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--- |
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license: cc-by-4.0 |
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language: |
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- zh |
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tags: |
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- text-generation |
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- e-commerce advertise |
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pretty_name: AdvertiseGen |
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task_categories: |
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- text-generation |
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--- |
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# Dataset Card for Alpaca-zh |
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- **formal url:** https://www.luge.ai/#/luge/dataDetail?id=9 |
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## Dataset Description |
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数据集介绍 |
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AdvertiseGen是电商广告文案生成数据集。 |
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AdvertiseGen以商品网页的标签与文案的信息对应关系为基础构造，是典型的开放式生成任务，在模型基于key-value输入生成开放式文案时，与输入信息的事实一致性需要得到重点关注。 |
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- 任务描述：给定商品信息的关键词和属性列表kv-list，生成适合该商品的广告文案adv； |
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- 数据规模：训练集114k，验证集1k，测试集3k； |
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- 数据来源：清华大学CoAI小组； |
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### Supported Tasks and Leaderboards |
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The Alpaca dataset designed for instruction training pretrained language models. |
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### Languages |
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The data in AdvertiseGen are in Chinese. |
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## Dataset Structure |
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### Data Instances |
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An example of "train" looks as follows: |
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```json |
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{ |
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"content": "类型#上衣*材质#牛仔布*颜色#白色*风格#简约*图案#刺绣*衣样式#外套*衣款式#破洞", |
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"summary": "简约而不简单的牛仔外套，白色的衣身十分百搭。衣身多处有做旧破洞设计，打破单调乏味，增加一丝造型看点。衣身后背处有趣味刺绣装饰，丰富层次感，彰显别样时尚。" |
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} |
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``` |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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The `alpaca` data is generated by a language model (`text-davinci-003`) and inevitably contains some errors or biases. We encourage users to use this data with caution and propose new methods to filter or improve the imperfections. |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Citation Information |
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数据集引用 |
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如在学术论文中使用本数据集，请添加相关引用说明，具体如下： |
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``` |
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Shao, Zhihong, et al. "Long and Diverse Text Generation with Planning-based Hierarchical Variational Model." Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019. |
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``` |
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### Contributions |
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[More Information Needed] |
