readme: ---
  tags:
  - spacy
  - token-classification
  language:
  - hu
  license: cc-by-sa-4.0
  model-index:
  - name: hu_core_news_md
    results:
    - task:
        name: NER
        type: token-classification
      metrics:
      - name: NER Precision
        type: precision
        value: 0.8538804639
      - name: NER Recall
        type: recall
        value: 0.8414205345
      - name: NER F Score
        type: f_score
        value: 0.8476047109
    - task:
        name: TAG
        type: token-classification
      metrics:
      - name: TAG (XPOS) Accuracy
        type: accuracy
        value: 0.9619102306
    - task:
        name: POS
        type: token-classification
      metrics:
      - name: POS (UPOS) Accuracy
        type: accuracy
        value: 0.9619102306
    - task:
        name: MORPH
        type: token-classification
      metrics:
      - name: Morph (UFeats) Accuracy
        type: accuracy
        value: 0.9279356876
    - task:
        name: LEMMA
        type: token-classification
      metrics:
      - name: Lemma Accuracy
        type: accuracy
        value: 0.9716773514
    - task:
        name: UNLABELED_DEPENDENCIES
        type: token-classification
      metrics:
      - name: Unlabeled Attachment Score (UAS)
        type: f_score
        value: 0.8106528823
    - task:
        name: LABELED_DEPENDENCIES
        type: token-classification
      metrics:
      - name: Labeled Attachment Score (LAS)
        type: f_score
        value: 0.7407573885
    - task:
        name: SENTS
        type: token-classification
      metrics:
      - name: Sentences F-Score
        type: f_score
        value: 0.9719416386
  ---
  Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner
  
  | Feature | Description |
  | --- | --- |
  | **Name** | `hu_core_news_md` |
  | **Version** | `3.4.2` |
  | **spaCy** | `>=3.4.0,<3.5.0` |
  | **Default Pipeline** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `lemmatizer`, `lemma_smoother`, `parser`, `ner` |
  | **Components** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `lemmatizer`, `lemma_smoother`, `parser`, `ner` |
  | **Vectors** | -1 keys, 200000 unique vectors (100 dimensions) |
  | **Sources** | [UD Hungarian Szeged](https://universaldependencies.org/treebanks/hu_szeged/index.html) (Richárd Farkas, Katalin Simkó, Zsolt Szántó, Viktor Varga, Veronika Vincze (MTA-SZTE Research Group on Artificial Intelligence))<br />[NYTK-NerKor Corpus](https://github.com/nytud/NYTK-NerKor) (Eszter Simon, Noémi Vadász (Department of Language Technology and Applied Linguistics))<br />[hunNERwiki](http://hlt.sztaki.hu/resources/hunnerwiki.html) (Eszter Simon, Dávid Márk Nemeskey (HLT Group, Budapest University of Technology and Economics))<br />[Szeged NER Corpus](https://rgai.inf.u-szeged.hu/node/130) (György Szarvas, Richárd Farkas, László Felföldi, András Kocsor, János Csirik (MTA-SZTE Research Group on Artificial Intelligence)) |
  | **License** | `cc-by-sa-4.0` |
  | **Author** | [SzegedAI, MILAB](https://github.com/huspacy/huspacy) |
  
  ### Label Scheme
  
  <details>
  
  <summary>View label scheme (1209 labels for 4 components)</summary>
  
  | Component | Labels |
  | --- | --- |
  | **`tagger`** | `ADJ`, `ADP`, `ADV`, `AUX`, `CCONJ`, `DET`, `INTJ`, `NOUN`, `NUM`, `PART`, `PRON`, `PROPN`, `PUNCT`, `SCONJ`, `SYM`, `VERB`, `X` |
  | **`morphologizer`** | `Definite=Def\|POS=DET\|PronType=Art`, `Case=Ine\|Number=Sing\|POS=NOUN`, `POS=ADV`, `Case=Nom\|NumType=Card\|Number=Sing\|POS=NUM`, `Case=Nom\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Nom\|Number=Sing\|POS=ADJ\|VerbForm=PartPres`, `Case=Nom\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Nom\|Number=Sing\|POS=NOUN`, `Definite=Ind\|POS=DET\|PronType=Tot`, `Case=Ade\|Number=Sing\|POS=NOUN`, `Case=Nom\|Degree=Cmp\|Number=Sing\|POS=ADJ`, `POS=PUNCT`, `Case=Nom\|Number=Sing\|POS=DET\|Person=3\|PronType=Dem`, `Case=Acc\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=3`, `Definite=Ind\|POS=DET\|PronType=Ind`, `Definite=Def\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `POS=ADP`, `POS=CCONJ`, `Case=Del\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=3\|PronType=Dem`, `Case=Sbl\|Number=Sing\|POS=NOUN`, `Case=Nom\|Number=Sing\|POS=ADJ\|VerbForm=PartPast`, `Case=Del\|Number=Plur\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Nom\|Number=Sing\|POS=PROPN`, `Definite=Ind\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Past\|VerbForm=Fin\|Voice=Act`, `Case=Acc\|Number=Sing\|POS=NOUN`, `Case=Sup\|Number=Sing\|POS=PROPN`, `Case=Ess\|Degree=Pos\|Number=Sing\|POS=ADJ`, `Case=Ine\|Number=Sing\|Number[psor]=Sing\|POS=NOUN\|Person[psor]=3`, `Case=Sup\|Number=Plur\|POS=NOUN`, `Degree=Pos\|POS=ADV`, `Case=Sup\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Mood=Ind\|Number=Sing\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, `Case=Cau\|Number=Plur\|POS=NOUN`, `Case=Cau\|Number=Sing\|POS=NOUN`, `Case=Gen\|Number=Sing\|POS=NOUN`, `Definite=Ind\|Mood=Ind\|Number=Plur\|POS=VERB\|Person=3\|Tense=Pres\|VerbForm=Fin\|Voice=Act`, 