I’m unsure what the concern is and why the outputs wouldn’t make sense, so please add some more details in case I misunderstand it.
For multi-class classification/segmentation use cases usually nn.CrossEntropyLoss is used as the criterion, which expects raw logits as the model output. These logits are not bound to a specific range and can take arbitrary values. If you want to see the probabilities, you could apply a softmax on the output (but don’t pass the softmax output to nn.CrossEntropyLoss).