In my task, I have eight classes in the output in which each class for each image in my data set has a different label, so instead of having only zero and one in my target vector to show that image belongs to which classes, for each class I have a score for each class.  e.x
for img1_ label = [1, 0.2, 0.5, 0.33, 0.666, 1, 0.25, 0.133], and img2_label = [0.666, 1, 0.5, 0.33, 1, 0.5, 0.25, 0.133]. So for img1 the class 1 and 6 has a score one, and class 3 has score 0.5 and so on.
In this case, is still nn.BCEWithLogitsLoss a good option for loss function? and if I used this loss function do I need to have Sigmoid as an activate function on the last layer?