How can I optimize my NLP model for better performance?

How can I optimize my NLP model for better performance?

To optimize your NLP model, consider techniques like hyperparameter tuning, data augmentation, and model pruning.

What is hyperparameter tuning and how do I do it?

Hyperparameter tuning involves adjusting the parameters that govern the training process. You can use methods like grid search or random search.

Can you explain data augmentation in the context of NLP?

Data augmentation in NLP involves creating synthetic data by paraphrasing, synonym replacement, or back-translation to enhance model training.

What are some common pitfalls to avoid during optimization?

Common pitfalls include overfitting, neglecting validation data, and not monitoring performance metrics effectively.