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README.md
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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
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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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