license: agpl-3.0
language:
- pt
- gl
widget:
- text: >-
A minha amiga Rosa, de São Paulo, estudou en Montreal. Agora trabalha em
Santiago de Compostela com o Mário.
Named Entity Recognition (NER) model for Portuguese
This is a NER model for Portuguese which uses the standard 'enamex' classes: LOC (geographical locations); PER (people); ORG (organizations); MISC (other entities).
The model is based on BERTimbau Base, which has been fine-tuned using a combination of available corpora (see [1] for details).
There is an alternative model trained using BERTimbau Large: bert-large-pt-ner-enamex.
It was trained with a batch size of 8 and a learning rate of 2e-5 during 3 epochs. It achieved the following results on the test set (Precision/Recall/F1): 0.913/0.918/0.915.
[1] Pablo Gamallo, Marcos Garcia & Patricia Martín-Rodilla, 2019. NER and open information extraction for Portuguese notebook for IberLEF 2019 Portuguese named entity recognition and relation extraction tasks. In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2019) co-located with 35th Conference of the Spanish Society for Natural Language Processing (SEPLN 2019): 457-467.