Update README.md

README.md

@@ -23,2501 +23,6 @@ tags:
 - fever
 - hotpot_qa
 - mteb
-model-index:
-- name: LLM2Vec-Sheared-LLaMA-unsup-simcse-mean
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 72.92537313432835
-    - type: ap
-      value: 36.6875749512053
-    - type: f1
-      value: 67.36274146169845
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 74.282675
-    - type: ap
-      value: 69.15441866642587
-    - type: f1
-      value: 74.13028166370813
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 36.136
-    - type: f1
-      value: 35.840498320506235
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.407999999999998
-    - type: map_at_10
-      value: 35.474
-    - type: map_at_100
-      value: 36.653999999999996
-    - type: map_at_1000
-      value: 36.68
-    - type: map_at_3
-      value: 30.974
-    - type: map_at_5
-      value: 33.265
-    - type: mrr_at_1
-      value: 22.119
-    - type: mrr_at_10
-      value: 35.714
-    - type: mrr_at_100
-      value: 36.895
-    - type: mrr_at_1000
-      value: 36.921
-    - type: mrr_at_3
-      value: 31.2
-    - type: mrr_at_5
-      value: 33.518
-    - type: ndcg_at_1
-      value: 21.407999999999998
-    - type: ndcg_at_10
-      value: 43.644
-    - type: ndcg_at_100
-      value: 49.035000000000004
-    - type: ndcg_at_1000
-      value: 49.685
-    - type: ndcg_at_3
-      value: 34.174
-    - type: ndcg_at_5
-      value: 38.288
-    - type: precision_at_1
-      value: 21.407999999999998
-    - type: precision_at_10
-      value: 6.999
-    - type: precision_at_100
-      value: 0.9440000000000001
-    - type: precision_at_1000
-      value: 0.099
-    - type: precision_at_3
-      value: 14.485999999999999
-    - type: precision_at_5
-      value: 10.683
-    - type: recall_at_1
-      value: 21.407999999999998
-    - type: recall_at_10
-      value: 69.986
-    - type: recall_at_100
-      value: 94.381
-    - type: recall_at_1000
-      value: 99.431
-    - type: recall_at_3
-      value: 43.457
-    - type: recall_at_5
-      value: 53.413999999999994
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 42.915010245699904
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 35.19568272188972
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 52.696972763822615
-    - type: mrr
-      value: 65.87136701402629
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_spearman
-      value: 75.12038636775851
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 78.99675324675324
-    - type: f1
-      value: 78.90527329824852
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 35.02170435970243
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 27.208216971540782
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/android
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 16.432
-    - type: map_at_10
-      value: 23.769000000000002
-    - type: map_at_100
-      value: 25.038
-    - type: map_at_1000
-      value: 25.208000000000002
-    - type: map_at_3
-      value: 21.532999999999998
-    - type: map_at_5
-      value: 22.668
-    - type: mrr_at_1
-      value: 21.316
-    - type: mrr_at_10
-      value: 28.89
-    - type: mrr_at_100
-      value: 29.799999999999997
-    - type: mrr_at_1000
-      value: 29.887999999999998
-    - type: mrr_at_3
-      value: 26.705000000000002
-    - type: mrr_at_5
-      value: 27.864
-    - type: ndcg_at_1
-      value: 21.316
-    - type: ndcg_at_10
-      value: 28.656
-    - type: ndcg_at_100
-      value: 34.405
-    - type: ndcg_at_1000
-      value: 37.771
-    - type: ndcg_at_3
-      value: 24.98
-    - type: ndcg_at_5
-      value: 26.384999999999998
-    - type: precision_at_1
-      value: 21.316
-    - type: precision_at_10
-      value: 5.8229999999999995
-    - type: precision_at_100
-      value: 1.157
-    - type: precision_at_1000
-      value: 0.181
-    - type: precision_at_3
-      value: 12.446
-    - type: precision_at_5
-      value: 8.984
-    - type: recall_at_1
-      value: 16.432
-    - type: recall_at_10
-      value: 37.696000000000005
-    - type: recall_at_100
-      value: 63.198
-    - type: recall_at_1000
-      value: 86.651
-    - type: recall_at_3
-      value: 26.651000000000003
-    - type: recall_at_5
-      value: 30.901
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/english
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 16.106
-    - type: map_at_10
-      value: 21.770999999999997
-    - type: map_at_100
-      value: 22.538
-    - type: map_at_1000
-      value: 22.656000000000002
-    - type: map_at_3
-      value: 19.918
-    - type: map_at_5
-      value: 20.957
-    - type: mrr_at_1
-      value: 21.083
-    - type: mrr_at_10
-      value: 26.502
-    - type: mrr_at_100
-      value: 27.161
-    - type: mrr_at_1000
-      value: 27.234
-    - type: mrr_at_3
-      value: 24.735
-    - type: mrr_at_5
-      value: 25.753999999999998
-    - type: ndcg_at_1
-      value: 21.083
-    - type: ndcg_at_10
-      value: 25.625999999999998
-    - type: ndcg_at_100
-      value: 29.152
-    - type: ndcg_at_1000
-      value: 32.025
-    - type: ndcg_at_3
-      value: 22.721
-    - type: ndcg_at_5
-      value: 24.029
-    - type: precision_at_1
-      value: 21.083
-    - type: precision_at_10
-      value: 4.8919999999999995
-    - type: precision_at_100
-      value: 0.844
-    - type: precision_at_1000
-      value: 0.13699999999999998
-    - type: precision_at_3
-      value: 11.104
-    - type: precision_at_5
-      value: 7.987
-    - type: recall_at_1
-      value: 16.106
-    - type: recall_at_10
-      value: 32.385999999999996
-    - type: recall_at_100
-      value: 47.961999999999996
-    - type: recall_at_1000
-      value: 67.63900000000001
-    - type: recall_at_3
-      value: 23.568
-    - type: recall_at_5
-      value: 27.326
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/gaming
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.517
-    - type: map_at_10
-      value: 29.593999999999998
-    - type: map_at_100
-      value: 30.695
-    - type: map_at_1000
-      value: 30.803000000000004
-    - type: map_at_3
-      value: 27.592
-    - type: map_at_5
-      value: 28.768
-    - type: mrr_at_1
-      value: 26.27
-    - type: mrr_at_10
-      value: 33.076
-    - type: mrr_at_100
-      value: 33.998
-    - type: mrr_at_1000
-      value: 34.073
-    - type: mrr_at_3
-      value: 31.223
-    - type: mrr_at_5
-      value: 32.257000000000005
-    - type: ndcg_at_1
-      value: 26.27
-    - type: ndcg_at_10
-      value: 33.726
-    - type: ndcg_at_100
-      value: 39.079
-    - type: ndcg_at_1000
-      value: 41.762
-    - type: ndcg_at_3
-      value: 30.064
-    - type: ndcg_at_5
-      value: 31.858999999999998
-    - type: precision_at_1
-      value: 26.27
-    - type: precision_at_10
-      value: 5.448
-    - type: precision_at_100
-      value: 0.898
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 13.417000000000002
-    - type: precision_at_5
-      value: 9.317
-    - type: recall_at_1
-      value: 22.517
-    - type: recall_at_10
-      value: 42.814
-    - type: recall_at_100
-      value: 67.037
-    - type: recall_at_1000
-      value: 86.89099999999999
-    - type: recall_at_3
-      value: 33.041
-    - type: recall_at_5
-      value: 37.389
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/gis
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 7.681
-    - type: map_at_10
-      value: 10.655000000000001
-    - type: map_at_100
-      value: 11.274000000000001
-    - type: map_at_1000
-      value: 11.381
-    - type: map_at_3
-      value: 9.793000000000001
-    - type: map_at_5
-      value: 10.202
-    - type: mrr_at_1
-      value: 8.248999999999999
-    - type: mrr_at_10
-      value: 11.453000000000001
-    - type: mrr_at_100
-      value: 12.074
-    - type: mrr_at_1000
-      value: 12.174
-    - type: mrr_at_3
-      value: 10.452
-    - type: mrr_at_5
-      value: 10.989
-    - type: ndcg_at_1
-      value: 8.248999999999999
-    - type: ndcg_at_10
-      value: 12.467
-    - type: ndcg_at_100
-      value: 15.942
-    - type: ndcg_at_1000
-      value: 19.378999999999998
-    - type: ndcg_at_3
-      value: 10.631
-    - type: ndcg_at_5
-      value: 11.411
-    - type: precision_at_1
-      value: 8.248999999999999
-    - type: precision_at_10
-      value: 1.966
-    - type: precision_at_100
-      value: 0.40099999999999997
-    - type: precision_at_1000
-      value: 0.075
-    - type: precision_at_3
-      value: 4.444
-    - type: precision_at_5
-      value: 3.186
-    - type: recall_at_1
-      value: 7.681
-    - type: recall_at_10
-      value: 17.302
-    - type: recall_at_100
-      value: 34.014
-    - type: recall_at_1000
-      value: 61.207
-    - type: recall_at_3
-      value: 12.389
-    - type: recall_at_5
-      value: 14.158999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/mathematica
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 3.868
-    - type: map_at_10
-      value: 6.281000000000001
-    - type: map_at_100
-      value: 6.903
-    - type: map_at_1000
-      value: 7.038
-    - type: map_at_3
-      value: 5.234
-    - type: map_at_5
-      value: 5.685
-    - type: mrr_at_1
-      value: 5.1
-    - type: mrr_at_10
-      value: 8.148
-    - type: mrr_at_100
-      value: 8.846
-    - type: mrr_at_1000
-      value: 8.963000000000001
-    - type: mrr_at_3
-      value: 6.944
-    - type: mrr_at_5
-      value: 7.498
-    - type: ndcg_at_1
-      value: 5.1
-    - type: ndcg_at_10
-      value: 8.405999999999999
-    - type: ndcg_at_100
-      value: 12.014
-    - type: ndcg_at_1000
-      value: 15.956999999999999
-    - type: ndcg_at_3
-      value: 6.22
-    - type: ndcg_at_5
-      value: 6.962
-    - type: precision_at_1
-      value: 5.1
-    - type: precision_at_10
-      value: 1.8159999999999998
-    - type: precision_at_100
-      value: 0.437
-    - type: precision_at_1000
-      value: 0.09
-    - type: precision_at_3
-      value: 3.1510000000000002
-    - type: precision_at_5
-      value: 2.463
-    - type: recall_at_1
-      value: 3.868
-    - type: recall_at_10
-      value: 13.319
-    - type: recall_at_100
-      value: 29.985
-    - type: recall_at_1000
-      value: 59.245999999999995
-    - type: recall_at_3
-      value: 7.0809999999999995
-    - type: recall_at_5
-      value: 8.914
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/physics
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 13.091
-    - type: map_at_10
-      value: 18.701999999999998
-    - type: map_at_100
-      value: 19.897000000000002
-    - type: map_at_1000
-      value: 20.044
-    - type: map_at_3
-      value: 17.041999999999998
-    - type: map_at_5
-      value: 17.943
-    - type: mrr_at_1
-      value: 16.939
-    - type: mrr_at_10
-      value: 23.038
-    - type: mrr_at_100
-      value: 24.029
-    - type: mrr_at_1000
-      value: 24.12
-    - type: mrr_at_3
-      value: 21.221999999999998
-    - type: mrr_at_5
-      value: 22.198999999999998
-    - type: ndcg_at_1
-      value: 16.939
-    - type: ndcg_at_10
-      value: 22.566
-    - type: ndcg_at_100
-      value: 28.364
-    - type: ndcg_at_1000
-      value: 31.646
-    - type: ndcg_at_3
-      value: 19.646
-    - type: ndcg_at_5
-      value: 20.915
-    - type: precision_at_1
-      value: 16.939
-    - type: precision_at_10
-      value: 4.340999999999999
-    - type: precision_at_100
-      value: 0.882
-    - type: precision_at_1000
-      value: 0.13799999999999998
-    - type: precision_at_3
-      value: 9.785
-    - type: precision_at_5
-      value: 6.93
-    - type: recall_at_1
-      value: 13.091
-    - type: recall_at_10
-      value: 30.022
-    - type: recall_at_100
-      value: 55.579
-    - type: recall_at_1000
-      value: 78.14
-    - type: recall_at_3
-      value: 21.4
-    - type: recall_at_5
-      value: 25.020999999999997
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/programmers
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 11.315999999999999
-    - type: map_at_10
-      value: 16.191
-    - type: map_at_100
-      value: 17.116
-    - type: map_at_1000
-      value: 17.262
-    - type: map_at_3
-      value: 14.302999999999999
-    - type: map_at_5
-      value: 15.278
-    - type: mrr_at_1
-      value: 14.269000000000002
-    - type: mrr_at_10
-      value: 19.409000000000002
-    - type: mrr_at_100
-      value: 20.298
-    - type: mrr_at_1000
-      value: 20.393
-    - type: mrr_at_3
-      value: 17.504
-    - type: mrr_at_5
-      value: 18.423000000000002
-    - type: ndcg_at_1
-      value: 14.269000000000002
-    - type: ndcg_at_10
-      value: 19.735
-    - type: ndcg_at_100
-      value: 24.582
-    - type: ndcg_at_1000
-      value: 28.337
-    - type: ndcg_at_3
-      value: 16.220000000000002
-    - type: ndcg_at_5
-      value: 17.644000000000002
-    - type: precision_at_1
-      value: 14.269000000000002
-    - type: precision_at_10
-      value: 3.721
-    - type: precision_at_100
-      value: 0.752
-    - type: precision_at_1000
-      value: 0.129
-    - type: precision_at_3
-      value: 7.800999999999999
-    - type: precision_at_5
-      value: 5.753
-    - type: recall_at_1
-      value: 11.315999999999999
-    - type: recall_at_10
-      value: 27.693
-    - type: recall_at_100
-      value: 49.265
-    - type: recall_at_1000
-      value: 76.291
-    - type: recall_at_3
-      value: 17.593
-    - type: recall_at_5
-      value: 21.368000000000002
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 11.131583333333332
-    - type: map_at_10
-      value: 15.4605
-    - type: map_at_100
-      value: 16.3075
-    - type: map_at_1000
-      value: 16.4375
-    - type: map_at_3
-      value: 13.995833333333332
-    - type: map_at_5
-      value: 14.783666666666667
-    - type: mrr_at_1
-      value: 13.805833333333334
-    - type: mrr_at_10
-      value: 18.405749999999998
-    - type: mrr_at_100
-      value: 19.17516666666667
-    - type: mrr_at_1000
-      value: 19.265833333333333
-    - type: mrr_at_3
-      value: 16.892416666666666
-    - type: mrr_at_5
-      value: 17.71058333333333
-    - type: ndcg_at_1
-      value: 13.805833333333334
-    - type: ndcg_at_10
-      value: 18.500666666666664
-    - type: ndcg_at_100
-      value: 22.78191666666667
-    - type: ndcg_at_1000
-      value: 26.095583333333334
-    - type: ndcg_at_3
-      value: 15.846916666666663
-    - type: ndcg_at_5
-      value: 17.004250000000003
-    - type: precision_at_1
-      value: 13.805833333333334
-    - type: precision_at_10
-      value: 3.4233333333333325
-    - type: precision_at_100
-      value: 0.6828333333333333
-    - type: precision_at_1000
-      value: 0.11641666666666667
-    - type: precision_at_3
-      value: 7.511749999999999
-    - type: precision_at_5
-      value: 5.440916666666666
-    - type: recall_at_1
-      value: 11.131583333333332
-    - type: recall_at_10
-      value: 24.794166666666666
-    - type: recall_at_100
-      value: 44.356
-    - type: recall_at_1000
-      value: 68.71899999999998
-    - type: recall_at_3
-      value: 17.145583333333335
-    - type: recall_at_5
-      value: 20.229083333333335
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/stats
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 7.5520000000000005
-    - type: map_at_10
-      value: 10.355
-    - type: map_at_100
-      value: 10.875
-    - type: map_at_1000
-      value: 10.972999999999999
-    - type: map_at_3
-      value: 9.341000000000001
-    - type: map_at_5
-      value: 9.969
-    - type: mrr_at_1
-      value: 9.049
-    - type: mrr_at_10
-      value: 12.002
-    - type: mrr_at_100
-      value: 12.55
-    - type: mrr_at_1000
-      value: 12.635
-    - type: mrr_at_3
-      value: 11.12
-    - type: mrr_at_5
-      value: 11.626
-    - type: ndcg_at_1
-      value: 9.049
-    - type: ndcg_at_10
-      value: 12.241
-    - type: ndcg_at_100
-      value: 15.231
-    - type: ndcg_at_1000
-      value: 18.265
-    - type: ndcg_at_3
-      value: 10.424999999999999
-    - type: ndcg_at_5
-      value: 11.360000000000001
-    - type: precision_at_1
-      value: 9.049
-    - type: precision_at_10
-      value: 2.147
-    - type: precision_at_100
-      value: 0.411
-    - type: precision_at_1000
-      value: 0.073
-    - type: precision_at_3
-      value: 4.755
-    - type: precision_at_5
-      value: 3.558
-    - type: recall_at_1
-      value: 7.5520000000000005
-    - type: recall_at_10
-      value: 16.448999999999998
-    - type: recall_at_100
-      value: 30.505
-    - type: recall_at_1000
-      value: 54.435
-    - type: recall_at_3
-      value: 11.366
-    - type: recall_at_5
-      value: 13.758999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/tex
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.954000000000001
-    - type: map_at_10
-      value: 8.229000000000001
-    - type: map_at_100
-      value: 8.694
-    - type: map_at_1000
-      value: 8.788
-    - type: map_at_3
-      value: 7.5
-    - type: map_at_5
-      value: 7.856000000000001
-    - type: mrr_at_1
-      value: 7.983
-    - type: mrr_at_10
-      value: 10.833
-    - type: mrr_at_100
-      value: 11.324
-    - type: mrr_at_1000
-      value: 11.404
-    - type: mrr_at_3
-      value: 9.911
-    - type: mrr_at_5
-      value: 10.401
-    - type: ndcg_at_1
-      value: 7.983
-    - type: ndcg_at_10
-      value: 10.126
-    - type: ndcg_at_100
-      value: 12.702
-    - type: ndcg_at_1000
-      value: 15.581999999999999
-    - type: ndcg_at_3
-      value: 8.779
-    - type: ndcg_at_5
-      value: 9.279
-    - type: precision_at_1
-      value: 7.983
-    - type: precision_at_10
-      value: 1.955
-    - type: precision_at_100
-      value: 0.392
-    - type: precision_at_1000
-      value: 0.076
-    - type: precision_at_3
-      value: 4.382
-    - type: precision_at_5
-      value: 3.09
-    - type: recall_at_1
-      value: 5.954000000000001
-    - type: recall_at_10
-      value: 13.472000000000001
-    - type: recall_at_100
-      value: 25.407999999999998
-    - type: recall_at_1000
-      value: 47.028
-    - type: recall_at_3
-      value: 9.367
-    - type: recall_at_5
-      value: 10.867
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/unix
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 8.894
-    - type: map_at_10
-      value: 12.758
-    - type: map_at_100
-      value: 13.639999999999999
-    - type: map_at_1000
-      value: 13.76
-    - type: map_at_3
-      value: 11.447000000000001
-    - type: map_at_5
-      value: 12.205
-    - type: mrr_at_1
-      value: 10.914
-    - type: mrr_at_10
-      value: 15.739
-    - type: mrr_at_100
-      value: 16.589000000000002
-    - type: mrr_at_1000
-      value: 16.679
-    - type: mrr_at_3
-      value: 14.179
-    - type: mrr_at_5
-      value: 15.162999999999998
-    - type: ndcg_at_1
-      value: 10.914
-    - type: ndcg_at_10
-      value: 15.629000000000001
-    - type: ndcg_at_100
-      value: 20.261000000000003
-    - type: ndcg_at_1000
-      value: 23.781
-    - type: ndcg_at_3
-      value: 13.102
-    - type: ndcg_at_5
-      value: 14.338000000000001
-    - type: precision_at_1
-      value: 10.914
-    - type: precision_at_10
-      value: 2.91
-    - type: precision_at_100
-      value: 0.601
-    - type: precision_at_1000
-      value: 0.10200000000000001
-    - type: precision_at_3
-      value: 6.311999999999999
-    - type: precision_at_5
-      value: 4.683
-    - type: recall_at_1
-      value: 8.894
-    - type: recall_at_10
-      value: 21.45
-    - type: recall_at_100
-      value: 42.617
-    - type: recall_at_1000
-      value: 69.233
-    - type: recall_at_3
-      value: 14.52
-    - type: recall_at_5
-      value: 17.681
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/webmasters
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 12.158
-    - type: map_at_10
-      value: 16.332
-    - type: map_at_100
-      value: 17.458000000000002
-    - type: map_at_1000
-      value: 17.687
-    - type: map_at_3
-      value: 14.529
-    - type: map_at_5
-      value: 15.515
-    - type: mrr_at_1
-      value: 15.809999999999999
-    - type: mrr_at_10
-      value: 19.917
-    - type: mrr_at_100
-      value: 20.875
-    - type: mrr_at_1000
-      value: 20.985
-    - type: mrr_at_3
-      value: 18.116
-    - type: mrr_at_5
-      value: 19.025
-    - type: ndcg_at_1
-      value: 15.809999999999999
-    - type: ndcg_at_10
-      value: 19.869999999999997
-    - type: ndcg_at_100
-      value: 24.907
-    - type: ndcg_at_1000
-      value: 29.076999999999998
-    - type: ndcg_at_3
-      value: 16.899
-    - type: ndcg_at_5
-      value: 18.23
-    - type: precision_at_1
-      value: 15.809999999999999
-    - type: precision_at_10
-      value: 3.972
-    - type: precision_at_100
-      value: 0.9860000000000001
-    - type: precision_at_1000
-      value: 0.203
-    - type: precision_at_3
-      value: 8.169
-    - type: precision_at_5
-      value: 6.087
-    - type: recall_at_1
-      value: 12.158
-    - type: recall_at_10
-      value: 26.338
-    - type: recall_at_100
-      value: 49.845
-    - type: recall_at_1000
-      value: 78.82000000000001
-    - type: recall_at_3
-      value: 16.997
-    - type: recall_at_5
-      value: 20.848
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/wordpress
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 8.01
-    - type: map_at_10
-      value: 10.889
-    - type: map_at_100
-      value: 11.562
-    - type: map_at_1000
-      value: 11.65
-    - type: map_at_3
-      value: 9.718
-    - type: map_at_5
-      value: 10.358
-    - type: mrr_at_1
-      value: 8.688
-    - type: mrr_at_10
-      value: 11.862
-    - type: mrr_at_100
-      value: 12.558
-    - type: mrr_at_1000
-      value: 12.642000000000001
-    - type: mrr_at_3
-      value: 10.598
-    - type: mrr_at_5
-      value: 11.328000000000001
-    - type: ndcg_at_1
-      value: 8.688
-    - type: ndcg_at_10
-      value: 12.959999999999999
-    - type: ndcg_at_100
-      value: 16.744
-    - type: ndcg_at_1000
-      value: 19.564999999999998
-    - type: ndcg_at_3
-      value: 10.476
-    - type: ndcg_at_5
-      value: 11.639
-    - type: precision_at_1
-      value: 8.688
-    - type: precision_at_10
-      value: 2.089
-    - type: precision_at_100
-      value: 0.43299999999999994
-    - type: precision_at_1000
-      value: 0.07200000000000001
-    - type: precision_at_3
-      value: 4.375
-    - type: precision_at_5
-      value: 3.253
-    - type: recall_at_1
-      value: 8.01
-    - type: recall_at_10
-      value: 18.589
-    - type: recall_at_100
-      value: 36.857
-    - type: recall_at_1000
-      value: 59.047000000000004
-    - type: recall_at_3
-      value: 11.774
-    - type: recall_at_5
-      value: 14.516000000000002
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 6.4719999999999995
-    - type: map_at_10
-      value: 12.322
-    - type: map_at_100
-      value: 14.122000000000002
-    - type: map_at_1000
-      value: 14.35
-    - type: map_at_3
-      value: 9.667
-    - type: map_at_5
-      value: 10.931000000000001
-    - type: mrr_at_1
-      value: 15.179
-    - type: mrr_at_10
-      value: 24.864
-    - type: mrr_at_100
-      value: 26.144000000000002
-    - type: mrr_at_1000
-      value: 26.198
-    - type: mrr_at_3
-      value: 20.999000000000002
-    - type: mrr_at_5
-      value: 23.097
-    - type: ndcg_at_1
-      value: 15.179
-    - type: ndcg_at_10
-      value: 18.951999999999998
-    - type: ndcg_at_100
-      value: 26.924
-    - type: ndcg_at_1000
-      value: 30.991999999999997
-    - type: ndcg_at_3
-      value: 13.778000000000002
-    - type: ndcg_at_5
-      value: 15.549
-    - type: precision_at_1
-      value: 15.179
-    - type: precision_at_10
-      value: 6.625
-    - type: precision_at_100
-      value: 1.516
-    - type: precision_at_1000
-      value: 0.22599999999999998
-    - type: precision_at_3
-      value: 10.51
-    - type: precision_at_5
-      value: 8.847
-    - type: recall_at_1
-      value: 6.4719999999999995
-    - type: recall_at_10
-      value: 25.191999999999997
-    - type: recall_at_100
-      value: 53.315
-    - type: recall_at_1000
-      value: 76.163
-    - type: recall_at_3
-      value: 12.834999999999999
-    - type: recall_at_5
-      value: 17.388
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 1.947
-    - type: map_at_10
-      value: 4.858
-    - type: map_at_100
-      value: 7.185999999999999
-    - type: map_at_1000
-      value: 7.931000000000001
-    - type: map_at_3
-      value: 3.2939999999999996
-    - type: map_at_5
-      value: 3.914
-    - type: mrr_at_1
-      value: 23.25
-    - type: mrr_at_10
-      value: 33.035
-    - type: mrr_at_100
-      value: 33.721000000000004
-    - type: mrr_at_1000
-      value: 33.789
-    - type: mrr_at_3
-      value: 29.75
-    - type: mrr_at_5
-      value: 31.738
-    - type: ndcg_at_1
-      value: 15.625
-    - type: ndcg_at_10
-      value: 13.211999999999998
-    - type: ndcg_at_100
-      value: 16.422
-    - type: ndcg_at_1000
-      value: 23.058999999999997
-    - type: ndcg_at_3
-      value: 14.573
-    - type: ndcg_at_5
-      value: 13.733999999999998
-    - type: precision_at_1
-      value: 23.25
-    - type: precision_at_10
-      value: 12.45
-    - type: precision_at_100
-      value: 4.192
-    - type: precision_at_1000
-      value: 1.083
-    - type: precision_at_3
-      value: 18.667
-    - type: precision_at_5
-      value: 15.950000000000001
-    - type: recall_at_1
-      value: 1.947
-    - type: recall_at_10
-      value: 9.317
-    - type: recall_at_100
-      value: 23.066
-    - type: recall_at_1000
-      value: 45.704
-    - type: recall_at_3
-      value: 4.12
-    - type: recall_at_5
-      value: 5.591
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 42.855
-    - type: f1
-      value: 39.029787102377576
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 8.461
-    - type: map_at_10
-      value: 13.655999999999999
-    - type: map_at_100
-      value: 14.499
-    - type: map_at_1000
-      value: 14.585999999999999
-    - type: map_at_3
-      value: 11.848
-    - type: map_at_5
-      value: 12.842999999999998
-    - type: mrr_at_1
-      value: 9.136
-    - type: mrr_at_10
-      value: 14.587
-    - type: mrr_at_100
-      value: 15.436
-    - type: mrr_at_1000
-      value: 15.518
-    - type: mrr_at_3
-      value: 12.690999999999999
-    - type: mrr_at_5
-      value: 13.747000000000002
-    - type: ndcg_at_1
-      value: 9.136
-    - type: ndcg_at_10
-      value: 16.958000000000002
-    - type: ndcg_at_100
-      value: 21.43
-    - type: ndcg_at_1000
-      value: 24.031
-    - type: ndcg_at_3
-      value: 13.191
-    - type: ndcg_at_5
-      value: 14.987
-    - type: precision_at_1
-      value: 9.136
-    - type: precision_at_10
-      value: 2.897
-    - type: precision_at_100
-      value: 0.532
-    - type: precision_at_1000
-      value: 0.077
-    - type: precision_at_3
-      value: 5.8709999999999996
-    - type: precision_at_5
-      value: 4.47
-    - type: recall_at_1
-      value: 8.461
-    - type: recall_at_10
-      value: 26.509
-    - type: recall_at_100
-      value: 47.776
-    - type: recall_at_1000
-      value: 68.26299999999999
-    - type: recall_at_3
-      value: 16.203
-    - type: recall_at_5
-      value: 20.505000000000003
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 7.396
-    - type: map_at_10
-      value: 12.393
-    - type: map_at_100
-      value: 13.857
-    - type: map_at_1000
-      value: 14.086000000000002
-    - type: map_at_3
-      value: 10.545
-    - type: map_at_5
-      value: 11.505
-    - type: mrr_at_1
-      value: 15.432000000000002
-    - type: mrr_at_10
-      value: 21.615000000000002
-    - type: mrr_at_100
-      value: 22.833000000000002
-    - type: mrr_at_1000
-      value: 22.931
-    - type: mrr_at_3
-      value: 19.522000000000002
-    - type: mrr_at_5
-      value: 20.663999999999998
-    - type: ndcg_at_1
-      value: 15.432000000000002
-    - type: ndcg_at_10
-      value: 16.986
-    - type: ndcg_at_100
-      value: 23.880000000000003
-    - type: ndcg_at_1000
-      value: 28.762999999999998
-    - type: ndcg_at_3
-      value: 14.482999999999999
-    - type: ndcg_at_5
-      value: 15.334999999999999
-    - type: precision_at_1
-      value: 15.432000000000002
-    - type: precision_at_10
-      value: 4.984999999999999
-    - type: precision_at_100
-      value: 1.167
-    - type: precision_at_1000
-      value: 0.2
-    - type: precision_at_3
-      value: 9.825000000000001
-    - type: precision_at_5
-      value: 7.469
-    - type: recall_at_1
-      value: 7.396
-    - type: recall_at_10
-      value: 21.389
-    - type: recall_at_100
-      value: 48.107
-    - type: recall_at_1000
-      value: 78.366
-    - type: recall_at_3
-      value: 13.181000000000001
-    - type: recall_at_5
-      value: 16.611
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 11.884
-    - type: map_at_10
-      value: 17.09
-    - type: map_at_100
-      value: 17.96
-    - type: map_at_1000
-      value: 18.081
-    - type: map_at_3
-      value: 15.296000000000001
-    - type: map_at_5
-      value: 16.289
-    - type: mrr_at_1
-      value: 23.768
-    - type: mrr_at_10
-      value: 29.991
-    - type: mrr_at_100
-      value: 30.862000000000002
-    - type: mrr_at_1000
-      value: 30.935000000000002
-    - type: mrr_at_3
-      value: 27.986
-    - type: mrr_at_5
-      value: 29.078
-    - type: ndcg_at_1
-      value: 23.768
-    - type: ndcg_at_10
-      value: 22.634999999999998
-    - type: ndcg_at_100
-      value: 27.059
-    - type: ndcg_at_1000
-      value: 30.145
-    - type: ndcg_at_3
-      value: 19.058
-    - type: ndcg_at_5
-      value: 20.762
-    - type: precision_at_1
-      value: 23.768
-    - type: precision_at_10
-      value: 5.2490000000000006
-    - type: precision_at_100
-      value: 0.8829999999999999
-    - type: precision_at_1000
-      value: 0.13
-    - type: precision_at_3
-      value: 12.091000000000001
-    - type: precision_at_5
-      value: 8.605
-    - type: recall_at_1
-      value: 11.884
-    - type: recall_at_10
-      value: 26.246000000000002
-    - type: recall_at_100
-      value: 44.153
-    - type: recall_at_1000
-      value: 64.889
-    - type: recall_at_3
-      value: 18.136
-    - type: recall_at_5
-      value: 21.512
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 71.9232
-    - type: ap
-      value: 66.56619827391917
-    - type: f1
-      value: 71.60536244284128
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 3.037
-    - type: map_at_10
-      value: 5.414
-    - type: map_at_100
-      value: 6.072
-    - type: map_at_1000
-      value: 6.172
-    - type: map_at_3
-      value: 4.437
-    - type: map_at_5
-      value: 4.939
-    - type: mrr_at_1
-      value: 3.123
-    - type: mrr_at_10
-      value: 5.572
-    - type: mrr_at_100
-      value: 6.235
-    - type: mrr_at_1000
-      value: 6.334
-    - type: mrr_at_3
-      value: 4.563
-    - type: mrr_at_5
-      value: 5.09
-    - type: ndcg_at_1
-      value: 3.123
-    - type: ndcg_at_10
-      value: 7.027
-    - type: ndcg_at_100
-      value: 10.776
-    - type: ndcg_at_1000
-      value: 13.904
-    - type: ndcg_at_3
-      value: 4.95
-    - type: ndcg_at_5
-      value: 5.865
-    - type: precision_at_1
-      value: 3.123
-    - type: precision_at_10
-      value: 1.252
-    - type: precision_at_100
-      value: 0.32299999999999995
-    - type: precision_at_1000
-      value: 0.059000000000000004
-    - type: precision_at_3
-      value: 2.168
-    - type: precision_at_5
-      value: 1.7680000000000002
-    - type: recall_at_1
-      value: 3.037
-    - type: recall_at_10
-      value: 12.11
-    - type: recall_at_100
-      value: 30.714999999999996
-    - type: recall_at_1000
-      value: 56.006
-    - type: recall_at_3
-      value: 6.3229999999999995
-    - type: recall_at_5
-      value: 8.518
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 91.24259005927954
-    - type: f1
-      value: 90.7594022786747
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 74.08344733242134
-    - type: f1
-      value: 52.377556461789055
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 69.99327505043712
-    - type: f1
-      value: 66.15141376479805
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 75.1546738399462
-    - type: f1
-      value: 74.83013584700711
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 30.146364191412356
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 26.96347584990607
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 29.520993847103533
-    - type: mrr
-      value: 30.402007095845374
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 1.72
-    - type: map_at_10
-      value: 4.041
-    - type: map_at_100
-      value: 5.356000000000001
-    - type: map_at_1000
-      value: 6.413
-    - type: map_at_3
-      value: 2.9770000000000003
-    - type: map_at_5
-      value: 3.3689999999999998
-    - type: mrr_at_1
-      value: 21.981
-    - type: mrr_at_10
-      value: 30.286
-    - type: mrr_at_100
-      value: 31.272
-    - type: mrr_at_1000
-      value: 31.347
-    - type: mrr_at_3
-      value: 27.193
-    - type: mrr_at_5
-      value: 28.694999999999997
-    - type: ndcg_at_1
-      value: 19.814
-    - type: ndcg_at_10
-      value: 15.732
-    - type: ndcg_at_100
-      value: 16.033
-    - type: ndcg_at_1000
-      value: 25.865
-    - type: ndcg_at_3
-      value: 17.944
-    - type: ndcg_at_5
-      value: 16.634
-    - type: precision_at_1
-      value: 21.981
-    - type: precision_at_10
-      value: 12.786
-    - type: precision_at_100
-      value: 4.83
-    - type: precision_at_1000
-      value: 1.765
-    - type: precision_at_3
-      value: 17.75
-    - type: precision_at_5
-      value: 15.232000000000001
-    - type: recall_at_1
-      value: 1.72
-    - type: recall_at_10
-      value: 7.436
-    - type: recall_at_100
-      value: 20.275000000000002
-    - type: recall_at_1000
-      value: 54.19500000000001
-    - type: recall_at_3
-      value: 3.787
-    - type: recall_at_5
-      value: 4.829
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 7.964
-    - type: map_at_10
-      value: 14.025000000000002
-    - type: map_at_100
-      value: 15.222
-    - type: map_at_1000
-      value: 15.32
-    - type: map_at_3
-      value: 11.886
-    - type: map_at_5
-      value: 13.056999999999999
-    - type: mrr_at_1
-      value: 9.183
-    - type: mrr_at_10
-      value: 15.651000000000002
-    - type: mrr_at_100
-      value: 16.753999999999998
-    - type: mrr_at_1000
-      value: 16.833000000000002
-    - type: mrr_at_3
-      value: 13.437
-    - type: mrr_at_5
-      value: 14.69
-    - type: ndcg_at_1
-      value: 9.183
-    - type: ndcg_at_10
-      value: 17.96
-    - type: ndcg_at_100
-      value: 23.823
-    - type: ndcg_at_1000
-      value: 26.461000000000002
-    - type: ndcg_at_3
-      value: 13.536999999999999
-    - type: ndcg_at_5
-      value: 15.642
-    - type: precision_at_1
-      value: 9.183
-    - type: precision_at_10
-      value: 3.366
-    - type: precision_at_100
-      value: 0.67
-    - type: precision_at_1000
-      value: 0.092
-    - type: precision_at_3
-      value: 6.547
-    - type: precision_at_5
-      value: 5.098
-    - type: recall_at_1
-      value: 7.964
-    - type: recall_at_10
-      value: 28.599000000000004
-    - type: recall_at_100
-      value: 55.381
-    - type: recall_at_1000
-      value: 75.63
-    - type: recall_at_3
-      value: 16.77
-    - type: recall_at_5
-      value: 21.671000000000003
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 59.846999999999994
-    - type: map_at_10
-      value: 73.18599999999999
-    - type: map_at_100
-      value: 74.055
-    - type: map_at_1000
-      value: 74.09
-    - type: map_at_3
-      value: 69.95700000000001
-    - type: map_at_5
-      value: 71.925
-    - type: mrr_at_1
-      value: 69.0
-    - type: mrr_at_10
-      value: 77.23299999999999
-    - type: mrr_at_100
-      value: 77.52
-    - type: mrr_at_1000
-      value: 77.526
-    - type: mrr_at_3
-      value: 75.59
-    - type: mrr_at_5
-      value: 76.63799999999999
-    - type: ndcg_at_1
-      value: 69.02000000000001
-    - type: ndcg_at_10
-      value: 78.226
-    - type: ndcg_at_100
-      value: 80.60199999999999
-    - type: ndcg_at_1000
-      value: 80.971
-    - type: ndcg_at_3
-      value: 74.124
-    - type: ndcg_at_5
-      value: 76.265
-    - type: precision_at_1
-      value: 69.02000000000001
-    - type: precision_at_10
-      value: 12.102
-    - type: precision_at_100
-      value: 1.468
-    - type: precision_at_1000
-      value: 0.155
-    - type: precision_at_3
-      value: 32.5
-    - type: precision_at_5
-      value: 21.7
-    - type: recall_at_1
-      value: 59.846999999999994
-    - type: recall_at_10
-      value: 88.485
-    - type: recall_at_100
-      value: 97.425
-    - type: recall_at_1000
-      value: 99.523
-    - type: recall_at_3
-      value: 77.051
-    - type: recall_at_5
-      value: 82.762
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 38.67296729610079
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 53.42017351823769
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.893
-    - type: map_at_10
-      value: 2.804
-    - type: map_at_100
-      value: 3.6740000000000004
-    - type: map_at_1000
-      value: 3.94
-    - type: map_at_3
-      value: 1.926
-    - type: map_at_5
-      value: 2.363
-    - type: mrr_at_1
-      value: 4.3
-    - type: mrr_at_10
-      value: 9.520000000000001
-    - type: mrr_at_100
-      value: 10.692
-    - type: mrr_at_1000
-      value: 10.841000000000001
-    - type: mrr_at_3
-      value: 7.6
-    - type: mrr_at_5
-      value: 8.63
-    - type: ndcg_at_1
-      value: 4.3
-    - type: ndcg_at_10
-      value: 5.531
-    - type: ndcg_at_100
-      value: 10.512
-    - type: ndcg_at_1000
-      value: 16.683
-    - type: ndcg_at_3
-      value: 4.632
-    - type: ndcg_at_5
-      value: 4.3229999999999995
-    - type: precision_at_1
-      value: 4.3
-    - type: precision_at_10
-      value: 3.16
-    - type: precision_at_100
-      value: 1.065
-    - type: precision_at_1000
-      value: 0.256
-    - type: precision_at_3
-      value: 4.667000000000001
-    - type: precision_at_5
-      value: 4.1000000000000005
-    - type: recall_at_1
-      value: 0.893
-    - type: recall_at_10
-      value: 6.428000000000001
-    - type: recall_at_100
-      value: 21.662
-    - type: recall_at_1000
-      value: 52.162
-    - type: recall_at_3
-      value: 2.868
-    - type: recall_at_5
-      value: 4.188
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_spearman
-      value: 69.34396953516386
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_spearman
-      value: 60.094374065360746
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_spearman
-      value: 72.51503781013379
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_spearman
-      value: 66.6954698644186
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_spearman
-      value: 77.69462578028768
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_spearman
-      value: 75.9397626457859
-  - 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_spearman
-      value: 81.67242768943406
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts22-crosslingual-sts
-      name: MTEB STS22 (en)
-      config: en
-      split: test
-      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
-    metrics:
-    - type: cos_sim_spearman
-      value: 63.7027324700292
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_spearman
-      value: 73.36074244064153
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 67.75984402370518
-    - type: mrr
-      value: 86.9951798383171
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 24.583
-    - type: map_at_10
-      value: 33.125
-    - type: map_at_100
-      value: 34.14
-    - type: map_at_1000
-      value: 34.22
-    - type: map_at_3
-      value: 29.616
-    - type: map_at_5
-      value: 31.896
-    - type: mrr_at_1
-      value: 26.333000000000002
-    - type: mrr_at_10
-      value: 34.437
-    - type: mrr_at_100
-      value: 35.363
-    - type: mrr_at_1000
-      value: 35.433
-    - type: mrr_at_3
-      value: 31.333
-    - type: mrr_at_5
-      value: 33.267
-    - type: ndcg_at_1
-      value: 26.333000000000002
-    - type: ndcg_at_10
-      value: 38.311
-    - type: ndcg_at_100
-      value: 43.923
-    - type: ndcg_at_1000
-      value: 45.923
-    - type: ndcg_at_3
-      value: 31.596000000000004
-    - type: ndcg_at_5
-      value: 35.448
-    - type: precision_at_1
-      value: 26.333000000000002
-    - type: precision_at_10
-      value: 5.933
-    - type: precision_at_100
-      value: 0.91
-    - type: precision_at_1000
-      value: 0.109
-    - type: precision_at_3
-      value: 13.0
-    - type: precision_at_5
-      value: 9.933
-    - type: recall_at_1
-      value: 24.583
-    - type: recall_at_10
-      value: 53.417
-    - type: recall_at_100
-      value: 80.989
-    - type: recall_at_1000
-      value: 96.322
-    - type: recall_at_3
-      value: 35.611
-    - type: recall_at_5
-      value: 44.833
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.48514851485149
-    - type: cos_sim_ap
-      value: 77.36426466374054
-    - type: cos_sim_f1
-      value: 72.0702116675271
-    - type: cos_sim_precision
-      value: 74.49306296691569
-    - type: cos_sim_recall
-      value: 69.8
-    - type: dot_accuracy
-      value: 99.15049504950495
-    - type: dot_ap
-      value: 46.792474140260715
-    - type: dot_f1
-      value: 48.76476906552094
-    - type: dot_precision
-      value: 52.66821345707656
-    - type: dot_recall
-      value: 45.4
-    - type: euclidean_accuracy
-      value: 99.46534653465346
-    - type: euclidean_ap
-      value: 74.1978837990589
-    - type: euclidean_f1
-      value: 69.47256259989345
-    - type: euclidean_precision
-      value: 74.34435575826683
-    - type: euclidean_recall
-      value: 65.2
-    - type: manhattan_accuracy
-      value: 99.47128712871287
-    - type: manhattan_ap
-      value: 75.31910551743364
-    - type: manhattan_f1
-      value: 70.1582105837425
-    - type: manhattan_precision
-      value: 77.19087635054022
-    - type: manhattan_recall
-      value: 64.3
-    - type: max_accuracy
-      value: 99.48514851485149
-    - type: max_ap
-      value: 77.36426466374054
-    - type: max_f1
-      value: 72.0702116675271
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 59.353792480720436
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 31.474896484744836
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 40.82378653430986
-    - type: mrr
-      value: 41.13905600118835
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 31.08154836998798
-    - type: cos_sim_spearman
-      value: 31.232033308845907
-    - type: dot_pearson
-      value: 23.767593496465828
-    - type: dot_spearman
-      value: 25.6201612766572
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.186
-    - type: map_at_10
-      value: 1.1809999999999998
-    - type: map_at_100
-      value: 5.21
-    - type: map_at_1000
-      value: 12.447999999999999
-    - type: map_at_3
-      value: 0.44200000000000006
-    - type: map_at_5
-      value: 0.673
-    - type: mrr_at_1
-      value: 72.0
-    - type: mrr_at_10
-      value: 80.01899999999999
-    - type: mrr_at_100
-      value: 80.42099999999999
-    - type: mrr_at_1000
-      value: 80.42099999999999
-    - type: mrr_at_3
-      value: 78.0
-    - type: mrr_at_5
-      value: 79.4
-    - type: ndcg_at_1
-      value: 66.0
-    - type: ndcg_at_10
-      value: 56.041
-    - type: ndcg_at_100
-      value: 37.987
-    - type: ndcg_at_1000
-      value: 34.198
-    - type: ndcg_at_3
-      value: 60.23500000000001
-    - type: ndcg_at_5
-      value: 58.025999999999996
-    - type: precision_at_1
-      value: 72.0
-    - type: precision_at_10
-      value: 60.4
-    - type: precision_at_100
-      value: 38.940000000000005
-    - type: precision_at_1000
-      value: 16.106
-    - type: precision_at_3
-      value: 63.333
-    - type: precision_at_5
-      value: 61.6
-    - type: recall_at_1
-      value: 0.186
-    - type: recall_at_10
-      value: 1.458
-    - type: recall_at_100
-      value: 8.455
-    - type: recall_at_1000
-      value: 33.141999999999996
-    - type: recall_at_3
-      value: 0.461
-    - type: recall_at_5
-      value: 0.756
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 2.2849999999999997
-    - type: map_at_10
-      value: 6.909
-    - type: map_at_100
-      value: 11.231
-    - type: map_at_1000
-      value: 12.472
-    - type: map_at_3
-      value: 3.53
-    - type: map_at_5
-      value: 4.675
-    - type: mrr_at_1
-      value: 26.531
-    - type: mrr_at_10
-      value: 40.73
-    - type: mrr_at_100
-      value: 41.637
-    - type: mrr_at_1000
-      value: 41.647
-    - type: mrr_at_3
-      value: 34.354
-    - type: mrr_at_5
-      value: 38.741
-    - type: ndcg_at_1
-      value: 24.490000000000002
-    - type: ndcg_at_10
-      value: 19.17
-    - type: ndcg_at_100
-      value: 29.946
-    - type: ndcg_at_1000
-      value: 40.842
-    - type: ndcg_at_3
-      value: 19.088
-    - type: ndcg_at_5
-      value: 19.445999999999998
-    - type: precision_at_1
-      value: 26.531
-    - type: precision_at_10
-      value: 17.959
-    - type: precision_at_100
-      value: 6.468999999999999
-    - type: precision_at_1000
-      value: 1.351
-    - type: precision_at_3
-      value: 19.048000000000002
-    - type: precision_at_5
-      value: 19.592000000000002
-    - type: recall_at_1
-      value: 2.2849999999999997
-    - type: recall_at_10
-      value: 12.973
-    - type: recall_at_100
-      value: 40.239999999999995
-    - type: recall_at_1000
-      value: 73.247
-    - type: recall_at_3
-      value: 4.407
-    - type: recall_at_5
-      value: 6.908
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 68.405
-    - type: ap
-      value: 13.9913678628558
-    - type: f1
-      value: 53.209691917560285
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 56.080928126768534
-    - type: f1
-      value: 56.36329965117965
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 31.540976715818065
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 82.90516778923526
-    - type: cos_sim_ap
-      value: 61.5394989621502
-    - type: cos_sim_f1
-      value: 58.02297689685646
-    - type: cos_sim_precision
-      value: 55.62817719680465
-    - type: cos_sim_recall
-      value: 60.633245382585756
-    - type: dot_accuracy
-      value: 78.95928950348691
-    - type: dot_ap
-      value: 48.61088896690895
-    - type: dot_f1
-      value: 51.0104674059488
-    - type: dot_precision
-      value: 42.00375490698071
-    - type: dot_recall
-      value: 64.93403693931398
-    - type: euclidean_accuracy
-      value: 82.476008821601
-    - type: euclidean_ap
-      value: 59.59406971314053
-    - type: euclidean_f1
-      value: 56.424962447084525
-    - type: euclidean_precision
-      value: 58.47721483158789
-    - type: euclidean_recall
-      value: 54.51187335092348
-    - type: manhattan_accuracy
-      value: 82.66078559933241
-    - type: manhattan_ap
-      value: 60.414321716856925
-    - type: manhattan_f1
-      value: 56.88221089348002
-    - type: manhattan_precision
-      value: 57.86026200873362
-    - type: manhattan_recall
-      value: 55.93667546174142
-    - type: max_accuracy
-      value: 82.90516778923526
-    - type: max_ap
-      value: 61.5394989621502
-    - type: max_f1
-      value: 58.02297689685646
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 85.71622618077386
-    - type: cos_sim_ap
-      value: 77.72774861009667
-    - type: cos_sim_f1
-      value: 71.40275165062152
-    - type: cos_sim_precision
-      value: 68.53359767754726
-    - type: cos_sim_recall
-      value: 74.52263627964275
-    - type: dot_accuracy
-      value: 83.97174680793262
-    - type: dot_ap
-      value: 72.89480417427734
-    - type: dot_f1
-      value: 68.57803792366198
-    - type: dot_precision
-      value: 62.94151708164447
-    - type: dot_recall
-      value: 75.32337542346782
-    - type: euclidean_accuracy
-      value: 84.88570652384834
-    - type: euclidean_ap
-      value: 75.78371710915128
-    - type: euclidean_f1
-      value: 69.44268877569989
-    - type: euclidean_precision
-      value: 67.1435761018046
-    - type: euclidean_recall
-      value: 71.90483523252233
-    - type: manhattan_accuracy
-      value: 85.6114409904141
-    - type: manhattan_ap
-      value: 77.38579436755944
-    - type: manhattan_f1
-      value: 70.8608538430316
-    - type: manhattan_precision
-      value: 68.03656203500319
-    - type: manhattan_recall
-      value: 73.92978133661842
-    - type: max_accuracy
-      value: 85.71622618077386
-    - type: max_ap
-      value: 77.72774861009667
-    - type: max_f1
-      value: 71.40275165062152
 ---
 
 # LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders