nvidia/OpenMath-MATH-masked

---
license: other
license_name: nvidia-license
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- math
- nvidia
pretty_name: OpenMath MATH Masked
size_categories:
- 1K<n<10K
---

# OpenMath GSM8K Masked

We release a *masked* version of the [MATH](https://github.com/hendrycks/math) solutions.
This data can be used to aid synthetic generation of additional solutions for MATH dataset
as it is much less likely to lead to inconsistent reasoning compared to using
the original solutions directly.

This dataset was used to construct [OpenMathInstruct-1](https://huggingface.co/datasets/nvidia/OpenMathInstruct-1):
a math instruction tuning dataset with 1.8M problem-solution pairs
generated using permissively licensed [Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) model.

For details of how the masked solutions were created, see our [paper](https://arxiv.org/abs/2402.10176).

You can re-create this dataset or apply similar techniques to mask solutions for other datasets
by using our [open-sourced code](https://github.com/Kipok/NeMo-Skills).

## Citation

If you find our work useful, please consider citing us!

```bibtex
@article{toshniwal2024openmath,
title = {OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset},
author = {Shubham Toshniwal and Ivan Moshkov and Sean Narenthiran and Daria Gitman and Fei Jia and Igor Gitman},
year = {2024},
journal = {arXiv preprint arXiv: Arxiv-2402.10176}
}
```

## License

The use of this dataset is governed by the [NVIDIA License](LICENSE) which permits commercial usage.

原始信息汇总

OpenMath GSM8K Masked

概述

• 数据集名称: OpenMath GSM8K Masked
• 许可证: NVIDIA License
• 任务类别:
  • 问答
  • 文本生成
• 语言: 英语
• 标签:
  • 数学
  • NVIDIA
• 大小类别: 1K<n<10K
• 别名: OpenMath MATH Masked

描述

• 该数据集是MATH解决方案的掩码版本。
• 用于辅助生成MATH数据集的额外解决方案，相比直接使用原始解决方案，更不容易导致推理不一致。
• 用于构建OpenMathInstruct-1，一个包含180万个问题-解决方案对的数学指令调优数据集。
• 解决方案的生成使用了Mixtral-8x7B模型。

参考文献

• 论文: OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
• 作者: Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, Daria Gitman, Fei Jia, Igor Gitman
• 年份: 2024