I’m trying to train a model based on segmentation using Encoder (LBCnet) and decoder (Unet). My dataset contains biomedical images of skin lesion and corresponding masks, but whenever i run it losses corresponding to each batch give me very big negative values and i can’t figure out why?.
10 epochs, 260 total_steps per epoch
Epoch [1/10], Step [100/260], Loss: -53.379780
Epoch [1/10], Step [200/260], Loss: -49.816761
Epoch [2/10], Step [100/260], Loss: -23.087646
Epoch [2/10], Step [200/260], Loss: -48.471092
Epoch [3/10], Step [100/260], Loss: -52.749981
Epoch [3/10], Step [200/260], Loss: -29.466999
Epoch [4/10], Step [100/260], Loss: -57.213978
Epoch [4/10], Step [200/260], Loss: -20.504835
Epoch [5/10], Step [100/260], Loss: -80.539688
Epoch [5/10], Step [200/260], Loss: -70.907478
Epoch [6/10], Step [100/260], Loss: -62.066265
Epoch [6/10], Step [200/260], Loss: -51.600151
Epoch [7/10], Step [100/260], Loss: -24.601454
Epoch [7/10], Step [200/260], Loss: -72.403343
Epoch [8/10], Step [100/260], Loss: -45.917526
Epoch [8/10], Step [200/260], Loss: -62.943592
Epoch [9/10], Step [100/260], Loss: -36.994308