bertweet-base /
# <a name="introduction"></a> BERTweet: A pre-trained language model for English Tweets
BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the [RoBERTa]( pre-training procedure. The corpus used to pre-train BERTweet consists of 850M English Tweets (16B word tokens ~ 80GB), containing 845M Tweets streamed from 01/2012 to 08/2019 and 5M Tweets related to the **COVID-19** pandemic. The general architecture and experimental results of BERTweet can be found in our [paper](
title = {{BERTweet: A pre-trained language model for English Tweets}},
author = {Dat Quoc Nguyen and Thanh Vu and Anh Tuan Nguyen},
booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
pages = {9--14},
year = {2020}
**Please CITE** our paper when BERTweet is used to help produce published results or is incorporated into other software.
For further information or requests, please go to [BERTweet's homepage](!
### Main results
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<img width="275" alt="postagging" src="" />
<img width="275" alt="ner" src="" />
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<img width="275" alt="sentiment" src="" />
<img width="275" alt="irony" src="" />