In the paper it is mentioned that the softmax function is being applied to the outputs after computing scores for each candidate item (equation 9), however, the PyTroch Implemention (compute_scores method) doesn't seem to be doing that. Is there a reason why it isn't used?
I have tested the model with the softmax function (default hyperparameters), and the evaulation metrics peformance has drastically decreased. I suspect if it has anything to do with the low output values after softmax. Any thoughts on this?
In the paper it is mentioned that the softmax function is being applied to the outputs after computing scores for each candidate item (equation 9), however, the PyTroch Implemention (compute_scores method) doesn't seem to be doing that. Is there a reason why it isn't used?
I have tested the model with the softmax function (default hyperparameters), and the evaulation metrics peformance has drastically decreased. I suspect if it has anything to do with the low output values after softmax. Any thoughts on this?