mteb license:mit model-index region:us
---
license: mit
tags:
- mteb
model-index:
- name: mpnet_3_300_bi_normalise_main
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 65.6865671641791
    - type: ap
      value: 28.04126838012943
    - type: f1
      value: 59.309850663425564
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.007025
    - type: ap
      value: 61.85427490258544
    - type: f1
      value: 66.8488072684233
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.23
    - type: f1
      value: 32.75315515971823
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 23.400000000000002
    - type: map_at_10
      value: 37.995000000000005
    - type: map_at_100
      value: 39.093
    - type: map_at_1000
      value: 39.108
    - type: map_at_3
      value: 33.345
    - type: map_at_5
      value: 35.894999999999996
    - type: mrr_at_1
      value: 24.04
    - type: mrr_at_10
      value: 38.217
    - type: mrr_at_100
      value: 39.315
    - type: mrr_at_1000
      value: 39.33
    - type: mrr_at_3
      value: 33.582
    - type: mrr_at_5
      value: 36.120999999999995
    - type: ndcg_at_1
      value: 23.400000000000002
    - type: ndcg_at_10
      value: 46.367999999999995
    - type: ndcg_at_100
      value: 51.459999999999994
    - type: ndcg_at_1000
      value: 51.849000000000004
    - type: ndcg_at_3
      value: 36.683
    - type: ndcg_at_5
      value: 41.311
    - type: precision_at_1
      value: 23.400000000000002
    - type: precision_at_10
      value: 7.3260000000000005
    - type: precision_at_100
      value: 0.964
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.458
    - type: precision_at_5
      value: 11.536
    - type: recall_at_1
      value: 23.400000000000002
    - type: recall_at_10
      value: 73.257
    - type: recall_at_100
      value: 96.444
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 46.373
    - type: recall_at_5
      value: 57.681000000000004
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.100967823968105
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 25.746974843516373
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.20457407639654
    - type: mrr
      value: 67.88429406850459
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 77.98350876563916
    - type: cos_sim_spearman
      value: 74.97339506665477
    - type: euclidean_pearson
      value: 77.11245136181245
    - type: euclidean_spearman
      value: 74.97339506665477
    - type: manhattan_pearson
      value: 77.07256110422662
    - type: manhattan_spearman
      value: 75.23846134733367
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.46753246753246
    - type: f1
      value: 71.53921122667349
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.828680696715345
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 24.08897068127219
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.455
    - type: map_at_10
      value: 28.976000000000003
    - type: map_at_100
      value: 30.09
    - type: map_at_1000
      value: 30.237000000000002
    - type: map_at_3
      value: 26.124000000000002
    - type: map_at_5
      value: 27.788
    - type: mrr_at_1
      value: 26.753
    - type: mrr_at_10
      value: 34.041
    - type: mrr_at_100
      value: 34.814
    - type: mrr_at_1000
      value: 34.885
    - type: mrr_at_3
      value: 31.545
    - type: mrr_at_5
      value: 33.011
    - type: ndcg_at_1
      value: 26.753
    - type: ndcg_at_10
      value: 34.188
    - type: ndcg_at_100
      value: 39.204
    - type: ndcg_at_1000
      value: 42.175000000000004
    - type: ndcg_at_3
      value: 29.787999999999997
    - type: ndcg_at_5
      value: 31.929999999999996
    - type: precision_at_1
      value: 26.753
    - type: precision_at_10
      value: 6.781
    - type: precision_at_100
      value: 1.173
    - type: precision_at_1000
      value: 0.178
    - type: precision_at_3
      value: 14.449000000000002
    - type: precision_at_5
      value: 10.815
    - type: recall_at_1
      value: 21.455
    - type: recall_at_10
      value: 43.883
    - type: recall_at_100
      value: 66.625
    - type: recall_at_1000
      value: 87.004
    - type: recall_at_3
      value: 31.039
    - type: recall_at_5
      value: 36.929
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 14.31
    - type: map_at_10
      value: 19.832
    - type: map_at_100
      value: 20.825
    - type: map_at_1000
      value: 20.948
    - type: map_at_3
      value: 18.102
    - type: map_at_5
      value: 19.062
    - type: mrr_at_1
      value: 17.962
    - type: mrr_at_10
      value: 23.319000000000003
    - type: mrr_at_100
      value: 24.201
    - type: mrr_at_1000
      value: 24.276
    - type: mrr_at_3
      value: 21.497
    - type: mrr_at_5
      value: 22.548000000000002
    - type: ndcg_at_1
      value: 17.962
    - type: ndcg_at_10
      value: 23.413999999999998
    - type: ndcg_at_100
      value: 28.021
    - type: ndcg_at_1000
      value: 31.069999999999997
    - type: ndcg_at_3
      value: 20.339
    - type: ndcg_at_5
      value: 21.75
    - type: precision_at_1
      value: 17.962
    - type: precision_at_10
      value: 4.465
    - type: precision_at_100
      value: 0.843
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 9.83
    - type: precision_at_5
      value: 7.1209999999999996
    - type: recall_at_1
      value: 14.31
    - type: recall_at_10
      value: 30.576999999999998
    - type: recall_at_100
      value: 50.807
    - type: recall_at_1000
      value: 71.946
    - type: recall_at_3
      value: 21.866
    - type: recall_at_5
      value: 25.573
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.893
    - type: map_at_10
      value: 32.838
    - type: map_at_100
      value: 34.038000000000004
    - type: map_at_1000
      value: 34.142
    - type: map_at_3
      value: 30.171999999999997
    - type: map_at_5
      value: 31.813000000000002
    - type: mrr_at_1
      value: 28.84
    - type: mrr_at_10
      value: 36.015
    - type: mrr_at_100
      value: 37.0
    - type: mrr_at_1000
      value: 37.068
    - type: mrr_at_3
      value: 33.584
    - type: mrr_at_5
      value: 35.120000000000005
    - type: ndcg_at_1
      value: 28.84
    - type: ndcg_at_10
      value: 37.489
    - type: ndcg_at_100
      value: 42.986999999999995
    - type: ndcg_at_1000
      value: 45.363
    - type: ndcg_at_3
      value: 32.659
    - type: ndcg_at_5
      value: 35.295
    - type: precision_at_1
      value: 28.84
    - type: precision_at_10
      value: 6.176
    - type: precision_at_100
      value: 0.9809999999999999
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 14.524999999999999
    - type: precision_at_5
      value: 10.445
    - type: recall_at_1
      value: 24.893
    - type: recall_at_10
      value: 48.411
    - type: recall_at_100
      value: 72.831
    - type: recall_at_1000
      value: 90.19800000000001
    - type: recall_at_3
      value: 35.562
    - type: recall_at_5
      value: 42.081
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.203
    - type: map_at_10
      value: 16.617
    - type: map_at_100
      value: 17.427
    - type: map_at_1000
      value: 17.538
    - type: map_at_3
      value: 15.364
    - type: map_at_5
      value: 16.085
    - type: mrr_at_1
      value: 13.333
    - type: mrr_at_10
      value: 17.737
    - type: mrr_at_100
      value: 18.567
    - type: mrr_at_1000
      value: 18.666
    - type: mrr_at_3
      value: 16.478
    - type: mrr_at_5
      value: 17.218
    - type: ndcg_at_1
      value: 13.333
    - type: ndcg_at_10
      value: 19.207
    - type: ndcg_at_100
      value: 23.669
    - type: ndcg_at_1000
      value: 27.002
    - type: ndcg_at_3
      value: 16.68
    - type: ndcg_at_5
      value: 17.977
    - type: precision_at_1
      value: 13.333
    - type: precision_at_10
      value: 2.96
    - type: precision_at_100
      value: 0.557
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 7.119000000000001
    - type: precision_at_5
      value: 5.04
    - type: recall_at_1
      value: 12.203
    - type: recall_at_10
      value: 26.096000000000004
    - type: recall_at_100
      value: 47.372
    - type: recall_at_1000
      value: 73.515
    - type: recall_at_3
      value: 19.322
    - type: recall_at_5
      value: 22.439
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.106999999999999
    - type: map_at_10
      value: 8.903
    - type: map_at_100
      value: 9.844
    - type: map_at_1000
      value: 9.968
    - type: map_at_3
      value: 7.654
    - type: map_at_5
      value: 8.369
    - type: mrr_at_1
      value: 6.841
    - type: mrr_at_10
      value: 11.274000000000001
    - type: mrr_at_100
      value: 12.173
    - type: mrr_at_1000
      value: 12.276
    - type: mrr_at_3
      value: 9.701
    - type: mrr_at_5
      value: 10.585
    - type: ndcg_at_1
      value: 6.841
    - type: ndcg_at_10
      value: 11.635
    - type: ndcg_at_100
      value: 16.616
    - type: ndcg_at_1000
      value: 20.149
    - type: ndcg_at_3
      value: 9.115
    - type: ndcg_at_5
      value: 10.366
    - type: precision_at_1
      value: 6.841
    - type: precision_at_10
      value: 2.4
    - type: precision_at_100
      value: 0.582
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 4.768
    - type: precision_at_5
      value: 3.682
    - type: recall_at_1
      value: 5.106999999999999
    - type: recall_at_10
      value: 17.662
    - type: recall_at_100
      value: 40.219
    - type: recall_at_1000
      value: 66.349
    - type: recall_at_3
      value: 11.0
    - type: recall_at_5
      value: 14.097999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.086
    - type: map_at_10
      value: 24.15
    - type: map_at_100
      value: 25.358999999999998
    - type: map_at_1000
      value: 25.497999999999998
    - type: map_at_3
      value: 21.761
    - type: map_at_5
      value: 23.067999999999998
    - type: mrr_at_1
      value: 22.233
    - type: mrr_at_10
      value: 28.584
    - type: mrr_at_100
      value: 29.526999999999997
    - type: mrr_at_1000
      value: 29.603
    - type: mrr_at_3
      value: 26.243
    - type: mrr_at_5
      value: 27.61
    - type: ndcg_at_1
      value: 22.233
    - type: ndcg_at_10
      value: 28.704
    - type: ndcg_at_100
      value: 34.58
    - type: ndcg_at_1000
      value: 37.639
    - type: ndcg_at_3
      value: 24.542
    - type: ndcg_at_5
      value: 26.456000000000003
    - type: precision_at_1
      value: 22.233
    - type: precision_at_10
      value: 5.390000000000001
    - type: precision_at_100
      value: 1.006
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 11.55
    - type: precision_at_5
      value: 8.527
    - type: recall_at_1
      value: 18.086
    - type: recall_at_10
      value: 38.080999999999996
    - type: recall_at_100
      value: 64.474
    - type: recall_at_1000
      value: 85.397
    - type: recall_at_3
      value: 26.228
    - type: recall_at_5
      value: 31.127
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.522
    - type: map_at_10
      value: 18.201
    - type: map_at_100
      value: 19.339000000000002
    - type: map_at_1000
      value: 19.471
    - type: map_at_3
      value: 16.059
    - type: map_at_5
      value: 17.166
    - type: mrr_at_1
      value: 15.639
    - type: mrr_at_10
      value: 21.688
    - type: mrr_at_100
      value: 22.666
    - type: mrr_at_1000
      value: 22.75
    - type: mrr_at_3
      value: 19.559
    - type: mrr_at_5
      value: 20.677
    - type: ndcg_at_1
      value: 15.639
    - type: ndcg_at_10
      value: 22.232
    - type: ndcg_at_100
      value: 27.803
    - type: ndcg_at_1000
      value: 31.186999999999998
    - type: ndcg_at_3
      value: 18.288
    - type: ndcg_at_5
      value: 19.962
    - type: precision_at_1
      value: 15.639
    - type: precision_at_10
      value: 4.338
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 8.828
    - type: precision_at_5
      value: 6.644
    - type: recall_at_1
      value: 12.522
    - type: recall_at_10
      value: 31.137999999999998
    - type: recall_at_100
      value: 55.745999999999995
    - type: recall_at_1000
      value: 79.945
    - type: recall_at_3
      value: 20.105
    - type: recall_at_5
      value: 24.315
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.380416666666664
    - type: map_at_10
      value: 18.699916666666667
    - type: map_at_100
      value: 19.68725
    - type: map_at_1000
      value: 19.815916666666666
    - type: map_at_3
      value: 16.937416666666664
    - type: map_at_5
      value: 17.940250000000002
    - type: mrr_at_1
      value: 16.226000000000003
    - type: mrr_at_10
      value: 21.661833333333334
    - type: mrr_at_100
      value: 22.536916666666666
    - type: mrr_at_1000
      value: 22.625166666666665
    - type: mrr_at_3
      value: 19.896250000000002
    - type: mrr_at_5
      value: 20.922416666666667
    - type: ndcg_at_1
      value: 16.226000000000003
    - type: ndcg_at_10
      value: 22.22533333333333
    - type: ndcg_at_100
      value: 27.107083333333332
    - type: ndcg_at_1000
      value: 30.357916666666668
    - type: ndcg_at_3
      value: 19.040083333333328
    - type: ndcg_at_5
      value: 20.576083333333337
    - type: precision_at_1
      value: 16.226000000000003
    - type: precision_at_10
      value: 4.0544166666666674
    - type: precision_at_100
      value: 0.7731666666666667
    - type: precision_at_1000
      value: 0.12425000000000001
    - type: precision_at_3
      value: 8.94275
    - type: precision_at_5
      value: 6.5365
    - type: recall_at_1
      value: 13.380416666666664
    - type: recall_at_10
      value: 29.85875
    - type: recall_at_100
      value: 52.161500000000004
    - type: recall_at_1000
      value: 75.80958333333334
    - type: recall_at_3
      value: 20.929416666666665
    - type: recall_at_5
      value: 24.88216666666667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.693
    - type: map_at_10
      value: 13.938999999999998
    - type: map_at_100
      value: 14.77
    - type: map_at_1000
      value: 14.87
    - type: map_at_3
      value: 12.542
    - type: map_at_5
      value: 13.331000000000001
    - type: mrr_at_1
      value: 11.503
    - type: mrr_at_10
      value: 15.722
    - type: mrr_at_100
      value: 16.566
    - type: mrr_at_1000
      value: 16.649
    - type: mrr_at_3
      value: 14.289
    - type: mrr_at_5
      value: 15.110000000000001
    - type: ndcg_at_1
      value: 11.503
    - type: ndcg_at_10
      value: 16.66
    - type: ndcg_at_100
      value: 20.779
    - type: ndcg_at_1000
      value: 23.660999999999998
    - type: ndcg_at_3
      value: 13.933000000000002
    - type: ndcg_at_5
      value: 15.232999999999999
    - type: precision_at_1
      value: 11.503
    - type: precision_at_10
      value: 2.883
    - type: precision_at_100
      value: 0.534
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.493
    - type: precision_at_5
      value: 4.662999999999999
    - type: recall_at_1
      value: 9.693
    - type: recall_at_10
      value: 23.388
    - type: recall_at_100
      value: 41.955999999999996
    - type: recall_at_1000
      value: 64.044
    - type: recall_at_3
      value: 15.775
    - type: recall_at_5
      value: 19.067
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.007
    - type: map_at_10
      value: 10.462
    - type: map_at_100
      value: 11.134
    - type: map_at_1000
      value: 11.26
    - type: map_at_3
      value: 9.379
    - type: map_at_5
      value: 9.997
    - type: mrr_at_1
      value: 9.119
    - type: mrr_at_10
      value: 12.950000000000001
    - type: mrr_at_100
      value: 13.63
    - type: mrr_at_1000
      value: 13.735
    - type: mrr_at_3
      value: 11.757
    - type: mrr_at_5
      value: 12.411
    - type: ndcg_at_1
      value: 9.119
    - type: ndcg_at_10
      value: 12.862000000000002
    - type: ndcg_at_100
      value: 16.544
    - type: ndcg_at_1000
      value: 20.183
    - type: ndcg_at_3
      value: 10.850999999999999
    - type: ndcg_at_5
      value: 11.802
    - type: precision_at_1
      value: 9.119
    - type: precision_at_10
      value: 2.4570000000000003
    - type: precision_at_100
      value: 0.516
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 5.322
    - type: precision_at_5
      value: 3.923
    - type: recall_at_1
      value: 7.007
    - type: recall_at_10
      value: 17.72
    - type: recall_at_100
      value: 34.971999999999994
    - type: recall_at_1000
      value: 62.0
    - type: recall_at_3
      value: 12.124
    - type: recall_at_5
      value: 14.580000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.741999999999999
    - type: map_at_10
      value: 16.122
    - type: map_at_100
      value: 17.069000000000003
    - type: map_at_1000
      value: 17.19
    - type: map_at_3
      value: 14.687
    - type: map_at_5
      value: 15.49
    - type: mrr_at_1
      value: 14.179
    - type: mrr_at_10
      value: 19.064
    - type: mrr_at_100
      value: 19.997999999999998
    - type: mrr_at_1000
      value: 20.086000000000002
    - type: mrr_at_3
      value: 17.522
    - type: mrr_at_5
      value: 18.398999999999997
    - type: ndcg_at_1
      value: 14.179
    - type: ndcg_at_10
      value: 19.200999999999997
    - type: ndcg_at_100
      value: 24.243000000000002
    - type: ndcg_at_1000
      value: 27.589000000000002
    - type: ndcg_at_3
      value: 16.394000000000002
    - type: ndcg_at_5
      value: 17.678
    - type: precision_at_1
      value: 14.179
    - type: precision_at_10
      value: 3.2840000000000003
    - type: precision_at_100
      value: 0.654
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 7.587000000000001
    - type: precision_at_5
      value: 5.41
    - type: recall_at_1
      value: 11.741999999999999
    - type: recall_at_10
      value: 25.962000000000003
    - type: recall_at_100
      value: 49.189
    - type: recall_at_1000
      value: 73.886
    - type: recall_at_3
      value: 17.977
    - type: recall_at_5
      value: 21.298000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.015
    - type: map_at_10
      value: 20.263
    - type: map_at_100
      value: 21.39
    - type: map_at_1000
      value: 21.586
    - type: map_at_3
      value: 18.796
    - type: map_at_5
      value: 19.494
    - type: mrr_at_1
      value: 17.589
    - type: mrr_at_10
      value: 23.97
    - type: mrr_at_100
      value: 24.879
    - type: mrr_at_1000
      value: 24.973
    - type: mrr_at_3
      value: 22.563
    - type: mrr_at_5
      value: 23.235
    - type: ndcg_at_1
      value: 17.589
    - type: ndcg_at_10
      value: 24.297
    - type: ndcg_at_100
      value: 29.496
    - type: ndcg_at_1000
      value: 33.336
    - type: ndcg_at_3
      value: 21.978
    - type: ndcg_at_5
      value: 22.746
    - type: precision_at_1
      value: 17.589
    - type: precision_at_10
      value: 4.7829999999999995
    - type: precision_at_100
      value: 1.047
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 10.804
    - type: precision_at_5
      value: 7.51
    - type: recall_at_1
      value: 14.015
    - type: recall_at_10
      value: 31.61
    - type: recall_at_100
      value: 56.559000000000005
    - type: recall_at_1000
      value: 82.733
    - type: recall_at_3
      value: 23.963
    - type: recall_at_5
      value: 26.512
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.532
    - type: map_at_10
      value: 14.096
    - type: map_at_100
      value: 14.962
    - type: map_at_1000
      value: 15.082999999999998
    - type: map_at_3
      value: 12.609
    - type: map_at_5
      value: 13.62
    - type: mrr_at_1
      value: 10.721
    - type: mrr_at_10
      value: 15.578
    - type: mrr_at_100
      value: 16.422
    - type: mrr_at_1000
      value: 16.535
    - type: mrr_at_3
      value: 14.017
    - type: mrr_at_5
      value: 15.145
    - type: ndcg_at_1
      value: 10.721
    - type: ndcg_at_10
      value: 16.814999999999998
    - type: ndcg_at_100
      value: 21.343
    - type: ndcg_at_1000
      value: 24.941
    - type: ndcg_at_3
      value: 13.914000000000001
    - type: ndcg_at_5
      value: 15.717999999999998
    - type: precision_at_1
      value: 10.721
    - type: precision_at_10
      value: 2.7359999999999998
    - type: precision_at_100
      value: 0.532
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 6.038
    - type: precision_at_5
      value: 4.658
    - type: recall_at_1
      value: 9.532
    - type: recall_at_10
      value: 23.777
    - type: recall_at_100
      value: 45.188
    - type: recall_at_1000
      value: 72.698
    - type: recall_at_3
      value: 16.192
    - type: recall_at_5
      value: 20.567
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.7299999999999995
    - type: map_at_10
      value: 12.158
    - type: map_at_100
      value: 13.63
    - type: map_at_1000
      value: 13.846
    - type: map_at_3
      value: 9.788
    - type: map_at_5
      value: 10.949
    - type: mrr_at_1
      value: 14.918999999999999
    - type: mrr_at_10
      value: 24.043999999999997
    - type: mrr_at_100
      value: 25.139
    - type: mrr_at_1000
      value: 25.206
    - type: mrr_at_3
      value: 20.630000000000003
    - type: mrr_at_5
      value: 22.441
    - type: ndcg_at_1
      value: 14.918999999999999
    - type: ndcg_at_10
      value: 18.223
    - type: ndcg_at_100
      value: 24.981
    - type: ndcg_at_1000
      value: 29.218
    - type: ndcg_at_3
      value: 13.672999999999998
    - type: ndcg_at_5
      value: 15.293000000000001
    - type: precision_at_1
      value: 14.918999999999999
    - type: precision_at_10
      value: 6.1240000000000006
    - type: precision_at_100
      value: 1.344
    - type: precision_at_1000
      value: 0.211
    - type: precision_at_3
      value: 10.270999999999999
    - type: precision_at_5
      value: 8.391
    - type: recall_at_1
      value: 6.7299999999999995
    - type: recall_at_10
      value: 23.587
    - type: recall_at_100
      value: 47.636
    - type: recall_at_1000
      value: 71.951
    - type: recall_at_3
      value: 12.895999999999999
    - type: recall_at_5
      value: 16.967
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.1919999999999997
    - type: map_at_10
      value: 8.308
    - type: map_at_100
      value: 11.503
    - type: map_at_1000
      value: 12.409
    - type: map_at_3
      value: 5.695
    - type: map_at_5
      value: 6.779
    - type: mrr_at_1
      value: 35.75
    - type: mrr_at_10
      value: 46.782000000000004
    - type: mrr_at_100
      value: 47.58
    - type: mrr_at_1000
      value: 47.612
    - type: mrr_at_3
      value: 43.625
    - type: mrr_at_5
      value: 45.638
    - type: ndcg_at_1
      value: 25.5
    - type: ndcg_at_10
      value: 21.609
    - type: ndcg_at_100
      value: 24.111
    - type: ndcg_at_1000
      value: 30.723
    - type: ndcg_at_3
      value: 23.761
    - type: ndcg_at_5
      value: 22.74
    - type: precision_at_1
      value: 35.75
    - type: precision_at_10
      value: 19.775000000000002
    - type: precision_at_100
      value: 6.18
    - type: precision_at_1000
      value: 1.379
    - type: precision_at_3
      value: 28.749999999999996
    - type: precision_at_5
      value: 25.5
    - type: recall_at_1
      value: 3.1919999999999997
    - type: recall_at_10
      value: 13.405000000000001
    - type: recall_at_100
      value: 29.939
    - type: recall_at_1000
      value: 52.425999999999995
    - type: recall_at_3
      value: 7.087000000000001
    - type: recall_at_5
      value: 9.263
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.51499999999999
    - type: f1
      value: 42.15882226016995
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.620999999999999
    - type: map_at_10
      value: 19.061
    - type: map_at_100
      value: 19.911
    - type: map_at_1000
      value: 19.980999999999998
    - type: map_at_3
      value: 16.908
    - type: map_at_5
      value: 18.166
    - type: mrr_at_1
      value: 13.501
    - type: mrr_at_10
      value: 20.278
    - type: mrr_at_100
      value: 21.134
    - type: mrr_at_1000
      value: 21.198
    - type: mrr_at_3
      value: 18.022
    - type: mrr_at_5
      value: 19.344
    - type: ndcg_at_1
      value: 13.501
    - type: ndcg_at_10
      value: 23.04
    - type: ndcg_at_100
      value: 27.532
    - type: ndcg_at_1000
      value: 29.616999999999997
    - type: ndcg_at_3
      value: 18.622
    - type: ndcg_at_5
      value: 20.887
    - type: precision_at_1
      value: 13.501
    - type: precision_at_10
      value: 3.734
    - type: precision_at_100
      value: 0.619
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 8.031
    - type: precision_at_5
      value: 6.022
    - type: recall_at_1
      value: 12.620999999999999
    - type: recall_at_10
      value: 34.391
    - type: recall_at_100
      value: 55.645
    - type: recall_at_1000
      value: 72.03399999999999
    - type: recall_at_3
      value: 22.445
    - type: recall_at_5
      value: 27.881
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.031
    - type: map_at_10
      value: 11.713999999999999
    - type: map_at_100
      value: 12.864999999999998
    - type: map_at_1000
      value: 13.088
    - type: map_at_3
      value: 9.976
    - type: map_at_5
      value: 10.945
    - type: mrr_at_1
      value: 14.043
    - type: mrr_at_10
      value: 20.127
    - type: mrr_at_100
      value: 21.171
    - type: mrr_at_1000
      value: 21.276
    - type: mrr_at_3
      value: 18.081
    - type: mrr_at_5
      value: 19.216
    - type: ndcg_at_1
      value: 14.043
    - type: ndcg_at_10
      value: 16.070999999999998
    - type: ndcg_at_100
      value: 21.863
    - type: ndcg_at_1000
      value: 26.691
    - type: ndcg_at_3
      value: 13.617
    - type: ndcg_at_5
      value: 14.585999999999999
    - type: precision_at_1
      value: 14.043
    - type: precision_at_10
      value: 4.552
    - type: precision_at_100
      value: 1.042
    - type: precision_at_1000
      value: 0.188
    - type: precision_at_3
      value: 9.259
    - type: precision_at_5
      value: 7.005999999999999
    - type: recall_at_1
      value: 7.031
    - type: recall_at_10
      value: 20.589
    - type: recall_at_100
      value: 43.425999999999995
    - type: recall_at_1000
      value: 73.048
    - type: recall_at_3
      value: 12.812999999999999
    - type: recall_at_5
      value: 16.205
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.072000000000001
    - type: map_at_10
      value: 18.454
    - type: map_at_100
      value: 19.220000000000002
    - type: map_at_1000
      value: 19.325
    - type: map_at_3
      value: 16.906
    - type: map_at_5
      value: 17.757
    - type: mrr_at_1
      value: 26.144000000000002
    - type: mrr_at_10
      value: 32.269999999999996
    - type: mrr_at_100
      value: 33.001999999999995
    - type: mrr_at_1000
      value: 33.07
    - type: mrr_at_3
      value: 30.526999999999997
    - type: mrr_at_5
      value: 31.505
    - type: ndcg_at_1
      value: 26.144000000000002
    - type: ndcg_at_10
      value: 24.024
    - type: ndcg_at_100
      value: 27.79
    - type: ndcg_at_1000
      value: 30.493
    - type: ndcg_at_3
      value: 20.944
    - type: ndcg_at_5
      value: 22.431
    - type: precision_at_1
      value: 26.144000000000002
    - type: precision_at_10
      value: 5.383
    - type: precision_at_100
      value: 0.8410000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 13.306000000000001
    - type: precision_at_5
      value: 9.167
    - type: recall_at_1
      value: 13.072000000000001
    - type: recall_at_10
      value: 26.913999999999998
    - type: recall_at_100
      value: 42.046
    - type: recall_at_1000
      value: 60.182
    - type: recall_at_3
      value: 19.959
    - type: recall_at_5
      value: 22.917
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 68.328
    - type: ap
      value: 62.53568270720666
    - type: f1
      value: 68.13780615543227
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.678
    - type: map_at_10
      value: 10.087
    - type: map_at_100
      value: 10.913
    - type: map_at_1000
      value: 11.017000000000001
    - type: map_at_3
      value: 8.476
    - type: map_at_5
      value: 9.411
    - type: mrr_at_1
      value: 5.86
    - type: mrr_at_10
      value: 10.34
    - type: mrr_at_100
      value: 11.179
    - type: mrr_at_1000
      value: 11.279
    - type: mrr_at_3
      value: 8.718
    - type: mrr_at_5
      value: 9.648
    - type: ndcg_at_1
      value: 5.845000000000001
    - type: ndcg_at_10
      value: 12.801000000000002
    - type: ndcg_at_100
      value: 17.405
    - type: ndcg_at_1000
      value: 20.534
    - type: ndcg_at_3
      value: 9.479
    - type: ndcg_at_5
      value: 11.152
    - type: precision_at_1
      value: 5.845000000000001
    - type: precision_at_10
      value: 2.2089999999999996
    - type: precision_at_100
      value: 0.461
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 4.222
    - type: precision_at_5
      value: 3.3640000000000003
    - type: recall_at_1
      value: 5.678
    - type: recall_at_10
      value: 21.240000000000002
    - type: recall_at_100
      value: 43.875
    - type: recall_at_1000
      value: 69.011
    - type: recall_at_3
      value: 12.141
    - type: recall_at_5
      value: 16.178
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.56041951664386
    - type: f1
      value: 87.00152417080298
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 55.54491564067489
    - type: f1
      value: 38.08722415882758
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.094821788836576
    - type: f1
      value: 60.45065028350709
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.30127774041695
    - type: f1
      value: 69.75836812124443
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.54283175725888
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.32735432360623
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.245394641935835
    - type: mrr
      value: 31.220929230846338
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.601
    - type: map_at_10
      value: 7.33
    - type: map_at_100
      value: 9.408
    - type: map_at_1000
      value: 10.718
    - type: map_at_3
      value: 5.641
    - type: map_at_5
      value: 6.424
    - type: mrr_at_1
      value: 31.579
    - type: mrr_at_10
      value: 41.708
    - type: mrr_at_100
      value: 42.57
    - type: mrr_at_1000
      value: 42.631
    - type: mrr_at_3
      value: 39.577
    - type: mrr_at_5
      value: 40.861999999999995
    - type: ndcg_at_1
      value: 29.412
    - type: ndcg_at_10
      value: 23.651
    - type: ndcg_at_100
      value: 22.66
    - type: ndcg_at_1000
      value: 32.440999999999995
    - type: ndcg_at_3
      value: 27.916999999999998
    - type: ndcg_at_5
      value: 26.144000000000002
    - type: precision_at_1
      value: 31.579
    - type: precision_at_10
      value: 17.554
    - type: precision_at_100
      value: 6.409
    - type: precision_at_1000
      value: 1.973
    - type: precision_at_3
      value: 27.348
    - type: precision_at_5
      value: 23.158
    - type: recall_at_1
      value: 3.601
    - type: recall_at_10
      value: 11.393
    - type: recall_at_100
      value: 24.736
    - type: recall_at_1000
      value: 60.032
    - type: recall_at_3
      value: 6.834999999999999
    - type: recall_at_5
      value: 8.635
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.07
    - type: map_at_10
      value: 13.408999999999999
    - type: map_at_100
      value: 14.584
    - type: map_at_1000
      value: 14.692
    - type: map_at_3
      value: 11.337
    - type: map_at_5
      value: 12.426
    - type: mrr_at_1
      value: 9.299
    - type: mrr_at_10
      value: 15.012
    - type: mrr_at_100
      value: 16.117
    - type: mrr_at_1000
      value: 16.207
    - type: mrr_at_3
      value: 12.881
    - type: mrr_at_5
      value: 14.005
    - type: ndcg_at_1
      value: 9.299
    - type: ndcg_at_10
      value: 17.080000000000002
    - type: ndcg_at_100
      value: 23.04
    - type: ndcg_at_1000
      value: 25.948
    - type: ndcg_at_3
      value: 12.787
    - type: ndcg_at_5
      value: 14.74
    - type: precision_at_1
      value: 9.299
    - type: precision_at_10
      value: 3.2009999999999996
    - type: precision_at_100
      value: 0.656
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 6.035
    - type: precision_at_5
      value: 4.71
    - type: recall_at_1
      value: 8.07
    - type: recall_at_10
      value: 26.934
    - type: recall_at_100
      value: 54.581999999999994
    - type: recall_at_1000
      value: 76.888
    - type: recall_at_3
      value: 15.501000000000001
    - type: recall_at_5
      value: 20.063
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 62.815
    - type: map_at_10
      value: 75.652
    - type: map_at_100
      value: 76.48
    - type: map_at_1000
      value: 76.51
    - type: map_at_3
      value: 72.765
    - type: map_at_5
      value: 74.547
    - type: mrr_at_1
      value: 72.41
    - type: mrr_at_10
      value: 79.68499999999999
    - type: mrr_at_100
      value: 79.967
    - type: mrr_at_1000
      value: 79.972
    - type: mrr_at_3
      value: 78.292
    - type: mrr_at_5
      value: 79.205
    - type: ndcg_at_1
      value: 72.42
    - type: ndcg_at_10
      value: 80.226
    - type: ndcg_at_100
      value: 82.50699999999999
    - type: ndcg_at_1000
      value: 82.842
    - type: ndcg_at_3
      value: 76.775
    - type: ndcg_at_5
      value: 78.613
    - type: precision_at_1
      value: 72.42
    - type: precision_at_10
      value: 12.184000000000001
    - type: precision_at_100
      value: 1.466
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.5
    - type: precision_at_5
      value: 22.137999999999998
    - type: recall_at_1
      value: 62.815
    - type: recall_at_10
      value: 89.1
    - type: recall_at_100
      value: 97.725
    - type: recall_at_1000
      value: 99.59
    - type: recall_at_3
      value: 79.208
    - type: recall_at_5
      value: 84.316
    - type: map_at_1
      value: 3.148
    - type: map_at_10
      value: 6.977
    - type: map_at_100
      value: 8.414000000000001
    - type: map_at_1000
      value: 8.672
    - type: map_at_3
      value: 5.11
    - type: map_at_5
      value: 5.949
    - type: mrr_at_1
      value: 15.4
    - type: mrr_at_10
      value: 22.531000000000002
    - type: mrr_at_100
      value: 23.873
    - type: mrr_at_1000
      value: 23.959
    - type: mrr_at_3
      value: 19.783
    - type: mrr_at_5
      value: 21.263
    - type: ndcg_at_1
      value: 15.4
    - type: ndcg_at_10
      value: 12.418999999999999
    - type: ndcg_at_100
      value: 18.972
    - type: ndcg_at_1000
      value: 24.263
    - type: ndcg_at_3
      value: 11.581
    - type: ndcg_at_5
      value: 10.097000000000001
    - type: precision_at_1
      value: 15.4
    - type: precision_at_10
      value: 6.4399999999999995
    - type: precision_at_100
      value: 1.595
    - type: precision_at_1000
      value: 0.28800000000000003
    - type: precision_at_3
      value: 10.533
    - type: precision_at_5
      value: 8.66
    - type: recall_at_1
      value: 3.148
    - type: recall_at_10
      value: 13.043
    - type: recall_at_100
      value: 32.342
    - type: recall_at_1000
      value: 58.431999999999995
    - type: recall_at_3
      value: 6.422999999999999
    - type: recall_at_5
      value: 8.773
    - type: map_at_1
      value: 0.122
    - type: map_at_10
      value: 0.8380000000000001
    - type: map_at_100
      value: 4.359
    - type: map_at_1000
      value: 11.024000000000001
    - type: map_at_3
      value: 0.33
    - type: map_at_5
      value: 0.488
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 61.269
    - type: mrr_at_100
      value: 61.775999999999996
    - type: mrr_at_1000
      value: 61.789
    - type: mrr_at_3
      value: 60.0
    - type: mrr_at_5
      value: 60.4
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 42.097
    - type: ndcg_at_100
      value: 32.121
    - type: ndcg_at_1000
      value: 30.064
    - type: ndcg_at_3
      value: 47.05
    - type: ndcg_at_5
      value: 45.095
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 45.2
    - type: precision_at_100
      value: 33.82
    - type: precision_at_1000
      value: 14.707999999999998
    - type: precision_at_3
      value: 52.666999999999994
    - type: precision_at_5
      value: 48.8
    - type: recall_at_1
      value: 0.122
    - type: recall_at_10
      value: 1.0699999999999998
    - type: recall_at_100
      value: 7.382
    - type: recall_at_1000
      value: 29.464000000000002
    - type: recall_at_3
      value: 0.39699999999999996
    - type: recall_at_5
      value: 0.598
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 41.40274475749348
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 45.36558797926236
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.9591742900809
    - type: cos_sim_spearman
      value: 65.2393736828013
    - type: euclidean_pearson
      value: 71.93106026843658
    - type: euclidean_spearman
      value: 65.23946562040364
    - type: manhattan_pearson
      value: 71.08424184461768
    - type: manhattan_spearman
      value: 65.01099207618003
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 75.89296742979977
    - type: cos_sim_spearman
      value: 67.91111133885116
    - type: euclidean_pearson
      value: 72.83363008777634
    - type: euclidean_spearman
      value: 67.91239581159331
    - type: manhattan_pearson
      value: 72.16796694518214
    - type: manhattan_spearman
      value: 67.89208953134717
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.92938262292805
    - type: cos_sim_spearman
      value: 78.27549006281241
    - type: euclidean_pearson
      value: 77.92233868049291
    - type: euclidean_spearman
      value: 78.27548985407766
    - type: manhattan_pearson
      value: 78.13380526389417
    - type: manhattan_spearman
      value: 78.53594391632303
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.64082827417963
    - type: cos_sim_spearman
      value: 72.84464317386625
    - type: euclidean_pearson
      value: 76.42666008614871
    - type: euclidean_spearman
      value: 72.84463348486912
    - type: manhattan_pearson
      value: 76.07228202147503
    - type: manhattan_spearman
      value: 72.77147467020583
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.80175783397232
    - type: cos_sim_spearman
      value: 81.1395072429369
    - type: euclidean_pearson
      value: 81.1207213416848
    - type: euclidean_spearman
      value: 81.13950373549197
    - type: manhattan_pearson
      value: 80.70637859712825
    - type: manhattan_spearman
      value: 80.77272480740696
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.15681332201778
    - type: cos_sim_spearman
      value: 76.62657807402795
    - type: euclidean_pearson
      value: 76.65599360457624
    - type: euclidean_spearman
      value: 76.62684964660313
    - type: manhattan_pearson
      value: 76.4684205504751
    - type: manhattan_spearman
      value: 76.48746197080307
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.16774243543202
    - type: cos_sim_spearman
      value: 83.33346918777738
    - type: euclidean_pearson
      value: 83.28296290476054
    - type: euclidean_spearman
      value: 83.33434373879857
    - type: manhattan_pearson
      value: 83.14374338850754
    - type: manhattan_spearman
      value: 83.06911006763188
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.75551611175316
    - type: cos_sim_spearman
      value: 61.07525543654076
    - type: euclidean_pearson
      value: 63.50619233372331
    - type: euclidean_spearman
      value: 61.07525543654076
    - type: manhattan_pearson
      value: 64.18612277498849
    - type: manhattan_spearman
      value: 61.84411341639111
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.9064972604624
    - type: cos_sim_spearman
      value: 75.32111671842594
    - type: euclidean_pearson
      value: 77.46089976383304
    - type: euclidean_spearman
      value: 75.32113518705334
    - type: manhattan_pearson
      value: 77.15161309764346
    - type: manhattan_spearman
      value: 75.19910900320157
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.33741829988382
    - type: mrr
      value: 91.39431556098224
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 30.139
    - type: map_at_10
      value: 37.730999999999995
    - type: map_at_100
      value: 38.665
    - type: map_at_1000
      value: 38.751999999999995
    - type: map_at_3
      value: 35.556
    - type: map_at_5
      value: 36.925000000000004
    - type: mrr_at_1
      value: 32.0
    - type: mrr_at_10
      value: 39.364
    - type: mrr_at_100
      value: 40.214
    - type: mrr_at_1000
      value: 40.289
    - type: mrr_at_3
      value: 37.389
    - type: mrr_at_5
      value: 38.772
    - type: ndcg_at_1
      value: 32.0
    - type: ndcg_at_10
      value: 41.844
    - type: ndcg_at_100
      value: 46.976
    - type: ndcg_at_1000
      value: 49.303999999999995
    - type: ndcg_at_3
      value: 37.716
    - type: ndcg_at_5
      value: 40.086
    - type: precision_at_1
      value: 32.0
    - type: precision_at_10
      value: 5.867
    - type: precision_at_100
      value: 0.8829999999999999
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 15.110999999999999
    - type: precision_at_5
      value: 10.333
    - type: recall_at_1
      value: 30.139
    - type: recall_at_10
      value: 52.917
    - type: recall_at_100
      value: 77.972
    - type: recall_at_1000
      value: 96.2
    - type: recall_at_3
      value: 41.943999999999996
    - type: recall_at_5
      value: 47.806
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.74158415841585
    - type: cos_sim_ap
      value: 92.14775153471328
    - type: cos_sim_f1
      value: 86.35650810245687
    - type: cos_sim_precision
      value: 90.4709748083242
    - type: cos_sim_recall
      value: 82.6
    - type: dot_accuracy
      value: 99.74158415841585
    - type: dot_ap
      value: 92.14775153471328
    - type: dot_f1
      value: 86.35650810245687
    - type: dot_precision
      value: 90.4709748083242
    - type: dot_recall
      value: 82.6
    - type: euclidean_accuracy
      value: 99.74158415841585
    - type: euclidean_ap
      value: 92.14775153471328
    - type: euclidean_f1
      value: 86.35650810245687
    - type: euclidean_precision
      value: 90.4709748083242
    - type: euclidean_recall
      value: 82.6
    - type: manhattan_accuracy
      value: 99.75247524752476
    - type: manhattan_ap
      value: 92.78507974555151
    - type: manhattan_f1
      value: 87.02290076335878
    - type: manhattan_precision
      value: 88.60103626943005
    - type: manhattan_recall
      value: 85.5
    - type: max_accuracy
      value: 99.75247524752476
    - type: max_ap
      value: 92.78507974555151
    - type: max_f1
      value: 87.02290076335878
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 44.43312002306653
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 31.24233740178471
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.15283231442346
    - type: mrr
      value: 42.4727845683728
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.336258546740332
    - type: cos_sim_spearman
      value: 30.445852974569153
    - type: dot_pearson
      value: 31.336258546740343
    - type: dot_spearman
      value: 30.51894557486332
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.3009999999999997
    - type: map_at_10
      value: 7.323
    - type: map_at_100
      value: 13.428
    - type: map_at_1000
      value: 15.001999999999999
    - type: map_at_3
      value: 4.340999999999999
    - type: map_at_5
      value: 5.664000000000001
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 43.934
    - type: mrr_at_100
      value: 44.984
    - type: mrr_at_1000
      value: 44.984
    - type: mrr_at_3
      value: 39.116
    - type: mrr_at_5
      value: 42.687000000000005
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 20.433
    - type: ndcg_at_100
      value: 34.909
    - type: ndcg_at_1000
      value: 46.363
    - type: ndcg_at_3
      value: 24.032999999999998
    - type: ndcg_at_5
      value: 22.93
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 17.959
    - type: precision_at_100
      value: 8.02
    - type: precision_at_1000
      value: 1.545
    - type: precision_at_3
      value: 25.169999999999998
    - type: precision_at_5
      value: 23.673
    - type: recall_at_1
      value: 2.3009999999999997
    - type: recall_at_10
      value: 12.991
    - type: recall_at_100
      value: 48.952
    - type: recall_at_1000
      value: 83.898
    - type: recall_at_3
      value: 5.3629999999999995
    - type: recall_at_5
      value: 8.519
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.15559999999999
    - type: ap
      value: 14.339341085976546
    - type: f1
      value: 54.753780679579265
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.76683644595358
    - type: f1
      value: 55.96404908693344
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 36.2783470973587
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.96340227692674
    - type: cos_sim_ap
      value: 59.41058199758212
    - type: cos_sim_f1
      value: 57.32984293193717
    - type: cos_sim_precision
      value: 52.210663198959686
    - type: cos_sim_recall
      value: 63.562005277044854
    - type: dot_accuracy
      value: 81.96340227692674
    - type: dot_ap
      value: 59.41058199758212
    - type: dot_f1
      value: 57.32984293193717
    - type: dot_precision
      value: 52.210663198959686
    - type: dot_recall
      value: 63.562005277044854
    - type: euclidean_accuracy
      value: 81.96340227692674
    - type: euclidean_ap
      value: 59.41058199758212
    - type: euclidean_f1
      value: 57.32984293193717
    - type: euclidean_precision
      value: 52.210663198959686
    - type: euclidean_recall
      value: 63.562005277044854
    - type: manhattan_accuracy
      value: 81.68325683972104
    - type: manhattan_ap
      value: 58.90711838511802
    - type: manhattan_f1
      value: 57.186223000583766
    - type: manhattan_precision
      value: 51.287958115183244
    - type: manhattan_recall
      value: 64.6174142480211
    - type: max_accuracy
      value: 81.96340227692674
    - type: max_ap
      value: 59.41058199758212
    - type: max_f1
      value: 57.32984293193717
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.8843870066364
    - type: cos_sim_ap
      value: 81.78253291412273
    - type: cos_sim_f1
      value: 74.01401187808953
    - type: cos_sim_precision
      value: 68.77271826052474
    - type: cos_sim_recall
      value: 80.12011087157376
    - type: dot_accuracy
      value: 86.8843870066364
    - type: dot_ap
      value: 81.78253377474518
    - type: dot_f1
      value: 74.01401187808953
    - type: dot_precision
      value: 68.77271826052474
    - type: dot_recall
      value: 80.12011087157376
    - type: euclidean_accuracy
      value: 86.8843870066364
    - type: euclidean_ap
      value: 81.7825333923772
    - type: euclidean_f1
      value: 74.01401187808953
    - type: euclidean_precision
      value: 68.77271826052474
    - type: euclidean_recall
      value: 80.12011087157376
    - type: manhattan_accuracy
      value: 86.98335079753173
    - type: manhattan_ap
      value: 81.90204232055142
    - type: manhattan_f1
      value: 74.17194570135747
    - type: manhattan_precision
      value: 69.99385119901619
    - type: manhattan_recall
      value: 78.88050508161379
    - type: max_accuracy
      value: 86.98335079753173
    - type: max_ap
      value: 81.90204232055142
    - type: max_f1
      value: 74.17194570135747
---
