mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mxbai-embed-large
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.79104477611942
    - type: ap
      value: 33.14457985552527
    - type: f1
      value: 64.6795929769069
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.55495
    - type: ap
      value: 60.45299066797184
    - type: f1
      value: 65.35055059041356
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.552
    - type: f1
      value: 32.97727905295129
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 22.333
    - type: map_at_10
      value: 36.221
    - type: map_at_100
      value: 37.401
    - type: map_at_1000
      value: 37.421
    - type: map_at_3
      value: 31.602999999999998
    - type: map_at_5
      value: 34.174
    - type: mrr_at_1
      value: 22.688
    - type: mrr_at_10
      value: 36.364000000000004
    - type: mrr_at_100
      value: 37.536
    - type: mrr_at_1000
      value: 37.556
    - type: mrr_at_3
      value: 31.78
    - type: mrr_at_5
      value: 34.323
    - type: ndcg_at_1
      value: 22.333
    - type: ndcg_at_10
      value: 44.289
    - type: ndcg_at_100
      value: 49.775999999999996
    - type: ndcg_at_1000
      value: 50.288999999999994
    - type: ndcg_at_3
      value: 34.747
    - type: ndcg_at_5
      value: 39.363
    - type: precision_at_1
      value: 22.333
    - type: precision_at_10
      value: 7.02
    - type: precision_at_100
      value: 0.9520000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.628
    - type: precision_at_5
      value: 11.01
    - type: recall_at_1
      value: 22.333
    - type: recall_at_10
      value: 70.199
    - type: recall_at_100
      value: 95.235
    - type: recall_at_1000
      value: 99.21799999999999
    - type: recall_at_3
      value: 43.883
    - type: recall_at_5
      value: 55.05
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 36.36773977733561
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 26.709237577840263
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.4495071592947
    - type: mrr
      value: 67.1552785472453
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 80.60374133399762
    - type: cos_sim_spearman
      value: 78.56504316985354
    - type: euclidean_pearson
      value: 79.54265962464729
    - type: euclidean_spearman
      value: 78.56504316985354
    - type: manhattan_pearson
      value: 79.6937941481841
    - type: manhattan_spearman
      value: 78.2409393993871
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.3668831168831
    - type: f1
      value: 72.59754513880783
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.77282622047086
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.213004302435504
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.142999999999997
    - type: map_at_10
      value: 29.335
    - type: map_at_100
      value: 30.45
    - type: map_at_1000
      value: 30.603
    - type: map_at_3
      value: 26.882
    - type: map_at_5
      value: 28.315
    - type: mrr_at_1
      value: 27.611
    - type: mrr_at_10
      value: 34.760999999999996
    - type: mrr_at_100
      value: 35.581
    - type: mrr_at_1000
      value: 35.658
    - type: mrr_at_3
      value: 32.809
    - type: mrr_at_5
      value: 33.995999999999995
    - type: ndcg_at_1
      value: 27.611
    - type: ndcg_at_10
      value: 34.166000000000004
    - type: ndcg_at_100
      value: 39.111000000000004
    - type: ndcg_at_1000
      value: 42.143
    - type: ndcg_at_3
      value: 30.658
    - type: ndcg_at_5
      value: 32.297
    - type: precision_at_1
      value: 27.611
    - type: precision_at_10
      value: 6.537999999999999
    - type: precision_at_100
      value: 1.114
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_3
      value: 14.783
    - type: precision_at_5
      value: 10.644
    - type: recall_at_1
      value: 22.142999999999997
    - type: recall_at_10
      value: 42.436
    - type: recall_at_100
      value: 65.037
    - type: recall_at_1000
      value: 85.485
    - type: recall_at_3
      value: 31.642
    - type: recall_at_5
      value: 36.736000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.058
    - type: map_at_10
      value: 21.701999999999998
    - type: map_at_100
      value: 22.617
    - type: map_at_1000
      value: 22.731
    - type: map_at_3
      value: 19.93
    - type: map_at_5
      value: 20.968
    - type: mrr_at_1
      value: 20.637
    - type: mrr_at_10
      value: 25.823
    - type: mrr_at_100
      value: 26.653
    - type: mrr_at_1000
      value: 26.723999999999997
    - type: mrr_at_3
      value: 24.044999999999998
    - type: mrr_at_5
      value: 25.121
    - type: ndcg_at_1
      value: 20.637
    - type: ndcg_at_10
      value: 25.383
    - type: ndcg_at_100
      value: 29.729
    - type: ndcg_at_1000
      value: 32.591
    - type: ndcg_at_3
      value: 22.393
    - type: ndcg_at_5
      value: 23.868000000000002
    - type: precision_at_1
      value: 20.637
    - type: precision_at_10
      value: 4.72
    - type: precision_at_100
      value: 0.8630000000000001
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 10.743
    - type: precision_at_5
      value: 7.7829999999999995
    - type: recall_at_1
      value: 16.058
    - type: recall_at_10
      value: 32.356
    - type: recall_at_100
      value: 51.589
    - type: recall_at_1000
      value: 71.50999999999999
    - type: recall_at_3
      value: 23.812
    - type: recall_at_5
      value: 27.695999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.818
    - type: map_at_10
      value: 33.206
    - type: map_at_100
      value: 34.378
    - type: map_at_1000
      value: 34.473
    - type: map_at_3
      value: 30.822
    - type: map_at_5
      value: 32.105
    - type: mrr_at_1
      value: 28.84
    - type: mrr_at_10
      value: 36.303999999999995
    - type: mrr_at_100
      value: 37.321
    - type: mrr_at_1000
      value: 37.377
    - type: mrr_at_3
      value: 34.284
    - type: mrr_at_5
      value: 35.331
    - type: ndcg_at_1
      value: 28.84
    - type: ndcg_at_10
      value: 37.775
    - type: ndcg_at_100
      value: 43.338
    - type: ndcg_at_1000
      value: 45.513
    - type: ndcg_at_3
      value: 33.446999999999996
    - type: ndcg_at_5
      value: 35.404
    - type: precision_at_1
      value: 28.84
    - type: precision_at_10
      value: 6.157
    - type: precision_at_100
      value: 0.979
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 14.984
    - type: precision_at_5
      value: 10.37
    - type: recall_at_1
      value: 24.818
    - type: recall_at_10
      value: 48.614000000000004
    - type: recall_at_100
      value: 73.534
    - type: recall_at_1000
      value: 89.23299999999999
    - type: recall_at_3
      value: 36.85
    - type: recall_at_5
      value: 41.763
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.373000000000001
    - type: map_at_10
      value: 16.711000000000002
    - type: map_at_100
      value: 17.499000000000002
    - type: map_at_1000
      value: 17.612
    - type: map_at_3
      value: 15.129000000000001
    - type: map_at_5
      value: 15.928999999999998
    - type: mrr_at_1
      value: 13.559
    - type: mrr_at_10
      value: 17.863
    - type: mrr_at_100
      value: 18.642
    - type: mrr_at_1000
      value: 18.744
    - type: mrr_at_3
      value: 16.252
    - type: mrr_at_5
      value: 17.021
    - type: ndcg_at_1
      value: 13.559
    - type: ndcg_at_10
      value: 19.529
    - type: ndcg_at_100
      value: 23.771
    - type: ndcg_at_1000
      value: 27.224999999999998
    - type: ndcg_at_3
      value: 16.266
    - type: ndcg_at_5
      value: 17.635
    - type: precision_at_1
      value: 13.559
    - type: precision_at_10
      value: 3.073
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 6.816999999999999
    - type: precision_at_5
      value: 4.791
    - type: recall_at_1
      value: 12.373000000000001
    - type: recall_at_10
      value: 27.311000000000003
    - type: recall_at_100
      value: 47.405
    - type: recall_at_1000
      value: 74.339
    - type: recall_at_3
      value: 18.323999999999998
    - type: recall_at_5
      value: 21.637999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.081
    - type: map_at_10
      value: 9.395000000000001
    - type: map_at_100
      value: 10.181
    - type: map_at_1000
      value: 10.311
    - type: map_at_3
      value: 8.121
    - type: map_at_5
      value: 8.826
    - type: mrr_at_1
      value: 7.836
    - type: mrr_at_10
      value: 11.665000000000001
    - type: mrr_at_100
      value: 12.492
    - type: mrr_at_1000
      value: 12.598999999999998
    - type: mrr_at_3
      value: 10.302999999999999
    - type: mrr_at_5
      value: 11.099
    - type: ndcg_at_1
      value: 7.836
    - type: ndcg_at_10
      value: 11.874
    - type: ndcg_at_100
      value: 16.399
    - type: ndcg_at_1000
      value: 20.127
    - type: ndcg_at_3
      value: 9.372
    - type: ndcg_at_5
      value: 10.561
    - type: precision_at_1
      value: 7.836
    - type: precision_at_10
      value: 2.3009999999999997
    - type: precision_at_100
      value: 0.542
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 4.601999999999999
    - type: precision_at_5
      value: 3.557
    - type: recall_at_1
      value: 6.081
    - type: recall_at_10
      value: 17.44
    - type: recall_at_100
      value: 38.437
    - type: recall_at_1000
      value: 66.039
    - type: recall_at_3
      value: 10.551
    - type: recall_at_5
      value: 13.447000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.049
    - type: map_at_10
      value: 23.753
    - type: map_at_100
      value: 24.958
    - type: map_at_1000
      value: 25.099
    - type: map_at_3
      value: 21.608
    - type: map_at_5
      value: 22.759999999999998
    - type: mrr_at_1
      value: 22.329
    - type: mrr_at_10
      value: 28.256999999999998
    - type: mrr_at_100
      value: 29.219
    - type: mrr_at_1000
      value: 29.304000000000002
    - type: mrr_at_3
      value: 26.115
    - type: mrr_at_5
      value: 27.371000000000002
    - type: ndcg_at_1
      value: 22.329
    - type: ndcg_at_10
      value: 27.993000000000002
    - type: ndcg_at_100
      value: 33.521
    - type: ndcg_at_1000
      value: 36.791000000000004
    - type: ndcg_at_3
      value: 24.232
    - type: ndcg_at_5
      value: 25.929999999999996
    - type: precision_at_1
      value: 22.329
    - type: precision_at_10
      value: 5.149
    - type: precision_at_100
      value: 0.9390000000000001
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.357000000000001
    - type: precision_at_5
      value: 8.258000000000001
    - type: recall_at_1
      value: 18.049
    - type: recall_at_10
      value: 36.565
    - type: recall_at_100
      value: 60.55500000000001
    - type: recall_at_1000
      value: 83.36
    - type: recall_at_3
      value: 25.505
    - type: recall_at_5
      value: 30.061
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.837
    - type: map_at_10
      value: 17.613
    - type: map_at_100
      value: 18.644
    - type: map_at_1000
      value: 18.790000000000003
    - type: map_at_3
      value: 15.739
    - type: map_at_5
      value: 16.672
    - type: mrr_at_1
      value: 14.726
    - type: mrr_at_10
      value: 21.027
    - type: mrr_at_100
      value: 21.901
    - type: mrr_at_1000
      value: 21.997
    - type: mrr_at_3
      value: 19.253999999999998
    - type: mrr_at_5
      value: 20.076
    - type: ndcg_at_1
      value: 14.726
    - type: ndcg_at_10
      value: 21.488
    - type: ndcg_at_100
      value: 26.625
    - type: ndcg_at_1000
      value: 30.101
    - type: ndcg_at_3
      value: 18.134
    - type: ndcg_at_5
      value: 19.39
    - type: precision_at_1
      value: 14.726
    - type: precision_at_10
      value: 4.154999999999999
    - type: precision_at_100
      value: 0.812
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 9.209
    - type: precision_at_5
      value: 6.529999999999999
    - type: recall_at_1
      value: 11.837
    - type: recall_at_10
      value: 29.969
    - type: recall_at_100
      value: 52.635
    - type: recall_at_1000
      value: 77.228
    - type: recall_at_3
      value: 20.132
    - type: recall_at_5
      value: 23.637
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.873583333333334
    - type: map_at_10
      value: 19.144833333333334
    - type: map_at_100
      value: 20.06008333333333
    - type: map_at_1000
      value: 20.186416666666663
    - type: map_at_3
      value: 17.416083333333336
    - type: map_at_5
      value: 18.341250000000002
    - type: mrr_at_1
      value: 16.83141666666667
    - type: mrr_at_10
      value: 22.19625
    - type: mrr_at_100
      value: 23.02541666666667
    - type: mrr_at_1000
      value: 23.1135
    - type: mrr_at_3
      value: 20.53841666666667
    - type: mrr_at_5
      value: 21.414583333333333
    - type: ndcg_at_1
      value: 16.83141666666667
    - type: ndcg_at_10
      value: 22.643416666666663
    - type: ndcg_at_100
      value: 27.206416666666662
    - type: ndcg_at_1000
      value: 30.408
    - type: ndcg_at_3
      value: 19.53908333333333
    - type: ndcg_at_5
      value: 20.8925
    - type: precision_at_1
      value: 16.83141666666667
    - type: precision_at_10
      value: 4.062749999999999
    - type: precision_at_100
      value: 0.7528333333333334
    - type: precision_at_1000
      value: 0.12083333333333332
    - type: precision_at_3
      value: 9.139666666666665
    - type: precision_at_5
      value: 6.530083333333334
    - type: recall_at_1
      value: 13.873583333333334
    - type: recall_at_10
      value: 30.217083333333335
    - type: recall_at_100
      value: 51.07408333333334
    - type: recall_at_1000
      value: 74.35125
    - type: recall_at_3
      value: 21.33625
    - type: recall_at_5
      value: 24.91333333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.709
    - type: map_at_10
      value: 15.064
    - type: map_at_100
      value: 15.763
    - type: map_at_1000
      value: 15.845999999999998
    - type: map_at_3
      value: 13.471
    - type: map_at_5
      value: 14.385
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.380000000000003
    - type: mrr_at_100
      value: 18.084
    - type: mrr_at_1000
      value: 18.154
    - type: mrr_at_3
      value: 15.925
    - type: mrr_at_5
      value: 16.715
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.064
    - type: ndcg_at_100
      value: 21.746
    - type: ndcg_at_1000
      value: 24.229
    - type: ndcg_at_3
      value: 15.119
    - type: ndcg_at_5
      value: 16.529
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.129
    - type: precision_at_100
      value: 0.541
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 6.952999999999999
    - type: precision_at_5
      value: 5.092
    - type: recall_at_1
      value: 10.709
    - type: recall_at_10
      value: 25.238
    - type: recall_at_100
      value: 42.181000000000004
    - type: recall_at_1000
      value: 61.208
    - type: recall_at_3
      value: 17.036
    - type: recall_at_5
      value: 20.495
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.544
    - type: map_at_10
      value: 10.871
    - type: map_at_100
      value: 11.488
    - type: map_at_1000
      value: 11.615
    - type: map_at_3
      value: 9.683
    - type: map_at_5
      value: 10.346
    - type: mrr_at_1
      value: 9.565999999999999
    - type: mrr_at_10
      value: 13.222999999999999
    - type: mrr_at_100
      value: 13.865
    - type: mrr_at_1000
      value: 13.969000000000001
    - type: mrr_at_3
      value: 11.941
    - type: mrr_at_5
      value: 12.622
    - type: ndcg_at_1
      value: 9.565999999999999
    - type: ndcg_at_10
      value: 13.318
    - type: ndcg_at_100
      value: 16.735
    - type: ndcg_at_1000
      value: 20.347
    - type: ndcg_at_3
      value: 11.053
    - type: ndcg_at_5
      value: 12.084999999999999
    - type: precision_at_1
      value: 9.565999999999999
    - type: precision_at_10
      value: 2.519
    - type: precision_at_100
      value: 0.507
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 5.299
    - type: precision_at_5
      value: 3.923
    - type: recall_at_1
      value: 7.544
    - type: recall_at_10
      value: 18.490000000000002
    - type: recall_at_100
      value: 34.42
    - type: recall_at_1000
      value: 61.275
    - type: recall_at_3
      value: 12.208
    - type: recall_at_5
      value: 14.872
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.626999999999999
    - type: map_at_10
      value: 16.954
    - type: map_at_100
      value: 17.762
    - type: map_at_1000
      value: 17.881
    - type: map_at_3
      value: 15.432000000000002
    - type: map_at_5
      value: 16.206
    - type: mrr_at_1
      value: 15.112
    - type: mrr_at_10
      value: 19.952
    - type: mrr_at_100
      value: 20.751
    - type: mrr_at_1000
      value: 20.845
    - type: mrr_at_3
      value: 18.237000000000002
    - type: mrr_at_5
      value: 19.081
    - type: ndcg_at_1
      value: 15.112
    - type: ndcg_at_10
      value: 20.256
    - type: ndcg_at_100
      value: 24.532999999999998
    - type: ndcg_at_1000
      value: 27.876
    - type: ndcg_at_3
      value: 17.158
    - type: ndcg_at_5
      value: 18.418
    - type: precision_at_1
      value: 15.112
    - type: precision_at_10
      value: 3.479
    - type: precision_at_100
      value: 0.629
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 7.805
    - type: precision_at_5
      value: 5.522
    - type: recall_at_1
      value: 12.626999999999999
    - type: recall_at_10
      value: 27.677000000000003
    - type: recall_at_100
      value: 47.174
    - type: recall_at_1000
      value: 72.096
    - type: recall_at_3
      value: 18.942
    - type: recall_at_5
      value: 22.187
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.286999999999999
    - type: map_at_10
      value: 20.199
    - type: map_at_100
      value: 21.324
    - type: map_at_1000
      value: 21.518
    - type: map_at_3
      value: 18.504
    - type: map_at_5
      value: 19.198999999999998
    - type: mrr_at_1
      value: 17.787
    - type: mrr_at_10
      value: 23.765
    - type: mrr_at_100
      value: 24.712
    - type: mrr_at_1000
      value: 24.81
    - type: mrr_at_3
      value: 22.2
    - type: mrr_at_5
      value: 22.744
    - type: ndcg_at_1
      value: 17.787
    - type: ndcg_at_10
      value: 24.199
    - type: ndcg_at_100
      value: 28.977999999999998
    - type: ndcg_at_1000
      value: 32.802
    - type: ndcg_at_3
      value: 21.432000000000002
    - type: ndcg_at_5
      value: 22.189
    - type: precision_at_1
      value: 17.787
    - type: precision_at_10
      value: 4.723
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 10.408000000000001
    - type: precision_at_5
      value: 7.2330000000000005
    - type: recall_at_1
      value: 14.286999999999999
    - type: recall_at_10
      value: 31.752000000000002
    - type: recall_at_100
      value: 53.964
    - type: recall_at_1000
      value: 79.913
    - type: recall_at_3
      value: 22.844
    - type: recall_at_5
      value: 25.337
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.957
    - type: map_at_10
      value: 14.935
    - type: map_at_100
      value: 15.656999999999998
    - type: map_at_1000
      value: 15.758
    - type: map_at_3
      value: 13.672
    - type: map_at_5
      value: 14.384
    - type: mrr_at_1
      value: 11.091
    - type: mrr_at_10
      value: 16.335
    - type: mrr_at_100
      value: 17.084
    - type: mrr_at_1000
      value: 17.180999999999997
    - type: mrr_at_3
      value: 15.096000000000002
    - type: mrr_at_5
      value: 15.798000000000002
    - type: ndcg_at_1
      value: 11.091
    - type: ndcg_at_10
      value: 17.676
    - type: ndcg_at_100
      value: 21.991
    - type: ndcg_at_1000
      value: 25.151
    - type: ndcg_at_3
      value: 15.204999999999998
    - type: ndcg_at_5
      value: 16.404
    - type: precision_at_1
      value: 11.091
    - type: precision_at_10
      value: 2.81
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 6.715999999999999
    - type: precision_at_5
      value: 4.658
    - type: recall_at_1
      value: 9.957
    - type: recall_at_10
      value: 24.757
    - type: recall_at_100
      value: 45.958
    - type: recall_at_1000
      value: 70.529
    - type: recall_at_3
      value: 18.189
    - type: recall_at_5
      value: 21.090999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.822
    - type: map_at_10
      value: 12.751000000000001
    - type: map_at_100
      value: 14.386
    - type: map_at_1000
      value: 14.594
    - type: map_at_3
      value: 10.191
    - type: map_at_5
      value: 11.353
    - type: mrr_at_1
      value: 15.504999999999999
    - type: mrr_at_10
      value: 25.484
    - type: mrr_at_100
      value: 26.63
    - type: mrr_at_1000
      value: 26.69
    - type: mrr_at_3
      value: 21.868000000000002
    - type: mrr_at_5
      value: 23.845
    - type: ndcg_at_1
      value: 15.504999999999999
    - type: ndcg_at_10
      value: 19.353
    - type: ndcg_at_100
      value: 26.608999999999998
    - type: ndcg_at_1000
      value: 30.775000000000002
    - type: ndcg_at_3
      value: 14.479000000000001
    - type: ndcg_at_5
      value: 16.102
    - type: precision_at_1
      value: 15.504999999999999
    - type: precision_at_10
      value: 6.619
    - type: precision_at_100
      value: 1.444
    - type: precision_at_1000
      value: 0.22
    - type: precision_at_3
      value: 11.27
    - type: precision_at_5
      value: 9.055
    - type: recall_at_1
      value: 6.822
    - type: recall_at_10
      value: 25.266
    - type: recall_at_100
      value: 50.937
    - type: recall_at_1000
      value: 74.94800000000001
    - type: recall_at_3
      value: 13.682
    - type: recall_at_5
      value: 17.902
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.7960000000000003
    - type: map_at_10
      value: 8.855
    - type: map_at_100
      value: 12.781999999999998
    - type: map_at_1000
      value: 13.805
    - type: map_at_3
      value: 6.036
    - type: map_at_5
      value: 7.217999999999999
    - type: mrr_at_1
      value: 40.25
    - type: mrr_at_10
      value: 49.899
    - type: mrr_at_100
      value: 50.619
    - type: mrr_at_1000
      value: 50.648
    - type: mrr_at_3
      value: 46.75
    - type: mrr_at_5
      value: 48.463
    - type: ndcg_at_1
      value: 29.875
    - type: ndcg_at_10
      value: 23.518
    - type: ndcg_at_100
      value: 26.632
    - type: ndcg_at_1000
      value: 33.567
    - type: ndcg_at_3
      value: 25.718000000000004
    - type: ndcg_at_5
      value: 24.474
    - type: precision_at_1
      value: 40.25
    - type: precision_at_10
      value: 21.475
    - type: precision_at_100
      value: 6.908
    - type: precision_at_1000
      value: 1.502
    - type: precision_at_3
      value: 30.833
    - type: precision_at_5
      value: 27.1
    - type: recall_at_1
      value: 3.7960000000000003
    - type: recall_at_10
      value: 13.802
    - type: recall_at_100
      value: 33.72
    - type: recall_at_1000
      value: 58.074999999999996
    - type: recall_at_3
      value: 6.999
    - type: recall_at_5
      value: 9.196
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.425
    - type: f1
      value: 42.77638425014079
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.888
    - type: map_at_10
      value: 25.161
    - type: map_at_100
      value: 26.074
    - type: map_at_1000
      value: 26.145000000000003
    - type: map_at_3
      value: 22.595000000000002
    - type: map_at_5
      value: 24.03
    - type: mrr_at_1
      value: 18.017
    - type: mrr_at_10
      value: 26.749000000000002
    - type: mrr_at_100
      value: 27.645999999999997
    - type: mrr_at_1000
      value: 27.705999999999996
    - type: mrr_at_3
      value: 24.085
    - type: mrr_at_5
      value: 25.576999999999998
    - type: ndcg_at_1
      value: 18.017
    - type: ndcg_at_10
      value: 30.144
    - type: ndcg_at_100
      value: 34.760000000000005
    - type: ndcg_at_1000
      value: 36.718
    - type: ndcg_at_3
      value: 24.9
    - type: ndcg_at_5
      value: 27.462999999999997
    - type: precision_at_1
      value: 18.017
    - type: precision_at_10
      value: 4.842
    - type: precision_at_100
      value: 0.734
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 10.841000000000001
    - type: precision_at_5
      value: 7.882
    - type: recall_at_1
      value: 16.888
    - type: recall_at_10
      value: 44.183
    - type: recall_at_100
      value: 65.642
    - type: recall_at_1000
      value: 80.74900000000001
    - type: recall_at_3
      value: 30.026000000000003
    - type: recall_at_5
      value: 36.159
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.987
    - type: map_at_10
      value: 10.633
    - type: map_at_100
      value: 11.718
    - type: map_at_1000
      value: 11.927
    - type: map_at_3
      value: 8.965
    - type: map_at_5
      value: 9.622
    - type: mrr_at_1
      value: 11.883000000000001
    - type: mrr_at_10
      value: 18.39
    - type: mrr_at_100
      value: 19.486
    - type: mrr_at_1000
      value: 19.585
    - type: mrr_at_3
      value: 16.512
    - type: mrr_at_5
      value: 17.438000000000002
    - type: ndcg_at_1
      value: 11.883000000000001
    - type: ndcg_at_10
      value: 14.965
    - type: ndcg_at_100
      value: 20.491
    - type: ndcg_at_1000
      value: 25.151
    - type: ndcg_at_3
      value: 12.346
    - type: ndcg_at_5
      value: 12.963
    - type: precision_at_1
      value: 11.883000000000001
    - type: precision_at_10
      value: 4.383
    - type: precision_at_100
      value: 0.985
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 8.488
    - type: precision_at_5
      value: 6.358
    - type: recall_at_1
      value: 5.987
    - type: recall_at_10
      value: 20.108
    - type: recall_at_100
      value: 41.854
    - type: recall_at_1000
      value: 70.61500000000001
    - type: recall_at_3
      value: 11.874
    - type: recall_at_5
      value: 14.188999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 16.34
    - type: map_at_10
      value: 23.026
    - type: map_at_100
      value: 23.921
    - type: map_at_1000
      value: 24.035
    - type: map_at_3
      value: 21.121000000000002
    - type: map_at_5
      value: 22.191
    - type: mrr_at_1
      value: 32.681
    - type: mrr_at_10
      value: 39.583
    - type: mrr_at_100
      value: 40.306
    - type: mrr_at_1000
      value: 40.366
    - type: mrr_at_3
      value: 37.65
    - type: mrr_at_5
      value: 38.769999999999996
    - type: ndcg_at_1
      value: 32.681
    - type: ndcg_at_10
      value: 29.578
    - type: ndcg_at_100
      value: 33.742
    - type: ndcg_at_1000
      value: 36.504
    - type: ndcg_at_3
      value: 25.935000000000002
    - type: ndcg_at_5
      value: 27.74
    - type: precision_at_1
      value: 32.681
    - type: precision_at_10
      value: 6.551
    - type: precision_at_100
      value: 0.989
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 16.367
    - type: precision_at_5
      value: 11.251999999999999
    - type: recall_at_1
      value: 16.34
    - type: recall_at_10
      value: 32.755
    - type: recall_at_100
      value: 49.433
    - type: recall_at_1000
      value: 67.927
    - type: recall_at_3
      value: 24.551000000000002
    - type: recall_at_5
      value: 28.13
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 65.7364
    - type: ap
      value: 60.57183715346659
    - type: f1
      value: 65.51915706047664
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.273
    - type: map_at_10
      value: 10.777000000000001
    - type: map_at_100
      value: 11.645
    - type: map_at_1000
      value: 11.75
    - type: map_at_3
      value: 9.086
    - type: map_at_5
      value: 10.006
    - type: mrr_at_1
      value: 6.5040000000000004
    - type: mrr_at_10
      value: 11.092
    - type: mrr_at_100
      value: 11.968
    - type: mrr_at_1000
      value: 12.069
    - type: mrr_at_3
      value: 9.362
    - type: mrr_at_5
      value: 10.301
    - type: ndcg_at_1
      value: 6.476
    - type: ndcg_at_10
      value: 13.663
    - type: ndcg_at_100
      value: 18.43
    - type: ndcg_at_1000
      value: 21.578
    - type: ndcg_at_3
      value: 10.119
    - type: ndcg_at_5
      value: 11.781
    - type: precision_at_1
      value: 6.476
    - type: precision_at_10
      value: 2.36
    - type: precision_at_100
      value: 0.483
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_3
      value: 4.441
    - type: precision_at_5
      value: 3.504
    - type: recall_at_1
      value: 6.273
    - type: recall_at_10
      value: 22.633
    - type: recall_at_100
      value: 45.977000000000004
    - type: recall_at_1000
      value: 71.24000000000001
    - type: recall_at_3
      value: 12.862000000000002
    - type: recall_at_5
      value: 16.861
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.22389420884633
    - type: f1
      value: 87.64396367277254
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 57.64477884176926
    - type: f1
      value: 40.163687026031184
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.76731674512441
    - type: f1
      value: 61.091308868436975
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.41829186281103
    - type: f1
      value: 68.31043799018511
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.83976118152166
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.816942965695233
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.370605538323442
    - type: mrr
      value: 32.51161029506204
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.257
    - type: map_at_10
      value: 8.892
    - type: map_at_100
      value: 11.440999999999999
    - type: map_at_1000
      value: 12.894
    - type: map_at_3
      value: 6.728000000000001
    - type: map_at_5
      value: 7.821
    - type: mrr_at_1
      value: 34.985
    - type: mrr_at_10
      value: 45.084999999999994
    - type: mrr_at_100
      value: 45.666000000000004
    - type: mrr_at_1000
      value: 45.732
    - type: mrr_at_3
      value: 42.054
    - type: mrr_at_5
      value: 44.066
    - type: ndcg_at_1
      value: 33.282000000000004
    - type: ndcg_at_10
      value: 27.194000000000003
    - type: ndcg_at_100
      value: 25.636
    - type: ndcg_at_1000
      value: 35.264
    - type: ndcg_at_3
      value: 30.553
    - type: ndcg_at_5
      value: 29.372
    - type: precision_at_1
      value: 34.985
    - type: precision_at_10
      value: 20.526
    - type: precision_at_100
      value: 7.173
    - type: precision_at_1000
      value: 2.067
    - type: precision_at_3
      value: 28.999000000000002
    - type: precision_at_5
      value: 25.759
    - type: recall_at_1
      value: 4.257
    - type: recall_at_10
      value: 13.065
    - type: recall_at_100
      value: 27.738000000000003
    - type: recall_at_1000
      value: 62.818
    - type: recall_at_3
      value: 8.094999999999999
    - type: recall_at_5
      value: 10.377
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.866999999999999
    - type: map_at_10
      value: 15.186
    - type: map_at_100
      value: 16.386
    - type: map_at_1000
      value: 16.486
    - type: map_at_3
      value: 12.7
    - type: map_at_5
      value: 13.977
    - type: mrr_at_1
      value: 9.994
    - type: mrr_at_10
      value: 16.766000000000002
    - type: mrr_at_100
      value: 17.875
    - type: mrr_at_1000
      value: 17.958
    - type: mrr_at_3
      value: 14.151
    - type: mrr_at_5
      value: 15.533
    - type: ndcg_at_1
      value: 9.994
    - type: ndcg_at_10
      value: 19.492
    - type: ndcg_at_100
      value: 25.555
    - type: ndcg_at_1000
      value: 28.366000000000003
    - type: ndcg_at_3
      value: 14.29
    - type: ndcg_at_5
      value: 16.608
    - type: precision_at_1
      value: 9.994
    - type: precision_at_10
      value: 3.6990000000000003
    - type: precision_at_100
      value: 0.716
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.701
    - type: precision_at_5
      value: 5.313
    - type: recall_at_1
      value: 8.866999999999999
    - type: recall_at_10
      value: 31.354
    - type: recall_at_100
      value: 59.429
    - type: recall_at_1000
      value: 81.182
    - type: recall_at_3
      value: 17.474999999999998
    - type: recall_at_5
      value: 22.868
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.41
    - type: map_at_10
      value: 76.143
    - type: map_at_100
      value: 76.904
    - type: map_at_1000
      value: 76.936
    - type: map_at_3
      value: 73.146
    - type: map_at_5
      value: 75.003
    - type: mrr_at_1
      value: 72.98
    - type: mrr_at_10
      value: 80.262
    - type: mrr_at_100
      value: 80.5
    - type: mrr_at_1000
      value: 80.50500000000001
    - type: mrr_at_3
      value: 78.782
    - type: mrr_at_5
      value: 79.74799999999999
    - type: ndcg_at_1
      value: 73.04
    - type: ndcg_at_10
      value: 80.78699999999999
    - type: ndcg_at_100
      value: 82.884
    - type: ndcg_at_1000
      value: 83.231
    - type: ndcg_at_3
      value: 77.12599999999999
    - type: ndcg_at_5
      value: 79.077
    - type: precision_at_1
      value: 73.04
    - type: precision_at_10
      value: 12.239
    - type: precision_at_100
      value: 1.463
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.437
    - type: precision_at_5
      value: 22.178
    - type: recall_at_1
      value: 63.41
    - type: recall_at_10
      value: 89.795
    - type: recall_at_100
      value: 97.71600000000001
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 79.415
    - type: recall_at_5
      value: 84.76
    - type: map_at_1
      value: 2.758
    - type: map_at_10
      value: 6.7589999999999995
    - type: map_at_100
      value: 8.157
    - type: map_at_1000
      value: 8.427999999999999
    - type: map_at_3
      value: 4.984999999999999
    - type: map_at_5
      value: 5.782
    - type: mrr_at_1
      value: 13.5
    - type: mrr_at_10
      value: 21.547
    - type: mrr_at_100
      value: 22.811
    - type: mrr_at_1000
      value: 22.906000000000002
    - type: mrr_at_3
      value: 18.95
    - type: mrr_at_5
      value: 20.275000000000002
    - type: ndcg_at_1
      value: 13.5
    - type: ndcg_at_10
      value: 12.061
    - type: ndcg_at_100
      value: 18.501
    - type: ndcg_at_1000
      value: 23.954
    - type: ndcg_at_3
      value: 11.468
    - type: ndcg_at_5
      value: 9.832
    - type: precision_at_1
      value: 13.5
    - type: precision_at_10
      value: 6.3100000000000005
    - type: precision_at_100
      value: 1.5699999999999998
    - type: precision_at_1000
      value: 0.28900000000000003
    - type: precision_at_3
      value: 10.867
    - type: precision_at_5
      value: 8.6
    - type: recall_at_1
      value: 2.758
    - type: recall_at_10
      value: 12.802
    - type: recall_at_100
      value: 31.881999999999998
    - type: recall_at_1000
      value: 58.617
    - type: recall_at_3
      value: 6.6129999999999995
    - type: recall_at_5
      value: 8.728
    - type: map_at_1
      value: 0.14300000000000002
    - type: map_at_10
      value: 0.852
    - type: map_at_100
      value: 4.5089999999999995
    - type: map_at_1000
      value: 11.663
    - type: map_at_3
      value: 0.318
    - type: map_at_5
      value: 0.47000000000000003
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 64.151
    - type: mrr_at_100
      value: 64.885
    - type: mrr_at_1000
      value: 64.885
    - type: mrr_at_3
      value: 61.0
    - type: mrr_at_5
      value: 62.0
    - type: ndcg_at_1
      value: 49.0
    - type: ndcg_at_10
      value: 43.096000000000004
    - type: ndcg_at_100
      value: 32.491
    - type: ndcg_at_1000
      value: 30.432
    - type: ndcg_at_3
      value: 44.285000000000004
    - type: ndcg_at_5
      value: 43.505
    - type: precision_at_1
      value: 54.0
    - type: precision_at_10
      value: 46.6
    - type: precision_at_100
      value: 34.28
    - type: precision_at_1000
      value: 14.886
    - type: precision_at_3
      value: 47.333
    - type: precision_at_5
      value: 46.800000000000004
    - type: recall_at_1
      value: 0.14300000000000002
    - type: recall_at_10
      value: 1.117
    - type: recall_at_100
      value: 7.477
    - type: recall_at_1000
      value: 29.666999999999998
    - type: recall_at_3
      value: 0.347
    - type: recall_at_5
      value: 0.545
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 45.5601666470677
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 47.770988895550886
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 78.26245951353962
    - type: cos_sim_spearman
      value: 67.84539204408432
    - type: euclidean_pearson
      value: 74.21607093942097
    - type: euclidean_spearman
      value: 67.84545822363431
    - type: manhattan_pearson
      value: 70.65836714092913
    - type: manhattan_spearman
      value: 65.25792725583983
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 75.59583415996339
    - type: cos_sim_spearman
      value: 66.89861267363996
    - type: euclidean_pearson
      value: 71.86752820469697
    - type: euclidean_spearman
      value: 66.89991282290966
    - type: manhattan_pearson
      value: 70.7284632544075
    - type: manhattan_spearman
      value: 67.18845064858152
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.15298679945339
    - type: cos_sim_spearman
      value: 77.76141248614337
    - type: euclidean_pearson
      value: 77.53737892012191
    - type: euclidean_spearman
      value: 77.76142467622597
    - type: manhattan_pearson
      value: 78.03597553951049
    - type: manhattan_spearman
      value: 78.39772333414133
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.35224122791287
    - type: cos_sim_spearman
      value: 74.47677736391881
    - type: euclidean_pearson
      value: 77.57019604889985
    - type: euclidean_spearman
      value: 74.47676767297182
    - type: manhattan_pearson
      value: 76.73163796164971
    - type: manhattan_spearman
      value: 74.23587008360492
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.1042939648847
    - type: cos_sim_spearman
      value: 81.41368013571659
    - type: euclidean_pearson
      value: 81.48626463776695
    - type: euclidean_spearman
      value: 81.41368637874736
    - type: manhattan_pearson
      value: 81.48355965065436
    - type: manhattan_spearman
      value: 81.62079694097419
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.89019846614487
    - type: cos_sim_spearman
      value: 76.2566739236189
    - type: euclidean_pearson
      value: 76.10119093261383
    - type: euclidean_spearman
      value: 76.25694553078488
    - type: manhattan_pearson
      value: 76.58400661123387
    - type: manhattan_spearman
      value: 76.89895753816454
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.76823435555784
    - type: cos_sim_spearman
      value: 84.21685158024917
    - type: euclidean_pearson
      value: 83.81240661938682
    - type: euclidean_spearman
      value: 84.21772562243359
    - type: manhattan_pearson
      value: 83.09771367107825
    - type: manhattan_spearman
      value: 83.60926420491222
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.31916082130928
    - type: cos_sim_spearman
      value: 60.643988533267
    - type: euclidean_pearson
      value: 63.378219985105154
    - type: euclidean_spearman
      value: 60.643988533267
    - type: manhattan_pearson
      value: 63.029437112042075
    - type: manhattan_spearman
      value: 60.53647700671018
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.92130991519997
    - type: cos_sim_spearman
      value: 76.70092643265069
    - type: euclidean_pearson
      value: 78.364944073085
    - type: euclidean_spearman
      value: 76.70094489969958
    - type: manhattan_pearson
      value: 78.0607681465912
    - type: manhattan_spearman
      value: 76.6577342175607
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.2154507905421
    - type: mrr
      value: 91.38974678190365
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 32.694
    - type: map_at_10
      value: 42.122
    - type: map_at_100
      value: 43.221
    - type: map_at_1000
      value: 43.282
    - type: map_at_3
      value: 40.204
    - type: map_at_5
      value: 41.187000000000005
    - type: mrr_at_1
      value: 35.333
    - type: mrr_at_10
      value: 44.095
    - type: mrr_at_100
      value: 45.036
    - type: mrr_at_1000
      value: 45.086
    - type: mrr_at_3
      value: 42.333
    - type: mrr_at_5
      value: 43.2
    - type: ndcg_at_1
      value: 35.333
    - type: ndcg_at_10
      value: 46.882000000000005
    - type: ndcg_at_100
      value: 52.372
    - type: ndcg_at_1000
      value: 53.903
    - type: ndcg_at_3
      value: 43.079
    - type: ndcg_at_5
      value: 44.732
    - type: precision_at_1
      value: 35.333
    - type: precision_at_10
      value: 6.567
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 17.778
    - type: precision_at_5
      value: 11.600000000000001
    - type: recall_at_1
      value: 32.694
    - type: recall_at_10
      value: 59.760999999999996
    - type: recall_at_100
      value: 85.572
    - type: recall_at_1000
      value: 97.26700000000001
    - type: recall_at_3
      value: 49.167
    - type: recall_at_5
      value: 53.417
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.66336633663366
    - type: cos_sim_ap
      value: 88.65731696253445
    - type: cos_sim_f1
      value: 82.55872063968016
    - type: cos_sim_precision
      value: 82.51748251748252
    - type: cos_sim_recall
      value: 82.6
    - type: dot_accuracy
      value: 99.66336633663366
    - type: dot_ap
      value: 88.65731696253445
    - type: dot_f1
      value: 82.55872063968016
    - type: dot_precision
      value: 82.51748251748252
    - type: dot_recall
      value: 82.6
    - type: euclidean_accuracy
      value: 99.66336633663366
    - type: euclidean_ap
      value: 88.65731696253445
    - type: euclidean_f1
      value: 82.55872063968016
    - type: euclidean_precision
      value: 82.51748251748252
    - type: euclidean_recall
      value: 82.6
    - type: manhattan_accuracy
      value: 99.71089108910891
    - type: manhattan_ap
      value: 91.30880834064459
    - type: manhattan_f1
      value: 85.34906588003933
    - type: manhattan_precision
      value: 83.9458413926499
    - type: manhattan_recall
      value: 86.8
    - type: max_accuracy
      value: 99.71089108910891
    - type: max_ap
      value: 91.30880834064459
    - type: max_f1
      value: 85.34906588003933
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 47.527866810545916
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.65831891956486
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.70015713936949
    - type: mrr
      value: 43.080383668618964
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.30482857228984
    - type: cos_sim_spearman
      value: 30.858770002347647
    - type: dot_pearson
      value: 30.304828494593238
    - type: dot_spearman
      value: 30.907161646082997
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.139
    - type: map_at_10
      value: 7.116
    - type: map_at_100
      value: 13.464
    - type: map_at_1000
      value: 15.160000000000002
    - type: map_at_3
      value: 4.0169999999999995
    - type: map_at_5
      value: 5.587000000000001
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 42.225
    - type: mrr_at_100
      value: 43.206
    - type: mrr_at_1000
      value: 43.225
    - type: mrr_at_3
      value: 36.394999999999996
    - type: mrr_at_5
      value: 38.946
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 20.948
    - type: ndcg_at_100
      value: 34.647
    - type: ndcg_at_1000
      value: 46.587
    - type: ndcg_at_3
      value: 23.158
    - type: ndcg_at_5
      value: 22.516
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 18.776
    - type: precision_at_100
      value: 7.959
    - type: precision_at_1000
      value: 1.559
    - type: precision_at_3
      value: 23.128999999999998
    - type: precision_at_5
      value: 22.041
    - type: recall_at_1
      value: 2.139
    - type: recall_at_10
      value: 12.666
    - type: recall_at_100
      value: 47.965
    - type: recall_at_1000
      value: 84.198
    - type: recall_at_3
      value: 4.671
    - type: recall_at_5
      value: 7.736999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 72.687
    - type: ap
      value: 15.402386367537005
    - type: f1
      value: 56.15906014663372
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.592529711375214
    - type: f1
      value: 54.81939839369587
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 41.53016653534568
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.01841807236097
    - type: cos_sim_ap
      value: 62.587389637610734
    - type: cos_sim_f1
      value: 60.42787139954583
    - type: cos_sim_precision
      value: 55.23268516495521
    - type: cos_sim_recall
      value: 66.7018469656992
    - type: dot_accuracy
      value: 83.01841807236097
    - type: dot_ap
      value: 62.587389637610734
    - type: dot_f1
      value: 60.42787139954583
    - type: dot_precision
      value: 55.23268516495521
    - type: dot_recall
      value: 66.7018469656992
    - type: euclidean_accuracy
      value: 83.01841807236097
    - type: euclidean_ap
      value: 62.587389637610734
    - type: euclidean_f1
      value: 60.42787139954583
    - type: euclidean_precision
      value: 55.23268516495521
    - type: euclidean_recall
      value: 66.7018469656992
    - type: manhattan_accuracy
      value: 82.04684985396675
    - type: manhattan_ap
      value: 59.95337772978148
    - type: manhattan_f1
      value: 58.11441198134053
    - type: manhattan_precision
      value: 54.33884297520662
    - type: manhattan_recall
      value: 62.45382585751978
    - type: max_accuracy
      value: 83.01841807236097
    - type: max_ap
      value: 62.587389637610734
    - type: max_f1
      value: 60.42787139954583
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.69228082431016
    - type: cos_sim_ap
      value: 81.48688355409183
    - type: cos_sim_f1
      value: 73.30082742316786
    - type: cos_sim_precision
      value: 70.44873615450156
    - type: cos_sim_recall
      value: 76.3935940868494
    - type: dot_accuracy
      value: 86.69228082431016
    - type: dot_ap
      value: 81.48689290676025
    - type: dot_f1
      value: 73.30082742316786
    - type: dot_precision
      value: 70.44873615450156
    - type: dot_recall
      value: 76.3935940868494
    - type: euclidean_accuracy
      value: 86.69228082431016
    - type: euclidean_ap
      value: 81.48688312356714
    - type: euclidean_f1
      value: 73.30082742316786
    - type: euclidean_precision
      value: 70.44873615450156
    - type: euclidean_recall
      value: 76.3935940868494
    - type: manhattan_accuracy
      value: 86.649590561571
    - type: manhattan_ap
      value: 81.46446557002017
    - type: manhattan_f1
      value: 73.55033730231872
    - type: manhattan_precision
      value: 70.55661645095127
    - type: manhattan_recall
      value: 76.80936248845089
    - type: max_accuracy
      value: 86.69228082431016
    - type: max_ap
      value: 81.48689290676025
    - type: max_f1
      value: 73.55033730231872
---
