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--- |
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language: de |
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widget: |
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- text: Das Sachgebiet Investive Ausgaben des Bundes Bundesfinanzminister Apel hat gemäß BMF Finanznachrichten vom 1. Januar erklärt, die Investitionsquote des Bundes sei in den letzten zehn Jahren nahezu konstant geblieben. |
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--- |
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### Welcome to ParlBERT-Topic-German! |
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🏷 **Model description** |
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This model was trained on \~10k manually annotated interpellations (📚 [Breunig/ Schnatterer 2019](https://www.tandfonline.com/doi/abs/10.1080/13572334.2021.2010395)) with topics from the [Comparative Agendas Project](https://www.comparativeagendas.net/datasets_codebooks) to classify text into one of twenty labels (annotation codebook). |
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_Note: "Interpellation is a formal request of a parliament to the respective government."([Wikipedia](https://en.wikipedia.org/wiki/Interpellation_(politics)))_ |
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🗃 **Dataset** |
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| party | speeches | tokens | |
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|----|----|----| |
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| CDU/CSU | 7,635 | 4,862,654 | |
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| SPD | 5,321 | 3,158,315 | |
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| AfD | 3,465 | 1,844,707 | |
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| FDP | 3,067 | 1,593,108 | |
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| The Greens | 2,866 | 1,522,305 | |
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| The Left | 2,671 | 1,394,089 | |
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| cross-bencher | 200 | 86,170 | |
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🏃🏼♂️**Model training** |
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**ParlBERT-Topic-German** was fine-tuned on a domain adapted model (GermanBERT fine-tuned on [DeuParl](https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2889?show=full)) for topic modeling with an interpellations dataset (📚 [Breunig/ Schnatterer 2019](https://oxford.universitypressscholarship.com/view/10.1093/oso/9780198835332.001.0001/oso-9780198835332)) from the [Comparative Agendas Project](https://www.comparativeagendas.net/datasets_codebooks). |
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🤖 **Use** |
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```python |
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from transformers import pipeline |
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pipeline_classification_topics = pipeline("text-classification", model="chkla/parlbert-topic-german", return_all_scores=False) |
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text = "Das Sachgebiet Investive Ausgaben des Bundes Bundesfinanzminister Apel hat gemäß BMF Finanznachrichten vom 1. Januar erklärt, die Investitionsquote des Bundes sei in den letzten zehn Jahren nahezu konstant geblieben." |
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pipeline_classification_topics(text) # Macroeconomics |
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``` |
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📊 **Evaluation** |
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The model was evaluated on an evaluation set (20%): |
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| Label | F1 | support | |
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|----|----|----| |
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| International | 80.0 | 1,126 | |
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| Defense | 85.0 | 1,099 | |
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| Government | 71.3 | 989 | |
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| Civil Rights | 76.5 | 978 | |
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| Environment | 76.6 | 845 | |
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| Transportation | 86.0 | 800 | |
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| Law & Crime | 67.1 | 492 | |
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| Energy | 78.6 | 424 | |
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| Health | 78.2 | 418 | |
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| Domestic Com. | 64.4 | 382 | |
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| Immigration | 81.0 | 376 | |
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| Labor | 69.1 | 344 | |
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| Macroeconom. | 62.8 | 339 | |
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| Agriculture | 76.3 | 292 | |
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| Social Welfare | 49.2 | 253 | |
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| Technology | 63.0 | 252 | |
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| Education | 71.6 | 183 | |
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| Housing | 79.6 | 178 | |
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| Foreign Trade | 61.5 | 139 | |
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| Culture | 54.6 | 69 | |
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| Public Lands | 45.4 | 55 | |
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⚠️ **Limitations** |
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Models are often highly topic dependent. Therefore, the model may perform less well on different topics and text types not included in the training set. |
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👥 **Cite** |
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``` |
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@article{klamm2022frameast, |
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title={FrameASt: A Framework for Second-level Agenda Setting in Parliamentary Debates through the Lense of Comparative Agenda Topics}, |
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author={Klamm, Christopher and Rehbein, Ines and Ponzetto, Simone}, |
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journal={ParlaCLARIN III at LREC2022}, |
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year={2022} |
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} |
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``` |
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🐦 Twitter: [@chklamm](http://twitter.com/chklamm) |
