readme: ---
  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: 55.70
          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](https://wandb.ai/dominguesm/RestorePunctuationPTBR)
  * ⛭ [GitHub](https://github.com/DominguesM/respunct)
  
  
  This is a [bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) model finetuned for punctuation restoration on [WikiLingua](https://github.com/esdurmus/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.**
  
  1. First, install the package.
  
  ```
  pip install respunct
  ```
  
  2. Sample python code.
  
  ``` python
  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](dominguesm@outlook.com) for questions, feedback and/or requests for similar models.
  