This repository is dedicated to the development of a custom transformer model for text generation. The model utilizes the Penn Treebank dataset for training, aiming to produce coherent and meaningful text outputs.
- data_preprocessing: Contains scripts for processing raw text data, including tokenization, formatting, and preparation for model input.
- model_architecture: Includes implementations of the transformer model, such as encoding layers, attention mechanisms, and feed-forward networks.
- training_evaluation: Scripts for training the model, optimizing parameters, and evaluating performance using metrics like accuracy, loss, and perplexity.
- tests: Scripts for testing Scripts of the whole project(different levels of testing).
- Develop a transformer model from scratch based on the Penn Treebank dataset.
- Experiment with different hyperparameters to optimize text generation quality.
- Collaborate as a team using branches and pull requests to ensure smooth integration.