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Related Questions
- How does fine-tuning a pre-trained language model impact its generalizability to new domains?
- What are the key differences between fine-tuning and adaptation in the context of pre-trained models?
- Can you explain the concept of domain adaptation in machine learning and its importance in real-world applications?
- How does the choice of pre-training task and architecture affect the performance of a pre-trained model in a target domain?
- What are some common challenges encountered during the adaptation process of pre-trained models and how to address them?
- How does the amount of adaptation data impact the performance of a fine-tuned pre-trained model?
- Can you discuss the role of transfer learning in adapting pre-trained models to specific domains and its benefits?
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