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metadata
license: apache-2.0
tags:
  - mteb
  - arctic
  - arctic-embed
model-index:
  - name: snowflake-arctic-embed-l
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 74.80597014925374
          - type: ap
            value: 37.911466766189875
          - type: f1
            value: 68.88606927542106
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 78.402275
          - type: ap
            value: 73.03294793248114
          - type: f1
            value: 78.3147786132161
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 36.717999999999996
          - type: f1
            value: 35.918044248787766
      - task:
          type: Retrieval
        dataset:
          type: mteb/arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
        metrics:
          - type: map_at_1
            value: 34.495
          - type: map_at_10
            value: 50.236000000000004
          - type: map_at_100
            value: 50.944
          - type: map_at_1000
            value: 50.94499999999999
          - type: map_at_3
            value: 45.341
          - type: map_at_5
            value: 48.286
          - type: mrr_at_1
            value: 35.135
          - type: mrr_at_10
            value: 50.471
          - type: mrr_at_100
            value: 51.185
          - type: mrr_at_1000
            value: 51.187000000000005
          - type: mrr_at_3
            value: 45.602
          - type: mrr_at_5
            value: 48.468
          - type: ndcg_at_1
            value: 34.495
          - type: ndcg_at_10
            value: 59.086000000000006
          - type: ndcg_at_100
            value: 61.937
          - type: ndcg_at_1000
            value: 61.966
          - type: ndcg_at_3
            value: 49.062
          - type: ndcg_at_5
            value: 54.367
          - type: precision_at_1
            value: 34.495
          - type: precision_at_10
            value: 8.734
          - type: precision_at_100
            value: 0.9939999999999999
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 19.962
          - type: precision_at_5
            value: 14.552000000000001
          - type: recall_at_1
            value: 34.495
          - type: recall_at_10
            value: 87.33999999999999
          - type: recall_at_100
            value: 99.431
          - type: recall_at_1000
            value: 99.644
          - type: recall_at_3
            value: 59.885999999999996
          - type: recall_at_5
            value: 72.76
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 47.46440874635501
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 38.28720154213723
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 60.34614226394902
          - type: mrr
            value: 75.05628105351096
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 87.41072716728198
          - type: cos_sim_spearman
            value: 86.34534093114372
          - type: euclidean_pearson
            value: 85.34009667750838
          - type: euclidean_spearman
            value: 86.34534093114372
          - type: manhattan_pearson
            value: 85.2158833586889
          - type: manhattan_spearman
            value: 86.60920236509224
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 80.06493506493507
          - type: f1
            value: 79.28108600339833
      - task:
          type: Clustering
        dataset:
          type: jinaai/big-patent-clustering
          name: MTEB BigPatentClustering
          config: default
          split: test
          revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
        metrics:
          - type: v_measure
            value: 20.545049432417287
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 37.54369718479804
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 32.64941588219162
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-android
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: f46a197baaae43b4f621051089b82a364682dfeb
        metrics:
          - type: map_at_1
            value: 37.264
          - type: map_at_10
            value: 49.43
          - type: map_at_100
            value: 50.967
          - type: map_at_1000
            value: 51.08200000000001
          - type: map_at_3
            value: 45.742
          - type: map_at_5
            value: 47.764
          - type: mrr_at_1
            value: 44.921
          - type: mrr_at_10
            value: 54.879999999999995
          - type: mrr_at_100
            value: 55.525000000000006
          - type: mrr_at_1000
            value: 55.565
          - type: mrr_at_3
            value: 52.480000000000004
          - type: mrr_at_5
            value: 53.86
          - type: ndcg_at_1
            value: 44.921
          - type: ndcg_at_10
            value: 55.664
          - type: ndcg_at_100
            value: 60.488
          - type: ndcg_at_1000
            value: 62.138000000000005
          - type: ndcg_at_3
            value: 50.797000000000004
          - type: ndcg_at_5
            value: 52.94799999999999
          - type: precision_at_1
            value: 44.921
          - type: precision_at_10
            value: 10.587
          - type: precision_at_100
            value: 1.629
          - type: precision_at_1000
            value: 0.203
          - type: precision_at_3
            value: 24.034
          - type: precision_at_5
            value: 17.224999999999998
          - type: recall_at_1
            value: 37.264
          - type: recall_at_10
            value: 67.15
          - type: recall_at_100
            value: 86.811
          - type: recall_at_1000
            value: 97.172
          - type: recall_at_3
            value: 53.15800000000001
          - type: recall_at_5
            value: 59.116
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-english
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
        metrics:
          - type: map_at_1
            value: 36.237
          - type: map_at_10
            value: 47.941
          - type: map_at_100
            value: 49.131
          - type: map_at_1000
            value: 49.26
          - type: map_at_3
            value: 44.561
          - type: map_at_5
            value: 46.28
          - type: mrr_at_1
            value: 45.605000000000004
          - type: mrr_at_10
            value: 54.039
          - type: mrr_at_100
            value: 54.653
          - type: mrr_at_1000
            value: 54.688
          - type: mrr_at_3
            value: 52.006
          - type: mrr_at_5
            value: 53.096
          - type: ndcg_at_1
            value: 45.605000000000004
          - type: ndcg_at_10
            value: 53.916
          - type: ndcg_at_100
            value: 57.745999999999995
          - type: ndcg_at_1000
            value: 59.492999999999995
          - type: ndcg_at_3
            value: 49.774
          - type: ndcg_at_5
            value: 51.434999999999995
          - type: precision_at_1
            value: 45.605000000000004
          - type: precision_at_10
            value: 10.229000000000001
          - type: precision_at_100
            value: 1.55
          - type: precision_at_1000
            value: 0.2
          - type: precision_at_3
            value: 24.098
          - type: precision_at_5
            value: 16.726
          - type: recall_at_1
            value: 36.237
          - type: recall_at_10
            value: 64.03
          - type: recall_at_100
            value: 80.423
          - type: recall_at_1000
            value: 91.03
          - type: recall_at_3
            value: 51.20400000000001
          - type: recall_at_5
            value: 56.298
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-gaming
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: 4885aa143210c98657558c04aaf3dc47cfb54340
        metrics:
          - type: map_at_1
            value: 47.278
          - type: map_at_10
            value: 59.757000000000005
          - type: map_at_100
            value: 60.67
          - type: map_at_1000
            value: 60.714
          - type: map_at_3
            value: 56.714
          - type: map_at_5
            value: 58.453
          - type: mrr_at_1
            value: 53.73
          - type: mrr_at_10
            value: 62.970000000000006
          - type: mrr_at_100
            value: 63.507999999999996
          - type: mrr_at_1000
            value: 63.53
          - type: mrr_at_3
            value: 60.909
          - type: mrr_at_5
            value: 62.172000000000004
          - type: ndcg_at_1
            value: 53.73
          - type: ndcg_at_10
            value: 64.97
          - type: ndcg_at_100
            value: 68.394
          - type: ndcg_at_1000
            value: 69.255
          - type: ndcg_at_3
            value: 60.228
          - type: ndcg_at_5
            value: 62.617999999999995
          - type: precision_at_1
            value: 53.73
          - type: precision_at_10
            value: 10.056
          - type: precision_at_100
            value: 1.265
          - type: precision_at_1000
            value: 0.13699999999999998
          - type: precision_at_3
            value: 26.332
          - type: precision_at_5
            value: 17.743000000000002
          - type: recall_at_1
            value: 47.278
          - type: recall_at_10
            value: 76.86500000000001
          - type: recall_at_100
            value: 91.582
          - type: recall_at_1000
            value: 97.583
          - type: recall_at_3
            value: 64.443
          - type: recall_at_5
            value: 70.283
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-gis
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: 5003b3064772da1887988e05400cf3806fe491f2
        metrics:
          - type: map_at_1
            value: 29.702
          - type: map_at_10
            value: 39.463
          - type: map_at_100
            value: 40.508
          - type: map_at_1000
            value: 40.579
          - type: map_at_3
            value: 36.748999999999995
          - type: map_at_5
            value: 38.296
          - type: mrr_at_1
            value: 31.977
          - type: mrr_at_10
            value: 41.739
          - type: mrr_at_100
            value: 42.586
          - type: mrr_at_1000
            value: 42.636
          - type: mrr_at_3
            value: 39.096
          - type: mrr_at_5
            value: 40.695
          - type: ndcg_at_1
            value: 31.977
          - type: ndcg_at_10
            value: 44.855000000000004
          - type: ndcg_at_100
            value: 49.712
          - type: ndcg_at_1000
            value: 51.443000000000005
          - type: ndcg_at_3
            value: 39.585
          - type: ndcg_at_5
            value: 42.244
          - type: precision_at_1
            value: 31.977
          - type: precision_at_10
            value: 6.768000000000001
          - type: precision_at_100
            value: 0.9690000000000001
          - type: precision_at_1000
            value: 0.116
          - type: precision_at_3
            value: 16.761
          - type: precision_at_5
            value: 11.593
          - type: recall_at_1
            value: 29.702
          - type: recall_at_10
            value: 59.082
          - type: recall_at_100
            value: 80.92
          - type: recall_at_1000
            value: 93.728
          - type: recall_at_3
            value: 45.212
          - type: recall_at_5
            value: 51.449
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-mathematica
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: 90fceea13679c63fe563ded68f3b6f06e50061de
        metrics:
          - type: map_at_1
            value: 21.336
          - type: map_at_10
            value: 30.137999999999998
          - type: map_at_100
            value: 31.385
          - type: map_at_1000
            value: 31.495
          - type: map_at_3
            value: 27.481
          - type: map_at_5
            value: 28.772
          - type: mrr_at_1
            value: 25.871
          - type: mrr_at_10
            value: 34.686
          - type: mrr_at_100
            value: 35.649
          - type: mrr_at_1000
            value: 35.705
          - type: mrr_at_3
            value: 32.09
          - type: mrr_at_5
            value: 33.52
          - type: ndcg_at_1
            value: 25.871
          - type: ndcg_at_10
            value: 35.617
          - type: ndcg_at_100
            value: 41.272999999999996
          - type: ndcg_at_1000
            value: 43.725
          - type: ndcg_at_3
            value: 30.653999999999996
          - type: ndcg_at_5
            value: 32.714
          - type: precision_at_1
            value: 25.871
          - type: precision_at_10
            value: 6.4799999999999995
          - type: precision_at_100
            value: 1.0699999999999998
          - type: precision_at_1000
            value: 0.13999999999999999
          - type: precision_at_3
            value: 14.469000000000001
          - type: precision_at_5
            value: 10.274
          - type: recall_at_1
            value: 21.336
          - type: recall_at_10
            value: 47.746
          - type: recall_at_100
            value: 71.773
          - type: recall_at_1000
            value: 89.05199999999999
          - type: recall_at_3
            value: 34.172999999999995
          - type: recall_at_5
            value: 39.397999999999996
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-physics
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
        metrics:
          - type: map_at_1
            value: 34.424
          - type: map_at_10
            value: 45.647999999999996
          - type: map_at_100
            value: 46.907
          - type: map_at_1000
            value: 47.010999999999996
          - type: map_at_3
            value: 42.427
          - type: map_at_5
            value: 44.285000000000004
          - type: mrr_at_1
            value: 41.867
          - type: mrr_at_10
            value: 51.17699999999999
          - type: mrr_at_100
            value: 51.937
          - type: mrr_at_1000
            value: 51.975
          - type: mrr_at_3
            value: 48.941
          - type: mrr_at_5
            value: 50.322
          - type: ndcg_at_1
            value: 41.867
          - type: ndcg_at_10
            value: 51.534
          - type: ndcg_at_100
            value: 56.696999999999996
          - type: ndcg_at_1000
            value: 58.475
          - type: ndcg_at_3
            value: 46.835
          - type: ndcg_at_5
            value: 49.161
          - type: precision_at_1
            value: 41.867
          - type: precision_at_10
            value: 9.134
          - type: precision_at_100
            value: 1.362
          - type: precision_at_1000
            value: 0.17099999999999999
          - type: precision_at_3
            value: 22.073
          - type: precision_at_5
            value: 15.495999999999999
          - type: recall_at_1
            value: 34.424
          - type: recall_at_10
            value: 63.237
          - type: recall_at_100
            value: 84.774
          - type: recall_at_1000
            value: 95.987
          - type: recall_at_3
            value: 49.888
          - type: recall_at_5
            value: 55.940999999999995
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-programmers
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
        metrics:
          - type: map_at_1
            value: 30.72
          - type: map_at_10
            value: 41.327999999999996
          - type: map_at_100
            value: 42.651
          - type: map_at_1000
            value: 42.739
          - type: map_at_3
            value: 38.223
          - type: map_at_5
            value: 40.053
          - type: mrr_at_1
            value: 37.9
          - type: mrr_at_10
            value: 46.857
          - type: mrr_at_100
            value: 47.673
          - type: mrr_at_1000
            value: 47.711999999999996
          - type: mrr_at_3
            value: 44.292
          - type: mrr_at_5
            value: 45.845
          - type: ndcg_at_1
            value: 37.9
          - type: ndcg_at_10
            value: 47.105999999999995
          - type: ndcg_at_100
            value: 52.56999999999999
          - type: ndcg_at_1000
            value: 54.37800000000001
          - type: ndcg_at_3
            value: 42.282
          - type: ndcg_at_5
            value: 44.646
          - type: precision_at_1
            value: 37.9
          - type: precision_at_10
            value: 8.368
          - type: precision_at_100
            value: 1.283
          - type: precision_at_1000
            value: 0.16
          - type: precision_at_3
            value: 20.015
          - type: precision_at_5
            value: 14.132
          - type: recall_at_1
            value: 30.72
          - type: recall_at_10
            value: 58.826
          - type: recall_at_100
            value: 82.104
          - type: recall_at_1000
            value: 94.194
          - type: recall_at_3
            value: 44.962999999999994
          - type: recall_at_5
            value: 51.426
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
        metrics:
          - type: map_at_1
            value: 31.656583333333334
          - type: map_at_10
            value: 41.59883333333333
          - type: map_at_100
            value: 42.80350000000001
          - type: map_at_1000
            value: 42.91075
          - type: map_at_3
            value: 38.68908333333333
          - type: map_at_5
            value: 40.27733333333334
          - type: mrr_at_1
            value: 37.23483333333334
          - type: mrr_at_10
            value: 45.782000000000004
          - type: mrr_at_100
            value: 46.577083333333334
          - type: mrr_at_1000
            value: 46.62516666666667
          - type: mrr_at_3
            value: 43.480666666666664
          - type: mrr_at_5
            value: 44.79833333333333
          - type: ndcg_at_1
            value: 37.23483333333334
          - type: ndcg_at_10
            value: 46.971500000000006
          - type: ndcg_at_100
            value: 51.90125
          - type: ndcg_at_1000
            value: 53.86366666666667
          - type: ndcg_at_3
            value: 42.31791666666667
          - type: ndcg_at_5
            value: 44.458666666666666
          - type: precision_at_1
            value: 37.23483333333334
          - type: precision_at_10
            value: 8.044583333333332
          - type: precision_at_100
            value: 1.2334166666666666
          - type: precision_at_1000
            value: 0.15925
          - type: precision_at_3
            value: 19.240833333333327
          - type: precision_at_5
            value: 13.435083333333333
          - type: recall_at_1
            value: 31.656583333333334
          - type: recall_at_10
            value: 58.44758333333333
          - type: recall_at_100
            value: 79.93658333333332
          - type: recall_at_1000
            value: 93.32491666666668
          - type: recall_at_3
            value: 45.44266666666667
          - type: recall_at_5
            value: 50.99866666666666
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-stats
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
        metrics:
          - type: map_at_1
            value: 28.247
          - type: map_at_10
            value: 35.443999999999996
          - type: map_at_100
            value: 36.578
          - type: map_at_1000
            value: 36.675999999999995
          - type: map_at_3
            value: 33.276
          - type: map_at_5
            value: 34.536
          - type: mrr_at_1
            value: 31.747999999999998
          - type: mrr_at_10
            value: 38.413000000000004
          - type: mrr_at_100
            value: 39.327
          - type: mrr_at_1000
            value: 39.389
          - type: mrr_at_3
            value: 36.401
          - type: mrr_at_5
            value: 37.543
          - type: ndcg_at_1
            value: 31.747999999999998
          - type: ndcg_at_10
            value: 39.646
          - type: ndcg_at_100
            value: 44.861000000000004
          - type: ndcg_at_1000
            value: 47.197
          - type: ndcg_at_3
            value: 35.764
          - type: ndcg_at_5
            value: 37.635999999999996
          - type: precision_at_1
            value: 31.747999999999998
          - type: precision_at_10
            value: 6.12
          - type: precision_at_100
            value: 0.942
          - type: precision_at_1000
            value: 0.123
          - type: precision_at_3
            value: 15.235000000000001
          - type: precision_at_5
            value: 10.491
          - type: recall_at_1
            value: 28.247
          - type: recall_at_10
            value: 49.456
          - type: recall_at_100
            value: 73.02499999999999
          - type: recall_at_1000
            value: 89.898
          - type: recall_at_3
            value: 38.653999999999996
          - type: recall_at_5
            value: 43.259
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-tex
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: 46989137a86843e03a6195de44b09deda022eec7
        metrics:
          - type: map_at_1
            value: 22.45
          - type: map_at_10
            value: 30.476999999999997
          - type: map_at_100
            value: 31.630999999999997
          - type: map_at_1000
            value: 31.755
          - type: map_at_3
            value: 27.989000000000004
          - type: map_at_5
            value: 29.410999999999998
          - type: mrr_at_1
            value: 26.979
          - type: mrr_at_10
            value: 34.316
          - type: mrr_at_100
            value: 35.272999999999996
          - type: mrr_at_1000
            value: 35.342
          - type: mrr_at_3
            value: 32.14
          - type: mrr_at_5
            value: 33.405
          - type: ndcg_at_1
            value: 26.979
          - type: ndcg_at_10
            value: 35.166
          - type: ndcg_at_100
            value: 40.583000000000006
          - type: ndcg_at_1000
            value: 43.282
          - type: ndcg_at_3
            value: 30.916
          - type: ndcg_at_5
            value: 32.973
          - type: precision_at_1
            value: 26.979
          - type: precision_at_10
            value: 6.132
          - type: precision_at_100
            value: 1.047
          - type: precision_at_1000
            value: 0.145
          - type: precision_at_3
            value: 14.360999999999999
          - type: precision_at_5
            value: 10.227
          - type: recall_at_1
            value: 22.45
          - type: recall_at_10
            value: 45.348
          - type: recall_at_100
            value: 69.484
          - type: recall_at_1000
            value: 88.628
          - type: recall_at_3
            value: 33.338
          - type: recall_at_5
            value: 38.746
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-unix
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
        metrics:
          - type: map_at_1
            value: 32.123000000000005
          - type: map_at_10
            value: 41.778
          - type: map_at_100
            value: 42.911
          - type: map_at_1000
            value: 42.994
          - type: map_at_3
            value: 38.558
          - type: map_at_5
            value: 40.318
          - type: mrr_at_1
            value: 37.687
          - type: mrr_at_10
            value: 45.889
          - type: mrr_at_100
            value: 46.672999999999995
          - type: mrr_at_1000
            value: 46.72
          - type: mrr_at_3
            value: 43.33
          - type: mrr_at_5
            value: 44.734
          - type: ndcg_at_1
            value: 37.687
          - type: ndcg_at_10
            value: 47.258
          - type: ndcg_at_100
            value: 52.331
          - type: ndcg_at_1000
            value: 54.152
          - type: ndcg_at_3
            value: 41.857
          - type: ndcg_at_5
            value: 44.283
          - type: precision_at_1
            value: 37.687
          - type: precision_at_10
            value: 7.892
          - type: precision_at_100
            value: 1.183
          - type: precision_at_1000
            value: 0.14300000000000002
          - type: precision_at_3
            value: 18.781
          - type: precision_at_5
            value: 13.134
          - type: recall_at_1
            value: 32.123000000000005
          - type: recall_at_10
            value: 59.760000000000005
          - type: recall_at_100
            value: 81.652
          - type: recall_at_1000
            value: 94.401
          - type: recall_at_3
            value: 44.996
          - type: recall_at_5
            value: 51.184
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-webmasters
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: 160c094312a0e1facb97e55eeddb698c0abe3571
        metrics:
          - type: map_at_1
            value: 33.196999999999996
          - type: map_at_10
            value: 42.012
          - type: map_at_100
            value: 43.663999999999994
          - type: map_at_1000
            value: 43.883
          - type: map_at_3
            value: 39.33
          - type: map_at_5
            value: 40.586
          - type: mrr_at_1
            value: 39.328
          - type: mrr_at_10
            value: 46.57
          - type: mrr_at_100
            value: 47.508
          - type: mrr_at_1000
            value: 47.558
          - type: mrr_at_3
            value: 44.532
          - type: mrr_at_5
            value: 45.58
          - type: ndcg_at_1
            value: 39.328
          - type: ndcg_at_10
            value: 47.337
          - type: ndcg_at_100
            value: 52.989
          - type: ndcg_at_1000
            value: 55.224
          - type: ndcg_at_3
            value: 43.362
          - type: ndcg_at_5
            value: 44.866
          - type: precision_at_1
            value: 39.328
          - type: precision_at_10
            value: 8.577
          - type: precision_at_100
            value: 1.5789999999999997
          - type: precision_at_1000
            value: 0.25
          - type: precision_at_3
            value: 19.697
          - type: precision_at_5
            value: 13.755
          - type: recall_at_1
            value: 33.196999999999996
          - type: recall_at_10
            value: 56.635000000000005
          - type: recall_at_100
            value: 81.882
          - type: recall_at_1000
            value: 95.342
          - type: recall_at_3
            value: 44.969
          - type: recall_at_5
            value: 49.266
      - task:
          type: Retrieval
        dataset:
          type: mteb/cqadupstack-wordpress
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
        metrics:
          - type: map_at_1
            value: 26.901000000000003
          - type: map_at_10
            value: 35.77
          - type: map_at_100
            value: 36.638999999999996
          - type: map_at_1000
            value: 36.741
          - type: map_at_3
            value: 33.219
          - type: map_at_5
            value: 34.574
          - type: mrr_at_1
            value: 29.205
          - type: mrr_at_10
            value: 37.848
          - type: mrr_at_100
            value: 38.613
          - type: mrr_at_1000
            value: 38.682
          - type: mrr_at_3
            value: 35.551
          - type: mrr_at_5
            value: 36.808
          - type: ndcg_at_1
            value: 29.205
          - type: ndcg_at_10
            value: 40.589
          - type: ndcg_at_100
            value: 45.171
          - type: ndcg_at_1000
            value: 47.602
          - type: ndcg_at_3
            value: 35.760999999999996
          - type: ndcg_at_5
            value: 37.980000000000004
          - type: precision_at_1
            value: 29.205
          - type: precision_at_10
            value: 6.192
          - type: precision_at_100
            value: 0.922
          - type: precision_at_1000
            value: 0.123
          - type: precision_at_3
            value: 15.034
          - type: precision_at_5
            value: 10.424999999999999
          - type: recall_at_1
            value: 26.901000000000003
          - type: recall_at_10
            value: 53.236000000000004
          - type: recall_at_100
            value: 74.809
          - type: recall_at_1000
            value: 92.884
          - type: recall_at_3
            value: 40.314
          - type: recall_at_5
            value: 45.617999999999995
      - task:
          type: Retrieval
        dataset:
          type: mteb/climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
        metrics:
          - type: map_at_1
            value: 16.794999999999998
          - type: map_at_10
            value: 29.322
          - type: map_at_100
            value: 31.463
          - type: map_at_1000
            value: 31.643
          - type: map_at_3
            value: 24.517
          - type: map_at_5
            value: 27.237000000000002
          - type: mrr_at_1
            value: 37.655
          - type: mrr_at_10
            value: 50.952
          - type: mrr_at_100
            value: 51.581999999999994
          - type: mrr_at_1000
            value: 51.61
          - type: mrr_at_3
            value: 47.991
          - type: mrr_at_5
            value: 49.744
          - type: ndcg_at_1
            value: 37.655
          - type: ndcg_at_10
            value: 39.328
          - type: ndcg_at_100
            value: 46.358
          - type: ndcg_at_1000
            value: 49.245
          - type: ndcg_at_3
            value: 33.052
          - type: ndcg_at_5
            value: 35.407
          - type: precision_at_1
            value: 37.655
          - type: precision_at_10
            value: 12.202
          - type: precision_at_100
            value: 1.9789999999999999
          - type: precision_at_1000
            value: 0.252
          - type: precision_at_3
            value: 24.973
          - type: precision_at_5
            value: 19.075
          - type: recall_at_1
            value: 16.794999999999998
          - type: recall_at_10
            value: 45.716
          - type: recall_at_100
            value: 68.919
          - type: recall_at_1000
            value: 84.71600000000001
          - type: recall_at_3
            value: 30.135
          - type: recall_at_5
            value: 37.141999999999996
      - task:
          type: Retrieval
        dataset:
          type: mteb/dbpedia
          name: MTEB DBPedia
          config: default
          split: test
          revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
        metrics:
          - type: map_at_1
            value: 9.817
          - type: map_at_10
            value: 22.058
          - type: map_at_100
            value: 31.805
          - type: map_at_1000
            value: 33.562999999999995
          - type: map_at_3
            value: 15.537
          - type: map_at_5
            value: 18.199
          - type: mrr_at_1
            value: 72.75
          - type: mrr_at_10
            value: 79.804
          - type: mrr_at_100
            value: 80.089
          - type: mrr_at_1000
            value: 80.09100000000001
          - type: mrr_at_3
            value: 78.75
          - type: mrr_at_5
            value: 79.325
          - type: ndcg_at_1
            value: 59.875
          - type: ndcg_at_10
            value: 45.972
          - type: ndcg_at_100
            value: 51.092999999999996
          - type: ndcg_at_1000
            value: 58.048
          - type: ndcg_at_3
            value: 50.552
          - type: ndcg_at_5
            value: 47.672
          - type: precision_at_1
            value: 72.75
          - type: precision_at_10
            value: 37.05
          - type: precision_at_100
            value: 12.005
          - type: precision_at_1000
            value: 2.221
          - type: precision_at_3
            value: 54.083000000000006
          - type: precision_at_5
            value: 46.2
          - type: recall_at_1
            value: 9.817
          - type: recall_at_10
            value: 27.877000000000002
          - type: recall_at_100
            value: 57.974000000000004
          - type: recall_at_1000
            value: 80.085
          - type: recall_at_3
            value: 16.911
          - type: recall_at_5
            value: 20.689
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 46.464999999999996
          - type: f1
            value: 42.759588662873796
      - task:
          type: Retrieval
        dataset:
          type: mteb/fever
          name: MTEB FEVER
          config: default
          split: test
          revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
        metrics:
          - type: map_at_1
            value: 75.82900000000001
          - type: map_at_10
            value: 84.613
          - type: map_at_100
            value: 84.845
          - type: map_at_1000
            value: 84.855
          - type: map_at_3
            value: 83.498
          - type: map_at_5
            value: 84.29299999999999
          - type: mrr_at_1
            value: 81.69800000000001
          - type: mrr_at_10
            value: 88.84100000000001
          - type: mrr_at_100
            value: 88.887
          - type: mrr_at_1000
            value: 88.888
          - type: mrr_at_3
            value: 88.179
          - type: mrr_at_5
            value: 88.69200000000001
          - type: ndcg_at_1
            value: 81.69800000000001
          - type: ndcg_at_10
            value: 88.21799999999999
          - type: ndcg_at_100
            value: 88.961
          - type: ndcg_at_1000
            value: 89.131
          - type: ndcg_at_3
            value: 86.591
          - type: ndcg_at_5
            value: 87.666
          - type: precision_at_1
            value: 81.69800000000001
          - type: precision_at_10
            value: 10.615
          - type: precision_at_100
            value: 1.125
          - type: precision_at_1000
            value: 0.11499999999999999
          - type: precision_at_3
            value: 33.208
          - type: precision_at_5
            value: 20.681
          - type: recall_at_1
            value: 75.82900000000001
          - type: recall_at_10
            value: 94.97
          - type: recall_at_100
            value: 97.786
          - type: recall_at_1000
            value: 98.809
          - type: recall_at_3
            value: 90.625
          - type: recall_at_5
            value: 93.345
      - task:
          type: Retrieval
        dataset:
          type: mteb/fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: 27a168819829fe9bcd655c2df245fb19452e8e06
        metrics:
          - type: map_at_1
            value: 22.788
          - type: map_at_10
            value: 36.71
          - type: map_at_100
            value: 38.527
          - type: map_at_1000
            value: 38.701
          - type: map_at_3
            value: 32.318999999999996
          - type: map_at_5
            value: 34.809
          - type: mrr_at_1
            value: 44.444
          - type: mrr_at_10
            value: 52.868
          - type: mrr_at_100
            value: 53.52400000000001
          - type: mrr_at_1000
            value: 53.559999999999995
          - type: mrr_at_3
            value: 50.153999999999996
          - type: mrr_at_5
            value: 51.651
          - type: ndcg_at_1
            value: 44.444
          - type: ndcg_at_10
            value: 44.707
          - type: ndcg_at_100
            value: 51.174
          - type: ndcg_at_1000
            value: 53.996
          - type: ndcg_at_3
            value: 40.855999999999995
          - type: ndcg_at_5
            value: 42.113
          - type: precision_at_1
            value: 44.444
          - type: precision_at_10
            value: 12.021999999999998
          - type: precision_at_100
            value: 1.8950000000000002
          - type: precision_at_1000
            value: 0.241
          - type: precision_at_3
            value: 26.8
          - type: precision_at_5
            value: 19.66
          - type: recall_at_1
            value: 22.788
          - type: recall_at_10
            value: 51.793
          - type: recall_at_100
            value: 75.69500000000001
          - type: recall_at_1000
            value: 92.292
          - type: recall_at_3
            value: 37.375
          - type: recall_at_5
            value: 43.682
      - task:
          type: Retrieval
        dataset:
          type: mteb/hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: ab518f4d6fcca38d87c25209f94beba119d02014
        metrics:
          - type: map_at_1
            value: 41.276
          - type: map_at_10
            value: 67.245
          - type: map_at_100
            value: 68.061
          - type: map_at_1000
            value: 68.11399999999999
          - type: map_at_3
            value: 63.693
          - type: map_at_5
            value: 65.90899999999999
          - type: mrr_at_1
            value: 82.552
          - type: mrr_at_10
            value: 87.741
          - type: mrr_at_100
            value: 87.868
          - type: mrr_at_1000
            value: 87.871
          - type: mrr_at_3
            value: 86.98599999999999
          - type: mrr_at_5
            value: 87.469
          - type: ndcg_at_1
            value: 82.552
          - type: ndcg_at_10
            value: 75.176
          - type: ndcg_at_100
            value: 77.902
          - type: ndcg_at_1000
            value: 78.852
          - type: ndcg_at_3
            value: 70.30499999999999
          - type: ndcg_at_5
            value: 73.00999999999999
          - type: precision_at_1
            value: 82.552
          - type: precision_at_10
            value: 15.765
          - type: precision_at_100
            value: 1.788
          - type: precision_at_1000
            value: 0.191
          - type: precision_at_3
            value: 45.375
          - type: precision_at_5
            value: 29.360999999999997
          - type: recall_at_1
            value: 41.276
          - type: recall_at_10
            value: 78.825
          - type: recall_at_100
            value: 89.41900000000001
          - type: recall_at_1000
            value: 95.625
          - type: recall_at_3
            value: 68.062
          - type: recall_at_5
            value: 73.40299999999999
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 72.876
          - type: ap
            value: 67.15477852410164
          - type: f1
            value: 72.65147370025373
      - task:
          type: Retrieval
        dataset:
          type: mteb/msmarco
          name: MTEB MSMARCO
          config: default
          split: dev
          revision: c5a29a104738b98a9e76336939199e264163d4a0
        metrics:
          - type: map_at_1
            value: 21.748
          - type: map_at_10
            value: 34.626000000000005
          - type: map_at_100
            value: 35.813
          - type: map_at_1000
            value: 35.859
          - type: map_at_3
            value: 30.753000000000004
          - type: map_at_5
            value: 33.049
          - type: mrr_at_1
            value: 22.35
          - type: mrr_at_10
            value: 35.23
          - type: mrr_at_100
            value: 36.359
          - type: mrr_at_1000
            value: 36.399
          - type: mrr_at_3
            value: 31.436999999999998
          - type: mrr_at_5
            value: 33.687
          - type: ndcg_at_1
            value: 22.364
          - type: ndcg_at_10
            value: 41.677
          - type: ndcg_at_100
            value: 47.355999999999995
          - type: ndcg_at_1000
            value: 48.494
          - type: ndcg_at_3
            value: 33.85
          - type: ndcg_at_5
            value: 37.942
          - type: precision_at_1
            value: 22.364
          - type: precision_at_10
            value: 6.6000000000000005
          - type: precision_at_100
            value: 0.9450000000000001
          - type: precision_at_1000
            value: 0.104
          - type: precision_at_3
            value: 14.527000000000001
          - type: precision_at_5
            value: 10.796999999999999
          - type: recall_at_1
            value: 21.748
          - type: recall_at_10
            value: 63.292
          - type: recall_at_100
            value: 89.427
          - type: recall_at_1000
            value: 98.13499999999999
          - type: recall_at_3
            value: 42.126000000000005
          - type: recall_at_5
            value: 51.968
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 92.62425900592795
          - type: f1
            value: 92.08497761553683
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 64.51436388508893
          - type: f1
            value: 45.884016531912906
      - task:
          type: Classification
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClassification (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: accuracy
            value: 76.57172995780591
          - type: f1
            value: 75.52979910878491
      - task:
          type: Clustering
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClusteringP2P (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: v_measure
            value: 44.84052695201612
      - task:
          type: Clustering
        dataset:
          type: masakhane/masakhanews
          name: MTEB MasakhaNEWSClusteringS2S (eng)
          config: eng
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: v_measure
            value: 21.443971229936494
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 65.79354404841965
          - type: f1
            value: 63.17260074126185
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 71.09616677874916
          - type: f1
            value: 69.74285784421075
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 31.474709231086184
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 28.93630367824217
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 29.08234393834005
          - type: mrr
            value: 29.740466971605432
      - task:
          type: Retrieval
        dataset:
          type: mteb/nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
        metrics:
          - type: map_at_1
            value: 6.2059999999999995
          - type: map_at_10
            value: 14.442
          - type: map_at_100
            value: 18.005
          - type: map_at_1000
            value: 19.488
          - type: map_at_3
            value: 10.666
          - type: map_at_5
            value: 12.45
          - type: mrr_at_1
            value: 47.678
          - type: mrr_at_10
            value: 57.519
          - type: mrr_at_100
            value: 58.13700000000001
          - type: mrr_at_1000
            value: 58.167
          - type: mrr_at_3
            value: 55.779
          - type: mrr_at_5
            value: 56.940000000000005
          - type: ndcg_at_1
            value: 45.82
          - type: ndcg_at_10
            value: 37.651
          - type: ndcg_at_100
            value: 34.001999999999995
          - type: ndcg_at_1000
            value: 42.626
          - type: ndcg_at_3
            value: 43.961
          - type: ndcg_at_5
            value: 41.461
          - type: precision_at_1
            value: 47.678
          - type: precision_at_10
            value: 27.584999999999997
          - type: precision_at_100
            value: 8.455
          - type: precision_at_1000
            value: 2.118
          - type: precision_at_3
            value: 41.692
          - type: precision_at_5
            value: 36.161
          - type: recall_at_1
            value: 6.2059999999999995
          - type: recall_at_10
            value: 18.599
          - type: recall_at_100
            value: 33.608
          - type: recall_at_1000
            value: 65.429
          - type: recall_at_3
            value: 12.126000000000001
          - type: recall_at_5
            value: 14.902000000000001
      - task:
          type: Retrieval
        dataset:
          type: mteb/nq
          name: MTEB NQ
          config: default
          split: test
          revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
        metrics:
          - type: map_at_1
            value: 39.117000000000004
          - type: map_at_10
            value: 55.535000000000004
          - type: map_at_100
            value: 56.32899999999999
          - type: map_at_1000
            value: 56.34400000000001
          - type: map_at_3
            value: 51.439
          - type: map_at_5
            value: 53.89699999999999
          - type: mrr_at_1
            value: 43.714
          - type: mrr_at_10
            value: 58.05200000000001
          - type: mrr_at_100
            value: 58.582
          - type: mrr_at_1000
            value: 58.592
          - type: mrr_at_3
            value: 54.896
          - type: mrr_at_5
            value: 56.874
          - type: ndcg_at_1
            value: 43.685
          - type: ndcg_at_10
            value: 63.108
          - type: ndcg_at_100
            value: 66.231
          - type: ndcg_at_1000
            value: 66.583
          - type: ndcg_at_3
            value: 55.659000000000006
          - type: ndcg_at_5
            value: 59.681
          - type: precision_at_1
            value: 43.685
          - type: precision_at_10
            value: 9.962
          - type: precision_at_100
            value: 1.174
          - type: precision_at_1000
            value: 0.121
          - type: precision_at_3
            value: 24.961
          - type: precision_at_5
            value: 17.352
          - type: recall_at_1
            value: 39.117000000000004
          - type: recall_at_10
            value: 83.408
          - type: recall_at_100
            value: 96.553
          - type: recall_at_1000
            value: 99.136
          - type: recall_at_3
            value: 64.364
          - type: recall_at_5
            value: 73.573
      - task:
          type: Classification
        dataset:
          type: ag_news
          name: MTEB NewsClassification
          config: default
          split: test
          revision: eb185aade064a813bc0b7f42de02595523103ca4
        metrics:
          - type: accuracy
            value: 78.87763157894737
          - type: f1
            value: 78.69611753876177
      - 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: 62
          - type: cos_sim_ap
            value: 62.26837791655737
          - type: cos_sim_f1
            value: 62.607449856733524
          - type: cos_sim_precision
            value: 46.36604774535809
          - type: cos_sim_recall
            value: 96.36163175303197
          - type: dot_accuracy
            value: 62
          - type: dot_ap
            value: 62.26736459439965
          - type: dot_f1
            value: 62.607449856733524
          - type: dot_precision
            value: 46.36604774535809
          - type: dot_recall
            value: 96.36163175303197
          - type: euclidean_accuracy
            value: 62
          - type: euclidean_ap
            value: 62.26826112548132
          - type: euclidean_f1
            value: 62.607449856733524
          - type: euclidean_precision
            value: 46.36604774535809
          - type: euclidean_recall
            value: 96.36163175303197
          - type: manhattan_accuracy
            value: 62
          - type: manhattan_ap
            value: 62.26223761507973
          - type: manhattan_f1
            value: 62.585034013605444
          - type: manhattan_precision
            value: 46.34146341463415
          - type: manhattan_recall
            value: 96.36163175303197
          - type: max_accuracy
            value: 62
          - type: max_ap
            value: 62.26837791655737
          - type: max_f1
            value: 62.607449856733524
      - task:
          type: Retrieval
        dataset:
          type: mteb/quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
        metrics:
          - type: map_at_1
            value: 69.90899999999999
          - type: map_at_10
            value: 83.56700000000001
          - type: map_at_100
            value: 84.19200000000001
          - type: map_at_1000
            value: 84.212
          - type: map_at_3
            value: 80.658
          - type: map_at_5
            value: 82.473
          - type: mrr_at_1
            value: 80.4
          - type: mrr_at_10
            value: 86.699
          - type: mrr_at_100
            value: 86.798
          - type: mrr_at_1000
            value: 86.80099999999999
          - type: mrr_at_3
            value: 85.677
          - type: mrr_at_5
            value: 86.354
          - type: ndcg_at_1
            value: 80.43
          - type: ndcg_at_10
            value: 87.41
          - type: ndcg_at_100
            value: 88.653
          - type: ndcg_at_1000
            value: 88.81599999999999
          - type: ndcg_at_3
            value: 84.516
          - type: ndcg_at_5
            value: 86.068
          - type: precision_at_1
            value: 80.43
          - type: precision_at_10
            value: 13.234000000000002
          - type: precision_at_100
            value: 1.513
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 36.93
          - type: precision_at_5
            value: 24.26
          - type: recall_at_1
            value: 69.90899999999999
          - type: recall_at_10
            value: 94.687
          - type: recall_at_100
            value: 98.96000000000001
          - type: recall_at_1000
            value: 99.79599999999999
          - type: recall_at_3
            value: 86.25699999999999
          - type: recall_at_5
            value: 90.70700000000001
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 46.02256865360266
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
        metrics:
          - type: v_measure
            value: 62.43157528757563
      - task:
          type: Retrieval
        dataset:
          type: mteb/scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
        metrics:
          - type: map_at_1
            value: 5.093
          - type: map_at_10
            value: 12.982
          - type: map_at_100
            value: 15.031
          - type: map_at_1000
            value: 15.334
          - type: map_at_3
            value: 9.339
          - type: map_at_5
            value: 11.183
          - type: mrr_at_1
            value: 25.1
          - type: mrr_at_10
            value: 36.257
          - type: mrr_at_100
            value: 37.351
          - type: mrr_at_1000
            value: 37.409
          - type: mrr_at_3
            value: 33.050000000000004
          - type: mrr_at_5
            value: 35.205
          - type: ndcg_at_1
            value: 25.1
          - type: ndcg_at_10
            value: 21.361
          - type: ndcg_at_100
            value: 29.396
          - type: ndcg_at_1000
            value: 34.849999999999994
          - type: ndcg_at_3
            value: 20.704
          - type: ndcg_at_5
            value: 18.086
          - type: precision_at_1
            value: 25.1
          - type: precision_at_10
            value: 10.94
          - type: precision_at_100
            value: 2.257
          - type: precision_at_1000
            value: 0.358
          - type: precision_at_3
            value: 19.467000000000002
          - type: precision_at_5
            value: 15.98
          - type: recall_at_1
            value: 5.093
          - type: recall_at_10
            value: 22.177
          - type: recall_at_100
            value: 45.842
          - type: recall_at_1000
            value: 72.598
          - type: recall_at_3
            value: 11.833
          - type: recall_at_5
            value: 16.173000000000002
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
        metrics:
          - type: cos_sim_pearson
            value: 73.56535226754596
          - type: cos_sim_spearman
            value: 69.32425977603488
          - type: euclidean_pearson
            value: 71.32425703470898
          - type: euclidean_spearman
            value: 69.32425217267013
          - type: manhattan_pearson
            value: 71.25897281394246
          - type: manhattan_spearman
            value: 69.27132577049578
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 69.66387868726018
          - type: cos_sim_spearman
            value: 67.85470749045027
          - type: euclidean_pearson
            value: 66.62075098063795
          - type: euclidean_spearman
            value: 67.85470749045027
          - type: manhattan_pearson
            value: 66.61455061901262
          - type: manhattan_spearman
            value: 67.87229618498695
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 75.65731331392575
          - type: cos_sim_spearman
            value: 77.48991626780108
          - type: euclidean_pearson
            value: 77.19884738623692
          - type: euclidean_spearman
            value: 77.48985836619045
          - type: manhattan_pearson
            value: 77.0656684243772
          - type: manhattan_spearman
            value: 77.30289226582691
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 69.37003253666457
          - type: cos_sim_spearman
            value: 69.77157648098141
          - type: euclidean_pearson
            value: 69.39543876030432
          - type: euclidean_spearman
            value: 69.77157648098141
          - type: manhattan_pearson
            value: 69.29901600459745
          - type: manhattan_spearman
            value: 69.65074167527128
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 78.56777256540136
          - type: cos_sim_spearman
            value: 80.16458787843023
          - type: euclidean_pearson
            value: 80.16475730686916
          - type: euclidean_spearman
            value: 80.16458787843023
          - type: manhattan_pearson
            value: 80.12814463670401
          - type: manhattan_spearman
            value: 80.1357907984809
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 76.09572350919031
          - type: cos_sim_spearman
            value: 77.94490233429326
          - type: euclidean_pearson
            value: 78.36595251203524
          - type: euclidean_spearman
            value: 77.94490233429326
          - type: manhattan_pearson
            value: 78.41538768125166
          - type: manhattan_spearman
            value: 78.01244379569542
      - 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: 80.7843552187951
          - type: cos_sim_spearman
            value: 82.28085055047386
          - type: euclidean_pearson
            value: 82.37373672515267
          - type: euclidean_spearman
            value: 82.28085055047386
          - type: manhattan_pearson
            value: 82.39387241346917
          - type: manhattan_spearman
            value: 82.36503339515906
      - 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: 68.29963929962095
          - type: cos_sim_spearman
            value: 67.96868942546051
          - type: euclidean_pearson
            value: 68.93524903869285
          - type: euclidean_spearman
            value: 67.96868942546051
          - type: manhattan_pearson
            value: 68.79144468444811
          - type: manhattan_spearman
            value: 67.69311483884324
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 72.84789696700685
          - type: cos_sim_spearman
            value: 75.67875747588545
          - type: euclidean_pearson
            value: 75.07752300463038
          - type: euclidean_spearman
            value: 75.67875747588545
          - type: manhattan_pearson
            value: 74.97934248140928
          - type: manhattan_spearman
            value: 75.62525644178724
      - 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: 72.84789702519309
          - type: cos_sim_spearman
            value: 75.67875747588545
          - type: euclidean_pearson
            value: 75.07752310061133
          - type: euclidean_spearman
            value: 75.67875747588545
          - type: manhattan_pearson
            value: 74.97934257159595
          - type: manhattan_spearman
            value: 75.62525644178724
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 81.55557720431086
          - type: mrr
            value: 94.91178665198272
      - task:
          type: Retrieval
        dataset:
          type: mteb/scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
        metrics:
          - type: map_at_1
            value: 59.260999999999996
          - type: map_at_10
            value: 69.36099999999999
          - type: map_at_100
            value: 69.868
          - type: map_at_1000
            value: 69.877
          - type: map_at_3
            value: 66.617
          - type: map_at_5
            value: 68.061
          - type: mrr_at_1
            value: 62.333000000000006
          - type: mrr_at_10
            value: 70.533
          - type: mrr_at_100
            value: 70.966
          - type: mrr_at_1000
            value: 70.975
          - type: mrr_at_3
            value: 68.667
          - type: mrr_at_5
            value: 69.717
          - type: ndcg_at_1
            value: 62.333000000000006
          - type: ndcg_at_10
            value: 73.82300000000001
          - type: ndcg_at_100
            value: 76.122
          - type: ndcg_at_1000
            value: 76.374
          - type: ndcg_at_3
            value: 69.27499999999999
          - type: ndcg_at_5
            value: 71.33
          - type: precision_at_1
            value: 62.333000000000006
          - type: precision_at_10
            value: 9.8
          - type: precision_at_100
            value: 1.097
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 26.889000000000003
          - type: precision_at_5
            value: 17.599999999999998
          - type: recall_at_1
            value: 59.260999999999996
          - type: recall_at_10
            value: 86.2
          - type: recall_at_100
            value: 96.667
          - type: recall_at_1000
            value: 98.667
          - type: recall_at_3
            value: 74.006
          - type: recall_at_5
            value: 79.167
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.81881188118813
          - type: cos_sim_ap
            value: 95.20169041096409
          - type: cos_sim_f1
            value: 90.76224129227664
          - type: cos_sim_precision
            value: 91.64118246687055
          - type: cos_sim_recall
            value: 89.9
          - type: dot_accuracy
            value: 99.81881188118813
          - type: dot_ap
            value: 95.20169041096409
          - type: dot_f1
            value: 90.76224129227664
          - type: dot_precision
            value: 91.64118246687055
          - type: dot_recall
            value: 89.9
          - type: euclidean_accuracy
            value: 99.81881188118813
          - type: euclidean_ap
            value: 95.2016904109641
          - type: euclidean_f1
            value: 90.76224129227664
          - type: euclidean_precision
            value: 91.64118246687055
          - type: euclidean_recall
            value: 89.9
          - type: manhattan_accuracy
            value: 99.81881188118813
          - type: manhattan_ap
            value: 95.22680188132777
          - type: manhattan_f1
            value: 90.79013588324108
          - type: manhattan_precision
            value: 91.38804457953394
          - type: manhattan_recall
            value: 90.2
          - type: max_accuracy
            value: 99.81881188118813
          - type: max_ap
            value: 95.22680188132777
          - type: max_f1
            value: 90.79013588324108
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 57.8638628701308
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 37.82028248106046
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 50.870860210170946
          - type: mrr
            value: 51.608084521687466
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 31.60384207444685
          - type: cos_sim_spearman
            value: 30.84047452209471
          - type: dot_pearson
            value: 31.60384104417333
          - type: dot_spearman
            value: 30.84047452209471
      - task:
          type: Retrieval
        dataset:
          type: mteb/trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
        metrics:
          - type: map_at_1
            value: 0.246
          - type: map_at_10
            value: 2.051
          - type: map_at_100
            value: 13.129
          - type: map_at_1000
            value: 31.56
          - type: map_at_3
            value: 0.681
          - type: map_at_5
            value: 1.105
          - type: mrr_at_1
            value: 94
          - type: mrr_at_10
            value: 97
          - type: mrr_at_100
            value: 97
          - type: mrr_at_1000
            value: 97
          - type: mrr_at_3
            value: 97
          - type: mrr_at_5
            value: 97
          - type: ndcg_at_1
            value: 87
          - type: ndcg_at_10
            value: 80.716
          - type: ndcg_at_100
            value: 63.83
          - type: ndcg_at_1000
            value: 56.215
          - type: ndcg_at_3
            value: 84.531
          - type: ndcg_at_5
            value: 84.777
          - type: precision_at_1
            value: 94
          - type: precision_at_10
            value: 84.6
          - type: precision_at_100
            value: 66.03999999999999
          - type: precision_at_1000
            value: 24.878
          - type: precision_at_3
            value: 88.667
          - type: precision_at_5
            value: 89.60000000000001
          - type: recall_at_1
            value: 0.246
          - type: recall_at_10
            value: 2.2079999999999997
          - type: recall_at_100
            value: 15.895999999999999
          - type: recall_at_1000
            value: 52.683
          - type: recall_at_3
            value: 0.7040000000000001
          - type: recall_at_5
            value: 1.163
      - task:
          type: Retrieval
        dataset:
          type: mteb/touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
        metrics:
          - type: map_at_1
            value: 3.852
          - type: map_at_10
            value: 14.316
          - type: map_at_100
            value: 20.982
          - type: map_at_1000
            value: 22.58
          - type: map_at_3
            value: 7.767
          - type: map_at_5
            value: 10.321
          - type: mrr_at_1
            value: 51.019999999999996
          - type: mrr_at_10
            value: 66.365
          - type: mrr_at_100
            value: 66.522
          - type: mrr_at_1000
            value: 66.522
          - type: mrr_at_3
            value: 62.925
          - type: mrr_at_5
            value: 64.762
          - type: ndcg_at_1
            value: 46.939
          - type: ndcg_at_10
            value: 34.516999999999996
          - type: ndcg_at_100
            value: 44.25
          - type: ndcg_at_1000
            value: 54.899
          - type: ndcg_at_3
            value: 40.203
          - type: ndcg_at_5
            value: 37.004
          - type: precision_at_1
            value: 51.019999999999996
          - type: precision_at_10
            value: 29.796
          - type: precision_at_100
            value: 8.633000000000001
          - type: precision_at_1000
            value: 1.584
          - type: precision_at_3
            value: 40.816
          - type: precision_at_5
            value: 35.918
          - type: recall_at_1
            value: 3.852
          - type: recall_at_10
            value: 20.891000000000002
          - type: recall_at_100
            value: 52.428
          - type: recall_at_1000
            value: 84.34899999999999
          - type: recall_at_3
            value: 8.834
          - type: recall_at_5
            value: 12.909
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
        metrics:
          - type: accuracy
            value: 64.7092
          - type: ap
            value: 11.972915012305819
          - type: f1
            value: 49.91050149892115
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 56.737408036219584
          - type: f1
            value: 57.07235266246011
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 35.9147539025798
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 82.52369315133814
          - type: cos_sim_ap
            value: 62.34858091376534
          - type: cos_sim_f1
            value: 58.18225190839694
          - type: cos_sim_precision
            value: 53.09098824553766
          - type: cos_sim_recall
            value: 64.35356200527704
          - type: dot_accuracy
            value: 82.52369315133814
          - type: dot_ap
            value: 62.34857753814992
          - type: dot_f1
            value: 58.18225190839694
          - type: dot_precision
            value: 53.09098824553766
          - type: dot_recall
            value: 64.35356200527704
          - type: euclidean_accuracy
            value: 82.52369315133814
          - type: euclidean_ap
            value: 62.34857756663386
          - type: euclidean_f1
            value: 58.18225190839694
          - type: euclidean_precision
            value: 53.09098824553766
          - type: euclidean_recall
            value: 64.35356200527704
          - type: manhattan_accuracy
            value: 82.49389044525243
          - type: manhattan_ap
            value: 62.32245347238179
          - type: manhattan_f1
            value: 58.206309819213054
          - type: manhattan_precision
            value: 52.70704044511021
          - type: manhattan_recall
            value: 64.9868073878628
          - type: max_accuracy
            value: 82.52369315133814
          - type: max_ap
            value: 62.34858091376534
          - type: max_f1
            value: 58.206309819213054
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.34555827220863
          - type: cos_sim_ap
            value: 84.84152481680071
          - type: cos_sim_f1
            value: 76.860456739428
          - type: cos_sim_precision
            value: 72.21470150263978
          - type: cos_sim_recall
            value: 82.14505697566985
          - type: dot_accuracy
            value: 88.34555827220863
          - type: dot_ap
            value: 84.84152743322608
          - type: dot_f1
            value: 76.860456739428
          - type: dot_precision
            value: 72.21470150263978
          - type: dot_recall
            value: 82.14505697566985
          - type: euclidean_accuracy
            value: 88.34555827220863
          - type: euclidean_ap
            value: 84.84152589453169
          - type: euclidean_f1
            value: 76.860456739428
          - type: euclidean_precision
            value: 72.21470150263978
          - type: euclidean_recall
            value: 82.14505697566985
          - type: manhattan_accuracy
            value: 88.38242713548337
          - type: manhattan_ap
            value: 84.8112124970968
          - type: manhattan_f1
            value: 76.83599206057487
          - type: manhattan_precision
            value: 73.51244900829934
          - type: manhattan_recall
            value: 80.47428395441946
          - type: max_accuracy
            value: 88.38242713548337
          - type: max_ap
            value: 84.84152743322608
          - type: max_f1
            value: 76.860456739428
      - task:
          type: Clustering
        dataset:
          type: jinaai/cities_wiki_clustering
          name: MTEB WikiCitiesClustering
          config: default
          split: test
          revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
        metrics:
          - type: v_measure
            value: 85.5314389263015