A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”
Hello!
I have some general questions on understanding the metrics used in training. From the example below:
2022-08-13 19:12:26,520 maskrcnn_benchmark INFO: eta: 1:05:16 iter: 26000 loss: 0.0018 (0.0215) loss_refine_att: 0.0003 (0.0013) loss_refine_obj: 0.0014 (0.0201) loss_rel: 0.0000 (0.0002) time: 0.9628 (0.9792) data: 0.0123 (0.0197) lr: 0.000009 max mem: 8478
What is this general loss? And how is it different from the loss value inside parenthesis () and what about data? What does data here refer to?
I would greatly appreciate your answer.
❓ Questions and Help
Hello! I have some general questions on understanding the metrics used in training. From the example below:
2022-08-13 19:12:26,520 maskrcnn_benchmark INFO: eta: 1:05:16 iter: 26000 loss: 0.0018 (0.0215) loss_refine_att: 0.0003 (0.0013) loss_refine_obj: 0.0014 (0.0201) loss_rel: 0.0000 (0.0002) time: 0.9628 (0.9792) data: 0.0123 (0.0197) lr: 0.000009 max mem: 8478What is this generalloss? And how is it different from the loss value inside parenthesis()and what aboutdata? What doesdatahere refer to? I would greatly appreciate your answer.Thank you and have a good day!