Fine-Tuning Sparse Models

Fine-tuning sparse models requires a different approach compared to dense models, as using standard hyperparameters can negate pre-training benefits. Increasing noise during fine-tuning can help mitigate overfitting due to the larger modeling capacity of sparse models. Additionally, maintaining an optimal balance between parameters and computation is crucial for effective model performance.