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Related Questions
- What are the key metrics to consider when evaluating the performance of a fine-tuned language model?
- How can I use automatic metrics such as accuracy, precision, and recall to evaluate the model's performance?
- What are some common evaluation methods for language models, such as perplexity, ROUGE score, or BLEU score?
- How can I use human evaluation, such as annotating a test dataset, to assess the model's performance?
- What are some common sources of bias in language models, and how can I mitigate them during evaluation?
- How can I use techniques like cross-validation and stratified sampling to ensure a representative evaluation of the model's performance?
- What are some best practices for tuning hyperparameters to optimize the performance of the fine-tuned language model?
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