mteb model-index region:us
---
tags:
- mteb
model-index:
- name: bge_finetuned
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 61.64179104477612
    - type: ap
      value: 25.20497978200253
    - type: f1
      value: 55.51169205110252
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 58.6114
    - type: ap
      value: 55.013881977883706
    - type: f1
      value: 58.0798269108889
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 27.009999999999994
    - type: f1
      value: 26.230644551993027
  - task:
      type: Retrieval
    dataset:
      type: arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 14.011000000000001
    - type: map_at_10
      value: 24.082
    - type: map_at_100
      value: 25.273
    - type: map_at_1000
      value: 25.336
    - type: map_at_3
      value: 20.341
    - type: map_at_5
      value: 22.155
    - type: mrr_at_1
      value: 14.651
    - type: mrr_at_10
      value: 24.306
    - type: mrr_at_100
      value: 25.503999999999998
    - type: mrr_at_1000
      value: 25.566
    - type: mrr_at_3
      value: 20.59
    - type: mrr_at_5
      value: 22.400000000000002
    - type: ndcg_at_1
      value: 14.011000000000001
    - type: ndcg_at_10
      value: 30.316
    - type: ndcg_at_100
      value: 36.146
    - type: ndcg_at_1000
      value: 37.972
    - type: ndcg_at_3
      value: 22.422
    - type: ndcg_at_5
      value: 25.727
    - type: precision_at_1
      value: 14.011000000000001
    - type: precision_at_10
      value: 5.0569999999999995
    - type: precision_at_100
      value: 0.7799999999999999
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 9.483
    - type: precision_at_5
      value: 7.312
    - type: recall_at_1
      value: 14.011000000000001
    - type: recall_at_10
      value: 50.568999999999996
    - type: recall_at_100
      value: 77.952
    - type: recall_at_1000
      value: 92.674
    - type: recall_at_3
      value: 28.449999999999996
    - type: recall_at_5
      value: 36.558
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 21.580787107217457
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 12.755947651867459
  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 50.36895415359604
    - type: mrr
      value: 62.93244075100032
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 54.84190098866484
    - type: cos_sim_spearman
      value: 52.065644182348144
    - type: euclidean_pearson
      value: 54.181073661388034
    - type: euclidean_spearman
      value: 52.065644182348144
    - type: manhattan_pearson
      value: 54.98368207013862
    - type: manhattan_spearman
      value: 53.66387337016872
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 63.48051948051948
    - type: f1
      value: 61.45740352513437
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 16.23123129183937
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 6.846095550717324
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 14.587
    - type: map_at_10
      value: 20.032
    - type: map_at_100
      value: 21.2
    - type: map_at_1000
      value: 21.351
    - type: map_at_3
      value: 18.224
    - type: map_at_5
      value: 19.028
    - type: mrr_at_1
      value: 18.312
    - type: mrr_at_10
      value: 24.343999999999998
    - type: mrr_at_100
      value: 25.302000000000003
    - type: mrr_at_1000
      value: 25.385
    - type: mrr_at_3
      value: 22.461000000000002
    - type: mrr_at_5
      value: 23.219
    - type: ndcg_at_1
      value: 18.312
    - type: ndcg_at_10
      value: 24.05
    - type: ndcg_at_100
      value: 29.512
    - type: ndcg_at_1000
      value: 33.028999999999996
    - type: ndcg_at_3
      value: 20.947
    - type: ndcg_at_5
      value: 21.807000000000002
    - type: precision_at_1
      value: 18.312
    - type: precision_at_10
      value: 4.664
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 10.11
    - type: precision_at_5
      value: 7.066999999999999
    - type: recall_at_1
      value: 14.587
    - type: recall_at_10
      value: 31.865
    - type: recall_at_100
      value: 55.922000000000004
    - type: recall_at_1000
      value: 80.878
    - type: recall_at_3
      value: 22.229
    - type: recall_at_5
      value: 25.09
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.456
    - type: map_at_10
      value: 11.429
    - type: map_at_100
      value: 11.956
    - type: map_at_1000
      value: 12.04
    - type: map_at_3
      value: 10.309
    - type: map_at_5
      value: 11.006
    - type: mrr_at_1
      value: 10.637
    - type: mrr_at_10
      value: 14.047
    - type: mrr_at_100
      value: 14.591999999999999
    - type: mrr_at_1000
      value: 14.66
    - type: mrr_at_3
      value: 12.876999999999999
    - type: mrr_at_5
      value: 13.644
    - type: ndcg_at_1
      value: 10.637
    - type: ndcg_at_10
      value: 13.623
    - type: ndcg_at_100
      value: 16.337
    - type: ndcg_at_1000
      value: 18.881
    - type: ndcg_at_3
      value: 11.76
    - type: ndcg_at_5
      value: 12.803
    - type: precision_at_1
      value: 10.637
    - type: precision_at_10
      value: 2.611
    - type: precision_at_100
      value: 0.49899999999999994
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 5.7540000000000004
    - type: precision_at_5
      value: 4.306
    - type: recall_at_1
      value: 8.456
    - type: recall_at_10
      value: 17.543
    - type: recall_at_100
      value: 29.696
    - type: recall_at_1000
      value: 48.433
    - type: recall_at_3
      value: 12.299
    - type: recall_at_5
      value: 15.126000000000001
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.517999999999999
    - type: map_at_10
      value: 14.924999999999999
    - type: map_at_100
      value: 15.716
    - type: map_at_1000
      value: 15.804000000000002
    - type: map_at_3
      value: 13.228000000000002
    - type: map_at_5
      value: 14.155999999999999
    - type: mrr_at_1
      value: 12.790000000000001
    - type: mrr_at_10
      value: 17.122999999999998
    - type: mrr_at_100
      value: 17.874000000000002
    - type: mrr_at_1000
      value: 17.947
    - type: mrr_at_3
      value: 15.528
    - type: mrr_at_5
      value: 16.421
    - type: ndcg_at_1
      value: 12.790000000000001
    - type: ndcg_at_10
      value: 17.967
    - type: ndcg_at_100
      value: 22.016
    - type: ndcg_at_1000
      value: 24.57
    - type: ndcg_at_3
      value: 14.745
    - type: ndcg_at_5
      value: 16.247
    - type: precision_at_1
      value: 12.790000000000001
    - type: precision_at_10
      value: 3.229
    - type: precision_at_100
      value: 0.592
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.792
    - type: precision_at_5
      value: 5.066
    - type: recall_at_1
      value: 10.517999999999999
    - type: recall_at_10
      value: 25.194
    - type: recall_at_100
      value: 43.858999999999995
    - type: recall_at_1000
      value: 63.410999999999994
    - type: recall_at_3
      value: 16.384999999999998
    - type: recall_at_5
      value: 20.09
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.325000000000001
    - type: map_at_10
      value: 12.262
    - type: map_at_100
      value: 13.003
    - type: map_at_1000
      value: 13.126999999999999
    - type: map_at_3
      value: 10.946
    - type: map_at_5
      value: 11.581
    - type: mrr_at_1
      value: 9.379
    - type: mrr_at_10
      value: 13.527000000000001
    - type: mrr_at_100
      value: 14.249999999999998
    - type: mrr_at_1000
      value: 14.365
    - type: mrr_at_3
      value: 12.166
    - type: mrr_at_5
      value: 12.798000000000002
    - type: ndcg_at_1
      value: 9.379
    - type: ndcg_at_10
      value: 14.878
    - type: ndcg_at_100
      value: 19.17
    - type: ndcg_at_1000
      value: 22.861
    - type: ndcg_at_3
      value: 12.136
    - type: ndcg_at_5
      value: 13.209000000000001
    - type: precision_at_1
      value: 9.379
    - type: precision_at_10
      value: 2.5309999999999997
    - type: precision_at_100
      value: 0.505
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 5.386
    - type: precision_at_5
      value: 3.887
    - type: recall_at_1
      value: 8.325000000000001
    - type: recall_at_10
      value: 21.886
    - type: recall_at_100
      value: 42.977
    - type: recall_at_1000
      value: 71.946
    - type: recall_at_3
      value: 14.123
    - type: recall_at_5
      value: 16.747
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.982
    - type: map_at_10
      value: 9.249
    - type: map_at_100
      value: 10.0
    - type: map_at_1000
      value: 10.127
    - type: map_at_3
      value: 7.913
    - type: map_at_5
      value: 8.540000000000001
    - type: mrr_at_1
      value: 7.960000000000001
    - type: mrr_at_10
      value: 11.703
    - type: mrr_at_100
      value: 12.43
    - type: mrr_at_1000
      value: 12.534999999999998
    - type: mrr_at_3
      value: 10.344000000000001
    - type: mrr_at_5
      value: 11.022
    - type: ndcg_at_1
      value: 7.960000000000001
    - type: ndcg_at_10
      value: 11.863
    - type: ndcg_at_100
      value: 16.086
    - type: ndcg_at_1000
      value: 19.738
    - type: ndcg_at_3
      value: 9.241000000000001
    - type: ndcg_at_5
      value: 10.228
    - type: precision_at_1
      value: 7.960000000000001
    - type: precision_at_10
      value: 2.4
    - type: precision_at_100
      value: 0.534
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 4.561
    - type: precision_at_5
      value: 3.408
    - type: recall_at_1
      value: 5.982
    - type: recall_at_10
      value: 17.669999999999998
    - type: recall_at_100
      value: 37.261
    - type: recall_at_1000
      value: 64.416
    - type: recall_at_3
      value: 10.376000000000001
    - type: recall_at_5
      value: 12.933
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.068
    - type: map_at_10
      value: 12.101
    - type: map_at_100
      value: 12.828000000000001
    - type: map_at_1000
      value: 12.953000000000001
    - type: map_at_3
      value: 11.047
    - type: map_at_5
      value: 11.542
    - type: mrr_at_1
      value: 10.972
    - type: mrr_at_10
      value: 14.873
    - type: mrr_at_100
      value: 15.584000000000001
    - type: mrr_at_1000
      value: 15.681999999999999
    - type: mrr_at_3
      value: 13.523
    - type: mrr_at_5
      value: 14.254
    - type: ndcg_at_1
      value: 10.972
    - type: ndcg_at_10
      value: 14.557999999999998
    - type: ndcg_at_100
      value: 18.56
    - type: ndcg_at_1000
      value: 21.975
    - type: ndcg_at_3
      value: 12.436
    - type: ndcg_at_5
      value: 13.270999999999999
    - type: precision_at_1
      value: 10.972
    - type: precision_at_10
      value: 2.714
    - type: precision_at_100
      value: 0.5720000000000001
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 5.711
    - type: precision_at_5
      value: 4.1579999999999995
    - type: recall_at_1
      value: 9.068
    - type: recall_at_10
      value: 19.381999999999998
    - type: recall_at_100
      value: 37.602999999999994
    - type: recall_at_1000
      value: 62.376
    - type: recall_at_3
      value: 13.48
    - type: recall_at_5
      value: 15.506
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.206
    - type: map_at_10
      value: 12.032
    - type: map_at_100
      value: 12.992
    - type: map_at_1000
      value: 13.135
    - type: map_at_3
      value: 10.741
    - type: map_at_5
      value: 11.392
    - type: mrr_at_1
      value: 10.502
    - type: mrr_at_10
      value: 14.818999999999999
    - type: mrr_at_100
      value: 15.716
    - type: mrr_at_1000
      value: 15.823
    - type: mrr_at_3
      value: 13.375
    - type: mrr_at_5
      value: 14.169
    - type: ndcg_at_1
      value: 10.502
    - type: ndcg_at_10
      value: 14.790000000000001
    - type: ndcg_at_100
      value: 19.881999999999998
    - type: ndcg_at_1000
      value: 23.703
    - type: ndcg_at_3
      value: 12.281
    - type: ndcg_at_5
      value: 13.33
    - type: precision_at_1
      value: 10.502
    - type: precision_at_10
      value: 2.911
    - type: precision_at_100
      value: 0.668
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 6.012
    - type: precision_at_5
      value: 4.475
    - type: recall_at_1
      value: 8.206
    - type: recall_at_10
      value: 20.508000000000003
    - type: recall_at_100
      value: 43.568
    - type: recall_at_1000
      value: 71.56400000000001
    - type: recall_at_3
      value: 13.607
    - type: recall_at_5
      value: 16.211000000000002
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.4159999999999995
    - type: map_at_10
      value: 9.581000000000001
    - type: map_at_100
      value: 10.123999999999999
    - type: map_at_1000
      value: 10.226
    - type: map_at_3
      value: 8.51
    - type: map_at_5
      value: 9.078999999999999
    - type: mrr_at_1
      value: 7.515
    - type: mrr_at_10
      value: 10.801
    - type: mrr_at_100
      value: 11.373
    - type: mrr_at_1000
      value: 11.466999999999999
    - type: mrr_at_3
      value: 9.637
    - type: mrr_at_5
      value: 10.197000000000001
    - type: ndcg_at_1
      value: 7.515
    - type: ndcg_at_10
      value: 11.776
    - type: ndcg_at_100
      value: 14.776
    - type: ndcg_at_1000
      value: 17.7
    - type: ndcg_at_3
      value: 9.515
    - type: ndcg_at_5
      value: 10.511
    - type: precision_at_1
      value: 7.515
    - type: precision_at_10
      value: 2.086
    - type: precision_at_100
      value: 0.402
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 4.397
    - type: precision_at_5
      value: 3.19
    - type: recall_at_1
      value: 6.4159999999999995
    - type: recall_at_10
      value: 17.468
    - type: recall_at_100
      value: 31.398
    - type: recall_at_1000
      value: 53.686
    - type: recall_at_3
      value: 11.379999999999999
    - type: recall_at_5
      value: 13.745
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.646
    - type: map_at_10
      value: 7.047000000000001
    - type: map_at_100
      value: 7.697
    - type: map_at_1000
      value: 7.806
    - type: map_at_3
      value: 6.258
    - type: map_at_5
      value: 6.628
    - type: mrr_at_1
      value: 5.919
    - type: mrr_at_10
      value: 8.767999999999999
    - type: mrr_at_100
      value: 9.434
    - type: mrr_at_1000
      value: 9.524000000000001
    - type: mrr_at_3
      value: 7.8
    - type: mrr_at_5
      value: 8.275
    - type: ndcg_at_1
      value: 5.919
    - type: ndcg_at_10
      value: 8.927999999999999
    - type: ndcg_at_100
      value: 12.467
    - type: ndcg_at_1000
      value: 15.674
    - type: ndcg_at_3
      value: 7.3260000000000005
    - type: ndcg_at_5
      value: 7.931000000000001
    - type: precision_at_1
      value: 5.919
    - type: precision_at_10
      value: 1.7760000000000002
    - type: precision_at_100
      value: 0.438
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 3.6249999999999996
    - type: precision_at_5
      value: 2.657
    - type: recall_at_1
      value: 4.646
    - type: recall_at_10
      value: 12.973
    - type: recall_at_100
      value: 29.444
    - type: recall_at_1000
      value: 53.413999999999994
    - type: recall_at_3
      value: 8.378
    - type: recall_at_5
      value: 9.957
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.202
    - type: map_at_10
      value: 13.402
    - type: map_at_100
      value: 14.330000000000002
    - type: map_at_1000
      value: 14.455000000000002
    - type: map_at_3
      value: 11.916
    - type: map_at_5
      value: 12.828000000000001
    - type: mrr_at_1
      value: 10.634
    - type: mrr_at_10
      value: 15.528
    - type: mrr_at_100
      value: 16.393
    - type: mrr_at_1000
      value: 16.497999999999998
    - type: mrr_at_3
      value: 13.837
    - type: mrr_at_5
      value: 14.821000000000002
    - type: ndcg_at_1
      value: 10.634
    - type: ndcg_at_10
      value: 16.267
    - type: ndcg_at_100
      value: 21.149
    - type: ndcg_at_1000
      value: 24.509
    - type: ndcg_at_3
      value: 13.320000000000002
    - type: ndcg_at_5
      value: 14.857000000000001
    - type: precision_at_1
      value: 10.634
    - type: precision_at_10
      value: 2.948
    - type: precision_at_100
      value: 0.618
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 6.188
    - type: precision_at_5
      value: 4.7010000000000005
    - type: recall_at_1
      value: 9.202
    - type: recall_at_10
      value: 22.921
    - type: recall_at_100
      value: 45.292
    - type: recall_at_1000
      value: 69.853
    - type: recall_at_3
      value: 15.126000000000001
    - type: recall_at_5
      value: 18.863
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 11.278
    - type: map_at_10
      value: 15.72
    - type: map_at_100
      value: 16.832
    - type: map_at_1000
      value: 17.025000000000002
    - type: map_at_3
      value: 13.852999999999998
    - type: map_at_5
      value: 14.654
    - type: mrr_at_1
      value: 14.822
    - type: mrr_at_10
      value: 19.564
    - type: mrr_at_100
      value: 20.509
    - type: mrr_at_1000
      value: 20.607
    - type: mrr_at_3
      value: 17.721
    - type: mrr_at_5
      value: 18.451999999999998
    - type: ndcg_at_1
      value: 14.822
    - type: ndcg_at_10
      value: 19.548
    - type: ndcg_at_100
      value: 24.734
    - type: ndcg_at_1000
      value: 28.832
    - type: ndcg_at_3
      value: 16.14
    - type: ndcg_at_5
      value: 17.253
    - type: precision_at_1
      value: 14.822
    - type: precision_at_10
      value: 3.972
    - type: precision_at_100
      value: 0.943
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 7.642
    - type: precision_at_5
      value: 5.6129999999999995
    - type: recall_at_1
      value: 11.278
    - type: recall_at_10
      value: 27.006999999999998
    - type: recall_at_100
      value: 51.012
    - type: recall_at_1000
      value: 79.833
    - type: recall_at_3
      value: 16.785
    - type: recall_at_5
      value: 19.82
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.305
    - type: map_at_10
      value: 9.099
    - type: map_at_100
      value: 9.927999999999999
    - type: map_at_1000
      value: 10.027
    - type: map_at_3
      value: 7.7700000000000005
    - type: map_at_5
      value: 8.333
    - type: mrr_at_1
      value: 6.1
    - type: mrr_at_10
      value: 10.227
    - type: mrr_at_100
      value: 11.057
    - type: mrr_at_1000
      value: 11.151
    - type: mrr_at_3
      value: 8.842
    - type: mrr_at_5
      value: 9.442
    - type: ndcg_at_1
      value: 6.1
    - type: ndcg_at_10
      value: 11.769
    - type: ndcg_at_100
      value: 16.378999999999998
    - type: ndcg_at_1000
      value: 19.517
    - type: ndcg_at_3
      value: 8.936
    - type: ndcg_at_5
      value: 9.907
    - type: precision_at_1
      value: 6.1
    - type: precision_at_10
      value: 2.181
    - type: precision_at_100
      value: 0.481
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 4.19
    - type: precision_at_5
      value: 3.031
    - type: recall_at_1
      value: 5.305
    - type: recall_at_10
      value: 19.236
    - type: recall_at_100
      value: 41.333999999999996
    - type: recall_at_1000
      value: 65.96600000000001
    - type: recall_at_3
      value: 11.189
    - type: recall_at_5
      value: 13.592
  - task:
      type: Retrieval
    dataset:
      type: climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.882
    - type: map_at_10
      value: 1.6
    - type: map_at_100
      value: 1.894
    - type: map_at_1000
      value: 1.9640000000000002
    - type: map_at_3
      value: 1.345
    - type: map_at_5
      value: 1.444
    - type: mrr_at_1
      value: 2.2800000000000002
    - type: mrr_at_10
      value: 3.8510000000000004
    - type: mrr_at_100
      value: 4.401
    - type: mrr_at_1000
      value: 4.472
    - type: mrr_at_3
      value: 3.2359999999999998
    - type: mrr_at_5
      value: 3.519
    - type: ndcg_at_1
      value: 2.2800000000000002
    - type: ndcg_at_10
      value: 2.5829999999999997
    - type: ndcg_at_100
      value: 4.629
    - type: ndcg_at_1000
      value: 6.709
    - type: ndcg_at_3
      value: 1.978
    - type: ndcg_at_5
      value: 2.133
    - type: precision_at_1
      value: 2.2800000000000002
    - type: precision_at_10
      value: 0.86
    - type: precision_at_100
      value: 0.298
    - type: precision_at_1000
      value: 0.065
    - type: precision_at_3
      value: 1.52
    - type: precision_at_5
      value: 1.173
    - type: recall_at_1
      value: 0.882
    - type: recall_at_10
      value: 3.273
    - type: recall_at_100
      value: 11.254
    - type: recall_at_1000
      value: 23.988
    - type: recall_at_3
      value: 1.818
    - type: recall_at_5
      value: 2.236
  - task:
      type: Retrieval
    dataset:
      type: dbpedia-entity
      name: MTEB DBPedia
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.057
    - type: map_at_10
      value: 2.289
    - type: map_at_100
      value: 2.844
    - type: map_at_1000
      value: 3.026
    - type: map_at_3
      value: 1.661
    - type: map_at_5
      value: 1.931
    - type: mrr_at_1
      value: 12.75
    - type: mrr_at_10
      value: 17.645
    - type: mrr_at_100
      value: 18.312
    - type: mrr_at_1000
      value: 18.385
    - type: mrr_at_3
      value: 15.958
    - type: mrr_at_5
      value: 17.046
    - type: ndcg_at_1
      value: 10.0
    - type: ndcg_at_10
      value: 6.890000000000001
    - type: ndcg_at_100
      value: 7.131
    - type: ndcg_at_1000
      value: 9.725
    - type: ndcg_at_3
      value: 8.222
    - type: ndcg_at_5
      value: 7.536
    - type: precision_at_1
      value: 12.75
    - type: precision_at_10
      value: 5.925
    - type: precision_at_100
      value: 1.6469999999999998
    - type: precision_at_1000
      value: 0.40299999999999997
    - type: precision_at_3
      value: 9.667
    - type: precision_at_5
      value: 8.0
    - type: recall_at_1
      value: 1.057
    - type: recall_at_10
      value: 3.8580000000000005
    - type: recall_at_100
      value: 8.685
    - type: recall_at_1000
      value: 17.605
    - type: recall_at_3
      value: 2.041
    - type: recall_at_5
      value: 2.811
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 20.674999999999997
    - type: f1
      value: 17.79184478487413
  - task:
      type: Retrieval
    dataset:
      type: fever
      name: MTEB FEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.637
    - type: map_at_10
      value: 3.9730000000000003
    - type: map_at_100
      value: 4.228
    - type: map_at_1000
      value: 4.268000000000001
    - type: map_at_3
      value: 3.542
    - type: map_at_5
      value: 3.763
    - type: mrr_at_1
      value: 2.7449999999999997
    - type: mrr_at_10
      value: 4.146
    - type: mrr_at_100
      value: 4.42
    - type: mrr_at_1000
      value: 4.460999999999999
    - type: mrr_at_3
      value: 3.695
    - type: mrr_at_5
      value: 3.925
    - type: ndcg_at_1
      value: 2.7449999999999997
    - type: ndcg_at_10
      value: 4.801
    - type: ndcg_at_100
      value: 6.198
    - type: ndcg_at_1000
      value: 7.468
    - type: ndcg_at_3
      value: 3.882
    - type: ndcg_at_5
      value: 4.283
    - type: precision_at_1
      value: 2.7449999999999997
    - type: precision_at_10
      value: 0.771
    - type: precision_at_100
      value: 0.152
    - type: precision_at_1000
      value: 0.027
    - type: precision_at_3
      value: 1.6549999999999998
    - type: precision_at_5
      value: 1.206
    - type: recall_at_1
      value: 2.637
    - type: recall_at_10
      value: 7.2669999999999995
    - type: recall_at_100
      value: 13.982
    - type: recall_at_1000
      value: 24.192
    - type: recall_at_3
      value: 4.712000000000001
    - type: recall_at_5
      value: 5.6739999999999995
  - task:
      type: Retrieval
    dataset:
      type: fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.91
    - type: map_at_10
      value: 5.721
    - type: map_at_100
      value: 6.489000000000001
    - type: map_at_1000
      value: 6.642
    - type: map_at_3
      value: 4.797
    - type: map_at_5
      value: 5.292
    - type: mrr_at_1
      value: 6.481000000000001
    - type: mrr_at_10
      value: 10.624
    - type: mrr_at_100
      value: 11.498999999999999
    - type: mrr_at_1000
      value: 11.599
    - type: mrr_at_3
      value: 9.285
    - type: mrr_at_5
      value: 10.003
    - type: ndcg_at_1
      value: 6.481000000000001
    - type: ndcg_at_10
      value: 8.303
    - type: ndcg_at_100
      value: 12.512
    - type: ndcg_at_1000
      value: 16.665
    - type: ndcg_at_3
      value: 6.827
    - type: ndcg_at_5
      value: 7.367
    - type: precision_at_1
      value: 6.481000000000001
    - type: precision_at_10
      value: 2.485
    - type: precision_at_100
      value: 0.668
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 4.733
    - type: precision_at_5
      value: 3.642
    - type: recall_at_1
      value: 2.91
    - type: recall_at_10
      value: 11.239
    - type: recall_at_100
      value: 27.877999999999997
    - type: recall_at_1000
      value: 54.507000000000005
    - type: recall_at_3
      value: 6.683
    - type: recall_at_5
      value: 8.591
  - task:
      type: Retrieval
    dataset:
      type: hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.073
    - type: map_at_10
      value: 2.919
    - type: map_at_100
      value: 3.107
    - type: map_at_1000
      value: 3.143
    - type: map_at_3
      value: 2.6100000000000003
    - type: map_at_5
      value: 2.773
    - type: mrr_at_1
      value: 4.146
    - type: mrr_at_10
      value: 5.657
    - type: mrr_at_100
      value: 5.970000000000001
    - type: mrr_at_1000
      value: 6.022
    - type: mrr_at_3
      value: 5.116
    - type: mrr_at_5
      value: 5.411
    - type: ndcg_at_1
      value: 4.146
    - type: ndcg_at_10
      value: 4.115
    - type: ndcg_at_100
      value: 5.319
    - type: ndcg_at_1000
      value: 6.584
    - type: ndcg_at_3
      value: 3.3709999999999996
    - type: ndcg_at_5
      value: 3.7159999999999997
    - type: precision_at_1
      value: 4.146
    - type: precision_at_10
      value: 0.983
    - type: precision_at_100
      value: 0.197
    - type: precision_at_1000
      value: 0.037
    - type: precision_at_3
      value: 2.152
    - type: precision_at_5
      value: 1.564
    - type: recall_at_1
      value: 2.073
    - type: recall_at_10
      value: 4.916
    - type: recall_at_100
      value: 9.844999999999999
    - type: recall_at_1000
      value: 18.454
    - type: recall_at_3
      value: 3.228
    - type: recall_at_5
      value: 3.91
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 53.28480000000001
    - type: ap
      value: 51.81084207241404
    - type: f1
      value: 52.83683146513476
  - task:
      type: Retrieval
    dataset:
      type: msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 2.613
    - type: map_at_10
      value: 4.33
    - type: map_at_100
      value: 4.681
    - type: map_at_1000
      value: 4.731
    - type: map_at_3
      value: 3.7560000000000002
    - type: map_at_5
      value: 4.035
    - type: mrr_at_1
      value: 2.665
    - type: mrr_at_10
      value: 4.436
    - type: mrr_at_100
      value: 4.797
    - type: mrr_at_1000
      value: 4.848
    - type: mrr_at_3
      value: 3.83
    - type: mrr_at_5
      value: 4.123
    - type: ndcg_at_1
      value: 2.665
    - type: ndcg_at_10
      value: 5.399
    - type: ndcg_at_100
      value: 7.402
    - type: ndcg_at_1000
      value: 9.08
    - type: ndcg_at_3
      value: 4.1579999999999995
    - type: ndcg_at_5
      value: 4.664
    - type: precision_at_1
      value: 2.665
    - type: precision_at_10
      value: 0.907
    - type: precision_at_100
      value: 0.19499999999999998
    - type: precision_at_1000
      value: 0.034
    - type: precision_at_3
      value: 1.791
    - type: precision_at_5
      value: 1.3299999999999998
    - type: recall_at_1
      value: 2.613
    - type: recall_at_10
      value: 8.729000000000001
    - type: recall_at_100
      value: 18.668000000000003
    - type: recall_at_1000
      value: 32.387
    - type: recall_at_3
      value: 5.25
    - type: recall_at_5
      value: 6.465
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 73.57729138166896
    - type: f1
      value: 71.0267308110663
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 38.76652986776106
    - type: f1
      value: 24.385724192837007
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 43.43308675184936
    - type: f1
      value: 39.072401899805016
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 55.225285810356425
    - type: f1
      value: 49.81719052485716
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 20.583405653329283
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 17.155646378261917
  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 24.26316550665883
    - type: mrr
      value: 23.951621402458755
  - task:
      type: Retrieval
    dataset:
      type: nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.4040000000000001
    - type: map_at_10
      value: 2.199
    - type: map_at_100
      value: 2.597
    - type: map_at_1000
      value: 3.15
    - type: map_at_3
      value: 1.7850000000000001
    - type: map_at_5
      value: 2.005
    - type: mrr_at_1
      value: 13.932
    - type: mrr_at_10
      value: 19.529
    - type: mrr_at_100
      value: 20.53
    - type: mrr_at_1000
      value: 20.635
    - type: mrr_at_3
      value: 17.647
    - type: mrr_at_5
      value: 18.731
    - type: ndcg_at_1
      value: 12.539
    - type: ndcg_at_10
      value: 8.676
    - type: ndcg_at_100
      value: 8.092
    - type: ndcg_at_1000
      value: 16.375999999999998
    - type: ndcg_at_3
      value: 10.615
    - type: ndcg_at_5
      value: 9.690999999999999
    - type: precision_at_1
      value: 13.622
    - type: precision_at_10
      value: 6.315999999999999
    - type: precision_at_100
      value: 2.486
    - type: precision_at_1000
      value: 1.317
    - type: precision_at_3
      value: 10.113999999999999
    - type: precision_at_5
      value: 8.235000000000001
    - type: recall_at_1
      value: 1.4040000000000001
    - type: recall_at_10
      value: 3.794
    - type: recall_at_100
      value: 9.71
    - type: recall_at_1000
      value: 37.476
    - type: recall_at_3
      value: 2.197
    - type: recall_at_5
      value: 2.929
  - task:
      type: Retrieval
    dataset:
      type: nq
      name: MTEB NQ
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.299
    - type: map_at_10
      value: 2.7279999999999998
    - type: map_at_100
      value: 3.065
    - type: map_at_1000
      value: 3.118
    - type: map_at_3
      value: 2.182
    - type: map_at_5
      value: 2.48
    - type: mrr_at_1
      value: 1.6219999999999999
    - type: mrr_at_10
      value: 3.237
    - type: mrr_at_100
      value: 3.5749999999999997
    - type: mrr_at_1000
      value: 3.626
    - type: mrr_at_3
      value: 2.6550000000000002
    - type: mrr_at_5
      value: 2.9770000000000003
    - type: ndcg_at_1
      value: 1.6219999999999999
    - type: ndcg_at_10
      value: 3.768
    - type: ndcg_at_100
      value: 5.721
    - type: ndcg_at_1000
      value: 7.346
    - type: ndcg_at_3
      value: 2.604
    - type: ndcg_at_5
      value: 3.1530000000000005
    - type: precision_at_1
      value: 1.6219999999999999
    - type: precision_at_10
      value: 0.776
    - type: precision_at_100
      value: 0.194
    - type: precision_at_1000
      value: 0.034999999999999996
    - type: precision_at_3
      value: 1.371
    - type: precision_at_5
      value: 1.1119999999999999
    - type: recall_at_1
      value: 1.299
    - type: recall_at_10
      value: 6.54
    - type: recall_at_100
      value: 16.014999999999997
    - type: recall_at_1000
      value: 28.776000000000003
    - type: recall_at_3
      value: 3.37
    - type: recall_at_5
      value: 4.676
  - task:
      type: Retrieval
    dataset:
      type: quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 50.827
    - type: map_at_10
      value: 60.903
    - type: map_at_100
      value: 61.67700000000001
    - type: map_at_1000
      value: 61.729
    - type: map_at_3
      value: 58.411
    - type: map_at_5
      value: 59.854
    - type: mrr_at_1
      value: 58.52
    - type: mrr_at_10
      value: 65.53999999999999
    - type: mrr_at_100
      value: 65.94
    - type: mrr_at_1000
      value: 65.962
    - type: mrr_at_3
      value: 63.905
    - type: mrr_at_5
      value: 64.883
    - type: ndcg_at_1
      value: 58.51
    - type: ndcg_at_10
      value: 65.458
    - type: ndcg_at_100
      value: 68.245
    - type: ndcg_at_1000
      value: 69.244
    - type: ndcg_at_3
      value: 61.970000000000006
    - type: ndcg_at_5
      value: 63.664
    - type: precision_at_1
      value: 58.51
    - type: precision_at_10
      value: 9.873999999999999
    - type: precision_at_100
      value: 1.24
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 26.650000000000002
    - type: precision_at_5
      value: 17.666
    - type: recall_at_1
      value: 50.827
    - type: recall_at_10
      value: 74.13300000000001
    - type: recall_at_100
      value: 85.724
    - type: recall_at_1000
      value: 92.551
    - type: recall_at_3
      value: 64.122
    - type: recall_at_5
      value: 68.757
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 15.106948858308094
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 30.968103547012337
  - task:
      type: Retrieval
    dataset:
      type: scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.4749999999999999
    - type: map_at_10
      value: 3.434
    - type: map_at_100
      value: 4.139
    - type: map_at_1000
      value: 4.312
    - type: map_at_3
      value: 2.554
    - type: map_at_5
      value: 2.999
    - type: mrr_at_1
      value: 7.3
    - type: mrr_at_10
      value: 12.031
    - type: mrr_at_100
      value: 12.97
    - type: mrr_at_1000
      value: 13.092
    - type: mrr_at_3
      value: 10.217
    - type: mrr_at_5
      value: 11.172
    - type: ndcg_at_1
      value: 7.3
    - type: ndcg_at_10
      value: 6.406000000000001
    - type: ndcg_at_100
      value: 10.302999999999999
    - type: ndcg_at_1000
      value: 14.791000000000002
    - type: ndcg_at_3
      value: 5.982
    - type: ndcg_at_5
      value: 5.274
    - type: precision_at_1
      value: 7.3
    - type: precision_at_10
      value: 3.37
    - type: precision_at_100
      value: 0.914
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 5.567
    - type: precision_at_5
      value: 4.68
    - type: recall_at_1
      value: 1.4749999999999999
    - type: recall_at_10
      value: 6.79
    - type: recall_at_100
      value: 18.55
    - type: recall_at_1000
      value: 40.842
    - type: recall_at_3
      value: 3.36
    - type: recall_at_5
      value: 4.72
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 59.464420082440526
    - type: cos_sim_spearman
      value: 54.319988337451704
    - type: euclidean_pearson
      value: 57.042312873314295
    - type: euclidean_spearman
      value: 54.31996388571784
    - type: manhattan_pearson
      value: 57.078786802338435
    - type: manhattan_spearman
      value: 54.323312153757456
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 60.08105871689929
    - type: cos_sim_spearman
      value: 57.53293836132526
    - type: euclidean_pearson
      value: 57.69984777047449
    - type: euclidean_spearman
      value: 57.534154476967345
    - type: manhattan_pearson
      value: 57.661519973840946
    - type: manhattan_spearman
      value: 57.447636234309854
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 57.12692049687197
    - type: cos_sim_spearman
      value: 57.4759438730368
    - type: euclidean_pearson
      value: 58.41782334532981
    - type: euclidean_spearman
      value: 57.47613008122331
    - type: manhattan_pearson
      value: 58.41335837274888
    - type: manhattan_spearman
      value: 57.465936751045746
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 53.84165004759765
    - type: cos_sim_spearman
      value: 52.32112048731462
    - type: euclidean_pearson
      value: 52.790405817119094
    - type: euclidean_spearman
      value: 52.32112268628659
    - type: manhattan_pearson
      value: 52.804939090733804
    - type: manhattan_spearman
      value: 52.31750678935915
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 63.555819199866036
    - type: cos_sim_spearman
      value: 64.05841117331784
    - type: euclidean_pearson
      value: 63.659991414541786
    - type: euclidean_spearman
      value: 64.05841071779129
    - type: manhattan_pearson
      value: 63.6915442281397
    - type: manhattan_spearman
      value: 64.07728265258595
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 63.03024268207247
    - type: cos_sim_spearman
      value: 63.53003651570799
    - type: euclidean_pearson
      value: 64.09620752390686
    - type: euclidean_spearman
      value: 63.530036058718096
    - type: manhattan_pearson
      value: 64.07468313413827
    - type: manhattan_spearman
      value: 63.526415746516285
  - task:
      type: STS
    dataset:
      type: mteb/sts17-crosslingual-sts
      name: MTEB STS17 (en-en)
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 70.18862439704168
    - type: cos_sim_spearman
      value: 70.97966882821095
    - type: euclidean_pearson
      value: 71.04858522892525
    - type: euclidean_spearman
      value: 70.97966882821095
    - type: manhattan_pearson
      value: 71.0777838495318
    - type: manhattan_spearman
      value: 71.08141859528023
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (en)
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 49.680993011354964
    - type: cos_sim_spearman
      value: 55.990646519065734
    - type: euclidean_pearson
      value: 52.53309325175639
    - type: euclidean_spearman
      value: 55.990646519065734
    - type: manhattan_pearson
      value: 52.55809108662631
    - type: manhattan_spearman
      value: 55.65236114980215
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 61.18394695826386
    - type: cos_sim_spearman
      value: 60.77402126712771
    - type: euclidean_pearson
      value: 61.202070794992736
    - type: euclidean_spearman
      value: 60.77402126712771
    - type: manhattan_pearson
      value: 61.2505175850885
    - type: manhattan_spearman
      value: 60.77213463387346
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 58.251838750265804
    - type: mrr
      value: 81.27406090641384
  - task:
      type: Retrieval
    dataset:
      type: scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.833
    - type: map_at_10
      value: 11.219999999999999
    - type: map_at_100
      value: 12.086
    - type: map_at_1000
      value: 12.200999999999999
    - type: map_at_3
      value: 10.056
    - type: map_at_5
      value: 10.664
    - type: mrr_at_1
      value: 9.0
    - type: mrr_at_10
      value: 11.875
    - type: mrr_at_100
      value: 12.757
    - type: mrr_at_1000
      value: 12.864
    - type: mrr_at_3
      value: 10.722
    - type: mrr_at_5
      value: 11.322000000000001
    - type: ndcg_at_1
      value: 9.0
    - type: ndcg_at_10
      value: 13.001
    - type: ndcg_at_100
      value: 17.784
    - type: ndcg_at_1000
      value: 21.695
    - type: ndcg_at_3
      value: 10.63
    - type: ndcg_at_5
      value: 11.693000000000001
    - type: precision_at_1
      value: 9.0
    - type: precision_at_10
      value: 2.0
    - type: precision_at_100
      value: 0.46299999999999997
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 4.222
    - type: precision_at_5
      value: 3.1329999999999996
    - type: recall_at_1
      value: 8.833
    - type: recall_at_10
      value: 18.0
    - type: recall_at_100
      value: 41.211
    - type: recall_at_1000
      value: 73.14399999999999
    - type: recall_at_3
      value: 11.5
    - type: recall_at_5
      value: 14.083000000000002
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.44455445544554
    - type: cos_sim_ap
      value: 68.76115592640271
    - type: cos_sim_f1
      value: 67.29805013927577
    - type: cos_sim_precision
      value: 75.9748427672956
    - type: cos_sim_recall
      value: 60.4
    - type: dot_accuracy
      value: 99.44455445544554
    - type: dot_ap
      value: 68.76115778951738
    - type: dot_f1
      value: 67.29805013927577
    - type: dot_precision
      value: 75.9748427672956
    - type: dot_recall
      value: 60.4
    - type: euclidean_accuracy
      value: 99.44455445544554
    - type: euclidean_ap
      value: 68.76115530286063
    - type: euclidean_f1
      value: 67.29805013927577
    - type: euclidean_precision
      value: 75.9748427672956
    - type: euclidean_recall
      value: 60.4
    - type: manhattan_accuracy
      value: 99.44653465346535
    - type: manhattan_ap
      value: 68.76446446842253
    - type: manhattan_f1
      value: 67.34926052332196
    - type: manhattan_precision
      value: 78.10026385224275
    - type: manhattan_recall
      value: 59.199999999999996
    - type: max_accuracy
      value: 99.44653465346535
    - type: max_ap
      value: 68.76446446842253
    - type: max_f1
      value: 67.34926052332196
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 28.486032726226675
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.654061810103283
  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 39.81455140801657
    - type: mrr
      value: 40.09712407690349
  - task:
      type: Retrieval
    dataset:
      type: trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.05
    - type: map_at_10
      value: 0.191
    - type: map_at_100
      value: 0.346
    - type: map_at_1000
      value: 0.553
    - type: map_at_3
      value: 0.11299999999999999
    - type: map_at_5
      value: 0.148
    - type: mrr_at_1
      value: 22.0
    - type: mrr_at_10
      value: 30.091
    - type: mrr_at_100
      value: 31.241999999999997
    - type: mrr_at_1000
      value: 31.298
    - type: mrr_at_3
      value: 28.000000000000004
    - type: mrr_at_5
      value: 28.999999999999996
    - type: ndcg_at_1
      value: 18.0
    - type: ndcg_at_10
      value: 12.501000000000001
    - type: ndcg_at_100
      value: 5.605
    - type: ndcg_at_1000
      value: 4.543
    - type: ndcg_at_3
      value: 17.531
    - type: ndcg_at_5
      value: 15.254999999999999
    - type: precision_at_1
      value: 22.0
    - type: precision_at_10
      value: 12.6
    - type: precision_at_100
      value: 5.06
    - type: precision_at_1000
      value: 2.028
    - type: precision_at_3
      value: 20.666999999999998
    - type: precision_at_5
      value: 16.8
    - type: recall_at_1
      value: 0.05
    - type: recall_at_10
      value: 0.267
    - type: recall_at_100
      value: 1.102
    - type: recall_at_1000
      value: 4.205
    - type: recall_at_3
      value: 0.134
    - type: recall_at_5
      value: 0.182
  - task:
      type: Retrieval
    dataset:
      type: webis-touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.45199999999999996
    - type: map_at_10
      value: 1.986
    - type: map_at_100
      value: 3.887
    - type: map_at_1000
      value: 4.5809999999999995
    - type: map_at_3
      value: 0.9299999999999999
    - type: map_at_5
      value: 1.287
    - type: mrr_at_1
      value: 8.163
    - type: mrr_at_10
      value: 16.152
    - type: mrr_at_100
      value: 17.187
    - type: mrr_at_1000
      value: 17.301
    - type: mrr_at_3
      value: 11.224
    - type: mrr_at_5
      value: 12.653
    - type: ndcg_at_1
      value: 4.082
    - type: ndcg_at_10
      value: 6.687
    - type: ndcg_at_100
      value: 13.158
    - type: ndcg_at_1000
      value: 22.259
    - type: ndcg_at_3
      value: 5.039
    - type: ndcg_at_5
      value: 5.519
    - type: precision_at_1
      value: 8.163
    - type: precision_at_10
      value: 8.163
    - type: precision_at_100
      value: 3.51
    - type: precision_at_1000
      value: 0.9159999999999999
    - type: precision_at_3
      value: 7.483
    - type: precision_at_5
      value: 7.3469999999999995
    - type: recall_at_1
      value: 0.45199999999999996
    - type: recall_at_10
      value: 5.27
    - type: recall_at_100
      value: 20.75
    - type: recall_at_1000
      value: 49.236999999999995
    - type: recall_at_3
      value: 1.28
    - type: recall_at_5
      value: 2.045
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 57.08740000000001
    - type: ap
      value: 9.092681400063896
    - type: f1
      value: 43.966684273361125
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 42.314657611771366
    - type: f1
      value: 42.2349043058169
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 15.71319288909283
  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 78.84007867914407
    - type: cos_sim_ap
      value: 42.2183603452187
    - type: cos_sim_f1
      value: 43.1781412906705
    - type: cos_sim_precision
      value: 32.74263904034896
    - type: cos_sim_recall
      value: 63.377308707124016
    - type: dot_accuracy
      value: 78.84007867914407
    - type: dot_ap
      value: 42.21836359699547
    - type: dot_f1
      value: 43.1781412906705
    - type: dot_precision
      value: 32.74263904034896
    - type: dot_recall
      value: 63.377308707124016
    - type: euclidean_accuracy
      value: 78.84007867914407
    - type: euclidean_ap
      value: 42.218363575958854
    - type: euclidean_f1
      value: 43.1781412906705
    - type: euclidean_precision
      value: 32.74263904034896
    - type: euclidean_recall
      value: 63.377308707124016
    - type: manhattan_accuracy
      value: 78.79239434940692
    - type: manhattan_ap
      value: 42.178124350579
    - type: manhattan_f1
      value: 43.16231513602337
    - type: manhattan_precision
      value: 32.99832495812395
    - type: manhattan_recall
      value: 62.37467018469657
    - type: max_accuracy
      value: 78.84007867914407
    - type: max_ap
      value: 42.21836359699547
    - type: max_f1
      value: 43.1781412906705
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 82.51445647533667
    - type: cos_sim_ap
      value: 69.65701766911302
    - type: cos_sim_f1
      value: 62.92060699362217
    - type: cos_sim_precision
      value: 60.046173219532676
    - type: cos_sim_recall
      value: 66.08407761010163
    - type: dot_accuracy
      value: 82.51445647533667
    - type: dot_ap
      value: 69.6569952654014
    - type: dot_f1
      value: 62.92060699362217
    - type: dot_precision
      value: 60.046173219532676
    - type: dot_recall
      value: 66.08407761010163
    - type: euclidean_accuracy
      value: 82.51445647533667
    - type: euclidean_ap
      value: 69.65697749857492
    - type: euclidean_f1
      value: 62.92060699362217
    - type: euclidean_precision
      value: 60.046173219532676
    - type: euclidean_recall
      value: 66.08407761010163
    - type: manhattan_accuracy
      value: 82.52221834128925
    - type: manhattan_ap
      value: 69.65965534790995
    - type: manhattan_f1
      value: 62.865817064991006
    - type: manhattan_precision
      value: 58.04811265401917
    - type: manhattan_recall
      value: 68.55558977517708
    - type: max_accuracy
      value: 82.52221834128925
    - type: max_ap
      value: 69.65965534790995
    - type: max_f1
      value: 62.92060699362217
---
