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Related Questions
- What are the common pitfalls to avoid when fine-tuning a large language model for a specific task?
- How does the choice of pre-training data and model architecture impact fine-tuning performance?
- What are the key considerations for selecting the optimal hyperparameters for fine-tuning a large language model?
- Can you explain the concept of catastrophic forgetting and how it affects fine-tuning a large language model?
- How does the quality of the task-specific data impact the performance of the fine-tuned model?
- What are the best practices for regularizing a large language model during fine-tuning to prevent overfitting?
- How does the level of task-specific supervision impact the performance of the fine-tuned model compared to self-supervised learning?
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