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Related Questions
- What are the potential causes of a low F1-score in a text generation model?
- How does a low F1-score impact the model's ability to generate coherent and relevant text?
- Can a low F1-score lead to biased text generation, and if so, how can it be mitigated?
- What are the implications of a low F1-score on the model's performance in real-world applications?
- How can a low F1-score be used as an indicator for further fine-tuning or model retraining?
- What are the relationships between F1-score, precision, and recall in evaluating text generation models?
- Can a low F1-score be a result of overfitting, and if so, how can it be addressed?
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