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metadata
tags:
  - spacy
  - token-classification
  - ner
  - named-entity-recognition
language:
  - en
model-index:
  - name: en_roberta_fine_tuned_ner
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8937349752
          - name: NER Recall
            type: recall
            value: 0.8950083522
          - name: NER F Score
            type: f_score
            value: 0.8943712104

This is a roBERTa 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_roberta_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 Nicola Disabato

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 89.44
ENTS_P 89.37
ENTS_R 89.50
TRANSFORMER_LOSS 294822.05
NER_LOSS 316133.78