Edit model card

Details: https://spacy.io/models/mk#mk_core_news_sm

Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.

Feature Description
Name mk_core_news_sm
Version 3.7.0
spaCy >=3.7.0,<3.8.0
Default Pipeline morphologizer, parser, attribute_ruler, lemmatizer, ner
Components morphologizer, parser, senter, attribute_ruler, lemmatizer, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska)
spaCy lookups data (Explosion)
License CC BY-SA 4.0
Author Explosion

Label Scheme

View label scheme (54 labels for 3 components)
Component Labels
morphologizer POS=PROPN, POS=AUX, POS=ADJ, POS=NOUN, POS=ADP, POS=PUNCT, POS=CONJ, POS=NUM, POS=VERB, POS=PRON, POS=ADV, POS=SCONJ, POS=PART, POS=SYM, _, POS=SPACE, POS=X, POS=INTJ
parser ROOT, advmod, att, aux, cc, dep, det, dobj, iobj, neg, nsubj, pobj, poss, pozm, pozv, prep, punct, relcl
ner CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART

Accuracy

Type Score
TOKEN_ACC 100.00
TOKEN_P 100.00
TOKEN_R 100.00
TOKEN_F 100.00
SENTS_P 76.06
SENTS_R 70.13
SENTS_F 72.97
DEP_UAS 64.64
DEP_LAS 47.54
ENTS_P 72.65
ENTS_R 70.98
ENTS_F 71.80
POS_ACC 91.99
Downloads last month
39
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Evaluation results