Different hidden layer architectures deliver the same classification results, is that normal?
There are several things I would like to mention :


I do not think that much change on your architecture will impact a lot. Try comparing 10, 20, 50, 100 or more depth. Difference will be most likely to be slightly more noticeable.
You are comparing accuracy which is based on labels instead of the probabilities. Try comparing logloss or auc score which is more sensitive to small changes.


Hope this helps.