---
tags:
- spacy
- token-classification
- text-classification
language:
- en
model-index:
- name: en_generic
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.8626560726
    - name: NER Recall
      type: recall
      value: 0.8315098468
    - name: NER F Score
      type: f_score
      value: 0.8467966574
---
| Feature | Description |
| --- | --- |
| **Name** | `en_generic` |
| **Version** | `0.0.1` |
| **spaCy** | `>=3.7.5,<3.8.0` |
| **Default Pipeline** | `tok2vec`, `ner`, `textcat` |
| **Components** | `tok2vec`, `ner`, `textcat` |
| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (51 labels for 2 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `AGE`, `BRAND`, `CAPACITY`, `CLOCK_SPEED`, `COLOR`, `CORE_COUNT`, `DECORATION`, `FEATURE`, `FIT`, `GEN`, `GENDER`, `GRAPHICS`, `GRAPHICS_RAM`, `LENGTH`, `MATERIAL`, `MEASUREMENT`, `MEASUREMENT_AREA`, `MODEL`, `MODEL_NUMBER`, `NECKLINE`, `OPERATING_SYSTEM`, `PATTERN`, `PROCESSOR`, `PROCESSOR_MODEL`, `PRODUCT_SERIES`, `RAM`, `RESOLUTION`, `SCREEN_SIZE`, `SCREEN_TYPE`, `SIZE`, `SLEEVE`, `STORAGE`, `STORAGE_TYPE`, `TAG`, `TYPE`, `ZIP` |
| **`textcat`** | `100`, `187`, `204`, `207`, `211`, `212`, `267`, `325`, `328`, `2271`, `2331`, `5250`, `5424`, `5598`, `6228` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 84.68 |
| `ENTS_P` | 86.27 |
| `ENTS_R` | 83.15 |
| `CATS_SCORE` | 95.82 |
| `CATS_MICRO_P` | 96.90 |
| `CATS_MICRO_R` | 96.90 |
| `CATS_MICRO_F` | 96.90 |
| `CATS_MACRO_P` | 96.76 |
| `CATS_MACRO_R` | 95.22 |
| `CATS_MACRO_F` | 95.82 |
| `CATS_MACRO_AUC` | 99.85 |
| `TOK2VEC_LOSS` | 4855291.83 |
| `NER_LOSS` | 58817.60 |
| `TEXTCAT_LOSS` | 0.37 |