Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod
Learn how we fine-tuned GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod, and how to decide between supervised fine-tuning (SFT) and reinforcement learning with GRPO. SFT took reasoning-language accuracy from 22% to 100%, and GRPO added measurable gains where headroom existed.
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Qué ocurrió
Learn how we fine-tuned GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod, and how to decide between supervised fine-tuning (SFT) and reinforcement learning with GRPO. SFT took reasoning-language accuracy from 22% to 100%, and GRPO added measurable gains where headroom existed.
Por que importa
The development may change operating conditions or market expectations around Amazon. Further confirmation and measurable outcomes matter.
Entidades afectadas
Ver evidencia
1 articulos · 1 informe original · 1 independientes
- AWS Machine Learning BlogFuente primaria · Respalda · EN · 100%Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod ↗
Afirmaciones
- Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod Observado
Conflictos
No se detectaron conflictos importantes en la evidencia disponible.
Cronología
- Primera publicación
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