Solved by Caruso in post #2 
              
              
                It could be that nn.CrossEntropyLoss was used as a loss function, which does combine F.log_softmax and nn.NLLLoss (https://pytorch.org/docs/stable/nn.html#crossentropyloss). So therefor you don’t need a activation function at the end! 
Softmax could also be applied later on in the training loop, rig…