In the context of multilabel image classification, I am aware that the complexity of the model must match the size of the training set to not overfit. However, I don’t know what is the criteria.
Can someone give me an approximate number of  samples depending on the standard models say resnetxxx, densenetxxx, xceptionxxx, or others. Also, it will surely depend on the number of the layers trained in the case of transfer learning.
I could use all the help I can get.
Thanks in advance