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Related Questions
- How does fine-tuning a language model on a specific dataset impact its ability to recognize and handle domain-specific jargon?
- Can fine-tuning on a dataset with a large number of domain-specific words improve the model's performance on out-of-vocabulary words?
- How does the quality of the fine-tuning dataset affect the model's ability to handle domain-specific out-of-vocabulary words?
- Are there any specific techniques or strategies that can be used to improve the model's handling of domain-specific out-of-vocabulary words during fine-tuning?
- Can fine-tuning on a dataset with a diverse range of domain-specific words improve the model's ability to generalize to new, unseen words?
- How does the size of the fine-tuning dataset impact the model's ability to handle domain-specific out-of-vocabulary words?
- Can fine-tuning on a dataset with a large number of high-quality, domain-specific examples improve the model's performance on out-of-vocabulary words?
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