Hi
Yes, I removed the sigmoid and altered a few other things from the code originally posted (as for example the BCELoss() which is no longer used in favor of CrossEntropyLoss()).
I made the following visualization:

I am a little surprised to see that the model actually seems to be working 
In fact, the model has classified pixels that belong to the object class in the original image (which I unfortunately cannot show) but weren’t annotated as object in the labeled image.
I reckon that the zero loss I calculated from loss.item() is in fact a very small number, and maybe I should figure out a way to upscale it so it can be tracked