ONNX 模型库
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说明文档

tags:

  • sentence-transformers
  • feature-extraction
  • sentence-similarity
  • transformers
  • mteb model-index:
  • name: bge-small-en-v1.5 results:
    • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
      • type: accuracy value: 73.79104477611939
      • type: ap value: 37.21923821573361
      • type: f1 value: 68.0914945617093
    • task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
      • type: accuracy value: 92.75377499999999
      • type: ap value: 89.46766124546022
      • type: f1 value: 92.73884001331487
    • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
      • type: accuracy value: 46.986
      • type: f1 value: 46.55936786727896
    • task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
      • type: map_at_1 value: 35.846000000000004
      • type: map_at_10 value: 51.388
      • type: map_at_100 value: 52.132999999999996
      • type: map_at_1000 value: 52.141000000000005
      • type: map_at_3 value: 47.037
      • type: map_at_5 value: 49.579
      • type: mrr_at_1 value: 36.558
      • type: mrr_at_10 value: 51.658
      • type: mrr_at_100 value: 52.402
      • type: mrr_at_1000 value: 52.410000000000004
      • type: mrr_at_3 value: 47.345
      • type: mrr_at_5 value: 49.797999999999995
      • type: ndcg_at_1 value: 35.846000000000004
      • type: ndcg_at_10 value: 59.550000000000004
      • type: ndcg_at_100 value: 62.596
      • type: ndcg_at_1000 value: 62.759
      • type: ndcg_at_3 value: 50.666999999999994
      • type: ndcg_at_5 value: 55.228
      • type: precision_at_1 value: 35.846000000000004
      • type: precision_at_10 value: 8.542
      • type: precision_at_100 value: 0.984
      • type: precision_at_1000 value: 0.1
      • type: precision_at_3 value: 20.389
      • type: precision_at_5 value: 14.438
      • type: recall_at_1 value: 35.846000000000004
      • type: recall_at_10 value: 85.42
      • type: recall_at_100 value: 98.43499999999999
      • type: recall_at_1000 value: 99.644
      • type: recall_at_3 value: 61.166
      • type: recall_at_5 value: 72.191
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
      • type: v_measure value: 47.402770198163594
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
      • type: v_measure value: 40.01545436974177
    • task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
      • type: map value: 62.586465273207196
      • type: mrr value: 74.42169019038825
    • task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
      • type: cos_sim_pearson value: 85.1891186537969
      • type: cos_sim_spearman value: 83.75492046087288
      • type: euclidean_pearson value: 84.11766204805357
      • type: euclidean_spearman value: 84.01456493126516
      • type: manhattan_pearson value: 84.2132950502772
      • type: manhattan_spearman value: 83.89227298813377
    • task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
      • type: accuracy value: 85.74025974025975
      • type: f1 value: 85.71493566466381
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
      • type: v_measure value: 38.467181385006434
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
      • type: v_measure value: 34.719496037339056
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 29.587000000000003
      • type: map_at_10 value: 41.114
      • type: map_at_100 value: 42.532
      • type: map_at_1000 value: 42.661
      • type: map_at_3 value: 37.483
      • type: map_at_5 value: 39.652
      • type: mrr_at_1 value: 36.338
      • type: mrr_at_10 value: 46.763
      • type: mrr_at_100 value: 47.393
      • type: mrr_at_1000 value: 47.445
      • type: mrr_at_3 value: 43.538
      • type: mrr_at_5 value: 45.556000000000004
      • type: ndcg_at_1 value: 36.338
      • type: ndcg_at_10 value: 47.658
      • type: ndcg_at_100 value: 52.824000000000005
      • type: ndcg_at_1000 value: 54.913999999999994
      • type: ndcg_at_3 value: 41.989
      • type: ndcg_at_5 value: 44.944
      • type: precision_at_1 value: 36.338
      • type: precision_at_10 value: 9.156
      • type: precision_at_100 value: 1.4789999999999999
      • type: precision_at_1000 value: 0.196
      • type: precision_at_3 value: 20.076
      • type: precision_at_5 value: 14.85
      • type: recall_at_1 value: 29.587000000000003
      • type: recall_at_10 value: 60.746
      • type: recall_at_100 value: 82.157
      • type: recall_at_1000 value: 95.645
      • type: recall_at_3 value: 44.821
      • type: recall_at_5 value: 52.819
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 30.239
      • type: map_at_10 value: 39.989000000000004
      • type: map_at_100 value: 41.196
      • type: map_at_1000 value: 41.325
      • type: map_at_3 value: 37.261
      • type: map_at_5 value: 38.833
      • type: mrr_at_1 value: 37.516
      • type: mrr_at_10 value: 46.177
      • type: mrr_at_100 value: 46.806
      • type: mrr_at_1000 value: 46.849000000000004
      • type: mrr_at_3 value: 44.002
      • type: mrr_at_5 value: 45.34
      • type: ndcg_at_1 value: 37.516
      • type: ndcg_at_10 value: 45.586
      • type: ndcg_at_100 value: 49.897000000000006
      • type: ndcg_at_1000 value: 51.955
      • type: ndcg_at_3 value: 41.684
      • type: ndcg_at_5 value: 43.617
      • type: precision_at_1 value: 37.516
      • type: precision_at_10 value: 8.522
      • type: precision_at_100 value: 1.374
      • type: precision_at_1000 value: 0.184
      • type: precision_at_3 value: 20.105999999999998
      • type: precision_at_5 value: 14.152999999999999
      • type: recall_at_1 value: 30.239
      • type: recall_at_10 value: 55.03
      • type: recall_at_100 value: 73.375
      • type: recall_at_1000 value: 86.29599999999999
      • type: recall_at_3 value: 43.269000000000005
      • type: recall_at_5 value: 48.878
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 38.338
      • type: map_at_10 value: 50.468999999999994
      • type: map_at_100 value: 51.553000000000004
      • type: map_at_1000 value: 51.608
      • type: map_at_3 value: 47.107
      • type: map_at_5 value: 49.101
      • type: mrr_at_1 value: 44.201
      • type: mrr_at_10 value: 54.057
      • type: mrr_at_100 value: 54.764
      • type: mrr_at_1000 value: 54.791000000000004
      • type: mrr_at_3 value: 51.56699999999999
      • type: mrr_at_5 value: 53.05
      • type: ndcg_at_1 value: 44.201
      • type: ndcg_at_10 value: 56.379000000000005
      • type: ndcg_at_100 value: 60.645
      • type: ndcg_at_1000 value: 61.73499999999999
      • type: ndcg_at_3 value: 50.726000000000006
      • type: ndcg_at_5 value: 53.58500000000001
      • type: precision_at_1 value: 44.201
      • type: precision_at_10 value: 9.141
      • type: precision_at_100 value: 1.216
      • type: precision_at_1000 value: 0.135
      • type: precision_at_3 value: 22.654
      • type: precision_at_5 value: 15.723999999999998
      • type: recall_at_1 value: 38.338
      • type: recall_at_10 value: 70.30499999999999
      • type: recall_at_100 value: 88.77199999999999
      • type: recall_at_1000 value: 96.49799999999999
      • type: recall_at_3 value: 55.218
      • type: recall_at_5 value: 62.104000000000006
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 25.682
      • type: map_at_10 value: 33.498
      • type: map_at_100 value: 34.461000000000006
      • type: map_at_1000 value: 34.544000000000004
      • type: map_at_3 value: 30.503999999999998
      • type: map_at_5 value: 32.216
      • type: mrr_at_1 value: 27.683999999999997
      • type: mrr_at_10 value: 35.467999999999996
      • type: mrr_at_100 value: 36.32
      • type: mrr_at_1000 value: 36.386
      • type: mrr_at_3 value: 32.618
      • type: mrr_at_5 value: 34.262
      • type: ndcg_at_1 value: 27.683999999999997
      • type: ndcg_at_10 value: 38.378
      • type: ndcg_at_100 value: 43.288
      • type: ndcg_at_1000 value: 45.413
      • type: ndcg_at_3 value: 32.586
      • type: ndcg_at_5 value: 35.499
      • type: precision_at_1 value: 27.683999999999997
      • type: precision_at_10 value: 5.864
      • type: precision_at_100 value: 0.882
      • type: precision_at_1000 value: 0.11
      • type: precision_at_3 value: 13.446
      • type: precision_at_5 value: 9.718
      • type: recall_at_1 value: 25.682
      • type: recall_at_10 value: 51.712
      • type: recall_at_100 value: 74.446
      • type: recall_at_1000 value: 90.472
      • type: recall_at_3 value: 36.236000000000004
      • type: recall_at_5 value: 43.234
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 16.073999999999998
      • type: map_at_10 value: 24.352999999999998
      • type: map_at_100 value: 25.438
      • type: map_at_1000 value: 25.545
      • type: map_at_3 value: 21.614
      • type: map_at_5 value: 23.104
      • type: mrr_at_1 value: 19.776
      • type: mrr_at_10 value: 28.837000000000003
      • type: mrr_at_100 value: 29.755
      • type: mrr_at_1000 value: 29.817
      • type: mrr_at_3 value: 26.201999999999998
      • type: mrr_at_5 value: 27.714
      • type: ndcg_at_1 value: 19.776
      • type: ndcg_at_10 value: 29.701
      • type: ndcg_at_100 value: 35.307
      • type: ndcg_at_1000 value: 37.942
      • type: ndcg_at_3 value: 24.764
      • type: ndcg_at_5 value: 27.025
      • type: precision_at_1 value: 19.776
      • type: precision_at_10 value: 5.659
      • type: precision_at_100 value: 0.971
      • type: precision_at_1000 value: 0.133
      • type: precision_at_3 value: 12.065
      • type: precision_at_5 value: 8.905000000000001
      • type: recall_at_1 value: 16.073999999999998
      • type: recall_at_10 value: 41.647
      • type: recall_at_100 value: 66.884
      • type: recall_at_1000 value: 85.91499999999999
      • type: recall_at_3 value: 27.916
      • type: recall_at_5 value: 33.729
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 28.444999999999997
      • type: map_at_10 value: 38.218999999999994
      • type: map_at_100 value: 39.595
      • type: map_at_1000 value: 39.709
      • type: map_at_3 value: 35.586
      • type: map_at_5 value: 36.895
      • type: mrr_at_1 value: 34.841
      • type: mrr_at_10 value: 44.106
      • type: mrr_at_100 value: 44.98
      • type: mrr_at_1000 value: 45.03
      • type: mrr_at_3 value: 41.979
      • type: mrr_at_5 value: 43.047999999999995
      • type: ndcg_at_1 value: 34.841
      • type: ndcg_at_10 value: 43.922
      • type: ndcg_at_100 value: 49.504999999999995
      • type: ndcg_at_1000 value: 51.675000000000004
      • type: ndcg_at_3 value: 39.858
      • type: ndcg_at_5 value: 41.408
      • type: precision_at_1 value: 34.841
      • type: precision_at_10 value: 7.872999999999999
      • type: precision_at_100 value: 1.2449999999999999
      • type: precision_at_1000 value: 0.161
      • type: precision_at_3 value: 18.993
      • type: precision_at_5 value: 13.032
      • type: recall_at_1 value: 28.444999999999997
      • type: recall_at_10 value: 54.984
      • type: recall_at_100 value: 78.342
      • type: recall_at_1000 value: 92.77
      • type: recall_at_3 value: 42.842999999999996
      • type: recall_at_5 value: 47.247
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.072
      • type: map_at_10 value: 32.354
      • type: map_at_100 value: 33.800000000000004
      • type: map_at_1000 value: 33.908
      • type: map_at_3 value: 29.232000000000003
      • type: map_at_5 value: 31.049
      • type: mrr_at_1 value: 29.110000000000003
      • type: mrr_at_10 value: 38.03
      • type: mrr_at_100 value: 39.032
      • type: mrr_at_1000 value: 39.086999999999996
      • type: mrr_at_3 value: 35.407
      • type: mrr_at_5 value: 36.76
      • type: ndcg_at_1 value: 29.110000000000003
      • type: ndcg_at_10 value: 38.231
      • type: ndcg_at_100 value: 44.425
      • type: ndcg_at_1000 value: 46.771
      • type: ndcg_at_3 value: 33.095
      • type: ndcg_at_5 value: 35.459
      • type: precision_at_1 value: 29.110000000000003
      • type: precision_at_10 value: 7.215000000000001
      • type: precision_at_100 value: 1.2109999999999999
      • type: precision_at_1000 value: 0.157
      • type: precision_at_3 value: 16.058
      • type: precision_at_5 value: 11.644
      • type: recall_at_1 value: 23.072
      • type: recall_at_10 value: 50.285999999999994
      • type: recall_at_100 value: 76.596
      • type: recall_at_1000 value: 92.861
      • type: recall_at_3 value: 35.702
      • type: recall_at_5 value: 42.152
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.937916666666666
      • type: map_at_10 value: 33.755250000000004
      • type: map_at_100 value: 34.955999999999996
      • type: map_at_1000 value: 35.070499999999996
      • type: map_at_3 value: 30.98708333333333
      • type: map_at_5 value: 32.51491666666666
      • type: mrr_at_1 value: 29.48708333333333
      • type: mrr_at_10 value: 37.92183333333334
      • type: mrr_at_100 value: 38.76583333333333
      • type: mrr_at_1000 value: 38.82466666666667
      • type: mrr_at_3 value: 35.45125
      • type: mrr_at_5 value: 36.827000000000005
      • type: ndcg_at_1 value: 29.48708333333333
      • type: ndcg_at_10 value: 39.05225
      • type: ndcg_at_100 value: 44.25983333333334
      • type: ndcg_at_1000 value: 46.568333333333335
      • type: ndcg_at_3 value: 34.271583333333325
      • type: ndcg_at_5 value: 36.483916666666666
      • type: precision_at_1 value: 29.48708333333333
      • type: precision_at_10 value: 6.865749999999999
      • type: precision_at_100 value: 1.1195833333333332
      • type: precision_at_1000 value: 0.15058333333333335
      • type: precision_at_3 value: 15.742083333333333
      • type: precision_at_5 value: 11.221916666666667
      • type: recall_at_1 value: 24.937916666666666
      • type: recall_at_10 value: 50.650416666666665
      • type: recall_at_100 value: 73.55383333333334
      • type: recall_at_1000 value: 89.61691666666667
      • type: recall_at_3 value: 37.27808333333334
      • type: recall_at_5 value: 42.99475
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.947
      • type: map_at_10 value: 30.575000000000003
      • type: map_at_100 value: 31.465
      • type: map_at_1000 value: 31.558000000000003
      • type: map_at_3 value: 28.814
      • type: map_at_5 value: 29.738999999999997
      • type: mrr_at_1 value: 26.994
      • type: mrr_at_10 value: 33.415
      • type: mrr_at_100 value: 34.18
      • type: mrr_at_1000 value: 34.245
      • type: mrr_at_3 value: 31.621
      • type: mrr_at_5 value: 32.549
      • type: ndcg_at_1 value: 26.994
      • type: ndcg_at_10 value: 34.482
      • type: ndcg_at_100 value: 38.915
      • type: ndcg_at_1000 value: 41.355
      • type: ndcg_at_3 value: 31.139
      • type: ndcg_at_5 value: 32.589
      • type: precision_at_1 value: 26.994
      • type: precision_at_10 value: 5.322
      • type: precision_at_100 value: 0.8160000000000001
      • type: precision_at_1000 value: 0.11100000000000002
      • type: precision_at_3 value: 13.344000000000001
      • type: precision_at_5 value: 8.988
      • type: recall_at_1 value: 23.947
      • type: recall_at_10 value: 43.647999999999996
      • type: recall_at_100 value: 63.851
      • type: recall_at_1000 value: 82.0
      • type: recall_at_3 value: 34.288000000000004
      • type: recall_at_5 value: 38.117000000000004
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 16.197
      • type: map_at_10 value: 22.968
      • type: map_at_100 value: 24.095
      • type: map_at_1000 value: 24.217
      • type: map_at_3 value: 20.771
      • type: map_at_5 value: 21.995
      • type: mrr_at_1 value: 19.511
      • type: mrr_at_10 value: 26.55
      • type: mrr_at_100 value: 27.500999999999998
      • type: mrr_at_1000 value: 27.578999999999997
      • type: mrr_at_3 value: 24.421
      • type: mrr_at_5 value: 25.604
      • type: ndcg_at_1 value: 19.511
      • type: ndcg_at_10 value: 27.386
      • type: ndcg_at_100 value: 32.828
      • type: ndcg_at_1000 value: 35.739
      • type: ndcg_at_3 value: 23.405
      • type: ndcg_at_5 value: 25.255
      • type: precision_at_1 value: 19.511
      • type: precision_at_10 value: 5.017
      • type: precision_at_100 value: 0.91
      • type: precision_at_1000 value: 0.133
      • type: precision_at_3 value: 11.023
      • type: precision_at_5 value: 8.025
      • type: recall_at_1 value: 16.197
      • type: recall_at_10 value: 37.09
      • type: recall_at_100 value: 61.778
      • type: recall_at_1000 value: 82.56599999999999
      • type: recall_at_3 value: 26.034000000000002
      • type: recall_at_5 value: 30.762
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 25.41
      • type: map_at_10 value: 33.655
      • type: map_at_100 value: 34.892
      • type: map_at_1000 value: 34.995
      • type: map_at_3 value: 30.94
      • type: map_at_5 value: 32.303
      • type: mrr_at_1 value: 29.477999999999998
      • type: mrr_at_10 value: 37.443
      • type: mrr_at_100 value: 38.383
      • type: mrr_at_1000 value: 38.440000000000005
      • type: mrr_at_3 value: 34.949999999999996
      • type: mrr_at_5 value: 36.228
      • type: ndcg_at_1 value: 29.477999999999998
      • type: ndcg_at_10 value: 38.769
      • type: ndcg_at_100 value: 44.245000000000005
      • type: ndcg_at_1000 value: 46.593
      • type: ndcg_at_3 value: 33.623
      • type: ndcg_at_5 value: 35.766
      • type: precision_at_1 value: 29.477999999999998
      • type: precision_at_10 value: 6.455
      • type: precision_at_100 value: 1.032
      • type: precision_at_1000 value: 0.135
      • type: precision_at_3 value: 14.893999999999998
      • type: precision_at_5 value: 10.485
      • type: recall_at_1 value: 25.41
      • type: recall_at_10 value: 50.669
      • type: recall_at_100 value: 74.084
      • type: recall_at_1000 value: 90.435
      • type: recall_at_3 value: 36.679
      • type: recall_at_5 value: 41.94
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.339
      • type: map_at_10 value: 31.852000000000004
      • type: map_at_100 value: 33.411
      • type: map_at_1000 value: 33.62
      • type: map_at_3 value: 28.929
      • type: map_at_5 value: 30.542
      • type: mrr_at_1 value: 28.063
      • type: mrr_at_10 value: 36.301
      • type: mrr_at_100 value: 37.288
      • type: mrr_at_1000 value: 37.349
      • type: mrr_at_3 value: 33.663
      • type: mrr_at_5 value: 35.165
      • type: ndcg_at_1 value: 28.063
      • type: ndcg_at_10 value: 37.462
      • type: ndcg_at_100 value: 43.620999999999995
      • type: ndcg_at_1000 value: 46.211
      • type: ndcg_at_3 value: 32.68
      • type: ndcg_at_5 value: 34.981
      • type: precision_at_1 value: 28.063
      • type: precision_at_10 value: 7.1739999999999995
      • type: precision_at_100 value: 1.486
      • type: precision_at_1000 value: 0.23500000000000001
      • type: precision_at_3 value: 15.217
      • type: precision_at_5 value: 11.265
      • type: recall_at_1 value: 23.339
      • type: recall_at_10 value: 48.376999999999995
      • type: recall_at_100 value: 76.053
      • type: recall_at_1000 value: 92.455
      • type: recall_at_3 value: 34.735
      • type: recall_at_5 value: 40.71
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 18.925
      • type: map_at_10 value: 26.017000000000003
      • type: map_at_100 value: 27.034000000000002
      • type: map_at_1000 value: 27.156000000000002
      • type: map_at_3 value: 23.604
      • type: map_at_5 value: 24.75
      • type: mrr_at_1 value: 20.333000000000002
      • type: mrr_at_10 value: 27.915
      • type: mrr_at_100 value: 28.788000000000004
      • type: mrr_at_1000 value: 28.877999999999997
      • type: mrr_at_3 value: 25.446999999999996
      • type: mrr_at_5 value: 26.648
      • type: ndcg_at_1 value: 20.333000000000002
      • type: ndcg_at_10 value: 30.673000000000002
      • type: ndcg_at_100 value: 35.618
      • type: ndcg_at_1000 value: 38.517
      • type: ndcg_at_3 value: 25.71
      • type: ndcg_at_5 value: 27.679
      • type: precision_at_1 value: 20.333000000000002
      • type: precision_at_10 value: 4.9910000000000005
      • type: precision_at_100 value: 0.8130000000000001
      • type: precision_at_1000 value: 0.117
      • type: precision_at_3 value: 11.029
      • type: precision_at_5 value: 7.8740000000000006
      • type: recall_at_1 value: 18.925
      • type: recall_at_10 value: 43.311
      • type: recall_at_100 value: 66.308
      • type: recall_at_1000 value: 87.49
      • type: recall_at_3 value: 29.596
      • type: recall_at_5 value: 34.245
    • task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 13.714
      • type: map_at_10 value: 23.194
      • type: map_at_100 value: 24.976000000000003
      • type: map_at_1000 value: 25.166
      • type: map_at_3 value: 19.709
      • type: map_at_5 value: 21.523999999999997
      • type: mrr_at_1 value: 30.619000000000003
      • type: mrr_at_10 value: 42.563
      • type: mrr_at_100 value: 43.386
      • type: mrr_at_1000 value: 43.423
      • type: mrr_at_3 value: 39.555
      • type: mrr_at_5 value: 41.268
      • type: ndcg_at_1 value: 30.619000000000003
      • type: ndcg_at_10 value: 31.836
      • type: ndcg_at_100 value: 38.652
      • type: ndcg_at_1000 value: 42.088
      • type: ndcg_at_3 value: 26.733
      • type: ndcg_at_5 value: 28.435
      • type: precision_at_1 value: 30.619000000000003
      • type: precision_at_10 value: 9.751999999999999
      • type: precision_at_100 value: 1.71
      • type: precision_at_1000 value: 0.23500000000000001
      • type: precision_at_3 value: 19.935
      • type: precision_at_5 value: 14.984
      • type: recall_at_1 value: 13.714
      • type: recall_at_10 value: 37.26
      • type: recall_at_100 value: 60.546
      • type: recall_at_1000 value: 79.899
      • type: recall_at_3 value: 24.325
      • type: recall_at_5 value: 29.725
    • task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
      • type: map_at_1 value: 8.462
      • type: map_at_10 value: 18.637
      • type: map_at_100 value: 26.131999999999998
      • type: map_at_1000 value: 27.607
      • type: map_at_3 value: 13.333
      • type: map_at_5 value: 15.654000000000002
      • type: mrr_at_1 value: 66.25
      • type: mrr_at_10 value: 74.32600000000001
      • type: mrr_at_100 value: 74.60900000000001
      • type: mrr_at_1000 value: 74.62
      • type: mrr_at_3 value: 72.667
      • type: mrr_at_5 value: 73.817
      • type: ndcg_at_1 value: 53.87499999999999
      • type: ndcg_at_10 value: 40.028999999999996
      • type: ndcg_at_100 value: 44.199
      • type: ndcg_at_1000 value: 51.629999999999995
      • type: ndcg_at_3 value: 44.113
      • type: ndcg_at_5 value: 41.731
      • type: precision_at_1 value: 66.25
      • type: precision_at_10 value: 31.900000000000002
      • type: precision_at_100 value: 10.043000000000001
      • type: precision_at_1000 value: 1.926
      • type: precision_at_3 value: 47.417
      • type: precision_at_5 value: 40.65
      • type: recall_at_1 value: 8.462
      • type: recall_at_10 value: 24.293
      • type: recall_at_100 value: 50.146
      • type: recall_at_1000 value: 74.034
      • type: recall_at_3 value: 14.967
      • type: recall_at_5 value: 18.682000000000002
    • task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
      • type: accuracy value: 47.84499999999999
      • type: f1 value: 42.48106691979349
    • task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 74.034
      • type: map_at_10 value: 82.76
      • type: map_at_100 value: 82.968
      • type: map_at_1000 value: 82.98299999999999
      • type: map_at_3 value: 81.768
      • type: map_at_5 value: 82.418
      • type: mrr_at_1 value: 80.048
      • type: mrr_at_10 value: 87.64999999999999
      • type: mrr_at_100 value: 87.712
      • type: mrr_at_1000 value: 87.713
      • type: mrr_at_3 value: 87.01100000000001
      • type: mrr_at_5 value: 87.466
      • type: ndcg_at_1 value: 80.048
      • type: ndcg_at_10 value: 86.643
      • type: ndcg_at_100 value: 87.361
      • type: ndcg_at_1000 value: 87.606
      • type: ndcg_at_3 value: 85.137
      • type: ndcg_at_5 value: 86.016
      • type: precision_at_1 value: 80.048
      • type: precision_at_10 value: 10.372
      • type: precision_at_100 value: 1.093
      • type: precision_at_1000 value: 0.11299999999999999
      • type: precision_at_3 value: 32.638
      • type: precision_at_5 value: 20.177
      • type: recall_at_1 value: 74.034
      • type: recall_at_10 value: 93.769
      • type: recall_at_100 value: 96.569
      • type: recall_at_1000 value: 98.039
      • type: recall_at_3 value: 89.581
      • type: recall_at_5 value: 91.906
    • task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
      • type: map_at_1 value: 20.5
      • type: map_at_10 value: 32.857
      • type: map_at_100 value: 34.589
      • type: map_at_1000 value: 34.778
      • type: map_at_3 value: 29.160999999999998
      • type: map_at_5 value: 31.033
      • type: mrr_at_1 value: 40.123
      • type: mrr_at_10 value: 48.776
      • type: mrr_at_100 value: 49.495
      • type: mrr_at_1000 value: 49.539
      • type: mrr_at_3 value: 46.605000000000004
      • type: mrr_at_5 value: 47.654
      • type: ndcg_at_1 value: 40.123
      • type: ndcg_at_10 value: 40.343
      • type: ndcg_at_100 value: 46.56
      • type: ndcg_at_1000 value: 49.777
      • type: ndcg_at_3 value: 37.322
      • type: ndcg_at_5 value: 37.791000000000004
      • type: precision_at_1 value: 40.123
      • type: precision_at_10 value: 11.08
      • type: precision_at_100 value: 1.752
      • type: precision_at_1000 value: 0.232
      • type: precision_at_3 value: 24.897
      • type: precision_at_5 value: 17.809
      • type: recall_at_1 value: 20.5
      • type: recall_at_10 value: 46.388
      • type: recall_at_100 value: 69.552
      • type: recall_at_1000 value: 89.011
      • type: recall_at_3 value: 33.617999999999995
      • type: recall_at_5 value: 38.211
    • task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
      • type: map_at_1 value: 39.135999999999996
      • type: map_at_10 value: 61.673
      • type: map_at_100 value: 62.562
      • type: map_at_1000 value: 62.62
      • type: map_at_3 value: 58.467999999999996
      • type: map_at_5 value: 60.463
      • type: mrr_at_1 value: 78.271
      • type: mrr_at_10 value: 84.119
      • type: mrr_at_100 value: 84.29299999999999
      • type: mrr_at_1000 value: 84.299
      • type: mrr_at_3 value: 83.18900000000001
      • type: mrr_at_5 value: 83.786
      • type: ndcg_at_1 value: 78.271
      • type: ndcg_at_10 value: 69.935
      • type: ndcg_at_100 value: 73.01299999999999
      • type: ndcg_at_1000 value: 74.126
      • type: ndcg_at_3 value: 65.388
      • type: ndcg_at_5 value: 67.906
      • type: precision_at_1 value: 78.271
      • type: precision_at_10 value: 14.562
      • type: precision_at_100 value: 1.6969999999999998
      • type: precision_at_1000 value: 0.184
      • type: precision_at_3 value: 41.841
      • type: precision_at_5 value: 27.087
      • type: recall_at_1 value: 39.135999999999996
      • type: recall_at_10 value: 72.809
      • type: recall_at_100 value: 84.86200000000001
      • type: recall_at_1000 value: 92.208
      • type: recall_at_3 value: 62.76199999999999
      • type: recall_at_5 value: 67.718
    • task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
      • type: accuracy value: 90.60600000000001
      • type: ap value: 86.6579587804335
      • type: f1 value: 90.5938853929307
    • task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
      • type: map_at_1 value: 21.852
      • type: map_at_10 value: 33.982
      • type: map_at_100 value: 35.116
      • type: map_at_1000 value: 35.167
      • type: map_at_3 value: 30.134
      • type: map_at_5 value: 32.340999999999994
      • type: mrr_at_1 value: 22.479
      • type: mrr_at_10 value: 34.594
      • type: mrr_at_100 value: 35.672
      • type: mrr_at_1000 value: 35.716
      • type: mrr_at_3 value: 30.84
      • type: mrr_at_5 value: 32.998
      • type: ndcg_at_1 value: 22.493
      • type: ndcg_at_10 value: 40.833000000000006
      • type: ndcg_at_100 value: 46.357
      • type: ndcg_at_1000 value: 47.637
      • type: ndcg_at_3 value: 32.995999999999995
      • type: ndcg_at_5 value: 36.919000000000004
      • type: precision_at_1 value: 22.493
      • type: precision_at_10 value: 6.465999999999999
      • type: precision_at_100 value: 0.9249999999999999
      • type: precision_at_1000 value: 0.104
      • type: precision_at_3 value: 14.030999999999999
      • type: precision_at_5 value: 10.413
      • type: recall_at_1 value: 21.852
      • type: recall_at_10 value: 61.934999999999995
      • type: recall_at_100 value: 87.611
      • type: recall_at_1000 value: 97.441
      • type: recall_at_3 value: 40.583999999999996
      • type: recall_at_5 value: 49.992999999999995
    • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
      • type: accuracy value: 93.36069311445507
      • type: f1 value: 93.16456330371453
    • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
      • type: accuracy value: 74.74692202462381
      • type: f1 value: 58.17903579421599
    • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
      • type: accuracy value: 74.80833893745796
      • type: f1 value: 72.70786592684664
    • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
      • type: accuracy value: 78.69872225958305
      • type: f1 value: 78.61626934504731
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
      • type: v_measure value: 33.058658628717694
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
      • type: v_measure value: 30.85561739360599
    • task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
      • type: map value: 31.290259910144385
      • type: mrr value: 32.44223046102856
    • task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
      • type: map_at_1 value: 5.288
      • type: map_at_10 value: 12.267999999999999
      • type: map_at_100 value: 15.557000000000002
      • type: map_at_1000 value: 16.98
      • type: map_at_3 value: 8.866
      • type: map_at_5 value: 10.418
      • type: mrr_at_1 value: 43.653
      • type: mrr_at_10 value: 52.681
      • type: mrr_at_100 value: 53.315999999999995
      • type: mrr_at_1000 value: 53.357
      • type: mrr_at_3 value: 51.393
      • type: mrr_at_5 value: 51.903999999999996
      • type: ndcg_at_1 value: 42.415000000000006
      • type: ndcg_at_10 value: 34.305
      • type: ndcg_at_100 value: 30.825999999999997
      • type: ndcg_at_1000 value: 39.393
      • type: ndcg_at_3 value: 39.931
      • type: ndcg_at_5 value: 37.519999999999996
      • type: precision_at_1 value: 43.653
      • type: precision_at_10 value: 25.728
      • type: precision_at_100 value: 7.932
      • type: precision_at_1000 value: 2.07
      • type: precision_at_3 value: 38.184000000000005
      • type: precision_at_5 value: 32.879000000000005
      • type: recall_at_1 value: 5.288
      • type: recall_at_10 value: 16.195
      • type: recall_at_100 value: 31.135
      • type: recall_at_1000 value: 61.531000000000006
      • type: recall_at_3 value: 10.313
      • type: recall_at_5 value: 12.754999999999999
    • task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
      • type: map_at_1 value: 28.216
      • type: map_at_10 value: 42.588
      • type: map_at_100 value: 43.702999999999996
      • type: map_at_1000 value: 43.739
      • type: map_at_3 value: 38.177
      • type: map_at_5 value: 40.754000000000005
      • type: mrr_at_1 value: 31.866
      • type: mrr_at_10 value: 45.189
      • type: mrr_at_100 value: 46.056000000000004
      • type: mrr_at_1000 value: 46.081
      • type: mrr_at_3 value: 41.526999999999994
      • type: mrr_at_5 value: 43.704
      • type: ndcg_at_1 value: 31.837
      • type: ndcg_at_10 value: 50.178
      • type: ndcg_at_100 value: 54.98800000000001
      • type: ndcg_at_1000 value: 55.812
      • type: ndcg_at_3 value: 41.853
      • type: ndcg_at_5 value: 46.153
      • type: precision_at_1 value: 31.837
      • type: precision_at_10 value: 8.43
      • type: precision_at_100 value: 1.1119999999999999
      • type: precision_at_1000 value: 0.11900000000000001
      • type: precision_at_3 value: 19.023
      • type: precision_at_5 value: 13.911000000000001
      • type: recall_at_1 value: 28.216
      • type: recall_at_10 value: 70.8
      • type: recall_at_100 value: 91.857
      • type: recall_at_1000 value: 97.941
      • type: recall_at_3 value: 49.196
      • type: recall_at_5 value: 59.072
    • task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 71.22800000000001
      • type: map_at_10 value: 85.115
      • type: map_at_100 value: 85.72
      • type: map_at_1000 value: 85.737
      • type: map_at_3 value: 82.149
      • type: map_at_5 value: 84.029
      • type: mrr_at_1 value: 81.96
      • type: mrr_at_10 value: 88.00200000000001
      • type: mrr_at_100 value: 88.088
      • type: mrr_at_1000 value: 88.089
      • type: mrr_at_3 value: 87.055
      • type: mrr_at_5 value: 87.715
      • type: ndcg_at_1 value: 82.01
      • type: ndcg_at_10 value: 88.78
      • type: ndcg_at_100 value: 89.91
      • type: ndcg_at_1000 value: 90.013
      • type: ndcg_at_3 value: 85.957
      • type: ndcg_at_5 value: 87.56
      • type: precision_at_1 value: 82.01
      • type: precision_at_10 value: 13.462
      • type: precision_at_100 value: 1.528
      • type: precision_at_1000 value: 0.157
      • type: precision_at_3 value: 37.553
      • type: precision_at_5 value: 24.732000000000003
      • type: recall_at_1 value: 71.22800000000001
      • type: recall_at_10 value: 95.69
      • type: recall_at_100 value: 99.531
      • type: recall_at_1000 value: 99.98
      • type: recall_at_3 value: 87.632
      • type: recall_at_5 value: 92.117
    • task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
      • type: v_measure value: 52.31768034366916
    • task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
      • type: v_measure value: 60.640266772723606
    • task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
      • type: map_at_1 value: 4.7780000000000005
      • type: map_at_10 value: 12.299
      • type: map_at_100 value: 14.363000000000001
      • type: map_at_1000 value: 14.71
      • type: map_at_3 value: 8.738999999999999
      • type: map_at_5 value: 10.397
      • type: mrr_at_1 value: 23.599999999999998
      • type: mrr_at_10 value: 34.845
      • type: mrr_at_100 value: 35.916
      • type: mrr_at_1000 value: 35.973
      • type: mrr_at_3 value: 31.7
      • type: mrr_at_5 value: 33.535
      • type: ndcg_at_1 value: 23.599999999999998
      • type: ndcg_at_10 value: 20.522000000000002
      • type: ndcg_at_100 value: 28.737000000000002
      • type: ndcg_at_1000 value: 34.596
      • type: ndcg_at_3 value: 19.542
      • type: ndcg_at_5 value: 16.958000000000002
      • type: precision_at_1 value: 23.599999999999998
      • type: precision_at_10 value: 10.67
      • type: precision_at_100 value: 2.259
      • type: precision_at_1000 value: 0.367
      • type: precision_at_3 value: 18.333
      • type: precision_at_5 value: 14.879999999999999
      • type: recall_at_1 value: 4.7780000000000005
      • type: recall_at_10 value: 21.617
      • type: recall_at_100 value: 45.905
      • type: recall_at_1000 value: 74.42
      • type: recall_at_3 value: 11.148
      • type: recall_at_5 value: 15.082999999999998
    • task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
      • type: cos_sim_pearson value: 83.22372750297885
      • type: cos_sim_spearman value: 79.40972617119405
      • type: euclidean_pearson value: 80.6101072020434
      • type: euclidean_spearman value: 79.53844217225202
      • type: manhattan_pearson value: 80.57265975286111
      • type: manhattan_spearman value: 79.46335611792958
    • task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
      • type: cos_sim_pearson value: 85.43713315520749
      • type: cos_sim_spearman value: 77.44128693329532
      • type: euclidean_pearson value: 81.63869928101123
      • type: euclidean_spearman value: 77.29512977961515
      • type: manhattan_pearson value: 81.63704185566183
      • type: manhattan_spearman value: 77.29909412738657
    • task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
      • type: cos_sim_pearson value: 81.59451537860527
      • type: cos_sim_spearman value: 82.97994638856723
      • type: euclidean_pearson value: 82.89478688288412
      • type: euclidean_spearman value: 83.58740751053104
      • type: manhattan_pearson value: 82.69140840941608
      • type: manhattan_spearman value: 83.33665956040555
    • task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
      • type: cos_sim_pearson value: 82.00756527711764
      • type: cos_sim_spearman value: 81.83560996841379
      • type: euclidean_pearson value: 82.07684151976518
      • type: euclidean_spearman value: 82.00913052060511
      • type: manhattan_pearson value: 82.05690778488794
      • type: manhattan_spearman value: 82.02260252019525
    • task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
      • type: cos_sim_pearson value: 86.13710262895447
      • type: cos_sim_spearman value: 87.26412811156248
      • type: euclidean_pearson value: 86.94151453230228
      • type: euclidean_spearman value: 87.5363796699571
      • type: manhattan_pearson value: 86.86989424083748
      • type: manhattan_spearman value: 87.47315940781353
    • task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
      • type: cos_sim_pearson value: 83.0230597603627
      • type: cos_sim_spearman value: 84.93344499318864
      • type: euclidean_pearson value: 84.23754743431141
      • type: euclidean_spearman value: 85.09707376597099
      • type: manhattan_pearson value: 84.04325160987763
      • type: manhattan_spearman value: 84.89353071339909
    • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
      • type: cos_sim_pearson value: 86.75620824563921
      • type: cos_sim_spearman value: 87.15065513706398
      • type: euclidean_pearson value: 88.26281533633521
      • type: euclidean_spearman value: 87.51963738643983
      • type: manhattan_pearson value: 88.25599267618065
      • type: manhattan_spearman value: 87.58048736047483
    • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
      • type: cos_sim_pearson value: 64.74645319195137
      • type: cos_sim_spearman value: 65.29996325037214
      • type: euclidean_pearson value: 67.04297794086443
      • type: euclidean_spearman value: 65.43841726694343
      • type: manhattan_pearson value: 67.39459955690904
      • type: manhattan_spearman value: 65.92864704413651
    • task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
      • type: cos_sim_pearson value: 84.31291020270801
      • type: cos_sim_spearman value: 85.86473738688068
      • type: euclidean_pearson value: 85.65537275064152
      • type: euclidean_spearman value: 86.13087454209642
      • type: manhattan_pearson value: 85.43946955047609
      • type: manhattan_spearman value: 85.91568175344916
    • task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
      • type: map value: 85.93798118350695
      • type: mrr value: 95.93536274908824
    • task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
      • type: map_at_1 value: 57.594
      • type: map_at_10 value: 66.81899999999999
      • type: map_at_100 value: 67.368
      • type: map_at_1000 value: 67.4
      • type: map_at_3 value: 64.061
      • type: map_at_5 value: 65.47
      • type: mrr_at_1 value: 60.667
      • type: mrr_at_10 value: 68.219
      • type: mrr_at_100 value: 68.655
      • type: mrr_at_1000 value: 68.684
      • type: mrr_at_3 value: 66.22200000000001
      • type: mrr_at_5 value: 67.289
      • type: ndcg_at_1 value: 60.667
      • type: ndcg_at_10 value: 71.275
      • type: ndcg_at_100 value: 73.642
      • type: ndcg_at_1000 value: 74.373
      • type: ndcg_at_3 value: 66.521
      • type: ndcg_at_5 value: 68.581
      • type: precision_at_1 value: 60.667
      • type: precision_at_10 value: 9.433
      • type: precision_at_100 value: 1.0699999999999998
      • type: precision_at_1000 value: 0.11299999999999999
      • type: precision_at_3 value: 25.556
      • type: precision_at_5 value: 16.8
      • type: recall_at_1 value: 57.594
      • type: recall_at_10 value: 83.622
      • type: recall_at_100 value: 94.167
      • type: recall_at_1000 value: 99.667
      • type: recall_at_3 value: 70.64399999999999
      • type: recall_at_5 value: 75.983
    • task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics:
      • type: cos_sim_accuracy value: 99.85841584158416
      • type: cos_sim_ap value: 96.66996142314342
      • type: cos_sim_f1 value: 92.83208020050125
      • type: cos_sim_precision value: 93.06532663316584
      • type: cos_sim_recall value: 92.60000000000001
      • type: dot_accuracy value: 99.85841584158416
      • type: dot_ap value: 96.6775307676576
      • type: dot_f1 value: 92.69289729177312
      • type: dot_precision value: 94.77533960292581
      • type: dot_recall value: 90.7
      • type: euclidean_accuracy value: 99.86138613861387
      • type: euclidean_ap value: 96.6338454403108
      • type: euclidean_f1 value: 92.92214357937311
      • type: euclidean_precision value: 93.96728016359918
      • type: euclidean_recall value: 91.9
      • type: manhattan_accuracy value: 99.86237623762376
      • type: manhattan_ap value: 96.60370449645053
      • type: manhattan_f1 value: 92.91177970423253
      • type: manhattan_precision value: 94.7970863683663
      • type: manhattan_recall value: 91.10000000000001
      • type: max_accuracy value: 99.86237623762376
      • type: max_ap value: 96.6775307676576
      • type: max_f1 value: 92.92214357937311
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics:
      • type: v_measure value: 60.77977058695198
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics:
      • type: v_measure value: 35.2725272535638
    • task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics:
      • type: map value: 53.64052466362125
      • type: mrr value: 54.533067014684654
    • task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics:
      • type: cos_sim_pearson value: 30.677624219206578
      • type: cos_sim_spearman value: 30.121368518123447
      • type: dot_pearson value: 30.69870088041608
      • type: dot_spearman value: 29.61284927093751
    • task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics:
      • type: map_at_1 value: 0.22
      • type: map_at_10 value: 1.855
      • type: map_at_100 value: 9.885
      • type: map_at_1000 value: 23.416999999999998
      • type: map_at_3 value: 0.637
      • type: map_at_5 value: 1.024
      • type: mrr_at_1 value: 88.0
      • type: mrr_at_10 value: 93.067
      • type: mrr_at_100 value: 93.067
      • type: mrr_at_1000 value: 93.067
      • type: mrr_at_3 value: 92.667
      • type: mrr_at_5 value: 93.067
      • type: ndcg_at_1 value: 82.0
      • type: ndcg_at_10 value: 75.899
      • type: ndcg_at_100 value: 55.115
      • type: ndcg_at_1000 value: 48.368
      • type: ndcg_at_3 value: 79.704
      • type: ndcg_at_5 value: 78.39699999999999
      • type: precision_at_1 value: 88.0
      • type: precision_at_10 value: 79.60000000000001
      • type: precision_at_100 value: 56.06
      • type: precision_at_1000 value: 21.206
      • type: precision_at_3 value: 84.667
      • type: precision_at_5 value: 83.2
      • type: recall_at_1 value: 0.22
      • type: recall_at_10 value: 2.078
      • type: recall_at_100 value: 13.297
      • type: recall_at_1000 value: 44.979
      • type: recall_at_3 value: 0.6689999999999999
      • type: recall_at_5 value: 1.106
    • task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics:
      • type: map_at_1 value: 2.258
      • type: map_at_10 value: 10.439
      • type: map_at_100 value: 16.89
      • type: map_at_1000 value: 18.407999999999998
      • type: map_at_3 value: 5.668
      • type: map_at_5 value: 7.718
      • type: mrr_at_1 value: 32.653
      • type: mrr_at_10 value: 51.159
      • type: mrr_at_100 value: 51.714000000000006
      • type: mrr_at_1000 value: 51.714000000000006
      • type: mrr_at_3 value: 47.959
      • type: mrr_at_5 value: 50.407999999999994
      • type: ndcg_at_1 value: 29.592000000000002
      • type: ndcg_at_10 value: 26.037
      • type: ndcg_at_100 value: 37.924
      • type: ndcg_at_1000 value: 49.126999999999995
      • type: ndcg_at_3 value: 30.631999999999998
      • type: ndcg_at_5 value: 28.571
      • type: precision_at_1 value: 32.653
      • type: precision_at_10 value: 22.857
      • type: precision_at_100 value: 7.754999999999999
      • type: precision_at_1000 value: 1.529
      • type: precision_at_3 value: 34.014
      • type: precision_at_5 value: 29.796
      • type: recall_at_1 value: 2.258
      • type: recall_at_10 value: 16.554
      • type: recall_at_100 value: 48.439
      • type: recall_at_1000 value: 82.80499999999999
      • type: recall_at_3 value: 7.283
      • type: recall_at_5 value: 10.732
    • task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics:
      • type: accuracy value: 69.8858
      • type: ap value: 13.835684144362109
      • type: f1 value: 53.803351693244586
    • task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics:
      • type: accuracy value: 60.50650820599886
      • type: f1 value: 60.84357825979259
    • task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics:
      • type: v_measure value: 48.52131044852134
    • task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics:
      • type: cos_sim_accuracy value: 85.59337187816654
      • type: cos_sim_ap value: 73.23925826533437
      • type: cos_sim_f1 value: 67.34693877551021
      • type: cos_sim_precision value: 62.40432237730752
      • type: cos_sim_recall value: 73.13984168865434
      • type: dot_accuracy value: 85.31322644096085
      • type: dot_ap value: 72.30723963807422
      • type: dot_f1 value: 66.47051612112296
      • type: dot_precision value: 62.0792305930845
      • type: dot_recall value: 71.53034300791556
      • type: euclidean_accuracy value: 85.61125350181797
      • type: euclidean_ap value: 73.32843720487845
      • type: euclidean_f1 value: 67.36549633745895
      • type: euclidean_precision value: 64.60755813953489
      • type: euclidean_recall value: 70.36939313984169
      • type: manhattan_accuracy value: 85.63509566668654
      • type: manhattan_ap value: 73.16658488311325
      • type: manhattan_f1 value: 67.20597386434349
      • type: manhattan_precision value: 63.60424028268551
      • type: manhattan_recall value: 71.2401055408971
      • type: max_accuracy value: 85.63509566668654
      • type: max_ap value: 73.32843720487845
      • type: max_f1 value: 67.36549633745895
    • task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics:
      • type: cos_sim_accuracy value: 88.33779640625606
      • type: cos_sim_ap value: 84.83868375898157
      • type: cos_sim_f1 value: 77.16506154017773
      • type: cos_sim_precision value: 74.62064005753327
      • type: cos_sim_recall value: 79.88912842623961
      • type: dot_accuracy value: 88.02732176815307
      • type: dot_ap value: 83.95089283763002
      • type: dot_f1 value: 76.29635101196631
      • type: dot_precision value: 73.31771720613288
      • type: dot_recall value: 79.52725592854944
      • type: euclidean_accuracy value: 88.44452206310397
      • type: euclidean_ap value: 84.98384576824827
      • type: euclidean_f1 value: 77.29311047696697
      • type: euclidean_precision value: 74.51232583065381
      • type: euclidean_recall value: 80.28949799815214
      • type: manhattan_accuracy value: 88.47362906042613
      • type: manhattan_ap value: 84.91421462218432
      • type: manhattan_f1 value: 77.05107637204792
      • type: manhattan_precision value: 74.74484256243214
      • type: manhattan_recall value: 79.50415768401602
      • type: max_accuracy value: 88.47362906042613
      • type: max_ap value: 84.98384576824827
      • type: max_f1 value: 77.29311047696697 license: mit language:
  • en

aajonaa/bge-small-en-v1.5

作者 aajonaa

feature-extraction sentence-transformers
↓ 27 ♥ 0

创建时间: 2025-02-06 09:41:22+00:00

更新时间: 2025-02-06 09:54:32+00:00

在 Hugging Face 上查看

文件 (14)

.gitattributes
1_Pooling/config.json
README.md
config.json
config_sentence_transformers.json
model.safetensors
modules.json
onnx/model.onnx ONNX
pytorch_model.bin
sentence_bert_config.json
special_tokens_map.json
tokenizer.json
tokenizer_config.json
vocab.txt