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roberta-postoperative-sentiment-twitter
crich011/roberta-postoperative-sentiment-twitter
roberta-postoperative-sentiment-twitter is a text classification model from crich011. Use it when you need a label for a piece of text. The card lists the license as mit.
- 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
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At a glance
- Task
- Text Classification
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026
- SHA
- f47ec7f3
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Base models
Model card
From the Hugging Face model README
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 size8(train) /16(eval), max length256
Evaluation (Holdout)
| Cohort | n | Macro F1 | Weighted F1 | Accuracy |
|---|---|---|---|---|
| Spine | 205 | 0.684667 | 0.756538 | 0.756098 |
| Arthroplasty | 191 | 0.666545 | 0.737915 | 0.769634 |
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.
- Task
- Text Classification
- Type
- roberta
- License
- mit
- Languages
- en
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026