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models F1Score Evaluator
github-actions[bot] edited this page Nov 6, 2024
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Score range | Float [0-1] |
What is this metric? | Measures the ratio of the number of shared words between the model generation and the ground truth answers. |
How does it work? | The F1-score computes the ratio of the number of shared words between the model generation and the ground truth. Ratio is computed over the individual words in the generated response against those in the ground truth answer. The number of shared words between the generation and the truth is the basis of the F1 score: precision is the ratio of the number of shared words to the total number of words in the generation, and recall is the ratio of the number of shared words to the total number of words in the ground truth. |
When to use it? | Use the F1 score when you want a single comprehensive metric that combines both recall and precision in your model's responses. It provides a balanced evaluation of your model's performance in terms of capturing accurate information in the response. |
What does it need as input? | Query, Ground Truth Response, Generated Response |
Version: 3
hiddenlayerscanned
View in Studio: https://ml.azure.com/registries/azureml/models/F1Score-Evaluator/version/3
is-promptflow: True
is-evaluator: True
show-artifact: True
_default-display-file: ./F1ScoreEvaluator/_f1_score.py