readme: ---
  tags:
  - spacy
  - token-classification
  language:
  - de
  model-index:
  - name: de_fnhd_nerdh
    results:
    - task:
        name: NER
        type: token-classification
      metrics:
      - name: NER Precision
        type: precision
        value: 0.9629324547
      - name: NER Recall
        type: recall
        value: 0.9504065041
      - name: NER F Score
        type: f_score
        value: 0.9566284779
  ---
  Deutsche NER-Pipeline für frühneuhochdeutsche Texte (2.Version)
  
  | Feature | Description |
  | --- | --- |
  | **Name** | `de_fnhd_nerdh` |
  | **Version** | `0.0.2` |
  | **spaCy** | `>=3.4.1,<3.5.0` |
  | **Default Pipeline** | `tok2vec`, `ner` |
  | **Components** | `tok2vec`, `ner` |
  | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
  | **Sources** | n/a |
  | **License** | n/a |
  | **Author** | [ih]() |
  
  ### Label Scheme
  
  <details>
  
  <summary>View label scheme (5 labels for 1 components)</summary>
  
  | Component | Labels |
  | --- | --- |
  | **`ner`** | `OBJEKT`, `ORGANISATION`, `ORT`, `PERSON`, `ZEIT` |
  
  </details>
  
  ### Accuracy
  
  | Type | Score |
  | --- | --- |
  | `ENTS_F` | 95.66 |
  | `ENTS_P` | 96.29 |
  | `ENTS_R` | 95.04 |
  | `TOK2VEC_LOSS` | 25311.59 |
  | `NER_LOSS` | 15478.32 |