Our new X account is live! Follow @wizwand_team for updates
WorkDL logo mark

BERTweet: A pre-trained language model for English Tweets

About

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

Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen• 2020

Related benchmarks

TaskDatasetResultRank
Semantic Textual SimilaritySTS tasks (STS12, STS13, STS14, STS15, STS16, STS-B, SICK-R) various (test)
STS12 Score29.2
393
Named Entity RecognitionWnut 2017
F1 Score56.5
79
Named Entity RecognitionWNUT 2017 (test)
F1 Score57.1
63
Part-of-Speech TaggingTWEEBANK V2 (test)
Accuracy95.38
38
Named Entity RecognitionWNUT 2016
F1 Score52.1
28
Named Entity RecognitionWNUT 2016 (test)
F1 Score52.1
26
Transfer LearningSentEval Transfer tasks (test)
MR79.58
23
POS TaggingRitter11 T-POS (test)
Accuracy90.1
20
POS TaggingARK-Twitter (test)
Accuracy94.1
18
Tweet ClassificationTweetEval 1.0 (test)
Emoji (M-F1)33.4
18
Showing 10 of 25 rows

Other info

Code

Follow for update