[Discussion] Influence of the number of classes on the performance of triplet loss

Does the number of classes need to be huge (1000+) in order to get good performance with triplet loss?

I am experimenting with a dataset which has 15 classes and 200 examples for each class. I kept a few classes for the test set and trained on the rest by constructing triplets. The loss drops steadily on the train set but not so much on the test set, it overfits.

I am contemplating is the reason for bad performance the …

influence loss machinelearning performance