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Related Questions
- What is the impact of pre-training dataset size on the out-of-vocabulary (OOV) word handling in BERT and RoBERTa models?
- How does the pre-training dataset size influence the ability of BERT and RoBERTa models to generalize to words with rare or unseen frequencies?
- Can a larger pre-training dataset improve the robustness of BERT and RoBERTa models to words with unknown or out-of-domain vocabulary?
- What is the relationship between pre-training dataset size and the ability of BERT and RoBERTa models to adapt to new, unseen words in a downstream task?
- How does the pre-training dataset size affect the performance of BERT and RoBERTa models on tasks that require understanding of rare or domain-specific words?
- Can a larger pre-training dataset help BERT and RoBERTa models generalize better to words with high-dimensional or abstract meanings?
- What are the implications of using a smaller versus a larger pre-training dataset on the ability of BERT and RoBERTa models to generalize to unseen words in a real-world setting?
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