RoBERTa Amazon Reviews Sentiment Classifier
Fine-tuned version of roberta-base for 3-class sentiment classification (negative / neutral / positive) on Amazon product reviews.
Model Details
- Base model: roberta-base
- Task: Sentiment classification (3-class)
- Dataset: Amazon product reviews (balanced sample)
- Language: English
- Repository: amazon-review-classifier-roberta-sentiment-finetuning
Performance
Evaluated on a held-out test set of 1,086 reviews:
| Class | Precision | Recall | F1-Score | Support |
|---|---|---|---|---|
| Negative | 0.84 | 0.85 | 0.85 | 361 |
| Neutral | 0.77 | 0.71 | 0.74 | 350 |
| Positive | 0.86 | 0.91 | 0.89 | 375 |
| Macro avg | 0.82 | 0.82 | 0.82 | 1086 |
| Weighted avg | 0.82 | 0.83 | 0.83 | 1086 |
Overall accuracy: 83%
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="c-ram/roberta-amazon-reviews-sentiment")
classifier("This product exceeded my expectations!")
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Model tree for c-ram/roberta-amazon-reviews-sentiment
Base model
FacebookAI/roberta-base