en_Task3_pipeline / README.md
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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_Task3_pipeline
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.883527267
          - name: NER Recall
            type: recall
            value: 0.9118275574
          - name: NER F Score
            type: f_score
            value: 0.8974543626
Feature Description
Name en_Task3_pipeline
Version 0.0.0
spaCy >=3.6.1,<3.7.0
Default Pipeline tok2vec, ner
Components tok2vec, ner
Vectors 514157 keys, 514157 unique vectors (300 dimensions)
Sources n/a
License n/a
Author n/a

Label Scheme

View label scheme (4 labels for 1 components)
Component Labels
ner Allergy, Cancer, Chronic Disease, Treatment

Accuracy

Type Score
ENTS_F 89.75
ENTS_P 88.35
ENTS_R 91.18
TOK2VEC_LOSS 42393.86
NER_LOSS 790020.07