A more general solution to model answer extraction instead of output_regex
#358
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sadra-barikbin
commented
Oct 11, 2024
| @@ -504,7 +507,19 @@ def get_metric_method_from_category(self, metric_category): | |||
| if not self.has_metric_category[metric_category]: | |||
| raise ValueError(f"Requested a metric category {metric_category} absent from the task list.") | |||
|
|
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| return LightevalTask._get_metric_method_from_category(metric_category) | |||
| metric_method = LightevalTask._get_metric_method_from_category(metric_category) | |||
| # Bad hack. I had no other way. | |||
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I suggest considering task as the argument of apply_*_metrics functions as a workaround.
|
Hi Sadra, |
NathanHB
reviewed
Oct 14, 2024
Co-authored-by: Nathan Habib <[email protected]>
|
Hi! We removed output_regex a couple PRs ago, and it's likely we would want this answer extraction step to happen at the metric stage and not in the task itself, so I'm going to close this PR. |
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Hi there!
Here is the PR for model answer extraction. Currently, we have
output_regexand this PR attempts to replace it with a more general solution.By the way, our current
output_regexseems to be broken as it's not fed intoapply_generative_metricinPipeline._compute_metricsFixes #360