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Related Questions
- What is the relationship between model complexity and overfitting in NLP, and how can it be mitigated?
- How do semantic preserving techniques, such as word embeddings and contextualized embeddings, address overfitting in NLP models?
- Can you explain the concept of overfitting in NLP and how it occurs when training complex models?
- How does the choice of model architecture and hyperparameters impact the risk of overfitting in NLP tasks?
- What are some common techniques used to prevent overfitting in NLP models, and how do they relate to model complexity?
- How do techniques like data augmentation and regularization address overfitting in NLP models, and what are their limitations?
- Can you describe the role of semantic preserving techniques in reducing overfitting and improving the generalizability of NLP models?
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