Frequent discontinuities in loss function during training

I know it’s very difficult to debug without context, but I’m asking just in case this is a known phenomenon. I’m training a U-Net architecture for regression. During training, I frequently see discontinuities in the loss funciton, which look very strange to me. Here’s how the training history looks like:

I’m using Adam optimizer with a learning rate of 1e-3.

Are you using any learning rate schedulers or are resetting any objects (e.g. the optimizer)?

No, I use the default values:

optimizer = torch.optim.Adam(model.parameters(), lr=lr)

My bad, I think the graph shows a different paramter that I wanted to observe during training, not the actual loss function.