Train a new model using the new labeling campaign for huwiki. https://github.com/wikimedia/editquality/pull/195/files
Description
Description
Status | Subtype | Assigned | Task | ||
---|---|---|---|---|---|
Open | None | T223892 [EPIC] Support Hungarian Wikipedia editor retention project | |||
Resolved | Bencemac | T210224 Revert FlaggedRevs changes on the Hungarian Wikipedia | |||
Resolved | Tgr | T209224 Analyze effect of huwiki FlaggedRevs configuration change on problematic edits and new user retention | |||
Resolved | • ACraze | T229848 ORES deployment, Early August 2019 | |||
Resolved | Tgr | T230031 Update ORES filter thresholds for huwiki | |||
Resolved | • ACraze | T228078 Retrain damaging/goodfaith models for huwiki | |||
Resolved | Halfak | T223882 Re-label huwiki damaging and badfaith edits | |||
Open | None | T223899 Information about finished campaigns should be accessible in Wikilabels |
Event Timeline
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@Halfak the models have been retrained, let me know your thoughts about the tuning reports
https://github.com/wikimedia/editquality/pull/207
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I just reviewed. Just a minor note on file naming. The fitness statistics look good to me. I think we're running into issues with the fragility of our AUC measures. If you look at the ROC AUC and the PR AUC of the target classes (true for damaging, false for badfaith) then it looks like we're getting a nice improvement here.