Closed zlyin closed 4 years ago
Hi,
First thing I would check is the learning rate -- maybe it is too high for your fine-tuning.
Apart from that, I would encourage checking the discussion in https://github.com/facebookresearch/detr/issues/9 and https://github.com/facebookresearch/detr/issues/125 for some issues that can bring more insights into where the problem might be.
I would double check if one of your validation losses is going up - that would hint at overfitting
Hi @fmassa @alcinos Thank you for your reply! I actually have gone through the issue of #9 & #125 to reach current progress. I'll go through them again to see if can extract more insights.
As for your suggestions,
{loss_ce : 0.5, loss_bbox : 1, loss_giou : 1}
, is this ok to use?Thank you very much!
I haven't plotted out the losses separately. I'll try it and come up with an updated plot for your information. By the way, if I only use it for object detection task, what's the weight of each loss? Currently, I have {loss_ce : 0.5, loss_bbox : 1, loss_giou : 1}, is this ok to use?
I believe it would be preferable to use the default values for the loss coefficients, as changing them while using a pre-trained model might be suboptimal
Instructions To Reproduce the Issue:
Hi there, thank you for making this architecture available! I'm trying to use it on my custom dataset but confronted a wired situation, as indicated by the title. If you guys happen to come across the same issue, could you let me know the reason? Great thanks in advance!
what changes you made (
git diff
) or what code you wrotewhat exact command you run:
what you observed (including full logs):
please simplify the steps as much as possible so they do not require additional resources to run, such as a private dataset.
Expected behavior:
Environment:
Provide your environment information using the following command: