BAAI/IndustryCorpus_automobile

该数据集是为了解决行业模型训练中数据量不足、质量低和缺乏领域专业知识的问题而构建的。通过使用22个行业数据处理算子，从超过100TB的开源数据集中清洗和过滤出3.4TB的高质量多行业分类中英文预训练数据集。数据集包括1TB的中文数据和2.4TB的英文数据，并对中文数据进行了12种类型的标注。此外，数据集在医疗行业示范模型上进行了预训练、SFT和DPO训练，结果显示客观性能提升了20%，主观胜率为82%。数据集涵盖了18个行业类别，并提供了基于规则和模型的过滤方法，以及数据去重处理。最后，为了方便用户使用，数据集被分割为18个行业的子数据集，当前提供的是汽车行业的子数据集。

The dataset contains 3.4TB of high-quality multi-industry classified Chinese and English pre-training data, which has been cleaned and filtered through 22 industry data processing operators, resulting in 1TB of Chinese data and 2.4TB of English data. The dataset covers 18 industry categories and annotates Chinese data with 12 types of labels, including alphanumeric ratio, average line length, language confidence score, maximum line length, and perplexity. Additionally, model validation was conducted, showing a 20% performance improvement on a medical industry demonstration model.