crich011/roberta-postoperative-sentiment-twitter

Postoperative Patient Sentiment

Model Details

• —Base model: cardiffnlp/twitter-roberta-base-sentiment-latest
• —Task: 3-class sentiment classification
• —Labels: negative, mixed/neutral, positive, assigned by two physicians training as orthopedic surgeons

Intended Use

Sentiment classification of postoperative patient comments for research and quality-improvement workflows.

Training

• —Fine-tuning set: 400 comments total (200 spine, 200 arthroplasty)
• —Hyperparameters: 4 epochs, learning rate 2e-5, batch size 8 (train) / 16 (eval), max length 256

Evaluation (Holdout)

Limitations

• —Developed in a specific institutional context; external generalization is not guaranteed.
• —Fine-tuning labels are based on physician rater judgement and may reflect rater variability.
• —Not intended as a standalone clinical decision tool.