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Related Questions
- What are the advantages of training a model from scratch compared to fine-tuning a pre-trained model?
- How does the size of a dataset impact the decision to train a model from scratch versus fine-tuning?
- Can you provide examples of scenarios where training from scratch is more suitable than fine-tuning?
- What are the potential drawbacks of training a model from scratch, especially for small datasets?
- How does the concept of 'domain adaptation' relate to fine-tuning pre-trained models versus training from scratch?
- Are there any specific techniques or algorithms that are more suitable for training from scratch versus fine-tuning?
- Can you discuss the role of transfer learning in fine-tuning pre-trained models, and how it compares to training from scratch?
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