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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_bert_fine_tuned_ner
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8826268309
          - name: NER Recall
            type: recall
            value: 0.8940748747
          - name: NER F Score
            type: f_score
            value: 0.8883139705

This is a BERT model for Named Entity Recognition, fine-tuned on OntoNotes v5 using Spacy in coNLL-2003 format and BIO tagged. For more details: https://github.com/nicoladisabato/ner-with-transformers

Feature Description
Name en_bert_fine_tuned_ner
Version 0.0.0
spaCy >=3.5.0,<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 88.83
ENTS_P 88.26
ENTS_R 89.41
TRANSFORMER_LOSS 135007.00
NER_LOSS 132971.85