Hello!
I’m working on a Multi-class model where my target is a one-hot encoded vector of size C for each input sample. Since the output should be a vector of probabilities with dimension C, I’m having trouble finding what combination of output layer activation and Loss Function to use.
Based on what I’ve read so far, vanilla nn.NLLLoss and nn.CrossEntropyLoss can’t be used since the output is a label. My guess is that I would either need to tweak these loss functions to use one-hot encoded target or write my own loss. I’m somewhat confused on how to proceed form here since I don’t know how each of these options are going to impact the final model performance.