Abstract
We present BERTweet, the first public large-scale pre-trained language model for English Tweets. Our BERTweet, having the same architecture as BERT-base (Devlin et al., 2019), is trained using the RoBERTa pre-training procedure (Liu et al., 2019). Experiments show that BERTweet outperforms strong baselines RoBERTa-base and XLM-R-base (Conneau et al., 2020), producing better performance results than the previous state-of-the-art models on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification. We release BERTweet under the MIT License to facilitate future research and applications on Tweet data. Our BERTweet is available at https://github.com/VinAIResearch/BERTweet- Anthology ID:
- 2020.emnlp-demos.2
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- October
- Year:
- 2020
- Address:
- Online
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 9–14
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-demos.2
- DOI:
- 10.18653/v1/2020.emnlp-demos.2
- Cite (ACL):
- Dat Quoc Nguyen, Thanh Vu, and Anh Tuan Nguyen. 2020. BERTweet: A pre-trained language model for English Tweets. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 9–14, Online. Association for Computational Linguistics.
- Cite (Informal):
- BERTweet: A pre-trained language model for English Tweets (Nguyen et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.emnlp-demos.2.pdf
- Code
- VinAIResearch/BERTweet + additional community code
- Data
- Tweebank, TweetEval, WNUT 2016 NER, WNUT 2017