Why it matters

PPO is RLHF historical baseline. Understanding shapes evolution.

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The architecture

Reward model separate.

PPO: clipped advantage + KL penalty.

Value model reduces variance.

PPO RLHF flowReward modeltrained on prefsRollout + scorewith RMPPO updateclip + KLInstructGPT + ChatGPT used PPO originally; complex + expensive to tune
PPO FT.
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How it works end to end

Requires reward model + value model.

KL to SFT reference.

Sensitive to hyperparameters.