| --- |
| tags: |
| - spacy |
| - token-classification |
| language: |
| - es |
| model-index: |
| - name: es_COLNER |
| results: |
| - task: |
| name: NER |
| type: token-classification |
| metrics: |
| - name: NER Precision |
| type: precision |
| value: 0.9414893617 |
| - name: NER Recall |
| type: recall |
| value: 0.8939393939 |
| - name: NER F Score |
| type: f_score |
| value: 0.9170984456 |
| --- |
| | Feature | Description | |
| | --- | --- | |
| | **Name** | `es_COLNER` | |
| | **Version** | `0.0.0` | |
| | **spaCy** | `>=3.7.5,<3.8.0` | |
| | **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`** | `LOC` | |
|
|
| </details> |
|
|
| ### Accuracy |
|
|
| | Type | Score | |
| | --- | --- | |
| | `ENTS_F` | 91.71 | |
| | `ENTS_P` | 94.15 | |
| | `ENTS_R` | 89.39 | |
| | `TOK2VEC_LOSS` | 2941.78 | |
| | `NER_LOSS` | 38738.45 | |
