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Related Questions
- What is the main difference between fine-tuning and retraining a model from scratch?
- How does fine-tuning a pre-trained model affect its performance and accuracy?
- Under what circumstances is fine-tuning a model more suitable than retraining from scratch?
- Can you provide an example of when fine-tuning a pre-trained model would be preferred over retraining from scratch?
- How does fine-tuning a model impact its computational requirements compared to retraining from scratch?
- What are some potential drawbacks of fine-tuning a pre-trained model?
- In what scenarios would retraining a model from scratch be preferred over fine-tuning a pre-trained model?
- How does fine-tuning a model allow for domain adaptation and zero-shot learning?
- Can you explain the process of fine-tuning a pre-trained model on a new dataset?
- What are some common hyperparameters to adjust when fine-tuning a pre-trained model?
- How does fine-tuning a model enable transfer learning between tasks and domains?
- What are some strategies for selecting the optimal hyperparameters for fine-tuning a pre-trained model?
- Can you describe the concept of 'model distillation' in the context of fine-tuning a pre-trained model?
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