# shrugging-grace/tweetclassifier | |
## Model description | |
This model classifies tweets as either relating to the Covid-19 pandemic or not. | |
## Intended uses & limitations | |
It is intended to be used on tweets commenting on UK politics, in particular those trending with the #PMQs hashtag, as this refers to weekly Prime Ministers' Questions. | |
#### How to use | |
``LABEL_0`` means that the tweet relates to Covid-19 | |
``LABEL_1`` means that the tweet does not relate to Covid-19 | |
## Training data | |
The model was trained on 1000 tweets (with the "#PMQs'), which were manually labeled by the author. The tweets were collected between May-July 2020. | |
### BibTeX entry and citation info | |
This was based on a pretrained version of BERT. | |
@article{devlin2018bert, | |
title={Bert: Pre-training of deep bidirectional transformers for language understanding}, | |
author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina}, | |
journal={arXiv preprint arXiv:1810.04805}, | |
year={2018} | |
} | |