readme: ---
  tags:
  - spacy
  - token-classification
  language:
  - de
  model-index:
  - name: de_GERNERMEDpp_GermanBERT
    results:
    - task:
        name: NER
        type: token-classification
      metrics:
      - name: NER Precision
        type: precision
        value: 0.9088501091
      - name: NER Recall
        type: recall
        value: 0.9085669782
      - name: NER F Score
        type: f_score
        value: 0.9087085216
  ---
  GottBERT-based model of the GERNERMED++ German NER model for medical entities.
  
  | Feature | Description |
  | --- | --- |
  | **Name** | `de_GERNERMEDpp_GermanBERT` |
  | **Version** | `1.0.0` |
  | **spaCy** | `>=3.2.3,<3.3.0` |
  | **Default Pipeline** | `transformer`, `ner` |
  | **Components** | `transformer`, `ner` |
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
  | **Sources** | n/a |
  | **License** | n/a |
  | **Author** | [Johann Frei](https://github.com/frankkramer-lab/GERNERMED-pp) |
  
  ### 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` | 90.87 |
  | `ENTS_P` | 90.89 |
  | `ENTS_R` | 90.86 |
  | `TRANSFORMER_LOSS` | 193600.80 |
  | `NER_LOSS` | 255416.71 |