readme: ---
  language: de
  license: mit
  datasets:
  - wikipedia
  - OPUS
  - OpenLegalData
  - oscar
  ---
  
  # German BERT large
  
  Released, Oct 2020, this is a German BERT language model trained collaboratively by the makers of the original German BERT (aka "bert-base-german-cased") and the dbmdz BERT (aka bert-base-german-dbmdz-cased). In our [paper](https://arxiv.org/pdf/2010.10906.pdf), we outline the steps taken to train our model and show that it outperforms its predecessors.  
  
  ## Overview  
  **Paper:** [here](https://arxiv.org/pdf/2010.10906.pdf)  
  **Architecture:** BERT large  
  **Language:** German  
  
  ## Performance  
  ```
  GermEval18 Coarse: 80.08
  GermEval18 Fine:   52.48
  GermEval14:        88.16
  ```
  
  See also:  
  deepset/gbert-base    
  deepset/gbert-large    
  deepset/gelectra-base    
  deepset/gelectra-large    
  deepset/gelectra-base-generator    
  deepset/gelectra-large-generator    
  
  ## Authors
  **Branden Chan:** branden.chan@deepset.ai    
  **Stefan Schweter:** stefan@schweter.eu        
  **Timo Möller:** timo.moeller@deepset.ai    
  
  ## About us
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  [deepset](http://deepset.ai/) is the company behind the open-source NLP framework [Haystack](https://haystack.deepset.ai/) which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.
  
  
  Some of our other work: 
  - [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")]([https://huggingface.co/deepset/tinyroberta-squad2)
  - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
  - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
  
  ## Get in touch and join the Haystack community
  
  <p>For more info on Haystack, visit our <strong><a href="https://github.com/deepset-ai/haystack">GitHub</a></strong> repo and <strong><a href="https://docs.haystack.deepset.ai">Documentation</a></strong>. 
  
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