Dropout is usually a good idea. I would just be careful about setting it at the output, as your logits will be zeroed out.
If you are using nn.CrossEntropyLoss, and are dealing with two classes, the output of your model should have the shape [batch_size, 2] and the targets should contain the class indices in the range [0, 1] with the shape [batch_size].