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fastNLP/reproduction/Summarization
Danqing Wang 610791ad78 update Readme.md 5 years ago
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README.md

Summarization

Extractive Summarization

Models

FastNLP中实现的模型包括：

  1. Get To The Point: Summarization with Pointer-Generator Networks (See et al. 2017)
  2. 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
    • NYT
    • NYT50
  • 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

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一款轻量级的自然语言处理（NLP）工具包，目标是减少用户项目中的工程型代码，例如数据处理循环、训练循环、多卡运行等

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