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README.md

language

datasets

widget

Jean-Baptiste/wikiner_fr

text
Je m'appelle Jean-Baptiste et je vis à Paris

camembert-ner: model fine-tuned from camemBERT for NER task.

Introduction

[camembert-ner] is a NER model that was fine-tuned from camemBERT on wikiner-fr dataset. Model was trained on subset of wikiner-fr dataset (~36 000 sentences)

How to use camembert-ner with HuggingFace

Load camembert-ner and its sub-word tokenizer :

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("Jean-Baptiste/camembert-ner")
model = AutoModelForTokenClassification.from_pretrained("Jean-Baptiste/camembert-ner")


##### Process text sample (from wikipedia)

from transformers import pipeline

nlp = pipeline('ner', model=model, tokenizer=tokenizer, grouped_entities=True)
nlp("Apple est créée le 1er avril 1976 dans le garage de la maison d'enfance de Steve Jobs à Los Altos en Californie par Steve Jobs, Steve Wozniak et Ronald Wayne14, puis constituée sous forme de société le 3 janvier 1977 à l'origine sous le nom d'Apple Computer, mais pour ses 30 ans et pour refléter la diversification de ses produits, le mot « computer » est retiré le 9 janvier 2015.")


[{'entity_group': 'ORG',
  'score': 0.9472818374633789,
  'word': 'Apple',
  'start': 0,
  'end': 5},
 {'entity_group': 'PER',
  'score': 0.9838564991950989,
  'word': 'Steve Jobs',
  'start': 74,
  'end': 85},
 {'entity_group': 'LOC',
  'score': 0.9831605950991312,
  'word': 'Los Altos',
  'start': 87,
  'end': 97},
 {'entity_group': 'LOC',
  'score': 0.9834540486335754,
  'word': 'Californie',
  'start': 100,
  'end': 111},
 {'entity_group': 'PER',
  'score': 0.9841555754343668,
  'word': 'Steve Jobs',
  'start': 115,
  'end': 126},
 {'entity_group': 'PER',
  'score': 0.9843501806259155,
  'word': 'Steve Wozniak',
  'start': 127,
  'end': 141},
 {'entity_group': 'PER',
  'score': 0.9841533899307251,
  'word': 'Ronald Wayne',
  'start': 144,
  'end': 157},
 {'entity_group': 'ORG',
  'score': 0.9468960364659628,
  'word': 'Apple Computer',
  'start': 243,
  'end': 257}]

Model performances (metric: seqeval)

Global

'precision': 0.8830965723967158
'recall': 0.8915789473684211
'f1': 0.8873174883781837

By entity

'LOC': {'precision': 0.8701754385964913,
        'recall': 0.8878281622911695,
        'f1': 0.8789131718842291},
'MISC': {'precision': 0.831053901850362,
         'recall': 0.815955766192733,
          'f1': 0.823435631725787},
'ORG': {'precision': 0.8620199146514936,
        'recall': 0.8335625859697386,
         'f1': 0.8475524475524475},
 'PER': {'precision': 0.9367143476376246,
         'recall': 0.9583148558758315,
         'f1': 0.947391494958}