This repo contains resources to further pre-train and fine-tune the BERT model for twitter sentiment analysis. The code was written/adapted prior to tensorflow team lauching the "classify text with bert" guide. If you'd like a simpler method for training the BERT model for TSA, I'd recommend you to follow the mentioned guide. I plan to implement this code according to such, in the near future.
| Model | Avg Recall | F1 | Accuracy |
|---|---|---|---|
| BB_twtr | 0.681 | 0.685 | 0.658 |
| DataStories | 0.681 | 0.677 | 0.651 |
| VADER | 0.524 | 0.567 | 0.530 |
| BERT_M4 | 0.711 | 0.703 | 0.697 |