Carbon

Carbon is an open-source Neural Network (NN) trainer for chess engines, designed primarily to support Rice's neural networks.

Features

• Learning Rate Schedulers: Utilize advanced learning rate scheduling techniques, including Step Decay and Cosine Annealing.
• Optimizers: Implement various optimization algorithms like SGD, Adam, Adamax to your preferences.
• Configuration Made Easy: Easily customize training parameters and model architecture to suit your needs.
• Visualize Training: Monitor training progress and loss using the included lossplot.py script.

Getting Started

1. Clone the Repository:

   git clone https://github.com/rafid-dev/carbon.git
   cd carbon

2. Building:

   make
   ./bin/CarbonTrainer

3. Start Training: Follow the provided instructions to start training your neural networks and improving your chess engine's evaluation capabilities. (TODO)