Create README.md

README.md

@@ -0,0 +1,51 @@
+---
+language: de
+license: mit
+tags:
+- exbert
+---
+
+## Overview
+**Language model:** gbert-large-sts
+
+**Language:** German  
+**Training data:** German STS benchmark train and dev set  
+**Eval data:** German STS benchmark test set   
+**Infrastructure**: 1x V100 GPU  
+**Published**: August 12th, 2021
+
+## Details
+- We trained a gbert-large model on the task of estimating semantic similarity of German-language text pairs. The dataset is a machine-translated version of the [STS benchmark](https://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark), which is available [here](https://github.com/t-systems-on-site-services-gmbh/german-STSbenchmark).
+
+## Hyperparameters
+```
+batch_size = 16
+n_epochs = 4
+warmup_ratio = 0.1
+learning_rate = 2e-5
+lr_schedule = LinearWarmup
+```
+## Performance
+Stay tuned... and watch out for new papers on arxiv.org ;)
+
+## Authors
+- Julian Risch: `julian.risch [at] deepset.ai`
+- Timo Möller: `timo.moeller [at] deepset.ai`
+- Julian Gutsch: `julian.gutsch [at] deepset.ai`
+- Malte Pietsch: `malte.pietsch [at] deepset.ai`
+
+## About us
+![deepset logo](https://workablehr.s3.amazonaws.com/uploads/account/logo/476306/logo)
+We bring NLP to the industry via open source!  
+Our focus: Industry specific language models & large scale QA systems.  
+  
+Some of our work: 
+- [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)
+- [FARM](https://github.com/deepset-ai/FARM)
+- [Haystack](https://github.com/deepset-ai/haystack/)
+
+Get in touch:
+[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Website](https://deepset.ai)  
+
+By the way: [we're hiring!](https://apply.workable.com/deepset/)