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Related Questions
- What are the primary factors that contribute to overfitting in deep learning models?
- How do pre-trained models handle overfitting compared to models trained from scratch?
- What are the trade-offs between fine-tuning a pre-trained model and training a model from scratch in terms of generalization and adaptability?
- Can you explain the concept of catastrophic forgetting in the context of fine-tuning pre-trained models?
- What techniques can be used to mitigate overfitting in both fine-tuning and training from scratch?
- How does the choice of pre-training task and dataset impact the trade-offs between fine-tuning and training from scratch?
- What are some common scenarios where training a model from scratch might be preferred over fine-tuning a pre-trained model?
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