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Related Questions
- What are the advantages of pre-training a large language model on a large dataset?
- How does fine-tuning on a smaller dataset affect the performance of a pre-trained language model?
- What are the potential drawbacks of pre-training on a large dataset, such as increased computational resources and storage requirements?
- Can you explain the concept of 'domain adaptation' in the context of fine-tuning a pre-trained model on a smaller dataset?
- How does the quality of the pre-training dataset impact the performance of the fine-tuned model?
- What are some strategies for selecting a suitable pre-training dataset for a specific downstream task?
- How does the size of the fine-tuning dataset affect the model's ability to generalize to new, unseen data?
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