What is transfer learning in natural language processing?
Transfer learning in NLP is a technique where a model trained on one task is adapted to perform another task, leveraging knowledge from the first.
Can you give me an example of how it's used?
Sure! A common example is using a model trained on a large corpus for sentiment analysis and then fine-tuning it on a smaller dataset for a specific domain.
What are the benefits of using transfer learning?
The main benefits include reduced training time, improved performance on smaller datasets, and the ability to leverage large pre-trained models.
Are there any popular models that utilize transfer learning?
Yes, models like BERT, GPT, and RoBERTa are popular examples that utilize transfer learning in NLP tasks.
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