Update README.md

README.md

@@ -23,2501 +23,6 @@ tags:
 - fever
 - hotpot_qa
 - mteb
-model-index:
-- name: LLM2Vec-Mistral-7B-Instruct-v2-mntp-supervised
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 77.58208955223881
-    - type: ap
-      value: 41.45474097979136
-    - type: f1
-      value: 71.76059891468786
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 91.12039999999999
-    - type: ap
-      value: 88.01002974730474
-    - type: f1
-      value: 91.1049266954883
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 49.966
-    - type: f1
-      value: 48.908221884634386
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.788000000000004
-    - type: map_at_10
-      value: 48.665000000000006
-    - type: map_at_100
-      value: 49.501
-    - type: map_at_1000
-      value: 49.504
-    - type: map_at_3
-      value: 43.883
-    - type: map_at_5
-      value: 46.501
-    - type: mrr_at_1
-      value: 33.357
-    - type: mrr_at_10
-      value: 48.882
-    - type: mrr_at_100
-      value: 49.718
-    - type: mrr_at_1000
-      value: 49.721
-    - type: mrr_at_3
-      value: 44.025999999999996
-    - type: mrr_at_5
-      value: 46.732
-    - type: ndcg_at_1
-      value: 32.788000000000004
-    - type: ndcg_at_10
-      value: 57.483
-    - type: ndcg_at_100
-      value: 60.745000000000005
-    - type: ndcg_at_1000
-      value: 60.797000000000004
-    - type: ndcg_at_3
-      value: 47.534
-    - type: ndcg_at_5
-      value: 52.266
-    - type: precision_at_1
-      value: 32.788000000000004
-    - type: precision_at_10
-      value: 8.57
-    - type: precision_at_100
-      value: 0.993
-    - type: precision_at_1000
-      value: 0.1
-    - type: precision_at_3
-      value: 19.369
-    - type: precision_at_5
-      value: 13.926
-    - type: recall_at_1
-      value: 32.788000000000004
-    - type: recall_at_10
-      value: 85.70400000000001
-    - type: recall_at_100
-      value: 99.289
-    - type: recall_at_1000
-      value: 99.644
-    - type: recall_at_3
-      value: 58.108000000000004
-    - type: recall_at_5
-      value: 69.63000000000001
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 42.805075760047906
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 44.235789514284214
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 63.98320383943591
-    - type: mrr
-      value: 76.53189992525174
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_spearman
-      value: 85.24411101959603
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 88.31493506493506
-    - type: f1
-      value: 88.28524975751309
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 34.27007175430729
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 35.52517776034658
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/android
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 38.686
-    - type: map_at_10
-      value: 51.939
-    - type: map_at_100
-      value: 53.751000000000005
-    - type: map_at_1000
-      value: 53.846000000000004
-    - type: map_at_3
-      value: 48.296
-    - type: map_at_5
-      value: 50.312999999999995
-    - type: mrr_at_1
-      value: 49.641999999999996
-    - type: mrr_at_10
-      value: 59.157000000000004
-    - type: mrr_at_100
-      value: 59.85
-    - type: mrr_at_1000
-      value: 59.876
-    - type: mrr_at_3
-      value: 57.058
-    - type: mrr_at_5
-      value: 58.231
-    - type: ndcg_at_1
-      value: 49.641999999999996
-    - type: ndcg_at_10
-      value: 58.714
-    - type: ndcg_at_100
-      value: 63.776999999999994
-    - type: ndcg_at_1000
-      value: 64.95
-    - type: ndcg_at_3
-      value: 54.799
-    - type: ndcg_at_5
-      value: 56.372
-    - type: precision_at_1
-      value: 49.641999999999996
-    - type: precision_at_10
-      value: 11.373
-    - type: precision_at_100
-      value: 1.712
-    - type: precision_at_1000
-      value: 0.209
-    - type: precision_at_3
-      value: 27.229
-    - type: precision_at_5
-      value: 19.056
-    - type: recall_at_1
-      value: 38.686
-    - type: recall_at_10
-      value: 69.976
-    - type: recall_at_100
-      value: 90.512
-    - type: recall_at_1000
-      value: 97.64
-    - type: recall_at_3
-      value: 56.625
-    - type: recall_at_5
-      value: 62.348000000000006
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/english
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 36.356
-    - type: map_at_10
-      value: 48.004000000000005
-    - type: map_at_100
-      value: 49.342999999999996
-    - type: map_at_1000
-      value: 49.461
-    - type: map_at_3
-      value: 44.692
-    - type: map_at_5
-      value: 46.576
-    - type: mrr_at_1
-      value: 46.561
-    - type: mrr_at_10
-      value: 54.547000000000004
-    - type: mrr_at_100
-      value: 55.159000000000006
-    - type: mrr_at_1000
-      value: 55.193000000000005
-    - type: mrr_at_3
-      value: 52.516
-    - type: mrr_at_5
-      value: 53.701
-    - type: ndcg_at_1
-      value: 46.561
-    - type: ndcg_at_10
-      value: 53.835
-    - type: ndcg_at_100
-      value: 57.92699999999999
-    - type: ndcg_at_1000
-      value: 59.671
-    - type: ndcg_at_3
-      value: 49.997
-    - type: ndcg_at_5
-      value: 51.714000000000006
-    - type: precision_at_1
-      value: 46.561
-    - type: precision_at_10
-      value: 10.344000000000001
-    - type: precision_at_100
-      value: 1.5779999999999998
-    - type: precision_at_1000
-      value: 0.202
-    - type: precision_at_3
-      value: 24.437
-    - type: precision_at_5
-      value: 17.197000000000003
-    - type: recall_at_1
-      value: 36.356
-    - type: recall_at_10
-      value: 63.019000000000005
-    - type: recall_at_100
-      value: 80.55099999999999
-    - type: recall_at_1000
-      value: 91.38300000000001
-    - type: recall_at_3
-      value: 50.431000000000004
-    - type: recall_at_5
-      value: 56.00000000000001
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/gaming
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 46.736
-    - type: map_at_10
-      value: 60.775999999999996
-    - type: map_at_100
-      value: 61.755
-    - type: map_at_1000
-      value: 61.783
-    - type: map_at_3
-      value: 57.293000000000006
-    - type: map_at_5
-      value: 59.382000000000005
-    - type: mrr_at_1
-      value: 54.232
-    - type: mrr_at_10
-      value: 64.424
-    - type: mrr_at_100
-      value: 64.996
-    - type: mrr_at_1000
-      value: 65.009
-    - type: mrr_at_3
-      value: 62.226000000000006
-    - type: mrr_at_5
-      value: 63.592000000000006
-    - type: ndcg_at_1
-      value: 54.232
-    - type: ndcg_at_10
-      value: 66.654
-    - type: ndcg_at_100
-      value: 70.152
-    - type: ndcg_at_1000
-      value: 70.648
-    - type: ndcg_at_3
-      value: 61.405
-    - type: ndcg_at_5
-      value: 64.137
-    - type: precision_at_1
-      value: 54.232
-    - type: precision_at_10
-      value: 10.607999999999999
-    - type: precision_at_100
-      value: 1.321
-    - type: precision_at_1000
-      value: 0.13899999999999998
-    - type: precision_at_3
-      value: 27.544
-    - type: precision_at_5
-      value: 18.645999999999997
-    - type: recall_at_1
-      value: 46.736
-    - type: recall_at_10
-      value: 80.10199999999999
-    - type: recall_at_100
-      value: 94.976
-    - type: recall_at_1000
-      value: 98.402
-    - type: recall_at_3
-      value: 66.094
-    - type: recall_at_5
-      value: 73.028
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/gis
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 30.238
-    - type: map_at_10
-      value: 39.798
-    - type: map_at_100
-      value: 40.892
-    - type: map_at_1000
-      value: 40.971000000000004
-    - type: map_at_3
-      value: 36.788
-    - type: map_at_5
-      value: 38.511
-    - type: mrr_at_1
-      value: 32.994
-    - type: mrr_at_10
-      value: 42.028
-    - type: mrr_at_100
-      value: 42.959
-    - type: mrr_at_1000
-      value: 43.010999999999996
-    - type: mrr_at_3
-      value: 39.322
-    - type: mrr_at_5
-      value: 40.977000000000004
-    - type: ndcg_at_1
-      value: 32.994
-    - type: ndcg_at_10
-      value: 45.062000000000005
-    - type: ndcg_at_100
-      value: 50.166999999999994
-    - type: ndcg_at_1000
-      value: 51.961
-    - type: ndcg_at_3
-      value: 39.378
-    - type: ndcg_at_5
-      value: 42.281
-    - type: precision_at_1
-      value: 32.994
-    - type: precision_at_10
-      value: 6.836
-    - type: precision_at_100
-      value: 0.9860000000000001
-    - type: precision_at_1000
-      value: 0.11800000000000001
-    - type: precision_at_3
-      value: 16.384
-    - type: precision_at_5
-      value: 11.548
-    - type: recall_at_1
-      value: 30.238
-    - type: recall_at_10
-      value: 59.080999999999996
-    - type: recall_at_100
-      value: 82.033
-    - type: recall_at_1000
-      value: 95.281
-    - type: recall_at_3
-      value: 43.902
-    - type: recall_at_5
-      value: 50.952
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/mathematica
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.512999999999998
-    - type: map_at_10
-      value: 31.339
-    - type: map_at_100
-      value: 32.651
-    - type: map_at_1000
-      value: 32.762
-    - type: map_at_3
-      value: 27.590999999999998
-    - type: map_at_5
-      value: 29.946
-    - type: mrr_at_1
-      value: 26.866
-    - type: mrr_at_10
-      value: 36.525
-    - type: mrr_at_100
-      value: 37.357
-    - type: mrr_at_1000
-      value: 37.419999999999995
-    - type: mrr_at_3
-      value: 33.085
-    - type: mrr_at_5
-      value: 35.379
-    - type: ndcg_at_1
-      value: 26.866
-    - type: ndcg_at_10
-      value: 37.621
-    - type: ndcg_at_100
-      value: 43.031000000000006
-    - type: ndcg_at_1000
-      value: 45.573
-    - type: ndcg_at_3
-      value: 31.046000000000003
-    - type: ndcg_at_5
-      value: 34.709
-    - type: precision_at_1
-      value: 26.866
-    - type: precision_at_10
-      value: 7.052
-    - type: precision_at_100
-      value: 1.117
-    - type: precision_at_1000
-      value: 0.145
-    - type: precision_at_3
-      value: 14.884
-    - type: precision_at_5
-      value: 11.517
-    - type: recall_at_1
-      value: 21.512999999999998
-    - type: recall_at_10
-      value: 51.751999999999995
-    - type: recall_at_100
-      value: 74.34100000000001
-    - type: recall_at_1000
-      value: 92.426
-    - type: recall_at_3
-      value: 34.008
-    - type: recall_at_5
-      value: 43.075
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/physics
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 35.327
-    - type: map_at_10
-      value: 47.783
-    - type: map_at_100
-      value: 49.153999999999996
-    - type: map_at_1000
-      value: 49.260999999999996
-    - type: map_at_3
-      value: 44.145
-    - type: map_at_5
-      value: 46.207
-    - type: mrr_at_1
-      value: 44.37
-    - type: mrr_at_10
-      value: 53.864999999999995
-    - type: mrr_at_100
-      value: 54.625
-    - type: mrr_at_1000
-      value: 54.662
-    - type: mrr_at_3
-      value: 51.604000000000006
-    - type: mrr_at_5
-      value: 52.894
-    - type: ndcg_at_1
-      value: 44.37
-    - type: ndcg_at_10
-      value: 54.054
-    - type: ndcg_at_100
-      value: 59.168
-    - type: ndcg_at_1000
-      value: 60.769
-    - type: ndcg_at_3
-      value: 49.091
-    - type: ndcg_at_5
-      value: 51.444
-    - type: precision_at_1
-      value: 44.37
-    - type: precision_at_10
-      value: 9.827
-    - type: precision_at_100
-      value: 1.456
-    - type: precision_at_1000
-      value: 0.17600000000000002
-    - type: precision_at_3
-      value: 23.580000000000002
-    - type: precision_at_5
-      value: 16.554
-    - type: recall_at_1
-      value: 35.327
-    - type: recall_at_10
-      value: 66.43900000000001
-    - type: recall_at_100
-      value: 87.41600000000001
-    - type: recall_at_1000
-      value: 97.37400000000001
-    - type: recall_at_3
-      value: 51.64
-    - type: recall_at_5
-      value: 58.242000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/programmers
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.397999999999996
-    - type: map_at_10
-      value: 44.932
-    - type: map_at_100
-      value: 46.336
-    - type: map_at_1000
-      value: 46.421
-    - type: map_at_3
-      value: 41.128
-    - type: map_at_5
-      value: 43.364999999999995
-    - type: mrr_at_1
-      value: 41.324
-    - type: mrr_at_10
-      value: 51.080000000000005
-    - type: mrr_at_100
-      value: 51.878
-    - type: mrr_at_1000
-      value: 51.910000000000004
-    - type: mrr_at_3
-      value: 48.382999999999996
-    - type: mrr_at_5
-      value: 50.004000000000005
-    - type: ndcg_at_1
-      value: 41.324
-    - type: ndcg_at_10
-      value: 51.466
-    - type: ndcg_at_100
-      value: 56.874
-    - type: ndcg_at_1000
-      value: 58.321999999999996
-    - type: ndcg_at_3
-      value: 45.928999999999995
-    - type: ndcg_at_5
-      value: 48.532
-    - type: precision_at_1
-      value: 41.324
-    - type: precision_at_10
-      value: 9.565999999999999
-    - type: precision_at_100
-      value: 1.428
-    - type: precision_at_1000
-      value: 0.172
-    - type: precision_at_3
-      value: 22.184
-    - type: precision_at_5
-      value: 15.867999999999999
-    - type: recall_at_1
-      value: 32.397999999999996
-    - type: recall_at_10
-      value: 64.512
-    - type: recall_at_100
-      value: 87.425
-    - type: recall_at_1000
-      value: 96.937
-    - type: recall_at_3
-      value: 48.513
-    - type: recall_at_5
-      value: 55.721
-  - task:
-      type: Retrieval
-    dataset:
-      type: mteb/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.001916666666666
-    - type: map_at_10
-      value: 42.91216666666667
-    - type: map_at_100
-      value: 44.21125000000001
-    - type: map_at_1000
-      value: 44.314166666666665
-    - type: map_at_3
-      value: 39.579
-    - type: map_at_5
-      value: 41.497166666666665
-    - type: mrr_at_1
-      value: 38.669583333333335
-    - type: mrr_at_10
-      value: 47.708
-    - type: mrr_at_100
-      value: 48.4875
-    - type: mrr_at_1000
-      value: 48.530833333333334
-    - type: mrr_at_3
-      value: 45.196333333333335
-    - type: mrr_at_5
-      value: 46.702999999999996
-    - type: ndcg_at_1
-      value: 38.669583333333335
-    - type: ndcg_at_10
-      value: 48.842
-    - type: ndcg_at_100
-      value: 53.79400000000001
-    - type: ndcg_at_1000
-      value: 55.566416666666676
-    - type: ndcg_at_3
-      value: 43.70975
-    - type: ndcg_at_5
-      value: 46.204499999999996
-    - type: precision_at_1
-      value: 38.669583333333335
-    - type: precision_at_10
-      value: 8.652999999999999
-    - type: precision_at_100
-      value: 1.3168333333333333
-    - type: precision_at_1000
-      value: 0.164
-    - type: precision_at_3
-      value: 20.343249999999998
-    - type: precision_at_5
-      value: 14.426
-    - type: recall_at_1
-      value: 32.001916666666666
-    - type: recall_at_10
-      value: 61.31158333333334
-    - type: recall_at_100
-      value: 82.80691666666667
-    - type: recall_at_1000
-      value: 94.977
-    - type: recall_at_3
-      value: 46.63558333333333
-    - type: recall_at_5
-      value: 53.32383333333334
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/stats
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.311999999999998
-    - type: map_at_10
-      value: 37.735
-    - type: map_at_100
-      value: 38.702
-    - type: map_at_1000
-      value: 38.803
-    - type: map_at_3
-      value: 35.17
-    - type: map_at_5
-      value: 36.6
-    - type: mrr_at_1
-      value: 33.282000000000004
-    - type: mrr_at_10
-      value: 41.059
-    - type: mrr_at_100
-      value: 41.881
-    - type: mrr_at_1000
-      value: 41.943000000000005
-    - type: mrr_at_3
-      value: 38.829
-    - type: mrr_at_5
-      value: 40.11
-    - type: ndcg_at_1
-      value: 33.282000000000004
-    - type: ndcg_at_10
-      value: 42.625
-    - type: ndcg_at_100
-      value: 47.313
-    - type: ndcg_at_1000
-      value: 49.683
-    - type: ndcg_at_3
-      value: 38.043
-    - type: ndcg_at_5
-      value: 40.217999999999996
-    - type: precision_at_1
-      value: 33.282000000000004
-    - type: precision_at_10
-      value: 6.748
-    - type: precision_at_100
-      value: 0.979
-    - type: precision_at_1000
-      value: 0.126
-    - type: precision_at_3
-      value: 16.462
-    - type: precision_at_5
-      value: 11.411
-    - type: recall_at_1
-      value: 29.311999999999998
-    - type: recall_at_10
-      value: 54.294
-    - type: recall_at_100
-      value: 75.82
-    - type: recall_at_1000
-      value: 93.19800000000001
-    - type: recall_at_3
-      value: 41.382999999999996
-    - type: recall_at_5
-      value: 46.898
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/tex
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.823
-    - type: map_at_10
-      value: 31.682
-    - type: map_at_100
-      value: 32.864
-    - type: map_at_1000
-      value: 32.988
-    - type: map_at_3
-      value: 28.878999999999998
-    - type: map_at_5
-      value: 30.459000000000003
-    - type: mrr_at_1
-      value: 28.63
-    - type: mrr_at_10
-      value: 36.672
-    - type: mrr_at_100
-      value: 37.519999999999996
-    - type: mrr_at_1000
-      value: 37.588
-    - type: mrr_at_3
-      value: 34.262
-    - type: mrr_at_5
-      value: 35.653
-    - type: ndcg_at_1
-      value: 28.63
-    - type: ndcg_at_10
-      value: 37.158
-    - type: ndcg_at_100
-      value: 42.4
-    - type: ndcg_at_1000
-      value: 45.001000000000005
-    - type: ndcg_at_3
-      value: 32.529
-    - type: ndcg_at_5
-      value: 34.673
-    - type: precision_at_1
-      value: 28.63
-    - type: precision_at_10
-      value: 6.848
-    - type: precision_at_100
-      value: 1.111
-    - type: precision_at_1000
-      value: 0.152
-    - type: precision_at_3
-      value: 15.623000000000001
-    - type: precision_at_5
-      value: 11.218
-    - type: recall_at_1
-      value: 22.823
-    - type: recall_at_10
-      value: 48.559000000000005
-    - type: recall_at_100
-      value: 72.048
-    - type: recall_at_1000
-      value: 90.322
-    - type: recall_at_3
-      value: 35.134
-    - type: recall_at_5
-      value: 40.897
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/unix
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.79
-    - type: map_at_10
-      value: 43.578
-    - type: map_at_100
-      value: 44.782
-    - type: map_at_1000
-      value: 44.869
-    - type: map_at_3
-      value: 39.737
-    - type: map_at_5
-      value: 41.92
-    - type: mrr_at_1
-      value: 39.086
-    - type: mrr_at_10
-      value: 48.135
-    - type: mrr_at_100
-      value: 48.949
-    - type: mrr_at_1000
-      value: 48.995
-    - type: mrr_at_3
-      value: 45.086999999999996
-    - type: mrr_at_5
-      value: 46.939
-    - type: ndcg_at_1
-      value: 39.086
-    - type: ndcg_at_10
-      value: 49.736999999999995
-    - type: ndcg_at_100
-      value: 54.818999999999996
-    - type: ndcg_at_1000
-      value: 56.515
-    - type: ndcg_at_3
-      value: 43.503
-    - type: ndcg_at_5
-      value: 46.499
-    - type: precision_at_1
-      value: 39.086
-    - type: precision_at_10
-      value: 8.685
-    - type: precision_at_100
-      value: 1.2449999999999999
-    - type: precision_at_1000
-      value: 0.148
-    - type: precision_at_3
-      value: 19.963
-    - type: precision_at_5
-      value: 14.366000000000001
-    - type: recall_at_1
-      value: 32.79
-    - type: recall_at_10
-      value: 63.766
-    - type: recall_at_100
-      value: 85.465
-    - type: recall_at_1000
-      value: 96.90299999999999
-    - type: recall_at_3
-      value: 46.515
-    - type: recall_at_5
-      value: 54.178000000000004
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/webmasters
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.896
-    - type: map_at_10
-      value: 41.241
-    - type: map_at_100
-      value: 43.178
-    - type: map_at_1000
-      value: 43.395
-    - type: map_at_3
-      value: 37.702999999999996
-    - type: map_at_5
-      value: 39.524
-    - type: mrr_at_1
-      value: 36.364000000000004
-    - type: mrr_at_10
-      value: 46.184999999999995
-    - type: mrr_at_100
-      value: 47.051
-    - type: mrr_at_1000
-      value: 47.085
-    - type: mrr_at_3
-      value: 43.478
-    - type: mrr_at_5
-      value: 44.98
-    - type: ndcg_at_1
-      value: 36.364000000000004
-    - type: ndcg_at_10
-      value: 48.044
-    - type: ndcg_at_100
-      value: 53.818999999999996
-    - type: ndcg_at_1000
-      value: 55.504
-    - type: ndcg_at_3
-      value: 42.604
-    - type: ndcg_at_5
-      value: 44.971
-    - type: precision_at_1
-      value: 36.364000000000004
-    - type: precision_at_10
-      value: 9.664
-    - type: precision_at_100
-      value: 1.917
-    - type: precision_at_1000
-      value: 0.255
-    - type: precision_at_3
-      value: 20.487
-    - type: precision_at_5
-      value: 14.862
-    - type: recall_at_1
-      value: 29.896
-    - type: recall_at_10
-      value: 60.28
-    - type: recall_at_100
-      value: 86.271
-    - type: recall_at_1000
-      value: 97.121
-    - type: recall_at_3
-      value: 44.885999999999996
-    - type: recall_at_5
-      value: 51.351
-  - task:
-      type: Retrieval
-    dataset:
-      type: cqadupstack/wordpress
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 27.948
-    - type: map_at_10
-      value: 36.138999999999996
-    - type: map_at_100
-      value: 37.126999999999995
-    - type: map_at_1000
-      value: 37.21
-    - type: map_at_3
-      value: 33.526
-    - type: map_at_5
-      value: 35.163
-    - type: mrr_at_1
-      value: 30.684
-    - type: mrr_at_10
-      value: 38.818999999999996
-    - type: mrr_at_100
-      value: 39.625
-    - type: mrr_at_1000
-      value: 39.678000000000004
-    - type: mrr_at_3
-      value: 36.506
-    - type: mrr_at_5
-      value: 37.976
-    - type: ndcg_at_1
-      value: 30.684
-    - type: ndcg_at_10
-      value: 41.134
-    - type: ndcg_at_100
-      value: 46.081
-    - type: ndcg_at_1000
-      value: 48.199999999999996
-    - type: ndcg_at_3
-      value: 36.193
-    - type: ndcg_at_5
-      value: 38.903999999999996
-    - type: precision_at_1
-      value: 30.684
-    - type: precision_at_10
-      value: 6.285
-    - type: precision_at_100
-      value: 0.9520000000000001
-    - type: precision_at_1000
-      value: 0.126
-    - type: precision_at_3
-      value: 15.342
-    - type: precision_at_5
-      value: 10.869
-    - type: recall_at_1
-      value: 27.948
-    - type: recall_at_10
-      value: 53.959
-    - type: recall_at_100
-      value: 76.825
-    - type: recall_at_1000
-      value: 92.73700000000001
-    - type: recall_at_3
-      value: 40.495999999999995
-    - type: recall_at_5
-      value: 47.196
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 15.27
-    - type: map_at_10
-      value: 25.570999999999998
-    - type: map_at_100
-      value: 27.664
-    - type: map_at_1000
-      value: 27.848
-    - type: map_at_3
-      value: 21.224
-    - type: map_at_5
-      value: 23.508000000000003
-    - type: mrr_at_1
-      value: 34.137
-    - type: mrr_at_10
-      value: 46.583000000000006
-    - type: mrr_at_100
-      value: 47.339999999999996
-    - type: mrr_at_1000
-      value: 47.370000000000005
-    - type: mrr_at_3
-      value: 43.376999999999995
-    - type: mrr_at_5
-      value: 45.26
-    - type: ndcg_at_1
-      value: 34.137
-    - type: ndcg_at_10
-      value: 35.189
-    - type: ndcg_at_100
-      value: 42.568
-    - type: ndcg_at_1000
-      value: 45.660000000000004
-    - type: ndcg_at_3
-      value: 28.965000000000003
-    - type: ndcg_at_5
-      value: 31.169999999999998
-    - type: precision_at_1
-      value: 34.137
-    - type: precision_at_10
-      value: 10.971
-    - type: precision_at_100
-      value: 1.8870000000000002
-    - type: precision_at_1000
-      value: 0.247
-    - type: precision_at_3
-      value: 21.368000000000002
-    - type: precision_at_5
-      value: 16.573
-    - type: recall_at_1
-      value: 15.27
-    - type: recall_at_10
-      value: 41.516999999999996
-    - type: recall_at_100
-      value: 66.486
-    - type: recall_at_1000
-      value: 83.533
-    - type: recall_at_3
-      value: 26.325
-    - type: recall_at_5
-      value: 32.574
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 9.982000000000001
-    - type: map_at_10
-      value: 23.724999999999998
-    - type: map_at_100
-      value: 33.933
-    - type: map_at_1000
-      value: 35.965
-    - type: map_at_3
-      value: 16.158
-    - type: map_at_5
-      value: 19.433
-    - type: mrr_at_1
-      value: 75.75
-    - type: mrr_at_10
-      value: 82.065
-    - type: mrr_at_100
-      value: 82.334
-    - type: mrr_at_1000
-      value: 82.34
-    - type: mrr_at_3
-      value: 80.708
-    - type: mrr_at_5
-      value: 81.671
-    - type: ndcg_at_1
-      value: 63.625
-    - type: ndcg_at_10
-      value: 49.576
-    - type: ndcg_at_100
-      value: 53.783
-    - type: ndcg_at_1000
-      value: 61.012
-    - type: ndcg_at_3
-      value: 53.822
-    - type: ndcg_at_5
-      value: 51.72
-    - type: precision_at_1
-      value: 75.75
-    - type: precision_at_10
-      value: 39.925
-    - type: precision_at_100
-      value: 12.525
-    - type: precision_at_1000
-      value: 2.399
-    - type: precision_at_3
-      value: 56.667
-    - type: precision_at_5
-      value: 50.5
-    - type: recall_at_1
-      value: 9.982000000000001
-    - type: recall_at_10
-      value: 29.325000000000003
-    - type: recall_at_100
-      value: 59.181
-    - type: recall_at_1000
-      value: 82.095
-    - type: recall_at_3
-      value: 17.338
-    - type: recall_at_5
-      value: 22.216
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 52.04500000000001
-    - type: f1
-      value: 47.32462453881906
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 78.68
-    - type: map_at_10
-      value: 86.207
-    - type: map_at_100
-      value: 86.375
-    - type: map_at_1000
-      value: 86.388
-    - type: map_at_3
-      value: 85.35199999999999
-    - type: map_at_5
-      value: 85.954
-    - type: mrr_at_1
-      value: 84.923
-    - type: mrr_at_10
-      value: 90.902
-    - type: mrr_at_100
-      value: 90.952
-    - type: mrr_at_1000
-      value: 90.952
-    - type: mrr_at_3
-      value: 90.489
-    - type: mrr_at_5
-      value: 90.822
-    - type: ndcg_at_1
-      value: 84.923
-    - type: ndcg_at_10
-      value: 89.403
-    - type: ndcg_at_100
-      value: 90.023
-    - type: ndcg_at_1000
-      value: 90.235
-    - type: ndcg_at_3
-      value: 88.24300000000001
-    - type: ndcg_at_5
-      value: 89.005
-    - type: precision_at_1
-      value: 84.923
-    - type: precision_at_10
-      value: 10.495000000000001
-    - type: precision_at_100
-      value: 1.103
-    - type: precision_at_1000
-      value: 0.11399999999999999
-    - type: precision_at_3
-      value: 33.358
-    - type: precision_at_5
-      value: 20.579
-    - type: recall_at_1
-      value: 78.68
-    - type: recall_at_10
-      value: 94.622
-    - type: recall_at_100
-      value: 97.083
-    - type: recall_at_1000
-      value: 98.348
-    - type: recall_at_3
-      value: 91.499
-    - type: recall_at_5
-      value: 93.486
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 25.781
-    - type: map_at_10
-      value: 44.669
-    - type: map_at_100
-      value: 46.831
-    - type: map_at_1000
-      value: 46.96
-    - type: map_at_3
-      value: 38.714
-    - type: map_at_5
-      value: 42.186
-    - type: mrr_at_1
-      value: 51.235
-    - type: mrr_at_10
-      value: 60.083
-    - type: mrr_at_100
-      value: 60.675999999999995
-    - type: mrr_at_1000
-      value: 60.706
-    - type: mrr_at_3
-      value: 57.665
-    - type: mrr_at_5
-      value: 59.084
-    - type: ndcg_at_1
-      value: 51.235
-    - type: ndcg_at_10
-      value: 53.111
-    - type: ndcg_at_100
-      value: 59.57900000000001
-    - type: ndcg_at_1000
-      value: 61.57
-    - type: ndcg_at_3
-      value: 48.397
-    - type: ndcg_at_5
-      value: 50.169
-    - type: precision_at_1
-      value: 51.235
-    - type: precision_at_10
-      value: 14.877
-    - type: precision_at_100
-      value: 2.173
-    - type: precision_at_1000
-      value: 0.253
-    - type: precision_at_3
-      value: 32.87
-    - type: precision_at_5
-      value: 24.29
-    - type: recall_at_1
-      value: 25.781
-    - type: recall_at_10
-      value: 61.464
-    - type: recall_at_100
-      value: 84.244
-    - type: recall_at_1000
-      value: 96.039
-    - type: recall_at_3
-      value: 44.105
-    - type: recall_at_5
-      value: 52.205999999999996
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 39.041
-    - type: map_at_10
-      value: 66.622
-    - type: map_at_100
-      value: 67.472
-    - type: map_at_1000
-      value: 67.52
-    - type: map_at_3
-      value: 62.81099999999999
-    - type: map_at_5
-      value: 65.23
-    - type: mrr_at_1
-      value: 78.082
-    - type: mrr_at_10
-      value: 83.827
-    - type: mrr_at_100
-      value: 84.03
-    - type: mrr_at_1000
-      value: 84.036
-    - type: mrr_at_3
-      value: 82.894
-    - type: mrr_at_5
-      value: 83.482
-    - type: ndcg_at_1
-      value: 78.082
-    - type: ndcg_at_10
-      value: 74.068
-    - type: ndcg_at_100
-      value: 76.981
-    - type: ndcg_at_1000
-      value: 77.887
-    - type: ndcg_at_3
-      value: 68.77600000000001
-    - type: ndcg_at_5
-      value: 71.763
-    - type: precision_at_1
-      value: 78.082
-    - type: precision_at_10
-      value: 15.822
-    - type: precision_at_100
-      value: 1.807
-    - type: precision_at_1000
-      value: 0.193
-    - type: precision_at_3
-      value: 44.956
-    - type: precision_at_5
-      value: 29.332
-    - type: recall_at_1
-      value: 39.041
-    - type: recall_at_10
-      value: 79.109
-    - type: recall_at_100
-      value: 90.371
-    - type: recall_at_1000
-      value: 96.313
-    - type: recall_at_3
-      value: 67.43400000000001
-    - type: recall_at_5
-      value: 73.329
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 87.422
-    - type: ap
-      value: 83.07360776629146
-    - type: f1
-      value: 87.38583428778229
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.715999999999998
-    - type: map_at_10
-      value: 34.821000000000005
-    - type: map_at_100
-      value: 36.022999999999996
-    - type: map_at_1000
-      value: 36.067
-    - type: map_at_3
-      value: 30.666
-    - type: map_at_5
-      value: 33.134
-    - type: mrr_at_1
-      value: 22.421
-    - type: mrr_at_10
-      value: 35.461
-    - type: mrr_at_100
-      value: 36.6
-    - type: mrr_at_1000
-      value: 36.638
-    - type: mrr_at_3
-      value: 31.413999999999998
-    - type: mrr_at_5
-      value: 33.823
-    - type: ndcg_at_1
-      value: 22.421
-    - type: ndcg_at_10
-      value: 42.169000000000004
-    - type: ndcg_at_100
-      value: 47.887
-    - type: ndcg_at_1000
-      value: 48.939
-    - type: ndcg_at_3
-      value: 33.786
-    - type: ndcg_at_5
-      value: 38.164
-    - type: precision_at_1
-      value: 22.421
-    - type: precision_at_10
-      value: 6.773999999999999
-    - type: precision_at_100
-      value: 0.962
-    - type: precision_at_1000
-      value: 0.105
-    - type: precision_at_3
-      value: 14.575
-    - type: precision_at_5
-      value: 10.963000000000001
-    - type: recall_at_1
-      value: 21.715999999999998
-    - type: recall_at_10
-      value: 64.75999999999999
-    - type: recall_at_100
-      value: 91.015
-    - type: recall_at_1000
-      value: 98.96000000000001
-    - type: recall_at_3
-      value: 42.089999999999996
-    - type: recall_at_5
-      value: 52.578
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 96.04195166438669
-    - type: f1
-      value: 95.76962987454031
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 84.76744186046513
-    - type: f1
-      value: 70.3328215706764
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 79.29051782111635
-    - type: f1
-      value: 77.0837414890434
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 81.64425016812373
-    - type: f1
-      value: 81.36288379329044
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 31.0673311773222
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 31.266850505047234
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 31.49575275757744
-    - type: mrr
-      value: 32.64979714009148
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 6.151
-    - type: map_at_10
-      value: 14.879999999999999
-    - type: map_at_100
-      value: 19.445999999999998
-    - type: map_at_1000
-      value: 21.101
-    - type: map_at_3
-      value: 10.613999999999999
-    - type: map_at_5
-      value: 12.709000000000001
-    - type: mrr_at_1
-      value: 51.393
-    - type: mrr_at_10
-      value: 59.935
-    - type: mrr_at_100
-      value: 60.455000000000005
-    - type: mrr_at_1000
-      value: 60.485
-    - type: mrr_at_3
-      value: 57.894999999999996
-    - type: mrr_at_5
-      value: 59.303
-    - type: ndcg_at_1
-      value: 50.0
-    - type: ndcg_at_10
-      value: 39.324999999999996
-    - type: ndcg_at_100
-      value: 37.133
-    - type: ndcg_at_1000
-      value: 45.663
-    - type: ndcg_at_3
-      value: 45.294000000000004
-    - type: ndcg_at_5
-      value: 42.88
-    - type: precision_at_1
-      value: 51.393
-    - type: precision_at_10
-      value: 29.412
-    - type: precision_at_100
-      value: 9.666
-    - type: precision_at_1000
-      value: 2.263
-    - type: precision_at_3
-      value: 42.415000000000006
-    - type: precision_at_5
-      value: 37.399
-    - type: recall_at_1
-      value: 6.151
-    - type: recall_at_10
-      value: 19.121
-    - type: recall_at_100
-      value: 39.012
-    - type: recall_at_1000
-      value: 70.726
-    - type: recall_at_3
-      value: 11.855
-    - type: recall_at_5
-      value: 15.204
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 36.382
-    - type: map_at_10
-      value: 53.657
-    - type: map_at_100
-      value: 54.547999999999995
-    - type: map_at_1000
-      value: 54.562999999999995
-    - type: map_at_3
-      value: 49.236999999999995
-    - type: map_at_5
-      value: 51.949
-    - type: mrr_at_1
-      value: 41.309000000000005
-    - type: mrr_at_10
-      value: 56.25599999999999
-    - type: mrr_at_100
-      value: 56.855999999999995
-    - type: mrr_at_1000
-      value: 56.867000000000004
-    - type: mrr_at_3
-      value: 52.891999999999996
-    - type: mrr_at_5
-      value: 54.99699999999999
-    - type: ndcg_at_1
-      value: 41.28
-    - type: ndcg_at_10
-      value: 61.702999999999996
-    - type: ndcg_at_100
-      value: 65.092
-    - type: ndcg_at_1000
-      value: 65.392
-    - type: ndcg_at_3
-      value: 53.722
-    - type: ndcg_at_5
-      value: 58.11300000000001
-    - type: precision_at_1
-      value: 41.28
-    - type: precision_at_10
-      value: 10.014000000000001
-    - type: precision_at_100
-      value: 1.187
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 24.614
-    - type: precision_at_5
-      value: 17.317
-    - type: recall_at_1
-      value: 36.382
-    - type: recall_at_10
-      value: 83.38600000000001
-    - type: recall_at_100
-      value: 97.528
-    - type: recall_at_1000
-      value: 99.696
-    - type: recall_at_3
-      value: 63.053000000000004
-    - type: recall_at_5
-      value: 73.16
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 69.577
-    - type: map_at_10
-      value: 83.944
-    - type: map_at_100
-      value: 84.604
-    - type: map_at_1000
-      value: 84.61800000000001
-    - type: map_at_3
-      value: 80.93599999999999
-    - type: map_at_5
-      value: 82.812
-    - type: mrr_at_1
-      value: 80.4
-    - type: mrr_at_10
-      value: 86.734
-    - type: mrr_at_100
-      value: 86.851
-    - type: mrr_at_1000
-      value: 86.85199999999999
-    - type: mrr_at_3
-      value: 85.75500000000001
-    - type: mrr_at_5
-      value: 86.396
-    - type: ndcg_at_1
-      value: 80.43
-    - type: ndcg_at_10
-      value: 87.75
-    - type: ndcg_at_100
-      value: 88.999
-    - type: ndcg_at_1000
-      value: 89.092
-    - type: ndcg_at_3
-      value: 84.88
-    - type: ndcg_at_5
-      value: 86.416
-    - type: precision_at_1
-      value: 80.43
-    - type: precision_at_10
-      value: 13.453000000000001
-    - type: precision_at_100
-      value: 1.539
-    - type: precision_at_1000
-      value: 0.157
-    - type: precision_at_3
-      value: 37.403
-    - type: precision_at_5
-      value: 24.648
-    - type: recall_at_1
-      value: 69.577
-    - type: recall_at_10
-      value: 95.233
-    - type: recall_at_100
-      value: 99.531
-    - type: recall_at_1000
-      value: 99.984
-    - type: recall_at_3
-      value: 86.867
-    - type: recall_at_5
-      value: 91.254
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 60.23690763558931
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 64.12391112159126
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.288
-    - type: map_at_10
-      value: 13.611999999999998
-    - type: map_at_100
-      value: 15.909
-    - type: map_at_1000
-      value: 16.235
-    - type: map_at_3
-      value: 9.644
-    - type: map_at_5
-      value: 11.559
-    - type: mrr_at_1
-      value: 26.1
-    - type: mrr_at_10
-      value: 37.571
-    - type: mrr_at_100
-      value: 38.72
-    - type: mrr_at_1000
-      value: 38.76
-    - type: mrr_at_3
-      value: 34.383
-    - type: mrr_at_5
-      value: 36.187999999999995
-    - type: ndcg_at_1
-      value: 26.1
-    - type: ndcg_at_10
-      value: 22.497
-    - type: ndcg_at_100
-      value: 31.098
-    - type: ndcg_at_1000
-      value: 36.434
-    - type: ndcg_at_3
-      value: 21.401
-    - type: ndcg_at_5
-      value: 18.66
-    - type: precision_at_1
-      value: 26.1
-    - type: precision_at_10
-      value: 11.67
-    - type: precision_at_100
-      value: 2.405
-    - type: precision_at_1000
-      value: 0.368
-    - type: precision_at_3
-      value: 20.0
-    - type: precision_at_5
-      value: 16.34
-    - type: recall_at_1
-      value: 5.288
-    - type: recall_at_10
-      value: 23.652
-    - type: recall_at_100
-      value: 48.79
-    - type: recall_at_1000
-      value: 74.703
-    - type: recall_at_3
-      value: 12.158
-    - type: recall_at_5
-      value: 16.582
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_spearman
-      value: 83.6969699802343
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_spearman
-      value: 78.8031221769135
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_spearman
-      value: 86.37435789895171
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_spearman
-      value: 84.04036612478626
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_spearman
-      value: 88.99055778929946
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_spearman
-      value: 87.22140434759893
-  - 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: 90.1862731405498
-  - 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: 67.67995229420237
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_spearman
-      value: 88.65370934976113
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 83.79832393152147
-    - type: mrr
-      value: 95.78404438698557
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 64.883
-    - type: map_at_10
-      value: 74.48
-    - type: map_at_100
-      value: 74.85000000000001
-    - type: map_at_1000
-      value: 74.861
-    - type: map_at_3
-      value: 71.596
-    - type: map_at_5
-      value: 73.545
-    - type: mrr_at_1
-      value: 67.667
-    - type: mrr_at_10
-      value: 75.394
-    - type: mrr_at_100
-      value: 75.644
-    - type: mrr_at_1000
-      value: 75.655
-    - type: mrr_at_3
-      value: 73.5
-    - type: mrr_at_5
-      value: 74.63300000000001
-    - type: ndcg_at_1
-      value: 67.667
-    - type: ndcg_at_10
-      value: 78.855
-    - type: ndcg_at_100
-      value: 80.361
-    - type: ndcg_at_1000
-      value: 80.624
-    - type: ndcg_at_3
-      value: 74.37899999999999
-    - type: ndcg_at_5
-      value: 76.89200000000001
-    - type: precision_at_1
-      value: 67.667
-    - type: precision_at_10
-      value: 10.267
-    - type: precision_at_100
-      value: 1.11
-    - type: precision_at_1000
-      value: 0.11299999999999999
-    - type: precision_at_3
-      value: 28.778
-    - type: precision_at_5
-      value: 19.133
-    - type: recall_at_1
-      value: 64.883
-    - type: recall_at_10
-      value: 91.2
-    - type: recall_at_100
-      value: 98.0
-    - type: recall_at_1000
-      value: 100.0
-    - type: recall_at_3
-      value: 79.406
-    - type: recall_at_5
-      value: 85.578
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.85445544554456
-    - type: cos_sim_ap
-      value: 96.81785428870712
-    - type: cos_sim_f1
-      value: 92.67563527653213
-    - type: cos_sim_precision
-      value: 92.35352532274081
-    - type: cos_sim_recall
-      value: 93.0
-    - type: dot_accuracy
-      value: 99.75643564356436
-    - type: dot_ap
-      value: 94.46746929160422
-    - type: dot_f1
-      value: 87.74900398406375
-    - type: dot_precision
-      value: 87.40079365079364
-    - type: dot_recall
-      value: 88.1
-    - type: euclidean_accuracy
-      value: 99.85445544554456
-    - type: euclidean_ap
-      value: 96.59180137299155
-    - type: euclidean_f1
-      value: 92.48850281042411
-    - type: euclidean_precision
-      value: 94.56635318704284
-    - type: euclidean_recall
-      value: 90.5
-    - type: manhattan_accuracy
-      value: 99.85643564356435
-    - type: manhattan_ap
-      value: 96.66599616275849
-    - type: manhattan_f1
-      value: 92.69746646795828
-    - type: manhattan_precision
-      value: 92.10266535044423
-    - type: manhattan_recall
-      value: 93.30000000000001
-    - type: max_accuracy
-      value: 99.85643564356435
-    - type: max_ap
-      value: 96.81785428870712
-    - type: max_f1
-      value: 92.69746646795828
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 70.72970157362414
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 34.49706344517027
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 54.41010678297881
-    - type: mrr
-      value: 55.15095811051693
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.5030094989814
-    - type: cos_sim_spearman
-      value: 29.959138274084797
-    - type: dot_pearson
-      value: 29.740134155639076
-    - type: dot_spearman
-      value: 29.18174652067779
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.22200000000000003
-    - type: map_at_10
-      value: 1.925
-    - type: map_at_100
-      value: 13.150999999999998
-    - type: map_at_1000
-      value: 33.410000000000004
-    - type: map_at_3
-      value: 0.631
-    - type: map_at_5
-      value: 0.9990000000000001
-    - type: mrr_at_1
-      value: 82.0
-    - type: mrr_at_10
-      value: 90.0
-    - type: mrr_at_100
-      value: 90.0
-    - type: mrr_at_1000
-      value: 90.0
-    - type: mrr_at_3
-      value: 89.0
-    - type: mrr_at_5
-      value: 90.0
-    - type: ndcg_at_1
-      value: 79.0
-    - type: ndcg_at_10
-      value: 77.69200000000001
-    - type: ndcg_at_100
-      value: 64.89
-    - type: ndcg_at_1000
-      value: 59.748999999999995
-    - type: ndcg_at_3
-      value: 79.296
-    - type: ndcg_at_5
-      value: 78.63
-    - type: precision_at_1
-      value: 82.0
-    - type: precision_at_10
-      value: 82.19999999999999
-    - type: precision_at_100
-      value: 67.52
-    - type: precision_at_1000
-      value: 26.512
-    - type: precision_at_3
-      value: 83.333
-    - type: precision_at_5
-      value: 83.2
-    - type: recall_at_1
-      value: 0.22200000000000003
-    - type: recall_at_10
-      value: 2.164
-    - type: recall_at_100
-      value: 16.608
-    - type: recall_at_1000
-      value: 56.89999999999999
-    - type: recall_at_3
-      value: 0.658
-    - type: recall_at_5
-      value: 1.084
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 1.8519999999999999
-    - type: map_at_10
-      value: 8.569
-    - type: map_at_100
-      value: 14.238999999999999
-    - type: map_at_1000
-      value: 15.876000000000001
-    - type: map_at_3
-      value: 3.9859999999999998
-    - type: map_at_5
-      value: 5.785
-    - type: mrr_at_1
-      value: 26.531
-    - type: mrr_at_10
-      value: 40.581
-    - type: mrr_at_100
-      value: 41.379
-    - type: mrr_at_1000
-      value: 41.388999999999996
-    - type: mrr_at_3
-      value: 35.034
-    - type: mrr_at_5
-      value: 38.299
-    - type: ndcg_at_1
-      value: 25.509999999999998
-    - type: ndcg_at_10
-      value: 22.18
-    - type: ndcg_at_100
-      value: 34.695
-    - type: ndcg_at_1000
-      value: 46.854
-    - type: ndcg_at_3
-      value: 23.112
-    - type: ndcg_at_5
-      value: 23.089000000000002
-    - type: precision_at_1
-      value: 26.531
-    - type: precision_at_10
-      value: 20.408
-    - type: precision_at_100
-      value: 7.428999999999999
-    - type: precision_at_1000
-      value: 1.559
-    - type: precision_at_3
-      value: 23.810000000000002
-    - type: precision_at_5
-      value: 23.265
-    - type: recall_at_1
-      value: 1.8519999999999999
-    - type: recall_at_10
-      value: 15.038000000000002
-    - type: recall_at_100
-      value: 46.499
-    - type: recall_at_1000
-      value: 84.11800000000001
-    - type: recall_at_3
-      value: 5.179
-    - type: recall_at_5
-      value: 8.758000000000001
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 69.26140000000001
-    - type: ap
-      value: 14.138284541193421
-    - type: f1
-      value: 53.715363590501916
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 62.136389360498015
-    - type: f1
-      value: 62.33290824449911
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 52.18306009684791
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.27561542588067
-    - type: cos_sim_ap
-      value: 80.59558041410928
-    - type: cos_sim_f1
-      value: 73.54724608388075
-    - type: cos_sim_precision
-      value: 70.55259331071255
-    - type: cos_sim_recall
-      value: 76.80738786279684
-    - type: dot_accuracy
-      value: 85.00923883888657
-    - type: dot_ap
-      value: 71.76942851966301
-    - type: dot_f1
-      value: 66.84518013631937
-    - type: dot_precision
-      value: 62.042476276547674
-    - type: dot_recall
-      value: 72.45382585751979
-    - type: euclidean_accuracy
-      value: 88.26965488466352
-    - type: euclidean_ap
-      value: 80.44398056118867
-    - type: euclidean_f1
-      value: 73.28244274809161
-    - type: euclidean_precision
-      value: 68.69806094182826
-    - type: euclidean_recall
-      value: 78.52242744063325
-    - type: manhattan_accuracy
-      value: 88.25773380222924
-    - type: manhattan_ap
-      value: 80.25000483445007
-    - type: manhattan_f1
-      value: 73.10447023956533
-    - type: manhattan_precision
-      value: 68.70937790157846
-    - type: manhattan_recall
-      value: 78.10026385224275
-    - type: max_accuracy
-      value: 88.27561542588067
-    - type: max_ap
-      value: 80.59558041410928
-    - type: max_f1
-      value: 73.54724608388075
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 89.52536189700004
-    - type: cos_sim_ap
-      value: 86.55972191277392
-    - type: cos_sim_f1
-      value: 79.31733569243245
-    - type: cos_sim_precision
-      value: 76.08372816632487
-    - type: cos_sim_recall
-      value: 82.83800431167231
-    - type: dot_accuracy
-      value: 87.77506112469437
-    - type: dot_ap
-      value: 82.92833178514168
-    - type: dot_f1
-      value: 76.12050479839702
-    - type: dot_precision
-      value: 70.03687172520861
-    - type: dot_recall
-      value: 83.3615645210964
-    - type: euclidean_accuracy
-      value: 89.3643031784841
-    - type: euclidean_ap
-      value: 86.45902920741383
-    - type: euclidean_f1
-      value: 79.4788514062154
-    - type: euclidean_precision
-      value: 76.32922160782645
-    - type: euclidean_recall
-      value: 82.89959963042809
-    - type: manhattan_accuracy
-      value: 89.38564830985369
-    - type: manhattan_ap
-      value: 86.47558438668958
-    - type: manhattan_f1
-      value: 79.46758328152997
-    - type: manhattan_precision
-      value: 75.67379343965457
-    - type: manhattan_recall
-      value: 83.66184170003079
-    - type: max_accuracy
-      value: 89.52536189700004
-    - type: max_ap
-      value: 86.55972191277392
-    - type: max_f1
-      value: 79.4788514062154
 ---
 
 # LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders