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Related Questions
- What are the primary goals of fine-tuning a pre-trained model versus retraining it from scratch?
- How do the architectures of pre-trained models impact the fine-tuning process?
- What are the key considerations for selecting the optimal learning rate and batch size during fine-tuning?
- Can you explain the concept of 'feature extraction' in the context of fine-tuning a pre-trained model?
- How does the choice of pre-trained model architecture influence the performance of the fine-tuned model?
- What are the differences in hyperparameter tuning between fine-tuning and retraining a model from scratch?
- Can you provide examples of tasks where fine-tuning a pre-trained model is more effective than retraining from scratch?
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