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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_xlnet_fine_tuned_ner
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8847416707
          - name: NER Recall
            type: recall
            value: 0.9002161737
          - name: NER F Score
            type: f_score
            value: 0.8924118449
Feature Description
Name en_xlnet_fine_tuned_ner
Version 0.0.0
spaCy >=3.5.1,<3.6.0
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 (18 labels for 1 components)
Component Labels
ner CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART

Accuracy

Type Score
ENTS_F 89.24
ENTS_P 88.47
ENTS_R 90.02
TRANSFORMER_LOSS 124848.21
NER_LOSS 196123.19