How many samples for setfit?

I understood that setfit is a light weight solution for few shot learning. Two questions came up:
.) What would be a number of samples of class you would switch to standard supervised learning and fine-tuning? E.g. 100 samples?
.) Is there any disadvantage of generating too many pairs (num_iterations) If I have 30 classes, wouldnt be the default of 20 too small to learn meaningful embeddings?