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---
datasets:
- meta-math/MetaMathQA
---
## Introduction
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.
## Links
- **Code**: [https://github.com/ChangyuChen347/MaskedThought](https://github.com/ChangyuChen347/MaskedThought)
- **Paper**: [https://arxiv.org/abs/2403.02178](https://arxiv.org/abs/2403.02178)
## Results
We test it with the scripts provided in [MetaMath](https://github.com/meta-math/MetaMath).
| Model | GSM8K | MATH |
|--------------------------------------------------------------------------------------------------------------------------------------------------|-------|-------|
| [adalaw/MetaMath-Mistral-7B-MFT](https://huggingface.co/adalaw/MetaMath-Mistral-7B-MFT) | 79.90 | 29.0 |
| [meta-math/MetaMath-Mistral-7B-SFT](https://huggingface.co/meta-math/MetaMath-Mistral-7B) | 77.70 | 28.2 |
|