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Related Questions
- How does task-specific training impact the performance of language models on out-of-distribution tasks?
- What are the advantages and disadvantages of fine-tuning language models on specific tasks versus training them from scratch?
- Can you explain the concept of 'catastrophic forgetting' in the context of language model training and how it relates to generalizability?
- How do different optimization algorithms and hyperparameters affect the trade-off between task-specific performance and generalizability in language models?
- What are some strategies for regularizing language models to improve their generalizability while maintaining task-specific performance?
- Can you discuss the role of data augmentation in improving the generalizability of language models trained on specific tasks?
- How do the architecture and design of language models impact their ability to generalize to new tasks and domains?
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