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+ ---
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+ datasets:
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+ - meta-math/MetaMathQA
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+ ---
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+
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+ ## Introduction
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+ The model is trained with Masked Thought Fine-Tuning (MFT), a simple variant of standard Supervised Fine-Tuning (SFT). You can refer to our code and paper below.
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+
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+ ## Links
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+ - **Code**: [https://github.com/ChangyuChen347/MaskedThought](https://github.com/ChangyuChen347/MaskedThought)
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+ - **Paper**: [https://arxiv.org/abs/2403.02178](https://arxiv.org/abs/2403.02178)
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+
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+ ## Results
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+ We test it with the scripts provided in [MetaMath](https://github.com/meta-math/MetaMath).
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+ | Model | GSM8K | MATH |
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+ |--------------------------------------------------------------------------------------------------------------------------------------------------|-------|-------|
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+ | [adalaw/MetaMath-Mistral-7B-MFT](https://huggingface.co/adalaw/MetaMath-Mistral-7B-MFT) | 79.90 | 29.0 |
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+ | [meta-math/MetaMath-Mistral-7B-SFT](https://huggingface.co/meta-math/MetaMath-Mistral-7B) | 77.70 | 28.2 |