Hi @ptrblck , thanks for taking a look at my problem, could you provide example of how to do this transformation?
I also resized the number of my labels since last question due to high imbalance in my target data. So now, each label has 6 genres and looks as follows :
tensor([1, 4, 1, 0, 5, 2])
and the output of my model looks like that :
tensor([[-0.0372, -0.0156, -0.0152,  0.0168, -0.0080,  0.0074],
[-0.0337, -0.0016, -0.0026, -0.0089, -0.0027,  0.0187]],
I am not sure how do some classes active while other inactive, could you give a hint or provide example?        I know, that nn.BCEWithLogitsLoss has to be followed by sigmoid as activation function, but I am not sure what’s the best way to use it in my case.