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Related Questions
- What are some common metrics used to evaluate the fluency of generated text?
- How does using a diverse set of evaluation metrics help in understanding the strengths and weaknesses of a text generation model?
- What are some potential limitations of relying on a single evaluation metric to assess a text generation model?
- Can you explain how a diverse set of evaluation metrics can help in fine-tuning a text generation model for a specific task or domain?
- How does using a diverse set of evaluation metrics impact the interpretability of text generation models?
- What are some ways to balance the trade-off between the diversity of evaluation metrics and the computational resources required to evaluate a model?
- How does using a diverse set of evaluation metrics contribute to the development of more robust and reliable text generation models?
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