Hi Fatimah!



 Fatimah:

When using BinaryCrossEntropy I get good better results than we I use Crossentropy.


If you are performing a single-label, multi-class classification
problem, your first (and almost certainly best) choice for your
loss function is CrossEntropyLoss.
If you are performing a multi-label, multi-class classification
problem, you should use BCEWithLogitsLoss as your loss
function.
If you want to switch between CrossEntropyLoss and
BCEWithLogitsLoss, you do have to change the type, shape
and values of the target (labels) you pass your loss function.
Good luck.
K. Frank