Please provide the following information when requesting support.
• Hardware (T4/V100/Xavier/Nano/etc) : GTX-1080ti
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc): lprnet/detectnet_v2
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here): TLT:3.0, docker_tag:v3.0-py3
I want to train lprnet and detectnet_v2 on custom dataset, and this is my learning rate schedule:
The process of training continue to 61 epochs, but I set to 120.
I guest the end of training really related to values of soft_start/annealing and number of dataset.
I want to know how I can calculate these value to training process reach to num_epochs.