Cheatsheet: RL Loss Functions
PPO and GRPO loss functions annotated term-by-term — the clipped surrogate, GAE, value loss, entropy bonus, and group-normalised advantages — with links to the posts explaining each design choice.
PPO and GRPO loss functions annotated term-by-term — the clipped surrogate, GAE, value loss, entropy bonus, and group-normalised advantages — with links to the posts explaining each design choice.
PPO and GRPO loss functions annotated term-by-term — the clipped surrogate, GAE, value loss, entropy bonus, and group-normalised advantages — with links to the posts explaining each design choice.
GRPO achieves competitive alignment results without a value function. Here's exactly what changes in the math and implementation, and why that matters for training efficiency and stability.
ppo-loss-per-token covered the clipped surrogate objective. This post covers what surrounds it: how the value function is trained, where the advantage estimates come from, and why the entropy bonus exists.
GRPO achieves competitive alignment results without a value function. Here's exactly what changes in the math and implementation, and why that matters for training efficiency and stability.
ppo-loss-per-token covered the clipped surrogate objective. This post covers what surrounds it: how the value function is trained, where the advantage estimates come from, and why the entropy bonus exists.