I'm training my network (UNET) on Oxford Pets Dataset. Looking at the plots of train loss and validation loss, I'm pretty sure that the network overfits.
I trained the network for 100 epochs, with a learning rate of 0,0001 and a batch size=1.
My question is: Could it be since I have used a batch size=1? If I use a batch size higher, for example, a batch size = 8, then the network at each epoch should move the weights based on 8 images, is it right? Could it happen because I have trained too much my network (many steps)?
Additionally, a strange behavior that I have seen is that at the start the network seems to learn something about some images, but then It gets lost.
Could anyone give me some suggestions on how I could avoid this problem?