Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Update README.md
Browse files
README.md
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---
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configs:
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- config_name: default
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data_files:
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---
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# Dataset Card for "competition_math"
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---
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license: mit
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task_categories:
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- text-generation
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language:
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- en
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pretty_name: MATH
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size_categories:
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- 10K<n<100K
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configs:
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- config_name: default
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data_files:
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---
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# Dataset Card for "competition_math"
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## Dataset Description
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- **Homepage:** https://github.com/hendrycks/math/blob/main/README.md
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- **Repository:** https://github.com/hendrycks/math
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- **Paper:** https://arxiv.org/abs/2103.03874
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### Dataset Summary
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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
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This dataset card aims to be a base template for new datasets.
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### Languages
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[English]
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## Dataset Structure
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### Data Instances
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7 sub-datasets
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### Data Splits
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training: 7500
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test: 5000
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## Additional Information
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### Licensing Information
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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).
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### Citation Information
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@article{hendrycksmath2021,
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title={Measuring Mathematical Problem Solving With the MATH Dataset},
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author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt},
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journal={NeurIPS},
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year={2021}
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}
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