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For the test at the end of training, why would you use the one loaded from the training set instead of the train_test_loader, instead of the test_loader loaded from the test set, and the accuracy of the test from the training set is not accurate, right?
The text was updated successfully, but these errors were encountered:
Thank you for your concern. The test() function defaults to using the test_loader since the parameter mode is default set to "test".
The train_test_loader is only used when adding an option test_train True. For instance, if you run python main.py -d imagenet_lt -m clip_vit_b16_peft test_train True, you will obtain the training accuracy on ImageNet-LT. This can be used for comparing training/test accuracy, as presented in Table 8 in our paper. Aside from this, all results are calculated from the test set.
For the test at the end of training, why would you use the one loaded from the training set instead of the train_test_loader, instead of the test_loader loaded from the test set, and the accuracy of the test from the training set is not accurate, right?
The text was updated successfully, but these errors were encountered: