Thanks @ptrblck Can you show me a code snippet. As I have a pre-trained resnet for CIFAR10 and I am using that to load for training with the same resnet18 definition as torchvision.models.resnet18. My model doesn’t learn anything and has only 10% accuracy.
But when I print the model, all the biases=False except for the last fc layer.
Now when I try training the whole pre-trained model over my new data which is adversary of CIFAR10, it gives me 76% test accuracy but the original accuracy on CIFAR10 decreases from 93.33% to 87%
I am not sure where am I going wrong and I am unsure which one of the above methods would be good for me if I want my model to be trained for both the data (CIFAR10 and adversary of CIFAR10).