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Related Questions
- How does the quality of pre-training data affect fine-tuning performance for language models?
- What are the key differences between supervised and unsupervised pre-training in terms of fine-tuning needs?
- Can semi-supervised pre-training alleviate the need for large labeled datasets during fine-tuning?
- How does the level of supervision during pre-training impact the required number of fine-tuning epochs?
- In what scenarios is unsupervised pre-training more effective for fine-tuning compared to supervised pre-training?
- What are some best practices for selecting the most effective pre-training approach to reduce fine-tuning requirements?
- How can understanding the pre-training phase impact the design of subsequent fine-tuning tasks to improve overall model performance?
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