NB-NORDIC-LID
This repo contains models for the identification of language in text (also referred to as language detection). It is based on Fasttext and designed with the Nordic languages in mind, including several Sámi languages. It comes in two flavours, nb-nordic-lid
, a model that identifies between the 12 most common languages in the Nordic countries (plus English), and nb-nordic-lid.159
, a model that extends that list to 159 languages of the world. Moreover, each of them come in large and small (quantized) versions.
Model | Size | Precision | Recall | F1-Score | Support |
---|---|---|---|---|---|
nb-nordic-lid.bin (large) |
274 MB | 0.9901 | 0.9900 | 0.9900 | 5500 |
nb-nordic-lid.ftz (small) |
1.87 MB | 0.9889 | 0.9890 | 0.9890 | 5500 |
nb-nordic-lid.159.bin (large) |
9.63 GB | 0.9434 | 0.9528 | 0.9476 | 44049 |
nb-nordic-lid.159.ftz (small) |
11.2 MB | 0.9275 | 0.9399 | 0.9327 | 44049 |
Usage
After download, the models can be used through the Fasttext library:
from huggingface_hub import hf_hub_download
import fasttext
model_name = "nb-nordic-lid.ftz"
model = fasttext.load_model(hf_hub_download("NbAiLab/nb-nordic-lid", model_name))
model.predict("Debatt er bra og sunt for demokratier, og en forutsetning for politikkutvikling.", threshold=0.25)
# (('__label__nob',), array([0.95482141]))
Alternatively, these models are also integrated into the the experimental nbailab
CLI application:
$ echo "Jeg leser en bok" | nbailab langid --model-name nb-nordic-lid.ftz
nob,0.9999788999557495
Languages
nb-nordic-lid.bin
Trained on sentences from the GiellaT's Translation Memories and Wortschatz's corpora.
ISO-639-3 | Language | Precision | Recall | F1-Score | Support |
---|---|---|---|---|---|
dan | Danish | 0.9720 | 0.9838 | 0.9779 | 494 |
eng | English | 0.9980 | 0.9940 | 0.9960 | 502 |
fao | Faroese | 0.9920 | 0.9940 | 0.9930 | 499 |
fin | Finnish | 1.0000 | 1.0000 | 1.0000 | 500 |
isl | Icelandic | 0.9900 | 0.9920 | 0.9910 | 499 |
nno | Norwegian Nynorsk | 0.9920 | 0.9861 | 0.9890 | 503 |
nob | Norwegian Bokmål | 0.9840 | 0.9743 | 0.9791 | 505 |
sma | Southern Sami | 0.9800 | 0.9703 | 0.9751 | 101 |
sme | Northern Sami | 1.0000 | 0.9921 | 0.9960 | 504 |
smj | Lule Sami | 0.9920 | 0.9960 | 0.9940 | 498 |
smn | Inari Sami | 0.9950 | 1.0000 | 0.9975 | 199 |
sms | Skolt Sami | 0.9900 | 0.9950 | 0.9925 | 199 |
swe | Swedish | 0.9860 | 0.9920 | 0.9890 | 497 |
Accuracy | 0.9905 | 5500 | |||
Weighted avg | 0.9906 | 0.9905 | 0.9905 | 5500 | |
Macro avg | 0.9901 | 0.9900 | 0.9900 | 5500 |
nb-nordic-lid.159.bin
Scores for the 159 languages
Additionally trained on sentences from Taoteba.
ISO-639-3 | Language | Precision | Recall | F1-Score | Support |
---|---|---|---|---|---|
afr | Afrikaans | 0.9634 | 0.9485 | 0.9558 | 194 |
ara | Arabic | 0.9771 | 0.9533 | 0.9650 | 492 |
arq | Algerian Arabic | 0.9478 | 0.9316 | 0.9397 | 117 |
arz | Egyptian Arabic | 0.7193 | 0.8542 | 0.7810 | 48 |
asm | Assamese | 0.9828 | 0.9884 | 0.9856 | 173 |
avk | Kotava | 0.9895 | 0.9844 | 0.9869 | 192 |
aze | Azerbaijani | 0.9707 | 0.9831 | 0.9768 | 236 |
bel | Belarusian | 0.9864 | 0.9785 | 0.9825 | 372 |
ben | Bengali | 0.9915 | 0.9873 | 0.9894 | 236 |
ber | Berber | 0.8991 | 0.8507 | 0.8742 | 576 |
bos | Bosnian | 0.1548 | 0.1781 | 0.1656 | 73 |
bre | Breton | 0.9613 | 0.9681 | 0.9647 | 282 |
bua | Buryat | 0.9333 | 0.9130 | 0.9231 | 46 |
bul | Bulgarian | 0.9530 | 0.9660 | 0.9595 | 441 |
cat | Catalan | 0.9604 | 0.9510 | 0.9557 | 306 |
cbk | Chavacano | 0.9627 | 0.9923 | 0.9773 | 130 |
ceb | Cebuano | 0.8974 | 0.9091 | 0.9032 | 77 |
ces | Czech | 0.9684 | 0.9665 | 0.9675 | 508 |
chv | Chuvash | 0.9878 | 0.9643 | 0.9759 | 84 |
ckb | Central Kurdish (Soranî) | 0.9751 | 0.9944 | 0.9846 | 354 |
ckt | Chukchi | 0.9615 | 1.0000 | 0.9804 | 25 |
cmn | Mandarin Chinese | 0.9726 | 0.8674 | 0.9170 | 573 |
cor | Cornish | 1.0000 | 0.9733 | 0.9864 | 187 |
csb | Kashubian | 0.9787 | 1.0000 | 0.9892 | 46 |
cym | Welsh | 0.9625 | 0.9625 | 0.9625 | 80 |
dan | Danish | 0.9401 | 0.9345 | 0.9373 | 1007 |
deu | German | 0.9908 | 0.9765 | 0.9836 | 553 |
dsb | Lower Sorbian | 0.8704 | 0.8246 | 0.8468 | 57 |
dtp | Central Dusun | 0.9161 | 0.9562 | 0.9357 | 137 |
ell | Greek | 1.0000 | 0.9979 | 0.9989 | 476 |
eng | English | 0.9914 | 0.9886 | 0.9900 | 1052 |
epo | Esperanto | 0.9817 | 0.9853 | 0.9835 | 544 |
est | Estonian | 0.9659 | 0.9770 | 0.9714 | 174 |
eus | Basque | 0.9883 | 0.9585 | 0.9732 | 265 |
fao | Faroese | 0.9840 | 0.9899 | 0.9870 | 497 |
fin | Finnish | 0.9932 | 0.9817 | 0.9874 | 1041 |
fkv | Kven Finnish | 0.5769 | 0.7500 | 0.6522 | 20 |
fra | French | 0.9890 | 0.9890 | 0.9890 | 544 |
frr | North Frisian | 0.9784 | 0.9784 | 0.9784 | 139 |
fry | Frisian | 0.7419 | 0.9200 | 0.8214 | 25 |
gcf | Guadeloupean Creole French | 0.9810 | 0.9904 | 0.9856 | 104 |
gla | Scottish Gaelic | 0.9608 | 0.9800 | 0.9703 | 50 |
gle | Irish | 0.9781 | 0.9853 | 0.9817 | 136 |
glg | Galician | 0.9198 | 0.9330 | 0.9264 | 209 |
gos | Gronings | 0.9631 | 0.9671 | 0.9651 | 243 |
grc | Ancient Greek | 0.9828 | 1.0000 | 0.9913 | 57 |
grn | Guarani | 0.9810 | 0.9936 | 0.9873 | 156 |
guc | Wayuu | 0.9556 | 1.0000 | 0.9773 | 43 |
hau | Hausa | 0.9930 | 0.9930 | 0.9930 | 431 |
heb | Hebrew | 1.0000 | 1.0000 | 1.0000 | 536 |
hin | Hindi | 1.0000 | 0.9974 | 0.9987 | 391 |
hoc | Ho | 0.9143 | 1.0000 | 0.9552 | 32 |
hrv | Croatian | 0.6085 | 0.5652 | 0.5861 | 253 |
hrx | Hunsrik | 0.8727 | 0.9231 | 0.8972 | 52 |
hsb | Upper Sorbian | 0.8533 | 0.8312 | 0.8421 | 77 |
hun | Hungarian | 0.9853 | 0.9889 | 0.9871 | 541 |
hye | Armenian | 1.0000 | 1.0000 | 1.0000 | 225 |
ido | Ido | 0.9731 | 0.9560 | 0.9645 | 341 |
ile | Interlingue | 0.9386 | 0.9450 | 0.9418 | 291 |
ilo | Ilocano | 0.9917 | 0.9677 | 0.9796 | 124 |
ina | Interlingua | 0.9602 | 0.9775 | 0.9688 | 444 |
ind | Indonesian | 0.8550 | 0.8305 | 0.8426 | 419 |
isl | Icelandic | 0.9874 | 0.9931 | 0.9902 | 869 |
ita | Italian | 0.9835 | 0.9746 | 0.9791 | 552 |
jav | Javanese | 0.9400 | 0.9792 | 0.9592 | 48 |
jbo | Lojban | 1.0000 | 1.0000 | 1.0000 | 402 |
jpn | Japanese | 0.9870 | 1.0000 | 0.9935 | 531 |
kab | Kabyle | 0.8382 | 0.9012 | 0.8686 | 506 |
kat | Georgian | 1.0000 | 0.9885 | 0.9942 | 260 |
kaz | Kazakh | 0.9896 | 0.9896 | 0.9896 | 192 |
kha | Khasi | 0.9038 | 0.9400 | 0.9216 | 100 |
khm | Khmer | 1.0000 | 1.0000 | 1.0000 | 75 |
kmr | Northern Kurdish (Kurmancî) | 0.9881 | 0.9793 | 0.9837 | 338 |
knc | Central Kanuri | 0.9775 | 1.0000 | 0.9886 | 174 |
kor | Korean | 1.0000 | 0.9806 | 0.9902 | 360 |
kzj | Coastal Kadazan | 0.9744 | 0.9580 | 0.9661 | 238 |
lad | Ladino | 0.8154 | 0.8281 | 0.8217 | 64 |
lat | Latin | 0.9756 | 0.9677 | 0.9717 | 496 |
lfn | Lingua Franca Nova | 0.9745 | 0.9768 | 0.9757 | 431 |
lij | Ligurian | 0.9556 | 0.9556 | 0.9556 | 90 |
lin | Lingala | 0.9859 | 0.9859 | 0.9859 | 213 |
lit | Lithuanian | 0.9903 | 0.9942 | 0.9922 | 513 |
ltz | Luxembourgish | 0.9773 | 0.9149 | 0.9451 | 47 |
lvs | Latvian | 0.9732 | 0.9797 | 0.9764 | 148 |
lzh | Literary Chinese | 0.7473 | 0.9444 | 0.8344 | 72 |
mal | Malayalam | 1.0000 | 1.0000 | 1.0000 | 44 |
mar | Marathi | 0.9961 | 1.0000 | 0.9980 | 509 |
mhr | Meadow Mari | 0.9899 | 0.9801 | 0.9850 | 201 |
mkd | Macedonian | 0.9630 | 0.9447 | 0.9538 | 524 |
mon | Mongolian | 0.9781 | 0.9710 | 0.9745 | 138 |
mus | Muskogee (Creek) | 0.9333 | 0.9655 | 0.9492 | 29 |
mya | Burmese | 1.0000 | 1.0000 | 1.0000 | 27 |
nds | Low German (Low Saxon) | 0.9829 | 0.9805 | 0.9817 | 410 |
nld | Dutch | 0.9681 | 0.9810 | 0.9745 | 526 |
nnb | Nande | 0.9896 | 0.9845 | 0.9870 | 387 |
nno | Norwegian Nynorsk | 0.9551 | 0.9685 | 0.9617 | 571 |
nob | Norwegian Bokmål | 0.9280 | 0.9168 | 0.9224 | 914 |
nst | Naga (Tangshang) | 1.0000 | 1.0000 | 1.0000 | 39 |
nus | Nuer | 0.9903 | 1.0000 | 0.9951 | 102 |
oci | Occitan | 0.9795 | 0.9598 | 0.9696 | 249 |
orv | Old East Slavic | 0.9846 | 1.0000 | 0.9922 | 64 |
oss | Ossetian | 0.9891 | 0.9963 | 0.9927 | 272 |
ota | Ottoman Turkish | 0.9469 | 0.9727 | 0.9596 | 110 |
pam | Kapampangan | 0.9865 | 0.9733 | 0.9799 | 75 |
pcd | Picard | 0.9552 | 0.9697 | 0.9624 | 66 |
pes | Persian | 0.9934 | 0.9956 | 0.9945 | 454 |
pms | Piedmontese | 0.9268 | 0.9744 | 0.9500 | 39 |
pol | Polish | 0.9886 | 0.9886 | 0.9886 | 525 |
por | Portuguese | 0.9669 | 0.9686 | 0.9677 | 542 |
prg | Old Prussian | 0.9800 | 0.9608 | 0.9703 | 51 |
rhg | Rohingya | 0.9890 | 1.0000 | 0.9945 | 180 |
rom | Romani | 0.9535 | 0.8913 | 0.9213 | 46 |
ron | Romanian | 0.9870 | 0.9785 | 0.9827 | 465 |
run | Kirundi | 0.9871 | 0.9746 | 0.9808 | 236 |
rus | Russian | 0.9671 | 0.9796 | 0.9733 | 540 |
sah | Yakut | 1.0000 | 1.0000 | 1.0000 | 48 |
sat | Santali | 1.0000 | 1.0000 | 1.0000 | 171 |
sdh | Southern Kurdish | 0.9808 | 0.9107 | 0.9444 | 56 |
shi | Tashelhit | 0.9779 | 0.9172 | 0.9466 | 145 |
slk | Slovak | 0.9235 | 0.9421 | 0.9327 | 397 |
slv | Slovenian | 0.7544 | 0.8958 | 0.8190 | 48 |
sma | Southern Sami | 0.9600 | 0.9600 | 0.9600 | 100 |
sme | Northern Sami | 1.0000 | 0.9901 | 0.9950 | 505 |
smj | Lule Sami | 0.9860 | 1.0000 | 0.9930 | 493 |
smn | Inari Sami | 0.9950 | 0.9950 | 0.9950 | 200 |
sms | Skolt Sami | 0.9850 | 0.9899 | 0.9875 | 199 |
spa | Spanish | 0.9779 | 0.9619 | 0.9698 | 551 |
sqi | Albanian | 0.9683 | 0.9839 | 0.9760 | 124 |
srp | Serbian | 0.8347 | 0.8313 | 0.8330 | 492 |
swc | Congo Swahili | 0.8750 | 0.8594 | 0.8671 | 448 |
swe | Swedish | 0.9809 | 0.9839 | 0.9824 | 991 |
swg | Swabian | 0.9898 | 0.9604 | 0.9749 | 101 |
swh | Swahili | 0.6946 | 0.7382 | 0.7157 | 191 |
tat | Tatar | 0.9817 | 0.9843 | 0.9830 | 382 |
tgl | Tagalog | 0.9830 | 0.9830 | 0.9830 | 412 |
tha | Thai | 1.0000 | 1.0000 | 1.0000 | 220 |
thv | Tahaggart Tamahaq | 0.7241 | 0.8400 | 0.7778 | 25 |
tig | Tigre | 1.0000 | 1.0000 | 1.0000 | 181 |
tlh | Klingon | 1.0000 | 1.0000 | 1.0000 | 439 |
tok | Toki Pona | 1.0000 | 1.0000 | 1.0000 | 495 |
tpw | Old Tupi | 0.8929 | 0.9615 | 0.9259 | 26 |
tuk | Turkmen | 0.9890 | 0.9711 | 0.9800 | 277 |
tur | Turkish | 0.9872 | 0.9659 | 0.9764 | 558 |
uig | Uyghur | 0.9966 | 0.9933 | 0.9950 | 299 |
ukr | Ukrainian | 0.9813 | 0.9850 | 0.9831 | 532 |
urd | Urdu | 1.0000 | 0.9914 | 0.9957 | 116 |
uzb | Uzbek | 0.8200 | 0.9762 | 0.8913 | 42 |
vie | Vietnamese | 0.9977 | 0.9977 | 0.9977 | 426 |
vol | Volapük | 0.9862 | 0.9908 | 0.9885 | 217 |
war | Waray | 0.9505 | 0.9796 | 0.9648 | 98 |
wuu | Shanghainese | 0.8364 | 0.9275 | 0.8796 | 193 |
xal | Kalmyk | 0.9302 | 0.9756 | 0.9524 | 41 |
xmf | Mingrelian | 0.7419 | 0.8519 | 0.7931 | 27 |
yid | Yiddish | 0.9971 | 1.0000 | 0.9986 | 348 |
yue | Cantonese | 0.9195 | 0.9877 | 0.9524 | 243 |
zgh | Standard Moroccan Tamazight | 0.9873 | 0.9873 | 0.9873 | 158 |
zlm | Malay (Vernacular) | 0.8605 | 0.9024 | 0.8810 | 82 |
zsm | Malay | 0.7782 | 0.7921 | 0.7851 | 279 |
zza | Zaza | 0.9294 | 0.9294 | 0.9294 | 85 |
Accuracy | 0.9620 | 44049 | |||
Weighted avg | 0.9627 | 0.9620 | 0.9621 | 44049 | |
Macro avg | 0.9434 | 0.9528 | 0.9476 | 44049 |
nb-nordic-lid.ftz
The small models are quantized versions of the large versions using a cutoff of 50,000 words and ngrams and quantizing the norm separately.
ISO-639-3 | Language | Precision | Recall | F1-Score | Support |
---|---|---|---|---|---|
dan | Danish | 0.9700 | 0.9838 | 0.9768 | 493 |
eng | English | 0.9980 | 0.9940 | 0.9960 | 502 |
fao | Faroese | 0.9920 | 0.9920 | 0.9920 | 500 |
fin | Finnish | 1.0000 | 1.0000 | 1.0000 | 500 |
isl | Icelandic | 0.9880 | 0.9920 | 0.9900 | 498 |
nno | Norwegian Nynorsk | 0.9880 | 0.9841 | 0.9860 | 502 |
nob | Norwegian Bokmål | 0.9860 | 0.9705 | 0.9782 | 508 |
sma | Southern Sami | 0.9800 | 0.9703 | 0.9751 | 101 |
sme | Northern Sami | 1.0000 | 0.9921 | 0.9960 | 504 |
smj | Lule Sami | 0.9920 | 0.9940 | 0.9930 | 499 |
smn | Inari Sami | 0.9950 | 1.0000 | 0.9975 | 199 |
sms | Skolt Sami | 0.9850 | 0.9949 | 0.9899 | 198 |
swe | Swedish | 0.9820 | 0.9899 | 0.9859 | 496 |
Accuracy | 0.9895 | 5500 | |||
Weighted avg | 0.9895 | 0.9895 | 0.9895 | 5500 | |
Macro avg | 0.9889 | 0.9890 | 0.9890 | 5500 |
nb-nordic-lid.159.ftz
Scores for the 159 languages (compressed model)
ISO-639-3 | Language | Precision | Recall | F1-Score | Support |
---|---|---|---|---|---|
afr | Afrikaans | 0.9529 | 0.9333 | 0.9430 | 195 |
ara | Arabic | 0.9708 | 0.9191 | 0.9443 | 507 |
arq | Algerian Arabic | 0.8783 | 0.8783 | 0.8783 | 115 |
arz | Egyptian Arabic | 0.5439 | 0.8378 | 0.6596 | 37 |
asm | Assamese | 0.9828 | 0.9448 | 0.9634 | 181 |
avk | Kotava | 0.9843 | 0.9792 | 0.9817 | 192 |
aze | Azerbaijani | 0.9582 | 0.9828 | 0.9703 | 233 |
bel | Belarusian | 0.9919 | 0.9683 | 0.9799 | 378 |
ben | Bengali | 0.9574 | 0.9868 | 0.9719 | 228 |
ber | Berber | 0.8495 | 0.7928 | 0.8202 | 584 |
bos | Bosnian | 0.1429 | 0.2264 | 0.1752 | 53 |
bre | Breton | 0.9507 | 0.9712 | 0.9609 | 278 |
bua | Buryat | 0.9333 | 0.9333 | 0.9333 | 45 |
bul | Bulgarian | 0.9351 | 0.9457 | 0.9404 | 442 |
cat | Catalan | 0.9406 | 0.9406 | 0.9406 | 303 |
cbk | Chavacano | 0.9552 | 0.9624 | 0.9588 | 133 |
ceb | Cebuano | 0.8718 | 0.8500 | 0.8608 | 80 |
ces | Czech | 0.9586 | 0.9548 | 0.9567 | 509 |
chv | Chuvash | 1.0000 | 0.9647 | 0.9820 | 85 |
ckb | Central Kurdish (Soranî) | 0.9640 | 0.9748 | 0.9694 | 357 |
ckt | Chukchi | 0.9615 | 1.0000 | 0.9804 | 25 |
cmn | Mandarin Chinese | 0.9667 | 0.8165 | 0.8853 | 605 |
cor | Cornish | 0.9780 | 0.9674 | 0.9727 | 184 |
csb | Kashubian | 0.9574 | 1.0000 | 0.9783 | 45 |
cym | Welsh | 0.9625 | 0.9506 | 0.9565 | 81 |
dan | Danish | 0.9281 | 0.9355 | 0.9318 | 993 |
deu | German | 0.9853 | 0.9781 | 0.9817 | 549 |
dsb | Lower Sorbian | 0.8889 | 0.8276 | 0.8571 | 58 |
dtp | Central Dusun | 0.8741 | 0.9470 | 0.9091 | 132 |
ell | Greek | 0.9958 | 0.9937 | 0.9947 | 476 |
eng | English | 0.9886 | 0.9876 | 0.9881 | 1050 |
epo | Esperanto | 0.9853 | 0.9818 | 0.9835 | 548 |
est | Estonian | 0.9489 | 0.9766 | 0.9625 | 171 |
eus | Basque | 0.9844 | 0.9583 | 0.9712 | 264 |
fao | Faroese | 0.9780 | 0.9819 | 0.9800 | 498 |
fin | Finnish | 0.9922 | 0.9724 | 0.9822 | 1050 |
fkv | Kven Finnish | 0.5385 | 0.7368 | 0.6222 | 19 |
fra | French | 0.9871 | 0.9728 | 0.9799 | 552 |
frr | North Frisian | 0.9640 | 0.9640 | 0.9640 | 139 |
fry | Frisian | 0.7097 | 0.8462 | 0.7719 | 26 |
gcf | Guadeloupean Creole French | 0.9714 | 0.9808 | 0.9761 | 104 |
gla | Scottish Gaelic | 0.9608 | 0.9608 | 0.9608 | 51 |
gle | Irish | 0.9489 | 0.9924 | 0.9701 | 131 |
glg | Galician | 0.8868 | 0.9082 | 0.8974 | 207 |
gos | Gronings | 0.9426 | 0.9544 | 0.9485 | 241 |
grc | Ancient Greek | 0.9483 | 0.9483 | 0.9483 | 58 |
grn | Guarani | 0.9684 | 0.9935 | 0.9808 | 154 |
guc | Wayuu | 0.9333 | 1.0000 | 0.9655 | 42 |
hau | Hausa | 0.9861 | 0.9884 | 0.9872 | 430 |
heb | Hebrew | 0.9981 | 0.9907 | 0.9944 | 540 |
hin | Hindi | 0.9974 | 0.9898 | 0.9936 | 393 |
hoc | Ho | 0.8571 | 1.0000 | 0.9231 | 30 |
hrv | Croatian | 0.6766 | 0.5911 | 0.6310 | 269 |
hrx | Hunsrik | 0.8545 | 0.9216 | 0.8868 | 51 |
hsb | Upper Sorbian | 0.8400 | 0.8182 | 0.8289 | 77 |
hun | Hungarian | 0.9816 | 0.9852 | 0.9834 | 541 |
hye | Armenian | 1.0000 | 1.0000 | 1.0000 | 225 |
ido | Ido | 0.9672 | 0.9501 | 0.9586 | 341 |
ile | Interlingue | 0.9352 | 0.9547 | 0.9448 | 287 |
ilo | Ilocano | 0.9917 | 0.9600 | 0.9756 | 125 |
ina | Interlingua | 0.9580 | 0.9558 | 0.9569 | 453 |
ind | Indonesian | 0.8231 | 0.8034 | 0.8131 | 417 |
isl | Icelandic | 0.9805 | 0.9885 | 0.9845 | 867 |
ita | Italian | 0.9817 | 0.9555 | 0.9684 | 562 |
jav | Javanese | 0.9400 | 0.9792 | 0.9592 | 48 |
jbo | Lojban | 1.0000 | 0.9975 | 0.9988 | 403 |
jpn | Japanese | 0.9684 | 0.9981 | 0.9830 | 522 |
kab | Kabyle | 0.7702 | 0.8516 | 0.8089 | 492 |
kat | Georgian | 1.0000 | 0.9847 | 0.9923 | 261 |
kaz | Kazakh | 0.9792 | 0.9843 | 0.9817 | 191 |
kha | Khasi | 0.8942 | 0.9300 | 0.9118 | 100 |
khm | Khmer | 1.0000 | 0.9868 | 0.9934 | 76 |
kmr | Northern Kurdish (Kurmancî) | 0.9791 | 0.9647 | 0.9719 | 340 |
knc | Central Kanuri | 0.9775 | 0.9943 | 0.9858 | 175 |
kor | Korean | 0.9972 | 0.9778 | 0.9874 | 360 |
kzj | Coastal Kadazan | 0.9658 | 0.9378 | 0.9516 | 241 |
lad | Ladino | 0.7538 | 0.8033 | 0.7778 | 61 |
lat | Latin | 0.9614 | 0.9594 | 0.9604 | 493 |
lfn | Lingua Franca Nova | 0.9722 | 0.9611 | 0.9666 | 437 |
lij | Ligurian | 0.8778 | 0.9753 | 0.9240 | 81 |
lin | Lingala | 0.9859 | 0.9677 | 0.9767 | 217 |
lit | Lithuanian | 0.9864 | 0.9864 | 0.9864 | 515 |
ltz | Luxembourgish | 0.9773 | 0.9149 | 0.9451 | 47 |
lvs | Latvian | 0.9597 | 0.9662 | 0.9630 | 148 |
lzh | Literary Chinese | 0.6593 | 0.8108 | 0.7273 | 74 |
mal | Malayalam | 1.0000 | 1.0000 | 1.0000 | 44 |
mar | Marathi | 0.9902 | 0.9980 | 0.9941 | 507 |
mhr | Meadow Mari | 0.9899 | 0.9752 | 0.9825 | 202 |
mkd | Macedonian | 0.9397 | 0.9253 | 0.9324 | 522 |
mon | Mongolian | 0.9781 | 0.9571 | 0.9675 | 140 |
mus | Muskogee (Creek) | 0.9000 | 0.9643 | 0.9310 | 28 |
mya | Burmese | 1.0000 | 1.0000 | 1.0000 | 27 |
nds | Low German (Low Saxon) | 0.9829 | 0.9687 | 0.9757 | 415 |
nld | Dutch | 0.9644 | 0.9735 | 0.9689 | 528 |
nnb | Nande | 0.9870 | 0.9896 | 0.9883 | 384 |
nno | Norwegian Nynorsk | 0.9499 | 0.9632 | 0.9565 | 571 |
nob | Norwegian Bokmål | 0.9324 | 0.9073 | 0.9197 | 928 |
nst | Naga (Tangshang) | 1.0000 | 0.9750 | 0.9873 | 40 |
nus | Nuer | 0.9903 | 1.0000 | 0.9951 | 102 |
oci | Occitan | 0.9631 | 0.9476 | 0.9553 | 248 |
orv | Old East Slavic | 0.9538 | 0.9254 | 0.9394 | 67 |
oss | Ossetian | 0.9818 | 0.9926 | 0.9872 | 271 |
ota | Ottoman Turkish | 0.9204 | 0.9455 | 0.9327 | 110 |
pam | Kapampangan | 0.9730 | 0.9600 | 0.9664 | 75 |
pcd | Picard | 0.9254 | 0.9688 | 0.9466 | 64 |
pes | Persian | 0.9846 | 0.9868 | 0.9857 | 454 |
pms | Piedmontese | 0.9024 | 0.9487 | 0.9250 | 39 |
pol | Polish | 0.9867 | 0.9885 | 0.9876 | 524 |
por | Portuguese | 0.9595 | 0.9577 | 0.9586 | 544 |
prg | Old Prussian | 0.9800 | 0.9423 | 0.9608 | 52 |
rhg | Rohingya | 0.9835 | 0.9835 | 0.9835 | 182 |
rom | Romani | 0.9302 | 0.8511 | 0.8889 | 47 |
ron | Romanian | 0.9783 | 0.9762 | 0.9772 | 462 |
run | Kirundi | 0.9871 | 0.9426 | 0.9644 | 244 |
rus | Russian | 0.9561 | 0.9757 | 0.9658 | 536 |
sah | Yakut | 0.9792 | 1.0000 | 0.9895 | 47 |
sat | Santali | 0.9942 | 1.0000 | 0.9971 | 170 |
sdh | Southern Kurdish | 0.8462 | 0.8627 | 0.8544 | 51 |
shi | Tashelhit | 0.9706 | 0.8980 | 0.9329 | 147 |
slk | Slovak | 0.9111 | 0.9318 | 0.9213 | 396 |
slv | Slovenian | 0.7018 | 0.9302 | 0.8000 | 43 |
sma | Southern Sami | 0.9500 | 0.9406 | 0.9453 | 101 |
sme | Northern Sami | 1.0000 | 0.9843 | 0.9921 | 508 |
smj | Lule Sami | 0.9840 | 0.9980 | 0.9909 | 493 |
smn | Inari Sami | 0.9850 | 0.9949 | 0.9899 | 198 |
sms | Skolt Sami | 0.9700 | 0.9848 | 0.9773 | 197 |
spa | Spanish | 0.9613 | 0.9560 | 0.9586 | 545 |
sqi | Albanian | 0.9603 | 0.9680 | 0.9641 | 125 |
srp | Serbian | 0.8122 | 0.8106 | 0.8114 | 491 |
swc | Congo Swahili | 0.8500 | 0.8367 | 0.8433 | 447 |
swe | Swedish | 0.9759 | 0.9778 | 0.9768 | 992 |
swg | Swabian | 0.9796 | 0.9320 | 0.9552 | 103 |
swh | Swahili | 0.6650 | 0.7068 | 0.6853 | 191 |
tat | Tatar | 0.9739 | 0.9816 | 0.9777 | 380 |
tgl | Tagalog | 0.9709 | 0.9732 | 0.9721 | 411 |
tha | Thai | 1.0000 | 1.0000 | 1.0000 | 220 |
thv | Tahaggart Tamahaq | 0.6552 | 0.7600 | 0.7037 | 25 |
tig | Tigre | 1.0000 | 1.0000 | 1.0000 | 181 |
tlh | Klingon | 0.9977 | 0.9955 | 0.9966 | 440 |
tok | Toki Pona | 1.0000 | 1.0000 | 1.0000 | 495 |
tpw | Old Tupi | 0.8214 | 0.8846 | 0.8519 | 26 |
tuk | Turkmen | 0.9779 | 0.9708 | 0.9744 | 274 |
tur | Turkish | 0.9780 | 0.9604 | 0.9691 | 556 |
uig | Uyghur | 0.9933 | 0.9900 | 0.9916 | 299 |
ukr | Ukrainian | 0.9682 | 0.9700 | 0.9691 | 533 |
urd | Urdu | 1.0000 | 0.9914 | 0.9957 | 116 |
uzb | Uzbek | 0.8000 | 0.9756 | 0.8791 | 41 |
vie | Vietnamese | 0.9977 | 0.9977 | 0.9977 | 426 |
vol | Volapük | 0.9862 | 0.9817 | 0.9840 | 219 |
war | Waray | 0.9208 | 0.9688 | 0.9442 | 96 |
wuu | Shanghainese | 0.8037 | 0.9053 | 0.8515 | 190 |
xal | Kalmyk | 0.9070 | 0.9512 | 0.9286 | 41 |
xmf | Mingrelian | 0.6774 | 0.8400 | 0.7500 | 25 |
yid | Yiddish | 0.9828 | 0.9942 | 0.9885 | 345 |
yue | Cantonese | 0.8314 | 0.9688 | 0.8948 | 224 |
zgh | Standard Moroccan Tamazight | 0.9873 | 0.9873 | 0.9873 | 158 |
zlm | Malay (Vernacular) | 0.8488 | 0.8588 | 0.8538 | 85 |
zsm | Malay | 0.7465 | 0.7544 | 0.7504 | 281 |
zza | Zaza | 0.8824 | 0.9146 | 0.8982 | 82 |
Accuracy | 0.9513 | 44049 | |||
Weighted avg | 0.9529 | 0.9513 | 0.9518 | 44049 | |
Macro avg | 0.9275 | 0.9399 | 0.9327 | 44049 |
Citing & Authors
The model was trained by Javier de la Rosa. Data was prepared by Per Egil Kummervold and Javier de la Rosa. Documentation written by Javier de la Rosa.
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