Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
explanation-generation
License:
metadata
annotations_creators:
- expert-generated
language_creators:
- expert-generated
pretty_name: Mathematics Aptitude Test of Heuristics (MATH)
size_categories:
- 10K<n<100K
source_datasets:
- hendrycks/competition_math
license: mit
dataset_info:
- config_name: algebra
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
splits:
- name: train
num_bytes: 955021
num_examples: 1744
- name: test
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num_examples: 1187
download_size: 858300
dataset_size: 1603312
- config_name: counting_and_probability
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
splits:
- name: train
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num_examples: 771
- name: test
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num_examples: 474
download_size: 504386
dataset_size: 1021188
- config_name: default
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
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- name: test
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- config_name: geometry
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- name: level
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- name: solution
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- name: type
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- config_name: intermediate_algebra
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
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- config_name: number_theory
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
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num_examples: 869
- name: test
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download_size: 490656
dataset_size: 945248
- config_name: prealgebra
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
splits:
- name: train
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- name: test
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num_examples: 871
download_size: 651355
dataset_size: 1225806
- config_name: precalculus
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: solution
dtype: string
- name: type
dtype: string
splits:
- name: train
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num_examples: 746
- name: test
num_bytes: 552893
num_examples: 546
download_size: 595986
dataset_size: 1369138
configs:
- config_name: algebra
data_files:
- split: train
path: algebra/train-*
- split: test
path: algebra/test-*
- config_name: counting_and_probability
data_files:
- split: train
path: counting_and_probability/train-*
- split: test
path: counting_and_probability/test-*
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- config_name: geometry
data_files:
- split: train
path: geometry/train-*
- split: test
path: geometry/test-*
- config_name: intermediate_algebra
data_files:
- split: train
path: intermediate_algebra/train-*
- split: test
path: intermediate_algebra/test-*
- config_name: number_theory
data_files:
- split: train
path: number_theory/train-*
- split: test
path: number_theory/test-*
- config_name: prealgebra
data_files:
- split: train
path: prealgebra/train-*
- split: test
path: prealgebra/test-*
- config_name: precalculus
data_files:
- split: train
path: precalculus/train-*
- split: test
path: precalculus/test-*
language:
- en
tags:
- explanation-generation
task_categories:
- text2text-generation
Dataset Card for Mathematics Aptitude Test of Heuristics (MATH) dataset in lighteval format
Table of Contents
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. This version of the dataset
contains appropriate builder configs s.t. it can be used as a drop-in replacement
for the inexplicably missing lighteval/MATH dataset.
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.
Data Splits
- train: 7,500 examples
- test: 5,000 examples
Builder Configs
- default: 7,500 train and 5,000 test examples (full dataset)
- algebra: 1,744 train and 1,187 test examples
- counting_and_probability: 771 train and 474 test examples
- geometry: 870 train 479 test examples
- intermediate_algebra: 1,295 train and 903 test examples
- number_theory: 869 train and 540 test examples
- prealgebra: 1,205 train and 871 test examples
- precalculus: 746 train and 546 test examples
Additional Information
Licensing Information
https://github.com/hendrycks/math/blob/main/LICENSE
This repository was created from the hendrycks/competition_math dataset. All credit goes to the original authors.
Citation Information
@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}
}
Contributions
Thanks to @hacobe for adding this dataset.