Getting 0 accuracy and NaN mae for all epochs training my NN
Maybe I'm not interpreting this correctly (I don't use Keras), but why does your softmax layer only have a single unit? The softmax function normalizes a vector to represent a probability distribution: $ f : ℝ^n \rightarrow (0,1)^n  $ such that $\sum f(\vec x)=1 $. I would have assumed the softmax layer to use the same number of units as the previous, but again, maybe I'm not understanding Keras.
Usually, gradient explosions cause nan. If you are unfamiliar with it, you could read about the related vanishing gradient problem here. However, in your case, I think the final layer is more suspicious.