Shypd.aiThe largest open index of AI toolsDFT is an AI Agents & Automation tool that improves the generalization of Supervised Fine-Tuning (SFT) for Large Language Models. It offers a one-line code change to significantly enhance performance across challenging benchmarks.
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DFT (Dynamic Fine-Tuning) is an open-source tool designed to enhance the generalization capabilities of Supervised Fine-Tuning (SFT) for Large Language Models (LLMs). Through mathematical analysis, DFT identifies and rectifies problematic reward structures implicitly encoded in standard SFT gradients. The core innovation lies in a single-line code modification that dynamically rescales the objective function with the token's probability, stabilizing gradient updates. This approach has demonstrated significant performance gains over standard SFT on various benchmarks, particularly in mathematical reasoning and code-focused tasks. DFT also shows competitive results in offline reinforcement learning settings, providing a simpler yet effective alternative. It is available on GitHub and integrates with popular frameworks like TRL, LLaMA-Factory, and ms-swift.
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