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Fine-tune BERT for Extractive Summarization
March 25, 2019 · Entered Twilight · 🏛 arXiv.org
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Repo contents: LICENSE, README.md, bert_config_uncased_base.json, bert_data, json_data, logs, models, raw_data, results, src, urls
Authors
Yang Liu
arXiv ID
1903.10318
Category
cs.CL: Computation & Language
Citations
521
Venue
arXiv.org
Repository
https://github.com/nlpyang/BertSum
⭐ 1504
Last Checked
1 month ago
Abstract
BERT, a pre-trained Transformer model, has achieved ground-breaking performance on multiple NLP tasks. In this paper, we describe BERTSUM, a simple variant of BERT, for extractive summarization. Our system is the state of the art on the CNN/Dailymail dataset, outperforming the previous best-performed system by 1.65 on ROUGE-L. The codes to reproduce our results are available at https://github.com/nlpyang/BertSum
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