readme: add initial version

README.md

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+---
+tags:
+- flair
+- token-classification
+- sequence-tagger-model
+language: de
+widget:
+- text: "Herr Oberst Brunner ist nämlich Hauptagent für den Kanton Zürich."
+license: mit
+---
+
+# Triple E - Effective Ensembling of Embeddings and Language Models for NER of Historical German
+
+Based on [our paper](http://ceur-ws.org/Vol-2696/paper_173.pdf) we release a new baseline model for the German
+[CLEF-HIPE shared task](https://impresso.github.io/CLEF-HIPE-2020/).
+
+In contrast to the models used in the paper, we manually sentence-segmented and normalize hyphenations and
+trained a NER model using the German Europeana BERT model.
+
+Additionally, we perform experiments with different context sizes. This approach is described in
+more detail in [this paper](https://arxiv.org/abs/2011.06993).
+
+# Results
+
+The results with different context sizes can be seen in the following table:
+| Model                      | Run 1           | Run 2           | Run 3           | Run 4               | Run 5           | Avg.
+| -------------------------- | --------------- | --------------- | --------------- | ------------------- | --------------- | ---------------
+| German Europeana BERT      | (81.45) / 76.92 | (**81.53**) / 77.03 | (80.49) / 77.83 | (80.88) / 77.19 | (81.39) / 77.00 | (81.15 ± 0.45) / 77.19 ± 0.34
+| German Europeana BERT (16) | (**82.56**) / 77.38 | (81.19) / 77.76 | (80.99) / 76.34 | (81.27) / 77.70 | (81.28) / 77.22 | (81.46 ± 0.63) / 77.28 ± 0.57
+| German Europeana BERT (32) | (**82.04**) / 78.50 | (81.14) / 76.56 | (81.81) / 78.28 | (81.50) / 76.90 | (81.64) / 77.94 | (81.63 ± 0.34) / 77.64 ± 0.86
+| German Europeana BERT (64) | (81.21) / 78.39 | (81.27) / 75.98 | (**81.88**) / 78.40 | (81.66) / 77.35 | (81.29) / 76.70 | (81.46 ± 0.29) / 77.36 ± 1.06
+| German Europeana BERT (80) | (82.13) / 77.77 | (81.31) / 76.81 | (82.09) / 78.69 | (**82.30**) / 76.79 | (80.65) / 77.10 | (81.70 ± 0.70) / 77.43 ± 0.81
+
+## Comparisons
+
+The following figure shows the results with different context sized (on development dataset):
+
+<link>
+
+We perform "Almost Stochastic Order" tests as proposed in the
+["Deep Dominance - How to Properly Compare Deep Neural Models"](https://www.aclweb.org/anthology/P19-1266/) paper.
+The heatmap figure is heavily inspired by the ["CharacterBERT"](https://arxiv.org/abs/2010.10392) paper.
+
+<link>