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Text quality evaluation metric
Last updated: May 08, 2025
The text quality metric evaluates the output of a model against SuperGLUE datasets by measuring the F1 score, precision, and recall against the model predictions and its ground truth data.
Metric details
Text quality is a generative AI quality evaluation metric that measures how well generative AI assets perform tasks.
Scope
Text quality evaluates generative AI assets only.
- Types of AI assets: Prompt templates
- Generative AI tasks:
- Text summarization
- Content generation
- Supported languages: English
Scores and values
The text quality metric score indicates the similarity between the predictions and references. Higher scores indicate higher similarity between the predictions and references.
Settings
- Thresholds:
- Lower limit: 0.8
- Upper limit: 1
Parent topic: Evaluation metrics
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