dbmdz/flair-historic-ner-onb

Towards Robust Named Entity Recognition for Historic German

Based on our paper 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.