What is transfer learning in NLP applications?

What is transfer learning in NLP applications?

Transfer learning in NLP involves taking a pre-trained model on one task and fine-tuning it for another, improving efficiency.

Can you give me an example of how it's used?

Sure! A common example is using BERT, which is pre-trained on a large corpus, and then fine-tuning it for sentiment analysis.

What are the benefits of using transfer learning?

The main benefits include reduced training time, improved performance on smaller datasets, and leveraging existing knowledge.

Are there any limitations to transfer learning?

Yes, limitations include potential overfitting on small datasets and the need for careful selection of the pre-trained model.