CCI3.0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models

Liangdong Wang, Bo-Wen Zhang, Chengwei Wu, Hanyu Zhao, Xiaofeng Shi +5 more
10/24/2024
cs.CL

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Abstract

We present CCI3.0-HQ (https://huggingface.co/datasets/BAAI/CCI3-HQ), a high-quality 500GB subset of the Chinese Corpora Internet 3.0 (CCI3.0)(https://huggingface.co/datasets/BAAI/CCI3-Data), developed using a novel two-stage hybrid filtering pipeline that significantly enhances data quality. To evaluate its effectiveness, we trained a 0.5B parameter model from scratch on 100B tokens across various datasets, achieving superior performance on 10 benchmarks in a zero-shot setting compared to CCI3.0, SkyPile, and WanjuanV1. The high-quality filtering process effectively distills the capabilities of the Qwen2-72B-instruct model into a compact 0.5B model, attaining optimal F1 scores for Chinese web data classification. We believe this open-access dataset will facilitate broader access to high-quality language models.

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@article{wang2024ccihq,
  title  = {CCI3.0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models},
  author = {Liangdong Wang and Bo-Wen Zhang and Chengwei Wu and Hanyu Zhao and Xiaofeng Shi and Shuhao Gu and Jijie Li and Quanyue Ma and TengFei Pan and Guang Liu},
  year   = {2024},
  eprint = {2410.18505},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.18505v2}
}

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