---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_parsigs
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.8482521186
    - name: NER Recall
      type: recall
      value: 0.8848066298
    - name: NER F Score
      type: f_score
      value: 0.8661438615
---
| Feature | Description |
| --- | --- |
| **Name** | `en_parsigs` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.5.0,<3.6.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Author** | [royashcenazi]() |

### Label Scheme

<details>

<summary>View label scheme (6 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `Dosage`, `Drug`, `Duration`, `Form`, `Frequency`, `Strength` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 86.61 |
| `ENTS_P` | 84.83 |
| `ENTS_R` | 88.48 |
| `TRANSFORMER_LOSS` | 5347024.15 |
| `NER_LOSS` | 3459290.82 |