transformers/model_cards/shrugging-grace/tweetclassifier
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Create README.md (#6273)
I am adding a descriptive README.md file to my recently uploaded twitter classification model: shrugging-grace/tweetclassifier.
2020-08-05 12:36:24 -04:00
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README.md Create README.md (#6273) 2020-08-05 12:36:24 -04:00

README.md

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} }