readme: ---
  tags:
  - flair
  - token-classification
  - sequence-tagger-model
  language: de
  inference: false
  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 LFT 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   | 76.32 | 76.13 | **76.36** | 76.27
  | Test          | 77.07 | 77.35 | 77.20     | 77.21
  
  Paper reported an averaged F1-score of 77.51.
  
  † denotes that this model is selected for upload.
  