
# GermanPolitical-Gelectra-base

Released May 2022, we fine-tuned the german electra model pre-trained by german-nlp-group (orginal model can be found at 'german-nlp-group/electra-base-german-uncased') to classify political sentiment of popular german parties. 
Supported parties at the moment are "CDU/CSU", "SPD", "FDP", "Grüne", "Die Linke", "AfD".

## Overview  
**Architecture:** Gelectra-base (uncased)

**Language:** German  

## Datasets & Methodology
![Methodology for model](https://www.wahl-o-bot.de/img/Method.315efe28.jpg)

For more information about data and methodology visit: https://www.wahl-o-bot.de/Methodik

## Production

The model can be used for free at https://www.wahl-o-bot.de

## Authors

Feel free to contact us about questions or feedback. We are always happy to help.

* Maximilian Witte: `maximilian.witte@uni-hamburg.de`
* Jasper Schwenzow: `jasper.schwenzow@uni-hamburg.de`
* Mark Heitmann: `mark.heitmann@uni-hamburg.de`
* Matthias Assenmacher: `matthias@stat.uni-muenchen.de`

The model is built in collaboration of the University of Hamburg and Ludwig Maximilians University Munich. 

https://www.bwl.uni-hamburg.de/ci.html
{"language": "de", "license": "mit", "datasets": ["Wahl-o-Mat", "Wahlprogramme"], "widget": [{"text": "cdu/csu: kohlekraftwerke sollten verboten werden", "example_title": "Predict whether CDU/CSU would like to forbid coal-fired power plants"}, {"text": "gr\u00fcne: gefl\u00fcchtete weiter aufnehmen", "example_title": "Predict whether gr\u00fcne are positive to accept refugees"}, {"text": "die linke: vier tage woche", "example_title": "Predict if 'die Linke' wants people to work 4 instead of 5 days per week"}]}
transformers tf electra text-classification de dataset:Wahl-o-Mat dataset:Wahlprogramme license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #electra #text-classification #de #dataset-Wahl-o-Mat #dataset-Wahlprogramme #license-mit #autotrain_compatible #endpoints_compatible #region-us 


# GermanPolitical-Gelectra-base

Released May 2022, we fine-tuned the german electra model pre-trained by german-nlp-group (orginal model can be found at 'german-nlp-group/electra-base-german-uncased') to classify political sentiment of popular german parties. 
Supported parties at the moment are "CDU/CSU", "SPD", "FDP", "Grüne", "Die Linke", "AfD".

## Overview  
Architecture: Gelectra-base (uncased)

Language: German  

## Datasets & Methodology
!Methodology for model

For more information about data and methodology visit: URL

## Production

The model can be used for free at URL

## Authors

Feel free to contact us about questions or feedback. We are always happy to help.

* Maximilian Witte: 'URL@URL'
* Jasper Schwenzow: 'jasper.schwenzow@URL'
* Mark Heitmann: 'mark.heitmann@URL'
* Matthias Assenmacher: 'matthias@URL'

The model is built in collaboration of the University of Hamburg and Ludwig Maximilians University Munich. 

URL
# GermanPolitical-Gelectra-base

Released May 2022, we fine-tuned the german electra model pre-trained by german-nlp-group (orginal model can be found at 'german-nlp-group/electra-base-german-uncased') to classify political sentiment of popular german parties. 
Supported parties at the moment are "CDU/CSU", "SPD", "FDP", "Grüne", "Die Linke", "AfD". ## Overview  
Architecture: Gelectra-base (uncased)

Language: German ## Datasets & Methodology
!Methodology for model

For more information about data and methodology visit: URL ## Production

The model can be used for free at URL ## Authors

Feel free to contact us about questions or feedback. We are always happy to help.

* Maximilian Witte: 'URL@URL'
* Jasper Schwenzow: 'jasper.schwenzow@URL'
* Mark Heitmann: 'mark.heitmann@URL'
* Matthias Assenmacher: 'matthias@URL'

The model is built in collaboration of the University of Hamburg and Ludwig Maximilians University Munich. 

URL
TAGS
#transformers #tf #electra #text-classification #de #dataset-Wahl-o-Mat #dataset-Wahlprogramme #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # GermanPolitical-Gelectra-base

Released May 2022, we fine-tuned the german electra model pre-trained by german-nlp-group (orginal model can be found at 'german-nlp-group/electra-base-german-uncased') to classify political sentiment of popular german parties. 
Supported parties at the moment are "CDU/CSU", "SPD", "FDP", "Grüne", "Die Linke", "AfD". ## Overview  
Architecture: Gelectra-base (uncased)

Language: German ## Datasets & Methodology
!Methodology for model

For more information about data and methodology visit: URL ## Production

The model can be used for free at URL ## Authors

Feel free to contact us about questions or feedback. We are always happy to help.

* Maximilian Witte: 'URL@URL'
* Jasper Schwenzow: 'jasper.schwenzow@URL'
* Mark Heitmann: 'mark.heitmann@URL'
* Matthias Assenmacher: 'matthias@URL'

The model is built in collaboration of the University of Hamburg and Ludwig Maximilians University Munich. 

URL
passage: TAGS
#transformers #tf #electra #text-classification #de #dataset-Wahl-o-Mat #dataset-Wahlprogramme #license-mit #autotrain_compatible #endpoints_compatible #region-us 
# GermanPolitical-Gelectra-base

Released May 2022, we fine-tuned the german electra model pre-trained by german-nlp-group (orginal model can be found at 'german-nlp-group/electra-base-german-uncased') to classify political sentiment of popular german parties. 
Supported parties at the moment are "CDU/CSU", "SPD", "FDP", "Grüne", "Die Linke", "AfD".## Overview  
Architecture: Gelectra-base (uncased)

Language: German## Datasets & Methodology
!Methodology for model

For more information about data and methodology visit: URL## Production

The model can be used for free at URL## Authors

Feel free to contact us about questions or feedback. We are always happy to help.

* Maximilian Witte: 'URL@URL'
* Jasper Schwenzow: 'jasper.schwenzow@URL'
* Mark Heitmann: 'mark.heitmann@URL'
* Matthias Assenmacher: 'matthias@URL'

The model is built in collaboration of the University of Hamburg and Ludwig Maximilians University Munich. 

URL