0.0004 Mask loss: 0.15156 RPN box loss: 0.01204 RPN score loss: 0.0052 RPN total loss: 0.01724 Total loss: 0.93209 timestamp: 1655066445.6345048 iteration: 73680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04861 FastRCNN class loss: 0.04412 FastRCNN total loss: 0.09273 L1 loss: 0.0000e+00 L2 loss: 0.56463 Learning rate: 0.0004 Mask loss: 0.1446 RPN box loss: 0.01091 RPN score loss: 0.00247 RPN total loss: 0.01339 Total loss: 0.81535 timestamp: 1655066448.9007776 iteration: 73685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08783 FastRCNN class loss: 0.06026 FastRCNN total loss: 0.14809 L1 loss: 0.0000e+00 L2 loss: 0.56463 Learning rate: 0.0004 Mask loss: 0.13463 RPN box loss: 0.01393 RPN score loss: 0.00936 RPN total loss: 0.02328 Total loss: 0.87063 timestamp: 1655066452.1075816 iteration: 73690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11414 FastRCNN class loss: 0.11351 FastRCNN total loss: 0.22766 L1 loss: 0.0000e+00 L2 loss: 0.56463 Learning rate: 0.0004 Mask loss: 0.16235 RPN box loss: 0.01751 RPN score loss: 0.00069 RPN total loss: 0.01821 Total loss: 0.97284 timestamp: 1655066455.4270446 iteration: 73695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09527 FastRCNN class loss: 0.04709 FastRCNN total loss: 0.14236 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.09958 RPN box loss: 0.0069 RPN score loss: 0.00326 RPN total loss: 0.01016 Total loss: 0.81672 timestamp: 1655066458.7140398 iteration: 73700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10933 FastRCNN class loss: 0.10253 FastRCNN total loss: 0.21186 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.16288 RPN box loss: 0.04307 RPN score loss: 0.00869 RPN total loss: 0.05176 Total loss: 0.99113 timestamp: 1655066462.007506 iteration: 73705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06712 FastRCNN class loss: 0.04 FastRCNN total loss: 0.10712 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.08952 RPN box loss: 0.00741 RPN score loss: 0.00357 RPN total loss: 0.01098 Total loss: 0.77225 timestamp: 1655066465.2943325 iteration: 73710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13585 FastRCNN class loss: 0.07341 FastRCNN total loss: 0.20926 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.2168 RPN box loss: 0.01279 RPN score loss: 0.00659 RPN total loss: 0.01939 Total loss: 1.01007 timestamp: 1655066468.507913 iteration: 73715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07034 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.12538 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.12432 RPN box loss: 0.00576 RPN score loss: 0.00816 RPN total loss: 0.01391 Total loss: 0.82824 timestamp: 1655066471.8272805 iteration: 73720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11034 FastRCNN class loss: 0.08549 FastRCNN total loss: 0.19583 L1 loss: 0.0000e+00 L2 loss: 0.56462 Learning rate: 0.0004 Mask loss: 0.13615 RPN box loss: 0.00887 RPN score loss: 0.00516 RPN total loss: 0.01403 Total loss: 0.91063 timestamp: 1655066475.0963764 iteration: 73725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10182 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.17941 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.18978 RPN box loss: 0.01693 RPN score loss: 0.01642 RPN total loss: 0.03335 Total loss: 0.96716 timestamp: 1655066478.4250998 iteration: 73730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1031 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.17883 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.19236 RPN box loss: 0.0134 RPN score loss: 0.00652 RPN total loss: 0.01993 Total loss: 0.95573 timestamp: 1655066481.7448263 iteration: 73735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0763 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.15217 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.1491 RPN box loss: 0.02845 RPN score loss: 0.00297 RPN total loss: 0.03142 Total loss: 0.8973 timestamp: 1655066485.0717926 iteration: 73740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08281 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.13661 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.11176 RPN box loss: 0.00401 RPN score loss: 0.00294 RPN total loss: 0.00695 Total loss: 0.81993 timestamp: 1655066488.3974802 iteration: 73745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.07093 FastRCNN total loss: 0.16208 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.15347 RPN box loss: 0.00944 RPN score loss: 0.00639 RPN total loss: 0.01583 Total loss: 0.89598 timestamp: 1655066491.7152262 iteration: 73750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17465 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.25428 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.16503 RPN box loss: 0.01094 RPN score loss: 0.00796 RPN total loss: 0.01889 Total loss: 1.00281 timestamp: 1655066495.0259883 iteration: 73755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09571 FastRCNN class loss: 0.05289 FastRCNN total loss: 0.14861 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.14976 RPN box loss: 0.01138 RPN score loss: 0.00255 RPN total loss: 0.01393 Total loss: 0.8769 timestamp: 1655066498.2947283 iteration: 73760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.05185 FastRCNN total loss: 0.13282 L1 loss: 0.0000e+00 L2 loss: 0.56461 Learning rate: 0.0004 Mask loss: 0.14687 RPN box loss: 0.00851 RPN score loss: 0.0075 RPN total loss: 0.01601 Total loss: 0.86031 timestamp: 1655066501.5296104 iteration: 73765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09532 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.16238 RPN box loss: 0.00691 RPN score loss: 0.00351 RPN total loss: 0.01042 Total loss: 0.8948 timestamp: 1655066504.7544196 iteration: 73770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10225 FastRCNN class loss: 0.06885 FastRCNN total loss: 0.1711 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.14541 RPN box loss: 0.02104 RPN score loss: 0.0051 RPN total loss: 0.02614 Total loss: 0.90725 timestamp: 1655066508.047074 iteration: 73775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10476 FastRCNN class loss: 0.07717 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.14968 RPN box loss: 0.01326 RPN score loss: 0.00669 RPN total loss: 0.01995 Total loss: 0.91616 timestamp: 1655066511.2452044 iteration: 73780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06425 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.13111 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.07511 RPN box loss: 0.01394 RPN score loss: 0.00456 RPN total loss: 0.01849 Total loss: 0.78931 timestamp: 1655066514.5515535 iteration: 73785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09367 FastRCNN class loss: 0.07395 FastRCNN total loss: 0.16762 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.17942 RPN box loss: 0.00423 RPN score loss: 0.00612 RPN total loss: 0.01036 Total loss: 0.92199 timestamp: 1655066517.9102533 iteration: 73790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10322 FastRCNN class loss: 0.08547 FastRCNN total loss: 0.18869 L1 loss: 0.0000e+00 L2 loss: 0.5646 Learning rate: 0.0004 Mask loss: 0.18423 RPN box loss: 0.02917 RPN score loss: 0.01174 RPN total loss: 0.04091 Total loss: 0.97842 timestamp: 1655066521.1426651 iteration: 73795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13956 FastRCNN class loss: 0.07604 FastRCNN total loss: 0.2156 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.12719 RPN box loss: 0.01915 RPN score loss: 0.0067 RPN total loss: 0.02585 Total loss: 0.93324 timestamp: 1655066524.4171119 iteration: 73800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.131 FastRCNN class loss: 0.07709 FastRCNN total loss: 0.20809 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.14446 RPN box loss: 0.01358 RPN score loss: 0.00182 RPN total loss: 0.01541 Total loss: 0.93255 timestamp: 1655066527.7426548 iteration: 73805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11947 FastRCNN class loss: 0.10769 FastRCNN total loss: 0.22717 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.26132 RPN box loss: 0.01639 RPN score loss: 0.01007 RPN total loss: 0.02646 Total loss: 1.07954 timestamp: 1655066531.0447423 iteration: 73810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12592 FastRCNN class loss: 0.11578 FastRCNN total loss: 0.2417 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.13263 RPN box loss: 0.02677 RPN score loss: 0.01458 RPN total loss: 0.04135 Total loss: 0.98027 timestamp: 1655066534.3349705 iteration: 73815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08312 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.16074 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.11153 RPN box loss: 0.02545 RPN score loss: 0.0028 RPN total loss: 0.02826 Total loss: 0.86512 timestamp: 1655066537.6179893 iteration: 73820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09823 FastRCNN class loss: 0.07291 FastRCNN total loss: 0.17114 L1 loss: 0.0000e+00 L2 loss: 0.56459 Learning rate: 0.0004 Mask loss: 0.18508 RPN box loss: 0.00983 RPN score loss: 0.00194 RPN total loss: 0.01177 Total loss: 0.93257 timestamp: 1655066540.8906496 iteration: 73825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17525 FastRCNN class loss: 0.11259 FastRCNN total loss: 0.28784 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.18066 RPN box loss: 0.07686 RPN score loss: 0.01932 RPN total loss: 0.09618 Total loss: 1.12927 timestamp: 1655066544.1335127 iteration: 73830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07604 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.14099 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.08275 RPN box loss: 0.00829 RPN score loss: 0.00622 RPN total loss: 0.01451 Total loss: 0.80283 timestamp: 1655066547.4446707 iteration: 73835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10115 FastRCNN class loss: 0.07161 FastRCNN total loss: 0.17276 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.11171 RPN box loss: 0.01007 RPN score loss: 0.00221 RPN total loss: 0.01228 Total loss: 0.86133 timestamp: 1655066550.732514 iteration: 73840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06747 FastRCNN class loss: 0.03523 FastRCNN total loss: 0.1027 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.09288 RPN box loss: 0.00652 RPN score loss: 0.00602 RPN total loss: 0.01254 Total loss: 0.7727 timestamp: 1655066553.9838655 iteration: 73845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08681 FastRCNN class loss: 0.07912 FastRCNN total loss: 0.16593 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.16847 RPN box loss: 0.00792 RPN score loss: 0.00712 RPN total loss: 0.01504 Total loss: 0.91402 timestamp: 1655066557.2854457 iteration: 73850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10674 FastRCNN class loss: 0.05105 FastRCNN total loss: 0.1578 L1 loss: 0.0000e+00 L2 loss: 0.56458 Learning rate: 0.0004 Mask loss: 0.08841 RPN box loss: 0.00304 RPN score loss: 0.00196 RPN total loss: 0.005 Total loss: 0.81578 timestamp: 1655066560.5253825 iteration: 73855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13091 FastRCNN class loss: 0.06099 FastRCNN total loss: 0.1919 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.14455 RPN box loss: 0.00522 RPN score loss: 0.00647 RPN total loss: 0.0117 Total loss: 0.91273 timestamp: 1655066563.7971416 iteration: 73860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07029 FastRCNN class loss: 0.0794 FastRCNN total loss: 0.14969 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.1517 RPN box loss: 0.00852 RPN score loss: 0.0014 RPN total loss: 0.00992 Total loss: 0.87588 timestamp: 1655066567.0195465 iteration: 73865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05648 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.10365 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.12038 RPN box loss: 0.00298 RPN score loss: 0.00237 RPN total loss: 0.00535 Total loss: 0.79395 timestamp: 1655066570.201222 iteration: 73870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08895 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.1687 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.18555 RPN box loss: 0.00815 RPN score loss: 0.00556 RPN total loss: 0.0137 Total loss: 0.93253 timestamp: 1655066573.5532095 iteration: 73875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11254 FastRCNN class loss: 0.07413 FastRCNN total loss: 0.18666 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.15676 RPN box loss: 0.01599 RPN score loss: 0.00821 RPN total loss: 0.0242 Total loss: 0.93219 timestamp: 1655066576.794749 iteration: 73880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10694 FastRCNN class loss: 0.06987 FastRCNN total loss: 0.17681 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.18791 RPN box loss: 0.0249 RPN score loss: 0.00659 RPN total loss: 0.03149 Total loss: 0.96078 timestamp: 1655066580.055115 iteration: 73885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06678 FastRCNN class loss: 0.05575 FastRCNN total loss: 0.12253 L1 loss: 0.0000e+00 L2 loss: 0.56457 Learning rate: 0.0004 Mask loss: 0.15473 RPN box loss: 0.00414 RPN score loss: 0.00109 RPN total loss: 0.00523 Total loss: 0.84706 timestamp: 1655066583.2428327 iteration: 73890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06918 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.12973 L1 loss: 0.0000e+00 L2 loss: 0.56456 Learning rate: 0.0004 Mask loss: 0.184 RPN box loss: 0.01162 RPN score loss: 0.00519 RPN total loss: 0.01681 Total loss: 0.89511 timestamp: 1655066586.5074158 iteration: 73895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10605 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.17091 L1 loss: 0.0000e+00 L2 loss: 0.56456 Learning rate: 0.0004 Mask loss: 0.18036 RPN box loss: 0.02524 RPN score loss: 0.0046 RPN total loss: 0.02984 Total loss: 0.94567 timestamp: 1655066589.7840645 iteration: 73900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10425 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.18069 L1 loss: 0.0000e+00 L2 loss: 0.56456 Learning rate: 0.0004 Mask loss: 0.14067 RPN box loss: 0.03369 RPN score loss: 0.00773 RPN total loss: 0.04142 Total loss: 0.92734 timestamp: 1655066593.1328044 iteration: 73905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1138 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.19018 L1 loss: 0.0000e+00 L2 loss: 0.56456 Learning rate: 0.0004 Mask loss: 0.1254 RPN box loss: 0.01316 RPN score loss: 0.00305 RPN total loss: 0.01621 Total loss: 0.89635 timestamp: 1655066596.4330657 iteration: 73910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13071 FastRCNN class loss: 0.08232 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 0.56456 Learning rate: 0.0004 Mask loss: 0.15495 RPN box loss: 0.01475 RPN score loss: 0.0151 RPN total loss: 0.02985 Total loss: 0.96238 timestamp: 1655066599.7455075 iteration: 73915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1171 FastRCNN class loss: 0.08012 FastRCNN total loss: 0.19722 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.10198 RPN box loss: 0.00565 RPN score loss: 0.00755 RPN total loss: 0.0132 Total loss: 0.87696 timestamp: 1655066603.0178676 iteration: 73920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.07039 FastRCNN total loss: 0.20817 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.17074 RPN box loss: 0.00981 RPN score loss: 0.01253 RPN total loss: 0.02234 Total loss: 0.9658 timestamp: 1655066606.3111548 iteration: 73925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.1413 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.12895 RPN box loss: 0.00857 RPN score loss: 0.00323 RPN total loss: 0.01181 Total loss: 0.8466 timestamp: 1655066609.5997336 iteration: 73930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05901 FastRCNN class loss: 0.06468 FastRCNN total loss: 0.12369 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.09852 RPN box loss: 0.02967 RPN score loss: 0.00299 RPN total loss: 0.03266 Total loss: 0.81942 timestamp: 1655066612.875957 iteration: 73935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11446 FastRCNN class loss: 0.0776 FastRCNN total loss: 0.19206 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.20579 RPN box loss: 0.00369 RPN score loss: 0.00518 RPN total loss: 0.00887 Total loss: 0.97127 timestamp: 1655066616.1501365 iteration: 73940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09304 FastRCNN class loss: 0.06207 FastRCNN total loss: 0.15511 L1 loss: 0.0000e+00 L2 loss: 0.56455 Learning rate: 0.0004 Mask loss: 0.1494 RPN box loss: 0.00778 RPN score loss: 0.0074 RPN total loss: 0.01518 Total loss: 0.88424 timestamp: 1655066619.4188445 iteration: 73945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09186 FastRCNN class loss: 0.07911 FastRCNN total loss: 0.17096 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.18147 RPN box loss: 0.01138 RPN score loss: 0.00613 RPN total loss: 0.01752 Total loss: 0.93449 timestamp: 1655066622.7085574 iteration: 73950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11486 FastRCNN class loss: 0.10746 FastRCNN total loss: 0.22232 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.1583 RPN box loss: 0.01403 RPN score loss: 0.01505 RPN total loss: 0.02908 Total loss: 0.97424 timestamp: 1655066625.951344 iteration: 73955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13279 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.20117 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.1851 RPN box loss: 0.00676 RPN score loss: 0.004 RPN total loss: 0.01076 Total loss: 0.96158 timestamp: 1655066629.1948223 iteration: 73960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11522 FastRCNN class loss: 0.0604 FastRCNN total loss: 0.17562 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.13049 RPN box loss: 0.00929 RPN score loss: 0.00216 RPN total loss: 0.01146 Total loss: 0.8821 timestamp: 1655066632.412699 iteration: 73965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11642 FastRCNN class loss: 0.10701 FastRCNN total loss: 0.22343 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.22671 RPN box loss: 0.01204 RPN score loss: 0.01606 RPN total loss: 0.0281 Total loss: 1.04278 timestamp: 1655066635.651328 iteration: 73970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10263 FastRCNN class loss: 0.08471 FastRCNN total loss: 0.18734 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.13689 RPN box loss: 0.01278 RPN score loss: 0.00892 RPN total loss: 0.0217 Total loss: 0.91047 timestamp: 1655066638.9184873 iteration: 73975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10317 FastRCNN class loss: 0.09059 FastRCNN total loss: 0.19376 L1 loss: 0.0000e+00 L2 loss: 0.56454 Learning rate: 0.0004 Mask loss: 0.14518 RPN box loss: 0.02367 RPN score loss: 0.00579 RPN total loss: 0.02946 Total loss: 0.93294 timestamp: 1655066642.2113981 iteration: 73980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06341 FastRCNN class loss: 0.06874 FastRCNN total loss: 0.13215 L1 loss: 0.0000e+00 L2 loss: 0.56453 Learning rate: 0.0004 Mask loss: 0.16654 RPN box loss: 0.01699 RPN score loss: 0.01902 RPN total loss: 0.03602 Total loss: 0.89924 timestamp: 1655066645.479006 iteration: 73985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15088 FastRCNN class loss: 0.05568 FastRCNN total loss: 0.20656 L1 loss: 0.0000e+00 L2 loss: 0.56453 Learning rate: 0.0004 Mask loss: 0.10043 RPN box loss: 0.00694 RPN score loss: 0.00377 RPN total loss: 0.01071 Total loss: 0.88223 timestamp: 1655066648.7255664 iteration: 73990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11769 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.20261 L1 loss: 0.0000e+00 L2 loss: 0.56453 Learning rate: 0.0004 Mask loss: 0.14105 RPN box loss: 0.0078 RPN score loss: 0.00675 RPN total loss: 0.01455 Total loss: 0.92274 timestamp: 1655066652.0303242 iteration: 73995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04937 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.10078 L1 loss: 0.0000e+00 L2 loss: 0.56453 Learning rate: 0.0004 Mask loss: 0.11189 RPN box loss: 0.00785 RPN score loss: 0.00374 RPN total loss: 0.01159 Total loss: 0.78878 timestamp: 1655066655.303459 iteration: 74000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14981 FastRCNN class loss: 0.06379 FastRCNN total loss: 0.2136 L1 loss: 0.0000e+00 L2 loss: 0.56453 Learning rate: 0.0004 Mask loss: 0.12726 RPN box loss: 0.00824 RPN score loss: 0.00486 RPN total loss: 0.0131 Total loss: 0.91849 timestamp: 1655066658.584319 iteration: 74005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.10287 FastRCNN total loss: 0.18109 L1 loss: 0.0000e+00 L2 loss: 0.56452 Learning rate: 0.0004 Mask loss: 0.12819 RPN box loss: 0.00731 RPN score loss: 0.00699 RPN total loss: 0.0143 Total loss: 0.8881 timestamp: 1655066661.764833 iteration: 74010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12203 FastRCNN class loss: 0.08989 FastRCNN total loss: 0.21192 L1 loss: 0.0000e+00 L2 loss: 0.56452 Learning rate: 0.0004 Mask loss: 0.14993 RPN box loss: 0.02029 RPN score loss: 0.00889 RPN total loss: 0.02919 Total loss: 0.95556 timestamp: 1655066665.0575762 iteration: 74015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1015 FastRCNN class loss: 0.05096 FastRCNN total loss: 0.15246 L1 loss: 0.0000e+00 L2 loss: 0.56452 Learning rate: 0.0004 Mask loss: 0.1006 RPN box loss: 0.00624 RPN score loss: 0.00731 RPN total loss: 0.01355 Total loss: 0.83113 timestamp: 1655066668.264194 iteration: 74020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09539 FastRCNN class loss: 0.0947 FastRCNN total loss: 0.19009 L1 loss: 0.0000e+00 L2 loss: 0.56452 Learning rate: 0.0004 Mask loss: 0.16079 RPN box loss: 0.0297 RPN score loss: 0.0036 RPN total loss: 0.0333 Total loss: 0.9487 timestamp: 1655066671.5618556 iteration: 74025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10049 FastRCNN class loss: 0.05277 FastRCNN total loss: 0.15326 L1 loss: 0.0000e+00 L2 loss: 0.56452 Learning rate: 0.0004 Mask loss: 0.13366 RPN box loss: 0.00533 RPN score loss: 0.00313 RPN total loss: 0.00845 Total loss: 0.85988 timestamp: 1655066674.8588326 iteration: 74030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09096 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.16899 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.16401 RPN box loss: 0.00561 RPN score loss: 0.0045 RPN total loss: 0.01012 Total loss: 0.90763 timestamp: 1655066678.1227562 iteration: 74035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10823 FastRCNN class loss: 0.06791 FastRCNN total loss: 0.17615 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.12958 RPN box loss: 0.01983 RPN score loss: 0.01025 RPN total loss: 0.03008 Total loss: 0.90031 timestamp: 1655066681.3557634 iteration: 74040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1136 FastRCNN class loss: 0.14647 FastRCNN total loss: 0.26007 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.19944 RPN box loss: 0.01161 RPN score loss: 0.00984 RPN total loss: 0.02144 Total loss: 1.04547 timestamp: 1655066684.6614096 iteration: 74045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0842 FastRCNN class loss: 0.05295 FastRCNN total loss: 0.13715 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.16192 RPN box loss: 0.01219 RPN score loss: 0.00614 RPN total loss: 0.01833 Total loss: 0.88191 timestamp: 1655066687.9514377 iteration: 74050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05432 FastRCNN class loss: 0.03687 FastRCNN total loss: 0.09119 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.09559 RPN box loss: 0.01448 RPN score loss: 0.00214 RPN total loss: 0.01662 Total loss: 0.76791 timestamp: 1655066691.2526724 iteration: 74055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09565 FastRCNN class loss: 0.05631 FastRCNN total loss: 0.15196 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.13899 RPN box loss: 0.03254 RPN score loss: 0.00864 RPN total loss: 0.04118 Total loss: 0.89664 timestamp: 1655066694.5642834 iteration: 74060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17647 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.24099 L1 loss: 0.0000e+00 L2 loss: 0.56451 Learning rate: 0.0004 Mask loss: 0.12015 RPN box loss: 0.03088 RPN score loss: 0.00543 RPN total loss: 0.03631 Total loss: 0.96195 timestamp: 1655066697.8692007 iteration: 74065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11189 FastRCNN class loss: 0.04295 FastRCNN total loss: 0.15484 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.14067 RPN box loss: 0.00909 RPN score loss: 0.00448 RPN total loss: 0.01357 Total loss: 0.87359 timestamp: 1655066701.135668 iteration: 74070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09067 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.1457 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.14735 RPN box loss: 0.00653 RPN score loss: 0.00336 RPN total loss: 0.0099 Total loss: 0.86745 timestamp: 1655066704.4638867 iteration: 74075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0605 FastRCNN class loss: 0.05992 FastRCNN total loss: 0.12041 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.1567 RPN box loss: 0.00735 RPN score loss: 0.00879 RPN total loss: 0.01614 Total loss: 0.85776 timestamp: 1655066707.7458906 iteration: 74080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09765 FastRCNN class loss: 0.06457 FastRCNN total loss: 0.16222 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.18648 RPN box loss: 0.01839 RPN score loss: 0.00447 RPN total loss: 0.02286 Total loss: 0.93606 timestamp: 1655066711.040877 iteration: 74085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12969 FastRCNN class loss: 0.10639 FastRCNN total loss: 0.23607 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.1874 RPN box loss: 0.01433 RPN score loss: 0.01071 RPN total loss: 0.02504 Total loss: 1.01301 timestamp: 1655066714.3406034 iteration: 74090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10777 FastRCNN class loss: 0.10595 FastRCNN total loss: 0.21373 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.14139 RPN box loss: 0.0074 RPN score loss: 0.00433 RPN total loss: 0.01173 Total loss: 0.93134 timestamp: 1655066717.6025622 iteration: 74095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08455 FastRCNN class loss: 0.07016 FastRCNN total loss: 0.15471 L1 loss: 0.0000e+00 L2 loss: 0.5645 Learning rate: 0.0004 Mask loss: 0.10549 RPN box loss: 0.00464 RPN score loss: 0.00173 RPN total loss: 0.00637 Total loss: 0.83107 timestamp: 1655066720.8765266 iteration: 74100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11816 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.18484 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.14273 RPN box loss: 0.02229 RPN score loss: 0.0031 RPN total loss: 0.02538 Total loss: 0.91746 timestamp: 1655066724.1110744 iteration: 74105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1246 FastRCNN class loss: 0.08724 FastRCNN total loss: 0.21184 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.16464 RPN box loss: 0.0058 RPN score loss: 0.00346 RPN total loss: 0.00927 Total loss: 0.95024 timestamp: 1655066727.35299 iteration: 74110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11071 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.18167 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.15733 RPN box loss: 0.03047 RPN score loss: 0.01041 RPN total loss: 0.04088 Total loss: 0.94436 timestamp: 1655066730.6589196 iteration: 74115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09055 FastRCNN class loss: 0.09494 FastRCNN total loss: 0.18549 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.13882 RPN box loss: 0.01284 RPN score loss: 0.0068 RPN total loss: 0.01964 Total loss: 0.90844 timestamp: 1655066733.998876 iteration: 74120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10826 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.18034 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.1667 RPN box loss: 0.02304 RPN score loss: 0.01065 RPN total loss: 0.03368 Total loss: 0.94521 timestamp: 1655066737.3046465 iteration: 74125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18446 FastRCNN class loss: 0.06241 FastRCNN total loss: 0.24687 L1 loss: 0.0000e+00 L2 loss: 0.56449 Learning rate: 0.0004 Mask loss: 0.13305 RPN box loss: 0.02434 RPN score loss: 0.00666 RPN total loss: 0.031 Total loss: 0.97541 timestamp: 1655066740.5617502 iteration: 74130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11414 FastRCNN class loss: 0.15751 FastRCNN total loss: 0.27165 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.2365 RPN box loss: 0.04167 RPN score loss: 0.06989 RPN total loss: 0.11155 Total loss: 1.18419 timestamp: 1655066743.8240187 iteration: 74135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05358 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.09772 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.11919 RPN box loss: 0.01629 RPN score loss: 0.00457 RPN total loss: 0.02086 Total loss: 0.80226 timestamp: 1655066747.1314104 iteration: 74140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14065 FastRCNN class loss: 0.06229 FastRCNN total loss: 0.20294 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.12826 RPN box loss: 0.01173 RPN score loss: 0.00334 RPN total loss: 0.01507 Total loss: 0.91076 timestamp: 1655066750.360612 iteration: 74145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.131 FastRCNN class loss: 0.08663 FastRCNN total loss: 0.21762 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.15065 RPN box loss: 0.012 RPN score loss: 0.00663 RPN total loss: 0.01863 Total loss: 0.95139 timestamp: 1655066753.6733828 iteration: 74150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1223 FastRCNN class loss: 0.06584 FastRCNN total loss: 0.18814 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.16103 RPN box loss: 0.01236 RPN score loss: 0.00665 RPN total loss: 0.01901 Total loss: 0.93265 timestamp: 1655066756.966636 iteration: 74155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08339 FastRCNN class loss: 0.05882 FastRCNN total loss: 0.14222 L1 loss: 0.0000e+00 L2 loss: 0.56448 Learning rate: 0.0004 Mask loss: 0.1523 RPN box loss: 0.02277 RPN score loss: 0.00133 RPN total loss: 0.0241 Total loss: 0.88309 timestamp: 1655066760.1560311 iteration: 74160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.064 FastRCNN class loss: 0.04339 FastRCNN total loss: 0.1074 L1 loss: 0.0000e+00 L2 loss: 0.56447 Learning rate: 0.0004 Mask loss: 0.09102 RPN box loss: 0.00648 RPN score loss: 0.00134 RPN total loss: 0.00782 Total loss: 0.77071 timestamp: 1655066763.4342165 iteration: 74165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06911 FastRCNN class loss: 0.04128 FastRCNN total loss: 0.11038 L1 loss: 0.0000e+00 L2 loss: 0.56447 Learning rate: 0.0004 Mask loss: 0.16612 RPN box loss: 0.01116 RPN score loss: 0.00807 RPN total loss: 0.01923 Total loss: 0.86021 timestamp: 1655066766.6639524 iteration: 74170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1188 FastRCNN class loss: 0.08461 FastRCNN total loss: 0.20341 L1 loss: 0.0000e+00 L2 loss: 0.56447 Learning rate: 0.0004 Mask loss: 0.17852 RPN box loss: 0.01131 RPN score loss: 0.00759 RPN total loss: 0.0189 Total loss: 0.9653 timestamp: 1655066769.9569232 iteration: 74175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06606 FastRCNN class loss: 0.04176 FastRCNN total loss: 0.10782 L1 loss: 0.0000e+00 L2 loss: 0.56447 Learning rate: 0.0004 Mask loss: 0.1114 RPN box loss: 0.0101 RPN score loss: 0.00339 RPN total loss: 0.0135 Total loss: 0.79718 timestamp: 1655066773.304554 iteration: 74180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16369 FastRCNN class loss: 0.0593 FastRCNN total loss: 0.22298 L1 loss: 0.0000e+00 L2 loss: 0.56447 Learning rate: 0.0004 Mask loss: 0.16604 RPN box loss: 0.01285 RPN score loss: 0.00959 RPN total loss: 0.02244 Total loss: 0.97593 timestamp: 1655066776.575867 iteration: 74185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0447 FastRCNN class loss: 0.02712 FastRCNN total loss: 0.07182 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.13976 RPN box loss: 0.00267 RPN score loss: 0.00111 RPN total loss: 0.00378 Total loss: 0.77983 timestamp: 1655066779.8837352 iteration: 74190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.09348 FastRCNN total loss: 0.19354 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.16215 RPN box loss: 0.01195 RPN score loss: 0.01143 RPN total loss: 0.02339 Total loss: 0.94353 timestamp: 1655066783.124867 iteration: 74195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13094 FastRCNN class loss: 0.13342 FastRCNN total loss: 0.26436 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.21463 RPN box loss: 0.0261 RPN score loss: 0.01023 RPN total loss: 0.03634 Total loss: 1.07979 timestamp: 1655066786.3875356 iteration: 74200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11501 FastRCNN class loss: 0.07406 FastRCNN total loss: 0.18907 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.13369 RPN box loss: 0.02039 RPN score loss: 0.01626 RPN total loss: 0.03665 Total loss: 0.92388 timestamp: 1655066789.5940454 iteration: 74205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08026 FastRCNN class loss: 0.06403 FastRCNN total loss: 0.14428 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.1302 RPN box loss: 0.00933 RPN score loss: 0.00207 RPN total loss: 0.0114 Total loss: 0.85034 timestamp: 1655066792.8455746 iteration: 74210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.04284 FastRCNN total loss: 0.13786 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.11961 RPN box loss: 0.00942 RPN score loss: 0.00413 RPN total loss: 0.01355 Total loss: 0.83549 timestamp: 1655066796.1296802 iteration: 74215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08487 FastRCNN class loss: 0.04121 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.56446 Learning rate: 0.0004 Mask loss: 0.15709 RPN box loss: 0.00385 RPN score loss: 0.00195 RPN total loss: 0.00581 Total loss: 0.85343 timestamp: 1655066799.3509295 iteration: 74220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09539 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.14955 L1 loss: 0.0000e+00 L2 loss: 0.56445 Learning rate: 0.0004 Mask loss: 0.11548 RPN box loss: 0.0079 RPN score loss: 0.00446 RPN total loss: 0.01236 Total loss: 0.84184 timestamp: 1655066802.6255915 iteration: 74225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10422 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.56445 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.03285 RPN score loss: 0.00861 RPN total loss: 0.04146 Total loss: 0.92614 timestamp: 1655066805.8913372 iteration: 74230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14406 FastRCNN class loss: 0.06585 FastRCNN total loss: 0.20991 L1 loss: 0.0000e+00 L2 loss: 0.56445 Learning rate: 0.0004 Mask loss: 0.12874 RPN box loss: 0.00414 RPN score loss: 0.00113 RPN total loss: 0.00527 Total loss: 0.90837 timestamp: 1655066809.2203271 iteration: 74235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1601 FastRCNN class loss: 0.07463 FastRCNN total loss: 0.23474 L1 loss: 0.0000e+00 L2 loss: 0.56445 Learning rate: 0.0004 Mask loss: 0.153 RPN box loss: 0.01378 RPN score loss: 0.00418 RPN total loss: 0.01796 Total loss: 0.97015 timestamp: 1655066812.5299082 iteration: 74240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1015 FastRCNN class loss: 0.08975 FastRCNN total loss: 0.19125 L1 loss: 0.0000e+00 L2 loss: 0.56445 Learning rate: 0.0004 Mask loss: 0.1746 RPN box loss: 0.01185 RPN score loss: 0.00169 RPN total loss: 0.01354 Total loss: 0.94383 timestamp: 1655066815.7567735 iteration: 74245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0785 FastRCNN class loss: 0.04799 FastRCNN total loss: 0.12649 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.17399 RPN box loss: 0.01533 RPN score loss: 0.00538 RPN total loss: 0.02071 Total loss: 0.88563 timestamp: 1655066819.0375001 iteration: 74250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.08269 FastRCNN total loss: 0.15076 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.12826 RPN box loss: 0.00543 RPN score loss: 0.00325 RPN total loss: 0.00868 Total loss: 0.85215 timestamp: 1655066822.325087 iteration: 74255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07689 FastRCNN class loss: 0.06048 FastRCNN total loss: 0.13737 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.09394 RPN box loss: 0.02104 RPN score loss: 0.00691 RPN total loss: 0.02796 Total loss: 0.82371 timestamp: 1655066825.6528773 iteration: 74260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05494 FastRCNN class loss: 0.09277 FastRCNN total loss: 0.14771 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.15945 RPN box loss: 0.00794 RPN score loss: 0.00523 RPN total loss: 0.01318 Total loss: 0.88478 timestamp: 1655066828.8892026 iteration: 74265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05737 FastRCNN class loss: 0.08066 FastRCNN total loss: 0.13803 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.0941 RPN box loss: 0.01321 RPN score loss: 0.02014 RPN total loss: 0.03335 Total loss: 0.82992 timestamp: 1655066832.1654155 iteration: 74270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.07876 FastRCNN total loss: 0.16116 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.15867 RPN box loss: 0.00977 RPN score loss: 0.00625 RPN total loss: 0.01603 Total loss: 0.9003 timestamp: 1655066835.4258993 iteration: 74275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.06167 FastRCNN total loss: 0.13406 L1 loss: 0.0000e+00 L2 loss: 0.56444 Learning rate: 0.0004 Mask loss: 0.12404 RPN box loss: 0.01059 RPN score loss: 0.00204 RPN total loss: 0.01263 Total loss: 0.83516 timestamp: 1655066838.6740997 iteration: 74280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07151 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.12502 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.12641 RPN box loss: 0.01541 RPN score loss: 0.00362 RPN total loss: 0.01903 Total loss: 0.83489 timestamp: 1655066841.9619942 iteration: 74285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10619 FastRCNN class loss: 0.06842 FastRCNN total loss: 0.17461 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.18359 RPN box loss: 0.00978 RPN score loss: 0.00324 RPN total loss: 0.01302 Total loss: 0.93565 timestamp: 1655066845.205625 iteration: 74290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07866 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.13134 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.14232 RPN box loss: 0.01349 RPN score loss: 0.00607 RPN total loss: 0.01956 Total loss: 0.85766 timestamp: 1655066848.5219216 iteration: 74295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07207 FastRCNN class loss: 0.05001 FastRCNN total loss: 0.12208 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.14355 RPN box loss: 0.00519 RPN score loss: 0.00208 RPN total loss: 0.00727 Total loss: 0.83734 timestamp: 1655066851.8902116 iteration: 74300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07104 FastRCNN class loss: 0.05536 FastRCNN total loss: 0.1264 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.16144 RPN box loss: 0.00694 RPN score loss: 0.00506 RPN total loss: 0.012 Total loss: 0.86426 timestamp: 1655066855.1663923 iteration: 74305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06735 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.12434 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.11989 RPN box loss: 0.0054 RPN score loss: 0.0016 RPN total loss: 0.007 Total loss: 0.81566 timestamp: 1655066858.4619973 iteration: 74310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12324 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.21488 L1 loss: 0.0000e+00 L2 loss: 0.56443 Learning rate: 0.0004 Mask loss: 0.1347 RPN box loss: 0.01451 RPN score loss: 0.00204 RPN total loss: 0.01655 Total loss: 0.93056 timestamp: 1655066861.6953788 iteration: 74315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09123 FastRCNN class loss: 0.07512 FastRCNN total loss: 0.16635 L1 loss: 0.0000e+00 L2 loss: 0.56442 Learning rate: 0.0004 Mask loss: 0.16078 RPN box loss: 0.02506 RPN score loss: 0.00695 RPN total loss: 0.03202 Total loss: 0.92357 timestamp: 1655066864.9382977 iteration: 74320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14977 FastRCNN class loss: 0.10221 FastRCNN total loss: 0.25198 L1 loss: 0.0000e+00 L2 loss: 0.56442 Learning rate: 0.0004 Mask loss: 0.16682 RPN box loss: 0.02964 RPN score loss: 0.01145 RPN total loss: 0.04109 Total loss: 1.02432 timestamp: 1655066868.2492633 iteration: 74325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10968 FastRCNN class loss: 0.06844 FastRCNN total loss: 0.17812 L1 loss: 0.0000e+00 L2 loss: 0.56442 Learning rate: 0.0004 Mask loss: 0.11004 RPN box loss: 0.02669 RPN score loss: 0.03023 RPN total loss: 0.05692 Total loss: 0.90951 timestamp: 1655066871.5583186 iteration: 74330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09105 FastRCNN class loss: 0.05262 FastRCNN total loss: 0.14367 L1 loss: 0.0000e+00 L2 loss: 0.56442 Learning rate: 0.0004 Mask loss: 0.13556 RPN box loss: 0.02584 RPN score loss: 0.00272 RPN total loss: 0.02856 Total loss: 0.8722 timestamp: 1655066874.7816246 iteration: 74335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11269 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.17897 L1 loss: 0.0000e+00 L2 loss: 0.56442 Learning rate: 0.0004 Mask loss: 0.13181 RPN box loss: 0.01958 RPN score loss: 0.00613 RPN total loss: 0.02571 Total loss: 0.9009 timestamp: 1655066878.005447 iteration: 74340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10867 FastRCNN class loss: 0.04692 FastRCNN total loss: 0.15559 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.09446 RPN box loss: 0.00823 RPN score loss: 0.00129 RPN total loss: 0.00952 Total loss: 0.82399 timestamp: 1655066881.3263788 iteration: 74345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07298 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.13838 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.09056 RPN box loss: 0.00735 RPN score loss: 0.00214 RPN total loss: 0.00949 Total loss: 0.80285 timestamp: 1655066884.5413747 iteration: 74350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14549 FastRCNN class loss: 0.09528 FastRCNN total loss: 0.24077 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.20028 RPN box loss: 0.01794 RPN score loss: 0.01282 RPN total loss: 0.03076 Total loss: 1.03622 timestamp: 1655066887.8221335 iteration: 74355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08763 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.14658 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.16559 RPN box loss: 0.01475 RPN score loss: 0.00318 RPN total loss: 0.01793 Total loss: 0.89451 timestamp: 1655066891.0983694 iteration: 74360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07168 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.13064 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.13087 RPN box loss: 0.0089 RPN score loss: 0.00376 RPN total loss: 0.01266 Total loss: 0.83858 timestamp: 1655066894.3445258 iteration: 74365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.05075 FastRCNN total loss: 0.13596 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.12147 RPN box loss: 0.02179 RPN score loss: 0.00767 RPN total loss: 0.02946 Total loss: 0.8513 timestamp: 1655066897.5659008 iteration: 74370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08976 FastRCNN class loss: 0.09734 FastRCNN total loss: 0.18709 L1 loss: 0.0000e+00 L2 loss: 0.56441 Learning rate: 0.0004 Mask loss: 0.16288 RPN box loss: 0.01166 RPN score loss: 0.00106 RPN total loss: 0.01272 Total loss: 0.92709 timestamp: 1655066900.810767 iteration: 74375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13921 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.2121 L1 loss: 0.0000e+00 L2 loss: 0.5644 Learning rate: 0.0004 Mask loss: 0.18912 RPN box loss: 0.01143 RPN score loss: 0.00708 RPN total loss: 0.01851 Total loss: 0.98413 timestamp: 1655066904.1175177 iteration: 74380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.0561 FastRCNN total loss: 0.13842 L1 loss: 0.0000e+00 L2 loss: 0.5644 Learning rate: 0.0004 Mask loss: 0.11779 RPN box loss: 0.00719 RPN score loss: 0.009 RPN total loss: 0.01619 Total loss: 0.83681 timestamp: 1655066907.282891 iteration: 74385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11366 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.16841 L1 loss: 0.0000e+00 L2 loss: 0.5644 Learning rate: 0.0004 Mask loss: 0.13716 RPN box loss: 0.00919 RPN score loss: 0.00132 RPN total loss: 0.01051 Total loss: 0.88048 timestamp: 1655066910.5614667 iteration: 74390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08829 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.15304 L1 loss: 0.0000e+00 L2 loss: 0.5644 Learning rate: 0.0004 Mask loss: 0.10652 RPN box loss: 0.00676 RPN score loss: 0.00537 RPN total loss: 0.01213 Total loss: 0.83608 timestamp: 1655066913.8098261 iteration: 74395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11241 FastRCNN class loss: 0.10897 FastRCNN total loss: 0.22138 L1 loss: 0.0000e+00 L2 loss: 0.5644 Learning rate: 0.0004 Mask loss: 0.16373 RPN box loss: 0.0218 RPN score loss: 0.01616 RPN total loss: 0.03796 Total loss: 0.98746 timestamp: 1655066917.0061612 iteration: 74400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07465 FastRCNN class loss: 0.083 FastRCNN total loss: 0.15764 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.13338 RPN box loss: 0.01013 RPN score loss: 0.00424 RPN total loss: 0.01437 Total loss: 0.86978 timestamp: 1655066920.2739968 iteration: 74405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0829 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.15088 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.23702 RPN box loss: 0.01793 RPN score loss: 0.00285 RPN total loss: 0.02078 Total loss: 0.97307 timestamp: 1655066923.5778842 iteration: 74410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11516 FastRCNN class loss: 0.07746 FastRCNN total loss: 0.19262 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.1849 RPN box loss: 0.01093 RPN score loss: 0.00297 RPN total loss: 0.0139 Total loss: 0.95581 timestamp: 1655066926.7494204 iteration: 74415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11153 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.18266 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.19955 RPN box loss: 0.02498 RPN score loss: 0.01162 RPN total loss: 0.0366 Total loss: 0.9832 timestamp: 1655066930.051248 iteration: 74420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10948 FastRCNN class loss: 0.06336 FastRCNN total loss: 0.17284 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.10891 RPN box loss: 0.00479 RPN score loss: 0.00062 RPN total loss: 0.00541 Total loss: 0.85155 timestamp: 1655066933.3339713 iteration: 74425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08215 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.14312 L1 loss: 0.0000e+00 L2 loss: 0.56439 Learning rate: 0.0004 Mask loss: 0.10983 RPN box loss: 0.01075 RPN score loss: 0.00828 RPN total loss: 0.01903 Total loss: 0.83637 timestamp: 1655066936.6625388 iteration: 74430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16099 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.22678 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.13061 RPN box loss: 0.01201 RPN score loss: 0.00477 RPN total loss: 0.01677 Total loss: 0.93855 timestamp: 1655066939.9162338 iteration: 74435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12422 FastRCNN class loss: 0.08436 FastRCNN total loss: 0.20858 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.16993 RPN box loss: 0.01284 RPN score loss: 0.01062 RPN total loss: 0.02346 Total loss: 0.96636 timestamp: 1655066943.2159004 iteration: 74440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08839 FastRCNN class loss: 0.08499 FastRCNN total loss: 0.17338 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.15498 RPN box loss: 0.01642 RPN score loss: 0.00863 RPN total loss: 0.02505 Total loss: 0.91779 timestamp: 1655066946.4351308 iteration: 74445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12105 FastRCNN class loss: 0.07935 FastRCNN total loss: 0.2004 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.1544 RPN box loss: 0.03797 RPN score loss: 0.00674 RPN total loss: 0.04471 Total loss: 0.96389 timestamp: 1655066949.741362 iteration: 74450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09675 FastRCNN class loss: 0.08777 FastRCNN total loss: 0.18452 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.13899 RPN box loss: 0.01158 RPN score loss: 0.01491 RPN total loss: 0.0265 Total loss: 0.91439 timestamp: 1655066952.9494412 iteration: 74455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10008 FastRCNN class loss: 0.05707 FastRCNN total loss: 0.15715 L1 loss: 0.0000e+00 L2 loss: 0.56438 Learning rate: 0.0004 Mask loss: 0.18394 RPN box loss: 0.03024 RPN score loss: 0.01262 RPN total loss: 0.04286 Total loss: 0.94833 timestamp: 1655066956.2121723 iteration: 74460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17932 FastRCNN class loss: 0.10456 FastRCNN total loss: 0.28388 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.18505 RPN box loss: 0.00743 RPN score loss: 0.00289 RPN total loss: 0.01033 Total loss: 1.04364 timestamp: 1655066959.4519029 iteration: 74465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08198 FastRCNN class loss: 0.06462 FastRCNN total loss: 0.1466 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.12787 RPN box loss: 0.02696 RPN score loss: 0.00788 RPN total loss: 0.03483 Total loss: 0.87368 timestamp: 1655066962.7206576 iteration: 74470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09259 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.17295 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.17376 RPN box loss: 0.01028 RPN score loss: 0.00412 RPN total loss: 0.01439 Total loss: 0.92548 timestamp: 1655066965.9754906 iteration: 74475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14125 FastRCNN class loss: 0.11469 FastRCNN total loss: 0.25595 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.14968 RPN box loss: 0.01527 RPN score loss: 0.00476 RPN total loss: 0.02003 Total loss: 0.99002 timestamp: 1655066969.2480662 iteration: 74480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06866 FastRCNN class loss: 0.06849 FastRCNN total loss: 0.13715 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.17165 RPN box loss: 0.01964 RPN score loss: 0.00561 RPN total loss: 0.02525 Total loss: 0.89843 timestamp: 1655066972.6022067 iteration: 74485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07859 FastRCNN class loss: 0.0378 FastRCNN total loss: 0.11638 L1 loss: 0.0000e+00 L2 loss: 0.56437 Learning rate: 0.0004 Mask loss: 0.07637 RPN box loss: 0.01141 RPN score loss: 0.00174 RPN total loss: 0.01315 Total loss: 0.77027 timestamp: 1655066975.827178 iteration: 74490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06444 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.11906 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.09207 RPN box loss: 0.00811 RPN score loss: 0.00221 RPN total loss: 0.01032 Total loss: 0.7858 timestamp: 1655066979.175678 iteration: 74495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08232 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.13936 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.12414 RPN box loss: 0.02287 RPN score loss: 0.00612 RPN total loss: 0.02899 Total loss: 0.85685 timestamp: 1655066982.422022 iteration: 74500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09101 FastRCNN class loss: 0.04552 FastRCNN total loss: 0.13653 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.11379 RPN box loss: 0.00816 RPN score loss: 0.00189 RPN total loss: 0.01004 Total loss: 0.82473 timestamp: 1655066985.6639261 iteration: 74505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09696 FastRCNN class loss: 0.09645 FastRCNN total loss: 0.19341 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.16171 RPN box loss: 0.02126 RPN score loss: 0.00274 RPN total loss: 0.02399 Total loss: 0.94348 timestamp: 1655066988.9230738 iteration: 74510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12935 FastRCNN class loss: 0.06766 FastRCNN total loss: 0.19701 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.2239 RPN box loss: 0.01763 RPN score loss: 0.00247 RPN total loss: 0.0201 Total loss: 1.00537 timestamp: 1655066992.2535048 iteration: 74515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14379 FastRCNN class loss: 0.08193 FastRCNN total loss: 0.22571 L1 loss: 0.0000e+00 L2 loss: 0.56436 Learning rate: 0.0004 Mask loss: 0.21466 RPN box loss: 0.01189 RPN score loss: 0.00869 RPN total loss: 0.02058 Total loss: 1.02531 timestamp: 1655066995.5396 iteration: 74520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1319 FastRCNN class loss: 0.05705 FastRCNN total loss: 0.18895 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.15384 RPN box loss: 0.0125 RPN score loss: 0.00982 RPN total loss: 0.02232 Total loss: 0.92946 timestamp: 1655066998.7953358 iteration: 74525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07863 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.15743 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.16957 RPN box loss: 0.01738 RPN score loss: 0.00355 RPN total loss: 0.02093 Total loss: 0.91229 timestamp: 1655067002.0400727 iteration: 74530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.04833 FastRCNN total loss: 0.14006 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.07352 RPN box loss: 0.00652 RPN score loss: 0.00069 RPN total loss: 0.00721 Total loss: 0.78514 timestamp: 1655067005.3927653 iteration: 74535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.18731 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.13051 RPN box loss: 0.02111 RPN score loss: 0.00234 RPN total loss: 0.02345 Total loss: 0.90562 timestamp: 1655067008.7111201 iteration: 74540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09572 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.19483 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.1987 RPN box loss: 0.02306 RPN score loss: 0.02313 RPN total loss: 0.04619 Total loss: 1.00406 timestamp: 1655067011.8849201 iteration: 74545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06468 FastRCNN class loss: 0.066 FastRCNN total loss: 0.13068 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.10769 RPN box loss: 0.01024 RPN score loss: 0.00352 RPN total loss: 0.01376 Total loss: 0.81648 timestamp: 1655067015.148799 iteration: 74550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08405 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.1275 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.11688 RPN box loss: 0.00448 RPN score loss: 0.00236 RPN total loss: 0.00684 Total loss: 0.81557 timestamp: 1655067018.4695776 iteration: 74555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08134 FastRCNN class loss: 0.06283 FastRCNN total loss: 0.14417 L1 loss: 0.0000e+00 L2 loss: 0.56435 Learning rate: 0.0004 Mask loss: 0.12774 RPN box loss: 0.01843 RPN score loss: 0.00312 RPN total loss: 0.02155 Total loss: 0.8578 timestamp: 1655067021.7031379 iteration: 74560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15464 FastRCNN class loss: 0.14364 FastRCNN total loss: 0.29827 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.24588 RPN box loss: 0.0166 RPN score loss: 0.00998 RPN total loss: 0.02658 Total loss: 1.13507 timestamp: 1655067025.0211408 iteration: 74565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05112 FastRCNN class loss: 0.08391 FastRCNN total loss: 0.13503 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.17086 RPN box loss: 0.01435 RPN score loss: 0.00633 RPN total loss: 0.02068 Total loss: 0.89091 timestamp: 1655067028.296696 iteration: 74570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13023 FastRCNN class loss: 0.06725 FastRCNN total loss: 0.19748 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.09875 RPN box loss: 0.00972 RPN score loss: 0.01212 RPN total loss: 0.02184 Total loss: 0.88241 timestamp: 1655067031.5483046 iteration: 74575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08604 FastRCNN class loss: 0.05793 FastRCNN total loss: 0.14396 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.13639 RPN box loss: 0.01035 RPN score loss: 0.00578 RPN total loss: 0.01614 Total loss: 0.86083 timestamp: 1655067034.8163548 iteration: 74580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08973 FastRCNN class loss: 0.05013 FastRCNN total loss: 0.13987 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.13656 RPN box loss: 0.01695 RPN score loss: 0.0024 RPN total loss: 0.01936 Total loss: 0.86012 timestamp: 1655067038.1263223 iteration: 74585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04112 FastRCNN class loss: 0.03399 FastRCNN total loss: 0.07512 L1 loss: 0.0000e+00 L2 loss: 0.56434 Learning rate: 0.0004 Mask loss: 0.09499 RPN box loss: 0.00226 RPN score loss: 0.0023 RPN total loss: 0.00456 Total loss: 0.739 timestamp: 1655067041.3910165 iteration: 74590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04522 FastRCNN class loss: 0.04052 FastRCNN total loss: 0.08574 L1 loss: 0.0000e+00 L2 loss: 0.56433 Learning rate: 0.0004 Mask loss: 0.08965 RPN box loss: 0.00392 RPN score loss: 0.00299 RPN total loss: 0.00692 Total loss: 0.74664 timestamp: 1655067044.6752648 iteration: 74595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10766 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.17307 L1 loss: 0.0000e+00 L2 loss: 0.56433 Learning rate: 0.0004 Mask loss: 0.13685 RPN box loss: 0.00806 RPN score loss: 0.00317 RPN total loss: 0.01123 Total loss: 0.88547 timestamp: 1655067047.9201026 iteration: 74600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1059 FastRCNN class loss: 0.06279 FastRCNN total loss: 0.16869 L1 loss: 0.0000e+00 L2 loss: 0.56433 Learning rate: 0.0004 Mask loss: 0.12967 RPN box loss: 0.00725 RPN score loss: 0.00524 RPN total loss: 0.01249 Total loss: 0.87518 timestamp: 1655067051.2359378 iteration: 74605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07232 FastRCNN class loss: 0.06722 FastRCNN total loss: 0.13954 L1 loss: 0.0000e+00 L2 loss: 0.56433 Learning rate: 0.0004 Mask loss: 0.13994 RPN box loss: 0.00998 RPN score loss: 0.00418 RPN total loss: 0.01416 Total loss: 0.85796 timestamp: 1655067054.5847955 iteration: 74610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12477 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.20416 L1 loss: 0.0000e+00 L2 loss: 0.56433 Learning rate: 0.0004 Mask loss: 0.14064 RPN box loss: 0.00685 RPN score loss: 0.00505 RPN total loss: 0.0119 Total loss: 0.92102 timestamp: 1655067057.853889 iteration: 74615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.07643 FastRCNN total loss: 0.16226 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.15466 RPN box loss: 0.01865 RPN score loss: 0.01105 RPN total loss: 0.0297 Total loss: 0.91094 timestamp: 1655067061.1148548 iteration: 74620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10575 FastRCNN class loss: 0.09368 FastRCNN total loss: 0.19943 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.15255 RPN box loss: 0.00992 RPN score loss: 0.00647 RPN total loss: 0.0164 Total loss: 0.93271 timestamp: 1655067064.4410625 iteration: 74625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16379 FastRCNN class loss: 0.1428 FastRCNN total loss: 0.30659 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.15239 RPN box loss: 0.01277 RPN score loss: 0.00472 RPN total loss: 0.01749 Total loss: 1.04079 timestamp: 1655067067.7068965 iteration: 74630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12609 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.20773 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.1867 RPN box loss: 0.01651 RPN score loss: 0.00468 RPN total loss: 0.0212 Total loss: 0.97995 timestamp: 1655067071.0299697 iteration: 74635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08515 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.14002 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.16051 RPN box loss: 0.01395 RPN score loss: 0.00416 RPN total loss: 0.01811 Total loss: 0.88295 timestamp: 1655067074.383287 iteration: 74640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07328 FastRCNN class loss: 0.07338 FastRCNN total loss: 0.14665 L1 loss: 0.0000e+00 L2 loss: 0.56432 Learning rate: 0.0004 Mask loss: 0.12532 RPN box loss: 0.0152 RPN score loss: 0.00846 RPN total loss: 0.02365 Total loss: 0.85994 timestamp: 1655067077.6424274 iteration: 74645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05926 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.13631 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.11062 RPN box loss: 0.01955 RPN score loss: 0.00278 RPN total loss: 0.02233 Total loss: 0.83357 timestamp: 1655067080.905226 iteration: 74650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08568 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.15148 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.12332 RPN box loss: 0.01298 RPN score loss: 0.00248 RPN total loss: 0.01546 Total loss: 0.85457 timestamp: 1655067084.1350138 iteration: 74655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.04755 FastRCNN total loss: 0.12113 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.12883 RPN box loss: 0.01171 RPN score loss: 0.00125 RPN total loss: 0.01297 Total loss: 0.82723 timestamp: 1655067087.3662198 iteration: 74660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12233 FastRCNN class loss: 0.09384 FastRCNN total loss: 0.21617 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.10847 RPN box loss: 0.0212 RPN score loss: 0.00418 RPN total loss: 0.02538 Total loss: 0.91432 timestamp: 1655067090.6279333 iteration: 74665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13132 FastRCNN class loss: 0.14536 FastRCNN total loss: 0.27668 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.17079 RPN box loss: 0.01985 RPN score loss: 0.00893 RPN total loss: 0.02878 Total loss: 1.04055 timestamp: 1655067094.0288117 iteration: 74670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04552 FastRCNN class loss: 0.029 FastRCNN total loss: 0.07452 L1 loss: 0.0000e+00 L2 loss: 0.56431 Learning rate: 0.0004 Mask loss: 0.09944 RPN box loss: 0.00332 RPN score loss: 0.00135 RPN total loss: 0.00466 Total loss: 0.74293 timestamp: 1655067097.2559903 iteration: 74675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0967 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.18309 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.13829 RPN box loss: 0.01252 RPN score loss: 0.00679 RPN total loss: 0.01931 Total loss: 0.90499 timestamp: 1655067100.540971 iteration: 74680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1416 FastRCNN class loss: 0.09819 FastRCNN total loss: 0.23979 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.13983 RPN box loss: 0.01141 RPN score loss: 0.00568 RPN total loss: 0.01709 Total loss: 0.96103 timestamp: 1655067103.8126693 iteration: 74685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09218 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.16314 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.16316 RPN box loss: 0.01579 RPN score loss: 0.00877 RPN total loss: 0.02455 Total loss: 0.91515 timestamp: 1655067107.0713542 iteration: 74690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05054 FastRCNN class loss: 0.06741 FastRCNN total loss: 0.11795 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.13196 RPN box loss: 0.00995 RPN score loss: 0.00176 RPN total loss: 0.01172 Total loss: 0.82593 timestamp: 1655067110.3825438 iteration: 74695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09712 FastRCNN class loss: 0.09195 FastRCNN total loss: 0.18907 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.13496 RPN box loss: 0.01137 RPN score loss: 0.00423 RPN total loss: 0.0156 Total loss: 0.90393 timestamp: 1655067113.6368186 iteration: 74700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16701 FastRCNN class loss: 0.13665 FastRCNN total loss: 0.30367 L1 loss: 0.0000e+00 L2 loss: 0.5643 Learning rate: 0.0004 Mask loss: 0.19727 RPN box loss: 0.02217 RPN score loss: 0.01605 RPN total loss: 0.03821 Total loss: 1.10345 timestamp: 1655067116.8751357 iteration: 74705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04854 FastRCNN class loss: 0.03838 FastRCNN total loss: 0.08692 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.11487 RPN box loss: 0.00766 RPN score loss: 0.00123 RPN total loss: 0.0089 Total loss: 0.77498 timestamp: 1655067120.1896255 iteration: 74710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09634 FastRCNN class loss: 0.08836 FastRCNN total loss: 0.18469 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.14584 RPN box loss: 0.0186 RPN score loss: 0.00972 RPN total loss: 0.02832 Total loss: 0.92314 timestamp: 1655067123.4573665 iteration: 74715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07924 FastRCNN class loss: 0.04615 FastRCNN total loss: 0.12539 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.12649 RPN box loss: 0.01735 RPN score loss: 0.00126 RPN total loss: 0.01862 Total loss: 0.83479 timestamp: 1655067126.7336702 iteration: 74720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09129 FastRCNN class loss: 0.05727 FastRCNN total loss: 0.14857 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.11965 RPN box loss: 0.02464 RPN score loss: 0.01299 RPN total loss: 0.03763 Total loss: 0.87014 timestamp: 1655067130.01448 iteration: 74725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12189 FastRCNN class loss: 0.07541 FastRCNN total loss: 0.19731 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.14263 RPN box loss: 0.02152 RPN score loss: 0.00527 RPN total loss: 0.02678 Total loss: 0.93101 timestamp: 1655067133.3617282 iteration: 74730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12973 FastRCNN class loss: 0.09457 FastRCNN total loss: 0.22431 L1 loss: 0.0000e+00 L2 loss: 0.56429 Learning rate: 0.0004 Mask loss: 0.15428 RPN box loss: 0.01355 RPN score loss: 0.0091 RPN total loss: 0.02265 Total loss: 0.96552 timestamp: 1655067136.6541278 iteration: 74735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0469 FastRCNN class loss: 0.04524 FastRCNN total loss: 0.09214 L1 loss: 0.0000e+00 L2 loss: 0.56428 Learning rate: 0.0004 Mask loss: 0.14168 RPN box loss: 0.00817 RPN score loss: 0.00103 RPN total loss: 0.0092 Total loss: 0.8073 timestamp: 1655067139.8924816 iteration: 74740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1284 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.20646 L1 loss: 0.0000e+00 L2 loss: 0.56428 Learning rate: 0.0004 Mask loss: 0.11818 RPN box loss: 0.00634 RPN score loss: 0.00368 RPN total loss: 0.01002 Total loss: 0.89895 timestamp: 1655067143.0820465 iteration: 74745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06573 FastRCNN class loss: 0.07601 FastRCNN total loss: 0.14175 L1 loss: 0.0000e+00 L2 loss: 0.56428 Learning rate: 0.0004 Mask loss: 0.13831 RPN box loss: 0.01635 RPN score loss: 0.00297 RPN total loss: 0.01933 Total loss: 0.86366 timestamp: 1655067146.3137636 iteration: 74750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11559 FastRCNN class loss: 0.07822 FastRCNN total loss: 0.19381 L1 loss: 0.0000e+00 L2 loss: 0.56428 Learning rate: 0.0004 Mask loss: 0.11662 RPN box loss: 0.01847 RPN score loss: 0.00649 RPN total loss: 0.02496 Total loss: 0.89966 timestamp: 1655067149.5842042 iteration: 74755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06317 FastRCNN class loss: 0.07355 FastRCNN total loss: 0.13672 L1 loss: 0.0000e+00 L2 loss: 0.56428 Learning rate: 0.0004 Mask loss: 0.16365 RPN box loss: 0.02191 RPN score loss: 0.0149 RPN total loss: 0.03681 Total loss: 0.90145 timestamp: 1655067152.8316188 iteration: 74760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1164 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.19311 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.19459 RPN box loss: 0.0206 RPN score loss: 0.0051 RPN total loss: 0.0257 Total loss: 0.97768 timestamp: 1655067156.0877373 iteration: 74765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05448 FastRCNN class loss: 0.04817 FastRCNN total loss: 0.10265 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.09859 RPN box loss: 0.01652 RPN score loss: 0.00488 RPN total loss: 0.0214 Total loss: 0.78692 timestamp: 1655067159.3481658 iteration: 74770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10053 FastRCNN class loss: 0.11526 FastRCNN total loss: 0.21579 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.20113 RPN box loss: 0.01893 RPN score loss: 0.00986 RPN total loss: 0.0288 Total loss: 1.00999 timestamp: 1655067162.6203566 iteration: 74775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0868 FastRCNN class loss: 0.05349 FastRCNN total loss: 0.14029 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.21985 RPN box loss: 0.03352 RPN score loss: 0.00918 RPN total loss: 0.04269 Total loss: 0.9671 timestamp: 1655067165.9289982 iteration: 74780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06539 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.12665 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.13304 RPN box loss: 0.01233 RPN score loss: 0.01151 RPN total loss: 0.02383 Total loss: 0.84779 timestamp: 1655067169.1742082 iteration: 74785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08682 FastRCNN class loss: 0.06092 FastRCNN total loss: 0.14774 L1 loss: 0.0000e+00 L2 loss: 0.56427 Learning rate: 0.0004 Mask loss: 0.13225 RPN box loss: 0.06504 RPN score loss: 0.00425 RPN total loss: 0.06929 Total loss: 0.91355 timestamp: 1655067172.3965557 iteration: 74790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06804 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.11785 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.14661 RPN box loss: 0.00882 RPN score loss: 0.00148 RPN total loss: 0.0103 Total loss: 0.83902 timestamp: 1655067175.6301394 iteration: 74795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07291 FastRCNN class loss: 0.06292 FastRCNN total loss: 0.13584 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.18984 RPN box loss: 0.01377 RPN score loss: 0.00459 RPN total loss: 0.01835 Total loss: 0.9083 timestamp: 1655067178.9507742 iteration: 74800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11248 FastRCNN class loss: 0.0748 FastRCNN total loss: 0.18727 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.15729 RPN box loss: 0.01266 RPN score loss: 0.00461 RPN total loss: 0.01727 Total loss: 0.9261 timestamp: 1655067182.2545528 iteration: 74805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09777 FastRCNN class loss: 0.08073 FastRCNN total loss: 0.17851 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.14708 RPN box loss: 0.01905 RPN score loss: 0.00495 RPN total loss: 0.024 Total loss: 0.91384 timestamp: 1655067185.5450017 iteration: 74810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.118 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.18267 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.12659 RPN box loss: 0.00991 RPN score loss: 0.00299 RPN total loss: 0.0129 Total loss: 0.88642 timestamp: 1655067188.815444 iteration: 74815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04815 FastRCNN class loss: 0.0562 FastRCNN total loss: 0.10436 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.13425 RPN box loss: 0.01119 RPN score loss: 0.00368 RPN total loss: 0.01487 Total loss: 0.81774 timestamp: 1655067192.161519 iteration: 74820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03835 FastRCNN class loss: 0.04127 FastRCNN total loss: 0.07962 L1 loss: 0.0000e+00 L2 loss: 0.56426 Learning rate: 0.0004 Mask loss: 0.09796 RPN box loss: 0.01071 RPN score loss: 0.00427 RPN total loss: 0.01498 Total loss: 0.75682 timestamp: 1655067195.5086396 iteration: 74825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1517 FastRCNN class loss: 0.09799 FastRCNN total loss: 0.2497 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.23643 RPN box loss: 0.01235 RPN score loss: 0.00848 RPN total loss: 0.02083 Total loss: 1.07121 timestamp: 1655067198.7921464 iteration: 74830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09839 FastRCNN class loss: 0.04488 FastRCNN total loss: 0.14326 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.11036 RPN box loss: 0.007 RPN score loss: 0.00187 RPN total loss: 0.00886 Total loss: 0.82673 timestamp: 1655067202.008405 iteration: 74835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10014 FastRCNN class loss: 0.08516 FastRCNN total loss: 0.1853 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.13768 RPN box loss: 0.02793 RPN score loss: 0.00857 RPN total loss: 0.0365 Total loss: 0.92373 timestamp: 1655067205.2012084 iteration: 74840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06725 FastRCNN class loss: 0.0395 FastRCNN total loss: 0.10675 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.10885 RPN box loss: 0.01248 RPN score loss: 0.00317 RPN total loss: 0.01564 Total loss: 0.79549 timestamp: 1655067208.486066 iteration: 74845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.03583 FastRCNN total loss: 0.11494 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.11849 RPN box loss: 0.00375 RPN score loss: 0.00317 RPN total loss: 0.00692 Total loss: 0.8046 timestamp: 1655067211.7291708 iteration: 74850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09265 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.1663 L1 loss: 0.0000e+00 L2 loss: 0.56425 Learning rate: 0.0004 Mask loss: 0.13403 RPN box loss: 0.00674 RPN score loss: 0.00715 RPN total loss: 0.01389 Total loss: 0.87846 timestamp: 1655067215.0556958 iteration: 74855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06518 FastRCNN class loss: 0.04324 FastRCNN total loss: 0.10841 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.14739 RPN box loss: 0.01105 RPN score loss: 0.00914 RPN total loss: 0.02019 Total loss: 0.84023 timestamp: 1655067218.3152978 iteration: 74860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10578 FastRCNN class loss: 0.08899 FastRCNN total loss: 0.19477 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.12817 RPN box loss: 0.01517 RPN score loss: 0.00807 RPN total loss: 0.02324 Total loss: 0.91042 timestamp: 1655067221.5871756 iteration: 74865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12439 FastRCNN class loss: 0.07131 FastRCNN total loss: 0.19569 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.1792 RPN box loss: 0.0105 RPN score loss: 0.01512 RPN total loss: 0.02562 Total loss: 0.96476 timestamp: 1655067224.868147 iteration: 74870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.05367 FastRCNN total loss: 0.11881 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.10267 RPN box loss: 0.01342 RPN score loss: 0.00376 RPN total loss: 0.01718 Total loss: 0.8029 timestamp: 1655067228.1299825 iteration: 74875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09529 FastRCNN class loss: 0.07283 FastRCNN total loss: 0.16812 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.14224 RPN box loss: 0.01709 RPN score loss: 0.00753 RPN total loss: 0.02462 Total loss: 0.89922 timestamp: 1655067231.4137917 iteration: 74880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09511 FastRCNN class loss: 0.10051 FastRCNN total loss: 0.19562 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.18536 RPN box loss: 0.01232 RPN score loss: 0.00723 RPN total loss: 0.01955 Total loss: 0.96477 timestamp: 1655067234.6923363 iteration: 74885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1242 FastRCNN class loss: 0.10302 FastRCNN total loss: 0.22721 L1 loss: 0.0000e+00 L2 loss: 0.56424 Learning rate: 0.0004 Mask loss: 0.12511 RPN box loss: 0.01937 RPN score loss: 0.0055 RPN total loss: 0.02486 Total loss: 0.94142 timestamp: 1655067237.959865 iteration: 74890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07155 FastRCNN class loss: 0.0466 FastRCNN total loss: 0.11815 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.07932 RPN box loss: 0.00631 RPN score loss: 0.00103 RPN total loss: 0.00733 Total loss: 0.76904 timestamp: 1655067241.227623 iteration: 74895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11108 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.17271 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.14936 RPN box loss: 0.00961 RPN score loss: 0.00467 RPN total loss: 0.01428 Total loss: 0.90057 timestamp: 1655067244.505298 iteration: 74900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14444 FastRCNN class loss: 0.08346 FastRCNN total loss: 0.2279 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.14087 RPN box loss: 0.00877 RPN score loss: 0.00368 RPN total loss: 0.01245 Total loss: 0.94545 timestamp: 1655067247.8285418 iteration: 74905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07819 FastRCNN class loss: 0.07199 FastRCNN total loss: 0.15019 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.15273 RPN box loss: 0.06572 RPN score loss: 0.00464 RPN total loss: 0.07036 Total loss: 0.9375 timestamp: 1655067251.084044 iteration: 74910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07687 FastRCNN class loss: 0.03784 FastRCNN total loss: 0.11471 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.10722 RPN box loss: 0.0127 RPN score loss: 0.00077 RPN total loss: 0.01347 Total loss: 0.79963 timestamp: 1655067254.365544 iteration: 74915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0793 FastRCNN class loss: 0.07705 FastRCNN total loss: 0.15635 L1 loss: 0.0000e+00 L2 loss: 0.56423 Learning rate: 0.0004 Mask loss: 0.163 RPN box loss: 0.01153 RPN score loss: 0.00686 RPN total loss: 0.01839 Total loss: 0.90196 timestamp: 1655067257.7286582 iteration: 74920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05767 FastRCNN class loss: 0.03241 FastRCNN total loss: 0.09008 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.12016 RPN box loss: 0.00496 RPN score loss: 0.00123 RPN total loss: 0.00619 Total loss: 0.78066 timestamp: 1655067261.0694015 iteration: 74925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11082 FastRCNN class loss: 0.04532 FastRCNN total loss: 0.15614 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.10124 RPN box loss: 0.01062 RPN score loss: 0.00386 RPN total loss: 0.01448 Total loss: 0.83609 timestamp: 1655067264.3355284 iteration: 74930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08253 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.142 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.13433 RPN box loss: 0.01747 RPN score loss: 0.01299 RPN total loss: 0.03047 Total loss: 0.87101 timestamp: 1655067267.631763 iteration: 74935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05368 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.10784 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.13769 RPN box loss: 0.01586 RPN score loss: 0.00359 RPN total loss: 0.01945 Total loss: 0.82919 timestamp: 1655067270.9116168 iteration: 74940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1153 FastRCNN class loss: 0.04496 FastRCNN total loss: 0.16025 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.13217 RPN box loss: 0.01215 RPN score loss: 0.00209 RPN total loss: 0.01424 Total loss: 0.87088 timestamp: 1655067274.1243658 iteration: 74945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.16106 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.15229 RPN box loss: 0.02005 RPN score loss: 0.01141 RPN total loss: 0.03146 Total loss: 0.90903 timestamp: 1655067277.4640028 iteration: 74950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14274 FastRCNN class loss: 0.16588 FastRCNN total loss: 0.30862 L1 loss: 0.0000e+00 L2 loss: 0.56422 Learning rate: 0.0004 Mask loss: 0.22858 RPN box loss: 0.03433 RPN score loss: 0.01622 RPN total loss: 0.05055 Total loss: 1.15196 timestamp: 1655067280.752905 iteration: 74955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16391 FastRCNN class loss: 0.05844 FastRCNN total loss: 0.22235 L1 loss: 0.0000e+00 L2 loss: 0.56421 Learning rate: 0.0004 Mask loss: 0.14671 RPN box loss: 0.01249 RPN score loss: 0.00272 RPN total loss: 0.01521 Total loss: 0.94848 timestamp: 1655067284.0776336 iteration: 74960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04838 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.10036 L1 loss: 0.0000e+00 L2 loss: 0.56421 Learning rate: 0.0004 Mask loss: 0.13711 RPN box loss: 0.0076 RPN score loss: 0.00208 RPN total loss: 0.00969 Total loss: 0.81137 timestamp: 1655067287.433006 iteration: 74965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08316 FastRCNN class loss: 0.04642 FastRCNN total loss: 0.12958 L1 loss: 0.0000e+00 L2 loss: 0.56421 Learning rate: 0.0004 Mask loss: 0.16891 RPN box loss: 0.00765 RPN score loss: 0.0013 RPN total loss: 0.00895 Total loss: 0.87164 timestamp: 1655067290.6752877 iteration: 74970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.09218 FastRCNN total loss: 0.1842 L1 loss: 0.0000e+00 L2 loss: 0.56421 Learning rate: 0.0004 Mask loss: 0.13242 RPN box loss: 0.00898 RPN score loss: 0.00285 RPN total loss: 0.01183 Total loss: 0.89265 timestamp: 1655067293.9045427 iteration: 74975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11516 FastRCNN class loss: 0.0758 FastRCNN total loss: 0.19095 L1 loss: 0.0000e+00 L2 loss: 0.56421 Learning rate: 0.0004 Mask loss: 0.18753 RPN box loss: 0.01642 RPN score loss: 0.01057 RPN total loss: 0.02699 Total loss: 0.96968 timestamp: 1655067297.2197745 iteration: 74980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.08036 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.16446 RPN box loss: 0.01045 RPN score loss: 0.0046 RPN total loss: 0.01505 Total loss: 0.90393 timestamp: 1655067300.4801614 iteration: 74985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07451 FastRCNN class loss: 0.07058 FastRCNN total loss: 0.14508 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.14041 RPN box loss: 0.01093 RPN score loss: 0.00818 RPN total loss: 0.01911 Total loss: 0.86881 timestamp: 1655067303.7605739 iteration: 74990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14238 FastRCNN class loss: 0.09562 FastRCNN total loss: 0.238 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.14087 RPN box loss: 0.01963 RPN score loss: 0.00692 RPN total loss: 0.02654 Total loss: 0.96961 timestamp: 1655067307.0514932 iteration: 74995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09303 FastRCNN class loss: 0.09553 FastRCNN total loss: 0.18856 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.18914 RPN box loss: 0.00791 RPN score loss: 0.00208 RPN total loss: 0.00999 Total loss: 0.9519 timestamp: 1655067310.343151 iteration: 75000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07365 FastRCNN class loss: 0.06698 FastRCNN total loss: 0.14062 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.16511 RPN box loss: 0.01402 RPN score loss: 0.00533 RPN total loss: 0.01935 Total loss: 0.88928 timestamp: 1655067313.5117493 iteration: 75005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13806 FastRCNN class loss: 0.1111 FastRCNN total loss: 0.24916 L1 loss: 0.0000e+00 L2 loss: 0.5642 Learning rate: 0.0004 Mask loss: 0.16227 RPN box loss: 0.01702 RPN score loss: 0.02786 RPN total loss: 0.04488 Total loss: 1.02051 timestamp: 1655067316.820148 iteration: 75010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0908 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.15554 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.15974 RPN box loss: 0.01376 RPN score loss: 0.00443 RPN total loss: 0.01819 Total loss: 0.89767 timestamp: 1655067320.0349424 iteration: 75015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09362 FastRCNN class loss: 0.0818 FastRCNN total loss: 0.17541 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.18226 RPN box loss: 0.05024 RPN score loss: 0.01179 RPN total loss: 0.06203 Total loss: 0.9839 timestamp: 1655067323.3521147 iteration: 75020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07155 FastRCNN class loss: 0.05326 FastRCNN total loss: 0.1248 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.08262 RPN box loss: 0.00644 RPN score loss: 0.00677 RPN total loss: 0.01321 Total loss: 0.78483 timestamp: 1655067326.6621234 iteration: 75025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13093 FastRCNN class loss: 0.10913 FastRCNN total loss: 0.24006 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.19634 RPN box loss: 0.02036 RPN score loss: 0.01459 RPN total loss: 0.03495 Total loss: 1.03554 timestamp: 1655067329.993151 iteration: 75030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09657 FastRCNN class loss: 0.04175 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.10852 RPN box loss: 0.00462 RPN score loss: 0.00464 RPN total loss: 0.00926 Total loss: 0.8203 timestamp: 1655067333.2495804 iteration: 75035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08436 FastRCNN class loss: 0.04752 FastRCNN total loss: 0.13188 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.13453 RPN box loss: 0.0087 RPN score loss: 0.00424 RPN total loss: 0.01294 Total loss: 0.84354 timestamp: 1655067336.5198956 iteration: 75040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10856 FastRCNN class loss: 0.10876 FastRCNN total loss: 0.21732 L1 loss: 0.0000e+00 L2 loss: 0.56419 Learning rate: 0.0004 Mask loss: 0.20746 RPN box loss: 0.01575 RPN score loss: 0.01148 RPN total loss: 0.02724 Total loss: 1.01621 timestamp: 1655067339.789986 iteration: 75045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06103 FastRCNN class loss: 0.04411 FastRCNN total loss: 0.10514 L1 loss: 0.0000e+00 L2 loss: 0.56418 Learning rate: 0.0004 Mask loss: 0.06837 RPN box loss: 0.00625 RPN score loss: 0.00531 RPN total loss: 0.01156 Total loss: 0.74926 timestamp: 1655067343.0620892 iteration: 75050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05038 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.09888 L1 loss: 0.0000e+00 L2 loss: 0.56418 Learning rate: 0.0004 Mask loss: 0.13784 RPN box loss: 0.00601 RPN score loss: 0.0054 RPN total loss: 0.01142 Total loss: 0.81231 timestamp: 1655067346.3846424 iteration: 75055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09569 FastRCNN class loss: 0.06636 FastRCNN total loss: 0.16206 L1 loss: 0.0000e+00 L2 loss: 0.56418 Learning rate: 0.0004 Mask loss: 0.11844 RPN box loss: 0.01072 RPN score loss: 0.00334 RPN total loss: 0.01407 Total loss: 0.85874 timestamp: 1655067349.650401 iteration: 75060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09752 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.56418 Learning rate: 0.0004 Mask loss: 0.12383 RPN box loss: 0.00634 RPN score loss: 0.01067 RPN total loss: 0.01701 Total loss: 0.88156 timestamp: 1655067352.9233491 iteration: 75065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10253 FastRCNN class loss: 0.05779 FastRCNN total loss: 0.16032 L1 loss: 0.0000e+00 L2 loss: 0.56418 Learning rate: 0.0004 Mask loss: 0.1396 RPN box loss: 0.03164 RPN score loss: 0.01372 RPN total loss: 0.04536 Total loss: 0.90946 timestamp: 1655067356.2341256 iteration: 75070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12483 FastRCNN class loss: 0.09158 FastRCNN total loss: 0.21641 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.1342 RPN box loss: 0.03638 RPN score loss: 0.0049 RPN total loss: 0.04128 Total loss: 0.95606 timestamp: 1655067359.4530673 iteration: 75075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08327 FastRCNN class loss: 0.09203 FastRCNN total loss: 0.1753 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.12553 RPN box loss: 0.01009 RPN score loss: 0.00204 RPN total loss: 0.01213 Total loss: 0.87714 timestamp: 1655067362.721503 iteration: 75080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10399 FastRCNN class loss: 0.05888 FastRCNN total loss: 0.16288 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.12493 RPN box loss: 0.0074 RPN score loss: 0.00709 RPN total loss: 0.0145 Total loss: 0.86647 timestamp: 1655067365.9604294 iteration: 75085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07131 FastRCNN class loss: 0.07631 FastRCNN total loss: 0.14761 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.14224 RPN box loss: 0.01149 RPN score loss: 0.00776 RPN total loss: 0.01926 Total loss: 0.87328 timestamp: 1655067369.2628386 iteration: 75090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07414 FastRCNN class loss: 0.05212 FastRCNN total loss: 0.12626 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.15112 RPN box loss: 0.01246 RPN score loss: 0.0015 RPN total loss: 0.01396 Total loss: 0.85551 timestamp: 1655067372.5941973 iteration: 75095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09262 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.17175 L1 loss: 0.0000e+00 L2 loss: 0.56417 Learning rate: 0.0004 Mask loss: 0.13452 RPN box loss: 0.02026 RPN score loss: 0.0091 RPN total loss: 0.02936 Total loss: 0.89979 timestamp: 1655067375.8657038 iteration: 75100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0874 FastRCNN class loss: 0.05656 FastRCNN total loss: 0.14396 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.09154 RPN box loss: 0.01586 RPN score loss: 0.00849 RPN total loss: 0.02435 Total loss: 0.82402 timestamp: 1655067379.1210675 iteration: 75105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05787 FastRCNN class loss: 0.0425 FastRCNN total loss: 0.10036 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.10115 RPN box loss: 0.00671 RPN score loss: 0.00453 RPN total loss: 0.01124 Total loss: 0.77691 timestamp: 1655067382.38625 iteration: 75110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07908 FastRCNN class loss: 0.07171 FastRCNN total loss: 0.15079 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.15173 RPN box loss: 0.02199 RPN score loss: 0.00424 RPN total loss: 0.02623 Total loss: 0.89292 timestamp: 1655067385.7123013 iteration: 75115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11246 FastRCNN class loss: 0.07914 FastRCNN total loss: 0.1916 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.14554 RPN box loss: 0.01378 RPN score loss: 0.00334 RPN total loss: 0.01711 Total loss: 0.91841 timestamp: 1655067389.0524454 iteration: 75120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.15371 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.18901 RPN box loss: 0.00491 RPN score loss: 0.00552 RPN total loss: 0.01043 Total loss: 0.91731 timestamp: 1655067392.3743334 iteration: 75125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04609 FastRCNN class loss: 0.047 FastRCNN total loss: 0.09309 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.11075 RPN box loss: 0.00676 RPN score loss: 0.00363 RPN total loss: 0.01039 Total loss: 0.77839 timestamp: 1655067395.6463706 iteration: 75130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07938 FastRCNN class loss: 0.06639 FastRCNN total loss: 0.14576 L1 loss: 0.0000e+00 L2 loss: 0.56416 Learning rate: 0.0004 Mask loss: 0.14241 RPN box loss: 0.00798 RPN score loss: 0.0052 RPN total loss: 0.01318 Total loss: 0.86551 timestamp: 1655067398.917954 iteration: 75135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.11349 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.13418 RPN box loss: 0.00631 RPN score loss: 0.00666 RPN total loss: 0.01297 Total loss: 0.82479 timestamp: 1655067402.2292464 iteration: 75140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10348 FastRCNN class loss: 0.05855 FastRCNN total loss: 0.16203 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.10291 RPN box loss: 0.0058 RPN score loss: 0.00443 RPN total loss: 0.01023 Total loss: 0.83932 timestamp: 1655067405.4509082 iteration: 75145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05819 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.11266 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.13173 RPN box loss: 0.02296 RPN score loss: 0.00328 RPN total loss: 0.02624 Total loss: 0.83478 timestamp: 1655067408.646522 iteration: 75150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09114 FastRCNN class loss: 0.07561 FastRCNN total loss: 0.16675 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.16518 RPN box loss: 0.01369 RPN score loss: 0.00518 RPN total loss: 0.01887 Total loss: 0.91495 timestamp: 1655067411.8822796 iteration: 75155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07964 FastRCNN class loss: 0.0569 FastRCNN total loss: 0.13654 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.08914 RPN box loss: 0.00526 RPN score loss: 0.00338 RPN total loss: 0.00864 Total loss: 0.79847 timestamp: 1655067415.2175853 iteration: 75160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10339 FastRCNN class loss: 0.08496 FastRCNN total loss: 0.18835 L1 loss: 0.0000e+00 L2 loss: 0.56415 Learning rate: 0.0004 Mask loss: 0.10224 RPN box loss: 0.01741 RPN score loss: 0.00231 RPN total loss: 0.01971 Total loss: 0.87444 timestamp: 1655067418.479519 iteration: 75165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09252 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.14965 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.1403 RPN box loss: 0.00335 RPN score loss: 0.00494 RPN total loss: 0.00829 Total loss: 0.86239 timestamp: 1655067421.7740037 iteration: 75170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13411 FastRCNN class loss: 0.10711 FastRCNN total loss: 0.24121 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.20943 RPN box loss: 0.01475 RPN score loss: 0.00583 RPN total loss: 0.02059 Total loss: 1.03538 timestamp: 1655067425.0253265 iteration: 75175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09464 FastRCNN class loss: 0.06882 FastRCNN total loss: 0.16346 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.1052 RPN box loss: 0.01704 RPN score loss: 0.00446 RPN total loss: 0.0215 Total loss: 0.8543 timestamp: 1655067428.2518826 iteration: 75180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12517 FastRCNN class loss: 0.12397 FastRCNN total loss: 0.24914 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.18032 RPN box loss: 0.0079 RPN score loss: 0.00703 RPN total loss: 0.01493 Total loss: 1.00853 timestamp: 1655067431.5272124 iteration: 75185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12952 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.20086 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.16465 RPN box loss: 0.00513 RPN score loss: 0.0108 RPN total loss: 0.01594 Total loss: 0.94558 timestamp: 1655067434.8437014 iteration: 75190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08622 FastRCNN class loss: 0.0618 FastRCNN total loss: 0.14802 L1 loss: 0.0000e+00 L2 loss: 0.56414 Learning rate: 0.0004 Mask loss: 0.15196 RPN box loss: 0.0088 RPN score loss: 0.00879 RPN total loss: 0.0176 Total loss: 0.88171 timestamp: 1655067438.0924265 iteration: 75195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15654 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.23191 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.11825 RPN box loss: 0.0563 RPN score loss: 0.00727 RPN total loss: 0.06357 Total loss: 0.97787 timestamp: 1655067441.3380907 iteration: 75200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17531 FastRCNN class loss: 0.07846 FastRCNN total loss: 0.25377 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.15512 RPN box loss: 0.01492 RPN score loss: 0.0022 RPN total loss: 0.01712 Total loss: 0.99015 timestamp: 1655067444.5694773 iteration: 75205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08882 FastRCNN class loss: 0.06646 FastRCNN total loss: 0.15529 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.15033 RPN box loss: 0.0073 RPN score loss: 0.00305 RPN total loss: 0.01035 Total loss: 0.8801 timestamp: 1655067447.8135052 iteration: 75210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10834 FastRCNN class loss: 0.07782 FastRCNN total loss: 0.18616 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.15729 RPN box loss: 0.01816 RPN score loss: 0.00618 RPN total loss: 0.02434 Total loss: 0.93192 timestamp: 1655067451.0783246 iteration: 75215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15536 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.22147 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.16567 RPN box loss: 0.01107 RPN score loss: 0.01297 RPN total loss: 0.02403 Total loss: 0.9753 timestamp: 1655067454.3414595 iteration: 75220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12554 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.20616 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.08969 RPN box loss: 0.01536 RPN score loss: 0.01633 RPN total loss: 0.03168 Total loss: 0.89166 timestamp: 1655067457.6154885 iteration: 75225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13777 FastRCNN class loss: 0.112 FastRCNN total loss: 0.24977 L1 loss: 0.0000e+00 L2 loss: 0.56413 Learning rate: 0.0004 Mask loss: 0.19414 RPN box loss: 0.01381 RPN score loss: 0.01558 RPN total loss: 0.0294 Total loss: 1.03743 timestamp: 1655067460.883724 iteration: 75230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06096 FastRCNN class loss: 0.0676 FastRCNN total loss: 0.12856 L1 loss: 0.0000e+00 L2 loss: 0.56412 Learning rate: 0.0004 Mask loss: 0.19404 RPN box loss: 0.01282 RPN score loss: 0.00747 RPN total loss: 0.0203 Total loss: 0.90703 timestamp: 1655067464.2357192 iteration: 75235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08653 FastRCNN class loss: 0.05426 FastRCNN total loss: 0.14079 L1 loss: 0.0000e+00 L2 loss: 0.56412 Learning rate: 0.0004 Mask loss: 0.11849 RPN box loss: 0.00594 RPN score loss: 0.00311 RPN total loss: 0.00906 Total loss: 0.83245 timestamp: 1655067467.5470357 iteration: 75240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06735 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.1331 L1 loss: 0.0000e+00 L2 loss: 0.56412 Learning rate: 0.0004 Mask loss: 0.11198 RPN box loss: 0.01141 RPN score loss: 0.00375 RPN total loss: 0.01516 Total loss: 0.82436 timestamp: 1655067470.874846 iteration: 75245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07942 FastRCNN class loss: 0.06013 FastRCNN total loss: 0.13954 L1 loss: 0.0000e+00 L2 loss: 0.56412 Learning rate: 0.0004 Mask loss: 0.12613 RPN box loss: 0.01613 RPN score loss: 0.00822 RPN total loss: 0.02435 Total loss: 0.85414 timestamp: 1655067474.177298 iteration: 75250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11312 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.18048 L1 loss: 0.0000e+00 L2 loss: 0.56412 Learning rate: 0.0004 Mask loss: 0.14923 RPN box loss: 0.01172 RPN score loss: 0.00281 RPN total loss: 0.01454 Total loss: 0.90836 timestamp: 1655067477.425143 iteration: 75255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1933 FastRCNN class loss: 0.07181 FastRCNN total loss: 0.26511 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.11385 RPN box loss: 0.00617 RPN score loss: 0.00274 RPN total loss: 0.00891 Total loss: 0.95199 timestamp: 1655067480.73866 iteration: 75260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07016 FastRCNN class loss: 0.06335 FastRCNN total loss: 0.13352 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.14495 RPN box loss: 0.00929 RPN score loss: 0.00602 RPN total loss: 0.01531 Total loss: 0.85789 timestamp: 1655067484.013407 iteration: 75265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06455 FastRCNN class loss: 0.04101 FastRCNN total loss: 0.10556 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.06002 RPN box loss: 0.00281 RPN score loss: 0.00166 RPN total loss: 0.00447 Total loss: 0.73416 timestamp: 1655067487.2700422 iteration: 75270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07584 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.13641 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.15756 RPN box loss: 0.0141 RPN score loss: 0.00267 RPN total loss: 0.01678 Total loss: 0.87485 timestamp: 1655067490.5627918 iteration: 75275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09764 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.17936 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.13446 RPN box loss: 0.01281 RPN score loss: 0.00646 RPN total loss: 0.01927 Total loss: 0.8972 timestamp: 1655067493.8698077 iteration: 75280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09759 FastRCNN class loss: 0.0907 FastRCNN total loss: 0.18829 L1 loss: 0.0000e+00 L2 loss: 0.56411 Learning rate: 0.0004 Mask loss: 0.11022 RPN box loss: 0.01939 RPN score loss: 0.01203 RPN total loss: 0.03142 Total loss: 0.89403 timestamp: 1655067497.1436532 iteration: 75285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12588 FastRCNN class loss: 0.05469 FastRCNN total loss: 0.18058 L1 loss: 0.0000e+00 L2 loss: 0.5641 Learning rate: 0.0004 Mask loss: 0.12554 RPN box loss: 0.01252 RPN score loss: 0.00104 RPN total loss: 0.01356 Total loss: 0.88378 timestamp: 1655067500.4552655 iteration: 75290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11798 FastRCNN class loss: 0.04835 FastRCNN total loss: 0.16632 L1 loss: 0.0000e+00 L2 loss: 0.5641 Learning rate: 0.0004 Mask loss: 0.09554 RPN box loss: 0.01123 RPN score loss: 0.00216 RPN total loss: 0.01339 Total loss: 0.83936 timestamp: 1655067503.7715287 iteration: 75295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10743 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.17265 L1 loss: 0.0000e+00 L2 loss: 0.5641 Learning rate: 0.0004 Mask loss: 0.17192 RPN box loss: 0.01758 RPN score loss: 0.00193 RPN total loss: 0.01951 Total loss: 0.92818 timestamp: 1655067507.0778756 iteration: 75300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07942 FastRCNN class loss: 0.04132 FastRCNN total loss: 0.12074 L1 loss: 0.0000e+00 L2 loss: 0.5641 Learning rate: 0.0004 Mask loss: 0.15779 RPN box loss: 0.00685 RPN score loss: 0.0051 RPN total loss: 0.01196 Total loss: 0.85459 timestamp: 1655067510.298833 iteration: 75305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09256 FastRCNN class loss: 0.08702 FastRCNN total loss: 0.17958 L1 loss: 0.0000e+00 L2 loss: 0.5641 Learning rate: 0.0004 Mask loss: 0.20407 RPN box loss: 0.01764 RPN score loss: 0.00777 RPN total loss: 0.02541 Total loss: 0.97316 timestamp: 1655067513.601008 iteration: 75310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04556 FastRCNN class loss: 0.03754 FastRCNN total loss: 0.0831 L1 loss: 0.0000e+00 L2 loss: 0.56409 Learning rate: 0.0004 Mask loss: 0.10323 RPN box loss: 0.00306 RPN score loss: 0.00107 RPN total loss: 0.00413 Total loss: 0.75455 timestamp: 1655067516.889546 iteration: 75315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06303 FastRCNN class loss: 0.0568 FastRCNN total loss: 0.11983 L1 loss: 0.0000e+00 L2 loss: 0.56409 Learning rate: 0.0004 Mask loss: 0.15843 RPN box loss: 0.01529 RPN score loss: 0.00441 RPN total loss: 0.0197 Total loss: 0.86205 timestamp: 1655067520.1525729 iteration: 75320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07932 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.1494 L1 loss: 0.0000e+00 L2 loss: 0.56409 Learning rate: 0.0004 Mask loss: 0.15143 RPN box loss: 0.02892 RPN score loss: 0.00104 RPN total loss: 0.02995 Total loss: 0.89487 timestamp: 1655067523.414273 iteration: 75325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06573 FastRCNN class loss: 0.06826 FastRCNN total loss: 0.13399 L1 loss: 0.0000e+00 L2 loss: 0.56409 Learning rate: 0.0004 Mask loss: 0.13702 RPN box loss: 0.00772 RPN score loss: 0.00671 RPN total loss: 0.01443 Total loss: 0.84953 timestamp: 1655067526.7122939 iteration: 75330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10767 FastRCNN class loss: 0.09581 FastRCNN total loss: 0.20348 L1 loss: 0.0000e+00 L2 loss: 0.56409 Learning rate: 0.0004 Mask loss: 0.15026 RPN box loss: 0.00912 RPN score loss: 0.00563 RPN total loss: 0.01475 Total loss: 0.93258 timestamp: 1655067529.959836 iteration: 75335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09671 FastRCNN class loss: 0.0529 FastRCNN total loss: 0.14961 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.12009 RPN box loss: 0.00974 RPN score loss: 0.00797 RPN total loss: 0.01771 Total loss: 0.8515 timestamp: 1655067533.2310567 iteration: 75340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08776 FastRCNN class loss: 0.0629 FastRCNN total loss: 0.15066 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.12137 RPN box loss: 0.04913 RPN score loss: 0.00432 RPN total loss: 0.05345 Total loss: 0.88957 timestamp: 1655067536.5052035 iteration: 75345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05768 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.11501 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.13703 RPN box loss: 0.02719 RPN score loss: 0.00811 RPN total loss: 0.0353 Total loss: 0.85142 timestamp: 1655067539.7447073 iteration: 75350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08838 FastRCNN class loss: 0.07289 FastRCNN total loss: 0.16126 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.12326 RPN box loss: 0.00854 RPN score loss: 0.00603 RPN total loss: 0.01457 Total loss: 0.86318 timestamp: 1655067543.079271 iteration: 75355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15673 FastRCNN class loss: 0.09533 FastRCNN total loss: 0.25207 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.15199 RPN box loss: 0.02274 RPN score loss: 0.02158 RPN total loss: 0.04432 Total loss: 1.01246 timestamp: 1655067546.380276 iteration: 75360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10313 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.14954 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.11299 RPN box loss: 0.03533 RPN score loss: 0.00172 RPN total loss: 0.03706 Total loss: 0.86367 timestamp: 1655067549.6782289 iteration: 75365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06009 FastRCNN class loss: 0.03987 FastRCNN total loss: 0.09997 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.16187 RPN box loss: 0.0063 RPN score loss: 0.00585 RPN total loss: 0.01215 Total loss: 0.83807 timestamp: 1655067552.977102 iteration: 75370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08133 FastRCNN class loss: 0.06457 FastRCNN total loss: 0.1459 L1 loss: 0.0000e+00 L2 loss: 0.56408 Learning rate: 0.0004 Mask loss: 0.12476 RPN box loss: 0.01194 RPN score loss: 0.00593 RPN total loss: 0.01788 Total loss: 0.85261 timestamp: 1655067556.1969678 iteration: 75375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12159 FastRCNN class loss: 0.07402 FastRCNN total loss: 0.19561 L1 loss: 0.0000e+00 L2 loss: 0.56407 Learning rate: 0.0004 Mask loss: 0.19085 RPN box loss: 0.0442 RPN score loss: 0.00799 RPN total loss: 0.05219 Total loss: 1.00273 timestamp: 1655067559.4098182 iteration: 75380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15216 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.22769 L1 loss: 0.0000e+00 L2 loss: 0.56407 Learning rate: 0.0004 Mask loss: 0.14768 RPN box loss: 0.01284 RPN score loss: 0.00613 RPN total loss: 0.01897 Total loss: 0.95841 timestamp: 1655067562.6621811 iteration: 75385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08126 FastRCNN class loss: 0.04937 FastRCNN total loss: 0.13064 L1 loss: 0.0000e+00 L2 loss: 0.56407 Learning rate: 0.0004 Mask loss: 0.1153 RPN box loss: 0.01792 RPN score loss: 0.00378 RPN total loss: 0.0217 Total loss: 0.83171 timestamp: 1655067565.9136994 iteration: 75390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06242 FastRCNN class loss: 0.08757 FastRCNN total loss: 0.15 L1 loss: 0.0000e+00 L2 loss: 0.56407 Learning rate: 0.0004 Mask loss: 0.14219 RPN box loss: 0.03225 RPN score loss: 0.00609 RPN total loss: 0.03834 Total loss: 0.8946 timestamp: 1655067569.1492453 iteration: 75395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04496 FastRCNN class loss: 0.03595 FastRCNN total loss: 0.08091 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.12664 RPN box loss: 0.0194 RPN score loss: 0.00333 RPN total loss: 0.02273 Total loss: 0.79435 timestamp: 1655067572.4110594 iteration: 75400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1156 FastRCNN class loss: 0.0466 FastRCNN total loss: 0.1622 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.15431 RPN box loss: 0.00855 RPN score loss: 0.0019 RPN total loss: 0.01046 Total loss: 0.89103 timestamp: 1655067575.634689 iteration: 75405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06141 FastRCNN class loss: 0.06687 FastRCNN total loss: 0.12829 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.08553 RPN box loss: 0.01227 RPN score loss: 0.00171 RPN total loss: 0.01398 Total loss: 0.79186 timestamp: 1655067578.8658612 iteration: 75410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07275 FastRCNN class loss: 0.04016 FastRCNN total loss: 0.11291 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.12257 RPN box loss: 0.00489 RPN score loss: 0.00315 RPN total loss: 0.00804 Total loss: 0.80758 timestamp: 1655067582.1172411 iteration: 75415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17305 FastRCNN class loss: 0.05459 FastRCNN total loss: 0.22764 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.18018 RPN box loss: 0.01494 RPN score loss: 0.00734 RPN total loss: 0.02228 Total loss: 0.99416 timestamp: 1655067585.3764389 iteration: 75420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05775 FastRCNN class loss: 0.03882 FastRCNN total loss: 0.09657 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.10194 RPN box loss: 0.01111 RPN score loss: 0.00746 RPN total loss: 0.01858 Total loss: 0.78115 timestamp: 1655067588.6351266 iteration: 75425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05276 FastRCNN class loss: 0.07602 FastRCNN total loss: 0.12878 L1 loss: 0.0000e+00 L2 loss: 0.56406 Learning rate: 0.0004 Mask loss: 0.16583 RPN box loss: 0.02087 RPN score loss: 0.00977 RPN total loss: 0.03063 Total loss: 0.88929 timestamp: 1655067591.897606 iteration: 75430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07565 FastRCNN class loss: 0.04438 FastRCNN total loss: 0.12003 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.11956 RPN box loss: 0.01253 RPN score loss: 0.00265 RPN total loss: 0.01518 Total loss: 0.81882 timestamp: 1655067595.196454 iteration: 75435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06799 FastRCNN class loss: 0.0563 FastRCNN total loss: 0.1243 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.10646 RPN box loss: 0.01185 RPN score loss: 0.00374 RPN total loss: 0.01559 Total loss: 0.81041 timestamp: 1655067598.4424286 iteration: 75440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.07881 FastRCNN total loss: 0.18227 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.20722 RPN box loss: 0.02548 RPN score loss: 0.00783 RPN total loss: 0.03331 Total loss: 0.98685 timestamp: 1655067601.7320967 iteration: 75445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05137 FastRCNN class loss: 0.04852 FastRCNN total loss: 0.09989 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.12952 RPN box loss: 0.0078 RPN score loss: 0.00383 RPN total loss: 0.01164 Total loss: 0.80509 timestamp: 1655067604.9689922 iteration: 75450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08845 FastRCNN class loss: 0.05368 FastRCNN total loss: 0.14213 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.10347 RPN box loss: 0.00932 RPN score loss: 0.00115 RPN total loss: 0.01047 Total loss: 0.82011 timestamp: 1655067608.278404 iteration: 75455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10338 FastRCNN class loss: 0.07017 FastRCNN total loss: 0.17355 L1 loss: 0.0000e+00 L2 loss: 0.56405 Learning rate: 0.0004 Mask loss: 0.15006 RPN box loss: 0.02288 RPN score loss: 0.01126 RPN total loss: 0.03414 Total loss: 0.92179 timestamp: 1655067611.5449178 iteration: 75460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15038 FastRCNN class loss: 0.08783 FastRCNN total loss: 0.23821 L1 loss: 0.0000e+00 L2 loss: 0.56404 Learning rate: 0.0004 Mask loss: 0.10348 RPN box loss: 0.01042 RPN score loss: 0.00291 RPN total loss: 0.01333 Total loss: 0.91906 timestamp: 1655067614.8225298 iteration: 75465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08308 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.15426 L1 loss: 0.0000e+00 L2 loss: 0.56404 Learning rate: 0.0004 Mask loss: 0.15522 RPN box loss: 0.01201 RPN score loss: 0.00466 RPN total loss: 0.01667 Total loss: 0.89019 timestamp: 1655067618.1180792 iteration: 75470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10727 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.19289 L1 loss: 0.0000e+00 L2 loss: 0.56404 Learning rate: 0.0004 Mask loss: 0.18435 RPN box loss: 0.01011 RPN score loss: 0.00825 RPN total loss: 0.01836 Total loss: 0.95964 timestamp: 1655067621.384321 iteration: 75475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08646 FastRCNN class loss: 0.03779 FastRCNN total loss: 0.12425 L1 loss: 0.0000e+00 L2 loss: 0.56404 Learning rate: 0.0004 Mask loss: 0.13646 RPN box loss: 0.01046 RPN score loss: 0.00589 RPN total loss: 0.01635 Total loss: 0.84111 timestamp: 1655067624.6455827 iteration: 75480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05472 FastRCNN class loss: 0.05223 FastRCNN total loss: 0.10696 L1 loss: 0.0000e+00 L2 loss: 0.56404 Learning rate: 0.0004 Mask loss: 0.11113 RPN box loss: 0.01853 RPN score loss: 0.00528 RPN total loss: 0.02382 Total loss: 0.80594 timestamp: 1655067627.9125404 iteration: 75485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09303 FastRCNN class loss: 0.0902 FastRCNN total loss: 0.18323 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.21897 RPN box loss: 0.00955 RPN score loss: 0.00437 RPN total loss: 0.01392 Total loss: 0.98015 timestamp: 1655067631.213312 iteration: 75490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11604 FastRCNN class loss: 0.10975 FastRCNN total loss: 0.22579 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.15627 RPN box loss: 0.01385 RPN score loss: 0.00987 RPN total loss: 0.02372 Total loss: 0.96982 timestamp: 1655067634.4749675 iteration: 75495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11408 FastRCNN class loss: 0.0842 FastRCNN total loss: 0.19828 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.14415 RPN box loss: 0.04542 RPN score loss: 0.0065 RPN total loss: 0.05192 Total loss: 0.95837 timestamp: 1655067637.7673085 iteration: 75500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04844 FastRCNN class loss: 0.03453 FastRCNN total loss: 0.08297 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.09517 RPN box loss: 0.00141 RPN score loss: 0.00289 RPN total loss: 0.0043 Total loss: 0.74647 timestamp: 1655067641.072829 iteration: 75505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.05684 FastRCNN total loss: 0.13041 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.15784 RPN box loss: 0.00921 RPN score loss: 0.0017 RPN total loss: 0.01091 Total loss: 0.86319 timestamp: 1655067644.3679447 iteration: 75510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08588 FastRCNN class loss: 0.09232 FastRCNN total loss: 0.1782 L1 loss: 0.0000e+00 L2 loss: 0.56403 Learning rate: 0.0004 Mask loss: 0.15694 RPN box loss: 0.01826 RPN score loss: 0.00956 RPN total loss: 0.02782 Total loss: 0.92699 timestamp: 1655067647.6806931 iteration: 75515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10667 FastRCNN class loss: 0.07958 FastRCNN total loss: 0.18625 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.18421 RPN box loss: 0.02275 RPN score loss: 0.01174 RPN total loss: 0.03449 Total loss: 0.96897 timestamp: 1655067650.941157 iteration: 75520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12296 FastRCNN class loss: 0.09239 FastRCNN total loss: 0.21536 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.18239 RPN box loss: 0.01532 RPN score loss: 0.0116 RPN total loss: 0.02692 Total loss: 0.98869 timestamp: 1655067654.2365036 iteration: 75525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09322 FastRCNN class loss: 0.06342 FastRCNN total loss: 0.15664 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.09936 RPN box loss: 0.01274 RPN score loss: 0.0021 RPN total loss: 0.01484 Total loss: 0.83486 timestamp: 1655067657.5463154 iteration: 75530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1338 FastRCNN class loss: 0.08009 FastRCNN total loss: 0.21389 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.18961 RPN box loss: 0.0107 RPN score loss: 0.00367 RPN total loss: 0.01437 Total loss: 0.9819 timestamp: 1655067660.9226844 iteration: 75535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09726 FastRCNN class loss: 0.1076 FastRCNN total loss: 0.20485 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.20178 RPN box loss: 0.01705 RPN score loss: 0.009 RPN total loss: 0.02606 Total loss: 0.99671 timestamp: 1655067664.1865392 iteration: 75540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12279 FastRCNN class loss: 0.069 FastRCNN total loss: 0.19179 L1 loss: 0.0000e+00 L2 loss: 0.56402 Learning rate: 0.0004 Mask loss: 0.14333 RPN box loss: 0.00676 RPN score loss: 0.01062 RPN total loss: 0.01737 Total loss: 0.91652 timestamp: 1655067667.463534 iteration: 75545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1386 FastRCNN class loss: 0.07913 FastRCNN total loss: 0.21773 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.16965 RPN box loss: 0.03138 RPN score loss: 0.00571 RPN total loss: 0.03709 Total loss: 0.98848 timestamp: 1655067670.7276008 iteration: 75550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09731 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.14748 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.09324 RPN box loss: 0.01666 RPN score loss: 0.00644 RPN total loss: 0.0231 Total loss: 0.82783 timestamp: 1655067673.9888864 iteration: 75555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13631 FastRCNN class loss: 0.11566 FastRCNN total loss: 0.25197 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.2266 RPN box loss: 0.01751 RPN score loss: 0.01597 RPN total loss: 0.03348 Total loss: 1.07606 timestamp: 1655067677.2911425 iteration: 75560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0519 FastRCNN class loss: 0.03762 FastRCNN total loss: 0.08953 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.10721 RPN box loss: 0.00264 RPN score loss: 0.00898 RPN total loss: 0.01163 Total loss: 0.77237 timestamp: 1655067680.6182966 iteration: 75565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13252 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.2098 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.15435 RPN box loss: 0.01865 RPN score loss: 0.00124 RPN total loss: 0.0199 Total loss: 0.94805 timestamp: 1655067683.844015 iteration: 75570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06157 FastRCNN class loss: 0.06359 FastRCNN total loss: 0.12516 L1 loss: 0.0000e+00 L2 loss: 0.56401 Learning rate: 0.0004 Mask loss: 0.13781 RPN box loss: 0.02073 RPN score loss: 0.00947 RPN total loss: 0.0302 Total loss: 0.85717 timestamp: 1655067687.1168923 iteration: 75575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11149 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.20237 L1 loss: 0.0000e+00 L2 loss: 0.564 Learning rate: 0.0004 Mask loss: 0.11106 RPN box loss: 0.01054 RPN score loss: 0.00581 RPN total loss: 0.01636 Total loss: 0.8938 timestamp: 1655067690.3660553 iteration: 75580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08175 FastRCNN class loss: 0.08853 FastRCNN total loss: 0.17028 L1 loss: 0.0000e+00 L2 loss: 0.564 Learning rate: 0.0004 Mask loss: 0.12039 RPN box loss: 0.02125 RPN score loss: 0.00431 RPN total loss: 0.02555 Total loss: 0.88022 timestamp: 1655067693.6602607 iteration: 75585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08485 FastRCNN class loss: 0.0599 FastRCNN total loss: 0.14475 L1 loss: 0.0000e+00 L2 loss: 0.564 Learning rate: 0.0004 Mask loss: 0.09117 RPN box loss: 0.00522 RPN score loss: 0.00284 RPN total loss: 0.00805 Total loss: 0.80797 timestamp: 1655067696.8977382 iteration: 75590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08585 FastRCNN class loss: 0.06857 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 0.564 Learning rate: 0.0004 Mask loss: 0.12434 RPN box loss: 0.01223 RPN score loss: 0.01013 RPN total loss: 0.02236 Total loss: 0.86511 timestamp: 1655067700.173745 iteration: 75595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07665 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.14193 L1 loss: 0.0000e+00 L2 loss: 0.564 Learning rate: 0.0004 Mask loss: 0.16865 RPN box loss: 0.01848 RPN score loss: 0.00874 RPN total loss: 0.02722 Total loss: 0.9018 timestamp: 1655067703.376113 iteration: 75600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.132 FastRCNN class loss: 0.12301 FastRCNN total loss: 0.25501 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.17404 RPN box loss: 0.02339 RPN score loss: 0.00632 RPN total loss: 0.02972 Total loss: 1.02277 timestamp: 1655067706.6542583 iteration: 75605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03126 FastRCNN class loss: 0.03214 FastRCNN total loss: 0.0634 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.10715 RPN box loss: 0.0034 RPN score loss: 0.00167 RPN total loss: 0.00507 Total loss: 0.73961 timestamp: 1655067709.9830823 iteration: 75610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05927 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.11472 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.15427 RPN box loss: 0.01554 RPN score loss: 0.00161 RPN total loss: 0.01716 Total loss: 0.85014 timestamp: 1655067713.219319 iteration: 75615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12631 FastRCNN class loss: 0.05345 FastRCNN total loss: 0.17976 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.16252 RPN box loss: 0.00886 RPN score loss: 0.00609 RPN total loss: 0.01495 Total loss: 0.92121 timestamp: 1655067716.533738 iteration: 75620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10696 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.16566 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.13248 RPN box loss: 0.02391 RPN score loss: 0.00707 RPN total loss: 0.03099 Total loss: 0.89311 timestamp: 1655067719.7979422 iteration: 75625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12233 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.19121 L1 loss: 0.0000e+00 L2 loss: 0.56399 Learning rate: 0.0004 Mask loss: 0.1456 RPN box loss: 0.02038 RPN score loss: 0.00203 RPN total loss: 0.02241 Total loss: 0.9232 timestamp: 1655067723.0439577 iteration: 75630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09109 FastRCNN class loss: 0.08061 FastRCNN total loss: 0.1717 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.16102 RPN box loss: 0.00823 RPN score loss: 0.00581 RPN total loss: 0.01404 Total loss: 0.91074 timestamp: 1655067726.3480256 iteration: 75635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10976 FastRCNN class loss: 0.06506 FastRCNN total loss: 0.17482 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.16239 RPN box loss: 0.01004 RPN score loss: 0.00346 RPN total loss: 0.0135 Total loss: 0.91469 timestamp: 1655067729.6899316 iteration: 75640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05883 FastRCNN class loss: 0.04865 FastRCNN total loss: 0.10747 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.08729 RPN box loss: 0.00244 RPN score loss: 0.00432 RPN total loss: 0.00677 Total loss: 0.7655 timestamp: 1655067733.0056434 iteration: 75645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07424 FastRCNN class loss: 0.03145 FastRCNN total loss: 0.10569 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.12927 RPN box loss: 0.00651 RPN score loss: 0.00268 RPN total loss: 0.00919 Total loss: 0.80813 timestamp: 1655067736.269727 iteration: 75650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06267 FastRCNN class loss: 0.03946 FastRCNN total loss: 0.10213 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.16617 RPN box loss: 0.01003 RPN score loss: 0.00469 RPN total loss: 0.01473 Total loss: 0.847 timestamp: 1655067739.4863605 iteration: 75655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11999 FastRCNN class loss: 0.0879 FastRCNN total loss: 0.2079 L1 loss: 0.0000e+00 L2 loss: 0.56398 Learning rate: 0.0004 Mask loss: 0.18218 RPN box loss: 0.01106 RPN score loss: 0.00563 RPN total loss: 0.01669 Total loss: 0.97075 timestamp: 1655067742.749844 iteration: 75660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11777 FastRCNN class loss: 0.08354 FastRCNN total loss: 0.20131 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.13522 RPN box loss: 0.0166 RPN score loss: 0.00332 RPN total loss: 0.01992 Total loss: 0.92042 timestamp: 1655067746.0345836 iteration: 75665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07793 FastRCNN class loss: 0.07587 FastRCNN total loss: 0.1538 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.14951 RPN box loss: 0.03259 RPN score loss: 0.02087 RPN total loss: 0.05346 Total loss: 0.92075 timestamp: 1655067749.2996051 iteration: 75670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05245 FastRCNN class loss: 0.03725 FastRCNN total loss: 0.0897 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.09383 RPN box loss: 0.03955 RPN score loss: 0.00159 RPN total loss: 0.04114 Total loss: 0.78865 timestamp: 1655067752.5482886 iteration: 75675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04411 FastRCNN class loss: 0.06725 FastRCNN total loss: 0.11136 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.1601 RPN box loss: 0.00468 RPN score loss: 0.00324 RPN total loss: 0.00792 Total loss: 0.84335 timestamp: 1655067755.8233445 iteration: 75680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15768 FastRCNN class loss: 0.12077 FastRCNN total loss: 0.27845 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.18352 RPN box loss: 0.01538 RPN score loss: 0.00684 RPN total loss: 0.02222 Total loss: 1.04816 timestamp: 1655067759.08904 iteration: 75685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12384 FastRCNN class loss: 0.08649 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.14598 RPN box loss: 0.01437 RPN score loss: 0.0028 RPN total loss: 0.01717 Total loss: 0.93744 timestamp: 1655067762.3114598 iteration: 75690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.07995 FastRCNN total loss: 0.16234 L1 loss: 0.0000e+00 L2 loss: 0.56397 Learning rate: 0.0004 Mask loss: 0.12136 RPN box loss: 0.00778 RPN score loss: 0.0089 RPN total loss: 0.01668 Total loss: 0.86435 timestamp: 1655067765.6158903 iteration: 75695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07676 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.13672 L1 loss: 0.0000e+00 L2 loss: 0.56396 Learning rate: 0.0004 Mask loss: 0.12017 RPN box loss: 0.01864 RPN score loss: 0.00922 RPN total loss: 0.02786 Total loss: 0.84871 timestamp: 1655067768.8429732 iteration: 75700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14214 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.23911 L1 loss: 0.0000e+00 L2 loss: 0.56396 Learning rate: 0.0004 Mask loss: 0.12332 RPN box loss: 0.01305 RPN score loss: 0.00855 RPN total loss: 0.0216 Total loss: 0.94799 timestamp: 1655067772.1271074 iteration: 75705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05669 FastRCNN class loss: 0.05121 FastRCNN total loss: 0.1079 L1 loss: 0.0000e+00 L2 loss: 0.56396 Learning rate: 0.0004 Mask loss: 0.15179 RPN box loss: 0.00456 RPN score loss: 0.00408 RPN total loss: 0.00864 Total loss: 0.8323 timestamp: 1655067775.4279075 iteration: 75710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10175 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.18111 L1 loss: 0.0000e+00 L2 loss: 0.56396 Learning rate: 0.0004 Mask loss: 0.21345 RPN box loss: 0.01852 RPN score loss: 0.01025 RPN total loss: 0.02877 Total loss: 0.98729 timestamp: 1655067778.775009 iteration: 75715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07225 FastRCNN class loss: 0.07138 FastRCNN total loss: 0.14364 L1 loss: 0.0000e+00 L2 loss: 0.56396 Learning rate: 0.0004 Mask loss: 0.15553 RPN box loss: 0.01769 RPN score loss: 0.00791 RPN total loss: 0.0256 Total loss: 0.88872 timestamp: 1655067782.0933197 iteration: 75720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06675 FastRCNN class loss: 0.03867 FastRCNN total loss: 0.10542 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.10343 RPN box loss: 0.00916 RPN score loss: 0.00193 RPN total loss: 0.0111 Total loss: 0.7839 timestamp: 1655067785.4132636 iteration: 75725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06414 FastRCNN class loss: 0.04372 FastRCNN total loss: 0.10786 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.12261 RPN box loss: 0.01281 RPN score loss: 0.00412 RPN total loss: 0.01693 Total loss: 0.81136 timestamp: 1655067788.6403062 iteration: 75730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08901 FastRCNN class loss: 0.08113 FastRCNN total loss: 0.17014 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.12132 RPN box loss: 0.01489 RPN score loss: 0.00258 RPN total loss: 0.01747 Total loss: 0.87288 timestamp: 1655067791.9233067 iteration: 75735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06158 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.10821 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.12911 RPN box loss: 0.03837 RPN score loss: 0.00149 RPN total loss: 0.03987 Total loss: 0.84113 timestamp: 1655067795.2069879 iteration: 75740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0751 FastRCNN class loss: 0.06504 FastRCNN total loss: 0.14014 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.14072 RPN box loss: 0.03404 RPN score loss: 0.01611 RPN total loss: 0.05015 Total loss: 0.89496 timestamp: 1655067798.4844892 iteration: 75745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08948 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.14004 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.15377 RPN box loss: 0.00756 RPN score loss: 0.00327 RPN total loss: 0.01083 Total loss: 0.86859 timestamp: 1655067801.8673213 iteration: 75750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05456 FastRCNN class loss: 0.06938 FastRCNN total loss: 0.12394 L1 loss: 0.0000e+00 L2 loss: 0.56395 Learning rate: 0.0004 Mask loss: 0.14612 RPN box loss: 0.01048 RPN score loss: 0.00598 RPN total loss: 0.01646 Total loss: 0.85046 timestamp: 1655067805.2232451 iteration: 75755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06919 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.14296 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.11552 RPN box loss: 0.0167 RPN score loss: 0.0047 RPN total loss: 0.0214 Total loss: 0.84382 timestamp: 1655067808.5432904 iteration: 75760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0854 FastRCNN class loss: 0.05063 FastRCNN total loss: 0.13603 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.16989 RPN box loss: 0.01092 RPN score loss: 0.00775 RPN total loss: 0.01867 Total loss: 0.88853 timestamp: 1655067811.8047438 iteration: 75765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08511 FastRCNN class loss: 0.06543 FastRCNN total loss: 0.15054 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.15547 RPN box loss: 0.0035 RPN score loss: 0.00555 RPN total loss: 0.00905 Total loss: 0.879 timestamp: 1655067815.048107 iteration: 75770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08726 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.17248 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.15596 RPN box loss: 0.04832 RPN score loss: 0.00535 RPN total loss: 0.05366 Total loss: 0.94604 timestamp: 1655067818.282387 iteration: 75775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05683 FastRCNN class loss: 0.04441 FastRCNN total loss: 0.10124 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.14857 RPN box loss: 0.00484 RPN score loss: 0.0072 RPN total loss: 0.01204 Total loss: 0.82578 timestamp: 1655067821.5625832 iteration: 75780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05375 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.11642 L1 loss: 0.0000e+00 L2 loss: 0.56394 Learning rate: 0.0004 Mask loss: 0.11369 RPN box loss: 0.00921 RPN score loss: 0.00147 RPN total loss: 0.01068 Total loss: 0.80473 timestamp: 1655067824.8674366 iteration: 75785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06563 FastRCNN class loss: 0.05501 FastRCNN total loss: 0.12065 L1 loss: 0.0000e+00 L2 loss: 0.56393 Learning rate: 0.0004 Mask loss: 0.13523 RPN box loss: 0.00593 RPN score loss: 0.00356 RPN total loss: 0.0095 Total loss: 0.82931 timestamp: 1655067828.1171439 iteration: 75790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11161 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.17473 L1 loss: 0.0000e+00 L2 loss: 0.56393 Learning rate: 0.0004 Mask loss: 0.14693 RPN box loss: 0.01914 RPN score loss: 0.00862 RPN total loss: 0.02776 Total loss: 0.91335 timestamp: 1655067831.3485296 iteration: 75795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05419 FastRCNN class loss: 0.03687 FastRCNN total loss: 0.09106 L1 loss: 0.0000e+00 L2 loss: 0.56393 Learning rate: 0.0004 Mask loss: 0.12297 RPN box loss: 0.00859 RPN score loss: 0.00093 RPN total loss: 0.00951 Total loss: 0.78747 timestamp: 1655067834.6610212 iteration: 75800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13135 FastRCNN class loss: 0.09015 FastRCNN total loss: 0.2215 L1 loss: 0.0000e+00 L2 loss: 0.56393 Learning rate: 0.0004 Mask loss: 0.16731 RPN box loss: 0.0162 RPN score loss: 0.00763 RPN total loss: 0.02382 Total loss: 0.97656 timestamp: 1655067837.9228811 iteration: 75805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.15763 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.12744 RPN box loss: 0.02274 RPN score loss: 0.01036 RPN total loss: 0.03309 Total loss: 0.88209 timestamp: 1655067841.157122 iteration: 75810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13561 FastRCNN class loss: 0.10014 FastRCNN total loss: 0.23576 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.17211 RPN box loss: 0.02862 RPN score loss: 0.01136 RPN total loss: 0.03998 Total loss: 1.01178 timestamp: 1655067844.4594066 iteration: 75815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08739 FastRCNN class loss: 0.07256 FastRCNN total loss: 0.15995 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.20499 RPN box loss: 0.02004 RPN score loss: 0.00911 RPN total loss: 0.02915 Total loss: 0.95801 timestamp: 1655067847.6869051 iteration: 75820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13904 FastRCNN class loss: 0.07073 FastRCNN total loss: 0.20976 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.14604 RPN box loss: 0.00654 RPN score loss: 0.0038 RPN total loss: 0.01034 Total loss: 0.93006 timestamp: 1655067850.9667656 iteration: 75825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05581 FastRCNN class loss: 0.04556 FastRCNN total loss: 0.10137 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.1386 RPN box loss: 0.00811 RPN score loss: 0.00168 RPN total loss: 0.00979 Total loss: 0.81368 timestamp: 1655067854.206209 iteration: 75830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11959 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.19622 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.14922 RPN box loss: 0.0261 RPN score loss: 0.00429 RPN total loss: 0.03039 Total loss: 0.93975 timestamp: 1655067857.4725926 iteration: 75835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10168 FastRCNN class loss: 0.06477 FastRCNN total loss: 0.16645 L1 loss: 0.0000e+00 L2 loss: 0.56392 Learning rate: 0.0004 Mask loss: 0.13367 RPN box loss: 0.00649 RPN score loss: 0.00655 RPN total loss: 0.01305 Total loss: 0.87708 timestamp: 1655067860.8046927 iteration: 75840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10434 FastRCNN class loss: 0.06836 FastRCNN total loss: 0.1727 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.3267 RPN box loss: 0.03351 RPN score loss: 0.01058 RPN total loss: 0.04409 Total loss: 1.1074 timestamp: 1655067864.0611453 iteration: 75845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07316 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.1394 RPN box loss: 0.02154 RPN score loss: 0.0053 RPN total loss: 0.02685 Total loss: 0.87258 timestamp: 1655067867.333981 iteration: 75850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08888 FastRCNN class loss: 0.1121 FastRCNN total loss: 0.20098 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.15783 RPN box loss: 0.0302 RPN score loss: 0.00731 RPN total loss: 0.03751 Total loss: 0.96023 timestamp: 1655067870.6163983 iteration: 75855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06952 FastRCNN class loss: 0.06304 FastRCNN total loss: 0.13255 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.17198 RPN box loss: 0.012 RPN score loss: 0.01454 RPN total loss: 0.02655 Total loss: 0.89499 timestamp: 1655067873.9035778 iteration: 75860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06072 FastRCNN class loss: 0.04077 FastRCNN total loss: 0.10148 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.08212 RPN box loss: 0.00588 RPN score loss: 0.00184 RPN total loss: 0.00772 Total loss: 0.75523 timestamp: 1655067877.1265101 iteration: 75865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0624 FastRCNN class loss: 0.05713 FastRCNN total loss: 0.11953 L1 loss: 0.0000e+00 L2 loss: 0.56391 Learning rate: 0.0004 Mask loss: 0.0933 RPN box loss: 0.00441 RPN score loss: 0.00302 RPN total loss: 0.00744 Total loss: 0.78417 timestamp: 1655067880.47648 iteration: 75870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08962 FastRCNN class loss: 0.09664 FastRCNN total loss: 0.18625 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.09613 RPN box loss: 0.00605 RPN score loss: 0.00253 RPN total loss: 0.00858 Total loss: 0.85487 timestamp: 1655067883.7358308 iteration: 75875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05093 FastRCNN class loss: 0.03888 FastRCNN total loss: 0.08981 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.13034 RPN box loss: 0.00605 RPN score loss: 0.01194 RPN total loss: 0.01799 Total loss: 0.80204 timestamp: 1655067886.9808085 iteration: 75880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08701 FastRCNN class loss: 0.06433 FastRCNN total loss: 0.15134 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.13265 RPN box loss: 0.02056 RPN score loss: 0.00225 RPN total loss: 0.02281 Total loss: 0.8707 timestamp: 1655067890.286367 iteration: 75885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09748 FastRCNN class loss: 0.06919 FastRCNN total loss: 0.16668 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.19189 RPN box loss: 0.01143 RPN score loss: 0.01723 RPN total loss: 0.02866 Total loss: 0.95112 timestamp: 1655067893.5349681 iteration: 75890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10344 FastRCNN class loss: 0.11127 FastRCNN total loss: 0.21471 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.13323 RPN box loss: 0.02159 RPN score loss: 0.00524 RPN total loss: 0.02682 Total loss: 0.93866 timestamp: 1655067896.8489802 iteration: 75895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10681 FastRCNN class loss: 0.06212 FastRCNN total loss: 0.16893 L1 loss: 0.0000e+00 L2 loss: 0.5639 Learning rate: 0.0004 Mask loss: 0.11119 RPN box loss: 0.01318 RPN score loss: 0.00284 RPN total loss: 0.01602 Total loss: 0.86004 timestamp: 1655067900.1438189 iteration: 75900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09454 FastRCNN class loss: 0.06461 FastRCNN total loss: 0.15915 L1 loss: 0.0000e+00 L2 loss: 0.56389 Learning rate: 0.0004 Mask loss: 0.12868 RPN box loss: 0.01065 RPN score loss: 0.00207 RPN total loss: 0.01272 Total loss: 0.86444 timestamp: 1655067903.4864879 iteration: 75905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09568 FastRCNN class loss: 0.07463 FastRCNN total loss: 0.17031 L1 loss: 0.0000e+00 L2 loss: 0.56389 Learning rate: 0.0004 Mask loss: 0.20666 RPN box loss: 0.02843 RPN score loss: 0.00807 RPN total loss: 0.0365 Total loss: 0.97736 timestamp: 1655067906.7956648 iteration: 75910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16377 FastRCNN class loss: 0.10089 FastRCNN total loss: 0.26466 L1 loss: 0.0000e+00 L2 loss: 0.56389 Learning rate: 0.0004 Mask loss: 0.1625 RPN box loss: 0.0093 RPN score loss: 0.00465 RPN total loss: 0.01395 Total loss: 1.005 timestamp: 1655067909.9939063 iteration: 75915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09708 FastRCNN class loss: 0.07837 FastRCNN total loss: 0.17545 L1 loss: 0.0000e+00 L2 loss: 0.56389 Learning rate: 0.0004 Mask loss: 0.13472 RPN box loss: 0.01299 RPN score loss: 0.0026 RPN total loss: 0.01558 Total loss: 0.88965 timestamp: 1655067913.337824 iteration: 75920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07909 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.1458 L1 loss: 0.0000e+00 L2 loss: 0.56389 Learning rate: 0.0004 Mask loss: 0.13922 RPN box loss: 0.01134 RPN score loss: 0.00896 RPN total loss: 0.0203 Total loss: 0.86921 timestamp: 1655067916.6171231 iteration: 75925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07681 FastRCNN class loss: 0.0866 FastRCNN total loss: 0.1634 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.12984 RPN box loss: 0.02713 RPN score loss: 0.01306 RPN total loss: 0.0402 Total loss: 0.89732 timestamp: 1655067919.923726 iteration: 75930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.09995 FastRCNN total loss: 0.21991 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.18698 RPN box loss: 0.00767 RPN score loss: 0.00265 RPN total loss: 0.01032 Total loss: 0.98109 timestamp: 1655067923.1304626 iteration: 75935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09286 FastRCNN class loss: 0.04709 FastRCNN total loss: 0.13995 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.12486 RPN box loss: 0.0134 RPN score loss: 0.00668 RPN total loss: 0.02009 Total loss: 0.84878 timestamp: 1655067926.4719803 iteration: 75940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05273 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.11667 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.16888 RPN box loss: 0.01784 RPN score loss: 0.00925 RPN total loss: 0.02709 Total loss: 0.87652 timestamp: 1655067929.8027687 iteration: 75945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08918 FastRCNN class loss: 0.09601 FastRCNN total loss: 0.18519 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.16516 RPN box loss: 0.02252 RPN score loss: 0.02157 RPN total loss: 0.04409 Total loss: 0.95832 timestamp: 1655067933.0855634 iteration: 75950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10791 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.17086 L1 loss: 0.0000e+00 L2 loss: 0.56388 Learning rate: 0.0004 Mask loss: 0.14172 RPN box loss: 0.01455 RPN score loss: 0.0043 RPN total loss: 0.01885 Total loss: 0.89531 timestamp: 1655067936.2880332 iteration: 75955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13285 FastRCNN class loss: 0.07972 FastRCNN total loss: 0.21257 L1 loss: 0.0000e+00 L2 loss: 0.56387 Learning rate: 0.0004 Mask loss: 0.14062 RPN box loss: 0.01178 RPN score loss: 0.00345 RPN total loss: 0.01523 Total loss: 0.93229 timestamp: 1655067939.588137 iteration: 75960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11853 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.18019 L1 loss: 0.0000e+00 L2 loss: 0.56387 Learning rate: 0.0004 Mask loss: 0.12398 RPN box loss: 0.00901 RPN score loss: 0.00313 RPN total loss: 0.01213 Total loss: 0.88017 timestamp: 1655067942.827917 iteration: 75965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13705 FastRCNN class loss: 0.09706 FastRCNN total loss: 0.23411 L1 loss: 0.0000e+00 L2 loss: 0.56387 Learning rate: 0.0004 Mask loss: 0.17217 RPN box loss: 0.01409 RPN score loss: 0.00848 RPN total loss: 0.02257 Total loss: 0.99272 timestamp: 1655067946.101042 iteration: 75970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08549 FastRCNN class loss: 0.03982 FastRCNN total loss: 0.1253 L1 loss: 0.0000e+00 L2 loss: 0.56387 Learning rate: 0.0004 Mask loss: 0.11253 RPN box loss: 0.00604 RPN score loss: 0.00105 RPN total loss: 0.0071 Total loss: 0.8088 timestamp: 1655067949.405497 iteration: 75975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12279 FastRCNN class loss: 0.0895 FastRCNN total loss: 0.2123 L1 loss: 0.0000e+00 L2 loss: 0.56387 Learning rate: 0.0004 Mask loss: 0.19791 RPN box loss: 0.00809 RPN score loss: 0.00388 RPN total loss: 0.01198 Total loss: 0.98605 timestamp: 1655067952.6158576 iteration: 75980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0692 FastRCNN class loss: 0.06034 FastRCNN total loss: 0.12954 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.17375 RPN box loss: 0.00917 RPN score loss: 0.00238 RPN total loss: 0.01155 Total loss: 0.8787 timestamp: 1655067955.8632538 iteration: 75985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09465 FastRCNN class loss: 0.07059 FastRCNN total loss: 0.16524 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.19191 RPN box loss: 0.00849 RPN score loss: 0.00193 RPN total loss: 0.01042 Total loss: 0.93144 timestamp: 1655067959.1270766 iteration: 75990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10623 FastRCNN class loss: 0.08751 FastRCNN total loss: 0.19374 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.12467 RPN box loss: 0.01968 RPN score loss: 0.00561 RPN total loss: 0.02529 Total loss: 0.90756 timestamp: 1655067962.3741207 iteration: 75995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0339 FastRCNN class loss: 0.02543 FastRCNN total loss: 0.05932 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.11097 RPN box loss: 0.00109 RPN score loss: 0.00181 RPN total loss: 0.00291 Total loss: 0.73706 timestamp: 1655067965.628303 iteration: 76000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06456 FastRCNN class loss: 0.04597 FastRCNN total loss: 0.11053 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.17134 RPN box loss: 0.00792 RPN score loss: 0.00118 RPN total loss: 0.0091 Total loss: 0.85483 timestamp: 1655067968.9765215 iteration: 76005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11451 FastRCNN class loss: 0.05081 FastRCNN total loss: 0.16532 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.10542 RPN box loss: 0.01435 RPN score loss: 0.00368 RPN total loss: 0.01803 Total loss: 0.85262 timestamp: 1655067972.2123504 iteration: 76010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07933 FastRCNN class loss: 0.09503 FastRCNN total loss: 0.17436 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.16651 RPN box loss: 0.01647 RPN score loss: 0.00565 RPN total loss: 0.02213 Total loss: 0.92685 timestamp: 1655067975.5660002 iteration: 76015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11229 FastRCNN class loss: 0.08805 FastRCNN total loss: 0.20034 L1 loss: 0.0000e+00 L2 loss: 0.56386 Learning rate: 0.0004 Mask loss: 0.13984 RPN box loss: 0.00737 RPN score loss: 0.00926 RPN total loss: 0.01662 Total loss: 0.92066 timestamp: 1655067978.828944 iteration: 76020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16024 FastRCNN class loss: 0.05838 FastRCNN total loss: 0.21862 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.15906 RPN box loss: 0.01709 RPN score loss: 0.00277 RPN total loss: 0.01986 Total loss: 0.9614 timestamp: 1655067982.087844 iteration: 76025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17396 FastRCNN class loss: 0.07265 FastRCNN total loss: 0.24661 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.12652 RPN box loss: 0.0119 RPN score loss: 0.00228 RPN total loss: 0.01419 Total loss: 0.95118 timestamp: 1655067985.4210615 iteration: 76030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05339 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.11885 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.29156 RPN box loss: 0.02409 RPN score loss: 0.00229 RPN total loss: 0.02638 Total loss: 1.00065 timestamp: 1655067988.7225196 iteration: 76035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07184 FastRCNN class loss: 0.09587 FastRCNN total loss: 0.16771 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.15028 RPN box loss: 0.01716 RPN score loss: 0.01089 RPN total loss: 0.02805 Total loss: 0.90989 timestamp: 1655067991.9343574 iteration: 76040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11363 FastRCNN class loss: 0.08984 FastRCNN total loss: 0.20348 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.1386 RPN box loss: 0.00909 RPN score loss: 0.00358 RPN total loss: 0.01266 Total loss: 0.91858 timestamp: 1655067995.136836 iteration: 76045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11756 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.2004 L1 loss: 0.0000e+00 L2 loss: 0.56385 Learning rate: 0.0004 Mask loss: 0.22121 RPN box loss: 0.02129 RPN score loss: 0.00597 RPN total loss: 0.02727 Total loss: 1.01273 timestamp: 1655067998.4515333 iteration: 76050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10641 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.16809 L1 loss: 0.0000e+00 L2 loss: 0.56384 Learning rate: 0.0004 Mask loss: 0.1471 RPN box loss: 0.04194 RPN score loss: 0.00426 RPN total loss: 0.0462 Total loss: 0.92523 timestamp: 1655068001.7317462 iteration: 76055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05468 FastRCNN class loss: 0.0401 FastRCNN total loss: 0.09478 L1 loss: 0.0000e+00 L2 loss: 0.56384 Learning rate: 0.0004 Mask loss: 0.09016 RPN box loss: 0.04666 RPN score loss: 0.00327 RPN total loss: 0.04993 Total loss: 0.79871 timestamp: 1655068005.0349407 iteration: 76060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12439 FastRCNN class loss: 0.07464 FastRCNN total loss: 0.19904 L1 loss: 0.0000e+00 L2 loss: 0.56384 Learning rate: 0.0004 Mask loss: 0.15493 RPN box loss: 0.02344 RPN score loss: 0.00594 RPN total loss: 0.02938 Total loss: 0.94719 timestamp: 1655068008.2972705 iteration: 76065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05956 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.12196 L1 loss: 0.0000e+00 L2 loss: 0.56384 Learning rate: 0.0004 Mask loss: 0.12557 RPN box loss: 0.01073 RPN score loss: 0.00282 RPN total loss: 0.01355 Total loss: 0.82492 timestamp: 1655068011.5206845 iteration: 76070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14742 FastRCNN class loss: 0.12471 FastRCNN total loss: 0.27213 L1 loss: 0.0000e+00 L2 loss: 0.56384 Learning rate: 0.0004 Mask loss: 0.13667 RPN box loss: 0.01758 RPN score loss: 0.00774 RPN total loss: 0.02533 Total loss: 0.99797 timestamp: 1655068014.8224013 iteration: 76075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10166 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.16293 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.12822 RPN box loss: 0.00611 RPN score loss: 0.00345 RPN total loss: 0.00956 Total loss: 0.86454 timestamp: 1655068018.0872266 iteration: 76080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07888 FastRCNN class loss: 0.05045 FastRCNN total loss: 0.12933 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.10899 RPN box loss: 0.00836 RPN score loss: 0.00339 RPN total loss: 0.01175 Total loss: 0.81391 timestamp: 1655068021.3914468 iteration: 76085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06251 FastRCNN class loss: 0.04718 FastRCNN total loss: 0.10968 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.10756 RPN box loss: 0.02753 RPN score loss: 0.00719 RPN total loss: 0.03472 Total loss: 0.81579 timestamp: 1655068024.6780534 iteration: 76090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.04824 FastRCNN total loss: 0.13496 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.13467 RPN box loss: 0.01185 RPN score loss: 0.00221 RPN total loss: 0.01406 Total loss: 0.84752 timestamp: 1655068027.9525223 iteration: 76095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10832 FastRCNN class loss: 0.08094 FastRCNN total loss: 0.18926 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.19017 RPN box loss: 0.00882 RPN score loss: 0.00389 RPN total loss: 0.01271 Total loss: 0.95598 timestamp: 1655068031.2628887 iteration: 76100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10255 FastRCNN class loss: 0.07415 FastRCNN total loss: 0.1767 L1 loss: 0.0000e+00 L2 loss: 0.56383 Learning rate: 0.0004 Mask loss: 0.15397 RPN box loss: 0.01326 RPN score loss: 0.00431 RPN total loss: 0.01757 Total loss: 0.91207 timestamp: 1655068034.4643831 iteration: 76105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10367 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.16905 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.18242 RPN box loss: 0.00929 RPN score loss: 0.00457 RPN total loss: 0.01386 Total loss: 0.92916 timestamp: 1655068037.7022114 iteration: 76110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.04358 FastRCNN total loss: 0.1337 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.07801 RPN box loss: 0.00543 RPN score loss: 0.00423 RPN total loss: 0.00966 Total loss: 0.78519 timestamp: 1655068040.9914503 iteration: 76115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05861 FastRCNN class loss: 0.06307 FastRCNN total loss: 0.12168 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.14206 RPN box loss: 0.01946 RPN score loss: 0.00691 RPN total loss: 0.02637 Total loss: 0.85393 timestamp: 1655068044.2783704 iteration: 76120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10567 FastRCNN class loss: 0.10036 FastRCNN total loss: 0.20604 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.14043 RPN box loss: 0.01226 RPN score loss: 0.00568 RPN total loss: 0.01794 Total loss: 0.92823 timestamp: 1655068047.5378857 iteration: 76125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09901 FastRCNN class loss: 0.08519 FastRCNN total loss: 0.1842 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.124 RPN box loss: 0.01159 RPN score loss: 0.00476 RPN total loss: 0.01635 Total loss: 0.88837 timestamp: 1655068050.7995062 iteration: 76130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13868 FastRCNN class loss: 0.07663 FastRCNN total loss: 0.21531 L1 loss: 0.0000e+00 L2 loss: 0.56382 Learning rate: 0.0004 Mask loss: 0.13398 RPN box loss: 0.03597 RPN score loss: 0.00665 RPN total loss: 0.04262 Total loss: 0.95573 timestamp: 1655068054.051067 iteration: 76135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06485 FastRCNN class loss: 0.05921 FastRCNN total loss: 0.12406 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.12819 RPN box loss: 0.01145 RPN score loss: 0.00398 RPN total loss: 0.01542 Total loss: 0.83149 timestamp: 1655068057.3127863 iteration: 76140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08129 FastRCNN class loss: 0.05354 FastRCNN total loss: 0.13483 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.0924 RPN box loss: 0.00782 RPN score loss: 0.00182 RPN total loss: 0.00964 Total loss: 0.80068 timestamp: 1655068060.6111658 iteration: 76145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11804 FastRCNN class loss: 0.06978 FastRCNN total loss: 0.18782 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.13057 RPN box loss: 0.00739 RPN score loss: 0.00492 RPN total loss: 0.01231 Total loss: 0.89451 timestamp: 1655068063.9320407 iteration: 76150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05214 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.12269 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.11112 RPN box loss: 0.01392 RPN score loss: 0.00518 RPN total loss: 0.01909 Total loss: 0.81671 timestamp: 1655068067.2488537 iteration: 76155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07035 FastRCNN class loss: 0.07113 FastRCNN total loss: 0.14149 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.12437 RPN box loss: 0.01346 RPN score loss: 0.00318 RPN total loss: 0.01665 Total loss: 0.84632 timestamp: 1655068070.5085356 iteration: 76160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09127 FastRCNN class loss: 0.05299 FastRCNN total loss: 0.14425 L1 loss: 0.0000e+00 L2 loss: 0.56381 Learning rate: 0.0004 Mask loss: 0.0987 RPN box loss: 0.00646 RPN score loss: 0.00288 RPN total loss: 0.00934 Total loss: 0.8161 timestamp: 1655068073.8227687 iteration: 76165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08064 FastRCNN class loss: 0.06588 FastRCNN total loss: 0.14652 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.1556 RPN box loss: 0.02492 RPN score loss: 0.0109 RPN total loss: 0.03582 Total loss: 0.90174 timestamp: 1655068077.0391655 iteration: 76170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11743 FastRCNN class loss: 0.11463 FastRCNN total loss: 0.23205 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.12205 RPN box loss: 0.01761 RPN score loss: 0.02182 RPN total loss: 0.03943 Total loss: 0.95733 timestamp: 1655068080.3193462 iteration: 76175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13779 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.21948 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.22715 RPN box loss: 0.01482 RPN score loss: 0.00586 RPN total loss: 0.02068 Total loss: 1.03111 timestamp: 1655068083.605592 iteration: 76180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08586 FastRCNN class loss: 0.05663 FastRCNN total loss: 0.14249 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.10176 RPN box loss: 0.00532 RPN score loss: 0.00505 RPN total loss: 0.01037 Total loss: 0.81842 timestamp: 1655068086.8930538 iteration: 76185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11778 FastRCNN class loss: 0.11917 FastRCNN total loss: 0.23695 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.19107 RPN box loss: 0.02936 RPN score loss: 0.0112 RPN total loss: 0.04056 Total loss: 1.03238 timestamp: 1655068090.248001 iteration: 76190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05884 FastRCNN class loss: 0.05619 FastRCNN total loss: 0.11503 L1 loss: 0.0000e+00 L2 loss: 0.5638 Learning rate: 0.0004 Mask loss: 0.19677 RPN box loss: 0.0119 RPN score loss: 0.00385 RPN total loss: 0.01575 Total loss: 0.89134 timestamp: 1655068093.5357733 iteration: 76195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10812 FastRCNN class loss: 0.0461 FastRCNN total loss: 0.15421 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.12511 RPN box loss: 0.01026 RPN score loss: 0.00488 RPN total loss: 0.01514 Total loss: 0.85825 timestamp: 1655068096.8040638 iteration: 76200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05205 FastRCNN class loss: 0.04323 FastRCNN total loss: 0.09528 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.10489 RPN box loss: 0.01783 RPN score loss: 0.00073 RPN total loss: 0.01855 Total loss: 0.78252 timestamp: 1655068100.0381517 iteration: 76205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09868 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.17539 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.12406 RPN box loss: 0.01034 RPN score loss: 0.00585 RPN total loss: 0.01619 Total loss: 0.87943 timestamp: 1655068103.3337567 iteration: 76210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07096 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.12966 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.15181 RPN box loss: 0.02569 RPN score loss: 0.00444 RPN total loss: 0.03012 Total loss: 0.87538 timestamp: 1655068106.5758743 iteration: 76215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.07095 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.144 RPN box loss: 0.0398 RPN score loss: 0.00502 RPN total loss: 0.04482 Total loss: 0.91569 timestamp: 1655068109.7643416 iteration: 76220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06656 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.14273 L1 loss: 0.0000e+00 L2 loss: 0.56379 Learning rate: 0.0004 Mask loss: 0.16272 RPN box loss: 0.0256 RPN score loss: 0.00474 RPN total loss: 0.03033 Total loss: 0.89956 timestamp: 1655068112.9853148 iteration: 76225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08489 FastRCNN class loss: 0.05939 FastRCNN total loss: 0.14428 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.11701 RPN box loss: 0.02012 RPN score loss: 0.00943 RPN total loss: 0.02954 Total loss: 0.85462 timestamp: 1655068116.206438 iteration: 76230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11296 FastRCNN class loss: 0.08876 FastRCNN total loss: 0.20172 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.15782 RPN box loss: 0.03278 RPN score loss: 0.01284 RPN total loss: 0.04562 Total loss: 0.96894 timestamp: 1655068119.4879293 iteration: 76235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09012 FastRCNN class loss: 0.10835 FastRCNN total loss: 0.19847 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.1513 RPN box loss: 0.01346 RPN score loss: 0.00667 RPN total loss: 0.02013 Total loss: 0.93367 timestamp: 1655068122.7583344 iteration: 76240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.08148 FastRCNN total loss: 0.18673 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.13898 RPN box loss: 0.01567 RPN score loss: 0.01125 RPN total loss: 0.02693 Total loss: 0.91642 timestamp: 1655068125.9784164 iteration: 76245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.03414 FastRCNN total loss: 0.14855 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.10693 RPN box loss: 0.00291 RPN score loss: 0.00353 RPN total loss: 0.00644 Total loss: 0.8257 timestamp: 1655068129.2248645 iteration: 76250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07222 FastRCNN class loss: 0.03607 FastRCNN total loss: 0.10828 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.1366 RPN box loss: 0.01023 RPN score loss: 0.00101 RPN total loss: 0.01124 Total loss: 0.81989 timestamp: 1655068132.577092 iteration: 76255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13505 FastRCNN class loss: 0.03961 FastRCNN total loss: 0.17467 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.09248 RPN box loss: 0.01262 RPN score loss: 0.00642 RPN total loss: 0.01904 Total loss: 0.84997 timestamp: 1655068135.8735678 iteration: 76260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10616 FastRCNN class loss: 0.11258 FastRCNN total loss: 0.21874 L1 loss: 0.0000e+00 L2 loss: 0.56378 Learning rate: 0.0004 Mask loss: 0.15538 RPN box loss: 0.01753 RPN score loss: 0.00392 RPN total loss: 0.02145 Total loss: 0.95934 timestamp: 1655068139.1223834 iteration: 76265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09485 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.17088 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.16324 RPN box loss: 0.01422 RPN score loss: 0.0119 RPN total loss: 0.02613 Total loss: 0.92402 timestamp: 1655068142.4337058 iteration: 76270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10564 FastRCNN class loss: 0.06257 FastRCNN total loss: 0.1682 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.13759 RPN box loss: 0.00882 RPN score loss: 0.00417 RPN total loss: 0.01299 Total loss: 0.88255 timestamp: 1655068145.7158382 iteration: 76275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08295 FastRCNN class loss: 0.07489 FastRCNN total loss: 0.15783 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.11434 RPN box loss: 0.00884 RPN score loss: 0.00161 RPN total loss: 0.01045 Total loss: 0.84639 timestamp: 1655068149.0045977 iteration: 76280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07028 FastRCNN class loss: 0.05318 FastRCNN total loss: 0.12346 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.12634 RPN box loss: 0.00473 RPN score loss: 0.00153 RPN total loss: 0.00626 Total loss: 0.81983 timestamp: 1655068152.2714713 iteration: 76285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11673 FastRCNN class loss: 0.1018 FastRCNN total loss: 0.21853 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.13312 RPN box loss: 0.01004 RPN score loss: 0.00964 RPN total loss: 0.01967 Total loss: 0.93509 timestamp: 1655068155.5663006 iteration: 76290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05788 FastRCNN class loss: 0.04759 FastRCNN total loss: 0.10546 L1 loss: 0.0000e+00 L2 loss: 0.56377 Learning rate: 0.0004 Mask loss: 0.20513 RPN box loss: 0.01993 RPN score loss: 0.00673 RPN total loss: 0.02666 Total loss: 0.90102 timestamp: 1655068158.9010143 iteration: 76295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15231 FastRCNN class loss: 0.08442 FastRCNN total loss: 0.23673 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.15429 RPN box loss: 0.02257 RPN score loss: 0.00454 RPN total loss: 0.02711 Total loss: 0.9819 timestamp: 1655068162.1441455 iteration: 76300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10455 FastRCNN class loss: 0.06438 FastRCNN total loss: 0.16893 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.15918 RPN box loss: 0.02225 RPN score loss: 0.00294 RPN total loss: 0.02519 Total loss: 0.91706 timestamp: 1655068165.3560836 iteration: 76305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13204 FastRCNN class loss: 0.13416 FastRCNN total loss: 0.2662 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.19102 RPN box loss: 0.01069 RPN score loss: 0.01083 RPN total loss: 0.02152 Total loss: 1.0425 timestamp: 1655068168.6648238 iteration: 76310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11588 FastRCNN class loss: 0.08937 FastRCNN total loss: 0.20525 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.2597 RPN box loss: 0.01931 RPN score loss: 0.00673 RPN total loss: 0.02603 Total loss: 1.05475 timestamp: 1655068171.9445283 iteration: 76315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07589 FastRCNN class loss: 0.06149 FastRCNN total loss: 0.13737 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.12765 RPN box loss: 0.00583 RPN score loss: 0.00636 RPN total loss: 0.01219 Total loss: 0.84097 timestamp: 1655068175.2189906 iteration: 76320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10621 FastRCNN class loss: 0.1042 FastRCNN total loss: 0.21041 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.14984 RPN box loss: 0.01587 RPN score loss: 0.00309 RPN total loss: 0.01896 Total loss: 0.94296 timestamp: 1655068178.5464609 iteration: 76325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09295 FastRCNN class loss: 0.0455 FastRCNN total loss: 0.13846 L1 loss: 0.0000e+00 L2 loss: 0.56376 Learning rate: 0.0004 Mask loss: 0.12888 RPN box loss: 0.00588 RPN score loss: 0.00622 RPN total loss: 0.0121 Total loss: 0.84319 timestamp: 1655068181.8232834 iteration: 76330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12172 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.18959 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.15962 RPN box loss: 0.02334 RPN score loss: 0.00233 RPN total loss: 0.02567 Total loss: 0.93864 timestamp: 1655068185.0104294 iteration: 76335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10146 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.18551 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.16854 RPN box loss: 0.03723 RPN score loss: 0.00773 RPN total loss: 0.04496 Total loss: 0.96277 timestamp: 1655068188.261711 iteration: 76340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05263 FastRCNN class loss: 0.04154 FastRCNN total loss: 0.09417 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.12734 RPN box loss: 0.00382 RPN score loss: 0.00421 RPN total loss: 0.00803 Total loss: 0.79329 timestamp: 1655068191.5810843 iteration: 76345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09752 FastRCNN class loss: 0.07603 FastRCNN total loss: 0.17355 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.15884 RPN box loss: 0.01974 RPN score loss: 0.00361 RPN total loss: 0.02335 Total loss: 0.9195 timestamp: 1655068194.8938892 iteration: 76350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05695 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.12241 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.12133 RPN box loss: 0.0225 RPN score loss: 0.00401 RPN total loss: 0.02651 Total loss: 0.834 timestamp: 1655068198.132475 iteration: 76355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11802 FastRCNN class loss: 0.11867 FastRCNN total loss: 0.23669 L1 loss: 0.0000e+00 L2 loss: 0.56375 Learning rate: 0.0004 Mask loss: 0.13986 RPN box loss: 0.02409 RPN score loss: 0.0104 RPN total loss: 0.03449 Total loss: 0.97478 timestamp: 1655068201.4040987 iteration: 76360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14956 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.21529 L1 loss: 0.0000e+00 L2 loss: 0.56374 Learning rate: 0.0004 Mask loss: 0.11602 RPN box loss: 0.00582 RPN score loss: 0.00377 RPN total loss: 0.00959 Total loss: 0.90464 timestamp: 1655068204.7132928 iteration: 76365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09668 FastRCNN class loss: 0.05809 FastRCNN total loss: 0.15478 L1 loss: 0.0000e+00 L2 loss: 0.56374 Learning rate: 0.0004 Mask loss: 0.14899 RPN box loss: 0.01634 RPN score loss: 0.01051 RPN total loss: 0.02684 Total loss: 0.89435 timestamp: 1655068207.9503827 iteration: 76370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0877 FastRCNN class loss: 0.07408 FastRCNN total loss: 0.16178 L1 loss: 0.0000e+00 L2 loss: 0.56374 Learning rate: 0.0004 Mask loss: 0.13642 RPN box loss: 0.00677 RPN score loss: 0.00385 RPN total loss: 0.01062 Total loss: 0.87256 timestamp: 1655068211.169962 iteration: 76375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08216 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.13293 L1 loss: 0.0000e+00 L2 loss: 0.56374 Learning rate: 0.0004 Mask loss: 0.10953 RPN box loss: 0.00459 RPN score loss: 0.00251 RPN total loss: 0.0071 Total loss: 0.8133 timestamp: 1655068214.461388 iteration: 76380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08875 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.14802 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.11706 RPN box loss: 0.01367 RPN score loss: 0.00213 RPN total loss: 0.0158 Total loss: 0.84462 timestamp: 1655068217.7552986 iteration: 76385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05547 FastRCNN class loss: 0.04873 FastRCNN total loss: 0.1042 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.16259 RPN box loss: 0.00757 RPN score loss: 0.003 RPN total loss: 0.01057 Total loss: 0.84109 timestamp: 1655068221.0335596 iteration: 76390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05844 FastRCNN class loss: 0.04732 FastRCNN total loss: 0.10577 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.15295 RPN box loss: 0.00862 RPN score loss: 0.00327 RPN total loss: 0.01189 Total loss: 0.83434 timestamp: 1655068224.3475916 iteration: 76395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06753 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.13547 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.1465 RPN box loss: 0.00865 RPN score loss: 0.00505 RPN total loss: 0.0137 Total loss: 0.8594 timestamp: 1655068227.6369083 iteration: 76400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0714 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.13359 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.15495 RPN box loss: 0.0079 RPN score loss: 0.00242 RPN total loss: 0.01031 Total loss: 0.86258 timestamp: 1655068230.9258063 iteration: 76405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08518 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.16004 L1 loss: 0.0000e+00 L2 loss: 0.56373 Learning rate: 0.0004 Mask loss: 0.14859 RPN box loss: 0.02055 RPN score loss: 0.0104 RPN total loss: 0.03095 Total loss: 0.90331 timestamp: 1655068234.22529 iteration: 76410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07338 FastRCNN class loss: 0.07283 FastRCNN total loss: 0.14621 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.11636 RPN box loss: 0.0131 RPN score loss: 0.00169 RPN total loss: 0.0148 Total loss: 0.84109 timestamp: 1655068237.5949204 iteration: 76415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06751 FastRCNN class loss: 0.07129 FastRCNN total loss: 0.1388 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.18123 RPN box loss: 0.02986 RPN score loss: 0.00526 RPN total loss: 0.03512 Total loss: 0.91888 timestamp: 1655068240.8604062 iteration: 76420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11028 FastRCNN class loss: 0.06536 FastRCNN total loss: 0.17564 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.13215 RPN box loss: 0.01318 RPN score loss: 0.00201 RPN total loss: 0.01519 Total loss: 0.88671 timestamp: 1655068244.09228 iteration: 76425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.08679 FastRCNN total loss: 0.18532 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.18545 RPN box loss: 0.01437 RPN score loss: 0.00228 RPN total loss: 0.01665 Total loss: 0.95114 timestamp: 1655068247.319872 iteration: 76430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09148 FastRCNN class loss: 0.07673 FastRCNN total loss: 0.16821 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.12342 RPN box loss: 0.01016 RPN score loss: 0.00284 RPN total loss: 0.013 Total loss: 0.86835 timestamp: 1655068250.536116 iteration: 76435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.1784 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.17632 RPN box loss: 0.00548 RPN score loss: 0.01288 RPN total loss: 0.01836 Total loss: 0.93679 timestamp: 1655068253.8403664 iteration: 76440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.06772 FastRCNN total loss: 0.1499 L1 loss: 0.0000e+00 L2 loss: 0.56372 Learning rate: 0.0004 Mask loss: 0.14419 RPN box loss: 0.01303 RPN score loss: 0.00274 RPN total loss: 0.01577 Total loss: 0.87357 timestamp: 1655068257.1716018 iteration: 76445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12443 FastRCNN class loss: 0.07762 FastRCNN total loss: 0.20205 L1 loss: 0.0000e+00 L2 loss: 0.56371 Learning rate: 0.0004 Mask loss: 0.16976 RPN box loss: 0.01013 RPN score loss: 0.00249 RPN total loss: 0.01262 Total loss: 0.94814 timestamp: 1655068260.4304826 iteration: 76450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.10105 FastRCNN total loss: 0.20289 L1 loss: 0.0000e+00 L2 loss: 0.56371 Learning rate: 0.0004 Mask loss: 0.20009 RPN box loss: 0.00508 RPN score loss: 0.0041 RPN total loss: 0.00918 Total loss: 0.97587 timestamp: 1655068263.6332986 iteration: 76455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08456 FastRCNN class loss: 0.06512 FastRCNN total loss: 0.14968 L1 loss: 0.0000e+00 L2 loss: 0.56371 Learning rate: 0.0004 Mask loss: 0.16046 RPN box loss: 0.01027 RPN score loss: 0.0028 RPN total loss: 0.01307 Total loss: 0.88693 timestamp: 1655068266.9577522 iteration: 76460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13671 FastRCNN class loss: 0.06865 FastRCNN total loss: 0.20536 L1 loss: 0.0000e+00 L2 loss: 0.56371 Learning rate: 0.0004 Mask loss: 0.136 RPN box loss: 0.01633 RPN score loss: 0.00371 RPN total loss: 0.02004 Total loss: 0.92511 timestamp: 1655068270.2352452 iteration: 76465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15392 FastRCNN class loss: 0.08055 FastRCNN total loss: 0.23447 L1 loss: 0.0000e+00 L2 loss: 0.56371 Learning rate: 0.0004 Mask loss: 0.15855 RPN box loss: 0.01153 RPN score loss: 0.00218 RPN total loss: 0.01372 Total loss: 0.97045 timestamp: 1655068273.5533988 iteration: 76470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08535 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.15503 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.17965 RPN box loss: 0.00709 RPN score loss: 0.00333 RPN total loss: 0.01042 Total loss: 0.90881 timestamp: 1655068276.8230708 iteration: 76475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07622 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.1327 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.11213 RPN box loss: 0.01359 RPN score loss: 0.00672 RPN total loss: 0.02031 Total loss: 0.82885 timestamp: 1655068280.0469913 iteration: 76480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14292 FastRCNN class loss: 0.06529 FastRCNN total loss: 0.20821 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.10531 RPN box loss: 0.00698 RPN score loss: 0.00358 RPN total loss: 0.01056 Total loss: 0.88779 timestamp: 1655068283.261122 iteration: 76485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0785 FastRCNN class loss: 0.05412 FastRCNN total loss: 0.13262 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.14156 RPN box loss: 0.01108 RPN score loss: 0.00337 RPN total loss: 0.01445 Total loss: 0.85233 timestamp: 1655068286.476169 iteration: 76490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14306 FastRCNN class loss: 0.0747 FastRCNN total loss: 0.21777 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.15009 RPN box loss: 0.01451 RPN score loss: 0.01161 RPN total loss: 0.02613 Total loss: 0.95768 timestamp: 1655068289.744417 iteration: 76495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1452 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.22424 L1 loss: 0.0000e+00 L2 loss: 0.5637 Learning rate: 0.0004 Mask loss: 0.14702 RPN box loss: 0.01423 RPN score loss: 0.00327 RPN total loss: 0.0175 Total loss: 0.95245 timestamp: 1655068293.0548434 iteration: 76500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07152 FastRCNN class loss: 0.04725 FastRCNN total loss: 0.11878 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.13756 RPN box loss: 0.01647 RPN score loss: 0.0014 RPN total loss: 0.01786 Total loss: 0.83789 timestamp: 1655068296.3121448 iteration: 76505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06058 FastRCNN class loss: 0.05938 FastRCNN total loss: 0.11996 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.16637 RPN box loss: 0.02098 RPN score loss: 0.00982 RPN total loss: 0.0308 Total loss: 0.88083 timestamp: 1655068299.5397086 iteration: 76510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10548 FastRCNN class loss: 0.0729 FastRCNN total loss: 0.17838 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.11869 RPN box loss: 0.00555 RPN score loss: 0.00771 RPN total loss: 0.01326 Total loss: 0.87402 timestamp: 1655068302.7591763 iteration: 76515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11211 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.17496 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.14679 RPN box loss: 0.00482 RPN score loss: 0.00388 RPN total loss: 0.0087 Total loss: 0.89414 timestamp: 1655068306.0266507 iteration: 76520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.19925 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.12934 RPN box loss: 0.00679 RPN score loss: 0.0064 RPN total loss: 0.01319 Total loss: 0.90546 timestamp: 1655068309.2554333 iteration: 76525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.07385 FastRCNN total loss: 0.16703 L1 loss: 0.0000e+00 L2 loss: 0.56369 Learning rate: 0.0004 Mask loss: 0.16697 RPN box loss: 0.00949 RPN score loss: 0.00477 RPN total loss: 0.01427 Total loss: 0.91196 timestamp: 1655068312.4602718 iteration: 76530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08583 FastRCNN class loss: 0.07297 FastRCNN total loss: 0.1588 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.1147 RPN box loss: 0.0068 RPN score loss: 0.00497 RPN total loss: 0.01178 Total loss: 0.84896 timestamp: 1655068315.7900734 iteration: 76535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09116 FastRCNN class loss: 0.09564 FastRCNN total loss: 0.18679 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.17586 RPN box loss: 0.01529 RPN score loss: 0.00785 RPN total loss: 0.02314 Total loss: 0.94947 timestamp: 1655068319.0221193 iteration: 76540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10374 FastRCNN class loss: 0.07513 FastRCNN total loss: 0.17887 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.17799 RPN box loss: 0.00591 RPN score loss: 0.01034 RPN total loss: 0.01625 Total loss: 0.9368 timestamp: 1655068322.3331332 iteration: 76545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13915 FastRCNN class loss: 0.13596 FastRCNN total loss: 0.27512 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.2253 RPN box loss: 0.03795 RPN score loss: 0.03352 RPN total loss: 0.07146 Total loss: 1.13556 timestamp: 1655068325.577791 iteration: 76550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05515 FastRCNN class loss: 0.04017 FastRCNN total loss: 0.09532 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.11333 RPN box loss: 0.00656 RPN score loss: 0.00379 RPN total loss: 0.01035 Total loss: 0.78268 timestamp: 1655068328.8397987 iteration: 76555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03941 FastRCNN class loss: 0.04874 FastRCNN total loss: 0.08815 L1 loss: 0.0000e+00 L2 loss: 0.56368 Learning rate: 0.0004 Mask loss: 0.12657 RPN box loss: 0.0042 RPN score loss: 0.0011 RPN total loss: 0.0053 Total loss: 0.7837 timestamp: 1655068332.080059 iteration: 76560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07504 FastRCNN class loss: 0.05609 FastRCNN total loss: 0.13113 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.13224 RPN box loss: 0.02008 RPN score loss: 0.0038 RPN total loss: 0.02388 Total loss: 0.85092 timestamp: 1655068335.310978 iteration: 76565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04719 FastRCNN class loss: 0.04033 FastRCNN total loss: 0.08752 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.11827 RPN box loss: 0.01764 RPN score loss: 0.00868 RPN total loss: 0.02632 Total loss: 0.79578 timestamp: 1655068338.6188383 iteration: 76570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04955 FastRCNN class loss: 0.05231 FastRCNN total loss: 0.10186 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.13 RPN box loss: 0.0098 RPN score loss: 0.00265 RPN total loss: 0.01245 Total loss: 0.80799 timestamp: 1655068341.9272788 iteration: 76575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04955 FastRCNN class loss: 0.04029 FastRCNN total loss: 0.08984 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.12293 RPN box loss: 0.01614 RPN score loss: 0.00231 RPN total loss: 0.01845 Total loss: 0.79489 timestamp: 1655068345.1786866 iteration: 76580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0561 FastRCNN class loss: 0.03584 FastRCNN total loss: 0.09194 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.12419 RPN box loss: 0.00594 RPN score loss: 0.00122 RPN total loss: 0.00716 Total loss: 0.78696 timestamp: 1655068348.470133 iteration: 76585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.094 FastRCNN class loss: 0.07723 FastRCNN total loss: 0.17123 L1 loss: 0.0000e+00 L2 loss: 0.56367 Learning rate: 0.0004 Mask loss: 0.12976 RPN box loss: 0.0157 RPN score loss: 0.00576 RPN total loss: 0.02146 Total loss: 0.88612 timestamp: 1655068351.7354445 iteration: 76590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0621 FastRCNN class loss: 0.05168 FastRCNN total loss: 0.11378 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.15464 RPN box loss: 0.00386 RPN score loss: 0.00701 RPN total loss: 0.01087 Total loss: 0.84296 timestamp: 1655068355.0176706 iteration: 76595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12292 FastRCNN class loss: 0.07643 FastRCNN total loss: 0.19935 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.1498 RPN box loss: 0.0115 RPN score loss: 0.01201 RPN total loss: 0.02352 Total loss: 0.93632 timestamp: 1655068358.2960343 iteration: 76600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.20563 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.13618 RPN box loss: 0.02896 RPN score loss: 0.01434 RPN total loss: 0.0433 Total loss: 0.94877 timestamp: 1655068361.539468 iteration: 76605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05191 FastRCNN class loss: 0.04703 FastRCNN total loss: 0.09894 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.12465 RPN box loss: 0.00686 RPN score loss: 0.00423 RPN total loss: 0.01109 Total loss: 0.79834 timestamp: 1655068364.809049 iteration: 76610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14301 FastRCNN class loss: 0.07734 FastRCNN total loss: 0.22035 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.11218 RPN box loss: 0.0161 RPN score loss: 0.00478 RPN total loss: 0.02088 Total loss: 0.91707 timestamp: 1655068368.0465932 iteration: 76615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.09338 FastRCNN total loss: 0.17159 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.16463 RPN box loss: 0.01268 RPN score loss: 0.01016 RPN total loss: 0.02284 Total loss: 0.92272 timestamp: 1655068371.3346436 iteration: 76620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10886 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.16754 L1 loss: 0.0000e+00 L2 loss: 0.56366 Learning rate: 0.0004 Mask loss: 0.11011 RPN box loss: 0.05732 RPN score loss: 0.00553 RPN total loss: 0.06285 Total loss: 0.90416 timestamp: 1655068374.647898 iteration: 76625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09296 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.15741 L1 loss: 0.0000e+00 L2 loss: 0.56365 Learning rate: 0.0004 Mask loss: 0.17814 RPN box loss: 0.01238 RPN score loss: 0.0088 RPN total loss: 0.02118 Total loss: 0.92039 timestamp: 1655068377.949043 iteration: 76630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06852 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.11833 L1 loss: 0.0000e+00 L2 loss: 0.56365 Learning rate: 0.0004 Mask loss: 0.21132 RPN box loss: 0.01469 RPN score loss: 0.00158 RPN total loss: 0.01626 Total loss: 0.90957 timestamp: 1655068381.1864939 iteration: 76635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06267 FastRCNN class loss: 0.04803 FastRCNN total loss: 0.1107 L1 loss: 0.0000e+00 L2 loss: 0.56365 Learning rate: 0.0004 Mask loss: 0.09843 RPN box loss: 0.00757 RPN score loss: 0.0057 RPN total loss: 0.01327 Total loss: 0.78605 timestamp: 1655068384.463465 iteration: 76640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09478 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.1692 L1 loss: 0.0000e+00 L2 loss: 0.56365 Learning rate: 0.0004 Mask loss: 0.16077 RPN box loss: 0.01535 RPN score loss: 0.01424 RPN total loss: 0.02959 Total loss: 0.92321 timestamp: 1655068387.7333126 iteration: 76645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10753 FastRCNN class loss: 0.10854 FastRCNN total loss: 0.21608 L1 loss: 0.0000e+00 L2 loss: 0.56365 Learning rate: 0.0004 Mask loss: 0.17382 RPN box loss: 0.01747 RPN score loss: 0.00772 RPN total loss: 0.02519 Total loss: 0.97873 timestamp: 1655068390.9772193 iteration: 76650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13375 FastRCNN class loss: 0.07806 FastRCNN total loss: 0.21181 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.12957 RPN box loss: 0.02003 RPN score loss: 0.01171 RPN total loss: 0.03174 Total loss: 0.93677 timestamp: 1655068394.2537782 iteration: 76655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07087 FastRCNN class loss: 0.07078 FastRCNN total loss: 0.14165 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.12164 RPN box loss: 0.00938 RPN score loss: 0.00464 RPN total loss: 0.01402 Total loss: 0.84095 timestamp: 1655068397.5044243 iteration: 76660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07502 FastRCNN class loss: 0.05195 FastRCNN total loss: 0.12696 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.10629 RPN box loss: 0.03463 RPN score loss: 0.00185 RPN total loss: 0.03648 Total loss: 0.83338 timestamp: 1655068400.780155 iteration: 76665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06244 FastRCNN class loss: 0.05651 FastRCNN total loss: 0.11894 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.14968 RPN box loss: 0.00601 RPN score loss: 0.00451 RPN total loss: 0.01052 Total loss: 0.84279 timestamp: 1655068404.0631251 iteration: 76670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10583 FastRCNN class loss: 0.07786 FastRCNN total loss: 0.18369 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.15822 RPN box loss: 0.0054 RPN score loss: 0.00208 RPN total loss: 0.00748 Total loss: 0.91302 timestamp: 1655068407.3365982 iteration: 76675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1421 FastRCNN class loss: 0.09574 FastRCNN total loss: 0.23784 L1 loss: 0.0000e+00 L2 loss: 0.56364 Learning rate: 0.0004 Mask loss: 0.15736 RPN box loss: 0.00672 RPN score loss: 0.00244 RPN total loss: 0.00916 Total loss: 0.968 timestamp: 1655068410.6245089 iteration: 76680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0868 FastRCNN class loss: 0.0481 FastRCNN total loss: 0.1349 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.14502 RPN box loss: 0.00545 RPN score loss: 0.00937 RPN total loss: 0.01482 Total loss: 0.85838 timestamp: 1655068413.8687463 iteration: 76685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10457 FastRCNN class loss: 0.08289 FastRCNN total loss: 0.18746 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.16129 RPN box loss: 0.01317 RPN score loss: 0.00509 RPN total loss: 0.01826 Total loss: 0.93064 timestamp: 1655068417.138479 iteration: 76690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12595 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.20963 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.11503 RPN box loss: 0.00721 RPN score loss: 0.00437 RPN total loss: 0.01159 Total loss: 0.89987 timestamp: 1655068420.3944218 iteration: 76695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11154 FastRCNN class loss: 0.077 FastRCNN total loss: 0.18855 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.21777 RPN box loss: 0.02055 RPN score loss: 0.00339 RPN total loss: 0.02394 Total loss: 0.99388 timestamp: 1655068423.6696286 iteration: 76700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.15041 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.16622 RPN box loss: 0.0118 RPN score loss: 0.00098 RPN total loss: 0.01278 Total loss: 0.89304 timestamp: 1655068426.9507854 iteration: 76705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07439 FastRCNN class loss: 0.08506 FastRCNN total loss: 0.15945 L1 loss: 0.0000e+00 L2 loss: 0.56363 Learning rate: 0.0004 Mask loss: 0.10939 RPN box loss: 0.00549 RPN score loss: 0.00173 RPN total loss: 0.00722 Total loss: 0.83969 timestamp: 1655068430.2421098 iteration: 76710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06305 FastRCNN class loss: 0.06875 FastRCNN total loss: 0.1318 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.17107 RPN box loss: 0.07077 RPN score loss: 0.00945 RPN total loss: 0.08022 Total loss: 0.94672 timestamp: 1655068433.5285046 iteration: 76715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.13379 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.14797 RPN box loss: 0.0077 RPN score loss: 0.00296 RPN total loss: 0.01066 Total loss: 0.85605 timestamp: 1655068436.7336843 iteration: 76720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0961 FastRCNN class loss: 0.07929 FastRCNN total loss: 0.17539 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.14414 RPN box loss: 0.02621 RPN score loss: 0.0028 RPN total loss: 0.02901 Total loss: 0.91216 timestamp: 1655068440.0839758 iteration: 76725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09889 FastRCNN class loss: 0.09148 FastRCNN total loss: 0.19036 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.1799 RPN box loss: 0.0108 RPN score loss: 0.00399 RPN total loss: 0.0148 Total loss: 0.94868 timestamp: 1655068443.4097302 iteration: 76730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12655 FastRCNN class loss: 0.09168 FastRCNN total loss: 0.21823 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.2183 RPN box loss: 0.02303 RPN score loss: 0.01214 RPN total loss: 0.03517 Total loss: 1.03532 timestamp: 1655068446.673518 iteration: 76735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08812 FastRCNN class loss: 0.06156 FastRCNN total loss: 0.14968 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.0876 RPN box loss: 0.02402 RPN score loss: 0.00205 RPN total loss: 0.02608 Total loss: 0.82697 timestamp: 1655068449.9453802 iteration: 76740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0882 FastRCNN class loss: 0.08169 FastRCNN total loss: 0.16989 L1 loss: 0.0000e+00 L2 loss: 0.56362 Learning rate: 0.0004 Mask loss: 0.21978 RPN box loss: 0.02909 RPN score loss: 0.00315 RPN total loss: 0.03225 Total loss: 0.98552 timestamp: 1655068453.1773183 iteration: 76745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10377 FastRCNN class loss: 0.04587 FastRCNN total loss: 0.14964 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.0944 RPN box loss: 0.01206 RPN score loss: 0.00211 RPN total loss: 0.01417 Total loss: 0.82182 timestamp: 1655068456.4744663 iteration: 76750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13633 FastRCNN class loss: 0.09443 FastRCNN total loss: 0.23076 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.12578 RPN box loss: 0.00948 RPN score loss: 0.00521 RPN total loss: 0.01469 Total loss: 0.93483 timestamp: 1655068459.7137172 iteration: 76755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08106 FastRCNN class loss: 0.07842 FastRCNN total loss: 0.15948 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.12457 RPN box loss: 0.00943 RPN score loss: 0.00642 RPN total loss: 0.01585 Total loss: 0.86351 timestamp: 1655068463.0188367 iteration: 76760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07222 FastRCNN class loss: 0.0334 FastRCNN total loss: 0.10562 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.10097 RPN box loss: 0.02743 RPN score loss: 0.00123 RPN total loss: 0.02866 Total loss: 0.79887 timestamp: 1655068466.244471 iteration: 76765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08282 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.14521 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.13418 RPN box loss: 0.0135 RPN score loss: 0.00628 RPN total loss: 0.01978 Total loss: 0.86277 timestamp: 1655068469.5218568 iteration: 76770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.09164 FastRCNN total loss: 0.18495 L1 loss: 0.0000e+00 L2 loss: 0.56361 Learning rate: 0.0004 Mask loss: 0.13791 RPN box loss: 0.01748 RPN score loss: 0.00515 RPN total loss: 0.02264 Total loss: 0.90911 timestamp: 1655068472.7508464 iteration: 76775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.09825 FastRCNN total loss: 0.1776 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.14876 RPN box loss: 0.01102 RPN score loss: 0.00367 RPN total loss: 0.01469 Total loss: 0.90466 timestamp: 1655068476.0552325 iteration: 76780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05829 FastRCNN class loss: 0.04719 FastRCNN total loss: 0.10549 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.21732 RPN box loss: 0.00712 RPN score loss: 0.00262 RPN total loss: 0.00975 Total loss: 0.89616 timestamp: 1655068479.3564777 iteration: 76785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.08644 FastRCNN total loss: 0.17415 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.08953 RPN box loss: 0.00893 RPN score loss: 0.00448 RPN total loss: 0.01342 Total loss: 0.84069 timestamp: 1655068482.5843072 iteration: 76790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08001 FastRCNN class loss: 0.04572 FastRCNN total loss: 0.12573 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.13429 RPN box loss: 0.00662 RPN score loss: 0.00468 RPN total loss: 0.01129 Total loss: 0.83491 timestamp: 1655068485.8736007 iteration: 76795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10035 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.18394 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.12292 RPN box loss: 0.01791 RPN score loss: 0.00619 RPN total loss: 0.0241 Total loss: 0.89455 timestamp: 1655068489.1721902 iteration: 76800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07528 FastRCNN class loss: 0.04232 FastRCNN total loss: 0.11759 L1 loss: 0.0000e+00 L2 loss: 0.5636 Learning rate: 0.0004 Mask loss: 0.16686 RPN box loss: 0.01312 RPN score loss: 0.00347 RPN total loss: 0.01659 Total loss: 0.86464 timestamp: 1655068492.5017455 iteration: 76805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07127 FastRCNN class loss: 0.04916 FastRCNN total loss: 0.12043 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.12891 RPN box loss: 0.00634 RPN score loss: 0.00288 RPN total loss: 0.00922 Total loss: 0.82216 timestamp: 1655068495.7286184 iteration: 76810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04345 FastRCNN class loss: 0.04762 FastRCNN total loss: 0.09108 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.15978 RPN box loss: 0.0177 RPN score loss: 0.00103 RPN total loss: 0.01873 Total loss: 0.83318 timestamp: 1655068498.961112 iteration: 76815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.08691 FastRCNN total loss: 0.16608 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.19498 RPN box loss: 0.01725 RPN score loss: 0.00658 RPN total loss: 0.02383 Total loss: 0.94848 timestamp: 1655068502.228362 iteration: 76820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.04445 FastRCNN total loss: 0.13215 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.10064 RPN box loss: 0.00482 RPN score loss: 0.00206 RPN total loss: 0.00688 Total loss: 0.80326 timestamp: 1655068505.5033853 iteration: 76825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11465 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.18215 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.14012 RPN box loss: 0.02687 RPN score loss: 0.0026 RPN total loss: 0.02947 Total loss: 0.91532 timestamp: 1655068508.7305486 iteration: 76830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09171 FastRCNN class loss: 0.07932 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.56359 Learning rate: 0.0004 Mask loss: 0.10756 RPN box loss: 0.01442 RPN score loss: 0.00314 RPN total loss: 0.01756 Total loss: 0.85973 timestamp: 1655068511.969069 iteration: 76835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09814 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.1642 L1 loss: 0.0000e+00 L2 loss: 0.56358 Learning rate: 0.0004 Mask loss: 0.12846 RPN box loss: 0.01584 RPN score loss: 0.00402 RPN total loss: 0.01986 Total loss: 0.87611 timestamp: 1655068515.1919808 iteration: 76840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06605 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.12439 L1 loss: 0.0000e+00 L2 loss: 0.56358 Learning rate: 0.0004 Mask loss: 0.16525 RPN box loss: 0.01096 RPN score loss: 0.00269 RPN total loss: 0.01365 Total loss: 0.86687 timestamp: 1655068518.465735 iteration: 76845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11606 FastRCNN class loss: 0.09116 FastRCNN total loss: 0.20722 L1 loss: 0.0000e+00 L2 loss: 0.56358 Learning rate: 0.0004 Mask loss: 0.14033 RPN box loss: 0.00507 RPN score loss: 0.00194 RPN total loss: 0.00701 Total loss: 0.91814 timestamp: 1655068521.7451882 iteration: 76850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07407 FastRCNN class loss: 0.05203 FastRCNN total loss: 0.1261 L1 loss: 0.0000e+00 L2 loss: 0.56358 Learning rate: 0.0004 Mask loss: 0.12564 RPN box loss: 0.00372 RPN score loss: 0.00334 RPN total loss: 0.00705 Total loss: 0.82237 timestamp: 1655068525.0261998 iteration: 76855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05569 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.10254 L1 loss: 0.0000e+00 L2 loss: 0.56358 Learning rate: 0.0004 Mask loss: 0.23021 RPN box loss: 0.00814 RPN score loss: 0.00159 RPN total loss: 0.00973 Total loss: 0.90605 timestamp: 1655068528.2970116 iteration: 76860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.06441 FastRCNN total loss: 0.15525 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.11251 RPN box loss: 0.02051 RPN score loss: 0.00129 RPN total loss: 0.02181 Total loss: 0.85314 timestamp: 1655068531.6176095 iteration: 76865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13869 FastRCNN class loss: 0.07841 FastRCNN total loss: 0.2171 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.16476 RPN box loss: 0.01224 RPN score loss: 0.00247 RPN total loss: 0.01472 Total loss: 0.96015 timestamp: 1655068534.9581065 iteration: 76870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07691 FastRCNN class loss: 0.04809 FastRCNN total loss: 0.125 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.16277 RPN box loss: 0.01024 RPN score loss: 0.00415 RPN total loss: 0.01439 Total loss: 0.86573 timestamp: 1655068538.229728 iteration: 76875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08087 FastRCNN class loss: 0.0526 FastRCNN total loss: 0.13347 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.11526 RPN box loss: 0.01299 RPN score loss: 0.00168 RPN total loss: 0.01466 Total loss: 0.82696 timestamp: 1655068541.567113 iteration: 76880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10527 FastRCNN class loss: 0.06522 FastRCNN total loss: 0.1705 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.1083 RPN box loss: 0.00972 RPN score loss: 0.00776 RPN total loss: 0.01749 Total loss: 0.85985 timestamp: 1655068544.8037624 iteration: 76885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07021 FastRCNN class loss: 0.04288 FastRCNN total loss: 0.11308 L1 loss: 0.0000e+00 L2 loss: 0.56357 Learning rate: 0.0004 Mask loss: 0.10972 RPN box loss: 0.0058 RPN score loss: 0.00705 RPN total loss: 0.01285 Total loss: 0.79922 timestamp: 1655068548.1001368 iteration: 76890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09374 FastRCNN class loss: 0.05925 FastRCNN total loss: 0.15299 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.10364 RPN box loss: 0.00462 RPN score loss: 0.01032 RPN total loss: 0.01494 Total loss: 0.83513 timestamp: 1655068551.442961 iteration: 76895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08815 FastRCNN class loss: 0.07992 FastRCNN total loss: 0.16807 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.168 RPN box loss: 0.04437 RPN score loss: 0.00628 RPN total loss: 0.05065 Total loss: 0.95029 timestamp: 1655068554.739274 iteration: 76900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08423 FastRCNN class loss: 0.06474 FastRCNN total loss: 0.14897 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.15558 RPN box loss: 0.03676 RPN score loss: 0.01422 RPN total loss: 0.05098 Total loss: 0.91909 timestamp: 1655068558.0329716 iteration: 76905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07903 FastRCNN class loss: 0.06557 FastRCNN total loss: 0.14461 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.10498 RPN box loss: 0.0173 RPN score loss: 0.00207 RPN total loss: 0.01937 Total loss: 0.83252 timestamp: 1655068561.299608 iteration: 76910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09437 FastRCNN class loss: 0.07602 FastRCNN total loss: 0.17039 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.14226 RPN box loss: 0.00904 RPN score loss: 0.00301 RPN total loss: 0.01205 Total loss: 0.88827 timestamp: 1655068564.5475752 iteration: 76915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13466 FastRCNN class loss: 0.11135 FastRCNN total loss: 0.246 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.19183 RPN box loss: 0.01653 RPN score loss: 0.01164 RPN total loss: 0.02817 Total loss: 1.02956 timestamp: 1655068567.8461921 iteration: 76920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05934 FastRCNN class loss: 0.04389 FastRCNN total loss: 0.10323 L1 loss: 0.0000e+00 L2 loss: 0.56356 Learning rate: 0.0004 Mask loss: 0.12633 RPN box loss: 0.00927 RPN score loss: 0.00599 RPN total loss: 0.01527 Total loss: 0.80839 timestamp: 1655068571.1579676 iteration: 76925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09937 FastRCNN class loss: 0.04955 FastRCNN total loss: 0.14892 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.16075 RPN box loss: 0.01317 RPN score loss: 0.00222 RPN total loss: 0.01539 Total loss: 0.88861 timestamp: 1655068574.4668515 iteration: 76930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11007 FastRCNN class loss: 0.08522 FastRCNN total loss: 0.1953 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.1945 RPN box loss: 0.016 RPN score loss: 0.00355 RPN total loss: 0.01955 Total loss: 0.9729 timestamp: 1655068577.8510845 iteration: 76935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09256 FastRCNN class loss: 0.05287 FastRCNN total loss: 0.14542 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.09651 RPN box loss: 0.00695 RPN score loss: 0.0045 RPN total loss: 0.01145 Total loss: 0.81693 timestamp: 1655068581.0717123 iteration: 76940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15802 FastRCNN class loss: 0.08758 FastRCNN total loss: 0.24559 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.17934 RPN box loss: 0.03353 RPN score loss: 0.00532 RPN total loss: 0.03885 Total loss: 1.02734 timestamp: 1655068584.3306365 iteration: 76945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08178 FastRCNN class loss: 0.08062 FastRCNN total loss: 0.1624 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.15724 RPN box loss: 0.02242 RPN score loss: 0.00878 RPN total loss: 0.0312 Total loss: 0.91439 timestamp: 1655068587.6609113 iteration: 76950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10912 FastRCNN class loss: 0.08754 FastRCNN total loss: 0.19666 L1 loss: 0.0000e+00 L2 loss: 0.56355 Learning rate: 0.0004 Mask loss: 0.2018 RPN box loss: 0.00715 RPN score loss: 0.00357 RPN total loss: 0.01072 Total loss: 0.97273 timestamp: 1655068590.9294713 iteration: 76955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06113 FastRCNN class loss: 0.06475 FastRCNN total loss: 0.12588 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.13929 RPN box loss: 0.00611 RPN score loss: 0.01031 RPN total loss: 0.01642 Total loss: 0.84514 timestamp: 1655068594.1633222 iteration: 76960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18189 FastRCNN class loss: 0.06002 FastRCNN total loss: 0.24191 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.11221 RPN box loss: 0.00805 RPN score loss: 0.00344 RPN total loss: 0.01149 Total loss: 0.92916 timestamp: 1655068597.3947172 iteration: 76965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16581 FastRCNN class loss: 0.11263 FastRCNN total loss: 0.27844 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.17329 RPN box loss: 0.01727 RPN score loss: 0.00916 RPN total loss: 0.02643 Total loss: 1.0417 timestamp: 1655068600.6235101 iteration: 76970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12798 FastRCNN class loss: 0.10573 FastRCNN total loss: 0.23371 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.19425 RPN box loss: 0.01096 RPN score loss: 0.00201 RPN total loss: 0.01297 Total loss: 1.00446 timestamp: 1655068603.9304078 iteration: 76975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07742 FastRCNN class loss: 0.05999 FastRCNN total loss: 0.1374 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.15228 RPN box loss: 0.00608 RPN score loss: 0.00784 RPN total loss: 0.01393 Total loss: 0.86715 timestamp: 1655068607.2476416 iteration: 76980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.0653 FastRCNN total loss: 0.16732 L1 loss: 0.0000e+00 L2 loss: 0.56354 Learning rate: 0.0004 Mask loss: 0.14205 RPN box loss: 0.01627 RPN score loss: 0.00823 RPN total loss: 0.0245 Total loss: 0.8974 timestamp: 1655068610.4800951 iteration: 76985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08614 FastRCNN class loss: 0.05902 FastRCNN total loss: 0.14516 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.15055 RPN box loss: 0.01263 RPN score loss: 0.00462 RPN total loss: 0.01725 Total loss: 0.87649 timestamp: 1655068613.7696934 iteration: 76990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07429 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.13424 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.14661 RPN box loss: 0.01333 RPN score loss: 0.00382 RPN total loss: 0.01716 Total loss: 0.86154 timestamp: 1655068617.0574825 iteration: 76995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16037 FastRCNN class loss: 0.05673 FastRCNN total loss: 0.21709 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.13813 RPN box loss: 0.01426 RPN score loss: 0.00241 RPN total loss: 0.01666 Total loss: 0.93542 timestamp: 1655068620.3638313 iteration: 77000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10787 FastRCNN class loss: 0.09486 FastRCNN total loss: 0.20273 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.11524 RPN box loss: 0.01085 RPN score loss: 0.00386 RPN total loss: 0.0147 Total loss: 0.8962 timestamp: 1655068623.6457102 iteration: 77005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05078 FastRCNN class loss: 0.04827 FastRCNN total loss: 0.09905 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.11023 RPN box loss: 0.0255 RPN score loss: 0.00295 RPN total loss: 0.02845 Total loss: 0.80126 timestamp: 1655068626.9623923 iteration: 77010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04698 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.10103 L1 loss: 0.0000e+00 L2 loss: 0.56353 Learning rate: 0.0004 Mask loss: 0.12305 RPN box loss: 0.01864 RPN score loss: 0.00383 RPN total loss: 0.02247 Total loss: 0.81009 timestamp: 1655068630.253933 iteration: 77015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12375 FastRCNN class loss: 0.05396 FastRCNN total loss: 0.17771 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.08926 RPN box loss: 0.02059 RPN score loss: 0.00692 RPN total loss: 0.02751 Total loss: 0.85801 timestamp: 1655068633.5015395 iteration: 77020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07817 FastRCNN class loss: 0.04285 FastRCNN total loss: 0.12102 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.11868 RPN box loss: 0.01295 RPN score loss: 0.00404 RPN total loss: 0.01699 Total loss: 0.82021 timestamp: 1655068636.755475 iteration: 77025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10112 FastRCNN class loss: 0.05329 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.08452 RPN box loss: 0.00807 RPN score loss: 0.00288 RPN total loss: 0.01095 Total loss: 0.8134 timestamp: 1655068640.0261693 iteration: 77030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11491 FastRCNN class loss: 0.08417 FastRCNN total loss: 0.19908 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.13007 RPN box loss: 0.00639 RPN score loss: 0.00153 RPN total loss: 0.00792 Total loss: 0.90059 timestamp: 1655068643.3332086 iteration: 77035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11781 FastRCNN class loss: 0.0953 FastRCNN total loss: 0.21311 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.13343 RPN box loss: 0.01212 RPN score loss: 0.00529 RPN total loss: 0.01741 Total loss: 0.92747 timestamp: 1655068646.558694 iteration: 77040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09156 FastRCNN class loss: 0.05544 FastRCNN total loss: 0.147 L1 loss: 0.0000e+00 L2 loss: 0.56352 Learning rate: 0.0004 Mask loss: 0.1318 RPN box loss: 0.01201 RPN score loss: 0.00401 RPN total loss: 0.01603 Total loss: 0.85833 timestamp: 1655068649.8339732 iteration: 77045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11484 FastRCNN class loss: 0.08721 FastRCNN total loss: 0.20205 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.19959 RPN box loss: 0.00819 RPN score loss: 0.00976 RPN total loss: 0.01795 Total loss: 0.98311 timestamp: 1655068653.1319697 iteration: 77050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09888 FastRCNN class loss: 0.073 FastRCNN total loss: 0.17187 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.14475 RPN box loss: 0.01256 RPN score loss: 0.00391 RPN total loss: 0.01648 Total loss: 0.89661 timestamp: 1655068656.4057014 iteration: 77055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09593 FastRCNN class loss: 0.06814 FastRCNN total loss: 0.16407 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.13481 RPN box loss: 0.0292 RPN score loss: 0.00473 RPN total loss: 0.03393 Total loss: 0.89632 timestamp: 1655068659.6991024 iteration: 77060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08086 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.13365 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.15843 RPN box loss: 0.01004 RPN score loss: 0.00333 RPN total loss: 0.01337 Total loss: 0.86896 timestamp: 1655068662.9979594 iteration: 77065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04002 FastRCNN class loss: 0.0527 FastRCNN total loss: 0.09271 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.15592 RPN box loss: 0.00329 RPN score loss: 0.00848 RPN total loss: 0.01177 Total loss: 0.82391 timestamp: 1655068666.235536 iteration: 77070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08425 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.14834 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.1941 RPN box loss: 0.01283 RPN score loss: 0.00492 RPN total loss: 0.01775 Total loss: 0.92371 timestamp: 1655068669.553446 iteration: 77075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08104 FastRCNN class loss: 0.04897 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 0.56351 Learning rate: 0.0004 Mask loss: 0.21184 RPN box loss: 0.01851 RPN score loss: 0.00522 RPN total loss: 0.02373 Total loss: 0.92909 timestamp: 1655068672.863177 iteration: 77080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.12324 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.18298 RPN box loss: 0.00465 RPN score loss: 0.00419 RPN total loss: 0.00883 Total loss: 0.87856 timestamp: 1655068676.088291 iteration: 77085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12536 FastRCNN class loss: 0.10329 FastRCNN total loss: 0.22865 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.17675 RPN box loss: 0.01113 RPN score loss: 0.00179 RPN total loss: 0.01292 Total loss: 0.98182 timestamp: 1655068679.375854 iteration: 77090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10295 FastRCNN class loss: 0.07507 FastRCNN total loss: 0.17802 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.12366 RPN box loss: 0.01732 RPN score loss: 0.00565 RPN total loss: 0.02297 Total loss: 0.88815 timestamp: 1655068682.607223 iteration: 77095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06166 FastRCNN class loss: 0.05999 FastRCNN total loss: 0.12164 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.12541 RPN box loss: 0.00998 RPN score loss: 0.00842 RPN total loss: 0.0184 Total loss: 0.82896 timestamp: 1655068685.8782768 iteration: 77100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06303 FastRCNN class loss: 0.07755 FastRCNN total loss: 0.14058 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.20255 RPN box loss: 0.01665 RPN score loss: 0.01039 RPN total loss: 0.02704 Total loss: 0.93367 timestamp: 1655068689.1255925 iteration: 77105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05546 FastRCNN class loss: 0.04367 FastRCNN total loss: 0.09914 L1 loss: 0.0000e+00 L2 loss: 0.5635 Learning rate: 0.0004 Mask loss: 0.14214 RPN box loss: 0.00453 RPN score loss: 0.00503 RPN total loss: 0.00956 Total loss: 0.81434 timestamp: 1655068692.3728313 iteration: 77110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.03178 FastRCNN total loss: 0.09869 L1 loss: 0.0000e+00 L2 loss: 0.56349 Learning rate: 0.0004 Mask loss: 0.09433 RPN box loss: 0.00376 RPN score loss: 0.00394 RPN total loss: 0.0077 Total loss: 0.76421 timestamp: 1655068695.6759338 iteration: 77115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11221 FastRCNN class loss: 0.0615 FastRCNN total loss: 0.17372 L1 loss: 0.0000e+00 L2 loss: 0.56349 Learning rate: 0.0004 Mask loss: 0.13162 RPN box loss: 0.01131 RPN score loss: 0.00395 RPN total loss: 0.01526 Total loss: 0.88409 timestamp: 1655068699.0060377 iteration: 77120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11646 FastRCNN class loss: 0.10802 FastRCNN total loss: 0.22448 L1 loss: 0.0000e+00 L2 loss: 0.56349 Learning rate: 0.0004 Mask loss: 0.13614 RPN box loss: 0.01472 RPN score loss: 0.01329 RPN total loss: 0.028 Total loss: 0.95211 timestamp: 1655068702.3083735 iteration: 77125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10361 FastRCNN class loss: 0.0745 FastRCNN total loss: 0.17811 L1 loss: 0.0000e+00 L2 loss: 0.56349 Learning rate: 0.0004 Mask loss: 0.15121 RPN box loss: 0.00796 RPN score loss: 0.00147 RPN total loss: 0.00943 Total loss: 0.90224 timestamp: 1655068705.5823634 iteration: 77130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10485 FastRCNN class loss: 0.05493 FastRCNN total loss: 0.15978 L1 loss: 0.0000e+00 L2 loss: 0.56349 Learning rate: 0.0004 Mask loss: 0.13693 RPN box loss: 0.0092 RPN score loss: 0.00172 RPN total loss: 0.01091 Total loss: 0.87111 timestamp: 1655068708.8320258 iteration: 77135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09769 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.17454 L1 loss: 0.0000e+00 L2 loss: 0.56348 Learning rate: 0.0004 Mask loss: 0.1221 RPN box loss: 0.03519 RPN score loss: 0.00478 RPN total loss: 0.03997 Total loss: 0.9001 timestamp: 1655068712.1677222 iteration: 77140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08209 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.14989 L1 loss: 0.0000e+00 L2 loss: 0.56348 Learning rate: 0.0004 Mask loss: 0.14042 RPN box loss: 0.00786 RPN score loss: 0.00344 RPN total loss: 0.01131 Total loss: 0.8651 timestamp: 1655068715.421241 iteration: 77145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13864 FastRCNN class loss: 0.08714 FastRCNN total loss: 0.22578 L1 loss: 0.0000e+00 L2 loss: 0.56348 Learning rate: 0.0004 Mask loss: 0.20179 RPN box loss: 0.01822 RPN score loss: 0.00492 RPN total loss: 0.02314 Total loss: 1.0142 timestamp: 1655068718.7468638 iteration: 77150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.06918 FastRCNN total loss: 0.16838 L1 loss: 0.0000e+00 L2 loss: 0.56348 Learning rate: 0.0004 Mask loss: 0.14393 RPN box loss: 0.01442 RPN score loss: 0.00123 RPN total loss: 0.01564 Total loss: 0.89143 timestamp: 1655068722.0359492 iteration: 77155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06357 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.12933 L1 loss: 0.0000e+00 L2 loss: 0.56348 Learning rate: 0.0004 Mask loss: 0.11036 RPN box loss: 0.00379 RPN score loss: 0.00598 RPN total loss: 0.00976 Total loss: 0.81293 timestamp: 1655068725.292618 iteration: 77160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11341 FastRCNN class loss: 0.13328 FastRCNN total loss: 0.2467 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.16928 RPN box loss: 0.03166 RPN score loss: 0.01127 RPN total loss: 0.04293 Total loss: 1.02239 timestamp: 1655068728.5669756 iteration: 77165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10128 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.17333 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.14337 RPN box loss: 0.01423 RPN score loss: 0.00409 RPN total loss: 0.01832 Total loss: 0.89849 timestamp: 1655068731.8031216 iteration: 77170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09689 FastRCNN class loss: 0.06095 FastRCNN total loss: 0.15784 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.16335 RPN box loss: 0.00791 RPN score loss: 0.00321 RPN total loss: 0.01112 Total loss: 0.89578 timestamp: 1655068735.0578732 iteration: 77175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13611 FastRCNN class loss: 0.1127 FastRCNN total loss: 0.24881 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.1746 RPN box loss: 0.02377 RPN score loss: 0.00569 RPN total loss: 0.02946 Total loss: 1.01635 timestamp: 1655068738.23805 iteration: 77180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10638 FastRCNN class loss: 0.11473 FastRCNN total loss: 0.22111 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.14312 RPN box loss: 0.02647 RPN score loss: 0.00338 RPN total loss: 0.02985 Total loss: 0.95755 timestamp: 1655068741.5246058 iteration: 77185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0866 FastRCNN class loss: 0.07415 FastRCNN total loss: 0.16075 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.15029 RPN box loss: 0.01195 RPN score loss: 0.00265 RPN total loss: 0.0146 Total loss: 0.88911 timestamp: 1655068744.7885332 iteration: 77190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06504 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.12244 L1 loss: 0.0000e+00 L2 loss: 0.56347 Learning rate: 0.0004 Mask loss: 0.1055 RPN box loss: 0.00523 RPN score loss: 0.00325 RPN total loss: 0.00848 Total loss: 0.79989 timestamp: 1655068748.0727499 iteration: 77195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0932 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.15992 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.1857 RPN box loss: 0.01052 RPN score loss: 0.00505 RPN total loss: 0.01556 Total loss: 0.92465 timestamp: 1655068751.3440619 iteration: 77200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08285 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.16924 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.198 RPN box loss: 0.00705 RPN score loss: 0.00283 RPN total loss: 0.00988 Total loss: 0.94058 timestamp: 1655068754.5938725 iteration: 77205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.12276 FastRCNN total loss: 0.23993 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.10749 RPN box loss: 0.00552 RPN score loss: 0.00297 RPN total loss: 0.00849 Total loss: 0.91938 timestamp: 1655068757.8122475 iteration: 77210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07089 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.1398 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.12406 RPN box loss: 0.02434 RPN score loss: 0.00234 RPN total loss: 0.02668 Total loss: 0.85399 timestamp: 1655068761.0973425 iteration: 77215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14585 FastRCNN class loss: 0.10634 FastRCNN total loss: 0.25219 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.17892 RPN box loss: 0.01475 RPN score loss: 0.01949 RPN total loss: 0.03424 Total loss: 1.0288 timestamp: 1655068764.3762474 iteration: 77220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05818 FastRCNN class loss: 0.06782 FastRCNN total loss: 0.126 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.27561 RPN box loss: 0.01016 RPN score loss: 0.0019 RPN total loss: 0.01206 Total loss: 0.97712 timestamp: 1655068767.6333528 iteration: 77225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10699 FastRCNN class loss: 0.06464 FastRCNN total loss: 0.17163 L1 loss: 0.0000e+00 L2 loss: 0.56346 Learning rate: 0.0004 Mask loss: 0.12825 RPN box loss: 0.01038 RPN score loss: 0.00352 RPN total loss: 0.01389 Total loss: 0.87723 timestamp: 1655068770.8878467 iteration: 77230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07803 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.16539 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.20418 RPN box loss: 0.01119 RPN score loss: 0.00285 RPN total loss: 0.01404 Total loss: 0.94707 timestamp: 1655068774.1947002 iteration: 77235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1405 FastRCNN class loss: 0.07431 FastRCNN total loss: 0.21481 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.10691 RPN box loss: 0.00415 RPN score loss: 0.00359 RPN total loss: 0.00773 Total loss: 0.8929 timestamp: 1655068777.5143895 iteration: 77240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10852 FastRCNN class loss: 0.14785 FastRCNN total loss: 0.25637 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.22652 RPN box loss: 0.0116 RPN score loss: 0.00491 RPN total loss: 0.01651 Total loss: 1.06285 timestamp: 1655068780.769373 iteration: 77245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09514 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.1764 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.13486 RPN box loss: 0.01262 RPN score loss: 0.00683 RPN total loss: 0.01945 Total loss: 0.89416 timestamp: 1655068784.0140595 iteration: 77250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.16308 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.18151 RPN box loss: 0.03895 RPN score loss: 0.00197 RPN total loss: 0.04091 Total loss: 0.94896 timestamp: 1655068787.341959 iteration: 77255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07925 FastRCNN class loss: 0.07459 FastRCNN total loss: 0.15384 L1 loss: 0.0000e+00 L2 loss: 0.56345 Learning rate: 0.0004 Mask loss: 0.13597 RPN box loss: 0.00706 RPN score loss: 0.00506 RPN total loss: 0.01213 Total loss: 0.86539 timestamp: 1655068790.5442603 iteration: 77260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13683 FastRCNN class loss: 0.11457 FastRCNN total loss: 0.2514 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.15537 RPN box loss: 0.0431 RPN score loss: 0.00521 RPN total loss: 0.04831 Total loss: 1.01852 timestamp: 1655068793.7985148 iteration: 77265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09208 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.14617 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.09822 RPN box loss: 0.0116 RPN score loss: 0.00288 RPN total loss: 0.01448 Total loss: 0.82231 timestamp: 1655068797.0887482 iteration: 77270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06242 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.12513 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.15915 RPN box loss: 0.00686 RPN score loss: 0.00574 RPN total loss: 0.0126 Total loss: 0.86031 timestamp: 1655068800.3640728 iteration: 77275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07787 FastRCNN class loss: 0.06886 FastRCNN total loss: 0.14674 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.13193 RPN box loss: 0.00831 RPN score loss: 0.00134 RPN total loss: 0.00965 Total loss: 0.85175 timestamp: 1655068803.6558156 iteration: 77280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09388 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.17629 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.1183 RPN box loss: 0.00978 RPN score loss: 0.00744 RPN total loss: 0.01723 Total loss: 0.87525 timestamp: 1655068806.9412274 iteration: 77285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07849 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.14043 L1 loss: 0.0000e+00 L2 loss: 0.56344 Learning rate: 0.0004 Mask loss: 0.10955 RPN box loss: 0.00879 RPN score loss: 0.00282 RPN total loss: 0.01161 Total loss: 0.82502 timestamp: 1655068810.2224543 iteration: 77290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09958 FastRCNN class loss: 0.05455 FastRCNN total loss: 0.15413 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.1224 RPN box loss: 0.01221 RPN score loss: 0.00602 RPN total loss: 0.01823 Total loss: 0.8582 timestamp: 1655068813.5115247 iteration: 77295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08101 FastRCNN class loss: 0.07321 FastRCNN total loss: 0.15422 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.10635 RPN box loss: 0.01389 RPN score loss: 0.0053 RPN total loss: 0.0192 Total loss: 0.8432 timestamp: 1655068816.806348 iteration: 77300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11676 FastRCNN class loss: 0.08345 FastRCNN total loss: 0.20021 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.14763 RPN box loss: 0.00641 RPN score loss: 0.00578 RPN total loss: 0.01219 Total loss: 0.92347 timestamp: 1655068820.1002862 iteration: 77305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08989 FastRCNN class loss: 0.0583 FastRCNN total loss: 0.1482 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.13403 RPN box loss: 0.00799 RPN score loss: 0.00446 RPN total loss: 0.01244 Total loss: 0.8581 timestamp: 1655068823.364708 iteration: 77310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14081 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.20795 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.15692 RPN box loss: 0.01469 RPN score loss: 0.00549 RPN total loss: 0.02018 Total loss: 0.94848 timestamp: 1655068826.6495893 iteration: 77315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05812 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.11623 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.15139 RPN box loss: 0.00562 RPN score loss: 0.0071 RPN total loss: 0.01272 Total loss: 0.84376 timestamp: 1655068829.934662 iteration: 77320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14162 FastRCNN class loss: 0.08284 FastRCNN total loss: 0.22446 L1 loss: 0.0000e+00 L2 loss: 0.56343 Learning rate: 0.0004 Mask loss: 0.17383 RPN box loss: 0.01359 RPN score loss: 0.00932 RPN total loss: 0.02291 Total loss: 0.98463 timestamp: 1655068833.1494567 iteration: 77325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09274 FastRCNN class loss: 0.08011 FastRCNN total loss: 0.17285 L1 loss: 0.0000e+00 L2 loss: 0.56342 Learning rate: 0.0004 Mask loss: 0.12389 RPN box loss: 0.02736 RPN score loss: 0.01382 RPN total loss: 0.04119 Total loss: 0.90135 timestamp: 1655068836.4315546 iteration: 77330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13355 FastRCNN class loss: 0.12962 FastRCNN total loss: 0.26317 L1 loss: 0.0000e+00 L2 loss: 0.56342 Learning rate: 0.0004 Mask loss: 0.17841 RPN box loss: 0.02083 RPN score loss: 0.01112 RPN total loss: 0.03195 Total loss: 1.03695 timestamp: 1655068839.7219534 iteration: 77335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0735 FastRCNN class loss: 0.06197 FastRCNN total loss: 0.13546 L1 loss: 0.0000e+00 L2 loss: 0.56342 Learning rate: 0.0004 Mask loss: 0.16965 RPN box loss: 0.00765 RPN score loss: 0.00454 RPN total loss: 0.01219 Total loss: 0.88073 timestamp: 1655068842.9874299 iteration: 77340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08138 FastRCNN class loss: 0.05641 FastRCNN total loss: 0.13779 L1 loss: 0.0000e+00 L2 loss: 0.56342 Learning rate: 0.0004 Mask loss: 0.11734 RPN box loss: 0.01969 RPN score loss: 0.00273 RPN total loss: 0.02242 Total loss: 0.84097 timestamp: 1655068846.2559218 iteration: 77345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11209 FastRCNN class loss: 0.07387 FastRCNN total loss: 0.18597 L1 loss: 0.0000e+00 L2 loss: 0.56342 Learning rate: 0.0004 Mask loss: 0.16824 RPN box loss: 0.0082 RPN score loss: 0.00408 RPN total loss: 0.01227 Total loss: 0.9299 timestamp: 1655068849.5011208 iteration: 77350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07847 FastRCNN class loss: 0.08264 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.16649 RPN box loss: 0.04021 RPN score loss: 0.0031 RPN total loss: 0.04331 Total loss: 0.93432 timestamp: 1655068852.7862413 iteration: 77355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14861 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.23684 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.16759 RPN box loss: 0.00651 RPN score loss: 0.00971 RPN total loss: 0.01622 Total loss: 0.98406 timestamp: 1655068856.1001108 iteration: 77360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.0822 FastRCNN total loss: 0.16553 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.16677 RPN box loss: 0.01807 RPN score loss: 0.0013 RPN total loss: 0.01937 Total loss: 0.91508 timestamp: 1655068859.2832282 iteration: 77365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04921 FastRCNN class loss: 0.0394 FastRCNN total loss: 0.08861 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.15379 RPN box loss: 0.00441 RPN score loss: 0.00343 RPN total loss: 0.00783 Total loss: 0.81364 timestamp: 1655068862.5799437 iteration: 77370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13304 FastRCNN class loss: 0.07759 FastRCNN total loss: 0.21063 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.11352 RPN box loss: 0.03982 RPN score loss: 0.00629 RPN total loss: 0.04611 Total loss: 0.93368 timestamp: 1655068865.917339 iteration: 77375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08067 FastRCNN class loss: 0.04058 FastRCNN total loss: 0.12126 L1 loss: 0.0000e+00 L2 loss: 0.56341 Learning rate: 0.0004 Mask loss: 0.13209 RPN box loss: 0.01096 RPN score loss: 0.00517 RPN total loss: 0.01613 Total loss: 0.83288 timestamp: 1655068869.1562552 iteration: 77380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09198 FastRCNN class loss: 0.0958 FastRCNN total loss: 0.18778 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.18339 RPN box loss: 0.01953 RPN score loss: 0.01975 RPN total loss: 0.03928 Total loss: 0.97385 timestamp: 1655068872.38825 iteration: 77385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09199 FastRCNN class loss: 0.06631 FastRCNN total loss: 0.1583 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.14739 RPN box loss: 0.01133 RPN score loss: 0.00871 RPN total loss: 0.02004 Total loss: 0.88913 timestamp: 1655068875.6320894 iteration: 77390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08801 FastRCNN class loss: 0.06186 FastRCNN total loss: 0.14987 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.14706 RPN box loss: 0.01466 RPN score loss: 0.00589 RPN total loss: 0.02055 Total loss: 0.88088 timestamp: 1655068878.9353049 iteration: 77395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05964 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.11349 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.14123 RPN box loss: 0.00368 RPN score loss: 0.00163 RPN total loss: 0.00531 Total loss: 0.82343 timestamp: 1655068882.2171135 iteration: 77400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11331 FastRCNN class loss: 0.06321 FastRCNN total loss: 0.17652 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.14198 RPN box loss: 0.00517 RPN score loss: 0.00521 RPN total loss: 0.01039 Total loss: 0.89229 timestamp: 1655068885.4866135 iteration: 77405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10044 FastRCNN class loss: 0.08672 FastRCNN total loss: 0.18717 L1 loss: 0.0000e+00 L2 loss: 0.5634 Learning rate: 0.0004 Mask loss: 0.13317 RPN box loss: 0.03329 RPN score loss: 0.01512 RPN total loss: 0.04841 Total loss: 0.93214 timestamp: 1655068888.7732987 iteration: 77410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06953 FastRCNN class loss: 0.06761 FastRCNN total loss: 0.13715 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.12775 RPN box loss: 0.013 RPN score loss: 0.01833 RPN total loss: 0.03133 Total loss: 0.85962 timestamp: 1655068892.041419 iteration: 77415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04543 FastRCNN class loss: 0.03152 FastRCNN total loss: 0.07695 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.09083 RPN box loss: 0.0088 RPN score loss: 0.00094 RPN total loss: 0.00974 Total loss: 0.74092 timestamp: 1655068895.3156323 iteration: 77420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06989 FastRCNN class loss: 0.04299 FastRCNN total loss: 0.11288 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.12365 RPN box loss: 0.01475 RPN score loss: 0.0028 RPN total loss: 0.01755 Total loss: 0.81747 timestamp: 1655068898.6343915 iteration: 77425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05407 FastRCNN class loss: 0.03985 FastRCNN total loss: 0.09391 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.11842 RPN box loss: 0.00333 RPN score loss: 0.01574 RPN total loss: 0.01907 Total loss: 0.7948 timestamp: 1655068901.8472743 iteration: 77430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09559 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.13906 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.12848 RPN box loss: 0.00661 RPN score loss: 0.01116 RPN total loss: 0.01776 Total loss: 0.84869 timestamp: 1655068905.2662265 iteration: 77435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1565 FastRCNN class loss: 0.11812 FastRCNN total loss: 0.27462 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.1782 RPN box loss: 0.02332 RPN score loss: 0.008 RPN total loss: 0.03132 Total loss: 1.04753 timestamp: 1655068908.5349681 iteration: 77440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06098 FastRCNN class loss: 0.06173 FastRCNN total loss: 0.12272 L1 loss: 0.0000e+00 L2 loss: 0.56339 Learning rate: 0.0004 Mask loss: 0.09977 RPN box loss: 0.0047 RPN score loss: 0.00607 RPN total loss: 0.01077 Total loss: 0.79664 timestamp: 1655068911.7663352 iteration: 77445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09023 FastRCNN class loss: 0.04842 FastRCNN total loss: 0.13865 L1 loss: 0.0000e+00 L2 loss: 0.56338 Learning rate: 0.0004 Mask loss: 0.10439 RPN box loss: 0.00652 RPN score loss: 0.00317 RPN total loss: 0.00969 Total loss: 0.81611 timestamp: 1655068915.014442 iteration: 77450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08562 FastRCNN class loss: 0.08816 FastRCNN total loss: 0.17378 L1 loss: 0.0000e+00 L2 loss: 0.56338 Learning rate: 0.0004 Mask loss: 0.23626 RPN box loss: 0.02318 RPN score loss: 0.00418 RPN total loss: 0.02735 Total loss: 1.00077 timestamp: 1655068918.295308 iteration: 77455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05142 FastRCNN class loss: 0.04496 FastRCNN total loss: 0.09638 L1 loss: 0.0000e+00 L2 loss: 0.56338 Learning rate: 0.0004 Mask loss: 0.07747 RPN box loss: 0.00852 RPN score loss: 0.00088 RPN total loss: 0.0094 Total loss: 0.74663 timestamp: 1655068921.6076722 iteration: 77460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13162 FastRCNN class loss: 0.05876 FastRCNN total loss: 0.19038 L1 loss: 0.0000e+00 L2 loss: 0.56338 Learning rate: 0.0004 Mask loss: 0.11545 RPN box loss: 0.01898 RPN score loss: 0.00253 RPN total loss: 0.02151 Total loss: 0.89071 timestamp: 1655068924.8776362 iteration: 77465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12584 FastRCNN class loss: 0.0804 FastRCNN total loss: 0.20623 L1 loss: 0.0000e+00 L2 loss: 0.56338 Learning rate: 0.0004 Mask loss: 0.13822 RPN box loss: 0.00992 RPN score loss: 0.00328 RPN total loss: 0.0132 Total loss: 0.92103 timestamp: 1655068928.1695716 iteration: 77470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09536 FastRCNN class loss: 0.0975 FastRCNN total loss: 0.19287 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.18387 RPN box loss: 0.02952 RPN score loss: 0.01073 RPN total loss: 0.04025 Total loss: 0.98035 timestamp: 1655068931.4966996 iteration: 77475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0871 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.17676 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.12939 RPN box loss: 0.01949 RPN score loss: 0.01104 RPN total loss: 0.03053 Total loss: 0.90005 timestamp: 1655068934.8096018 iteration: 77480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08675 FastRCNN class loss: 0.0978 FastRCNN total loss: 0.18455 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.16215 RPN box loss: 0.02833 RPN score loss: 0.01439 RPN total loss: 0.04271 Total loss: 0.95279 timestamp: 1655068938.0974166 iteration: 77485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.06825 FastRCNN total loss: 0.17633 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.1377 RPN box loss: 0.00517 RPN score loss: 0.00083 RPN total loss: 0.006 Total loss: 0.8834 timestamp: 1655068941.423005 iteration: 77490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15436 FastRCNN class loss: 0.08514 FastRCNN total loss: 0.2395 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.18246 RPN box loss: 0.02597 RPN score loss: 0.00611 RPN total loss: 0.03208 Total loss: 1.01741 timestamp: 1655068944.7445295 iteration: 77495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12495 FastRCNN class loss: 0.06618 FastRCNN total loss: 0.19112 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.12323 RPN box loss: 0.01313 RPN score loss: 0.00765 RPN total loss: 0.02078 Total loss: 0.8985 timestamp: 1655068948.095838 iteration: 77500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08365 FastRCNN class loss: 0.05913 FastRCNN total loss: 0.14279 L1 loss: 0.0000e+00 L2 loss: 0.56337 Learning rate: 0.0004 Mask loss: 0.10361 RPN box loss: 0.00658 RPN score loss: 0.00302 RPN total loss: 0.0096 Total loss: 0.81936 timestamp: 1655068951.3902955 iteration: 77505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10027 FastRCNN class loss: 0.06769 FastRCNN total loss: 0.16796 L1 loss: 0.0000e+00 L2 loss: 0.56336 Learning rate: 0.0004 Mask loss: 0.14267 RPN box loss: 0.02841 RPN score loss: 0.00358 RPN total loss: 0.03199 Total loss: 0.90599 timestamp: 1655068954.5477245 iteration: 77510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07953 FastRCNN class loss: 0.05689 FastRCNN total loss: 0.13643 L1 loss: 0.0000e+00 L2 loss: 0.56336 Learning rate: 0.0004 Mask loss: 0.10719 RPN box loss: 0.02373 RPN score loss: 0.00372 RPN total loss: 0.02746 Total loss: 0.83444 timestamp: 1655068957.8150513 iteration: 77515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09927 FastRCNN class loss: 0.08058 FastRCNN total loss: 0.17985 L1 loss: 0.0000e+00 L2 loss: 0.56336 Learning rate: 0.0004 Mask loss: 0.16026 RPN box loss: 0.01451 RPN score loss: 0.0072 RPN total loss: 0.02171 Total loss: 0.92518 timestamp: 1655068961.0877094 iteration: 77520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09471 FastRCNN class loss: 0.08366 FastRCNN total loss: 0.17837 L1 loss: 0.0000e+00 L2 loss: 0.56336 Learning rate: 0.0004 Mask loss: 0.12934 RPN box loss: 0.02198 RPN score loss: 0.00815 RPN total loss: 0.03012 Total loss: 0.90119 timestamp: 1655068964.4144468 iteration: 77525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0964 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.16075 L1 loss: 0.0000e+00 L2 loss: 0.56336 Learning rate: 0.0004 Mask loss: 0.16835 RPN box loss: 0.01602 RPN score loss: 0.00256 RPN total loss: 0.01858 Total loss: 0.91103 timestamp: 1655068967.6735702 iteration: 77530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.24999 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.19813 RPN box loss: 0.02616 RPN score loss: 0.01631 RPN total loss: 0.04248 Total loss: 1.05395 timestamp: 1655068970.9172945 iteration: 77535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1035 FastRCNN class loss: 0.09715 FastRCNN total loss: 0.20065 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.25136 RPN box loss: 0.02682 RPN score loss: 0.01043 RPN total loss: 0.03725 Total loss: 1.05261 timestamp: 1655068974.1847222 iteration: 77540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07776 FastRCNN class loss: 0.0623 FastRCNN total loss: 0.14006 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.11995 RPN box loss: 0.012 RPN score loss: 0.0021 RPN total loss: 0.0141 Total loss: 0.83746 timestamp: 1655068977.500303 iteration: 77545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08791 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.15767 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.26187 RPN box loss: 0.01902 RPN score loss: 0.00505 RPN total loss: 0.02407 Total loss: 1.00696 timestamp: 1655068980.7370307 iteration: 77550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08304 FastRCNN class loss: 0.06209 FastRCNN total loss: 0.14512 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.09232 RPN box loss: 0.0166 RPN score loss: 0.00193 RPN total loss: 0.01853 Total loss: 0.81932 timestamp: 1655068983.9720228 iteration: 77555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.063 FastRCNN class loss: 0.06422 FastRCNN total loss: 0.12722 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.16612 RPN box loss: 0.01291 RPN score loss: 0.00638 RPN total loss: 0.01929 Total loss: 0.87598 timestamp: 1655068987.1999657 iteration: 77560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10017 FastRCNN class loss: 0.0825 FastRCNN total loss: 0.18267 L1 loss: 0.0000e+00 L2 loss: 0.56335 Learning rate: 0.0004 Mask loss: 0.23098 RPN box loss: 0.01881 RPN score loss: 0.01084 RPN total loss: 0.02965 Total loss: 1.00664 timestamp: 1655068990.4823716 iteration: 77565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05209 FastRCNN class loss: 0.0404 FastRCNN total loss: 0.09249 L1 loss: 0.0000e+00 L2 loss: 0.56334 Learning rate: 0.0004 Mask loss: 0.1293 RPN box loss: 0.02583 RPN score loss: 0.00732 RPN total loss: 0.03316 Total loss: 0.81829 timestamp: 1655068993.7732656 iteration: 77570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09269 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.16442 L1 loss: 0.0000e+00 L2 loss: 0.56334 Learning rate: 0.0004 Mask loss: 0.10097 RPN box loss: 0.01608 RPN score loss: 0.00444 RPN total loss: 0.02052 Total loss: 0.84925 timestamp: 1655068996.9983637 iteration: 77575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14754 FastRCNN class loss: 0.10366 FastRCNN total loss: 0.25121 L1 loss: 0.0000e+00 L2 loss: 0.56334 Learning rate: 0.0004 Mask loss: 0.15867 RPN box loss: 0.01519 RPN score loss: 0.00643 RPN total loss: 0.02162 Total loss: 0.99483 timestamp: 1655069000.2894113 iteration: 77580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14849 FastRCNN class loss: 0.0674 FastRCNN total loss: 0.21589 L1 loss: 0.0000e+00 L2 loss: 0.56334 Learning rate: 0.0004 Mask loss: 0.37021 RPN box loss: 0.02957 RPN score loss: 0.00339 RPN total loss: 0.03296 Total loss: 1.1824 timestamp: 1655069003.5808806 iteration: 77585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0808 FastRCNN class loss: 0.09498 FastRCNN total loss: 0.17578 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.15707 RPN box loss: 0.00918 RPN score loss: 0.00725 RPN total loss: 0.01644 Total loss: 0.91262 timestamp: 1655069006.8634062 iteration: 77590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06328 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.1228 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.13537 RPN box loss: 0.01573 RPN score loss: 0.01304 RPN total loss: 0.02877 Total loss: 0.85027 timestamp: 1655069010.1772108 iteration: 77595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10242 FastRCNN class loss: 0.11377 FastRCNN total loss: 0.21619 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.17345 RPN box loss: 0.01585 RPN score loss: 0.01211 RPN total loss: 0.02796 Total loss: 0.98093 timestamp: 1655069013.4037745 iteration: 77600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14153 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.20405 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.12957 RPN box loss: 0.00697 RPN score loss: 0.00591 RPN total loss: 0.01288 Total loss: 0.90984 timestamp: 1655069016.6825445 iteration: 77605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07271 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.13 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.07309 RPN box loss: 0.00871 RPN score loss: 0.00257 RPN total loss: 0.01128 Total loss: 0.7777 timestamp: 1655069019.960172 iteration: 77610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.05203 FastRCNN total loss: 0.15057 L1 loss: 0.0000e+00 L2 loss: 0.56333 Learning rate: 0.0004 Mask loss: 0.0714 RPN box loss: 0.01486 RPN score loss: 0.00192 RPN total loss: 0.01678 Total loss: 0.80207 timestamp: 1655069023.2668073 iteration: 77615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14877 FastRCNN class loss: 0.10073 FastRCNN total loss: 0.2495 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.15822 RPN box loss: 0.01327 RPN score loss: 0.00621 RPN total loss: 0.01948 Total loss: 0.99052 timestamp: 1655069026.5628877 iteration: 77620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04917 FastRCNN class loss: 0.04705 FastRCNN total loss: 0.09622 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.12267 RPN box loss: 0.01938 RPN score loss: 0.00414 RPN total loss: 0.02352 Total loss: 0.80573 timestamp: 1655069029.8303978 iteration: 77625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09881 FastRCNN class loss: 0.05845 FastRCNN total loss: 0.15726 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.18267 RPN box loss: 0.00977 RPN score loss: 0.00794 RPN total loss: 0.01771 Total loss: 0.92096 timestamp: 1655069033.0831673 iteration: 77630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13954 FastRCNN class loss: 0.09543 FastRCNN total loss: 0.23497 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.1538 RPN box loss: 0.0164 RPN score loss: 0.00781 RPN total loss: 0.02421 Total loss: 0.9763 timestamp: 1655069036.3664732 iteration: 77635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14015 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.20578 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.16627 RPN box loss: 0.014 RPN score loss: 0.00203 RPN total loss: 0.01603 Total loss: 0.9514 timestamp: 1655069039.6299806 iteration: 77640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10159 FastRCNN class loss: 0.06562 FastRCNN total loss: 0.16721 L1 loss: 0.0000e+00 L2 loss: 0.56332 Learning rate: 0.0004 Mask loss: 0.13353 RPN box loss: 0.01557 RPN score loss: 0.00341 RPN total loss: 0.01898 Total loss: 0.88304 timestamp: 1655069042.8387089 iteration: 77645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04336 FastRCNN class loss: 0.03616 FastRCNN total loss: 0.07952 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.1317 RPN box loss: 0.0055 RPN score loss: 0.00888 RPN total loss: 0.01438 Total loss: 0.78891 timestamp: 1655069046.153866 iteration: 77650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04751 FastRCNN class loss: 0.02479 FastRCNN total loss: 0.0723 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.10348 RPN box loss: 0.00154 RPN score loss: 0.00028 RPN total loss: 0.00182 Total loss: 0.74091 timestamp: 1655069049.4513938 iteration: 77655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09658 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.14783 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.10777 RPN box loss: 0.01216 RPN score loss: 0.00435 RPN total loss: 0.01651 Total loss: 0.83543 timestamp: 1655069052.802757 iteration: 77660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10363 FastRCNN class loss: 0.06538 FastRCNN total loss: 0.16901 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.13446 RPN box loss: 0.01152 RPN score loss: 0.00459 RPN total loss: 0.01611 Total loss: 0.88288 timestamp: 1655069056.0791144 iteration: 77665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06911 FastRCNN class loss: 0.05013 FastRCNN total loss: 0.11924 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.12761 RPN box loss: 0.01115 RPN score loss: 0.002 RPN total loss: 0.01315 Total loss: 0.8233 timestamp: 1655069059.2856793 iteration: 77670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06088 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.12658 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.15728 RPN box loss: 0.01282 RPN score loss: 0.01023 RPN total loss: 0.02305 Total loss: 0.87021 timestamp: 1655069062.567797 iteration: 77675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13459 FastRCNN class loss: 0.09635 FastRCNN total loss: 0.23094 L1 loss: 0.0000e+00 L2 loss: 0.56331 Learning rate: 0.0004 Mask loss: 0.14418 RPN box loss: 0.01266 RPN score loss: 0.00264 RPN total loss: 0.01529 Total loss: 0.95373 timestamp: 1655069065.8707664 iteration: 77680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08368 FastRCNN class loss: 0.04187 FastRCNN total loss: 0.12555 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.13501 RPN box loss: 0.03745 RPN score loss: 0.00751 RPN total loss: 0.04496 Total loss: 0.86883 timestamp: 1655069069.0796804 iteration: 77685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07618 FastRCNN class loss: 0.05933 FastRCNN total loss: 0.13551 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.1345 RPN box loss: 0.0258 RPN score loss: 0.00724 RPN total loss: 0.03304 Total loss: 0.86635 timestamp: 1655069072.4179678 iteration: 77690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10041 FastRCNN class loss: 0.09556 FastRCNN total loss: 0.19597 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.1788 RPN box loss: 0.01242 RPN score loss: 0.0029 RPN total loss: 0.01531 Total loss: 0.95339 timestamp: 1655069075.7109628 iteration: 77695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09628 FastRCNN class loss: 0.09267 FastRCNN total loss: 0.18895 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.15602 RPN box loss: 0.00856 RPN score loss: 0.00781 RPN total loss: 0.01637 Total loss: 0.92464 timestamp: 1655069079.0102353 iteration: 77700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10556 FastRCNN class loss: 0.07691 FastRCNN total loss: 0.18247 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.11494 RPN box loss: 0.00551 RPN score loss: 0.00413 RPN total loss: 0.00964 Total loss: 0.87035 timestamp: 1655069082.3480341 iteration: 77705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08325 FastRCNN class loss: 0.07104 FastRCNN total loss: 0.15428 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.17796 RPN box loss: 0.01476 RPN score loss: 0.00691 RPN total loss: 0.02167 Total loss: 0.91721 timestamp: 1655069085.6870608 iteration: 77710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07639 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.16102 L1 loss: 0.0000e+00 L2 loss: 0.5633 Learning rate: 0.0004 Mask loss: 0.22221 RPN box loss: 0.03926 RPN score loss: 0.01546 RPN total loss: 0.05472 Total loss: 1.00125 timestamp: 1655069088.9655542 iteration: 77715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11594 FastRCNN class loss: 0.06212 FastRCNN total loss: 0.17806 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.18553 RPN box loss: 0.00745 RPN score loss: 0.00383 RPN total loss: 0.01128 Total loss: 0.93816 timestamp: 1655069092.2198215 iteration: 77720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08939 FastRCNN class loss: 0.0875 FastRCNN total loss: 0.17689 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.16908 RPN box loss: 0.01347 RPN score loss: 0.01052 RPN total loss: 0.02399 Total loss: 0.93326 timestamp: 1655069095.5086074 iteration: 77725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05674 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.11322 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.11258 RPN box loss: 0.00898 RPN score loss: 0.00998 RPN total loss: 0.01896 Total loss: 0.80806 timestamp: 1655069098.8299577 iteration: 77730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09533 FastRCNN class loss: 0.0721 FastRCNN total loss: 0.16743 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.17028 RPN box loss: 0.00972 RPN score loss: 0.02002 RPN total loss: 0.02975 Total loss: 0.93074 timestamp: 1655069102.0669022 iteration: 77735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10437 FastRCNN class loss: 0.04819 FastRCNN total loss: 0.15256 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.09818 RPN box loss: 0.01139 RPN score loss: 0.00672 RPN total loss: 0.01811 Total loss: 0.83214 timestamp: 1655069105.2478902 iteration: 77740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1225 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.19816 L1 loss: 0.0000e+00 L2 loss: 0.56329 Learning rate: 0.0004 Mask loss: 0.09202 RPN box loss: 0.00644 RPN score loss: 0.00183 RPN total loss: 0.00827 Total loss: 0.86173 timestamp: 1655069108.4424276 iteration: 77745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14582 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.20318 L1 loss: 0.0000e+00 L2 loss: 0.56328 Learning rate: 0.0004 Mask loss: 0.10317 RPN box loss: 0.02269 RPN score loss: 0.00171 RPN total loss: 0.02439 Total loss: 0.89403 timestamp: 1655069111.708474 iteration: 77750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.05527 FastRCNN total loss: 0.15127 L1 loss: 0.0000e+00 L2 loss: 0.56328 Learning rate: 0.0004 Mask loss: 0.11447 RPN box loss: 0.01543 RPN score loss: 0.00314 RPN total loss: 0.01857 Total loss: 0.84759 timestamp: 1655069115.0187955 iteration: 77755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06592 FastRCNN class loss: 0.05926 FastRCNN total loss: 0.12519 L1 loss: 0.0000e+00 L2 loss: 0.56328 Learning rate: 0.0004 Mask loss: 0.13187 RPN box loss: 0.022 RPN score loss: 0.00261 RPN total loss: 0.02461 Total loss: 0.84495 timestamp: 1655069118.3632038 iteration: 77760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12248 FastRCNN class loss: 0.09243 FastRCNN total loss: 0.21491 L1 loss: 0.0000e+00 L2 loss: 0.56328 Learning rate: 0.0004 Mask loss: 0.14501 RPN box loss: 0.03096 RPN score loss: 0.01193 RPN total loss: 0.04289 Total loss: 0.96609 timestamp: 1655069121.5577323 iteration: 77765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11708 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.19051 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.11369 RPN box loss: 0.01142 RPN score loss: 0.00399 RPN total loss: 0.01541 Total loss: 0.88288 timestamp: 1655069124.8229015 iteration: 77770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0613 FastRCNN class loss: 0.07019 FastRCNN total loss: 0.13149 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.10208 RPN box loss: 0.00942 RPN score loss: 0.00695 RPN total loss: 0.01637 Total loss: 0.81321 timestamp: 1655069128.0776005 iteration: 77775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10484 FastRCNN class loss: 0.05919 FastRCNN total loss: 0.16402 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.13101 RPN box loss: 0.01667 RPN score loss: 0.00453 RPN total loss: 0.0212 Total loss: 0.8795 timestamp: 1655069131.3657365 iteration: 77780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11647 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.18538 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.14461 RPN box loss: 0.01643 RPN score loss: 0.0038 RPN total loss: 0.02023 Total loss: 0.91349 timestamp: 1655069134.6487129 iteration: 77785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10928 FastRCNN class loss: 0.08675 FastRCNN total loss: 0.19603 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.15 RPN box loss: 0.00581 RPN score loss: 0.01047 RPN total loss: 0.01628 Total loss: 0.92557 timestamp: 1655069137.900841 iteration: 77790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09078 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.16194 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.16895 RPN box loss: 0.00677 RPN score loss: 0.00395 RPN total loss: 0.01072 Total loss: 0.90487 timestamp: 1655069141.203126 iteration: 77795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10809 FastRCNN class loss: 0.06928 FastRCNN total loss: 0.17737 L1 loss: 0.0000e+00 L2 loss: 0.56327 Learning rate: 0.0004 Mask loss: 0.10086 RPN box loss: 0.01224 RPN score loss: 0.01343 RPN total loss: 0.02567 Total loss: 0.86716 timestamp: 1655069144.4880316 iteration: 77800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05501 FastRCNN class loss: 0.04386 FastRCNN total loss: 0.09888 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.11545 RPN box loss: 0.00429 RPN score loss: 0.00911 RPN total loss: 0.0134 Total loss: 0.791 timestamp: 1655069147.7878525 iteration: 77805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.1891 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.13134 RPN box loss: 0.03675 RPN score loss: 0.00367 RPN total loss: 0.04042 Total loss: 0.92412 timestamp: 1655069151.0459833 iteration: 77810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06031 FastRCNN class loss: 0.03968 FastRCNN total loss: 0.09999 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.11855 RPN box loss: 0.00249 RPN score loss: 0.00639 RPN total loss: 0.00888 Total loss: 0.79068 timestamp: 1655069154.3170052 iteration: 77815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1021 FastRCNN class loss: 0.07606 FastRCNN total loss: 0.17816 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.11824 RPN box loss: 0.00951 RPN score loss: 0.00517 RPN total loss: 0.01468 Total loss: 0.87433 timestamp: 1655069157.6117802 iteration: 77820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09524 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.14995 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.12633 RPN box loss: 0.01461 RPN score loss: 0.00235 RPN total loss: 0.01696 Total loss: 0.8565 timestamp: 1655069160.930014 iteration: 77825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07777 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.1531 L1 loss: 0.0000e+00 L2 loss: 0.56326 Learning rate: 0.0004 Mask loss: 0.19162 RPN box loss: 0.02064 RPN score loss: 0.00424 RPN total loss: 0.02488 Total loss: 0.93286 timestamp: 1655069164.1912858 iteration: 77830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09095 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.14691 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.12447 RPN box loss: 0.01238 RPN score loss: 0.0015 RPN total loss: 0.01388 Total loss: 0.84852 timestamp: 1655069167.4496124 iteration: 77835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08678 FastRCNN class loss: 0.07459 FastRCNN total loss: 0.16137 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.11251 RPN box loss: 0.00715 RPN score loss: 0.0024 RPN total loss: 0.00955 Total loss: 0.84668 timestamp: 1655069170.6881316 iteration: 77840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.05396 FastRCNN total loss: 0.12526 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.1439 RPN box loss: 0.01067 RPN score loss: 0.00516 RPN total loss: 0.01582 Total loss: 0.84824 timestamp: 1655069173.9146402 iteration: 77845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11086 FastRCNN class loss: 0.07595 FastRCNN total loss: 0.18681 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.11781 RPN box loss: 0.01088 RPN score loss: 0.00598 RPN total loss: 0.01685 Total loss: 0.88473 timestamp: 1655069177.175331 iteration: 77850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10312 FastRCNN class loss: 0.07483 FastRCNN total loss: 0.17796 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.15378 RPN box loss: 0.03291 RPN score loss: 0.00285 RPN total loss: 0.03576 Total loss: 0.93075 timestamp: 1655069180.4651659 iteration: 77855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10664 FastRCNN class loss: 0.04364 FastRCNN total loss: 0.15028 L1 loss: 0.0000e+00 L2 loss: 0.56325 Learning rate: 0.0004 Mask loss: 0.11873 RPN box loss: 0.00948 RPN score loss: 0.00083 RPN total loss: 0.01031 Total loss: 0.84257 timestamp: 1655069183.763717 iteration: 77860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.05151 FastRCNN total loss: 0.13644 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.11357 RPN box loss: 0.00411 RPN score loss: 0.00254 RPN total loss: 0.00665 Total loss: 0.81991 timestamp: 1655069187.0419767 iteration: 77865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11449 FastRCNN class loss: 0.09804 FastRCNN total loss: 0.21253 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.15153 RPN box loss: 0.02391 RPN score loss: 0.00587 RPN total loss: 0.02978 Total loss: 0.95708 timestamp: 1655069190.3665087 iteration: 77870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09179 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.15216 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.14104 RPN box loss: 0.00854 RPN score loss: 0.0026 RPN total loss: 0.01114 Total loss: 0.86757 timestamp: 1655069193.596089 iteration: 77875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08955 FastRCNN class loss: 0.05366 FastRCNN total loss: 0.14321 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.12113 RPN box loss: 0.02084 RPN score loss: 0.00178 RPN total loss: 0.02262 Total loss: 0.8502 timestamp: 1655069196.7841718 iteration: 77880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07288 FastRCNN class loss: 0.06151 FastRCNN total loss: 0.13439 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.16918 RPN box loss: 0.00483 RPN score loss: 0.00321 RPN total loss: 0.00804 Total loss: 0.87485 timestamp: 1655069200.0558145 iteration: 77885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11071 FastRCNN class loss: 0.06148 FastRCNN total loss: 0.17219 L1 loss: 0.0000e+00 L2 loss: 0.56324 Learning rate: 0.0004 Mask loss: 0.21103 RPN box loss: 0.01904 RPN score loss: 0.00319 RPN total loss: 0.02223 Total loss: 0.96868 timestamp: 1655069203.288677 iteration: 77890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10589 FastRCNN class loss: 0.07035 FastRCNN total loss: 0.17624 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.15248 RPN box loss: 0.0168 RPN score loss: 0.00216 RPN total loss: 0.01896 Total loss: 0.91091 timestamp: 1655069206.5556946 iteration: 77895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08787 FastRCNN class loss: 0.05111 FastRCNN total loss: 0.13898 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.12032 RPN box loss: 0.01988 RPN score loss: 0.00647 RPN total loss: 0.02635 Total loss: 0.84888 timestamp: 1655069209.8253763 iteration: 77900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06543 FastRCNN class loss: 0.06994 FastRCNN total loss: 0.13537 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.15052 RPN box loss: 0.00487 RPN score loss: 0.00111 RPN total loss: 0.00598 Total loss: 0.8551 timestamp: 1655069213.043027 iteration: 77905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09119 FastRCNN class loss: 0.08583 FastRCNN total loss: 0.17702 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.12851 RPN box loss: 0.01557 RPN score loss: 0.0106 RPN total loss: 0.02617 Total loss: 0.89492 timestamp: 1655069216.3832293 iteration: 77910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05319 FastRCNN class loss: 0.03915 FastRCNN total loss: 0.09234 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.10931 RPN box loss: 0.00429 RPN score loss: 0.00157 RPN total loss: 0.00587 Total loss: 0.77075 timestamp: 1655069219.6378758 iteration: 77915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11387 FastRCNN class loss: 0.06103 FastRCNN total loss: 0.1749 L1 loss: 0.0000e+00 L2 loss: 0.56323 Learning rate: 0.0004 Mask loss: 0.14324 RPN box loss: 0.02583 RPN score loss: 0.00199 RPN total loss: 0.02782 Total loss: 0.90918 timestamp: 1655069222.8598044 iteration: 77920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11189 FastRCNN class loss: 0.05463 FastRCNN total loss: 0.16652 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.11612 RPN box loss: 0.00768 RPN score loss: 0.00176 RPN total loss: 0.00944 Total loss: 0.8553 timestamp: 1655069226.1791553 iteration: 77925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07122 FastRCNN class loss: 0.04571 FastRCNN total loss: 0.11693 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.12669 RPN box loss: 0.0034 RPN score loss: 0.00191 RPN total loss: 0.00532 Total loss: 0.81216 timestamp: 1655069229.4176772 iteration: 77930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09007 FastRCNN class loss: 0.06715 FastRCNN total loss: 0.15722 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.14055 RPN box loss: 0.01279 RPN score loss: 0.00257 RPN total loss: 0.01536 Total loss: 0.87636 timestamp: 1655069232.668165 iteration: 77935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08012 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.15 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.10931 RPN box loss: 0.00738 RPN score loss: 0.00253 RPN total loss: 0.00991 Total loss: 0.83244 timestamp: 1655069235.9522755 iteration: 77940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0785 FastRCNN class loss: 0.07612 FastRCNN total loss: 0.15462 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.10538 RPN box loss: 0.00403 RPN score loss: 0.00096 RPN total loss: 0.00499 Total loss: 0.82821 timestamp: 1655069239.2777023 iteration: 77945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08958 FastRCNN class loss: 0.04861 FastRCNN total loss: 0.13819 L1 loss: 0.0000e+00 L2 loss: 0.56322 Learning rate: 0.0004 Mask loss: 0.11659 RPN box loss: 0.01281 RPN score loss: 0.00249 RPN total loss: 0.0153 Total loss: 0.8333 timestamp: 1655069242.6047866 iteration: 77950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06174 FastRCNN class loss: 0.04148 FastRCNN total loss: 0.10322 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.10945 RPN box loss: 0.00809 RPN score loss: 0.00137 RPN total loss: 0.00946 Total loss: 0.78534 timestamp: 1655069245.8034306 iteration: 77955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10366 FastRCNN class loss: 0.07306 FastRCNN total loss: 0.17672 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.13487 RPN box loss: 0.01288 RPN score loss: 0.0047 RPN total loss: 0.01758 Total loss: 0.89238 timestamp: 1655069249.0938296 iteration: 77960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15311 FastRCNN class loss: 0.06765 FastRCNN total loss: 0.22076 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.15917 RPN box loss: 0.04661 RPN score loss: 0.00787 RPN total loss: 0.05448 Total loss: 0.99762 timestamp: 1655069252.4085202 iteration: 77965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.05584 FastRCNN total loss: 0.14668 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.09837 RPN box loss: 0.00954 RPN score loss: 0.00535 RPN total loss: 0.01489 Total loss: 0.82315 timestamp: 1655069255.7011554 iteration: 77970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12526 FastRCNN class loss: 0.05766 FastRCNN total loss: 0.18292 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.14778 RPN box loss: 0.01738 RPN score loss: 0.00113 RPN total loss: 0.01852 Total loss: 0.91243 timestamp: 1655069258.96977 iteration: 77975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.07725 FastRCNN total loss: 0.18764 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.13511 RPN box loss: 0.0162 RPN score loss: 0.00533 RPN total loss: 0.02153 Total loss: 0.90748 timestamp: 1655069262.2216792 iteration: 77980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07997 FastRCNN class loss: 0.09194 FastRCNN total loss: 0.17192 L1 loss: 0.0000e+00 L2 loss: 0.56321 Learning rate: 0.0004 Mask loss: 0.12778 RPN box loss: 0.01211 RPN score loss: 0.00267 RPN total loss: 0.01478 Total loss: 0.87768 timestamp: 1655069265.4662926 iteration: 77985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.07902 FastRCNN total loss: 0.18318 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.13766 RPN box loss: 0.00898 RPN score loss: 0.00562 RPN total loss: 0.0146 Total loss: 0.89865 timestamp: 1655069268.7009518 iteration: 77990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1124 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.20474 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.13458 RPN box loss: 0.01313 RPN score loss: 0.003 RPN total loss: 0.01613 Total loss: 0.91865 timestamp: 1655069272.0279303 iteration: 77995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08216 FastRCNN class loss: 0.06934 FastRCNN total loss: 0.1515 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.13533 RPN box loss: 0.01465 RPN score loss: 0.00543 RPN total loss: 0.02008 Total loss: 0.87011 timestamp: 1655069275.2907495 iteration: 78000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07262 FastRCNN class loss: 0.04725 FastRCNN total loss: 0.11987 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.17368 RPN box loss: 0.00736 RPN score loss: 0.00542 RPN total loss: 0.01278 Total loss: 0.86953 timestamp: 1655069278.5107207 iteration: 78005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08738 FastRCNN class loss: 0.06702 FastRCNN total loss: 0.15439 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.09795 RPN box loss: 0.01133 RPN score loss: 0.00292 RPN total loss: 0.01425 Total loss: 0.8298 timestamp: 1655069281.7617064 iteration: 78010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1231 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.19004 L1 loss: 0.0000e+00 L2 loss: 0.5632 Learning rate: 0.0004 Mask loss: 0.14503 RPN box loss: 0.03028 RPN score loss: 0.00518 RPN total loss: 0.03546 Total loss: 0.93373 timestamp: 1655069285.0684156 iteration: 78015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08218 FastRCNN class loss: 0.08287 FastRCNN total loss: 0.16504 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.09568 RPN box loss: 0.0162 RPN score loss: 0.00712 RPN total loss: 0.02332 Total loss: 0.84723 timestamp: 1655069288.3491466 iteration: 78020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07907 FastRCNN class loss: 0.06354 FastRCNN total loss: 0.1426 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.1331 RPN box loss: 0.00712 RPN score loss: 0.00489 RPN total loss: 0.01201 Total loss: 0.8509 timestamp: 1655069291.7386582 iteration: 78025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14909 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.21792 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.1159 RPN box loss: 0.01874 RPN score loss: 0.00916 RPN total loss: 0.0279 Total loss: 0.92492 timestamp: 1655069295.1347895 iteration: 78030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16897 FastRCNN class loss: 0.07877 FastRCNN total loss: 0.24774 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.1294 RPN box loss: 0.01019 RPN score loss: 0.01053 RPN total loss: 0.02072 Total loss: 0.96105 timestamp: 1655069298.3352559 iteration: 78035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09622 FastRCNN class loss: 0.11201 FastRCNN total loss: 0.20823 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.15369 RPN box loss: 0.02612 RPN score loss: 0.01816 RPN total loss: 0.04428 Total loss: 0.96939 timestamp: 1655069301.636486 iteration: 78040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0709 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.12552 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.08617 RPN box loss: 0.00571 RPN score loss: 0.00224 RPN total loss: 0.00795 Total loss: 0.78284 timestamp: 1655069304.831125 iteration: 78045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12414 FastRCNN class loss: 0.08118 FastRCNN total loss: 0.20532 L1 loss: 0.0000e+00 L2 loss: 0.56319 Learning rate: 0.0004 Mask loss: 0.15834 RPN box loss: 0.01347 RPN score loss: 0.00747 RPN total loss: 0.02094 Total loss: 0.94779 timestamp: 1655069308.1019425 iteration: 78050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06964 FastRCNN class loss: 0.05056 FastRCNN total loss: 0.1202 L1 loss: 0.0000e+00 L2 loss: 0.56318 Learning rate: 0.0004 Mask loss: 0.12672 RPN box loss: 0.00612 RPN score loss: 0.00523 RPN total loss: 0.01135 Total loss: 0.82145 timestamp: 1655069311.4095306 iteration: 78055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09512 FastRCNN class loss: 0.05561 FastRCNN total loss: 0.15073 L1 loss: 0.0000e+00 L2 loss: 0.56318 Learning rate: 0.0004 Mask loss: 0.1604 RPN box loss: 0.01862 RPN score loss: 0.00837 RPN total loss: 0.02699 Total loss: 0.9013 timestamp: 1655069314.7159064 iteration: 78060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07098 FastRCNN class loss: 0.07267 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.56318 Learning rate: 0.0004 Mask loss: 0.0909 RPN box loss: 0.01009 RPN score loss: 0.00229 RPN total loss: 0.01237 Total loss: 0.8101 timestamp: 1655069318.0155017 iteration: 78065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11833 FastRCNN class loss: 0.10088 FastRCNN total loss: 0.21921 L1 loss: 0.0000e+00 L2 loss: 0.56318 Learning rate: 0.0004 Mask loss: 0.15793 RPN box loss: 0.01986 RPN score loss: 0.00809 RPN total loss: 0.02796 Total loss: 0.96828 timestamp: 1655069321.3270433 iteration: 78070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07462 FastRCNN class loss: 0.09233 FastRCNN total loss: 0.16696 L1 loss: 0.0000e+00 L2 loss: 0.56318 Learning rate: 0.0004 Mask loss: 0.19161 RPN box loss: 0.02398 RPN score loss: 0.00479 RPN total loss: 0.02877 Total loss: 0.95051 timestamp: 1655069324.6516972 iteration: 78075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08257 FastRCNN class loss: 0.07143 FastRCNN total loss: 0.154 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.16958 RPN box loss: 0.01257 RPN score loss: 0.00154 RPN total loss: 0.01411 Total loss: 0.90087 timestamp: 1655069327.9186094 iteration: 78080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13218 FastRCNN class loss: 0.10691 FastRCNN total loss: 0.23909 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.18431 RPN box loss: 0.01353 RPN score loss: 0.00508 RPN total loss: 0.01861 Total loss: 1.00519 timestamp: 1655069331.246136 iteration: 78085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09879 FastRCNN class loss: 0.05731 FastRCNN total loss: 0.1561 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.26115 RPN box loss: 0.00433 RPN score loss: 0.00154 RPN total loss: 0.00587 Total loss: 0.9863 timestamp: 1655069334.5194323 iteration: 78090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08733 FastRCNN class loss: 0.04871 FastRCNN total loss: 0.13605 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.1158 RPN box loss: 0.0124 RPN score loss: 0.0061 RPN total loss: 0.0185 Total loss: 0.83352 timestamp: 1655069337.8102705 iteration: 78095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05685 FastRCNN class loss: 0.07823 FastRCNN total loss: 0.13508 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.10081 RPN box loss: 0.0196 RPN score loss: 0.00591 RPN total loss: 0.02551 Total loss: 0.82456 timestamp: 1655069341.0748873 iteration: 78100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0734 FastRCNN class loss: 0.05539 FastRCNN total loss: 0.12879 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.12778 RPN box loss: 0.00933 RPN score loss: 0.00251 RPN total loss: 0.01184 Total loss: 0.83158 timestamp: 1655069344.2557704 iteration: 78105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.07644 FastRCNN total loss: 0.18103 L1 loss: 0.0000e+00 L2 loss: 0.56317 Learning rate: 0.0004 Mask loss: 0.17432 RPN box loss: 0.04179 RPN score loss: 0.01384 RPN total loss: 0.05563 Total loss: 0.97414 timestamp: 1655069347.3987885 iteration: 78110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09523 FastRCNN class loss: 0.06468 FastRCNN total loss: 0.15991 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.13628 RPN box loss: 0.01323 RPN score loss: 0.00196 RPN total loss: 0.0152 Total loss: 0.87454 timestamp: 1655069350.6969867 iteration: 78115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07131 FastRCNN class loss: 0.07314 FastRCNN total loss: 0.14445 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.13167 RPN box loss: 0.01735 RPN score loss: 0.00354 RPN total loss: 0.0209 Total loss: 0.86018 timestamp: 1655069354.0086465 iteration: 78120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08771 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.14832 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.1421 RPN box loss: 0.01168 RPN score loss: 0.00114 RPN total loss: 0.01281 Total loss: 0.86639 timestamp: 1655069357.3061576 iteration: 78125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14791 FastRCNN class loss: 0.13205 FastRCNN total loss: 0.27996 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.18652 RPN box loss: 0.04387 RPN score loss: 0.00762 RPN total loss: 0.05149 Total loss: 1.08114 timestamp: 1655069360.5770414 iteration: 78130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07959 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.12517 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.08698 RPN box loss: 0.03877 RPN score loss: 0.00133 RPN total loss: 0.0401 Total loss: 0.81541 timestamp: 1655069363.9228752 iteration: 78135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06261 FastRCNN class loss: 0.04521 FastRCNN total loss: 0.10782 L1 loss: 0.0000e+00 L2 loss: 0.56316 Learning rate: 0.0004 Mask loss: 0.12611 RPN box loss: 0.00971 RPN score loss: 0.00315 RPN total loss: 0.01286 Total loss: 0.80995 timestamp: 1655069367.2741585 iteration: 78140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0551 FastRCNN class loss: 0.05694 FastRCNN total loss: 0.11204 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.08952 RPN box loss: 0.00663 RPN score loss: 0.00749 RPN total loss: 0.01412 Total loss: 0.77884 timestamp: 1655069370.5344782 iteration: 78145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08174 FastRCNN class loss: 0.0718 FastRCNN total loss: 0.15353 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.24996 RPN box loss: 0.02098 RPN score loss: 0.00767 RPN total loss: 0.02865 Total loss: 0.9953 timestamp: 1655069373.785595 iteration: 78150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10636 FastRCNN class loss: 0.17219 FastRCNN total loss: 0.27855 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.13734 RPN box loss: 0.00944 RPN score loss: 0.0082 RPN total loss: 0.01765 Total loss: 0.99669 timestamp: 1655069377.0157833 iteration: 78155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08136 FastRCNN class loss: 0.0404 FastRCNN total loss: 0.12176 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.13556 RPN box loss: 0.00706 RPN score loss: 0.00629 RPN total loss: 0.01336 Total loss: 0.83383 timestamp: 1655069380.364561 iteration: 78160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13406 FastRCNN class loss: 0.09609 FastRCNN total loss: 0.23015 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.14381 RPN box loss: 0.01693 RPN score loss: 0.00672 RPN total loss: 0.02366 Total loss: 0.96076 timestamp: 1655069383.6131752 iteration: 78165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08099 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.13177 L1 loss: 0.0000e+00 L2 loss: 0.56315 Learning rate: 0.0004 Mask loss: 0.1366 RPN box loss: 0.01566 RPN score loss: 0.00499 RPN total loss: 0.02065 Total loss: 0.85216 timestamp: 1655069386.8377085 iteration: 78170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0573 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.11492 L1 loss: 0.0000e+00 L2 loss: 0.56314 Learning rate: 0.0004 Mask loss: 0.18455 RPN box loss: 0.01045 RPN score loss: 0.00886 RPN total loss: 0.01931 Total loss: 0.88192 timestamp: 1655069390.0493002 iteration: 78175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09029 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.15676 L1 loss: 0.0000e+00 L2 loss: 0.56314 Learning rate: 0.0004 Mask loss: 0.13674 RPN box loss: 0.0114 RPN score loss: 0.00335 RPN total loss: 0.01475 Total loss: 0.87139 timestamp: 1655069393.3081865 iteration: 78180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08947 FastRCNN class loss: 0.08784 FastRCNN total loss: 0.17731 L1 loss: 0.0000e+00 L2 loss: 0.56314 Learning rate: 0.0004 Mask loss: 0.15413 RPN box loss: 0.01159 RPN score loss: 0.00553 RPN total loss: 0.01712 Total loss: 0.9117 timestamp: 1655069396.6303022 iteration: 78185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09132 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.14608 L1 loss: 0.0000e+00 L2 loss: 0.56314 Learning rate: 0.0004 Mask loss: 0.13846 RPN box loss: 0.00415 RPN score loss: 0.00455 RPN total loss: 0.0087 Total loss: 0.85637 timestamp: 1655069399.9045227 iteration: 78190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08708 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.16202 L1 loss: 0.0000e+00 L2 loss: 0.56314 Learning rate: 0.0004 Mask loss: 0.12193 RPN box loss: 0.01516 RPN score loss: 0.0024 RPN total loss: 0.01756 Total loss: 0.86464 timestamp: 1655069403.218604 iteration: 78195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06124 FastRCNN class loss: 0.03194 FastRCNN total loss: 0.09318 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.1214 RPN box loss: 0.00981 RPN score loss: 0.00409 RPN total loss: 0.0139 Total loss: 0.79161 timestamp: 1655069406.4887872 iteration: 78200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10645 FastRCNN class loss: 0.07009 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.13396 RPN box loss: 0.01434 RPN score loss: 0.00752 RPN total loss: 0.02186 Total loss: 0.8955 timestamp: 1655069409.778738 iteration: 78205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07869 FastRCNN class loss: 0.06993 FastRCNN total loss: 0.14863 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.13596 RPN box loss: 0.01798 RPN score loss: 0.00877 RPN total loss: 0.02675 Total loss: 0.87446 timestamp: 1655069412.9866614 iteration: 78210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10634 FastRCNN class loss: 0.06658 FastRCNN total loss: 0.17293 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.13968 RPN box loss: 0.02109 RPN score loss: 0.00401 RPN total loss: 0.0251 Total loss: 0.90084 timestamp: 1655069416.2805276 iteration: 78215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09515 FastRCNN class loss: 0.03989 FastRCNN total loss: 0.13505 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.07803 RPN box loss: 0.01816 RPN score loss: 0.00266 RPN total loss: 0.02083 Total loss: 0.79703 timestamp: 1655069419.5992796 iteration: 78220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09321 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.16746 L1 loss: 0.0000e+00 L2 loss: 0.56313 Learning rate: 0.0004 Mask loss: 0.13454 RPN box loss: 0.01152 RPN score loss: 0.00508 RPN total loss: 0.0166 Total loss: 0.88173 timestamp: 1655069422.837663 iteration: 78225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07238 FastRCNN class loss: 0.06479 FastRCNN total loss: 0.13717 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.13609 RPN box loss: 0.01148 RPN score loss: 0.00985 RPN total loss: 0.02133 Total loss: 0.85772 timestamp: 1655069426.0937872 iteration: 78230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11988 FastRCNN class loss: 0.09474 FastRCNN total loss: 0.21463 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.15783 RPN box loss: 0.01109 RPN score loss: 0.00497 RPN total loss: 0.01606 Total loss: 0.95164 timestamp: 1655069429.3421276 iteration: 78235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06272 FastRCNN class loss: 0.03975 FastRCNN total loss: 0.10247 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.12232 RPN box loss: 0.01571 RPN score loss: 0.00433 RPN total loss: 0.02004 Total loss: 0.80795 timestamp: 1655069432.5699415 iteration: 78240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.17846 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.16449 RPN box loss: 0.01986 RPN score loss: 0.00695 RPN total loss: 0.02681 Total loss: 0.93288 timestamp: 1655069435.778024 iteration: 78245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0832 FastRCNN class loss: 0.06084 FastRCNN total loss: 0.14404 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.1242 RPN box loss: 0.00891 RPN score loss: 0.00301 RPN total loss: 0.01192 Total loss: 0.84328 timestamp: 1655069439.0220087 iteration: 78250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16321 FastRCNN class loss: 0.11845 FastRCNN total loss: 0.28166 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.22123 RPN box loss: 0.0073 RPN score loss: 0.01111 RPN total loss: 0.01842 Total loss: 1.08442 timestamp: 1655069442.263485 iteration: 78255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07097 FastRCNN class loss: 0.03469 FastRCNN total loss: 0.10566 L1 loss: 0.0000e+00 L2 loss: 0.56312 Learning rate: 0.0004 Mask loss: 0.10522 RPN box loss: 0.00693 RPN score loss: 0.0027 RPN total loss: 0.00964 Total loss: 0.78364 timestamp: 1655069445.5177186 iteration: 78260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09597 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.15526 L1 loss: 0.0000e+00 L2 loss: 0.56311 Learning rate: 0.0004 Mask loss: 0.13036 RPN box loss: 0.01315 RPN score loss: 0.00227 RPN total loss: 0.01543 Total loss: 0.86416 timestamp: 1655069448.7563152 iteration: 78265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11799 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.16917 L1 loss: 0.0000e+00 L2 loss: 0.56311 Learning rate: 0.0004 Mask loss: 0.1502 RPN box loss: 0.0076 RPN score loss: 0.00218 RPN total loss: 0.00978 Total loss: 0.89226 timestamp: 1655069452.0442061 iteration: 78270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13068 FastRCNN class loss: 0.09569 FastRCNN total loss: 0.22638 L1 loss: 0.0000e+00 L2 loss: 0.56311 Learning rate: 0.0004 Mask loss: 0.25288 RPN box loss: 0.01602 RPN score loss: 0.00612 RPN total loss: 0.02214 Total loss: 1.06452 timestamp: 1655069455.2930243 iteration: 78275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09601 FastRCNN class loss: 0.08228 FastRCNN total loss: 0.17829 L1 loss: 0.0000e+00 L2 loss: 0.56311 Learning rate: 0.0004 Mask loss: 0.13961 RPN box loss: 0.00845 RPN score loss: 0.00597 RPN total loss: 0.01442 Total loss: 0.89543 timestamp: 1655069458.528133 iteration: 78280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11715 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.18474 L1 loss: 0.0000e+00 L2 loss: 0.56311 Learning rate: 0.0004 Mask loss: 0.13699 RPN box loss: 0.00714 RPN score loss: 0.00305 RPN total loss: 0.01018 Total loss: 0.89502 timestamp: 1655069461.8218677 iteration: 78285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.04347 FastRCNN total loss: 0.14343 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.11111 RPN box loss: 0.00939 RPN score loss: 0.00557 RPN total loss: 0.01496 Total loss: 0.83259 timestamp: 1655069465.0879931 iteration: 78290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12711 FastRCNN class loss: 0.08925 FastRCNN total loss: 0.21636 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.19631 RPN box loss: 0.02086 RPN score loss: 0.00092 RPN total loss: 0.02179 Total loss: 0.99756 timestamp: 1655069468.3435018 iteration: 78295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08878 FastRCNN class loss: 0.0816 FastRCNN total loss: 0.17039 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.15468 RPN box loss: 0.01307 RPN score loss: 0.00993 RPN total loss: 0.023 Total loss: 0.91117 timestamp: 1655069471.6343594 iteration: 78300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11651 FastRCNN class loss: 0.14042 FastRCNN total loss: 0.25693 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.18345 RPN box loss: 0.02385 RPN score loss: 0.0106 RPN total loss: 0.03445 Total loss: 1.03794 timestamp: 1655069474.846257 iteration: 78305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12155 FastRCNN class loss: 0.06256 FastRCNN total loss: 0.18411 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.10835 RPN box loss: 0.03739 RPN score loss: 0.00155 RPN total loss: 0.03894 Total loss: 0.8945 timestamp: 1655069478.1175542 iteration: 78310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15293 FastRCNN class loss: 0.10494 FastRCNN total loss: 0.25787 L1 loss: 0.0000e+00 L2 loss: 0.5631 Learning rate: 0.0004 Mask loss: 0.20747 RPN box loss: 0.03176 RPN score loss: 0.02013 RPN total loss: 0.05189 Total loss: 1.08033 timestamp: 1655069481.4012196 iteration: 78315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13507 FastRCNN class loss: 0.11414 FastRCNN total loss: 0.24921 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.15552 RPN box loss: 0.01879 RPN score loss: 0.00824 RPN total loss: 0.02703 Total loss: 0.99486 timestamp: 1655069484.6912186 iteration: 78320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08481 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.13585 RPN box loss: 0.01211 RPN score loss: 0.00371 RPN total loss: 0.01581 Total loss: 0.87146 timestamp: 1655069487.929657 iteration: 78325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05556 FastRCNN class loss: 0.06125 FastRCNN total loss: 0.11681 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.08989 RPN box loss: 0.00682 RPN score loss: 0.00356 RPN total loss: 0.01038 Total loss: 0.78016 timestamp: 1655069491.1631663 iteration: 78330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.05516 FastRCNN total loss: 0.13452 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.12748 RPN box loss: 0.00552 RPN score loss: 0.00512 RPN total loss: 0.01064 Total loss: 0.83572 timestamp: 1655069494.4285975 iteration: 78335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08056 FastRCNN class loss: 0.07683 FastRCNN total loss: 0.15739 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.15107 RPN box loss: 0.02042 RPN score loss: 0.00416 RPN total loss: 0.02458 Total loss: 0.89614 timestamp: 1655069497.6978788 iteration: 78340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0831 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.14921 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.13163 RPN box loss: 0.01697 RPN score loss: 0.00385 RPN total loss: 0.02083 Total loss: 0.86475 timestamp: 1655069501.006907 iteration: 78345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0759 FastRCNN class loss: 0.05431 FastRCNN total loss: 0.13021 L1 loss: 0.0000e+00 L2 loss: 0.56309 Learning rate: 0.0004 Mask loss: 0.15745 RPN box loss: 0.01102 RPN score loss: 0.00351 RPN total loss: 0.01453 Total loss: 0.86528 timestamp: 1655069504.2068088 iteration: 78350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12232 FastRCNN class loss: 0.07588 FastRCNN total loss: 0.1982 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.178 RPN box loss: 0.01486 RPN score loss: 0.00204 RPN total loss: 0.01689 Total loss: 0.95618 timestamp: 1655069507.4901993 iteration: 78355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11416 FastRCNN class loss: 0.05546 FastRCNN total loss: 0.16962 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.14593 RPN box loss: 0.02547 RPN score loss: 0.007 RPN total loss: 0.03247 Total loss: 0.9111 timestamp: 1655069510.6840377 iteration: 78360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05842 FastRCNN class loss: 0.06262 FastRCNN total loss: 0.12104 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.13702 RPN box loss: 0.00838 RPN score loss: 0.00221 RPN total loss: 0.01059 Total loss: 0.83173 timestamp: 1655069513.944927 iteration: 78365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05342 FastRCNN class loss: 0.04167 FastRCNN total loss: 0.09509 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.13182 RPN box loss: 0.00765 RPN score loss: 0.00252 RPN total loss: 0.01017 Total loss: 0.80016 timestamp: 1655069517.302743 iteration: 78370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08572 FastRCNN class loss: 0.0772 FastRCNN total loss: 0.16292 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.13353 RPN box loss: 0.01356 RPN score loss: 0.00155 RPN total loss: 0.01512 Total loss: 0.87464 timestamp: 1655069520.5238183 iteration: 78375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07902 FastRCNN class loss: 0.04103 FastRCNN total loss: 0.12004 L1 loss: 0.0000e+00 L2 loss: 0.56308 Learning rate: 0.0004 Mask loss: 0.13692 RPN box loss: 0.00523 RPN score loss: 0.0031 RPN total loss: 0.00834 Total loss: 0.82837 timestamp: 1655069523.7740161 iteration: 78380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10477 FastRCNN class loss: 0.08672 FastRCNN total loss: 0.19149 L1 loss: 0.0000e+00 L2 loss: 0.56307 Learning rate: 0.0004 Mask loss: 0.15032 RPN box loss: 0.01577 RPN score loss: 0.00535 RPN total loss: 0.02112 Total loss: 0.92601 timestamp: 1655069527.0303738 iteration: 78385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15937 FastRCNN class loss: 0.08774 FastRCNN total loss: 0.24712 L1 loss: 0.0000e+00 L2 loss: 0.56307 Learning rate: 0.0004 Mask loss: 0.15325 RPN box loss: 0.00756 RPN score loss: 0.0036 RPN total loss: 0.01117 Total loss: 0.9746 timestamp: 1655069530.2864182 iteration: 78390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08847 FastRCNN class loss: 0.07434 FastRCNN total loss: 0.16281 L1 loss: 0.0000e+00 L2 loss: 0.56307 Learning rate: 0.0004 Mask loss: 0.1384 RPN box loss: 0.01372 RPN score loss: 0.00691 RPN total loss: 0.02063 Total loss: 0.88491 timestamp: 1655069533.5807793 iteration: 78395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06545 FastRCNN class loss: 0.04203 FastRCNN total loss: 0.10747 L1 loss: 0.0000e+00 L2 loss: 0.56307 Learning rate: 0.0004 Mask loss: 0.08826 RPN box loss: 0.01772 RPN score loss: 0.00387 RPN total loss: 0.02159 Total loss: 0.7804 timestamp: 1655069536.8789928 iteration: 78400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13656 FastRCNN class loss: 0.11535 FastRCNN total loss: 0.25191 L1 loss: 0.0000e+00 L2 loss: 0.56307 Learning rate: 0.0004 Mask loss: 0.19619 RPN box loss: 0.04715 RPN score loss: 0.01394 RPN total loss: 0.06108 Total loss: 1.07225 timestamp: 1655069540.1552627 iteration: 78405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.05736 FastRCNN total loss: 0.11958 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.10388 RPN box loss: 0.00723 RPN score loss: 0.00284 RPN total loss: 0.01007 Total loss: 0.79659 timestamp: 1655069543.3914266 iteration: 78410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12871 FastRCNN class loss: 0.1544 FastRCNN total loss: 0.28311 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.15425 RPN box loss: 0.01028 RPN score loss: 0.01354 RPN total loss: 0.02382 Total loss: 1.02424 timestamp: 1655069546.6779366 iteration: 78415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12535 FastRCNN class loss: 0.10267 FastRCNN total loss: 0.22802 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.15443 RPN box loss: 0.04023 RPN score loss: 0.00398 RPN total loss: 0.04421 Total loss: 0.98972 timestamp: 1655069549.9181674 iteration: 78420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06937 FastRCNN class loss: 0.0803 FastRCNN total loss: 0.14967 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.18486 RPN box loss: 0.02107 RPN score loss: 0.01092 RPN total loss: 0.032 Total loss: 0.92959 timestamp: 1655069553.2415414 iteration: 78425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.05328 FastRCNN total loss: 0.12905 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.07562 RPN box loss: 0.00678 RPN score loss: 0.00669 RPN total loss: 0.01347 Total loss: 0.7812 timestamp: 1655069556.5011158 iteration: 78430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1473 FastRCNN class loss: 0.0788 FastRCNN total loss: 0.2261 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.18066 RPN box loss: 0.01835 RPN score loss: 0.00623 RPN total loss: 0.02457 Total loss: 0.99439 timestamp: 1655069559.7570052 iteration: 78435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13683 FastRCNN class loss: 0.07545 FastRCNN total loss: 0.21227 L1 loss: 0.0000e+00 L2 loss: 0.56306 Learning rate: 0.0004 Mask loss: 0.16678 RPN box loss: 0.03249 RPN score loss: 0.01086 RPN total loss: 0.04335 Total loss: 0.98546 timestamp: 1655069562.9944253 iteration: 78440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06004 FastRCNN class loss: 0.04221 FastRCNN total loss: 0.10224 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.124 RPN box loss: 0.01413 RPN score loss: 0.00627 RPN total loss: 0.0204 Total loss: 0.8097 timestamp: 1655069566.2652757 iteration: 78445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0862 FastRCNN class loss: 0.06121 FastRCNN total loss: 0.14741 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.09472 RPN box loss: 0.01654 RPN score loss: 0.00316 RPN total loss: 0.01971 Total loss: 0.82489 timestamp: 1655069569.5113611 iteration: 78450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18263 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.2685 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.19067 RPN box loss: 0.01528 RPN score loss: 0.00452 RPN total loss: 0.0198 Total loss: 1.04202 timestamp: 1655069572.827405 iteration: 78455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09081 FastRCNN class loss: 0.08966 FastRCNN total loss: 0.18048 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.13785 RPN box loss: 0.02469 RPN score loss: 0.01177 RPN total loss: 0.03646 Total loss: 0.91784 timestamp: 1655069576.1063535 iteration: 78460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08087 FastRCNN class loss: 0.09029 FastRCNN total loss: 0.17116 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.2045 RPN box loss: 0.0246 RPN score loss: 0.00226 RPN total loss: 0.02686 Total loss: 0.96558 timestamp: 1655069579.4083667 iteration: 78465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07503 FastRCNN class loss: 0.0438 FastRCNN total loss: 0.11883 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.11063 RPN box loss: 0.00997 RPN score loss: 0.0012 RPN total loss: 0.01116 Total loss: 0.80366 timestamp: 1655069582.7721808 iteration: 78470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06964 FastRCNN class loss: 0.05981 FastRCNN total loss: 0.12945 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.18845 RPN box loss: 0.01146 RPN score loss: 0.00584 RPN total loss: 0.0173 Total loss: 0.89825 timestamp: 1655069585.970819 iteration: 78475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0617 FastRCNN class loss: 0.06541 FastRCNN total loss: 0.12711 L1 loss: 0.0000e+00 L2 loss: 0.56305 Learning rate: 0.0004 Mask loss: 0.11644 RPN box loss: 0.01471 RPN score loss: 0.00102 RPN total loss: 0.01573 Total loss: 0.82233 timestamp: 1655069589.2242134 iteration: 78480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07166 FastRCNN class loss: 0.07295 FastRCNN total loss: 0.1446 L1 loss: 0.0000e+00 L2 loss: 0.56304 Learning rate: 0.0004 Mask loss: 0.18334 RPN box loss: 0.00963 RPN score loss: 0.0183 RPN total loss: 0.02794 Total loss: 0.91892 timestamp: 1655069592.4898562 iteration: 78485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08394 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.14532 L1 loss: 0.0000e+00 L2 loss: 0.56304 Learning rate: 0.0004 Mask loss: 0.13637 RPN box loss: 0.04736 RPN score loss: 0.00263 RPN total loss: 0.05 Total loss: 0.89473 timestamp: 1655069595.774172 iteration: 78490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06096 FastRCNN class loss: 0.05039 FastRCNN total loss: 0.11134 L1 loss: 0.0000e+00 L2 loss: 0.56304 Learning rate: 0.0004 Mask loss: 0.09536 RPN box loss: 0.01708 RPN score loss: 0.00517 RPN total loss: 0.02225 Total loss: 0.79199 timestamp: 1655069598.9898512 iteration: 78495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06821 FastRCNN class loss: 0.05681 FastRCNN total loss: 0.12502 L1 loss: 0.0000e+00 L2 loss: 0.56304 Learning rate: 0.0004 Mask loss: 0.07394 RPN box loss: 0.00513 RPN score loss: 0.00216 RPN total loss: 0.00729 Total loss: 0.7693 timestamp: 1655069602.3208737 iteration: 78500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09189 FastRCNN class loss: 0.08116 FastRCNN total loss: 0.17305 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.20388 RPN box loss: 0.0348 RPN score loss: 0.00347 RPN total loss: 0.03827 Total loss: 0.97824 timestamp: 1655069605.5922256 iteration: 78505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07785 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.14638 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.15217 RPN box loss: 0.01092 RPN score loss: 0.00499 RPN total loss: 0.01591 Total loss: 0.8775 timestamp: 1655069608.9054718 iteration: 78510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15492 FastRCNN class loss: 0.08351 FastRCNN total loss: 0.23844 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.22089 RPN box loss: 0.00585 RPN score loss: 0.00735 RPN total loss: 0.0132 Total loss: 1.03556 timestamp: 1655069612.1630776 iteration: 78515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09506 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.14355 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.09764 RPN box loss: 0.01034 RPN score loss: 0.00447 RPN total loss: 0.01481 Total loss: 0.81904 timestamp: 1655069615.4147167 iteration: 78520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09051 FastRCNN class loss: 0.05026 FastRCNN total loss: 0.14077 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.14146 RPN box loss: 0.00509 RPN score loss: 0.00121 RPN total loss: 0.0063 Total loss: 0.85156 timestamp: 1655069618.7016776 iteration: 78525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06648 FastRCNN class loss: 0.05095 FastRCNN total loss: 0.11743 L1 loss: 0.0000e+00 L2 loss: 0.56303 Learning rate: 0.0004 Mask loss: 0.0831 RPN box loss: 0.00893 RPN score loss: 0.00116 RPN total loss: 0.0101 Total loss: 0.77366 timestamp: 1655069622.036216 iteration: 78530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12332 FastRCNN class loss: 0.06976 FastRCNN total loss: 0.19308 L1 loss: 0.0000e+00 L2 loss: 0.56302 Learning rate: 0.0004 Mask loss: 0.14093 RPN box loss: 0.00742 RPN score loss: 0.00313 RPN total loss: 0.01056 Total loss: 0.90759 timestamp: 1655069625.2886312 iteration: 78535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0831 FastRCNN class loss: 0.0926 FastRCNN total loss: 0.1757 L1 loss: 0.0000e+00 L2 loss: 0.56302 Learning rate: 0.0004 Mask loss: 0.22496 RPN box loss: 0.01125 RPN score loss: 0.00237 RPN total loss: 0.01362 Total loss: 0.9773 timestamp: 1655069628.5692973 iteration: 78540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15376 FastRCNN class loss: 0.08218 FastRCNN total loss: 0.23594 L1 loss: 0.0000e+00 L2 loss: 0.56302 Learning rate: 0.0004 Mask loss: 0.12544 RPN box loss: 0.01721 RPN score loss: 0.00367 RPN total loss: 0.02088 Total loss: 0.94527 timestamp: 1655069631.8499908 iteration: 78545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09281 FastRCNN class loss: 0.08089 FastRCNN total loss: 0.1737 L1 loss: 0.0000e+00 L2 loss: 0.56302 Learning rate: 0.0004 Mask loss: 0.13123 RPN box loss: 0.00812 RPN score loss: 0.00387 RPN total loss: 0.01199 Total loss: 0.87994 timestamp: 1655069635.1410158 iteration: 78550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08433 FastRCNN class loss: 0.07407 FastRCNN total loss: 0.1584 L1 loss: 0.0000e+00 L2 loss: 0.56302 Learning rate: 0.0004 Mask loss: 0.16997 RPN box loss: 0.01062 RPN score loss: 0.01275 RPN total loss: 0.02337 Total loss: 0.91476 timestamp: 1655069638.3858464 iteration: 78555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12373 FastRCNN class loss: 0.10516 FastRCNN total loss: 0.2289 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.19995 RPN box loss: 0.02261 RPN score loss: 0.00979 RPN total loss: 0.0324 Total loss: 1.02426 timestamp: 1655069641.641808 iteration: 78560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09644 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.18083 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.18936 RPN box loss: 0.02695 RPN score loss: 0.01066 RPN total loss: 0.03761 Total loss: 0.97081 timestamp: 1655069644.9970427 iteration: 78565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06303 FastRCNN class loss: 0.06459 FastRCNN total loss: 0.12762 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.11908 RPN box loss: 0.00791 RPN score loss: 0.00207 RPN total loss: 0.00998 Total loss: 0.81969 timestamp: 1655069648.3175235 iteration: 78570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08933 FastRCNN class loss: 0.06337 FastRCNN total loss: 0.1527 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.11511 RPN box loss: 0.00927 RPN score loss: 0.00231 RPN total loss: 0.01158 Total loss: 0.8424 timestamp: 1655069651.6354322 iteration: 78575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13979 FastRCNN class loss: 0.08517 FastRCNN total loss: 0.22496 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.11624 RPN box loss: 0.01628 RPN score loss: 0.00718 RPN total loss: 0.02346 Total loss: 0.92766 timestamp: 1655069654.889583 iteration: 78580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06925 FastRCNN class loss: 0.07078 FastRCNN total loss: 0.14003 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.12718 RPN box loss: 0.01027 RPN score loss: 0.00231 RPN total loss: 0.01258 Total loss: 0.84279 timestamp: 1655069658.1365519 iteration: 78585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07214 FastRCNN class loss: 0.08434 FastRCNN total loss: 0.15648 L1 loss: 0.0000e+00 L2 loss: 0.56301 Learning rate: 0.0004 Mask loss: 0.13692 RPN box loss: 0.03077 RPN score loss: 0.01017 RPN total loss: 0.04094 Total loss: 0.89735 timestamp: 1655069661.402863 iteration: 78590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11546 FastRCNN class loss: 0.10018 FastRCNN total loss: 0.21564 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.1945 RPN box loss: 0.01178 RPN score loss: 0.00306 RPN total loss: 0.01485 Total loss: 0.98798 timestamp: 1655069664.7147865 iteration: 78595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08977 FastRCNN class loss: 0.07499 FastRCNN total loss: 0.16477 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.16134 RPN box loss: 0.01368 RPN score loss: 0.00648 RPN total loss: 0.02017 Total loss: 0.90927 timestamp: 1655069667.9569407 iteration: 78600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11315 FastRCNN class loss: 0.11041 FastRCNN total loss: 0.22356 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.17378 RPN box loss: 0.01836 RPN score loss: 0.01581 RPN total loss: 0.03417 Total loss: 0.99451 timestamp: 1655069671.205443 iteration: 78605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06767 FastRCNN class loss: 0.08 FastRCNN total loss: 0.14768 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.14019 RPN box loss: 0.00885 RPN score loss: 0.00778 RPN total loss: 0.01663 Total loss: 0.86749 timestamp: 1655069674.4640968 iteration: 78610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.068 FastRCNN class loss: 0.04294 FastRCNN total loss: 0.11094 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.14945 RPN box loss: 0.00548 RPN score loss: 0.00663 RPN total loss: 0.01211 Total loss: 0.83549 timestamp: 1655069677.7594693 iteration: 78615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08571 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.15145 L1 loss: 0.0000e+00 L2 loss: 0.563 Learning rate: 0.0004 Mask loss: 0.14018 RPN box loss: 0.02184 RPN score loss: 0.01106 RPN total loss: 0.03289 Total loss: 0.88752 timestamp: 1655069681.0216436 iteration: 78620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06976 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.13209 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.10553 RPN box loss: 0.01058 RPN score loss: 0.00866 RPN total loss: 0.01925 Total loss: 0.81986 timestamp: 1655069684.2602875 iteration: 78625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07954 FastRCNN class loss: 0.05586 FastRCNN total loss: 0.13539 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.16385 RPN box loss: 0.00643 RPN score loss: 0.00442 RPN total loss: 0.01085 Total loss: 0.87309 timestamp: 1655069687.5250854 iteration: 78630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07997 FastRCNN class loss: 0.04403 FastRCNN total loss: 0.12401 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.10194 RPN box loss: 0.00622 RPN score loss: 0.00248 RPN total loss: 0.0087 Total loss: 0.79764 timestamp: 1655069690.8140788 iteration: 78635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12892 FastRCNN class loss: 0.09489 FastRCNN total loss: 0.2238 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.15545 RPN box loss: 0.04798 RPN score loss: 0.0171 RPN total loss: 0.06508 Total loss: 1.00731 timestamp: 1655069694.0483859 iteration: 78640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11166 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.19354 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.13132 RPN box loss: 0.00833 RPN score loss: 0.00381 RPN total loss: 0.01213 Total loss: 0.89998 timestamp: 1655069697.3525074 iteration: 78645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05595 FastRCNN class loss: 0.05546 FastRCNN total loss: 0.11141 L1 loss: 0.0000e+00 L2 loss: 0.56299 Learning rate: 0.0004 Mask loss: 0.1215 RPN box loss: 0.0084 RPN score loss: 0.00874 RPN total loss: 0.01714 Total loss: 0.81304 timestamp: 1655069700.6956909 iteration: 78650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.17321 L1 loss: 0.0000e+00 L2 loss: 0.56298 Learning rate: 0.0004 Mask loss: 0.132 RPN box loss: 0.01544 RPN score loss: 0.0069 RPN total loss: 0.02233 Total loss: 0.89053 timestamp: 1655069703.9858022 iteration: 78655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09502 FastRCNN class loss: 0.0905 FastRCNN total loss: 0.18553 L1 loss: 0.0000e+00 L2 loss: 0.56298 Learning rate: 0.0004 Mask loss: 0.17145 RPN box loss: 0.01291 RPN score loss: 0.00299 RPN total loss: 0.0159 Total loss: 0.93586 timestamp: 1655069707.255247 iteration: 78660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15857 FastRCNN class loss: 0.16286 FastRCNN total loss: 0.32144 L1 loss: 0.0000e+00 L2 loss: 0.56298 Learning rate: 0.0004 Mask loss: 0.19041 RPN box loss: 0.01234 RPN score loss: 0.01383 RPN total loss: 0.02618 Total loss: 1.101 timestamp: 1655069710.509773 iteration: 78665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06764 FastRCNN class loss: 0.04693 FastRCNN total loss: 0.11457 L1 loss: 0.0000e+00 L2 loss: 0.56298 Learning rate: 0.0004 Mask loss: 0.1133 RPN box loss: 0.00621 RPN score loss: 0.00325 RPN total loss: 0.00947 Total loss: 0.80031 timestamp: 1655069713.8205159 iteration: 78670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10763 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.19006 L1 loss: 0.0000e+00 L2 loss: 0.56298 Learning rate: 0.0004 Mask loss: 0.16582 RPN box loss: 0.01174 RPN score loss: 0.00797 RPN total loss: 0.01971 Total loss: 0.93857 timestamp: 1655069717.0749762 iteration: 78675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09072 FastRCNN class loss: 0.05997 FastRCNN total loss: 0.15069 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.13465 RPN box loss: 0.00629 RPN score loss: 0.00516 RPN total loss: 0.01146 Total loss: 0.85977 timestamp: 1655069720.381565 iteration: 78680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09123 FastRCNN class loss: 0.03813 FastRCNN total loss: 0.12936 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.08883 RPN box loss: 0.00511 RPN score loss: 0.00195 RPN total loss: 0.00706 Total loss: 0.78822 timestamp: 1655069723.6887565 iteration: 78685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12685 FastRCNN class loss: 0.12764 FastRCNN total loss: 0.25449 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.14553 RPN box loss: 0.01127 RPN score loss: 0.00431 RPN total loss: 0.01558 Total loss: 0.97858 timestamp: 1655069726.9745643 iteration: 78690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04872 FastRCNN class loss: 0.05245 FastRCNN total loss: 0.10116 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.13931 RPN box loss: 0.00629 RPN score loss: 0.00096 RPN total loss: 0.00725 Total loss: 0.8107 timestamp: 1655069730.241252 iteration: 78695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10594 FastRCNN class loss: 0.05281 FastRCNN total loss: 0.15875 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.15233 RPN box loss: 0.01574 RPN score loss: 0.0028 RPN total loss: 0.01854 Total loss: 0.89258 timestamp: 1655069733.4535482 iteration: 78700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11445 FastRCNN class loss: 0.0688 FastRCNN total loss: 0.18325 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.15846 RPN box loss: 0.01812 RPN score loss: 0.0029 RPN total loss: 0.02102 Total loss: 0.92569 timestamp: 1655069736.767279 iteration: 78705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10274 FastRCNN class loss: 0.06393 FastRCNN total loss: 0.16666 L1 loss: 0.0000e+00 L2 loss: 0.56297 Learning rate: 0.0004 Mask loss: 0.12633 RPN box loss: 0.01018 RPN score loss: 0.00473 RPN total loss: 0.01491 Total loss: 0.87088 timestamp: 1655069740.0404468 iteration: 78710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10993 FastRCNN class loss: 0.04323 FastRCNN total loss: 0.15317 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.11605 RPN box loss: 0.00366 RPN score loss: 0.00935 RPN total loss: 0.013 Total loss: 0.84518 timestamp: 1655069743.3325734 iteration: 78715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10362 FastRCNN class loss: 0.0756 FastRCNN total loss: 0.17922 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.15007 RPN box loss: 0.0163 RPN score loss: 0.01348 RPN total loss: 0.02979 Total loss: 0.92204 timestamp: 1655069746.6153302 iteration: 78720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13763 FastRCNN class loss: 0.08669 FastRCNN total loss: 0.22432 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.16001 RPN box loss: 0.01332 RPN score loss: 0.01068 RPN total loss: 0.02399 Total loss: 0.97129 timestamp: 1655069749.8043041 iteration: 78725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05169 FastRCNN class loss: 0.04849 FastRCNN total loss: 0.10018 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.10178 RPN box loss: 0.00692 RPN score loss: 0.00384 RPN total loss: 0.01076 Total loss: 0.77568 timestamp: 1655069753.1093671 iteration: 78730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16736 FastRCNN class loss: 0.10155 FastRCNN total loss: 0.26891 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.13083 RPN box loss: 0.02889 RPN score loss: 0.00567 RPN total loss: 0.03456 Total loss: 0.99725 timestamp: 1655069756.3476937 iteration: 78735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10051 FastRCNN class loss: 0.10233 FastRCNN total loss: 0.20284 L1 loss: 0.0000e+00 L2 loss: 0.56296 Learning rate: 0.0004 Mask loss: 0.18422 RPN box loss: 0.02541 RPN score loss: 0.00953 RPN total loss: 0.03494 Total loss: 0.98496 timestamp: 1655069759.597624 iteration: 78740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15226 FastRCNN class loss: 0.0974 FastRCNN total loss: 0.24966 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.18844 RPN box loss: 0.02871 RPN score loss: 0.00498 RPN total loss: 0.03369 Total loss: 1.03474 timestamp: 1655069762.8160396 iteration: 78745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05961 FastRCNN class loss: 0.04628 FastRCNN total loss: 0.10589 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.11945 RPN box loss: 0.00424 RPN score loss: 0.00417 RPN total loss: 0.00841 Total loss: 0.79671 timestamp: 1655069766.123368 iteration: 78750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04537 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.11761 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.15644 RPN box loss: 0.00552 RPN score loss: 0.0164 RPN total loss: 0.02191 Total loss: 0.85892 timestamp: 1655069769.3304274 iteration: 78755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07344 FastRCNN class loss: 0.07813 FastRCNN total loss: 0.15156 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.12451 RPN box loss: 0.00986 RPN score loss: 0.00155 RPN total loss: 0.01141 Total loss: 0.85044 timestamp: 1655069772.5936413 iteration: 78760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08134 FastRCNN class loss: 0.04899 FastRCNN total loss: 0.13033 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.13379 RPN box loss: 0.00679 RPN score loss: 0.00217 RPN total loss: 0.00896 Total loss: 0.83603 timestamp: 1655069775.839174 iteration: 78765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11606 FastRCNN class loss: 0.10115 FastRCNN total loss: 0.21721 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.1664 RPN box loss: 0.01608 RPN score loss: 0.00563 RPN total loss: 0.0217 Total loss: 0.96827 timestamp: 1655069779.0908885 iteration: 78770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05747 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.11208 L1 loss: 0.0000e+00 L2 loss: 0.56295 Learning rate: 0.0004 Mask loss: 0.11344 RPN box loss: 0.01021 RPN score loss: 0.00406 RPN total loss: 0.01428 Total loss: 0.80274 timestamp: 1655069782.3283575 iteration: 78775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13883 FastRCNN class loss: 0.11131 FastRCNN total loss: 0.25014 L1 loss: 0.0000e+00 L2 loss: 0.56294 Learning rate: 0.0004 Mask loss: 0.17284 RPN box loss: 0.02984 RPN score loss: 0.01145 RPN total loss: 0.04129 Total loss: 1.02721 timestamp: 1655069785.6526725 iteration: 78780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11009 FastRCNN class loss: 0.06106 FastRCNN total loss: 0.17115 L1 loss: 0.0000e+00 L2 loss: 0.56294 Learning rate: 0.0004 Mask loss: 0.10192 RPN box loss: 0.00414 RPN score loss: 0.00242 RPN total loss: 0.00656 Total loss: 0.84257 timestamp: 1655069788.8502307 iteration: 78785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0698 FastRCNN class loss: 0.0487 FastRCNN total loss: 0.11849 L1 loss: 0.0000e+00 L2 loss: 0.56294 Learning rate: 0.0004 Mask loss: 0.08594 RPN box loss: 0.01353 RPN score loss: 0.00806 RPN total loss: 0.02159 Total loss: 0.78897 timestamp: 1655069792.0808475 iteration: 78790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09711 FastRCNN class loss: 0.08155 FastRCNN total loss: 0.17866 L1 loss: 0.0000e+00 L2 loss: 0.56294 Learning rate: 0.0004 Mask loss: 0.16643 RPN box loss: 0.0252 RPN score loss: 0.01327 RPN total loss: 0.03847 Total loss: 0.9465 timestamp: 1655069795.4272923 iteration: 78795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0839 FastRCNN class loss: 0.05905 FastRCNN total loss: 0.14295 L1 loss: 0.0000e+00 L2 loss: 0.56294 Learning rate: 0.0004 Mask loss: 0.12471 RPN box loss: 0.03647 RPN score loss: 0.01229 RPN total loss: 0.04876 Total loss: 0.87935 timestamp: 1655069798.7196047 iteration: 78800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09451 FastRCNN class loss: 0.03927 FastRCNN total loss: 0.13378 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.10254 RPN box loss: 0.00387 RPN score loss: 0.00318 RPN total loss: 0.00705 Total loss: 0.80631 timestamp: 1655069801.960921 iteration: 78805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09689 FastRCNN class loss: 0.06869 FastRCNN total loss: 0.16558 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.15315 RPN box loss: 0.01109 RPN score loss: 0.0038 RPN total loss: 0.01489 Total loss: 0.89656 timestamp: 1655069805.232546 iteration: 78810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03877 FastRCNN class loss: 0.03879 FastRCNN total loss: 0.07756 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.17559 RPN box loss: 0.00704 RPN score loss: 0.00254 RPN total loss: 0.00958 Total loss: 0.82566 timestamp: 1655069808.5075095 iteration: 78815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08832 FastRCNN class loss: 0.07033 FastRCNN total loss: 0.15864 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.17892 RPN box loss: 0.01553 RPN score loss: 0.01744 RPN total loss: 0.03297 Total loss: 0.93347 timestamp: 1655069811.824294 iteration: 78820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09617 FastRCNN class loss: 0.11211 FastRCNN total loss: 0.20828 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.21343 RPN box loss: 0.0167 RPN score loss: 0.04404 RPN total loss: 0.06074 Total loss: 1.04537 timestamp: 1655069815.1004148 iteration: 78825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.07701 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.13835 RPN box loss: 0.0033 RPN score loss: 0.0008 RPN total loss: 0.00409 Total loss: 0.87553 timestamp: 1655069818.3741834 iteration: 78830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07769 FastRCNN class loss: 0.04868 FastRCNN total loss: 0.12637 L1 loss: 0.0000e+00 L2 loss: 0.56293 Learning rate: 0.0004 Mask loss: 0.14494 RPN box loss: 0.00819 RPN score loss: 0.00181 RPN total loss: 0.01 Total loss: 0.84424 timestamp: 1655069821.6087716 iteration: 78835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07311 FastRCNN class loss: 0.06486 FastRCNN total loss: 0.13797 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.15152 RPN box loss: 0.00642 RPN score loss: 0.00498 RPN total loss: 0.0114 Total loss: 0.86381 timestamp: 1655069824.919282 iteration: 78840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12257 FastRCNN class loss: 0.06273 FastRCNN total loss: 0.1853 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.14251 RPN box loss: 0.01309 RPN score loss: 0.00758 RPN total loss: 0.02068 Total loss: 0.91141 timestamp: 1655069828.2375853 iteration: 78845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0593 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.12149 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.16508 RPN box loss: 0.02171 RPN score loss: 0.00223 RPN total loss: 0.02394 Total loss: 0.87343 timestamp: 1655069831.467742 iteration: 78850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12042 FastRCNN class loss: 0.05438 FastRCNN total loss: 0.1748 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.09112 RPN box loss: 0.02083 RPN score loss: 0.00457 RPN total loss: 0.0254 Total loss: 0.85424 timestamp: 1655069834.6873991 iteration: 78855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17611 FastRCNN class loss: 0.07412 FastRCNN total loss: 0.25023 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.15127 RPN box loss: 0.01935 RPN score loss: 0.00715 RPN total loss: 0.0265 Total loss: 0.99092 timestamp: 1655069837.9183478 iteration: 78860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06431 FastRCNN class loss: 0.0525 FastRCNN total loss: 0.11681 L1 loss: 0.0000e+00 L2 loss: 0.56292 Learning rate: 0.0004 Mask loss: 0.16213 RPN box loss: 0.0112 RPN score loss: 0.00966 RPN total loss: 0.02086 Total loss: 0.86272 timestamp: 1655069841.1933987 iteration: 78865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10609 FastRCNN class loss: 0.04591 FastRCNN total loss: 0.152 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.13836 RPN box loss: 0.01181 RPN score loss: 0.0063 RPN total loss: 0.01811 Total loss: 0.87139 timestamp: 1655069844.4554558 iteration: 78870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09517 FastRCNN class loss: 0.1284 FastRCNN total loss: 0.22357 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.17372 RPN box loss: 0.0229 RPN score loss: 0.01221 RPN total loss: 0.03511 Total loss: 0.99531 timestamp: 1655069847.735246 iteration: 78875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06876 FastRCNN class loss: 0.04837 FastRCNN total loss: 0.11713 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.10299 RPN box loss: 0.01373 RPN score loss: 0.0014 RPN total loss: 0.01513 Total loss: 0.79816 timestamp: 1655069851.0323296 iteration: 78880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09363 FastRCNN class loss: 0.11927 FastRCNN total loss: 0.2129 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.16435 RPN box loss: 0.02192 RPN score loss: 0.01586 RPN total loss: 0.03778 Total loss: 0.97794 timestamp: 1655069854.215421 iteration: 78885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.05247 FastRCNN total loss: 0.12621 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.11074 RPN box loss: 0.01111 RPN score loss: 0.00701 RPN total loss: 0.01812 Total loss: 0.81798 timestamp: 1655069857.5163693 iteration: 78890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08385 FastRCNN class loss: 0.06163 FastRCNN total loss: 0.14549 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.1522 RPN box loss: 0.00994 RPN score loss: 0.00558 RPN total loss: 0.01552 Total loss: 0.87611 timestamp: 1655069860.7799704 iteration: 78895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10734 FastRCNN class loss: 0.04774 FastRCNN total loss: 0.15507 L1 loss: 0.0000e+00 L2 loss: 0.56291 Learning rate: 0.0004 Mask loss: 0.14065 RPN box loss: 0.03656 RPN score loss: 0.00627 RPN total loss: 0.04284 Total loss: 0.90146 timestamp: 1655069864.1826913 iteration: 78900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04924 FastRCNN class loss: 0.05235 FastRCNN total loss: 0.1016 L1 loss: 0.0000e+00 L2 loss: 0.5629 Learning rate: 0.0004 Mask loss: 0.10901 RPN box loss: 0.0072 RPN score loss: 0.0028 RPN total loss: 0.01 Total loss: 0.7835 timestamp: 1655069867.4077547 iteration: 78905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09156 FastRCNN class loss: 0.09352 FastRCNN total loss: 0.18509 L1 loss: 0.0000e+00 L2 loss: 0.5629 Learning rate: 0.0004 Mask loss: 0.14193 RPN box loss: 0.00901 RPN score loss: 0.00578 RPN total loss: 0.0148 Total loss: 0.90471 timestamp: 1655069870.6558626 iteration: 78910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12423 FastRCNN class loss: 0.12198 FastRCNN total loss: 0.24621 L1 loss: 0.0000e+00 L2 loss: 0.5629 Learning rate: 0.0004 Mask loss: 0.17931 RPN box loss: 0.03989 RPN score loss: 0.02205 RPN total loss: 0.06194 Total loss: 1.05036 timestamp: 1655069873.9035916 iteration: 78915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16879 FastRCNN class loss: 0.06444 FastRCNN total loss: 0.23324 L1 loss: 0.0000e+00 L2 loss: 0.5629 Learning rate: 0.0004 Mask loss: 0.15749 RPN box loss: 0.01104 RPN score loss: 0.00298 RPN total loss: 0.01402 Total loss: 0.96764 timestamp: 1655069877.2158666 iteration: 78920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09656 FastRCNN class loss: 0.09215 FastRCNN total loss: 0.1887 L1 loss: 0.0000e+00 L2 loss: 0.5629 Learning rate: 0.0004 Mask loss: 0.14146 RPN box loss: 0.00961 RPN score loss: 0.00662 RPN total loss: 0.01623 Total loss: 0.90928 timestamp: 1655069880.487884 iteration: 78925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0509 FastRCNN class loss: 0.04378 FastRCNN total loss: 0.09468 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.0946 RPN box loss: 0.00315 RPN score loss: 0.00455 RPN total loss: 0.0077 Total loss: 0.75987 timestamp: 1655069883.7186363 iteration: 78930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09058 FastRCNN class loss: 0.07172 FastRCNN total loss: 0.1623 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.10279 RPN box loss: 0.01378 RPN score loss: 0.00219 RPN total loss: 0.01597 Total loss: 0.84395 timestamp: 1655069886.9495661 iteration: 78935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14109 FastRCNN class loss: 0.127 FastRCNN total loss: 0.26809 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.23007 RPN box loss: 0.0145 RPN score loss: 0.01795 RPN total loss: 0.03245 Total loss: 1.09349 timestamp: 1655069890.2105067 iteration: 78940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06954 FastRCNN class loss: 0.11185 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.13811 RPN box loss: 0.01689 RPN score loss: 0.00433 RPN total loss: 0.02122 Total loss: 0.90361 timestamp: 1655069893.546419 iteration: 78945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0984 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.18286 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.26163 RPN box loss: 0.01069 RPN score loss: 0.00428 RPN total loss: 0.01497 Total loss: 1.02235 timestamp: 1655069896.804026 iteration: 78950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10328 FastRCNN class loss: 0.08861 FastRCNN total loss: 0.19188 L1 loss: 0.0000e+00 L2 loss: 0.56289 Learning rate: 0.0004 Mask loss: 0.12134 RPN box loss: 0.00793 RPN score loss: 0.00785 RPN total loss: 0.01578 Total loss: 0.89189 timestamp: 1655069900.0330057 iteration: 78955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08969 FastRCNN class loss: 0.07198 FastRCNN total loss: 0.16167 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.12674 RPN box loss: 0.00808 RPN score loss: 0.00877 RPN total loss: 0.01685 Total loss: 0.86815 timestamp: 1655069903.3089805 iteration: 78960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12046 FastRCNN class loss: 0.09551 FastRCNN total loss: 0.21596 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.1464 RPN box loss: 0.00971 RPN score loss: 0.00357 RPN total loss: 0.01328 Total loss: 0.93853 timestamp: 1655069906.5856452 iteration: 78965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0957 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.14534 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.15201 RPN box loss: 0.04154 RPN score loss: 0.0014 RPN total loss: 0.04294 Total loss: 0.90318 timestamp: 1655069909.8808198 iteration: 78970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08593 FastRCNN class loss: 0.06619 FastRCNN total loss: 0.15212 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.13784 RPN box loss: 0.01554 RPN score loss: 0.00149 RPN total loss: 0.01703 Total loss: 0.86987 timestamp: 1655069913.1300845 iteration: 78975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10408 FastRCNN class loss: 0.10626 FastRCNN total loss: 0.21033 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.16014 RPN box loss: 0.01117 RPN score loss: 0.00519 RPN total loss: 0.01635 Total loss: 0.94971 timestamp: 1655069916.5010798 iteration: 78980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08429 FastRCNN class loss: 0.04139 FastRCNN total loss: 0.12567 L1 loss: 0.0000e+00 L2 loss: 0.56288 Learning rate: 0.0004 Mask loss: 0.09636 RPN box loss: 0.00828 RPN score loss: 0.00098 RPN total loss: 0.00927 Total loss: 0.79417 timestamp: 1655069919.729546 iteration: 78985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09253 FastRCNN class loss: 0.04759 FastRCNN total loss: 0.14012 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.09907 RPN box loss: 0.00805 RPN score loss: 0.00206 RPN total loss: 0.01011 Total loss: 0.81218 timestamp: 1655069923.0182185 iteration: 78990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08918 FastRCNN class loss: 0.06744 FastRCNN total loss: 0.15662 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.12397 RPN box loss: 0.013 RPN score loss: 0.01118 RPN total loss: 0.02418 Total loss: 0.86764 timestamp: 1655069926.2511086 iteration: 78995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0683 FastRCNN class loss: 0.06495 FastRCNN total loss: 0.13325 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.12352 RPN box loss: 0.02132 RPN score loss: 0.00965 RPN total loss: 0.03098 Total loss: 0.85062 timestamp: 1655069929.5545795 iteration: 79000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08765 FastRCNN class loss: 0.02976 FastRCNN total loss: 0.11741 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.11466 RPN box loss: 0.02517 RPN score loss: 0.00195 RPN total loss: 0.02712 Total loss: 0.82207 timestamp: 1655069932.824733 iteration: 79005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13645 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.21026 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.15858 RPN box loss: 0.00804 RPN score loss: 0.00581 RPN total loss: 0.01385 Total loss: 0.94555 timestamp: 1655069936.068717 iteration: 79010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10688 FastRCNN class loss: 0.08172 FastRCNN total loss: 0.1886 L1 loss: 0.0000e+00 L2 loss: 0.56287 Learning rate: 0.0004 Mask loss: 0.10936 RPN box loss: 0.01066 RPN score loss: 0.0024 RPN total loss: 0.01307 Total loss: 0.87389 timestamp: 1655069939.2634919 iteration: 79015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0796 FastRCNN class loss: 0.07924 FastRCNN total loss: 0.15884 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.17704 RPN box loss: 0.01223 RPN score loss: 0.00139 RPN total loss: 0.01362 Total loss: 0.91237 timestamp: 1655069942.4709306 iteration: 79020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06844 FastRCNN class loss: 0.05737 FastRCNN total loss: 0.1258 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.14408 RPN box loss: 0.01116 RPN score loss: 0.00544 RPN total loss: 0.0166 Total loss: 0.84935 timestamp: 1655069945.730792 iteration: 79025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06987 FastRCNN class loss: 0.08226 FastRCNN total loss: 0.15212 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.1363 RPN box loss: 0.01169 RPN score loss: 0.00653 RPN total loss: 0.01821 Total loss: 0.8695 timestamp: 1655069948.983027 iteration: 79030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05348 FastRCNN class loss: 0.03964 FastRCNN total loss: 0.09312 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.11006 RPN box loss: 0.00793 RPN score loss: 0.00201 RPN total loss: 0.00994 Total loss: 0.77598 timestamp: 1655069952.2478535 iteration: 79035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14446 FastRCNN class loss: 0.1311 FastRCNN total loss: 0.27556 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.2411 RPN box loss: 0.02057 RPN score loss: 0.00805 RPN total loss: 0.02862 Total loss: 1.10814 timestamp: 1655069955.5278656 iteration: 79040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15714 FastRCNN class loss: 0.14751 FastRCNN total loss: 0.30465 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.19 RPN box loss: 0.0137 RPN score loss: 0.00922 RPN total loss: 0.02292 Total loss: 1.08043 timestamp: 1655069958.7507834 iteration: 79045 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12523 FastRCNN class loss: 0.08427 FastRCNN total loss: 0.2095 L1 loss: 0.0000e+00 L2 loss: 0.56286 Learning rate: 0.0004 Mask loss: 0.15128 RPN box loss: 0.02169 RPN score loss: 0.00778 RPN total loss: 0.02948 Total loss: 0.95311 timestamp: 1655069962.04352 iteration: 79050 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11828 FastRCNN class loss: 0.08938 FastRCNN total loss: 0.20767 L1 loss: 0.0000e+00 L2 loss: 0.56285 Learning rate: 0.0004 Mask loss: 0.18606 RPN box loss: 0.01685 RPN score loss: 0.00575 RPN total loss: 0.02261 Total loss: 0.97919 timestamp: 1655069965.2473862 iteration: 79055 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06729 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.13717 L1 loss: 0.0000e+00 L2 loss: 0.56285 Learning rate: 0.0004 Mask loss: 0.13506 RPN box loss: 0.00727 RPN score loss: 0.00181 RPN total loss: 0.00908 Total loss: 0.84415 timestamp: 1655069968.5562432 iteration: 79060 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14482 FastRCNN class loss: 0.10599 FastRCNN total loss: 0.25081 L1 loss: 0.0000e+00 L2 loss: 0.56285 Learning rate: 0.0004 Mask loss: 0.12138 RPN box loss: 0.00834 RPN score loss: 0.00878 RPN total loss: 0.01712 Total loss: 0.95216 timestamp: 1655069971.8886604 iteration: 79065 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09146 FastRCNN class loss: 0.05245 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.56285 Learning rate: 0.0004 Mask loss: 0.11742 RPN box loss: 0.01946 RPN score loss: 0.00639 RPN total loss: 0.02585 Total loss: 0.85002 timestamp: 1655069975.1522677 iteration: 79070 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06836 FastRCNN class loss: 0.06394 FastRCNN total loss: 0.1323 L1 loss: 0.0000e+00 L2 loss: 0.56285 Learning rate: 0.0004 Mask loss: 0.10911 RPN box loss: 0.01625 RPN score loss: 0.00177 RPN total loss: 0.01802 Total loss: 0.82227 timestamp: 1655069978.4592414 iteration: 79075 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14453 FastRCNN class loss: 0.07971 FastRCNN total loss: 0.22423 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.14732 RPN box loss: 0.01117 RPN score loss: 0.00496 RPN total loss: 0.01613 Total loss: 0.95052 timestamp: 1655069981.7453656 iteration: 79080 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0739 FastRCNN class loss: 0.05109 FastRCNN total loss: 0.12498 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.10223 RPN box loss: 0.00701 RPN score loss: 0.01081 RPN total loss: 0.01782 Total loss: 0.80788 timestamp: 1655069985.0333507 iteration: 79085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12469 FastRCNN class loss: 0.05558 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.14741 RPN box loss: 0.00988 RPN score loss: 0.0028 RPN total loss: 0.01268 Total loss: 0.9032 timestamp: 1655069988.2852783 iteration: 79090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05073 FastRCNN class loss: 0.0382 FastRCNN total loss: 0.08893 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.12827 RPN box loss: 0.01518 RPN score loss: 0.00097 RPN total loss: 0.01615 Total loss: 0.79619 timestamp: 1655069991.5337925 iteration: 79095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07938 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.12917 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.08183 RPN box loss: 0.01618 RPN score loss: 0.00114 RPN total loss: 0.01732 Total loss: 0.79116 timestamp: 1655069994.7899542 iteration: 79100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04452 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.09967 L1 loss: 0.0000e+00 L2 loss: 0.56284 Learning rate: 0.0004 Mask loss: 0.0901 RPN box loss: 0.00705 RPN score loss: 0.001 RPN total loss: 0.00805 Total loss: 0.76065 timestamp: 1655069998.0544496 iteration: 79105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09895 FastRCNN class loss: 0.07212 FastRCNN total loss: 0.17106 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.14097 RPN box loss: 0.04409 RPN score loss: 0.00972 RPN total loss: 0.05381 Total loss: 0.92868 timestamp: 1655070001.3763003 iteration: 79110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09186 FastRCNN class loss: 0.11504 FastRCNN total loss: 0.2069 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.14699 RPN box loss: 0.04934 RPN score loss: 0.01512 RPN total loss: 0.06446 Total loss: 0.98119 timestamp: 1655070004.682227 iteration: 79115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.07874 FastRCNN total loss: 0.17913 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.12761 RPN box loss: 0.01357 RPN score loss: 0.00602 RPN total loss: 0.01959 Total loss: 0.88917 timestamp: 1655070007.9490955 iteration: 79120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07713 FastRCNN class loss: 0.05633 FastRCNN total loss: 0.13346 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.12296 RPN box loss: 0.02015 RPN score loss: 0.0077 RPN total loss: 0.02785 Total loss: 0.84711 timestamp: 1655070011.1765652 iteration: 79125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08125 FastRCNN class loss: 0.03994 FastRCNN total loss: 0.12119 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.11064 RPN box loss: 0.00983 RPN score loss: 0.00527 RPN total loss: 0.0151 Total loss: 0.80976 timestamp: 1655070014.4380581 iteration: 79130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09071 FastRCNN class loss: 0.09014 FastRCNN total loss: 0.18085 L1 loss: 0.0000e+00 L2 loss: 0.56283 Learning rate: 0.0004 Mask loss: 0.18885 RPN box loss: 0.00921 RPN score loss: 0.00924 RPN total loss: 0.01844 Total loss: 0.95096 timestamp: 1655070017.6909752 iteration: 79135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08814 FastRCNN class loss: 0.05373 FastRCNN total loss: 0.14187 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.13589 RPN box loss: 0.01359 RPN score loss: 0.00908 RPN total loss: 0.02267 Total loss: 0.86325 timestamp: 1655070020.964626 iteration: 79140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09275 FastRCNN class loss: 0.07369 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.11859 RPN box loss: 0.01041 RPN score loss: 0.00252 RPN total loss: 0.01293 Total loss: 0.86078 timestamp: 1655070024.1843157 iteration: 79145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07558 FastRCNN class loss: 0.06735 FastRCNN total loss: 0.14293 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.17707 RPN box loss: 0.05319 RPN score loss: 0.00801 RPN total loss: 0.06119 Total loss: 0.94402 timestamp: 1655070027.5117056 iteration: 79150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09203 FastRCNN class loss: 0.06596 FastRCNN total loss: 0.15798 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.20247 RPN box loss: 0.00892 RPN score loss: 0.00971 RPN total loss: 0.01863 Total loss: 0.9419 timestamp: 1655070030.7122285 iteration: 79155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09348 FastRCNN class loss: 0.06827 FastRCNN total loss: 0.16174 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.13946 RPN box loss: 0.00562 RPN score loss: 0.00124 RPN total loss: 0.00687 Total loss: 0.87089 timestamp: 1655070034.0593536 iteration: 79160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06783 FastRCNN class loss: 0.0636 FastRCNN total loss: 0.13143 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.14938 RPN box loss: 0.00625 RPN score loss: 0.00197 RPN total loss: 0.00822 Total loss: 0.85185 timestamp: 1655070037.3690026 iteration: 79165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10733 FastRCNN class loss: 0.06056 FastRCNN total loss: 0.16789 L1 loss: 0.0000e+00 L2 loss: 0.56282 Learning rate: 0.0004 Mask loss: 0.1531 RPN box loss: 0.01326 RPN score loss: 0.01987 RPN total loss: 0.03313 Total loss: 0.91694 timestamp: 1655070040.6074312 iteration: 79170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0782 FastRCNN class loss: 0.04678 FastRCNN total loss: 0.12497 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.07137 RPN box loss: 0.00699 RPN score loss: 0.0037 RPN total loss: 0.01068 Total loss: 0.76984 timestamp: 1655070043.8486402 iteration: 79175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09643 FastRCNN class loss: 0.05659 FastRCNN total loss: 0.15302 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.08461 RPN box loss: 0.024 RPN score loss: 0.00387 RPN total loss: 0.02787 Total loss: 0.82832 timestamp: 1655070047.1829417 iteration: 79180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07079 FastRCNN class loss: 0.07285 FastRCNN total loss: 0.14365 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.09569 RPN box loss: 0.0083 RPN score loss: 0.00466 RPN total loss: 0.01297 Total loss: 0.81511 timestamp: 1655070050.4802046 iteration: 79185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09463 FastRCNN class loss: 0.065 FastRCNN total loss: 0.15963 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.16712 RPN box loss: 0.02842 RPN score loss: 0.00798 RPN total loss: 0.03639 Total loss: 0.92595 timestamp: 1655070053.812626 iteration: 79190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05916 FastRCNN class loss: 0.06396 FastRCNN total loss: 0.12311 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.15257 RPN box loss: 0.00579 RPN score loss: 0.00235 RPN total loss: 0.00814 Total loss: 0.84663 timestamp: 1655070057.0803976 iteration: 79195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05131 FastRCNN class loss: 0.04704 FastRCNN total loss: 0.09835 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.13619 RPN box loss: 0.01174 RPN score loss: 0.00605 RPN total loss: 0.0178 Total loss: 0.81515 timestamp: 1655070060.362518 iteration: 79200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14763 FastRCNN class loss: 0.19141 FastRCNN total loss: 0.33904 L1 loss: 0.0000e+00 L2 loss: 0.56281 Learning rate: 0.0004 Mask loss: 0.13369 RPN box loss: 0.01716 RPN score loss: 0.00251 RPN total loss: 0.01967 Total loss: 1.05521 timestamp: 1655070063.5999346 iteration: 79205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10209 FastRCNN class loss: 0.0639 FastRCNN total loss: 0.16599 L1 loss: 0.0000e+00 L2 loss: 0.5628 Learning rate: 0.0004 Mask loss: 0.13589 RPN box loss: 0.02801 RPN score loss: 0.00418 RPN total loss: 0.03219 Total loss: 0.89688 timestamp: 1655070066.8448477 iteration: 79210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05759 FastRCNN class loss: 0.03528 FastRCNN total loss: 0.09287 L1 loss: 0.0000e+00 L2 loss: 0.5628 Learning rate: 0.0004 Mask loss: 0.07498 RPN box loss: 0.00599 RPN score loss: 0.00381 RPN total loss: 0.00981 Total loss: 0.74046 timestamp: 1655070070.1207037 iteration: 79215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09235 FastRCNN class loss: 0.06499 FastRCNN total loss: 0.15734 L1 loss: 0.0000e+00 L2 loss: 0.5628 Learning rate: 0.0004 Mask loss: 0.1013 RPN box loss: 0.0092 RPN score loss: 0.00491 RPN total loss: 0.01411 Total loss: 0.83555 timestamp: 1655070073.399455 iteration: 79220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11954 FastRCNN class loss: 0.0566 FastRCNN total loss: 0.17614 L1 loss: 0.0000e+00 L2 loss: 0.5628 Learning rate: 0.0004 Mask loss: 0.13305 RPN box loss: 0.015 RPN score loss: 0.00158 RPN total loss: 0.01658 Total loss: 0.88858 timestamp: 1655070076.641958 iteration: 79225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07247 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.13822 L1 loss: 0.0000e+00 L2 loss: 0.5628 Learning rate: 0.0004 Mask loss: 0.13818 RPN box loss: 0.00906 RPN score loss: 0.00263 RPN total loss: 0.01168 Total loss: 0.85088 timestamp: 1655070079.9329991 iteration: 79230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08617 FastRCNN class loss: 0.06408 FastRCNN total loss: 0.15025 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.11336 RPN box loss: 0.01307 RPN score loss: 0.00722 RPN total loss: 0.0203 Total loss: 0.84671 timestamp: 1655070083.253997 iteration: 79235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08513 FastRCNN class loss: 0.05078 FastRCNN total loss: 0.13591 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.12201 RPN box loss: 0.00528 RPN score loss: 0.00292 RPN total loss: 0.0082 Total loss: 0.82891 timestamp: 1655070086.5675247 iteration: 79240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.106 FastRCNN class loss: 0.12968 FastRCNN total loss: 0.23568 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.22531 RPN box loss: 0.01967 RPN score loss: 0.0304 RPN total loss: 0.05007 Total loss: 1.07385 timestamp: 1655070089.8231804 iteration: 79245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13912 FastRCNN class loss: 0.07781 FastRCNN total loss: 0.21693 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.15526 RPN box loss: 0.02075 RPN score loss: 0.00585 RPN total loss: 0.0266 Total loss: 0.96158 timestamp: 1655070093.104865 iteration: 79250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10227 FastRCNN class loss: 0.08544 FastRCNN total loss: 0.18771 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.13333 RPN box loss: 0.0384 RPN score loss: 0.01089 RPN total loss: 0.04928 Total loss: 0.93311 timestamp: 1655070096.3458273 iteration: 79255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06739 FastRCNN class loss: 0.04641 FastRCNN total loss: 0.1138 L1 loss: 0.0000e+00 L2 loss: 0.56279 Learning rate: 0.0004 Mask loss: 0.16909 RPN box loss: 0.00679 RPN score loss: 0.00713 RPN total loss: 0.01392 Total loss: 0.85959 timestamp: 1655070099.6034873 iteration: 79260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11044 FastRCNN class loss: 0.07916 FastRCNN total loss: 0.18961 L1 loss: 0.0000e+00 L2 loss: 0.56278 Learning rate: 0.0004 Mask loss: 0.16857 RPN box loss: 0.00909 RPN score loss: 0.00774 RPN total loss: 0.01682 Total loss: 0.93778 timestamp: 1655070102.904008 iteration: 79265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11777 FastRCNN class loss: 0.08063 FastRCNN total loss: 0.1984 L1 loss: 0.0000e+00 L2 loss: 0.56278 Learning rate: 0.0004 Mask loss: 0.18115 RPN box loss: 0.01673 RPN score loss: 0.01619 RPN total loss: 0.03292 Total loss: 0.97524 timestamp: 1655070106.179162 iteration: 79270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04991 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.11688 L1 loss: 0.0000e+00 L2 loss: 0.56278 Learning rate: 0.0004 Mask loss: 0.12916 RPN box loss: 0.01497 RPN score loss: 0.00287 RPN total loss: 0.01784 Total loss: 0.82666 timestamp: 1655070109.485768 iteration: 79275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07263 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.13529 L1 loss: 0.0000e+00 L2 loss: 0.56278 Learning rate: 0.0004 Mask loss: 0.0918 RPN box loss: 0.01163 RPN score loss: 0.0019 RPN total loss: 0.01353 Total loss: 0.80339 timestamp: 1655070112.8018563 iteration: 79280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08361 FastRCNN class loss: 0.06028 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.56278 Learning rate: 0.0004 Mask loss: 0.12232 RPN box loss: 0.01866 RPN score loss: 0.00221 RPN total loss: 0.02088 Total loss: 0.84987 timestamp: 1655070116.1539254 iteration: 79285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13867 FastRCNN class loss: 0.07796 FastRCNN total loss: 0.21663 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.12912 RPN box loss: 0.0088 RPN score loss: 0.00524 RPN total loss: 0.01404 Total loss: 0.92257 timestamp: 1655070119.470268 iteration: 79290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09142 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.15777 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.11316 RPN box loss: 0.00369 RPN score loss: 0.00329 RPN total loss: 0.00698 Total loss: 0.84068 timestamp: 1655070122.7408473 iteration: 79295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06369 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.11855 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.11151 RPN box loss: 0.00794 RPN score loss: 0.00514 RPN total loss: 0.01309 Total loss: 0.80591 timestamp: 1655070125.9867327 iteration: 79300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06738 FastRCNN class loss: 0.10627 FastRCNN total loss: 0.17365 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.1363 RPN box loss: 0.02081 RPN score loss: 0.00419 RPN total loss: 0.025 Total loss: 0.89771 timestamp: 1655070129.2380688 iteration: 79305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07674 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.14791 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.13257 RPN box loss: 0.00528 RPN score loss: 0.00169 RPN total loss: 0.00696 Total loss: 0.85021 timestamp: 1655070132.506475 iteration: 79310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05058 FastRCNN class loss: 0.04157 FastRCNN total loss: 0.09215 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.11285 RPN box loss: 0.01402 RPN score loss: 0.00715 RPN total loss: 0.02117 Total loss: 0.78894 timestamp: 1655070135.7746024 iteration: 79315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12399 FastRCNN class loss: 0.09978 FastRCNN total loss: 0.22377 L1 loss: 0.0000e+00 L2 loss: 0.56277 Learning rate: 0.0004 Mask loss: 0.17183 RPN box loss: 0.01411 RPN score loss: 0.01149 RPN total loss: 0.0256 Total loss: 0.98396 timestamp: 1655070139.1121407 iteration: 79320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10953 FastRCNN class loss: 0.04956 FastRCNN total loss: 0.15909 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.13325 RPN box loss: 0.00252 RPN score loss: 0.00443 RPN total loss: 0.00695 Total loss: 0.86205 timestamp: 1655070142.3017373 iteration: 79325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06488 FastRCNN class loss: 0.06125 FastRCNN total loss: 0.12613 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.21687 RPN box loss: 0.0053 RPN score loss: 0.00899 RPN total loss: 0.01429 Total loss: 0.92006 timestamp: 1655070145.543061 iteration: 79330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0807 FastRCNN class loss: 0.06382 FastRCNN total loss: 0.14453 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.12318 RPN box loss: 0.01519 RPN score loss: 0.00746 RPN total loss: 0.02265 Total loss: 0.85311 timestamp: 1655070148.8854475 iteration: 79335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10817 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.18012 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.08204 RPN box loss: 0.01193 RPN score loss: 0.01478 RPN total loss: 0.02671 Total loss: 0.85163 timestamp: 1655070152.180048 iteration: 79340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1033 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.16265 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.15572 RPN box loss: 0.0113 RPN score loss: 0.00817 RPN total loss: 0.01947 Total loss: 0.90059 timestamp: 1655070155.3937662 iteration: 79345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09289 FastRCNN class loss: 0.0858 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.16288 RPN box loss: 0.01291 RPN score loss: 0.00781 RPN total loss: 0.02072 Total loss: 0.92505 timestamp: 1655070158.6855793 iteration: 79350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12099 FastRCNN class loss: 0.06581 FastRCNN total loss: 0.1868 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.11915 RPN box loss: 0.01698 RPN score loss: 0.00209 RPN total loss: 0.01907 Total loss: 0.88777 timestamp: 1655070161.9914527 iteration: 79355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10265 FastRCNN class loss: 0.11594 FastRCNN total loss: 0.21859 L1 loss: 0.0000e+00 L2 loss: 0.56276 Learning rate: 0.0004 Mask loss: 0.20202 RPN box loss: 0.01863 RPN score loss: 0.01241 RPN total loss: 0.03104 Total loss: 1.0144 timestamp: 1655070165.211755 iteration: 79360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09794 FastRCNN class loss: 0.05701 FastRCNN total loss: 0.15495 L1 loss: 0.0000e+00 L2 loss: 0.56275 Learning rate: 0.0004 Mask loss: 0.07791 RPN box loss: 0.00702 RPN score loss: 0.00635 RPN total loss: 0.01338 Total loss: 0.80899 timestamp: 1655070168.465538 iteration: 79365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07724 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.1555 L1 loss: 0.0000e+00 L2 loss: 0.56275 Learning rate: 0.0004 Mask loss: 0.14613 RPN box loss: 0.01068 RPN score loss: 0.00365 RPN total loss: 0.01433 Total loss: 0.87871 timestamp: 1655070171.73424 iteration: 79370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07537 FastRCNN class loss: 0.05976 FastRCNN total loss: 0.13514 L1 loss: 0.0000e+00 L2 loss: 0.56275 Learning rate: 0.0004 Mask loss: 0.16732 RPN box loss: 0.03075 RPN score loss: 0.00911 RPN total loss: 0.03986 Total loss: 0.90508 timestamp: 1655070175.047789 iteration: 79375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09349 FastRCNN class loss: 0.09449 FastRCNN total loss: 0.18798 L1 loss: 0.0000e+00 L2 loss: 0.56275 Learning rate: 0.0004 Mask loss: 0.14579 RPN box loss: 0.00981 RPN score loss: 0.00644 RPN total loss: 0.01625 Total loss: 0.91277 timestamp: 1655070178.3359084 iteration: 79380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15935 FastRCNN class loss: 0.08678 FastRCNN total loss: 0.24614 L1 loss: 0.0000e+00 L2 loss: 0.56275 Learning rate: 0.0004 Mask loss: 0.1438 RPN box loss: 0.01726 RPN score loss: 0.01066 RPN total loss: 0.02791 Total loss: 0.98059 timestamp: 1655070181.6563272 iteration: 79385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05792 FastRCNN class loss: 0.07417 FastRCNN total loss: 0.13209 L1 loss: 0.0000e+00 L2 loss: 0.56274 Learning rate: 0.0004 Mask loss: 0.13464 RPN box loss: 0.01332 RPN score loss: 0.0032 RPN total loss: 0.01652 Total loss: 0.846 timestamp: 1655070184.9238908 iteration: 79390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08951 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.14983 L1 loss: 0.0000e+00 L2 loss: 0.56274 Learning rate: 0.0004 Mask loss: 0.12352 RPN box loss: 0.00919 RPN score loss: 0.00133 RPN total loss: 0.01052 Total loss: 0.84661 timestamp: 1655070188.0996838 iteration: 79395 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11814 FastRCNN class loss: 0.08914 FastRCNN total loss: 0.20728 L1 loss: 0.0000e+00 L2 loss: 0.56274 Learning rate: 0.0004 Mask loss: 0.14256 RPN box loss: 0.0164 RPN score loss: 0.02018 RPN total loss: 0.03658 Total loss: 0.94916 timestamp: 1655070191.337191 iteration: 79400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07603 FastRCNN class loss: 0.05549 FastRCNN total loss: 0.13152 L1 loss: 0.0000e+00 L2 loss: 0.56274 Learning rate: 0.0004 Mask loss: 0.21603 RPN box loss: 0.02084 RPN score loss: 0.00191 RPN total loss: 0.02274 Total loss: 0.93303 timestamp: 1655070194.57381 iteration: 79405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06437 FastRCNN class loss: 0.05917 FastRCNN total loss: 0.12354 L1 loss: 0.0000e+00 L2 loss: 0.56274 Learning rate: 0.0004 Mask loss: 0.13996 RPN box loss: 0.01867 RPN score loss: 0.0034 RPN total loss: 0.02207 Total loss: 0.84831 timestamp: 1655070197.83808 iteration: 79410 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08846 FastRCNN class loss: 0.08365 FastRCNN total loss: 0.17211 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.12191 RPN box loss: 0.01027 RPN score loss: 0.00273 RPN total loss: 0.013 Total loss: 0.86976 timestamp: 1655070201.1364863 iteration: 79415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06614 FastRCNN class loss: 0.04119 FastRCNN total loss: 0.10732 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.12273 RPN box loss: 0.00574 RPN score loss: 0.00256 RPN total loss: 0.00829 Total loss: 0.80108 timestamp: 1655070204.4879704 iteration: 79420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06271 FastRCNN class loss: 0.05896 FastRCNN total loss: 0.12168 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.15826 RPN box loss: 0.01707 RPN score loss: 0.00946 RPN total loss: 0.02654 Total loss: 0.86921 timestamp: 1655070207.7580266 iteration: 79425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06952 FastRCNN class loss: 0.067 FastRCNN total loss: 0.13653 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.1571 RPN box loss: 0.02256 RPN score loss: 0.00762 RPN total loss: 0.03019 Total loss: 0.88654 timestamp: 1655070211.0700076 iteration: 79430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13797 FastRCNN class loss: 0.08976 FastRCNN total loss: 0.22772 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.17686 RPN box loss: 0.03172 RPN score loss: 0.00361 RPN total loss: 0.03532 Total loss: 1.00263 timestamp: 1655070214.3305495 iteration: 79435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11534 FastRCNN class loss: 0.08497 FastRCNN total loss: 0.20031 L1 loss: 0.0000e+00 L2 loss: 0.56273 Learning rate: 0.0004 Mask loss: 0.153 RPN box loss: 0.01278 RPN score loss: 0.00344 RPN total loss: 0.01622 Total loss: 0.93226 timestamp: 1655070217.6084194 iteration: 79440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07258 FastRCNN class loss: 0.06756 FastRCNN total loss: 0.14014 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.14813 RPN box loss: 0.0109 RPN score loss: 0.00431 RPN total loss: 0.01522 Total loss: 0.8662 timestamp: 1655070220.8322875 iteration: 79445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08908 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.16133 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.17544 RPN box loss: 0.03505 RPN score loss: 0.0113 RPN total loss: 0.04635 Total loss: 0.94585 timestamp: 1655070224.0936592 iteration: 79450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0541 FastRCNN class loss: 0.04573 FastRCNN total loss: 0.09983 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.08374 RPN box loss: 0.00642 RPN score loss: 0.00222 RPN total loss: 0.00864 Total loss: 0.75493 timestamp: 1655070227.31845 iteration: 79455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.081 FastRCNN class loss: 0.0877 FastRCNN total loss: 0.16871 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.20056 RPN box loss: 0.0144 RPN score loss: 0.01087 RPN total loss: 0.02527 Total loss: 0.95725 timestamp: 1655070230.565542 iteration: 79460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09851 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.18487 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.13998 RPN box loss: 0.01415 RPN score loss: 0.00741 RPN total loss: 0.02156 Total loss: 0.90913 timestamp: 1655070233.8022656 iteration: 79465 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0657 FastRCNN class loss: 0.05666 FastRCNN total loss: 0.12236 L1 loss: 0.0000e+00 L2 loss: 0.56272 Learning rate: 0.0004 Mask loss: 0.12618 RPN box loss: 0.01067 RPN score loss: 0.00976 RPN total loss: 0.02043 Total loss: 0.83169 timestamp: 1655070237.0981379 iteration: 79470 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09194 FastRCNN class loss: 0.05048 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.09161 RPN box loss: 0.01497 RPN score loss: 0.00276 RPN total loss: 0.01772 Total loss: 0.81447 timestamp: 1655070240.2939272 iteration: 79475 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09908 FastRCNN class loss: 0.13495 FastRCNN total loss: 0.23402 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.23696 RPN box loss: 0.04523 RPN score loss: 0.0666 RPN total loss: 0.11183 Total loss: 1.14552 timestamp: 1655070243.5361693 iteration: 79480 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06738 FastRCNN class loss: 0.04879 FastRCNN total loss: 0.11616 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.16739 RPN box loss: 0.00576 RPN score loss: 0.00761 RPN total loss: 0.01337 Total loss: 0.85963 timestamp: 1655070246.8222783 iteration: 79485 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08277 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.15753 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.21277 RPN box loss: 0.01272 RPN score loss: 0.00494 RPN total loss: 0.01766 Total loss: 0.95067 timestamp: 1655070250.0505123 iteration: 79490 throughput: 24.6 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10767 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.17644 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.16412 RPN box loss: 0.00606 RPN score loss: 0.00152 RPN total loss: 0.00758 Total loss: 0.91085 timestamp: 1655070253.3203685 iteration: 79495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12538 FastRCNN class loss: 0.07954 FastRCNN total loss: 0.20492 L1 loss: 0.0000e+00 L2 loss: 0.56271 Learning rate: 0.0004 Mask loss: 0.16419 RPN box loss: 0.0106 RPN score loss: 0.00971 RPN total loss: 0.02031 Total loss: 0.95213 timestamp: 1655070256.557577 iteration: 79500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12288 FastRCNN class loss: 0.08908 FastRCNN total loss: 0.21196 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.14227 RPN box loss: 0.00843 RPN score loss: 0.00587 RPN total loss: 0.0143 Total loss: 0.93124 timestamp: 1655070259.8571448 iteration: 79505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07301 FastRCNN class loss: 0.05482 FastRCNN total loss: 0.12783 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.10596 RPN box loss: 0.01342 RPN score loss: 0.00298 RPN total loss: 0.0164 Total loss: 0.81289 timestamp: 1655070263.0911474 iteration: 79510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15186 FastRCNN class loss: 0.05191 FastRCNN total loss: 0.20376 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.12747 RPN box loss: 0.00997 RPN score loss: 0.00262 RPN total loss: 0.01258 Total loss: 0.90652 timestamp: 1655070266.4518518 iteration: 79515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12366 FastRCNN class loss: 0.10189 FastRCNN total loss: 0.22555 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.16017 RPN box loss: 0.01309 RPN score loss: 0.00606 RPN total loss: 0.01915 Total loss: 0.96757 timestamp: 1655070269.7529466 iteration: 79520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05999 FastRCNN class loss: 0.07563 FastRCNN total loss: 0.13562 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.14854 RPN box loss: 0.00614 RPN score loss: 0.00661 RPN total loss: 0.01275 Total loss: 0.85961 timestamp: 1655070273.0249233 iteration: 79525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06721 FastRCNN class loss: 0.05014 FastRCNN total loss: 0.11735 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.13163 RPN box loss: 0.02792 RPN score loss: 0.00389 RPN total loss: 0.03181 Total loss: 0.84349 timestamp: 1655070276.263595 iteration: 79530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10292 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.16362 L1 loss: 0.0000e+00 L2 loss: 0.5627 Learning rate: 0.0004 Mask loss: 0.14028 RPN box loss: 0.01836 RPN score loss: 0.00624 RPN total loss: 0.0246 Total loss: 0.8912 timestamp: 1655070279.514627 iteration: 79535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08582 FastRCNN class loss: 0.07683 FastRCNN total loss: 0.16265 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.1598 RPN box loss: 0.00947 RPN score loss: 0.00176 RPN total loss: 0.01123 Total loss: 0.89637 timestamp: 1655070282.8101695 iteration: 79540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1013 FastRCNN class loss: 0.09536 FastRCNN total loss: 0.19665 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.15129 RPN box loss: 0.00978 RPN score loss: 0.00203 RPN total loss: 0.01181 Total loss: 0.92245 timestamp: 1655070286.1078503 iteration: 79545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10086 FastRCNN class loss: 0.09862 FastRCNN total loss: 0.19948 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.15263 RPN box loss: 0.02604 RPN score loss: 0.00356 RPN total loss: 0.0296 Total loss: 0.9444 timestamp: 1655070289.3901014 iteration: 79550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1163 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.1868 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.13409 RPN box loss: 0.01401 RPN score loss: 0.01208 RPN total loss: 0.02609 Total loss: 0.90967 timestamp: 1655070292.610013 iteration: 79555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1027 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.18686 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.13676 RPN box loss: 0.0221 RPN score loss: 0.00513 RPN total loss: 0.02723 Total loss: 0.91353 timestamp: 1655070295.8594167 iteration: 79560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11711 FastRCNN class loss: 0.08439 FastRCNN total loss: 0.2015 L1 loss: 0.0000e+00 L2 loss: 0.56269 Learning rate: 0.0004 Mask loss: 0.11899 RPN box loss: 0.0119 RPN score loss: 0.00582 RPN total loss: 0.01771 Total loss: 0.9009 timestamp: 1655070299.109209 iteration: 79565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13276 FastRCNN class loss: 0.04756 FastRCNN total loss: 0.18032 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.09962 RPN box loss: 0.0099 RPN score loss: 0.00289 RPN total loss: 0.01279 Total loss: 0.85541 timestamp: 1655070302.3359544 iteration: 79570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09368 FastRCNN class loss: 0.09436 FastRCNN total loss: 0.18803 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.15573 RPN box loss: 0.01874 RPN score loss: 0.00484 RPN total loss: 0.02358 Total loss: 0.93003 timestamp: 1655070305.7169468 iteration: 79575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06357 FastRCNN class loss: 0.07178 FastRCNN total loss: 0.13535 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.11776 RPN box loss: 0.01809 RPN score loss: 0.00504 RPN total loss: 0.02314 Total loss: 0.83893 timestamp: 1655070308.996455 iteration: 79580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12449 FastRCNN class loss: 0.06737 FastRCNN total loss: 0.19186 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.11802 RPN box loss: 0.01812 RPN score loss: 0.00763 RPN total loss: 0.02575 Total loss: 0.89832 timestamp: 1655070312.2526183 iteration: 79585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13146 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.20588 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.16286 RPN box loss: 0.01227 RPN score loss: 0.00845 RPN total loss: 0.02072 Total loss: 0.95214 timestamp: 1655070315.5169063 iteration: 79590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07237 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.12979 L1 loss: 0.0000e+00 L2 loss: 0.56268 Learning rate: 0.0004 Mask loss: 0.12188 RPN box loss: 0.00696 RPN score loss: 0.00263 RPN total loss: 0.00959 Total loss: 0.82393 timestamp: 1655070318.88 iteration: 79595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11829 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.18455 L1 loss: 0.0000e+00 L2 loss: 0.56267 Learning rate: 0.0004 Mask loss: 0.12956 RPN box loss: 0.00848 RPN score loss: 0.00386 RPN total loss: 0.01234 Total loss: 0.88913 timestamp: 1655070322.1293988 iteration: 79600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.07103 FastRCNN total loss: 0.14425 L1 loss: 0.0000e+00 L2 loss: 0.56267 Learning rate: 0.0004 Mask loss: 0.14545 RPN box loss: 0.01632 RPN score loss: 0.00387 RPN total loss: 0.02019 Total loss: 0.87255 timestamp: 1655070325.4378476 iteration: 79605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09397 FastRCNN class loss: 0.04888 FastRCNN total loss: 0.14285 L1 loss: 0.0000e+00 L2 loss: 0.56267 Learning rate: 0.0004 Mask loss: 0.14206 RPN box loss: 0.00644 RPN score loss: 0.00309 RPN total loss: 0.00954 Total loss: 0.85711 timestamp: 1655070328.6285253 iteration: 79610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12066 FastRCNN class loss: 0.10565 FastRCNN total loss: 0.22631 L1 loss: 0.0000e+00 L2 loss: 0.56267 Learning rate: 0.0004 Mask loss: 0.15369 RPN box loss: 0.03722 RPN score loss: 0.01895 RPN total loss: 0.05617 Total loss: 0.99884 timestamp: 1655070331.894815 iteration: 79615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09032 FastRCNN class loss: 0.05445 FastRCNN total loss: 0.14477 L1 loss: 0.0000e+00 L2 loss: 0.56267 Learning rate: 0.0004 Mask loss: 0.0991 RPN box loss: 0.00948 RPN score loss: 0.00166 RPN total loss: 0.01114 Total loss: 0.81767 timestamp: 1655070335.1810253 iteration: 79620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04021 FastRCNN class loss: 0.02258 FastRCNN total loss: 0.06279 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.08196 RPN box loss: 0.01865 RPN score loss: 0.00205 RPN total loss: 0.0207 Total loss: 0.72812 timestamp: 1655070338.5020194 iteration: 79625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09996 FastRCNN class loss: 0.06162 FastRCNN total loss: 0.16158 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.12975 RPN box loss: 0.00953 RPN score loss: 0.00758 RPN total loss: 0.01712 Total loss: 0.87112 timestamp: 1655070341.84601 iteration: 79630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18603 FastRCNN class loss: 0.08825 FastRCNN total loss: 0.27427 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.16912 RPN box loss: 0.01303 RPN score loss: 0.01439 RPN total loss: 0.02742 Total loss: 1.03347 timestamp: 1655070345.1365855 iteration: 79635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11058 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.17373 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.14625 RPN box loss: 0.00872 RPN score loss: 0.00495 RPN total loss: 0.01367 Total loss: 0.89631 timestamp: 1655070348.4075203 iteration: 79640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13395 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.18064 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.15307 RPN box loss: 0.01686 RPN score loss: 0.00132 RPN total loss: 0.01818 Total loss: 0.91455 timestamp: 1655070351.666447 iteration: 79645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12173 FastRCNN class loss: 0.07173 FastRCNN total loss: 0.19346 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.10827 RPN box loss: 0.01297 RPN score loss: 0.00424 RPN total loss: 0.01721 Total loss: 0.88159 timestamp: 1655070355.0075657 iteration: 79650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04966 FastRCNN class loss: 0.06004 FastRCNN total loss: 0.10969 L1 loss: 0.0000e+00 L2 loss: 0.56266 Learning rate: 0.0004 Mask loss: 0.12708 RPN box loss: 0.01451 RPN score loss: 0.00799 RPN total loss: 0.0225 Total loss: 0.82193 timestamp: 1655070358.318149 iteration: 79655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.108 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.16209 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.14839 RPN box loss: 0.00799 RPN score loss: 0.00191 RPN total loss: 0.0099 Total loss: 0.88302 timestamp: 1655070361.619253 iteration: 79660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09205 FastRCNN class loss: 0.09471 FastRCNN total loss: 0.18676 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.1358 RPN box loss: 0.01419 RPN score loss: 0.00496 RPN total loss: 0.01915 Total loss: 0.90436 timestamp: 1655070364.9286692 iteration: 79665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08523 FastRCNN class loss: 0.08532 FastRCNN total loss: 0.17055 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.19517 RPN box loss: 0.01661 RPN score loss: 0.00298 RPN total loss: 0.01959 Total loss: 0.94796 timestamp: 1655070368.1763115 iteration: 79670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09871 FastRCNN class loss: 0.06542 FastRCNN total loss: 0.16412 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.11084 RPN box loss: 0.00861 RPN score loss: 0.00468 RPN total loss: 0.01329 Total loss: 0.85091 timestamp: 1655070371.5041835 iteration: 79675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10109 FastRCNN class loss: 0.05005 FastRCNN total loss: 0.15114 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.14626 RPN box loss: 0.01203 RPN score loss: 0.00491 RPN total loss: 0.01695 Total loss: 0.87699 timestamp: 1655070374.8015506 iteration: 79680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.04831 FastRCNN total loss: 0.15721 L1 loss: 0.0000e+00 L2 loss: 0.56265 Learning rate: 0.0004 Mask loss: 0.12968 RPN box loss: 0.00546 RPN score loss: 0.00419 RPN total loss: 0.00966 Total loss: 0.8592 timestamp: 1655070378.098169 iteration: 79685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0819 FastRCNN class loss: 0.04417 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.56264 Learning rate: 0.0004 Mask loss: 0.15421 RPN box loss: 0.01127 RPN score loss: 0.00402 RPN total loss: 0.0153 Total loss: 0.85822 timestamp: 1655070381.3237033 iteration: 79690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04925 FastRCNN class loss: 0.05234 FastRCNN total loss: 0.10159 L1 loss: 0.0000e+00 L2 loss: 0.56264 Learning rate: 0.0004 Mask loss: 0.12632 RPN box loss: 0.00873 RPN score loss: 0.00304 RPN total loss: 0.01177 Total loss: 0.80233 timestamp: 1655070384.5690596 iteration: 79695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10169 FastRCNN class loss: 0.05493 FastRCNN total loss: 0.15662 L1 loss: 0.0000e+00 L2 loss: 0.56264 Learning rate: 0.0004 Mask loss: 0.10052 RPN box loss: 0.00392 RPN score loss: 0.00641 RPN total loss: 0.01033 Total loss: 0.83011 timestamp: 1655070387.9198995 iteration: 79700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14275 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.22255 L1 loss: 0.0000e+00 L2 loss: 0.56264 Learning rate: 0.0004 Mask loss: 0.07189 RPN box loss: 0.00379 RPN score loss: 0.00149 RPN total loss: 0.00527 Total loss: 0.86235 timestamp: 1655070391.2235312 iteration: 79705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07522 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.14276 L1 loss: 0.0000e+00 L2 loss: 0.56264 Learning rate: 0.0004 Mask loss: 0.12143 RPN box loss: 0.00767 RPN score loss: 0.00374 RPN total loss: 0.0114 Total loss: 0.83823 timestamp: 1655070394.400064 iteration: 79710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09462 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.15084 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.10196 RPN box loss: 0.01258 RPN score loss: 0.00384 RPN total loss: 0.01642 Total loss: 0.83185 timestamp: 1655070397.6723704 iteration: 79715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09014 FastRCNN class loss: 0.09313 FastRCNN total loss: 0.18327 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.18146 RPN box loss: 0.02394 RPN score loss: 0.00882 RPN total loss: 0.03276 Total loss: 0.96012 timestamp: 1655070400.9243042 iteration: 79720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11123 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.19371 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.16103 RPN box loss: 0.03148 RPN score loss: 0.00445 RPN total loss: 0.03593 Total loss: 0.95331 timestamp: 1655070404.145729 iteration: 79725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10979 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.12021 RPN box loss: 0.02098 RPN score loss: 0.00461 RPN total loss: 0.02559 Total loss: 0.87945 timestamp: 1655070407.3852546 iteration: 79730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05484 FastRCNN class loss: 0.03439 FastRCNN total loss: 0.08923 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.09943 RPN box loss: 0.00374 RPN score loss: 0.0011 RPN total loss: 0.00485 Total loss: 0.75613 timestamp: 1655070410.6407778 iteration: 79735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04335 FastRCNN class loss: 0.03226 FastRCNN total loss: 0.07561 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.12039 RPN box loss: 0.0043 RPN score loss: 0.00138 RPN total loss: 0.00568 Total loss: 0.76431 timestamp: 1655070413.862308 iteration: 79740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06914 FastRCNN class loss: 0.11074 FastRCNN total loss: 0.17988 L1 loss: 0.0000e+00 L2 loss: 0.56263 Learning rate: 0.0004 Mask loss: 0.16789 RPN box loss: 0.05566 RPN score loss: 0.01834 RPN total loss: 0.074 Total loss: 0.9844 timestamp: 1655070417.1385002 iteration: 79745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06402 FastRCNN class loss: 0.05512 FastRCNN total loss: 0.11914 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.16873 RPN box loss: 0.01453 RPN score loss: 0.00529 RPN total loss: 0.01982 Total loss: 0.8703 timestamp: 1655070420.4454305 iteration: 79750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.091 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.18172 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.17578 RPN box loss: 0.01865 RPN score loss: 0.00764 RPN total loss: 0.02629 Total loss: 0.94641 timestamp: 1655070423.6879458 iteration: 79755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04847 FastRCNN class loss: 0.05699 FastRCNN total loss: 0.10547 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.13175 RPN box loss: 0.01786 RPN score loss: 0.00117 RPN total loss: 0.01903 Total loss: 0.81887 timestamp: 1655070426.974903 iteration: 79760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06525 FastRCNN class loss: 0.07024 FastRCNN total loss: 0.13549 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.13331 RPN box loss: 0.00673 RPN score loss: 0.00493 RPN total loss: 0.01166 Total loss: 0.84308 timestamp: 1655070430.2340264 iteration: 79765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08241 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.1718 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.1747 RPN box loss: 0.01671 RPN score loss: 0.00707 RPN total loss: 0.02379 Total loss: 0.9329 timestamp: 1655070433.4913118 iteration: 79770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09766 FastRCNN class loss: 0.06751 FastRCNN total loss: 0.16517 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.12509 RPN box loss: 0.00797 RPN score loss: 0.00471 RPN total loss: 0.01268 Total loss: 0.86556 timestamp: 1655070436.8057039 iteration: 79775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15999 FastRCNN class loss: 0.07851 FastRCNN total loss: 0.2385 L1 loss: 0.0000e+00 L2 loss: 0.56262 Learning rate: 0.0004 Mask loss: 0.1586 RPN box loss: 0.02582 RPN score loss: 0.00314 RPN total loss: 0.02896 Total loss: 0.98869 timestamp: 1655070440.0836885 iteration: 79780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09087 FastRCNN class loss: 0.13214 FastRCNN total loss: 0.22301 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.1365 RPN box loss: 0.02343 RPN score loss: 0.00772 RPN total loss: 0.03116 Total loss: 0.95328 timestamp: 1655070443.332713 iteration: 79785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11283 FastRCNN class loss: 0.09089 FastRCNN total loss: 0.20372 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.17612 RPN box loss: 0.02683 RPN score loss: 0.00497 RPN total loss: 0.0318 Total loss: 0.97426 timestamp: 1655070446.57494 iteration: 79790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07169 FastRCNN class loss: 0.05584 FastRCNN total loss: 0.12753 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.12969 RPN box loss: 0.00498 RPN score loss: 0.00158 RPN total loss: 0.00657 Total loss: 0.8264 timestamp: 1655070449.7740326 iteration: 79795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14218 FastRCNN class loss: 0.14216 FastRCNN total loss: 0.28434 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.22103 RPN box loss: 0.03274 RPN score loss: 0.01402 RPN total loss: 0.04675 Total loss: 1.11473 timestamp: 1655070453.0647538 iteration: 79800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09314 FastRCNN class loss: 0.07795 FastRCNN total loss: 0.17109 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.11502 RPN box loss: 0.00647 RPN score loss: 0.00163 RPN total loss: 0.0081 Total loss: 0.85681 timestamp: 1655070456.2999332 iteration: 79805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08092 FastRCNN class loss: 0.04762 FastRCNN total loss: 0.12853 L1 loss: 0.0000e+00 L2 loss: 0.56261 Learning rate: 0.0004 Mask loss: 0.10356 RPN box loss: 0.00364 RPN score loss: 0.00081 RPN total loss: 0.00445 Total loss: 0.79915 timestamp: 1655070459.583174 iteration: 79810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04831 FastRCNN class loss: 0.04953 FastRCNN total loss: 0.09784 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.09733 RPN box loss: 0.0063 RPN score loss: 0.00575 RPN total loss: 0.01205 Total loss: 0.76982 timestamp: 1655070462.9844372 iteration: 79815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06554 FastRCNN class loss: 0.09943 FastRCNN total loss: 0.16497 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.1259 RPN box loss: 0.0111 RPN score loss: 0.01483 RPN total loss: 0.02593 Total loss: 0.87939 timestamp: 1655070466.2527962 iteration: 79820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08557 FastRCNN class loss: 0.05653 FastRCNN total loss: 0.1421 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.17823 RPN box loss: 0.01763 RPN score loss: 0.00698 RPN total loss: 0.02461 Total loss: 0.90754 timestamp: 1655070469.547867 iteration: 79825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11137 FastRCNN class loss: 0.08528 FastRCNN total loss: 0.19666 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.14021 RPN box loss: 0.00638 RPN score loss: 0.00241 RPN total loss: 0.00879 Total loss: 0.90826 timestamp: 1655070472.8588653 iteration: 79830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04464 FastRCNN class loss: 0.03271 FastRCNN total loss: 0.07735 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.11701 RPN box loss: 0.00342 RPN score loss: 0.00325 RPN total loss: 0.00668 Total loss: 0.76363 timestamp: 1655070476.1783292 iteration: 79835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.20256 FastRCNN class loss: 0.09685 FastRCNN total loss: 0.29942 L1 loss: 0.0000e+00 L2 loss: 0.5626 Learning rate: 0.0004 Mask loss: 0.23019 RPN box loss: 0.01355 RPN score loss: 0.00192 RPN total loss: 0.01547 Total loss: 1.10768 timestamp: 1655070479.4812653 iteration: 79840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05668 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.11991 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.1385 RPN box loss: 0.00481 RPN score loss: 0.00775 RPN total loss: 0.01256 Total loss: 0.83356 timestamp: 1655070482.7589407 iteration: 79845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10732 FastRCNN class loss: 0.07585 FastRCNN total loss: 0.18318 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.12358 RPN box loss: 0.01676 RPN score loss: 0.01607 RPN total loss: 0.03283 Total loss: 0.90218 timestamp: 1655070486.0095193 iteration: 79850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07494 FastRCNN class loss: 0.05596 FastRCNN total loss: 0.1309 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.12711 RPN box loss: 0.02484 RPN score loss: 0.00914 RPN total loss: 0.03398 Total loss: 0.85458 timestamp: 1655070489.2499576 iteration: 79855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10377 FastRCNN class loss: 0.07221 FastRCNN total loss: 0.17598 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.13075 RPN box loss: 0.00729 RPN score loss: 0.00403 RPN total loss: 0.01132 Total loss: 0.88064 timestamp: 1655070492.460865 iteration: 79860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08687 FastRCNN class loss: 0.04942 FastRCNN total loss: 0.13629 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.13341 RPN box loss: 0.00828 RPN score loss: 0.00525 RPN total loss: 0.01353 Total loss: 0.84581 timestamp: 1655070495.7473192 iteration: 79865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08979 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.16212 L1 loss: 0.0000e+00 L2 loss: 0.56259 Learning rate: 0.0004 Mask loss: 0.16653 RPN box loss: 0.00902 RPN score loss: 0.00763 RPN total loss: 0.01665 Total loss: 0.90788 timestamp: 1655070499.0057268 iteration: 79870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10356 FastRCNN class loss: 0.06808 FastRCNN total loss: 0.17165 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.14165 RPN box loss: 0.018 RPN score loss: 0.00417 RPN total loss: 0.02216 Total loss: 0.89804 timestamp: 1655070502.2568235 iteration: 79875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11914 FastRCNN class loss: 0.06502 FastRCNN total loss: 0.18416 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.13307 RPN box loss: 0.01127 RPN score loss: 0.01436 RPN total loss: 0.02563 Total loss: 0.90544 timestamp: 1655070505.5818646 iteration: 79880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11513 FastRCNN class loss: 0.05824 FastRCNN total loss: 0.17337 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.1583 RPN box loss: 0.00771 RPN score loss: 0.00986 RPN total loss: 0.01757 Total loss: 0.91181 timestamp: 1655070508.8636172 iteration: 79885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0667 FastRCNN class loss: 0.06905 FastRCNN total loss: 0.13575 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.13627 RPN box loss: 0.0061 RPN score loss: 0.00355 RPN total loss: 0.00965 Total loss: 0.84425 timestamp: 1655070512.0941381 iteration: 79890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.099 FastRCNN class loss: 0.09583 FastRCNN total loss: 0.19483 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.13407 RPN box loss: 0.02453 RPN score loss: 0.00855 RPN total loss: 0.03309 Total loss: 0.92456 timestamp: 1655070515.39446 iteration: 79895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10866 FastRCNN class loss: 0.04406 FastRCNN total loss: 0.15272 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.17032 RPN box loss: 0.01256 RPN score loss: 0.00362 RPN total loss: 0.01618 Total loss: 0.90179 timestamp: 1655070518.7206354 iteration: 79900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06364 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.12929 L1 loss: 0.0000e+00 L2 loss: 0.56258 Learning rate: 0.0004 Mask loss: 0.11122 RPN box loss: 0.01058 RPN score loss: 0.00523 RPN total loss: 0.01581 Total loss: 0.81889 timestamp: 1655070521.9728072 iteration: 79905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12081 FastRCNN class loss: 0.11762 FastRCNN total loss: 0.23843 L1 loss: 0.0000e+00 L2 loss: 0.56257 Learning rate: 0.0004 Mask loss: 0.25825 RPN box loss: 0.01689 RPN score loss: 0.01084 RPN total loss: 0.02773 Total loss: 1.08699 timestamp: 1655070525.205997 iteration: 79910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13591 FastRCNN class loss: 0.08174 FastRCNN total loss: 0.21765 L1 loss: 0.0000e+00 L2 loss: 0.56257 Learning rate: 0.0004 Mask loss: 0.15738 RPN box loss: 0.00576 RPN score loss: 0.00536 RPN total loss: 0.01111 Total loss: 0.94871 timestamp: 1655070528.4346755 iteration: 79915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1084 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.16515 L1 loss: 0.0000e+00 L2 loss: 0.56257 Learning rate: 0.0004 Mask loss: 0.18566 RPN box loss: 0.03118 RPN score loss: 0.0066 RPN total loss: 0.03778 Total loss: 0.95116 timestamp: 1655070531.6794825 iteration: 79920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06007 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.11065 L1 loss: 0.0000e+00 L2 loss: 0.56257 Learning rate: 0.0004 Mask loss: 0.09922 RPN box loss: 0.00666 RPN score loss: 0.00551 RPN total loss: 0.01216 Total loss: 0.7846 timestamp: 1655070534.9545205 iteration: 79925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17309 FastRCNN class loss: 0.11028 FastRCNN total loss: 0.28336 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.20853 RPN box loss: 0.01217 RPN score loss: 0.00584 RPN total loss: 0.01801 Total loss: 1.07247 timestamp: 1655070538.198355 iteration: 79930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10594 FastRCNN class loss: 0.08739 FastRCNN total loss: 0.19333 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.17343 RPN box loss: 0.01046 RPN score loss: 0.00419 RPN total loss: 0.01465 Total loss: 0.94397 timestamp: 1655070541.422815 iteration: 79935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12483 FastRCNN class loss: 0.04788 FastRCNN total loss: 0.17271 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.15228 RPN box loss: 0.02296 RPN score loss: 0.00699 RPN total loss: 0.02994 Total loss: 0.9175 timestamp: 1655070544.7069156 iteration: 79940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10039 FastRCNN class loss: 0.09285 FastRCNN total loss: 0.19324 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.20041 RPN box loss: 0.01135 RPN score loss: 0.00647 RPN total loss: 0.01782 Total loss: 0.97403 timestamp: 1655070547.9679952 iteration: 79945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10075 FastRCNN class loss: 0.05623 FastRCNN total loss: 0.15698 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.12015 RPN box loss: 0.0174 RPN score loss: 0.00128 RPN total loss: 0.01869 Total loss: 0.85837 timestamp: 1655070551.2110918 iteration: 79950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11749 FastRCNN class loss: 0.08906 FastRCNN total loss: 0.20655 L1 loss: 0.0000e+00 L2 loss: 0.56256 Learning rate: 0.0004 Mask loss: 0.15001 RPN box loss: 0.01533 RPN score loss: 0.00204 RPN total loss: 0.01737 Total loss: 0.93648 timestamp: 1655070554.5192287 iteration: 79955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06691 FastRCNN class loss: 0.04332 FastRCNN total loss: 0.11022 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.1558 RPN box loss: 0.0067 RPN score loss: 0.00212 RPN total loss: 0.00882 Total loss: 0.8374 timestamp: 1655070557.842918 iteration: 79960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12589 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.17828 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.12605 RPN box loss: 0.01735 RPN score loss: 0.0026 RPN total loss: 0.01995 Total loss: 0.88683 timestamp: 1655070561.104743 iteration: 79965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06565 FastRCNN class loss: 0.04712 FastRCNN total loss: 0.11277 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.09857 RPN box loss: 0.00799 RPN score loss: 0.00183 RPN total loss: 0.00981 Total loss: 0.7837 timestamp: 1655070564.3577049 iteration: 79970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.06123 FastRCNN total loss: 0.15674 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.17663 RPN box loss: 0.01515 RPN score loss: 0.00302 RPN total loss: 0.01817 Total loss: 0.91409 timestamp: 1655070567.6303525 iteration: 79975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05398 FastRCNN class loss: 0.03663 FastRCNN total loss: 0.09062 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.10669 RPN box loss: 0.00595 RPN score loss: 0.00271 RPN total loss: 0.00866 Total loss: 0.76852 timestamp: 1655070570.9497278 iteration: 79980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1256 FastRCNN class loss: 0.08592 FastRCNN total loss: 0.21152 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.11683 RPN box loss: 0.01351 RPN score loss: 0.00231 RPN total loss: 0.01581 Total loss: 0.90672 timestamp: 1655070574.1920986 iteration: 79985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14448 FastRCNN class loss: 0.07434 FastRCNN total loss: 0.21882 L1 loss: 0.0000e+00 L2 loss: 0.56255 Learning rate: 0.0004 Mask loss: 0.18673 RPN box loss: 0.02144 RPN score loss: 0.00768 RPN total loss: 0.02912 Total loss: 0.99722 timestamp: 1655070577.4442103 iteration: 79990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09369 FastRCNN class loss: 0.07676 FastRCNN total loss: 0.17045 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 0.0004 Mask loss: 0.0992 RPN box loss: 0.00442 RPN score loss: 0.00454 RPN total loss: 0.00896 Total loss: 0.84116 timestamp: 1655070580.6818318 iteration: 79995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09772 FastRCNN class loss: 0.06685 FastRCNN total loss: 0.16457 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 0.0004 Mask loss: 0.20437 RPN box loss: 0.01724 RPN score loss: 0.00873 RPN total loss: 0.02598 Total loss: 0.95746 timestamp: 1655070583.953828 iteration: 80000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0729 FastRCNN class loss: 0.06927 FastRCNN total loss: 0.14217 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 0.0004 Mask loss: 0.16692 RPN box loss: 0.01038 RPN score loss: 0.00662 RPN total loss: 0.017 Total loss: 0.88862 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 5.9360s - Throughput: 0.7 imgs/s Running inference on batch 002/125... - Step Time: 0.9447s - Throughput: 4.2 imgs/s Running inference on batch 003/125... - Step Time: 0.9162s - Throughput: 4.4 imgs/s Running inference on batch 004/125... - Step Time: 0.9590s - Throughput: 4.2 imgs/s Running inference on batch 005/125... - Step Time: 0.8986s - Throughput: 4.5 imgs/s Running inference on batch 006/125... - Step Time: 0.8925s - Throughput: 4.5 imgs/s Running inference on batch 007/125... - Step Time: 0.9199s - Throughput: 4.3 imgs/s Running inference on batch 008/125... - Step Time: 0.9472s - Throughput: 4.2 imgs/s Running inference on batch 009/125... - Step Time: 1.0101s - Throughput: 4.0 imgs/s Running inference on batch 010/125... - Step Time: 0.9554s - Throughput: 4.2 imgs/s Running inference on batch 011/125... - Step Time: 0.9816s - Throughput: 4.1 imgs/s Running inference on batch 012/125... - Step Time: 0.9201s - Throughput: 4.3 imgs/s Running inference on batch 013/125... - Step Time: 0.8783s - Throughput: 4.6 imgs/s Running inference on batch 014/125... - Step Time: 0.9156s - Throughput: 4.4 imgs/s Running inference on batch 015/125... - Step Time: 0.9780s - Throughput: 4.1 imgs/s Running inference on batch 016/125... - Step Time: 0.8874s - Throughput: 4.5 imgs/s Running inference on batch 017/125... - Step Time: 0.8856s - Throughput: 4.5 imgs/s Running inference on batch 018/125... - Step Time: 0.9056s - Throughput: 4.4 imgs/s Running inference on batch 019/125... - Step Time: 0.9681s - Throughput: 4.1 imgs/s Running inference on batch 020/125... - Step Time: 0.8989s - Throughput: 4.4 imgs/s Running inference on batch 021/125... - Step Time: 0.9198s - Throughput: 4.3 imgs/s Running inference on batch 022/125... - Step Time: 1.0251s - Throughput: 3.9 imgs/s Running inference on batch 023/125... - Step Time: 0.9458s - Throughput: 4.2 imgs/s Running inference on batch 024/125... - Step Time: 0.9158s - Throughput: 4.4 imgs/s Running inference on batch 025/125... - Step Time: 0.8931s - Throughput: 4.5 imgs/s Running inference on batch 026/125... - Step Time: 0.9302s - Throughput: 4.3 imgs/s Running inference on batch 027/125... - Step Time: 0.8321s - Throughput: 4.8 imgs/s Running inference on batch 028/125... - Step Time: 0.9034s - Throughput: 4.4 imgs/s Running inference on batch 029/125... - Step Time: 0.9228s - Throughput: 4.3 imgs/s Running inference on batch 030/125... - Step Time: 0.9408s - Throughput: 4.3 imgs/s Running inference on batch 031/125... - Step Time: 0.9151s - Throughput: 4.4 imgs/s Running inference on batch 032/125... - Step Time: 0.9675s - Throughput: 4.1 imgs/s Running inference on batch 033/125... - Step Time: 0.9936s - Throughput: 4.0 imgs/s Running inference on batch 034/125... - Step Time: 0.9565s - Throughput: 4.2 imgs/s Running inference on batch 035/125... - Step Time: 0.8961s - Throughput: 4.5 imgs/s Running inference on batch 036/125... - Step Time: 0.9228s - Throughput: 4.3 imgs/s Running inference on batch 037/125... - Step Time: 0.9570s - Throughput: 4.2 imgs/s Running inference on batch 038/125... - Step Time: 0.9427s - Throughput: 4.2 imgs/s Running inference on batch 039/125... - Step Time: 0.9237s - Throughput: 4.3 imgs/s Running inference on batch 040/125... - Step Time: 0.9221s - Throughput: 4.3 imgs/s Running inference on batch 041/125... - Step Time: 0.9953s - Throughput: 4.0 imgs/s Running inference on batch 042/125... - Step Time: 0.9473s - Throughput: 4.2 imgs/s Running inference on batch 043/125... - Step Time: 0.9288s - Throughput: 4.3 imgs/s Running inference on batch 044/125... - Step Time: 0.9512s - Throughput: 4.2 imgs/s Running inference on batch 045/125... - Step Time: 0.8982s - Throughput: 4.5 imgs/s Running inference on batch 046/125... - Step Time: 0.9102s - Throughput: 4.4 imgs/s Running inference on batch 047/125... - Step Time: 0.9149s - Throughput: 4.4 imgs/s Running inference on batch 048/125... - Step Time: 1.0179s - Throughput: 3.9 imgs/s Running inference on batch 049/125... - Step Time: 0.9603s - Throughput: 4.2 imgs/s Running inference on batch 050/125... - Step Time: 0.9847s - Throughput: 4.1 imgs/s Running inference on batch 051/125... - Step Time: 0.9300s - Throughput: 4.3 imgs/s Running inference on batch 052/125... - Step Time: 0.8572s - Throughput: 4.7 imgs/s Running inference on batch 053/125... - Step Time: 0.9809s - Throughput: 4.1 imgs/s Running inference on batch 054/125... - Step Time: 0.9116s - Throughput: 4.4 imgs/s Running inference on batch 055/125... - Step Time: 0.9452s - Throughput: 4.2 imgs/s Running inference on batch 056/125... - Step Time: 0.9114s - Throughput: 4.4 imgs/s Running inference on batch 057/125... - Step Time: 0.9404s - Throughput: 4.3 imgs/s Running inference on batch 058/125... - Step Time: 0.9549s - Throughput: 4.2 imgs/s Running inference on batch 059/125... - Step Time: 0.9439s - Throughput: 4.2 imgs/s Running inference on batch 060/125... - Step Time: 0.9218s - Throughput: 4.3 imgs/s Running inference on batch 061/125... - Step Time: 0.9183s - Throughput: 4.4 imgs/s Running inference on batch 062/125... - Step Time: 0.9679s - Throughput: 4.1 imgs/s Running inference on batch 063/125... - Step Time: 0.9140s - Throughput: 4.4 imgs/s Running inference on batch 064/125... - Step Time: 0.9464s - Throughput: 4.2 imgs/s Running inference on batch 065/125... - Step Time: 0.9554s - Throughput: 4.2 imgs/s Running inference on batch 066/125... - Step Time: 0.9697s - Throughput: 4.1 imgs/s Running inference on batch 067/125... - Step Time: 0.9019s - Throughput: 4.4 imgs/s Running inference on batch 068/125... - Step Time: 0.9198s - Throughput: 4.3 imgs/s Running inference on batch 069/125... - Step Time: 0.9886s - Throughput: 4.0 imgs/s Running inference on batch 070/125... - Step Time: 0.9713s - Throughput: 4.1 imgs/s Running inference on batch 071/125... - Step Time: 0.9583s - Throughput: 4.2 imgs/s Running inference on batch 072/125... - Step Time: 0.9904s - Throughput: 4.0 imgs/s Running inference on batch 073/125... - Step Time: 0.9087s - Throughput: 4.4 imgs/s Running inference on batch 074/125... - Step Time: 0.9437s - Throughput: 4.2 imgs/s Running inference on batch 075/125... - Step Time: 0.9905s - Throughput: 4.0 imgs/s Running inference on batch 076/125... - Step Time: 0.9500s - Throughput: 4.2 imgs/s Running inference on batch 077/125... - Step Time: 0.9432s - Throughput: 4.2 imgs/s Running inference on batch 078/125... - Step Time: 0.9072s - Throughput: 4.4 imgs/s Running inference on batch 079/125... - Step Time: 0.9217s - Throughput: 4.3 imgs/s Running inference on batch 080/125... - Step Time: 0.9683s - Throughput: 4.1 imgs/s Running inference on batch 081/125... - Step Time: 0.9490s - Throughput: 4.2 imgs/s Running inference on batch 082/125... - Step Time: 0.9307s - Throughput: 4.3 imgs/s Running inference on batch 083/125... - Step Time: 0.9149s - Throughput: 4.4 imgs/s Running inference on batch 084/125... - Step Time: 0.9463s - Throughput: 4.2 imgs/s Running inference on batch 085/125... - Step Time: 0.9074s - Throughput: 4.4 imgs/s Running inference on batch 086/125... - Step Time: 0.8668s - Throughput: 4.6 imgs/s Running inference on batch 087/125... - Step Time: 0.9387s - Throughput: 4.3 imgs/s Running inference on batch 088/125... - Step Time: 0.9763s - Throughput: 4.1 imgs/s Running inference on batch 089/125... - Step Time: 0.9875s - Throughput: 4.1 imgs/s Running inference on batch 090/125... - Step Time: 0.5672s - Throughput: 7.1 imgs/s Running inference on batch 091/125... - Step Time: 0.9762s - Throughput: 4.1 imgs/s Running inference on batch 092/125... - Step Time: 0.7166s - Throughput: 5.6 imgs/s Running inference on batch 093/125... - Step Time: 0.8717s - Throughput: 4.6 imgs/s Running inference on batch 094/125... - Step Time: 0.9429s - Throughput: 4.2 imgs/s Running inference on batch 095/125... - Step Time: 0.9108s - Throughput: 4.4 imgs/s Running inference on batch 096/125... - Step Time: 1.0010s - Throughput: 4.0 imgs/s Running inference on batch 097/125... - Step Time: 0.9778s - Throughput: 4.1 imgs/s Running inference on batch 098/125... - Step Time: 0.9765s - Throughput: 4.1 imgs/s Running inference on batch 099/125... - Step Time: 0.9122s - Throughput: 4.4 imgs/s Running inference on batch 100/125... - Step Time: 0.8755s - Throughput: 4.6 imgs/s Running inference on batch 101/125... - Step Time: 0.9303s - Throughput: 4.3 imgs/s Running inference on batch 102/125... - Step Time: 0.9004s - Throughput: 4.4 imgs/s Running inference on batch 103/125... - Step Time: 0.9489s - Throughput: 4.2 imgs/s Running inference on batch 104/125... - Step Time: 0.9313s - Throughput: 4.3 imgs/s Running inference on batch 105/125... - Step Time: 0.6838s - Throughput: 5.8 imgs/s Running inference on batch 106/125... - Step Time: 0.9622s - Throughput: 4.2 imgs/s Running inference on batch 107/125... - Step Time: 0.9369s - Throughput: 4.3 imgs/s Running inference on batch 108/125... - Step Time: 0.9591s - Throughput: 4.2 imgs/s Running inference on batch 109/125... - Step Time: 0.9494s - Throughput: 4.2 imgs/s Running inference on batch 110/125... - Step Time: 0.9659s - Throughput: 4.1 imgs/s Running inference on batch 111/125... - Step Time: 0.9168s - Throughput: 4.4 imgs/s Running inference on batch 112/125... - Step Time: 0.9692s - Throughput: 4.1 imgs/s Running inference on batch 113/125... - Step Time: 0.9231s - Throughput: 4.3 imgs/s Running inference on batch 114/125... - Step Time: 0.9102s - Throughput: 4.4 imgs/s Running inference on batch 115/125... - Step Time: 0.9475s - Throughput: 4.2 imgs/s Running inference on batch 116/125... - Step Time: 0.9244s - Throughput: 4.3 imgs/s Running inference on batch 117/125... - Step Time: 0.9615s - Throughput: 4.2 imgs/s Running inference on batch 118/125... - Step Time: 1.0053s - Throughput: 4.0 imgs/s Running inference on batch 119/125... - Step Time: 0.9426s - Throughput: 4.2 imgs/s Running inference on batch 120/125... - Step Time: 0.9199s - Throughput: 4.3 imgs/s Running inference on batch 121/125... - Step Time: 0.8895s - Throughput: 4.5 imgs/s Running inference on batch 122/125... - Step Time: 0.9105s - Throughput: 4.4 imgs/s Running inference on batch 123/125... - Step Time: 0.9107s - Throughput: 4.4 imgs/s Running inference on batch 124/125... - Step Time: 0.9981s - Throughput: 4.0 imgs/s Running inference on batch 125/125... - Step Time: 0.9396s - Throughput: 4.3 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: 4.3 samples/sec Total processed steps: 125 Total processing time: 0.0h 08m 56s ==================== Metrics ==================== AP: 0.195626825 AP50: 0.319213539 AP75: 0.190873787 APl: 0.227852792 APm: 0.042316843 APs: 0.002894448 ARl: 0.436018378 ARm: 0.091910072 ARmax1: 0.281606406 ARmax10: 0.369614422 ARmax100: 0.375160962 ARs: 0.012983092 mask_AP: 0.144847482 mask_AP50: 0.253848553 mask_AP75: 0.147369534 mask_APl: 0.171724662 mask_APm: 0.016352363 mask_APs: 0.000000000 mask_ARl: 0.292857558 mask_ARm: 0.041682594 mask_ARmax1: 0.198275477 mask_ARmax10: 0.242508903 mask_ARmax100: 0.245282158 mask_ARs: 0.000000000 ================================= 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] 549.0 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: 1655071842.2954648 iteration: 80005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10792 FastRCNN class loss: 0.04695 FastRCNN total loss: 0.15486 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.10494 RPN box loss: 0.0135 RPN score loss: 0.00144 RPN total loss: 0.01493 Total loss: 0.83728 timestamp: 1655071845.5735326 iteration: 80010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0653 FastRCNN class loss: 0.06184 FastRCNN total loss: 0.12714 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.1337 RPN box loss: 0.01411 RPN score loss: 0.00467 RPN total loss: 0.01878 Total loss: 0.84216 timestamp: 1655071848.725967 iteration: 80015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09773 FastRCNN class loss: 0.0558 FastRCNN total loss: 0.15353 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.15998 RPN box loss: 0.00755 RPN score loss: 0.00183 RPN total loss: 0.00937 Total loss: 0.88543 timestamp: 1655071851.9901032 iteration: 80020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12254 FastRCNN class loss: 0.06548 FastRCNN total loss: 0.18802 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.1486 RPN box loss: 0.00882 RPN score loss: 0.00258 RPN total loss: 0.0114 Total loss: 0.91055 timestamp: 1655071855.2126575 iteration: 80025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09128 FastRCNN class loss: 0.04486 FastRCNN total loss: 0.13614 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.12385 RPN box loss: 0.03145 RPN score loss: 0.00476 RPN total loss: 0.0362 Total loss: 0.85873 timestamp: 1655071858.4855192 iteration: 80030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08352 FastRCNN class loss: 0.07245 FastRCNN total loss: 0.15597 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.08591 RPN box loss: 0.00997 RPN score loss: 0.0063 RPN total loss: 0.01627 Total loss: 0.82068 timestamp: 1655071861.682489 iteration: 80035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05399 FastRCNN class loss: 0.0514 FastRCNN total loss: 0.1054 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.1824 RPN box loss: 0.00801 RPN score loss: 0.00264 RPN total loss: 0.01064 Total loss: 0.86098 timestamp: 1655071864.9074376 iteration: 80040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07712 FastRCNN class loss: 0.06519 FastRCNN total loss: 0.14231 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.16201 RPN box loss: 0.00292 RPN score loss: 0.00194 RPN total loss: 0.00485 Total loss: 0.87172 timestamp: 1655071868.154723 iteration: 80045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14949 FastRCNN class loss: 0.07021 FastRCNN total loss: 0.2197 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.0986 RPN box loss: 0.0116 RPN score loss: 0.00338 RPN total loss: 0.01497 Total loss: 0.89581 timestamp: 1655071871.4295444 iteration: 80050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0958 FastRCNN class loss: 0.05425 FastRCNN total loss: 0.15004 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.13499 RPN box loss: 0.01199 RPN score loss: 0.00136 RPN total loss: 0.01335 Total loss: 0.86092 timestamp: 1655071874.6824143 iteration: 80055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09552 FastRCNN class loss: 0.05484 FastRCNN total loss: 0.15036 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.1041 RPN box loss: 0.01042 RPN score loss: 0.00693 RPN total loss: 0.01735 Total loss: 0.83435 timestamp: 1655071877.9681265 iteration: 80060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11091 FastRCNN class loss: 0.11951 FastRCNN total loss: 0.23042 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.19607 RPN box loss: 0.01562 RPN score loss: 0.00969 RPN total loss: 0.0253 Total loss: 1.01433 timestamp: 1655071881.2366416 iteration: 80065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07411 FastRCNN class loss: 0.06153 FastRCNN total loss: 0.13563 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.14232 RPN box loss: 0.02566 RPN score loss: 0.00441 RPN total loss: 0.03006 Total loss: 0.87055 timestamp: 1655071884.460827 iteration: 80070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1065 FastRCNN class loss: 0.09597 FastRCNN total loss: 0.20247 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.11981 RPN box loss: 0.01262 RPN score loss: 0.0053 RPN total loss: 0.01792 Total loss: 0.90273 timestamp: 1655071887.7655487 iteration: 80075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09172 FastRCNN class loss: 0.07486 FastRCNN total loss: 0.16658 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.13155 RPN box loss: 0.01183 RPN score loss: 0.00732 RPN total loss: 0.01916 Total loss: 0.87982 timestamp: 1655071891.0063765 iteration: 80080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05179 FastRCNN class loss: 0.03348 FastRCNN total loss: 0.08528 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.11722 RPN box loss: 0.00433 RPN score loss: 0.00414 RPN total loss: 0.00847 Total loss: 0.7735 timestamp: 1655071894.369678 iteration: 80085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09646 FastRCNN class loss: 0.07168 FastRCNN total loss: 0.16814 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.18384 RPN box loss: 0.01657 RPN score loss: 0.00484 RPN total loss: 0.02141 Total loss: 0.93593 timestamp: 1655071897.6497335 iteration: 80090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09335 FastRCNN class loss: 0.07722 FastRCNN total loss: 0.17056 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.13557 RPN box loss: 0.01046 RPN score loss: 0.0064 RPN total loss: 0.01687 Total loss: 0.88554 timestamp: 1655071900.9314184 iteration: 80095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05059 FastRCNN class loss: 0.04947 FastRCNN total loss: 0.10006 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.09335 RPN box loss: 0.01117 RPN score loss: 0.00216 RPN total loss: 0.01334 Total loss: 0.76928 timestamp: 1655071904.2876065 iteration: 80100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08264 FastRCNN class loss: 0.04155 FastRCNN total loss: 0.12419 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.09419 RPN box loss: 0.0134 RPN score loss: 0.00529 RPN total loss: 0.01869 Total loss: 0.7996 timestamp: 1655071907.5102024 iteration: 80105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0919 FastRCNN class loss: 0.07134 FastRCNN total loss: 0.16324 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.12337 RPN box loss: 0.02823 RPN score loss: 0.00365 RPN total loss: 0.03188 Total loss: 0.88102 timestamp: 1655071910.7552507 iteration: 80110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06219 FastRCNN class loss: 0.05749 FastRCNN total loss: 0.11968 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.10372 RPN box loss: 0.00433 RPN score loss: 0.00303 RPN total loss: 0.00736 Total loss: 0.79329 timestamp: 1655071913.999366 iteration: 80115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10792 FastRCNN class loss: 0.06939 FastRCNN total loss: 0.17732 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.17212 RPN box loss: 0.01291 RPN score loss: 0.00907 RPN total loss: 0.02198 Total loss: 0.93395 timestamp: 1655071917.252708 iteration: 80120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03867 FastRCNN class loss: 0.03771 FastRCNN total loss: 0.07638 L1 loss: 0.0000e+00 L2 loss: 0.56254 Learning rate: 4.0000e-05 Mask loss: 0.09586 RPN box loss: 0.003 RPN score loss: 0.00389 RPN total loss: 0.00689 Total loss: 0.74166 timestamp: 1655071920.5896883 iteration: 80125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06977 FastRCNN class loss: 0.06656 FastRCNN total loss: 0.13633 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11795 RPN box loss: 0.00766 RPN score loss: 0.00538 RPN total loss: 0.01304 Total loss: 0.82986 timestamp: 1655071923.8917086 iteration: 80130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09453 FastRCNN class loss: 0.07312 FastRCNN total loss: 0.16764 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.17237 RPN box loss: 0.03523 RPN score loss: 0.0093 RPN total loss: 0.04453 Total loss: 0.94709 timestamp: 1655071927.2329645 iteration: 80135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11602 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.19429 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.17235 RPN box loss: 0.01809 RPN score loss: 0.01052 RPN total loss: 0.02861 Total loss: 0.95779 timestamp: 1655071930.5395105 iteration: 80140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12045 FastRCNN class loss: 0.09034 FastRCNN total loss: 0.21079 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.1249 RPN box loss: 0.01625 RPN score loss: 0.00214 RPN total loss: 0.01838 Total loss: 0.91661 timestamp: 1655071933.8241863 iteration: 80145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08043 FastRCNN class loss: 0.05161 FastRCNN total loss: 0.13204 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10784 RPN box loss: 0.00482 RPN score loss: 0.00292 RPN total loss: 0.00775 Total loss: 0.81016 timestamp: 1655071937.086837 iteration: 80150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0946 FastRCNN class loss: 0.07529 FastRCNN total loss: 0.16988 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11415 RPN box loss: 0.01765 RPN score loss: 0.00502 RPN total loss: 0.02268 Total loss: 0.86924 timestamp: 1655071940.4052467 iteration: 80155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07226 FastRCNN class loss: 0.04853 FastRCNN total loss: 0.12079 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.08784 RPN box loss: 0.006 RPN score loss: 0.00243 RPN total loss: 0.00844 Total loss: 0.7796 timestamp: 1655071943.698622 iteration: 80160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09151 FastRCNN class loss: 0.07774 FastRCNN total loss: 0.16925 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15897 RPN box loss: 0.00933 RPN score loss: 0.00426 RPN total loss: 0.01359 Total loss: 0.90434 timestamp: 1655071947.0417025 iteration: 80165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08625 FastRCNN class loss: 0.03949 FastRCNN total loss: 0.12574 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11539 RPN box loss: 0.00538 RPN score loss: 0.00551 RPN total loss: 0.01088 Total loss: 0.81455 timestamp: 1655071950.3062885 iteration: 80170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09771 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.17735 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.224 RPN box loss: 0.03585 RPN score loss: 0.0061 RPN total loss: 0.04195 Total loss: 1.00584 timestamp: 1655071953.6132805 iteration: 80175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10749 FastRCNN class loss: 0.0608 FastRCNN total loss: 0.16829 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13152 RPN box loss: 0.00624 RPN score loss: 0.00614 RPN total loss: 0.01238 Total loss: 0.87473 timestamp: 1655071956.9559934 iteration: 80180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11796 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.18576 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.14405 RPN box loss: 0.01221 RPN score loss: 0.0037 RPN total loss: 0.01591 Total loss: 0.90826 timestamp: 1655071960.232008 iteration: 80185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.14737 FastRCNN total loss: 0.22767 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.17897 RPN box loss: 0.01666 RPN score loss: 0.01854 RPN total loss: 0.03521 Total loss: 1.00438 timestamp: 1655071963.4871528 iteration: 80190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06929 FastRCNN class loss: 0.08651 FastRCNN total loss: 0.15579 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15674 RPN box loss: 0.01029 RPN score loss: 0.00706 RPN total loss: 0.01735 Total loss: 0.89242 timestamp: 1655071966.737407 iteration: 80195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14216 FastRCNN class loss: 0.10504 FastRCNN total loss: 0.2472 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.19104 RPN box loss: 0.01838 RPN score loss: 0.01076 RPN total loss: 0.02914 Total loss: 1.02992 timestamp: 1655071969.9662335 iteration: 80200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10845 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.18841 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.1216 RPN box loss: 0.04154 RPN score loss: 0.00742 RPN total loss: 0.04896 Total loss: 0.9215 timestamp: 1655071973.172759 iteration: 80205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07118 FastRCNN class loss: 0.08922 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.12925 RPN box loss: 0.01204 RPN score loss: 0.00123 RPN total loss: 0.01327 Total loss: 0.86545 timestamp: 1655071976.463417 iteration: 80210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08309 FastRCNN class loss: 0.0588 FastRCNN total loss: 0.14189 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.22154 RPN box loss: 0.01328 RPN score loss: 0.00823 RPN total loss: 0.02151 Total loss: 0.94746 timestamp: 1655071979.6978824 iteration: 80215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09793 FastRCNN class loss: 0.07027 FastRCNN total loss: 0.1682 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.2026 RPN box loss: 0.00782 RPN score loss: 0.0089 RPN total loss: 0.01672 Total loss: 0.95005 timestamp: 1655071983.041837 iteration: 80220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05093 FastRCNN class loss: 0.0416 FastRCNN total loss: 0.09253 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.09562 RPN box loss: 0.01158 RPN score loss: 0.00267 RPN total loss: 0.01425 Total loss: 0.76493 timestamp: 1655071986.383553 iteration: 80225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04634 FastRCNN class loss: 0.04467 FastRCNN total loss: 0.09101 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11017 RPN box loss: 0.00947 RPN score loss: 0.00397 RPN total loss: 0.01344 Total loss: 0.77715 timestamp: 1655071989.675043 iteration: 80230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07736 FastRCNN class loss: 0.06696 FastRCNN total loss: 0.14433 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.22139 RPN box loss: 0.00641 RPN score loss: 0.00488 RPN total loss: 0.01129 Total loss: 0.93954 timestamp: 1655071992.96312 iteration: 80235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07233 FastRCNN class loss: 0.06042 FastRCNN total loss: 0.13275 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.09162 RPN box loss: 0.0073 RPN score loss: 0.00552 RPN total loss: 0.01281 Total loss: 0.79972 timestamp: 1655071996.1924446 iteration: 80240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09193 FastRCNN class loss: 0.05414 FastRCNN total loss: 0.14607 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11267 RPN box loss: 0.00752 RPN score loss: 0.00567 RPN total loss: 0.01319 Total loss: 0.83447 timestamp: 1655071999.4496553 iteration: 80245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10057 FastRCNN class loss: 0.0705 FastRCNN total loss: 0.17107 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15153 RPN box loss: 0.00592 RPN score loss: 0.00919 RPN total loss: 0.01512 Total loss: 0.90025 timestamp: 1655072002.7772655 iteration: 80250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0563 FastRCNN class loss: 0.04427 FastRCNN total loss: 0.10057 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10475 RPN box loss: 0.01165 RPN score loss: 0.00263 RPN total loss: 0.01429 Total loss: 0.78214 timestamp: 1655072006.041453 iteration: 80255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10395 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.16156 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.08784 RPN box loss: 0.00991 RPN score loss: 0.00389 RPN total loss: 0.0138 Total loss: 0.82573 timestamp: 1655072009.4019144 iteration: 80260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04986 FastRCNN class loss: 0.0619 FastRCNN total loss: 0.11176 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.11665 RPN box loss: 0.00766 RPN score loss: 0.00231 RPN total loss: 0.00997 Total loss: 0.80091 timestamp: 1655072012.7384415 iteration: 80265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10837 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.1905 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.14556 RPN box loss: 0.01199 RPN score loss: 0.01281 RPN total loss: 0.02481 Total loss: 0.9234 timestamp: 1655072016.0263307 iteration: 80270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08643 FastRCNN class loss: 0.06405 FastRCNN total loss: 0.15047 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15982 RPN box loss: 0.00949 RPN score loss: 0.00554 RPN total loss: 0.01503 Total loss: 0.88785 timestamp: 1655072019.2699804 iteration: 80275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09427 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.16963 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15222 RPN box loss: 0.02231 RPN score loss: 0.0016 RPN total loss: 0.02391 Total loss: 0.90829 timestamp: 1655072022.6094608 iteration: 80280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12118 FastRCNN class loss: 0.06144 FastRCNN total loss: 0.18262 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.14025 RPN box loss: 0.00498 RPN score loss: 0.00227 RPN total loss: 0.00725 Total loss: 0.89265 timestamp: 1655072025.9441688 iteration: 80285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08378 FastRCNN class loss: 0.05239 FastRCNN total loss: 0.13617 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.09077 RPN box loss: 0.01655 RPN score loss: 0.00365 RPN total loss: 0.02019 Total loss: 0.80966 timestamp: 1655072029.2240446 iteration: 80290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07969 FastRCNN class loss: 0.06956 FastRCNN total loss: 0.14925 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10964 RPN box loss: 0.01028 RPN score loss: 0.00325 RPN total loss: 0.01352 Total loss: 0.83493 timestamp: 1655072032.4457273 iteration: 80295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1022 FastRCNN class loss: 0.05891 FastRCNN total loss: 0.16111 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15211 RPN box loss: 0.03607 RPN score loss: 0.0082 RPN total loss: 0.04427 Total loss: 0.92002 timestamp: 1655072035.7554832 iteration: 80300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13356 FastRCNN class loss: 0.09931 FastRCNN total loss: 0.23287 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.16571 RPN box loss: 0.01235 RPN score loss: 0.00933 RPN total loss: 0.02168 Total loss: 0.98279 timestamp: 1655072038.9921083 iteration: 80305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08789 FastRCNN class loss: 0.06384 FastRCNN total loss: 0.15173 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13411 RPN box loss: 0.00786 RPN score loss: 0.00386 RPN total loss: 0.01172 Total loss: 0.86008 timestamp: 1655072042.268775 iteration: 80310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10116 FastRCNN class loss: 0.08413 FastRCNN total loss: 0.18529 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15711 RPN box loss: 0.0214 RPN score loss: 0.00171 RPN total loss: 0.02311 Total loss: 0.92803 timestamp: 1655072045.5930355 iteration: 80315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10879 FastRCNN class loss: 0.06058 FastRCNN total loss: 0.16937 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15364 RPN box loss: 0.01577 RPN score loss: 0.00446 RPN total loss: 0.02023 Total loss: 0.90577 timestamp: 1655072048.8685927 iteration: 80320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12872 FastRCNN class loss: 0.07067 FastRCNN total loss: 0.19939 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.18736 RPN box loss: 0.00702 RPN score loss: 0.00177 RPN total loss: 0.00879 Total loss: 0.95807 timestamp: 1655072052.1471214 iteration: 80325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06951 FastRCNN class loss: 0.0425 FastRCNN total loss: 0.11201 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13598 RPN box loss: 0.00766 RPN score loss: 0.00236 RPN total loss: 0.01002 Total loss: 0.82054 timestamp: 1655072055.460436 iteration: 80330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08972 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.14917 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13452 RPN box loss: 0.00507 RPN score loss: 0.00171 RPN total loss: 0.00678 Total loss: 0.85299 timestamp: 1655072058.78026 iteration: 80335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10851 FastRCNN class loss: 0.08534 FastRCNN total loss: 0.19385 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15664 RPN box loss: 0.0159 RPN score loss: 0.01456 RPN total loss: 0.03046 Total loss: 0.94348 timestamp: 1655072062.0339284 iteration: 80340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05068 FastRCNN class loss: 0.054 FastRCNN total loss: 0.10467 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.17554 RPN box loss: 0.01093 RPN score loss: 0.00184 RPN total loss: 0.01277 Total loss: 0.85552 timestamp: 1655072065.250849 iteration: 80345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05531 FastRCNN class loss: 0.04626 FastRCNN total loss: 0.10157 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.12845 RPN box loss: 0.00768 RPN score loss: 0.00591 RPN total loss: 0.01359 Total loss: 0.80614 timestamp: 1655072068.5350733 iteration: 80350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12808 FastRCNN class loss: 0.09763 FastRCNN total loss: 0.22571 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.2353 RPN box loss: 0.01266 RPN score loss: 0.00952 RPN total loss: 0.02218 Total loss: 1.04572 timestamp: 1655072071.8065708 iteration: 80355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06545 FastRCNN class loss: 0.04392 FastRCNN total loss: 0.10937 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.09093 RPN box loss: 0.00873 RPN score loss: 0.00169 RPN total loss: 0.01042 Total loss: 0.77324 timestamp: 1655072075.1672804 iteration: 80360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.10199 FastRCNN total loss: 0.18438 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15414 RPN box loss: 0.01485 RPN score loss: 0.00776 RPN total loss: 0.02261 Total loss: 0.92366 timestamp: 1655072078.4518888 iteration: 80365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11343 FastRCNN class loss: 0.04742 FastRCNN total loss: 0.16085 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10124 RPN box loss: 0.01492 RPN score loss: 0.00409 RPN total loss: 0.01901 Total loss: 0.84362 timestamp: 1655072081.6957107 iteration: 80370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08862 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.15442 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10138 RPN box loss: 0.01475 RPN score loss: 0.0025 RPN total loss: 0.01725 Total loss: 0.83557 timestamp: 1655072084.9300208 iteration: 80375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.1293 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.16959 RPN box loss: 0.02426 RPN score loss: 0.00642 RPN total loss: 0.03068 Total loss: 0.8921 timestamp: 1655072088.2488747 iteration: 80380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10365 FastRCNN class loss: 0.09396 FastRCNN total loss: 0.19761 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.20093 RPN box loss: 0.03218 RPN score loss: 0.00492 RPN total loss: 0.0371 Total loss: 0.99817 timestamp: 1655072091.541027 iteration: 80385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1744 FastRCNN class loss: 0.15528 FastRCNN total loss: 0.32967 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.16639 RPN box loss: 0.02607 RPN score loss: 0.03576 RPN total loss: 0.06183 Total loss: 1.12042 timestamp: 1655072094.8257103 iteration: 80390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07399 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.12916 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.23547 RPN box loss: 0.01635 RPN score loss: 0.00228 RPN total loss: 0.01862 Total loss: 0.94578 timestamp: 1655072098.1328528 iteration: 80395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0728 FastRCNN class loss: 0.10453 FastRCNN total loss: 0.17734 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13117 RPN box loss: 0.00846 RPN score loss: 0.00398 RPN total loss: 0.01244 Total loss: 0.88347 timestamp: 1655072101.549097 iteration: 80400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07165 FastRCNN class loss: 0.04994 FastRCNN total loss: 0.12159 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.12098 RPN box loss: 0.00514 RPN score loss: 0.00218 RPN total loss: 0.00731 Total loss: 0.81241 timestamp: 1655072104.7867508 iteration: 80405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06553 FastRCNN class loss: 0.0695 FastRCNN total loss: 0.13502 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13357 RPN box loss: 0.00698 RPN score loss: 0.00088 RPN total loss: 0.00786 Total loss: 0.83898 timestamp: 1655072108.047508 iteration: 80410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1098 FastRCNN class loss: 0.10246 FastRCNN total loss: 0.21226 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13681 RPN box loss: 0.02676 RPN score loss: 0.00996 RPN total loss: 0.03672 Total loss: 0.94832 timestamp: 1655072111.3372946 iteration: 80415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08036 FastRCNN class loss: 0.06285 FastRCNN total loss: 0.14322 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.10824 RPN box loss: 0.01061 RPN score loss: 0.00431 RPN total loss: 0.01491 Total loss: 0.8289 timestamp: 1655072114.6353462 iteration: 80420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.05058 FastRCNN total loss: 0.14838 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.13571 RPN box loss: 0.00772 RPN score loss: 0.00124 RPN total loss: 0.00897 Total loss: 0.85559 timestamp: 1655072117.903095 iteration: 80425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09668 FastRCNN class loss: 0.07416 FastRCNN total loss: 0.17084 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.14616 RPN box loss: 0.00615 RPN score loss: 0.01115 RPN total loss: 0.0173 Total loss: 0.89683 timestamp: 1655072121.162857 iteration: 80430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17253 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.25451 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.16682 RPN box loss: 0.01584 RPN score loss: 0.00338 RPN total loss: 0.01922 Total loss: 1.00308 timestamp: 1655072124.4388494 iteration: 80435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08278 FastRCNN class loss: 0.07827 FastRCNN total loss: 0.16105 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.18437 RPN box loss: 0.01982 RPN score loss: 0.00516 RPN total loss: 0.02498 Total loss: 0.93292 timestamp: 1655072127.7236667 iteration: 80440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11106 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.16868 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.17083 RPN box loss: 0.00666 RPN score loss: 0.00405 RPN total loss: 0.0107 Total loss: 0.91274 timestamp: 1655072130.96797 iteration: 80445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08268 FastRCNN class loss: 0.0434 FastRCNN total loss: 0.12609 L1 loss: 0.0000e+00 L2 loss: 0.56253 Learning rate: 4.0000e-05 Mask loss: 0.15253 RPN box loss: 0.00828 RPN score loss: 0.00428 RPN total loss: 0.01256 Total loss: 0.8537 timestamp: 1655072134.2131338 iteration: 80450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09914 FastRCNN class loss: 0.06027 FastRCNN total loss: 0.1594 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1384 RPN box loss: 0.00802 RPN score loss: 0.00671 RPN total loss: 0.01473 Total loss: 0.87506 timestamp: 1655072137.5430553 iteration: 80455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12617 FastRCNN class loss: 0.17386 FastRCNN total loss: 0.30003 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.19183 RPN box loss: 0.01945 RPN score loss: 0.00753 RPN total loss: 0.02698 Total loss: 1.08138 timestamp: 1655072140.8213634 iteration: 80460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09483 FastRCNN class loss: 0.06952 FastRCNN total loss: 0.16435 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15133 RPN box loss: 0.01125 RPN score loss: 0.00576 RPN total loss: 0.01701 Total loss: 0.89521 timestamp: 1655072144.0876613 iteration: 80465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08063 FastRCNN class loss: 0.03821 FastRCNN total loss: 0.11884 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13557 RPN box loss: 0.0026 RPN score loss: 0.0045 RPN total loss: 0.0071 Total loss: 0.82404 timestamp: 1655072147.3052206 iteration: 80470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10603 FastRCNN class loss: 0.09028 FastRCNN total loss: 0.19631 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1504 RPN box loss: 0.0167 RPN score loss: 0.01727 RPN total loss: 0.03397 Total loss: 0.9432 timestamp: 1655072150.5826452 iteration: 80475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.05826 FastRCNN total loss: 0.16888 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13809 RPN box loss: 0.01296 RPN score loss: 0.00178 RPN total loss: 0.01474 Total loss: 0.88424 timestamp: 1655072153.920725 iteration: 80480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10006 FastRCNN class loss: 0.08894 FastRCNN total loss: 0.189 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.14748 RPN box loss: 0.00896 RPN score loss: 0.00697 RPN total loss: 0.01593 Total loss: 0.91493 timestamp: 1655072157.2520044 iteration: 80485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0783 FastRCNN class loss: 0.06387 FastRCNN total loss: 0.14216 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13811 RPN box loss: 0.01045 RPN score loss: 0.00741 RPN total loss: 0.01786 Total loss: 0.86066 timestamp: 1655072160.5003152 iteration: 80490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05316 FastRCNN class loss: 0.04378 FastRCNN total loss: 0.09695 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1174 RPN box loss: 0.01011 RPN score loss: 0.00969 RPN total loss: 0.0198 Total loss: 0.79667 timestamp: 1655072163.7665517 iteration: 80495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08114 FastRCNN class loss: 0.06276 FastRCNN total loss: 0.1439 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15897 RPN box loss: 0.01935 RPN score loss: 0.00289 RPN total loss: 0.02225 Total loss: 0.88764 timestamp: 1655072167.1131 iteration: 80500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11693 FastRCNN class loss: 0.0683 FastRCNN total loss: 0.18522 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1494 RPN box loss: 0.00716 RPN score loss: 0.00139 RPN total loss: 0.00854 Total loss: 0.90569 timestamp: 1655072170.3933375 iteration: 80505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06626 FastRCNN class loss: 0.03648 FastRCNN total loss: 0.10274 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1211 RPN box loss: 0.00306 RPN score loss: 0.00296 RPN total loss: 0.00602 Total loss: 0.79239 timestamp: 1655072173.6497061 iteration: 80510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10848 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.1616 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13669 RPN box loss: 0.01067 RPN score loss: 0.00395 RPN total loss: 0.01463 Total loss: 0.87544 timestamp: 1655072176.8995504 iteration: 80515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0882 FastRCNN class loss: 0.07923 FastRCNN total loss: 0.16743 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13891 RPN box loss: 0.01406 RPN score loss: 0.00286 RPN total loss: 0.01692 Total loss: 0.88578 timestamp: 1655072180.1259215 iteration: 80520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05146 FastRCNN class loss: 0.03163 FastRCNN total loss: 0.08309 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13003 RPN box loss: 0.02073 RPN score loss: 0.00175 RPN total loss: 0.02248 Total loss: 0.79813 timestamp: 1655072183.4098644 iteration: 80525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13938 FastRCNN class loss: 0.08023 FastRCNN total loss: 0.21961 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13029 RPN box loss: 0.01232 RPN score loss: 0.00423 RPN total loss: 0.01655 Total loss: 0.92897 timestamp: 1655072186.6132262 iteration: 80530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06797 FastRCNN class loss: 0.07008 FastRCNN total loss: 0.13805 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15313 RPN box loss: 0.01459 RPN score loss: 0.00357 RPN total loss: 0.01816 Total loss: 0.87186 timestamp: 1655072189.9368699 iteration: 80535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07498 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.13173 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15836 RPN box loss: 0.00911 RPN score loss: 0.00131 RPN total loss: 0.01042 Total loss: 0.86303 timestamp: 1655072193.2798436 iteration: 80540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06984 FastRCNN class loss: 0.04199 FastRCNN total loss: 0.11183 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.0663 RPN box loss: 0.00453 RPN score loss: 0.00269 RPN total loss: 0.00722 Total loss: 0.74787 timestamp: 1655072196.5203438 iteration: 80545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10477 FastRCNN class loss: 0.08789 FastRCNN total loss: 0.19266 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1842 RPN box loss: 0.01253 RPN score loss: 0.01912 RPN total loss: 0.03164 Total loss: 0.97102 timestamp: 1655072199.858109 iteration: 80550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10189 FastRCNN class loss: 0.06581 FastRCNN total loss: 0.1677 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12585 RPN box loss: 0.01196 RPN score loss: 0.00787 RPN total loss: 0.01984 Total loss: 0.87591 timestamp: 1655072203.186201 iteration: 80555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06815 FastRCNN class loss: 0.06308 FastRCNN total loss: 0.13123 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15267 RPN box loss: 0.01718 RPN score loss: 0.00361 RPN total loss: 0.0208 Total loss: 0.86722 timestamp: 1655072206.4447875 iteration: 80560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1528 FastRCNN class loss: 0.09957 FastRCNN total loss: 0.25238 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.21599 RPN box loss: 0.01305 RPN score loss: 0.00626 RPN total loss: 0.01931 Total loss: 1.05019 timestamp: 1655072209.7771819 iteration: 80565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05487 FastRCNN class loss: 0.05813 FastRCNN total loss: 0.11301 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1444 RPN box loss: 0.00715 RPN score loss: 0.00342 RPN total loss: 0.01056 Total loss: 0.83049 timestamp: 1655072213.103487 iteration: 80570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07629 FastRCNN class loss: 0.069 FastRCNN total loss: 0.1453 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.23721 RPN box loss: 0.00654 RPN score loss: 0.00439 RPN total loss: 0.01093 Total loss: 0.95596 timestamp: 1655072216.328368 iteration: 80575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0672 FastRCNN class loss: 0.03487 FastRCNN total loss: 0.10208 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15119 RPN box loss: 0.00496 RPN score loss: 0.00212 RPN total loss: 0.00708 Total loss: 0.82286 timestamp: 1655072219.6670578 iteration: 80580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07894 FastRCNN class loss: 0.08055 FastRCNN total loss: 0.15949 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13727 RPN box loss: 0.01162 RPN score loss: 0.00299 RPN total loss: 0.01461 Total loss: 0.87388 timestamp: 1655072222.939035 iteration: 80585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13647 FastRCNN class loss: 0.08096 FastRCNN total loss: 0.21743 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.23601 RPN box loss: 0.00929 RPN score loss: 0.00469 RPN total loss: 0.01398 Total loss: 1.02994 timestamp: 1655072226.2453454 iteration: 80590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07896 FastRCNN class loss: 0.05697 FastRCNN total loss: 0.13593 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.14637 RPN box loss: 0.01145 RPN score loss: 0.00339 RPN total loss: 0.01484 Total loss: 0.85967 timestamp: 1655072229.5195382 iteration: 80595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09694 FastRCNN class loss: 0.06879 FastRCNN total loss: 0.16572 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12048 RPN box loss: 0.01001 RPN score loss: 0.00655 RPN total loss: 0.01656 Total loss: 0.86529 timestamp: 1655072232.8466818 iteration: 80600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14861 FastRCNN class loss: 0.0862 FastRCNN total loss: 0.23481 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12888 RPN box loss: 0.02734 RPN score loss: 0.00778 RPN total loss: 0.03512 Total loss: 0.96134 timestamp: 1655072236.060203 iteration: 80605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10868 FastRCNN class loss: 0.06449 FastRCNN total loss: 0.17316 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.10164 RPN box loss: 0.01091 RPN score loss: 0.00845 RPN total loss: 0.01936 Total loss: 0.85668 timestamp: 1655072239.3681521 iteration: 80610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08663 FastRCNN class loss: 0.06533 FastRCNN total loss: 0.15196 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.11246 RPN box loss: 0.00904 RPN score loss: 0.00597 RPN total loss: 0.01501 Total loss: 0.84195 timestamp: 1655072242.6785676 iteration: 80615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10308 FastRCNN class loss: 0.07397 FastRCNN total loss: 0.17705 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15574 RPN box loss: 0.04039 RPN score loss: 0.00298 RPN total loss: 0.04337 Total loss: 0.93867 timestamp: 1655072246.0311587 iteration: 80620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09448 FastRCNN class loss: 0.10287 FastRCNN total loss: 0.19735 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15273 RPN box loss: 0.01033 RPN score loss: 0.00445 RPN total loss: 0.01478 Total loss: 0.92739 timestamp: 1655072249.3166292 iteration: 80625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07587 FastRCNN class loss: 0.046 FastRCNN total loss: 0.12187 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12349 RPN box loss: 0.00742 RPN score loss: 0.00398 RPN total loss: 0.01139 Total loss: 0.81927 timestamp: 1655072252.5884912 iteration: 80630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08925 FastRCNN class loss: 0.04731 FastRCNN total loss: 0.13656 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.11273 RPN box loss: 0.02814 RPN score loss: 0.00223 RPN total loss: 0.03036 Total loss: 0.84217 timestamp: 1655072255.9044986 iteration: 80635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0855 FastRCNN class loss: 0.06139 FastRCNN total loss: 0.14689 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.10607 RPN box loss: 0.0061 RPN score loss: 0.00513 RPN total loss: 0.01123 Total loss: 0.82671 timestamp: 1655072259.2075334 iteration: 80640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11667 FastRCNN class loss: 0.08507 FastRCNN total loss: 0.20174 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.16415 RPN box loss: 0.02241 RPN score loss: 0.00155 RPN total loss: 0.02396 Total loss: 0.95238 timestamp: 1655072262.4847023 iteration: 80645 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14917 FastRCNN class loss: 0.07613 FastRCNN total loss: 0.2253 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15767 RPN box loss: 0.00708 RPN score loss: 0.0034 RPN total loss: 0.01048 Total loss: 0.95598 timestamp: 1655072265.733463 iteration: 80650 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06651 FastRCNN class loss: 0.05825 FastRCNN total loss: 0.12476 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.16353 RPN box loss: 0.01207 RPN score loss: 0.00482 RPN total loss: 0.01689 Total loss: 0.8677 timestamp: 1655072268.945326 iteration: 80655 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04134 FastRCNN class loss: 0.05607 FastRCNN total loss: 0.0974 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.10392 RPN box loss: 0.00493 RPN score loss: 0.00111 RPN total loss: 0.00605 Total loss: 0.76989 timestamp: 1655072272.313296 iteration: 80660 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08076 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.15758 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.16224 RPN box loss: 0.01131 RPN score loss: 0.0085 RPN total loss: 0.0198 Total loss: 0.90213 timestamp: 1655072275.5624247 iteration: 80665 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07878 FastRCNN class loss: 0.05071 FastRCNN total loss: 0.12949 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.11702 RPN box loss: 0.00947 RPN score loss: 0.00351 RPN total loss: 0.01298 Total loss: 0.82202 timestamp: 1655072278.8803658 iteration: 80670 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11189 FastRCNN class loss: 0.08803 FastRCNN total loss: 0.19992 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1245 RPN box loss: 0.01484 RPN score loss: 0.00384 RPN total loss: 0.01868 Total loss: 0.90562 timestamp: 1655072282.143702 iteration: 80675 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07788 FastRCNN class loss: 0.04058 FastRCNN total loss: 0.11846 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15219 RPN box loss: 0.00281 RPN score loss: 0.0043 RPN total loss: 0.00711 Total loss: 0.84028 timestamp: 1655072285.4754386 iteration: 80680 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15778 FastRCNN class loss: 0.06846 FastRCNN total loss: 0.22624 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.10817 RPN box loss: 0.01195 RPN score loss: 0.00229 RPN total loss: 0.01424 Total loss: 0.91116 timestamp: 1655072288.7241693 iteration: 80685 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11135 FastRCNN class loss: 0.06891 FastRCNN total loss: 0.18026 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.14643 RPN box loss: 0.02831 RPN score loss: 0.00467 RPN total loss: 0.03298 Total loss: 0.92218 timestamp: 1655072292.0452979 iteration: 80690 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13299 FastRCNN class loss: 0.10497 FastRCNN total loss: 0.23797 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.18218 RPN box loss: 0.01351 RPN score loss: 0.00884 RPN total loss: 0.02235 Total loss: 1.00501 timestamp: 1655072295.3724651 iteration: 80695 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12197 FastRCNN class loss: 0.09919 FastRCNN total loss: 0.22115 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.19 RPN box loss: 0.01874 RPN score loss: 0.0038 RPN total loss: 0.02254 Total loss: 0.99621 timestamp: 1655072298.6758773 iteration: 80700 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12784 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.19309 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.14735 RPN box loss: 0.00938 RPN score loss: 0.00646 RPN total loss: 0.01584 Total loss: 0.9188 timestamp: 1655072301.9672601 iteration: 80705 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04703 FastRCNN class loss: 0.04046 FastRCNN total loss: 0.08748 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.078 RPN box loss: 0.004 RPN score loss: 0.00372 RPN total loss: 0.00772 Total loss: 0.73572 timestamp: 1655072305.2167673 iteration: 80710 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07487 FastRCNN class loss: 0.04952 FastRCNN total loss: 0.12439 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12955 RPN box loss: 0.00474 RPN score loss: 0.00228 RPN total loss: 0.00702 Total loss: 0.82348 timestamp: 1655072308.4869874 iteration: 80715 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07258 FastRCNN class loss: 0.04173 FastRCNN total loss: 0.11431 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12686 RPN box loss: 0.00873 RPN score loss: 0.00364 RPN total loss: 0.01236 Total loss: 0.81605 timestamp: 1655072311.713638 iteration: 80720 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19097 FastRCNN class loss: 0.07714 FastRCNN total loss: 0.26811 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13186 RPN box loss: 0.01883 RPN score loss: 0.01399 RPN total loss: 0.03281 Total loss: 0.99529 timestamp: 1655072315.041917 iteration: 80725 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07853 FastRCNN class loss: 0.04179 FastRCNN total loss: 0.12032 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12397 RPN box loss: 0.00886 RPN score loss: 0.00195 RPN total loss: 0.01082 Total loss: 0.81762 timestamp: 1655072318.3402457 iteration: 80730 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05881 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.12134 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13234 RPN box loss: 0.0234 RPN score loss: 0.00233 RPN total loss: 0.02573 Total loss: 0.84194 timestamp: 1655072321.6278281 iteration: 80735 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06681 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.1419 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.10029 RPN box loss: 0.00637 RPN score loss: 0.00252 RPN total loss: 0.00888 Total loss: 0.81359 timestamp: 1655072324.9179327 iteration: 80740 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06113 FastRCNN class loss: 0.03353 FastRCNN total loss: 0.09466 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.09352 RPN box loss: 0.0066 RPN score loss: 0.00312 RPN total loss: 0.00973 Total loss: 0.76042 timestamp: 1655072328.1490314 iteration: 80745 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07442 FastRCNN class loss: 0.0672 FastRCNN total loss: 0.14163 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.13333 RPN box loss: 0.0188 RPN score loss: 0.00394 RPN total loss: 0.02274 Total loss: 0.86021 timestamp: 1655072331.3438654 iteration: 80750 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10756 FastRCNN class loss: 0.08229 FastRCNN total loss: 0.18985 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.01433 RPN score loss: 0.01172 RPN total loss: 0.02605 Total loss: 0.93482 timestamp: 1655072334.6540868 iteration: 80755 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07936 FastRCNN class loss: 0.09308 FastRCNN total loss: 0.17243 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.16276 RPN box loss: 0.01537 RPN score loss: 0.00601 RPN total loss: 0.02138 Total loss: 0.91909 timestamp: 1655072337.923651 iteration: 80760 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06968 FastRCNN class loss: 0.07554 FastRCNN total loss: 0.14522 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.1329 RPN box loss: 0.00935 RPN score loss: 0.00563 RPN total loss: 0.01499 Total loss: 0.85562 timestamp: 1655072341.2499843 iteration: 80765 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14462 FastRCNN class loss: 0.07097 FastRCNN total loss: 0.21559 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.17902 RPN box loss: 0.01547 RPN score loss: 0.00436 RPN total loss: 0.01982 Total loss: 0.97695 timestamp: 1655072344.508352 iteration: 80770 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1859 FastRCNN class loss: 0.09604 FastRCNN total loss: 0.28194 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.17426 RPN box loss: 0.00802 RPN score loss: 0.00245 RPN total loss: 0.01046 Total loss: 1.02918 timestamp: 1655072347.7656696 iteration: 80775 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07173 FastRCNN class loss: 0.0678 FastRCNN total loss: 0.13953 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.11948 RPN box loss: 0.01836 RPN score loss: 0.00386 RPN total loss: 0.02222 Total loss: 0.84375 timestamp: 1655072351.0178227 iteration: 80780 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04784 FastRCNN class loss: 0.04671 FastRCNN total loss: 0.09455 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.14496 RPN box loss: 0.00461 RPN score loss: 0.00117 RPN total loss: 0.00578 Total loss: 0.8078 timestamp: 1655072354.274651 iteration: 80785 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10278 FastRCNN class loss: 0.08141 FastRCNN total loss: 0.18419 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.18095 RPN box loss: 0.00986 RPN score loss: 0.00503 RPN total loss: 0.01489 Total loss: 0.94254 timestamp: 1655072357.489289 iteration: 80790 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07878 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.1578 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.12304 RPN box loss: 0.00927 RPN score loss: 0.00893 RPN total loss: 0.0182 Total loss: 0.86156 timestamp: 1655072360.8084698 iteration: 80795 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06086 FastRCNN class loss: 0.06315 FastRCNN total loss: 0.12401 L1 loss: 0.0000e+00 L2 loss: 0.56252 Learning rate: 4.0000e-05 Mask loss: 0.15226 RPN box loss: 0.00744 RPN score loss: 0.00812 RPN total loss: 0.01556 Total loss: 0.85435 timestamp: 1655072364.14231 iteration: 80800 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16897 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.23735 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.1073 RPN box loss: 0.02323 RPN score loss: 0.00327 RPN total loss: 0.0265 Total loss: 0.93368 timestamp: 1655072367.4036772 iteration: 80805 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10453 FastRCNN class loss: 0.06908 FastRCNN total loss: 0.17361 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15167 RPN box loss: 0.02287 RPN score loss: 0.00415 RPN total loss: 0.02702 Total loss: 0.91481 timestamp: 1655072370.6674793 iteration: 80810 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08298 FastRCNN class loss: 0.03676 FastRCNN total loss: 0.11974 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13418 RPN box loss: 0.00469 RPN score loss: 0.00374 RPN total loss: 0.00843 Total loss: 0.82486 timestamp: 1655072373.9615316 iteration: 80815 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10131 FastRCNN class loss: 0.06608 FastRCNN total loss: 0.16738 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.16303 RPN box loss: 0.01575 RPN score loss: 0.00716 RPN total loss: 0.02291 Total loss: 0.91584 timestamp: 1655072377.1717844 iteration: 80820 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13718 FastRCNN class loss: 0.11288 FastRCNN total loss: 0.25006 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.18791 RPN box loss: 0.00752 RPN score loss: 0.00358 RPN total loss: 0.0111 Total loss: 1.01159 timestamp: 1655072380.4492316 iteration: 80825 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12755 FastRCNN class loss: 0.06883 FastRCNN total loss: 0.19637 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.149 RPN box loss: 0.01128 RPN score loss: 0.00884 RPN total loss: 0.02012 Total loss: 0.92801 timestamp: 1655072383.7054052 iteration: 80830 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09664 FastRCNN class loss: 0.08625 FastRCNN total loss: 0.18289 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14636 RPN box loss: 0.00793 RPN score loss: 0.00374 RPN total loss: 0.01167 Total loss: 0.90344 timestamp: 1655072387.0105605 iteration: 80835 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04021 FastRCNN class loss: 0.06828 FastRCNN total loss: 0.10849 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.10948 RPN box loss: 0.00998 RPN score loss: 0.00417 RPN total loss: 0.01415 Total loss: 0.79464 timestamp: 1655072390.272985 iteration: 80840 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11564 FastRCNN class loss: 0.05951 FastRCNN total loss: 0.17515 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.1295 RPN box loss: 0.00819 RPN score loss: 0.005 RPN total loss: 0.01319 Total loss: 0.88035 timestamp: 1655072393.4648125 iteration: 80845 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04636 FastRCNN class loss: 0.05296 FastRCNN total loss: 0.09932 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.09316 RPN box loss: 0.01018 RPN score loss: 0.00109 RPN total loss: 0.01127 Total loss: 0.76626 timestamp: 1655072396.733308 iteration: 80850 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06079 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.11862 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.10737 RPN box loss: 0.01146 RPN score loss: 0.00373 RPN total loss: 0.01519 Total loss: 0.80369 timestamp: 1655072400.032304 iteration: 80855 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10126 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.1698 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.11814 RPN box loss: 0.00766 RPN score loss: 0.00227 RPN total loss: 0.00992 Total loss: 0.86037 timestamp: 1655072403.2385712 iteration: 80860 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10932 FastRCNN class loss: 0.09088 FastRCNN total loss: 0.2002 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13968 RPN box loss: 0.01964 RPN score loss: 0.01094 RPN total loss: 0.03058 Total loss: 0.93298 timestamp: 1655072406.4541793 iteration: 80865 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09589 FastRCNN class loss: 0.07814 FastRCNN total loss: 0.17402 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15027 RPN box loss: 0.01435 RPN score loss: 0.00955 RPN total loss: 0.02389 Total loss: 0.9107 timestamp: 1655072409.7891014 iteration: 80870 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08927 FastRCNN class loss: 0.07685 FastRCNN total loss: 0.16611 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13676 RPN box loss: 0.01091 RPN score loss: 0.01173 RPN total loss: 0.02263 Total loss: 0.88802 timestamp: 1655072413.0463116 iteration: 80875 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13576 FastRCNN class loss: 0.07049 FastRCNN total loss: 0.20624 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15593 RPN box loss: 0.01162 RPN score loss: 0.00739 RPN total loss: 0.01901 Total loss: 0.94369 timestamp: 1655072416.352267 iteration: 80880 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14401 FastRCNN class loss: 0.13197 FastRCNN total loss: 0.27599 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.24342 RPN box loss: 0.01808 RPN score loss: 0.01131 RPN total loss: 0.02938 Total loss: 1.11131 timestamp: 1655072419.6230845 iteration: 80885 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09648 FastRCNN class loss: 0.09303 FastRCNN total loss: 0.18951 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15058 RPN box loss: 0.0138 RPN score loss: 0.01119 RPN total loss: 0.02499 Total loss: 0.9276 timestamp: 1655072422.8520033 iteration: 80890 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0821 FastRCNN class loss: 0.05704 FastRCNN total loss: 0.13914 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.18017 RPN box loss: 0.00991 RPN score loss: 0.01279 RPN total loss: 0.0227 Total loss: 0.90452 timestamp: 1655072426.086354 iteration: 80895 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07923 FastRCNN class loss: 0.04685 FastRCNN total loss: 0.12607 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.08831 RPN box loss: 0.00665 RPN score loss: 0.00356 RPN total loss: 0.01021 Total loss: 0.7871 timestamp: 1655072429.3412545 iteration: 80900 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08531 FastRCNN class loss: 0.06788 FastRCNN total loss: 0.15319 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.18958 RPN box loss: 0.00787 RPN score loss: 0.02102 RPN total loss: 0.02889 Total loss: 0.93417 timestamp: 1655072432.6912816 iteration: 80905 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0848 FastRCNN class loss: 0.04037 FastRCNN total loss: 0.12518 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.09406 RPN box loss: 0.00824 RPN score loss: 0.00489 RPN total loss: 0.01312 Total loss: 0.79487 timestamp: 1655072435.8959324 iteration: 80910 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10519 FastRCNN class loss: 0.06105 FastRCNN total loss: 0.16624 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.16844 RPN box loss: 0.02634 RPN score loss: 0.01585 RPN total loss: 0.04219 Total loss: 0.93938 timestamp: 1655072439.130855 iteration: 80915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07133 FastRCNN class loss: 0.05492 FastRCNN total loss: 0.12625 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.08722 RPN box loss: 0.01979 RPN score loss: 0.01167 RPN total loss: 0.03145 Total loss: 0.80743 timestamp: 1655072442.3933506 iteration: 80920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04745 FastRCNN class loss: 0.0499 FastRCNN total loss: 0.09735 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.08582 RPN box loss: 0.00467 RPN score loss: 0.00194 RPN total loss: 0.00661 Total loss: 0.7523 timestamp: 1655072445.6821253 iteration: 80925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05207 FastRCNN class loss: 0.04407 FastRCNN total loss: 0.09615 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14589 RPN box loss: 0.00389 RPN score loss: 0.00531 RPN total loss: 0.0092 Total loss: 0.81375 timestamp: 1655072448.920713 iteration: 80930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06208 FastRCNN class loss: 0.05603 FastRCNN total loss: 0.11811 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.11444 RPN box loss: 0.0101 RPN score loss: 0.00297 RPN total loss: 0.01306 Total loss: 0.80813 timestamp: 1655072452.1721282 iteration: 80935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15996 FastRCNN class loss: 0.09642 FastRCNN total loss: 0.25637 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.16203 RPN box loss: 0.0164 RPN score loss: 0.00954 RPN total loss: 0.02595 Total loss: 1.00686 timestamp: 1655072455.4067166 iteration: 80940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10027 FastRCNN class loss: 0.07074 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13593 RPN box loss: 0.00829 RPN score loss: 0.00556 RPN total loss: 0.01384 Total loss: 0.8833 timestamp: 1655072458.7258832 iteration: 80945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08085 FastRCNN class loss: 0.05057 FastRCNN total loss: 0.13142 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13955 RPN box loss: 0.00305 RPN score loss: 0.00323 RPN total loss: 0.00628 Total loss: 0.83977 timestamp: 1655072461.9853723 iteration: 80950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11098 FastRCNN class loss: 0.11366 FastRCNN total loss: 0.22465 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.1864 RPN box loss: 0.02197 RPN score loss: 0.00437 RPN total loss: 0.02634 Total loss: 0.9999 timestamp: 1655072465.2540455 iteration: 80955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07379 FastRCNN class loss: 0.06731 FastRCNN total loss: 0.1411 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.08678 RPN box loss: 0.02216 RPN score loss: 0.00625 RPN total loss: 0.02841 Total loss: 0.8188 timestamp: 1655072468.5356202 iteration: 80960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12856 FastRCNN class loss: 0.08903 FastRCNN total loss: 0.21758 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14986 RPN box loss: 0.01235 RPN score loss: 0.00836 RPN total loss: 0.02071 Total loss: 0.95066 timestamp: 1655072471.8384016 iteration: 80965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08397 FastRCNN class loss: 0.07524 FastRCNN total loss: 0.15921 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14824 RPN box loss: 0.01044 RPN score loss: 0.00943 RPN total loss: 0.01987 Total loss: 0.88983 timestamp: 1655072475.1007278 iteration: 80970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09639 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.15101 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15099 RPN box loss: 0.01553 RPN score loss: 0.00629 RPN total loss: 0.02182 Total loss: 0.88633 timestamp: 1655072478.3311226 iteration: 80975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07705 FastRCNN class loss: 0.07155 FastRCNN total loss: 0.1486 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.11451 RPN box loss: 0.01892 RPN score loss: 0.00426 RPN total loss: 0.02318 Total loss: 0.84879 timestamp: 1655072481.6507509 iteration: 80980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07244 FastRCNN class loss: 0.06037 FastRCNN total loss: 0.13281 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.11145 RPN box loss: 0.00551 RPN score loss: 0.00204 RPN total loss: 0.00755 Total loss: 0.81432 timestamp: 1655072484.8923597 iteration: 80985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.02356 FastRCNN class loss: 0.03516 FastRCNN total loss: 0.05871 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.17667 RPN box loss: 0.0055 RPN score loss: 0.00359 RPN total loss: 0.00909 Total loss: 0.80698 timestamp: 1655072488.2155123 iteration: 80990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.07067 FastRCNN total loss: 0.15561 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.12406 RPN box loss: 0.0078 RPN score loss: 0.00718 RPN total loss: 0.01498 Total loss: 0.85715 timestamp: 1655072491.4611177 iteration: 80995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10922 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.19017 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14103 RPN box loss: 0.02775 RPN score loss: 0.0131 RPN total loss: 0.04085 Total loss: 0.93457 timestamp: 1655072494.7134337 iteration: 81000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13182 FastRCNN class loss: 0.06381 FastRCNN total loss: 0.19562 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.10734 RPN box loss: 0.01716 RPN score loss: 0.00335 RPN total loss: 0.02051 Total loss: 0.88599 timestamp: 1655072497.9800978 iteration: 81005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0793 FastRCNN class loss: 0.05944 FastRCNN total loss: 0.13874 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.12465 RPN box loss: 0.00698 RPN score loss: 0.00494 RPN total loss: 0.01192 Total loss: 0.83782 timestamp: 1655072501.2439716 iteration: 81010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14586 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.21533 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15886 RPN box loss: 0.02149 RPN score loss: 0.00595 RPN total loss: 0.02744 Total loss: 0.96415 timestamp: 1655072504.587045 iteration: 81015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04375 FastRCNN class loss: 0.0371 FastRCNN total loss: 0.08085 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.12938 RPN box loss: 0.00257 RPN score loss: 0.00531 RPN total loss: 0.00788 Total loss: 0.78062 timestamp: 1655072507.8330903 iteration: 81020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1061 FastRCNN class loss: 0.08341 FastRCNN total loss: 0.18951 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.23599 RPN box loss: 0.01942 RPN score loss: 0.01188 RPN total loss: 0.0313 Total loss: 1.01931 timestamp: 1655072511.1527317 iteration: 81025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08367 FastRCNN class loss: 0.07754 FastRCNN total loss: 0.16121 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.09973 RPN box loss: 0.01088 RPN score loss: 0.00627 RPN total loss: 0.01716 Total loss: 0.8406 timestamp: 1655072514.4544914 iteration: 81030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0577 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.11632 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13058 RPN box loss: 0.03913 RPN score loss: 0.01072 RPN total loss: 0.04984 Total loss: 0.85925 timestamp: 1655072517.7658598 iteration: 81035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09855 FastRCNN class loss: 0.08473 FastRCNN total loss: 0.18328 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.16524 RPN box loss: 0.02384 RPN score loss: 0.0069 RPN total loss: 0.03074 Total loss: 0.94176 timestamp: 1655072521.0575824 iteration: 81040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15089 FastRCNN class loss: 0.08903 FastRCNN total loss: 0.23992 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.17239 RPN box loss: 0.01361 RPN score loss: 0.00905 RPN total loss: 0.02266 Total loss: 0.99747 timestamp: 1655072524.3406947 iteration: 81045 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09488 FastRCNN class loss: 0.0498 FastRCNN total loss: 0.14468 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.13197 RPN box loss: 0.01028 RPN score loss: 0.00224 RPN total loss: 0.01252 Total loss: 0.85168 timestamp: 1655072527.5146484 iteration: 81050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05677 FastRCNN class loss: 0.04501 FastRCNN total loss: 0.10179 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14693 RPN box loss: 0.04901 RPN score loss: 0.00496 RPN total loss: 0.05397 Total loss: 0.86519 timestamp: 1655072530.7381856 iteration: 81055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0593 FastRCNN class loss: 0.04714 FastRCNN total loss: 0.10644 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.08948 RPN box loss: 0.00799 RPN score loss: 0.00276 RPN total loss: 0.01075 Total loss: 0.76918 timestamp: 1655072534.046665 iteration: 81060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12998 FastRCNN class loss: 0.07116 FastRCNN total loss: 0.20114 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.12492 RPN box loss: 0.00441 RPN score loss: 0.00534 RPN total loss: 0.00975 Total loss: 0.89832 timestamp: 1655072537.2408202 iteration: 81065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11717 FastRCNN class loss: 0.06841 FastRCNN total loss: 0.18557 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14732 RPN box loss: 0.01602 RPN score loss: 0.00308 RPN total loss: 0.0191 Total loss: 0.91451 timestamp: 1655072540.539479 iteration: 81070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07072 FastRCNN class loss: 0.08643 FastRCNN total loss: 0.15715 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15916 RPN box loss: 0.02214 RPN score loss: 0.0099 RPN total loss: 0.03204 Total loss: 0.91086 timestamp: 1655072543.7825341 iteration: 81075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12087 FastRCNN class loss: 0.04683 FastRCNN total loss: 0.1677 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15843 RPN box loss: 0.01336 RPN score loss: 0.00205 RPN total loss: 0.01541 Total loss: 0.90404 timestamp: 1655072547.0432234 iteration: 81080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08091 FastRCNN class loss: 0.05673 FastRCNN total loss: 0.13764 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.12975 RPN box loss: 0.00561 RPN score loss: 0.0055 RPN total loss: 0.0111 Total loss: 0.84101 timestamp: 1655072550.3936071 iteration: 81085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12104 FastRCNN class loss: 0.09844 FastRCNN total loss: 0.21948 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.17536 RPN box loss: 0.00548 RPN score loss: 0.00165 RPN total loss: 0.00713 Total loss: 0.96447 timestamp: 1655072553.701125 iteration: 81090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11435 FastRCNN class loss: 0.06704 FastRCNN total loss: 0.18139 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15871 RPN box loss: 0.01744 RPN score loss: 0.01003 RPN total loss: 0.02746 Total loss: 0.93006 timestamp: 1655072556.9883358 iteration: 81095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14467 FastRCNN class loss: 0.09854 FastRCNN total loss: 0.24321 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.20847 RPN box loss: 0.01443 RPN score loss: 0.0044 RPN total loss: 0.01883 Total loss: 1.03302 timestamp: 1655072560.2227466 iteration: 81100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09556 FastRCNN class loss: 0.06626 FastRCNN total loss: 0.16182 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.18492 RPN box loss: 0.04183 RPN score loss: 0.00394 RPN total loss: 0.04577 Total loss: 0.95502 timestamp: 1655072563.4918375 iteration: 81105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07518 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.13323 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.15413 RPN box loss: 0.02127 RPN score loss: 0.00528 RPN total loss: 0.02655 Total loss: 0.87642 timestamp: 1655072566.7618783 iteration: 81110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12064 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.18039 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.17215 RPN box loss: 0.01414 RPN score loss: 0.00626 RPN total loss: 0.02039 Total loss: 0.93544 timestamp: 1655072570.062579 iteration: 81115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11441 FastRCNN class loss: 0.09314 FastRCNN total loss: 0.20756 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14798 RPN box loss: 0.01063 RPN score loss: 0.00266 RPN total loss: 0.01329 Total loss: 0.93133 timestamp: 1655072573.3653088 iteration: 81120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11545 FastRCNN class loss: 0.07509 FastRCNN total loss: 0.19054 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.11164 RPN box loss: 0.02465 RPN score loss: 0.00605 RPN total loss: 0.0307 Total loss: 0.89538 timestamp: 1655072576.6589434 iteration: 81125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09393 FastRCNN class loss: 0.05758 FastRCNN total loss: 0.15151 L1 loss: 0.0000e+00 L2 loss: 0.56251 Learning rate: 4.0000e-05 Mask loss: 0.14085 RPN box loss: 0.01387 RPN score loss: 0.00543 RPN total loss: 0.0193 Total loss: 0.87417 timestamp: 1655072579.9807475 iteration: 81130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1058 FastRCNN class loss: 0.03038 FastRCNN total loss: 0.13618 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09595 RPN box loss: 0.00651 RPN score loss: 0.00188 RPN total loss: 0.00838 Total loss: 0.80302 timestamp: 1655072583.285843 iteration: 81135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05836 FastRCNN class loss: 0.05665 FastRCNN total loss: 0.11501 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12712 RPN box loss: 0.00499 RPN score loss: 0.00361 RPN total loss: 0.0086 Total loss: 0.81324 timestamp: 1655072586.5824187 iteration: 81140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.0433 FastRCNN total loss: 0.12195 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09353 RPN box loss: 0.00408 RPN score loss: 0.00254 RPN total loss: 0.00662 Total loss: 0.7846 timestamp: 1655072589.775678 iteration: 81145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13448 FastRCNN class loss: 0.06854 FastRCNN total loss: 0.20302 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09743 RPN box loss: 0.00834 RPN score loss: 0.00539 RPN total loss: 0.01372 Total loss: 0.87668 timestamp: 1655072593.0136552 iteration: 81150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13976 FastRCNN class loss: 0.09911 FastRCNN total loss: 0.23886 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.17422 RPN box loss: 0.0086 RPN score loss: 0.00146 RPN total loss: 0.01006 Total loss: 0.98565 timestamp: 1655072596.305154 iteration: 81155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.06446 FastRCNN total loss: 0.16226 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12081 RPN box loss: 0.00628 RPN score loss: 0.00322 RPN total loss: 0.00951 Total loss: 0.85508 timestamp: 1655072599.5169961 iteration: 81160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10556 FastRCNN class loss: 0.04926 FastRCNN total loss: 0.15481 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09483 RPN box loss: 0.00825 RPN score loss: 0.0025 RPN total loss: 0.01076 Total loss: 0.82291 timestamp: 1655072602.7714694 iteration: 81165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08471 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.1428 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.16638 RPN box loss: 0.00738 RPN score loss: 0.00161 RPN total loss: 0.00899 Total loss: 0.88068 timestamp: 1655072605.9769034 iteration: 81170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11198 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.18152 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12459 RPN box loss: 0.0186 RPN score loss: 0.00281 RPN total loss: 0.02141 Total loss: 0.89002 timestamp: 1655072609.1986177 iteration: 81175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15205 FastRCNN class loss: 0.06436 FastRCNN total loss: 0.2164 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.16406 RPN box loss: 0.01096 RPN score loss: 0.00637 RPN total loss: 0.01733 Total loss: 0.96029 timestamp: 1655072612.463005 iteration: 81180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.11367 FastRCNN total loss: 0.22612 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.157 RPN box loss: 0.02156 RPN score loss: 0.00621 RPN total loss: 0.02777 Total loss: 0.9734 timestamp: 1655072615.6847148 iteration: 81185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11603 FastRCNN class loss: 0.08678 FastRCNN total loss: 0.20282 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.16568 RPN box loss: 0.0087 RPN score loss: 0.0022 RPN total loss: 0.0109 Total loss: 0.9419 timestamp: 1655072618.9084263 iteration: 81190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10579 FastRCNN class loss: 0.07809 FastRCNN total loss: 0.18388 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11294 RPN box loss: 0.01225 RPN score loss: 0.00468 RPN total loss: 0.01693 Total loss: 0.87625 timestamp: 1655072622.2165458 iteration: 81195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07323 FastRCNN class loss: 0.0484 FastRCNN total loss: 0.12164 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13753 RPN box loss: 0.01619 RPN score loss: 0.00473 RPN total loss: 0.02092 Total loss: 0.84259 timestamp: 1655072625.521794 iteration: 81200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09266 FastRCNN class loss: 0.05875 FastRCNN total loss: 0.15141 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12275 RPN box loss: 0.0048 RPN score loss: 0.00372 RPN total loss: 0.00852 Total loss: 0.84518 timestamp: 1655072628.7213097 iteration: 81205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.09467 FastRCNN total loss: 0.18152 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.21194 RPN box loss: 0.11545 RPN score loss: 0.008 RPN total loss: 0.12346 Total loss: 1.07941 timestamp: 1655072631.9784803 iteration: 81210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05561 FastRCNN class loss: 0.03266 FastRCNN total loss: 0.08827 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09847 RPN box loss: 0.00647 RPN score loss: 0.00732 RPN total loss: 0.01379 Total loss: 0.76303 timestamp: 1655072635.2517471 iteration: 81215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07503 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.13756 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.15325 RPN box loss: 0.01634 RPN score loss: 0.00313 RPN total loss: 0.01948 Total loss: 0.87279 timestamp: 1655072638.4954028 iteration: 81220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1246 FastRCNN class loss: 0.07511 FastRCNN total loss: 0.19971 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.17864 RPN box loss: 0.01471 RPN score loss: 0.00662 RPN total loss: 0.02133 Total loss: 0.96218 timestamp: 1655072641.770189 iteration: 81225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07454 FastRCNN class loss: 0.0495 FastRCNN total loss: 0.12404 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12675 RPN box loss: 0.00577 RPN score loss: 0.00272 RPN total loss: 0.00849 Total loss: 0.82178 timestamp: 1655072645.0977502 iteration: 81230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07872 FastRCNN class loss: 0.05742 FastRCNN total loss: 0.13614 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13471 RPN box loss: 0.01098 RPN score loss: 0.01025 RPN total loss: 0.02123 Total loss: 0.85459 timestamp: 1655072648.391467 iteration: 81235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10395 FastRCNN class loss: 0.08051 FastRCNN total loss: 0.18446 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.20503 RPN box loss: 0.00853 RPN score loss: 0.00935 RPN total loss: 0.01788 Total loss: 0.96986 timestamp: 1655072651.6076381 iteration: 81240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13169 FastRCNN class loss: 0.08676 FastRCNN total loss: 0.21844 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.21024 RPN box loss: 0.01521 RPN score loss: 0.00598 RPN total loss: 0.02119 Total loss: 1.01238 timestamp: 1655072654.8674827 iteration: 81245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09029 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.15727 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13653 RPN box loss: 0.01262 RPN score loss: 0.00658 RPN total loss: 0.0192 Total loss: 0.8755 timestamp: 1655072658.0696883 iteration: 81250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.1497 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11166 RPN box loss: 0.012 RPN score loss: 0.00377 RPN total loss: 0.01577 Total loss: 0.83963 timestamp: 1655072661.3780534 iteration: 81255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09521 FastRCNN class loss: 0.08091 FastRCNN total loss: 0.17612 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11538 RPN box loss: 0.01621 RPN score loss: 0.00526 RPN total loss: 0.02147 Total loss: 0.87547 timestamp: 1655072664.5944045 iteration: 81260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15924 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.25901 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.15832 RPN box loss: 0.00452 RPN score loss: 0.00263 RPN total loss: 0.00715 Total loss: 0.98698 timestamp: 1655072667.9097462 iteration: 81265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12506 FastRCNN class loss: 0.09551 FastRCNN total loss: 0.22057 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13216 RPN box loss: 0.02955 RPN score loss: 0.00334 RPN total loss: 0.03289 Total loss: 0.94812 timestamp: 1655072671.126521 iteration: 81270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06958 FastRCNN class loss: 0.05188 FastRCNN total loss: 0.12147 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09106 RPN box loss: 0.00586 RPN score loss: 0.00312 RPN total loss: 0.00899 Total loss: 0.78401 timestamp: 1655072674.3510106 iteration: 81275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09395 FastRCNN class loss: 0.07012 FastRCNN total loss: 0.16408 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.10854 RPN box loss: 0.00553 RPN score loss: 0.00673 RPN total loss: 0.01227 Total loss: 0.84738 timestamp: 1655072677.5738506 iteration: 81280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11561 FastRCNN class loss: 0.06572 FastRCNN total loss: 0.18133 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.18769 RPN box loss: 0.0189 RPN score loss: 0.00429 RPN total loss: 0.02319 Total loss: 0.95472 timestamp: 1655072680.864648 iteration: 81285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07614 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.1465 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.15828 RPN box loss: 0.00771 RPN score loss: 0.00235 RPN total loss: 0.01006 Total loss: 0.87734 timestamp: 1655072684.0666804 iteration: 81290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09972 FastRCNN class loss: 0.04866 FastRCNN total loss: 0.14838 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.14148 RPN box loss: 0.015 RPN score loss: 0.00201 RPN total loss: 0.01701 Total loss: 0.86936 timestamp: 1655072687.3066506 iteration: 81295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09861 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.16893 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11099 RPN box loss: 0.00916 RPN score loss: 0.00565 RPN total loss: 0.01481 Total loss: 0.85723 timestamp: 1655072690.5726933 iteration: 81300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17188 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.25339 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.10746 RPN box loss: 0.01253 RPN score loss: 0.00467 RPN total loss: 0.0172 Total loss: 0.94055 timestamp: 1655072693.8483791 iteration: 81305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07804 FastRCNN class loss: 0.04482 FastRCNN total loss: 0.12286 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09623 RPN box loss: 0.00965 RPN score loss: 0.00113 RPN total loss: 0.01079 Total loss: 0.79238 timestamp: 1655072697.1151178 iteration: 81310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07075 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.13867 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.14441 RPN box loss: 0.00732 RPN score loss: 0.00555 RPN total loss: 0.01287 Total loss: 0.85846 timestamp: 1655072700.4116275 iteration: 81315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13629 FastRCNN class loss: 0.08128 FastRCNN total loss: 0.21756 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.16975 RPN box loss: 0.02025 RPN score loss: 0.00928 RPN total loss: 0.02953 Total loss: 0.97935 timestamp: 1655072703.644965 iteration: 81320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07855 FastRCNN class loss: 0.05993 FastRCNN total loss: 0.13848 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09848 RPN box loss: 0.01632 RPN score loss: 0.00195 RPN total loss: 0.01827 Total loss: 0.81772 timestamp: 1655072706.9141357 iteration: 81325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13103 FastRCNN class loss: 0.08683 FastRCNN total loss: 0.21786 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.18819 RPN box loss: 0.02613 RPN score loss: 0.00413 RPN total loss: 0.03026 Total loss: 0.99881 timestamp: 1655072710.2119355 iteration: 81330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10962 FastRCNN class loss: 0.10101 FastRCNN total loss: 0.21064 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.17718 RPN box loss: 0.01965 RPN score loss: 0.00171 RPN total loss: 0.02136 Total loss: 0.97167 timestamp: 1655072713.4074423 iteration: 81335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03405 FastRCNN class loss: 0.04394 FastRCNN total loss: 0.07799 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.10173 RPN box loss: 0.0094 RPN score loss: 0.00299 RPN total loss: 0.01238 Total loss: 0.7546 timestamp: 1655072716.5928304 iteration: 81340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08886 FastRCNN class loss: 0.07508 FastRCNN total loss: 0.16394 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11651 RPN box loss: 0.01446 RPN score loss: 0.00513 RPN total loss: 0.01959 Total loss: 0.86254 timestamp: 1655072719.8557563 iteration: 81345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11976 FastRCNN class loss: 0.11086 FastRCNN total loss: 0.23062 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.24182 RPN box loss: 0.01104 RPN score loss: 0.01298 RPN total loss: 0.02403 Total loss: 1.05897 timestamp: 1655072723.152682 iteration: 81350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.057 FastRCNN class loss: 0.04275 FastRCNN total loss: 0.09975 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09777 RPN box loss: 0.00799 RPN score loss: 0.00321 RPN total loss: 0.0112 Total loss: 0.77122 timestamp: 1655072726.4470212 iteration: 81355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1123 FastRCNN class loss: 0.06255 FastRCNN total loss: 0.17484 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11144 RPN box loss: 0.00745 RPN score loss: 0.00317 RPN total loss: 0.01062 Total loss: 0.8594 timestamp: 1655072729.6462324 iteration: 81360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08685 FastRCNN class loss: 0.05745 FastRCNN total loss: 0.1443 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.10503 RPN box loss: 0.00424 RPN score loss: 0.00233 RPN total loss: 0.00657 Total loss: 0.81839 timestamp: 1655072732.9492226 iteration: 81365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07334 FastRCNN class loss: 0.02995 FastRCNN total loss: 0.10328 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09337 RPN box loss: 0.01351 RPN score loss: 0.00143 RPN total loss: 0.01494 Total loss: 0.77409 timestamp: 1655072736.3171287 iteration: 81370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10094 FastRCNN class loss: 0.07065 FastRCNN total loss: 0.17159 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12479 RPN box loss: 0.00763 RPN score loss: 0.00304 RPN total loss: 0.01067 Total loss: 0.86955 timestamp: 1655072739.6012332 iteration: 81375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07277 FastRCNN class loss: 0.06595 FastRCNN total loss: 0.13872 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.14597 RPN box loss: 0.00945 RPN score loss: 0.00682 RPN total loss: 0.01627 Total loss: 0.86346 timestamp: 1655072742.8447056 iteration: 81380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09844 FastRCNN class loss: 0.05516 FastRCNN total loss: 0.1536 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12954 RPN box loss: 0.01517 RPN score loss: 0.00801 RPN total loss: 0.02318 Total loss: 0.86882 timestamp: 1655072746.1377969 iteration: 81385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11584 FastRCNN class loss: 0.0529 FastRCNN total loss: 0.16875 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.09811 RPN box loss: 0.00809 RPN score loss: 0.00186 RPN total loss: 0.00995 Total loss: 0.83931 timestamp: 1655072749.43939 iteration: 81390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06534 FastRCNN class loss: 0.04389 FastRCNN total loss: 0.10923 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11501 RPN box loss: 0.00426 RPN score loss: 0.00201 RPN total loss: 0.00627 Total loss: 0.79301 timestamp: 1655072752.7204697 iteration: 81395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07499 FastRCNN class loss: 0.061 FastRCNN total loss: 0.13598 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12884 RPN box loss: 0.00444 RPN score loss: 0.00117 RPN total loss: 0.00561 Total loss: 0.83293 timestamp: 1655072756.007401 iteration: 81400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12259 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.18425 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.12062 RPN box loss: 0.01104 RPN score loss: 0.0066 RPN total loss: 0.01764 Total loss: 0.88501 timestamp: 1655072759.3145146 iteration: 81405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13757 FastRCNN class loss: 0.0877 FastRCNN total loss: 0.22527 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.19748 RPN box loss: 0.04543 RPN score loss: 0.01028 RPN total loss: 0.05571 Total loss: 1.04095 timestamp: 1655072762.5999823 iteration: 81410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10415 FastRCNN class loss: 0.07323 FastRCNN total loss: 0.17738 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13326 RPN box loss: 0.00674 RPN score loss: 0.00256 RPN total loss: 0.00929 Total loss: 0.88243 timestamp: 1655072765.8943079 iteration: 81415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14532 FastRCNN class loss: 0.11974 FastRCNN total loss: 0.26506 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.18221 RPN box loss: 0.01756 RPN score loss: 0.0101 RPN total loss: 0.02765 Total loss: 1.03742 timestamp: 1655072769.1698625 iteration: 81420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08395 FastRCNN class loss: 0.05077 FastRCNN total loss: 0.13472 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.10214 RPN box loss: 0.01418 RPN score loss: 0.00234 RPN total loss: 0.01652 Total loss: 0.81588 timestamp: 1655072772.488334 iteration: 81425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.07506 FastRCNN total loss: 0.15423 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.15303 RPN box loss: 0.03491 RPN score loss: 0.013 RPN total loss: 0.04791 Total loss: 0.91766 timestamp: 1655072775.7764983 iteration: 81430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10011 FastRCNN class loss: 0.08164 FastRCNN total loss: 0.18175 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.17761 RPN box loss: 0.00838 RPN score loss: 0.00919 RPN total loss: 0.01758 Total loss: 0.93944 timestamp: 1655072779.099632 iteration: 81435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12983 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.19973 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.13647 RPN box loss: 0.01379 RPN score loss: 0.00288 RPN total loss: 0.01667 Total loss: 0.91536 timestamp: 1655072782.352933 iteration: 81440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07174 FastRCNN class loss: 0.05942 FastRCNN total loss: 0.13116 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.11976 RPN box loss: 0.00749 RPN score loss: 0.003 RPN total loss: 0.01049 Total loss: 0.82391 timestamp: 1655072785.6248868 iteration: 81445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11275 FastRCNN class loss: 0.07311 FastRCNN total loss: 0.18586 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.16068 RPN box loss: 0.01604 RPN score loss: 0.00468 RPN total loss: 0.02072 Total loss: 0.92974 timestamp: 1655072788.9498088 iteration: 81450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07 FastRCNN class loss: 0.07562 FastRCNN total loss: 0.14562 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.1648 RPN box loss: 0.00743 RPN score loss: 0.00832 RPN total loss: 0.01575 Total loss: 0.88867 timestamp: 1655072792.2572296 iteration: 81455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11062 FastRCNN class loss: 0.09342 FastRCNN total loss: 0.20404 L1 loss: 0.0000e+00 L2 loss: 0.5625 Learning rate: 4.0000e-05 Mask loss: 0.17307 RPN box loss: 0.01256 RPN score loss: 0.0057 RPN total loss: 0.01827 Total loss: 0.95788 timestamp: 1655072795.477995 iteration: 81460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08742 FastRCNN class loss: 0.0774 FastRCNN total loss: 0.16483 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13502 RPN box loss: 0.02397 RPN score loss: 0.00362 RPN total loss: 0.02759 Total loss: 0.88993 timestamp: 1655072798.7837684 iteration: 81465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.0934 FastRCNN total loss: 0.16699 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15331 RPN box loss: 0.01134 RPN score loss: 0.00427 RPN total loss: 0.01561 Total loss: 0.8984 timestamp: 1655072802.0768938 iteration: 81470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.097 FastRCNN class loss: 0.11883 FastRCNN total loss: 0.21583 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.21715 RPN box loss: 0.01866 RPN score loss: 0.00806 RPN total loss: 0.02672 Total loss: 1.0222 timestamp: 1655072805.4553783 iteration: 81475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12158 FastRCNN class loss: 0.06916 FastRCNN total loss: 0.19074 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15969 RPN box loss: 0.01326 RPN score loss: 0.00581 RPN total loss: 0.01907 Total loss: 0.93199 timestamp: 1655072808.6846201 iteration: 81480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.05327 FastRCNN total loss: 0.13085 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10522 RPN box loss: 0.01665 RPN score loss: 0.00455 RPN total loss: 0.02121 Total loss: 0.81977 timestamp: 1655072812.0430825 iteration: 81485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09406 FastRCNN class loss: 0.08278 FastRCNN total loss: 0.17684 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.17357 RPN box loss: 0.02683 RPN score loss: 0.007 RPN total loss: 0.03383 Total loss: 0.94673 timestamp: 1655072815.3305142 iteration: 81490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05444 FastRCNN class loss: 0.0523 FastRCNN total loss: 0.10674 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.08311 RPN box loss: 0.00933 RPN score loss: 0.00253 RPN total loss: 0.01185 Total loss: 0.7642 timestamp: 1655072818.610202 iteration: 81495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11712 FastRCNN class loss: 0.06432 FastRCNN total loss: 0.18144 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13536 RPN box loss: 0.00655 RPN score loss: 0.0095 RPN total loss: 0.01606 Total loss: 0.89535 timestamp: 1655072821.857102 iteration: 81500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11705 FastRCNN class loss: 0.10437 FastRCNN total loss: 0.22142 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.23344 RPN box loss: 0.03077 RPN score loss: 0.01166 RPN total loss: 0.04243 Total loss: 1.05978 timestamp: 1655072825.116382 iteration: 81505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06523 FastRCNN class loss: 0.03645 FastRCNN total loss: 0.10168 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11607 RPN box loss: 0.02307 RPN score loss: 0.00424 RPN total loss: 0.02731 Total loss: 0.80756 timestamp: 1655072828.3673272 iteration: 81510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0623 FastRCNN class loss: 0.06178 FastRCNN total loss: 0.12407 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.17082 RPN box loss: 0.0127 RPN score loss: 0.00554 RPN total loss: 0.01824 Total loss: 0.87563 timestamp: 1655072831.6273816 iteration: 81515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1077 FastRCNN class loss: 0.05665 FastRCNN total loss: 0.16435 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1005 RPN box loss: 0.00772 RPN score loss: 0.00382 RPN total loss: 0.01154 Total loss: 0.83888 timestamp: 1655072834.9384584 iteration: 81520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08493 FastRCNN class loss: 0.08342 FastRCNN total loss: 0.16835 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15103 RPN box loss: 0.00955 RPN score loss: 0.00757 RPN total loss: 0.01711 Total loss: 0.89898 timestamp: 1655072838.1839545 iteration: 81525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05128 FastRCNN class loss: 0.04328 FastRCNN total loss: 0.09456 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1304 RPN box loss: 0.00501 RPN score loss: 0.00448 RPN total loss: 0.0095 Total loss: 0.79695 timestamp: 1655072841.459271 iteration: 81530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05683 FastRCNN class loss: 0.05367 FastRCNN total loss: 0.1105 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13409 RPN box loss: 0.01941 RPN score loss: 0.01123 RPN total loss: 0.03065 Total loss: 0.83773 timestamp: 1655072844.7694173 iteration: 81535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09523 FastRCNN class loss: 0.07149 FastRCNN total loss: 0.16672 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15652 RPN box loss: 0.01883 RPN score loss: 0.00291 RPN total loss: 0.02175 Total loss: 0.90748 timestamp: 1655072847.9773881 iteration: 81540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07809 FastRCNN class loss: 0.04617 FastRCNN total loss: 0.12426 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16594 RPN box loss: 0.00424 RPN score loss: 0.00157 RPN total loss: 0.00581 Total loss: 0.85851 timestamp: 1655072851.2065904 iteration: 81545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07791 FastRCNN class loss: 0.04579 FastRCNN total loss: 0.1237 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11885 RPN box loss: 0.00819 RPN score loss: 0.00123 RPN total loss: 0.00943 Total loss: 0.81447 timestamp: 1655072854.46482 iteration: 81550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05428 FastRCNN class loss: 0.02934 FastRCNN total loss: 0.08362 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10632 RPN box loss: 0.01051 RPN score loss: 0.00187 RPN total loss: 0.01238 Total loss: 0.76481 timestamp: 1655072857.7634528 iteration: 81555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16595 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.23776 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10437 RPN box loss: 0.00823 RPN score loss: 0.00822 RPN total loss: 0.01645 Total loss: 0.92108 timestamp: 1655072861.0711782 iteration: 81560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10341 FastRCNN class loss: 0.05709 FastRCNN total loss: 0.16051 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11832 RPN box loss: 0.01207 RPN score loss: 0.00588 RPN total loss: 0.01796 Total loss: 0.85928 timestamp: 1655072864.4500704 iteration: 81565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08908 FastRCNN class loss: 0.0872 FastRCNN total loss: 0.17628 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13076 RPN box loss: 0.01621 RPN score loss: 0.00641 RPN total loss: 0.02262 Total loss: 0.89215 timestamp: 1655072867.668629 iteration: 81570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10323 FastRCNN class loss: 0.10434 FastRCNN total loss: 0.20757 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.18378 RPN box loss: 0.02322 RPN score loss: 0.00407 RPN total loss: 0.0273 Total loss: 0.98113 timestamp: 1655072870.9329746 iteration: 81575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12044 FastRCNN class loss: 0.10178 FastRCNN total loss: 0.22222 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16316 RPN box loss: 0.03002 RPN score loss: 0.01025 RPN total loss: 0.04027 Total loss: 0.98814 timestamp: 1655072874.1618328 iteration: 81580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05852 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.10351 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.12525 RPN box loss: 0.00645 RPN score loss: 0.00346 RPN total loss: 0.00991 Total loss: 0.80116 timestamp: 1655072877.365009 iteration: 81585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0937 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.14992 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1203 RPN box loss: 0.00599 RPN score loss: 0.0058 RPN total loss: 0.01179 Total loss: 0.8445 timestamp: 1655072880.6094968 iteration: 81590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11765 FastRCNN class loss: 0.06409 FastRCNN total loss: 0.18174 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.18365 RPN box loss: 0.03831 RPN score loss: 0.00894 RPN total loss: 0.04725 Total loss: 0.97513 timestamp: 1655072883.891509 iteration: 81595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05073 FastRCNN class loss: 0.04794 FastRCNN total loss: 0.09867 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16271 RPN box loss: 0.00705 RPN score loss: 0.00185 RPN total loss: 0.0089 Total loss: 0.83277 timestamp: 1655072887.153517 iteration: 81600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10858 FastRCNN class loss: 0.10888 FastRCNN total loss: 0.21746 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.18303 RPN box loss: 0.01073 RPN score loss: 0.00736 RPN total loss: 0.0181 Total loss: 0.98108 timestamp: 1655072890.4295762 iteration: 81605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1626 FastRCNN class loss: 0.12763 FastRCNN total loss: 0.29023 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.17475 RPN box loss: 0.02084 RPN score loss: 0.01372 RPN total loss: 0.03456 Total loss: 1.06203 timestamp: 1655072893.6706476 iteration: 81610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12837 FastRCNN class loss: 0.09718 FastRCNN total loss: 0.22555 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15667 RPN box loss: 0.01887 RPN score loss: 0.00288 RPN total loss: 0.02175 Total loss: 0.96646 timestamp: 1655072896.9563522 iteration: 81615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.06927 FastRCNN total loss: 0.16932 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13279 RPN box loss: 0.02176 RPN score loss: 0.0025 RPN total loss: 0.02425 Total loss: 0.88885 timestamp: 1655072900.259126 iteration: 81620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09083 FastRCNN class loss: 0.08391 FastRCNN total loss: 0.17474 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11763 RPN box loss: 0.00818 RPN score loss: 0.00547 RPN total loss: 0.01365 Total loss: 0.86852 timestamp: 1655072903.5179894 iteration: 81625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12516 FastRCNN class loss: 0.10299 FastRCNN total loss: 0.22815 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16008 RPN box loss: 0.0606 RPN score loss: 0.00757 RPN total loss: 0.06817 Total loss: 1.01888 timestamp: 1655072906.8032598 iteration: 81630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06447 FastRCNN class loss: 0.04293 FastRCNN total loss: 0.10739 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.12975 RPN box loss: 0.00741 RPN score loss: 0.00551 RPN total loss: 0.01292 Total loss: 0.81256 timestamp: 1655072910.0784624 iteration: 81635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07664 FastRCNN class loss: 0.12035 FastRCNN total loss: 0.19699 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.23757 RPN box loss: 0.03659 RPN score loss: 0.06925 RPN total loss: 0.10584 Total loss: 1.10289 timestamp: 1655072913.287422 iteration: 81640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06717 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.15501 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.17118 RPN box loss: 0.01894 RPN score loss: 0.00355 RPN total loss: 0.02249 Total loss: 0.91117 timestamp: 1655072916.5308928 iteration: 81645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1062 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.17334 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15442 RPN box loss: 0.01718 RPN score loss: 0.00386 RPN total loss: 0.02104 Total loss: 0.91128 timestamp: 1655072919.8362162 iteration: 81650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.05928 FastRCNN total loss: 0.15995 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16233 RPN box loss: 0.00903 RPN score loss: 0.00924 RPN total loss: 0.01827 Total loss: 0.90303 timestamp: 1655072923.064676 iteration: 81655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14726 FastRCNN class loss: 0.06575 FastRCNN total loss: 0.21302 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11393 RPN box loss: 0.01317 RPN score loss: 0.00646 RPN total loss: 0.01963 Total loss: 0.90907 timestamp: 1655072926.3044705 iteration: 81660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11911 FastRCNN class loss: 0.08196 FastRCNN total loss: 0.20107 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16183 RPN box loss: 0.01171 RPN score loss: 0.00792 RPN total loss: 0.01963 Total loss: 0.94503 timestamp: 1655072929.536432 iteration: 81665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09018 FastRCNN class loss: 0.0575 FastRCNN total loss: 0.14768 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.12052 RPN box loss: 0.01149 RPN score loss: 0.00237 RPN total loss: 0.01386 Total loss: 0.84455 timestamp: 1655072932.7883234 iteration: 81670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04587 FastRCNN class loss: 0.05785 FastRCNN total loss: 0.10372 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10535 RPN box loss: 0.01106 RPN score loss: 0.00479 RPN total loss: 0.01585 Total loss: 0.78741 timestamp: 1655072936.1134894 iteration: 81675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1108 FastRCNN class loss: 0.07588 FastRCNN total loss: 0.18667 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10982 RPN box loss: 0.02867 RPN score loss: 0.00164 RPN total loss: 0.03031 Total loss: 0.88929 timestamp: 1655072939.373565 iteration: 81680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.04542 FastRCNN total loss: 0.1203 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.09434 RPN box loss: 0.02006 RPN score loss: 0.00132 RPN total loss: 0.02137 Total loss: 0.7985 timestamp: 1655072942.614482 iteration: 81685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08534 FastRCNN class loss: 0.10422 FastRCNN total loss: 0.18957 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1783 RPN box loss: 0.01062 RPN score loss: 0.00441 RPN total loss: 0.01503 Total loss: 0.94538 timestamp: 1655072945.906926 iteration: 81690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06471 FastRCNN class loss: 0.07126 FastRCNN total loss: 0.13597 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15837 RPN box loss: 0.01754 RPN score loss: 0.00721 RPN total loss: 0.02475 Total loss: 0.88158 timestamp: 1655072949.2094226 iteration: 81695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08069 FastRCNN class loss: 0.0809 FastRCNN total loss: 0.16159 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.11584 RPN box loss: 0.0054 RPN score loss: 0.00164 RPN total loss: 0.00704 Total loss: 0.84696 timestamp: 1655072952.528636 iteration: 81700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09071 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.15104 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.12319 RPN box loss: 0.0143 RPN score loss: 0.00483 RPN total loss: 0.01913 Total loss: 0.85585 timestamp: 1655072955.8150258 iteration: 81705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14755 FastRCNN class loss: 0.11323 FastRCNN total loss: 0.26078 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.17617 RPN box loss: 0.01165 RPN score loss: 0.01413 RPN total loss: 0.02578 Total loss: 1.02522 timestamp: 1655072959.0660305 iteration: 81710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10238 FastRCNN class loss: 0.08212 FastRCNN total loss: 0.1845 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13343 RPN box loss: 0.05533 RPN score loss: 0.00989 RPN total loss: 0.06522 Total loss: 0.94564 timestamp: 1655072962.3763206 iteration: 81715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08914 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.15593 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16751 RPN box loss: 0.00895 RPN score loss: 0.00231 RPN total loss: 0.01126 Total loss: 0.89718 timestamp: 1655072965.6643622 iteration: 81720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08851 FastRCNN class loss: 0.04711 FastRCNN total loss: 0.13562 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10389 RPN box loss: 0.01014 RPN score loss: 0.01089 RPN total loss: 0.02103 Total loss: 0.82303 timestamp: 1655072968.9539003 iteration: 81725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12653 FastRCNN class loss: 0.10515 FastRCNN total loss: 0.23168 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.21969 RPN box loss: 0.01959 RPN score loss: 0.00889 RPN total loss: 0.02848 Total loss: 1.04234 timestamp: 1655072972.2262635 iteration: 81730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05326 FastRCNN class loss: 0.03377 FastRCNN total loss: 0.08704 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1515 RPN box loss: 0.00848 RPN score loss: 0.00171 RPN total loss: 0.0102 Total loss: 0.81122 timestamp: 1655072975.4869933 iteration: 81735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09831 FastRCNN class loss: 0.09543 FastRCNN total loss: 0.19374 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1306 RPN box loss: 0.01965 RPN score loss: 0.00349 RPN total loss: 0.02314 Total loss: 0.90997 timestamp: 1655072978.7808526 iteration: 81740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12669 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.1889 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.13751 RPN box loss: 0.01225 RPN score loss: 0.00374 RPN total loss: 0.01598 Total loss: 0.90489 timestamp: 1655072982.092131 iteration: 81745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.05214 FastRCNN total loss: 0.12081 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1135 RPN box loss: 0.00428 RPN score loss: 0.00379 RPN total loss: 0.00807 Total loss: 0.80486 timestamp: 1655072985.3467996 iteration: 81750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09967 FastRCNN class loss: 0.06097 FastRCNN total loss: 0.16064 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.12163 RPN box loss: 0.00618 RPN score loss: 0.00239 RPN total loss: 0.00857 Total loss: 0.85332 timestamp: 1655072988.5949223 iteration: 81755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05983 FastRCNN class loss: 0.04333 FastRCNN total loss: 0.10316 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.10946 RPN box loss: 0.0067 RPN score loss: 0.00109 RPN total loss: 0.00779 Total loss: 0.7829 timestamp: 1655072991.820858 iteration: 81760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10129 FastRCNN class loss: 0.10478 FastRCNN total loss: 0.20607 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1081 RPN box loss: 0.02282 RPN score loss: 0.00661 RPN total loss: 0.02944 Total loss: 0.90609 timestamp: 1655072995.1228542 iteration: 81765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11396 FastRCNN class loss: 0.07879 FastRCNN total loss: 0.19274 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.19772 RPN box loss: 0.02525 RPN score loss: 0.00274 RPN total loss: 0.02799 Total loss: 0.98094 timestamp: 1655072998.3313224 iteration: 81770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12538 FastRCNN class loss: 0.0749 FastRCNN total loss: 0.20028 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.1724 RPN box loss: 0.00988 RPN score loss: 0.01106 RPN total loss: 0.02095 Total loss: 0.95611 timestamp: 1655073001.5870833 iteration: 81775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07057 FastRCNN class loss: 0.05462 FastRCNN total loss: 0.12519 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.16004 RPN box loss: 0.01633 RPN score loss: 0.00374 RPN total loss: 0.02008 Total loss: 0.86778 timestamp: 1655073004.8251903 iteration: 81780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.07758 FastRCNN total loss: 0.1932 L1 loss: 0.0000e+00 L2 loss: 0.56249 Learning rate: 4.0000e-05 Mask loss: 0.15458 RPN box loss: 0.01172 RPN score loss: 0.00582 RPN total loss: 0.01754 Total loss: 0.9278 timestamp: 1655073008.0904179 iteration: 81785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07061 FastRCNN class loss: 0.04235 FastRCNN total loss: 0.11296 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1234 RPN box loss: 0.0058 RPN score loss: 0.00071 RPN total loss: 0.00651 Total loss: 0.80535 timestamp: 1655073011.3674798 iteration: 81790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12872 FastRCNN class loss: 0.08356 FastRCNN total loss: 0.21228 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.16572 RPN box loss: 0.02515 RPN score loss: 0.00549 RPN total loss: 0.03065 Total loss: 0.97113 timestamp: 1655073014.6587825 iteration: 81795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05245 FastRCNN class loss: 0.04851 FastRCNN total loss: 0.10096 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.15273 RPN box loss: 0.01974 RPN score loss: 0.00228 RPN total loss: 0.02203 Total loss: 0.83821 timestamp: 1655073017.956175 iteration: 81800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13404 FastRCNN class loss: 0.0794 FastRCNN total loss: 0.21344 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.18837 RPN box loss: 0.0175 RPN score loss: 0.00387 RPN total loss: 0.02137 Total loss: 0.98566 timestamp: 1655073021.2886229 iteration: 81805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05381 FastRCNN class loss: 0.04978 FastRCNN total loss: 0.10359 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13556 RPN box loss: 0.0131 RPN score loss: 0.00224 RPN total loss: 0.01534 Total loss: 0.81697 timestamp: 1655073024.54954 iteration: 81810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10228 FastRCNN class loss: 0.06783 FastRCNN total loss: 0.17011 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.09798 RPN box loss: 0.00784 RPN score loss: 0.00238 RPN total loss: 0.01023 Total loss: 0.8408 timestamp: 1655073027.8133893 iteration: 81815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10421 FastRCNN class loss: 0.06683 FastRCNN total loss: 0.17104 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13731 RPN box loss: 0.01148 RPN score loss: 0.00745 RPN total loss: 0.01892 Total loss: 0.88975 timestamp: 1655073031.0990381 iteration: 81820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08262 FastRCNN class loss: 0.07348 FastRCNN total loss: 0.15611 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1219 RPN box loss: 0.00635 RPN score loss: 0.00238 RPN total loss: 0.00873 Total loss: 0.84922 timestamp: 1655073034.3808384 iteration: 81825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10738 FastRCNN class loss: 0.07872 FastRCNN total loss: 0.1861 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.18773 RPN box loss: 0.01532 RPN score loss: 0.00509 RPN total loss: 0.02042 Total loss: 0.95673 timestamp: 1655073037.6961744 iteration: 81830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08923 FastRCNN class loss: 0.04223 FastRCNN total loss: 0.13146 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.11702 RPN box loss: 0.01292 RPN score loss: 0.00439 RPN total loss: 0.01731 Total loss: 0.82826 timestamp: 1655073040.922698 iteration: 81835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14933 FastRCNN class loss: 0.08022 FastRCNN total loss: 0.22955 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1096 RPN box loss: 0.00856 RPN score loss: 0.00323 RPN total loss: 0.01179 Total loss: 0.91343 timestamp: 1655073044.182976 iteration: 81840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0799 FastRCNN class loss: 0.05062 FastRCNN total loss: 0.13052 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.09792 RPN box loss: 0.00509 RPN score loss: 0.0062 RPN total loss: 0.01129 Total loss: 0.80221 timestamp: 1655073047.41637 iteration: 81845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06022 FastRCNN class loss: 0.06661 FastRCNN total loss: 0.12684 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.09769 RPN box loss: 0.01144 RPN score loss: 0.00226 RPN total loss: 0.0137 Total loss: 0.80071 timestamp: 1655073050.6477506 iteration: 81850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09683 FastRCNN class loss: 0.07549 FastRCNN total loss: 0.17232 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13878 RPN box loss: 0.06373 RPN score loss: 0.00551 RPN total loss: 0.06924 Total loss: 0.94281 timestamp: 1655073053.9262338 iteration: 81855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08144 FastRCNN class loss: 0.08963 FastRCNN total loss: 0.17107 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.12342 RPN box loss: 0.00722 RPN score loss: 0.00296 RPN total loss: 0.01018 Total loss: 0.86715 timestamp: 1655073057.2576616 iteration: 81860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10246 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.16591 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13538 RPN box loss: 0.01565 RPN score loss: 0.00258 RPN total loss: 0.01823 Total loss: 0.88201 timestamp: 1655073060.4992757 iteration: 81865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10745 FastRCNN class loss: 0.10392 FastRCNN total loss: 0.21137 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.15592 RPN box loss: 0.01904 RPN score loss: 0.00849 RPN total loss: 0.02753 Total loss: 0.95731 timestamp: 1655073063.7611866 iteration: 81870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10801 FastRCNN class loss: 0.1013 FastRCNN total loss: 0.20931 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.19667 RPN box loss: 0.00635 RPN score loss: 0.00557 RPN total loss: 0.01192 Total loss: 0.98039 timestamp: 1655073067.0019832 iteration: 81875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07456 FastRCNN class loss: 0.04799 FastRCNN total loss: 0.12255 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1322 RPN box loss: 0.01695 RPN score loss: 0.00356 RPN total loss: 0.02051 Total loss: 0.83774 timestamp: 1655073070.280603 iteration: 81880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05271 FastRCNN class loss: 0.04692 FastRCNN total loss: 0.09963 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.17721 RPN box loss: 0.01023 RPN score loss: 0.00407 RPN total loss: 0.0143 Total loss: 0.85362 timestamp: 1655073073.6483717 iteration: 81885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06373 FastRCNN class loss: 0.04561 FastRCNN total loss: 0.10935 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.20205 RPN box loss: 0.01376 RPN score loss: 0.002 RPN total loss: 0.01576 Total loss: 0.88964 timestamp: 1655073076.8317354 iteration: 81890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06344 FastRCNN class loss: 0.0654 FastRCNN total loss: 0.12885 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14199 RPN box loss: 0.01068 RPN score loss: 0.00215 RPN total loss: 0.01283 Total loss: 0.84615 timestamp: 1655073080.1003952 iteration: 81895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12126 FastRCNN class loss: 0.07111 FastRCNN total loss: 0.19236 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1845 RPN box loss: 0.03018 RPN score loss: 0.00887 RPN total loss: 0.03905 Total loss: 0.9784 timestamp: 1655073083.3903732 iteration: 81900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07593 FastRCNN class loss: 0.06051 FastRCNN total loss: 0.13644 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.12155 RPN box loss: 0.01029 RPN score loss: 0.0155 RPN total loss: 0.02578 Total loss: 0.84626 timestamp: 1655073086.6911676 iteration: 81905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08761 FastRCNN class loss: 0.05238 FastRCNN total loss: 0.13999 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.12712 RPN box loss: 0.01494 RPN score loss: 0.00893 RPN total loss: 0.02387 Total loss: 0.85345 timestamp: 1655073089.980224 iteration: 81910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1146 FastRCNN class loss: 0.10026 FastRCNN total loss: 0.21486 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.23676 RPN box loss: 0.0167 RPN score loss: 0.00517 RPN total loss: 0.02187 Total loss: 1.03597 timestamp: 1655073093.2704668 iteration: 81915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08575 FastRCNN class loss: 0.04292 FastRCNN total loss: 0.12867 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.10775 RPN box loss: 0.0224 RPN score loss: 0.00325 RPN total loss: 0.02565 Total loss: 0.82455 timestamp: 1655073096.635619 iteration: 81920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09677 FastRCNN class loss: 0.06468 FastRCNN total loss: 0.16145 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.12312 RPN box loss: 0.0053 RPN score loss: 0.00732 RPN total loss: 0.01261 Total loss: 0.85966 timestamp: 1655073099.9755378 iteration: 81925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.06323 FastRCNN total loss: 0.18466 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.17836 RPN box loss: 0.0167 RPN score loss: 0.00116 RPN total loss: 0.01785 Total loss: 0.94335 timestamp: 1655073103.293426 iteration: 81930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10678 FastRCNN class loss: 0.08374 FastRCNN total loss: 0.19052 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13971 RPN box loss: 0.01317 RPN score loss: 0.00199 RPN total loss: 0.01515 Total loss: 0.90786 timestamp: 1655073106.535301 iteration: 81935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12769 FastRCNN class loss: 0.07803 FastRCNN total loss: 0.20572 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.17888 RPN box loss: 0.04002 RPN score loss: 0.01858 RPN total loss: 0.05861 Total loss: 1.00569 timestamp: 1655073109.7821147 iteration: 81940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06406 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.12277 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.15679 RPN box loss: 0.00657 RPN score loss: 0.00325 RPN total loss: 0.00982 Total loss: 0.85185 timestamp: 1655073113.0539205 iteration: 81945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05859 FastRCNN class loss: 0.06429 FastRCNN total loss: 0.12288 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.09158 RPN box loss: 0.01051 RPN score loss: 0.00394 RPN total loss: 0.01445 Total loss: 0.79139 timestamp: 1655073116.3728716 iteration: 81950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06663 FastRCNN class loss: 0.0457 FastRCNN total loss: 0.11233 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14709 RPN box loss: 0.01852 RPN score loss: 0.00601 RPN total loss: 0.02452 Total loss: 0.84642 timestamp: 1655073119.6480634 iteration: 81955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07173 FastRCNN class loss: 0.0485 FastRCNN total loss: 0.12023 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13089 RPN box loss: 0.01062 RPN score loss: 0.00489 RPN total loss: 0.01551 Total loss: 0.82911 timestamp: 1655073123.0139034 iteration: 81960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05871 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.11859 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1246 RPN box loss: 0.01155 RPN score loss: 0.00316 RPN total loss: 0.01471 Total loss: 0.82038 timestamp: 1655073126.3033042 iteration: 81965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09537 FastRCNN class loss: 0.07621 FastRCNN total loss: 0.17158 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14607 RPN box loss: 0.01256 RPN score loss: 0.00365 RPN total loss: 0.01621 Total loss: 0.89633 timestamp: 1655073129.6367218 iteration: 81970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08588 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.1423 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.11884 RPN box loss: 0.00863 RPN score loss: 0.00378 RPN total loss: 0.01241 Total loss: 0.83603 timestamp: 1655073132.883873 iteration: 81975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08631 FastRCNN class loss: 0.11364 FastRCNN total loss: 0.19996 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.20068 RPN box loss: 0.01596 RPN score loss: 0.02094 RPN total loss: 0.03691 Total loss: 1.00002 timestamp: 1655073136.118609 iteration: 81980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09015 FastRCNN class loss: 0.06911 FastRCNN total loss: 0.15926 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13537 RPN box loss: 0.00881 RPN score loss: 0.00722 RPN total loss: 0.01604 Total loss: 0.87314 timestamp: 1655073139.4548106 iteration: 81985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11355 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.18551 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.15247 RPN box loss: 0.0166 RPN score loss: 0.00522 RPN total loss: 0.02183 Total loss: 0.92229 timestamp: 1655073142.7457325 iteration: 81990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.08367 FastRCNN total loss: 0.15724 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.21984 RPN box loss: 0.02214 RPN score loss: 0.00406 RPN total loss: 0.02619 Total loss: 0.96575 timestamp: 1655073146.092175 iteration: 81995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09193 FastRCNN class loss: 0.05233 FastRCNN total loss: 0.14426 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13527 RPN box loss: 0.03703 RPN score loss: 0.00314 RPN total loss: 0.04017 Total loss: 0.88217 timestamp: 1655073149.374335 iteration: 82000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09006 FastRCNN class loss: 0.07377 FastRCNN total loss: 0.16382 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.11386 RPN box loss: 0.01068 RPN score loss: 0.00373 RPN total loss: 0.01441 Total loss: 0.85457 timestamp: 1655073152.637018 iteration: 82005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06954 FastRCNN class loss: 0.05419 FastRCNN total loss: 0.12373 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.18669 RPN box loss: 0.00338 RPN score loss: 0.00349 RPN total loss: 0.00688 Total loss: 0.87978 timestamp: 1655073155.849579 iteration: 82010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11377 FastRCNN class loss: 0.071 FastRCNN total loss: 0.18477 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.21977 RPN box loss: 0.00829 RPN score loss: 0.00539 RPN total loss: 0.01368 Total loss: 0.9807 timestamp: 1655073159.0838528 iteration: 82015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12882 FastRCNN class loss: 0.0829 FastRCNN total loss: 0.21172 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14223 RPN box loss: 0.01656 RPN score loss: 0.0088 RPN total loss: 0.02536 Total loss: 0.94179 timestamp: 1655073162.3936803 iteration: 82020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10555 FastRCNN class loss: 0.09317 FastRCNN total loss: 0.19872 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.16265 RPN box loss: 0.02363 RPN score loss: 0.01224 RPN total loss: 0.03587 Total loss: 0.95972 timestamp: 1655073165.7042325 iteration: 82025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.09281 FastRCNN total loss: 0.19465 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.1498 RPN box loss: 0.03821 RPN score loss: 0.00769 RPN total loss: 0.0459 Total loss: 0.95282 timestamp: 1655073168.989802 iteration: 82030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11186 FastRCNN class loss: 0.0691 FastRCNN total loss: 0.18095 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.16188 RPN box loss: 0.01272 RPN score loss: 0.00261 RPN total loss: 0.01533 Total loss: 0.92064 timestamp: 1655073172.3374138 iteration: 82035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.04335 FastRCNN total loss: 0.11516 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.10039 RPN box loss: 0.00681 RPN score loss: 0.00528 RPN total loss: 0.01209 Total loss: 0.79012 timestamp: 1655073175.5887945 iteration: 82040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09284 FastRCNN class loss: 0.05735 FastRCNN total loss: 0.15019 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.10361 RPN box loss: 0.01417 RPN score loss: 0.00418 RPN total loss: 0.01835 Total loss: 0.83463 timestamp: 1655073178.8053308 iteration: 82045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11891 FastRCNN class loss: 0.07304 FastRCNN total loss: 0.19195 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.16345 RPN box loss: 0.03173 RPN score loss: 0.00772 RPN total loss: 0.03945 Total loss: 0.95733 timestamp: 1655073182.0850685 iteration: 82050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11504 FastRCNN class loss: 0.03451 FastRCNN total loss: 0.14954 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14321 RPN box loss: 0.01195 RPN score loss: 0.00366 RPN total loss: 0.01561 Total loss: 0.87085 timestamp: 1655073185.3995247 iteration: 82055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06759 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.14199 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13737 RPN box loss: 0.01396 RPN score loss: 0.00532 RPN total loss: 0.01928 Total loss: 0.86111 timestamp: 1655073188.665223 iteration: 82060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15137 FastRCNN class loss: 0.1043 FastRCNN total loss: 0.25566 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13415 RPN box loss: 0.00536 RPN score loss: 0.00871 RPN total loss: 0.01406 Total loss: 0.96636 timestamp: 1655073191.9586546 iteration: 82065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0784 FastRCNN class loss: 0.08771 FastRCNN total loss: 0.16611 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.15972 RPN box loss: 0.00577 RPN score loss: 0.01169 RPN total loss: 0.01746 Total loss: 0.90576 timestamp: 1655073195.128795 iteration: 82070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10686 FastRCNN class loss: 0.05808 FastRCNN total loss: 0.16494 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14573 RPN box loss: 0.00301 RPN score loss: 0.0015 RPN total loss: 0.00451 Total loss: 0.87766 timestamp: 1655073198.35135 iteration: 82075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0542 FastRCNN class loss: 0.045 FastRCNN total loss: 0.0992 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.14706 RPN box loss: 0.00846 RPN score loss: 0.01055 RPN total loss: 0.01901 Total loss: 0.82775 timestamp: 1655073201.6663704 iteration: 82080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08868 FastRCNN class loss: 0.03274 FastRCNN total loss: 0.12142 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.09053 RPN box loss: 0.01509 RPN score loss: 0.00114 RPN total loss: 0.01623 Total loss: 0.79066 timestamp: 1655073204.892128 iteration: 82085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09936 FastRCNN class loss: 0.07381 FastRCNN total loss: 0.17317 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.17363 RPN box loss: 0.00392 RPN score loss: 0.00275 RPN total loss: 0.00667 Total loss: 0.91595 timestamp: 1655073208.1237864 iteration: 82090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10517 FastRCNN class loss: 0.08312 FastRCNN total loss: 0.18829 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.13353 RPN box loss: 0.02517 RPN score loss: 0.01178 RPN total loss: 0.03695 Total loss: 0.92126 timestamp: 1655073211.4259489 iteration: 82095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07744 FastRCNN class loss: 0.06455 FastRCNN total loss: 0.142 L1 loss: 0.0000e+00 L2 loss: 0.56248 Learning rate: 4.0000e-05 Mask loss: 0.17316 RPN box loss: 0.00847 RPN score loss: 0.00313 RPN total loss: 0.01159 Total loss: 0.88923 timestamp: 1655073214.6196778 iteration: 82100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09998 FastRCNN class loss: 0.08179 FastRCNN total loss: 0.18177 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12946 RPN box loss: 0.02771 RPN score loss: 0.0077 RPN total loss: 0.03541 Total loss: 0.90911 timestamp: 1655073217.8900857 iteration: 82105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08809 FastRCNN class loss: 0.05799 FastRCNN total loss: 0.14608 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.16994 RPN box loss: 0.01493 RPN score loss: 0.00781 RPN total loss: 0.02273 Total loss: 0.90123 timestamp: 1655073221.2160487 iteration: 82110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12685 FastRCNN class loss: 0.07195 FastRCNN total loss: 0.19881 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.10799 RPN box loss: 0.02328 RPN score loss: 0.00757 RPN total loss: 0.03085 Total loss: 0.90011 timestamp: 1655073224.4975116 iteration: 82115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15658 FastRCNN class loss: 0.10354 FastRCNN total loss: 0.26012 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14539 RPN box loss: 0.01531 RPN score loss: 0.00678 RPN total loss: 0.0221 Total loss: 0.99008 timestamp: 1655073227.798338 iteration: 82120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11531 FastRCNN class loss: 0.07131 FastRCNN total loss: 0.18662 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1423 RPN box loss: 0.00956 RPN score loss: 0.00677 RPN total loss: 0.01632 Total loss: 0.90772 timestamp: 1655073231.0923796 iteration: 82125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05074 FastRCNN class loss: 0.06798 FastRCNN total loss: 0.11872 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12472 RPN box loss: 0.0173 RPN score loss: 0.00545 RPN total loss: 0.02275 Total loss: 0.82867 timestamp: 1655073234.4268465 iteration: 82130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06268 FastRCNN class loss: 0.04419 FastRCNN total loss: 0.10686 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.08474 RPN box loss: 0.00706 RPN score loss: 0.00134 RPN total loss: 0.0084 Total loss: 0.76247 timestamp: 1655073237.7084188 iteration: 82135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07197 FastRCNN class loss: 0.04961 FastRCNN total loss: 0.12157 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1148 RPN box loss: 0.00902 RPN score loss: 0.00204 RPN total loss: 0.01106 Total loss: 0.8099 timestamp: 1655073240.9691648 iteration: 82140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06995 FastRCNN class loss: 0.08817 FastRCNN total loss: 0.15811 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12657 RPN box loss: 0.0201 RPN score loss: 0.00373 RPN total loss: 0.02384 Total loss: 0.871 timestamp: 1655073244.3111298 iteration: 82145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14888 FastRCNN class loss: 0.11033 FastRCNN total loss: 0.25921 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.20366 RPN box loss: 0.02749 RPN score loss: 0.0101 RPN total loss: 0.03759 Total loss: 1.06293 timestamp: 1655073247.540562 iteration: 82150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12983 FastRCNN class loss: 0.10744 FastRCNN total loss: 0.23727 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12382 RPN box loss: 0.02042 RPN score loss: 0.00858 RPN total loss: 0.029 Total loss: 0.95257 timestamp: 1655073250.7682424 iteration: 82155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09539 FastRCNN class loss: 0.07491 FastRCNN total loss: 0.1703 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.16953 RPN box loss: 0.02263 RPN score loss: 0.00502 RPN total loss: 0.02764 Total loss: 0.92995 timestamp: 1655073254.019815 iteration: 82160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.063 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.1416 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.09735 RPN box loss: 0.01809 RPN score loss: 0.00809 RPN total loss: 0.02618 Total loss: 0.8276 timestamp: 1655073257.368616 iteration: 82165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07079 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.12672 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14582 RPN box loss: 0.00363 RPN score loss: 0.00631 RPN total loss: 0.00995 Total loss: 0.84496 timestamp: 1655073260.6059918 iteration: 82170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1069 FastRCNN class loss: 0.06826 FastRCNN total loss: 0.17516 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12359 RPN box loss: 0.02353 RPN score loss: 0.00964 RPN total loss: 0.03317 Total loss: 0.89439 timestamp: 1655073263.8892956 iteration: 82175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0472 FastRCNN class loss: 0.04973 FastRCNN total loss: 0.09693 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1343 RPN box loss: 0.01077 RPN score loss: 0.00953 RPN total loss: 0.0203 Total loss: 0.81401 timestamp: 1655073267.1507063 iteration: 82180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15086 FastRCNN class loss: 0.14756 FastRCNN total loss: 0.29842 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12241 RPN box loss: 0.01246 RPN score loss: 0.00575 RPN total loss: 0.01821 Total loss: 1.00152 timestamp: 1655073270.4536238 iteration: 82185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06862 FastRCNN class loss: 0.04266 FastRCNN total loss: 0.11129 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12315 RPN box loss: 0.00644 RPN score loss: 0.00456 RPN total loss: 0.011 Total loss: 0.80791 timestamp: 1655073273.6880333 iteration: 82190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11581 FastRCNN class loss: 0.06277 FastRCNN total loss: 0.17859 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14653 RPN box loss: 0.00981 RPN score loss: 0.00844 RPN total loss: 0.01825 Total loss: 0.90584 timestamp: 1655073276.9650497 iteration: 82195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09576 FastRCNN class loss: 0.05907 FastRCNN total loss: 0.15482 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.2308 RPN box loss: 0.00598 RPN score loss: 0.00318 RPN total loss: 0.00916 Total loss: 0.95726 timestamp: 1655073280.2313745 iteration: 82200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.06221 FastRCNN total loss: 0.11885 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.0982 RPN box loss: 0.00448 RPN score loss: 0.00251 RPN total loss: 0.007 Total loss: 0.78652 timestamp: 1655073283.5406692 iteration: 82205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0402 FastRCNN class loss: 0.03392 FastRCNN total loss: 0.07412 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12796 RPN box loss: 0.00973 RPN score loss: 0.00081 RPN total loss: 0.01054 Total loss: 0.77509 timestamp: 1655073286.8232937 iteration: 82210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.09705 FastRCNN total loss: 0.21022 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.22208 RPN box loss: 0.03327 RPN score loss: 0.01698 RPN total loss: 0.05025 Total loss: 1.04501 timestamp: 1655073290.0592797 iteration: 82215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11898 FastRCNN class loss: 0.09667 FastRCNN total loss: 0.21565 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.19826 RPN box loss: 0.00901 RPN score loss: 0.00586 RPN total loss: 0.01488 Total loss: 0.99126 timestamp: 1655073293.3495193 iteration: 82220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10495 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.17486 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.10693 RPN box loss: 0.01815 RPN score loss: 0.00594 RPN total loss: 0.02409 Total loss: 0.86835 timestamp: 1655073296.644144 iteration: 82225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10769 FastRCNN class loss: 0.06786 FastRCNN total loss: 0.17555 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12759 RPN box loss: 0.01234 RPN score loss: 0.00948 RPN total loss: 0.02182 Total loss: 0.88744 timestamp: 1655073299.9467428 iteration: 82230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13394 FastRCNN class loss: 0.06523 FastRCNN total loss: 0.19917 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14444 RPN box loss: 0.0056 RPN score loss: 0.0025 RPN total loss: 0.0081 Total loss: 0.91418 timestamp: 1655073303.2669222 iteration: 82235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08845 FastRCNN class loss: 0.08005 FastRCNN total loss: 0.16851 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11834 RPN box loss: 0.01423 RPN score loss: 0.00627 RPN total loss: 0.0205 Total loss: 0.86982 timestamp: 1655073306.4478884 iteration: 82240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0956 FastRCNN class loss: 0.10356 FastRCNN total loss: 0.19916 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1818 RPN box loss: 0.01219 RPN score loss: 0.00759 RPN total loss: 0.01978 Total loss: 0.96321 timestamp: 1655073309.7647865 iteration: 82245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06059 FastRCNN class loss: 0.0438 FastRCNN total loss: 0.1044 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.13836 RPN box loss: 0.00727 RPN score loss: 0.00292 RPN total loss: 0.01019 Total loss: 0.81542 timestamp: 1655073313.0000334 iteration: 82250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10032 FastRCNN class loss: 0.08429 FastRCNN total loss: 0.18461 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11887 RPN box loss: 0.03128 RPN score loss: 0.00821 RPN total loss: 0.03949 Total loss: 0.90545 timestamp: 1655073316.2047882 iteration: 82255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04428 FastRCNN class loss: 0.03778 FastRCNN total loss: 0.08206 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1117 RPN box loss: 0.00462 RPN score loss: 0.00488 RPN total loss: 0.0095 Total loss: 0.76573 timestamp: 1655073319.5341163 iteration: 82260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11251 FastRCNN class loss: 0.096 FastRCNN total loss: 0.20852 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.20594 RPN box loss: 0.01697 RPN score loss: 0.00598 RPN total loss: 0.02295 Total loss: 0.99988 timestamp: 1655073322.7789984 iteration: 82265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09916 FastRCNN class loss: 0.07484 FastRCNN total loss: 0.174 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11786 RPN box loss: 0.0349 RPN score loss: 0.00868 RPN total loss: 0.04358 Total loss: 0.89791 timestamp: 1655073326.0787437 iteration: 82270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07464 FastRCNN class loss: 0.04774 FastRCNN total loss: 0.12238 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11571 RPN box loss: 0.01143 RPN score loss: 0.00474 RPN total loss: 0.01617 Total loss: 0.81674 timestamp: 1655073329.3699179 iteration: 82275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06964 FastRCNN class loss: 0.05686 FastRCNN total loss: 0.1265 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.10993 RPN box loss: 0.02428 RPN score loss: 0.01041 RPN total loss: 0.0347 Total loss: 0.83359 timestamp: 1655073332.6363966 iteration: 82280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07545 FastRCNN class loss: 0.06483 FastRCNN total loss: 0.14028 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11193 RPN box loss: 0.01098 RPN score loss: 0.00442 RPN total loss: 0.0154 Total loss: 0.83008 timestamp: 1655073335.8602037 iteration: 82285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12971 FastRCNN class loss: 0.10418 FastRCNN total loss: 0.23389 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14505 RPN box loss: 0.01181 RPN score loss: 0.00777 RPN total loss: 0.01959 Total loss: 0.961 timestamp: 1655073339.201463 iteration: 82290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11509 FastRCNN class loss: 0.05762 FastRCNN total loss: 0.17271 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11933 RPN box loss: 0.00479 RPN score loss: 0.00373 RPN total loss: 0.00852 Total loss: 0.86304 timestamp: 1655073342.4599066 iteration: 82295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15699 FastRCNN class loss: 0.06295 FastRCNN total loss: 0.21994 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.19152 RPN box loss: 0.00791 RPN score loss: 0.00791 RPN total loss: 0.01582 Total loss: 0.98975 timestamp: 1655073345.76889 iteration: 82300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10131 FastRCNN class loss: 0.0719 FastRCNN total loss: 0.17321 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11538 RPN box loss: 0.0071 RPN score loss: 0.00334 RPN total loss: 0.01044 Total loss: 0.8615 timestamp: 1655073349.0889273 iteration: 82305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06841 FastRCNN class loss: 0.05852 FastRCNN total loss: 0.12694 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.15434 RPN box loss: 0.0102 RPN score loss: 0.00199 RPN total loss: 0.01219 Total loss: 0.85594 timestamp: 1655073352.2821128 iteration: 82310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04055 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.09866 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.09656 RPN box loss: 0.00931 RPN score loss: 0.00237 RPN total loss: 0.01168 Total loss: 0.76937 timestamp: 1655073355.5749025 iteration: 82315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0676 FastRCNN class loss: 0.07363 FastRCNN total loss: 0.14123 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.10305 RPN box loss: 0.01365 RPN score loss: 0.005 RPN total loss: 0.01865 Total loss: 0.8254 timestamp: 1655073358.8537223 iteration: 82320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09464 FastRCNN class loss: 0.0716 FastRCNN total loss: 0.16625 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.15772 RPN box loss: 0.01794 RPN score loss: 0.01195 RPN total loss: 0.0299 Total loss: 0.91633 timestamp: 1655073362.065376 iteration: 82325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11815 FastRCNN class loss: 0.06244 FastRCNN total loss: 0.18059 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12332 RPN box loss: 0.00988 RPN score loss: 0.00183 RPN total loss: 0.01171 Total loss: 0.87809 timestamp: 1655073365.323026 iteration: 82330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0987 FastRCNN class loss: 0.06977 FastRCNN total loss: 0.16847 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.0085 RPN score loss: 0.00389 RPN total loss: 0.01239 Total loss: 0.89974 timestamp: 1655073368.6796684 iteration: 82335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07562 FastRCNN class loss: 0.04859 FastRCNN total loss: 0.12421 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11401 RPN box loss: 0.01629 RPN score loss: 0.00715 RPN total loss: 0.02344 Total loss: 0.82413 timestamp: 1655073372.0202703 iteration: 82340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05364 FastRCNN class loss: 0.06796 FastRCNN total loss: 0.12159 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.09824 RPN box loss: 0.00905 RPN score loss: 0.00593 RPN total loss: 0.01498 Total loss: 0.79728 timestamp: 1655073375.3047206 iteration: 82345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0736 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.12789 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.15181 RPN box loss: 0.00414 RPN score loss: 0.00345 RPN total loss: 0.00759 Total loss: 0.84976 timestamp: 1655073378.6887968 iteration: 82350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06668 FastRCNN class loss: 0.0647 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12325 RPN box loss: 0.00482 RPN score loss: 0.00408 RPN total loss: 0.00891 Total loss: 0.82601 timestamp: 1655073381.9713538 iteration: 82355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13557 FastRCNN class loss: 0.10186 FastRCNN total loss: 0.23743 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.14525 RPN box loss: 0.02441 RPN score loss: 0.00472 RPN total loss: 0.02913 Total loss: 0.97428 timestamp: 1655073385.209266 iteration: 82360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05737 FastRCNN class loss: 0.05012 FastRCNN total loss: 0.10749 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.22338 RPN box loss: 0.00445 RPN score loss: 0.00125 RPN total loss: 0.0057 Total loss: 0.89904 timestamp: 1655073388.5327053 iteration: 82365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05092 FastRCNN class loss: 0.04914 FastRCNN total loss: 0.10006 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.09876 RPN box loss: 0.01423 RPN score loss: 0.00316 RPN total loss: 0.01739 Total loss: 0.77868 timestamp: 1655073391.7612684 iteration: 82370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06095 FastRCNN class loss: 0.05691 FastRCNN total loss: 0.11787 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12079 RPN box loss: 0.00796 RPN score loss: 0.00558 RPN total loss: 0.01354 Total loss: 0.81466 timestamp: 1655073395.0583518 iteration: 82375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08147 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.15343 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.15232 RPN box loss: 0.0262 RPN score loss: 0.00337 RPN total loss: 0.02956 Total loss: 0.89778 timestamp: 1655073398.306907 iteration: 82380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.07132 FastRCNN total loss: 0.14929 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.10819 RPN box loss: 0.00804 RPN score loss: 0.00102 RPN total loss: 0.00906 Total loss: 0.82901 timestamp: 1655073401.5686066 iteration: 82385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08607 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.16512 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11129 RPN box loss: 0.0271 RPN score loss: 0.00906 RPN total loss: 0.03616 Total loss: 0.87504 timestamp: 1655073404.869296 iteration: 82390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06694 FastRCNN class loss: 0.04781 FastRCNN total loss: 0.11475 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.13347 RPN box loss: 0.01048 RPN score loss: 0.00203 RPN total loss: 0.01251 Total loss: 0.82319 timestamp: 1655073408.1157358 iteration: 82395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07837 FastRCNN class loss: 0.03961 FastRCNN total loss: 0.11798 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.115 RPN box loss: 0.02102 RPN score loss: 0.01051 RPN total loss: 0.03153 Total loss: 0.82698 timestamp: 1655073411.3845248 iteration: 82400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08073 FastRCNN class loss: 0.06427 FastRCNN total loss: 0.145 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.11554 RPN box loss: 0.02665 RPN score loss: 0.00289 RPN total loss: 0.02954 Total loss: 0.85255 timestamp: 1655073414.6337445 iteration: 82405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10875 FastRCNN class loss: 0.05954 FastRCNN total loss: 0.16829 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.1784 RPN box loss: 0.00872 RPN score loss: 0.00475 RPN total loss: 0.01347 Total loss: 0.92262 timestamp: 1655073417.9465685 iteration: 82410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11378 FastRCNN class loss: 0.08339 FastRCNN total loss: 0.19717 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.19694 RPN box loss: 0.01092 RPN score loss: 0.00424 RPN total loss: 0.01516 Total loss: 0.97174 timestamp: 1655073421.2202613 iteration: 82415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12286 FastRCNN class loss: 0.0657 FastRCNN total loss: 0.18856 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.12144 RPN box loss: 0.02334 RPN score loss: 0.00262 RPN total loss: 0.02595 Total loss: 0.89842 timestamp: 1655073424.4970052 iteration: 82420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.05818 FastRCNN total loss: 0.14221 L1 loss: 0.0000e+00 L2 loss: 0.56247 Learning rate: 4.0000e-05 Mask loss: 0.13427 RPN box loss: 0.01657 RPN score loss: 0.01222 RPN total loss: 0.02879 Total loss: 0.86773 timestamp: 1655073427.779863 iteration: 82425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07023 FastRCNN class loss: 0.06571 FastRCNN total loss: 0.13595 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.16397 RPN box loss: 0.03052 RPN score loss: 0.0076 RPN total loss: 0.03812 Total loss: 0.9005 timestamp: 1655073430.9976919 iteration: 82430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0724 FastRCNN class loss: 0.07931 FastRCNN total loss: 0.15172 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13388 RPN box loss: 0.0119 RPN score loss: 0.00463 RPN total loss: 0.01653 Total loss: 0.86459 timestamp: 1655073434.297126 iteration: 82435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10829 FastRCNN class loss: 0.04339 FastRCNN total loss: 0.15168 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.10182 RPN box loss: 0.01066 RPN score loss: 0.00302 RPN total loss: 0.01368 Total loss: 0.82964 timestamp: 1655073437.5908115 iteration: 82440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09666 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.16525 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.16456 RPN box loss: 0.03505 RPN score loss: 0.00879 RPN total loss: 0.04384 Total loss: 0.93612 timestamp: 1655073440.8769906 iteration: 82445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09241 FastRCNN class loss: 0.07602 FastRCNN total loss: 0.16843 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.17291 RPN box loss: 0.02244 RPN score loss: 0.00611 RPN total loss: 0.02855 Total loss: 0.93235 timestamp: 1655073444.194358 iteration: 82450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0732 FastRCNN class loss: 0.08392 FastRCNN total loss: 0.15712 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15647 RPN box loss: 0.01142 RPN score loss: 0.00951 RPN total loss: 0.02093 Total loss: 0.89698 timestamp: 1655073447.5328836 iteration: 82455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10459 FastRCNN class loss: 0.05486 FastRCNN total loss: 0.15945 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.18337 RPN box loss: 0.01874 RPN score loss: 0.00194 RPN total loss: 0.02068 Total loss: 0.92596 timestamp: 1655073450.783156 iteration: 82460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.186 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.18777 RPN box loss: 0.01856 RPN score loss: 0.00495 RPN total loss: 0.02352 Total loss: 0.95976 timestamp: 1655073453.9990346 iteration: 82465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06932 FastRCNN class loss: 0.04897 FastRCNN total loss: 0.11829 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.11816 RPN box loss: 0.00537 RPN score loss: 0.00436 RPN total loss: 0.00974 Total loss: 0.80865 timestamp: 1655073457.2727015 iteration: 82470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10604 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.17292 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15043 RPN box loss: 0.01443 RPN score loss: 0.00305 RPN total loss: 0.01748 Total loss: 0.9033 timestamp: 1655073460.5231628 iteration: 82475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10915 FastRCNN class loss: 0.06605 FastRCNN total loss: 0.17521 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.16281 RPN box loss: 0.00634 RPN score loss: 0.00838 RPN total loss: 0.01472 Total loss: 0.9152 timestamp: 1655073463.7631528 iteration: 82480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08335 FastRCNN class loss: 0.07537 FastRCNN total loss: 0.15872 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14051 RPN box loss: 0.00955 RPN score loss: 0.01134 RPN total loss: 0.02089 Total loss: 0.88259 timestamp: 1655073467.0638347 iteration: 82485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08503 FastRCNN class loss: 0.06435 FastRCNN total loss: 0.14938 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.10784 RPN box loss: 0.01463 RPN score loss: 0.00186 RPN total loss: 0.01648 Total loss: 0.83617 timestamp: 1655073470.3737628 iteration: 82490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.06165 FastRCNN total loss: 0.15496 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.08579 RPN box loss: 0.00872 RPN score loss: 0.00395 RPN total loss: 0.01267 Total loss: 0.81589 timestamp: 1655073473.6340756 iteration: 82495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07778 FastRCNN class loss: 0.05169 FastRCNN total loss: 0.12947 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.10012 RPN box loss: 0.00866 RPN score loss: 0.00241 RPN total loss: 0.01107 Total loss: 0.80312 timestamp: 1655073476.9576886 iteration: 82500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09474 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.17391 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.08525 RPN box loss: 0.02093 RPN score loss: 0.00441 RPN total loss: 0.02533 Total loss: 0.84696 timestamp: 1655073480.2701044 iteration: 82505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08398 FastRCNN class loss: 0.07327 FastRCNN total loss: 0.15725 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13943 RPN box loss: 0.01515 RPN score loss: 0.0047 RPN total loss: 0.01985 Total loss: 0.87899 timestamp: 1655073483.5270987 iteration: 82510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06455 FastRCNN class loss: 0.06776 FastRCNN total loss: 0.13231 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13135 RPN box loss: 0.00903 RPN score loss: 0.00532 RPN total loss: 0.01435 Total loss: 0.84048 timestamp: 1655073486.823245 iteration: 82515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14082 FastRCNN class loss: 0.10818 FastRCNN total loss: 0.24901 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.18628 RPN box loss: 0.01963 RPN score loss: 0.00889 RPN total loss: 0.02851 Total loss: 1.02626 timestamp: 1655073490.1534286 iteration: 82520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09394 FastRCNN class loss: 0.07798 FastRCNN total loss: 0.17192 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.1863 RPN box loss: 0.01496 RPN score loss: 0.01382 RPN total loss: 0.02878 Total loss: 0.94946 timestamp: 1655073493.3999462 iteration: 82525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05803 FastRCNN class loss: 0.05829 FastRCNN total loss: 0.11632 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.128 RPN box loss: 0.02077 RPN score loss: 0.00187 RPN total loss: 0.02263 Total loss: 0.82941 timestamp: 1655073496.7414846 iteration: 82530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07465 FastRCNN class loss: 0.05477 FastRCNN total loss: 0.12942 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.1195 RPN box loss: 0.01071 RPN score loss: 0.00331 RPN total loss: 0.01402 Total loss: 0.82541 timestamp: 1655073500.0559168 iteration: 82535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.07617 FastRCNN total loss: 0.20456 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15782 RPN box loss: 0.00801 RPN score loss: 0.00315 RPN total loss: 0.01116 Total loss: 0.936 timestamp: 1655073503.272537 iteration: 82540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10333 FastRCNN class loss: 0.07828 FastRCNN total loss: 0.18162 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.18698 RPN box loss: 0.01783 RPN score loss: 0.00405 RPN total loss: 0.02187 Total loss: 0.95293 timestamp: 1655073506.585188 iteration: 82545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0668 FastRCNN class loss: 0.04415 FastRCNN total loss: 0.11095 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.16036 RPN box loss: 0.00747 RPN score loss: 0.00238 RPN total loss: 0.00985 Total loss: 0.84361 timestamp: 1655073509.8518674 iteration: 82550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0757 FastRCNN class loss: 0.05801 FastRCNN total loss: 0.13372 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14513 RPN box loss: 0.00867 RPN score loss: 0.00291 RPN total loss: 0.01158 Total loss: 0.85288 timestamp: 1655073513.1110528 iteration: 82555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07941 FastRCNN class loss: 0.06277 FastRCNN total loss: 0.14219 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.18589 RPN box loss: 0.01763 RPN score loss: 0.00677 RPN total loss: 0.0244 Total loss: 0.91494 timestamp: 1655073516.4129505 iteration: 82560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05997 FastRCNN class loss: 0.08591 FastRCNN total loss: 0.14588 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.155 RPN box loss: 0.02519 RPN score loss: 0.00705 RPN total loss: 0.03225 Total loss: 0.89559 timestamp: 1655073519.701415 iteration: 82565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10717 FastRCNN class loss: 0.07557 FastRCNN total loss: 0.18274 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14529 RPN box loss: 0.01435 RPN score loss: 0.00366 RPN total loss: 0.018 Total loss: 0.9085 timestamp: 1655073522.904674 iteration: 82570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08555 FastRCNN class loss: 0.04458 FastRCNN total loss: 0.13013 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.09641 RPN box loss: 0.00792 RPN score loss: 0.00107 RPN total loss: 0.00899 Total loss: 0.79799 timestamp: 1655073526.1422327 iteration: 82575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06853 FastRCNN class loss: 0.07004 FastRCNN total loss: 0.13857 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13448 RPN box loss: 0.00741 RPN score loss: 0.00419 RPN total loss: 0.0116 Total loss: 0.84711 timestamp: 1655073529.5183659 iteration: 82580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09888 FastRCNN class loss: 0.09883 FastRCNN total loss: 0.1977 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.17642 RPN box loss: 0.02289 RPN score loss: 0.01175 RPN total loss: 0.03464 Total loss: 0.97122 timestamp: 1655073532.7495039 iteration: 82585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09125 FastRCNN class loss: 0.04789 FastRCNN total loss: 0.13914 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.17171 RPN box loss: 0.01266 RPN score loss: 0.00242 RPN total loss: 0.01507 Total loss: 0.88839 timestamp: 1655073535.9600923 iteration: 82590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13526 FastRCNN class loss: 0.04844 FastRCNN total loss: 0.1837 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.09697 RPN box loss: 0.01305 RPN score loss: 0.00307 RPN total loss: 0.01613 Total loss: 0.85925 timestamp: 1655073539.2589867 iteration: 82595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17345 FastRCNN class loss: 0.12188 FastRCNN total loss: 0.29534 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14409 RPN box loss: 0.01402 RPN score loss: 0.00862 RPN total loss: 0.02263 Total loss: 1.02452 timestamp: 1655073542.5105317 iteration: 82600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0802 FastRCNN class loss: 0.05248 FastRCNN total loss: 0.13268 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.17489 RPN box loss: 0.01334 RPN score loss: 0.00241 RPN total loss: 0.01575 Total loss: 0.88579 timestamp: 1655073545.7829716 iteration: 82605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07208 FastRCNN class loss: 0.06017 FastRCNN total loss: 0.13225 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15821 RPN box loss: 0.00485 RPN score loss: 0.00285 RPN total loss: 0.0077 Total loss: 0.86062 timestamp: 1655073548.988046 iteration: 82610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0776 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.14408 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.08813 RPN box loss: 0.00755 RPN score loss: 0.00261 RPN total loss: 0.01016 Total loss: 0.80482 timestamp: 1655073552.2180605 iteration: 82615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12429 FastRCNN class loss: 0.07976 FastRCNN total loss: 0.20406 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.179 RPN box loss: 0.01028 RPN score loss: 0.00821 RPN total loss: 0.01848 Total loss: 0.964 timestamp: 1655073555.406545 iteration: 82620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10752 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.17017 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.24503 RPN box loss: 0.00466 RPN score loss: 0.00312 RPN total loss: 0.00777 Total loss: 0.98544 timestamp: 1655073558.6288714 iteration: 82625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11392 FastRCNN class loss: 0.06659 FastRCNN total loss: 0.18052 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12124 RPN box loss: 0.00734 RPN score loss: 0.00476 RPN total loss: 0.0121 Total loss: 0.87631 timestamp: 1655073561.8854513 iteration: 82630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0465 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.11126 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12011 RPN box loss: 0.01646 RPN score loss: 0.00483 RPN total loss: 0.02129 Total loss: 0.81512 timestamp: 1655073565.1933987 iteration: 82635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.04602 FastRCNN total loss: 0.12715 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.08737 RPN box loss: 0.00419 RPN score loss: 0.00274 RPN total loss: 0.00693 Total loss: 0.78391 timestamp: 1655073568.4801104 iteration: 82640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11406 FastRCNN class loss: 0.06351 FastRCNN total loss: 0.17757 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12867 RPN box loss: 0.01661 RPN score loss: 0.00383 RPN total loss: 0.02044 Total loss: 0.88914 timestamp: 1655073571.763787 iteration: 82645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06535 FastRCNN class loss: 0.04186 FastRCNN total loss: 0.10722 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.08697 RPN box loss: 0.00276 RPN score loss: 0.00569 RPN total loss: 0.00846 Total loss: 0.7651 timestamp: 1655073575.1085432 iteration: 82650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06898 FastRCNN class loss: 0.05624 FastRCNN total loss: 0.12522 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.11599 RPN box loss: 0.0041 RPN score loss: 0.00183 RPN total loss: 0.00594 Total loss: 0.8096 timestamp: 1655073578.4021754 iteration: 82655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05614 FastRCNN class loss: 0.05856 FastRCNN total loss: 0.1147 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14451 RPN box loss: 0.00749 RPN score loss: 0.00474 RPN total loss: 0.01224 Total loss: 0.83391 timestamp: 1655073581.67877 iteration: 82660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12707 FastRCNN class loss: 0.06691 FastRCNN total loss: 0.19398 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12845 RPN box loss: 0.0127 RPN score loss: 0.00146 RPN total loss: 0.01416 Total loss: 0.89904 timestamp: 1655073584.9300337 iteration: 82665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13418 FastRCNN class loss: 0.09769 FastRCNN total loss: 0.23186 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14221 RPN box loss: 0.02708 RPN score loss: 0.00945 RPN total loss: 0.03654 Total loss: 0.97307 timestamp: 1655073588.2112682 iteration: 82670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11965 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.19063 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.1641 RPN box loss: 0.02476 RPN score loss: 0.00339 RPN total loss: 0.02815 Total loss: 0.94534 timestamp: 1655073591.5162842 iteration: 82675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07995 FastRCNN class loss: 0.05712 FastRCNN total loss: 0.13707 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13691 RPN box loss: 0.0062 RPN score loss: 0.0009 RPN total loss: 0.0071 Total loss: 0.84353 timestamp: 1655073594.820655 iteration: 82680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09748 FastRCNN class loss: 0.07055 FastRCNN total loss: 0.16803 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.16295 RPN box loss: 0.00928 RPN score loss: 0.00505 RPN total loss: 0.01433 Total loss: 0.90777 timestamp: 1655073598.158496 iteration: 82685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06812 FastRCNN class loss: 0.06754 FastRCNN total loss: 0.13566 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13666 RPN box loss: 0.01902 RPN score loss: 0.00802 RPN total loss: 0.02704 Total loss: 0.86183 timestamp: 1655073601.3892176 iteration: 82690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09084 FastRCNN class loss: 0.10459 FastRCNN total loss: 0.19543 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14495 RPN box loss: 0.01821 RPN score loss: 0.01154 RPN total loss: 0.02976 Total loss: 0.9326 timestamp: 1655073604.6961536 iteration: 82695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03215 FastRCNN class loss: 0.03665 FastRCNN total loss: 0.0688 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12973 RPN box loss: 0.01388 RPN score loss: 0.00317 RPN total loss: 0.01705 Total loss: 0.77804 timestamp: 1655073608.03849 iteration: 82700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06709 FastRCNN class loss: 0.05741 FastRCNN total loss: 0.1245 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12704 RPN box loss: 0.01897 RPN score loss: 0.00606 RPN total loss: 0.02502 Total loss: 0.83902 timestamp: 1655073611.307276 iteration: 82705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12895 FastRCNN class loss: 0.09195 FastRCNN total loss: 0.2209 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15594 RPN box loss: 0.01948 RPN score loss: 0.00956 RPN total loss: 0.02904 Total loss: 0.96833 timestamp: 1655073614.525857 iteration: 82710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04908 FastRCNN class loss: 0.04443 FastRCNN total loss: 0.0935 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.11082 RPN box loss: 0.01554 RPN score loss: 0.0019 RPN total loss: 0.01745 Total loss: 0.78423 timestamp: 1655073617.7715085 iteration: 82715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.08449 FastRCNN total loss: 0.18955 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.10263 RPN box loss: 0.00743 RPN score loss: 0.00563 RPN total loss: 0.01306 Total loss: 0.86769 timestamp: 1655073621.023535 iteration: 82720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06384 FastRCNN class loss: 0.07047 FastRCNN total loss: 0.13432 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13948 RPN box loss: 0.01663 RPN score loss: 0.0109 RPN total loss: 0.02754 Total loss: 0.86379 timestamp: 1655073624.2374227 iteration: 82725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0737 FastRCNN class loss: 0.07557 FastRCNN total loss: 0.14927 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.17422 RPN box loss: 0.00971 RPN score loss: 0.007 RPN total loss: 0.01671 Total loss: 0.90266 timestamp: 1655073627.4592476 iteration: 82730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12756 FastRCNN class loss: 0.06336 FastRCNN total loss: 0.19091 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.11494 RPN box loss: 0.01797 RPN score loss: 0.01012 RPN total loss: 0.02809 Total loss: 0.8964 timestamp: 1655073630.687446 iteration: 82735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07958 FastRCNN class loss: 0.05843 FastRCNN total loss: 0.13801 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.13567 RPN box loss: 0.00827 RPN score loss: 0.00519 RPN total loss: 0.01346 Total loss: 0.8496 timestamp: 1655073633.9286044 iteration: 82740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08674 FastRCNN class loss: 0.05416 FastRCNN total loss: 0.1409 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.15747 RPN box loss: 0.02411 RPN score loss: 0.00207 RPN total loss: 0.02618 Total loss: 0.887 timestamp: 1655073637.243525 iteration: 82745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10179 FastRCNN class loss: 0.06923 FastRCNN total loss: 0.17102 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.14983 RPN box loss: 0.05784 RPN score loss: 0.00582 RPN total loss: 0.06366 Total loss: 0.94697 timestamp: 1655073640.4651825 iteration: 82750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.18347 L1 loss: 0.0000e+00 L2 loss: 0.56246 Learning rate: 4.0000e-05 Mask loss: 0.12069 RPN box loss: 0.02958 RPN score loss: 0.0044 RPN total loss: 0.03397 Total loss: 0.90059 timestamp: 1655073643.7203102 iteration: 82755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16102 FastRCNN class loss: 0.06682 FastRCNN total loss: 0.22784 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.18631 RPN box loss: 0.02004 RPN score loss: 0.0064 RPN total loss: 0.02644 Total loss: 1.00304 timestamp: 1655073647.011474 iteration: 82760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09238 FastRCNN class loss: 0.0956 FastRCNN total loss: 0.18798 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.15079 RPN box loss: 0.01051 RPN score loss: 0.00562 RPN total loss: 0.01613 Total loss: 0.91736 timestamp: 1655073650.3362496 iteration: 82765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12911 FastRCNN class loss: 0.06713 FastRCNN total loss: 0.19624 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.16283 RPN box loss: 0.01612 RPN score loss: 0.007 RPN total loss: 0.02313 Total loss: 0.94465 timestamp: 1655073653.667958 iteration: 82770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05391 FastRCNN class loss: 0.05873 FastRCNN total loss: 0.11264 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.10582 RPN box loss: 0.02911 RPN score loss: 0.01027 RPN total loss: 0.03937 Total loss: 0.82028 timestamp: 1655073656.8905156 iteration: 82775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09014 FastRCNN class loss: 0.10194 FastRCNN total loss: 0.19208 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.16463 RPN box loss: 0.00976 RPN score loss: 0.00296 RPN total loss: 0.01273 Total loss: 0.93189 timestamp: 1655073660.1614842 iteration: 82780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11482 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.16526 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1085 RPN box loss: 0.02005 RPN score loss: 0.00154 RPN total loss: 0.02159 Total loss: 0.8578 timestamp: 1655073663.4450452 iteration: 82785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.05076 FastRCNN total loss: 0.14509 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1238 RPN box loss: 0.02199 RPN score loss: 0.00775 RPN total loss: 0.02974 Total loss: 0.86108 timestamp: 1655073666.6998577 iteration: 82790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04346 FastRCNN class loss: 0.04219 FastRCNN total loss: 0.08565 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1267 RPN box loss: 0.00714 RPN score loss: 0.00333 RPN total loss: 0.01047 Total loss: 0.78527 timestamp: 1655073669.9877074 iteration: 82795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.118 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13333 RPN box loss: 0.00806 RPN score loss: 0.00321 RPN total loss: 0.01127 Total loss: 0.82505 timestamp: 1655073673.2079055 iteration: 82800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09886 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.19862 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.18819 RPN box loss: 0.00962 RPN score loss: 0.00361 RPN total loss: 0.01322 Total loss: 0.9625 timestamp: 1655073676.4797528 iteration: 82805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07391 FastRCNN class loss: 0.06331 FastRCNN total loss: 0.13721 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.09988 RPN box loss: 0.00289 RPN score loss: 0.00179 RPN total loss: 0.00468 Total loss: 0.80423 timestamp: 1655073679.726582 iteration: 82810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08199 FastRCNN class loss: 0.07388 FastRCNN total loss: 0.15586 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.16115 RPN box loss: 0.03554 RPN score loss: 0.00452 RPN total loss: 0.04007 Total loss: 0.91953 timestamp: 1655073683.0588844 iteration: 82815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08354 FastRCNN class loss: 0.05344 FastRCNN total loss: 0.13698 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11965 RPN box loss: 0.00561 RPN score loss: 0.00257 RPN total loss: 0.00818 Total loss: 0.82726 timestamp: 1655073686.311787 iteration: 82820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11715 FastRCNN class loss: 0.06478 FastRCNN total loss: 0.18193 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1022 RPN box loss: 0.00901 RPN score loss: 0.00481 RPN total loss: 0.01382 Total loss: 0.8604 timestamp: 1655073689.6177146 iteration: 82825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09681 FastRCNN class loss: 0.05805 FastRCNN total loss: 0.15486 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14508 RPN box loss: 0.00904 RPN score loss: 0.00439 RPN total loss: 0.01343 Total loss: 0.87582 timestamp: 1655073692.878102 iteration: 82830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06768 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.13318 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.18702 RPN box loss: 0.01259 RPN score loss: 0.0066 RPN total loss: 0.01919 Total loss: 0.90184 timestamp: 1655073696.112099 iteration: 82835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07235 FastRCNN class loss: 0.07117 FastRCNN total loss: 0.14353 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.10901 RPN box loss: 0.02737 RPN score loss: 0.00228 RPN total loss: 0.02965 Total loss: 0.84464 timestamp: 1655073699.3442562 iteration: 82840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17655 FastRCNN class loss: 0.10598 FastRCNN total loss: 0.28252 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.19776 RPN box loss: 0.01304 RPN score loss: 0.01267 RPN total loss: 0.02571 Total loss: 1.06845 timestamp: 1655073702.6037428 iteration: 82845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07302 FastRCNN class loss: 0.06166 FastRCNN total loss: 0.13468 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.10195 RPN box loss: 0.01582 RPN score loss: 0.00528 RPN total loss: 0.02111 Total loss: 0.82019 timestamp: 1655073705.8342874 iteration: 82850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11848 FastRCNN class loss: 0.06997 FastRCNN total loss: 0.18845 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14834 RPN box loss: 0.0107 RPN score loss: 0.00279 RPN total loss: 0.01349 Total loss: 0.91273 timestamp: 1655073709.1000328 iteration: 82855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07175 FastRCNN class loss: 0.08947 FastRCNN total loss: 0.16122 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1617 RPN box loss: 0.0083 RPN score loss: 0.01268 RPN total loss: 0.02098 Total loss: 0.90636 timestamp: 1655073712.4491866 iteration: 82860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13057 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.19941 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.09151 RPN box loss: 0.01379 RPN score loss: 0.00251 RPN total loss: 0.0163 Total loss: 0.86967 timestamp: 1655073715.7305782 iteration: 82865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.05978 FastRCNN total loss: 0.12492 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12167 RPN box loss: 0.00758 RPN score loss: 0.00304 RPN total loss: 0.01061 Total loss: 0.81965 timestamp: 1655073718.9954824 iteration: 82870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07795 FastRCNN class loss: 0.05429 FastRCNN total loss: 0.13224 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1583 RPN box loss: 0.0188 RPN score loss: 0.00356 RPN total loss: 0.02236 Total loss: 0.87536 timestamp: 1655073722.2603092 iteration: 82875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08637 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.16819 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13174 RPN box loss: 0.02096 RPN score loss: 0.00378 RPN total loss: 0.02474 Total loss: 0.88712 timestamp: 1655073725.51937 iteration: 82880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09544 FastRCNN class loss: 0.05384 FastRCNN total loss: 0.14928 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11234 RPN box loss: 0.00703 RPN score loss: 0.00455 RPN total loss: 0.01158 Total loss: 0.83565 timestamp: 1655073728.7691686 iteration: 82885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09974 FastRCNN class loss: 0.04157 FastRCNN total loss: 0.14131 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.17373 RPN box loss: 0.01239 RPN score loss: 0.00783 RPN total loss: 0.02022 Total loss: 0.89772 timestamp: 1655073732.1129508 iteration: 82890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11552 FastRCNN class loss: 0.08053 FastRCNN total loss: 0.19606 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.17377 RPN box loss: 0.00835 RPN score loss: 0.00419 RPN total loss: 0.01254 Total loss: 0.94482 timestamp: 1655073735.3785214 iteration: 82895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09682 FastRCNN class loss: 0.07205 FastRCNN total loss: 0.16887 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14517 RPN box loss: 0.0462 RPN score loss: 0.01022 RPN total loss: 0.05641 Total loss: 0.93291 timestamp: 1655073738.6397042 iteration: 82900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09331 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.1752 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.16497 RPN box loss: 0.01481 RPN score loss: 0.00571 RPN total loss: 0.02052 Total loss: 0.92314 timestamp: 1655073741.8912985 iteration: 82905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10984 FastRCNN class loss: 0.06589 FastRCNN total loss: 0.17573 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14267 RPN box loss: 0.06565 RPN score loss: 0.00765 RPN total loss: 0.0733 Total loss: 0.95414 timestamp: 1655073745.2572718 iteration: 82910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11768 FastRCNN class loss: 0.08071 FastRCNN total loss: 0.19839 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.17551 RPN box loss: 0.0113 RPN score loss: 0.00584 RPN total loss: 0.01714 Total loss: 0.9535 timestamp: 1655073748.4726586 iteration: 82915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07923 FastRCNN class loss: 0.0311 FastRCNN total loss: 0.11033 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.0969 RPN box loss: 0.00664 RPN score loss: 0.00103 RPN total loss: 0.00767 Total loss: 0.77734 timestamp: 1655073751.758011 iteration: 82920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14639 FastRCNN class loss: 0.07831 FastRCNN total loss: 0.2247 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.17221 RPN box loss: 0.0397 RPN score loss: 0.01311 RPN total loss: 0.0528 Total loss: 1.01216 timestamp: 1655073755.061392 iteration: 82925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14745 FastRCNN class loss: 0.07268 FastRCNN total loss: 0.22012 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.20806 RPN box loss: 0.02127 RPN score loss: 0.0023 RPN total loss: 0.02358 Total loss: 1.01421 timestamp: 1655073758.256107 iteration: 82930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09709 FastRCNN class loss: 0.05183 FastRCNN total loss: 0.14892 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.1964 RPN box loss: 0.04288 RPN score loss: 0.00417 RPN total loss: 0.04705 Total loss: 0.95482 timestamp: 1655073761.5232346 iteration: 82935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08752 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.15927 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12366 RPN box loss: 0.01686 RPN score loss: 0.00369 RPN total loss: 0.02054 Total loss: 0.86592 timestamp: 1655073764.8520126 iteration: 82940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05681 FastRCNN class loss: 0.03236 FastRCNN total loss: 0.08917 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.29904 RPN box loss: 0.01426 RPN score loss: 0.00394 RPN total loss: 0.0182 Total loss: 0.96886 timestamp: 1655073768.149713 iteration: 82945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09082 FastRCNN class loss: 0.06196 FastRCNN total loss: 0.15277 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14989 RPN box loss: 0.02134 RPN score loss: 0.01539 RPN total loss: 0.03673 Total loss: 0.90184 timestamp: 1655073771.4605677 iteration: 82950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07562 FastRCNN class loss: 0.04706 FastRCNN total loss: 0.12268 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11014 RPN box loss: 0.01194 RPN score loss: 0.00426 RPN total loss: 0.01621 Total loss: 0.81148 timestamp: 1655073774.7705564 iteration: 82955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07405 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.13847 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14718 RPN box loss: 0.00535 RPN score loss: 0.00358 RPN total loss: 0.00893 Total loss: 0.85703 timestamp: 1655073778.0796375 iteration: 82960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04702 FastRCNN class loss: 0.0476 FastRCNN total loss: 0.09462 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11261 RPN box loss: 0.00876 RPN score loss: 0.0084 RPN total loss: 0.01716 Total loss: 0.78684 timestamp: 1655073781.3206217 iteration: 82965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10435 FastRCNN class loss: 0.06794 FastRCNN total loss: 0.17229 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11146 RPN box loss: 0.02028 RPN score loss: 0.00416 RPN total loss: 0.02444 Total loss: 0.87064 timestamp: 1655073784.565202 iteration: 82970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09952 FastRCNN class loss: 0.07785 FastRCNN total loss: 0.17737 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11803 RPN box loss: 0.01464 RPN score loss: 0.00714 RPN total loss: 0.02178 Total loss: 0.87963 timestamp: 1655073787.8153274 iteration: 82975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04784 FastRCNN class loss: 0.04494 FastRCNN total loss: 0.09278 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12409 RPN box loss: 0.00136 RPN score loss: 0.00081 RPN total loss: 0.00217 Total loss: 0.78149 timestamp: 1655073791.0574684 iteration: 82980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12659 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.19518 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.15559 RPN box loss: 0.00781 RPN score loss: 0.00519 RPN total loss: 0.013 Total loss: 0.92622 timestamp: 1655073794.3101823 iteration: 82985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05487 FastRCNN class loss: 0.05783 FastRCNN total loss: 0.1127 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.15117 RPN box loss: 0.00616 RPN score loss: 0.00283 RPN total loss: 0.00899 Total loss: 0.83531 timestamp: 1655073797.5542943 iteration: 82990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11562 FastRCNN class loss: 0.06319 FastRCNN total loss: 0.17881 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13342 RPN box loss: 0.00882 RPN score loss: 0.00347 RPN total loss: 0.01229 Total loss: 0.88697 timestamp: 1655073800.7973928 iteration: 82995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09413 FastRCNN class loss: 0.06576 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11339 RPN box loss: 0.06099 RPN score loss: 0.00465 RPN total loss: 0.06564 Total loss: 0.90137 timestamp: 1655073804.0571518 iteration: 83000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08472 FastRCNN class loss: 0.07893 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13218 RPN box loss: 0.01639 RPN score loss: 0.00741 RPN total loss: 0.0238 Total loss: 0.88208 timestamp: 1655073807.3040302 iteration: 83005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.085 FastRCNN class loss: 0.05986 FastRCNN total loss: 0.14485 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.15284 RPN box loss: 0.00944 RPN score loss: 0.00583 RPN total loss: 0.01527 Total loss: 0.87541 timestamp: 1655073810.591942 iteration: 83010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.1188 FastRCNN total loss: 0.21221 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.25 RPN box loss: 0.02225 RPN score loss: 0.00796 RPN total loss: 0.03021 Total loss: 1.05487 timestamp: 1655073813.8940413 iteration: 83015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10345 FastRCNN class loss: 0.08019 FastRCNN total loss: 0.18365 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12797 RPN box loss: 0.01097 RPN score loss: 0.00932 RPN total loss: 0.02029 Total loss: 0.89435 timestamp: 1655073817.1788394 iteration: 83020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09209 FastRCNN class loss: 0.03899 FastRCNN total loss: 0.13108 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11913 RPN box loss: 0.00462 RPN score loss: 0.00096 RPN total loss: 0.00558 Total loss: 0.81823 timestamp: 1655073820.4304044 iteration: 83025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11021 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.19338 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13533 RPN box loss: 0.01946 RPN score loss: 0.00224 RPN total loss: 0.0217 Total loss: 0.91286 timestamp: 1655073823.6534407 iteration: 83030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07999 FastRCNN class loss: 0.04939 FastRCNN total loss: 0.12938 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.13983 RPN box loss: 0.00832 RPN score loss: 0.01097 RPN total loss: 0.01929 Total loss: 0.85095 timestamp: 1655073826.9286225 iteration: 83035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0668 FastRCNN class loss: 0.03933 FastRCNN total loss: 0.10612 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11195 RPN box loss: 0.00809 RPN score loss: 0.00562 RPN total loss: 0.01371 Total loss: 0.79423 timestamp: 1655073830.2144947 iteration: 83040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14536 FastRCNN class loss: 0.06504 FastRCNN total loss: 0.2104 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14314 RPN box loss: 0.01123 RPN score loss: 0.00379 RPN total loss: 0.01502 Total loss: 0.93101 timestamp: 1655073833.5556412 iteration: 83045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16281 FastRCNN class loss: 0.07294 FastRCNN total loss: 0.23575 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14001 RPN box loss: 0.0077 RPN score loss: 0.0025 RPN total loss: 0.0102 Total loss: 0.94841 timestamp: 1655073836.82777 iteration: 83050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09526 FastRCNN class loss: 0.07063 FastRCNN total loss: 0.16588 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.15578 RPN box loss: 0.01245 RPN score loss: 0.00867 RPN total loss: 0.02111 Total loss: 0.90523 timestamp: 1655073840.0421407 iteration: 83055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06684 FastRCNN class loss: 0.06081 FastRCNN total loss: 0.12764 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12375 RPN box loss: 0.00862 RPN score loss: 0.00799 RPN total loss: 0.01661 Total loss: 0.83045 timestamp: 1655073843.367748 iteration: 83060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17358 FastRCNN class loss: 0.05571 FastRCNN total loss: 0.2293 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11055 RPN box loss: 0.00989 RPN score loss: 0.00631 RPN total loss: 0.0162 Total loss: 0.91849 timestamp: 1655073846.6795127 iteration: 83065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09653 FastRCNN class loss: 0.04768 FastRCNN total loss: 0.14421 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.12357 RPN box loss: 0.00611 RPN score loss: 0.00325 RPN total loss: 0.00936 Total loss: 0.83959 timestamp: 1655073849.9713883 iteration: 83070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13817 FastRCNN class loss: 0.08823 FastRCNN total loss: 0.2264 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.14739 RPN box loss: 0.00478 RPN score loss: 0.01073 RPN total loss: 0.01551 Total loss: 0.95175 timestamp: 1655073853.2519572 iteration: 83075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08107 FastRCNN class loss: 0.06871 FastRCNN total loss: 0.14978 L1 loss: 0.0000e+00 L2 loss: 0.56245 Learning rate: 4.0000e-05 Mask loss: 0.11989 RPN box loss: 0.01468 RPN score loss: 0.00555 RPN total loss: 0.02023 Total loss: 0.85236 timestamp: 1655073856.525259 iteration: 83080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10845 FastRCNN class loss: 0.04441 FastRCNN total loss: 0.15287 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14392 RPN box loss: 0.00598 RPN score loss: 0.00454 RPN total loss: 0.01053 Total loss: 0.86976 timestamp: 1655073859.8012958 iteration: 83085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13512 FastRCNN class loss: 0.06277 FastRCNN total loss: 0.19789 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15033 RPN box loss: 0.02182 RPN score loss: 0.00376 RPN total loss: 0.02557 Total loss: 0.93624 timestamp: 1655073863.0917845 iteration: 83090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07709 FastRCNN class loss: 0.051 FastRCNN total loss: 0.12809 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.12763 RPN box loss: 0.02226 RPN score loss: 0.00648 RPN total loss: 0.02874 Total loss: 0.8469 timestamp: 1655073866.4098334 iteration: 83095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10005 FastRCNN class loss: 0.09394 FastRCNN total loss: 0.19399 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.22091 RPN box loss: 0.00823 RPN score loss: 0.00417 RPN total loss: 0.0124 Total loss: 0.98975 timestamp: 1655073869.689453 iteration: 83100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04369 FastRCNN class loss: 0.06627 FastRCNN total loss: 0.10996 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1503 RPN box loss: 0.00851 RPN score loss: 0.00853 RPN total loss: 0.01704 Total loss: 0.83974 timestamp: 1655073872.985423 iteration: 83105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11591 FastRCNN class loss: 0.10253 FastRCNN total loss: 0.21844 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.16846 RPN box loss: 0.01505 RPN score loss: 0.00831 RPN total loss: 0.02336 Total loss: 0.97271 timestamp: 1655073876.314276 iteration: 83110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1408 FastRCNN class loss: 0.13024 FastRCNN total loss: 0.27105 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15007 RPN box loss: 0.01614 RPN score loss: 0.0041 RPN total loss: 0.02024 Total loss: 1.0038 timestamp: 1655073879.5465357 iteration: 83115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1194 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.19365 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13745 RPN box loss: 0.01039 RPN score loss: 0.00852 RPN total loss: 0.01891 Total loss: 0.91246 timestamp: 1655073882.8029501 iteration: 83120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10378 FastRCNN class loss: 0.0777 FastRCNN total loss: 0.18148 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.11806 RPN box loss: 0.01499 RPN score loss: 0.00714 RPN total loss: 0.02213 Total loss: 0.88412 timestamp: 1655073886.056867 iteration: 83125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06632 FastRCNN class loss: 0.06755 FastRCNN total loss: 0.13387 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.09777 RPN box loss: 0.00869 RPN score loss: 0.00262 RPN total loss: 0.01131 Total loss: 0.8054 timestamp: 1655073889.426399 iteration: 83130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04393 FastRCNN class loss: 0.02548 FastRCNN total loss: 0.06941 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.08789 RPN box loss: 0.01642 RPN score loss: 0.00199 RPN total loss: 0.01842 Total loss: 0.73816 timestamp: 1655073892.7180166 iteration: 83135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10611 FastRCNN class loss: 0.05724 FastRCNN total loss: 0.16335 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14899 RPN box loss: 0.00783 RPN score loss: 0.01014 RPN total loss: 0.01798 Total loss: 0.89276 timestamp: 1655073895.964534 iteration: 83140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10942 FastRCNN class loss: 0.0778 FastRCNN total loss: 0.18722 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17693 RPN box loss: 0.02789 RPN score loss: 0.01712 RPN total loss: 0.04501 Total loss: 0.9716 timestamp: 1655073899.244233 iteration: 83145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11629 FastRCNN class loss: 0.08772 FastRCNN total loss: 0.204 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17283 RPN box loss: 0.01748 RPN score loss: 0.01007 RPN total loss: 0.02755 Total loss: 0.96683 timestamp: 1655073902.5092516 iteration: 83150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10505 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.18002 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14349 RPN box loss: 0.00982 RPN score loss: 0.01062 RPN total loss: 0.02043 Total loss: 0.90638 timestamp: 1655073905.7934358 iteration: 83155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11838 FastRCNN class loss: 0.07794 FastRCNN total loss: 0.19633 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14259 RPN box loss: 0.01031 RPN score loss: 0.00387 RPN total loss: 0.01418 Total loss: 0.91554 timestamp: 1655073909.064661 iteration: 83160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08164 FastRCNN class loss: 0.09863 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1685 RPN box loss: 0.02213 RPN score loss: 0.01412 RPN total loss: 0.03625 Total loss: 0.94746 timestamp: 1655073912.334988 iteration: 83165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0952 FastRCNN class loss: 0.08957 FastRCNN total loss: 0.18476 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15665 RPN box loss: 0.00628 RPN score loss: 0.00933 RPN total loss: 0.0156 Total loss: 0.91946 timestamp: 1655073915.6251154 iteration: 83170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11454 FastRCNN class loss: 0.10207 FastRCNN total loss: 0.21661 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14473 RPN box loss: 0.0194 RPN score loss: 0.01425 RPN total loss: 0.03365 Total loss: 0.95743 timestamp: 1655073918.8857687 iteration: 83175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08997 FastRCNN class loss: 0.08962 FastRCNN total loss: 0.17959 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15153 RPN box loss: 0.01684 RPN score loss: 0.00795 RPN total loss: 0.0248 Total loss: 0.91836 timestamp: 1655073922.1803207 iteration: 83180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0879 FastRCNN class loss: 0.0948 FastRCNN total loss: 0.18269 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.19325 RPN box loss: 0.01615 RPN score loss: 0.00328 RPN total loss: 0.01942 Total loss: 0.9578 timestamp: 1655073925.5173519 iteration: 83185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13701 FastRCNN class loss: 0.11804 FastRCNN total loss: 0.25505 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.16461 RPN box loss: 0.02642 RPN score loss: 0.00776 RPN total loss: 0.03419 Total loss: 1.01629 timestamp: 1655073928.7580557 iteration: 83190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15671 FastRCNN class loss: 0.13039 FastRCNN total loss: 0.2871 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17068 RPN box loss: 0.03328 RPN score loss: 0.01175 RPN total loss: 0.04502 Total loss: 1.06525 timestamp: 1655073932.0323327 iteration: 83195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1222 FastRCNN class loss: 0.10889 FastRCNN total loss: 0.23109 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1396 RPN box loss: 0.00803 RPN score loss: 0.00102 RPN total loss: 0.00905 Total loss: 0.94218 timestamp: 1655073935.3520849 iteration: 83200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12749 FastRCNN class loss: 0.08267 FastRCNN total loss: 0.21016 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17956 RPN box loss: 0.02657 RPN score loss: 0.00585 RPN total loss: 0.03242 Total loss: 0.98458 timestamp: 1655073938.6366725 iteration: 83205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09797 FastRCNN class loss: 0.07497 FastRCNN total loss: 0.17294 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17397 RPN box loss: 0.00679 RPN score loss: 0.00427 RPN total loss: 0.01106 Total loss: 0.92041 timestamp: 1655073941.9851232 iteration: 83210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05972 FastRCNN class loss: 0.04772 FastRCNN total loss: 0.10744 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.10627 RPN box loss: 0.0026 RPN score loss: 0.00139 RPN total loss: 0.00399 Total loss: 0.78015 timestamp: 1655073945.2526672 iteration: 83215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13275 FastRCNN class loss: 0.11486 FastRCNN total loss: 0.24761 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15393 RPN box loss: 0.00955 RPN score loss: 0.00196 RPN total loss: 0.01151 Total loss: 0.97549 timestamp: 1655073948.5234942 iteration: 83220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15644 FastRCNN class loss: 0.10193 FastRCNN total loss: 0.25837 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.20177 RPN box loss: 0.01981 RPN score loss: 0.00506 RPN total loss: 0.02487 Total loss: 1.04745 timestamp: 1655073951.8201697 iteration: 83225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08377 FastRCNN class loss: 0.04665 FastRCNN total loss: 0.13042 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14253 RPN box loss: 0.0106 RPN score loss: 0.0063 RPN total loss: 0.0169 Total loss: 0.85229 timestamp: 1655073955.145896 iteration: 83230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10694 FastRCNN class loss: 0.07114 FastRCNN total loss: 0.17808 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.09007 RPN box loss: 0.00683 RPN score loss: 0.00167 RPN total loss: 0.00851 Total loss: 0.83909 timestamp: 1655073958.5002034 iteration: 83235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07017 FastRCNN class loss: 0.06484 FastRCNN total loss: 0.13501 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.16224 RPN box loss: 0.0234 RPN score loss: 0.00477 RPN total loss: 0.02817 Total loss: 0.88786 timestamp: 1655073961.761733 iteration: 83240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08411 FastRCNN class loss: 0.07032 FastRCNN total loss: 0.15443 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.20185 RPN box loss: 0.00954 RPN score loss: 0.01001 RPN total loss: 0.01955 Total loss: 0.93827 timestamp: 1655073965.0316834 iteration: 83245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0681 FastRCNN class loss: 0.05963 FastRCNN total loss: 0.12774 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.10443 RPN box loss: 0.00635 RPN score loss: 0.00978 RPN total loss: 0.01614 Total loss: 0.81074 timestamp: 1655073968.3393939 iteration: 83250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11727 FastRCNN class loss: 0.09041 FastRCNN total loss: 0.20768 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13466 RPN box loss: 0.01964 RPN score loss: 0.00432 RPN total loss: 0.02396 Total loss: 0.92873 timestamp: 1655073971.6182857 iteration: 83255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11288 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.17457 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15553 RPN box loss: 0.01216 RPN score loss: 0.0048 RPN total loss: 0.01697 Total loss: 0.90951 timestamp: 1655073974.890384 iteration: 83260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04939 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.10434 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.0934 RPN box loss: 0.03235 RPN score loss: 0.00422 RPN total loss: 0.03658 Total loss: 0.79675 timestamp: 1655073978.2233927 iteration: 83265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06484 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.11888 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.12404 RPN box loss: 0.00885 RPN score loss: 0.00288 RPN total loss: 0.01172 Total loss: 0.81709 timestamp: 1655073981.504085 iteration: 83270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.08153 FastRCNN total loss: 0.16392 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1596 RPN box loss: 0.0141 RPN score loss: 0.00842 RPN total loss: 0.02252 Total loss: 0.90848 timestamp: 1655073984.7479653 iteration: 83275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12726 FastRCNN class loss: 0.08038 FastRCNN total loss: 0.20764 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.19299 RPN box loss: 0.02628 RPN score loss: 0.01483 RPN total loss: 0.04111 Total loss: 1.00418 timestamp: 1655073988.0341523 iteration: 83280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06154 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.1289 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.09437 RPN box loss: 0.00509 RPN score loss: 0.00358 RPN total loss: 0.00867 Total loss: 0.79437 timestamp: 1655073991.2803717 iteration: 83285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08255 FastRCNN class loss: 0.06141 FastRCNN total loss: 0.14395 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14872 RPN box loss: 0.0189 RPN score loss: 0.00333 RPN total loss: 0.02223 Total loss: 0.87733 timestamp: 1655073994.5484126 iteration: 83290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07362 FastRCNN class loss: 0.06888 FastRCNN total loss: 0.1425 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14747 RPN box loss: 0.01354 RPN score loss: 0.01161 RPN total loss: 0.02515 Total loss: 0.87757 timestamp: 1655073997.8505359 iteration: 83295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09459 FastRCNN class loss: 0.09923 FastRCNN total loss: 0.19382 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1274 RPN box loss: 0.0083 RPN score loss: 0.00411 RPN total loss: 0.01241 Total loss: 0.89606 timestamp: 1655074001.1155548 iteration: 83300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0965 FastRCNN class loss: 0.08736 FastRCNN total loss: 0.18386 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.11005 RPN box loss: 0.01273 RPN score loss: 0.0059 RPN total loss: 0.01863 Total loss: 0.87499 timestamp: 1655074004.398973 iteration: 83305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12881 FastRCNN class loss: 0.10446 FastRCNN total loss: 0.23327 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.15616 RPN box loss: 0.01309 RPN score loss: 0.00215 RPN total loss: 0.01524 Total loss: 0.96711 timestamp: 1655074007.7067904 iteration: 83310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11051 FastRCNN class loss: 0.08627 FastRCNN total loss: 0.19678 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.21832 RPN box loss: 0.02616 RPN score loss: 0.00591 RPN total loss: 0.03207 Total loss: 1.00961 timestamp: 1655074010.9654438 iteration: 83315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.087 FastRCNN total loss: 0.18445 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.17112 RPN box loss: 0.01069 RPN score loss: 0.00354 RPN total loss: 0.01423 Total loss: 0.93224 timestamp: 1655074014.1815698 iteration: 83320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1586 FastRCNN class loss: 0.09342 FastRCNN total loss: 0.25202 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14324 RPN box loss: 0.00618 RPN score loss: 0.00325 RPN total loss: 0.00944 Total loss: 0.96714 timestamp: 1655074017.4971666 iteration: 83325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.17126 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.14911 RPN box loss: 0.00604 RPN score loss: 0.0019 RPN total loss: 0.00794 Total loss: 0.89075 timestamp: 1655074020.8305945 iteration: 83330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13869 FastRCNN class loss: 0.08399 FastRCNN total loss: 0.22268 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13073 RPN box loss: 0.01323 RPN score loss: 0.00507 RPN total loss: 0.0183 Total loss: 0.93415 timestamp: 1655074024.2032425 iteration: 83335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.06196 FastRCNN total loss: 0.17981 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13672 RPN box loss: 0.0106 RPN score loss: 0.00812 RPN total loss: 0.01872 Total loss: 0.89769 timestamp: 1655074027.4658036 iteration: 83340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05735 FastRCNN class loss: 0.05987 FastRCNN total loss: 0.11722 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.11201 RPN box loss: 0.00545 RPN score loss: 0.00957 RPN total loss: 0.01502 Total loss: 0.80669 timestamp: 1655074030.738401 iteration: 83345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11912 FastRCNN class loss: 0.066 FastRCNN total loss: 0.18513 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1351 RPN box loss: 0.00873 RPN score loss: 0.00384 RPN total loss: 0.01258 Total loss: 0.89524 timestamp: 1655074034.032545 iteration: 83350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08553 FastRCNN class loss: 0.08623 FastRCNN total loss: 0.17176 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1457 RPN box loss: 0.01534 RPN score loss: 0.0054 RPN total loss: 0.02074 Total loss: 0.90063 timestamp: 1655074037.3899202 iteration: 83355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10795 FastRCNN class loss: 0.07358 FastRCNN total loss: 0.18153 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.26405 RPN box loss: 0.03386 RPN score loss: 0.01225 RPN total loss: 0.04612 Total loss: 1.05414 timestamp: 1655074040.679251 iteration: 83360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10828 FastRCNN class loss: 0.09095 FastRCNN total loss: 0.19923 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13799 RPN box loss: 0.02276 RPN score loss: 0.00573 RPN total loss: 0.02849 Total loss: 0.92814 timestamp: 1655074043.955428 iteration: 83365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0863 FastRCNN class loss: 0.09796 FastRCNN total loss: 0.18426 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.18528 RPN box loss: 0.00769 RPN score loss: 0.01254 RPN total loss: 0.02023 Total loss: 0.9522 timestamp: 1655074047.1919413 iteration: 83370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07399 FastRCNN class loss: 0.08903 FastRCNN total loss: 0.16302 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.19101 RPN box loss: 0.01506 RPN score loss: 0.00899 RPN total loss: 0.02406 Total loss: 0.94053 timestamp: 1655074050.516109 iteration: 83375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07299 FastRCNN class loss: 0.05816 FastRCNN total loss: 0.13114 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.1127 RPN box loss: 0.01612 RPN score loss: 0.00467 RPN total loss: 0.0208 Total loss: 0.82708 timestamp: 1655074053.7961762 iteration: 83380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07798 FastRCNN class loss: 0.04266 FastRCNN total loss: 0.12064 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.12198 RPN box loss: 0.00562 RPN score loss: 0.00233 RPN total loss: 0.00795 Total loss: 0.81301 timestamp: 1655074057.088473 iteration: 83385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06884 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.12541 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.11231 RPN box loss: 0.00522 RPN score loss: 0.00269 RPN total loss: 0.00791 Total loss: 0.80807 timestamp: 1655074060.4137776 iteration: 83390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08437 FastRCNN class loss: 0.06867 FastRCNN total loss: 0.15304 L1 loss: 0.0000e+00 L2 loss: 0.56244 Learning rate: 4.0000e-05 Mask loss: 0.13453 RPN box loss: 0.0068 RPN score loss: 0.00499 RPN total loss: 0.01179 Total loss: 0.8618 timestamp: 1655074063.805008 iteration: 83395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12103 FastRCNN class loss: 0.10865 FastRCNN total loss: 0.22969 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.21035 RPN box loss: 0.02684 RPN score loss: 0.00415 RPN total loss: 0.031 Total loss: 1.03347 timestamp: 1655074067.0769923 iteration: 83400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10961 FastRCNN class loss: 0.07231 FastRCNN total loss: 0.18192 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17707 RPN box loss: 0.01132 RPN score loss: 0.00249 RPN total loss: 0.01381 Total loss: 0.93524 timestamp: 1655074070.3333418 iteration: 83405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05739 FastRCNN class loss: 0.05094 FastRCNN total loss: 0.10833 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11856 RPN box loss: 0.03472 RPN score loss: 0.00396 RPN total loss: 0.03868 Total loss: 0.82801 timestamp: 1655074073.5759058 iteration: 83410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06577 FastRCNN class loss: 0.05003 FastRCNN total loss: 0.1158 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13556 RPN box loss: 0.00815 RPN score loss: 0.00378 RPN total loss: 0.01193 Total loss: 0.82572 timestamp: 1655074076.8008468 iteration: 83415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07667 FastRCNN class loss: 0.05979 FastRCNN total loss: 0.13646 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14317 RPN box loss: 0.01486 RPN score loss: 0.01245 RPN total loss: 0.02732 Total loss: 0.86938 timestamp: 1655074080.0400958 iteration: 83420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06446 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.11851 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.27313 RPN box loss: 0.01325 RPN score loss: 0.00213 RPN total loss: 0.01538 Total loss: 0.96945 timestamp: 1655074083.2922206 iteration: 83425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09997 FastRCNN class loss: 0.08422 FastRCNN total loss: 0.18419 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.19004 RPN box loss: 0.01044 RPN score loss: 0.00832 RPN total loss: 0.01876 Total loss: 0.95542 timestamp: 1655074086.5780525 iteration: 83430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09022 FastRCNN class loss: 0.04558 FastRCNN total loss: 0.1358 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11512 RPN box loss: 0.02633 RPN score loss: 0.00559 RPN total loss: 0.03192 Total loss: 0.84528 timestamp: 1655074089.848109 iteration: 83435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10364 FastRCNN class loss: 0.07505 FastRCNN total loss: 0.17869 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11222 RPN box loss: 0.0058 RPN score loss: 0.01229 RPN total loss: 0.01809 Total loss: 0.87144 timestamp: 1655074093.1287575 iteration: 83440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09741 FastRCNN class loss: 0.07001 FastRCNN total loss: 0.16741 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17647 RPN box loss: 0.01468 RPN score loss: 0.0097 RPN total loss: 0.02438 Total loss: 0.9307 timestamp: 1655074096.4466949 iteration: 83445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0935 FastRCNN class loss: 0.06065 FastRCNN total loss: 0.15415 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17 RPN box loss: 0.00416 RPN score loss: 0.00353 RPN total loss: 0.00769 Total loss: 0.89427 timestamp: 1655074099.7444293 iteration: 83450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0788 FastRCNN class loss: 0.0346 FastRCNN total loss: 0.11339 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11469 RPN box loss: 0.00248 RPN score loss: 0.00082 RPN total loss: 0.00329 Total loss: 0.79381 timestamp: 1655074103.1377792 iteration: 83455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08221 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.13974 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.08495 RPN box loss: 0.0101 RPN score loss: 0.00448 RPN total loss: 0.01459 Total loss: 0.80171 timestamp: 1655074106.404769 iteration: 83460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08084 FastRCNN class loss: 0.06677 FastRCNN total loss: 0.14761 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14347 RPN box loss: 0.01081 RPN score loss: 0.00482 RPN total loss: 0.01563 Total loss: 0.86915 timestamp: 1655074109.6763375 iteration: 83465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13155 FastRCNN class loss: 0.08469 FastRCNN total loss: 0.21625 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.18728 RPN box loss: 0.01377 RPN score loss: 0.01051 RPN total loss: 0.02427 Total loss: 0.99024 timestamp: 1655074112.8684762 iteration: 83470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10695 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.16791 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13886 RPN box loss: 0.00781 RPN score loss: 0.00478 RPN total loss: 0.01259 Total loss: 0.88179 timestamp: 1655074116.1403205 iteration: 83475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10668 FastRCNN class loss: 0.09256 FastRCNN total loss: 0.19924 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.21654 RPN box loss: 0.01507 RPN score loss: 0.009 RPN total loss: 0.02406 Total loss: 1.00227 timestamp: 1655074119.4643579 iteration: 83480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12953 FastRCNN class loss: 0.10342 FastRCNN total loss: 0.23295 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16366 RPN box loss: 0.01814 RPN score loss: 0.01071 RPN total loss: 0.02884 Total loss: 0.98788 timestamp: 1655074122.7683487 iteration: 83485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07974 FastRCNN class loss: 0.08795 FastRCNN total loss: 0.16769 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.12605 RPN box loss: 0.0128 RPN score loss: 0.00254 RPN total loss: 0.01535 Total loss: 0.87152 timestamp: 1655074126.1157103 iteration: 83490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07114 FastRCNN class loss: 0.06582 FastRCNN total loss: 0.13695 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.12678 RPN box loss: 0.00638 RPN score loss: 0.0032 RPN total loss: 0.00958 Total loss: 0.83574 timestamp: 1655074129.3826044 iteration: 83495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08985 FastRCNN class loss: 0.06219 FastRCNN total loss: 0.15204 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10458 RPN box loss: 0.00592 RPN score loss: 0.00454 RPN total loss: 0.01045 Total loss: 0.82951 timestamp: 1655074132.6895235 iteration: 83500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05948 FastRCNN class loss: 0.05578 FastRCNN total loss: 0.11526 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13879 RPN box loss: 0.01464 RPN score loss: 0.00656 RPN total loss: 0.0212 Total loss: 0.83768 timestamp: 1655074136.001115 iteration: 83505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07163 FastRCNN class loss: 0.05109 FastRCNN total loss: 0.12273 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10519 RPN box loss: 0.00563 RPN score loss: 0.00812 RPN total loss: 0.01375 Total loss: 0.8041 timestamp: 1655074139.2080915 iteration: 83510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1318 FastRCNN class loss: 0.11304 FastRCNN total loss: 0.24484 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16304 RPN box loss: 0.04123 RPN score loss: 0.01192 RPN total loss: 0.05315 Total loss: 1.02346 timestamp: 1655074142.4957392 iteration: 83515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10115 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.17064 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16188 RPN box loss: 0.00597 RPN score loss: 0.00345 RPN total loss: 0.00942 Total loss: 0.90437 timestamp: 1655074145.8560917 iteration: 83520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08108 FastRCNN class loss: 0.0556 FastRCNN total loss: 0.13669 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17422 RPN box loss: 0.0087 RPN score loss: 0.00332 RPN total loss: 0.01202 Total loss: 0.88535 timestamp: 1655074149.01205 iteration: 83525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07718 FastRCNN class loss: 0.0565 FastRCNN total loss: 0.13368 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10425 RPN box loss: 0.01332 RPN score loss: 0.0038 RPN total loss: 0.01712 Total loss: 0.81748 timestamp: 1655074152.300616 iteration: 83530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10297 FastRCNN class loss: 0.06089 FastRCNN total loss: 0.16385 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.1511 RPN box loss: 0.00723 RPN score loss: 0.00362 RPN total loss: 0.01085 Total loss: 0.88823 timestamp: 1655074155.6657073 iteration: 83535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08952 FastRCNN class loss: 0.0987 FastRCNN total loss: 0.18822 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.1282 RPN box loss: 0.02301 RPN score loss: 0.0097 RPN total loss: 0.03272 Total loss: 0.91157 timestamp: 1655074158.8964043 iteration: 83540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11254 FastRCNN class loss: 0.08463 FastRCNN total loss: 0.19717 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.18189 RPN box loss: 0.01673 RPN score loss: 0.0017 RPN total loss: 0.01843 Total loss: 0.95992 timestamp: 1655074162.180825 iteration: 83545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06356 FastRCNN class loss: 0.05487 FastRCNN total loss: 0.11843 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11041 RPN box loss: 0.02344 RPN score loss: 0.00292 RPN total loss: 0.02636 Total loss: 0.81763 timestamp: 1655074165.4596243 iteration: 83550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0994 FastRCNN class loss: 0.05989 FastRCNN total loss: 0.15929 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.12851 RPN box loss: 0.01028 RPN score loss: 0.00397 RPN total loss: 0.01425 Total loss: 0.86448 timestamp: 1655074168.7150557 iteration: 83555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06308 FastRCNN class loss: 0.0555 FastRCNN total loss: 0.11859 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.02084 RPN score loss: 0.00109 RPN total loss: 0.02193 Total loss: 0.85936 timestamp: 1655074171.9745638 iteration: 83560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08751 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.14353 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10761 RPN box loss: 0.0106 RPN score loss: 0.00466 RPN total loss: 0.01527 Total loss: 0.82884 timestamp: 1655074175.2071514 iteration: 83565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11138 FastRCNN class loss: 0.08915 FastRCNN total loss: 0.20053 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11467 RPN box loss: 0.01832 RPN score loss: 0.00283 RPN total loss: 0.02115 Total loss: 0.89878 timestamp: 1655074178.5481641 iteration: 83570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08497 FastRCNN class loss: 0.07213 FastRCNN total loss: 0.1571 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13535 RPN box loss: 0.02974 RPN score loss: 0.00386 RPN total loss: 0.0336 Total loss: 0.88847 timestamp: 1655074181.8198478 iteration: 83575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07721 FastRCNN class loss: 0.06451 FastRCNN total loss: 0.14172 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10304 RPN box loss: 0.00871 RPN score loss: 0.00386 RPN total loss: 0.01257 Total loss: 0.81976 timestamp: 1655074185.1203318 iteration: 83580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13059 FastRCNN class loss: 0.07999 FastRCNN total loss: 0.21058 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14495 RPN box loss: 0.00819 RPN score loss: 0.00473 RPN total loss: 0.01292 Total loss: 0.93088 timestamp: 1655074188.3569844 iteration: 83585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09763 FastRCNN class loss: 0.06327 FastRCNN total loss: 0.1609 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.09125 RPN box loss: 0.0331 RPN score loss: 0.00156 RPN total loss: 0.03467 Total loss: 0.84924 timestamp: 1655074191.6466174 iteration: 83590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05945 FastRCNN class loss: 0.04515 FastRCNN total loss: 0.1046 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.18553 RPN box loss: 0.00346 RPN score loss: 0.00231 RPN total loss: 0.00577 Total loss: 0.85833 timestamp: 1655074194.8758938 iteration: 83595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11403 FastRCNN class loss: 0.11274 FastRCNN total loss: 0.22677 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.22117 RPN box loss: 0.01653 RPN score loss: 0.01021 RPN total loss: 0.02675 Total loss: 1.03712 timestamp: 1655074198.1957655 iteration: 83600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13515 FastRCNN class loss: 0.06988 FastRCNN total loss: 0.20503 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17671 RPN box loss: 0.01763 RPN score loss: 0.01347 RPN total loss: 0.0311 Total loss: 0.97527 timestamp: 1655074201.4359665 iteration: 83605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05599 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.10563 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.0601 RPN box loss: 0.01294 RPN score loss: 0.00247 RPN total loss: 0.01541 Total loss: 0.74357 timestamp: 1655074204.7107182 iteration: 83610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06543 FastRCNN class loss: 0.05647 FastRCNN total loss: 0.1219 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14664 RPN box loss: 0.00877 RPN score loss: 0.00278 RPN total loss: 0.01155 Total loss: 0.84251 timestamp: 1655074207.912934 iteration: 83615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11233 FastRCNN class loss: 0.11053 FastRCNN total loss: 0.22286 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16166 RPN box loss: 0.00908 RPN score loss: 0.00213 RPN total loss: 0.0112 Total loss: 0.95815 timestamp: 1655074211.164692 iteration: 83620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14536 FastRCNN class loss: 0.07671 FastRCNN total loss: 0.22208 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.1219 RPN box loss: 0.01305 RPN score loss: 0.00652 RPN total loss: 0.01956 Total loss: 0.92597 timestamp: 1655074214.4164398 iteration: 83625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10122 FastRCNN class loss: 0.05334 FastRCNN total loss: 0.15456 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.1357 RPN box loss: 0.0195 RPN score loss: 0.00121 RPN total loss: 0.0207 Total loss: 0.87339 timestamp: 1655074217.7002013 iteration: 83630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09132 FastRCNN class loss: 0.07684 FastRCNN total loss: 0.16816 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.15374 RPN box loss: 0.00776 RPN score loss: 0.00264 RPN total loss: 0.0104 Total loss: 0.89472 timestamp: 1655074220.9487364 iteration: 83635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14525 FastRCNN class loss: 0.1086 FastRCNN total loss: 0.25384 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.18995 RPN box loss: 0.0463 RPN score loss: 0.01324 RPN total loss: 0.05954 Total loss: 1.06576 timestamp: 1655074224.305865 iteration: 83640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07184 FastRCNN class loss: 0.05523 FastRCNN total loss: 0.12707 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10182 RPN box loss: 0.02156 RPN score loss: 0.00268 RPN total loss: 0.02425 Total loss: 0.81557 timestamp: 1655074227.6091454 iteration: 83645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.092 FastRCNN class loss: 0.09343 FastRCNN total loss: 0.18543 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13871 RPN box loss: 0.01943 RPN score loss: 0.01309 RPN total loss: 0.03253 Total loss: 0.91909 timestamp: 1655074230.8680856 iteration: 83650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06711 FastRCNN class loss: 0.05171 FastRCNN total loss: 0.11882 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.13012 RPN box loss: 0.006 RPN score loss: 0.00751 RPN total loss: 0.01352 Total loss: 0.82488 timestamp: 1655074234.2081652 iteration: 83655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10889 FastRCNN class loss: 0.09483 FastRCNN total loss: 0.20372 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.17792 RPN box loss: 0.02433 RPN score loss: 0.00441 RPN total loss: 0.02874 Total loss: 0.97281 timestamp: 1655074237.487769 iteration: 83660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10392 FastRCNN class loss: 0.07476 FastRCNN total loss: 0.17867 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11333 RPN box loss: 0.02389 RPN score loss: 0.01494 RPN total loss: 0.03883 Total loss: 0.89326 timestamp: 1655074240.793449 iteration: 83665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11754 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.21143 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.12244 RPN box loss: 0.01038 RPN score loss: 0.00653 RPN total loss: 0.01691 Total loss: 0.91321 timestamp: 1655074244.0951068 iteration: 83670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11777 FastRCNN class loss: 0.04599 FastRCNN total loss: 0.16377 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.11868 RPN box loss: 0.01018 RPN score loss: 0.00128 RPN total loss: 0.01147 Total loss: 0.85634 timestamp: 1655074247.3671672 iteration: 83675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08245 FastRCNN class loss: 0.09712 FastRCNN total loss: 0.17958 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.15655 RPN box loss: 0.01018 RPN score loss: 0.00557 RPN total loss: 0.01574 Total loss: 0.91429 timestamp: 1655074250.6133626 iteration: 83680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07394 FastRCNN class loss: 0.04218 FastRCNN total loss: 0.11611 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14212 RPN box loss: 0.01022 RPN score loss: 0.00462 RPN total loss: 0.01484 Total loss: 0.8355 timestamp: 1655074253.8857954 iteration: 83685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08015 FastRCNN class loss: 0.06227 FastRCNN total loss: 0.14242 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.14083 RPN box loss: 0.01189 RPN score loss: 0.0134 RPN total loss: 0.02529 Total loss: 0.87096 timestamp: 1655074257.2441266 iteration: 83690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1317 FastRCNN class loss: 0.10452 FastRCNN total loss: 0.23621 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16933 RPN box loss: 0.01477 RPN score loss: 0.00244 RPN total loss: 0.01721 Total loss: 0.98518 timestamp: 1655074260.519107 iteration: 83695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10164 FastRCNN class loss: 0.04575 FastRCNN total loss: 0.1474 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.10777 RPN box loss: 0.00588 RPN score loss: 0.00125 RPN total loss: 0.00713 Total loss: 0.82472 timestamp: 1655074263.7784708 iteration: 83700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09357 FastRCNN class loss: 0.09275 FastRCNN total loss: 0.18633 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.16326 RPN box loss: 0.01788 RPN score loss: 0.01304 RPN total loss: 0.03092 Total loss: 0.94293 timestamp: 1655074267.0377512 iteration: 83705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06398 FastRCNN class loss: 0.03744 FastRCNN total loss: 0.10142 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.09333 RPN box loss: 0.0072 RPN score loss: 0.00345 RPN total loss: 0.01065 Total loss: 0.76783 timestamp: 1655074270.3035784 iteration: 83710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12681 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.19407 L1 loss: 0.0000e+00 L2 loss: 0.56243 Learning rate: 4.0000e-05 Mask loss: 0.20238 RPN box loss: 0.01331 RPN score loss: 0.00483 RPN total loss: 0.01814 Total loss: 0.97702 timestamp: 1655074273.6500132 iteration: 83715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0692 FastRCNN class loss: 0.05366 FastRCNN total loss: 0.12286 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.12182 RPN box loss: 0.00557 RPN score loss: 0.00531 RPN total loss: 0.01088 Total loss: 0.81799 timestamp: 1655074276.8685205 iteration: 83720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1118 FastRCNN class loss: 0.07754 FastRCNN total loss: 0.18934 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.12619 RPN box loss: 0.00934 RPN score loss: 0.0058 RPN total loss: 0.01515 Total loss: 0.89311 timestamp: 1655074280.1483665 iteration: 83725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09596 FastRCNN class loss: 0.08199 FastRCNN total loss: 0.17795 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.20601 RPN box loss: 0.01941 RPN score loss: 0.01971 RPN total loss: 0.03912 Total loss: 0.98551 timestamp: 1655074283.4042919 iteration: 83730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09237 FastRCNN class loss: 0.0798 FastRCNN total loss: 0.17218 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.1845 RPN box loss: 0.0117 RPN score loss: 0.0014 RPN total loss: 0.0131 Total loss: 0.9322 timestamp: 1655074286.7772987 iteration: 83735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.07907 FastRCNN total loss: 0.15264 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14296 RPN box loss: 0.02776 RPN score loss: 0.00272 RPN total loss: 0.03048 Total loss: 0.88851 timestamp: 1655074290.0472307 iteration: 83740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06477 FastRCNN class loss: 0.05165 FastRCNN total loss: 0.11642 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.10989 RPN box loss: 0.0068 RPN score loss: 0.00135 RPN total loss: 0.00816 Total loss: 0.79689 timestamp: 1655074293.2893124 iteration: 83745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09026 FastRCNN class loss: 0.0648 FastRCNN total loss: 0.15506 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14558 RPN box loss: 0.00983 RPN score loss: 0.00561 RPN total loss: 0.01544 Total loss: 0.8785 timestamp: 1655074296.5427768 iteration: 83750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14651 FastRCNN class loss: 0.0736 FastRCNN total loss: 0.22011 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.16035 RPN box loss: 0.01047 RPN score loss: 0.00848 RPN total loss: 0.01895 Total loss: 0.96183 timestamp: 1655074299.7989428 iteration: 83755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0995 FastRCNN class loss: 0.05101 FastRCNN total loss: 0.15051 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14476 RPN box loss: 0.011 RPN score loss: 0.00241 RPN total loss: 0.0134 Total loss: 0.87109 timestamp: 1655074303.0382738 iteration: 83760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09045 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.15888 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14784 RPN box loss: 0.00821 RPN score loss: 0.00639 RPN total loss: 0.0146 Total loss: 0.88374 timestamp: 1655074306.3053944 iteration: 83765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09554 FastRCNN class loss: 0.06408 FastRCNN total loss: 0.15962 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.16158 RPN box loss: 0.00678 RPN score loss: 0.00297 RPN total loss: 0.00974 Total loss: 0.89337 timestamp: 1655074309.5599282 iteration: 83770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.096 FastRCNN class loss: 0.07013 FastRCNN total loss: 0.16613 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13966 RPN box loss: 0.02066 RPN score loss: 0.00093 RPN total loss: 0.02159 Total loss: 0.8898 timestamp: 1655074312.9335668 iteration: 83775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10208 FastRCNN class loss: 0.07256 FastRCNN total loss: 0.17465 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14435 RPN box loss: 0.01239 RPN score loss: 0.00517 RPN total loss: 0.01756 Total loss: 0.89898 timestamp: 1655074316.2145913 iteration: 83780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05645 FastRCNN class loss: 0.06666 FastRCNN total loss: 0.12311 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.07596 RPN box loss: 0.0142 RPN score loss: 0.00291 RPN total loss: 0.01711 Total loss: 0.7786 timestamp: 1655074319.5414577 iteration: 83785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09039 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.16501 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.17699 RPN box loss: 0.00399 RPN score loss: 0.00535 RPN total loss: 0.00934 Total loss: 0.91376 timestamp: 1655074322.9254367 iteration: 83790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08683 FastRCNN class loss: 0.09145 FastRCNN total loss: 0.17828 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.18066 RPN box loss: 0.01624 RPN score loss: 0.01057 RPN total loss: 0.02681 Total loss: 0.94817 timestamp: 1655074326.1627102 iteration: 83795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13675 FastRCNN class loss: 0.07897 FastRCNN total loss: 0.21572 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.1271 RPN box loss: 0.01913 RPN score loss: 0.00515 RPN total loss: 0.02428 Total loss: 0.92952 timestamp: 1655074329.4678817 iteration: 83800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11791 FastRCNN class loss: 0.07241 FastRCNN total loss: 0.19033 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14521 RPN box loss: 0.01481 RPN score loss: 0.00216 RPN total loss: 0.01697 Total loss: 0.91493 timestamp: 1655074332.7353468 iteration: 83805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11021 FastRCNN class loss: 0.10913 FastRCNN total loss: 0.21935 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.2567 RPN box loss: 0.01574 RPN score loss: 0.00725 RPN total loss: 0.02298 Total loss: 1.06145 timestamp: 1655074335.9904993 iteration: 83810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12564 FastRCNN class loss: 0.10904 FastRCNN total loss: 0.23468 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13368 RPN box loss: 0.02265 RPN score loss: 0.01318 RPN total loss: 0.03583 Total loss: 0.9666 timestamp: 1655074339.309241 iteration: 83815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09575 FastRCNN class loss: 0.07248 FastRCNN total loss: 0.16822 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.11761 RPN box loss: 0.02806 RPN score loss: 0.00366 RPN total loss: 0.03172 Total loss: 0.87997 timestamp: 1655074342.5673547 iteration: 83820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09652 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.17535 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.17725 RPN box loss: 0.00788 RPN score loss: 0.00232 RPN total loss: 0.0102 Total loss: 0.92522 timestamp: 1655074345.7617526 iteration: 83825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14573 FastRCNN class loss: 0.08297 FastRCNN total loss: 0.2287 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15996 RPN box loss: 0.05093 RPN score loss: 0.01982 RPN total loss: 0.07076 Total loss: 1.02184 timestamp: 1655074349.0581279 iteration: 83830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07726 FastRCNN class loss: 0.06928 FastRCNN total loss: 0.14654 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.08711 RPN box loss: 0.00812 RPN score loss: 0.00701 RPN total loss: 0.01513 Total loss: 0.8112 timestamp: 1655074352.3306274 iteration: 83835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09829 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.17025 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.1043 RPN box loss: 0.00812 RPN score loss: 0.0026 RPN total loss: 0.01072 Total loss: 0.8477 timestamp: 1655074355.6073453 iteration: 83840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06538 FastRCNN class loss: 0.03661 FastRCNN total loss: 0.10199 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.08848 RPN box loss: 0.00715 RPN score loss: 0.00455 RPN total loss: 0.0117 Total loss: 0.76459 timestamp: 1655074358.8112466 iteration: 83845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09365 FastRCNN class loss: 0.07662 FastRCNN total loss: 0.17027 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.19034 RPN box loss: 0.00854 RPN score loss: 0.00348 RPN total loss: 0.01202 Total loss: 0.93505 timestamp: 1655074362.0917852 iteration: 83850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11768 FastRCNN class loss: 0.04271 FastRCNN total loss: 0.1604 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.08631 RPN box loss: 0.0054 RPN score loss: 0.00583 RPN total loss: 0.01123 Total loss: 0.82036 timestamp: 1655074365.3662512 iteration: 83855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13323 FastRCNN class loss: 0.06044 FastRCNN total loss: 0.19367 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14441 RPN box loss: 0.00512 RPN score loss: 0.00367 RPN total loss: 0.0088 Total loss: 0.90929 timestamp: 1655074368.657071 iteration: 83860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.072 FastRCNN class loss: 0.07422 FastRCNN total loss: 0.14622 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15167 RPN box loss: 0.00874 RPN score loss: 0.00859 RPN total loss: 0.01733 Total loss: 0.87764 timestamp: 1655074371.886948 iteration: 83865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06002 FastRCNN class loss: 0.04883 FastRCNN total loss: 0.10885 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.12058 RPN box loss: 0.01652 RPN score loss: 0.00424 RPN total loss: 0.02076 Total loss: 0.81262 timestamp: 1655074375.1503386 iteration: 83870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07899 FastRCNN class loss: 0.08289 FastRCNN total loss: 0.16188 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.18289 RPN box loss: 0.00842 RPN score loss: 0.00201 RPN total loss: 0.01042 Total loss: 0.91762 timestamp: 1655074378.455251 iteration: 83875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12905 FastRCNN class loss: 0.07188 FastRCNN total loss: 0.20093 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15293 RPN box loss: 0.01866 RPN score loss: 0.00664 RPN total loss: 0.0253 Total loss: 0.94158 timestamp: 1655074381.6981022 iteration: 83880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12068 FastRCNN class loss: 0.08785 FastRCNN total loss: 0.20853 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.19255 RPN box loss: 0.01558 RPN score loss: 0.00697 RPN total loss: 0.02254 Total loss: 0.98604 timestamp: 1655074384.9860518 iteration: 83885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0631 FastRCNN class loss: 0.05418 FastRCNN total loss: 0.11728 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15759 RPN box loss: 0.0094 RPN score loss: 0.00161 RPN total loss: 0.01101 Total loss: 0.8483 timestamp: 1655074388.315948 iteration: 83890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05979 FastRCNN class loss: 0.05642 FastRCNN total loss: 0.1162 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.18141 RPN box loss: 0.01149 RPN score loss: 0.00601 RPN total loss: 0.01751 Total loss: 0.87754 timestamp: 1655074391.5865278 iteration: 83895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10296 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.16875 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.17695 RPN box loss: 0.02518 RPN score loss: 0.00552 RPN total loss: 0.0307 Total loss: 0.93881 timestamp: 1655074394.8148997 iteration: 83900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10931 FastRCNN class loss: 0.07487 FastRCNN total loss: 0.18418 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14099 RPN box loss: 0.03248 RPN score loss: 0.0042 RPN total loss: 0.03668 Total loss: 0.92427 timestamp: 1655074398.065148 iteration: 83905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11212 FastRCNN class loss: 0.06621 FastRCNN total loss: 0.17833 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.11475 RPN box loss: 0.0089 RPN score loss: 0.00493 RPN total loss: 0.01382 Total loss: 0.86932 timestamp: 1655074401.3794804 iteration: 83910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1075 FastRCNN class loss: 0.07214 FastRCNN total loss: 0.17964 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15189 RPN box loss: 0.01459 RPN score loss: 0.01349 RPN total loss: 0.02809 Total loss: 0.92204 timestamp: 1655074404.589311 iteration: 83915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10101 FastRCNN class loss: 0.07553 FastRCNN total loss: 0.17654 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.10271 RPN box loss: 0.00502 RPN score loss: 0.00737 RPN total loss: 0.01239 Total loss: 0.85406 timestamp: 1655074407.825612 iteration: 83920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1289 FastRCNN class loss: 0.0728 FastRCNN total loss: 0.2017 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.17453 RPN box loss: 0.02303 RPN score loss: 0.005 RPN total loss: 0.02803 Total loss: 0.96667 timestamp: 1655074411.104751 iteration: 83925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08758 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.14669 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.12682 RPN box loss: 0.00602 RPN score loss: 0.00869 RPN total loss: 0.01471 Total loss: 0.85063 timestamp: 1655074414.398553 iteration: 83930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06053 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.13044 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.0965 RPN box loss: 0.02848 RPN score loss: 0.00332 RPN total loss: 0.0318 Total loss: 0.82115 timestamp: 1655074417.6687596 iteration: 83935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1353 FastRCNN class loss: 0.07124 FastRCNN total loss: 0.20654 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.2077 RPN box loss: 0.00439 RPN score loss: 0.00747 RPN total loss: 0.01186 Total loss: 0.98851 timestamp: 1655074420.875226 iteration: 83940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1018 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.16873 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15867 RPN box loss: 0.00685 RPN score loss: 0.00767 RPN total loss: 0.01452 Total loss: 0.90434 timestamp: 1655074424.1312263 iteration: 83945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08611 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.16049 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.17379 RPN box loss: 0.0119 RPN score loss: 0.00352 RPN total loss: 0.01542 Total loss: 0.91211 timestamp: 1655074427.4002228 iteration: 83950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12634 FastRCNN class loss: 0.10761 FastRCNN total loss: 0.23395 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.16238 RPN box loss: 0.01068 RPN score loss: 0.01098 RPN total loss: 0.02166 Total loss: 0.98041 timestamp: 1655074430.6540196 iteration: 83955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15274 FastRCNN class loss: 0.06693 FastRCNN total loss: 0.21967 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.18992 RPN box loss: 0.008 RPN score loss: 0.0039 RPN total loss: 0.0119 Total loss: 0.9839 timestamp: 1655074433.902271 iteration: 83960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11512 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.1846 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13584 RPN box loss: 0.01442 RPN score loss: 0.00898 RPN total loss: 0.0234 Total loss: 0.90625 timestamp: 1655074437.1320388 iteration: 83965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12176 FastRCNN class loss: 0.1147 FastRCNN total loss: 0.23646 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.22095 RPN box loss: 0.01134 RPN score loss: 0.01437 RPN total loss: 0.02571 Total loss: 1.04553 timestamp: 1655074440.3857863 iteration: 83970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09711 FastRCNN class loss: 0.0846 FastRCNN total loss: 0.18171 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13069 RPN box loss: 0.00769 RPN score loss: 0.00491 RPN total loss: 0.0126 Total loss: 0.88742 timestamp: 1655074443.656472 iteration: 83975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10022 FastRCNN class loss: 0.0919 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14457 RPN box loss: 0.02313 RPN score loss: 0.00624 RPN total loss: 0.02937 Total loss: 0.92848 timestamp: 1655074446.9792128 iteration: 83980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06349 FastRCNN class loss: 0.06914 FastRCNN total loss: 0.13263 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15998 RPN box loss: 0.03364 RPN score loss: 0.0087 RPN total loss: 0.04234 Total loss: 0.89737 timestamp: 1655074450.3293772 iteration: 83985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1423 FastRCNN class loss: 0.04983 FastRCNN total loss: 0.19213 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.10159 RPN box loss: 0.00714 RPN score loss: 0.00166 RPN total loss: 0.0088 Total loss: 0.86494 timestamp: 1655074453.5757434 iteration: 83990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09318 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.1814 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.15167 RPN box loss: 0.00984 RPN score loss: 0.00339 RPN total loss: 0.01323 Total loss: 0.90872 timestamp: 1655074456.8548117 iteration: 83995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05802 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.11253 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.10972 RPN box loss: 0.00831 RPN score loss: 0.00357 RPN total loss: 0.01188 Total loss: 0.79655 timestamp: 1655074460.1408272 iteration: 84000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15537 FastRCNN class loss: 0.06949 FastRCNN total loss: 0.22486 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.11758 RPN box loss: 0.00823 RPN score loss: 0.00529 RPN total loss: 0.01353 Total loss: 0.91838 timestamp: 1655074463.4171753 iteration: 84005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09866 FastRCNN class loss: 0.11084 FastRCNN total loss: 0.2095 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13976 RPN box loss: 0.0062 RPN score loss: 0.00379 RPN total loss: 0.01 Total loss: 0.92168 timestamp: 1655074466.6395223 iteration: 84010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12142 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.20237 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14033 RPN box loss: 0.0195 RPN score loss: 0.01196 RPN total loss: 0.03145 Total loss: 0.93657 timestamp: 1655074469.9386296 iteration: 84015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0978 FastRCNN class loss: 0.04955 FastRCNN total loss: 0.14735 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.10294 RPN box loss: 0.00576 RPN score loss: 0.00949 RPN total loss: 0.01525 Total loss: 0.82796 timestamp: 1655074473.2211342 iteration: 84020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09992 FastRCNN class loss: 0.0792 FastRCNN total loss: 0.17913 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.1632 RPN box loss: 0.05233 RPN score loss: 0.00596 RPN total loss: 0.05828 Total loss: 0.96303 timestamp: 1655074476.4739974 iteration: 84025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11287 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.16674 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.14338 RPN box loss: 0.01122 RPN score loss: 0.00153 RPN total loss: 0.01276 Total loss: 0.88529 timestamp: 1655074479.778744 iteration: 84030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09103 FastRCNN class loss: 0.08125 FastRCNN total loss: 0.17228 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.16369 RPN box loss: 0.00741 RPN score loss: 0.00231 RPN total loss: 0.00972 Total loss: 0.9081 timestamp: 1655074483.022094 iteration: 84035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10925 FastRCNN class loss: 0.05733 FastRCNN total loss: 0.16657 L1 loss: 0.0000e+00 L2 loss: 0.56242 Learning rate: 4.0000e-05 Mask loss: 0.13454 RPN box loss: 0.02296 RPN score loss: 0.01629 RPN total loss: 0.03925 Total loss: 0.90277 timestamp: 1655074486.2291431 iteration: 84040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10201 FastRCNN class loss: 0.10957 FastRCNN total loss: 0.21158 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.20668 RPN box loss: 0.01097 RPN score loss: 0.01265 RPN total loss: 0.02362 Total loss: 1.00429 timestamp: 1655074489.5090234 iteration: 84045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08519 FastRCNN class loss: 0.05341 FastRCNN total loss: 0.1386 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.16538 RPN box loss: 0.01619 RPN score loss: 0.00572 RPN total loss: 0.02191 Total loss: 0.88831 timestamp: 1655074492.8113089 iteration: 84050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06044 FastRCNN class loss: 0.03159 FastRCNN total loss: 0.09202 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.09234 RPN box loss: 0.00358 RPN score loss: 0.00337 RPN total loss: 0.00695 Total loss: 0.75372 timestamp: 1655074496.1101136 iteration: 84055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08708 FastRCNN class loss: 0.05553 FastRCNN total loss: 0.14261 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13513 RPN box loss: 0.03204 RPN score loss: 0.0105 RPN total loss: 0.04254 Total loss: 0.88269 timestamp: 1655074499.3813472 iteration: 84060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14721 FastRCNN class loss: 0.06729 FastRCNN total loss: 0.2145 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12314 RPN box loss: 0.02821 RPN score loss: 0.00243 RPN total loss: 0.03064 Total loss: 0.9307 timestamp: 1655074502.647619 iteration: 84065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08474 FastRCNN class loss: 0.04711 FastRCNN total loss: 0.13185 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1373 RPN box loss: 0.00906 RPN score loss: 0.0054 RPN total loss: 0.01445 Total loss: 0.84602 timestamp: 1655074505.964286 iteration: 84070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09113 FastRCNN class loss: 0.05754 FastRCNN total loss: 0.14867 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14335 RPN box loss: 0.00609 RPN score loss: 0.00227 RPN total loss: 0.00836 Total loss: 0.8628 timestamp: 1655074509.2150764 iteration: 84075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05706 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.11327 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15917 RPN box loss: 0.00728 RPN score loss: 0.00678 RPN total loss: 0.01405 Total loss: 0.84891 timestamp: 1655074512.4754074 iteration: 84080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09584 FastRCNN class loss: 0.06417 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1731 RPN box loss: 0.0167 RPN score loss: 0.00529 RPN total loss: 0.02199 Total loss: 0.91752 timestamp: 1655074515.72386 iteration: 84085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16406 FastRCNN class loss: 0.10782 FastRCNN total loss: 0.27188 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.20322 RPN box loss: 0.01071 RPN score loss: 0.00478 RPN total loss: 0.01549 Total loss: 1.05301 timestamp: 1655074519.0046723 iteration: 84090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11824 FastRCNN class loss: 0.12062 FastRCNN total loss: 0.23886 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14289 RPN box loss: 0.00712 RPN score loss: 0.0037 RPN total loss: 0.01082 Total loss: 0.95498 timestamp: 1655074522.256347 iteration: 84095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06566 FastRCNN class loss: 0.06877 FastRCNN total loss: 0.13443 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.09979 RPN box loss: 0.00721 RPN score loss: 0.00231 RPN total loss: 0.00952 Total loss: 0.80615 timestamp: 1655074525.546601 iteration: 84100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1256 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.18594 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14476 RPN box loss: 0.02069 RPN score loss: 0.00776 RPN total loss: 0.02846 Total loss: 0.92157 timestamp: 1655074528.8500562 iteration: 84105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15221 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.23217 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.16174 RPN box loss: 0.00491 RPN score loss: 0.00455 RPN total loss: 0.00947 Total loss: 0.96579 timestamp: 1655074532.1897898 iteration: 84110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11144 FastRCNN class loss: 0.07426 FastRCNN total loss: 0.18571 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15894 RPN box loss: 0.02889 RPN score loss: 0.00448 RPN total loss: 0.03337 Total loss: 0.94043 timestamp: 1655074535.490878 iteration: 84115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.08622 FastRCNN total loss: 0.16025 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12864 RPN box loss: 0.02187 RPN score loss: 0.01611 RPN total loss: 0.03799 Total loss: 0.88929 timestamp: 1655074538.7636473 iteration: 84120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13829 FastRCNN class loss: 0.07441 FastRCNN total loss: 0.21269 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17255 RPN box loss: 0.0356 RPN score loss: 0.0059 RPN total loss: 0.04151 Total loss: 0.98917 timestamp: 1655074542.0170212 iteration: 84125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16813 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.22822 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13714 RPN box loss: 0.02334 RPN score loss: 0.00557 RPN total loss: 0.02892 Total loss: 0.95669 timestamp: 1655074545.2319138 iteration: 84130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1182 FastRCNN class loss: 0.16849 FastRCNN total loss: 0.28669 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.23916 RPN box loss: 0.03278 RPN score loss: 0.08806 RPN total loss: 0.12084 Total loss: 1.20911 timestamp: 1655074548.512473 iteration: 84135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06514 FastRCNN class loss: 0.04573 FastRCNN total loss: 0.11086 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12333 RPN box loss: 0.00735 RPN score loss: 0.00306 RPN total loss: 0.01041 Total loss: 0.80702 timestamp: 1655074551.6936448 iteration: 84140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1386 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.20097 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12956 RPN box loss: 0.01117 RPN score loss: 0.0045 RPN total loss: 0.01568 Total loss: 0.90862 timestamp: 1655074554.9961886 iteration: 84145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09551 FastRCNN class loss: 0.09039 FastRCNN total loss: 0.1859 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14757 RPN box loss: 0.01927 RPN score loss: 0.00647 RPN total loss: 0.02574 Total loss: 0.92163 timestamp: 1655074558.3027 iteration: 84150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09357 FastRCNN class loss: 0.07362 FastRCNN total loss: 0.16719 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17225 RPN box loss: 0.01266 RPN score loss: 0.00737 RPN total loss: 0.02003 Total loss: 0.92188 timestamp: 1655074561.5843124 iteration: 84155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09252 FastRCNN class loss: 0.06528 FastRCNN total loss: 0.1578 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1486 RPN box loss: 0.01385 RPN score loss: 0.00684 RPN total loss: 0.02069 Total loss: 0.8895 timestamp: 1655074564.8460333 iteration: 84160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0688 FastRCNN class loss: 0.04066 FastRCNN total loss: 0.10946 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.0898 RPN box loss: 0.00454 RPN score loss: 0.00249 RPN total loss: 0.00702 Total loss: 0.76869 timestamp: 1655074568.1753428 iteration: 84165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05479 FastRCNN class loss: 0.0421 FastRCNN total loss: 0.09689 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1658 RPN box loss: 0.00749 RPN score loss: 0.01246 RPN total loss: 0.01995 Total loss: 0.84506 timestamp: 1655074571.4448295 iteration: 84170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11793 FastRCNN class loss: 0.08277 FastRCNN total loss: 0.2007 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.16827 RPN box loss: 0.02043 RPN score loss: 0.00723 RPN total loss: 0.02766 Total loss: 0.95904 timestamp: 1655074574.6479118 iteration: 84175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0595 FastRCNN class loss: 0.04191 FastRCNN total loss: 0.10142 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.11158 RPN box loss: 0.00932 RPN score loss: 0.00653 RPN total loss: 0.01585 Total loss: 0.79126 timestamp: 1655074577.9659586 iteration: 84180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16682 FastRCNN class loss: 0.06311 FastRCNN total loss: 0.22993 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17035 RPN box loss: 0.0112 RPN score loss: 0.00457 RPN total loss: 0.01576 Total loss: 0.97846 timestamp: 1655074581.2161126 iteration: 84185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04775 FastRCNN class loss: 0.02511 FastRCNN total loss: 0.07285 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13926 RPN box loss: 0.00243 RPN score loss: 0.00229 RPN total loss: 0.00472 Total loss: 0.77925 timestamp: 1655074584.497159 iteration: 84190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10771 FastRCNN class loss: 0.08521 FastRCNN total loss: 0.19291 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15829 RPN box loss: 0.01123 RPN score loss: 0.01353 RPN total loss: 0.02475 Total loss: 0.93837 timestamp: 1655074587.8421464 iteration: 84195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13216 FastRCNN class loss: 0.13207 FastRCNN total loss: 0.26423 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.2162 RPN box loss: 0.02469 RPN score loss: 0.0092 RPN total loss: 0.03389 Total loss: 1.07673 timestamp: 1655074591.0634022 iteration: 84200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08378 FastRCNN class loss: 0.0662 FastRCNN total loss: 0.14998 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13348 RPN box loss: 0.02041 RPN score loss: 0.02007 RPN total loss: 0.04048 Total loss: 0.88635 timestamp: 1655074594.309279 iteration: 84205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08934 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.15661 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13279 RPN box loss: 0.00661 RPN score loss: 0.00178 RPN total loss: 0.00838 Total loss: 0.86019 timestamp: 1655074597.5730102 iteration: 84210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0993 FastRCNN class loss: 0.04028 FastRCNN total loss: 0.13957 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.11555 RPN box loss: 0.00884 RPN score loss: 0.00451 RPN total loss: 0.01335 Total loss: 0.83088 timestamp: 1655074600.8812156 iteration: 84215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09367 FastRCNN class loss: 0.04227 FastRCNN total loss: 0.13593 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15216 RPN box loss: 0.00387 RPN score loss: 0.0019 RPN total loss: 0.00577 Total loss: 0.85628 timestamp: 1655074604.0824208 iteration: 84220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08015 FastRCNN class loss: 0.04452 FastRCNN total loss: 0.12467 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.11568 RPN box loss: 0.00803 RPN score loss: 0.00262 RPN total loss: 0.01064 Total loss: 0.8134 timestamp: 1655074607.3509216 iteration: 84225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1089 FastRCNN class loss: 0.07668 FastRCNN total loss: 0.18559 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13818 RPN box loss: 0.02948 RPN score loss: 0.00951 RPN total loss: 0.03899 Total loss: 0.92516 timestamp: 1655074610.609386 iteration: 84230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1271 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.19283 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12756 RPN box loss: 0.00485 RPN score loss: 0.00164 RPN total loss: 0.00649 Total loss: 0.88928 timestamp: 1655074613.961665 iteration: 84235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16106 FastRCNN class loss: 0.07903 FastRCNN total loss: 0.24009 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15674 RPN box loss: 0.01433 RPN score loss: 0.00352 RPN total loss: 0.01786 Total loss: 0.97709 timestamp: 1655074617.231277 iteration: 84240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09426 FastRCNN class loss: 0.08492 FastRCNN total loss: 0.17918 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17099 RPN box loss: 0.01173 RPN score loss: 0.0023 RPN total loss: 0.01402 Total loss: 0.92661 timestamp: 1655074620.5544748 iteration: 84245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0781 FastRCNN class loss: 0.04652 FastRCNN total loss: 0.12462 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17323 RPN box loss: 0.01448 RPN score loss: 0.00695 RPN total loss: 0.02143 Total loss: 0.88169 timestamp: 1655074623.788369 iteration: 84250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08459 FastRCNN class loss: 0.07912 FastRCNN total loss: 0.16372 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12168 RPN box loss: 0.00707 RPN score loss: 0.00991 RPN total loss: 0.01698 Total loss: 0.86479 timestamp: 1655074627.0689962 iteration: 84255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.06253 FastRCNN total loss: 0.16399 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.0947 RPN box loss: 0.0204 RPN score loss: 0.00791 RPN total loss: 0.02831 Total loss: 0.8494 timestamp: 1655074630.309842 iteration: 84260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07123 FastRCNN class loss: 0.07721 FastRCNN total loss: 0.14844 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15659 RPN box loss: 0.0071 RPN score loss: 0.00423 RPN total loss: 0.01133 Total loss: 0.87878 timestamp: 1655074633.651503 iteration: 84265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06803 FastRCNN class loss: 0.09149 FastRCNN total loss: 0.15952 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.11019 RPN box loss: 0.00866 RPN score loss: 0.00694 RPN total loss: 0.01561 Total loss: 0.84772 timestamp: 1655074636.9295845 iteration: 84270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07952 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.15198 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1729 RPN box loss: 0.00736 RPN score loss: 0.00433 RPN total loss: 0.01169 Total loss: 0.89897 timestamp: 1655074640.118491 iteration: 84275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06385 FastRCNN class loss: 0.0607 FastRCNN total loss: 0.12455 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12645 RPN box loss: 0.01031 RPN score loss: 0.00188 RPN total loss: 0.01219 Total loss: 0.82559 timestamp: 1655074643.4191535 iteration: 84280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07133 FastRCNN class loss: 0.04507 FastRCNN total loss: 0.1164 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12465 RPN box loss: 0.01515 RPN score loss: 0.00328 RPN total loss: 0.01843 Total loss: 0.82188 timestamp: 1655074646.7196364 iteration: 84285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10539 FastRCNN class loss: 0.08004 FastRCNN total loss: 0.18543 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17913 RPN box loss: 0.01005 RPN score loss: 0.00362 RPN total loss: 0.01367 Total loss: 0.94064 timestamp: 1655074649.9935997 iteration: 84290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.05412 FastRCNN total loss: 0.13442 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14603 RPN box loss: 0.01207 RPN score loss: 0.0065 RPN total loss: 0.01858 Total loss: 0.86144 timestamp: 1655074653.3421838 iteration: 84295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08371 FastRCNN class loss: 0.05531 FastRCNN total loss: 0.13902 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.1427 RPN box loss: 0.00399 RPN score loss: 0.00128 RPN total loss: 0.00528 Total loss: 0.84941 timestamp: 1655074656.6404018 iteration: 84300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07027 FastRCNN class loss: 0.06452 FastRCNN total loss: 0.13479 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14834 RPN box loss: 0.01432 RPN score loss: 0.0059 RPN total loss: 0.02022 Total loss: 0.86576 timestamp: 1655074659.894202 iteration: 84305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.06904 FastRCNN total loss: 0.14285 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12376 RPN box loss: 0.00878 RPN score loss: 0.00154 RPN total loss: 0.01032 Total loss: 0.83933 timestamp: 1655074663.160652 iteration: 84310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08942 FastRCNN class loss: 0.08056 FastRCNN total loss: 0.16997 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12658 RPN box loss: 0.01241 RPN score loss: 0.00168 RPN total loss: 0.01409 Total loss: 0.87305 timestamp: 1655074666.4730668 iteration: 84315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08436 FastRCNN class loss: 0.07407 FastRCNN total loss: 0.15842 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.15654 RPN box loss: 0.02317 RPN score loss: 0.00609 RPN total loss: 0.02926 Total loss: 0.90664 timestamp: 1655074669.746564 iteration: 84320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14208 FastRCNN class loss: 0.09962 FastRCNN total loss: 0.24171 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.16989 RPN box loss: 0.02815 RPN score loss: 0.01303 RPN total loss: 0.04118 Total loss: 1.01518 timestamp: 1655074672.9805567 iteration: 84325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10945 FastRCNN class loss: 0.07003 FastRCNN total loss: 0.17948 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.11793 RPN box loss: 0.02655 RPN score loss: 0.02956 RPN total loss: 0.05611 Total loss: 0.91593 timestamp: 1655074676.2030787 iteration: 84330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06747 FastRCNN class loss: 0.0675 FastRCNN total loss: 0.13497 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.14353 RPN box loss: 0.01455 RPN score loss: 0.00196 RPN total loss: 0.0165 Total loss: 0.85742 timestamp: 1655074679.4473307 iteration: 84335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12162 FastRCNN class loss: 0.07449 FastRCNN total loss: 0.19612 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13246 RPN box loss: 0.02027 RPN score loss: 0.00499 RPN total loss: 0.02525 Total loss: 0.91623 timestamp: 1655074682.6534357 iteration: 84340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09833 FastRCNN class loss: 0.04369 FastRCNN total loss: 0.14203 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.09221 RPN box loss: 0.00798 RPN score loss: 0.00156 RPN total loss: 0.00954 Total loss: 0.80618 timestamp: 1655074685.941133 iteration: 84345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07703 FastRCNN class loss: 0.06792 FastRCNN total loss: 0.14496 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.09095 RPN box loss: 0.00574 RPN score loss: 0.006 RPN total loss: 0.01175 Total loss: 0.81006 timestamp: 1655074689.137925 iteration: 84350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12898 FastRCNN class loss: 0.08627 FastRCNN total loss: 0.21525 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.19527 RPN box loss: 0.02032 RPN score loss: 0.01068 RPN total loss: 0.031 Total loss: 1.00393 timestamp: 1655074692.3150072 iteration: 84355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07401 FastRCNN class loss: 0.05968 FastRCNN total loss: 0.13369 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17506 RPN box loss: 0.00609 RPN score loss: 0.0042 RPN total loss: 0.01029 Total loss: 0.88144 timestamp: 1655074695.5997877 iteration: 84360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05247 FastRCNN class loss: 0.05166 FastRCNN total loss: 0.10412 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.13159 RPN box loss: 0.00951 RPN score loss: 0.0034 RPN total loss: 0.01291 Total loss: 0.81103 timestamp: 1655074698.8439748 iteration: 84365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06869 FastRCNN class loss: 0.04999 FastRCNN total loss: 0.11868 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.12364 RPN box loss: 0.0217 RPN score loss: 0.00476 RPN total loss: 0.02646 Total loss: 0.83119 timestamp: 1655074702.11711 iteration: 84370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10422 FastRCNN class loss: 0.11072 FastRCNN total loss: 0.21494 L1 loss: 0.0000e+00 L2 loss: 0.56241 Learning rate: 4.0000e-05 Mask loss: 0.17141 RPN box loss: 0.00924 RPN score loss: 0.00166 RPN total loss: 0.0109 Total loss: 0.95966 timestamp: 1655074705.3996224 iteration: 84375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15693 FastRCNN class loss: 0.0861 FastRCNN total loss: 0.24302 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.19112 RPN box loss: 0.0127 RPN score loss: 0.00724 RPN total loss: 0.01994 Total loss: 1.01648 timestamp: 1655074708.7314084 iteration: 84380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08345 FastRCNN class loss: 0.0559 FastRCNN total loss: 0.13935 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.11868 RPN box loss: 0.0076 RPN score loss: 0.00992 RPN total loss: 0.01752 Total loss: 0.83795 timestamp: 1655074712.026628 iteration: 84385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11039 FastRCNN class loss: 0.07861 FastRCNN total loss: 0.18901 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14782 RPN box loss: 0.00935 RPN score loss: 0.00338 RPN total loss: 0.01273 Total loss: 0.91197 timestamp: 1655074715.2729568 iteration: 84390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07784 FastRCNN class loss: 0.05753 FastRCNN total loss: 0.13537 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.10838 RPN box loss: 0.01019 RPN score loss: 0.00628 RPN total loss: 0.01647 Total loss: 0.82263 timestamp: 1655074718.5275817 iteration: 84395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1012 FastRCNN class loss: 0.10799 FastRCNN total loss: 0.20919 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.16467 RPN box loss: 0.02191 RPN score loss: 0.01916 RPN total loss: 0.04106 Total loss: 0.97733 timestamp: 1655074721.7864149 iteration: 84400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07463 FastRCNN class loss: 0.07949 FastRCNN total loss: 0.15411 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13674 RPN box loss: 0.00914 RPN score loss: 0.00517 RPN total loss: 0.01431 Total loss: 0.86756 timestamp: 1655074725.0076575 iteration: 84405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09949 FastRCNN class loss: 0.06707 FastRCNN total loss: 0.16656 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.24585 RPN box loss: 0.01743 RPN score loss: 0.00211 RPN total loss: 0.01954 Total loss: 0.99436 timestamp: 1655074728.3082643 iteration: 84410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11811 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.18627 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.17059 RPN box loss: 0.01736 RPN score loss: 0.00604 RPN total loss: 0.0234 Total loss: 0.94267 timestamp: 1655074731.5410805 iteration: 84415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11603 FastRCNN class loss: 0.07438 FastRCNN total loss: 0.19041 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.20145 RPN box loss: 0.02253 RPN score loss: 0.00842 RPN total loss: 0.03095 Total loss: 0.98521 timestamp: 1655074734.7937157 iteration: 84420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09396 FastRCNN class loss: 0.06565 FastRCNN total loss: 0.15961 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.10652 RPN box loss: 0.00512 RPN score loss: 0.00153 RPN total loss: 0.00665 Total loss: 0.83519 timestamp: 1655074738.1503801 iteration: 84425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.04751 FastRCNN total loss: 0.12736 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.10965 RPN box loss: 0.01056 RPN score loss: 0.00685 RPN total loss: 0.01742 Total loss: 0.81682 timestamp: 1655074741.4550598 iteration: 84430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16247 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.21915 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12638 RPN box loss: 0.01194 RPN score loss: 0.00442 RPN total loss: 0.01636 Total loss: 0.92429 timestamp: 1655074744.7395725 iteration: 84435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12653 FastRCNN class loss: 0.07686 FastRCNN total loss: 0.20338 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.18095 RPN box loss: 0.02083 RPN score loss: 0.00758 RPN total loss: 0.02841 Total loss: 0.97515 timestamp: 1655074748.0153735 iteration: 84440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06244 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.1317 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.15191 RPN box loss: 0.0078 RPN score loss: 0.00883 RPN total loss: 0.01663 Total loss: 0.86264 timestamp: 1655074751.2529938 iteration: 84445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13332 FastRCNN class loss: 0.07824 FastRCNN total loss: 0.21156 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.17013 RPN box loss: 0.01682 RPN score loss: 0.00801 RPN total loss: 0.02484 Total loss: 0.96893 timestamp: 1655074754.5035086 iteration: 84450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07656 FastRCNN class loss: 0.07965 FastRCNN total loss: 0.15621 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14058 RPN box loss: 0.0113 RPN score loss: 0.01568 RPN total loss: 0.02697 Total loss: 0.88617 timestamp: 1655074757.8197773 iteration: 84455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10917 FastRCNN class loss: 0.05448 FastRCNN total loss: 0.16365 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.18405 RPN box loss: 0.01598 RPN score loss: 0.00884 RPN total loss: 0.02482 Total loss: 0.93492 timestamp: 1655074761.108129 iteration: 84460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13527 FastRCNN class loss: 0.08416 FastRCNN total loss: 0.21943 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.18198 RPN box loss: 0.0097 RPN score loss: 0.00523 RPN total loss: 0.01492 Total loss: 0.97873 timestamp: 1655074764.3542135 iteration: 84465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08526 FastRCNN class loss: 0.05777 FastRCNN total loss: 0.14303 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12555 RPN box loss: 0.02824 RPN score loss: 0.00906 RPN total loss: 0.0373 Total loss: 0.86828 timestamp: 1655074767.6316538 iteration: 84470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.08346 FastRCNN total loss: 0.17661 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.18118 RPN box loss: 0.00769 RPN score loss: 0.00494 RPN total loss: 0.01263 Total loss: 0.93283 timestamp: 1655074770.8888876 iteration: 84475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13367 FastRCNN class loss: 0.09389 FastRCNN total loss: 0.22756 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14758 RPN box loss: 0.0078 RPN score loss: 0.00688 RPN total loss: 0.01467 Total loss: 0.95222 timestamp: 1655074774.1034555 iteration: 84480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06398 FastRCNN class loss: 0.06968 FastRCNN total loss: 0.13366 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.17027 RPN box loss: 0.01893 RPN score loss: 0.00839 RPN total loss: 0.02732 Total loss: 0.89365 timestamp: 1655074777.3925269 iteration: 84485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0749 FastRCNN class loss: 0.03859 FastRCNN total loss: 0.11349 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.07697 RPN box loss: 0.01146 RPN score loss: 0.00252 RPN total loss: 0.01398 Total loss: 0.76684 timestamp: 1655074780.6449385 iteration: 84490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04962 FastRCNN class loss: 0.05275 FastRCNN total loss: 0.10237 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.09067 RPN box loss: 0.02132 RPN score loss: 0.00215 RPN total loss: 0.02348 Total loss: 0.77892 timestamp: 1655074783.9480028 iteration: 84495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06638 FastRCNN class loss: 0.04029 FastRCNN total loss: 0.10667 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12239 RPN box loss: 0.01619 RPN score loss: 0.00264 RPN total loss: 0.01883 Total loss: 0.81029 timestamp: 1655074787.2823439 iteration: 84500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08977 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.13993 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.10766 RPN box loss: 0.00663 RPN score loss: 0.00104 RPN total loss: 0.00768 Total loss: 0.81766 timestamp: 1655074790.5407512 iteration: 84505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09393 FastRCNN class loss: 0.09871 FastRCNN total loss: 0.19264 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.15887 RPN box loss: 0.02104 RPN score loss: 0.00396 RPN total loss: 0.025 Total loss: 0.93891 timestamp: 1655074793.8411312 iteration: 84510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12823 FastRCNN class loss: 0.07679 FastRCNN total loss: 0.20502 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.2064 RPN box loss: 0.01288 RPN score loss: 0.00262 RPN total loss: 0.0155 Total loss: 0.98932 timestamp: 1655074797.0788484 iteration: 84515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14432 FastRCNN class loss: 0.08681 FastRCNN total loss: 0.23113 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.21878 RPN box loss: 0.01133 RPN score loss: 0.00929 RPN total loss: 0.02062 Total loss: 1.03293 timestamp: 1655074800.3334177 iteration: 84520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09861 FastRCNN class loss: 0.05055 FastRCNN total loss: 0.14916 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13638 RPN box loss: 0.01317 RPN score loss: 0.00998 RPN total loss: 0.02315 Total loss: 0.8711 timestamp: 1655074803.5266483 iteration: 84525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09073 FastRCNN class loss: 0.07361 FastRCNN total loss: 0.16434 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.17414 RPN box loss: 0.0128 RPN score loss: 0.00729 RPN total loss: 0.02009 Total loss: 0.92098 timestamp: 1655074806.840209 iteration: 84530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07927 FastRCNN class loss: 0.04516 FastRCNN total loss: 0.12443 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.07323 RPN box loss: 0.00649 RPN score loss: 0.00066 RPN total loss: 0.00715 Total loss: 0.76722 timestamp: 1655074810.1310937 iteration: 84535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12034 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.19715 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13015 RPN box loss: 0.01926 RPN score loss: 0.00301 RPN total loss: 0.02226 Total loss: 0.91196 timestamp: 1655074813.3794277 iteration: 84540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08749 FastRCNN class loss: 0.09808 FastRCNN total loss: 0.18556 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.20151 RPN box loss: 0.02251 RPN score loss: 0.02354 RPN total loss: 0.04605 Total loss: 0.99552 timestamp: 1655074816.639678 iteration: 84545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06861 FastRCNN class loss: 0.06635 FastRCNN total loss: 0.13496 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.09983 RPN box loss: 0.00794 RPN score loss: 0.0041 RPN total loss: 0.01204 Total loss: 0.80923 timestamp: 1655074819.8456976 iteration: 84550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08278 FastRCNN class loss: 0.04404 FastRCNN total loss: 0.12682 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.11652 RPN box loss: 0.0044 RPN score loss: 0.00253 RPN total loss: 0.00693 Total loss: 0.81267 timestamp: 1655074823.0661795 iteration: 84555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06819 FastRCNN class loss: 0.06493 FastRCNN total loss: 0.13312 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.11726 RPN box loss: 0.0176 RPN score loss: 0.00277 RPN total loss: 0.02038 Total loss: 0.83316 timestamp: 1655074826.2927585 iteration: 84560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1694 FastRCNN class loss: 0.13331 FastRCNN total loss: 0.3027 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.25057 RPN box loss: 0.01341 RPN score loss: 0.01234 RPN total loss: 0.02575 Total loss: 1.14143 timestamp: 1655074829.5700595 iteration: 84565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04474 FastRCNN class loss: 0.08406 FastRCNN total loss: 0.1288 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.16754 RPN box loss: 0.01395 RPN score loss: 0.00571 RPN total loss: 0.01966 Total loss: 0.87839 timestamp: 1655074832.8947797 iteration: 84570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12449 FastRCNN class loss: 0.06546 FastRCNN total loss: 0.18995 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.1082 RPN box loss: 0.04143 RPN score loss: 0.00399 RPN total loss: 0.04542 Total loss: 0.90597 timestamp: 1655074836.1675544 iteration: 84575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07139 FastRCNN class loss: 0.06406 FastRCNN total loss: 0.13545 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14024 RPN box loss: 0.00457 RPN score loss: 0.0022 RPN total loss: 0.00677 Total loss: 0.84486 timestamp: 1655074839.4355435 iteration: 84580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08161 FastRCNN class loss: 0.05124 FastRCNN total loss: 0.13286 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13421 RPN box loss: 0.01674 RPN score loss: 0.00315 RPN total loss: 0.01989 Total loss: 0.84936 timestamp: 1655074842.7057564 iteration: 84585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03781 FastRCNN class loss: 0.03462 FastRCNN total loss: 0.07244 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.09771 RPN box loss: 0.00231 RPN score loss: 0.00102 RPN total loss: 0.00333 Total loss: 0.73587 timestamp: 1655074845.9973845 iteration: 84590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05404 FastRCNN class loss: 0.04028 FastRCNN total loss: 0.09431 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.08946 RPN box loss: 0.005 RPN score loss: 0.00075 RPN total loss: 0.00575 Total loss: 0.75192 timestamp: 1655074849.236636 iteration: 84595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08298 FastRCNN class loss: 0.06083 FastRCNN total loss: 0.14381 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13387 RPN box loss: 0.00968 RPN score loss: 0.00263 RPN total loss: 0.01231 Total loss: 0.85239 timestamp: 1655074852.569582 iteration: 84600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08672 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.14769 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.1276 RPN box loss: 0.00776 RPN score loss: 0.00587 RPN total loss: 0.01363 Total loss: 0.85132 timestamp: 1655074855.8907282 iteration: 84605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0658 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14496 RPN box loss: 0.00927 RPN score loss: 0.00382 RPN total loss: 0.01309 Total loss: 0.8497 timestamp: 1655074859.1871424 iteration: 84610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12745 FastRCNN class loss: 0.0725 FastRCNN total loss: 0.19995 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14171 RPN box loss: 0.00677 RPN score loss: 0.00578 RPN total loss: 0.01255 Total loss: 0.91661 timestamp: 1655074862.5031219 iteration: 84615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07869 FastRCNN class loss: 0.07444 FastRCNN total loss: 0.15312 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.15247 RPN box loss: 0.0166 RPN score loss: 0.00944 RPN total loss: 0.02604 Total loss: 0.89403 timestamp: 1655074865.7834878 iteration: 84620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10496 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.18569 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13736 RPN box loss: 0.00933 RPN score loss: 0.00483 RPN total loss: 0.01416 Total loss: 0.89961 timestamp: 1655074869.0027323 iteration: 84625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13241 FastRCNN class loss: 0.11968 FastRCNN total loss: 0.25209 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.14273 RPN box loss: 0.01937 RPN score loss: 0.00304 RPN total loss: 0.02241 Total loss: 0.97962 timestamp: 1655074872.2632096 iteration: 84630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0924 FastRCNN class loss: 0.07908 FastRCNN total loss: 0.17147 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.17983 RPN box loss: 0.0149 RPN score loss: 0.00929 RPN total loss: 0.02419 Total loss: 0.93788 timestamp: 1655074875.5204449 iteration: 84635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06976 FastRCNN class loss: 0.04924 FastRCNN total loss: 0.119 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.16003 RPN box loss: 0.01431 RPN score loss: 0.00839 RPN total loss: 0.0227 Total loss: 0.86413 timestamp: 1655074878.741071 iteration: 84640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08517 FastRCNN class loss: 0.06501 FastRCNN total loss: 0.15018 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13672 RPN box loss: 0.01356 RPN score loss: 0.00619 RPN total loss: 0.01975 Total loss: 0.86905 timestamp: 1655074882.0241954 iteration: 84645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11678 FastRCNN class loss: 0.08664 FastRCNN total loss: 0.20342 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12361 RPN box loss: 0.0226 RPN score loss: 0.00331 RPN total loss: 0.02592 Total loss: 0.91534 timestamp: 1655074885.292495 iteration: 84650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08552 FastRCNN class loss: 0.06169 FastRCNN total loss: 0.14722 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12171 RPN box loss: 0.0066 RPN score loss: 0.00583 RPN total loss: 0.01242 Total loss: 0.84374 timestamp: 1655074888.5851243 iteration: 84655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04218 FastRCNN class loss: 0.03932 FastRCNN total loss: 0.0815 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.12806 RPN box loss: 0.01214 RPN score loss: 0.00153 RPN total loss: 0.01367 Total loss: 0.78563 timestamp: 1655074891.8627703 iteration: 84660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10347 FastRCNN class loss: 0.09447 FastRCNN total loss: 0.19793 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.10636 RPN box loss: 0.01217 RPN score loss: 0.00414 RPN total loss: 0.01631 Total loss: 0.88299 timestamp: 1655074895.2369375 iteration: 84665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13557 FastRCNN class loss: 0.14704 FastRCNN total loss: 0.28262 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.1734 RPN box loss: 0.01941 RPN score loss: 0.00774 RPN total loss: 0.02715 Total loss: 1.04556 timestamp: 1655074898.5265195 iteration: 84670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05142 FastRCNN class loss: 0.02984 FastRCNN total loss: 0.08125 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.09242 RPN box loss: 0.00365 RPN score loss: 0.00039 RPN total loss: 0.00404 Total loss: 0.74011 timestamp: 1655074901.8039405 iteration: 84675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08302 FastRCNN class loss: 0.0835 FastRCNN total loss: 0.16652 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.13397 RPN box loss: 0.01228 RPN score loss: 0.00748 RPN total loss: 0.01976 Total loss: 0.88264 timestamp: 1655074905.0833728 iteration: 84680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15676 FastRCNN class loss: 0.08326 FastRCNN total loss: 0.24002 L1 loss: 0.0000e+00 L2 loss: 0.5624 Learning rate: 4.0000e-05 Mask loss: 0.15799 RPN box loss: 0.01957 RPN score loss: 0.00978 RPN total loss: 0.02935 Total loss: 0.98976 timestamp: 1655074908.412018 iteration: 84685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10698 FastRCNN class loss: 0.08627 FastRCNN total loss: 0.19325 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.17238 RPN box loss: 0.01238 RPN score loss: 0.00868 RPN total loss: 0.02106 Total loss: 0.94908 timestamp: 1655074911.6689906 iteration: 84690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06114 FastRCNN class loss: 0.05908 FastRCNN total loss: 0.12022 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13521 RPN box loss: 0.02658 RPN score loss: 0.0029 RPN total loss: 0.02948 Total loss: 0.8473 timestamp: 1655074914.9712577 iteration: 84695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11751 FastRCNN class loss: 0.1099 FastRCNN total loss: 0.22741 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.1534 RPN box loss: 0.0067 RPN score loss: 0.00713 RPN total loss: 0.01384 Total loss: 0.95704 timestamp: 1655074918.3021007 iteration: 84700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16804 FastRCNN class loss: 0.10674 FastRCNN total loss: 0.27477 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.18844 RPN box loss: 0.01696 RPN score loss: 0.01221 RPN total loss: 0.02917 Total loss: 1.05478 timestamp: 1655074921.5568266 iteration: 84705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04835 FastRCNN class loss: 0.04431 FastRCNN total loss: 0.09266 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.11621 RPN box loss: 0.00742 RPN score loss: 0.00774 RPN total loss: 0.01516 Total loss: 0.78642 timestamp: 1655074924.8214731 iteration: 84710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10436 FastRCNN class loss: 0.08829 FastRCNN total loss: 0.19265 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13873 RPN box loss: 0.02718 RPN score loss: 0.01333 RPN total loss: 0.04052 Total loss: 0.93429 timestamp: 1655074928.170609 iteration: 84715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08512 FastRCNN class loss: 0.04239 FastRCNN total loss: 0.12752 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13156 RPN box loss: 0.01755 RPN score loss: 0.00156 RPN total loss: 0.01911 Total loss: 0.84058 timestamp: 1655074931.5023966 iteration: 84720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06811 FastRCNN class loss: 0.05156 FastRCNN total loss: 0.11967 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.11735 RPN box loss: 0.02018 RPN score loss: 0.0056 RPN total loss: 0.02578 Total loss: 0.82519 timestamp: 1655074934.842227 iteration: 84725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11068 FastRCNN class loss: 0.06233 FastRCNN total loss: 0.17301 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13075 RPN box loss: 0.01763 RPN score loss: 0.00344 RPN total loss: 0.02107 Total loss: 0.88723 timestamp: 1655074938.179109 iteration: 84730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12782 FastRCNN class loss: 0.10782 FastRCNN total loss: 0.23564 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.16326 RPN box loss: 0.01423 RPN score loss: 0.00815 RPN total loss: 0.02239 Total loss: 0.98368 timestamp: 1655074941.4358926 iteration: 84735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.04284 FastRCNN total loss: 0.09949 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.15558 RPN box loss: 0.00943 RPN score loss: 0.00221 RPN total loss: 0.01164 Total loss: 0.8291 timestamp: 1655074944.7151253 iteration: 84740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11057 FastRCNN class loss: 0.09688 FastRCNN total loss: 0.20745 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12853 RPN box loss: 0.01601 RPN score loss: 0.00274 RPN total loss: 0.01875 Total loss: 0.91713 timestamp: 1655074948.019424 iteration: 84745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07999 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.1461 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14109 RPN box loss: 0.01513 RPN score loss: 0.00763 RPN total loss: 0.02276 Total loss: 0.87235 timestamp: 1655074951.2867186 iteration: 84750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13279 FastRCNN class loss: 0.06989 FastRCNN total loss: 0.20268 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.10833 RPN box loss: 0.01746 RPN score loss: 0.00509 RPN total loss: 0.02255 Total loss: 0.89596 timestamp: 1655074954.5694451 iteration: 84755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06164 FastRCNN class loss: 0.06761 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.16305 RPN box loss: 0.02072 RPN score loss: 0.01452 RPN total loss: 0.03524 Total loss: 0.88994 timestamp: 1655074957.8127716 iteration: 84760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.07218 FastRCNN total loss: 0.16179 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.20422 RPN box loss: 0.02115 RPN score loss: 0.00321 RPN total loss: 0.02435 Total loss: 0.95276 timestamp: 1655074961.056248 iteration: 84765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04429 FastRCNN class loss: 0.04067 FastRCNN total loss: 0.08496 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.10151 RPN box loss: 0.01357 RPN score loss: 0.00361 RPN total loss: 0.01718 Total loss: 0.76605 timestamp: 1655074964.3499756 iteration: 84770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11466 FastRCNN class loss: 0.11118 FastRCNN total loss: 0.22583 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.20811 RPN box loss: 0.02082 RPN score loss: 0.00836 RPN total loss: 0.02918 Total loss: 1.02552 timestamp: 1655074967.6690617 iteration: 84775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09368 FastRCNN class loss: 0.04934 FastRCNN total loss: 0.14303 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.22608 RPN box loss: 0.03325 RPN score loss: 0.00657 RPN total loss: 0.03982 Total loss: 0.97132 timestamp: 1655074970.945004 iteration: 84780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06806 FastRCNN class loss: 0.058 FastRCNN total loss: 0.12606 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.128 RPN box loss: 0.01282 RPN score loss: 0.0103 RPN total loss: 0.02312 Total loss: 0.83957 timestamp: 1655074974.2288318 iteration: 84785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08166 FastRCNN class loss: 0.05841 FastRCNN total loss: 0.14007 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14349 RPN box loss: 0.01703 RPN score loss: 0.00403 RPN total loss: 0.02106 Total loss: 0.86701 timestamp: 1655074977.555392 iteration: 84790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06957 FastRCNN class loss: 0.05435 FastRCNN total loss: 0.12391 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.15118 RPN box loss: 0.00687 RPN score loss: 0.00275 RPN total loss: 0.00962 Total loss: 0.8471 timestamp: 1655074980.8022678 iteration: 84795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07433 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.14036 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.19828 RPN box loss: 0.01344 RPN score loss: 0.00382 RPN total loss: 0.01726 Total loss: 0.91828 timestamp: 1655074984.0201037 iteration: 84800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10816 FastRCNN class loss: 0.07083 FastRCNN total loss: 0.17898 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.15714 RPN box loss: 0.01303 RPN score loss: 0.0048 RPN total loss: 0.01782 Total loss: 0.91634 timestamp: 1655074987.3082683 iteration: 84805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09315 FastRCNN class loss: 0.07917 FastRCNN total loss: 0.17232 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14571 RPN box loss: 0.01883 RPN score loss: 0.00414 RPN total loss: 0.02297 Total loss: 0.90339 timestamp: 1655074990.6910636 iteration: 84810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11808 FastRCNN class loss: 0.07252 FastRCNN total loss: 0.1906 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12325 RPN box loss: 0.01091 RPN score loss: 0.0028 RPN total loss: 0.01371 Total loss: 0.88994 timestamp: 1655074994.0314133 iteration: 84815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04204 FastRCNN class loss: 0.04502 FastRCNN total loss: 0.08705 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12494 RPN box loss: 0.00404 RPN score loss: 0.00609 RPN total loss: 0.01013 Total loss: 0.78452 timestamp: 1655074997.3271315 iteration: 84820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03968 FastRCNN class loss: 0.04257 FastRCNN total loss: 0.08225 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.09662 RPN box loss: 0.00919 RPN score loss: 0.00584 RPN total loss: 0.01503 Total loss: 0.75628 timestamp: 1655075000.5530186 iteration: 84825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14034 FastRCNN class loss: 0.09836 FastRCNN total loss: 0.2387 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.2328 RPN box loss: 0.01081 RPN score loss: 0.01077 RPN total loss: 0.02158 Total loss: 1.05547 timestamp: 1655075003.828147 iteration: 84830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09987 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.14809 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.11527 RPN box loss: 0.0137 RPN score loss: 0.00268 RPN total loss: 0.01639 Total loss: 0.84213 timestamp: 1655075007.0588255 iteration: 84835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10033 FastRCNN class loss: 0.08381 FastRCNN total loss: 0.18414 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14229 RPN box loss: 0.02674 RPN score loss: 0.00424 RPN total loss: 0.03098 Total loss: 0.91979 timestamp: 1655075010.2733998 iteration: 84840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06947 FastRCNN class loss: 0.03935 FastRCNN total loss: 0.10882 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.1108 RPN box loss: 0.01188 RPN score loss: 0.00109 RPN total loss: 0.01298 Total loss: 0.79498 timestamp: 1655075013.499819 iteration: 84845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07649 FastRCNN class loss: 0.03638 FastRCNN total loss: 0.11287 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12549 RPN box loss: 0.00468 RPN score loss: 0.00209 RPN total loss: 0.00677 Total loss: 0.80752 timestamp: 1655075016.7357175 iteration: 84850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09537 FastRCNN class loss: 0.06606 FastRCNN total loss: 0.16142 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13482 RPN box loss: 0.00561 RPN score loss: 0.00731 RPN total loss: 0.01292 Total loss: 0.87155 timestamp: 1655075019.9817417 iteration: 84855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05674 FastRCNN class loss: 0.0417 FastRCNN total loss: 0.09845 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14772 RPN box loss: 0.0107 RPN score loss: 0.00515 RPN total loss: 0.01586 Total loss: 0.82441 timestamp: 1655075023.2166536 iteration: 84860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10222 FastRCNN class loss: 0.08562 FastRCNN total loss: 0.18783 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13268 RPN box loss: 0.01494 RPN score loss: 0.00524 RPN total loss: 0.02018 Total loss: 0.90308 timestamp: 1655075026.5137227 iteration: 84865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14116 FastRCNN class loss: 0.07609 FastRCNN total loss: 0.21724 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.19642 RPN box loss: 0.01053 RPN score loss: 0.00956 RPN total loss: 0.02009 Total loss: 0.99614 timestamp: 1655075029.81832 iteration: 84870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06116 FastRCNN class loss: 0.05505 FastRCNN total loss: 0.11621 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.09988 RPN box loss: 0.01363 RPN score loss: 0.00467 RPN total loss: 0.0183 Total loss: 0.79678 timestamp: 1655075033.1571536 iteration: 84875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11452 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.18663 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.16521 RPN box loss: 0.02152 RPN score loss: 0.0053 RPN total loss: 0.02682 Total loss: 0.94105 timestamp: 1655075036.4618187 iteration: 84880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0962 FastRCNN class loss: 0.09796 FastRCNN total loss: 0.19416 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.18381 RPN box loss: 0.012 RPN score loss: 0.00776 RPN total loss: 0.01976 Total loss: 0.96012 timestamp: 1655075039.7028515 iteration: 84885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11682 FastRCNN class loss: 0.07953 FastRCNN total loss: 0.19635 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.11969 RPN box loss: 0.03174 RPN score loss: 0.00346 RPN total loss: 0.0352 Total loss: 0.91363 timestamp: 1655075042.9700081 iteration: 84890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08159 FastRCNN class loss: 0.0483 FastRCNN total loss: 0.12989 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.08538 RPN box loss: 0.00763 RPN score loss: 0.00102 RPN total loss: 0.00864 Total loss: 0.7863 timestamp: 1655075046.1990325 iteration: 84895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09489 FastRCNN class loss: 0.05759 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14671 RPN box loss: 0.00413 RPN score loss: 0.00503 RPN total loss: 0.00916 Total loss: 0.87073 timestamp: 1655075049.588873 iteration: 84900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14325 FastRCNN class loss: 0.07494 FastRCNN total loss: 0.21818 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14157 RPN box loss: 0.00858 RPN score loss: 0.00286 RPN total loss: 0.01144 Total loss: 0.93358 timestamp: 1655075052.9079533 iteration: 84905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09339 FastRCNN class loss: 0.06748 FastRCNN total loss: 0.16087 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.11557 RPN box loss: 0.00541 RPN score loss: 0.00349 RPN total loss: 0.0089 Total loss: 0.84774 timestamp: 1655075056.2241316 iteration: 84910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06272 FastRCNN class loss: 0.03717 FastRCNN total loss: 0.09989 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.10562 RPN box loss: 0.01314 RPN score loss: 0.00099 RPN total loss: 0.01413 Total loss: 0.78202 timestamp: 1655075059.5528853 iteration: 84915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08602 FastRCNN class loss: 0.07406 FastRCNN total loss: 0.16008 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.16515 RPN box loss: 0.00933 RPN score loss: 0.00759 RPN total loss: 0.01692 Total loss: 0.90453 timestamp: 1655075062.8131948 iteration: 84920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05591 FastRCNN class loss: 0.03245 FastRCNN total loss: 0.08836 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12114 RPN box loss: 0.00482 RPN score loss: 0.00086 RPN total loss: 0.00567 Total loss: 0.77757 timestamp: 1655075066.0395043 iteration: 84925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1048 FastRCNN class loss: 0.04198 FastRCNN total loss: 0.14678 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.10071 RPN box loss: 0.00882 RPN score loss: 0.00398 RPN total loss: 0.0128 Total loss: 0.82267 timestamp: 1655075069.3278825 iteration: 84930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07277 FastRCNN class loss: 0.05776 FastRCNN total loss: 0.13054 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13089 RPN box loss: 0.01463 RPN score loss: 0.01059 RPN total loss: 0.02522 Total loss: 0.84903 timestamp: 1655075072.569351 iteration: 84935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05063 FastRCNN class loss: 0.05225 FastRCNN total loss: 0.10288 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.13358 RPN box loss: 0.01499 RPN score loss: 0.00709 RPN total loss: 0.02208 Total loss: 0.82093 timestamp: 1655075075.9394565 iteration: 84940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12144 FastRCNN class loss: 0.03885 FastRCNN total loss: 0.16029 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14079 RPN box loss: 0.01036 RPN score loss: 0.00432 RPN total loss: 0.01468 Total loss: 0.87814 timestamp: 1655075079.24577 iteration: 84945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07891 FastRCNN class loss: 0.09063 FastRCNN total loss: 0.16954 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.15722 RPN box loss: 0.0192 RPN score loss: 0.00838 RPN total loss: 0.02759 Total loss: 0.91674 timestamp: 1655075082.5654323 iteration: 84950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16555 FastRCNN class loss: 0.18298 FastRCNN total loss: 0.34853 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.21125 RPN box loss: 0.03289 RPN score loss: 0.01062 RPN total loss: 0.04352 Total loss: 1.16568 timestamp: 1655075085.8199317 iteration: 84955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15771 FastRCNN class loss: 0.04425 FastRCNN total loss: 0.20196 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14043 RPN box loss: 0.00997 RPN score loss: 0.00167 RPN total loss: 0.01164 Total loss: 0.91642 timestamp: 1655075089.1005673 iteration: 84960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07352 FastRCNN class loss: 0.05869 FastRCNN total loss: 0.13221 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.14335 RPN box loss: 0.02855 RPN score loss: 0.00157 RPN total loss: 0.03012 Total loss: 0.86806 timestamp: 1655075092.5088708 iteration: 84965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07409 FastRCNN class loss: 0.04121 FastRCNN total loss: 0.1153 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.17673 RPN box loss: 0.00713 RPN score loss: 0.00235 RPN total loss: 0.00948 Total loss: 0.8639 timestamp: 1655075095.7674966 iteration: 84970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1026 FastRCNN class loss: 0.09697 FastRCNN total loss: 0.19957 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.12788 RPN box loss: 0.00909 RPN score loss: 0.00477 RPN total loss: 0.01386 Total loss: 0.9037 timestamp: 1655075099.0055792 iteration: 84975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11242 FastRCNN class loss: 0.07595 FastRCNN total loss: 0.18837 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.19879 RPN box loss: 0.01148 RPN score loss: 0.00972 RPN total loss: 0.0212 Total loss: 0.97075 timestamp: 1655075102.3111148 iteration: 84980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08522 FastRCNN class loss: 0.09985 FastRCNN total loss: 0.18507 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.18118 RPN box loss: 0.014 RPN score loss: 0.00687 RPN total loss: 0.02087 Total loss: 0.9495 timestamp: 1655075105.6484745 iteration: 84985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07587 FastRCNN class loss: 0.07421 FastRCNN total loss: 0.15007 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.1347 RPN box loss: 0.01073 RPN score loss: 0.00707 RPN total loss: 0.01781 Total loss: 0.86496 timestamp: 1655075108.9316432 iteration: 84990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12448 FastRCNN class loss: 0.09372 FastRCNN total loss: 0.2182 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.15138 RPN box loss: 0.01319 RPN score loss: 0.0042 RPN total loss: 0.0174 Total loss: 0.94936 timestamp: 1655075112.288273 iteration: 84995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0814 FastRCNN class loss: 0.08245 FastRCNN total loss: 0.16385 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.18731 RPN box loss: 0.00757 RPN score loss: 0.0021 RPN total loss: 0.00967 Total loss: 0.92322 timestamp: 1655075115.5652046 iteration: 85000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07095 FastRCNN class loss: 0.06463 FastRCNN total loss: 0.13558 L1 loss: 0.0000e+00 L2 loss: 0.56239 Learning rate: 4.0000e-05 Mask loss: 0.1634 RPN box loss: 0.01384 RPN score loss: 0.0047 RPN total loss: 0.01855 Total loss: 0.87991 timestamp: 1655075118.855526 iteration: 85005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13605 FastRCNN class loss: 0.10661 FastRCNN total loss: 0.24267 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.16029 RPN box loss: 0.01545 RPN score loss: 0.02754 RPN total loss: 0.04299 Total loss: 1.00833 timestamp: 1655075122.0741644 iteration: 85010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07877 FastRCNN class loss: 0.06152 FastRCNN total loss: 0.14029 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15462 RPN box loss: 0.01363 RPN score loss: 0.00277 RPN total loss: 0.0164 Total loss: 0.8737 timestamp: 1655075125.346566 iteration: 85015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10557 FastRCNN class loss: 0.13499 FastRCNN total loss: 0.24056 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.19362 RPN box loss: 0.06722 RPN score loss: 0.01295 RPN total loss: 0.08017 Total loss: 1.07674 timestamp: 1655075128.5175211 iteration: 85020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07854 FastRCNN class loss: 0.05858 FastRCNN total loss: 0.13712 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.08055 RPN box loss: 0.00627 RPN score loss: 0.00363 RPN total loss: 0.0099 Total loss: 0.78996 timestamp: 1655075131.8223972 iteration: 85025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12522 FastRCNN class loss: 0.09072 FastRCNN total loss: 0.21595 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.18766 RPN box loss: 0.0186 RPN score loss: 0.01786 RPN total loss: 0.03646 Total loss: 1.00245 timestamp: 1655075135.1087654 iteration: 85030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09661 FastRCNN class loss: 0.03838 FastRCNN total loss: 0.13499 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.10895 RPN box loss: 0.00423 RPN score loss: 0.00405 RPN total loss: 0.00828 Total loss: 0.8146 timestamp: 1655075138.4063182 iteration: 85035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06467 FastRCNN class loss: 0.04716 FastRCNN total loss: 0.11183 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13623 RPN box loss: 0.0213 RPN score loss: 0.00457 RPN total loss: 0.02587 Total loss: 0.83632 timestamp: 1655075141.674755 iteration: 85040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09874 FastRCNN class loss: 0.114 FastRCNN total loss: 0.21274 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.20287 RPN box loss: 0.01562 RPN score loss: 0.00814 RPN total loss: 0.02376 Total loss: 1.00175 timestamp: 1655075144.9516656 iteration: 85045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0717 FastRCNN class loss: 0.04008 FastRCNN total loss: 0.11178 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.07093 RPN box loss: 0.01038 RPN score loss: 0.0014 RPN total loss: 0.01179 Total loss: 0.75688 timestamp: 1655075148.232411 iteration: 85050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05776 FastRCNN class loss: 0.04928 FastRCNN total loss: 0.10705 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13919 RPN box loss: 0.00592 RPN score loss: 0.00195 RPN total loss: 0.00787 Total loss: 0.81649 timestamp: 1655075151.5026317 iteration: 85055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09042 FastRCNN class loss: 0.0611 FastRCNN total loss: 0.15152 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11993 RPN box loss: 0.01052 RPN score loss: 0.00128 RPN total loss: 0.0118 Total loss: 0.84563 timestamp: 1655075154.75767 iteration: 85060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10099 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.17697 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13294 RPN box loss: 0.01096 RPN score loss: 0.00811 RPN total loss: 0.01907 Total loss: 0.89137 timestamp: 1655075157.9555228 iteration: 85065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09924 FastRCNN class loss: 0.07774 FastRCNN total loss: 0.17698 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13915 RPN box loss: 0.02077 RPN score loss: 0.01058 RPN total loss: 0.03134 Total loss: 0.90986 timestamp: 1655075161.2363465 iteration: 85070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12025 FastRCNN class loss: 0.08547 FastRCNN total loss: 0.20572 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13138 RPN box loss: 0.03566 RPN score loss: 0.00347 RPN total loss: 0.03913 Total loss: 0.93861 timestamp: 1655075164.5563931 iteration: 85075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.089 FastRCNN class loss: 0.09522 FastRCNN total loss: 0.18423 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12834 RPN box loss: 0.00917 RPN score loss: 0.00094 RPN total loss: 0.01011 Total loss: 0.88506 timestamp: 1655075167.8283622 iteration: 85080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0933 FastRCNN class loss: 0.05549 FastRCNN total loss: 0.14879 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12417 RPN box loss: 0.01187 RPN score loss: 0.00637 RPN total loss: 0.01824 Total loss: 0.85359 timestamp: 1655075171.080458 iteration: 85085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06355 FastRCNN class loss: 0.07319 FastRCNN total loss: 0.13674 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13258 RPN box loss: 0.01305 RPN score loss: 0.00551 RPN total loss: 0.01855 Total loss: 0.85025 timestamp: 1655075174.3728127 iteration: 85090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08057 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.13363 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14943 RPN box loss: 0.01197 RPN score loss: 0.0006 RPN total loss: 0.01257 Total loss: 0.85801 timestamp: 1655075177.6434 iteration: 85095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12053 FastRCNN class loss: 0.07277 FastRCNN total loss: 0.1933 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12901 RPN box loss: 0.02748 RPN score loss: 0.01053 RPN total loss: 0.03801 Total loss: 0.9227 timestamp: 1655075180.9146082 iteration: 85100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07076 FastRCNN class loss: 0.04691 FastRCNN total loss: 0.11767 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.08062 RPN box loss: 0.01043 RPN score loss: 0.01127 RPN total loss: 0.0217 Total loss: 0.78237 timestamp: 1655075184.2319899 iteration: 85105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07181 FastRCNN class loss: 0.04394 FastRCNN total loss: 0.11576 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.09971 RPN box loss: 0.00671 RPN score loss: 0.00196 RPN total loss: 0.00867 Total loss: 0.78652 timestamp: 1655075187.5063043 iteration: 85110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08684 FastRCNN class loss: 0.07414 FastRCNN total loss: 0.16099 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15763 RPN box loss: 0.02154 RPN score loss: 0.00521 RPN total loss: 0.02675 Total loss: 0.90775 timestamp: 1655075190.7757947 iteration: 85115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15058 FastRCNN class loss: 0.09182 FastRCNN total loss: 0.2424 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.16357 RPN box loss: 0.01347 RPN score loss: 0.01509 RPN total loss: 0.02856 Total loss: 0.99692 timestamp: 1655075194.08305 iteration: 85120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09903 FastRCNN class loss: 0.055 FastRCNN total loss: 0.15403 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.187 RPN box loss: 0.00457 RPN score loss: 0.00517 RPN total loss: 0.00974 Total loss: 0.91315 timestamp: 1655075197.3292577 iteration: 85125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03498 FastRCNN class loss: 0.0503 FastRCNN total loss: 0.08528 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11293 RPN box loss: 0.007 RPN score loss: 0.00325 RPN total loss: 0.01025 Total loss: 0.77084 timestamp: 1655075200.626736 iteration: 85130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04841 FastRCNN class loss: 0.06399 FastRCNN total loss: 0.1124 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12263 RPN box loss: 0.01012 RPN score loss: 0.00583 RPN total loss: 0.01595 Total loss: 0.81336 timestamp: 1655075203.8614888 iteration: 85135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0627 FastRCNN class loss: 0.06312 FastRCNN total loss: 0.12583 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13788 RPN box loss: 0.0073 RPN score loss: 0.00403 RPN total loss: 0.01133 Total loss: 0.83741 timestamp: 1655075207.17145 iteration: 85140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10102 FastRCNN class loss: 0.05778 FastRCNN total loss: 0.1588 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.09774 RPN box loss: 0.00542 RPN score loss: 0.00281 RPN total loss: 0.00824 Total loss: 0.82716 timestamp: 1655075210.3937 iteration: 85145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07899 FastRCNN class loss: 0.06316 FastRCNN total loss: 0.14215 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12689 RPN box loss: 0.00852 RPN score loss: 0.00538 RPN total loss: 0.0139 Total loss: 0.84532 timestamp: 1655075213.6585698 iteration: 85150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08112 FastRCNN class loss: 0.07445 FastRCNN total loss: 0.15556 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.17668 RPN box loss: 0.01297 RPN score loss: 0.00351 RPN total loss: 0.01649 Total loss: 0.91111 timestamp: 1655075217.0137148 iteration: 85155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07649 FastRCNN class loss: 0.05497 FastRCNN total loss: 0.13147 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.08736 RPN box loss: 0.00451 RPN score loss: 0.00524 RPN total loss: 0.00975 Total loss: 0.79095 timestamp: 1655075220.265067 iteration: 85160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10051 FastRCNN class loss: 0.0847 FastRCNN total loss: 0.18521 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.10945 RPN box loss: 0.02092 RPN score loss: 0.00229 RPN total loss: 0.02321 Total loss: 0.88025 timestamp: 1655075223.549335 iteration: 85165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09362 FastRCNN class loss: 0.05268 FastRCNN total loss: 0.1463 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14145 RPN box loss: 0.00336 RPN score loss: 0.00445 RPN total loss: 0.00781 Total loss: 0.85794 timestamp: 1655075226.8335605 iteration: 85170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13571 FastRCNN class loss: 0.10337 FastRCNN total loss: 0.23908 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.20747 RPN box loss: 0.0148 RPN score loss: 0.00623 RPN total loss: 0.02103 Total loss: 1.02996 timestamp: 1655075230.1437056 iteration: 85175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10957 FastRCNN class loss: 0.08007 FastRCNN total loss: 0.18964 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.10594 RPN box loss: 0.01434 RPN score loss: 0.00589 RPN total loss: 0.02023 Total loss: 0.87818 timestamp: 1655075233.4274814 iteration: 85180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12905 FastRCNN class loss: 0.12102 FastRCNN total loss: 0.25006 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.17779 RPN box loss: 0.00831 RPN score loss: 0.00391 RPN total loss: 0.01222 Total loss: 1.00245 timestamp: 1655075236.6934042 iteration: 85185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11106 FastRCNN class loss: 0.07182 FastRCNN total loss: 0.18288 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.16588 RPN box loss: 0.00587 RPN score loss: 0.00238 RPN total loss: 0.00825 Total loss: 0.91939 timestamp: 1655075240.0211608 iteration: 85190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08803 FastRCNN class loss: 0.05935 FastRCNN total loss: 0.14738 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14768 RPN box loss: 0.00685 RPN score loss: 0.00118 RPN total loss: 0.00803 Total loss: 0.86546 timestamp: 1655075243.2764819 iteration: 85195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15035 FastRCNN class loss: 0.07493 FastRCNN total loss: 0.22528 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.1181 RPN box loss: 0.05379 RPN score loss: 0.00936 RPN total loss: 0.06314 Total loss: 0.96891 timestamp: 1655075246.593849 iteration: 85200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14677 FastRCNN class loss: 0.07442 FastRCNN total loss: 0.22119 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15326 RPN box loss: 0.0183 RPN score loss: 0.00382 RPN total loss: 0.02212 Total loss: 0.95894 timestamp: 1655075249.9057717 iteration: 85205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08197 FastRCNN class loss: 0.06689 FastRCNN total loss: 0.14886 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14993 RPN box loss: 0.00663 RPN score loss: 0.00223 RPN total loss: 0.00886 Total loss: 0.87002 timestamp: 1655075253.1452227 iteration: 85210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11445 FastRCNN class loss: 0.07728 FastRCNN total loss: 0.19174 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14871 RPN box loss: 0.01939 RPN score loss: 0.01302 RPN total loss: 0.0324 Total loss: 0.93523 timestamp: 1655075256.4530241 iteration: 85215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13385 FastRCNN class loss: 0.05996 FastRCNN total loss: 0.19381 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13832 RPN box loss: 0.00977 RPN score loss: 0.01009 RPN total loss: 0.01985 Total loss: 0.91436 timestamp: 1655075259.7289305 iteration: 85220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14188 FastRCNN class loss: 0.09216 FastRCNN total loss: 0.23403 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.10546 RPN box loss: 0.00944 RPN score loss: 0.00957 RPN total loss: 0.01902 Total loss: 0.92089 timestamp: 1655075262.973932 iteration: 85225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15463 FastRCNN class loss: 0.13132 FastRCNN total loss: 0.28595 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.21275 RPN box loss: 0.01405 RPN score loss: 0.01323 RPN total loss: 0.02729 Total loss: 1.08837 timestamp: 1655075266.1835108 iteration: 85230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05645 FastRCNN class loss: 0.05802 FastRCNN total loss: 0.11447 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.20443 RPN box loss: 0.01213 RPN score loss: 0.00735 RPN total loss: 0.01948 Total loss: 0.90077 timestamp: 1655075269.5430756 iteration: 85235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08896 FastRCNN class loss: 0.05874 FastRCNN total loss: 0.1477 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11477 RPN box loss: 0.0062 RPN score loss: 0.00685 RPN total loss: 0.01305 Total loss: 0.83791 timestamp: 1655075272.8732293 iteration: 85240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07763 FastRCNN class loss: 0.07495 FastRCNN total loss: 0.15258 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13127 RPN box loss: 0.01358 RPN score loss: 0.00763 RPN total loss: 0.02121 Total loss: 0.86744 timestamp: 1655075276.16893 iteration: 85245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07423 FastRCNN class loss: 0.05648 FastRCNN total loss: 0.13071 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12368 RPN box loss: 0.01496 RPN score loss: 0.00408 RPN total loss: 0.01904 Total loss: 0.83581 timestamp: 1655075279.493471 iteration: 85250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10249 FastRCNN class loss: 0.06414 FastRCNN total loss: 0.16664 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14957 RPN box loss: 0.01123 RPN score loss: 0.00485 RPN total loss: 0.01608 Total loss: 0.89467 timestamp: 1655075282.828275 iteration: 85255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16193 FastRCNN class loss: 0.07218 FastRCNN total loss: 0.23411 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11764 RPN box loss: 0.00463 RPN score loss: 0.00298 RPN total loss: 0.00761 Total loss: 0.92174 timestamp: 1655075286.0835607 iteration: 85260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06662 FastRCNN class loss: 0.05701 FastRCNN total loss: 0.12363 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14347 RPN box loss: 0.00927 RPN score loss: 0.00692 RPN total loss: 0.01618 Total loss: 0.84567 timestamp: 1655075289.3953044 iteration: 85265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06232 FastRCNN class loss: 0.04461 FastRCNN total loss: 0.10693 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.0579 RPN box loss: 0.0031 RPN score loss: 0.00188 RPN total loss: 0.00497 Total loss: 0.73219 timestamp: 1655075292.6547236 iteration: 85270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07878 FastRCNN class loss: 0.0629 FastRCNN total loss: 0.14168 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15195 RPN box loss: 0.02994 RPN score loss: 0.00203 RPN total loss: 0.03197 Total loss: 0.88798 timestamp: 1655075295.9970708 iteration: 85275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0934 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.16376 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.13316 RPN box loss: 0.01233 RPN score loss: 0.00553 RPN total loss: 0.01787 Total loss: 0.87715 timestamp: 1655075299.3070958 iteration: 85280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08581 FastRCNN class loss: 0.08681 FastRCNN total loss: 0.17262 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.1052 RPN box loss: 0.01837 RPN score loss: 0.01046 RPN total loss: 0.02884 Total loss: 0.86903 timestamp: 1655075302.559859 iteration: 85285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12082 FastRCNN class loss: 0.0713 FastRCNN total loss: 0.19212 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.12183 RPN box loss: 0.005 RPN score loss: 0.0015 RPN total loss: 0.0065 Total loss: 0.88283 timestamp: 1655075305.799282 iteration: 85290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09814 FastRCNN class loss: 0.05179 FastRCNN total loss: 0.14992 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.09202 RPN box loss: 0.01183 RPN score loss: 0.00338 RPN total loss: 0.01522 Total loss: 0.81954 timestamp: 1655075309.0327315 iteration: 85295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10584 FastRCNN class loss: 0.07393 FastRCNN total loss: 0.17977 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.16661 RPN box loss: 0.00929 RPN score loss: 0.00458 RPN total loss: 0.01387 Total loss: 0.92263 timestamp: 1655075312.3756607 iteration: 85300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07403 FastRCNN class loss: 0.04822 FastRCNN total loss: 0.12225 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.1612 RPN box loss: 0.00983 RPN score loss: 0.00832 RPN total loss: 0.01814 Total loss: 0.86396 timestamp: 1655075315.675342 iteration: 85305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06582 FastRCNN class loss: 0.07469 FastRCNN total loss: 0.14051 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.19108 RPN box loss: 0.01772 RPN score loss: 0.00782 RPN total loss: 0.02553 Total loss: 0.9195 timestamp: 1655075318.9113045 iteration: 85310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04415 FastRCNN class loss: 0.03738 FastRCNN total loss: 0.08153 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.10217 RPN box loss: 0.00309 RPN score loss: 0.00024 RPN total loss: 0.00333 Total loss: 0.74941 timestamp: 1655075322.194805 iteration: 85315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06626 FastRCNN class loss: 0.05143 FastRCNN total loss: 0.11769 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15965 RPN box loss: 0.01425 RPN score loss: 0.00181 RPN total loss: 0.01606 Total loss: 0.85577 timestamp: 1655075325.417468 iteration: 85320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06217 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.13034 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14303 RPN box loss: 0.01675 RPN score loss: 0.004 RPN total loss: 0.02075 Total loss: 0.85648 timestamp: 1655075328.6855063 iteration: 85325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09687 FastRCNN class loss: 0.06242 FastRCNN total loss: 0.15929 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.1431 RPN box loss: 0.00729 RPN score loss: 0.0098 RPN total loss: 0.01708 Total loss: 0.88185 timestamp: 1655075332.0221326 iteration: 85330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14902 FastRCNN class loss: 0.10511 FastRCNN total loss: 0.25412 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.15271 RPN box loss: 0.013 RPN score loss: 0.00688 RPN total loss: 0.01988 Total loss: 0.98909 timestamp: 1655075335.2401652 iteration: 85335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05992 FastRCNN class loss: 0.06135 FastRCNN total loss: 0.12127 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11369 RPN box loss: 0.01059 RPN score loss: 0.0032 RPN total loss: 0.01379 Total loss: 0.81112 timestamp: 1655075338.5332935 iteration: 85340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08127 FastRCNN class loss: 0.06101 FastRCNN total loss: 0.14229 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.11671 RPN box loss: 0.03347 RPN score loss: 0.00587 RPN total loss: 0.03934 Total loss: 0.86071 timestamp: 1655075341.7390084 iteration: 85345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05085 FastRCNN class loss: 0.05052 FastRCNN total loss: 0.10138 L1 loss: 0.0000e+00 L2 loss: 0.56238 Learning rate: 4.0000e-05 Mask loss: 0.14354 RPN box loss: 0.00965 RPN score loss: 0.00361 RPN total loss: 0.01325 Total loss: 0.82055 timestamp: 1655075345.0034528 iteration: 85350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.17512 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12347 RPN box loss: 0.00697 RPN score loss: 0.01009 RPN total loss: 0.01706 Total loss: 0.87802 timestamp: 1655075348.1980383 iteration: 85355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12679 FastRCNN class loss: 0.07629 FastRCNN total loss: 0.20308 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15026 RPN box loss: 0.01473 RPN score loss: 0.02388 RPN total loss: 0.03861 Total loss: 0.95433 timestamp: 1655075351.4298851 iteration: 85360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10865 FastRCNN class loss: 0.04761 FastRCNN total loss: 0.15626 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.11773 RPN box loss: 0.03391 RPN score loss: 0.00135 RPN total loss: 0.03525 Total loss: 0.87162 timestamp: 1655075354.778857 iteration: 85365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05254 FastRCNN class loss: 0.03964 FastRCNN total loss: 0.09218 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.19317 RPN box loss: 0.00273 RPN score loss: 0.00612 RPN total loss: 0.00885 Total loss: 0.85658 timestamp: 1655075358.0503306 iteration: 85370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.06448 FastRCNN total loss: 0.14587 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12111 RPN box loss: 0.01045 RPN score loss: 0.00734 RPN total loss: 0.01779 Total loss: 0.84714 timestamp: 1655075361.3897753 iteration: 85375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10318 FastRCNN class loss: 0.07511 FastRCNN total loss: 0.17829 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.19057 RPN box loss: 0.01378 RPN score loss: 0.01039 RPN total loss: 0.02417 Total loss: 0.9554 timestamp: 1655075364.6696315 iteration: 85380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13758 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.21662 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14882 RPN box loss: 0.01297 RPN score loss: 0.00448 RPN total loss: 0.01744 Total loss: 0.94526 timestamp: 1655075367.9816897 iteration: 85385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09236 FastRCNN class loss: 0.0427 FastRCNN total loss: 0.13506 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.10398 RPN box loss: 0.01751 RPN score loss: 0.00224 RPN total loss: 0.01975 Total loss: 0.82117 timestamp: 1655075371.2733052 iteration: 85390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06951 FastRCNN class loss: 0.08097 FastRCNN total loss: 0.15048 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14833 RPN box loss: 0.02651 RPN score loss: 0.00916 RPN total loss: 0.03567 Total loss: 0.89686 timestamp: 1655075374.5367184 iteration: 85395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05042 FastRCNN class loss: 0.03973 FastRCNN total loss: 0.09015 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.11594 RPN box loss: 0.02355 RPN score loss: 0.00699 RPN total loss: 0.03054 Total loss: 0.799 timestamp: 1655075377.8367944 iteration: 85400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11964 FastRCNN class loss: 0.04078 FastRCNN total loss: 0.16042 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14067 RPN box loss: 0.01577 RPN score loss: 0.00284 RPN total loss: 0.01861 Total loss: 0.88207 timestamp: 1655075381.130987 iteration: 85405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06308 FastRCNN class loss: 0.06531 FastRCNN total loss: 0.12839 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.08814 RPN box loss: 0.01205 RPN score loss: 0.00142 RPN total loss: 0.01347 Total loss: 0.79237 timestamp: 1655075384.4581585 iteration: 85410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05456 FastRCNN class loss: 0.04383 FastRCNN total loss: 0.09839 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.11962 RPN box loss: 0.00481 RPN score loss: 0.00106 RPN total loss: 0.00587 Total loss: 0.78624 timestamp: 1655075387.702095 iteration: 85415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13016 FastRCNN class loss: 0.05288 FastRCNN total loss: 0.18304 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.1743 RPN box loss: 0.00755 RPN score loss: 0.00276 RPN total loss: 0.01031 Total loss: 0.93002 timestamp: 1655075391.019279 iteration: 85420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05769 FastRCNN class loss: 0.03825 FastRCNN total loss: 0.09594 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09735 RPN box loss: 0.00723 RPN score loss: 0.00579 RPN total loss: 0.01302 Total loss: 0.76869 timestamp: 1655075394.2898715 iteration: 85425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06542 FastRCNN class loss: 0.08539 FastRCNN total loss: 0.15081 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15929 RPN box loss: 0.01423 RPN score loss: 0.01153 RPN total loss: 0.02576 Total loss: 0.89824 timestamp: 1655075397.6254022 iteration: 85430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06796 FastRCNN class loss: 0.03943 FastRCNN total loss: 0.10738 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12166 RPN box loss: 0.01187 RPN score loss: 0.00289 RPN total loss: 0.01476 Total loss: 0.80618 timestamp: 1655075400.9776764 iteration: 85435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07988 FastRCNN class loss: 0.05237 FastRCNN total loss: 0.13225 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09779 RPN box loss: 0.01832 RPN score loss: 0.00315 RPN total loss: 0.02147 Total loss: 0.81388 timestamp: 1655075404.2387075 iteration: 85440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10349 FastRCNN class loss: 0.0659 FastRCNN total loss: 0.16939 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.22492 RPN box loss: 0.02417 RPN score loss: 0.01254 RPN total loss: 0.03672 Total loss: 0.9934 timestamp: 1655075407.5070193 iteration: 85445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05129 FastRCNN class loss: 0.042 FastRCNN total loss: 0.09329 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12491 RPN box loss: 0.00688 RPN score loss: 0.00493 RPN total loss: 0.01181 Total loss: 0.79238 timestamp: 1655075410.9027581 iteration: 85450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.05517 FastRCNN total loss: 0.15261 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.10204 RPN box loss: 0.01063 RPN score loss: 0.00076 RPN total loss: 0.01139 Total loss: 0.82841 timestamp: 1655075414.1572263 iteration: 85455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12651 FastRCNN class loss: 0.07534 FastRCNN total loss: 0.20185 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14839 RPN box loss: 0.01581 RPN score loss: 0.00694 RPN total loss: 0.02275 Total loss: 0.93536 timestamp: 1655075417.3342183 iteration: 85460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15066 FastRCNN class loss: 0.08248 FastRCNN total loss: 0.23314 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.10188 RPN box loss: 0.00993 RPN score loss: 0.00252 RPN total loss: 0.01244 Total loss: 0.90983 timestamp: 1655075420.631813 iteration: 85465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06809 FastRCNN class loss: 0.06251 FastRCNN total loss: 0.1306 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15391 RPN box loss: 0.01423 RPN score loss: 0.00631 RPN total loss: 0.02054 Total loss: 0.86742 timestamp: 1655075423.8850732 iteration: 85470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09083 FastRCNN class loss: 0.07386 FastRCNN total loss: 0.16469 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.175 RPN box loss: 0.00995 RPN score loss: 0.0091 RPN total loss: 0.01905 Total loss: 0.92112 timestamp: 1655075427.231207 iteration: 85475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09392 FastRCNN class loss: 0.0361 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12783 RPN box loss: 0.00979 RPN score loss: 0.00557 RPN total loss: 0.01536 Total loss: 0.83558 timestamp: 1655075430.4956095 iteration: 85480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05407 FastRCNN class loss: 0.05545 FastRCNN total loss: 0.10953 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12026 RPN box loss: 0.01686 RPN score loss: 0.00538 RPN total loss: 0.02223 Total loss: 0.81439 timestamp: 1655075433.779098 iteration: 85485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08436 FastRCNN class loss: 0.08126 FastRCNN total loss: 0.16562 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.21809 RPN box loss: 0.00909 RPN score loss: 0.00214 RPN total loss: 0.01123 Total loss: 0.95732 timestamp: 1655075437.0439296 iteration: 85490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15374 FastRCNN class loss: 0.1058 FastRCNN total loss: 0.25954 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15486 RPN box loss: 0.02332 RPN score loss: 0.00493 RPN total loss: 0.02825 Total loss: 1.00502 timestamp: 1655075440.3082767 iteration: 85495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1005 FastRCNN class loss: 0.09492 FastRCNN total loss: 0.19541 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.13998 RPN box loss: 0.03946 RPN score loss: 0.01193 RPN total loss: 0.0514 Total loss: 0.94916 timestamp: 1655075443.6346204 iteration: 85500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05772 FastRCNN class loss: 0.03606 FastRCNN total loss: 0.09378 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09506 RPN box loss: 0.00139 RPN score loss: 0.00155 RPN total loss: 0.00293 Total loss: 0.75415 timestamp: 1655075446.904502 iteration: 85505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06781 FastRCNN class loss: 0.06144 FastRCNN total loss: 0.12925 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.155 RPN box loss: 0.00794 RPN score loss: 0.00065 RPN total loss: 0.00858 Total loss: 0.85521 timestamp: 1655075450.1429236 iteration: 85510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1053 FastRCNN class loss: 0.102 FastRCNN total loss: 0.2073 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15721 RPN box loss: 0.01779 RPN score loss: 0.00938 RPN total loss: 0.02716 Total loss: 0.95404 timestamp: 1655075453.3949568 iteration: 85515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10252 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.18403 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.17615 RPN box loss: 0.02168 RPN score loss: 0.00744 RPN total loss: 0.02912 Total loss: 0.95167 timestamp: 1655075456.6802588 iteration: 85520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11518 FastRCNN class loss: 0.08891 FastRCNN total loss: 0.20409 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.1799 RPN box loss: 0.01502 RPN score loss: 0.00947 RPN total loss: 0.02449 Total loss: 0.97085 timestamp: 1655075459.9817915 iteration: 85525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07878 FastRCNN class loss: 0.0624 FastRCNN total loss: 0.14118 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09656 RPN box loss: 0.00861 RPN score loss: 0.0016 RPN total loss: 0.01021 Total loss: 0.81032 timestamp: 1655075463.2442808 iteration: 85530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10368 FastRCNN class loss: 0.06998 FastRCNN total loss: 0.17367 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.18342 RPN box loss: 0.0103 RPN score loss: 0.00351 RPN total loss: 0.01381 Total loss: 0.93327 timestamp: 1655075466.506188 iteration: 85535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08145 FastRCNN class loss: 0.10455 FastRCNN total loss: 0.186 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.19301 RPN box loss: 0.01547 RPN score loss: 0.0101 RPN total loss: 0.02557 Total loss: 0.96695 timestamp: 1655075469.7352471 iteration: 85540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12494 FastRCNN class loss: 0.07364 FastRCNN total loss: 0.19858 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.13781 RPN box loss: 0.00593 RPN score loss: 0.00767 RPN total loss: 0.0136 Total loss: 0.91236 timestamp: 1655075472.9997613 iteration: 85545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13512 FastRCNN class loss: 0.08465 FastRCNN total loss: 0.21977 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.16075 RPN box loss: 0.03028 RPN score loss: 0.00597 RPN total loss: 0.03625 Total loss: 0.97913 timestamp: 1655075476.31725 iteration: 85550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07168 FastRCNN class loss: 0.04589 FastRCNN total loss: 0.11756 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09074 RPN box loss: 0.01215 RPN score loss: 0.00221 RPN total loss: 0.01436 Total loss: 0.78503 timestamp: 1655075479.6007714 iteration: 85555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14059 FastRCNN class loss: 0.11983 FastRCNN total loss: 0.26042 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.22183 RPN box loss: 0.01695 RPN score loss: 0.01577 RPN total loss: 0.03272 Total loss: 1.07733 timestamp: 1655075482.8098023 iteration: 85560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05398 FastRCNN class loss: 0.04195 FastRCNN total loss: 0.09593 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.10211 RPN box loss: 0.00373 RPN score loss: 0.00957 RPN total loss: 0.0133 Total loss: 0.77371 timestamp: 1655075486.145407 iteration: 85565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14888 FastRCNN class loss: 0.07698 FastRCNN total loss: 0.22586 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.15786 RPN box loss: 0.01189 RPN score loss: 0.00525 RPN total loss: 0.01714 Total loss: 0.96323 timestamp: 1655075489.3857417 iteration: 85570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06674 FastRCNN class loss: 0.06893 FastRCNN total loss: 0.13567 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.1376 RPN box loss: 0.02012 RPN score loss: 0.01126 RPN total loss: 0.03139 Total loss: 0.86703 timestamp: 1655075492.6283622 iteration: 85575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12911 FastRCNN class loss: 0.09255 FastRCNN total loss: 0.22166 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.11411 RPN box loss: 0.01008 RPN score loss: 0.00446 RPN total loss: 0.01453 Total loss: 0.91267 timestamp: 1655075495.8156624 iteration: 85580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06259 FastRCNN class loss: 0.11319 FastRCNN total loss: 0.17578 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12398 RPN box loss: 0.01797 RPN score loss: 0.0032 RPN total loss: 0.02116 Total loss: 0.8833 timestamp: 1655075499.1257606 iteration: 85585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08937 FastRCNN class loss: 0.05635 FastRCNN total loss: 0.14573 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.08988 RPN box loss: 0.00508 RPN score loss: 0.00115 RPN total loss: 0.00623 Total loss: 0.80421 timestamp: 1655075502.4717731 iteration: 85590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08385 FastRCNN class loss: 0.06829 FastRCNN total loss: 0.15214 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12379 RPN box loss: 0.0161 RPN score loss: 0.00649 RPN total loss: 0.02259 Total loss: 0.86089 timestamp: 1655075505.6905513 iteration: 85595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07599 FastRCNN class loss: 0.06547 FastRCNN total loss: 0.14146 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.16604 RPN box loss: 0.01808 RPN score loss: 0.01059 RPN total loss: 0.02866 Total loss: 0.89853 timestamp: 1655075508.949994 iteration: 85600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11261 FastRCNN class loss: 0.11529 FastRCNN total loss: 0.2279 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.17499 RPN box loss: 0.0176 RPN score loss: 0.00256 RPN total loss: 0.02016 Total loss: 0.98542 timestamp: 1655075512.2041454 iteration: 85605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03439 FastRCNN class loss: 0.0335 FastRCNN total loss: 0.0679 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.10783 RPN box loss: 0.00339 RPN score loss: 0.00365 RPN total loss: 0.00705 Total loss: 0.74514 timestamp: 1655075515.4933164 iteration: 85610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0474 FastRCNN class loss: 0.05773 FastRCNN total loss: 0.10513 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14405 RPN box loss: 0.01244 RPN score loss: 0.00446 RPN total loss: 0.0169 Total loss: 0.82845 timestamp: 1655075518.7668116 iteration: 85615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.0513 FastRCNN total loss: 0.16447 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.16425 RPN box loss: 0.00885 RPN score loss: 0.00822 RPN total loss: 0.01707 Total loss: 0.90816 timestamp: 1655075522.035388 iteration: 85620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.16092 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12457 RPN box loss: 0.02307 RPN score loss: 0.0086 RPN total loss: 0.03168 Total loss: 0.87953 timestamp: 1655075525.3300762 iteration: 85625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14233 FastRCNN class loss: 0.07533 FastRCNN total loss: 0.21765 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.1352 RPN box loss: 0.02133 RPN score loss: 0.00287 RPN total loss: 0.0242 Total loss: 0.93943 timestamp: 1655075528.5372999 iteration: 85630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09862 FastRCNN class loss: 0.07789 FastRCNN total loss: 0.17651 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.1623 RPN box loss: 0.00933 RPN score loss: 0.00542 RPN total loss: 0.01474 Total loss: 0.91593 timestamp: 1655075531.7910137 iteration: 85635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12545 FastRCNN class loss: 0.07028 FastRCNN total loss: 0.19573 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.16091 RPN box loss: 0.00932 RPN score loss: 0.00175 RPN total loss: 0.01107 Total loss: 0.93007 timestamp: 1655075534.9982557 iteration: 85640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07076 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.12296 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.08589 RPN box loss: 0.00239 RPN score loss: 0.00443 RPN total loss: 0.00682 Total loss: 0.77803 timestamp: 1655075538.3136885 iteration: 85645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07723 FastRCNN class loss: 0.03463 FastRCNN total loss: 0.11186 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12463 RPN box loss: 0.01289 RPN score loss: 0.00194 RPN total loss: 0.01483 Total loss: 0.81368 timestamp: 1655075541.5980074 iteration: 85650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05266 FastRCNN class loss: 0.03487 FastRCNN total loss: 0.08753 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.16995 RPN box loss: 0.00883 RPN score loss: 0.0026 RPN total loss: 0.01143 Total loss: 0.83128 timestamp: 1655075544.8837814 iteration: 85655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11529 FastRCNN class loss: 0.09367 FastRCNN total loss: 0.20896 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.18462 RPN box loss: 0.01347 RPN score loss: 0.00267 RPN total loss: 0.01614 Total loss: 0.97208 timestamp: 1655075548.1480942 iteration: 85660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06916 FastRCNN class loss: 0.06183 FastRCNN total loss: 0.13099 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.12658 RPN box loss: 0.01058 RPN score loss: 0.00489 RPN total loss: 0.01547 Total loss: 0.83541 timestamp: 1655075551.5001428 iteration: 85665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09882 FastRCNN class loss: 0.08468 FastRCNN total loss: 0.1835 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.14793 RPN box loss: 0.02476 RPN score loss: 0.02314 RPN total loss: 0.0479 Total loss: 0.94169 timestamp: 1655075555.0012531 iteration: 85670 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05768 FastRCNN class loss: 0.04153 FastRCNN total loss: 0.09921 L1 loss: 0.0000e+00 L2 loss: 0.56237 Learning rate: 4.0000e-05 Mask loss: 0.09431 RPN box loss: 0.03954 RPN score loss: 0.00162 RPN total loss: 0.04116 Total loss: 0.79705 timestamp: 1655075558.254046 iteration: 85675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04991 FastRCNN class loss: 0.06126 FastRCNN total loss: 0.11117 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.16847 RPN box loss: 0.00408 RPN score loss: 0.00208 RPN total loss: 0.00616 Total loss: 0.84816 timestamp: 1655075561.605836 iteration: 85680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14868 FastRCNN class loss: 0.11926 FastRCNN total loss: 0.26793 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17815 RPN box loss: 0.01426 RPN score loss: 0.00857 RPN total loss: 0.02284 Total loss: 1.03129 timestamp: 1655075564.8438337 iteration: 85685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11816 FastRCNN class loss: 0.08225 FastRCNN total loss: 0.2004 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14023 RPN box loss: 0.01326 RPN score loss: 0.00295 RPN total loss: 0.01621 Total loss: 0.9192 timestamp: 1655075568.1387055 iteration: 85690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08346 FastRCNN class loss: 0.07411 FastRCNN total loss: 0.15757 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12043 RPN box loss: 0.00759 RPN score loss: 0.0103 RPN total loss: 0.01789 Total loss: 0.85825 timestamp: 1655075571.3819733 iteration: 85695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0888 FastRCNN class loss: 0.05709 FastRCNN total loss: 0.14589 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.10843 RPN box loss: 0.01924 RPN score loss: 0.00708 RPN total loss: 0.02632 Total loss: 0.843 timestamp: 1655075574.6053276 iteration: 85700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09743 FastRCNN class loss: 0.08459 FastRCNN total loss: 0.18202 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.1323 RPN box loss: 0.00856 RPN score loss: 0.00502 RPN total loss: 0.01358 Total loss: 0.89027 timestamp: 1655075577.853281 iteration: 85705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06729 FastRCNN class loss: 0.05442 FastRCNN total loss: 0.12171 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14754 RPN box loss: 0.00439 RPN score loss: 0.00424 RPN total loss: 0.00863 Total loss: 0.84024 timestamp: 1655075581.1304364 iteration: 85710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10683 FastRCNN class loss: 0.0744 FastRCNN total loss: 0.18123 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.19523 RPN box loss: 0.02524 RPN score loss: 0.0089 RPN total loss: 0.03414 Total loss: 0.97296 timestamp: 1655075584.404816 iteration: 85715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07985 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.14733 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15802 RPN box loss: 0.01676 RPN score loss: 0.00245 RPN total loss: 0.0192 Total loss: 0.88692 timestamp: 1655075587.671253 iteration: 85720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07187 FastRCNN class loss: 0.03799 FastRCNN total loss: 0.10986 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.11126 RPN box loss: 0.0142 RPN score loss: 0.00359 RPN total loss: 0.01778 Total loss: 0.80127 timestamp: 1655075590.9351556 iteration: 85725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06528 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.10722 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13267 RPN box loss: 0.0064 RPN score loss: 0.00133 RPN total loss: 0.00774 Total loss: 0.80999 timestamp: 1655075594.234796 iteration: 85730 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08396 FastRCNN class loss: 0.0738 FastRCNN total loss: 0.15776 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.117 RPN box loss: 0.01498 RPN score loss: 0.00121 RPN total loss: 0.01618 Total loss: 0.85331 timestamp: 1655075597.5030022 iteration: 85735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06392 FastRCNN class loss: 0.0495 FastRCNN total loss: 0.11342 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13212 RPN box loss: 0.00752 RPN score loss: 0.00349 RPN total loss: 0.01101 Total loss: 0.81892 timestamp: 1655075600.747035 iteration: 85740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10145 FastRCNN class loss: 0.07697 FastRCNN total loss: 0.17843 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14122 RPN box loss: 0.02277 RPN score loss: 0.01477 RPN total loss: 0.03754 Total loss: 0.91955 timestamp: 1655075604.0523224 iteration: 85745 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.04992 FastRCNN total loss: 0.12938 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15156 RPN box loss: 0.00688 RPN score loss: 0.00367 RPN total loss: 0.01055 Total loss: 0.85386 timestamp: 1655075607.2701306 iteration: 85750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08154 FastRCNN class loss: 0.08189 FastRCNN total loss: 0.16343 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15274 RPN box loss: 0.01503 RPN score loss: 0.00644 RPN total loss: 0.02147 Total loss: 0.90001 timestamp: 1655075610.5918436 iteration: 85755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06335 FastRCNN class loss: 0.0668 FastRCNN total loss: 0.13015 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.10207 RPN box loss: 0.00881 RPN score loss: 0.00358 RPN total loss: 0.01239 Total loss: 0.80698 timestamp: 1655075613.8805995 iteration: 85760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0794 FastRCNN class loss: 0.05041 FastRCNN total loss: 0.12981 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.16768 RPN box loss: 0.01131 RPN score loss: 0.00621 RPN total loss: 0.01751 Total loss: 0.87736 timestamp: 1655075617.1888177 iteration: 85765 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08713 FastRCNN class loss: 0.06076 FastRCNN total loss: 0.14788 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15678 RPN box loss: 0.00345 RPN score loss: 0.00445 RPN total loss: 0.0079 Total loss: 0.87492 timestamp: 1655075620.3783097 iteration: 85770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.0831 FastRCNN total loss: 0.15887 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17596 RPN box loss: 0.04674 RPN score loss: 0.00782 RPN total loss: 0.05456 Total loss: 0.95176 timestamp: 1655075623.5706248 iteration: 85775 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04749 FastRCNN class loss: 0.04178 FastRCNN total loss: 0.08927 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14576 RPN box loss: 0.00524 RPN score loss: 0.00787 RPN total loss: 0.01311 Total loss: 0.8105 timestamp: 1655075626.8814743 iteration: 85780 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05021 FastRCNN class loss: 0.06107 FastRCNN total loss: 0.11128 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.10824 RPN box loss: 0.00978 RPN score loss: 0.00284 RPN total loss: 0.01262 Total loss: 0.7945 timestamp: 1655075630.1767595 iteration: 85785 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07103 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.13015 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13553 RPN box loss: 0.00577 RPN score loss: 0.00533 RPN total loss: 0.0111 Total loss: 0.83914 timestamp: 1655075633.4337692 iteration: 85790 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11061 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.18227 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.1459 RPN box loss: 0.01964 RPN score loss: 0.01057 RPN total loss: 0.03021 Total loss: 0.92074 timestamp: 1655075636.626299 iteration: 85795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0533 FastRCNN class loss: 0.03805 FastRCNN total loss: 0.09136 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12926 RPN box loss: 0.00754 RPN score loss: 0.00184 RPN total loss: 0.00938 Total loss: 0.79235 timestamp: 1655075639.8272939 iteration: 85800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10674 FastRCNN class loss: 0.09026 FastRCNN total loss: 0.197 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15685 RPN box loss: 0.01531 RPN score loss: 0.00745 RPN total loss: 0.02276 Total loss: 0.93897 timestamp: 1655075643.107682 iteration: 85805 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08613 FastRCNN class loss: 0.08985 FastRCNN total loss: 0.17598 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12963 RPN box loss: 0.05475 RPN score loss: 0.00824 RPN total loss: 0.063 Total loss: 0.93097 timestamp: 1655075646.4063191 iteration: 85810 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13019 FastRCNN class loss: 0.10213 FastRCNN total loss: 0.23232 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17259 RPN box loss: 0.02804 RPN score loss: 0.00958 RPN total loss: 0.03762 Total loss: 1.00489 timestamp: 1655075649.7285686 iteration: 85815 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07983 FastRCNN class loss: 0.06679 FastRCNN total loss: 0.14662 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.20625 RPN box loss: 0.0203 RPN score loss: 0.01324 RPN total loss: 0.03354 Total loss: 0.94877 timestamp: 1655075652.9819238 iteration: 85820 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12871 FastRCNN class loss: 0.07203 FastRCNN total loss: 0.20074 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15137 RPN box loss: 0.00639 RPN score loss: 0.00112 RPN total loss: 0.00752 Total loss: 0.92199 timestamp: 1655075656.2992864 iteration: 85825 throughput: 24.4 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05776 FastRCNN class loss: 0.04719 FastRCNN total loss: 0.10495 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13917 RPN box loss: 0.00597 RPN score loss: 0.00333 RPN total loss: 0.00929 Total loss: 0.81577 timestamp: 1655075659.5119557 iteration: 85830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12546 FastRCNN class loss: 0.07682 FastRCNN total loss: 0.20228 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14846 RPN box loss: 0.02556 RPN score loss: 0.0082 RPN total loss: 0.03377 Total loss: 0.94686 timestamp: 1655075662.808583 iteration: 85835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11419 FastRCNN class loss: 0.06865 FastRCNN total loss: 0.18284 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13862 RPN box loss: 0.00656 RPN score loss: 0.00115 RPN total loss: 0.00772 Total loss: 0.89154 timestamp: 1655075666.0739326 iteration: 85840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08654 FastRCNN class loss: 0.06994 FastRCNN total loss: 0.15648 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.31662 RPN box loss: 0.03487 RPN score loss: 0.00962 RPN total loss: 0.04449 Total loss: 1.07995 timestamp: 1655075669.353134 iteration: 85845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07142 FastRCNN class loss: 0.06789 FastRCNN total loss: 0.13931 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15153 RPN box loss: 0.02225 RPN score loss: 0.00704 RPN total loss: 0.02929 Total loss: 0.88249 timestamp: 1655075672.5993996 iteration: 85850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12364 FastRCNN class loss: 0.11962 FastRCNN total loss: 0.24326 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.16943 RPN box loss: 0.02454 RPN score loss: 0.00705 RPN total loss: 0.03159 Total loss: 1.00663 timestamp: 1655075675.873738 iteration: 85855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05917 FastRCNN class loss: 0.0643 FastRCNN total loss: 0.12347 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.16489 RPN box loss: 0.01192 RPN score loss: 0.01604 RPN total loss: 0.02796 Total loss: 0.87868 timestamp: 1655075679.2278128 iteration: 85860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07415 FastRCNN class loss: 0.04432 FastRCNN total loss: 0.11847 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.08439 RPN box loss: 0.00523 RPN score loss: 0.00275 RPN total loss: 0.00798 Total loss: 0.77321 timestamp: 1655075682.4922223 iteration: 85865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06181 FastRCNN class loss: 0.05643 FastRCNN total loss: 0.11824 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.09352 RPN box loss: 0.0046 RPN score loss: 0.00285 RPN total loss: 0.00745 Total loss: 0.78157 timestamp: 1655075685.752502 iteration: 85870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08749 FastRCNN class loss: 0.09151 FastRCNN total loss: 0.179 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.09713 RPN box loss: 0.0149 RPN score loss: 0.00422 RPN total loss: 0.01912 Total loss: 0.85761 timestamp: 1655075688.9783401 iteration: 85875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04571 FastRCNN class loss: 0.0326 FastRCNN total loss: 0.07831 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13166 RPN box loss: 0.00735 RPN score loss: 0.01168 RPN total loss: 0.01903 Total loss: 0.79136 timestamp: 1655075692.1666427 iteration: 85880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07108 FastRCNN class loss: 0.05657 FastRCNN total loss: 0.12765 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12527 RPN box loss: 0.02153 RPN score loss: 0.00202 RPN total loss: 0.02355 Total loss: 0.83882 timestamp: 1655075695.5166118 iteration: 85885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09148 FastRCNN class loss: 0.08551 FastRCNN total loss: 0.17699 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.19765 RPN box loss: 0.0101 RPN score loss: 0.00788 RPN total loss: 0.01798 Total loss: 0.95498 timestamp: 1655075698.7702014 iteration: 85890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09588 FastRCNN class loss: 0.11134 FastRCNN total loss: 0.20722 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12809 RPN box loss: 0.02089 RPN score loss: 0.00766 RPN total loss: 0.02855 Total loss: 0.92621 timestamp: 1655075702.0237846 iteration: 85895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12061 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.18036 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.10878 RPN box loss: 0.01175 RPN score loss: 0.00592 RPN total loss: 0.01767 Total loss: 0.86916 timestamp: 1655075705.2979228 iteration: 85900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09408 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12507 RPN box loss: 0.01031 RPN score loss: 0.00154 RPN total loss: 0.01185 Total loss: 0.85949 timestamp: 1655075708.573866 iteration: 85905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09606 FastRCNN class loss: 0.06664 FastRCNN total loss: 0.16271 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.20121 RPN box loss: 0.0274 RPN score loss: 0.00926 RPN total loss: 0.03665 Total loss: 0.96293 timestamp: 1655075711.8954358 iteration: 85910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15282 FastRCNN class loss: 0.08537 FastRCNN total loss: 0.23819 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15474 RPN box loss: 0.00703 RPN score loss: 0.00889 RPN total loss: 0.01592 Total loss: 0.97121 timestamp: 1655075715.1531422 iteration: 85915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08705 FastRCNN class loss: 0.07333 FastRCNN total loss: 0.16038 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13738 RPN box loss: 0.0144 RPN score loss: 0.00344 RPN total loss: 0.01784 Total loss: 0.87796 timestamp: 1655075718.459556 iteration: 85920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07721 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.1396 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13682 RPN box loss: 0.01057 RPN score loss: 0.00946 RPN total loss: 0.02003 Total loss: 0.85881 timestamp: 1655075721.7873573 iteration: 85925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07725 FastRCNN class loss: 0.08933 FastRCNN total loss: 0.16657 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13093 RPN box loss: 0.02458 RPN score loss: 0.00856 RPN total loss: 0.03314 Total loss: 0.893 timestamp: 1655075725.0113487 iteration: 85930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10036 FastRCNN class loss: 0.09917 FastRCNN total loss: 0.19953 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17744 RPN box loss: 0.00651 RPN score loss: 0.00457 RPN total loss: 0.01108 Total loss: 0.9504 timestamp: 1655075728.3361874 iteration: 85935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10116 FastRCNN class loss: 0.05243 FastRCNN total loss: 0.15359 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12682 RPN box loss: 0.01325 RPN score loss: 0.00324 RPN total loss: 0.01649 Total loss: 0.85925 timestamp: 1655075731.6303797 iteration: 85940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0338 FastRCNN class loss: 0.05581 FastRCNN total loss: 0.08962 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.15479 RPN box loss: 0.01533 RPN score loss: 0.00885 RPN total loss: 0.02417 Total loss: 0.83094 timestamp: 1655075734.9240258 iteration: 85945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0804 FastRCNN class loss: 0.08867 FastRCNN total loss: 0.16907 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17172 RPN box loss: 0.01943 RPN score loss: 0.0143 RPN total loss: 0.03373 Total loss: 0.93688 timestamp: 1655075738.126781 iteration: 85950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09875 FastRCNN class loss: 0.05795 FastRCNN total loss: 0.15671 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.14055 RPN box loss: 0.01414 RPN score loss: 0.00845 RPN total loss: 0.02259 Total loss: 0.8822 timestamp: 1655075741.4445043 iteration: 85955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13999 FastRCNN class loss: 0.08185 FastRCNN total loss: 0.22184 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.13954 RPN box loss: 0.01177 RPN score loss: 0.00542 RPN total loss: 0.01718 Total loss: 0.94091 timestamp: 1655075744.670203 iteration: 85960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12777 FastRCNN class loss: 0.06711 FastRCNN total loss: 0.19488 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.12201 RPN box loss: 0.00878 RPN score loss: 0.0059 RPN total loss: 0.01468 Total loss: 0.89392 timestamp: 1655075747.9835722 iteration: 85965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10002 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.17349 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17667 RPN box loss: 0.01328 RPN score loss: 0.00714 RPN total loss: 0.02042 Total loss: 0.93294 timestamp: 1655075751.3125288 iteration: 85970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08465 FastRCNN class loss: 0.03705 FastRCNN total loss: 0.1217 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.11253 RPN box loss: 0.0059 RPN score loss: 0.00042 RPN total loss: 0.00632 Total loss: 0.8029 timestamp: 1655075754.5270905 iteration: 85975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12526 FastRCNN class loss: 0.08328 FastRCNN total loss: 0.20854 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.19946 RPN box loss: 0.00793 RPN score loss: 0.00432 RPN total loss: 0.01225 Total loss: 0.9826 timestamp: 1655075757.74418 iteration: 85980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06054 FastRCNN class loss: 0.05952 FastRCNN total loss: 0.12006 L1 loss: 0.0000e+00 L2 loss: 0.56236 Learning rate: 4.0000e-05 Mask loss: 0.17202 RPN box loss: 0.00269 RPN score loss: 0.00346 RPN total loss: 0.00615 Total loss: 0.86058 timestamp: 1655075760.9922762 iteration: 85985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09561 FastRCNN class loss: 0.07433 FastRCNN total loss: 0.16993 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.19779 RPN box loss: 0.0071 RPN score loss: 0.00193 RPN total loss: 0.00903 Total loss: 0.93911 timestamp: 1655075764.2239976 iteration: 85990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11609 FastRCNN class loss: 0.08318 FastRCNN total loss: 0.19927 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.11809 RPN box loss: 0.03541 RPN score loss: 0.00543 RPN total loss: 0.04084 Total loss: 0.92056 timestamp: 1655075767.4239283 iteration: 85995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03845 FastRCNN class loss: 0.02152 FastRCNN total loss: 0.05997 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.11104 RPN box loss: 0.00107 RPN score loss: 0.00113 RPN total loss: 0.0022 Total loss: 0.73557 timestamp: 1655075770.6913154 iteration: 86000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06673 FastRCNN class loss: 0.05053 FastRCNN total loss: 0.11726 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1661 RPN box loss: 0.00819 RPN score loss: 0.00079 RPN total loss: 0.00898 Total loss: 0.85469 timestamp: 1655075773.9326413 iteration: 86005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11891 FastRCNN class loss: 0.06611 FastRCNN total loss: 0.18502 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.09619 RPN box loss: 0.00967 RPN score loss: 0.00145 RPN total loss: 0.01111 Total loss: 0.85467 timestamp: 1655075777.2031028 iteration: 86010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07334 FastRCNN class loss: 0.12531 FastRCNN total loss: 0.19865 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.16533 RPN box loss: 0.01804 RPN score loss: 0.0038 RPN total loss: 0.02184 Total loss: 0.94816 timestamp: 1655075780.5145493 iteration: 86015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10485 FastRCNN class loss: 0.07914 FastRCNN total loss: 0.18399 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13725 RPN box loss: 0.00697 RPN score loss: 0.00709 RPN total loss: 0.01406 Total loss: 0.89766 timestamp: 1655075783.7622125 iteration: 86020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12787 FastRCNN class loss: 0.06951 FastRCNN total loss: 0.19738 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15547 RPN box loss: 0.01415 RPN score loss: 0.00462 RPN total loss: 0.01877 Total loss: 0.93398 timestamp: 1655075787.0756152 iteration: 86025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17604 FastRCNN class loss: 0.06747 FastRCNN total loss: 0.24351 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1307 RPN box loss: 0.01065 RPN score loss: 0.00074 RPN total loss: 0.01139 Total loss: 0.94796 timestamp: 1655075790.3882153 iteration: 86030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05741 FastRCNN class loss: 0.06838 FastRCNN total loss: 0.1258 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.29603 RPN box loss: 0.02264 RPN score loss: 0.00264 RPN total loss: 0.02529 Total loss: 1.00947 timestamp: 1655075793.6928747 iteration: 86035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07195 FastRCNN class loss: 0.09776 FastRCNN total loss: 0.16971 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15303 RPN box loss: 0.01762 RPN score loss: 0.01418 RPN total loss: 0.03181 Total loss: 0.9169 timestamp: 1655075796.8819098 iteration: 86040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11333 FastRCNN class loss: 0.09603 FastRCNN total loss: 0.20936 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1491 RPN box loss: 0.0097 RPN score loss: 0.00478 RPN total loss: 0.01448 Total loss: 0.93529 timestamp: 1655075800.107785 iteration: 86045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1062 FastRCNN class loss: 0.07947 FastRCNN total loss: 0.18567 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.2251 RPN box loss: 0.01904 RPN score loss: 0.00628 RPN total loss: 0.02532 Total loss: 0.99844 timestamp: 1655075803.427541 iteration: 86050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09901 FastRCNN class loss: 0.06208 FastRCNN total loss: 0.16109 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15807 RPN box loss: 0.03684 RPN score loss: 0.00579 RPN total loss: 0.04262 Total loss: 0.92413 timestamp: 1655075806.7143285 iteration: 86055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05788 FastRCNN class loss: 0.0406 FastRCNN total loss: 0.09849 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.09238 RPN box loss: 0.04521 RPN score loss: 0.00224 RPN total loss: 0.04744 Total loss: 0.80066 timestamp: 1655075809.9993825 iteration: 86060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12972 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.21803 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.16046 RPN box loss: 0.02483 RPN score loss: 0.00887 RPN total loss: 0.0337 Total loss: 0.97455 timestamp: 1655075813.254845 iteration: 86065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06227 FastRCNN class loss: 0.05605 FastRCNN total loss: 0.11832 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12201 RPN box loss: 0.0113 RPN score loss: 0.0058 RPN total loss: 0.0171 Total loss: 0.81977 timestamp: 1655075816.4935977 iteration: 86070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16341 FastRCNN class loss: 0.12089 FastRCNN total loss: 0.2843 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15866 RPN box loss: 0.01301 RPN score loss: 0.00266 RPN total loss: 0.01567 Total loss: 1.02098 timestamp: 1655075819.7678552 iteration: 86075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09277 FastRCNN class loss: 0.0597 FastRCNN total loss: 0.15248 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12973 RPN box loss: 0.0059 RPN score loss: 0.00315 RPN total loss: 0.00905 Total loss: 0.85361 timestamp: 1655075823.0296166 iteration: 86080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06799 FastRCNN class loss: 0.04431 FastRCNN total loss: 0.1123 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.10603 RPN box loss: 0.00549 RPN score loss: 0.00033 RPN total loss: 0.00582 Total loss: 0.7865 timestamp: 1655075826.2814221 iteration: 86085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06329 FastRCNN class loss: 0.04755 FastRCNN total loss: 0.11084 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.11244 RPN box loss: 0.02715 RPN score loss: 0.00711 RPN total loss: 0.03426 Total loss: 0.8199 timestamp: 1655075829.5474138 iteration: 86090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07156 FastRCNN class loss: 0.04773 FastRCNN total loss: 0.1193 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13138 RPN box loss: 0.00616 RPN score loss: 0.00408 RPN total loss: 0.01025 Total loss: 0.82327 timestamp: 1655075832.8433661 iteration: 86095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08411 FastRCNN class loss: 0.07301 FastRCNN total loss: 0.15713 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1791 RPN box loss: 0.02 RPN score loss: 0.00244 RPN total loss: 0.02244 Total loss: 0.92102 timestamp: 1655075836.0862422 iteration: 86100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11559 FastRCNN class loss: 0.0949 FastRCNN total loss: 0.21049 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1747 RPN box loss: 0.01092 RPN score loss: 0.00455 RPN total loss: 0.01547 Total loss: 0.96301 timestamp: 1655075839.3081672 iteration: 86105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09297 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.16896 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.19081 RPN box loss: 0.00709 RPN score loss: 0.00344 RPN total loss: 0.01053 Total loss: 0.93266 timestamp: 1655075842.6674132 iteration: 86110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09854 FastRCNN class loss: 0.04516 FastRCNN total loss: 0.1437 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.07475 RPN box loss: 0.00915 RPN score loss: 0.00373 RPN total loss: 0.01288 Total loss: 0.79369 timestamp: 1655075845.9810276 iteration: 86115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06777 FastRCNN class loss: 0.05714 FastRCNN total loss: 0.12491 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14311 RPN box loss: 0.016 RPN score loss: 0.00123 RPN total loss: 0.01722 Total loss: 0.8476 timestamp: 1655075849.3400695 iteration: 86120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1029 FastRCNN class loss: 0.10072 FastRCNN total loss: 0.20362 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13803 RPN box loss: 0.01224 RPN score loss: 0.0051 RPN total loss: 0.01734 Total loss: 0.92134 timestamp: 1655075852.592829 iteration: 86125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09828 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.16995 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12677 RPN box loss: 0.01008 RPN score loss: 0.00441 RPN total loss: 0.0145 Total loss: 0.87356 timestamp: 1655075855.8617833 iteration: 86130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1349 FastRCNN class loss: 0.0774 FastRCNN total loss: 0.21231 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13597 RPN box loss: 0.0343 RPN score loss: 0.00723 RPN total loss: 0.04152 Total loss: 0.95215 timestamp: 1655075859.0778775 iteration: 86135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06817 FastRCNN class loss: 0.06302 FastRCNN total loss: 0.1312 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12666 RPN box loss: 0.02481 RPN score loss: 0.00248 RPN total loss: 0.0273 Total loss: 0.8475 timestamp: 1655075862.3500223 iteration: 86140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07358 FastRCNN class loss: 0.05029 FastRCNN total loss: 0.12388 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.08986 RPN box loss: 0.00747 RPN score loss: 0.0027 RPN total loss: 0.01016 Total loss: 0.78625 timestamp: 1655075865.6169724 iteration: 86145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1137 FastRCNN class loss: 0.06957 FastRCNN total loss: 0.18328 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12502 RPN box loss: 0.00666 RPN score loss: 0.0057 RPN total loss: 0.01235 Total loss: 0.883 timestamp: 1655075868.8753366 iteration: 86150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06161 FastRCNN class loss: 0.06217 FastRCNN total loss: 0.12378 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.10163 RPN box loss: 0.01442 RPN score loss: 0.0033 RPN total loss: 0.01772 Total loss: 0.80547 timestamp: 1655075872.1978753 iteration: 86155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07172 FastRCNN class loss: 0.07102 FastRCNN total loss: 0.14273 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12363 RPN box loss: 0.01341 RPN score loss: 0.0045 RPN total loss: 0.01792 Total loss: 0.84662 timestamp: 1655075875.4821482 iteration: 86160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07695 FastRCNN class loss: 0.04696 FastRCNN total loss: 0.12391 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.10031 RPN box loss: 0.00587 RPN score loss: 0.00143 RPN total loss: 0.0073 Total loss: 0.79387 timestamp: 1655075878.759695 iteration: 86165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08297 FastRCNN class loss: 0.06814 FastRCNN total loss: 0.15111 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13602 RPN box loss: 0.01448 RPN score loss: 0.01157 RPN total loss: 0.02605 Total loss: 0.87553 timestamp: 1655075882.0110471 iteration: 86170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12908 FastRCNN class loss: 0.11724 FastRCNN total loss: 0.24633 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13015 RPN box loss: 0.01614 RPN score loss: 0.00731 RPN total loss: 0.02346 Total loss: 0.96228 timestamp: 1655075885.3406444 iteration: 86175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1408 FastRCNN class loss: 0.08726 FastRCNN total loss: 0.22806 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.22499 RPN box loss: 0.01406 RPN score loss: 0.0033 RPN total loss: 0.01736 Total loss: 1.03275 timestamp: 1655075888.636111 iteration: 86180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07374 FastRCNN class loss: 0.047 FastRCNN total loss: 0.12075 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.09886 RPN box loss: 0.00407 RPN score loss: 0.00688 RPN total loss: 0.01095 Total loss: 0.7929 timestamp: 1655075891.9949358 iteration: 86185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11662 FastRCNN class loss: 0.12475 FastRCNN total loss: 0.24137 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.19477 RPN box loss: 0.02752 RPN score loss: 0.00747 RPN total loss: 0.03499 Total loss: 1.03347 timestamp: 1655075895.3202133 iteration: 86190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05653 FastRCNN class loss: 0.05912 FastRCNN total loss: 0.11566 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1938 RPN box loss: 0.01191 RPN score loss: 0.00534 RPN total loss: 0.01725 Total loss: 0.88906 timestamp: 1655075898.529355 iteration: 86195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08533 FastRCNN class loss: 0.04588 FastRCNN total loss: 0.13122 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.1229 RPN box loss: 0.00451 RPN score loss: 0.00126 RPN total loss: 0.00578 Total loss: 0.82224 timestamp: 1655075901.716435 iteration: 86200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03769 FastRCNN class loss: 0.05242 FastRCNN total loss: 0.0901 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.09032 RPN box loss: 0.00448 RPN score loss: 0.00183 RPN total loss: 0.0063 Total loss: 0.74908 timestamp: 1655075904.9464717 iteration: 86205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07155 FastRCNN class loss: 0.05611 FastRCNN total loss: 0.12767 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.11264 RPN box loss: 0.02011 RPN score loss: 0.0047 RPN total loss: 0.02481 Total loss: 0.82747 timestamp: 1655075908.2096078 iteration: 86210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07355 FastRCNN class loss: 0.05672 FastRCNN total loss: 0.13026 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14349 RPN box loss: 0.02465 RPN score loss: 0.00408 RPN total loss: 0.02873 Total loss: 0.86483 timestamp: 1655075911.4282808 iteration: 86215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0951 FastRCNN class loss: 0.06469 FastRCNN total loss: 0.15978 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14428 RPN box loss: 0.03699 RPN score loss: 0.00376 RPN total loss: 0.04075 Total loss: 0.90716 timestamp: 1655075914.6733596 iteration: 86220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06734 FastRCNN class loss: 0.07343 FastRCNN total loss: 0.14078 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.16515 RPN box loss: 0.00888 RPN score loss: 0.0039 RPN total loss: 0.01278 Total loss: 0.88105 timestamp: 1655075917.9999952 iteration: 86225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08961 FastRCNN class loss: 0.06248 FastRCNN total loss: 0.1521 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.11992 RPN box loss: 0.01988 RPN score loss: 0.00853 RPN total loss: 0.02841 Total loss: 0.86278 timestamp: 1655075921.2751496 iteration: 86230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09893 FastRCNN class loss: 0.08095 FastRCNN total loss: 0.17988 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15145 RPN box loss: 0.03307 RPN score loss: 0.00828 RPN total loss: 0.04135 Total loss: 0.93503 timestamp: 1655075924.567642 iteration: 86235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08378 FastRCNN class loss: 0.10523 FastRCNN total loss: 0.18901 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15253 RPN box loss: 0.01126 RPN score loss: 0.00586 RPN total loss: 0.01713 Total loss: 0.92102 timestamp: 1655075927.8114147 iteration: 86240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10769 FastRCNN class loss: 0.07854 FastRCNN total loss: 0.18623 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13466 RPN box loss: 0.01467 RPN score loss: 0.00944 RPN total loss: 0.02411 Total loss: 0.90735 timestamp: 1655075931.0912883 iteration: 86245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11321 FastRCNN class loss: 0.03416 FastRCNN total loss: 0.14737 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.10761 RPN box loss: 0.00275 RPN score loss: 0.00264 RPN total loss: 0.00539 Total loss: 0.82272 timestamp: 1655075934.354246 iteration: 86250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07627 FastRCNN class loss: 0.03931 FastRCNN total loss: 0.11559 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14029 RPN box loss: 0.01489 RPN score loss: 0.0025 RPN total loss: 0.01739 Total loss: 0.83561 timestamp: 1655075937.61859 iteration: 86255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08991 FastRCNN class loss: 0.04957 FastRCNN total loss: 0.13948 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.10893 RPN box loss: 0.00468 RPN score loss: 0.00367 RPN total loss: 0.00835 Total loss: 0.8191 timestamp: 1655075940.963575 iteration: 86260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10104 FastRCNN class loss: 0.10211 FastRCNN total loss: 0.20315 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15429 RPN box loss: 0.01564 RPN score loss: 0.00126 RPN total loss: 0.0169 Total loss: 0.93669 timestamp: 1655075944.2642286 iteration: 86265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10094 FastRCNN class loss: 0.07242 FastRCNN total loss: 0.17336 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.16352 RPN box loss: 0.01336 RPN score loss: 0.00688 RPN total loss: 0.02024 Total loss: 0.91947 timestamp: 1655075947.608961 iteration: 86270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09954 FastRCNN class loss: 0.06179 FastRCNN total loss: 0.16133 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14077 RPN box loss: 0.01861 RPN score loss: 0.00551 RPN total loss: 0.02411 Total loss: 0.88856 timestamp: 1655075950.8123317 iteration: 86275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09173 FastRCNN class loss: 0.07384 FastRCNN total loss: 0.16557 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12064 RPN box loss: 0.00729 RPN score loss: 0.00867 RPN total loss: 0.01596 Total loss: 0.86452 timestamp: 1655075954.0921683 iteration: 86280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06696 FastRCNN class loss: 0.0573 FastRCNN total loss: 0.12426 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.12926 RPN box loss: 0.00732 RPN score loss: 0.00146 RPN total loss: 0.00879 Total loss: 0.82465 timestamp: 1655075957.3871489 iteration: 86285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1139 FastRCNN class loss: 0.09723 FastRCNN total loss: 0.21113 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.13208 RPN box loss: 0.0096 RPN score loss: 0.00832 RPN total loss: 0.01792 Total loss: 0.92348 timestamp: 1655075960.5994763 iteration: 86290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0596 FastRCNN class loss: 0.04738 FastRCNN total loss: 0.10698 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.20802 RPN box loss: 0.0224 RPN score loss: 0.00796 RPN total loss: 0.03036 Total loss: 0.9077 timestamp: 1655075963.8807523 iteration: 86295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16386 FastRCNN class loss: 0.07896 FastRCNN total loss: 0.24282 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.14969 RPN box loss: 0.02205 RPN score loss: 0.00689 RPN total loss: 0.02895 Total loss: 0.98381 timestamp: 1655075967.183699 iteration: 86300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12596 FastRCNN class loss: 0.0656 FastRCNN total loss: 0.19155 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.15735 RPN box loss: 0.01994 RPN score loss: 0.00221 RPN total loss: 0.02215 Total loss: 0.93341 timestamp: 1655075970.4679923 iteration: 86305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.11883 FastRCNN total loss: 0.2163 L1 loss: 0.0000e+00 L2 loss: 0.56235 Learning rate: 4.0000e-05 Mask loss: 0.17007 RPN box loss: 0.01483 RPN score loss: 0.00795 RPN total loss: 0.02278 Total loss: 0.9715 timestamp: 1655075973.7524505 iteration: 86310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09633 FastRCNN class loss: 0.08943 FastRCNN total loss: 0.18576 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.22582 RPN box loss: 0.01141 RPN score loss: 0.00605 RPN total loss: 0.01746 Total loss: 0.99139 timestamp: 1655075977.0039823 iteration: 86315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07294 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.13385 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12512 RPN box loss: 0.00502 RPN score loss: 0.00548 RPN total loss: 0.01049 Total loss: 0.83181 timestamp: 1655075980.3055065 iteration: 86320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10127 FastRCNN class loss: 0.10587 FastRCNN total loss: 0.20714 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14929 RPN box loss: 0.01232 RPN score loss: 0.01012 RPN total loss: 0.02244 Total loss: 0.94122 timestamp: 1655075983.541283 iteration: 86325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08989 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.13334 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.1452 RPN box loss: 0.007 RPN score loss: 0.0092 RPN total loss: 0.01621 Total loss: 0.85709 timestamp: 1655075986.732696 iteration: 86330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10843 FastRCNN class loss: 0.07098 FastRCNN total loss: 0.17941 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16601 RPN box loss: 0.01972 RPN score loss: 0.00257 RPN total loss: 0.02229 Total loss: 0.93006 timestamp: 1655075990.0233746 iteration: 86335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10451 FastRCNN class loss: 0.09466 FastRCNN total loss: 0.19917 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16425 RPN box loss: 0.0253 RPN score loss: 0.0083 RPN total loss: 0.0336 Total loss: 0.95936 timestamp: 1655075993.2694647 iteration: 86340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05344 FastRCNN class loss: 0.04069 FastRCNN total loss: 0.09413 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.116 RPN box loss: 0.00648 RPN score loss: 0.00413 RPN total loss: 0.01061 Total loss: 0.78308 timestamp: 1655075996.551094 iteration: 86345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09053 FastRCNN class loss: 0.0703 FastRCNN total loss: 0.16084 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15978 RPN box loss: 0.0216 RPN score loss: 0.00358 RPN total loss: 0.02518 Total loss: 0.90814 timestamp: 1655075999.784288 iteration: 86350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05397 FastRCNN class loss: 0.06201 FastRCNN total loss: 0.11598 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12025 RPN box loss: 0.02024 RPN score loss: 0.00433 RPN total loss: 0.02458 Total loss: 0.82315 timestamp: 1655076003.0903306 iteration: 86355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12651 FastRCNN class loss: 0.12381 FastRCNN total loss: 0.25031 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14252 RPN box loss: 0.02303 RPN score loss: 0.00919 RPN total loss: 0.03222 Total loss: 0.9874 timestamp: 1655076006.3724437 iteration: 86360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15696 FastRCNN class loss: 0.06647 FastRCNN total loss: 0.22343 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12872 RPN box loss: 0.0075 RPN score loss: 0.00365 RPN total loss: 0.01115 Total loss: 0.92565 timestamp: 1655076009.6268473 iteration: 86365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08875 FastRCNN class loss: 0.05728 FastRCNN total loss: 0.14602 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.13774 RPN box loss: 0.01029 RPN score loss: 0.00763 RPN total loss: 0.01792 Total loss: 0.86403 timestamp: 1655076012.9052045 iteration: 86370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10372 FastRCNN class loss: 0.0983 FastRCNN total loss: 0.20202 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14538 RPN box loss: 0.00844 RPN score loss: 0.00165 RPN total loss: 0.01009 Total loss: 0.91984 timestamp: 1655076016.1004941 iteration: 86375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08125 FastRCNN class loss: 0.04687 FastRCNN total loss: 0.12812 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11127 RPN box loss: 0.00416 RPN score loss: 0.0008 RPN total loss: 0.00496 Total loss: 0.8067 timestamp: 1655076019.412345 iteration: 86380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08718 FastRCNN class loss: 0.05911 FastRCNN total loss: 0.14629 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11578 RPN box loss: 0.0141 RPN score loss: 0.00398 RPN total loss: 0.01808 Total loss: 0.84248 timestamp: 1655076022.7200253 iteration: 86385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06118 FastRCNN class loss: 0.05421 FastRCNN total loss: 0.11539 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16691 RPN box loss: 0.01112 RPN score loss: 0.00437 RPN total loss: 0.01549 Total loss: 0.86013 timestamp: 1655076026.0531292 iteration: 86390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06418 FastRCNN class loss: 0.05004 FastRCNN total loss: 0.11423 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15652 RPN box loss: 0.00759 RPN score loss: 0.00792 RPN total loss: 0.01551 Total loss: 0.84861 timestamp: 1655076029.3592772 iteration: 86395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06662 FastRCNN class loss: 0.06467 FastRCNN total loss: 0.1313 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14012 RPN box loss: 0.00821 RPN score loss: 0.004 RPN total loss: 0.01221 Total loss: 0.84597 timestamp: 1655076032.669555 iteration: 86400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07394 FastRCNN class loss: 0.06154 FastRCNN total loss: 0.13548 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14447 RPN box loss: 0.00752 RPN score loss: 0.00333 RPN total loss: 0.01085 Total loss: 0.85315 timestamp: 1655076035.9468021 iteration: 86405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09449 FastRCNN class loss: 0.08266 FastRCNN total loss: 0.17716 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.1535 RPN box loss: 0.01996 RPN score loss: 0.00787 RPN total loss: 0.02782 Total loss: 0.92082 timestamp: 1655076039.2044163 iteration: 86410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07911 FastRCNN class loss: 0.08026 FastRCNN total loss: 0.15937 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.13667 RPN box loss: 0.00839 RPN score loss: 0.00664 RPN total loss: 0.01503 Total loss: 0.87342 timestamp: 1655076042.4935415 iteration: 86415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07043 FastRCNN class loss: 0.06931 FastRCNN total loss: 0.13974 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16899 RPN box loss: 0.02568 RPN score loss: 0.00633 RPN total loss: 0.03201 Total loss: 0.90307 timestamp: 1655076045.7748895 iteration: 86420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0882 FastRCNN class loss: 0.06726 FastRCNN total loss: 0.15546 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12899 RPN box loss: 0.00702 RPN score loss: 0.00249 RPN total loss: 0.0095 Total loss: 0.85629 timestamp: 1655076049.0903652 iteration: 86425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10829 FastRCNN class loss: 0.0881 FastRCNN total loss: 0.19639 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.19146 RPN box loss: 0.01471 RPN score loss: 0.00464 RPN total loss: 0.01935 Total loss: 0.96954 timestamp: 1655076052.3920493 iteration: 86430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08365 FastRCNN class loss: 0.07115 FastRCNN total loss: 0.1548 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12206 RPN box loss: 0.0091 RPN score loss: 0.00741 RPN total loss: 0.01651 Total loss: 0.85572 timestamp: 1655076055.7111425 iteration: 86435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0844 FastRCNN class loss: 0.07871 FastRCNN total loss: 0.16311 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16607 RPN box loss: 0.00612 RPN score loss: 0.00747 RPN total loss: 0.01359 Total loss: 0.90511 timestamp: 1655076058.9304426 iteration: 86440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08635 FastRCNN class loss: 0.06982 FastRCNN total loss: 0.15618 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14442 RPN box loss: 0.01197 RPN score loss: 0.00296 RPN total loss: 0.01493 Total loss: 0.87787 timestamp: 1655076062.1265538 iteration: 86445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14052 FastRCNN class loss: 0.06736 FastRCNN total loss: 0.20788 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16204 RPN box loss: 0.01258 RPN score loss: 0.00161 RPN total loss: 0.01418 Total loss: 0.94644 timestamp: 1655076065.4442525 iteration: 86450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10975 FastRCNN class loss: 0.0974 FastRCNN total loss: 0.20715 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.19685 RPN box loss: 0.00661 RPN score loss: 0.00837 RPN total loss: 0.01498 Total loss: 0.98132 timestamp: 1655076068.7254915 iteration: 86455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0786 FastRCNN class loss: 0.06549 FastRCNN total loss: 0.14409 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15484 RPN box loss: 0.00942 RPN score loss: 0.00385 RPN total loss: 0.01328 Total loss: 0.87455 timestamp: 1655076071.9572442 iteration: 86460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14141 FastRCNN class loss: 0.05467 FastRCNN total loss: 0.19608 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12813 RPN box loss: 0.0156 RPN score loss: 0.00914 RPN total loss: 0.02474 Total loss: 0.91129 timestamp: 1655076075.2125328 iteration: 86465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15333 FastRCNN class loss: 0.07302 FastRCNN total loss: 0.22635 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15058 RPN box loss: 0.01224 RPN score loss: 0.00553 RPN total loss: 0.01777 Total loss: 0.95705 timestamp: 1655076078.4704936 iteration: 86470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09473 FastRCNN class loss: 0.06688 FastRCNN total loss: 0.16161 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.18846 RPN box loss: 0.00669 RPN score loss: 0.00383 RPN total loss: 0.01052 Total loss: 0.92294 timestamp: 1655076081.7207882 iteration: 86475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07322 FastRCNN class loss: 0.05461 FastRCNN total loss: 0.12783 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11122 RPN box loss: 0.01167 RPN score loss: 0.00535 RPN total loss: 0.01702 Total loss: 0.8184 timestamp: 1655076085.0409164 iteration: 86480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14673 FastRCNN class loss: 0.06423 FastRCNN total loss: 0.21096 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.10289 RPN box loss: 0.0064 RPN score loss: 0.00095 RPN total loss: 0.00735 Total loss: 0.88354 timestamp: 1655076088.2850974 iteration: 86485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08482 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.14578 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14144 RPN box loss: 0.01016 RPN score loss: 0.00125 RPN total loss: 0.01141 Total loss: 0.86097 timestamp: 1655076091.5466092 iteration: 86490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1385 FastRCNN class loss: 0.07923 FastRCNN total loss: 0.21773 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15123 RPN box loss: 0.01346 RPN score loss: 0.01281 RPN total loss: 0.02627 Total loss: 0.95757 timestamp: 1655076094.7799501 iteration: 86495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14298 FastRCNN class loss: 0.07592 FastRCNN total loss: 0.2189 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.15442 RPN box loss: 0.01056 RPN score loss: 0.00379 RPN total loss: 0.01435 Total loss: 0.95001 timestamp: 1655076098.1271102 iteration: 86500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07446 FastRCNN class loss: 0.05061 FastRCNN total loss: 0.12507 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14369 RPN box loss: 0.01554 RPN score loss: 0.00276 RPN total loss: 0.0183 Total loss: 0.8494 timestamp: 1655076101.4151483 iteration: 86505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05541 FastRCNN class loss: 0.06525 FastRCNN total loss: 0.12066 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.17359 RPN box loss: 0.01969 RPN score loss: 0.00692 RPN total loss: 0.02661 Total loss: 0.8832 timestamp: 1655076104.6924698 iteration: 86510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10533 FastRCNN class loss: 0.06046 FastRCNN total loss: 0.16579 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11839 RPN box loss: 0.00609 RPN score loss: 0.00595 RPN total loss: 0.01204 Total loss: 0.85856 timestamp: 1655076107.9002984 iteration: 86515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09088 FastRCNN class loss: 0.06236 FastRCNN total loss: 0.15324 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14075 RPN box loss: 0.01083 RPN score loss: 0.00439 RPN total loss: 0.01523 Total loss: 0.87155 timestamp: 1655076111.150947 iteration: 86520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0888 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.16518 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.13076 RPN box loss: 0.00721 RPN score loss: 0.00261 RPN total loss: 0.00982 Total loss: 0.86809 timestamp: 1655076114.4254975 iteration: 86525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09523 FastRCNN class loss: 0.08052 FastRCNN total loss: 0.17576 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.17875 RPN box loss: 0.00776 RPN score loss: 0.00206 RPN total loss: 0.00981 Total loss: 0.92666 timestamp: 1655076117.774689 iteration: 86530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07577 FastRCNN class loss: 0.07234 FastRCNN total loss: 0.14811 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11166 RPN box loss: 0.00567 RPN score loss: 0.00629 RPN total loss: 0.01196 Total loss: 0.83406 timestamp: 1655076121.0860338 iteration: 86535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.08781 FastRCNN total loss: 0.19306 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.17789 RPN box loss: 0.01402 RPN score loss: 0.00503 RPN total loss: 0.01906 Total loss: 0.95234 timestamp: 1655076124.33687 iteration: 86540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09746 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.18067 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.19199 RPN box loss: 0.0058 RPN score loss: 0.00729 RPN total loss: 0.01308 Total loss: 0.94808 timestamp: 1655076127.6231377 iteration: 86545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14924 FastRCNN class loss: 0.11558 FastRCNN total loss: 0.26482 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.22212 RPN box loss: 0.0336 RPN score loss: 0.02887 RPN total loss: 0.06247 Total loss: 1.11174 timestamp: 1655076130.8937917 iteration: 86550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06781 FastRCNN class loss: 0.04662 FastRCNN total loss: 0.11443 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11674 RPN box loss: 0.00481 RPN score loss: 0.00702 RPN total loss: 0.01183 Total loss: 0.80533 timestamp: 1655076134.0928361 iteration: 86555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04727 FastRCNN class loss: 0.05187 FastRCNN total loss: 0.09914 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12845 RPN box loss: 0.00404 RPN score loss: 0.00207 RPN total loss: 0.00611 Total loss: 0.79604 timestamp: 1655076137.4521902 iteration: 86560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06776 FastRCNN class loss: 0.05495 FastRCNN total loss: 0.1227 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.13638 RPN box loss: 0.01123 RPN score loss: 0.00301 RPN total loss: 0.01424 Total loss: 0.83566 timestamp: 1655076140.6910405 iteration: 86565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05728 FastRCNN class loss: 0.0511 FastRCNN total loss: 0.10838 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12724 RPN box loss: 0.01389 RPN score loss: 0.00274 RPN total loss: 0.01663 Total loss: 0.81459 timestamp: 1655076143.9370685 iteration: 86570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04499 FastRCNN class loss: 0.05425 FastRCNN total loss: 0.09924 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11997 RPN box loss: 0.00971 RPN score loss: 0.00236 RPN total loss: 0.01207 Total loss: 0.79362 timestamp: 1655076147.243618 iteration: 86575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05046 FastRCNN class loss: 0.04163 FastRCNN total loss: 0.0921 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12316 RPN box loss: 0.01475 RPN score loss: 0.00212 RPN total loss: 0.01687 Total loss: 0.79446 timestamp: 1655076150.5106971 iteration: 86580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05456 FastRCNN class loss: 0.03342 FastRCNN total loss: 0.08798 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11549 RPN box loss: 0.00503 RPN score loss: 0.00127 RPN total loss: 0.0063 Total loss: 0.77211 timestamp: 1655076153.818516 iteration: 86585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09516 FastRCNN class loss: 0.07996 FastRCNN total loss: 0.17512 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.13127 RPN box loss: 0.01568 RPN score loss: 0.0051 RPN total loss: 0.02078 Total loss: 0.88951 timestamp: 1655076157.1015003 iteration: 86590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08295 FastRCNN class loss: 0.05687 FastRCNN total loss: 0.13982 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16306 RPN box loss: 0.00732 RPN score loss: 0.00476 RPN total loss: 0.01207 Total loss: 0.87729 timestamp: 1655076160.366678 iteration: 86595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13218 FastRCNN class loss: 0.07299 FastRCNN total loss: 0.20517 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.14961 RPN box loss: 0.01132 RPN score loss: 0.00676 RPN total loss: 0.01808 Total loss: 0.93519 timestamp: 1655076163.6099572 iteration: 86600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09089 FastRCNN class loss: 0.08088 FastRCNN total loss: 0.17177 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.12686 RPN box loss: 0.02562 RPN score loss: 0.01209 RPN total loss: 0.03771 Total loss: 0.89868 timestamp: 1655076166.8645391 iteration: 86605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04655 FastRCNN class loss: 0.05284 FastRCNN total loss: 0.09939 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11344 RPN box loss: 0.00441 RPN score loss: 0.00408 RPN total loss: 0.0085 Total loss: 0.78366 timestamp: 1655076170.1514149 iteration: 86610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14179 FastRCNN class loss: 0.0656 FastRCNN total loss: 0.20739 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.11024 RPN box loss: 0.01583 RPN score loss: 0.00605 RPN total loss: 0.02188 Total loss: 0.90185 timestamp: 1655076173.4362352 iteration: 86615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07979 FastRCNN class loss: 0.10154 FastRCNN total loss: 0.18134 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.16631 RPN box loss: 0.01306 RPN score loss: 0.00783 RPN total loss: 0.02089 Total loss: 0.93088 timestamp: 1655076176.7676747 iteration: 86620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11453 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.18296 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.1084 RPN box loss: 0.00865 RPN score loss: 0.00555 RPN total loss: 0.0142 Total loss: 0.86789 timestamp: 1655076180.0721831 iteration: 86625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0886 FastRCNN class loss: 0.06297 FastRCNN total loss: 0.15157 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.17558 RPN box loss: 0.00897 RPN score loss: 0.0076 RPN total loss: 0.01657 Total loss: 0.90605 timestamp: 1655076183.3541114 iteration: 86630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07114 FastRCNN class loss: 0.05401 FastRCNN total loss: 0.12515 L1 loss: 0.0000e+00 L2 loss: 0.56234 Learning rate: 4.0000e-05 Mask loss: 0.21544 RPN box loss: 0.01279 RPN score loss: 0.00249 RPN total loss: 0.01528 Total loss: 0.91821 timestamp: 1655076186.6238158 iteration: 86635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06084 FastRCNN class loss: 0.04197 FastRCNN total loss: 0.1028 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10581 RPN box loss: 0.00728 RPN score loss: 0.00937 RPN total loss: 0.01665 Total loss: 0.7876 timestamp: 1655076189.8618455 iteration: 86640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09847 FastRCNN class loss: 0.07196 FastRCNN total loss: 0.17043 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.14877 RPN box loss: 0.01913 RPN score loss: 0.01249 RPN total loss: 0.03163 Total loss: 0.91316 timestamp: 1655076193.1353018 iteration: 86645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10477 FastRCNN class loss: 0.10434 FastRCNN total loss: 0.20911 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.17033 RPN box loss: 0.01675 RPN score loss: 0.00891 RPN total loss: 0.02566 Total loss: 0.96744 timestamp: 1655076196.3443549 iteration: 86650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16042 FastRCNN class loss: 0.09006 FastRCNN total loss: 0.25048 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12899 RPN box loss: 0.02645 RPN score loss: 0.0146 RPN total loss: 0.04105 Total loss: 0.98286 timestamp: 1655076199.6105986 iteration: 86655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07126 FastRCNN class loss: 0.07229 FastRCNN total loss: 0.14355 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12139 RPN box loss: 0.00881 RPN score loss: 0.00506 RPN total loss: 0.01387 Total loss: 0.84115 timestamp: 1655076202.8508594 iteration: 86660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07677 FastRCNN class loss: 0.0538 FastRCNN total loss: 0.13057 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.107 RPN box loss: 0.03393 RPN score loss: 0.00204 RPN total loss: 0.03597 Total loss: 0.83588 timestamp: 1655076206.0351052 iteration: 86665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08261 FastRCNN class loss: 0.05388 FastRCNN total loss: 0.13649 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15319 RPN box loss: 0.00614 RPN score loss: 0.00346 RPN total loss: 0.0096 Total loss: 0.86162 timestamp: 1655076209.2485788 iteration: 86670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.091 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.15819 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15365 RPN box loss: 0.00568 RPN score loss: 0.00339 RPN total loss: 0.00908 Total loss: 0.88325 timestamp: 1655076212.543525 iteration: 86675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13811 FastRCNN class loss: 0.08793 FastRCNN total loss: 0.22603 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15618 RPN box loss: 0.00687 RPN score loss: 0.00378 RPN total loss: 0.01065 Total loss: 0.95519 timestamp: 1655076215.8623378 iteration: 86680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08413 FastRCNN class loss: 0.04588 FastRCNN total loss: 0.13002 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.14111 RPN box loss: 0.0069 RPN score loss: 0.00806 RPN total loss: 0.01496 Total loss: 0.84841 timestamp: 1655076219.1685264 iteration: 86685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09434 FastRCNN class loss: 0.08161 FastRCNN total loss: 0.17595 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15865 RPN box loss: 0.02384 RPN score loss: 0.00333 RPN total loss: 0.02717 Total loss: 0.9241 timestamp: 1655076222.4742222 iteration: 86690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14208 FastRCNN class loss: 0.07963 FastRCNN total loss: 0.22171 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12231 RPN box loss: 0.01175 RPN score loss: 0.00551 RPN total loss: 0.01726 Total loss: 0.92361 timestamp: 1655076225.7286417 iteration: 86695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14039 FastRCNN class loss: 0.07566 FastRCNN total loss: 0.21605 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.21453 RPN box loss: 0.01824 RPN score loss: 0.00379 RPN total loss: 0.02203 Total loss: 1.01495 timestamp: 1655076228.9901524 iteration: 86700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07581 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.13591 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.17298 RPN box loss: 0.00856 RPN score loss: 0.00144 RPN total loss: 0.01 Total loss: 0.88122 timestamp: 1655076232.3086014 iteration: 86705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07381 FastRCNN class loss: 0.08 FastRCNN total loss: 0.15381 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.11046 RPN box loss: 0.0048 RPN score loss: 0.00357 RPN total loss: 0.00836 Total loss: 0.83497 timestamp: 1655076235.6283371 iteration: 86710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06443 FastRCNN class loss: 0.05795 FastRCNN total loss: 0.12239 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.16832 RPN box loss: 0.06623 RPN score loss: 0.00619 RPN total loss: 0.07242 Total loss: 0.92546 timestamp: 1655076238.9538772 iteration: 86715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09716 FastRCNN class loss: 0.06719 FastRCNN total loss: 0.16435 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.166 RPN box loss: 0.01393 RPN score loss: 0.00844 RPN total loss: 0.02237 Total loss: 0.91506 timestamp: 1655076242.2567027 iteration: 86720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09695 FastRCNN class loss: 0.07246 FastRCNN total loss: 0.16942 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.1435 RPN box loss: 0.02376 RPN score loss: 0.00238 RPN total loss: 0.02614 Total loss: 0.90139 timestamp: 1655076245.5023165 iteration: 86725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09472 FastRCNN class loss: 0.08064 FastRCNN total loss: 0.17536 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13667 RPN box loss: 0.01752 RPN score loss: 0.00691 RPN total loss: 0.02443 Total loss: 0.89879 timestamp: 1655076248.7596827 iteration: 86730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11249 FastRCNN class loss: 0.09128 FastRCNN total loss: 0.20377 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.20573 RPN box loss: 0.02042 RPN score loss: 0.00677 RPN total loss: 0.02719 Total loss: 0.99902 timestamp: 1655076252.0076787 iteration: 86735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08655 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.14102 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.07816 RPN box loss: 0.02966 RPN score loss: 0.00239 RPN total loss: 0.03204 Total loss: 0.81355 timestamp: 1655076255.306525 iteration: 86740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07975 FastRCNN class loss: 0.08057 FastRCNN total loss: 0.16032 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.21394 RPN box loss: 0.02196 RPN score loss: 0.00186 RPN total loss: 0.02382 Total loss: 0.96042 timestamp: 1655076258.5226269 iteration: 86745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10401 FastRCNN class loss: 0.05044 FastRCNN total loss: 0.15445 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.09399 RPN box loss: 0.01105 RPN score loss: 0.00358 RPN total loss: 0.01463 Total loss: 0.8254 timestamp: 1655076261.7623591 iteration: 86750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12794 FastRCNN class loss: 0.09461 FastRCNN total loss: 0.22255 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12296 RPN box loss: 0.00653 RPN score loss: 0.00218 RPN total loss: 0.00871 Total loss: 0.91655 timestamp: 1655076265.0372639 iteration: 86755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07043 FastRCNN class loss: 0.07219 FastRCNN total loss: 0.14262 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13095 RPN box loss: 0.00822 RPN score loss: 0.00572 RPN total loss: 0.01394 Total loss: 0.84983 timestamp: 1655076268.2994726 iteration: 86760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06933 FastRCNN class loss: 0.03478 FastRCNN total loss: 0.1041 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.09917 RPN box loss: 0.02659 RPN score loss: 0.00181 RPN total loss: 0.0284 Total loss: 0.794 timestamp: 1655076271.6074305 iteration: 86765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07166 FastRCNN class loss: 0.06574 FastRCNN total loss: 0.1374 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13432 RPN box loss: 0.01536 RPN score loss: 0.00533 RPN total loss: 0.02069 Total loss: 0.85474 timestamp: 1655076274.9098651 iteration: 86770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09456 FastRCNN class loss: 0.07938 FastRCNN total loss: 0.17395 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13722 RPN box loss: 0.01218 RPN score loss: 0.01158 RPN total loss: 0.02376 Total loss: 0.89725 timestamp: 1655076278.2143943 iteration: 86775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09552 FastRCNN class loss: 0.1047 FastRCNN total loss: 0.20022 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.1461 RPN box loss: 0.00728 RPN score loss: 0.00529 RPN total loss: 0.01257 Total loss: 0.92121 timestamp: 1655076281.552631 iteration: 86780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06863 FastRCNN class loss: 0.04736 FastRCNN total loss: 0.11599 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.21273 RPN box loss: 0.00704 RPN score loss: 0.00342 RPN total loss: 0.01046 Total loss: 0.90151 timestamp: 1655076284.8637238 iteration: 86785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09169 FastRCNN class loss: 0.08401 FastRCNN total loss: 0.1757 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.09208 RPN box loss: 0.00796 RPN score loss: 0.00708 RPN total loss: 0.01504 Total loss: 0.84514 timestamp: 1655076288.096695 iteration: 86790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07028 FastRCNN class loss: 0.0434 FastRCNN total loss: 0.11369 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12106 RPN box loss: 0.00692 RPN score loss: 0.00867 RPN total loss: 0.01559 Total loss: 0.81267 timestamp: 1655076291.3883376 iteration: 86795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14215 FastRCNN class loss: 0.10085 FastRCNN total loss: 0.243 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13322 RPN box loss: 0.00917 RPN score loss: 0.0016 RPN total loss: 0.01077 Total loss: 0.94931 timestamp: 1655076294.7442808 iteration: 86800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07195 FastRCNN class loss: 0.04448 FastRCNN total loss: 0.11643 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.16532 RPN box loss: 0.0121 RPN score loss: 0.00176 RPN total loss: 0.01387 Total loss: 0.85794 timestamp: 1655076297.996968 iteration: 86805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06763 FastRCNN class loss: 0.04907 FastRCNN total loss: 0.11671 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.1305 RPN box loss: 0.00617 RPN score loss: 0.00493 RPN total loss: 0.0111 Total loss: 0.82064 timestamp: 1655076301.3329523 iteration: 86810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04308 FastRCNN class loss: 0.048 FastRCNN total loss: 0.09107 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.16496 RPN box loss: 0.01813 RPN score loss: 0.0039 RPN total loss: 0.02203 Total loss: 0.84039 timestamp: 1655076304.5831065 iteration: 86815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07153 FastRCNN class loss: 0.08446 FastRCNN total loss: 0.15599 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.17673 RPN box loss: 0.01208 RPN score loss: 0.00424 RPN total loss: 0.01632 Total loss: 0.91137 timestamp: 1655076307.916134 iteration: 86820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08825 FastRCNN class loss: 0.04101 FastRCNN total loss: 0.12926 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10212 RPN box loss: 0.00428 RPN score loss: 0.00568 RPN total loss: 0.00996 Total loss: 0.80367 timestamp: 1655076311.215159 iteration: 86825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.06672 FastRCNN total loss: 0.17479 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13594 RPN box loss: 0.02667 RPN score loss: 0.00146 RPN total loss: 0.02813 Total loss: 0.9012 timestamp: 1655076314.5230088 iteration: 86830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09201 FastRCNN class loss: 0.07904 FastRCNN total loss: 0.17105 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.11159 RPN box loss: 0.01187 RPN score loss: 0.00538 RPN total loss: 0.01726 Total loss: 0.86223 timestamp: 1655076317.8169317 iteration: 86835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1048 FastRCNN class loss: 0.08598 FastRCNN total loss: 0.19078 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.14205 RPN box loss: 0.01743 RPN score loss: 0.00638 RPN total loss: 0.02382 Total loss: 0.91897 timestamp: 1655076321.0189352 iteration: 86840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06442 FastRCNN class loss: 0.04634 FastRCNN total loss: 0.11076 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15873 RPN box loss: 0.01096 RPN score loss: 0.00539 RPN total loss: 0.01634 Total loss: 0.84817 timestamp: 1655076324.344098 iteration: 86845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10619 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.18939 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13484 RPN box loss: 0.00521 RPN score loss: 0.00282 RPN total loss: 0.00803 Total loss: 0.89458 timestamp: 1655076327.5967624 iteration: 86850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08364 FastRCNN class loss: 0.05467 FastRCNN total loss: 0.13832 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12612 RPN box loss: 0.00411 RPN score loss: 0.00402 RPN total loss: 0.00813 Total loss: 0.83489 timestamp: 1655076330.9175534 iteration: 86855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06044 FastRCNN class loss: 0.03883 FastRCNN total loss: 0.09927 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.21539 RPN box loss: 0.01961 RPN score loss: 0.00112 RPN total loss: 0.02073 Total loss: 0.89772 timestamp: 1655076334.2061954 iteration: 86860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08376 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.1536 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12579 RPN box loss: 0.0186 RPN score loss: 0.00268 RPN total loss: 0.02128 Total loss: 0.863 timestamp: 1655076337.4597406 iteration: 86865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15227 FastRCNN class loss: 0.07599 FastRCNN total loss: 0.22826 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.17756 RPN box loss: 0.01126 RPN score loss: 0.00898 RPN total loss: 0.02024 Total loss: 0.98839 timestamp: 1655076340.6983767 iteration: 86870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07836 FastRCNN class loss: 0.04125 FastRCNN total loss: 0.11961 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13807 RPN box loss: 0.01001 RPN score loss: 0.00399 RPN total loss: 0.014 Total loss: 0.83401 timestamp: 1655076344.0020862 iteration: 86875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08171 FastRCNN class loss: 0.04261 FastRCNN total loss: 0.12433 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.0946 RPN box loss: 0.00714 RPN score loss: 0.0022 RPN total loss: 0.00935 Total loss: 0.79059 timestamp: 1655076347.2321093 iteration: 86880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09721 FastRCNN class loss: 0.06239 FastRCNN total loss: 0.1596 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10988 RPN box loss: 0.00975 RPN score loss: 0.00557 RPN total loss: 0.01532 Total loss: 0.84712 timestamp: 1655076350.4758759 iteration: 86885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08113 FastRCNN class loss: 0.04804 FastRCNN total loss: 0.12917 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12123 RPN box loss: 0.00643 RPN score loss: 0.00503 RPN total loss: 0.01146 Total loss: 0.82418 timestamp: 1655076353.7133634 iteration: 86890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08779 FastRCNN class loss: 0.06098 FastRCNN total loss: 0.14877 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10247 RPN box loss: 0.00575 RPN score loss: 0.00877 RPN total loss: 0.01452 Total loss: 0.82809 timestamp: 1655076356.9749086 iteration: 86895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08368 FastRCNN class loss: 0.0753 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15369 RPN box loss: 0.04345 RPN score loss: 0.00718 RPN total loss: 0.05063 Total loss: 0.92562 timestamp: 1655076360.2861347 iteration: 86900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12198 FastRCNN class loss: 0.08028 FastRCNN total loss: 0.20226 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.16923 RPN box loss: 0.01879 RPN score loss: 0.01265 RPN total loss: 0.03143 Total loss: 0.96525 timestamp: 1655076363.547839 iteration: 86905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07412 FastRCNN class loss: 0.06061 FastRCNN total loss: 0.13473 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10594 RPN box loss: 0.01648 RPN score loss: 0.00178 RPN total loss: 0.01825 Total loss: 0.82125 timestamp: 1655076366.769834 iteration: 86910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0913 FastRCNN class loss: 0.07792 FastRCNN total loss: 0.16921 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13963 RPN box loss: 0.00755 RPN score loss: 0.00555 RPN total loss: 0.0131 Total loss: 0.88427 timestamp: 1655076370.0613542 iteration: 86915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12514 FastRCNN class loss: 0.11015 FastRCNN total loss: 0.23529 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.19092 RPN box loss: 0.01588 RPN score loss: 0.00695 RPN total loss: 0.02283 Total loss: 1.01137 timestamp: 1655076373.287099 iteration: 86920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05613 FastRCNN class loss: 0.03741 FastRCNN total loss: 0.09354 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.12745 RPN box loss: 0.00778 RPN score loss: 0.00624 RPN total loss: 0.01402 Total loss: 0.79734 timestamp: 1655076376.563032 iteration: 86925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06839 FastRCNN class loss: 0.04248 FastRCNN total loss: 0.11087 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.13453 RPN box loss: 0.00996 RPN score loss: 0.0026 RPN total loss: 0.01256 Total loss: 0.82029 timestamp: 1655076379.860367 iteration: 86930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10652 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.19288 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.18494 RPN box loss: 0.01143 RPN score loss: 0.00645 RPN total loss: 0.01788 Total loss: 0.95803 timestamp: 1655076383.1505184 iteration: 86935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09142 FastRCNN class loss: 0.04722 FastRCNN total loss: 0.13864 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.10082 RPN box loss: 0.00663 RPN score loss: 0.0023 RPN total loss: 0.00893 Total loss: 0.81073 timestamp: 1655076386.4419816 iteration: 86940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10525 FastRCNN class loss: 0.05602 FastRCNN total loss: 0.16127 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.16369 RPN box loss: 0.01525 RPN score loss: 0.01035 RPN total loss: 0.0256 Total loss: 0.91289 timestamp: 1655076389.729582 iteration: 86945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08749 FastRCNN class loss: 0.09044 FastRCNN total loss: 0.17793 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.15631 RPN box loss: 0.02231 RPN score loss: 0.00829 RPN total loss: 0.03059 Total loss: 0.92715 timestamp: 1655076392.947822 iteration: 86950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10852 FastRCNN class loss: 0.08898 FastRCNN total loss: 0.1975 L1 loss: 0.0000e+00 L2 loss: 0.56233 Learning rate: 4.0000e-05 Mask loss: 0.20302 RPN box loss: 0.0063 RPN score loss: 0.00491 RPN total loss: 0.0112 Total loss: 0.97404 timestamp: 1655076396.252608 iteration: 86955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05037 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.10971 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13078 RPN box loss: 0.003 RPN score loss: 0.00832 RPN total loss: 0.01133 Total loss: 0.81414 timestamp: 1655076399.5364583 iteration: 86960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16977 FastRCNN class loss: 0.05846 FastRCNN total loss: 0.22823 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.11102 RPN box loss: 0.0079 RPN score loss: 0.00579 RPN total loss: 0.01369 Total loss: 0.91526 timestamp: 1655076402.788685 iteration: 86965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16034 FastRCNN class loss: 0.10491 FastRCNN total loss: 0.26525 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.17082 RPN box loss: 0.01669 RPN score loss: 0.01051 RPN total loss: 0.0272 Total loss: 1.02559 timestamp: 1655076406.0139716 iteration: 86970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11928 FastRCNN class loss: 0.11212 FastRCNN total loss: 0.23141 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.18951 RPN box loss: 0.01024 RPN score loss: 0.00345 RPN total loss: 0.01369 Total loss: 0.99694 timestamp: 1655076409.2457318 iteration: 86975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07892 FastRCNN class loss: 0.05866 FastRCNN total loss: 0.13759 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.15151 RPN box loss: 0.00623 RPN score loss: 0.00472 RPN total loss: 0.01096 Total loss: 0.86237 timestamp: 1655076412.5055108 iteration: 86980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10391 FastRCNN class loss: 0.06579 FastRCNN total loss: 0.1697 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14133 RPN box loss: 0.01203 RPN score loss: 0.00658 RPN total loss: 0.01861 Total loss: 0.89197 timestamp: 1655076415.8458664 iteration: 86985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0814 FastRCNN class loss: 0.06266 FastRCNN total loss: 0.14406 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14305 RPN box loss: 0.01218 RPN score loss: 0.00325 RPN total loss: 0.01542 Total loss: 0.86486 timestamp: 1655076419.1077166 iteration: 86990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0822 FastRCNN class loss: 0.06643 FastRCNN total loss: 0.14863 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14727 RPN box loss: 0.01598 RPN score loss: 0.00395 RPN total loss: 0.01993 Total loss: 0.87815 timestamp: 1655076422.3534195 iteration: 86995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12351 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.17233 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13978 RPN box loss: 0.01454 RPN score loss: 0.00265 RPN total loss: 0.0172 Total loss: 0.89163 timestamp: 1655076425.6691172 iteration: 87000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12839 FastRCNN class loss: 0.08291 FastRCNN total loss: 0.2113 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.11453 RPN box loss: 0.01458 RPN score loss: 0.00332 RPN total loss: 0.0179 Total loss: 0.90605 timestamp: 1655076428.9656632 iteration: 87005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05981 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.10174 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.10944 RPN box loss: 0.01554 RPN score loss: 0.00386 RPN total loss: 0.0194 Total loss: 0.79291 timestamp: 1655076432.207936 iteration: 87010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04934 FastRCNN class loss: 0.0551 FastRCNN total loss: 0.10444 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1217 RPN box loss: 0.01444 RPN score loss: 0.00173 RPN total loss: 0.01617 Total loss: 0.80463 timestamp: 1655076435.508078 iteration: 87015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12028 FastRCNN class loss: 0.04981 FastRCNN total loss: 0.17008 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.08745 RPN box loss: 0.01995 RPN score loss: 0.00536 RPN total loss: 0.02532 Total loss: 0.84518 timestamp: 1655076438.7369306 iteration: 87020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07498 FastRCNN class loss: 0.04355 FastRCNN total loss: 0.11854 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12627 RPN box loss: 0.02346 RPN score loss: 0.00601 RPN total loss: 0.02947 Total loss: 0.8366 timestamp: 1655076442.075521 iteration: 87025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10832 FastRCNN class loss: 0.05376 FastRCNN total loss: 0.16208 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.08246 RPN box loss: 0.00663 RPN score loss: 0.00273 RPN total loss: 0.00936 Total loss: 0.81622 timestamp: 1655076445.350221 iteration: 87030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08953 FastRCNN class loss: 0.08208 FastRCNN total loss: 0.17161 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12649 RPN box loss: 0.0058 RPN score loss: 0.00336 RPN total loss: 0.00916 Total loss: 0.86958 timestamp: 1655076448.5785294 iteration: 87035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14279 FastRCNN class loss: 0.0884 FastRCNN total loss: 0.23119 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13762 RPN box loss: 0.0178 RPN score loss: 0.00905 RPN total loss: 0.02685 Total loss: 0.95798 timestamp: 1655076451.7514803 iteration: 87040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08452 FastRCNN class loss: 0.05375 FastRCNN total loss: 0.13826 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13336 RPN box loss: 0.01071 RPN score loss: 0.00367 RPN total loss: 0.01438 Total loss: 0.84832 timestamp: 1655076455.0248396 iteration: 87045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11003 FastRCNN class loss: 0.08243 FastRCNN total loss: 0.19246 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1882 RPN box loss: 0.00789 RPN score loss: 0.00552 RPN total loss: 0.01341 Total loss: 0.95639 timestamp: 1655076458.2869027 iteration: 87050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11677 FastRCNN class loss: 0.07081 FastRCNN total loss: 0.18758 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14893 RPN box loss: 0.01386 RPN score loss: 0.00483 RPN total loss: 0.01869 Total loss: 0.91752 timestamp: 1655076461.5630915 iteration: 87055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10229 FastRCNN class loss: 0.07088 FastRCNN total loss: 0.17317 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13428 RPN box loss: 0.0282 RPN score loss: 0.00544 RPN total loss: 0.03364 Total loss: 0.90342 timestamp: 1655076464.8363147 iteration: 87060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07337 FastRCNN class loss: 0.05765 FastRCNN total loss: 0.13102 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.15759 RPN box loss: 0.00801 RPN score loss: 0.00178 RPN total loss: 0.00979 Total loss: 0.86072 timestamp: 1655076468.052566 iteration: 87065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04641 FastRCNN class loss: 0.05194 FastRCNN total loss: 0.09835 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1556 RPN box loss: 0.00338 RPN score loss: 0.00625 RPN total loss: 0.00963 Total loss: 0.82591 timestamp: 1655076471.340271 iteration: 87070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11412 FastRCNN class loss: 0.06376 FastRCNN total loss: 0.17788 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.19021 RPN box loss: 0.00731 RPN score loss: 0.00468 RPN total loss: 0.01199 Total loss: 0.9424 timestamp: 1655076474.5423014 iteration: 87075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06146 FastRCNN class loss: 0.04758 FastRCNN total loss: 0.10903 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.21776 RPN box loss: 0.01233 RPN score loss: 0.00123 RPN total loss: 0.01356 Total loss: 0.90267 timestamp: 1655076477.8323479 iteration: 87080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08214 FastRCNN class loss: 0.06185 FastRCNN total loss: 0.14399 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.16418 RPN box loss: 0.00584 RPN score loss: 0.00242 RPN total loss: 0.00826 Total loss: 0.87875 timestamp: 1655076481.122214 iteration: 87085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14265 FastRCNN class loss: 0.10919 FastRCNN total loss: 0.25184 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.18074 RPN box loss: 0.01285 RPN score loss: 0.00637 RPN total loss: 0.01922 Total loss: 1.01412 timestamp: 1655076484.3936825 iteration: 87090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08998 FastRCNN class loss: 0.06476 FastRCNN total loss: 0.15475 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12621 RPN box loss: 0.01656 RPN score loss: 0.00294 RPN total loss: 0.01951 Total loss: 0.86278 timestamp: 1655076487.6473475 iteration: 87095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05969 FastRCNN class loss: 0.06846 FastRCNN total loss: 0.12815 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14157 RPN box loss: 0.01023 RPN score loss: 0.00702 RPN total loss: 0.01725 Total loss: 0.84929 timestamp: 1655076490.9083374 iteration: 87100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06714 FastRCNN class loss: 0.07477 FastRCNN total loss: 0.14191 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.21492 RPN box loss: 0.01722 RPN score loss: 0.00905 RPN total loss: 0.02627 Total loss: 0.94542 timestamp: 1655076494.1496763 iteration: 87105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07583 FastRCNN class loss: 0.04194 FastRCNN total loss: 0.11777 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14265 RPN box loss: 0.00399 RPN score loss: 0.00347 RPN total loss: 0.00745 Total loss: 0.8302 timestamp: 1655076497.3920631 iteration: 87110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06216 FastRCNN class loss: 0.03235 FastRCNN total loss: 0.09451 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.09327 RPN box loss: 0.00365 RPN score loss: 0.00159 RPN total loss: 0.00524 Total loss: 0.75534 timestamp: 1655076500.6810434 iteration: 87115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11861 FastRCNN class loss: 0.05632 FastRCNN total loss: 0.17494 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12774 RPN box loss: 0.01059 RPN score loss: 0.00194 RPN total loss: 0.01252 Total loss: 0.87752 timestamp: 1655076503.9155853 iteration: 87120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10454 FastRCNN class loss: 0.10517 FastRCNN total loss: 0.20971 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14019 RPN box loss: 0.01321 RPN score loss: 0.01339 RPN total loss: 0.0266 Total loss: 0.93881 timestamp: 1655076507.2271 iteration: 87125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10624 FastRCNN class loss: 0.06975 FastRCNN total loss: 0.17598 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14763 RPN box loss: 0.00758 RPN score loss: 0.00188 RPN total loss: 0.00946 Total loss: 0.89539 timestamp: 1655076510.5084555 iteration: 87130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.06306 FastRCNN total loss: 0.15683 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14032 RPN box loss: 0.01182 RPN score loss: 0.00297 RPN total loss: 0.01479 Total loss: 0.87426 timestamp: 1655076513.7539701 iteration: 87135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11258 FastRCNN class loss: 0.08661 FastRCNN total loss: 0.19919 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12119 RPN box loss: 0.03913 RPN score loss: 0.00716 RPN total loss: 0.04629 Total loss: 0.92899 timestamp: 1655076516.9806209 iteration: 87140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06162 FastRCNN class loss: 0.06271 FastRCNN total loss: 0.12432 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13842 RPN box loss: 0.00789 RPN score loss: 0.0029 RPN total loss: 0.01079 Total loss: 0.83585 timestamp: 1655076520.3479247 iteration: 87145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12743 FastRCNN class loss: 0.0886 FastRCNN total loss: 0.21603 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1819 RPN box loss: 0.01155 RPN score loss: 0.00653 RPN total loss: 0.01807 Total loss: 0.97832 timestamp: 1655076523.628481 iteration: 87150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09254 FastRCNN class loss: 0.061 FastRCNN total loss: 0.15354 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13866 RPN box loss: 0.01651 RPN score loss: 0.00159 RPN total loss: 0.0181 Total loss: 0.87261 timestamp: 1655076526.8943338 iteration: 87155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07609 FastRCNN class loss: 0.07092 FastRCNN total loss: 0.14701 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.10667 RPN box loss: 0.00469 RPN score loss: 0.00257 RPN total loss: 0.00726 Total loss: 0.82326 timestamp: 1655076530.1221895 iteration: 87160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11769 FastRCNN class loss: 0.13777 FastRCNN total loss: 0.25546 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.16833 RPN box loss: 0.03076 RPN score loss: 0.01155 RPN total loss: 0.04231 Total loss: 1.02842 timestamp: 1655076533.3364115 iteration: 87165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11916 FastRCNN class loss: 0.07878 FastRCNN total loss: 0.19794 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.15235 RPN box loss: 0.01404 RPN score loss: 0.00261 RPN total loss: 0.01665 Total loss: 0.92927 timestamp: 1655076536.574839 iteration: 87170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08527 FastRCNN class loss: 0.07795 FastRCNN total loss: 0.16322 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.18367 RPN box loss: 0.00665 RPN score loss: 0.00447 RPN total loss: 0.01113 Total loss: 0.92034 timestamp: 1655076539.874891 iteration: 87175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09028 FastRCNN class loss: 0.08817 FastRCNN total loss: 0.17845 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.17443 RPN box loss: 0.01419 RPN score loss: 0.00466 RPN total loss: 0.01885 Total loss: 0.93406 timestamp: 1655076543.200777 iteration: 87180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11852 FastRCNN class loss: 0.1185 FastRCNN total loss: 0.23703 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13876 RPN box loss: 0.02593 RPN score loss: 0.00665 RPN total loss: 0.03258 Total loss: 0.97069 timestamp: 1655076546.5914154 iteration: 87185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09326 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.17209 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.14976 RPN box loss: 0.00523 RPN score loss: 0.00435 RPN total loss: 0.00958 Total loss: 0.89375 timestamp: 1655076549.853319 iteration: 87190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06854 FastRCNN class loss: 0.05609 FastRCNN total loss: 0.12463 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1042 RPN box loss: 0.00552 RPN score loss: 0.00245 RPN total loss: 0.00796 Total loss: 0.79911 timestamp: 1655076553.1000428 iteration: 87195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10025 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.17251 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.18392 RPN box loss: 0.01425 RPN score loss: 0.00714 RPN total loss: 0.02139 Total loss: 0.94013 timestamp: 1655076556.4297366 iteration: 87200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08774 FastRCNN class loss: 0.10257 FastRCNN total loss: 0.19031 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.20509 RPN box loss: 0.00972 RPN score loss: 0.00721 RPN total loss: 0.01693 Total loss: 0.97464 timestamp: 1655076559.7234435 iteration: 87205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10739 FastRCNN class loss: 0.15934 FastRCNN total loss: 0.26673 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.10422 RPN box loss: 0.00664 RPN score loss: 0.00244 RPN total loss: 0.00908 Total loss: 0.94234 timestamp: 1655076563.0419312 iteration: 87210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07104 FastRCNN class loss: 0.06729 FastRCNN total loss: 0.13833 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12085 RPN box loss: 0.02439 RPN score loss: 0.0022 RPN total loss: 0.02659 Total loss: 0.84809 timestamp: 1655076566.3238916 iteration: 87215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15581 FastRCNN class loss: 0.09268 FastRCNN total loss: 0.24849 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.16744 RPN box loss: 0.03133 RPN score loss: 0.01615 RPN total loss: 0.04748 Total loss: 1.02573 timestamp: 1655076569.5606856 iteration: 87220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05824 FastRCNN class loss: 0.05965 FastRCNN total loss: 0.1179 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.25578 RPN box loss: 0.00972 RPN score loss: 0.00262 RPN total loss: 0.01235 Total loss: 0.94834 timestamp: 1655076572.8217316 iteration: 87225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12365 FastRCNN class loss: 0.06878 FastRCNN total loss: 0.19243 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12726 RPN box loss: 0.00863 RPN score loss: 0.0069 RPN total loss: 0.01553 Total loss: 0.89753 timestamp: 1655076576.1934385 iteration: 87230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10056 FastRCNN class loss: 0.08619 FastRCNN total loss: 0.18676 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.20002 RPN box loss: 0.0121 RPN score loss: 0.00311 RPN total loss: 0.0152 Total loss: 0.9643 timestamp: 1655076579.5058231 iteration: 87235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13502 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.19725 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.10864 RPN box loss: 0.00395 RPN score loss: 0.0038 RPN total loss: 0.00776 Total loss: 0.87596 timestamp: 1655076582.7638268 iteration: 87240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10391 FastRCNN class loss: 0.14015 FastRCNN total loss: 0.24405 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.226 RPN box loss: 0.01148 RPN score loss: 0.00716 RPN total loss: 0.01864 Total loss: 1.05101 timestamp: 1655076585.996542 iteration: 87245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0992 FastRCNN class loss: 0.0774 FastRCNN total loss: 0.1766 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12784 RPN box loss: 0.00826 RPN score loss: 0.00612 RPN total loss: 0.01438 Total loss: 0.88113 timestamp: 1655076589.2738688 iteration: 87250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10901 FastRCNN class loss: 0.07208 FastRCNN total loss: 0.18109 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.17933 RPN box loss: 0.01523 RPN score loss: 0.00241 RPN total loss: 0.01764 Total loss: 0.94038 timestamp: 1655076592.592865 iteration: 87255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07756 FastRCNN class loss: 0.07743 FastRCNN total loss: 0.15499 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.13569 RPN box loss: 0.0072 RPN score loss: 0.00949 RPN total loss: 0.0167 Total loss: 0.86969 timestamp: 1655076595.8594768 iteration: 87260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1086 FastRCNN class loss: 0.08834 FastRCNN total loss: 0.19694 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.15021 RPN box loss: 0.04165 RPN score loss: 0.00348 RPN total loss: 0.04513 Total loss: 0.95459 timestamp: 1655076599.1459332 iteration: 87265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09429 FastRCNN class loss: 0.05827 FastRCNN total loss: 0.15256 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.10057 RPN box loss: 0.01081 RPN score loss: 0.00256 RPN total loss: 0.01337 Total loss: 0.82882 timestamp: 1655076602.3499517 iteration: 87270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06591 FastRCNN class loss: 0.06628 FastRCNN total loss: 0.13219 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.1624 RPN box loss: 0.00574 RPN score loss: 0.00245 RPN total loss: 0.00819 Total loss: 0.8651 timestamp: 1655076605.6471612 iteration: 87275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05657 FastRCNN class loss: 0.07423 FastRCNN total loss: 0.1308 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.12752 RPN box loss: 0.00759 RPN score loss: 0.00307 RPN total loss: 0.01066 Total loss: 0.8313 timestamp: 1655076608.9511814 iteration: 87280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10834 FastRCNN class loss: 0.09438 FastRCNN total loss: 0.20272 L1 loss: 0.0000e+00 L2 loss: 0.56232 Learning rate: 4.0000e-05 Mask loss: 0.11657 RPN box loss: 0.01359 RPN score loss: 0.01004 RPN total loss: 0.02363 Total loss: 0.90524 timestamp: 1655076612.146831 iteration: 87285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08792 FastRCNN class loss: 0.06697 FastRCNN total loss: 0.15489 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11179 RPN box loss: 0.00907 RPN score loss: 0.00387 RPN total loss: 0.01295 Total loss: 0.84194 timestamp: 1655076615.4942327 iteration: 87290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09938 FastRCNN class loss: 0.06138 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12326 RPN box loss: 0.01152 RPN score loss: 0.00275 RPN total loss: 0.01427 Total loss: 0.86061 timestamp: 1655076618.6878715 iteration: 87295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08142 FastRCNN class loss: 0.07713 FastRCNN total loss: 0.15854 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10568 RPN box loss: 0.01337 RPN score loss: 0.00419 RPN total loss: 0.01755 Total loss: 0.84409 timestamp: 1655076621.9208112 iteration: 87300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11407 FastRCNN class loss: 0.08206 FastRCNN total loss: 0.19613 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15158 RPN box loss: 0.00596 RPN score loss: 0.00539 RPN total loss: 0.01135 Total loss: 0.92137 timestamp: 1655076625.1436758 iteration: 87305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09884 FastRCNN class loss: 0.06567 FastRCNN total loss: 0.16451 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.13487 RPN box loss: 0.00698 RPN score loss: 0.0035 RPN total loss: 0.01048 Total loss: 0.87218 timestamp: 1655076628.391688 iteration: 87310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13082 FastRCNN class loss: 0.06885 FastRCNN total loss: 0.19966 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15206 RPN box loss: 0.01549 RPN score loss: 0.00297 RPN total loss: 0.01846 Total loss: 0.9325 timestamp: 1655076631.6594818 iteration: 87315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06765 FastRCNN class loss: 0.06057 FastRCNN total loss: 0.12822 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15317 RPN box loss: 0.00526 RPN score loss: 0.00476 RPN total loss: 0.01001 Total loss: 0.85372 timestamp: 1655076634.915463 iteration: 87320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16021 FastRCNN class loss: 0.0897 FastRCNN total loss: 0.24991 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.17814 RPN box loss: 0.01349 RPN score loss: 0.00986 RPN total loss: 0.02335 Total loss: 1.01372 timestamp: 1655076638.1120787 iteration: 87325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10184 FastRCNN class loss: 0.07925 FastRCNN total loss: 0.1811 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12392 RPN box loss: 0.01217 RPN score loss: 0.01356 RPN total loss: 0.02573 Total loss: 0.89306 timestamp: 1655076641.3689504 iteration: 87330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12852 FastRCNN class loss: 0.1242 FastRCNN total loss: 0.25271 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.18542 RPN box loss: 0.023 RPN score loss: 0.0053 RPN total loss: 0.02829 Total loss: 1.02874 timestamp: 1655076644.6658432 iteration: 87335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07947 FastRCNN class loss: 0.05975 FastRCNN total loss: 0.13922 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.18032 RPN box loss: 0.00309 RPN score loss: 0.00168 RPN total loss: 0.00476 Total loss: 0.88662 timestamp: 1655076647.8987262 iteration: 87340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07436 FastRCNN class loss: 0.05588 FastRCNN total loss: 0.13024 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11935 RPN box loss: 0.01952 RPN score loss: 0.00363 RPN total loss: 0.02314 Total loss: 0.83505 timestamp: 1655076651.1294053 iteration: 87345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10067 FastRCNN class loss: 0.07167 FastRCNN total loss: 0.17235 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15613 RPN box loss: 0.0092 RPN score loss: 0.00288 RPN total loss: 0.01208 Total loss: 0.90286 timestamp: 1655076654.4327161 iteration: 87350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08616 FastRCNN class loss: 0.07336 FastRCNN total loss: 0.15952 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.16395 RPN box loss: 0.03703 RPN score loss: 0.00309 RPN total loss: 0.04012 Total loss: 0.9259 timestamp: 1655076657.733926 iteration: 87355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13383 FastRCNN class loss: 0.08871 FastRCNN total loss: 0.22254 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.16395 RPN box loss: 0.02952 RPN score loss: 0.00493 RPN total loss: 0.03444 Total loss: 0.98325 timestamp: 1655076660.9762213 iteration: 87360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06867 FastRCNN class loss: 0.07906 FastRCNN total loss: 0.14773 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15895 RPN box loss: 0.01566 RPN score loss: 0.00137 RPN total loss: 0.01703 Total loss: 0.88603 timestamp: 1655076664.1941345 iteration: 87365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04265 FastRCNN class loss: 0.03927 FastRCNN total loss: 0.08192 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1557 RPN box loss: 0.00425 RPN score loss: 0.00165 RPN total loss: 0.00591 Total loss: 0.80584 timestamp: 1655076667.5234158 iteration: 87370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11558 FastRCNN class loss: 0.07425 FastRCNN total loss: 0.18983 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11663 RPN box loss: 0.0389 RPN score loss: 0.00755 RPN total loss: 0.04644 Total loss: 0.91522 timestamp: 1655076670.8175917 iteration: 87375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0627 FastRCNN class loss: 0.04464 FastRCNN total loss: 0.10734 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.13262 RPN box loss: 0.01716 RPN score loss: 0.00444 RPN total loss: 0.02161 Total loss: 0.82387 timestamp: 1655076674.0699198 iteration: 87380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08943 FastRCNN class loss: 0.08994 FastRCNN total loss: 0.17937 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.17948 RPN box loss: 0.01944 RPN score loss: 0.01306 RPN total loss: 0.03249 Total loss: 0.95365 timestamp: 1655076677.2405663 iteration: 87385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10684 FastRCNN class loss: 0.07282 FastRCNN total loss: 0.17967 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14215 RPN box loss: 0.01091 RPN score loss: 0.01063 RPN total loss: 0.02154 Total loss: 0.90566 timestamp: 1655076680.5054874 iteration: 87390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0956 FastRCNN class loss: 0.06377 FastRCNN total loss: 0.15937 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14747 RPN box loss: 0.01479 RPN score loss: 0.00537 RPN total loss: 0.02016 Total loss: 0.88932 timestamp: 1655076683.8551807 iteration: 87395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06843 FastRCNN class loss: 0.05016 FastRCNN total loss: 0.11859 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14646 RPN box loss: 0.00362 RPN score loss: 0.00145 RPN total loss: 0.00507 Total loss: 0.83244 timestamp: 1655076687.1143703 iteration: 87400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12827 FastRCNN class loss: 0.06712 FastRCNN total loss: 0.19539 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14892 RPN box loss: 0.00688 RPN score loss: 0.01011 RPN total loss: 0.01698 Total loss: 0.9236 timestamp: 1655076690.3315477 iteration: 87405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08655 FastRCNN class loss: 0.08371 FastRCNN total loss: 0.17025 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12596 RPN box loss: 0.03675 RPN score loss: 0.01656 RPN total loss: 0.05331 Total loss: 0.91183 timestamp: 1655076693.5606358 iteration: 87410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09055 FastRCNN class loss: 0.07961 FastRCNN total loss: 0.17016 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12291 RPN box loss: 0.01253 RPN score loss: 0.01231 RPN total loss: 0.02484 Total loss: 0.88022 timestamp: 1655076696.87301 iteration: 87415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04633 FastRCNN class loss: 0.03123 FastRCNN total loss: 0.07756 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.09132 RPN box loss: 0.00954 RPN score loss: 0.00052 RPN total loss: 0.01006 Total loss: 0.74125 timestamp: 1655076700.1269267 iteration: 87420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06155 FastRCNN class loss: 0.0428 FastRCNN total loss: 0.10435 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12341 RPN box loss: 0.01421 RPN score loss: 0.00323 RPN total loss: 0.01744 Total loss: 0.80751 timestamp: 1655076703.4722497 iteration: 87425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05197 FastRCNN class loss: 0.03763 FastRCNN total loss: 0.0896 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11296 RPN box loss: 0.00316 RPN score loss: 0.01985 RPN total loss: 0.02301 Total loss: 0.78788 timestamp: 1655076706.7757769 iteration: 87430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09214 FastRCNN class loss: 0.04825 FastRCNN total loss: 0.14039 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11871 RPN box loss: 0.0081 RPN score loss: 0.00857 RPN total loss: 0.01667 Total loss: 0.83808 timestamp: 1655076710.0187705 iteration: 87435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15349 FastRCNN class loss: 0.10919 FastRCNN total loss: 0.26268 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1817 RPN box loss: 0.02305 RPN score loss: 0.00682 RPN total loss: 0.02987 Total loss: 1.03656 timestamp: 1655076713.3464215 iteration: 87440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05983 FastRCNN class loss: 0.06145 FastRCNN total loss: 0.12128 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10084 RPN box loss: 0.00397 RPN score loss: 0.00582 RPN total loss: 0.00979 Total loss: 0.79422 timestamp: 1655076716.6488705 iteration: 87445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09172 FastRCNN class loss: 0.05154 FastRCNN total loss: 0.14326 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10685 RPN box loss: 0.00477 RPN score loss: 0.0025 RPN total loss: 0.00728 Total loss: 0.8197 timestamp: 1655076719.9378564 iteration: 87450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.08405 FastRCNN total loss: 0.16644 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.21901 RPN box loss: 0.02178 RPN score loss: 0.00437 RPN total loss: 0.02616 Total loss: 0.97392 timestamp: 1655076723.2947986 iteration: 87455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06846 FastRCNN class loss: 0.04965 FastRCNN total loss: 0.11811 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.08262 RPN box loss: 0.00948 RPN score loss: 0.00064 RPN total loss: 0.01012 Total loss: 0.77316 timestamp: 1655076726.5711148 iteration: 87460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10144 FastRCNN class loss: 0.05669 FastRCNN total loss: 0.15812 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11171 RPN box loss: 0.01561 RPN score loss: 0.00324 RPN total loss: 0.01884 Total loss: 0.85099 timestamp: 1655076729.931028 iteration: 87465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11272 FastRCNN class loss: 0.08693 FastRCNN total loss: 0.19965 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14038 RPN box loss: 0.00951 RPN score loss: 0.00722 RPN total loss: 0.01674 Total loss: 0.91908 timestamp: 1655076733.1772559 iteration: 87470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09516 FastRCNN class loss: 0.10324 FastRCNN total loss: 0.1984 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.18178 RPN box loss: 0.02945 RPN score loss: 0.0126 RPN total loss: 0.04205 Total loss: 0.98454 timestamp: 1655076736.4743707 iteration: 87475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1047 FastRCNN class loss: 0.10355 FastRCNN total loss: 0.20825 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1525 RPN box loss: 0.01266 RPN score loss: 0.00644 RPN total loss: 0.0191 Total loss: 0.94215 timestamp: 1655076739.7743223 iteration: 87480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08937 FastRCNN class loss: 0.09334 FastRCNN total loss: 0.18271 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.16315 RPN box loss: 0.01414 RPN score loss: 0.01334 RPN total loss: 0.02747 Total loss: 0.93564 timestamp: 1655076743.0702677 iteration: 87485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09371 FastRCNN class loss: 0.06969 FastRCNN total loss: 0.1634 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.13528 RPN box loss: 0.00528 RPN score loss: 0.00831 RPN total loss: 0.01359 Total loss: 0.87458 timestamp: 1655076746.3350558 iteration: 87490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16904 FastRCNN class loss: 0.08409 FastRCNN total loss: 0.25313 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.17625 RPN box loss: 0.02542 RPN score loss: 0.00371 RPN total loss: 0.02914 Total loss: 1.02082 timestamp: 1655076749.6374753 iteration: 87495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13486 FastRCNN class loss: 0.07228 FastRCNN total loss: 0.20714 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1317 RPN box loss: 0.01313 RPN score loss: 0.00355 RPN total loss: 0.01668 Total loss: 0.91783 timestamp: 1655076753.0202277 iteration: 87500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0777 FastRCNN class loss: 0.05811 FastRCNN total loss: 0.1358 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10408 RPN box loss: 0.00628 RPN score loss: 0.00383 RPN total loss: 0.01012 Total loss: 0.81231 timestamp: 1655076756.3163478 iteration: 87505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08877 FastRCNN class loss: 0.06066 FastRCNN total loss: 0.14943 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.14879 RPN box loss: 0.02857 RPN score loss: 0.00332 RPN total loss: 0.03188 Total loss: 0.8924 timestamp: 1655076759.4972243 iteration: 87510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07257 FastRCNN class loss: 0.0587 FastRCNN total loss: 0.13127 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.11393 RPN box loss: 0.02207 RPN score loss: 0.00228 RPN total loss: 0.02436 Total loss: 0.83186 timestamp: 1655076762.7500646 iteration: 87515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10795 FastRCNN class loss: 0.07952 FastRCNN total loss: 0.18747 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15054 RPN box loss: 0.02072 RPN score loss: 0.00747 RPN total loss: 0.02819 Total loss: 0.92851 timestamp: 1655076766.0463488 iteration: 87520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10196 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.18101 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1248 RPN box loss: 0.02131 RPN score loss: 0.00417 RPN total loss: 0.02548 Total loss: 0.89361 timestamp: 1655076769.3021011 iteration: 87525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08964 FastRCNN class loss: 0.05871 FastRCNN total loss: 0.14835 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15736 RPN box loss: 0.01505 RPN score loss: 0.00375 RPN total loss: 0.0188 Total loss: 0.88682 timestamp: 1655076772.5850105 iteration: 87530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13853 FastRCNN class loss: 0.09424 FastRCNN total loss: 0.23276 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.19527 RPN box loss: 0.02454 RPN score loss: 0.01774 RPN total loss: 0.04229 Total loss: 1.03263 timestamp: 1655076775.858072 iteration: 87535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12883 FastRCNN class loss: 0.10835 FastRCNN total loss: 0.23718 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.25534 RPN box loss: 0.01359 RPN score loss: 0.00659 RPN total loss: 0.02018 Total loss: 1.07501 timestamp: 1655076779.0726805 iteration: 87540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08787 FastRCNN class loss: 0.06461 FastRCNN total loss: 0.15247 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10949 RPN box loss: 0.01454 RPN score loss: 0.00245 RPN total loss: 0.01699 Total loss: 0.84126 timestamp: 1655076782.2881112 iteration: 87545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09007 FastRCNN class loss: 0.06782 FastRCNN total loss: 0.15789 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.26121 RPN box loss: 0.01679 RPN score loss: 0.00413 RPN total loss: 0.02092 Total loss: 1.00232 timestamp: 1655076785.5398514 iteration: 87550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07906 FastRCNN class loss: 0.06552 FastRCNN total loss: 0.14458 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.09121 RPN box loss: 0.01621 RPN score loss: 0.00287 RPN total loss: 0.01907 Total loss: 0.81717 timestamp: 1655076788.756777 iteration: 87555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06743 FastRCNN class loss: 0.06545 FastRCNN total loss: 0.13288 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.1722 RPN box loss: 0.0108 RPN score loss: 0.00797 RPN total loss: 0.01877 Total loss: 0.88616 timestamp: 1655076792.0790904 iteration: 87560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11357 FastRCNN class loss: 0.08822 FastRCNN total loss: 0.20179 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.23784 RPN box loss: 0.02289 RPN score loss: 0.01643 RPN total loss: 0.03932 Total loss: 1.04126 timestamp: 1655076795.349982 iteration: 87565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05716 FastRCNN class loss: 0.04784 FastRCNN total loss: 0.105 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12689 RPN box loss: 0.02158 RPN score loss: 0.00562 RPN total loss: 0.0272 Total loss: 0.82139 timestamp: 1655076798.597691 iteration: 87570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09366 FastRCNN class loss: 0.07834 FastRCNN total loss: 0.172 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.10248 RPN box loss: 0.01217 RPN score loss: 0.00203 RPN total loss: 0.0142 Total loss: 0.85098 timestamp: 1655076801.806042 iteration: 87575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13171 FastRCNN class loss: 0.10067 FastRCNN total loss: 0.23238 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.15068 RPN box loss: 0.01369 RPN score loss: 0.0073 RPN total loss: 0.02099 Total loss: 0.96635 timestamp: 1655076805.0555763 iteration: 87580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15842 FastRCNN class loss: 0.0726 FastRCNN total loss: 0.23102 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.38183 RPN box loss: 0.02859 RPN score loss: 0.00317 RPN total loss: 0.03175 Total loss: 1.20691 timestamp: 1655076808.2804325 iteration: 87585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06382 FastRCNN class loss: 0.08636 FastRCNN total loss: 0.15018 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.13952 RPN box loss: 0.00747 RPN score loss: 0.01123 RPN total loss: 0.0187 Total loss: 0.87071 timestamp: 1655076811.5337687 iteration: 87590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06918 FastRCNN class loss: 0.05514 FastRCNN total loss: 0.12432 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.13498 RPN box loss: 0.01453 RPN score loss: 0.01331 RPN total loss: 0.02783 Total loss: 0.84944 timestamp: 1655076814.7545216 iteration: 87595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09992 FastRCNN class loss: 0.10226 FastRCNN total loss: 0.20218 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.16761 RPN box loss: 0.01503 RPN score loss: 0.00531 RPN total loss: 0.02034 Total loss: 0.95244 timestamp: 1655076818.0721357 iteration: 87600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11157 FastRCNN class loss: 0.05515 FastRCNN total loss: 0.16672 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.12596 RPN box loss: 0.00861 RPN score loss: 0.00324 RPN total loss: 0.01186 Total loss: 0.86684 timestamp: 1655076821.3804736 iteration: 87605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04863 FastRCNN class loss: 0.05183 FastRCNN total loss: 0.10046 L1 loss: 0.0000e+00 L2 loss: 0.56231 Learning rate: 4.0000e-05 Mask loss: 0.07279 RPN box loss: 0.00921 RPN score loss: 0.00179 RPN total loss: 0.011 Total loss: 0.74655 timestamp: 1655076824.5759773 iteration: 87610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12475 FastRCNN class loss: 0.05447 FastRCNN total loss: 0.17922 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.07184 RPN box loss: 0.00629 RPN score loss: 0.0026 RPN total loss: 0.00889 Total loss: 0.82224 timestamp: 1655076827.8492892 iteration: 87615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13745 FastRCNN class loss: 0.10742 FastRCNN total loss: 0.24487 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.15403 RPN box loss: 0.0115 RPN score loss: 0.01016 RPN total loss: 0.02165 Total loss: 0.98285 timestamp: 1655076831.1503785 iteration: 87620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05456 FastRCNN class loss: 0.05405 FastRCNN total loss: 0.10862 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12334 RPN box loss: 0.02037 RPN score loss: 0.00788 RPN total loss: 0.02825 Total loss: 0.82251 timestamp: 1655076834.3989062 iteration: 87625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09936 FastRCNN class loss: 0.05633 FastRCNN total loss: 0.15569 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.17991 RPN box loss: 0.01364 RPN score loss: 0.00808 RPN total loss: 0.02172 Total loss: 0.91963 timestamp: 1655076837.6445818 iteration: 87630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1085 FastRCNN class loss: 0.0824 FastRCNN total loss: 0.1909 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14889 RPN box loss: 0.02262 RPN score loss: 0.00501 RPN total loss: 0.02763 Total loss: 0.92972 timestamp: 1655076840.9681742 iteration: 87635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14757 FastRCNN class loss: 0.07108 FastRCNN total loss: 0.21865 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.16545 RPN box loss: 0.0132 RPN score loss: 0.00318 RPN total loss: 0.01639 Total loss: 0.96279 timestamp: 1655076844.2783039 iteration: 87640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11195 FastRCNN class loss: 0.07521 FastRCNN total loss: 0.18715 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.13252 RPN box loss: 0.01141 RPN score loss: 0.00199 RPN total loss: 0.01339 Total loss: 0.89537 timestamp: 1655076847.525808 iteration: 87645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03083 FastRCNN class loss: 0.03146 FastRCNN total loss: 0.06229 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.13129 RPN box loss: 0.00559 RPN score loss: 0.01225 RPN total loss: 0.01783 Total loss: 0.77372 timestamp: 1655076850.8357425 iteration: 87650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04778 FastRCNN class loss: 0.02653 FastRCNN total loss: 0.07431 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10722 RPN box loss: 0.00147 RPN score loss: 0.00106 RPN total loss: 0.00254 Total loss: 0.74637 timestamp: 1655076854.1281078 iteration: 87655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08627 FastRCNN class loss: 0.05084 FastRCNN total loss: 0.1371 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10581 RPN box loss: 0.00592 RPN score loss: 0.00131 RPN total loss: 0.00723 Total loss: 0.81244 timestamp: 1655076857.3795097 iteration: 87660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09509 FastRCNN class loss: 0.06211 FastRCNN total loss: 0.1572 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12701 RPN box loss: 0.01087 RPN score loss: 0.00158 RPN total loss: 0.01244 Total loss: 0.85896 timestamp: 1655076860.6180656 iteration: 87665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07115 FastRCNN class loss: 0.04499 FastRCNN total loss: 0.11615 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.1389 RPN box loss: 0.00851 RPN score loss: 0.00161 RPN total loss: 0.01012 Total loss: 0.82747 timestamp: 1655076863.878991 iteration: 87670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08066 FastRCNN class loss: 0.07513 FastRCNN total loss: 0.15579 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.16235 RPN box loss: 0.01017 RPN score loss: 0.00642 RPN total loss: 0.0166 Total loss: 0.89704 timestamp: 1655076867.1574447 iteration: 87675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.18574 FastRCNN class loss: 0.09398 FastRCNN total loss: 0.27972 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14029 RPN box loss: 0.01151 RPN score loss: 0.00456 RPN total loss: 0.01607 Total loss: 0.99839 timestamp: 1655076870.4523556 iteration: 87680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07641 FastRCNN class loss: 0.04735 FastRCNN total loss: 0.12376 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.13468 RPN box loss: 0.03368 RPN score loss: 0.01075 RPN total loss: 0.04443 Total loss: 0.86517 timestamp: 1655076873.743442 iteration: 87685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09049 FastRCNN class loss: 0.06855 FastRCNN total loss: 0.15904 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.15478 RPN box loss: 0.02263 RPN score loss: 0.00385 RPN total loss: 0.02647 Total loss: 0.90259 timestamp: 1655076877.1121602 iteration: 87690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10093 FastRCNN class loss: 0.06954 FastRCNN total loss: 0.17047 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.17847 RPN box loss: 0.02294 RPN score loss: 0.00224 RPN total loss: 0.02519 Total loss: 0.93643 timestamp: 1655076880.4218652 iteration: 87695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08707 FastRCNN class loss: 0.09428 FastRCNN total loss: 0.18135 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14937 RPN box loss: 0.00866 RPN score loss: 0.00617 RPN total loss: 0.01483 Total loss: 0.90786 timestamp: 1655076883.701686 iteration: 87700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10191 FastRCNN class loss: 0.08151 FastRCNN total loss: 0.18342 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11478 RPN box loss: 0.00837 RPN score loss: 0.00634 RPN total loss: 0.01471 Total loss: 0.87522 timestamp: 1655076886.9976091 iteration: 87705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08337 FastRCNN class loss: 0.07007 FastRCNN total loss: 0.15344 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.17697 RPN box loss: 0.01432 RPN score loss: 0.0065 RPN total loss: 0.02081 Total loss: 0.91353 timestamp: 1655076890.346904 iteration: 87710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07396 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.1539 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.2179 RPN box loss: 0.03899 RPN score loss: 0.01127 RPN total loss: 0.05026 Total loss: 0.98437 timestamp: 1655076893.5816824 iteration: 87715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1181 FastRCNN class loss: 0.06122 FastRCNN total loss: 0.17932 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.18279 RPN box loss: 0.00741 RPN score loss: 0.00293 RPN total loss: 0.01034 Total loss: 0.93475 timestamp: 1655076896.807063 iteration: 87720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10224 FastRCNN class loss: 0.09278 FastRCNN total loss: 0.19502 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.15835 RPN box loss: 0.01367 RPN score loss: 0.01051 RPN total loss: 0.02418 Total loss: 0.93985 timestamp: 1655076900.060478 iteration: 87725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04275 FastRCNN class loss: 0.04882 FastRCNN total loss: 0.09157 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10744 RPN box loss: 0.00213 RPN score loss: 0.00633 RPN total loss: 0.00845 Total loss: 0.76977 timestamp: 1655076903.3029227 iteration: 87730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09908 FastRCNN class loss: 0.07749 FastRCNN total loss: 0.17657 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.16275 RPN box loss: 0.01001 RPN score loss: 0.02893 RPN total loss: 0.03895 Total loss: 0.94056 timestamp: 1655076906.5557363 iteration: 87735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10342 FastRCNN class loss: 0.05322 FastRCNN total loss: 0.15664 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.09554 RPN box loss: 0.01098 RPN score loss: 0.00643 RPN total loss: 0.01741 Total loss: 0.8319 timestamp: 1655076909.8762732 iteration: 87740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11873 FastRCNN class loss: 0.07249 FastRCNN total loss: 0.19122 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.09137 RPN box loss: 0.00625 RPN score loss: 0.00388 RPN total loss: 0.01013 Total loss: 0.85502 timestamp: 1655076913.1612754 iteration: 87745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13815 FastRCNN class loss: 0.05452 FastRCNN total loss: 0.19268 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10335 RPN box loss: 0.02217 RPN score loss: 0.00629 RPN total loss: 0.02846 Total loss: 0.88679 timestamp: 1655076916.4488783 iteration: 87750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08102 FastRCNN class loss: 0.04529 FastRCNN total loss: 0.12632 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11285 RPN box loss: 0.01521 RPN score loss: 0.00314 RPN total loss: 0.01835 Total loss: 0.81981 timestamp: 1655076919.7159004 iteration: 87755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07821 FastRCNN class loss: 0.06267 FastRCNN total loss: 0.14087 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12745 RPN box loss: 0.01332 RPN score loss: 0.0092 RPN total loss: 0.02252 Total loss: 0.85314 timestamp: 1655076923.0048437 iteration: 87760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13169 FastRCNN class loss: 0.07994 FastRCNN total loss: 0.21162 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14325 RPN box loss: 0.01694 RPN score loss: 0.01352 RPN total loss: 0.03046 Total loss: 0.94763 timestamp: 1655076926.2298992 iteration: 87765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11661 FastRCNN class loss: 0.06564 FastRCNN total loss: 0.18225 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10832 RPN box loss: 0.01135 RPN score loss: 0.00338 RPN total loss: 0.01473 Total loss: 0.8676 timestamp: 1655076929.4699185 iteration: 87770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03677 FastRCNN class loss: 0.06922 FastRCNN total loss: 0.10599 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.09789 RPN box loss: 0.01554 RPN score loss: 0.00496 RPN total loss: 0.02051 Total loss: 0.78669 timestamp: 1655076932.7502773 iteration: 87775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10859 FastRCNN class loss: 0.0531 FastRCNN total loss: 0.16169 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12374 RPN box loss: 0.01628 RPN score loss: 0.0041 RPN total loss: 0.02038 Total loss: 0.86811 timestamp: 1655076935.992713 iteration: 87780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11909 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.18899 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14442 RPN box loss: 0.0156 RPN score loss: 0.0033 RPN total loss: 0.0189 Total loss: 0.91461 timestamp: 1655076939.3135517 iteration: 87785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10891 FastRCNN class loss: 0.08863 FastRCNN total loss: 0.19754 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14389 RPN box loss: 0.0055 RPN score loss: 0.0086 RPN total loss: 0.0141 Total loss: 0.91783 timestamp: 1655076942.5610247 iteration: 87790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06123 FastRCNN class loss: 0.06016 FastRCNN total loss: 0.12139 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.17541 RPN box loss: 0.00996 RPN score loss: 0.00546 RPN total loss: 0.01542 Total loss: 0.87452 timestamp: 1655076945.810784 iteration: 87795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10583 FastRCNN class loss: 0.06996 FastRCNN total loss: 0.17578 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10172 RPN box loss: 0.01181 RPN score loss: 0.00439 RPN total loss: 0.0162 Total loss: 0.856 timestamp: 1655076949.0833654 iteration: 87800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05317 FastRCNN class loss: 0.0442 FastRCNN total loss: 0.09736 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11569 RPN box loss: 0.00376 RPN score loss: 0.01006 RPN total loss: 0.01382 Total loss: 0.78918 timestamp: 1655076952.3157704 iteration: 87805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12095 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.18462 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.1308 RPN box loss: 0.03692 RPN score loss: 0.00168 RPN total loss: 0.0386 Total loss: 0.91631 timestamp: 1655076955.5865297 iteration: 87810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06992 FastRCNN class loss: 0.04076 FastRCNN total loss: 0.11067 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11477 RPN box loss: 0.00912 RPN score loss: 0.00667 RPN total loss: 0.01579 Total loss: 0.80354 timestamp: 1655076958.8498063 iteration: 87815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08662 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.14948 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11119 RPN box loss: 0.00953 RPN score loss: 0.00442 RPN total loss: 0.01395 Total loss: 0.83691 timestamp: 1655076962.0942647 iteration: 87820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09918 FastRCNN class loss: 0.05593 FastRCNN total loss: 0.15511 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12483 RPN box loss: 0.0138 RPN score loss: 0.00171 RPN total loss: 0.01552 Total loss: 0.85775 timestamp: 1655076965.3969345 iteration: 87825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07488 FastRCNN class loss: 0.07296 FastRCNN total loss: 0.14784 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.18632 RPN box loss: 0.02047 RPN score loss: 0.00443 RPN total loss: 0.0249 Total loss: 0.92136 timestamp: 1655076968.6275766 iteration: 87830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09825 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.15464 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12474 RPN box loss: 0.0132 RPN score loss: 0.00219 RPN total loss: 0.01539 Total loss: 0.85707 timestamp: 1655076971.9104092 iteration: 87835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07515 FastRCNN class loss: 0.07009 FastRCNN total loss: 0.14524 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10846 RPN box loss: 0.00857 RPN score loss: 0.00121 RPN total loss: 0.00978 Total loss: 0.82579 timestamp: 1655076975.1465104 iteration: 87840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08674 FastRCNN class loss: 0.0574 FastRCNN total loss: 0.14414 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.13799 RPN box loss: 0.03129 RPN score loss: 0.00335 RPN total loss: 0.03464 Total loss: 0.87906 timestamp: 1655076978.4136813 iteration: 87845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09292 FastRCNN class loss: 0.07731 FastRCNN total loss: 0.17023 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11416 RPN box loss: 0.01031 RPN score loss: 0.00186 RPN total loss: 0.01216 Total loss: 0.85885 timestamp: 1655076981.689528 iteration: 87850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08508 FastRCNN class loss: 0.05675 FastRCNN total loss: 0.14183 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14148 RPN box loss: 0.0286 RPN score loss: 0.0057 RPN total loss: 0.0343 Total loss: 0.87991 timestamp: 1655076984.9693418 iteration: 87855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09684 FastRCNN class loss: 0.04132 FastRCNN total loss: 0.13816 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12577 RPN box loss: 0.00765 RPN score loss: 0.00304 RPN total loss: 0.01069 Total loss: 0.83692 timestamp: 1655076988.2610893 iteration: 87860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0839 FastRCNN class loss: 0.04198 FastRCNN total loss: 0.12588 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.1083 RPN box loss: 0.01446 RPN score loss: 0.00182 RPN total loss: 0.01628 Total loss: 0.81277 timestamp: 1655076991.5614076 iteration: 87865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10949 FastRCNN class loss: 0.09097 FastRCNN total loss: 0.20046 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.15407 RPN box loss: 0.01711 RPN score loss: 0.00518 RPN total loss: 0.02229 Total loss: 0.93911 timestamp: 1655076994.843123 iteration: 87870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08355 FastRCNN class loss: 0.05929 FastRCNN total loss: 0.14284 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14177 RPN box loss: 0.00855 RPN score loss: 0.00359 RPN total loss: 0.01214 Total loss: 0.85905 timestamp: 1655076998.1779597 iteration: 87875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08239 FastRCNN class loss: 0.04814 FastRCNN total loss: 0.13053 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.12059 RPN box loss: 0.01894 RPN score loss: 0.00241 RPN total loss: 0.02134 Total loss: 0.83475 timestamp: 1655077001.4997735 iteration: 87880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07345 FastRCNN class loss: 0.05279 FastRCNN total loss: 0.12624 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.15506 RPN box loss: 0.02122 RPN score loss: 0.00793 RPN total loss: 0.02915 Total loss: 0.87275 timestamp: 1655077004.8025773 iteration: 87885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09999 FastRCNN class loss: 0.05769 FastRCNN total loss: 0.15768 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.18797 RPN box loss: 0.01555 RPN score loss: 0.00646 RPN total loss: 0.02201 Total loss: 0.92995 timestamp: 1655077008.096382 iteration: 87890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10611 FastRCNN class loss: 0.06091 FastRCNN total loss: 0.16702 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14419 RPN box loss: 0.01924 RPN score loss: 0.00212 RPN total loss: 0.02136 Total loss: 0.89487 timestamp: 1655077011.3661463 iteration: 87895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14006 FastRCNN class loss: 0.06012 FastRCNN total loss: 0.20018 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.11879 RPN box loss: 0.01798 RPN score loss: 0.00483 RPN total loss: 0.02281 Total loss: 0.90408 timestamp: 1655077014.6497111 iteration: 87900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06222 FastRCNN class loss: 0.07614 FastRCNN total loss: 0.13836 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.14648 RPN box loss: 0.00478 RPN score loss: 0.00124 RPN total loss: 0.00603 Total loss: 0.85316 timestamp: 1655077017.9171984 iteration: 87905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0998 FastRCNN class loss: 0.07951 FastRCNN total loss: 0.17931 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.13369 RPN box loss: 0.01549 RPN score loss: 0.0102 RPN total loss: 0.02568 Total loss: 0.90097 timestamp: 1655077021.1651025 iteration: 87910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05442 FastRCNN class loss: 0.04246 FastRCNN total loss: 0.09688 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.10999 RPN box loss: 0.00809 RPN score loss: 0.00254 RPN total loss: 0.01063 Total loss: 0.7798 timestamp: 1655077024.4074404 iteration: 87915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10901 FastRCNN class loss: 0.06032 FastRCNN total loss: 0.16933 L1 loss: 0.0000e+00 L2 loss: 0.5623 Learning rate: 4.0000e-05 Mask loss: 0.137 RPN box loss: 0.02463 RPN score loss: 0.00456 RPN total loss: 0.02919 Total loss: 0.89781 timestamp: 1655077027.726314 iteration: 87920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14416 FastRCNN class loss: 0.06082 FastRCNN total loss: 0.20498 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.1256 RPN box loss: 0.00573 RPN score loss: 0.00117 RPN total loss: 0.0069 Total loss: 0.89977 timestamp: 1655077031.006742 iteration: 87925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0773 FastRCNN class loss: 0.05409 FastRCNN total loss: 0.13138 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13253 RPN box loss: 0.00344 RPN score loss: 0.00393 RPN total loss: 0.00737 Total loss: 0.83358 timestamp: 1655077034.2622848 iteration: 87930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.081 FastRCNN class loss: 0.06563 FastRCNN total loss: 0.14663 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13971 RPN box loss: 0.00571 RPN score loss: 0.00188 RPN total loss: 0.00759 Total loss: 0.85622 timestamp: 1655077037.554848 iteration: 87935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07507 FastRCNN class loss: 0.06442 FastRCNN total loss: 0.13949 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.11012 RPN box loss: 0.00743 RPN score loss: 0.00396 RPN total loss: 0.01138 Total loss: 0.8233 timestamp: 1655077040.8341105 iteration: 87940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08495 FastRCNN class loss: 0.07136 FastRCNN total loss: 0.15631 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.10373 RPN box loss: 0.00417 RPN score loss: 0.00215 RPN total loss: 0.00632 Total loss: 0.82866 timestamp: 1655077044.111235 iteration: 87945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08987 FastRCNN class loss: 0.05174 FastRCNN total loss: 0.14161 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.11893 RPN box loss: 0.01226 RPN score loss: 0.00193 RPN total loss: 0.01418 Total loss: 0.83702 timestamp: 1655077047.372162 iteration: 87950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06817 FastRCNN class loss: 0.03911 FastRCNN total loss: 0.10728 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.10556 RPN box loss: 0.00444 RPN score loss: 0.00522 RPN total loss: 0.00966 Total loss: 0.78479 timestamp: 1655077050.6229277 iteration: 87955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10358 FastRCNN class loss: 0.07211 FastRCNN total loss: 0.1757 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13672 RPN box loss: 0.01744 RPN score loss: 0.00836 RPN total loss: 0.02579 Total loss: 0.9005 timestamp: 1655077053.8267007 iteration: 87960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13442 FastRCNN class loss: 0.06147 FastRCNN total loss: 0.1959 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15641 RPN box loss: 0.04433 RPN score loss: 0.00824 RPN total loss: 0.05257 Total loss: 0.96717 timestamp: 1655077057.1056206 iteration: 87965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08695 FastRCNN class loss: 0.05439 FastRCNN total loss: 0.14134 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.09516 RPN box loss: 0.0041 RPN score loss: 0.00516 RPN total loss: 0.00926 Total loss: 0.80805 timestamp: 1655077060.403165 iteration: 87970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09079 FastRCNN class loss: 0.0522 FastRCNN total loss: 0.143 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14011 RPN box loss: 0.01242 RPN score loss: 0.00181 RPN total loss: 0.01423 Total loss: 0.85963 timestamp: 1655077063.627928 iteration: 87975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0803 FastRCNN class loss: 0.07812 FastRCNN total loss: 0.15842 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12993 RPN box loss: 0.01862 RPN score loss: 0.00728 RPN total loss: 0.0259 Total loss: 0.87654 timestamp: 1655077066.9721646 iteration: 87980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08876 FastRCNN class loss: 0.08145 FastRCNN total loss: 0.1702 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12975 RPN box loss: 0.0123 RPN score loss: 0.00406 RPN total loss: 0.01636 Total loss: 0.87861 timestamp: 1655077070.2764196 iteration: 87985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10727 FastRCNN class loss: 0.06818 FastRCNN total loss: 0.17544 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14378 RPN box loss: 0.00969 RPN score loss: 0.00753 RPN total loss: 0.01722 Total loss: 0.89874 timestamp: 1655077073.557953 iteration: 87990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12536 FastRCNN class loss: 0.09703 FastRCNN total loss: 0.22239 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13512 RPN box loss: 0.01232 RPN score loss: 0.00445 RPN total loss: 0.01677 Total loss: 0.93657 timestamp: 1655077076.867358 iteration: 87995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08431 FastRCNN class loss: 0.08023 FastRCNN total loss: 0.16453 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14227 RPN box loss: 0.01432 RPN score loss: 0.00529 RPN total loss: 0.0196 Total loss: 0.88869 timestamp: 1655077080.1790292 iteration: 88000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06953 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.11792 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.16607 RPN box loss: 0.00748 RPN score loss: 0.0031 RPN total loss: 0.01059 Total loss: 0.85687 timestamp: 1655077083.518823 iteration: 88005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08125 FastRCNN class loss: 0.06701 FastRCNN total loss: 0.14826 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.0979 RPN box loss: 0.00779 RPN score loss: 0.00308 RPN total loss: 0.01086 Total loss: 0.81932 timestamp: 1655077086.8031611 iteration: 88010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1147 FastRCNN class loss: 0.07072 FastRCNN total loss: 0.18542 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14744 RPN box loss: 0.03929 RPN score loss: 0.00365 RPN total loss: 0.04294 Total loss: 0.93809 timestamp: 1655077090.1317494 iteration: 88015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08139 FastRCNN class loss: 0.08182 FastRCNN total loss: 0.16321 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.09111 RPN box loss: 0.01592 RPN score loss: 0.00657 RPN total loss: 0.02249 Total loss: 0.83911 timestamp: 1655077093.4189558 iteration: 88020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07124 FastRCNN class loss: 0.06843 FastRCNN total loss: 0.13967 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13937 RPN box loss: 0.0097 RPN score loss: 0.0037 RPN total loss: 0.01341 Total loss: 0.85473 timestamp: 1655077096.723382 iteration: 88025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13417 FastRCNN class loss: 0.06925 FastRCNN total loss: 0.20342 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.11878 RPN box loss: 0.01294 RPN score loss: 0.00618 RPN total loss: 0.01912 Total loss: 0.90361 timestamp: 1655077099.9803493 iteration: 88030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19366 FastRCNN class loss: 0.09146 FastRCNN total loss: 0.28511 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12064 RPN box loss: 0.01062 RPN score loss: 0.01217 RPN total loss: 0.02278 Total loss: 0.99083 timestamp: 1655077103.2289114 iteration: 88035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08536 FastRCNN class loss: 0.11273 FastRCNN total loss: 0.19809 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15083 RPN box loss: 0.02708 RPN score loss: 0.01315 RPN total loss: 0.04023 Total loss: 0.95144 timestamp: 1655077106.4723494 iteration: 88040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06766 FastRCNN class loss: 0.05312 FastRCNN total loss: 0.12078 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.08464 RPN box loss: 0.00548 RPN score loss: 0.00394 RPN total loss: 0.00942 Total loss: 0.77713 timestamp: 1655077109.7771814 iteration: 88045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12556 FastRCNN class loss: 0.08355 FastRCNN total loss: 0.2091 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15351 RPN box loss: 0.01324 RPN score loss: 0.0065 RPN total loss: 0.01973 Total loss: 0.94464 timestamp: 1655077113.0314062 iteration: 88050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08314 FastRCNN class loss: 0.04938 FastRCNN total loss: 0.13252 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12956 RPN box loss: 0.01121 RPN score loss: 0.00189 RPN total loss: 0.0131 Total loss: 0.83747 timestamp: 1655077116.3115418 iteration: 88055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08269 FastRCNN class loss: 0.05361 FastRCNN total loss: 0.13631 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15561 RPN box loss: 0.01755 RPN score loss: 0.00167 RPN total loss: 0.01921 Total loss: 0.87342 timestamp: 1655077119.6300006 iteration: 88060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05666 FastRCNN class loss: 0.06733 FastRCNN total loss: 0.12399 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.09176 RPN box loss: 0.00912 RPN score loss: 0.00236 RPN total loss: 0.01148 Total loss: 0.78951 timestamp: 1655077122.9777858 iteration: 88065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12659 FastRCNN class loss: 0.10731 FastRCNN total loss: 0.2339 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15624 RPN box loss: 0.01815 RPN score loss: 0.00484 RPN total loss: 0.023 Total loss: 0.97543 timestamp: 1655077126.307758 iteration: 88070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05673 FastRCNN class loss: 0.08115 FastRCNN total loss: 0.13787 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.17099 RPN box loss: 0.0178 RPN score loss: 0.00555 RPN total loss: 0.02335 Total loss: 0.89451 timestamp: 1655077129.5485663 iteration: 88075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07648 FastRCNN class loss: 0.08022 FastRCNN total loss: 0.1567 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.1763 RPN box loss: 0.01271 RPN score loss: 0.00367 RPN total loss: 0.01638 Total loss: 0.91167 timestamp: 1655077132.8521762 iteration: 88080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10346 FastRCNN class loss: 0.08242 FastRCNN total loss: 0.18588 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.16417 RPN box loss: 0.01172 RPN score loss: 0.00126 RPN total loss: 0.01298 Total loss: 0.92531 timestamp: 1655077136.1057854 iteration: 88085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05401 FastRCNN class loss: 0.05246 FastRCNN total loss: 0.10647 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.26609 RPN box loss: 0.00474 RPN score loss: 0.00046 RPN total loss: 0.0052 Total loss: 0.94005 timestamp: 1655077139.3660254 iteration: 88090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08415 FastRCNN class loss: 0.05398 FastRCNN total loss: 0.13813 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.11606 RPN box loss: 0.0112 RPN score loss: 0.00445 RPN total loss: 0.01565 Total loss: 0.83213 timestamp: 1655077142.669045 iteration: 88095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05756 FastRCNN class loss: 0.062 FastRCNN total loss: 0.11956 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.10018 RPN box loss: 0.02229 RPN score loss: 0.00436 RPN total loss: 0.02666 Total loss: 0.80869 timestamp: 1655077145.9115043 iteration: 88100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0615 FastRCNN class loss: 0.05585 FastRCNN total loss: 0.11735 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12925 RPN box loss: 0.00815 RPN score loss: 0.00363 RPN total loss: 0.01178 Total loss: 0.82067 timestamp: 1655077149.1426826 iteration: 88105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09344 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.16601 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.17904 RPN box loss: 0.04669 RPN score loss: 0.0125 RPN total loss: 0.05919 Total loss: 0.96653 timestamp: 1655077152.363301 iteration: 88110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09374 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.16079 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13689 RPN box loss: 0.00985 RPN score loss: 0.00159 RPN total loss: 0.01145 Total loss: 0.87142 timestamp: 1655077155.544009 iteration: 88115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0818 FastRCNN class loss: 0.06286 FastRCNN total loss: 0.14466 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12698 RPN box loss: 0.00626 RPN score loss: 0.00324 RPN total loss: 0.00951 Total loss: 0.84344 timestamp: 1655077158.80423 iteration: 88120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09225 FastRCNN class loss: 0.05125 FastRCNN total loss: 0.1435 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13544 RPN box loss: 0.01119 RPN score loss: 0.00138 RPN total loss: 0.01257 Total loss: 0.8538 timestamp: 1655077162.0731301 iteration: 88125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15466 FastRCNN class loss: 0.1332 FastRCNN total loss: 0.28785 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.18515 RPN box loss: 0.04384 RPN score loss: 0.00802 RPN total loss: 0.05187 Total loss: 1.08716 timestamp: 1655077165.3608887 iteration: 88130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08758 FastRCNN class loss: 0.04818 FastRCNN total loss: 0.13576 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.08024 RPN box loss: 0.01598 RPN score loss: 0.00559 RPN total loss: 0.02157 Total loss: 0.79986 timestamp: 1655077168.615637 iteration: 88135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06021 FastRCNN class loss: 0.04702 FastRCNN total loss: 0.10723 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.1307 RPN box loss: 0.00828 RPN score loss: 0.00392 RPN total loss: 0.0122 Total loss: 0.81242 timestamp: 1655077171.9261644 iteration: 88140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05733 FastRCNN class loss: 0.04839 FastRCNN total loss: 0.10572 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.0874 RPN box loss: 0.01381 RPN score loss: 0.00972 RPN total loss: 0.02353 Total loss: 0.77895 timestamp: 1655077175.163691 iteration: 88145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07554 FastRCNN class loss: 0.07135 FastRCNN total loss: 0.14688 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.2374 RPN box loss: 0.02863 RPN score loss: 0.00279 RPN total loss: 0.03141 Total loss: 0.97798 timestamp: 1655077178.3747387 iteration: 88150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11094 FastRCNN class loss: 0.18035 FastRCNN total loss: 0.29129 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13723 RPN box loss: 0.00903 RPN score loss: 0.0095 RPN total loss: 0.01853 Total loss: 1.00934 timestamp: 1655077181.6502774 iteration: 88155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07224 FastRCNN class loss: 0.04199 FastRCNN total loss: 0.11422 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13015 RPN box loss: 0.0066 RPN score loss: 0.00702 RPN total loss: 0.01362 Total loss: 0.82028 timestamp: 1655077184.9873192 iteration: 88160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12476 FastRCNN class loss: 0.09608 FastRCNN total loss: 0.22084 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15745 RPN box loss: 0.01672 RPN score loss: 0.00668 RPN total loss: 0.02341 Total loss: 0.96399 timestamp: 1655077188.23729 iteration: 88165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06177 FastRCNN class loss: 0.04806 FastRCNN total loss: 0.10983 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13917 RPN box loss: 0.01918 RPN score loss: 0.00533 RPN total loss: 0.02451 Total loss: 0.83579 timestamp: 1655077191.4104333 iteration: 88170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09998 FastRCNN class loss: 0.08213 FastRCNN total loss: 0.18211 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.19313 RPN box loss: 0.01078 RPN score loss: 0.00636 RPN total loss: 0.01714 Total loss: 0.95466 timestamp: 1655077194.6844754 iteration: 88175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08048 FastRCNN class loss: 0.06985 FastRCNN total loss: 0.15032 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13957 RPN box loss: 0.01187 RPN score loss: 0.0035 RPN total loss: 0.01537 Total loss: 0.86755 timestamp: 1655077197.9193099 iteration: 88180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08106 FastRCNN class loss: 0.09037 FastRCNN total loss: 0.17143 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15238 RPN box loss: 0.01089 RPN score loss: 0.00415 RPN total loss: 0.01504 Total loss: 0.90114 timestamp: 1655077201.2389405 iteration: 88185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09184 FastRCNN class loss: 0.05679 FastRCNN total loss: 0.14863 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13253 RPN box loss: 0.00397 RPN score loss: 0.00327 RPN total loss: 0.00723 Total loss: 0.85068 timestamp: 1655077204.5066037 iteration: 88190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08658 FastRCNN class loss: 0.06787 FastRCNN total loss: 0.15445 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12083 RPN box loss: 0.01463 RPN score loss: 0.00654 RPN total loss: 0.02118 Total loss: 0.85874 timestamp: 1655077207.8011663 iteration: 88195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05337 FastRCNN class loss: 0.04 FastRCNN total loss: 0.09337 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.11508 RPN box loss: 0.00808 RPN score loss: 0.00252 RPN total loss: 0.0106 Total loss: 0.78133 timestamp: 1655077211.097783 iteration: 88200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09117 FastRCNN class loss: 0.0699 FastRCNN total loss: 0.16107 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12324 RPN box loss: 0.01334 RPN score loss: 0.00764 RPN total loss: 0.02099 Total loss: 0.86758 timestamp: 1655077214.3037374 iteration: 88205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08315 FastRCNN class loss: 0.06853 FastRCNN total loss: 0.15168 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12593 RPN box loss: 0.01038 RPN score loss: 0.0068 RPN total loss: 0.01718 Total loss: 0.85708 timestamp: 1655077217.6378386 iteration: 88210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09687 FastRCNN class loss: 0.05901 FastRCNN total loss: 0.15589 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.13292 RPN box loss: 0.03677 RPN score loss: 0.00478 RPN total loss: 0.04155 Total loss: 0.89264 timestamp: 1655077220.893326 iteration: 88215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09017 FastRCNN class loss: 0.03982 FastRCNN total loss: 0.12999 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.07834 RPN box loss: 0.01661 RPN score loss: 0.00359 RPN total loss: 0.02019 Total loss: 0.7908 timestamp: 1655077224.1534123 iteration: 88220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06914 FastRCNN class loss: 0.0649 FastRCNN total loss: 0.13404 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12761 RPN box loss: 0.01158 RPN score loss: 0.00222 RPN total loss: 0.0138 Total loss: 0.83773 timestamp: 1655077227.451986 iteration: 88225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08242 FastRCNN class loss: 0.06603 FastRCNN total loss: 0.14844 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14793 RPN box loss: 0.00994 RPN score loss: 0.00625 RPN total loss: 0.01619 Total loss: 0.87485 timestamp: 1655077230.7860029 iteration: 88230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11015 FastRCNN class loss: 0.07926 FastRCNN total loss: 0.18941 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.14384 RPN box loss: 0.00855 RPN score loss: 0.00319 RPN total loss: 0.01173 Total loss: 0.90727 timestamp: 1655077234.049518 iteration: 88235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05914 FastRCNN class loss: 0.03782 FastRCNN total loss: 0.09697 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.1189 RPN box loss: 0.01525 RPN score loss: 0.00124 RPN total loss: 0.01649 Total loss: 0.79464 timestamp: 1655077237.2738729 iteration: 88240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10143 FastRCNN class loss: 0.07884 FastRCNN total loss: 0.18027 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.15676 RPN box loss: 0.01709 RPN score loss: 0.00879 RPN total loss: 0.02588 Total loss: 0.9252 timestamp: 1655077240.588341 iteration: 88245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08404 FastRCNN class loss: 0.05995 FastRCNN total loss: 0.144 L1 loss: 0.0000e+00 L2 loss: 0.56229 Learning rate: 4.0000e-05 Mask loss: 0.12648 RPN box loss: 0.00842 RPN score loss: 0.00189 RPN total loss: 0.01031 Total loss: 0.84308 timestamp: 1655077243.8785372 iteration: 88250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1593 FastRCNN class loss: 0.1229 FastRCNN total loss: 0.2822 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.22443 RPN box loss: 0.00666 RPN score loss: 0.0102 RPN total loss: 0.01685 Total loss: 1.08577 timestamp: 1655077247.1484764 iteration: 88255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06644 FastRCNN class loss: 0.03148 FastRCNN total loss: 0.09792 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.10599 RPN box loss: 0.0071 RPN score loss: 0.00201 RPN total loss: 0.00911 Total loss: 0.7753 timestamp: 1655077250.4077184 iteration: 88260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09219 FastRCNN class loss: 0.06096 FastRCNN total loss: 0.15315 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13032 RPN box loss: 0.01339 RPN score loss: 0.00143 RPN total loss: 0.01482 Total loss: 0.86058 timestamp: 1655077253.6730857 iteration: 88265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12713 FastRCNN class loss: 0.05293 FastRCNN total loss: 0.18006 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14257 RPN box loss: 0.00791 RPN score loss: 0.00234 RPN total loss: 0.01025 Total loss: 0.89517 timestamp: 1655077256.9391322 iteration: 88270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12062 FastRCNN class loss: 0.07947 FastRCNN total loss: 0.2001 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.253 RPN box loss: 0.02346 RPN score loss: 0.0074 RPN total loss: 0.03086 Total loss: 1.04625 timestamp: 1655077260.1836178 iteration: 88275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09432 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.17362 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13599 RPN box loss: 0.00779 RPN score loss: 0.00402 RPN total loss: 0.0118 Total loss: 0.8837 timestamp: 1655077263.5139794 iteration: 88280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1174 FastRCNN class loss: 0.06265 FastRCNN total loss: 0.18006 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13932 RPN box loss: 0.00828 RPN score loss: 0.0041 RPN total loss: 0.01238 Total loss: 0.89405 timestamp: 1655077266.816854 iteration: 88285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10615 FastRCNN class loss: 0.04462 FastRCNN total loss: 0.15078 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.11492 RPN box loss: 0.00939 RPN score loss: 0.00519 RPN total loss: 0.01458 Total loss: 0.84255 timestamp: 1655077270.1073866 iteration: 88290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1312 FastRCNN class loss: 0.07259 FastRCNN total loss: 0.20379 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.20087 RPN box loss: 0.01349 RPN score loss: 0.00299 RPN total loss: 0.01647 Total loss: 0.98342 timestamp: 1655077273.3586462 iteration: 88295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.073 FastRCNN class loss: 0.08255 FastRCNN total loss: 0.15555 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15663 RPN box loss: 0.01165 RPN score loss: 0.00886 RPN total loss: 0.0205 Total loss: 0.89497 timestamp: 1655077276.6464992 iteration: 88300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1162 FastRCNN class loss: 0.13477 FastRCNN total loss: 0.25097 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.18089 RPN box loss: 0.02421 RPN score loss: 0.00848 RPN total loss: 0.03269 Total loss: 1.02684 timestamp: 1655077279.9179232 iteration: 88305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12866 FastRCNN class loss: 0.05769 FastRCNN total loss: 0.18635 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.1055 RPN box loss: 0.02226 RPN score loss: 0.0021 RPN total loss: 0.02436 Total loss: 0.8785 timestamp: 1655077283.2216418 iteration: 88310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14833 FastRCNN class loss: 0.10602 FastRCNN total loss: 0.25435 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.20727 RPN box loss: 0.03134 RPN score loss: 0.02031 RPN total loss: 0.05166 Total loss: 1.07555 timestamp: 1655077286.4613385 iteration: 88315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12742 FastRCNN class loss: 0.10878 FastRCNN total loss: 0.2362 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15421 RPN box loss: 0.01864 RPN score loss: 0.00819 RPN total loss: 0.02683 Total loss: 0.97952 timestamp: 1655077289.709261 iteration: 88320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07887 FastRCNN class loss: 0.07622 FastRCNN total loss: 0.15509 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13995 RPN box loss: 0.01141 RPN score loss: 0.01161 RPN total loss: 0.02302 Total loss: 0.88034 timestamp: 1655077292.9259396 iteration: 88325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05021 FastRCNN class loss: 0.05984 FastRCNN total loss: 0.11005 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.08992 RPN box loss: 0.00676 RPN score loss: 0.00477 RPN total loss: 0.01153 Total loss: 0.77378 timestamp: 1655077296.2102525 iteration: 88330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06595 FastRCNN class loss: 0.05374 FastRCNN total loss: 0.11969 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13447 RPN box loss: 0.00376 RPN score loss: 0.00208 RPN total loss: 0.00584 Total loss: 0.82229 timestamp: 1655077299.571251 iteration: 88335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07236 FastRCNN class loss: 0.07451 FastRCNN total loss: 0.14687 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14495 RPN box loss: 0.0137 RPN score loss: 0.00524 RPN total loss: 0.01893 Total loss: 0.87304 timestamp: 1655077302.8306782 iteration: 88340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0896 FastRCNN class loss: 0.06947 FastRCNN total loss: 0.15907 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13232 RPN box loss: 0.0175 RPN score loss: 0.00515 RPN total loss: 0.02265 Total loss: 0.87633 timestamp: 1655077306.1725452 iteration: 88345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07168 FastRCNN class loss: 0.05116 FastRCNN total loss: 0.12283 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15842 RPN box loss: 0.01026 RPN score loss: 0.00324 RPN total loss: 0.0135 Total loss: 0.85703 timestamp: 1655077309.4773564 iteration: 88350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1126 FastRCNN class loss: 0.07753 FastRCNN total loss: 0.19013 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.17305 RPN box loss: 0.01392 RPN score loss: 0.00256 RPN total loss: 0.01648 Total loss: 0.94193 timestamp: 1655077312.7660568 iteration: 88355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11143 FastRCNN class loss: 0.05906 FastRCNN total loss: 0.17048 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.145 RPN box loss: 0.02553 RPN score loss: 0.00617 RPN total loss: 0.0317 Total loss: 0.90947 timestamp: 1655077316.0741355 iteration: 88360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05658 FastRCNN class loss: 0.06668 FastRCNN total loss: 0.12326 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13616 RPN box loss: 0.00857 RPN score loss: 0.00335 RPN total loss: 0.01193 Total loss: 0.83363 timestamp: 1655077319.3654306 iteration: 88365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03971 FastRCNN class loss: 0.04178 FastRCNN total loss: 0.08149 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14085 RPN box loss: 0.00986 RPN score loss: 0.00084 RPN total loss: 0.0107 Total loss: 0.79532 timestamp: 1655077322.6707177 iteration: 88370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07574 FastRCNN class loss: 0.07371 FastRCNN total loss: 0.14945 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13427 RPN box loss: 0.01271 RPN score loss: 0.00197 RPN total loss: 0.01468 Total loss: 0.86068 timestamp: 1655077325.9454248 iteration: 88375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07917 FastRCNN class loss: 0.04239 FastRCNN total loss: 0.12156 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14244 RPN box loss: 0.0052 RPN score loss: 0.00316 RPN total loss: 0.00835 Total loss: 0.83463 timestamp: 1655077329.2899861 iteration: 88380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11317 FastRCNN class loss: 0.09875 FastRCNN total loss: 0.21192 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15443 RPN box loss: 0.02241 RPN score loss: 0.00811 RPN total loss: 0.03052 Total loss: 0.95915 timestamp: 1655077332.5766478 iteration: 88385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14032 FastRCNN class loss: 0.07066 FastRCNN total loss: 0.21098 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15571 RPN box loss: 0.00651 RPN score loss: 0.00339 RPN total loss: 0.0099 Total loss: 0.93887 timestamp: 1655077335.868434 iteration: 88390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09793 FastRCNN class loss: 0.07646 FastRCNN total loss: 0.17439 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14548 RPN box loss: 0.01065 RPN score loss: 0.00967 RPN total loss: 0.02032 Total loss: 0.90247 timestamp: 1655077339.1914666 iteration: 88395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07011 FastRCNN class loss: 0.04014 FastRCNN total loss: 0.11026 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.08701 RPN box loss: 0.01503 RPN score loss: 0.00306 RPN total loss: 0.01809 Total loss: 0.77764 timestamp: 1655077342.514119 iteration: 88400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12868 FastRCNN class loss: 0.10706 FastRCNN total loss: 0.23574 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.19535 RPN box loss: 0.04495 RPN score loss: 0.01301 RPN total loss: 0.05796 Total loss: 1.05133 timestamp: 1655077345.7916028 iteration: 88405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06204 FastRCNN class loss: 0.05512 FastRCNN total loss: 0.11716 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.10225 RPN box loss: 0.00725 RPN score loss: 0.00304 RPN total loss: 0.01029 Total loss: 0.79198 timestamp: 1655077349.0237927 iteration: 88410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1374 FastRCNN class loss: 0.13906 FastRCNN total loss: 0.27646 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.1586 RPN box loss: 0.01953 RPN score loss: 0.00871 RPN total loss: 0.02825 Total loss: 1.02558 timestamp: 1655077352.2786548 iteration: 88415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1449 FastRCNN class loss: 0.1118 FastRCNN total loss: 0.25671 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.16678 RPN box loss: 0.03537 RPN score loss: 0.00601 RPN total loss: 0.04139 Total loss: 1.02715 timestamp: 1655077355.5406282 iteration: 88420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05906 FastRCNN class loss: 0.07848 FastRCNN total loss: 0.13754 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.17879 RPN box loss: 0.02077 RPN score loss: 0.01077 RPN total loss: 0.03154 Total loss: 0.91015 timestamp: 1655077358.8220634 iteration: 88425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06683 FastRCNN class loss: 0.04492 FastRCNN total loss: 0.11175 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.07592 RPN box loss: 0.00635 RPN score loss: 0.00094 RPN total loss: 0.0073 Total loss: 0.75725 timestamp: 1655077362.0955293 iteration: 88430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15021 FastRCNN class loss: 0.07905 FastRCNN total loss: 0.22926 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.17229 RPN box loss: 0.01918 RPN score loss: 0.00621 RPN total loss: 0.02539 Total loss: 0.98922 timestamp: 1655077365.3381844 iteration: 88435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12483 FastRCNN class loss: 0.08106 FastRCNN total loss: 0.20589 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.16953 RPN box loss: 0.01146 RPN score loss: 0.00656 RPN total loss: 0.01802 Total loss: 0.95572 timestamp: 1655077368.5682552 iteration: 88440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05323 FastRCNN class loss: 0.04955 FastRCNN total loss: 0.10278 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13206 RPN box loss: 0.00497 RPN score loss: 0.00331 RPN total loss: 0.00828 Total loss: 0.80539 timestamp: 1655077371.7670798 iteration: 88445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08932 FastRCNN class loss: 0.0506 FastRCNN total loss: 0.13992 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.09667 RPN box loss: 0.01504 RPN score loss: 0.00377 RPN total loss: 0.01881 Total loss: 0.81768 timestamp: 1655077374.9966161 iteration: 88450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.19289 FastRCNN class loss: 0.08074 FastRCNN total loss: 0.27363 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.18915 RPN box loss: 0.01432 RPN score loss: 0.00422 RPN total loss: 0.01854 Total loss: 1.0436 timestamp: 1655077378.2265046 iteration: 88455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08833 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.16972 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14133 RPN box loss: 0.0231 RPN score loss: 0.01146 RPN total loss: 0.03456 Total loss: 0.9079 timestamp: 1655077381.56971 iteration: 88460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07865 FastRCNN class loss: 0.07228 FastRCNN total loss: 0.15093 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.18931 RPN box loss: 0.01985 RPN score loss: 0.00235 RPN total loss: 0.02219 Total loss: 0.92472 timestamp: 1655077384.8573604 iteration: 88465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0781 FastRCNN class loss: 0.04528 FastRCNN total loss: 0.12338 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.10987 RPN box loss: 0.00975 RPN score loss: 0.00393 RPN total loss: 0.01368 Total loss: 0.80921 timestamp: 1655077388.124471 iteration: 88470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06441 FastRCNN class loss: 0.05948 FastRCNN total loss: 0.12389 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.18793 RPN box loss: 0.01071 RPN score loss: 0.00567 RPN total loss: 0.01639 Total loss: 0.89049 timestamp: 1655077391.4453294 iteration: 88475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0611 FastRCNN class loss: 0.06828 FastRCNN total loss: 0.12938 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.11724 RPN box loss: 0.01406 RPN score loss: 0.00128 RPN total loss: 0.01535 Total loss: 0.82424 timestamp: 1655077394.6815445 iteration: 88480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10061 FastRCNN class loss: 0.06694 FastRCNN total loss: 0.16755 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.1774 RPN box loss: 0.01127 RPN score loss: 0.01744 RPN total loss: 0.02871 Total loss: 0.93594 timestamp: 1655077397.9082084 iteration: 88485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09508 FastRCNN class loss: 0.06493 FastRCNN total loss: 0.16001 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.13094 RPN box loss: 0.04635 RPN score loss: 0.00301 RPN total loss: 0.04936 Total loss: 0.90259 timestamp: 1655077401.2473075 iteration: 88490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05349 FastRCNN class loss: 0.06055 FastRCNN total loss: 0.11403 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.09302 RPN box loss: 0.02628 RPN score loss: 0.00154 RPN total loss: 0.02782 Total loss: 0.79715 timestamp: 1655077404.5177057 iteration: 88495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06151 FastRCNN class loss: 0.05471 FastRCNN total loss: 0.11622 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.07156 RPN box loss: 0.00652 RPN score loss: 0.00725 RPN total loss: 0.01377 Total loss: 0.76383 timestamp: 1655077407.859076 iteration: 88500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1064 FastRCNN class loss: 0.0793 FastRCNN total loss: 0.1857 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.19787 RPN box loss: 0.03386 RPN score loss: 0.00136 RPN total loss: 0.03522 Total loss: 0.98107 timestamp: 1655077411.2334898 iteration: 88505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06707 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.12901 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.14932 RPN box loss: 0.01031 RPN score loss: 0.00564 RPN total loss: 0.01595 Total loss: 0.85655 timestamp: 1655077414.597033 iteration: 88510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1403 FastRCNN class loss: 0.07364 FastRCNN total loss: 0.21394 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.21447 RPN box loss: 0.00531 RPN score loss: 0.00202 RPN total loss: 0.00733 Total loss: 0.99802 timestamp: 1655077417.7984858 iteration: 88515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08599 FastRCNN class loss: 0.0496 FastRCNN total loss: 0.13559 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.09323 RPN box loss: 0.01061 RPN score loss: 0.00375 RPN total loss: 0.01437 Total loss: 0.80547 timestamp: 1655077421.1035485 iteration: 88520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07115 FastRCNN class loss: 0.04345 FastRCNN total loss: 0.1146 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.12763 RPN box loss: 0.00602 RPN score loss: 0.00045 RPN total loss: 0.00647 Total loss: 0.81098 timestamp: 1655077424.3824923 iteration: 88525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07654 FastRCNN class loss: 0.05297 FastRCNN total loss: 0.12951 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.08357 RPN box loss: 0.0089 RPN score loss: 0.00078 RPN total loss: 0.00968 Total loss: 0.78504 timestamp: 1655077427.637348 iteration: 88530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1314 FastRCNN class loss: 0.08117 FastRCNN total loss: 0.21257 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.1428 RPN box loss: 0.00473 RPN score loss: 0.00328 RPN total loss: 0.00801 Total loss: 0.92566 timestamp: 1655077430.8830483 iteration: 88535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09353 FastRCNN class loss: 0.08698 FastRCNN total loss: 0.18051 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.23037 RPN box loss: 0.01258 RPN score loss: 0.00163 RPN total loss: 0.01421 Total loss: 0.98737 timestamp: 1655077434.217176 iteration: 88540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16772 FastRCNN class loss: 0.0947 FastRCNN total loss: 0.26242 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.12672 RPN box loss: 0.00808 RPN score loss: 0.00438 RPN total loss: 0.01245 Total loss: 0.96387 timestamp: 1655077437.4979537 iteration: 88545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06646 FastRCNN class loss: 0.06705 FastRCNN total loss: 0.13351 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.15676 RPN box loss: 0.01381 RPN score loss: 0.0029 RPN total loss: 0.01671 Total loss: 0.86926 timestamp: 1655077440.7126417 iteration: 88550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07837 FastRCNN class loss: 0.06926 FastRCNN total loss: 0.14763 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.17687 RPN box loss: 0.00734 RPN score loss: 0.00875 RPN total loss: 0.01609 Total loss: 0.90287 timestamp: 1655077443.9937816 iteration: 88555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12233 FastRCNN class loss: 0.10165 FastRCNN total loss: 0.22399 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.20808 RPN box loss: 0.02215 RPN score loss: 0.00975 RPN total loss: 0.0319 Total loss: 1.02625 timestamp: 1655077447.2864969 iteration: 88560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0968 FastRCNN class loss: 0.08639 FastRCNN total loss: 0.18319 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.19573 RPN box loss: 0.02641 RPN score loss: 0.00855 RPN total loss: 0.03495 Total loss: 0.97614 timestamp: 1655077450.5557022 iteration: 88565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05874 FastRCNN class loss: 0.05999 FastRCNN total loss: 0.11873 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.11709 RPN box loss: 0.00751 RPN score loss: 0.00496 RPN total loss: 0.01247 Total loss: 0.81057 timestamp: 1655077453.8319561 iteration: 88570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09719 FastRCNN class loss: 0.06469 FastRCNN total loss: 0.16188 L1 loss: 0.0000e+00 L2 loss: 0.56228 Learning rate: 4.0000e-05 Mask loss: 0.11688 RPN box loss: 0.00725 RPN score loss: 0.00211 RPN total loss: 0.00936 Total loss: 0.85039 timestamp: 1655077457.0464501 iteration: 88575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11432 FastRCNN class loss: 0.06759 FastRCNN total loss: 0.18191 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11938 RPN box loss: 0.01202 RPN score loss: 0.01098 RPN total loss: 0.02301 Total loss: 0.88658 timestamp: 1655077460.3028948 iteration: 88580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06058 FastRCNN class loss: 0.06083 FastRCNN total loss: 0.12141 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.1204 RPN box loss: 0.01451 RPN score loss: 0.00314 RPN total loss: 0.01766 Total loss: 0.82174 timestamp: 1655077463.5889313 iteration: 88585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08408 FastRCNN class loss: 0.07826 FastRCNN total loss: 0.16234 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14368 RPN box loss: 0.01742 RPN score loss: 0.00934 RPN total loss: 0.02676 Total loss: 0.89505 timestamp: 1655077466.8604162 iteration: 88590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11289 FastRCNN class loss: 0.08848 FastRCNN total loss: 0.20137 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.19578 RPN box loss: 0.01887 RPN score loss: 0.00252 RPN total loss: 0.02139 Total loss: 0.98081 timestamp: 1655077470.113458 iteration: 88595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08402 FastRCNN class loss: 0.07573 FastRCNN total loss: 0.15974 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.18087 RPN box loss: 0.00511 RPN score loss: 0.00173 RPN total loss: 0.00683 Total loss: 0.90972 timestamp: 1655077473.4069223 iteration: 88600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11133 FastRCNN class loss: 0.11212 FastRCNN total loss: 0.22345 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16646 RPN box loss: 0.01857 RPN score loss: 0.01515 RPN total loss: 0.03372 Total loss: 0.9859 timestamp: 1655077476.751829 iteration: 88605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06685 FastRCNN class loss: 0.08453 FastRCNN total loss: 0.15139 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14221 RPN box loss: 0.0089 RPN score loss: 0.00623 RPN total loss: 0.01513 Total loss: 0.871 timestamp: 1655077480.069023 iteration: 88610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08461 FastRCNN class loss: 0.0579 FastRCNN total loss: 0.14252 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15226 RPN box loss: 0.00619 RPN score loss: 0.00477 RPN total loss: 0.01096 Total loss: 0.86801 timestamp: 1655077483.3558397 iteration: 88615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11481 FastRCNN class loss: 0.07638 FastRCNN total loss: 0.19118 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15953 RPN box loss: 0.02688 RPN score loss: 0.00684 RPN total loss: 0.03372 Total loss: 0.94671 timestamp: 1655077486.6087978 iteration: 88620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05308 FastRCNN class loss: 0.06296 FastRCNN total loss: 0.11604 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.10525 RPN box loss: 0.00597 RPN score loss: 0.01019 RPN total loss: 0.01616 Total loss: 0.79972 timestamp: 1655077489.8976579 iteration: 88625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08653 FastRCNN class loss: 0.05862 FastRCNN total loss: 0.14515 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.1626 RPN box loss: 0.01282 RPN score loss: 0.00254 RPN total loss: 0.01537 Total loss: 0.88539 timestamp: 1655077493.2177775 iteration: 88630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06252 FastRCNN class loss: 0.04289 FastRCNN total loss: 0.1054 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.09458 RPN box loss: 0.00969 RPN score loss: 0.00117 RPN total loss: 0.01086 Total loss: 0.77312 timestamp: 1655077496.405006 iteration: 88635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14091 FastRCNN class loss: 0.09916 FastRCNN total loss: 0.24008 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.17208 RPN box loss: 0.02325 RPN score loss: 0.01239 RPN total loss: 0.03564 Total loss: 1.01007 timestamp: 1655077499.6943424 iteration: 88640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11442 FastRCNN class loss: 0.07883 FastRCNN total loss: 0.19324 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.13535 RPN box loss: 0.00756 RPN score loss: 0.00469 RPN total loss: 0.01225 Total loss: 0.90311 timestamp: 1655077502.9374216 iteration: 88645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0589 FastRCNN class loss: 0.05898 FastRCNN total loss: 0.11788 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.12134 RPN box loss: 0.01233 RPN score loss: 0.00659 RPN total loss: 0.01893 Total loss: 0.82042 timestamp: 1655077506.1814873 iteration: 88650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10865 FastRCNN class loss: 0.07936 FastRCNN total loss: 0.18801 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.13103 RPN box loss: 0.01428 RPN score loss: 0.00263 RPN total loss: 0.01691 Total loss: 0.89822 timestamp: 1655077509.4665368 iteration: 88655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11257 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.19098 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.172 RPN box loss: 0.01272 RPN score loss: 0.00186 RPN total loss: 0.01458 Total loss: 0.93983 timestamp: 1655077512.738244 iteration: 88660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14709 FastRCNN class loss: 0.15777 FastRCNN total loss: 0.30486 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.18965 RPN box loss: 0.01175 RPN score loss: 0.01193 RPN total loss: 0.02368 Total loss: 1.08046 timestamp: 1655077515.9629679 iteration: 88665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05067 FastRCNN class loss: 0.0394 FastRCNN total loss: 0.09007 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11848 RPN box loss: 0.00663 RPN score loss: 0.0033 RPN total loss: 0.00993 Total loss: 0.78074 timestamp: 1655077519.2069116 iteration: 88670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0946 FastRCNN class loss: 0.07825 FastRCNN total loss: 0.17285 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16105 RPN box loss: 0.01131 RPN score loss: 0.00641 RPN total loss: 0.01772 Total loss: 0.91389 timestamp: 1655077522.5403223 iteration: 88675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09024 FastRCNN class loss: 0.05601 FastRCNN total loss: 0.14625 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11796 RPN box loss: 0.00638 RPN score loss: 0.01215 RPN total loss: 0.01854 Total loss: 0.84502 timestamp: 1655077525.8011913 iteration: 88680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07357 FastRCNN class loss: 0.02805 FastRCNN total loss: 0.10162 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.09384 RPN box loss: 0.00822 RPN score loss: 0.00209 RPN total loss: 0.01031 Total loss: 0.76804 timestamp: 1655077529.033434 iteration: 88685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14371 FastRCNN class loss: 0.1037 FastRCNN total loss: 0.2474 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.1478 RPN box loss: 0.02156 RPN score loss: 0.00592 RPN total loss: 0.02748 Total loss: 0.98495 timestamp: 1655077532.2761664 iteration: 88690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04735 FastRCNN class loss: 0.05666 FastRCNN total loss: 0.10401 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14072 RPN box loss: 0.00632 RPN score loss: 0.00112 RPN total loss: 0.00744 Total loss: 0.81445 timestamp: 1655077535.4735174 iteration: 88695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05589 FastRCNN class loss: 0.05131 FastRCNN total loss: 0.1072 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14171 RPN box loss: 0.00782 RPN score loss: 0.00183 RPN total loss: 0.00965 Total loss: 0.82083 timestamp: 1655077538.725578 iteration: 88700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11679 FastRCNN class loss: 0.07681 FastRCNN total loss: 0.1936 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16813 RPN box loss: 0.01748 RPN score loss: 0.00169 RPN total loss: 0.01917 Total loss: 0.94317 timestamp: 1655077542.0424685 iteration: 88705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11608 FastRCNN class loss: 0.06992 FastRCNN total loss: 0.186 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.12474 RPN box loss: 0.00674 RPN score loss: 0.00953 RPN total loss: 0.01627 Total loss: 0.88928 timestamp: 1655077545.362677 iteration: 88710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1166 FastRCNN class loss: 0.04329 FastRCNN total loss: 0.15989 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.12037 RPN box loss: 0.00289 RPN score loss: 0.0042 RPN total loss: 0.00709 Total loss: 0.84962 timestamp: 1655077548.5867512 iteration: 88715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11368 FastRCNN class loss: 0.08123 FastRCNN total loss: 0.19491 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15811 RPN box loss: 0.01618 RPN score loss: 0.01356 RPN total loss: 0.02974 Total loss: 0.94503 timestamp: 1655077551.923801 iteration: 88720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14555 FastRCNN class loss: 0.0859 FastRCNN total loss: 0.23145 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15722 RPN box loss: 0.0124 RPN score loss: 0.00545 RPN total loss: 0.01786 Total loss: 0.9688 timestamp: 1655077555.1563482 iteration: 88725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04515 FastRCNN class loss: 0.04238 FastRCNN total loss: 0.08753 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.09634 RPN box loss: 0.00546 RPN score loss: 0.00158 RPN total loss: 0.00704 Total loss: 0.75317 timestamp: 1655077558.4135263 iteration: 88730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.17101 FastRCNN class loss: 0.10216 FastRCNN total loss: 0.27317 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11882 RPN box loss: 0.02954 RPN score loss: 0.00797 RPN total loss: 0.03751 Total loss: 0.99176 timestamp: 1655077561.6356294 iteration: 88735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0905 FastRCNN class loss: 0.10064 FastRCNN total loss: 0.19114 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.18965 RPN box loss: 0.01733 RPN score loss: 0.00895 RPN total loss: 0.02628 Total loss: 0.96934 timestamp: 1655077564.9205108 iteration: 88740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12606 FastRCNN class loss: 0.09241 FastRCNN total loss: 0.21847 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.18607 RPN box loss: 0.02765 RPN score loss: 0.00496 RPN total loss: 0.03261 Total loss: 0.99942 timestamp: 1655077568.247242 iteration: 88745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04896 FastRCNN class loss: 0.03659 FastRCNN total loss: 0.08555 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11465 RPN box loss: 0.00733 RPN score loss: 0.0012 RPN total loss: 0.00853 Total loss: 0.771 timestamp: 1655077571.5872226 iteration: 88750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04872 FastRCNN class loss: 0.0658 FastRCNN total loss: 0.11452 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16848 RPN box loss: 0.00539 RPN score loss: 0.00975 RPN total loss: 0.01514 Total loss: 0.86041 timestamp: 1655077574.8290772 iteration: 88755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11784 FastRCNN class loss: 0.0784 FastRCNN total loss: 0.19624 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11593 RPN box loss: 0.00663 RPN score loss: 0.0025 RPN total loss: 0.00913 Total loss: 0.88358 timestamp: 1655077578.118513 iteration: 88760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08047 FastRCNN class loss: 0.04498 FastRCNN total loss: 0.12546 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.13828 RPN box loss: 0.00613 RPN score loss: 0.00437 RPN total loss: 0.01051 Total loss: 0.83651 timestamp: 1655077581.4521246 iteration: 88765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12227 FastRCNN class loss: 0.10907 FastRCNN total loss: 0.23134 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16762 RPN box loss: 0.01749 RPN score loss: 0.00927 RPN total loss: 0.02675 Total loss: 0.98799 timestamp: 1655077584.743267 iteration: 88770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06807 FastRCNN class loss: 0.05198 FastRCNN total loss: 0.12005 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.11256 RPN box loss: 0.00864 RPN score loss: 0.00666 RPN total loss: 0.01531 Total loss: 0.81019 timestamp: 1655077588.0076685 iteration: 88775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12193 FastRCNN class loss: 0.1069 FastRCNN total loss: 0.22883 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.17091 RPN box loss: 0.01778 RPN score loss: 0.01144 RPN total loss: 0.02922 Total loss: 0.99122 timestamp: 1655077591.3633163 iteration: 88780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11651 FastRCNN class loss: 0.06194 FastRCNN total loss: 0.17845 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.10404 RPN box loss: 0.01402 RPN score loss: 0.00225 RPN total loss: 0.01628 Total loss: 0.86104 timestamp: 1655077594.6377995 iteration: 88785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07096 FastRCNN class loss: 0.04682 FastRCNN total loss: 0.11778 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.0852 RPN box loss: 0.01326 RPN score loss: 0.00391 RPN total loss: 0.01718 Total loss: 0.78242 timestamp: 1655077597.9412231 iteration: 88790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09108 FastRCNN class loss: 0.09159 FastRCNN total loss: 0.18267 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.17913 RPN box loss: 0.01596 RPN score loss: 0.00786 RPN total loss: 0.02382 Total loss: 0.94789 timestamp: 1655077601.1663167 iteration: 88795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10355 FastRCNN class loss: 0.06205 FastRCNN total loss: 0.1656 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14571 RPN box loss: 0.04733 RPN score loss: 0.00719 RPN total loss: 0.05452 Total loss: 0.9281 timestamp: 1655077604.4082208 iteration: 88800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10422 FastRCNN class loss: 0.05371 FastRCNN total loss: 0.15793 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.10833 RPN box loss: 0.00894 RPN score loss: 0.00684 RPN total loss: 0.01578 Total loss: 0.84431 timestamp: 1655077607.7212977 iteration: 88805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08743 FastRCNN class loss: 0.06498 FastRCNN total loss: 0.15241 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14252 RPN box loss: 0.01045 RPN score loss: 0.00218 RPN total loss: 0.01262 Total loss: 0.86982 timestamp: 1655077610.950817 iteration: 88810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04874 FastRCNN class loss: 0.03399 FastRCNN total loss: 0.08273 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15559 RPN box loss: 0.00633 RPN score loss: 0.00143 RPN total loss: 0.00776 Total loss: 0.80834 timestamp: 1655077614.2366426 iteration: 88815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09278 FastRCNN class loss: 0.06614 FastRCNN total loss: 0.15892 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.17852 RPN box loss: 0.01533 RPN score loss: 0.01386 RPN total loss: 0.02919 Total loss: 0.9289 timestamp: 1655077617.5297034 iteration: 88820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12162 FastRCNN class loss: 0.1284 FastRCNN total loss: 0.25001 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.22514 RPN box loss: 0.01615 RPN score loss: 0.03697 RPN total loss: 0.05311 Total loss: 1.09053 timestamp: 1655077620.7845726 iteration: 88825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09122 FastRCNN class loss: 0.07523 FastRCNN total loss: 0.16645 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.13284 RPN box loss: 0.00262 RPN score loss: 0.00355 RPN total loss: 0.00617 Total loss: 0.86773 timestamp: 1655077624.014837 iteration: 88830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05675 FastRCNN class loss: 0.04728 FastRCNN total loss: 0.10403 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14465 RPN box loss: 0.00808 RPN score loss: 0.00075 RPN total loss: 0.00883 Total loss: 0.81978 timestamp: 1655077627.371811 iteration: 88835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06397 FastRCNN class loss: 0.06415 FastRCNN total loss: 0.12811 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14559 RPN box loss: 0.01093 RPN score loss: 0.00888 RPN total loss: 0.0198 Total loss: 0.85577 timestamp: 1655077630.676394 iteration: 88840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07862 FastRCNN class loss: 0.05305 FastRCNN total loss: 0.13167 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.13306 RPN box loss: 0.00368 RPN score loss: 0.00446 RPN total loss: 0.00814 Total loss: 0.83514 timestamp: 1655077633.9553041 iteration: 88845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06918 FastRCNN class loss: 0.06676 FastRCNN total loss: 0.13594 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16061 RPN box loss: 0.01215 RPN score loss: 0.00192 RPN total loss: 0.01408 Total loss: 0.87289 timestamp: 1655077637.195742 iteration: 88850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11872 FastRCNN class loss: 0.05096 FastRCNN total loss: 0.16968 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.09338 RPN box loss: 0.01312 RPN score loss: 0.00655 RPN total loss: 0.01968 Total loss: 0.845 timestamp: 1655077640.4914405 iteration: 88855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1408 FastRCNN class loss: 0.08832 FastRCNN total loss: 0.22912 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15001 RPN box loss: 0.00884 RPN score loss: 0.0072 RPN total loss: 0.01604 Total loss: 0.95743 timestamp: 1655077643.8226817 iteration: 88860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09376 FastRCNN class loss: 0.06168 FastRCNN total loss: 0.15544 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.15761 RPN box loss: 0.00576 RPN score loss: 0.00412 RPN total loss: 0.00988 Total loss: 0.8852 timestamp: 1655077647.1100025 iteration: 88865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09098 FastRCNN class loss: 0.04058 FastRCNN total loss: 0.13157 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.14515 RPN box loss: 0.0191 RPN score loss: 0.00374 RPN total loss: 0.02284 Total loss: 0.86182 timestamp: 1655077650.4075084 iteration: 88870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09625 FastRCNN class loss: 0.1148 FastRCNN total loss: 0.21105 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.18117 RPN box loss: 0.0209 RPN score loss: 0.00563 RPN total loss: 0.02654 Total loss: 0.98102 timestamp: 1655077653.6436703 iteration: 88875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07453 FastRCNN class loss: 0.04702 FastRCNN total loss: 0.12155 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.10162 RPN box loss: 0.02211 RPN score loss: 0.00373 RPN total loss: 0.02584 Total loss: 0.81128 timestamp: 1655077656.933438 iteration: 88880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09324 FastRCNN class loss: 0.1192 FastRCNN total loss: 0.21245 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.16207 RPN box loss: 0.02178 RPN score loss: 0.0181 RPN total loss: 0.03989 Total loss: 0.97667 timestamp: 1655077660.1546195 iteration: 88885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0772 FastRCNN class loss: 0.04813 FastRCNN total loss: 0.12533 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.10888 RPN box loss: 0.00942 RPN score loss: 0.00316 RPN total loss: 0.01259 Total loss: 0.80906 timestamp: 1655077663.3749728 iteration: 88890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1188 FastRCNN class loss: 0.08316 FastRCNN total loss: 0.20196 L1 loss: 0.0000e+00 L2 loss: 0.56227 Learning rate: 4.0000e-05 Mask loss: 0.17088 RPN box loss: 0.02384 RPN score loss: 0.00306 RPN total loss: 0.0269 Total loss: 0.962 timestamp: 1655077666.697595 iteration: 88895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10335 FastRCNN class loss: 0.05686 FastRCNN total loss: 0.16021 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.14399 RPN box loss: 0.01528 RPN score loss: 0.00886 RPN total loss: 0.02413 Total loss: 0.8906 timestamp: 1655077669.9189258 iteration: 88900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04823 FastRCNN class loss: 0.05088 FastRCNN total loss: 0.09911 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10226 RPN box loss: 0.00646 RPN score loss: 0.00298 RPN total loss: 0.00944 Total loss: 0.77308 timestamp: 1655077673.2084646 iteration: 88905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07179 FastRCNN class loss: 0.08969 FastRCNN total loss: 0.16148 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13882 RPN box loss: 0.01391 RPN score loss: 0.00853 RPN total loss: 0.02244 Total loss: 0.885 timestamp: 1655077676.492233 iteration: 88910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09217 FastRCNN class loss: 0.11853 FastRCNN total loss: 0.21071 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16104 RPN box loss: 0.02796 RPN score loss: 0.01943 RPN total loss: 0.04739 Total loss: 0.9814 timestamp: 1655077679.7595472 iteration: 88915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14748 FastRCNN class loss: 0.07137 FastRCNN total loss: 0.21885 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15847 RPN box loss: 0.01193 RPN score loss: 0.00391 RPN total loss: 0.01584 Total loss: 0.95542 timestamp: 1655077683.0794988 iteration: 88920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09609 FastRCNN class loss: 0.09624 FastRCNN total loss: 0.19233 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.14065 RPN box loss: 0.0092 RPN score loss: 0.0052 RPN total loss: 0.0144 Total loss: 0.90965 timestamp: 1655077686.32928 iteration: 88925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.03493 FastRCNN class loss: 0.03378 FastRCNN total loss: 0.06872 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10489 RPN box loss: 0.00235 RPN score loss: 0.00278 RPN total loss: 0.00513 Total loss: 0.741 timestamp: 1655077689.6395237 iteration: 88930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07672 FastRCNN class loss: 0.07365 FastRCNN total loss: 0.15038 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10602 RPN box loss: 0.00923 RPN score loss: 0.00125 RPN total loss: 0.01048 Total loss: 0.82914 timestamp: 1655077692.9084022 iteration: 88935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.133 FastRCNN class loss: 0.12945 FastRCNN total loss: 0.26245 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.22528 RPN box loss: 0.01311 RPN score loss: 0.01441 RPN total loss: 0.02751 Total loss: 1.07751 timestamp: 1655077696.1756895 iteration: 88940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06819 FastRCNN class loss: 0.09594 FastRCNN total loss: 0.16413 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13795 RPN box loss: 0.01844 RPN score loss: 0.00402 RPN total loss: 0.02246 Total loss: 0.8868 timestamp: 1655077699.467294 iteration: 88945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12428 FastRCNN class loss: 0.09234 FastRCNN total loss: 0.21663 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.26233 RPN box loss: 0.01067 RPN score loss: 0.00286 RPN total loss: 0.01353 Total loss: 1.05475 timestamp: 1655077702.779456 iteration: 88950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08935 FastRCNN class loss: 0.0817 FastRCNN total loss: 0.17105 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.12795 RPN box loss: 0.00867 RPN score loss: 0.00466 RPN total loss: 0.01333 Total loss: 0.87459 timestamp: 1655077706.0206423 iteration: 88955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09557 FastRCNN class loss: 0.06837 FastRCNN total loss: 0.16394 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.1385 RPN box loss: 0.00539 RPN score loss: 0.00395 RPN total loss: 0.00934 Total loss: 0.87405 timestamp: 1655077709.282471 iteration: 88960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13299 FastRCNN class loss: 0.09885 FastRCNN total loss: 0.23184 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.14862 RPN box loss: 0.00916 RPN score loss: 0.00168 RPN total loss: 0.01084 Total loss: 0.95356 timestamp: 1655077712.551088 iteration: 88965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08585 FastRCNN class loss: 0.05157 FastRCNN total loss: 0.13742 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15687 RPN box loss: 0.04615 RPN score loss: 0.00432 RPN total loss: 0.05047 Total loss: 0.90702 timestamp: 1655077715.7914667 iteration: 88970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09049 FastRCNN class loss: 0.06859 FastRCNN total loss: 0.15909 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13658 RPN box loss: 0.01642 RPN score loss: 0.00262 RPN total loss: 0.01904 Total loss: 0.87697 timestamp: 1655077719.05129 iteration: 88975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11866 FastRCNN class loss: 0.10148 FastRCNN total loss: 0.22013 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15849 RPN box loss: 0.01324 RPN score loss: 0.00296 RPN total loss: 0.0162 Total loss: 0.95709 timestamp: 1655077722.328464 iteration: 88980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0745 FastRCNN class loss: 0.04272 FastRCNN total loss: 0.11722 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.09436 RPN box loss: 0.00786 RPN score loss: 0.00214 RPN total loss: 0.01 Total loss: 0.78384 timestamp: 1655077725.5905516 iteration: 88985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07523 FastRCNN class loss: 0.05024 FastRCNN total loss: 0.12546 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10076 RPN box loss: 0.01814 RPN score loss: 0.00145 RPN total loss: 0.01959 Total loss: 0.80808 timestamp: 1655077728.8405676 iteration: 88990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08622 FastRCNN class loss: 0.06602 FastRCNN total loss: 0.15224 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.12615 RPN box loss: 0.01237 RPN score loss: 0.00783 RPN total loss: 0.0202 Total loss: 0.86085 timestamp: 1655077732.0967314 iteration: 88995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06043 FastRCNN class loss: 0.06367 FastRCNN total loss: 0.12409 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11999 RPN box loss: 0.02075 RPN score loss: 0.01026 RPN total loss: 0.03101 Total loss: 0.83735 timestamp: 1655077735.4232829 iteration: 89000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08987 FastRCNN class loss: 0.03343 FastRCNN total loss: 0.1233 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10964 RPN box loss: 0.02456 RPN score loss: 0.00398 RPN total loss: 0.02854 Total loss: 0.82374 timestamp: 1655077738.800632 iteration: 89005 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12954 FastRCNN class loss: 0.07347 FastRCNN total loss: 0.20301 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16413 RPN box loss: 0.00781 RPN score loss: 0.00624 RPN total loss: 0.01405 Total loss: 0.94346 timestamp: 1655077742.1007261 iteration: 89010 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15892 FastRCNN class loss: 0.09977 FastRCNN total loss: 0.25869 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11633 RPN box loss: 0.00902 RPN score loss: 0.0027 RPN total loss: 0.01172 Total loss: 0.94901 timestamp: 1655077745.3961756 iteration: 89015 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08087 FastRCNN class loss: 0.07818 FastRCNN total loss: 0.15905 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16706 RPN box loss: 0.01163 RPN score loss: 0.00248 RPN total loss: 0.01411 Total loss: 0.90247 timestamp: 1655077748.6301606 iteration: 89020 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07799 FastRCNN class loss: 0.05848 FastRCNN total loss: 0.13647 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15039 RPN box loss: 0.01336 RPN score loss: 0.0045 RPN total loss: 0.01786 Total loss: 0.86698 timestamp: 1655077751.8697007 iteration: 89025 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0713 FastRCNN class loss: 0.08491 FastRCNN total loss: 0.15621 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13082 RPN box loss: 0.01397 RPN score loss: 0.00774 RPN total loss: 0.02171 Total loss: 0.871 timestamp: 1655077755.1063297 iteration: 89030 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05233 FastRCNN class loss: 0.03858 FastRCNN total loss: 0.09091 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11511 RPN box loss: 0.00632 RPN score loss: 0.00244 RPN total loss: 0.00876 Total loss: 0.77704 timestamp: 1655077758.3309283 iteration: 89035 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15016 FastRCNN class loss: 0.12927 FastRCNN total loss: 0.27943 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.24516 RPN box loss: 0.02129 RPN score loss: 0.00831 RPN total loss: 0.0296 Total loss: 1.11645 timestamp: 1655077761.63403 iteration: 89040 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15753 FastRCNN class loss: 0.15415 FastRCNN total loss: 0.31168 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.18622 RPN box loss: 0.01298 RPN score loss: 0.00444 RPN total loss: 0.01743 Total loss: 1.07759 timestamp: 1655077764.9097733 iteration: 89045 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12625 FastRCNN class loss: 0.08755 FastRCNN total loss: 0.2138 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15559 RPN box loss: 0.02158 RPN score loss: 0.00659 RPN total loss: 0.02817 Total loss: 0.95983 timestamp: 1655077768.2001603 iteration: 89050 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12417 FastRCNN class loss: 0.08587 FastRCNN total loss: 0.21004 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.1802 RPN box loss: 0.01629 RPN score loss: 0.00564 RPN total loss: 0.02193 Total loss: 0.97442 timestamp: 1655077771.4576862 iteration: 89055 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07165 FastRCNN class loss: 0.11377 FastRCNN total loss: 0.18542 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16016 RPN box loss: 0.00722 RPN score loss: 0.00159 RPN total loss: 0.00881 Total loss: 0.91665 timestamp: 1655077774.686887 iteration: 89060 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14131 FastRCNN class loss: 0.13831 FastRCNN total loss: 0.27962 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.12701 RPN box loss: 0.0139 RPN score loss: 0.00751 RPN total loss: 0.02141 Total loss: 0.99031 timestamp: 1655077777.9615579 iteration: 89065 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10291 FastRCNN class loss: 0.0601 FastRCNN total loss: 0.16301 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.1093 RPN box loss: 0.01957 RPN score loss: 0.00476 RPN total loss: 0.02433 Total loss: 0.85891 timestamp: 1655077781.2306094 iteration: 89070 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06214 FastRCNN class loss: 0.05864 FastRCNN total loss: 0.12078 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10827 RPN box loss: 0.01166 RPN score loss: 0.00091 RPN total loss: 0.01257 Total loss: 0.80388 timestamp: 1655077784.5917513 iteration: 89075 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13476 FastRCNN class loss: 0.08113 FastRCNN total loss: 0.21589 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15097 RPN box loss: 0.0099 RPN score loss: 0.00439 RPN total loss: 0.01429 Total loss: 0.94341 timestamp: 1655077787.848049 iteration: 89080 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06074 FastRCNN class loss: 0.05548 FastRCNN total loss: 0.11623 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10778 RPN box loss: 0.00692 RPN score loss: 0.0083 RPN total loss: 0.01521 Total loss: 0.80147 timestamp: 1655077791.1058557 iteration: 89085 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13231 FastRCNN class loss: 0.05621 FastRCNN total loss: 0.18851 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15251 RPN box loss: 0.00991 RPN score loss: 0.00437 RPN total loss: 0.01428 Total loss: 0.91756 timestamp: 1655077794.3425393 iteration: 89090 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04984 FastRCNN class loss: 0.03371 FastRCNN total loss: 0.08355 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.12995 RPN box loss: 0.01461 RPN score loss: 0.00169 RPN total loss: 0.0163 Total loss: 0.79205 timestamp: 1655077797.6043205 iteration: 89095 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07655 FastRCNN class loss: 0.04792 FastRCNN total loss: 0.12447 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.07936 RPN box loss: 0.01817 RPN score loss: 0.00121 RPN total loss: 0.01938 Total loss: 0.78547 timestamp: 1655077800.850199 iteration: 89100 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04733 FastRCNN class loss: 0.05761 FastRCNN total loss: 0.10494 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.09496 RPN box loss: 0.00592 RPN score loss: 0.00188 RPN total loss: 0.00779 Total loss: 0.76995 timestamp: 1655077804.1496174 iteration: 89105 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10339 FastRCNN class loss: 0.0696 FastRCNN total loss: 0.17299 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13775 RPN box loss: 0.05148 RPN score loss: 0.00787 RPN total loss: 0.05934 Total loss: 0.93234 timestamp: 1655077807.4706838 iteration: 89110 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08131 FastRCNN class loss: 0.12302 FastRCNN total loss: 0.20433 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13932 RPN box loss: 0.04982 RPN score loss: 0.01347 RPN total loss: 0.06329 Total loss: 0.9692 timestamp: 1655077810.799836 iteration: 89115 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07498 FastRCNN class loss: 0.09304 FastRCNN total loss: 0.16802 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11938 RPN box loss: 0.01442 RPN score loss: 0.00411 RPN total loss: 0.01853 Total loss: 0.86819 timestamp: 1655077814.0868697 iteration: 89120 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08179 FastRCNN class loss: 0.05534 FastRCNN total loss: 0.13713 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11581 RPN box loss: 0.0064 RPN score loss: 0.00478 RPN total loss: 0.01118 Total loss: 0.82638 timestamp: 1655077817.4317997 iteration: 89125 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07424 FastRCNN class loss: 0.04414 FastRCNN total loss: 0.11838 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11781 RPN box loss: 0.00983 RPN score loss: 0.00539 RPN total loss: 0.01522 Total loss: 0.81368 timestamp: 1655077820.6772044 iteration: 89130 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09042 FastRCNN class loss: 0.08323 FastRCNN total loss: 0.17365 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.18584 RPN box loss: 0.00552 RPN score loss: 0.00863 RPN total loss: 0.01415 Total loss: 0.93589 timestamp: 1655077823.922064 iteration: 89135 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09383 FastRCNN class loss: 0.06033 FastRCNN total loss: 0.15416 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.14536 RPN box loss: 0.03052 RPN score loss: 0.00373 RPN total loss: 0.03425 Total loss: 0.89603 timestamp: 1655077827.1168396 iteration: 89140 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1564 FastRCNN class loss: 0.08422 FastRCNN total loss: 0.24062 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.11777 RPN box loss: 0.01384 RPN score loss: 0.00277 RPN total loss: 0.01661 Total loss: 0.93725 timestamp: 1655077830.364905 iteration: 89145 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08155 FastRCNN class loss: 0.06669 FastRCNN total loss: 0.14824 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.17891 RPN box loss: 0.05026 RPN score loss: 0.00391 RPN total loss: 0.05417 Total loss: 0.94358 timestamp: 1655077833.6723666 iteration: 89150 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09608 FastRCNN class loss: 0.06469 FastRCNN total loss: 0.16077 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.19271 RPN box loss: 0.01607 RPN score loss: 0.03118 RPN total loss: 0.04725 Total loss: 0.96298 timestamp: 1655077836.9710011 iteration: 89155 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08656 FastRCNN class loss: 0.07189 FastRCNN total loss: 0.15845 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13818 RPN box loss: 0.00672 RPN score loss: 0.00402 RPN total loss: 0.01074 Total loss: 0.86963 timestamp: 1655077840.2786236 iteration: 89160 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10617 FastRCNN class loss: 0.07699 FastRCNN total loss: 0.18316 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16514 RPN box loss: 0.0053 RPN score loss: 0.00361 RPN total loss: 0.0089 Total loss: 0.91946 timestamp: 1655077843.5721395 iteration: 89165 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11156 FastRCNN class loss: 0.07225 FastRCNN total loss: 0.18381 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.14346 RPN box loss: 0.01335 RPN score loss: 0.01271 RPN total loss: 0.02605 Total loss: 0.91558 timestamp: 1655077846.866933 iteration: 89170 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07206 FastRCNN class loss: 0.04663 FastRCNN total loss: 0.11869 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.07025 RPN box loss: 0.00711 RPN score loss: 0.00621 RPN total loss: 0.01332 Total loss: 0.76452 timestamp: 1655077850.0333688 iteration: 89175 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08935 FastRCNN class loss: 0.04563 FastRCNN total loss: 0.13498 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.08922 RPN box loss: 0.00741 RPN score loss: 0.00581 RPN total loss: 0.01322 Total loss: 0.79968 timestamp: 1655077853.2617643 iteration: 89180 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06707 FastRCNN class loss: 0.07223 FastRCNN total loss: 0.1393 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.09588 RPN box loss: 0.00853 RPN score loss: 0.00361 RPN total loss: 0.01213 Total loss: 0.80957 timestamp: 1655077856.4681818 iteration: 89185 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10748 FastRCNN class loss: 0.07306 FastRCNN total loss: 0.18054 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.16875 RPN box loss: 0.02432 RPN score loss: 0.01125 RPN total loss: 0.03557 Total loss: 0.94712 timestamp: 1655077859.7305365 iteration: 89190 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06454 FastRCNN class loss: 0.07357 FastRCNN total loss: 0.13811 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.15079 RPN box loss: 0.00627 RPN score loss: 0.0057 RPN total loss: 0.01197 Total loss: 0.86313 timestamp: 1655077863.0385175 iteration: 89195 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06037 FastRCNN class loss: 0.05407 FastRCNN total loss: 0.11444 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13509 RPN box loss: 0.01453 RPN score loss: 0.00335 RPN total loss: 0.01788 Total loss: 0.82967 timestamp: 1655077866.3138404 iteration: 89200 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11189 FastRCNN class loss: 0.15776 FastRCNN total loss: 0.26966 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.12288 RPN box loss: 0.00821 RPN score loss: 0.00802 RPN total loss: 0.01623 Total loss: 0.97102 timestamp: 1655077869.6097128 iteration: 89205 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09948 FastRCNN class loss: 0.05329 FastRCNN total loss: 0.15277 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13505 RPN box loss: 0.00762 RPN score loss: 0.00416 RPN total loss: 0.01177 Total loss: 0.86185 timestamp: 1655077872.8368812 iteration: 89210 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05809 FastRCNN class loss: 0.03983 FastRCNN total loss: 0.09792 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.0754 RPN box loss: 0.00564 RPN score loss: 0.00388 RPN total loss: 0.00952 Total loss: 0.7451 timestamp: 1655077876.0606906 iteration: 89215 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09115 FastRCNN class loss: 0.06771 FastRCNN total loss: 0.15886 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.10496 RPN box loss: 0.00756 RPN score loss: 0.00138 RPN total loss: 0.00894 Total loss: 0.83502 timestamp: 1655077879.27904 iteration: 89220 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13016 FastRCNN class loss: 0.06573 FastRCNN total loss: 0.19589 L1 loss: 0.0000e+00 L2 loss: 0.56226 Learning rate: 4.0000e-05 Mask loss: 0.13348 RPN box loss: 0.01486 RPN score loss: 0.00541 RPN total loss: 0.02027 Total loss: 0.91189 timestamp: 1655077882.5552554 iteration: 89225 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0755 FastRCNN class loss: 0.06128 FastRCNN total loss: 0.13678 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14164 RPN box loss: 0.00898 RPN score loss: 0.00204 RPN total loss: 0.01102 Total loss: 0.85169 timestamp: 1655077885.9415643 iteration: 89230 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08908 FastRCNN class loss: 0.05478 FastRCNN total loss: 0.14385 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11435 RPN box loss: 0.01382 RPN score loss: 0.00496 RPN total loss: 0.01877 Total loss: 0.83924 timestamp: 1655077889.2615044 iteration: 89235 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07578 FastRCNN class loss: 0.05038 FastRCNN total loss: 0.12616 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.12138 RPN box loss: 0.00476 RPN score loss: 0.00523 RPN total loss: 0.00999 Total loss: 0.81979 timestamp: 1655077892.5837357 iteration: 89240 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07585 FastRCNN class loss: 0.11303 FastRCNN total loss: 0.18888 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.22055 RPN box loss: 0.01902 RPN score loss: 0.02867 RPN total loss: 0.04769 Total loss: 1.01938 timestamp: 1655077895.870102 iteration: 89245 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1265 FastRCNN class loss: 0.07527 FastRCNN total loss: 0.20177 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14445 RPN box loss: 0.01989 RPN score loss: 0.01172 RPN total loss: 0.0316 Total loss: 0.94009 timestamp: 1655077899.2346575 iteration: 89250 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10257 FastRCNN class loss: 0.09063 FastRCNN total loss: 0.1932 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13658 RPN box loss: 0.01368 RPN score loss: 0.00654 RPN total loss: 0.02023 Total loss: 0.91226 timestamp: 1655077902.4855573 iteration: 89255 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06613 FastRCNN class loss: 0.04287 FastRCNN total loss: 0.109 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16731 RPN box loss: 0.00677 RPN score loss: 0.00763 RPN total loss: 0.0144 Total loss: 0.85296 timestamp: 1655077905.7696052 iteration: 89260 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11468 FastRCNN class loss: 0.08778 FastRCNN total loss: 0.20246 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.17096 RPN box loss: 0.00859 RPN score loss: 0.00882 RPN total loss: 0.01742 Total loss: 0.95308 timestamp: 1655077909.0575297 iteration: 89265 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07645 FastRCNN class loss: 0.05838 FastRCNN total loss: 0.13483 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.17917 RPN box loss: 0.01831 RPN score loss: 0.0142 RPN total loss: 0.03251 Total loss: 0.90877 timestamp: 1655077912.3414085 iteration: 89270 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0745 FastRCNN class loss: 0.08078 FastRCNN total loss: 0.15528 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14435 RPN box loss: 0.02234 RPN score loss: 0.00178 RPN total loss: 0.02412 Total loss: 0.886 timestamp: 1655077915.6290753 iteration: 89275 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06856 FastRCNN class loss: 0.06212 FastRCNN total loss: 0.13068 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.09373 RPN box loss: 0.01543 RPN score loss: 0.00094 RPN total loss: 0.01636 Total loss: 0.80303 timestamp: 1655077918.9290009 iteration: 89280 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07375 FastRCNN class loss: 0.04298 FastRCNN total loss: 0.11673 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.10612 RPN box loss: 0.01416 RPN score loss: 0.00141 RPN total loss: 0.01557 Total loss: 0.80067 timestamp: 1655077922.1781585 iteration: 89285 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16009 FastRCNN class loss: 0.07525 FastRCNN total loss: 0.23534 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.12507 RPN box loss: 0.01102 RPN score loss: 0.00708 RPN total loss: 0.0181 Total loss: 0.94077 timestamp: 1655077925.4817197 iteration: 89290 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0839 FastRCNN class loss: 0.06345 FastRCNN total loss: 0.14735 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11356 RPN box loss: 0.00379 RPN score loss: 0.00143 RPN total loss: 0.00522 Total loss: 0.82839 timestamp: 1655077928.7775705 iteration: 89295 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06593 FastRCNN class loss: 0.04895 FastRCNN total loss: 0.11488 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11087 RPN box loss: 0.00497 RPN score loss: 0.00628 RPN total loss: 0.01124 Total loss: 0.79925 timestamp: 1655077931.9987075 iteration: 89300 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07326 FastRCNN class loss: 0.11 FastRCNN total loss: 0.18327 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13965 RPN box loss: 0.02033 RPN score loss: 0.00463 RPN total loss: 0.02496 Total loss: 0.91013 timestamp: 1655077935.3070266 iteration: 89305 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06768 FastRCNN class loss: 0.06728 FastRCNN total loss: 0.13496 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13234 RPN box loss: 0.0028 RPN score loss: 0.00173 RPN total loss: 0.00453 Total loss: 0.83408 timestamp: 1655077938.5788953 iteration: 89310 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05665 FastRCNN class loss: 0.03598 FastRCNN total loss: 0.09263 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.10738 RPN box loss: 0.04561 RPN score loss: 0.00308 RPN total loss: 0.0487 Total loss: 0.81096 timestamp: 1655077941.9317513 iteration: 89315 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15127 FastRCNN class loss: 0.1121 FastRCNN total loss: 0.26337 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.18424 RPN box loss: 0.02668 RPN score loss: 0.00863 RPN total loss: 0.03531 Total loss: 1.04517 timestamp: 1655077945.2904365 iteration: 89320 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11269 FastRCNN class loss: 0.0552 FastRCNN total loss: 0.16789 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13877 RPN box loss: 0.00242 RPN score loss: 0.00252 RPN total loss: 0.00495 Total loss: 0.87386 timestamp: 1655077948.4918168 iteration: 89325 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1001 FastRCNN class loss: 0.06826 FastRCNN total loss: 0.16836 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.20709 RPN box loss: 0.0087 RPN score loss: 0.00995 RPN total loss: 0.01866 Total loss: 0.95636 timestamp: 1655077951.8376343 iteration: 89330 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06404 FastRCNN class loss: 0.05293 FastRCNN total loss: 0.11697 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.1281 RPN box loss: 0.0146 RPN score loss: 0.00709 RPN total loss: 0.02169 Total loss: 0.82901 timestamp: 1655077955.1120608 iteration: 89335 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10959 FastRCNN class loss: 0.07835 FastRCNN total loss: 0.18795 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.0834 RPN box loss: 0.00995 RPN score loss: 0.00181 RPN total loss: 0.01176 Total loss: 0.84535 timestamp: 1655077958.431103 iteration: 89340 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11245 FastRCNN class loss: 0.05859 FastRCNN total loss: 0.17104 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15833 RPN box loss: 0.0204 RPN score loss: 0.00806 RPN total loss: 0.02846 Total loss: 0.92008 timestamp: 1655077961.6819477 iteration: 89345 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10451 FastRCNN class loss: 0.08359 FastRCNN total loss: 0.1881 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15814 RPN box loss: 0.01297 RPN score loss: 0.01127 RPN total loss: 0.02424 Total loss: 0.93273 timestamp: 1655077964.990635 iteration: 89350 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11937 FastRCNN class loss: 0.06884 FastRCNN total loss: 0.18821 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11991 RPN box loss: 0.0165 RPN score loss: 0.00243 RPN total loss: 0.01893 Total loss: 0.8893 timestamp: 1655077968.2488668 iteration: 89355 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10942 FastRCNN class loss: 0.11314 FastRCNN total loss: 0.22256 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.18684 RPN box loss: 0.009 RPN score loss: 0.01195 RPN total loss: 0.02095 Total loss: 0.9926 timestamp: 1655077971.465222 iteration: 89360 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11919 FastRCNN class loss: 0.06291 FastRCNN total loss: 0.1821 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.07836 RPN box loss: 0.00661 RPN score loss: 0.00631 RPN total loss: 0.01292 Total loss: 0.83562 timestamp: 1655077974.715978 iteration: 89365 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07443 FastRCNN class loss: 0.07772 FastRCNN total loss: 0.15215 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14526 RPN box loss: 0.01052 RPN score loss: 0.0031 RPN total loss: 0.01362 Total loss: 0.87328 timestamp: 1655077978.001293 iteration: 89370 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06588 FastRCNN class loss: 0.05622 FastRCNN total loss: 0.1221 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16365 RPN box loss: 0.03029 RPN score loss: 0.00657 RPN total loss: 0.03687 Total loss: 0.88487 timestamp: 1655077981.2548692 iteration: 89375 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10561 FastRCNN class loss: 0.10666 FastRCNN total loss: 0.21227 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14826 RPN box loss: 0.00789 RPN score loss: 0.00387 RPN total loss: 0.01176 Total loss: 0.93454 timestamp: 1655077984.5145793 iteration: 89380 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.14245 FastRCNN class loss: 0.09021 FastRCNN total loss: 0.23267 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13084 RPN box loss: 0.01971 RPN score loss: 0.00834 RPN total loss: 0.02805 Total loss: 0.95381 timestamp: 1655077987.717944 iteration: 89385 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07308 FastRCNN class loss: 0.07394 FastRCNN total loss: 0.14702 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15045 RPN box loss: 0.00671 RPN score loss: 0.0112 RPN total loss: 0.01791 Total loss: 0.87763 timestamp: 1655077990.9928062 iteration: 89390 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08429 FastRCNN class loss: 0.0524 FastRCNN total loss: 0.13669 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.12511 RPN box loss: 0.00935 RPN score loss: 0.00267 RPN total loss: 0.01202 Total loss: 0.83606 timestamp: 1655077994.3086393 iteration: 89395 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12141 FastRCNN class loss: 0.09332 FastRCNN total loss: 0.21473 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15968 RPN box loss: 0.01313 RPN score loss: 0.01907 RPN total loss: 0.0322 Total loss: 0.96886 timestamp: 1655077997.5943017 iteration: 89400 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06047 FastRCNN class loss: 0.05946 FastRCNN total loss: 0.11992 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.20624 RPN box loss: 0.01403 RPN score loss: 0.00419 RPN total loss: 0.01821 Total loss: 0.90663 timestamp: 1655078000.8085735 iteration: 89405 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05592 FastRCNN class loss: 0.06569 FastRCNN total loss: 0.1216 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15256 RPN box loss: 0.01 RPN score loss: 0.0044 RPN total loss: 0.0144 Total loss: 0.85081 timestamp: 1655078004.0963151 iteration: 89410 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07807 FastRCNN class loss: 0.077 FastRCNN total loss: 0.15507 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11939 RPN box loss: 0.01007 RPN score loss: 0.00235 RPN total loss: 0.01242 Total loss: 0.84913 timestamp: 1655078007.3471327 iteration: 89415 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06221 FastRCNN class loss: 0.03764 FastRCNN total loss: 0.09985 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.12214 RPN box loss: 0.00558 RPN score loss: 0.00254 RPN total loss: 0.00813 Total loss: 0.79236 timestamp: 1655078010.6292765 iteration: 89420 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06266 FastRCNN class loss: 0.07036 FastRCNN total loss: 0.13302 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.14928 RPN box loss: 0.01819 RPN score loss: 0.00699 RPN total loss: 0.02517 Total loss: 0.86972 timestamp: 1655078013.9335117 iteration: 89425 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07938 FastRCNN class loss: 0.05897 FastRCNN total loss: 0.13835 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15714 RPN box loss: 0.00832 RPN score loss: 0.01393 RPN total loss: 0.02224 Total loss: 0.87998 timestamp: 1655078017.2879672 iteration: 89430 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12283 FastRCNN class loss: 0.09236 FastRCNN total loss: 0.21519 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.17531 RPN box loss: 0.02911 RPN score loss: 0.00365 RPN total loss: 0.03277 Total loss: 0.98552 timestamp: 1655078020.6034071 iteration: 89435 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13806 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.21608 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15265 RPN box loss: 0.01567 RPN score loss: 0.00555 RPN total loss: 0.02123 Total loss: 0.95221 timestamp: 1655078023.8790045 iteration: 89440 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07282 FastRCNN class loss: 0.06781 FastRCNN total loss: 0.14064 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15005 RPN box loss: 0.00998 RPN score loss: 0.00309 RPN total loss: 0.01308 Total loss: 0.86601 timestamp: 1655078027.1281767 iteration: 89445 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11642 FastRCNN class loss: 0.0673 FastRCNN total loss: 0.18372 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.17623 RPN box loss: 0.0146 RPN score loss: 0.00948 RPN total loss: 0.02408 Total loss: 0.94627 timestamp: 1655078030.4504929 iteration: 89450 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05812 FastRCNN class loss: 0.04835 FastRCNN total loss: 0.10647 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.08627 RPN box loss: 0.00605 RPN score loss: 0.00058 RPN total loss: 0.00662 Total loss: 0.76161 timestamp: 1655078033.716987 iteration: 89455 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07758 FastRCNN class loss: 0.0814 FastRCNN total loss: 0.15898 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.20304 RPN box loss: 0.01093 RPN score loss: 0.01065 RPN total loss: 0.02158 Total loss: 0.94584 timestamp: 1655078037.036991 iteration: 89460 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08731 FastRCNN class loss: 0.08237 FastRCNN total loss: 0.16967 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13331 RPN box loss: 0.01403 RPN score loss: 0.00518 RPN total loss: 0.01921 Total loss: 0.88444 timestamp: 1655078040.28035 iteration: 89465 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08949 FastRCNN class loss: 0.0627 FastRCNN total loss: 0.15219 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.12793 RPN box loss: 0.01436 RPN score loss: 0.01128 RPN total loss: 0.02564 Total loss: 0.86802 timestamp: 1655078043.5534694 iteration: 89470 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10448 FastRCNN class loss: 0.0581 FastRCNN total loss: 0.16258 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.08809 RPN box loss: 0.0064 RPN score loss: 0.0021 RPN total loss: 0.0085 Total loss: 0.82141 timestamp: 1655078046.8538866 iteration: 89475 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11372 FastRCNN class loss: 0.1304 FastRCNN total loss: 0.24412 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.23402 RPN box loss: 0.04609 RPN score loss: 0.06646 RPN total loss: 0.11254 Total loss: 1.15293 timestamp: 1655078050.0447097 iteration: 89480 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06541 FastRCNN class loss: 0.04989 FastRCNN total loss: 0.1153 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.1659 RPN box loss: 0.00531 RPN score loss: 0.00646 RPN total loss: 0.01177 Total loss: 0.85523 timestamp: 1655078053.2710624 iteration: 89485 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08266 FastRCNN class loss: 0.07038 FastRCNN total loss: 0.15305 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.19806 RPN box loss: 0.01083 RPN score loss: 0.00653 RPN total loss: 0.01736 Total loss: 0.93072 timestamp: 1655078056.5310822 iteration: 89490 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08244 FastRCNN class loss: 0.05556 FastRCNN total loss: 0.138 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16967 RPN box loss: 0.00578 RPN score loss: 0.00281 RPN total loss: 0.00859 Total loss: 0.87851 timestamp: 1655078059.7455692 iteration: 89495 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11995 FastRCNN class loss: 0.08494 FastRCNN total loss: 0.20489 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16475 RPN box loss: 0.01002 RPN score loss: 0.00521 RPN total loss: 0.01523 Total loss: 0.94712 timestamp: 1655078062.9642117 iteration: 89500 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13015 FastRCNN class loss: 0.08939 FastRCNN total loss: 0.21954 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15375 RPN box loss: 0.00983 RPN score loss: 0.00603 RPN total loss: 0.01585 Total loss: 0.95139 timestamp: 1655078066.2544925 iteration: 89505 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06765 FastRCNN class loss: 0.04858 FastRCNN total loss: 0.11623 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.10789 RPN box loss: 0.0155 RPN score loss: 0.0038 RPN total loss: 0.01931 Total loss: 0.80567 timestamp: 1655078069.547067 iteration: 89510 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12591 FastRCNN class loss: 0.05556 FastRCNN total loss: 0.18147 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.1181 RPN box loss: 0.01361 RPN score loss: 0.00822 RPN total loss: 0.02183 Total loss: 0.88365 timestamp: 1655078072.804341 iteration: 89515 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11658 FastRCNN class loss: 0.09855 FastRCNN total loss: 0.21513 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16111 RPN box loss: 0.01431 RPN score loss: 0.00331 RPN total loss: 0.01761 Total loss: 0.9561 timestamp: 1655078076.1611524 iteration: 89520 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05774 FastRCNN class loss: 0.07085 FastRCNN total loss: 0.12859 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.1392 RPN box loss: 0.00627 RPN score loss: 0.00357 RPN total loss: 0.00985 Total loss: 0.83989 timestamp: 1655078079.4178967 iteration: 89525 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04943 FastRCNN class loss: 0.04898 FastRCNN total loss: 0.09841 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13057 RPN box loss: 0.01167 RPN score loss: 0.00929 RPN total loss: 0.02096 Total loss: 0.81218 timestamp: 1655078082.7382975 iteration: 89530 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10634 FastRCNN class loss: 0.05934 FastRCNN total loss: 0.16568 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13846 RPN box loss: 0.01793 RPN score loss: 0.00223 RPN total loss: 0.02016 Total loss: 0.88655 timestamp: 1655078086.0735042 iteration: 89535 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07735 FastRCNN class loss: 0.08482 FastRCNN total loss: 0.16216 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15371 RPN box loss: 0.01012 RPN score loss: 0.0037 RPN total loss: 0.01381 Total loss: 0.89193 timestamp: 1655078089.3245842 iteration: 89540 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13725 FastRCNN class loss: 0.09902 FastRCNN total loss: 0.23627 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.16433 RPN box loss: 0.00816 RPN score loss: 0.00245 RPN total loss: 0.0106 Total loss: 0.97345 timestamp: 1655078092.6636257 iteration: 89545 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11033 FastRCNN class loss: 0.07304 FastRCNN total loss: 0.18337 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15049 RPN box loss: 0.03004 RPN score loss: 0.00685 RPN total loss: 0.03689 Total loss: 0.93299 timestamp: 1655078095.9281435 iteration: 89550 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1184 FastRCNN class loss: 0.08724 FastRCNN total loss: 0.20565 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13157 RPN box loss: 0.00669 RPN score loss: 0.0081 RPN total loss: 0.0148 Total loss: 0.91426 timestamp: 1655078099.2345383 iteration: 89555 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10206 FastRCNN class loss: 0.07802 FastRCNN total loss: 0.18008 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.13679 RPN box loss: 0.01705 RPN score loss: 0.00537 RPN total loss: 0.02241 Total loss: 0.90153 timestamp: 1655078102.4991503 iteration: 89560 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10854 FastRCNN class loss: 0.09324 FastRCNN total loss: 0.20178 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.11873 RPN box loss: 0.01268 RPN score loss: 0.00357 RPN total loss: 0.01625 Total loss: 0.899 timestamp: 1655078105.7660959 iteration: 89565 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.133 FastRCNN class loss: 0.0441 FastRCNN total loss: 0.1771 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.09611 RPN box loss: 0.01004 RPN score loss: 0.00433 RPN total loss: 0.01437 Total loss: 0.84982 timestamp: 1655078109.0455642 iteration: 89570 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08407 FastRCNN class loss: 0.08438 FastRCNN total loss: 0.16844 L1 loss: 0.0000e+00 L2 loss: 0.56225 Learning rate: 4.0000e-05 Mask loss: 0.15227 RPN box loss: 0.01783 RPN score loss: 0.00682 RPN total loss: 0.02465 Total loss: 0.90762 timestamp: 1655078112.2326226 iteration: 89575 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07734 FastRCNN class loss: 0.07711 FastRCNN total loss: 0.15445 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.114 RPN box loss: 0.02542 RPN score loss: 0.00419 RPN total loss: 0.0296 Total loss: 0.8603 timestamp: 1655078115.5778072 iteration: 89580 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11769 FastRCNN class loss: 0.07261 FastRCNN total loss: 0.19029 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.11874 RPN box loss: 0.0168 RPN score loss: 0.00842 RPN total loss: 0.02522 Total loss: 0.8965 timestamp: 1655078118.8236144 iteration: 89585 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09881 FastRCNN class loss: 0.07037 FastRCNN total loss: 0.16918 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15321 RPN box loss: 0.00738 RPN score loss: 0.00793 RPN total loss: 0.01531 Total loss: 0.89995 timestamp: 1655078122.0732625 iteration: 89590 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08527 FastRCNN class loss: 0.05579 FastRCNN total loss: 0.14107 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12123 RPN box loss: 0.00854 RPN score loss: 0.00754 RPN total loss: 0.01609 Total loss: 0.84063 timestamp: 1655078125.4134462 iteration: 89595 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11335 FastRCNN class loss: 0.07057 FastRCNN total loss: 0.18392 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12957 RPN box loss: 0.00807 RPN score loss: 0.00605 RPN total loss: 0.01412 Total loss: 0.88985 timestamp: 1655078128.6355555 iteration: 89600 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07597 FastRCNN class loss: 0.07197 FastRCNN total loss: 0.14794 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14649 RPN box loss: 0.01094 RPN score loss: 0.0052 RPN total loss: 0.01615 Total loss: 0.87283 timestamp: 1655078131.9119241 iteration: 89605 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08333 FastRCNN class loss: 0.05118 FastRCNN total loss: 0.13451 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13402 RPN box loss: 0.00586 RPN score loss: 0.00343 RPN total loss: 0.0093 Total loss: 0.84007 timestamp: 1655078135.1282504 iteration: 89610 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13359 FastRCNN class loss: 0.09745 FastRCNN total loss: 0.23104 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1643 RPN box loss: 0.05117 RPN score loss: 0.0188 RPN total loss: 0.06997 Total loss: 1.02755 timestamp: 1655078138.430399 iteration: 89615 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08458 FastRCNN class loss: 0.05379 FastRCNN total loss: 0.13837 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.10379 RPN box loss: 0.02185 RPN score loss: 0.00424 RPN total loss: 0.02609 Total loss: 0.83049 timestamp: 1655078141.6781642 iteration: 89620 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04855 FastRCNN class loss: 0.02516 FastRCNN total loss: 0.07371 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.08842 RPN box loss: 0.01562 RPN score loss: 0.00208 RPN total loss: 0.0177 Total loss: 0.74208 timestamp: 1655078144.974367 iteration: 89625 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06611 FastRCNN class loss: 0.05391 FastRCNN total loss: 0.12002 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13907 RPN box loss: 0.00531 RPN score loss: 0.00261 RPN total loss: 0.00793 Total loss: 0.82926 timestamp: 1655078148.180979 iteration: 89630 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15659 FastRCNN class loss: 0.0902 FastRCNN total loss: 0.24679 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.16684 RPN box loss: 0.02159 RPN score loss: 0.00492 RPN total loss: 0.02651 Total loss: 1.00239 timestamp: 1655078151.4718626 iteration: 89635 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09703 FastRCNN class loss: 0.05834 FastRCNN total loss: 0.15537 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.16455 RPN box loss: 0.00439 RPN score loss: 0.00299 RPN total loss: 0.00738 Total loss: 0.88954 timestamp: 1655078154.7732906 iteration: 89640 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09807 FastRCNN class loss: 0.04827 FastRCNN total loss: 0.14634 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14681 RPN box loss: 0.01574 RPN score loss: 0.00231 RPN total loss: 0.01805 Total loss: 0.87344 timestamp: 1655078158.1095405 iteration: 89645 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11918 FastRCNN class loss: 0.07121 FastRCNN total loss: 0.19039 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.10775 RPN box loss: 0.0128 RPN score loss: 0.00383 RPN total loss: 0.01663 Total loss: 0.87701 timestamp: 1655078161.425996 iteration: 89650 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05297 FastRCNN class loss: 0.06006 FastRCNN total loss: 0.11302 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13572 RPN box loss: 0.01198 RPN score loss: 0.00764 RPN total loss: 0.01962 Total loss: 0.83061 timestamp: 1655078164.7362654 iteration: 89655 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12425 FastRCNN class loss: 0.05884 FastRCNN total loss: 0.18309 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15137 RPN box loss: 0.00752 RPN score loss: 0.00267 RPN total loss: 0.01019 Total loss: 0.90689 timestamp: 1655078167.9705544 iteration: 89660 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09839 FastRCNN class loss: 0.14248 FastRCNN total loss: 0.24087 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15115 RPN box loss: 0.01883 RPN score loss: 0.00364 RPN total loss: 0.02247 Total loss: 0.97674 timestamp: 1655078171.2022808 iteration: 89665 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09092 FastRCNN class loss: 0.09613 FastRCNN total loss: 0.18705 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.19211 RPN box loss: 0.01518 RPN score loss: 0.00326 RPN total loss: 0.01844 Total loss: 0.95984 timestamp: 1655078174.4504645 iteration: 89670 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12246 FastRCNN class loss: 0.07175 FastRCNN total loss: 0.19422 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.11705 RPN box loss: 0.00847 RPN score loss: 0.00417 RPN total loss: 0.01264 Total loss: 0.88615 timestamp: 1655078177.7545185 iteration: 89675 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06954 FastRCNN class loss: 0.04604 FastRCNN total loss: 0.11558 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14835 RPN box loss: 0.01305 RPN score loss: 0.0018 RPN total loss: 0.01485 Total loss: 0.84102 timestamp: 1655078181.0520701 iteration: 89680 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11168 FastRCNN class loss: 0.04652 FastRCNN total loss: 0.1582 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12713 RPN box loss: 0.00452 RPN score loss: 0.00084 RPN total loss: 0.00536 Total loss: 0.85293 timestamp: 1655078184.314732 iteration: 89685 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05257 FastRCNN class loss: 0.04146 FastRCNN total loss: 0.09403 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14976 RPN box loss: 0.02035 RPN score loss: 0.00344 RPN total loss: 0.02379 Total loss: 0.82982 timestamp: 1655078187.5503333 iteration: 89690 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04472 FastRCNN class loss: 0.05504 FastRCNN total loss: 0.09975 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12374 RPN box loss: 0.00798 RPN score loss: 0.0019 RPN total loss: 0.00988 Total loss: 0.79562 timestamp: 1655078190.844105 iteration: 89695 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10795 FastRCNN class loss: 0.04669 FastRCNN total loss: 0.15463 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.09612 RPN box loss: 0.00385 RPN score loss: 0.00572 RPN total loss: 0.00957 Total loss: 0.82256 timestamp: 1655078194.1310303 iteration: 89700 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.13081 FastRCNN class loss: 0.0795 FastRCNN total loss: 0.2103 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.07008 RPN box loss: 0.01939 RPN score loss: 0.00383 RPN total loss: 0.02322 Total loss: 0.86585 timestamp: 1655078197.4837458 iteration: 89705 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06017 FastRCNN class loss: 0.05529 FastRCNN total loss: 0.11546 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12035 RPN box loss: 0.00732 RPN score loss: 0.0034 RPN total loss: 0.01072 Total loss: 0.80877 timestamp: 1655078200.7730207 iteration: 89710 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10801 FastRCNN class loss: 0.06036 FastRCNN total loss: 0.16837 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.10197 RPN box loss: 0.01117 RPN score loss: 0.00351 RPN total loss: 0.01467 Total loss: 0.84725 timestamp: 1655078203.9955277 iteration: 89715 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08948 FastRCNN class loss: 0.10144 FastRCNN total loss: 0.19092 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.17566 RPN box loss: 0.01359 RPN score loss: 0.00785 RPN total loss: 0.02144 Total loss: 0.95026 timestamp: 1655078207.2792706 iteration: 89720 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12144 FastRCNN class loss: 0.0832 FastRCNN total loss: 0.20464 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15777 RPN box loss: 0.03135 RPN score loss: 0.00714 RPN total loss: 0.03849 Total loss: 0.96314 timestamp: 1655078210.486297 iteration: 89725 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11971 FastRCNN class loss: 0.07044 FastRCNN total loss: 0.19015 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14324 RPN box loss: 0.01784 RPN score loss: 0.00348 RPN total loss: 0.02132 Total loss: 0.91695 timestamp: 1655078213.8612936 iteration: 89730 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05666 FastRCNN class loss: 0.03694 FastRCNN total loss: 0.0936 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.09955 RPN box loss: 0.00368 RPN score loss: 0.00244 RPN total loss: 0.00612 Total loss: 0.7615 timestamp: 1655078217.0954628 iteration: 89735 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05279 FastRCNN class loss: 0.03713 FastRCNN total loss: 0.08992 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12371 RPN box loss: 0.00451 RPN score loss: 0.00162 RPN total loss: 0.00613 Total loss: 0.782 timestamp: 1655078220.3539584 iteration: 89740 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05814 FastRCNN class loss: 0.09445 FastRCNN total loss: 0.1526 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15241 RPN box loss: 0.03811 RPN score loss: 0.01306 RPN total loss: 0.05117 Total loss: 0.91842 timestamp: 1655078223.5825312 iteration: 89745 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07435 FastRCNN class loss: 0.05967 FastRCNN total loss: 0.13402 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.16532 RPN box loss: 0.01293 RPN score loss: 0.00856 RPN total loss: 0.02149 Total loss: 0.88307 timestamp: 1655078226.8359058 iteration: 89750 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1068 FastRCNN class loss: 0.08279 FastRCNN total loss: 0.18959 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.18257 RPN box loss: 0.01991 RPN score loss: 0.00606 RPN total loss: 0.02596 Total loss: 0.96036 timestamp: 1655078230.1707377 iteration: 89755 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0353 FastRCNN class loss: 0.0564 FastRCNN total loss: 0.0917 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12767 RPN box loss: 0.01163 RPN score loss: 0.00252 RPN total loss: 0.01415 Total loss: 0.79575 timestamp: 1655078233.4719796 iteration: 89760 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05553 FastRCNN class loss: 0.06699 FastRCNN total loss: 0.12252 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13057 RPN box loss: 0.0064 RPN score loss: 0.00502 RPN total loss: 0.01143 Total loss: 0.82675 timestamp: 1655078236.8077133 iteration: 89765 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09765 FastRCNN class loss: 0.11433 FastRCNN total loss: 0.21198 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1787 RPN box loss: 0.0126 RPN score loss: 0.00705 RPN total loss: 0.01965 Total loss: 0.97258 timestamp: 1655078240.0639634 iteration: 89770 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11273 FastRCNN class loss: 0.06326 FastRCNN total loss: 0.17599 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12527 RPN box loss: 0.00705 RPN score loss: 0.00413 RPN total loss: 0.01118 Total loss: 0.87468 timestamp: 1655078243.2976208 iteration: 89775 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15029 FastRCNN class loss: 0.07461 FastRCNN total loss: 0.2249 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.15755 RPN box loss: 0.02534 RPN score loss: 0.00431 RPN total loss: 0.02964 Total loss: 0.97433 timestamp: 1655078246.5682225 iteration: 89780 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08097 FastRCNN class loss: 0.10654 FastRCNN total loss: 0.18751 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13795 RPN box loss: 0.01969 RPN score loss: 0.00671 RPN total loss: 0.02639 Total loss: 0.91409 timestamp: 1655078249.8209496 iteration: 89785 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09878 FastRCNN class loss: 0.09131 FastRCNN total loss: 0.19009 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.17563 RPN box loss: 0.02536 RPN score loss: 0.0052 RPN total loss: 0.03057 Total loss: 0.95853 timestamp: 1655078253.1227193 iteration: 89790 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0656 FastRCNN class loss: 0.05136 FastRCNN total loss: 0.11696 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12681 RPN box loss: 0.005 RPN score loss: 0.00368 RPN total loss: 0.00868 Total loss: 0.81469 timestamp: 1655078256.377384 iteration: 89795 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.1431 FastRCNN class loss: 0.13341 FastRCNN total loss: 0.27651 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.23631 RPN box loss: 0.03301 RPN score loss: 0.01877 RPN total loss: 0.05178 Total loss: 1.12684 timestamp: 1655078259.5928144 iteration: 89800 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08984 FastRCNN class loss: 0.0663 FastRCNN total loss: 0.15614 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.10728 RPN box loss: 0.03447 RPN score loss: 0.00513 RPN total loss: 0.0396 Total loss: 0.86526 timestamp: 1655078262.9431264 iteration: 89805 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08448 FastRCNN class loss: 0.04391 FastRCNN total loss: 0.12839 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.10746 RPN box loss: 0.00303 RPN score loss: 0.00087 RPN total loss: 0.00391 Total loss: 0.80199 timestamp: 1655078266.190506 iteration: 89810 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04663 FastRCNN class loss: 0.05351 FastRCNN total loss: 0.10014 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1005 RPN box loss: 0.00632 RPN score loss: 0.00471 RPN total loss: 0.01104 Total loss: 0.77391 timestamp: 1655078269.45366 iteration: 89815 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06854 FastRCNN class loss: 0.09572 FastRCNN total loss: 0.16426 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1282 RPN box loss: 0.01261 RPN score loss: 0.01085 RPN total loss: 0.02345 Total loss: 0.87815 timestamp: 1655078272.689415 iteration: 89820 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09163 FastRCNN class loss: 0.06223 FastRCNN total loss: 0.15386 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.17597 RPN box loss: 0.0297 RPN score loss: 0.00608 RPN total loss: 0.03578 Total loss: 0.92784 timestamp: 1655078275.9864454 iteration: 89825 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10666 FastRCNN class loss: 0.08466 FastRCNN total loss: 0.19132 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13989 RPN box loss: 0.00652 RPN score loss: 0.00326 RPN total loss: 0.00978 Total loss: 0.90322 timestamp: 1655078279.2364652 iteration: 89830 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.04549 FastRCNN class loss: 0.03369 FastRCNN total loss: 0.07918 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12445 RPN box loss: 0.00343 RPN score loss: 0.00566 RPN total loss: 0.0091 Total loss: 0.77497 timestamp: 1655078282.4786067 iteration: 89835 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16212 FastRCNN class loss: 0.09307 FastRCNN total loss: 0.25519 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.21013 RPN box loss: 0.01832 RPN score loss: 0.00184 RPN total loss: 0.02016 Total loss: 1.04772 timestamp: 1655078285.7372203 iteration: 89840 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06282 FastRCNN class loss: 0.07257 FastRCNN total loss: 0.13539 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13752 RPN box loss: 0.00841 RPN score loss: 0.00977 RPN total loss: 0.01818 Total loss: 0.85333 timestamp: 1655078288.982533 iteration: 89845 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09394 FastRCNN class loss: 0.06237 FastRCNN total loss: 0.15631 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1135 RPN box loss: 0.01269 RPN score loss: 0.01005 RPN total loss: 0.02274 Total loss: 0.85479 timestamp: 1655078292.2859757 iteration: 89850 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.06498 FastRCNN class loss: 0.06058 FastRCNN total loss: 0.12556 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12858 RPN box loss: 0.04618 RPN score loss: 0.00935 RPN total loss: 0.05554 Total loss: 0.87191 timestamp: 1655078295.6174362 iteration: 89855 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09517 FastRCNN class loss: 0.07639 FastRCNN total loss: 0.17156 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.12717 RPN box loss: 0.00712 RPN score loss: 0.00415 RPN total loss: 0.01126 Total loss: 0.87223 timestamp: 1655078298.8793275 iteration: 89860 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07977 FastRCNN class loss: 0.05476 FastRCNN total loss: 0.13453 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.1313 RPN box loss: 0.0081 RPN score loss: 0.00194 RPN total loss: 0.01004 Total loss: 0.83811 timestamp: 1655078302.142132 iteration: 89865 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07797 FastRCNN class loss: 0.0786 FastRCNN total loss: 0.15657 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.16207 RPN box loss: 0.00753 RPN score loss: 0.00242 RPN total loss: 0.00994 Total loss: 0.89082 timestamp: 1655078305.3212729 iteration: 89870 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10808 FastRCNN class loss: 0.06709 FastRCNN total loss: 0.17517 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14012 RPN box loss: 0.01758 RPN score loss: 0.00597 RPN total loss: 0.02355 Total loss: 0.90107 timestamp: 1655078308.5819085 iteration: 89875 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11588 FastRCNN class loss: 0.06861 FastRCNN total loss: 0.18448 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.14174 RPN box loss: 0.0091 RPN score loss: 0.0114 RPN total loss: 0.02049 Total loss: 0.90895 timestamp: 1655078311.8500915 iteration: 89880 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.12781 FastRCNN class loss: 0.05784 FastRCNN total loss: 0.18565 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.16223 RPN box loss: 0.00655 RPN score loss: 0.00707 RPN total loss: 0.01363 Total loss: 0.92374 timestamp: 1655078315.0718179 iteration: 89885 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.0646 FastRCNN class loss: 0.06934 FastRCNN total loss: 0.13394 L1 loss: 0.0000e+00 L2 loss: 0.56224 Learning rate: 4.0000e-05 Mask loss: 0.13932 RPN box loss: 0.0058 RPN score loss: 0.00495 RPN total loss: 0.01075 Total loss: 0.84625 timestamp: 1655078318.3233771 iteration: 89890 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09358 FastRCNN class loss: 0.08254 FastRCNN total loss: 0.17612 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.14141 RPN box loss: 0.01352 RPN score loss: 0.00663 RPN total loss: 0.02015 Total loss: 0.89991 timestamp: 1655078321.6229627 iteration: 89895 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09575 FastRCNN class loss: 0.04488 FastRCNN total loss: 0.14063 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.15689 RPN box loss: 0.00442 RPN score loss: 0.00153 RPN total loss: 0.00595 Total loss: 0.86571 timestamp: 1655078324.92391 iteration: 89900 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07387 FastRCNN class loss: 0.06984 FastRCNN total loss: 0.1437 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.11238 RPN box loss: 0.01037 RPN score loss: 0.00398 RPN total loss: 0.01436 Total loss: 0.83268 timestamp: 1655078328.132168 iteration: 89905 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.15277 FastRCNN class loss: 0.11954 FastRCNN total loss: 0.27231 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.27356 RPN box loss: 0.01733 RPN score loss: 0.00878 RPN total loss: 0.02611 Total loss: 1.13422 timestamp: 1655078331.436924 iteration: 89910 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16303 FastRCNN class loss: 0.08217 FastRCNN total loss: 0.24521 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.15092 RPN box loss: 0.02783 RPN score loss: 0.00499 RPN total loss: 0.03282 Total loss: 0.99118 timestamp: 1655078334.6881182 iteration: 89915 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09605 FastRCNN class loss: 0.06892 FastRCNN total loss: 0.16497 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.18403 RPN box loss: 0.03092 RPN score loss: 0.01056 RPN total loss: 0.04148 Total loss: 0.95272 timestamp: 1655078337.9218328 iteration: 89920 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05639 FastRCNN class loss: 0.05092 FastRCNN total loss: 0.10731 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.09692 RPN box loss: 0.00678 RPN score loss: 0.0111 RPN total loss: 0.01788 Total loss: 0.78434 timestamp: 1655078341.2222292 iteration: 89925 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.16515 FastRCNN class loss: 0.1097 FastRCNN total loss: 0.27485 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.21471 RPN box loss: 0.01195 RPN score loss: 0.00886 RPN total loss: 0.02081 Total loss: 1.0726 timestamp: 1655078344.4985688 iteration: 89930 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.08994 FastRCNN class loss: 0.08568 FastRCNN total loss: 0.17562 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.17265 RPN box loss: 0.0093 RPN score loss: 0.0031 RPN total loss: 0.01239 Total loss: 0.9229 timestamp: 1655078347.8035448 iteration: 89935 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07873 FastRCNN class loss: 0.03926 FastRCNN total loss: 0.11799 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.14453 RPN box loss: 0.02214 RPN score loss: 0.00576 RPN total loss: 0.0279 Total loss: 0.85266 timestamp: 1655078350.9858444 iteration: 89940 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.09838 FastRCNN class loss: 0.09456 FastRCNN total loss: 0.19295 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.19271 RPN box loss: 0.01134 RPN score loss: 0.00795 RPN total loss: 0.01929 Total loss: 0.96718 timestamp: 1655078354.2276378 iteration: 89945 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10125 FastRCNN class loss: 0.05571 FastRCNN total loss: 0.15696 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.12084 RPN box loss: 0.00757 RPN score loss: 0.00363 RPN total loss: 0.0112 Total loss: 0.85124 timestamp: 1655078357.5382924 iteration: 89950 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11755 FastRCNN class loss: 0.07779 FastRCNN total loss: 0.19534 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.13946 RPN box loss: 0.01482 RPN score loss: 0.00333 RPN total loss: 0.01815 Total loss: 0.91518 timestamp: 1655078360.8511078 iteration: 89955 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05999 FastRCNN class loss: 0.04353 FastRCNN total loss: 0.10352 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.15698 RPN box loss: 0.00439 RPN score loss: 0.00228 RPN total loss: 0.00667 Total loss: 0.82939 timestamp: 1655078364.1276693 iteration: 89960 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10284 FastRCNN class loss: 0.05054 FastRCNN total loss: 0.15338 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.13666 RPN box loss: 0.02286 RPN score loss: 0.00269 RPN total loss: 0.02555 Total loss: 0.87783 timestamp: 1655078367.3152804 iteration: 89965 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05998 FastRCNN class loss: 0.04157 FastRCNN total loss: 0.10155 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.09637 RPN box loss: 0.00707 RPN score loss: 0.0023 RPN total loss: 0.00937 Total loss: 0.76952 timestamp: 1655078370.5417836 iteration: 89970 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07801 FastRCNN class loss: 0.05729 FastRCNN total loss: 0.1353 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.18898 RPN box loss: 0.01421 RPN score loss: 0.00784 RPN total loss: 0.02205 Total loss: 0.90856 timestamp: 1655078373.7874944 iteration: 89975 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.05275 FastRCNN class loss: 0.03992 FastRCNN total loss: 0.09267 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.10485 RPN box loss: 0.00596 RPN score loss: 0.00196 RPN total loss: 0.00792 Total loss: 0.76767 timestamp: 1655078377.0529766 iteration: 89980 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.11873 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.19876 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.11768 RPN box loss: 0.01361 RPN score loss: 0.0096 RPN total loss: 0.02321 Total loss: 0.90188 timestamp: 1655078380.3644428 iteration: 89985 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10416 FastRCNN class loss: 0.06816 FastRCNN total loss: 0.17233 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.18995 RPN box loss: 0.01186 RPN score loss: 0.00696 RPN total loss: 0.01882 Total loss: 0.94333 timestamp: 1655078383.647432 iteration: 89990 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10094 FastRCNN class loss: 0.08003 FastRCNN total loss: 0.18098 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.10071 RPN box loss: 0.00398 RPN score loss: 0.00271 RPN total loss: 0.00669 Total loss: 0.85061 timestamp: 1655078386.8904526 iteration: 89995 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.10557 FastRCNN class loss: 0.07224 FastRCNN total loss: 0.1778 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.21471 RPN box loss: 0.01588 RPN score loss: 0.00813 RPN total loss: 0.02401 Total loss: 0.97876 timestamp: 1655078390.119393 iteration: 90000 throughput: 24.5 samples/sec ==================== Metrics ===================== FastRCNN box loss: 0.07314 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.13968 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.16035 RPN box loss: 0.01013 RPN score loss: 0.00494 RPN total loss: 0.01507 Total loss: 0.87733 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] 535.9 GFLOPS/image Running inference on batch 001/125... - Step Time: 7.1191s - Throughput: 0.6 imgs/s Running inference on batch 002/125... - Step Time: 0.9457s - Throughput: 4.2 imgs/s Running inference on batch 003/125... - Step Time: 0.9242s - Throughput: 4.3 imgs/s Running inference on batch 004/125... - Step Time: 0.9635s - Throughput: 4.2 imgs/s Running inference on batch 005/125... - Step Time: 0.9532s - Throughput: 4.2 imgs/s Running inference on batch 006/125... - Step Time: 0.6858s - Throughput: 5.8 imgs/s Running inference on batch 007/125... - Step Time: 0.9256s - Throughput: 4.3 imgs/s Running inference on batch 008/125... - Step Time: 0.9595s - Throughput: 4.2 imgs/s Running inference on batch 009/125... - Step Time: 1.0114s - Throughput: 4.0 imgs/s Running inference on batch 010/125... - Step Time: 0.9229s - Throughput: 4.3 imgs/s Running inference on batch 011/125... - Step Time: 0.9736s - Throughput: 4.1 imgs/s Running inference on batch 012/125... - 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Step Time: 0.9381s - Throughput: 4.3 imgs/s Running inference on batch 121/125... - Step Time: 0.8952s - Throughput: 4.5 imgs/s Running inference on batch 122/125... - Step Time: 0.9182s - Throughput: 4.4 imgs/s Running inference on batch 123/125... - Step Time: 0.9132s - Throughput: 4.4 imgs/s Running inference on batch 124/125... - Step Time: 1.0150s - Throughput: 3.9 imgs/s Running inference on batch 125/125... - Step Time: 0.9519s - Throughput: 4.2 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: 4.2 samples/sec Total processed steps: 125 Total processing time: 0.0h 08m 49s ==================== Metrics ==================== AP: 0.194935068 AP50: 0.320598215 AP75: 0.191744179 APl: 0.226381645 APm: 0.029419964 APs: 0.002213070 ARl: 0.434327364 ARm: 0.086473964 ARmax1: 0.285757750 ARmax10: 0.369832128 ARmax100: 0.374349028 ARs: 0.015053486 mask_AP: 0.143762723 mask_AP50: 0.255517960 mask_AP75: 0.144010365 mask_APl: 0.169036180 mask_APm: 0.017159620 mask_APs: 0.000000000 mask_ARl: 0.292368293 mask_ARm: 0.049971864 mask_ARmax1: 0.201763809 mask_ARmax10: 0.245515078 mask_ARmax100: 0.248252228 mask_ARs: 0.000000000 # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Training Performance Summary # @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ # Average throughput: 24.5 samples/sec Total processed steps: 90000 Total processing time: 16h 30m 53s ==================== Metrics ==================== FastRCNN box loss: 0.07314 FastRCNN class loss: 0.06654 FastRCNN total loss: 0.13968 L1 loss: 0.0000e+00 L2 loss: 0.56223 Learning rate: 4.0000e-05 Mask loss: 0.16035 RPN box loss: 0.01013 RPN score loss: 0.00494 RPN total loss: 0.01507 Total loss: 0.87733 Job finished with status: `SUCCESS`