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tags:
- spacy
- token-classification
language:
- vi
model-index:
- name: vi_task_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8979591837
- name: NER Recall
type: recall
value: 0.8979591837
- name: NER F Score
type: f_score
value: 0.8979591837
---
This is ner model for task
| Feature | Description |
| --- | --- |
| **Name** | `vi_task_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.7.5,<3.8.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [Chánh Hỷ]() |
### Label Scheme
<details>
<summary>View label scheme (5 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `DATE`, `LOCATION`, `PERSON`, `TASK`, `TIME` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 89.80 |
| `ENTS_P` | 89.80 |
| `ENTS_R` | 89.80 |
| `TOK2VEC_LOSS` | 19657.96 |
| `NER_LOSS` | 12221.95 | |