Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
100K - 1M
License:
Zhangir Azerbayev
commited on
Commit
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727c257
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Parent(s):
cda48cc
updatd readme
Browse files
README.md
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@@ -56,7 +56,7 @@ This dataset contains only the training set of the [MATH dataset](https://github
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# Data Preprocessing
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This section describes any significant filtering and transformations made to various subsets of the data.
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**arXiv.math
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The arXiv.math dataset is large, heterogeneous, and contains a great deal of noise. We used the following heuristics
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when choosing which files from arXiv.math source folders to include in the dataset:
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- Keep only files with a `.tex` extension.
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In [this notebook](https://github.com/zhangir-azerbayev/proof-pile/blob/main/analysis/arxiv_noisedetection.ipynb), we provide an analysis of the prevalence of noisy documents in the arXiv.math subset of the
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proof-pile.
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**Stack Exchange
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We only include questions that have at least 5 upvotes and an answer. We format Stack Exchange posts as follows
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```
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QUESTION [{num_upvotes} upvotes]: {text of question}
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.
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```
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**set.mm
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We converted `set.mm` into human-readable form by following the instructions in the [mm-extract repo](https://github.com/zhangir-azerbayev/mm-extract)
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## Contributions
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# Data Preprocessing
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This section describes any significant filtering and transformations made to various subsets of the data.
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+
**arXiv.math.**
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The arXiv.math dataset is large, heterogeneous, and contains a great deal of noise. We used the following heuristics
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when choosing which files from arXiv.math source folders to include in the dataset:
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- Keep only files with a `.tex` extension.
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In [this notebook](https://github.com/zhangir-azerbayev/proof-pile/blob/main/analysis/arxiv_noisedetection.ipynb), we provide an analysis of the prevalence of noisy documents in the arXiv.math subset of the
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proof-pile.
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+
**Stack Exchange.**
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We only include questions that have at least 5 upvotes and an answer. We format Stack Exchange posts as follows
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```
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QUESTION [{num_upvotes} upvotes]: {text of question}
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.
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```
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+
**set.mm.**
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We converted `set.mm` into human-readable form by following the instructions in the [mm-extract repo](https://github.com/zhangir-azerbayev/mm-extract)
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## Contributions
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