Update README.md
#1
by
lbourdois
- opened
README.md
CHANGED
@@ -1,3 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
1 |
# <a name="introduction"></a> BERTweet: A pre-trained language model for English Tweets
|
2 |
|
3 |
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/):
|
|
|
1 |
+
---
|
2 |
+
language:
|
3 |
+
- en
|
4 |
+
---
|
5 |
+
|
6 |
# <a name="introduction"></a> BERTweet: A pre-trained language model for English Tweets
|
7 |
|
8 |
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/):
|