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