sentence-transformers pytorch t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction sentence-similarity transformers English Sentence Similarity natural_questions ms_marco fever hotpot_qa mteb en license:apache-2.0 model-index autotrain_compatible text-generation-inference region:us
---
language: en
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- text-embedding
- embeddings
- information-retrieval
- beir
- text-classification
- language-model
- text-clustering
- text-semantic-similarity
- text-evaluation
- prompt-retrieval
- text-reranking
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- t5
- English
- Sentence Similarity
- natural_questions
- ms_marco
- fever
- hotpot_qa
- mteb
inference: false
model-index:
- name: INSTRUCTOR
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 88.13432835820896
    - type: ap
      value: 59.298209334395665
    - type: f1
      value: 83.31769058643586
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 91.526375
    - type: ap
      value: 88.16327709705504
    - type: f1
      value: 91.51095801287843
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 47.856
    - type: f1
      value: 45.41490917650942
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.223
    - type: map_at_10
      value: 47.947
    - type: map_at_100
      value: 48.742000000000004
    - type: map_at_1000
      value: 48.745
    - type: map_at_3
      value: 43.137
    - type: map_at_5
      value: 45.992
    - type: mrr_at_1
      value: 32.432
    - type: mrr_at_10
      value: 48.4
    - type: mrr_at_100
      value: 49.202
    - type: mrr_at_1000
      value: 49.205
    - type: mrr_at_3
      value: 43.551
    - type: mrr_at_5
      value: 46.467999999999996
    - type: ndcg_at_1
      value: 31.223
    - type: ndcg_at_10
      value: 57.045
    - type: ndcg_at_100
      value: 60.175
    - type: ndcg_at_1000
      value: 60.233000000000004
    - type: ndcg_at_3
      value: 47.171
    - type: ndcg_at_5
      value: 52.322
    - type: precision_at_1
      value: 31.223
    - type: precision_at_10
      value: 8.599
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 19.63
    - type: precision_at_5
      value: 14.282
    - type: recall_at_1
      value: 31.223
    - type: recall_at_10
      value: 85.989
    - type: recall_at_100
      value: 99.075
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 58.89
    - type: recall_at_5
      value: 71.408
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 43.1621946393635
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 32.56417132407894
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 64.29539304390207
    - type: mrr
      value: 76.44484017060196
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_spearman
      value: 84.38746499431112
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 78.51298701298701
    - type: f1
      value: 77.49041754069235
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.61848554098577
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 31.32623280148178
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 35.803000000000004
    - type: map_at_10
      value: 48.848
    - type: map_at_100
      value: 50.5
    - type: map_at_1000
      value: 50.602999999999994
    - type: map_at_3
      value: 45.111000000000004
    - type: map_at_5
      value: 47.202
    - type: mrr_at_1
      value: 44.635000000000005
    - type: mrr_at_10
      value: 55.593
    - type: mrr_at_100
      value: 56.169999999999995
    - type: mrr_at_1000
      value: 56.19499999999999
    - type: mrr_at_3
      value: 53.361999999999995
    - type: mrr_at_5
      value: 54.806999999999995
    - type: ndcg_at_1
      value: 44.635000000000005
    - type: ndcg_at_10
      value: 55.899
    - type: ndcg_at_100
      value: 60.958
    - type: ndcg_at_1000
      value: 62.302
    - type: ndcg_at_3
      value: 51.051
    - type: ndcg_at_5
      value: 53.351000000000006
    - type: precision_at_1
      value: 44.635000000000005
    - type: precision_at_10
      value: 10.786999999999999
    - type: precision_at_100
      value: 1.6580000000000001
    - type: precision_at_1000
      value: 0.213
    - type: precision_at_3
      value: 24.893
    - type: precision_at_5
      value: 17.740000000000002
    - type: recall_at_1
      value: 35.803000000000004
    - type: recall_at_10
      value: 68.657
    - type: recall_at_100
      value: 89.77199999999999
    - type: recall_at_1000
      value: 97.67
    - type: recall_at_3
      value: 54.066
    - type: recall_at_5
      value: 60.788
    - type: map_at_1
      value: 33.706
    - type: map_at_10
      value: 44.896
    - type: map_at_100
      value: 46.299
    - type: map_at_1000
      value: 46.44
    - type: map_at_3
      value: 41.721000000000004
    - type: map_at_5
      value: 43.486000000000004
    - type: mrr_at_1
      value: 41.592
    - type: mrr_at_10
      value: 50.529
    - type: mrr_at_100
      value: 51.22
    - type: mrr_at_1000
      value: 51.258
    - type: mrr_at_3
      value: 48.205999999999996
    - type: mrr_at_5
      value: 49.528
    - type: ndcg_at_1
      value: 41.592
    - type: ndcg_at_10
      value: 50.77199999999999
    - type: ndcg_at_100
      value: 55.383
    - type: ndcg_at_1000
      value: 57.288
    - type: ndcg_at_3
      value: 46.324
    - type: ndcg_at_5
      value: 48.346000000000004
    - type: precision_at_1
      value: 41.592
    - type: precision_at_10
      value: 9.516
    - type: precision_at_100
      value: 1.541
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 22.399
    - type: precision_at_5
      value: 15.770999999999999
    - type: recall_at_1
      value: 33.706
    - type: recall_at_10
      value: 61.353
    - type: recall_at_100
      value: 80.182
    - type: recall_at_1000
      value: 91.896
    - type: recall_at_3
      value: 48.204
    - type: recall_at_5
      value: 53.89699999999999
    - type: map_at_1
      value: 44.424
    - type: map_at_10
      value: 57.169000000000004
    - type: map_at_100
      value: 58.202
    - type: map_at_1000
      value: 58.242000000000004
    - type: map_at_3
      value: 53.825
    - type: map_at_5
      value: 55.714
    - type: mrr_at_1
      value: 50.470000000000006
    - type: mrr_at_10
      value: 60.489000000000004
    - type: mrr_at_100
      value: 61.096
    - type: mrr_at_1000
      value: 61.112
    - type: mrr_at_3
      value: 58.192
    - type: mrr_at_5
      value: 59.611999999999995
    - type: ndcg_at_1
      value: 50.470000000000006
    - type: ndcg_at_10
      value: 63.071999999999996
    - type: ndcg_at_100
      value: 66.964
    - type: ndcg_at_1000
      value: 67.659
    - type: ndcg_at_3
      value: 57.74399999999999
    - type: ndcg_at_5
      value: 60.367000000000004
    - type: precision_at_1
      value: 50.470000000000006
    - type: precision_at_10
      value: 10.019
    - type: precision_at_100
      value: 1.29
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 25.558999999999997
    - type: precision_at_5
      value: 17.467
    - type: recall_at_1
      value: 44.424
    - type: recall_at_10
      value: 77.02
    - type: recall_at_100
      value: 93.738
    - type: recall_at_1000
      value: 98.451
    - type: recall_at_3
      value: 62.888
    - type: recall_at_5
      value: 69.138
    - type: map_at_1
      value: 26.294
    - type: map_at_10
      value: 34.503
    - type: map_at_100
      value: 35.641
    - type: map_at_1000
      value: 35.724000000000004
    - type: map_at_3
      value: 31.753999999999998
    - type: map_at_5
      value: 33.190999999999995
    - type: mrr_at_1
      value: 28.362
    - type: mrr_at_10
      value: 36.53
    - type: mrr_at_100
      value: 37.541000000000004
    - type: mrr_at_1000
      value: 37.602000000000004
    - type: mrr_at_3
      value: 33.917
    - type: mrr_at_5
      value: 35.358000000000004
    - type: ndcg_at_1
      value: 28.362
    - type: ndcg_at_10
      value: 39.513999999999996
    - type: ndcg_at_100
      value: 44.815
    - type: ndcg_at_1000
      value: 46.839
    - type: ndcg_at_3
      value: 34.02
    - type: ndcg_at_5
      value: 36.522
    - type: precision_at_1
      value: 28.362
    - type: precision_at_10
      value: 6.101999999999999
    - type: precision_at_100
      value: 0.9129999999999999
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 14.161999999999999
    - type: precision_at_5
      value: 9.966
    - type: recall_at_1
      value: 26.294
    - type: recall_at_10
      value: 53.098
    - type: recall_at_100
      value: 76.877
    - type: recall_at_1000
      value: 91.834
    - type: recall_at_3
      value: 38.266
    - type: recall_at_5
      value: 44.287
    - type: map_at_1
      value: 16.407
    - type: map_at_10
      value: 25.185999999999996
    - type: map_at_100
      value: 26.533
    - type: map_at_1000
      value: 26.657999999999998
    - type: map_at_3
      value: 22.201999999999998
    - type: map_at_5
      value: 23.923
    - type: mrr_at_1
      value: 20.522000000000002
    - type: mrr_at_10
      value: 29.522
    - type: mrr_at_100
      value: 30.644
    - type: mrr_at_1000
      value: 30.713
    - type: mrr_at_3
      value: 26.679000000000002
    - type: mrr_at_5
      value: 28.483000000000004
    - type: ndcg_at_1
      value: 20.522000000000002
    - type: ndcg_at_10
      value: 30.656
    - type: ndcg_at_100
      value: 36.864999999999995
    - type: ndcg_at_1000
      value: 39.675
    - type: ndcg_at_3
      value: 25.319000000000003
    - type: ndcg_at_5
      value: 27.992
    - type: precision_at_1
      value: 20.522000000000002
    - type: precision_at_10
      value: 5.795999999999999
    - type: precision_at_100
      value: 1.027
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_3
      value: 12.396
    - type: precision_at_5
      value: 9.328
    - type: recall_at_1
      value: 16.407
    - type: recall_at_10
      value: 43.164
    - type: recall_at_100
      value: 69.695
    - type: recall_at_1000
      value: 89.41900000000001
    - type: recall_at_3
      value: 28.634999999999998
    - type: recall_at_5
      value: 35.308
    - type: map_at_1
      value: 30.473
    - type: map_at_10
      value: 41.676
    - type: map_at_100
      value: 43.120999999999995
    - type: map_at_1000
      value: 43.230000000000004
    - type: map_at_3
      value: 38.306000000000004
    - type: map_at_5
      value: 40.355999999999995
    - type: mrr_at_1
      value: 37.536
    - type: mrr_at_10
      value: 47.643
    - type: mrr_at_100
      value: 48.508
    - type: mrr_at_1000
      value: 48.551
    - type: mrr_at_3
      value: 45.348
    - type: mrr_at_5
      value: 46.744
    - type: ndcg_at_1
      value: 37.536
    - type: ndcg_at_10
      value: 47.823
    - type: ndcg_at_100
      value: 53.395
    - type: ndcg_at_1000
      value: 55.271
    - type: ndcg_at_3
      value: 42.768
    - type: ndcg_at_5
      value: 45.373000000000005
    - type: precision_at_1
      value: 37.536
    - type: precision_at_10
      value: 8.681
    - type: precision_at_100
      value: 1.34
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 20.468
    - type: precision_at_5
      value: 14.495
    - type: recall_at_1
      value: 30.473
    - type: recall_at_10
      value: 60.092999999999996
    - type: recall_at_100
      value: 82.733
    - type: recall_at_1000
      value: 94.875
    - type: recall_at_3
      value: 45.734
    - type: recall_at_5
      value: 52.691
    - type: map_at_1
      value: 29.976000000000003
    - type: map_at_10
      value: 41.097
    - type: map_at_100
      value: 42.547000000000004
    - type: map_at_1000
      value: 42.659000000000006
    - type: map_at_3
      value: 37.251
    - type: map_at_5
      value: 39.493
    - type: mrr_at_1
      value: 37.557
    - type: mrr_at_10
      value: 46.605000000000004
    - type: mrr_at_100
      value: 47.487
    - type: mrr_at_1000
      value: 47.54
    - type: mrr_at_3
      value: 43.721
    - type: mrr_at_5
      value: 45.411
    - type: ndcg_at_1
      value: 37.557
    - type: ndcg_at_10
      value: 47.449000000000005
    - type: ndcg_at_100
      value: 53.052
    - type: ndcg_at_1000
      value: 55.010999999999996
    - type: ndcg_at_3
      value: 41.439
    - type: ndcg_at_5
      value: 44.292
    - type: precision_at_1
      value: 37.557
    - type: precision_at_10
      value: 8.847
    - type: precision_at_100
      value: 1.357
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_3
      value: 20.091
    - type: precision_at_5
      value: 14.384
    - type: recall_at_1
      value: 29.976000000000003
    - type: recall_at_10
      value: 60.99099999999999
    - type: recall_at_100
      value: 84.245
    - type: recall_at_1000
      value: 96.97200000000001
    - type: recall_at_3
      value: 43.794
    - type: recall_at_5
      value: 51.778999999999996
    - type: map_at_1
      value: 28.099166666666665
    - type: map_at_10
      value: 38.1365
    - type: map_at_100
      value: 39.44491666666667
    - type: map_at_1000
      value: 39.55858333333334
    - type: map_at_3
      value: 35.03641666666666
    - type: map_at_5
      value: 36.79833333333334
    - type: mrr_at_1
      value: 33.39966666666667
    - type: mrr_at_10
      value: 42.42583333333333
    - type: mrr_at_100
      value: 43.28575
    - type: mrr_at_1000
      value: 43.33741666666667
    - type: mrr_at_3
      value: 39.94975
    - type: mrr_at_5
      value: 41.41633333333334
    - type: ndcg_at_1
      value: 33.39966666666667
    - type: ndcg_at_10
      value: 43.81741666666667
    - type: ndcg_at_100
      value: 49.08166666666667
    - type: ndcg_at_1000
      value: 51.121166666666674
    - type: ndcg_at_3
      value: 38.73575
    - type: ndcg_at_5
      value: 41.18158333333333
    - type: precision_at_1
      value: 33.39966666666667
    - type: precision_at_10
      value: 7.738916666666667
    - type: precision_at_100
      value: 1.2265833333333331
    - type: precision_at_1000
      value: 0.15983333333333336
    - type: precision_at_3
      value: 17.967416666666665
    - type: precision_at_5
      value: 12.78675
    - type: recall_at_1
      value: 28.099166666666665
    - type: recall_at_10
      value: 56.27049999999999
    - type: recall_at_100
      value: 78.93291666666667
    - type: recall_at_1000
      value: 92.81608333333334
    - type: recall_at_3
      value: 42.09775
    - type: recall_at_5
      value: 48.42533333333334
    - type: map_at_1
      value: 23.663
    - type: map_at_10
      value: 30.377
    - type: map_at_100
      value: 31.426
    - type: map_at_1000
      value: 31.519000000000002
    - type: map_at_3
      value: 28.069
    - type: map_at_5
      value: 29.256999999999998
    - type: mrr_at_1
      value: 26.687
    - type: mrr_at_10
      value: 33.107
    - type: mrr_at_100
      value: 34.055
    - type: mrr_at_1000
      value: 34.117999999999995
    - type: mrr_at_3
      value: 31.058000000000003
    - type: mrr_at_5
      value: 32.14
    - type: ndcg_at_1
      value: 26.687
    - type: ndcg_at_10
      value: 34.615
    - type: ndcg_at_100
      value: 39.776
    - type: ndcg_at_1000
      value: 42.05
    - type: ndcg_at_3
      value: 30.322
    - type: ndcg_at_5
      value: 32.157000000000004
    - type: precision_at_1
      value: 26.687
    - type: precision_at_10
      value: 5.491
    - type: precision_at_100
      value: 0.877
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 13.139000000000001
    - type: precision_at_5
      value: 9.049
    - type: recall_at_1
      value: 23.663
    - type: recall_at_10
      value: 45.035
    - type: recall_at_100
      value: 68.554
    - type: recall_at_1000
      value: 85.077
    - type: recall_at_3
      value: 32.982
    - type: recall_at_5
      value: 37.688
    - type: map_at_1
      value: 17.403
    - type: map_at_10
      value: 25.197000000000003
    - type: map_at_100
      value: 26.355
    - type: map_at_1000
      value: 26.487
    - type: map_at_3
      value: 22.733
    - type: map_at_5
      value: 24.114
    - type: mrr_at_1
      value: 21.37
    - type: mrr_at_10
      value: 29.091
    - type: mrr_at_100
      value: 30.018
    - type: mrr_at_1000
      value: 30.096
    - type: mrr_at_3
      value: 26.887
    - type: mrr_at_5
      value: 28.157
    - type: ndcg_at_1
      value: 21.37
    - type: ndcg_at_10
      value: 30.026000000000003
    - type: ndcg_at_100
      value: 35.416
    - type: ndcg_at_1000
      value: 38.45
    - type: ndcg_at_3
      value: 25.764
    - type: ndcg_at_5
      value: 27.742
    - type: precision_at_1
      value: 21.37
    - type: precision_at_10
      value: 5.609
    - type: precision_at_100
      value: 0.9860000000000001
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 12.423
    - type: precision_at_5
      value: 9.009
    - type: recall_at_1
      value: 17.403
    - type: recall_at_10
      value: 40.573
    - type: recall_at_100
      value: 64.818
    - type: recall_at_1000
      value: 86.53699999999999
    - type: recall_at_3
      value: 28.493000000000002
    - type: recall_at_5
      value: 33.660000000000004
    - type: map_at_1
      value: 28.639
    - type: map_at_10
      value: 38.951
    - type: map_at_100
      value: 40.238
    - type: map_at_1000
      value: 40.327
    - type: map_at_3
      value: 35.842
    - type: map_at_5
      value: 37.617
    - type: mrr_at_1
      value: 33.769
    - type: mrr_at_10
      value: 43.088
    - type: mrr_at_100
      value: 44.03
    - type: mrr_at_1000
      value: 44.072
    - type: mrr_at_3
      value: 40.656
    - type: mrr_at_5
      value: 42.138999999999996
    - type: ndcg_at_1
      value: 33.769
    - type: ndcg_at_10
      value: 44.676
    - type: ndcg_at_100
      value: 50.416000000000004
    - type: ndcg_at_1000
      value: 52.227999999999994
    - type: ndcg_at_3
      value: 39.494
    - type: ndcg_at_5
      value: 42.013
    - type: precision_at_1
      value: 33.769
    - type: precision_at_10
      value: 7.668
    - type: precision_at_100
      value: 1.18
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 18.221
    - type: precision_at_5
      value: 12.966
    - type: recall_at_1
      value: 28.639
    - type: recall_at_10
      value: 57.687999999999995
    - type: recall_at_100
      value: 82.541
    - type: recall_at_1000
      value: 94.896
    - type: recall_at_3
      value: 43.651
    - type: recall_at_5
      value: 49.925999999999995
    - type: map_at_1
      value: 29.57
    - type: map_at_10
      value: 40.004
    - type: map_at_100
      value: 41.75
    - type: map_at_1000
      value: 41.97
    - type: map_at_3
      value: 36.788
    - type: map_at_5
      value: 38.671
    - type: mrr_at_1
      value: 35.375
    - type: mrr_at_10
      value: 45.121
    - type: mrr_at_100
      value: 45.994
    - type: mrr_at_1000
      value: 46.04
    - type: mrr_at_3
      value: 42.227
    - type: mrr_at_5
      value: 43.995
    - type: ndcg_at_1
      value: 35.375
    - type: ndcg_at_10
      value: 46.392
    - type: ndcg_at_100
      value: 52.196
    - type: ndcg_at_1000
      value: 54.274
    - type: ndcg_at_3
      value: 41.163
    - type: ndcg_at_5
      value: 43.813
    - type: precision_at_1
      value: 35.375
    - type: precision_at_10
      value: 8.676
    - type: precision_at_100
      value: 1.678
    - type: precision_at_1000
      value: 0.253
    - type: precision_at_3
      value: 19.104
    - type: precision_at_5
      value: 13.913
    - type: recall_at_1
      value: 29.57
    - type: recall_at_10
      value: 58.779
    - type: recall_at_100
      value: 83.337
    - type: recall_at_1000
      value: 95.979
    - type: recall_at_3
      value: 44.005
    - type: recall_at_5
      value: 50.975
    - type: map_at_1
      value: 20.832
    - type: map_at_10
      value: 29.733999999999998
    - type: map_at_100
      value: 30.727
    - type: map_at_1000
      value: 30.843999999999998
    - type: map_at_3
      value: 26.834999999999997
    - type: map_at_5
      value: 28.555999999999997
    - type: mrr_at_1
      value: 22.921
    - type: mrr_at_10
      value: 31.791999999999998
    - type: mrr_at_100
      value: 32.666000000000004
    - type: mrr_at_1000
      value: 32.751999999999995
    - type: mrr_at_3
      value: 29.144
    - type: mrr_at_5
      value: 30.622
    - type: ndcg_at_1
      value: 22.921
    - type: ndcg_at_10
      value: 34.915
    - type: ndcg_at_100
      value: 39.744
    - type: ndcg_at_1000
      value: 42.407000000000004
    - type: ndcg_at_3
      value: 29.421000000000003
    - type: ndcg_at_5
      value: 32.211
    - type: precision_at_1
      value: 22.921
    - type: precision_at_10
      value: 5.675
    - type: precision_at_100
      value: 0.872
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 12.753999999999998
    - type: precision_at_5
      value: 9.353
    - type: recall_at_1
      value: 20.832
    - type: recall_at_10
      value: 48.795
    - type: recall_at_100
      value: 70.703
    - type: recall_at_1000
      value: 90.187
    - type: recall_at_3
      value: 34.455000000000005
    - type: recall_at_5
      value: 40.967
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.334
    - type: map_at_10
      value: 19.009999999999998
    - type: map_at_100
      value: 21.129
    - type: map_at_1000
      value: 21.328
    - type: map_at_3
      value: 15.152
    - type: map_at_5
      value: 17.084
    - type: mrr_at_1
      value: 23.453
    - type: mrr_at_10
      value: 36.099
    - type: mrr_at_100
      value: 37.069
    - type: mrr_at_1000
      value: 37.104
    - type: mrr_at_3
      value: 32.096000000000004
    - type: mrr_at_5
      value: 34.451
    - type: ndcg_at_1
      value: 23.453
    - type: ndcg_at_10
      value: 27.739000000000004
    - type: ndcg_at_100
      value: 35.836
    - type: ndcg_at_1000
      value: 39.242
    - type: ndcg_at_3
      value: 21.263
    - type: ndcg_at_5
      value: 23.677
    - type: precision_at_1
      value: 23.453
    - type: precision_at_10
      value: 9.199
    - type: precision_at_100
      value: 1.791
    - type: precision_at_1000
      value: 0.242
    - type: precision_at_3
      value: 16.2
    - type: precision_at_5
      value: 13.147
    - type: recall_at_1
      value: 10.334
    - type: recall_at_10
      value: 35.177
    - type: recall_at_100
      value: 63.009
    - type: recall_at_1000
      value: 81.938
    - type: recall_at_3
      value: 19.914
    - type: recall_at_5
      value: 26.077
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.212
    - type: map_at_10
      value: 17.386
    - type: map_at_100
      value: 24.234
    - type: map_at_1000
      value: 25.724999999999998
    - type: map_at_3
      value: 12.727
    - type: map_at_5
      value: 14.785
    - type: mrr_at_1
      value: 59.25
    - type: mrr_at_10
      value: 68.687
    - type: mrr_at_100
      value: 69.133
    - type: mrr_at_1000
      value: 69.14099999999999
    - type: mrr_at_3
      value: 66.917
    - type: mrr_at_5
      value: 67.742
    - type: ndcg_at_1
      value: 48.625
    - type: ndcg_at_10
      value: 36.675999999999995
    - type: ndcg_at_100
      value: 41.543
    - type: ndcg_at_1000
      value: 49.241
    - type: ndcg_at_3
      value: 41.373
    - type: ndcg_at_5
      value: 38.707
    - type: precision_at_1
      value: 59.25
    - type: precision_at_10
      value: 28.525
    - type: precision_at_100
      value: 9.027000000000001
    - type: precision_at_1000
      value: 1.8339999999999999
    - type: precision_at_3
      value: 44.833
    - type: precision_at_5
      value: 37.35
    - type: recall_at_1
      value: 8.212
    - type: recall_at_10
      value: 23.188
    - type: recall_at_100
      value: 48.613
    - type: recall_at_1000
      value: 73.093
    - type: recall_at_3
      value: 14.419
    - type: recall_at_5
      value: 17.798
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 52.725
    - type: f1
      value: 46.50743309855908
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 55.086
    - type: map_at_10
      value: 66.914
    - type: map_at_100
      value: 67.321
    - type: map_at_1000
      value: 67.341
    - type: map_at_3
      value: 64.75800000000001
    - type: map_at_5
      value: 66.189
    - type: mrr_at_1
      value: 59.28600000000001
    - type: mrr_at_10
      value: 71.005
    - type: mrr_at_100
      value: 71.304
    - type: mrr_at_1000
      value: 71.313
    - type: mrr_at_3
      value: 69.037
    - type: mrr_at_5
      value: 70.35
    - type: ndcg_at_1
      value: 59.28600000000001
    - type: ndcg_at_10
      value: 72.695
    - type: ndcg_at_100
      value: 74.432
    - type: ndcg_at_1000
      value: 74.868
    - type: ndcg_at_3
      value: 68.72200000000001
    - type: ndcg_at_5
      value: 71.081
    - type: precision_at_1
      value: 59.28600000000001
    - type: precision_at_10
      value: 9.499
    - type: precision_at_100
      value: 1.052
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 27.503
    - type: precision_at_5
      value: 17.854999999999997
    - type: recall_at_1
      value: 55.086
    - type: recall_at_10
      value: 86.453
    - type: recall_at_100
      value: 94.028
    - type: recall_at_1000
      value: 97.052
    - type: recall_at_3
      value: 75.821
    - type: recall_at_5
      value: 81.6
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.262999999999998
    - type: map_at_10
      value: 37.488
    - type: map_at_100
      value: 39.498
    - type: map_at_1000
      value: 39.687
    - type: map_at_3
      value: 32.529
    - type: map_at_5
      value: 35.455
    - type: mrr_at_1
      value: 44.907000000000004
    - type: mrr_at_10
      value: 53.239000000000004
    - type: mrr_at_100
      value: 54.086
    - type: mrr_at_1000
      value: 54.122
    - type: mrr_at_3
      value: 51.235
    - type: mrr_at_5
      value: 52.415
    - type: ndcg_at_1
      value: 44.907000000000004
    - type: ndcg_at_10
      value: 45.446
    - type: ndcg_at_100
      value: 52.429
    - type: ndcg_at_1000
      value: 55.169000000000004
    - type: ndcg_at_3
      value: 41.882000000000005
    - type: ndcg_at_5
      value: 43.178
    - type: precision_at_1
      value: 44.907000000000004
    - type: precision_at_10
      value: 12.931999999999999
    - type: precision_at_100
      value: 2.025
    - type: precision_at_1000
      value: 0.248
    - type: precision_at_3
      value: 28.652
    - type: precision_at_5
      value: 21.204
    - type: recall_at_1
      value: 22.262999999999998
    - type: recall_at_10
      value: 52.447
    - type: recall_at_100
      value: 78.045
    - type: recall_at_1000
      value: 94.419
    - type: recall_at_3
      value: 38.064
    - type: recall_at_5
      value: 44.769
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 32.519
    - type: map_at_10
      value: 45.831
    - type: map_at_100
      value: 46.815
    - type: map_at_1000
      value: 46.899
    - type: map_at_3
      value: 42.836
    - type: map_at_5
      value: 44.65
    - type: mrr_at_1
      value: 65.037
    - type: mrr_at_10
      value: 72.16
    - type: mrr_at_100
      value: 72.51100000000001
    - type: mrr_at_1000
      value: 72.53
    - type: mrr_at_3
      value: 70.682
    - type: mrr_at_5
      value: 71.54599999999999
    - type: ndcg_at_1
      value: 65.037
    - type: ndcg_at_10
      value: 55.17999999999999
    - type: ndcg_at_100
      value: 58.888
    - type: ndcg_at_1000
      value: 60.648
    - type: ndcg_at_3
      value: 50.501
    - type: ndcg_at_5
      value: 52.977
    - type: precision_at_1
      value: 65.037
    - type: precision_at_10
      value: 11.530999999999999
    - type: precision_at_100
      value: 1.4460000000000002
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 31.483
    - type: precision_at_5
      value: 20.845
    - type: recall_at_1
      value: 32.519
    - type: recall_at_10
      value: 57.657000000000004
    - type: recall_at_100
      value: 72.30199999999999
    - type: recall_at_1000
      value: 84.024
    - type: recall_at_3
      value: 47.225
    - type: recall_at_5
      value: 52.113
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 88.3168
    - type: ap
      value: 83.80165516037135
    - type: f1
      value: 88.29942471066407
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 20.724999999999998
    - type: map_at_10
      value: 32.736
    - type: map_at_100
      value: 33.938
    - type: map_at_1000
      value: 33.991
    - type: map_at_3
      value: 28.788000000000004
    - type: map_at_5
      value: 31.016
    - type: mrr_at_1
      value: 21.361
    - type: mrr_at_10
      value: 33.323
    - type: mrr_at_100
      value: 34.471000000000004
    - type: mrr_at_1000
      value: 34.518
    - type: mrr_at_3
      value: 29.453000000000003
    - type: mrr_at_5
      value: 31.629
    - type: ndcg_at_1
      value: 21.361
    - type: ndcg_at_10
      value: 39.649
    - type: ndcg_at_100
      value: 45.481
    - type: ndcg_at_1000
      value: 46.775
    - type: ndcg_at_3
      value: 31.594
    - type: ndcg_at_5
      value: 35.543
    - type: precision_at_1
      value: 21.361
    - type: precision_at_10
      value: 6.3740000000000006
    - type: precision_at_100
      value: 0.931
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 13.514999999999999
    - type: precision_at_5
      value: 10.100000000000001
    - type: recall_at_1
      value: 20.724999999999998
    - type: recall_at_10
      value: 61.034
    - type: recall_at_100
      value: 88.062
    - type: recall_at_1000
      value: 97.86399999999999
    - type: recall_at_3
      value: 39.072
    - type: recall_at_5
      value: 48.53
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 93.8919288645691
    - type: f1
      value: 93.57059586398059
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 67.97993616051072
    - type: f1
      value: 48.244319183606535
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 68.90047074646941
    - type: f1
      value: 66.48999056063725
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.34566240753195
    - type: f1
      value: 73.54164154290658
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 34.21866934757011
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 32.000936217235534
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.68189362520352
    - type: mrr
      value: 32.69603637784303
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.078
    - type: map_at_10
      value: 12.671
    - type: map_at_100
      value: 16.291
    - type: map_at_1000
      value: 17.855999999999998
    - type: map_at_3
      value: 9.610000000000001
    - type: map_at_5
      value: 11.152
    - type: mrr_at_1
      value: 43.963
    - type: mrr_at_10
      value: 53.173
    - type: mrr_at_100
      value: 53.718999999999994
    - type: mrr_at_1000
      value: 53.756
    - type: mrr_at_3
      value: 50.980000000000004
    - type: mrr_at_5
      value: 52.42
    - type: ndcg_at_1
      value: 42.415000000000006
    - type: ndcg_at_10
      value: 34.086
    - type: ndcg_at_100
      value: 32.545
    - type: ndcg_at_1000
      value: 41.144999999999996
    - type: ndcg_at_3
      value: 39.434999999999995
    - type: ndcg_at_5
      value: 37.888
    - type: precision_at_1
      value: 43.653
    - type: precision_at_10
      value: 25.014999999999997
    - type: precision_at_100
      value: 8.594
    - type: precision_at_1000
      value: 2.169
    - type: precision_at_3
      value: 37.049
    - type: precision_at_5
      value: 33.065
    - type: recall_at_1
      value: 6.078
    - type: recall_at_10
      value: 16.17
    - type: recall_at_100
      value: 34.512
    - type: recall_at_1000
      value: 65.447
    - type: recall_at_3
      value: 10.706
    - type: recall_at_5
      value: 13.158
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 27.378000000000004
    - type: map_at_10
      value: 42.178
    - type: map_at_100
      value: 43.32
    - type: map_at_1000
      value: 43.358000000000004
    - type: map_at_3
      value: 37.474000000000004
    - type: map_at_5
      value: 40.333000000000006
    - type: mrr_at_1
      value: 30.823
    - type: mrr_at_10
      value: 44.626
    - type: mrr_at_100
      value: 45.494
    - type: mrr_at_1000
      value: 45.519
    - type: mrr_at_3
      value: 40.585
    - type: mrr_at_5
      value: 43.146
    - type: ndcg_at_1
      value: 30.794
    - type: ndcg_at_10
      value: 50.099000000000004
    - type: ndcg_at_100
      value: 54.900999999999996
    - type: ndcg_at_1000
      value: 55.69499999999999
    - type: ndcg_at_3
      value: 41.238
    - type: ndcg_at_5
      value: 46.081
    - type: precision_at_1
      value: 30.794
    - type: precision_at_10
      value: 8.549
    - type: precision_at_100
      value: 1.124
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 18.926000000000002
    - type: precision_at_5
      value: 14.16
    - type: recall_at_1
      value: 27.378000000000004
    - type: recall_at_10
      value: 71.842
    - type: recall_at_100
      value: 92.565
    - type: recall_at_1000
      value: 98.402
    - type: recall_at_3
      value: 49.053999999999995
    - type: recall_at_5
      value: 60.207
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.557
    - type: map_at_10
      value: 84.729
    - type: map_at_100
      value: 85.369
    - type: map_at_1000
      value: 85.382
    - type: map_at_3
      value: 81.72
    - type: map_at_5
      value: 83.613
    - type: mrr_at_1
      value: 81.3
    - type: mrr_at_10
      value: 87.488
    - type: mrr_at_100
      value: 87.588
    - type: mrr_at_1000
      value: 87.589
    - type: mrr_at_3
      value: 86.53
    - type: mrr_at_5
      value: 87.18599999999999
    - type: ndcg_at_1
      value: 81.28999999999999
    - type: ndcg_at_10
      value: 88.442
    - type: ndcg_at_100
      value: 89.637
    - type: ndcg_at_1000
      value: 89.70700000000001
    - type: ndcg_at_3
      value: 85.55199999999999
    - type: ndcg_at_5
      value: 87.154
    - type: precision_at_1
      value: 81.28999999999999
    - type: precision_at_10
      value: 13.489999999999998
    - type: precision_at_100
      value: 1.54
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.553
    - type: precision_at_5
      value: 24.708
    - type: recall_at_1
      value: 70.557
    - type: recall_at_10
      value: 95.645
    - type: recall_at_100
      value: 99.693
    - type: recall_at_1000
      value: 99.995
    - type: recall_at_3
      value: 87.359
    - type: recall_at_5
      value: 91.89699999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 63.65060114776209
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 64.63271250680617
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.263
    - type: map_at_10
      value: 10.801
    - type: map_at_100
      value: 12.888
    - type: map_at_1000
      value: 13.224
    - type: map_at_3
      value: 7.362
    - type: map_at_5
      value: 9.149000000000001
    - type: mrr_at_1
      value: 21
    - type: mrr_at_10
      value: 31.416
    - type: mrr_at_100
      value: 32.513
    - type: mrr_at_1000
      value: 32.58
    - type: mrr_at_3
      value: 28.116999999999997
    - type: mrr_at_5
      value: 29.976999999999997
    - type: ndcg_at_1
      value: 21
    - type: ndcg_at_10
      value: 18.551000000000002
    - type: ndcg_at_100
      value: 26.657999999999998
    - type: ndcg_at_1000
      value: 32.485
    - type: ndcg_at_3
      value: 16.834
    - type: ndcg_at_5
      value: 15.204999999999998
    - type: precision_at_1
      value: 21
    - type: precision_at_10
      value: 9.84
    - type: precision_at_100
      value: 2.16
    - type: precision_at_1000
      value: 0.35500000000000004
    - type: precision_at_3
      value: 15.667
    - type: precision_at_5
      value: 13.62
    - type: recall_at_1
      value: 4.263
    - type: recall_at_10
      value: 19.922
    - type: recall_at_100
      value: 43.808
    - type: recall_at_1000
      value: 72.14500000000001
    - type: recall_at_3
      value: 9.493
    - type: recall_at_5
      value: 13.767999999999999
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_spearman
      value: 81.27446313317233
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_spearman
      value: 76.27963301217527
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_spearman
      value: 88.18495048450949
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_spearman
      value: 81.91982338692046
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_spearman
      value: 89.00896818385291
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_spearman
      value: 85.48814644586132
  - 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_spearman
      value: 90.30116926966582
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_spearman
      value: 67.74132963032342
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_spearman
      value: 86.87741355780479
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 82.0019012295875
    - type: mrr
      value: 94.70267024188593
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 50.05
    - type: map_at_10
      value: 59.36
    - type: map_at_100
      value: 59.967999999999996
    - type: map_at_1000
      value: 60.023
    - type: map_at_3
      value: 56.515
    - type: map_at_5
      value: 58.272999999999996
    - type: mrr_at_1
      value: 53
    - type: mrr_at_10
      value: 61.102000000000004
    - type: mrr_at_100
      value: 61.476
    - type: mrr_at_1000
      value: 61.523
    - type: mrr_at_3
      value: 58.778
    - type: mrr_at_5
      value: 60.128
    - type: ndcg_at_1
      value: 53
    - type: ndcg_at_10
      value: 64.43100000000001
    - type: ndcg_at_100
      value: 66.73599999999999
    - type: ndcg_at_1000
      value: 68.027
    - type: ndcg_at_3
      value: 59.279
    - type: ndcg_at_5
      value: 61.888
    - type: precision_at_1
      value: 53
    - type: precision_at_10
      value: 8.767
    - type: precision_at_100
      value: 1.01
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 23.444000000000003
    - type: precision_at_5
      value: 15.667
    - type: recall_at_1
      value: 50.05
    - type: recall_at_10
      value: 78.511
    - type: recall_at_100
      value: 88.5
    - type: recall_at_1000
      value: 98.333
    - type: recall_at_3
      value: 64.117
    - type: recall_at_5
      value: 70.867
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.72178217821782
    - type: cos_sim_ap
      value: 93.0728601593541
    - type: cos_sim_f1
      value: 85.6727976766699
    - type: cos_sim_precision
      value: 83.02063789868667
    - type: cos_sim_recall
      value: 88.5
    - type: dot_accuracy
      value: 99.72178217821782
    - type: dot_ap
      value: 93.07287396168348
    - type: dot_f1
      value: 85.6727976766699
    - type: dot_precision
      value: 83.02063789868667
    - type: dot_recall
      value: 88.5
    - type: euclidean_accuracy
      value: 99.72178217821782
    - type: euclidean_ap
      value: 93.07285657982895
    - type: euclidean_f1
      value: 85.6727976766699
    - type: euclidean_precision
      value: 83.02063789868667
    - type: euclidean_recall
      value: 88.5
    - type: manhattan_accuracy
      value: 99.72475247524753
    - type: manhattan_ap
      value: 93.02792973059809
    - type: manhattan_f1
      value: 85.7727737973388
    - type: manhattan_precision
      value: 87.84067085953879
    - type: manhattan_recall
      value: 83.8
    - type: max_accuracy
      value: 99.72475247524753
    - type: max_ap
      value: 93.07287396168348
    - type: max_f1
      value: 85.7727737973388
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 68.77583615550819
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 36.151636938606956
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 52.16607939471187
    - type: mrr
      value: 52.95172046091163
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.314646669495666
    - type: cos_sim_spearman
      value: 31.83562491439455
    - type: dot_pearson
      value: 31.314590842874157
    - type: dot_spearman
      value: 31.83363065810437
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.198
    - type: map_at_10
      value: 1.3010000000000002
    - type: map_at_100
      value: 7.2139999999999995
    - type: map_at_1000
      value: 20.179
    - type: map_at_3
      value: 0.528
    - type: map_at_5
      value: 0.8019999999999999
    - type: mrr_at_1
      value: 72
    - type: mrr_at_10
      value: 83.39999999999999
    - type: mrr_at_100
      value: 83.39999999999999
    - type: mrr_at_1000
      value: 83.39999999999999
    - type: mrr_at_3
      value: 81.667
    - type: mrr_at_5
      value: 83.06700000000001
    - type: ndcg_at_1
      value: 66
    - type: ndcg_at_10
      value: 58.059000000000005
    - type: ndcg_at_100
      value: 44.316
    - type: ndcg_at_1000
      value: 43.147000000000006
    - type: ndcg_at_3
      value: 63.815999999999995
    - type: ndcg_at_5
      value: 63.005
    - type: precision_at_1
      value: 72
    - type: precision_at_10
      value: 61.4
    - type: precision_at_100
      value: 45.62
    - type: precision_at_1000
      value: 19.866
    - type: precision_at_3
      value: 70
    - type: precision_at_5
      value: 68.8
    - type: recall_at_1
      value: 0.198
    - type: recall_at_10
      value: 1.517
    - type: recall_at_100
      value: 10.587
    - type: recall_at_1000
      value: 41.233
    - type: recall_at_3
      value: 0.573
    - type: recall_at_5
      value: 0.907
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.894
    - type: map_at_10
      value: 8.488999999999999
    - type: map_at_100
      value: 14.445
    - type: map_at_1000
      value: 16.078
    - type: map_at_3
      value: 4.589
    - type: map_at_5
      value: 6.019
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 39.82
    - type: mrr_at_100
      value: 40.752
    - type: mrr_at_1000
      value: 40.771
    - type: mrr_at_3
      value: 34.354
    - type: mrr_at_5
      value: 37.721
    - type: ndcg_at_1
      value: 19.387999999999998
    - type: ndcg_at_10
      value: 21.563
    - type: ndcg_at_100
      value: 33.857
    - type: ndcg_at_1000
      value: 46.199
    - type: ndcg_at_3
      value: 22.296
    - type: ndcg_at_5
      value: 21.770999999999997
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 19.796
    - type: precision_at_100
      value: 7.142999999999999
    - type: precision_at_1000
      value: 1.541
    - type: precision_at_3
      value: 24.490000000000002
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 1.894
    - type: recall_at_10
      value: 14.931
    - type: recall_at_100
      value: 45.524
    - type: recall_at_1000
      value: 83.243
    - type: recall_at_3
      value: 5.712
    - type: recall_at_5
      value: 8.386000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.049
    - type: ap
      value: 13.85116971310922
    - type: f1
      value: 54.37504302487686
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 64.1312959818902
    - type: f1
      value: 64.11413877009383
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 54.13103431861502
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.327889372355
    - type: cos_sim_ap
      value: 77.42059895975699
    - type: cos_sim_f1
      value: 71.02706903250873
    - type: cos_sim_precision
      value: 69.75324344950394
    - type: cos_sim_recall
      value: 72.34828496042216
    - type: dot_accuracy
      value: 87.327889372355
    - type: dot_ap
      value: 77.4209479346677
    - type: dot_f1
      value: 71.02706903250873
    - type: dot_precision
      value: 69.75324344950394
    - type: dot_recall
      value: 72.34828496042216
    - type: euclidean_accuracy
      value: 87.327889372355
    - type: euclidean_ap
      value: 77.42096495861037
    - type: euclidean_f1
      value: 71.02706903250873
    - type: euclidean_precision
      value: 69.75324344950394
    - type: euclidean_recall
      value: 72.34828496042216
    - type: manhattan_accuracy
      value: 87.31000774870358
    - type: manhattan_ap
      value: 77.38930750711619
    - type: manhattan_f1
      value: 71.07935314027831
    - type: manhattan_precision
      value: 67.70957726295677
    - type: manhattan_recall
      value: 74.80211081794195
    - type: max_accuracy
      value: 87.327889372355
    - type: max_ap
      value: 77.42096495861037
    - type: max_f1
      value: 71.07935314027831
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.58939729110878
    - type: cos_sim_ap
      value: 87.17594155025475
    - type: cos_sim_f1
      value: 79.21146953405018
    - type: cos_sim_precision
      value: 76.8918527109307
    - type: cos_sim_recall
      value: 81.67539267015707
    - type: dot_accuracy
      value: 89.58939729110878
    - type: dot_ap
      value: 87.17593963273593
    - type: dot_f1
      value: 79.21146953405018
    - type: dot_precision
      value: 76.8918527109307
    - type: dot_recall
      value: 81.67539267015707
    - type: euclidean_accuracy
      value: 89.58939729110878
    - type: euclidean_ap
      value: 87.17592466925834
    - type: euclidean_f1
      value: 79.21146953405018
    - type: euclidean_precision
      value: 76.8918527109307
    - type: euclidean_recall
      value: 81.67539267015707
    - type: manhattan_accuracy
      value: 89.62626615438352
    - type: manhattan_ap
      value: 87.16589873161546
    - type: manhattan_f1
      value: 79.25143598295348
    - type: manhattan_precision
      value: 76.39494177323712
    - type: manhattan_recall
      value: 82.32984293193716
    - type: max_accuracy
      value: 89.62626615438352
    - type: max_ap
      value: 87.17594155025475
    - type: max_f1
      value: 79.25143598295348
---
