I have a binary classification task. I have shown the loss curve here. I have decreased the learning rate by 1/10 every 15 epochs. There is also dropout put in the model. As you can see, I am trying to figure out the optimal point for model training. My initial assumption was that the point came at around epoch 28 since the validation error almost remains constant and then increases ever so slightly. However, I still wanted to know if this is fine or the model is indeed overfitting.
Another concern I have is that the training and validation curves are very very close to each other. Is this an expected behavior?
Being a newbie I would really appreciate any help in here