transformers pytorch onnx bert feature-extraction mteb model-index text-embeddings-inference endpoints_compatible region:us
---
tags:
- mteb
model-index:
- name: andersonbcdefg/bge-small-4096
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 68.74626865671641
    - type: ap
      value: 31.113961861085855
    - type: f1
      value: 62.628656720790275
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 81.30347499999999
    - type: ap
      value: 76.05639977935193
    - type: f1
      value: 81.23180016825499
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 38.566
    - type: f1
      value: 38.014543974125615
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 29.445
    - type: map_at_10
      value: 44.157999999999994
    - type: map_at_100
      value: 45.169
    - type: map_at_1000
      value: 45.178000000000004
    - type: map_at_3
      value: 39.545
    - type: map_at_5
      value: 42.233
    - type: mrr_at_1
      value: 29.445
    - type: mrr_at_10
      value: 44.157999999999994
    - type: mrr_at_100
      value: 45.169
    - type: mrr_at_1000
      value: 45.178000000000004
    - type: mrr_at_3
      value: 39.545
    - type: mrr_at_5
      value: 42.233
    - type: ndcg_at_1
      value: 29.445
    - type: ndcg_at_10
      value: 52.446000000000005
    - type: ndcg_at_100
      value: 56.782
    - type: ndcg_at_1000
      value: 56.989999999999995
    - type: ndcg_at_3
      value: 42.935
    - type: ndcg_at_5
      value: 47.833999999999996
    - type: precision_at_1
      value: 29.445
    - type: precision_at_10
      value: 7.8950000000000005
    - type: precision_at_100
      value: 0.979
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 17.591
    - type: precision_at_5
      value: 12.959000000000001
    - type: recall_at_1
      value: 29.445
    - type: recall_at_10
      value: 78.947
    - type: recall_at_100
      value: 97.937
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 52.774
    - type: recall_at_5
      value: 64.794
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 43.85187820924144
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.5939502757938
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 58.539409343284674
    - type: mrr
      value: 71.58982983775228
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.31440765254087
    - type: cos_sim_spearman
      value: 81.59884723689632
    - type: euclidean_pearson
      value: 80.65818473893147
    - type: euclidean_spearman
      value: 81.40004752638717
    - type: manhattan_pearson
      value: 80.52256901536644
    - type: manhattan_spearman
      value: 80.57292024599603
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 79.98376623376623
    - type: f1
      value: 79.91981901371503
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.79541356345093
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 26.760513681350375
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 23.794
    - type: map_at_10
      value: 33.361000000000004
    - type: map_at_100
      value: 34.86
    - type: map_at_1000
      value: 35.0
    - type: map_at_3
      value: 30.579
    - type: map_at_5
      value: 31.996000000000002
    - type: mrr_at_1
      value: 30.186
    - type: mrr_at_10
      value: 39.681
    - type: mrr_at_100
      value: 40.616
    - type: mrr_at_1000
      value: 40.669
    - type: mrr_at_3
      value: 37.244
    - type: mrr_at_5
      value: 38.588
    - type: ndcg_at_1
      value: 30.186
    - type: ndcg_at_10
      value: 39.34
    - type: ndcg_at_100
      value: 45.266
    - type: ndcg_at_1000
      value: 47.9
    - type: ndcg_at_3
      value: 35.164
    - type: ndcg_at_5
      value: 36.854
    - type: precision_at_1
      value: 30.186
    - type: precision_at_10
      value: 7.639
    - type: precision_at_100
      value: 1.328
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 17.31
    - type: precision_at_5
      value: 12.275
    - type: recall_at_1
      value: 23.794
    - type: recall_at_10
      value: 50.463
    - type: recall_at_100
      value: 75.268
    - type: recall_at_1000
      value: 93.138
    - type: recall_at_3
      value: 37.797
    - type: recall_at_5
      value: 42.985
    - type: map_at_1
      value: 17.968999999999998
    - type: map_at_10
      value: 23.846999999999998
    - type: map_at_100
      value: 24.712999999999997
    - type: map_at_1000
      value: 24.833
    - type: map_at_3
      value: 22.024
    - type: map_at_5
      value: 23.087
    - type: mrr_at_1
      value: 22.038
    - type: mrr_at_10
      value: 27.808
    - type: mrr_at_100
      value: 28.532999999999998
    - type: mrr_at_1000
      value: 28.604000000000003
    - type: mrr_at_3
      value: 26.029999999999998
    - type: mrr_at_5
      value: 27.122
    - type: ndcg_at_1
      value: 22.038
    - type: ndcg_at_10
      value: 27.559
    - type: ndcg_at_100
      value: 31.541999999999998
    - type: ndcg_at_1000
      value: 34.343
    - type: ndcg_at_3
      value: 24.585
    - type: ndcg_at_5
      value: 26.026
    - type: precision_at_1
      value: 22.038
    - type: precision_at_10
      value: 5.019
    - type: precision_at_100
      value: 0.8920000000000001
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.423
    - type: precision_at_5
      value: 8.28
    - type: recall_at_1
      value: 17.968999999999998
    - type: recall_at_10
      value: 34.583000000000006
    - type: recall_at_100
      value: 51.849000000000004
    - type: recall_at_1000
      value: 70.832
    - type: recall_at_3
      value: 26.057000000000002
    - type: recall_at_5
      value: 29.816
    - type: map_at_1
      value: 29.183999999999997
    - type: map_at_10
      value: 40.245
    - type: map_at_100
      value: 41.324
    - type: map_at_1000
      value: 41.402
    - type: map_at_3
      value: 37.395
    - type: map_at_5
      value: 38.964999999999996
    - type: mrr_at_1
      value: 33.981
    - type: mrr_at_10
      value: 43.471
    - type: mrr_at_100
      value: 44.303
    - type: mrr_at_1000
      value: 44.352999999999994
    - type: mrr_at_3
      value: 41.149
    - type: mrr_at_5
      value: 42.466
    - type: ndcg_at_1
      value: 33.981
    - type: ndcg_at_10
      value: 45.776
    - type: ndcg_at_100
      value: 50.441
    - type: ndcg_at_1000
      value: 52.16
    - type: ndcg_at_3
      value: 40.756
    - type: ndcg_at_5
      value: 43.132
    - type: precision_at_1
      value: 33.981
    - type: precision_at_10
      value: 7.617999999999999
    - type: precision_at_100
      value: 1.083
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 18.558
    - type: precision_at_5
      value: 12.915
    - type: recall_at_1
      value: 29.183999999999997
    - type: recall_at_10
      value: 59.114
    - type: recall_at_100
      value: 79.549
    - type: recall_at_1000
      value: 91.925
    - type: recall_at_3
      value: 45.551
    - type: recall_at_5
      value: 51.38399999999999
    - type: map_at_1
      value: 20.286
    - type: map_at_10
      value: 27.143
    - type: map_at_100
      value: 28.107
    - type: map_at_1000
      value: 28.212
    - type: map_at_3
      value: 25.149
    - type: map_at_5
      value: 26.179999999999996
    - type: mrr_at_1
      value: 22.034000000000002
    - type: mrr_at_10
      value: 28.875
    - type: mrr_at_100
      value: 29.785
    - type: mrr_at_1000
      value: 29.876
    - type: mrr_at_3
      value: 27.023999999999997
    - type: mrr_at_5
      value: 28.058
    - type: ndcg_at_1
      value: 22.034000000000002
    - type: ndcg_at_10
      value: 31.148999999999997
    - type: ndcg_at_100
      value: 35.936
    - type: ndcg_at_1000
      value: 38.682
    - type: ndcg_at_3
      value: 27.230999999999998
    - type: ndcg_at_5
      value: 29.034
    - type: precision_at_1
      value: 22.034000000000002
    - type: precision_at_10
      value: 4.836
    - type: precision_at_100
      value: 0.754
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 11.562999999999999
    - type: precision_at_5
      value: 8.068
    - type: recall_at_1
      value: 20.286
    - type: recall_at_10
      value: 41.827999999999996
    - type: recall_at_100
      value: 63.922000000000004
    - type: recall_at_1000
      value: 84.639
    - type: recall_at_3
      value: 31.227
    - type: recall_at_5
      value: 35.546
    - type: map_at_1
      value: 13.488
    - type: map_at_10
      value: 18.595
    - type: map_at_100
      value: 19.783
    - type: map_at_1000
      value: 19.918
    - type: map_at_3
      value: 16.274
    - type: map_at_5
      value: 17.558
    - type: mrr_at_1
      value: 16.791
    - type: mrr_at_10
      value: 22.53
    - type: mrr_at_100
      value: 23.651
    - type: mrr_at_1000
      value: 23.738999999999997
    - type: mrr_at_3
      value: 20.232
    - type: mrr_at_5
      value: 21.644
    - type: ndcg_at_1
      value: 16.791
    - type: ndcg_at_10
      value: 22.672
    - type: ndcg_at_100
      value: 28.663
    - type: ndcg_at_1000
      value: 31.954
    - type: ndcg_at_3
      value: 18.372
    - type: ndcg_at_5
      value: 20.47
    - type: precision_at_1
      value: 16.791
    - type: precision_at_10
      value: 4.2540000000000004
    - type: precision_at_100
      value: 0.8370000000000001
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 8.706
    - type: precision_at_5
      value: 6.666999999999999
    - type: recall_at_1
      value: 13.488
    - type: recall_at_10
      value: 31.451
    - type: recall_at_100
      value: 58.085
    - type: recall_at_1000
      value: 81.792
    - type: recall_at_3
      value: 19.811
    - type: recall_at_5
      value: 24.973
    - type: map_at_1
      value: 21.436
    - type: map_at_10
      value: 29.105999999999998
    - type: map_at_100
      value: 30.442000000000004
    - type: map_at_1000
      value: 30.567
    - type: map_at_3
      value: 26.430999999999997
    - type: map_at_5
      value: 27.866000000000003
    - type: mrr_at_1
      value: 26.083000000000002
    - type: mrr_at_10
      value: 33.975
    - type: mrr_at_100
      value: 35.014
    - type: mrr_at_1000
      value: 35.07
    - type: mrr_at_3
      value: 31.649
    - type: mrr_at_5
      value: 32.944
    - type: ndcg_at_1
      value: 26.083000000000002
    - type: ndcg_at_10
      value: 34.229
    - type: ndcg_at_100
      value: 40.439
    - type: ndcg_at_1000
      value: 43.081
    - type: ndcg_at_3
      value: 29.64
    - type: ndcg_at_5
      value: 31.704
    - type: precision_at_1
      value: 26.083000000000002
    - type: precision_at_10
      value: 6.246
    - type: precision_at_100
      value: 1.1199999999999999
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 13.858999999999998
    - type: precision_at_5
      value: 10.01
    - type: recall_at_1
      value: 21.436
    - type: recall_at_10
      value: 44.938
    - type: recall_at_100
      value: 72.029
    - type: recall_at_1000
      value: 90.009
    - type: recall_at_3
      value: 31.954
    - type: recall_at_5
      value: 37.303
    - type: map_at_1
      value: 18.217
    - type: map_at_10
      value: 25.16
    - type: map_at_100
      value: 26.490000000000002
    - type: map_at_1000
      value: 26.619
    - type: map_at_3
      value: 22.926
    - type: map_at_5
      value: 24.251
    - type: mrr_at_1
      value: 22.831000000000003
    - type: mrr_at_10
      value: 30.009000000000004
    - type: mrr_at_100
      value: 31.045
    - type: mrr_at_1000
      value: 31.122
    - type: mrr_at_3
      value: 28.025
    - type: mrr_at_5
      value: 29.07
    - type: ndcg_at_1
      value: 22.831000000000003
    - type: ndcg_at_10
      value: 29.664
    - type: ndcg_at_100
      value: 35.900999999999996
    - type: ndcg_at_1000
      value: 38.932
    - type: ndcg_at_3
      value: 26.051000000000002
    - type: ndcg_at_5
      value: 27.741
    - type: precision_at_1
      value: 22.831000000000003
    - type: precision_at_10
      value: 5.479
    - type: precision_at_100
      value: 1.027
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 12.481
    - type: precision_at_5
      value: 8.973
    - type: recall_at_1
      value: 18.217
    - type: recall_at_10
      value: 38.336
    - type: recall_at_100
      value: 65.854
    - type: recall_at_1000
      value: 87.498
    - type: recall_at_3
      value: 28.158
    - type: recall_at_5
      value: 32.841
    - type: map_at_1
      value: 19.100666666666665
    - type: map_at_10
      value: 26.22883333333333
    - type: map_at_100
      value: 27.34241666666667
    - type: map_at_1000
      value: 27.468416666666666
    - type: map_at_3
      value: 23.953916666666668
    - type: map_at_5
      value: 25.20125
    - type: mrr_at_1
      value: 22.729249999999997
    - type: mrr_at_10
      value: 29.86491666666667
    - type: mrr_at_100
      value: 30.76925
    - type: mrr_at_1000
      value: 30.846333333333337
    - type: mrr_at_3
      value: 27.733999999999998
    - type: mrr_at_5
      value: 28.94058333333333
    - type: ndcg_at_1
      value: 22.729249999999997
    - type: ndcg_at_10
      value: 30.708250000000003
    - type: ndcg_at_100
      value: 35.89083333333333
    - type: ndcg_at_1000
      value: 38.75891666666666
    - type: ndcg_at_3
      value: 26.661083333333334
    - type: ndcg_at_5
      value: 28.54
    - type: precision_at_1
      value: 22.729249999999997
    - type: precision_at_10
      value: 5.433833333333333
    - type: precision_at_100
      value: 0.9486666666666665
    - type: precision_at_1000
      value: 0.13808333333333334
    - type: precision_at_3
      value: 12.292166666666668
    - type: precision_at_5
      value: 8.825
    - type: recall_at_1
      value: 19.100666666666665
    - type: recall_at_10
      value: 40.54208333333334
    - type: recall_at_100
      value: 63.67975
    - type: recall_at_1000
      value: 84.13574999999999
    - type: recall_at_3
      value: 29.311000000000003
    - type: recall_at_5
      value: 34.1105
    - type: map_at_1
      value: 17.762
    - type: map_at_10
      value: 23.905
    - type: map_at_100
      value: 24.663
    - type: map_at_1000
      value: 24.765
    - type: map_at_3
      value: 22.032
    - type: map_at_5
      value: 23.025000000000002
    - type: mrr_at_1
      value: 20.244999999999997
    - type: mrr_at_10
      value: 26.162999999999997
    - type: mrr_at_100
      value: 26.907999999999998
    - type: mrr_at_1000
      value: 26.987
    - type: mrr_at_3
      value: 24.361
    - type: mrr_at_5
      value: 25.326999999999998
    - type: ndcg_at_1
      value: 20.244999999999997
    - type: ndcg_at_10
      value: 27.577
    - type: ndcg_at_100
      value: 31.473000000000003
    - type: ndcg_at_1000
      value: 34.217999999999996
    - type: ndcg_at_3
      value: 24.092
    - type: ndcg_at_5
      value: 25.657000000000004
    - type: precision_at_1
      value: 20.244999999999997
    - type: precision_at_10
      value: 4.433
    - type: precision_at_100
      value: 0.692
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 10.634
    - type: precision_at_5
      value: 7.362
    - type: recall_at_1
      value: 17.762
    - type: recall_at_10
      value: 36.661
    - type: recall_at_100
      value: 54.581999999999994
    - type: recall_at_1000
      value: 75.28099999999999
    - type: recall_at_3
      value: 27.084999999999997
    - type: recall_at_5
      value: 31.064999999999998
    - type: map_at_1
      value: 12.998000000000001
    - type: map_at_10
      value: 18.926000000000002
    - type: map_at_100
      value: 19.836000000000002
    - type: map_at_1000
      value: 19.96
    - type: map_at_3
      value: 16.932
    - type: map_at_5
      value: 17.963
    - type: mrr_at_1
      value: 15.692
    - type: mrr_at_10
      value: 22.206
    - type: mrr_at_100
      value: 23.021
    - type: mrr_at_1000
      value: 23.108999999999998
    - type: mrr_at_3
      value: 20.114
    - type: mrr_at_5
      value: 21.241
    - type: ndcg_at_1
      value: 15.692
    - type: ndcg_at_10
      value: 22.997999999999998
    - type: ndcg_at_100
      value: 27.541
    - type: ndcg_at_1000
      value: 30.758000000000003
    - type: ndcg_at_3
      value: 19.117
    - type: ndcg_at_5
      value: 20.778
    - type: precision_at_1
      value: 15.692
    - type: precision_at_10
      value: 4.277
    - type: precision_at_100
      value: 0.774
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 9.027000000000001
    - type: precision_at_5
      value: 6.641
    - type: recall_at_1
      value: 12.998000000000001
    - type: recall_at_10
      value: 32.135999999999996
    - type: recall_at_100
      value: 52.937
    - type: recall_at_1000
      value: 76.348
    - type: recall_at_3
      value: 21.292
    - type: recall_at_5
      value: 25.439
    - type: map_at_1
      value: 20.219
    - type: map_at_10
      value: 27.306
    - type: map_at_100
      value: 28.337
    - type: map_at_1000
      value: 28.459
    - type: map_at_3
      value: 25.423000000000002
    - type: map_at_5
      value: 26.375999999999998
    - type: mrr_at_1
      value: 23.787
    - type: mrr_at_10
      value: 30.977
    - type: mrr_at_100
      value: 31.85
    - type: mrr_at_1000
      value: 31.939
    - type: mrr_at_3
      value: 29.073
    - type: mrr_at_5
      value: 30.095
    - type: ndcg_at_1
      value: 23.787
    - type: ndcg_at_10
      value: 31.615
    - type: ndcg_at_100
      value: 36.641
    - type: ndcg_at_1000
      value: 39.707
    - type: ndcg_at_3
      value: 27.994000000000003
    - type: ndcg_at_5
      value: 29.508000000000003
    - type: precision_at_1
      value: 23.787
    - type: precision_at_10
      value: 5.271
    - type: precision_at_100
      value: 0.865
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 12.748999999999999
    - type: precision_at_5
      value: 8.806
    - type: recall_at_1
      value: 20.219
    - type: recall_at_10
      value: 41.108
    - type: recall_at_100
      value: 63.596
    - type: recall_at_1000
      value: 85.54899999999999
    - type: recall_at_3
      value: 31.129
    - type: recall_at_5
      value: 34.845
    - type: map_at_1
      value: 19.949
    - type: map_at_10
      value: 26.629
    - type: map_at_100
      value: 28.006999999999998
    - type: map_at_1000
      value: 28.221
    - type: map_at_3
      value: 24.099999999999998
    - type: map_at_5
      value: 25.487
    - type: mrr_at_1
      value: 24.111
    - type: mrr_at_10
      value: 30.592000000000002
    - type: mrr_at_100
      value: 31.448999999999998
    - type: mrr_at_1000
      value: 31.538
    - type: mrr_at_3
      value: 28.128999999999998
    - type: mrr_at_5
      value: 29.503
    - type: ndcg_at_1
      value: 24.111
    - type: ndcg_at_10
      value: 31.373
    - type: ndcg_at_100
      value: 36.897999999999996
    - type: ndcg_at_1000
      value: 40.288000000000004
    - type: ndcg_at_3
      value: 26.895000000000003
    - type: ndcg_at_5
      value: 29.009
    - type: precision_at_1
      value: 24.111
    - type: precision_at_10
      value: 6.067
    - type: precision_at_100
      value: 1.269
    - type: precision_at_1000
      value: 0.22
    - type: precision_at_3
      value: 12.385
    - type: precision_at_5
      value: 9.249
    - type: recall_at_1
      value: 19.949
    - type: recall_at_10
      value: 40.394000000000005
    - type: recall_at_100
      value: 65.812
    - type: recall_at_1000
      value: 88.247
    - type: recall_at_3
      value: 28.116000000000003
    - type: recall_at_5
      value: 33.4
    - type: map_at_1
      value: 13.905999999999999
    - type: map_at_10
      value: 20.523
    - type: map_at_100
      value: 21.547
    - type: map_at_1000
      value: 21.665
    - type: map_at_3
      value: 18.182000000000002
    - type: map_at_5
      value: 19.661
    - type: mrr_at_1
      value: 14.972
    - type: mrr_at_10
      value: 22.092
    - type: mrr_at_100
      value: 23.055999999999997
    - type: mrr_at_1000
      value: 23.150000000000002
    - type: mrr_at_3
      value: 19.778000000000002
    - type: mrr_at_5
      value: 21.229
    - type: ndcg_at_1
      value: 14.972
    - type: ndcg_at_10
      value: 24.547
    - type: ndcg_at_100
      value: 29.948999999999998
    - type: ndcg_at_1000
      value: 33.084
    - type: ndcg_at_3
      value: 20.036
    - type: ndcg_at_5
      value: 22.567
    - type: precision_at_1
      value: 14.972
    - type: precision_at_10
      value: 4.067
    - type: precision_at_100
      value: 0.743
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 8.811
    - type: precision_at_5
      value: 6.654
    - type: recall_at_1
      value: 13.905999999999999
    - type: recall_at_10
      value: 35.493
    - type: recall_at_100
      value: 60.67399999999999
    - type: recall_at_1000
      value: 84.371
    - type: recall_at_3
      value: 23.555
    - type: recall_at_5
      value: 29.729
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.529
    - type: map_at_10
      value: 12.794
    - type: map_at_100
      value: 14.315
    - type: map_at_1000
      value: 14.523
    - type: map_at_3
      value: 10.367999999999999
    - type: map_at_5
      value: 11.546
    - type: mrr_at_1
      value: 16.872999999999998
    - type: mrr_at_10
      value: 25.709
    - type: mrr_at_100
      value: 26.907999999999998
    - type: mrr_at_1000
      value: 26.962000000000003
    - type: mrr_at_3
      value: 22.486
    - type: mrr_at_5
      value: 24.245
    - type: ndcg_at_1
      value: 16.872999999999998
    - type: ndcg_at_10
      value: 19.005
    - type: ndcg_at_100
      value: 25.990999999999996
    - type: ndcg_at_1000
      value: 29.955
    - type: ndcg_at_3
      value: 14.573
    - type: ndcg_at_5
      value: 16.118
    - type: precision_at_1
      value: 16.872999999999998
    - type: precision_at_10
      value: 6.235
    - type: precision_at_100
      value: 1.374
    - type: precision_at_1000
      value: 0.21
    - type: precision_at_3
      value: 10.793
    - type: precision_at_5
      value: 8.73
    - type: recall_at_1
      value: 7.529
    - type: recall_at_10
      value: 24.007
    - type: recall_at_100
      value: 48.742000000000004
    - type: recall_at_1000
      value: 71.35000000000001
    - type: recall_at_3
      value: 13.467
    - type: recall_at_5
      value: 17.502000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.614
    - type: map_at_10
      value: 11.42
    - type: map_at_100
      value: 15.873000000000001
    - type: map_at_1000
      value: 17.021
    - type: map_at_3
      value: 8.495
    - type: map_at_5
      value: 9.790000000000001
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 52.477
    - type: mrr_at_100
      value: 53.095000000000006
    - type: mrr_at_1000
      value: 53.135
    - type: mrr_at_3
      value: 49.833
    - type: mrr_at_5
      value: 51.183
    - type: ndcg_at_1
      value: 31.374999999999996
    - type: ndcg_at_10
      value: 25.27
    - type: ndcg_at_100
      value: 29.709999999999997
    - type: ndcg_at_1000
      value: 36.975
    - type: ndcg_at_3
      value: 27.688000000000002
    - type: ndcg_at_5
      value: 25.987
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 21.2
    - type: precision_at_100
      value: 7.053
    - type: precision_at_1000
      value: 1.512
    - type: precision_at_3
      value: 32.333
    - type: precision_at_5
      value: 26.6
    - type: recall_at_1
      value: 5.614
    - type: recall_at_10
      value: 16.112000000000002
    - type: recall_at_100
      value: 36.165000000000006
    - type: recall_at_1000
      value: 60.362
    - type: recall_at_3
      value: 9.761000000000001
    - type: recall_at_5
      value: 12.279
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 40.085
    - type: f1
      value: 35.53934111316537
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 34.185
    - type: map_at_10
      value: 44.491
    - type: map_at_100
      value: 45.204
    - type: map_at_1000
      value: 45.254
    - type: map_at_3
      value: 42.006
    - type: map_at_5
      value: 43.516
    - type: mrr_at_1
      value: 37.024
    - type: mrr_at_10
      value: 47.524
    - type: mrr_at_100
      value: 48.185
    - type: mrr_at_1000
      value: 48.227
    - type: mrr_at_3
      value: 45.086999999999996
    - type: mrr_at_5
      value: 46.575
    - type: ndcg_at_1
      value: 37.024
    - type: ndcg_at_10
      value: 50.126000000000005
    - type: ndcg_at_100
      value: 53.577
    - type: ndcg_at_1000
      value: 54.906
    - type: ndcg_at_3
      value: 45.25
    - type: ndcg_at_5
      value: 47.842
    - type: precision_at_1
      value: 37.024
    - type: precision_at_10
      value: 7.132
    - type: precision_at_100
      value: 0.898
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 18.767
    - type: precision_at_5
      value: 12.676000000000002
    - type: recall_at_1
      value: 34.185
    - type: recall_at_10
      value: 64.703
    - type: recall_at_100
      value: 80.58
    - type: recall_at_1000
      value: 90.742
    - type: recall_at_3
      value: 51.483000000000004
    - type: recall_at_5
      value: 57.775
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.358
    - type: map_at_10
      value: 16.391
    - type: map_at_100
      value: 17.698
    - type: map_at_1000
      value: 17.912
    - type: map_at_3
      value: 13.831
    - type: map_at_5
      value: 15.187000000000001
    - type: mrr_at_1
      value: 18.673000000000002
    - type: mrr_at_10
      value: 26.907999999999998
    - type: mrr_at_100
      value: 27.842
    - type: mrr_at_1000
      value: 27.933000000000003
    - type: mrr_at_3
      value: 24.486
    - type: mrr_at_5
      value: 25.766
    - type: ndcg_at_1
      value: 18.673000000000002
    - type: ndcg_at_10
      value: 22.137
    - type: ndcg_at_100
      value: 28.126
    - type: ndcg_at_1000
      value: 32.489000000000004
    - type: ndcg_at_3
      value: 18.723
    - type: ndcg_at_5
      value: 19.858
    - type: precision_at_1
      value: 18.673000000000002
    - type: precision_at_10
      value: 6.389
    - type: precision_at_100
      value: 1.262
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 12.757
    - type: precision_at_5
      value: 9.753
    - type: recall_at_1
      value: 9.358
    - type: recall_at_10
      value: 28.605000000000004
    - type: recall_at_100
      value: 51.713
    - type: recall_at_1000
      value: 78.408
    - type: recall_at_3
      value: 17.674
    - type: recall_at_5
      value: 21.97
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.997999999999998
    - type: map_at_10
      value: 32.957
    - type: map_at_100
      value: 33.972
    - type: map_at_1000
      value: 34.072
    - type: map_at_3
      value: 30.44
    - type: map_at_5
      value: 31.869999999999997
    - type: mrr_at_1
      value: 45.995999999999995
    - type: mrr_at_10
      value: 54.473000000000006
    - type: mrr_at_100
      value: 55.103
    - type: mrr_at_1000
      value: 55.139
    - type: mrr_at_3
      value: 52.349999999999994
    - type: mrr_at_5
      value: 53.61900000000001
    - type: ndcg_at_1
      value: 45.995999999999995
    - type: ndcg_at_10
      value: 41.333
    - type: ndcg_at_100
      value: 45.635999999999996
    - type: ndcg_at_1000
      value: 47.847
    - type: ndcg_at_3
      value: 36.825
    - type: ndcg_at_5
      value: 39.099000000000004
    - type: precision_at_1
      value: 45.995999999999995
    - type: precision_at_10
      value: 9.020999999999999
    - type: precision_at_100
      value: 1.244
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 23.34
    - type: precision_at_5
      value: 15.8
    - type: recall_at_1
      value: 22.997999999999998
    - type: recall_at_10
      value: 45.105000000000004
    - type: recall_at_100
      value: 62.188
    - type: recall_at_1000
      value: 76.907
    - type: recall_at_3
      value: 35.010000000000005
    - type: recall_at_5
      value: 39.5
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 80.0944
    - type: ap
      value: 74.43301569395831
    - type: f1
      value: 80.04407647044388
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 10.171
    - type: map_at_10
      value: 17.558
    - type: map_at_100
      value: 18.694
    - type: map_at_1000
      value: 18.787000000000003
    - type: map_at_3
      value: 14.826
    - type: map_at_5
      value: 16.249
    - type: mrr_at_1
      value: 10.473
    - type: mrr_at_10
      value: 17.967
    - type: mrr_at_100
      value: 19.089
    - type: mrr_at_1000
      value: 19.177
    - type: mrr_at_3
      value: 15.222
    - type: mrr_at_5
      value: 16.655
    - type: ndcg_at_1
      value: 10.473
    - type: ndcg_at_10
      value: 22.148
    - type: ndcg_at_100
      value: 28.028
    - type: ndcg_at_1000
      value: 30.659
    - type: ndcg_at_3
      value: 16.474
    - type: ndcg_at_5
      value: 19.017
    - type: precision_at_1
      value: 10.473
    - type: precision_at_10
      value: 3.7969999999999997
    - type: precision_at_100
      value: 0.6779999999999999
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 7.187
    - type: precision_at_5
      value: 5.599
    - type: recall_at_1
      value: 10.171
    - type: recall_at_10
      value: 36.459
    - type: recall_at_100
      value: 64.512
    - type: recall_at_1000
      value: 85.27900000000001
    - type: recall_at_3
      value: 20.868000000000002
    - type: recall_at_5
      value: 26.933
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 90.35795713634292
    - type: f1
      value: 89.72064544336776
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 66.4546283629731
    - type: f1
      value: 49.487271168215095
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 67.58238063214527
    - type: f1
      value: 65.54281371907213
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.47343644922664
    - type: f1
      value: 72.80522894672785
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.53600917473176
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 28.04699774280647
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.984352865575797
    - type: mrr
      value: 32.02736001972659
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.666
    - type: map_at_10
      value: 10.066
    - type: map_at_100
      value: 12.794
    - type: map_at_1000
      value: 14.184
    - type: map_at_3
      value: 7.622
    - type: map_at_5
      value: 8.587
    - type: mrr_at_1
      value: 39.318999999999996
    - type: mrr_at_10
      value: 47.678
    - type: mrr_at_100
      value: 48.355
    - type: mrr_at_1000
      value: 48.400999999999996
    - type: mrr_at_3
      value: 45.82
    - type: mrr_at_5
      value: 46.656
    - type: ndcg_at_1
      value: 37.926
    - type: ndcg_at_10
      value: 29.049999999999997
    - type: ndcg_at_100
      value: 26.826
    - type: ndcg_at_1000
      value: 35.841
    - type: ndcg_at_3
      value: 33.513
    - type: ndcg_at_5
      value: 31.227
    - type: precision_at_1
      value: 39.318999999999996
    - type: precision_at_10
      value: 21.424000000000003
    - type: precision_at_100
      value: 7.231999999999999
    - type: precision_at_1000
      value: 2.012
    - type: precision_at_3
      value: 30.857
    - type: precision_at_5
      value: 26.378
    - type: recall_at_1
      value: 4.666
    - type: recall_at_10
      value: 13.898
    - type: recall_at_100
      value: 26.983
    - type: recall_at_1000
      value: 59.485
    - type: recall_at_3
      value: 8.953
    - type: recall_at_5
      value: 10.496
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.26
    - type: map_at_10
      value: 17.907999999999998
    - type: map_at_100
      value: 19.245
    - type: map_at_1000
      value: 19.339000000000002
    - type: map_at_3
      value: 14.634
    - type: map_at_5
      value: 16.386
    - type: mrr_at_1
      value: 10.574
    - type: mrr_at_10
      value: 19.438
    - type: mrr_at_100
      value: 20.638
    - type: mrr_at_1000
      value: 20.715
    - type: mrr_at_3
      value: 16.276
    - type: mrr_at_5
      value: 17.971999999999998
    - type: ndcg_at_1
      value: 10.574
    - type: ndcg_at_10
      value: 23.451
    - type: ndcg_at_100
      value: 29.982
    - type: ndcg_at_1000
      value: 32.449
    - type: ndcg_at_3
      value: 16.817
    - type: ndcg_at_5
      value: 19.867
    - type: precision_at_1
      value: 10.574
    - type: precision_at_10
      value: 4.609
    - type: precision_at_100
      value: 0.8330000000000001
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 8.266
    - type: precision_at_5
      value: 6.6739999999999995
    - type: recall_at_1
      value: 9.26
    - type: recall_at_10
      value: 39.224
    - type: recall_at_100
      value: 69.107
    - type: recall_at_1000
      value: 87.908
    - type: recall_at_3
      value: 21.490000000000002
    - type: recall_at_5
      value: 28.560999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 65.655
    - type: map_at_10
      value: 79.199
    - type: map_at_100
      value: 79.937
    - type: map_at_1000
      value: 79.964
    - type: map_at_3
      value: 76.19399999999999
    - type: map_at_5
      value: 78.08800000000001
    - type: mrr_at_1
      value: 75.53999999999999
    - type: mrr_at_10
      value: 82.89
    - type: mrr_at_100
      value: 83.074
    - type: mrr_at_1000
      value: 83.077
    - type: mrr_at_3
      value: 81.577
    - type: mrr_at_5
      value: 82.452
    - type: ndcg_at_1
      value: 75.53999999999999
    - type: ndcg_at_10
      value: 83.62899999999999
    - type: ndcg_at_100
      value: 85.411
    - type: ndcg_at_1000
      value: 85.646
    - type: ndcg_at_3
      value: 80.23700000000001
    - type: ndcg_at_5
      value: 82.107
    - type: precision_at_1
      value: 75.53999999999999
    - type: precision_at_10
      value: 12.695
    - type: precision_at_100
      value: 1.493
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 34.983
    - type: precision_at_5
      value: 23.164
    - type: recall_at_1
      value: 65.655
    - type: recall_at_10
      value: 92.269
    - type: recall_at_100
      value: 98.598
    - type: recall_at_1000
      value: 99.815
    - type: recall_at_3
      value: 82.616
    - type: recall_at_5
      value: 87.75800000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.67844919460687
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 54.32866004447611
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.238
    - type: map_at_10
      value: 8.539
    - type: map_at_100
      value: 10.267
    - type: map_at_1000
      value: 10.552999999999999
    - type: map_at_3
      value: 6.165
    - type: map_at_5
      value: 7.22
    - type: mrr_at_1
      value: 15.9
    - type: mrr_at_10
      value: 25.557999999999996
    - type: mrr_at_100
      value: 26.867
    - type: mrr_at_1000
      value: 26.939
    - type: mrr_at_3
      value: 22.633
    - type: mrr_at_5
      value: 24.233
    - type: ndcg_at_1
      value: 15.9
    - type: ndcg_at_10
      value: 14.954
    - type: ndcg_at_100
      value: 22.486
    - type: ndcg_at_1000
      value: 27.986
    - type: ndcg_at_3
      value: 14.069
    - type: ndcg_at_5
      value: 12.200999999999999
    - type: precision_at_1
      value: 15.9
    - type: precision_at_10
      value: 7.9399999999999995
    - type: precision_at_100
      value: 1.8929999999999998
    - type: precision_at_1000
      value: 0.32299999999999995
    - type: precision_at_3
      value: 13.5
    - type: precision_at_5
      value: 10.9
    - type: recall_at_1
      value: 3.238
    - type: recall_at_10
      value: 16.1
    - type: recall_at_100
      value: 38.427
    - type: recall_at_1000
      value: 65.498
    - type: recall_at_3
      value: 8.212
    - type: recall_at_5
      value: 11.032
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 80.7612029200118
    - type: cos_sim_spearman
      value: 74.17706899450974
    - type: euclidean_pearson
      value: 78.6240925347838
    - type: euclidean_spearman
      value: 74.22104652352341
    - type: manhattan_pearson
      value: 78.49956480878576
    - type: manhattan_spearman
      value: 74.0528957569391
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 80.0377294417705
    - type: cos_sim_spearman
      value: 72.19570903733732
    - type: euclidean_pearson
      value: 77.060604990743
    - type: euclidean_spearman
      value: 71.54251658956483
    - type: manhattan_pearson
      value: 77.28301977645965
    - type: manhattan_spearman
      value: 71.77449045278667
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 79.69841558517969
    - type: cos_sim_spearman
      value: 80.54022353649157
    - type: euclidean_pearson
      value: 80.03651743688496
    - type: euclidean_spearman
      value: 80.45116824930123
    - type: manhattan_pearson
      value: 79.89688370680031
    - type: manhattan_spearman
      value: 80.27208259746283
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 79.92235427443056
    - type: cos_sim_spearman
      value: 76.20243980748161
    - type: euclidean_pearson
      value: 79.28031963400572
    - type: euclidean_spearman
      value: 76.3568261868673
    - type: manhattan_pearson
      value: 79.24527845959733
    - type: manhattan_spearman
      value: 76.39886696744185
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 84.2762365324788
    - type: cos_sim_spearman
      value: 85.19929628214842
    - type: euclidean_pearson
      value: 84.82568872953075
    - type: euclidean_spearman
      value: 85.11039387706913
    - type: manhattan_pearson
      value: 84.72922084197847
    - type: manhattan_spearman
      value: 85.04448532444505
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 80.23256564746382
    - type: cos_sim_spearman
      value: 81.92968415429543
    - type: euclidean_pearson
      value: 81.12612888308936
    - type: euclidean_spearman
      value: 81.97396557448675
    - type: manhattan_pearson
      value: 81.15685601512081
    - type: manhattan_spearman
      value: 82.01929408689
  - 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: 85.35057935029289
    - type: cos_sim_spearman
      value: 86.60658025867397
    - type: euclidean_pearson
      value: 86.48666975508912
    - type: euclidean_spearman
      value: 86.70310223264862
    - type: manhattan_pearson
      value: 86.23959282751626
    - type: manhattan_spearman
      value: 86.48318896577922
  - 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: 63.15375299804011
    - type: cos_sim_spearman
      value: 65.4588500819246
    - type: euclidean_pearson
      value: 65.60180021985416
    - type: euclidean_spearman
      value: 65.55596512146833
    - type: manhattan_pearson
      value: 66.12421335157649
    - type: manhattan_spearman
      value: 66.05163838991123
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 81.82391915730462
    - type: cos_sim_spearman
      value: 81.93942545767499
    - type: euclidean_pearson
      value: 83.16752744889406
    - type: euclidean_spearman
      value: 82.31380947581034
    - type: manhattan_pearson
      value: 82.98915741609575
    - type: manhattan_spearman
      value: 82.16585239338073
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 77.19504204180527
    - type: mrr
      value: 92.85429983959396
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 49.528
    - type: map_at_10
      value: 57.62199999999999
    - type: map_at_100
      value: 58.544
    - type: map_at_1000
      value: 58.573
    - type: map_at_3
      value: 54.56999999999999
    - type: map_at_5
      value: 56.552
    - type: mrr_at_1
      value: 52.0
    - type: mrr_at_10
      value: 58.939
    - type: mrr_at_100
      value: 59.653
    - type: mrr_at_1000
      value: 59.68
    - type: mrr_at_3
      value: 56.389
    - type: mrr_at_5
      value: 57.989000000000004
    - type: ndcg_at_1
      value: 52.0
    - type: ndcg_at_10
      value: 61.964
    - type: ndcg_at_100
      value: 65.871
    - type: ndcg_at_1000
      value: 66.724
    - type: ndcg_at_3
      value: 56.621
    - type: ndcg_at_5
      value: 59.551
    - type: precision_at_1
      value: 52.0
    - type: precision_at_10
      value: 8.333
    - type: precision_at_100
      value: 1.04
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 21.778
    - type: precision_at_5
      value: 14.933
    - type: recall_at_1
      value: 49.528
    - type: recall_at_10
      value: 74.2
    - type: recall_at_100
      value: 91.5
    - type: recall_at_1000
      value: 98.333
    - type: recall_at_3
      value: 60.06700000000001
    - type: recall_at_5
      value: 67.133
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81287128712871
    - type: cos_sim_ap
      value: 95.15039468118793
    - type: cos_sim_f1
      value: 90.48817312531455
    - type: cos_sim_precision
      value: 91.08409321175279
    - type: cos_sim_recall
      value: 89.9
    - type: dot_accuracy
      value: 99.78019801980199
    - type: dot_ap
      value: 93.60256835857994
    - type: dot_f1
      value: 88.73096446700508
    - type: dot_precision
      value: 90.10309278350516
    - type: dot_recall
      value: 87.4
    - type: euclidean_accuracy
      value: 99.81188118811882
    - type: euclidean_ap
      value: 95.15954231276913
    - type: euclidean_f1
      value: 90.48096192384769
    - type: euclidean_precision
      value: 90.66265060240963
    - type: euclidean_recall
      value: 90.3
    - type: manhattan_accuracy
      value: 99.81188118811882
    - type: manhattan_ap
      value: 95.17107000565468
    - type: manhattan_f1
      value: 90.5
    - type: manhattan_precision
      value: 90.5
    - type: manhattan_recall
      value: 90.5
    - type: max_accuracy
      value: 99.81287128712871
    - type: max_ap
      value: 95.17107000565468
    - type: max_f1
      value: 90.5
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 51.77488276525734
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 33.30657214418171
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 47.84571922992432
    - type: mrr
      value: 48.549107142857146
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.840750357585556
    - type: cos_sim_spearman
      value: 29.832953864936567
    - type: dot_pearson
      value: 30.499687946740657
    - type: dot_spearman
      value: 30.73436062481656
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.16999999999999998
    - type: map_at_10
      value: 1.014
    - type: map_at_100
      value: 5.623
    - type: map_at_1000
      value: 15.190999999999999
    - type: map_at_3
      value: 0.377
    - type: map_at_5
      value: 0.577
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 74.45
    - type: mrr_at_100
      value: 74.846
    - type: mrr_at_1000
      value: 74.846
    - type: mrr_at_3
      value: 71.333
    - type: mrr_at_5
      value: 73.533
    - type: ndcg_at_1
      value: 64.0
    - type: ndcg_at_10
      value: 47.52
    - type: ndcg_at_100
      value: 37.419999999999995
    - type: ndcg_at_1000
      value: 36.318
    - type: ndcg_at_3
      value: 51.13999999999999
    - type: ndcg_at_5
      value: 49.101
    - type: precision_at_1
      value: 68.0
    - type: precision_at_10
      value: 50.8
    - type: precision_at_100
      value: 39.160000000000004
    - type: precision_at_1000
      value: 16.948
    - type: precision_at_3
      value: 52.0
    - type: precision_at_5
      value: 51.6
    - type: recall_at_1
      value: 0.16999999999999998
    - type: recall_at_10
      value: 1.269
    - type: recall_at_100
      value: 8.937000000000001
    - type: recall_at_1000
      value: 35.036
    - type: recall_at_3
      value: 0.396
    - type: recall_at_5
      value: 0.6669999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.672
    - type: map_at_10
      value: 6.739000000000001
    - type: map_at_100
      value: 12.006
    - type: map_at_1000
      value: 13.474
    - type: map_at_3
      value: 2.617
    - type: map_at_5
      value: 4.329000000000001
    - type: mrr_at_1
      value: 20.408
    - type: mrr_at_10
      value: 30.764000000000003
    - type: mrr_at_100
      value: 32.457
    - type: mrr_at_1000
      value: 32.481
    - type: mrr_at_3
      value: 26.531
    - type: mrr_at_5
      value: 28.877999999999997
    - type: ndcg_at_1
      value: 18.367
    - type: ndcg_at_10
      value: 17.471999999999998
    - type: ndcg_at_100
      value: 29.341
    - type: ndcg_at_1000
      value: 41.005
    - type: ndcg_at_3
      value: 14.64
    - type: ndcg_at_5
      value: 17.039
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 17.551
    - type: precision_at_100
      value: 6.673
    - type: precision_at_1000
      value: 1.4160000000000001
    - type: precision_at_3
      value: 14.966
    - type: precision_at_5
      value: 18.776
    - type: recall_at_1
      value: 1.672
    - type: recall_at_10
      value: 12.795000000000002
    - type: recall_at_100
      value: 41.289
    - type: recall_at_1000
      value: 76.947
    - type: recall_at_3
      value: 3.334
    - type: recall_at_5
      value: 6.864000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.3424
    - type: ap
      value: 13.45149708639965
    - type: f1
      value: 53.278180518373574
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 57.60045274476513
    - type: f1
      value: 57.9395926195531
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 36.649067825169446
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.68599868868093
    - type: cos_sim_ap
      value: 65.7938550603812
    - type: cos_sim_f1
      value: 61.81946735800141
    - type: cos_sim_precision
      value: 55.85604770017035
    - type: cos_sim_recall
      value: 69.2084432717678
    - type: dot_accuracy
      value: 82.09453418370389
    - type: dot_ap
      value: 61.00867337905922
    - type: dot_f1
      value: 58.56196783349101
    - type: dot_precision
      value: 53.06472353193313
    - type: dot_recall
      value: 65.32981530343008
    - type: euclidean_accuracy
      value: 83.68599868868093
    - type: euclidean_ap
      value: 66.17065796133883
    - type: euclidean_f1
      value: 62.440610152538135
    - type: euclidean_precision
      value: 59.3393536121673
    - type: euclidean_recall
      value: 65.88390501319262
    - type: manhattan_accuracy
      value: 83.57870894677237
    - type: manhattan_ap
      value: 65.89925640001532
    - type: manhattan_f1
      value: 62.2255119664446
    - type: manhattan_precision
      value: 58.43373493975904
    - type: manhattan_recall
      value: 66.54353562005278
    - type: max_accuracy
      value: 83.68599868868093
    - type: max_ap
      value: 66.17065796133883
    - type: max_f1
      value: 62.440610152538135
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.68579966623976
    - type: cos_sim_ap
      value: 83.2666595805096
    - type: cos_sim_f1
      value: 75.11536297129996
    - type: cos_sim_precision
      value: 73.24943294065999
    - type: cos_sim_recall
      value: 77.07884200800738
    - type: dot_accuracy
      value: 86.76213761788334
    - type: dot_ap
      value: 80.85199640255004
    - type: dot_f1
      value: 73.27634898520165
    - type: dot_precision
      value: 71.70756872282409
    - type: dot_recall
      value: 74.91530643671081
    - type: euclidean_accuracy
      value: 87.79640625606395
    - type: euclidean_ap
      value: 83.52666327503474
    - type: euclidean_f1
      value: 75.37022886875523
    - type: euclidean_precision
      value: 71.4522249051397
    - type: euclidean_recall
      value: 79.74283954419464
    - type: manhattan_accuracy
      value: 87.80804905499282
    - type: manhattan_ap
      value: 83.4995899990913
    - type: manhattan_f1
      value: 75.44320420223242
    - type: manhattan_precision
      value: 71.68307223069458
    - type: manhattan_recall
      value: 79.6196489066831
    - type: max_accuracy
      value: 87.80804905499282
    - type: max_ap
      value: 83.52666327503474
    - type: max_f1
      value: 75.44320420223242
---
