Fast decay is a training strategy that rapidly decreases the learning rate during model training. For large language models, it can help reduce overfitting and improve generalization after initial learning.
A training technique to improve the performance of LLMs. Fast decay involves rapidly decreasing the learning rate during training. This strategy helps prevent the model from overfitting to the training data, and improves generalization.