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Related Questions
- What are the common evaluation metrics used to evaluate the performance of pre-trained language models?
- How does the choice of evaluation metric affect the selection of a pre-trained model for a specific task?
- Can you explain the trade-offs between different evaluation metrics such as accuracy, F1-score, and ROUGE score?
- What are the implications of using a particular evaluation metric on the selection of a pre-trained model for a downstream task?
- How does the choice of evaluation metric influence the choice of pre-trained model architecture and training objectives?
- Can you discuss the role of evaluation metrics in model selection for tasks such as sentiment analysis, question answering, and machine translation?
- What are the best practices for selecting the right evaluation metric for a pre-trained model, and how does it impact the model's performance on a specific task?
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