gbert-large-paraphrase-cosine

This is a sentence-transformers model. It maps sentences & paragraphs (text) into a 1024 dimensional dense vector space. The model is intended to be used together with SetFit to improve German few-shot text classification. It has a sibling model called deutsche-telekom/gbert-large-paraphrase-euclidean. **Loss Function**\ We have used MultipleNegativesRankingLoss with cosine similarity as the loss function. **Training Data**\ The model is trained on a carefully filtered dataset of deutsche-telekom/ger-backtrans-paraphrase. We deleted the following pairs of sentences: - `min_char_len` less than 15 - `jaccard_similarity` greater than 0.3 - `de_token_count` greater than 30 - `en_de_token_count` greater than 30 - `cos_sim` less than 0.85

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