Maybe that's why the Phi models do so well for their size. I'm guessing they may have been trained close to convergence, but the loss graphs aren't published. Phi-1.5 (1.3B parameters) was trained on 150B tokens (5 epochs), yet phi-1.5-web was trained on 300B so they didn't stop for lack of compute. Phi-2 (2.7B params) was trained on 1.4T tokens, epochs unknown.