ts model-index region:us
---
tags:
- ts
model-index:
- name: new7
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 90.25373134328359
    - type: ap
      value: 65.16915484773354
    - type: f1
      value: 86.23066728099059
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.974875
    - type: ap
      value: 91.14317344009288
    - type: f1
      value: 93.9685240564202
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 55.77799999999999
    - type: f1
      value: 55.30626203111084
  - task:
      type: Retrieval
    dataset:
      type: arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 28.663
    - type: map_at_10
      value: 43.903
    - type: map_at_100
      value: 44.779
    - type: map_at_1000
      value: 44.799
    - type: map_at_3
      value: 39.486
    - type: map_at_5
      value: 42.199
    - type: mrr_at_1
      value: 28.663
    - type: mrr_at_10
      value: 43.903
    - type: mrr_at_100
      value: 44.779
    - type: mrr_at_1000
      value: 44.799
    - type: mrr_at_3
      value: 39.486
    - type: mrr_at_5
      value: 42.199
    - type: ndcg_at_1
      value: 28.663
    - type: ndcg_at_10
      value: 51.983999999999995
    - type: ndcg_at_100
      value: 55.981
    - type: ndcg_at_1000
      value: 56.474000000000004
    - type: ndcg_at_3
      value: 43.025000000000006
    - type: ndcg_at_5
      value: 47.916
    - type: precision_at_1
      value: 28.663
    - type: precision_at_10
      value: 7.76
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 17.757
    - type: precision_at_5
      value: 13.03
    - type: recall_at_1
      value: 28.663
    - type: recall_at_10
      value: 77.596
    - type: recall_at_100
      value: 95.661
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 53.272
    - type: recall_at_5
      value: 65.149
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 41.06284026514476
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 32.96711301401968
  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 58.05094332005456
    - type: mrr
      value: 70.90808160752759
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 93.67415724859552
    - type: cos_sim_spearman
      value: 93.37019979249912
    - type: euclidean_pearson
      value: 91.767368542047
    - type: euclidean_spearman
      value: 92.75874007684216
    - type: manhattan_pearson
      value: 91.7931347639689
    - type: manhattan_spearman
      value: 92.94428647331738
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 91.6720779220779
    - type: f1
      value: 91.68597413806214
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.160011542775695
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 24.890267612946595
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.52
    - type: map_at_10
      value: 31.905
    - type: map_at_100
      value: 33.146
    - type: map_at_1000
      value: 33.315
    - type: map_at_3
      value: 29.567
    - type: map_at_5
      value: 30.729
    - type: mrr_at_1
      value: 28.469
    - type: mrr_at_10
      value: 37.884
    - type: mrr_at_100
      value: 38.757000000000005
    - type: mrr_at_1000
      value: 38.827
    - type: mrr_at_3
      value: 36.004000000000005
    - type: mrr_at_5
      value: 36.927
    - type: ndcg_at_1
      value: 28.469
    - type: ndcg_at_10
      value: 37.436
    - type: ndcg_at_100
      value: 42.754
    - type: ndcg_at_1000
      value: 45.744
    - type: ndcg_at_3
      value: 34.121
    - type: ndcg_at_5
      value: 35.315000000000005
    - type: precision_at_1
      value: 28.469
    - type: precision_at_10
      value: 7.167
    - type: precision_at_100
      value: 1.24
    - type: precision_at_1000
      value: 0.184
    - type: precision_at_3
      value: 17.072000000000003
    - type: precision_at_5
      value: 11.731
    - type: recall_at_1
      value: 22.52
    - type: recall_at_10
      value: 47.61
    - type: recall_at_100
      value: 70.494
    - type: recall_at_1000
      value: 90.081
    - type: recall_at_3
      value: 37.012
    - type: recall_at_5
      value: 41.053
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.167
    - type: map_at_10
      value: 29.227999999999998
    - type: map_at_100
      value: 30.361
    - type: map_at_1000
      value: 30.483
    - type: map_at_3
      value: 27.046
    - type: map_at_5
      value: 28.253
    - type: mrr_at_1
      value: 27.961999999999996
    - type: mrr_at_10
      value: 34.474
    - type: mrr_at_100
      value: 35.257
    - type: mrr_at_1000
      value: 35.312
    - type: mrr_at_3
      value: 32.633
    - type: mrr_at_5
      value: 33.7
    - type: ndcg_at_1
      value: 27.961999999999996
    - type: ndcg_at_10
      value: 33.800000000000004
    - type: ndcg_at_100
      value: 38.435
    - type: ndcg_at_1000
      value: 40.753
    - type: ndcg_at_3
      value: 30.584
    - type: ndcg_at_5
      value: 32.036
    - type: precision_at_1
      value: 27.961999999999996
    - type: precision_at_10
      value: 6.338000000000001
    - type: precision_at_100
      value: 1.127
    - type: precision_at_1000
      value: 0.159
    - type: precision_at_3
      value: 14.649999999999999
    - type: precision_at_5
      value: 10.408000000000001
    - type: recall_at_1
      value: 22.167
    - type: recall_at_10
      value: 41.735
    - type: recall_at_100
      value: 61.612
    - type: recall_at_1000
      value: 77.046
    - type: recall_at_3
      value: 31.985000000000003
    - type: recall_at_5
      value: 36.216
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 28.88
    - type: map_at_10
      value: 39.483000000000004
    - type: map_at_100
      value: 40.65
    - type: map_at_1000
      value: 40.727000000000004
    - type: map_at_3
      value: 36.095
    - type: map_at_5
      value: 38.138
    - type: mrr_at_1
      value: 33.292
    - type: mrr_at_10
      value: 42.655
    - type: mrr_at_100
      value: 43.505
    - type: mrr_at_1000
      value: 43.555
    - type: mrr_at_3
      value: 39.634
    - type: mrr_at_5
      value: 41.589999999999996
    - type: ndcg_at_1
      value: 33.292
    - type: ndcg_at_10
      value: 45.216
    - type: ndcg_at_100
      value: 50.029999999999994
    - type: ndcg_at_1000
      value: 51.795
    - type: ndcg_at_3
      value: 39.184000000000005
    - type: ndcg_at_5
      value: 42.416
    - type: precision_at_1
      value: 33.292
    - type: precision_at_10
      value: 7.661
    - type: precision_at_100
      value: 1.089
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 17.701
    - type: precision_at_5
      value: 12.878
    - type: recall_at_1
      value: 28.88
    - type: recall_at_10
      value: 59.148
    - type: recall_at_100
      value: 80.10300000000001
    - type: recall_at_1000
      value: 92.938
    - type: recall_at_3
      value: 43.262
    - type: recall_at_5
      value: 51.05800000000001
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.732
    - type: map_at_10
      value: 24.104999999999997
    - type: map_at_100
      value: 25.085
    - type: map_at_1000
      value: 25.180000000000003
    - type: map_at_3
      value: 21.826999999999998
    - type: map_at_5
      value: 22.988
    - type: mrr_at_1
      value: 19.209
    - type: mrr_at_10
      value: 25.528000000000002
    - type: mrr_at_100
      value: 26.477
    - type: mrr_at_1000
      value: 26.56
    - type: mrr_at_3
      value: 23.315
    - type: mrr_at_5
      value: 24.427
    - type: ndcg_at_1
      value: 19.209
    - type: ndcg_at_10
      value: 28.055000000000003
    - type: ndcg_at_100
      value: 33.357
    - type: ndcg_at_1000
      value: 35.996
    - type: ndcg_at_3
      value: 23.526
    - type: ndcg_at_5
      value: 25.471
    - type: precision_at_1
      value: 19.209
    - type: precision_at_10
      value: 4.463
    - type: precision_at_100
      value: 0.756
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 9.981
    - type: precision_at_5
      value: 7.119000000000001
    - type: recall_at_1
      value: 17.732
    - type: recall_at_10
      value: 39.086999999999996
    - type: recall_at_100
      value: 64.264
    - type: recall_at_1000
      value: 84.589
    - type: recall_at_3
      value: 26.668999999999997
    - type: recall_at_5
      value: 31.361
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.99
    - type: map_at_10
      value: 16.661
    - type: map_at_100
      value: 17.763
    - type: map_at_1000
      value: 17.892
    - type: map_at_3
      value: 14.813
    - type: map_at_5
      value: 15.678
    - type: mrr_at_1
      value: 13.930000000000001
    - type: mrr_at_10
      value: 20.25
    - type: mrr_at_100
      value: 21.233
    - type: mrr_at_1000
      value: 21.325
    - type: mrr_at_3
      value: 18.262999999999998
    - type: mrr_at_5
      value: 19.177
    - type: ndcg_at_1
      value: 13.930000000000001
    - type: ndcg_at_10
      value: 20.558
    - type: ndcg_at_100
      value: 26.137
    - type: ndcg_at_1000
      value: 29.54
    - type: ndcg_at_3
      value: 17.015
    - type: ndcg_at_5
      value: 18.314
    - type: precision_at_1
      value: 13.930000000000001
    - type: precision_at_10
      value: 3.9050000000000002
    - type: precision_at_100
      value: 0.782
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 8.333
    - type: precision_at_5
      value: 5.92
    - type: recall_at_1
      value: 10.99
    - type: recall_at_10
      value: 29.156
    - type: recall_at_100
      value: 54.06100000000001
    - type: recall_at_1000
      value: 78.69699999999999
    - type: recall_at_3
      value: 19.11
    - type: recall_at_5
      value: 22.609
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 21.351
    - type: map_at_10
      value: 29.961
    - type: map_at_100
      value: 31.214
    - type: map_at_1000
      value: 31.349
    - type: map_at_3
      value: 27.283
    - type: map_at_5
      value: 28.851
    - type: mrr_at_1
      value: 25.602000000000004
    - type: mrr_at_10
      value: 34.554
    - type: mrr_at_100
      value: 35.423
    - type: mrr_at_1000
      value: 35.492000000000004
    - type: mrr_at_3
      value: 31.97
    - type: mrr_at_5
      value: 33.399
    - type: ndcg_at_1
      value: 25.602000000000004
    - type: ndcg_at_10
      value: 35.339999999999996
    - type: ndcg_at_100
      value: 40.89
    - type: ndcg_at_1000
      value: 43.732
    - type: ndcg_at_3
      value: 30.657
    - type: ndcg_at_5
      value: 32.945
    - type: precision_at_1
      value: 25.602000000000004
    - type: precision_at_10
      value: 6.574000000000001
    - type: precision_at_100
      value: 1.095
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 14.629
    - type: precision_at_5
      value: 10.645
    - type: recall_at_1
      value: 21.351
    - type: recall_at_10
      value: 46.754
    - type: recall_at_100
      value: 70.247
    - type: recall_at_1000
      value: 89.653
    - type: recall_at_3
      value: 33.894000000000005
    - type: recall_at_5
      value: 39.667
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.052999999999997
    - type: map_at_10
      value: 24.291999999999998
    - type: map_at_100
      value: 25.348
    - type: map_at_1000
      value: 25.487
    - type: map_at_3
      value: 21.922
    - type: map_at_5
      value: 23.256
    - type: mrr_at_1
      value: 20.776
    - type: mrr_at_10
      value: 28.17
    - type: mrr_at_100
      value: 28.99
    - type: mrr_at_1000
      value: 29.082
    - type: mrr_at_3
      value: 25.951
    - type: mrr_at_5
      value: 27.241
    - type: ndcg_at_1
      value: 20.776
    - type: ndcg_at_10
      value: 28.909000000000002
    - type: ndcg_at_100
      value: 33.917
    - type: ndcg_at_1000
      value: 37.173
    - type: ndcg_at_3
      value: 24.769
    - type: ndcg_at_5
      value: 26.698
    - type: precision_at_1
      value: 20.776
    - type: precision_at_10
      value: 5.445
    - type: precision_at_100
      value: 0.943
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.985999999999999
    - type: precision_at_5
      value: 8.699
    - type: recall_at_1
      value: 17.052999999999997
    - type: recall_at_10
      value: 38.922000000000004
    - type: recall_at_100
      value: 60.624
    - type: recall_at_1000
      value: 83.83
    - type: recall_at_3
      value: 27.35
    - type: recall_at_5
      value: 32.513999999999996
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.981
    - type: map_at_10
      value: 24.99583333333333
    - type: map_at_100
      value: 26.054083333333335
    - type: map_at_1000
      value: 26.180916666666672
    - type: map_at_3
      value: 22.802666666666667
    - type: map_at_5
      value: 24.00508333333333
    - type: mrr_at_1
      value: 21.373916666666666
    - type: mrr_at_10
      value: 28.53433333333333
    - type: mrr_at_100
      value: 29.404000000000003
    - type: mrr_at_1000
      value: 29.481999999999996
    - type: mrr_at_3
      value: 26.462999999999997
    - type: mrr_at_5
      value: 27.596083333333333
    - type: ndcg_at_1
      value: 21.373916666666666
    - type: ndcg_at_10
      value: 29.40908333333333
    - type: ndcg_at_100
      value: 34.43266666666666
    - type: ndcg_at_1000
      value: 37.334916666666665
    - type: ndcg_at_3
      value: 25.518250000000002
    - type: ndcg_at_5
      value: 27.286916666666666
    - type: precision_at_1
      value: 21.373916666666666
    - type: precision_at_10
      value: 5.265666666666667
    - type: precision_at_100
      value: 0.9175833333333334
    - type: precision_at_1000
      value: 0.13533333333333336
    - type: precision_at_3
      value: 11.92425
    - type: precision_at_5
      value: 8.532250000000001
    - type: recall_at_1
      value: 17.981
    - type: recall_at_10
      value: 39.14641666666667
    - type: recall_at_100
      value: 61.65433333333334
    - type: recall_at_1000
      value: 82.39216666666665
    - type: recall_at_3
      value: 28.15266666666667
    - type: recall_at_5
      value: 32.795
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 16.834
    - type: map_at_10
      value: 22.046
    - type: map_at_100
      value: 22.954
    - type: map_at_1000
      value: 23.051
    - type: map_at_3
      value: 20.602999999999998
    - type: map_at_5
      value: 21.387999999999998
    - type: mrr_at_1
      value: 19.172
    - type: mrr_at_10
      value: 24.558
    - type: mrr_at_100
      value: 25.439
    - type: mrr_at_1000
      value: 25.509999999999998
    - type: mrr_at_3
      value: 23.185
    - type: mrr_at_5
      value: 23.852
    - type: ndcg_at_1
      value: 19.172
    - type: ndcg_at_10
      value: 25.189
    - type: ndcg_at_100
      value: 29.918
    - type: ndcg_at_1000
      value: 32.677
    - type: ndcg_at_3
      value: 22.496
    - type: ndcg_at_5
      value: 23.677
    - type: precision_at_1
      value: 19.172
    - type: precision_at_10
      value: 3.834
    - type: precision_at_100
      value: 0.679
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 9.611
    - type: precision_at_5
      value: 6.4719999999999995
    - type: recall_at_1
      value: 16.834
    - type: recall_at_10
      value: 32.554
    - type: recall_at_100
      value: 54.416
    - type: recall_at_1000
      value: 75.334
    - type: recall_at_3
      value: 25.057000000000002
    - type: recall_at_5
      value: 28.155
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.778
    - type: map_at_10
      value: 15.885
    - type: map_at_100
      value: 16.716
    - type: map_at_1000
      value: 16.838
    - type: map_at_3
      value: 14.283999999999999
    - type: map_at_5
      value: 15.067
    - type: mrr_at_1
      value: 13.421
    - type: mrr_at_10
      value: 19.022
    - type: mrr_at_100
      value: 19.819
    - type: mrr_at_1000
      value: 19.912
    - type: mrr_at_3
      value: 17.366
    - type: mrr_at_5
      value: 18.18
    - type: ndcg_at_1
      value: 13.421
    - type: ndcg_at_10
      value: 19.375
    - type: ndcg_at_100
      value: 23.733999999999998
    - type: ndcg_at_1000
      value: 26.878
    - type: ndcg_at_3
      value: 16.383
    - type: ndcg_at_5
      value: 17.53
    - type: precision_at_1
      value: 13.421
    - type: precision_at_10
      value: 3.637
    - type: precision_at_100
      value: 0.681
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 7.983
    - type: precision_at_5
      value: 5.671
    - type: recall_at_1
      value: 10.778
    - type: recall_at_10
      value: 26.985999999999997
    - type: recall_at_100
      value: 47.143
    - type: recall_at_1000
      value: 69.842
    - type: recall_at_3
      value: 18.289
    - type: recall_at_5
      value: 21.459
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.077
    - type: map_at_10
      value: 23.31
    - type: map_at_100
      value: 24.351
    - type: map_at_1000
      value: 24.471
    - type: map_at_3
      value: 21.272
    - type: map_at_5
      value: 22.320999999999998
    - type: mrr_at_1
      value: 19.683
    - type: mrr_at_10
      value: 26.44
    - type: mrr_at_100
      value: 27.395000000000003
    - type: mrr_at_1000
      value: 27.479
    - type: mrr_at_3
      value: 24.549000000000003
    - type: mrr_at_5
      value: 25.477
    - type: ndcg_at_1
      value: 19.683
    - type: ndcg_at_10
      value: 27.33
    - type: ndcg_at_100
      value: 32.595
    - type: ndcg_at_1000
      value: 35.671
    - type: ndcg_at_3
      value: 23.536
    - type: ndcg_at_5
      value: 25.09
    - type: precision_at_1
      value: 19.683
    - type: precision_at_10
      value: 4.711
    - type: precision_at_100
      value: 0.84
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 10.697
    - type: precision_at_5
      value: 7.5
    - type: recall_at_1
      value: 17.077
    - type: recall_at_10
      value: 36.532
    - type: recall_at_100
      value: 59.955999999999996
    - type: recall_at_1000
      value: 82.536
    - type: recall_at_3
      value: 25.982
    - type: recall_at_5
      value: 29.965999999999998
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.137
    - type: map_at_10
      value: 23.889
    - type: map_at_100
      value: 25.089
    - type: map_at_1000
      value: 25.284000000000002
    - type: map_at_3
      value: 21.844
    - type: map_at_5
      value: 23.185
    - type: mrr_at_1
      value: 20.552999999999997
    - type: mrr_at_10
      value: 27.996
    - type: mrr_at_100
      value: 28.921000000000003
    - type: mrr_at_1000
      value: 28.999999999999996
    - type: mrr_at_3
      value: 25.955000000000002
    - type: mrr_at_5
      value: 27.269
    - type: ndcg_at_1
      value: 20.552999999999997
    - type: ndcg_at_10
      value: 28.555000000000003
    - type: ndcg_at_100
      value: 34.035
    - type: ndcg_at_1000
      value: 37.466
    - type: ndcg_at_3
      value: 25.105
    - type: ndcg_at_5
      value: 27.13
    - type: precision_at_1
      value: 20.552999999999997
    - type: precision_at_10
      value: 5.534
    - type: precision_at_100
      value: 1.117
    - type: precision_at_1000
      value: 0.20400000000000001
    - type: precision_at_3
      value: 12.253
    - type: precision_at_5
      value: 9.17
    - type: recall_at_1
      value: 17.137
    - type: recall_at_10
      value: 37.527
    - type: recall_at_100
      value: 62.905
    - type: recall_at_1000
      value: 85.839
    - type: recall_at_3
      value: 27.262999999999998
    - type: recall_at_5
      value: 32.735
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 13.253
    - type: map_at_10
      value: 19.185
    - type: map_at_100
      value: 19.972
    - type: map_at_1000
      value: 20.094
    - type: map_at_3
      value: 17.076
    - type: map_at_5
      value: 18.207
    - type: mrr_at_1
      value: 14.418000000000001
    - type: mrr_at_10
      value: 20.881
    - type: mrr_at_100
      value: 21.632
    - type: mrr_at_1000
      value: 21.73
    - type: mrr_at_3
      value: 18.731
    - type: mrr_at_5
      value: 19.914
    - type: ndcg_at_1
      value: 14.418000000000001
    - type: ndcg_at_10
      value: 23.146
    - type: ndcg_at_100
      value: 27.389999999999997
    - type: ndcg_at_1000
      value: 30.593999999999998
    - type: ndcg_at_3
      value: 18.843
    - type: ndcg_at_5
      value: 20.821
    - type: precision_at_1
      value: 14.418000000000001
    - type: precision_at_10
      value: 3.9190000000000005
    - type: precision_at_100
      value: 0.662
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 8.195
    - type: precision_at_5
      value: 6.174
    - type: recall_at_1
      value: 13.253
    - type: recall_at_10
      value: 33.745999999999995
    - type: recall_at_100
      value: 54.027
    - type: recall_at_1000
      value: 78.321
    - type: recall_at_3
      value: 21.959
    - type: recall_at_5
      value: 26.747
  - task:
      type: Retrieval
    dataset:
      type: climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: ndcg_at_1
      value: 9.446
    - type: ndcg_at_3
      value: 8.708
    - type: ndcg_at_5
      value: 9.583
    - type: ndcg_at_10
      value: 11.324
    - type: ndcg_at_100
      value: 16.563
    - type: ndcg_at_1000
      value: 20.402
    - type: map_at_1
      value: 4.407
    - type: map_at_3
      value: 6.283999999999999
    - type: map_at_5
      value: 6.888
    - type: map_at_10
      value: 7.545
    - type: map_at_100
      value: 8.502
    - type: map_at_1000
      value: 8.677
    - type: recall_at_1
      value: 4.407
    - type: recall_at_3
      value: 8.341999999999999
    - type: recall_at_5
      value: 10.609
    - type: recall_at_10
      value: 14.572
    - type: recall_at_100
      value: 33.802
    - type: recall_at_1000
      value: 56.13
    - type: precision_at_1
      value: 9.446
    - type: precision_at_3
      value: 6.3839999999999995
    - type: precision_at_5
      value: 5.029
    - type: precision_at_10
      value: 3.655
    - type: precision_at_100
      value: 0.9169999999999999
    - type: precision_at_1000
      value: 0.159
    - type: mrr_at_1
      value: 9.446
    - type: mrr_at_3
      value: 12.975
    - type: mrr_at_5
      value: 14.102
    - type: mrr_at_10
      value: 15.223999999999998
    - type: mrr_at_100
      value: 16.378
    - type: mrr_at_1000
      value: 16.469
  - task:
      type: Retrieval
    dataset:
      type: dbpedia-entity
      name: MTEB DBPedia
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.3839999999999995
    - type: map_at_10
      value: 8.92
    - type: map_at_100
      value: 12.509999999999998
    - type: map_at_1000
      value: 13.555
    - type: map_at_3
      value: 6.508
    - type: map_at_5
      value: 7.521
    - type: mrr_at_1
      value: 38.0
    - type: mrr_at_10
      value: 47.796
    - type: mrr_at_100
      value: 48.554
    - type: mrr_at_1000
      value: 48.579
    - type: mrr_at_3
      value: 44.708
    - type: mrr_at_5
      value: 46.521
    - type: ndcg_at_1
      value: 29.125
    - type: ndcg_at_10
      value: 22.126
    - type: ndcg_at_100
      value: 26.369999999999997
    - type: ndcg_at_1000
      value: 33.604
    - type: ndcg_at_3
      value: 24.102999999999998
    - type: ndcg_at_5
      value: 22.926
    - type: precision_at_1
      value: 38.0
    - type: precision_at_10
      value: 18.2
    - type: precision_at_100
      value: 6.208
    - type: precision_at_1000
      value: 1.3679999999999999
    - type: precision_at_3
      value: 26.5
    - type: precision_at_5
      value: 22.900000000000002
    - type: recall_at_1
      value: 4.3839999999999995
    - type: recall_at_10
      value: 13.520999999999999
    - type: recall_at_100
      value: 33.053
    - type: recall_at_1000
      value: 56.516
    - type: recall_at_3
      value: 7.515
    - type: recall_at_5
      value: 9.775
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 90.38999999999999
    - type: f1
      value: 87.12778738994012
  - task:
      type: Retrieval
    dataset:
      type: fever
      name: MTEB FEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.132
    - type: map_at_10
      value: 79.527
    - type: map_at_100
      value: 79.81200000000001
    - type: map_at_1000
      value: 79.828
    - type: map_at_3
      value: 78.191
    - type: map_at_5
      value: 79.092
    - type: mrr_at_1
      value: 75.563
    - type: mrr_at_10
      value: 83.80199999999999
    - type: mrr_at_100
      value: 83.93
    - type: mrr_at_1000
      value: 83.933
    - type: mrr_at_3
      value: 82.818
    - type: mrr_at_5
      value: 83.505
    - type: ndcg_at_1
      value: 75.563
    - type: ndcg_at_10
      value: 83.692
    - type: ndcg_at_100
      value: 84.706
    - type: ndcg_at_1000
      value: 85.001
    - type: ndcg_at_3
      value: 81.51
    - type: ndcg_at_5
      value: 82.832
    - type: precision_at_1
      value: 75.563
    - type: precision_at_10
      value: 10.245
    - type: precision_at_100
      value: 1.0959999999999999
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 31.518
    - type: precision_at_5
      value: 19.772000000000002
    - type: recall_at_1
      value: 70.132
    - type: recall_at_10
      value: 92.204
    - type: recall_at_100
      value: 96.261
    - type: recall_at_1000
      value: 98.17399999999999
    - type: recall_at_3
      value: 86.288
    - type: recall_at_5
      value: 89.63799999999999
  - task:
      type: Retrieval
    dataset:
      type: fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.688000000000001
    - type: map_at_10
      value: 13.839000000000002
    - type: map_at_100
      value: 15.082999999999998
    - type: map_at_1000
      value: 15.276
    - type: map_at_3
      value: 11.662
    - type: map_at_5
      value: 12.827
    - type: mrr_at_1
      value: 15.741
    - type: mrr_at_10
      value: 23.304
    - type: mrr_at_100
      value: 24.239
    - type: mrr_at_1000
      value: 24.319
    - type: mrr_at_3
      value: 20.962
    - type: mrr_at_5
      value: 22.243
    - type: ndcg_at_1
      value: 15.741
    - type: ndcg_at_10
      value: 18.914
    - type: ndcg_at_100
      value: 24.742
    - type: ndcg_at_1000
      value: 28.938000000000002
    - type: ndcg_at_3
      value: 16.181
    - type: ndcg_at_5
      value: 17.078
    - type: precision_at_1
      value: 15.741
    - type: precision_at_10
      value: 5.7410000000000005
    - type: precision_at_100
      value: 1.168
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 11.368
    - type: precision_at_5
      value: 8.735
    - type: recall_at_1
      value: 7.688000000000001
    - type: recall_at_10
      value: 24.442
    - type: recall_at_100
      value: 47.288999999999994
    - type: recall_at_1000
      value: 73.49900000000001
    - type: recall_at_3
      value: 15.15
    - type: recall_at_5
      value: 18.858
  - task:
      type: Retrieval
    dataset:
      type: hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.412
    - type: map_at_10
      value: 66.376
    - type: map_at_100
      value: 67.217
    - type: map_at_1000
      value: 67.271
    - type: map_at_3
      value: 62.741
    - type: map_at_5
      value: 65.069
    - type: mrr_at_1
      value: 80.824
    - type: mrr_at_10
      value: 86.53
    - type: mrr_at_100
      value: 86.67399999999999
    - type: mrr_at_1000
      value: 86.678
    - type: mrr_at_3
      value: 85.676
    - type: mrr_at_5
      value: 86.256
    - type: ndcg_at_1
      value: 80.824
    - type: ndcg_at_10
      value: 74.332
    - type: ndcg_at_100
      value: 77.154
    - type: ndcg_at_1000
      value: 78.12400000000001
    - type: ndcg_at_3
      value: 69.353
    - type: ndcg_at_5
      value: 72.234
    - type: precision_at_1
      value: 80.824
    - type: precision_at_10
      value: 15.652
    - type: precision_at_100
      value: 1.7840000000000003
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 44.911
    - type: precision_at_5
      value: 29.221000000000004
    - type: recall_at_1
      value: 40.412
    - type: recall_at_10
      value: 78.25800000000001
    - type: recall_at_100
      value: 89.196
    - type: recall_at_1000
      value: 95.544
    - type: recall_at_3
      value: 67.367
    - type: recall_at_5
      value: 73.05199999999999
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 88.8228
    - type: ap
      value: 84.52103126779862
    - type: f1
      value: 88.797782219813
  - task:
      type: Retrieval
    dataset:
      type: msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 8.461
    - type: map_at_10
      value: 14.979999999999999
    - type: map_at_100
      value: 16.032
    - type: map_at_1000
      value: 16.128
    - type: map_at_3
      value: 12.64
    - type: map_at_5
      value: 13.914000000000001
    - type: mrr_at_1
      value: 8.681999999999999
    - type: mrr_at_10
      value: 15.341
    - type: mrr_at_100
      value: 16.377
    - type: mrr_at_1000
      value: 16.469
    - type: mrr_at_3
      value: 12.963
    - type: mrr_at_5
      value: 14.262
    - type: ndcg_at_1
      value: 8.681999999999999
    - type: ndcg_at_10
      value: 19.045
    - type: ndcg_at_100
      value: 24.735
    - type: ndcg_at_1000
      value: 27.556000000000004
    - type: ndcg_at_3
      value: 14.154
    - type: ndcg_at_5
      value: 16.448
    - type: precision_at_1
      value: 8.681999999999999
    - type: precision_at_10
      value: 3.292
    - type: precision_at_100
      value: 0.623
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.275
    - type: precision_at_5
      value: 4.92
    - type: recall_at_1
      value: 8.461
    - type: recall_at_10
      value: 31.729000000000003
    - type: recall_at_100
      value: 59.367000000000004
    - type: recall_at_1000
      value: 81.86
    - type: recall_at_3
      value: 18.234
    - type: recall_at_5
      value: 23.74
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 98.1623347013224
    - type: f1
      value: 97.95934123221338
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 93.0141358869129
    - type: f1
      value: 77.42161481798763
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 77.20242098184264
    - type: f1
      value: 73.64580701123289
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 88.38264963012777
    - type: f1
      value: 87.6445935642575
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.982276213044095
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.08731318128303
  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.680164236394784
    - type: mrr
      value: 30.60242075910688
  - task:
      type: Retrieval
    dataset:
      type: nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.35
    - type: map_at_10
      value: 10.03
    - type: map_at_100
      value: 12.61
    - type: map_at_1000
      value: 13.916999999999998
    - type: map_at_3
      value: 7.428
    - type: map_at_5
      value: 8.625
    - type: mrr_at_1
      value: 39.009
    - type: mrr_at_10
      value: 47.63
    - type: mrr_at_100
      value: 48.259
    - type: mrr_at_1000
      value: 48.302
    - type: mrr_at_3
      value: 45.408
    - type: mrr_at_5
      value: 46.971000000000004
    - type: ndcg_at_1
      value: 36.997
    - type: ndcg_at_10
      value: 28.781000000000002
    - type: ndcg_at_100
      value: 26.644000000000002
    - type: ndcg_at_1000
      value: 35.812
    - type: ndcg_at_3
      value: 34.056
    - type: ndcg_at_5
      value: 31.804
    - type: precision_at_1
      value: 38.080000000000005
    - type: precision_at_10
      value: 20.96
    - type: precision_at_100
      value: 6.808
    - type: precision_at_1000
      value: 1.991
    - type: precision_at_3
      value: 32.095
    - type: precision_at_5
      value: 27.43
    - type: recall_at_1
      value: 4.35
    - type: recall_at_10
      value: 14.396
    - type: recall_at_100
      value: 28.126
    - type: recall_at_1000
      value: 60.785
    - type: recall_at_3
      value: 9.001000000000001
    - type: recall_at_5
      value: 11.197
  - task:
      type: Retrieval
    dataset:
      type: nq
      name: MTEB NQ
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.408
    - type: map_at_10
      value: 17.247
    - type: map_at_100
      value: 18.578
    - type: map_at_1000
      value: 18.683
    - type: map_at_3
      value: 14.424999999999999
    - type: map_at_5
      value: 15.967999999999998
    - type: mrr_at_1
      value: 10.718
    - type: mrr_at_10
      value: 18.974
    - type: mrr_at_100
      value: 20.153
    - type: mrr_at_1000
      value: 20.238
    - type: mrr_at_3
      value: 16.087
    - type: mrr_at_5
      value: 17.685000000000002
    - type: ndcg_at_1
      value: 10.718
    - type: ndcg_at_10
      value: 22.313
    - type: ndcg_at_100
      value: 28.810999999999996
    - type: ndcg_at_1000
      value: 31.495
    - type: ndcg_at_3
      value: 16.487
    - type: ndcg_at_5
      value: 19.252
    - type: precision_at_1
      value: 10.718
    - type: precision_at_10
      value: 4.256
    - type: precision_at_100
      value: 0.7979999999999999
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 7.976
    - type: precision_at_5
      value: 6.3149999999999995
    - type: recall_at_1
      value: 9.408
    - type: recall_at_10
      value: 36.364999999999995
    - type: recall_at_100
      value: 66.16499999999999
    - type: recall_at_1000
      value: 86.47399999999999
    - type: recall_at_3
      value: 20.829
    - type: recall_at_5
      value: 27.296
  - task:
      type: Retrieval
    dataset:
      type: quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 65.499
    - type: map_at_10
      value: 78.432
    - type: map_at_100
      value: 79.169
    - type: map_at_1000
      value: 79.199
    - type: map_at_3
      value: 75.476
    - type: map_at_5
      value: 77.28399999999999
    - type: mrr_at_1
      value: 75.55
    - type: mrr_at_10
      value: 82.16499999999999
    - type: mrr_at_100
      value: 82.37
    - type: mrr_at_1000
      value: 82.375
    - type: mrr_at_3
      value: 80.925
    - type: mrr_at_5
      value: 81.748
    - type: ndcg_at_1
      value: 75.58
    - type: ndcg_at_10
      value: 82.663
    - type: ndcg_at_100
      value: 84.526
    - type: ndcg_at_1000
      value: 84.843
    - type: ndcg_at_3
      value: 79.38300000000001
    - type: ndcg_at_5
      value: 81.133
    - type: precision_at_1
      value: 75.58
    - type: precision_at_10
      value: 12.562000000000001
    - type: precision_at_100
      value: 1.48
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 34.583000000000006
    - type: precision_at_5
      value: 22.858
    - type: recall_at_1
      value: 65.499
    - type: recall_at_10
      value: 90.71000000000001
    - type: recall_at_100
      value: 97.717
    - type: recall_at_1000
      value: 99.551
    - type: recall_at_3
      value: 81.273
    - type: recall_at_5
      value: 86.172
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.28689524907211
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 54.41734813535957
  - task:
      type: Retrieval
    dataset:
      type: scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.305
    - type: map_at_10
      value: 8.502
    - type: map_at_100
      value: 10.288
    - type: map_at_1000
      value: 10.599
    - type: map_at_3
      value: 6.146
    - type: map_at_5
      value: 7.207
    - type: mrr_at_1
      value: 16.400000000000002
    - type: mrr_at_10
      value: 26.054
    - type: mrr_at_100
      value: 27.319
    - type: mrr_at_1000
      value: 27.400000000000002
    - type: mrr_at_3
      value: 22.967000000000002
    - type: mrr_at_5
      value: 24.542
    - type: ndcg_at_1
      value: 16.400000000000002
    - type: ndcg_at_10
      value: 14.943000000000001
    - type: ndcg_at_100
      value: 22.596
    - type: ndcg_at_1000
      value: 28.345
    - type: ndcg_at_3
      value: 14.011000000000001
    - type: ndcg_at_5
      value: 12.065
    - type: precision_at_1
      value: 16.400000000000002
    - type: precision_at_10
      value: 7.93
    - type: precision_at_100
      value: 1.902
    - type: precision_at_1000
      value: 0.328
    - type: precision_at_3
      value: 13.233
    - type: precision_at_5
      value: 10.620000000000001
    - type: recall_at_1
      value: 3.305
    - type: recall_at_10
      value: 16.07
    - type: recall_at_100
      value: 38.592999999999996
    - type: recall_at_1000
      value: 66.678
    - type: recall_at_3
      value: 8.025
    - type: recall_at_5
      value: 10.743
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 94.03602783680165
    - type: cos_sim_spearman
      value: 91.93466287712853
    - type: euclidean_pearson
      value: 91.5804659261222
    - type: euclidean_spearman
      value: 91.84239224991634
    - type: manhattan_pearson
      value: 91.57789872896991
    - type: manhattan_spearman
      value: 91.82031929038708
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 97.2530615783017
    - type: cos_sim_spearman
      value: 95.61025838976805
    - type: euclidean_pearson
      value: 95.41071037458771
    - type: euclidean_spearman
      value: 95.6207550803838
    - type: manhattan_pearson
      value: 95.39723545188045
    - type: manhattan_spearman
      value: 95.61540593501014
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 95.27491458980685
    - type: cos_sim_spearman
      value: 95.1521844663505
    - type: euclidean_pearson
      value: 94.63883752108002
    - type: euclidean_spearman
      value: 94.85954995945424
    - type: manhattan_pearson
      value: 94.59749433419627
    - type: manhattan_spearman
      value: 94.80626857571967
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 97.10518525877228
    - type: cos_sim_spearman
      value: 96.85836209648471
    - type: euclidean_pearson
      value: 95.8019730340664
    - type: euclidean_spearman
      value: 96.78892865690494
    - type: manhattan_pearson
      value: 95.79265816494754
    - type: manhattan_spearman
      value: 96.7712534155723
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 96.66550105336606
    - type: cos_sim_spearman
      value: 96.73134982392861
    - type: euclidean_pearson
      value: 95.50375963201927
    - type: euclidean_spearman
      value: 96.46785996403956
    - type: manhattan_pearson
      value: 95.47555707089327
    - type: manhattan_spearman
      value: 96.40825860300748
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 96.07365154052914
    - type: cos_sim_spearman
      value: 96.1720485037732
    - type: euclidean_pearson
      value: 95.58880196128803
    - type: euclidean_spearman
      value: 96.02102007396296
    - type: manhattan_pearson
      value: 95.60295336628664
    - type: manhattan_spearman
      value: 96.03461694944212
  - task:
      type: STS
    dataset:
      type: mteb/sts17-crosslingual-sts
      name: MTEB STS17 (en-en)
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 96.14907313714893
    - type: cos_sim_spearman
      value: 96.14822520805113
    - type: euclidean_pearson
      value: 95.62140726773103
    - type: euclidean_spearman
      value: 96.01818385482282
    - type: manhattan_pearson
      value: 95.60795162280982
    - type: manhattan_spearman
      value: 96.00703635484169
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (en)
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 66.35513203366195
    - type: cos_sim_spearman
      value: 64.92002333937089
    - type: euclidean_pearson
      value: 67.06304516009153
    - type: euclidean_spearman
      value: 65.3504536039936
    - type: manhattan_pearson
      value: 67.22016756598737
    - type: manhattan_spearman
      value: 65.64455991383844
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 96.59372149477922
    - type: cos_sim_spearman
      value: 96.97247348665515
    - type: euclidean_pearson
      value: 95.64890160850817
    - type: euclidean_spearman
      value: 96.84619618958573
    - type: manhattan_pearson
      value: 95.65581449537562
    - type: manhattan_spearman
      value: 96.853383309355
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.9991957697061
    - type: mrr
      value: 93.85864317236866
  - task:
      type: Retrieval
    dataset:
      type: scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 42.25
    - type: map_at_10
      value: 51.257
    - type: map_at_100
      value: 52.261
    - type: map_at_1000
      value: 52.309000000000005
    - type: map_at_3
      value: 48.759
    - type: map_at_5
      value: 50.413
    - type: mrr_at_1
      value: 44.0
    - type: mrr_at_10
      value: 52.367
    - type: mrr_at_100
      value: 53.181999999999995
    - type: mrr_at_1000
      value: 53.223
    - type: mrr_at_3
      value: 50.222
    - type: mrr_at_5
      value: 51.656
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 55.672
    - type: ndcg_at_100
      value: 59.779
    - type: ndcg_at_1000
      value: 61.114999999999995
    - type: ndcg_at_3
      value: 51.136
    - type: ndcg_at_5
      value: 53.822
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 7.6
    - type: precision_at_100
      value: 0.9730000000000001
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 20.111
    - type: precision_at_5
      value: 13.733
    - type: recall_at_1
      value: 42.25
    - type: recall_at_10
      value: 67.989
    - type: recall_at_100
      value: 85.56700000000001
    - type: recall_at_1000
      value: 96.267
    - type: recall_at_3
      value: 56.27799999999999
    - type: recall_at_5
      value: 62.678
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.75346534653465
    - type: cos_sim_ap
      value: 92.92934020206276
    - type: cos_sim_f1
      value: 87.37373737373737
    - type: cos_sim_precision
      value: 88.26530612244898
    - type: cos_sim_recall
      value: 86.5
    - type: dot_accuracy
      value: 99.7
    - type: dot_ap
      value: 90.30253078505329
    - type: dot_f1
      value: 84.55696202531644
    - type: dot_precision
      value: 85.64102564102564
    - type: dot_recall
      value: 83.5
    - type: euclidean_accuracy
      value: 99.75742574257426
    - type: euclidean_ap
      value: 92.97542565802068
    - type: euclidean_f1
      value: 87.48083801737351
    - type: euclidean_precision
      value: 89.44618599791013
    - type: euclidean_recall
      value: 85.6
    - type: manhattan_accuracy
      value: 99.75643564356436
    - type: manhattan_ap
      value: 92.92733519229752
    - type: manhattan_f1
      value: 87.41044012282498
    - type: manhattan_precision
      value: 89.51781970649894
    - type: manhattan_recall
      value: 85.39999999999999
    - type: max_accuracy
      value: 99.75742574257426
    - type: max_ap
      value: 92.97542565802068
    - type: max_f1
      value: 87.48083801737351
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 46.968629347107225
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 31.76101811464947
  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 47.838618465936364
    - type: mrr
      value: 48.51134772090654
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.101149949190837
    - type: cos_sim_spearman
      value: 30.99886288816569
    - type: dot_pearson
      value: 28.905040829977978
    - type: dot_spearman
      value: 28.101690957830428
  - task:
      type: Retrieval
    dataset:
      type: trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.129
    - type: map_at_10
      value: 0.6930000000000001
    - type: map_at_100
      value: 2.408
    - type: map_at_1000
      value: 4.731
    - type: map_at_3
      value: 0.314
    - type: map_at_5
      value: 0.43
    - type: mrr_at_1
      value: 44.0
    - type: mrr_at_10
      value: 55.132999999999996
    - type: mrr_at_100
      value: 56.455
    - type: mrr_at_1000
      value: 56.474000000000004
    - type: mrr_at_3
      value: 53.333
    - type: mrr_at_5
      value: 55.132999999999996
    - type: ndcg_at_1
      value: 40.0
    - type: ndcg_at_10
      value: 33.283
    - type: ndcg_at_100
      value: 18.892
    - type: ndcg_at_1000
      value: 17.457
    - type: ndcg_at_3
      value: 39.073
    - type: ndcg_at_5
      value: 35.609
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 33.800000000000004
    - type: precision_at_100
      value: 17.44
    - type: precision_at_1000
      value: 7.04
    - type: precision_at_3
      value: 40.666999999999994
    - type: precision_at_5
      value: 36.4
    - type: recall_at_1
      value: 0.129
    - type: recall_at_10
      value: 0.91
    - type: recall_at_100
      value: 4.449
    - type: recall_at_1000
      value: 16.091
    - type: recall_at_3
      value: 0.349
    - type: recall_at_5
      value: 0.518
  - task:
      type: Retrieval
    dataset:
      type: webis-touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.189
    - type: map_at_10
      value: 5.196
    - type: map_at_100
      value: 8.984
    - type: map_at_1000
      value: 10.333
    - type: map_at_3
      value: 2.513
    - type: map_at_5
      value: 3.8089999999999997
    - type: mrr_at_1
      value: 14.285999999999998
    - type: mrr_at_10
      value: 26.295
    - type: mrr_at_100
      value: 28.285
    - type: mrr_at_1000
      value: 28.303
    - type: mrr_at_3
      value: 22.109
    - type: mrr_at_5
      value: 24.864
    - type: ndcg_at_1
      value: 12.245000000000001
    - type: ndcg_at_10
      value: 13.196
    - type: ndcg_at_100
      value: 24.189
    - type: ndcg_at_1000
      value: 36.015
    - type: ndcg_at_3
      value: 12.153
    - type: ndcg_at_5
      value: 13.459999999999999
    - type: precision_at_1
      value: 14.285999999999998
    - type: precision_at_10
      value: 12.653
    - type: precision_at_100
      value: 5.673
    - type: precision_at_1000
      value: 1.32
    - type: precision_at_3
      value: 12.925
    - type: precision_at_5
      value: 15.101999999999999
    - type: recall_at_1
      value: 1.189
    - type: recall_at_10
      value: 9.478
    - type: recall_at_100
      value: 36.076
    - type: recall_at_1000
      value: 71.88900000000001
    - type: recall_at_3
      value: 3.1710000000000003
    - type: recall_at_5
      value: 5.944
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 81.1632
    - type: ap
      value: 21.801031224655016
    - type: f1
      value: 63.93057804886679
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 68.15789473684211
    - type: f1
      value: 68.55744497973521
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 53.77313771942972
  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 85.79603027954938
    - type: cos_sim_ap
      value: 73.19931192854375
    - type: cos_sim_f1
      value: 66.7699457784663
    - type: cos_sim_precision
      value: 65.3690596562184
    - type: cos_sim_recall
      value: 68.23218997361478
    - type: dot_accuracy
      value: 84.72313286046374
    - type: dot_ap
      value: 69.84066382008972
    - type: dot_f1
      value: 64.42618869803336
    - type: dot_precision
      value: 60.98020735155514
    - type: dot_recall
      value: 68.28496042216359
    - type: euclidean_accuracy
      value: 85.81391190320082
    - type: euclidean_ap
      value: 73.4051677083228
    - type: euclidean_f1
      value: 67.35092864125122
    - type: euclidean_precision
      value: 62.721893491124256
    - type: euclidean_recall
      value: 72.71767810026385
    - type: manhattan_accuracy
      value: 85.81391190320082
    - type: manhattan_ap
      value: 73.33759860950396
    - type: manhattan_f1
      value: 67.32576589771757
    - type: manhattan_precision
      value: 62.63910969793323
    - type: manhattan_recall
      value: 72.77044854881267
    - type: max_accuracy
      value: 85.81391190320082
    - type: max_ap
      value: 73.4051677083228
    - type: max_f1
      value: 67.35092864125122
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.17479722125199
    - type: cos_sim_ap
      value: 84.37486145048878
    - type: cos_sim_f1
      value: 76.65294717365856
    - type: cos_sim_precision
      value: 75.21304186735827
    - type: cos_sim_recall
      value: 78.14906067138897
    - type: dot_accuracy
      value: 87.72460899600264
    - type: dot_ap
      value: 83.01188676406672
    - type: dot_f1
      value: 75.8810775054206
    - type: dot_precision
      value: 72.58665541728186
    - type: dot_recall
      value: 79.48875885432707
    - type: euclidean_accuracy
      value: 88.16315442232313
    - type: euclidean_ap
      value: 84.32021529803454
    - type: euclidean_f1
      value: 76.60147856804691
    - type: euclidean_precision
      value: 72.67638725727316
    - type: euclidean_recall
      value: 80.97474591931014
    - type: manhattan_accuracy
      value: 88.19226141964528
    - type: manhattan_ap
      value: 84.30111334073442
    - type: manhattan_f1
      value: 76.48944401459048
    - type: manhattan_precision
      value: 73.34134105843285
    - type: manhattan_recall
      value: 79.91992608561749
    - type: max_accuracy
      value: 88.19226141964528
    - type: max_ap
      value: 84.37486145048878
    - type: max_f1
      value: 76.65294717365856
---