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Related Questions
- What is the primary goal of task-specific fine-tuning in the context of pre-trained language models?
- How does fine-tuning a pre-trained model on a specific task affect its ability to generalize to similar tasks?
- What are some common challenges that pre-trained models face when adapting to out-of-distribution data, and how can task-specific fine-tuning address these challenges?
- Can you explain the difference between task-specific fine-tuning and domain adaptation in the context of pre-trained models?
- How does the quality of the fine-tuning dataset impact the performance of pre-trained models on out-of-distribution data?
- What are some strategies for selecting the optimal fine-tuning dataset for a specific task, given a pre-trained model?
- How does task-specific fine-tuning affect the interpretability of pre-trained models, particularly in terms of understanding their decision-making processes?
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