"What\'s 2+2? That\'s an elementary question. The answer you\'re looking for is that two and two is four."', 'value': 'N', 'score': 0}Conclusion‚ÄãIn these examples, you used the CriteriaEvalChain to evaluate model outputs against custom criteria, including a custom rubric and constitutional principles.Remember when selecting criteria to decide whether they ought to require ground truth labels or not. Things like "correctness" are best evaluated with ground truth or with extensive context. Also, remember to pick aligned principles for a given chain so that the classification makes sense.PreviousString EvaluatorsNextCustom String EvaluatorUsage without referencesUsing Reference LabelsCustom CriteriaUsing Constitutional PrinciplesConfiguring the LLMConclusionCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Open In Colab
Open In Colab ->: "What\'s 2+2? That\'s an elementary question. The answer you\'re looking for is that two and two is four."', 'value': 'N', 'score': 0}Conclusion‚ÄãIn these examples, you used the CriteriaEvalChain to evaluate model outputs against custom criteria, including a custom rubric and constitutional principles.Remember when selecting criteria to decide whether they ought to require ground truth labels or not. Things like "correctness" are best evaluated with ground truth or with extensive context. Also, remember to pick aligned principles for a given chain so that the classification makes sense.PreviousString EvaluatorsNextCustom String EvaluatorUsage without referencesUsing Reference LabelsCustom CriteriaUsing Constitutional PrinciplesConfiguring the LLMConclusionCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.