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Related Questions
- What are some common pitfalls or challenges associated with choosing the right evaluation metric for text generation models?
- How can the choice of evaluation metric impact the performance and interpretability of text generation models?
- What are some common evaluation metrics used for text generation models, and what are their limitations?
- How can the evaluation metric be chosen based on the specific task or application of the text generation model?
- What are some common challenges in evaluating the performance of text generation models, such as measuring coherence and relevance?
- How can the evaluation metric be used to compare the performance of different text generation models?
- What are some emerging trends and challenges in evaluating the performance of text generation models, such as the use of adversarial testing and human evaluation?
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