huglabs/math_250

---
license: mit
datasets:
- openai/prm800k
language:
- en
---

# MATH - Processed Subset (250 Samples)

This dataset is a curated selection of 250 samples from the **MATH** dataset (specifically the splits found in the PRM800K repository). It is organized into three nested tiers for progressive benchmarking.

## Dataset Description

This version provides a controlled set of 250 mathematical problems divided into three tiers: **Small**, **Medium**, and **Large**.

**Nested Structure:**
The tiers are designed to be cumulative. Each subsequent tier includes all samples from the previous ones:
* **Small Tier:** The base selection of foundational samples.
* **Medium Tier:** Includes all samples from "Small" plus additional problems.
* **Large Tier:** Includes all samples from "Medium" (and "Small"), representing the full 250-sample subset.

## Dataset Sources

This subset is derived from the MATH dataset splits provided by OpenAI:
* **Repository:** [OpenAI PRM800K - MATH Splits](https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits)
* **Paper:** [Let's Verify Step by Step (Lightman et al., 2023)](https://arxiv.org/abs/2305.20050)

## Uses

This dataset is intended for:
* Benchmarking LLM mathematical reasoning.
* Experiments involving scalable oversight and process-based supervision.
* Quick evaluation runs where the full MATH dataset is too large for rapid iteration.

## Modifications and Attribution

This repository contains a **modified subset** of the original MATH data. The primary modifications include the selection of 250 specific rows and their categorization into the Small, Medium, and Large hierarchical tiers.

## Citation

If you use this dataset, please cite the original work:

```bibtex
@article{lightman2023lets,
title={Let's Verify Step by Step},
author={Lightman, Hunter and Kosaraju, Vineet and Burda, Yura and Edwards, Harri and Baker, Bowen and Lee, Teddy and Leike, Jan and Schulman, John and Sutskever, Ilya and Cobbe, Karl},
journal={arXiv preprint arXiv:2305.20050},
year={2023}
}

license: MIT许可证
datasets:
- openai/prm800k
language:
- 英语

# MATH - 预处理子集（250个样本）

本数据集是从**MATH**数据集（具体为PRM800K仓库中的划分子集）中精选的250个样本，采用三级嵌套结构以支持渐进式基准测试。

## 数据集描述

本版本提供了经过严格筛选的250道数学题，分为**基础（Small）**、**中等（Medium）**和**大规模（Large）**三个等级。

**嵌套结构说明：**
该等级设计遵循累积原则，后一级别包含前一级别的全部样本：
* **基础等级**：基础样本的核心集合。
* **中等等级**：包含所有基础等级样本与额外新增题目。
* **大规模等级**：包含所有中等等级（及基础等级）样本，即完整的250个样本子集。

## 数据集来源

该子集源自OpenAI提供的MATH数据集划分：
* **代码仓库**：[OpenAI PRM800K - MATH划分](https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits)
* **研究论文**：[《循序渐进验证（Let's Verify Step by Step）》（Lightman等人，2023）](https://arxiv.org/abs/2305.20050)

## 应用场景

本数据集适用于：
* 大语言模型（LLM/Large Language Model）数学推理能力的基准测试
* 涉及可扩展监督与过程式监督的实验研究
* 当完整MATH数据集规模过大无法快速迭代时，用于快速评估实验

## 修改与署名说明

本仓库包含原始MATH数据集的修改后子集，主要修改内容为筛选出250个特定样本，并将其划分为基础、中等、大规模三级层级结构。

## 引用规范

若您使用本数据集，请引用原始研究：
bibtex
@article{lightman2023lets,
title={Let's Verify Step by Step},
author={Lightman, Hunter and Kosaraju, Vineet and Burda, Yura and Edwards, Harri and Baker, Bowen and Lee, Teddy and Leike, Jan and Schulman, John and Sutskever, Ilya and Cobbe, Karl},
journal={arXiv预印本 arXiv:2305.20050},
year={2023}
}