transformers bert feature-extraction mteb model-index endpoints_compatible region:us
---
tags:
- mteb
model-index:
- name: multi-qa-MiniLM-L6-cos-v1
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 61.791044776119406
    - type: ap
      value: 25.829130082463124
    - type: f1
      value: 56.00432262887535
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 62.36077499999999
    - type: ap
      value: 57.68938427410222
    - type: f1
      value: 62.247666843818436
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 29.59
    - type: f1
      value: 29.241975951560622
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 25.249
    - type: map_at_10
      value: 40.196
    - type: map_at_100
      value: 41.336
    - type: map_at_1000
      value: 41.343
    - type: map_at_3
      value: 34.934
    - type: map_at_5
      value: 37.871
    - type: mrr_at_1
      value: 26.031
    - type: mrr_at_10
      value: 40.488
    - type: mrr_at_100
      value: 41.628
    - type: mrr_at_1000
      value: 41.634
    - type: mrr_at_3
      value: 35.171
    - type: mrr_at_5
      value: 38.126
    - type: ndcg_at_1
      value: 25.249
    - type: ndcg_at_10
      value: 49.11
    - type: ndcg_at_100
      value: 53.827999999999996
    - type: ndcg_at_1000
      value: 53.993
    - type: ndcg_at_3
      value: 38.175
    - type: ndcg_at_5
      value: 43.488
    - type: precision_at_1
      value: 25.249
    - type: precision_at_10
      value: 7.788
    - type: precision_at_100
      value: 0.9820000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.861
    - type: precision_at_5
      value: 12.105
    - type: recall_at_1
      value: 25.249
    - type: recall_at_10
      value: 77.881
    - type: recall_at_100
      value: 98.222
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 47.582
    - type: recall_at_5
      value: 60.526
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 37.75242616816114
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 27.70031808300247
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 63.09199068762668
    - type: mrr
      value: 76.08055225783757
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 80.83007234777145
    - type: cos_sim_spearman
      value: 79.76446808992547
    - type: euclidean_pearson
      value: 80.24418669808917
    - type: euclidean_spearman
      value: 79.76446808992547
    - type: manhattan_pearson
      value: 79.58896133042379
    - type: manhattan_spearman
      value: 78.9614377441415
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 78.6038961038961
    - type: f1
      value: 77.95572823168757
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.240388191413935
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 22.670413424756212
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.694
    - type: map_at_10
      value: 43.811
    - type: map_at_100
      value: 45.274
    - type: map_at_1000
      value: 45.393
    - type: map_at_3
      value: 40.043
    - type: map_at_5
      value: 41.983
    - type: mrr_at_1
      value: 39.628
    - type: mrr_at_10
      value: 49.748
    - type: mrr_at_100
      value: 50.356
    - type: mrr_at_1000
      value: 50.39900000000001
    - type: mrr_at_3
      value: 46.924
    - type: mrr_at_5
      value: 48.598
    - type: ndcg_at_1
      value: 39.628
    - type: ndcg_at_10
      value: 50.39
    - type: ndcg_at_100
      value: 55.489
    - type: ndcg_at_1000
      value: 57.291000000000004
    - type: ndcg_at_3
      value: 44.849
    - type: ndcg_at_5
      value: 47.195
    - type: precision_at_1
      value: 39.628
    - type: precision_at_10
      value: 9.714
    - type: precision_at_100
      value: 1.591
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 21.507
    - type: precision_at_5
      value: 15.393
    - type: recall_at_1
      value: 32.694
    - type: recall_at_10
      value: 63.031000000000006
    - type: recall_at_100
      value: 84.49
    - type: recall_at_1000
      value: 96.148
    - type: recall_at_3
      value: 46.851
    - type: recall_at_5
      value: 53.64
    - type: map_at_1
      value: 28.183000000000003
    - type: map_at_10
      value: 38.796
    - type: map_at_100
      value: 40.117000000000004
    - type: map_at_1000
      value: 40.251
    - type: map_at_3
      value: 35.713
    - type: map_at_5
      value: 37.446
    - type: mrr_at_1
      value: 35.605
    - type: mrr_at_10
      value: 44.824000000000005
    - type: mrr_at_100
      value: 45.544000000000004
    - type: mrr_at_1000
      value: 45.59
    - type: mrr_at_3
      value: 42.452
    - type: mrr_at_5
      value: 43.891999999999996
    - type: ndcg_at_1
      value: 35.605
    - type: ndcg_at_10
      value: 44.857
    - type: ndcg_at_100
      value: 49.68
    - type: ndcg_at_1000
      value: 51.841
    - type: ndcg_at_3
      value: 40.445
    - type: ndcg_at_5
      value: 42.535000000000004
    - type: precision_at_1
      value: 35.605
    - type: precision_at_10
      value: 8.624
    - type: precision_at_100
      value: 1.438
    - type: precision_at_1000
      value: 0.193
    - type: precision_at_3
      value: 19.808999999999997
    - type: precision_at_5
      value: 14.191
    - type: recall_at_1
      value: 28.183000000000003
    - type: recall_at_10
      value: 55.742000000000004
    - type: recall_at_100
      value: 76.416
    - type: recall_at_1000
      value: 90.20899999999999
    - type: recall_at_3
      value: 42.488
    - type: recall_at_5
      value: 48.431999999999995
    - type: map_at_1
      value: 36.156
    - type: map_at_10
      value: 47.677
    - type: map_at_100
      value: 48.699999999999996
    - type: map_at_1000
      value: 48.756
    - type: map_at_3
      value: 44.467
    - type: map_at_5
      value: 46.132
    - type: mrr_at_1
      value: 41.567
    - type: mrr_at_10
      value: 51.06699999999999
    - type: mrr_at_100
      value: 51.800000000000004
    - type: mrr_at_1000
      value: 51.827999999999996
    - type: mrr_at_3
      value: 48.620999999999995
    - type: mrr_at_5
      value: 50.013
    - type: ndcg_at_1
      value: 41.567
    - type: ndcg_at_10
      value: 53.418
    - type: ndcg_at_100
      value: 57.743
    - type: ndcg_at_1000
      value: 58.940000000000005
    - type: ndcg_at_3
      value: 47.923
    - type: ndcg_at_5
      value: 50.352
    - type: precision_at_1
      value: 41.567
    - type: precision_at_10
      value: 8.74
    - type: precision_at_100
      value: 1.1809999999999998
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 21.337999999999997
    - type: precision_at_5
      value: 14.646
    - type: recall_at_1
      value: 36.156
    - type: recall_at_10
      value: 67.084
    - type: recall_at_100
      value: 86.299
    - type: recall_at_1000
      value: 94.82000000000001
    - type: recall_at_3
      value: 52.209
    - type: recall_at_5
      value: 58.175
    - type: map_at_1
      value: 23.513
    - type: map_at_10
      value: 32.699
    - type: map_at_100
      value: 33.788000000000004
    - type: map_at_1000
      value: 33.878
    - type: map_at_3
      value: 30.044999999999998
    - type: map_at_5
      value: 31.506
    - type: mrr_at_1
      value: 25.311
    - type: mrr_at_10
      value: 34.457
    - type: mrr_at_100
      value: 35.443999999999996
    - type: mrr_at_1000
      value: 35.504999999999995
    - type: mrr_at_3
      value: 31.902
    - type: mrr_at_5
      value: 33.36
    - type: ndcg_at_1
      value: 25.311
    - type: ndcg_at_10
      value: 37.929
    - type: ndcg_at_100
      value: 43.1
    - type: ndcg_at_1000
      value: 45.275999999999996
    - type: ndcg_at_3
      value: 32.745999999999995
    - type: ndcg_at_5
      value: 35.235
    - type: precision_at_1
      value: 25.311
    - type: precision_at_10
      value: 6.034
    - type: precision_at_100
      value: 0.8959999999999999
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 14.237
    - type: precision_at_5
      value: 10.034
    - type: recall_at_1
      value: 23.513
    - type: recall_at_10
      value: 52.312999999999995
    - type: recall_at_100
      value: 75.762
    - type: recall_at_1000
      value: 91.85799999999999
    - type: recall_at_3
      value: 38.222
    - type: recall_at_5
      value: 44.316
    - type: map_at_1
      value: 16.333000000000002
    - type: map_at_10
      value: 24.605
    - type: map_at_100
      value: 25.924000000000003
    - type: map_at_1000
      value: 26.039
    - type: map_at_3
      value: 21.907
    - type: map_at_5
      value: 23.294999999999998
    - type: mrr_at_1
      value: 20.647
    - type: mrr_at_10
      value: 29.442
    - type: mrr_at_100
      value: 30.54
    - type: mrr_at_1000
      value: 30.601
    - type: mrr_at_3
      value: 26.802999999999997
    - type: mrr_at_5
      value: 28.147
    - type: ndcg_at_1
      value: 20.647
    - type: ndcg_at_10
      value: 30.171999999999997
    - type: ndcg_at_100
      value: 36.466
    - type: ndcg_at_1000
      value: 39.095
    - type: ndcg_at_3
      value: 25.134
    - type: ndcg_at_5
      value: 27.211999999999996
    - type: precision_at_1
      value: 20.647
    - type: precision_at_10
      value: 5.659
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 12.148
    - type: precision_at_5
      value: 8.881
    - type: recall_at_1
      value: 16.333000000000002
    - type: recall_at_10
      value: 42.785000000000004
    - type: recall_at_100
      value: 70.282
    - type: recall_at_1000
      value: 88.539
    - type: recall_at_3
      value: 28.307
    - type: recall_at_5
      value: 33.751
    - type: map_at_1
      value: 26.821
    - type: map_at_10
      value: 37.188
    - type: map_at_100
      value: 38.516
    - type: map_at_1000
      value: 38.635000000000005
    - type: map_at_3
      value: 33.821
    - type: map_at_5
      value: 35.646
    - type: mrr_at_1
      value: 33.109
    - type: mrr_at_10
      value: 43.003
    - type: mrr_at_100
      value: 43.849
    - type: mrr_at_1000
      value: 43.889
    - type: mrr_at_3
      value: 40.263
    - type: mrr_at_5
      value: 41.957
    - type: ndcg_at_1
      value: 33.109
    - type: ndcg_at_10
      value: 43.556
    - type: ndcg_at_100
      value: 49.197
    - type: ndcg_at_1000
      value: 51.269
    - type: ndcg_at_3
      value: 38.01
    - type: ndcg_at_5
      value: 40.647
    - type: precision_at_1
      value: 33.109
    - type: precision_at_10
      value: 8.085
    - type: precision_at_100
      value: 1.286
    - type: precision_at_1000
      value: 0.166
    - type: precision_at_3
      value: 18.191
    - type: precision_at_5
      value: 13.050999999999998
    - type: recall_at_1
      value: 26.821
    - type: recall_at_10
      value: 56.818000000000005
    - type: recall_at_100
      value: 80.63
    - type: recall_at_1000
      value: 94.042
    - type: recall_at_3
      value: 41.266000000000005
    - type: recall_at_5
      value: 48.087999999999994
    - type: map_at_1
      value: 22.169
    - type: map_at_10
      value: 31.682
    - type: map_at_100
      value: 32.988
    - type: map_at_1000
      value: 33.097
    - type: map_at_3
      value: 28.708
    - type: map_at_5
      value: 30.319000000000003
    - type: mrr_at_1
      value: 27.854
    - type: mrr_at_10
      value: 36.814
    - type: mrr_at_100
      value: 37.741
    - type: mrr_at_1000
      value: 37.798
    - type: mrr_at_3
      value: 34.418
    - type: mrr_at_5
      value: 35.742000000000004
    - type: ndcg_at_1
      value: 27.854
    - type: ndcg_at_10
      value: 37.388
    - type: ndcg_at_100
      value: 43.342999999999996
    - type: ndcg_at_1000
      value: 45.829
    - type: ndcg_at_3
      value: 32.512
    - type: ndcg_at_5
      value: 34.613
    - type: precision_at_1
      value: 27.854
    - type: precision_at_10
      value: 7.031999999999999
    - type: precision_at_100
      value: 1.18
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 15.753
    - type: precision_at_5
      value: 11.301
    - type: recall_at_1
      value: 22.169
    - type: recall_at_10
      value: 49.44
    - type: recall_at_100
      value: 75.644
    - type: recall_at_1000
      value: 92.919
    - type: recall_at_3
      value: 35.528999999999996
    - type: recall_at_5
      value: 41.271
    - type: map_at_1
      value: 24.20158333333334
    - type: map_at_10
      value: 33.509
    - type: map_at_100
      value: 34.76525
    - type: map_at_1000
      value: 34.885999999999996
    - type: map_at_3
      value: 30.594333333333335
    - type: map_at_5
      value: 32.160666666666664
    - type: mrr_at_1
      value: 28.803833333333333
    - type: mrr_at_10
      value: 37.61358333333333
    - type: mrr_at_100
      value: 38.5105
    - type: mrr_at_1000
      value: 38.56841666666667
    - type: mrr_at_3
      value: 35.090666666666664
    - type: mrr_at_5
      value: 36.49575
    - type: ndcg_at_1
      value: 28.803833333333333
    - type: ndcg_at_10
      value: 39.038333333333334
    - type: ndcg_at_100
      value: 44.49175
    - type: ndcg_at_1000
      value: 46.835499999999996
    - type: ndcg_at_3
      value: 34.011916666666664
    - type: ndcg_at_5
      value: 36.267
    - type: precision_at_1
      value: 28.803833333333333
    - type: precision_at_10
      value: 6.974583333333334
    - type: precision_at_100
      value: 1.1565
    - type: precision_at_1000
      value: 0.15533333333333332
    - type: precision_at_3
      value: 15.78025
    - type: precision_at_5
      value: 11.279583333333333
    - type: recall_at_1
      value: 24.20158333333334
    - type: recall_at_10
      value: 51.408
    - type: recall_at_100
      value: 75.36958333333334
    - type: recall_at_1000
      value: 91.5765
    - type: recall_at_3
      value: 37.334500000000006
    - type: recall_at_5
      value: 43.14666666666667
    - type: map_at_1
      value: 21.394
    - type: map_at_10
      value: 28.807
    - type: map_at_100
      value: 29.851
    - type: map_at_1000
      value: 29.959999999999997
    - type: map_at_3
      value: 26.694000000000003
    - type: map_at_5
      value: 27.805999999999997
    - type: mrr_at_1
      value: 23.773
    - type: mrr_at_10
      value: 30.895
    - type: mrr_at_100
      value: 31.894
    - type: mrr_at_1000
      value: 31.971
    - type: mrr_at_3
      value: 28.988000000000003
    - type: mrr_at_5
      value: 29.908
    - type: ndcg_at_1
      value: 23.773
    - type: ndcg_at_10
      value: 32.976
    - type: ndcg_at_100
      value: 38.109
    - type: ndcg_at_1000
      value: 40.797
    - type: ndcg_at_3
      value: 28.993999999999996
    - type: ndcg_at_5
      value: 30.659999999999997
    - type: precision_at_1
      value: 23.773
    - type: precision_at_10
      value: 5.2299999999999995
    - type: precision_at_100
      value: 0.857
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 12.73
    - type: precision_at_5
      value: 8.741999999999999
    - type: recall_at_1
      value: 21.394
    - type: recall_at_10
      value: 43.75
    - type: recall_at_100
      value: 66.765
    - type: recall_at_1000
      value: 86.483
    - type: recall_at_3
      value: 32.542
    - type: recall_at_5
      value: 36.689
    - type: map_at_1
      value: 16.266
    - type: map_at_10
      value: 23.639
    - type: map_at_100
      value: 24.814
    - type: map_at_1000
      value: 24.948
    - type: map_at_3
      value: 21.401999999999997
    - type: map_at_5
      value: 22.581
    - type: mrr_at_1
      value: 19.718
    - type: mrr_at_10
      value: 27.276
    - type: mrr_at_100
      value: 28.252
    - type: mrr_at_1000
      value: 28.33
    - type: mrr_at_3
      value: 25.086000000000002
    - type: mrr_at_5
      value: 26.304
    - type: ndcg_at_1
      value: 19.718
    - type: ndcg_at_10
      value: 28.254
    - type: ndcg_at_100
      value: 34.022999999999996
    - type: ndcg_at_1000
      value: 37.031
    - type: ndcg_at_3
      value: 24.206
    - type: ndcg_at_5
      value: 26.009
    - type: precision_at_1
      value: 19.718
    - type: precision_at_10
      value: 5.189
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.551
    - type: precision_at_5
      value: 8.362
    - type: recall_at_1
      value: 16.266
    - type: recall_at_10
      value: 38.550000000000004
    - type: recall_at_100
      value: 64.63499999999999
    - type: recall_at_1000
      value: 86.059
    - type: recall_at_3
      value: 27.156000000000002
    - type: recall_at_5
      value: 31.829
    - type: map_at_1
      value: 26.124000000000002
    - type: map_at_10
      value: 35.099000000000004
    - type: map_at_100
      value: 36.269
    - type: map_at_1000
      value: 36.388999999999996
    - type: map_at_3
      value: 32.017
    - type: map_at_5
      value: 33.614
    - type: mrr_at_1
      value: 31.25
    - type: mrr_at_10
      value: 39.269999999999996
    - type: mrr_at_100
      value: 40.134
    - type: mrr_at_1000
      value: 40.197
    - type: mrr_at_3
      value: 36.536
    - type: mrr_at_5
      value: 37.842
    - type: ndcg_at_1
      value: 31.25
    - type: ndcg_at_10
      value: 40.643
    - type: ndcg_at_100
      value: 45.967999999999996
    - type: ndcg_at_1000
      value: 48.455999999999996
    - type: ndcg_at_3
      value: 34.954
    - type: ndcg_at_5
      value: 37.273
    - type: precision_at_1
      value: 31.25
    - type: precision_at_10
      value: 6.894
    - type: precision_at_100
      value: 1.086
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 15.672
    - type: precision_at_5
      value: 11.082
    - type: recall_at_1
      value: 26.124000000000002
    - type: recall_at_10
      value: 53.730999999999995
    - type: recall_at_100
      value: 76.779
    - type: recall_at_1000
      value: 93.908
    - type: recall_at_3
      value: 37.869
    - type: recall_at_5
      value: 43.822
    - type: map_at_1
      value: 21.776
    - type: map_at_10
      value: 31.384
    - type: map_at_100
      value: 33.108
    - type: map_at_1000
      value: 33.339
    - type: map_at_3
      value: 28.269
    - type: map_at_5
      value: 30.108
    - type: mrr_at_1
      value: 26.482
    - type: mrr_at_10
      value: 35.876000000000005
    - type: mrr_at_100
      value: 36.887
    - type: mrr_at_1000
      value: 36.949
    - type: mrr_at_3
      value: 32.971000000000004
    - type: mrr_at_5
      value: 34.601
    - type: ndcg_at_1
      value: 26.482
    - type: ndcg_at_10
      value: 37.403999999999996
    - type: ndcg_at_100
      value: 43.722
    - type: ndcg_at_1000
      value: 46.417
    - type: ndcg_at_3
      value: 32.149
    - type: ndcg_at_5
      value: 34.818
    - type: precision_at_1
      value: 26.482
    - type: precision_at_10
      value: 7.411
    - type: precision_at_100
      value: 1.532
    - type: precision_at_1000
      value: 0.24
    - type: precision_at_3
      value: 15.152
    - type: precision_at_5
      value: 11.501999999999999
    - type: recall_at_1
      value: 21.776
    - type: recall_at_10
      value: 49.333
    - type: recall_at_100
      value: 76.753
    - type: recall_at_1000
      value: 93.762
    - type: recall_at_3
      value: 35.329
    - type: recall_at_5
      value: 41.82
    - type: map_at_1
      value: 18.990000000000002
    - type: map_at_10
      value: 26.721
    - type: map_at_100
      value: 27.833999999999996
    - type: map_at_1000
      value: 27.947
    - type: map_at_3
      value: 24.046
    - type: map_at_5
      value: 25.491999999999997
    - type: mrr_at_1
      value: 20.702
    - type: mrr_at_10
      value: 28.691
    - type: mrr_at_100
      value: 29.685
    - type: mrr_at_1000
      value: 29.764000000000003
    - type: mrr_at_3
      value: 26.124000000000002
    - type: mrr_at_5
      value: 27.584999999999997
    - type: ndcg_at_1
      value: 20.702
    - type: ndcg_at_10
      value: 31.473000000000003
    - type: ndcg_at_100
      value: 37.061
    - type: ndcg_at_1000
      value: 39.784000000000006
    - type: ndcg_at_3
      value: 26.221
    - type: ndcg_at_5
      value: 28.655
    - type: precision_at_1
      value: 20.702
    - type: precision_at_10
      value: 5.083
    - type: precision_at_100
      value: 0.8500000000000001
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 11.275
    - type: precision_at_5
      value: 8.17
    - type: recall_at_1
      value: 18.990000000000002
    - type: recall_at_10
      value: 44.318999999999996
    - type: recall_at_100
      value: 69.98
    - type: recall_at_1000
      value: 90.171
    - type: recall_at_3
      value: 30.246000000000002
    - type: recall_at_5
      value: 35.927
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.584
    - type: map_at_10
      value: 16.148
    - type: map_at_100
      value: 17.727
    - type: map_at_1000
      value: 17.913999999999998
    - type: map_at_3
      value: 13.456000000000001
    - type: map_at_5
      value: 14.841999999999999
    - type: mrr_at_1
      value: 21.564
    - type: mrr_at_10
      value: 31.579
    - type: mrr_at_100
      value: 32.586999999999996
    - type: mrr_at_1000
      value: 32.638
    - type: mrr_at_3
      value: 28.294999999999998
    - type: mrr_at_5
      value: 30.064
    - type: ndcg_at_1
      value: 21.564
    - type: ndcg_at_10
      value: 23.294999999999998
    - type: ndcg_at_100
      value: 29.997
    - type: ndcg_at_1000
      value: 33.517
    - type: ndcg_at_3
      value: 18.759
    - type: ndcg_at_5
      value: 20.324
    - type: precision_at_1
      value: 21.564
    - type: precision_at_10
      value: 7.362
    - type: precision_at_100
      value: 1.451
    - type: precision_at_1000
      value: 0.21
    - type: precision_at_3
      value: 13.919999999999998
    - type: precision_at_5
      value: 10.879
    - type: recall_at_1
      value: 9.584
    - type: recall_at_10
      value: 28.508
    - type: recall_at_100
      value: 51.873999999999995
    - type: recall_at_1000
      value: 71.773
    - type: recall_at_3
      value: 17.329
    - type: recall_at_5
      value: 21.823
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.034
    - type: map_at_10
      value: 14.664
    - type: map_at_100
      value: 19.652
    - type: map_at_1000
      value: 20.701
    - type: map_at_3
      value: 10.626
    - type: map_at_5
      value: 12.334
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 63.132
    - type: mrr_at_100
      value: 63.639
    - type: mrr_at_1000
      value: 63.663000000000004
    - type: mrr_at_3
      value: 61.083
    - type: mrr_at_5
      value: 62.483
    - type: ndcg_at_1
      value: 42.875
    - type: ndcg_at_10
      value: 32.04
    - type: ndcg_at_100
      value: 35.157
    - type: ndcg_at_1000
      value: 41.4
    - type: ndcg_at_3
      value: 35.652
    - type: ndcg_at_5
      value: 33.617000000000004
    - type: precision_at_1
      value: 54.0
    - type: precision_at_10
      value: 25.55
    - type: precision_at_100
      value: 7.5600000000000005
    - type: precision_at_1000
      value: 1.577
    - type: precision_at_3
      value: 38.833
    - type: precision_at_5
      value: 33.15
    - type: recall_at_1
      value: 7.034
    - type: recall_at_10
      value: 19.627
    - type: recall_at_100
      value: 40.528
    - type: recall_at_1000
      value: 60.789
    - type: recall_at_3
      value: 11.833
    - type: recall_at_5
      value: 14.804
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 39.6
    - type: f1
      value: 35.3770765501984
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 35.098
    - type: map_at_10
      value: 46.437
    - type: map_at_100
      value: 47.156
    - type: map_at_1000
      value: 47.193000000000005
    - type: map_at_3
      value: 43.702000000000005
    - type: map_at_5
      value: 45.326
    - type: mrr_at_1
      value: 37.774
    - type: mrr_at_10
      value: 49.512
    - type: mrr_at_100
      value: 50.196
    - type: mrr_at_1000
      value: 50.224000000000004
    - type: mrr_at_3
      value: 46.747
    - type: mrr_at_5
      value: 48.415
    - type: ndcg_at_1
      value: 37.774
    - type: ndcg_at_10
      value: 52.629000000000005
    - type: ndcg_at_100
      value: 55.995
    - type: ndcg_at_1000
      value: 56.962999999999994
    - type: ndcg_at_3
      value: 47.188
    - type: ndcg_at_5
      value: 50.019000000000005
    - type: precision_at_1
      value: 37.774
    - type: precision_at_10
      value: 7.541
    - type: precision_at_100
      value: 0.931
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 19.572
    - type: precision_at_5
      value: 13.288
    - type: recall_at_1
      value: 35.098
    - type: recall_at_10
      value: 68.818
    - type: recall_at_100
      value: 84.004
    - type: recall_at_1000
      value: 91.36800000000001
    - type: recall_at_3
      value: 54.176
    - type: recall_at_5
      value: 60.968999999999994
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.982
    - type: map_at_10
      value: 28.994999999999997
    - type: map_at_100
      value: 30.868000000000002
    - type: map_at_1000
      value: 31.045
    - type: map_at_3
      value: 25.081999999999997
    - type: map_at_5
      value: 27.303
    - type: mrr_at_1
      value: 35.031
    - type: mrr_at_10
      value: 43.537
    - type: mrr_at_100
      value: 44.422
    - type: mrr_at_1000
      value: 44.471
    - type: mrr_at_3
      value: 41.024
    - type: mrr_at_5
      value: 42.42
    - type: ndcg_at_1
      value: 35.031
    - type: ndcg_at_10
      value: 36.346000000000004
    - type: ndcg_at_100
      value: 43.275000000000006
    - type: ndcg_at_1000
      value: 46.577
    - type: ndcg_at_3
      value: 32.42
    - type: ndcg_at_5
      value: 33.841
    - type: precision_at_1
      value: 35.031
    - type: precision_at_10
      value: 10.231
    - type: precision_at_100
      value: 1.728
    - type: precision_at_1000
      value: 0.231
    - type: precision_at_3
      value: 21.553
    - type: precision_at_5
      value: 16.204
    - type: recall_at_1
      value: 17.982
    - type: recall_at_10
      value: 43.169000000000004
    - type: recall_at_100
      value: 68.812
    - type: recall_at_1000
      value: 89.008
    - type: recall_at_3
      value: 29.309
    - type: recall_at_5
      value: 35.514
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 27.387
    - type: map_at_10
      value: 36.931000000000004
    - type: map_at_100
      value: 37.734
    - type: map_at_1000
      value: 37.818000000000005
    - type: map_at_3
      value: 34.691
    - type: map_at_5
      value: 36.016999999999996
    - type: mrr_at_1
      value: 54.774
    - type: mrr_at_10
      value: 62.133
    - type: mrr_at_100
      value: 62.587
    - type: mrr_at_1000
      value: 62.61600000000001
    - type: mrr_at_3
      value: 60.49099999999999
    - type: mrr_at_5
      value: 61.480999999999995
    - type: ndcg_at_1
      value: 54.774
    - type: ndcg_at_10
      value: 45.657
    - type: ndcg_at_100
      value: 48.954
    - type: ndcg_at_1000
      value: 50.78
    - type: ndcg_at_3
      value: 41.808
    - type: ndcg_at_5
      value: 43.816
    - type: precision_at_1
      value: 54.774
    - type: precision_at_10
      value: 9.479
    - type: precision_at_100
      value: 1.208
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 25.856
    - type: precision_at_5
      value: 17.102
    - type: recall_at_1
      value: 27.387
    - type: recall_at_10
      value: 47.394
    - type: recall_at_100
      value: 60.397999999999996
    - type: recall_at_1000
      value: 72.54599999999999
    - type: recall_at_3
      value: 38.785
    - type: recall_at_5
      value: 42.754999999999995
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 61.217999999999996
    - type: ap
      value: 56.84286974948407
    - type: f1
      value: 60.99211195455131
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 19.224
    - type: map_at_10
      value: 30.448999999999998
    - type: map_at_100
      value: 31.663999999999998
    - type: map_at_1000
      value: 31.721
    - type: map_at_3
      value: 26.922
    - type: map_at_5
      value: 28.906
    - type: mrr_at_1
      value: 19.756
    - type: mrr_at_10
      value: 30.994
    - type: mrr_at_100
      value: 32.161
    - type: mrr_at_1000
      value: 32.213
    - type: mrr_at_3
      value: 27.502
    - type: mrr_at_5
      value: 29.48
    - type: ndcg_at_1
      value: 19.742
    - type: ndcg_at_10
      value: 36.833
    - type: ndcg_at_100
      value: 42.785000000000004
    - type: ndcg_at_1000
      value: 44.291000000000004
    - type: ndcg_at_3
      value: 29.580000000000002
    - type: ndcg_at_5
      value: 33.139
    - type: precision_at_1
      value: 19.742
    - type: precision_at_10
      value: 5.894
    - type: precision_at_100
      value: 0.889
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 12.665000000000001
    - type: precision_at_5
      value: 9.393
    - type: recall_at_1
      value: 19.224
    - type: recall_at_10
      value: 56.538999999999994
    - type: recall_at_100
      value: 84.237
    - type: recall_at_1000
      value: 95.965
    - type: recall_at_3
      value: 36.71
    - type: recall_at_5
      value: 45.283
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.97264021887824
    - type: f1
      value: 89.53607318488027
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.566803465572285
    - type: f1
      value: 40.94003955225124
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 66.7787491593813
    - type: f1
      value: 64.51190971513093
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.7794216543376
    - type: f1
      value: 72.71852261076475
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.40883054472429
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.144338339113617
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.894071459751267
    - type: mrr
      value: 31.965886150526256
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.024
    - type: map_at_10
      value: 10.533
    - type: map_at_100
      value: 12.97
    - type: map_at_1000
      value: 14.163
    - type: map_at_3
      value: 7.971
    - type: map_at_5
      value: 9.15
    - type: mrr_at_1
      value: 40.867
    - type: mrr_at_10
      value: 48.837
    - type: mrr_at_100
      value: 49.464999999999996
    - type: mrr_at_1000
      value: 49.509
    - type: mrr_at_3
      value: 46.800999999999995
    - type: mrr_at_5
      value: 47.745
    - type: ndcg_at_1
      value: 38.854
    - type: ndcg_at_10
      value: 29.674
    - type: ndcg_at_100
      value: 26.66
    - type: ndcg_at_1000
      value: 35.088
    - type: ndcg_at_3
      value: 34.838
    - type: ndcg_at_5
      value: 32.423
    - type: precision_at_1
      value: 40.248
    - type: precision_at_10
      value: 21.826999999999998
    - type: precision_at_100
      value: 6.78
    - type: precision_at_1000
      value: 1.889
    - type: precision_at_3
      value: 32.405
    - type: precision_at_5
      value: 27.74
    - type: recall_at_1
      value: 5.024
    - type: recall_at_10
      value: 13.996
    - type: recall_at_100
      value: 26.636
    - type: recall_at_1000
      value: 57.816
    - type: recall_at_3
      value: 9.063
    - type: recall_at_5
      value: 10.883
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 23.088
    - type: map_at_10
      value: 36.915
    - type: map_at_100
      value: 38.141999999999996
    - type: map_at_1000
      value: 38.191
    - type: map_at_3
      value: 32.458999999999996
    - type: map_at_5
      value: 35.004999999999995
    - type: mrr_at_1
      value: 26.101000000000003
    - type: mrr_at_10
      value: 39.1
    - type: mrr_at_100
      value: 40.071
    - type: mrr_at_1000
      value: 40.106
    - type: mrr_at_3
      value: 35.236000000000004
    - type: mrr_at_5
      value: 37.43
    - type: ndcg_at_1
      value: 26.072
    - type: ndcg_at_10
      value: 44.482
    - type: ndcg_at_100
      value: 49.771
    - type: ndcg_at_1000
      value: 50.903
    - type: ndcg_at_3
      value: 35.922
    - type: ndcg_at_5
      value: 40.178000000000004
    - type: precision_at_1
      value: 26.072
    - type: precision_at_10
      value: 7.795000000000001
    - type: precision_at_100
      value: 1.072
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 16.725
    - type: precision_at_5
      value: 12.468
    - type: recall_at_1
      value: 23.088
    - type: recall_at_10
      value: 65.534
    - type: recall_at_100
      value: 88.68
    - type: recall_at_1000
      value: 97.101
    - type: recall_at_3
      value: 43.161
    - type: recall_at_5
      value: 52.959999999999994
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.612
    - type: map_at_10
      value: 83.292
    - type: map_at_100
      value: 83.96000000000001
    - type: map_at_1000
      value: 83.978
    - type: map_at_3
      value: 80.26299999999999
    - type: map_at_5
      value: 82.11500000000001
    - type: mrr_at_1
      value: 80.21000000000001
    - type: mrr_at_10
      value: 86.457
    - type: mrr_at_100
      value: 86.58500000000001
    - type: mrr_at_1000
      value: 86.587
    - type: mrr_at_3
      value: 85.452
    - type: mrr_at_5
      value: 86.101
    - type: ndcg_at_1
      value: 80.21000000000001
    - type: ndcg_at_10
      value: 87.208
    - type: ndcg_at_100
      value: 88.549
    - type: ndcg_at_1000
      value: 88.683
    - type: ndcg_at_3
      value: 84.20400000000001
    - type: ndcg_at_5
      value: 85.768
    - type: precision_at_1
      value: 80.21000000000001
    - type: precision_at_10
      value: 13.29
    - type: precision_at_100
      value: 1.5230000000000001
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 36.767
    - type: precision_at_5
      value: 24.2
    - type: recall_at_1
      value: 69.612
    - type: recall_at_10
      value: 94.651
    - type: recall_at_100
      value: 99.297
    - type: recall_at_1000
      value: 99.95100000000001
    - type: recall_at_3
      value: 86.003
    - type: recall_at_5
      value: 90.45100000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 46.28945925252077
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 50.954446620859684
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.888
    - type: map_at_10
      value: 9.21
    - type: map_at_100
      value: 10.629
    - type: map_at_1000
      value: 10.859
    - type: map_at_3
      value: 6.743
    - type: map_at_5
      value: 7.982
    - type: mrr_at_1
      value: 19.1
    - type: mrr_at_10
      value: 28.294000000000004
    - type: mrr_at_100
      value: 29.326999999999998
    - type: mrr_at_1000
      value: 29.414
    - type: mrr_at_3
      value: 25.367
    - type: mrr_at_5
      value: 27.002
    - type: ndcg_at_1
      value: 19.1
    - type: ndcg_at_10
      value: 15.78
    - type: ndcg_at_100
      value: 21.807000000000002
    - type: ndcg_at_1000
      value: 26.593
    - type: ndcg_at_3
      value: 15.204999999999998
    - type: ndcg_at_5
      value: 13.217
    - type: precision_at_1
      value: 19.1
    - type: precision_at_10
      value: 7.9799999999999995
    - type: precision_at_100
      value: 1.667
    - type: precision_at_1000
      value: 0.28300000000000003
    - type: precision_at_3
      value: 13.933000000000002
    - type: precision_at_5
      value: 11.379999999999999
    - type: recall_at_1
      value: 3.888
    - type: recall_at_10
      value: 16.17
    - type: recall_at_100
      value: 33.848
    - type: recall_at_1000
      value: 57.345
    - type: recall_at_3
      value: 8.468
    - type: recall_at_5
      value: 11.540000000000001
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 79.05803116288386
    - type: cos_sim_spearman
      value: 70.0403855402571
    - type: euclidean_pearson
      value: 75.59006280166072
    - type: euclidean_spearman
      value: 70.04038926247613
    - type: manhattan_pearson
      value: 75.48136278078455
    - type: manhattan_spearman
      value: 69.9608897701754
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 68.56836430603597
    - type: cos_sim_spearman
      value: 64.38407759822387
    - type: euclidean_pearson
      value: 65.93619045541732
    - type: euclidean_spearman
      value: 64.38184049884836
    - type: manhattan_pearson
      value: 65.97148637646873
    - type: manhattan_spearman
      value: 64.48011982438929
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.990362280318
    - type: cos_sim_spearman
      value: 76.40621890996734
    - type: euclidean_pearson
      value: 76.01739766577184
    - type: euclidean_spearman
      value: 76.4062736496846
    - type: manhattan_pearson
      value: 76.04738378838042
    - type: manhattan_spearman
      value: 76.44991409719592
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 74.8516957692617
    - type: cos_sim_spearman
      value: 69.325199098278
    - type: euclidean_pearson
      value: 73.37922793254768
    - type: euclidean_spearman
      value: 69.32520119670215
    - type: manhattan_pearson
      value: 73.3795212376615
    - type: manhattan_spearman
      value: 69.35306787926315
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 78.644002190612
    - type: cos_sim_spearman
      value: 80.18337978181648
    - type: euclidean_pearson
      value: 79.7628642371887
    - type: euclidean_spearman
      value: 80.18337906907526
    - type: manhattan_pearson
      value: 79.68810722704522
    - type: manhattan_spearman
      value: 80.10664518173466
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.8303940874723
    - type: cos_sim_spearman
      value: 79.56812599677549
    - type: euclidean_pearson
      value: 79.38928950396344
    - type: euclidean_spearman
      value: 79.56812556750812
    - type: manhattan_pearson
      value: 79.41057583507681
    - type: manhattan_spearman
      value: 79.57604428731142
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.90792116013353
    - type: cos_sim_spearman
      value: 81.18059230233499
    - type: euclidean_pearson
      value: 80.2622631297375
    - type: euclidean_spearman
      value: 81.18059230233499
    - type: manhattan_pearson
      value: 80.23946026135997
    - type: manhattan_spearman
      value: 81.11947325071426
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 64.46850619973324
    - type: cos_sim_spearman
      value: 65.50839374141563
    - type: euclidean_pearson
      value: 66.60130812260707
    - type: euclidean_spearman
      value: 65.50839374141563
    - type: manhattan_pearson
      value: 66.58871918195092
    - type: manhattan_spearman
      value: 65.7347325297592
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 75.71536124107834
    - type: cos_sim_spearman
      value: 75.98365906208434
    - type: euclidean_pearson
      value: 76.64573753881218
    - type: euclidean_spearman
      value: 75.98365906208434
    - type: manhattan_pearson
      value: 76.63637189172626
    - type: manhattan_spearman
      value: 75.9660207821009
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.27669440147513
    - type: mrr
      value: 91.7729356699945
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 41.028
    - type: map_at_10
      value: 49.919000000000004
    - type: map_at_100
      value: 50.91
    - type: map_at_1000
      value: 50.955
    - type: map_at_3
      value: 47.785
    - type: map_at_5
      value: 49.084
    - type: mrr_at_1
      value: 43.667
    - type: mrr_at_10
      value: 51.342
    - type: mrr_at_100
      value: 52.197
    - type: mrr_at_1000
      value: 52.236000000000004
    - type: mrr_at_3
      value: 49.667
    - type: mrr_at_5
      value: 50.766999999999996
    - type: ndcg_at_1
      value: 43.667
    - type: ndcg_at_10
      value: 54.029
    - type: ndcg_at_100
      value: 58.909
    - type: ndcg_at_1000
      value: 60.131
    - type: ndcg_at_3
      value: 50.444
    - type: ndcg_at_5
      value: 52.354
    - type: precision_at_1
      value: 43.667
    - type: precision_at_10
      value: 7.432999999999999
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 20.444000000000003
    - type: precision_at_5
      value: 13.533000000000001
    - type: recall_at_1
      value: 41.028
    - type: recall_at_10
      value: 65.011
    - type: recall_at_100
      value: 88.033
    - type: recall_at_1000
      value: 97.667
    - type: recall_at_3
      value: 55.394
    - type: recall_at_5
      value: 60.183
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.76534653465346
    - type: cos_sim_ap
      value: 93.83756773536699
    - type: cos_sim_f1
      value: 87.91097622660598
    - type: cos_sim_precision
      value: 88.94575230296827
    - type: cos_sim_recall
      value: 86.9
    - type: dot_accuracy
      value: 99.76534653465346
    - type: dot_ap
      value: 93.83756773536699
    - type: dot_f1
      value: 87.91097622660598
    - type: dot_precision
      value: 88.94575230296827
    - type: dot_recall
      value: 86.9
    - type: euclidean_accuracy
      value: 99.76534653465346
    - type: euclidean_ap
      value: 93.837567735367
    - type: euclidean_f1
      value: 87.91097622660598
    - type: euclidean_precision
      value: 88.94575230296827
    - type: euclidean_recall
      value: 86.9
    - type: manhattan_accuracy
      value: 99.76633663366337
    - type: manhattan_ap
      value: 93.84480825492724
    - type: manhattan_f1
      value: 87.97145769622833
    - type: manhattan_precision
      value: 89.70893970893971
    - type: manhattan_recall
      value: 86.3
    - type: max_accuracy
      value: 99.76633663366337
    - type: max_ap
      value: 93.84480825492724
    - type: max_f1
      value: 87.97145769622833
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 48.078155553339585
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 33.34857297824906
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 50.06219491505384
    - type: mrr
      value: 50.77479097699686
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.48401937651373
    - type: cos_sim_spearman
      value: 31.048654273022606
    - type: dot_pearson
      value: 30.484020082707847
    - type: dot_spearman
      value: 31.048654273022606
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.183
    - type: map_at_10
      value: 1.32
    - type: map_at_100
      value: 7.01
    - type: map_at_1000
      value: 16.957
    - type: map_at_3
      value: 0.481
    - type: map_at_5
      value: 0.737
    - type: mrr_at_1
      value: 66.0
    - type: mrr_at_10
      value: 78.7
    - type: mrr_at_100
      value: 78.7
    - type: mrr_at_1000
      value: 78.7
    - type: mrr_at_3
      value: 76.0
    - type: mrr_at_5
      value: 78.7
    - type: ndcg_at_1
      value: 56.99999999999999
    - type: ndcg_at_10
      value: 55.846
    - type: ndcg_at_100
      value: 43.138
    - type: ndcg_at_1000
      value: 39.4
    - type: ndcg_at_3
      value: 57.306999999999995
    - type: ndcg_at_5
      value: 57.294
    - type: precision_at_1
      value: 66.0
    - type: precision_at_10
      value: 60.0
    - type: precision_at_100
      value: 44.6
    - type: precision_at_1000
      value: 17.8
    - type: precision_at_3
      value: 62.0
    - type: precision_at_5
      value: 62.0
    - type: recall_at_1
      value: 0.183
    - type: recall_at_10
      value: 1.583
    - type: recall_at_100
      value: 10.412
    - type: recall_at_1000
      value: 37.358999999999995
    - type: recall_at_3
      value: 0.516
    - type: recall_at_5
      value: 0.845
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.7420000000000002
    - type: map_at_10
      value: 6.4879999999999995
    - type: map_at_100
      value: 11.654
    - type: map_at_1000
      value: 13.23
    - type: map_at_3
      value: 3.148
    - type: map_at_5
      value: 4.825
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 30.258000000000003
    - type: mrr_at_100
      value: 31.570999999999998
    - type: mrr_at_1000
      value: 31.594
    - type: mrr_at_3
      value: 26.19
    - type: mrr_at_5
      value: 28.027
    - type: ndcg_at_1
      value: 15.306000000000001
    - type: ndcg_at_10
      value: 15.608
    - type: ndcg_at_100
      value: 28.808
    - type: ndcg_at_1000
      value: 41.603
    - type: ndcg_at_3
      value: 13.357
    - type: ndcg_at_5
      value: 15.306000000000001
    - type: precision_at_1
      value: 18.367
    - type: precision_at_10
      value: 15.101999999999999
    - type: precision_at_100
      value: 6.49
    - type: precision_at_1000
      value: 1.488
    - type: precision_at_3
      value: 14.966
    - type: precision_at_5
      value: 17.143
    - type: recall_at_1
      value: 1.7420000000000002
    - type: recall_at_10
      value: 12.267
    - type: recall_at_100
      value: 41.105999999999995
    - type: recall_at_1000
      value: 80.569
    - type: recall_at_3
      value: 4.009
    - type: recall_at_5
      value: 7.417999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 65.1178
    - type: ap
      value: 11.974961582206614
    - type: f1
      value: 50.24491996814835
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 51.63271080928127
    - type: f1
      value: 51.81589904316042
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 40.791709673552276
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.05418131966383
    - type: cos_sim_ap
      value: 64.72353098186304
    - type: cos_sim_f1
      value: 61.313330054107226
    - type: cos_sim_precision
      value: 57.415937356057114
    - type: cos_sim_recall
      value: 65.77836411609499
    - type: dot_accuracy
      value: 83.05418131966383
    - type: dot_ap
      value: 64.72352701424393
    - type: dot_f1
      value: 61.313330054107226
    - type: dot_precision
      value: 57.415937356057114
    - type: dot_recall
      value: 65.77836411609499
    - type: euclidean_accuracy
      value: 83.05418131966383
    - type: euclidean_ap
      value: 64.72353124585976
    - type: euclidean_f1
      value: 61.313330054107226
    - type: euclidean_precision
      value: 57.415937356057114
    - type: euclidean_recall
      value: 65.77836411609499
    - type: manhattan_accuracy
      value: 82.98861536627525
    - type: manhattan_ap
      value: 64.53981837182303
    - type: manhattan_f1
      value: 60.94911377930246
    - type: manhattan_precision
      value: 53.784056508577194
    - type: manhattan_recall
      value: 70.31662269129288
    - type: max_accuracy
      value: 83.05418131966383
    - type: max_ap
      value: 64.72353124585976
    - type: max_f1
      value: 61.313330054107226
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.06225016493966
    - type: cos_sim_ap
      value: 84.00829172423475
    - type: cos_sim_f1
      value: 76.1288446157202
    - type: cos_sim_precision
      value: 72.11737153877945
    - type: cos_sim_recall
      value: 80.61287342161995
    - type: dot_accuracy
      value: 88.06225016493966
    - type: dot_ap
      value: 84.00827913374181
    - type: dot_f1
      value: 76.1288446157202
    - type: dot_precision
      value: 72.11737153877945
    - type: dot_recall
      value: 80.61287342161995
    - type: euclidean_accuracy
      value: 88.06225016493966
    - type: euclidean_ap
      value: 84.00827099295034
    - type: euclidean_f1
      value: 76.1288446157202
    - type: euclidean_precision
      value: 72.11737153877945
    - type: euclidean_recall
      value: 80.61287342161995
    - type: manhattan_accuracy
      value: 88.05642876547523
    - type: manhattan_ap
      value: 83.9157542691417
    - type: manhattan_f1
      value: 76.09045667447307
    - type: manhattan_precision
      value: 72.50348675034869
    - type: manhattan_recall
      value: 80.05081613797351
    - type: max_accuracy
      value: 88.06225016493966
    - type: max_ap
      value: 84.00829172423475
    - type: max_f1
      value: 76.1288446157202
---

MTEB evaluation results on English language for 'multi-qa-MiniLM-L6-cos-v1' sbert model

Model and licence can be found [here](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1)
