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| title: Arabic Sentiment Analysis | |
| emoji: 🧠 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 6.5.1 | |
| python_version: '3.10' | |
| app_file: app.py | |
| pinned: false | |
| # Arabic Sentiment Analysis with AraBERT | |
| This project presents an **Arabic Sentiment Analysis system** based on a fine-tuned version of **AraBERT**. | |
| The model predicts the sentiment of Arabic text as **Positive** or **Negative**, along with a confidence score. | |
| The application is deployed using **Gradio** on **Hugging Face Spaces**, providing an interactive web interface for real-time inference. | |
| --- | |
| ## 🚀 Demo | |
| Simply enter an Arabic text in the input box and the model will return: | |
| - **Sentiment**: Positive / Negative | |
| - **Confidence**: Prediction confidence in percentage (%) | |
| --- | |
| ## 🧠 Model | |
| - **Base model**: `aubmindlab/bert-base-arabertv02` | |
| - **Task**: Binary Sentiment Classification | |
| - **Labels**: | |
| - `0` → Negative | |
| - `1` → Positive | |
| - **Preprocessing**: AraBERT text normalization and cleaning | |
| --- | |
| ## 📊 Dataset | |
| - **Dataset**: Arabic Sentiment Analysis dataset | |
| - **Classes**: | |
| - Negative (0): 1,784 samples | |
| - Positive (1): 2,332 samples | |
| - **Domain**: Arabic tweets and short texts | |
| > ⚠️ The dataset is **not included** in this repository, as it is used only during training. | |
| --- | |
| ## ⚙️ Training Details | |
| - Fine-tuning performed on **Google Colab** | |
| - **Early Stopping** used to prevent overfitting | |
| - **Checkpointing** enabled during training | |
| - Final model selected based on validation performance | |
| --- | |
| ## 🖥️ Deployment | |
| - **Framework**: Gradio | |
| - **Platform**: Hugging Face Spaces | |
| - **Hardware**: CPU (Zero GPU) | |
| - **Inference**: Real-time | |
| --- | |
| ## 📦 Project Structure |