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Related Questions
- What are the key differences between regularization and early stopping techniques in preventing overfitting in language models?
- How does cross-validation affect the performance of a fine-tuned language model and what are its implications?
- What role does data augmentation play in reducing overfitting in language models and how is it implemented?
- Can ensemble methods, such as bagging or boosting, help mitigate underfitting and overfitting in language models?
- How do hyperparameter tuning and gradient clipping techniques address underfitting and overfitting in language models?
- What are the advantages and limitations of using pruning and quantization techniques to reduce overfitting in language models?
- How do knowledge distillation and teacher-student learning methods improve the generalizability of fine-tuned language models and prevent overfitting?
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