Agatha:

The idea of [0, 7] comes because I use PyTorch and the labels have to range from [0- n_labels-1].


That’s true for a multi-class classification use case using nn.CrossEntropyLoss or nn.NLLLoss, but wrong for a multi-label classification using nn.BCEWithLogitsLoss.
For the latter use case, your targets should have the same shape as the model outputs and be multi-hot encoded, so that you can set multiple classes to “active” or “inactive” (1 and 0).