Datasets:
competition_math

Tasks:

Text2Text Generation

Languages: English

Multilinguality: monolingual

Size Categories: 10K<n<100K

Language Creators: expert-generated

Annotations Creators: expert-generated

Source Datasets: original

ArXiv:

Tags: explanation-generation

License: mit

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Cannot load the dataset split (in streaming mode) to extract the first rows.

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}
}