BERT Model Project

This project implements a BERT-based model from scratch for natural language processing tasks. It includes components for data loading, model definition, training, and evaluation.

bert-model-project
├── src
│   ├── data
│   │   └── data_loader.py       # Handles loading and preprocessing the dataset
│   ├── model
│   │   └── bert_model.py         # Implements the BERT architecture
│   ├── training
│   │   └── train.py              # Orchestrates the training process
│   ├── evaluation
│   │   └── evaluate.py           # Evaluates the trained model
│   └── utils
│       └── utils.py              # Contains utility functions
├── requirements.txt               # Lists project dependencies
├── setup.py                       # Configuration file for packaging
└── README.md                      # Documentation for the project

1. Clone the repository:

   git clone <repository-url>
   cd bert-model-project
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Run the training script:

   python src/training/train.py
   

• Use DataLoader from src/data/data_loader.py to load and preprocess your dataset.
• Define your model using BertModel from src/model/bert_model.py.
• Train your model using the train_model function in src/training/train.py.
• Evaluate your model with the evaluate_model function in src/evaluation/evaluate.py.

• DataLoader: Loads and preprocesses the dataset.
• BertModel: Implements the BERT architecture for NLP tasks.
• Training: Contains logic for training the model.
• Evaluation: Evaluates the model's performance on validation data.
• Utilities: Provides helper functions for model saving and loading.

This project is licensed under the MIT License.