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Modelo para Reconhecimento de Entidade Nomeadas em português utilizando o modelo spaCy pt_core_news_lg

Link do trabalho no Kaggle: https://www.kaggle.com/datasets/flaviagg/lenerbr .

Criei um Web App que proporciona a comparação dos modelos sm e lg: https://huggingface.co/spaces/flaviaggp/Streamlit_Lener .

Métricas por entidade

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Feature Description
Name pt_lg_pipeline
Version 0.0.0
spaCy >=3.4.4,<3.5.0
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 (6 labels for 1 components)
Component Labels
ner JURISPRUDENCIA, LEGISLACAO, LOCAL, ORGANIZACAO, PESSOA, TEMPO

Accuracy

Type Score
ENTS_F 83.79
ENTS_P 83.98
ENTS_R 83.61
TOK2VEC_LOSS 23620.33
NER_LOSS 127975.46
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Dataset used to train flaviaggp/pt_lg_pipeline

Space using flaviaggp/pt_lg_pipeline 1

Evaluation results