Create README.md

README.md

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+---
+language:
+- is
+---
+README
+
+Overview
+
+This project implements a language translation model using GPT-2, capable of translating between Icelandic and English. The pipeline includes data preprocessing, model training, evaluation, and an interactive user interface for translations.
+
+Features
+
+Text Preprocessing: Tokenization and padding for uniform input size.
+
+Model Training: Training a GPT-2 model on paired Icelandic-English sentences.
+
+Evaluation: Perplexity-based validation of model performance.
+
+Interactive Interface: An easy-to-use widget for real-time translations.
+
+Installation
+
+Prerequisites
+
+Ensure you have the following installed:
+
+Python (>= 3.8)
+
+PyTorch
+
+Transformers library by Hugging Face
+
+ipywidgets (for the translation interface)
+
+Steps
+
+Clone the repository:
+
+git clone <repository_url>
+cd <repository_name>
+
+Install the required libraries:
+
+pip install -r requirements.txt
+
+Ensure GPU availability for faster training (optional but recommended).
+
+Usage
+
+Training the Model
+
+Prepare your dataset with English-Icelandic sentence pairs.
+
+Run the script to preprocess the data and train the model:
+
+python train_model.py
+
+The trained model and tokenizer will be saved in the ./trained_gpt2 directory.
+
+Evaluating the Model
+
+Evaluate the trained model using validation data:
+
+python evaluate_model.py
+
+The script computes perplexity to measure model performance.
+
+Running the Interactive Interface
+
+Launch a Jupyter Notebook or Jupyter Lab.
+
+Open the file interactive_translation.ipynb.
+
+Enter a sentence in English or Icelandic, and view the translation in real-time.
+
+File Structure
+
+train_model.py: Contains code for data preprocessing, model training, and saving.
+
+evaluate_model.py: Evaluates model performance using perplexity.
+
+interactive_translation.ipynb: Interactive interface for testing translations.
+
+requirements.txt: List of required Python packages.
+
+trained_gpt2/: Directory to save trained model and tokenizer.
+
+Key Parameters
+
+Max Length: Maximum token length for inputs (default: 128).
+
+Learning Rate: .
+
+Batch Size: 4 (both training and validation).
+
+Epochs: 10.
+
+Beam Search: Used for generating translations, with a beam size of 5.
+
+Future Improvements
+
+Expand dataset to include additional language pairs.
+
+Optimize the model for faster inference.
+
+Integrate the application into a web-based interface.
+
+Acknowledgements
+
+Hugging Face for providing the GPT-2 model and libraries.
+
+PyTorch for enabling seamless implementation and training.
+
+License
+
+This project is licensed under the MIT License. See the LICENSE file for details.