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**Evaluation**
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Here we will use [AspectCritic](../concepts/metrics/available_metrics/aspect_critic.md), which an LLM based metric that outputs pass/fail given the evaluation criteria.
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Here we will use [AspectCritic](../concepts/metrics/available_metrics/aspect_critic.md), which is an LLM based metric that outputs pass/fail given the evaluation criteria.
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```python
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{'summary_accuracy': 0.84}
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```
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This score shows that out of all the samples in our test data, only 84% of summaries passes the given evaluation criteria. Now, **It
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s important to see why is this the case**.
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This score shows that out of all the samples in our test data, only 84% of summaries passes the given evaluation criteria. Now, **It's
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important to see why is this the case**.
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Export the sample level scores to pandas dataframe
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@@ -187,4 +187,4 @@ If you want help with improving and scaling up your AI application using evals.
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