This model was trained to identify articles quoted in brazilian legal documents.
tags:
- spacy
- token-classification language:
- pt model-index:
- name: pt_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision type: precision value: 0.4862058736
- name: NER Recall type: recall value: 0.8215538847
- name: NER F Score type: f_score value: 0.6108833395
- task:
name: NER
type: token-classification
metrics:
| Feature | Description |
|---|---|
| Name | pt_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.6.1,<3.7.0 |
| 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
<details>
<summary>View label scheme (1 labels for 1 components)</summary>
| Component | Labels |
|---|---|
ner |
ARTICLE |
</details>
Accuracy
| Type | Score |
|---|---|
ENTS_F |
61.09 |
ENTS_P |
48.62 |
ENTS_R |
82.16 |
TOK2VEC_LOSS |
2327.02 |
NER_LOSS |
50668.25 |