Oh it seems you are right since it converges quickly to 0 and hovers around there.
However since I am doing semantic segmentation, I am likely to have much more background than objects as most of my objects are small-medium sized, how would I be able to prevent it converge towards class 0 then?
Also another thing, since I can reobtain the probabilities by just doing torch.exp(log probs) wouldn’t that mean that the probability for class 0 be 1 and hence the other should be 0 or -inf in log probs? Or is it because it is rounded up that’s why the other can be large negative values?
Btw, appreciate your help for here and around the forums, it has helped a lot of the problems I have faced when learning pytorch.