---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_predii_ner
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.8568965517
    - name: NER Recall
      type: recall
      value: 0.7729393468
    - name: NER F Score
      type: f_score
      value: 0.8127555192
widget:
- text: "conditions can result in the bottoming out the suspension and amplification of the stressplaced on the floor truss network."
  example_title: "Entity recognition"
- text: "the additional stress can result in the fracture of welds securing the floor truss network system to the chassis frame rail and/or fracture of the floor truss network support system."
  example_title: "Entity recognition"
- text: "the possibility exists that there could be damage to electrical wiring and/or fuel lines which could potentially lead to a fire.You could contact to the MONACO CORPORATION"
  example_title: "Entity recognition"
---
| Feature | Description |
| --- | --- |
| **Name** | `en_predii_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.7.4,<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** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (8 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `CHASSIS TYPE`, `COMPONENT`, `CORRECTIVE ACTION`, `FAILURE ISSUE`, `MANUFACTURER`, `PARTS`, `PROCESS`, `VEHICLE MODEL` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 81.28 |
| `ENTS_P` | 85.69 |
| `ENTS_R` | 77.29 |
| `TOK2VEC_LOSS` | 74793.71 |
| `NER_LOSS` | 798047.72 |