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.
Runs of dbmdz flair-historic-ner-onb on huggingface.co
30
Total runs
0
24-hour runs
1
3-day runs
3
7-day runs
24
30-day runs
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