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Related Questions
- How does the pre-training objective of a masked language modeling task compare to a next sentence prediction task in terms of the model's ability to capture contextual understanding?
- Can you explain the difference in performance between a model fine-tuned on a specific task and one that is fine-tuned on a general language understanding task?
- How does the choice of pre-training objective affect the model's ability to generalize to out-of-domain tasks?
- What are the implications of fine-tuning a pre-trained language model on a task with a small dataset versus a large dataset?
- How does the choice of pre-training objective influence the model's ability to capture nuances in language, such as sarcasm and idioms?
- Can you discuss the trade-offs between using a model pre-trained on a large corpus and one pre-trained on a smaller, curated dataset?
- How does the fine-tuning objective impact the model's ability to adapt to different linguistic styles and registers?
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