# <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](https://github.com/pytorch/fairseq/blob/master/examples/roberta/README.md)  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](https://aclanthology.org/2020.emnlp-demos.2/):

    @inproceedings{bertweet,
    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](https://github.com/VinAIResearch/BERTweet)!


{}
transformers pytorch tf jax roberta fill-mask autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

# <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:

    @inproceedings{bertweet,
    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!


# <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:

    @inproceedings{bertweet,
    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!
TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
 # <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:

    @inproceedings{bertweet,
    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!
passage: TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
# <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:

    @inproceedings{bertweet,
    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!