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README.md
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---
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license: odc-by
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---
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license: odc-by
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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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tags:
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- biology
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- chemistry
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- engineering
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- computer science
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- physics
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- material science
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- math
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- psychology
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- economics
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- political science
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- business
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- geology
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- sociology
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- geography
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- environmental science
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- art
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- history
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- philosophy
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pretty_name: PES2O
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size_categories:
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- 10B<n<100B
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---
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# PES2O 🌿🎓
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*Pretraining Efficiently on [S2ORC][2]!*
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The PES2O dataset is a collection of ~40M creative commmon licensed academic papers,
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cleaned, filtered, and formatted for pre-training of language models. It is derived from
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the [Semantic Scholar Open Research Corpus][2]([Lo et al, 2020][1]), or S2ORC.
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We release multiple version of PES2O, each with different processing and knowledge cutoff
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date. We recommend you to use the latest version available.
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## Document Format
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TODO
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## PES2O V1
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### Key Facts
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- *Knowledge cutoff*: 2023-01-03
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- *Number of documents*: 67.56M
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- *Number of whitespace-separated tokens**: 47,3M
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### Processing
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TODO
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| Dataset | Split | # Documents | # Words |
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|:-------:|:-------:|:-----------:|:--------------:|
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|s2orc | train | 8,242,162 | 36,088,195,908 |
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|s2orc | valid | 51,323 | 255,139,074 |
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|s2ag | train | 59,382,301 | 11,009,123,378 |
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|s2ag | valid | 111,228 | 24,398,512 |
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## PES2O V2
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### Key Facts
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- *Knowledge cutoff*: 2023-01-03
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- *Number of documents*: 38.97M
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- *Number of whitespace-separated tokens**: 42,28
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### Processing
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TODO
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| Dataset | Split | # Documents | # Words |
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|:-------:|:-----:|------------:|---------------:|
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| s2orc | train | 8,242,162 | 36,088,195,908 |
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| s2orc | valid | 51,323 | 255,139,074 |
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| s2ag | train | 30,569,017 | 5,920,099,207 |
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| s2ag | valid | 109,709 | 24,029,459 |
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[1]: https://aclanthology.org/2020.acl-main.447/
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[2]: https://github.com/allenai/s2orc
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