en_pipeline / README.md
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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_pipeline
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.9334257975
          - name: NER Recall
            type: recall
            value: 0.9734811958
          - name: NER F Score
            type: f_score
            value: 0.9530328062
Feature Description
Name en_pipeline
Version 0.0.0
spaCy >=3.8.7,<3.9.0
Default Pipeline transformer, ner
Components transformer, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources n/a
License n/a
Author n/a

Label Scheme

View label scheme (11 labels for 1 components)
Component Labels
ner College Name, Companies worked at, Degree, Designation, Email Address, Graduation Year, Location, Name, Skills, UNKNOWN, Years of Experience

Accuracy

Type Score
ENTS_F 95.30
ENTS_P 93.34
ENTS_R 97.35
TRANSFORMER_LOSS 2380063.94
NER_LOSS 1373288.48