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metadata
pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
model-index:
  - name: SGPT-5.8B-weightedmean-msmarco-specb-bitfit
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
        metrics:
          - type: accuracy
            value: 69.22388059701493
          - type: ap
            value: 32.04724673950256
          - type: f1
            value: 63.25719825770428
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
        metrics:
          - type: accuracy
            value: 71.26109999999998
          - type: ap
            value: 66.16336378255403
          - type: f1
            value: 70.89719145825303
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: c379a6705fec24a2493fa68e011692605f44e119
        metrics:
          - type: accuracy
            value: 39.19199999999999
          - type: f1
            value: 38.580766731113826
      - task:
          type: Retrieval
        dataset:
          type: arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
        metrics:
          - type: map_at_1
            value: 27.311999999999998
          - type: map_at_10
            value: 42.620000000000005
          - type: map_at_100
            value: 43.707
          - type: map_at_1000
            value: 43.714999999999996
          - type: map_at_3
            value: 37.624
          - type: map_at_5
            value: 40.498
          - type: mrr_at_1
            value: 27.667
          - type: mrr_at_10
            value: 42.737
          - type: mrr_at_100
            value: 43.823
          - type: mrr_at_1000
            value: 43.830999999999996
          - type: mrr_at_3
            value: 37.743
          - type: mrr_at_5
            value: 40.616
          - type: ndcg_at_1
            value: 27.311999999999998
          - type: ndcg_at_10
            value: 51.37500000000001
          - type: ndcg_at_100
            value: 55.778000000000006
          - type: ndcg_at_1000
            value: 55.96600000000001
          - type: ndcg_at_3
            value: 41.087
          - type: ndcg_at_5
            value: 46.269
          - type: precision_at_1
            value: 27.311999999999998
          - type: precision_at_10
            value: 7.945
          - type: precision_at_100
            value: 0.9820000000000001
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 17.046
          - type: precision_at_5
            value: 12.745000000000001
          - type: recall_at_1
            value: 27.311999999999998
          - type: recall_at_10
            value: 79.445
          - type: recall_at_100
            value: 98.151
          - type: recall_at_1000
            value: 99.57300000000001
          - type: recall_at_3
            value: 51.13799999999999
          - type: recall_at_5
            value: 63.727000000000004
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
        metrics:
          - type: v_measure
            value: 45.59037428592033
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
        metrics:
          - type: v_measure
            value: 38.86371701986363
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
        metrics:
          - type: map
            value: 61.625568691427766
          - type: mrr
            value: 75.83256386580486
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: 9ee918f184421b6bd48b78f6c714d86546106103
        metrics:
          - type: cos_sim_pearson
            value: 89.96074355094802
          - type: cos_sim_spearman
            value: 86.2501580394454
          - type: euclidean_pearson
            value: 82.18427440380462
          - type: euclidean_spearman
            value: 80.14760935017947
          - type: manhattan_pearson
            value: 82.24621578156392
          - type: manhattan_spearman
            value: 80.00363016590163
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
        metrics:
          - type: accuracy
            value: 84.49350649350649
          - type: f1
            value: 84.4249343233736
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
        metrics:
          - type: v_measure
            value: 36.551459722989385
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
        metrics:
          - type: v_measure
            value: 33.69901851846774
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 30.499
          - type: map_at_10
            value: 41.208
          - type: map_at_100
            value: 42.638
          - type: map_at_1000
            value: 42.754
          - type: map_at_3
            value: 37.506
          - type: map_at_5
            value: 39.422000000000004
          - type: mrr_at_1
            value: 37.339
          - type: mrr_at_10
            value: 47.051
          - type: mrr_at_100
            value: 47.745
          - type: mrr_at_1000
            value: 47.786
          - type: mrr_at_3
            value: 44.086999999999996
          - type: mrr_at_5
            value: 45.711
          - type: ndcg_at_1
            value: 37.339
          - type: ndcg_at_10
            value: 47.666
          - type: ndcg_at_100
            value: 52.994
          - type: ndcg_at_1000
            value: 54.928999999999995
          - type: ndcg_at_3
            value: 41.982
          - type: ndcg_at_5
            value: 44.42
          - type: precision_at_1
            value: 37.339
          - type: precision_at_10
            value: 9.127
          - type: precision_at_100
            value: 1.4749999999999999
          - type: precision_at_1000
            value: 0.194
          - type: precision_at_3
            value: 20.076
          - type: precision_at_5
            value: 14.449000000000002
          - type: recall_at_1
            value: 30.499
          - type: recall_at_10
            value: 60.328
          - type: recall_at_100
            value: 82.57900000000001
          - type: recall_at_1000
            value: 95.074
          - type: recall_at_3
            value: 44.17
          - type: recall_at_5
            value: 50.94
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 30.613
          - type: map_at_10
            value: 40.781
          - type: map_at_100
            value: 42.018
          - type: map_at_1000
            value: 42.132999999999996
          - type: map_at_3
            value: 37.816
          - type: map_at_5
            value: 39.389
          - type: mrr_at_1
            value: 38.408
          - type: mrr_at_10
            value: 46.631
          - type: mrr_at_100
            value: 47.332
          - type: mrr_at_1000
            value: 47.368
          - type: mrr_at_3
            value: 44.384
          - type: mrr_at_5
            value: 45.661
          - type: ndcg_at_1
            value: 38.408
          - type: ndcg_at_10
            value: 46.379999999999995
          - type: ndcg_at_100
            value: 50.81
          - type: ndcg_at_1000
            value: 52.663000000000004
          - type: ndcg_at_3
            value: 42.18
          - type: ndcg_at_5
            value: 43.974000000000004
          - type: precision_at_1
            value: 38.408
          - type: precision_at_10
            value: 8.656
          - type: precision_at_100
            value: 1.3860000000000001
          - type: precision_at_1000
            value: 0.184
          - type: precision_at_3
            value: 20.276
          - type: precision_at_5
            value: 14.241999999999999
          - type: recall_at_1
            value: 30.613
          - type: recall_at_10
            value: 56.44
          - type: recall_at_100
            value: 75.044
          - type: recall_at_1000
            value: 86.426
          - type: recall_at_3
            value: 43.766
          - type: recall_at_5
            value: 48.998000000000005
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 37.370999999999995
          - type: map_at_10
            value: 49.718
          - type: map_at_100
            value: 50.737
          - type: map_at_1000
            value: 50.79
          - type: map_at_3
            value: 46.231
          - type: map_at_5
            value: 48.329
          - type: mrr_at_1
            value: 42.884
          - type: mrr_at_10
            value: 53.176
          - type: mrr_at_100
            value: 53.81700000000001
          - type: mrr_at_1000
            value: 53.845
          - type: mrr_at_3
            value: 50.199000000000005
          - type: mrr_at_5
            value: 52.129999999999995
          - type: ndcg_at_1
            value: 42.884
          - type: ndcg_at_10
            value: 55.826
          - type: ndcg_at_100
            value: 59.93000000000001
          - type: ndcg_at_1000
            value: 61.013
          - type: ndcg_at_3
            value: 49.764
          - type: ndcg_at_5
            value: 53.025999999999996
          - type: precision_at_1
            value: 42.884
          - type: precision_at_10
            value: 9.046999999999999
          - type: precision_at_100
            value: 1.212
          - type: precision_at_1000
            value: 0.135
          - type: precision_at_3
            value: 22.131999999999998
          - type: precision_at_5
            value: 15.524
          - type: recall_at_1
            value: 37.370999999999995
          - type: recall_at_10
            value: 70.482
          - type: recall_at_100
            value: 88.425
          - type: recall_at_1000
            value: 96.03399999999999
          - type: recall_at_3
            value: 54.43
          - type: recall_at_5
            value: 62.327999999999996
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 22.875999999999998
          - type: map_at_10
            value: 31.715
          - type: map_at_100
            value: 32.847
          - type: map_at_1000
            value: 32.922000000000004
          - type: map_at_3
            value: 29.049999999999997
          - type: map_at_5
            value: 30.396
          - type: mrr_at_1
            value: 24.52
          - type: mrr_at_10
            value: 33.497
          - type: mrr_at_100
            value: 34.455000000000005
          - type: mrr_at_1000
            value: 34.510000000000005
          - type: mrr_at_3
            value: 30.791
          - type: mrr_at_5
            value: 32.175
          - type: ndcg_at_1
            value: 24.52
          - type: ndcg_at_10
            value: 36.95
          - type: ndcg_at_100
            value: 42.238
          - type: ndcg_at_1000
            value: 44.147999999999996
          - type: ndcg_at_3
            value: 31.435000000000002
          - type: ndcg_at_5
            value: 33.839000000000006
          - type: precision_at_1
            value: 24.52
          - type: precision_at_10
            value: 5.9319999999999995
          - type: precision_at_100
            value: 0.901
          - type: precision_at_1000
            value: 0.11
          - type: precision_at_3
            value: 13.446
          - type: precision_at_5
            value: 9.469
          - type: recall_at_1
            value: 22.875999999999998
          - type: recall_at_10
            value: 51.38
          - type: recall_at_100
            value: 75.31099999999999
          - type: recall_at_1000
            value: 89.718
          - type: recall_at_3
            value: 36.26
          - type: recall_at_5
            value: 42.248999999999995
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 14.984
          - type: map_at_10
            value: 23.457
          - type: map_at_100
            value: 24.723
          - type: map_at_1000
            value: 24.846
          - type: map_at_3
            value: 20.873
          - type: map_at_5
            value: 22.357
          - type: mrr_at_1
            value: 18.159
          - type: mrr_at_10
            value: 27.431
          - type: mrr_at_100
            value: 28.449
          - type: mrr_at_1000
            value: 28.52
          - type: mrr_at_3
            value: 24.979000000000003
          - type: mrr_at_5
            value: 26.447
          - type: ndcg_at_1
            value: 18.159
          - type: ndcg_at_10
            value: 28.627999999999997
          - type: ndcg_at_100
            value: 34.741
          - type: ndcg_at_1000
            value: 37.516
          - type: ndcg_at_3
            value: 23.902
          - type: ndcg_at_5
            value: 26.294
          - type: precision_at_1
            value: 18.159
          - type: precision_at_10
            value: 5.485
          - type: precision_at_100
            value: 0.985
          - type: precision_at_1000
            value: 0.136
          - type: precision_at_3
            value: 11.774
          - type: precision_at_5
            value: 8.731
          - type: recall_at_1
            value: 14.984
          - type: recall_at_10
            value: 40.198
          - type: recall_at_100
            value: 67.11500000000001
          - type: recall_at_1000
            value: 86.497
          - type: recall_at_3
            value: 27.639000000000003
          - type: recall_at_5
            value: 33.595000000000006
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 29.067
          - type: map_at_10
            value: 39.457
          - type: map_at_100
            value: 40.83
          - type: map_at_1000
            value: 40.94
          - type: map_at_3
            value: 35.995
          - type: map_at_5
            value: 38.159
          - type: mrr_at_1
            value: 34.937000000000005
          - type: mrr_at_10
            value: 44.755
          - type: mrr_at_100
            value: 45.549
          - type: mrr_at_1000
            value: 45.589
          - type: mrr_at_3
            value: 41.947
          - type: mrr_at_5
            value: 43.733
          - type: ndcg_at_1
            value: 34.937000000000005
          - type: ndcg_at_10
            value: 45.573
          - type: ndcg_at_100
            value: 51.266999999999996
          - type: ndcg_at_1000
            value: 53.184
          - type: ndcg_at_3
            value: 39.961999999999996
          - type: ndcg_at_5
            value: 43.02
          - type: precision_at_1
            value: 34.937000000000005
          - type: precision_at_10
            value: 8.296000000000001
          - type: precision_at_100
            value: 1.32
          - type: precision_at_1000
            value: 0.167
          - type: precision_at_3
            value: 18.8
          - type: precision_at_5
            value: 13.763
          - type: recall_at_1
            value: 29.067
          - type: recall_at_10
            value: 58.298
          - type: recall_at_100
            value: 82.25099999999999
          - type: recall_at_1000
            value: 94.476
          - type: recall_at_3
            value: 42.984
          - type: recall_at_5
            value: 50.658
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 25.985999999999997
          - type: map_at_10
            value: 35.746
          - type: map_at_100
            value: 37.067
          - type: map_at_1000
            value: 37.191
          - type: map_at_3
            value: 32.599000000000004
          - type: map_at_5
            value: 34.239000000000004
          - type: mrr_at_1
            value: 31.735000000000003
          - type: mrr_at_10
            value: 40.515
          - type: mrr_at_100
            value: 41.459
          - type: mrr_at_1000
            value: 41.516
          - type: mrr_at_3
            value: 37.938
          - type: mrr_at_5
            value: 39.25
          - type: ndcg_at_1
            value: 31.735000000000003
          - type: ndcg_at_10
            value: 41.484
          - type: ndcg_at_100
            value: 47.047
          - type: ndcg_at_1000
            value: 49.427
          - type: ndcg_at_3
            value: 36.254999999999995
          - type: ndcg_at_5
            value: 38.375
          - type: precision_at_1
            value: 31.735000000000003
          - type: precision_at_10
            value: 7.66
          - type: precision_at_100
            value: 1.234
          - type: precision_at_1000
            value: 0.16
          - type: precision_at_3
            value: 17.427999999999997
          - type: precision_at_5
            value: 12.328999999999999
          - type: recall_at_1
            value: 25.985999999999997
          - type: recall_at_10
            value: 53.761
          - type: recall_at_100
            value: 77.149
          - type: recall_at_1000
            value: 93.342
          - type: recall_at_3
            value: 39.068000000000005
          - type: recall_at_5
            value: 44.693
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 24.949749999999998
          - type: map_at_10
            value: 34.04991666666667
          - type: map_at_100
            value: 35.26825
          - type: map_at_1000
            value: 35.38316666666667
          - type: map_at_3
            value: 31.181333333333335
          - type: map_at_5
            value: 32.77391666666667
          - type: mrr_at_1
            value: 29.402833333333334
          - type: mrr_at_10
            value: 38.01633333333333
          - type: mrr_at_100
            value: 38.88033333333334
          - type: mrr_at_1000
            value: 38.938500000000005
          - type: mrr_at_3
            value: 35.5175
          - type: mrr_at_5
            value: 36.93808333333333
          - type: ndcg_at_1
            value: 29.402833333333334
          - type: ndcg_at_10
            value: 39.403166666666664
          - type: ndcg_at_100
            value: 44.66408333333333
          - type: ndcg_at_1000
            value: 46.96283333333333
          - type: ndcg_at_3
            value: 34.46633333333334
          - type: ndcg_at_5
            value: 36.78441666666667
          - type: precision_at_1
            value: 29.402833333333334
          - type: precision_at_10
            value: 6.965833333333333
          - type: precision_at_100
            value: 1.1330833333333334
          - type: precision_at_1000
            value: 0.15158333333333335
          - type: precision_at_3
            value: 15.886666666666665
          - type: precision_at_5
            value: 11.360416666666667
          - type: recall_at_1
            value: 24.949749999999998
          - type: recall_at_10
            value: 51.29325
          - type: recall_at_100
            value: 74.3695
          - type: recall_at_1000
            value: 90.31299999999999
          - type: recall_at_3
            value: 37.580083333333334
          - type: recall_at_5
            value: 43.529666666666664
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 22.081999999999997
          - type: map_at_10
            value: 29.215999999999998
          - type: map_at_100
            value: 30.163
          - type: map_at_1000
            value: 30.269000000000002
          - type: map_at_3
            value: 26.942
          - type: map_at_5
            value: 28.236
          - type: mrr_at_1
            value: 24.847
          - type: mrr_at_10
            value: 31.918999999999997
          - type: mrr_at_100
            value: 32.817
          - type: mrr_at_1000
            value: 32.897
          - type: mrr_at_3
            value: 29.831000000000003
          - type: mrr_at_5
            value: 31.019999999999996
          - type: ndcg_at_1
            value: 24.847
          - type: ndcg_at_10
            value: 33.4
          - type: ndcg_at_100
            value: 38.354
          - type: ndcg_at_1000
            value: 41.045
          - type: ndcg_at_3
            value: 29.236
          - type: ndcg_at_5
            value: 31.258000000000003
          - type: precision_at_1
            value: 24.847
          - type: precision_at_10
            value: 5.353
          - type: precision_at_100
            value: 0.853
          - type: precision_at_1000
            value: 0.116
          - type: precision_at_3
            value: 12.679000000000002
          - type: precision_at_5
            value: 8.988
          - type: recall_at_1
            value: 22.081999999999997
          - type: recall_at_10
            value: 43.505
          - type: recall_at_100
            value: 66.45400000000001
          - type: recall_at_1000
            value: 86.378
          - type: recall_at_3
            value: 32.163000000000004
          - type: recall_at_5
            value: 37.059999999999995
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 15.540000000000001
          - type: map_at_10
            value: 22.362000000000002
          - type: map_at_100
            value: 23.435
          - type: map_at_1000
            value: 23.564
          - type: map_at_3
            value: 20.143
          - type: map_at_5
            value: 21.324
          - type: mrr_at_1
            value: 18.892
          - type: mrr_at_10
            value: 25.942999999999998
          - type: mrr_at_100
            value: 26.883000000000003
          - type: mrr_at_1000
            value: 26.968999999999998
          - type: mrr_at_3
            value: 23.727
          - type: mrr_at_5
            value: 24.923000000000002
          - type: ndcg_at_1
            value: 18.892
          - type: ndcg_at_10
            value: 26.811
          - type: ndcg_at_100
            value: 32.066
          - type: ndcg_at_1000
            value: 35.166
          - type: ndcg_at_3
            value: 22.706
          - type: ndcg_at_5
            value: 24.508
          - type: precision_at_1
            value: 18.892
          - type: precision_at_10
            value: 4.942
          - type: precision_at_100
            value: 0.878
          - type: precision_at_1000
            value: 0.131
          - type: precision_at_3
            value: 10.748000000000001
          - type: precision_at_5
            value: 7.784000000000001
          - type: recall_at_1
            value: 15.540000000000001
          - type: recall_at_10
            value: 36.742999999999995
          - type: recall_at_100
            value: 60.525
          - type: recall_at_1000
            value: 82.57600000000001
          - type: recall_at_3
            value: 25.252000000000002
          - type: recall_at_5
            value: 29.872
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 24.453
          - type: map_at_10
            value: 33.363
          - type: map_at_100
            value: 34.579
          - type: map_at_1000
            value: 34.686
          - type: map_at_3
            value: 30.583
          - type: map_at_5
            value: 32.118
          - type: mrr_at_1
            value: 28.918
          - type: mrr_at_10
            value: 37.675
          - type: mrr_at_100
            value: 38.567
          - type: mrr_at_1000
            value: 38.632
          - type: mrr_at_3
            value: 35.260999999999996
          - type: mrr_at_5
            value: 36.576
          - type: ndcg_at_1
            value: 28.918
          - type: ndcg_at_10
            value: 38.736
          - type: ndcg_at_100
            value: 44.261
          - type: ndcg_at_1000
            value: 46.72
          - type: ndcg_at_3
            value: 33.81
          - type: ndcg_at_5
            value: 36.009
          - type: precision_at_1
            value: 28.918
          - type: precision_at_10
            value: 6.586
          - type: precision_at_100
            value: 1.047
          - type: precision_at_1000
            value: 0.13699999999999998
          - type: precision_at_3
            value: 15.360999999999999
          - type: precision_at_5
            value: 10.857999999999999
          - type: recall_at_1
            value: 24.453
          - type: recall_at_10
            value: 50.885999999999996
          - type: recall_at_100
            value: 75.03
          - type: recall_at_1000
            value: 92.123
          - type: recall_at_3
            value: 37.138
          - type: recall_at_5
            value: 42.864999999999995
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 24.57
          - type: map_at_10
            value: 33.672000000000004
          - type: map_at_100
            value: 35.244
          - type: map_at_1000
            value: 35.467
          - type: map_at_3
            value: 30.712
          - type: map_at_5
            value: 32.383
          - type: mrr_at_1
            value: 29.644
          - type: mrr_at_10
            value: 38.344
          - type: mrr_at_100
            value: 39.219
          - type: mrr_at_1000
            value: 39.282000000000004
          - type: mrr_at_3
            value: 35.771
          - type: mrr_at_5
            value: 37.273
          - type: ndcg_at_1
            value: 29.644
          - type: ndcg_at_10
            value: 39.567
          - type: ndcg_at_100
            value: 45.097
          - type: ndcg_at_1000
            value: 47.923
          - type: ndcg_at_3
            value: 34.768
          - type: ndcg_at_5
            value: 37.122
          - type: precision_at_1
            value: 29.644
          - type: precision_at_10
            value: 7.5889999999999995
          - type: precision_at_100
            value: 1.478
          - type: precision_at_1000
            value: 0.23500000000000001
          - type: precision_at_3
            value: 16.337
          - type: precision_at_5
            value: 12.055
          - type: recall_at_1
            value: 24.57
          - type: recall_at_10
            value: 51.00900000000001
          - type: recall_at_100
            value: 75.423
          - type: recall_at_1000
            value: 93.671
          - type: recall_at_3
            value: 36.925999999999995
          - type: recall_at_5
            value: 43.245
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
        metrics:
          - type: map_at_1
            value: 21.356
          - type: map_at_10
            value: 27.904
          - type: map_at_100
            value: 28.938000000000002
          - type: map_at_1000
            value: 29.036
          - type: map_at_3
            value: 25.726
          - type: map_at_5
            value: 26.935
          - type: mrr_at_1
            value: 22.551
          - type: mrr_at_10
            value: 29.259
          - type: mrr_at_100
            value: 30.272
          - type: mrr_at_1000
            value: 30.348000000000003
          - type: mrr_at_3
            value: 27.295
          - type: mrr_at_5
            value: 28.358
          - type: ndcg_at_1
            value: 22.551
          - type: ndcg_at_10
            value: 31.817
          - type: ndcg_at_100
            value: 37.164
          - type: ndcg_at_1000
            value: 39.82
          - type: ndcg_at_3
            value: 27.595999999999997
          - type: ndcg_at_5
            value: 29.568
          - type: precision_at_1
            value: 22.551
          - type: precision_at_10
            value: 4.917
          - type: precision_at_100
            value: 0.828
          - type: precision_at_1000
            value: 0.11399999999999999
          - type: precision_at_3
            value: 11.583
          - type: precision_at_5
            value: 8.133
          - type: recall_at_1
            value: 21.356
          - type: recall_at_10
            value: 42.489
          - type: recall_at_100
            value: 67.128
          - type: recall_at_1000
            value: 87.441
          - type: recall_at_3
            value: 31.165
          - type: recall_at_5
            value: 35.853
      - task:
          type: Retrieval
        dataset:
          type: climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
        metrics:
          - type: map_at_1
            value: 12.306000000000001
          - type: map_at_10
            value: 21.523
          - type: map_at_100
            value: 23.358
          - type: map_at_1000
            value: 23.541
          - type: map_at_3
            value: 17.809
          - type: map_at_5
            value: 19.631
          - type: mrr_at_1
            value: 27.948
          - type: mrr_at_10
            value: 40.355000000000004
          - type: mrr_at_100
            value: 41.166000000000004
          - type: mrr_at_1000
            value: 41.203
          - type: mrr_at_3
            value: 36.819
          - type: mrr_at_5
            value: 38.958999999999996
          - type: ndcg_at_1
            value: 27.948
          - type: ndcg_at_10
            value: 30.462
          - type: ndcg_at_100
            value: 37.473
          - type: ndcg_at_1000
            value: 40.717999999999996
          - type: ndcg_at_3
            value: 24.646
          - type: ndcg_at_5
            value: 26.642
          - type: precision_at_1
            value: 27.948
          - type: precision_at_10
            value: 9.648
          - type: precision_at_100
            value: 1.7239999999999998
          - type: precision_at_1000
            value: 0.232
          - type: precision_at_3
            value: 18.48
          - type: precision_at_5
            value: 14.293
          - type: recall_at_1
            value: 12.306000000000001
          - type: recall_at_10
            value: 37.181
          - type: recall_at_100
            value: 61.148
          - type: recall_at_1000
            value: 79.401
          - type: recall_at_3
            value: 22.883
          - type: recall_at_5
            value: 28.59
      - task:
          type: Retrieval
        dataset:
          type: dbpedia-entity
          name: MTEB DBPedia
          config: default
          split: test
          revision: f097057d03ed98220bc7309ddb10b71a54d667d6
        metrics:
          - type: map_at_1
            value: 9.357
          - type: map_at_10
            value: 18.849
          - type: map_at_100
            value: 25.369000000000003
          - type: map_at_1000
            value: 26.950000000000003
          - type: map_at_3
            value: 13.625000000000002
          - type: map_at_5
            value: 15.956999999999999
          - type: mrr_at_1
            value: 67.75
          - type: mrr_at_10
            value: 74.734
          - type: mrr_at_100
            value: 75.1
          - type: mrr_at_1000
            value: 75.10900000000001
          - type: mrr_at_3
            value: 73.542
          - type: mrr_at_5
            value: 74.167
          - type: ndcg_at_1
            value: 55.375
          - type: ndcg_at_10
            value: 39.873999999999995
          - type: ndcg_at_100
            value: 43.098
          - type: ndcg_at_1000
            value: 50.69200000000001
          - type: ndcg_at_3
            value: 44.856
          - type: ndcg_at_5
            value: 42.138999999999996
          - type: precision_at_1
            value: 67.75
          - type: precision_at_10
            value: 31.1
          - type: precision_at_100
            value: 9.303
          - type: precision_at_1000
            value: 2.0060000000000002
          - type: precision_at_3
            value: 48.25
          - type: precision_at_5
            value: 40.949999999999996
          - type: recall_at_1
            value: 9.357
          - type: recall_at_10
            value: 23.832
          - type: recall_at_100
            value: 47.906
          - type: recall_at_1000
            value: 71.309
          - type: recall_at_3
            value: 14.512
          - type: recall_at_5
            value: 18.3
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 829147f8f75a25f005913200eb5ed41fae320aa1
        metrics:
          - type: accuracy
            value: 49.655
          - type: f1
            value: 45.51976190938951
      - task:
          type: Retrieval
        dataset:
          type: fever
          name: MTEB FEVER
          config: default
          split: test
          revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
        metrics:
          - type: map_at_1
            value: 62.739999999999995
          - type: map_at_10
            value: 73.07000000000001
          - type: map_at_100
            value: 73.398
          - type: map_at_1000
            value: 73.41
          - type: map_at_3
            value: 71.33800000000001
          - type: map_at_5
            value: 72.423
          - type: mrr_at_1
            value: 67.777
          - type: mrr_at_10
            value: 77.873
          - type: mrr_at_100
            value: 78.091
          - type: mrr_at_1000
            value: 78.094
          - type: mrr_at_3
            value: 76.375
          - type: mrr_at_5
            value: 77.316
          - type: ndcg_at_1
            value: 67.777
          - type: ndcg_at_10
            value: 78.24
          - type: ndcg_at_100
            value: 79.557
          - type: ndcg_at_1000
            value: 79.814
          - type: ndcg_at_3
            value: 75.125
          - type: ndcg_at_5
            value: 76.834
          - type: precision_at_1
            value: 67.777
          - type: precision_at_10
            value: 9.832
          - type: precision_at_100
            value: 1.061
          - type: precision_at_1000
            value: 0.11
          - type: precision_at_3
            value: 29.433
          - type: precision_at_5
            value: 18.665000000000003
          - type: recall_at_1
            value: 62.739999999999995
          - type: recall_at_10
            value: 89.505
          - type: recall_at_100
            value: 95.102
          - type: recall_at_1000
            value: 96.825
          - type: recall_at_3
            value: 81.028
          - type: recall_at_5
            value: 85.28099999999999
      - task:
          type: Retrieval
        dataset:
          type: fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
        metrics:
          - type: map_at_1
            value: 18.467
          - type: map_at_10
            value: 30.020999999999997
          - type: map_at_100
            value: 31.739
          - type: map_at_1000
            value: 31.934
          - type: map_at_3
            value: 26.003
          - type: map_at_5
            value: 28.338
          - type: mrr_at_1
            value: 35.339999999999996
          - type: mrr_at_10
            value: 44.108999999999995
          - type: mrr_at_100
            value: 44.993
          - type: mrr_at_1000
            value: 45.042
          - type: mrr_at_3
            value: 41.667
          - type: mrr_at_5
            value: 43.14
          - type: ndcg_at_1
            value: 35.339999999999996
          - type: ndcg_at_10
            value: 37.202
          - type: ndcg_at_100
            value: 43.852999999999994
          - type: ndcg_at_1000
            value: 47.235
          - type: ndcg_at_3
            value: 33.5
          - type: ndcg_at_5
            value: 34.985
          - type: precision_at_1
            value: 35.339999999999996
          - type: precision_at_10
            value: 10.247
          - type: precision_at_100
            value: 1.7149999999999999
          - type: precision_at_1000
            value: 0.232
          - type: precision_at_3
            value: 22.222
          - type: precision_at_5
            value: 16.573999999999998
          - type: recall_at_1
            value: 18.467
          - type: recall_at_10
            value: 44.080999999999996
          - type: recall_at_100
            value: 68.72200000000001
          - type: recall_at_1000
            value: 89.087
          - type: recall_at_3
            value: 30.567
          - type: recall_at_5
            value: 36.982
      - task:
          type: Retrieval
        dataset:
          type: hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
        metrics:
          - type: map_at_1
            value: 35.726
          - type: map_at_10
            value: 50.207
          - type: map_at_100
            value: 51.05499999999999
          - type: map_at_1000
            value: 51.12799999999999
          - type: map_at_3
            value: 47.576
          - type: map_at_5
            value: 49.172
          - type: mrr_at_1
            value: 71.452
          - type: mrr_at_10
            value: 77.41900000000001
          - type: mrr_at_100
            value: 77.711
          - type: mrr_at_1000
            value: 77.723
          - type: mrr_at_3
            value: 76.39399999999999
          - type: mrr_at_5
            value: 77.00099999999999
          - type: ndcg_at_1
            value: 71.452
          - type: ndcg_at_10
            value: 59.260999999999996
          - type: ndcg_at_100
            value: 62.424
          - type: ndcg_at_1000
            value: 63.951
          - type: ndcg_at_3
            value: 55.327000000000005
          - type: ndcg_at_5
            value: 57.416999999999994
          - type: precision_at_1
            value: 71.452
          - type: precision_at_10
            value: 12.061
          - type: precision_at_100
            value: 1.455
          - type: precision_at_1000
            value: 0.166
          - type: precision_at_3
            value: 34.36
          - type: precision_at_5
            value: 22.266
          - type: recall_at_1
            value: 35.726
          - type: recall_at_10
            value: 60.304
          - type: recall_at_100
            value: 72.75500000000001
          - type: recall_at_1000
            value: 82.978
          - type: recall_at_3
            value: 51.54
          - type: recall_at_5
            value: 55.665
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
        metrics:
          - type: accuracy
            value: 66.63759999999999
          - type: ap
            value: 61.48938261286748
          - type: f1
            value: 66.35089269264965
      - task:
          type: Retrieval
        dataset:
          type: msmarco
          name: MTEB MSMARCO
          config: default
          split: validation
          revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
        metrics:
          - type: map_at_1
            value: 20.842
          - type: map_at_10
            value: 32.992
          - type: map_at_100
            value: 34.236
          - type: map_at_1000
            value: 34.286
          - type: map_at_3
            value: 29.049000000000003
          - type: map_at_5
            value: 31.391999999999996
          - type: mrr_at_1
            value: 21.375
          - type: mrr_at_10
            value: 33.581
          - type: mrr_at_100
            value: 34.760000000000005
          - type: mrr_at_1000
            value: 34.803
          - type: mrr_at_3
            value: 29.704000000000004
          - type: mrr_at_5
            value: 32.015
          - type: ndcg_at_1
            value: 21.375
          - type: ndcg_at_10
            value: 39.905
          - type: ndcg_at_100
            value: 45.843
          - type: ndcg_at_1000
            value: 47.083999999999996
          - type: ndcg_at_3
            value: 31.918999999999997
          - type: ndcg_at_5
            value: 36.107
          - type: precision_at_1
            value: 21.375
          - type: precision_at_10
            value: 6.393
          - type: precision_at_100
            value: 0.935
          - type: precision_at_1000
            value: 0.104
          - type: precision_at_3
            value: 13.663
          - type: precision_at_5
            value: 10.324
          - type: recall_at_1
            value: 20.842
          - type: recall_at_10
            value: 61.17
          - type: recall_at_100
            value: 88.518
          - type: recall_at_1000
            value: 97.993
          - type: recall_at_3
            value: 39.571
          - type: recall_at_5
            value: 49.653999999999996
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
        metrics:
          - type: accuracy
            value: 93.46557227542178
          - type: f1
            value: 92.87345917772146
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: 6299947a7777084cc2d4b64235bf7190381ce755
        metrics:
          - type: accuracy
            value: 72.42134062927497
          - type: f1
            value: 55.03624810959269
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
        metrics:
          - type: accuracy
            value: 70.3866845998655
          - type: f1
            value: 68.9674519872921
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 76.27774041694687
          - type: f1
            value: 76.72936190462792
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: dcefc037ef84348e49b0d29109e891c01067226b
        metrics:
          - type: v_measure
            value: 31.511745925773337
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc
        metrics:
          - type: v_measure
            value: 28.764235987575365
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 32.29353136386601
          - type: mrr
            value: 33.536774455851685
      - task:
          type: Retrieval
        dataset:
          type: nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610
        metrics:
          - type: map_at_1
            value: 5.702
          - type: map_at_10
            value: 13.642000000000001
          - type: map_at_100
            value: 17.503
          - type: map_at_1000
            value: 19.126
          - type: map_at_3
            value: 9.748
          - type: map_at_5
            value: 11.642
          - type: mrr_at_1
            value: 45.82
          - type: mrr_at_10
            value: 54.821
          - type: mrr_at_100
            value: 55.422000000000004
          - type: mrr_at_1000
            value: 55.452999999999996
          - type: mrr_at_3
            value: 52.373999999999995
          - type: mrr_at_5
            value: 53.937000000000005
          - type: ndcg_at_1
            value: 44.272
          - type: ndcg_at_10
            value: 36.213
          - type: ndcg_at_100
            value: 33.829
          - type: ndcg_at_1000
            value: 42.557
          - type: ndcg_at_3
            value: 40.814
          - type: ndcg_at_5
            value: 39.562000000000005
          - type: precision_at_1
            value: 45.511
          - type: precision_at_10
            value: 27.214
          - type: precision_at_100
            value: 8.941
          - type: precision_at_1000
            value: 2.1870000000000003
          - type: precision_at_3
            value: 37.874
          - type: precision_at_5
            value: 34.489
          - type: recall_at_1
            value: 5.702
          - type: recall_at_10
            value: 17.638
          - type: recall_at_100
            value: 34.419
          - type: recall_at_1000
            value: 66.41
          - type: recall_at_3
            value: 10.914
          - type: recall_at_5
            value: 14.032
      - task:
          type: Retrieval
        dataset:
          type: nq
          name: MTEB NQ
          config: default
          split: test
          revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c
        metrics:
          - type: map_at_1
            value: 30.567
          - type: map_at_10
            value: 45.01
          - type: map_at_100
            value: 46.091
          - type: map_at_1000
            value: 46.126
          - type: map_at_3
            value: 40.897
          - type: map_at_5
            value: 43.301
          - type: mrr_at_1
            value: 34.56
          - type: mrr_at_10
            value: 47.725
          - type: mrr_at_100
            value: 48.548
          - type: mrr_at_1000
            value: 48.571999999999996
          - type: mrr_at_3
            value: 44.361
          - type: mrr_at_5
            value: 46.351
          - type: ndcg_at_1
            value: 34.531
          - type: ndcg_at_10
            value: 52.410000000000004
          - type: ndcg_at_100
            value: 56.999
          - type: ndcg_at_1000
            value: 57.830999999999996
          - type: ndcg_at_3
            value: 44.734
          - type: ndcg_at_5
            value: 48.701
          - type: precision_at_1
            value: 34.531
          - type: precision_at_10
            value: 8.612
          - type: precision_at_100
            value: 1.118
          - type: precision_at_1000
            value: 0.12
          - type: precision_at_3
            value: 20.307
          - type: precision_at_5
            value: 14.519000000000002
          - type: recall_at_1
            value: 30.567
          - type: recall_at_10
            value: 72.238
          - type: recall_at_100
            value: 92.154
          - type: recall_at_1000
            value: 98.375
          - type: recall_at_3
            value: 52.437999999999995
          - type: recall_at_5
            value: 61.516999999999996
      - task:
          type: Retrieval
        dataset:
          type: quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: 6205996560df11e3a3da9ab4f926788fc30a7db4
        metrics:
          - type: map_at_1
            value: 65.98
          - type: map_at_10
            value: 80.05600000000001
          - type: map_at_100
            value: 80.76299999999999
          - type: map_at_1000
            value: 80.786
          - type: map_at_3
            value: 76.848
          - type: map_at_5
            value: 78.854
          - type: mrr_at_1
            value: 75.86
          - type: mrr_at_10
            value: 83.397
          - type: mrr_at_100
            value: 83.555
          - type: mrr_at_1000
            value: 83.557
          - type: mrr_at_3
            value: 82.033
          - type: mrr_at_5
            value: 82.97
          - type: ndcg_at_1
            value: 75.88000000000001
          - type: ndcg_at_10
            value: 84.58099999999999
          - type: ndcg_at_100
            value: 86.151
          - type: ndcg_at_1000
            value: 86.315
          - type: ndcg_at_3
            value: 80.902
          - type: ndcg_at_5
            value: 82.953
          - type: precision_at_1
            value: 75.88000000000001
          - type: precision_at_10
            value: 12.986
          - type: precision_at_100
            value: 1.5110000000000001
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 35.382999999999996
          - type: precision_at_5
            value: 23.555999999999997
          - type: recall_at_1
            value: 65.98
          - type: recall_at_10
            value: 93.716
          - type: recall_at_100
            value: 99.21799999999999
          - type: recall_at_1000
            value: 99.97
          - type: recall_at_3
            value: 83.551
          - type: recall_at_5
            value: 88.998
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: b2805658ae38990172679479369a78b86de8c390
        metrics:
          - type: v_measure
            value: 40.45148482612238
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
        metrics:
          - type: v_measure
            value: 55.749490673039126
      - task:
          type: Retrieval
        dataset:
          type: scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
        metrics:
          - type: map_at_1
            value: 4.903
          - type: map_at_10
            value: 11.926
          - type: map_at_100
            value: 13.916999999999998
          - type: map_at_1000
            value: 14.215
          - type: map_at_3
            value: 8.799999999999999
          - type: map_at_5
            value: 10.360999999999999
          - type: mrr_at_1
            value: 24.099999999999998
          - type: mrr_at_10
            value: 34.482
          - type: mrr_at_100
            value: 35.565999999999995
          - type: mrr_at_1000
            value: 35.619
          - type: mrr_at_3
            value: 31.433
          - type: mrr_at_5
            value: 33.243
          - type: ndcg_at_1
            value: 24.099999999999998
          - type: ndcg_at_10
            value: 19.872999999999998
          - type: ndcg_at_100
            value: 27.606
          - type: ndcg_at_1000
            value: 32.811
          - type: ndcg_at_3
            value: 19.497999999999998
          - type: ndcg_at_5
            value: 16.813
          - type: precision_at_1
            value: 24.099999999999998
          - type: precision_at_10
            value: 10.08
          - type: precision_at_100
            value: 2.122
          - type: precision_at_1000
            value: 0.337
          - type: precision_at_3
            value: 18.2
          - type: precision_at_5
            value: 14.62
          - type: recall_at_1
            value: 4.903
          - type: recall_at_10
            value: 20.438000000000002
          - type: recall_at_100
            value: 43.043
          - type: recall_at_1000
            value: 68.41000000000001
          - type: recall_at_3
            value: 11.068
          - type: recall_at_5
            value: 14.818000000000001
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
        metrics:
          - type: cos_sim_pearson
            value: 78.58086597995997
          - type: cos_sim_spearman
            value: 69.63214182814991
          - type: euclidean_pearson
            value: 72.76175489042691
          - type: euclidean_spearman
            value: 67.84965161872971
          - type: manhattan_pearson
            value: 72.73812689782592
          - type: manhattan_spearman
            value: 67.83610439531277
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
        metrics:
          - type: cos_sim_pearson
            value: 75.13970861325006
          - type: cos_sim_spearman
            value: 67.5020551515597
          - type: euclidean_pearson
            value: 66.33415412418276
          - type: euclidean_spearman
            value: 66.82145056673268
          - type: manhattan_pearson
            value: 66.55489484006415
          - type: manhattan_spearman
            value: 66.95147433279057
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
        metrics:
          - type: cos_sim_pearson
            value: 78.85850536483447
          - type: cos_sim_spearman
            value: 79.1633350177206
          - type: euclidean_pearson
            value: 72.74090561408477
          - type: euclidean_spearman
            value: 73.57374448302961
          - type: manhattan_pearson
            value: 72.92980654233226
          - type: manhattan_spearman
            value: 73.72777155112588
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
        metrics:
          - type: cos_sim_pearson
            value: 79.51125593897028
          - type: cos_sim_spearman
            value: 74.46048326701329
          - type: euclidean_pearson
            value: 70.87726087052985
          - type: euclidean_spearman
            value: 67.7721470654411
          - type: manhattan_pearson
            value: 71.05892792135637
          - type: manhattan_spearman
            value: 67.93472619779037
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
        metrics:
          - type: cos_sim_pearson
            value: 83.8299348880489
          - type: cos_sim_spearman
            value: 84.47194637929275
          - type: euclidean_pearson
            value: 78.68768462480418
          - type: euclidean_spearman
            value: 79.80526323901917
          - type: manhattan_pearson
            value: 78.6810718151946
          - type: manhattan_spearman
            value: 79.7820584821254
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
        metrics:
          - type: cos_sim_pearson
            value: 79.99206664843005
          - type: cos_sim_spearman
            value: 80.96089203722137
          - type: euclidean_pearson
            value: 71.31216213716365
          - type: euclidean_spearman
            value: 71.45258140049407
          - type: manhattan_pearson
            value: 71.26140340402836
          - type: manhattan_spearman
            value: 71.3896894666943
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-en)
          config: en-en
          split: test
          revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
        metrics:
          - type: cos_sim_pearson
            value: 87.35697089594868
          - type: cos_sim_spearman
            value: 87.78202647220289
          - type: euclidean_pearson
            value: 84.20969668786667
          - type: euclidean_spearman
            value: 83.91876425459982
          - type: manhattan_pearson
            value: 84.24429755612542
          - type: manhattan_spearman
            value: 83.98826315103398
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (en)
          config: en
          split: test
          revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
        metrics:
          - type: cos_sim_pearson
            value: 69.06962775868384
          - type: cos_sim_spearman
            value: 69.34889515492327
          - type: euclidean_pearson
            value: 69.28108180412313
          - type: euclidean_spearman
            value: 69.6437114853659
          - type: manhattan_pearson
            value: 69.39974983734993
          - type: manhattan_spearman
            value: 69.69057284482079
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: 8913289635987208e6e7c72789e4be2fe94b6abd
        metrics:
          - type: cos_sim_pearson
            value: 82.42553734213958
          - type: cos_sim_spearman
            value: 81.38977341532744
          - type: euclidean_pearson
            value: 76.47494587945522
          - type: euclidean_spearman
            value: 75.92794860531089
          - type: manhattan_pearson
            value: 76.4768777169467
          - type: manhattan_spearman
            value: 75.9252673228599
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: 56a6d0140cf6356659e2a7c1413286a774468d44
        metrics:
          - type: map
            value: 80.78825425914722
          - type: mrr
            value: 94.60017197762296
      - task:
          type: Retrieval
        dataset:
          type: scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: a75ae049398addde9b70f6b268875f5cbce99089
        metrics:
          - type: map_at_1
            value: 60.633
          - type: map_at_10
            value: 70.197
          - type: map_at_100
            value: 70.758
          - type: map_at_1000
            value: 70.765
          - type: map_at_3
            value: 67.082
          - type: map_at_5
            value: 69.209
          - type: mrr_at_1
            value: 63.333
          - type: mrr_at_10
            value: 71.17
          - type: mrr_at_100
            value: 71.626
          - type: mrr_at_1000
            value: 71.633
          - type: mrr_at_3
            value: 68.833
          - type: mrr_at_5
            value: 70.6
          - type: ndcg_at_1
            value: 63.333
          - type: ndcg_at_10
            value: 74.697
          - type: ndcg_at_100
            value: 76.986
          - type: ndcg_at_1000
            value: 77.225
          - type: ndcg_at_3
            value: 69.527
          - type: ndcg_at_5
            value: 72.816
          - type: precision_at_1
            value: 63.333
          - type: precision_at_10
            value: 9.9
          - type: precision_at_100
            value: 1.103
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 26.889000000000003
          - type: precision_at_5
            value: 18.2
          - type: recall_at_1
            value: 60.633
          - type: recall_at_10
            value: 87.36699999999999
          - type: recall_at_100
            value: 97.333
          - type: recall_at_1000
            value: 99.333
          - type: recall_at_3
            value: 73.656
          - type: recall_at_5
            value: 82.083
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
        metrics:
          - type: cos_sim_accuracy
            value: 99.76633663366337
          - type: cos_sim_ap
            value: 93.84024096781063
          - type: cos_sim_f1
            value: 88.08080808080808
          - type: cos_sim_precision
            value: 88.9795918367347
          - type: cos_sim_recall
            value: 87.2
          - type: dot_accuracy
            value: 99.46336633663367
          - type: dot_ap
            value: 75.78127156965245
          - type: dot_f1
            value: 71.41403865717193
          - type: dot_precision
            value: 72.67080745341616
          - type: dot_recall
            value: 70.19999999999999
          - type: euclidean_accuracy
            value: 99.67524752475248
          - type: euclidean_ap
            value: 88.61274955249769
          - type: euclidean_f1
            value: 82.30852211434735
          - type: euclidean_precision
            value: 89.34426229508196
          - type: euclidean_recall
            value: 76.3
          - type: manhattan_accuracy
            value: 99.67722772277227
          - type: manhattan_ap
            value: 88.77516158012779
          - type: manhattan_f1
            value: 82.36536430834212
          - type: manhattan_precision
            value: 87.24832214765101
          - type: manhattan_recall
            value: 78
          - type: max_accuracy
            value: 99.76633663366337
          - type: max_ap
            value: 93.84024096781063
          - type: max_f1
            value: 88.08080808080808
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
        metrics:
          - type: v_measure
            value: 59.20812266121527
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
        metrics:
          - type: v_measure
            value: 33.954248554638056
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
        metrics:
          - type: map
            value: 51.52800990025549
          - type: mrr
            value: 52.360394915541974
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
        metrics:
          - type: cos_sim_pearson
            value: 24.57438758817976
          - type: cos_sim_spearman
            value: 24.747448399760643
          - type: dot_pearson
            value: 26.589017584184987
          - type: dot_spearman
            value: 25.653620812462783
      - task:
          type: Retrieval
        dataset:
          type: trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
        metrics:
          - type: map_at_1
            value: 0.253
          - type: map_at_10
            value: 2.1399999999999997
          - type: map_at_100
            value: 12.873000000000001
          - type: map_at_1000
            value: 31.002000000000002
          - type: map_at_3
            value: 0.711
          - type: map_at_5
            value: 1.125
          - type: mrr_at_1
            value: 96
          - type: mrr_at_10
            value: 98
          - type: mrr_at_100
            value: 98
          - type: mrr_at_1000
            value: 98
          - type: mrr_at_3
            value: 98
          - type: mrr_at_5
            value: 98
          - type: ndcg_at_1
            value: 94
          - type: ndcg_at_10
            value: 84.881
          - type: ndcg_at_100
            value: 64.694
          - type: ndcg_at_1000
            value: 56.85
          - type: ndcg_at_3
            value: 90.061
          - type: ndcg_at_5
            value: 87.155
          - type: precision_at_1
            value: 96
          - type: precision_at_10
            value: 88.8
          - type: precision_at_100
            value: 65.7
          - type: precision_at_1000
            value: 25.080000000000002
          - type: precision_at_3
            value: 92.667
          - type: precision_at_5
            value: 90
          - type: recall_at_1
            value: 0.253
          - type: recall_at_10
            value: 2.292
          - type: recall_at_100
            value: 15.78
          - type: recall_at_1000
            value: 53.015
          - type: recall_at_3
            value: 0.7270000000000001
          - type: recall_at_5
            value: 1.162
      - task:
          type: Retrieval
        dataset:
          type: webis-touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
        metrics:
          - type: map_at_1
            value: 2.116
          - type: map_at_10
            value: 9.625
          - type: map_at_100
            value: 15.641
          - type: map_at_1000
            value: 17.127
          - type: map_at_3
            value: 4.316
          - type: map_at_5
            value: 6.208
          - type: mrr_at_1
            value: 32.653
          - type: mrr_at_10
            value: 48.083999999999996
          - type: mrr_at_100
            value: 48.631
          - type: mrr_at_1000
            value: 48.649
          - type: mrr_at_3
            value: 42.857
          - type: mrr_at_5
            value: 46.224
          - type: ndcg_at_1
            value: 29.592000000000002
          - type: ndcg_at_10
            value: 25.430999999999997
          - type: ndcg_at_100
            value: 36.344
          - type: ndcg_at_1000
            value: 47.676
          - type: ndcg_at_3
            value: 26.144000000000002
          - type: ndcg_at_5
            value: 26.304
          - type: precision_at_1
            value: 32.653
          - type: precision_at_10
            value: 24.082
          - type: precision_at_100
            value: 7.714
          - type: precision_at_1000
            value: 1.5310000000000001
          - type: precision_at_3
            value: 26.531
          - type: precision_at_5
            value: 26.939
          - type: recall_at_1
            value: 2.116
          - type: recall_at_10
            value: 16.794
          - type: recall_at_100
            value: 47.452
          - type: recall_at_1000
            value: 82.312
          - type: recall_at_3
            value: 5.306
          - type: recall_at_5
            value: 9.306000000000001
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
        metrics:
          - type: accuracy
            value: 67.709
          - type: ap
            value: 13.541535578501716
          - type: f1
            value: 52.569619919446794
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: 62146448f05be9e52a36b8ee9936447ea787eede
        metrics:
          - type: accuracy
            value: 56.850594227504246
          - type: f1
            value: 57.233377364910574
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
        metrics:
          - type: v_measure
            value: 39.463722986090474
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 84.09131549144662
          - type: cos_sim_ap
            value: 66.86677647503386
          - type: cos_sim_f1
            value: 62.94631710362049
          - type: cos_sim_precision
            value: 59.73933649289099
          - type: cos_sim_recall
            value: 66.51715039577837
          - type: dot_accuracy
            value: 80.27656911247541
          - type: dot_ap
            value: 54.291720398612085
          - type: dot_f1
            value: 54.77150537634409
          - type: dot_precision
            value: 47.58660957571039
          - type: dot_recall
            value: 64.5118733509235
          - type: euclidean_accuracy
            value: 82.76211480002385
          - type: euclidean_ap
            value: 62.430397690753296
          - type: euclidean_f1
            value: 59.191590539356774
          - type: euclidean_precision
            value: 56.296119971435374
          - type: euclidean_recall
            value: 62.401055408970976
          - type: manhattan_accuracy
            value: 82.7561542588067
          - type: manhattan_ap
            value: 62.41882051995577
          - type: manhattan_f1
            value: 59.32101002778785
          - type: manhattan_precision
            value: 54.71361711611321
          - type: manhattan_recall
            value: 64.77572559366754
          - type: max_accuracy
            value: 84.09131549144662
          - type: max_ap
            value: 66.86677647503386
          - type: max_f1
            value: 62.94631710362049
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.79574649745798
          - type: cos_sim_ap
            value: 85.28960532524223
          - type: cos_sim_f1
            value: 77.98460043358001
          - type: cos_sim_precision
            value: 75.78090948714224
          - type: cos_sim_recall
            value: 80.32029565753002
          - type: dot_accuracy
            value: 85.5939767920208
          - type: dot_ap
            value: 76.14131706694056
          - type: dot_f1
            value: 72.70246298696868
          - type: dot_precision
            value: 65.27012127894156
          - type: dot_recall
            value: 82.04496458269172
          - type: euclidean_accuracy
            value: 86.72332828812046
          - type: euclidean_ap
            value: 80.84854809178995
          - type: euclidean_f1
            value: 72.47657499809551
          - type: euclidean_precision
            value: 71.71717171717171
          - type: euclidean_recall
            value: 73.25223283030489
          - type: manhattan_accuracy
            value: 86.7563162184189
          - type: manhattan_ap
            value: 80.87598895575626
          - type: manhattan_f1
            value: 72.54617892068092
          - type: manhattan_precision
            value: 68.49268225960881
          - type: manhattan_recall
            value: 77.10963966738528
          - type: max_accuracy
            value: 88.79574649745798
          - type: max_ap
            value: 85.28960532524223
          - type: max_f1
            value: 77.98460043358001

SGPT-5.8B-weightedmean-msmarco-specb-bitfit

Usage

For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt

Evaluation Results

For eval results, refer to our paper: https://arxiv.org/abs/2202.08904

Training

The model was trained with the parameters:

DataLoader:

torch.utils.data.dataloader.DataLoader of length 249592 with parameters:

{'batch_size': 2, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}

Loss:

sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss with parameters:

{'scale': 20.0, 'similarity_fct': 'cos_sim'}

Parameters of the fit()-Method:

{
    "epochs": 10,
    "evaluation_steps": 0,
    "evaluator": "NoneType",
    "max_grad_norm": 1,
    "optimizer_class": "<class 'transformers.optimization.AdamW'>",
    "optimizer_params": {
        "lr": 5e-05
    },
    "scheduler": "WarmupLinear",
    "steps_per_epoch": null,
    "warmup_steps": 1000,
    "weight_decay": 0.01
}

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTJModel 
  (1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
)

Citing & Authors

@article{muennighoff2022sgpt,
  title={SGPT: GPT Sentence Embeddings for Semantic Search},
  author={Muennighoff, Niklas},
  journal={arXiv preprint arXiv:2202.08904},
  year={2022}
}