network converging again, albeit slowly. not using quantized data nor loss prediction. Just 800 sample points, mean=0 and std=1, classification loss with SOFTMAX. This is important, softmax should be the one being used, since the preictal and interictal classes are independent and mutually exclusive. Next going to achieve same convergence in quantized data and then introduce prediction loss.
network converging again, albeit slowly. not using quantized data nor loss prediction. Just 800 sample points, mean=0 and std=1, classification loss with SOFTMAX. This is important, softmax should be the one being used, since the preictal and interictal classes are independent and mutually exclusive. Next going to achieve same convergence in quantized data and then introduce prediction loss.

projectappia/eegnet,projectappia/eegnet