What are the best practices for transfer learning in NLP?

What are the best practices for transfer learning in NLP?

Some best practices include selecting the right pre-trained model, fine-tuning on your specific dataset, and using appropriate evaluation metrics.

How do I choose the right pre-trained model?

Consider the task at hand, the size of your dataset, and the model's architecture. Popular models include BERT, GPT, and RoBERTa.

What is fine-tuning and why is it important?

Fine-tuning adjusts the pre-trained model on your specific dataset, improving its performance for your particular task.

Can you recommend some evaluation metrics for NLP tasks?

Sure! Common metrics include accuracy, F1 score, precision, recall, and BLEU score for translation tasks.