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license: odc-by |
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--- |
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# Zynemo-5T |
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<!-- Provide a quick summary of the dataset. --> |
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Zynemo is a 5 trillion token language modeling dataset created by collecting open and high quality datasets and combining them and cross-deduplication and model-based quality filtering. Zynemo comprises diverse sources of web data, highly educational content, math, code, and scientific papers. |
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To construct Zynemo, we took the best open-source datasets available: Zyda, FineWeb, DCLM, Dolma. Models trained on Zynemo significantly outperform identical models trained on the Pile, RefinedWeb, FineWeb, FineWeb-Edu, and DCLM. Due to our post-processing deduplication, filtering, and weighting pipeline, Zynemo outperforms all its constituent datasets in resulting model quality. |
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An early version of Zynemo was used as the primary dataset for phase 1 pretraining of our Zamba2 series [of](Zyphra/Zamba2-2.7B) [models](Zyphra/Zamba2-1.2B) which perform extremely strongly on a per-token basis and are often state-of-the-art for their size, testifying to the strength of Zynemo as a pretraining dataset. |
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According to our evaluations, Zynemo is the most performant per-token open dataset available. Zynemo excels at educational and natural language reasoning content. For code performance, we reccomend mixing it with a pure code dataset such as [Starcoder](https://huggingface.co/bigcode/starcoder). |
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// TODO Ablation scores key plots |
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For more information, please see our technical blog (-/TODO LINK) |
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## How to download |
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// TODO YURY |
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## Breakdown by component |
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// TODO YURY |
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### Dataset Description |
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<!-- Provide a longer summary of what this dataset is. --> |
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- **Curated by:** Zyphra |
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- **Language(s) (NLP):** Primarily English |
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- **License:** Open Data Commons License |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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// TODO IS THIS CORRECT YURY? |
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Dataset fields: |
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- `text`: contains actual text for training |
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- `source`: component the text is coming from |
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- `filtering_features`: precomputed values of different features that were used for filtering (converted to json string) |
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- `source_other`: metadata from the source dataset (converted to json string) |
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### Source Data |
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Zynemo is comprised of four high quality open-source datasets: |
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Zyda1: https://huggingface.co/datasets/Zyphra/Zyda |
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Dolma-1.7-cc https://huggingface.co/datasets/allenai/dolma |
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DCLM-baseline: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0 |
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FineWeb-Edu-2 https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu |
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// Pie chart of composition -- YURY! |
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#### Personal and Sensitive Information |
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As a language modelling dataset, it likely contains PII which has not been filtered out of the component datasets and which may have been missed by our own filters. |
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## Bias, Risks, and Limitations |
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As a dataset comprised of open web scrapes, it is likely that it contains biased and toxic content. |
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## Licensing Information |
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We are releasing this dataset under the terms of [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). By using this dataset, you are also bound by any license agreements and terms of use of the original data sources. |
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## Citation |
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If you use our dataset to train a model, please cite us at: |
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``` |
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@misc{tokpanov2024zyda, |
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title={Zyda: A 1.3T Dataset for Open Language Modeling}, |
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author={Yury Tokpanov and Beren Millidge and Paolo Glorioso and Jonathan Pilault and Adam Ibrahim and James Whittington and Quentin Anthony}, |
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year={2024}, |
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eprint={2406.01981}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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