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@@ -10,11 +10,42 @@ tags:
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  - feature-extraction
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  - sentence-similarity
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  library_name: sentence-transformers
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # biencoder-camembert-base-mmarcoFR
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- This is a dense single-vector bi-encoder model. It maps sentences & paragraphs to a 768 dimensional dense vector space and should be used for semantic search. The model was trained on the **French** portion of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) retrieval dataset.
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  ## Usage
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  - feature-extraction
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  - sentence-similarity
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  library_name: sentence-transformers
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+ model-index:
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+ - name: biencoder-camembert-base-mmarcoFR
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+ results:
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+ - task:
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+ type: sentence-similarity
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+ name: Information Retrieval
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+ dataset:
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+ type: unicamp-dl/mmarco
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+ name: mMARCO
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+ config: french
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+ split: dev
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+ revision: None
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+ metrics:
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+ - type: recall_at_500
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+ name: Recall@500
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+ value: 89.13
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+ - type: recall_at_100
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+ name: Recall@100
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+ value: 77.82
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+ - type: recall_at_10
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+ name: Recall@10
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+ value: 51.46
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+ - type: map_at_10
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+ name: MAP@10
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+ value: 27.93
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+ - type: ndcg_at_10
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+ name: nDCG@10
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+ value: 33.72
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+ - type: mrr_at_10
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+ name: MRR@10
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+ value: 28.53
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  ---
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  # biencoder-camembert-base-mmarcoFR
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+ This is a dense single-vector bi-encoder model. It maps sentences and paragraphs to a 768 dimensional dense vector space and should be used for semantic search. The model was trained on the **French** portion of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) retrieval dataset.
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  ## Usage
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