mteb model-index region:us
---
tags:
- mteb
model-index:
- name: fasttext_main_gcp
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.8358208955224
    - type: ap
      value: 37.05932769419306
    - type: f1
      value: 67.99060869048547
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 63.01004999999999
    - type: ap
      value: 58.920579113672666
    - type: f1
      value: 62.040535535193975
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.124000000000002
    - type: f1
      value: 30.521326335491246
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 13.94
    - type: map_at_10
      value: 23.919
    - type: map_at_100
      value: 24.977
    - type: map_at_1000
      value: 25.047000000000004
    - type: map_at_3
      value: 20.816000000000003
    - type: map_at_5
      value: 22.608
    - type: mrr_at_1
      value: 14.296000000000001
    - type: mrr_at_10
      value: 24.061
    - type: mrr_at_100
      value: 25.125999999999998
    - type: mrr_at_1000
      value: 25.196
    - type: mrr_at_3
      value: 20.934
    - type: mrr_at_5
      value: 22.758
    - type: ndcg_at_1
      value: 13.94
    - type: ndcg_at_10
      value: 29.543000000000003
    - type: ndcg_at_100
      value: 35.086
    - type: ndcg_at_1000
      value: 37.156
    - type: ndcg_at_3
      value: 23.169
    - type: ndcg_at_5
      value: 26.395000000000003
    - type: precision_at_1
      value: 13.94
    - type: precision_at_10
      value: 4.7509999999999994
    - type: precision_at_100
      value: 0.743
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 10.005
    - type: precision_at_5
      value: 7.568
    - type: recall_at_1
      value: 13.94
    - type: recall_at_10
      value: 47.510999999999996
    - type: recall_at_100
      value: 74.324
    - type: recall_at_1000
      value: 91.11
    - type: recall_at_3
      value: 30.014000000000003
    - type: recall_at_5
      value: 37.838
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 36.773959267301734
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 27.53911280726287
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 50.148759855706025
    - type: mrr
      value: 63.64430813876797
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 60.96274580639198
    - type: cos_sim_spearman
      value: 62.97673617247494
    - type: euclidean_pearson
      value: 62.52462544675977
    - type: euclidean_spearman
      value: 62.97673617247494
    - type: manhattan_pearson
      value: 63.39097043635172
    - type: manhattan_spearman
      value: 64.39182865728104
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 60.532467532467535
    - type: f1
      value: 58.874915306211506
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.068622978919585
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 24.801372128107964
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 14.469999999999999
    - type: map_at_10
      value: 20.473
    - type: map_at_100
      value: 21.379
    - type: map_at_1000
      value: 21.522
    - type: map_at_3
      value: 18.603
    - type: map_at_5
      value: 19.814
    - type: mrr_at_1
      value: 19.313
    - type: mrr_at_10
      value: 25.483
    - type: mrr_at_100
      value: 26.249
    - type: mrr_at_1000
      value: 26.338
    - type: mrr_at_3
      value: 23.748
    - type: mrr_at_5
      value: 24.914
    - type: ndcg_at_1
      value: 19.313
    - type: ndcg_at_10
      value: 24.507
    - type: ndcg_at_100
      value: 29.009
    - type: ndcg_at_1000
      value: 32.4
    - type: ndcg_at_3
      value: 21.902
    - type: ndcg_at_5
      value: 23.379
    - type: precision_at_1
      value: 19.313
    - type: precision_at_10
      value: 4.893
    - type: precision_at_100
      value: 0.8999999999999999
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 11.206000000000001
    - type: precision_at_5
      value: 8.24
    - type: recall_at_1
      value: 14.469999999999999
    - type: recall_at_10
      value: 31.205
    - type: recall_at_100
      value: 52.23100000000001
    - type: recall_at_1000
      value: 76.144
    - type: recall_at_3
      value: 22.975
    - type: recall_at_5
      value: 27.515
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 13.507
    - type: map_at_10
      value: 18.556
    - type: map_at_100
      value: 19.317999999999998
    - type: map_at_1000
      value: 19.426
    - type: map_at_3
      value: 17.037
    - type: map_at_5
      value: 17.949
    - type: mrr_at_1
      value: 17.261000000000003
    - type: mrr_at_10
      value: 22.595000000000002
    - type: mrr_at_100
      value: 23.305
    - type: mrr_at_1000
      value: 23.380000000000003
    - type: mrr_at_3
      value: 21.072
    - type: mrr_at_5
      value: 21.97
    - type: ndcg_at_1
      value: 17.261000000000003
    - type: ndcg_at_10
      value: 21.859
    - type: ndcg_at_100
      value: 25.531
    - type: ndcg_at_1000
      value: 28.402
    - type: ndcg_at_3
      value: 19.354
    - type: ndcg_at_5
      value: 20.613
    - type: precision_at_1
      value: 17.261000000000003
    - type: precision_at_10
      value: 4.159
    - type: precision_at_100
      value: 0.757
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 9.447999999999999
    - type: precision_at_5
      value: 6.854
    - type: recall_at_1
      value: 13.507
    - type: recall_at_10
      value: 27.677000000000003
    - type: recall_at_100
      value: 43.657000000000004
    - type: recall_at_1000
      value: 63.865
    - type: recall_at_3
      value: 20.483
    - type: recall_at_5
      value: 23.78
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 19.11
    - type: map_at_10
      value: 25.22
    - type: map_at_100
      value: 26.138
    - type: map_at_1000
      value: 26.229000000000003
    - type: map_at_3
      value: 23.284
    - type: map_at_5
      value: 24.305
    - type: mrr_at_1
      value: 22.131999999999998
    - type: mrr_at_10
      value: 28.08
    - type: mrr_at_100
      value: 28.912
    - type: mrr_at_1000
      value: 28.98
    - type: mrr_at_3
      value: 26.217000000000002
    - type: mrr_at_5
      value: 27.217000000000002
    - type: ndcg_at_1
      value: 22.131999999999998
    - type: ndcg_at_10
      value: 29.041
    - type: ndcg_at_100
      value: 33.681
    - type: ndcg_at_1000
      value: 36.162
    - type: ndcg_at_3
      value: 25.261
    - type: ndcg_at_5
      value: 26.938000000000002
    - type: precision_at_1
      value: 22.131999999999998
    - type: precision_at_10
      value: 4.715
    - type: precision_at_100
      value: 0.769
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 11.181000000000001
    - type: precision_at_5
      value: 7.762
    - type: recall_at_1
      value: 19.11
    - type: recall_at_10
      value: 38.085
    - type: recall_at_100
      value: 59.207
    - type: recall_at_1000
      value: 77.718
    - type: recall_at_3
      value: 27.722
    - type: recall_at_5
      value: 31.919999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 5.970000000000001
    - type: map_at_10
      value: 8.695
    - type: map_at_100
      value: 9.261
    - type: map_at_1000
      value: 9.347
    - type: map_at_3
      value: 7.516
    - type: map_at_5
      value: 8.225999999999999
    - type: mrr_at_1
      value: 6.554
    - type: mrr_at_10
      value: 9.503
    - type: mrr_at_100
      value: 10.09
    - type: mrr_at_1000
      value: 10.174
    - type: mrr_at_3
      value: 8.267
    - type: mrr_at_5
      value: 9.008
    - type: ndcg_at_1
      value: 6.554
    - type: ndcg_at_10
      value: 10.626
    - type: ndcg_at_100
      value: 13.893
    - type: ndcg_at_1000
      value: 16.723
    - type: ndcg_at_3
      value: 8.246
    - type: ndcg_at_5
      value: 9.472999999999999
    - type: precision_at_1
      value: 6.554
    - type: precision_at_10
      value: 1.831
    - type: precision_at_100
      value: 0.372
    - type: precision_at_1000
      value: 0.065
    - type: precision_at_3
      value: 3.578
    - type: precision_at_5
      value: 2.825
    - type: recall_at_1
      value: 5.970000000000001
    - type: recall_at_10
      value: 15.962000000000002
    - type: recall_at_100
      value: 31.962000000000003
    - type: recall_at_1000
      value: 54.581
    - type: recall_at_3
      value: 9.464
    - type: recall_at_5
      value: 12.43
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 3.946
    - type: map_at_10
      value: 6.2010000000000005
    - type: map_at_100
      value: 6.676
    - type: map_at_1000
      value: 6.7669999999999995
    - type: map_at_3
      value: 5.364
    - type: map_at_5
      value: 5.835
    - type: mrr_at_1
      value: 5.1
    - type: mrr_at_10
      value: 7.815999999999999
    - type: mrr_at_100
      value: 8.38
    - type: mrr_at_1000
      value: 8.466
    - type: mrr_at_3
      value: 6.675000000000001
    - type: mrr_at_5
      value: 7.3469999999999995
    - type: ndcg_at_1
      value: 5.1
    - type: ndcg_at_10
      value: 7.947
    - type: ndcg_at_100
      value: 10.811
    - type: ndcg_at_1000
      value: 13.614999999999998
    - type: ndcg_at_3
      value: 6.172
    - type: ndcg_at_5
      value: 7.049999999999999
    - type: precision_at_1
      value: 5.1
    - type: precision_at_10
      value: 1.555
    - type: precision_at_100
      value: 0.35200000000000004
    - type: precision_at_1000
      value: 0.06899999999999999
    - type: precision_at_3
      value: 2.902
    - type: precision_at_5
      value: 2.363
    - type: recall_at_1
      value: 3.946
    - type: recall_at_10
      value: 11.795
    - type: recall_at_100
      value: 25.183
    - type: recall_at_1000
      value: 46.206
    - type: recall_at_3
      value: 7.19
    - type: recall_at_5
      value: 9.251
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 12.08
    - type: map_at_10
      value: 16.421
    - type: map_at_100
      value: 17.272000000000002
    - type: map_at_1000
      value: 17.391000000000002
    - type: map_at_3
      value: 14.793000000000001
    - type: map_at_5
      value: 15.648000000000001
    - type: mrr_at_1
      value: 14.726
    - type: mrr_at_10
      value: 19.676
    - type: mrr_at_100
      value: 20.461
    - type: mrr_at_1000
      value: 20.546
    - type: mrr_at_3
      value: 17.902
    - type: mrr_at_5
      value: 18.811
    - type: ndcg_at_1
      value: 14.726
    - type: ndcg_at_10
      value: 19.656000000000002
    - type: ndcg_at_100
      value: 24.043999999999997
    - type: ndcg_at_1000
      value: 27.209
    - type: ndcg_at_3
      value: 16.619
    - type: ndcg_at_5
      value: 17.959
    - type: precision_at_1
      value: 14.726
    - type: precision_at_10
      value: 3.6769999999999996
    - type: precision_at_100
      value: 0.724
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 7.732
    - type: precision_at_5
      value: 5.736
    - type: recall_at_1
      value: 12.08
    - type: recall_at_10
      value: 26.334000000000003
    - type: recall_at_100
      value: 45.854
    - type: recall_at_1000
      value: 68.589
    - type: recall_at_3
      value: 17.773
    - type: recall_at_5
      value: 21.113
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 8.486
    - type: map_at_10
      value: 11.785
    - type: map_at_100
      value: 12.572
    - type: map_at_1000
      value: 12.681999999999999
    - type: map_at_3
      value: 10.439
    - type: map_at_5
      value: 11.227
    - type: mrr_at_1
      value: 10.502
    - type: mrr_at_10
      value: 14.255999999999998
    - type: mrr_at_100
      value: 15.068999999999999
    - type: mrr_at_1000
      value: 15.15
    - type: mrr_at_3
      value: 12.690000000000001
    - type: mrr_at_5
      value: 13.678
    - type: ndcg_at_1
      value: 10.502
    - type: ndcg_at_10
      value: 14.369000000000002
    - type: ndcg_at_100
      value: 18.807
    - type: ndcg_at_1000
      value: 21.998
    - type: ndcg_at_3
      value: 11.706
    - type: ndcg_at_5
      value: 13.114999999999998
    - type: precision_at_1
      value: 10.502
    - type: precision_at_10
      value: 2.705
    - type: precision_at_100
      value: 0.606
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 5.479
    - type: precision_at_5
      value: 4.338
    - type: recall_at_1
      value: 8.486
    - type: recall_at_10
      value: 19.895
    - type: recall_at_100
      value: 40.233999999999995
    - type: recall_at_1000
      value: 63.502
    - type: recall_at_3
      value: 12.934000000000001
    - type: recall_at_5
      value: 16.227
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 9.86625
    - type: map_at_10
      value: 13.610333333333333
    - type: map_at_100
      value: 14.300916666666666
    - type: map_at_1000
      value: 14.408333333333335
    - type: map_at_3
      value: 12.315333333333333
    - type: map_at_5
      value: 13.012833333333331
    - type: mrr_at_1
      value: 12.075833333333334
    - type: mrr_at_10
      value: 16.16466666666667
    - type: mrr_at_100
      value: 16.834999999999997
    - type: mrr_at_1000
      value: 16.91916666666667
    - type: mrr_at_3
      value: 14.80633333333333
    - type: mrr_at_5
      value: 15.5455
    - type: ndcg_at_1
      value: 12.075833333333334
    - type: ndcg_at_10
      value: 16.30866666666667
    - type: ndcg_at_100
      value: 19.96975
    - type: ndcg_at_1000
      value: 22.941499999999998
    - type: ndcg_at_3
      value: 13.900000000000002
    - type: ndcg_at_5
      value: 14.974749999999998
    - type: precision_at_1
      value: 12.075833333333334
    - type: precision_at_10
      value: 2.990333333333334
    - type: precision_at_100
      value: 0.5833333333333335
    - type: precision_at_1000
      value: 0.10024999999999999
    - type: precision_at_3
      value: 6.517250000000001
    - type: precision_at_5
      value: 4.741833333333333
    - type: recall_at_1
      value: 9.86625
    - type: recall_at_10
      value: 21.98225
    - type: recall_at_100
      value: 39.01191666666667
    - type: recall_at_1000
      value: 61.04558333333333
    - type: recall_at_3
      value: 15.127416666666669
    - type: recall_at_5
      value: 17.91883333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 7.297
    - type: map_at_10
      value: 10.67
    - type: map_at_100
      value: 11.257
    - type: map_at_1000
      value: 11.328000000000001
    - type: map_at_3
      value: 9.513
    - type: map_at_5
      value: 10.184999999999999
    - type: mrr_at_1
      value: 8.741999999999999
    - type: mrr_at_10
      value: 12.423
    - type: mrr_at_100
      value: 12.989
    - type: mrr_at_1000
      value: 13.055
    - type: mrr_at_3
      value: 11.222
    - type: mrr_at_5
      value: 11.95
    - type: ndcg_at_1
      value: 8.741999999999999
    - type: ndcg_at_10
      value: 12.937000000000001
    - type: ndcg_at_100
      value: 16.055
    - type: ndcg_at_1000
      value: 18.265
    - type: ndcg_at_3
      value: 10.674999999999999
    - type: ndcg_at_5
      value: 11.82
    - type: precision_at_1
      value: 8.741999999999999
    - type: precision_at_10
      value: 2.316
    - type: precision_at_100
      value: 0.422
    - type: precision_at_1000
      value: 0.067
    - type: precision_at_3
      value: 4.9590000000000005
    - type: precision_at_5
      value: 3.681
    - type: recall_at_1
      value: 7.297
    - type: recall_at_10
      value: 18.249000000000002
    - type: recall_at_100
      value: 32.897999999999996
    - type: recall_at_1000
      value: 49.96
    - type: recall_at_3
      value: 12.025
    - type: recall_at_5
      value: 14.911
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 4.707
    - type: map_at_10
      value: 6.880999999999999
    - type: map_at_100
      value: 7.333
    - type: map_at_1000
      value: 7.4190000000000005
    - type: map_at_3
      value: 6.099
    - type: map_at_5
      value: 6.497
    - type: mrr_at_1
      value: 6.091
    - type: mrr_at_10
      value: 8.716
    - type: mrr_at_100
      value: 9.199
    - type: mrr_at_1000
      value: 9.279
    - type: mrr_at_3
      value: 7.8229999999999995
    - type: mrr_at_5
      value: 8.277
    - type: ndcg_at_1
      value: 6.091
    - type: ndcg_at_10
      value: 8.606
    - type: ndcg_at_100
      value: 11.199
    - type: ndcg_at_1000
      value: 13.900000000000002
    - type: ndcg_at_3
      value: 7.090000000000001
    - type: ndcg_at_5
      value: 7.702000000000001
    - type: precision_at_1
      value: 6.091
    - type: precision_at_10
      value: 1.686
    - type: precision_at_100
      value: 0.359
    - type: precision_at_1000
      value: 0.06999999999999999
    - type: precision_at_3
      value: 3.4639999999999995
    - type: precision_at_5
      value: 2.581
    - type: recall_at_1
      value: 4.707
    - type: recall_at_10
      value: 12.167
    - type: recall_at_100
      value: 24.428
    - type: recall_at_1000
      value: 44.789
    - type: recall_at_3
      value: 7.775
    - type: recall_at_5
      value: 9.386999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 10.186
    - type: map_at_10
      value: 13.07
    - type: map_at_100
      value: 13.654
    - type: map_at_1000
      value: 13.761000000000001
    - type: map_at_3
      value: 11.89
    - type: map_at_5
      value: 12.386999999999999
    - type: mrr_at_1
      value: 12.127
    - type: mrr_at_10
      value: 15.678
    - type: mrr_at_100
      value: 16.262
    - type: mrr_at_1000
      value: 16.361
    - type: mrr_at_3
      value: 14.396999999999998
    - type: mrr_at_5
      value: 14.887
    - type: ndcg_at_1
      value: 12.127
    - type: ndcg_at_10
      value: 15.607
    - type: ndcg_at_100
      value: 18.759999999999998
    - type: ndcg_at_1000
      value: 22.019
    - type: ndcg_at_3
      value: 13.166
    - type: ndcg_at_5
      value: 13.916999999999998
    - type: precision_at_1
      value: 12.127
    - type: precision_at_10
      value: 2.649
    - type: precision_at_100
      value: 0.473
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 5.908
    - type: precision_at_5
      value: 4.067
    - type: recall_at_1
      value: 10.186
    - type: recall_at_10
      value: 21.227999999999998
    - type: recall_at_100
      value: 35.812
    - type: recall_at_1000
      value: 60.436
    - type: recall_at_3
      value: 14.011999999999999
    - type: recall_at_5
      value: 16.04
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 11.088000000000001
    - type: map_at_10
      value: 15.311
    - type: map_at_100
      value: 16.104
    - type: map_at_1000
      value: 16.285
    - type: map_at_3
      value: 13.911000000000001
    - type: map_at_5
      value: 14.454
    - type: mrr_at_1
      value: 14.229
    - type: mrr_at_10
      value: 18.834999999999997
    - type: mrr_at_100
      value: 19.564999999999998
    - type: mrr_at_1000
      value: 19.665
    - type: mrr_at_3
      value: 17.589
    - type: mrr_at_5
      value: 18.034
    - type: ndcg_at_1
      value: 14.229
    - type: ndcg_at_10
      value: 18.715
    - type: ndcg_at_100
      value: 22.689999999999998
    - type: ndcg_at_1000
      value: 26.351999999999997
    - type: ndcg_at_3
      value: 16.424
    - type: ndcg_at_5
      value: 16.991999999999997
    - type: precision_at_1
      value: 14.229
    - type: precision_at_10
      value: 3.794
    - type: precision_at_100
      value: 0.874
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 8.036999999999999
    - type: precision_at_5
      value: 5.534
    - type: recall_at_1
      value: 11.088000000000001
    - type: recall_at_10
      value: 24.603
    - type: recall_at_100
      value: 44.41
    - type: recall_at_1000
      value: 70.00800000000001
    - type: recall_at_3
      value: 17.192
    - type: recall_at_5
      value: 19.236
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 7.548000000000001
    - type: map_at_10
      value: 10.041
    - type: map_at_100
      value: 10.647
    - type: map_at_1000
      value: 10.743
    - type: map_at_3
      value: 9.335
    - type: map_at_5
      value: 9.626999999999999
    - type: mrr_at_1
      value: 8.133
    - type: mrr_at_10
      value: 10.915
    - type: mrr_at_100
      value: 11.539000000000001
    - type: mrr_at_1000
      value: 11.636000000000001
    - type: mrr_at_3
      value: 10.074
    - type: mrr_at_5
      value: 10.453
    - type: ndcg_at_1
      value: 8.133
    - type: ndcg_at_10
      value: 11.834
    - type: ndcg_at_100
      value: 15.157000000000002
    - type: ndcg_at_1000
      value: 18.253
    - type: ndcg_at_3
      value: 10.184999999999999
    - type: ndcg_at_5
      value: 10.739
    - type: precision_at_1
      value: 8.133
    - type: precision_at_10
      value: 1.9040000000000001
    - type: precision_at_100
      value: 0.392
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 4.313000000000001
    - type: precision_at_5
      value: 2.921
    - type: recall_at_1
      value: 7.548000000000001
    - type: recall_at_10
      value: 16.587
    - type: recall_at_100
      value: 32.267
    - type: recall_at_1000
      value: 56.749
    - type: recall_at_3
      value: 11.984
    - type: recall_at_5
      value: 13.216
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.405
    - type: map_at_10
      value: 9.92
    - type: map_at_100
      value: 11.148
    - type: map_at_1000
      value: 11.315999999999999
    - type: map_at_3
      value: 8.121
    - type: map_at_5
      value: 8.985
    - type: mrr_at_1
      value: 13.16
    - type: mrr_at_10
      value: 20.937
    - type: mrr_at_100
      value: 21.97
    - type: mrr_at_1000
      value: 22.047
    - type: mrr_at_3
      value: 18.295
    - type: mrr_at_5
      value: 19.706000000000003
    - type: ndcg_at_1
      value: 13.16
    - type: ndcg_at_10
      value: 15.091
    - type: ndcg_at_100
      value: 20.957
    - type: ndcg_at_1000
      value: 24.538
    - type: ndcg_at_3
      value: 11.75
    - type: ndcg_at_5
      value: 12.851
    - type: precision_at_1
      value: 13.16
    - type: precision_at_10
      value: 5.049
    - type: precision_at_100
      value: 1.131
    - type: precision_at_1000
      value: 0.178
    - type: precision_at_3
      value: 9.034
    - type: precision_at_5
      value: 7.127
    - type: recall_at_1
      value: 5.405
    - type: recall_at_10
      value: 19.029
    - type: recall_at_100
      value: 40.198
    - type: recall_at_1000
      value: 60.731
    - type: recall_at_3
      value: 10.938
    - type: recall_at_5
      value: 14.052000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 1.8339999999999999
    - type: map_at_10
      value: 4.495
    - type: map_at_100
      value: 6.571000000000001
    - type: map_at_1000
      value: 7.219
    - type: map_at_3
      value: 3.011
    - type: map_at_5
      value: 3.7409999999999997
    - type: mrr_at_1
      value: 23.0
    - type: mrr_at_10
      value: 32.812999999999995
    - type: mrr_at_100
      value: 33.79
    - type: mrr_at_1000
      value: 33.853
    - type: mrr_at_3
      value: 29.875
    - type: mrr_at_5
      value: 31.624999999999996
    - type: ndcg_at_1
      value: 16.375
    - type: ndcg_at_10
      value: 13.153
    - type: ndcg_at_100
      value: 16.036
    - type: ndcg_at_1000
      value: 22.221
    - type: ndcg_at_3
      value: 14.135
    - type: ndcg_at_5
      value: 13.825999999999999
    - type: precision_at_1
      value: 23.0
    - type: precision_at_10
      value: 12.425
    - type: precision_at_100
      value: 4.287
    - type: precision_at_1000
      value: 0.9950000000000001
    - type: precision_at_3
      value: 17.583
    - type: precision_at_5
      value: 15.8
    - type: recall_at_1
      value: 1.8339999999999999
    - type: recall_at_10
      value: 8.286
    - type: recall_at_100
      value: 21.938
    - type: recall_at_1000
      value: 43.192
    - type: recall_at_3
      value: 3.904
    - type: recall_at_5
      value: 5.821
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 32.865
    - type: f1
      value: 30.37449911679073
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 10.581999999999999
    - type: map_at_10
      value: 15.384999999999998
    - type: map_at_100
      value: 16.173000000000002
    - type: map_at_1000
      value: 16.253
    - type: map_at_3
      value: 13.819999999999999
    - type: map_at_5
      value: 14.627
    - type: mrr_at_1
      value: 11.296000000000001
    - type: mrr_at_10
      value: 16.305
    - type: mrr_at_100
      value: 17.131
    - type: mrr_at_1000
      value: 17.205000000000002
    - type: mrr_at_3
      value: 14.655999999999999
    - type: mrr_at_5
      value: 15.512
    - type: ndcg_at_1
      value: 11.296000000000001
    - type: ndcg_at_10
      value: 18.401999999999997
    - type: ndcg_at_100
      value: 22.677
    - type: ndcg_at_1000
      value: 25.072
    - type: ndcg_at_3
      value: 15.089
    - type: ndcg_at_5
      value: 16.554
    - type: precision_at_1
      value: 11.296000000000001
    - type: precision_at_10
      value: 2.934
    - type: precision_at_100
      value: 0.524
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 6.411
    - type: precision_at_5
      value: 4.623
    - type: recall_at_1
      value: 10.581999999999999
    - type: recall_at_10
      value: 27.061
    - type: recall_at_100
      value: 47.522999999999996
    - type: recall_at_1000
      value: 66.376
    - type: recall_at_3
      value: 17.942
    - type: recall_at_5
      value: 21.453
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.1419999999999995
    - type: map_at_10
      value: 7.237
    - type: map_at_100
      value: 7.9670000000000005
    - type: map_at_1000
      value: 8.118
    - type: map_at_3
      value: 6.129
    - type: map_at_5
      value: 6.569
    - type: mrr_at_1
      value: 8.025
    - type: mrr_at_10
      value: 12.7
    - type: mrr_at_100
      value: 13.565
    - type: mrr_at_1000
      value: 13.679
    - type: mrr_at_3
      value: 11.06
    - type: mrr_at_5
      value: 11.824
    - type: ndcg_at_1
      value: 8.025
    - type: ndcg_at_10
      value: 10.324
    - type: ndcg_at_100
      value: 14.494000000000002
    - type: ndcg_at_1000
      value: 18.552
    - type: ndcg_at_3
      value: 8.161
    - type: ndcg_at_5
      value: 8.745
    - type: precision_at_1
      value: 8.025
    - type: precision_at_10
      value: 2.948
    - type: precision_at_100
      value: 0.7100000000000001
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 5.453
    - type: precision_at_5
      value: 4.105
    - type: recall_at_1
      value: 4.1419999999999995
    - type: recall_at_10
      value: 14.329
    - type: recall_at_100
      value: 31.011
    - type: recall_at_1000
      value: 56.995
    - type: recall_at_3
      value: 8.043
    - type: recall_at_5
      value: 9.777
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 11.296000000000001
    - type: map_at_10
      value: 15.665999999999999
    - type: map_at_100
      value: 16.337
    - type: map_at_1000
      value: 16.425
    - type: map_at_3
      value: 14.318
    - type: map_at_5
      value: 15.068000000000001
    - type: mrr_at_1
      value: 22.593
    - type: mrr_at_10
      value: 27.923
    - type: mrr_at_100
      value: 28.639
    - type: mrr_at_1000
      value: 28.708
    - type: mrr_at_3
      value: 26.349
    - type: mrr_at_5
      value: 27.282
    - type: ndcg_at_1
      value: 22.593
    - type: ndcg_at_10
      value: 20.558
    - type: ndcg_at_100
      value: 23.957
    - type: ndcg_at_1000
      value: 26.381
    - type: ndcg_at_3
      value: 17.843999999999998
    - type: ndcg_at_5
      value: 19.189
    - type: precision_at_1
      value: 22.593
    - type: precision_at_10
      value: 4.601
    - type: precision_at_100
      value: 0.732
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 11.254
    - type: precision_at_5
      value: 7.819
    - type: recall_at_1
      value: 11.296000000000001
    - type: recall_at_10
      value: 23.005
    - type: recall_at_100
      value: 36.597
    - type: recall_at_1000
      value: 52.93
    - type: recall_at_3
      value: 16.88
    - type: recall_at_5
      value: 19.548
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.0888
    - type: ap
      value: 59.22274617570268
    - type: f1
      value: 63.820834375197286
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 2.822
    - type: map_at_10
      value: 4.9079999999999995
    - type: map_at_100
      value: 5.4670000000000005
    - type: map_at_1000
      value: 5.552
    - type: map_at_3
      value: 4.064
    - type: map_at_5
      value: 4.479
    - type: mrr_at_1
      value: 2.851
    - type: mrr_at_10
      value: 5.013
    - type: mrr_at_100
      value: 5.582
    - type: mrr_at_1000
      value: 5.666
    - type: mrr_at_3
      value: 4.14
    - type: mrr_at_5
      value: 4.566
    - type: ndcg_at_1
      value: 2.8369999999999997
    - type: ndcg_at_10
      value: 6.32
    - type: ndcg_at_100
      value: 9.546000000000001
    - type: ndcg_at_1000
      value: 12.223
    - type: ndcg_at_3
      value: 4.517
    - type: ndcg_at_5
      value: 5.267
    - type: precision_at_1
      value: 2.8369999999999997
    - type: precision_at_10
      value: 1.119
    - type: precision_at_100
      value: 0.28300000000000003
    - type: precision_at_1000
      value: 0.052
    - type: precision_at_3
      value: 1.968
    - type: precision_at_5
      value: 1.559
    - type: recall_at_1
      value: 2.822
    - type: recall_at_10
      value: 10.788
    - type: recall_at_100
      value: 26.848
    - type: recall_at_1000
      value: 48.613
    - type: recall_at_3
      value: 5.759
    - type: recall_at_5
      value: 7.5600000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.23255813953489
    - type: f1
      value: 84.76831380049289
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.27906976744186
    - type: f1
      value: 36.70422505440829
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 56.38870208473436
    - type: f1
      value: 53.66913773017876
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.53597848016139
    - type: f1
      value: 62.79623963098659
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.851032342558657
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.45639299405684
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 26.933564143700906
    - type: mrr
      value: 27.269913096479957
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.405
    - type: map_at_10
      value: 7.180000000000001
    - type: map_at_100
      value: 9.014999999999999
    - type: map_at_1000
      value: 10.211
    - type: map_at_3
      value: 5.541
    - type: map_at_5
      value: 6.29
    - type: mrr_at_1
      value: 26.316
    - type: mrr_at_10
      value: 37.216
    - type: mrr_at_100
      value: 38.155
    - type: mrr_at_1000
      value: 38.216
    - type: mrr_at_3
      value: 35.243
    - type: mrr_at_5
      value: 36.434
    - type: ndcg_at_1
      value: 24.768
    - type: ndcg_at_10
      value: 21.11
    - type: ndcg_at_100
      value: 21.051000000000002
    - type: ndcg_at_1000
      value: 30.789
    - type: ndcg_at_3
      value: 23.94
    - type: ndcg_at_5
      value: 22.512
    - type: precision_at_1
      value: 26.316
    - type: precision_at_10
      value: 15.387
    - type: precision_at_100
      value: 5.824
    - type: precision_at_1000
      value: 1.923
    - type: precision_at_3
      value: 22.601
    - type: precision_at_5
      value: 19.195
    - type: recall_at_1
      value: 3.405
    - type: recall_at_10
      value: 11.04
    - type: recall_at_100
      value: 24.92
    - type: recall_at_1000
      value: 58.472
    - type: recall_at_3
      value: 6.746
    - type: recall_at_5
      value: 8.366
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 3.879
    - type: map_at_10
      value: 6.714
    - type: map_at_100
      value: 7.2989999999999995
    - type: map_at_1000
      value: 7.376
    - type: map_at_3
      value: 5.5440000000000005
    - type: map_at_5
      value: 6.128
    - type: mrr_at_1
      value: 4.635
    - type: mrr_at_10
      value: 7.686999999999999
    - type: mrr_at_100
      value: 8.272
    - type: mrr_at_1000
      value: 8.341
    - type: mrr_at_3
      value: 6.4750000000000005
    - type: mrr_at_5
      value: 7.093000000000001
    - type: ndcg_at_1
      value: 4.635
    - type: ndcg_at_10
      value: 8.745
    - type: ndcg_at_100
      value: 11.95
    - type: ndcg_at_1000
      value: 14.248
    - type: ndcg_at_3
      value: 6.311
    - type: ndcg_at_5
      value: 7.364
    - type: precision_at_1
      value: 4.635
    - type: precision_at_10
      value: 1.7149999999999999
    - type: precision_at_100
      value: 0.358
    - type: precision_at_1000
      value: 0.058
    - type: precision_at_3
      value: 3.042
    - type: precision_at_5
      value: 2.4330000000000003
    - type: recall_at_1
      value: 3.879
    - type: recall_at_10
      value: 14.129
    - type: recall_at_100
      value: 29.369
    - type: recall_at_1000
      value: 47.313
    - type: recall_at_3
      value: 7.631
    - type: recall_at_5
      value: 10.098
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 53.702000000000005
    - type: map_at_10
      value: 65.176
    - type: map_at_100
      value: 65.999
    - type: map_at_1000
      value: 66.049
    - type: map_at_3
      value: 62.368
    - type: map_at_5
      value: 64.077
    - type: mrr_at_1
      value: 61.91
    - type: mrr_at_10
      value: 69.99
    - type: mrr_at_100
      value: 70.365
    - type: mrr_at_1000
      value: 70.383
    - type: mrr_at_3
      value: 68.21000000000001
    - type: mrr_at_5
      value: 69.33
    - type: ndcg_at_1
      value: 61.92999999999999
    - type: ndcg_at_10
      value: 70.295
    - type: ndcg_at_100
      value: 73.1
    - type: ndcg_at_1000
      value: 73.916
    - type: ndcg_at_3
      value: 66.355
    - type: ndcg_at_5
      value: 68.403
    - type: precision_at_1
      value: 61.92999999999999
    - type: precision_at_10
      value: 10.671999999999999
    - type: precision_at_100
      value: 1.332
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_3
      value: 28.83
    - type: precision_at_5
      value: 19.216
    - type: recall_at_1
      value: 53.702000000000005
    - type: recall_at_10
      value: 80.455
    - type: recall_at_100
      value: 91.75999999999999
    - type: recall_at_1000
      value: 97.033
    - type: recall_at_3
      value: 69.228
    - type: recall_at_5
      value: 74.766
    - type: map_at_1
      value: 1.043
    - type: map_at_10
      value: 2.456
    - type: map_at_100
      value: 2.913
    - type: map_at_1000
      value: 3.078
    - type: map_at_3
      value: 1.7870000000000001
    - type: map_at_5
      value: 2.173
    - type: mrr_at_1
      value: 5.1
    - type: mrr_at_10
      value: 8.515
    - type: mrr_at_100
      value: 9.149000000000001
    - type: mrr_at_1000
      value: 9.276
    - type: mrr_at_3
      value: 7.2669999999999995
    - type: mrr_at_5
      value: 7.962
    - type: ndcg_at_1
      value: 5.1
    - type: ndcg_at_10
      value: 4.578
    - type: ndcg_at_100
      value: 7.26
    - type: ndcg_at_1000
      value: 11.705
    - type: ndcg_at_3
      value: 4.194
    - type: ndcg_at_5
      value: 3.823
    - type: precision_at_1
      value: 5.1
    - type: precision_at_10
      value: 2.39
    - type: precision_at_100
      value: 0.645
    - type: precision_at_1000
      value: 0.174
    - type: precision_at_3
      value: 3.9
    - type: precision_at_5
      value: 3.4000000000000004
    - type: recall_at_1
      value: 1.043
    - type: recall_at_10
      value: 4.882000000000001
    - type: recall_at_100
      value: 13.15
    - type: recall_at_1000
      value: 35.385
    - type: recall_at_3
      value: 2.388
    - type: recall_at_5
      value: 3.4770000000000003
    - type: map_at_1
      value: 0.123
    - type: map_at_10
      value: 0.8380000000000001
    - type: map_at_100
      value: 3.5389999999999997
    - type: map_at_1000
      value: 8.105
    - type: map_at_3
      value: 0.319
    - type: map_at_5
      value: 0.482
    - type: mrr_at_1
      value: 52.0
    - type: mrr_at_10
      value: 63.839
    - type: mrr_at_100
      value: 64.274
    - type: mrr_at_1000
      value: 64.274
    - type: mrr_at_3
      value: 62.0
    - type: mrr_at_5
      value: 62.5
    - type: ndcg_at_1
      value: 45.0
    - type: ndcg_at_10
      value: 43.013
    - type: ndcg_at_100
      value: 28.294999999999998
    - type: ndcg_at_1000
      value: 24.868000000000002
    - type: ndcg_at_3
      value: 45.112
    - type: ndcg_at_5
      value: 44.41
    - type: precision_at_1
      value: 52.0
    - type: precision_at_10
      value: 47.4
    - type: precision_at_100
      value: 29.42
    - type: precision_at_1000
      value: 12.126000000000001
    - type: precision_at_3
      value: 50.666999999999994
    - type: precision_at_5
      value: 50.0
    - type: recall_at_1
      value: 0.123
    - type: recall_at_10
      value: 1.101
    - type: recall_at_100
      value: 6.366
    - type: recall_at_1000
      value: 24.29
    - type: recall_at_3
      value: 0.368
    - type: recall_at_5
      value: 0.5910000000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 25.781222642642586
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 39.46989553732726
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 69.93170082002553
    - type: cos_sim_spearman
      value: 60.08741092780676
    - type: euclidean_pearson
      value: 65.60500561965856
    - type: euclidean_spearman
      value: 60.08755668871506
    - type: manhattan_pearson
      value: 66.26288910017067
    - type: manhattan_spearman
      value: 60.258444365922024
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 62.63440086574824
    - type: cos_sim_spearman
      value: 57.22862459567004
    - type: euclidean_pearson
      value: 61.33135391980671
    - type: euclidean_spearman
      value: 57.2287396395971
    - type: manhattan_pearson
      value: 63.538353299276665
    - type: manhattan_spearman
      value: 59.31604272847601
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 66.99729287299299
    - type: cos_sim_spearman
      value: 69.20264774948375
    - type: euclidean_pearson
      value: 68.83879433164682
    - type: euclidean_spearman
      value: 69.20257380705361
    - type: manhattan_pearson
      value: 68.82235273988779
    - type: manhattan_spearman
      value: 69.12895594376502
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 63.43542239265359
    - type: cos_sim_spearman
      value: 62.75650954855537
    - type: euclidean_pearson
      value: 63.87500752354951
    - type: euclidean_spearman
      value: 62.75647357698498
    - type: manhattan_pearson
      value: 64.30854220561612
    - type: manhattan_spearman
      value: 63.221533112975756
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 70.3113558570832
    - type: cos_sim_spearman
      value: 72.99345938388264
    - type: euclidean_pearson
      value: 72.46131589134022
    - type: euclidean_spearman
      value: 72.99345776180552
    - type: manhattan_pearson
      value: 72.98365443642383
    - type: manhattan_spearman
      value: 73.52773752441843
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 59.508816955942734
    - type: cos_sim_spearman
      value: 64.16476610475141
    - type: euclidean_pearson
      value: 63.49096301327081
    - type: euclidean_spearman
      value: 64.16559631894077
    - type: manhattan_pearson
      value: 63.756149631030304
    - type: manhattan_spearman
      value: 64.26840399223137
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 64.67239774871666
    - type: cos_sim_spearman
      value: 70.22507344222888
    - type: euclidean_pearson
      value: 68.64452662209249
    - type: euclidean_spearman
      value: 70.22507344222888
    - type: manhattan_pearson
      value: 69.50174122996509
    - type: manhattan_spearman
      value: 70.95654177971161
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 37.43959179391427
    - type: cos_sim_spearman
      value: 52.14129987772493
    - type: euclidean_pearson
      value: 45.75262378066364
    - type: euclidean_spearman
      value: 52.14129987772493
    - type: manhattan_pearson
      value: 46.45004553263895
    - type: manhattan_spearman
      value: 52.6763345299464
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 57.22043463404035
    - type: cos_sim_spearman
      value: 56.454056579980794
    - type: euclidean_pearson
      value: 58.48035388318515
    - type: euclidean_spearman
      value: 56.454075070192246
    - type: manhattan_pearson
      value: 59.27047962449207
    - type: manhattan_spearman
      value: 57.15898290207574
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 58.73824844121353
    - type: mrr
      value: 83.14232245604795
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 28.278
    - type: map_at_10
      value: 38.059
    - type: map_at_100
      value: 39.017
    - type: map_at_1000
      value: 39.086999999999996
    - type: map_at_3
      value: 35.157
    - type: map_at_5
      value: 36.321
    - type: mrr_at_1
      value: 28.999999999999996
    - type: mrr_at_10
      value: 38.842
    - type: mrr_at_100
      value: 39.683
    - type: mrr_at_1000
      value: 39.739999999999995
    - type: mrr_at_3
      value: 36.111
    - type: mrr_at_5
      value: 37.128
    - type: ndcg_at_1
      value: 28.999999999999996
    - type: ndcg_at_10
      value: 43.833
    - type: ndcg_at_100
      value: 48.478
    - type: ndcg_at_1000
      value: 50.287000000000006
    - type: ndcg_at_3
      value: 37.649
    - type: ndcg_at_5
      value: 39.635
    - type: precision_at_1
      value: 28.999999999999996
    - type: precision_at_10
      value: 6.633
    - type: precision_at_100
      value: 0.923
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 15.556000000000001
    - type: precision_at_5
      value: 10.467
    - type: recall_at_1
      value: 28.278
    - type: recall_at_10
      value: 61.306000000000004
    - type: recall_at_100
      value: 82.794
    - type: recall_at_1000
      value: 96.68299999999999
    - type: recall_at_3
      value: 43.722
    - type: recall_at_5
      value: 48.528
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.45049504950495
    - type: cos_sim_ap
      value: 72.53477415157148
    - type: cos_sim_f1
      value: 69.14778856526429
    - type: cos_sim_precision
      value: 75.05854800936767
    - type: cos_sim_recall
      value: 64.1
    - type: dot_accuracy
      value: 99.45049504950495
    - type: dot_ap
      value: 72.53477415157148
    - type: dot_f1
      value: 69.14778856526429
    - type: dot_precision
      value: 75.05854800936767
    - type: dot_recall
      value: 64.1
    - type: euclidean_accuracy
      value: 99.45049504950495
    - type: euclidean_ap
      value: 72.53477415157148
    - type: euclidean_f1
      value: 69.14778856526429
    - type: euclidean_precision
      value: 75.05854800936767
    - type: euclidean_recall
      value: 64.1
    - type: manhattan_accuracy
      value: 99.5039603960396
    - type: manhattan_ap
      value: 76.7082832888717
    - type: manhattan_f1
      value: 72.13822894168467
    - type: manhattan_precision
      value: 78.40375586854461
    - type: manhattan_recall
      value: 66.8
    - type: max_accuracy
      value: 99.5039603960396
    - type: max_ap
      value: 76.7082832888717
    - type: max_f1
      value: 72.13822894168467
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 41.45680507027172
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.745763504328544
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 38.69439810906393
    - type: mrr
      value: 38.741538281979466
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.143974591712965
    - type: cos_sim_spearman
      value: 30.326736776986202
    - type: dot_pearson
      value: 31.14397457870977
    - type: dot_spearman
      value: 30.338990239435514
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.1280000000000001
    - type: map_at_10
      value: 3.533
    - type: map_at_100
      value: 6.584
    - type: map_at_1000
      value: 7.983
    - type: map_at_3
      value: 2.1399999999999997
    - type: map_at_5
      value: 2.825
    - type: mrr_at_1
      value: 20.408
    - type: mrr_at_10
      value: 29.62
    - type: mrr_at_100
      value: 31.746000000000002
    - type: mrr_at_1000
      value: 31.767
    - type: mrr_at_3
      value: 25.169999999999998
    - type: mrr_at_5
      value: 28.231
    - type: ndcg_at_1
      value: 18.367
    - type: ndcg_at_10
      value: 11.927
    - type: ndcg_at_100
      value: 21.722
    - type: ndcg_at_1000
      value: 34.343
    - type: ndcg_at_3
      value: 14.097999999999999
    - type: ndcg_at_5
      value: 13.475000000000001
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 11.224
    - type: precision_at_100
      value: 5.3469999999999995
    - type: precision_at_1000
      value: 1.316
    - type: precision_at_3
      value: 14.285999999999998
    - type: precision_at_5
      value: 14.285999999999998
    - type: recall_at_1
      value: 1.1280000000000001
    - type: recall_at_10
      value: 7.104000000000001
    - type: recall_at_100
      value: 32.883
    - type: recall_at_1000
      value: 71.486
    - type: recall_at_3
      value: 2.828
    - type: recall_at_5
      value: 4.619
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.7376
    - type: ap
      value: 13.162929064348921
    - type: f1
      value: 53.248619291006186
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 51.479909451046964
    - type: f1
      value: 51.59328707931989
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 28.331197809553117
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.19449245991535
    - type: cos_sim_ap
      value: 53.831102581174925
    - type: cos_sim_f1
      value: 52.64428881912582
    - type: cos_sim_precision
      value: 48.53072128227961
    - type: cos_sim_recall
      value: 57.519788918205805
    - type: dot_accuracy
      value: 81.19449245991535
    - type: dot_ap
      value: 53.831102581174925
    - type: dot_f1
      value: 52.64428881912582
    - type: dot_precision
      value: 48.53072128227961
    - type: dot_recall
      value: 57.519788918205805
    - type: euclidean_accuracy
      value: 81.19449245991535
    - type: euclidean_ap
      value: 53.831102581174925
    - type: euclidean_f1
      value: 52.64428881912582
    - type: euclidean_precision
      value: 48.53072128227961
    - type: euclidean_recall
      value: 57.519788918205805
    - type: manhattan_accuracy
      value: 81.06932109435536
    - type: manhattan_ap
      value: 53.40351129456407
    - type: manhattan_f1
      value: 51.96813495782568
    - type: manhattan_precision
      value: 46.73409186683523
    - type: manhattan_recall
      value: 58.52242744063324
    - type: max_accuracy
      value: 81.19449245991535
    - type: max_ap
      value: 53.831102581174925
    - type: max_f1
      value: 52.64428881912582
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 83.53708231458843
    - type: cos_sim_ap
      value: 70.93155202991022
    - type: cos_sim_f1
      value: 63.92679900744417
    - type: cos_sim_precision
      value: 64.38612933458295
    - type: cos_sim_recall
      value: 63.47397597782568
    - type: dot_accuracy
      value: 83.53708231458843
    - type: dot_ap
      value: 70.93155188455967
    - type: dot_f1
      value: 63.92679900744417
    - type: dot_precision
      value: 64.38612933458295
    - type: dot_recall
      value: 63.47397597782568
    - type: euclidean_accuracy
      value: 83.53708231458843
    - type: euclidean_ap
      value: 70.93155157551972
    - type: euclidean_f1
      value: 63.92679900744417
    - type: euclidean_precision
      value: 64.38612933458295
    - type: euclidean_recall
      value: 63.47397597782568
    - type: manhattan_accuracy
      value: 83.77187875965382
    - type: manhattan_ap
      value: 71.99220572523825
    - type: manhattan_f1
      value: 65.04077318030807
    - type: manhattan_precision
      value: 63.80740740740741
    - type: manhattan_recall
      value: 66.32275947028026
    - type: max_accuracy
      value: 83.77187875965382
    - type: max_ap
      value: 71.99220572523825
    - type: max_f1
      value: 65.04077318030807
---
