mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_50
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 67.26865671641791
    - type: ap
      value: 30.002473367582354
    - type: f1
      value: 61.1971953752801
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.285825
    - type: ap
      value: 59.48909573055728
    - type: f1
      value: 63.9870581887586
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.094
    - type: f1
      value: 31.58604218365913
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 13.016
    - type: map_at_10
      value: 22.521
    - type: map_at_100
      value: 23.799
    - type: map_at_1000
      value: 23.883
    - type: map_at_3
      value: 19.381
    - type: map_at_5
      value: 20.928
    - type: mrr_at_1
      value: 13.442000000000002
    - type: mrr_at_10
      value: 22.667
    - type: mrr_at_100
      value: 23.944
    - type: mrr_at_1000
      value: 24.029
    - type: mrr_at_3
      value: 19.523
    - type: mrr_at_5
      value: 21.102
    - type: ndcg_at_1
      value: 13.016
    - type: ndcg_at_10
      value: 28.059
    - type: ndcg_at_100
      value: 34.812
    - type: ndcg_at_1000
      value: 37.074
    - type: ndcg_at_3
      value: 21.438
    - type: ndcg_at_5
      value: 24.238
    - type: precision_at_1
      value: 13.016
    - type: precision_at_10
      value: 4.595
    - type: precision_at_100
      value: 0.787
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 9.128
    - type: precision_at_5
      value: 6.842
    - type: recall_at_1
      value: 13.016
    - type: recall_at_10
      value: 45.946
    - type: recall_at_100
      value: 78.73400000000001
    - type: recall_at_1000
      value: 96.515
    - type: recall_at_3
      value: 27.383000000000003
    - type: recall_at_5
      value: 34.211000000000006
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 25.72708581045921
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 17.273102202229808
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 48.99875215426555
    - type: mrr
      value: 60.91731521786923
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 67.57739420865997
    - type: cos_sim_spearman
      value: 68.8491591362424
    - type: euclidean_pearson
      value: 67.94540320514962
    - type: euclidean_spearman
      value: 68.8491591362424
    - type: manhattan_pearson
      value: 65.69150432274179
    - type: manhattan_spearman
      value: 66.33223431652344
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 57.698051948051955
    - type: f1
      value: 56.00046616188858
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 24.472330529075432
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 15.20312280133779
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 11.856
    - type: map_at_10
      value: 15.922
    - type: map_at_100
      value: 16.692999999999998
    - type: map_at_1000
      value: 16.844
    - type: map_at_3
      value: 14.233
    - type: map_at_5
      value: 15.315999999999999
    - type: mrr_at_1
      value: 14.449000000000002
    - type: mrr_at_10
      value: 19.359
    - type: mrr_at_100
      value: 20.095
    - type: mrr_at_1000
      value: 20.194000000000003
    - type: mrr_at_3
      value: 17.501
    - type: mrr_at_5
      value: 18.66
    - type: ndcg_at_1
      value: 14.449000000000002
    - type: ndcg_at_10
      value: 19.192999999999998
    - type: ndcg_at_100
      value: 23.237
    - type: ndcg_at_1000
      value: 27.032
    - type: ndcg_at_3
      value: 16.265
    - type: ndcg_at_5
      value: 17.863
    - type: precision_at_1
      value: 14.449000000000002
    - type: precision_at_10
      value: 3.662
    - type: precision_at_100
      value: 0.718
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 7.630000000000001
    - type: precision_at_5
      value: 5.866
    - type: recall_at_1
      value: 11.856
    - type: recall_at_10
      value: 25.694
    - type: recall_at_100
      value: 44.003
    - type: recall_at_1000
      value: 71.039
    - type: recall_at_3
      value: 17.136000000000003
    - type: recall_at_5
      value: 21.393
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 8.758000000000001
    - type: map_at_10
      value: 12.205
    - type: map_at_100
      value: 12.859000000000002
    - type: map_at_1000
      value: 12.967
    - type: map_at_3
      value: 11.196
    - type: map_at_5
      value: 11.676
    - type: mrr_at_1
      value: 11.21
    - type: mrr_at_10
      value: 15.062000000000001
    - type: mrr_at_100
      value: 15.720999999999998
    - type: mrr_at_1000
      value: 15.803
    - type: mrr_at_3
      value: 13.896
    - type: mrr_at_5
      value: 14.456
    - type: ndcg_at_1
      value: 11.21
    - type: ndcg_at_10
      value: 14.64
    - type: ndcg_at_100
      value: 18.163
    - type: ndcg_at_1000
      value: 21.15
    - type: ndcg_at_3
      value: 12.838
    - type: ndcg_at_5
      value: 13.475000000000001
    - type: precision_at_1
      value: 11.21
    - type: precision_at_10
      value: 2.79
    - type: precision_at_100
      value: 0.575
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 6.306000000000001
    - type: precision_at_5
      value: 4.369
    - type: recall_at_1
      value: 8.758000000000001
    - type: recall_at_10
      value: 19.213
    - type: recall_at_100
      value: 35.434
    - type: recall_at_1000
      value: 56.720000000000006
    - type: recall_at_3
      value: 13.758999999999999
    - type: recall_at_5
      value: 15.618000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 11.655999999999999
    - type: map_at_10
      value: 15.429
    - type: map_at_100
      value: 16.223000000000003
    - type: map_at_1000
      value: 16.334
    - type: map_at_3
      value: 14.069999999999999
    - type: map_at_5
      value: 14.815000000000001
    - type: mrr_at_1
      value: 13.48
    - type: mrr_at_10
      value: 17.421
    - type: mrr_at_100
      value: 18.195
    - type: mrr_at_1000
      value: 18.285
    - type: mrr_at_3
      value: 15.967
    - type: mrr_at_5
      value: 16.75
    - type: ndcg_at_1
      value: 13.48
    - type: ndcg_at_10
      value: 18.053
    - type: ndcg_at_100
      value: 22.471
    - type: ndcg_at_1000
      value: 25.689
    - type: ndcg_at_3
      value: 15.290000000000001
    - type: ndcg_at_5
      value: 16.536
    - type: precision_at_1
      value: 13.48
    - type: precision_at_10
      value: 2.991
    - type: precision_at_100
      value: 0.586
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.729
    - type: precision_at_5
      value: 4.853
    - type: recall_at_1
      value: 11.655999999999999
    - type: recall_at_10
      value: 24.329
    - type: recall_at_100
      value: 45.178000000000004
    - type: recall_at_1000
      value: 69.83200000000001
    - type: recall_at_3
      value: 16.692
    - type: recall_at_5
      value: 19.767000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 3.672
    - type: map_at_10
      value: 5.507
    - type: map_at_100
      value: 5.853
    - type: map_at_1000
      value: 5.9319999999999995
    - type: map_at_3
      value: 4.648
    - type: map_at_5
      value: 5.087
    - type: mrr_at_1
      value: 4.0680000000000005
    - type: mrr_at_10
      value: 6.03
    - type: mrr_at_100
      value: 6.404999999999999
    - type: mrr_at_1000
      value: 6.485
    - type: mrr_at_3
      value: 5.16
    - type: mrr_at_5
      value: 5.595
    - type: ndcg_at_1
      value: 4.0680000000000005
    - type: ndcg_at_10
      value: 6.955
    - type: ndcg_at_100
      value: 9.059000000000001
    - type: ndcg_at_1000
      value: 11.916
    - type: ndcg_at_3
      value: 5.137
    - type: ndcg_at_5
      value: 5.912
    - type: precision_at_1
      value: 4.0680000000000005
    - type: precision_at_10
      value: 1.232
    - type: precision_at_100
      value: 0.246
    - type: precision_at_1000
      value: 0.053
    - type: precision_at_3
      value: 2.26
    - type: precision_at_5
      value: 1.763
    - type: recall_at_1
      value: 3.672
    - type: recall_at_10
      value: 11.149000000000001
    - type: recall_at_100
      value: 21.564
    - type: recall_at_1000
      value: 44.851
    - type: recall_at_3
      value: 6.008
    - type: recall_at_5
      value: 7.91
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 2.308
    - type: map_at_10
      value: 3.431
    - type: map_at_100
      value: 3.8890000000000002
    - type: map_at_1000
      value: 3.988
    - type: map_at_3
      value: 2.896
    - type: map_at_5
      value: 3.182
    - type: mrr_at_1
      value: 2.9850000000000003
    - type: mrr_at_10
      value: 4.4110000000000005
    - type: mrr_at_100
      value: 4.925
    - type: mrr_at_1000
      value: 5.022
    - type: mrr_at_3
      value: 3.669
    - type: mrr_at_5
      value: 4.086
    - type: ndcg_at_1
      value: 2.9850000000000003
    - type: ndcg_at_10
      value: 4.463
    - type: ndcg_at_100
      value: 7.03
    - type: ndcg_at_1000
      value: 10.358
    - type: ndcg_at_3
      value: 3.3529999999999998
    - type: ndcg_at_5
      value: 3.866
    - type: precision_at_1
      value: 2.9850000000000003
    - type: precision_at_10
      value: 0.9079999999999999
    - type: precision_at_100
      value: 0.26
    - type: precision_at_1000
      value: 0.065
    - type: precision_at_3
      value: 1.575
    - type: precision_at_5
      value: 1.318
    - type: recall_at_1
      value: 2.308
    - type: recall_at_10
      value: 6.776999999999999
    - type: recall_at_100
      value: 18.618000000000002
    - type: recall_at_1000
      value: 44.175
    - type: recall_at_3
      value: 3.687
    - type: recall_at_5
      value: 4.948
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 6.862
    - type: map_at_10
      value: 9.94
    - type: map_at_100
      value: 10.624
    - type: map_at_1000
      value: 10.742
    - type: map_at_3
      value: 8.690000000000001
    - type: map_at_5
      value: 9.372
    - type: mrr_at_1
      value: 8.469999999999999
    - type: mrr_at_10
      value: 12.328999999999999
    - type: mrr_at_100
      value: 13.035
    - type: mrr_at_1000
      value: 13.123999999999999
    - type: mrr_at_3
      value: 10.828
    - type: mrr_at_5
      value: 11.752
    - type: ndcg_at_1
      value: 8.469999999999999
    - type: ndcg_at_10
      value: 12.377
    - type: ndcg_at_100
      value: 16.151
    - type: ndcg_at_1000
      value: 19.580000000000002
    - type: ndcg_at_3
      value: 9.964
    - type: ndcg_at_5
      value: 11.137
    - type: precision_at_1
      value: 8.469999999999999
    - type: precision_at_10
      value: 2.4250000000000003
    - type: precision_at_100
      value: 0.5479999999999999
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 4.812
    - type: precision_at_5
      value: 3.7539999999999996
    - type: recall_at_1
      value: 6.862
    - type: recall_at_10
      value: 17.59
    - type: recall_at_100
      value: 34.557
    - type: recall_at_1000
      value: 59.78099999999999
    - type: recall_at_3
      value: 10.838000000000001
    - type: recall_at_5
      value: 13.8
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 4.569
    - type: map_at_10
      value: 6.9190000000000005
    - type: map_at_100
      value: 7.435
    - type: map_at_1000
      value: 7.553999999999999
    - type: map_at_3
      value: 6.0409999999999995
    - type: map_at_5
      value: 6.4159999999999995
    - type: mrr_at_1
      value: 5.822
    - type: mrr_at_10
      value: 8.639
    - type: mrr_at_100
      value: 9.195
    - type: mrr_at_1000
      value: 9.292
    - type: mrr_at_3
      value: 7.571999999999999
    - type: mrr_at_5
      value: 8.04
    - type: ndcg_at_1
      value: 5.822
    - type: ndcg_at_10
      value: 8.808
    - type: ndcg_at_100
      value: 11.846
    - type: ndcg_at_1000
      value: 15.476
    - type: ndcg_at_3
      value: 6.995
    - type: ndcg_at_5
      value: 7.5920000000000005
    - type: precision_at_1
      value: 5.822
    - type: precision_at_10
      value: 1.7469999999999999
    - type: precision_at_100
      value: 0.398
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 3.4250000000000003
    - type: precision_at_5
      value: 2.489
    - type: recall_at_1
      value: 4.569
    - type: recall_at_10
      value: 13.035
    - type: recall_at_100
      value: 27.102999999999998
    - type: recall_at_1000
      value: 54.137
    - type: recall_at_3
      value: 7.839
    - type: recall_at_5
      value: 9.469
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 6.289666666666665
    - type: map_at_10
      value: 8.76325
    - type: map_at_100
      value: 9.314083333333333
    - type: map_at_1000
      value: 9.419
    - type: map_at_3
      value: 7.856916666666668
    - type: map_at_5
      value: 8.359333333333334
    - type: mrr_at_1
      value: 7.752333333333332
    - type: mrr_at_10
      value: 10.620333333333333
    - type: mrr_at_100
      value: 11.191083333333333
    - type: mrr_at_1000
      value: 11.2795
    - type: mrr_at_3
      value: 9.572916666666668
    - type: mrr_at_5
      value: 10.152499999999998
    - type: ndcg_at_1
      value: 7.752333333333332
    - type: ndcg_at_10
      value: 10.657000000000002
    - type: ndcg_at_100
      value: 13.755166666666666
    - type: ndcg_at_1000
      value: 16.9275
    - type: ndcg_at_3
      value: 8.904916666666665
    - type: ndcg_at_5
      value: 9.709083333333334
    - type: precision_at_1
      value: 7.752333333333332
    - type: precision_at_10
      value: 1.969166666666667
    - type: precision_at_100
      value: 0.42624999999999996
    - type: precision_at_1000
      value: 0.08475000000000002
    - type: precision_at_3
      value: 4.182
    - type: precision_at_5
      value: 3.0942499999999997
    - type: recall_at_1
      value: 6.289666666666665
    - type: recall_at_10
      value: 14.695083333333333
    - type: recall_at_100
      value: 29.238666666666663
    - type: recall_at_1000
      value: 53.20016666666667
    - type: recall_at_3
      value: 9.667
    - type: recall_at_5
      value: 11.766416666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 5.188000000000001
    - type: map_at_10
      value: 6.97
    - type: map_at_100
      value: 7.380000000000001
    - type: map_at_1000
      value: 7.446999999999999
    - type: map_at_3
      value: 6.357
    - type: map_at_5
      value: 6.736000000000001
    - type: mrr_at_1
      value: 6.748
    - type: mrr_at_10
      value: 8.885
    - type: mrr_at_100
      value: 9.285
    - type: mrr_at_1000
      value: 9.353
    - type: mrr_at_3
      value: 8.206
    - type: mrr_at_5
      value: 8.689
    - type: ndcg_at_1
      value: 6.748
    - type: ndcg_at_10
      value: 8.394
    - type: ndcg_at_100
      value: 10.554
    - type: ndcg_at_1000
      value: 12.786
    - type: ndcg_at_3
      value: 7.227
    - type: ndcg_at_5
      value: 7.878
    - type: precision_at_1
      value: 6.748
    - type: precision_at_10
      value: 1.442
    - type: precision_at_100
      value: 0.27799999999999997
    - type: precision_at_1000
      value: 0.052
    - type: precision_at_3
      value: 3.3230000000000004
    - type: precision_at_5
      value: 2.4539999999999997
    - type: recall_at_1
      value: 5.188000000000001
    - type: recall_at_10
      value: 11.109
    - type: recall_at_100
      value: 21.134
    - type: recall_at_1000
      value: 38.686
    - type: recall_at_3
      value: 7.795000000000001
    - type: recall_at_5
      value: 9.435
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 3.4070000000000005
    - type: map_at_10
      value: 4.735
    - type: map_at_100
      value: 5.083
    - type: map_at_1000
      value: 5.162
    - type: map_at_3
      value: 4.261
    - type: map_at_5
      value: 4.504
    - type: mrr_at_1
      value: 4.1290000000000004
    - type: mrr_at_10
      value: 5.792
    - type: mrr_at_100
      value: 6.209
    - type: mrr_at_1000
      value: 6.283999999999999
    - type: mrr_at_3
      value: 5.173
    - type: mrr_at_5
      value: 5.505
    - type: ndcg_at_1
      value: 4.1290000000000004
    - type: ndcg_at_10
      value: 5.8020000000000005
    - type: ndcg_at_100
      value: 7.861
    - type: ndcg_at_1000
      value: 10.495000000000001
    - type: ndcg_at_3
      value: 4.79
    - type: ndcg_at_5
      value: 5.2299999999999995
    - type: precision_at_1
      value: 4.1290000000000004
    - type: precision_at_10
      value: 1.084
    - type: precision_at_100
      value: 0.262
    - type: precision_at_1000
      value: 0.06
    - type: precision_at_3
      value: 2.237
    - type: precision_at_5
      value: 1.6789999999999998
    - type: recall_at_1
      value: 3.4070000000000005
    - type: recall_at_10
      value: 8.057
    - type: recall_at_100
      value: 17.662
    - type: recall_at_1000
      value: 37.738
    - type: recall_at_3
      value: 5.27
    - type: recall_at_5
      value: 6.314
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 5.559
    - type: map_at_10
      value: 7.374
    - type: map_at_100
      value: 7.9159999999999995
    - type: map_at_1000
      value: 8.007
    - type: map_at_3
      value: 6.882000000000001
    - type: map_at_5
      value: 7.1209999999999996
    - type: mrr_at_1
      value: 6.622999999999999
    - type: mrr_at_10
      value: 8.873000000000001
    - type: mrr_at_100
      value: 9.478
    - type: mrr_at_1000
      value: 9.562
    - type: mrr_at_3
      value: 8.256
    - type: mrr_at_5
      value: 8.535
    - type: ndcg_at_1
      value: 6.622999999999999
    - type: ndcg_at_10
      value: 8.738999999999999
    - type: ndcg_at_100
      value: 11.931
    - type: ndcg_at_1000
      value: 14.862
    - type: ndcg_at_3
      value: 7.713
    - type: ndcg_at_5
      value: 8.116
    - type: precision_at_1
      value: 6.622999999999999
    - type: precision_at_10
      value: 1.493
    - type: precision_at_100
      value: 0.361
    - type: precision_at_1000
      value: 0.06899999999999999
    - type: precision_at_3
      value: 3.6069999999999998
    - type: precision_at_5
      value: 2.463
    - type: recall_at_1
      value: 5.559
    - type: recall_at_10
      value: 11.509
    - type: recall_at_100
      value: 26.573
    - type: recall_at_1000
      value: 49.16
    - type: recall_at_3
      value: 8.468
    - type: recall_at_5
      value: 9.64
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 7.291
    - type: map_at_10
      value: 9.99
    - type: map_at_100
      value: 10.659
    - type: map_at_1000
      value: 10.793999999999999
    - type: map_at_3
      value: 8.968
    - type: map_at_5
      value: 9.59
    - type: mrr_at_1
      value: 9.684
    - type: mrr_at_10
      value: 12.812000000000001
    - type: mrr_at_100
      value: 13.482
    - type: mrr_at_1000
      value: 13.575999999999999
    - type: mrr_at_3
      value: 11.561
    - type: mrr_at_5
      value: 12.232999999999999
    - type: ndcg_at_1
      value: 9.684
    - type: ndcg_at_10
      value: 12.281
    - type: ndcg_at_100
      value: 15.994
    - type: ndcg_at_1000
      value: 19.578
    - type: ndcg_at_3
      value: 10.525
    - type: ndcg_at_5
      value: 11.349
    - type: precision_at_1
      value: 9.684
    - type: precision_at_10
      value: 2.451
    - type: precision_at_100
      value: 0.5910000000000001
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 5.138
    - type: precision_at_5
      value: 3.794
    - type: recall_at_1
      value: 7.291
    - type: recall_at_10
      value: 16.28
    - type: recall_at_100
      value: 34.432
    - type: recall_at_1000
      value: 60.155
    - type: recall_at_3
      value: 10.767
    - type: recall_at_5
      value: 13.156
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 4.35
    - type: map_at_10
      value: 6.737
    - type: map_at_100
      value: 7.155
    - type: map_at_1000
      value: 7.257
    - type: map_at_3
      value: 6.0409999999999995
    - type: map_at_5
      value: 6.497
    - type: mrr_at_1
      value: 5.36
    - type: mrr_at_10
      value: 7.831
    - type: mrr_at_100
      value: 8.268
    - type: mrr_at_1000
      value: 8.373999999999999
    - type: mrr_at_3
      value: 7.086
    - type: mrr_at_5
      value: 7.529
    - type: ndcg_at_1
      value: 5.36
    - type: ndcg_at_10
      value: 8.179
    - type: ndcg_at_100
      value: 10.764999999999999
    - type: ndcg_at_1000
      value: 14.208000000000002
    - type: ndcg_at_3
      value: 6.762
    - type: ndcg_at_5
      value: 7.555000000000001
    - type: precision_at_1
      value: 5.36
    - type: precision_at_10
      value: 1.405
    - type: precision_at_100
      value: 0.292
    - type: precision_at_1000
      value: 0.066
    - type: precision_at_3
      value: 3.1419999999999995
    - type: precision_at_5
      value: 2.329
    - type: recall_at_1
      value: 4.35
    - type: recall_at_10
      value: 11.599
    - type: recall_at_100
      value: 24.606
    - type: recall_at_1000
      value: 52.128
    - type: recall_at_3
      value: 7.745
    - type: recall_at_5
      value: 9.747
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 1.496
    - type: map_at_10
      value: 2.412
    - type: map_at_100
      value: 2.899
    - type: map_at_1000
      value: 2.996
    - type: map_at_3
      value: 1.9949999999999999
    - type: map_at_5
      value: 2.171
    - type: mrr_at_1
      value: 3.1919999999999997
    - type: mrr_at_10
      value: 5.2589999999999995
    - type: mrr_at_100
      value: 6.053
    - type: mrr_at_1000
      value: 6.142
    - type: mrr_at_3
      value: 4.376
    - type: mrr_at_5
      value: 4.793
    - type: ndcg_at_1
      value: 3.1919999999999997
    - type: ndcg_at_10
      value: 3.81
    - type: ndcg_at_100
      value: 6.822
    - type: ndcg_at_1000
      value: 9.649000000000001
    - type: ndcg_at_3
      value: 2.817
    - type: ndcg_at_5
      value: 3.114
    - type: precision_at_1
      value: 3.1919999999999997
    - type: precision_at_10
      value: 1.29
    - type: precision_at_100
      value: 0.45199999999999996
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 2.085
    - type: precision_at_5
      value: 1.6680000000000001
    - type: recall_at_1
      value: 1.496
    - type: recall_at_10
      value: 5.053
    - type: recall_at_100
      value: 16.066
    - type: recall_at_1000
      value: 32.796
    - type: recall_at_3
      value: 2.662
    - type: recall_at_5
      value: 3.434
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 0.473
    - type: map_at_10
      value: 1.149
    - type: map_at_100
      value: 1.614
    - type: map_at_1000
      value: 1.7760000000000002
    - type: map_at_3
      value: 0.808
    - type: map_at_5
      value: 0.9520000000000001
    - type: mrr_at_1
      value: 9.0
    - type: mrr_at_10
      value: 13.528
    - type: mrr_at_100
      value: 14.567
    - type: mrr_at_1000
      value: 14.648
    - type: mrr_at_3
      value: 12.417
    - type: mrr_at_5
      value: 13.129
    - type: ndcg_at_1
      value: 6.375
    - type: ndcg_at_10
      value: 4.561
    - type: ndcg_at_100
      value: 5.412
    - type: ndcg_at_1000
      value: 8.173
    - type: ndcg_at_3
      value: 5.882
    - type: ndcg_at_5
      value: 5.16
    - type: precision_at_1
      value: 9.0
    - type: precision_at_10
      value: 4.45
    - type: precision_at_100
      value: 1.53
    - type: precision_at_1000
      value: 0.41000000000000003
    - type: precision_at_3
      value: 7.667
    - type: precision_at_5
      value: 6.1
    - type: recall_at_1
      value: 0.473
    - type: recall_at_10
      value: 2.11
    - type: recall_at_100
      value: 6.957000000000001
    - type: recall_at_1000
      value: 16.188
    - type: recall_at_3
      value: 1.031
    - type: recall_at_5
      value: 1.447
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 36.510000000000005
    - type: f1
      value: 32.55269059609507
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 1.735
    - type: map_at_10
      value: 2.7969999999999997
    - type: map_at_100
      value: 3.0300000000000002
    - type: map_at_1000
      value: 3.078
    - type: map_at_3
      value: 2.408
    - type: map_at_5
      value: 2.62
    - type: mrr_at_1
      value: 1.83
    - type: mrr_at_10
      value: 2.946
    - type: mrr_at_100
      value: 3.196
    - type: mrr_at_1000
      value: 3.2460000000000004
    - type: mrr_at_3
      value: 2.54
    - type: mrr_at_5
      value: 2.768
    - type: ndcg_at_1
      value: 1.83
    - type: ndcg_at_10
      value: 3.481
    - type: ndcg_at_100
      value: 4.9110000000000005
    - type: ndcg_at_1000
      value: 6.553000000000001
    - type: ndcg_at_3
      value: 2.661
    - type: ndcg_at_5
      value: 3.052
    - type: precision_at_1
      value: 1.83
    - type: precision_at_10
      value: 0.59
    - type: precision_at_100
      value: 0.13899999999999998
    - type: precision_at_1000
      value: 0.029
    - type: precision_at_3
      value: 1.16
    - type: precision_at_5
      value: 0.897
    - type: recall_at_1
      value: 1.735
    - type: recall_at_10
      value: 5.514
    - type: recall_at_100
      value: 12.671
    - type: recall_at_1000
      value: 26.081
    - type: recall_at_3
      value: 3.2649999999999997
    - type: recall_at_5
      value: 4.205
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 1.8519999999999999
    - type: map_at_10
      value: 3.3000000000000003
    - type: map_at_100
      value: 3.7699999999999996
    - type: map_at_1000
      value: 3.904
    - type: map_at_3
      value: 2.665
    - type: map_at_5
      value: 2.991
    - type: mrr_at_1
      value: 3.8580000000000005
    - type: mrr_at_10
      value: 6.611000000000001
    - type: mrr_at_100
      value: 7.244000000000001
    - type: mrr_at_1000
      value: 7.356999999999999
    - type: mrr_at_3
      value: 5.607
    - type: mrr_at_5
      value: 6.101
    - type: ndcg_at_1
      value: 3.8580000000000005
    - type: ndcg_at_10
      value: 5.081
    - type: ndcg_at_100
      value: 8.054
    - type: ndcg_at_1000
      value: 12.078999999999999
    - type: ndcg_at_3
      value: 3.934
    - type: ndcg_at_5
      value: 4.349
    - type: precision_at_1
      value: 3.8580000000000005
    - type: precision_at_10
      value: 1.6199999999999999
    - type: precision_at_100
      value: 0.477
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 2.881
    - type: precision_at_5
      value: 2.253
    - type: recall_at_1
      value: 1.8519999999999999
    - type: recall_at_10
      value: 7.109999999999999
    - type: recall_at_100
      value: 19.224
    - type: recall_at_1000
      value: 45.913
    - type: recall_at_3
      value: 3.6839999999999997
    - type: recall_at_5
      value: 4.999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 1.789
    - type: map_at_10
      value: 2.761
    - type: map_at_100
      value: 2.997
    - type: map_at_1000
      value: 3.05
    - type: map_at_3
      value: 2.4330000000000003
    - type: map_at_5
      value: 2.612
    - type: mrr_at_1
      value: 3.579
    - type: mrr_at_10
      value: 5.311
    - type: mrr_at_100
      value: 5.692
    - type: mrr_at_1000
      value: 5.762
    - type: mrr_at_3
      value: 4.718
    - type: mrr_at_5
      value: 5.035
    - type: ndcg_at_1
      value: 3.579
    - type: ndcg_at_10
      value: 3.988
    - type: ndcg_at_100
      value: 5.508
    - type: ndcg_at_1000
      value: 7.3340000000000005
    - type: ndcg_at_3
      value: 3.183
    - type: ndcg_at_5
      value: 3.5589999999999997
    - type: precision_at_1
      value: 3.579
    - type: precision_at_10
      value: 1.002
    - type: precision_at_100
      value: 0.22599999999999998
    - type: precision_at_1000
      value: 0.047
    - type: precision_at_3
      value: 2.116
    - type: precision_at_5
      value: 1.569
    - type: recall_at_1
      value: 1.789
    - type: recall_at_10
      value: 5.01
    - type: recall_at_100
      value: 11.296000000000001
    - type: recall_at_1000
      value: 23.733999999999998
    - type: recall_at_3
      value: 3.174
    - type: recall_at_5
      value: 3.923
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.362
    - type: ap
      value: 59.55580844913024
    - type: f1
      value: 64.25451691590179
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 1.719
    - type: map_at_10
      value: 2.812
    - type: map_at_100
      value: 3.124
    - type: map_at_1000
      value: 3.18
    - type: map_at_3
      value: 2.4
    - type: map_at_5
      value: 2.598
    - type: mrr_at_1
      value: 1.7770000000000001
    - type: mrr_at_10
      value: 2.889
    - type: mrr_at_100
      value: 3.211
    - type: mrr_at_1000
      value: 3.2680000000000002
    - type: mrr_at_3
      value: 2.467
    - type: mrr_at_5
      value: 2.67
    - type: ndcg_at_1
      value: 1.762
    - type: ndcg_at_10
      value: 3.52
    - type: ndcg_at_100
      value: 5.343
    - type: ndcg_at_1000
      value: 7.217999999999999
    - type: ndcg_at_3
      value: 2.64
    - type: ndcg_at_5
      value: 2.9979999999999998
    - type: precision_at_1
      value: 1.762
    - type: precision_at_10
      value: 0.5950000000000001
    - type: precision_at_100
      value: 0.155
    - type: precision_at_1000
      value: 0.032
    - type: precision_at_3
      value: 1.127
    - type: precision_at_5
      value: 0.857
    - type: recall_at_1
      value: 1.719
    - type: recall_at_10
      value: 5.743
    - type: recall_at_100
      value: 14.89
    - type: recall_at_1000
      value: 30.267
    - type: recall_at_3
      value: 3.2779999999999996
    - type: recall_at_5
      value: 4.136
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 80.50615595075239
    - type: f1
      value: 80.1136210996985
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 54.031007751937985
    - type: f1
      value: 34.910049182212575
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 54.96973772696705
    - type: f1
      value: 51.482021499786136
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 63.19771351714862
    - type: f1
      value: 61.16551291933069
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 23.502491371355365
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 20.04508433667435
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 27.223268042111425
    - type: mrr
      value: 27.804265249287663
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 0.438
    - type: map_at_10
      value: 1.414
    - type: map_at_100
      value: 2.027
    - type: map_at_1000
      value: 2.866
    - type: map_at_3
      value: 0.9690000000000001
    - type: map_at_5
      value: 1.214
    - type: mrr_at_1
      value: 8.978
    - type: mrr_at_10
      value: 16.274
    - type: mrr_at_100
      value: 17.544999999999998
    - type: mrr_at_1000
      value: 17.649
    - type: mrr_at_3
      value: 13.674
    - type: mrr_at_5
      value: 15.021
    - type: ndcg_at_1
      value: 8.514
    - type: ndcg_at_10
      value: 7.301
    - type: ndcg_at_100
      value: 8.613999999999999
    - type: ndcg_at_1000
      value: 18.851000000000003
    - type: ndcg_at_3
      value: 8.193
    - type: ndcg_at_5
      value: 7.747999999999999
    - type: precision_at_1
      value: 8.978
    - type: precision_at_10
      value: 5.913
    - type: precision_at_100
      value: 3.198
    - type: precision_at_1000
      value: 1.6
    - type: precision_at_3
      value: 8.256
    - type: precision_at_5
      value: 7.1209999999999996
    - type: recall_at_1
      value: 0.438
    - type: recall_at_10
      value: 3.5360000000000005
    - type: recall_at_100
      value: 12.414
    - type: recall_at_1000
      value: 47.949000000000005
    - type: recall_at_3
      value: 1.462
    - type: recall_at_5
      value: 2.4299999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 2.2640000000000002
    - type: map_at_10
      value: 3.6859999999999995
    - type: map_at_100
      value: 4.071000000000001
    - type: map_at_1000
      value: 4.141
    - type: map_at_3
      value: 3.136
    - type: map_at_5
      value: 3.4130000000000003
    - type: mrr_at_1
      value: 2.52
    - type: mrr_at_10
      value: 4.093
    - type: mrr_at_100
      value: 4.51
    - type: mrr_at_1000
      value: 4.583
    - type: mrr_at_3
      value: 3.4909999999999997
    - type: mrr_at_5
      value: 3.791
    - type: ndcg_at_1
      value: 2.52
    - type: ndcg_at_10
      value: 4.696
    - type: ndcg_at_100
      value: 6.914
    - type: ndcg_at_1000
      value: 9.264999999999999
    - type: ndcg_at_3
      value: 3.5159999999999996
    - type: ndcg_at_5
      value: 4.026
    - type: precision_at_1
      value: 2.52
    - type: precision_at_10
      value: 0.855
    - type: precision_at_100
      value: 0.211
    - type: precision_at_1000
      value: 0.044000000000000004
    - type: precision_at_3
      value: 1.6420000000000001
    - type: precision_at_5
      value: 1.257
    - type: recall_at_1
      value: 2.2640000000000002
    - type: recall_at_10
      value: 7.478999999999999
    - type: recall_at_100
      value: 18.163
    - type: recall_at_1000
      value: 36.846000000000004
    - type: recall_at_3
      value: 4.268000000000001
    - type: recall_at_5
      value: 5.485
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 44.559
    - type: map_at_10
      value: 53.623
    - type: map_at_100
      value: 54.513999999999996
    - type: map_at_1000
      value: 54.584999999999994
    - type: map_at_3
      value: 51.229
    - type: map_at_5
      value: 52.635
    - type: mrr_at_1
      value: 51.23
    - type: mrr_at_10
      value: 58.431999999999995
    - type: mrr_at_100
      value: 59.00300000000001
    - type: mrr_at_1000
      value: 59.036
    - type: mrr_at_3
      value: 56.61000000000001
    - type: mrr_at_5
      value: 57.730000000000004
    - type: ndcg_at_1
      value: 51.28
    - type: ndcg_at_10
      value: 58.306000000000004
    - type: ndcg_at_100
      value: 61.915
    - type: ndcg_at_1000
      value: 63.343
    - type: ndcg_at_3
      value: 54.608000000000004
    - type: ndcg_at_5
      value: 56.431
    - type: precision_at_1
      value: 51.28
    - type: precision_at_10
      value: 8.755
    - type: precision_at_100
      value: 1.17
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 23.297
    - type: precision_at_5
      value: 15.598
    - type: recall_at_1
      value: 44.559
    - type: recall_at_10
      value: 67.491
    - type: recall_at_100
      value: 82.938
    - type: recall_at_1000
      value: 92.72200000000001
    - type: recall_at_3
      value: 56.952999999999996
    - type: recall_at_5
      value: 61.83
    - type: map_at_1
      value: 1.13
    - type: map_at_10
      value: 2.4570000000000003
    - type: map_at_100
      value: 3.048
    - type: map_at_1000
      value: 3.234
    - type: map_at_3
      value: 1.802
    - type: map_at_5
      value: 2.078
    - type: mrr_at_1
      value: 5.6000000000000005
    - type: mrr_at_10
      value: 9.468
    - type: mrr_at_100
      value: 10.472
    - type: mrr_at_1000
      value: 10.605
    - type: mrr_at_3
      value: 7.7829999999999995
    - type: mrr_at_5
      value: 8.468
    - type: ndcg_at_1
      value: 5.6000000000000005
    - type: ndcg_at_10
      value: 4.936999999999999
    - type: ndcg_at_100
      value: 8.597000000000001
    - type: ndcg_at_1000
      value: 13.508999999999999
    - type: ndcg_at_3
      value: 4.345000000000001
    - type: ndcg_at_5
      value: 3.782
    - type: precision_at_1
      value: 5.6000000000000005
    - type: precision_at_10
      value: 2.68
    - type: precision_at_100
      value: 0.814
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 4.0
    - type: precision_at_5
      value: 3.2800000000000002
    - type: recall_at_1
      value: 1.13
    - type: recall_at_10
      value: 5.457999999999999
    - type: recall_at_100
      value: 16.533
    - type: recall_at_1000
      value: 40.983000000000004
    - type: recall_at_3
      value: 2.44
    - type: recall_at_5
      value: 3.343
    - type: map_at_1
      value: 0.055999999999999994
    - type: map_at_10
      value: 0.292
    - type: map_at_100
      value: 1.335
    - type: map_at_1000
      value: 3.074
    - type: map_at_3
      value: 0.123
    - type: map_at_5
      value: 0.191
    - type: mrr_at_1
      value: 28.000000000000004
    - type: mrr_at_10
      value: 38.879999999999995
    - type: mrr_at_100
      value: 39.953
    - type: mrr_at_1000
      value: 39.978
    - type: mrr_at_3
      value: 33.333
    - type: mrr_at_5
      value: 37.233
    - type: ndcg_at_1
      value: 22.0
    - type: ndcg_at_10
      value: 19.601
    - type: ndcg_at_100
      value: 14.735000000000001
    - type: ndcg_at_1000
      value: 14.915000000000001
    - type: ndcg_at_3
      value: 20.358
    - type: ndcg_at_5
      value: 21.543
    - type: precision_at_1
      value: 28.000000000000004
    - type: precision_at_10
      value: 21.2
    - type: precision_at_100
      value: 15.5
    - type: precision_at_1000
      value: 7.417999999999999
    - type: precision_at_3
      value: 22.667
    - type: precision_at_5
      value: 24.4
    - type: recall_at_1
      value: 0.055999999999999994
    - type: recall_at_10
      value: 0.44799999999999995
    - type: recall_at_100
      value: 3.3070000000000004
    - type: recall_at_1000
      value: 15.334
    - type: recall_at_3
      value: 0.13699999999999998
    - type: recall_at_5
      value: 0.27499999999999997
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 22.705180109905008
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 34.83434688813055
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 73.60605619256489
    - type: cos_sim_spearman
      value: 67.90225840700592
    - type: euclidean_pearson
      value: 72.33353541178548
    - type: euclidean_spearman
      value: 67.9022659941869
    - type: manhattan_pearson
      value: 72.05976338595539
    - type: manhattan_spearman
      value: 67.56691734710643
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 64.53970557195757
    - type: cos_sim_spearman
      value: 57.30488503100292
    - type: euclidean_pearson
      value: 61.892226450716926
    - type: euclidean_spearman
      value: 57.30614347479237
    - type: manhattan_pearson
      value: 62.211926976767394
    - type: manhattan_spearman
      value: 57.68789726090663
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 71.42835803449617
    - type: cos_sim_spearman
      value: 73.427655387467
    - type: euclidean_pearson
      value: 72.95603876012058
    - type: euclidean_spearman
      value: 73.42766761221965
    - type: manhattan_pearson
      value: 72.95156508487149
    - type: manhattan_spearman
      value: 73.50217040506452
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 68.76336169760297
    - type: cos_sim_spearman
      value: 65.84204583356208
    - type: euclidean_pearson
      value: 68.43410821913582
    - type: euclidean_spearman
      value: 65.84203615293073
    - type: manhattan_pearson
      value: 68.31068072556376
    - type: manhattan_spearman
      value: 65.83052670300172
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 70.72278060206496
    - type: cos_sim_spearman
      value: 72.94488223638993
    - type: euclidean_pearson
      value: 72.87272723558824
    - type: euclidean_spearman
      value: 72.9448808909619
    - type: manhattan_pearson
      value: 73.14312374863987
    - type: manhattan_spearman
      value: 73.17094226040652
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 67.38872313741369
    - type: cos_sim_spearman
      value: 69.39591053377866
    - type: euclidean_pearson
      value: 69.51934754021094
    - type: euclidean_spearman
      value: 69.39674025878926
    - type: manhattan_pearson
      value: 69.45552921345616
    - type: manhattan_spearman
      value: 69.43073792027799
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 74.8928962240664
    - type: cos_sim_spearman
      value: 78.20100249603948
    - type: euclidean_pearson
      value: 78.32388609298962
    - type: euclidean_spearman
      value: 78.20188000341075
    - type: manhattan_pearson
      value: 78.4500539248116
    - type: manhattan_spearman
      value: 78.19642157133745
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 58.85262050940674
    - type: cos_sim_spearman
      value: 58.37965417152291
    - type: euclidean_pearson
      value: 59.76016227940433
    - type: euclidean_spearman
      value: 58.37965417152291
    - type: manhattan_pearson
      value: 60.2166257965911
    - type: manhattan_spearman
      value: 58.747276855442045
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 65.88908703880968
    - type: cos_sim_spearman
      value: 64.7638356299519
    - type: euclidean_pearson
      value: 66.43284083997051
    - type: euclidean_spearman
      value: 64.76388404493919
    - type: manhattan_pearson
      value: 66.54689278447367
    - type: manhattan_spearman
      value: 64.76609191059656
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 62.39526919052546
    - type: mrr
      value: 83.57624673801143
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 11.472
    - type: map_at_10
      value: 15.892000000000001
    - type: map_at_100
      value: 16.75
    - type: map_at_1000
      value: 16.898
    - type: map_at_3
      value: 14.167
    - type: map_at_5
      value: 15.0
    - type: mrr_at_1
      value: 12.667
    - type: mrr_at_10
      value: 17.065
    - type: mrr_at_100
      value: 17.899
    - type: mrr_at_1000
      value: 18.035999999999998
    - type: mrr_at_3
      value: 15.443999999999999
    - type: mrr_at_5
      value: 16.228
    - type: ndcg_at_1
      value: 12.667
    - type: ndcg_at_10
      value: 18.856
    - type: ndcg_at_100
      value: 23.555999999999997
    - type: ndcg_at_1000
      value: 28.138
    - type: ndcg_at_3
      value: 15.360999999999999
    - type: ndcg_at_5
      value: 16.712
    - type: precision_at_1
      value: 12.667
    - type: precision_at_10
      value: 3.033
    - type: precision_at_100
      value: 0.563
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.444
    - type: precision_at_5
      value: 4.6
    - type: recall_at_1
      value: 11.472
    - type: recall_at_10
      value: 27.278000000000002
    - type: recall_at_100
      value: 49.917
    - type: recall_at_1000
      value: 86.75
    - type: recall_at_3
      value: 17.416999999999998
    - type: recall_at_5
      value: 20.75
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.31683168316832
    - type: cos_sim_ap
      value: 61.13034379900418
    - type: cos_sim_f1
      value: 58.92957746478873
    - type: cos_sim_precision
      value: 67.48387096774194
    - type: cos_sim_recall
      value: 52.300000000000004
    - type: dot_accuracy
      value: 99.31683168316832
    - type: dot_ap
      value: 61.13034379900418
    - type: dot_f1
      value: 58.92957746478873
    - type: dot_precision
      value: 67.48387096774194
    - type: dot_recall
      value: 52.300000000000004
    - type: euclidean_accuracy
      value: 99.31683168316832
    - type: euclidean_ap
      value: 61.13034379900418
    - type: euclidean_f1
      value: 58.92957746478873
    - type: euclidean_precision
      value: 67.48387096774194
    - type: euclidean_recall
      value: 52.300000000000004
    - type: manhattan_accuracy
      value: 99.34554455445544
    - type: manhattan_ap
      value: 63.09142729872116
    - type: manhattan_f1
      value: 61.02425876010782
    - type: manhattan_precision
      value: 66.19883040935673
    - type: manhattan_recall
      value: 56.599999999999994
    - type: max_accuracy
      value: 99.34554455445544
    - type: max_ap
      value: 63.09142729872116
    - type: max_f1
      value: 61.02425876010782
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 31.859456190950397
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.22083488612398
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 38.763497690161216
    - type: mrr
      value: 38.9332134368899
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.037408929578664
    - type: cos_sim_spearman
      value: 29.62877340560356
    - type: dot_pearson
      value: 31.037408876961713
    - type: dot_spearman
      value: 29.578544636218147
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.66
    - type: map_at_10
      value: 4.183
    - type: map_at_100
      value: 5.748
    - type: map_at_1000
      value: 6.645
    - type: map_at_3
      value: 3.024
    - type: map_at_5
      value: 3.711
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 30.226
    - type: mrr_at_100
      value: 31.849
    - type: mrr_at_1000
      value: 31.915
    - type: mrr_at_3
      value: 27.211000000000002
    - type: mrr_at_5
      value: 29.048000000000002
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 12.527
    - type: ndcg_at_100
      value: 17.624000000000002
    - type: ndcg_at_1000
      value: 28.534
    - type: ndcg_at_3
      value: 18.118000000000002
    - type: ndcg_at_5
      value: 15.520999999999999
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 9.592
    - type: precision_at_100
      value: 3.653
    - type: precision_at_1000
      value: 1.006
    - type: precision_at_3
      value: 17.687
    - type: precision_at_5
      value: 14.285999999999998
    - type: recall_at_1
      value: 1.66
    - type: recall_at_10
      value: 6.419
    - type: recall_at_100
      value: 20.97
    - type: recall_at_1000
      value: 55.001
    - type: recall_at_3
      value: 3.37
    - type: recall_at_5
      value: 4.855
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 64.55300000000001
    - type: ap
      value: 11.51171190900715
    - type: f1
      value: 49.64107076870409
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.857951329937755
    - type: f1
      value: 52.984245378050296
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 25.391338056888934
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.24491863861239
    - type: cos_sim_ap
      value: 63.21977665263634
    - type: cos_sim_f1
      value: 60.90813587019961
    - type: cos_sim_precision
      value: 54.61586769939293
    - type: cos_sim_recall
      value: 68.83905013192611
    - type: dot_accuracy
      value: 83.24491863861239
    - type: dot_ap
      value: 63.21977665263634
    - type: dot_f1
      value: 60.90813587019961
    - type: dot_precision
      value: 54.61586769939293
    - type: dot_recall
      value: 68.83905013192611
    - type: euclidean_accuracy
      value: 83.24491863861239
    - type: euclidean_ap
      value: 63.21977665263634
    - type: euclidean_f1
      value: 60.90813587019961
    - type: euclidean_precision
      value: 54.61586769939293
    - type: euclidean_recall
      value: 68.83905013192611
    - type: manhattan_accuracy
      value: 83.05418131966383
    - type: manhattan_ap
      value: 62.73044800285885
    - type: manhattan_f1
      value: 60.47024246877296
    - type: manhattan_precision
      value: 56.42138939670932
    - type: manhattan_recall
      value: 65.14511873350924
    - type: max_accuracy
      value: 83.24491863861239
    - type: max_ap
      value: 63.21977665263634
    - type: max_f1
      value: 60.90813587019961
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 85.89086816470679
    - type: cos_sim_ap
      value: 78.81106183704443
    - type: cos_sim_f1
      value: 71.13646466143133
    - type: cos_sim_precision
      value: 68.54654483152484
    - type: cos_sim_recall
      value: 73.92978133661842
    - type: dot_accuracy
      value: 85.89086816470679
    - type: dot_ap
      value: 78.81106438949705
    - type: dot_f1
      value: 71.13646466143133
    - type: dot_precision
      value: 68.54654483152484
    - type: dot_recall
      value: 73.92978133661842
    - type: euclidean_accuracy
      value: 85.89086816470679
    - type: euclidean_ap
      value: 78.81106117828325
    - type: euclidean_f1
      value: 71.13646466143133
    - type: euclidean_precision
      value: 68.54654483152484
    - type: euclidean_recall
      value: 73.92978133661842
    - type: manhattan_accuracy
      value: 85.89474909768309
    - type: manhattan_ap
      value: 78.67476153897563
    - type: manhattan_f1
      value: 70.78659868900219
    - type: manhattan_precision
      value: 67.15726920950802
    - type: manhattan_recall
      value: 74.83061287342161
    - type: max_accuracy
      value: 85.89474909768309
    - type: max_ap
      value: 78.81106438949705
    - type: max_f1
      value: 71.13646466143133
---
