Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
File size: 2,937 Bytes
f0ed5c4 bc97b22 75227dd bc97b22 75227dd f0ed5c4 11a3b83 7e7bdd0 f0ed5c4 75227dd 11a3b83 e6243e4 11a3b83 bd76e17 11a3b83 bd76e17 75227dd f0ed5c4 bc97b22 5d51899 bc97b22 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 | ---
language:
- en
license: mit
size_categories:
- 10K<n<100K
task_categories:
- text-generation
pretty_name: MATH
configs:
- config_name: numeric
data_files:
- split: train
path: numeric/train-*
- split: test
path: numeric/test-*
- config_name: original
data_files:
- split: train
path: original/train-*
- split: test
path: original/test-*
dataset_info:
- config_name: default
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: type
dtype: string
- name: solution
dtype: string
- name: extracted_solution
dtype: string
splits:
- name: train
num_bytes: 6062403
num_examples: 7500
- name: test
num_bytes: 3783919
num_examples: 5000
download_size: 4921628
dataset_size: 9846322
- config_name: numeric
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: type
dtype: string
- name: solution
dtype: string
- name: extracted_solution
dtype: float64
splits:
- name: train
num_bytes: 3712169
num_examples: 4866
- name: test
num_bytes: 2229985
num_examples: 3199
download_size: 3035498
dataset_size: 5942154
- config_name: original
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: type
dtype: string
- name: solution
dtype: string
- name: extracted_solution
dtype: string
splits:
- name: train
num_bytes: 6062403
num_examples: 7500
- name: test
num_bytes: 3783919
num_examples: 5000
download_size: 4921628
dataset_size: 9846322
---
# Dataset Card for "competition_math"
Added column with final solution extracted from \boxed{} tags.
Added `numeric` congig that only contains questions with numeric answers.
## Dataset Description
- **Homepage:** https://github.com/hendrycks/math/blob/main/README.md
- **Repository:** https://github.com/hendrycks/math
- **Paper:** https://arxiv.org/abs/2103.03874
### Dataset Summary
MATH contains 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanation
This dataset card aims to be a base template for new datasets.
### Languages
[English]
## Dataset Structure
### Data Instances
7 sub-datasets
### Data Splits
training: 7500
test: 5000
## Additional Information
### Licensing Information
MIT but check the [Legal Compliance](https://arxiv.org/pdf/2103.03874.pdf) section in appendix B of the paper as well as the [repo](https://github.com/hendrycks/math/blob/main/LICENSE).
### 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={NeurIPS},
year={2021}
} |