---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_ner_fashion
  results:
  - task:
      name: NER
      type: token-classification
      metrics:
      - name: Precision
        type: precision
        value: 0.0
      - name: Recall
        type: recall
        value: 0.0
      - name: F Score
        type: f_score
        value: 0.0
---
| Feature | Description |
| --- | --- |
| **Name** | `en_ner_fashion` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.1.0,<3.2.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 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`** | `FASHION_BRAND` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 0.00 |
| `ENTS_P` | 0.00 |
| `ENTS_R` | 0.00 |
| `TOK2VEC_LOSS` | 1043.55 |
| `NER_LOSS` | 1414323.43 |
{"language": ["en"], "license": "mit", "tags": ["spacy", "token-classification"]}
spacy token-classification en license:mit model-index region:us
TAGS
#spacy #token-classification #en #license-mit #model-index #region-us 



---


tags:


* spacy
* token-classification
language:
* en
model-index:
* name: en\_ner\_fashion
results:
	+ task:
	name: NER
	type: token-classification
	metrics:
		- name: Precision
		type: precision
		value: 0.0
		- name: Recall
		type: recall
		value: 0.0
		- name: F Score
		type: f\_score
		value: 0.0




---



### Label Scheme



View label scheme (1 labels for 1 components)


### Accuracy




### Label Scheme



View label scheme (1 labels for 1 components) ### Accuracy
TAGS
#spacy #token-classification #en #license-mit #model-index #region-us 
 ### Label Scheme



View label scheme (1 labels for 1 components) ### Accuracy
passage: TAGS
#spacy #token-classification #en #license-mit #model-index #region-us 
### Label Scheme



View label scheme (1 labels for 1 components)### Accuracy