hyzmodel/competition_math

---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: Mathematics Aptitude Test of Heuristics (MATH)
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
tags:
- explanation-generation
---

# Dataset Card for Mathematics Aptitude Test of Heuristics (MATH) dataset

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://github.com/hendrycks/math
- **Repository:** https://github.com/hendrycks/math
- **Paper:** https://arxiv.org/pdf/2103.03874.pdf
- **Leaderboard:** N/A
- **Point of Contact:** Dan Hendrycks

### Dataset Summary

The Mathematics Aptitude Test of Heuristics (MATH) dataset consists of problems
from mathematics competitions, including the AMC 10, AMC 12, AIME, and more.
Each problem in MATH has a full step-by-step solution, which can be used to teach
models to generate answer derivations and explanations.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

A data instance consists of a competition math problem and its step-by-step solution written in LaTeX and natural language. The step-by-step solution contains the final answer enclosed in LaTeX's `\boxed` tag.

An example from the dataset is:
```
{'problem': 'A board game spinner is divided into three parts labeled $A$, $B$ and $C$. The probability of the spinner landing on $A$ is $\\frac{1}{3}$ and the probability of the spinner landing on $B$ is $\\frac{5}{12}$. What is the probability of the spinner landing on $C$? Express your answer as a common fraction.',
'level': 'Level 1',
'type': 'Counting & Probability',
'solution': 'The spinner is guaranteed to land on exactly one of the three regions, so we know that the sum of the probabilities of it landing in each region will be 1. If we let the probability of it landing in region $C$ be $x$, we then have the equation $1 = \\frac{5}{12}+\\frac{1}{3}+x$, from which we have $x=\\boxed{\\frac{1}{4}}$.'}
```

### Data Fields

* `problem`: The competition math problem.
* `solution`: The step-by-step solution.
* `level`: The problem's difficulty level from 'Level 1' to 'Level 5', where a subject's easiest problems for humans are assigned to 'Level 1' and a subject's hardest problems are assigned to 'Level 5'.
* `type`: The subject of the problem: Algebra, Counting & Probability, Geometry, Intermediate Algebra, Number Theory, Prealgebra and Precalculus.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

https://github.com/hendrycks/math/blob/main/LICENSE

### Citation Information
```bibtex
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
and Steven Basart
and Eric Tang
and Dawn Song
and Jacob Steinhardt},
journal={arXiv preprint arXiv:2103.03874},
year={2021}
}
```

---
annotations_creators:
- 专家生成
language_creators:
- 专家生成
language:
- 英文
license:
- MIT
multilinguality:
- 单语
pretty_name: 启发式数学能力测试（Mathematics Aptitude Test of Heuristics，MATH）
size_categories:
- 10K<n<100K
source_datasets:
- 原创
task_categories:
- 文本到文本生成（text2text-generation）
task_ids: []
tags:
- 解释生成（explanation-generation）
---

# 启发式数学能力测试（MATH）数据集卡片

## 目录
- [目录](#table-of-contents)
- [数据集描述](#dataset-description)
- [数据集概述](#dataset-summary)
- [支持的任务与排行榜](#supported-tasks-and-leaderboards)
- [语言](#languages)
- [数据集结构](#dataset-structure)
- [数据实例](#data-instances)
- [数据字段](#data-fields)
- [数据拆分](#data-splits)
- [数据集创建](#dataset-creation)
- [构建理由](#curation-rationale)
- [来源数据](#source-data)
- [标注信息](#annotations)
- [个人与敏感信息](#personal-and-sensitive-information)
- [数据使用注意事项](#considerations-for-using-the-data)
- [数据集的社会影响](#social-impact-of-dataset)
- [偏差讨论](#discussion-of-biases)
- [已知局限性](#other-known-limitations)
- [附加信息](#additional-information)
- [数据集维护者](#dataset-curators)
- [许可信息](#licensing-information)
- [引用信息](#citation-information)
- [贡献](#contributions)

## 数据集描述

- **主页**: https://github.com/hendrycks/math
- **仓库**: https://github.com/hendrycks/math
- **论文**: https://arxiv.org/pdf/2103.03874.pdf
- **排行榜**: 无
- **联系人**: Dan Hendrycks

### 数据集概述

启发式数学能力测试（MATH）数据集包含来自数学竞赛的题目，涵盖AMC 10、AMC 12、AIME等赛事。数据集中的每个题目均配有完整的分步解答，可用于训练模型生成答案推导过程与解释。

### 支持的任务与排行榜

[需补充更多信息]

### 语言

[需补充更多信息]

## 数据集结构

### 数据实例

一个数据实例包含一道竞赛数学题及其用LaTeX和自然语言编写的分步解答。分步解答中包含用LaTeX的`oxed`标签包裹的最终答案。

数据集中的示例如下：

{'problem': 'A board game spinner is divided into three parts labeled $A$, $B$ and $C$. The probability of the spinner landing on $A$ is $\frac{1}{3}$ and the probability of the spinner landing on $B$ is $\frac{5}{12}$. What is the probability of the spinner landing on $C$? Express your answer as a common fraction.',
'level': 'Level 1',
'type': 'Counting & Probability',
'solution': 'The spinner is guaranteed to land on exactly one of the three regions, so we know that the sum of the probabilities of it landing in each region will be 1. If we let the probability of it landing in region $C$ be $x$, we then have the equation $1 = \frac{5}{12}+\frac{1}{3}+x$, from which we have $x=\boxed{\frac{1}{4}}$.'}

### 数据字段

* `problem`: 竞赛数学题
* `solution`: 分步解答
* `level`: 题目难度等级（从'Level 1'到'Level 5'，其中人类最容易解决的题目归为'Level 1'，最难的题目归为'Level 5'）
* `type`: 题目类型：代数、计数与概率、几何、中级代数、数论、预代数和预微积分

## 数据集创建

### 构建理由

[需补充更多信息]

### 来源数据

#### 初始数据收集与标准化

[需补充更多信息]

#### 源语言生产者

[需补充更多信息]

### 标注信息

#### 标注流程

[需补充更多信息]

#### 标注者

[需补充更多信息]

### 个人与敏感信息

[需补充更多信息]

## 数据使用注意事项

### 数据集的社会影响

[需补充更多信息]

### 偏差讨论

[需补充更多信息]

### 已知局限性

[需补充更多信息]

## 附加信息

### 数据集维护者

[需补充更多信息]

### 许可信息

https://github.com/hendrycks/math/blob/main/LICENSE

### 引用信息
bibtex
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
and Steven Basart
and Eric Tang
and Dawn Song
and Jacob Steinhardt},
journal={arXiv preprint arXiv:2103.03874},
year={2021}
}