BayJarvis: Blogs on dpo

paper Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models - 2024-02-06

A key challenge has been improving these models beyond a certain point, especially without the continuous infusion of human-annotated data. A groundbreaking paper by Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, and Quanquan Gu presents an innovative solution: Self-Play Fine-Tuning (SPIN). …

llm Harnessing Zephyr's Breeze: DPO Training on Mistral-7B-GPTQ for Language Model Alignment - 2023-11-09

We've taken on the exciting challenge of implementing the cutting-edge strategies presented in "ZEPHYR: Direct Distillation of LM Alignment". This paper's approach is not just theoretical—it's a blueprint for a significant leap in language model training. By adopting ZEPHYR's distilled direct preference optimization (dDPO), we've embarked on a code journey that brings these innovations from concept to reality. …

paper Direct Preference Optimization: Your Language Model is Secretly a Reward Model - 2023-11-05

In today's post, we delve into a recent paper that investigates the intricacies of Reinforcement Learning in the context of Large Language Models (LLMs). This study shines a light on the challenges and nuances of training such models to align better with human preferences. …