I have a multi-class classification problem and the model I train gives an overall reasonable accuracy but fails in one or a few smaller classes (very low performance only on that class). I think part of the reason is that I use regular CrossEntropy as my loss function so I am optimizing for overall accuracy and not enforcing minimum per-class performance in any way. Is there any loss function in Keras that can do that for me? In other words, how do I force my model to not just focus on overall accuracy but ensure that I will have a reasonable performance in all classes?