Pre trained sentence embedding models are the state of the art of Sentence Embeddings for French. Model is Fine tuned using pre trained facebook/camembert base and Siamese BERT Networks with 'sentences transformers' on dataset stsb Usage The model can be used directly (without a language model) as follows: Evaluation The model can be evaluated as follows on the French test data of stsb. Test Result : The performance is measured using Pearson and Spearman correlation: On dev Model Pearson correlation Spearman correlation params dangvantuan/sentence camembert base 86.73 86.54 110M distiluse base multilingual cased 79.22 79.16 135M On test Model Pearson correlation Spearman correlation dangvantuan/sentence camembert base 82.36 81.64 distiluse base multilingual cased 78.62 77.48 Citation @article{reimers2019sentence, title={Sentence BERT: Sentence Embeddings using Siamese BERT Networks}, author={Nils Reimers, Iryna Gurevych}, journal={https://arxiv.org/abs/1908.10084}, year={2019} } @article{martin2020camembert, title={CamemBERT: a Tasty French Language Mode}, author={Martin, Louis and Muller, Benjamin and Su{\'a}rez, Pedro Javier Ortiz and Dupont, Yoann and Romary, Laurent and de la C…
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