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Related Questions
- What are the common fine-tuning techniques used in pre-trained models, such as transfer learning and task-specific training?
- How do domain-specific adaptations, such as lexicalization and specialization, enhance model performance in a particular domain?
- What is the impact of varying the fine-tuning parameters, such as epoch number and batch size, on the model's convergence and accuracy?
- Can you explain how multitask learning and hierarchical fine-tuning can help a model adapt to a new domain?
- What are some common domain adaptation techniques used to mitigate the effects of domain mismatch during fine-tuning?
- How can attention mechanisms and other transferable components be used to leverage knowledge from pre-trained models?
- What are the trade-offs between fine-tuning the entire model and only a few layers when adapting a pre-trained model to a new domain?
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