README.md

metadata

license: apache-2.0
tags:
  - mteb
model-index:
  - name: tiny
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 65.08955223880598
          - type: ap
            value: 28.514291209445364
          - type: f1
            value: 59.2604580112738
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 70.035375
          - type: ap
            value: 64.29444264250405
          - type: f1
            value: 69.78382333907138
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 35.343999999999994
          - type: f1
            value: 34.69618251902858
      - task:
          type: Retrieval
        dataset:
          type: mteb/arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
        metrics:
          - type: map_at_1
            value: 28.592000000000002
          - type: map_at_10
            value: 43.597
          - type: map_at_100
            value: 44.614
          - type: map_at_1000
            value: 44.624
          - type: map_at_3
            value: 38.928000000000004
          - type: map_at_5
            value: 41.453
          - type: mrr_at_1
            value: 29.232000000000003
          - type: mrr_at_10
            value: 43.829
          - type: mrr_at_100
            value: 44.852
          - type: mrr_at_1000
            value: 44.862
          - type: mrr_at_3
            value: 39.118
          - type: mrr_at_5
            value: 41.703
          - type: ndcg_at_1
            value: 28.592000000000002
          - type: ndcg_at_10
            value: 52.081
          - type: ndcg_at_100
            value: 56.37
          - type: ndcg_at_1000
            value: 56.598000000000006
          - type: ndcg_at_3
            value: 42.42
          - type: ndcg_at_5
            value: 46.965
          - type: precision_at_1
            value: 28.592000000000002
          - type: precision_at_10
            value: 7.922999999999999
          - type: precision_at_100
            value: 0.979
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 17.52
          - type: precision_at_5
            value: 12.717
          - type: recall_at_1
            value: 28.592000000000002
          - type: recall_at_10
            value: 79.232
          - type: recall_at_100
            value: 97.866
          - type: recall_at_1000
            value: 99.57300000000001
          - type: recall_at_3
            value: 52.559999999999995
          - type: recall_at_5
            value: 63.585
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 43.50220588953974
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 32.08725826118282
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 60.25381587694928
          - type: mrr
            value: 73.79776194873148
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 85.47489332445278
          - type: cos_sim_spearman
            value: 84.05432487336698
          - type: euclidean_pearson
            value: 84.5108222177219
          - type: euclidean_spearman
            value: 84.05432487336698
          - type: manhattan_pearson
            value: 84.20440618321464
          - type: manhattan_spearman
            value: 83.9290208134097
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 76.37337662337663
          - type: f1
            value: 75.33296834885043
      - task:
          type: Clustering
        dataset:
          type: jinaai/big-patent-clustering
          name: MTEB BigPatentClustering
          config: default
          split: test
          revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
        metrics:
          - type: v_measure
            value: 21.31174373264835
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 34.481973521597844
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 26.14094256567341
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-android
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: f46a197baaae43b4f621051089b82a364682dfeb
        metrics:
          - type: map_at_1
            value: 32.527
          - type: map_at_10
            value: 43.699
          - type: map_at_100
            value: 45.03
          - type: map_at_1000
            value: 45.157000000000004
          - type: map_at_3
            value: 39.943
          - type: map_at_5
            value: 42.324
          - type: mrr_at_1
            value: 39.771
          - type: mrr_at_10
            value: 49.277
          - type: mrr_at_100
            value: 49.956
          - type: mrr_at_1000
            value: 50.005
          - type: mrr_at_3
            value: 46.304
          - type: mrr_at_5
            value: 48.493
          - type: ndcg_at_1
            value: 39.771
          - type: ndcg_at_10
            value: 49.957
          - type: ndcg_at_100
            value: 54.678000000000004
          - type: ndcg_at_1000
            value: 56.751
          - type: ndcg_at_3
            value: 44.608
          - type: ndcg_at_5
            value: 47.687000000000005
          - type: precision_at_1
            value: 39.771
          - type: precision_at_10
            value: 9.557
          - type: precision_at_100
            value: 1.5010000000000001
          - type: precision_at_1000
            value: 0.194
          - type: precision_at_3
            value: 21.173000000000002
          - type: precision_at_5
            value: 15.794
          - type: recall_at_1
            value: 32.527
          - type: recall_at_10
            value: 61.791
          - type: recall_at_100
            value: 81.49300000000001
          - type: recall_at_1000
            value: 95.014
          - type: recall_at_3
            value: 46.605000000000004
          - type: recall_at_5
            value: 54.83
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-english
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
        metrics:
          - type: map_at_1
            value: 29.424
          - type: map_at_10
            value: 38.667
          - type: map_at_100
            value: 39.771
          - type: map_at_1000
            value: 39.899
          - type: map_at_3
            value: 35.91
          - type: map_at_5
            value: 37.45
          - type: mrr_at_1
            value: 36.687999999999995
          - type: mrr_at_10
            value: 44.673
          - type: mrr_at_100
            value: 45.289
          - type: mrr_at_1000
            value: 45.338
          - type: mrr_at_3
            value: 42.601
          - type: mrr_at_5
            value: 43.875
          - type: ndcg_at_1
            value: 36.687999999999995
          - type: ndcg_at_10
            value: 44.013000000000005
          - type: ndcg_at_100
            value: 48.13
          - type: ndcg_at_1000
            value: 50.294000000000004
          - type: ndcg_at_3
            value: 40.056999999999995
          - type: ndcg_at_5
            value: 41.902
          - type: precision_at_1
            value: 36.687999999999995
          - type: precision_at_10
            value: 8.158999999999999
          - type: precision_at_100
            value: 1.321
          - type: precision_at_1000
            value: 0.179
          - type: precision_at_3
            value: 19.045
          - type: precision_at_5
            value: 13.427
          - type: recall_at_1
            value: 29.424
          - type: recall_at_10
            value: 53.08500000000001
          - type: recall_at_100
            value: 70.679
          - type: recall_at_1000
            value: 84.66
          - type: recall_at_3
            value: 41.399
          - type: recall_at_5
            value: 46.632
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-gaming
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: 4885aa143210c98657558c04aaf3dc47cfb54340
        metrics:
          - type: map_at_1
            value: 39.747
          - type: map_at_10
            value: 51.452
          - type: map_at_100
            value: 52.384
          - type: map_at_1000
            value: 52.437
          - type: map_at_3
            value: 48.213
          - type: map_at_5
            value: 50.195
          - type: mrr_at_1
            value: 45.391999999999996
          - type: mrr_at_10
            value: 54.928
          - type: mrr_at_100
            value: 55.532000000000004
          - type: mrr_at_1000
            value: 55.565
          - type: mrr_at_3
            value: 52.456
          - type: mrr_at_5
            value: 54.054
          - type: ndcg_at_1
            value: 45.391999999999996
          - type: ndcg_at_10
            value: 57.055
          - type: ndcg_at_100
            value: 60.751999999999995
          - type: ndcg_at_1000
            value: 61.864
          - type: ndcg_at_3
            value: 51.662
          - type: ndcg_at_5
            value: 54.613
          - type: precision_at_1
            value: 45.391999999999996
          - type: precision_at_10
            value: 9.103
          - type: precision_at_100
            value: 1.1780000000000002
          - type: precision_at_1000
            value: 0.132
          - type: precision_at_3
            value: 22.717000000000002
          - type: precision_at_5
            value: 15.812000000000001
          - type: recall_at_1
            value: 39.747
          - type: recall_at_10
            value: 70.10499999999999
          - type: recall_at_100
            value: 86.23100000000001
          - type: recall_at_1000
            value: 94.025
          - type: recall_at_3
            value: 55.899
          - type: recall_at_5
            value: 63.05500000000001
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-gis
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: 5003b3064772da1887988e05400cf3806fe491f2
        metrics:
          - type: map_at_1
            value: 27.168999999999997
          - type: map_at_10
            value: 34.975
          - type: map_at_100
            value: 35.94
          - type: map_at_1000
            value: 36.021
          - type: map_at_3
            value: 32.35
          - type: map_at_5
            value: 33.831
          - type: mrr_at_1
            value: 28.701
          - type: mrr_at_10
            value: 36.698
          - type: mrr_at_100
            value: 37.546
          - type: mrr_at_1000
            value: 37.613
          - type: mrr_at_3
            value: 34.256
          - type: mrr_at_5
            value: 35.685
          - type: ndcg_at_1
            value: 28.701
          - type: ndcg_at_10
            value: 39.639
          - type: ndcg_at_100
            value: 44.389
          - type: ndcg_at_1000
            value: 46.46
          - type: ndcg_at_3
            value: 34.52
          - type: ndcg_at_5
            value: 37.076
          - type: precision_at_1
            value: 28.701
          - type: precision_at_10
            value: 5.955
          - type: precision_at_100
            value: 0.8880000000000001
          - type: precision_at_1000
            value: 0.109
          - type: precision_at_3
            value: 14.274999999999999
          - type: precision_at_5
            value: 10.011000000000001
          - type: recall_at_1
            value: 27.168999999999997
          - type: recall_at_10
            value: 52.347
          - type: recall_at_100
            value: 74.1
          - type: recall_at_1000
            value: 89.739
          - type: recall_at_3
            value: 38.567
          - type: recall_at_5
            value: 44.767
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-mathematica
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: 90fceea13679c63fe563ded68f3b6f06e50061de
        metrics:
          - type: map_at_1
            value: 15.872
          - type: map_at_10
            value: 23.153000000000002
          - type: map_at_100
            value: 24.311
          - type: map_at_1000
            value: 24.432000000000002
          - type: map_at_3
            value: 20.707
          - type: map_at_5
            value: 21.921
          - type: mrr_at_1
            value: 19.776
          - type: mrr_at_10
            value: 27.755999999999997
          - type: mrr_at_100
            value: 28.709
          - type: mrr_at_1000
            value: 28.778
          - type: mrr_at_3
            value: 25.186999999999998
          - type: mrr_at_5
            value: 26.43
          - type: ndcg_at_1
            value: 19.776
          - type: ndcg_at_10
            value: 28.288999999999998
          - type: ndcg_at_100
            value: 34.011
          - type: ndcg_at_1000
            value: 36.916
          - type: ndcg_at_3
            value: 23.551
          - type: ndcg_at_5
            value: 25.429000000000002
          - type: precision_at_1
            value: 19.776
          - type: precision_at_10
            value: 5.311
          - type: precision_at_100
            value: 0.9440000000000001
          - type: precision_at_1000
            value: 0.132
          - type: precision_at_3
            value: 11.360000000000001
          - type: precision_at_5
            value: 8.209
          - type: recall_at_1
            value: 15.872
          - type: recall_at_10
            value: 39.726
          - type: recall_at_100
            value: 65.035
          - type: recall_at_1000
            value: 85.846
          - type: recall_at_3
            value: 26.432
          - type: recall_at_5
            value: 31.22
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-physics
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
        metrics:
          - type: map_at_1
            value: 28.126
          - type: map_at_10
            value: 37.537
          - type: map_at_100
            value: 38.807
          - type: map_at_1000
            value: 38.923
          - type: map_at_3
            value: 34.65
          - type: map_at_5
            value: 36.248000000000005
          - type: mrr_at_1
            value: 34.649
          - type: mrr_at_10
            value: 42.893
          - type: mrr_at_100
            value: 43.721
          - type: mrr_at_1000
            value: 43.775999999999996
          - type: mrr_at_3
            value: 40.488
          - type: mrr_at_5
            value: 41.729
          - type: ndcg_at_1
            value: 34.649
          - type: ndcg_at_10
            value: 43.072
          - type: ndcg_at_100
            value: 48.464
          - type: ndcg_at_1000
            value: 50.724000000000004
          - type: ndcg_at_3
            value: 38.506
          - type: ndcg_at_5
            value: 40.522000000000006
          - type: precision_at_1
            value: 34.649
          - type: precision_at_10
            value: 7.68
          - type: precision_at_100
            value: 1.214
          - type: precision_at_1000
            value: 0.16
          - type: precision_at_3
            value: 18.029999999999998
          - type: precision_at_5
            value: 12.666
          - type: recall_at_1
            value: 28.126
          - type: recall_at_10
            value: 54.396
          - type: recall_at_100
            value: 76.988
          - type: recall_at_1000
            value: 91.85799999999999
          - type: recall_at_3
            value: 41.169
          - type: recall_at_5
            value: 46.658
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-programmers
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
        metrics:
          - type: map_at_1
            value: 26.68
          - type: map_at_10
            value: 35.702
          - type: map_at_100
            value: 36.864999999999995
          - type: map_at_1000
            value: 36.977
          - type: map_at_3
            value: 32.828
          - type: map_at_5
            value: 34.481
          - type: mrr_at_1
            value: 32.991
          - type: mrr_at_10
            value: 40.993
          - type: mrr_at_100
            value: 41.827
          - type: mrr_at_1000
            value: 41.887
          - type: mrr_at_3
            value: 38.623000000000005
          - type: mrr_at_5
            value: 40.021
          - type: ndcg_at_1
            value: 32.991
          - type: ndcg_at_10
            value: 41.036
          - type: ndcg_at_100
            value: 46.294000000000004
          - type: ndcg_at_1000
            value: 48.644
          - type: ndcg_at_3
            value: 36.419000000000004
          - type: ndcg_at_5
            value: 38.618
          - type: precision_at_1
            value: 32.991
          - type: precision_at_10
            value: 7.385999999999999
          - type: precision_at_100
            value: 1.176
          - type: precision_at_1000
            value: 0.151
          - type: precision_at_3
            value: 17.122999999999998
          - type: precision_at_5
            value: 12.215
          - type: recall_at_1
            value: 26.68
          - type: recall_at_10
            value: 51.644
          - type: recall_at_100
            value: 74.55000000000001
          - type: recall_at_1000
            value: 90.825
          - type: recall_at_3
            value: 38.579
          - type: recall_at_5
            value: 44.512
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
        metrics:
          - type: map_at_1
            value: 26.30825
          - type: map_at_10
            value: 34.97866666666666
          - type: map_at_100
            value: 36.109249999999996
          - type: map_at_1000
            value: 36.22508333333333
          - type: map_at_3
            value: 32.239083333333326
          - type: map_at_5
            value: 33.75933333333334
          - type: mrr_at_1
            value: 31.05308333333333
          - type: mrr_at_10
            value: 39.099833333333336
          - type: mrr_at_100
            value: 39.92008333333334
          - type: mrr_at_1000
            value: 39.980000000000004
          - type: mrr_at_3
            value: 36.75958333333333
          - type: mrr_at_5
            value: 38.086416666666665
          - type: ndcg_at_1
            value: 31.05308333333333
          - type: ndcg_at_10
            value: 40.11558333333334
          - type: ndcg_at_100
            value: 45.05966666666667
          - type: ndcg_at_1000
            value: 47.36516666666667
          - type: ndcg_at_3
            value: 35.490833333333335
          - type: ndcg_at_5
            value: 37.64541666666666
          - type: precision_at_1
            value: 31.05308333333333
          - type: precision_at_10
            value: 6.968416666666666
          - type: precision_at_100
            value: 1.1156666666666666
          - type: precision_at_1000
            value: 0.14950000000000002
          - type: precision_at_3
            value: 16.123
          - type: precision_at_5
            value: 11.451166666666666
          - type: recall_at_1
            value: 26.30825
          - type: recall_at_10
            value: 51.19283333333333
          - type: recall_at_100
            value: 73.0285
          - type: recall_at_1000
            value: 89.11133333333333
          - type: recall_at_3
            value: 38.26208333333333
          - type: recall_at_5
            value: 43.855916666666666
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-stats
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
        metrics:
          - type: map_at_1
            value: 23.363999999999997
          - type: map_at_10
            value: 30.606
          - type: map_at_100
            value: 31.491999999999997
          - type: map_at_1000
            value: 31.578
          - type: map_at_3
            value: 28.610000000000003
          - type: map_at_5
            value: 29.602
          - type: mrr_at_1
            value: 26.38
          - type: mrr_at_10
            value: 33.472
          - type: mrr_at_100
            value: 34.299
          - type: mrr_at_1000
            value: 34.361999999999995
          - type: mrr_at_3
            value: 31.696999999999996
          - type: mrr_at_5
            value: 32.503
          - type: ndcg_at_1
            value: 26.38
          - type: ndcg_at_10
            value: 34.772999999999996
          - type: ndcg_at_100
            value: 39.334
          - type: ndcg_at_1000
            value: 41.676
          - type: ndcg_at_3
            value: 31.097
          - type: ndcg_at_5
            value: 32.561
          - type: precision_at_1
            value: 26.38
          - type: precision_at_10
            value: 5.475
          - type: precision_at_100
            value: 0.84
          - type: precision_at_1000
            value: 0.11100000000000002
          - type: precision_at_3
            value: 13.395000000000001
          - type: precision_at_5
            value: 9.11
          - type: recall_at_1
            value: 23.363999999999997
          - type: recall_at_10
            value: 44.656
          - type: recall_at_100
            value: 65.77199999999999
          - type: recall_at_1000
            value: 83.462
          - type: recall_at_3
            value: 34.213
          - type: recall_at_5
            value: 38.091
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-tex
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: 46989137a86843e03a6195de44b09deda022eec7
        metrics:
          - type: map_at_1
            value: 17.971999999999998
          - type: map_at_10
            value: 24.913
          - type: map_at_100
            value: 25.916
          - type: map_at_1000
            value: 26.049
          - type: map_at_3
            value: 22.569
          - type: map_at_5
            value: 23.858999999999998
          - type: mrr_at_1
            value: 21.748
          - type: mrr_at_10
            value: 28.711
          - type: mrr_at_100
            value: 29.535
          - type: mrr_at_1000
            value: 29.621
          - type: mrr_at_3
            value: 26.484999999999996
          - type: mrr_at_5
            value: 27.701999999999998
          - type: ndcg_at_1
            value: 21.748
          - type: ndcg_at_10
            value: 29.412
          - type: ndcg_at_100
            value: 34.204
          - type: ndcg_at_1000
            value: 37.358000000000004
          - type: ndcg_at_3
            value: 25.202
          - type: ndcg_at_5
            value: 27.128000000000004
          - type: precision_at_1
            value: 21.748
          - type: precision_at_10
            value: 5.279
          - type: precision_at_100
            value: 0.902
          - type: precision_at_1000
            value: 0.135
          - type: precision_at_3
            value: 11.551
          - type: precision_at_5
            value: 8.437999999999999
          - type: recall_at_1
            value: 17.971999999999998
          - type: recall_at_10
            value: 39.186
          - type: recall_at_100
            value: 60.785999999999994
          - type: recall_at_1000
            value: 83.372
          - type: recall_at_3
            value: 27.584999999999997
          - type: recall_at_5
            value: 32.448
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-unix
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
        metrics:
          - type: map_at_1
            value: 26.684
          - type: map_at_10
            value: 35.188
          - type: map_at_100
            value: 36.379
          - type: map_at_1000
            value: 36.481
          - type: map_at_3
            value: 32.401
          - type: map_at_5
            value: 34.132
          - type: mrr_at_1
            value: 31.063000000000002
          - type: mrr_at_10
            value: 39.104
          - type: mrr_at_100
            value: 40.062999999999995
          - type: mrr_at_1000
            value: 40.119
          - type: mrr_at_3
            value: 36.692
          - type: mrr_at_5
            value: 38.161
          - type: ndcg_at_1
            value: 31.063000000000002
          - type: ndcg_at_10
            value: 40.096
          - type: ndcg_at_100
            value: 45.616
          - type: ndcg_at_1000
            value: 47.869
          - type: ndcg_at_3
            value: 35.256
          - type: ndcg_at_5
            value: 37.826
          - type: precision_at_1
            value: 31.063000000000002
          - type: precision_at_10
            value: 6.622999999999999
          - type: precision_at_100
            value: 1.046
          - type: precision_at_1000
            value: 0.135
          - type: precision_at_3
            value: 15.641
          - type: precision_at_5
            value: 11.231
          - type: recall_at_1
            value: 26.684
          - type: recall_at_10
            value: 51.092999999999996
          - type: recall_at_100
            value: 75.099
          - type: recall_at_1000
            value: 90.644
          - type: recall_at_3
            value: 38.063
          - type: recall_at_5
            value: 44.518
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-webmasters
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: 160c094312a0e1facb97e55eeddb698c0abe3571
        metrics:
          - type: map_at_1
            value: 26.249
          - type: map_at_10
            value: 34.694
          - type: map_at_100
            value: 36.208
          - type: map_at_1000
            value: 36.443
          - type: map_at_3
            value: 31.868000000000002
          - type: map_at_5
            value: 33.018
          - type: mrr_at_1
            value: 31.818
          - type: mrr_at_10
            value: 39.416000000000004
          - type: mrr_at_100
            value: 40.327
          - type: mrr_at_1000
            value: 40.388000000000005
          - type: mrr_at_3
            value: 37.120999999999995
          - type: mrr_at_5
            value: 38.07
          - type: ndcg_at_1
            value: 31.818
          - type: ndcg_at_10
            value: 40.405
          - type: ndcg_at_100
            value: 45.816
          - type: ndcg_at_1000
            value: 48.403
          - type: ndcg_at_3
            value: 35.823
          - type: ndcg_at_5
            value: 37.191
          - type: precision_at_1
            value: 31.818
          - type: precision_at_10
            value: 7.806
          - type: precision_at_100
            value: 1.518
          - type: precision_at_1000
            value: 0.241
          - type: precision_at_3
            value: 16.535
          - type: precision_at_5
            value: 11.738999999999999
          - type: recall_at_1
            value: 26.249
          - type: recall_at_10
            value: 50.928
          - type: recall_at_100
            value: 75.271
          - type: recall_at_1000
            value: 91.535
          - type: recall_at_3
            value: 37.322
          - type: recall_at_5
            value: 41.318
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-wordpress
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
        metrics:
          - type: map_at_1
            value: 21.884999999999998
          - type: map_at_10
            value: 29.158
          - type: map_at_100
            value: 30.208000000000002
          - type: map_at_1000
            value: 30.304
          - type: map_at_3
            value: 26.82
          - type: map_at_5
            value: 28.051
          - type: mrr_at_1
            value: 23.66
          - type: mrr_at_10
            value: 31.277
          - type: mrr_at_100
            value: 32.237
          - type: mrr_at_1000
            value: 32.308
          - type: mrr_at_3
            value: 29.205
          - type: mrr_at_5
            value: 30.314000000000004
          - type: ndcg_at_1
            value: 23.66
          - type: ndcg_at_10
            value: 33.64
          - type: ndcg_at_100
            value: 39.028
          - type: ndcg_at_1000
            value: 41.423
          - type: ndcg_at_3
            value: 29.189
          - type: ndcg_at_5
            value: 31.191999999999997
          - type: precision_at_1
            value: 23.66
          - type: precision_at_10
            value: 5.287
          - type: precision_at_100
            value: 0.86
          - type: precision_at_1000
            value: 0.11499999999999999
          - type: precision_at_3
            value: 12.631
          - type: precision_at_5
            value: 8.762
          - type: recall_at_1
            value: 21.884999999999998
          - type: recall_at_10
            value: 45.357
          - type: recall_at_100
            value: 70.338
          - type: recall_at_1000
            value: 88.356
          - type: recall_at_3
            value: 33.312000000000005
          - type: recall_at_5
            value: 38.222
      - task:
          type: Retrieval
        dataset:
          type: mteb/climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
        metrics:
          - type: map_at_1
            value: 13.058
          - type: map_at_10
            value: 21.549
          - type: map_at_100
            value: 23.287
          - type: map_at_1000
            value: 23.444000000000003
          - type: map_at_3
            value: 18.18
          - type: map_at_5
            value: 19.886
          - type: mrr_at_1
            value: 28.73
          - type: mrr_at_10
            value: 40.014
          - type: mrr_at_100
            value: 40.827000000000005
          - type: mrr_at_1000
            value: 40.866
          - type: mrr_at_3
            value: 36.602000000000004
          - type: mrr_at_5
            value: 38.702
          - type: ndcg_at_1
            value: 28.73
          - type: ndcg_at_10
            value: 29.881
          - type: ndcg_at_100
            value: 36.662
          - type: ndcg_at_1000
            value: 39.641999999999996
          - type: ndcg_at_3
            value: 24.661
          - type: ndcg_at_5
            value: 26.548
          - type: precision_at_1
            value: 28.73
          - type: precision_at_10
            value: 9.094
          - type: precision_at_100
            value: 1.6480000000000001
          - type: precision_at_1000
            value: 0.22100000000000003
          - type: precision_at_3
            value: 17.98
          - type: precision_at_5
            value: 13.811000000000002
          - type: recall_at_1
            value: 13.058
          - type: recall_at_10
            value: 35.458
          - type: recall_at_100
            value: 58.719
          - type: recall_at_1000
            value: 75.495
          - type: recall_at_3
            value: 22.607
          - type: recall_at_5
            value: 28.067999999999998
      - task:
          type: Retrieval
        dataset:
          type: mteb/dbpedia
          name: MTEB DBPedia
          config: default
          split: test
          revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
        metrics:
          - type: map_at_1
            value: 8.811
          - type: map_at_10
            value: 19.134999999999998
          - type: map_at_100
            value: 26.905
          - type: map_at_1000
            value: 28.503
          - type: map_at_3
            value: 13.863
          - type: map_at_5
            value: 16.062
          - type: mrr_at_1
            value: 67
          - type: mrr_at_10
            value: 74.607
          - type: mrr_at_100
            value: 74.941
          - type: mrr_at_1000
            value: 74.954
          - type: mrr_at_3
            value: 73.042
          - type: mrr_at_5
            value: 73.992
          - type: ndcg_at_1
            value: 52.87500000000001
          - type: ndcg_at_10
            value: 40.199
          - type: ndcg_at_100
            value: 44.901
          - type: ndcg_at_1000
            value: 52.239999999999995
          - type: ndcg_at_3
            value: 44.983000000000004
          - type: ndcg_at_5
            value: 42.137
          - type: precision_at_1
            value: 67
          - type: precision_at_10
            value: 31.8
          - type: precision_at_100
            value: 10.315000000000001
          - type: precision_at_1000
            value: 2.0420000000000003
          - type: precision_at_3
            value: 48.667
          - type: precision_at_5
            value: 40.9
          - type: recall_at_1
            value: 8.811
          - type: recall_at_10
            value: 24.503
          - type: recall_at_100
            value: 51.288999999999994
          - type: recall_at_1000
            value: 74.827
          - type: recall_at_3
            value: 15.254999999999999
          - type: recall_at_5
            value: 18.698999999999998
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 41.839999999999996
          - type: f1
            value: 37.78718146306379
      - task:
          type: Retrieval
        dataset:
          type: mteb/fever
          name: MTEB FEVER
          config: default
          split: test
          revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
        metrics:
          - type: map_at_1
            value: 68.47999999999999
          - type: map_at_10
            value: 78.782
          - type: map_at_100
            value: 79.021
          - type: map_at_1000
            value: 79.035
          - type: map_at_3
            value: 77.389
          - type: map_at_5
            value: 78.347
          - type: mrr_at_1
            value: 73.837
          - type: mrr_at_10
            value: 83.41499999999999
          - type: mrr_at_100
            value: 83.53399999999999
          - type: mrr_at_1000
            value: 83.535
          - type: mrr_at_3
            value: 82.32300000000001
          - type: mrr_at_5
            value: 83.13000000000001
          - type: ndcg_at_1
            value: 73.837
          - type: ndcg_at_10
            value: 83.404
          - type: ndcg_at_100
            value: 84.287
          - type: ndcg_at_1000
            value: 84.52199999999999
          - type: ndcg_at_3
            value: 81.072
          - type: ndcg_at_5
            value: 82.537
          - type: precision_at_1
            value: 73.837
          - type: precision_at_10
            value: 10.254000000000001
          - type: precision_at_100
            value: 1.088
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: precision_at_3
            value: 31.538
          - type: precision_at_5
            value: 19.811
          - type: recall_at_1
            value: 68.47999999999999
          - type: recall_at_10
            value: 92.98100000000001
          - type: recall_at_100
            value: 96.50800000000001
          - type: recall_at_1000
            value: 97.925
          - type: recall_at_3
            value: 86.764
          - type: recall_at_5
            value: 90.39
      - task:
          type: Retrieval
        dataset:
          type: mteb/fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: 27a168819829fe9bcd655c2df245fb19452e8e06
        metrics:
          - type: map_at_1
            value: 16.786
          - type: map_at_10
            value: 26.97
          - type: map_at_100
            value: 28.488000000000003
          - type: map_at_1000
            value: 28.665000000000003
          - type: map_at_3
            value: 23.3
          - type: map_at_5
            value: 25.249
          - type: mrr_at_1
            value: 33.025
          - type: mrr_at_10
            value: 41.86
          - type: mrr_at_100
            value: 42.673
          - type: mrr_at_1000
            value: 42.714
          - type: mrr_at_3
            value: 39.403
          - type: mrr_at_5
            value: 40.723
          - type: ndcg_at_1
            value: 33.025
          - type: ndcg_at_10
            value: 34.522999999999996
          - type: ndcg_at_100
            value: 40.831
          - type: ndcg_at_1000
            value: 44.01
          - type: ndcg_at_3
            value: 30.698999999999998
          - type: ndcg_at_5
            value: 31.832
          - type: precision_at_1
            value: 33.025
          - type: precision_at_10
            value: 9.583
          - type: precision_at_100
            value: 1.619
          - type: precision_at_1000
            value: 0.22100000000000003
          - type: precision_at_3
            value: 20.216
          - type: precision_at_5
            value: 15.031
          - type: recall_at_1
            value: 16.786
          - type: recall_at_10
            value: 41.969
          - type: recall_at_100
            value: 66.353
          - type: recall_at_1000
            value: 85.299
          - type: recall_at_3
            value: 28.111000000000004
          - type: recall_at_5
            value: 33.645
      - task:
          type: Retrieval
        dataset:
          type: mteb/hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: ab518f4d6fcca38d87c25209f94beba119d02014
        metrics:
          - type: map_at_1
            value: 37.346000000000004
          - type: map_at_10
            value: 56.184999999999995
          - type: map_at_100
            value: 57.062000000000005
          - type: map_at_1000
            value: 57.126999999999995
          - type: map_at_3
            value: 52.815
          - type: map_at_5
            value: 54.893
          - type: mrr_at_1
            value: 74.693
          - type: mrr_at_10
            value: 81.128
          - type: mrr_at_100
            value: 81.356
          - type: mrr_at_1000
            value: 81.363
          - type: mrr_at_3
            value: 80.05600000000001
          - type: mrr_at_5
            value: 80.74
          - type: ndcg_at_1
            value: 74.693
          - type: ndcg_at_10
            value: 65.249
          - type: ndcg_at_100
            value: 68.357
          - type: ndcg_at_1000
            value: 69.64200000000001
          - type: ndcg_at_3
            value: 60.377
          - type: ndcg_at_5
            value: 63.044
          - type: precision_at_1
            value: 74.693
          - type: precision_at_10
            value: 13.630999999999998
          - type: precision_at_100
            value: 1.606
          - type: precision_at_1000
            value: 0.178
          - type: precision_at_3
            value: 38.222
          - type: precision_at_5
            value: 25.040000000000003
          - type: recall_at_1
            value: 37.346000000000004
          - type: recall_at_10
            value: 68.157
          - type: recall_at_100
            value: 80.297
          - type: recall_at_1000
            value: 88.832
          - type: recall_at_3
            value: 57.333
          - type: recall_at_5
            value: 62.6
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 62.80240000000001
          - type: ap
            value: 58.22949464075975
          - type: f1
            value: 62.55694937343487
      - task:
          type: Retrieval
        dataset:
          type: mteb/msmarco
          name: MTEB MSMARCO
          config: default
          split: dev
          revision: c5a29a104738b98a9e76336939199e264163d4a0
        metrics:
          - type: map_at_1
            value: 20.918
          - type: map_at_10
            value: 32.732
          - type: map_at_100
            value: 33.922000000000004
          - type: map_at_1000
            value: 33.976
          - type: map_at_3
            value: 29.051
          - type: map_at_5
            value: 31.101
          - type: mrr_at_1
            value: 21.418
          - type: mrr_at_10
            value: 33.284000000000006
          - type: mrr_at_100
            value: 34.426
          - type: mrr_at_1000
            value: 34.473
          - type: mrr_at_3
            value: 29.644
          - type: mrr_at_5
            value: 31.691000000000003
          - type: ndcg_at_1
            value: 21.418
          - type: ndcg_at_10
            value: 39.427
          - type: ndcg_at_100
            value: 45.190999999999995
          - type: ndcg_at_1000
            value: 46.544000000000004
          - type: ndcg_at_3
            value: 31.885
          - type: ndcg_at_5
            value: 35.555
          - type: precision_at_1
            value: 21.418
          - type: precision_at_10
            value: 6.254999999999999
          - type: precision_at_100
            value: 0.915
          - type: precision_at_1000
            value: 0.10300000000000001
          - type: precision_at_3
            value: 13.591000000000001
          - type: precision_at_5
            value: 10.011000000000001
          - type: recall_at_1
            value: 20.918
          - type: recall_at_10
            value: 60.074000000000005
          - type: recall_at_100
            value: 86.726
          - type: recall_at_1000
            value: 97.116
          - type: recall_at_3
            value: 39.506
          - type: recall_at_5
            value: 48.319
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 90.79799361605106
          - type: f1
            value: 90.0757957511057
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 58.00501595987233
          - type: f1
            value: 39.85731569133947
      - task:
          type: Classification
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClassification (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: accuracy
            value: 77.10970464135022
          - type: f1
            value: 76.12037616356896
      - task:
          type: Clustering
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClusteringP2P (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: v_measure
            value: 69.81323966287493
      - task:
          type: Clustering
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClusteringS2S (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: v_measure
            value: 33.112774215788455
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 63.51042367182246
          - type: f1
            value: 60.99310361578824
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 71.0053799596503
          - type: f1
            value: 69.7794673003686
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 30.56899174856954
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 26.21848014733929
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 30.256308756916646
          - type: mrr
            value: 31.123872086825656
      - task:
          type: Retrieval
        dataset:
          type: mteb/nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
        metrics:
          - type: map_at_1
            value: 5.07
          - type: map_at_10
            value: 11.286999999999999
          - type: map_at_100
            value: 13.630999999999998
          - type: map_at_1000
            value: 14.844
          - type: map_at_3
            value: 8.395
          - type: map_at_5
            value: 9.721
          - type: mrr_at_1
            value: 41.486000000000004
          - type: mrr_at_10
            value: 51.041000000000004
          - type: mrr_at_100
            value: 51.661
          - type: mrr_at_1000
            value: 51.7
          - type: mrr_at_3
            value: 49.226
          - type: mrr_at_5
            value: 50.526
          - type: ndcg_at_1
            value: 39.783
          - type: ndcg_at_10
            value: 30.885
          - type: ndcg_at_100
            value: 27.459
          - type: ndcg_at_1000
            value: 35.988
          - type: ndcg_at_3
            value: 36.705
          - type: ndcg_at_5
            value: 34.156
          - type: precision_at_1
            value: 41.486000000000004
          - type: precision_at_10
            value: 22.415
          - type: precision_at_100
            value: 6.819999999999999
          - type: precision_at_1000
            value: 1.8980000000000001
          - type: precision_at_3
            value: 34.572
          - type: precision_at_5
            value: 29.287999999999997
          - type: recall_at_1
            value: 5.07
          - type: recall_at_10
            value: 14.576
          - type: recall_at_100
            value: 27.112000000000002
          - type: recall_at_1000
            value: 57.995
          - type: recall_at_3
            value: 9.242
          - type: recall_at_5
            value: 11.668000000000001
      - task:
          type: Retrieval
        dataset:
          type: mteb/nq
          name: MTEB NQ
          config: default
          split: test
          revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
        metrics:
          - type: map_at_1
            value: 32.263999999999996
          - type: map_at_10
            value: 47.219
          - type: map_at_100
            value: 48.209999999999994
          - type: map_at_1000
            value: 48.24
          - type: map_at_3
            value: 42.905
          - type: map_at_5
            value: 45.501000000000005
          - type: mrr_at_1
            value: 36.153
          - type: mrr_at_10
            value: 49.636
          - type: mrr_at_100
            value: 50.357
          - type: mrr_at_1000
            value: 50.378
          - type: mrr_at_3
            value: 46.094
          - type: mrr_at_5
            value: 48.233
          - type: ndcg_at_1
            value: 36.124
          - type: ndcg_at_10
            value: 54.764
          - type: ndcg_at_100
            value: 58.867999999999995
          - type: ndcg_at_1000
            value: 59.548
          - type: ndcg_at_3
            value: 46.717999999999996
          - type: ndcg_at_5
            value: 50.981
          - type: precision_at_1
            value: 36.124
          - type: precision_at_10
            value: 8.931000000000001
          - type: precision_at_100
            value: 1.126
          - type: precision_at_1000
            value: 0.11900000000000001
          - type: precision_at_3
            value: 21.051000000000002
          - type: precision_at_5
            value: 15.104000000000001
          - type: recall_at_1
            value: 32.263999999999996
          - type: recall_at_10
            value: 75.39099999999999
          - type: recall_at_100
            value: 93.038
          - type: recall_at_1000
            value: 98.006
          - type: recall_at_3
            value: 54.562999999999995
          - type: recall_at_5
            value: 64.352
      - task:
          type: Classification
        dataset:
          type: ag_news
          name: MTEB NewsClassification
          config: default
          split: test
          revision: eb185aade064a813bc0b7f42de02595523103ca4
        metrics:
          - type: accuracy
            value: 77.75
          - type: f1
            value: 77.504243291547
      - task:
          type: PairClassification
        dataset:
          type: GEM/opusparcus
          name: MTEB OpusparcusPC (en)
          config: en
          split: test
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
        metrics:
          - type: cos_sim_accuracy
            value: 99.89816700610999
          - type: cos_sim_ap
            value: 100
          - type: cos_sim_f1
            value: 99.9490575649516
          - type: cos_sim_precision
            value: 100
          - type: cos_sim_recall
            value: 99.89816700610999
          - type: dot_accuracy
            value: 99.89816700610999
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.9490575649516
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.89816700610999
          - type: euclidean_accuracy
            value: 99.89816700610999
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.9490575649516
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.89816700610999
          - type: manhattan_accuracy
            value: 99.89816700610999
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.9490575649516
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.89816700610999
          - type: max_accuracy
            value: 99.89816700610999
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.9490575649516
      - task:
          type: PairClassification
        dataset:
          type: paws-x
          name: MTEB PawsX (en)
          config: en
          split: test
          revision: 8a04d940a42cd40658986fdd8e3da561533a3646
        metrics:
          - type: cos_sim_accuracy
            value: 61.75000000000001
          - type: cos_sim_ap
            value: 57.9482264289061
          - type: cos_sim_f1
            value: 62.444061962134256
          - type: cos_sim_precision
            value: 45.3953953953954
          - type: cos_sim_recall
            value: 100
          - type: dot_accuracy
            value: 61.75000000000001
          - type: dot_ap
            value: 57.94808038610475
          - type: dot_f1
            value: 62.444061962134256
          - type: dot_precision
            value: 45.3953953953954
          - type: dot_recall
            value: 100
          - type: euclidean_accuracy
            value: 61.75000000000001
          - type: euclidean_ap
            value: 57.94808038610475
          - type: euclidean_f1
            value: 62.444061962134256
          - type: euclidean_precision
            value: 45.3953953953954
          - type: euclidean_recall
            value: 100
          - type: manhattan_accuracy
            value: 61.7
          - type: manhattan_ap
            value: 57.996119308184966
          - type: manhattan_f1
            value: 62.46078773091669
          - type: manhattan_precision
            value: 45.66768603465851
          - type: manhattan_recall
            value: 98.78721058434398
          - type: max_accuracy
            value: 61.75000000000001
          - type: max_ap
            value: 57.996119308184966
          - type: max_f1
            value: 62.46078773091669
      - task:
          type: Retrieval
        dataset:
          type: mteb/quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
        metrics:
          - type: map_at_1
            value: 69.001
          - type: map_at_10
            value: 82.573
          - type: map_at_100
            value: 83.226
          - type: map_at_1000
            value: 83.246
          - type: map_at_3
            value: 79.625
          - type: map_at_5
            value: 81.491
          - type: mrr_at_1
            value: 79.44
          - type: mrr_at_10
            value: 85.928
          - type: mrr_at_100
            value: 86.05199999999999
          - type: mrr_at_1000
            value: 86.054
          - type: mrr_at_3
            value: 84.847
          - type: mrr_at_5
            value: 85.596
          - type: ndcg_at_1
            value: 79.41
          - type: ndcg_at_10
            value: 86.568
          - type: ndcg_at_100
            value: 87.965
          - type: ndcg_at_1000
            value: 88.134
          - type: ndcg_at_3
            value: 83.55900000000001
          - type: ndcg_at_5
            value: 85.244
          - type: precision_at_1
            value: 79.41
          - type: precision_at_10
            value: 13.108
          - type: precision_at_100
            value: 1.509
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 36.443
          - type: precision_at_5
            value: 24.03
          - type: recall_at_1
            value: 69.001
          - type: recall_at_10
            value: 94.132
          - type: recall_at_100
            value: 99.043
          - type: recall_at_1000
            value: 99.878
          - type: recall_at_3
            value: 85.492
          - type: recall_at_5
            value: 90.226
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 48.3161352736264
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
        metrics:
          - type: v_measure
            value: 57.83784484156747
      - task:
          type: Retrieval
        dataset:
          type: mteb/scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
        metrics:
          - type: map_at_1
            value: 4.403
          - type: map_at_10
            value: 10.922
          - type: map_at_100
            value: 12.626000000000001
          - type: map_at_1000
            value: 12.883
          - type: map_at_3
            value: 7.982
          - type: map_at_5
            value: 9.442
          - type: mrr_at_1
            value: 21.7
          - type: mrr_at_10
            value: 31.653
          - type: mrr_at_100
            value: 32.757999999999996
          - type: mrr_at_1000
            value: 32.824999999999996
          - type: mrr_at_3
            value: 28.266999999999996
          - type: mrr_at_5
            value: 30.127
          - type: ndcg_at_1
            value: 21.7
          - type: ndcg_at_10
            value: 18.355
          - type: ndcg_at_100
            value: 25.228
          - type: ndcg_at_1000
            value: 30.164
          - type: ndcg_at_3
            value: 17.549
          - type: ndcg_at_5
            value: 15.260000000000002
          - type: precision_at_1
            value: 21.7
          - type: precision_at_10
            value: 9.47
          - type: precision_at_100
            value: 1.9290000000000003
          - type: precision_at_1000
            value: 0.312
          - type: precision_at_3
            value: 16.3
          - type: precision_at_5
            value: 13.28
          - type: recall_at_1
            value: 4.403
          - type: recall_at_10
            value: 19.18
          - type: recall_at_100
            value: 39.182
          - type: recall_at_1000
            value: 63.378
          - type: recall_at_3
            value: 9.934999999999999
          - type: recall_at_5
            value: 13.459999999999999
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
        metrics:
          - type: cos_sim_pearson
            value: 76.90841073432534
          - type: cos_sim_spearman
            value: 69.2566375434526
          - type: euclidean_pearson
            value: 73.00183878559413
          - type: euclidean_spearman
            value: 69.25664656235413
          - type: manhattan_pearson
            value: 72.89594756197533
          - type: manhattan_spearman
            value: 69.23247111043545
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 69.60878511794063
          - type: cos_sim_spearman
            value: 65.89916377105551
          - type: euclidean_pearson
            value: 66.90761876557181
          - type: euclidean_spearman
            value: 65.89915018368384
          - type: manhattan_pearson
            value: 66.78502575257721
          - type: manhattan_spearman
            value: 65.79977053467938
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 77.2869334987418
          - type: cos_sim_spearman
            value: 77.86961921643416
          - type: euclidean_pearson
            value: 77.43179820479914
          - type: euclidean_spearman
            value: 77.86961921643416
          - type: manhattan_pearson
            value: 77.18900647348373
          - type: manhattan_spearman
            value: 77.61209060062608
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 76.26453932960364
          - type: cos_sim_spearman
            value: 72.81574657995401
          - type: euclidean_pearson
            value: 75.0708953437423
          - type: euclidean_spearman
            value: 72.81574657995401
          - type: manhattan_pearson
            value: 74.88396609999512
          - type: manhattan_spearman
            value: 72.65437562156805
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 82.37827653919395
          - type: cos_sim_spearman
            value: 83.4885552472602
          - type: euclidean_pearson
            value: 82.89377087926749
          - type: euclidean_spearman
            value: 83.4885552472602
          - type: manhattan_pearson
            value: 82.82440771787735
          - type: manhattan_spearman
            value: 83.41449537888975
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 78.7995043673964
          - type: cos_sim_spearman
            value: 80.57804447517638
          - type: euclidean_pearson
            value: 80.03013884278195
          - type: euclidean_spearman
            value: 80.57804447517638
          - type: manhattan_pearson
            value: 80.13406111544424
          - type: manhattan_spearman
            value: 80.65354602648962
      - 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: 83.63565989937278
          - type: cos_sim_spearman
            value: 84.4948593656943
          - type: euclidean_pearson
            value: 84.68743074820951
          - type: euclidean_spearman
            value: 84.4948593656943
          - type: manhattan_pearson
            value: 84.43639397781811
          - type: manhattan_spearman
            value: 84.32595552115242
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (en)
          config: en
          split: test
          revision: eea2b4fe26a775864c896887d910b76a8098ad3f
        metrics:
          - type: cos_sim_pearson
            value: 65.06382649277246
          - type: cos_sim_spearman
            value: 66.28447782018655
          - type: euclidean_pearson
            value: 67.09895930908392
          - type: euclidean_spearman
            value: 66.28447782018655
          - type: manhattan_pearson
            value: 66.96342453888376
          - type: manhattan_spearman
            value: 66.33876259551842
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 78.43883428940346
          - type: cos_sim_spearman
            value: 79.18395553127085
          - type: euclidean_pearson
            value: 79.22986635457109
          - type: euclidean_spearman
            value: 79.18395553127085
          - type: manhattan_pearson
            value: 79.10921229934691
          - type: manhattan_spearman
            value: 79.02283553930171
      - task:
          type: STS
        dataset:
          type: PhilipMay/stsb_multi_mt
          name: MTEB STSBenchmarkMultilingualSTS (en)
          config: en
          split: test
          revision: 93d57ef91790589e3ce9c365164337a8a78b7632
        metrics:
          - type: cos_sim_pearson
            value: 78.43883433444418
          - type: cos_sim_spearman
            value: 79.18395553127085
          - type: euclidean_pearson
            value: 79.22986642351681
          - type: euclidean_spearman
            value: 79.18395553127085
          - type: manhattan_pearson
            value: 79.10921236746302
          - type: manhattan_spearman
            value: 79.02283553930171
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 76.9361627171417
          - type: mrr
            value: 93.06577046773126
      - task:
          type: Retrieval
        dataset:
          type: mteb/scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
        metrics:
          - type: map_at_1
            value: 50.693999999999996
          - type: map_at_10
            value: 59.784000000000006
          - type: map_at_100
            value: 60.443000000000005
          - type: map_at_1000
            value: 60.480000000000004
          - type: map_at_3
            value: 57.028
          - type: map_at_5
            value: 58.306999999999995
          - type: mrr_at_1
            value: 53.333
          - type: mrr_at_10
            value: 61.565000000000005
          - type: mrr_at_100
            value: 62.095
          - type: mrr_at_1000
            value: 62.131
          - type: mrr_at_3
            value: 59.721999999999994
          - type: mrr_at_5
            value: 60.589000000000006
          - type: ndcg_at_1
            value: 53.333
          - type: ndcg_at_10
            value: 64.512
          - type: ndcg_at_100
            value: 67.366
          - type: ndcg_at_1000
            value: 68.46799999999999
          - type: ndcg_at_3
            value: 59.748999999999995
          - type: ndcg_at_5
            value: 61.526
          - type: precision_at_1
            value: 53.333
          - type: precision_at_10
            value: 8.733
          - type: precision_at_100
            value: 1.027
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 23.222
          - type: precision_at_5
            value: 15.2
          - type: recall_at_1
            value: 50.693999999999996
          - type: recall_at_10
            value: 77.333
          - type: recall_at_100
            value: 90.10000000000001
          - type: recall_at_1000
            value: 99
          - type: recall_at_3
            value: 64.39399999999999
          - type: recall_at_5
            value: 68.7
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.81386138613861
          - type: cos_sim_ap
            value: 94.96375600031361
          - type: cos_sim_f1
            value: 90.36885245901641
          - type: cos_sim_precision
            value: 92.64705882352942
          - type: cos_sim_recall
            value: 88.2
          - type: dot_accuracy
            value: 99.81386138613861
          - type: dot_ap
            value: 94.96375600031361
          - type: dot_f1
            value: 90.36885245901641
          - type: dot_precision
            value: 92.64705882352942
          - type: dot_recall
            value: 88.2
          - type: euclidean_accuracy
            value: 99.81386138613861
          - type: euclidean_ap
            value: 94.96375600031361
          - type: euclidean_f1
            value: 90.36885245901641
          - type: euclidean_precision
            value: 92.64705882352942
          - type: euclidean_recall
            value: 88.2
          - type: manhattan_accuracy
            value: 99.81287128712871
          - type: manhattan_ap
            value: 94.92563500640084
          - type: manhattan_f1
            value: 90.27277406073082
          - type: manhattan_precision
            value: 93.00106044538707
          - type: manhattan_recall
            value: 87.7
          - type: max_accuracy
            value: 99.81386138613861
          - type: max_ap
            value: 94.96375600031361
          - type: max_f1
            value: 90.36885245901641
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 57.486984956276274
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 34.58453023612073
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 50.16317315282306
          - type: mrr
            value: 50.82617137764197
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 30.2927995133324
          - type: cos_sim_spearman
            value: 30.09648622523191
          - type: dot_pearson
            value: 30.29279853541771
          - type: dot_spearman
            value: 30.09648622523191
      - task:
          type: Retrieval
        dataset:
          type: mteb/trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
        metrics:
          - type: map_at_1
            value: 0.23500000000000001
          - type: map_at_10
            value: 2.01
          - type: map_at_100
            value: 12.064
          - type: map_at_1000
            value: 27.437
          - type: map_at_3
            value: 0.6649999999999999
          - type: map_at_5
            value: 1.0959999999999999
          - type: mrr_at_1
            value: 88
          - type: mrr_at_10
            value: 92.667
          - type: mrr_at_100
            value: 92.667
          - type: mrr_at_1000
            value: 92.667
          - type: mrr_at_3
            value: 91.667
          - type: mrr_at_5
            value: 92.667
          - type: ndcg_at_1
            value: 84
          - type: ndcg_at_10
            value: 79.431
          - type: ndcg_at_100
            value: 60.914
          - type: ndcg_at_1000
            value: 52.005
          - type: ndcg_at_3
            value: 82.285
          - type: ndcg_at_5
            value: 81.565
          - type: precision_at_1
            value: 88
          - type: precision_at_10
            value: 84.8
          - type: precision_at_100
            value: 62.32
          - type: precision_at_1000
            value: 23.014000000000003
          - type: precision_at_3
            value: 86.667
          - type: precision_at_5
            value: 87.2
          - type: recall_at_1
            value: 0.23500000000000001
          - type: recall_at_10
            value: 2.19
          - type: recall_at_100
            value: 14.904
          - type: recall_at_1000
            value: 47.875
          - type: recall_at_3
            value: 0.695
          - type: recall_at_5
            value: 1.165
      - task:
          type: Retrieval
        dataset:
          type: mteb/touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
        metrics:
          - type: map_at_1
            value: 3.639
          - type: map_at_10
            value: 14.184
          - type: map_at_100
            value: 20.61
          - type: map_at_1000
            value: 22.377
          - type: map_at_3
            value: 9.163
          - type: map_at_5
            value: 10.773000000000001
          - type: mrr_at_1
            value: 46.939
          - type: mrr_at_10
            value: 59.345000000000006
          - type: mrr_at_100
            value: 60.07599999999999
          - type: mrr_at_1000
            value: 60.07599999999999
          - type: mrr_at_3
            value: 55.782
          - type: mrr_at_5
            value: 58.231
          - type: ndcg_at_1
            value: 41.837
          - type: ndcg_at_10
            value: 32.789
          - type: ndcg_at_100
            value: 42.232
          - type: ndcg_at_1000
            value: 53.900999999999996
          - type: ndcg_at_3
            value: 41.963
          - type: ndcg_at_5
            value: 35.983
          - type: precision_at_1
            value: 46.939
          - type: precision_at_10
            value: 28.163
          - type: precision_at_100
            value: 8.102
          - type: precision_at_1000
            value: 1.59
          - type: precision_at_3
            value: 44.897999999999996
          - type: precision_at_5
            value: 34.694
          - type: recall_at_1
            value: 3.639
          - type: recall_at_10
            value: 19.308
          - type: recall_at_100
            value: 48.992000000000004
          - type: recall_at_1000
            value: 84.59400000000001
          - type: recall_at_3
            value: 9.956
          - type: recall_at_5
            value: 12.33
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
        metrics:
          - type: accuracy
            value: 64.305
          - type: ap
            value: 11.330746746072599
          - type: f1
            value: 49.290704382387865
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 56.1941143180532
          - type: f1
            value: 56.40189765095578
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 36.28189332526842
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 83.1912737676581
          - type: cos_sim_ap
            value: 64.31536990146257
          - type: cos_sim_f1
            value: 61.095167030191696
          - type: cos_sim_precision
            value: 54.074375127006704
          - type: cos_sim_recall
            value: 70.21108179419525
          - type: dot_accuracy
            value: 83.1912737676581
          - type: dot_ap
            value: 64.31539216162541
          - type: dot_f1
            value: 61.095167030191696
          - type: dot_precision
            value: 54.074375127006704
          - type: dot_recall
            value: 70.21108179419525
          - type: euclidean_accuracy
            value: 83.1912737676581
          - type: euclidean_ap
            value: 64.31538391358727
          - type: euclidean_f1
            value: 61.095167030191696
          - type: euclidean_precision
            value: 54.074375127006704
          - type: euclidean_recall
            value: 70.21108179419525
          - type: manhattan_accuracy
            value: 83.07206294331525
          - type: manhattan_ap
            value: 64.14646315556838
          - type: manhattan_f1
            value: 61.194029850746254
          - type: manhattan_precision
            value: 54.166666666666664
          - type: manhattan_recall
            value: 70.31662269129288
          - type: max_accuracy
            value: 83.1912737676581
          - type: max_ap
            value: 64.31539216162541
          - type: max_f1
            value: 61.194029850746254
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.38242713548337
          - type: cos_sim_ap
            value: 84.70041255196017
          - type: cos_sim_f1
            value: 77.13222561986515
          - type: cos_sim_precision
            value: 73.95266690215472
          - type: cos_sim_recall
            value: 80.59747459193102
          - type: dot_accuracy
            value: 88.38242713548337
          - type: dot_ap
            value: 84.7004118720222
          - type: dot_f1
            value: 77.13222561986515
          - type: dot_precision
            value: 73.95266690215472
          - type: dot_recall
            value: 80.59747459193102
          - type: euclidean_accuracy
            value: 88.38242713548337
          - type: euclidean_ap
            value: 84.70041593996575
          - type: euclidean_f1
            value: 77.13222561986515
          - type: euclidean_precision
            value: 73.95266690215472
          - type: euclidean_recall
            value: 80.59747459193102
          - type: manhattan_accuracy
            value: 88.36108200411378
          - type: manhattan_ap
            value: 84.66897701572054
          - type: manhattan_f1
            value: 77.00707640360645
          - type: manhattan_precision
            value: 72.17695778062082
          - type: manhattan_recall
            value: 82.53002771789343
          - type: max_accuracy
            value: 88.38242713548337
          - type: max_ap
            value: 84.70041593996575
          - type: max_f1
            value: 77.13222561986515
      - task:
          type: Clustering
        dataset:
          type: jinaai/cities_wiki_clustering
          name: MTEB WikiCitiesClustering
          config: default
          split: test
          revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
        metrics:
          - type: v_measure
            value: 81.46426354153643