Ararest Arabic Restaurant Reviews Sentiment Analysis
This is an Arabic restaurant review sentiment analysis model fine-tuned based on AraBERT, capable of classifying reviews as positive or negative.
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Release Time : 1/22/2025
Model Overview
This model is specifically designed for analyzing the sentiment tendencies of Arabic restaurant reviews, fine-tuned on aubmindlab/bert-base-arabertv02, suitable for sentiment analysis applications in the food and beverage industry.
Model Features
Real Data Training
Trained using a real dataset of Arabic restaurant reviews to ensure reliability in practical applications.
Balanced Dataset
The training data includes 2418 positive reviews and 2418 negative reviews, ensuring balanced recognition capabilities for both sentiment types.
High Performance
Achieves 87.4% accuracy and an F1 score of 85.81% on the test set, demonstrating excellent performance.
Full Fine-tuning
Employs full model fine-tuning rather than adapter methods to maximize model performance.
Model Capabilities
Arabic Text Classification
Sentiment Analysis
Restaurant Review Rating Prediction
Use Cases
Food and Beverage Industry
Restaurant Review Sentiment Analysis
Automatically analyzes whether customer reviews of restaurants are positive or negative.
87.4% accuracy, helping restaurants quickly understand customer feedback.
Service Quality Monitoring
Monitors service quality trends by analyzing sentiment changes in reviews.
Helps identify service issues promptly and make improvements.
Market Research
Competitive Analysis
Compares customer satisfaction across different restaurants.
Provides quantitative data to support business decisions.
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