metadata

language:
  - pt
license: cc-by-4.0
datasets:
  - wiki_lingua
thumbnail: null
tags:
  - named-entity-recognition
  - Transformer
  - pytorch
  - bert
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: rpunct-ptbr
    results:
      - task:
          type: named-entity-recognition
        dataset:
          type: wiki_lingua
          name: wiki_lingua
        metrics:
          - type: f1
            value: 55.7
            name: F1 Score
          - type: precision
            value: 57.72
            name: Precision
          - type: recall
            value: 53.83
            name: Recall
widget:
  - text: >-
      henrique foi no lago pescar com o pedro mais tarde foram para a casa do
      pedro fritar os peixes
  - text: >-
      cinco trabalhadores da construção civil em capacetes e coletes amarelos
      estão ocupados no trabalho
  - text: >-
      na quinta feira em visita a belo horizonte pedro sobrevoa a cidade
      atingida pelas chuvas
  - text: >-
      coube ao representante de classe contar que na avaliação de língua
      portuguesa alguns alunos se mantiveram concentrados e outros dispersos

🤗 bert-restore-punctuation-ptbr

🪄 W&B Dashboard
⛭ GitHub

This is a bert-base-portuguese-cased model finetuned for punctuation restoration on WikiLingua.

This model is intended for direct use as a punctuation restoration model for the general Portuguese language. Alternatively, you can use this for further fine-tuning on domain-specific texts for punctuation restoration tasks.

Model restores the following punctuations -- [! ? . , - : ; ' ]

The model also restores the upper-casing of words.

🤷 Usage

🇧🇷 easy-to-use package to restore punctuation of portuguese texts.

Below is a quick way to use the template.

First, install the package.

pip install respunct

Sample python code.

from respunct import RestorePuncts

model = RestorePuncts()

model.restore_puncts("""
henrique foi no lago pescar com o pedro mais tarde foram para a casa do pedro fritar os peixes""")
# output:
# Henrique foi no lago pescar com o Pedro. Mais tarde, foram para a casa do Pedro fritar os peixes.

🎯 Accuracy

label	precision	recall	f1-score	support
Upper - OU	0.89	0.91	0.90	69376
None - OO	0.99	0.98	0.98	857659
Full stop/period - .O	0.86	0.93	0.89	60410
Comma - ,O	0.85	0.83	0.84	48608
Upper + Comma - ,U	0.73	0.76	0.75	3521
Question - ?O	0.68	0.78	0.73	1168
Upper + period - .U	0.66	0.72	0.69	1884
Upper + colon - :U	0.59	0.63	0.61	352
Colon - :O	0.70	0.53	0.60	2420
Question Mark - ?U	0.50	0.56	0.53	36
Upper + Exclam. - !U	0.38	0.32	0.34	38
Exclamation Mark - !O	0.30	0.05	0.08	783
Semicolon - ;O	0.35	0.04	0.08	1557
Apostrophe - 'O	0.00	0.00	0.00	3
Hyphen - -O	0.00	0.00	0.00	3

accuracy			0.96	1047818
macro avg	0.57	0.54	0.54	1047818
weighted avg	0.96	0.96	0.96	1047818

🤙 Contact

Maicon Domingues for questions, feedback and/or requests for similar models.