This is a theoretical question. Is it possible to overfit a model on infinite amounts of data?
Let me clarify there are no duplicates.
Say, we have a generator function that produces data, with the correct classification/regression value, and we can generate infinite amounts of valid data. How long does it take for the model to overfit?
This question arose because I'm training an RNN model for fake news classification, and MSE loss is almost always 0.000, only 25% of the training data.
Will it be possible to overfit with one epoch of training on the infinite data generator?
(I'm thinking what will happen is the model will either get perfect, or sync into the generator's non-perfect randomness, and learn nothing)