diff --git a/model_cards/deepset/gbert-base/README.md b/model_cards/deepset/gbert-base/README.md new file mode 100644 index 00000000000000..d6404262d0b468 --- /dev/null +++ b/model_cards/deepset/gbert-base/README.md @@ -0,0 +1,51 @@ +--- +language: de +license: mit +datasets: +- wikipedia +- OPUS +- OpenLegalData +--- + +# German BERT base + +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 base +**Language:** German + +## Performance +``` +GermEval18 Coarse: 78.17 +GermEval18 Fine: 50.90 +GermEval14: 87.98 +``` + +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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) diff --git a/model_cards/deepset/gbert-large/README.md b/model_cards/deepset/gbert-large/README.md new file mode 100644 index 00000000000000..a8aea0d6c20630 --- /dev/null +++ b/model_cards/deepset/gbert-large/README.md @@ -0,0 +1,54 @@ +--- +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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) + + diff --git a/model_cards/deepset/gelectra-base-generator/README.md b/model_cards/deepset/gelectra-base-generator/README.md new file mode 100644 index 00000000000000..ed7ee78e51fb53 --- /dev/null +++ b/model_cards/deepset/gelectra-base-generator/README.md @@ -0,0 +1,46 @@ +--- +language: de +license: mit +datasets: +- wikipedia +- OPUS +- OpenLegalData +--- + +# German ELECTRA base generator + +Released, Oct 2020, this is the generator component of the German ELECTRA 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. + +The generator is useful for performing masking experiments. If you are looking for a regular language model for embedding extraction, or downstream tasks like NER, classification or QA, please use deepset/gelectra-base. + +## Overview +**Paper:** [here](https://arxiv.org/pdf/2010.10906.pdf) +**Architecture:** ELECTRA base (generator) +**Language:** German + +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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) diff --git a/model_cards/deepset/gelectra-base/README.md b/model_cards/deepset/gelectra-base/README.md new file mode 100644 index 00000000000000..a0b2e2f0ed8dd4 --- /dev/null +++ b/model_cards/deepset/gelectra-base/README.md @@ -0,0 +1,51 @@ +--- +language: de +license: mit +datasets: +- wikipedia +- OPUS +- OpenLegalData +--- + +# German ELECTRA base + +Released, Oct 2020, this is a German ELECTRA 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. Our evaluation suggests that this model is somewhat undertrained. For best performance from a base sized model, we recommend deepset/gbert-base + +## Overview +**Paper:** [here](https://arxiv.org/pdf/2010.10906.pdf) +**Architecture:** ELECTRA base (discriminator) +**Language:** German + +## Performance +``` +GermEval18 Coarse: 76.02 +GermEval18 Fine: 42.22 +GermEval14: 86.02 +``` + +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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) diff --git a/model_cards/deepset/gelectra-large-generator/README.md b/model_cards/deepset/gelectra-large-generator/README.md new file mode 100644 index 00000000000000..606e332547aa13 --- /dev/null +++ b/model_cards/deepset/gelectra-large-generator/README.md @@ -0,0 +1,56 @@ +--- +language: de +license: mit +datasets: +- wikipedia +- OPUS +- OpenLegalData +- OSCAR +--- + +# German ELECTRA large generator + +Released, Oct 2020, this is the generator component of the German ELECTRA 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. + +The generator is useful for performing masking experiments. If you are looking for a regular language model for embedding extraction, or downstream tasks like NER, classification or QA, please use deepset/gelectra-large. + +## Overview +**Paper:** [here](https://arxiv.org/pdf/2010.10906.pdf) +**Architecture:** ELECTRA large (generator) +**Language:** German + +## Performance +``` +GermEval18 Coarse: 80.70 +GermEval18 Fine: 55.16 +GermEval14: 88.95 +``` + +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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) + + diff --git a/model_cards/deepset/gelectra-large/README.md b/model_cards/deepset/gelectra-large/README.md new file mode 100644 index 00000000000000..a76f8a928daccf --- /dev/null +++ b/model_cards/deepset/gelectra-large/README.md @@ -0,0 +1,52 @@ +--- +language: de +license: mit +datasets: +- wikipedia +- OPUS +- OpenLegalData +- OSCAR +--- + +# German ELECTRA large + +Released, Oct 2020, this is a German ELECTRA 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 this is the state of the art German language model. + +## Overview +**Paper:** [here](https://arxiv.org/pdf/2010.10906.pdf) +**Architecture:** ELECTRA large (discriminator) +**Language:** German + +## Performance +``` +GermEval18 Coarse: 80.70 +GermEval18 Fine: 55.16 +GermEval14: 88.95 +``` + +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 [at] deepset.ai` +Stefan Schweter: `stefan [at] schweter.eu` +Timo Möller: `timo.moeller [at] deepset.ai` + +## About us +![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png) + +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) +- [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)