readme: ---
  tags:
  - flair
  - token-classification
  - sequence-tagger-model
  language: de
  widget:
  - text: "April Martin Ansclm, K. Gefangen-Auffehers Georg Sausgruber."
  license: mit
  ---
  
  # Towards Robust Named Entity Recognition for Historic German
  
  Based on [our paper](https://www.aclweb.org/anthology/W19-4312/)
  we release a new model trained on the ONB dataset.
  
  **Note:** We use BPEmbeddings instead of the combination of
  Wikipedia, Common Crawl and character embeddings (as used in the paper),
  so save space and training/inferencing time.
  
  # Results
  
  | Dataset \ Run | Run 1 | Run 2 | Run 3     | Avg.
  | ------------- | ----- | ----- | --------- | ------------
  | Development   | 86.69 | 86.13 | **87.18** | 86.67
  | Test          | 85.27 | 86.05 | 85.75†    | 85.69
  
  Paper reported an averaged F1-score of 85.31.
  
  † denotes that this model is selected for upload.
  