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Related Questions
- Can you describe a scenario where a pre-trained language model was fine-tuned on a specific task, such as named entity recognition, to improve performance on a related but distinct task, like sentiment analysis?
- How do task-specific objectives, like masked language modeling, impact the performance of a pre-trained model when adapting to a new domain, such as from news articles to social media posts?
- What are some examples of pre-training objectives that have been successfully applied to domain adaptation in areas like question answering, text classification, or machine translation?
- Can you provide an example of a pre-trained model being fine-tuned on a specific dataset to adapt to a new domain, and how the task-specific objective influenced the results?
- How do task-specific objectives, like next sentence prediction, affect the performance of a pre-trained model when adapting to a new domain, such as from product reviews to customer feedback?
- What are some best practices for selecting task-specific objectives during pre-training to improve domain adaptation performance in real-world scenarios?
- Can you describe a scenario where a pre-trained model was pre-trained on a diverse set of tasks, and how the task-specific objectives influenced the model's ability to adapt to a new domain?
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