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--- |
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license: cc-by-sa-4.0 |
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language: |
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- de |
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- en |
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- es |
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- da |
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- pl |
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- sv |
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- nl |
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metrics: |
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- accuracy |
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pipeline_tag: text-classification |
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tags: |
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- partypress |
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- political science |
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- parties |
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- press releases |
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--- |
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# PARTYPRESS multilingual |
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Fine-tuned model in seven languages on texts from nine countries, based on [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased). It used in Erfort et al. (2023). |
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## Model description |
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tbs |
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## Model variations |
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tbd (monolingual) |
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## Intended uses & limitations |
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tbd |
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### How to use |
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tbd |
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### Limitations and bias |
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tbd |
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## Training data |
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For the training data, please refer to [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) |
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## Training procedure |
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### Preprocessing |
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For the preprocessing, please refer to [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) |
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### Pretraining |
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For the pretraining, please refer to [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) |
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## Evaluation results |
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Fine-tuned on our downstream task, this model achieves the following results: |
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### BibTeX entry and citation info |
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```bibtex |
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@article{erfort_partypress_2023, |
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author = {Cornelius Erfort and |
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Lukas F. Stoetzer and |
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Heike Klüver}, |
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title = {The PARTYPRESS Database: A New Comparative Database of Parties’ Press Releases}, |
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journal = {Research and Politics}, |
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volume = {forthcoming}, |
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year = {2023}, |
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} |
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``` |
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