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Related Questions
- What are the key differences in evaluation metrics for fine-tuning a pre-trained model versus training a model from scratch?
- How do evaluation metrics change when adapting a pre-trained model to a new domain?
- What are some evaluation metrics that are more suitable for models adapted to a new domain versus those trained from scratch?
- Can you explain the concept of 'domain adaptation' in the context of machine learning and its impact on evaluation metrics?
- How does the choice of evaluation metric affect the performance of models adapted to a new domain versus those trained from scratch?
- What are some common pitfalls when evaluating models adapted to a new domain versus those trained from scratch?
- How do model interpretability techniques differ for models adapted to a new domain versus those trained from scratch?
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