transformers safetensors mistral feature-extraction mteb arxiv:2402.15449 model-index text-generation-inference text-embeddings-inference endpoints_compatible region:us
---
tags:
- mteb
model-index:
- name: mlm
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 82.97014925373135
    - type: ap
      value: 49.6288385893607
    - type: f1
      value: 77.58957447993662
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 90.975425
    - type: ap
      value: 87.57349835900825
    - type: f1
      value: 90.96732416386632
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.708
    - type: f1
      value: 47.736228936979586
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.006
    - type: map_at_10
      value: 49.268
    - type: map_at_100
      value: 49.903999999999996
    - type: map_at_1000
      value: 49.909
    - type: map_at_3
      value: 44.334
    - type: map_at_5
      value: 47.374
    - type: mrr_at_1
      value: 32.788000000000004
    - type: mrr_at_10
      value: 49.707
    - type: mrr_at_100
      value: 50.346999999999994
    - type: mrr_at_1000
      value: 50.352
    - type: mrr_at_3
      value: 44.95
    - type: mrr_at_5
      value: 47.766999999999996
    - type: ndcg_at_1
      value: 32.006
    - type: ndcg_at_10
      value: 58.523
    - type: ndcg_at_100
      value: 61.095
    - type: ndcg_at_1000
      value: 61.190999999999995
    - type: ndcg_at_3
      value: 48.431000000000004
    - type: ndcg_at_5
      value: 53.94
    - type: precision_at_1
      value: 32.006
    - type: precision_at_10
      value: 8.791
    - type: precision_at_100
      value: 0.989
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 20.104
    - type: precision_at_5
      value: 14.751
    - type: recall_at_1
      value: 32.006
    - type: recall_at_10
      value: 87.909
    - type: recall_at_100
      value: 98.86200000000001
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 60.313
    - type: recall_at_5
      value: 73.75500000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 47.01500173547629
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 43.52209238193538
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 64.1348784470504
    - type: mrr
      value: 76.93762916062083
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 87.8322696692348
    - type: cos_sim_spearman
      value: 86.53751398463592
    - type: euclidean_pearson
      value: 86.1435544054336
    - type: euclidean_spearman
      value: 86.70799979698164
    - type: manhattan_pearson
      value: 86.1206703865016
    - type: manhattan_spearman
      value: 86.47004256773585
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 88.1461038961039
    - type: f1
      value: 88.09877611214092
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.53021718892608
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 35.34236915611622
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.435
    - type: map_at_10
      value: 49.437999999999995
    - type: map_at_100
      value: 51.105999999999995
    - type: map_at_1000
      value: 51.217999999999996
    - type: map_at_3
      value: 44.856
    - type: map_at_5
      value: 47.195
    - type: mrr_at_1
      value: 45.78
    - type: mrr_at_10
      value: 56.302
    - type: mrr_at_100
      value: 56.974000000000004
    - type: mrr_at_1000
      value: 57.001999999999995
    - type: mrr_at_3
      value: 53.6
    - type: mrr_at_5
      value: 55.059999999999995
    - type: ndcg_at_1
      value: 44.921
    - type: ndcg_at_10
      value: 56.842000000000006
    - type: ndcg_at_100
      value: 61.586
    - type: ndcg_at_1000
      value: 63.039
    - type: ndcg_at_3
      value: 50.612
    - type: ndcg_at_5
      value: 53.181
    - type: precision_at_1
      value: 44.921
    - type: precision_at_10
      value: 11.245
    - type: precision_at_100
      value: 1.7069999999999999
    - type: precision_at_1000
      value: 0.216
    - type: precision_at_3
      value: 24.224999999999998
    - type: precision_at_5
      value: 17.511
    - type: recall_at_1
      value: 36.435
    - type: recall_at_10
      value: 70.998
    - type: recall_at_100
      value: 89.64
    - type: recall_at_1000
      value: 98.654
    - type: recall_at_3
      value: 53.034000000000006
    - type: recall_at_5
      value: 60.41
    - type: map_at_1
      value: 33.371
    - type: map_at_10
      value: 45.301
    - type: map_at_100
      value: 46.663
    - type: map_at_1000
      value: 46.791
    - type: map_at_3
      value: 41.79
    - type: map_at_5
      value: 43.836999999999996
    - type: mrr_at_1
      value: 42.611
    - type: mrr_at_10
      value: 51.70400000000001
    - type: mrr_at_100
      value: 52.342
    - type: mrr_at_1000
      value: 52.38
    - type: mrr_at_3
      value: 49.374
    - type: mrr_at_5
      value: 50.82
    - type: ndcg_at_1
      value: 42.166
    - type: ndcg_at_10
      value: 51.49
    - type: ndcg_at_100
      value: 56.005
    - type: ndcg_at_1000
      value: 57.748
    - type: ndcg_at_3
      value: 46.769
    - type: ndcg_at_5
      value: 49.155
    - type: precision_at_1
      value: 42.166
    - type: precision_at_10
      value: 9.841
    - type: precision_at_100
      value: 1.569
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 22.803
    - type: precision_at_5
      value: 16.229
    - type: recall_at_1
      value: 33.371
    - type: recall_at_10
      value: 62.52799999999999
    - type: recall_at_100
      value: 81.269
    - type: recall_at_1000
      value: 91.824
    - type: recall_at_3
      value: 48.759
    - type: recall_at_5
      value: 55.519
    - type: map_at_1
      value: 41.421
    - type: map_at_10
      value: 55.985
    - type: map_at_100
      value: 56.989999999999995
    - type: map_at_1000
      value: 57.028
    - type: map_at_3
      value: 52.271
    - type: map_at_5
      value: 54.517
    - type: mrr_at_1
      value: 47.272999999999996
    - type: mrr_at_10
      value: 59.266
    - type: mrr_at_100
      value: 59.821999999999996
    - type: mrr_at_1000
      value: 59.839
    - type: mrr_at_3
      value: 56.677
    - type: mrr_at_5
      value: 58.309999999999995
    - type: ndcg_at_1
      value: 47.147
    - type: ndcg_at_10
      value: 62.596
    - type: ndcg_at_100
      value: 66.219
    - type: ndcg_at_1000
      value: 66.886
    - type: ndcg_at_3
      value: 56.558
    - type: ndcg_at_5
      value: 59.805
    - type: precision_at_1
      value: 47.147
    - type: precision_at_10
      value: 10.245
    - type: precision_at_100
      value: 1.302
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 25.663999999999998
    - type: precision_at_5
      value: 17.793
    - type: recall_at_1
      value: 41.421
    - type: recall_at_10
      value: 78.77499999999999
    - type: recall_at_100
      value: 93.996
    - type: recall_at_1000
      value: 98.60600000000001
    - type: recall_at_3
      value: 62.891
    - type: recall_at_5
      value: 70.819
    - type: map_at_1
      value: 27.517999999999997
    - type: map_at_10
      value: 37.468
    - type: map_at_100
      value: 38.667
    - type: map_at_1000
      value: 38.743
    - type: map_at_3
      value: 34.524
    - type: map_at_5
      value: 36.175000000000004
    - type: mrr_at_1
      value: 29.378999999999998
    - type: mrr_at_10
      value: 39.54
    - type: mrr_at_100
      value: 40.469
    - type: mrr_at_1000
      value: 40.522000000000006
    - type: mrr_at_3
      value: 36.685
    - type: mrr_at_5
      value: 38.324000000000005
    - type: ndcg_at_1
      value: 29.718
    - type: ndcg_at_10
      value: 43.091
    - type: ndcg_at_100
      value: 48.44
    - type: ndcg_at_1000
      value: 50.181
    - type: ndcg_at_3
      value: 37.34
    - type: ndcg_at_5
      value: 40.177
    - type: precision_at_1
      value: 29.718
    - type: precision_at_10
      value: 6.723
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 16.083
    - type: precision_at_5
      value: 11.322000000000001
    - type: recall_at_1
      value: 27.517999999999997
    - type: recall_at_10
      value: 58.196999999999996
    - type: recall_at_100
      value: 82.07799999999999
    - type: recall_at_1000
      value: 94.935
    - type: recall_at_3
      value: 42.842
    - type: recall_at_5
      value: 49.58
    - type: map_at_1
      value: 19.621
    - type: map_at_10
      value: 30.175
    - type: map_at_100
      value: 31.496000000000002
    - type: map_at_1000
      value: 31.602000000000004
    - type: map_at_3
      value: 26.753
    - type: map_at_5
      value: 28.857
    - type: mrr_at_1
      value: 25.497999999999998
    - type: mrr_at_10
      value: 35.44
    - type: mrr_at_100
      value: 36.353
    - type: mrr_at_1000
      value: 36.412
    - type: mrr_at_3
      value: 32.275999999999996
    - type: mrr_at_5
      value: 34.434
    - type: ndcg_at_1
      value: 24.502
    - type: ndcg_at_10
      value: 36.423
    - type: ndcg_at_100
      value: 42.289
    - type: ndcg_at_1000
      value: 44.59
    - type: ndcg_at_3
      value: 30.477999999999998
    - type: ndcg_at_5
      value: 33.787
    - type: precision_at_1
      value: 24.502
    - type: precision_at_10
      value: 6.978
    - type: precision_at_100
      value: 1.139
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 15.008
    - type: precision_at_5
      value: 11.468
    - type: recall_at_1
      value: 19.621
    - type: recall_at_10
      value: 50.516000000000005
    - type: recall_at_100
      value: 75.721
    - type: recall_at_1000
      value: 91.77199999999999
    - type: recall_at_3
      value: 34.695
    - type: recall_at_5
      value: 42.849
    - type: map_at_1
      value: 33.525
    - type: map_at_10
      value: 46.153
    - type: map_at_100
      value: 47.61
    - type: map_at_1000
      value: 47.715
    - type: map_at_3
      value: 42.397
    - type: map_at_5
      value: 44.487
    - type: mrr_at_1
      value: 42.445
    - type: mrr_at_10
      value: 52.174
    - type: mrr_at_100
      value: 52.986999999999995
    - type: mrr_at_1000
      value: 53.016
    - type: mrr_at_3
      value: 49.647000000000006
    - type: mrr_at_5
      value: 51.215999999999994
    - type: ndcg_at_1
      value: 42.156
    - type: ndcg_at_10
      value: 52.698
    - type: ndcg_at_100
      value: 58.167
    - type: ndcg_at_1000
      value: 59.71300000000001
    - type: ndcg_at_3
      value: 47.191
    - type: ndcg_at_5
      value: 49.745
    - type: precision_at_1
      value: 42.156
    - type: precision_at_10
      value: 9.682
    - type: precision_at_100
      value: 1.469
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 22.682
    - type: precision_at_5
      value: 16.035
    - type: recall_at_1
      value: 33.525
    - type: recall_at_10
      value: 66.142
    - type: recall_at_100
      value: 88.248
    - type: recall_at_1000
      value: 97.806
    - type: recall_at_3
      value: 50.541000000000004
    - type: recall_at_5
      value: 57.275
    - type: map_at_1
      value: 28.249000000000002
    - type: map_at_10
      value: 41.659
    - type: map_at_100
      value: 43.001
    - type: map_at_1000
      value: 43.094
    - type: map_at_3
      value: 37.607
    - type: map_at_5
      value: 39.662
    - type: mrr_at_1
      value: 36.301
    - type: mrr_at_10
      value: 47.482
    - type: mrr_at_100
      value: 48.251
    - type: mrr_at_1000
      value: 48.288
    - type: mrr_at_3
      value: 44.444
    - type: mrr_at_5
      value: 46.013999999999996
    - type: ndcg_at_1
      value: 35.616
    - type: ndcg_at_10
      value: 49.021
    - type: ndcg_at_100
      value: 54.362
    - type: ndcg_at_1000
      value: 55.864999999999995
    - type: ndcg_at_3
      value: 42.515
    - type: ndcg_at_5
      value: 45.053
    - type: precision_at_1
      value: 35.616
    - type: precision_at_10
      value: 9.372
    - type: precision_at_100
      value: 1.4120000000000001
    - type: precision_at_1000
      value: 0.172
    - type: precision_at_3
      value: 21.043
    - type: precision_at_5
      value: 14.84
    - type: recall_at_1
      value: 28.249000000000002
    - type: recall_at_10
      value: 65.514
    - type: recall_at_100
      value: 87.613
    - type: recall_at_1000
      value: 97.03
    - type: recall_at_3
      value: 47.21
    - type: recall_at_5
      value: 54.077
    - type: map_at_1
      value: 29.164583333333333
    - type: map_at_10
      value: 40.632000000000005
    - type: map_at_100
      value: 41.96875
    - type: map_at_1000
      value: 42.07508333333333
    - type: map_at_3
      value: 37.18458333333333
    - type: map_at_5
      value: 39.13700000000001
    - type: mrr_at_1
      value: 35.2035
    - type: mrr_at_10
      value: 45.28816666666666
    - type: mrr_at_100
      value: 46.11466666666667
    - type: mrr_at_1000
      value: 46.15741666666667
    - type: mrr_at_3
      value: 42.62925
    - type: mrr_at_5
      value: 44.18141666666667
    - type: ndcg_at_1
      value: 34.88958333333333
    - type: ndcg_at_10
      value: 46.90650000000001
    - type: ndcg_at_100
      value: 52.135333333333335
    - type: ndcg_at_1000
      value: 53.89766666666668
    - type: ndcg_at_3
      value: 41.32075
    - type: ndcg_at_5
      value: 44.02083333333333
    - type: precision_at_1
      value: 34.88958333333333
    - type: precision_at_10
      value: 8.392833333333332
    - type: precision_at_100
      value: 1.3085833333333334
    - type: precision_at_1000
      value: 0.16458333333333333
    - type: precision_at_3
      value: 19.361166666666666
    - type: precision_at_5
      value: 13.808416666666668
    - type: recall_at_1
      value: 29.164583333333333
    - type: recall_at_10
      value: 60.874666666666656
    - type: recall_at_100
      value: 83.21008333333334
    - type: recall_at_1000
      value: 95.09275000000001
    - type: recall_at_3
      value: 45.37591666666667
    - type: recall_at_5
      value: 52.367666666666665
    - type: map_at_1
      value: 28.682000000000002
    - type: map_at_10
      value: 37.913000000000004
    - type: map_at_100
      value: 39.037
    - type: map_at_1000
      value: 39.123999999999995
    - type: map_at_3
      value: 35.398
    - type: map_at_5
      value: 36.906
    - type: mrr_at_1
      value: 32.362
    - type: mrr_at_10
      value: 40.92
    - type: mrr_at_100
      value: 41.748000000000005
    - type: mrr_at_1000
      value: 41.81
    - type: mrr_at_3
      value: 38.701
    - type: mrr_at_5
      value: 39.936
    - type: ndcg_at_1
      value: 32.208999999999996
    - type: ndcg_at_10
      value: 42.84
    - type: ndcg_at_100
      value: 47.927
    - type: ndcg_at_1000
      value: 50.048
    - type: ndcg_at_3
      value: 38.376
    - type: ndcg_at_5
      value: 40.661
    - type: precision_at_1
      value: 32.208999999999996
    - type: precision_at_10
      value: 6.718
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 16.667
    - type: precision_at_5
      value: 11.503
    - type: recall_at_1
      value: 28.682000000000002
    - type: recall_at_10
      value: 54.872
    - type: recall_at_100
      value: 77.42999999999999
    - type: recall_at_1000
      value: 93.054
    - type: recall_at_3
      value: 42.577999999999996
    - type: recall_at_5
      value: 48.363
    - type: map_at_1
      value: 19.698
    - type: map_at_10
      value: 28.777
    - type: map_at_100
      value: 30.091
    - type: map_at_1000
      value: 30.209999999999997
    - type: map_at_3
      value: 25.874000000000002
    - type: map_at_5
      value: 27.438000000000002
    - type: mrr_at_1
      value: 24.295
    - type: mrr_at_10
      value: 33.077
    - type: mrr_at_100
      value: 34.036
    - type: mrr_at_1000
      value: 34.1
    - type: mrr_at_3
      value: 30.523
    - type: mrr_at_5
      value: 31.891000000000002
    - type: ndcg_at_1
      value: 24.535
    - type: ndcg_at_10
      value: 34.393
    - type: ndcg_at_100
      value: 40.213
    - type: ndcg_at_1000
      value: 42.748000000000005
    - type: ndcg_at_3
      value: 29.316
    - type: ndcg_at_5
      value: 31.588
    - type: precision_at_1
      value: 24.535
    - type: precision_at_10
      value: 6.483
    - type: precision_at_100
      value: 1.102
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_3
      value: 14.201
    - type: precision_at_5
      value: 10.344000000000001
    - type: recall_at_1
      value: 19.698
    - type: recall_at_10
      value: 46.903
    - type: recall_at_100
      value: 72.624
    - type: recall_at_1000
      value: 90.339
    - type: recall_at_3
      value: 32.482
    - type: recall_at_5
      value: 38.452
    - type: map_at_1
      value: 30.56
    - type: map_at_10
      value: 41.993
    - type: map_at_100
      value: 43.317
    - type: map_at_1000
      value: 43.399
    - type: map_at_3
      value: 38.415
    - type: map_at_5
      value: 40.472
    - type: mrr_at_1
      value: 36.474000000000004
    - type: mrr_at_10
      value: 46.562
    - type: mrr_at_100
      value: 47.497
    - type: mrr_at_1000
      value: 47.532999999999994
    - type: mrr_at_3
      value: 43.905
    - type: mrr_at_5
      value: 45.379000000000005
    - type: ndcg_at_1
      value: 36.287000000000006
    - type: ndcg_at_10
      value: 48.262
    - type: ndcg_at_100
      value: 53.789
    - type: ndcg_at_1000
      value: 55.44
    - type: ndcg_at_3
      value: 42.358000000000004
    - type: ndcg_at_5
      value: 45.221000000000004
    - type: precision_at_1
      value: 36.287000000000006
    - type: precision_at_10
      value: 8.265
    - type: precision_at_100
      value: 1.24
    - type: precision_at_1000
      value: 0.148
    - type: precision_at_3
      value: 19.558
    - type: precision_at_5
      value: 13.880999999999998
    - type: recall_at_1
      value: 30.56
    - type: recall_at_10
      value: 62.891
    - type: recall_at_100
      value: 85.964
    - type: recall_at_1000
      value: 97.087
    - type: recall_at_3
      value: 46.755
    - type: recall_at_5
      value: 53.986000000000004
    - type: map_at_1
      value: 29.432000000000002
    - type: map_at_10
      value: 40.898
    - type: map_at_100
      value: 42.794
    - type: map_at_1000
      value: 43.029
    - type: map_at_3
      value: 37.658
    - type: map_at_5
      value: 39.519
    - type: mrr_at_1
      value: 36.364000000000004
    - type: mrr_at_10
      value: 46.9
    - type: mrr_at_100
      value: 47.819
    - type: mrr_at_1000
      value: 47.848
    - type: mrr_at_3
      value: 44.202999999999996
    - type: mrr_at_5
      value: 45.715
    - type: ndcg_at_1
      value: 35.573
    - type: ndcg_at_10
      value: 47.628
    - type: ndcg_at_100
      value: 53.88699999999999
    - type: ndcg_at_1000
      value: 55.584
    - type: ndcg_at_3
      value: 42.669000000000004
    - type: ndcg_at_5
      value: 45.036
    - type: precision_at_1
      value: 35.573
    - type: precision_at_10
      value: 8.933
    - type: precision_at_100
      value: 1.8159999999999998
    - type: precision_at_1000
      value: 0.256
    - type: precision_at_3
      value: 20.29
    - type: precision_at_5
      value: 14.387
    - type: recall_at_1
      value: 29.432000000000002
    - type: recall_at_10
      value: 60.388
    - type: recall_at_100
      value: 87.144
    - type: recall_at_1000
      value: 97.154
    - type: recall_at_3
      value: 45.675
    - type: recall_at_5
      value: 52.35300000000001
    - type: map_at_1
      value: 21.462999999999997
    - type: map_at_10
      value: 31.824
    - type: map_at_100
      value: 32.853
    - type: map_at_1000
      value: 32.948
    - type: map_at_3
      value: 28.671999999999997
    - type: map_at_5
      value: 30.579
    - type: mrr_at_1
      value: 23.66
    - type: mrr_at_10
      value: 34.091
    - type: mrr_at_100
      value: 35.077999999999996
    - type: mrr_at_1000
      value: 35.138999999999996
    - type: mrr_at_3
      value: 31.516
    - type: mrr_at_5
      value: 33.078
    - type: ndcg_at_1
      value: 23.845
    - type: ndcg_at_10
      value: 37.594
    - type: ndcg_at_100
      value: 42.74
    - type: ndcg_at_1000
      value: 44.93
    - type: ndcg_at_3
      value: 31.667
    - type: ndcg_at_5
      value: 34.841
    - type: precision_at_1
      value: 23.845
    - type: precision_at_10
      value: 6.229
    - type: precision_at_100
      value: 0.943
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 14.11
    - type: precision_at_5
      value: 10.388
    - type: recall_at_1
      value: 21.462999999999997
    - type: recall_at_10
      value: 52.772
    - type: recall_at_100
      value: 76.794
    - type: recall_at_1000
      value: 92.852
    - type: recall_at_3
      value: 37.049
    - type: recall_at_5
      value: 44.729
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.466
    - type: map_at_10
      value: 25.275
    - type: map_at_100
      value: 27.176000000000002
    - type: map_at_1000
      value: 27.374
    - type: map_at_3
      value: 21.438
    - type: map_at_5
      value: 23.366
    - type: mrr_at_1
      value: 35.699999999999996
    - type: mrr_at_10
      value: 47.238
    - type: mrr_at_100
      value: 47.99
    - type: mrr_at_1000
      value: 48.021
    - type: mrr_at_3
      value: 44.463
    - type: mrr_at_5
      value: 46.039
    - type: ndcg_at_1
      value: 35.244
    - type: ndcg_at_10
      value: 34.559
    - type: ndcg_at_100
      value: 41.74
    - type: ndcg_at_1000
      value: 45.105000000000004
    - type: ndcg_at_3
      value: 29.284
    - type: ndcg_at_5
      value: 30.903999999999996
    - type: precision_at_1
      value: 35.244
    - type: precision_at_10
      value: 10.463000000000001
    - type: precision_at_100
      value: 1.8259999999999998
    - type: precision_at_1000
      value: 0.246
    - type: precision_at_3
      value: 21.65
    - type: precision_at_5
      value: 16.078
    - type: recall_at_1
      value: 15.466
    - type: recall_at_10
      value: 39.782000000000004
    - type: recall_at_100
      value: 64.622
    - type: recall_at_1000
      value: 83.233
    - type: recall_at_3
      value: 26.398
    - type: recall_at_5
      value: 31.676
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.414
    - type: map_at_10
      value: 22.435
    - type: map_at_100
      value: 32.393
    - type: map_at_1000
      value: 34.454
    - type: map_at_3
      value: 15.346000000000002
    - type: map_at_5
      value: 18.282999999999998
    - type: mrr_at_1
      value: 71.5
    - type: mrr_at_10
      value: 78.795
    - type: mrr_at_100
      value: 79.046
    - type: mrr_at_1000
      value: 79.054
    - type: mrr_at_3
      value: 77.333
    - type: mrr_at_5
      value: 78.146
    - type: ndcg_at_1
      value: 60.75000000000001
    - type: ndcg_at_10
      value: 46.829
    - type: ndcg_at_100
      value: 52.370000000000005
    - type: ndcg_at_1000
      value: 59.943999999999996
    - type: ndcg_at_3
      value: 51.33
    - type: ndcg_at_5
      value: 48.814
    - type: precision_at_1
      value: 71.75
    - type: precision_at_10
      value: 37.525
    - type: precision_at_100
      value: 12.075
    - type: precision_at_1000
      value: 2.464
    - type: precision_at_3
      value: 54.75
    - type: precision_at_5
      value: 47.55
    - type: recall_at_1
      value: 9.414
    - type: recall_at_10
      value: 28.67
    - type: recall_at_100
      value: 59.924
    - type: recall_at_1000
      value: 83.921
    - type: recall_at_3
      value: 16.985
    - type: recall_at_5
      value: 21.372
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 52.18000000000001
    - type: f1
      value: 47.04613218997081
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 82.57900000000001
    - type: map_at_10
      value: 88.465
    - type: map_at_100
      value: 88.649
    - type: map_at_1000
      value: 88.661
    - type: map_at_3
      value: 87.709
    - type: map_at_5
      value: 88.191
    - type: mrr_at_1
      value: 88.899
    - type: mrr_at_10
      value: 93.35900000000001
    - type: mrr_at_100
      value: 93.38499999999999
    - type: mrr_at_1000
      value: 93.38499999999999
    - type: mrr_at_3
      value: 93.012
    - type: mrr_at_5
      value: 93.282
    - type: ndcg_at_1
      value: 88.98899999999999
    - type: ndcg_at_10
      value: 91.22
    - type: ndcg_at_100
      value: 91.806
    - type: ndcg_at_1000
      value: 92.013
    - type: ndcg_at_3
      value: 90.236
    - type: ndcg_at_5
      value: 90.798
    - type: precision_at_1
      value: 88.98899999999999
    - type: precision_at_10
      value: 10.537
    - type: precision_at_100
      value: 1.106
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 33.598
    - type: precision_at_5
      value: 20.618
    - type: recall_at_1
      value: 82.57900000000001
    - type: recall_at_10
      value: 94.95400000000001
    - type: recall_at_100
      value: 97.14
    - type: recall_at_1000
      value: 98.407
    - type: recall_at_3
      value: 92.203
    - type: recall_at_5
      value: 93.747
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 27.871000000000002
    - type: map_at_10
      value: 46.131
    - type: map_at_100
      value: 48.245
    - type: map_at_1000
      value: 48.361
    - type: map_at_3
      value: 40.03
    - type: map_at_5
      value: 43.634
    - type: mrr_at_1
      value: 52.932
    - type: mrr_at_10
      value: 61.61299999999999
    - type: mrr_at_100
      value: 62.205
    - type: mrr_at_1000
      value: 62.224999999999994
    - type: mrr_at_3
      value: 59.388
    - type: mrr_at_5
      value: 60.760999999999996
    - type: ndcg_at_1
      value: 53.395
    - type: ndcg_at_10
      value: 54.506
    - type: ndcg_at_100
      value: 61.151999999999994
    - type: ndcg_at_1000
      value: 62.882000000000005
    - type: ndcg_at_3
      value: 49.903999999999996
    - type: ndcg_at_5
      value: 51.599
    - type: precision_at_1
      value: 53.395
    - type: precision_at_10
      value: 15.247
    - type: precision_at_100
      value: 2.221
    - type: precision_at_1000
      value: 0.255
    - type: precision_at_3
      value: 33.539
    - type: precision_at_5
      value: 24.722
    - type: recall_at_1
      value: 27.871000000000002
    - type: recall_at_10
      value: 62.074
    - type: recall_at_100
      value: 86.531
    - type: recall_at_1000
      value: 96.574
    - type: recall_at_3
      value: 45.003
    - type: recall_at_5
      value: 53.00899999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.513
    - type: map_at_10
      value: 69.066
    - type: map_at_100
      value: 69.903
    - type: map_at_1000
      value: 69.949
    - type: map_at_3
      value: 65.44200000000001
    - type: map_at_5
      value: 67.784
    - type: mrr_at_1
      value: 80.891
    - type: mrr_at_10
      value: 86.42699999999999
    - type: mrr_at_100
      value: 86.577
    - type: mrr_at_1000
      value: 86.58200000000001
    - type: mrr_at_3
      value: 85.6
    - type: mrr_at_5
      value: 86.114
    - type: ndcg_at_1
      value: 81.026
    - type: ndcg_at_10
      value: 76.412
    - type: ndcg_at_100
      value: 79.16
    - type: ndcg_at_1000
      value: 79.989
    - type: ndcg_at_3
      value: 71.45
    - type: ndcg_at_5
      value: 74.286
    - type: precision_at_1
      value: 81.026
    - type: precision_at_10
      value: 16.198999999999998
    - type: precision_at_100
      value: 1.831
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 46.721000000000004
    - type: precision_at_5
      value: 30.266
    - type: recall_at_1
      value: 40.513
    - type: recall_at_10
      value: 80.99300000000001
    - type: recall_at_100
      value: 91.526
    - type: recall_at_1000
      value: 96.935
    - type: recall_at_3
      value: 70.081
    - type: recall_at_5
      value: 75.665
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 87.42320000000001
    - type: ap
      value: 83.59975323233843
    - type: f1
      value: 87.38669942597816
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 22.676
    - type: map_at_10
      value: 35.865
    - type: map_at_100
      value: 37.019000000000005
    - type: map_at_1000
      value: 37.062
    - type: map_at_3
      value: 31.629
    - type: map_at_5
      value: 34.050999999999995
    - type: mrr_at_1
      value: 23.023
    - type: mrr_at_10
      value: 36.138999999999996
    - type: mrr_at_100
      value: 37.242
    - type: mrr_at_1000
      value: 37.28
    - type: mrr_at_3
      value: 32.053
    - type: mrr_at_5
      value: 34.383
    - type: ndcg_at_1
      value: 23.308999999999997
    - type: ndcg_at_10
      value: 43.254
    - type: ndcg_at_100
      value: 48.763
    - type: ndcg_at_1000
      value: 49.788
    - type: ndcg_at_3
      value: 34.688
    - type: ndcg_at_5
      value: 38.973
    - type: precision_at_1
      value: 23.308999999999997
    - type: precision_at_10
      value: 6.909999999999999
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 14.818999999999999
    - type: precision_at_5
      value: 11.072
    - type: recall_at_1
      value: 22.676
    - type: recall_at_10
      value: 66.077
    - type: recall_at_100
      value: 91.4
    - type: recall_at_1000
      value: 99.143
    - type: recall_at_3
      value: 42.845
    - type: recall_at_5
      value: 53.08500000000001
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 96.16279069767444
    - type: f1
      value: 96.02183835878418
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 85.74783401732788
    - type: f1
      value: 70.59661579230463
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 79.67047747141895
    - type: f1
      value: 77.06311183471965
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 82.82447881640887
    - type: f1
      value: 82.37598020010746
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.266131881264467
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 29.673653452453998
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.91846122902102
    - type: mrr
      value: 34.2557300204471
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.762
    - type: map_at_10
      value: 15.134
    - type: map_at_100
      value: 19.341
    - type: map_at_1000
      value: 20.961
    - type: map_at_3
      value: 10.735999999999999
    - type: map_at_5
      value: 12.751999999999999
    - type: mrr_at_1
      value: 52.941
    - type: mrr_at_10
      value: 60.766
    - type: mrr_at_100
      value: 61.196
    - type: mrr_at_1000
      value: 61.227
    - type: mrr_at_3
      value: 58.720000000000006
    - type: mrr_at_5
      value: 59.866
    - type: ndcg_at_1
      value: 50.929
    - type: ndcg_at_10
      value: 39.554
    - type: ndcg_at_100
      value: 36.307
    - type: ndcg_at_1000
      value: 44.743
    - type: ndcg_at_3
      value: 44.157000000000004
    - type: ndcg_at_5
      value: 42.142
    - type: precision_at_1
      value: 52.322
    - type: precision_at_10
      value: 29.412
    - type: precision_at_100
      value: 9.365
    - type: precision_at_1000
      value: 2.2159999999999997
    - type: precision_at_3
      value: 40.557
    - type: precision_at_5
      value: 35.913000000000004
    - type: recall_at_1
      value: 6.762
    - type: recall_at_10
      value: 19.689999999999998
    - type: recall_at_100
      value: 36.687
    - type: recall_at_1000
      value: 67.23
    - type: recall_at_3
      value: 11.773
    - type: recall_at_5
      value: 15.18
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.612
    - type: map_at_10
      value: 54.208
    - type: map_at_100
      value: 55.056000000000004
    - type: map_at_1000
      value: 55.069
    - type: map_at_3
      value: 49.45
    - type: map_at_5
      value: 52.556000000000004
    - type: mrr_at_1
      value: 41.976
    - type: mrr_at_10
      value: 56.972
    - type: mrr_at_100
      value: 57.534
    - type: mrr_at_1000
      value: 57.542
    - type: mrr_at_3
      value: 53.312000000000005
    - type: mrr_at_5
      value: 55.672999999999995
    - type: ndcg_at_1
      value: 41.338
    - type: ndcg_at_10
      value: 62.309000000000005
    - type: ndcg_at_100
      value: 65.557
    - type: ndcg_at_1000
      value: 65.809
    - type: ndcg_at_3
      value: 53.74100000000001
    - type: ndcg_at_5
      value: 58.772999999999996
    - type: precision_at_1
      value: 41.338
    - type: precision_at_10
      value: 10.107
    - type: precision_at_100
      value: 1.1900000000000002
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 24.488
    - type: precision_at_5
      value: 17.596
    - type: recall_at_1
      value: 36.612
    - type: recall_at_10
      value: 84.408
    - type: recall_at_100
      value: 97.929
    - type: recall_at_1000
      value: 99.725
    - type: recall_at_3
      value: 62.676
    - type: recall_at_5
      value: 74.24199999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 71.573
    - type: map_at_10
      value: 85.81
    - type: map_at_100
      value: 86.434
    - type: map_at_1000
      value: 86.446
    - type: map_at_3
      value: 82.884
    - type: map_at_5
      value: 84.772
    - type: mrr_at_1
      value: 82.53
    - type: mrr_at_10
      value: 88.51299999999999
    - type: mrr_at_100
      value: 88.59700000000001
    - type: mrr_at_1000
      value: 88.598
    - type: mrr_at_3
      value: 87.595
    - type: mrr_at_5
      value: 88.266
    - type: ndcg_at_1
      value: 82.39999999999999
    - type: ndcg_at_10
      value: 89.337
    - type: ndcg_at_100
      value: 90.436
    - type: ndcg_at_1000
      value: 90.498
    - type: ndcg_at_3
      value: 86.676
    - type: ndcg_at_5
      value: 88.241
    - type: precision_at_1
      value: 82.39999999999999
    - type: precision_at_10
      value: 13.58
    - type: precision_at_100
      value: 1.543
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 38.04
    - type: precision_at_5
      value: 25.044
    - type: recall_at_1
      value: 71.573
    - type: recall_at_10
      value: 96.066
    - type: recall_at_100
      value: 99.73100000000001
    - type: recall_at_1000
      value: 99.991
    - type: recall_at_3
      value: 88.34
    - type: recall_at_5
      value: 92.79899999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 61.767168063971724
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 66.00502775826037
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.718
    - type: map_at_10
      value: 12.13
    - type: map_at_100
      value: 14.269000000000002
    - type: map_at_1000
      value: 14.578
    - type: map_at_3
      value: 8.605
    - type: map_at_5
      value: 10.483
    - type: mrr_at_1
      value: 23.7
    - type: mrr_at_10
      value: 34.354
    - type: mrr_at_100
      value: 35.522
    - type: mrr_at_1000
      value: 35.571999999999996
    - type: mrr_at_3
      value: 31.15
    - type: mrr_at_5
      value: 32.98
    - type: ndcg_at_1
      value: 23.3
    - type: ndcg_at_10
      value: 20.171
    - type: ndcg_at_100
      value: 28.456
    - type: ndcg_at_1000
      value: 33.826
    - type: ndcg_at_3
      value: 19.104
    - type: ndcg_at_5
      value: 16.977999999999998
    - type: precision_at_1
      value: 23.3
    - type: precision_at_10
      value: 10.45
    - type: precision_at_100
      value: 2.239
    - type: precision_at_1000
      value: 0.35300000000000004
    - type: precision_at_3
      value: 17.933
    - type: precision_at_5
      value: 15.1
    - type: recall_at_1
      value: 4.718
    - type: recall_at_10
      value: 21.221999999999998
    - type: recall_at_100
      value: 45.42
    - type: recall_at_1000
      value: 71.642
    - type: recall_at_3
      value: 10.922
    - type: recall_at_5
      value: 15.322
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 85.2065344862739
    - type: cos_sim_spearman
      value: 83.2276569587515
    - type: euclidean_pearson
      value: 83.42726762105312
    - type: euclidean_spearman
      value: 83.31396596997742
    - type: manhattan_pearson
      value: 83.41123401762816
    - type: manhattan_spearman
      value: 83.34393052682026
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 81.28253173719754
    - type: cos_sim_spearman
      value: 76.12995701324436
    - type: euclidean_pearson
      value: 75.30693691794121
    - type: euclidean_spearman
      value: 75.12472789129536
    - type: manhattan_pearson
      value: 75.35860808729171
    - type: manhattan_spearman
      value: 75.30445827952794
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 82.09358031005694
    - type: cos_sim_spearman
      value: 83.18811147636619
    - type: euclidean_pearson
      value: 82.65513459991631
    - type: euclidean_spearman
      value: 82.71085530442987
    - type: manhattan_pearson
      value: 82.67700926821576
    - type: manhattan_spearman
      value: 82.73815539380426
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 81.51365440223137
    - type: cos_sim_spearman
      value: 80.59933905019179
    - type: euclidean_pearson
      value: 80.56660025433806
    - type: euclidean_spearman
      value: 80.27926539084027
    - type: manhattan_pearson
      value: 80.64632724055481
    - type: manhattan_spearman
      value: 80.43616365139444
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.8590461417506
    - type: cos_sim_spearman
      value: 87.16337291721602
    - type: euclidean_pearson
      value: 85.8847725068404
    - type: euclidean_spearman
      value: 86.12602873624066
    - type: manhattan_pearson
      value: 86.04095861363909
    - type: manhattan_spearman
      value: 86.35535645007629
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 83.61371557181502
    - type: cos_sim_spearman
      value: 85.16330754442785
    - type: euclidean_pearson
      value: 84.20831431260608
    - type: euclidean_spearman
      value: 84.33191523212125
    - type: manhattan_pearson
      value: 84.34911007642411
    - type: manhattan_spearman
      value: 84.49670164290394
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 90.54452933158781
    - type: cos_sim_spearman
      value: 90.88214621695892
    - type: euclidean_pearson
      value: 91.38488015281216
    - type: euclidean_spearman
      value: 91.01822259603908
    - type: manhattan_pearson
      value: 91.36449776198687
    - type: manhattan_spearman
      value: 90.90478717381717
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 68.00941643037453
    - type: cos_sim_spearman
      value: 67.03588472081898
    - type: euclidean_pearson
      value: 67.35224911601603
    - type: euclidean_spearman
      value: 66.35544831459266
    - type: manhattan_pearson
      value: 67.35080066508304
    - type: manhattan_spearman
      value: 66.07893473733782
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 85.18291011086279
    - type: cos_sim_spearman
      value: 85.66913777481429
    - type: euclidean_pearson
      value: 84.81115930027242
    - type: euclidean_spearman
      value: 85.07133983924173
    - type: manhattan_pearson
      value: 84.88932120524983
    - type: manhattan_spearman
      value: 85.176903109055
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 83.67543572266588
    - type: mrr
      value: 95.9468146232852
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 59.633
    - type: map_at_10
      value: 69.801
    - type: map_at_100
      value: 70.504
    - type: map_at_1000
      value: 70.519
    - type: map_at_3
      value: 67.72500000000001
    - type: map_at_5
      value: 68.812
    - type: mrr_at_1
      value: 62.333000000000006
    - type: mrr_at_10
      value: 70.956
    - type: mrr_at_100
      value: 71.489
    - type: mrr_at_1000
      value: 71.504
    - type: mrr_at_3
      value: 69.44399999999999
    - type: mrr_at_5
      value: 70.244
    - type: ndcg_at_1
      value: 62.0
    - type: ndcg_at_10
      value: 73.98599999999999
    - type: ndcg_at_100
      value: 76.629
    - type: ndcg_at_1000
      value: 77.054
    - type: ndcg_at_3
      value: 70.513
    - type: ndcg_at_5
      value: 71.978
    - type: precision_at_1
      value: 62.0
    - type: precision_at_10
      value: 9.633
    - type: precision_at_100
      value: 1.097
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 27.556000000000004
    - type: precision_at_5
      value: 17.666999999999998
    - type: recall_at_1
      value: 59.633
    - type: recall_at_10
      value: 85.52199999999999
    - type: recall_at_100
      value: 96.667
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 75.767
    - type: recall_at_5
      value: 79.76100000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.77821782178218
    - type: cos_sim_ap
      value: 94.58684455008866
    - type: cos_sim_f1
      value: 88.51282051282053
    - type: cos_sim_precision
      value: 90.84210526315789
    - type: cos_sim_recall
      value: 86.3
    - type: dot_accuracy
      value: 99.77623762376237
    - type: dot_ap
      value: 94.86277541733045
    - type: dot_f1
      value: 88.66897575457693
    - type: dot_precision
      value: 87.75710088148874
    - type: dot_recall
      value: 89.60000000000001
    - type: euclidean_accuracy
      value: 99.76732673267327
    - type: euclidean_ap
      value: 94.12114402691984
    - type: euclidean_f1
      value: 87.96804792810784
    - type: euclidean_precision
      value: 87.83649052841476
    - type: euclidean_recall
      value: 88.1
    - type: manhattan_accuracy
      value: 99.77227722772277
    - type: manhattan_ap
      value: 94.33665105240306
    - type: manhattan_f1
      value: 88.25587206396803
    - type: manhattan_precision
      value: 88.21178821178822
    - type: manhattan_recall
      value: 88.3
    - type: max_accuracy
      value: 99.77821782178218
    - type: max_ap
      value: 94.86277541733045
    - type: max_f1
      value: 88.66897575457693
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 72.03943478268592
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 35.285037897356496
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 51.83578447913503
    - type: mrr
      value: 52.69070696460402
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.89437612567638
    - type: cos_sim_spearman
      value: 30.7277819987126
    - type: dot_pearson
      value: 30.999783674122526
    - type: dot_spearman
      value: 30.992168551124905
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.22699999999999998
    - type: map_at_10
      value: 1.8950000000000002
    - type: map_at_100
      value: 11.712
    - type: map_at_1000
      value: 28.713
    - type: map_at_3
      value: 0.65
    - type: map_at_5
      value: 1.011
    - type: mrr_at_1
      value: 92.0
    - type: mrr_at_10
      value: 95.39999999999999
    - type: mrr_at_100
      value: 95.39999999999999
    - type: mrr_at_1000
      value: 95.39999999999999
    - type: mrr_at_3
      value: 95.0
    - type: mrr_at_5
      value: 95.39999999999999
    - type: ndcg_at_1
      value: 83.0
    - type: ndcg_at_10
      value: 76.658
    - type: ndcg_at_100
      value: 60.755
    - type: ndcg_at_1000
      value: 55.05
    - type: ndcg_at_3
      value: 82.961
    - type: ndcg_at_5
      value: 80.008
    - type: precision_at_1
      value: 90.0
    - type: precision_at_10
      value: 79.80000000000001
    - type: precision_at_100
      value: 62.019999999999996
    - type: precision_at_1000
      value: 24.157999999999998
    - type: precision_at_3
      value: 88.0
    - type: precision_at_5
      value: 83.6
    - type: recall_at_1
      value: 0.22699999999999998
    - type: recall_at_10
      value: 2.086
    - type: recall_at_100
      value: 15.262
    - type: recall_at_1000
      value: 51.800000000000004
    - type: recall_at_3
      value: 0.679
    - type: recall_at_5
      value: 1.0739999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.521
    - type: map_at_10
      value: 7.281
    - type: map_at_100
      value: 12.717
    - type: map_at_1000
      value: 14.266000000000002
    - type: map_at_3
      value: 3.62
    - type: map_at_5
      value: 4.7010000000000005
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 34.906
    - type: mrr_at_100
      value: 36.333
    - type: mrr_at_1000
      value: 36.348
    - type: mrr_at_3
      value: 29.592000000000002
    - type: mrr_at_5
      value: 33.367000000000004
    - type: ndcg_at_1
      value: 19.387999999999998
    - type: ndcg_at_10
      value: 18.523
    - type: ndcg_at_100
      value: 30.932
    - type: ndcg_at_1000
      value: 42.942
    - type: ndcg_at_3
      value: 18.901
    - type: ndcg_at_5
      value: 17.974999999999998
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 17.347
    - type: precision_at_100
      value: 6.898
    - type: precision_at_1000
      value: 1.482
    - type: precision_at_3
      value: 21.088
    - type: precision_at_5
      value: 19.184
    - type: recall_at_1
      value: 1.521
    - type: recall_at_10
      value: 13.406
    - type: recall_at_100
      value: 43.418
    - type: recall_at_1000
      value: 80.247
    - type: recall_at_3
      value: 4.673
    - type: recall_at_5
      value: 7.247000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.9084
    - type: ap
      value: 15.388385311898144
    - type: f1
      value: 55.760189174489426
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.399547255234864
    - type: f1
      value: 62.61398519525303
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 53.041094760846164
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.92394349406926
    - type: cos_sim_ap
      value: 79.93037248584875
    - type: cos_sim_f1
      value: 73.21063394683026
    - type: cos_sim_precision
      value: 70.99652949925633
    - type: cos_sim_recall
      value: 75.56728232189973
    - type: dot_accuracy
      value: 87.80473266972642
    - type: dot_ap
      value: 79.11055417163318
    - type: dot_f1
      value: 72.79587473273801
    - type: dot_precision
      value: 69.55058880076905
    - type: dot_recall
      value: 76.35883905013192
    - type: euclidean_accuracy
      value: 87.91202241163496
    - type: euclidean_ap
      value: 79.61955502404068
    - type: euclidean_f1
      value: 72.65956080647231
    - type: euclidean_precision
      value: 70.778083562672
    - type: euclidean_recall
      value: 74.64379947229551
    - type: manhattan_accuracy
      value: 87.7749299636407
    - type: manhattan_ap
      value: 79.33286131650932
    - type: manhattan_f1
      value: 72.44748412310699
    - type: manhattan_precision
      value: 67.43974533879036
    - type: manhattan_recall
      value: 78.25857519788919
    - type: max_accuracy
      value: 87.92394349406926
    - type: max_ap
      value: 79.93037248584875
    - type: max_f1
      value: 73.21063394683026
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.89987192921178
    - type: cos_sim_ap
      value: 87.49525152555509
    - type: cos_sim_f1
      value: 80.05039276715578
    - type: cos_sim_precision
      value: 77.15714285714286
    - type: cos_sim_recall
      value: 83.1690791499846
    - type: dot_accuracy
      value: 89.58163542515621
    - type: dot_ap
      value: 86.87353801172357
    - type: dot_f1
      value: 79.50204384986993
    - type: dot_precision
      value: 76.83522482401953
    - type: dot_recall
      value: 82.36064059131506
    - type: euclidean_accuracy
      value: 89.81255093724532
    - type: euclidean_ap
      value: 87.41058010369022
    - type: euclidean_f1
      value: 79.94095829233214
    - type: euclidean_precision
      value: 78.61396456751525
    - type: euclidean_recall
      value: 81.3135201724669
    - type: manhattan_accuracy
      value: 89.84553886754377
    - type: manhattan_ap
      value: 87.41173628281432
    - type: manhattan_f1
      value: 79.9051922079846
    - type: manhattan_precision
      value: 76.98016269444841
    - type: manhattan_recall
      value: 83.06128734216199
    - type: max_accuracy
      value: 89.89987192921178
    - type: max_ap
      value: 87.49525152555509
    - type: max_f1
      value: 80.05039276715578
---

# Repetition Improves Language Model Embeddings

Please refer to our paper: [https://arxiv.org/abs/2402.15449](https://arxiv.org/abs/2402.15449)

And our GitHub: [https://github.com/jakespringer/echo-embeddings](https://github.com/jakespringer/echo-embeddings)

We provide a description of the model as well as example usage in the above links.
