Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
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} | |
} |