Thanks for input. Until now i managed to run 4 different regularization schemes, L1, L2, L1L2 on different layers, just the output layers and whole model, with default textbook parameters and some wild guesses. No change in outcome, regularization has no impact besides wild loss output in the begining of training.
I think i’ll give up on that and get back to making the net wider xor deeper.
Unless you have any other ideas?
Regards