---
tags:
- spacy
- token-classification
- text-classification
language:
- en
model-index:
- name: en_generic_big
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.9469753547
    - name: NER Recall
      type: recall
      value: 0.9399555226
    - name: NER F Score
      type: f_score
      value: 0.943452381
---
| Feature | Description |
| --- | --- |
| **Name** | `en_generic_big` |
| **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 (35 labels for 2 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `AGE`, `BRAND`, `CLOCK_SPEED`, `COLOR`, `CORE_COUNT`, `DECORATION`, `FEATURE`, `FIT`, `GENDER`, `GRAPHICS`, `GRAPHICS_RAM`, `MATERIAL`, `MEASUREMENT`, `MEASUREMENT_AREA`, `MEM_TYPE`, `MODEL_NUMBER`, `NECKLINE`, `OPERATING_SYSTEM`, `PROCESSOR`, `PROCESSOR_MODEL`, `PRODUCT_SERIES`, `RAM`, `RESOLUTION`, `SCREEN_SIZE`, `SCREEN_TYPE`, `SIZE`, `SLEEVE`, `STORAGE`, `STORAGE_TYPE`, `TAG`, `TYPE`, `ZIP` |
| **`textcat`** | `212`, `297`, `328` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 94.35 |
| `ENTS_P` | 94.70 |
| `ENTS_R` | 94.00 |
| `CATS_SCORE` | 100.00 |
| `CATS_MICRO_P` | 100.00 |
| `CATS_MICRO_R` | 100.00 |
| `CATS_MICRO_F` | 100.00 |
| `CATS_MACRO_P` | 100.00 |
| `CATS_MACRO_R` | 100.00 |
| `CATS_MACRO_F` | 100.00 |
| `CATS_MACRO_AUC` | 100.00 |
| `TOK2VEC_LOSS` | 28927.81 |
| `NER_LOSS` | 63903.29 |
| `TEXTCAT_LOSS` | 0.08 |