mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_200
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.28358208955224
    - type: ap
      value: 33.66386574331778
    - type: f1
      value: 65.12063489555823
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.02680000000001
    - type: ap
      value: 60.070622711685154
    - type: f1
      value: 64.78260173963163
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.3
    - type: f1
      value: 33.7662445845029
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.341
    - type: map_at_10
      value: 33.341
    - type: map_at_100
      value: 34.624
    - type: map_at_1000
      value: 34.654
    - type: map_at_3
      value: 29.195999999999998
    - type: map_at_5
      value: 31.479000000000003
    - type: mrr_at_1
      value: 21.053
    - type: mrr_at_10
      value: 33.6
    - type: mrr_at_100
      value: 34.882999999999996
    - type: mrr_at_1000
      value: 34.913
    - type: mrr_at_3
      value: 29.421999999999997
    - type: mrr_at_5
      value: 31.740000000000002
    - type: ndcg_at_1
      value: 20.341
    - type: ndcg_at_10
      value: 40.826
    - type: ndcg_at_100
      value: 46.908
    - type: ndcg_at_1000
      value: 47.668
    - type: ndcg_at_3
      value: 32.193
    - type: ndcg_at_5
      value: 36.33
    - type: precision_at_1
      value: 20.341
    - type: precision_at_10
      value: 6.486
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.632
    - type: precision_at_5
      value: 10.199
    - type: recall_at_1
      value: 20.341
    - type: recall_at_10
      value: 64.865
    - type: recall_at_100
      value: 92.959
    - type: recall_at_1000
      value: 98.86200000000001
    - type: recall_at_3
      value: 40.896
    - type: recall_at_5
      value: 50.995999999999995
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 32.63202519294819
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 22.783776496468455
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.48633508778761
    - type: mrr
      value: 67.45174339357165
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.88720886246492
    - type: cos_sim_spearman
      value: 77.41381211899598
    - type: euclidean_pearson
      value: 78.55889174914572
    - type: euclidean_spearman
      value: 77.41381211899598
    - type: manhattan_pearson
      value: 79.12804749919536
    - type: manhattan_spearman
      value: 77.78851945213748
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 70.7792207792208
    - type: f1
      value: 69.8536410744015
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 31.335127380323787
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 22.292135810452425
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.015
    - type: map_at_10
      value: 27.367
    - type: map_at_100
      value: 28.445999999999998
    - type: map_at_1000
      value: 28.594
    - type: map_at_3
      value: 25.041000000000004
    - type: map_at_5
      value: 26.36
    - type: mrr_at_1
      value: 25.322
    - type: mrr_at_10
      value: 32.632
    - type: mrr_at_100
      value: 33.476
    - type: mrr_at_1000
      value: 33.553
    - type: mrr_at_3
      value: 30.544
    - type: mrr_at_5
      value: 31.680999999999997
    - type: ndcg_at_1
      value: 25.322
    - type: ndcg_at_10
      value: 32.147
    - type: ndcg_at_100
      value: 37.099
    - type: ndcg_at_1000
      value: 40.354
    - type: ndcg_at_3
      value: 28.565
    - type: ndcg_at_5
      value: 30.153999999999996
    - type: precision_at_1
      value: 25.322
    - type: precision_at_10
      value: 6.209
    - type: precision_at_100
      value: 1.0739999999999998
    - type: precision_at_1000
      value: 0.164
    - type: precision_at_3
      value: 13.733999999999998
    - type: precision_at_5
      value: 10.100000000000001
    - type: recall_at_1
      value: 20.015
    - type: recall_at_10
      value: 40.727000000000004
    - type: recall_at_100
      value: 62.831
    - type: recall_at_1000
      value: 85.287
    - type: recall_at_3
      value: 30.23
    - type: recall_at_5
      value: 34.589
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.783
    - type: map_at_10
      value: 20.898
    - type: map_at_100
      value: 21.797
    - type: map_at_1000
      value: 21.924
    - type: map_at_3
      value: 19.247
    - type: map_at_5
      value: 20.145
    - type: mrr_at_1
      value: 19.936
    - type: mrr_at_10
      value: 24.984
    - type: mrr_at_100
      value: 25.752000000000002
    - type: mrr_at_1000
      value: 25.832
    - type: mrr_at_3
      value: 23.238
    - type: mrr_at_5
      value: 24.149
    - type: ndcg_at_1
      value: 19.936
    - type: ndcg_at_10
      value: 24.445
    - type: ndcg_at_100
      value: 28.624
    - type: ndcg_at_1000
      value: 31.627
    - type: ndcg_at_3
      value: 21.611
    - type: ndcg_at_5
      value: 22.781000000000002
    - type: precision_at_1
      value: 19.936
    - type: precision_at_10
      value: 4.503
    - type: precision_at_100
      value: 0.8290000000000001
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 10.318
    - type: precision_at_5
      value: 7.248
    - type: recall_at_1
      value: 15.783
    - type: recall_at_10
      value: 30.999
    - type: recall_at_100
      value: 49.441
    - type: recall_at_1000
      value: 70.169
    - type: recall_at_3
      value: 22.676
    - type: recall_at_5
      value: 26.003999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 23.971
    - type: map_at_10
      value: 31.85
    - type: map_at_100
      value: 32.92
    - type: map_at_1000
      value: 33.016
    - type: map_at_3
      value: 29.578
    - type: map_at_5
      value: 30.740000000000002
    - type: mrr_at_1
      value: 27.773999999999997
    - type: mrr_at_10
      value: 34.955000000000005
    - type: mrr_at_100
      value: 35.846000000000004
    - type: mrr_at_1000
      value: 35.91
    - type: mrr_at_3
      value: 32.873999999999995
    - type: mrr_at_5
      value: 33.902
    - type: ndcg_at_1
      value: 27.773999999999997
    - type: ndcg_at_10
      value: 36.334
    - type: ndcg_at_100
      value: 41.522999999999996
    - type: ndcg_at_1000
      value: 43.838
    - type: ndcg_at_3
      value: 32.062000000000005
    - type: ndcg_at_5
      value: 33.83
    - type: precision_at_1
      value: 27.773999999999997
    - type: precision_at_10
      value: 5.956
    - type: precision_at_100
      value: 0.9369999999999999
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 14.232
    - type: precision_at_5
      value: 9.754999999999999
    - type: recall_at_1
      value: 23.971
    - type: recall_at_10
      value: 46.878
    - type: recall_at_100
      value: 70.474
    - type: recall_at_1000
      value: 87.362
    - type: recall_at_3
      value: 35.265
    - type: recall_at_5
      value: 39.660000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.639999999999999
    - type: map_at_10
      value: 14.456
    - type: map_at_100
      value: 15.161
    - type: map_at_1000
      value: 15.271
    - type: map_at_3
      value: 13.227
    - type: map_at_5
      value: 13.911999999999999
    - type: mrr_at_1
      value: 11.751000000000001
    - type: mrr_at_10
      value: 15.695
    - type: mrr_at_100
      value: 16.395
    - type: mrr_at_1000
      value: 16.497
    - type: mrr_at_3
      value: 14.482000000000001
    - type: mrr_at_5
      value: 15.121
    - type: ndcg_at_1
      value: 11.751000000000001
    - type: ndcg_at_10
      value: 16.898
    - type: ndcg_at_100
      value: 20.824
    - type: ndcg_at_1000
      value: 24.127000000000002
    - type: ndcg_at_3
      value: 14.413
    - type: ndcg_at_5
      value: 15.595999999999998
    - type: precision_at_1
      value: 11.751000000000001
    - type: precision_at_10
      value: 2.644
    - type: precision_at_100
      value: 0.492
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 6.215
    - type: precision_at_5
      value: 4.3839999999999995
    - type: recall_at_1
      value: 10.639999999999999
    - type: recall_at_10
      value: 23.346
    - type: recall_at_100
      value: 42.341
    - type: recall_at_1000
      value: 68.136
    - type: recall_at_3
      value: 16.544
    - type: recall_at_5
      value: 19.416
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.461
    - type: map_at_10
      value: 8.798
    - type: map_at_100
      value: 9.379
    - type: map_at_1000
      value: 9.494
    - type: map_at_3
      value: 7.541
    - type: map_at_5
      value: 8.241999999999999
    - type: mrr_at_1
      value: 7.2139999999999995
    - type: mrr_at_10
      value: 10.821
    - type: mrr_at_100
      value: 11.472999999999999
    - type: mrr_at_1000
      value: 11.573
    - type: mrr_at_3
      value: 9.411
    - type: mrr_at_5
      value: 10.176
    - type: ndcg_at_1
      value: 7.2139999999999995
    - type: ndcg_at_10
      value: 11.175
    - type: ndcg_at_100
      value: 14.634
    - type: ndcg_at_1000
      value: 18.203
    - type: ndcg_at_3
      value: 8.729000000000001
    - type: ndcg_at_5
      value: 9.876999999999999
    - type: precision_at_1
      value: 7.2139999999999995
    - type: precision_at_10
      value: 2.189
    - type: precision_at_100
      value: 0.46299999999999997
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 4.229
    - type: precision_at_5
      value: 3.2840000000000003
    - type: recall_at_1
      value: 5.461
    - type: recall_at_10
      value: 16.6
    - type: recall_at_100
      value: 32.747
    - type: recall_at_1000
      value: 59.382999999999996
    - type: recall_at_3
      value: 9.856
    - type: recall_at_5
      value: 12.763
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 16.426
    - type: map_at_10
      value: 21.875
    - type: map_at_100
      value: 22.918
    - type: map_at_1000
      value: 23.058999999999997
    - type: map_at_3
      value: 19.924
    - type: map_at_5
      value: 20.964
    - type: mrr_at_1
      value: 20.5
    - type: mrr_at_10
      value: 26.284000000000002
    - type: mrr_at_100
      value: 27.159
    - type: mrr_at_1000
      value: 27.249000000000002
    - type: mrr_at_3
      value: 24.334
    - type: mrr_at_5
      value: 25.427
    - type: ndcg_at_1
      value: 20.5
    - type: ndcg_at_10
      value: 25.85
    - type: ndcg_at_100
      value: 30.994
    - type: ndcg_at_1000
      value: 34.309
    - type: ndcg_at_3
      value: 22.355
    - type: ndcg_at_5
      value: 23.904
    - type: precision_at_1
      value: 20.5
    - type: precision_at_10
      value: 4.726
    - type: precision_at_100
      value: 0.885
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 10.491
    - type: precision_at_5
      value: 7.603
    - type: recall_at_1
      value: 16.426
    - type: recall_at_10
      value: 33.777
    - type: recall_at_100
      value: 56.346
    - type: recall_at_1000
      value: 79.522
    - type: recall_at_3
      value: 23.695
    - type: recall_at_5
      value: 27.647
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.634
    - type: map_at_10
      value: 15.799
    - type: map_at_100
      value: 16.698
    - type: map_at_1000
      value: 16.838
    - type: map_at_3
      value: 14.106
    - type: map_at_5
      value: 14.915000000000001
    - type: mrr_at_1
      value: 13.469999999999999
    - type: mrr_at_10
      value: 18.925
    - type: mrr_at_100
      value: 19.789
    - type: mrr_at_1000
      value: 19.884
    - type: mrr_at_3
      value: 17.199
    - type: mrr_at_5
      value: 18.056
    - type: ndcg_at_1
      value: 13.469999999999999
    - type: ndcg_at_10
      value: 19.292
    - type: ndcg_at_100
      value: 23.813000000000002
    - type: ndcg_at_1000
      value: 27.423
    - type: ndcg_at_3
      value: 16.141
    - type: ndcg_at_5
      value: 17.330000000000002
    - type: precision_at_1
      value: 13.469999999999999
    - type: precision_at_10
      value: 3.7560000000000002
    - type: precision_at_100
      value: 0.716
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 7.915
    - type: precision_at_5
      value: 5.731
    - type: recall_at_1
      value: 10.634
    - type: recall_at_10
      value: 26.808
    - type: recall_at_100
      value: 46.653
    - type: recall_at_1000
      value: 72.539
    - type: recall_at_3
      value: 17.993000000000002
    - type: recall_at_5
      value: 21.159
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.800083333333333
    - type: map_at_10
      value: 17.65583333333333
    - type: map_at_100
      value: 18.47741666666667
    - type: map_at_1000
      value: 18.600916666666667
    - type: map_at_3
      value: 16.103666666666665
    - type: map_at_5
      value: 16.951
    - type: mrr_at_1
      value: 15.638666666666664
    - type: mrr_at_10
      value: 20.579250000000005
    - type: mrr_at_100
      value: 21.334916666666672
    - type: mrr_at_1000
      value: 21.425666666666668
    - type: mrr_at_3
      value: 18.994333333333334
    - type: mrr_at_5
      value: 19.87133333333333
    - type: ndcg_at_1
      value: 15.638666666666664
    - type: ndcg_at_10
      value: 20.875833333333325
    - type: ndcg_at_100
      value: 25.0565
    - type: ndcg_at_1000
      value: 28.304666666666666
    - type: ndcg_at_3
      value: 18.02975
    - type: ndcg_at_5
      value: 19.315499999999997
    - type: precision_at_1
      value: 15.638666666666664
    - type: precision_at_10
      value: 3.753416666666667
    - type: precision_at_100
      value: 0.6961666666666666
    - type: precision_at_1000
      value: 0.11475
    - type: precision_at_3
      value: 8.384416666666665
    - type: precision_at_5
      value: 6.048583333333333
    - type: recall_at_1
      value: 12.800083333333333
    - type: recall_at_10
      value: 27.719583333333333
    - type: recall_at_100
      value: 46.8605
    - type: recall_at_1000
      value: 70.65391666666666
    - type: recall_at_3
      value: 19.736000000000004
    - type: recall_at_5
      value: 23.03333333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.246
    - type: map_at_10
      value: 12.98
    - type: map_at_100
      value: 13.569999999999999
    - type: map_at_1000
      value: 13.663
    - type: map_at_3
      value: 11.747
    - type: map_at_5
      value: 12.457
    - type: mrr_at_1
      value: 11.35
    - type: mrr_at_10
      value: 15.07
    - type: mrr_at_100
      value: 15.661
    - type: mrr_at_1000
      value: 15.745999999999999
    - type: mrr_at_3
      value: 13.753000000000002
    - type: mrr_at_5
      value: 14.527000000000001
    - type: ndcg_at_1
      value: 11.35
    - type: ndcg_at_10
      value: 15.475
    - type: ndcg_at_100
      value: 18.58
    - type: ndcg_at_1000
      value: 21.174
    - type: ndcg_at_3
      value: 13.175999999999998
    - type: ndcg_at_5
      value: 14.324
    - type: precision_at_1
      value: 11.35
    - type: precision_at_10
      value: 2.669
    - type: precision_at_100
      value: 0.468
    - type: precision_at_1000
      value: 0.074
    - type: precision_at_3
      value: 5.982
    - type: precision_at_5
      value: 4.4479999999999995
    - type: recall_at_1
      value: 9.246
    - type: recall_at_10
      value: 21.17
    - type: recall_at_100
      value: 35.565999999999995
    - type: recall_at_1000
      value: 55.323
    - type: recall_at_3
      value: 14.889
    - type: recall_at_5
      value: 17.685000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.927999999999999
    - type: map_at_10
      value: 10.035
    - type: map_at_100
      value: 10.615
    - type: map_at_1000
      value: 10.727
    - type: map_at_3
      value: 9.058
    - type: map_at_5
      value: 9.600999999999999
    - type: mrr_at_1
      value: 8.534
    - type: mrr_at_10
      value: 12.063
    - type: mrr_at_100
      value: 12.666
    - type: mrr_at_1000
      value: 12.763
    - type: mrr_at_3
      value: 10.926
    - type: mrr_at_5
      value: 11.557
    - type: ndcg_at_1
      value: 8.534
    - type: ndcg_at_10
      value: 12.22
    - type: ndcg_at_100
      value: 15.472
    - type: ndcg_at_1000
      value: 18.898
    - type: ndcg_at_3
      value: 10.290000000000001
    - type: ndcg_at_5
      value: 11.193999999999999
    - type: precision_at_1
      value: 8.534
    - type: precision_at_10
      value: 2.2849999999999997
    - type: precision_at_100
      value: 0.47200000000000003
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.944
    - type: precision_at_5
      value: 3.627
    - type: recall_at_1
      value: 6.927999999999999
    - type: recall_at_10
      value: 16.872
    - type: recall_at_100
      value: 31.983
    - type: recall_at_1000
      value: 57.742000000000004
    - type: recall_at_3
      value: 11.552999999999999
    - type: recall_at_5
      value: 13.791999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.292
    - type: map_at_10
      value: 15.271
    - type: map_at_100
      value: 16.014999999999997
    - type: map_at_1000
      value: 16.133
    - type: map_at_3
      value: 13.897
    - type: map_at_5
      value: 14.616000000000001
    - type: mrr_at_1
      value: 13.713000000000001
    - type: mrr_at_10
      value: 17.943
    - type: mrr_at_100
      value: 18.740000000000002
    - type: mrr_at_1000
      value: 18.841
    - type: mrr_at_3
      value: 16.48
    - type: mrr_at_5
      value: 17.273
    - type: ndcg_at_1
      value: 13.713000000000001
    - type: ndcg_at_10
      value: 18.163999999999998
    - type: ndcg_at_100
      value: 22.157
    - type: ndcg_at_1000
      value: 25.588
    - type: ndcg_at_3
      value: 15.459
    - type: ndcg_at_5
      value: 16.634
    - type: precision_at_1
      value: 13.713000000000001
    - type: precision_at_10
      value: 3.125
    - type: precision_at_100
      value: 0.5640000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 7.090000000000001
    - type: precision_at_5
      value: 5.037
    - type: recall_at_1
      value: 11.292
    - type: recall_at_10
      value: 24.583
    - type: recall_at_100
      value: 42.943
    - type: recall_at_1000
      value: 68.504
    - type: recall_at_3
      value: 16.976
    - type: recall_at_5
      value: 20.021
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.672999999999998
    - type: map_at_10
      value: 19.087
    - type: map_at_100
      value: 20.027
    - type: map_at_1000
      value: 20.199
    - type: map_at_3
      value: 17.491
    - type: map_at_5
      value: 18.44
    - type: mrr_at_1
      value: 17.194000000000003
    - type: mrr_at_10
      value: 22.621
    - type: mrr_at_100
      value: 23.408
    - type: mrr_at_1000
      value: 23.5
    - type: mrr_at_3
      value: 20.982
    - type: mrr_at_5
      value: 22.148
    - type: ndcg_at_1
      value: 17.194000000000003
    - type: ndcg_at_10
      value: 22.694
    - type: ndcg_at_100
      value: 27.099
    - type: ndcg_at_1000
      value: 30.830999999999996
    - type: ndcg_at_3
      value: 20.009
    - type: ndcg_at_5
      value: 21.461
    - type: precision_at_1
      value: 17.194000000000003
    - type: precision_at_10
      value: 4.447
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 9.486
    - type: precision_at_5
      value: 7.115
    - type: recall_at_1
      value: 13.672999999999998
    - type: recall_at_10
      value: 29.137
    - type: recall_at_100
      value: 49.652
    - type: recall_at_1000
      value: 75.766
    - type: recall_at_3
      value: 21.647
    - type: recall_at_5
      value: 25.291000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.532
    - type: map_at_10
      value: 13.453999999999999
    - type: map_at_100
      value: 14.183000000000002
    - type: map_at_1000
      value: 14.293
    - type: map_at_3
      value: 12.386999999999999
    - type: map_at_5
      value: 13.020000000000001
    - type: mrr_at_1
      value: 10.906
    - type: mrr_at_10
      value: 14.957999999999998
    - type: mrr_at_100
      value: 15.654000000000002
    - type: mrr_at_1000
      value: 15.76
    - type: mrr_at_3
      value: 13.709
    - type: mrr_at_5
      value: 14.438999999999998
    - type: ndcg_at_1
      value: 10.906
    - type: ndcg_at_10
      value: 15.815999999999999
    - type: ndcg_at_100
      value: 19.858999999999998
    - type: ndcg_at_1000
      value: 23.284
    - type: ndcg_at_3
      value: 13.547
    - type: ndcg_at_5
      value: 14.701
    - type: precision_at_1
      value: 10.906
    - type: precision_at_10
      value: 2.532
    - type: precision_at_100
      value: 0.494
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 5.976999999999999
    - type: precision_at_5
      value: 4.251
    - type: recall_at_1
      value: 9.532
    - type: recall_at_10
      value: 21.738
    - type: recall_at_100
      value: 41.349000000000004
    - type: recall_at_1000
      value: 68.11399999999999
    - type: recall_at_3
      value: 15.508
    - type: recall_at_5
      value: 18.373
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.144
    - type: map_at_10
      value: 8.993
    - type: map_at_100
      value: 10.158000000000001
    - type: map_at_1000
      value: 10.35
    - type: map_at_3
      value: 7.133000000000001
    - type: map_at_5
      value: 8.065
    - type: mrr_at_1
      value: 11.27
    - type: mrr_at_10
      value: 18.188
    - type: mrr_at_100
      value: 19.303
    - type: mrr_at_1000
      value: 19.389
    - type: mrr_at_3
      value: 15.342
    - type: mrr_at_5
      value: 16.869999999999997
    - type: ndcg_at_1
      value: 11.27
    - type: ndcg_at_10
      value: 13.73
    - type: ndcg_at_100
      value: 19.566
    - type: ndcg_at_1000
      value: 23.738
    - type: ndcg_at_3
      value: 10.029
    - type: ndcg_at_5
      value: 11.4
    - type: precision_at_1
      value: 11.27
    - type: precision_at_10
      value: 4.704
    - type: precision_at_100
      value: 1.1039999999999999
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 7.535
    - type: precision_at_5
      value: 6.345000000000001
    - type: recall_at_1
      value: 5.144
    - type: recall_at_10
      value: 17.933
    - type: recall_at_100
      value: 38.919
    - type: recall_at_1000
      value: 63.21
    - type: recall_at_3
      value: 9.372
    - type: recall_at_5
      value: 12.673000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.473
    - type: map_at_10
      value: 6.051
    - type: map_at_100
      value: 8.325000000000001
    - type: map_at_1000
      value: 8.962
    - type: map_at_3
      value: 4.204
    - type: map_at_5
      value: 4.949
    - type: mrr_at_1
      value: 28.499999999999996
    - type: mrr_at_10
      value: 38.123000000000005
    - type: mrr_at_100
      value: 39.052
    - type: mrr_at_1000
      value: 39.103
    - type: mrr_at_3
      value: 35.333
    - type: mrr_at_5
      value: 37.108000000000004
    - type: ndcg_at_1
      value: 20.625
    - type: ndcg_at_10
      value: 16.834
    - type: ndcg_at_100
      value: 18.847
    - type: ndcg_at_1000
      value: 24.842
    - type: ndcg_at_3
      value: 18.395
    - type: ndcg_at_5
      value: 17.454
    - type: precision_at_1
      value: 28.499999999999996
    - type: precision_at_10
      value: 15.4
    - type: precision_at_100
      value: 4.75
    - type: precision_at_1000
      value: 1.028
    - type: precision_at_3
      value: 21.833
    - type: precision_at_5
      value: 19.3
    - type: recall_at_1
      value: 2.473
    - type: recall_at_10
      value: 9.828000000000001
    - type: recall_at_100
      value: 23.686
    - type: recall_at_1000
      value: 44.414
    - type: recall_at_3
      value: 5.0569999999999995
    - type: recall_at_5
      value: 6.662
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.42
    - type: f1
      value: 39.33089229309943
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 10.352
    - type: map_at_10
      value: 15.461
    - type: map_at_100
      value: 16.3
    - type: map_at_1000
      value: 16.381999999999998
    - type: map_at_3
      value: 13.736999999999998
    - type: map_at_5
      value: 14.665000000000001
    - type: mrr_at_1
      value: 11.011
    - type: mrr_at_10
      value: 16.45
    - type: mrr_at_100
      value: 17.311
    - type: mrr_at_1000
      value: 17.388
    - type: mrr_at_3
      value: 14.613999999999999
    - type: mrr_at_5
      value: 15.603
    - type: ndcg_at_1
      value: 11.011
    - type: ndcg_at_10
      value: 18.724
    - type: ndcg_at_100
      value: 23.180999999999997
    - type: ndcg_at_1000
      value: 25.630999999999997
    - type: ndcg_at_3
      value: 15.091
    - type: ndcg_at_5
      value: 16.787
    - type: precision_at_1
      value: 11.011
    - type: precision_at_10
      value: 3.0540000000000003
    - type: precision_at_100
      value: 0.545
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 6.511
    - type: precision_at_5
      value: 4.8
    - type: recall_at_1
      value: 10.352
    - type: recall_at_10
      value: 28.076
    - type: recall_at_100
      value: 49.275000000000006
    - type: recall_at_1000
      value: 68.601
    - type: recall_at_3
      value: 18.128
    - type: recall_at_5
      value: 22.231
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.813
    - type: map_at_10
      value: 9.283
    - type: map_at_100
      value: 10.215
    - type: map_at_1000
      value: 10.397
    - type: map_at_3
      value: 7.832999999999999
    - type: map_at_5
      value: 8.626000000000001
    - type: mrr_at_1
      value: 11.728
    - type: mrr_at_10
      value: 16.657
    - type: mrr_at_100
      value: 17.560000000000002
    - type: mrr_at_1000
      value: 17.671
    - type: mrr_at_3
      value: 14.738000000000001
    - type: mrr_at_5
      value: 15.764
    - type: ndcg_at_1
      value: 11.728
    - type: ndcg_at_10
      value: 12.912
    - type: ndcg_at_100
      value: 17.749000000000002
    - type: ndcg_at_1000
      value: 22.393
    - type: ndcg_at_3
      value: 10.729
    - type: ndcg_at_5
      value: 11.600000000000001
    - type: precision_at_1
      value: 11.728
    - type: precision_at_10
      value: 3.7350000000000003
    - type: precision_at_100
      value: 0.864
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 7.202
    - type: precision_at_5
      value: 5.679
    - type: recall_at_1
      value: 5.813
    - type: recall_at_10
      value: 16.436
    - type: recall_at_100
      value: 35.632000000000005
    - type: recall_at_1000
      value: 65.389
    - type: recall_at_3
      value: 9.771
    - type: recall_at_5
      value: 12.5
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 12.120000000000001
    - type: map_at_10
      value: 17.019000000000002
    - type: map_at_100
      value: 17.765
    - type: map_at_1000
      value: 17.87
    - type: map_at_3
      value: 15.603
    - type: map_at_5
      value: 16.344
    - type: mrr_at_1
      value: 24.240000000000002
    - type: mrr_at_10
      value: 30.262
    - type: mrr_at_100
      value: 30.993
    - type: mrr_at_1000
      value: 31.067
    - type: mrr_at_3
      value: 28.591
    - type: mrr_at_5
      value: 29.507
    - type: ndcg_at_1
      value: 24.240000000000002
    - type: ndcg_at_10
      value: 22.355
    - type: ndcg_at_100
      value: 26.128
    - type: ndcg_at_1000
      value: 28.953
    - type: ndcg_at_3
      value: 19.458000000000002
    - type: ndcg_at_5
      value: 20.784
    - type: precision_at_1
      value: 24.240000000000002
    - type: precision_at_10
      value: 5.025
    - type: precision_at_100
      value: 0.808
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 12.348
    - type: precision_at_5
      value: 8.459
    - type: recall_at_1
      value: 12.120000000000001
    - type: recall_at_10
      value: 25.124999999999996
    - type: recall_at_100
      value: 40.405
    - type: recall_at_1000
      value: 59.413000000000004
    - type: recall_at_3
      value: 18.521
    - type: recall_at_5
      value: 21.148
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 65.2588
    - type: ap
      value: 60.23157934233188
    - type: f1
      value: 65.12947184169569
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.322
    - type: map_at_10
      value: 8.837
    - type: map_at_100
      value: 9.538
    - type: map_at_1000
      value: 9.635
    - type: map_at_3
      value: 7.457999999999999
    - type: map_at_5
      value: 8.161
    - type: mrr_at_1
      value: 5.501
    - type: mrr_at_10
      value: 9.094
    - type: mrr_at_100
      value: 9.802
    - type: mrr_at_1000
      value: 9.897
    - type: mrr_at_3
      value: 7.689
    - type: mrr_at_5
      value: 8.404
    - type: ndcg_at_1
      value: 5.473
    - type: ndcg_at_10
      value: 11.153
    - type: ndcg_at_100
      value: 15.167
    - type: ndcg_at_1000
      value: 18.188
    - type: ndcg_at_3
      value: 8.238
    - type: ndcg_at_5
      value: 9.507
    - type: precision_at_1
      value: 5.473
    - type: precision_at_10
      value: 1.9140000000000001
    - type: precision_at_100
      value: 0.40299999999999997
    - type: precision_at_1000
      value: 0.066
    - type: precision_at_3
      value: 3.558
    - type: precision_at_5
      value: 2.777
    - type: recall_at_1
      value: 5.322
    - type: recall_at_10
      value: 18.387999999999998
    - type: recall_at_100
      value: 38.307
    - type: recall_at_1000
      value: 62.709
    - type: recall_at_3
      value: 10.294
    - type: recall_at_5
      value: 13.34
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.34473324213405
    - type: f1
      value: 87.67380611922604
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.079799361605104
    - type: f1
      value: 40.94145320708008
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.5084061869536
    - type: f1
      value: 60.45328085918922
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.30733019502352
    - type: f1
      value: 67.93760790702412
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.52146393422655
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.72290764990727
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.70371324884553
    - type: mrr
      value: 29.579215048956236
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.844
    - type: map_at_10
      value: 5.992999999999999
    - type: map_at_100
      value: 7.622
    - type: map_at_1000
      value: 8.837
    - type: map_at_3
      value: 4.533
    - type: map_at_5
      value: 5.251
    - type: mrr_at_1
      value: 27.554000000000002
    - type: mrr_at_10
      value: 37.674
    - type: mrr_at_100
      value: 38.334
    - type: mrr_at_1000
      value: 38.412
    - type: mrr_at_3
      value: 35.036
    - type: mrr_at_5
      value: 36.305
    - type: ndcg_at_1
      value: 26.006
    - type: ndcg_at_10
      value: 20.526
    - type: ndcg_at_100
      value: 19.554
    - type: ndcg_at_1000
      value: 29.331000000000003
    - type: ndcg_at_3
      value: 23.471
    - type: ndcg_at_5
      value: 22.229
    - type: precision_at_1
      value: 27.554000000000002
    - type: precision_at_10
      value: 15.139
    - type: precision_at_100
      value: 5.628
    - type: precision_at_1000
      value: 1.894
    - type: precision_at_3
      value: 22.291
    - type: precision_at_5
      value: 19.195
    - type: recall_at_1
      value: 2.844
    - type: recall_at_10
      value: 10.363
    - type: recall_at_100
      value: 22.177
    - type: recall_at_1000
      value: 56.688
    - type: recall_at_3
      value: 5.955
    - type: recall_at_5
      value: 7.684
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.727
    - type: map_at_10
      value: 13.036
    - type: map_at_100
      value: 14.033000000000001
    - type: map_at_1000
      value: 14.141
    - type: map_at_3
      value: 11.01
    - type: map_at_5
      value: 12.049999999999999
    - type: mrr_at_1
      value: 8.834999999999999
    - type: mrr_at_10
      value: 14.482999999999999
    - type: mrr_at_100
      value: 15.442
    - type: mrr_at_1000
      value: 15.536
    - type: mrr_at_3
      value: 12.365
    - type: mrr_at_5
      value: 13.459999999999999
    - type: ndcg_at_1
      value: 8.834999999999999
    - type: ndcg_at_10
      value: 16.633
    - type: ndcg_at_100
      value: 21.907
    - type: ndcg_at_1000
      value: 24.868000000000002
    - type: ndcg_at_3
      value: 12.384
    - type: ndcg_at_5
      value: 14.258000000000001
    - type: precision_at_1
      value: 8.834999999999999
    - type: precision_at_10
      value: 3.094
    - type: precision_at_100
      value: 0.612
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 5.774
    - type: precision_at_5
      value: 4.496
    - type: recall_at_1
      value: 7.727
    - type: recall_at_10
      value: 26.497
    - type: recall_at_100
      value: 51.376
    - type: recall_at_1000
      value: 74.10900000000001
    - type: recall_at_3
      value: 15.059000000000001
    - type: recall_at_5
      value: 19.457
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 59.06400000000001
    - type: map_at_10
      value: 70.985
    - type: map_at_100
      value: 71.811
    - type: map_at_1000
      value: 71.854
    - type: map_at_3
      value: 68.113
    - type: map_at_5
      value: 69.782
    - type: mrr_at_1
      value: 68.02
    - type: mrr_at_10
      value: 75.626
    - type: mrr_at_100
      value: 75.955
    - type: mrr_at_1000
      value: 75.965
    - type: mrr_at_3
      value: 74.008
    - type: mrr_at_5
      value: 75.006
    - type: ndcg_at_1
      value: 68.14
    - type: ndcg_at_10
      value: 75.901
    - type: ndcg_at_100
      value: 78.469
    - type: ndcg_at_1000
      value: 79.066
    - type: ndcg_at_3
      value: 72.107
    - type: ndcg_at_5
      value: 73.944
    - type: precision_at_1
      value: 68.14
    - type: precision_at_10
      value: 11.498
    - type: precision_at_100
      value: 1.409
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 31.136999999999997
    - type: precision_at_5
      value: 20.608
    - type: recall_at_1
      value: 59.06400000000001
    - type: recall_at_10
      value: 85.37
    - type: recall_at_100
      value: 95.49499999999999
    - type: recall_at_1000
      value: 99.10600000000001
    - type: recall_at_3
      value: 74.504
    - type: recall_at_5
      value: 79.617
    - type: map_at_1
      value: 2.393
    - type: map_at_10
      value: 5.681
    - type: map_at_100
      value: 6.8580000000000005
    - type: map_at_1000
      value: 7.087000000000001
    - type: map_at_3
      value: 4.226
    - type: map_at_5
      value: 4.982
    - type: mrr_at_1
      value: 11.700000000000001
    - type: mrr_at_10
      value: 18.883
    - type: mrr_at_100
      value: 20.133000000000003
    - type: mrr_at_1000
      value: 20.235
    - type: mrr_at_3
      value: 16.483
    - type: mrr_at_5
      value: 17.868000000000002
    - type: ndcg_at_1
      value: 11.700000000000001
    - type: ndcg_at_10
      value: 10.334999999999999
    - type: ndcg_at_100
      value: 16.182
    - type: ndcg_at_1000
      value: 21.252
    - type: ndcg_at_3
      value: 9.837
    - type: ndcg_at_5
      value: 8.665000000000001
    - type: precision_at_1
      value: 11.700000000000001
    - type: precision_at_10
      value: 5.37
    - type: precision_at_100
      value: 1.396
    - type: precision_at_1000
      value: 0.263
    - type: precision_at_3
      value: 9.333
    - type: precision_at_5
      value: 7.720000000000001
    - type: recall_at_1
      value: 2.393
    - type: recall_at_10
      value: 10.902000000000001
    - type: recall_at_100
      value: 28.377000000000002
    - type: recall_at_1000
      value: 53.378
    - type: recall_at_3
      value: 5.6930000000000005
    - type: recall_at_5
      value: 7.828
    - type: map_at_1
      value: 0.092
    - type: map_at_10
      value: 0.585
    - type: map_at_100
      value: 3.256
    - type: map_at_1000
      value: 8.3
    - type: map_at_3
      value: 0.232
    - type: map_at_5
      value: 0.33
    - type: mrr_at_1
      value: 44.0
    - type: mrr_at_10
      value: 54.848
    - type: mrr_at_100
      value: 55.55
    - type: mrr_at_1000
      value: 55.586999999999996
    - type: mrr_at_3
      value: 51.666999999999994
    - type: mrr_at_5
      value: 52.567
    - type: ndcg_at_1
      value: 36.0
    - type: ndcg_at_10
      value: 35.045
    - type: ndcg_at_100
      value: 27.206000000000003
    - type: ndcg_at_1000
      value: 25.343
    - type: ndcg_at_3
      value: 37.123
    - type: ndcg_at_5
      value: 34.885
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 39.2
    - type: precision_at_100
      value: 28.720000000000002
    - type: precision_at_1000
      value: 12.617999999999999
    - type: precision_at_3
      value: 42.667
    - type: precision_at_5
      value: 38.0
    - type: recall_at_1
      value: 0.092
    - type: recall_at_10
      value: 0.8460000000000001
    - type: recall_at_100
      value: 5.985
    - type: recall_at_1000
      value: 24.909
    - type: recall_at_3
      value: 0.263
    - type: recall_at_5
      value: 0.395
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 36.43153810326964
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 43.541298978174936
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.5584234869778
    - type: cos_sim_spearman
      value: 67.9364372842477
    - type: euclidean_pearson
      value: 73.27076465715946
    - type: euclidean_spearman
      value: 67.93647749958936
    - type: manhattan_pearson
      value: 72.13910193683036
    - type: manhattan_spearman
      value: 66.61518749698374
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 72.86660961012544
    - type: cos_sim_spearman
      value: 65.57182934430755
    - type: euclidean_pearson
      value: 69.29233759067908
    - type: euclidean_spearman
      value: 65.57304558951748
    - type: manhattan_pearson
      value: 70.31781501220479
    - type: manhattan_spearman
      value: 66.85340801659174
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.69577150435398
    - type: cos_sim_spearman
      value: 79.03112671704807
    - type: euclidean_pearson
      value: 78.60981017083087
    - type: euclidean_spearman
      value: 79.0311645213213
    - type: manhattan_pearson
      value: 79.22756096679643
    - type: manhattan_spearman
      value: 79.7311227799491
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.93990405247241
    - type: cos_sim_spearman
      value: 73.79147577901793
    - type: euclidean_pearson
      value: 76.14246068970958
    - type: euclidean_spearman
      value: 73.79146608888966
    - type: manhattan_pearson
      value: 76.36222818331179
    - type: manhattan_spearman
      value: 74.28614733053001
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.34424026928464
    - type: cos_sim_spearman
      value: 80.5594037713743
    - type: euclidean_pearson
      value: 80.63525752212392
    - type: euclidean_spearman
      value: 80.55939249403838
    - type: manhattan_pearson
      value: 81.34602933631498
    - type: manhattan_spearman
      value: 81.38418448767962
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.61995336850698
    - type: cos_sim_spearman
      value: 76.0347837515053
    - type: euclidean_pearson
      value: 75.86835266904347
    - type: euclidean_spearman
      value: 76.03505537942084
    - type: manhattan_pearson
      value: 76.51813387781434
    - type: manhattan_spearman
      value: 76.74020230470897
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.19299429529762
    - type: cos_sim_spearman
      value: 83.50456422406354
    - type: euclidean_pearson
      value: 83.73656764055873
    - type: euclidean_spearman
      value: 83.50543867653234
    - type: manhattan_pearson
      value: 84.06556681959736
    - type: manhattan_spearman
      value: 83.83490502371635
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.47312170802807
    - type: cos_sim_spearman
      value: 60.18545716262269
    - type: euclidean_pearson
      value: 62.71728709453116
    - type: euclidean_spearman
      value: 60.18545716262269
    - type: manhattan_pearson
      value: 63.624462431857054
    - type: manhattan_spearman
      value: 61.26879246163699
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.51955498871753
    - type: cos_sim_spearman
      value: 75.31849064221164
    - type: euclidean_pearson
      value: 76.81716282761909
    - type: euclidean_spearman
      value: 75.31850911084204
    - type: manhattan_pearson
      value: 77.37977858758349
    - type: manhattan_spearman
      value: 75.83034176427023
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.66775280209716
    - type: mrr
      value: 89.82565818350132
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 29.471999999999998
    - type: map_at_10
      value: 37.045
    - type: map_at_100
      value: 38.098
    - type: map_at_1000
      value: 38.182
    - type: map_at_3
      value: 35.111
    - type: map_at_5
      value: 36.219
    - type: mrr_at_1
      value: 31.0
    - type: mrr_at_10
      value: 38.579
    - type: mrr_at_100
      value: 39.443
    - type: mrr_at_1000
      value: 39.515
    - type: mrr_at_3
      value: 36.944
    - type: mrr_at_5
      value: 37.794
    - type: ndcg_at_1
      value: 31.0
    - type: ndcg_at_10
      value: 41.112
    - type: ndcg_at_100
      value: 46.665
    - type: ndcg_at_1000
      value: 48.852000000000004
    - type: ndcg_at_3
      value: 37.385000000000005
    - type: ndcg_at_5
      value: 39.094
    - type: precision_at_1
      value: 31.0
    - type: precision_at_10
      value: 5.7669999999999995
    - type: precision_at_100
      value: 0.893
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 15.110999999999999
    - type: precision_at_5
      value: 10.133000000000001
    - type: recall_at_1
      value: 29.471999999999998
    - type: recall_at_10
      value: 52.178000000000004
    - type: recall_at_100
      value: 79.072
    - type: recall_at_1000
      value: 96.133
    - type: recall_at_3
      value: 41.833
    - type: recall_at_5
      value: 45.928000000000004
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.60792079207921
    - type: cos_sim_ap
      value: 86.1403533011479
    - type: cos_sim_f1
      value: 79.5031055900621
    - type: cos_sim_precision
      value: 82.40343347639485
    - type: cos_sim_recall
      value: 76.8
    - type: dot_accuracy
      value: 99.60792079207921
    - type: dot_ap
      value: 86.1403533011479
    - type: dot_f1
      value: 79.5031055900621
    - type: dot_precision
      value: 82.40343347639485
    - type: dot_recall
      value: 76.8
    - type: euclidean_accuracy
      value: 99.60792079207921
    - type: euclidean_ap
      value: 86.1403533011479
    - type: euclidean_f1
      value: 79.5031055900621
    - type: euclidean_precision
      value: 82.40343347639485
    - type: euclidean_recall
      value: 76.8
    - type: manhattan_accuracy
      value: 99.66930693069307
    - type: manhattan_ap
      value: 89.31222064600665
    - type: manhattan_f1
      value: 82.57930317212688
    - type: manhattan_precision
      value: 86.02383531960996
    - type: manhattan_recall
      value: 79.4
    - type: max_accuracy
      value: 99.66930693069307
    - type: max_ap
      value: 89.31222064600665
    - type: max_f1
      value: 82.57930317212688
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 39.947170328852884
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.337074507154036
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.1628779493265
    - type: mrr
      value: 43.62989135047959
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.58115865136649
    - type: cos_sim_spearman
      value: 29.922054056097767
    - type: dot_pearson
      value: 30.58115861521069
    - type: dot_spearman
      value: 29.81538965399958
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.944
    - type: map_at_10
      value: 7.631
    - type: map_at_100
      value: 12.347
    - type: map_at_1000
      value: 13.877999999999998
    - type: map_at_3
      value: 4.766
    - type: map_at_5
      value: 6.232
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 39.657
    - type: mrr_at_100
      value: 40.69
    - type: mrr_at_1000
      value: 40.692
    - type: mrr_at_3
      value: 35.374
    - type: mrr_at_5
      value: 37.517
    - type: ndcg_at_1
      value: 25.509999999999998
    - type: ndcg_at_10
      value: 19.248
    - type: ndcg_at_100
      value: 31.335
    - type: ndcg_at_1000
      value: 42.858000000000004
    - type: ndcg_at_3
      value: 23.812
    - type: ndcg_at_5
      value: 22.506
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 16.735
    - type: precision_at_100
      value: 6.938999999999999
    - type: precision_at_1000
      value: 1.427
    - type: precision_at_3
      value: 25.169999999999998
    - type: precision_at_5
      value: 22.857
    - type: recall_at_1
      value: 1.944
    - type: recall_at_10
      value: 11.404
    - type: recall_at_100
      value: 41.831
    - type: recall_at_1000
      value: 77.27199999999999
    - type: recall_at_3
      value: 5.5440000000000005
    - type: recall_at_5
      value: 7.969999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.45700000000001
    - type: ap
      value: 13.469175027934261
    - type: f1
      value: 53.36791912322706
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.08602150537634
    - type: f1
      value: 54.293272673368165
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 34.138276585709114
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.07939440901234
    - type: cos_sim_ap
      value: 67.0405163640066
    - type: cos_sim_f1
      value: 63.662932294203614
    - type: cos_sim_precision
      value: 59.11352329262777
    - type: cos_sim_recall
      value: 68.97097625329816
    - type: dot_accuracy
      value: 84.07939440901234
    - type: dot_ap
      value: 67.0405163640066
    - type: dot_f1
      value: 63.662932294203614
    - type: dot_precision
      value: 59.11352329262777
    - type: dot_recall
      value: 68.97097625329816
    - type: euclidean_accuracy
      value: 84.07939440901234
    - type: euclidean_ap
      value: 67.0405163640066
    - type: euclidean_f1
      value: 63.662932294203614
    - type: euclidean_precision
      value: 59.11352329262777
    - type: euclidean_recall
      value: 68.97097625329816
    - type: manhattan_accuracy
      value: 83.87673600762949
    - type: manhattan_ap
      value: 66.16533283565825
    - type: manhattan_f1
      value: 62.82331746236005
    - type: manhattan_precision
      value: 61.316252197940216
    - type: manhattan_recall
      value: 64.40633245382585
    - type: max_accuracy
      value: 84.07939440901234
    - type: max_ap
      value: 67.0405163640066
    - type: max_f1
      value: 63.662932294203614
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.35592036325532
    - type: cos_sim_ap
      value: 82.35246546365819
    - type: cos_sim_f1
      value: 74.62482455824667
    - type: cos_sim_precision
      value: 70.05878775592946
    - type: cos_sim_recall
      value: 79.82753310748383
    - type: dot_accuracy
      value: 87.35592036325532
    - type: dot_ap
      value: 82.35246501956695
    - type: dot_f1
      value: 74.62482455824667
    - type: dot_precision
      value: 70.05878775592946
    - type: dot_recall
      value: 79.82753310748383
    - type: euclidean_accuracy
      value: 87.35592036325532
    - type: euclidean_ap
      value: 82.35246658420216
    - type: euclidean_f1
      value: 74.62482455824667
    - type: euclidean_precision
      value: 70.05878775592946
    - type: euclidean_recall
      value: 79.82753310748383
    - type: manhattan_accuracy
      value: 87.23755190747856
    - type: manhattan_ap
      value: 82.40925935550737
    - type: manhattan_f1
      value: 74.54605723546095
    - type: manhattan_precision
      value: 71.45378803925722
    - type: manhattan_recall
      value: 77.91807822605482
    - type: max_accuracy
      value: 87.35592036325532
    - type: max_ap
      value: 82.40925935550737
    - type: max_f1
      value: 74.62482455824667
---
