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            Special thanks to [deepset](https://huggingface.co/deepset/) for providing the model gBERT-large and also to [Philip May](https://huggingface.co/philipMay) for the Translation of the dataset and chats about the topic.
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            Model score after fine-tuning  | 
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            **STS-B Test: 0.8626 (Spearman)**
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            This is the best result achieved that I know of.
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            <!--- Describe your model here -->
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            Special thanks to [deepset](https://huggingface.co/deepset/) for providing the model gBERT-large and also to [Philip May](https://huggingface.co/philipMay) for the Translation of the dataset and chats about the topic.
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            Model score after fine-tuning scores best, compared to these models:
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            | Model Name                                                    | Spearman<br/>German |
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            | xlm-r-distilroberta-base-paraphrase-v1                        | 0.8079            |
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            | [xlm-r-100langs-bert-base-nli-stsb-mean-tokens](https://huggingface.co/sentence-transformers/xlm-r-100langs-bert-base-nli-stsb-mean-tokens)                 | 0.7877            |
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            | xlm-r-bert-base-nli-stsb-mean-tokens                          | 0.7877            |
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            | [roberta-large-nli-stsb-mean-tokens](https://huggingface.co/sentence-transformers/roberta-large-nli-stsb-mean-tokens)                            | 0.6371            |
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            | [T-Systems-onsite/<br/>german-roberta-sentence-transformer-v2](https://huggingface.co/T-Systems-onsite/german-roberta-sentence-transformer-v2)       | 0.8529            |
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            | [paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) | 0.8355 |
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            | [T-Systems-onsite/<br/>cross-en-de-roberta-sentence-transformer](https://huggingface.co/T-Systems-onsite/<br/>cross-en-de-roberta-sentence-transformer) | 0.8550        |
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            | aari1995/German_Semantic_STS_V2 | **0.8626**        |
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            <!--- Describe your model here -->
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