mteb model-index region:us
---
tags:
- mteb
model-index:
- name: winberta
  results:
  - task:
      type: Clustering
    dataset:
      type: PL-MTEB/8tags-clustering
      name: MTEB 8TagsClustering
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 4.6762575299584555
  - task:
      type: STS
    dataset:
      type: C-MTEB/AFQMC
      name: MTEB AFQMC
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 39.92944665836267
    - type: cos_sim_spearman
      value: 44.25208147787637
    - type: euclidean_pearson
      value: 42.772842908404925
    - type: euclidean_spearman
      value: 44.25208147787637
    - type: manhattan_pearson
      value: 42.600565541302124
    - type: manhattan_spearman
      value: 44.10077657065955
  - task:
      type: STS
    dataset:
      type: C-MTEB/ATEC
      name: MTEB ATEC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 40.99236789888241
    - type: cos_sim_spearman
      value: 48.23930486989189
    - type: euclidean_pearson
      value: 48.58722571676781
    - type: euclidean_spearman
      value: 48.23930486989189
    - type: manhattan_pearson
      value: 48.46099247089918
    - type: manhattan_spearman
      value: 48.146434253428446
  - task:
      type: Classification
    dataset:
      type: PL-MTEB/allegro-reviews
      name: MTEB AllegroReviews
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 24.890656063618295
    - type: f1
      value: 22.302214664290936
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 69.91044776119402
    - type: ap
      value: 31.66723912472561
    - type: f1
      value: 63.421139457970746
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (de)
      config: de
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 54.111349036402565
    - type: ap
      value: 71.1991959997261
    - type: f1
      value: 51.56958434326653
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en-ext)
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.38230884557721
    - type: ap
      value: 19.909214544678782
    - type: f1
      value: 57.875461279657294
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (ja)
      config: ja
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 53.9507494646681
    - type: ap
      value: 11.599932987437649
    - type: f1
      value: 43.985879202841346
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 72.94987499999999
    - type: ap
      value: 67.05052265683933
    - type: f1
      value: 72.74508057235695
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (zh)
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 39.681999999999995
    - type: f1
      value: 37.89870143785791
  - task:
      type: Classification
    dataset:
      type: DDSC/angry-tweets
      name: MTEB AngryTweetsClassification
      config: default
      split: test
      revision: 20b0e6081892e78179356fada741b7afa381443d
    metrics:
    - type: accuracy
      value: 46.170009551098374
    - type: f1
      value: 45.00796485732147
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 33.69909330263927
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.04252711340139
  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.987091172373944
    - type: mrr
      value: 67.65840038693224
  - task:
      type: STS
    dataset:
      type: C-MTEB/BQ
      name: MTEB BQ
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 54.56093256747345
    - type: cos_sim_spearman
      value: 56.27367976851523
    - type: euclidean_pearson
      value: 55.38528627937832
    - type: euclidean_spearman
      value: 56.27367284031196
    - type: manhattan_pearson
      value: 55.30402898692059
    - type: manhattan_spearman
      value: 56.19811385550433
  - task:
      type: BitextMining
    dataset:
      type: mteb/bucc-bitext-mining
      name: MTEB BUCC (de-en)
      config: de-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 9.384133611691023
    - type: f1
      value: 9.25678496868476
    - type: precision
      value: 9.204791728800078
    - type: recall
      value: 9.384133611691023
  - task:
      type: BitextMining
    dataset:
      type: mteb/bucc-bitext-mining
      name: MTEB BUCC (fr-en)
      config: fr-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 17.719568567026194
    - type: f1
      value: 17.413603345806735
    - type: precision
      value: 17.284183459067894
    - type: recall
      value: 17.719568567026194
  - task:
      type: BitextMining
    dataset:
      type: mteb/bucc-bitext-mining
      name: MTEB BUCC (ru-en)
      config: ru-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 52.70523034291652
    - type: f1
      value: 51.97355963514606
    - type: precision
      value: 51.642562994485395
    - type: recall
      value: 52.70523034291652
  - task:
      type: BitextMining
    dataset:
      type: mteb/bucc-bitext-mining
      name: MTEB BUCC (zh-en)
      config: zh-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 89.0995260663507
    - type: f1
      value: 88.70458135860979
    - type: precision
      value: 88.5202738283307
    - type: recall
      value: 89.0995260663507
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 64.12337662337661
    - type: f1
      value: 62.35908261257942
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.70437969303962
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.27850834359782
  - task:
      type: Clustering
    dataset:
      type: slvnwhrl/blurbs-clustering-p2p
      name: MTEB BlurbsClusteringP2P
      config: default
      split: test
      revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
    metrics:
    - type: v_measure
      value: 17.471535040494018
  - task:
      type: Clustering
    dataset:
      type: slvnwhrl/blurbs-clustering-s2s
      name: MTEB BlurbsClusteringS2S
      config: default
      split: test
      revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d
    metrics:
    - type: v_measure
      value: 7.957798776861661
  - task:
      type: Classification
    dataset:
      type: PL-MTEB/cbd
      name: MTEB CBD
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 53.78000000000001
    - type: ap
      value: 16.030265142358818
    - type: f1
      value: 46.39936854646567
  - task:
      type: PairClassification
    dataset:
      type: PL-MTEB/cdsce-pairclassification
      name: MTEB CDSC-E
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 82.69999999999999
    - type: cos_sim_ap
      value: 43.50726455006939
    - type: cos_sim_f1
      value: 55.21472392638037
    - type: cos_sim_precision
      value: 45.1505016722408
    - type: cos_sim_recall
      value: 71.05263157894737
    - type: dot_accuracy
      value: 82.69999999999999
    - type: dot_ap
      value: 43.50726455006939
    - type: dot_f1
      value: 55.21472392638037
    - type: dot_precision
      value: 45.1505016722408
    - type: dot_recall
      value: 71.05263157894737
    - type: euclidean_accuracy
      value: 82.69999999999999
    - type: euclidean_ap
      value: 43.50726455006939
    - type: euclidean_f1
      value: 55.21472392638037
    - type: euclidean_precision
      value: 45.1505016722408
    - type: euclidean_recall
      value: 71.05263157894737
    - type: manhattan_accuracy
      value: 83.1
    - type: manhattan_ap
      value: 43.95534719205733
    - type: manhattan_f1
      value: 55.34351145038169
    - type: manhattan_precision
      value: 43.41317365269461
    - type: manhattan_recall
      value: 76.31578947368422
    - type: max_accuracy
      value: 83.1
    - type: max_ap
      value: 43.95534719205733
    - type: max_f1
      value: 55.34351145038169
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringP2P
      name: MTEB CLSClusteringP2P
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 42.20892953002924
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringS2S
      name: MTEB CLSClusteringS2S
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 40.33286164241634
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv1-reranking
      name: MTEB CMedQAv1
      config: default
      split: test
      revision: None
    metrics:
    - type: map
      value: 76.47170720756812
    - type: mrr
      value: 79.89289682539682
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv2-reranking
      name: MTEB CMedQAv2
      config: default
      split: test
      revision: None
    metrics:
    - type: map
      value: 77.43675520157939
    - type: mrr
      value: 81.11420634920636
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CmedqaRetrieval
      name: MTEB CmedqaRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 17.308
    - type: map_at_10
      value: 26.144000000000002
    - type: map_at_100
      value: 27.864
    - type: map_at_1000
      value: 28.032
    - type: map_at_3
      value: 23.058999999999997
    - type: map_at_5
      value: 24.724
    - type: mrr_at_1
      value: 27.206999999999997
    - type: mrr_at_10
      value: 34.287
    - type: mrr_at_100
      value: 35.375
    - type: mrr_at_1000
      value: 35.449999999999996
    - type: mrr_at_3
      value: 31.912000000000003
    - type: mrr_at_5
      value: 33.222
    - type: ndcg_at_1
      value: 27.206999999999997
    - type: ndcg_at_10
      value: 31.789
    - type: ndcg_at_100
      value: 39.251000000000005
    - type: ndcg_at_1000
      value: 42.536
    - type: ndcg_at_3
      value: 27.503
    - type: ndcg_at_5
      value: 29.226999999999997
    - type: precision_at_1
      value: 27.206999999999997
    - type: precision_at_10
      value: 7.3069999999999995
    - type: precision_at_100
      value: 1.345
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 15.854
    - type: precision_at_5
      value: 11.593
    - type: recall_at_1
      value: 17.308
    - type: recall_at_10
      value: 40.474
    - type: recall_at_100
      value: 71.897
    - type: recall_at_1000
      value: 94.375
    - type: recall_at_3
      value: 27.563
    - type: recall_at_5
      value: 32.944
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/CMNLI
      name: MTEB Cmnli
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 76.11545399879735
    - type: cos_sim_ap
      value: 84.09842598179311
    - type: cos_sim_f1
      value: 77.66760077602932
    - type: cos_sim_precision
      value: 72.04559088182364
    - type: cos_sim_recall
      value: 84.24129062426935
    - type: dot_accuracy
      value: 76.11545399879735
    - type: dot_ap
      value: 84.11185112340806
    - type: dot_f1
      value: 77.66760077602932
    - type: dot_precision
      value: 72.04559088182364
    - type: dot_recall
      value: 84.24129062426935
    - type: euclidean_accuracy
      value: 76.11545399879735
    - type: euclidean_ap
      value: 84.09842259671359
    - type: euclidean_f1
      value: 77.66760077602932
    - type: euclidean_precision
      value: 72.04559088182364
    - type: euclidean_recall
      value: 84.24129062426935
    - type: manhattan_accuracy
      value: 76.12748045700542
    - type: manhattan_ap
      value: 84.07246090513767
    - type: manhattan_f1
      value: 77.41864555848726
    - type: manhattan_precision
      value: 73.064951234696
    - type: manhattan_recall
      value: 82.3240589198036
    - type: max_accuracy
      value: 76.12748045700542
    - type: max_ap
      value: 84.11185112340806
    - type: max_f1
      value: 77.66760077602932
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CovidRetrieval
      name: MTEB CovidRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 53.266999999999996
    - type: map_at_10
      value: 61.807
    - type: map_at_100
      value: 62.342
    - type: map_at_1000
      value: 62.36000000000001
    - type: map_at_3
      value: 59.255
    - type: map_at_5
      value: 60.757000000000005
    - type: mrr_at_1
      value: 53.21399999999999
    - type: mrr_at_10
      value: 61.760999999999996
    - type: mrr_at_100
      value: 62.283
    - type: mrr_at_1000
      value: 62.300999999999995
    - type: mrr_at_3
      value: 59.272999999999996
    - type: mrr_at_5
      value: 60.727
    - type: ndcg_at_1
      value: 53.319
    - type: ndcg_at_10
      value: 66.334
    - type: ndcg_at_100
      value: 69.128
    - type: ndcg_at_1000
      value: 69.651
    - type: ndcg_at_3
      value: 61.105
    - type: ndcg_at_5
      value: 63.806
    - type: precision_at_1
      value: 53.319
    - type: precision_at_10
      value: 8.145
    - type: precision_at_100
      value: 0.9530000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 22.234
    - type: precision_at_5
      value: 14.668000000000001
    - type: recall_at_1
      value: 53.266999999999996
    - type: recall_at_10
      value: 80.717
    - type: recall_at_100
      value: 94.204
    - type: recall_at_1000
      value: 98.419
    - type: recall_at_3
      value: 66.359
    - type: recall_at_5
      value: 72.94500000000001
  - task:
      type: Classification
    dataset:
      type: DDSC/dkhate
      name: MTEB DKHateClassification
      config: default
      split: test
      revision: 59d12749a3c91a186063c7d729ec392fda94681c
    metrics:
    - type: accuracy
      value: 55.89665653495442
    - type: ap
      value: 13.442306681200666
    - type: f1
      value: 45.52792790494033
  - task:
      type: Classification
    dataset:
      type: AI-Sweden/SuperLim
      name: MTEB DalajClassification
      config: default
      split: test
      revision: 7ebf0b4caa7b2ae39698a889de782c09e6f5ee56
    metrics:
    - type: accuracy
      value: 49.77477477477478
    - type: ap
      value: 49.891019810950006
    - type: f1
      value: 49.271004191082156
  - task:
      type: Classification
    dataset:
      type: danish_political_comments
      name: MTEB DanishPoliticalCommentsClassification
      config: default
      split: train
      revision: edbb03726c04a0efab14fc8c3b8b79e4d420e5a1
    metrics:
    - type: accuracy
      value: 28.334721065778517
    - type: f1
      value: 25.604541019064698
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/DuRetrieval
      name: MTEB DuRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 21.575
    - type: map_at_10
      value: 65.302
    - type: map_at_100
      value: 68.85
    - type: map_at_1000
      value: 68.94200000000001
    - type: map_at_3
      value: 44.824000000000005
    - type: map_at_5
      value: 56.303000000000004
    - type: mrr_at_1
      value: 77.9
    - type: mrr_at_10
      value: 84.612
    - type: mrr_at_100
      value: 84.774
    - type: mrr_at_1000
      value: 84.78099999999999
    - type: mrr_at_3
      value: 84.05
    - type: mrr_at_5
      value: 84.42699999999999
    - type: ndcg_at_1
      value: 77.9
    - type: ndcg_at_10
      value: 75.247
    - type: ndcg_at_100
      value: 80.252
    - type: ndcg_at_1000
      value: 81.21000000000001
    - type: ndcg_at_3
      value: 73.664
    - type: ndcg_at_5
      value: 72.36200000000001
    - type: precision_at_1
      value: 77.9
    - type: precision_at_10
      value: 36.875
    - type: precision_at_100
      value: 4.607
    - type: precision_at_1000
      value: 0.483
    - type: precision_at_3
      value: 66.567
    - type: precision_at_5
      value: 55.97
    - type: recall_at_1
      value: 21.575
    - type: recall_at_10
      value: 77.268
    - type: recall_at_100
      value: 92.706
    - type: recall_at_1000
      value: 97.721
    - type: recall_at_3
      value: 48.42
    - type: recall_at_5
      value: 62.92
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/EcomRetrieval
      name: MTEB EcomRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 41.199999999999996
    - type: map_at_10
      value: 52.12
    - type: map_at_100
      value: 52.878
    - type: map_at_1000
      value: 52.898
    - type: map_at_3
      value: 49.6
    - type: map_at_5
      value: 51.23
    - type: mrr_at_1
      value: 41.199999999999996
    - type: mrr_at_10
      value: 52.12
    - type: mrr_at_100
      value: 52.878
    - type: mrr_at_1000
      value: 52.898
    - type: mrr_at_3
      value: 49.6
    - type: mrr_at_5
      value: 51.23
    - type: ndcg_at_1
      value: 41.199999999999996
    - type: ndcg_at_10
      value: 57.321
    - type: ndcg_at_100
      value: 61.019
    - type: ndcg_at_1000
      value: 61.638000000000005
    - type: ndcg_at_3
      value: 52.20399999999999
    - type: ndcg_at_5
      value: 55.177
    - type: precision_at_1
      value: 41.199999999999996
    - type: precision_at_10
      value: 7.359999999999999
    - type: precision_at_100
      value: 0.909
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 19.900000000000002
    - type: precision_at_5
      value: 13.4
    - type: recall_at_1
      value: 41.199999999999996
    - type: recall_at_10
      value: 73.6
    - type: recall_at_100
      value: 90.9
    - type: recall_at_1000
      value: 95.89999999999999
    - type: recall_at_3
      value: 59.699999999999996
    - type: recall_at_5
      value: 67.0
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 31.514999999999997
    - type: f1
      value: 26.58222460337632
  - task:
      type: Classification
    dataset:
      type: C-MTEB/IFlyTek-classification
      name: MTEB IFlyTek
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 47.00269334359369
    - type: f1
      value: 35.35096851514498
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 65.1704
    - type: ap
      value: 59.97217670850408
    - type: f1
      value: 64.92509757731281
  - task:
      type: Classification
    dataset:
      type: C-MTEB/JDReview-classification
      name: MTEB JDReview
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 77.33583489681051
    - type: ap
      value: 39.86267586660359
    - type: f1
      value: 71.07975139386433
  - task:
      type: STS
    dataset:
      type: C-MTEB/LCQMC
      name: MTEB LCQMC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 68.22943962011342
    - type: cos_sim_spearman
      value: 74.09285052519111
    - type: euclidean_pearson
      value: 72.99465307442854
    - type: euclidean_spearman
      value: 74.09285052519111
    - type: manhattan_pearson
      value: 73.00139084439715
    - type: manhattan_spearman
      value: 74.07472412844967
  - task:
      type: Classification
    dataset:
      type: DDSC/lcc
      name: MTEB LccSentimentClassification
      config: default
      split: test
      revision: de7ba3406ee55ea2cc52a0a41408fa6aede6d3c6
    metrics:
    - type: accuracy
      value: 42.266666666666666
    - type: f1
      value: 40.963628523464294
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/Mmarco-reranking
      name: MTEB MMarcoReranking
      config: default
      split: dev
      revision: None
    metrics:
    - type: map
      value: 24.311577701296468
    - type: mrr
      value: 23.545238095238094
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MMarcoRetrieval
      name: MTEB MMarcoRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 55.757
    - type: map_at_10
      value: 64.866
    - type: map_at_100
      value: 65.398
    - type: map_at_1000
      value: 65.41900000000001
    - type: map_at_3
      value: 62.634
    - type: map_at_5
      value: 63.993
    - type: mrr_at_1
      value: 57.794000000000004
    - type: mrr_at_10
      value: 65.661
    - type: mrr_at_100
      value: 66.137
    - type: mrr_at_1000
      value: 66.156
    - type: mrr_at_3
      value: 63.625
    - type: mrr_at_5
      value: 64.863
    - type: ndcg_at_1
      value: 57.794000000000004
    - type: ndcg_at_10
      value: 69.107
    - type: ndcg_at_100
      value: 71.56700000000001
    - type: ndcg_at_1000
      value: 72.146
    - type: ndcg_at_3
      value: 64.756
    - type: ndcg_at_5
      value: 67.094
    - type: precision_at_1
      value: 57.794000000000004
    - type: precision_at_10
      value: 8.656
    - type: precision_at_100
      value: 0.989
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 24.623
    - type: precision_at_5
      value: 15.991
    - type: recall_at_1
      value: 55.757
    - type: recall_at_10
      value: 81.55799999999999
    - type: recall_at_100
      value: 92.826
    - type: recall_at_1000
      value: 97.38900000000001
    - type: recall_at_3
      value: 69.903
    - type: recall_at_5
      value: 75.497
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 81.20611035111718
    - type: f1
      value: 80.7763576575655
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (de)
      config: de
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 57.22175260636799
    - type: f1
      value: 53.81709852420842
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (es)
      config: es
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 58.40226817878585
    - type: f1
      value: 57.10362737664957
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (fr)
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 54.97337926714688
    - type: f1
      value: 54.14308620410437
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (hi)
      config: hi
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 64.16636787378988
    - type: f1
      value: 61.67057141912039
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (th)
      config: th
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 70.47377938517178
    - type: f1
      value: 70.31854571152071
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 51.56406748746011
    - type: f1
      value: 35.39870036930897
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (de)
      config: de
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 32.17807833192449
    - type: f1
      value: 19.018762850873046
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (es)
      config: es
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 33.89593062041361
    - type: f1
      value: 20.385240649662023
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (fr)
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 26.689633573441906
    - type: f1
      value: 19.339198990825825
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (hi)
      config: hi
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 38.2717820007171
    - type: f1
      value: 20.92023255890095
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (th)
      config: th
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 42.72694394213382
    - type: f1
      value: 30.207341681902918
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (af)
      config: af
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 33.496973772696705
    - type: f1
      value: 30.700367642324967
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (am)
      config: am
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 19.559515803631474
    - type: f1
      value: 16.655700010020094
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ar)
      config: ar
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 26.46267652992602
    - type: f1
      value: 23.470618969045958
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (az)
      config: az
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 31.577000672494947
    - type: f1
      value: 29.663054588730454
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (bn)
      config: bn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 27.985877605917953
    - type: f1
      value: 25.140738617026408
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (cy)
      config: cy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 28.261600537995967
    - type: f1
      value: 25.406976600356344
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (da)
      config: da
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 40.373234700739744
    - type: f1
      value: 36.84775969220266
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (de)
      config: de
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 34.20309347679893
    - type: f1
      value: 29.937516367091355
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (el)
      config: el
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 26.01546738399462
    - type: f1
      value: 23.974936009024375
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.48419636852724
    - type: f1
      value: 57.07615823930852
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (es)
      config: es
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 36.368527236045736
    - type: f1
      value: 35.28610128351216
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (fa)
      config: fa
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 48.913920645595155
    - type: f1
      value: 45.10811063972933
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (fi)
      config: fi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 30.114324142568925
    - type: f1
      value: 27.789916812631493
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (fr)
      config: fr
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 37.53194351042367
    - type: f1
      value: 35.77870968876826
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (he)
      config: he
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 24.858776059179558
    - type: f1
      value: 24.016121696621195
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (hi)
      config: hi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 39.14256893073302
    - type: f1
      value: 35.82510556127162
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (hu)
      config: hu
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 31.97041022192334
    - type: f1
      value: 29.964722488737355
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (hy)
      config: hy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 31.355077336919972
    - type: f1
      value: 27.175518791441
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (id)
      config: id
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 37.03765971755212
    - type: f1
      value: 35.94269966729341
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (is)
      config: is
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 28.6079354404842
    - type: f1
      value: 25.780613738124625
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (it)
      config: it
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 37.85810356422326
    - type: f1
      value: 35.910057289042975
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ja)
      config: ja
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 47.901815736381984
    - type: f1
      value: 44.49582926460981
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (jv)
      config: jv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 29.078681909885677
    - type: f1
      value: 27.191374864489585
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ka)
      config: ka
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 25.770006724949564
    - type: f1
      value: 23.628483056948564
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (km)
      config: km
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 23.661735036987224
    - type: f1
      value: 20.66379761523298
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (kn)
      config: kn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 21.267652992602553
    - type: f1
      value: 18.69704378377225
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ko)
      config: ko
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 40.42367182246133
    - type: f1
      value: 37.08072704015134
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (lv)
      config: lv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 30.12777404169469
    - type: f1
      value: 28.12098399487521
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ml)
      config: ml
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 25.89105581708137
    - type: f1
      value: 23.62828321219826
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (mn)
      config: mn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 27.713517148621385
    - type: f1
      value: 26.39822334010705
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ms)
      config: ms
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 33.03631472763954
    - type: f1
      value: 32.08618313202589
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (my)
      config: my
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 24.193006052454603
    - type: f1
      value: 20.242784930454743
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (nb)
      config: nb
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
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      type: Classification
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  - task:
      type: Classification
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      type: Classification
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      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
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  - task:
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  - task:
      type: Classification
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  - task:
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  - task:
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  - task:
      type: Classification
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  - task:
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  - task:
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  - task:
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  - task:
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  - task:
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  - task:
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  - task:
      type: Classification
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  - task:
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  - task:
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  - task:
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  - task:
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  - task:
      type: Classification
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  - task:
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  - task:
      type: Classification
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  - task:
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  - task:
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  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (sw)
      config: sw
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 36.0221923335575
    - type: f1
      value: 31.880593511438942
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ta)
      config: ta
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 37.80766644250168
    - type: f1
      value: 35.80909783577956
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (te)
      config: te
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 34.5965030262273
    - type: f1
      value: 33.552796756090274
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (th)
      config: th
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 57.38399462004035
    - type: f1
      value: 53.92067950173084
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (tl)
      config: tl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 39.36112979152656
    - type: f1
      value: 35.73348460761388
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (tr)
      config: tr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 36.163416274377944
    - type: f1
      value: 35.36946437302125
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ur)
      config: ur
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 36.425689307330195
    - type: f1
      value: 35.72323238273122
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (vi)
      config: vi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 47.04438466711499
    - type: f1
      value: 46.775815838841666
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (zh-CN)
      config: zh-CN
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 75.69266980497646
    - type: f1
      value: 75.03810873420112
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (zh-TW)
      config: zh-TW
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.96032279757902
    - type: f1
      value: 71.05327209484685
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MedicalRetrieval
      name: MTEB MedicalRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 41.3
    - type: map_at_10
      value: 46.753
    - type: map_at_100
      value: 47.344
    - type: map_at_1000
      value: 47.410000000000004
    - type: map_at_3
      value: 45.533
    - type: map_at_5
      value: 46.248
    - type: mrr_at_1
      value: 41.5
    - type: mrr_at_10
      value: 46.853
    - type: mrr_at_100
      value: 47.443999999999996
    - type: mrr_at_1000
      value: 47.510000000000005
    - type: mrr_at_3
      value: 45.633
    - type: mrr_at_5
      value: 46.348
    - type: ndcg_at_1
      value: 41.3
    - type: ndcg_at_10
      value: 49.283
    - type: ndcg_at_100
      value: 52.602000000000004
    - type: ndcg_at_1000
      value: 54.556000000000004
    - type: ndcg_at_3
      value: 46.793
    - type: ndcg_at_5
      value: 48.075
    - type: precision_at_1
      value: 41.3
    - type: precision_at_10
      value: 5.72
    - type: precision_at_100
      value: 0.738
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 16.8
    - type: precision_at_5
      value: 10.7
    - type: recall_at_1
      value: 41.3
    - type: recall_at_10
      value: 57.199999999999996
    - type: recall_at_100
      value: 73.8
    - type: recall_at_1000
      value: 89.60000000000001
    - type: recall_at_3
      value: 50.4
    - type: recall_at_5
      value: 53.5
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.936450521634473
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 28.047583673034808
  - task:
      type: Classification
    dataset:
      type: C-MTEB/MultilingualSentiment-classification
      name: MTEB MultilingualSentiment
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 69.17
    - type: f1
      value: 68.72937085716812
  - task:
      type: Classification
    dataset:
      type: ScandEval/norec-mini
      name: MTEB NoRecClassification
      config: default
      split: test
      revision: 07b99ab3363c2e7f8f87015b01c21f4d9b917ce3
    metrics:
    - type: accuracy
      value: 43.5302734375
    - type: f1
      value: 40.85343331953274
  - task:
      type: Classification
    dataset:
      type: NbAiLab/norwegian_parliament
      name: MTEB NorwegianParliament
      config: default
      split: test
      revision: f7393532774c66312378d30b197610b43d751972
    metrics:
    - type: accuracy
      value: 54.900000000000006
    - type: ap
      value: 52.72583551130585
    - type: f1
      value: 54.72449827992906
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/OCNLI
      name: MTEB Ocnli
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 70.27612344342177
    - type: cos_sim_ap
      value: 73.44116481862304
    - type: cos_sim_f1
      value: 72.28607918263091
    - type: cos_sim_precision
      value: 60.556348074179745
    - type: cos_sim_recall
      value: 89.65153115100317
    - type: dot_accuracy
      value: 70.27612344342177
    - type: dot_ap
      value: 73.44116481862304
    - type: dot_f1
      value: 72.28607918263091
    - type: dot_precision
      value: 60.556348074179745
    - type: dot_recall
      value: 89.65153115100317
    - type: euclidean_accuracy
      value: 70.27612344342177
    - type: euclidean_ap
      value: 73.44116481862304
    - type: euclidean_f1
      value: 72.28607918263091
    - type: euclidean_precision
      value: 60.556348074179745
    - type: euclidean_recall
      value: 89.65153115100317
    - type: manhattan_accuracy
      value: 70.38440714672441
    - type: manhattan_ap
      value: 73.46922542436253
    - type: manhattan_f1
      value: 72.38838318162117
    - type: manhattan_precision
      value: 61.39705882352941
    - type: manhattan_recall
      value: 88.17317845828934
    - type: max_accuracy
      value: 70.38440714672441
    - type: max_ap
      value: 73.46922542436253
    - type: max_f1
      value: 72.38838318162117
  - task:
      type: Classification
    dataset:
      type: C-MTEB/OnlineShopping-classification
      name: MTEB OnlineShopping
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 89.79000000000002
    - type: ap
      value: 87.04275277120101
    - type: f1
      value: 89.77446550482388
  - task:
      type: Classification
    dataset:
      type: laugustyniak/abusive-clauses-pl
      name: MTEB PAC
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 57.138719953663475
    - type: ap
      value: 72.7490265036156
    - type: f1
      value: 55.67596841902006
  - task:
      type: STS
    dataset:
      type: C-MTEB/PAWSX
      name: MTEB PAWSX
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 11.928849138540556
    - type: cos_sim_spearman
      value: 12.182908575820269
    - type: euclidean_pearson
      value: 14.455528347393356
    - type: euclidean_spearman
      value: 12.182908575820269
    - type: manhattan_pearson
      value: 14.506141564058982
    - type: manhattan_spearman
      value: 12.25397844569351
  - task:
      type: PairClassification
    dataset:
      type: PL-MTEB/ppc-pairclassification
      name: MTEB PPC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 67.0
    - type: cos_sim_ap
      value: 70.19022218012687
    - type: cos_sim_f1
      value: 75.44529262086515
    - type: cos_sim_precision
      value: 61.2603305785124
    - type: cos_sim_recall
      value: 98.17880794701986
    - type: dot_accuracy
      value: 67.0
    - type: dot_ap
      value: 70.19022218012687
    - type: dot_f1
      value: 75.44529262086515
    - type: dot_precision
      value: 61.2603305785124
    - type: dot_recall
      value: 98.17880794701986
    - type: euclidean_accuracy
      value: 67.0
    - type: euclidean_ap
      value: 70.19022218012687
    - type: euclidean_f1
      value: 75.44529262086515
    - type: euclidean_precision
      value: 61.2603305785124
    - type: euclidean_recall
      value: 98.17880794701986
    - type: manhattan_accuracy
      value: 66.7
    - type: manhattan_ap
      value: 70.20851258919818
    - type: manhattan_f1
      value: 75.40574282147317
    - type: manhattan_precision
      value: 60.52104208416834
    - type: manhattan_recall
      value: 100.0
    - type: max_accuracy
      value: 67.0
    - type: max_ap
      value: 70.20851258919818
    - type: max_f1
      value: 75.44529262086515
  - task:
      type: PairClassification
    dataset:
      type: PL-MTEB/psc-pairclassification
      name: MTEB PSC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 83.20964749536178
    - type: cos_sim_ap
      value: 77.83239751517948
    - type: cos_sim_f1
      value: 70.17045454545455
    - type: cos_sim_precision
      value: 65.69148936170212
    - type: cos_sim_recall
      value: 75.3048780487805
    - type: dot_accuracy
      value: 83.20964749536178
    - type: dot_ap
      value: 77.83239751517948
    - type: dot_f1
      value: 70.17045454545455
    - type: dot_precision
      value: 65.69148936170212
    - type: dot_recall
      value: 75.3048780487805
    - type: euclidean_accuracy
      value: 83.20964749536178
    - type: euclidean_ap
      value: 77.83239751517948
    - type: euclidean_f1
      value: 70.17045454545455
    - type: euclidean_precision
      value: 65.69148936170212
    - type: euclidean_recall
      value: 75.3048780487805
    - type: manhattan_accuracy
      value: 82.74582560296847
    - type: manhattan_ap
      value: 77.71434418573791
    - type: manhattan_f1
      value: 69.89720998531571
    - type: manhattan_precision
      value: 67.42209631728045
    - type: manhattan_recall
      value: 72.5609756097561
    - type: max_accuracy
      value: 83.20964749536178
    - type: max_ap
      value: 77.83239751517948
    - type: max_f1
      value: 70.17045454545455
  - task:
      type: Classification
    dataset:
      type: PL-MTEB/polemo2_in
      name: MTEB PolEmo2.0-IN
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 40.96952908587258
    - type: f1
      value: 40.34996985581621
  - task:
      type: Classification
    dataset:
      type: PL-MTEB/polemo2_out
      name: MTEB PolEmo2.0-OUT
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 17.57085020242915
    - type: f1
      value: 13.699227854176883
  - task:
      type: STS
    dataset:
      type: C-MTEB/QBQTC
      name: MTEB QBQTC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 28.3302552745107
    - type: cos_sim_spearman
      value: 29.935415470590353
    - type: euclidean_pearson
      value: 28.406125326818536
    - type: euclidean_spearman
      value: 29.935394196825893
    - type: manhattan_pearson
      value: 28.535226539445524
    - type: manhattan_spearman
      value: 30.110291572017182
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 30.831283224792134
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 46.29339268141013
  - task:
      type: PairClassification
    dataset:
      type: PL-MTEB/sicke-pl-pairclassification
      name: MTEB SICK-E-PL
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 73.11455360782715
    - type: cos_sim_ap
      value: 46.51191750197438
    - type: cos_sim_f1
      value: 53.48066298342542
    - type: cos_sim_precision
      value: 43.682310469314075
    - type: cos_sim_recall
      value: 68.94586894586895
    - type: dot_accuracy
      value: 73.11455360782715
    - type: dot_ap
      value: 46.511775041787075
    - type: dot_f1
      value: 53.48066298342542
    - type: dot_precision
      value: 43.682310469314075
    - type: dot_recall
      value: 68.94586894586895
    - type: euclidean_accuracy
      value: 73.11455360782715
    - type: euclidean_ap
      value: 46.51191750197438
    - type: euclidean_f1
      value: 53.48066298342542
    - type: euclidean_precision
      value: 43.682310469314075
    - type: euclidean_recall
      value: 68.94586894586895
    - type: manhattan_accuracy
      value: 73.11455360782715
    - type: manhattan_ap
      value: 46.514972647839905
    - type: manhattan_f1
      value: 53.430821147356575
    - type: manhattan_precision
      value: 44.1449814126394
    - type: manhattan_recall
      value: 67.66381766381767
    - type: max_accuracy
      value: 73.11455360782715
    - type: max_ap
      value: 46.514972647839905
    - type: max_f1
      value: 53.48066298342542
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (zh)
      config: zh
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 65.06521909332356
    - type: cos_sim_spearman
      value: 66.05535986394263
    - type: euclidean_pearson
      value: 65.77030042276493
    - type: euclidean_spearman
      value: 66.05535986394263
    - type: manhattan_pearson
      value: 65.91869122430603
    - type: manhattan_spearman
      value: 66.15477943325074
  - task:
      type: STS
    dataset:
      type: C-MTEB/STSB
      name: MTEB STSB
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 79.77776864632986
    - type: cos_sim_spearman
      value: 80.54295891407341
    - type: euclidean_pearson
      value: 80.15310049503712
    - type: euclidean_spearman
      value: 80.54295891407341
    - type: manhattan_pearson
      value: 80.16703044389185
    - type: manhattan_spearman
      value: 80.61034669195091
  - task:
      type: Classification
    dataset:
      type: ScandEval/scala-da
      name: MTEB ScalaDaClassification
      config: default
      split: test
      revision: 1de08520a7b361e92ffa2a2201ebd41942c54675
    metrics:
    - type: accuracy
      value: 50.1123046875
    - type: ap
      value: 50.05839950666221
    - type: f1
      value: 49.75320900875982
  - task:
      type: Classification
    dataset:
      type: ScandEval/scala-sv
      name: MTEB ScalaSvClassification
      config: default
      split: test
      revision: 1b48e3dcb02872335ff985ff938a054a4ed99008
    metrics:
    - type: accuracy
      value: 49.8193359375
    - type: ap
      value: 49.91266630748165
    - type: f1
      value: 49.56571584707715
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.71188118811881
    - type: cos_sim_ap
      value: 90.71339192859018
    - type: cos_sim_f1
      value: 85.26740665993945
    - type: cos_sim_precision
      value: 86.0488798370672
    - type: cos_sim_recall
      value: 84.5
    - type: dot_accuracy
      value: 99.71188118811881
    - type: dot_ap
      value: 90.71339192859018
    - type: dot_f1
      value: 85.26740665993945
    - type: dot_precision
      value: 86.0488798370672
    - type: dot_recall
      value: 84.5
    - type: euclidean_accuracy
      value: 99.71188118811881
    - type: euclidean_ap
      value: 90.71339192859018
    - type: euclidean_f1
      value: 85.26740665993945
    - type: euclidean_precision
      value: 86.0488798370672
    - type: euclidean_recall
      value: 84.5
    - type: manhattan_accuracy
      value: 99.71881188118812
    - type: manhattan_ap
      value: 91.25511397395691
    - type: manhattan_f1
      value: 85.48548548548548
    - type: manhattan_precision
      value: 85.57114228456913
    - type: manhattan_recall
      value: 85.39999999999999
    - type: max_accuracy
      value: 99.71881188118812
    - type: max_ap
      value: 91.25511397395691
    - type: max_f1
      value: 85.48548548548548
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 39.44467533846411
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.60878918655969
  - task:
      type: Classification
    dataset:
      type: ScandEval/swerec-mini
      name: MTEB SweRecClassification
      config: default
      split: test
      revision: 3c62f26bafdc4c4e1c16401ad4b32f0a94b46612
    metrics:
    - type: accuracy
      value: 62.9736328125
    - type: f1
      value: 55.59659753835253
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/T2Reranking
      name: MTEB T2Reranking
      config: default
      split: dev
      revision: None
    metrics:
    - type: map
      value: 67.18460327564007
    - type: mrr
      value: 77.58419442026417
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/T2Retrieval
      name: MTEB T2Retrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 24.196
    - type: map_at_10
      value: 66.633
    - type: map_at_100
      value: 70.417
    - type: map_at_1000
      value: 70.54
    - type: map_at_3
      value: 47.166999999999994
    - type: map_at_5
      value: 57.711
    - type: mrr_at_1
      value: 83.947
    - type: mrr_at_10
      value: 87.47500000000001
    - type: mrr_at_100
      value: 87.62100000000001
    - type: mrr_at_1000
      value: 87.628
    - type: mrr_at_3
      value: 86.813
    - type: mrr_at_5
      value: 87.202
    - type: ndcg_at_1
      value: 83.943
    - type: ndcg_at_10
      value: 75.936
    - type: ndcg_at_100
      value: 80.73700000000001
    - type: ndcg_at_1000
      value: 81.989
    - type: ndcg_at_3
      value: 78.417
    - type: ndcg_at_5
      value: 76.301
    - type: precision_at_1
      value: 83.943
    - type: precision_at_10
      value: 37.984
    - type: precision_at_100
      value: 4.772
    - type: precision_at_1000
      value: 0.507
    - type: precision_at_3
      value: 68.911
    - type: precision_at_5
      value: 57.267
    - type: recall_at_1
      value: 24.196
    - type: recall_at_10
      value: 74.67099999999999
    - type: recall_at_100
      value: 90.18599999999999
    - type: recall_at_1000
      value: 96.54700000000001
    - type: recall_at_3
      value: 49.217
    - type: recall_at_5
      value: 61.765
  - task:
      type: Classification
    dataset:
      type: C-MTEB/TNews-classification
      name: MTEB TNews
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 49.769
    - type: f1
      value: 48.06519294990893
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (sqi-eng)
      config: sqi-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 20.4
    - type: f1
      value: 15.828455908556528
    - type: precision
      value: 14.818339585714199
    - type: recall
      value: 20.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (fry-eng)
      config: fry-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 26.589595375722542
    - type: f1
      value: 19.027433709514636
    - type: precision
      value: 17.053635189473336
    - type: recall
      value: 26.589595375722542
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kur-eng)
      config: kur-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.780487804878048
    - type: f1
      value: 6.111094140071713
    - type: precision
      value: 5.623318968152088
    - type: recall
      value: 8.780487804878048
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tur-eng)
      config: tur-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 12.4
    - type: f1
      value: 9.377654588051435
    - type: precision
      value: 8.787308104062777
    - type: recall
      value: 12.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (deu-eng)
      config: deu-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 23.0
    - type: f1
      value: 20.202147869674185
    - type: precision
      value: 19.391492475731603
    - type: recall
      value: 23.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (nld-eng)
      config: nld-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 34.1
    - type: f1
      value: 29.410775916893563
    - type: precision
      value: 28.070429087454624
    - type: recall
      value: 34.1
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ron-eng)
      config: ron-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 20.599999999999998
    - type: f1
      value: 17.35632359863931
    - type: precision
      value: 16.518293570846236
    - type: recall
      value: 20.599999999999998
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ang-eng)
      config: ang-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 20.8955223880597
    - type: f1
      value: 13.264176317293085
    - type: precision
      value: 11.76782203505206
    - type: recall
      value: 20.8955223880597
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ido-eng)
      config: ido-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 15.6
    - type: f1
      value: 11.7763376390295
    - type: precision
      value: 10.914347870755636
    - type: recall
      value: 15.6
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (jav-eng)
      config: jav-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 10.24390243902439
    - type: f1
      value: 6.743976890318354
    - type: precision
      value: 6.10895202358617
    - type: recall
      value: 10.24390243902439
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (isl-eng)
      config: isl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 9.700000000000001
    - type: f1
      value: 7.491822942738051
    - type: precision
      value: 7.074516864427855
    - type: recall
      value: 9.700000000000001
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (slv-eng)
      config: slv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 14.094775212636696
    - type: f1
      value: 10.166440808088712
    - type: precision
      value: 9.417657228214015
    - type: recall
      value: 14.094775212636696
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cym-eng)
      config: cym-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.521739130434783
    - type: f1
      value: 5.637620426566197
    - type: precision
      value: 5.181579047619263
    - type: recall
      value: 8.521739130434783
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kaz-eng)
      config: kaz-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 21.913043478260867
    - type: f1
      value: 16.97458403110577
    - type: precision
      value: 15.775659428291005
    - type: recall
      value: 21.913043478260867
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (est-eng)
      config: est-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 7.8
    - type: f1
      value: 5.450419697471649
    - type: precision
      value: 5.062362215300643
    - type: recall
      value: 7.8
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (heb-eng)
      config: heb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 34.4
    - type: f1
      value: 30.260987068487072
    - type: precision
      value: 28.893481007908996
    - type: recall
      value: 34.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (gla-eng)
      config: gla-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 4.2219541616405305
    - type: f1
      value: 2.684516189451713
    - type: precision
      value: 2.463954323534627
    - type: recall
      value: 4.2219541616405305
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (mar-eng)
      config: mar-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 33.300000000000004
    - type: f1
      value: 28.55938229523907
    - type: precision
      value: 27.10483987488783
    - type: recall
      value: 33.300000000000004
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (lat-eng)
      config: lat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.200000000000001
    - type: f1
      value: 7.868244347487681
    - type: precision
      value: 7.121914265161029
    - type: recall
      value: 11.200000000000001
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (bel-eng)
      config: bel-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 29.799999999999997
    - type: f1
      value: 24.34143569640063
    - type: precision
      value: 22.947270794132873
    - type: recall
      value: 29.799999999999997
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (pms-eng)
      config: pms-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 12.95238095238095
    - type: f1
      value: 9.269868736708247
    - type: precision
      value: 8.408018250035058
    - type: recall
      value: 12.95238095238095
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (gle-eng)
      config: gle-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 6.0
    - type: f1
      value: 3.647551182853867
    - type: precision
      value: 3.2680275654986537
    - type: recall
      value: 6.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (pes-eng)
      config: pes-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 57.099999999999994
    - type: f1
      value: 51.06459207459208
    - type: precision
      value: 48.901510822510815
    - type: recall
      value: 57.099999999999994
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (nob-eng)
      config: nob-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 32.4
    - type: f1
      value: 27.89405452374492
    - type: precision
      value: 26.51932166043579
    - type: recall
      value: 32.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (bul-eng)
      config: bul-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 47.4
    - type: f1
      value: 42.17928673178673
    - type: precision
      value: 40.436673759871375
    - type: recall
      value: 47.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cbk-eng)
      config: cbk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 14.000000000000002
    - type: f1
      value: 10.949295388694702
    - type: precision
      value: 10.259331172194964
    - type: recall
      value: 14.000000000000002
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (hun-eng)
      config: hun-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 18.2
    - type: f1
      value: 14.773692094643707
    - type: precision
      value: 13.903416806571641
    - type: recall
      value: 18.2
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (uig-eng)
      config: uig-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 4.5
    - type: f1
      value: 2.64568935010746
    - type: precision
      value: 2.4019067331153896
    - type: recall
      value: 4.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (rus-eng)
      config: rus-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 65.8
    - type: f1
      value: 60.679131295533736
    - type: precision
      value: 58.812619047619044
    - type: recall
      value: 65.8
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (spa-eng)
      config: spa-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 32.9
    - type: f1
      value: 28.186653736628603
    - type: precision
      value: 26.8010262685625
    - type: recall
      value: 32.9
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (hye-eng)
      config: hye-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 25.60646900269542
    - type: f1
      value: 23.12611992122878
    - type: precision
      value: 22.426345061728544
    - type: recall
      value: 25.60646900269542
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tel-eng)
      config: tel-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 29.48717948717949
    - type: f1
      value: 23.68695247318436
    - type: precision
      value: 22.09868834868835
    - type: recall
      value: 29.48717948717949
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (afr-eng)
      config: afr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 16.400000000000002
    - type: f1
      value: 13.221122174926522
    - type: precision
      value: 12.33469931277381
    - type: recall
      value: 16.400000000000002
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (mon-eng)
      config: mon-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 29.772727272727273
    - type: f1
      value: 24.851015943121205
    - type: precision
      value: 23.526050931889745
    - type: recall
      value: 29.772727272727273
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (arz-eng)
      config: arz-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 13.626834381551362
    - type: f1
      value: 11.419087551163022
    - type: precision
      value: 10.700808625336927
    - type: recall
      value: 13.626834381551362
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (hrv-eng)
      config: hrv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 13.4
    - type: f1
      value: 10.050831111434281
    - type: precision
      value: 9.371874912594967
    - type: recall
      value: 13.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (nov-eng)
      config: nov-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 31.1284046692607
    - type: f1
      value: 25.220003329410517
    - type: precision
      value: 23.700114736106954
    - type: recall
      value: 31.1284046692607
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (gsw-eng)
      config: gsw-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 17.94871794871795
    - type: f1
      value: 11.687818354485021
    - type: precision
      value: 10.603332951114169
    - type: recall
      value: 17.94871794871795
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (nds-eng)
      config: nds-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 18.9
    - type: f1
      value: 14.988123337504142
    - type: precision
      value: 14.116226418627315
    - type: recall
      value: 18.9
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ukr-eng)
      config: ukr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 44.800000000000004
    - type: f1
      value: 39.7999924337166
    - type: precision
      value: 38.31692251705409
    - type: recall
      value: 44.800000000000004
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (uzb-eng)
      config: uzb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 5.607476635514018
    - type: f1
      value: 3.5310597299663247
    - type: precision
      value: 3.2762993077737717
    - type: recall
      value: 5.607476635514018
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (lit-eng)
      config: lit-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.0
    - type: f1
      value: 8.130418841674222
    - type: precision
      value: 7.4862958556343395
    - type: recall
      value: 11.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ina-eng)
      config: ina-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 27.700000000000003
    - type: f1
      value: 23.21816159401837
    - type: precision
      value: 22.008571800809705
    - type: recall
      value: 27.700000000000003
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (lfn-eng)
      config: lfn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 12.1
    - type: f1
      value: 8.762797265443172
    - type: precision
      value: 8.08486589350323
    - type: recall
      value: 12.1
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (zsm-eng)
      config: zsm-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 35.099999999999994
    - type: f1
      value: 30.896978216485955
    - type: precision
      value: 29.761690118074224
    - type: recall
      value: 35.099999999999994
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ita-eng)
      config: ita-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 20.5
    - type: f1
      value: 15.977011148466255
    - type: precision
      value: 14.96707597911526
    - type: recall
      value: 20.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cmn-eng)
      config: cmn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 89.3
    - type: f1
      value: 86.26333333333335
    - type: precision
      value: 84.88666666666666
    - type: recall
      value: 89.3
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (lvs-eng)
      config: lvs-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 10.299999999999999
    - type: f1
      value: 7.404212810418141
    - type: precision
      value: 6.846457701679114
    - type: recall
      value: 10.299999999999999
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (glg-eng)
      config: glg-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 23.599999999999998
    - type: f1
      value: 19.32375026259617
    - type: precision
      value: 18.23710400667444
    - type: recall
      value: 23.599999999999998
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ceb-eng)
      config: ceb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 6.5
    - type: f1
      value: 4.796580557105162
    - type: precision
      value: 4.547019472479999
    - type: recall
      value: 6.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (bre-eng)
      config: bre-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 4.5
    - type: f1
      value: 3.2163409836594195
    - type: precision
      value: 2.9845718982896057
    - type: recall
      value: 4.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ben-eng)
      config: ben-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 28.4
    - type: f1
      value: 23.44851541733121
    - type: precision
      value: 22.01784835391281
    - type: recall
      value: 28.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (swg-eng)
      config: swg-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 16.071428571428573
    - type: f1
      value: 10.953798185941043
    - type: precision
      value: 9.992677626606197
    - type: recall
      value: 16.071428571428573
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (arq-eng)
      config: arq-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 5.26893523600439
    - type: f1
      value: 3.9908791491106923
    - type: precision
      value: 3.7779047220052937
    - type: recall
      value: 5.26893523600439
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kab-eng)
      config: kab-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 1.3
    - type: f1
      value: 0.603027485224566
    - type: precision
      value: 0.5195844597160387
    - type: recall
      value: 1.3
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (fra-eng)
      config: fra-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 24.0
    - type: f1
      value: 19.96240217555452
    - type: precision
      value: 18.802741591297085
    - type: recall
      value: 24.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (por-eng)
      config: por-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 33.6
    - type: f1
      value: 28.597393691065413
    - type: precision
      value: 27.188430429408495
    - type: recall
      value: 33.6
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tat-eng)
      config: tat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 4.5
    - type: f1
      value: 2.5102180790224264
    - type: precision
      value: 2.236767959648205
    - type: recall
      value: 4.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (oci-eng)
      config: oci-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.7
    - type: f1
      value: 6.688281884758027
    - type: precision
      value: 6.198557972329553
    - type: recall
      value: 8.7
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (pol-eng)
      config: pol-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 17.4
    - type: f1
      value: 14.513506869901672
    - type: precision
      value: 13.789660772909999
    - type: recall
      value: 17.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (war-eng)
      config: war-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 6.6000000000000005
    - type: f1
      value: 4.842727926144423
    - type: precision
      value: 4.54242126134823
    - type: recall
      value: 6.6000000000000005
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (aze-eng)
      config: aze-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.799999999999999
    - type: f1
      value: 8.548331316616201
    - type: precision
      value: 7.820128737629438
    - type: recall
      value: 11.799999999999999
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (vie-eng)
      config: vie-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 55.50000000000001
    - type: f1
      value: 49.56005716505717
    - type: precision
      value: 47.503501400560225
    - type: recall
      value: 55.50000000000001
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (nno-eng)
      config: nno-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 16.900000000000002
    - type: f1
      value: 13.80254156510093
    - type: precision
      value: 13.026236549222661
    - type: recall
      value: 16.900000000000002
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cha-eng)
      config: cha-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 14.5985401459854
    - type: f1
      value: 9.10786699107867
    - type: precision
      value: 7.985485722712
    - type: recall
      value: 14.5985401459854
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (mhr-eng)
      config: mhr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 5.7
    - type: f1
      value: 3.5188978346475572
    - type: precision
      value: 3.158298308588556
    - type: recall
      value: 5.7
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (dan-eng)
      config: dan-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 30.5
    - type: f1
      value: 25.997416905156033
    - type: precision
      value: 24.596070762988056
    - type: recall
      value: 30.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ell-eng)
      config: ell-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.700000000000001
    - type: f1
      value: 9.498482945625803
    - type: precision
      value: 8.987285930402825
    - type: recall
      value: 11.700000000000001
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (amh-eng)
      config: amh-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.333333333333332
    - type: f1
      value: 5.745982981006023
    - type: precision
      value: 5.401133186459273
    - type: recall
      value: 8.333333333333332
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (pam-eng)
      config: pam-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 5.0
    - type: f1
      value: 3.085855110083055
    - type: precision
      value: 2.816700840061992
    - type: recall
      value: 5.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (hsb-eng)
      config: hsb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.902691511387163
    - type: f1
      value: 6.435632935092832
    - type: precision
      value: 5.983137847614094
    - type: recall
      value: 8.902691511387163
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (srp-eng)
      config: srp-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 15.5
    - type: f1
      value: 12.91642697840956
    - type: precision
      value: 12.27655802325753
    - type: recall
      value: 15.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (epo-eng)
      config: epo-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 10.6
    - type: f1
      value: 8.25444066151791
    - type: precision
      value: 7.838679485283888
    - type: recall
      value: 10.6
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kzj-eng)
      config: kzj-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 3.5000000000000004
    - type: f1
      value: 2.339236097978308
    - type: precision
      value: 2.223062696511718
    - type: recall
      value: 3.5000000000000004
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (awa-eng)
      config: awa-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 22.51082251082251
    - type: f1
      value: 16.74832651150451
    - type: precision
      value: 15.469328651146835
    - type: recall
      value: 22.51082251082251
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (fao-eng)
      config: fao-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 9.16030534351145
    - type: f1
      value: 6.340001193595815
    - type: precision
      value: 5.839561202156622
    - type: recall
      value: 9.16030534351145
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (mal-eng)
      config: mal-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 42.066957787481805
    - type: f1
      value: 36.61324818401623
    - type: precision
      value: 34.71464471808596
    - type: recall
      value: 42.066957787481805
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ile-eng)
      config: ile-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 21.5
    - type: f1
      value: 17.235331398320522
    - type: precision
      value: 16.204611769215212
    - type: recall
      value: 21.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (bos-eng)
      config: bos-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 22.598870056497177
    - type: f1
      value: 15.808069297141552
    - type: precision
      value: 14.216539784336394
    - type: recall
      value: 22.598870056497177
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cor-eng)
      config: cor-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 3.9
    - type: f1
      value: 1.9378227948724842
    - type: precision
      value: 1.7177968874340983
    - type: recall
      value: 3.9
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (cat-eng)
      config: cat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 20.200000000000003
    - type: f1
      value: 15.962850129692935
    - type: precision
      value: 14.831492566514589
    - type: recall
      value: 20.200000000000003
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (eus-eng)
      config: eus-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 9.700000000000001
    - type: f1
      value: 7.3770897326135305
    - type: precision
      value: 6.927006519505818
    - type: recall
      value: 9.700000000000001
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (yue-eng)
      config: yue-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 63.5
    - type: f1
      value: 58.353888888888896
    - type: precision
      value: 56.41114468864469
    - type: recall
      value: 63.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (swe-eng)
      config: swe-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 26.0
    - type: f1
      value: 21.75037437399202
    - type: precision
      value: 20.57120606116242
    - type: recall
      value: 26.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (dtp-eng)
      config: dtp-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 2.4
    - type: f1
      value: 1.7611348003539113
    - type: precision
      value: 1.6490144671379943
    - type: recall
      value: 2.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kat-eng)
      config: kat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 38.605898123324394
    - type: f1
      value: 33.00341324278513
    - type: precision
      value: 31.243423531164034
    - type: recall
      value: 38.605898123324394
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (jpn-eng)
      config: jpn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 57.4
    - type: f1
      value: 52.341290679908326
    - type: precision
      value: 50.74419584500466
    - type: recall
      value: 57.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (csb-eng)
      config: csb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.462450592885375
    - type: f1
      value: 7.1683505686002045
    - type: precision
      value: 6.267734051287927
    - type: recall
      value: 11.462450592885375
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (xho-eng)
      config: xho-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 11.267605633802818
    - type: f1
      value: 8.034434678244908
    - type: precision
      value: 7.4930465143804
    - type: recall
      value: 11.267605633802818
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (orv-eng)
      config: orv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 5.029940119760479
    - type: f1
      value: 3.1094915169923047
    - type: precision
      value: 2.708633372048006
    - type: recall
      value: 5.029940119760479
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ind-eng)
      config: ind-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 36.7
    - type: f1
      value: 32.12717818306083
    - type: precision
      value: 30.816954398121375
    - type: recall
      value: 36.7
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tuk-eng)
      config: tuk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 6.896551724137931
    - type: f1
      value: 4.022988505747127
    - type: precision
      value: 3.3913545619534733
    - type: recall
      value: 6.896551724137931
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (max-eng)
      config: max-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 19.366197183098592
    - type: f1
      value: 13.728751930776578
    - type: precision
      value: 12.40776989741364
    - type: recall
      value: 19.366197183098592
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (swh-eng)
      config: swh-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 9.743589743589745
    - type: f1
      value: 6.368220492881125
    - type: precision
      value: 5.755926465392591
    - type: recall
      value: 9.743589743589745
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (hin-eng)
      config: hin-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 55.2
    - type: f1
      value: 49.45361290600652
    - type: precision
      value: 47.434083591084736
    - type: recall
      value: 55.2
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (dsb-eng)
      config: dsb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 6.6805845511482245
    - type: f1
      value: 4.493424007014965
    - type: precision
      value: 4.131033519879768
    - type: recall
      value: 6.6805845511482245
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ber-eng)
      config: ber-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 4.5
    - type: f1
      value: 2.488223360284137
    - type: precision
      value: 2.1928034718812546
    - type: recall
      value: 4.5
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tam-eng)
      config: tam-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 31.921824104234524
    - type: f1
      value: 26.717853265084536
    - type: precision
      value: 25.08341519742171
    - type: recall
      value: 31.921824104234524
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (slk-eng)
      config: slk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 17.4
    - type: f1
      value: 14.049848881932899
    - type: precision
      value: 13.225483025465493
    - type: recall
      value: 17.4
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tgl-eng)
      config: tgl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 7.9
    - type: f1
      value: 5.764422668778745
    - type: precision
      value: 5.318704596860335
    - type: recall
      value: 7.9
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ast-eng)
      config: ast-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 23.62204724409449
    - type: f1
      value: 17.735908011498562
    - type: precision
      value: 16.31534545023977
    - type: recall
      value: 23.62204724409449
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (mkd-eng)
      config: mkd-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 19.400000000000002
    - type: f1
      value: 16.688139723374675
    - type: precision
      value: 16.0446811984312
    - type: recall
      value: 19.400000000000002
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (khm-eng)
      config: khm-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 19.390581717451525
    - type: f1
      value: 15.330085364864166
    - type: precision
      value: 14.23910323480727
    - type: recall
      value: 19.390581717451525
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ces-eng)
      config: ces-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 14.899999999999999
    - type: f1
      value: 11.89041342121772
    - type: precision
      value: 11.273006536745667
    - type: recall
      value: 14.899999999999999
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tzl-eng)
      config: tzl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 24.03846153846154
    - type: f1
      value: 20.606022267206477
    - type: precision
      value: 19.935897435897438
    - type: recall
      value: 24.03846153846154
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (urd-eng)
      config: urd-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 29.599999999999998
    - type: f1
      value: 24.793469753676277
    - type: precision
      value: 23.43004941257573
    - type: recall
      value: 29.599999999999998
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (ara-eng)
      config: ara-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 24.6
    - type: f1
      value: 19.561599234099237
    - type: precision
      value: 18.231733884473016
    - type: recall
      value: 24.6
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (kor-eng)
      config: kor-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 53.800000000000004
    - type: f1
      value: 48.1892730115302
    - type: precision
      value: 46.16164682539682
    - type: recall
      value: 53.800000000000004
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (yid-eng)
      config: yid-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 3.6556603773584904
    - type: f1
      value: 2.2631181434426764
    - type: precision
      value: 2.082608234687079
    - type: recall
      value: 3.6556603773584904
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (fin-eng)
      config: fin-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 16.0
    - type: f1
      value: 13.533088016975684
    - type: precision
      value: 12.965331925224502
    - type: recall
      value: 16.0
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (tha-eng)
      config: tha-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 65.69343065693431
    - type: f1
      value: 60.208146297669686
    - type: precision
      value: 58.18983631939836
    - type: recall
      value: 65.69343065693431
  - task:
      type: BitextMining
    dataset:
      type: mteb/tatoeba-bitext-mining
      name: MTEB Tatoeba (wuu-eng)
      config: wuu-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 78.2
    - type: f1
      value: 73.25492063492062
    - type: precision
      value: 71.14833333333334
    - type: recall
      value: 78.2
  - task:
      type: Clustering
    dataset:
      type: slvnwhrl/tenkgnad-clustering-p2p
      name: MTEB TenKGnadClusteringP2P
      config: default
      split: test
      revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
    metrics:
    - type: v_measure
      value: 29.791089429037896
  - task:
      type: Clustering
    dataset:
      type: slvnwhrl/tenkgnad-clustering-s2s
      name: MTEB TenKGnadClusteringS2S
      config: default
      split: test
      revision: 6cddbe003f12b9b140aec477b583ac4191f01786
    metrics:
    - type: v_measure
      value: 11.270010272065322
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringP2P
      name: MTEB ThuNewsClusteringP2P
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 55.805739403705914
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringS2S
      name: MTEB ThuNewsClusteringS2S
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 50.50265410416623
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 65.6482
    - type: ap
      value: 11.625197643165249
    - type: f1
      value: 50.23643212069197
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 57.41086587436334
    - type: f1
      value: 57.58586420979367
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 26.543120146469633
  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.49848006198962
    - type: cos_sim_ap
      value: 58.06838035805121
    - type: cos_sim_f1
      value: 55.897019598747534
    - type: cos_sim_precision
      value: 49.86550796606662
    - type: cos_sim_recall
      value: 63.58839050131926
    - type: dot_accuracy
      value: 81.49848006198962
    - type: dot_ap
      value: 58.06837481847699
    - type: dot_f1
      value: 55.897019598747534
    - type: dot_precision
      value: 49.86550796606662
    - type: dot_recall
      value: 63.58839050131926
    - type: euclidean_accuracy
      value: 81.49848006198962
    - type: euclidean_ap
      value: 58.06838167667462
    - type: euclidean_f1
      value: 55.897019598747534
    - type: euclidean_precision
      value: 49.86550796606662
    - type: euclidean_recall
      value: 63.58839050131926
    - type: manhattan_accuracy
      value: 81.43291410860107
    - type: manhattan_ap
      value: 57.83294460595276
    - type: manhattan_f1
      value: 55.628827131417815
    - type: manhattan_precision
      value: 50.233943002977455
    - type: manhattan_recall
      value: 62.321899736147756
    - type: max_accuracy
      value: 81.49848006198962
    - type: max_ap
      value: 58.06838167667462
    - type: max_f1
      value: 55.897019598747534
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.24725423991929
    - type: cos_sim_ap
      value: 82.09462792672173
    - type: cos_sim_f1
      value: 74.30311032863851
    - type: cos_sim_precision
      value: 70.95124684785654
    - type: cos_sim_recall
      value: 77.98737295965506
    - type: dot_accuracy
      value: 87.24725423991929
    - type: dot_ap
      value: 82.0946313711965
    - type: dot_f1
      value: 74.30311032863851
    - type: dot_precision
      value: 70.95124684785654
    - type: dot_recall
      value: 77.98737295965506
    - type: euclidean_accuracy
      value: 87.24725423991929
    - type: euclidean_ap
      value: 82.09462900001712
    - type: euclidean_f1
      value: 74.30311032863851
    - type: euclidean_precision
      value: 70.95124684785654
    - type: euclidean_recall
      value: 77.98737295965506
    - type: manhattan_accuracy
      value: 87.30934916753988
    - type: manhattan_ap
      value: 82.22847590036976
    - type: manhattan_f1
      value: 74.5143604081188
    - type: manhattan_precision
      value: 70.50779907922765
    - type: manhattan_recall
      value: 79.00369571912535
    - type: max_accuracy
      value: 87.30934916753988
    - type: max_ap
      value: 82.22847590036976
    - type: max_f1
      value: 74.5143604081188
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/VideoRetrieval
      name: MTEB VideoRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 44.800000000000004
    - type: map_at_10
      value: 54.806
    - type: map_at_100
      value: 55.477
    - type: map_at_1000
      value: 55.498999999999995
    - type: map_at_3
      value: 52.333
    - type: map_at_5
      value: 53.933
    - type: mrr_at_1
      value: 44.800000000000004
    - type: mrr_at_10
      value: 54.806
    - type: mrr_at_100
      value: 55.477
    - type: mrr_at_1000
      value: 55.498999999999995
    - type: mrr_at_3
      value: 52.333
    - type: mrr_at_5
      value: 53.933
    - type: ndcg_at_1
      value: 44.800000000000004
    - type: ndcg_at_10
      value: 59.75899999999999
    - type: ndcg_at_100
      value: 63.171
    - type: ndcg_at_1000
      value: 63.818
    - type: ndcg_at_3
      value: 54.790000000000006
    - type: ndcg_at_5
      value: 57.652
    - type: precision_at_1
      value: 44.800000000000004
    - type: precision_at_10
      value: 7.53
    - type: precision_at_100
      value: 0.9159999999999999
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 20.633000000000003
    - type: precision_at_5
      value: 13.76
    - type: recall_at_1
      value: 44.800000000000004
    - type: recall_at_10
      value: 75.3
    - type: recall_at_100
      value: 91.60000000000001
    - type: recall_at_1000
      value: 96.8
    - type: recall_at_3
      value: 61.9
    - type: recall_at_5
      value: 68.8
  - task:
      type: Classification
    dataset:
      type: C-MTEB/waimai-classification
      name: MTEB Waimai
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 84.33999999999999
    - type: ap
      value: 65.75892461630445
    - type: f1
      value: 82.55845192469975
---

---
license: apache-2.0
---
