Hi everyone,
I have an issue with my UNet model, in the upsampling stage, I concatenated convolution layers with some layers that I created, for some reason my loss function decreases very slowly, after 40-50 epochs my image disappeared and I got a plane image with some pixels pattern.  Are there any suggestions on what it might be, and how can I fix it?
I used perceptual loss combined with MSE loss
torch.optim.SGD(prior_weights, lr=0.00001, momentum=0.9, weight_decay=0.0001)
Thank
Epoch:   0   Loss:  0.0021450244821608067
Epoch:   1   Loss:  0.002144632861018181
Epoch:   2   Loss:  0.0021442414727061987
Epoch:   3   Loss:  0.002143850550055504
Epoch:   4   Loss:  0.0021434600930660963
Epoch:   5   Loss:  0.0021430705673992634
Epoch:   6   Loss:  0.0021426803432404995
Epoch:   7   Loss:  0.0021422908175736666
Epoch:   8   Loss:  0.002141902456060052
Epoch:   9   Loss:  0.002141514327377081
Epoch:   10   Loss:  0.00214112619869411
Epoch:   11   Loss:  0.0021407371386885643
Epoch:   12   Loss:  0.0021403473801910877