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README.md
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- political science
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- parties
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- press releases
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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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