3.3 Model Checkpointing, Early Stopping, and Callbacks in Keras
Training neural networks often presents challenges like overfitting and extended training periods. To address these issues, Keras provides callbacks, powerful tools that enable real-time monitoring and control of the training process.
These callbacks automatically trigger predefined actions at specific points during training, allowing for dynamic adjustments and optimizations. Among the most valuable callbacks are model checkpointing and early stopping. Model checkpointing ensures that the best-performing model is saved throughout the training process, while early stopping intelligently terminates training when performance improvements plateau, preventing unnecessary computational ...