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---
tags:
- spacy
- token-classification
language:
- es
license: mit
model-index:
- name: es_neg_uncert_ehr_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8964797136
- name: NER Recall
type: recall
value: 0.8997005988
- name: NER F Score
type: f_score
value: 0.8980872684
---
| Feature | Description |
| --- | --- |
| **Name** | `es_neg_uncert_ehr_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.7.2,<3.8.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | `mit` |
| **Author** | [Álvaro García Barragán](Alvaro8gb/NegUncertaintyNER) |
### Label Scheme
<details>
<summary>View label scheme (4 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `NEG`, `NSCO`, `UNC`, `USCO` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 89.81 |
| `ENTS_P` | 89.65 |
| `ENTS_R` | 89.97 |
| `TRANSFORMER_LOSS` | 34598.52 |
| `NER_LOSS` | 35036.89 | |