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metadata
license: apache-2.0
pipeline_tag: sentence-similarity
inference: false
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
language: en
datasets:
  - s2orc
  - flax-sentence-embeddings/stackexchange_title_body_jsonl
  - flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl
  - flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl
  - >-
    flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl
  - sentence-transformers/reddit-title-body
  - msmarco
  - gooaq
  - yahoo_answers_topics
  - code_search_net
  - search_qa
  - eli5
  - snli
  - multi_nli
  - wikihow
  - natural_questions
  - trivia_qa
  - embedding-data/sentence-compression
  - embedding-data/flickr30k-captions
  - embedding-data/altlex
  - embedding-data/simple-wiki
  - embedding-data/QQP
  - embedding-data/SPECTER
  - embedding-data/PAQ_pairs
  - embedding-data/WikiAnswers
  - sentence-transformers/embedding-training-data
model-index:
  - name: lodestone-base-4096-v1
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 69.7313432835821
          - type: ap
            value: 31.618259511417733
          - type: f1
            value: 63.30313825394228
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 86.89837499999999
          - type: ap
            value: 82.39500885672128
          - type: f1
            value: 86.87317947399657
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 44.05
          - type: f1
            value: 42.67624383248947
      - task:
          type: Retrieval
        dataset:
          type: arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 26.173999999999996
          - type: map_at_10
            value: 40.976
          - type: map_at_100
            value: 42.067
          - type: map_at_1000
            value: 42.075
          - type: map_at_3
            value: 35.917
          - type: map_at_5
            value: 38.656
          - type: mrr_at_1
            value: 26.814
          - type: mrr_at_10
            value: 41.252
          - type: mrr_at_100
            value: 42.337
          - type: mrr_at_1000
            value: 42.345
          - type: mrr_at_3
            value: 36.226
          - type: mrr_at_5
            value: 38.914
          - type: ndcg_at_1
            value: 26.173999999999996
          - type: ndcg_at_10
            value: 49.819
          - type: ndcg_at_100
            value: 54.403999999999996
          - type: ndcg_at_1000
            value: 54.59
          - type: ndcg_at_3
            value: 39.231
          - type: ndcg_at_5
            value: 44.189
          - type: precision_at_1
            value: 26.173999999999996
          - type: precision_at_10
            value: 7.838000000000001
          - type: precision_at_100
            value: 0.9820000000000001
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 16.287
          - type: precision_at_5
            value: 12.191
          - type: recall_at_1
            value: 26.173999999999996
          - type: recall_at_10
            value: 78.378
          - type: recall_at_100
            value: 98.222
          - type: recall_at_1000
            value: 99.644
          - type: recall_at_3
            value: 48.862
          - type: recall_at_5
            value: 60.953
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 42.31689035788179
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 31.280245136660984
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 58.79109720839415
          - type: mrr
            value: 71.79615705931495
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 76.44918756608115
          - type: cos_sim_spearman
            value: 70.86607256286257
          - type: euclidean_pearson
            value: 74.12154678100815
          - type: euclidean_spearman
            value: 70.86607256286257
          - type: manhattan_pearson
            value: 74.0078626964417
          - type: manhattan_spearman
            value: 70.68353828321327
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 75.40584415584415
          - type: f1
            value: 74.29514617572676
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 37.41860080664014
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 29.319217023090705
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 26.595000000000002
          - type: map_at_10
            value: 36.556
          - type: map_at_100
            value: 37.984
          - type: map_at_1000
            value: 38.134
          - type: map_at_3
            value: 33.417
          - type: map_at_5
            value: 35.160000000000004
          - type: mrr_at_1
            value: 32.761
          - type: mrr_at_10
            value: 41.799
          - type: mrr_at_100
            value: 42.526
          - type: mrr_at_1000
            value: 42.582
          - type: mrr_at_3
            value: 39.39
          - type: mrr_at_5
            value: 40.727000000000004
          - type: ndcg_at_1
            value: 32.761
          - type: ndcg_at_10
            value: 42.549
          - type: ndcg_at_100
            value: 47.915
          - type: ndcg_at_1000
            value: 50.475
          - type: ndcg_at_3
            value: 37.93
          - type: ndcg_at_5
            value: 39.939
          - type: precision_at_1
            value: 32.761
          - type: precision_at_10
            value: 8.312
          - type: precision_at_100
            value: 1.403
          - type: precision_at_1000
            value: 0.197
          - type: precision_at_3
            value: 18.741
          - type: precision_at_5
            value: 13.447999999999999
          - type: recall_at_1
            value: 26.595000000000002
          - type: recall_at_10
            value: 54.332
          - type: recall_at_100
            value: 76.936
          - type: recall_at_1000
            value: 93.914
          - type: recall_at_3
            value: 40.666000000000004
          - type: recall_at_5
            value: 46.513
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 22.528000000000002
          - type: map_at_10
            value: 30.751
          - type: map_at_100
            value: 31.855
          - type: map_at_1000
            value: 31.972
          - type: map_at_3
            value: 28.465
          - type: map_at_5
            value: 29.738
          - type: mrr_at_1
            value: 28.662
          - type: mrr_at_10
            value: 35.912
          - type: mrr_at_100
            value: 36.726
          - type: mrr_at_1000
            value: 36.777
          - type: mrr_at_3
            value: 34.013
          - type: mrr_at_5
            value: 35.156
          - type: ndcg_at_1
            value: 28.662
          - type: ndcg_at_10
            value: 35.452
          - type: ndcg_at_100
            value: 40.1
          - type: ndcg_at_1000
            value: 42.323
          - type: ndcg_at_3
            value: 32.112
          - type: ndcg_at_5
            value: 33.638
          - type: precision_at_1
            value: 28.662
          - type: precision_at_10
            value: 6.688
          - type: precision_at_100
            value: 1.13
          - type: precision_at_1000
            value: 0.16
          - type: precision_at_3
            value: 15.562999999999999
          - type: precision_at_5
            value: 11.019
          - type: recall_at_1
            value: 22.528000000000002
          - type: recall_at_10
            value: 43.748
          - type: recall_at_100
            value: 64.235
          - type: recall_at_1000
            value: 78.609
          - type: recall_at_3
            value: 33.937
          - type: recall_at_5
            value: 38.234
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 33.117999999999995
          - type: map_at_10
            value: 44.339
          - type: map_at_100
            value: 45.367000000000004
          - type: map_at_1000
            value: 45.437
          - type: map_at_3
            value: 41.195
          - type: map_at_5
            value: 42.922
          - type: mrr_at_1
            value: 38.37
          - type: mrr_at_10
            value: 47.786
          - type: mrr_at_100
            value: 48.522
          - type: mrr_at_1000
            value: 48.567
          - type: mrr_at_3
            value: 45.371
          - type: mrr_at_5
            value: 46.857
          - type: ndcg_at_1
            value: 38.37
          - type: ndcg_at_10
            value: 50.019999999999996
          - type: ndcg_at_100
            value: 54.36299999999999
          - type: ndcg_at_1000
            value: 55.897
          - type: ndcg_at_3
            value: 44.733000000000004
          - type: ndcg_at_5
            value: 47.292
          - type: precision_at_1
            value: 38.37
          - type: precision_at_10
            value: 8.288
          - type: precision_at_100
            value: 1.139
          - type: precision_at_1000
            value: 0.132
          - type: precision_at_3
            value: 20.293
          - type: precision_at_5
            value: 14.107
          - type: recall_at_1
            value: 33.117999999999995
          - type: recall_at_10
            value: 63.451
          - type: recall_at_100
            value: 82.767
          - type: recall_at_1000
            value: 93.786
          - type: recall_at_3
            value: 48.964999999999996
          - type: recall_at_5
            value: 55.358
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 16.028000000000002
          - type: map_at_10
            value: 23.186999999999998
          - type: map_at_100
            value: 24.236
          - type: map_at_1000
            value: 24.337
          - type: map_at_3
            value: 20.816000000000003
          - type: map_at_5
            value: 22.311
          - type: mrr_at_1
            value: 17.514
          - type: mrr_at_10
            value: 24.84
          - type: mrr_at_100
            value: 25.838
          - type: mrr_at_1000
            value: 25.924999999999997
          - type: mrr_at_3
            value: 22.542
          - type: mrr_at_5
            value: 24.04
          - type: ndcg_at_1
            value: 17.514
          - type: ndcg_at_10
            value: 27.391
          - type: ndcg_at_100
            value: 32.684999999999995
          - type: ndcg_at_1000
            value: 35.367
          - type: ndcg_at_3
            value: 22.820999999999998
          - type: ndcg_at_5
            value: 25.380999999999997
          - type: precision_at_1
            value: 17.514
          - type: precision_at_10
            value: 4.463
          - type: precision_at_100
            value: 0.745
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 10.019
          - type: precision_at_5
            value: 7.457999999999999
          - type: recall_at_1
            value: 16.028000000000002
          - type: recall_at_10
            value: 38.81
          - type: recall_at_100
            value: 63.295
          - type: recall_at_1000
            value: 83.762
          - type: recall_at_3
            value: 26.604
          - type: recall_at_5
            value: 32.727000000000004
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 11.962
          - type: map_at_10
            value: 17.218
          - type: map_at_100
            value: 18.321
          - type: map_at_1000
            value: 18.455
          - type: map_at_3
            value: 15.287999999999998
          - type: map_at_5
            value: 16.417
          - type: mrr_at_1
            value: 14.677000000000001
          - type: mrr_at_10
            value: 20.381
          - type: mrr_at_100
            value: 21.471999999999998
          - type: mrr_at_1000
            value: 21.566
          - type: mrr_at_3
            value: 18.448999999999998
          - type: mrr_at_5
            value: 19.587
          - type: ndcg_at_1
            value: 14.677000000000001
          - type: ndcg_at_10
            value: 20.86
          - type: ndcg_at_100
            value: 26.519
          - type: ndcg_at_1000
            value: 30.020000000000003
          - type: ndcg_at_3
            value: 17.208000000000002
          - type: ndcg_at_5
            value: 19.037000000000003
          - type: precision_at_1
            value: 14.677000000000001
          - type: precision_at_10
            value: 3.856
          - type: precision_at_100
            value: 0.7889999999999999
          - type: precision_at_1000
            value: 0.124
          - type: precision_at_3
            value: 8.043
          - type: precision_at_5
            value: 6.069999999999999
          - type: recall_at_1
            value: 11.962
          - type: recall_at_10
            value: 28.994999999999997
          - type: recall_at_100
            value: 54.071999999999996
          - type: recall_at_1000
            value: 79.309
          - type: recall_at_3
            value: 19.134999999999998
          - type: recall_at_5
            value: 23.727999999999998
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 22.764
          - type: map_at_10
            value: 31.744
          - type: map_at_100
            value: 33.037
          - type: map_at_1000
            value: 33.156
          - type: map_at_3
            value: 29.015
          - type: map_at_5
            value: 30.434
          - type: mrr_at_1
            value: 28.296
          - type: mrr_at_10
            value: 37.03
          - type: mrr_at_100
            value: 37.902
          - type: mrr_at_1000
            value: 37.966
          - type: mrr_at_3
            value: 34.568
          - type: mrr_at_5
            value: 35.786
          - type: ndcg_at_1
            value: 28.296
          - type: ndcg_at_10
            value: 37.289
          - type: ndcg_at_100
            value: 42.787
          - type: ndcg_at_1000
            value: 45.382
          - type: ndcg_at_3
            value: 32.598
          - type: ndcg_at_5
            value: 34.521
          - type: precision_at_1
            value: 28.296
          - type: precision_at_10
            value: 6.901
          - type: precision_at_100
            value: 1.135
          - type: precision_at_1000
            value: 0.152
          - type: precision_at_3
            value: 15.367
          - type: precision_at_5
            value: 11.03
          - type: recall_at_1
            value: 22.764
          - type: recall_at_10
            value: 48.807
          - type: recall_at_100
            value: 71.859
          - type: recall_at_1000
            value: 89.606
          - type: recall_at_3
            value: 35.594
          - type: recall_at_5
            value: 40.541
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 19.742
          - type: map_at_10
            value: 27.741
          - type: map_at_100
            value: 29.323
          - type: map_at_1000
            value: 29.438
          - type: map_at_3
            value: 25.217
          - type: map_at_5
            value: 26.583000000000002
          - type: mrr_at_1
            value: 24.657999999999998
          - type: mrr_at_10
            value: 32.407000000000004
          - type: mrr_at_100
            value: 33.631
          - type: mrr_at_1000
            value: 33.686
          - type: mrr_at_3
            value: 30.194
          - type: mrr_at_5
            value: 31.444
          - type: ndcg_at_1
            value: 24.657999999999998
          - type: ndcg_at_10
            value: 32.614
          - type: ndcg_at_100
            value: 39.61
          - type: ndcg_at_1000
            value: 42.114000000000004
          - type: ndcg_at_3
            value: 28.516000000000002
          - type: ndcg_at_5
            value: 30.274
          - type: precision_at_1
            value: 24.657999999999998
          - type: precision_at_10
            value: 6.176
          - type: precision_at_100
            value: 1.1400000000000001
          - type: precision_at_1000
            value: 0.155
          - type: precision_at_3
            value: 13.927
          - type: precision_at_5
            value: 9.954
          - type: recall_at_1
            value: 19.742
          - type: recall_at_10
            value: 42.427
          - type: recall_at_100
            value: 72.687
          - type: recall_at_1000
            value: 89.89
          - type: recall_at_3
            value: 30.781
          - type: recall_at_5
            value: 35.606
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 19.72608333333333
          - type: map_at_10
            value: 27.165333333333336
          - type: map_at_100
            value: 28.292499999999997
          - type: map_at_1000
            value: 28.416333333333327
          - type: map_at_3
            value: 24.783833333333334
          - type: map_at_5
            value: 26.101750000000003
          - type: mrr_at_1
            value: 23.721500000000002
          - type: mrr_at_10
            value: 30.853333333333328
          - type: mrr_at_100
            value: 31.741750000000003
          - type: mrr_at_1000
            value: 31.812999999999995
          - type: mrr_at_3
            value: 28.732249999999997
          - type: mrr_at_5
            value: 29.945166666666665
          - type: ndcg_at_1
            value: 23.721500000000002
          - type: ndcg_at_10
            value: 31.74883333333333
          - type: ndcg_at_100
            value: 36.883583333333334
          - type: ndcg_at_1000
            value: 39.6145
          - type: ndcg_at_3
            value: 27.639583333333334
          - type: ndcg_at_5
            value: 29.543666666666667
          - type: precision_at_1
            value: 23.721500000000002
          - type: precision_at_10
            value: 5.709083333333333
          - type: precision_at_100
            value: 0.9859166666666666
          - type: precision_at_1000
            value: 0.1413333333333333
          - type: precision_at_3
            value: 12.85683333333333
          - type: precision_at_5
            value: 9.258166666666668
          - type: recall_at_1
            value: 19.72608333333333
          - type: recall_at_10
            value: 41.73583333333334
          - type: recall_at_100
            value: 64.66566666666668
          - type: recall_at_1000
            value: 84.09833333333336
          - type: recall_at_3
            value: 30.223083333333328
          - type: recall_at_5
            value: 35.153083333333335
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 17.582
          - type: map_at_10
            value: 22.803
          - type: map_at_100
            value: 23.503
          - type: map_at_1000
            value: 23.599999999999998
          - type: map_at_3
            value: 21.375
          - type: map_at_5
            value: 22.052
          - type: mrr_at_1
            value: 20.399
          - type: mrr_at_10
            value: 25.369999999999997
          - type: mrr_at_100
            value: 26.016000000000002
          - type: mrr_at_1000
            value: 26.090999999999998
          - type: mrr_at_3
            value: 23.952
          - type: mrr_at_5
            value: 24.619
          - type: ndcg_at_1
            value: 20.399
          - type: ndcg_at_10
            value: 25.964
          - type: ndcg_at_100
            value: 29.607
          - type: ndcg_at_1000
            value: 32.349
          - type: ndcg_at_3
            value: 23.177
          - type: ndcg_at_5
            value: 24.276
          - type: precision_at_1
            value: 20.399
          - type: precision_at_10
            value: 4.018
          - type: precision_at_100
            value: 0.629
          - type: precision_at_1000
            value: 0.093
          - type: precision_at_3
            value: 9.969
          - type: precision_at_5
            value: 6.748
          - type: recall_at_1
            value: 17.582
          - type: recall_at_10
            value: 33.35
          - type: recall_at_100
            value: 50.219
          - type: recall_at_1000
            value: 71.06099999999999
          - type: recall_at_3
            value: 25.619999999999997
          - type: recall_at_5
            value: 28.291
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 11.071
          - type: map_at_10
            value: 16.201999999999998
          - type: map_at_100
            value: 17.112
          - type: map_at_1000
            value: 17.238
          - type: map_at_3
            value: 14.508
          - type: map_at_5
            value: 15.440999999999999
          - type: mrr_at_1
            value: 13.833
          - type: mrr_at_10
            value: 19.235
          - type: mrr_at_100
            value: 20.108999999999998
          - type: mrr_at_1000
            value: 20.196
          - type: mrr_at_3
            value: 17.515
          - type: mrr_at_5
            value: 18.505
          - type: ndcg_at_1
            value: 13.833
          - type: ndcg_at_10
            value: 19.643
          - type: ndcg_at_100
            value: 24.298000000000002
          - type: ndcg_at_1000
            value: 27.614
          - type: ndcg_at_3
            value: 16.528000000000002
          - type: ndcg_at_5
            value: 17.991
          - type: precision_at_1
            value: 13.833
          - type: precision_at_10
            value: 3.6990000000000003
          - type: precision_at_100
            value: 0.713
          - type: precision_at_1000
            value: 0.116
          - type: precision_at_3
            value: 7.9030000000000005
          - type: precision_at_5
            value: 5.891
          - type: recall_at_1
            value: 11.071
          - type: recall_at_10
            value: 27.019
          - type: recall_at_100
            value: 48.404
          - type: recall_at_1000
            value: 72.641
          - type: recall_at_3
            value: 18.336
          - type: recall_at_5
            value: 21.991
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 18.573
          - type: map_at_10
            value: 25.008999999999997
          - type: map_at_100
            value: 26.015
          - type: map_at_1000
            value: 26.137
          - type: map_at_3
            value: 22.798
          - type: map_at_5
            value: 24.092
          - type: mrr_at_1
            value: 22.108
          - type: mrr_at_10
            value: 28.646
          - type: mrr_at_100
            value: 29.477999999999998
          - type: mrr_at_1000
            value: 29.57
          - type: mrr_at_3
            value: 26.415
          - type: mrr_at_5
            value: 27.693
          - type: ndcg_at_1
            value: 22.108
          - type: ndcg_at_10
            value: 29.42
          - type: ndcg_at_100
            value: 34.385
          - type: ndcg_at_1000
            value: 37.572
          - type: ndcg_at_3
            value: 25.274
          - type: ndcg_at_5
            value: 27.315
          - type: precision_at_1
            value: 22.108
          - type: precision_at_10
            value: 5.093
          - type: precision_at_100
            value: 0.859
          - type: precision_at_1000
            value: 0.124
          - type: precision_at_3
            value: 11.474
          - type: precision_at_5
            value: 8.321000000000002
          - type: recall_at_1
            value: 18.573
          - type: recall_at_10
            value: 39.433
          - type: recall_at_100
            value: 61.597
          - type: recall_at_1000
            value: 84.69
          - type: recall_at_3
            value: 27.849
          - type: recall_at_5
            value: 33.202999999999996
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 22.807
          - type: map_at_10
            value: 30.014000000000003
          - type: map_at_100
            value: 31.422
          - type: map_at_1000
            value: 31.652
          - type: map_at_3
            value: 27.447
          - type: map_at_5
            value: 28.711
          - type: mrr_at_1
            value: 27.668
          - type: mrr_at_10
            value: 34.489
          - type: mrr_at_100
            value: 35.453
          - type: mrr_at_1000
            value: 35.526
          - type: mrr_at_3
            value: 32.477000000000004
          - type: mrr_at_5
            value: 33.603
          - type: ndcg_at_1
            value: 27.668
          - type: ndcg_at_10
            value: 34.983
          - type: ndcg_at_100
            value: 40.535
          - type: ndcg_at_1000
            value: 43.747
          - type: ndcg_at_3
            value: 31.026999999999997
          - type: ndcg_at_5
            value: 32.608
          - type: precision_at_1
            value: 27.668
          - type: precision_at_10
            value: 6.837999999999999
          - type: precision_at_100
            value: 1.411
          - type: precision_at_1000
            value: 0.23600000000000002
          - type: precision_at_3
            value: 14.295
          - type: precision_at_5
            value: 10.435
          - type: recall_at_1
            value: 22.807
          - type: recall_at_10
            value: 43.545
          - type: recall_at_100
            value: 69.39800000000001
          - type: recall_at_1000
            value: 90.706
          - type: recall_at_3
            value: 32.183
          - type: recall_at_5
            value: 36.563
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 13.943
          - type: map_at_10
            value: 20.419999999999998
          - type: map_at_100
            value: 21.335
          - type: map_at_1000
            value: 21.44
          - type: map_at_3
            value: 17.865000000000002
          - type: map_at_5
            value: 19.36
          - type: mrr_at_1
            value: 15.712000000000002
          - type: mrr_at_10
            value: 22.345000000000002
          - type: mrr_at_100
            value: 23.227999999999998
          - type: mrr_at_1000
            value: 23.304
          - type: mrr_at_3
            value: 19.901
          - type: mrr_at_5
            value: 21.325
          - type: ndcg_at_1
            value: 15.712000000000002
          - type: ndcg_at_10
            value: 24.801000000000002
          - type: ndcg_at_100
            value: 29.799
          - type: ndcg_at_1000
            value: 32.513999999999996
          - type: ndcg_at_3
            value: 19.750999999999998
          - type: ndcg_at_5
            value: 22.252
          - type: precision_at_1
            value: 15.712000000000002
          - type: precision_at_10
            value: 4.1770000000000005
          - type: precision_at_100
            value: 0.738
          - type: precision_at_1000
            value: 0.106
          - type: precision_at_3
            value: 8.688
          - type: precision_at_5
            value: 6.617000000000001
          - type: recall_at_1
            value: 13.943
          - type: recall_at_10
            value: 36.913000000000004
          - type: recall_at_100
            value: 60.519
          - type: recall_at_1000
            value: 81.206
          - type: recall_at_3
            value: 23.006999999999998
          - type: recall_at_5
            value: 29.082
      - task:
          type: Retrieval
        dataset:
          type: climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 9.468
          - type: map_at_10
            value: 16.029
          - type: map_at_100
            value: 17.693
          - type: map_at_1000
            value: 17.886
          - type: map_at_3
            value: 13.15
          - type: map_at_5
            value: 14.568
          - type: mrr_at_1
            value: 21.173000000000002
          - type: mrr_at_10
            value: 31.028
          - type: mrr_at_100
            value: 32.061
          - type: mrr_at_1000
            value: 32.119
          - type: mrr_at_3
            value: 27.534999999999997
          - type: mrr_at_5
            value: 29.431
          - type: ndcg_at_1
            value: 21.173000000000002
          - type: ndcg_at_10
            value: 23.224
          - type: ndcg_at_100
            value: 30.225
          - type: ndcg_at_1000
            value: 33.961000000000006
          - type: ndcg_at_3
            value: 18.174
          - type: ndcg_at_5
            value: 19.897000000000002
          - type: precision_at_1
            value: 21.173000000000002
          - type: precision_at_10
            value: 7.4719999999999995
          - type: precision_at_100
            value: 1.5010000000000001
          - type: precision_at_1000
            value: 0.219
          - type: precision_at_3
            value: 13.312
          - type: precision_at_5
            value: 10.619
          - type: recall_at_1
            value: 9.468
          - type: recall_at_10
            value: 28.823
          - type: recall_at_100
            value: 53.26499999999999
          - type: recall_at_1000
            value: 74.536
          - type: recall_at_3
            value: 16.672
          - type: recall_at_5
            value: 21.302
      - task:
          type: Retrieval
        dataset:
          type: dbpedia-entity
          name: MTEB DBPedia
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 6.343
          - type: map_at_10
            value: 12.717
          - type: map_at_100
            value: 16.48
          - type: map_at_1000
            value: 17.381
          - type: map_at_3
            value: 9.568999999999999
          - type: map_at_5
            value: 11.125
          - type: mrr_at_1
            value: 48.75
          - type: mrr_at_10
            value: 58.425000000000004
          - type: mrr_at_100
            value: 59.075
          - type: mrr_at_1000
            value: 59.095
          - type: mrr_at_3
            value: 56.291999999999994
          - type: mrr_at_5
            value: 57.679
          - type: ndcg_at_1
            value: 37.875
          - type: ndcg_at_10
            value: 27.77
          - type: ndcg_at_100
            value: 30.288999999999998
          - type: ndcg_at_1000
            value: 36.187999999999995
          - type: ndcg_at_3
            value: 31.385999999999996
          - type: ndcg_at_5
            value: 29.923
          - type: precision_at_1
            value: 48.75
          - type: precision_at_10
            value: 22.375
          - type: precision_at_100
            value: 6.3420000000000005
          - type: precision_at_1000
            value: 1.4489999999999998
          - type: precision_at_3
            value: 35.5
          - type: precision_at_5
            value: 30.55
          - type: recall_at_1
            value: 6.343
          - type: recall_at_10
            value: 16.936
          - type: recall_at_100
            value: 35.955999999999996
          - type: recall_at_1000
            value: 55.787
          - type: recall_at_3
            value: 10.771
          - type: recall_at_5
            value: 13.669999999999998
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 41.99
          - type: f1
            value: 36.823402174564954
      - task:
          type: Retrieval
        dataset:
          type: fever
          name: MTEB FEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 40.088
          - type: map_at_10
            value: 52.69200000000001
          - type: map_at_100
            value: 53.296
          - type: map_at_1000
            value: 53.325
          - type: map_at_3
            value: 49.905
          - type: map_at_5
            value: 51.617000000000004
          - type: mrr_at_1
            value: 43.009
          - type: mrr_at_10
            value: 56.203
          - type: mrr_at_100
            value: 56.75
          - type: mrr_at_1000
            value: 56.769000000000005
          - type: mrr_at_3
            value: 53.400000000000006
          - type: mrr_at_5
            value: 55.163
          - type: ndcg_at_1
            value: 43.009
          - type: ndcg_at_10
            value: 59.39
          - type: ndcg_at_100
            value: 62.129999999999995
          - type: ndcg_at_1000
            value: 62.793
          - type: ndcg_at_3
            value: 53.878
          - type: ndcg_at_5
            value: 56.887
          - type: precision_at_1
            value: 43.009
          - type: precision_at_10
            value: 8.366
          - type: precision_at_100
            value: 0.983
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 22.377
          - type: precision_at_5
            value: 15.035000000000002
          - type: recall_at_1
            value: 40.088
          - type: recall_at_10
            value: 76.68700000000001
          - type: recall_at_100
            value: 88.91
          - type: recall_at_1000
            value: 93.782
          - type: recall_at_3
            value: 61.809999999999995
          - type: recall_at_5
            value: 69.131
      - task:
          type: Retrieval
        dataset:
          type: fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 10.817
          - type: map_at_10
            value: 18.9
          - type: map_at_100
            value: 20.448
          - type: map_at_1000
            value: 20.660999999999998
          - type: map_at_3
            value: 15.979
          - type: map_at_5
            value: 17.415
          - type: mrr_at_1
            value: 23.148
          - type: mrr_at_10
            value: 31.208000000000002
          - type: mrr_at_100
            value: 32.167
          - type: mrr_at_1000
            value: 32.242
          - type: mrr_at_3
            value: 28.498
          - type: mrr_at_5
            value: 29.964000000000002
          - type: ndcg_at_1
            value: 23.148
          - type: ndcg_at_10
            value: 25.325999999999997
          - type: ndcg_at_100
            value: 31.927
          - type: ndcg_at_1000
            value: 36.081
          - type: ndcg_at_3
            value: 21.647
          - type: ndcg_at_5
            value: 22.762999999999998
          - type: precision_at_1
            value: 23.148
          - type: precision_at_10
            value: 7.546
          - type: precision_at_100
            value: 1.415
          - type: precision_at_1000
            value: 0.216
          - type: precision_at_3
            value: 14.969
          - type: precision_at_5
            value: 11.327
          - type: recall_at_1
            value: 10.817
          - type: recall_at_10
            value: 32.164
          - type: recall_at_100
            value: 57.655
          - type: recall_at_1000
            value: 82.797
          - type: recall_at_3
            value: 19.709
          - type: recall_at_5
            value: 24.333
      - task:
          type: Retrieval
        dataset:
          type: hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 25.380999999999997
          - type: map_at_10
            value: 33.14
          - type: map_at_100
            value: 33.948
          - type: map_at_1000
            value: 34.028000000000006
          - type: map_at_3
            value: 31.019999999999996
          - type: map_at_5
            value: 32.23
          - type: mrr_at_1
            value: 50.763000000000005
          - type: mrr_at_10
            value: 57.899
          - type: mrr_at_100
            value: 58.426
          - type: mrr_at_1000
            value: 58.457
          - type: mrr_at_3
            value: 56.093
          - type: mrr_at_5
            value: 57.116
          - type: ndcg_at_1
            value: 50.763000000000005
          - type: ndcg_at_10
            value: 41.656
          - type: ndcg_at_100
            value: 45.079
          - type: ndcg_at_1000
            value: 46.916999999999994
          - type: ndcg_at_3
            value: 37.834
          - type: ndcg_at_5
            value: 39.732
          - type: precision_at_1
            value: 50.763000000000005
          - type: precision_at_10
            value: 8.648
          - type: precision_at_100
            value: 1.135
          - type: precision_at_1000
            value: 0.13799999999999998
          - type: precision_at_3
            value: 23.105999999999998
          - type: precision_at_5
            value: 15.363
          - type: recall_at_1
            value: 25.380999999999997
          - type: recall_at_10
            value: 43.241
          - type: recall_at_100
            value: 56.745000000000005
          - type: recall_at_1000
            value: 69.048
          - type: recall_at_3
            value: 34.659
          - type: recall_at_5
            value: 38.406
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 79.544
          - type: ap
            value: 73.82920133396664
          - type: f1
            value: 79.51048124883265
      - task:
          type: Retrieval
        dataset:
          type: msmarco
          name: MTEB MSMARCO
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 11.174000000000001
          - type: map_at_10
            value: 19.451999999999998
          - type: map_at_100
            value: 20.612
          - type: map_at_1000
            value: 20.703
          - type: map_at_3
            value: 16.444
          - type: map_at_5
            value: 18.083
          - type: mrr_at_1
            value: 11.447000000000001
          - type: mrr_at_10
            value: 19.808
          - type: mrr_at_100
            value: 20.958
          - type: mrr_at_1000
            value: 21.041999999999998
          - type: mrr_at_3
            value: 16.791
          - type: mrr_at_5
            value: 18.459
          - type: ndcg_at_1
            value: 11.447000000000001
          - type: ndcg_at_10
            value: 24.556
          - type: ndcg_at_100
            value: 30.637999999999998
          - type: ndcg_at_1000
            value: 33.14
          - type: ndcg_at_3
            value: 18.325
          - type: ndcg_at_5
            value: 21.278
          - type: precision_at_1
            value: 11.447000000000001
          - type: precision_at_10
            value: 4.215
          - type: precision_at_100
            value: 0.732
          - type: precision_at_1000
            value: 0.095
          - type: precision_at_3
            value: 8.052
          - type: precision_at_5
            value: 6.318
          - type: recall_at_1
            value: 11.174000000000001
          - type: recall_at_10
            value: 40.543
          - type: recall_at_100
            value: 69.699
          - type: recall_at_1000
            value: 89.403
          - type: recall_at_3
            value: 23.442
          - type: recall_at_5
            value: 30.536
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 89.6671226630187
          - type: f1
            value: 89.57660424361246
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 60.284997720018254
          - type: f1
            value: 40.30637400152823
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 63.33557498318763
          - type: f1
            value: 60.24039910680179
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 72.37390719569603
          - type: f1
            value: 72.33097333477316
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 34.68158939060552
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 30.340061711905236
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 32.01814326295803
          - type: mrr
            value: 33.20555240055367
      - task:
          type: Retrieval
        dataset:
          type: nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 3.3910000000000005
          - type: map_at_10
            value: 7.7219999999999995
          - type: map_at_100
            value: 10.286
          - type: map_at_1000
            value: 11.668000000000001
          - type: map_at_3
            value: 5.552
          - type: map_at_5
            value: 6.468
          - type: mrr_at_1
            value: 34.365
          - type: mrr_at_10
            value: 42.555
          - type: mrr_at_100
            value: 43.295
          - type: mrr_at_1000
            value: 43.357
          - type: mrr_at_3
            value: 40.299
          - type: mrr_at_5
            value: 41.182
          - type: ndcg_at_1
            value: 31.424000000000003
          - type: ndcg_at_10
            value: 24.758
          - type: ndcg_at_100
            value: 23.677999999999997
          - type: ndcg_at_1000
            value: 33.377
          - type: ndcg_at_3
            value: 28.302
          - type: ndcg_at_5
            value: 26.342
          - type: precision_at_1
            value: 33.437
          - type: precision_at_10
            value: 19.256999999999998
          - type: precision_at_100
            value: 6.662999999999999
          - type: precision_at_1000
            value: 1.9900000000000002
          - type: precision_at_3
            value: 27.761000000000003
          - type: precision_at_5
            value: 23.715
          - type: recall_at_1
            value: 3.3910000000000005
          - type: recall_at_10
            value: 11.068
          - type: recall_at_100
            value: 25.878
          - type: recall_at_1000
            value: 60.19
          - type: recall_at_3
            value: 6.1690000000000005
          - type: recall_at_5
            value: 7.767
      - task:
          type: Retrieval
        dataset:
          type: nq
          name: MTEB NQ
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 15.168000000000001
          - type: map_at_10
            value: 26.177
          - type: map_at_100
            value: 27.564
          - type: map_at_1000
            value: 27.628999999999998
          - type: map_at_3
            value: 22.03
          - type: map_at_5
            value: 24.276
          - type: mrr_at_1
            value: 17.439
          - type: mrr_at_10
            value: 28.205000000000002
          - type: mrr_at_100
            value: 29.357
          - type: mrr_at_1000
            value: 29.408
          - type: mrr_at_3
            value: 24.377
          - type: mrr_at_5
            value: 26.540000000000003
          - type: ndcg_at_1
            value: 17.41
          - type: ndcg_at_10
            value: 32.936
          - type: ndcg_at_100
            value: 39.196999999999996
          - type: ndcg_at_1000
            value: 40.892
          - type: ndcg_at_3
            value: 24.721
          - type: ndcg_at_5
            value: 28.615000000000002
          - type: precision_at_1
            value: 17.41
          - type: precision_at_10
            value: 6.199000000000001
          - type: precision_at_100
            value: 0.9690000000000001
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: precision_at_3
            value: 11.790000000000001
          - type: precision_at_5
            value: 9.264
          - type: recall_at_1
            value: 15.168000000000001
          - type: recall_at_10
            value: 51.914
          - type: recall_at_100
            value: 79.804
          - type: recall_at_1000
            value: 92.75999999999999
          - type: recall_at_3
            value: 30.212
          - type: recall_at_5
            value: 39.204
      - task:
          type: Retrieval
        dataset:
          type: quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 67.306
          - type: map_at_10
            value: 80.634
          - type: map_at_100
            value: 81.349
          - type: map_at_1000
            value: 81.37299999999999
          - type: map_at_3
            value: 77.691
          - type: map_at_5
            value: 79.512
          - type: mrr_at_1
            value: 77.56
          - type: mrr_at_10
            value: 84.177
          - type: mrr_at_100
            value: 84.35000000000001
          - type: mrr_at_1000
            value: 84.353
          - type: mrr_at_3
            value: 83.003
          - type: mrr_at_5
            value: 83.799
          - type: ndcg_at_1
            value: 77.58
          - type: ndcg_at_10
            value: 84.782
          - type: ndcg_at_100
            value: 86.443
          - type: ndcg_at_1000
            value: 86.654
          - type: ndcg_at_3
            value: 81.67
          - type: ndcg_at_5
            value: 83.356
          - type: precision_at_1
            value: 77.58
          - type: precision_at_10
            value: 12.875
          - type: precision_at_100
            value: 1.503
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 35.63
          - type: precision_at_5
            value: 23.483999999999998
          - type: recall_at_1
            value: 67.306
          - type: recall_at_10
            value: 92.64
          - type: recall_at_100
            value: 98.681
          - type: recall_at_1000
            value: 99.79
          - type: recall_at_3
            value: 83.682
          - type: recall_at_5
            value: 88.424
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 50.76319866126382
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 282350215ef01743dc01b456c7f5241fa8937f16
        metrics:
          - type: v_measure
            value: 55.024711941648995
      - task:
          type: Retrieval
        dataset:
          type: scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 3.9379999999999997
          - type: map_at_10
            value: 8.817
          - type: map_at_100
            value: 10.546999999999999
          - type: map_at_1000
            value: 10.852
          - type: map_at_3
            value: 6.351999999999999
          - type: map_at_5
            value: 7.453
          - type: mrr_at_1
            value: 19.400000000000002
          - type: mrr_at_10
            value: 27.371000000000002
          - type: mrr_at_100
            value: 28.671999999999997
          - type: mrr_at_1000
            value: 28.747
          - type: mrr_at_3
            value: 24.583
          - type: mrr_at_5
            value: 26.143
          - type: ndcg_at_1
            value: 19.400000000000002
          - type: ndcg_at_10
            value: 15.264
          - type: ndcg_at_100
            value: 22.63
          - type: ndcg_at_1000
            value: 28.559
          - type: ndcg_at_3
            value: 14.424999999999999
          - type: ndcg_at_5
            value: 12.520000000000001
          - type: precision_at_1
            value: 19.400000000000002
          - type: precision_at_10
            value: 7.8100000000000005
          - type: precision_at_100
            value: 1.854
          - type: precision_at_1000
            value: 0.329
          - type: precision_at_3
            value: 13.100000000000001
          - type: precision_at_5
            value: 10.68
          - type: recall_at_1
            value: 3.9379999999999997
          - type: recall_at_10
            value: 15.903
          - type: recall_at_100
            value: 37.645
          - type: recall_at_1000
            value: 66.86
          - type: recall_at_3
            value: 7.993
          - type: recall_at_5
            value: 10.885
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 80.12689060151425
          - type: cos_sim_spearman
            value: 70.46515535094771
          - type: euclidean_pearson
            value: 77.17160003557223
          - type: euclidean_spearman
            value: 70.4651757047438
          - type: manhattan_pearson
            value: 77.18129609281937
          - type: manhattan_spearman
            value: 70.46610403752913
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 70.451157033355
          - type: cos_sim_spearman
            value: 63.99899601697852
          - type: euclidean_pearson
            value: 67.46985359967678
          - type: euclidean_spearman
            value: 64.00001637764805
          - type: manhattan_pearson
            value: 67.56534741780037
          - type: manhattan_spearman
            value: 64.06533893575366
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 77.65086614464292
          - type: cos_sim_spearman
            value: 78.20169706921848
          - type: euclidean_pearson
            value: 77.77758172155283
          - type: euclidean_spearman
            value: 78.20169706921848
          - type: manhattan_pearson
            value: 77.75077884860052
          - type: manhattan_spearman
            value: 78.16875216484164
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 76.26381598259717
          - type: cos_sim_spearman
            value: 70.78377709313477
          - type: euclidean_pearson
            value: 74.82646556532096
          - type: euclidean_spearman
            value: 70.78377658155212
          - type: manhattan_pearson
            value: 74.81784766108225
          - type: manhattan_spearman
            value: 70.79351454692176
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 79.00532026789739
          - type: cos_sim_spearman
            value: 80.02708383244838
          - type: euclidean_pearson
            value: 79.48345422610525
          - type: euclidean_spearman
            value: 80.02708383244838
          - type: manhattan_pearson
            value: 79.44519739854803
          - type: manhattan_spearman
            value: 79.98344094559687
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 77.32783048164805
          - type: cos_sim_spearman
            value: 78.79729961288045
          - type: euclidean_pearson
            value: 78.72111945793154
          - type: euclidean_spearman
            value: 78.79729904606872
          - type: manhattan_pearson
            value: 78.72464311117116
          - type: manhattan_spearman
            value: 78.822591248334
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-en)
          config: en-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 82.04318630630854
          - type: cos_sim_spearman
            value: 83.87886389259836
          - type: euclidean_pearson
            value: 83.40385877895086
          - type: euclidean_spearman
            value: 83.87886389259836
          - type: manhattan_pearson
            value: 83.46337128901547
          - type: manhattan_spearman
            value: 83.9723106941644
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (en)
          config: en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 63.003511169944595
          - type: cos_sim_spearman
            value: 64.39318805580227
          - type: euclidean_pearson
            value: 65.4797990735967
          - type: euclidean_spearman
            value: 64.39318805580227
          - type: manhattan_pearson
            value: 65.44604544280844
          - type: manhattan_spearman
            value: 64.38742899984233
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 76.63101237585029
          - type: cos_sim_spearman
            value: 75.57446967644269
          - type: euclidean_pearson
            value: 76.93491768734478
          - type: euclidean_spearman
            value: 75.57446967644269
          - type: manhattan_pearson
            value: 76.92187567800636
          - type: manhattan_spearman
            value: 75.57239337194585
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 78.5376604868993
          - type: mrr
            value: 92.94422897364073
      - task:
          type: Retrieval
        dataset:
          type: scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 38.872
          - type: map_at_10
            value: 50.417
          - type: map_at_100
            value: 51.202000000000005
          - type: map_at_1000
            value: 51.25999999999999
          - type: map_at_3
            value: 47.02
          - type: map_at_5
            value: 49.326
          - type: mrr_at_1
            value: 41
          - type: mrr_at_10
            value: 51.674
          - type: mrr_at_100
            value: 52.32599999999999
          - type: mrr_at_1000
            value: 52.376999999999995
          - type: mrr_at_3
            value: 48.778
          - type: mrr_at_5
            value: 50.744
          - type: ndcg_at_1
            value: 41
          - type: ndcg_at_10
            value: 56.027
          - type: ndcg_at_100
            value: 59.362
          - type: ndcg_at_1000
            value: 60.839
          - type: ndcg_at_3
            value: 50.019999999999996
          - type: ndcg_at_5
            value: 53.644999999999996
          - type: precision_at_1
            value: 41
          - type: precision_at_10
            value: 8.1
          - type: precision_at_100
            value: 0.987
          - type: precision_at_1000
            value: 0.11100000000000002
          - type: precision_at_3
            value: 20.444000000000003
          - type: precision_at_5
            value: 14.466999999999999
          - type: recall_at_1
            value: 38.872
          - type: recall_at_10
            value: 71.906
          - type: recall_at_100
            value: 86.367
          - type: recall_at_1000
            value: 98
          - type: recall_at_3
            value: 56.206
          - type: recall_at_5
            value: 65.05
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.7039603960396
          - type: cos_sim_ap
            value: 90.40809844250262
          - type: cos_sim_f1
            value: 84.53181583031557
          - type: cos_sim_precision
            value: 87.56698821007502
          - type: cos_sim_recall
            value: 81.69999999999999
          - type: dot_accuracy
            value: 99.7039603960396
          - type: dot_ap
            value: 90.40809844250262
          - type: dot_f1
            value: 84.53181583031557
          - type: dot_precision
            value: 87.56698821007502
          - type: dot_recall
            value: 81.69999999999999
          - type: euclidean_accuracy
            value: 99.7039603960396
          - type: euclidean_ap
            value: 90.4080982863383
          - type: euclidean_f1
            value: 84.53181583031557
          - type: euclidean_precision
            value: 87.56698821007502
          - type: euclidean_recall
            value: 81.69999999999999
          - type: manhattan_accuracy
            value: 99.7
          - type: manhattan_ap
            value: 90.39771161966652
          - type: manhattan_f1
            value: 84.32989690721648
          - type: manhattan_precision
            value: 87.02127659574468
          - type: manhattan_recall
            value: 81.8
          - type: max_accuracy
            value: 99.7039603960396
          - type: max_ap
            value: 90.40809844250262
          - type: max_f1
            value: 84.53181583031557
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 59.663210666678715
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 32.107791216468776
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 46.440691925067604
          - type: mrr
            value: 47.03390257618199
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 31.067177519784074
          - type: cos_sim_spearman
            value: 31.234728424648967
          - type: dot_pearson
            value: 31.06717083018107
          - type: dot_spearman
            value: 31.234728424648967
      - task:
          type: Retrieval
        dataset:
          type: trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 0.136
          - type: map_at_10
            value: 0.767
          - type: map_at_100
            value: 3.3689999999999998
          - type: map_at_1000
            value: 8.613999999999999
          - type: map_at_3
            value: 0.369
          - type: map_at_5
            value: 0.514
          - type: mrr_at_1
            value: 48
          - type: mrr_at_10
            value: 63.908
          - type: mrr_at_100
            value: 64.615
          - type: mrr_at_1000
            value: 64.615
          - type: mrr_at_3
            value: 62
          - type: mrr_at_5
            value: 63.4
          - type: ndcg_at_1
            value: 44
          - type: ndcg_at_10
            value: 38.579
          - type: ndcg_at_100
            value: 26.409
          - type: ndcg_at_1000
            value: 26.858999999999998
          - type: ndcg_at_3
            value: 47.134
          - type: ndcg_at_5
            value: 43.287
          - type: precision_at_1
            value: 48
          - type: precision_at_10
            value: 40.400000000000006
          - type: precision_at_100
            value: 26.640000000000004
          - type: precision_at_1000
            value: 12.04
          - type: precision_at_3
            value: 52.666999999999994
          - type: precision_at_5
            value: 46.800000000000004
          - type: recall_at_1
            value: 0.136
          - type: recall_at_10
            value: 1.0070000000000001
          - type: recall_at_100
            value: 6.318
          - type: recall_at_1000
            value: 26.522000000000002
          - type: recall_at_3
            value: 0.41700000000000004
          - type: recall_at_5
            value: 0.606
      - task:
          type: Retrieval
        dataset:
          type: webis-touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 1.9949999999999999
          - type: map_at_10
            value: 8.304
          - type: map_at_100
            value: 13.644
          - type: map_at_1000
            value: 15.43
          - type: map_at_3
            value: 4.788
          - type: map_at_5
            value: 6.22
          - type: mrr_at_1
            value: 22.448999999999998
          - type: mrr_at_10
            value: 37.658
          - type: mrr_at_100
            value: 38.491
          - type: mrr_at_1000
            value: 38.503
          - type: mrr_at_3
            value: 32.312999999999995
          - type: mrr_at_5
            value: 35.68
          - type: ndcg_at_1
            value: 21.429000000000002
          - type: ndcg_at_10
            value: 18.995
          - type: ndcg_at_100
            value: 32.029999999999994
          - type: ndcg_at_1000
            value: 44.852
          - type: ndcg_at_3
            value: 19.464000000000002
          - type: ndcg_at_5
            value: 19.172
          - type: precision_at_1
            value: 22.448999999999998
          - type: precision_at_10
            value: 17.143
          - type: precision_at_100
            value: 6.877999999999999
          - type: precision_at_1000
            value: 1.524
          - type: precision_at_3
            value: 21.769
          - type: precision_at_5
            value: 20
          - type: recall_at_1
            value: 1.9949999999999999
          - type: recall_at_10
            value: 13.395999999999999
          - type: recall_at_100
            value: 44.348
          - type: recall_at_1000
            value: 82.622
          - type: recall_at_3
            value: 5.896
          - type: recall_at_5
            value: 8.554
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 67.9394
          - type: ap
            value: 12.943337263423334
          - type: f1
            value: 52.28243093094156
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 56.414827391058296
          - type: f1
            value: 56.666412409573105
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 47.009746255495465
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 84.02574953805807
          - type: cos_sim_ap
            value: 67.66599910763128
          - type: cos_sim_f1
            value: 63.491277990844985
          - type: cos_sim_precision
            value: 59.77172140694154
          - type: cos_sim_recall
            value: 67.70448548812665
          - type: dot_accuracy
            value: 84.02574953805807
          - type: dot_ap
            value: 67.66600090945406
          - type: dot_f1
            value: 63.491277990844985
          - type: dot_precision
            value: 59.77172140694154
          - type: dot_recall
            value: 67.70448548812665
          - type: euclidean_accuracy
            value: 84.02574953805807
          - type: euclidean_ap
            value: 67.6659842364448
          - type: euclidean_f1
            value: 63.491277990844985
          - type: euclidean_precision
            value: 59.77172140694154
          - type: euclidean_recall
            value: 67.70448548812665
          - type: manhattan_accuracy
            value: 84.0317100792752
          - type: manhattan_ap
            value: 67.66351692448987
          - type: manhattan_f1
            value: 63.48610948306178
          - type: manhattan_precision
            value: 57.11875131828729
          - type: manhattan_recall
            value: 71.45118733509234
          - type: max_accuracy
            value: 84.0317100792752
          - type: max_ap
            value: 67.66600090945406
          - type: max_f1
            value: 63.491277990844985
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 87.53832421314084
          - type: cos_sim_ap
            value: 83.11416594316626
          - type: cos_sim_f1
            value: 75.41118114347518
          - type: cos_sim_precision
            value: 73.12839059674504
          - type: cos_sim_recall
            value: 77.8410840776101
          - type: dot_accuracy
            value: 87.53832421314084
          - type: dot_ap
            value: 83.11416226342155
          - type: dot_f1
            value: 75.41118114347518
          - type: dot_precision
            value: 73.12839059674504
          - type: dot_recall
            value: 77.8410840776101
          - type: euclidean_accuracy
            value: 87.53832421314084
          - type: euclidean_ap
            value: 83.11416284455395
          - type: euclidean_f1
            value: 75.41118114347518
          - type: euclidean_precision
            value: 73.12839059674504
          - type: euclidean_recall
            value: 77.8410840776101
          - type: manhattan_accuracy
            value: 87.49369348391353
          - type: manhattan_ap
            value: 83.08066812574694
          - type: manhattan_f1
            value: 75.36561228603892
          - type: manhattan_precision
            value: 71.9202518363064
          - type: manhattan_recall
            value: 79.15768401601478
          - type: max_accuracy
            value: 87.53832421314084
          - type: max_ap
            value: 83.11416594316626
          - type: max_f1
            value: 75.41118114347518