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This model was trained to identify articles quoted in brazilian legal documents.


tags: - spacy - token-classification language: - pt model-index: - name: pt_pipeline results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.4862058736 - name: NER Recall type: recall value: 0.8215538847 - name: NER F Score type: f_score value: 0.6108833395

Feature Description
Name pt_pipeline
Version 0.0.0
spaCy >=3.6.1,<3.7.0
Default Pipeline tok2vec, ner
Components tok2vec, ner
Vectors 500000 keys, 500000 unique vectors (300 dimensions)
Sources n/a
License n/a
Author n/a

Label Scheme

View label scheme (1 labels for 1 components)
Component Labels
ner ARTICLE

Accuracy

Type Score
ENTS_F 61.09
ENTS_P 48.62
ENTS_R 82.16
TOK2VEC_LOSS 2327.02
NER_LOSS 50668.25
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