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Related Questions
- What are the key differences between fine-tuning and training a language model from scratch in the context of text summarization and information retrieval tasks?
- How does the choice of fine-tuning objective function affect the performance of a pre-trained language model in summarization and retrieval tasks?
- Can you explain the concept of 'transfer learning' in the context of fine-tuning a pre-trained language model for text summarization and information retrieval tasks?
- What are some common techniques used to adapt a pre-trained language model to a specific domain or task, such as text summarization and information retrieval?
- How does fine-tuning a pre-trained language model impact its ability to generalize to out-of-domain data in text summarization and information retrieval tasks?
- What are some common evaluation metrics used to assess the performance of a fine-tuned language model in text summarization and information retrieval tasks?
- Can you provide examples of successful applications of fine-tuning pre-trained language models in text summarization and information retrieval tasks, such as in the news industry or research settings?
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