Update README.md

README.md

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----
-tags:
-- mteb
-model-index:
-- name: bge_micro
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 66.26865671641792
-    - type: ap
-      value: 28.174006539079688
-    - type: f1
-      value: 59.724963358211035
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 75.3691
-    - type: ap
-      value: 69.64182876373573
-    - type: f1
-      value: 75.2906345000088
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 35.806
-    - type: f1
-      value: 35.506516495961904
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 27.24
-    - type: map_at_10
-      value: 42.832
-    - type: map_at_100
-      value: 43.797000000000004
-    - type: map_at_1000
-      value: 43.804
-    - type: map_at_3
-      value: 38.134
-    - type: map_at_5
-      value: 40.744
-    - type: mrr_at_1
-      value: 27.951999999999998
-    - type: mrr_at_10
-      value: 43.111
-    - type: mrr_at_100
-      value: 44.083
-    - type: mrr_at_1000
-      value: 44.09
-    - type: mrr_at_3
-      value: 38.431
-    - type: mrr_at_5
-      value: 41.019
-    - type: ndcg_at_1
-      value: 27.24
-    - type: ndcg_at_10
-      value: 51.513
-    - type: ndcg_at_100
-      value: 55.762
-    - type: ndcg_at_1000
-      value: 55.938
-    - type: ndcg_at_3
-      value: 41.743
-    - type: ndcg_at_5
-      value: 46.454
-    - type: precision_at_1
-      value: 27.24
-    - type: precision_at_10
-      value: 7.93
-    - type: precision_at_100
-      value: 0.9820000000000001
-    - type: precision_at_1000
-      value: 0.1
-    - type: precision_at_3
-      value: 17.402
-    - type: precision_at_5
-      value: 12.731
-    - type: recall_at_1
-      value: 27.24
-    - type: recall_at_10
-      value: 79.303
-    - type: recall_at_100
-      value: 98.151
-    - type: recall_at_1000
-      value: 99.502
-    - type: recall_at_3
-      value: 52.205
-    - type: recall_at_5
-      value: 63.656
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 44.59766397469585
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 34.480143023109626
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 58.09326229984527
-    - type: mrr
-      value: 72.18429846546191
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 85.47582391622187
-    - type: cos_sim_spearman
-      value: 83.41635852964214
-    - type: euclidean_pearson
-      value: 84.21969728559216
-    - type: euclidean_spearman
-      value: 83.46575724558684
-    - type: manhattan_pearson
-      value: 83.83107014910223
-    - type: manhattan_spearman
-      value: 83.13321954800792
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 80.58116883116882
-    - type: f1
-      value: 80.53335622619781
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 37.13458676004344
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 29.720429607514898
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.051000000000002
-    - type: map_at_10
-      value: 36.291000000000004
-    - type: map_at_100
-      value: 37.632
-    - type: map_at_1000
-      value: 37.772
-    - type: map_at_3
-      value: 33.288000000000004
-    - type: map_at_5
-      value: 35.035
-    - type: mrr_at_1
-      value: 33.333
-    - type: mrr_at_10
-      value: 42.642
-    - type: mrr_at_100
-      value: 43.401
-    - type: mrr_at_1000
-      value: 43.463
-    - type: mrr_at_3
-      value: 40.272000000000006
-    - type: mrr_at_5
-      value: 41.753
-    - type: ndcg_at_1
-      value: 33.333
-    - type: ndcg_at_10
-      value: 42.291000000000004
-    - type: ndcg_at_100
-      value: 47.602
-    - type: ndcg_at_1000
-      value: 50.109
-    - type: ndcg_at_3
-      value: 38.033
-    - type: ndcg_at_5
-      value: 40.052
-    - type: precision_at_1
-      value: 33.333
-    - type: precision_at_10
-      value: 8.254999999999999
-    - type: precision_at_100
-      value: 1.353
-    - type: precision_at_1000
-      value: 0.185
-    - type: precision_at_3
-      value: 18.884
-    - type: precision_at_5
-      value: 13.447999999999999
-    - type: recall_at_1
-      value: 26.051000000000002
-    - type: recall_at_10
-      value: 53.107000000000006
-    - type: recall_at_100
-      value: 76.22
-    - type: recall_at_1000
-      value: 92.92399999999999
-    - type: recall_at_3
-      value: 40.073
-    - type: recall_at_5
-      value: 46.327
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.698999999999998
-    - type: map_at_10
-      value: 26.186
-    - type: map_at_100
-      value: 27.133000000000003
-    - type: map_at_1000
-      value: 27.256999999999998
-    - type: map_at_3
-      value: 24.264
-    - type: map_at_5
-      value: 25.307000000000002
-    - type: mrr_at_1
-      value: 24.712999999999997
-    - type: mrr_at_10
-      value: 30.703999999999997
-    - type: mrr_at_100
-      value: 31.445
-    - type: mrr_at_1000
-      value: 31.517
-    - type: mrr_at_3
-      value: 28.992
-    - type: mrr_at_5
-      value: 29.963
-    - type: ndcg_at_1
-      value: 24.712999999999997
-    - type: ndcg_at_10
-      value: 30.198000000000004
-    - type: ndcg_at_100
-      value: 34.412
-    - type: ndcg_at_1000
-      value: 37.174
-    - type: ndcg_at_3
-      value: 27.148
-    - type: ndcg_at_5
-      value: 28.464
-    - type: precision_at_1
-      value: 24.712999999999997
-    - type: precision_at_10
-      value: 5.489999999999999
-    - type: precision_at_100
-      value: 0.955
-    - type: precision_at_1000
-      value: 0.14400000000000002
-    - type: precision_at_3
-      value: 12.803
-    - type: precision_at_5
-      value: 8.981
-    - type: recall_at_1
-      value: 19.698999999999998
-    - type: recall_at_10
-      value: 37.595
-    - type: recall_at_100
-      value: 55.962
-    - type: recall_at_1000
-      value: 74.836
-    - type: recall_at_3
-      value: 28.538999999999998
-    - type: recall_at_5
-      value: 32.279
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 34.224
-    - type: map_at_10
-      value: 44.867000000000004
-    - type: map_at_100
-      value: 45.944
-    - type: map_at_1000
-      value: 46.013999999999996
-    - type: map_at_3
-      value: 42.009
-    - type: map_at_5
-      value: 43.684
-    - type: mrr_at_1
-      value: 39.436
-    - type: mrr_at_10
-      value: 48.301
-    - type: mrr_at_100
-      value: 49.055
-    - type: mrr_at_1000
-      value: 49.099
-    - type: mrr_at_3
-      value: 45.956
-    - type: mrr_at_5
-      value: 47.445
-    - type: ndcg_at_1
-      value: 39.436
-    - type: ndcg_at_10
-      value: 50.214000000000006
-    - type: ndcg_at_100
-      value: 54.63
-    - type: ndcg_at_1000
-      value: 56.165
-    - type: ndcg_at_3
-      value: 45.272
-    - type: ndcg_at_5
-      value: 47.826
-    - type: precision_at_1
-      value: 39.436
-    - type: precision_at_10
-      value: 8.037999999999998
-    - type: precision_at_100
-      value: 1.118
-    - type: precision_at_1000
-      value: 0.13
-    - type: precision_at_3
-      value: 20.125
-    - type: precision_at_5
-      value: 13.918
-    - type: recall_at_1
-      value: 34.224
-    - type: recall_at_10
-      value: 62.690999999999995
-    - type: recall_at_100
-      value: 81.951
-    - type: recall_at_1000
-      value: 92.93299999999999
-    - type: recall_at_3
-      value: 49.299
-    - type: recall_at_5
-      value: 55.533
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.375
-    - type: map_at_10
-      value: 28.366000000000003
-    - type: map_at_100
-      value: 29.363
-    - type: map_at_1000
-      value: 29.458000000000002
-    - type: map_at_3
-      value: 26.247
-    - type: map_at_5
-      value: 27.439000000000004
-    - type: mrr_at_1
-      value: 22.938
-    - type: mrr_at_10
-      value: 30.072
-    - type: mrr_at_100
-      value: 30.993
-    - type: mrr_at_1000
-      value: 31.070999999999998
-    - type: mrr_at_3
-      value: 28.004
-    - type: mrr_at_5
-      value: 29.179
-    - type: ndcg_at_1
-      value: 22.938
-    - type: ndcg_at_10
-      value: 32.516
-    - type: ndcg_at_100
-      value: 37.641999999999996
-    - type: ndcg_at_1000
-      value: 40.150999999999996
-    - type: ndcg_at_3
-      value: 28.341
-    - type: ndcg_at_5
-      value: 30.394
-    - type: precision_at_1
-      value: 22.938
-    - type: precision_at_10
-      value: 5.028
-    - type: precision_at_100
-      value: 0.8
-    - type: precision_at_1000
-      value: 0.105
-    - type: precision_at_3
-      value: 12.052999999999999
-    - type: precision_at_5
-      value: 8.497
-    - type: recall_at_1
-      value: 21.375
-    - type: recall_at_10
-      value: 43.682
-    - type: recall_at_100
-      value: 67.619
-    - type: recall_at_1000
-      value: 86.64699999999999
-    - type: recall_at_3
-      value: 32.478
-    - type: recall_at_5
-      value: 37.347
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 14.95
-    - type: map_at_10
-      value: 21.417
-    - type: map_at_100
-      value: 22.525000000000002
-    - type: map_at_1000
-      value: 22.665
-    - type: map_at_3
-      value: 18.684
-    - type: map_at_5
-      value: 20.275000000000002
-    - type: mrr_at_1
-      value: 18.159
-    - type: mrr_at_10
-      value: 25.373
-    - type: mrr_at_100
-      value: 26.348
-    - type: mrr_at_1000
-      value: 26.432
-    - type: mrr_at_3
-      value: 22.698999999999998
-    - type: mrr_at_5
-      value: 24.254
-    - type: ndcg_at_1
-      value: 18.159
-    - type: ndcg_at_10
-      value: 26.043
-    - type: ndcg_at_100
-      value: 31.491999999999997
-    - type: ndcg_at_1000
-      value: 34.818
-    - type: ndcg_at_3
-      value: 21.05
-    - type: ndcg_at_5
-      value: 23.580000000000002
-    - type: precision_at_1
-      value: 18.159
-    - type: precision_at_10
-      value: 4.938
-    - type: precision_at_100
-      value: 0.872
-    - type: precision_at_1000
-      value: 0.129
-    - type: precision_at_3
-      value: 9.908999999999999
-    - type: precision_at_5
-      value: 7.611999999999999
-    - type: recall_at_1
-      value: 14.95
-    - type: recall_at_10
-      value: 36.285000000000004
-    - type: recall_at_100
-      value: 60.431999999999995
-    - type: recall_at_1000
-      value: 84.208
-    - type: recall_at_3
-      value: 23.006
-    - type: recall_at_5
-      value: 29.304999999999996
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 23.580000000000002
-    - type: map_at_10
-      value: 32.906
-    - type: map_at_100
-      value: 34.222
-    - type: map_at_1000
-      value: 34.346
-    - type: map_at_3
-      value: 29.891000000000002
-    - type: map_at_5
-      value: 31.679000000000002
-    - type: mrr_at_1
-      value: 28.778
-    - type: mrr_at_10
-      value: 37.783
-    - type: mrr_at_100
-      value: 38.746
-    - type: mrr_at_1000
-      value: 38.804
-    - type: mrr_at_3
-      value: 35.098
-    - type: mrr_at_5
-      value: 36.739
-    - type: ndcg_at_1
-      value: 28.778
-    - type: ndcg_at_10
-      value: 38.484
-    - type: ndcg_at_100
-      value: 44.322
-    - type: ndcg_at_1000
-      value: 46.772000000000006
-    - type: ndcg_at_3
-      value: 33.586
-    - type: ndcg_at_5
-      value: 36.098
-    - type: precision_at_1
-      value: 28.778
-    - type: precision_at_10
-      value: 7.151000000000001
-    - type: precision_at_100
-      value: 1.185
-    - type: precision_at_1000
-      value: 0.158
-    - type: precision_at_3
-      value: 16.105
-    - type: precision_at_5
-      value: 11.704
-    - type: recall_at_1
-      value: 23.580000000000002
-    - type: recall_at_10
-      value: 50.151999999999994
-    - type: recall_at_100
-      value: 75.114
-    - type: recall_at_1000
-      value: 91.467
-    - type: recall_at_3
-      value: 36.552
-    - type: recall_at_5
-      value: 43.014
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 20.669999999999998
-    - type: map_at_10
-      value: 28.687
-    - type: map_at_100
-      value: 30.061
-    - type: map_at_1000
-      value: 30.197000000000003
-    - type: map_at_3
-      value: 26.134
-    - type: map_at_5
-      value: 27.508
-    - type: mrr_at_1
-      value: 26.256
-    - type: mrr_at_10
-      value: 34.105999999999995
-    - type: mrr_at_100
-      value: 35.137
-    - type: mrr_at_1000
-      value: 35.214
-    - type: mrr_at_3
-      value: 31.791999999999998
-    - type: mrr_at_5
-      value: 33.145
-    - type: ndcg_at_1
-      value: 26.256
-    - type: ndcg_at_10
-      value: 33.68
-    - type: ndcg_at_100
-      value: 39.7
-    - type: ndcg_at_1000
-      value: 42.625
-    - type: ndcg_at_3
-      value: 29.457
-    - type: ndcg_at_5
-      value: 31.355
-    - type: precision_at_1
-      value: 26.256
-    - type: precision_at_10
-      value: 6.2330000000000005
-    - type: precision_at_100
-      value: 1.08
-    - type: precision_at_1000
-      value: 0.149
-    - type: precision_at_3
-      value: 14.193
-    - type: precision_at_5
-      value: 10.113999999999999
-    - type: recall_at_1
-      value: 20.669999999999998
-    - type: recall_at_10
-      value: 43.254999999999995
-    - type: recall_at_100
-      value: 69.118
-    - type: recall_at_1000
-      value: 89.408
-    - type: recall_at_3
-      value: 31.135
-    - type: recall_at_5
-      value: 36.574
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.488833333333336
-    - type: map_at_10
-      value: 29.025416666666665
-    - type: map_at_100
-      value: 30.141249999999992
-    - type: map_at_1000
-      value: 30.264083333333335
-    - type: map_at_3
-      value: 26.599333333333337
-    - type: map_at_5
-      value: 28.004666666666665
-    - type: mrr_at_1
-      value: 25.515
-    - type: mrr_at_10
-      value: 32.8235
-    - type: mrr_at_100
-      value: 33.69958333333333
-    - type: mrr_at_1000
-      value: 33.77191666666668
-    - type: mrr_at_3
-      value: 30.581000000000003
-    - type: mrr_at_5
-      value: 31.919666666666668
-    - type: ndcg_at_1
-      value: 25.515
-    - type: ndcg_at_10
-      value: 33.64241666666666
-    - type: ndcg_at_100
-      value: 38.75816666666667
-    - type: ndcg_at_1000
-      value: 41.472166666666666
-    - type: ndcg_at_3
-      value: 29.435083333333335
-    - type: ndcg_at_5
-      value: 31.519083333333338
-    - type: precision_at_1
-      value: 25.515
-    - type: precision_at_10
-      value: 5.89725
-    - type: precision_at_100
-      value: 0.9918333333333335
-    - type: precision_at_1000
-      value: 0.14075
-    - type: precision_at_3
-      value: 13.504000000000001
-    - type: precision_at_5
-      value: 9.6885
-    - type: recall_at_1
-      value: 21.488833333333336
-    - type: recall_at_10
-      value: 43.60808333333333
-    - type: recall_at_100
-      value: 66.5045
-    - type: recall_at_1000
-      value: 85.70024999999998
-    - type: recall_at_3
-      value: 31.922166666666662
-    - type: recall_at_5
-      value: 37.29758333333334
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 20.781
-    - type: map_at_10
-      value: 27.173000000000002
-    - type: map_at_100
-      value: 27.967
-    - type: map_at_1000
-      value: 28.061999999999998
-    - type: map_at_3
-      value: 24.973
-    - type: map_at_5
-      value: 26.279999999999998
-    - type: mrr_at_1
-      value: 23.773
-    - type: mrr_at_10
-      value: 29.849999999999998
-    - type: mrr_at_100
-      value: 30.595
-    - type: mrr_at_1000
-      value: 30.669
-    - type: mrr_at_3
-      value: 27.761000000000003
-    - type: mrr_at_5
-      value: 29.003
-    - type: ndcg_at_1
-      value: 23.773
-    - type: ndcg_at_10
-      value: 31.033
-    - type: ndcg_at_100
-      value: 35.174
-    - type: ndcg_at_1000
-      value: 37.72
-    - type: ndcg_at_3
-      value: 26.927
-    - type: ndcg_at_5
-      value: 29.047
-    - type: precision_at_1
-      value: 23.773
-    - type: precision_at_10
-      value: 4.8469999999999995
-    - type: precision_at_100
-      value: 0.75
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 11.452
-    - type: precision_at_5
-      value: 8.129
-    - type: recall_at_1
-      value: 20.781
-    - type: recall_at_10
-      value: 40.463
-    - type: recall_at_100
-      value: 59.483
-    - type: recall_at_1000
-      value: 78.396
-    - type: recall_at_3
-      value: 29.241
-    - type: recall_at_5
-      value: 34.544000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 15.074000000000002
-    - type: map_at_10
-      value: 20.757
-    - type: map_at_100
-      value: 21.72
-    - type: map_at_1000
-      value: 21.844
-    - type: map_at_3
-      value: 18.929000000000002
-    - type: map_at_5
-      value: 19.894000000000002
-    - type: mrr_at_1
-      value: 18.307000000000002
-    - type: mrr_at_10
-      value: 24.215
-    - type: mrr_at_100
-      value: 25.083
-    - type: mrr_at_1000
-      value: 25.168000000000003
-    - type: mrr_at_3
-      value: 22.316
-    - type: mrr_at_5
-      value: 23.36
-    - type: ndcg_at_1
-      value: 18.307000000000002
-    - type: ndcg_at_10
-      value: 24.651999999999997
-    - type: ndcg_at_100
-      value: 29.296
-    - type: ndcg_at_1000
-      value: 32.538
-    - type: ndcg_at_3
-      value: 21.243000000000002
-    - type: ndcg_at_5
-      value: 22.727
-    - type: precision_at_1
-      value: 18.307000000000002
-    - type: precision_at_10
-      value: 4.446
-    - type: precision_at_100
-      value: 0.792
-    - type: precision_at_1000
-      value: 0.124
-    - type: precision_at_3
-      value: 9.945
-    - type: precision_at_5
-      value: 7.123
-    - type: recall_at_1
-      value: 15.074000000000002
-    - type: recall_at_10
-      value: 33.031
-    - type: recall_at_100
-      value: 53.954
-    - type: recall_at_1000
-      value: 77.631
-    - type: recall_at_3
-      value: 23.253
-    - type: recall_at_5
-      value: 27.218999999999998
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.04
-    - type: map_at_10
-      value: 28.226000000000003
-    - type: map_at_100
-      value: 29.337999999999997
-    - type: map_at_1000
-      value: 29.448999999999998
-    - type: map_at_3
-      value: 25.759
-    - type: map_at_5
-      value: 27.226
-    - type: mrr_at_1
-      value: 24.067
-    - type: mrr_at_10
-      value: 31.646
-    - type: mrr_at_100
-      value: 32.592999999999996
-    - type: mrr_at_1000
-      value: 32.668
-    - type: mrr_at_3
-      value: 29.26
-    - type: mrr_at_5
-      value: 30.725
-    - type: ndcg_at_1
-      value: 24.067
-    - type: ndcg_at_10
-      value: 32.789
-    - type: ndcg_at_100
-      value: 38.253
-    - type: ndcg_at_1000
-      value: 40.961
-    - type: ndcg_at_3
-      value: 28.189999999999998
-    - type: ndcg_at_5
-      value: 30.557000000000002
-    - type: precision_at_1
-      value: 24.067
-    - type: precision_at_10
-      value: 5.532
-    - type: precision_at_100
-      value: 0.928
-    - type: precision_at_1000
-      value: 0.128
-    - type: precision_at_3
-      value: 12.5
-    - type: precision_at_5
-      value: 9.16
-    - type: recall_at_1
-      value: 21.04
-    - type: recall_at_10
-      value: 43.167
-    - type: recall_at_100
-      value: 67.569
-    - type: recall_at_1000
-      value: 86.817
-    - type: recall_at_3
-      value: 31.178
-    - type: recall_at_5
-      value: 36.730000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.439
-    - type: map_at_10
-      value: 28.531000000000002
-    - type: map_at_100
-      value: 29.953999999999997
-    - type: map_at_1000
-      value: 30.171
-    - type: map_at_3
-      value: 26.546999999999997
-    - type: map_at_5
-      value: 27.71
-    - type: mrr_at_1
-      value: 26.087
-    - type: mrr_at_10
-      value: 32.635
-    - type: mrr_at_100
-      value: 33.629999999999995
-    - type: mrr_at_1000
-      value: 33.71
-    - type: mrr_at_3
-      value: 30.731
-    - type: mrr_at_5
-      value: 31.807999999999996
-    - type: ndcg_at_1
-      value: 26.087
-    - type: ndcg_at_10
-      value: 32.975
-    - type: ndcg_at_100
-      value: 38.853
-    - type: ndcg_at_1000
-      value: 42.158
-    - type: ndcg_at_3
-      value: 29.894
-    - type: ndcg_at_5
-      value: 31.397000000000002
-    - type: precision_at_1
-      value: 26.087
-    - type: precision_at_10
-      value: 6.2059999999999995
-    - type: precision_at_100
-      value: 1.298
-    - type: precision_at_1000
-      value: 0.22200000000000003
-    - type: precision_at_3
-      value: 14.097000000000001
-    - type: precision_at_5
-      value: 9.959999999999999
-    - type: recall_at_1
-      value: 21.439
-    - type: recall_at_10
-      value: 40.519
-    - type: recall_at_100
-      value: 68.073
-    - type: recall_at_1000
-      value: 89.513
-    - type: recall_at_3
-      value: 31.513
-    - type: recall_at_5
-      value: 35.702
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 18.983
-    - type: map_at_10
-      value: 24.898
-    - type: map_at_100
-      value: 25.836
-    - type: map_at_1000
-      value: 25.934
-    - type: map_at_3
-      value: 22.467000000000002
-    - type: map_at_5
-      value: 24.019
-    - type: mrr_at_1
-      value: 20.333000000000002
-    - type: mrr_at_10
-      value: 26.555
-    - type: mrr_at_100
-      value: 27.369
-    - type: mrr_at_1000
-      value: 27.448
-    - type: mrr_at_3
-      value: 24.091
-    - type: mrr_at_5
-      value: 25.662000000000003
-    - type: ndcg_at_1
-      value: 20.333000000000002
-    - type: ndcg_at_10
-      value: 28.834
-    - type: ndcg_at_100
-      value: 33.722
-    - type: ndcg_at_1000
-      value: 36.475
-    - type: ndcg_at_3
-      value: 24.08
-    - type: ndcg_at_5
-      value: 26.732
-    - type: precision_at_1
-      value: 20.333000000000002
-    - type: precision_at_10
-      value: 4.603
-    - type: precision_at_100
-      value: 0.771
-    - type: precision_at_1000
-      value: 0.11100000000000002
-    - type: precision_at_3
-      value: 9.982000000000001
-    - type: precision_at_5
-      value: 7.6160000000000005
-    - type: recall_at_1
-      value: 18.983
-    - type: recall_at_10
-      value: 39.35
-    - type: recall_at_100
-      value: 62.559
-    - type: recall_at_1000
-      value: 83.623
-    - type: recall_at_3
-      value: 26.799
-    - type: recall_at_5
-      value: 32.997
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 10.621
-    - type: map_at_10
-      value: 17.298
-    - type: map_at_100
-      value: 18.983
-    - type: map_at_1000
-      value: 19.182
-    - type: map_at_3
-      value: 14.552999999999999
-    - type: map_at_5
-      value: 15.912
-    - type: mrr_at_1
-      value: 23.453
-    - type: mrr_at_10
-      value: 33.932
-    - type: mrr_at_100
-      value: 34.891
-    - type: mrr_at_1000
-      value: 34.943000000000005
-    - type: mrr_at_3
-      value: 30.770999999999997
-    - type: mrr_at_5
-      value: 32.556000000000004
-    - type: ndcg_at_1
-      value: 23.453
-    - type: ndcg_at_10
-      value: 24.771
-    - type: ndcg_at_100
-      value: 31.738
-    - type: ndcg_at_1000
-      value: 35.419
-    - type: ndcg_at_3
-      value: 20.22
-    - type: ndcg_at_5
-      value: 21.698999999999998
-    - type: precision_at_1
-      value: 23.453
-    - type: precision_at_10
-      value: 7.785
-    - type: precision_at_100
-      value: 1.5270000000000001
-    - type: precision_at_1000
-      value: 0.22
-    - type: precision_at_3
-      value: 14.962
-    - type: precision_at_5
-      value: 11.401
-    - type: recall_at_1
-      value: 10.621
-    - type: recall_at_10
-      value: 29.726000000000003
-    - type: recall_at_100
-      value: 53.996
-    - type: recall_at_1000
-      value: 74.878
-    - type: recall_at_3
-      value: 18.572
-    - type: recall_at_5
-      value: 22.994999999999997
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 6.819
-    - type: map_at_10
-      value: 14.188
-    - type: map_at_100
-      value: 19.627
-    - type: map_at_1000
-      value: 20.757
-    - type: map_at_3
-      value: 10.352
-    - type: map_at_5
-      value: 12.096
-    - type: mrr_at_1
-      value: 54.25
-    - type: mrr_at_10
-      value: 63.798
-    - type: mrr_at_100
-      value: 64.25
-    - type: mrr_at_1000
-      value: 64.268
-    - type: mrr_at_3
-      value: 61.667
-    - type: mrr_at_5
-      value: 63.153999999999996
-    - type: ndcg_at_1
-      value: 39.5
-    - type: ndcg_at_10
-      value: 31.064999999999998
-    - type: ndcg_at_100
-      value: 34.701
-    - type: ndcg_at_1000
-      value: 41.687000000000005
-    - type: ndcg_at_3
-      value: 34.455999999999996
-    - type: ndcg_at_5
-      value: 32.919
-    - type: precision_at_1
-      value: 54.25
-    - type: precision_at_10
-      value: 25.4
-    - type: precision_at_100
-      value: 7.79
-    - type: precision_at_1000
-      value: 1.577
-    - type: precision_at_3
-      value: 39.333
-    - type: precision_at_5
-      value: 33.6
-    - type: recall_at_1
-      value: 6.819
-    - type: recall_at_10
-      value: 19.134
-    - type: recall_at_100
-      value: 41.191
-    - type: recall_at_1000
-      value: 64.699
-    - type: recall_at_3
-      value: 11.637
-    - type: recall_at_5
-      value: 14.807
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 42.474999999999994
-    - type: f1
-      value: 37.79154895614037
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 53.187
-    - type: map_at_10
-      value: 64.031
-    - type: map_at_100
-      value: 64.507
-    - type: map_at_1000
-      value: 64.526
-    - type: map_at_3
-      value: 61.926
-    - type: map_at_5
-      value: 63.278999999999996
-    - type: mrr_at_1
-      value: 57.396
-    - type: mrr_at_10
-      value: 68.296
-    - type: mrr_at_100
-      value: 68.679
-    - type: mrr_at_1000
-      value: 68.688
-    - type: mrr_at_3
-      value: 66.289
-    - type: mrr_at_5
-      value: 67.593
-    - type: ndcg_at_1
-      value: 57.396
-    - type: ndcg_at_10
-      value: 69.64
-    - type: ndcg_at_100
-      value: 71.75399999999999
-    - type: ndcg_at_1000
-      value: 72.179
-    - type: ndcg_at_3
-      value: 65.66199999999999
-    - type: ndcg_at_5
-      value: 67.932
-    - type: precision_at_1
-      value: 57.396
-    - type: precision_at_10
-      value: 9.073
-    - type: precision_at_100
-      value: 1.024
-    - type: precision_at_1000
-      value: 0.107
-    - type: precision_at_3
-      value: 26.133
-    - type: precision_at_5
-      value: 16.943
-    - type: recall_at_1
-      value: 53.187
-    - type: recall_at_10
-      value: 82.839
-    - type: recall_at_100
-      value: 92.231
-    - type: recall_at_1000
-      value: 95.249
-    - type: recall_at_3
-      value: 72.077
-    - type: recall_at_5
-      value: 77.667
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 10.957
-    - type: map_at_10
-      value: 18.427
-    - type: map_at_100
-      value: 19.885
-    - type: map_at_1000
-      value: 20.088
-    - type: map_at_3
-      value: 15.709000000000001
-    - type: map_at_5
-      value: 17.153
-    - type: mrr_at_1
-      value: 22.377
-    - type: mrr_at_10
-      value: 30.076999999999998
-    - type: mrr_at_100
-      value: 31.233
-    - type: mrr_at_1000
-      value: 31.311
-    - type: mrr_at_3
-      value: 27.521
-    - type: mrr_at_5
-      value: 29.025000000000002
-    - type: ndcg_at_1
-      value: 22.377
-    - type: ndcg_at_10
-      value: 24.367
-    - type: ndcg_at_100
-      value: 31.04
-    - type: ndcg_at_1000
-      value: 35.106
-    - type: ndcg_at_3
-      value: 21.051000000000002
-    - type: ndcg_at_5
-      value: 22.231
-    - type: precision_at_1
-      value: 22.377
-    - type: precision_at_10
-      value: 7.005999999999999
-    - type: precision_at_100
-      value: 1.3599999999999999
-    - type: precision_at_1000
-      value: 0.208
-    - type: precision_at_3
-      value: 13.991999999999999
-    - type: precision_at_5
-      value: 10.833
-    - type: recall_at_1
-      value: 10.957
-    - type: recall_at_10
-      value: 30.274
-    - type: recall_at_100
-      value: 55.982
-    - type: recall_at_1000
-      value: 80.757
-    - type: recall_at_3
-      value: 19.55
-    - type: recall_at_5
-      value: 24.105999999999998
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.526999999999997
-    - type: map_at_10
-      value: 40.714
-    - type: map_at_100
-      value: 41.655
-    - type: map_at_1000
-      value: 41.744
-    - type: map_at_3
-      value: 38.171
-    - type: map_at_5
-      value: 39.646
-    - type: mrr_at_1
-      value: 59.055
-    - type: mrr_at_10
-      value: 66.411
-    - type: mrr_at_100
-      value: 66.85900000000001
-    - type: mrr_at_1000
-      value: 66.88300000000001
-    - type: mrr_at_3
-      value: 64.846
-    - type: mrr_at_5
-      value: 65.824
-    - type: ndcg_at_1
-      value: 59.055
-    - type: ndcg_at_10
-      value: 49.732
-    - type: ndcg_at_100
-      value: 53.441
-    - type: ndcg_at_1000
-      value: 55.354000000000006
-    - type: ndcg_at_3
-      value: 45.551
-    - type: ndcg_at_5
-      value: 47.719
-    - type: precision_at_1
-      value: 59.055
-    - type: precision_at_10
-      value: 10.366
-    - type: precision_at_100
-      value: 1.328
-    - type: precision_at_1000
-      value: 0.158
-    - type: precision_at_3
-      value: 28.322999999999997
-    - type: precision_at_5
-      value: 18.709
-    - type: recall_at_1
-      value: 29.526999999999997
-    - type: recall_at_10
-      value: 51.83
-    - type: recall_at_100
-      value: 66.42099999999999
-    - type: recall_at_1000
-      value: 79.176
-    - type: recall_at_3
-      value: 42.485
-    - type: recall_at_5
-      value: 46.772000000000006
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 70.69959999999999
-    - type: ap
-      value: 64.95539314492567
-    - type: f1
-      value: 70.5554935943308
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 13.153
-    - type: map_at_10
-      value: 22.277
-    - type: map_at_100
-      value: 23.462
-    - type: map_at_1000
-      value: 23.546
-    - type: map_at_3
-      value: 19.026
-    - type: map_at_5
-      value: 20.825
-    - type: mrr_at_1
-      value: 13.539000000000001
-    - type: mrr_at_10
-      value: 22.753
-    - type: mrr_at_100
-      value: 23.906
-    - type: mrr_at_1000
-      value: 23.982999999999997
-    - type: mrr_at_3
-      value: 19.484
-    - type: mrr_at_5
-      value: 21.306
-    - type: ndcg_at_1
-      value: 13.553
-    - type: ndcg_at_10
-      value: 27.848
-    - type: ndcg_at_100
-      value: 33.900999999999996
-    - type: ndcg_at_1000
-      value: 36.155
-    - type: ndcg_at_3
-      value: 21.116
-    - type: ndcg_at_5
-      value: 24.349999999999998
-    - type: precision_at_1
-      value: 13.553
-    - type: precision_at_10
-      value: 4.695
-    - type: precision_at_100
-      value: 0.7779999999999999
-    - type: precision_at_1000
-      value: 0.097
-    - type: precision_at_3
-      value: 9.207
-    - type: precision_at_5
-      value: 7.155
-    - type: recall_at_1
-      value: 13.153
-    - type: recall_at_10
-      value: 45.205
-    - type: recall_at_100
-      value: 73.978
-    - type: recall_at_1000
-      value: 91.541
-    - type: recall_at_3
-      value: 26.735
-    - type: recall_at_5
-      value: 34.493
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 90.2530779753762
-    - type: f1
-      value: 89.59402328284126
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 67.95029639762883
-    - type: f1
-      value: 48.99988836758662
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 67.77740416946874
-    - type: f1
-      value: 66.21341120969817
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 73.03631472763955
-    - type: f1
-      value: 72.5779336237941
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 31.98182669158824
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 29.259462874407582
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 31.29342377286548
-    - type: mrr
-      value: 32.32805799117226
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 4.692
-    - type: map_at_10
-      value: 10.559000000000001
-    - type: map_at_100
-      value: 13.665
-    - type: map_at_1000
-      value: 15.082
-    - type: map_at_3
-      value: 7.68
-    - type: map_at_5
-      value: 8.844000000000001
-    - type: mrr_at_1
-      value: 38.7
-    - type: mrr_at_10
-      value: 47.864000000000004
-    - type: mrr_at_100
-      value: 48.583999999999996
-    - type: mrr_at_1000
-      value: 48.636
-    - type: mrr_at_3
-      value: 45.975
-    - type: mrr_at_5
-      value: 47.074
-    - type: ndcg_at_1
-      value: 36.378
-    - type: ndcg_at_10
-      value: 30.038999999999998
-    - type: ndcg_at_100
-      value: 28.226000000000003
-    - type: ndcg_at_1000
-      value: 36.958
-    - type: ndcg_at_3
-      value: 33.469
-    - type: ndcg_at_5
-      value: 32.096999999999994
-    - type: precision_at_1
-      value: 38.080000000000005
-    - type: precision_at_10
-      value: 22.941
-    - type: precision_at_100
-      value: 7.632
-    - type: precision_at_1000
-      value: 2.0420000000000003
-    - type: precision_at_3
-      value: 31.579
-    - type: precision_at_5
-      value: 28.235
-    - type: recall_at_1
-      value: 4.692
-    - type: recall_at_10
-      value: 14.496
-    - type: recall_at_100
-      value: 29.69
-    - type: recall_at_1000
-      value: 61.229
-    - type: recall_at_3
-      value: 8.871
-    - type: recall_at_5
-      value: 10.825999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 13.120000000000001
-    - type: map_at_10
-      value: 24.092
-    - type: map_at_100
-      value: 25.485999999999997
-    - type: map_at_1000
-      value: 25.557999999999996
-    - type: map_at_3
-      value: 20.076
-    - type: map_at_5
-      value: 22.368
-    - type: mrr_at_1
-      value: 15.093
-    - type: mrr_at_10
-      value: 26.142
-    - type: mrr_at_100
-      value: 27.301
-    - type: mrr_at_1000
-      value: 27.357
-    - type: mrr_at_3
-      value: 22.364
-    - type: mrr_at_5
-      value: 24.564
-    - type: ndcg_at_1
-      value: 15.093
-    - type: ndcg_at_10
-      value: 30.734
-    - type: ndcg_at_100
-      value: 37.147999999999996
-    - type: ndcg_at_1000
-      value: 38.997
-    - type: ndcg_at_3
-      value: 22.82
-    - type: ndcg_at_5
-      value: 26.806
-    - type: precision_at_1
-      value: 15.093
-    - type: precision_at_10
-      value: 5.863
-    - type: precision_at_100
-      value: 0.942
-    - type: precision_at_1000
-      value: 0.11199999999999999
-    - type: precision_at_3
-      value: 11.047
-    - type: precision_at_5
-      value: 8.863999999999999
-    - type: recall_at_1
-      value: 13.120000000000001
-    - type: recall_at_10
-      value: 49.189
-    - type: recall_at_100
-      value: 78.032
-    - type: recall_at_1000
-      value: 92.034
-    - type: recall_at_3
-      value: 28.483000000000004
-    - type: recall_at_5
-      value: 37.756
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 67.765
-    - type: map_at_10
-      value: 81.069
-    - type: map_at_100
-      value: 81.757
-    - type: map_at_1000
-      value: 81.782
-    - type: map_at_3
-      value: 78.148
-    - type: map_at_5
-      value: 79.95400000000001
-    - type: mrr_at_1
-      value: 77.8
-    - type: mrr_at_10
-      value: 84.639
-    - type: mrr_at_100
-      value: 84.789
-    - type: mrr_at_1000
-      value: 84.79100000000001
-    - type: mrr_at_3
-      value: 83.467
-    - type: mrr_at_5
-      value: 84.251
-    - type: ndcg_at_1
-      value: 77.82
-    - type: ndcg_at_10
-      value: 85.286
-    - type: ndcg_at_100
-      value: 86.86500000000001
-    - type: ndcg_at_1000
-      value: 87.062
-    - type: ndcg_at_3
-      value: 82.116
-    - type: ndcg_at_5
-      value: 83.811
-    - type: precision_at_1
-      value: 77.82
-    - type: precision_at_10
-      value: 12.867999999999999
-    - type: precision_at_100
-      value: 1.498
-    - type: precision_at_1000
-      value: 0.156
-    - type: precision_at_3
-      value: 35.723
-    - type: precision_at_5
-      value: 23.52
-    - type: recall_at_1
-      value: 67.765
-    - type: recall_at_10
-      value: 93.381
-    - type: recall_at_100
-      value: 98.901
-    - type: recall_at_1000
-      value: 99.864
-    - type: recall_at_3
-      value: 84.301
-    - type: recall_at_5
-      value: 89.049
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 45.27190981742137
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 54.47444004585028
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 4.213
-    - type: map_at_10
-      value: 10.166
-    - type: map_at_100
-      value: 11.987
-    - type: map_at_1000
-      value: 12.285
-    - type: map_at_3
-      value: 7.538
-    - type: map_at_5
-      value: 8.606
-    - type: mrr_at_1
-      value: 20.8
-    - type: mrr_at_10
-      value: 30.066
-    - type: mrr_at_100
-      value: 31.290000000000003
-    - type: mrr_at_1000
-      value: 31.357000000000003
-    - type: mrr_at_3
-      value: 27.083000000000002
-    - type: mrr_at_5
-      value: 28.748
-    - type: ndcg_at_1
-      value: 20.8
-    - type: ndcg_at_10
-      value: 17.258000000000003
-    - type: ndcg_at_100
-      value: 24.801000000000002
-    - type: ndcg_at_1000
-      value: 30.348999999999997
-    - type: ndcg_at_3
-      value: 16.719
-    - type: ndcg_at_5
-      value: 14.145
-    - type: precision_at_1
-      value: 20.8
-    - type: precision_at_10
-      value: 8.88
-    - type: precision_at_100
-      value: 1.9789999999999999
-    - type: precision_at_1000
-      value: 0.332
-    - type: precision_at_3
-      value: 15.5
-    - type: precision_at_5
-      value: 12.1
-    - type: recall_at_1
-      value: 4.213
-    - type: recall_at_10
-      value: 17.983
-    - type: recall_at_100
-      value: 40.167
-    - type: recall_at_1000
-      value: 67.43
-    - type: recall_at_3
-      value: 9.433
-    - type: recall_at_5
-      value: 12.267999999999999
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_pearson
-      value: 80.36742239848913
-    - type: cos_sim_spearman
-      value: 72.39470010828755
-    - type: euclidean_pearson
-      value: 77.26919895870947
-    - type: euclidean_spearman
-      value: 72.26534999077315
-    - type: manhattan_pearson
-      value: 77.04066349814258
-    - type: manhattan_spearman
-      value: 72.0072248699278
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_pearson
-      value: 80.26991474037257
-    - type: cos_sim_spearman
-      value: 71.90287122017716
-    - type: euclidean_pearson
-      value: 76.68006075912453
-    - type: euclidean_spearman
-      value: 71.69301858764365
-    - type: manhattan_pearson
-      value: 76.72277285842371
-    - type: manhattan_spearman
-      value: 71.73265239703795
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_pearson
-      value: 79.74371413317881
-    - type: cos_sim_spearman
-      value: 80.9279612820358
-    - type: euclidean_pearson
-      value: 80.6417435294782
-    - type: euclidean_spearman
-      value: 81.17460969254459
-    - type: manhattan_pearson
-      value: 80.51820155178402
-    - type: manhattan_spearman
-      value: 81.08028700017084
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_pearson
-      value: 80.37085777051112
-    - type: cos_sim_spearman
-      value: 76.60308382518285
-    - type: euclidean_pearson
-      value: 79.59684787227351
-    - type: euclidean_spearman
-      value: 76.8769048249242
-    - type: manhattan_pearson
-      value: 79.55617632538295
-    - type: manhattan_spearman
-      value: 76.90186497973124
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_pearson
-      value: 83.99513105301321
-    - type: cos_sim_spearman
-      value: 84.92034548133665
-    - type: euclidean_pearson
-      value: 84.70872540095195
-    - type: euclidean_spearman
-      value: 85.14591726040749
-    - type: manhattan_pearson
-      value: 84.65707417430595
-    - type: manhattan_spearman
-      value: 85.10407163865375
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_pearson
-      value: 79.40758449150897
-    - type: cos_sim_spearman
-      value: 80.71692246880549
-    - type: euclidean_pearson
-      value: 80.51658552062683
-    - type: euclidean_spearman
-      value: 80.87118389043233
-    - type: manhattan_pearson
-      value: 80.41534690825016
-    - type: manhattan_spearman
-      value: 80.73925282537256
-  - 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: 84.93617076910748
-    - type: cos_sim_spearman
-      value: 85.61118538966805
-    - type: euclidean_pearson
-      value: 85.56187558635287
-    - type: euclidean_spearman
-      value: 85.21910090757267
-    - type: manhattan_pearson
-      value: 85.29916699037645
-    - type: manhattan_spearman
-      value: 84.96820527868671
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts22-crosslingual-sts
-      name: MTEB STS22 (en)
-      config: en
-      split: test
-      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
-    metrics:
-    - type: cos_sim_pearson
-      value: 64.22294088543077
-    - type: cos_sim_spearman
-      value: 65.89748502901078
-    - type: euclidean_pearson
-      value: 66.15637850660805
-    - type: euclidean_spearman
-      value: 65.86095841381278
-    - type: manhattan_pearson
-      value: 66.80966197857856
-    - type: manhattan_spearman
-      value: 66.48325202219692
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_pearson
-      value: 81.75298158703048
-    - type: cos_sim_spearman
-      value: 81.32168373072322
-    - type: euclidean_pearson
-      value: 82.3251793712207
-    - type: euclidean_spearman
-      value: 81.31655163330606
-    - type: manhattan_pearson
-      value: 82.14136865023298
-    - type: manhattan_spearman
-      value: 81.13410964028606
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 78.77937068780793
-    - type: mrr
-      value: 93.334709952357
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 50.705999999999996
-    - type: map_at_10
-      value: 60.699999999999996
-    - type: map_at_100
-      value: 61.256
-    - type: map_at_1000
-      value: 61.285000000000004
-    - type: map_at_3
-      value: 57.633
-    - type: map_at_5
-      value: 59.648
-    - type: mrr_at_1
-      value: 53.0
-    - type: mrr_at_10
-      value: 61.717999999999996
-    - type: mrr_at_100
-      value: 62.165000000000006
-    - type: mrr_at_1000
-      value: 62.190999999999995
-    - type: mrr_at_3
-      value: 59.389
-    - type: mrr_at_5
-      value: 60.922
-    - type: ndcg_at_1
-      value: 53.0
-    - type: ndcg_at_10
-      value: 65.413
-    - type: ndcg_at_100
-      value: 68.089
-    - type: ndcg_at_1000
-      value: 69.01899999999999
-    - type: ndcg_at_3
-      value: 60.327
-    - type: ndcg_at_5
-      value: 63.263999999999996
-    - type: precision_at_1
-      value: 53.0
-    - type: precision_at_10
-      value: 8.933
-    - type: precision_at_100
-      value: 1.04
-    - type: precision_at_1000
-      value: 0.11199999999999999
-    - type: precision_at_3
-      value: 23.778
-    - type: precision_at_5
-      value: 16.2
-    - type: recall_at_1
-      value: 50.705999999999996
-    - type: recall_at_10
-      value: 78.633
-    - type: recall_at_100
-      value: 91.333
-    - type: recall_at_1000
-      value: 99.0
-    - type: recall_at_3
-      value: 65.328
-    - type: recall_at_5
-      value: 72.583
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.82178217821782
-    - type: cos_sim_ap
-      value: 95.30078788098801
-    - type: cos_sim_f1
-      value: 91.11549851924975
-    - type: cos_sim_precision
-      value: 89.96101364522417
-    - type: cos_sim_recall
-      value: 92.30000000000001
-    - type: dot_accuracy
-      value: 99.74851485148515
-    - type: dot_ap
-      value: 93.12383012680787
-    - type: dot_f1
-      value: 87.17171717171716
-    - type: dot_precision
-      value: 88.06122448979592
-    - type: dot_recall
-      value: 86.3
-    - type: euclidean_accuracy
-      value: 99.82673267326733
-    - type: euclidean_ap
-      value: 95.29507269622621
-    - type: euclidean_f1
-      value: 91.3151364764268
-    - type: euclidean_precision
-      value: 90.64039408866995
-    - type: euclidean_recall
-      value: 92.0
-    - type: manhattan_accuracy
-      value: 99.82178217821782
-    - type: manhattan_ap
-      value: 95.34300712110257
-    - type: manhattan_f1
-      value: 91.05367793240556
-    - type: manhattan_precision
-      value: 90.51383399209486
-    - type: manhattan_recall
-      value: 91.60000000000001
-    - type: max_accuracy
-      value: 99.82673267326733
-    - type: max_ap
-      value: 95.34300712110257
-    - type: max_f1
-      value: 91.3151364764268
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 53.10993894014712
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 34.67216071080345
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 48.96344255085851
-    - type: mrr
-      value: 49.816123419064596
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.580410074992177
-    - type: cos_sim_spearman
-      value: 31.155995112739966
-    - type: dot_pearson
-      value: 31.112094423048998
-    - type: dot_spearman
-      value: 31.29974829801922
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.17700000000000002
-    - type: map_at_10
-      value: 1.22
-    - type: map_at_100
-      value: 6.2170000000000005
-    - type: map_at_1000
-      value: 15.406
-    - type: map_at_3
-      value: 0.483
-    - type: map_at_5
-      value: 0.729
-    - type: mrr_at_1
-      value: 64.0
-    - type: mrr_at_10
-      value: 76.333
-    - type: mrr_at_100
-      value: 76.47
-    - type: mrr_at_1000
-      value: 76.47
-    - type: mrr_at_3
-      value: 75.0
-    - type: mrr_at_5
-      value: 76.0
-    - type: ndcg_at_1
-      value: 59.0
-    - type: ndcg_at_10
-      value: 52.62
-    - type: ndcg_at_100
-      value: 39.932
-    - type: ndcg_at_1000
-      value: 37.317
-    - type: ndcg_at_3
-      value: 57.123000000000005
-    - type: ndcg_at_5
-      value: 56.376000000000005
-    - type: precision_at_1
-      value: 64.0
-    - type: precision_at_10
-      value: 55.800000000000004
-    - type: precision_at_100
-      value: 41.04
-    - type: precision_at_1000
-      value: 17.124
-    - type: precision_at_3
-      value: 63.333
-    - type: precision_at_5
-      value: 62.0
-    - type: recall_at_1
-      value: 0.17700000000000002
-    - type: recall_at_10
-      value: 1.46
-    - type: recall_at_100
-      value: 9.472999999999999
-    - type: recall_at_1000
-      value: 35.661
-    - type: recall_at_3
-      value: 0.527
-    - type: recall_at_5
-      value: 0.8250000000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 1.539
-    - type: map_at_10
-      value: 7.178
-    - type: map_at_100
-      value: 12.543000000000001
-    - type: map_at_1000
-      value: 14.126
-    - type: map_at_3
-      value: 3.09
-    - type: map_at_5
-      value: 5.008
-    - type: mrr_at_1
-      value: 18.367
-    - type: mrr_at_10
-      value: 32.933
-    - type: mrr_at_100
-      value: 34.176
-    - type: mrr_at_1000
-      value: 34.176
-    - type: mrr_at_3
-      value: 27.551
-    - type: mrr_at_5
-      value: 30.714000000000002
-    - type: ndcg_at_1
-      value: 15.306000000000001
-    - type: ndcg_at_10
-      value: 18.343
-    - type: ndcg_at_100
-      value: 30.076000000000004
-    - type: ndcg_at_1000
-      value: 42.266999999999996
-    - type: ndcg_at_3
-      value: 17.233999999999998
-    - type: ndcg_at_5
-      value: 18.677
-    - type: precision_at_1
-      value: 18.367
-    - type: precision_at_10
-      value: 18.367
-    - type: precision_at_100
-      value: 6.837
-    - type: precision_at_1000
-      value: 1.467
-    - type: precision_at_3
-      value: 19.048000000000002
-    - type: precision_at_5
-      value: 21.224
-    - type: recall_at_1
-      value: 1.539
-    - type: recall_at_10
-      value: 13.289000000000001
-    - type: recall_at_100
-      value: 42.480000000000004
-    - type: recall_at_1000
-      value: 79.463
-    - type: recall_at_3
-      value: 4.202999999999999
-    - type: recall_at_5
-      value: 7.9030000000000005
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 69.2056
-    - type: ap
-      value: 13.564165903349778
-    - type: f1
-      value: 53.303385089202656
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 56.71477079796264
-    - type: f1
-      value: 57.01563439439609
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 39.373040570976514
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 83.44757703999524
-    - type: cos_sim_ap
-      value: 65.78689843625949
-    - type: cos_sim_f1
-      value: 62.25549384206713
-    - type: cos_sim_precision
-      value: 57.39091718610864
-    - type: cos_sim_recall
-      value: 68.02110817941951
-    - type: dot_accuracy
-      value: 81.3971508612982
-    - type: dot_ap
-      value: 58.42933051967154
-    - type: dot_f1
-      value: 57.85580214198962
-    - type: dot_precision
-      value: 49.74368710841086
-    - type: dot_recall
-      value: 69.12928759894459
-    - type: euclidean_accuracy
-      value: 83.54294569946951
-    - type: euclidean_ap
-      value: 66.10612585693795
-    - type: euclidean_f1
-      value: 62.66666666666667
-    - type: euclidean_precision
-      value: 58.88631090487239
-    - type: euclidean_recall
-      value: 66.96569920844327
-    - type: manhattan_accuracy
-      value: 83.43565595756095
-    - type: manhattan_ap
-      value: 65.88532290329134
-    - type: manhattan_f1
-      value: 62.58408721874276
-    - type: manhattan_precision
-      value: 55.836092715231786
-    - type: manhattan_recall
-      value: 71.18733509234828
-    - type: max_accuracy
-      value: 83.54294569946951
-    - type: max_ap
-      value: 66.10612585693795
-    - type: max_f1
-      value: 62.66666666666667
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.02344083517679
-    - type: cos_sim_ap
-      value: 84.21589190889944
-    - type: cos_sim_f1
-      value: 76.36723039754007
-    - type: cos_sim_precision
-      value: 72.79134682484299
-    - type: cos_sim_recall
-      value: 80.31259624268556
-    - type: dot_accuracy
-      value: 87.43353902278108
-    - type: dot_ap
-      value: 82.08962394120071
-    - type: dot_f1
-      value: 74.97709923664122
-    - type: dot_precision
-      value: 74.34150772025431
-    - type: dot_recall
-      value: 75.62365260240222
-    - type: euclidean_accuracy
-      value: 87.97686963946133
-    - type: euclidean_ap
-      value: 84.20578083922416
-    - type: euclidean_f1
-      value: 76.4299182903834
-    - type: euclidean_precision
-      value: 73.51874244256348
-    - type: euclidean_recall
-      value: 79.58115183246073
-    - type: manhattan_accuracy
-      value: 88.00209570380719
-    - type: manhattan_ap
-      value: 84.14700304263556
-    - type: manhattan_f1
-      value: 76.36429345861944
-    - type: manhattan_precision
-      value: 71.95886119057349
-    - type: manhattan_recall
-      value: 81.34431783184478
-    - type: max_accuracy
-      value: 88.02344083517679
-    - type: max_ap
-      value: 84.21589190889944
-    - type: max_f1
-      value: 76.4299182903834
----