Sentence Similarity
sentence-transformers
Safetensors
Transformers
French
English
bilingual
feature-extraction
sentence-embedding
mteb
custom_code
Eval Results (legacy)
Instructions to use Lajavaness/bilingual-embedding-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Lajavaness/bilingual-embedding-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Lajavaness/bilingual-embedding-small", trust_remote_code=True) sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use Lajavaness/bilingual-embedding-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Lajavaness/bilingual-embedding-small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: sentence-transformers | |
| pipeline_tag: sentence-similarity | |
| tags: | |
| - sentence-transformers | |
| - feature-extraction | |
| - sentence-similarity | |
| - transformers | |
| - sentence-embedding | |
| - mteb | |
| model-index: | |
| - name: bilingual-embedding-small | |
| results: | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: lyon-nlp/alloprof | |
| name: MTEB AlloProfClusteringP2P | |
| config: default | |
| split: test | |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b | |
| metrics: | |
| - type: v_measure | |
| value: 63.19030822769444 | |
| - type: v_measures | |
| value: [0.5938891912573394, 0.6171518411959, 0.6042518292029612, 0.6626602879382325, 0.6471224639325329] | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: lyon-nlp/alloprof | |
| name: MTEB AlloProfClusteringS2S | |
| config: default | |
| split: test | |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b | |
| metrics: | |
| - type: v_measure | |
| value: 41.32807908087869 | |
| - type: v_measures | |
| value: [0.3351458197856525, 0.48472823318531566, 0.4631757871803168, 0.43580166532679027, 0.4219041689415661] | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: lyon-nlp/mteb-fr-reranking-alloprof-s2p | |
| name: MTEB AlloprofReranking | |
| config: default | |
| split: test | |
| revision: 65393d0d7a08a10b4e348135e824f385d420b0fd | |
| metrics: | |
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| value: 68.43888603876276 | |
| - type: mrr | |
| value: 69.59097513501659 | |
| - type: nAUC_map_diff1 | |
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| - type: nAUC_map_max | |
| value: 10.206900586093957 | |
| - type: nAUC_mrr_diff1 | |
| value: 47.823670000503014 | |
| - type: nAUC_mrr_max | |
| value: 10.266197221615979 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: lyon-nlp/alloprof | |
| name: MTEB AlloprofRetrieval | |
| config: default | |
| split: test | |
| revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.23 | |
| - type: map_at_10 | |
| value: 33.513999999999996 | |
| - type: map_at_100 | |
| value: 34.554 | |
| - type: map_at_1000 | |
| value: 34.621 | |
| - type: map_at_20 | |
| value: 34.129 | |
| - type: map_at_3 | |
| value: 30.526999999999997 | |
| - type: map_at_5 | |
| value: 32.107 | |
| - type: mrr_at_1 | |
| value: 23.229706390328154 | |
| - type: mrr_at_10 | |
| value: 33.51421786331119 | |
| - type: mrr_at_100 | |
| value: 34.55441665729269 | |
| - type: mrr_at_1000 | |
| value: 34.62084787184653 | |
| - type: mrr_at_20 | |
| value: 34.12901601558586 | |
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| value: 44.566 | |
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| value: 32.993 | |
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| value: 35.839 | |
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| value: 23.23 | |
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| value: 23.23 | |
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| value: 40.155 | |
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| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (fr) | |
| config: fr | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 37.102000000000004 | |
| - type: f1 | |
| value: 36.48213245522153 | |
| - type: f1_weighted | |
| value: 36.48213245522153 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: maastrichtlawtech/bsard | |
| name: MTEB BSARDRetrieval | |
| config: default | |
| split: test | |
| revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 | |
| metrics: | |
| - type: map_at_1 | |
| value: 5.405 | |
| - type: map_at_10 | |
| value: 8.372 | |
| - type: map_at_100 | |
| value: 9.522 | |
| - type: map_at_1000 | |
| value: 9.645 | |
| - type: map_at_20 | |
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| - type: map_at_3 | |
| value: 7.132 | |
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| - task: | |
| type: Clustering | |
| dataset: | |
| type: lyon-nlp/clustering-hal-s2s | |
| name: MTEB HALClusteringS2S | |
| config: default | |
| split: test | |
| revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 | |
| metrics: | |
| - type: v_measure | |
| value: 23.773322308353517 | |
| - type: v_measures | |
| value: [0.28321300949906897, 0.26004472642751963, 0.25956951558284086, 0.24123195304666292, 0.22207486085944725] | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: reciTAL/mlsum | |
| name: MTEB MLSUMClusteringP2P | |
| config: default | |
| split: test | |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 | |
| metrics: | |
| - type: v_measure | |
| value: 44.10635133884183 | |
| - type: v_measures | |
| value: [0.4352021194557699, 0.4616076200837005, 0.4407517544208635, 0.4387026615402928, 0.40575306284000634] | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: reciTAL/mlsum | |
| name: MTEB MLSUMClusteringS2S | |
| config: default | |
| split: test | |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 | |
| metrics: | |
| - type: v_measure | |
| value: 43.6574557237274 | |
| - type: v_measures | |
| value: [0.431013360873005, 0.45456972088535785, 0.4474907746228345, 0.4318507494303067, 0.3857692351737129] | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (fr) | |
| config: fr | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 86.08518634512997 | |
| - type: f1 | |
| value: 86.01437763316983 | |
| - type: f1_weighted | |
| value: 86.03483392539235 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (fr) | |
| config: fr | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 61.23081741309113 | |
| - type: f1 | |
| value: 44.76981337966934 | |
| - type: f1_weighted | |
| value: 64.86577219367403 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/masakhanews | |
| name: MTEB MasakhaNEWSClassification (fra) | |
| config: fra | |
| split: test | |
| revision: 18193f187b92da67168c655c9973a165ed9593dd | |
| metrics: | |
| - type: accuracy | |
| value: 78.34123222748815 | |
| - type: f1 | |
| value: 74.19808376161188 | |
| - type: f1_weighted | |
| value: 78.465165305135 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: masakhane/masakhanews | |
| name: MTEB MasakhaNEWSClusteringP2P (fra) | |
| config: fra | |
| split: test | |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 | |
| metrics: | |
| - type: v_measure | |
| value: 58.6260598345145 | |
| - type: v_measures | |
| value: [1.0, 0.052551289167589395, 0.4126124221990744, 0.690570263898874, 0.7755690164601873] | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: masakhane/masakhanews | |
| name: MTEB MasakhaNEWSClusteringS2S (fra) | |
| config: fra | |
| split: test | |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 | |
| metrics: | |
| - type: v_measure | |
| value: 53.47058992788083 | |
| - type: v_measures | |
| value: [1.0, 0.06287268264858063, 0.6712730568122484, 0.2169401386066275, 0.7224436183265853] | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (fr) | |
| config: fr | |
| split: test | |
| revision: 4672e20407010da34463acc759c162ca9734bca6 | |
| metrics: | |
| - type: accuracy | |
| value: 65.48755884330868 | |
| - type: f1 | |
| value: 63.42516904610099 | |
| - type: f1_weighted | |
| value: 65.62227422445625 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (fr) | |
| config: fr | |
| split: test | |
| revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 | |
| metrics: | |
| - type: accuracy | |
| value: 69.27370544720914 | |
| - type: f1 | |
| value: 68.92639289886843 | |
| - type: f1_weighted | |
| value: 69.39025426049528 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: jinaai/mintakaqa | |
| name: MTEB MintakaRetrieval (fr) | |
| config: fr | |
| split: test | |
| revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e | |
| metrics: | |
| - type: map_at_1 | |
| value: 13.718 | |
| - type: map_at_10 | |
| value: 21.404 | |
| - type: map_at_100 | |
| value: 22.371 | |
| - type: map_at_1000 | |
| value: 22.493 | |
| - type: map_at_20 | |
| value: 21.972 | |
| - type: map_at_3 | |
| value: 19.192 | |
| - type: map_at_5 | |
| value: 20.366999999999997 | |
| - type: mrr_at_1 | |
| value: 13.718263718263717 | |
| - type: mrr_at_10 | |
| value: 21.40396890396889 | |
| - type: mrr_at_100 | |
| value: 22.370673563176524 | |
| - type: mrr_at_1000 | |
| value: 22.49316476646458 | |
| - type: mrr_at_20 | |
| value: 21.971667600361627 | |
| - type: mrr_at_3 | |
| value: 19.191919191919162 | |
| - type: mrr_at_5 | |
| value: 20.36718536718532 | |
| - type: nauc_map_at_1000_diff1 | |
| value: 18.66186772676608 | |
| - type: nauc_map_at_1000_max | |
| value: 32.45794220535016 | |
| - type: nauc_map_at_100_diff1 | |
| value: 18.620993318615394 | |
| - type: nauc_map_at_100_max | |
| value: 32.44820369787587 | |
| - type: nauc_map_at_10_diff1 | |
| value: 18.884049513804037 | |
| - type: nauc_map_at_10_max | |
| value: 32.77552431144882 | |
| - type: nauc_map_at_1_diff1 | |
| value: 25.49080673895181 | |
| - type: nauc_map_at_1_max | |
| value: 29.25311987317655 | |
| - type: nauc_map_at_20_diff1 | |
| value: 18.704330878419075 | |
| - type: nauc_map_at_20_max | |
| value: 32.55837988078994 | |
| - type: nauc_map_at_3_diff1 | |
| value: 20.095857563209314 | |
| - type: nauc_map_at_3_max | |
| value: 32.93191322461617 | |
| - type: nauc_map_at_5_diff1 | |
| value: 19.281813313113396 | |
| - type: nauc_map_at_5_max | |
| value: 32.786844756856475 | |
| - type: nauc_mrr_at_1000_diff1 | |
| value: 18.66186763232669 | |
| - type: nauc_mrr_at_1000_max | |
| value: 32.45794216874754 | |
| - type: nauc_mrr_at_100_diff1 | |
| value: 18.620993318615394 | |
| - type: nauc_mrr_at_100_max | |
| value: 32.44820369787587 | |
| - type: nauc_mrr_at_10_diff1 | |
| value: 18.884049513804037 | |
| - type: nauc_mrr_at_10_max | |
| value: 32.77552431144882 | |
| - type: nauc_mrr_at_1_diff1 | |
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| - type: nauc_mrr_at_1_max | |
| value: 29.25311987317655 | |
| - type: nauc_mrr_at_20_diff1 | |
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| - type: nauc_mrr_at_20_max | |
| value: 32.55837988078994 | |
| - type: nauc_mrr_at_3_diff1 | |
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| - type: nauc_mrr_at_3_max | |
| value: 32.93191322461617 | |
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| - type: nauc_mrr_at_5_max | |
| value: 32.786844756856475 | |
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| - type: nauc_ndcg_at_1000_max | |
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| value: 31.74628993952365 | |
| - type: nauc_ndcg_at_10_diff1 | |
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| - type: nauc_ndcg_at_10_max | |
| value: 33.34322548472455 | |
| - type: nauc_ndcg_at_1_diff1 | |
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| value: 29.25311987317655 | |
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| - type: nauc_ndcg_at_3_diff1 | |
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| - type: nauc_precision_at_1000_diff1 | |
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| - type: nauc_precision_at_5_max | |
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| - type: nauc_recall_at_1000_diff1 | |
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| - type: nauc_recall_at_1000_max | |
| value: 19.93551888234777 | |
| - type: nauc_recall_at_100_diff1 | |
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| - type: nauc_recall_at_100_max | |
| value: 27.293014978686276 | |
| - type: nauc_recall_at_10_diff1 | |
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| - type: nauc_recall_at_10_max | |
| value: 34.38806262714581 | |
| - type: nauc_recall_at_1_diff1 | |
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| - type: nauc_recall_at_1_max | |
| value: 29.25311987317655 | |
| - type: nauc_recall_at_20_diff1 | |
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| - type: nauc_recall_at_20_max | |
| value: 32.113399922346744 | |
| - type: nauc_recall_at_3_diff1 | |
| value: 15.622074491261479 | |
| - type: nauc_recall_at_3_max | |
| value: 35.725010828159924 | |
| - type: nauc_recall_at_5_diff1 | |
| value: 13.229128818765403 | |
| - type: nauc_recall_at_5_max | |
| value: 35.14850024280548 | |
| - type: ndcg_at_1 | |
| value: 13.718 | |
| - type: ndcg_at_10 | |
| value: 25.576 | |
| - type: ndcg_at_100 | |
| value: 30.537999999999997 | |
| - type: ndcg_at_1000 | |
| value: 34.364 | |
| - type: ndcg_at_20 | |
| value: 27.619 | |
| - type: ndcg_at_3 | |
| value: 20.924 | |
| - type: ndcg_at_5 | |
| value: 23.046 | |
| - type: precision_at_1 | |
| value: 13.718 | |
| - type: precision_at_10 | |
| value: 3.894 | |
| - type: precision_at_100 | |
| value: 0.628 | |
| - type: precision_at_1000 | |
| value: 0.094 | |
| - type: precision_at_20 | |
| value: 2.348 | |
| - type: precision_at_3 | |
| value: 8.64 | |
| - type: precision_at_5 | |
| value: 6.216 | |
| - type: recall_at_1 | |
| value: 13.718 | |
| - type: recall_at_10 | |
| value: 38.943 | |
| - type: recall_at_100 | |
| value: 62.775999999999996 | |
| - type: recall_at_1000 | |
| value: 94.10300000000001 | |
| - type: recall_at_20 | |
| value: 46.97 | |
| - type: recall_at_3 | |
| value: 25.921 | |
| - type: recall_at_5 | |
| value: 31.080999999999996 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: GEM/opusparcus | |
| name: MTEB OpusparcusPC (fr) | |
| config: fr | |
| split: test | |
| revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 81.81198910081744 | |
| - type: cos_sim_ap | |
| value: 92.92034333454589 | |
| - type: cos_sim_f1 | |
| value: 87.20651653090561 | |
| - type: cos_sim_precision | |
| value: 84.25925925925926 | |
| - type: cos_sim_recall | |
| value: 90.36742800397219 | |
| - type: dot_accuracy | |
| value: 81.06267029992752 | |
| - type: dot_ap | |
| value: 92.19923182286357 | |
| - type: dot_f1 | |
| value: 87.23307587460246 | |
| - type: dot_precision | |
| value: 80.40200995025126 | |
| - type: dot_recall | |
| value: 95.33267130089378 | |
| - type: euclidean_accuracy | |
| value: 81.06267029992752 | |
| - type: euclidean_ap | |
| value: 92.58456772515232 | |
| - type: euclidean_f1 | |
| value: 86.94835680751173 | |
| - type: euclidean_precision | |
| value: 82.45770258236865 | |
| - type: euclidean_recall | |
| value: 91.95630585898709 | |
| - type: manhattan_accuracy | |
| value: 80.92643051771117 | |
| - type: manhattan_ap | |
| value: 92.47972548332238 | |
| - type: manhattan_f1 | |
| value: 86.88372093023257 | |
| - type: manhattan_precision | |
| value: 81.71478565179353 | |
| - type: manhattan_recall | |
| value: 92.75074478649454 | |
| - type: max_accuracy | |
| value: 81.81198910081744 | |
| - type: max_ap | |
| value: 92.92034333454589 | |
| - type: max_f1 | |
| value: 87.23307587460246 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: google-research-datasets/paws-x | |
| name: MTEB PawsX (fr) | |
| config: fr | |
| split: test | |
| revision: 8a04d940a42cd40658986fdd8e3da561533a3646 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 60.550000000000004 | |
| - type: cos_sim_ap | |
| value: 58.1865824487652 | |
| - type: cos_sim_f1 | |
| value: 62.491349480968864 | |
| - type: cos_sim_precision | |
| value: 45.44539506794162 | |
| - type: cos_sim_recall | |
| value: 100.0 | |
| - type: dot_accuracy | |
| value: 56.49999999999999 | |
| - type: dot_ap | |
| value: 49.511525626044474 | |
| - type: dot_f1 | |
| value: 62.76595744680852 | |
| - type: dot_precision | |
| value: 46.165884194053206 | |
| - type: dot_recall | |
| value: 98.00664451827242 | |
| - type: euclidean_accuracy | |
| value: 60.199999999999996 | |
| - type: euclidean_ap | |
| value: 58.003058708335246 | |
| - type: euclidean_f1 | |
| value: 62.491349480968864 | |
| - type: euclidean_precision | |
| value: 45.44539506794162 | |
| - type: euclidean_recall | |
| value: 100.0 | |
| - type: manhattan_accuracy | |
| value: 60.199999999999996 | |
| - type: manhattan_ap | |
| value: 58.02420001567834 | |
| - type: manhattan_f1 | |
| value: 62.491349480968864 | |
| - type: manhattan_precision | |
| value: 45.44539506794162 | |
| - type: manhattan_recall | |
| value: 100.0 | |
| - type: max_accuracy | |
| value: 60.550000000000004 | |
| - type: max_ap | |
| value: 58.1865824487652 | |
| - type: max_f1 | |
| value: 62.76595744680852 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: Lajavaness/SICK-fr | |
| name: MTEB SICKFr | |
| config: default | |
| split: test | |
| revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 81.35988610550564 | |
| - type: cos_sim_spearman | |
| value: 74.30702501405389 | |
| - type: euclidean_pearson | |
| value: 77.98265846914386 | |
| - type: euclidean_spearman | |
| value: 74.28309779423242 | |
| - type: manhattan_pearson | |
| value: 77.91611618952486 | |
| - type: manhattan_spearman | |
| value: 74.09543847416339 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (fr) | |
| config: fr | |
| split: test | |
| revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.87930229178569 | |
| - type: cos_sim_spearman | |
| value: 82.91122500126046 | |
| - type: euclidean_pearson | |
| value: 82.30161381658885 | |
| - type: euclidean_spearman | |
| value: 82.80157531184477 | |
| - type: manhattan_pearson | |
| value: 82.59746592491155 | |
| - type: manhattan_spearman | |
| value: 82.91620907805208 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsb_multi_mt | |
| name: MTEB STSBenchmarkMultilingualSTS (fr) | |
| config: fr | |
| split: test | |
| revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.44206580073515 | |
| - type: cos_sim_spearman | |
| value: 83.29855460437528 | |
| - type: euclidean_pearson | |
| value: 82.28885833656986 | |
| - type: euclidean_spearman | |
| value: 83.17545506016941 | |
| - type: manhattan_pearson | |
| value: 82.16568250036501 | |
| - type: manhattan_spearman | |
| value: 83.0743139221437 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: lyon-nlp/summarization-summeval-fr-p2p | |
| name: MTEB SummEvalFr | |
| config: default | |
| split: test | |
| revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 31.280485627024635 | |
| - type: cos_sim_spearman | |
| value: 32.33005962500831 | |
| - type: dot_pearson | |
| value: 30.158348138782753 | |
| - type: dot_spearman | |
| value: 30.392045689426418 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: lyon-nlp/mteb-fr-reranking-syntec-s2p | |
| name: MTEB SyntecReranking | |
| config: default | |
| split: test | |
| revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad | |
| metrics: | |
| - type: map | |
| value: 81.67777777777776 | |
| - type: mrr | |
| value: 81.67777777777776 | |
| - type: nAUC_map_diff1 | |
| value: 59.89472485574524 | |
| - type: nAUC_map_max | |
| value: 8.215249384307162 | |
| - type: nAUC_mrr_diff1 | |
| value: 59.89472485574524 | |
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