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Related Questions
- What are the potential consequences of using a suboptimal tokenization scheme on the overall quality of generated text in data augmentation?
- How does suboptimal tokenization impact the accuracy and coherence of generated text in data augmentation?
- Can you explain the relationship between tokenization quality and the diversity of generated text in data augmentation?
- What are some common pitfalls that can lead to suboptimal tokenization in data augmentation, and how can they be avoided?
- How does suboptimal tokenization affect the ability of the model to capture nuanced language patterns and idioms in data augmentation?
- What are some strategies for evaluating the quality of tokenization in data augmentation, and how can they be used to improve model performance?
- Can you discuss the trade-offs between tokenization complexity and model performance in data augmentation, and how to strike a balance between the two?
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