#
Datasets:

## The dataset preview is not available for this split.

Error code: StreamingRowsError Exception: NotImplementedError Message: Extraction protocol for TAR archives like 'https://people.eecs.berkeley.edu/~hendrycks/MATH.tar' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead. Example usage: url = dl_manager.download(url) tar_archive_iterator = dl_manager.iter_archive(url) for filename, file in tar_archive_iterator: ... Traceback: Traceback (most recent call last): File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 485, in compute_first_rows_response rows = get_rows( File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 120, in decorator return func(*args, **kwargs) File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 164, in get_rows ds = load_dataset( File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/load.py", line 1751, in load_dataset return builder_instance.as_streaming_dataset(split=split) File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1206, in as_streaming_dataset splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)} File "/tmp/modules-cache/datasets_modules/datasets/competition_math/2a2a2995c2847186883ecd64f69be7d602b8a6f6b51950624d4dc2263f93333b/competition_math.py", line 70, in _split_generators download_dir = dl_manager.download_and_extract(_URL) File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1074, in download_and_extract return self.extract(self.download(url_or_urls)) File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1026, in extract urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True) File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 436, in map_nested return function(data_struct) File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1036, in _extract raise NotImplementedError( NotImplementedError: Extraction protocol for TAR archives like 'https://people.eecs.berkeley.edu/~hendrycks/MATH.tar' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead. Example usage: url = dl_manager.download(url) tar_archive_iterator = dl_manager.iter_archive(url) for filename, file in tar_archive_iterator: ...

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

### 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.

### Data Splits

- train: 7,500 examples
- test: 5,000 examples

## 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

```
@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.

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