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Related Questions
- What are some common techniques for regularizing language models to prevent overfitting?
- How can the size of the pre-training dataset affect the model's ability to generalize to new tasks?
- What is the relationship between pre-training on a large dataset and the model's tendency to memorize rather than learn?
- Can you explain the concept of 'pre-training for pre-training's sake' and how it relates to the trade-off between benefits and drawbacks?
- What are some methods for evaluating the performance of a pre-trained model on a specific task to determine if it's worth fine-tuning?
- How can the use of transfer learning and fine-tuning affect the trade-off between benefits and drawbacks of pre-training on a large dataset?
- What are some strategies for leveraging the benefits of pre-training while minimizing the potential drawbacks of overfitting or memorization?
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