Hi everyone!
I’m pretty new to PyTorch.
I’ve been trying to train a VGG16 to perform multiclass classification of face images.
I’ve used ‘torchvision.models’ to import vgg16 pretrained model as follows:
model = models.vgg16(pretrained=True)
I’ve changed the last linear layer in the classifier to output 27 classes but it seems that it can’t learn good enough; It stops at 0.0333 accuracy and can’t go better than that.
I’ve used Cross Entropy Loss and SGD optimizer of PyTorch.
Must mention that I did try to train other models from ‘torchvision.models’ (VGG11, GoogleNet and others) and they went amazing.
Can someone please help me to understand why is this happening?