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---
dataset_info:
features:
- name: problem
dtype: string
- name: level
dtype: string
- name: type
dtype: string
- name: solution
dtype: string
- name: solution_variants
list: string
splits:
- name: train
num_bytes: 6120153
num_examples: 7500
download_size: 3239633
dataset_size: 6120153
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- en
tags:
- math
- reinforcement-learning
---
# MATH with Solution Variants
## Dataset Summary
This dataset is a processed version of [EleutherAI/hendrycks_math](https://huggingface.co/datasets/EleutherAI/hendrycks_math), which is derived from the original [MATH dataset](https://github.com/hendrycks/math) by Hendrycks et al.
The key addition in this version is the **`solution_variants`** column. This column contains semantically equivalent variations of the ground truth answer (e.g., "0.5" vs "1/2"), generated to serve as a robust reward signal for Reinforcement Learning (RL) training.
## Dataset Structure
Each example contains:
- **`problem`**: The original mathematics problem statement.
- **`solution`**: The original step-by-step solution.
- **`solution_variants`** (New): A list of valid, equivalent short answers extracted and verified with math_verify.
### Sample
```json
{
"problem": "What is 1/4 + 1/4?",
"solution": "... \\boxed{1/2}",
"solution_variants": ["1/2", "0.5"]
}
```
# Citation & Attribution
If you use this dataset, please cite the original MATH paper:
```json
@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}
}
``` |