delete mteb_metadata.md

mteb_metadata.md

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----
-tags:
-- mteb
-model-index:
-- name: mteb_metrics
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 76.22388059701493
-    - type: ap
-      value: 40.27466219523129
-    - type: f1
-      value: 70.60533006025108
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 87.525775
-    - type: ap
-      value: 83.51063993897611
-    - type: f1
-      value: 87.49342736805572
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 42.611999999999995
-    - type: f1
-      value: 42.05088045932892
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 23.826
-    - type: map_at_10
-      value: 38.269
-    - type: map_at_100
-      value: 39.322
-    - type: map_at_1000
-      value: 39.344
-    - type: map_at_3
-      value: 33.428000000000004
-    - type: map_at_5
-      value: 36.063
-    - type: mrr_at_1
-      value: 24.253
-    - type: mrr_at_10
-      value: 38.425
-    - type: mrr_at_100
-      value: 39.478
-    - type: mrr_at_1000
-      value: 39.5
-    - type: mrr_at_3
-      value: 33.606
-    - type: mrr_at_5
-      value: 36.195
-    - type: ndcg_at_1
-      value: 23.826
-    - type: ndcg_at_10
-      value: 46.693
-    - type: ndcg_at_100
-      value: 51.469
-    - type: ndcg_at_1000
-      value: 52.002
-    - type: ndcg_at_3
-      value: 36.603
-    - type: ndcg_at_5
-      value: 41.365
-    - type: precision_at_1
-      value: 23.826
-    - type: precision_at_10
-      value: 7.383000000000001
-    - type: precision_at_100
-      value: 0.9530000000000001
-    - type: precision_at_1000
-      value: 0.099
-    - type: precision_at_3
-      value: 15.268
-    - type: precision_at_5
-      value: 11.479000000000001
-    - type: recall_at_1
-      value: 23.826
-    - type: recall_at_10
-      value: 73.82600000000001
-    - type: recall_at_100
-      value: 95.306
-    - type: recall_at_1000
-      value: 99.431
-    - type: recall_at_3
-      value: 45.804
-    - type: recall_at_5
-      value: 57.397
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 44.13995374767436
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 37.13950072624313
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 59.35843292105327
-    - type: mrr
-      value: 73.72312359846987
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 84.55140418324174
-    - type: cos_sim_spearman
-      value: 84.21637675860022
-    - type: euclidean_pearson
-      value: 81.26069614610006
-    - type: euclidean_spearman
-      value: 83.25069210421785
-    - type: manhattan_pearson
-      value: 80.17441422581014
-    - type: manhattan_spearman
-      value: 81.87596198487877
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 81.87337662337661
-    - type: f1
-      value: 81.76647866926402
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 35.80600542614507
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 31.86321613256603
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.054
-    - type: map_at_10
-      value: 40.699999999999996
-    - type: map_at_100
-      value: 41.818
-    - type: map_at_1000
-      value: 41.959999999999994
-    - type: map_at_3
-      value: 37.742
-    - type: map_at_5
-      value: 39.427
-    - type: mrr_at_1
-      value: 38.769999999999996
-    - type: mrr_at_10
-      value: 46.150000000000006
-    - type: mrr_at_100
-      value: 46.865
-    - type: mrr_at_1000
-      value: 46.925
-    - type: mrr_at_3
-      value: 43.705
-    - type: mrr_at_5
-      value: 45.214999999999996
-    - type: ndcg_at_1
-      value: 38.769999999999996
-    - type: ndcg_at_10
-      value: 45.778
-    - type: ndcg_at_100
-      value: 50.38
-    - type: ndcg_at_1000
-      value: 52.922999999999995
-    - type: ndcg_at_3
-      value: 41.597
-    - type: ndcg_at_5
-      value: 43.631
-    - type: precision_at_1
-      value: 38.769999999999996
-    - type: precision_at_10
-      value: 8.269
-    - type: precision_at_100
-      value: 1.278
-    - type: precision_at_1000
-      value: 0.178
-    - type: precision_at_3
-      value: 19.266
-    - type: precision_at_5
-      value: 13.705
-    - type: recall_at_1
-      value: 32.054
-    - type: recall_at_10
-      value: 54.947
-    - type: recall_at_100
-      value: 74.79599999999999
-    - type: recall_at_1000
-      value: 91.40899999999999
-    - type: recall_at_3
-      value: 42.431000000000004
-    - type: recall_at_5
-      value: 48.519
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.035
-    - type: map_at_10
-      value: 38.007000000000005
-    - type: map_at_100
-      value: 39.125
-    - type: map_at_1000
-      value: 39.251999999999995
-    - type: map_at_3
-      value: 35.77
-    - type: map_at_5
-      value: 37.057
-    - type: mrr_at_1
-      value: 36.497
-    - type: mrr_at_10
-      value: 44.077
-    - type: mrr_at_100
-      value: 44.743
-    - type: mrr_at_1000
-      value: 44.79
-    - type: mrr_at_3
-      value: 42.123
-    - type: mrr_at_5
-      value: 43.308
-    - type: ndcg_at_1
-      value: 36.497
-    - type: ndcg_at_10
-      value: 42.986000000000004
-    - type: ndcg_at_100
-      value: 47.323
-    - type: ndcg_at_1000
-      value: 49.624
-    - type: ndcg_at_3
-      value: 39.805
-    - type: ndcg_at_5
-      value: 41.286
-    - type: precision_at_1
-      value: 36.497
-    - type: precision_at_10
-      value: 7.8340000000000005
-    - type: precision_at_100
-      value: 1.269
-    - type: precision_at_1000
-      value: 0.178
-    - type: precision_at_3
-      value: 19.023
-    - type: precision_at_5
-      value: 13.248
-    - type: recall_at_1
-      value: 29.035
-    - type: recall_at_10
-      value: 51.06
-    - type: recall_at_100
-      value: 69.64099999999999
-    - type: recall_at_1000
-      value: 84.49
-    - type: recall_at_3
-      value: 41.333999999999996
-    - type: recall_at_5
-      value: 45.663
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 37.239
-    - type: map_at_10
-      value: 47.873
-    - type: map_at_100
-      value: 48.842999999999996
-    - type: map_at_1000
-      value: 48.913000000000004
-    - type: map_at_3
-      value: 45.050000000000004
-    - type: map_at_5
-      value: 46.498
-    - type: mrr_at_1
-      value: 42.508
-    - type: mrr_at_10
-      value: 51.44
-    - type: mrr_at_100
-      value: 52.087
-    - type: mrr_at_1000
-      value: 52.129999999999995
-    - type: mrr_at_3
-      value: 49.164
-    - type: mrr_at_5
-      value: 50.343
-    - type: ndcg_at_1
-      value: 42.508
-    - type: ndcg_at_10
-      value: 53.31399999999999
-    - type: ndcg_at_100
-      value: 57.245000000000005
-    - type: ndcg_at_1000
-      value: 58.794000000000004
-    - type: ndcg_at_3
-      value: 48.295
-    - type: ndcg_at_5
-      value: 50.415
-    - type: precision_at_1
-      value: 42.508
-    - type: precision_at_10
-      value: 8.458
-    - type: precision_at_100
-      value: 1.133
-    - type: precision_at_1000
-      value: 0.132
-    - type: precision_at_3
-      value: 21.191
-    - type: precision_at_5
-      value: 14.307
-    - type: recall_at_1
-      value: 37.239
-    - type: recall_at_10
-      value: 65.99000000000001
-    - type: recall_at_100
-      value: 82.99499999999999
-    - type: recall_at_1000
-      value: 94.128
-    - type: recall_at_3
-      value: 52.382
-    - type: recall_at_5
-      value: 57.648999999999994
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 23.039
-    - type: map_at_10
-      value: 29.694
-    - type: map_at_100
-      value: 30.587999999999997
-    - type: map_at_1000
-      value: 30.692999999999998
-    - type: map_at_3
-      value: 27.708
-    - type: map_at_5
-      value: 28.774
-    - type: mrr_at_1
-      value: 24.633
-    - type: mrr_at_10
-      value: 31.478
-    - type: mrr_at_100
-      value: 32.299
-    - type: mrr_at_1000
-      value: 32.381
-    - type: mrr_at_3
-      value: 29.435
-    - type: mrr_at_5
-      value: 30.446
-    - type: ndcg_at_1
-      value: 24.633
-    - type: ndcg_at_10
-      value: 33.697
-    - type: ndcg_at_100
-      value: 38.080000000000005
-    - type: ndcg_at_1000
-      value: 40.812
-    - type: ndcg_at_3
-      value: 29.654000000000003
-    - type: ndcg_at_5
-      value: 31.474000000000004
-    - type: precision_at_1
-      value: 24.633
-    - type: precision_at_10
-      value: 5.0729999999999995
-    - type: precision_at_100
-      value: 0.753
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 12.279
-    - type: precision_at_5
-      value: 8.452
-    - type: recall_at_1
-      value: 23.039
-    - type: recall_at_10
-      value: 44.275999999999996
-    - type: recall_at_100
-      value: 64.4
-    - type: recall_at_1000
-      value: 85.135
-    - type: recall_at_3
-      value: 33.394
-    - type: recall_at_5
-      value: 37.687
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 13.594999999999999
-    - type: map_at_10
-      value: 19.933999999999997
-    - type: map_at_100
-      value: 20.966
-    - type: map_at_1000
-      value: 21.087
-    - type: map_at_3
-      value: 17.749000000000002
-    - type: map_at_5
-      value: 19.156000000000002
-    - type: mrr_at_1
-      value: 17.662
-    - type: mrr_at_10
-      value: 24.407
-    - type: mrr_at_100
-      value: 25.385
-    - type: mrr_at_1000
-      value: 25.465
-    - type: mrr_at_3
-      value: 22.056
-    - type: mrr_at_5
-      value: 23.630000000000003
-    - type: ndcg_at_1
-      value: 17.662
-    - type: ndcg_at_10
-      value: 24.391
-    - type: ndcg_at_100
-      value: 29.681
-    - type: ndcg_at_1000
-      value: 32.923
-    - type: ndcg_at_3
-      value: 20.271
-    - type: ndcg_at_5
-      value: 22.621
-    - type: precision_at_1
-      value: 17.662
-    - type: precision_at_10
-      value: 4.44
-    - type: precision_at_100
-      value: 0.8200000000000001
-    - type: precision_at_1000
-      value: 0.125
-    - type: precision_at_3
-      value: 9.577
-    - type: precision_at_5
-      value: 7.313
-    - type: recall_at_1
-      value: 13.594999999999999
-    - type: recall_at_10
-      value: 33.976
-    - type: recall_at_100
-      value: 57.43000000000001
-    - type: recall_at_1000
-      value: 80.958
-    - type: recall_at_3
-      value: 22.897000000000002
-    - type: recall_at_5
-      value: 28.714000000000002
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.683
-    - type: map_at_10
-      value: 35.068
-    - type: map_at_100
-      value: 36.311
-    - type: map_at_1000
-      value: 36.436
-    - type: map_at_3
-      value: 32.371
-    - type: map_at_5
-      value: 33.761
-    - type: mrr_at_1
-      value: 32.435
-    - type: mrr_at_10
-      value: 40.721000000000004
-    - type: mrr_at_100
-      value: 41.535
-    - type: mrr_at_1000
-      value: 41.593
-    - type: mrr_at_3
-      value: 38.401999999999994
-    - type: mrr_at_5
-      value: 39.567
-    - type: ndcg_at_1
-      value: 32.435
-    - type: ndcg_at_10
-      value: 40.538000000000004
-    - type: ndcg_at_100
-      value: 45.963
-    - type: ndcg_at_1000
-      value: 48.400999999999996
-    - type: ndcg_at_3
-      value: 36.048
-    - type: ndcg_at_5
-      value: 37.899
-    - type: precision_at_1
-      value: 32.435
-    - type: precision_at_10
-      value: 7.1129999999999995
-    - type: precision_at_100
-      value: 1.162
-    - type: precision_at_1000
-      value: 0.156
-    - type: precision_at_3
-      value: 16.683
-    - type: precision_at_5
-      value: 11.684
-    - type: recall_at_1
-      value: 26.683
-    - type: recall_at_10
-      value: 51.517
-    - type: recall_at_100
-      value: 74.553
-    - type: recall_at_1000
-      value: 90.649
-    - type: recall_at_3
-      value: 38.495000000000005
-    - type: recall_at_5
-      value: 43.495
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 24.186
-    - type: map_at_10
-      value: 31.972
-    - type: map_at_100
-      value: 33.117000000000004
-    - type: map_at_1000
-      value: 33.243
-    - type: map_at_3
-      value: 29.423
-    - type: map_at_5
-      value: 30.847
-    - type: mrr_at_1
-      value: 29.794999999999998
-    - type: mrr_at_10
-      value: 36.767
-    - type: mrr_at_100
-      value: 37.645
-    - type: mrr_at_1000
-      value: 37.716
-    - type: mrr_at_3
-      value: 34.513
-    - type: mrr_at_5
-      value: 35.791000000000004
-    - type: ndcg_at_1
-      value: 29.794999999999998
-    - type: ndcg_at_10
-      value: 36.786
-    - type: ndcg_at_100
-      value: 41.94
-    - type: ndcg_at_1000
-      value: 44.830999999999996
-    - type: ndcg_at_3
-      value: 32.504
-    - type: ndcg_at_5
-      value: 34.404
-    - type: precision_at_1
-      value: 29.794999999999998
-    - type: precision_at_10
-      value: 6.518
-    - type: precision_at_100
-      value: 1.0659999999999998
-    - type: precision_at_1000
-      value: 0.149
-    - type: precision_at_3
-      value: 15.296999999999999
-    - type: precision_at_5
-      value: 10.731
-    - type: recall_at_1
-      value: 24.186
-    - type: recall_at_10
-      value: 46.617
-    - type: recall_at_100
-      value: 68.75
-    - type: recall_at_1000
-      value: 88.864
-    - type: recall_at_3
-      value: 34.199
-    - type: recall_at_5
-      value: 39.462
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 24.22083333333333
-    - type: map_at_10
-      value: 31.606666666666662
-    - type: map_at_100
-      value: 32.6195
-    - type: map_at_1000
-      value: 32.739999999999995
-    - type: map_at_3
-      value: 29.37825
-    - type: map_at_5
-      value: 30.596083333333336
-    - type: mrr_at_1
-      value: 28.607916666666668
-    - type: mrr_at_10
-      value: 35.54591666666666
-    - type: mrr_at_100
-      value: 36.33683333333333
-    - type: mrr_at_1000
-      value: 36.40624999999999
-    - type: mrr_at_3
-      value: 33.526250000000005
-    - type: mrr_at_5
-      value: 34.6605
-    - type: ndcg_at_1
-      value: 28.607916666666668
-    - type: ndcg_at_10
-      value: 36.07966666666667
-    - type: ndcg_at_100
-      value: 40.73308333333333
-    - type: ndcg_at_1000
-      value: 43.40666666666666
-    - type: ndcg_at_3
-      value: 32.23525
-    - type: ndcg_at_5
-      value: 33.97083333333333
-    - type: precision_at_1
-      value: 28.607916666666668
-    - type: precision_at_10
-      value: 6.120333333333335
-    - type: precision_at_100
-      value: 0.9921666666666668
-    - type: precision_at_1000
-      value: 0.14091666666666666
-    - type: precision_at_3
-      value: 14.54975
-    - type: precision_at_5
-      value: 10.153166666666667
-    - type: recall_at_1
-      value: 24.22083333333333
-    - type: recall_at_10
-      value: 45.49183333333334
-    - type: recall_at_100
-      value: 66.28133333333332
-    - type: recall_at_1000
-      value: 85.16541666666667
-    - type: recall_at_3
-      value: 34.6485
-    - type: recall_at_5
-      value: 39.229749999999996
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.842
-    - type: map_at_10
-      value: 27.573999999999998
-    - type: map_at_100
-      value: 28.410999999999998
-    - type: map_at_1000
-      value: 28.502
-    - type: map_at_3
-      value: 25.921
-    - type: map_at_5
-      value: 26.888
-    - type: mrr_at_1
-      value: 24.08
-    - type: mrr_at_10
-      value: 29.915999999999997
-    - type: mrr_at_100
-      value: 30.669
-    - type: mrr_at_1000
-      value: 30.746000000000002
-    - type: mrr_at_3
-      value: 28.349000000000004
-    - type: mrr_at_5
-      value: 29.246
-    - type: ndcg_at_1
-      value: 24.08
-    - type: ndcg_at_10
-      value: 30.898999999999997
-    - type: ndcg_at_100
-      value: 35.272999999999996
-    - type: ndcg_at_1000
-      value: 37.679
-    - type: ndcg_at_3
-      value: 27.881
-    - type: ndcg_at_5
-      value: 29.432000000000002
-    - type: precision_at_1
-      value: 24.08
-    - type: precision_at_10
-      value: 4.678
-    - type: precision_at_100
-      value: 0.744
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 11.860999999999999
-    - type: precision_at_5
-      value: 8.16
-    - type: recall_at_1
-      value: 21.842
-    - type: recall_at_10
-      value: 38.66
-    - type: recall_at_100
-      value: 59.169000000000004
-    - type: recall_at_1000
-      value: 76.887
-    - type: recall_at_3
-      value: 30.532999999999998
-    - type: recall_at_5
-      value: 34.354
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 17.145
-    - type: map_at_10
-      value: 22.729
-    - type: map_at_100
-      value: 23.574
-    - type: map_at_1000
-      value: 23.695
-    - type: map_at_3
-      value: 21.044
-    - type: map_at_5
-      value: 21.981
-    - type: mrr_at_1
-      value: 20.888
-    - type: mrr_at_10
-      value: 26.529000000000003
-    - type: mrr_at_100
-      value: 27.308
-    - type: mrr_at_1000
-      value: 27.389000000000003
-    - type: mrr_at_3
-      value: 24.868000000000002
-    - type: mrr_at_5
-      value: 25.825
-    - type: ndcg_at_1
-      value: 20.888
-    - type: ndcg_at_10
-      value: 26.457000000000004
-    - type: ndcg_at_100
-      value: 30.764000000000003
-    - type: ndcg_at_1000
-      value: 33.825
-    - type: ndcg_at_3
-      value: 23.483999999999998
-    - type: ndcg_at_5
-      value: 24.836
-    - type: precision_at_1
-      value: 20.888
-    - type: precision_at_10
-      value: 4.58
-    - type: precision_at_100
-      value: 0.784
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 10.874
-    - type: precision_at_5
-      value: 7.639
-    - type: recall_at_1
-      value: 17.145
-    - type: recall_at_10
-      value: 33.938
-    - type: recall_at_100
-      value: 53.672
-    - type: recall_at_1000
-      value: 76.023
-    - type: recall_at_3
-      value: 25.363000000000003
-    - type: recall_at_5
-      value: 29.023
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 24.275
-    - type: map_at_10
-      value: 30.438
-    - type: map_at_100
-      value: 31.489
-    - type: map_at_1000
-      value: 31.601000000000003
-    - type: map_at_3
-      value: 28.647
-    - type: map_at_5
-      value: 29.660999999999998
-    - type: mrr_at_1
-      value: 28.077999999999996
-    - type: mrr_at_10
-      value: 34.098
-    - type: mrr_at_100
-      value: 35.025
-    - type: mrr_at_1000
-      value: 35.109
-    - type: mrr_at_3
-      value: 32.4
-    - type: mrr_at_5
-      value: 33.379999999999995
-    - type: ndcg_at_1
-      value: 28.077999999999996
-    - type: ndcg_at_10
-      value: 34.271
-    - type: ndcg_at_100
-      value: 39.352
-    - type: ndcg_at_1000
-      value: 42.199
-    - type: ndcg_at_3
-      value: 30.978
-    - type: ndcg_at_5
-      value: 32.498
-    - type: precision_at_1
-      value: 28.077999999999996
-    - type: precision_at_10
-      value: 5.345
-    - type: precision_at_100
-      value: 0.897
-    - type: precision_at_1000
-      value: 0.125
-    - type: precision_at_3
-      value: 13.526
-    - type: precision_at_5
-      value: 9.16
-    - type: recall_at_1
-      value: 24.275
-    - type: recall_at_10
-      value: 42.362
-    - type: recall_at_100
-      value: 64.461
-    - type: recall_at_1000
-      value: 84.981
-    - type: recall_at_3
-      value: 33.249
-    - type: recall_at_5
-      value: 37.214999999999996
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.358
-    - type: map_at_10
-      value: 30.062
-    - type: map_at_100
-      value: 31.189
-    - type: map_at_1000
-      value: 31.386999999999997
-    - type: map_at_3
-      value: 27.672
-    - type: map_at_5
-      value: 28.76
-    - type: mrr_at_1
-      value: 26.877000000000002
-    - type: mrr_at_10
-      value: 33.948
-    - type: mrr_at_100
-      value: 34.746
-    - type: mrr_at_1000
-      value: 34.816
-    - type: mrr_at_3
-      value: 31.884
-    - type: mrr_at_5
-      value: 33.001000000000005
-    - type: ndcg_at_1
-      value: 26.877000000000002
-    - type: ndcg_at_10
-      value: 34.977000000000004
-    - type: ndcg_at_100
-      value: 39.753
-    - type: ndcg_at_1000
-      value: 42.866
-    - type: ndcg_at_3
-      value: 30.956
-    - type: ndcg_at_5
-      value: 32.381
-    - type: precision_at_1
-      value: 26.877000000000002
-    - type: precision_at_10
-      value: 6.7
-    - type: precision_at_100
-      value: 1.287
-    - type: precision_at_1000
-      value: 0.215
-    - type: precision_at_3
-      value: 14.360999999999999
-    - type: precision_at_5
-      value: 10.119
-    - type: recall_at_1
-      value: 22.358
-    - type: recall_at_10
-      value: 44.183
-    - type: recall_at_100
-      value: 67.14
-    - type: recall_at_1000
-      value: 87.53999999999999
-    - type: recall_at_3
-      value: 32.79
-    - type: recall_at_5
-      value: 36.829
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.198999999999998
-    - type: map_at_10
-      value: 25.229000000000003
-    - type: map_at_100
-      value: 26.003
-    - type: map_at_1000
-      value: 26.111
-    - type: map_at_3
-      value: 23.442
-    - type: map_at_5
-      value: 24.343
-    - type: mrr_at_1
-      value: 21.072
-    - type: mrr_at_10
-      value: 27.02
-    - type: mrr_at_100
-      value: 27.735
-    - type: mrr_at_1000
-      value: 27.815
-    - type: mrr_at_3
-      value: 25.416
-    - type: mrr_at_5
-      value: 26.173999999999996
-    - type: ndcg_at_1
-      value: 21.072
-    - type: ndcg_at_10
-      value: 28.862
-    - type: ndcg_at_100
-      value: 33.043
-    - type: ndcg_at_1000
-      value: 36.003
-    - type: ndcg_at_3
-      value: 25.35
-    - type: ndcg_at_5
-      value: 26.773000000000003
-    - type: precision_at_1
-      value: 21.072
-    - type: precision_at_10
-      value: 4.436
-    - type: precision_at_100
-      value: 0.713
-    - type: precision_at_1000
-      value: 0.106
-    - type: precision_at_3
-      value: 10.659
-    - type: precision_at_5
-      value: 7.32
-    - type: recall_at_1
-      value: 19.198999999999998
-    - type: recall_at_10
-      value: 38.376
-    - type: recall_at_100
-      value: 58.36900000000001
-    - type: recall_at_1000
-      value: 80.92099999999999
-    - type: recall_at_3
-      value: 28.715000000000003
-    - type: recall_at_5
-      value: 32.147
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.9319999999999995
-    - type: map_at_10
-      value: 10.483
-    - type: map_at_100
-      value: 11.97
-    - type: map_at_1000
-      value: 12.171999999999999
-    - type: map_at_3
-      value: 8.477
-    - type: map_at_5
-      value: 9.495000000000001
-    - type: mrr_at_1
-      value: 13.094
-    - type: mrr_at_10
-      value: 21.282
-    - type: mrr_at_100
-      value: 22.556
-    - type: mrr_at_1000
-      value: 22.628999999999998
-    - type: mrr_at_3
-      value: 18.218999999999998
-    - type: mrr_at_5
-      value: 19.900000000000002
-    - type: ndcg_at_1
-      value: 13.094
-    - type: ndcg_at_10
-      value: 15.811
-    - type: ndcg_at_100
-      value: 23.035
-    - type: ndcg_at_1000
-      value: 27.089999999999996
-    - type: ndcg_at_3
-      value: 11.905000000000001
-    - type: ndcg_at_5
-      value: 13.377
-    - type: precision_at_1
-      value: 13.094
-    - type: precision_at_10
-      value: 5.225
-    - type: precision_at_100
-      value: 1.2970000000000002
-    - type: precision_at_1000
-      value: 0.203
-    - type: precision_at_3
-      value: 8.86
-    - type: precision_at_5
-      value: 7.309
-    - type: recall_at_1
-      value: 5.9319999999999995
-    - type: recall_at_10
-      value: 20.305
-    - type: recall_at_100
-      value: 46.314
-    - type: recall_at_1000
-      value: 69.612
-    - type: recall_at_3
-      value: 11.21
-    - type: recall_at_5
-      value: 14.773
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 8.674
-    - type: map_at_10
-      value: 17.822
-    - type: map_at_100
-      value: 24.794
-    - type: map_at_1000
-      value: 26.214
-    - type: map_at_3
-      value: 12.690999999999999
-    - type: map_at_5
-      value: 15.033
-    - type: mrr_at_1
-      value: 61.75000000000001
-    - type: mrr_at_10
-      value: 71.58
-    - type: mrr_at_100
-      value: 71.923
-    - type: mrr_at_1000
-      value: 71.932
-    - type: mrr_at_3
-      value: 70.125
-    - type: mrr_at_5
-      value: 71.038
-    - type: ndcg_at_1
-      value: 51.0
-    - type: ndcg_at_10
-      value: 38.637
-    - type: ndcg_at_100
-      value: 42.398
-    - type: ndcg_at_1000
-      value: 48.962
-    - type: ndcg_at_3
-      value: 43.29
-    - type: ndcg_at_5
-      value: 40.763
-    - type: precision_at_1
-      value: 61.75000000000001
-    - type: precision_at_10
-      value: 30.125
-    - type: precision_at_100
-      value: 9.53
-    - type: precision_at_1000
-      value: 1.9619999999999997
-    - type: precision_at_3
-      value: 45.583
-    - type: precision_at_5
-      value: 38.95
-    - type: recall_at_1
-      value: 8.674
-    - type: recall_at_10
-      value: 23.122
-    - type: recall_at_100
-      value: 47.46
-    - type: recall_at_1000
-      value: 67.662
-    - type: recall_at_3
-      value: 13.946
-    - type: recall_at_5
-      value: 17.768
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 46.86000000000001
-    - type: f1
-      value: 41.343580452760776
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 36.609
-    - type: map_at_10
-      value: 47.552
-    - type: map_at_100
-      value: 48.283
-    - type: map_at_1000
-      value: 48.321
-    - type: map_at_3
-      value: 44.869
-    - type: map_at_5
-      value: 46.509
-    - type: mrr_at_1
-      value: 39.214
-    - type: mrr_at_10
-      value: 50.434999999999995
-    - type: mrr_at_100
-      value: 51.122
-    - type: mrr_at_1000
-      value: 51.151
-    - type: mrr_at_3
-      value: 47.735
-    - type: mrr_at_5
-      value: 49.394
-    - type: ndcg_at_1
-      value: 39.214
-    - type: ndcg_at_10
-      value: 53.52400000000001
-    - type: ndcg_at_100
-      value: 56.997
-    - type: ndcg_at_1000
-      value: 57.975
-    - type: ndcg_at_3
-      value: 48.173
-    - type: ndcg_at_5
-      value: 51.05800000000001
-    - type: precision_at_1
-      value: 39.214
-    - type: precision_at_10
-      value: 7.573
-    - type: precision_at_100
-      value: 0.9440000000000001
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 19.782
-    - type: precision_at_5
-      value: 13.453000000000001
-    - type: recall_at_1
-      value: 36.609
-    - type: recall_at_10
-      value: 69.247
-    - type: recall_at_100
-      value: 84.99600000000001
-    - type: recall_at_1000
-      value: 92.40899999999999
-    - type: recall_at_3
-      value: 54.856
-    - type: recall_at_5
-      value: 61.797000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 16.466
-    - type: map_at_10
-      value: 27.060000000000002
-    - type: map_at_100
-      value: 28.511999999999997
-    - type: map_at_1000
-      value: 28.693
-    - type: map_at_3
-      value: 22.777
-    - type: map_at_5
-      value: 25.086000000000002
-    - type: mrr_at_1
-      value: 32.716
-    - type: mrr_at_10
-      value: 41.593999999999994
-    - type: mrr_at_100
-      value: 42.370000000000005
-    - type: mrr_at_1000
-      value: 42.419000000000004
-    - type: mrr_at_3
-      value: 38.143
-    - type: mrr_at_5
-      value: 40.288000000000004
-    - type: ndcg_at_1
-      value: 32.716
-    - type: ndcg_at_10
-      value: 34.795
-    - type: ndcg_at_100
-      value: 40.58
-    - type: ndcg_at_1000
-      value: 43.993
-    - type: ndcg_at_3
-      value: 29.573
-    - type: ndcg_at_5
-      value: 31.583
-    - type: precision_at_1
-      value: 32.716
-    - type: precision_at_10
-      value: 9.937999999999999
-    - type: precision_at_100
-      value: 1.585
-    - type: precision_at_1000
-      value: 0.22
-    - type: precision_at_3
-      value: 19.496
-    - type: precision_at_5
-      value: 15.247
-    - type: recall_at_1
-      value: 16.466
-    - type: recall_at_10
-      value: 42.886
-    - type: recall_at_100
-      value: 64.724
-    - type: recall_at_1000
-      value: 85.347
-    - type: recall_at_3
-      value: 26.765
-    - type: recall_at_5
-      value: 33.603
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 33.025
-    - type: map_at_10
-      value: 47.343
-    - type: map_at_100
-      value: 48.207
-    - type: map_at_1000
-      value: 48.281
-    - type: map_at_3
-      value: 44.519
-    - type: map_at_5
-      value: 46.217000000000006
-    - type: mrr_at_1
-      value: 66.05
-    - type: mrr_at_10
-      value: 72.94699999999999
-    - type: mrr_at_100
-      value: 73.289
-    - type: mrr_at_1000
-      value: 73.30499999999999
-    - type: mrr_at_3
-      value: 71.686
-    - type: mrr_at_5
-      value: 72.491
-    - type: ndcg_at_1
-      value: 66.05
-    - type: ndcg_at_10
-      value: 56.338
-    - type: ndcg_at_100
-      value: 59.599999999999994
-    - type: ndcg_at_1000
-      value: 61.138000000000005
-    - type: ndcg_at_3
-      value: 52.034000000000006
-    - type: ndcg_at_5
-      value: 54.352000000000004
-    - type: precision_at_1
-      value: 66.05
-    - type: precision_at_10
-      value: 11.693000000000001
-    - type: precision_at_100
-      value: 1.425
-    - type: precision_at_1000
-      value: 0.163
-    - type: precision_at_3
-      value: 32.613
-    - type: precision_at_5
-      value: 21.401999999999997
-    - type: recall_at_1
-      value: 33.025
-    - type: recall_at_10
-      value: 58.467
-    - type: recall_at_100
-      value: 71.242
-    - type: recall_at_1000
-      value: 81.452
-    - type: recall_at_3
-      value: 48.92
-    - type: recall_at_5
-      value: 53.504
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 75.5492
-    - type: ap
-      value: 69.42911637216271
-    - type: f1
-      value: 75.39113704261024
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 23.173
-    - type: map_at_10
-      value: 35.453
-    - type: map_at_100
-      value: 36.573
-    - type: map_at_1000
-      value: 36.620999999999995
-    - type: map_at_3
-      value: 31.655
-    - type: map_at_5
-      value: 33.823
-    - type: mrr_at_1
-      value: 23.868000000000002
-    - type: mrr_at_10
-      value: 36.085
-    - type: mrr_at_100
-      value: 37.15
-    - type: mrr_at_1000
-      value: 37.193
-    - type: mrr_at_3
-      value: 32.376
-    - type: mrr_at_5
-      value: 34.501
-    - type: ndcg_at_1
-      value: 23.854
-    - type: ndcg_at_10
-      value: 42.33
-    - type: ndcg_at_100
-      value: 47.705999999999996
-    - type: ndcg_at_1000
-      value: 48.91
-    - type: ndcg_at_3
-      value: 34.604
-    - type: ndcg_at_5
-      value: 38.473
-    - type: precision_at_1
-      value: 23.854
-    - type: precision_at_10
-      value: 6.639
-    - type: precision_at_100
-      value: 0.932
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 14.685
-    - type: precision_at_5
-      value: 10.782
-    - type: recall_at_1
-      value: 23.173
-    - type: recall_at_10
-      value: 63.441
-    - type: recall_at_100
-      value: 88.25
-    - type: recall_at_1000
-      value: 97.438
-    - type: recall_at_3
-      value: 42.434
-    - type: recall_at_5
-      value: 51.745
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 92.05426356589147
-    - type: f1
-      value: 91.88068588063942
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 73.23985408116735
-    - type: f1
-      value: 55.858906745287506
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 72.21923335574984
-    - type: f1
-      value: 70.0174116204253
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 75.77673167451245
-    - type: f1
-      value: 75.44811354778666
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 31.340414710728737
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 28.196676760061578
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 29.564149683482206
-    - type: mrr
-      value: 30.28995474250486
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.93
-    - type: map_at_10
-      value: 12.828000000000001
-    - type: map_at_100
-      value: 15.501000000000001
-    - type: map_at_1000
-      value: 16.791
-    - type: map_at_3
-      value: 9.727
-    - type: map_at_5
-      value: 11.318999999999999
-    - type: mrr_at_1
-      value: 47.678
-    - type: mrr_at_10
-      value: 55.893
-    - type: mrr_at_100
-      value: 56.491
-    - type: mrr_at_1000
-      value: 56.53
-    - type: mrr_at_3
-      value: 54.386
-    - type: mrr_at_5
-      value: 55.516
-    - type: ndcg_at_1
-      value: 45.975
-    - type: ndcg_at_10
-      value: 33.928999999999995
-    - type: ndcg_at_100
-      value: 30.164
-    - type: ndcg_at_1000
-      value: 38.756
-    - type: ndcg_at_3
-      value: 41.077000000000005
-    - type: ndcg_at_5
-      value: 38.415
-    - type: precision_at_1
-      value: 47.678
-    - type: precision_at_10
-      value: 24.365000000000002
-    - type: precision_at_100
-      value: 7.344
-    - type: precision_at_1000
-      value: 1.994
-    - type: precision_at_3
-      value: 38.184000000000005
-    - type: precision_at_5
-      value: 33.003
-    - type: recall_at_1
-      value: 5.93
-    - type: recall_at_10
-      value: 16.239
-    - type: recall_at_100
-      value: 28.782999999999998
-    - type: recall_at_1000
-      value: 60.11
-    - type: recall_at_3
-      value: 10.700999999999999
-    - type: recall_at_5
-      value: 13.584
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 36.163000000000004
-    - type: map_at_10
-      value: 51.520999999999994
-    - type: map_at_100
-      value: 52.449
-    - type: map_at_1000
-      value: 52.473000000000006
-    - type: map_at_3
-      value: 47.666
-    - type: map_at_5
-      value: 50.043000000000006
-    - type: mrr_at_1
-      value: 40.266999999999996
-    - type: mrr_at_10
-      value: 54.074
-    - type: mrr_at_100
-      value: 54.722
-    - type: mrr_at_1000
-      value: 54.739000000000004
-    - type: mrr_at_3
-      value: 51.043000000000006
-    - type: mrr_at_5
-      value: 52.956
-    - type: ndcg_at_1
-      value: 40.238
-    - type: ndcg_at_10
-      value: 58.73199999999999
-    - type: ndcg_at_100
-      value: 62.470000000000006
-    - type: ndcg_at_1000
-      value: 63.083999999999996
-    - type: ndcg_at_3
-      value: 51.672
-    - type: ndcg_at_5
-      value: 55.564
-    - type: precision_at_1
-      value: 40.238
-    - type: precision_at_10
-      value: 9.279
-    - type: precision_at_100
-      value: 1.139
-    - type: precision_at_1000
-      value: 0.12
-    - type: precision_at_3
-      value: 23.078000000000003
-    - type: precision_at_5
-      value: 16.176
-    - type: recall_at_1
-      value: 36.163000000000004
-    - type: recall_at_10
-      value: 77.88199999999999
-    - type: recall_at_100
-      value: 93.83399999999999
-    - type: recall_at_1000
-      value: 98.465
-    - type: recall_at_3
-      value: 59.857000000000006
-    - type: recall_at_5
-      value: 68.73599999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 70.344
-    - type: map_at_10
-      value: 83.907
-    - type: map_at_100
-      value: 84.536
-    - type: map_at_1000
-      value: 84.557
-    - type: map_at_3
-      value: 80.984
-    - type: map_at_5
-      value: 82.844
-    - type: mrr_at_1
-      value: 81.02000000000001
-    - type: mrr_at_10
-      value: 87.158
-    - type: mrr_at_100
-      value: 87.268
-    - type: mrr_at_1000
-      value: 87.26899999999999
-    - type: mrr_at_3
-      value: 86.17
-    - type: mrr_at_5
-      value: 86.87
-    - type: ndcg_at_1
-      value: 81.02000000000001
-    - type: ndcg_at_10
-      value: 87.70700000000001
-    - type: ndcg_at_100
-      value: 89.004
-    - type: ndcg_at_1000
-      value: 89.139
-    - type: ndcg_at_3
-      value: 84.841
-    - type: ndcg_at_5
-      value: 86.455
-    - type: precision_at_1
-      value: 81.02000000000001
-    - type: precision_at_10
-      value: 13.248999999999999
-    - type: precision_at_100
-      value: 1.516
-    - type: precision_at_1000
-      value: 0.156
-    - type: precision_at_3
-      value: 36.963
-    - type: precision_at_5
-      value: 24.33
-    - type: recall_at_1
-      value: 70.344
-    - type: recall_at_10
-      value: 94.75099999999999
-    - type: recall_at_100
-      value: 99.30499999999999
-    - type: recall_at_1000
-      value: 99.928
-    - type: recall_at_3
-      value: 86.506
-    - type: recall_at_5
-      value: 91.083
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 42.873718018378305
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 56.39477366450528
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 3.868
-    - type: map_at_10
-      value: 9.611
-    - type: map_at_100
-      value: 11.087
-    - type: map_at_1000
-      value: 11.332
-    - type: map_at_3
-      value: 6.813
-    - type: map_at_5
-      value: 8.233
-    - type: mrr_at_1
-      value: 19.0
-    - type: mrr_at_10
-      value: 28.457
-    - type: mrr_at_100
-      value: 29.613
-    - type: mrr_at_1000
-      value: 29.695
-    - type: mrr_at_3
-      value: 25.55
-    - type: mrr_at_5
-      value: 27.29
-    - type: ndcg_at_1
-      value: 19.0
-    - type: ndcg_at_10
-      value: 16.419
-    - type: ndcg_at_100
-      value: 22.817999999999998
-    - type: ndcg_at_1000
-      value: 27.72
-    - type: ndcg_at_3
-      value: 15.379000000000001
-    - type: ndcg_at_5
-      value: 13.645
-    - type: precision_at_1
-      value: 19.0
-    - type: precision_at_10
-      value: 8.540000000000001
-    - type: precision_at_100
-      value: 1.7819999999999998
-    - type: precision_at_1000
-      value: 0.297
-    - type: precision_at_3
-      value: 14.267
-    - type: precision_at_5
-      value: 12.04
-    - type: recall_at_1
-      value: 3.868
-    - type: recall_at_10
-      value: 17.288
-    - type: recall_at_100
-      value: 36.144999999999996
-    - type: recall_at_1000
-      value: 60.199999999999996
-    - type: recall_at_3
-      value: 8.688
-    - type: recall_at_5
-      value: 12.198
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_pearson
-      value: 83.96614722598582
-    - type: cos_sim_spearman
-      value: 78.9003023008781
-    - type: euclidean_pearson
-      value: 81.01829384436505
-    - type: euclidean_spearman
-      value: 78.93248416788914
-    - type: manhattan_pearson
-      value: 81.1665428926402
-    - type: manhattan_spearman
-      value: 78.93264116287453
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_pearson
-      value: 83.54613363895993
-    - type: cos_sim_spearman
-      value: 75.1883451602451
-    - type: euclidean_pearson
-      value: 79.70320886899894
-    - type: euclidean_spearman
-      value: 74.5917140136796
-    - type: manhattan_pearson
-      value: 79.82157067185999
-    - type: manhattan_spearman
-      value: 74.74185720594735
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_pearson
-      value: 81.30430156721782
-    - type: cos_sim_spearman
-      value: 81.79962989974364
-    - type: euclidean_pearson
-      value: 80.89058823224924
-    - type: euclidean_spearman
-      value: 81.35929372984597
-    - type: manhattan_pearson
-      value: 81.12204370487478
-    - type: manhattan_spearman
-      value: 81.6248963282232
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_pearson
-      value: 81.13064504403134
-    - type: cos_sim_spearman
-      value: 78.48371403924872
-    - type: euclidean_pearson
-      value: 80.16794919665591
-    - type: euclidean_spearman
-      value: 78.29216082221699
-    - type: manhattan_pearson
-      value: 80.22308565207301
-    - type: manhattan_spearman
-      value: 78.37829229948022
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_pearson
-      value: 86.52918899541099
-    - type: cos_sim_spearman
-      value: 87.49276894673142
-    - type: euclidean_pearson
-      value: 86.77440570164254
-    - type: euclidean_spearman
-      value: 87.5753295736756
-    - type: manhattan_pearson
-      value: 86.86098573892133
-    - type: manhattan_spearman
-      value: 87.65848591821947
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_pearson
-      value: 82.86805307244882
-    - type: cos_sim_spearman
-      value: 84.58066253757511
-    - type: euclidean_pearson
-      value: 84.38377000876991
-    - type: euclidean_spearman
-      value: 85.1837278784528
-    - type: manhattan_pearson
-      value: 84.41903291363842
-    - type: manhattan_spearman
-      value: 85.19023736251052
-  - 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: 86.77218560282436
-    - type: cos_sim_spearman
-      value: 87.94243515296604
-    - type: euclidean_pearson
-      value: 88.22800939214864
-    - type: euclidean_spearman
-      value: 87.91106839439841
-    - type: manhattan_pearson
-      value: 88.17063269848741
-    - type: manhattan_spearman
-      value: 87.72751904126062
-  - 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: 60.40731554300387
-    - type: cos_sim_spearman
-      value: 63.76300532966479
-    - type: euclidean_pearson
-      value: 62.94727878229085
-    - type: euclidean_spearman
-      value: 63.678039531461216
-    - type: manhattan_pearson
-      value: 63.00661039863549
-    - type: manhattan_spearman
-      value: 63.6282591984376
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_pearson
-      value: 84.92731569745344
-    - type: cos_sim_spearman
-      value: 86.36336704300167
-    - type: euclidean_pearson
-      value: 86.09122224841195
-    - type: euclidean_spearman
-      value: 86.2116149319238
-    - type: manhattan_pearson
-      value: 86.07879456717032
-    - type: manhattan_spearman
-      value: 86.2022069635119
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 79.75976311752326
-    - type: mrr
-      value: 94.15782837351466
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 51.193999999999996
-    - type: map_at_10
-      value: 61.224999999999994
-    - type: map_at_100
-      value: 62.031000000000006
-    - type: map_at_1000
-      value: 62.066
-    - type: map_at_3
-      value: 59.269000000000005
-    - type: map_at_5
-      value: 60.159
-    - type: mrr_at_1
-      value: 53.667
-    - type: mrr_at_10
-      value: 62.74999999999999
-    - type: mrr_at_100
-      value: 63.39399999999999
-    - type: mrr_at_1000
-      value: 63.425
-    - type: mrr_at_3
-      value: 61.389
-    - type: mrr_at_5
-      value: 61.989000000000004
-    - type: ndcg_at_1
-      value: 53.667
-    - type: ndcg_at_10
-      value: 65.596
-    - type: ndcg_at_100
-      value: 68.906
-    - type: ndcg_at_1000
-      value: 69.78999999999999
-    - type: ndcg_at_3
-      value: 62.261
-    - type: ndcg_at_5
-      value: 63.453
-    - type: precision_at_1
-      value: 53.667
-    - type: precision_at_10
-      value: 8.667
-    - type: precision_at_100
-      value: 1.04
-    - type: precision_at_1000
-      value: 0.11100000000000002
-    - type: precision_at_3
-      value: 24.556
-    - type: precision_at_5
-      value: 15.6
-    - type: recall_at_1
-      value: 51.193999999999996
-    - type: recall_at_10
-      value: 77.156
-    - type: recall_at_100
-      value: 91.43299999999999
-    - type: recall_at_1000
-      value: 98.333
-    - type: recall_at_3
-      value: 67.994
-    - type: recall_at_5
-      value: 71.14399999999999
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.81485148514851
-    - type: cos_sim_ap
-      value: 95.28896513388551
-    - type: cos_sim_f1
-      value: 90.43478260869566
-    - type: cos_sim_precision
-      value: 92.56544502617801
-    - type: cos_sim_recall
-      value: 88.4
-    - type: dot_accuracy
-      value: 99.30594059405941
-    - type: dot_ap
-      value: 61.6432597455472
-    - type: dot_f1
-      value: 59.46481665014866
-    - type: dot_precision
-      value: 58.93909626719057
-    - type: dot_recall
-      value: 60.0
-    - type: euclidean_accuracy
-      value: 99.81980198019802
-    - type: euclidean_ap
-      value: 95.21411049527
-    - type: euclidean_f1
-      value: 91.06090373280944
-    - type: euclidean_precision
-      value: 89.47876447876449
-    - type: euclidean_recall
-      value: 92.7
-    - type: manhattan_accuracy
-      value: 99.81782178217821
-    - type: manhattan_ap
-      value: 95.32449994414968
-    - type: manhattan_f1
-      value: 90.86395233366436
-    - type: manhattan_precision
-      value: 90.23668639053254
-    - type: manhattan_recall
-      value: 91.5
-    - type: max_accuracy
-      value: 99.81980198019802
-    - type: max_ap
-      value: 95.32449994414968
-    - type: max_f1
-      value: 91.06090373280944
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 59.08045614613064
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 30.297802606804748
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 49.12801740706292
-    - type: mrr
-      value: 50.05592956879722
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 23.380995453661917
-    - type: cos_sim_spearman
-      value: 24.941761858688917
-    - type: dot_pearson
-      value: 24.930577961642413
-    - type: dot_spearman
-      value: 24.804715835064492
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.243
-    - type: map_at_10
-      value: 1.886
-    - type: map_at_100
-      value: 10.040000000000001
-    - type: map_at_1000
-      value: 23.768
-    - type: map_at_3
-      value: 0.674
-    - type: map_at_5
-      value: 1.079
-    - type: mrr_at_1
-      value: 88.0
-    - type: mrr_at_10
-      value: 93.667
-    - type: mrr_at_100
-      value: 93.667
-    - type: mrr_at_1000
-      value: 93.667
-    - type: mrr_at_3
-      value: 93.667
-    - type: mrr_at_5
-      value: 93.667
-    - type: ndcg_at_1
-      value: 83.0
-    - type: ndcg_at_10
-      value: 76.777
-    - type: ndcg_at_100
-      value: 55.153
-    - type: ndcg_at_1000
-      value: 47.912
-    - type: ndcg_at_3
-      value: 81.358
-    - type: ndcg_at_5
-      value: 80.74799999999999
-    - type: precision_at_1
-      value: 88.0
-    - type: precision_at_10
-      value: 80.80000000000001
-    - type: precision_at_100
-      value: 56.02
-    - type: precision_at_1000
-      value: 21.51
-    - type: precision_at_3
-      value: 86.0
-    - type: precision_at_5
-      value: 86.0
-    - type: recall_at_1
-      value: 0.243
-    - type: recall_at_10
-      value: 2.0869999999999997
-    - type: recall_at_100
-      value: 13.014000000000001
-    - type: recall_at_1000
-      value: 44.433
-    - type: recall_at_3
-      value: 0.6910000000000001
-    - type: recall_at_5
-      value: 1.1440000000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 3.066
-    - type: map_at_10
-      value: 10.615
-    - type: map_at_100
-      value: 16.463
-    - type: map_at_1000
-      value: 17.815
-    - type: map_at_3
-      value: 5.7860000000000005
-    - type: map_at_5
-      value: 7.353999999999999
-    - type: mrr_at_1
-      value: 38.775999999999996
-    - type: mrr_at_10
-      value: 53.846000000000004
-    - type: mrr_at_100
-      value: 54.37
-    - type: mrr_at_1000
-      value: 54.37
-    - type: mrr_at_3
-      value: 48.980000000000004
-    - type: mrr_at_5
-      value: 51.735
-    - type: ndcg_at_1
-      value: 34.694
-    - type: ndcg_at_10
-      value: 26.811
-    - type: ndcg_at_100
-      value: 37.342999999999996
-    - type: ndcg_at_1000
-      value: 47.964
-    - type: ndcg_at_3
-      value: 30.906
-    - type: ndcg_at_5
-      value: 27.77
-    - type: precision_at_1
-      value: 38.775999999999996
-    - type: precision_at_10
-      value: 23.878
-    - type: precision_at_100
-      value: 7.632999999999999
-    - type: precision_at_1000
-      value: 1.469
-    - type: precision_at_3
-      value: 31.973000000000003
-    - type: precision_at_5
-      value: 26.939
-    - type: recall_at_1
-      value: 3.066
-    - type: recall_at_10
-      value: 17.112
-    - type: recall_at_100
-      value: 47.723
-    - type: recall_at_1000
-      value: 79.50500000000001
-    - type: recall_at_3
-      value: 6.825
-    - type: recall_at_5
-      value: 9.584
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 72.76460000000002
-    - type: ap
-      value: 14.944240012137053
-    - type: f1
-      value: 55.89805777266571
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 63.30503678551217
-    - type: f1
-      value: 63.57492701921179
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 37.51066495006874
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 86.07021517553794
-    - type: cos_sim_ap
-      value: 74.15520712370555
-    - type: cos_sim_f1
-      value: 68.64321608040201
-    - type: cos_sim_precision
-      value: 65.51558752997602
-    - type: cos_sim_recall
-      value: 72.0844327176781
-    - type: dot_accuracy
-      value: 80.23484532395541
-    - type: dot_ap
-      value: 54.298763810214176
-    - type: dot_f1
-      value: 53.22254659779924
-    - type: dot_precision
-      value: 46.32525410476936
-    - type: dot_recall
-      value: 62.532981530343015
-    - type: euclidean_accuracy
-      value: 86.04637301066937
-    - type: euclidean_ap
-      value: 73.85333854233123
-    - type: euclidean_f1
-      value: 68.77723660599845
-    - type: euclidean_precision
-      value: 66.87437686939182
-    - type: euclidean_recall
-      value: 70.79155672823218
-    - type: manhattan_accuracy
-      value: 85.98676759849795
-    - type: manhattan_ap
-      value: 73.56016090035973
-    - type: manhattan_f1
-      value: 68.48878539036647
-    - type: manhattan_precision
-      value: 63.9505607690547
-    - type: manhattan_recall
-      value: 73.7203166226913
-    - type: max_accuracy
-      value: 86.07021517553794
-    - type: max_ap
-      value: 74.15520712370555
-    - type: max_f1
-      value: 68.77723660599845
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.92769821865176
-    - type: cos_sim_ap
-      value: 85.78879502899773
-    - type: cos_sim_f1
-      value: 78.14414083990464
-    - type: cos_sim_precision
-      value: 74.61651607480563
-    - type: cos_sim_recall
-      value: 82.0218663381583
-    - type: dot_accuracy
-      value: 84.95750378390964
-    - type: dot_ap
-      value: 75.80219641857563
-    - type: dot_f1
-      value: 70.13966179585681
-    - type: dot_precision
-      value: 65.71140262361251
-    - type: dot_recall
-      value: 75.20788420080073
-    - type: euclidean_accuracy
-      value: 88.93546008460433
-    - type: euclidean_ap
-      value: 85.72056428301667
-    - type: euclidean_f1
-      value: 78.14387902598124
-    - type: euclidean_precision
-      value: 75.3376688344172
-    - type: euclidean_recall
-      value: 81.16723129042192
-    - type: manhattan_accuracy
-      value: 88.96262661543835
-    - type: manhattan_ap
-      value: 85.76605136314335
-    - type: manhattan_f1
-      value: 78.26696165191743
-    - type: manhattan_precision
-      value: 75.0990659496179
-    - type: manhattan_recall
-      value: 81.71388974437943
-    - type: max_accuracy
-      value: 88.96262661543835
-    - type: max_ap
-      value: 85.78879502899773
-    - type: max_f1
-      value: 78.26696165191743
----