Abduuu/ArabReview-Sentiment

🍽️ Arabic Restaurant Review Sentiment Analysis 🚀

Model Is Under Development

📌 Overview

This project fine-tunes a transformer-based model to analyze sentiment in Arabic restaurant reviews.
We utilized Hugging Face’s model training pipeline and deployed the final model as an interactive Gradio web app.

📥 Data Collection

The dataset used for fine-tuning was sourced from Hugging Face Datasets, specifically:
📂 Arabic Restaurant Reviews Dataset
It contains restaurant reviews in Arabic labeled with sentiment polarity.

🔄 Data Preparation

• Cleaning & Normalization:
  • Removed non-Arabic text, special characters, and extra spaces.
  • Normalized Arabic characters (e.g., إ, أ, آ → ا, ة → ه).
  • Downsampled positive reviews to balance the dataset.
• Tokenization:
  • Used AraBERT tokenizer for efficient text processing.
• Train-Test Split:
  • 80% Training | 20% Testing.

🏋️ Fine-Tuning & Results

The model was fine-tuned using Hugging Face Transformers on a dataset of restaurant reviews.

📊 Evaluation Metrics

Metric	Score
Eval Loss	0.5665
Accuracy	70.37%
Precision	70.36%
Recall	70.37%
F1-score	69.75%
Eval Runtime	11.5 sec

⚙️ Training Parameters

training_args = TrainingArguments(
    output_dir="./results",
    evaluation_strategy="steps",
    eval_steps=200,
    per_device_train_batch_size=2,
    per_device_eval_batch_size=2,
    num_train_epochs=5,
    weight_decay=0.01,
    learning_rate=3e-5,
    logging_steps=100,
    fp16=True,
    report_to="none"
)