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--- |
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language: |
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- pt |
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license: cc-by-4.0 |
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datasets: |
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- wiki_lingua |
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thumbnail: null |
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tags: |
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- named-entity-recognition |
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- Transformer |
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- pytorch |
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- bert |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: rpunct-ptbr |
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results: |
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- task: |
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type: named-entity-recognition |
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dataset: |
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type: wiki_lingua |
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name: wiki_lingua |
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metrics: |
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- type: f1 |
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value: 55.70 |
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name: F1 Score |
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- type: precision |
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value: 57.72 |
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name: Precision |
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- type: recall |
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value: 53.83 |
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name: Recall |
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widget: |
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- text: "henrique foi no lago pescar com o pedro mais tarde foram para a casa do pedro fritar os peixes" |
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- text: "cinco trabalhadores da construção civil em capacetes e coletes amarelos estão ocupados no trabalho" |
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- text: "na quinta feira em visita a belo horizonte pedro sobrevoa a cidade atingida pelas chuvas" |
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- text: "coube ao representante de classe contar que na avaliação de língua portuguesa alguns alunos se mantiveram concentrados e outros dispersos" |
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--- |
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# 🤗 bert-restore-punctuation-ptbr |
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* 🪄 [W&B Dashboard](https://wandb.ai/dominguesm/RestorePunctuationPTBR) |
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* ⛭ [GitHub](https://github.com/DominguesM/respunct) |
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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). |
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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. |
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Model restores the following punctuations -- **[! ? . , - : ; ' ]** |
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The model also restores the upper-casing of words. |
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----------------------------------------------- |
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## 🤷 Usage |
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🇧🇷 easy-to-use package to restore punctuation of portuguese texts. |
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**Below is a quick way to use the template.** |
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1. First, install the package. |
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``` |
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pip install respunct |
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``` |
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2. Sample python code. |
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``` python |
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from respunct import RestorePuncts |
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model = RestorePuncts() |
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model.restore_puncts(""" |
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henrique foi no lago pescar com o pedro mais tarde foram para a casa do pedro fritar os peixes""") |
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# output: |
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# Henrique foi no lago pescar com o Pedro. Mais tarde, foram para a casa do Pedro fritar os peixes. |
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``` |
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## 🎯 Accuracy |
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| label | precision | recall | f1-score | support| |
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| ------------------------- | -------------|-------- | ----------|--------| |
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| **Upper - OU** | 0.89 | 0.91 | 0.90 | 69376 |
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| **None - OO** | 0.99 | 0.98 | 0.98 | 857659 |
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| **Full stop/period - .O** | 0.86 | 0.93 | 0.89 | 60410 |
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| **Comma - ,O** | 0.85 | 0.83 | 0.84 | 48608 |
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| **Upper + Comma - ,U** | 0.73 | 0.76 | 0.75 | 3521 |
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| **Question - ?O** | 0.68 | 0.78 | 0.73 | 1168 |
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| **Upper + period - .U** | 0.66 | 0.72 | 0.69 | 1884 |
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| **Upper + colon - :U** | 0.59 | 0.63 | 0.61 | 352 |
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| **Colon - :O** | 0.70 | 0.53 | 0.60 | 2420 |
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| **Question Mark - ?U** | 0.50 | 0.56 | 0.53 | 36 |
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| **Upper + Exclam. - !U** | 0.38 | 0.32 | 0.34 | 38 |
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| **Exclamation Mark - !O** | 0.30 | 0.05 | 0.08 | 783 |
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| **Semicolon - ;O** | 0.35 | 0.04 | 0.08 | 1557 |
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| **Apostrophe - 'O** | 0.00 | 0.00 | 0.00 | 3 |
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| **Hyphen - -O** | 0.00 | 0.00 | 0.00 | 3 |
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| | | | | |
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| **accuracy** | | | 0.96 | 1047818 |
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| **macro avg** | 0.57 | 0.54 | 0.54 | 1047818 |
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| **weighted avg** | 0.96 | 0.96 | 0.96 | 1047818 |
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----------------------------------------------- |
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## 🤙 Contact |
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[Maicon Domingues](dominguesm@outlook.com) for questions, feedback and/or requests for similar models. |
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