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@@ -113,6 +113,9 @@ The batch size for training was 12, for testing 2, with four epochs. All other h
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  Fine-tuned on our downstream task, this model achieves the following results in a five-fold cross validation that are comparable to the performance of our expert human coders. Please refer to Erfort et al. (2023)
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  ### BibTeX entry and citation info
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  ```bibtex
@@ -120,13 +123,19 @@ Fine-tuned on our downstream task, this model achieves the following results in
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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 PartiesPress 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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  ### Further resources
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  Github: [cornelius-erfort/partypress](https://github.com/cornelius-erfort/partypress)
 
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  Fine-tuned on our downstream task, this model achieves the following results in a five-fold cross validation that are comparable to the performance of our expert human coders. Please refer to Erfort et al. (2023)
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+ ### BibTeX entry and citation info
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  ### BibTeX entry and citation info
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  ```bibtex
 
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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 partiespress releases},
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  journal = {Research and Politics},
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+ volume = {10},
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+ number = {3},
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  year = {2023},
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+ doi = {10.1177/20531680231183512},
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+ URL = {https://doi.org/10.1177/20531680231183512}
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+
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  }
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  ```
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+ Erfort, C., Stoetzer, L. F., & Klüver, H. (2023). The PARTYPRESS Database: A new comparative database of parties’ press releases. Research & Politics, 10(3). [https://doi.org/10.1177/20531680231183512](https://doi.org/10.1177/20531680231183512)
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  ### Further resources
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  Github: [cornelius-erfort/partypress](https://github.com/cornelius-erfort/partypress)