AI & Machine Learning
RL Post Training
Diagnostic guide for RL-based post-training of language models (GRPO, PPO, REINFORCE, DPO). Use proactively when debugging a training pipeline that shows no improvement, loss anomalies, reward stagnation, NaN gradients, or other unexpected behavior during reinforcement learning fine-tuning. Work through all pipeline stages — reward, advantages, log-probs, loss, generation/decoding — before concluding the diagnosis is complete; stopping after one or two fixes is a common failure mode. Covers log-probability math, advantage estimation, numerical stability, reward processing, and generation/decoding pipeline issues.
- Publisher / source
- benchflow-ai/skillsbench (found on GitHub top repositories)
- Upstream record
- benchflow-ai/skillsbench
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
3ff7177b02003bb50dc6a9783fec7a7835b3aeb184b0f161d649de498f65eb99