metadata
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 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.