The softmax, after the network has been trained, yields an estimate of the probability in the training data, but it is not that probability itself.
replyWhich models are not trained with the log softmax as the loss function?
replySoftmax isn't a loss function. It is used to transform model outputs into positive numbers that sum to 1, so that they can be interpreted as probabilities, and then those numbers are passed into (typically) the cross entropy loss function. I think you mean, which models are trained using some function other than softmax to transform the model outputs. There are a number of alternatives to softmax, such as the ones described here https://www.emergentmind.com/topics/sparsemax
replyThe cross entropy loss function is softmax. They are one and the same.
replyThey’re not. Cross entropy loss is E[-log q] where q is a probability. You could convert the model outputs x into probabilities using some other function like q = 1/Z x^2, and compute cross entropy loss just fine.
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