Quick question: Am I correctly assuming that in order to evaluate the model on the 1,000-class ImageNet validation dataset one has to train the linear classifier first (using LinearProbing.py)? If so, would it be possible to release pre-trained weights for the classifier as well, such that one can use classifier.load_state_dict(checkpoint['classifier'])?
Hey there, thanks for the well-documented code!
Quick question: Am I correctly assuming that in order to evaluate the model on the 1,000-class ImageNet validation dataset one has to train the linear classifier first (using
LinearProbing.py
)? If so, would it be possible to release pre-trained weights for the classifier as well, such that one can useclassifier.load_state_dict(checkpoint['classifier'])
?