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Related Questions
- What is the primary function of weight decay in large language models?
- How does weight decay impact the model's ability to overfit the training data?
- Can weight decay be adjusted during the training process, and if so, how does it affect the model's performance?
- What are the trade-offs between regularizing the model with weight decay and preserving its ability to learn from the training data?
- How does the choice of weight decay strength influence the model's generalization capabilities?
- Can weight decay be combined with other regularization techniques, such as dropout or L1/L2 regularization?
- What are the potential consequences of not using weight decay in the training process, particularly for large models with many parameters?
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