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Related Questions
- What are the primary effects of weight decay on the performance of pre-trained language models during fine-tuning?
- How does weight decay influence the learning rate of pre-trained language models, and what are the implications for model convergence?
- Can you explain the relationship between weight decay and overfitting in pre-trained language models, and how it affects generalization performance?
- What are some common techniques used to implement weight decay in fine-tuning pre-trained language models, and their relative advantages?
- How does weight decay interact with other hyperparameters, such as learning rate and batch size, in fine-tuning pre-trained language models?
- What are the potential drawbacks or limitations of using weight decay in fine-tuning pre-trained language models, and how can they be mitigated?
- Can you provide examples or case studies of successful applications of weight decay in fine-tuning pre-trained language models for specific NLP tasks?
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