mabroukaymen1/tunisian_english

# Tunisian to English AI Translation AI model to translate Tunisian dialect to English language. ## Description This project implements an AI-based translation system for converting Tunisian Arabic dialect to English. ## Setup [Project setup instructions will go here] - Gradient checkpointing (reduce memory by 30-40%) - Mixed-precision training (FP16/FP32 hybrid) - 8-bit quantization (optional for low-memory devices) - **Advanced Monitoring**: - Real-time training dashboard - TensorBoard integration - GPU memory profiling - Translation quality sampling ### Technical Innovations - **Dynamic Batch Processing**: Automaticallly adjusts batch size based on available memory - **Curriculum Learning**: Progressive difficulty scheduling - **Noise Injection**: Improves model robustness - **Attention Visualization**: Interpret model decisions ## 🧠 Model Architecture ### mBART-50 Foundation The system builds on mBART-50, a multilingual sequence-to-sequence transformer pretrained on 50 languages. Key specifications: | Parameter | Value | |--------------------|---------------------| | Architecture | Transformer (seq2seq) | | Layers | 12 encoder, 12 decoder | | Attention Heads | 16 | | Hidden Size | 1024 | | Parameters | 610M | | Pretraining | 50 languages | ### Custom Modifications 1. **Dialect-Specific Tokenization**: - Extended vocabulary for Tunisian Arabic - Special tokens for code-switching markers - Subword regularization for dialectal variations 2. **Memory Optimization**: ```python # Example of gradient checkpointing implementation model.config.use_cache = False # Disable cache for checkpointing model.gradient_checkpointing_enable() ``` 3. **Attention Mechanisms**: - Multi-head attention with relative position bias - Learned attention temperature scaling ## 📊 Performance Metrics | Metric | Validation Score | Test Score | |------ …