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[ARTICLE · art-169535] src=runtimewire.com ↗ pub= topic=machine-learning verified=true sentiment=· neutral

Hugging Face fixes TRL CISPO default that shrank gradients fivefold in its reproduction

Hugging Face shipped TRL v1.18.0 on November 13th, 2026, raising the CISPO default for the 'epsilon_high' setting to 5.0 after an inherited 0.2 ceiling clipped every on-policy importance weight to 0.2 when users left the parameter unset, shrinking gradients fivefold in its reproduction. The fix corrects a reinforcement-learning loss default that had been silently capping on-policy weights near 1.

read1 min views2 publishedNov 14, 2026
Hugging Face fixes TRL CISPO default that shrank gradients fivefold in its reproduction
Image: Runtimewire (auto-discovered)

Hugging Face's TRL v1.18.0 sets the CISPO default to 5.0 after an inherited 0.2 ceiling clipped on-policy weights near 1.

        By [RuntimeWire Staff](https://runtimewire.com/author/runtimewire-staff)
        · Published

Hugging Face, co-founded by Clement Delangue, has corrected a default in TRL's CISPO reinforcement-learning loss that clipped every on-policy importance weight to 0.2 when users left 'epsilon_high' unset. The fix shipped in TRL v1.18.0 on November 13th, 2026, and raises the CISPO default for that setting to 5.0.…

source & further reading
runtimewire.com — original article Hugging Face TRL fix halves a Qwen3 H100 step in SDPA test Hugging Face makes exported models portable across ONNX, OpenVINO, ExecuTorch and Dynamo Vercel patches WorkflowAgent's ignored approval policy in AI SDK code
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