Summarization
Models
FastNLP中实现的模型包括:
- Get To The Point: Summarization with Pointer-Generator Networks (See et al. 2017)
- Searching for Effective Neural Extractive Summarization What Works and What's Next (Zhong et al. 2019)
Dataset
这里提供的摘要任务数据集包括:
- CNN/DailyMail
- Newsroom
- The New York Times Annotated Corpus
- DUC
- 2002 Task4
- 2003/2004 Task1
- arXiv
- PubMed
其中公开数据集(CNN/DailyMail, Newsroom, arXiv, PubMed)预处理之后的下载地址:
未公开数据集(NYT, NYT50, DUC)数据处理部分脚本放置于data文件夹
Dataset_loader
- SummarizationLoader: 用于读取处理好的jsonl格式数据集,返回以下field
- text: 文章正文
- summary: 摘要
- domain: 可选,文章发布网站
- tag: 可选,文章内容标签
- labels: 抽取式句子标签
Performance and Hyperparameters
| Model | ROUGE-1 | ROUGE-2 | ROUGE-L | Paper |
See
Abstractive Summarization
Still in Progress...