mteb model-index region:us
---
tags:
- mteb
model-index:
- name: fasttext_main_PCA_lower_gcp
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.92537313432837
    - type: ap
      value: 39.09594018546538
    - type: f1
      value: 69.9428592782495
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.669875
    - type: ap
      value: 62.33317529755745
    - type: f1
      value: 67.57760664151597
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.982000000000006
    - type: f1
      value: 32.4272011369089
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.131999999999998
    - type: map_at_10
      value: 32.364
    - type: map_at_100
      value: 33.591
    - type: map_at_1000
      value: 33.62
    - type: map_at_3
      value: 27.608
    - type: map_at_5
      value: 30.398999999999997
    - type: mrr_at_1
      value: 19.417
    - type: mrr_at_10
      value: 32.468
    - type: mrr_at_100
      value: 33.702
    - type: mrr_at_1000
      value: 33.731
    - type: mrr_at_3
      value: 27.703
    - type: mrr_at_5
      value: 30.525999999999996
    - type: ndcg_at_1
      value: 19.131999999999998
    - type: ndcg_at_10
      value: 40.150999999999996
    - type: ndcg_at_100
      value: 45.986
    - type: ndcg_at_1000
      value: 46.742
    - type: ndcg_at_3
      value: 30.381000000000004
    - type: ndcg_at_5
      value: 35.43
    - type: precision_at_1
      value: 19.131999999999998
    - type: precision_at_10
      value: 6.522
    - type: precision_at_100
      value: 0.922
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 12.802
    - type: precision_at_5
      value: 10.142
    - type: recall_at_1
      value: 19.131999999999998
    - type: recall_at_10
      value: 65.22
    - type: recall_at_100
      value: 92.24799999999999
    - type: recall_at_1000
      value: 98.151
    - type: recall_at_3
      value: 38.407000000000004
    - type: recall_at_5
      value: 50.711
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 38.195697272320295
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 30.8305090960797
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 51.94111195571449
    - type: mrr
      value: 64.8286285890164
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 66.07261251912074
    - type: cos_sim_spearman
      value: 65.11172457867025
    - type: euclidean_pearson
      value: 66.04669343047887
    - type: euclidean_spearman
      value: 65.11172457867025
    - type: manhattan_pearson
      value: 69.63607086934977
    - type: manhattan_spearman
      value: 68.55276684057421
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.99675324675324
    - type: f1
      value: 66.97580497914075
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.23958912729348
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 28.31865627812479
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 17.836
    - type: map_at_10
      value: 25.169999999999998
    - type: map_at_100
      value: 26.246000000000002
    - type: map_at_1000
      value: 26.395000000000003
    - type: map_at_3
      value: 22.698
    - type: map_at_5
      value: 24.12
    - type: mrr_at_1
      value: 23.462
    - type: mrr_at_10
      value: 30.471999999999998
    - type: mrr_at_100
      value: 31.308999999999997
    - type: mrr_at_1000
      value: 31.395
    - type: mrr_at_3
      value: 28.159
    - type: mrr_at_5
      value: 29.604000000000003
    - type: ndcg_at_1
      value: 23.462
    - type: ndcg_at_10
      value: 29.915000000000003
    - type: ndcg_at_100
      value: 35.007
    - type: ndcg_at_1000
      value: 38.251000000000005
    - type: ndcg_at_3
      value: 26.112000000000002
    - type: ndcg_at_5
      value: 27.92
    - type: precision_at_1
      value: 23.462
    - type: precision_at_10
      value: 5.951
    - type: precision_at_100
      value: 1.079
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_3
      value: 12.971
    - type: precision_at_5
      value: 9.642000000000001
    - type: recall_at_1
      value: 17.836
    - type: recall_at_10
      value: 38.538
    - type: recall_at_100
      value: 61.669
    - type: recall_at_1000
      value: 84.34
    - type: recall_at_3
      value: 27.124
    - type: recall_at_5
      value: 32.406
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.018
    - type: map_at_10
      value: 21.38
    - type: map_at_100
      value: 22.279
    - type: map_at_1000
      value: 22.404
    - type: map_at_3
      value: 19.479
    - type: map_at_5
      value: 20.485999999999997
    - type: mrr_at_1
      value: 20.637
    - type: mrr_at_10
      value: 25.993
    - type: mrr_at_100
      value: 26.717000000000002
    - type: mrr_at_1000
      value: 26.796
    - type: mrr_at_3
      value: 24.098
    - type: mrr_at_5
      value: 25.052999999999997
    - type: ndcg_at_1
      value: 20.637
    - type: ndcg_at_10
      value: 25.184
    - type: ndcg_at_100
      value: 29.292
    - type: ndcg_at_1000
      value: 32.277
    - type: ndcg_at_3
      value: 21.976000000000003
    - type: ndcg_at_5
      value: 23.32
    - type: precision_at_1
      value: 20.637
    - type: precision_at_10
      value: 4.8660000000000005
    - type: precision_at_100
      value: 0.873
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 10.637
    - type: precision_at_5
      value: 7.643
    - type: recall_at_1
      value: 16.018
    - type: recall_at_10
      value: 31.964
    - type: recall_at_100
      value: 49.986999999999995
    - type: recall_at_1000
      value: 70.64099999999999
    - type: recall_at_3
      value: 22.846
    - type: recall_at_5
      value: 26.503
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 21.718
    - type: map_at_10
      value: 29.471000000000004
    - type: map_at_100
      value: 30.532999999999998
    - type: map_at_1000
      value: 30.631999999999998
    - type: map_at_3
      value: 27.166
    - type: map_at_5
      value: 28.504
    - type: mrr_at_1
      value: 25.392
    - type: mrr_at_10
      value: 32.633
    - type: mrr_at_100
      value: 33.522
    - type: mrr_at_1000
      value: 33.593
    - type: mrr_at_3
      value: 30.366
    - type: mrr_at_5
      value: 31.704
    - type: ndcg_at_1
      value: 25.392
    - type: ndcg_at_10
      value: 33.967000000000006
    - type: ndcg_at_100
      value: 38.853
    - type: ndcg_at_1000
      value: 41.346
    - type: ndcg_at_3
      value: 29.559
    - type: ndcg_at_5
      value: 31.75
    - type: precision_at_1
      value: 25.392
    - type: precision_at_10
      value: 5.599
    - type: precision_at_100
      value: 0.88
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 13.25
    - type: precision_at_5
      value: 9.417
    - type: recall_at_1
      value: 21.718
    - type: recall_at_10
      value: 44.625
    - type: recall_at_100
      value: 66.322
    - type: recall_at_1000
      value: 84.83699999999999
    - type: recall_at_3
      value: 32.690999999999995
    - type: recall_at_5
      value: 38.073
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.169
    - type: map_at_10
      value: 14.082
    - type: map_at_100
      value: 14.748
    - type: map_at_1000
      value: 14.857000000000001
    - type: map_at_3
      value: 12.783
    - type: map_at_5
      value: 13.44
    - type: mrr_at_1
      value: 11.186
    - type: mrr_at_10
      value: 15.246
    - type: mrr_at_100
      value: 15.916
    - type: mrr_at_1000
      value: 16.019
    - type: mrr_at_3
      value: 13.936000000000002
    - type: mrr_at_5
      value: 14.62
    - type: ndcg_at_1
      value: 11.186
    - type: ndcg_at_10
      value: 16.669
    - type: ndcg_at_100
      value: 20.369
    - type: ndcg_at_1000
      value: 23.61
    - type: ndcg_at_3
      value: 13.969000000000001
    - type: ndcg_at_5
      value: 15.124
    - type: precision_at_1
      value: 11.186
    - type: precision_at_10
      value: 2.7119999999999997
    - type: precision_at_100
      value: 0.485
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 5.989
    - type: precision_at_5
      value: 4.316
    - type: recall_at_1
      value: 10.169
    - type: recall_at_10
      value: 23.679
    - type: recall_at_100
      value: 41.5
    - type: recall_at_1000
      value: 66.739
    - type: recall_at_3
      value: 16.192999999999998
    - type: recall_at_5
      value: 18.924
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.462
    - type: map_at_10
      value: 8.149000000000001
    - type: map_at_100
      value: 8.913
    - type: map_at_1000
      value: 9.016
    - type: map_at_3
      value: 7.175
    - type: map_at_5
      value: 7.724
    - type: mrr_at_1
      value: 7.338
    - type: mrr_at_10
      value: 10.526
    - type: mrr_at_100
      value: 11.371
    - type: mrr_at_1000
      value: 11.459999999999999
    - type: mrr_at_3
      value: 9.370000000000001
    - type: mrr_at_5
      value: 10.017
    - type: ndcg_at_1
      value: 7.338
    - type: ndcg_at_10
      value: 10.248
    - type: ndcg_at_100
      value: 14.352
    - type: ndcg_at_1000
      value: 17.622
    - type: ndcg_at_3
      value: 8.319
    - type: ndcg_at_5
      value: 9.232
    - type: precision_at_1
      value: 7.338
    - type: precision_at_10
      value: 1.9029999999999998
    - type: precision_at_100
      value: 0.47400000000000003
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 4.104
    - type: precision_at_5
      value: 3.06
    - type: recall_at_1
      value: 5.462
    - type: recall_at_10
      value: 14.59
    - type: recall_at_100
      value: 32.92
    - type: recall_at_1000
      value: 57.597
    - type: recall_at_3
      value: 9.131
    - type: recall_at_5
      value: 11.459999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.902
    - type: map_at_10
      value: 21.4
    - type: map_at_100
      value: 22.503999999999998
    - type: map_at_1000
      value: 22.634
    - type: map_at_3
      value: 19.633
    - type: map_at_5
      value: 20.505000000000003
    - type: mrr_at_1
      value: 18.864
    - type: mrr_at_10
      value: 25.070999999999998
    - type: mrr_at_100
      value: 26.0
    - type: mrr_at_1000
      value: 26.075
    - type: mrr_at_3
      value: 23.179
    - type: mrr_at_5
      value: 24.041
    - type: ndcg_at_1
      value: 18.864
    - type: ndcg_at_10
      value: 25.267
    - type: ndcg_at_100
      value: 30.689
    - type: ndcg_at_1000
      value: 33.639
    - type: ndcg_at_3
      value: 21.978
    - type: ndcg_at_5
      value: 23.255
    - type: precision_at_1
      value: 18.864
    - type: precision_at_10
      value: 4.562
    - type: precision_at_100
      value: 0.8959999999999999
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 10.202
    - type: precision_at_5
      value: 7.199
    - type: recall_at_1
      value: 15.902
    - type: recall_at_10
      value: 33.440999999999995
    - type: recall_at_100
      value: 57.260999999999996
    - type: recall_at_1000
      value: 77.699
    - type: recall_at_3
      value: 23.873
    - type: recall_at_5
      value: 27.261000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.815000000000001
    - type: map_at_10
      value: 16.415
    - type: map_at_100
      value: 17.366999999999997
    - type: map_at_1000
      value: 17.506
    - type: map_at_3
      value: 14.488999999999999
    - type: map_at_5
      value: 15.49
    - type: mrr_at_1
      value: 14.384
    - type: mrr_at_10
      value: 19.767000000000003
    - type: mrr_at_100
      value: 20.571
    - type: mrr_at_1000
      value: 20.673
    - type: mrr_at_3
      value: 17.618000000000002
    - type: mrr_at_5
      value: 18.651
    - type: ndcg_at_1
      value: 14.384
    - type: ndcg_at_10
      value: 20.003999999999998
    - type: ndcg_at_100
      value: 24.681
    - type: ndcg_at_1000
      value: 28.355000000000004
    - type: ndcg_at_3
      value: 16.188
    - type: ndcg_at_5
      value: 17.794999999999998
    - type: precision_at_1
      value: 14.384
    - type: precision_at_10
      value: 3.7670000000000003
    - type: precision_at_100
      value: 0.734
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 7.4959999999999996
    - type: precision_at_5
      value: 5.685
    - type: recall_at_1
      value: 11.815000000000001
    - type: recall_at_10
      value: 27.823999999999998
    - type: recall_at_100
      value: 48.269
    - type: recall_at_1000
      value: 74.62100000000001
    - type: recall_at_3
      value: 17.463
    - type: recall_at_5
      value: 21.368000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.581666666666669
    - type: map_at_10
      value: 17.372
    - type: map_at_100
      value: 18.233999999999998
    - type: map_at_1000
      value: 18.355583333333332
    - type: map_at_3
      value: 15.739500000000001
    - type: map_at_5
      value: 16.608833333333333
    - type: mrr_at_1
      value: 15.371833333333335
    - type: mrr_at_10
      value: 20.382583333333333
    - type: mrr_at_100
      value: 21.167
    - type: mrr_at_1000
      value: 21.254083333333334
    - type: mrr_at_3
      value: 18.69666666666667
    - type: mrr_at_5
      value: 19.604166666666668
    - type: ndcg_at_1
      value: 15.371833333333335
    - type: ndcg_at_10
      value: 20.707583333333332
    - type: ndcg_at_100
      value: 25.063166666666664
    - type: ndcg_at_1000
      value: 28.164666666666665
    - type: ndcg_at_3
      value: 17.675916666666666
    - type: ndcg_at_5
      value: 19.00775
    - type: precision_at_1
      value: 15.371833333333335
    - type: precision_at_10
      value: 3.764583333333333
    - type: precision_at_100
      value: 0.7164166666666668
    - type: precision_at_1000
      value: 0.11550000000000002
    - type: precision_at_3
      value: 8.251583333333334
    - type: precision_at_5
      value: 5.971666666666667
    - type: recall_at_1
      value: 12.581666666666669
    - type: recall_at_10
      value: 27.8755
    - type: recall_at_100
      value: 47.82383333333333
    - type: recall_at_1000
      value: 70.49825000000001
    - type: recall_at_3
      value: 19.260583333333333
    - type: recall_at_5
      value: 22.74125
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.5
    - type: map_at_10
      value: 13.592
    - type: map_at_100
      value: 14.357000000000001
    - type: map_at_1000
      value: 14.438
    - type: map_at_3
      value: 12.255
    - type: map_at_5
      value: 13.092
    - type: mrr_at_1
      value: 11.35
    - type: mrr_at_10
      value: 15.619
    - type: mrr_at_100
      value: 16.383
    - type: mrr_at_1000
      value: 16.455000000000002
    - type: mrr_at_3
      value: 14.264
    - type: mrr_at_5
      value: 15.146
    - type: ndcg_at_1
      value: 11.35
    - type: ndcg_at_10
      value: 16.253999999999998
    - type: ndcg_at_100
      value: 20.259
    - type: ndcg_at_1000
      value: 22.548000000000002
    - type: ndcg_at_3
      value: 13.753000000000002
    - type: ndcg_at_5
      value: 15.149000000000001
    - type: precision_at_1
      value: 11.35
    - type: precision_at_10
      value: 2.822
    - type: precision_at_100
      value: 0.518
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 6.442
    - type: precision_at_5
      value: 4.693
    - type: recall_at_1
      value: 9.5
    - type: recall_at_10
      value: 22.462
    - type: recall_at_100
      value: 41.229
    - type: recall_at_1000
      value: 58.413000000000004
    - type: recall_at_3
      value: 15.692999999999998
    - type: recall_at_5
      value: 19.264
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.6000000000000005
    - type: map_at_10
      value: 9.602
    - type: map_at_100
      value: 10.195
    - type: map_at_1000
      value: 10.302999999999999
    - type: map_at_3
      value: 8.609
    - type: map_at_5
      value: 9.110999999999999
    - type: mrr_at_1
      value: 8.741
    - type: mrr_at_10
      value: 11.999
    - type: mrr_at_100
      value: 12.61
    - type: mrr_at_1000
      value: 12.702
    - type: mrr_at_3
      value: 10.92
    - type: mrr_at_5
      value: 11.429
    - type: ndcg_at_1
      value: 8.741
    - type: ndcg_at_10
      value: 11.796
    - type: ndcg_at_100
      value: 14.995
    - type: ndcg_at_1000
      value: 18.177
    - type: ndcg_at_3
      value: 9.966
    - type: ndcg_at_5
      value: 10.663
    - type: precision_at_1
      value: 8.741
    - type: precision_at_10
      value: 2.268
    - type: precision_at_100
      value: 0.46299999999999997
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 4.886
    - type: precision_at_5
      value: 3.496
    - type: recall_at_1
      value: 6.6000000000000005
    - type: recall_at_10
      value: 16.207
    - type: recall_at_100
      value: 31.034
    - type: recall_at_1000
      value: 54.910000000000004
    - type: recall_at_3
      value: 10.822
    - type: recall_at_5
      value: 12.793
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.584999999999999
    - type: map_at_10
      value: 15.998000000000001
    - type: map_at_100
      value: 16.771
    - type: map_at_1000
      value: 16.884
    - type: map_at_3
      value: 14.765
    - type: map_at_5
      value: 15.386
    - type: mrr_at_1
      value: 13.899000000000001
    - type: mrr_at_10
      value: 18.878
    - type: mrr_at_100
      value: 19.648
    - type: mrr_at_1000
      value: 19.743
    - type: mrr_at_3
      value: 17.474999999999998
    - type: mrr_at_5
      value: 18.221
    - type: ndcg_at_1
      value: 13.899000000000001
    - type: ndcg_at_10
      value: 19.084
    - type: ndcg_at_100
      value: 23.384
    - type: ndcg_at_1000
      value: 26.606999999999996
    - type: ndcg_at_3
      value: 16.573
    - type: ndcg_at_5
      value: 17.610999999999997
    - type: precision_at_1
      value: 13.899000000000001
    - type: precision_at_10
      value: 3.2649999999999997
    - type: precision_at_100
      value: 0.61
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 7.710999999999999
    - type: precision_at_5
      value: 5.373
    - type: recall_at_1
      value: 11.584999999999999
    - type: recall_at_10
      value: 25.928
    - type: recall_at_100
      value: 46.012
    - type: recall_at_1000
      value: 69.754
    - type: recall_at_3
      value: 18.761
    - type: recall_at_5
      value: 21.416
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.586
    - type: map_at_10
      value: 19.008
    - type: map_at_100
      value: 19.976
    - type: map_at_1000
      value: 20.177999999999997
    - type: map_at_3
      value: 16.872
    - type: map_at_5
      value: 17.959
    - type: mrr_at_1
      value: 17.194000000000003
    - type: mrr_at_10
      value: 22.716
    - type: mrr_at_100
      value: 23.53
    - type: mrr_at_1000
      value: 23.619
    - type: mrr_at_3
      value: 20.619
    - type: mrr_at_5
      value: 21.834999999999997
    - type: ndcg_at_1
      value: 17.194000000000003
    - type: ndcg_at_10
      value: 23.351
    - type: ndcg_at_100
      value: 27.750999999999998
    - type: ndcg_at_1000
      value: 31.435000000000002
    - type: ndcg_at_3
      value: 19.665
    - type: ndcg_at_5
      value: 21.275
    - type: precision_at_1
      value: 17.194000000000003
    - type: precision_at_10
      value: 4.743
    - type: precision_at_100
      value: 1.051
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 9.354
    - type: precision_at_5
      value: 6.9959999999999996
    - type: recall_at_1
      value: 13.586
    - type: recall_at_10
      value: 31.841
    - type: recall_at_100
      value: 52.489
    - type: recall_at_1000
      value: 78.16199999999999
    - type: recall_at_3
      value: 20.738
    - type: recall_at_5
      value: 25.263
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.789
    - type: map_at_10
      value: 14.197000000000001
    - type: map_at_100
      value: 14.918999999999999
    - type: map_at_1000
      value: 15.02
    - type: map_at_3
      value: 12.950000000000001
    - type: map_at_5
      value: 13.489
    - type: mrr_at_1
      value: 12.015
    - type: mrr_at_10
      value: 15.671
    - type: mrr_at_100
      value: 16.427
    - type: mrr_at_1000
      value: 16.519000000000002
    - type: mrr_at_3
      value: 14.356
    - type: mrr_at_5
      value: 14.929
    - type: ndcg_at_1
      value: 12.015
    - type: ndcg_at_10
      value: 16.752
    - type: ndcg_at_100
      value: 21.126
    - type: ndcg_at_1000
      value: 24.108999999999998
    - type: ndcg_at_3
      value: 14.052999999999999
    - type: ndcg_at_5
      value: 14.999
    - type: precision_at_1
      value: 12.015
    - type: precision_at_10
      value: 2.717
    - type: precision_at_100
      value: 0.534
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 5.976999999999999
    - type: precision_at_5
      value: 4.14
    - type: recall_at_1
      value: 10.789
    - type: recall_at_10
      value: 23.407
    - type: recall_at_100
      value: 45.194
    - type: recall_at_1000
      value: 68.266
    - type: recall_at_3
      value: 15.792
    - type: recall_at_5
      value: 18.163999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.371
    - type: map_at_10
      value: 11.183
    - type: map_at_100
      value: 12.603
    - type: map_at_1000
      value: 12.781999999999998
    - type: map_at_3
      value: 9.303
    - type: map_at_5
      value: 10.323
    - type: mrr_at_1
      value: 14.593
    - type: mrr_at_10
      value: 23.125
    - type: mrr_at_100
      value: 24.296
    - type: mrr_at_1000
      value: 24.362000000000002
    - type: mrr_at_3
      value: 20.206
    - type: mrr_at_5
      value: 22.034000000000002
    - type: ndcg_at_1
      value: 14.593
    - type: ndcg_at_10
      value: 16.667
    - type: ndcg_at_100
      value: 23.205000000000002
    - type: ndcg_at_1000
      value: 26.889000000000003
    - type: ndcg_at_3
      value: 13.213
    - type: ndcg_at_5
      value: 14.635000000000002
    - type: precision_at_1
      value: 14.593
    - type: precision_at_10
      value: 5.362
    - type: precision_at_100
      value: 1.2309999999999999
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 9.837
    - type: precision_at_5
      value: 7.974
    - type: recall_at_1
      value: 6.371
    - type: recall_at_10
      value: 20.580000000000002
    - type: recall_at_100
      value: 43.668
    - type: recall_at_1000
      value: 64.782
    - type: recall_at_3
      value: 12.485
    - type: recall_at_5
      value: 16.152
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.7640000000000002
    - type: map_at_10
      value: 6.632000000000001
    - type: map_at_100
      value: 9.34
    - type: map_at_1000
      value: 10.02
    - type: map_at_3
      value: 4.65
    - type: map_at_5
      value: 5.441
    - type: mrr_at_1
      value: 32.0
    - type: mrr_at_10
      value: 42.124
    - type: mrr_at_100
      value: 42.794
    - type: mrr_at_1000
      value: 42.836
    - type: mrr_at_3
      value: 39.417
    - type: mrr_at_5
      value: 40.954
    - type: ndcg_at_1
      value: 23.375
    - type: ndcg_at_10
      value: 18.224
    - type: ndcg_at_100
      value: 20.645
    - type: ndcg_at_1000
      value: 26.509
    - type: ndcg_at_3
      value: 20.621000000000002
    - type: ndcg_at_5
      value: 19.222
    - type: precision_at_1
      value: 32.0
    - type: precision_at_10
      value: 16.925
    - type: precision_at_100
      value: 5.17
    - type: precision_at_1000
      value: 1.08
    - type: precision_at_3
      value: 25.333
    - type: precision_at_5
      value: 21.2
    - type: recall_at_1
      value: 2.7640000000000002
    - type: recall_at_10
      value: 10.572
    - type: recall_at_100
      value: 26.006
    - type: recall_at_1000
      value: 46.544999999999995
    - type: recall_at_3
      value: 5.628
    - type: recall_at_5
      value: 7.310999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 37.205000000000005
    - type: f1
      value: 34.1038142158891
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 10.462
    - type: map_at_10
      value: 15.586
    - type: map_at_100
      value: 16.297
    - type: map_at_1000
      value: 16.365
    - type: map_at_3
      value: 13.91
    - type: map_at_5
      value: 14.799999999999999
    - type: mrr_at_1
      value: 11.100999999999999
    - type: mrr_at_10
      value: 16.462
    - type: mrr_at_100
      value: 17.192
    - type: mrr_at_1000
      value: 17.256
    - type: mrr_at_3
      value: 14.713999999999999
    - type: mrr_at_5
      value: 15.641
    - type: ndcg_at_1
      value: 11.100999999999999
    - type: ndcg_at_10
      value: 18.783
    - type: ndcg_at_100
      value: 22.557
    - type: ndcg_at_1000
      value: 24.573999999999998
    - type: ndcg_at_3
      value: 15.251000000000001
    - type: ndcg_at_5
      value: 16.861
    - type: precision_at_1
      value: 11.100999999999999
    - type: precision_at_10
      value: 3.026
    - type: precision_at_100
      value: 0.506
    - type: precision_at_1000
      value: 0.06999999999999999
    - type: precision_at_3
      value: 6.526
    - type: precision_at_5
      value: 4.755
    - type: recall_at_1
      value: 10.462
    - type: recall_at_10
      value: 28.055000000000003
    - type: recall_at_100
      value: 45.988
    - type: recall_at_1000
      value: 61.816
    - type: recall_at_3
      value: 18.362000000000002
    - type: recall_at_5
      value: 22.221
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.5649999999999995
    - type: map_at_10
      value: 9.06
    - type: map_at_100
      value: 10.016
    - type: map_at_1000
      value: 10.2
    - type: map_at_3
      value: 7.693999999999999
    - type: map_at_5
      value: 8.49
    - type: mrr_at_1
      value: 10.957
    - type: mrr_at_10
      value: 16.016
    - type: mrr_at_100
      value: 17.006
    - type: mrr_at_1000
      value: 17.104
    - type: mrr_at_3
      value: 14.198
    - type: mrr_at_5
      value: 15.278
    - type: ndcg_at_1
      value: 10.957
    - type: ndcg_at_10
      value: 12.642999999999999
    - type: ndcg_at_100
      value: 17.833
    - type: ndcg_at_1000
      value: 22.187
    - type: ndcg_at_3
      value: 10.535
    - type: ndcg_at_5
      value: 11.469999999999999
    - type: precision_at_1
      value: 10.957
    - type: precision_at_10
      value: 3.58
    - type: precision_at_100
      value: 0.8670000000000001
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 7.047000000000001
    - type: precision_at_5
      value: 5.432
    - type: recall_at_1
      value: 5.5649999999999995
    - type: recall_at_10
      value: 16.374
    - type: recall_at_100
      value: 37.447
    - type: recall_at_1000
      value: 64.5
    - type: recall_at_3
      value: 10.11
    - type: recall_at_5
      value: 13.119
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 10.682
    - type: map_at_10
      value: 14.898
    - type: map_at_100
      value: 15.536
    - type: map_at_1000
      value: 15.626000000000001
    - type: map_at_3
      value: 13.578000000000001
    - type: map_at_5
      value: 14.280999999999999
    - type: mrr_at_1
      value: 21.364
    - type: mrr_at_10
      value: 26.673000000000002
    - type: mrr_at_100
      value: 27.317000000000004
    - type: mrr_at_1000
      value: 27.383999999999997
    - type: mrr_at_3
      value: 25.012
    - type: mrr_at_5
      value: 25.930999999999997
    - type: ndcg_at_1
      value: 21.364
    - type: ndcg_at_10
      value: 19.708000000000002
    - type: ndcg_at_100
      value: 22.977
    - type: ndcg_at_1000
      value: 25.454
    - type: ndcg_at_3
      value: 16.949
    - type: ndcg_at_5
      value: 18.233
    - type: precision_at_1
      value: 21.364
    - type: precision_at_10
      value: 4.47
    - type: precision_at_100
      value: 0.712
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 10.722
    - type: precision_at_5
      value: 7.449
    - type: recall_at_1
      value: 10.682
    - type: recall_at_10
      value: 22.35
    - type: recall_at_100
      value: 35.598
    - type: recall_at_1000
      value: 52.323
    - type: recall_at_3
      value: 16.084
    - type: recall_at_5
      value: 18.623
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 67.54279999999999
    - type: ap
      value: 61.86466459164338
    - type: f1
      value: 67.30679239744363
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.685
    - type: map_at_10
      value: 9.54
    - type: map_at_100
      value: 10.333
    - type: map_at_1000
      value: 10.43
    - type: map_at_3
      value: 8.023
    - type: map_at_5
      value: 8.818
    - type: mrr_at_1
      value: 5.86
    - type: mrr_at_10
      value: 9.783
    - type: mrr_at_100
      value: 10.589
    - type: mrr_at_1000
      value: 10.684000000000001
    - type: mrr_at_3
      value: 8.251999999999999
    - type: mrr_at_5
      value: 9.049
    - type: ndcg_at_1
      value: 5.817
    - type: ndcg_at_10
      value: 12.02
    - type: ndcg_at_100
      value: 16.476
    - type: ndcg_at_1000
      value: 19.448
    - type: ndcg_at_3
      value: 8.863999999999999
    - type: ndcg_at_5
      value: 10.284
    - type: precision_at_1
      value: 5.817
    - type: precision_at_10
      value: 2.052
    - type: precision_at_100
      value: 0.438
    - type: precision_at_1000
      value: 0.06999999999999999
    - type: precision_at_3
      value: 3.816
    - type: precision_at_5
      value: 3.0
    - type: recall_at_1
      value: 5.685
    - type: recall_at_10
      value: 19.785
    - type: recall_at_100
      value: 41.772999999999996
    - type: recall_at_1000
      value: 65.71900000000001
    - type: recall_at_3
      value: 11.113000000000001
    - type: recall_at_5
      value: 14.501
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.47378020975832
    - type: f1
      value: 86.88587239247583
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 63.39717282261742
    - type: f1
      value: 43.928052359223294
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.26765299260255
    - type: f1
      value: 58.35346013202813
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.20107599193005
    - type: f1
      value: 66.56682675618504
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.20300002939281
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.03355681231367
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.841410495856824
    - type: mrr
      value: 30.87222936013429
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.8350000000000004
    - type: map_at_10
      value: 8.227
    - type: map_at_100
      value: 10.166
    - type: map_at_1000
      value: 11.403
    - type: map_at_3
      value: 6.433999999999999
    - type: map_at_5
      value: 7.342
    - type: mrr_at_1
      value: 32.817
    - type: mrr_at_10
      value: 42.941
    - type: mrr_at_100
      value: 43.653999999999996
    - type: mrr_at_1000
      value: 43.718
    - type: mrr_at_3
      value: 40.351
    - type: mrr_at_5
      value: 42.022999999999996
    - type: ndcg_at_1
      value: 30.495
    - type: ndcg_at_10
      value: 24.187
    - type: ndcg_at_100
      value: 22.866
    - type: ndcg_at_1000
      value: 32.615
    - type: ndcg_at_3
      value: 28.03
    - type: ndcg_at_5
      value: 26.499
    - type: precision_at_1
      value: 32.507999999999996
    - type: precision_at_10
      value: 17.616
    - type: precision_at_100
      value: 6.09
    - type: precision_at_1000
      value: 1.9369999999999998
    - type: precision_at_3
      value: 26.522000000000002
    - type: precision_at_5
      value: 22.724
    - type: recall_at_1
      value: 3.8350000000000004
    - type: recall_at_10
      value: 12.073
    - type: recall_at_100
      value: 24.598
    - type: recall_at_1000
      value: 59.270999999999994
    - type: recall_at_3
      value: 7.957
    - type: recall_at_5
      value: 9.91
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 6.601999999999999
    - type: map_at_10
      value: 11.73
    - type: map_at_100
      value: 12.754999999999999
    - type: map_at_1000
      value: 12.859000000000002
    - type: map_at_3
      value: 9.824
    - type: map_at_5
      value: 10.788
    - type: mrr_at_1
      value: 7.619
    - type: mrr_at_10
      value: 13.056000000000001
    - type: mrr_at_100
      value: 14.027000000000001
    - type: mrr_at_1000
      value: 14.118
    - type: mrr_at_3
      value: 11.061
    - type: mrr_at_5
      value: 12.059000000000001
    - type: ndcg_at_1
      value: 7.619
    - type: ndcg_at_10
      value: 15.177
    - type: ndcg_at_100
      value: 20.477
    - type: ndcg_at_1000
      value: 23.355
    - type: ndcg_at_3
      value: 11.169
    - type: ndcg_at_5
      value: 12.895000000000001
    - type: precision_at_1
      value: 7.619
    - type: precision_at_10
      value: 2.935
    - type: precision_at_100
      value: 0.592
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 5.398
    - type: precision_at_5
      value: 4.218
    - type: recall_at_1
      value: 6.601999999999999
    - type: recall_at_10
      value: 24.602
    - type: recall_at_100
      value: 49.481
    - type: recall_at_1000
      value: 71.64
    - type: recall_at_3
      value: 13.84
    - type: recall_at_5
      value: 17.871000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 57.667
    - type: map_at_10
      value: 69.714
    - type: map_at_100
      value: 70.54599999999999
    - type: map_at_1000
      value: 70.59
    - type: map_at_3
      value: 66.774
    - type: map_at_5
      value: 68.54299999999999
    - type: mrr_at_1
      value: 66.41
    - type: mrr_at_10
      value: 74.311
    - type: mrr_at_100
      value: 74.654
    - type: mrr_at_1000
      value: 74.665
    - type: mrr_at_3
      value: 72.565
    - type: mrr_at_5
      value: 73.664
    - type: ndcg_at_1
      value: 66.44
    - type: ndcg_at_10
      value: 74.772
    - type: ndcg_at_100
      value: 77.42999999999999
    - type: ndcg_at_1000
      value: 78.037
    - type: ndcg_at_3
      value: 70.784
    - type: ndcg_at_5
      value: 72.83800000000001
    - type: precision_at_1
      value: 66.44
    - type: precision_at_10
      value: 11.347
    - type: precision_at_100
      value: 1.4000000000000001
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 30.723
    - type: precision_at_5
      value: 20.422
    - type: recall_at_1
      value: 57.667
    - type: recall_at_10
      value: 84.863
    - type: recall_at_100
      value: 95.293
    - type: recall_at_1000
      value: 98.989
    - type: recall_at_3
      value: 73.505
    - type: recall_at_5
      value: 79.12
    - type: map_at_1
      value: 2.6229999999999998
    - type: map_at_10
      value: 5.954000000000001
    - type: map_at_100
      value: 7.136000000000001
    - type: map_at_1000
      value: 7.369000000000001
    - type: map_at_3
      value: 4.468
    - type: map_at_5
      value: 5.313
    - type: mrr_at_1
      value: 12.9
    - type: mrr_at_10
      value: 20.180999999999997
    - type: mrr_at_100
      value: 21.259
    - type: mrr_at_1000
      value: 21.361
    - type: mrr_at_3
      value: 17.683
    - type: mrr_at_5
      value: 18.918
    - type: ndcg_at_1
      value: 12.9
    - type: ndcg_at_10
      value: 10.798
    - type: ndcg_at_100
      value: 16.567
    - type: ndcg_at_1000
      value: 21.644
    - type: ndcg_at_3
      value: 10.357
    - type: ndcg_at_5
      value: 9.075999999999999
    - type: precision_at_1
      value: 12.9
    - type: precision_at_10
      value: 5.52
    - type: precision_at_100
      value: 1.406
    - type: precision_at_1000
      value: 0.263
    - type: precision_at_3
      value: 9.567
    - type: precision_at_5
      value: 7.9
    - type: recall_at_1
      value: 2.6229999999999998
    - type: recall_at_10
      value: 11.21
    - type: recall_at_100
      value: 28.527
    - type: recall_at_1000
      value: 53.507000000000005
    - type: recall_at_3
      value: 5.8229999999999995
    - type: recall_at_5
      value: 8.027
    - type: map_at_1
      value: 0.148
    - type: map_at_10
      value: 0.786
    - type: map_at_100
      value: 3.723
    - type: map_at_1000
      value: 9.252
    - type: map_at_3
      value: 0.34199999999999997
    - type: map_at_5
      value: 0.46299999999999997
    - type: mrr_at_1
      value: 56.00000000000001
    - type: mrr_at_10
      value: 63.775000000000006
    - type: mrr_at_100
      value: 64.72
    - type: mrr_at_1000
      value: 64.72
    - type: mrr_at_3
      value: 61.667
    - type: mrr_at_5
      value: 63.06699999999999
    - type: ndcg_at_1
      value: 51.0
    - type: ndcg_at_10
      value: 38.761
    - type: ndcg_at_100
      value: 28.68
    - type: ndcg_at_1000
      value: 26.976
    - type: ndcg_at_3
      value: 44.682
    - type: ndcg_at_5
      value: 40.465
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 41.4
    - type: precision_at_100
      value: 29.9
    - type: precision_at_1000
      value: 13.075999999999999
    - type: precision_at_3
      value: 49.333
    - type: precision_at_5
      value: 43.2
    - type: recall_at_1
      value: 0.148
    - type: recall_at_10
      value: 0.9939999999999999
    - type: recall_at_100
      value: 6.601
    - type: recall_at_1000
      value: 26.717000000000002
    - type: recall_at_3
      value: 0.373
    - type: recall_at_5
      value: 0.532
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 36.21220747836975
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 44.00927310697719
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 71.53829609440724
    - type: cos_sim_spearman
      value: 62.081870620686516
    - type: euclidean_pearson
      value: 66.75919822051951
    - type: euclidean_spearman
      value: 62.08205566066758
    - type: manhattan_pearson
      value: 67.65206493169866
    - type: manhattan_spearman
      value: 62.450943140770875
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 60.268401821491516
    - type: cos_sim_spearman
      value: 54.72813175040998
    - type: euclidean_pearson
      value: 57.727785718156085
    - type: euclidean_spearman
      value: 54.72819282258163
    - type: manhattan_pearson
      value: 61.08601644705001
    - type: manhattan_spearman
      value: 57.419364847076416
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 70.53595268992352
    - type: cos_sim_spearman
      value: 72.77614149082761
    - type: euclidean_pearson
      value: 71.98176254430747
    - type: euclidean_spearman
      value: 72.77609312192283
    - type: manhattan_pearson
      value: 73.6463552704273
    - type: manhattan_spearman
      value: 74.3519202610035
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 69.53013033897608
    - type: cos_sim_spearman
      value: 66.79176523643766
    - type: euclidean_pearson
      value: 68.89815253634572
    - type: euclidean_spearman
      value: 66.79172925453702
    - type: manhattan_pearson
      value: 69.92961478202851
    - type: manhattan_spearman
      value: 67.64600960450629
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 73.98223162795816
    - type: cos_sim_spearman
      value: 75.33223462639201
    - type: euclidean_pearson
      value: 75.12573234119537
    - type: euclidean_spearman
      value: 75.33223494582792
    - type: manhattan_pearson
      value: 77.19391533513549
    - type: manhattan_spearman
      value: 77.45924928333606
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 73.22401536332508
    - type: cos_sim_spearman
      value: 74.42508873196522
    - type: euclidean_pearson
      value: 73.63586462754998
    - type: euclidean_spearman
      value: 74.42563924854562
    - type: manhattan_pearson
      value: 74.74324567485226
    - type: manhattan_spearman
      value: 75.57557015276247
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 76.73084119951304
    - type: cos_sim_spearman
      value: 78.88653583172292
    - type: euclidean_pearson
      value: 77.75652701912318
    - type: euclidean_spearman
      value: 78.88741294422042
    - type: manhattan_pearson
      value: 78.59665559928332
    - type: manhattan_spearman
      value: 79.46204745875241
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 59.39107452213269
    - type: cos_sim_spearman
      value: 59.943495188017515
    - type: euclidean_pearson
      value: 60.80952887001959
    - type: euclidean_spearman
      value: 59.943495188017515
    - type: manhattan_pearson
      value: 62.389596220621826
    - type: manhattan_spearman
      value: 60.845420045930254
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 69.82535423376984
    - type: cos_sim_spearman
      value: 67.86777525334008
    - type: euclidean_pearson
      value: 69.3521650052635
    - type: euclidean_spearman
      value: 67.86781213000704
    - type: manhattan_pearson
      value: 71.50710647072803
    - type: manhattan_spearman
      value: 69.75330140742277
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.894948115562
    - type: mrr
      value: 90.625872856265
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 30.361
    - type: map_at_10
      value: 38.190000000000005
    - type: map_at_100
      value: 39.156
    - type: map_at_1000
      value: 39.225
    - type: map_at_3
      value: 35.519
    - type: map_at_5
      value: 36.973
    - type: mrr_at_1
      value: 32.333
    - type: mrr_at_10
      value: 39.646
    - type: mrr_at_100
      value: 40.524
    - type: mrr_at_1000
      value: 40.583000000000006
    - type: mrr_at_3
      value: 37.111
    - type: mrr_at_5
      value: 38.661
    - type: ndcg_at_1
      value: 32.333
    - type: ndcg_at_10
      value: 42.72
    - type: ndcg_at_100
      value: 47.772
    - type: ndcg_at_1000
      value: 49.79
    - type: ndcg_at_3
      value: 37.521
    - type: ndcg_at_5
      value: 40.048
    - type: precision_at_1
      value: 32.333
    - type: precision_at_10
      value: 6.133
    - type: precision_at_100
      value: 0.897
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 15.0
    - type: precision_at_5
      value: 10.4
    - type: recall_at_1
      value: 30.361
    - type: recall_at_10
      value: 55.417
    - type: recall_at_100
      value: 79.739
    - type: recall_at_1000
      value: 95.85000000000001
    - type: recall_at_3
      value: 41.667
    - type: recall_at_5
      value: 47.611
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.58514851485148
    - type: cos_sim_ap
      value: 84.06841835548504
    - type: cos_sim_f1
      value: 77.32067510548524
    - type: cos_sim_precision
      value: 81.80803571428571
    - type: cos_sim_recall
      value: 73.3
    - type: dot_accuracy
      value: 99.58514851485148
    - type: dot_ap
      value: 84.06841835548504
    - type: dot_f1
      value: 77.32067510548524
    - type: dot_precision
      value: 81.80803571428571
    - type: dot_recall
      value: 73.3
    - type: euclidean_accuracy
      value: 99.58514851485148
    - type: euclidean_ap
      value: 84.06841835548504
    - type: euclidean_f1
      value: 77.32067510548524
    - type: euclidean_precision
      value: 81.80803571428571
    - type: euclidean_recall
      value: 73.3
    - type: manhattan_accuracy
      value: 99.64455445544554
    - type: manhattan_ap
      value: 87.74958362085812
    - type: manhattan_f1
      value: 80.47767393561786
    - type: manhattan_precision
      value: 83.69330453563715
    - type: manhattan_recall
      value: 77.5
    - type: max_accuracy
      value: 99.64455445544554
    - type: max_ap
      value: 87.74958362085812
    - type: max_f1
      value: 80.47767393561786
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 47.99636899846141
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.79193394084528
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 40.159974561686546
    - type: mrr
      value: 40.4807529072235
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.65509639451624
    - type: cos_sim_spearman
      value: 31.41189775849934
    - type: dot_pearson
      value: 30.655096211643336
    - type: dot_spearman
      value: 31.349184830663212
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.17
    - type: map_at_10
      value: 6.811
    - type: map_at_100
      value: 10.982
    - type: map_at_1000
      value: 12.651000000000002
    - type: map_at_3
      value: 3.1220000000000003
    - type: map_at_5
      value: 5.136
    - type: mrr_at_1
      value: 20.408
    - type: mrr_at_10
      value: 35.838
    - type: mrr_at_100
      value: 36.895
    - type: mrr_at_1000
      value: 36.899
    - type: mrr_at_3
      value: 30.952
    - type: mrr_at_5
      value: 33.81
    - type: ndcg_at_1
      value: 17.347
    - type: ndcg_at_10
      value: 18.073
    - type: ndcg_at_100
      value: 28.754999999999995
    - type: ndcg_at_1000
      value: 41.483
    - type: ndcg_at_3
      value: 18.209
    - type: ndcg_at_5
      value: 19.48
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 17.959
    - type: precision_at_100
      value: 6.734999999999999
    - type: precision_at_1000
      value: 1.48
    - type: precision_at_3
      value: 20.408
    - type: precision_at_5
      value: 22.041
    - type: recall_at_1
      value: 1.17
    - type: recall_at_10
      value: 12.386
    - type: recall_at_100
      value: 40.03
    - type: recall_at_1000
      value: 78.783
    - type: recall_at_3
      value: 4.511
    - type: recall_at_5
      value: 8.06
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.8118
    - type: ap
      value: 14.301595929800854
    - type: f1
      value: 54.57046391478173
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.94850028296547
    - type: f1
      value: 53.1489929211228
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.55309406800294
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.77266495797818
    - type: cos_sim_ap
      value: 57.03204699728573
    - type: cos_sim_f1
      value: 56.84717208182912
    - type: cos_sim_precision
      value: 52.256637168141594
    - type: cos_sim_recall
      value: 62.321899736147756
    - type: dot_accuracy
      value: 81.77266495797818
    - type: dot_ap
      value: 57.03204699728573
    - type: dot_f1
      value: 56.84717208182912
    - type: dot_precision
      value: 52.256637168141594
    - type: dot_recall
      value: 62.321899736147756
    - type: euclidean_accuracy
      value: 81.77266495797818
    - type: euclidean_ap
      value: 57.03204699728573
    - type: euclidean_f1
      value: 56.84717208182912
    - type: euclidean_precision
      value: 52.256637168141594
    - type: euclidean_recall
      value: 62.321899736147756
    - type: manhattan_accuracy
      value: 81.48655897955534
    - type: manhattan_ap
      value: 56.08576263049104
    - type: manhattan_f1
      value: 55.68435131520285
    - type: manhattan_precision
      value: 48.20532612890776
    - type: manhattan_recall
      value: 65.91029023746702
    - type: max_accuracy
      value: 81.77266495797818
    - type: max_ap
      value: 57.03204699728573
    - type: max_f1
      value: 56.84717208182912
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.93095820235185
    - type: cos_sim_ap
      value: 81.14067889412526
    - type: cos_sim_f1
      value: 73.27322907083716
    - type: cos_sim_precision
      value: 70.17692253471488
    - type: cos_sim_recall
      value: 76.65537419156145
    - type: dot_accuracy
      value: 86.93095820235185
    - type: dot_ap
      value: 81.14067889412526
    - type: dot_f1
      value: 73.27322907083716
    - type: dot_precision
      value: 70.17692253471488
    - type: dot_recall
      value: 76.65537419156145
    - type: euclidean_accuracy
      value: 86.93095820235185
    - type: euclidean_ap
      value: 81.14067861525255
    - type: euclidean_f1
      value: 73.27322907083716
    - type: euclidean_precision
      value: 70.17692253471488
    - type: euclidean_recall
      value: 76.65537419156145
    - type: manhattan_accuracy
      value: 86.93872006830442
    - type: manhattan_ap
      value: 81.37252100647802
    - type: manhattan_f1
      value: 73.71998998175248
    - type: manhattan_precision
      value: 68.85903348706637
    - type: manhattan_recall
      value: 79.31937172774869
    - type: max_accuracy
      value: 86.93872006830442
    - type: max_ap
      value: 81.37252100647802
    - type: max_f1
      value: 73.71998998175248
---
