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.
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.
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
The three weakest languages by F1: mt at 0.942, az at 0.958, tr at 0.963.
These are published rather than dropped. A coverage table with the bad rows removed is not a coverage table.