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license: odc-by |
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High-quality Chinese text from Common Crawl cleaned by the following steps: |
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- Documents containing more than 2% non-Chinese, non-English characters are removed. Those containing more than 30% digits or capital letters are also removed. |
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- Documents whose language is identified as non-Chinese by fasttext are removed. |
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- All text in Traditional Chinese is converted into Simplified Chinese. |
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- Low-quality documents (e.g. boilerplates, advertisements) are heuristically removed based on statistics such as average line length, portion of special characters, etc. |
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- Exact deduplication. |
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- Qwen2.5-32B-Instruct is used to generate language quality annotation (on a scale of 1-5) for 9.3M Chinese documents and 9.2M English documents, from which we sample 398K Chinese documents and 250K English documents to balance label distribution. An XLM-RoBERT-large classifier is trained with regression on these annotations. Any document receiving a score lower than 4 is removed. |
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**Details about Model Annotations** |
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On 2K samples, we compared the annotation distribution (in percentage) of Qwen2.5-Instruct 32B and 72B: |
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| Score | 1 | 2 | 3 | 4 | 5 | |
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| ----- | --- | ---- | ---- | ---- | ---- | |
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| 32B | 0.7 | 17.1 | 45.7 | 35.8 | 0.8 | |
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| 72B | 0.3 | 4.7 | 22.9 | 58.1 | 14.1 | |
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The scores between the two models have a correlation coefficient of 0.75, and manual inspection suggests that both are satisfactory. We eventually choose the 32B model for both efficiency and more balanced label distribution. |
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**Data Statistics** |
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- Number of samples: 623,807,180 |
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- Size: 1.1TB (2120 parquet files) |
