At finetue stage, is that classifier is new, not finetune from trained?
banjuanshua opened this issue · 4 comments
Thank's for your work!
I have a question that is it classifier at test stage is new?
I can't find classifier loading trained weights in code.
The classification layer of baseline and baseline++ is new. For other meta-learning methods, protonet/matchingnet/relationnet do not have classification layer, and MAML would load the trained weight for the entire model (including classification layer).
Tanks for your answer. And did you analyze the difference of protonet implement be between yours (74.65% ResNet34) and MetaOptNet(75.60% ResNet12 feature_dimension=16000). I find backbone is different.
What's the feature dimension in your protonet?
Hello, for the ResNet 34 model, the feature dimension of the final layer is 7x7x2048, but we have included the avg pooling layer, so our feature dimension is 2048.
As the difference is not large, it could depend on parameters for training.