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---
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 | |