mteb model-index region:us
---
tags:
- mteb
model-index:
- name: l3_wordllama_256
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 65.97014925373134
    - type: ap
      value: 27.33017285839569
    - type: f1
      value: 59.04330619047924
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 63.248250000000006
    - type: ap
      value: 58.695642654646576
    - type: f1
      value: 62.98826255412888
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.689999999999998
    - type: f1
      value: 31.106666192619258
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.986
    - type: map_at_10
      value: 34.634
    - type: map_at_100
      value: 35.937000000000005
    - type: map_at_1000
      value: 35.954
    - type: map_at_3
      value: 29.742
    - type: map_at_5
      value: 32.444
    - type: mrr_at_1
      value: 20.341
    - type: mrr_at_10
      value: 34.763
    - type: mrr_at_100
      value: 36.065999999999995
    - type: mrr_at_1000
      value: 36.083
    - type: mrr_at_3
      value: 29.872
    - type: mrr_at_5
      value: 32.574999999999996
    - type: ndcg_at_1
      value: 19.986
    - type: ndcg_at_10
      value: 43.074
    - type: ndcg_at_100
      value: 48.819
    - type: ndcg_at_1000
      value: 49.26
    - type: ndcg_at_3
      value: 32.934000000000005
    - type: ndcg_at_5
      value: 37.830999999999996
    - type: precision_at_1
      value: 19.986
    - type: precision_at_10
      value: 7.02
    - type: precision_at_100
      value: 0.958
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.059
    - type: precision_at_5
      value: 10.825
    - type: recall_at_1
      value: 19.986
    - type: recall_at_10
      value: 70.199
    - type: recall_at_100
      value: 95.804
    - type: recall_at_1000
      value: 99.21799999999999
    - type: recall_at_3
      value: 42.176
    - type: recall_at_5
      value: 54.125
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.64176717184799
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.06122250673383
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.808484614132844
    - type: mrr
      value: 71.09121487930351
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 74.96889982129713
    - type: cos_sim_spearman
      value: 70.34256665852179
    - type: euclidean_pearson
      value: 73.59375229907496
    - type: euclidean_spearman
      value: 70.34256665852179
    - type: manhattan_pearson
      value: 72.38820178677287
    - type: manhattan_spearman
      value: 69.3919425882689
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.56818181818181
    - type: f1
      value: 72.78107232170503
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.10380086081637
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.238238325966222
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.294999999999998
    - type: map_at_10
      value: 27.535999999999998
    - type: map_at_100
      value: 28.803
    - type: map_at_1000
      value: 28.971000000000004
    - type: map_at_3
      value: 25.029
    - type: map_at_5
      value: 26.526
    - type: mrr_at_1
      value: 24.893
    - type: mrr_at_10
      value: 32.554
    - type: mrr_at_100
      value: 33.504
    - type: mrr_at_1000
      value: 33.583
    - type: mrr_at_3
      value: 30.091
    - type: mrr_at_5
      value: 31.535999999999998
    - type: ndcg_at_1
      value: 24.893
    - type: ndcg_at_10
      value: 32.495000000000005
    - type: ndcg_at_100
      value: 38.288
    - type: ndcg_at_1000
      value: 41.559000000000005
    - type: ndcg_at_3
      value: 28.321
    - type: ndcg_at_5
      value: 30.401
    - type: precision_at_1
      value: 24.893
    - type: precision_at_10
      value: 6.109
    - type: precision_at_100
      value: 1.142
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 13.447999999999999
    - type: precision_at_5
      value: 9.927999999999999
    - type: recall_at_1
      value: 20.294999999999998
    - type: recall_at_10
      value: 42.129
    - type: recall_at_100
      value: 67.709
    - type: recall_at_1000
      value: 89.534
    - type: recall_at_3
      value: 30.148999999999997
    - type: recall_at_5
      value: 35.804
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.426
    - type: map_at_10
      value: 22.461000000000002
    - type: map_at_100
      value: 23.424
    - type: map_at_1000
      value: 23.559
    - type: map_at_3
      value: 20.643
    - type: map_at_5
      value: 21.602
    - type: mrr_at_1
      value: 20.701
    - type: mrr_at_10
      value: 26.734
    - type: mrr_at_100
      value: 27.516000000000002
    - type: mrr_at_1000
      value: 27.594
    - type: mrr_at_3
      value: 24.936
    - type: mrr_at_5
      value: 25.901000000000003
    - type: ndcg_at_1
      value: 20.701
    - type: ndcg_at_10
      value: 26.381
    - type: ndcg_at_100
      value: 30.731
    - type: ndcg_at_1000
      value: 33.603
    - type: ndcg_at_3
      value: 23.336000000000002
    - type: ndcg_at_5
      value: 24.644
    - type: precision_at_1
      value: 20.701
    - type: precision_at_10
      value: 5.006
    - type: precision_at_100
      value: 0.9339999999999999
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.315999999999999
    - type: precision_at_5
      value: 8.14
    - type: recall_at_1
      value: 16.426
    - type: recall_at_10
      value: 33.593
    - type: recall_at_100
      value: 52.746
    - type: recall_at_1000
      value: 72.15899999999999
    - type: recall_at_3
      value: 24.712
    - type: recall_at_5
      value: 28.233000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.46
    - type: map_at_10
      value: 33.292
    - type: map_at_100
      value: 34.437
    - type: map_at_1000
      value: 34.534
    - type: map_at_3
      value: 30.567
    - type: map_at_5
      value: 32.202
    - type: mrr_at_1
      value: 28.276
    - type: mrr_at_10
      value: 36.235
    - type: mrr_at_100
      value: 37.173
    - type: mrr_at_1000
      value: 37.234
    - type: mrr_at_3
      value: 33.783
    - type: mrr_at_5
      value: 35.237
    - type: ndcg_at_1
      value: 28.276
    - type: ndcg_at_10
      value: 38.202000000000005
    - type: ndcg_at_100
      value: 43.634
    - type: ndcg_at_1000
      value: 45.894
    - type: ndcg_at_3
      value: 33.19
    - type: ndcg_at_5
      value: 35.798
    - type: precision_at_1
      value: 28.276
    - type: precision_at_10
      value: 6.332
    - type: precision_at_100
      value: 1.008
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 14.671000000000001
    - type: precision_at_5
      value: 10.571
    - type: recall_at_1
      value: 24.46
    - type: recall_at_10
      value: 50.156
    - type: recall_at_100
      value: 74.648
    - type: recall_at_1000
      value: 91.269
    - type: recall_at_3
      value: 36.937999999999995
    - type: recall_at_5
      value: 43.15
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 14.052999999999999
    - type: map_at_10
      value: 18.287
    - type: map_at_100
      value: 19.137
    - type: map_at_1000
      value: 19.258
    - type: map_at_3
      value: 16.79
    - type: map_at_5
      value: 17.618000000000002
    - type: mrr_at_1
      value: 15.254000000000001
    - type: mrr_at_10
      value: 19.88
    - type: mrr_at_100
      value: 20.71
    - type: mrr_at_1000
      value: 20.812
    - type: mrr_at_3
      value: 18.23
    - type: mrr_at_5
      value: 19.185
    - type: ndcg_at_1
      value: 15.254000000000001
    - type: ndcg_at_10
      value: 21.183
    - type: ndcg_at_100
      value: 25.972
    - type: ndcg_at_1000
      value: 29.271
    - type: ndcg_at_3
      value: 18.046
    - type: ndcg_at_5
      value: 19.570999999999998
    - type: precision_at_1
      value: 15.254000000000001
    - type: precision_at_10
      value: 3.288
    - type: precision_at_100
      value: 0.614
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.5329999999999995
    - type: precision_at_5
      value: 5.379
    - type: recall_at_1
      value: 14.052999999999999
    - type: recall_at_10
      value: 28.599999999999998
    - type: recall_at_100
      value: 51.815
    - type: recall_at_1000
      value: 77.04299999999999
    - type: recall_at_3
      value: 20.238999999999997
    - type: recall_at_5
      value: 23.837
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 8.475000000000001
    - type: map_at_10
      value: 12.898000000000001
    - type: map_at_100
      value: 13.950000000000001
    - type: map_at_1000
      value: 14.063999999999998
    - type: map_at_3
      value: 10.965
    - type: map_at_5
      value: 11.905000000000001
    - type: mrr_at_1
      value: 10.323
    - type: mrr_at_10
      value: 15.431000000000001
    - type: mrr_at_100
      value: 16.442
    - type: mrr_at_1000
      value: 16.526
    - type: mrr_at_3
      value: 13.288
    - type: mrr_at_5
      value: 14.382
    - type: ndcg_at_1
      value: 10.323
    - type: ndcg_at_10
      value: 16.325
    - type: ndcg_at_100
      value: 21.831999999999997
    - type: ndcg_at_1000
      value: 25.079
    - type: ndcg_at_3
      value: 12.372
    - type: ndcg_at_5
      value: 14.011999999999999
    - type: precision_at_1
      value: 10.323
    - type: precision_at_10
      value: 3.197
    - type: precision_at_100
      value: 0.6930000000000001
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 5.970000000000001
    - type: precision_at_5
      value: 4.627
    - type: recall_at_1
      value: 8.475000000000001
    - type: recall_at_10
      value: 24.651999999999997
    - type: recall_at_100
      value: 49.63
    - type: recall_at_1000
      value: 73.35000000000001
    - type: recall_at_3
      value: 13.852
    - type: recall_at_5
      value: 17.813000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.278
    - type: map_at_10
      value: 24.852
    - type: map_at_100
      value: 26.308999999999997
    - type: map_at_1000
      value: 26.450000000000003
    - type: map_at_3
      value: 22.183
    - type: map_at_5
      value: 23.493
    - type: mrr_at_1
      value: 22.522000000000002
    - type: mrr_at_10
      value: 29.554000000000002
    - type: mrr_at_100
      value: 30.705
    - type: mrr_at_1000
      value: 30.774
    - type: mrr_at_3
      value: 26.821
    - type: mrr_at_5
      value: 28.288000000000004
    - type: ndcg_at_1
      value: 22.522000000000002
    - type: ndcg_at_10
      value: 29.79
    - type: ndcg_at_100
      value: 36.473
    - type: ndcg_at_1000
      value: 39.440999999999995
    - type: ndcg_at_3
      value: 24.915000000000003
    - type: ndcg_at_5
      value: 26.941
    - type: precision_at_1
      value: 22.522000000000002
    - type: precision_at_10
      value: 5.707
    - type: precision_at_100
      value: 1.076
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 11.645999999999999
    - type: precision_at_5
      value: 8.584999999999999
    - type: recall_at_1
      value: 18.278
    - type: recall_at_10
      value: 40.150999999999996
    - type: recall_at_100
      value: 68.978
    - type: recall_at_1000
      value: 89.295
    - type: recall_at_3
      value: 26.548
    - type: recall_at_5
      value: 31.772
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 14.634
    - type: map_at_10
      value: 21.377
    - type: map_at_100
      value: 22.522000000000002
    - type: map_at_1000
      value: 22.657
    - type: map_at_3
      value: 19.292
    - type: map_at_5
      value: 20.278
    - type: mrr_at_1
      value: 18.151
    - type: mrr_at_10
      value: 25.263999999999996
    - type: mrr_at_100
      value: 26.156000000000002
    - type: mrr_at_1000
      value: 26.247
    - type: mrr_at_3
      value: 23.154
    - type: mrr_at_5
      value: 24.188000000000002
    - type: ndcg_at_1
      value: 18.151
    - type: ndcg_at_10
      value: 25.773000000000003
    - type: ndcg_at_100
      value: 31.130999999999997
    - type: ndcg_at_1000
      value: 34.452
    - type: ndcg_at_3
      value: 21.975
    - type: ndcg_at_5
      value: 23.36
    - type: precision_at_1
      value: 18.151
    - type: precision_at_10
      value: 4.829
    - type: precision_at_100
      value: 0.894
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.693
    - type: precision_at_5
      value: 7.648000000000001
    - type: recall_at_1
      value: 14.634
    - type: recall_at_10
      value: 35.433
    - type: recall_at_100
      value: 58.617
    - type: recall_at_1000
      value: 82.364
    - type: recall_at_3
      value: 24.59
    - type: recall_at_5
      value: 28.217
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.736583333333334
    - type: map_at_10
      value: 20.393
    - type: map_at_100
      value: 21.42775
    - type: map_at_1000
      value: 21.560666666666666
    - type: map_at_3
      value: 18.52958333333333
    - type: map_at_5
      value: 19.509249999999998
    - type: mrr_at_1
      value: 17.61366666666667
    - type: mrr_at_10
      value: 23.522250000000003
    - type: mrr_at_100
      value: 24.424166666666668
    - type: mrr_at_1000
      value: 24.512166666666666
    - type: mrr_at_3
      value: 21.64875
    - type: mrr_at_5
      value: 22.648916666666665
    - type: ndcg_at_1
      value: 17.61366666666667
    - type: ndcg_at_10
      value: 24.16458333333333
    - type: ndcg_at_100
      value: 29.305916666666672
    - type: ndcg_at_1000
      value: 32.52291666666667
    - type: ndcg_at_3
      value: 20.732
    - type: ndcg_at_5
      value: 22.223333333333333
    - type: precision_at_1
      value: 17.61366666666667
    - type: precision_at_10
      value: 4.33925
    - type: precision_at_100
      value: 0.8296666666666666
    - type: precision_at_1000
      value: 0.12933333333333333
    - type: precision_at_3
      value: 9.6265
    - type: precision_at_5
      value: 6.921666666666666
    - type: recall_at_1
      value: 14.736583333333334
    - type: recall_at_10
      value: 32.46958333333333
    - type: recall_at_100
      value: 55.94050000000001
    - type: recall_at_1000
      value: 79.17466666666667
    - type: recall_at_3
      value: 22.765749999999997
    - type: recall_at_5
      value: 26.614583333333336
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.152
    - type: map_at_10
      value: 16.052
    - type: map_at_100
      value: 16.892
    - type: map_at_1000
      value: 17.0
    - type: map_at_3
      value: 14.677999999999999
    - type: map_at_5
      value: 15.424
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.871000000000002
    - type: mrr_at_100
      value: 18.694
    - type: mrr_at_1000
      value: 18.793000000000003
    - type: mrr_at_3
      value: 16.641000000000002
    - type: mrr_at_5
      value: 17.262
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.981
    - type: ndcg_at_100
      value: 23.704
    - type: ndcg_at_1000
      value: 26.810000000000002
    - type: ndcg_at_3
      value: 16.361
    - type: ndcg_at_5
      value: 17.507
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.221
    - type: precision_at_100
      value: 0.612
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.4639999999999995
    - type: precision_at_5
      value: 5.244999999999999
    - type: recall_at_1
      value: 11.152
    - type: recall_at_10
      value: 26.22
    - type: recall_at_100
      value: 48.870000000000005
    - type: recall_at_1000
      value: 72.328
    - type: recall_at_3
      value: 18.838
    - type: recall_at_5
      value: 21.693
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.338
    - type: map_at_10
      value: 12.315
    - type: map_at_100
      value: 13.086
    - type: map_at_1000
      value: 13.214
    - type: map_at_3
      value: 11.032
    - type: map_at_5
      value: 11.691
    - type: mrr_at_1
      value: 10.255
    - type: mrr_at_10
      value: 14.723
    - type: mrr_at_100
      value: 15.528
    - type: mrr_at_1000
      value: 15.626000000000001
    - type: mrr_at_3
      value: 13.289000000000001
    - type: mrr_at_5
      value: 14.047
    - type: ndcg_at_1
      value: 10.255
    - type: ndcg_at_10
      value: 15.058
    - type: ndcg_at_100
      value: 19.326
    - type: ndcg_at_1000
      value: 22.972
    - type: ndcg_at_3
      value: 12.565999999999999
    - type: ndcg_at_5
      value: 13.603000000000002
    - type: precision_at_1
      value: 10.255
    - type: precision_at_10
      value: 2.815
    - type: precision_at_100
      value: 0.597
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 6.045
    - type: precision_at_5
      value: 4.405
    - type: recall_at_1
      value: 8.338
    - type: recall_at_10
      value: 21.125
    - type: recall_at_100
      value: 40.936
    - type: recall_at_1000
      value: 67.984
    - type: recall_at_3
      value: 14.018
    - type: recall_at_5
      value: 16.725
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.575000000000001
    - type: map_at_10
      value: 18.967
    - type: map_at_100
      value: 19.924
    - type: map_at_1000
      value: 20.06
    - type: map_at_3
      value: 17.101
    - type: map_at_5
      value: 18.142
    - type: mrr_at_1
      value: 16.418
    - type: mrr_at_10
      value: 22.131
    - type: mrr_at_100
      value: 22.993
    - type: mrr_at_1000
      value: 23.101
    - type: mrr_at_3
      value: 20.288999999999998
    - type: mrr_at_5
      value: 21.282999999999998
    - type: ndcg_at_1
      value: 16.418
    - type: ndcg_at_10
      value: 22.625
    - type: ndcg_at_100
      value: 27.676000000000002
    - type: ndcg_at_1000
      value: 31.41
    - type: ndcg_at_3
      value: 19.136
    - type: ndcg_at_5
      value: 20.748
    - type: precision_at_1
      value: 16.418
    - type: precision_at_10
      value: 3.9739999999999998
    - type: precision_at_100
      value: 0.743
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 8.924
    - type: precision_at_5
      value: 6.381
    - type: recall_at_1
      value: 13.575000000000001
    - type: recall_at_10
      value: 30.794
    - type: recall_at_100
      value: 54.02400000000001
    - type: recall_at_1000
      value: 81.634
    - type: recall_at_3
      value: 21.095
    - type: recall_at_5
      value: 25.25
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.915999999999999
    - type: map_at_10
      value: 20.976
    - type: map_at_100
      value: 22.127
    - type: map_at_1000
      value: 22.329
    - type: map_at_3
      value: 19.62
    - type: map_at_5
      value: 20.247999999999998
    - type: mrr_at_1
      value: 18.379
    - type: mrr_at_10
      value: 24.822
    - type: mrr_at_100
      value: 25.765
    - type: mrr_at_1000
      value: 25.852000000000004
    - type: mrr_at_3
      value: 23.551
    - type: mrr_at_5
      value: 24.193
    - type: ndcg_at_1
      value: 18.379
    - type: ndcg_at_10
      value: 24.956999999999997
    - type: ndcg_at_100
      value: 30.224
    - type: ndcg_at_1000
      value: 33.883
    - type: ndcg_at_3
      value: 23.094
    - type: ndcg_at_5
      value: 23.659
    - type: precision_at_1
      value: 18.379
    - type: precision_at_10
      value: 4.802
    - type: precision_at_100
      value: 1.105
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 11.462
    - type: precision_at_5
      value: 7.826
    - type: recall_at_1
      value: 14.915999999999999
    - type: recall_at_10
      value: 31.902
    - type: recall_at_100
      value: 57.296
    - type: recall_at_1000
      value: 82.107
    - type: recall_at_3
      value: 25.013
    - type: recall_at_5
      value: 27.281
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.237
    - type: map_at_10
      value: 15.703
    - type: map_at_100
      value: 16.522000000000002
    - type: map_at_1000
      value: 16.631999999999998
    - type: map_at_3
      value: 14.455000000000002
    - type: map_at_5
      value: 14.982000000000001
    - type: mrr_at_1
      value: 13.309000000000001
    - type: mrr_at_10
      value: 17.068
    - type: mrr_at_100
      value: 17.904
    - type: mrr_at_1000
      value: 18.004
    - type: mrr_at_3
      value: 15.712000000000002
    - type: mrr_at_5
      value: 16.285
    - type: ndcg_at_1
      value: 13.309000000000001
    - type: ndcg_at_10
      value: 18.205
    - type: ndcg_at_100
      value: 22.68
    - type: ndcg_at_1000
      value: 25.901000000000003
    - type: ndcg_at_3
      value: 15.472
    - type: ndcg_at_5
      value: 16.436
    - type: precision_at_1
      value: 13.309000000000001
    - type: precision_at_10
      value: 2.791
    - type: precision_at_100
      value: 0.538
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 6.346
    - type: precision_at_5
      value: 4.324999999999999
    - type: recall_at_1
      value: 12.237
    - type: recall_at_10
      value: 24.88
    - type: recall_at_100
      value: 46.017
    - type: recall_at_1000
      value: 71.029
    - type: recall_at_3
      value: 17.197000000000003
    - type: recall_at_5
      value: 19.6
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.732
    - type: map_at_10
      value: 12.674
    - type: map_at_100
      value: 14.257
    - type: map_at_1000
      value: 14.463999999999999
    - type: map_at_3
      value: 10.355
    - type: map_at_5
      value: 11.524
    - type: mrr_at_1
      value: 15.831000000000001
    - type: mrr_at_10
      value: 25.972
    - type: mrr_at_100
      value: 27.107999999999997
    - type: mrr_at_1000
      value: 27.167
    - type: mrr_at_3
      value: 22.637999999999998
    - type: mrr_at_5
      value: 24.319
    - type: ndcg_at_1
      value: 15.831000000000001
    - type: ndcg_at_10
      value: 19.244
    - type: ndcg_at_100
      value: 26.329
    - type: ndcg_at_1000
      value: 30.270999999999997
    - type: ndcg_at_3
      value: 14.966
    - type: ndcg_at_5
      value: 16.377
    - type: precision_at_1
      value: 15.831000000000001
    - type: precision_at_10
      value: 6.404
    - type: precision_at_100
      value: 1.403
    - type: precision_at_1000
      value: 0.212
    - type: precision_at_3
      value: 11.64
    - type: precision_at_5
      value: 9.134
    - type: recall_at_1
      value: 6.732
    - type: recall_at_10
      value: 24.855
    - type: recall_at_100
      value: 49.730000000000004
    - type: recall_at_1000
      value: 72.214
    - type: recall_at_3
      value: 14.299000000000001
    - type: recall_at_5
      value: 18.363
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.529
    - type: map_at_10
      value: 9.075999999999999
    - type: map_at_100
      value: 12.394
    - type: map_at_1000
      value: 13.272999999999998
    - type: map_at_3
      value: 6.688
    - type: map_at_5
      value: 7.803
    - type: mrr_at_1
      value: 36.25
    - type: mrr_at_10
      value: 46.867
    - type: mrr_at_100
      value: 47.654
    - type: mrr_at_1000
      value: 47.679
    - type: mrr_at_3
      value: 43.791999999999994
    - type: mrr_at_5
      value: 45.742
    - type: ndcg_at_1
      value: 26.75
    - type: ndcg_at_10
      value: 21.146
    - type: ndcg_at_100
      value: 25.113999999999997
    - type: ndcg_at_1000
      value: 31.873
    - type: ndcg_at_3
      value: 23.142
    - type: ndcg_at_5
      value: 22.273
    - type: precision_at_1
      value: 36.25
    - type: precision_at_10
      value: 18.25
    - type: precision_at_100
      value: 6.16
    - type: precision_at_1000
      value: 1.34
    - type: precision_at_3
      value: 27.250000000000004
    - type: precision_at_5
      value: 23.75
    - type: recall_at_1
      value: 4.529
    - type: recall_at_10
      value: 13.442000000000002
    - type: recall_at_100
      value: 32.534
    - type: recall_at_1000
      value: 55.346
    - type: recall_at_3
      value: 7.771999999999999
    - type: recall_at_5
      value: 10.061
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 37.89000000000001
    - type: f1
      value: 34.12692942265391
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.28
    - type: map_at_10
      value: 24.729
    - type: map_at_100
      value: 25.785999999999998
    - type: map_at_1000
      value: 25.855
    - type: map_at_3
      value: 22.083
    - type: map_at_5
      value: 23.534
    - type: mrr_at_1
      value: 17.462
    - type: mrr_at_10
      value: 26.358999999999998
    - type: mrr_at_100
      value: 27.412
    - type: mrr_at_1000
      value: 27.473
    - type: mrr_at_3
      value: 23.615
    - type: mrr_at_5
      value: 25.115
    - type: ndcg_at_1
      value: 17.462
    - type: ndcg_at_10
      value: 29.885
    - type: ndcg_at_100
      value: 35.268
    - type: ndcg_at_1000
      value: 37.203
    - type: ndcg_at_3
      value: 24.397
    - type: ndcg_at_5
      value: 26.995
    - type: precision_at_1
      value: 17.462
    - type: precision_at_10
      value: 4.851
    - type: precision_at_100
      value: 0.77
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 10.666
    - type: precision_at_5
      value: 7.762
    - type: recall_at_1
      value: 16.28
    - type: recall_at_10
      value: 44.554
    - type: recall_at_100
      value: 69.736
    - type: recall_at_1000
      value: 84.654
    - type: recall_at_3
      value: 29.529
    - type: recall_at_5
      value: 35.789
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.406
    - type: map_at_10
      value: 12.162
    - type: map_at_100
      value: 13.501
    - type: map_at_1000
      value: 13.700000000000001
    - type: map_at_3
      value: 10.282
    - type: map_at_5
      value: 11.182
    - type: mrr_at_1
      value: 14.969
    - type: mrr_at_10
      value: 21.453
    - type: mrr_at_100
      value: 22.579
    - type: mrr_at_1000
      value: 22.665
    - type: mrr_at_3
      value: 19.084
    - type: mrr_at_5
      value: 20.233999999999998
    - type: ndcg_at_1
      value: 14.969
    - type: ndcg_at_10
      value: 17.022000000000002
    - type: ndcg_at_100
      value: 23.415
    - type: ndcg_at_1000
      value: 27.811000000000003
    - type: ndcg_at_3
      value: 14.191999999999998
    - type: ndcg_at_5
      value: 15.026
    - type: precision_at_1
      value: 14.969
    - type: precision_at_10
      value: 4.954
    - type: precision_at_100
      value: 1.133
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 9.516
    - type: precision_at_5
      value: 7.191
    - type: recall_at_1
      value: 7.406
    - type: recall_at_10
      value: 22.404
    - type: recall_at_100
      value: 47.351
    - type: recall_at_1000
      value: 74.701
    - type: recall_at_3
      value: 13.108
    - type: recall_at_5
      value: 16.531000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 20.662
    - type: map_at_10
      value: 28.956
    - type: map_at_100
      value: 29.942999999999998
    - type: map_at_1000
      value: 30.052
    - type: map_at_3
      value: 26.767999999999997
    - type: map_at_5
      value: 28.011000000000003
    - type: mrr_at_1
      value: 41.323
    - type: mrr_at_10
      value: 49.242999999999995
    - type: mrr_at_100
      value: 49.97
    - type: mrr_at_1000
      value: 50.016000000000005
    - type: mrr_at_3
      value: 47.207
    - type: mrr_at_5
      value: 48.364000000000004
    - type: ndcg_at_1
      value: 41.323
    - type: ndcg_at_10
      value: 36.756
    - type: ndcg_at_100
      value: 41.189
    - type: ndcg_at_1000
      value: 43.667
    - type: ndcg_at_3
      value: 32.690999999999995
    - type: ndcg_at_5
      value: 34.703
    - type: precision_at_1
      value: 41.323
    - type: precision_at_10
      value: 8.015
    - type: precision_at_100
      value: 1.155
    - type: precision_at_1000
      value: 0.148
    - type: precision_at_3
      value: 20.612
    - type: precision_at_5
      value: 13.961000000000002
    - type: recall_at_1
      value: 20.662
    - type: recall_at_10
      value: 40.074
    - type: recall_at_100
      value: 57.745000000000005
    - type: recall_at_1000
      value: 74.24
    - type: recall_at_3
      value: 30.918
    - type: recall_at_5
      value: 34.902
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.62239999999998
    - type: ap
      value: 59.505106899987936
    - type: f1
      value: 64.39587267286105
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.507000000000001
    - type: map_at_10
      value: 11.542
    - type: map_at_100
      value: 12.542
    - type: map_at_1000
      value: 12.658
    - type: map_at_3
      value: 9.67
    - type: map_at_5
      value: 10.631
    - type: mrr_at_1
      value: 6.705
    - type: mrr_at_10
      value: 11.857
    - type: mrr_at_100
      value: 12.863
    - type: mrr_at_1000
      value: 12.974
    - type: mrr_at_3
      value: 9.957
    - type: mrr_at_5
      value: 10.933
    - type: ndcg_at_1
      value: 6.705
    - type: ndcg_at_10
      value: 14.764
    - type: ndcg_at_100
      value: 20.258000000000003
    - type: ndcg_at_1000
      value: 23.685000000000002
    - type: ndcg_at_3
      value: 10.809000000000001
    - type: ndcg_at_5
      value: 12.543000000000001
    - type: precision_at_1
      value: 6.705
    - type: precision_at_10
      value: 2.579
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 4.771
    - type: precision_at_5
      value: 3.734
    - type: recall_at_1
      value: 6.507000000000001
    - type: recall_at_10
      value: 24.842
    - type: recall_at_100
      value: 51.697
    - type: recall_at_1000
      value: 79.081
    - type: recall_at_3
      value: 13.828
    - type: recall_at_5
      value: 18.009
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 84.40264477884178
    - type: f1
      value: 83.43871348215795
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 54.90196078431372
    - type: f1
      value: 35.66115135754105
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.371889710827176
    - type: f1
      value: 58.91304009131599
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.52185608607937
    - type: f1
      value: 66.27921261407421
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.40912967319626
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.77476593032722
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.522211560565317
    - type: mrr
      value: 31.540554976019745
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.871
    - type: map_at_10
      value: 6.643000000000001
    - type: map_at_100
      value: 8.801
    - type: map_at_1000
      value: 9.961
    - type: map_at_3
      value: 4.862
    - type: map_at_5
      value: 5.704
    - type: mrr_at_1
      value: 29.102
    - type: mrr_at_10
      value: 38.79
    - type: mrr_at_100
      value: 39.616
    - type: mrr_at_1000
      value: 39.659
    - type: mrr_at_3
      value: 35.913000000000004
    - type: mrr_at_5
      value: 37.74
    - type: ndcg_at_1
      value: 27.554000000000002
    - type: ndcg_at_10
      value: 22.215
    - type: ndcg_at_100
      value: 21.386
    - type: ndcg_at_1000
      value: 30.615
    - type: ndcg_at_3
      value: 25.546000000000003
    - type: ndcg_at_5
      value: 24.425
    - type: precision_at_1
      value: 29.102
    - type: precision_at_10
      value: 17.121
    - type: precision_at_100
      value: 6.146
    - type: precision_at_1000
      value: 1.9029999999999998
    - type: precision_at_3
      value: 24.871
    - type: precision_at_5
      value: 22.291
    - type: recall_at_1
      value: 2.871
    - type: recall_at_10
      value: 10.184999999999999
    - type: recall_at_100
      value: 24.057000000000002
    - type: recall_at_1000
      value: 56.788000000000004
    - type: recall_at_3
      value: 5.606
    - type: recall_at_5
      value: 7.353
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.455
    - type: map_at_10
      value: 17.904999999999998
    - type: map_at_100
      value: 19.215
    - type: map_at_1000
      value: 19.314
    - type: map_at_3
      value: 15.133
    - type: map_at_5
      value: 16.624
    - type: mrr_at_1
      value: 11.906
    - type: mrr_at_10
      value: 19.595000000000002
    - type: mrr_at_100
      value: 20.765
    - type: mrr_at_1000
      value: 20.845
    - type: mrr_at_3
      value: 16.7
    - type: mrr_at_5
      value: 18.314
    - type: ndcg_at_1
      value: 11.906
    - type: ndcg_at_10
      value: 22.733999999999998
    - type: ndcg_at_100
      value: 29.179
    - type: ndcg_at_1000
      value: 31.848
    - type: ndcg_at_3
      value: 16.98
    - type: ndcg_at_5
      value: 19.695
    - type: precision_at_1
      value: 11.906
    - type: precision_at_10
      value: 4.234999999999999
    - type: precision_at_100
      value: 0.79
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 7.976
    - type: precision_at_5
      value: 6.286
    - type: recall_at_1
      value: 10.455
    - type: recall_at_10
      value: 36.114000000000004
    - type: recall_at_100
      value: 65.742
    - type: recall_at_1000
      value: 86.22800000000001
    - type: recall_at_3
      value: 20.826
    - type: recall_at_5
      value: 27.165
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.336000000000006
    - type: map_at_10
      value: 76.859
    - type: map_at_100
      value: 77.679
    - type: map_at_1000
      value: 77.705
    - type: map_at_3
      value: 73.681
    - type: map_at_5
      value: 75.558
    - type: mrr_at_1
      value: 73.13
    - type: mrr_at_10
      value: 80.757
    - type: mrr_at_100
      value: 80.99300000000001
    - type: mrr_at_1000
      value: 80.99499999999999
    - type: mrr_at_3
      value: 79.267
    - type: mrr_at_5
      value: 80.209
    - type: ndcg_at_1
      value: 73.15
    - type: ndcg_at_10
      value: 81.693
    - type: ndcg_at_100
      value: 83.733
    - type: ndcg_at_1000
      value: 83.943
    - type: ndcg_at_3
      value: 77.866
    - type: ndcg_at_5
      value: 79.779
    - type: precision_at_1
      value: 73.15
    - type: precision_at_10
      value: 12.603
    - type: precision_at_100
      value: 1.51
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 34.123
    - type: precision_at_5
      value: 22.636
    - type: recall_at_1
      value: 63.336000000000006
    - type: recall_at_10
      value: 91.36999999999999
    - type: recall_at_100
      value: 98.831
    - type: recall_at_1000
      value: 99.901
    - type: recall_at_3
      value: 80.495
    - type: recall_at_5
      value: 85.799
    - type: map_at_1
      value: 3.5479999999999996
    - type: map_at_10
      value: 8.923
    - type: map_at_100
      value: 11.038
    - type: map_at_1000
      value: 11.384
    - type: map_at_3
      value: 6.387
    - type: map_at_5
      value: 7.646999999999999
    - type: mrr_at_1
      value: 17.5
    - type: mrr_at_10
      value: 27.71
    - type: mrr_at_100
      value: 28.898000000000003
    - type: mrr_at_1000
      value: 28.96
    - type: mrr_at_3
      value: 24.282999999999998
    - type: mrr_at_5
      value: 26.123
    - type: ndcg_at_1
      value: 17.5
    - type: ndcg_at_10
      value: 15.831999999999999
    - type: ndcg_at_100
      value: 24.478
    - type: ndcg_at_1000
      value: 30.548
    - type: ndcg_at_3
      value: 14.66
    - type: ndcg_at_5
      value: 12.969
    - type: precision_at_1
      value: 17.5
    - type: precision_at_10
      value: 8.38
    - type: precision_at_100
      value: 2.103
    - type: precision_at_1000
      value: 0.356
    - type: precision_at_3
      value: 13.866999999999999
    - type: precision_at_5
      value: 11.58
    - type: recall_at_1
      value: 3.5479999999999996
    - type: recall_at_10
      value: 16.958000000000002
    - type: recall_at_100
      value: 42.687999999999995
    - type: recall_at_1000
      value: 72.173
    - type: recall_at_3
      value: 8.437999999999999
    - type: recall_at_5
      value: 11.738
    - type: map_at_1
      value: 0.186
    - type: map_at_10
      value: 1.2149999999999999
    - type: map_at_100
      value: 6.516
    - type: map_at_1000
      value: 14.704999999999998
    - type: map_at_3
      value: 0.469
    - type: map_at_5
      value: 0.701
    - type: mrr_at_1
      value: 72.0
    - type: mrr_at_10
      value: 80.238
    - type: mrr_at_100
      value: 80.622
    - type: mrr_at_1000
      value: 80.622
    - type: mrr_at_3
      value: 79.667
    - type: mrr_at_5
      value: 79.667
    - type: ndcg_at_1
      value: 64.0
    - type: ndcg_at_10
      value: 57.147000000000006
    - type: ndcg_at_100
      value: 40.5
    - type: ndcg_at_1000
      value: 33.954
    - type: ndcg_at_3
      value: 62.754
    - type: ndcg_at_5
      value: 59.933
    - type: precision_at_1
      value: 72.0
    - type: precision_at_10
      value: 60.6
    - type: precision_at_100
      value: 42.1
    - type: precision_at_1000
      value: 15.512
    - type: precision_at_3
      value: 67.333
    - type: precision_at_5
      value: 64.0
    - type: recall_at_1
      value: 0.186
    - type: recall_at_10
      value: 1.385
    - type: recall_at_100
      value: 9.332
    - type: recall_at_1000
      value: 31.922
    - type: recall_at_3
      value: 0.503
    - type: recall_at_5
      value: 0.759
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.4964655583453
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 48.31404856068323
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 77.88215495721286
    - type: cos_sim_spearman
      value: 66.95635868609415
    - type: euclidean_pearson
      value: 71.95058611790435
    - type: euclidean_spearman
      value: 66.95635868609415
    - type: manhattan_pearson
      value: 71.73499967722593
    - type: manhattan_spearman
      value: 66.76136105777387
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 72.56521014258115
    - type: cos_sim_spearman
      value: 64.21841908004934
    - type: euclidean_pearson
      value: 68.51846331737438
    - type: euclidean_spearman
      value: 64.21841908004934
    - type: manhattan_pearson
      value: 68.27567108498233
    - type: manhattan_spearman
      value: 64.09725470920785
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 72.71775862893193
    - type: cos_sim_spearman
      value: 73.28911820172492
    - type: euclidean_pearson
      value: 72.83254599010056
    - type: euclidean_spearman
      value: 73.28922176679981
    - type: manhattan_pearson
      value: 72.56589783996398
    - type: manhattan_spearman
      value: 72.99829341365574
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 73.89757752366668
    - type: cos_sim_spearman
      value: 68.93443322328304
    - type: euclidean_pearson
      value: 71.74950262447223
    - type: euclidean_spearman
      value: 68.93447340804855
    - type: manhattan_pearson
      value: 71.53131355539159
    - type: manhattan_spearman
      value: 68.75571712820332
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.97565977782956
    - type: cos_sim_spearman
      value: 81.43311223145955
    - type: euclidean_pearson
      value: 80.99231321031297
    - type: euclidean_spearman
      value: 81.43311223145955
    - type: manhattan_pearson
      value: 80.85980250491755
    - type: manhattan_spearman
      value: 81.28760623160176
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.52199164461821
    - type: cos_sim_spearman
      value: 76.00370946904079
    - type: euclidean_pearson
      value: 75.52316904078243
    - type: euclidean_spearman
      value: 76.00370946904079
    - type: manhattan_pearson
      value: 75.3120467704852
    - type: manhattan_spearman
      value: 75.73102913980114
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.71078769268394
    - type: cos_sim_spearman
      value: 84.92569102013795
    - type: euclidean_pearson
      value: 84.42768434149738
    - type: euclidean_spearman
      value: 84.92569102013795
    - type: manhattan_pearson
      value: 84.36599569720875
    - type: manhattan_spearman
      value: 84.97627760625926
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 60.75551853889779
    - type: cos_sim_spearman
      value: 59.56097878013177
    - type: euclidean_pearson
      value: 62.25756001900302
    - type: euclidean_spearman
      value: 59.56097878013177
    - type: manhattan_pearson
      value: 61.56622096305194
    - type: manhattan_spearman
      value: 58.794887940253346
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.57502299404004
    - type: cos_sim_spearman
      value: 76.84123747775618
    - type: euclidean_pearson
      value: 78.18263544350317
    - type: euclidean_spearman
      value: 76.84123747775618
    - type: manhattan_pearson
      value: 78.06611402413624
    - type: manhattan_spearman
      value: 76.79100666899737
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 82.80038681665185
    - type: mrr
      value: 94.90057418978986
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 39.056000000000004
    - type: map_at_10
      value: 48.714
    - type: map_at_100
      value: 49.653999999999996
    - type: map_at_1000
      value: 49.706
    - type: map_at_3
      value: 45.806000000000004
    - type: map_at_5
      value: 47.5
    - type: mrr_at_1
      value: 41.0
    - type: mrr_at_10
      value: 50.104000000000006
    - type: mrr_at_100
      value: 50.859
    - type: mrr_at_1000
      value: 50.903
    - type: mrr_at_3
      value: 47.556
    - type: mrr_at_5
      value: 48.972
    - type: ndcg_at_1
      value: 41.0
    - type: ndcg_at_10
      value: 54.144999999999996
    - type: ndcg_at_100
      value: 58.269999999999996
    - type: ndcg_at_1000
      value: 59.648
    - type: ndcg_at_3
      value: 48.451
    - type: ndcg_at_5
      value: 51.319
    - type: precision_at_1
      value: 41.0
    - type: precision_at_10
      value: 7.7
    - type: precision_at_100
      value: 0.997
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 19.444
    - type: precision_at_5
      value: 13.333
    - type: recall_at_1
      value: 39.056000000000004
    - type: recall_at_10
      value: 69.61699999999999
    - type: recall_at_100
      value: 87.922
    - type: recall_at_1000
      value: 98.667
    - type: recall_at_3
      value: 54.193999999999996
    - type: recall_at_5
      value: 61.138999999999996
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.73762376237623
    - type: cos_sim_ap
      value: 91.61413659372461
    - type: cos_sim_f1
      value: 86.34046890927624
    - type: cos_sim_precision
      value: 88.04573804573805
    - type: cos_sim_recall
      value: 84.7
    - type: dot_accuracy
      value: 99.73762376237623
    - type: dot_ap
      value: 91.61413659372461
    - type: dot_f1
      value: 86.34046890927624
    - type: dot_precision
      value: 88.04573804573805
    - type: dot_recall
      value: 84.7
    - type: euclidean_accuracy
      value: 99.73762376237623
    - type: euclidean_ap
      value: 91.61413659372461
    - type: euclidean_f1
      value: 86.34046890927624
    - type: euclidean_precision
      value: 88.04573804573805
    - type: euclidean_recall
      value: 84.7
    - type: manhattan_accuracy
      value: 99.74059405940594
    - type: manhattan_ap
      value: 91.56213824792806
    - type: manhattan_f1
      value: 86.22502628811776
    - type: manhattan_precision
      value: 90.9090909090909
    - type: manhattan_recall
      value: 82.0
    - type: max_accuracy
      value: 99.74059405940594
    - type: max_ap
      value: 91.61413659372461
    - type: max_f1
      value: 86.34046890927624
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 53.09338784502622
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.57087655180163
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.59188785875835
    - type: mrr
      value: 41.92390024191495
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.69015090602311
    - type: cos_sim_spearman
      value: 30.124791626004075
    - type: dot_pearson
      value: 29.69015070868056
    - type: dot_spearman
      value: 30.09621990241238
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.0660000000000003
    - type: map_at_10
      value: 9.783999999999999
    - type: map_at_100
      value: 16.005
    - type: map_at_1000
      value: 17.694
    - type: map_at_3
      value: 4.524
    - type: map_at_5
      value: 6.651
    - type: mrr_at_1
      value: 32.653
    - type: mrr_at_10
      value: 49.26
    - type: mrr_at_100
      value: 49.791000000000004
    - type: mrr_at_1000
      value: 49.791000000000004
    - type: mrr_at_3
      value: 45.238
    - type: mrr_at_5
      value: 47.177
    - type: ndcg_at_1
      value: 29.592000000000002
    - type: ndcg_at_10
      value: 26.35
    - type: ndcg_at_100
      value: 38.078
    - type: ndcg_at_1000
      value: 49.222
    - type: ndcg_at_3
      value: 28.749000000000002
    - type: ndcg_at_5
      value: 28.156
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 25.306
    - type: precision_at_100
      value: 8.449
    - type: precision_at_1000
      value: 1.559
    - type: precision_at_3
      value: 31.293
    - type: precision_at_5
      value: 30.203999999999997
    - type: recall_at_1
      value: 2.0660000000000003
    - type: recall_at_10
      value: 17.009
    - type: recall_at_100
      value: 50.065000000000005
    - type: recall_at_1000
      value: 84.247
    - type: recall_at_3
      value: 6.223
    - type: recall_at_5
      value: 10.062
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 65.9572
    - type: ap
      value: 11.472412091038306
    - type: f1
      value: 50.25348253932964
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 49.60384833050367
    - type: f1
      value: 49.6458985672963
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 32.85259172670649
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 79.30500089408118
    - type: cos_sim_ap
      value: 48.463983264840934
    - type: cos_sim_f1
      value: 49.28199791883455
    - type: cos_sim_precision
      value: 40.687285223367695
    - type: cos_sim_recall
      value: 62.48021108179419
    - type: dot_accuracy
      value: 79.30500089408118
    - type: dot_ap
      value: 48.463988663433994
    - type: dot_f1
      value: 49.28199791883455
    - type: dot_precision
      value: 40.687285223367695
    - type: dot_recall
      value: 62.48021108179419
    - type: euclidean_accuracy
      value: 79.30500089408118
    - type: euclidean_ap
      value: 48.463983264840934
    - type: euclidean_f1
      value: 49.28199791883455
    - type: euclidean_precision
      value: 40.687285223367695
    - type: euclidean_recall
      value: 62.48021108179419
    - type: manhattan_accuracy
      value: 79.2811587292126
    - type: manhattan_ap
      value: 48.38522593516497
    - type: manhattan_f1
      value: 49.11896465903435
    - type: manhattan_precision
      value: 39.440447641886486
    - type: manhattan_recall
      value: 65.09234828496042
    - type: max_accuracy
      value: 79.30500089408118
    - type: max_ap
      value: 48.463988663433994
    - type: max_f1
      value: 49.28199791883455
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.58167423448597
    - type: cos_sim_ap
      value: 80.70276946703169
    - type: cos_sim_f1
      value: 73.6376389338513
    - type: cos_sim_precision
      value: 69.10146492945385
    - type: cos_sim_recall
      value: 78.81121034801355
    - type: dot_accuracy
      value: 86.58167423448597
    - type: dot_ap
      value: 80.70276237270826
    - type: dot_f1
      value: 73.6376389338513
    - type: dot_precision
      value: 69.10146492945385
    - type: dot_recall
      value: 78.81121034801355
    - type: euclidean_accuracy
      value: 86.58167423448597
    - type: euclidean_ap
      value: 80.70277058558774
    - type: euclidean_f1
      value: 73.6376389338513
    - type: euclidean_precision
      value: 69.10146492945385
    - type: euclidean_recall
      value: 78.81121034801355
    - type: manhattan_accuracy
      value: 86.47882951061435
    - type: manhattan_ap
      value: 80.56146544234434
    - type: manhattan_f1
      value: 73.43608995415659
    - type: manhattan_precision
      value: 69.1267414203194
    - type: manhattan_recall
      value: 78.31844779796735
    - type: max_accuracy
      value: 86.58167423448597
    - type: max_ap
      value: 80.70277058558774
    - type: max_f1
      value: 73.6376389338513
---
