From #wikimedia-ai:

[13:18:32] <halfak> Oh! I should check the model against water.
[13:18:34] <halfak> One sec.
[13:19:12] <halfak> Wikidata search is awful!
[13:20:22] <halfak> Amir1, looks like we're scoring edits to water with a bit less extreme scores.
[13:20:55] <Amir1> :))))
[13:21:22] <halfak> We're still scoring highly, but not at the 99-100% level.
[13:22:10] <halfak> Last 5 edits: 0.79, 0.94, 0.86, 0.81, 0.92
[13:22:25] <Amir1> that's better
[13:22:32] <Amir1> but we still need to work on them
[13:22:52] <halfak> Compared to 0.98, 1.00, 1.00, 0.98, 0.99

AUC = 0.8467 for Wikidata with user.age -- Still need to test against Water.

Just got a new dataset for training against from @Ladsgroup.

https://tools.wmflabs.org/dexbot/damaging_73k.tsv is list of 73K edits randomly sampled, balanced and ready to be sampled and fed to the training system. (the second row is damaging or not)

How was that detected? Does "is damaging" means "was reverted" here?

In T118731#1835355, @Halfak wrote:

Just got a new dataset for training against from @Ladsgroup.

https://tools.wmflabs.org/dexbot/damaging_73k.tsv is list of 73K edits randomly sampled, balanced and ready to be sampled and fed to the training system. (the second row is damaging or not)

Report: https://www.wikidata.org/wiki/Wikidata:ORES/Report_mistakes

PR: https://github.com/wiki-ai/wb-vandalism/pull/17