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Related Questions
- How does the diversity of the pre-training dataset impact a model's ability to generalize to new tasks?
- What are the effects of increasing the size of the pre-training dataset on a model's adaptability to new tasks?
- Can a model trained on a high-quality pre-training dataset but small in size adapt better to new tasks than a model trained on a large but low-quality pre-training dataset?
- How does the presence of noisy or irrelevant data in the pre-training dataset affect a model's ability to adapt to new tasks?
- What role does the quality of the pre-training dataset play in a model's ability to learn transferable representations?
- Can a model trained on a pre-training dataset with a narrow scope but high quality adapt better to new tasks than a model trained on a pre-training dataset with a broad scope but low quality?
- How does the level of domain adaptation required for a new task impact the importance of a high-quality pre-training dataset?
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