So I train on a train set, check on a dev set, and train on a train set after changing something?
I still don’t understand the chart with iterations. If I’m only evaluating my model on the dev set, I would feed my NN with inputs, run forward propagation, and check error (Y hat vs. true Y). There will be no multiple iterations - just a single iteration.
My understanding is that a single iteration is forward propagation + back propagation. Multiple iterations are run in the training phase (each iteration is updating my W and b).
So I don’t understand iterations in the dev set since we are not training in a dev set.