Solved by ptrblck in post #4 
              
              
                You have different options for a binary classification use case: 

you could use 1 output neuron and [nn.Sigmoid + nn.BCELoss]
1 output neuron and [raw logits (no non-linearity for the last layer) + nn.BCEWithLogitsLoss]
2 output neurons and [nn.LogSoftmax + nn.NLLLoss]
2 output neurons and [raw log…