MillID leaderboard

MillID (MultiLingual Language IDentifier) against GlotLID and Meta's fastText language identifier (NLLB). F1 is per language, then averaged with every language weighted equally (macro).

The models: MillID tiny v1.5, MillID medium v1, MillID large v1.5. Code, and running them in Python or JavaScript without a server: baobab-tech/millid.

Every score is on the test split of the build the models were trained on. The public baobabtech/millid-dataset is that build without Save the Children's and Nal'ibali's text, which is not ours to redistribute: the same splits, and a test split 1.3% smaller. udhr is the same everywhere.

• MillID knows 1,641 labels, GlotLID over 2,000, fastText 218. Each external model is shown restricted to MillID's labels (its best answer among them), the like-for-like comparison; its as-is scores are below.
• On test and udhr, fastText is mostly scored on languages it cannot answer. test-common and udhr-common keep the passages whose language all three know (about 210 languages): the head-to-head on equal terms.
• Read GlotLID's scores with their bias in mind: the dataset's FinePDFs and FineWeb-2 passages were labelled by GlotLID, and GlotLID was trained on UDHR, so both favour it.
• fastText's labels are mapped onto MillID's spelling: Simplified and Traditional Han as Hani, pes/prs as fas, est as ekk, tgl as fil.

Macro F1, every set

The three MillID models, and GlotLID and fastText restricted to MillID's labels. The best score on each set is in bold.

Set	Languages	tiny v1.5	medium v1	large v1.5	GlotLID	fastText
test	1,621	0.9554	0.9576	0.9646	0.9755	0.0659
test-common	213	0.9513	0.9527	0.9594	0.9846	0.9173
udhr	358	0.8764	0.8780	0.8812	0.8873	0.3499
udhr-common	170	0.9513	0.9480	0.9529	0.9659	0.9329
udhr-all	429	0.7149	0.7184	0.7201	0.7245	0.2797

• test: every language, passages from documents never seen in training
• test-common: the languages all three systems know
• udhr: the Declaration of Human Rights, languages MillID knows
• udhr-common: the Declaration, languages all three know
• udhr-all: the Declaration, every language in it

test

Every language, passages from documents never seen in training. F1 ≥ 0.9: how many of its 1,621 languages a system reaches that F1 on. Top-5 and median F1 are in leaderboard_overall.csv.

System	Size	Top-1	Top-3	Macro P	Macro R	Macro F1	F1 ≥ 0.9
GlotLID	1.7 GB	0.9783	0.9978	0.9778	0.9765	0.9755	1,490
GlotLID, as is	1.7 GB	0.9776	0.9977	0.9783	0.9752	0.9748	1,488
large v1.5	192.6M	0.9674	0.9924	0.9655	0.9663	0.9646	1,478
medium v1	115.0M	0.9616	0.9910	0.9564	0.9614	0.9576	1,451
tiny v1.5	2.9M	0.9587	0.9890	0.9550	0.9588	0.9554	1,446
fastText	1.2 GB	0.2515	0.2611	0.0521	0.1209	0.0659	26
fastText, as is	1.2 GB	0.2511	0.2610	0.0520	0.1205	0.0657	25

test-common

The languages all three systems know. F1 ≥ 0.9: how many of its 213 languages a system reaches that F1 on. Top-5 and median F1 are in leaderboard_overall.csv.

System	Size	Top-1	Top-3	Macro P	Macro R	Macro F1	F1 ≥ 0.9
GlotLID	1.7 GB	0.9749	0.9927	0.9923	0.9790	0.9846	203
GlotLID, as is	1.7 GB	0.9738	0.9925	0.9924	0.9771	0.9835	201
large v1.5	192.6M	0.9525	0.9898	0.9757	0.9460	0.9594	193
medium v1	115.0M	0.9425	0.9882	0.9732	0.9361	0.9527	191
tiny v1.5	2.9M	0.9396	0.9857	0.9709	0.9353	0.9513	188
fastText	1.2 GB	0.9352	0.9710	0.9354	0.9201	0.9173	166
fastText, as is	1.2 GB	0.9339	0.9707	0.9357	0.9169	0.9149	165

udhr

The Declaration of Human Rights, languages MillID knows. F1 ≥ 0.9: how many of its 358 languages a system reaches that F1 on. Top-5 and median F1 are in leaderboard_overall.csv.

System	Size	Top-1	Top-3	Macro P	Macro R	Macro F1	F1 ≥ 0.9
GlotLID	1.7 GB	0.8614	0.9294	0.9258	0.8844	0.8873	291
GlotLID, as is	1.7 GB	0.8598	0.9280	0.9261	0.8826	0.8865	287
large v1.5	192.6M	0.8579	0.9183	0.9171	0.8825	0.8812	283
medium v1	115.0M	0.8524	0.9194	0.9187	0.8769	0.8780	282
tiny v1.5	2.9M	0.8492	0.9117	0.9148	0.8736	0.8764	274
fastText	1.2 GB	0.4629	0.4857	0.3152	0.4483	0.3499	61
fastText, as is	1.2 GB	0.4625	0.4857	0.3152	0.4479	0.3497	60

udhr-common

The Declaration, languages all three know. F1 ≥ 0.9: how many of its 170 languages a system reaches that F1 on. Top-5 and median F1 are in leaderboard_overall.csv.

System	Size	Top-1	Top-3	Macro P	Macro R	Macro F1	F1 ≥ 0.9
GlotLID	1.7 GB	0.9338	0.9683	0.9888	0.9579	0.9659	156
GlotLID, as is	1.7 GB	0.9336	0.9678	0.9888	0.9576	0.9657	155
large v1.5	192.6M	0.9168	0.9630	0.9800	0.9436	0.9529	152
tiny v1.5	2.9M	0.9123	0.9606	0.9794	0.9393	0.9513	149
medium v1	115.0M	0.9121	0.9633	0.9770	0.9382	0.9480	153
fastText	1.2 GB	0.9195	0.9647	0.9474	0.9441	0.9329	142
fastText, as is	1.2 GB	0.9187	0.9647	0.9474	0.9431	0.9323	141

udhr-all

The Declaration, every language in it. F1 ≥ 0.9: how many of its 429 languages a system reaches that F1 on. Top-5 and median F1 are in leaderboard_overall.csv.

System	Size	Top-1	Top-3	Macro P	Macro R	Macro F1	F1 ≥ 0.9
GlotLID, as is	1.7 GB	0.7502	0.8145	0.7695	0.7529	0.7454	277
GlotLID	1.7 GB	0.7378	0.7960	0.7425	0.7381	0.7245	272
large v1.5	192.6M	0.7348	0.7865	0.7392	0.7364	0.7201	266
medium v1	115.0M	0.7301	0.7875	0.7415	0.7318	0.7184	266
tiny v1.5	2.9M	0.7274	0.7809	0.7340	0.7290	0.7149	254
fastText	1.2 GB	0.3964	0.4160	0.2479	0.3741	0.2797	55
fastText, as is	1.2 GB	0.3961	0.4160	0.2479	0.3737	0.2795	54

Per language, test

Against GlotLID restricted, the best MillID is better on 165 languages and worse on 498; against fastText restricted, the best MillID is better on 1616 languages and worse on 0 (F1 differing by more than 0.01), of 1621. F1 per language: tiny is MillID tiny v1.5, medium is MillID medium v1, large is MillID large v1.5; GlotLID and fastText are restricted to MillID's labels. Every language, with their unrestricted F1 too, is in leaderboard_{set_name}.csv.

The 30 languages with the most passages:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
fra_Latn	French	1652	0.929	0.952	0.960	0.928	0.808
eng_Latn	English	1444	0.917	0.916	0.934	0.859	0.648
spa_Latn	Spanish	1136	0.930	0.942	0.955	0.951	0.574
tam_Taml	Tamil	754	0.997	0.997	0.999	0.993	0.965
arb_Arab	Arabic (Modern Standard)	745	0.814	0.829	0.833	0.785	0.512
por_Latn	Portuguese	657	0.947	0.955	0.965	0.949	0.755
kan_Knda	Kannada	601	0.969	0.982	0.965	0.993	0.922
zul_Latn	Zulu	594	0.846	0.833	0.878	0.896	0.539
swh_Latn	Swahili	592	0.848	0.858	0.870	0.916	0.346
mar_Deva	Marathi	589	0.965	0.981	0.976	0.990	0.926
tso_Latn	Tsonga	581	0.965	0.970	0.978	0.956	0.425
hun_Latn	Hungarian	576	0.987	0.990	0.991	0.999	0.232
afr_Latn	Afrikaans	569	0.967	0.974	0.979	0.985	0.860
tel_Telu	Telugu	555	0.991	0.994	0.988	0.994	0.951
rus_Cyrl	Russian	528	0.932	0.925	0.949	0.949	0.462
nbl_Latn	South Ndebele	528	0.903	0.895	0.927	0.949	0.000
ory_Orya	Odia (individual language)	511	0.988	0.993	0.993	0.994	0.976
sot_Latn	Southern Sotho	491	0.966	0.966	0.972	0.978	0.660
nso_Latn	Northern Sotho	479	0.956	0.960	0.962	0.969	0.914
kua_Latn	Kuanyama	476	0.962	0.979	0.975	0.986	0.000
asm_Beng	Assamese	467	0.997	0.994	0.996	0.999	0.990
ben_Beng	Bangla	466	0.977	0.980	0.979	0.997	0.718
pan_Guru	Punjabi	460	1.000	1.000	1.000	1.000	0.990
amh_Ethi	Amharic	458	0.981	0.984	0.986	1.000	0.807
tsn_Latn	Tswana	456	0.945	0.939	0.947	0.961	0.652
vro_Latn	Võro	448	0.947	0.958	0.973	0.990	0.000
gaz_Latn	Oromo (West Central)	441	0.910	0.943	0.928	0.938	0.407
som_Latn	Somali	439	0.982	0.988	0.990	0.994	0.487
uzn_Latn	Northern Uzbek	436	0.976	0.978	0.982	0.994	0.449
tha_Thai	Thai	431	0.979	0.970	0.981	0.980	0.650

Where MillID gains most over GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
lbj_Tibt	Ladakhi	66	0.943	0.943	0.923	0.000	0.000
ain_Latn	Ainu	1	0.667	0.667	0.667	0.000	0.000
ajp_Arab	South Levantine Arabic	28	0.946	0.902	0.902	0.581	0.000
und_Laoo	und	20	0.923	0.857	0.788	0.621	0.000
sgh_Cyrl	Shughni	9	0.857	0.900	0.889	0.667	0.000
und_Thaa	und	29	0.881	0.873	0.863	0.651	0.000
icr_Latn	Islander Creole English	24	0.698	0.870	0.700	0.684	0.000
und_Geor	und	32	0.877	0.706	0.792	0.694	0.000
tdt_Latn	Tetun Dili	57	0.693	0.656	0.782	0.603	0.000
cek_Latn	Eastern Khumi Chin	67	0.785	0.853	0.825	0.684	0.000
und_Syrc	und	43	0.966	0.977	0.989	0.822	0.000
neb_Latn	Toura (Côte d'Ivoire)	11	0.957	0.957	1.000	0.842	0.000
dag_Latn	Dagbani	149	0.767	0.817	0.814	0.660	0.000
tuk_Arab	Turkmen	135	0.905	0.903	0.917	0.761	0.000
orv_Cyrl	Old Russian	239	0.931	0.935	0.938	0.800	0.000

Where MillID loses most to GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
mus_Latn	Muscogee	2	0.333	0.667	0.667	1.000	0.000
ttj_Latn	Tooro	28	0.485	0.490	0.622	0.946	0.000
knc_Arab	Central Kanuri	68	0.462	0.509	0.532	0.825	0.007
hrv_Latn	Croatian	168	0.622	0.687	0.707	0.944	0.178
esi_Latn	North Alaskan Inupiatun	9	0.455	0.500	0.556	0.783	0.000
hak_Hani	Hakka Chinese	29	0.621	0.415	0.581	0.824	0.000
bos_Latn	Bosnian	198	0.649	0.673	0.700	0.902	0.181
plw_Latn	Brooke's Point Palawano	8	0.727	0.800	0.762	1.000	0.000
ccp_Latn	Chakma	3	0.800	0.333	0.750	1.000	0.000
mbd_Latn	Dibabawon Manobo	14	0.596	0.757	0.800	1.000	0.000
taq_Tfng	Tamasheq	104	0.529	0.535	0.527	0.718	0.000
zsm_Latn	Standard Malay	244	0.770	0.746	0.781	0.957	0.319
biu_Latn	Biete	7	0.667	0.667	0.833	1.000	0.000
ldi_Latn	Laari	62	0.777	0.831	0.765	0.992	0.000
tzm_Tfng	Central Atlas Tamazight	157	0.659	0.620	0.614	0.816	0.569

Per language, test-common

Against GlotLID restricted, the best MillID is better on 13 languages and worse on 114; against fastText restricted, the best MillID is better on 111 languages and worse on 31 (F1 differing by more than 0.01), of 213. F1 per language: tiny is MillID tiny v1.5, medium is MillID medium v1, large is MillID large v1.5; GlotLID and fastText are restricted to MillID's labels. Every language, with their unrestricted F1 too, is in leaderboard_{set_name}.csv.

The 30 languages with the most passages:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
fra_Latn	French	1652	0.943	0.974	0.983	0.955	0.963
eng_Latn	English	1444	0.932	0.941	0.953	0.877	0.857
spa_Latn	Spanish	1136	0.937	0.953	0.972	0.958	0.941
tam_Taml	Tamil	754	0.997	0.998	0.999	1.000	0.997
arb_Arab	Arabic (Modern Standard)	745	0.871	0.905	0.905	0.886	0.954
por_Latn	Portuguese	657	0.959	0.963	0.973	0.956	0.949
kan_Knda	Kannada	601	0.973	0.987	0.967	0.994	0.999
zul_Latn	Zulu	594	0.883	0.871	0.909	0.904	0.970
swh_Latn	Swahili	592	0.893	0.897	0.909	0.953	0.945
mar_Deva	Marathi	589	0.968	0.981	0.979	0.990	0.987
tso_Latn	Tsonga	581	0.979	0.984	0.985	0.956	0.986
hun_Latn	Hungarian	576	0.989	0.991	0.993	1.000	0.980
afr_Latn	Afrikaans	569	0.972	0.976	0.983	0.985	0.986
tel_Telu	Telugu	555	0.997	1.000	0.999	0.998	0.999
rus_Cyrl	Russian	528	0.945	0.929	0.956	0.985	0.927
ory_Orya	Odia (individual language)	511	0.994	0.996	0.995	1.000	0.996
sot_Latn	Southern Sotho	491	0.969	0.967	0.974	0.978	0.856
nso_Latn	Northern Sotho	479	0.958	0.961	0.964	0.970	0.967
asm_Beng	Assamese	467	0.997	0.995	0.997	0.999	0.997
ben_Beng	Bangla	466	0.988	0.987	0.993	0.997	0.989
pan_Guru	Punjabi	460	1.000	1.000	1.000	1.000	0.990
amh_Ethi	Amharic	458	0.984	0.987	0.986	1.000	0.998
tsn_Latn	Tswana	456	0.948	0.940	0.947	0.961	0.870
gaz_Latn	Oromo (West Central)	441	0.935	0.955	0.941	0.974	0.973
som_Latn	Somali	439	0.984	0.992	0.991	0.995	0.991
uzn_Latn	Northern Uzbek	436	0.984	0.984	0.986	0.999	0.985
tha_Thai	Thai	431	0.980	0.970	0.981	0.980	0.981
ydd_Hebr	Eastern Yiddish	430	0.993	0.998	0.994	1.000	0.999
tur_Latn	Turkish	430	0.968	0.974	0.973	0.999	0.980
nno_Latn	Norwegian Nynorsk	427	0.913	0.919	0.927	0.985	0.954

Where MillID gains most over GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
ewo_Latn	Ewondo	134	0.959	0.965	0.978	0.883	0.860
eng_Latn	English	1444	0.932	0.941	0.953	0.877	0.857
arb_Latn	Standard Arabic	163	0.942	0.944	0.949	0.913	0.852
tso_Latn	Tsonga	581	0.979	0.984	0.985	0.956	0.986
fra_Latn	French	1652	0.943	0.974	0.983	0.955	0.963
arb_Arab	Arabic (Modern Standard)	745	0.871	0.905	0.905	0.886	0.954
por_Latn	Portuguese	657	0.959	0.963	0.973	0.956	0.949
hin_Deva	Hindi	392	0.855	0.817	0.893	0.877	0.863
fuv_Latn	Nigerian Fulfulde	164	0.907	0.797	0.844	0.892	0.859
kam_Latn	Kamba	272	0.980	0.980	0.989	0.974	0.863
knc_Latn	Central Kanuri	293	0.967	0.959	0.967	0.952	0.981
spa_Latn	Spanish	1136	0.937	0.953	0.972	0.958	0.941
bug_Latn	Buginese	78	0.981	0.987	0.994	0.981	0.938
bjn_Arab	Banjar	116	0.992	0.983	0.996	0.987	0.960
san_Deva	Sanskrit	239	0.990	0.996	0.998	0.990	0.971

Where MillID loses most to GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
knc_Arab	Central Kanuri	68	0.522	0.562	0.598	0.860	0.029
bos_Latn	Bosnian	198	0.685	0.727	0.762	1.000	0.897
tzm_Tfng	Central Atlas Tamazight	157	0.697	0.645	0.649	0.934	0.751
hrv_Latn	Croatian	168	0.659	0.717	0.757	0.994	0.856
zsm_Latn	Standard Malay	244	0.789	0.773	0.809	0.998	0.908
taq_Tfng	Tamasheq	104	0.654	0.613	0.604	0.805	0.000
ind_Latn	Indonesian	335	0.842	0.807	0.848	0.991	0.887
nob_Latn	Norwegian Bokmål	265	0.821	0.820	0.832	0.959	0.894
kin_Latn	Kinyarwanda	210	0.849	0.818	0.864	0.981	0.854
run_Latn	Rundi	291	0.883	0.843	0.879	0.985	0.855
mag_Deva	Magahi	97	0.890	0.905	0.897	1.000	0.772
cjk_Latn	Chokwe	24	0.857	0.909	0.837	1.000	0.807
taq_Latn	Tamasheq	106	0.902	0.909	0.922	1.000	0.838
dzo_Tibt	Dzongkha	346	0.906	0.926	0.916	0.999	0.696
lim_Latn	Limburgish	196	0.896	0.915	0.930	1.000	0.956

Per language, udhr

Against GlotLID restricted, the best MillID is better on 75 languages and worse on 57; against fastText restricted, the best MillID is better on 313 languages and worse on 8 (F1 differing by more than 0.01), of 358. F1 per language: tiny is MillID tiny v1.5, medium is MillID medium v1, large is MillID large v1.5; GlotLID and fastText are restricted to MillID's labels. Every language, with their unrestricted F1 too, is in leaderboard_{set_name}.csv.

The 30 languages with the most passages:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
roh_Latn	Romansh	399	0.994	0.991	0.998	0.999	0.946
oci_Latn	Occitan	398	0.277	0.331	0.338	0.376	0.435
cmn_Hani	Chinese (Mandarin)	319	0.892	0.886	0.875	0.868	0.468
krl_Latn	Karelian	183	0.000	0.000	0.000	0.011	0.000
qug_Latn	Chimborazo Highland Quichua	182	0.011	0.000	0.000	0.000	0.000
acu_Latn	Achuar-Shiwiar	180	0.828	0.743	0.801	0.854	0.000
hus_Latn	Huastec	175	0.977	0.991	0.988	0.986	0.000
hau_Latn	Hausa	155	0.990	0.997	1.000	1.000	0.876
auc_Latn	Waorani	154	0.000	0.050	0.025	0.000	0.000
kwi_Latn	Awa-Cuaiquer	145	0.880	0.775	0.863	0.877	0.000
jpn_Jpan	Japanese	140	1.000	1.000	1.000	1.000	0.944
snn_Latn	Siona	136	0.630	0.773	0.467	0.514	0.000
ktu_Latn	Kituba (Democratic Republic of Congo)	118	0.765	0.769	0.773	0.680	0.000
lat_Latn	Latin	118	0.996	0.996	0.996	0.992	0.000
hat_Latn	Haitian Creole	117	0.992	0.991	0.987	0.979	0.699
nya_Latn	Nyanja	116	0.991	0.987	0.978	1.000	0.806
kmb_Latn	Kimbundu	116	0.970	0.979	0.991	1.000	0.877
rmn_Latn	Balkan Romani	116	0.678	0.667	0.704	0.857	0.000
twi_Latn	Twi	116	0.983	0.987	0.991	0.996	0.396
chr_Cher	Cherokee	115	0.670	0.715	0.945	0.663	0.000
por_Latn	Portuguese	115	0.955	0.996	1.000	0.996	0.793
lvs_Latn	Standard Latvian	115	0.987	0.996	1.000	1.000	0.991
pov_Latn	Upper Guinea Crioulo	115	0.821	0.838	0.827	0.833	0.000
kng_Latn	Koongo	115	0.076	0.047	0.047	0.193	0.457
ell_Grek	Greek	115	0.670	0.655	0.670	1.000	1.000
tha_Thai	Thai	114	1.000	1.000	1.000	1.000	0.996
tso_Latn	Tsonga	114	0.860	0.882	0.774	0.781	0.691
cjk_Latn	Chokwe	114	0.871	0.949	0.959	1.000	0.533
fas_Arab	Persian	114	0.991	0.991	0.982	1.000	0.934
lin_Latn	Lingala	110	0.991	1.000	0.996	1.000	0.986

Where MillID gains most over GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
mic_Latn	Mi'kmaw	59	0.992	1.000	1.000	0.427	0.000
tet_Latn	Tetum	58	0.638	0.699	0.708	0.167	0.000
fuf_Latn	Pular	58	0.906	0.816	0.936	0.483	0.000
skr_Arab	Saraiki	63	0.867	0.923	0.875	0.500	0.000
sag_Latn	Sango	59	0.992	0.992	0.992	0.578	0.189
zgh_Tfng	Standard Moroccan Tamazight	60	0.750	0.824	0.652	0.462	0.000
qvh_Latn	Huamalíes-Dos de Mayo Huánuco Quechua	58	0.468	0.215	0.215	0.154	0.000
chr_Cher	Cherokee	115	0.670	0.715	0.945	0.663	0.000
tzm_Tfng	Central Atlas Tamazight	1	0.167	0.333	0.100	0.065	0.033
snn_Latn	Siona	136	0.630	0.773	0.467	0.514	0.000
fkv_Latn	Kven Finnish	58	0.635	0.697	0.906	0.667	0.000
bum_Latn	Bulu	58	0.215	0.319	0.188	0.098	0.000
mxv_Latn	Metlatónoc Mixtec	58	0.129	0.215	0.034	0.000	0.000
pnb_Arab	Western Panjabi	61	0.882	0.931	0.884	0.739	0.000
lld_Latn	Ladin	59	0.909	0.899	0.881	0.731	0.000

Where MillID loses most to GlotLID:

Label	Language	Passages	tiny	medium	large	GlotLID	fastText
gyr_Latn	Guarayu	49	0.537	0.339	0.393	0.990	0.000
dyu_Latn	Dyula	58	0.000	0.000	0.000	0.434	0.015
ell_Grek	Greek	115	0.670	0.655	0.670	1.000	1.000
cbu_Latn	Candoshi-Shapra	57	0.500	0.371	0.557	0.874	0.000
shp_Latn	Shipibo-Conibo	62	0.469	0.410	0.607	0.912	0.000
cpu_Latn	Pichis Ashéninka	60	0.729	0.571	0.571	0.974	0.000
qvn_Latn	North Junín Quechua	57	0.219	0.219	0.034	0.460	0.000
hin_Deva	Hindi	59	0.723	0.607	0.727	0.957	0.975
cni_Latn	Asháninka	52	0.773	0.708	0.717	0.963	0.000
hrv_Latn	Croatian	58	0.500	0.537	0.559	0.727	0.474
rmn_Latn	Balkan Romani	116	0.678	0.667	0.704	0.857	0.000
koi_Cyrl	Komi-Permyak	57	0.837	0.837	0.849	1.000	0.000
qvm_Latn	Margos-Yarowilca-Lauricocha Quechua	60	0.356	0.094	0.356	0.500	0.000
kea_Latn	Kabuverdianu	58	0.792	0.794	0.773	0.935	0.124
ind_Latn	Indonesian	60	0.768	0.674	0.645	0.903	0.565