mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_307_w50k_b30k
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.04477611940298
    - type: ap
      value: 34.133147681736574
    - type: f1
      value: 65.73569090089603
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.6129
    - type: ap
      value: 59.73474867106533
    - type: f1
      value: 64.37745361254407
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.86000000000001
    - type: f1
      value: 33.4167439582646
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.555
    - type: map_at_10
      value: 34.29
    - type: map_at_100
      value: 35.473
    - type: map_at_1000
      value: 35.498000000000005
    - type: map_at_3
      value: 29.753
    - type: map_at_5
      value: 32.257000000000005
    - type: mrr_at_1
      value: 21.266
    - type: mrr_at_10
      value: 34.571000000000005
    - type: mrr_at_100
      value: 35.732
    - type: mrr_at_1000
      value: 35.758
    - type: mrr_at_3
      value: 30.037999999999997
    - type: mrr_at_5
      value: 32.492
    - type: ndcg_at_1
      value: 20.555
    - type: ndcg_at_10
      value: 42.283
    - type: ndcg_at_100
      value: 47.904
    - type: ndcg_at_1000
      value: 48.518
    - type: ndcg_at_3
      value: 32.845
    - type: ndcg_at_5
      value: 37.372
    - type: precision_at_1
      value: 20.555
    - type: precision_at_10
      value: 6.7989999999999995
    - type: precision_at_100
      value: 0.9400000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.94
    - type: precision_at_5
      value: 10.569
    - type: recall_at_1
      value: 20.555
    - type: recall_at_10
      value: 67.994
    - type: recall_at_100
      value: 93.95400000000001
    - type: recall_at_1000
      value: 98.649
    - type: recall_at_3
      value: 41.821000000000005
    - type: recall_at_5
      value: 52.845
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 31.705177661382283
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 21.93065120477086
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.52224532394495
    - type: mrr
      value: 66.04625599085433
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.75516031950443
    - type: cos_sim_spearman
      value: 76.92645161656596
    - type: euclidean_pearson
      value: 78.07410163583403
    - type: euclidean_spearman
      value: 76.92645161656596
    - type: manhattan_pearson
      value: 77.99272531232194
    - type: manhattan_spearman
      value: 76.85596808284
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.29220779220779
    - type: f1
      value: 71.45293655648962
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 29.683083608126136
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 20.115223677732263
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.508
    - type: map_at_10
      value: 28.613
    - type: map_at_100
      value: 29.694
    - type: map_at_1000
      value: 29.848000000000003
    - type: map_at_3
      value: 26.444000000000003
    - type: map_at_5
      value: 27.705000000000002
    - type: mrr_at_1
      value: 27.039
    - type: mrr_at_10
      value: 34.28
    - type: mrr_at_100
      value: 35.156
    - type: mrr_at_1000
      value: 35.229
    - type: mrr_at_3
      value: 32.546
    - type: mrr_at_5
      value: 33.541
    - type: ndcg_at_1
      value: 27.039
    - type: ndcg_at_10
      value: 33.157
    - type: ndcg_at_100
      value: 38.172
    - type: ndcg_at_1000
      value: 41.407
    - type: ndcg_at_3
      value: 30.293999999999997
    - type: ndcg_at_5
      value: 31.540000000000003
    - type: precision_at_1
      value: 27.039
    - type: precision_at_10
      value: 6.223
    - type: precision_at_100
      value: 1.087
    - type: precision_at_1000
      value: 0.166
    - type: precision_at_3
      value: 14.688
    - type: precision_at_5
      value: 10.501000000000001
    - type: recall_at_1
      value: 21.508
    - type: recall_at_10
      value: 40.608
    - type: recall_at_100
      value: 63.131
    - type: recall_at_1000
      value: 85.292
    - type: recall_at_3
      value: 31.283
    - type: recall_at_5
      value: 35.237
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.338
    - type: map_at_10
      value: 21.65
    - type: map_at_100
      value: 22.549
    - type: map_at_1000
      value: 22.675
    - type: map_at_3
      value: 19.888
    - type: map_at_5
      value: 20.848
    - type: mrr_at_1
      value: 20.764
    - type: mrr_at_10
      value: 25.8
    - type: mrr_at_100
      value: 26.590000000000003
    - type: mrr_at_1000
      value: 26.663999999999998
    - type: mrr_at_3
      value: 24.066000000000003
    - type: mrr_at_5
      value: 24.907
    - type: ndcg_at_1
      value: 20.764
    - type: ndcg_at_10
      value: 25.229000000000003
    - type: ndcg_at_100
      value: 29.604000000000003
    - type: ndcg_at_1000
      value: 32.535
    - type: ndcg_at_3
      value: 22.294
    - type: ndcg_at_5
      value: 23.52
    - type: precision_at_1
      value: 20.764
    - type: precision_at_10
      value: 4.675
    - type: precision_at_100
      value: 0.859
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.616
    - type: precision_at_5
      value: 7.567
    - type: recall_at_1
      value: 16.338
    - type: recall_at_10
      value: 31.825
    - type: recall_at_100
      value: 51.400999999999996
    - type: recall_at_1000
      value: 71.50800000000001
    - type: recall_at_3
      value: 23.372
    - type: recall_at_5
      value: 26.662000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.196
    - type: map_at_10
      value: 33.175
    - type: map_at_100
      value: 34.239000000000004
    - type: map_at_1000
      value: 34.339
    - type: map_at_3
      value: 30.887999999999998
    - type: map_at_5
      value: 32.090999999999994
    - type: mrr_at_1
      value: 28.965999999999998
    - type: mrr_at_10
      value: 36.148
    - type: mrr_at_100
      value: 37.015
    - type: mrr_at_1000
      value: 37.078
    - type: mrr_at_3
      value: 33.992
    - type: mrr_at_5
      value: 35.117
    - type: ndcg_at_1
      value: 28.965999999999998
    - type: ndcg_at_10
      value: 37.687
    - type: ndcg_at_100
      value: 42.768
    - type: ndcg_at_1000
      value: 45.07
    - type: ndcg_at_3
      value: 33.341
    - type: ndcg_at_5
      value: 35.237
    - type: precision_at_1
      value: 28.965999999999998
    - type: precision_at_10
      value: 6.138
    - type: precision_at_100
      value: 0.95
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 14.796000000000001
    - type: precision_at_5
      value: 10.194
    - type: recall_at_1
      value: 25.196
    - type: recall_at_10
      value: 48.443000000000005
    - type: recall_at_100
      value: 71.414
    - type: recall_at_1000
      value: 88.108
    - type: recall_at_3
      value: 36.647999999999996
    - type: recall_at_5
      value: 41.384
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 11.036
    - type: map_at_10
      value: 15.011
    - type: map_at_100
      value: 15.751999999999999
    - type: map_at_1000
      value: 15.864
    - type: map_at_3
      value: 13.675
    - type: map_at_5
      value: 14.414
    - type: mrr_at_1
      value: 12.203
    - type: mrr_at_10
      value: 16.232
    - type: mrr_at_100
      value: 16.965
    - type: mrr_at_1000
      value: 17.069000000000003
    - type: mrr_at_3
      value: 14.84
    - type: mrr_at_5
      value: 15.591
    - type: ndcg_at_1
      value: 12.203
    - type: ndcg_at_10
      value: 17.59
    - type: ndcg_at_100
      value: 21.718
    - type: ndcg_at_1000
      value: 25.108000000000004
    - type: ndcg_at_3
      value: 14.857999999999999
    - type: ndcg_at_5
      value: 16.161
    - type: precision_at_1
      value: 12.203
    - type: precision_at_10
      value: 2.757
    - type: precision_at_100
      value: 0.518
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.328
    - type: precision_at_5
      value: 4.497
    - type: recall_at_1
      value: 11.036
    - type: recall_at_10
      value: 24.511
    - type: recall_at_100
      value: 44.396
    - type: recall_at_1000
      value: 70.916
    - type: recall_at_3
      value: 17.1
    - type: recall_at_5
      value: 20.244999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.329999999999999
    - type: map_at_10
      value: 9.338000000000001
    - type: map_at_100
      value: 10.047
    - type: map_at_1000
      value: 10.164
    - type: map_at_3
      value: 8.072
    - type: map_at_5
      value: 8.863
    - type: mrr_at_1
      value: 8.333
    - type: mrr_at_10
      value: 11.55
    - type: mrr_at_100
      value: 12.298
    - type: mrr_at_1000
      value: 12.393
    - type: mrr_at_3
      value: 10.095
    - type: mrr_at_5
      value: 10.947
    - type: ndcg_at_1
      value: 8.333
    - type: ndcg_at_10
      value: 11.676
    - type: ndcg_at_100
      value: 15.468000000000002
    - type: ndcg_at_1000
      value: 19.057
    - type: ndcg_at_3
      value: 9.17
    - type: ndcg_at_5
      value: 10.484
    - type: precision_at_1
      value: 8.333
    - type: precision_at_10
      value: 2.2640000000000002
    - type: precision_at_100
      value: 0.484
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.353
    - type: precision_at_5
      value: 3.458
    - type: recall_at_1
      value: 6.329999999999999
    - type: recall_at_10
      value: 16.825000000000003
    - type: recall_at_100
      value: 33.986
    - type: recall_at_1000
      value: 60.80799999999999
    - type: recall_at_3
      value: 9.98
    - type: recall_at_5
      value: 13.251
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.105999999999998
    - type: map_at_10
      value: 22.99
    - type: map_at_100
      value: 24.108999999999998
    - type: map_at_1000
      value: 24.239
    - type: map_at_3
      value: 21.096999999999998
    - type: map_at_5
      value: 22.076
    - type: mrr_at_1
      value: 21.752
    - type: mrr_at_10
      value: 27.793
    - type: mrr_at_100
      value: 28.676000000000002
    - type: mrr_at_1000
      value: 28.754999999999995
    - type: mrr_at_3
      value: 25.874000000000002
    - type: mrr_at_5
      value: 26.88
    - type: ndcg_at_1
      value: 21.752
    - type: ndcg_at_10
      value: 27.151999999999997
    - type: ndcg_at_100
      value: 32.492
    - type: ndcg_at_1000
      value: 35.563
    - type: ndcg_at_3
      value: 23.839
    - type: ndcg_at_5
      value: 25.188
    - type: precision_at_1
      value: 21.752
    - type: precision_at_10
      value: 4.986
    - type: precision_at_100
      value: 0.9249999999999999
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.197
    - type: precision_at_5
      value: 7.968999999999999
    - type: recall_at_1
      value: 17.105999999999998
    - type: recall_at_10
      value: 35.231
    - type: recall_at_100
      value: 58.634
    - type: recall_at_1000
      value: 80.077
    - type: recall_at_3
      value: 25.534000000000002
    - type: recall_at_5
      value: 29.175
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.303
    - type: map_at_10
      value: 16.778000000000002
    - type: map_at_100
      value: 17.802
    - type: map_at_1000
      value: 17.944
    - type: map_at_3
      value: 14.906
    - type: map_at_5
      value: 16.038
    - type: mrr_at_1
      value: 14.269000000000002
    - type: mrr_at_10
      value: 19.967
    - type: mrr_at_100
      value: 20.921
    - type: mrr_at_1000
      value: 21.009
    - type: mrr_at_3
      value: 18.075
    - type: mrr_at_5
      value: 19.198999999999998
    - type: ndcg_at_1
      value: 14.269000000000002
    - type: ndcg_at_10
      value: 20.294999999999998
    - type: ndcg_at_100
      value: 25.346999999999998
    - type: ndcg_at_1000
      value: 28.860999999999997
    - type: ndcg_at_3
      value: 16.858
    - type: ndcg_at_5
      value: 18.647
    - type: precision_at_1
      value: 14.269000000000002
    - type: precision_at_10
      value: 3.904
    - type: precision_at_100
      value: 0.757
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 8.029
    - type: precision_at_5
      value: 6.164
    - type: recall_at_1
      value: 11.303
    - type: recall_at_10
      value: 27.661
    - type: recall_at_100
      value: 49.976
    - type: recall_at_1000
      value: 75.01400000000001
    - type: recall_at_3
      value: 18.719
    - type: recall_at_5
      value: 23.061999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.457416666666669
    - type: map_at_10
      value: 18.469333333333335
    - type: map_at_100
      value: 19.32433333333334
    - type: map_at_1000
      value: 19.44766666666667
    - type: map_at_3
      value: 16.88808333333333
    - type: map_at_5
      value: 17.75958333333333
    - type: mrr_at_1
      value: 16.38458333333333
    - type: mrr_at_10
      value: 21.479583333333334
    - type: mrr_at_100
      value: 22.253666666666664
    - type: mrr_at_1000
      value: 22.340916666666665
    - type: mrr_at_3
      value: 19.879083333333334
    - type: mrr_at_5
      value: 20.749750000000002
    - type: ndcg_at_1
      value: 16.38458333333333
    - type: ndcg_at_10
      value: 21.7645
    - type: ndcg_at_100
      value: 26.100583333333333
    - type: ndcg_at_1000
      value: 29.30358333333334
    - type: ndcg_at_3
      value: 18.90866666666667
    - type: ndcg_at_5
      value: 20.19475
    - type: precision_at_1
      value: 16.38458333333333
    - type: precision_at_10
      value: 3.896916666666667
    - type: precision_at_100
      value: 0.7189999999999999
    - type: precision_at_1000
      value: 0.11716666666666666
    - type: precision_at_3
      value: 8.805583333333333
    - type: precision_at_5
      value: 6.311999999999999
    - type: recall_at_1
      value: 13.457416666666669
    - type: recall_at_10
      value: 28.731250000000003
    - type: recall_at_100
      value: 48.64233333333334
    - type: recall_at_1000
      value: 72.04116666666665
    - type: recall_at_3
      value: 20.665249999999997
    - type: recall_at_5
      value: 23.995583333333332
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.05
    - type: map_at_10
      value: 14.036999999999999
    - type: map_at_100
      value: 14.64
    - type: map_at_1000
      value: 14.722
    - type: map_at_3
      value: 12.85
    - type: map_at_5
      value: 13.517000000000001
    - type: mrr_at_1
      value: 12.117
    - type: mrr_at_10
      value: 16.145
    - type: mrr_at_100
      value: 16.732
    - type: mrr_at_1000
      value: 16.811
    - type: mrr_at_3
      value: 14.877
    - type: mrr_at_5
      value: 15.583
    - type: ndcg_at_1
      value: 12.117
    - type: ndcg_at_10
      value: 16.668
    - type: ndcg_at_100
      value: 19.971
    - type: ndcg_at_1000
      value: 22.527
    - type: ndcg_at_3
      value: 14.393
    - type: ndcg_at_5
      value: 15.436
    - type: precision_at_1
      value: 12.117
    - type: precision_at_10
      value: 2.822
    - type: precision_at_100
      value: 0.49500000000000005
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 6.646000000000001
    - type: precision_at_5
      value: 4.662999999999999
    - type: recall_at_1
      value: 10.05
    - type: recall_at_10
      value: 22.899
    - type: recall_at_100
      value: 38.489000000000004
    - type: recall_at_1000
      value: 58.275
    - type: recall_at_3
      value: 16.166
    - type: recall_at_5
      value: 18.976000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.185999999999999
    - type: map_at_10
      value: 10.324
    - type: map_at_100
      value: 10.921
    - type: map_at_1000
      value: 11.038
    - type: map_at_3
      value: 9.35
    - type: map_at_5
      value: 9.918000000000001
    - type: mrr_at_1
      value: 8.878
    - type: mrr_at_10
      value: 12.497
    - type: mrr_at_100
      value: 13.103000000000002
    - type: mrr_at_1000
      value: 13.203000000000001
    - type: mrr_at_3
      value: 11.373
    - type: mrr_at_5
      value: 12.061
    - type: ndcg_at_1
      value: 8.878
    - type: ndcg_at_10
      value: 12.543000000000001
    - type: ndcg_at_100
      value: 15.943999999999999
    - type: ndcg_at_1000
      value: 19.407
    - type: ndcg_at_3
      value: 10.687000000000001
    - type: ndcg_at_5
      value: 11.619
    - type: precision_at_1
      value: 8.878
    - type: precision_at_10
      value: 2.35
    - type: precision_at_100
      value: 0.488
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 5.127000000000001
    - type: precision_at_5
      value: 3.82
    - type: recall_at_1
      value: 7.185999999999999
    - type: recall_at_10
      value: 17.138
    - type: recall_at_100
      value: 33.194
    - type: recall_at_1000
      value: 59.14
    - type: recall_at_3
      value: 12.058
    - type: recall_at_5
      value: 14.329
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.498
    - type: map_at_10
      value: 15.725
    - type: map_at_100
      value: 16.515
    - type: map_at_1000
      value: 16.628
    - type: map_at_3
      value: 14.335999999999999
    - type: map_at_5
      value: 15.027
    - type: mrr_at_1
      value: 14.086000000000002
    - type: mrr_at_10
      value: 18.592
    - type: mrr_at_100
      value: 19.405
    - type: mrr_at_1000
      value: 19.500999999999998
    - type: mrr_at_3
      value: 17.086000000000002
    - type: mrr_at_5
      value: 17.855999999999998
    - type: ndcg_at_1
      value: 14.086000000000002
    - type: ndcg_at_10
      value: 18.686
    - type: ndcg_at_100
      value: 22.925
    - type: ndcg_at_1000
      value: 26.279999999999998
    - type: ndcg_at_3
      value: 15.955
    - type: ndcg_at_5
      value: 17.05
    - type: precision_at_1
      value: 14.086000000000002
    - type: precision_at_10
      value: 3.209
    - type: precision_at_100
      value: 0.587
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 7.338
    - type: precision_at_5
      value: 5.131
    - type: recall_at_1
      value: 11.498
    - type: recall_at_10
      value: 25.135
    - type: recall_at_100
      value: 44.751000000000005
    - type: recall_at_1000
      value: 69.75
    - type: recall_at_3
      value: 17.471999999999998
    - type: recall_at_5
      value: 20.273
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.111999999999998
    - type: map_at_10
      value: 19.224
    - type: map_at_100
      value: 20.183999999999997
    - type: map_at_1000
      value: 20.354
    - type: map_at_3
      value: 17.738
    - type: map_at_5
      value: 18.518
    - type: mrr_at_1
      value: 16.008
    - type: mrr_at_10
      value: 22.421
    - type: mrr_at_100
      value: 23.174
    - type: mrr_at_1000
      value: 23.261000000000003
    - type: mrr_at_3
      value: 20.784
    - type: mrr_at_5
      value: 21.634
    - type: ndcg_at_1
      value: 16.008
    - type: ndcg_at_10
      value: 23.082
    - type: ndcg_at_100
      value: 27.563
    - type: ndcg_at_1000
      value: 31.135
    - type: ndcg_at_3
      value: 20.517
    - type: ndcg_at_5
      value: 21.595
    - type: precision_at_1
      value: 16.008
    - type: precision_at_10
      value: 4.625
    - type: precision_at_100
      value: 0.966
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 10.079
    - type: precision_at_5
      value: 7.2330000000000005
    - type: recall_at_1
      value: 13.111999999999998
    - type: recall_at_10
      value: 30.297
    - type: recall_at_100
      value: 51.549
    - type: recall_at_1000
      value: 76.255
    - type: recall_at_3
      value: 22.817999999999998
    - type: recall_at_5
      value: 25.741000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.825999999999999
    - type: map_at_10
      value: 14.767
    - type: map_at_100
      value: 15.440000000000001
    - type: map_at_1000
      value: 15.557000000000002
    - type: map_at_3
      value: 13.413
    - type: map_at_5
      value: 14.099999999999998
    - type: mrr_at_1
      value: 12.2
    - type: mrr_at_10
      value: 16.33
    - type: mrr_at_100
      value: 17.009
    - type: mrr_at_1000
      value: 17.118
    - type: mrr_at_3
      value: 14.940999999999999
    - type: mrr_at_5
      value: 15.681000000000001
    - type: ndcg_at_1
      value: 12.2
    - type: ndcg_at_10
      value: 17.409
    - type: ndcg_at_100
      value: 21.235
    - type: ndcg_at_1000
      value: 24.693
    - type: ndcg_at_3
      value: 14.698
    - type: ndcg_at_5
      value: 15.86
    - type: precision_at_1
      value: 12.2
    - type: precision_at_10
      value: 2.81
    - type: precision_at_100
      value: 0.512
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 6.47
    - type: precision_at_5
      value: 4.547
    - type: recall_at_1
      value: 10.825999999999999
    - type: recall_at_10
      value: 24.202
    - type: recall_at_100
      value: 42.787
    - type: recall_at_1000
      value: 69.351
    - type: recall_at_3
      value: 16.833000000000002
    - type: recall_at_5
      value: 19.612
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.436
    - type: map_at_10
      value: 9.59
    - type: map_at_100
      value: 10.847
    - type: map_at_1000
      value: 11.043
    - type: map_at_3
      value: 7.797
    - type: map_at_5
      value: 8.627
    - type: mrr_at_1
      value: 12.182
    - type: mrr_at_10
      value: 19.584
    - type: mrr_at_100
      value: 20.772
    - type: mrr_at_1000
      value: 20.855999999999998
    - type: mrr_at_3
      value: 16.938
    - type: mrr_at_5
      value: 18.358
    - type: ndcg_at_1
      value: 12.182
    - type: ndcg_at_10
      value: 14.514
    - type: ndcg_at_100
      value: 20.495
    - type: ndcg_at_1000
      value: 24.664
    - type: ndcg_at_3
      value: 11.024000000000001
    - type: ndcg_at_5
      value: 12.200999999999999
    - type: precision_at_1
      value: 12.182
    - type: precision_at_10
      value: 4.853
    - type: precision_at_100
      value: 1.124
    - type: precision_at_1000
      value: 0.187
    - type: precision_at_3
      value: 8.317
    - type: precision_at_5
      value: 6.697
    - type: recall_at_1
      value: 5.436
    - type: recall_at_10
      value: 18.615000000000002
    - type: recall_at_100
      value: 39.621
    - type: recall_at_1000
      value: 63.852
    - type: recall_at_3
      value: 10.474
    - type: recall_at_5
      value: 13.370999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.8309999999999995
    - type: map_at_10
      value: 7.7490000000000006
    - type: map_at_100
      value: 10.421
    - type: map_at_1000
      value: 11.161
    - type: map_at_3
      value: 5.762
    - type: map_at_5
      value: 6.645
    - type: mrr_at_1
      value: 35.25
    - type: mrr_at_10
      value: 43.685
    - type: mrr_at_100
      value: 44.567
    - type: mrr_at_1000
      value: 44.618
    - type: mrr_at_3
      value: 41.375
    - type: mrr_at_5
      value: 42.85
    - type: ndcg_at_1
      value: 25.624999999999996
    - type: ndcg_at_10
      value: 19.837
    - type: ndcg_at_100
      value: 21.92
    - type: ndcg_at_1000
      value: 28.116000000000003
    - type: ndcg_at_3
      value: 22.561
    - type: ndcg_at_5
      value: 21.073
    - type: precision_at_1
      value: 35.25
    - type: precision_at_10
      value: 17.125
    - type: precision_at_100
      value: 5.35
    - type: precision_at_1000
      value: 1.142
    - type: precision_at_3
      value: 25.833000000000002
    - type: precision_at_5
      value: 22.0
    - type: recall_at_1
      value: 3.8309999999999995
    - type: recall_at_10
      value: 11.393
    - type: recall_at_100
      value: 26.519
    - type: recall_at_1000
      value: 47.249
    - type: recall_at_3
      value: 6.708
    - type: recall_at_5
      value: 8.584
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.69
    - type: f1
      value: 39.825457200782445
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 10.94
    - type: map_at_10
      value: 16.482
    - type: map_at_100
      value: 17.321
    - type: map_at_1000
      value: 17.403
    - type: map_at_3
      value: 14.679
    - type: map_at_5
      value: 15.637
    - type: mrr_at_1
      value: 11.701
    - type: mrr_at_10
      value: 17.583
    - type: mrr_at_100
      value: 18.444
    - type: mrr_at_1000
      value: 18.519
    - type: mrr_at_3
      value: 15.709000000000001
    - type: mrr_at_5
      value: 16.707
    - type: ndcg_at_1
      value: 11.701
    - type: ndcg_at_10
      value: 19.946
    - type: ndcg_at_100
      value: 24.462
    - type: ndcg_at_1000
      value: 26.863
    - type: ndcg_at_3
      value: 16.155
    - type: ndcg_at_5
      value: 17.888
    - type: precision_at_1
      value: 11.701
    - type: precision_at_10
      value: 3.2399999999999998
    - type: precision_at_100
      value: 0.5680000000000001
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 6.991
    - type: precision_at_5
      value: 5.101
    - type: recall_at_1
      value: 10.94
    - type: recall_at_10
      value: 29.848000000000003
    - type: recall_at_100
      value: 51.451
    - type: recall_at_1000
      value: 70.316
    - type: recall_at_3
      value: 19.39
    - type: recall_at_5
      value: 23.583000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.825
    - type: map_at_10
      value: 9.669
    - type: map_at_100
      value: 10.657
    - type: map_at_1000
      value: 10.850999999999999
    - type: map_at_3
      value: 8.174
    - type: map_at_5
      value: 8.931000000000001
    - type: mrr_at_1
      value: 11.574
    - type: mrr_at_10
      value: 17.153
    - type: mrr_at_100
      value: 18.027
    - type: mrr_at_1000
      value: 18.138
    - type: mrr_at_3
      value: 15.201
    - type: mrr_at_5
      value: 16.119
    - type: ndcg_at_1
      value: 11.574
    - type: ndcg_at_10
      value: 13.599
    - type: ndcg_at_100
      value: 18.422
    - type: ndcg_at_1000
      value: 23.124
    - type: ndcg_at_3
      value: 11.219999999999999
    - type: ndcg_at_5
      value: 11.984
    - type: precision_at_1
      value: 11.574
    - type: precision_at_10
      value: 4.043
    - type: precision_at_100
      value: 0.8869999999999999
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 7.716000000000001
    - type: precision_at_5
      value: 5.926
    - type: recall_at_1
      value: 5.825
    - type: recall_at_10
      value: 17.837
    - type: recall_at_100
      value: 36.771
    - type: recall_at_1000
      value: 66.81
    - type: recall_at_3
      value: 10.181999999999999
    - type: recall_at_5
      value: 12.909
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.558
    - type: map_at_10
      value: 18.987000000000002
    - type: map_at_100
      value: 19.768
    - type: map_at_1000
      value: 19.878999999999998
    - type: map_at_3
      value: 17.399
    - type: map_at_5
      value: 18.231
    - type: mrr_at_1
      value: 27.117
    - type: mrr_at_10
      value: 33.32
    - type: mrr_at_100
      value: 34.050000000000004
    - type: mrr_at_1000
      value: 34.122
    - type: mrr_at_3
      value: 31.570999999999998
    - type: mrr_at_5
      value: 32.519999999999996
    - type: ndcg_at_1
      value: 27.117
    - type: ndcg_at_10
      value: 24.708
    - type: ndcg_at_100
      value: 28.566000000000003
    - type: ndcg_at_1000
      value: 31.418000000000003
    - type: ndcg_at_3
      value: 21.549
    - type: ndcg_at_5
      value: 22.997
    - type: precision_at_1
      value: 27.117
    - type: precision_at_10
      value: 5.5169999999999995
    - type: precision_at_100
      value: 0.8630000000000001
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 13.603000000000002
    - type: precision_at_5
      value: 9.313
    - type: recall_at_1
      value: 13.558
    - type: recall_at_10
      value: 27.583000000000002
    - type: recall_at_100
      value: 43.153000000000006
    - type: recall_at_1000
      value: 62.255
    - type: recall_at_3
      value: 20.405
    - type: recall_at_5
      value: 23.282
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.06880000000001
    - type: ap
      value: 59.27294551535466
    - type: f1
      value: 63.91536827569369
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.241
    - type: map_at_10
      value: 9.158
    - type: map_at_100
      value: 9.907
    - type: map_at_1000
      value: 10.001
    - type: map_at_3
      value: 7.7
    - type: map_at_5
      value: 8.466999999999999
    - type: mrr_at_1
      value: 5.43
    - type: mrr_at_10
      value: 9.42
    - type: mrr_at_100
      value: 10.174999999999999
    - type: mrr_at_1000
      value: 10.267999999999999
    - type: mrr_at_3
      value: 7.932
    - type: mrr_at_5
      value: 8.718
    - type: ndcg_at_1
      value: 5.415
    - type: ndcg_at_10
      value: 11.655
    - type: ndcg_at_100
      value: 15.894
    - type: ndcg_at_1000
      value: 18.837
    - type: ndcg_at_3
      value: 8.59
    - type: ndcg_at_5
      value: 9.982000000000001
    - type: precision_at_1
      value: 5.415
    - type: precision_at_10
      value: 2.023
    - type: precision_at_100
      value: 0.42500000000000004
    - type: precision_at_1000
      value: 0.068
    - type: precision_at_3
      value: 3.7920000000000003
    - type: precision_at_5
      value: 2.971
    - type: recall_at_1
      value: 5.241
    - type: recall_at_10
      value: 19.429
    - type: recall_at_100
      value: 40.422999999999995
    - type: recall_at_1000
      value: 64.191
    - type: recall_at_3
      value: 10.95
    - type: recall_at_5
      value: 14.319
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.40264477884178
    - type: f1
      value: 88.48890314653876
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.86320109439125
    - type: f1
      value: 40.351741507970175
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.17552118359112
    - type: f1
      value: 59.92291942649051
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.89710827168797
    - type: f1
      value: 67.48141199477321
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.003683715948068
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.655067999182727
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.614207594880682
    - type: mrr
      value: 29.46624248673221
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.047
    - type: map_at_10
      value: 6.144
    - type: map_at_100
      value: 7.806
    - type: map_at_1000
      value: 8.998000000000001
    - type: map_at_3
      value: 4.566
    - type: map_at_5
      value: 5.321
    - type: mrr_at_1
      value: 30.65
    - type: mrr_at_10
      value: 39.213
    - type: mrr_at_100
      value: 39.973
    - type: mrr_at_1000
      value: 40.048
    - type: mrr_at_3
      value: 36.687
    - type: mrr_at_5
      value: 38.421
    - type: ndcg_at_1
      value: 28.638
    - type: ndcg_at_10
      value: 21.032
    - type: ndcg_at_100
      value: 19.85
    - type: ndcg_at_1000
      value: 29.416999999999998
    - type: ndcg_at_3
      value: 24.403
    - type: ndcg_at_5
      value: 22.956
    - type: precision_at_1
      value: 30.65
    - type: precision_at_10
      value: 15.479999999999999
    - type: precision_at_100
      value: 5.83
    - type: precision_at_1000
      value: 1.8800000000000001
    - type: precision_at_3
      value: 23.22
    - type: precision_at_5
      value: 19.628
    - type: recall_at_1
      value: 3.047
    - type: recall_at_10
      value: 9.871
    - type: recall_at_100
      value: 21.556
    - type: recall_at_1000
      value: 56.15
    - type: recall_at_3
      value: 5.476
    - type: recall_at_5
      value: 7.359
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.79
    - type: map_at_10
      value: 13.5
    - type: map_at_100
      value: 14.541
    - type: map_at_1000
      value: 14.643
    - type: map_at_3
      value: 11.446000000000002
    - type: map_at_5
      value: 12.437
    - type: mrr_at_1
      value: 8.863999999999999
    - type: mrr_at_10
      value: 14.985000000000001
    - type: mrr_at_100
      value: 15.989999999999998
    - type: mrr_at_1000
      value: 16.073
    - type: mrr_at_3
      value: 12.799
    - type: mrr_at_5
      value: 13.902999999999999
    - type: ndcg_at_1
      value: 8.863999999999999
    - type: ndcg_at_10
      value: 17.335
    - type: ndcg_at_100
      value: 22.884
    - type: ndcg_at_1000
      value: 25.747999999999998
    - type: ndcg_at_3
      value: 12.97
    - type: ndcg_at_5
      value: 14.799000000000001
    - type: precision_at_1
      value: 8.863999999999999
    - type: precision_at_10
      value: 3.2620000000000005
    - type: precision_at_100
      value: 0.6459999999999999
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 6.161
    - type: precision_at_5
      value: 4.733
    - type: recall_at_1
      value: 7.79
    - type: recall_at_10
      value: 27.868
    - type: recall_at_100
      value: 54.096999999999994
    - type: recall_at_1000
      value: 76.27199999999999
    - type: recall_at_3
      value: 16.063
    - type: recall_at_5
      value: 20.355
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.968
    - type: map_at_10
      value: 73.346
    - type: map_at_100
      value: 74.144
    - type: map_at_1000
      value: 74.181
    - type: map_at_3
      value: 70.462
    - type: map_at_5
      value: 72.167
    - type: mrr_at_1
      value: 70.24000000000001
    - type: mrr_at_10
      value: 77.794
    - type: mrr_at_100
      value: 78.079
    - type: mrr_at_1000
      value: 78.086
    - type: mrr_at_3
      value: 76.265
    - type: mrr_at_5
      value: 77.242
    - type: ndcg_at_1
      value: 70.28999999999999
    - type: ndcg_at_10
      value: 78.16199999999999
    - type: ndcg_at_100
      value: 80.515
    - type: ndcg_at_1000
      value: 80.987
    - type: ndcg_at_3
      value: 74.49
    - type: ndcg_at_5
      value: 76.334
    - type: precision_at_1
      value: 70.28999999999999
    - type: precision_at_10
      value: 11.827
    - type: precision_at_100
      value: 1.435
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 32.25
    - type: precision_at_5
      value: 21.342
    - type: recall_at_1
      value: 60.968
    - type: recall_at_10
      value: 87.449
    - type: recall_at_100
      value: 96.557
    - type: recall_at_1000
      value: 99.328
    - type: recall_at_3
      value: 76.91799999999999
    - type: recall_at_5
      value: 82.048
    - type: map_at_1
      value: 2.635
    - type: map_at_10
      value: 6.061
    - type: map_at_100
      value: 7.287000000000001
    - type: map_at_1000
      value: 7.528
    - type: map_at_3
      value: 4.424
    - type: map_at_5
      value: 5.226
    - type: mrr_at_1
      value: 13.0
    - type: mrr_at_10
      value: 20.066
    - type: mrr_at_100
      value: 21.352
    - type: mrr_at_1000
      value: 21.447
    - type: mrr_at_3
      value: 17.666999999999998
    - type: mrr_at_5
      value: 19.002
    - type: ndcg_at_1
      value: 13.0
    - type: ndcg_at_10
      value: 10.943
    - type: ndcg_at_100
      value: 16.822
    - type: ndcg_at_1000
      value: 21.905
    - type: ndcg_at_3
      value: 10.291
    - type: ndcg_at_5
      value: 9.028
    - type: precision_at_1
      value: 13.0
    - type: precision_at_10
      value: 5.680000000000001
    - type: precision_at_100
      value: 1.4200000000000002
    - type: precision_at_1000
      value: 0.265
    - type: precision_at_3
      value: 9.5
    - type: precision_at_5
      value: 7.86
    - type: recall_at_1
      value: 2.635
    - type: recall_at_10
      value: 11.501999999999999
    - type: recall_at_100
      value: 28.854999999999997
    - type: recall_at_1000
      value: 53.818
    - type: recall_at_3
      value: 5.798
    - type: recall_at_5
      value: 7.963000000000001
    - type: map_at_1
      value: 0.11299999999999999
    - type: map_at_10
      value: 0.652
    - type: map_at_100
      value: 3.51
    - type: map_at_1000
      value: 8.445
    - type: map_at_3
      value: 0.259
    - type: map_at_5
      value: 0.392
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 58.263
    - type: mrr_at_100
      value: 58.935
    - type: mrr_at_1000
      value: 58.935
    - type: mrr_at_3
      value: 55.00000000000001
    - type: mrr_at_5
      value: 56.39999999999999
    - type: ndcg_at_1
      value: 41.0
    - type: ndcg_at_10
      value: 34.724
    - type: ndcg_at_100
      value: 27.108999999999998
    - type: ndcg_at_1000
      value: 24.773999999999997
    - type: ndcg_at_3
      value: 38.48
    - type: ndcg_at_5
      value: 37.399
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 37.2
    - type: precision_at_100
      value: 28.4
    - type: precision_at_1000
      value: 12.21
    - type: precision_at_3
      value: 42.667
    - type: precision_at_5
      value: 40.8
    - type: recall_at_1
      value: 0.11299999999999999
    - type: recall_at_10
      value: 0.8370000000000001
    - type: recall_at_100
      value: 5.992
    - type: recall_at_1000
      value: 24.051000000000002
    - type: recall_at_3
      value: 0.28800000000000003
    - type: recall_at_5
      value: 0.469
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 28.013469586101447
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 43.29182795065702
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.50555278582816
    - type: cos_sim_spearman
      value: 67.67214548084267
    - type: euclidean_pearson
      value: 72.80672647042718
    - type: euclidean_spearman
      value: 67.67205019006775
    - type: manhattan_pearson
      value: 71.39917324420631
    - type: manhattan_spearman
      value: 66.3359934752193
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 73.46335143910176
    - type: cos_sim_spearman
      value: 66.48232205374549
    - type: euclidean_pearson
      value: 69.85631416436473
    - type: euclidean_spearman
      value: 66.48363705410418
    - type: manhattan_pearson
      value: 70.72055367256513
    - type: manhattan_spearman
      value: 67.85751320875836
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.64955371743831
    - type: cos_sim_spearman
      value: 78.9381622922565
    - type: euclidean_pearson
      value: 78.55659975799884
    - type: euclidean_spearman
      value: 78.93820009727344
    - type: manhattan_pearson
      value: 79.0225046950142
    - type: manhattan_spearman
      value: 79.48472901118284
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.25183335845733
    - type: cos_sim_spearman
      value: 74.24842723953067
    - type: euclidean_pearson
      value: 76.4686232324461
    - type: euclidean_spearman
      value: 74.24841754885648
    - type: manhattan_pearson
      value: 76.58863832312952
    - type: manhattan_spearman
      value: 74.65445574230469
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.89380076521006
    - type: cos_sim_spearman
      value: 80.97474081393298
    - type: euclidean_pearson
      value: 80.98258525159558
    - type: euclidean_spearman
      value: 80.97473932039865
    - type: manhattan_pearson
      value: 81.6739145030644
    - type: manhattan_spearman
      value: 81.84024193133868
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.47297982552274
    - type: cos_sim_spearman
      value: 76.78688389457616
    - type: euclidean_pearson
      value: 76.42350164312737
    - type: euclidean_spearman
      value: 76.78743419029857
    - type: manhattan_pearson
      value: 77.05352545216272
    - type: manhattan_spearman
      value: 77.51886896774369
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.91509212460161
    - type: cos_sim_spearman
      value: 84.0998411802368
    - type: euclidean_pearson
      value: 84.18246980817624
    - type: euclidean_spearman
      value: 84.10071528982036
    - type: manhattan_pearson
      value: 84.4128363010489
    - type: manhattan_spearman
      value: 84.43725453490214
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.86109059526856
    - type: cos_sim_spearman
      value: 60.51897891571115
    - type: euclidean_pearson
      value: 62.803664785666925
    - type: euclidean_spearman
      value: 60.51897891571115
    - type: manhattan_pearson
      value: 63.29647652965783
    - type: manhattan_spearman
      value: 61.57692163615942
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.23785194416263
    - type: cos_sim_spearman
      value: 75.86058891622369
    - type: euclidean_pearson
      value: 77.38393317729829
    - type: euclidean_spearman
      value: 75.86063730582144
    - type: manhattan_pearson
      value: 77.4860432550345
    - type: manhattan_spearman
      value: 76.0756045460265
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.65732608186795
    - type: mrr
      value: 90.0984182846928
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 30.721999999999998
    - type: map_at_10
      value: 37.522
    - type: map_at_100
      value: 38.699
    - type: map_at_1000
      value: 38.769
    - type: map_at_3
      value: 34.995
    - type: map_at_5
      value: 36.701
    - type: mrr_at_1
      value: 32.667
    - type: mrr_at_10
      value: 39.298
    - type: mrr_at_100
      value: 40.297
    - type: mrr_at_1000
      value: 40.354
    - type: mrr_at_3
      value: 37.167
    - type: mrr_at_5
      value: 38.533
    - type: ndcg_at_1
      value: 32.667
    - type: ndcg_at_10
      value: 41.634
    - type: ndcg_at_100
      value: 47.49
    - type: ndcg_at_1000
      value: 49.419000000000004
    - type: ndcg_at_3
      value: 36.925000000000004
    - type: ndcg_at_5
      value: 39.739000000000004
    - type: precision_at_1
      value: 32.667
    - type: precision_at_10
      value: 5.833
    - type: precision_at_100
      value: 0.91
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 14.556
    - type: precision_at_5
      value: 10.333
    - type: recall_at_1
      value: 30.721999999999998
    - type: recall_at_10
      value: 52.722
    - type: recall_at_100
      value: 80.417
    - type: recall_at_1000
      value: 95.8
    - type: recall_at_3
      value: 40.306
    - type: recall_at_5
      value: 47.083000000000006
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.63564356435643
    - type: cos_sim_ap
      value: 87.3180475245355
    - type: cos_sim_f1
      value: 80.3125
    - type: cos_sim_precision
      value: 83.80434782608695
    - type: cos_sim_recall
      value: 77.10000000000001
    - type: dot_accuracy
      value: 99.63564356435643
    - type: dot_ap
      value: 87.3180475245355
    - type: dot_f1
      value: 80.3125
    - type: dot_precision
      value: 83.80434782608695
    - type: dot_recall
      value: 77.10000000000001
    - type: euclidean_accuracy
      value: 99.63564356435643
    - type: euclidean_ap
      value: 87.3180475245355
    - type: euclidean_f1
      value: 80.3125
    - type: euclidean_precision
      value: 83.80434782608695
    - type: euclidean_recall
      value: 77.10000000000001
    - type: manhattan_accuracy
      value: 99.69504950495049
    - type: manhattan_ap
      value: 90.59998550104231
    - type: manhattan_f1
      value: 83.91462779802187
    - type: manhattan_precision
      value: 87.51357220412595
    - type: manhattan_recall
      value: 80.60000000000001
    - type: max_accuracy
      value: 99.69504950495049
    - type: max_ap
      value: 90.59998550104231
    - type: max_f1
      value: 83.91462779802187
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 32.31610507058257
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.125242344875502
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.09273403724595
    - type: mrr
      value: 43.54354999575587
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.14375732010076
    - type: cos_sim_spearman
      value: 29.565975101655656
    - type: dot_pearson
      value: 30.14375735419279
    - type: dot_spearman
      value: 29.497714274949065
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.173
    - type: map_at_10
      value: 8.079
    - type: map_at_100
      value: 13.44
    - type: map_at_1000
      value: 14.985000000000001
    - type: map_at_3
      value: 4.756
    - type: map_at_5
      value: 5.995
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 43.341
    - type: mrr_at_100
      value: 44.192
    - type: mrr_at_1000
      value: 44.192
    - type: mrr_at_3
      value: 40.136
    - type: mrr_at_5
      value: 41.463
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 20.093
    - type: ndcg_at_100
      value: 33.133
    - type: ndcg_at_1000
      value: 44.344
    - type: ndcg_at_3
      value: 25.82
    - type: ndcg_at_5
      value: 22.216
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 17.755000000000003
    - type: precision_at_100
      value: 7.469
    - type: precision_at_1000
      value: 1.465
    - type: precision_at_3
      value: 27.891
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 2.173
    - type: recall_at_10
      value: 12.662999999999998
    - type: recall_at_100
      value: 44.589
    - type: recall_at_1000
      value: 78.997
    - type: recall_at_3
      value: 5.955
    - type: recall_at_5
      value: 7.89
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.899
    - type: ap
      value: 13.50183607213333
    - type: f1
      value: 53.589735425592465
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.74080362195812
    - type: f1
      value: 53.940488490088434
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.38930659623301
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.71580139476664
    - type: cos_sim_ap
      value: 65.75325189939345
    - type: cos_sim_f1
      value: 62.39284383153186
    - type: cos_sim_precision
      value: 58.95750176097676
    - type: cos_sim_recall
      value: 66.25329815303431
    - type: dot_accuracy
      value: 83.71580139476664
    - type: dot_ap
      value: 65.75325189939345
    - type: dot_f1
      value: 62.39284383153186
    - type: dot_precision
      value: 58.95750176097676
    - type: dot_recall
      value: 66.25329815303431
    - type: euclidean_accuracy
      value: 83.71580139476664
    - type: euclidean_ap
      value: 65.75325189939345
    - type: euclidean_f1
      value: 62.39284383153186
    - type: euclidean_precision
      value: 58.95750176097676
    - type: euclidean_recall
      value: 66.25329815303431
    - type: manhattan_accuracy
      value: 83.4714192048638
    - type: manhattan_ap
      value: 64.42014741278865
    - type: manhattan_f1
      value: 60.886814469078175
    - type: manhattan_precision
      value: 54.58158995815899
    - type: manhattan_recall
      value: 68.83905013192611
    - type: max_accuracy
      value: 83.71580139476664
    - type: max_ap
      value: 65.75325189939345
    - type: max_f1
      value: 62.39284383153186
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.46846741956766
    - type: cos_sim_ap
      value: 82.74561195728911
    - type: cos_sim_f1
      value: 74.91745501762196
    - type: cos_sim_precision
      value: 72.29183074389633
    - type: cos_sim_recall
      value: 77.74099168463196
    - type: dot_accuracy
      value: 87.46846741956766
    - type: dot_ap
      value: 82.74561216064899
    - type: dot_f1
      value: 74.91745501762196
    - type: dot_precision
      value: 72.29183074389633
    - type: dot_recall
      value: 77.74099168463196
    - type: euclidean_accuracy
      value: 87.46846741956766
    - type: euclidean_ap
      value: 82.74561227188258
    - type: euclidean_f1
      value: 74.91745501762196
    - type: euclidean_precision
      value: 72.29183074389633
    - type: euclidean_recall
      value: 77.74099168463196
    - type: manhattan_accuracy
      value: 87.4607055536151
    - type: manhattan_ap
      value: 82.82100726504085
    - type: manhattan_f1
      value: 74.95324413753418
    - type: manhattan_precision
      value: 70.329373650108
    - type: manhattan_recall
      value: 80.22790267939637
    - type: max_accuracy
      value: 87.46846741956766
    - type: max_ap
      value: 82.82100726504085
    - type: max_f1
      value: 74.95324413753418
---
