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charlottegl/
CantoSent-Llama3.1-8B-OpenRice

Name: CantoSent-Llama3.1-8B-OpenRice
Rating: 2.5 (12 reviews)

text-generation-inference

endpoints_compatible

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🐉 CantoSent-Llama3.1-8B-OpenRice

📌 Model Summary

CantoSent-Llama3.1-8B-OpenRice is a fine-tuned version of lordjia/Llama-3.1-Cantonese-8B-Instruct, designed for Cantonese sentiment classification on OpenRice restaurant reviews.
The task is a binary classification: positive (3–5 stars) vs negative (1–2 stars).
This model is optimized for research and academic use in low-resource language sentiment analysis, especially in the domain of Cantonese NLP.

🧠 Model Details

Base Model: lordjia/Llama-3.1-Cantonese-8B-Instruct
Fine-tuned by: Geng Le
Language: Cantonese (Chinese Traditional + Emoji support)
Task: Binary Sentiment Classification
Dataset: Cantonese OpenRice Reviews
Emoji Handling: Retain emojis (with-emojis version)

📊 Evaluation Results

Metric	Score
Accuracy	91.23%
Precision	98.95%
Recall	91.40%
F1-score	95.03%

Evaluated on a held-out test set (10% of 60,000 examples).

📁 Dataset Information

Source: OpenRice review dataset from a public GitHub repository
Size: 60,000 examples
Labels:
- Positive = 3–5 stars
- Negative = 1–2 stars
Split:
- 90% training, 10% testing
Emoji Handling: Version without emojis used in this training

🎯 Use Cases

Cantonese sentiment analysis for food review systems
Research in low-resource or regional dialect NLP
Benchmarking multilingual/multi-dialect LLMs
Educational or academic projects

🔬 Intended Use & Limitations

This model is research-priority. It is intended for:

Academic research
Model benchmarking
Sentiment classification on food/dining-related Cantonese text

Limitations:

Domain-specific (trained only on restaurant reviews)
Performance may degrade on informal or non-Cantonese text

📄 License

This model is fine-tuned from [lordjia/Llama-3.1-Cantonese-8B-Instruct], which follows the [Meta Llama 3.1 Community License Agreement] The dataset is derived from a public GitHub repository for academic purposes.
Please use this model in accordance with the license terms of the base model and dataset.

✨ Citation

If you use this model in your research or applications, please consider citing:

@misc{cantosent2025,
  author = {Geng Le},
  title = {CantoSent-Llama3.1-8B-OpenRice: A Cantonese Sentiment Classifier},
  year = {2025},
  howpublished = {\url{https://huggingface.co/charlottegl/CantoSent-Llama3.1-8B-OpenRice}},
  note = {Fine-tuned from LLaMA-3 for sentiment analysis on OpenRice reviews}
}

📬 Contact

For questions or collaborations, feel free to reach out via Hugging Face or GitHub.