What are the main challenges of transfer learning in NLP?

What are the main challenges of transfer learning in NLP?

Some key challenges include domain adaptation, data scarcity, and model overfitting.

Can you explain domain adaptation in more detail?

Domain adaptation refers to the ability of a model to perform well on a target domain that differs from the source domain it was trained on.

What strategies can be used to overcome these challenges?

Strategies include fine-tuning, using domain-specific data, and employing regularization techniques.

Are there any specific models that excel in transfer learning for NLP?

Yes, models like BERT, GPT, and RoBERTa have shown great success in transfer learning for various NLP tasks.