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---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_ner_prompting
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.7517301038
- name: NER Recall
type: recall
value: 0.7376910017
- name: NER F Score
type: f_score
value: 0.7446443873
---
| Feature | Description |
| --- | --- |
| **Name** | `en_ner_prompting` |
| **Version** | `0.0.2` |
| **spaCy** | `>=3.4.3,<3.5.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | MIT |
| **Author** | Selas.ai(https://www.selas.ai/) |
### Label Scheme
<details>
<summary>View label scheme (1 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `FASHION_BRAND` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 71.02 |
| `ENTS_P` | 73.76 |
| `ENTS_R` | 68.49 |
| `TOK2VEC_LOSS` | 2670.31 |
| `NER_LOSS` | 913.14 | |