I’m using Adam as an optimizer and tried several learning rate.
But nothing actually changes. And haven’t tried training with 2 models yet.
The loss function is torch.nn.BCELoss and the reason that loss is large is that because reduction is sum.
The original data’s shapes are (batch size, C, H, W) = (32, 10, 100, 100) and during the training, I’m training each channel with an independent model and optimizer. Which means the shape of input data to model is (32, 1, 100, 100).
And also original data is the output of the segmentation model, so each channel is the probability.