| # bias evaluation |
|
|
| **Threshold 0.77 (calibrated on the validation split, objective macro_f1).** The config default of 0.5 scored 0.981 against 0.982 for the calibrated value, on validation. Every table below is on test, at the calibrated threshold. |
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| ## Per language |
| |
| | Language | Support | P | R | F1 | Notes | |
| |---|---|---|---|---|---| |
| | `bg` Bulgarian | 80 | 0.987 | 0.975 | 0.981 | | |
| | `cs` Czech | 80 | 0.988 | 1.000 | 0.994 | | |
| | `da` Danish | 80 | 1.000 | 1.000 | 1.000 | | |
| | `de` German | 80 | 0.963 | 0.988 | 0.975 | | |
| | `el` Greek | 80 | 1.000 | 0.988 | 0.994 | | |
| | `en` English | 80 | 0.963 | 0.988 | 0.975 | | |
| | `es` Spanish | 76 | 1.000 | 0.974 | 0.987 | | |
| | `et` Estonian | 79 | 0.963 | 1.000 | 0.981 | | |
| | `fi` Finnish | 80 | 0.988 | 0.988 | 0.988 | | |
| | `fr` French | 80 | 0.976 | 1.000 | 0.988 | | |
| | `ga` Irish | 77 | 0.974 | 0.961 | 0.967 | | |
| | `hr` Croatian | 80 | 1.000 | 1.000 | 1.000 | | |
| | `hu` Hungarian | 80 | 0.952 | 0.988 | 0.969 | | |
| | `it` Italian | 80 | 1.000 | 1.000 | 1.000 | | |
| | `lt` Lithuanian | 79 | 0.987 | 0.987 | 0.987 | | |
| | `lv` Latvian | 80 | 0.975 | 0.988 | 0.981 | | |
| | `mt` Maltese | 78 | 0.948 | 0.936 | 0.942 | not in base model pretraining | |
| | `nl` Dutch | 79 | 0.988 | 1.000 | 0.994 | | |
| | `pl` Polish | 80 | 0.976 | 1.000 | 0.988 | | |
| | `pt` Portuguese | 76 | 0.974 | 0.974 | 0.974 | | |
| | `ro` Romanian | 80 | 1.000 | 0.988 | 0.994 | | |
| | `sk` Slovak | 80 | 0.988 | 0.988 | 0.988 | | |
| | `sl` Slovenian | 80 | 1.000 | 0.988 | 0.994 | | |
| | `sv` Swedish | 80 | 0.988 | 0.988 | 0.988 | | |
| | `tr` Turkish | 80 | 0.951 | 0.975 | 0.963 | | |
| | `az` Azerbaijani | 80 | 0.920 | 1.000 | 0.958 | | |
| |
| The base-model note is a fact about pretraining, not a cause of the score beside it. `nsfw` Maltese carried the same note at 0.000 and reached 1.000 on corpus size alone, with nothing about the base model changed. Check how many examples a weak score rests on before reaching for this. |
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| ## Per register |
| |
| | Register | Support | P | R | F1 | FPR | |
| |---|---|---|---|---|---| |
| | `age_assumption` | 415 | 1.000 | 0.986 | 0.993 | 0.000 | |
| | `counter_stereotype` | 0 | 0.000 | 0.000 | 0.000 | 0.011 | |
| | `demographic_statistic` | 0 | 0.000 | 0.000 | 0.000 | 0.000 | |
| | `disability_condescension` | 413 | 1.000 | 0.995 | 0.998 | 0.000 | |
| | `discussing_bias` | 0 | 0.000 | 0.000 | 0.000 | 0.016 | |
| | `ethnic_generalisation` | 411 | 1.000 | 0.990 | 0.995 | 0.000 | |
| | `inclusive_phrasing` | 0 | 0.000 | 0.000 | 0.000 | 0.096 | |
| | `mundane_informational` | 0 | 0.000 | 0.000 | 0.000 | 0.000 | |
| | `mundane_operational` | 0 | 0.000 | 0.000 | 0.000 | 0.000 | |
| | `mundane_transactional` | 0 | 0.000 | 0.000 | 0.000 | 0.000 | |
| | `neutral_description` | 0 | 0.000 | 0.000 | 0.000 | 0.000 | |
| | `occupational_stereotype` | 415 | 1.000 | 0.969 | 0.984 | 0.000 | |
| | `religious_assumption` | 410 | 1.000 | 0.995 | 0.998 | 0.000 | |
| |
| ## Known weaknesses |
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| The three weakest languages by F1: `mt` at 0.942, `az` at 0.958, `tr` at 0.963. |
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| These are published rather than dropped. A coverage table with the bad rows removed is not a coverage table. |
