mteb model-index region:us
---
tags:
- mteb
model-index:
- name: gte-base-en-v1.5_embs_nofiltering_sortlenTrue_phrase2sent_512_15epoch__adam0.001_accum1_best_epoch_2611200_bs128_result
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.02985074626866
    - type: ap
      value: 38.2391132433526
    - type: f1
      value: 69.06974168824816
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 74.00564999999999
    - type: ap
      value: 68.12255640587608
    - type: f1
      value: 73.88644324572483
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 39.46000000000001
    - type: f1
      value: 38.77579430134605
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.337
    - type: map_at_10
      value: 36.104
    - type: map_at_100
      value: 37.363
    - type: map_at_1000
      value: 37.38
    - type: map_at_3
      value: 31.46
    - type: map_at_5
      value: 33.861000000000004
    - type: mrr_at_1
      value: 22.119
    - type: mrr_at_10
      value: 36.379
    - type: mrr_at_100
      value: 37.644
    - type: mrr_at_1000
      value: 37.662
    - type: mrr_at_3
      value: 31.745
    - type: mrr_at_5
      value: 34.12
    - type: ndcg_at_1
      value: 21.337
    - type: ndcg_at_10
      value: 44.557
    - type: ndcg_at_100
      value: 50.072
    - type: ndcg_at_1000
      value: 50.499
    - type: ndcg_at_3
      value: 34.794000000000004
    - type: ndcg_at_5
      value: 39.125
    - type: precision_at_1
      value: 21.337
    - type: precision_at_10
      value: 7.176
    - type: precision_at_100
      value: 0.962
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 14.817
    - type: precision_at_5
      value: 10.996
    - type: recall_at_1
      value: 21.337
    - type: recall_at_10
      value: 71.764
    - type: recall_at_100
      value: 96.23
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 44.452000000000005
    - type: recall_at_5
      value: 54.979
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 38.36878876355172
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 28.19433994044647
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.16001797554904
    - type: mrr
      value: 67.81130457723256
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.1086837226076
    - type: cos_sim_spearman
      value: 80.60966807127197
    - type: euclidean_pearson
      value: 80.73535719827952
    - type: euclidean_spearman
      value: 80.60966807127197
    - type: manhattan_pearson
      value: 79.10544477221981
    - type: manhattan_spearman
      value: 79.59759681777079
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.1525974025974
    - type: f1
      value: 74.45181803662257
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.568758810321945
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.645931603960374
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.36
    - type: map_at_10
      value: 29.034
    - type: map_at_100
      value: 30.197000000000003
    - type: map_at_1000
      value: 30.36
    - type: map_at_3
      value: 26.334999999999997
    - type: map_at_5
      value: 27.894999999999996
    - type: mrr_at_1
      value: 27.325
    - type: mrr_at_10
      value: 34.975
    - type: mrr_at_100
      value: 35.787
    - type: mrr_at_1000
      value: 35.864000000000004
    - type: mrr_at_3
      value: 32.761
    - type: mrr_at_5
      value: 34.083999999999996
    - type: ndcg_at_1
      value: 27.325
    - type: ndcg_at_10
      value: 34.302
    - type: ndcg_at_100
      value: 39.35
    - type: ndcg_at_1000
      value: 42.516999999999996
    - type: ndcg_at_3
      value: 30.336000000000002
    - type: ndcg_at_5
      value: 32.234
    - type: precision_at_1
      value: 27.325
    - type: precision_at_10
      value: 6.694999999999999
    - type: precision_at_100
      value: 1.157
    - type: precision_at_1000
      value: 0.17500000000000002
    - type: precision_at_3
      value: 14.926
    - type: precision_at_5
      value: 11.044
    - type: recall_at_1
      value: 21.36
    - type: recall_at_10
      value: 43.64
    - type: recall_at_100
      value: 66.219
    - type: recall_at_1000
      value: 87.675
    - type: recall_at_3
      value: 31.34
    - type: recall_at_5
      value: 36.896
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 19.008
    - type: map_at_10
      value: 25.762
    - type: map_at_100
      value: 26.819
    - type: map_at_1000
      value: 26.944000000000003
    - type: map_at_3
      value: 23.688000000000002
    - type: map_at_5
      value: 24.844
    - type: mrr_at_1
      value: 24.204
    - type: mrr_at_10
      value: 30.325999999999997
    - type: mrr_at_100
      value: 31.151
    - type: mrr_at_1000
      value: 31.22
    - type: mrr_at_3
      value: 28.311999999999998
    - type: mrr_at_5
      value: 29.424
    - type: ndcg_at_1
      value: 24.204
    - type: ndcg_at_10
      value: 30.020999999999997
    - type: ndcg_at_100
      value: 34.632000000000005
    - type: ndcg_at_1000
      value: 37.462
    - type: ndcg_at_3
      value: 26.607999999999997
    - type: ndcg_at_5
      value: 28.105999999999998
    - type: precision_at_1
      value: 24.204
    - type: precision_at_10
      value: 5.624
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_3
      value: 12.887
    - type: precision_at_5
      value: 9.159
    - type: recall_at_1
      value: 19.008
    - type: recall_at_10
      value: 38.156
    - type: recall_at_100
      value: 58.158
    - type: recall_at_1000
      value: 77.471
    - type: recall_at_3
      value: 27.964
    - type: recall_at_5
      value: 32.221
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.833999999999996
    - type: map_at_10
      value: 36.896
    - type: map_at_100
      value: 38.002
    - type: map_at_1000
      value: 38.088
    - type: map_at_3
      value: 34.283
    - type: map_at_5
      value: 35.754999999999995
    - type: mrr_at_1
      value: 32.351
    - type: mrr_at_10
      value: 40.275
    - type: mrr_at_100
      value: 41.152
    - type: mrr_at_1000
      value: 41.204
    - type: mrr_at_3
      value: 37.973
    - type: mrr_at_5
      value: 39.242
    - type: ndcg_at_1
      value: 32.351
    - type: ndcg_at_10
      value: 41.867
    - type: ndcg_at_100
      value: 47.073
    - type: ndcg_at_1000
      value: 49.125
    - type: ndcg_at_3
      value: 37.129
    - type: ndcg_at_5
      value: 39.361000000000004
    - type: precision_at_1
      value: 32.351
    - type: precision_at_10
      value: 6.765000000000001
    - type: precision_at_100
      value: 1.0330000000000001
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 16.489
    - type: precision_at_5
      value: 11.398
    - type: recall_at_1
      value: 27.833999999999996
    - type: recall_at_10
      value: 53.668000000000006
    - type: recall_at_100
      value: 77.114
    - type: recall_at_1000
      value: 92.131
    - type: recall_at_3
      value: 40.745
    - type: recall_at_5
      value: 46.375
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.863
    - type: map_at_10
      value: 17.881
    - type: map_at_100
      value: 18.742
    - type: map_at_1000
      value: 18.86
    - type: map_at_3
      value: 16.485
    - type: map_at_5
      value: 17.262
    - type: mrr_at_1
      value: 13.898
    - type: mrr_at_10
      value: 19.152
    - type: mrr_at_100
      value: 20.007
    - type: mrr_at_1000
      value: 20.116
    - type: mrr_at_3
      value: 17.759
    - type: mrr_at_5
      value: 18.544
    - type: ndcg_at_1
      value: 13.898
    - type: ndcg_at_10
      value: 20.818
    - type: ndcg_at_100
      value: 25.342
    - type: ndcg_at_1000
      value: 28.895
    - type: ndcg_at_3
      value: 18.034
    - type: ndcg_at_5
      value: 19.367
    - type: precision_at_1
      value: 13.898
    - type: precision_at_10
      value: 3.254
    - type: precision_at_100
      value: 0.582
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.8340000000000005
    - type: precision_at_5
      value: 5.446
    - type: recall_at_1
      value: 12.863
    - type: recall_at_10
      value: 28.636
    - type: recall_at_100
      value: 50.112
    - type: recall_at_1000
      value: 77.828
    - type: recall_at_3
      value: 21.087
    - type: recall_at_5
      value: 24.307000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.8020000000000005
    - type: map_at_10
      value: 11.673
    - type: map_at_100
      value: 12.462
    - type: map_at_1000
      value: 12.589
    - type: map_at_3
      value: 10.035
    - type: map_at_5
      value: 10.699
    - type: mrr_at_1
      value: 9.826
    - type: mrr_at_10
      value: 14.248
    - type: mrr_at_100
      value: 15.057
    - type: mrr_at_1000
      value: 15.156
    - type: mrr_at_3
      value: 12.5
    - type: mrr_at_5
      value: 13.221
    - type: ndcg_at_1
      value: 9.826
    - type: ndcg_at_10
      value: 14.818999999999999
    - type: ndcg_at_100
      value: 19.309
    - type: ndcg_at_1000
      value: 22.954
    - type: ndcg_at_3
      value: 11.535
    - type: ndcg_at_5
      value: 12.577
    - type: precision_at_1
      value: 9.826
    - type: precision_at_10
      value: 2.923
    - type: precision_at_100
      value: 0.618
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 5.5969999999999995
    - type: precision_at_5
      value: 4.08
    - type: recall_at_1
      value: 7.8020000000000005
    - type: recall_at_10
      value: 22.141
    - type: recall_at_100
      value: 42.653999999999996
    - type: recall_at_1000
      value: 70.02199999999999
    - type: recall_at_3
      value: 13.020000000000001
    - type: recall_at_5
      value: 15.645999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.532
    - type: map_at_10
      value: 24.692
    - type: map_at_100
      value: 26.023000000000003
    - type: map_at_1000
      value: 26.165
    - type: map_at_3
      value: 22.522000000000002
    - type: map_at_5
      value: 23.694000000000003
    - type: mrr_at_1
      value: 22.618
    - type: mrr_at_10
      value: 29.334
    - type: mrr_at_100
      value: 30.348999999999997
    - type: mrr_at_1000
      value: 30.435000000000002
    - type: mrr_at_3
      value: 26.997
    - type: mrr_at_5
      value: 28.282
    - type: ndcg_at_1
      value: 22.618
    - type: ndcg_at_10
      value: 29.188
    - type: ndcg_at_100
      value: 35.213
    - type: ndcg_at_1000
      value: 38.471
    - type: ndcg_at_3
      value: 25.313999999999997
    - type: ndcg_at_5
      value: 27.057
    - type: precision_at_1
      value: 22.618
    - type: precision_at_10
      value: 5.38
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 11.741999999999999
    - type: precision_at_5
      value: 8.662
    - type: recall_at_1
      value: 18.532
    - type: recall_at_10
      value: 38.164
    - type: recall_at_100
      value: 64.197
    - type: recall_at_1000
      value: 86.75399999999999
    - type: recall_at_3
      value: 27.262999999999998
    - type: recall_at_5
      value: 31.651
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 15.257000000000001
    - type: map_at_10
      value: 20.762
    - type: map_at_100
      value: 21.956999999999997
    - type: map_at_1000
      value: 22.102
    - type: map_at_3
      value: 18.826999999999998
    - type: map_at_5
      value: 19.911
    - type: mrr_at_1
      value: 18.836
    - type: mrr_at_10
      value: 24.484
    - type: mrr_at_100
      value: 25.561
    - type: mrr_at_1000
      value: 25.651000000000003
    - type: mrr_at_3
      value: 22.546
    - type: mrr_at_5
      value: 23.613
    - type: ndcg_at_1
      value: 18.836
    - type: ndcg_at_10
      value: 24.465999999999998
    - type: ndcg_at_100
      value: 30.337999999999997
    - type: ndcg_at_1000
      value: 33.775
    - type: ndcg_at_3
      value: 21.029
    - type: ndcg_at_5
      value: 22.576
    - type: precision_at_1
      value: 18.836
    - type: precision_at_10
      value: 4.5089999999999995
    - type: precision_at_100
      value: 0.895
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 9.893
    - type: precision_at_5
      value: 7.146
    - type: recall_at_1
      value: 15.257000000000001
    - type: recall_at_10
      value: 32.062000000000005
    - type: recall_at_100
      value: 57.577
    - type: recall_at_1000
      value: 81.75
    - type: recall_at_3
      value: 22.579
    - type: recall_at_5
      value: 26.613999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 15.333916666666667
    - type: map_at_10
      value: 20.908583333333333
    - type: map_at_100
      value: 21.891333333333332
    - type: map_at_1000
      value: 22.02225
    - type: map_at_3
      value: 19.053833333333333
    - type: map_at_5
      value: 20.053916666666666
    - type: mrr_at_1
      value: 18.5485
    - type: mrr_at_10
      value: 24.15733333333333
    - type: mrr_at_100
      value: 25.01325
    - type: mrr_at_1000
      value: 25.101000000000003
    - type: mrr_at_3
      value: 22.34708333333333
    - type: mrr_at_5
      value: 23.317833333333336
    - type: ndcg_at_1
      value: 18.5485
    - type: ndcg_at_10
      value: 24.614
    - type: ndcg_at_100
      value: 29.431166666666662
    - type: ndcg_at_1000
      value: 32.6675
    - type: ndcg_at_3
      value: 21.285083333333336
    - type: ndcg_at_5
      value: 22.751416666666664
    - type: precision_at_1
      value: 18.5485
    - type: precision_at_10
      value: 4.4013333333333335
    - type: precision_at_100
      value: 0.8160000000000001
    - type: precision_at_1000
      value: 0.12825
    - type: precision_at_3
      value: 9.847916666666666
    - type: precision_at_5
      value: 7.069166666666668
    - type: recall_at_1
      value: 15.333916666666667
    - type: recall_at_10
      value: 32.5695
    - type: recall_at_100
      value: 54.50375
    - type: recall_at_1000
      value: 78.02300000000001
    - type: recall_at_3
      value: 23.115000000000002
    - type: recall_at_5
      value: 26.968416666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.745
    - type: map_at_10
      value: 16.406000000000002
    - type: map_at_100
      value: 17.157
    - type: map_at_1000
      value: 17.249
    - type: map_at_3
      value: 14.835999999999999
    - type: map_at_5
      value: 15.803
    - type: mrr_at_1
      value: 13.804
    - type: mrr_at_10
      value: 18.55
    - type: mrr_at_100
      value: 19.306
    - type: mrr_at_1000
      value: 19.38
    - type: mrr_at_3
      value: 17.05
    - type: mrr_at_5
      value: 17.947
    - type: ndcg_at_1
      value: 13.804
    - type: ndcg_at_10
      value: 19.339000000000002
    - type: ndcg_at_100
      value: 23.624000000000002
    - type: ndcg_at_1000
      value: 26.301999999999996
    - type: ndcg_at_3
      value: 16.454
    - type: ndcg_at_5
      value: 17.999000000000002
    - type: precision_at_1
      value: 13.804
    - type: precision_at_10
      value: 3.282
    - type: precision_at_100
      value: 0.598
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 7.413
    - type: precision_at_5
      value: 5.428999999999999
    - type: recall_at_1
      value: 11.745
    - type: recall_at_10
      value: 26.255
    - type: recall_at_100
      value: 46.888000000000005
    - type: recall_at_1000
      value: 67.131
    - type: recall_at_3
      value: 18.434
    - type: recall_at_5
      value: 22.328
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.119
    - type: map_at_10
      value: 11.944
    - type: map_at_100
      value: 12.647
    - type: map_at_1000
      value: 12.770000000000001
    - type: map_at_3
      value: 10.612
    - type: map_at_5
      value: 11.292
    - type: mrr_at_1
      value: 10.22
    - type: mrr_at_10
      value: 14.496
    - type: mrr_at_100
      value: 15.18
    - type: mrr_at_1000
      value: 15.279000000000002
    - type: mrr_at_3
      value: 12.979
    - type: mrr_at_5
      value: 13.755
    - type: ndcg_at_1
      value: 10.22
    - type: ndcg_at_10
      value: 14.687
    - type: ndcg_at_100
      value: 18.543000000000003
    - type: ndcg_at_1000
      value: 22.099
    - type: ndcg_at_3
      value: 12.076
    - type: ndcg_at_5
      value: 13.161999999999999
    - type: precision_at_1
      value: 10.22
    - type: precision_at_10
      value: 2.822
    - type: precision_at_100
      value: 0.565
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 5.781
    - type: precision_at_5
      value: 4.301
    - type: recall_at_1
      value: 8.119
    - type: recall_at_10
      value: 20.527
    - type: recall_at_100
      value: 38.719
    - type: recall_at_1000
      value: 65.16300000000001
    - type: recall_at_3
      value: 13.275
    - type: recall_at_5
      value: 15.998999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.334999999999999
    - type: map_at_10
      value: 18.194
    - type: map_at_100
      value: 19.049
    - type: map_at_1000
      value: 19.17
    - type: map_at_3
      value: 16.625
    - type: map_at_5
      value: 17.509
    - type: mrr_at_1
      value: 16.231
    - type: mrr_at_10
      value: 21.308
    - type: mrr_at_100
      value: 22.154
    - type: mrr_at_1000
      value: 22.25
    - type: mrr_at_3
      value: 19.761
    - type: mrr_at_5
      value: 20.567
    - type: ndcg_at_1
      value: 16.231
    - type: ndcg_at_10
      value: 21.525
    - type: ndcg_at_100
      value: 26.008
    - type: ndcg_at_1000
      value: 29.351
    - type: ndcg_at_3
      value: 18.54
    - type: ndcg_at_5
      value: 19.916
    - type: precision_at_1
      value: 16.231
    - type: precision_at_10
      value: 3.6470000000000002
    - type: precision_at_100
      value: 0.655
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 8.488999999999999
    - type: precision_at_5
      value: 6.007
    - type: recall_at_1
      value: 13.334999999999999
    - type: recall_at_10
      value: 28.804999999999996
    - type: recall_at_100
      value: 49.303000000000004
    - type: recall_at_1000
      value: 73.95
    - type: recall_at_3
      value: 20.531
    - type: recall_at_5
      value: 24.067
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 16.002
    - type: map_at_10
      value: 21.282
    - type: map_at_100
      value: 22.518
    - type: map_at_1000
      value: 22.728
    - type: map_at_3
      value: 19.463
    - type: map_at_5
      value: 20.314
    - type: mrr_at_1
      value: 19.96
    - type: mrr_at_10
      value: 25.084
    - type: mrr_at_100
      value: 26.028000000000002
    - type: mrr_at_1000
      value: 26.119999999999997
    - type: mrr_at_3
      value: 23.352999999999998
    - type: mrr_at_5
      value: 24.203
    - type: ndcg_at_1
      value: 19.96
    - type: ndcg_at_10
      value: 25.275
    - type: ndcg_at_100
      value: 30.574
    - type: ndcg_at_1000
      value: 34.359
    - type: ndcg_at_3
      value: 22.281000000000002
    - type: ndcg_at_5
      value: 23.32
    - type: precision_at_1
      value: 19.96
    - type: precision_at_10
      value: 4.920999999999999
    - type: precision_at_100
      value: 1.1320000000000001
    - type: precision_at_1000
      value: 0.20400000000000001
    - type: precision_at_3
      value: 10.408000000000001
    - type: precision_at_5
      value: 7.352
    - type: recall_at_1
      value: 16.002
    - type: recall_at_10
      value: 32.452
    - type: recall_at_100
      value: 57.297
    - type: recall_at_1000
      value: 83.332
    - type: recall_at_3
      value: 23.101
    - type: recall_at_5
      value: 26.395999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.15
    - type: map_at_10
      value: 16.377
    - type: map_at_100
      value: 17.122999999999998
    - type: map_at_1000
      value: 17.241999999999997
    - type: map_at_3
      value: 14.935
    - type: map_at_5
      value: 15.669
    - type: mrr_at_1
      value: 13.309000000000001
    - type: mrr_at_10
      value: 17.656
    - type: mrr_at_100
      value: 18.427
    - type: mrr_at_1000
      value: 18.537
    - type: mrr_at_3
      value: 16.174
    - type: mrr_at_5
      value: 16.932
    - type: ndcg_at_1
      value: 13.309000000000001
    - type: ndcg_at_10
      value: 19.061
    - type: ndcg_at_100
      value: 23.168
    - type: ndcg_at_1000
      value: 26.700000000000003
    - type: ndcg_at_3
      value: 16.085
    - type: ndcg_at_5
      value: 17.342
    - type: precision_at_1
      value: 13.309000000000001
    - type: precision_at_10
      value: 2.994
    - type: precision_at_100
      value: 0.545
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 6.715999999999999
    - type: precision_at_5
      value: 4.806
    - type: recall_at_1
      value: 12.15
    - type: recall_at_10
      value: 26.328000000000003
    - type: recall_at_100
      value: 45.806999999999995
    - type: recall_at_1000
      value: 73.06899999999999
    - type: recall_at_3
      value: 18.041
    - type: recall_at_5
      value: 21.121000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.675999999999999
    - type: map_at_10
      value: 13.600000000000001
    - type: map_at_100
      value: 15.287999999999998
    - type: map_at_1000
      value: 15.508
    - type: map_at_3
      value: 11.256
    - type: map_at_5
      value: 12.312
    - type: mrr_at_1
      value: 17.459
    - type: mrr_at_10
      value: 27.166
    - type: mrr_at_100
      value: 28.406
    - type: mrr_at_1000
      value: 28.464
    - type: mrr_at_3
      value: 23.931
    - type: mrr_at_5
      value: 25.66
    - type: ndcg_at_1
      value: 17.459
    - type: ndcg_at_10
      value: 20.146
    - type: ndcg_at_100
      value: 27.625
    - type: ndcg_at_1000
      value: 31.819999999999997
    - type: ndcg_at_3
      value: 15.870999999999999
    - type: ndcg_at_5
      value: 17.158
    - type: precision_at_1
      value: 17.459
    - type: precision_at_10
      value: 6.638
    - type: precision_at_100
      value: 1.4569999999999999
    - type: precision_at_1000
      value: 0.22300000000000003
    - type: precision_at_3
      value: 12.074
    - type: precision_at_5
      value: 9.407
    - type: recall_at_1
      value: 7.675999999999999
    - type: recall_at_10
      value: 25.267
    - type: recall_at_100
      value: 51.69200000000001
    - type: recall_at_1000
      value: 75.58
    - type: recall_at_3
      value: 14.901
    - type: recall_at_5
      value: 18.543000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.424
    - type: map_at_10
      value: 10.278
    - type: map_at_100
      value: 14.516000000000002
    - type: map_at_1000
      value: 15.584999999999999
    - type: map_at_3
      value: 7.179
    - type: map_at_5
      value: 8.556
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 52.653000000000006
    - type: mrr_at_100
      value: 53.33599999999999
    - type: mrr_at_1000
      value: 53.364999999999995
    - type: mrr_at_3
      value: 50.542
    - type: mrr_at_5
      value: 51.803999999999995
    - type: ndcg_at_1
      value: 31.624999999999996
    - type: ndcg_at_10
      value: 25.167
    - type: ndcg_at_100
      value: 28.766000000000002
    - type: ndcg_at_1000
      value: 35.959
    - type: ndcg_at_3
      value: 27.807
    - type: ndcg_at_5
      value: 26.569
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 22.5
    - type: precision_at_100
      value: 7.295
    - type: precision_at_1000
      value: 1.543
    - type: precision_at_3
      value: 33.5
    - type: precision_at_5
      value: 29.099999999999998
    - type: recall_at_1
      value: 4.424
    - type: recall_at_10
      value: 15.359
    - type: recall_at_100
      value: 35.99
    - type: recall_at_1000
      value: 60.707
    - type: recall_at_3
      value: 8.803999999999998
    - type: recall_at_5
      value: 11.349
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 48.99
    - type: f1
      value: 44.72383731785718
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 17.753
    - type: map_at_10
      value: 26.762999999999998
    - type: map_at_100
      value: 27.773999999999997
    - type: map_at_1000
      value: 27.845
    - type: map_at_3
      value: 24.096
    - type: map_at_5
      value: 25.6
    - type: mrr_at_1
      value: 19.022
    - type: mrr_at_10
      value: 28.46
    - type: mrr_at_100
      value: 29.462
    - type: mrr_at_1000
      value: 29.520999999999997
    - type: mrr_at_3
      value: 25.679999999999996
    - type: mrr_at_5
      value: 27.272999999999996
    - type: ndcg_at_1
      value: 19.022
    - type: ndcg_at_10
      value: 32.063
    - type: ndcg_at_100
      value: 37.169999999999995
    - type: ndcg_at_1000
      value: 39.048
    - type: ndcg_at_3
      value: 26.558999999999997
    - type: ndcg_at_5
      value: 29.266
    - type: precision_at_1
      value: 19.022
    - type: precision_at_10
      value: 5.119
    - type: precision_at_100
      value: 0.786
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 11.571
    - type: precision_at_5
      value: 8.368
    - type: recall_at_1
      value: 17.753
    - type: recall_at_10
      value: 47.061
    - type: recall_at_100
      value: 70.75200000000001
    - type: recall_at_1000
      value: 85.134
    - type: recall_at_3
      value: 32.049
    - type: recall_at_5
      value: 38.556000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.845
    - type: map_at_10
      value: 11.806999999999999
    - type: map_at_100
      value: 13.104
    - type: map_at_1000
      value: 13.317
    - type: map_at_3
      value: 9.746
    - type: map_at_5
      value: 10.806000000000001
    - type: mrr_at_1
      value: 13.889000000000001
    - type: mrr_at_10
      value: 20.456
    - type: mrr_at_100
      value: 21.572
    - type: mrr_at_1000
      value: 21.666
    - type: mrr_at_3
      value: 18.184
    - type: mrr_at_5
      value: 19.387999999999998
    - type: ndcg_at_1
      value: 13.889000000000001
    - type: ndcg_at_10
      value: 16.552
    - type: ndcg_at_100
      value: 22.817999999999998
    - type: ndcg_at_1000
      value: 27.401999999999997
    - type: ndcg_at_3
      value: 13.527000000000001
    - type: ndcg_at_5
      value: 14.6
    - type: precision_at_1
      value: 13.889000000000001
    - type: precision_at_10
      value: 4.984999999999999
    - type: precision_at_100
      value: 1.097
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 9.208
    - type: precision_at_5
      value: 7.13
    - type: recall_at_1
      value: 6.845
    - type: recall_at_10
      value: 22.012999999999998
    - type: recall_at_100
      value: 46.75
    - type: recall_at_1000
      value: 74.945
    - type: recall_at_3
      value: 12.352
    - type: recall_at_5
      value: 16.217000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 18.886
    - type: map_at_10
      value: 26.729999999999997
    - type: map_at_100
      value: 27.732
    - type: map_at_1000
      value: 27.85
    - type: map_at_3
      value: 24.57
    - type: map_at_5
      value: 25.774
    - type: mrr_at_1
      value: 37.772
    - type: mrr_at_10
      value: 45.239000000000004
    - type: mrr_at_100
      value: 45.972
    - type: mrr_at_1000
      value: 46.027
    - type: mrr_at_3
      value: 43.279
    - type: mrr_at_5
      value: 44.397
    - type: ndcg_at_1
      value: 37.772
    - type: ndcg_at_10
      value: 33.973
    - type: ndcg_at_100
      value: 38.456
    - type: ndcg_at_1000
      value: 41.178
    - type: ndcg_at_3
      value: 29.988999999999997
    - type: ndcg_at_5
      value: 31.935999999999996
    - type: precision_at_1
      value: 37.772
    - type: precision_at_10
      value: 7.465
    - type: precision_at_100
      value: 1.1039999999999999
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_3
      value: 18.902
    - type: precision_at_5
      value: 12.883
    - type: recall_at_1
      value: 18.886
    - type: recall_at_10
      value: 37.326
    - type: recall_at_100
      value: 55.186
    - type: recall_at_1000
      value: 73.309
    - type: recall_at_3
      value: 28.352
    - type: recall_at_5
      value: 32.208
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 70.6808
    - type: ap
      value: 64.78268083902698
    - type: f1
      value: 70.48410216634053
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.300999999999999
    - type: map_at_10
      value: 11.068999999999999
    - type: map_at_100
      value: 12.0
    - type: map_at_1000
      value: 12.113999999999999
    - type: map_at_3
      value: 9.381
    - type: map_at_5
      value: 10.265
    - type: mrr_at_1
      value: 6.476
    - type: mrr_at_10
      value: 11.357000000000001
    - type: mrr_at_100
      value: 12.293
    - type: mrr_at_1000
      value: 12.403
    - type: mrr_at_3
      value: 9.62
    - type: mrr_at_5
      value: 10.544
    - type: ndcg_at_1
      value: 6.461
    - type: ndcg_at_10
      value: 14.058000000000002
    - type: ndcg_at_100
      value: 19.156000000000002
    - type: ndcg_at_1000
      value: 22.570999999999998
    - type: ndcg_at_3
      value: 10.475
    - type: ndcg_at_5
      value: 12.092
    - type: precision_at_1
      value: 6.461
    - type: precision_at_10
      value: 2.431
    - type: precision_at_100
      value: 0.508
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 4.6080000000000005
    - type: precision_at_5
      value: 3.5900000000000003
    - type: recall_at_1
      value: 6.300999999999999
    - type: recall_at_10
      value: 23.378
    - type: recall_at_100
      value: 48.258
    - type: recall_at_1000
      value: 75.652
    - type: recall_at_3
      value: 13.422
    - type: recall_at_5
      value: 17.316000000000003
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.34290925672595
    - type: f1
      value: 90.45651851550997
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 63.57045143638851
    - type: f1
      value: 44.02606500037181
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.63214525891057
    - type: f1
      value: 63.33629303043603
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.65635507733691
    - type: f1
      value: 71.52506282204605
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.593804768886113
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.41249151566158
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.0983658178549
    - type: mrr
      value: 32.18857446274346
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.79
    - type: map_at_10
      value: 9.095
    - type: map_at_100
      value: 11.738999999999999
    - type: map_at_1000
      value: 13.203000000000001
    - type: map_at_3
      value: 6.68
    - type: map_at_5
      value: 7.924
    - type: mrr_at_1
      value: 37.461
    - type: mrr_at_10
      value: 46.283
    - type: mrr_at_100
      value: 46.983999999999995
    - type: mrr_at_1000
      value: 47.046
    - type: mrr_at_3
      value: 43.55
    - type: mrr_at_5
      value: 45.268
    - type: ndcg_at_1
      value: 35.604
    - type: ndcg_at_10
      value: 27.249000000000002
    - type: ndcg_at_100
      value: 26.215
    - type: ndcg_at_1000
      value: 35.867
    - type: ndcg_at_3
      value: 30.330000000000002
    - type: ndcg_at_5
      value: 29.574
    - type: precision_at_1
      value: 37.152
    - type: precision_at_10
      value: 20.031
    - type: precision_at_100
      value: 7.217
    - type: precision_at_1000
      value: 2.072
    - type: precision_at_3
      value: 27.761000000000003
    - type: precision_at_5
      value: 25.448999999999998
    - type: recall_at_1
      value: 4.79
    - type: recall_at_10
      value: 13.197000000000001
    - type: recall_at_100
      value: 28.816999999999997
    - type: recall_at_1000
      value: 63.010999999999996
    - type: recall_at_3
      value: 7.53
    - type: recall_at_5
      value: 10.234
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.345
    - type: map_at_10
      value: 16.655
    - type: map_at_100
      value: 17.991
    - type: map_at_1000
      value: 18.093999999999998
    - type: map_at_3
      value: 13.825000000000001
    - type: map_at_5
      value: 15.445
    - type: mrr_at_1
      value: 10.834000000000001
    - type: mrr_at_10
      value: 18.533
    - type: mrr_at_100
      value: 19.750999999999998
    - type: mrr_at_1000
      value: 19.837
    - type: mrr_at_3
      value: 15.623999999999999
    - type: mrr_at_5
      value: 17.307
    - type: ndcg_at_1
      value: 10.834000000000001
    - type: ndcg_at_10
      value: 21.503
    - type: ndcg_at_100
      value: 28.141
    - type: ndcg_at_1000
      value: 30.951
    - type: ndcg_at_3
      value: 15.7
    - type: ndcg_at_5
      value: 18.608
    - type: precision_at_1
      value: 10.834000000000001
    - type: precision_at_10
      value: 4.09
    - type: precision_at_100
      value: 0.782
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 7.474
    - type: precision_at_5
      value: 6.089
    - type: recall_at_1
      value: 9.345
    - type: recall_at_10
      value: 34.760000000000005
    - type: recall_at_100
      value: 65.455
    - type: recall_at_1000
      value: 87.008
    - type: recall_at_3
      value: 19.397000000000002
    - type: recall_at_5
      value: 26.205000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.864
    - type: map_at_10
      value: 76.823
    - type: map_at_100
      value: 77.58699999999999
    - type: map_at_1000
      value: 77.619
    - type: map_at_3
      value: 73.834
    - type: map_at_5
      value: 75.703
    - type: mrr_at_1
      value: 73.55000000000001
    - type: mrr_at_10
      value: 81.077
    - type: mrr_at_100
      value: 81.296
    - type: mrr_at_1000
      value: 81.3
    - type: mrr_at_3
      value: 79.647
    - type: mrr_at_5
      value: 80.601
    - type: ndcg_at_1
      value: 73.63
    - type: ndcg_at_10
      value: 81.526
    - type: ndcg_at_100
      value: 83.544
    - type: ndcg_at_1000
      value: 83.86200000000001
    - type: ndcg_at_3
      value: 77.96300000000001
    - type: ndcg_at_5
      value: 79.888
    - type: precision_at_1
      value: 73.63
    - type: precision_at_10
      value: 12.325
    - type: precision_at_100
      value: 1.468
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.857
    - type: precision_at_5
      value: 22.428
    - type: recall_at_1
      value: 63.864
    - type: recall_at_10
      value: 90.537
    - type: recall_at_100
      value: 97.985
    - type: recall_at_1000
      value: 99.679
    - type: recall_at_3
      value: 80.351
    - type: recall_at_5
      value: 85.697
    - type: map_at_1
      value: 2.8979999999999997
    - type: map_at_10
      value: 7.376
    - type: map_at_100
      value: 8.902000000000001
    - type: map_at_1000
      value: 9.174
    - type: map_at_3
      value: 5.47
    - type: map_at_5
      value: 6.432
    - type: mrr_at_1
      value: 14.2
    - type: mrr_at_10
      value: 22.966
    - type: mrr_at_100
      value: 24.117
    - type: mrr_at_1000
      value: 24.209
    - type: mrr_at_3
      value: 20.033
    - type: mrr_at_5
      value: 21.532999999999998
    - type: ndcg_at_1
      value: 14.2
    - type: ndcg_at_10
      value: 13.016
    - type: ndcg_at_100
      value: 19.804
    - type: ndcg_at_1000
      value: 25.251
    - type: ndcg_at_3
      value: 12.395
    - type: ndcg_at_5
      value: 10.793999999999999
    - type: precision_at_1
      value: 14.2
    - type: precision_at_10
      value: 6.800000000000001
    - type: precision_at_100
      value: 1.6709999999999998
    - type: precision_at_1000
      value: 0.298
    - type: precision_at_3
      value: 11.767
    - type: precision_at_5
      value: 9.56
    - type: recall_at_1
      value: 2.8979999999999997
    - type: recall_at_10
      value: 13.753000000000002
    - type: recall_at_100
      value: 33.92
    - type: recall_at_1000
      value: 60.592
    - type: recall_at_3
      value: 7.163
    - type: recall_at_5
      value: 9.678
    - type: map_at_1
      value: 0.155
    - type: map_at_10
      value: 0.8330000000000001
    - type: map_at_100
      value: 4.590000000000001
    - type: map_at_1000
      value: 11.683
    - type: map_at_3
      value: 0.334
    - type: map_at_5
      value: 0.466
    - type: mrr_at_1
      value: 60.0
    - type: mrr_at_10
      value: 68.136
    - type: mrr_at_100
      value: 68.703
    - type: mrr_at_1000
      value: 68.703
    - type: mrr_at_3
      value: 66.0
    - type: mrr_at_5
      value: 66.4
    - type: ndcg_at_1
      value: 54.0
    - type: ndcg_at_10
      value: 44.658
    - type: ndcg_at_100
      value: 33.977000000000004
    - type: ndcg_at_1000
      value: 30.621
    - type: ndcg_at_3
      value: 48.939
    - type: ndcg_at_5
      value: 45.396
    - type: precision_at_1
      value: 57.99999999999999
    - type: precision_at_10
      value: 47.4
    - type: precision_at_100
      value: 35.82
    - type: precision_at_1000
      value: 14.876000000000001
    - type: precision_at_3
      value: 50.0
    - type: precision_at_5
      value: 45.6
    - type: recall_at_1
      value: 0.155
    - type: recall_at_10
      value: 1.0670000000000002
    - type: recall_at_100
      value: 7.651
    - type: recall_at_1000
      value: 29.537000000000003
    - type: recall_at_3
      value: 0.35500000000000004
    - type: recall_at_5
      value: 0.518
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 44.25321653229755
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 49.93875732877625
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.86234724246499
    - type: cos_sim_spearman
      value: 67.59298171796401
    - type: euclidean_pearson
      value: 72.34370409015565
    - type: euclidean_spearman
      value: 67.59294254877997
    - type: manhattan_pearson
      value: 70.76123243638206
    - type: manhattan_spearman
      value: 66.86233305574997
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 75.2193174164991
    - type: cos_sim_spearman
      value: 66.95885463258551
    - type: euclidean_pearson
      value: 70.69637254317986
    - type: euclidean_spearman
      value: 66.95991031425478
    - type: manhattan_pearson
      value: 67.25988575290648
    - type: manhattan_spearman
      value: 64.94406492662402
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.42103332836258
    - type: cos_sim_spearman
      value: 78.48875534932043
    - type: euclidean_pearson
      value: 78.1930584097837
    - type: euclidean_spearman
      value: 78.48879315793262
    - type: manhattan_pearson
      value: 75.7705791679418
    - type: manhattan_spearman
      value: 76.01194506942352
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.58218995046416
    - type: cos_sim_spearman
      value: 75.61279190671051
    - type: euclidean_pearson
      value: 77.58820759180631
    - type: euclidean_spearman
      value: 75.61278221440635
    - type: manhattan_pearson
      value: 76.12440001778819
    - type: manhattan_spearman
      value: 74.4269498969252
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 82.2891641302121
    - type: cos_sim_spearman
      value: 82.73098262647434
    - type: euclidean_pearson
      value: 82.5188483930312
    - type: euclidean_spearman
      value: 82.73097334698637
    - type: manhattan_pearson
      value: 81.05168739270556
    - type: manhattan_spearman
      value: 81.10750061837136
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.4670953467407
    - type: cos_sim_spearman
      value: 78.53536279187583
    - type: euclidean_pearson
      value: 77.6227824619736
    - type: euclidean_spearman
      value: 78.53591292409315
    - type: manhattan_pearson
      value: 76.24243879772493
    - type: manhattan_spearman
      value: 77.00775260881191
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 86.19161153621691
    - type: cos_sim_spearman
      value: 86.86584556712556
    - type: euclidean_pearson
      value: 86.08114835853017
    - type: euclidean_spearman
      value: 86.86671808346402
    - type: manhattan_pearson
      value: 85.71042782796158
    - type: manhattan_spearman
      value: 86.76481453820853
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 59.80818689506919
    - type: cos_sim_spearman
      value: 59.903534431363916
    - type: euclidean_pearson
      value: 60.967975393911466
    - type: euclidean_spearman
      value: 59.903534431363916
    - type: manhattan_pearson
      value: 59.348745545947104
    - type: manhattan_spearman
      value: 58.506942610232116
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 80.61911955925173
    - type: cos_sim_spearman
      value: 79.18748066540941
    - type: euclidean_pearson
      value: 80.06976231938555
    - type: euclidean_spearman
      value: 79.18749912961366
    - type: manhattan_pearson
      value: 78.3922696264025
    - type: manhattan_spearman
      value: 77.68224365306664
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.36063395414824
    - type: mrr
      value: 91.81411453470277
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 39.139
    - type: map_at_10
      value: 47.508
    - type: map_at_100
      value: 48.631
    - type: map_at_1000
      value: 48.691
    - type: map_at_3
      value: 44.926
    - type: map_at_5
      value: 46.093
    - type: mrr_at_1
      value: 41.333
    - type: mrr_at_10
      value: 49.289
    - type: mrr_at_100
      value: 50.209
    - type: mrr_at_1000
      value: 50.261
    - type: mrr_at_3
      value: 46.944
    - type: mrr_at_5
      value: 47.978
    - type: ndcg_at_1
      value: 41.333
    - type: ndcg_at_10
      value: 52.306
    - type: ndcg_at_100
      value: 57.403999999999996
    - type: ndcg_at_1000
      value: 58.733999999999995
    - type: ndcg_at_3
      value: 47.113
    - type: ndcg_at_5
      value: 48.966
    - type: precision_at_1
      value: 41.333
    - type: precision_at_10
      value: 7.167
    - type: precision_at_100
      value: 0.997
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 18.333
    - type: precision_at_5
      value: 12.0
    - type: recall_at_1
      value: 39.139
    - type: recall_at_10
      value: 65.84400000000001
    - type: recall_at_100
      value: 88.94999999999999
    - type: recall_at_1000
      value: 98.867
    - type: recall_at_3
      value: 51.222
    - type: recall_at_5
      value: 55.72200000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.66831683168317
    - type: cos_sim_ap
      value: 89.56758407722171
    - type: cos_sim_f1
      value: 82.97029702970298
    - type: cos_sim_precision
      value: 82.15686274509804
    - type: cos_sim_recall
      value: 83.8
    - type: dot_accuracy
      value: 99.66831683168317
    - type: dot_ap
      value: 89.56758407722171
    - type: dot_f1
      value: 82.97029702970298
    - type: dot_precision
      value: 82.15686274509804
    - type: dot_recall
      value: 83.8
    - type: euclidean_accuracy
      value: 99.66831683168317
    - type: euclidean_ap
      value: 89.56758407722171
    - type: euclidean_f1
      value: 82.97029702970298
    - type: euclidean_precision
      value: 82.15686274509804
    - type: euclidean_recall
      value: 83.8
    - type: manhattan_accuracy
      value: 99.65445544554456
    - type: manhattan_ap
      value: 88.81637821295462
    - type: manhattan_f1
      value: 81.9047619047619
    - type: manhattan_precision
      value: 82.1105527638191
    - type: manhattan_recall
      value: 81.69999999999999
    - type: max_accuracy
      value: 99.66831683168317
    - type: max_ap
      value: 89.56758407722171
    - type: max_f1
      value: 82.97029702970298
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 47.34055809539011
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.658298502445096
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.989840235812004
    - type: mrr
      value: 44.506899350649356
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.29667664654959
    - type: cos_sim_spearman
      value: 29.818596667773882
    - type: dot_pearson
      value: 31.296676647072026
    - type: dot_spearman
      value: 29.779857187330265
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.426
    - type: map_at_10
      value: 8.38
    - type: map_at_100
      value: 14.308000000000002
    - type: map_at_1000
      value: 15.956000000000001
    - type: map_at_3
      value: 4.596
    - type: map_at_5
      value: 6.1339999999999995
    - type: mrr_at_1
      value: 32.653
    - type: mrr_at_10
      value: 44.577
    - type: mrr_at_100
      value: 45.754
    - type: mrr_at_1000
      value: 45.754
    - type: mrr_at_3
      value: 41.156
    - type: mrr_at_5
      value: 43.401
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 21.116
    - type: ndcg_at_100
      value: 35.193000000000005
    - type: ndcg_at_1000
      value: 46.989
    - type: ndcg_at_3
      value: 24.708
    - type: ndcg_at_5
      value: 23.594
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 19.592000000000002
    - type: precision_at_100
      value: 8.265
    - type: precision_at_1000
      value: 1.5939999999999999
    - type: precision_at_3
      value: 27.211000000000002
    - type: precision_at_5
      value: 25.306
    - type: recall_at_1
      value: 2.426
    - type: recall_at_10
      value: 13.691
    - type: recall_at_100
      value: 49.446
    - type: recall_at_1000
      value: 86.124
    - type: recall_at_3
      value: 5.67
    - type: recall_at_5
      value: 8.506
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 79.2904
    - type: ap
      value: 19.73734798884487
    - type: f1
      value: 61.89018130098357
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 60.97906055461234
    - type: f1
      value: 61.25225658586279
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 41.859245341604115
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.4714192048638
    - type: cos_sim_ap
      value: 64.50474781834589
    - type: cos_sim_f1
      value: 60.58070866141732
    - type: cos_sim_precision
      value: 56.75426463808206
    - type: cos_sim_recall
      value: 64.96042216358839
    - type: dot_accuracy
      value: 83.4714192048638
    - type: dot_ap
      value: 64.50474781834589
    - type: dot_f1
      value: 60.58070866141732
    - type: dot_precision
      value: 56.75426463808206
    - type: dot_recall
      value: 64.96042216358839
    - type: euclidean_accuracy
      value: 83.4714192048638
    - type: euclidean_ap
      value: 64.50474781834589
    - type: euclidean_f1
      value: 60.58070866141732
    - type: euclidean_precision
      value: 56.75426463808206
    - type: euclidean_recall
      value: 64.96042216358839
    - type: manhattan_accuracy
      value: 83.48334028729809
    - type: manhattan_ap
      value: 64.6227449383717
    - type: manhattan_f1
      value: 60.88942307692308
    - type: manhattan_precision
      value: 55.916114790286976
    - type: manhattan_recall
      value: 66.83377308707124
    - type: max_accuracy
      value: 83.48334028729809
    - type: max_ap
      value: 64.6227449383717
    - type: max_f1
      value: 60.88942307692308
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.58295494236815
    - type: cos_sim_ap
      value: 83.22579648788027
    - type: cos_sim_f1
      value: 75.27357054859048
    - type: cos_sim_precision
      value: 71.09514031485284
    - type: cos_sim_recall
      value: 79.97382198952879
    - type: dot_accuracy
      value: 87.58295494236815
    - type: dot_ap
      value: 83.22579579937255
    - type: dot_f1
      value: 75.27357054859048
    - type: dot_precision
      value: 71.09514031485284
    - type: dot_recall
      value: 79.97382198952879
    - type: euclidean_accuracy
      value: 87.58295494236815
    - type: euclidean_ap
      value: 83.22580643443949
    - type: euclidean_f1
      value: 75.27357054859048
    - type: euclidean_precision
      value: 71.09514031485284
    - type: euclidean_recall
      value: 79.97382198952879
    - type: manhattan_accuracy
      value: 87.57325260992742
    - type: manhattan_ap
      value: 83.05240665725778
    - type: manhattan_f1
      value: 75.09726237641432
    - type: manhattan_precision
      value: 69.99800385920554
    - type: manhattan_recall
      value: 80.99784416384355
    - type: max_accuracy
      value: 87.58295494236815
    - type: max_ap
      value: 83.22580643443949
    - type: max_f1
      value: 75.27357054859048
---
