--- 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](http://deepset.ai/) is the company behind the production-ready open-source AI framework [Haystack](https://haystack.deepset.ai/). Some of our other work: - [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")](https://huggingface.co/deepset/tinyroberta-squad2) - [German BERT](https://deepset.ai/german-bert), [GermanQuAD and GermanDPR](https://deepset.ai/germanquad), [German embedding model](https://huggingface.co/mixedbread-ai/deepset-mxbai-embed-de-large-v1) - [deepset Cloud](https://www.deepset.ai/deepset-cloud-product), [deepset Studio](https://www.deepset.ai/deepset-studio) ## Get in touch and join the Haystack community

For more info on Haystack, visit our GitHub repo and Documentation. We also have a Discord community open to everyone!

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