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Related Questions
- What is the sweet spot in transfer learning and why is it crucial for achieving optimal performance?
- How does the degree of pre-training affect the model's ability to adapt to new tasks?
- What are the implications of over- and under-tuning the learning rate on the model's performance on unseen data?
- Can you explain the concept of learning rate scheduling and its role in finding the sweet spot?
- How does the choice of pre-trained model architecture impact the performance of the model on novel tasks?
- What are some common metrics used to evaluate the sweet spot in transfer learning?
- How can the sweet spot be found experimentally, and what are some best practices for tuning hyperparameters?
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