safetensors mteb model-index region:us
---
tags:
- mteb
model-index:
- name: 0523_mistralv2_sum3echo512_bbcc_8_16_16
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 79.65671641791045
    - type: ap
      value: 44.24063991266868
    - type: f1
      value: 73.91766997954294
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 94.480125
    - type: ap
      value: 92.21829806116952
    - type: f1
      value: 94.47801150800291
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.157999999999994
    - type: f1
      value: 47.11858175135973
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 31.935000000000002
    - type: map_at_10
      value: 49.482
    - type: map_at_100
      value: 49.482
    - type: map_at_1000
      value: 49.482
    - type: map_at_20
      value: 49.482
    - type: map_at_3
      value: 44.464
    - type: map_at_5
      value: 47.569
    - type: mrr_at_1
      value: 33.001000000000005
    - type: mrr_at_10
      value: 49.989
    - type: mrr_at_100
      value: 49.989
    - type: mrr_at_1000
      value: 49.989
    - type: mrr_at_20
      value: 49.989
    - type: mrr_at_3
      value: 44.903
    - type: mrr_at_5
      value: 48.054
    - type: ndcg_at_1
      value: 31.935000000000002
    - type: ndcg_at_10
      value: 58.819
    - type: ndcg_at_100
      value: 58.819
    - type: ndcg_at_1000
      value: 58.819
    - type: ndcg_at_20
      value: 58.819
    - type: ndcg_at_3
      value: 48.620000000000005
    - type: ndcg_at_5
      value: 54.230000000000004
    - type: precision_at_1
      value: 31.935000000000002
    - type: precision_at_10
      value: 8.841000000000001
    - type: precision_at_100
      value: 0.8840000000000001
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_20
      value: 4.42
    - type: precision_at_3
      value: 20.223
    - type: precision_at_5
      value: 14.865
    - type: recall_at_1
      value: 31.935000000000002
    - type: recall_at_10
      value: 88.407
    - type: recall_at_100
      value: 88.407
    - type: recall_at_1000
      value: 88.407
    - type: recall_at_20
      value: 88.407
    - type: recall_at_3
      value: 60.669
    - type: recall_at_5
      value: 74.324
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 48.7848435754835
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 66.7285956124022
    - type: mrr
      value: 79.72233214615486
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 88.73245869702066
    - type: cos_sim_spearman
      value: 87.28451895745819
    - type: euclidean_pearson
      value: 86.44569617089661
    - type: euclidean_spearman
      value: 86.7236628044763
    - type: manhattan_pearson
      value: 86.50853979799092
    - type: manhattan_spearman
      value: 86.75920578302187
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 88.91233766233766
    - type: f1
      value: 88.86315189747688
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 38.7850808112868
    - type: v_measures
      value:
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  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
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      value: 37.37318034700008
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      - 0.3717948730004672
      - 0.36026627188254456
      - 0.3669860108798917
      - 0.36731355824516293
      - 0.375291529012098
      - 0.38550090432534534
      - 0.36577228218454805
      - 0.38601776258844467
      - 0.36845423004088185
      - 0.38992061254062366
      - 0.3717948730004672
      - 0.36026627188254456
      - 0.3669860108798917
      - 0.36731355824516293
      - 0.375291529012098
      - 0.38550090432534534
      - 0.36577228218454805
      - 0.38601776258844467
      - 0.36845423004088185
      - 0.38992061254062366
      - 0.3717948730004672
      - 0.36026627188254456
      - 0.3669860108798917
      - 0.36731355824516293
      - 0.375291529012098
      - 0.38550090432534534
      - 0.36577228218454805
      - 0.38601776258844467
      - 0.36845423004088185
      - 0.38992061254062366
      - 0.3717948730004672
      - 0.36026627188254456
      - 0.3669860108798917
      - 0.36731355824516293
      - 0.375291529012098
      - 0.38550090432534534
      - 0.36577228218454805
      - 0.38601776258844467
      - 0.36845423004088185
      - 0.38992061254062366
      - 0.3717948730004672
      - 0.36026627188254456
      - 0.3669860108798917
      - 0.36731355824516293
      - 0.375291529012098
      - 0.38550090432534534
      - 0.36577228218454805
      - 0.38601776258844467
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 39.232
    - type: map_at_10
      value: 53.04299999999999
    - type: map_at_100
      value: 53.04299999999999
    - type: map_at_1000
      value: 53.04299999999999
    - type: map_at_20
      value: 53.04299999999999
    - type: map_at_3
      value: 48.588
    - type: map_at_5
      value: 51.17699999999999
    - type: mrr_at_1
      value: 49.356
    - type: mrr_at_10
      value: 59.550000000000004
    - type: mrr_at_100
      value: 59.550000000000004
    - type: mrr_at_1000
      value: 59.550000000000004
    - type: mrr_at_20
      value: 59.550000000000004
    - type: mrr_at_3
      value: 56.986000000000004
    - type: mrr_at_5
      value: 58.638999999999996
    - type: ndcg_at_1
      value: 49.356
    - type: ndcg_at_10
      value: 60.156
    - type: ndcg_at_100
      value: 59.714999999999996
    - type: ndcg_at_1000
      value: 59.699000000000005
    - type: ndcg_at_20
      value: 59.831
    - type: ndcg_at_3
      value: 54.75299999999999
    - type: ndcg_at_5
      value: 57.443999999999996
    - type: precision_at_1
      value: 49.356
    - type: precision_at_10
      value: 11.86
    - type: precision_at_100
      value: 1.1860000000000002
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_20
      value: 5.93
    - type: precision_at_3
      value: 26.895999999999997
    - type: precision_at_5
      value: 19.570999999999998
    - type: recall_at_1
      value: 39.232
    - type: recall_at_10
      value: 72.98400000000001
    - type: recall_at_100
      value: 72.98400000000001
    - type: recall_at_1000
      value: 72.98400000000001
    - type: recall_at_20
      value: 72.98400000000001
    - type: recall_at_3
      value: 56.213
    - type: recall_at_5
      value: 64.318
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 37.157000000000004
    - type: map_at_10
      value: 49.512
    - type: map_at_100
      value: 49.512
    - type: map_at_1000
      value: 49.512
    - type: map_at_20
      value: 49.512
    - type: map_at_3
      value: 46.099000000000004
    - type: map_at_5
      value: 48.061
    - type: mrr_at_1
      value: 47.516000000000005
    - type: mrr_at_10
      value: 55.803999999999995
    - type: mrr_at_100
      value: 55.803999999999995
    - type: mrr_at_1000
      value: 55.803999999999995
    - type: mrr_at_20
      value: 55.803999999999995
    - type: mrr_at_3
      value: 53.885000000000005
    - type: mrr_at_5
      value: 54.967999999999996
    - type: ndcg_at_1
      value: 47.516000000000005
    - type: ndcg_at_10
      value: 55.386
    - type: ndcg_at_100
      value: 54.952
    - type: ndcg_at_1000
      value: 54.952
    - type: ndcg_at_20
      value: 55.07300000000001
    - type: ndcg_at_3
      value: 51.458000000000006
    - type: ndcg_at_5
      value: 53.189
    - type: precision_at_1
      value: 47.516000000000005
    - type: precision_at_10
      value: 10.567
    - type: precision_at_100
      value: 1.057
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_20
      value: 5.283
    - type: precision_at_3
      value: 25.393
    - type: precision_at_5
      value: 17.656
    - type: recall_at_1
      value: 37.157000000000004
    - type: recall_at_10
      value: 65.026
    - type: recall_at_100
      value: 65.026
    - type: recall_at_1000
      value: 65.026
    - type: recall_at_20
      value: 65.026
    - type: recall_at_3
      value: 52.36300000000001
    - type: recall_at_5
      value: 57.989999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 48.522999999999996
    - type: map_at_10
      value: 62.844
    - type: map_at_100
      value: 62.844
    - type: map_at_1000
      value: 62.844
    - type: map_at_20
      value: 62.844
    - type: map_at_3
      value: 59.150999999999996
    - type: map_at_5
      value: 61.403
    - type: mrr_at_1
      value: 55.925000000000004
    - type: mrr_at_10
      value: 66.113
    - type: mrr_at_100
      value: 66.113
    - type: mrr_at_1000
      value: 66.113
    - type: mrr_at_20
      value: 66.113
    - type: mrr_at_3
      value: 63.783
    - type: mrr_at_5
      value: 65.212
    - type: ndcg_at_1
      value: 55.925000000000004
    - type: ndcg_at_10
      value: 68.869
    - type: ndcg_at_100
      value: 68.774
    - type: ndcg_at_1000
      value: 68.774
    - type: ndcg_at_20
      value: 68.777
    - type: ndcg_at_3
      value: 63.31400000000001
    - type: ndcg_at_5
      value: 66.247
    - type: precision_at_1
      value: 55.925000000000004
    - type: precision_at_10
      value: 10.997
    - type: precision_at_100
      value: 1.0999999999999999
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 5.498
    - type: precision_at_3
      value: 28.359
    - type: precision_at_5
      value: 19.386
    - type: recall_at_1
      value: 48.522999999999996
    - type: recall_at_10
      value: 83.045
    - type: recall_at_100
      value: 83.045
    - type: recall_at_1000
      value: 83.045
    - type: recall_at_20
      value: 83.045
    - type: recall_at_3
      value: 68.449
    - type: recall_at_5
      value: 75.62100000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 30.726
    - type: map_at_10
      value: 40.433
    - type: map_at_100
      value: 40.433
    - type: map_at_1000
      value: 40.433
    - type: map_at_20
      value: 40.433
    - type: map_at_3
      value: 37.135
    - type: map_at_5
      value: 39.17
    - type: mrr_at_1
      value: 33.672000000000004
    - type: mrr_at_10
      value: 42.836
    - type: mrr_at_100
      value: 42.836
    - type: mrr_at_1000
      value: 42.836
    - type: mrr_at_20
      value: 42.836
    - type: mrr_at_3
      value: 39.755
    - type: mrr_at_5
      value: 41.631
    - type: ndcg_at_1
      value: 33.672000000000004
    - type: ndcg_at_10
      value: 46.092
    - type: ndcg_at_100
      value: 46.092
    - type: ndcg_at_1000
      value: 46.092
    - type: ndcg_at_20
      value: 46.092
    - type: ndcg_at_3
      value: 39.797
    - type: ndcg_at_5
      value: 43.171
    - type: precision_at_1
      value: 33.672000000000004
    - type: precision_at_10
      value: 7.073
    - type: precision_at_100
      value: 0.707
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_20
      value: 3.537
    - type: precision_at_3
      value: 16.648
    - type: precision_at_5
      value: 11.91
    - type: recall_at_1
      value: 30.726
    - type: recall_at_10
      value: 61.24000000000001
    - type: recall_at_100
      value: 61.24000000000001
    - type: recall_at_1000
      value: 61.24000000000001
    - type: recall_at_20
      value: 61.24000000000001
    - type: recall_at_3
      value: 44.557
    - type: recall_at_5
      value: 52.608999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 21.554000000000002
    - type: map_at_10
      value: 31.508000000000003
    - type: map_at_100
      value: 31.508000000000003
    - type: map_at_1000
      value: 31.508000000000003
    - type: map_at_20
      value: 31.508000000000003
    - type: map_at_3
      value: 28.225
    - type: map_at_5
      value: 30.043
    - type: mrr_at_1
      value: 27.114
    - type: mrr_at_10
      value: 36.631
    - type: mrr_at_100
      value: 36.631
    - type: mrr_at_1000
      value: 36.631
    - type: mrr_at_20
      value: 36.631
    - type: mrr_at_3
      value: 34.059
    - type: mrr_at_5
      value: 35.601
    - type: ndcg_at_1
      value: 27.114
    - type: ndcg_at_10
      value: 37.592999999999996
    - type: ndcg_at_100
      value: 37.588
    - type: ndcg_at_1000
      value: 37.588
    - type: ndcg_at_20
      value: 37.588
    - type: ndcg_at_3
      value: 32.038
    - type: ndcg_at_5
      value: 34.689
    - type: precision_at_1
      value: 27.114
    - type: precision_at_10
      value: 7.090000000000001
    - type: precision_at_100
      value: 0.709
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_20
      value: 3.5450000000000004
    - type: precision_at_3
      value: 15.506
    - type: precision_at_5
      value: 11.393
    - type: recall_at_1
      value: 21.554000000000002
    - type: recall_at_10
      value: 50.879
    - type: recall_at_100
      value: 50.879
    - type: recall_at_1000
      value: 50.879
    - type: recall_at_20
      value: 50.879
    - type: recall_at_3
      value: 35.827999999999996
    - type: recall_at_5
      value: 42.476
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 35.36
    - type: map_at_10
      value: 48.483
    - type: map_at_100
      value: 48.483
    - type: map_at_1000
      value: 48.483
    - type: map_at_20
      value: 48.483
    - type: map_at_3
      value: 44.639
    - type: map_at_5
      value: 46.698
    - type: mrr_at_1
      value: 43.985
    - type: mrr_at_10
      value: 54.039
    - type: mrr_at_100
      value: 54.039
    - type: mrr_at_1000
      value: 54.039
    - type: mrr_at_20
      value: 54.039
    - type: mrr_at_3
      value: 51.54
    - type: mrr_at_5
      value: 52.859
    - type: ndcg_at_1
      value: 43.985
    - type: ndcg_at_10
      value: 55.069
    - type: ndcg_at_100
      value: 54.967
    - type: ndcg_at_1000
      value: 54.967
    - type: ndcg_at_20
      value: 54.996
    - type: ndcg_at_3
      value: 49.544
    - type: ndcg_at_5
      value: 51.932
    - type: precision_at_1
      value: 43.985
    - type: precision_at_10
      value: 10.202
    - type: precision_at_100
      value: 1.02
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_20
      value: 5.101
    - type: precision_at_3
      value: 23.933
    - type: precision_at_5
      value: 16.901
    - type: recall_at_1
      value: 35.36
    - type: recall_at_10
      value: 68.806
    - type: recall_at_100
      value: 68.806
    - type: recall_at_1000
      value: 68.806
    - type: recall_at_20
      value: 68.806
    - type: recall_at_3
      value: 52.714000000000006
    - type: recall_at_5
      value: 59.168
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 32.431
    - type: map_at_10
      value: 45.421
    - type: map_at_100
      value: 45.421
    - type: map_at_1000
      value: 45.421
    - type: map_at_20
      value: 45.421
    - type: map_at_3
      value: 41.82
    - type: map_at_5
      value: 43.692
    - type: mrr_at_1
      value: 41.096
    - type: mrr_at_10
      value: 51.293
    - type: mrr_at_100
      value: 51.293
    - type: mrr_at_1000
      value: 51.293
    - type: mrr_at_20
      value: 51.293
    - type: mrr_at_3
      value: 49.049
    - type: mrr_at_5
      value: 50.327
    - type: ndcg_at_1
      value: 41.096
    - type: ndcg_at_10
      value: 52.032999999999994
    - type: ndcg_at_100
      value: 51.903
    - type: ndcg_at_1000
      value: 51.897999999999996
    - type: ndcg_at_20
      value: 51.942
    - type: ndcg_at_3
      value: 47.024
    - type: ndcg_at_5
      value: 49.071
    - type: precision_at_1
      value: 41.096
    - type: precision_at_10
      value: 9.725999999999999
    - type: precision_at_100
      value: 0.9730000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_20
      value: 4.8629999999999995
    - type: precision_at_3
      value: 23.097
    - type: precision_at_5
      value: 16.096
    - type: recall_at_1
      value: 32.431
    - type: recall_at_10
      value: 65.42999999999999
    - type: recall_at_100
      value: 65.42999999999999
    - type: recall_at_1000
      value: 65.42999999999999
    - type: recall_at_20
      value: 65.42999999999999
    - type: recall_at_3
      value: 50.856
    - type: recall_at_5
      value: 56.846
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 32.074749999999995
    - type: map_at_10
      value: 43.474
    - type: map_at_100
      value: 43.474
    - type: map_at_1000
      value: 43.474
    - type: map_at_20
      value: 43.474
    - type: map_at_3
      value: 40.10458333333333
    - type: map_at_5
      value: 42.010749999999994
    - type: mrr_at_1
      value: 38.60425
    - type: mrr_at_10
      value: 48.05550000000001
    - type: mrr_at_100
      value: 48.05550000000001
    - type: mrr_at_1000
      value: 48.05550000000001
    - type: mrr_at_20
      value: 48.05550000000001
    - type: mrr_at_3
      value: 45.58083333333334
    - type: mrr_at_5
      value: 47.04750000000001
    - type: ndcg_at_1
      value: 38.60425
    - type: ndcg_at_10
      value: 49.51958333333334
    - type: ndcg_at_100
      value: 49.3385
    - type: ndcg_at_1000
      value: 49.33491666666667
    - type: ndcg_at_20
      value: 49.393
    - type: ndcg_at_3
      value: 44.32699999999999
    - type: ndcg_at_5
      value: 46.81008333333333
    - type: precision_at_1
      value: 38.60425
    - type: precision_at_10
      value: 8.800666666666668
    - type: precision_at_100
      value: 0.8800833333333334
    - type: precision_at_1000
      value: 0.08808333333333335
    - type: precision_at_20
      value: 4.400333333333334
    - type: precision_at_3
      value: 20.723166666666664
    - type: precision_at_5
      value: 14.65683333333333
    - type: recall_at_1
      value: 32.074749999999995
    - type: recall_at_10
      value: 62.5025
    - type: recall_at_100
      value: 62.5025
    - type: recall_at_1000
      value: 62.5025
    - type: recall_at_20
      value: 62.5025
    - type: recall_at_3
      value: 47.81091666666667
    - type: recall_at_5
      value: 54.38974999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 28.758
    - type: map_at_10
      value: 37.633
    - type: map_at_100
      value: 37.633
    - type: map_at_1000
      value: 37.633
    - type: map_at_20
      value: 37.633
    - type: map_at_3
      value: 34.865
    - type: map_at_5
      value: 36.437999999999995
    - type: mrr_at_1
      value: 32.208999999999996
    - type: mrr_at_10
      value: 40.598
    - type: mrr_at_100
      value: 40.598
    - type: mrr_at_1000
      value: 40.598
    - type: mrr_at_20
      value: 40.598
    - type: mrr_at_3
      value: 37.935
    - type: mrr_at_5
      value: 39.476
    - type: ndcg_at_1
      value: 32.208999999999996
    - type: ndcg_at_10
      value: 42.798
    - type: ndcg_at_100
      value: 42.768
    - type: ndcg_at_1000
      value: 42.768
    - type: ndcg_at_20
      value: 42.768
    - type: ndcg_at_3
      value: 37.651
    - type: ndcg_at_5
      value: 40.172999999999995
    - type: precision_at_1
      value: 32.208999999999996
    - type: precision_at_10
      value: 6.84
    - type: precision_at_100
      value: 0.6839999999999999
    - type: precision_at_1000
      value: 0.068
    - type: precision_at_20
      value: 3.42
    - type: precision_at_3
      value: 16.258
    - type: precision_at_5
      value: 11.472
    - type: recall_at_1
      value: 28.758
    - type: recall_at_10
      value: 55.55799999999999
    - type: recall_at_100
      value: 55.55799999999999
    - type: recall_at_1000
      value: 55.55799999999999
    - type: recall_at_20
      value: 55.55799999999999
    - type: recall_at_3
      value: 41.488
    - type: recall_at_5
      value: 47.659
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 21.088
    - type: map_at_10
      value: 30.297
    - type: map_at_100
      value: 30.297
    - type: map_at_1000
      value: 30.297
    - type: map_at_20
      value: 30.297
    - type: map_at_3
      value: 27.376
    - type: map_at_5
      value: 29.064
    - type: mrr_at_1
      value: 26.358999999999998
    - type: mrr_at_10
      value: 34.996
    - type: mrr_at_100
      value: 34.996
    - type: mrr_at_1000
      value: 34.996
    - type: mrr_at_20
      value: 34.996
    - type: mrr_at_3
      value: 32.467
    - type: mrr_at_5
      value: 33.944
    - type: ndcg_at_1
      value: 26.358999999999998
    - type: ndcg_at_10
      value: 35.851
    - type: ndcg_at_100
      value: 35.731
    - type: ndcg_at_1000
      value: 35.729
    - type: ndcg_at_20
      value: 35.77
    - type: ndcg_at_3
      value: 30.97
    - type: ndcg_at_5
      value: 33.312000000000005
    - type: precision_at_1
      value: 26.358999999999998
    - type: precision_at_10
      value: 6.641
    - type: precision_at_100
      value: 0.664
    - type: precision_at_1000
      value: 0.066
    - type: precision_at_20
      value: 3.321
    - type: precision_at_3
      value: 14.923
    - type: precision_at_5
      value: 10.86
    - type: recall_at_1
      value: 21.088
    - type: recall_at_10
      value: 47.818
    - type: recall_at_100
      value: 47.818
    - type: recall_at_1000
      value: 47.818
    - type: recall_at_20
      value: 47.818
    - type: recall_at_3
      value: 33.815
    - type: recall_at_5
      value: 39.973
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 33.579
    - type: map_at_10
      value: 44.875
    - type: map_at_100
      value: 44.875
    - type: map_at_1000
      value: 44.875
    - type: map_at_20
      value: 44.875
    - type: map_at_3
      value: 41.64
    - type: map_at_5
      value: 43.433
    - type: mrr_at_1
      value: 40.111999999999995
    - type: mrr_at_10
      value: 49.586999999999996
    - type: mrr_at_100
      value: 49.586999999999996
    - type: mrr_at_1000
      value: 49.586999999999996
    - type: mrr_at_20
      value: 49.586999999999996
    - type: mrr_at_3
      value: 47.233000000000004
    - type: mrr_at_5
      value: 48.613
    - type: ndcg_at_1
      value: 40.111999999999995
    - type: ndcg_at_10
      value: 50.836000000000006
    - type: ndcg_at_100
      value: 50.822
    - type: ndcg_at_1000
      value: 50.822
    - type: ndcg_at_20
      value: 50.822
    - type: ndcg_at_3
      value: 45.737
    - type: ndcg_at_5
      value: 48.081
    - type: precision_at_1
      value: 40.111999999999995
    - type: precision_at_10
      value: 8.674999999999999
    - type: precision_at_100
      value: 0.868
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_20
      value: 4.338
    - type: precision_at_3
      value: 21.02
    - type: precision_at_5
      value: 14.682999999999998
    - type: recall_at_1
      value: 33.579
    - type: recall_at_10
      value: 64.02600000000001
    - type: recall_at_100
      value: 64.02600000000001
    - type: recall_at_1000
      value: 64.02600000000001
    - type: recall_at_20
      value: 64.02600000000001
    - type: recall_at_3
      value: 49.788
    - type: recall_at_5
      value: 55.931
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 31.497999999999998
    - type: map_at_10
      value: 43.456
    - type: map_at_100
      value: 43.456
    - type: map_at_1000
      value: 43.456
    - type: map_at_20
      value: 43.456
    - type: map_at_3
      value: 40.125
    - type: map_at_5
      value: 41.829
    - type: mrr_at_1
      value: 38.735
    - type: mrr_at_10
      value: 48.756
    - type: mrr_at_100
      value: 48.756
    - type: mrr_at_1000
      value: 48.756
    - type: mrr_at_20
      value: 48.756
    - type: mrr_at_3
      value: 46.113
    - type: mrr_at_5
      value: 47.684
    - type: ndcg_at_1
      value: 38.735
    - type: ndcg_at_10
      value: 50.241
    - type: ndcg_at_100
      value: 49.458
    - type: ndcg_at_1000
      value: 49.437999999999995
    - type: ndcg_at_20
      value: 49.756
    - type: ndcg_at_3
      value: 45.14
    - type: ndcg_at_5
      value: 47.406
    - type: precision_at_1
      value: 38.735
    - type: precision_at_10
      value: 9.763
    - type: precision_at_100
      value: 0.976
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 4.881
    - type: precision_at_3
      value: 21.673000000000002
    - type: precision_at_5
      value: 15.455
    - type: recall_at_1
      value: 31.497999999999998
    - type: recall_at_10
      value: 62.568999999999996
    - type: recall_at_100
      value: 62.568999999999996
    - type: recall_at_1000
      value: 62.568999999999996
    - type: recall_at_20
      value: 62.568999999999996
    - type: recall_at_3
      value: 47.842
    - type: recall_at_5
      value: 54.159
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 24.991
    - type: map_at_10
      value: 34.183
    - type: map_at_100
      value: 34.183
    - type: map_at_1000
      value: 34.183
    - type: map_at_20
      value: 34.183
    - type: map_at_3
      value: 31.592
    - type: map_at_5
      value: 33.121
    - type: mrr_at_1
      value: 27.172
    - type: mrr_at_10
      value: 36.463
    - type: mrr_at_100
      value: 36.463
    - type: mrr_at_1000
      value: 36.463
    - type: mrr_at_20
      value: 36.463
    - type: mrr_at_3
      value: 34.165
    - type: mrr_at_5
      value: 35.616
    - type: ndcg_at_1
      value: 27.172
    - type: ndcg_at_10
      value: 39.311
    - type: ndcg_at_100
      value: 39.292
    - type: ndcg_at_1000
      value: 39.292
    - type: ndcg_at_20
      value: 39.301
    - type: ndcg_at_3
      value: 34.498
    - type: ndcg_at_5
      value: 37.006
    - type: precision_at_1
      value: 27.172
    - type: precision_at_10
      value: 6.174
    - type: precision_at_100
      value: 0.617
    - type: precision_at_1000
      value: 0.062
    - type: precision_at_20
      value: 3.087
    - type: precision_at_3
      value: 14.972
    - type: precision_at_5
      value: 10.499
    - type: recall_at_1
      value: 24.991
    - type: recall_at_10
      value: 52.649
    - type: recall_at_100
      value: 52.649
    - type: recall_at_1000
      value: 52.649
    - type: recall_at_20
      value: 52.649
    - type: recall_at_3
      value: 39.818
    - type: recall_at_5
      value: 45.927
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 12.475999999999999
    - type: map_at_10
      value: 22.999
    - type: map_at_100
      value: 22.999
    - type: map_at_1000
      value: 22.999
    - type: map_at_20
      value: 22.999
    - type: map_at_3
      value: 18.804000000000002
    - type: map_at_5
      value: 20.987000000000002
    - type: mrr_at_1
      value: 28.404
    - type: mrr_at_10
      value: 42.335
    - type: mrr_at_100
      value: 42.335
    - type: mrr_at_1000
      value: 42.335
    - type: mrr_at_20
      value: 42.335
    - type: mrr_at_3
      value: 39.11
    - type: mrr_at_5
      value: 40.953
    - type: ndcg_at_1
      value: 28.404
    - type: ndcg_at_10
      value: 32.467
    - type: ndcg_at_100
      value: 32.467
    - type: ndcg_at_1000
      value: 32.467
    - type: ndcg_at_20
      value: 32.467
    - type: ndcg_at_3
      value: 26.334999999999997
    - type: ndcg_at_5
      value: 28.493000000000002
    - type: precision_at_1
      value: 28.404
    - type: precision_at_10
      value: 10.43
    - type: precision_at_100
      value: 1.043
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 5.215
    - type: precision_at_3
      value: 20.13
    - type: precision_at_5
      value: 15.595999999999998
    - type: recall_at_1
      value: 12.475999999999999
    - type: recall_at_10
      value: 39.757
    - type: recall_at_100
      value: 39.757
    - type: recall_at_1000
      value: 39.757
    - type: recall_at_20
      value: 39.757
    - type: recall_at_3
      value: 24.695
    - type: recall_at_5
      value: 30.864000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 9.261999999999999
    - type: map_at_10
      value: 23.807000000000002
    - type: map_at_100
      value: 23.807000000000002
    - type: map_at_1000
      value: 23.807000000000002
    - type: map_at_20
      value: 23.807000000000002
    - type: map_at_3
      value: 15.776000000000002
    - type: map_at_5
      value: 19.17
    - type: mrr_at_1
      value: 71.75
    - type: mrr_at_10
      value: 79.959
    - type: mrr_at_100
      value: 79.959
    - type: mrr_at_1000
      value: 79.959
    - type: mrr_at_20
      value: 79.959
    - type: mrr_at_3
      value: 78.625
    - type: mrr_at_5
      value: 79.412
    - type: ndcg_at_1
      value: 59.5
    - type: ndcg_at_10
      value: 48.988
    - type: ndcg_at_100
      value: 37.452000000000005
    - type: ndcg_at_1000
      value: 37.32
    - type: ndcg_at_20
      value: 41.387
    - type: ndcg_at_3
      value: 52.567
    - type: ndcg_at_5
      value: 50.649
    - type: precision_at_1
      value: 71.75
    - type: precision_at_10
      value: 40.425
    - type: precision_at_100
      value: 4.042
    - type: precision_at_1000
      value: 0.404
    - type: precision_at_20
      value: 20.212
    - type: precision_at_3
      value: 57.75
    - type: precision_at_5
      value: 50.349999999999994
    - type: recall_at_1
      value: 9.261999999999999
    - type: recall_at_10
      value: 30.329
    - type: recall_at_100
      value: 30.329
    - type: recall_at_1000
      value: 30.329
    - type: recall_at_20
      value: 30.329
    - type: recall_at_3
      value: 17.422
    - type: recall_at_5
      value: 22.598
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 52.014999999999986
    - type: f1
      value: 47.33036786740981
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 82.00800000000001
    - type: map_at_10
      value: 88.02799999999999
    - type: map_at_100
      value: 88.02799999999999
    - type: map_at_1000
      value: 88.02799999999999
    - type: map_at_20
      value: 88.02799999999999
    - type: map_at_3
      value: 87.249
    - type: map_at_5
      value: 87.78399999999999
    - type: mrr_at_1
      value: 88.299
    - type: mrr_at_10
      value: 92.92
    - type: mrr_at_100
      value: 92.92
    - type: mrr_at_1000
      value: 92.92
    - type: mrr_at_20
      value: 92.92
    - type: mrr_at_3
      value: 92.56400000000001
    - type: mrr_at_5
      value: 92.83200000000001
    - type: ndcg_at_1
      value: 88.299
    - type: ndcg_at_10
      value: 90.88000000000001
    - type: ndcg_at_100
      value: 90.879
    - type: ndcg_at_1000
      value: 90.879
    - type: ndcg_at_20
      value: 90.879
    - type: ndcg_at_3
      value: 89.85499999999999
    - type: ndcg_at_5
      value: 90.485
    - type: precision_at_1
      value: 88.299
    - type: precision_at_10
      value: 10.522
    - type: precision_at_100
      value: 1.052
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_20
      value: 5.261
    - type: precision_at_3
      value: 33.573
    - type: precision_at_5
      value: 20.633000000000003
    - type: recall_at_1
      value: 82.00800000000001
    - type: recall_at_10
      value: 94.952
    - type: recall_at_100
      value: 94.952
    - type: recall_at_1000
      value: 94.952
    - type: recall_at_20
      value: 94.952
    - type: recall_at_3
      value: 92.089
    - type: recall_at_5
      value: 93.794
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 26.857
    - type: map_at_10
      value: 44.645
    - type: map_at_100
      value: 44.645
    - type: map_at_1000
      value: 44.645
    - type: map_at_20
      value: 44.645
    - type: map_at_3
      value: 38.166
    - type: map_at_5
      value: 41.992000000000004
    - type: mrr_at_1
      value: 50.309000000000005
    - type: mrr_at_10
      value: 59.59100000000001
    - type: mrr_at_100
      value: 59.59100000000001
    - type: mrr_at_1000
      value: 59.59100000000001
    - type: mrr_at_20
      value: 59.59100000000001
    - type: mrr_at_3
      value: 56.97
    - type: mrr_at_5
      value: 58.498000000000005
    - type: ndcg_at_1
      value: 50.309000000000005
    - type: ndcg_at_10
      value: 53.221
    - type: ndcg_at_100
      value: 53.15800000000001
    - type: ndcg_at_1000
      value: 53.15800000000001
    - type: ndcg_at_20
      value: 53.15800000000001
    - type: ndcg_at_3
      value: 47.506
    - type: ndcg_at_5
      value: 49.922
    - type: precision_at_1
      value: 50.309000000000005
    - type: precision_at_10
      value: 14.985000000000001
    - type: precision_at_100
      value: 1.498
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_20
      value: 7.492
    - type: precision_at_3
      value: 31.635999999999996
    - type: precision_at_5
      value: 24.043
    - type: recall_at_1
      value: 26.857
    - type: recall_at_10
      value: 62.051
    - type: recall_at_100
      value: 62.051
    - type: recall_at_1000
      value: 62.051
    - type: recall_at_20
      value: 62.051
    - type: recall_at_3
      value: 42.966
    - type: recall_at_5
      value: 51.943
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 40.891
    - type: map_at_10
      value: 70.431
    - type: map_at_100
      value: 70.431
    - type: map_at_1000
      value: 70.431
    - type: map_at_20
      value: 70.431
    - type: map_at_3
      value: 66.704
    - type: map_at_5
      value: 69.179
    - type: mrr_at_1
      value: 81.783
    - type: mrr_at_10
      value: 87.368
    - type: mrr_at_100
      value: 87.368
    - type: mrr_at_1000
      value: 87.368
    - type: mrr_at_20
      value: 87.368
    - type: mrr_at_3
      value: 86.59700000000001
    - type: mrr_at_5
      value: 87.128
    - type: ndcg_at_1
      value: 81.783
    - type: ndcg_at_10
      value: 77.697
    - type: ndcg_at_100
      value: 77.697
    - type: ndcg_at_1000
      value: 77.697
    - type: ndcg_at_20
      value: 77.697
    - type: ndcg_at_3
      value: 72.688
    - type: ndcg_at_5
      value: 75.69200000000001
    - type: precision_at_1
      value: 81.783
    - type: precision_at_10
      value: 16.488
    - type: precision_at_100
      value: 1.649
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_20
      value: 8.244
    - type: precision_at_3
      value: 47.693000000000005
    - type: precision_at_5
      value: 30.976
    - type: recall_at_1
      value: 40.891
    - type: recall_at_10
      value: 82.438
    - type: recall_at_100
      value: 82.438
    - type: recall_at_1000
      value: 82.438
    - type: recall_at_20
      value: 82.438
    - type: recall_at_3
      value: 71.54
    - type: recall_at_5
      value: 77.441
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 89.47240000000001
    - type: ap
      value: 85.75618304701787
    - type: f1
      value: 89.44156774176075
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 19.941
    - type: map_at_10
      value: 33.108
    - type: map_at_100
      value: 33.108
    - type: map_at_1000
      value: 33.108
    - type: map_at_20
      value: 33.108
    - type: map_at_3
      value: 28.716
    - type: map_at_5
      value: 31.255
    - type: mrr_at_1
      value: 20.458000000000002
    - type: mrr_at_10
      value: 33.646
    - type: mrr_at_100
      value: 33.646
    - type: mrr_at_1000
      value: 33.646
    - type: mrr_at_20
      value: 33.646
    - type: mrr_at_3
      value: 29.360000000000003
    - type: mrr_at_5
      value: 31.849
    - type: ndcg_at_1
      value: 20.458000000000002
    - type: ndcg_at_10
      value: 40.664
    - type: ndcg_at_100
      value: 40.664
    - type: ndcg_at_1000
      value: 40.664
    - type: ndcg_at_20
      value: 40.664
    - type: ndcg_at_3
      value: 31.733
    - type: ndcg_at_5
      value: 36.266999999999996
    - type: precision_at_1
      value: 20.458000000000002
    - type: precision_at_10
      value: 6.703
    - type: precision_at_100
      value: 0.67
    - type: precision_at_1000
      value: 0.067
    - type: precision_at_20
      value: 3.3520000000000003
    - type: precision_at_3
      value: 13.777000000000001
    - type: precision_at_5
      value: 10.564
    - type: recall_at_1
      value: 19.941
    - type: recall_at_10
      value: 64.103
    - type: recall_at_100
      value: 64.103
    - type: recall_at_1000
      value: 64.103
    - type: recall_at_20
      value: 64.103
    - type: recall_at_3
      value: 39.800999999999995
    - type: recall_at_5
      value: 50.727999999999994
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 96.45690834473322
    - type: f1
      value: 96.19980363353172
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 85.38075695394436
    - type: f1
      value: 71.33409850817071
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 80.12104909213183
    - type: f1
      value: 77.26691038674358
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 82.69670477471418
    - type: f1
      value: 82.31935226516424
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.733209733023
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 32.325298069936835
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  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.511595472837335
    - type: mrr
      value: 33.73044905745997
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 7.0760000000000005
    - type: map_at_10
      value: 16.039
    - type: map_at_100
      value: 16.039
    - type: map_at_1000
      value: 16.039
    - type: map_at_20
      value: 16.039
    - type: map_at_3
      value: 11.408
    - type: map_at_5
      value: 13.547
    - type: mrr_at_1
      value: 53.559999999999995
    - type: mrr_at_10
      value: 61.531000000000006
    - type: mrr_at_100
      value: 61.531000000000006
    - type: mrr_at_1000
      value: 61.531000000000006
    - type: mrr_at_20
      value: 61.531000000000006
    - type: mrr_at_3
      value: 59.236
    - type: mrr_at_5
      value: 60.49
    - type: ndcg_at_1
      value: 51.083999999999996
    - type: ndcg_at_10
      value: 41.332
    - type: ndcg_at_100
      value: 27.083000000000002
    - type: ndcg_at_1000
      value: 26.619
    - type: ndcg_at_20
      value: 33.188
    - type: ndcg_at_3
      value: 46.605999999999995
    - type: ndcg_at_5
      value: 44.362
    - type: precision_at_1
      value: 52.941
    - type: precision_at_10
      value: 30.65
    - type: precision_at_100
      value: 3.065
    - type: precision_at_1000
      value: 0.307
    - type: precision_at_20
      value: 15.325
    - type: precision_at_3
      value: 43.447
    - type: precision_at_5
      value: 38.266
    - type: recall_at_1
      value: 7.0760000000000005
    - type: recall_at_10
      value: 20.929000000000002
    - type: recall_at_100
      value: 20.929000000000002
    - type: recall_at_1000
      value: 20.929000000000002
    - type: recall_at_20
      value: 20.929000000000002
    - type: recall_at_3
      value: 12.601
    - type: recall_at_5
      value: 15.955
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 39.204
    - type: map_at_10
      value: 56.808
    - type: map_at_100
      value: 56.808
    - type: map_at_1000
      value: 56.808
    - type: map_at_20
      value: 56.808
    - type: map_at_3
      value: 52.471999999999994
    - type: map_at_5
      value: 55.191
    - type: mrr_at_1
      value: 44.032
    - type: mrr_at_10
      value: 59.158
    - type: mrr_at_100
      value: 59.158
    - type: mrr_at_1000
      value: 59.158
    - type: mrr_at_20
      value: 59.158
    - type: mrr_at_3
      value: 55.948
    - type: mrr_at_5
      value: 57.96
    - type: ndcg_at_1
      value: 44.032
    - type: ndcg_at_10
      value: 64.672
    - type: ndcg_at_100
      value: 64.672
    - type: ndcg_at_1000
      value: 64.672
    - type: ndcg_at_20
      value: 64.672
    - type: ndcg_at_3
      value: 56.955999999999996
    - type: ndcg_at_5
      value: 61.278999999999996
    - type: precision_at_1
      value: 44.032
    - type: precision_at_10
      value: 10.295
    - type: precision_at_100
      value: 1.03
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_20
      value: 5.148
    - type: precision_at_3
      value: 25.83
    - type: precision_at_5
      value: 18.053
    - type: recall_at_1
      value: 39.204
    - type: recall_at_10
      value: 85.936
    - type: recall_at_100
      value: 85.936
    - type: recall_at_1000
      value: 85.936
    - type: recall_at_20
      value: 85.936
    - type: recall_at_3
      value: 66.387
    - type: recall_at_5
      value: 76.238
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 71.068
    - type: map_at_10
      value: 85.271
    - type: map_at_100
      value: 85.271
    - type: map_at_1000
      value: 85.271
    - type: map_at_20
      value: 85.271
    - type: map_at_3
      value: 82.23899999999999
    - type: map_at_5
      value: 84.165
    - type: mrr_at_1
      value: 81.85
    - type: mrr_at_10
      value: 87.856
    - type: mrr_at_100
      value: 87.856
    - type: mrr_at_1000
      value: 87.856
    - type: mrr_at_20
      value: 87.856
    - type: mrr_at_3
      value: 86.925
    - type: mrr_at_5
      value: 87.559
    - type: ndcg_at_1
      value: 81.89
    - type: ndcg_at_10
      value: 88.856
    - type: ndcg_at_100
      value: 88.723
    - type: ndcg_at_1000
      value: 88.723
    - type: ndcg_at_20
      value: 88.74300000000001
    - type: ndcg_at_3
      value: 86.05199999999999
    - type: ndcg_at_5
      value: 87.61
    - type: precision_at_1
      value: 81.89
    - type: precision_at_10
      value: 13.569999999999999
    - type: precision_at_100
      value: 1.357
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_20
      value: 6.784999999999999
    - type: precision_at_3
      value: 37.807
    - type: precision_at_5
      value: 24.908
    - type: recall_at_1
      value: 71.068
    - type: recall_at_10
      value: 95.797
    - type: recall_at_100
      value: 95.797
    - type: recall_at_1000
      value: 95.797
    - type: recall_at_20
      value: 95.797
    - type: recall_at_3
      value: 87.65899999999999
    - type: recall_at_5
      value: 92.107
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 62.16385792305745
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
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      value: 65.96296778394698
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      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
      - 0.6994519018160104
      - 0.6685310786302858
      - 0.6560344637869603
      - 0.4053977970605211
      - 0.7423583342619767
      - 0.6657872853200192
      - 0.4487425514322897
      - 0.7791528368405061
      - 0.7406529421724692
      - 0.7901875870736593
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 5.433000000000001
    - type: map_at_10
      value: 13.991000000000001
    - type: map_at_100
      value: 13.991000000000001
    - type: map_at_1000
      value: 13.991000000000001
    - type: map_at_20
      value: 13.991000000000001
    - type: map_at_3
      value: 9.708
    - type: map_at_5
      value: 11.849
    - type: mrr_at_1
      value: 26.8
    - type: mrr_at_10
      value: 38.012
    - type: mrr_at_100
      value: 38.012
    - type: mrr_at_1000
      value: 38.012
    - type: mrr_at_20
      value: 38.012
    - type: mrr_at_3
      value: 34.449999999999996
    - type: mrr_at_5
      value: 36.59
    - type: ndcg_at_1
      value: 26.8
    - type: ndcg_at_10
      value: 23.006999999999998
    - type: ndcg_at_100
      value: 23.006999999999998
    - type: ndcg_at_1000
      value: 23.006999999999998
    - type: ndcg_at_20
      value: 23.006999999999998
    - type: ndcg_at_3
      value: 21.386
    - type: ndcg_at_5
      value: 19.046
    - type: precision_at_1
      value: 26.8
    - type: precision_at_10
      value: 12.01
    - type: precision_at_100
      value: 1.201
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 6.005
    - type: precision_at_3
      value: 19.833000000000002
    - type: precision_at_5
      value: 16.84
    - type: recall_at_1
      value: 5.433000000000001
    - type: recall_at_10
      value: 24.34
    - type: recall_at_100
      value: 24.34
    - type: recall_at_1000
      value: 24.34
    - type: recall_at_20
      value: 24.34
    - type: recall_at_3
      value: 12.058
    - type: recall_at_5
      value: 17.058
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 84.84178272773948
    - type: cos_sim_spearman
      value: 82.32746830315172
    - type: euclidean_pearson
      value: 82.11599650658388
    - type: euclidean_spearman
      value: 82.38102437050075
    - type: manhattan_pearson
      value: 82.07071847892156
    - type: manhattan_spearman
      value: 82.35710877093594
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 86.86916828280668
    - type: cos_sim_spearman
      value: 79.69553254808825
    - type: euclidean_pearson
      value: 82.86582224049857
    - type: euclidean_spearman
      value: 79.1765897124049
    - type: manhattan_pearson
      value: 83.15978473993391
    - type: manhattan_spearman
      value: 79.54192003597332
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 88.7719804239987
    - type: cos_sim_spearman
      value: 89.20788765830103
    - type: euclidean_pearson
      value: 88.67624029627581
    - type: euclidean_spearman
      value: 89.15058058277351
    - type: manhattan_pearson
      value: 88.43477620818435
    - type: manhattan_spearman
      value: 89.01994285052193
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 87.04733612348426
    - type: cos_sim_spearman
      value: 86.0120242985069
    - type: euclidean_pearson
      value: 86.07045247599824
    - type: euclidean_spearman
      value: 86.22185577032168
    - type: manhattan_pearson
      value: 85.79555943035328
    - type: manhattan_spearman
      value: 86.13821651705776
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 89.395594115739
    - type: cos_sim_spearman
      value: 89.70312809978681
    - type: euclidean_pearson
      value: 89.10137224981938
    - type: euclidean_spearman
      value: 89.74149793061072
    - type: manhattan_pearson
      value: 89.06144914118401
    - type: manhattan_spearman
      value: 89.78489015365638
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 86.1720394205624
    - type: cos_sim_spearman
      value: 87.67900288178751
    - type: euclidean_pearson
      value: 86.73052291563968
    - type: euclidean_spearman
      value: 87.49116803671033
    - type: manhattan_pearson
      value: 86.79988999910331
    - type: manhattan_spearman
      value: 87.57540934207157
  - 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: 88.75286004155564
    - type: cos_sim_spearman
      value: 88.03161515281518
    - type: euclidean_pearson
      value: 88.55464128719427
    - type: euclidean_spearman
      value: 87.78041200668837
    - type: manhattan_pearson
      value: 88.18469209314583
    - type: manhattan_spearman
      value: 87.31602253333598
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 70.48372140035973
    - type: cos_sim_spearman
      value: 70.16107814793419
    - type: euclidean_pearson
      value: 69.65789511103976
    - type: euclidean_spearman
      value: 68.92441073988654
    - type: manhattan_pearson
      value: 69.55306498752127
    - type: manhattan_spearman
      value: 68.82186378798527
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 87.43017430741797
    - type: cos_sim_spearman
      value: 88.14675226940803
    - type: euclidean_pearson
      value: 87.33329490848514
    - type: euclidean_spearman
      value: 87.94164481397011
    - type: manhattan_pearson
      value: 87.19303598684772
    - type: manhattan_spearman
      value: 87.86899889639051
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.03073019943413
    - type: mrr
      value: 96.67456726280255
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 64.328
    - type: map_at_10
      value: 75.046
    - type: map_at_100
      value: 75.046
    - type: map_at_1000
      value: 75.046
    - type: map_at_20
      value: 75.046
    - type: map_at_3
      value: 72.42
    - type: map_at_5
      value: 73.88900000000001
    - type: mrr_at_1
      value: 67.667
    - type: mrr_at_10
      value: 76.19200000000001
    - type: mrr_at_100
      value: 76.19200000000001
    - type: mrr_at_1000
      value: 76.19200000000001
    - type: mrr_at_20
      value: 76.19200000000001
    - type: mrr_at_3
      value: 74.556
    - type: mrr_at_5
      value: 75.372
    - type: ndcg_at_1
      value: 67.667
    - type: ndcg_at_10
      value: 79.621
    - type: ndcg_at_100
      value: 79.621
    - type: ndcg_at_1000
      value: 79.621
    - type: ndcg_at_20
      value: 79.621
    - type: ndcg_at_3
      value: 75.506
    - type: ndcg_at_5
      value: 77.269
    - type: precision_at_1
      value: 67.667
    - type: precision_at_10
      value: 10.467
    - type: precision_at_100
      value: 1.047
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_20
      value: 5.2330000000000005
    - type: precision_at_3
      value: 29.444
    - type: precision_at_5
      value: 19.133
    - type: recall_at_1
      value: 64.328
    - type: recall_at_10
      value: 92.389
    - type: recall_at_100
      value: 92.389
    - type: recall_at_1000
      value: 92.389
    - type: recall_at_20
      value: 92.389
    - type: recall_at_3
      value: 81.183
    - type: recall_at_5
      value: 85.60600000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.83762376237624
    - type: cos_sim_ap
      value: 96.51580702723564
    - type: cos_sim_f1
      value: 91.63265306122449
    - type: cos_sim_precision
      value: 93.54166666666667
    - type: cos_sim_recall
      value: 89.8
    - type: dot_accuracy
      value: 99.73663366336633
    - type: dot_ap
      value: 93.5764284433306
    - type: dot_f1
      value: 86.56565656565655
    - type: dot_precision
      value: 87.44897959183675
    - type: dot_recall
      value: 85.7
    - type: euclidean_accuracy
      value: 99.84059405940594
    - type: euclidean_ap
      value: 96.4738308210008
    - type: euclidean_f1
      value: 91.76470588235294
    - type: euclidean_precision
      value: 93.92670157068062
    - type: euclidean_recall
      value: 89.7
    - type: manhattan_accuracy
      value: 99.84356435643565
    - type: manhattan_ap
      value: 96.58366196890644
    - type: manhattan_f1
      value: 91.93054136874362
    - type: manhattan_precision
      value: 93.94572025052193
    - type: manhattan_recall
      value: 90.0
    - type: max_accuracy
      value: 99.84356435643565
    - type: max_ap
      value: 96.58366196890644
    - type: max_f1
      value: 91.93054136874362
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 71.3538865724681
    - type: v_measures
      value:
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      - 0.6679041279132695
      - 0.6706416821131351
      - 0.7400759063631245
      - 0.7205282507088282
      - 0.7207474445915961
      - 0.7076023322461216
      - 0.7919544039062477
      - 0.697356950041273
      - 0.7155185617564064
      - 0.8170975778555782
      - 0.7758530037956233
      - 0.7557716341966847
      - 0.7418030161151182
      - 0.6544532124169519
      - 0.7116665112917787
      - 0.6779566961395338
      - 0.6721164638120183
      - 0.6901024025391699
      - 0.6457684359608986
      - 0.7074519871138994
      - 0.7296079088233842
      - 0.7023239980988409
      - 0.6900078050266639
      - 0.6850583572154368
      - 0.7491029730754422
      - 0.6679041279132695
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 36.11009155563876
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  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 55.54551767207771
    - type: mrr
      value: 56.55926385705797
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.805678984951985
    - type: cos_sim_spearman
      value: 30.827574116605362
    - type: dot_pearson
      value: 29.899814768586204
    - type: dot_spearman
      value: 29.588760095881174
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.22200000000000003
    - type: map_at_10
      value: 2.046
    - type: map_at_100
      value: 2.046
    - type: map_at_1000
      value: 2.046
    - type: map_at_20
      value: 2.046
    - type: map_at_3
      value: 0.661
    - type: map_at_5
      value: 1.057
    - type: mrr_at_1
      value: 84.0
    - type: mrr_at_10
      value: 91.333
    - type: mrr_at_100
      value: 91.333
    - type: mrr_at_1000
      value: 91.333
    - type: mrr_at_20
      value: 91.333
    - type: mrr_at_3
      value: 91.0
    - type: mrr_at_5
      value: 91.0
    - type: ndcg_at_1
      value: 80.0
    - type: ndcg_at_10
      value: 80.74900000000001
    - type: ndcg_at_100
      value: 17.761
    - type: ndcg_at_1000
      value: 7.5920000000000005
    - type: ndcg_at_20
      value: 52.113
    - type: ndcg_at_3
      value: 83.542
    - type: ndcg_at_5
      value: 82.151
    - type: precision_at_1
      value: 84.0
    - type: precision_at_10
      value: 84.6
    - type: precision_at_100
      value: 8.459999999999999
    - type: precision_at_1000
      value: 0.8460000000000001
    - type: precision_at_20
      value: 42.3
    - type: precision_at_3
      value: 88.0
    - type: precision_at_5
      value: 86.0
    - type: recall_at_1
      value: 0.22200000000000003
    - type: recall_at_10
      value: 2.235
    - type: recall_at_100
      value: 2.235
    - type: recall_at_1000
      value: 2.235
    - type: recall_at_20
      value: 2.235
    - type: recall_at_3
      value: 0.695
    - type: recall_at_5
      value: 1.121
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 3.2750000000000004
    - type: map_at_10
      value: 10.514
    - type: map_at_100
      value: 10.514
    - type: map_at_1000
      value: 10.514
    - type: map_at_20
      value: 10.514
    - type: map_at_3
      value: 5.662
    - type: map_at_5
      value: 7.808
    - type: mrr_at_1
      value: 40.816
    - type: mrr_at_10
      value: 49.88
    - type: mrr_at_100
      value: 49.88
    - type: mrr_at_1000
      value: 49.88
    - type: mrr_at_20
      value: 49.88
    - type: mrr_at_3
      value: 46.259
    - type: mrr_at_5
      value: 47.585
    - type: ndcg_at_1
      value: 37.755
    - type: ndcg_at_10
      value: 25.237
    - type: ndcg_at_100
      value: 21.149
    - type: ndcg_at_1000
      value: 21.149
    - type: ndcg_at_20
      value: 21.401999999999997
    - type: ndcg_at_3
      value: 27.465
    - type: ndcg_at_5
      value: 26.169999999999998
    - type: precision_at_1
      value: 40.816
    - type: precision_at_10
      value: 21.224
    - type: precision_at_100
      value: 2.122
    - type: precision_at_1000
      value: 0.212
    - type: precision_at_20
      value: 10.612
    - type: precision_at_3
      value: 26.531
    - type: precision_at_5
      value: 24.490000000000002
    - type: recall_at_1
      value: 3.2750000000000004
    - type: recall_at_10
      value: 16.264
    - type: recall_at_100
      value: 16.264
    - type: recall_at_1000
      value: 16.264
    - type: recall_at_20
      value: 16.264
    - type: recall_at_3
      value: 6.265999999999999
    - type: recall_at_5
      value: 9.677
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 66.181640625
    - type: ap
      value: 12.61343083198892
    - type: f1
      value: 51.12214559856414
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.543859649122815
    - type: f1
      value: 62.742315191046295
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 54.7799424517948
    - type: v_measures
      value:
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      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
      - 0.550822270643678
      - 0.5550309505411892
      - 0.5374116804548088
      - 0.530806408291854
      - 0.5520216200733947
      - 0.5723223656123475
      - 0.5487505833189581
      - 0.5496668776225391
      - 0.5230606424471813
      - 0.5581008461735308
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 88.24581271979496
    - type: cos_sim_ap
      value: 81.34631603712425
    - type: cos_sim_f1
      value: 73.6588459099556
    - type: cos_sim_precision
      value: 70.91575091575092
    - type: cos_sim_recall
      value: 76.62269129287598
    - type: dot_accuracy
      value: 86.33247898909221
    - type: dot_ap
      value: 74.8713850965631
    - type: dot_f1
      value: 69.68152866242038
    - type: dot_precision
      value: 67.36453201970444
    - type: dot_recall
      value: 72.16358839050132
    - type: euclidean_accuracy
      value: 88.37098408535495
    - type: euclidean_ap
      value: 81.3880827682646
    - type: euclidean_f1
      value: 73.69367056104764
    - type: euclidean_precision
      value: 71.76794198549638
    - type: euclidean_recall
      value: 75.72559366754618
    - type: manhattan_accuracy
      value: 88.28157596709781
    - type: manhattan_ap
      value: 81.11568493905267
    - type: manhattan_f1
      value: 73.38364779874215
    - type: manhattan_precision
      value: 70.1201923076923
    - type: manhattan_recall
      value: 76.96569920844327
    - type: max_accuracy
      value: 88.37098408535495
    - type: max_ap
      value: 81.3880827682646
    - type: max_f1
      value: 73.69367056104764
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.54476656188147
    - type: cos_sim_ap
      value: 86.93964282285746
    - type: cos_sim_f1
      value: 79.50401702190103
    - type: cos_sim_precision
      value: 75.93020811435778
    - type: cos_sim_recall
      value: 83.43085925469664
    - type: dot_accuracy
      value: 88.64050917840649
    - type: dot_ap
      value: 84.81007248888473
    - type: dot_f1
      value: 77.95706670508572
    - type: dot_precision
      value: 73.24038982133189
    - type: dot_recall
      value: 83.32306744687403
    - type: euclidean_accuracy
      value: 89.53894516241705
    - type: euclidean_ap
      value: 86.92299719471643
    - type: euclidean_f1
      value: 79.55922060862585
    - type: euclidean_precision
      value: 75.61381606325426
    - type: euclidean_recall
      value: 83.93902063443178
    - type: manhattan_accuracy
      value: 89.5234214305119
    - type: manhattan_ap
      value: 86.93261273512803
    - type: manhattan_f1
      value: 79.54703705061019
    - type: manhattan_precision
      value: 75.90041261626688
    - type: manhattan_recall
      value: 83.56174930705266
    - type: max_accuracy
      value: 89.54476656188147
    - type: max_ap
      value: 86.93964282285746
    - type: max_f1
      value: 79.55922060862585
---

Details to run in https://github.com/raghavlite/TDTE