Update README.md

README.md

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 <!-- Provide a quick summary of what the model is/does. -->
 
-The [SwissBERT](https://huggingface.co/ZurichNLP/swissbert) model was finetuned via self-supervised [SimCSE](http://dx.doi.org/10.18653/v1/2021.emnlp-main.552) (Gao et al., EMNLP 2021) for sentence embeddings, using ~1.5 million Swiss news articles from up to 2022 retireved via [Swissdox@LiRI](https://t.uzh.ch/1hI). Following the [Sentence Transformers](https://huggingface.co/sentence-transformers) approach (Reimers and Gurevych,
+The [SwissBERT](https://huggingface.co/ZurichNLP/swissbert) model was finetuned via self-supervised [SimCSE](http://dx.doi.org/10.18653/v1/2021.emnlp-main.552) (Gao et al., EMNLP 2021) for sentence embeddings, using ~1.5 million Swiss news articles from up to 2023 retireved via [Swissdox@LiRI](https://t.uzh.ch/1hI). Following the [Sentence Transformers](https://huggingface.co/sentence-transformers) approach (Reimers and Gurevych,
 2019), the average of the last hidden states (pooler_type=avg) is used as sentence representation.
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6564ab8d113e2baa55830af0/zUUu7WLJdkM2hrIE5ev8L.png)