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Related Questions
- What are the most critical hyperparameters to consider when fine-tuning a pre-trained language model for a specific task?
- How does the choice of learning rate affect the fine-tuning process, and what are the optimal settings for different tasks?
- What is the impact of batch size on the fine-tuning process, and how does it relate to the available computational resources?
- How does the choice of optimizer influence the convergence of the model during fine-tuning, and which optimizers are commonly used?
- What is the role of regularization techniques, such as dropout and L1/L2 regularization, in preventing overfitting during fine-tuning?
- How does the choice of evaluation metric affect the fine-tuning process, and what are the most commonly used metrics for different tasks?
- What is the impact of the number of training epochs on the fine-tuning process, and how does it relate to the model's generalization ability?
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