Awesome.I think it is working (finally).
Now that you have seen the code I had three questions:

The batch accuracy does not represent the accuracy of our model as it can be very inaccurate in the first iterations. Ideally, the accuracy should be measured in the last epoch where most of the “learning” has been done. How can I move from the batch accuracy to a more general model accuracy that can even later be applied to testing?
2.Is the Loss function you mentioned just a binary cross-entropy loss?
3.Any tips to improve the model generally?I have a relu->sigmoid two-layer NN and have to stick to a very specific architecture.