Fine-tuning LFM2.5-350M with 100 GRPO steps improves structured-output compliance
Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps
What happened
A publicly available, low-cost recipe fine-tunes LFM2.5-350M with TRL's GRPO using about 500 samples and 100 training steps, raising the pass rate on IFStruct from 22.6% to 29.7%. Training can run on a free Colab or Kaggle GPU, while evaluation uses llama.cpp on a local MacBook. The code is open on GitHub.
Hugging FaceOpen sourceData and trainingTutorials#Tutorials and practice#Open source#Data and training#Hugging Face
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