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Hey, as an enhancement for custom model training, I propose to add a configuration argument so that the trainer does not evaluate after every epoch but a specification to validate every n epochs.
This would speed up the training process as the validation on adversarial examples can take quite a long time and maybe doesn't make sense in the early stages of a training.
The text was updated successfully, but these errors were encountered:
I verified by myself and find that the PGD 7 ACC reaches its peak after the lr is dropped (probably at 100 epoch or 150 epoch). The final (at 200 epoch) model achieves a lower PGD 20 than the best model. I load the pre-trained model ResNet50 provided in this repo and it said the epoch is 152. It looks like they provide the best one, not the last model.
Hey, as an enhancement for custom model training, I propose to add a configuration argument so that the trainer does not evaluate after every epoch but a specification to validate every n epochs.
This would speed up the training process as the validation on adversarial examples can take quite a long time and maybe doesn't make sense in the early stages of a training.
The text was updated successfully, but these errors were encountered: