Description: Sentence CamemBERT Large is the Embedding Model for French developed by La Javaness. The purpose of this embedding model is to represent the content and semantics of a French sentence in a mathematical vector which allows it to understand the meaning of the text beyond individual words in queries and documents, offering a powerful semantic search. Pre trained sentence embedding models are state of the art of Sentence Embeddings for French. The model is Fine tuned using pre trained facebook/camembert large 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 large 88.2 88.02 336M dangvantuan/sentence camembert base 86.73 86.54 110M distiluse base multilingual cased 79.22 79.16 135M GPT 3 (text davinci 003) 85 NaN 175B GPT (text embedding ada 002) 79.75 80.44 NaN On test Model Pearson correlation Spearman correlation dangvantu…
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