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Related Questions
- What are some common metrics used to evaluate text generation models and how can they be modified to mitigate overfitting?
- How can metrics like BLEU score and ROUGE score be used to evaluate the quality of generated text while reducing overfitting?
- What is the role of metrics like perplexity and cross-entropy in evaluating text generation models and how can they be used to detect overfitting?
- Can you explain how metrics like coherence and fluency can be used to evaluate the quality of generated text and reduce overfitting?
- How do metrics like adversarial evaluation and back-translation evaluation help in detecting overfitting in text generation models?
- What is the significance of using metrics like human evaluation and automatic evaluation in conjunction to reduce overfitting in text generation models?
- Can you discuss the use of metrics like inconsistency and redundancy in evaluating text generation models and reducing overfitting?
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