sentence-transformers feature-extraction sentence-similarity mteb en dataset:s2orc dataset:flax-sentence-embeddings/stackexchange_title_body_jsonl dataset:flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl dataset:flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl dataset:flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl dataset:sentence-transformers/reddit-title-body dataset:msmarco dataset:gooaq dataset:yahoo_answers_topics dataset:code_search_net dataset:search_qa dataset:eli5 dataset:snli dataset:multi_nli dataset:wikihow dataset:natural_questions dataset:trivia_qa dataset:embedding-data/sentence-compression dataset:embedding-data/flickr30k-captions dataset:embedding-data/altlex dataset:embedding-data/simple-wiki dataset:embedding-data/QQP dataset:embedding-data/SPECTER dataset:embedding-data/PAQ_pairs dataset:embedding-data/WikiAnswers dataset:sentence-transformers/embedding-training-data license:apache-2.0 model-index autotrain_compatible region:us
---
license: apache-2.0
pipeline_tag: sentence-similarity
inference: false
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
language: en
datasets:
- s2orc
- flax-sentence-embeddings/stackexchange_title_body_jsonl
- flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl
- flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl
- flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl
- sentence-transformers/reddit-title-body
- msmarco
- gooaq
- yahoo_answers_topics
- code_search_net
- search_qa
- eli5
- snli
- multi_nli
- wikihow
- natural_questions
- trivia_qa
- embedding-data/sentence-compression
- embedding-data/flickr30k-captions
- embedding-data/altlex
- embedding-data/simple-wiki
- embedding-data/QQP
- embedding-data/SPECTER
- embedding-data/PAQ_pairs
- embedding-data/WikiAnswers
- sentence-transformers/embedding-training-data
model-index:
- name: lodestone-base-4096-v1
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 69.7313432835821
    - type: ap
      value: 31.618259511417733
    - type: f1
      value: 63.30313825394228
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 86.89837499999999
    - type: ap
      value: 82.39500885672128
    - type: f1
      value: 86.87317947399657
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 44.05
    - type: f1
      value: 42.67624383248947
  - task:
      type: Retrieval
    dataset:
      type: arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 26.173999999999996
    - type: map_at_10
      value: 40.976
    - type: map_at_100
      value: 42.067
    - type: map_at_1000
      value: 42.075
    - type: map_at_3
      value: 35.917
    - type: map_at_5
      value: 38.656
    - type: mrr_at_1
      value: 26.814
    - type: mrr_at_10
      value: 41.252
    - type: mrr_at_100
      value: 42.337
    - type: mrr_at_1000
      value: 42.345
    - type: mrr_at_3
      value: 36.226
    - type: mrr_at_5
      value: 38.914
    - type: ndcg_at_1
      value: 26.173999999999996
    - type: ndcg_at_10
      value: 49.819
    - type: ndcg_at_100
      value: 54.403999999999996
    - type: ndcg_at_1000
      value: 54.59
    - type: ndcg_at_3
      value: 39.231
    - type: ndcg_at_5
      value: 44.189
    - type: precision_at_1
      value: 26.173999999999996
    - type: precision_at_10
      value: 7.838000000000001
    - type: precision_at_100
      value: 0.9820000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 16.287
    - type: precision_at_5
      value: 12.191
    - type: recall_at_1
      value: 26.173999999999996
    - type: recall_at_10
      value: 78.378
    - type: recall_at_100
      value: 98.222
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 48.862
    - type: recall_at_5
      value: 60.953
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 42.31689035788179
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 31.280245136660984
  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 58.79109720839415
    - type: mrr
      value: 71.79615705931495
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 76.44918756608115
    - type: cos_sim_spearman
      value: 70.86607256286257
    - type: euclidean_pearson
      value: 74.12154678100815
    - type: euclidean_spearman
      value: 70.86607256286257
    - type: manhattan_pearson
      value: 74.0078626964417
    - type: manhattan_spearman
      value: 70.68353828321327
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.40584415584415
    - type: f1
      value: 74.29514617572676
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.41860080664014
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 29.319217023090705
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 26.595000000000002
    - type: map_at_10
      value: 36.556
    - type: map_at_100
      value: 37.984
    - type: map_at_1000
      value: 38.134
    - type: map_at_3
      value: 33.417
    - type: map_at_5
      value: 35.160000000000004
    - type: mrr_at_1
      value: 32.761
    - type: mrr_at_10
      value: 41.799
    - type: mrr_at_100
      value: 42.526
    - type: mrr_at_1000
      value: 42.582
    - type: mrr_at_3
      value: 39.39
    - type: mrr_at_5
      value: 40.727000000000004
    - type: ndcg_at_1
      value: 32.761
    - type: ndcg_at_10
      value: 42.549
    - type: ndcg_at_100
      value: 47.915
    - type: ndcg_at_1000
      value: 50.475
    - type: ndcg_at_3
      value: 37.93
    - type: ndcg_at_5
      value: 39.939
    - type: precision_at_1
      value: 32.761
    - type: precision_at_10
      value: 8.312
    - type: precision_at_100
      value: 1.403
    - type: precision_at_1000
      value: 0.197
    - type: precision_at_3
      value: 18.741
    - type: precision_at_5
      value: 13.447999999999999
    - type: recall_at_1
      value: 26.595000000000002
    - type: recall_at_10
      value: 54.332
    - type: recall_at_100
      value: 76.936
    - type: recall_at_1000
      value: 93.914
    - type: recall_at_3
      value: 40.666000000000004
    - type: recall_at_5
      value: 46.513
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.528000000000002
    - type: map_at_10
      value: 30.751
    - type: map_at_100
      value: 31.855
    - type: map_at_1000
      value: 31.972
    - type: map_at_3
      value: 28.465
    - type: map_at_5
      value: 29.738
    - type: mrr_at_1
      value: 28.662
    - type: mrr_at_10
      value: 35.912
    - type: mrr_at_100
      value: 36.726
    - type: mrr_at_1000
      value: 36.777
    - type: mrr_at_3
      value: 34.013
    - type: mrr_at_5
      value: 35.156
    - type: ndcg_at_1
      value: 28.662
    - type: ndcg_at_10
      value: 35.452
    - type: ndcg_at_100
      value: 40.1
    - type: ndcg_at_1000
      value: 42.323
    - type: ndcg_at_3
      value: 32.112
    - type: ndcg_at_5
      value: 33.638
    - type: precision_at_1
      value: 28.662
    - type: precision_at_10
      value: 6.688
    - type: precision_at_100
      value: 1.13
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_3
      value: 15.562999999999999
    - type: precision_at_5
      value: 11.019
    - type: recall_at_1
      value: 22.528000000000002
    - type: recall_at_10
      value: 43.748
    - type: recall_at_100
      value: 64.235
    - type: recall_at_1000
      value: 78.609
    - type: recall_at_3
      value: 33.937
    - type: recall_at_5
      value: 38.234
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 33.117999999999995
    - type: map_at_10
      value: 44.339
    - type: map_at_100
      value: 45.367000000000004
    - type: map_at_1000
      value: 45.437
    - type: map_at_3
      value: 41.195
    - type: map_at_5
      value: 42.922
    - type: mrr_at_1
      value: 38.37
    - type: mrr_at_10
      value: 47.786
    - type: mrr_at_100
      value: 48.522
    - type: mrr_at_1000
      value: 48.567
    - type: mrr_at_3
      value: 45.371
    - type: mrr_at_5
      value: 46.857
    - type: ndcg_at_1
      value: 38.37
    - type: ndcg_at_10
      value: 50.019999999999996
    - type: ndcg_at_100
      value: 54.36299999999999
    - type: ndcg_at_1000
      value: 55.897
    - type: ndcg_at_3
      value: 44.733000000000004
    - type: ndcg_at_5
      value: 47.292
    - type: precision_at_1
      value: 38.37
    - type: precision_at_10
      value: 8.288
    - type: precision_at_100
      value: 1.139
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 20.293
    - type: precision_at_5
      value: 14.107
    - type: recall_at_1
      value: 33.117999999999995
    - type: recall_at_10
      value: 63.451
    - type: recall_at_100
      value: 82.767
    - type: recall_at_1000
      value: 93.786
    - type: recall_at_3
      value: 48.964999999999996
    - type: recall_at_5
      value: 55.358
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 16.028000000000002
    - type: map_at_10
      value: 23.186999999999998
    - type: map_at_100
      value: 24.236
    - type: map_at_1000
      value: 24.337
    - type: map_at_3
      value: 20.816000000000003
    - type: map_at_5
      value: 22.311
    - type: mrr_at_1
      value: 17.514
    - type: mrr_at_10
      value: 24.84
    - type: mrr_at_100
      value: 25.838
    - type: mrr_at_1000
      value: 25.924999999999997
    - type: mrr_at_3
      value: 22.542
    - type: mrr_at_5
      value: 24.04
    - type: ndcg_at_1
      value: 17.514
    - type: ndcg_at_10
      value: 27.391
    - type: ndcg_at_100
      value: 32.684999999999995
    - type: ndcg_at_1000
      value: 35.367
    - type: ndcg_at_3
      value: 22.820999999999998
    - type: ndcg_at_5
      value: 25.380999999999997
    - type: precision_at_1
      value: 17.514
    - type: precision_at_10
      value: 4.463
    - type: precision_at_100
      value: 0.745
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 10.019
    - type: precision_at_5
      value: 7.457999999999999
    - type: recall_at_1
      value: 16.028000000000002
    - type: recall_at_10
      value: 38.81
    - type: recall_at_100
      value: 63.295
    - type: recall_at_1000
      value: 83.762
    - type: recall_at_3
      value: 26.604
    - type: recall_at_5
      value: 32.727000000000004
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 11.962
    - type: map_at_10
      value: 17.218
    - type: map_at_100
      value: 18.321
    - type: map_at_1000
      value: 18.455
    - type: map_at_3
      value: 15.287999999999998
    - type: map_at_5
      value: 16.417
    - type: mrr_at_1
      value: 14.677000000000001
    - type: mrr_at_10
      value: 20.381
    - type: mrr_at_100
      value: 21.471999999999998
    - type: mrr_at_1000
      value: 21.566
    - type: mrr_at_3
      value: 18.448999999999998
    - type: mrr_at_5
      value: 19.587
    - type: ndcg_at_1
      value: 14.677000000000001
    - type: ndcg_at_10
      value: 20.86
    - type: ndcg_at_100
      value: 26.519
    - type: ndcg_at_1000
      value: 30.020000000000003
    - type: ndcg_at_3
      value: 17.208000000000002
    - type: ndcg_at_5
      value: 19.037000000000003
    - type: precision_at_1
      value: 14.677000000000001
    - type: precision_at_10
      value: 3.856
    - type: precision_at_100
      value: 0.7889999999999999
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 8.043
    - type: precision_at_5
      value: 6.069999999999999
    - type: recall_at_1
      value: 11.962
    - type: recall_at_10
      value: 28.994999999999997
    - type: recall_at_100
      value: 54.071999999999996
    - type: recall_at_1000
      value: 79.309
    - type: recall_at_3
      value: 19.134999999999998
    - type: recall_at_5
      value: 23.727999999999998
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.764
    - type: map_at_10
      value: 31.744
    - type: map_at_100
      value: 33.037
    - type: map_at_1000
      value: 33.156
    - type: map_at_3
      value: 29.015
    - type: map_at_5
      value: 30.434
    - type: mrr_at_1
      value: 28.296
    - type: mrr_at_10
      value: 37.03
    - type: mrr_at_100
      value: 37.902
    - type: mrr_at_1000
      value: 37.966
    - type: mrr_at_3
      value: 34.568
    - type: mrr_at_5
      value: 35.786
    - type: ndcg_at_1
      value: 28.296
    - type: ndcg_at_10
      value: 37.289
    - type: ndcg_at_100
      value: 42.787
    - type: ndcg_at_1000
      value: 45.382
    - type: ndcg_at_3
      value: 32.598
    - type: ndcg_at_5
      value: 34.521
    - type: precision_at_1
      value: 28.296
    - type: precision_at_10
      value: 6.901
    - type: precision_at_100
      value: 1.135
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 15.367
    - type: precision_at_5
      value: 11.03
    - type: recall_at_1
      value: 22.764
    - type: recall_at_10
      value: 48.807
    - type: recall_at_100
      value: 71.859
    - type: recall_at_1000
      value: 89.606
    - type: recall_at_3
      value: 35.594
    - type: recall_at_5
      value: 40.541
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.742
    - type: map_at_10
      value: 27.741
    - type: map_at_100
      value: 29.323
    - type: map_at_1000
      value: 29.438
    - type: map_at_3
      value: 25.217
    - type: map_at_5
      value: 26.583000000000002
    - type: mrr_at_1
      value: 24.657999999999998
    - type: mrr_at_10
      value: 32.407000000000004
    - type: mrr_at_100
      value: 33.631
    - type: mrr_at_1000
      value: 33.686
    - type: mrr_at_3
      value: 30.194
    - type: mrr_at_5
      value: 31.444
    - type: ndcg_at_1
      value: 24.657999999999998
    - type: ndcg_at_10
      value: 32.614
    - type: ndcg_at_100
      value: 39.61
    - type: ndcg_at_1000
      value: 42.114000000000004
    - type: ndcg_at_3
      value: 28.516000000000002
    - type: ndcg_at_5
      value: 30.274
    - type: precision_at_1
      value: 24.657999999999998
    - type: precision_at_10
      value: 6.176
    - type: precision_at_100
      value: 1.1400000000000001
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 13.927
    - type: precision_at_5
      value: 9.954
    - type: recall_at_1
      value: 19.742
    - type: recall_at_10
      value: 42.427
    - type: recall_at_100
      value: 72.687
    - type: recall_at_1000
      value: 89.89
    - type: recall_at_3
      value: 30.781
    - type: recall_at_5
      value: 35.606
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.72608333333333
    - type: map_at_10
      value: 27.165333333333336
    - type: map_at_100
      value: 28.292499999999997
    - type: map_at_1000
      value: 28.416333333333327
    - type: map_at_3
      value: 24.783833333333334
    - type: map_at_5
      value: 26.101750000000003
    - type: mrr_at_1
      value: 23.721500000000002
    - type: mrr_at_10
      value: 30.853333333333328
    - type: mrr_at_100
      value: 31.741750000000003
    - type: mrr_at_1000
      value: 31.812999999999995
    - type: mrr_at_3
      value: 28.732249999999997
    - type: mrr_at_5
      value: 29.945166666666665
    - type: ndcg_at_1
      value: 23.721500000000002
    - type: ndcg_at_10
      value: 31.74883333333333
    - type: ndcg_at_100
      value: 36.883583333333334
    - type: ndcg_at_1000
      value: 39.6145
    - type: ndcg_at_3
      value: 27.639583333333334
    - type: ndcg_at_5
      value: 29.543666666666667
    - type: precision_at_1
      value: 23.721500000000002
    - type: precision_at_10
      value: 5.709083333333333
    - type: precision_at_100
      value: 0.9859166666666666
    - type: precision_at_1000
      value: 0.1413333333333333
    - type: precision_at_3
      value: 12.85683333333333
    - type: precision_at_5
      value: 9.258166666666668
    - type: recall_at_1
      value: 19.72608333333333
    - type: recall_at_10
      value: 41.73583333333334
    - type: recall_at_100
      value: 64.66566666666668
    - type: recall_at_1000
      value: 84.09833333333336
    - type: recall_at_3
      value: 30.223083333333328
    - type: recall_at_5
      value: 35.153083333333335
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 17.582
    - type: map_at_10
      value: 22.803
    - type: map_at_100
      value: 23.503
    - type: map_at_1000
      value: 23.599999999999998
    - type: map_at_3
      value: 21.375
    - type: map_at_5
      value: 22.052
    - type: mrr_at_1
      value: 20.399
    - type: mrr_at_10
      value: 25.369999999999997
    - type: mrr_at_100
      value: 26.016000000000002
    - type: mrr_at_1000
      value: 26.090999999999998
    - type: mrr_at_3
      value: 23.952
    - type: mrr_at_5
      value: 24.619
    - type: ndcg_at_1
      value: 20.399
    - type: ndcg_at_10
      value: 25.964
    - type: ndcg_at_100
      value: 29.607
    - type: ndcg_at_1000
      value: 32.349
    - type: ndcg_at_3
      value: 23.177
    - type: ndcg_at_5
      value: 24.276
    - type: precision_at_1
      value: 20.399
    - type: precision_at_10
      value: 4.018
    - type: precision_at_100
      value: 0.629
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 9.969
    - type: precision_at_5
      value: 6.748
    - type: recall_at_1
      value: 17.582
    - type: recall_at_10
      value: 33.35
    - type: recall_at_100
      value: 50.219
    - type: recall_at_1000
      value: 71.06099999999999
    - type: recall_at_3
      value: 25.619999999999997
    - type: recall_at_5
      value: 28.291
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 11.071
    - type: map_at_10
      value: 16.201999999999998
    - type: map_at_100
      value: 17.112
    - type: map_at_1000
      value: 17.238
    - type: map_at_3
      value: 14.508
    - type: map_at_5
      value: 15.440999999999999
    - type: mrr_at_1
      value: 13.833
    - type: mrr_at_10
      value: 19.235
    - type: mrr_at_100
      value: 20.108999999999998
    - type: mrr_at_1000
      value: 20.196
    - type: mrr_at_3
      value: 17.515
    - type: mrr_at_5
      value: 18.505
    - type: ndcg_at_1
      value: 13.833
    - type: ndcg_at_10
      value: 19.643
    - type: ndcg_at_100
      value: 24.298000000000002
    - type: ndcg_at_1000
      value: 27.614
    - type: ndcg_at_3
      value: 16.528000000000002
    - type: ndcg_at_5
      value: 17.991
    - type: precision_at_1
      value: 13.833
    - type: precision_at_10
      value: 3.6990000000000003
    - type: precision_at_100
      value: 0.713
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 7.9030000000000005
    - type: precision_at_5
      value: 5.891
    - type: recall_at_1
      value: 11.071
    - type: recall_at_10
      value: 27.019
    - type: recall_at_100
      value: 48.404
    - type: recall_at_1000
      value: 72.641
    - type: recall_at_3
      value: 18.336
    - type: recall_at_5
      value: 21.991
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 18.573
    - type: map_at_10
      value: 25.008999999999997
    - type: map_at_100
      value: 26.015
    - type: map_at_1000
      value: 26.137
    - type: map_at_3
      value: 22.798
    - type: map_at_5
      value: 24.092
    - type: mrr_at_1
      value: 22.108
    - type: mrr_at_10
      value: 28.646
    - type: mrr_at_100
      value: 29.477999999999998
    - type: mrr_at_1000
      value: 29.57
    - type: mrr_at_3
      value: 26.415
    - type: mrr_at_5
      value: 27.693
    - type: ndcg_at_1
      value: 22.108
    - type: ndcg_at_10
      value: 29.42
    - type: ndcg_at_100
      value: 34.385
    - type: ndcg_at_1000
      value: 37.572
    - type: ndcg_at_3
      value: 25.274
    - type: ndcg_at_5
      value: 27.315
    - type: precision_at_1
      value: 22.108
    - type: precision_at_10
      value: 5.093
    - type: precision_at_100
      value: 0.859
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 11.474
    - type: precision_at_5
      value: 8.321000000000002
    - type: recall_at_1
      value: 18.573
    - type: recall_at_10
      value: 39.433
    - type: recall_at_100
      value: 61.597
    - type: recall_at_1000
      value: 84.69
    - type: recall_at_3
      value: 27.849
    - type: recall_at_5
      value: 33.202999999999996
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 22.807
    - type: map_at_10
      value: 30.014000000000003
    - type: map_at_100
      value: 31.422
    - type: map_at_1000
      value: 31.652
    - type: map_at_3
      value: 27.447
    - type: map_at_5
      value: 28.711
    - type: mrr_at_1
      value: 27.668
    - type: mrr_at_10
      value: 34.489
    - type: mrr_at_100
      value: 35.453
    - type: mrr_at_1000
      value: 35.526
    - type: mrr_at_3
      value: 32.477000000000004
    - type: mrr_at_5
      value: 33.603
    - type: ndcg_at_1
      value: 27.668
    - type: ndcg_at_10
      value: 34.983
    - type: ndcg_at_100
      value: 40.535
    - type: ndcg_at_1000
      value: 43.747
    - type: ndcg_at_3
      value: 31.026999999999997
    - type: ndcg_at_5
      value: 32.608
    - type: precision_at_1
      value: 27.668
    - type: precision_at_10
      value: 6.837999999999999
    - type: precision_at_100
      value: 1.411
    - type: precision_at_1000
      value: 0.23600000000000002
    - type: precision_at_3
      value: 14.295
    - type: precision_at_5
      value: 10.435
    - type: recall_at_1
      value: 22.807
    - type: recall_at_10
      value: 43.545
    - type: recall_at_100
      value: 69.39800000000001
    - type: recall_at_1000
      value: 90.706
    - type: recall_at_3
      value: 32.183
    - type: recall_at_5
      value: 36.563
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 13.943
    - type: map_at_10
      value: 20.419999999999998
    - type: map_at_100
      value: 21.335
    - type: map_at_1000
      value: 21.44
    - type: map_at_3
      value: 17.865000000000002
    - type: map_at_5
      value: 19.36
    - type: mrr_at_1
      value: 15.712000000000002
    - type: mrr_at_10
      value: 22.345000000000002
    - type: mrr_at_100
      value: 23.227999999999998
    - type: mrr_at_1000
      value: 23.304
    - type: mrr_at_3
      value: 19.901
    - type: mrr_at_5
      value: 21.325
    - type: ndcg_at_1
      value: 15.712000000000002
    - type: ndcg_at_10
      value: 24.801000000000002
    - type: ndcg_at_100
      value: 29.799
    - type: ndcg_at_1000
      value: 32.513999999999996
    - type: ndcg_at_3
      value: 19.750999999999998
    - type: ndcg_at_5
      value: 22.252
    - type: precision_at_1
      value: 15.712000000000002
    - type: precision_at_10
      value: 4.1770000000000005
    - type: precision_at_100
      value: 0.738
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 8.688
    - type: precision_at_5
      value: 6.617000000000001
    - type: recall_at_1
      value: 13.943
    - type: recall_at_10
      value: 36.913000000000004
    - type: recall_at_100
      value: 60.519
    - type: recall_at_1000
      value: 81.206
    - type: recall_at_3
      value: 23.006999999999998
    - type: recall_at_5
      value: 29.082
  - task:
      type: Retrieval
    dataset:
      type: climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.468
    - type: map_at_10
      value: 16.029
    - type: map_at_100
      value: 17.693
    - type: map_at_1000
      value: 17.886
    - type: map_at_3
      value: 13.15
    - type: map_at_5
      value: 14.568
    - type: mrr_at_1
      value: 21.173000000000002
    - type: mrr_at_10
      value: 31.028
    - type: mrr_at_100
      value: 32.061
    - type: mrr_at_1000
      value: 32.119
    - type: mrr_at_3
      value: 27.534999999999997
    - type: mrr_at_5
      value: 29.431
    - type: ndcg_at_1
      value: 21.173000000000002
    - type: ndcg_at_10
      value: 23.224
    - type: ndcg_at_100
      value: 30.225
    - type: ndcg_at_1000
      value: 33.961000000000006
    - type: ndcg_at_3
      value: 18.174
    - type: ndcg_at_5
      value: 19.897000000000002
    - type: precision_at_1
      value: 21.173000000000002
    - type: precision_at_10
      value: 7.4719999999999995
    - type: precision_at_100
      value: 1.5010000000000001
    - type: precision_at_1000
      value: 0.219
    - type: precision_at_3
      value: 13.312
    - type: precision_at_5
      value: 10.619
    - type: recall_at_1
      value: 9.468
    - type: recall_at_10
      value: 28.823
    - type: recall_at_100
      value: 53.26499999999999
    - type: recall_at_1000
      value: 74.536
    - type: recall_at_3
      value: 16.672
    - type: recall_at_5
      value: 21.302
  - task:
      type: Retrieval
    dataset:
      type: dbpedia-entity
      name: MTEB DBPedia
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.343
    - type: map_at_10
      value: 12.717
    - type: map_at_100
      value: 16.48
    - type: map_at_1000
      value: 17.381
    - type: map_at_3
      value: 9.568999999999999
    - type: map_at_5
      value: 11.125
    - type: mrr_at_1
      value: 48.75
    - type: mrr_at_10
      value: 58.425000000000004
    - type: mrr_at_100
      value: 59.075
    - type: mrr_at_1000
      value: 59.095
    - type: mrr_at_3
      value: 56.291999999999994
    - type: mrr_at_5
      value: 57.679
    - type: ndcg_at_1
      value: 37.875
    - type: ndcg_at_10
      value: 27.77
    - type: ndcg_at_100
      value: 30.288999999999998
    - type: ndcg_at_1000
      value: 36.187999999999995
    - type: ndcg_at_3
      value: 31.385999999999996
    - type: ndcg_at_5
      value: 29.923
    - type: precision_at_1
      value: 48.75
    - type: precision_at_10
      value: 22.375
    - type: precision_at_100
      value: 6.3420000000000005
    - type: precision_at_1000
      value: 1.4489999999999998
    - type: precision_at_3
      value: 35.5
    - type: precision_at_5
      value: 30.55
    - type: recall_at_1
      value: 6.343
    - type: recall_at_10
      value: 16.936
    - type: recall_at_100
      value: 35.955999999999996
    - type: recall_at_1000
      value: 55.787
    - type: recall_at_3
      value: 10.771
    - type: recall_at_5
      value: 13.669999999999998
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 41.99
    - type: f1
      value: 36.823402174564954
  - task:
      type: Retrieval
    dataset:
      type: fever
      name: MTEB FEVER
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.088
    - type: map_at_10
      value: 52.69200000000001
    - type: map_at_100
      value: 53.296
    - type: map_at_1000
      value: 53.325
    - type: map_at_3
      value: 49.905
    - type: map_at_5
      value: 51.617000000000004
    - type: mrr_at_1
      value: 43.009
    - type: mrr_at_10
      value: 56.203
    - type: mrr_at_100
      value: 56.75
    - type: mrr_at_1000
      value: 56.769000000000005
    - type: mrr_at_3
      value: 53.400000000000006
    - type: mrr_at_5
      value: 55.163
    - type: ndcg_at_1
      value: 43.009
    - type: ndcg_at_10
      value: 59.39
    - type: ndcg_at_100
      value: 62.129999999999995
    - type: ndcg_at_1000
      value: 62.793
    - type: ndcg_at_3
      value: 53.878
    - type: ndcg_at_5
      value: 56.887
    - type: precision_at_1
      value: 43.009
    - type: precision_at_10
      value: 8.366
    - type: precision_at_100
      value: 0.983
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 22.377
    - type: precision_at_5
      value: 15.035000000000002
    - type: recall_at_1
      value: 40.088
    - type: recall_at_10
      value: 76.68700000000001
    - type: recall_at_100
      value: 88.91
    - type: recall_at_1000
      value: 93.782
    - type: recall_at_3
      value: 61.809999999999995
    - type: recall_at_5
      value: 69.131
  - task:
      type: Retrieval
    dataset:
      type: fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.817
    - type: map_at_10
      value: 18.9
    - type: map_at_100
      value: 20.448
    - type: map_at_1000
      value: 20.660999999999998
    - type: map_at_3
      value: 15.979
    - type: map_at_5
      value: 17.415
    - type: mrr_at_1
      value: 23.148
    - type: mrr_at_10
      value: 31.208000000000002
    - type: mrr_at_100
      value: 32.167
    - type: mrr_at_1000
      value: 32.242
    - type: mrr_at_3
      value: 28.498
    - type: mrr_at_5
      value: 29.964000000000002
    - type: ndcg_at_1
      value: 23.148
    - type: ndcg_at_10
      value: 25.325999999999997
    - type: ndcg_at_100
      value: 31.927
    - type: ndcg_at_1000
      value: 36.081
    - type: ndcg_at_3
      value: 21.647
    - type: ndcg_at_5
      value: 22.762999999999998
    - type: precision_at_1
      value: 23.148
    - type: precision_at_10
      value: 7.546
    - type: precision_at_100
      value: 1.415
    - type: precision_at_1000
      value: 0.216
    - type: precision_at_3
      value: 14.969
    - type: precision_at_5
      value: 11.327
    - type: recall_at_1
      value: 10.817
    - type: recall_at_10
      value: 32.164
    - type: recall_at_100
      value: 57.655
    - type: recall_at_1000
      value: 82.797
    - type: recall_at_3
      value: 19.709
    - type: recall_at_5
      value: 24.333
  - task:
      type: Retrieval
    dataset:
      type: hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 25.380999999999997
    - type: map_at_10
      value: 33.14
    - type: map_at_100
      value: 33.948
    - type: map_at_1000
      value: 34.028000000000006
    - type: map_at_3
      value: 31.019999999999996
    - type: map_at_5
      value: 32.23
    - type: mrr_at_1
      value: 50.763000000000005
    - type: mrr_at_10
      value: 57.899
    - type: mrr_at_100
      value: 58.426
    - type: mrr_at_1000
      value: 58.457
    - type: mrr_at_3
      value: 56.093
    - type: mrr_at_5
      value: 57.116
    - type: ndcg_at_1
      value: 50.763000000000005
    - type: ndcg_at_10
      value: 41.656
    - type: ndcg_at_100
      value: 45.079
    - type: ndcg_at_1000
      value: 46.916999999999994
    - type: ndcg_at_3
      value: 37.834
    - type: ndcg_at_5
      value: 39.732
    - type: precision_at_1
      value: 50.763000000000005
    - type: precision_at_10
      value: 8.648
    - type: precision_at_100
      value: 1.135
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 23.105999999999998
    - type: precision_at_5
      value: 15.363
    - type: recall_at_1
      value: 25.380999999999997
    - type: recall_at_10
      value: 43.241
    - type: recall_at_100
      value: 56.745000000000005
    - type: recall_at_1000
      value: 69.048
    - type: recall_at_3
      value: 34.659
    - type: recall_at_5
      value: 38.406
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 79.544
    - type: ap
      value: 73.82920133396664
    - type: f1
      value: 79.51048124883265
  - task:
      type: Retrieval
    dataset:
      type: msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 11.174000000000001
    - type: map_at_10
      value: 19.451999999999998
    - type: map_at_100
      value: 20.612
    - type: map_at_1000
      value: 20.703
    - type: map_at_3
      value: 16.444
    - type: map_at_5
      value: 18.083
    - type: mrr_at_1
      value: 11.447000000000001
    - type: mrr_at_10
      value: 19.808
    - type: mrr_at_100
      value: 20.958
    - type: mrr_at_1000
      value: 21.041999999999998
    - type: mrr_at_3
      value: 16.791
    - type: mrr_at_5
      value: 18.459
    - type: ndcg_at_1
      value: 11.447000000000001
    - type: ndcg_at_10
      value: 24.556
    - type: ndcg_at_100
      value: 30.637999999999998
    - type: ndcg_at_1000
      value: 33.14
    - type: ndcg_at_3
      value: 18.325
    - type: ndcg_at_5
      value: 21.278
    - type: precision_at_1
      value: 11.447000000000001
    - type: precision_at_10
      value: 4.215
    - type: precision_at_100
      value: 0.732
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 8.052
    - type: precision_at_5
      value: 6.318
    - type: recall_at_1
      value: 11.174000000000001
    - type: recall_at_10
      value: 40.543
    - type: recall_at_100
      value: 69.699
    - type: recall_at_1000
      value: 89.403
    - type: recall_at_3
      value: 23.442
    - type: recall_at_5
      value: 30.536
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.6671226630187
    - type: f1
      value: 89.57660424361246
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.284997720018254
    - type: f1
      value: 40.30637400152823
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.33557498318763
    - type: f1
      value: 60.24039910680179
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.37390719569603
    - type: f1
      value: 72.33097333477316
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 34.68158939060552
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 30.340061711905236
  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.01814326295803
    - type: mrr
      value: 33.20555240055367
  - task:
      type: Retrieval
    dataset:
      type: nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.3910000000000005
    - type: map_at_10
      value: 7.7219999999999995
    - type: map_at_100
      value: 10.286
    - type: map_at_1000
      value: 11.668000000000001
    - type: map_at_3
      value: 5.552
    - type: map_at_5
      value: 6.468
    - type: mrr_at_1
      value: 34.365
    - type: mrr_at_10
      value: 42.555
    - type: mrr_at_100
      value: 43.295
    - type: mrr_at_1000
      value: 43.357
    - type: mrr_at_3
      value: 40.299
    - type: mrr_at_5
      value: 41.182
    - type: ndcg_at_1
      value: 31.424000000000003
    - type: ndcg_at_10
      value: 24.758
    - type: ndcg_at_100
      value: 23.677999999999997
    - type: ndcg_at_1000
      value: 33.377
    - type: ndcg_at_3
      value: 28.302
    - type: ndcg_at_5
      value: 26.342
    - type: precision_at_1
      value: 33.437
    - type: precision_at_10
      value: 19.256999999999998
    - type: precision_at_100
      value: 6.662999999999999
    - type: precision_at_1000
      value: 1.9900000000000002
    - type: precision_at_3
      value: 27.761000000000003
    - type: precision_at_5
      value: 23.715
    - type: recall_at_1
      value: 3.3910000000000005
    - type: recall_at_10
      value: 11.068
    - type: recall_at_100
      value: 25.878
    - type: recall_at_1000
      value: 60.19
    - type: recall_at_3
      value: 6.1690000000000005
    - type: recall_at_5
      value: 7.767
  - task:
      type: Retrieval
    dataset:
      type: nq
      name: MTEB NQ
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 15.168000000000001
    - type: map_at_10
      value: 26.177
    - type: map_at_100
      value: 27.564
    - type: map_at_1000
      value: 27.628999999999998
    - type: map_at_3
      value: 22.03
    - type: map_at_5
      value: 24.276
    - type: mrr_at_1
      value: 17.439
    - type: mrr_at_10
      value: 28.205000000000002
    - type: mrr_at_100
      value: 29.357
    - type: mrr_at_1000
      value: 29.408
    - type: mrr_at_3
      value: 24.377
    - type: mrr_at_5
      value: 26.540000000000003
    - type: ndcg_at_1
      value: 17.41
    - type: ndcg_at_10
      value: 32.936
    - type: ndcg_at_100
      value: 39.196999999999996
    - type: ndcg_at_1000
      value: 40.892
    - type: ndcg_at_3
      value: 24.721
    - type: ndcg_at_5
      value: 28.615000000000002
    - type: precision_at_1
      value: 17.41
    - type: precision_at_10
      value: 6.199000000000001
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 11.790000000000001
    - type: precision_at_5
      value: 9.264
    - type: recall_at_1
      value: 15.168000000000001
    - type: recall_at_10
      value: 51.914
    - type: recall_at_100
      value: 79.804
    - type: recall_at_1000
      value: 92.75999999999999
    - type: recall_at_3
      value: 30.212
    - type: recall_at_5
      value: 39.204
  - task:
      type: Retrieval
    dataset:
      type: quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 67.306
    - type: map_at_10
      value: 80.634
    - type: map_at_100
      value: 81.349
    - type: map_at_1000
      value: 81.37299999999999
    - type: map_at_3
      value: 77.691
    - type: map_at_5
      value: 79.512
    - type: mrr_at_1
      value: 77.56
    - type: mrr_at_10
      value: 84.177
    - type: mrr_at_100
      value: 84.35000000000001
    - type: mrr_at_1000
      value: 84.353
    - type: mrr_at_3
      value: 83.003
    - type: mrr_at_5
      value: 83.799
    - type: ndcg_at_1
      value: 77.58
    - type: ndcg_at_10
      value: 84.782
    - type: ndcg_at_100
      value: 86.443
    - type: ndcg_at_1000
      value: 86.654
    - type: ndcg_at_3
      value: 81.67
    - type: ndcg_at_5
      value: 83.356
    - type: precision_at_1
      value: 77.58
    - type: precision_at_10
      value: 12.875
    - type: precision_at_100
      value: 1.503
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 35.63
    - type: precision_at_5
      value: 23.483999999999998
    - type: recall_at_1
      value: 67.306
    - type: recall_at_10
      value: 92.64
    - type: recall_at_100
      value: 98.681
    - type: recall_at_1000
      value: 99.79
    - type: recall_at_3
      value: 83.682
    - type: recall_at_5
      value: 88.424
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 50.76319866126382
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 55.024711941648995
  - task:
      type: Retrieval
    dataset:
      type: scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.9379999999999997
    - type: map_at_10
      value: 8.817
    - type: map_at_100
      value: 10.546999999999999
    - type: map_at_1000
      value: 10.852
    - type: map_at_3
      value: 6.351999999999999
    - type: map_at_5
      value: 7.453
    - type: mrr_at_1
      value: 19.400000000000002
    - type: mrr_at_10
      value: 27.371000000000002
    - type: mrr_at_100
      value: 28.671999999999997
    - type: mrr_at_1000
      value: 28.747
    - type: mrr_at_3
      value: 24.583
    - type: mrr_at_5
      value: 26.143
    - type: ndcg_at_1
      value: 19.400000000000002
    - type: ndcg_at_10
      value: 15.264
    - type: ndcg_at_100
      value: 22.63
    - type: ndcg_at_1000
      value: 28.559
    - type: ndcg_at_3
      value: 14.424999999999999
    - type: ndcg_at_5
      value: 12.520000000000001
    - type: precision_at_1
      value: 19.400000000000002
    - type: precision_at_10
      value: 7.8100000000000005
    - type: precision_at_100
      value: 1.854
    - type: precision_at_1000
      value: 0.329
    - type: precision_at_3
      value: 13.100000000000001
    - type: precision_at_5
      value: 10.68
    - type: recall_at_1
      value: 3.9379999999999997
    - type: recall_at_10
      value: 15.903
    - type: recall_at_100
      value: 37.645
    - type: recall_at_1000
      value: 66.86
    - type: recall_at_3
      value: 7.993
    - type: recall_at_5
      value: 10.885
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 80.12689060151425
    - type: cos_sim_spearman
      value: 70.46515535094771
    - type: euclidean_pearson
      value: 77.17160003557223
    - type: euclidean_spearman
      value: 70.4651757047438
    - type: manhattan_pearson
      value: 77.18129609281937
    - type: manhattan_spearman
      value: 70.46610403752913
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 70.451157033355
    - type: cos_sim_spearman
      value: 63.99899601697852
    - type: euclidean_pearson
      value: 67.46985359967678
    - type: euclidean_spearman
      value: 64.00001637764805
    - type: manhattan_pearson
      value: 67.56534741780037
    - type: manhattan_spearman
      value: 64.06533893575366
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.65086614464292
    - type: cos_sim_spearman
      value: 78.20169706921848
    - type: euclidean_pearson
      value: 77.77758172155283
    - type: euclidean_spearman
      value: 78.20169706921848
    - type: manhattan_pearson
      value: 77.75077884860052
    - type: manhattan_spearman
      value: 78.16875216484164
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.26381598259717
    - type: cos_sim_spearman
      value: 70.78377709313477
    - type: euclidean_pearson
      value: 74.82646556532096
    - type: euclidean_spearman
      value: 70.78377658155212
    - type: manhattan_pearson
      value: 74.81784766108225
    - type: manhattan_spearman
      value: 70.79351454692176
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.00532026789739
    - type: cos_sim_spearman
      value: 80.02708383244838
    - type: euclidean_pearson
      value: 79.48345422610525
    - type: euclidean_spearman
      value: 80.02708383244838
    - type: manhattan_pearson
      value: 79.44519739854803
    - type: manhattan_spearman
      value: 79.98344094559687
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.32783048164805
    - type: cos_sim_spearman
      value: 78.79729961288045
    - type: euclidean_pearson
      value: 78.72111945793154
    - type: euclidean_spearman
      value: 78.79729904606872
    - type: manhattan_pearson
      value: 78.72464311117116
    - type: manhattan_spearman
      value: 78.822591248334
  - task:
      type: STS
    dataset:
      type: mteb/sts17-crosslingual-sts
      name: MTEB STS17 (en-en)
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.04318630630854
    - type: cos_sim_spearman
      value: 83.87886389259836
    - type: euclidean_pearson
      value: 83.40385877895086
    - type: euclidean_spearman
      value: 83.87886389259836
    - type: manhattan_pearson
      value: 83.46337128901547
    - type: manhattan_spearman
      value: 83.9723106941644
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (en)
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 63.003511169944595
    - type: cos_sim_spearman
      value: 64.39318805580227
    - type: euclidean_pearson
      value: 65.4797990735967
    - type: euclidean_spearman
      value: 64.39318805580227
    - type: manhattan_pearson
      value: 65.44604544280844
    - type: manhattan_spearman
      value: 64.38742899984233
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.63101237585029
    - type: cos_sim_spearman
      value: 75.57446967644269
    - type: euclidean_pearson
      value: 76.93491768734478
    - type: euclidean_spearman
      value: 75.57446967644269
    - type: manhattan_pearson
      value: 76.92187567800636
    - type: manhattan_spearman
      value: 75.57239337194585
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 78.5376604868993
    - type: mrr
      value: 92.94422897364073
  - task:
      type: Retrieval
    dataset:
      type: scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 38.872
    - type: map_at_10
      value: 50.417
    - type: map_at_100
      value: 51.202000000000005
    - type: map_at_1000
      value: 51.25999999999999
    - type: map_at_3
      value: 47.02
    - type: map_at_5
      value: 49.326
    - type: mrr_at_1
      value: 41.0
    - type: mrr_at_10
      value: 51.674
    - type: mrr_at_100
      value: 52.32599999999999
    - type: mrr_at_1000
      value: 52.376999999999995
    - type: mrr_at_3
      value: 48.778
    - type: mrr_at_5
      value: 50.744
    - type: ndcg_at_1
      value: 41.0
    - type: ndcg_at_10
      value: 56.027
    - type: ndcg_at_100
      value: 59.362
    - type: ndcg_at_1000
      value: 60.839
    - type: ndcg_at_3
      value: 50.019999999999996
    - type: ndcg_at_5
      value: 53.644999999999996
    - type: precision_at_1
      value: 41.0
    - type: precision_at_10
      value: 8.1
    - type: precision_at_100
      value: 0.987
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 20.444000000000003
    - type: precision_at_5
      value: 14.466999999999999
    - type: recall_at_1
      value: 38.872
    - type: recall_at_10
      value: 71.906
    - type: recall_at_100
      value: 86.367
    - type: recall_at_1000
      value: 98.0
    - type: recall_at_3
      value: 56.206
    - type: recall_at_5
      value: 65.05
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.7039603960396
    - type: cos_sim_ap
      value: 90.40809844250262
    - type: cos_sim_f1
      value: 84.53181583031557
    - type: cos_sim_precision
      value: 87.56698821007502
    - type: cos_sim_recall
      value: 81.69999999999999
    - type: dot_accuracy
      value: 99.7039603960396
    - type: dot_ap
      value: 90.40809844250262
    - type: dot_f1
      value: 84.53181583031557
    - type: dot_precision
      value: 87.56698821007502
    - type: dot_recall
      value: 81.69999999999999
    - type: euclidean_accuracy
      value: 99.7039603960396
    - type: euclidean_ap
      value: 90.4080982863383
    - type: euclidean_f1
      value: 84.53181583031557
    - type: euclidean_precision
      value: 87.56698821007502
    - type: euclidean_recall
      value: 81.69999999999999
    - type: manhattan_accuracy
      value: 99.7
    - type: manhattan_ap
      value: 90.39771161966652
    - type: manhattan_f1
      value: 84.32989690721648
    - type: manhattan_precision
      value: 87.02127659574468
    - type: manhattan_recall
      value: 81.8
    - type: max_accuracy
      value: 99.7039603960396
    - type: max_ap
      value: 90.40809844250262
    - type: max_f1
      value: 84.53181583031557
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 59.663210666678715
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.107791216468776
  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 46.440691925067604
    - type: mrr
      value: 47.03390257618199
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.067177519784074
    - type: cos_sim_spearman
      value: 31.234728424648967
    - type: dot_pearson
      value: 31.06717083018107
    - type: dot_spearman
      value: 31.234728424648967
  - task:
      type: Retrieval
    dataset:
      type: trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.136
    - type: map_at_10
      value: 0.767
    - type: map_at_100
      value: 3.3689999999999998
    - type: map_at_1000
      value: 8.613999999999999
    - type: map_at_3
      value: 0.369
    - type: map_at_5
      value: 0.514
    - type: mrr_at_1
      value: 48.0
    - type: mrr_at_10
      value: 63.908
    - type: mrr_at_100
      value: 64.615
    - type: mrr_at_1000
      value: 64.615
    - type: mrr_at_3
      value: 62.0
    - type: mrr_at_5
      value: 63.4
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 38.579
    - type: ndcg_at_100
      value: 26.409
    - type: ndcg_at_1000
      value: 26.858999999999998
    - type: ndcg_at_3
      value: 47.134
    - type: ndcg_at_5
      value: 43.287
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 40.400000000000006
    - type: precision_at_100
      value: 26.640000000000004
    - type: precision_at_1000
      value: 12.04
    - type: precision_at_3
      value: 52.666999999999994
    - type: precision_at_5
      value: 46.800000000000004
    - type: recall_at_1
      value: 0.136
    - type: recall_at_10
      value: 1.0070000000000001
    - type: recall_at_100
      value: 6.318
    - type: recall_at_1000
      value: 26.522000000000002
    - type: recall_at_3
      value: 0.41700000000000004
    - type: recall_at_5
      value: 0.606
  - task:
      type: Retrieval
    dataset:
      type: webis-touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.9949999999999999
    - type: map_at_10
      value: 8.304
    - type: map_at_100
      value: 13.644
    - type: map_at_1000
      value: 15.43
    - type: map_at_3
      value: 4.788
    - type: map_at_5
      value: 6.22
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 37.658
    - type: mrr_at_100
      value: 38.491
    - type: mrr_at_1000
      value: 38.503
    - type: mrr_at_3
      value: 32.312999999999995
    - type: mrr_at_5
      value: 35.68
    - type: ndcg_at_1
      value: 21.429000000000002
    - type: ndcg_at_10
      value: 18.995
    - type: ndcg_at_100
      value: 32.029999999999994
    - type: ndcg_at_1000
      value: 44.852
    - type: ndcg_at_3
      value: 19.464000000000002
    - type: ndcg_at_5
      value: 19.172
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 17.143
    - type: precision_at_100
      value: 6.877999999999999
    - type: precision_at_1000
      value: 1.524
    - type: precision_at_3
      value: 21.769
    - type: precision_at_5
      value: 20.0
    - type: recall_at_1
      value: 1.9949999999999999
    - type: recall_at_10
      value: 13.395999999999999
    - type: recall_at_100
      value: 44.348
    - type: recall_at_1000
      value: 82.622
    - type: recall_at_3
      value: 5.896
    - type: recall_at_5
      value: 8.554
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 67.9394
    - type: ap
      value: 12.943337263423334
    - type: f1
      value: 52.28243093094156
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 56.414827391058296
    - type: f1
      value: 56.666412409573105
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 47.009746255495465
  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.02574953805807
    - type: cos_sim_ap
      value: 67.66599910763128
    - type: cos_sim_f1
      value: 63.491277990844985
    - type: cos_sim_precision
      value: 59.77172140694154
    - type: cos_sim_recall
      value: 67.70448548812665
    - type: dot_accuracy
      value: 84.02574953805807
    - type: dot_ap
      value: 67.66600090945406
    - type: dot_f1
      value: 63.491277990844985
    - type: dot_precision
      value: 59.77172140694154
    - type: dot_recall
      value: 67.70448548812665
    - type: euclidean_accuracy
      value: 84.02574953805807
    - type: euclidean_ap
      value: 67.6659842364448
    - type: euclidean_f1
      value: 63.491277990844985
    - type: euclidean_precision
      value: 59.77172140694154
    - type: euclidean_recall
      value: 67.70448548812665
    - type: manhattan_accuracy
      value: 84.0317100792752
    - type: manhattan_ap
      value: 67.66351692448987
    - type: manhattan_f1
      value: 63.48610948306178
    - type: manhattan_precision
      value: 57.11875131828729
    - type: manhattan_recall
      value: 71.45118733509234
    - type: max_accuracy
      value: 84.0317100792752
    - type: max_ap
      value: 67.66600090945406
    - type: max_f1
      value: 63.491277990844985
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.53832421314084
    - type: cos_sim_ap
      value: 83.11416594316626
    - type: cos_sim_f1
      value: 75.41118114347518
    - type: cos_sim_precision
      value: 73.12839059674504
    - type: cos_sim_recall
      value: 77.8410840776101
    - type: dot_accuracy
      value: 87.53832421314084
    - type: dot_ap
      value: 83.11416226342155
    - type: dot_f1
      value: 75.41118114347518
    - type: dot_precision
      value: 73.12839059674504
    - type: dot_recall
      value: 77.8410840776101
    - type: euclidean_accuracy
      value: 87.53832421314084
    - type: euclidean_ap
      value: 83.11416284455395
    - type: euclidean_f1
      value: 75.41118114347518
    - type: euclidean_precision
      value: 73.12839059674504
    - type: euclidean_recall
      value: 77.8410840776101
    - type: manhattan_accuracy
      value: 87.49369348391353
    - type: manhattan_ap
      value: 83.08066812574694
    - type: manhattan_f1
      value: 75.36561228603892
    - type: manhattan_precision
      value: 71.9202518363064
    - type: manhattan_recall
      value: 79.15768401601478
    - type: max_accuracy
      value: 87.53832421314084
    - type: max_ap
      value: 83.11416594316626
    - type: max_f1
      value: 75.41118114347518
---

