en_core_web_md

---

tags:

• spacy
• token-classification language:
• en license: mit model-index:
• name: en_core_web_md results:
  • task: name: NER type: token-classification metrics:
    • name: NER Precision type: precision value: 0.8531330602
    • name: NER Recall type: recall value: 0.8448016827
    • name: NER F Score type: f_score value: 0.8489469314
  • task: name: POS type: token-classification metrics:
    • name: POS Accuracy type: accuracy value: 0.9736958159
  • task: name: SENTER type: token-classification metrics:
    • name: SENTER Precision type: precision value: 0.9144345238
    • name: SENTER Recall type: recall value: 0.8918134442
    • name: SENTER F Score type: f_score value: 0.9029823331
  • task: name: UNLABELED_DEPENDENCIES type: token-classification metrics:
    • name: Unlabeled Dependencies Accuracy type: accuracy value: 0.9186827918
  • task: name: LABELED_DEPENDENCIES type: token-classification metrics:
    • name: Labeled Dependencies Accuracy type: accuracy value: 0.9186827918

---

Details: https://spacy.io/models/en#en_core_web_md

English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.

Label Scheme

<details> <summary>View label scheme (114 labels for 4 components)</summary> </details>

Accuracy