When each label is either positive or negative it would be a binary classification or a (2 class) multi-class classification.
You can either return two logits (or log probabilities) from the model and use nn.CrossEntropyLoss (or nn.NLLLoss) or alternatively you can return a single logit and use nn.BCEWithLogitsLoss.