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yelp-review-quality-v2
RLau33/yelp-review-quality-v2
yelp-review-quality-v2 is a text classification model from RLau33. Use it when you need a label for a piece of text. The card lists the license as mit.
This model classifies Yelp restaurant reviews into three quality levels: - Low Quality: Short reviews (<30 characters) - Medium Quality: Average-length reviews (30-100 characters) - High Quality: Detailed reviews (100…
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At a glance
- Task
- Text Classification
- License
- mit
- Model type
- distilbert
- Access
- Public
- Created
- Dec 8, 2025
- Updated
- Dec 13, 2025
- SHA
- 411193dc
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Datasets
Model card
From the Hugging Face model README
Yelp Review Quality Classifier
This model classifies Yelp restaurant reviews into three quality levels:
- Low Quality: Short reviews (<30 characters)
- Medium Quality: Average-length reviews (30-100 characters)
- High Quality: Detailed reviews (>100 characters)
Model Details
- Base Model: DistilBERT (distilbert-base-uncased)
- Task: Multi-class text classification (3 classes)
- Training Samples: 8000
- Validation Samples: 2000
- Training Epochs: 3
Performance
- Accuracy: 0.8140
- F1 Macro: 0.4449
- F1 Weighted: 0.7853
- Precision: 0.7914
- Recall: 0.8140
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="RLau33/yelp-review-quality-v2")
result = classifier("The food was amazing and the service was excellent!")
print(result)
Training Details
- Learning Rate: 2e-05
- Batch Size: 32
- Max Length: 256 tokens
- Device: GPU (Tesla T4)
License
MIT License
- Task
- Text Classification
- Type
- distilbert
- License
- mit
- Languages
- en
- Created
- Dec 8, 2025
- Updated
- Dec 13, 2025