We used RoBERTa to do the sentiment analysis task.
train.py preprocesses the data, trains the model, and generates the prediction. The model/ and data/ directories are empty because it is where the dataset and the saved model should be in.
I referred to Chris McCormick's guide of fine-tuning BERT and it helped me with constructing the training loop.