readme: ---
  language: en
  tags:
  - transfer-learning
  - bert
  - hatespeech
  - covid19
  license: "mit"
  datasets:
  - COVID-HATE
  metrics:
  - f1-score
  ---
  Since the start of the COVID-19 pandemic, there has been a widespread increase in the amount of hate-speech being propagated online against the Asian community. This project builds upon and explores the work of He et al. Their COVID-HATE dataset contains 206 million tweets focused around anti-Asian hate speech. Using tweet data from before the COVID-19 pandemic, as well as the COVID-HATE dataset from He et al, we performed transfer learning. We tested several different models, including BERT, RoBERTa, LSTM, and BERT-CNN.
  Some of these models hindered the performance of He et al’s model, while others improved it.
  
  