--- 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
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