Hi,
I would like to know if anyone has encountered this problem:
When using the function for a more complex problem, I noticed that the current model error starts to increase.
I thought it was an error in my program, but when I tested the repository example, when I increased the epochs a little more, I found the same problem.

I leave below the image referring to the results of the example of the repository for more than 20 epochs:

On the one hand, I don't know if I should let the model evolve a little in this sense, hoping that it is just trying not to overfit.
However, I think that the assumption is always that the error decreases or at least stabilizes.
I tried to "fix" this by putting a simple "if" inside the anfis.py function itself that when the error increases more than 0.001, for more than 3 times (for exemple), it stops the training loop. However, I don't know to what extent this cannot be detrimental to the results

Thanks in advance