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@@ -14,6 +14,8 @@ The model assigns one of four possible labels:
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  For details on the model and its performance, see Koch and Pasch (2022). Please cite this article when using the model: <br />
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  Koch, Sebastian; Pasch, Stefan (2022): CultureBERT: Fine-Tuning Transformer Based Language Models for Corporate Culture. Available online at http://arxiv.org/abs/2212.00509.
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  Other References:
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  [1] Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; ... & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.
 
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  For details on the model and its performance, see Koch and Pasch (2022). Please cite this article when using the model: <br />
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  Koch, Sebastian; Pasch, Stefan (2022): CultureBERT: Fine-Tuning Transformer Based Language Models for Corporate Culture. Available online at http://arxiv.org/abs/2212.00509.
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+ Please see the following tutorial on how to apply CultureBERT to measure corporate culture in your own text documents: https://github.com/Stefan-Pasch/CultureBERT
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  Other References:
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  [1] Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; ... & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.