How to prevent a neural network from outputing too clustered probabilities?
That's usually the most ideal case that you get in classification, but if you really want to, you can add a penalty on the predictions to force them to be away from zero or one, e.g. loss'(x) = loss(x) - param * prob_hat(x) * (1 - prob_hat(x)), or some different penalty.