emrecan/bert base turkish cased mean nli stsb tr This is a sentence transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. The model was trained on Turkish machine translated versions of NLI and STS b datasets, using example training scripts from sentence transformers GitHub repository. Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling operation on top of the contextualized word embeddings. Evaluation Results Evaluation results on test and development sets are given below: Split Epoch cosine pearson cosine spearman euclidean pearson euclidean spearman manhattan pearson manhattan spearman dot pearson dot spearman test 0.834 0.830 0.820 0.819 0.819 0.818 0.799 0.789 validation 1 0.850 0.848 0.831 0.835 0.83 0.83 0.80 0.806 validation 2 0.857 0.857 0.844 0.848 0.844 0.848 0.813 0.810 validation 3 0.860…
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