Update README.md

README.md

@@ -11,11 +11,10 @@ license: apache-2.0
 ---
 # About `sbb_ner`
 
-This is a BERT model for named entity recognition in historical German. 
-It can predict the classes `PER`, `LOC` and `ORG`.
+This is a BERT model for named entity recognition (NER) in historical German. 
+It predicts the classes `PER`, `LOC` and `ORG`. The model is based on the 🤗 
+[`BERT base multilingual cased`](https://huggingface.co/bert-base-multilingual-cased) model.   
 
-The model is based on the 🤗 [Transformers](https://github.com/huggingface/transformers) 
-`BERT Base multi-lingual cased` model. 
 We applied unsupervised pre-training on 2,333,647 pages of 
 unlabeled historical German text from the Berlin State Library 
 digital collections, and supervised pre-training on two datasets 
@@ -27,7 +26,7 @@ and [germeval_14](https://huggingface.co/models?dataset=dataset:germeval_14).
 In a 5-fold cross validation with different historical German NER corpora, 
 the model obtained an F1-Score of **84.3**±1.1%. 
 
-For details, see our [paper](https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/KONVENS2019_paper_4.pdf) 
+For details, see our *KONVENS2019* [paper](https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/KONVENS2019_paper_4.pdf) 
 or have a look at [sbb_ner](https://github.com/qurator-spk/sbb_ner) on GitHub.
 
 # Weights