Thanks for the information!
Based on the description, I assume the output of [50, 288, 88] corresponds to [batch_size, seq_length, nb_classes]. Is this correct?
If so, the class dimension should be in dim1: [batch_size, nb_classes, seq_length].
Also, it does look as if your target is one-hot encoded, if you are setting a 1 for the active class.
If that’s the case, permute the target like the output (target = target.permute(0, 2, 1)) and use torch.argmax(target, 1) to get the class index.