--- tags: - spacy - token-classification language: - en model-index: - name: en_t1_pipeline results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.9898959627 - name: NER Recall type: recall value: 0.9868960219 - name: NER F Score type: f_score value: 0.9883937159 --- | Feature | Description | | --- | --- | | **Name** | `en_t1_pipeline` | | **Version** | `0.0.0` | | **spaCy** | `>=3.7.2,<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
View label scheme (5 labels for 1 components) | Component | Labels | | --- | --- | | **`ner`** | `Other`, `allergy_name`, `cancer`, `chronic_disease`, `treatment` |
### Accuracy | Type | Score | | --- | --- | | `ENTS_F` | 98.84 | | `ENTS_P` | 98.99 | | `ENTS_R` | 98.69 | | `TOK2VEC_LOSS` | 510175.31 | | `NER_LOSS` | 282233.89 |