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Related Questions
- What are some common techniques used to prevent overfitting in machine learning models, particularly when fine-tuning pre-trained language models on small datasets?
- How can data augmentation techniques be applied to mitigate overfitting when working with small datasets?
- What is the role of regularization in preventing overfitting, and how can it be implemented in fine-tuning pre-trained language models?
- Can you explain the concept of early stopping and its application in preventing overfitting during fine-tuning?
- How can ensemble methods be used to mitigate overfitting when fine-tuning pre-trained language models on small datasets?
- What are some strategies for increasing the size of the training dataset, even when working with limited data?
- Can you discuss the impact of batch size and number of epochs on overfitting during fine-tuning, and provide recommendations for optimal settings?
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