NaN loss when training regression network

Question

I have a data matrix in \"one-hot encoding\" (all ones and zeros) with 260,000 rows and 35 columns. I am using Keras to train a simple neural network to predict a continuou

Answer 1

I had the same problem with my keras CNN, as others I tried all above solutions: decrease learning rate, drop nullity from train data, normalize data, add dropout layer and ... but there couldn't solve nan problem, I tried change activation function in classifier (last) layer from sigmoid to softmax. It worked! try changing activation function of last layer to softmax!