sentence-transformers safetensors bert feature-extraction sentence-similarity mteb model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: MUG-B-1.6
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.04047976011994
    - type: ap
      value: 23.622442298323236
    - type: f1
      value: 61.681362134359354
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.38805970149255
    - type: ap
      value: 35.14527522183942
    - type: f1
      value: 66.40004634079556
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (de)
      type: mteb/amazon_counterfactual
      config: de
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 54.3254817987152
    - type: ap
      value: 71.95259605308317
    - type: f1
      value: 52.50731386267296
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (ja)
      type: mteb/amazon_counterfactual
      config: ja
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 56.33832976445397
    - type: ap
      value: 12.671021199223937
    - type: f1
      value: 46.127586182990605
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 93.70805000000001
    - type: ap
      value: 90.58639913354553
    - type: f1
      value: 93.69822635061847
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 50.85000000000001
    - type: f1
      value: 49.80013009020246
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (de)
      type: mteb/amazon_reviews_multi
      config: de
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 27.203999999999994
    - type: f1
      value: 26.60134413072989
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (es)
      type: mteb/amazon_reviews_multi
      config: es
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.878
    - type: f1
      value: 33.072592092252314
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (fr)
      type: mteb/amazon_reviews_multi
      config: fr
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.557999999999993
    - type: f1
      value: 30.866094552542624
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (ja)
      type: mteb/amazon_reviews_multi
      config: ja
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 22.706
    - type: f1
      value: 22.23195837325246
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 22.349999999999998
    - type: f1
      value: 21.80183891680617
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 41.892
    - type: map_at_10
      value: 57.989999999999995
    - type: map_at_100
      value: 58.45
    - type: map_at_1000
      value: 58.453
    - type: map_at_20
      value: 58.392999999999994
    - type: map_at_3
      value: 53.746
    - type: map_at_5
      value: 56.566
    - type: mrr_at_1
      value: 43.314
    - type: mrr_at_10
      value: 58.535000000000004
    - type: mrr_at_100
      value: 58.975
    - type: mrr_at_1000
      value: 58.977999999999994
    - type: mrr_at_20
      value: 58.916999999999994
    - type: mrr_at_3
      value: 54.303000000000004
    - type: mrr_at_5
      value: 57.055
    - type: ndcg_at_1
      value: 41.892
    - type: ndcg_at_10
      value: 66.176
    - type: ndcg_at_100
      value: 67.958
    - type: ndcg_at_1000
      value: 68.00699999999999
    - type: ndcg_at_20
      value: 67.565
    - type: ndcg_at_3
      value: 57.691
    - type: ndcg_at_5
      value: 62.766
    - type: precision_at_1
      value: 41.892
    - type: precision_at_10
      value: 9.189
    - type: precision_at_100
      value: 0.993
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.861
    - type: precision_at_3
      value: 23.044
    - type: precision_at_5
      value: 16.287
    - type: recall_at_1
      value: 41.892
    - type: recall_at_10
      value: 91.892
    - type: recall_at_100
      value: 99.289
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 97.226
    - type: recall_at_3
      value: 69.132
    - type: recall_at_5
      value: 81.437
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 49.03486273664411
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 43.04797567338598
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 64.29499572176032
    - type: mrr
      value: 77.28861627753592
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 89.53248242133246
    - type: cos_sim_spearman
      value: 88.38032705871927
    - type: euclidean_pearson
      value: 87.77994445569084
    - type: euclidean_spearman
      value: 88.38032705871927
    - type: manhattan_pearson
      value: 87.52369210088627
    - type: manhattan_spearman
      value: 88.27972235673434
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 85.4090909090909
    - type: f1
      value: 84.87743757972068
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.73840151083438
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 36.565075977998966
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 33.082
    - type: map_at_10
      value: 44.787
    - type: map_at_100
      value: 46.322
    - type: map_at_1000
      value: 46.446
    - type: map_at_20
      value: 45.572
    - type: map_at_3
      value: 40.913
    - type: map_at_5
      value: 42.922
    - type: mrr_at_1
      value: 40.629
    - type: mrr_at_10
      value: 51.119
    - type: mrr_at_100
      value: 51.783
    - type: mrr_at_1000
      value: 51.82
    - type: mrr_at_20
      value: 51.49700000000001
    - type: mrr_at_3
      value: 48.355
    - type: mrr_at_5
      value: 49.979
    - type: ndcg_at_1
      value: 40.629
    - type: ndcg_at_10
      value: 51.647
    - type: ndcg_at_100
      value: 56.923
    - type: ndcg_at_1000
      value: 58.682
    - type: ndcg_at_20
      value: 53.457
    - type: ndcg_at_3
      value: 46.065
    - type: ndcg_at_5
      value: 48.352000000000004
    - type: precision_at_1
      value: 40.629
    - type: precision_at_10
      value: 10.072000000000001
    - type: precision_at_100
      value: 1.5939999999999999
    - type: precision_at_1000
      value: 0.20600000000000002
    - type: precision_at_20
      value: 5.908
    - type: precision_at_3
      value: 22.222
    - type: precision_at_5
      value: 15.937000000000001
    - type: recall_at_1
      value: 33.082
    - type: recall_at_10
      value: 64.55300000000001
    - type: recall_at_100
      value: 86.86399999999999
    - type: recall_at_1000
      value: 97.667
    - type: recall_at_20
      value: 70.988
    - type: recall_at_3
      value: 48.067
    - type: recall_at_5
      value: 54.763
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 32.272
    - type: map_at_10
      value: 42.620000000000005
    - type: map_at_100
      value: 43.936
    - type: map_at_1000
      value: 44.066
    - type: map_at_20
      value: 43.349
    - type: map_at_3
      value: 39.458
    - type: map_at_5
      value: 41.351
    - type: mrr_at_1
      value: 40.127
    - type: mrr_at_10
      value: 48.437000000000005
    - type: mrr_at_100
      value: 49.096000000000004
    - type: mrr_at_1000
      value: 49.14
    - type: mrr_at_20
      value: 48.847
    - type: mrr_at_3
      value: 46.21
    - type: mrr_at_5
      value: 47.561
    - type: ndcg_at_1
      value: 40.127
    - type: ndcg_at_10
      value: 48.209999999999994
    - type: ndcg_at_100
      value: 52.632
    - type: ndcg_at_1000
      value: 54.59
    - type: ndcg_at_20
      value: 50.012
    - type: ndcg_at_3
      value: 43.996
    - type: ndcg_at_5
      value: 46.122
    - type: precision_at_1
      value: 40.127
    - type: precision_at_10
      value: 9.051
    - type: precision_at_100
      value: 1.465
    - type: precision_at_1000
      value: 0.193
    - type: precision_at_20
      value: 5.35
    - type: precision_at_3
      value: 21.104
    - type: precision_at_5
      value: 15.146
    - type: recall_at_1
      value: 32.272
    - type: recall_at_10
      value: 57.870999999999995
    - type: recall_at_100
      value: 76.211
    - type: recall_at_1000
      value: 88.389
    - type: recall_at_20
      value: 64.354
    - type: recall_at_3
      value: 45.426
    - type: recall_at_5
      value: 51.23799999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 40.261
    - type: map_at_10
      value: 53.400000000000006
    - type: map_at_100
      value: 54.42399999999999
    - type: map_at_1000
      value: 54.473000000000006
    - type: map_at_20
      value: 54.052
    - type: map_at_3
      value: 49.763000000000005
    - type: map_at_5
      value: 51.878
    - type: mrr_at_1
      value: 46.019
    - type: mrr_at_10
      value: 56.653
    - type: mrr_at_100
      value: 57.28
    - type: mrr_at_1000
      value: 57.303000000000004
    - type: mrr_at_20
      value: 57.057
    - type: mrr_at_3
      value: 53.971000000000004
    - type: mrr_at_5
      value: 55.632000000000005
    - type: ndcg_at_1
      value: 46.019
    - type: ndcg_at_10
      value: 59.597
    - type: ndcg_at_100
      value: 63.452
    - type: ndcg_at_1000
      value: 64.434
    - type: ndcg_at_20
      value: 61.404
    - type: ndcg_at_3
      value: 53.620999999999995
    - type: ndcg_at_5
      value: 56.688
    - type: precision_at_1
      value: 46.019
    - type: precision_at_10
      value: 9.748999999999999
    - type: precision_at_100
      value: 1.261
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_20
      value: 5.436
    - type: precision_at_3
      value: 24.075
    - type: precision_at_5
      value: 16.715
    - type: recall_at_1
      value: 40.261
    - type: recall_at_10
      value: 74.522
    - type: recall_at_100
      value: 91.014
    - type: recall_at_1000
      value: 98.017
    - type: recall_at_20
      value: 81.186
    - type: recall_at_3
      value: 58.72500000000001
    - type: recall_at_5
      value: 66.23599999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 27.666
    - type: map_at_10
      value: 36.744
    - type: map_at_100
      value: 37.794
    - type: map_at_1000
      value: 37.865
    - type: map_at_20
      value: 37.336999999999996
    - type: map_at_3
      value: 33.833999999999996
    - type: map_at_5
      value: 35.61
    - type: mrr_at_1
      value: 29.944
    - type: mrr_at_10
      value: 38.838
    - type: mrr_at_100
      value: 39.765
    - type: mrr_at_1000
      value: 39.818999999999996
    - type: mrr_at_20
      value: 39.373000000000005
    - type: mrr_at_3
      value: 36.234
    - type: mrr_at_5
      value: 37.844
    - type: ndcg_at_1
      value: 29.944
    - type: ndcg_at_10
      value: 41.986000000000004
    - type: ndcg_at_100
      value: 47.05
    - type: ndcg_at_1000
      value: 48.897
    - type: ndcg_at_20
      value: 43.989
    - type: ndcg_at_3
      value: 36.452
    - type: ndcg_at_5
      value: 39.395
    - type: precision_at_1
      value: 29.944
    - type: precision_at_10
      value: 6.4750000000000005
    - type: precision_at_100
      value: 0.946
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 3.6839999999999997
    - type: precision_at_3
      value: 15.443000000000001
    - type: precision_at_5
      value: 10.96
    - type: recall_at_1
      value: 27.666
    - type: recall_at_10
      value: 56.172999999999995
    - type: recall_at_100
      value: 79.142
    - type: recall_at_1000
      value: 93.013
    - type: recall_at_20
      value: 63.695
    - type: recall_at_3
      value: 41.285
    - type: recall_at_5
      value: 48.36
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 17.939
    - type: map_at_10
      value: 27.301
    - type: map_at_100
      value: 28.485
    - type: map_at_1000
      value: 28.616000000000003
    - type: map_at_20
      value: 27.843
    - type: map_at_3
      value: 24.342
    - type: map_at_5
      value: 26.259
    - type: mrr_at_1
      value: 22.761
    - type: mrr_at_10
      value: 32.391
    - type: mrr_at_100
      value: 33.297
    - type: mrr_at_1000
      value: 33.361000000000004
    - type: mrr_at_20
      value: 32.845
    - type: mrr_at_3
      value: 29.498
    - type: mrr_at_5
      value: 31.375999999999998
    - type: ndcg_at_1
      value: 22.761
    - type: ndcg_at_10
      value: 33.036
    - type: ndcg_at_100
      value: 38.743
    - type: ndcg_at_1000
      value: 41.568
    - type: ndcg_at_20
      value: 34.838
    - type: ndcg_at_3
      value: 27.803
    - type: ndcg_at_5
      value: 30.781
    - type: precision_at_1
      value: 22.761
    - type: precision_at_10
      value: 6.132
    - type: precision_at_100
      value: 1.031
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_20
      value: 3.582
    - type: precision_at_3
      value: 13.474
    - type: precision_at_5
      value: 10.123999999999999
    - type: recall_at_1
      value: 17.939
    - type: recall_at_10
      value: 45.515
    - type: recall_at_100
      value: 70.56700000000001
    - type: recall_at_1000
      value: 90.306
    - type: recall_at_20
      value: 51.946999999999996
    - type: recall_at_3
      value: 31.459
    - type: recall_at_5
      value: 39.007
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 31.156
    - type: map_at_10
      value: 42.317
    - type: map_at_100
      value: 43.742
    - type: map_at_1000
      value: 43.852000000000004
    - type: map_at_20
      value: 43.147999999999996
    - type: map_at_3
      value: 38.981
    - type: map_at_5
      value: 40.827000000000005
    - type: mrr_at_1
      value: 38.401999999999994
    - type: mrr_at_10
      value: 48.141
    - type: mrr_at_100
      value: 48.991
    - type: mrr_at_1000
      value: 49.03
    - type: mrr_at_20
      value: 48.665000000000006
    - type: mrr_at_3
      value: 45.684999999999995
    - type: mrr_at_5
      value: 47.042
    - type: ndcg_at_1
      value: 38.401999999999994
    - type: ndcg_at_10
      value: 48.541000000000004
    - type: ndcg_at_100
      value: 54.063
    - type: ndcg_at_1000
      value: 56.005
    - type: ndcg_at_20
      value: 50.895999999999994
    - type: ndcg_at_3
      value: 43.352000000000004
    - type: ndcg_at_5
      value: 45.769
    - type: precision_at_1
      value: 38.401999999999994
    - type: precision_at_10
      value: 8.738999999999999
    - type: precision_at_100
      value: 1.335
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_20
      value: 5.164
    - type: precision_at_3
      value: 20.468
    - type: precision_at_5
      value: 14.437
    - type: recall_at_1
      value: 31.156
    - type: recall_at_10
      value: 61.172000000000004
    - type: recall_at_100
      value: 83.772
    - type: recall_at_1000
      value: 96.192
    - type: recall_at_20
      value: 69.223
    - type: recall_at_3
      value: 46.628
    - type: recall_at_5
      value: 53.032000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 26.741999999999997
    - type: map_at_10
      value: 36.937
    - type: map_at_100
      value: 38.452
    - type: map_at_1000
      value: 38.557
    - type: map_at_20
      value: 37.858999999999995
    - type: map_at_3
      value: 33.579
    - type: map_at_5
      value: 35.415
    - type: mrr_at_1
      value: 32.991
    - type: mrr_at_10
      value: 42.297000000000004
    - type: mrr_at_100
      value: 43.282
    - type: mrr_at_1000
      value: 43.332
    - type: mrr_at_20
      value: 42.95
    - type: mrr_at_3
      value: 39.707
    - type: mrr_at_5
      value: 41.162
    - type: ndcg_at_1
      value: 32.991
    - type: ndcg_at_10
      value: 43.004999999999995
    - type: ndcg_at_100
      value: 49.053000000000004
    - type: ndcg_at_1000
      value: 51.166999999999994
    - type: ndcg_at_20
      value: 45.785
    - type: ndcg_at_3
      value: 37.589
    - type: ndcg_at_5
      value: 40.007999999999996
    - type: precision_at_1
      value: 32.991
    - type: precision_at_10
      value: 8.025
    - type: precision_at_100
      value: 1.268
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_20
      value: 4.846
    - type: precision_at_3
      value: 17.922
    - type: precision_at_5
      value: 13.059000000000001
    - type: recall_at_1
      value: 26.741999999999997
    - type: recall_at_10
      value: 55.635999999999996
    - type: recall_at_100
      value: 80.798
    - type: recall_at_1000
      value: 94.918
    - type: recall_at_20
      value: 65.577
    - type: recall_at_3
      value: 40.658
    - type: recall_at_5
      value: 46.812
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 27.274583333333336
    - type: map_at_10
      value: 37.04091666666666
    - type: map_at_100
      value: 38.27966666666667
    - type: map_at_1000
      value: 38.39383333333334
    - type: map_at_20
      value: 37.721500000000006
    - type: map_at_3
      value: 33.937999999999995
    - type: map_at_5
      value: 35.67974999999999
    - type: mrr_at_1
      value: 32.40525
    - type: mrr_at_10
      value: 41.43925000000001
    - type: mrr_at_100
      value: 42.271
    - type: mrr_at_1000
      value: 42.32416666666667
    - type: mrr_at_20
      value: 41.92733333333334
    - type: mrr_at_3
      value: 38.84941666666666
    - type: mrr_at_5
      value: 40.379583333333336
    - type: ndcg_at_1
      value: 32.40525
    - type: ndcg_at_10
      value: 42.73808333333334
    - type: ndcg_at_100
      value: 47.88941666666667
    - type: ndcg_at_1000
      value: 50.05008333333334
    - type: ndcg_at_20
      value: 44.74183333333334
    - type: ndcg_at_3
      value: 37.51908333333334
    - type: ndcg_at_5
      value: 40.01883333333333
    - type: precision_at_1
      value: 32.40525
    - type: precision_at_10
      value: 7.5361666666666665
    - type: precision_at_100
      value: 1.1934166666666666
    - type: precision_at_1000
      value: 0.1575
    - type: precision_at_20
      value: 4.429166666666667
    - type: precision_at_3
      value: 17.24941666666667
    - type: precision_at_5
      value: 12.362333333333336
    - type: recall_at_1
      value: 27.274583333333336
    - type: recall_at_10
      value: 55.21358333333334
    - type: recall_at_100
      value: 77.60366666666667
    - type: recall_at_1000
      value: 92.43691666666666
    - type: recall_at_20
      value: 62.474583333333335
    - type: recall_at_3
      value: 40.79375
    - type: recall_at_5
      value: 47.15158333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 27.389999999999997
    - type: map_at_10
      value: 34.107
    - type: map_at_100
      value: 35.022999999999996
    - type: map_at_1000
      value: 35.13
    - type: map_at_20
      value: 34.605999999999995
    - type: map_at_3
      value: 32.021
    - type: map_at_5
      value: 32.948
    - type: mrr_at_1
      value: 30.982
    - type: mrr_at_10
      value: 37.345
    - type: mrr_at_100
      value: 38.096999999999994
    - type: mrr_at_1000
      value: 38.179
    - type: mrr_at_20
      value: 37.769000000000005
    - type: mrr_at_3
      value: 35.481
    - type: mrr_at_5
      value: 36.293
    - type: ndcg_at_1
      value: 30.982
    - type: ndcg_at_10
      value: 38.223
    - type: ndcg_at_100
      value: 42.686
    - type: ndcg_at_1000
      value: 45.352
    - type: ndcg_at_20
      value: 39.889
    - type: ndcg_at_3
      value: 34.259
    - type: ndcg_at_5
      value: 35.664
    - type: precision_at_1
      value: 30.982
    - type: precision_at_10
      value: 5.7669999999999995
    - type: precision_at_100
      value: 0.877
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_20
      value: 3.3360000000000003
    - type: precision_at_3
      value: 14.264
    - type: precision_at_5
      value: 9.54
    - type: recall_at_1
      value: 27.389999999999997
    - type: recall_at_10
      value: 48.009
    - type: recall_at_100
      value: 68.244
    - type: recall_at_1000
      value: 87.943
    - type: recall_at_20
      value: 54.064
    - type: recall_at_3
      value: 36.813
    - type: recall_at_5
      value: 40.321
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 18.249000000000002
    - type: map_at_10
      value: 25.907000000000004
    - type: map_at_100
      value: 27.105
    - type: map_at_1000
      value: 27.233
    - type: map_at_20
      value: 26.541999999999998
    - type: map_at_3
      value: 23.376
    - type: map_at_5
      value: 24.673000000000002
    - type: mrr_at_1
      value: 21.989
    - type: mrr_at_10
      value: 29.846
    - type: mrr_at_100
      value: 30.808999999999997
    - type: mrr_at_1000
      value: 30.885
    - type: mrr_at_20
      value: 30.384
    - type: mrr_at_3
      value: 27.46
    - type: mrr_at_5
      value: 28.758
    - type: ndcg_at_1
      value: 21.989
    - type: ndcg_at_10
      value: 30.874000000000002
    - type: ndcg_at_100
      value: 36.504999999999995
    - type: ndcg_at_1000
      value: 39.314
    - type: ndcg_at_20
      value: 32.952999999999996
    - type: ndcg_at_3
      value: 26.249
    - type: ndcg_at_5
      value: 28.229
    - type: precision_at_1
      value: 21.989
    - type: precision_at_10
      value: 5.705
    - type: precision_at_100
      value: 0.9990000000000001
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_20
      value: 3.4459999999999997
    - type: precision_at_3
      value: 12.377
    - type: precision_at_5
      value: 8.961
    - type: recall_at_1
      value: 18.249000000000002
    - type: recall_at_10
      value: 41.824
    - type: recall_at_100
      value: 67.071
    - type: recall_at_1000
      value: 86.863
    - type: recall_at_20
      value: 49.573
    - type: recall_at_3
      value: 28.92
    - type: recall_at_5
      value: 34.003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 26.602999999999998
    - type: map_at_10
      value: 36.818
    - type: map_at_100
      value: 37.894
    - type: map_at_1000
      value: 37.991
    - type: map_at_20
      value: 37.389
    - type: map_at_3
      value: 33.615
    - type: map_at_5
      value: 35.432
    - type: mrr_at_1
      value: 31.53
    - type: mrr_at_10
      value: 41.144
    - type: mrr_at_100
      value: 41.937999999999995
    - type: mrr_at_1000
      value: 41.993
    - type: mrr_at_20
      value: 41.585
    - type: mrr_at_3
      value: 38.385999999999996
    - type: mrr_at_5
      value: 39.995000000000005
    - type: ndcg_at_1
      value: 31.53
    - type: ndcg_at_10
      value: 42.792
    - type: ndcg_at_100
      value: 47.749
    - type: ndcg_at_1000
      value: 49.946
    - type: ndcg_at_20
      value: 44.59
    - type: ndcg_at_3
      value: 37.025000000000006
    - type: ndcg_at_5
      value: 39.811
    - type: precision_at_1
      value: 31.53
    - type: precision_at_10
      value: 7.2669999999999995
    - type: precision_at_100
      value: 1.109
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_20
      value: 4.184
    - type: precision_at_3
      value: 16.791
    - type: precision_at_5
      value: 12.09
    - type: recall_at_1
      value: 26.602999999999998
    - type: recall_at_10
      value: 56.730999999999995
    - type: recall_at_100
      value: 78.119
    - type: recall_at_1000
      value: 93.458
    - type: recall_at_20
      value: 63.00599999999999
    - type: recall_at_3
      value: 41.306
    - type: recall_at_5
      value: 48.004999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 23.988
    - type: map_at_10
      value: 33.650999999999996
    - type: map_at_100
      value: 35.263
    - type: map_at_1000
      value: 35.481
    - type: map_at_20
      value: 34.463
    - type: map_at_3
      value: 30.330000000000002
    - type: map_at_5
      value: 32.056000000000004
    - type: mrr_at_1
      value: 29.644
    - type: mrr_at_10
      value: 38.987
    - type: mrr_at_100
      value: 39.973
    - type: mrr_at_1000
      value: 40.013
    - type: mrr_at_20
      value: 39.553
    - type: mrr_at_3
      value: 36.001
    - type: mrr_at_5
      value: 37.869
    - type: ndcg_at_1
      value: 29.644
    - type: ndcg_at_10
      value: 40.156
    - type: ndcg_at_100
      value: 46.244
    - type: ndcg_at_1000
      value: 48.483
    - type: ndcg_at_20
      value: 42.311
    - type: ndcg_at_3
      value: 34.492
    - type: ndcg_at_5
      value: 37.118
    - type: precision_at_1
      value: 29.644
    - type: precision_at_10
      value: 7.925
    - type: precision_at_100
      value: 1.5890000000000002
    - type: precision_at_1000
      value: 0.245
    - type: precision_at_20
      value: 4.97
    - type: precision_at_3
      value: 16.469
    - type: precision_at_5
      value: 12.174
    - type: recall_at_1
      value: 23.988
    - type: recall_at_10
      value: 52.844
    - type: recall_at_100
      value: 80.143
    - type: recall_at_1000
      value: 93.884
    - type: recall_at_20
      value: 61.050000000000004
    - type: recall_at_3
      value: 36.720000000000006
    - type: recall_at_5
      value: 43.614999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 21.947
    - type: map_at_10
      value: 29.902
    - type: map_at_100
      value: 30.916
    - type: map_at_1000
      value: 31.016
    - type: map_at_20
      value: 30.497999999999998
    - type: map_at_3
      value: 27.044
    - type: map_at_5
      value: 28.786
    - type: mrr_at_1
      value: 23.845
    - type: mrr_at_10
      value: 32.073
    - type: mrr_at_100
      value: 32.940999999999995
    - type: mrr_at_1000
      value: 33.015
    - type: mrr_at_20
      value: 32.603
    - type: mrr_at_3
      value: 29.205
    - type: mrr_at_5
      value: 31.044
    - type: ndcg_at_1
      value: 23.845
    - type: ndcg_at_10
      value: 34.79
    - type: ndcg_at_100
      value: 39.573
    - type: ndcg_at_1000
      value: 42.163000000000004
    - type: ndcg_at_20
      value: 36.778
    - type: ndcg_at_3
      value: 29.326
    - type: ndcg_at_5
      value: 32.289
    - type: precision_at_1
      value: 23.845
    - type: precision_at_10
      value: 5.527
    - type: precision_at_100
      value: 0.847
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_20
      value: 3.2439999999999998
    - type: precision_at_3
      value: 12.384
    - type: precision_at_5
      value: 9.205
    - type: recall_at_1
      value: 21.947
    - type: recall_at_10
      value: 47.713
    - type: recall_at_100
      value: 69.299
    - type: recall_at_1000
      value: 88.593
    - type: recall_at_20
      value: 55.032000000000004
    - type: recall_at_3
      value: 33.518
    - type: recall_at_5
      value: 40.427
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 13.655999999999999
    - type: map_at_10
      value: 23.954
    - type: map_at_100
      value: 26.07
    - type: map_at_1000
      value: 26.266000000000002
    - type: map_at_20
      value: 25.113000000000003
    - type: map_at_3
      value: 19.85
    - type: map_at_5
      value: 21.792
    - type: mrr_at_1
      value: 31.075000000000003
    - type: mrr_at_10
      value: 43.480000000000004
    - type: mrr_at_100
      value: 44.39
    - type: mrr_at_1000
      value: 44.42
    - type: mrr_at_20
      value: 44.06
    - type: mrr_at_3
      value: 40.38
    - type: mrr_at_5
      value: 42.138999999999996
    - type: ndcg_at_1
      value: 31.075000000000003
    - type: ndcg_at_10
      value: 33.129999999999995
    - type: ndcg_at_100
      value: 40.794000000000004
    - type: ndcg_at_1000
      value: 44.062
    - type: ndcg_at_20
      value: 36.223
    - type: ndcg_at_3
      value: 27.224999999999998
    - type: ndcg_at_5
      value: 28.969
    - type: precision_at_1
      value: 31.075000000000003
    - type: precision_at_10
      value: 10.476
    - type: precision_at_100
      value: 1.864
    - type: precision_at_1000
      value: 0.247
    - type: precision_at_20
      value: 6.593
    - type: precision_at_3
      value: 20.456
    - type: precision_at_5
      value: 15.440000000000001
    - type: recall_at_1
      value: 13.655999999999999
    - type: recall_at_10
      value: 39.678000000000004
    - type: recall_at_100
      value: 65.523
    - type: recall_at_1000
      value: 83.59100000000001
    - type: recall_at_20
      value: 48.27
    - type: recall_at_3
      value: 24.863
    - type: recall_at_5
      value: 30.453999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 9.139
    - type: map_at_10
      value: 20.366999999999997
    - type: map_at_100
      value: 29.755
    - type: map_at_1000
      value: 31.563999999999997
    - type: map_at_20
      value: 24.021
    - type: map_at_3
      value: 14.395
    - type: map_at_5
      value: 16.853
    - type: mrr_at_1
      value: 69.0
    - type: mrr_at_10
      value: 76.778
    - type: mrr_at_100
      value: 77.116
    - type: mrr_at_1000
      value: 77.12299999999999
    - type: mrr_at_20
      value: 77.046
    - type: mrr_at_3
      value: 75.208
    - type: mrr_at_5
      value: 76.146
    - type: ndcg_at_1
      value: 57.125
    - type: ndcg_at_10
      value: 42.84
    - type: ndcg_at_100
      value: 48.686
    - type: ndcg_at_1000
      value: 56.294
    - type: ndcg_at_20
      value: 42.717
    - type: ndcg_at_3
      value: 46.842
    - type: ndcg_at_5
      value: 44.248
    - type: precision_at_1
      value: 69.0
    - type: precision_at_10
      value: 34.625
    - type: precision_at_100
      value: 11.468
    - type: precision_at_1000
      value: 2.17
    - type: precision_at_20
      value: 26.562
    - type: precision_at_3
      value: 50.917
    - type: precision_at_5
      value: 43.35
    - type: recall_at_1
      value: 9.139
    - type: recall_at_10
      value: 26.247999999999998
    - type: recall_at_100
      value: 56.647000000000006
    - type: recall_at_1000
      value: 80.784
    - type: recall_at_20
      value: 35.010999999999996
    - type: recall_at_3
      value: 15.57
    - type: recall_at_5
      value: 19.198
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 55.93
    - type: f1
      value: 49.35314406745291
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 73.198
    - type: map_at_10
      value: 81.736
    - type: map_at_100
      value: 82.02000000000001
    - type: map_at_1000
      value: 82.03399999999999
    - type: map_at_20
      value: 81.937
    - type: map_at_3
      value: 80.692
    - type: map_at_5
      value: 81.369
    - type: mrr_at_1
      value: 78.803
    - type: mrr_at_10
      value: 86.144
    - type: mrr_at_100
      value: 86.263
    - type: mrr_at_1000
      value: 86.26599999999999
    - type: mrr_at_20
      value: 86.235
    - type: mrr_at_3
      value: 85.464
    - type: mrr_at_5
      value: 85.95
    - type: ndcg_at_1
      value: 78.803
    - type: ndcg_at_10
      value: 85.442
    - type: ndcg_at_100
      value: 86.422
    - type: ndcg_at_1000
      value: 86.68900000000001
    - type: ndcg_at_20
      value: 85.996
    - type: ndcg_at_3
      value: 83.839
    - type: ndcg_at_5
      value: 84.768
    - type: precision_at_1
      value: 78.803
    - type: precision_at_10
      value: 10.261000000000001
    - type: precision_at_100
      value: 1.0959999999999999
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 5.286
    - type: precision_at_3
      value: 32.083
    - type: precision_at_5
      value: 19.898
    - type: recall_at_1
      value: 73.198
    - type: recall_at_10
      value: 92.42099999999999
    - type: recall_at_100
      value: 96.28
    - type: recall_at_1000
      value: 97.995
    - type: recall_at_20
      value: 94.36
    - type: recall_at_3
      value: 88.042
    - type: recall_at_5
      value: 90.429
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 21.583
    - type: map_at_10
      value: 36.503
    - type: map_at_100
      value: 38.529
    - type: map_at_1000
      value: 38.701
    - type: map_at_20
      value: 37.69
    - type: map_at_3
      value: 31.807000000000002
    - type: map_at_5
      value: 34.424
    - type: mrr_at_1
      value: 43.827
    - type: mrr_at_10
      value: 53.528
    - type: mrr_at_100
      value: 54.291
    - type: mrr_at_1000
      value: 54.32599999999999
    - type: mrr_at_20
      value: 54.064
    - type: mrr_at_3
      value: 51.25999999999999
    - type: mrr_at_5
      value: 52.641000000000005
    - type: ndcg_at_1
      value: 43.827
    - type: ndcg_at_10
      value: 44.931
    - type: ndcg_at_100
      value: 51.778999999999996
    - type: ndcg_at_1000
      value: 54.532000000000004
    - type: ndcg_at_20
      value: 47.899
    - type: ndcg_at_3
      value: 41.062
    - type: ndcg_at_5
      value: 42.33
    - type: precision_at_1
      value: 43.827
    - type: precision_at_10
      value: 12.608
    - type: precision_at_100
      value: 1.974
    - type: precision_at_1000
      value: 0.247
    - type: precision_at_20
      value: 7.585
    - type: precision_at_3
      value: 27.778000000000002
    - type: precision_at_5
      value: 20.308999999999997
    - type: recall_at_1
      value: 21.583
    - type: recall_at_10
      value: 52.332
    - type: recall_at_100
      value: 77.256
    - type: recall_at_1000
      value: 93.613
    - type: recall_at_20
      value: 61.413
    - type: recall_at_3
      value: 37.477
    - type: recall_at_5
      value: 44.184
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 39.845000000000006
    - type: map_at_10
      value: 64.331
    - type: map_at_100
      value: 65.202
    - type: map_at_1000
      value: 65.261
    - type: map_at_20
      value: 64.833
    - type: map_at_3
      value: 60.663
    - type: map_at_5
      value: 62.94
    - type: mrr_at_1
      value: 79.689
    - type: mrr_at_10
      value: 85.299
    - type: mrr_at_100
      value: 85.461
    - type: mrr_at_1000
      value: 85.466
    - type: mrr_at_20
      value: 85.39099999999999
    - type: mrr_at_3
      value: 84.396
    - type: mrr_at_5
      value: 84.974
    - type: ndcg_at_1
      value: 79.689
    - type: ndcg_at_10
      value: 72.49
    - type: ndcg_at_100
      value: 75.485
    - type: ndcg_at_1000
      value: 76.563
    - type: ndcg_at_20
      value: 73.707
    - type: ndcg_at_3
      value: 67.381
    - type: ndcg_at_5
      value: 70.207
    - type: precision_at_1
      value: 79.689
    - type: precision_at_10
      value: 15.267
    - type: precision_at_100
      value: 1.7610000000000001
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_20
      value: 8.024000000000001
    - type: precision_at_3
      value: 43.363
    - type: precision_at_5
      value: 28.248
    - type: recall_at_1
      value: 39.845000000000006
    - type: recall_at_10
      value: 76.334
    - type: recall_at_100
      value: 88.042
    - type: recall_at_1000
      value: 95.09100000000001
    - type: recall_at_20
      value: 80.243
    - type: recall_at_3
      value: 65.044
    - type: recall_at_5
      value: 70.621
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 93.57079999999999
    - type: ap
      value: 90.50045924786099
    - type: f1
      value: 93.56673497845476
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 22.212
    - type: map_at_10
      value: 34.528
    - type: map_at_100
      value: 35.69
    - type: map_at_1000
      value: 35.74
    - type: map_at_20
      value: 35.251
    - type: map_at_3
      value: 30.628
    - type: map_at_5
      value: 32.903999999999996
    - type: mrr_at_1
      value: 22.794
    - type: mrr_at_10
      value: 35.160000000000004
    - type: mrr_at_100
      value: 36.251
    - type: mrr_at_1000
      value: 36.295
    - type: mrr_at_20
      value: 35.845
    - type: mrr_at_3
      value: 31.328
    - type: mrr_at_5
      value: 33.574
    - type: ndcg_at_1
      value: 22.779
    - type: ndcg_at_10
      value: 41.461
    - type: ndcg_at_100
      value: 47.049
    - type: ndcg_at_1000
      value: 48.254000000000005
    - type: ndcg_at_20
      value: 44.031
    - type: ndcg_at_3
      value: 33.561
    - type: ndcg_at_5
      value: 37.62
    - type: precision_at_1
      value: 22.779
    - type: precision_at_10
      value: 6.552
    - type: precision_at_100
      value: 0.936
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 3.8120000000000003
    - type: precision_at_3
      value: 14.274000000000001
    - type: precision_at_5
      value: 10.622
    - type: recall_at_1
      value: 22.212
    - type: recall_at_10
      value: 62.732
    - type: recall_at_100
      value: 88.567
    - type: recall_at_1000
      value: 97.727
    - type: recall_at_20
      value: 72.733
    - type: recall_at_3
      value: 41.367
    - type: recall_at_5
      value: 51.105999999999995
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 94.24988600091199
    - type: f1
      value: 94.06064583085202
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (de)
      type: mteb/mtop_domain
      config: de
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 74.86052409129333
    - type: f1
      value: 72.24661442078647
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (es)
      type: mteb/mtop_domain
      config: es
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 77.09139426284189
    - type: f1
      value: 76.3725044443502
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 79.79956154087064
    - type: f1
      value: 78.41859658401724
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (hi)
      type: mteb/mtop_domain
      config: hi
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 32.785944783076374
    - type: f1
      value: 31.182237278594922
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (th)
      type: mteb/mtop_domain
      config: th
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 16.654611211573236
    - type: f1
      value: 12.088413093236642
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 67.51481988144094
    - type: f1
      value: 49.561420234732125
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (de)
      type: mteb/mtop_intent
      config: de
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 42.36122851507467
    - type: f1
      value: 25.445030887504398
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (es)
      type: mteb/mtop_intent
      config: es
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 44.73315543695797
    - type: f1
      value: 28.42075153540265
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 38.96022549326651
    - type: f1
      value: 25.926979537146106
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (hi)
      type: mteb/mtop_intent
      config: hi
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 13.578343492291141
    - type: f1
      value: 8.929295550931657
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (th)
      type: mteb/mtop_intent
      config: th
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 5.396021699819168
    - type: f1
      value: 1.8587148785378742
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (af)
      type: mteb/amazon_massive_intent
      config: af
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 37.22259583053128
    - type: f1
      value: 34.63013680947778
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (am)
      type: mteb/amazon_massive_intent
      config: am
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 3.194351042367182
    - type: f1
      value: 1.2612010214639442
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ar)
      type: mteb/amazon_massive_intent
      config: ar
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 14.26361802286483
    - type: f1
      value: 13.70260406613821
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (az)
      type: mteb/amazon_massive_intent
      config: az
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 37.21923335574983
    - type: f1
      value: 36.33553913878251
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (bn)
      type: mteb/amazon_massive_intent
      config: bn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 10.756556825823807
    - type: f1
      value: 9.676431920229374
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (cy)
      type: mteb/amazon_massive_intent
      config: cy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 32.49831876260928
    - type: f1
      value: 30.818895782691868
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (da)
      type: mteb/amazon_massive_intent
      config: da
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 40.995292535305985
    - type: f1
      value: 37.68768183180129
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (de)
      type: mteb/amazon_massive_intent
      config: de
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 42.780766644250164
    - type: f1
      value: 37.82194830667135
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (el)
      type: mteb/amazon_massive_intent
      config: el
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 33.490248823133825
    - type: f1
      value: 29.71809045584527
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 73.8836583725622
    - type: f1
      value: 72.16381047416814
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (es)
      type: mteb/amazon_massive_intent
      config: es
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 44.45191661062542
    - type: f1
      value: 43.46583297093683
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fa)
      type: mteb/amazon_massive_intent
      config: fa
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 26.738399462004036
    - type: f1
      value: 24.11896530001951
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fi)
      type: mteb/amazon_massive_intent
      config: fi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 38.09683927370545
    - type: f1
      value: 35.34443269387154
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 46.89307330195024
    - type: f1
      value: 43.47164092514292
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (he)
      type: mteb/amazon_massive_intent
      config: he
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 25.198386012104912
    - type: f1
      value: 22.446286736401916
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hi)
      type: mteb/amazon_massive_intent
      config: hi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 13.940820443846672
    - type: f1
      value: 13.257747189396213
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hu)
      type: mteb/amazon_massive_intent
      config: hu
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 34.710827168796236
    - type: f1
      value: 32.036974696095996
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hy)
      type: mteb/amazon_massive_intent
      config: hy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 6.711499663752522
    - type: f1
      value: 5.439441019096591
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (id)
      type: mteb/amazon_massive_intent
      config: id
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 38.56758574310693
    - type: f1
      value: 36.83183505458304
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (is)
      type: mteb/amazon_massive_intent
      config: is
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 32.22595830531271
    - type: f1
      value: 30.10972675771159
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (it)
      type: mteb/amazon_massive_intent
      config: it
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 45.79690652320107
    - type: f1
      value: 44.37143784350453
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ja)
      type: mteb/amazon_massive_intent
      config: ja
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 29.189643577673163
    - type: f1
      value: 25.43718135312703
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (jv)
      type: mteb/amazon_massive_intent
      config: jv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 34.21990585070612
    - type: f1
      value: 32.333592263041396
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ka)
      type: mteb/amazon_massive_intent
      config: ka
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 8.890383322125084
    - type: f1
      value: 7.294310113130201
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (km)
      type: mteb/amazon_massive_intent
      config: km
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 4.616677874915938
    - type: f1
      value: 1.5028537477535886
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (kn)
      type: mteb/amazon_massive_intent
      config: kn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 3.170813718897109
    - type: f1
      value: 1.5771411815826382
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ko)
      type: mteb/amazon_massive_intent
      config: ko
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 15.026899798251513
    - type: f1
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      type: mteb/amazon_massive_scenario
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      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (pt)
      type: mteb/amazon_massive_scenario
      config: pt
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 55.59852051109617
    - type: f1
      value: 54.19610878409633
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ro)
      type: mteb/amazon_massive_scenario
      config: ro
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 50.54135843981169
    - type: f1
      value: 47.79393938467311
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ru)
      type: mteb/amazon_massive_scenario
      config: ru
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 37.73032952252858
    - type: f1
      value: 35.96450149708041
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sl)
      type: mteb/amazon_massive_scenario
      config: sl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 41.67114996637525
    - type: f1
      value: 40.28283538885605
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sq)
      type: mteb/amazon_massive_scenario
      config: sq
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 47.38063214525891
    - type: f1
      value: 44.93264016007152
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sv)
      type: mteb/amazon_massive_scenario
      config: sv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 49.28379287155347
    - type: f1
      value: 46.25486396570196
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sw)
      type: mteb/amazon_massive_scenario
      config: sw
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 44.18291862811029
    - type: f1
      value: 41.17519157172804
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ta)
      type: mteb/amazon_massive_scenario
      config: ta
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 12.599193006052452
    - type: f1
      value: 11.129236666238377
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (te)
      type: mteb/amazon_massive_scenario
      config: te
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 7.017484868863484
    - type: f1
      value: 3.9665415549749077
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (th)
      type: mteb/amazon_massive_scenario
      config: th
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 19.788164088769335
    - type: f1
      value: 15.783384761347582
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tl)
      type: mteb/amazon_massive_scenario
      config: tl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 50.35978480161398
    - type: f1
      value: 47.30586047800275
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tr)
      type: mteb/amazon_massive_scenario
      config: tr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 45.484196368527236
    - type: f1
      value: 44.65101184252231
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ur)
      type: mteb/amazon_massive_scenario
      config: ur
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 23.681909885675857
    - type: f1
      value: 22.247817138937524
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (vi)
      type: mteb/amazon_massive_scenario
      config: vi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 41.63080026899798
    - type: f1
      value: 39.546896741744
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 30.141223940820446
    - type: f1
      value: 28.177838960078123
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-TW)
      type: mteb/amazon_massive_scenario
      config: zh-TW
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 27.515131136516473
    - type: f1
      value: 26.514325837594654
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 33.70592767911301
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 31.80943770643908
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.66434973425713
    - type: mrr
      value: 33.92240574935323
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 6.561999999999999
    - type: map_at_10
      value: 14.854000000000001
    - type: map_at_100
      value: 19.187
    - type: map_at_1000
      value: 20.812
    - type: map_at_20
      value: 16.744
    - type: map_at_3
      value: 10.804
    - type: map_at_5
      value: 12.555
    - type: mrr_at_1
      value: 48.916
    - type: mrr_at_10
      value: 57.644
    - type: mrr_at_100
      value: 58.17
    - type: mrr_at_1000
      value: 58.206
    - type: mrr_at_20
      value: 57.969
    - type: mrr_at_3
      value: 55.36600000000001
    - type: mrr_at_5
      value: 56.729
    - type: ndcg_at_1
      value: 46.594
    - type: ndcg_at_10
      value: 37.897999999999996
    - type: ndcg_at_100
      value: 35.711
    - type: ndcg_at_1000
      value: 44.65
    - type: ndcg_at_20
      value: 35.989
    - type: ndcg_at_3
      value: 42.869
    - type: ndcg_at_5
      value: 40.373
    - type: precision_at_1
      value: 48.297000000000004
    - type: precision_at_10
      value: 28.297
    - type: precision_at_100
      value: 9.099
    - type: precision_at_1000
      value: 2.229
    - type: precision_at_20
      value: 21.455
    - type: precision_at_3
      value: 40.248
    - type: precision_at_5
      value: 34.675
    - type: recall_at_1
      value: 6.561999999999999
    - type: recall_at_10
      value: 19.205
    - type: recall_at_100
      value: 36.742999999999995
    - type: recall_at_1000
      value: 69.119
    - type: recall_at_20
      value: 23.787
    - type: recall_at_3
      value: 11.918
    - type: recall_at_5
      value: 14.860000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 30.306
    - type: map_at_10
      value: 46.916999999999994
    - type: map_at_100
      value: 47.899
    - type: map_at_1000
      value: 47.925000000000004
    - type: map_at_20
      value: 47.583
    - type: map_at_3
      value: 42.235
    - type: map_at_5
      value: 45.118
    - type: mrr_at_1
      value: 34.327999999999996
    - type: mrr_at_10
      value: 49.248999999999995
    - type: mrr_at_100
      value: 49.96
    - type: mrr_at_1000
      value: 49.977
    - type: mrr_at_20
      value: 49.738
    - type: mrr_at_3
      value: 45.403999999999996
    - type: mrr_at_5
      value: 47.786
    - type: ndcg_at_1
      value: 34.327999999999996
    - type: ndcg_at_10
      value: 55.123999999999995
    - type: ndcg_at_100
      value: 59.136
    - type: ndcg_at_1000
      value: 59.71300000000001
    - type: ndcg_at_20
      value: 57.232000000000006
    - type: ndcg_at_3
      value: 46.48
    - type: ndcg_at_5
      value: 51.237
    - type: precision_at_1
      value: 34.327999999999996
    - type: precision_at_10
      value: 9.261
    - type: precision_at_100
      value: 1.1520000000000001
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_20
      value: 5.148
    - type: precision_at_3
      value: 21.523999999999997
    - type: precision_at_5
      value: 15.659999999999998
    - type: recall_at_1
      value: 30.306
    - type: recall_at_10
      value: 77.65100000000001
    - type: recall_at_100
      value: 94.841
    - type: recall_at_1000
      value: 99.119
    - type: recall_at_20
      value: 85.37599999999999
    - type: recall_at_3
      value: 55.562
    - type: recall_at_5
      value: 66.5
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 71.516
    - type: map_at_10
      value: 85.48400000000001
    - type: map_at_100
      value: 86.11
    - type: map_at_1000
      value: 86.124
    - type: map_at_20
      value: 85.895
    - type: map_at_3
      value: 82.606
    - type: map_at_5
      value: 84.395
    - type: mrr_at_1
      value: 82.38
    - type: mrr_at_10
      value: 88.31099999999999
    - type: mrr_at_100
      value: 88.407
    - type: mrr_at_1000
      value: 88.407
    - type: mrr_at_20
      value: 88.385
    - type: mrr_at_3
      value: 87.42699999999999
    - type: mrr_at_5
      value: 88.034
    - type: ndcg_at_1
      value: 82.39999999999999
    - type: ndcg_at_10
      value: 89.07300000000001
    - type: ndcg_at_100
      value: 90.23400000000001
    - type: ndcg_at_1000
      value: 90.304
    - type: ndcg_at_20
      value: 89.714
    - type: ndcg_at_3
      value: 86.42699999999999
    - type: ndcg_at_5
      value: 87.856
    - type: precision_at_1
      value: 82.39999999999999
    - type: precision_at_10
      value: 13.499
    - type: precision_at_100
      value: 1.536
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_20
      value: 7.155
    - type: precision_at_3
      value: 37.846999999999994
    - type: precision_at_5
      value: 24.778
    - type: recall_at_1
      value: 71.516
    - type: recall_at_10
      value: 95.831
    - type: recall_at_100
      value: 99.714
    - type: recall_at_1000
      value: 99.979
    - type: recall_at_20
      value: 97.87599999999999
    - type: recall_at_3
      value: 88.08
    - type: recall_at_5
      value: 92.285
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 61.3760407207699
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 65.28621066626943
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 5.163
    - type: map_at_10
      value: 14.377
    - type: map_at_100
      value: 17.177
    - type: map_at_1000
      value: 17.588
    - type: map_at_20
      value: 15.827
    - type: map_at_3
      value: 9.879
    - type: map_at_5
      value: 12.133
    - type: mrr_at_1
      value: 25.5
    - type: mrr_at_10
      value: 38.435
    - type: mrr_at_100
      value: 39.573
    - type: mrr_at_1000
      value: 39.606
    - type: mrr_at_20
      value: 39.134
    - type: mrr_at_3
      value: 34.666999999999994
    - type: mrr_at_5
      value: 37.117
    - type: ndcg_at_1
      value: 25.5
    - type: ndcg_at_10
      value: 23.688000000000002
    - type: ndcg_at_100
      value: 33.849000000000004
    - type: ndcg_at_1000
      value: 39.879
    - type: ndcg_at_20
      value: 27.36
    - type: ndcg_at_3
      value: 22.009999999999998
    - type: ndcg_at_5
      value: 19.691
    - type: precision_at_1
      value: 25.5
    - type: precision_at_10
      value: 12.540000000000001
    - type: precision_at_100
      value: 2.721
    - type: precision_at_1000
      value: 0.415
    - type: precision_at_20
      value: 8.385
    - type: precision_at_3
      value: 21.099999999999998
    - type: precision_at_5
      value: 17.84
    - type: recall_at_1
      value: 5.163
    - type: recall_at_10
      value: 25.405
    - type: recall_at_100
      value: 55.213
    - type: recall_at_1000
      value: 84.243
    - type: recall_at_20
      value: 34.003
    - type: recall_at_3
      value: 12.837000000000002
    - type: recall_at_5
      value: 18.096999999999998
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 87.64406884822948
    - type: cos_sim_spearman
      value: 83.00239648251724
    - type: euclidean_pearson
      value: 85.03347205351844
    - type: euclidean_spearman
      value: 83.00240733538445
    - type: manhattan_pearson
      value: 85.0312758694447
    - type: manhattan_spearman
      value: 82.99430696077589
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 87.68832340658764
    - type: cos_sim_spearman
      value: 79.21679373212476
    - type: euclidean_pearson
      value: 85.17094885886415
    - type: euclidean_spearman
      value: 79.21421345946399
    - type: manhattan_pearson
      value: 85.17409319145995
    - type: manhattan_spearman
      value: 79.20992207976401
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 88.43733084958856
    - type: cos_sim_spearman
      value: 89.43082089321751
    - type: euclidean_pearson
      value: 88.63286785416938
    - type: euclidean_spearman
      value: 89.43082081372343
    - type: manhattan_pearson
      value: 88.62969346368385
    - type: manhattan_spearman
      value: 89.43131586189746
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 86.62185532014894
    - type: cos_sim_spearman
      value: 84.7923120886599
    - type: euclidean_pearson
      value: 85.99786490539253
    - type: euclidean_spearman
      value: 84.79231064318844
    - type: manhattan_pearson
      value: 85.97647892920392
    - type: manhattan_spearman
      value: 84.76865232132103
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 88.39303997282114
    - type: cos_sim_spearman
      value: 89.54273264876765
    - type: euclidean_pearson
      value: 88.8848627924181
    - type: euclidean_spearman
      value: 89.54275013645078
    - type: manhattan_pearson
      value: 88.86926987108802
    - type: manhattan_spearman
      value: 89.53259197721715
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 85.21814352466886
    - type: cos_sim_spearman
      value: 86.68505223422434
    - type: euclidean_pearson
      value: 86.07422446469991
    - type: euclidean_spearman
      value: 86.68505161067375
    - type: manhattan_pearson
      value: 86.05114200797293
    - type: manhattan_spearman
      value: 86.6587670422703
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 39.17871768366095
    - type: cos_sim_spearman
      value: 39.78510424960567
    - type: euclidean_pearson
      value: 41.65680175653682
    - type: euclidean_spearman
      value: 39.78538944779548
    - type: manhattan_pearson
      value: 41.567603690394755
    - type: manhattan_spearman
      value: 39.71393388259443
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 49.26766904195114
    - type: cos_sim_spearman
      value: 46.79722787057151
    - type: euclidean_pearson
      value: 51.2329334717446
    - type: euclidean_spearman
      value: 46.7920623095072
    - type: manhattan_pearson
      value: 51.26488560860826
    - type: manhattan_spearman
      value: 47.00400318665492
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 1.6821294132202447
    - type: cos_sim_spearman
      value: -0.7813676799492025
    - type: euclidean_pearson
      value: 1.9197388753860283
    - type: euclidean_spearman
      value: -0.7813676799492025
    - type: manhattan_pearson
      value: 2.209862430499871
    - type: manhattan_spearman
      value: -0.863014010062456
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 48.76382428941107
    - type: cos_sim_spearman
      value: 47.50280322999196
    - type: euclidean_pearson
      value: 48.73919143974209
    - type: euclidean_spearman
      value: 47.50280322999196
    - type: manhattan_pearson
      value: 48.76291223862666
    - type: manhattan_spearman
      value: 47.51318193687094
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 89.6579390263212
    - type: cos_sim_spearman
      value: 89.64423556388047
    - type: euclidean_pearson
      value: 90.1160733522703
    - type: euclidean_spearman
      value: 89.64423556388047
    - type: manhattan_pearson
      value: 90.1528407376387
    - type: manhattan_spearman
      value: 89.61290724496793
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 6.717092266815236
    - type: cos_sim_spearman
      value: 4.180543503488665
    - type: euclidean_pearson
      value: 7.120267092048099
    - type: euclidean_spearman
      value: 4.180543503488665
    - type: manhattan_pearson
      value: 6.396237465828514
    - type: manhattan_spearman
      value: 3.61244941411957
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 44.36476614938953
    - type: cos_sim_spearman
      value: 44.265723809500685
    - type: euclidean_pearson
      value: 44.61551298711104
    - type: euclidean_spearman
      value: 44.265723809500685
    - type: manhattan_pearson
      value: 44.54302374682193
    - type: manhattan_spearman
      value: 44.08642490624185
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 79.64871991975828
    - type: cos_sim_spearman
      value: 79.21979030014373
    - type: euclidean_pearson
      value: 81.8672798988218
    - type: euclidean_spearman
      value: 79.21950130108661
    - type: manhattan_pearson
      value: 82.02131606326583
    - type: manhattan_spearman
      value: 79.44848373553044
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 48.73898658957231
    - type: cos_sim_spearman
      value: 47.15192605817168
    - type: euclidean_pearson
      value: 49.11990573381456
    - type: euclidean_spearman
      value: 47.15192605817168
    - type: manhattan_pearson
      value: 48.5694400358235
    - type: manhattan_spearman
      value: 46.651326429708135
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 44.42168074232218
    - type: cos_sim_spearman
      value: 42.64799010889372
    - type: euclidean_pearson
      value: 44.41376048324183
    - type: euclidean_spearman
      value: 42.64799010889372
    - type: manhattan_pearson
      value: 44.724522621427546
    - type: manhattan_spearman
      value: 42.60912761758016
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 40.55050173163197
    - type: cos_sim_spearman
      value: 36.59720399843921
    - type: euclidean_pearson
      value: 41.49402389245919
    - type: euclidean_spearman
      value: 36.59720399843921
    - type: manhattan_pearson
      value: 41.877514420153666
    - type: manhattan_spearman
      value: 36.782790653297695
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 69.44405106094861
    - type: cos_sim_spearman
      value: 70.25621893108706
    - type: euclidean_pearson
      value: 71.15726637696066
    - type: euclidean_spearman
      value: 70.25621893108706
    - type: manhattan_pearson
      value: 71.28565265298322
    - type: manhattan_spearman
      value: 70.30317892414027
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 34.56638014500804
    - type: cos_sim_spearman
      value: 39.48672765878819
    - type: euclidean_pearson
      value: 31.61811391543846
    - type: euclidean_spearman
      value: 39.48672765878819
    - type: manhattan_pearson
      value: 31.839117286689977
    - type: manhattan_spearman
      value: 39.71519891403971
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 53.72389957326714
    - type: cos_sim_spearman
      value: 59.47018781803598
    - type: euclidean_pearson
      value: 57.02101112722141
    - type: euclidean_spearman
      value: 59.47018781803598
    - type: manhattan_pearson
      value: 57.16531255049132
    - type: manhattan_spearman
      value: 59.57320508684436
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 24.14602533311477
    - type: cos_sim_spearman
      value: 35.38039329704056
    - type: euclidean_pearson
      value: 13.540543553763765
    - type: euclidean_spearman
      value: 35.38039329704056
    - type: manhattan_pearson
      value: 13.566377379303256
    - type: manhattan_spearman
      value: 35.88351047224126
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (tr)
      type: mteb/sts22-crosslingual-sts
      config: tr
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 39.07697432450346
    - type: cos_sim_spearman
      value: 45.65479772235109
    - type: euclidean_pearson
      value: 41.68913259791294
    - type: euclidean_spearman
      value: 45.65479772235109
    - type: manhattan_pearson
      value: 41.58872552392231
    - type: manhattan_spearman
      value: 45.462070534023404
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ar)
      type: mteb/sts22-crosslingual-sts
      config: ar
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 23.917322166825183
    - type: cos_sim_spearman
      value: 25.06042767518008
    - type: euclidean_pearson
      value: 24.29850435278771
    - type: euclidean_spearman
      value: 25.06042767518008
    - type: manhattan_pearson
      value: 24.461400062927154
    - type: manhattan_spearman
      value: 25.285239684773046
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 20.39987623162105
    - type: cos_sim_spearman
      value: 30.62427846964406
    - type: euclidean_pearson
      value: 20.817950942480323
    - type: euclidean_spearman
      value: 30.618700916425222
    - type: manhattan_pearson
      value: 20.756787430880788
    - type: manhattan_spearman
      value: 30.813116243628436
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 43.838363041373974
    - type: cos_sim_spearman
      value: 54.17598089882719
    - type: euclidean_pearson
      value: 47.51044033919419
    - type: euclidean_spearman
      value: 54.17598089882719
    - type: manhattan_pearson
      value: 47.54911083403354
    - type: manhattan_spearman
      value: 54.2562151204606
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 77.69372699157654
    - type: cos_sim_spearman
      value: 79.88201388457435
    - type: euclidean_pearson
      value: 78.81259581302578
    - type: euclidean_spearman
      value: 79.88201388457435
    - type: manhattan_pearson
      value: 78.85098508555477
    - type: manhattan_spearman
      value: 80.20154858554835
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 51.83713469138834
    - type: cos_sim_spearman
      value: 54.2205845288082
    - type: euclidean_pearson
      value: 54.14828396506985
    - type: euclidean_spearman
      value: 54.2205845288082
    - type: manhattan_pearson
      value: 54.10701855179347
    - type: manhattan_spearman
      value: 54.30261135461622
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.59147752554915
    - type: cos_sim_spearman
      value: 66.65350021824162
    - type: euclidean_pearson
      value: 62.577915098325434
    - type: euclidean_spearman
      value: 66.65350021824162
    - type: manhattan_pearson
      value: 62.22817675366819
    - type: manhattan_spearman
      value: 66.35054389546214
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (it)
      type: mteb/sts22-crosslingual-sts
      config: it
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 65.23775897743552
    - type: cos_sim_spearman
      value: 68.1509652709288
    - type: euclidean_pearson
      value: 66.17577980319408
    - type: euclidean_spearman
      value: 68.1509652709288
    - type: manhattan_pearson
      value: 66.40051933918704
    - type: manhattan_spearman
      value: 68.37138808382802
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.943863830043725
    - type: cos_sim_spearman
      value: 62.699440972016774
    - type: euclidean_pearson
      value: 62.810366501196
    - type: euclidean_spearman
      value: 62.699440972016774
    - type: manhattan_pearson
      value: 63.13065659868621
    - type: manhattan_spearman
      value: 63.314141373703215
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 48.1108866326284
    - type: cos_sim_spearman
      value: 49.25274096772371
    - type: euclidean_pearson
      value: 47.87203797435136
    - type: euclidean_spearman
      value: 49.25274096772371
    - type: manhattan_pearson
      value: 47.39927722979605
    - type: manhattan_spearman
      value: 48.76629586560382
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-it)
      type: mteb/sts22-crosslingual-sts
      config: es-it
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 58.58401639298775
    - type: cos_sim_spearman
      value: 64.37272828346495
    - type: euclidean_pearson
      value: 61.03680632288844
    - type: euclidean_spearman
      value: 64.37272828346495
    - type: manhattan_pearson
      value: 61.381331848220675
    - type: manhattan_spearman
      value: 65.01053960017909
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 44.374682063416735
    - type: cos_sim_spearman
      value: 48.907776246550185
    - type: euclidean_pearson
      value: 45.473260322201284
    - type: euclidean_spearman
      value: 48.907776246550185
    - type: manhattan_pearson
      value: 46.051779591771854
    - type: manhattan_spearman
      value: 49.69297213757249
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 31.55497030143048
    - type: cos_sim_spearman
      value: 33.042073055100396
    - type: euclidean_pearson
      value: 33.548707962408955
    - type: euclidean_spearman
      value: 33.042073055100396
    - type: manhattan_pearson
      value: 31.704989941561873
    - type: manhattan_spearman
      value: 31.56395608711827
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 51.253093232573036
    - type: cos_sim_spearman
      value: 39.440531887330785
    - type: euclidean_pearson
      value: 51.42758694144294
    - type: euclidean_spearman
      value: 39.440531887330785
    - type: manhattan_pearson
      value: 49.623915715149394
    - type: manhattan_spearman
      value: 39.440531887330785
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 87.61260941646887
    - type: cos_sim_spearman
      value: 88.96384726759047
    - type: euclidean_pearson
      value: 88.72268994912045
    - type: euclidean_spearman
      value: 88.96384726759047
    - type: manhattan_pearson
      value: 88.72080954591475
    - type: manhattan_spearman
      value: 88.92379960545995
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.64768404690723
    - type: mrr
      value: 96.25675341361615
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 61.194
    - type: map_at_10
      value: 70.62899999999999
    - type: map_at_100
      value: 71.119
    - type: map_at_1000
      value: 71.14200000000001
    - type: map_at_20
      value: 71.033
    - type: map_at_3
      value: 67.51899999999999
    - type: map_at_5
      value: 69.215
    - type: mrr_at_1
      value: 63.666999999999994
    - type: mrr_at_10
      value: 71.456
    - type: mrr_at_100
      value: 71.844
    - type: mrr_at_1000
      value: 71.866
    - type: mrr_at_20
      value: 71.769
    - type: mrr_at_3
      value: 69.167
    - type: mrr_at_5
      value: 70.39999999999999
    - type: ndcg_at_1
      value: 63.666999999999994
    - type: ndcg_at_10
      value: 75.14
    - type: ndcg_at_100
      value: 77.071
    - type: ndcg_at_1000
      value: 77.55199999999999
    - type: ndcg_at_20
      value: 76.491
    - type: ndcg_at_3
      value: 69.836
    - type: ndcg_at_5
      value: 72.263
    - type: precision_at_1
      value: 63.666999999999994
    - type: precision_at_10
      value: 10.0
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 5.3
    - type: precision_at_3
      value: 27.0
    - type: precision_at_5
      value: 17.867
    - type: recall_at_1
      value: 61.194
    - type: recall_at_10
      value: 88.156
    - type: recall_at_100
      value: 96.5
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 93.389
    - type: recall_at_3
      value: 73.839
    - type: recall_at_5
      value: 79.828
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.87425742574257
    - type: cos_sim_ap
      value: 96.97141655369937
    - type: cos_sim_f1
      value: 93.6910084451068
    - type: cos_sim_precision
      value: 93.0898321816387
    - type: cos_sim_recall
      value: 94.3
    - type: dot_accuracy
      value: 99.87425742574257
    - type: dot_ap
      value: 96.97141655369938
    - type: dot_f1
      value: 93.6910084451068
    - type: dot_precision
      value: 93.0898321816387
    - type: dot_recall
      value: 94.3
    - type: euclidean_accuracy
      value: 99.87425742574257
    - type: euclidean_ap
      value: 96.97141655369938
    - type: euclidean_f1
      value: 93.6910084451068
    - type: euclidean_precision
      value: 93.0898321816387
    - type: euclidean_recall
      value: 94.3
    - type: manhattan_accuracy
      value: 99.87425742574257
    - type: manhattan_ap
      value: 96.98252972861131
    - type: manhattan_f1
      value: 93.68473396320238
    - type: manhattan_precision
      value: 93.17507418397626
    - type: manhattan_recall
      value: 94.19999999999999
    - type: max_accuracy
      value: 99.87425742574257
    - type: max_ap
      value: 96.98252972861131
    - type: max_f1
      value: 93.6910084451068
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 66.5976926394361
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 36.3221929214798
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 55.28322662897131
    - type: mrr
      value: 56.223620129870135
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.176396304511282
    - type: cos_sim_spearman
      value: 32.11989671564906
    - type: dot_pearson
      value: 31.17639740597169
    - type: dot_spearman
      value: 32.145586989831564
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.186
    - type: map_at_10
      value: 1.659
    - type: map_at_100
      value: 9.224
    - type: map_at_1000
      value: 22.506999999999998
    - type: map_at_20
      value: 2.937
    - type: map_at_3
      value: 0.5539999999999999
    - type: map_at_5
      value: 0.8920000000000001
    - type: mrr_at_1
      value: 72.0
    - type: mrr_at_10
      value: 82.633
    - type: mrr_at_100
      value: 82.633
    - type: mrr_at_1000
      value: 82.633
    - type: mrr_at_20
      value: 82.633
    - type: mrr_at_3
      value: 80.333
    - type: mrr_at_5
      value: 82.633
    - type: ndcg_at_1
      value: 69.0
    - type: ndcg_at_10
      value: 67.327
    - type: ndcg_at_100
      value: 51.626000000000005
    - type: ndcg_at_1000
      value: 47.396
    - type: ndcg_at_20
      value: 63.665000000000006
    - type: ndcg_at_3
      value: 68.95
    - type: ndcg_at_5
      value: 69.241
    - type: precision_at_1
      value: 72.0
    - type: precision_at_10
      value: 71.6
    - type: precision_at_100
      value: 53.22
    - type: precision_at_1000
      value: 20.721999999999998
    - type: precision_at_20
      value: 67.30000000000001
    - type: precision_at_3
      value: 72.667
    - type: precision_at_5
      value: 74.0
    - type: recall_at_1
      value: 0.186
    - type: recall_at_10
      value: 1.932
    - type: recall_at_100
      value: 12.883
    - type: recall_at_1000
      value: 44.511
    - type: recall_at_20
      value: 3.583
    - type: recall_at_3
      value: 0.601
    - type: recall_at_5
      value: 1.0
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.308
    - type: map_at_10
      value: 9.744
    - type: map_at_100
      value: 15.859000000000002
    - type: map_at_1000
      value: 17.396
    - type: map_at_20
      value: 12.49
    - type: map_at_3
      value: 4.848
    - type: map_at_5
      value: 6.912999999999999
    - type: mrr_at_1
      value: 32.653
    - type: mrr_at_10
      value: 47.207
    - type: mrr_at_100
      value: 48.116
    - type: mrr_at_1000
      value: 48.116
    - type: mrr_at_20
      value: 47.735
    - type: mrr_at_3
      value: 42.857
    - type: mrr_at_5
      value: 44.285999999999994
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 24.421
    - type: ndcg_at_100
      value: 35.961
    - type: ndcg_at_1000
      value: 47.541
    - type: ndcg_at_20
      value: 25.999
    - type: ndcg_at_3
      value: 25.333
    - type: ndcg_at_5
      value: 25.532
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 22.448999999999998
    - type: precision_at_100
      value: 7.571
    - type: precision_at_1000
      value: 1.5310000000000001
    - type: precision_at_20
      value: 17.959
    - type: precision_at_3
      value: 26.531
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 2.308
    - type: recall_at_10
      value: 16.075
    - type: recall_at_100
      value: 47.357
    - type: recall_at_1000
      value: 82.659
    - type: recall_at_20
      value: 24.554000000000002
    - type: recall_at_3
      value: 5.909
    - type: recall_at_5
      value: 9.718
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 67.2998046875
    - type: ap
      value: 12.796222498684031
    - type: f1
      value: 51.7465070845071
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.76004527447652
    - type: f1
      value: 61.88985723942393
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 52.69229715788263
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.42325803182929
    - type: cos_sim_ap
      value: 78.29203513753492
    - type: cos_sim_f1
      value: 71.33160557818093
    - type: cos_sim_precision
      value: 67.00672385810341
    - type: cos_sim_recall
      value: 76.2532981530343
    - type: dot_accuracy
      value: 87.42325803182929
    - type: dot_ap
      value: 78.29208368244002
    - type: dot_f1
      value: 71.33160557818093
    - type: dot_precision
      value: 67.00672385810341
    - type: dot_recall
      value: 76.2532981530343
    - type: euclidean_accuracy
      value: 87.42325803182929
    - type: euclidean_ap
      value: 78.29202838891078
    - type: euclidean_f1
      value: 71.33160557818093
    - type: euclidean_precision
      value: 67.00672385810341
    - type: euclidean_recall
      value: 76.2532981530343
    - type: manhattan_accuracy
      value: 87.42325803182929
    - type: manhattan_ap
      value: 78.23964459648822
    - type: manhattan_f1
      value: 71.1651728553137
    - type: manhattan_precision
      value: 69.12935323383084
    - type: manhattan_recall
      value: 73.3245382585752
    - type: max_accuracy
      value: 87.42325803182929
    - type: max_ap
      value: 78.29208368244002
    - type: max_f1
      value: 71.33160557818093
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.00725734466566
    - type: cos_sim_ap
      value: 86.1594112416402
    - type: cos_sim_f1
      value: 78.544568993303
    - type: cos_sim_precision
      value: 73.42484097756947
    - type: cos_sim_recall
      value: 84.43178318447798
    - type: dot_accuracy
      value: 89.00725734466566
    - type: dot_ap
      value: 86.15940795129771
    - type: dot_f1
      value: 78.544568993303
    - type: dot_precision
      value: 73.42484097756947
    - type: dot_recall
      value: 84.43178318447798
    - type: euclidean_accuracy
      value: 89.00725734466566
    - type: euclidean_ap
      value: 86.15939689541806
    - type: euclidean_f1
      value: 78.544568993303
    - type: euclidean_precision
      value: 73.42484097756947
    - type: euclidean_recall
      value: 84.43178318447798
    - type: manhattan_accuracy
      value: 88.97426941436721
    - type: manhattan_ap
      value: 86.14154348065739
    - type: manhattan_f1
      value: 78.53991175290814
    - type: manhattan_precision
      value: 74.60339452719086
    - type: manhattan_recall
      value: 82.91499846011703
    - type: max_accuracy
      value: 89.00725734466566
    - type: max_ap
      value: 86.1594112416402
    - type: max_f1
      value: 78.544568993303
---
