raining. In this work, we study Self-Rewarding Language Models, where the
language model itself is used via LLM-as-a-Judge prompting to provide its
own rewards during training. We show that during Iterative DPO training
that not only does instruction following ability improve, but also the ability
to provide high-quality rewards to itself. Fine-tuning Llama 2 70B on three
iterations of our approach yields a model that outperforms many existing
systems on the AlpacaEval 2.0 leaderboard, including Claude 2, G