Total Loss stops reducing while fine tuning for Instance Segmentation on Custom Dataset. Should I continue to train for more iterations ? about oneformer

[praeclarumjj3]

Hi @vineetsharma14, I suggest validating your model on a val set before tuning any hyper-parameters.

For example, at batch size of 1, the stating total loss was 87 which reduced to around 13 in 8000 iterations. But after that the train loss oscillates between the values of 9 to 28.

This is not uncommon, the range seems more than expected but it could be due to your dataset. I cannot make any comments without knowing the validation results. Any hyper-parameter tuning also depends on the number of classes in your dataset.

[vineetsharma14]

Thanks @praeclarumjj3 for the guidance. Really appreciate it !

I will check the dataset.

[BhavanaMP]

Hi @vineetsharma14 ,

Were you able to successfully reduce the training loss after finetuning? I am facing the same pattern in my finetuning experiments.. May I know how are you setting up the learning rate for text mapper while finetuning?