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tags:

  • mteb model-index:
  • name: Solon-embeddings-large-0.1 results:
    • task: type: sentence-similarity name: Passage Retrieval dataset: type: unicamp-dl/mmarco name: mMARCO-fr config: french split: validation metrics:
      • type: recall_at_500 name: Recall@500 value: 92.7
      • type: recall_at_100 name: Recall@100 value: 82.7
      • type: recall_at_10 name: Recall@10 value: 55.5
      • type: map_at_10 name: MAP@10 value: 29.4
      • type: ndcg_at_10 name: nDCG@10 value: 35.8
      • type: mrr_at_10 name: MRR@10 value: 29.9
    • task: type: Clustering dataset: type: lyon-nlp/alloprof name: MTEB AlloProfClusteringP2P config: default split: test revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b metrics:
      • type: v_measure value: 64.16942168287153
    • task: type: Clustering dataset: type: lyon-nlp/alloprof name: MTEB AlloProfClusteringS2S config: default split: test revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b metrics:
      • type: v_measure value: 38.17076313383054
    • task: type: Reranking dataset: type: lyon-nlp/mteb-fr-reranking-alloprof-s2p name: MTEB AlloprofReranking config: default split: test revision: 666fdacebe0291776e86f29345663dfaf80a0db9 metrics:
      • type: map value: 64.8770878097632
      • type: mrr value: 66.39132423169396
    • task: type: Retrieval dataset: type: lyon-nlp/alloprof name: MTEB AlloprofRetrieval config: default split: test revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b metrics:
      • type: map_at_1 value: 29.62
      • type: map_at_10 value: 40.963
      • type: map_at_100 value: 41.894
      • type: map_at_1000 value: 41.939
      • type: map_at_3 value: 37.708999999999996
      • type: map_at_5 value: 39.696999999999996
      • type: mrr_at_1 value: 29.62
      • type: mrr_at_10 value: 40.963
      • type: mrr_at_100 value: 41.894
      • type: mrr_at_1000 value: 41.939
      • type: mrr_at_3 value: 37.708999999999996
      • type: mrr_at_5 value: 39.696999999999996
      • type: ndcg_at_1 value: 29.62
      • type: ndcg_at_10 value: 46.942
      • type: ndcg_at_100 value: 51.629999999999995
      • type: ndcg_at_1000 value: 52.927
      • type: ndcg_at_3 value: 40.333999999999996
      • type: ndcg_at_5 value: 43.922
      • type: precision_at_1 value: 29.62
      • type: precision_at_10 value: 6.589
      • type: precision_at_100 value: 0.882
      • type: precision_at_1000 value: 0.099
      • type: precision_at_3 value: 15.976
      • type: precision_at_5 value: 11.33
      • type: recall_at_1 value: 29.62
      • type: recall_at_10 value: 65.889
      • type: recall_at_100 value: 88.212
      • type: recall_at_1000 value: 98.575
      • type: recall_at_3 value: 47.927
      • type: recall_at_5 value: 56.64900000000001
    • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) config: fr split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
      • type: accuracy value: 42.077999999999996
      • type: f1 value: 40.64511241732637
    • task: type: Retrieval dataset: type: maastrichtlawtech/bsard name: MTEB BSARDRetrieval config: default split: test revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 metrics:
      • type: map_at_1 value: 0.901
      • type: map_at_10 value: 1.524
      • type: map_at_100 value: 1.833
      • type: map_at_1000 value: 1.916
      • type: map_at_3 value: 1.276
      • type: map_at_5 value: 1.276
      • type: mrr_at_1 value: 0.901
      • type: mrr_at_10 value: 1.524
      • type: mrr_at_100 value: 1.833
      • type: mrr_at_1000 value: 1.916
      • type: mrr_at_3 value: 1.276
      • type: mrr_at_5 value: 1.276
      • type: ndcg_at_1 value: 0.901
      • type: ndcg_at_10 value: 2.085
      • type: ndcg_at_100 value: 3.805
      • type: ndcg_at_1000 value: 6.704000000000001
      • type: ndcg_at_3 value: 1.41
      • type: ndcg_at_5 value: 1.41
      • type: precision_at_1 value: 0.901
      • type: precision_at_10 value: 0.40499999999999997
      • type: precision_at_100 value: 0.126
      • type: precision_at_1000 value: 0.037
      • type: precision_at_3 value: 0.601
      • type: precision_at_5 value: 0.36
      • type: recall_at_1 value: 0.901
      • type: recall_at_10 value: 4.054
      • type: recall_at_100 value: 12.613
      • type: recall_at_1000 value: 36.937
      • type: recall_at_3 value: 1.802
      • type: recall_at_5 value: 1.802
    • task: type: BitextMining dataset: type: rbawden/DiaBLa name: MTEB DiaBLaBitextMining (fr-en) config: fr-en split: test revision: 5345895c56a601afe1a98519ce3199be60a27dba metrics:
      • type: accuracy value: 88.90048712595686
      • type: f1 value: 86.94952864886115
      • type: precision value: 86.20344379175826
      • type: recall value: 88.90048712595686
    • task: type: Clustering dataset: type: lyon-nlp/clustering-hal-s2s name: MTEB HALClusteringS2S config: default split: test revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 metrics:
      • type: v_measure value: 24.087988843991155
    • task: type: Clustering dataset: type: mlsum name: MTEB MLSUMClusteringP2P config: default split: test revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 metrics:
      • type: v_measure value: 43.79603865728535
    • task: type: Clustering dataset: type: mlsum name: MTEB MLSUMClusteringS2S config: default split: test revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 metrics:
      • type: v_measure value: 37.746550373003
    • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (fr) config: fr split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
      • type: accuracy value: 89.26088318196052
      • type: f1 value: 88.95811185929033
    • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (fr) config: fr split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
      • type: accuracy value: 68.55308487316003
      • type: f1 value: 48.2936682439785
    • task: type: Classification dataset: type: masakhane/masakhanews name: MTEB MasakhaNEWSClassification (fra) config: fra split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics:
      • type: accuracy value: 81.51658767772511
      • type: f1 value: 77.695234448912
    • task: type: Clustering dataset: type: masakhane/masakhanews name: MTEB MasakhaNEWSClusteringP2P (fra) config: fra split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics:
      • type: v_measure value: 40.80377094681114
    • task: type: Clustering dataset: type: masakhane/masakhanews name: MTEB MasakhaNEWSClusteringS2S (fra) config: fra split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics:
      • type: v_measure value: 28.79703837416241
    • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fr) config: fr split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
      • type: accuracy value: 67.40080699394755
      • type: f1 value: 65.60793135686376
    • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (fr) config: fr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
      • type: accuracy value: 71.29455279085406
      • type: f1 value: 70.80876673828983
    • task: type: Retrieval dataset: type: jinaai/mintakaqa name: MTEB MintakaRetrieval (fr) config: fr split: test revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e metrics:
      • type: map_at_1 value: 16.625999999999998
      • type: map_at_10 value: 25.224999999999998
      • type: map_at_100 value: 26.291999999999998
      • type: map_at_1000 value: 26.395000000000003
      • type: map_at_3 value: 22.378999999999998
      • type: map_at_5 value: 24.009
      • type: mrr_at_1 value: 16.625999999999998
      • type: mrr_at_10 value: 25.224999999999998
      • type: mrr_at_100 value: 26.291999999999998
      • type: mrr_at_1000 value: 26.395000000000003
      • type: mrr_at_3 value: 22.378999999999998
      • type: mrr_at_5 value: 24.009
      • type: ndcg_at_1 value: 16.625999999999998
      • type: ndcg_at_10 value: 30.074
      • type: ndcg_at_100 value: 35.683
      • type: ndcg_at_1000 value: 38.714999999999996
      • type: ndcg_at_3 value: 24.188000000000002
      • type: ndcg_at_5 value: 27.124
      • type: precision_at_1 value: 16.625999999999998
      • type: precision_at_10 value: 4.566
      • type: precision_at_100 value: 0.729
      • type: precision_at_1000 value: 0.097
      • type: precision_at_3 value: 9.801
      • type: precision_at_5 value: 7.305000000000001
      • type: recall_at_1 value: 16.625999999999998
      • type: recall_at_10 value: 45.659
      • type: recall_at_100 value: 72.85000000000001
      • type: recall_at_1000 value: 97.42
      • type: recall_at_3 value: 29.402
      • type: recall_at_5 value: 36.527
    • task: type: PairClassification dataset: type: GEM/opusparcus name: MTEB OpusparcusPC (fr) config: fr split: test revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a metrics:
      • type: cos_sim_accuracy value: 83.58310626702998
      • type: cos_sim_ap value: 94.01979957812989
      • type: cos_sim_f1 value: 88.70135958743555
      • type: cos_sim_precision value: 84.01420959147424
      • type: cos_sim_recall value: 93.94240317775571
      • type: dot_accuracy value: 83.58310626702998
      • type: dot_ap value: 94.01979957812989
      • type: dot_f1 value: 88.70135958743555
      • type: dot_precision value: 84.01420959147424
      • type: dot_recall value: 93.94240317775571
      • type: euclidean_accuracy value: 83.58310626702998
      • type: euclidean_ap value: 94.01979957812989
      • type: euclidean_f1 value: 88.70135958743555
      • type: euclidean_precision value: 84.01420959147424
      • type: euclidean_recall value: 93.94240317775571
      • type: manhattan_accuracy value: 83.58310626702998
      • type: manhattan_ap value: 93.99936024003892
      • type: manhattan_f1 value: 88.6924150767799
      • type: manhattan_precision value: 83.45008756567425
      • type: manhattan_recall value: 94.63753723932473
      • type: max_accuracy value: 83.58310626702998
      • type: max_ap value: 94.01979957812989
      • type: max_f1 value: 88.70135958743555
    • task: type: PairClassification dataset: type: paws-x name: MTEB PawsX (fr) config: fr split: test revision: 8a04d940a42cd40658986fdd8e3da561533a3646 metrics:
      • type: cos_sim_accuracy value: 60.6
      • type: cos_sim_ap value: 60.18915797975459
      • type: cos_sim_f1 value: 62.491349480968864
      • type: cos_sim_precision value: 45.44539506794162
      • type: cos_sim_recall value: 100
      • type: dot_accuracy value: 60.6
      • type: dot_ap value: 60.091135216056024
      • type: dot_f1 value: 62.491349480968864
      • type: dot_precision value: 45.44539506794162
      • type: dot_recall value: 100
      • type: euclidean_accuracy value: 60.6
      • type: euclidean_ap value: 60.18915797975459
      • type: euclidean_f1 value: 62.491349480968864
      • type: euclidean_precision value: 45.44539506794162
      • type: euclidean_recall value: 100
      • type: manhattan_accuracy value: 60.650000000000006
      • type: manhattan_ap value: 60.2082343915352
      • type: manhattan_f1 value: 62.491349480968864
      • type: manhattan_precision value: 45.44539506794162
      • type: manhattan_recall value: 100
      • type: max_accuracy value: 60.650000000000006
      • type: max_ap value: 60.2082343915352
      • type: max_f1 value: 62.491349480968864
    • task: type: STS dataset: type: Lajavaness/SICK-fr name: MTEB SICKFr config: default split: test revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a metrics:
      • type: cos_sim_pearson value: 79.77067200230256
      • type: cos_sim_spearman value: 76.7445532523278
      • type: euclidean_pearson value: 76.34017074673956
      • type: euclidean_spearman value: 76.7453011027832
      • type: manhattan_pearson value: 76.19578084197778
      • type: manhattan_spearman value: 76.56293456459228
    • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr) config: fr split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics:
      • type: cos_sim_pearson value: 81.2564160237984
      • type: cos_sim_spearman value: 83.30552085410882
      • type: euclidean_pearson value: 82.00494560507786
      • type: euclidean_spearman value: 83.30552085410882
      • type: manhattan_pearson value: 81.93132229157803
      • type: manhattan_spearman value: 83.04357992939353
    • task: type: STS dataset: type: stsb_multi_mt name: MTEB STSBenchmarkMultilingualSTS (fr) config: fr split: test revision: 93d57ef91790589e3ce9c365164337a8a78b7632 metrics:
      • type: cos_sim_pearson value: 80.34931905288978
      • type: cos_sim_spearman value: 79.99372771100049
      • type: euclidean_pearson value: 78.37976845123443
      • type: euclidean_spearman value: 79.99452356550658
      • type: manhattan_pearson value: 78.24434042082316
      • type: manhattan_spearman value: 79.87248340061164
    • 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: 30.476001473421586
      • type: cos_sim_spearman value: 29.687350195905456
      • type: dot_pearson value: 30.476000875190685
      • type: dot_spearman value: 29.662224660056562
    • task: type: Reranking dataset: type: lyon-nlp/mteb-fr-reranking-syntec-s2p name: MTEB SyntecReranking config: default split: test revision: b205c5084a0934ce8af14338bf03feb19499c84d metrics:
      • type: map value: 88.28333333333333
      • type: mrr value: 88.28333333333333
    • task: type: Retrieval dataset: type: lyon-nlp/mteb-fr-retrieval-syntec-s2p name: MTEB SyntecRetrieval config: default split: test revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff metrics:
      • type: map_at_1 value: 69
      • type: map_at_10 value: 79.906
      • type: map_at_100 value: 79.982
      • type: map_at_1000 value: 79.982
      • type: map_at_3 value: 77.667
      • type: map_at_5 value: 79.51700000000001
      • type: mrr_at_1 value: 69
      • type: mrr_at_10 value: 79.906
      • type: mrr_at_100 value: 79.982
      • type: mrr_at_1000 value: 79.982
      • type: mrr_at_3 value: 77.667
      • type: mrr_at_5 value: 79.51700000000001
      • type: ndcg_at_1 value: 69
      • type: ndcg_at_10 value: 84.60499999999999
      • type: ndcg_at_100 value: 84.868
      • type: ndcg_at_1000 value: 84.868
      • type: ndcg_at_3 value: 80.333
      • type: ndcg_at_5 value: 83.647
      • type: precision_at_1 value: 69
      • type: precision_at_10 value: 9.9
      • type: precision_at_100 value: 1
      • type: precision_at_1000 value: 0.1
      • type: precision_at_3 value: 29.333
      • type: precision_at_5 value: 19.2
      • type: recall_at_1 value: 69
      • type: recall_at_10 value: 99
      • type: recall_at_100 value: 100
      • type: recall_at_1000 value: 100
      • type: recall_at_3 value: 88
      • type: recall_at_5 value: 96
    • task: type: Retrieval dataset: type: jinaai/xpqa name: MTEB XPQARetrieval (fr) config: fr split: test revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f metrics:
      • type: map_at_1 value: 42.027
      • type: map_at_10 value: 64.331
      • type: map_at_100 value: 65.657
      • type: map_at_1000 value: 65.7
      • type: map_at_3 value: 57.967999999999996
      • type: map_at_5 value: 62.33800000000001
      • type: mrr_at_1 value: 65.688
      • type: mrr_at_10 value: 72.263
      • type: mrr_at_100 value: 72.679
      • type: mrr_at_1000 value: 72.69099999999999
      • type: mrr_at_3 value: 70.405
      • type: mrr_at_5 value: 71.587
      • type: ndcg_at_1 value: 65.688
      • type: ndcg_at_10 value: 70.221
      • type: ndcg_at_100 value: 74.457
      • type: ndcg_at_1000 value: 75.178
      • type: ndcg_at_3 value: 65.423
      • type: ndcg_at_5 value: 67.05499999999999
      • type: precision_at_1 value: 65.688
      • type: precision_at_10 value: 16.208
      • type: precision_at_100 value: 1.975
      • type: precision_at_1000 value: 0.207
      • type: precision_at_3 value: 39.831
      • type: precision_at_5 value: 28.652
      • type: recall_at_1 value: 42.027
      • type: recall_at_10 value: 78.803
      • type: recall_at_100 value: 95.051
      • type: recall_at_1000 value: 99.75500000000001
      • type: recall_at_3 value: 62.62799999999999
      • type: recall_at_5 value: 70.975 license: mit language:
  • fr

lbourdoispro/Solon-embeddings-large-0.1

作者 lbourdoispro

↓ 13 ♥ 0

创建时间: 2025-11-25 23:19:28+00:00

更新时间: 2025-11-25 23:30:52+00:00

在 Hugging Face 上查看

文件 (13)

.gitattributes
1_Pooling/config.json
README.md
config.json
config_sentence_transformers.json
modules.json
onnx/model.onnx ONNX
onnx/model.onnx_data
onnx/model_qint8_avx512_vnni.onnx ONNX
sentence_bert_config.json
special_tokens_map.json
tokenizer.json
tokenizer_config.json