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Related Questions
- What are some common pitfalls to watch out for when selecting a pre-trained language model for transfer learning?
- How can overfitting occur when fine-tuning a pre-trained model, and what strategies can be employed to mitigate it?
- What are some techniques for handling class imbalance in fine-tuning a pre-trained model?
- Can you explain the difference between 'freezing' and 'fine-tuning' a pre-trained model's weights, and when would you use each approach?
- What are some ways to diagnose and address poor transfer learning performance, such as suboptimal fine-tuning, incorrect model selection, or inadequate data preparation?
- How can data augmentation be used in conjunction with transfer learning to improve fine-tuning results?
- What are some best practices for setting hyperparameters when fine-tuning a pre-trained model, and how can these be tuned for optimal performance?
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