RLHF preference data curation pipeline: HH-RLHF + UltraFeedback + OASST1 → quality filter → MinHash dedup → DPO-ready JSONL
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Updated
Jun 7, 2026 - Python
RLHF preference data curation pipeline: HH-RLHF + UltraFeedback + OASST1 → quality filter → MinHash dedup → DPO-ready JSONL
Reinforcement learning from human feedback (RLHF) fine-tuning of Qwen2.5-0.5B-Instruct with LoRA and Hugging Face TRL on the UltraFeedback preference dataset. Runs on a free Colab T4.
Measuring verbosity bias in UltraFeedback (61K GPT-4-annotated preference pairs): statistically unambiguous, but a small effect. Python + Streamlit.
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