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distilbert-amazon-sentiment
rahiqr/distilbert-amazon-sentiment
distilbert-amazon-sentiment is a text classification model from rahiqr. Use it when you need a label for a piece of text. The card lists the license as apache-2.0.
distilbert-base-uncased fine-tuned on a subset of the amazonpolarity dataset for binary POSITIVE / NEGATIVE sentiment classification of product reviews.
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At a glance
- Task
- Text Classification
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 6, 2026
- Updated
- Jul 6, 2026
- SHA
- 54bb0fe1
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Base models
Datasets
Model card
From the Hugging Face model README
DistilBERT — Amazon Product Review Sentiment
distilbert-base-uncased fine-tuned on a subset of the
amazon_polarity dataset for
binary POSITIVE / NEGATIVE sentiment classification of product reviews.
Motivation: the common off-the-shelf sentiment model is trained on movie reviews (SST-2). This model adapts to the product-review domain.
Results (1,000 held-out product reviews)
| Model | Accuracy | F1 |
|---|---|---|
| Baseline (movie-trained, SST-2) | 88.6% | 0.888 |
| This model (product reviews) | 89.7% | 0.899 |
Usage
from transformers import pipeline
clf = pipeline("sentiment-analysis", model="rahiqr/distilbert-amazon-sentiment")
clf("Arrived quickly and works perfectly!")
- Live demo: https://huggingface.co/spaces/rahiqr/review-intelligence
- Source & training code: https://github.com/rahiqraees/review-intelligence
- Task
- Text Classification
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Jul 6, 2026
- Updated
- Jul 6, 2026